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- c763abe9-bfe0-4d2e-935a-460d060a0ace
- Digit Scroller
- TURN STEP
- false
- 0
- 12
- TURN STEP
- 2
- 0.0003419868
-
7974
28956
250
20
-
7974.39
28956.25
- fb6aba99-fead-4e42-b5d8-c6de5ff90ea6
- DotNET VB Script (LEGACY)
- A VB.NET scriptable component
- true
- a5d5a292-9ba5-4db7-87cc-0bb840e03f34
- DotNET VB Script (LEGACY)
- Turtle
- 0
- Dim i As Integer
Dim dir As New On3dVector(1, 0, 0)
Dim pos As New On3dVector(0, 0, 0)
Dim axis As New On3dVector(0, 0, 1)
Dim pnts As New List(Of On3dVector)
pnts.Add(pos)
Dim P As New On3dVector
For i = 0 To Forward.Count() - 1
dir.Rotate(Left(i), axis)
pnts.Add(dir * Forward(i) + pnts(i))
Next
Points = pnts
-
10116
28789
104
44
-
10171
28811
- 1
- 1
- 2
- Script Variable Forward
- Script Variable Left
- 84fa917c-1ed8-4db3-8be1-7bdc4a6495a2
- 84fa917c-1ed8-4db3-8be1-7bdc4a6495a2
- true
- true
- Forward
- Left
- true
- true
- 2
- Print, Reflect and Error streams
- Output parameter Points
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- true
- true
- Output
- Points
- false
- false
- 1
- false
- Script Variable Forward
- 169a6bf9-7051-47c9-8af9-6d54359501ea
- Forward
- Forward
- true
- 1
- true
- fafed710-e79d-472d-9b45-bedb0b22c125
- 1
- 8e991e99-5fb8-41e1-928d-1bba8fb9f7d7
-
10118
28791
41
20
-
10138.5
28801
- 1
- false
- Script Variable Left
- 2a3330da-d674-4b6a-a421-fc0cd3c74f7b
- Left
- Left
- true
- 1
- true
- fcee0c3b-74ec-4be8-81f5-750eae6bcae3
- 1
- 8e991e99-5fb8-41e1-928d-1bba8fb9f7d7
-
10118
28811
41
20
-
10138.5
28821
- Print, Reflect and Error streams
- b03c6bec-85be-48be-b72b-ca5d2a557279
- Output
- Output
- false
- 0
-
10183
28791
35
20
-
10200.5
28801
- Output parameter Points
- 770e8f58-8dfe-4f6f-905d-3f5cbadbdf1d
- Points
- Points
- false
- 0
-
10183
28811
35
20
-
10200.5
28821
- fbac3e32-f100-4292-8692-77240a42fd1a
- Point
- Contains a collection of three-dimensional points
- true
- 970781a8-0343-4bae-b5a7-02468ff37b8e
- Point
- Point
- false
- 44cddb8b-ba4f-4eab-b3bd-08f5b804d82c
- 1
-
7924
28206
50
24
-
7949.7
28218.66
- dd8134c0-109b-4012-92be-51d843edfff7
- Duplicate Data
- Duplicate data a predefined number of times.
- true
- 3c11906b-2011-4aac-bb44-b0a8260f0bbd
- Duplicate Data
- Duplicate Data
-
8623
28834
102
64
-
8686
28866
- 1
- Data to duplicate
- b9352246-308b-4a41-a51e-8d16471b4ff4
- Data
- Data
- false
- c4650d06-e701-488c-9dbc-a658d92b263e
- 1
-
8625
28836
49
20
-
8649.5
28846
- Number of duplicates
- ba80eda7-39e8-4da0-85be-76dd9f3294e9
- Number
- Number
- false
- 20c0c200-b972-4cd1-beae-aa1e2ba08217
- 1
-
8625
28856
49
20
-
8649.5
28866
- 1
- 1
- {0}
- 2
- Retain list order
- 25332cf5-26a4-42d3-83b4-0b5265331fcd
- Order
- Order
- false
- 0
-
8625
28876
49
20
-
8649.5
28886
- 1
- 1
- {0}
- true
- 1
- Duplicated data
- 8b096aad-41f0-4c90-bdc2-44ece26f1604
- Data
- Data
- false
- 0
-
8698
28836
25
60
-
8710.5
28866
- 797d922f-3a1d-46fe-9155-358b009b5997
- One Over X
- Compute one over x.
- true
- de29117b-9a5e-4a92-97ed-3c2864e3cbe8
- One Over X
- One Over X
-
8392
28922
88
28
-
8435
28936
- Input value
- b7bef66a-1949-4a17-83b4-4eb52de9765c
- Value
- Value
- false
- 20c0c200-b972-4cd1-beae-aa1e2ba08217
- 1
-
8394
28924
29
24
-
8408.5
28936
- Output value
- c4650d06-e701-488c-9dbc-a658d92b263e
- Result
- Result
- false
- 0
-
8447
28924
31
24
-
8462.5
28936
- 4fdfe351-6c07-47ce-9fb9-be027fb62186
- Shift List
- Offset all items in a list.
- true
- 7b5f5b19-5616-42d8-ba58-288544f41550
- Shift List
- Shift List
-
8770
28949
90
64
-
8827
28981
- 1
- List to shift
- aa9b1c36-5754-4429-b60c-d84826926824
- List
- List
- false
- 1d9ca0e8-950e-46ce-8479-db13c1cd3229
- 1
-
8772
28951
43
20
-
8793.5
28961
- Shift offset
- b8123dc8-4417-4532-836d-1b3667eef304
- Shift
- Shift
- false
- 0
-
8772
28971
43
20
-
8793.5
28981
- 1
- 1
- {0}
- 1
- Wrap values
- 712ba1ce-cc2a-4c2e-ab7f-c3dfb1e925db
- Wrap
- Wrap
- false
- 0
-
8772
28991
43
20
-
8793.5
29001
- 1
- 1
- {0}
- false
- 1
- Shifted list
- ed039296-6dd2-44c6-9e1a-c1e8dfc59069
- List
- List
- false
- 0
-
8839
28951
19
60
-
8848.5
28981
- 4fdfe351-6c07-47ce-9fb9-be027fb62186
- Shift List
- Offset all items in a list.
- true
- 7f9d1c96-2fbd-4af5-9e4c-9dd734401acd
- Shift List
- Shift List
-
8745
28843
90
64
-
8802
28875
- 1
- List to shift
- 9df69feb-1432-4fed-b436-f2fdcc9e6f5e
- List
- List
- false
- 8b096aad-41f0-4c90-bdc2-44ece26f1604
- 1
-
8747
28845
43
20
-
8768.5
28855
- Shift offset
- 05577071-06fc-48b9-9ea0-95de0ac6cc56
- Shift
- Shift
- false
- 0
-
8747
28865
43
20
-
8768.5
28875
- 1
- 1
- {0}
- 1
- Wrap values
- 1531b378-33ee-4cfb-96e9-50152c45e68c
- Wrap
- Wrap
- false
- 0
-
8747
28885
43
20
-
8768.5
28895
- 1
- 1
- {0}
- false
- 1
- Shifted list
- ab6779f5-8519-4c74-bf58-f285580cb58b
- List
- List
- false
- 0
-
8814
28845
19
60
-
8823.5
28875
- a0d62394-a118-422d-abb3-6af115c75b25
- Addition
- Mathematical addition
- true
- 6fcdde93-48bd-4eba-aff9-a0246408803c
- Addition
- Addition
-
8658
29090
85
44
-
8698
29112
- 2
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- First item for addition
- 66bca250-846f-4673-a9eb-159a32a2bd80
- A
- A
- true
- 0
-
8660
29092
26
20
-
8673
29102
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_String
- false
- 0
- Second item for addition
- 90e15842-1d83-4cd5-9f4b-9ba16be36eed
- B
- B
- true
- 6a8dea11-5285-47df-9db4-ae7cd329914e
- 1
-
8660
29112
26
20
-
8673
29122
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_Integer
- 1
- Result of addition
- 20c0c200-b972-4cd1-beae-aa1e2ba08217
- Result
- Result
- false
- 0
-
8710
29092
31
40
-
8725.5
29112
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- 6fcdde93-48bd-4eba-aff9-a0246408803c
- 1
- 38226a8a-96d4-43f8-864a-454d3069644d
- Group
- POINT NUMBER
- 4fdfe351-6c07-47ce-9fb9-be027fb62186
- Shift List
- Offset all items in a list.
- true
- 7fac966d-75d3-4d85-b4ea-7a678a11276c
- Shift List
- Shift List
-
10256
28791
90
64
-
10313
28823
- 1
- List to shift
- 53e4a544-1f0d-42c8-8181-edabc62890fb
- List
- List
- false
- 770e8f58-8dfe-4f6f-905d-3f5cbadbdf1d
- 1
-
10258
28793
43
20
-
10279.5
28803
- Shift offset
- 8f9c061e-cd01-4348-99ea-9f0af62458bc
- Shift
- Shift
- false
- 0
-
10258
28813
43
20
-
10279.5
28823
- 1
- 1
- {0}
- -1
- Wrap values
- ad18235a-a4ef-4d70-adcc-486461e889f1
- Wrap
- Wrap
- false
- 0
-
10258
28833
43
20
-
10279.5
28843
- 1
- 1
- {0}
- false
- 1
- Shifted list
- db13a26a-6a2c-48a4-a5e3-a419afc7c1b7
- List
- List
- false
- 0
-
10325
28793
19
60
-
10334.5
28823
- 9c007a04-d0d9-48e4-9da3-9ba142bc4d46
- Subtraction
- Mathematical subtraction
- true
- 8714601c-8d05-4922-a3e8-99ec5bee1bb8
- Subtraction
- Subtraction
-
8243
29234
85
44
-
8283
29256
- 2
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- First operand for subtraction
- 2e5c86e5-e70a-4903-9d2b-95c6bcb6c57a
- A
- A
- true
- c74b06ba-0741-400f-a4c8-676744774743
- 1
-
8245
29236
26
20
-
8258
29246
- Second operand for subtraction
- 6085835a-7965-4b8a-83c4-098ca7abca0e
- B
- B
- true
- 0
-
8245
29256
26
20
-
8258
29266
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_Integer
- 2
- Result of subtraction
- ab54d613-8d13-4335-a8f4-c01221b4b1df
- Result
- Result
- false
- 0
-
8295
29236
31
40
-
8310.5
29256
- ce46b74e-00c9-43c4-805a-193b69ea4a11
- Multiplication
- Mathematical multiplication
- true
- a7f6c94e-b5e4-4c5c-a6fc-1eb1aab9a9c6
- Multiplication
- Multiplication
-
8240
29305
85
44
-
8280
29327
- 2
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- First item for multiplication
- f18d75e7-d9af-44e1-bb5d-d0526569a9b0
- A
- A
- true
- ab54d613-8d13-4335-a8f4-c01221b4b1df
- 1
-
8242
29307
26
20
-
8255
29317
- Second item for multiplication
- 80a36f12-5318-43fe-8a19-c5f8cea93e2a
- B
- B
- true
- 0
-
8242
29327
26
20
-
8255
29337
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_Integer
- 2
- Result of multiplication
- b6aa70cd-ffce-47a3-a260-712054f216e7
- Result
- Result
- false
- 0
-
8292
29307
31
40
-
8307.5
29327
- 9c85271f-89fa-4e9f-9f4a-d75802120ccc
- Division
- Mathematical division
- true
- 5a82e036-1da3-46fc-bdb7-89e70238a8c5
- Division
- Division
-
8649
29222
85
44
-
8689
29244
- Item to divide (dividend)
- 00d9aad6-1954-4e86-909c-12ed594c867c
- A
- A
- false
- c74b06ba-0741-400f-a4c8-676744774743
- 1
-
8651
29224
26
20
-
8664
29234
- Item to divide with (divisor)
- 5971abd0-d534-469b-9280-deb118a30aab
- B
- B
- false
- 0
-
8651
29244
26
20
-
8664
29254
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_Integer
- 2
- The result of the Division
- 26ccf0cc-83e2-418a-8f4c-3a22dcee2db4
- Result
- Result
- false
- 0
-
8701
29224
31
40
-
8716.5
29244
- a0d62394-a118-422d-abb3-6af115c75b25
- Addition
- Mathematical addition
- true
- f3612ad2-8be3-46a2-b3c6-b260c7c8829f
- Addition
- Addition
-
8768
29203
85
44
-
8808
29225
- 2
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- First item for addition
- ae2bce56-0c27-47a9-845e-bcd3a3ec3adf
- A
- A
- true
- 26ccf0cc-83e2-418a-8f4c-3a22dcee2db4
- 1
-
8770
29205
26
20
-
8783
29215
- Second item for addition
- 1f518679-1901-4e25-b47c-95c43779b806
- B
- B
- true
- 0
-
8770
29225
26
20
-
8783
29235
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_Integer
- 2
- Result of addition
- 6ada5024-09f3-4903-bc95-bb9e58bfc140
- Result
- Result
- false
- 0
-
8820
29205
31
40
-
8835.5
29225
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 69a46f6d-5884-4eb5-aed5-3b2d6e594ef6
- Evaluate Length
- Evaluate Length
-
8094
28036
142
64
-
8172
28068
- Curve to evaluate
- ce38b61d-d6bd-4be1-9ba8-66ec9bf55379
- Curve
- Curve
- false
- fbe57887-2062-42c7-8b43-1b8cbf0f868c
- 1
-
8096
28038
64
20
-
8128
28048
- Length factor for curve evaluation
- 039927db-1f2e-44e5-822f-a8fc97e34554
- Length
- Length
- false
- 0
-
8096
28058
64
20
-
8128
28068
- 1
- 2
- {0}
- 0
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 7005dea7-81ff-4270-bacf-d190d0643895
- Normalized
- Normalized
- false
- 0
-
8096
28078
64
20
-
8128
28088
- 1
- 1
- {0}
- true
- Point at the specified length
- 484ba687-c0e4-4304-a4c9-f88e8e6271cc
- Point
- Point
- false
- 0
-
8184
28038
50
20
-
8209
28048
- Tangent vector at the specified length
- 72ce55c1-290d-4329-9208-b5c4d3190bc6
- Tangent
- Tangent
- false
- 0
-
8184
28058
50
20
-
8209
28068
- Curve parameter at the specified length
- 930c51b6-8d37-4be0-9339-ccebaca39c9e
- Parameter
- Parameter
- false
- 0
-
8184
28078
50
20
-
8209
28088
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 6a8dea11-5285-47df-9db4-ae7cd329914e
- Relay
- false
- 6ada5024-09f3-4903-bc95-bb9e58bfc140
- 1
-
8455
29076
40
16
-
8475
29084
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- aaa5a334-801a-4f37-a832-229d9cc793e6
- Relay
- false
- 236190cc-8c61-4e05-ad13-e2c8c13610f9
- 1
-
9169
28793
40
16
-
9189
28801
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 7b1b00c6-bee0-4135-8aef-c6998bb822a1
- Relay
- false
- 1fe668b1-ad7d-42fc-ba89-f43371616761
- 1
-
9144
29114
40
16
-
9164
29122
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- fafed710-e79d-472d-9b45-bedb0b22c125
- Relay
- false
- 08aafdf1-9cde-4d9a-a5c8-2f9081abd6d2
- 1
-
10036
28822
40
16
-
10056
28830
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- fcee0c3b-74ec-4be8-81f5-750eae6bcae3
- Relay
- false
- 58040f5e-60b6-45ff-8eaa-20ac9a1bc558
- 1
-
10076
29102
40
16
-
10096
29110
- 4fdfe351-6c07-47ce-9fb9-be027fb62186
- Shift List
- Offset all items in a list.
- true
- 0675152f-f085-47f2-9154-4be9991ccfd5
- Shift List
- Shift List
-
9327
29258
106
64
-
9384
29290
- 1
- List to shift
- 0a6f1940-14a0-4c11-8624-be6ebfe9a432
- List
- List
- false
- d6e1b8f2-80b4-40ff-a5ba-12ba23a8433f
- 1
-
9329
29260
43
20
-
9350.5
29270
- Shift offset
- ea53497d-2601-4b97-a4f1-ce79888ed6e4
- Shift
- Shift
- false
- 0
-
9329
29280
43
20
-
9350.5
29290
- 1
- 1
- {0}
- -1
- Wrap values
- 1764e100-1227-4791-b676-d899f68c6060
- Wrap
- Wrap
- false
- 0
-
9329
29300
43
20
-
9350.5
29310
- 1
- 1
- {0}
- false
- 1
- Shifted list
- c733a2e2-ed93-4f92-98e7-f6a908d64a92
- List
- List
- false
- true
- 0
-
9396
29260
35
60
-
9405.5
29290
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
- 134af8dc-fd98-4279-ba9a-9b330f78353c
- Merge
- Merge
-
9323
29196
106
64
-
9368
29228
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2
- Data stream 1
- a2d0a6fb-2703-40c6-af92-174831f5ba79
- false
- Data 1
- D1
- true
- d6e1b8f2-80b4-40ff-a5ba-12ba23a8433f
- 1
-
9325
29198
31
20
-
9340.5
29208
- 2
- Data stream 2
- f53a7097-cfde-42ef-b02f-408031044329
- false
- Data 2
- D2
- true
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- 1
-
9325
29218
31
20
-
9340.5
29228
- 2
- Data stream 3
- 5c136c4f-69be-407f-a1b7-5e2fcf65926c
- false
- Data 3
- D3
- true
- 0
-
9325
29238
31
20
-
9340.5
29248
- 2
- Result of merge
- 413ecb15-763e-4e83-90bf-3ffbecc8e2c0
- 1
- Result
- Result
- false
- 0
-
9380
29198
47
60
-
9395.5
29228
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- d6e1b8f2-80b4-40ff-a5ba-12ba23a8433f
- Relay
- false
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- 1
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9362
29347
40
16
-
9382
29355
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- fd8d01b6-550f-461d-bf89-7d885534636d
- Relay
- false
- 413ecb15-763e-4e83-90bf-3ffbecc8e2c0
- 1
-
9358
29177
40
16
-
9378
29185
- 2576f657-2f0d-4e3e-9dfb-c79eb4cd13d7
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- Loop Start
- Start the loop with this one. Double click to rerun.
- true
- ee8829f1-a69a-474f-ac63-380a98834db2
- true
- Loop Start
- Loop Start
-
10124
30372
118
84
-
10189
30414
- 4
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- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- 4
- 6cc73910-22ac-4eb4-882b-eb9d63b8f3c2
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- Number of repeats
- 3ca87afb-e6e9-4109-b4a2-70e62bad5866
- true
- Repeat
- Repeat
- true
- 0
-
10126
30374
51
20
-
10151.5
30384
- 1
- 1
- {0}
- 1
- 2
- If you want trigger loop to restart
- 48ad2736-1528-471c-914c-0958dcd53bf4
- true
- Trigger
- Trigger
- true
- 3dae4219-1a09-4c78-83fe-fafea0163300
- 1
-
10126
30394
51
20
-
10151.5
30404
- 2
- Contains a collection of generic data
- 6322e428-eca4-423b-a4b4-7a28c279addc
- true
- Data
- D0
- true
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- 1
-
10126
30414
51
20
-
10151.5
30424
- 2
- Contains a collection of generic data
- 10678145-91ad-4efa-b802-df158d8d0166
- true
- Data
- D1
- true
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- 1
-
10126
30434
51
20
-
10151.5
30444
- Connect to Loop End
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- true
- >
- >
- false
- 0
-
10201
30374
39
20
-
10220.5
30384
- Counter
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- true
- Counter
- Counter
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- 0
-
10201
30394
39
20
-
10220.5
30404
- 2
- Contains a collection of generic data
- 6e3091e5-a7ac-4ae5-8dd8-482aad3c899f
- true
- Data
- D0
- false
- 0
-
10201
30414
39
20
-
10220.5
30424
- 2
- Contains a collection of generic data
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- true
- Data
- D1
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- 0
-
10201
30434
39
20
-
10220.5
30444
- 15483310-2ce2-48c6-b803-9dee8cb7cc9b
- 4442bb24-c702-460c-a1e4-fcdd321eb886
- Loop End
- End the loop with this one. Double click to pause the loop.
- true
- 8e88c30a-54ad-4e0e-a86c-5a9cda0fd361
- true
- Loop End
- Loop End
- 0
- false
- Constant & Record
-
10327
30372
91
84
-
10372
30414
- 4
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- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- 2
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Connect to Loop Start
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- true
- <
- <
- false
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- 1
-
10329
30374
31
20
-
10344.5
30384
- Set to true to exit the loop
- 1f9ae913-365c-42e3-8e3f-cc69fed7e90b
- true
- Exit
- Exit
- true
- 0
-
10329
30394
31
20
-
10344.5
30404
- 1
- 1
- {0}
- false
- 2
- Contains a collection of generic data
- 3c417e2a-63b3-4784-bdb9-e29866396e66
- true
- Data
- D0
- false
- fa427076-9410-409a-a28f-ff2c773f6a9d
- 1
-
10329
30414
31
20
-
10344.5
30424
- 2
- Contains a collection of generic data
- 77f32577-d9af-4eb1-ada7-e225446be236
- true
- Data
- D1
- false
- fd8d01b6-550f-461d-bf89-7d885534636d
- 1
-
10329
30434
31
20
-
10344.5
30444
- 2
- Contains a collection of generic data
- fab7e2a7-7157-4003-b8e4-b15a9a4260d0
- true
- 1
- Data
- D0
- false
- 0
-
10384
30374
32
40
-
10392
30394
- 2
- Contains a collection of generic data
- 74f7012c-7fbd-4e26-8738-bbfa495bca3f
- true
- 1
- Data
- D1
- false
- 0
-
10384
30414
32
40
-
10392
30434
- 4fdfe351-6c07-47ce-9fb9-be027fb62186
- Shift List
- Offset all items in a list.
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- Shift List
- Shift List
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9283
28663
106
64
-
9340
28695
- 1
- List to shift
- a78d97e7-8217-47e4-aa22-6304b88ce3d9
- List
- List
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- 1
-
9285
28665
43
20
-
9306.5
28675
- Shift offset
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- Shift
- Shift
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- 0
-
9285
28685
43
20
-
9306.5
28695
- 1
- 1
- {0}
- -1
- Wrap values
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- Wrap
- Wrap
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- 0
-
9285
28705
43
20
-
9306.5
28715
- 1
- 1
- {0}
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- 1
- Shifted list
- 1cfa9398-84a0-4469-b446-2fb43cb74a8e
- List
- List
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- 0
-
9352
28665
35
60
-
9361.5
28695
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
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- 305cdec8-fbd3-4861-bdfb-d54cf581c887
- Merge
- Merge
-
9279
28601
106
64
-
9324
28633
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2
- Data stream 1
- 8ab8be51-71e4-41b6-9171-f19d1d81d758
- false
- Data 1
- D1
- true
- 4eba5543-8aae-4c2a-972c-7fc31ea91b76
- 1
-
9281
28603
31
20
-
9296.5
28613
- 2
- Data stream 2
- 03846402-d78d-4528-b02d-7e5dbe3e22be
- false
- Data 2
- D2
- true
- 1cfa9398-84a0-4469-b446-2fb43cb74a8e
- 1
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9281
28623
31
20
-
9296.5
28633
- 2
- Data stream 3
- c3a9f6af-05a9-4180-b959-03b902ced0ad
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- Data 3
- D3
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- 0
-
9281
28643
31
20
-
9296.5
28653
- 2
- Result of merge
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- 1
- Result
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- 0
-
9336
28603
47
60
-
9351.5
28633
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
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- Relay
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- aaa5a334-801a-4f37-a832-229d9cc793e6
- 1
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9312
28735
40
16
-
9332
28743
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
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- Relay
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- 03d583ba-67b6-4697-afd1-3a5f24c931cf
- 1
-
9314
28582
40
16
-
9334
28590
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- Number
- Contains a collection of floating point numbers
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- X/4
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- Number
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- 1
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12656
28599
50
24
-
12689.63
28611.84
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- Group
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-
255;255;255;255
- A group of Grasshopper objects
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- Group
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- Panel
- A panel for custom notes and text values
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- Panel
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- GraphMapper+
- External Graph mapper
You can Right click on the Heteromapper's icon and choose "AutoDomain" mode to define Output domain based on input domain interval; otherwise it'll be set to 0-1 in "Normalized" mode.
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- GraphMapper+
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- Curve
- false
- 9da3814a-8dc9-4bab-b390-b390edc62a2b
- 1
-
9226
29844
47
20
-
9249.5
29854
- Optional Rectangle boundary. If omitted the curve's would be landed
- b0339b52-7de2-4662-a003-50ccabe57648
- Boundary
- Boundary
- true
- 915ca187-0684-4984-90e1-1f06c10f7133
- 1
-
9226
29864
47
20
-
9249.5
29874
- 1
- List of input numbers
- ce0ef573-9001-4e88-a7d9-d6c99e0ca0c1
- Numbers
- Numbers
- false
- f8cfb071-35b2-4c7d-b14f-b623eac5d707
- 1
-
9226
29884
47
20
-
9249.5
29894
- 1
- 9
- {0}
- 0.1
- 0.2
- 0.3
- 0.4
- 0.5
- 0.6
- 0.7
- 0.8
- 0.9
- (Optional) Input Domain
if omitted, it would be 0-1 in "Normalize" mode by default
or be the interval of the input list in case of selecting "AutoDomain" mode
- 144027f2-4301-44ac-8786-7ab7b995b198
- Input
- Input
- true
- f570df43-5009-430d-bfd1-27f65f985d30
- 1
-
9226
29904
47
20
-
9249.5
29914
- (Optional) Output Domain
if omitted, it would be 0-1 in "Normalize" mode by default
or be the interval of the input list in case of selecting "AutoDomain" mode
- 0fb785c6-a8d7-4fe8-b1c6-d98c6ff80bec
- Output
- Output
- true
- f570df43-5009-430d-bfd1-27f65f985d30
- 1
-
9226
29924
47
20
-
9249.5
29934
- 1
- Output Numbers
- d49245f3-5bf7-4e07-a2dc-594dca29df34
- Number
- Number
- false
- 0
-
9297
29844
39
100
-
9316.5
29894
- 11bbd48b-bb0a-4f1b-8167-fa297590390d
- End Points
- Extract the end points of a curve.
- true
- b129a78c-ce0b-4659-9392-e69777ed9c5c
- End Points
- End Points
-
9180
30117
84
44
-
9224
30139
- Curve to evaluate
- 94a33f0c-dcb3-4361-ada3-e12df7594083
- Curve
- Curve
- false
- 9da3814a-8dc9-4bab-b390-b390edc62a2b
- 1
-
9182
30119
30
40
-
9197
30139
- Curve start point
- 05980ff6-43ba-4938-bab8-2f2daec47ffe
- Start
- Start
- false
- 0
-
9236
30119
26
20
-
9249
30129
- Curve end point
- 602db9d8-1f27-4fad-bab2-0fe9c4848923
- End
- End
- false
- 0
-
9236
30139
26
20
-
9249
30149
- 575660b1-8c79-4b8d-9222-7ab4a6ddb359
- Rectangle 2Pt
- Create a rectangle from a base plane and two points
- true
- 31e437e2-63c4-4b78-aac5-4914c287fe8c
- Rectangle 2Pt
- Rectangle 2Pt
-
9169
29986
198
101
-
9305
30037
- Rectangle base plane
- d5bfa5f9-7c76-478e-bc7a-ddb84429c3bf
- Plane
- Plane
- false
- 0
-
9171
29988
122
37
-
9232
30006.5
- 1
- 1
- {0}
-
0
0
0
1
0
0
0
1
0
- First corner point.
- b818243e-e2de-44d0-af69-d029b2edee73
- Point A
- Point A
- false
- 05980ff6-43ba-4938-bab8-2f2daec47ffe
- 1
-
9171
30025
122
20
-
9232
30035
- 1
- 1
- {0}
-
0
0
0
- Second corner point.
- 3f714117-1112-45d4-8770-7f2fa53939f9
- Point B
- Point B
- false
- 602db9d8-1f27-4fad-bab2-0fe9c4848923
- 1
-
9171
30045
122
20
-
9232
30055
- 1
- 1
- {0}
-
10
5
0
- Rectangle corner fillet radius
- b4a33b7f-64f6-466a-acf2-773dc5713387
- Radius
- Radius
- false
- 0
-
9171
30065
122
20
-
9232
30075
- 1
- 1
- {0}
- 0
- Rectangle defined by P, A and B
- 915ca187-0684-4984-90e1-1f06c10f7133
- Rectangle
- Rectangle
- false
- 0
-
9317
29988
48
48
-
9341
30012.25
- Length of rectangle curve
- 1a0fa2db-8b1e-4c0c-a25e-46189cdeb411
- Length
- Length
- false
- 0
-
9317
30036
48
49
-
9341
30060.75
- f44b92b0-3b5b-493a-86f4-fd7408c3daf3
- Bounds
- Create a numeric domain which encompasses a list of numbers.
- true
- 54581da1-580d-4778-93ab-674f6e734ffb
- Bounds
- Bounds
-
9069
29751
110
28
-
9127
29765
- 1
- Numbers to include in Bounds
- 61e1cd32-b63d-4ebe-90d8-1f22e5dfdbcf
- Numbers
- Numbers
- false
- f8cfb071-35b2-4c7d-b14f-b623eac5d707
- 1
-
9071
29753
44
24
-
9093
29765
- Numeric Domain between the lowest and highest numbers in {N}
- f570df43-5009-430d-bfd1-27f65f985d30
- Domain
- Domain
- false
- 0
-
9139
29753
38
24
-
9158
29765
- 3e8ca6be-fda8-4aaf-b5c0-3c54c8bb7312
- Number
- Contains a collection of floating point numbers
- f8cfb071-35b2-4c7d-b14f-b623eac5d707
- Number
- Number
- false
- 6db9b9da-e194-40ca-9875-d0c2d9271a4c
- 1
-
9060
29947
50
24
-
9085.572
29959.07
- d5967b9f-e8ee-436b-a8ad-29fdcecf32d5
- Curve
- Contains a collection of generic curves
- true
- 9da3814a-8dc9-4bab-b390-b390edc62a2b
- Curve
- Curve
- false
- 082832c7-f80b-4ab0-8cec-39daa2c6ee5b
- 1
-
9111
30198
50
24
-
9136.482
30210.44
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- db0c3f90-16aa-4bcb-ae4f-fc0bbeaa378f
- Relay
- false
- ed039296-6dd2-44c6-9e1a-c1e8dfc59069
- 1
-
8900
29011
40
16
-
8920
29019
- dc6f76a5-ffd3-4a50-b42b-fcb46a544902
- c6c19589-ab63-4b60-8d7c-2c1b6d60fac7
- True Only Button
- When clicked, the button object only raises recomputation one time.
- False
- True
- 3dae4219-1a09-4c78-83fe-fafea0163300
- true
- True Only Button
- false
- 0
- neutral,N
-
9789
30399
66
22
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 236190cc-8c61-4e05-ad13-e2c8c13610f9
- Relay
- false
- ab6779f5-8519-4c74-bf58-f285580cb58b
- 1
-
8834
28804
40
16
-
8854
28812
- 7cd2f235-466e-4d30-bd3c-3b9573ac7dda
- 4442bb24-c702-460c-a1e4-fcdd321eb886
- Fast Loop Start
- Loop Start
- true
- 6a0427dd-97fd-412a-be12-fe9558ccba8b
- true
- Fast Loop Start
- Fast Loop Start
-
9099
28919
127
84
-
9173
28961
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 4
- 6cc73910-22ac-4eb4-882b-eb9d63b8f3c2
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Loop iterations
- 62d27cfd-3b3f-45e5-aa28-62ccbed2e6b1
- true
- Iterations
- Iterations
- false
- 0
-
9101
28921
60
26
-
9131
28934.33
- 1
- 1
- {0}
- 1
- 2
- Contains a collection of generic data
- ed77f663-0b90-457c-afea-47cc55fafb50
- true
- Data
- D0
- true
- aaa5a334-801a-4f37-a832-229d9cc793e6
- 1
-
9101
28947
60
27
-
9131
28961
- 2
- Contains a collection of generic data
- 6157358f-b6ed-4b5e-b7de-1f696efcd3a7
- true
- Data
- D1
- true
- 7b1b00c6-bee0-4135-8aef-c6998bb822a1
- 1
-
9101
28974
60
27
-
9131
28987.67
- Connect to Loop End
- 6dea6cc4-dc4e-4113-9e42-6c3693b206af
- true
- >
- >
- false
- 0
-
9185
28921
39
20
-
9204.5
28931
- Counter
- daaf5468-a976-4ef0-a518-fb036bd9cf70
- true
- Counter
- Counter
- false
- 0
-
9185
28941
39
20
-
9204.5
28951
- 2
- Contains a collection of generic data
- b601bd0c-ff52-4987-a6d9-cb9fc1bcc354
- true
- Data
- D0
- false
- 0
-
9185
28961
39
20
-
9204.5
28971
- 2
- Contains a collection of generic data
- 8c825e90-4b27-4bb3-9e7f-bcb80b27812f
- true
- Data
- D1
- false
- 0
-
9185
28981
39
20
-
9204.5
28991
- 4e5b891f-3e8d-4b3d-b677-996c63b3ac70
- 4442bb24-c702-460c-a1e4-fcdd321eb886
- Fast Loop End
- Loop End
- true
- aaea4aad-2963-4409-84b7-3990db27a71b
- true
- Fast Loop End
- Fast Loop End
- true
- 0
-
9394
28908
91
84
-
9439
28950
- 4
- 6cc73910-22ac-4eb4-882b-eb9d63b8f3c2
- cb95db89-6165-43b6-9c41-5702bc5bf137
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Connect to Loop Start
- c3bc5aa8-1b46-4010-93bf-b4a248668950
- true
- <
- <
- false
- 6dea6cc4-dc4e-4113-9e42-6c3693b206af
- 1
-
9396
28910
31
20
-
9411.5
28920
- Set to true to exit the loop
- 2e52e7cf-2d99-4181-98d0-2711d19de7de
- true
- Exit
- Exit
- true
- 0
-
9396
28930
31
20
-
9411.5
28940
- 1
- 1
- {0}
- false
- 2
- Contains a collection of generic data
- 2355d77a-2930-4385-a1dd-414f4809c4c9
- true
- Data
- D0
- false
- fa427076-9410-409a-a28f-ff2c773f6a9d
- 1
-
9396
28950
31
20
-
9411.5
28960
- 2
- Contains a collection of generic data
- d95e8708-b9cf-4d9a-945e-5db46367d6c9
- true
- Data
- D1
- false
- fd8d01b6-550f-461d-bf89-7d885534636d
- 1
-
9396
28970
31
20
-
9411.5
28980
- 2
- Contains a collection of generic data
- 15aa5336-9858-4ec6-beda-c3a2d7f52046
- true
- 1
- Data
- D0
- false
- 0
-
9451
28910
32
40
-
9459
28930
- 2
- Contains a collection of generic data
- d7b42618-d2bc-436a-98d5-a8857d8b2666
- true
- 1
- Data
- D1
- false
- 0
-
9451
28950
32
40
-
9459
28970
- 3e8ca6be-fda8-4aaf-b5c0-3c54c8bb7312
- Number
- Contains a collection of floating point numbers
- 1fe668b1-ad7d-42fc-ba89-f43371616761
- Number
- Number
- false
- fb5477b8-182b-46c5-ac57-f253eb9baed8
- 1
-
9514
29863
50
24
-
9539.742
29875.1
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 3
-
255;255;255;255
- A group of Grasshopper objects
- e62a82d8-3c92-4e2a-9aca-b526644e6c8b
- da33a5bd-afb6-4917-a2ad-7b78b6875928
- a962b382-2559-410e-b76c-266d28450a4a
- 3
- ac124fdd-467b-493a-8722-fa10321d6afc
- Group
- 59e0b89a-e487-49f8-bab8-b5bab16be14c
- Panel
- A panel for custom notes and text values
- 0f23777f-356c-47ca-b703-f6f1e543bf2d
- true
- Panel
- X 128
- false
- 0
- 0
- 0,1/128,1/64,3/128,1/32,5/128,3/64,7/128,1/16,9/128,5/64,11/128,3/32,13/128,7/64,15/128,1/8,17/128,9/64,19/128,5/32,21/128,11/64,23/128,3/16,25/128,13/64,27/128,7/32,29/128,15/64,31/128,1/4,33/128,17/64,35/128,9/32,37/128,19/64,39/128,5/16,41/128,21/64,43/128,11/32,45/128,23/64,47/128,3/8,49/128,25/64,51/128,13/32,53/128,27/64,55/128,7/16,57/128,29/64,59/128,15/32,61/128,31/64,63/128,1/2,65/128,33/64,67/128,17/32,69/128,35/64,71/128,9/16,73/128,37/64,75/128,19/32,77/128,39/64,79/128,5/8,81/128,41/64,83/128,21/32,85/128,43/64,87/128,11/16,89/128,45/64,91/128,23/32,93/128,47/64,95/128,3/4,97/128,49/64,99/128,25/32,101/128,51/64,103/128,13/16,105/128,53/64,107/128,27/32,109/128,55/64,111/128,7/8,113/128,57/64,115/128,29/32,117/128,59/64,119/128,15/16,121/128,61/64,123/128,31/32,125/128,63/64,127/128,1
-
7620
29907
160
100
- 0
- 0
- 0
-
7620.861
29907.82
-
255;255;255;255
- true
- true
- false
- false
- false
- false
- 04887d01-504c-480e-b2a2-01ea19cc5922
- Text Split
- Split some text into fragments using separators
- true
- eb4824b9-1b6a-4da7-afef-ca0073312fbf
- true
- Text Split
- Text Split
-
7837
29922
127
44
-
7919
29944
- Text to split.
- 162bd387-789a-4a1e-b1e2-dff8ebe83834
- true
- Text
- Text
- false
- 0f23777f-356c-47ca-b703-f6f1e543bf2d
- 1
-
7839
29924
68
20
-
7873
29934
- Separator characters.
- 6307c6e9-babd-4a85-bb23-641ced7a1e15
- true
- Separators
- Separators
- false
- 0
-
7839
29944
68
20
-
7873
29954
- 1
- 1
- {0}
- false
- ,
- 1
- Resulting text fragments
- d975738e-73d2-4393-a83a-2b9bf445bd2e
- true
- Result
- Result
- false
- 0
-
7931
29924
31
40
-
7946.5
29944
- 59e0b89a-e487-49f8-bab8-b5bab16be14c
- Panel
- A panel for custom notes and text values
- 2d00a82a-689f-4535-a590-6ea8f4f00616
- true
- Panel
- Y 128
- false
- 0
- 0
- 0,583/179789679820800,1153/561842749440,10997359/179789679820800,19/33177600,105664189/35957935964160,29407171/2809213747200,5264015321/179789679820800,143/2073600,25686901721/179789679820800,753352771/2809213747200,16748792509/35957935964160,25219/33177600,211860341359/179789679820800,983043073/561842749440,450217958983/179789679820800,1/288,842215449017/179789679820800,3467317247/561842749440,1431724785041/179789679820800,334781/33177600,452428920131/35957935964160,43445431229/2809213747200,3373656816679/179789679820800,46657/2073600,4798686576679/179789679820800,88063341629/2809213747200,1311836172611/35957935964160,1396781/33177600,8666608497041/179789679820800,30786738047/561842749440,11124681522617/179789679820800,5/72,13933895269817/179789679820800,48344323967/561842749440,17094249738641/179789679820800,3470381/33177600,4121049919811/35957935964160,351427130429/2809213747200,24463182807079/179789679820800,305857/2073600,28656580541479/179789679820800,482385079229/2809213747200,6632699163971/35957935964160,6555581/33177600,37951503498641/179789679820800,126370418687/561842749440,42980421657017/179789679820800,73/288,48206851661383/179789679820800,159001316353/561842749440,53586921538159/179789679820800,10393219/33177600,11815446530749/35957935964160,966420578371/2809213747200,64637603087321/179789679820800,777743/2073600,70235607695321/179789679820800,1141272491971/2809213747200,15169859899069/35957935964160,14515219/33177600,81467209666159/179789679820800,263363789953/561842749440,87085626163783/179789679820800,1/2,92704053657017/179789679820800,298478959487/561842749440,98322470154641/179789679820800,18662381/33177600,20788076065091/35957935964160,1667941255229/2809213747200,109554072125479/179789679820800,1295857/2073600,115152076733479/179789679820800,1842793168829/2809213747200,24142489433411/35957935964160,22784381/33177600,126202758282641/179789679820800,402841433087/561842749440,131582828159417/179789679820800,215/288,136809258163783/179789679820800,435472330753/561842749440,141838176322159/179789679820800,26622019/33177600,29325236800189/35957935964160,2326828667971/2809213747200,151133099279321/179789679820800,1767743/2073600,155326497013721/179789679820800,2457786616771/2809213747200,31836886044349/35957935964160,29707219/33177600,162695430082159/179789679820800,513498425473/561842749440,165855784550983/179789679820800,67/72,168664998298183/179789679820800,531056011393/561842749440,171123071323759/179789679820800,31780819/33177600,34646099791549/35957935964160,2721150405571/2809213747200,174990993244121/179789679820800,2026943/2073600,176416023004121/179789679820800,2765768315971/2809213747200,35505507044029/35957935964160,32842819/33177600,178357955035759/179789679820800,558375432193/561842749440,178947464371783/179789679820800,287/288,179339461861817/179789679820800,560859706367/561842749440,179577819479441/179789679820800,33152381/33177600,35941187171651/35957935964160,2808460394429/2809213747200,179763992919079/179789679820800,2073457/2073600,179784415805479/179789679820800,2809184340029/2809213747200,35957830299971/35957935964160,33177581/33177600,179789668823441/179789679820800,561842748287/561842749440,179789679820217/179789679820800,1
-
7619
30028
160
100
- 0
- 0
- 0
-
7619.861
30028.82
-
255;255;255;255
- true
- true
- false
- false
- false
- false
- 04887d01-504c-480e-b2a2-01ea19cc5922
- Text Split
- Split some text into fragments using separators
- true
- 07472091-983a-4c72-9d9b-b25b01bbcb7a
- true
- Text Split
- Text Split
-
7828
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68
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58
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- Resulting text consisting of all the fragments
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- Resulting text consisting of all the fragments
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31
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- Construct a point from {xyz} coordinates.
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- Construct Point
- Construct Point
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134
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255;255;255;255
- A group of Grasshopper objects
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- Construct a point from {xyz} coordinates.
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- Create an interpolated curve through a set of points.
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- Interpolate
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225
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159
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159
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- A group of Grasshopper objects
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- Text Split
- Text Split
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127
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- Text to split.
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- Separator characters.
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68
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31
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127
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- Separator characters.
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- Group
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255;255;255;255
- A group of Grasshopper objects
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- Group
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- All files|*.*
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- 6587fcbf-e3cf-480a-b2f5-641794474194
- Read File
- Read the contents of a file
- true
- fa29e628-2090-4c46-8c09-20615141542c
- true
- Read File
- Read File
- true
- action = GH_LineParserAction.Include
- Return line
- 'Parse the line and return some data that represents the line.
- 'If the line cannot be parsed, you can return Nothing and
- 'assign a different action.
- 'The default implementation is to just return the line itself.
- 'If you return types that implement IGH_Goo, this component
- 'will work substantially faster.
- 10
-
7492
31321
196
28
-
7635
31335
- Uri of file to read
- false
- All files|*.*
- b9508b12-2cc1-4f4d-9ca6-7f22a30c05a5
- true
- File
- File
- false
- 0
-
7494
31323
129
24
-
7558.5
31335
- 1
- 1
- {0}
- false
- C:\FABIUS 4096 X.TXT
- 1
- File content
- 12097910-805a-4ef6-998c-9e5ce5b09bc2
- true
- Content
- Content
- false
- 0
-
7647
31323
39
24
-
7666.5
31335
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 3
-
255;255;255;255
- A group of Grasshopper objects
- e71ad0d7-3b06-4678-b7ce-ed5cd535f317
- 51570009-3d5d-4bbd-b8b1-bdfbbf85115e
- 0da2aad4-444e-4d52-8274-d2fb3e5aaf1f
- 3
- f9dde7c6-699c-440c-a632-c24a8eefd133
- Group
- 04887d01-504c-480e-b2a2-01ea19cc5922
- Text Split
- Split some text into fragments using separators
- true
- b761c393-2730-4efa-a305-9443ef7597fe
- true
- Text Split
- Text Split
-
7899
31335
127
44
-
7981
31357
- Text to split.
- c7fab27f-5725-4cd5-8379-6b7d5e760f4d
- true
- Text
- Text
- false
- 8a536d62-0be0-4943-a59f-2d6466d0d509
- 1
-
7901
31337
68
20
-
7935
31347
- Separator characters.
- fd51762b-3e12-4500-b43e-6405505e5163
- true
- Separators
- Separators
- false
- 0
-
7901
31357
68
20
-
7935
31367
- 1
- 1
- {0}
- false
- ,
- 1
- Resulting text fragments
- 6effe990-2695-4dc9-8bc3-19a78bb8deec
- true
- Result
- Result
- false
- 0
-
7993
31337
31
40
-
8008.5
31357
- 04887d01-504c-480e-b2a2-01ea19cc5922
- Text Split
- Split some text into fragments using separators
- true
- 364a8efd-eec6-404f-ab5c-e6e2078d6eb8
- true
- Text Split
- Text Split
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- Text to split.
- a662be09-6078-4b5f-8ec5-951f3dbe5db4
- true
- Text
- Text
- false
- b055e58f-3b57-49cf-ab76-33835accf6a7
- 1
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- Separator characters.
- c61c81d3-8364-4e61-85b5-46af31dd582e
- true
- Separators
- Separators
- false
- 0
-
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- 1
- 1
- {0}
- false
- ,
- 1
- Resulting text fragments
- f906afd1-1468-4e27-bc1a-ccca50b7e743
- true
- Result
- Result
- false
- 0
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- 2013e425-8713-42e2-a661-b57e78840337
- Concatenate
- Concatenate some fragments of text
- true
- 87091d69-a60b-4a19-842b-a866901fe24c
- true
- Concatenate
- Concatenate
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- 2
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- 1
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- First text fragment
- b12325ed-1f6b-4983-bb39-a82a446015b6
- true
- Fragment A
- Fragment A
- true
- 6effe990-2695-4dc9-8bc3-19a78bb8deec
- 1
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- Second text fragment
- 0a3b9102-73a4-4b03-8763-e99531cb10ba
- true
- Fragment B
- Fragment B
- true
- eeaadcbc-e19f-4e7d-ad8f-797c7c321297
- 1
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- 1
- 1
- {0}
- false
- *65536
- Resulting text consisting of all the fragments
- 428b4b1c-8794-4258-a90a-711dd03be945
- true
- Result
- Result
- false
- 0
-
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- 2013e425-8713-42e2-a661-b57e78840337
- Concatenate
- Concatenate some fragments of text
- true
- afc5ea2b-b28a-4c04-a477-8796a5939be3
- true
- Concatenate
- Concatenate
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- 2
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- 1
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- First text fragment
- 097ed67d-2e7b-4914-bdf3-f02afc65acc5
- true
- Fragment A
- Fragment A
- true
- f906afd1-1468-4e27-bc1a-ccca50b7e743
- 1
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- Second text fragment
- c4d40302-5b1d-42ec-8eac-05a22e88299e
- true
- Fragment B
- Fragment B
- true
- eeaadcbc-e19f-4e7d-ad8f-797c7c321297
- 1
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- {0}
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- *65536
- Resulting text consisting of all the fragments
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- true
- Result
- Result
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- 0
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- 3581f42a-9592-4549-bd6b-1c0fc39d067b
- Construct Point
- Construct a point from {xyz} coordinates.
- true
- e71ad0d7-3b06-4678-b7ce-ed5cd535f317
- true
- Construct Point
- Construct Point
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- {x} coordinate
- 7fcc7372-e36e-4d5c-87d6-b659a531b31f
- true
- X coordinate
- X coordinate
- false
- 6effe990-2695-4dc9-8bc3-19a78bb8deec
- 1
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- 1
- 1
- {0}
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- {y} coordinate
- b1fc1dda-00d4-451d-a8be-115616047918
- true
- Y coordinate
- Y coordinate
- false
- f906afd1-1468-4e27-bc1a-ccca50b7e743
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- {0}
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- {z} coordinate
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- true
- Z coordinate
- Z coordinate
- false
- 0
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- {0}
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- Point coordinate
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- true
- Point
- Point
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- 0
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- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 3
-
255;255;255;255
- A group of Grasshopper objects
- e71ad0d7-3b06-4678-b7ce-ed5cd535f317
- 1
- 51570009-3d5d-4bbd-b8b1-bdfbbf85115e
- Group
- 3581f42a-9592-4549-bd6b-1c0fc39d067b
- Construct Point
- Construct a point from {xyz} coordinates.
- true
- 0da2aad4-444e-4d52-8274-d2fb3e5aaf1f
- true
- Construct Point
- Construct Point
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- {x} coordinate
- 510af284-b3c7-4070-a1be-cd410899d051
- true
- X coordinate
- X coordinate
- false
- 428b4b1c-8794-4258-a90a-711dd03be945
- 1
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- 1
- 1
- {0}
- 0
- {y} coordinate
- c44d4c56-b7dc-4b23-9a1a-7d69b7d37585
- true
- Y coordinate
- Y coordinate
- false
- 3ce54405-e2d2-4a5e-ac72-d0e4f4ca3f26
- 1
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- 1
- 1
- {0}
- 0
- {z} coordinate
- a7b31229-98f5-4b91-af59-735fbc1070e3
- true
- Z coordinate
- Z coordinate
- false
- 0
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- 1
- 1
- {0}
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- Point coordinate
- dc56eb11-1ba6-4fdc-9332-a1688428a3bb
- true
- Point
- Point
- false
- 0
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- 59e0b89a-e487-49f8-bab8-b5bab16be14c
- Panel
- A panel for custom notes and text values
- 213f2fc8-3c62-4add-b084-ae87fdec816f
- true
- Panel
- false
- 1
- f906afd1-1468-4e27-bc1a-ccca50b7e743
- 1
- Double click to edit panel content…
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- 0
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- 0
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255;255;255;255
- true
- true
- true
- false
- false
- true
- 6587fcbf-e3cf-480a-b2f5-641794474194
- Read File
- Read the contents of a file
- true
- 149afc02-a382-4ca6-9322-7a4f060b8f7f
- true
- Read File
- Read File
- true
- action = GH_LineParserAction.Include
- Return line
- 'Parse the line and return some data that represents the line.
- 'If the line cannot be parsed, you can return Nothing and
- 'assign a different action.
- 'The default implementation is to just return the line itself.
- 'If you return types that implement IGH_Goo, this component
- 'will work substantially faster.
- 10
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- Uri of file to read
- false
- All files|*.*
- 4e906bfc-2333-4718-8a8b-42b774beb5db
- true
- File
- File
- false
- 0
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- 1
- 1
- {0}
- false
- C:\FABIUS 4096 Y.TXT
- 1
- File content
- 3d097a6b-53b5-4f50-b948-3a177d2c8203
- true
- Content
- Content
- false
- 0
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- Data
- Contains a collection of generic data
- true
- b055e58f-3b57-49cf-ab76-33835accf6a7
- true
- Data
- Data
- false
- 0
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- {0;0}
- Grasshopper.Kernel.Types.GH_String
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- d5967b9f-e8ee-436b-a8ad-29fdcecf32d5
- Curve
- Contains a collection of generic curves
- true
- f2aa309b-3dac-4084-aa45-453eaa9db884
- Curve
- Curve
- false
- 0
-
8832
30234
50
24
-
8857.633
30246.82
- 1
- 1
- {0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0}
- -1
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- 00000000-0000-0000-0000-000000000000
- dde71aef-d6ed-40a6-af98-6b0673983c82
- Nurbs Curve
- Construct a nurbs curve from control points.
- true
- 5953c941-4736-4fdc-be71-5b01d5096fc8
- true
- Nurbs Curve
- Nurbs Curve
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- Curve control points
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- Periodic curve
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- 1
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- Resulting nurbs curve
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- Curve length
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- Curve domain
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- Domain
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- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 8d8f2080-094e-4467-95f2-a8b6da5f1972
- Relay
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- 1
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- 6587fcbf-e3cf-480a-b2f5-641794474194
- Read File
- Read the contents of a file
- true
- 13aab24b-b036-4a08-a6ee-d32ebb1217ee
- true
- Read File
- Read File
- true
- action = GH_LineParserAction.Include
- Return line
- 'Parse the line and return some data that represents the line.
- 'If the line cannot be parsed, you can return Nothing and
- 'assign a different action.
- 'The default implementation is to just return the line itself.
- 'If you return types that implement IGH_Goo, this component
- 'will work substantially faster.
- 10
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- Uri of file to read
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- All files|*.*
- 64b96e62-3d7e-4959-893b-b1cb268333af
- true
- File
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- C:\FABIUS 16384 X.TXT
- 1
- File content
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- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
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-
255;255;255;255
- A group of Grasshopper objects
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- 9ec4a0af-799b-4e1f-a413-0ecab486e883
- 3
- be8005da-b6c8-4939-ae79-fcd9991bdca6
- Group
- 04887d01-504c-480e-b2a2-01ea19cc5922
- Text Split
- Split some text into fragments using separators
- true
- d4c354e4-6a25-40e4-b57c-0b9d21a35f38
- Text Split
- Text Split
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- Text to split.
- a67e2d37-6782-4828-8780-a248f66e2fe8
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- Separator characters.
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- Separators
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- false
- 0
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- {0}
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- ,
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- Resulting text fragments
- a3fc0dec-53ca-4b10-9e78-ad3723aca7db
- Result
- Result
- false
- 0
-
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- 04887d01-504c-480e-b2a2-01ea19cc5922
- Text Split
- Split some text into fragments using separators
- true
- 07f4ba56-a85f-400d-9a35-83a531f8b2bd
- Text Split
- Text Split
-
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- Text to split.
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- Resulting text fragments
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- Result
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- 0
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- 2013e425-8713-42e2-a661-b57e78840337
- Concatenate
- Concatenate some fragments of text
- true
- f782a2d9-35ab-461f-85c9-631c6445710d
- Concatenate
- Concatenate
-
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28748
40
16
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28756
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28595
40
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28603
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28674
106
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28706
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28676
43
20
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28676
35
60
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28706
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28612
106
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31
20
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31
20
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20
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47
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28746
40
16
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28754
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40
16
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28601
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106
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43
20
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28688
35
60
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28718
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28624
106
64
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28656
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28626
31
20
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28636
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28646
31
20
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28666
31
20
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28626
47
60
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28656
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28758
40
16
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28766
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40
16
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28613
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43
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43
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43
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29254
35
60
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29284
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29190
106
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29192
31
20
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29202
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29212
31
20
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29232
31
20
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29192
47
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29324
40
16
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29332
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29171
40
16
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29179
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29250
106
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29282
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43
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43
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43
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29252
35
60
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29282
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29188
106
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29220
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29190
31
20
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29200
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29210
31
20
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29220
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29230
31
20
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29240
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29190
47
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29220
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29322
40
16
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29330
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29169
40
16
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29177
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29262
106
64
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29264
43
20
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43
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29304
43
20
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29314
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29264
35
60
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29294
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29200
106
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29202
31
20
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29212
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29222
31
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29242
31
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47
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40
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29342
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29181
40
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29189
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524
75
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29078.26
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28038
180
64
-
7843
28070
- 1
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28040
113
30
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28055
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7718
28070
113
30
-
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28085
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28040
39
20
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28050
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28060
39
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7874.5
28070
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- Number of input points represented by this output point
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- Valence
- Valence
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- Solve oriented geometry bounding boxes.
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- Bounding Box
- Bounding Box
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- Geometry to contain
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- Content
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- BoundingBox orientation plane
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28718.5
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- {0}
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0
0
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0
0
0
1
0
- Aligned bounding box in world coordinates
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- Box
- Box
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- Bounding box in orientation plane coordinates
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21
29
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- Deconstruct a box into its constituent parts.
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- Deconstruct Box
- Deconstruct Box
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- Box
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- Box plane
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28
20
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- {x} dimension of box
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- X
- X
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- 0
-
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28
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- {y} dimension of box
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- Y
- Y
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- {z} dimension of box
- 935b49cc-2e35-41e0-a03f-3e8eb3085dc5
- Z
- Z
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- 0
-
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28
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28630
- 290f418a-65ee-406a-a9d0-35699815b512
- Scale NU
- Scale an object with non-uniform factors.
- true
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- Scale NU
- Scale NU
-
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121
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- Base geometry
- 47b77219-faa2-4b58-81cd-509e899e35d6
- Geometry
- Geometry
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- fbe57887-2062-42c7-8b43-1b8cbf0f868c
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148
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- Base plane
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148
37
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- 1
- {0}
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0
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0
0
0
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- Scaling factor in {x} direction
- 178202bc-1094-4264-bbdf-bd7742c3e46b
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- Scale X
- Scale X
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148
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- Scaling factor in {y} direction
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148
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- Scale Z
- Scale Z
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- 0
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148
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- Scaled geometry
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- Geometry
- Geometry
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- Transformation data
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- Transform
- Transform
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- 825ea536-aebb-41e9-af32-8baeb2ecb590
- Deconstruct Domain
- Deconstruct a numeric domain into its component parts.
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- Deconstruct Domain
- Deconstruct Domain
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- Base domain
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- d610762b-ba5c-4146-85c0-41f86ab7e1f2
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- Deconstruct Domain
- Deconstruct a numeric domain into its component parts.
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- Deconstruct Domain
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108
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- Base domain
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- 7462aae9-6924-4657-9557-023ddbe1777e
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-
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38
40
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- Start of domain
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28650
42
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- End of domain
- a02d96b9-b3dc-41ac-b3f5-2cd3d63dcf7c
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42
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28680
- a0d62394-a118-422d-abb3-6af115c75b25
- Addition
- Mathematical addition
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- ea0c141b-afe1-42a7-9d8a-9497a83f08e7
- Addition
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70
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- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- First item for addition
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- true
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- Second item for addition
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- 0a5760b9-9367-41d1-add4-88c1ac009626
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- Result of addition
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- a0d62394-a118-422d-abb3-6af115c75b25
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70
44
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- First item for addition
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11
20
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- Second item for addition
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- a02d96b9-b3dc-41ac-b3f5-2cd3d63dcf7c
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11
20
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- Result of addition
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-
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31
40
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- 607e693e-61a7-43d7-b2a6-f247c6ad518b
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- Close Curve
- Closes a curve by adding an additional span
- true
- aee3b354-db1f-4d3d-b360-291577ff054f
- true
- Close Curve
- Close Curve
-
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194
64
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- Open curve to close
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- Curve
- Curve
- false
- b717ca0a-dae4-45ac-85f2-1e2e411b70d4
- 1
-
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27832
102
20
-
8656
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- The bulge factor for Tangency and Curvature modes
- 1d71c377-42f0-41db-8c97-73a79ca22ae2
- true
- Factor
- Factor
- true
- 0
-
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27852
102
20
-
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27862
- 1
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- {0}
- 0.5
- Blend Continuity Type
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- true
- Continuity
- Continuity
- true
- 0
-
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27872
102
20
-
8656
27882
- 1
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- {0}
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- A closed curve
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- Closed Curve
- Closed Curve
- false
- 0
-
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27832
64
60
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27862
- 59e0b89a-e487-49f8-bab8-b5bab16be14c
- Panel
- A panel for custom notes and text values
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- Panel
- false
- 0
- 0
- 0.0003419868677042794559
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255;255;255;255
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- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
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- A wire relay object
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- Relay
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40
16
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- d5967b9f-e8ee-436b-a8ad-29fdcecf32d5
- Curve
- Contains a collection of generic curves
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- Curve
- Curve
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28659
50
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- 11e95a7b-1e2c-4b66-bd95-fcad51f8662a
- Vector Display Ex
- Preview vectors in the viewport
- true
- 52029166-0194-4a15-9f99-2a6459a22d1b
- Vector Display Ex
- Vector Display Ex
-
8431
27852
76
84
-
8493
27894
- Start point of vector
- 5550e5e9-4471-419b-8cdf-22d1a7c9f9f5
- Point
- Point
- true
- 484ba687-c0e4-4304-a4c9-f88e8e6271cc
- 1
-
8433
27854
48
20
-
8457
27864
- Vector to display
- d94d1c9a-40f8-44d6-80a8-c3050982aa56
- Vector
- Vector
- true
- 72ce55c1-290d-4329-9208-b5c4d3190bc6
- 1
-
8433
27874
48
20
-
8457
27884
- Colour of vector
- c4e5c9c0-483c-4478-8c2b-3a83f228b790
- Colour
- Colour
- true
- 0
-
8433
27894
48
20
-
8457
27904
- 1
- 1
- {0}
-
255;0;0;0
- Width of vector lines
- 426df84f-3d1e-4abc-8847-c8dee5fc0e74
- Width
- Width
- true
- 0
-
8433
27914
48
20
-
8457
27924
- 1
- 1
- {0}
- 2
- 758d91a0-4aec-47f8-9671-16739a8a2c5d
- Format
- Format some data using placeholders and formatting tags
- true
- 92df39c6-f1a0-40bf-be65-baededdefc8f
- Format
- Format
-
7907
29180
130
84
-
7999
29222
- 4
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- 7fa15783-70da-485c-98c0-a099e6988c3e
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- Text format
- 2d7b5f1c-8d43-40f1-92e2-515dd21b4dac
- Format
- Format
- false
- 0
-
7909
29182
78
20
-
7948
29192
- 1
- 1
- {0}
- false
- {0:R}
- Formatting culture
- 6130ffb5-3b3e-468c-b86e-51b878a033c2
- Culture
- Culture
- false
- 0
-
7909
29202
78
20
-
7948
29212
- 1
- 1
- {0}
- 127
- Data to insert at {0} placeholders
- d99ac31b-d785-487c-a2a1-375045f89430
- false
- Data 0
- 0
- true
- a16e0194-897c-4ae3-a86c-9b0a83b06ed2
- 1
-
7909
29222
78
20
-
7948
29232
- Data to insert at {1} placeholders
- 054d532a-5ce9-4105-9642-75bacb9fe37f
- false
- Data 1
- 1
- true
- 0
-
7909
29242
78
20
-
7948
29252
- Formatted text
- 1f21e48d-e605-4a50-ab07-e00f3c5b3303
- Text
- Text
- false
- 0
-
8011
29182
24
80
-
8023
29222
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- a16e0194-897c-4ae3-a86c-9b0a83b06ed2
- Relay
- false
- 540742f6-f4da-4da9-8ecf-b5af184a14a7
- 1
-
7829
29167
40
16
-
7849
29175
- 9abae6b7-fa1d-448c-9209-4a8155345841
- Deconstruct
- Deconstruct a point into its component parts.
- true
- 1e75a589-6fc6-435c-8651-5b205a2d7f12
- Deconstruct
- Deconstruct
-
7757
27904
120
64
-
7798
27936
- Input point
- 954b8f10-7fc8-4419-93cc-941ce30c0ea8
- Point
- Point
- false
- 484ba687-c0e4-4304-a4c9-f88e8e6271cc
- 1
-
7759
27906
27
60
-
7772.5
27936
- Point {x} component
- c5098eba-f62f-4204-b86a-be1c52aae0ee
- X component
- X component
- false
- 0
-
7810
27906
65
20
-
7842.5
27916
- Point {y} component
- 5da2d624-4c9e-4761-99f7-447ce0d151b3
- Y component
- Y component
- false
- 0
-
7810
27926
65
20
-
7842.5
27936
- Point {z} component
- 5c28713c-6330-4532-b78c-b6594dea3eb7
- Z component
- Z component
- false
- 0
-
7810
27946
65
20
-
7842.5
27956
- 74cad441-2264-45fe-a57d-85034751208a
- Explode Tree
- Extract all the branches from a tree
- true
- f74eae17-b09c-46ae-a891-13e3f5c122a6
- Explode Tree
- Explode Tree
-
7929
27871
102
44
-
7984
27893
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2
- Data to explode
- bf93038e-70a3-4294-8e4e-1255776bb924
- 2
- Data
- Data
- true
- c5098eba-f62f-4204-b86a-be1c52aae0ee
- 1
-
7931
27873
41
40
-
7959.5
27893
- 2
- All data inside the branch at index: 0
- f2c449e8-8648-4fd0-89f4-d6b30aee160c
- false
- Branch 0
- {0;0;0}
- false
- 0
-
7996
27873
33
20
-
8012.5
27883
- 2
- All data inside the branch at index: 1
- 9d43af13-00f9-48eb-b21e-66c4781aff05
- false
- Branch 1
- {0;0;1}
- false
- 0
-
7996
27893
33
20
-
8012.5
27903
- 9c007a04-d0d9-48e4-9da3-9ba142bc4d46
- Subtraction
- Mathematical subtraction
- true
- 740de8b6-5fb7-460e-8178-072c070ed481
- Subtraction
- Subtraction
-
8092
27866
70
44
-
8117
27888
- 2
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- First operand for subtraction
- f4ee9563-4697-4362-a46d-f2a88d9d99f8
- A
- A
- true
- f2c449e8-8648-4fd0-89f4-d6b30aee160c
- 1
-
8094
27868
11
20
-
8099.5
27878
- Second operand for subtraction
- f6494056-0ccc-4f44-b588-dfc48481a8c0
- B
- B
- true
- 9d43af13-00f9-48eb-b21e-66c4781aff05
- 1
-
8094
27888
11
20
-
8099.5
27898
- Result of subtraction
- 33c98b11-df16-46d3-b656-96b33d6aef91
- Result
- Result
- false
- 0
-
8129
27868
31
40
-
8144.5
27888
- 758d91a0-4aec-47f8-9671-16739a8a2c5d
- Format
- Format some data using placeholders and formatting tags
- true
- fee30ed6-da8a-4110-8085-01d2b9e95ad0
- Format
- Format
-
8071
27777
130
64
-
8163
27809
- 3
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- 7fa15783-70da-485c-98c0-a099e6988c3e
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- Text format
- 21de8572-a054-4a8f-afc6-a50cf0d85c62
- Format
- Format
- false
- 0
-
8073
27779
78
20
-
8112
27789
- 1
- 1
- {0}
- false
- {0:R}
- Formatting culture
- 6857890b-c6da-48dd-b132-9e47656b3e39
- Culture
- Culture
- false
- 0
-
8073
27799
78
20
-
8112
27809
- 1
- 1
- {0}
- 127
- Data to insert at {0} placeholders
- c0f6caad-0e96-4cc7-8583-9de6fa452fab
- false
- Data 0
- 0
- true
- 33c98b11-df16-46d3-b656-96b33d6aef91
- 1
-
8073
27819
78
20
-
8112
27829
- Formatted text
- b9b225c0-4c70-4081-ac8a-96f9165ae9ee
- Text
- Text
- false
- 0
-
8175
27779
24
60
-
8187
27809
- 59e0b89a-e487-49f8-bab8-b5bab16be14c
- Panel
- A panel for custom notes and text values
- 9e429655-c48d-4c69-a6df-97f0119bf853
- Panel
- X0-X1
- false
- 0
- de99d806-0033-411c-be6e-993093e9e3ee
- 1
- 0.0003419868677042794559
-
8004
28787
226
71
- 0
- 0
- 0
-
8004.624
28787.98
- 2
-
255;255;255;255
- false
- false
- false
- false
- false
- false
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
- 21908f9c-3469-4e68-b7d2-26fba26d4ce1
- Merge
- Merge
-
8201
27867
90
64
-
8246
27899
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2
- Data stream 1
- f6b328d5-3e57-42dc-9c76-e27d45737586
- false
- Data 1
- D1
- true
- 33c98b11-df16-46d3-b656-96b33d6aef91
- 1
-
8203
27869
31
20
-
8218.5
27879
- 2
- Data stream 2
- 8bc03a2d-699a-4702-bd83-32f9ec336d16
- false
- Data 2
- D2
- true
- b9b225c0-4c70-4081-ac8a-96f9165ae9ee
- 1
-
8203
27889
31
20
-
8218.5
27899
- 2
- Data stream 3
- 1ce934d7-faae-4e16-b12e-a53a9df4d87d
- false
- Data 3
- D3
- true
- 0
-
8203
27909
31
20
-
8218.5
27919
- 2
- Result of merge
- de99d806-0033-411c-be6e-993093e9e3ee
- Result
- Result
- false
- 0
-
8258
27869
31
60
-
8273.5
27899
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- d07e1734-c175-41dc-9d25-373919246eee
- Evaluate Length
- Evaluate Length
-
9380
28207
142
64
-
9458
28239
- Curve to evaluate
- 922fb345-dec3-4c66-a47c-cf1c70c4c06d
- Curve
- Curve
- false
- 029f8972-c08f-4c74-9db9-d1602083474e
- 1
-
9382
28209
64
20
-
9414
28219
- Length factor for curve evaluation
- a5a41833-3de3-4e10-ad09-bb0d69af0e55
- Length
- Length
- false
- 0
-
9382
28229
64
20
-
9414
28239
- 1
- 2
- {0}
- 0
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 709774e1-8703-4f77-91ca-5479de0d21b6
- Normalized
- Normalized
- false
- 0
-
9382
28249
64
20
-
9414
28259
- 1
- 1
- {0}
- true
- Point at the specified length
- 1ec44e12-457a-44a6-b455-2cddad198960
- Point
- Point
- false
- 0
-
9470
28209
50
20
-
9495
28219
- Tangent vector at the specified length
- de7cc693-b0ab-48da-9e9a-bbb70e346679
- Tangent
- Tangent
- false
- 0
-
9470
28229
50
20
-
9495
28239
- Curve parameter at the specified length
- 0b8eff06-2ff1-453a-ac98-75c220a7d25a
- Parameter
- Parameter
- false
- 0
-
9470
28249
50
20
-
9495
28259
- 575660b1-8c79-4b8d-9222-7ab4a6ddb359
- Rectangle 2Pt
- Create a rectangle from a base plane and two points
- true
- 69e73aa8-5fb4-432a-b17a-628f37c7dab6
- Rectangle 2Pt
- Rectangle 2Pt
-
9286
28086
198
101
-
9422
28137
- Rectangle base plane
- 5789ef64-c81f-49d2-a581-b940101a24a8
- Plane
- Plane
- false
- 0
-
9288
28088
122
37
-
9349
28106.5
- 1
- 1
- {0}
-
0
0
0
1
0
0
0
1
0
- First corner point.
- ba696505-bc99-4f4c-8d22-2b5a07c80e75
- Point A
- Point A
- false
- 912685f9-83b2-4eee-b25d-7d7508084c6f
- 1
-
9288
28125
122
20
-
9349
28135
- 1
- 1
- {0}
-
0
0
0
- Second corner point.
- fb5ff762-bba1-462e-8ec2-8bc24533c267
- Point B
- Point B
- false
- 769a26b5-630b-417d-a1e6-3b0ac91c036c
- 1
-
9288
28145
122
20
-
9349
28155
- 1
- 1
- {0}
-
10
5
0
- Rectangle corner fillet radius
- ff56c1f5-6801-481c-9c1d-3f4e1b9659a6
- Radius
- Radius
- false
- 0
-
9288
28165
122
20
-
9349
28175
- 1
- 1
- {0}
- 0
- Rectangle defined by P, A and B
- ab140c6b-29ae-45d9-aa46-1e4421c51c98
- Rectangle
- Rectangle
- false
- 0
-
9434
28088
48
48
-
9458
28112.25
- Length of rectangle curve
- b0b980cc-2211-4380-a9f5-5c37023a92ef
- Length
- Length
- false
- 0
-
9434
28136
48
49
-
9458
28160.75
- 74cad441-2264-45fe-a57d-85034751208a
- Explode Tree
- Extract all the branches from a tree
- true
- d64b70d5-0d0e-4816-b963-e8ce5a5bf063
- Explode Tree
- Explode Tree
-
9563
28212
110
44
-
9618
28234
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2
- Data to explode
- 1edb8292-bfc6-42f2-82ac-de09063950c1
- 2
- Data
- Data
- true
- 1ec44e12-457a-44a6-b455-2cddad198960
- 1
-
9565
28214
41
40
-
9593.5
28234
- 2
- All data inside the branch at index: 0
- 912685f9-83b2-4eee-b25d-7d7508084c6f
- false
- Branch 0
- {0;0;1;0}
- false
- 0
-
9630
28214
41
20
-
9650.5
28224
- 2
- All data inside the branch at index: 1
- 769a26b5-630b-417d-a1e6-3b0ac91c036c
- false
- Branch 1
- {0;0;1;1}
- false
- 0
-
9630
28234
41
20
-
9650.5
28244
- a10e8cdf-7c7a-4aac-aa70-ddb7010ab231
- Box Corners
- Extract all 8 corners of a box.
- true
- 90853453-e60c-4c56-881f-35159939390d
- Box Corners
- Box Corners
-
9391
27916
94
164
-
9426
27998
- Base box
- 99c0c0b5-7068-4beb-bf6d-c57bfb82b35b
- Box
- Box
- false
- ab140c6b-29ae-45d9-aa46-1e4421c51c98
- 1
-
9393
27918
21
160
-
9403.5
27998
- Corner at {x=min, y=min, z=min}
- 1c28e1fb-be98-4317-86af-247d8f23f089
- Corner A
- Corner A
- false
- 0
-
9438
27918
45
20
-
9460.5
27928
- Corner at {x=max, y=min, z=min}
- 8e5df580-5e9d-4a08-9a46-a4e6a05238b2
- Corner B
- Corner B
- false
- 0
-
9438
27938
45
20
-
9460.5
27948
- Corner at {x=max, y=max, z=min}
- ccdfdbdd-4946-4a27-ab01-6cf94d644f57
- Corner C
- Corner C
- false
- 0
-
9438
27958
45
20
-
9460.5
27968
- Corner at {x=min, y=max, z=min}
- b4ccb984-448f-470a-80f3-02e69cdd354b
- Corner D
- Corner D
- false
- 0
-
9438
27978
45
20
-
9460.5
27988
- Corner at {x=min, y=min, z=max}
- 6613177f-e885-47bc-bd7c-38384cde8c2e
- Corner E
- Corner E
- false
- 0
-
9438
27998
45
20
-
9460.5
28008
- Corner at {x=max, y=min, z=max}
- dfeea850-330d-4d9d-8319-0652cbc2403b
- Corner F
- Corner F
- false
- 0
-
9438
28018
45
20
-
9460.5
28028
- Corner at {x=max, y=max, z=max}
- b952775f-1985-41fb-babf-9822bafb5eee
- Corner G
- Corner G
- false
- 0
-
9438
28038
45
20
-
9460.5
28048
- Corner at {x=min, y=min, z=max}
- 456e74d8-c68f-4ff2-8850-324bdac54734
- Corner H
- Corner H
- false
- 0
-
9438
28058
45
20
-
9460.5
28068
- fbac3e32-f100-4292-8692-77240a42fd1a
- Point
- Contains a collection of three-dimensional points
- true
- 06ecc8ab-7209-4438-836b-119c5732583d
- Point
- Point
- false
- b4ccb984-448f-470a-80f3-02e69cdd354b
- 1
-
9426
27893
50
24
-
9451.633
27905.84
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- 607647b9-d6f4-4c29-9f4d-93d739deeb34
- Polar Array
- Polar Array
-
9449
27721
191
84
-
9576
27763
- Base geometry
- 6a69a647-aacb-48b8-ab0e-694504f42f0f
- Geometry
- Geometry
- true
- 029f8972-c08f-4c74-9db9-d1602083474e
- 1
-
9451
27723
113
20
-
9507.5
27733
- Polar array plane
- 8b5aac2a-2c0b-4d67-90cb-023cbd588d4b
- Plane
- Plane
- false
- 06ecc8ab-7209-4438-836b-119c5732583d
- 1
-
9451
27743
113
20
-
9507.5
27753
- 1
- 1
- {0}
-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
- a3f39ccd-7156-4ea7-bcb5-6c7ccee91adf
- Count
- Count
- false
- 0
-
9451
27763
113
20
-
9507.5
27773
- 1
- 1
- {0}
- 1
- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- 420355a6-aff5-4db9-a9d5-990bea2c4892
- Angle
- Angle
- false
- 0
- false
-
9451
27783
113
20
-
9507.5
27793
- 1
- 1
- {0}
- 6.2831853071795862
- 1
- Arrayed geometry
- e68c5fe8-1fed-41da-98f7-f3dac4eb9545
- Geometry
- Geometry
- false
- 0
-
9588
27723
50
40
-
9613
27743
- 1
- Transformation data
- 534ccd7e-686f-40ce-936e-3a8bf42c0ed5
- Transform
- Transform
- false
- 0
-
9588
27763
50
40
-
9613
27783
- 74cad441-2264-45fe-a57d-85034751208a
- Explode Tree
- Extract all the branches from a tree
- true
- 8ee13ade-d6bc-48c9-a10e-035cd34ec578
- Explode Tree
- Explode Tree
-
7968
27678
102
44
-
8023
27700
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2
- Data to explode
- f0706de4-e458-45ae-8fe4-2e2801f1a5ff
- 2
- Data
- Data
- true
- 484ba687-c0e4-4304-a4c9-f88e8e6271cc
- 1
-
7970
27680
41
40
-
7998.5
27700
- 2
- All data inside the branch at index: 0
- 15ba0a9e-7c13-47c9-a120-0c7ab3977abd
- false
- Branch 0
- {0;0;0}
- false
- 0
-
8035
27680
33
20
-
8051.5
27690
- 2
- All data inside the branch at index: 1
- 49801c49-68b9-499a-8324-7a78a638a3e8
- false
- Branch 1
- {0;0;1}
- false
- 0
-
8035
27700
33
20
-
8051.5
27710
- 9abae6b7-fa1d-448c-9209-4a8155345841
- Deconstruct
- Deconstruct a point into its component parts.
- true
- f3f58225-4602-49ba-91e6-6b555431f93f
- Deconstruct
- Deconstruct
-
8100
27683
120
64
-
8141
27715
- Input point
- ef106332-e5b6-400b-9328-8410a73fba9d
- Point
- Point
- false
- 49801c49-68b9-499a-8324-7a78a638a3e8
- 1
-
8102
27685
27
60
-
8115.5
27715
- Point {x} component
- 3c6f247f-4c49-4f68-b5b5-0ff3d33ed74d
- X component
- X component
- false
- 0
-
8153
27685
65
20
-
8185.5
27695
- Point {y} component
- c349f021-de67-4c6a-85cc-018bf530b608
- Y component
- Y component
- false
- 0
-
8153
27705
65
20
-
8185.5
27715
- Point {z} component
- 331e46af-08fb-44cd-926d-c48814f1b83f
- Z component
- Z component
- false
- 0
-
8153
27725
65
20
-
8185.5
27735
- f12daa2f-4fd5-48c1-8ac3-5dea476912ca
- Mirror
- Mirror an object.
- true
- d58d961c-ae9c-4fab-832b-12998948c201
- Mirror
- Mirror
-
8787
28119
126
44
-
8849
28141
- Base geometry
- b2a4d631-1ae1-430c-ac1f-6e7474481ae5
- Geometry
- Geometry
- true
- fbe57887-2062-42c7-8b43-1b8cbf0f868c
- 1
-
8789
28121
48
20
-
8813
28131
- Mirror plane
- f5855df0-191f-4026-b8aa-26f9286fb056
- Plane
- Plane
- false
- 4825d5c1-ae87-4bbc-96d9-f6813501ff2c
- 1
-
8789
28141
48
20
-
8813
28151
- 1
- 1
- {0}
-
0
0
0
0
1
0
0
0
1
- Mirrored geometry
- 1af07c62-ff38-4cdf-aee3-f6ec7a28a8a9
- Geometry
- Geometry
- false
- 0
-
8861
28121
50
20
-
8886
28131
- Transformation data
- 39ae8c27-b896-4798-a3b2-59a4b6329b04
- Transform
- Transform
- false
- 0
-
8861
28141
50
20
-
8886
28151
- 59daf374-bc21-4a5e-8282-5504fb7ae9ae
- List Item
- 0
- Retrieve a specific item from a list.
- true
- 3a0b8b19-f25c-4518-a98f-627474f69fab
- List Item
- List Item
-
8051
28129
77
64
-
8108
28161
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- cb95db89-6165-43b6-9c41-5702bc5bf137
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- Base list
- 1001d769-275c-4259-b1ac-c87542504c18
- List
- List
- false
- 970781a8-0343-4bae-b5a7-02468ff37b8e
- 1
-
8053
28131
43
20
-
8074.5
28141
- Item index
- 097d2964-74f2-443f-a872-0e24902794a0
- Index
- Index
- false
- 0
-
8053
28151
43
20
-
8074.5
28161
- 1
- 1
- {0}
- -1
- Wrap index to list bounds
- a14f2e60-f3b0-4b1f-9664-41adbbd76081
- Wrap
- Wrap
- false
- 0
-
8053
28171
43
20
-
8074.5
28181
- 1
- 1
- {0}
- true
- Item at {i'}
- 4ed77016-2fe9-49fc-9c97-a8f70ec22370
- false
- Item
- i
- false
- 0
-
8120
28131
6
60
-
8123
28161
- 4c619bc9-39fd-4717-82a6-1e07ea237bbe
- Line SDL
- Create a line segment defined by start point, tangent and length.}
- true
- b1a15299-df6f-41a0-bae3-3358fad867da
- Line SDL
- Line SDL
-
8850
27997
111
64
-
8925
28029
- Line start point
- c1c4fc3b-1eec-4434-83fc-26979a82bcf3
- Start
- Start
- false
- 4ed77016-2fe9-49fc-9c97-a8f70ec22370
- 1
-
8852
27999
61
20
-
8882.5
28009
- Line tangent (direction)
- 573f9951-0238-4b24-963e-4796a8be1751
- Direction
- Direction
- false
- 0ad32c15-e0bb-438f-9a7c-fa7f5af22f77
- 1
-
8852
28019
61
20
-
8882.5
28029
- 1
- 1
- {0}
-
1
1
0
- Line length
- 6de70698-9aa8-4be6-af4b-a303befbc25f
- Length
- Length
- false
- 0
-
8852
28039
61
20
-
8882.5
28049
- 1
- 1
- {0}
- 1
- Line segment
- 4825d5c1-ae87-4bbc-96d9-f6813501ff2c
- Line
- Line
- false
- 0
-
8937
27999
22
60
-
8948
28029
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
- 54492cdf-eec5-43f9-b305-c633663f407c
- Merge
- Merge
-
8949
28149
90
64
-
8994
28181
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2
- Data stream 1
- fd0b6619-1604-496d-ae9f-03fb46558d80
- false
- Data 1
- D1
- true
- fbe57887-2062-42c7-8b43-1b8cbf0f868c
- 1
-
8951
28151
31
20
-
8966.5
28161
- 2
- Data stream 2
- f9761a1d-3802-42d1-bef0-f0706c242541
- false
- Data 2
- D2
- true
- 1af07c62-ff38-4cdf-aee3-f6ec7a28a8a9
- 1
-
8951
28171
31
20
-
8966.5
28181
- 2
- Data stream 3
- 3d143dcc-983f-4265-bbd5-3cca664fd9f5
- false
- Data 3
- D3
- true
- 0
-
8951
28191
31
20
-
8966.5
28201
- 2
- Result of merge
- 7b24f9ce-d158-4f9e-8e14-e345e0de6d31
- Result
- Result
- false
- 0
-
9006
28151
31
60
-
9021.5
28181
- 8073a420-6bec-49e3-9b18-367f6fd76ac3
- Join Curves
- Join as many curves as possible
- true
- 0d824c3b-96fc-42d2-a484-6f796091f7f8
- Join Curves
- Join Curves
-
8274
28181
132
44
-
8357
28203
- 1
- Curves to join
- 9c3fee6b-58aa-41ca-93bc-ef2f1243c2b2
- 1
- Curves
- Curves
- false
- 7b24f9ce-d158-4f9e-8e14-e345e0de6d31
- 1
-
8276
28183
69
20
-
8318.5
28193
- Preserve direction of input curves
- cc5a0252-614e-4554-b451-d40d7f81c38e
- Preserve
- Preserve
- false
- 0
-
8276
28203
69
20
-
8318.5
28213
- 1
- 1
- {0}
- false
- 1
- Joined curves and individual curves that could not be joined.
- fa54f823-8a2e-4f67-8c01-f0cd00a64ba4
- Curves
- Curves
- false
- 0
-
8369
28183
35
40
-
8386.5
28203
- 75eb156d-d023-42f9-a85e-2f2456b8bcce
- Interpolate (t)
- Create an interpolated curve through a set of points with tangents.
- true
- 547daed3-e526-468b-800a-64b6209048bc
- true
- Interpolate (t)
- Interpolate (t)
-
7458
28495
244
84
-
7650
28537
- 1
- Interpolation points
- d1922547-7b3c-4853-8b35-dc9cf830798c
- true
- Vertices
- Vertices
- false
- 970781a8-0343-4bae-b5a7-02468ff37b8e
- 1
-
7460
28497
178
20
-
7549
28507
- Tangent at start of curve
- d486fe76-ae79-45ad-8054-bac4bcefd8fc
- true
- Tangent Start
- Tangent Start
- false
- 0
-
7460
28517
178
20
-
7549
28527
- 1
- 1
- {0}
-
1
0
0
- Tangent at end of curve
- f1998f4b-2ddd-46c3-9feb-f37c4f3ece6d
- true
- Tangent End
- Tangent End
- false
- 0
-
7460
28537
178
20
-
7549
28547
- 1
- 1
- {0}
-
0
1
0
- Knot spacing (0=uniform, 1=chord, 2=sqrtchord)
- f99689a7-e708-475b-b74d-a577d35e724a
- true
- KnotStyle
- KnotStyle
- false
- 0
-
7460
28557
178
20
-
7549
28567
- 1
- 1
- {0}
- 2
- Resulting nurbs curve
- 473f7647-6e58-4b9e-91d2-8f585d5a6649
- true
- Curve
- Curve
- false
- 0
-
7662
28497
38
26
-
7681
28510.33
- Curve length
- d2ed8027-a0e0-498f-a043-e358e6bb5ab0
- true
- Length
- Length
- false
- 0
-
7662
28523
38
27
-
7681
28537
- Curve domain
- 1f348736-b2e3-4af7-86af-c1a614441e90
- true
- Domain
- Domain
- false
- 0
-
7662
28550
38
27
-
7681
28563.67
- e9eb1dcf-92f6-4d4d-84ae-96222d60f56b
- Move
- Translate (move) an object along a vector.
- true
- 49641e2a-6345-4e2b-a88c-65b810efe4e3
- Move
- Move
-
9523
27958
158
44
-
9601
27980
- Base geometry
- b507da92-7dc2-480a-9fa1-0f0e90fa2618
- Geometry
- Geometry
- true
- e68c5fe8-1fed-41da-98f7-f3dac4eb9545
- 1
-
9525
27960
64
20
-
9565
27970
- Translation vector
- 42a20604-cfcb-42de-99b2-15990d9215e3
- -X
- Motion
- Motion
- false
- 06ecc8ab-7209-4438-836b-119c5732583d
- 1
-
9525
27980
64
20
-
9565
27990
- 1
- 1
- {0}
-
0
0
10
- Translated geometry
- 9f7378b6-9894-4b84-998a-f5226749112f
- 1
- Geometry
- Geometry
- false
- 0
-
9613
27960
66
20
-
9638
27970
- Transformation data
- 3b7e5e45-5dae-4b9a-a940-d75a94b88f48
- Transform
- Transform
- false
- 0
-
9613
27980
66
20
-
9638
27990
- 11bbd48b-bb0a-4f1b-8167-fa297590390d
- End Points
- Extract the end points of a curve.
- true
- 921a4c47-a14a-4ae8-a939-3fa685fa688d
- End Points
- End Points
-
8738
28378
84
44
-
8782
28400
- Curve to evaluate
- c0dcc44b-e03a-4be2-b2ca-2d753dc405e7
- Curve
- Curve
- false
- fbe57887-2062-42c7-8b43-1b8cbf0f868c
- 1
-
8740
28380
30
40
-
8755
28400
- Curve start point
- c475072e-1fe0-42c5-b3e5-ace9a4f477bc
- Start
- Start
- false
- 0
-
8794
28380
26
20
-
8807
28390
- Curve end point
- 796038b0-8393-4141-a4f4-fa10cae2524d
- End
- End
- false
- 0
-
8794
28400
26
20
-
8807
28410
- 4c4e56eb-2f04-43f9-95a3-cc46a14f495a
- Line
- Create a line between two points.
- true
- be9b2731-1a06-4cce-84c1-1c4881f7601a
- Line
- Line
-
8887
28378
102
44
-
8953
28400
- Line start point
- 3025a762-b90d-46e1-81c6-2d91538603f9
- Start Point
- Start Point
- false
- c475072e-1fe0-42c5-b3e5-ace9a4f477bc
- 1
-
8889
28380
52
20
-
8915
28390
- Line end point
- 950fbbca-eba8-46d3-b614-dfc70b04ce67
- End Point
- End Point
- false
- 796038b0-8393-4141-a4f4-fa10cae2524d
- 1
-
8889
28400
52
20
-
8915
28410
- Line segment
- df9ef313-9e68-44f2-b57a-df8a5f0a17a3
- Line
- Line
- false
- 0
-
8965
28380
22
40
-
8976
28400
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 98c446bc-5e7b-4949-bc4d-55a5abdcc6dc
- Evaluate Length
- Evaluate Length
-
9031
28369
149
64
-
9116
28401
- Curve to evaluate
- 0e75f930-85f2-4e6f-a02a-e76d332f1e8e
- Curve
- Curve
- false
- df9ef313-9e68-44f2-b57a-df8a5f0a17a3
- 1
-
9033
28371
71
20
-
9068.5
28381
- Length factor for curve evaluation
- a7c5e0af-e582-4ad0-93df-3660492d36df
- Length
- Length
- false
- 0
-
9033
28391
71
20
-
9068.5
28401
- 1
- 1
- {0}
- 0.5
- If True, the Length factor is normalized (0.0 ~ 1.0)
- d300cf4d-5b21-482f-98fb-a6424261ff24
- Normalized
- Normalized
- false
- 0
-
9033
28411
71
20
-
9068.5
28421
- 1
- 1
- {0}
- true
- Point at the specified length
- 25200f80-2e95-4f38-ab66-a92c473cb11e
- Point
- Point
- false
- 0
-
9128
28371
50
20
-
9153
28381
- Tangent vector at the specified length
- aed17c8c-373a-4521-b837-4c123720e32f
- Tangent
- Tangent
- false
- 0
-
9128
28391
50
20
-
9153
28401
- Curve parameter at the specified length
- d10df88d-d7b4-44a1-ba2c-423feaf79c00
- Parameter
- Parameter
- false
- 0
-
9128
28411
50
20
-
9153
28421
- 4c619bc9-39fd-4717-82a6-1e07ea237bbe
- Line SDL
- Create a line segment defined by start point, tangent and length.}
- true
- 6702c62f-e4c0-49b2-83f6-4419cd923fb7
- Line SDL
- Line SDL
-
9240
28381
94
64
-
9298
28413
- Line start point
- 2ef5a359-b0b1-41a3-982d-a20728a8dc11
- Start
- Start
- false
- 25200f80-2e95-4f38-ab66-a92c473cb11e
- 1
-
9242
28383
44
20
-
9264
28393
- Line tangent (direction)
- f4198ebb-ed97-4f14-93e1-dcf5e71fc811
- Direction
- Direction
- false
- 3641d63f-f6a1-410a-bb98-c00fec3be173
- 1
-
9242
28403
44
20
-
9264
28413
- 1
- 1
- {0}
-
0
0
1
- Line length
- 932422c3-938f-4896-bfba-93e9dc63dd8e
- Length
- Length
- false
- 9f3a6cd3-00a5-4f12-84f7-3a56eb5630da
- 1
-
9242
28423
44
20
-
9264
28433
- 1
- 1
- {0}
- 1
- Line segment
- 308c9394-dd98-4fc8-971a-a1b8bf4ce995
- Line
- Line
- false
- 0
-
9310
28383
22
60
-
9321
28413
- b6d7ba20-cf74-4191-a756-2216a36e30a7
- Rotate
- Rotate a vector around an axis.
- true
- ea049eb4-e34b-4db1-971c-23f959a7c78a
- Rotate
- Rotate
-
9005
28477
185
64
-
9143
28509
- Vector to rotate
- b8b25cd0-c4e0-4e97-a694-3999684b1fa1
- Vector
- Vector
- false
- aed17c8c-373a-4521-b837-4c123720e32f
- 1
-
9007
28479
124
20
-
9077
28489
- Rotation axis
- 5738ea86-6bef-4d8a-821c-df3f2582e45e
- Axis
- Axis
- false
- 0
-
9007
28499
124
20
-
9077
28509
- 1
- 1
- {0}
-
0
0
1
- Rotation angle (in degrees)
- 22b5c062-1d46-4959-bf7f-ce186f811a1c
- Angle
- Angle
- false
- 0
- true
-
9007
28519
124
20
-
9077
28529
- 1
- 1
- {0}
- 90
- Rotated vector
- 3641d63f-f6a1-410a-bb98-c00fec3be173
- Vector
- Vector
- false
- 0
-
9155
28479
33
60
-
9171.5
28509
- c75b62fa-0a33-4da7-a5bd-03fd0068fd93
- Length
- Measure the length of a curve.
- true
- 22c2fd8f-4f4b-486f-a523-4871ff61a4d0
- Length
- Length
-
8837
28292
92
28
-
8881
28306
- Curve to measure
- baa1397b-52fd-4f3f-be30-f33ffcadbf13
- Curve
- Curve
- false
- df9ef313-9e68-44f2-b57a-df8a5f0a17a3
- 1
-
8839
28294
30
24
-
8854
28306
- Curve length
- 0d72d33c-7529-4646-b0d3-e06c84ee7c1f
- Length
- Length
- false
- 0
-
8893
28294
34
24
-
8910
28306
- 9df5e896-552d-4c8c-b9ca-4fc147ffa022
- Expression
- Evaluate an expression
- O*SQRT(3)/6
- true
- 3d1f2fa7-968c-4d68-8a1f-878b5c7ca144
- Expression
- Expression
-
9011
28274
158
28
-
9080
28288
- 1
- ba80fd98-91a1-4958-b6a7-a94e40e52bdb
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Expression variable
- fd1f6b44-7166-48cf-a064-4545c7281f0f
- Variable O
- O
- true
- 0d72d33c-7529-4646-b0d3-e06c84ee7c1f
- 1
-
9013
28276
11
24
-
9018.5
28288
- Result of expression
- 9f3a6cd3-00a5-4f12-84f7-3a56eb5630da
- Result
- Result
- false
- 0
-
9136
28276
31
24
-
9151.5
28288
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 57393fcf-4116-4c07-92dd-e41339c0f525
- Evaluate Length
- Evaluate Length
-
9400
28360
149
64
-
9485
28392
- Curve to evaluate
- ce65bcce-f09a-44b3-94cd-cc73bb237aaf
- Curve
- Curve
- false
- 308c9394-dd98-4fc8-971a-a1b8bf4ce995
- 1
-
9402
28362
71
20
-
9437.5
28372
- Length factor for curve evaluation
- baafa833-4ef8-425f-b607-a7876121b49c
- Length
- Length
- false
- 0
-
9402
28382
71
20
-
9437.5
28392
- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- de9b5e2c-f3fc-426a-a76a-87c3039c08ba
- Normalized
- Normalized
- false
- 0
-
9402
28402
71
20
-
9437.5
28412
- 1
- 1
- {0}
- true
- Point at the specified length
- 53ada397-2c9c-431e-8a96-ba407a255873
- Point
- Point
- false
- 0
-
9497
28362
50
20
-
9522
28372
- Tangent vector at the specified length
- dd888f3a-4b87-4d6a-85e5-fb0aa6030ccb
- Tangent
- Tangent
- false
- 0
-
9497
28382
50
20
-
9522
28392
- Curve parameter at the specified length
- cfa9c748-f17c-4de8-8706-d009df92c6cf
- Parameter
- Parameter
- false
- 0
-
9497
28402
50
20
-
9522
28412
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- 643548c7-e04c-46c8-a912-73b81340f60c
- Polar Array
- Polar Array
-
9579
28299
191
84
-
9706
28341
- Base geometry
- 51b4c9be-a0a6-48b0-8a51-2b635cbf72ca
- Geometry
- Geometry
- true
- df9ef313-9e68-44f2-b57a-df8a5f0a17a3
- 1
-
9581
28301
113
20
-
9637.5
28311
- Polar array plane
- 14495758-452f-4515-833d-6b411c69c0fe
- Plane
- Plane
- false
- 53ada397-2c9c-431e-8a96-ba407a255873
- 1
-
9581
28321
113
20
-
9637.5
28331
- 1
- 1
- {0}
-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
- eea66035-3fac-4d03-950f-8296730c879e
- Count
- Count
- false
- 0
-
9581
28341
113
20
-
9637.5
28351
- 1
- 1
- {0}
- 3
- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- 2123eff2-fbe6-4059-9ae7-dcce8ac7add1
- Angle
- Angle
- false
- 0
- false
-
9581
28361
113
20
-
9637.5
28371
- 1
- 1
- {0}
- 6.2831853071795862
- 1
- Arrayed geometry
- f9dcf267-1e15-4850-9ec4-8e7ad6d9f2ad
- Geometry
- Geometry
- false
- 0
-
9718
28301
50
40
-
9743
28321
- 1
- Transformation data
- dd83b124-9569-4709-9a61-1a92bc7b736c
- Transform
- Transform
- false
- 0
-
9718
28341
50
40
-
9743
28361
- 8073a420-6bec-49e3-9b18-367f6fd76ac3
- Join Curves
- Join as many curves as possible
- true
- 5f125462-d0f8-4183-b286-475d3acf0b80
- Join Curves
- Join Curves
-
9944
28313
116
44
-
10011
28335
- 1
- Curves to join
- 12e37bce-c053-4efd-a977-c0f522b26642
- Curves
- Curves
- false
- f9dcf267-1e15-4850-9ec4-8e7ad6d9f2ad
- 1
-
9946
28315
53
20
-
9972.5
28325
- Preserve direction of input curves
- d117240c-4ab9-460f-bbfb-66dc61b43975
- Preserve
- Preserve
- false
- 0
-
9946
28335
53
20
-
9972.5
28345
- 1
- 1
- {0}
- false
- 1
- Joined curves and individual curves that could not be joined.
- 313dc56d-5db5-4cb0-88da-248d848cf9d0
- Curves
- Curves
- false
- 0
-
10023
28315
35
40
-
10040.5
28335
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- 3cc94df5-d9f1-4979-a5ab-be1fac63184f
- Polar Array
- Polar Array
-
9586
28421
191
84
-
9713
28463
- Base geometry
- e6740668-b9bc-4cec-88e7-68ca31ae6aee
- Geometry
- Geometry
- true
- fbe57887-2062-42c7-8b43-1b8cbf0f868c
- 1
-
9588
28423
113
20
-
9644.5
28433
- Polar array plane
- 50d41db2-0be5-414a-a105-cf75d7ca3326
- Plane
- Plane
- false
- 53ada397-2c9c-431e-8a96-ba407a255873
- 1
-
9588
28443
113
20
-
9644.5
28453
- 1
- 1
- {0}
-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
- a4c562c2-1370-489a-8662-0f28f19bec21
- Count
- Count
- false
- 0
-
9588
28463
113
20
-
9644.5
28473
- 1
- 1
- {0}
- 3
- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- b42ad307-1e85-4873-992e-8cb29886ba06
- Angle
- Angle
- false
- 0
- false
-
9588
28483
113
20
-
9644.5
28493
- 1
- 1
- {0}
- 6.2831853071795862
- 1
- Arrayed geometry
- bc6ee7cc-dfce-484f-b2eb-2a5a4d0007c8
- Geometry
- Geometry
- false
- 0
-
9725
28423
50
40
-
9750
28443
- 1
- Transformation data
- 914dfde9-23d3-4c32-8acf-801b3a0a96f7
- Transform
- Transform
- false
- 0
-
9725
28463
50
40
-
9750
28483
- d5967b9f-e8ee-436b-a8ad-29fdcecf32d5
- Curve
- Contains a collection of generic curves
- true
- 74f760b9-aa8a-4167-9ec4-7a13306ccf56
- true
- Curve
- Curve
- false
- 0
-
7000
-3940
50
24
-
7025.612
-3928.156
- 1
- 4
- {0;0;1;0;0}
- -1
-
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
- 00000000-0000-0000-0000-000000000000
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
- 00000000-0000-0000-0000-000000000000
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
- 00000000-0000-0000-0000-000000000000
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
- 00000000-0000-0000-0000-000000000000
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
- 00000000-0000-0000-0000-000000000000
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
- 00000000-0000-0000-0000-000000000000
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10743
28380
148
20
-
10825
28390
- Rotation angle in degrees
- 08234d50-5319-4eda-b011-e5a672193566
- true
- Angle
- Angle
- false
- 0
- true
-
10743
28400
148
20
-
10825
28410
- 1
- 1
- {0}
- 45
- Rotation plane
- 71cf7492-5d81-4727-b72d-dda2eb760d72
- true
- Plane
- Plane
- false
- 0
-
10743
28420
148
37
-
10825
28438.5
- 1
- 1
- {0}
-
0
0
0
1
0
0
0
1
0
- Rotated geometry
- d2a443aa-c60e-47a5-abed-2e2835b68a16
- true
- Geometry
- Geometry
- false
- 0
-
10915
28380
50
38
-
10940
28399.25
- Transformation data
- 897ce37d-d731-4fb4-b8fe-75df1d5dc9a2
- true
- Transform
- Transform
- false
- 0
-
10915
28418
50
39
-
10940
28437.75
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- e7a5cf4c-3f82-4f47-b79b-d8e2537d8afd
- 1
- a941ff94-f01d-41a5-8c0b-c7127477058b
- Group
- b7798b74-037e-4f0c-8ac7-dc1043d093e0
- Rotate
- Rotate an object in a plane.
- true
- 8c984148-7404-4d11-8d34-bca11770b24b
- true
- Rotate
- Rotate
-
11017
28380
226
81
-
11179
28421
- Base geometry
- 7f4e85e8-1d1c-48d7-8d91-6d18ec61aa57
- true
- Geometry
- Geometry
- true
- d2a443aa-c60e-47a5-abed-2e2835b68a16
- 1
-
11019
28382
148
20
-
11101
28392
- Rotation angle in degrees
- 7c6018ba-c804-42dc-9996-5cae1df22202
- true
- Angle
- Angle
- false
- 0
- true
-
11019
28402
148
20
-
11101
28412
- 1
- 1
- {0}
- 90
- Rotation plane
- 6f386100-34ea-43f2-b91b-92333417f7d4
- true
- Plane
- Plane
- false
- 0
-
11019
28422
148
37
-
11101
28440.5
- 1
- 1
- {0}
-
0
0
0
0
0
1
1
0
0
- Rotated geometry
- 187503ea-36dc-430c-b32c-9a0fc88ca815
- true
- Geometry
- Geometry
- false
- 0
-
11191
28382
50
38
-
11216
28401.25
- Transformation data
- 2edb102d-c38c-4b17-ad62-8b711fbd4fa7
- true
- Transform
- Transform
- false
- 0
-
11191
28420
50
39
-
11216
28439.75
- b7798b74-037e-4f0c-8ac7-dc1043d093e0
- Rotate
- Rotate an object in a plane.
- true
- f23308dc-6e0b-4773-8442-547e1fc6aa65
- true
- Rotate
- Rotate
-
11022
28474
226
81
-
11184
28515
- Base geometry
- 2c0ae8e6-3630-4763-8c31-b9bbfd2e3c67
- true
- Geometry
- Geometry
- true
- d2a443aa-c60e-47a5-abed-2e2835b68a16
- 1
-
11024
28476
148
20
-
11106
28486
- Rotation angle in degrees
- 92a62df3-18a7-497f-bad7-10c8f60f9a2d
- true
- Angle
- Angle
- false
- 0
- true
-
11024
28496
148
20
-
11106
28506
- 1
- 1
- {0}
- 90
- Rotation plane
- df893b4e-64c0-40e3-aab8-e58edaf6b4f6
- true
- Plane
- Plane
- false
- 0
-
11024
28516
148
37
-
11106
28534.5
- 1
- 1
- {0}
-
0
0
0
0
1
0
0
0
1
- Rotated geometry
- 95df8731-1a7f-41e7-a9cb-ee4366bdc926
- true
- Geometry
- Geometry
- false
- 0
-
11196
28476
50
38
-
11221
28495.25
- Transformation data
- 185ac99e-4fd1-4677-b7ff-41c7d45269a5
- true
- Transform
- Transform
- false
- 0
-
11196
28514
50
39
-
11221
28533.75
- 59daf374-bc21-4a5e-8282-5504fb7ae9ae
- List Item
- 0
- Retrieve a specific item from a list.
- true
- 0904875c-3233-4683-9546-caf8a1b3bca5
- true
- List Item
- List Item
-
10947
28201
77
64
-
11004
28233
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- cb95db89-6165-43b6-9c41-5702bc5bf137
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- Base list
- ee418169-09f2-4e76-b5d5-545d268e3f85
- true
- List
- List
- false
- d2a443aa-c60e-47a5-abed-2e2835b68a16
- 1
-
10949
28203
43
20
-
10970.5
28213
- Item index
- 0b00e8eb-bba4-4229-85d7-4a747af6e274
- true
- Index
- Index
- false
- 0
-
10949
28223
43
20
-
10970.5
28233
- 1
- 1
- {0}
- 1
- Wrap index to list bounds
- fae23512-71a1-4420-9312-ebcf2925939a
- true
- Wrap
- Wrap
- false
- 0
-
10949
28243
43
20
-
10970.5
28253
- 1
- 1
- {0}
- true
- Item at {i'}
- 1e161022-56a4-4db7-b405-3a1b081e4b21
- true
- false
- Item
- i
- false
- 0
-
11016
28203
6
60
-
11019
28233
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- e524ba89-65f4-457a-8f3b-566e3d69b338
- true
- Evaluate Length
- Evaluate Length
-
10915
28124
149
64
-
11000
28156
- Curve to evaluate
- f0ab2af7-69c9-43db-868b-caa852889764
- true
- Curve
- Curve
- false
- 1e161022-56a4-4db7-b405-3a1b081e4b21
- 1
-
10917
28126
71
20
-
10952.5
28136
- Length factor for curve evaluation
- fc420753-ba03-4fef-a0a8-a524c2294e69
- true
- Length
- Length
- false
- 0
-
10917
28146
71
20
-
10952.5
28156
- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 8f83b134-0f2b-4506-a36b-358c77416dd0
- true
- Normalized
- Normalized
- false
- 0
-
10917
28166
71
20
-
10952.5
28176
- 1
- 1
- {0}
- true
- Point at the specified length
- ac15329e-7811-4638-9e02-958d44a78172
- true
- Point
- Point
- false
- 0
-
11012
28126
50
20
-
11037
28136
- Tangent vector at the specified length
- 68eeceaf-bc83-493a-bd93-69c0745eb406
- true
- Tangent
- Tangent
- false
- 0
-
11012
28146
50
20
-
11037
28156
- Curve parameter at the specified length
- e5f26acc-dc65-4f84-b199-bac1f44df9f2
- true
- Parameter
- Parameter
- false
- 0
-
11012
28166
50
20
-
11037
28176
- 59daf374-bc21-4a5e-8282-5504fb7ae9ae
- List Item
- 0
- Retrieve a specific item from a list.
- true
- 17a07c24-0f69-4fa4-97bb-e3c74ef6d55c
- true
- List Item
- List Item
-
11236
28245
77
64
-
11293
28277
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- cb95db89-6165-43b6-9c41-5702bc5bf137
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- Base list
- a7eca345-3aa0-4a12-8aa2-d6a39cf2468e
- true
- List
- List
- false
- 187503ea-36dc-430c-b32c-9a0fc88ca815
- 1
-
11238
28247
43
20
-
11259.5
28257
- Item index
- d14122b2-7acb-4746-a18e-74977033a79e
- true
- Index
- Index
- false
- 0
-
11238
28267
43
20
-
11259.5
28277
- 1
- 1
- {0}
- 1
- Wrap index to list bounds
- 54a61329-e56d-43ff-bc17-2fb9301f00ac
- true
- Wrap
- Wrap
- false
- 0
-
11238
28287
43
20
-
11259.5
28297
- 1
- 1
- {0}
- true
- Item at {i'}
- 8cb14055-5fd5-4d4c-bef3-3b128ef5471a
- true
- false
- Item
- i
- false
- 0
-
11305
28247
6
60
-
11308
28277
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- a3a0987e-4742-48b6-afc7-5797464d4f9b
- true
- Evaluate Length
- Evaluate Length
-
11204
28168
149
64
-
11289
28200
- Curve to evaluate
- 30685dfe-7c69-42e5-8c42-242b51d3ca47
- true
- Curve
- Curve
- false
- 8cb14055-5fd5-4d4c-bef3-3b128ef5471a
- 1
-
11206
28170
71
20
-
11241.5
28180
- Length factor for curve evaluation
- 07212ece-558c-4b90-aab4-fa97e1419910
- true
- Length
- Length
- false
- 0
-
11206
28190
71
20
-
11241.5
28200
- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 24e30027-61a0-4bf9-8e3d-aaabcf947974
- true
- Normalized
- Normalized
- false
- 0
-
11206
28210
71
20
-
11241.5
28220
- 1
- 1
- {0}
- true
- Point at the specified length
- d862f42d-b7d5-4961-8f17-2c24fd595947
- true
- Point
- Point
- false
- 0
-
11301
28170
50
20
-
11326
28180
- Tangent vector at the specified length
- f285b504-4093-46e2-9eb0-9a385df801db
- true
- Tangent
- Tangent
- false
- 0
-
11301
28190
50
20
-
11326
28200
- Curve parameter at the specified length
- 5a57e3ed-694c-4971-b6d3-c608b9faaea3
- true
- Parameter
- Parameter
- false
- 0
-
11301
28210
50
20
-
11326
28220
- 59daf374-bc21-4a5e-8282-5504fb7ae9ae
- List Item
- 0
- Retrieve a specific item from a list.
- true
- ed800b1a-87bc-41be-b147-fd8cf8fee48b
- true
- List Item
- List Item
-
11319
28627
77
64
-
11376
28659
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- cb95db89-6165-43b6-9c41-5702bc5bf137
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- Base list
- 7cdfb12e-b2df-4b62-9889-6b875368dc1c
- true
- List
- List
- false
- 95df8731-1a7f-41e7-a9cb-ee4366bdc926
- 1
-
11321
28629
43
20
-
11342.5
28639
- Item index
- 46a9e4b4-4ee0-4a14-8717-9ee715e06e09
- true
- Index
- Index
- false
- 0
-
11321
28649
43
20
-
11342.5
28659
- 1
- 1
- {0}
- 1
- Wrap index to list bounds
- 385de72d-084e-43f5-87e9-f9b7a9fd90b3
- true
- Wrap
- Wrap
- false
- 0
-
11321
28669
43
20
-
11342.5
28679
- 1
- 1
- {0}
- true
- Item at {i'}
- 1ba44e11-3244-4b08-8f5a-53473e7444b0
- true
- false
- Item
- i
- false
- 0
-
11388
28629
6
60
-
11391
28659
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 74d54793-b4ac-4902-b2db-7eb97fad4e83
- true
- Evaluate Length
- Evaluate Length
-
11287
28550
149
64
-
11372
28582
- Curve to evaluate
- bcac2eb2-1cf5-4798-b21c-3c1c4e53b1a4
- true
- Curve
- Curve
- false
- 1ba44e11-3244-4b08-8f5a-53473e7444b0
- 1
-
11289
28552
71
20
-
11324.5
28562
- Length factor for curve evaluation
- 942ec385-14c4-436d-82bf-254a62c4a81d
- true
- Length
- Length
- false
- 0
-
11289
28572
71
20
-
11324.5
28582
- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- c507fc36-6518-440d-8b39-378189e13d72
- true
- Normalized
- Normalized
- false
- 0
-
11289
28592
71
20
-
11324.5
28602
- 1
- 1
- {0}
- true
- Point at the specified length
- 228ba4c9-f335-40d7-830a-930ba0b8f370
- true
- Point
- Point
- false
- 0
-
11384
28552
50
20
-
11409
28562
- Tangent vector at the specified length
- d66d6972-1966-4d7c-9727-8ccdb137e40d
- true
- Tangent
- Tangent
- false
- 0
-
11384
28572
50
20
-
11409
28582
- Curve parameter at the specified length
- ac5a3688-b5cc-4a0b-9013-606a50e82bfa
- true
- Parameter
- Parameter
- false
- 0
-
11384
28592
50
20
-
11409
28602
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
- true
- e22a8212-4fbe-44d1-8960-60bce1b0633f
- true
- PolyLine
- PolyLine
-
11590
28357
116
44
-
11654
28379
- 1
- Polyline vertex points
- 1946d427-26c0-48d0-917c-d955ea38c046
- true
- Vertices
- Vertices
- false
- ba092d75-6ec4-47d7-beb9-6b24514697d2
- 1
-
11592
28359
50
20
-
11617
28369
- Close polyline
- 44054ace-1398-46bc-9f17-4f9d8eeb27bd
- true
- Closed
- Closed
- false
- 0
-
11592
28379
50
20
-
11617
28389
- 1
- 1
- {0}
- true
- Resulting polyline
- 05892abf-8ecd-4e8f-8e64-1a63af85f8a0
- true
- Polyline
- Polyline
- false
- 0
-
11666
28359
38
40
-
11685
28379
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
- 02c8e8c3-a797-4e87-96c5-9928bebed6f3
- true
- Merge
- Merge
-
11455
28305
90
84
-
11500
28347
- 4
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2
- Data stream 1
- 60f109f9-2c6a-4f93-bf8b-8fb1a84cd617
- true
- false
- Data 1
- D1
- true
- 228ba4c9-f335-40d7-830a-930ba0b8f370
- 1
-
11457
28307
31
20
-
11472.5
28317
- 2
- Data stream 2
- 372d7189-edd9-4199-bcd3-a3c8ea2484c4
- true
- false
- Data 2
- D2
- true
- d862f42d-b7d5-4961-8f17-2c24fd595947
- 1
-
11457
28327
31
20
-
11472.5
28337
- 2
- Data stream 3
- 74aa7d1d-4920-4190-a60a-f45e0bd11a4b
- true
- false
- Data 3
- D3
- true
- ac15329e-7811-4638-9e02-958d44a78172
- 1
-
11457
28347
31
20
-
11472.5
28357
- 2
- Data stream 4
- 16d89d23-f403-40cf-869a-c47a5a6016e9
- true
- false
- Data 4
- D4
- true
- 0
-
11457
28367
31
20
-
11472.5
28377
- 2
- Result of merge
- ba092d75-6ec4-47d7-beb9-6b24514697d2
- true
- Result
- Result
- false
- 0
-
11512
28307
31
80
-
11527.5
28347
- 61d81100-c4d3-462d-8b51-d951c0ae32db
- Triangle Mapping
- Transform geometry from one triangle into another.
- true
- dc21fb8d-0ffb-45b1-aa92-8716354d0746
- true
- Triangle Mapping
- Triangle Mapping
-
11645
28236
126
64
-
11707
28268
- Base geometry
- 2746e58e-6745-45e5-bab3-d884e451357f
- true
- Geometry
- Geometry
- true
- bc6ee7cc-dfce-484f-b2eb-2a5a4d0007c8
- 1
-
11647
28238
48
20
-
11671
28248
- Triangle to map from
- e74900ea-b0f1-4464-9528-06aa310a52a1
- true
- Source
- Source
- false
- 313dc56d-5db5-4cb0-88da-248d848cf9d0
- 1
-
11647
28258
48
20
-
11671
28268
- Triangle to map into
- 909b36f8-16c1-4204-b306-99fd4cd11f04
- true
- Target
- Target
- false
- 05892abf-8ecd-4e8f-8e64-1a63af85f8a0
- 1
-
11647
28278
48
20
-
11671
28288
- Mapped geometry
- 311286dc-fe96-40a7-815b-24a54f71dd3c
- true
- Geometry
- Geometry
- false
- 0
-
11719
28238
50
30
-
11744
28253
- Transformation data
- e745e45c-567e-4db7-8ebc-2f3073131b2f
- true
- Transform
- Transform
- false
- 0
-
11719
28268
50
30
-
11744
28283
- c9785b8e-2f30-4f90-8ee3-cca710f82402
- Entwine
- Flatten and combine a collection of data streams
- false
- true
- 779daf5b-bb9f-4b0f-8250-d59d858f4457
- true
- Entwine
- Entwine
-
11461
28143
85
64
-
11501
28175
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2
- Data to entwine
- d3f7a5c9-5e8b-471c-8ae6-8a3fb0d3b7f8
- true
- false
- Branch {0;x}
- {0;x}
- true
- d2a443aa-c60e-47a5-abed-2e2835b68a16
- 1
-
11463
28145
26
20
-
11476
28155
- 2
- Data to entwine
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26
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11476
28175
- 2
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11463
28185
26
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11476
28195
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11513
28145
31
60
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11528.5
28175
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28066
85
44
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11657
28088
- 2
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11619
28068
26
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11632
28078
- 2
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11619
28088
26
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11632
28098
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11669
28068
31
40
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11684.5
28088
- b7798b74-037e-4f0c-8ac7-dc1043d093e0
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11532
28763
226
81
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11694
28804
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11534
28765
148
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11616
28775
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28785
148
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11616
28795
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28805
148
37
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11616
28823.5
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0
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11706
28765
50
38
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11731
28784.25
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11706
28803
50
39
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11731
28822.75
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28551
103
28
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10470
28565
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10414
28553
44
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10436
28565
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28553
31
24
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10497.5
28565
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28887
172
61
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11085
28918
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123
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28899
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10950
28909
123
37
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11011.5
28927.5
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11097
28889
21
28
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11107.5
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11097
28917
21
29
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11107.5
28931.75
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28796
77
84
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11053
28838
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11020
28798
21
80
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11030.5
28838
- Box plane
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11065
28798
28
20
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11079
28808
- {x} dimension of box
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11065
28818
28
20
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11079
28828
- {y} dimension of box
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11065
28838
28
20
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11079
28848
- {z} dimension of box
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11065
28858
28
20
-
11079
28868
- 290f418a-65ee-406a-a9d0-35699815b512
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- Scale an object with non-uniform factors.
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28896
210
121
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11388
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11244
28898
132
20
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11310
28908
- Base plane
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11244
28918
132
37
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11310
28936.5
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11244
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132
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11310
28965
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11244
28975
132
20
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11310
28985
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11244
28995
132
20
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11310
29005
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28898
50
58
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11425
28927.25
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11400
28956
50
59
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11425
28985.75
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28796
108
44
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- Base domain
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38
40
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- Start of domain
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11205
28798
42
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11218
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11205
28818
42
20
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11218
28828
- a0d62394-a118-422d-abb3-6af115c75b25
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28801
70
44
-
11302
28823
- 2
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11279
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11
20
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11284.5
28813
- Second item for addition
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11279
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11
20
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11314
28803
31
40
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- 9c85271f-89fa-4e9f-9f4a-d75802120ccc
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28760
70
44
-
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- Item to divide (dividend)
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11
20
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- Item to divide with (divisor)
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11379
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11
20
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11384.5
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-
11414
28762
31
40
-
11429.5
28782
- b7798b74-037e-4f0c-8ac7-dc1043d093e0
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-
11532
28945
226
81
-
11694
28986
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-
11534
28947
148
20
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11616
28957
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11534
28967
148
20
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11616
28977
- 1
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11534
28987
148
37
-
11616
29005.5
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0
0
0
0
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0
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0
1
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11706
28947
50
38
-
11731
28966.25
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-
11706
28985
50
39
-
11731
29004.75
- b7798b74-037e-4f0c-8ac7-dc1043d093e0
- Rotate
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-
11538
29048
226
81
-
11700
29089
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- 1
-
11540
29050
148
20
-
11622
29060
- Rotation angle in degrees
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-
11540
29070
148
20
-
11622
29080
- 1
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11540
29090
148
37
-
11622
29108.5
- 1
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0
0
0
1
0
0
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1
0
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-
11712
29050
50
38
-
11737
29069.25
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-
11712
29088
50
39
-
11737
29107.75
- c9785b8e-2f30-4f90-8ee3-cca710f82402
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11860
28142
85
44
-
11900
28164
- 2
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11862
28144
26
20
-
11875
28154
- 2
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- 311286dc-fe96-40a7-815b-24a54f71dd3c
- 1
-
11862
28164
26
20
-
11875
28174
- Entwined result
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- 0
-
11912
28144
31
40
-
11927.5
28164
- c9785b8e-2f30-4f90-8ee3-cca710f82402
- Entwine
- Flatten and combine a collection of data streams
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- true
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-
11862
28822
85
64
-
11902
28854
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
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11864
28824
26
20
-
11877
28834
- 2
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- 1
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11864
28844
26
20
-
11877
28854
- 2
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- 1
-
11864
28864
26
20
-
11877
28874
- Entwined result
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- 0
-
11914
28824
31
60
-
11929.5
28854
- c9785b8e-2f30-4f90-8ee3-cca710f82402
- Entwine
- Flatten and combine a collection of data streams
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-
11990
28180
100
64
-
12045
28212
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- 1
-
11992
28182
41
20
-
12012.5
28192
- 2
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-
11992
28202
41
20
-
12012.5
28212
- 2
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11992
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- true
- Merge
- Merge
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29087
90
64
-
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29119
- 3
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- Data stream 1
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- Data 1
- D1
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12400
29089
31
20
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12415.5
29099
- 2
- Data stream 2
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- Data 2
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12400
29109
31
20
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12415.5
29119
- 2
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- Data 3
- D3
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12400
29129
31
20
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12415.5
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-
12455
29089
31
60
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12470.5
29119
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- Create a polar array of geometry.
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- ba33b008-e040-47d1-8e6f-3b360b5bf43c
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- Polar Array
- Polar Array
-
12517
28994
207
84
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12644
29036
- Base geometry
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12519
28996
113
20
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12575.5
29006
- Polar array plane
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12519
29016
113
20
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12575.5
29026
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0
0
0
1
0
0
0
1
0
- Number of elements in array.
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- 0
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12519
29036
113
20
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12575.5
29046
- 1
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- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
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12519
29056
113
20
-
12575.5
29066
- 1
- 1
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- 6.2831853071795862
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- Arrayed geometry
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12656
28996
66
40
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12681
29016
- 1
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-
12656
29036
66
40
-
12681
29056
- 8073a420-6bec-49e3-9b18-367f6fd76ac3
- Join Curves
- Join as many curves as possible
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- Join Curves
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12564
28877
116
44
-
12631
28899
- 1
- Curves to join
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-
12566
28879
53
20
-
12592.5
28889
- Preserve direction of input curves
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- Preserve
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- 0
-
12566
28899
53
20
-
12592.5
28909
- 1
- 1
- {0}
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- 1
- Joined curves and individual curves that could not be joined.
- b1b2d77d-acac-4f93-9d49-1df12c7f025d
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- Curves
- Curves
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- 0
-
12643
28879
35
40
-
12660.5
28899
- 59daf374-bc21-4a5e-8282-5504fb7ae9ae
- List Item
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- Retrieve a specific item from a list.
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- 60b468ed-f005-442a-98a1-2f5f06f6910c
- true
- List Item
- List Item
-
12296
29265
77
64
-
12353
29297
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- 1
- Base list
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- List
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- 1
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12298
29267
43
20
-
12319.5
29277
- Item index
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- Index
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- 0
-
12298
29287
43
20
-
12319.5
29297
- 1
- 1
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- 1
- Wrap index to list bounds
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- Wrap
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- 0
-
12298
29307
43
20
-
12319.5
29317
- 1
- 1
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- true
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- Item
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- 0
-
12365
29267
6
60
-
12368
29297
- b7798b74-037e-4f0c-8ac7-dc1043d093e0
- Rotate
- Rotate an object in a plane.
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- 345e50d9-106f-48b0-8a5f-82619b7a42d8
- true
- Rotate
- Rotate
-
12430
29302
170
64
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12536
29334
- Base geometry
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- Geometry
- Geometry
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- 3914ac59-33d9-41bd-9611-37164936a031
- 1
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12432
29304
92
20
-
12486
29314
- Rotation angle in degrees
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- 0
- true
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12432
29324
92
20
-
12486
29334
- 1
- 1
- {0}
- 120
- Rotation plane
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- 8466f10c-3993-400e-8742-e7e3f179651f
- 1
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12432
29344
92
20
-
12486
29354
- 1
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-
0
0
0
1
0
0
0
1
0
- Rotated geometry
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- Geometry
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- 0
-
12548
29304
50
30
-
12573
29319
- Transformation data
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- Transform
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- 0
-
12548
29334
50
30
-
12573
29349
- 75164624-395a-4d24-b60b-6bf91cab0194
- Sweep2
- Create a sweep surface with two rail curves.
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- 2b841695-b801-4232-8cec-df1e95b3ffb0
- true
- Sweep2
- Sweep2
-
12832
28841
125
84
-
12918
28883
- First rail curve
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- Rail 1
- Rail 1
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- 5ef63ff9-6730-42b3-b53c-8762ec52dae5
- 1
-
12834
28843
72
20
-
12870
28853
- Second rail curve
- 77951b5e-c755-4586-93e1-b5073c2e9e8e
- true
- Rail 2
- Rail 2
- false
- 25b86b00-4b1e-44df-819e-b87ac8d0f104
- 1
-
12834
28863
72
20
-
12870
28873
- 1
- Section curves
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- Sections
- Sections
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- 3b6ac9ce-f66a-47f3-8b74-010a93404a3e
- 1
-
12834
28883
72
20
-
12870
28893
- Create a sweep with same-height properties.
- 1e488029-c63b-4aef-bc34-8917303e40cc
- true
- Same Height
- Same Height
- false
- 0
-
12834
28903
72
20
-
12870
28913
- 1
- 1
- {0}
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- 1
- Resulting Brep
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- Brep
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- 0
-
12930
28843
25
80
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12942.5
28883
- 59daf374-bc21-4a5e-8282-5504fb7ae9ae
- List Item
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- Retrieve a specific item from a list.
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- ed0799d7-3bc0-4ce1-9e3e-b4eafc3d5546
- true
- List Item
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12432
29448
77
64
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12489
29480
- 3
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- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- Base list
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- 1
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12434
29450
43
20
-
12455.5
29460
- Item index
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- Index
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- 0
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12434
29470
43
20
-
12455.5
29480
- 1
- 1
- {0}
- 12
- Wrap index to list bounds
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- 0
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12434
29490
43
20
-
12455.5
29500
- 1
- 1
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- 0
-
12501
29450
6
60
-
12504
29480
- b7798b74-037e-4f0c-8ac7-dc1043d093e0
- Rotate
- Rotate an object in a plane.
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- true
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- Rotate
-
12654
29337
226
81
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12816
29378
- Base geometry
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12656
29339
148
20
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12738
29349
- Rotation angle in degrees
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- 0
- true
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12656
29359
148
20
-
12738
29369
- 1
- 1
- {0}
- -90
- Rotation plane
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12656
29379
148
37
-
12738
29397.5
- 1
- 1
- {0}
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0
0
0
1
0
0
0
1
0
- Rotated geometry
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- 0
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12828
29339
50
38
-
12853
29358.25
- Transformation data
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- 0
-
12828
29377
50
39
-
12853
29396.75
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
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- true
- Merge
- Merge
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12642
29187
90
64
-
12687
29219
- 3
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- Data stream 1
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- Data 1
- D1
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- 3914ac59-33d9-41bd-9611-37164936a031
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12644
29189
31
20
-
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29199
- 2
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- Data 2
- D2
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12644
29209
31
20
-
12659.5
29219
- 2
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- Data 3
- D3
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- 0
-
12644
29229
31
20
-
12659.5
29239
- 2
- Result of merge
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-
12699
29189
31
60
-
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29219
- 22990b1f-9be6-477c-ad89-f775cd347105
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- Flip a curve using an optional guide curve.
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- Flip Curve
- Flip Curve
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29089
88
44
-
12750
29111
- Curve to flip
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- Curve
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- 1
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12708
29091
30
20
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12723
29101
- Optional guide curve
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-
12708
29111
30
20
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12723
29121
- Flipped curve
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- 0
-
12762
29091
30
20
-
12777
29101
- Flip action
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- Flag
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- 0
-
12762
29111
30
20
-
12777
29121
- 22990b1f-9be6-477c-ad89-f775cd347105
- Flip Curve
- Flip a curve using an optional guide curve.
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- Flip Curve
- Flip Curve
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29366
88
44
-
12973
29388
- Curve to flip
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- 1
-
12931
29368
30
20
-
12946
29378
- Optional guide curve
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-
12931
29388
30
20
-
12946
29398
- Flipped curve
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- Curve
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- 0
-
12985
29368
30
20
-
13000
29378
- Flip action
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- Flag
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-
12985
29388
30
20
-
13000
29398
- 59daf374-bc21-4a5e-8282-5504fb7ae9ae
- List Item
- 0
- Retrieve a specific item from a list.
- true
- 9935447c-3f80-44d3-8052-01fa076971e7
- true
- List Item
- List Item
-
12388
28539
77
64
-
12445
28571
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- 1
- Base list
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- List
- List
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- 1
-
12390
28541
43
20
-
12411.5
28551
- Item index
- 005f07a2-8048-404f-883d-5a342c3566e4
- true
- Index
- Index
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- 0
-
12390
28561
43
20
-
12411.5
28571
- 1
- 1
- {0}
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- Wrap index to list bounds
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- Wrap
- Wrap
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-
12390
28581
43
20
-
12411.5
28591
- 1
- 1
- {0}
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- Item
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- 0
-
12457
28541
6
60
-
12460
28571
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
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-
255;255;255;255
- A group of Grasshopper objects
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- Group
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- Get the point in the middle of a curve
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- true
- Curve Middle
- Curve Middle
-
13532
28584
101
28
-
13576
28598
- Curve for mid-point.
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- ff4b1356-82ea-4cf7-9d66-2ed9f409faef
- 1
-
13534
28586
30
24
-
13549
28598
- Point in the middle of the curve
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- Midpoint
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- 0
-
13588
28586
43
24
-
13609.5
28598
- fbac3e32-f100-4292-8692-77240a42fd1a
- Point
- Contains a collection of three-dimensional points
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- Point
- Point
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-
12962
28645
99
24
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13049.63
28657.84
- 1
- 1
- {0}
-
0
0
0
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
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- A wire relay object
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-
11664
28622
40
16
-
11684
28630
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
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- Polar Array
- Polar Array
-
12931
28944
207
84
-
13058
28986
- Base geometry
- fcd5c8ad-c3be-4e0f-aa7b-6a718f026e43
- true
- Geometry
- Geometry
- true
- 0490c4ad-b715-43e9-85d4-2fa26a0f17a7
- 1
-
12933
28946
113
20
-
12989.5
28956
- Polar array plane
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- Plane
- Plane
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- 8466f10c-3993-400e-8742-e7e3f179651f
- 1
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12933
28966
113
20
-
12989.5
28976
- 1
- 1
- {0}
-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
- 17c2c2bb-1438-410d-9450-05653a3d6610
- true
- Count
- Count
- false
- 0
-
12933
28986
113
20
-
12989.5
28996
- 1
- 1
- {0}
- 3
- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- cd9bc5d0-c344-4716-a064-eecf171207ef
- true
- Angle
- Angle
- false
- 0
- false
-
12933
29006
113
20
-
12989.5
29016
- 1
- 1
- {0}
- 6.2831853071795862
- 1
- Arrayed geometry
- 8417b745-f41f-4d9e-8bbb-9e5377f43932
- true
- 1
- Geometry
- Geometry
- false
- 0
-
13070
28946
66
40
-
13095
28966
- 1
- Transformation data
- 9beef5c1-f0e3-4213-8b40-a8de215f7c5b
- true
- Transform
- Transform
- false
- 0
-
13070
28986
66
40
-
13095
29006
- 75164624-395a-4d24-b60b-6bf91cab0194
- Sweep2
- Create a sweep surface with two rail curves.
- true
- 1df9d5e6-0ba1-4a1d-98c6-385bff3e9a5d
- true
- Sweep2
- Sweep2
-
12900
29204
125
84
-
12986
29246
- First rail curve
- b18cea78-d396-434a-b057-a5994b6649ae
- true
- Rail 1
- Rail 1
- false
- 788c609b-314a-42fc-9ea6-dd50e84c46d0
- 1
-
12902
29206
72
20
-
12938
29216
- Second rail curve
- 33b8c586-75e6-4631-828e-efad1f382d6b
- true
- Rail 2
- Rail 2
- false
- a9ba64db-3550-4932-9fee-3e0b1c0f003b
- 1
-
12902
29226
72
20
-
12938
29236
- 1
- Section curves
- 983cc157-3d94-43a5-9ddf-15500de2ac90
- true
- Sections
- Sections
- false
- 3914ac59-33d9-41bd-9611-37164936a031
- 1
-
12902
29246
72
20
-
12938
29256
- Create a sweep with same-height properties.
- 4f12b42c-ec4a-489b-887b-9f59ee1a5034
- true
- Same Height
- Same Height
- false
- 0
-
12902
29266
72
20
-
12938
29276
- 1
- 1
- {0}
- true
- 1
- Resulting Brep
- 3ae18dd7-3009-43a7-983b-2c350bfef07c
- true
- Brep
- Brep
- false
- 0
-
12998
29206
25
80
-
13010.5
29246
- 59daf374-bc21-4a5e-8282-5504fb7ae9ae
- List Item
- 0
- Retrieve a specific item from a list.
- true
- f9e9b3d3-0249-4fcd-9010-bda7192c49ec
- true
- List Item
- List Item
-
12550
29091
77
64
-
12607
29123
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- cb95db89-6165-43b6-9c41-5702bc5bf137
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- Base list
- e3fa9389-8bb9-4073-bc9a-8fe79cbc3dc9
- true
- List
- List
- false
- c7759ede-6017-4b39-8cfd-985e47669aa1
- 1
-
12552
29093
43
20
-
12573.5
29103
- Item index
- 1f0c42fb-a12e-4e1e-a081-0ae5918b3e34
- true
- Index
- Index
- false
- 0
-
12552
29113
43
20
-
12573.5
29123
- 1
- 1
- {0}
- 6
- Wrap index to list bounds
- e30de5c8-e07a-4549-97aa-1294a3f1ea5c
- true
- Wrap
- Wrap
- false
- 0
-
12552
29133
43
20
-
12573.5
29143
- 1
- 1
- {0}
- false
- Item at {i'}
- a9ba64db-3550-4932-9fee-3e0b1c0f003b
- true
- false
- Item
- i
- false
- 0
-
12619
29093
6
60
-
12622
29123
- f12daa2f-4fd5-48c1-8ac3-5dea476912ca
- Mirror
- Mirror an object.
- true
- 4b52ff38-2edb-42fc-ad3c-aad65645bfbf
- true
- Mirror
- Mirror
-
13151
29172
305
61
-
13392
29203
- Base geometry
- 505f36ba-5d42-4711-bb2f-12412b8d9067
- true
- Geometry
- Geometry
- true
- 3ae18dd7-3009-43a7-983b-2c350bfef07c
- 1
-
13153
29174
227
20
-
13266.5
29184
- Mirror plane
- f2f9db89-552e-445e-8378-f2fc9f019f55
- true
- Plane
- Plane
- false
- 0
-
13153
29194
227
37
-
13266.5
29212.5
- 1
- 1
- {0}
-
0
0
0
0
1
0
-0.707106781186548
0
0.707106781186547
- Mirrored geometry
- 9e81018f-eb0e-422b-8b03-5fa6f29962ba
- true
- Geometry
- Geometry
- false
- 0
-
13404
29174
50
28
-
13429
29188.25
- Transformation data
- 9cd75d03-875f-4f14-a38a-33fee0ebdc03
- true
- Transform
- Transform
- false
- 0
-
13404
29202
50
29
-
13429
29216.75
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- 2aa02528-07ad-4eb2-a14e-23480eb36571
- true
- Polar Array
- Polar Array
-
13242
29285
207
84
-
13369
29327
- Base geometry
- c7101f1b-5f11-4b5a-8ce4-aca0d3add6ab
- true
- Geometry
- Geometry
- true
- 060648e6-d9c2-477c-ba2f-71b14f63a036
- 1
-
13244
29287
113
20
-
13300.5
29297
- Polar array plane
- a8471fed-2546-4fb0-93a9-d9cebc0b92ea
- true
- Plane
- Plane
- false
- 8466f10c-3993-400e-8742-e7e3f179651f
- 1
-
13244
29307
113
20
-
13300.5
29317
- 1
- 1
- {0}
-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
- 0e17a2e0-16f2-4382-82e4-704ea4d7c239
- true
- Count
- Count
- false
- 0
-
13244
29327
113
20
-
13300.5
29337
- 1
- 1
- {0}
- 3
- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- 5bc28fd2-567f-42d5-976a-afe024f38684
- true
- Angle
- Angle
- false
- 0
- false
-
13244
29347
113
20
-
13300.5
29357
- 1
- 1
- {0}
- 6.2831853071795862
- 1
- Arrayed geometry
- b3e9652a-0589-4dbf-b8e1-243721b1bfc1
- true
- 1
- Geometry
- Geometry
- false
- 0
-
13381
29287
66
40
-
13406
29307
- 1
- Transformation data
- bbc36e0c-38f8-4c59-8ccd-b9ec863cf0e6
- true
- Transform
- Transform
- false
- 0
-
13381
29327
66
40
-
13406
29347
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
- a1881539-51c5-48a1-b579-c1eeb39cdbdd
- true
- Merge
- Merge
-
13233
29068
90
64
-
13278
29100
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2
- Data stream 1
- 38b8585d-bfe9-4a59-be1f-6f310459249a
- true
- false
- Data 1
- D1
- true
- 3ae18dd7-3009-43a7-983b-2c350bfef07c
- 1
-
13235
29070
31
20
-
13250.5
29080
- 2
- Data stream 2
- 6b0e7e6c-52be-48fb-934b-f4c80cd0c3fe
- true
- false
- Data 2
- D2
- true
- 9e81018f-eb0e-422b-8b03-5fa6f29962ba
- 1
-
13235
29090
31
20
-
13250.5
29100
- 2
- Data stream 3
- 264bee91-6031-4c1f-aae1-ef024f5be16e
- true
- false
- Data 3
- D3
- true
- 0
-
13235
29110
31
20
-
13250.5
29120
- 2
- Result of merge
- 060648e6-d9c2-477c-ba2f-71b14f63a036
- true
- Result
- Result
- false
- 0
-
13290
29070
31
60
-
13305.5
29100
- 57b2184c-8931-4e70-9220-612ec5b3809a
- Patch
- Create a patch surface
- true
- 896526e7-4b6f-49d0-9eba-8afd5bc1f034
- true
- Patch
- Patch
-
13037
28801
119
104
-
13113
28853
- 1
- Curves to patch
- 57e2c7ab-acb9-4ad3-98b6-2608f40034d6
- true
- Curves
- Curves
- true
- b1b2d77d-acac-4f93-9d49-1df12c7f025d
- 1
-
13039
28803
62
20
-
13070
28813
- 1
- Points to patch
- 63afc207-44e8-434b-a8b5-07bc63a085f4
- true
- Points
- Points
- true
- 5cacee03-857e-4f27-8db3-fad6acaee1f8
- 1
-
13039
28823
62
20
-
13070
28833
- Number of spans
- 94205002-ff33-4d56-aa50-8c9de91b06d7
- true
- Spans
- Spans
- false
- 0
-
13039
28843
62
20
-
13070
28853
- 1
- 1
- {0}
- 16
- Patch flexibility (low number; less flexibility)
- fc501350-14e6-48eb-a9a6-29dedcd983f8
- true
- Flexibility
- Flexibility
- false
- 0
-
13039
28863
62
20
-
13070
28873
- 1
- 1
- {0}
- 8
- Attempt to trim the result
- 5159e24d-fc93-4859-a5c5-506c1538b080
- true
- Trim
- Trim
- false
- 0
-
13039
28883
62
20
-
13070
28893
- 1
- 1
- {0}
- true
- Patch result
- d636886e-6a7c-4eda-b4a4-ca364081a1e2
- true
- Patch
- Patch
- false
- 0
-
13125
28803
29
100
-
13139.5
28853
- f31d8d7a-7536-4ac8-9c96-fde6ecda4d0a
- Curvature analysis
- Analyzes surface curvature
-
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- SEEDstudio | www.studioseed.net
- dga_3@hotmail.com
- Daniel Abalde
- www.studioseed.net
- 5
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- Base surface, brep, mesh or curve
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13169
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91
20
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13214.5
28960
- Number of divisions in UV directions
Note * Only subdivided surfaces, breps, and curves
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Note * For surfaces and breps
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30
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30
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13308
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- Extract the nurbs control polygon of a curve.
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- Curve to evaluate
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40
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44
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- Base Brep
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40
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13310
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- 3581f42a-9592-4549-bd6b-1c0fc39d067b
- Construct Point
- Construct a point from {xyz} coordinates.
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- Construct Point
- Construct Point
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- {x} coordinate
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- X coordinate
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62
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- {y} coordinate
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- Y coordinate
- Y coordinate
- false
- 6abad9f4-df4e-4bc9-a13a-fc424fe4c40a
- 1
-
13099
28722
62
20
-
13130
28732
- 1
- 1
- {0}
- 0
- {z} coordinate
- 17551570-925d-489c-8f4a-c7e1fe2c3dbb
- true
- Z coordinate
- Z coordinate
- false
- 6abad9f4-df4e-4bc9-a13a-fc424fe4c40a
- 1
-
13099
28742
62
20
-
13130
28752
- 1
- 1
- {0}
- 0
- Point coordinate
- 51179561-239d-4312-82e0-f4e7f66516de
- true
- Point
- Point
- false
- 0
-
13185
28702
27
60
-
13198.5
28732
- 9445ca40-cc73-4861-a455-146308676855
- Range
- Create a range of numbers.
- true
- c9a8dc4b-abf3-4367-b392-ec2e73e5858f
- true
- Range
- Range
-
13104
28634
144
44
-
13202
28656
- Domain of numeric range
- b84b7aad-7c57-4840-9ae9-d3962839170d
- true
- Domain
- Domain
- false
- 0
-
13106
28636
84
20
-
13148
28646
- 1
- 1
- {0}
-
0
1
- Number of steps
- aaafd565-907f-48bc-9256-389f9fbad5aa
- true
- Steps
- Steps
- false
- 0
-
13106
28656
84
20
-
13148
28666
- 1
- 1
- {0}
- 6
- 1
- Range of numbers
- 6abad9f4-df4e-4bc9-a13a-fc424fe4c40a
- true
- Range
- Range
- false
- 0
-
13214
28636
32
40
-
13230
28656
- 59daf374-bc21-4a5e-8282-5504fb7ae9ae
- List Item
- 0
- Retrieve a specific item from a list.
- true
- 450ec7d6-6e26-4b9a-970b-d0cbf1772eec
- true
- List Item
- List Item
-
12225
28782
77
64
-
12282
28814
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- cb95db89-6165-43b6-9c41-5702bc5bf137
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- Base list
- c4d83e97-6acf-4921-9e15-25465eddb845
- true
- List
- List
- false
- c7759ede-6017-4b39-8cfd-985e47669aa1
- 1
-
12227
28784
43
20
-
12248.5
28794
- Item index
- 3c027a27-2646-4367-9902-c20adeb5f6af
- true
- Index
- Index
- false
- 0
-
12227
28804
43
20
-
12248.5
28814
- 1
- 1
- {0}
- 0
- Wrap index to list bounds
- 58f4d409-cc2a-44ed-849a-d0442067a074
- true
- Wrap
- Wrap
- false
- 0
-
12227
28824
43
20
-
12248.5
28834
- 1
- 1
- {0}
- false
- Item at {i'}
- 04070efd-05f8-4658-8331-40f0368aa8fa
- true
- false
- Item
- i
- false
- 0
-
12294
28784
6
60
-
12297
28814
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 15462838-16ed-45b2-ae57-bf3140d2a0c4
- true
- Evaluate Length
- Evaluate Length
-
12369
28694
149
64
-
12454
28726
- Curve to evaluate
- 765a521b-aa26-4ea8-bd44-2d1ac48c4a29
- true
- Curve
- Curve
- false
- 04070efd-05f8-4658-8331-40f0368aa8fa
- 1
-
12371
28696
71
20
-
12406.5
28706
- Length factor for curve evaluation
- 89441ced-3308-4968-9a08-ca77e5fff5ca
- true
- Length
- Length
- false
- 0
-
12371
28716
71
20
-
12406.5
28726
- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 554ae01c-34f4-406a-9d3f-a64da5656529
- true
- Normalized
- Normalized
- false
- 0
-
12371
28736
71
20
-
12406.5
28746
- 1
- 1
- {0}
- true
- Point at the specified length
- f37cb892-e085-4d02-b622-0cf629b13abf
- true
- Point
- Point
- false
- 0
-
12466
28696
50
20
-
12491
28706
- Tangent vector at the specified length
- ccaef106-f7ec-4a61-955b-726eba10cb0f
- true
- Tangent
- Tangent
- false
- 0
-
12466
28716
50
20
-
12491
28726
- Curve parameter at the specified length
- 4158be2d-5059-4c52-9111-20bb07143d0e
- true
- Parameter
- Parameter
- false
- 0
-
12466
28736
50
20
-
12491
28746
- 269eaa85-9997-4d77-a9ba-4c58cb45c9d3
- Discontinuity
- Find all discontinuities along a curve.
- true
- 787bc2e4-45a8-4f65-ba4a-1370065d5bd7
- true
- Discontinuity
- Discontinuity
-
12493
28770
196
44
-
12620
28792
- Curve to analyze
- c620e97d-b1df-43da-84e2-a8167399f250
- true
- Curve
- Curve
- false
- b1b2d77d-acac-4f93-9d49-1df12c7f025d
- 1
-
12495
28772
113
20
-
12551.5
28782
- Level of discontinuity to test for (1=C1, 2=C2, 3=Cinfinite)
- 0ba9154e-97dd-41b5-8079-8af2e09ec5d7
- true
- Level
- Level
- false
- 0
-
12495
28792
113
20
-
12551.5
28802
- 1
- 1
- {0}
- 1
- 1
- Points at discontinuities
- df6e61e1-1184-4a91-97bf-62962510ac96
- true
- Points
- Points
- false
- 0
-
12632
28772
55
20
-
12659.5
28782
- 1
- Curve parameters at discontinuities
- c974fe53-cc46-49c9-963d-cc9c7e724e14
- true
- Parameters
- Parameters
- false
- 0
-
12632
28792
55
20
-
12659.5
28802
- 59daf374-bc21-4a5e-8282-5504fb7ae9ae
- List Item
- 0
- Retrieve a specific item from a list.
- true
- 413dab6f-30ff-4b34-9f67-90b9f0ff1ee3
- true
- List Item
- List Item
-
12603
28693
77
64
-
12660
28725
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- cb95db89-6165-43b6-9c41-5702bc5bf137
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- Base list
- b430cc72-3de3-4425-bb1c-86715c095b3c
- true
- List
- List
- false
- df6e61e1-1184-4a91-97bf-62962510ac96
- 1
-
12605
28695
43
20
-
12626.5
28705
- Item index
- 4a487015-cb96-43bd-9f37-765100234d74
- true
- Index
- Index
- false
- 0
-
12605
28715
43
20
-
12626.5
28725
- 1
- 1
- {0}
- 4
- Wrap index to list bounds
- d8cac58f-189f-498d-8607-9f7a513a1b26
- true
- Wrap
- Wrap
- false
- 0
-
12605
28735
43
20
-
12626.5
28745
- 1
- 1
- {0}
- false
- Item at {i'}
- c0156a88-eddd-4204-a1a9-6d6859b95655
- true
- false
- Item
- i
- false
- 0
-
12672
28695
6
60
-
12675
28725
- 59daf374-bc21-4a5e-8282-5504fb7ae9ae
- List Item
- 0
- Retrieve a specific item from a list.
- true
- 2b4ed57e-fb00-43dc-8e5f-783398616385
- true
- List Item
- List Item
-
12596
28615
77
64
-
12653
28647
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- cb95db89-6165-43b6-9c41-5702bc5bf137
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- Base list
- 5f3a2d0d-f2d2-4ee0-8ed5-2c4dbae31185
- true
- List
- List
- false
- df6e61e1-1184-4a91-97bf-62962510ac96
- 1
-
12598
28617
43
20
-
12619.5
28627
- Item index
- dff5cd65-cb06-41b2-b199-a1946585a002
- true
- Index
- Index
- false
- 0
-
12598
28637
43
20
-
12619.5
28647
- 1
- 1
- {0}
- 1
- Wrap index to list bounds
- e7e6673d-186e-4a1a-9466-639bf1eeddd1
- true
- Wrap
- Wrap
- false
- 0
-
12598
28657
43
20
-
12619.5
28667
- 1
- 1
- {0}
- false
- Item at {i'}
- 330006fd-b3f1-44f3-8f7d-9b4cca70cab1
- true
- false
- Item
- i
- false
- 0
-
12665
28617
6
60
-
12668
28647
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
- 2ac16693-cfbb-413e-95aa-4f61e4c28f43
- true
- Merge
- Merge
-
12720
28613
106
84
-
12781
28655
- 4
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2
- Data stream 1
- 4aa7a97a-2fa1-43b2-971f-37891cd5c08c
- true
- 1
- false
- Data 1
- D1
- true
- 330006fd-b3f1-44f3-8f7d-9b4cca70cab1
- 1
-
12722
28615
47
20
-
12753.5
28625
- 2
- Data stream 2
- cf5915bf-66c0-4066-92ac-d3d1b8b959eb
- true
- 1
- false
- Data 2
- D2
- true
- f37cb892-e085-4d02-b622-0cf629b13abf
- 1
-
12722
28635
47
20
-
12753.5
28645
- 2
- Data stream 3
- 8e0e32cb-a4ba-4c66-b3e7-461cba5c8d0b
- true
- 1
- false
- Data 3
- D3
- true
- c0156a88-eddd-4204-a1a9-6d6859b95655
- 1
-
12722
28655
47
20
-
12753.5
28665
- 2
- Data stream 4
- 5703caee-1e91-455a-b652-9f6cfe30e0f8
- true
- false
- Data 4
- D4
- true
- 0
-
12722
28675
47
20
-
12753.5
28685
- 2
- Result of merge
- 7c15dd75-0fb5-4a70-8968-035294646203
- true
- Result
- Result
- false
- 0
-
12793
28615
31
80
-
12808.5
28655
- 75eb156d-d023-42f9-a85e-2f2456b8bcce
- Interpolate (t)
- Create an interpolated curve through a set of points with tangents.
- true
- 4f97cf3f-ae0c-4d3c-9f34-ce92704918f5
- true
- Interpolate (t)
- Interpolate (t)
-
12077
28567
244
84
-
12269
28609
- 1
- Interpolation points
- d554d29a-fd6e-4dd5-8e2b-3e23c028de73
- true
- Vertices
- Vertices
- false
- 7c15dd75-0fb5-4a70-8968-035294646203
- 1
-
12079
28569
178
20
-
12168
28579
- Tangent at start of curve
- dadee473-b312-46ba-8f68-cd9361f1f948
- true
- Tangent Start
- Tangent Start
- false
- 0
-
12079
28589
178
20
-
12168
28599
- 1
- 1
- {0}
-
0
1
0
- Tangent at end of curve
- 30e48b0d-5118-47d5-a050-92e2ccd4925f
- true
- Tangent End
- Tangent End
- false
- 0
-
12079
28609
178
20
-
12168
28619
- 1
- 1
- {0}
-
1
0
-1
- Knot spacing (0=uniform, 1=chord, 2=sqrtchord)
- cc4486c6-435b-494a-90b6-38e39bf80feb
- true
- KnotStyle
- KnotStyle
- false
- 0
-
12079
28629
178
20
-
12168
28639
- 1
- 1
- {0}
- 2
- Resulting nurbs curve
- 0ad4a801-5c37-4f86-b0c9-cfa2810fbeed
- true
- Curve
- Curve
- false
- 0
-
12281
28569
38
26
-
12300
28582.33
- Curve length
- f19d34d8-952c-4b7b-9d1c-7cff6f55186e
- true
- Length
- Length
- false
- 0
-
12281
28595
38
27
-
12300
28609
- Curve domain
- 03e24465-d0af-4b53-bf1d-8f60b8c8be45
- true
- Domain
- Domain
- false
- 0
-
12281
28622
38
27
-
12300
28635.67
- 14cf43b6-5eb9-460f-899c-bdece732213a
- Blend Curve Pt
- Create a blend curve between two curves that intersects a point.
- true
- 81c31b9d-d9f4-48ac-8b75-2e11cf294f83
- true
- Blend Curve Pt
- Blend Curve Pt
-
11740
27619
167
84
-
11864
27661
- First curve for blend
- a4c7118a-7572-41be-b304-670fa4f0336a
- true
- Curve A
- Curve A
- false
- 5a30bc9c-1f0b-4a38-8546-68bfff78fe07
- 1
-
11742
27621
110
20
-
11797
27631
- Second curve for blend
- b9be3c42-571a-4365-b65c-6eb712673f9e
- true
- Curve B
- Curve B
- false
- 781927c7-3272-460b-af8b-3107b52db860
- 1
-
11742
27641
110
20
-
11797
27651
- Point for blend intersection
- 56da942a-7d64-4a15-a453-bd453c33c962
- true
- Point
- Point
- false
- f37cb892-e085-4d02-b622-0cf629b13abf
- 1
-
11742
27661
110
20
-
11797
27671
- Continuity of blend (1=tangency, 2=curvature)
- c921ac17-e66d-495f-b864-733f670a6de1
- true
- Continuity
- Continuity
- false
- 0
-
11742
27681
110
20
-
11797
27691
- 1
- 1
- {0}
- 2
- Blend curve connecting the end of A to the start of B, ideally coincident with P
- e7179353-b7a9-4734-995e-1ac6997baecc
- true
- Blend
- Blend
- false
- 0
-
11876
27621
29
80
-
11890.5
27661
- 62cc9684-6a39-422e-aefa-ed44643557b9
- Extend Curve
- Extend a curve by a specified distance.
- true
- 78bea16c-c7ca-42a2-8f5a-2cbb175c6b39
- true
- Extend Curve
- Extend Curve
-
12152
28342
124
84
-
12232
28384
- Curve to extend
- cb01bec1-5994-48f1-bdcc-f6c296ef31f8
- true
- Curve
- Curve
- false
- 0ad4a801-5c37-4f86-b0c9-cfa2810fbeed
- 1
-
12154
28344
66
20
-
12187
28354
- Type of extension (0=Line, 1=Arc, 2=Smooth)
- cea346a1-d619-486a-907c-9d9c84e216d8
- true
- Type
- Type
- false
- 0
-
12154
28364
66
20
-
12187
28374
- 1
- 1
- {0}
- 0
- Extension length at start of curve
- 2cc7cbe5-f621-4395-9528-fb47068a8b5f
- true
- Start
- Start
- false
- 0
-
12154
28384
66
20
-
12187
28394
- 1
- 1
- {0}
- 0.0625
- Extension length at end of curve
- 3bcb9a0c-7d15-470d-b3db-f84b1b79ace3
- true
- End
- End
- false
- 0
-
12154
28404
66
20
-
12187
28414
- 1
- 1
- {0}
- 0.0625
- Extended curve
- b7ece470-8963-4e98-b9fc-c87e811ab6a6
- true
- Curve
- Curve
- false
- 0
-
12244
28344
30
80
-
12259
28384
- afb96615-c59a-45c9-9cac-e27acb1c7ca0
- Explode
- Explode a curve into smaller segments.
- true
- 8ffd48b3-48cf-434f-9acc-297e520858bf
- true
- Explode
- Explode
-
12131
28279
134
44
-
12202
28301
- Curve to explode
- d9fa462d-da4f-4ce6-92e7-51395c617b2d
- true
- Curve
- Curve
- false
- b7ece470-8963-4e98-b9fc-c87e811ab6a6
- 1
-
12133
28281
57
20
-
12161.5
28291
- Recursive decomposition until all segments are atomic
- 16058c48-486f-427a-802c-3b8a1a421834
- true
- Recursive
- Recursive
- false
- 0
-
12133
28301
57
20
-
12161.5
28311
- 1
- 1
- {0}
- true
- 1
- Exploded segments that make up the base curve
- b6507732-c5c5-43eb-bc89-4c7b87a994c4
- true
- Segments
- Segments
- false
- 0
-
12214
28281
49
20
-
12238.5
28291
- 1
- Vertices of the exploded segments
- b55cf522-ec7a-460d-b821-829569c85064
- true
- Vertices
- Vertices
- false
- 0
-
12214
28301
49
20
-
12238.5
28311
- 59daf374-bc21-4a5e-8282-5504fb7ae9ae
- List Item
- 0
- Retrieve a specific item from a list.
- true
- 8a512fa1-3acb-436d-b89c-8cb084c66169
- true
- List Item
- List Item
-
12147
28151
77
64
-
12204
28183
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- cb95db89-6165-43b6-9c41-5702bc5bf137
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- Base list
- eeb4e85f-0bf6-474e-88c8-cc8acc779e91
- true
- List
- List
- false
- b6507732-c5c5-43eb-bc89-4c7b87a994c4
- 1
-
12149
28153
43
20
-
12170.5
28163
- Item index
- 0eb903a7-7ee6-43b4-944b-4f4e6ad99965
- true
- Index
- Index
- false
- 0
-
12149
28173
43
20
-
12170.5
28183
- 1
- 1
- {0}
- 0
- Wrap index to list bounds
- 99da5bf6-85bd-4a71-abf4-b7e058ad3f67
- true
- Wrap
- Wrap
- false
- 0
-
12149
28193
43
20
-
12170.5
28203
- 1
- 1
- {0}
- true
- Item at {i'}
- 36f43267-27de-4174-8fa7-7181d7f6dbfa
- true
- false
- Item
- i
- false
- 0
-
12216
28153
6
60
-
12219
28183
- 59daf374-bc21-4a5e-8282-5504fb7ae9ae
- List Item
- 0
- Retrieve a specific item from a list.
- true
- 50b2e22f-d285-4505-b5fb-8235c2d94057
- true
- List Item
- List Item
-
12163
28216
77
64
-
12220
28248
- 3
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- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- Base list
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12165
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12186.5
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- Item index
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- Index
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12165
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12186.5
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- Wrap index to list bounds
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12165
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12186.5
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12232
28218
6
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12235
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- ae4835db-ae71-4361-8536-1a5e50386819
- 1c9de8a1-315f-4c56-af06-8f69fee80a7a
- Smooth Curve
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- true
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- true
- Smooth Curve
- Smooth Curve
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- Curve to smooth
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12037
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12116
28015
- Number of recursive smoothing steps
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12037
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158
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12116
28035
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- Determines how the start of the curve is preserved
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1 = Preserve first two points
2 = Preserve first three points
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12037
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12116
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0 = Preserve end point only
1 = Preserve last two points
2 = Preserve last three points
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158
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12116
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- 0
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12037
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12116
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- Tolerance angle in degrees for kink smoothing
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12037
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158
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12116
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- Resulting smoothed curve
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12219
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- Fit Curve Smooth
- Fit a new curve through an existing curve with kink angle smoothing, without changing the general shape.
- true
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- Fit Curve Smooth
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12216
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- Curve to fit
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12046
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158
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12125
27900
- Degree to fit the curve to (if omitted input curve degree is used)
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- Degree
- Degree
- true
- 0
-
12046
27910
158
20
-
12125
27920
- Tolerance distance the fit curve is allowed to deviate from the curve to fit (if omitted document tolerance is used)
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- Deviation Tolerance
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- 0
-
12046
27930
158
20
-
12125
27940
- 1
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- {0}
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- Tolerance angle in degrees for kink smoothing (if omitted document angle tolerance is used)
- b006e454-520f-4644-b3a5-7101f3f1e20e
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12046
27950
158
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12125
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- {0}
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- Resulting fitted curve
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12242.5
27930
- a3f9f19e-3e6c-4ac7-97c3-946de32c3e8e
- Fit Curve
- Fit a curve along another curve.
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- Fit Curve
- Fit Curve
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171
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12140
27839
- Curve to fit
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- 1
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12015
27809
113
20
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12071.5
27819
- Optional degree of curve (if omitted, input degree is used)
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- Degree
- Degree
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12015
27829
113
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12071.5
27839
- 1
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- Tolerance for fitting (if omitted, document tolerance is used)
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- Tolerance
- Tolerance
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12015
27849
113
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12071.5
27859
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- Fitted curve
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12152
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30
60
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12167
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- Rebuild PolyCurve
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
- Rebuild a curve preserving the kinks in the polycurves
- true
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- Rebuild PolyCurve
- Rebuild PolyCurve
- false
- dga_3@hotmail.com
- Daniel Abalde
- https://www.facebook.com/DanielAbaldeDesigner
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198
64
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12141
27733
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11989
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20
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12059
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- Factor that multiplies the length of each curve segment to determine the number of control points for that segment.
Control points for each segment = length of the segment * Division factor.
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140
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12059
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11989
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140
20
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12059
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- Resulting curve
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12153
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30
60
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- Digit Scroller
- Numeric scroller for single numbers
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-
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11918
28681
250
20
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11918.63
28681.84
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- Join Curves
- Join as many curves as possible
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- Join Curves
- Join Curves
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116
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11849
28037
- 1
- Curves to join
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28017
53
20
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11810.5
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- Preserve direction of input curves
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11784
28037
53
20
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11810.5
28047
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- Joined curves and individual curves that could not be joined.
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11861
28017
35
40
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11878.5
28037
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- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- ca78e54f-2c7c-4550-9fbf-85e4695e34e4
- true
- Evaluate Length
- Evaluate Length
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149
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- Curve to evaluate
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11693
27826
71
20
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11728.5
27836
- Length factor for curve evaluation
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- Length
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11693
27846
71
20
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11728.5
27856
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- If True, the Length factor is normalized (0.0 ~ 1.0)
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11693
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71
20
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11728.5
27876
- 1
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- Point at the specified length
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11788
27826
50
20
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11813
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- Tangent vector at the specified length
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11788
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50
20
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11813
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- Curve parameter at the specified length
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50
20
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11813
27876
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
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- true
- 34c4c1ac-606a-4181-b6ea-85caebd18dee
- true
- Evaluate Length
- Evaluate Length
-
11687
27936
149
64
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11772
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- Curve to evaluate
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11689
27938
71
20
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11724.5
27948
- Length factor for curve evaluation
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- Length
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11689
27958
71
20
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11724.5
27968
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- If True, the Length factor is normalized (0.0 ~ 1.0)
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11689
27978
71
20
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11724.5
27988
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11784
27938
50
20
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11809
27948
- Tangent vector at the specified length
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- Tangent
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-
11784
27958
50
20
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11809
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- Curve parameter at the specified length
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- Parameter
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- 0
-
11784
27978
50
20
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11809
27988
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- Line SDL
- Create a line segment defined by start point, tangent and length.}
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- Line SDL
- Line SDL
-
11889
27929
111
64
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11964
27961
- Line start point
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11891
27931
61
20
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27941
- Line tangent (direction)
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11891
27951
61
20
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11921.5
27961
- 1
- 1
- {0}
-
0
0
1
- Line length
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- Length
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- 0
-
11891
27971
61
20
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11921.5
27981
- 1
- 1
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- 1
- Line segment
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-
11976
27931
22
60
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11987
27961
- 4c619bc9-39fd-4717-82a6-1e07ea237bbe
- Line SDL
- Create a line segment defined by start point, tangent and length.}
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- true
- Line SDL
- Line SDL
-
11864
27834
116
64
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11944
27866
- Line start point
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11866
27836
66
20
-
11899
27846
- Line tangent (direction)
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- 1
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11866
27856
66
20
-
11899
27866
- 1
- 1
- {0}
-
0
0
1
- Line length
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- Length
- Length
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- 0
-
11866
27876
66
20
-
11899
27886
- 1
- 1
- {0}
- -1
- Line segment
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- true
- Line
- Line
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- 0
-
11956
27836
22
60
-
11967
27866
- 22990b1f-9be6-477c-ad89-f775cd347105
- Flip Curve
- Flip a curve using an optional guide curve.
- true
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- true
- Flip Curve
- Flip Curve
-
11759
27759
88
44
-
11803
27781
- Curve to flip
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- Curve
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- 1
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11761
27761
30
20
-
11776
27771
- Optional guide curve
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- true
- Guide
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- 0
-
11761
27781
30
20
-
11776
27791
- Flipped curve
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- Curve
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- 0
-
11815
27761
30
20
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11830
27771
- Flip action
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- Flag
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-
11815
27781
30
20
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11830
27791
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
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- true
- Polar Array
- Polar Array
-
11726
27507
207
84
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11853
27549
- Base geometry
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- Geometry
- Geometry
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27509
113
20
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11784.5
27519
- Polar array plane
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11728
27529
113
20
-
11784.5
27539
- 1
- 1
- {0}
-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
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- Count
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- 0
-
11728
27549
113
20
-
11784.5
27559
- 1
- 1
- {0}
- 3
- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
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- Angle
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- 0
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-
11728
27569
113
20
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11784.5
27579
- 1
- 1
- {0}
- 6.2831853071795862
- 1
- Arrayed geometry
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- 1
- Geometry
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11865
27509
66
40
-
11890
27529
- 1
- Transformation data
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11865
27549
66
40
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11890
27569
- 4c0d75e1-4266-45b8-b5b4-826c9ad51ace
- 00000000-0000-0000-0000-000000000000
- Divide Curves on Intersects
- Divide curves on all of their intersects.
- true
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- true
- Divide Curves on Intersects
- Divide Curves on Intersects
-
11726
27450
174
44
-
11853
27472
- 1
- curves to be divided
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- true
- curves
- curves
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- d0b62982-5ce1-4b59-bf67-33f8e443f0be
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11728
27452
113
20
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11784.5
27462
- ZeroTolerance
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- Tolerance
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- 0
-
11728
27472
113
20
-
11784.5
27482
- 1
- 1
- {0}
- 4.768E-07
- 1
- aligned curves
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- curves
- curves
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-
11865
27452
33
40
-
11881.5
27472
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
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- Merge
- Merge
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12407
30097
106
64
-
12468
30129
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- 1
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- Data 1
- D1
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- acba9f12-7c5f-4b20-8140-fb2b4854a190
- 1
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12409
30099
47
20
-
12440.5
30109
- 2
- Data stream 2
- b3c3dc20-91ea-42ab-a774-508a452de635
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- 1
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- Data 2
- D2
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- f53f20a5-69ef-4f15-910d-10163e12842b
- 1
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12409
30119
47
20
-
12440.5
30129
- 2
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- 3e8e5b08-c7e2-44f7-a27c-3d7901e0ea27
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- Data 3
- D3
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-
12409
30139
47
20
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12440.5
30149
- 2
- Result of merge
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-
12480
30099
31
60
-
12495.5
30129
- 22990b1f-9be6-477c-ad89-f775cd347105
- Flip Curve
- Flip a curve using an optional guide curve.
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- c8952bed-4df0-4f17-9d79-43e809adecfd
- true
- Flip Curve
- Flip Curve
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12596
29491
88
44
-
12640
29513
- Curve to flip
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- Curve
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- 1
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12598
29493
30
20
-
12613
29503
- Optional guide curve
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- true
- Guide
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- 0
-
12598
29513
30
20
-
12613
29523
- Flipped curve
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- 0
-
12652
29493
30
20
-
12667
29503
- Flip action
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- Flag
- Flag
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-
12652
29513
30
20
-
12667
29523
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
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12825
29468
90
84
-
12870
29510
- 4
- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- Data stream 1
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- Data 1
- D1
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- aeaf0dce-3d62-4791-b43d-941eeac6c2dd
- 1
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12827
29470
31
20
-
12842.5
29480
- 2
- Data stream 2
- da9945ce-59f7-4a96-b705-16a66625fadb
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- Data 2
- D2
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- 1
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12827
29490
31
20
-
12842.5
29500
- 2
- Data stream 3
- 2c15933c-ed2d-41f2-b118-69a74a250e27
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- Data 3
- D3
- true
- a9ba64db-3550-4932-9fee-3e0b1c0f003b
- 1
-
12827
29510
31
20
-
12842.5
29520
- 2
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- a2635cde-6a9b-4bbf-8847-e4ee58b9bccf
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- Data 4
- D4
- true
- 0
-
12827
29530
31
20
-
12842.5
29540
- 2
- Result of merge
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-
12882
29470
31
80
-
12897.5
29510
- 4f8984c4-7c7a-4d69-b0a2-183cbb330d20
- Plane
- Contains a collection of three-dimensional axis-systems
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- Plane
- Plane
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- 1
-
12822
30384
50
24
-
12847.63
30396.82
- 962034e9-cc27-4394-afc4-5c16e3447cf9
- Extrude
- Extrude curves and surfaces along a vector.
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- true
- Extrude
- Extrude
-
12934
30358
133
44
-
13008
30380
- Profile curve or surface
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-
12936
30360
60
20
-
12974
30370
- Extrusion direction
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- -X
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- Direction
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- 1
-
12936
30380
60
20
-
12974
30390
- Extrusion result
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- Extrusion
- Extrusion
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- 0
-
13020
30360
45
40
-
13042.5
30380
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
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- A wire relay object
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- Relay
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-
12756
30344
40
16
-
12776
30352
- 4f8984c4-7c7a-4d69-b0a2-183cbb330d20
- Plane
- Contains a collection of three-dimensional axis-systems
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- Plane
- Plane
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- bc6cb778-3b9d-4212-b11d-dc534e071d3b
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-
12837
30487
50
24
-
12862.63
30499.82
- 962034e9-cc27-4394-afc4-5c16e3447cf9
- Extrude
- Extrude curves and surfaces along a vector.
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- true
- Extrude
- Extrude
-
12949
30461
133
44
-
13023
30483
- Profile curve or surface
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- Base
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- bc6cb778-3b9d-4212-b11d-dc534e071d3b
- 1
-
12951
30463
60
20
-
12989
30473
- Extrusion direction
- 3615e3e8-527c-484d-bab7-357debff0c3d
- -X
- true
- Direction
- Direction
- false
- b61abf08-a492-40ae-a5bd-8b6987016bfc
- 1
-
12951
30483
60
20
-
12989
30493
- Extrusion result
- c9f55136-fb6f-40a6-819e-aba3e906f9c8
- true
- Extrusion
- Extrusion
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- 0
-
13035
30463
45
40
-
13057.5
30483
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- bc6cb778-3b9d-4212-b11d-dc534e071d3b
- true
- Relay
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- 1
-
12771
30447
40
16
-
12791
30455
- 4f8984c4-7c7a-4d69-b0a2-183cbb330d20
- Plane
- Contains a collection of three-dimensional axis-systems
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- 347017c1-2ff4-494f-9650-d789a20b9830
- 1
-
12832
30263
50
24
-
12857.63
30275.82
- 962034e9-cc27-4394-afc4-5c16e3447cf9
- Extrude
- Extrude curves and surfaces along a vector.
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- true
- Extrude
- Extrude
-
12959
30236
117
44
-
13017
30258
- Profile curve or surface
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- 347017c1-2ff4-494f-9650-d789a20b9830
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-
12961
30238
44
20
-
12983
30248
- Extrusion direction
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- Direction
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- f9c4318e-f2c3-44de-9e4b-84056e68fa44
- 1
-
12961
30258
44
20
-
12983
30268
- Extrusion result
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- Extrusion
- Extrusion
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- 0
-
13029
30238
45
40
-
13051.5
30258
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
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12765
30222
40
16
-
12785
30230
- deaf8653-5528-4286-807c-3de8b8dad781
- Surface
- Contains a collection of generic surfaces
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- Surface
- Surface
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11334
30398
50
24
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11359.63
30410.82
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- List
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27146
38
20
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11829
27156
- Item index
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- Index
- Index
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- 0
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11810
27166
38
20
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11829
27176
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- Wrap index to list bounds
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- Wrap
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11810
27186
38
20
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11829
27196
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- 1
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11872
27146
6
60
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27176
- 59daf374-bc21-4a5e-8282-5504fb7ae9ae
- List Item
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- Retrieve a specific item from a list.
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27159
72
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27191
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- List
- List
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27161
38
20
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11724
27171
- Item index
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- Index
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11705
27181
38
20
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11724
27191
- 1
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11705
27201
38
20
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11724
27211
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27161
6
60
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27191
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
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- Merge a bunch of data streams
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- Merge
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27166
90
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27198
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31
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31
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31
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27168
31
60
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- 8073a420-6bec-49e3-9b18-367f6fd76ac3
- Join Curves
- Join as many curves as possible
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- Join Curves
- Join Curves
-
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27059
116
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27081
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- Curves to join
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53
20
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- Preserve direction of input curves
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- Preserve
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- 0
-
11791
27081
53
20
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11817.5
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- 1
- Joined curves and individual curves that could not be joined.
- c941d725-c216-43d8-937a-b93706e3dd70
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-
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27061
35
40
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11885.5
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- 8073a420-6bec-49e3-9b18-367f6fd76ac3
- Join Curves
- Join as many curves as possible
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- true
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- Join Curves
-
11677
27106
116
44
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27128
- 1
- Curves to join
- bd9b006a-4258-44f3-87a9-dcf4a6964510
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- Curves
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- f63e2038-e99c-4ba8-bdcb-667e1ffc18a9
- 1
-
11679
27108
53
20
-
11705.5
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- Preserve direction of input curves
- dc69c91d-b4d8-473d-80c9-ccbca9c4442e
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- Preserve
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- 0
-
11679
27128
53
20
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11705.5
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- 1
- 1
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- 1
- Joined curves and individual curves that could not be joined.
- 0ef5f963-ee98-4aeb-aa80-2bc5eae22ee8
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- Curves
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- 0
-
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27108
35
40
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- 046b132a-5362-439b-a57a-d4dbb32ff590
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- Weighted Average Curve
- Solve the arithmetic weighted average for a set of curves.
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- Weighted Average Curve
- Weighted Average Curve
-
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26883
186
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26925
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- Set of curves for averaging
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- b000eec6-2ed2-459f-ab6c-82168ce081e9
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79
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- Collection of weights for each curve
- d0bda1ca-40f4-47fd-9c4b-9953458bfb0e
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- Weights
- Weights
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- d25249ba-aef7-4d5e-9264-4a101848ac12
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11798
26905
79
20
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11837.5
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- 1
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- Optional Refit match method.
(No Integer or 0 = Off, Integer greater than 0 = On and curve degree of refit)
If an integer greater than zero, Refit match method is used if possible. When input curves are refit their control points are redistributed, added to, and removed from based on the curves curvature and the input integer degree, while trying to maintain their shapes. Refit results in tighter shaped averages, with curvature based control point distribution.
- 343200ae-fb51-4440-b046-591d01e6148b
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11798
26925
79
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11837.5
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- Optional Point Sample match method.
(No Integer or 0 = Off, Integer greater than 0 = On and amount of sample points)
If an integer greater than zero, Point Sample match method is used. When input curves are sampled their control points are recreated by equally dividing the curve by the input integer point count. Point Sample results in looser shaped averages, with uniform control point distribution.
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- Point Sample
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- 0
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11798
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79
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- Arithmetic mean (average) of all input curves
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- Arithmetic mean
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- 0
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79
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- Numeric slider for single values
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- Number Slider
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275
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- Numeric slider for single values
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275
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- Create a polar array of geometry.
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- Polar Array
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207
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- Base geometry
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- Geometry
- Geometry
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113
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- Polar array plane
- a1e248d4-ffeb-4800-ab56-cf15ce14d14b
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- Plane
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113
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- Number of elements in array.
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- Count
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113
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- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
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- Angle
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- Geometry
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66
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- Transform
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66
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- Divide curves on all of their intersects.
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- Divide Curves on Intersects
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174
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- curves to be divided
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- curves
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113
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113
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33
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- Retrieve a specific item from a list.
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30345
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43
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43
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6
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- Numeric scroller for single numbers
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- 12
- Digit Scroller
- 11
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30513
250
20
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12186.63
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- Retrieve a specific item from a list.
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77
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43
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43
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6
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- Surface
- Contains a collection of generic surfaces
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7bt1WFRb//dPd3cODUp3CSykRVJCpTsEREkBFSUEFBBQpAQlBQRpRAT2IqW7G0WQkFJUVOAZ73O8f+c597kvvs/1/f3Je649Lz5r1uyVs/Z6z2wwMDEwMA7R+sVfIsFCP50/5+J62VPV08PD87Igu6mjl7er52VFGWExCWFxMQlJWfQfoqJiguyqvu4+vl6OipcdfX28bN0F2Q187dxd7c86Bhh7ujleVpSSEheXFXOUk7GXkZKSkhDF/VUK9b9OLqzp6Onh6OMVIKzi5XgFB52O7/dHOUS2XvYurn6OEg4ehJ5XHC9f9vWy88ZxsPWx/ZWJgIAA61cVKfgwMMTRfPCTmIQQG/0H+a8nKiMMDKzvwVgYeEZ/NOfHIRYGzZ9NU23y3OLPJtBIH3822NLLL33ioEj+J/r13nN/vC6OcQtD+SnvHwHFr9P9qu6vs7WS/+fZGClLrAyJhymRAwyKUEzOLW2mAPpfZ4v5My8F1p8Z8dBHJsbftQX+I+mPdOTvKbnoI1olCn4JVIdHMfhQ7pI299G0/Kly2bhO7UjW5aws74sfzdRpCd6f91WPpDzTtQ9JXSpHcvJ8XaEE/tEMTMTw6FM5fSSZhtRE3G4qH0kfDqp3pD7gSJY/TnVWX1M8kjv0XOvX7RSOpOiD51cqJ+SP5BUyyd01A7kj+SKqLoCrXeZIbuCoH5gB6SMpeKsnJKFa8ki6/zDB7xSSOJKFfrP3MHPFjuTqthOFHIvokTw3OXtygVfoSPb3b4ob0PIfSb03GAoINt+R/KPd3Efyj3ZzHUntSk699Hn2Ixln4vyCIYP5SP6xLtAeSUpr09yCErIj+X56LyomGOdI5re2a2kPf0WOInFz/wPa5++P5J9L4a2j+GudfelDgapOsAax3DWF+s1WCN76jmRDXCbCEyUYbf8iGbkEIh8zkJcjLBTWT87WPEOWPJJPnjZ9jXz+mHe9OboMGaffMn+u14Qwa9imOyu+RDaD7wWp7bQhTBd5mRg36hCKptCP9SHdiM3KaObz+UZEjyISM49wABmp7TtnrN2K6PQbIesDQ4g4kQAWXmU7Eqj8ZVE8dRR5rUJzA7J2I77Xnp3ztptAntIy+N+O6EMWekpKrclnkDAJAdQiziDCqLhJyGE1j5DmYwiSagwj997ZH0RKvkXqV7Pj5CJGEflEQ5xFokXky+MzOY7t40jJTuyoyMJ7pO1R4scYwimkHFvhwJb8A4KXeC4msXoGsemMen1TcRURTyNe6xKbR2IfGGmHuK0jvI03UjQjFxCzF1N6bikbiBilgMnr2bfI41RLkXT7LaR8bnabR2oRYdH+8Dq7YhtRnlW5UzbwHtEqXLqahP0Jef9Nd0bk8jJiIQIWrhl9Rghrk+cziFYQ/bGfgtrZuwjvhH/hQd4q8kEhZYT00xdE4HzSCUPVdSQkS+rmgMo3RHSkOi977iPS1FoaGpGwh7CU0018CNpESg0jz4m//Y7UY9upUEZvIWaxIVeGxX4i1z3stk6abSMKn6aaPG/vIzhPktSVT+wgrBekaIkHDpDo/u5U0y87SNrOlx59Cgw40yGddKnlE9Iq4l5AX4MBOQf2aW4mfEauuV7tnLHGhJvRQagHNruIS6B4ZxY+FvzBWbn8XPgLcuHepw7nEiyI/2q9tOXnFyTC+0q+wHlseO7kvNxC51fEa5zyy8YBNtSaECnGTvmGXDEx4CvPw4GLNr2Gws57yJXJiy989XDhNzh0yV7qO3LV2l5K7gsuJOGYCE3G/oF4r8tQ7afjweSL6pTjAz+QN+bVZY3q+BAZ8z7H/fQncpPyx+2Ij/iwOy3yTvDlfWS+j2BGL5EAYixLdq4pHCBqsXSydIqEUFp8gfQC8SFibPKRdW6RECbg8NiOTBwibEGnVwqiiWDS7ahtcWMMyH21fd5PkhjqtbR0hL/GgN8odug0polhW0wC+yInJuwuZdalDSOBSudt/FXuYkLP78uNSwKk0O8Z1CnaxoTRUSbhtUOk0NzgbTjnRSyYPDboFRdEBhmYHbdyIRY0tzt14MxFDrdEvNhlTmBDto/ZUaCLHLapBRu038eGupNBF6PlKGBFNp2G81dsqNlCExAQQwGlfaiSaKxxYKxMaKHTAgUk1RdK72/DgZFPf0gZSVHCzAcmpmnCuDCE0KcRRFFC6fEb5E6PcKGIy5c8gRlKGHWnIggc4MKdVNWTdGJUcLnvfAKfEx7kM71odhBGBWu+NR6w9uLBav+k7bfjVBDrSvcshzQ+VEsZiXwjSA11l0cbeDLwIT+Hwp38W9SQvPg2lQweAVSPa1sLG6aGFNw+500uE8CYgPslZidooE9/1eObowTQcpl66MR1GhgnaadQrkQIhU2Sv3zpo4HFyWTT7/MIYZTmeEA9Fy0Mq+QZ5SIngj2LOX3X/GnhU1emMy7+RNDGmH1NoIsWfpdQuv9yjgi6y4zj96Ho4IN7j54TaBHDa0xx3F5edFDw3cabi6XEcO9KmApuGx3Eaw+qLWIggas5JAaPGenhRSvxeubbJNCU+XvzT3d6SNfKYW+1QgL5Q5VoLkN6KOQikNVnSAoPV0Mc5qgZoBqx1IJyLSlUUkPF2zozwKrVC6/mOcngUtfjBb1aBtizlts+f5cMXguKdnpMyghnp5kPfT+RwXfSG5htNozwbiAQ2Tcnh3o7+umbFYxQlsHeOqyFHN5/xaW/i8cElcVSW27SUUCM87m3MM2Y4MpIkVS/NgWMvYJK+FTEBN1FLDy5gingVbV2OHHIBPNDjRRCKyigCYPXJnKOGb4b0yZ8t0wB4/J0TqXmMsMx3ruu+iyUEKyH3HH6xgxxL+YPtBtQQvM8mdUTZ1mgocm7UaNwSug1K9K+kM4CZZD6RzuvKOFduhN5qVssEHUy2TR+gxI+7rY/OKPKCp9gUA2oclFBGoPutO1EVnj20xsi0gtUUOM89cuED6ww47ZL9GY0FRQlA89FTqHgjiCN/UYjFWRuvfSkOwYFNcYRuY9fqGCDQJC74zwKpj31cyRAz6MajHeVP8XZYNwZFT5VW2pYz/cuMCGcDXKWro9kPKKGRacfFAiPs0Emcol5jm5q2FvM4e5Iyw6pLges5mDSQIXKgZfVSuzQq9XcQF+GBrrrH0TQuLBDiahRX2EPGli+QjsaHM8OVW+foFbPpoGMtP4JX2vZITHJB5kHEzTw2S5iTTnJDjkr/Yd0sWjhhAyVgPgeO4QHks/5BGjhizFs6YsMHOj51mzLbkwLV1tf44fLcECpmz0F0jdoYapC960KUw6o10Nw1iWPFjpKj/HecOOAlUXh1bONtPBVbv93zVscUDU274ztDC0UuQqdqBM5YAIpttvmN1qI+Zr/9WwBB4x9zm0RSUMH7ebNzxY0cECWiU4LAVE66JOcyzUxwwG9WFtmnlykg5ENl1Xw9zngcM4zTIFQOrjrk2QlxsIJ7zp8PNVZRAfTyV8JmpzihBogfjZwlA6OhoyNXDHjhEwNZunyGPSQ/U0hyVooJ5yjpNpelKGHuq097abFnPAh/U2OQk96GBzNmF8yygkD6gsawp7Rw9m+m/k7h5zwFtS1vTJHDxW2KgLZTnLBjBn7h270DDCFYkVH5xwXrPse8MZJnwF+Id3YsgvigptiWPeuRjBA/06fKrscLljVrdMehTBAP8GzNHo9XPDWolNn6VcGSDUq4cf/hQvyy2svfRRhhKXBLON4bNxw7L4QloALI1y/Qq84rMkNHbkmZW4+ZYS0EUF4SVe4YZf1ws31cUb49JxEoUkKN9Q59Z3gJiUT/Gz2bYK6iRs+EymlltVmghuVRpjv33HDy5vWIboBTHCUs3e8CpcHysadHL+ZzwQnPmxcjeTjgeoYpfh9Y0zwTqagleUZHlg+iXcd4DPD2VAdlJgbD1xvH6HslmaGbR/PSJVF8MDLgt8Hp6yYobWeor9oDg/MpkJFH95hhuevOtAUQx5IeIbqq2QJMzSeEJngnOGByS8bW/zGmOHJexfOxuzxwH1U1of6Q2b47W3XKDk5L4xMSuY+hWKBD6wN3t/j5oXTNQ6erxVYYF6ozq0DOV7oWzwwLW/OAn14jBpd9HnhIyam+ZoAFrhjZrXb7MALL2Z3Ggsls8DrwZM4CX68MNFnRT++jAWqnFDMMInkhZqWAXkbnejzP5mZY0zlhbZvPNb0FlmgS72lTOtzXngqyuZR8j4LNGi/p+tRzwu9Xxdzz9GxwnvyrDcOg7F+7xH/berfk/7PTX0x6T+Y+pj/hamPRx+vCg02DBOllY/igPlQSebh0VzKSpngCZY5kj7Pt+NT+WSPpFOmu8e9zaOpITMr5zkvdyS5e/TxjAbkj2T0fs7cfvipI3m9fabV8+Bovv0m/oSpQuFINsXmuB1kKx7Jp9x0sm8fKh3JW7UROG3h4EiK5F//YHxK+UiyeVf1tlUcTXKljUpZwdNH8pCAL60w52huDlnfZmFVOZJzGcnOsYlHs891QBeDTPVIIpJEkl53jmbJoQrT4sHRfNIZhGHqr3Yk7ydWLr3ZPJrBNh+75VzUj2TAVKG8ePfRROZGH7mzaxxJTeza58I2R3PQPCjaNPFo/lrH/r5oOsnMXNt7xgutM2qxtVCs8H0gf1VoAi8UqjO8VcbDCsdfJg5h3OCFq2pcUSghVjgj1tB4yxm9KCfKOEZJskKRycTr+4a8sPvxgdmnU6zQdH2vQUSWFxqHMi+MqbFCPcYMJ0sUurz7b5lf67JCX3w+7Xs4vHAZ0NimmrJCr3ySwppVHujWvTPnY80KZeuT1pb6eaAYvMZwxoUV5jWG03W94IFUnr7fdrxZoZYw6CqN5oGnqanfxwezQsqItJSUSzxQYaaHjOseK8SAwpJ3tHggHefMt+xHrNB8CkfLj5cHsuAM91JlsUKhJJuHBAfcUCU4tjinhBWOrlxrfTLCDV9IhtCw1rNCOubF5FPF3PC2pVDLtU5WqLojGjEZxg21Q83MqsbQ9cOp3Q204IauWc2d/Yus8Fyw7ONRAW5omnf/atpnVvhd3OeK5A8uCG93fpfCQUGV56ci4zu5IOPLxZHH1Cjo0uVsvZrCBfXaLJ16OFHQ4XrgsLwrF6y019NvFUNBO6GYM/dkuSATJpCtV0ZBWc87FkP4XLBC8FnAdX0UDNPF1CMf44TM8tMuGFYoOLzAtqKQxwn31y5kqLujIIkHrbiFLydsa79NoBWIgr6JPfkVBpzQ4jL7eEcYCsJ8PUpsQU5Is25Ny3sfBffXhR208Tlh+OJdUvMUFPQontC4+5YD1rT9mHHKRkEpTu/B5noOuPze46lmMQpSXJkIA7kc0CLXwX+mAgXra9461kRzQALNMgGbWhTkY7jeLuzDAR+eUBbqgyiYrkVMl23OAckq7NZOvkFBuQt3IK0qBwzTuDbl2YOCeZtK8DSKA1ZnJzePj6KgkCIR5SX0ppZzhHmaCr35dtkVFI8bZodrX6QMWVZQMGTSuq+qhB3KaQVe/rSNglrtC/zTd9mhU/DWwKPvKPi9RO77q4vsUBsVa8qMxwYNpN4zp5xgh59YRJZUKdngz1MYxHsbbFDk82tJUhY2iLK8WdkVzQa7z1Zg+/KywS+bYbE5/Gxwvm36QaAoG+wLuedyox0FP5/G474lzwatI5i8LZxQ8Oa8rS+XGht8Oq56UxE9zsxYgen2umwwmk/mAgo9zxh1simUTdmgG+HIh33ACoVn93/WWLFB7TWvgJkZFqh25cKKmDO6fJvX8HUQC7yivain6ckGHbi885IYWeBgdrrZnh8b1Mkp5rn6khlKM3Htat1kg5feuQZomTDDYVQzlizafERw8vawfWKCV7jsKfjQ7Zhkc9j9HMcE1atZ46sS2GDxBWGhdmEmeGqgxPV9Mro8fZ3dlG5GmEVq4vsqgw2qDExYXbrECL8miL6UymGDTkbO7fIEjFCHgWSvrIANKto6DBHmMcDYJdaroy/Y4Ei8SvmYKgMMkionfFbBBnUfpE1lL9BDggI/8pM1bPCQeO+WRzA9VKtNibGrY4NlYaa8Mqz08FZXHfFjyAbTfWo0D2rpoFugElZMCxtcx9Tehxfo4GzsozMK7WzQVLQp6sYXWlj+6l5CWRcbrCi9mivzkBaeHryzsNHLBinEOBq3xWhh/+ptUcFBNmiDTeBegDblDNsh4WIjbLDdKDLMGm2mXrJlumGjzVh5eO0zWmIa+LWwRzp3kg2eC0MZdudTQ6xwlhKmGTa4HRLyPUSDGpJZu/HFzbFBdT0GfvlFKvg+YlpnYoENgs9pGTu3qeDay0fFe+/YIPNGYWoRGxVsDh96/fk9G1SwWxZyqaeEpjjOOT3LbNBqlKuRy5wSroZ8j85bYYMtLTFr898ooGz5or7lGrr/k7NePnlEAVscW1C762ywJ1Zny1qSAqqHWm9fQc/LyYQrd1RyyKEZxtmwoU10eQRagq1zZPDyDWl66W30eOBm42kzk0FaM69LwTtsMFDkw5V+U1JY9tRcvvwTG5Q0UIo7n0AC72Tz4Q98RrfvQkzMbA8xxDu4RT27ywZf2E7fdSQkhncuTLKtfWGDHue4ndbViGAJUaPb0lc2GHTYpOF1ixCKZOPLD35Dx1NfTb+8JoBvfzLFle6h+1fEbM7/Kz4cTQyQCf3OBmnD6pz3xPFhl/D4rMkPNlhioONy7TIexMIPGWP5yQbjZzJPfC7AhU8Ucdcm0HGc1ySZ+3scmCdL+Sx2nw1+qtrMn2PHgZ9JuG0UDtDjv4ejamSBDVUWpBlX0THr2pe4piQsOBZr0Bd3yAa549+wCQ1hQst3QWsMGOzwumxmTgIZJvxK3MTjjI4P2jY3d85gwOu+ClEV6Bjz+XW/PKJDBGOuev0QHVs8wk61uL2PeEY5BmhjssMPL6jX8L/9QCgH8LIeoGMPx8cK+Ze/I/BFcMMUOnaJv++n+P4bkuBiTsqFxQ4d6kNKB82/IvacMhaX0PGI1fygxeAucr7Gd6YUHd9IU3kzpfUZGZEo6vuCjmWT7kfrIztI95XV8wrY7PBKlId8jdQ2Motgh95Gx8nvl6moZjeRQhrq9Vp0LDxT5pJj8BEZU/1K8xkdLy3djOVrXkU2VpxxhHDYIdeX7/VpUh8Q7IX9akd0/PnEmj5m/ntkqd2QOQMdLwVEmRjdfocMPTuf0YOOTQ0kfqSaLSC6yv0rP9Gx7VQ+bZnzLDJlo/BFAJcdVlXTXWVgmkR+JleUmKFjpodYYh7dIwjq0AgnCh37FNXV3bw7iDyNDKQrQseFYkuKxPG9yDbxxEYvOo4SDHuETdqOhORnBm2jY++fh/dXIxsRjNdYPdR47DBN8qJ6IGE1ovZjv1gKHV8jzxeePJ+HKJXVrxuiYwO/KOl3cUbIlQjLGQ90LFnNMzOKygWi288motDxND65xxmPKrAwyE+di46lZYzjH/FAYHYYKA7RcQj5mPs/mb56gv+56Qsn+AfTZ/q/MH1m6OPqxkDj4aYBPIoByvUxP+uPpl+lau7h7aO5SUhjAsWPZguLdbhdgf6RNJCeOVffpnckp/XN2RkWdY+ki+vERy/Mo/k55PzrHpTOkbz1eCTyhMLZI0lSbWQaelH7SCb3DXDN+p05ktwr+tuyD7WOZClWb8ODMs0jmUSMm+q7q3EkI6pz976YHs1bGeUn9mfVj2Tsn3cUHMVfn4e/f/imFgKjhQQh8GV9cuXGBBvc2xmizhKHIDKjRtYvF30xWu8SIZaFwEY4klnvKhucPp1AfVkRAnNZ8W1eRfTFS0A4RFsFAoqOuvAdAjZYqsPOx6YFwQvmq77Gnb82XaZm4roQXK/xNcq+h4KczrfTawwh4JlPJV3RQUHReqHb0SYQYDXM2PKQoeCi+tvMlxcgWA8libbqY4X8irxCyxYQLDjNM1y5zgpvUClKbFlDcCr7K9v1k6ww2tnRuNMWArflSJXoURbIa8Sp5m+Hrm+iF0lRKAtkthpv3Ua//tJqbmBelAU2bmoaG6HjaJJVrse9zHBIrlUSF32+STFsXF93Zrg77paNYw5BIT2Drx8RM5z8KIjSQ9ePLlIdIzufCX6gnh+ZRbdnObmIY0+DCSYlU8EVNQi+ldfV6w0wQpOF4TkfOQi8Tzu+nDdnhIUCmeqBAhDcKEo/eL6E3nQ5oD5uMUHgAf0Wc64yQAy/p8Od+BDIqrNHNfykh0Tk6tfOrCAAq7NDaDyCHl5/d+5Ncz0C8hHVeCpqeihpXGi4Eo2AOrxb2TYZdPCRCs/rR6YIKDRM3K04SQd9jUMtC5jQ+Wn8+DGqaKGx08Lh69kGkDdmaq2jTAvL0jinJNIbQCUVtn98Fw08f2OmasOkAbz4HETVbEoDLdxNtjsI0PnTVEpHF6ih190B4+KqeuD1ketSmzs1jMzXrYmzqwdKAJe7+isVLNvtUb1OWA+mT2F+vx1CBT0V07IMCuvAouS6LRcpFRQMU+AgUq8D07HKtKlJlNAtOEYjfuI1kPxQrLrCQQkLA2fdGC6/BvdOM3vJFlFAV/45GY+fteB0aiazjTQFDFRWJ2gLqwV8/R8ah2+Rw68p7LIdeLXA62U47cuHZNBs7SsuT8grEBLrHuSSTwrrFfqGbu3XgARHowXGOhKIdycLSHnVAGfBsIupfcQwP9g7hXX+JbjNjxn65S0RLBqS2VXWfAnKvVAGyl8IIfuL0J31Z9VA+6ZSbxwhIXwQ2beZTFAN3kZZ6SywEEDflazYHjv0xezC7SBZUXwYcjeucqC6EhD08fK9UMWDSsoO73hwKwFGEAuX1XlcmKwpc19frwJQXPaQt3HDgTt6RKcCksoBh22DoV0wNlx9Nm1/baoMaKddCqt+gAV9LXNth5jKwIIZQaNPPiY8o/Ephsq0FLS8zLAoq8eAUz+e9Iszl4A2/KeOG3mHCLfbxXDlu8UA+ykWVeDgPkJ6TfTRzPZzUE2XJsFw+APZmhwzHT1XCK6/frw6K/gduUxyOq6oOB+onNncGjD/huRF6EhVYz0DTa/ZyafvfUHyPmXKGD/NBd44AY9biHYRS+uVgE9yOaBS0dbT4+4n5AlmgMSbvixw5nWgeifRDtLCgp21ZZsJdgzNhFrubSG3tLHCtBeegMJBfGE3pg1EYbRcCss7HeSf6GjoSFxDxll46gYOU4HS6NjeAOUK4qmTF/k9Ihl8pRyuMY9dQvzn70v2ET8Cmg8wd3iJF5G9mYW8kXsPQGlvJOGniAWEJvuOk8OzeCCY1RbGrjKHND27PxR1+z54Famza+4zheDQWX3WKb0HjJ82pSrljSGl1F2tE1MRAENXS3t2bAgZXdBtvokTBphWGWccCPoRjFHn2wX9t0AoSY2VanUHolz52T9DKgh8j/skJ23WjLRODvbItfsA9XTc/sL9V8jt+wK754vdgTwl5QZDYCHy9zsYZH1V/P66mcn72srw6141Crw/Nyh/vVfNEut/vsPhwfrLCX7p1314ZP+LHQ4Fxn+/V237CVuDDKPyv0mFM5lId1Xq3+w9qXglwZDn33x8M9q3xIz2b8T9N/8s8tbf+av+Nh/LQxlPtSMVUt28H+XbwT5fXSblqXbQkaF8yBPfhmi0aF2hT2gD61Wt6xryXaC25szS6YkWRKF3gFh1ogVUkvh2Up3oBTfDCAgaTRuRGc/JrQbTRtB3pXC1b28ANDY+o8djRpC30+k879Aro8VKmArmpSFwyicBkD96iTzIpUzXevQSxDf4YTPyj4KwqW8/IvMqEKe5iEm3vApwMYnk/Y+AMUBk/p7VuagAuRZVV3K7qACkYNqhBokmQKfDV9zctzkIyeSiRuzbHIApdDeK/MYEeHg2p5mtJBWRtrSxIClJBcm5P0i/bU+ADiSjqyM4EclmnvP1Ck4Ej7/FP8sinwTn5CUYpCvDkQyBcm23ynAQyRZ7OCwxCXSdr3ZmJPoi8rIr+HYPfYEs/s0fO3KTQK2Orvt5R7zSyvMkQ4f1eCW+Sxntj9DpZQlWbP+0nZ7B/J9PtlzMf5hsRP+LyUaC8d9/Q+nVV4y6Kq3wb0ovh7mWfVT+N6mdLlydb1T9N//bd6O/6qcQI3b+BbpTrKxlz7qgO8Xsz05JCNtLriRKRSRdqtabat82SMniWU+j0w2KF0vr9gqQokoiYFxX2LDZWucdvjQB5AJJjELoXiGUEQ2VTd8KlOgHPBkYi8aBWdmwnlRaA0I34Mu6QZisFPfgMI2ifQwU44eHP3ZqQXpccNe4xG416BRczjqsHwGeG8Mbz5E2BAbt+eE+CFQKbTC7dTl1GNxZEJ9NtO9CLlACZTlvs4YLN3ngU/1BYIg4NZmW9yA709NSMinZSo6d409kTgwAwfPK8mWHfch9UbPx9E8pDbIgYr78sA8wE08/+afBTv9/GGzHfxpsgv/FYP8aiP/mlbANeIZ2u/T+zW4haW388rP/5n/bu/6qz3etPzqhACwVJKM7IVH/j07g5XQIqsTsR0Q2w7WvYSYAWbq778sw+8HF9UmCV319yD2jlK1EuizwMR3Pt66vD3w6eC1/a7cX4bZ6a3ynBH3tjdtWvLHbC2YKn04rmPYieC9GAh2mqwBJftaaumkvaHUxHeBm6UZO5rn4TOI1gmxpMklWlm7AXh3zPVuoE3EPz7EoLW8Bqv2u/cLCnaB3ruJfK5rTZ4sTv1a0L8sCT3+taP12yg/+6dpQS/znAGD+ZQQzif9zBOnbbTTf/WUEn5+Ibfg1gq6/T/B7BPH+PH597Aj/FyP56xoxdeJ21vQkLzyKjLjpe8GPuf6Dq6rP5loC6P6DWg9eNjMib8BR/PVzLtMZbqxXbOzwKOpyNr7bwKL4D3ZxrjRUYeWDo+iOLkvcnyNJVs0MsYHNtNkGicgZ3lasT4KTIOjyPd2IIAvQ9CSSv9qOBZQ+LOaWU54EeSXjmJlDl0GNbjc/o+Mj8OLcd5UE80mQjPnjyXbZHUDDdW7PoyEXOC+5M0q0TAAtGtZFP8IwkJMo3X/uVjUYr357p5l8CiTVbWIb2t8B5g/Erx+MQrBH0qvld3IadCgeFnmbRAHlGfzv3DebQfrbkFmNvGlgr3jjJm1OJPCNtGB0t2kDyd/w43c1ZgCuwOnWTP1QUIQw732J7wATWW1iGjSzwHUER9s1PAxJF9hdIux7gJDhFNninpgEqdset9jwriMHAvJhjKfNQB6+IF65xiQQskLlKgR4IyV+nVfLppJAwMGHwhrbSZBEeOJN1B1nQBFz70eEWx5oYyOZk6icAFhksyZ5K45AryuWJqStGmAFVW/bdUyCp7Ufs3CY/UDswUar60cI0pnCNXnSpoDlVvLN6pPBILqxNiszphkQVl3v/rg7BRjJSTz9jW8BHW7P/tRLbeBOyMHhmN80GLerzEvIvQbOZJm1CSZ3gEeSbKwkvDNAk1ut/8VMAuLt1CU0opWAcIuPx6+gJsG21iVMqdj7SIaGbGWgiyuY2SJs2FGfBGNC/YF5fPeQlEUzpSz9FDDxPZEW32oShA8LVb5r8EWoCNYCnKifAad0p6YbaRNg0R0Xs4vAC7ktjUX/jeAlmOi8MTV8fRIgxCL7+6+4kCKpwVkLzEawJ/3t/R7hFKggzUq/2eMEOj2FhVZTm0FUys6bNvUpoD6SfI6F3xNMuFUGzXu1gez4UwVaBVOgiNZ8KwrXAWjkqgcPPO4ALR/vGLxXmAY+Jy7+JL+ahrwPe0Yd3RmHND3s4DJG7xOMH/J3vAlNRoRGXhqeL/QCuGd1ziWdmgQ/X5xa8Tr9CBGguMsoVpcKug8U9b3PTIKHYxiUW+H3kDS97r2a0mcAqpsZY/pNgD61EOlc1wiEPmiiBFF/CZo+BefZ8k4CHgMFqhwTf0RD1k8Tm6oRgB5pkgKvSeBb7di2x2iLOJ0Mv0SZ2wwsH3Vw30+YBNzj/sxZykpIVs1oh8O1NuB/cdgbNTUJFD0rhs4sGyO3OFbJSZ50gNsCtY3PTKbAa5fh5cydIoRr06oBTywCcYk0VSNsmgBVLzKJ8/qeIw5XD5gM00NBJ52erMjXCfDqIo7njeuFyHk1tkIo+gTcrDWZnJ2fAO1GLbH3MnMRK9E8HPzsAlD0ZWnz5odx8PlGDR97ShZCIEMj9Ry7Bnzfi7YZmh8HsqXJcYt7KQhXiRLrKTn0eAWKhheeHwfh0e2b1CwPkZnXX+31a5vBuySOzWTWcbD+wDjIzi4OyaU1l3l5vQ2I9J1Te0k2DlKmhWQfD8ci4iaOz8xTOsBwr6xYjOw4aAnAJ5cdrEJisz+dGTp5A1m173TMYZoATSjm3FqLKkRKj2rP+/E9MC6cWZ0oNgHIN7U+ycJK5EGxpgvd/lNA/iZ4C19+AgjhqAmbcJYjHcz7AeSnnoOtgh8P56THwZbA4fSlWy8QKqIfktGcNaBUyGFR1G4M6NVzWJoKPkN0yJp3akUagQkdlsxnm1FwdiJe+tu1bOTim0yHOPQ8lDNWAoRrI6Bl+96c3+ZTpP2EYlDCuTaQg005kZ03Aj5oMfpbTD1B7hqMcba7dwC8ZRdm66cjIPWE7BJ1ay1CY+I1NMztgzxQnIqcdR8HuaR0K472tUhFuZ2PicZ9oEjfUclxYxxEpol1GvLVIvnBuifJ2bMAK+4cGUnKOLDWNnll4/oSaTn/vM15+Dk4V6Ja616Jrr8cZ04QSSXy9vGN19lop34t7w7xuxejQPuuSPAmfiniJDNB1iXWCORq01xcb40AGn2W7xkMRciCCzP5k/RmoPBIAtXzdRiMcLJ+fmJYgJx/Ld7Ujm5X6Kclu430YRBsI1xkQJWPlKGY+ZsvdYCmFnr8xyHD4HLF/QHG3SYkJtQ6RcbABpEXin/QFTwK3Lj6uK8uNCE7pWXqNDcSAHthnd3jqFEwVSDuxY9OZ7/etDyhnQ1cB8s/Uz0ZBYR4I9+iMxuRt0o1VhFexcA3tUIkZWIEDAxnH3xfbkBUr5XfUPWvAcP1j03T84eBrslpzkGp18htt0s8d60aQWd021D40yHwBNO7i6ihBunpQjo705rB7Y7CVoPFQTDwE8M/kPMlUnpw4YuFchtoiC2gu3NlEGxoQGzshGqEKdPyTrd3B1g13A7U1h4E2kk0TM8G3iC9nd7rbmTmSBaP+yQV6zCYf5qaptTxBhH1Pl/5mf0B6FlyPc/APgxcWp3vlvW8QQK8v9MFL2SDJ0tCDA+4hoHwquvAcFsb8sP1Ks90YTFgsT33Jf3+EIgpE+dPmm1B1srfTlNU1QCDSi6DpAeDQOtyWcTPuibkweZDRk2pRuDfmj4s4DoA3A4Lb9TkNCI0e2kE1bebgcmGoIDdYD8oQ7WWfydtRDQxPo7cRl+/3HSNdLxv9wO+IF28xG6ICOhFnrNFr/Nae43dzvb9AMhlrePEdCIHlqdEihjNEDnawHOnKgeBCHkv2Vh0J1IQ02JW+OoBCO80ToU1gyBhAfVJM6cTcZK/R7YdmgM+mPb/aH0zCPwCU32JZjuQ1UOMlpcCJeB9bOGwycVBUDtJGDCk2o7oBFFNO6a8Au+3HjCoBg0A0qZRAa3JViTItO3VI+NGoHiDnYSTvx/4/CjSc9RrQVqyl25KcDeD5fTCpqa0XhDjw0+YLNeMvMYyana+3AqM48dxUZ494EJXWN+2L3peLfSuZZG0A5GBljy3x90g0qXO2deqB2lVqFdo5D2P2JS6nuE0GgCctBevnjbpQT4rMjUXaDwEecGNh/6GA8AhwbjzrlwPkiIWM3B7Iwe03VFdOqE2AD4FO8XOpXUjRv0xObpPSgALydIj+Z1+IK0wO5Vwsgt52rYs6/L1FbghS/gkQbAfsLqHv1mV6UCKa39yUI83glNKLW1qcr2gB165b8HTjqgw+RSQ8rSApfaVtWtkPSDkYdvJsP42xH3DXN0F1QYMVWtHuxO6wBy5B5VRXisimbGzQXEG7d/fiqh76nQCot3ZpTnKfkR7o/vR4a4x4nTqVWPWZB/QzC5q7KPpR9Srdz9npj8EhNgPK8MX+4Aqs+Hmib0+xDR6bPmGbi7YzTrLSVzZB+xj1gXWrfoQomQjjKwPJaDKAEdAjbYP1Ni3E9d97EG3q+cu4KkFd3SEXnnF9QBc7MZdl5Uu5FG6jd9gYyN4bz2WdsO2C4hOO94tmupENO3f7Bf/bAarNJOWNdKdgFDeGaXa3IHcci6X+CHdBmx9XR/2Y3YAbiNHJsLsdqTu4aibjE072GWywpVvfAPqzi6z/3UXzy02p/RrF5/ye8/8exOe5PSHDSBJfMj3ywZ8x//8Lxvw+yeqX5ycwovNe4mp9GvXD7lzKIvR3jUH10XPCe1dlf/0rr/z//63z9/vpTb4ww6xyLKfTkPbISfNP+wQ1p95sf6SfyxLaPJXJUf+Xsnf+v3Nz5/hrd8F/i5USJVl7a00E/h7vr/m+W3ofxvy35X4nef3Of6eD+svlf3tE3/7vr82Husv5/h7vufp4uq/Gpj4dzP73xr31x79a89iYGxesvrJDjDY6ddKUAL/0WCMIzTIKpFR/+394W/+bvw/dc5fR+n/rkMkVYvZd/S0yk426ef+jw77f63D7w7+p8796yz5v+oQMnia944Q2irykly0mFb6+3v/X+tQAtr5fw0Qz5+vU/wu7PdA/XW2/JJQ6t2wX28Q+zOm/OfR+mcZboW8+73Q/DZyvz/Avw3V743pb4P0qzATuj/L+GXB1f4M/mrBF4fH9DRXhiiR939YcKFXzBa/LDjJn3mlPDD+aZL83XJvgd+2+bfN/W1hf1tRUnMKFnXpn0CnzI0R22UVvN4PbiAavF5tMX5aKVU3VjJ17LTScveAEro08JcD+cvxt7RfPffrE/JnFWh/9+U/9efvj9nf0yn+S39HqC1rM5wfBX+w+l/v+9fMSk35pRXwR9m0f2b/PdY4v7NNxMgRCkj0RP9+EYOXj+cE5smTJzF4eLAFBPkFME8ICmDj4GBhCgjgYAkI4OFg4xLi4RIQ4eMRkhASEJMSEZJQkBCTU5KSUFCRkVLSUpDT0FFS0NJTUdIxUFPRM9HSMDLT0TKx0NMxszLQs7AzMbJxMDOxc7Iwc3CxsnByo1i59Hn19Az49PX1+Xh5DU7y8PAZ8PAYnjAwMDhx8qSuno7OWR09Pd6zenpaGCdPYp3ExDzDi55n5/j5zxnh4poQGBsb4xoZmRKbmBjyCwriYqPTcfn5CXCNjQlMiIlPGAoKavOeOcOrffbsGQwtLSzNkyfVsXBwtE5qampiaWhoYKmr46ipq6vhqKqqqOLj46ni4JxWQRNfVVX5ND4+EVBWxidSViYlIyJSIlJUJFIC4JQCGZkimYICmfypU1TyZGREZIqK54lNTcnPX7hwgYac3Izx4kWaCxcvmjOamV1kpKGxYWdjs+NgZ2djNDdnM7ewkKeiprZlt7GxtLKwsLVDp1vb2FizWVk5cTo6OjhycnJyODg4cNjbc9jZ21tYsbE5cXFyyspRU1PLycvLyFJTM0jLyFAzyMiwSjEwSEqhUAxS0tLiEiiUJEpCAsUtLi7FikJd4nZ15XLh5nbjvnRJnFtMzJXbxcXZhYtLlFtEhFtUTEzEXVjYXUhY2M0dHbuJiDhzOTmdJycmZsHFwOCaon7xr1mzhfPHrLk2SToUIzPiz4K/pVbQf4fVlpsxs6h2cfvrjSROxw8P3QO9AneME4KMllNX9VgMuW3V1VPeG4dNTUduOvtH7CRP6aIeyDsmpEsKCCS6lxwuVEl0pPeZ/OQe/vYy08aVKkl+kUCI2Ex0qeY+fsDr0rkSGRvuyjDNe3fD+7D9KefT+mRmMdJe5pOVbSsq+LwT4jAsxmF1WRCj8sxz7MkULH777MtjxzcVnpnf0nnrrQz5JHWK28q+kV/P70zy7eRf2Gol1pvynni97JhfKpOrKZIWfvqTlySQ5i4WwhRECnA8TXuyhr8rOFGbkYQP0FyKm7NfWxF3r6Af+lH+I8RpkpZGoYrr4lSg3/K4yHiAP0ooycLmDOEewUmxrIuqHt0+l4RT9VcHWT6e4X3kYGvXQL9335cgd5c+TslfzoOF0C7Ue+ep+5U8WtU9d2cnMt48uX4jN6kfQ5uSnZeWjKpciM516T+dU0yu82UjJA7qtXE1YhearE7xeJTedn72pqTfsvhapG4z+P7cZfwtx9l41jcZlOfPvXGFq/ZYbc9unPVUjBbLPKledZomwPIaJ7dPLjxwlPUVIbbt4On4dj4IP93KskXahafJ21r0fbRfeXJes+wshbLlOyNDJvbTBfH0VcvJUE6GxKzX6qdVfqflyzxSdVreaTUmoXVC00bQfne5uG5lyfxFyNQbmhf1oCf7hxNxdMnHeWxzPSKu9GKXYKveXPAlsE5xHOP5uPf1pd3rC4Um1CSCwjtVrxJRqYm6Lh+/5LQL6+f4B2UVqD5dscQyM2nId/XJfEpHTzJNFvbCQk1CQP1pXXGp3DvlVXf8omjCcO7BR9WbVeqlFDE9L0xpNpzCMztUL0i46jnz9Qyc52oucdAJd4j2GePuTmRKaBimWJY4Jzp0U7q+PC3mw7IrQ7Bo6CSq+5bKwyh7O90daremnStknM7X37JVgTKKzlazZsODUZuHKQgS2XYy1ELJMW5lgk7lZXFSRPVuuRIiUMOY/Tbejtac/iapq8jqtXkD1rMxr24/Jy6sKfGgfT7HExGlS5g0+VCU/PTt+BdYL0Ys4Xpb4YJw51tvtYtFYomqY0opX8d5KqAYjwZny8+LYcm63kWaez/YlX4qRaYIu0LmcObg4iv2JRGppQXD0cEnxOz7RqtUnjlmjTYEqGwdZpJaowxGDwRNiSI0TNqJ9PPraR6xKwwYvTv9TOPjezLShcB4pviDZ4/VXos/pim+ZLEqZz2VrVR0oeZ0jNpMScBb36gmb2XcMzcY5oZnDRl936K6J+RuivJrHcRYSyz2SFlkTH7gvtpwT7XwjcLsZ5FnuvHB0O6Nc4P897tD/kxVJ9wydFNoH8S+1KXNN0gbwpjjW0Ws8Sri1CtV3px9uBhA+0Ri5qRVffe2oQpHk/hoHH9zkyHyTeER6mfGIwFP2bZRZ3v/+cv8RHRyAV9zm70ywy6/T5LduJEeTU0tvlr/9PvH9TCSAm3GiWJCOqqH4sm7rLnbyGucBw3Z/eb+YTX3eSQs/HGk27Z9lE5FConGvlHV6lAQiPJVJgoIFmwltXSI2S+7kizMm+6HOyVrGX239sTdqSy7r6tZBg6spzkG6Ytm5LGUmoT5H8t1oIheb2mDMLPPPluN7DjN7w8PZ5zC9ndsHpcR5bTLnnWvIgtzKwIe9y+ELYQeXLBYVb191mI+oBn/ELN+11fLASNj5dciOKRoGPuvRfDj/7cI9kUBOj8W/Csv35QlBkwrqmR8WGhszma4OfdwIEbIvDdHt1c8t5tzmD/X3qzA2K2nymdcfvHazScr6kZWWVnv3utUhdGXkGnu5nzcZ6vrOStT9hOl+WK2nJCc7KA3RCIkwMufqgU8lHiightcz0u0Tyu07vf+UkOmndAHd1aBYqTP287Urt+gg8WS69rBvAyFqW/ZaB7f9b1vnNNrN5pU0ni/RRzsbelJ5SzF2lhZ1eA4xz5PKN1g9J/+GPPZ5MH6Mz0pBtrX2a2zd7xmfgb4SDRqeDN5XBzvwr+7yF6A59tawHVqiPEZv9SHt3hSstWnmossVDRNLPfGb+q3pEvn+exKN/gM0taqeNSWf+PyT10KqTPwTc0uwFwTd76wPsJ+/xqr7NJZirlFnYmknpphd+FevsgTHtak1tlreCNygZWnlnlKShIzhZRjpj2k5tk2sIrtjYqeLRhdmNLul13VjlBy+ZTx7PKV1Ypcdb57e6tnxbnFVe9eXXvX992yVPDMPaobJgus76KZB1+62w/45KMSYfBekPSMSeRC58T4bvhjHDkmha1UAfcdFpfQNlvU3FJYq8ajyoaXieaefmEOCGa9vGhj7gCVws/Dy8kl5FefsV4Ou192T4mX4lR326d4krxT2YWX+/lZd5NCktvnkp1lPE/HWIlW3FAovtxYRkIwmu7cORh+twj7pGgSm82js/RbDwdorgfnPqgvnM7Ses1EvF2MnlGij/vuRaumBHFVSOzrlRUJUTbLG+l4uuD1tt0rPWinYWYQ07x3jVc+KX+wF5PaXb9K5cm5dPEzkR1Ebg60rgPx74a2l6pJ7Q4o4ky/8MXNpodnnmYV9xpqLvGtjiQaydU877u18ZCBPqzWYVDkls1X90hVnw/2qRiEF/2+8Vgon7XEuZDsdn9u1MVoFdvjIW337UOUkPb2yJ2dcpwpecmTLol0vHPy7GM6D7TVUmue8KiXpOIlPjGJsE2QQGmPuDwrZnIQcaBgLIjzrSUy0+/aPt8c5Ddl3CGimBrxouiqtIlM21gTsa5utvv5HwRfJdLu07b2Tew6H+5429/UYl51MlSfmeZyJxTk2igPMPHf+4F7ekvosk1WlEZD/Te3x3VXUmYemm5rWqs3dX0jIRbgXwD414kfLlaE9IdOK3BTMopd7a4Ritr0PRPe8EpiqvDhTnLMCgGV34+iHSSboaJLbZ7g04ShWzbDXBlpXiaZlCzdmu+3d9LcLdOfJ07x7Cl8D6Sb/LpXEUHKU2VbcVPNuJ1DeiivbrSdgzSEOliih7q2aqTcwV07uLGQEym6/PHCvZN56nhcMSjTTZWFcydyQjEjnn9xJws5+KAzqXDh6scPQxiLOeMPzthY77YGL9mnl1DTXuI1Zt7cVvkeF32HzXpLUnRLuSWOWR2n/ov7EzF6fiK5jjcvz89ZLMXe5vPq7DmZz0jzmutj7uM2OzfFB7oz8ZVd6X6xhPX75YtasfFD6SCbtopuI5nkKpcHrW9DeRup56BDDq9VoxG3+AW6U4b92wpWnh/CbPDx73oIvdOop3roUZUdFL87rW+LT9LH6bGMP70eKfSCzixezTfS+ealmAw7yvQNAy9LTcoMmbQHC0K6Ob5pp+lsVAR4P1OMu2LNhPRprThgZKvyyp4v1LcM0IgMdL3b+cqs8lwrycw9wdLdBiIeBzOopBN2iPHktZONgGeQvAvaHHIsvc371wpYhPV7BVTsD9bpvsryZnuRzJGvOqvYzAyR5e+5/7bhydezUZWJ3fdJr1oOTNr6PhC++tXkuUZs6YHLvuj06CMBp7zc1rsXjI3N78XQUp89Y+RhmjfxY2q15M3s5tdPT/o063njmPSFeJbLPge8ZK3Vafgu7ugUYGUwk9W9Pm3xZExvRT27M+O9YtePN0lS84pdQX6XrU+9uHOC2GBDcO5iQ4X3V3/c298cR0+ydv3xsLR4q5Rr/+pfj+VaycmoVZvswYrp34/nicHlUZmS9O/rKyZb1pEJtUyPsZ/B29MfT5xbuuhh5/MWq7bC8VtBL+dwKnbED1cWfklbzX5C4/HorYlAGsbcgiu6srdWOrkV9KMijHYxP6fZ9wcDzN7zPHUv5nA7Gggb+249IV3LDKQkHJrCKApijH1aMqt1eYTTuZM1pefgW5lF6L5+nW1/4dXV2/izSTpG9TcY386RGG33tG55/dDiKqdGrZw68dL5samkZHze9bhulK+PeOb9Xofz8V+CmFk3Xmnf4YqplF9SeDV7Nc6Em/IO/xlaAcO1cjcf0amILE6hh9/nn1wJWys4dLqnxYQZTkcfuXby5uJCLuUb7ccFUk0vvHtcqOvbznIu2sa0i8sZqeXofv4YlVVl1MFp440iZW5W+zrvof3Vmns9t2cxYU44sYUsLtjyVU56SmY9a8rgq3eXI3vvPrrr/yMrX1q5k4S4eaiGNsGVJ65OncdX7+PpDy/PWPbcQmFnhMpXOs7frz7/9UdmdJRJiQ9HjHghXknkOC8jW0O+i21odEOMWGWmnsZGzHVx03bRoNncluuMTzYq4ybY33kOO/NHxZVZvg97cM+BoW26f8QV13evqc9Jfb9edPpu9dsO9aeXBrGSWtS+jQtdeJtB4luHq8vK+I3c6p5Fz2xarMN/scv/Uj8eBoYOZ2bWH84Y9/fkdhx0kxwOYIBXk1JtdeztRFNdD+xJikfyFlN36E8m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- Group
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- A group of Grasshopper objects
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- Group
- ᑐᑕ
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- Relay
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- A wire relay object
- 30377d3c-57fd-4ec7-9de3-54b95b3a7509
- true
- Relay
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- 6457973d-18aa-4d88-958b-85acd494ab86
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- Simple Mesh
- Create a mesh that represents a Brep as simply as possible
- true
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- Simple Mesh
- Simple Mesh
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- Brep to mesh, only breps with triangle or quad faces are supported.
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- Brep
- Brep
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- Mesh
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- Mesh
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- 4098ec7a-819a-4ced-9eee-86835d7e21c9
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- Weaverbird's Catmull-Clark Subdivision
- Calculates the type of mesh-based recursive subdivision described by Edwin Catmull and Jim Clark, at first in their 1978 paper. The resulting mesh always consists of quad faces.
Provided by Weaverbird 0.9.0.1.
- 2
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- 94698773-e34b-4d6a-ac31-6a2b9cabaed4
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- Weaverbird's Catmull-Clark Subdivision
- Weaverbird's Catmull-Clark Subdivision
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- The open or closed mesh, or closed curves list, to subdivide
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- Mesh/Curves
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- The number of subdividing iterations for each face
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- Level
- Level
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- {0}
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- Defines how to treat the naked edges
0: Fixed. Naked edges will not move or be modified.
1: Smooth. The naked edge will tend toward a spline.
2: Corner Fixed. Corners (2-sided vertices) will be fixed, while other naked vertices will tend toward a spline.
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- Smooth Naked Edges
- Smooth Naked Edges
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- The mesh after the subdividing process
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- Output Mesh/Curves
- Output Mesh/Curves
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- ba2d8f57-0738-42b4-b5a5-fe4d853517eb
- Deconstruct Mesh
- Deconstruct a mesh into its component parts.
- true
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- Deconstruct Mesh
- Deconstruct Mesh
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- Base mesh
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- Mesh vertices
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- Vertices
- Vertices
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- Mesh faces
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- Faces
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- Mesh vertex colours
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- Colours
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- Mesh normals
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- Normals
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- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
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- Pull Point
- Pull Point
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- Point to search from
- 00a77e54-a567-4ff5-9386-fce2c71d125d
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- Point
- Point
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- 6123bda8-5a08-4619-9c3c-d457a3a15fa2
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- Geometry that pulls
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- Geometry
- Geometry
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- Point on [G] closest to [P]
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- Closest Point
- Closest Point
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- Distance between [P] and its projection onto [G]
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- Distance
- Distance
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- e2c0f9db-a862-4bd9-810c-ef2610e7a56f
- Construct Mesh
- Construct a mesh from vertices, faces and optional colours.
- true
- 4214bc60-7b85-4968-9449-f2b31fe09985
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- Construct Mesh
- Construct Mesh
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- Vertices of mesh object
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- Vertices
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- Faces of mesh object
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- Faces
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- Optional vertex colours
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- Colours
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- Constructed mesh
- e2eb27fa-4759-4c6b-b0e2-999e4b9cb9f0
- true
- Mesh
- Mesh
- false
- 0
-
11927
30123
28
60
-
11941
30153
- 079bd9bd-54a0-41d4-98af-db999015f63d
- Fan+3
- Private Function appendprepend(ByVal i As Integer)
Dim srsEnum As IEnumerable(Of Integer) = Enumerable.Range(0, i + 1)
Dim arrVal As New list(Of Integer)
arrVal = srsEnum.tolist()
arrVal.add(0)
arrVal.insert(0, i)
Return arrVal.toarray()
End Function
Private Function matchDbl(ByVal a As list(Of Double), ByVal t As Integer)
Dim i,k As Integer
k = a.count()
For i = 0 To ((t + 1) - k) - 1 Step 1
a.add(a.item(k - 1))
Next
Return a
End Function
Private Function matchClr(ByVal a As list(Of Color), ByVal t As Integer)
Dim i,k As Integer
k = a.count()
For i = 0 To ((t + 1) - k) - 1 Step 1
a.add(a.item(k - 1))
Next
Return a
End Function
Private Function evalP(ByVal op As point3d, ByVal tp As Point3d, ByVal t As Double)
Return New point3d(op + (tp - op) * t)
End Function
Private Function evalV(ByVal ov As vector3d, ByVal tv As vector3d, ByVal t As Double)
Return New vector3d(ov + (tv - ov) * t)
End Function
Private Function evalN(ByVal u As Double, ByVal v As Double, ByVal t As Double)
Return u + (v - u) * t
End Function
Private Function avgVec(ByVal v() As vector3f)
Dim i As Integer
Dim tv As Vector3d
For i = 0 To ubound(v) Step 1
tv += v(i)
Next
tv /= (ubound(v) + 1)
tv.Unitize()
Return New vector3f(tv.X, tv.Y, tv.Z)
End Function
Private Function roundClr(ByVal r As Integer, ByVal g As Integer, ByVal b As Integer, ByVal i As Integer)
r = CInt(r / i)
g = CInt(g / i)
b = CInt(b / i)
If r > 255 Then r = 255 Else If r < 0 Then r = 0
If g > 255 Then g = 255 Else If g < 0 Then g = 0
If b > 255 Then b = 255 Else If b < 0 Then b = 0
Return color.FromArgb(r, g, b)
End Function
Private Function avgClr(ByVal c() As color)
Dim r,g,b As Integer
Dim i,k As Integer
k = ubound(c) + 1
For i = 0 To k - 1 Step 1
r += CInt(c(i).R)
g += CInt(c(i).G)
b += CInt(c(i).B)
Next
r = CInt(r / k)
g = CInt(g / k)
b = CInt(b / k)
If r > 255 Then r = 255 Else If r < 0 Then r = 0
If g > 255 Then g = 255 Else If g < 0 Then g = 0
If b > 255 Then b = 255 Else If b < 0 Then b = 0
Return color.FromArgb(r, g, b)
End Function
Private Function evalC(ByVal oc As color, ByVal tc As color, ByVal t As Double)
Dim r,g,b As Integer
r = CInt(CInt(oc.R) + (CInt(tc.R) - CInt(oc.R)) * t)
g = CInt(CInt(oc.G) + (CInt(tc.G) - CInt(oc.G)) * t)
b = CInt(CInt(oc.B) + (CInt(tc.B) - CInt(oc.B)) * t)
If r > 255 Then r = 255 Else If r < 0 Then r = 0
If g > 255 Then g = 255 Else If g < 0 Then g = 0
If b > 255 Then b = 255 Else If b < 0 Then b = 0
Return color.FromArgb(r, g, b)
End Function
- true
- Replaces selected faces of a mesh or the interior of a curve with a frame around the edge by creating 3 new points along the edge and removing the face's vertex.
-
251
91
- true
-
iVBORw0KGgoAAAANSUhEUgAAABgAAAAYCAYAAADgdz34AAAABGdBTUEAALGPC/xhBQAAAAlwSFlzAAAOvAAADrwBlbxySQAABHhJREFUSEvNlXlQlGUcx01hBgHLYYXAOAaEXZblFiQFARFSFGE3d9ldgpC4lEvlEhY0iNtIrpBzWA6VQ7lW0RrQ4ajAKGVwLJsiQQtQKQIiEhq/PS8v/tExJsUffWa+85vnd3zf93nfd95n1f8NeQaDEULianq5wmhpabnb2NoNq6ur715KrSjKW7ZslfH4ghtWNjbNZK1Ip1cIfVPjg1xPz37vgIAPuZ7Cz3SN2W8tlVaEWB01zXucTcxRIz3Wdxx95pi26sZhkj9Kl/8bu7a9qI1Wjhf6zALQZeKH6yQ2G4lhs04TpO5It/071pgqqt3utA5ClaUYM7wsjLqnYNojE1JzITo3B8JQgTFA+l6g25dPhNTKC7M++cjeLsZwcD7GwoowFJiDbFsR5rzyUGzGp3YRRLcvjw1uG41+nA4oxM9xNTgrisK1iJOYz7+C9pAM1AmjMBNdick38+CsZviQ9K+nx56foqqdAUBSI2ZOyTCQKkVF2HGgbRBlhxJwK0WK6awmPJHUodTOh9pFDj32fJj6sWyf1HOPoFAQhrsFTUDnVyiLT8ewrBvlcWnA1S/xTXY9CngH0eAWDm896wUyZ0iP/wMaCuuuff1GJuZTm3A9qRQ5h47hg+Kz6K5tRXFaNnrOtaAtvxI5QTH4NLEI84n1uL0/CQx5pStLFs+El2G6D7+FSzGVfgG40A/0DaG9phGS0KOwMjHD8YhoXK0itc47wJmPMHniHBYCS/A26zXqUbnSNn+P8qvKrwyNuJ7ATZ80dIRmoDEmCzVJ2bhcdR4xQaFQeWk94kMOo62iDtWSTDQeSUdHYCpuCpPxrVMcrBXV7xCftbTdXwkI1LCC1EKEcmd/tPgmoje5BD/IejHQ3IGK7HzUF5Sh4t18DDa241FDFz6WFKJJfAxl9r6Qmgjg97IFtQtv2u5PrFZSiPLVsMSUcxImfHMxlXAGCyUdGCqVISskBlOffIGGnBJM9txCZlAkhotayGd7GT9FS/FIeBKTDokQa5hhtdLasCXLP6Bm7+JySVNHZ7yV/AYmuBl4EHIa9yRSpPD8MVJ6Eb9c7EdZZDJ+lfVj6P0mpHj44X5sOcb98zCx5x2cZwmguUlvzMHFpZX4qdC2S7DY7ES+UPy5I29ftxNDb37CMRGjnllIsROgP/wUZnMv4UFuC0oOROMhibPvydAbnIXUbXyM8dIwbheH7Rt0H+/kc7v4AsENfSYzdsma3Lqa2lbHHTsG+SJRr39QcKe2KWfktL4bak1E6N0dDURUYy6aKKEW1a9H4DGJc5GVQIgUPU6HUW8sQp6eK3TNOXepeYGnuM/ewWmAnH5WTy8gZrLZlQYGrGo2myPVYRmUK66R+96dwUIqcxfijVyQYL4HEsu94OpZIsHSDRJTV8QZOiNV3wV7VZhQlJO7r8NilRmy2VLKh8lkV6qqqgoWL0CgTidqcYDIh8iLKJwoaRmiXiw1R81TPvuJFIgW2UxEFakkJT6RB5HbMsQlouaeelB+FkSLyBPJrbxWyf8OYp1ITVZZkf8AAAAASUVORK5CYII=
- d83cd624-e7c4-45b5-b4d0-2a3985556ca5
- true
- Fan+3
- Fan+3
- true
- 0
-
Component.Params.Input(0).Name = "Mesh or Curve"
Component.Params.Input(0).Description = "Open or closed mesh or curve"
Component.Params.Input(1).Name = "Index [Face]"
Component.Params.Input(1).Description = "An optional integer or list of integers which specify the faces to be modified if the input is a mesh. If no value is supplied then all faces will be modified"
Component.Params.Input(2).Name = "Along Edge"
Component.Params.Input(2).Description = "Evaluates a new vertex along the input geometry's edge"
Component.Params.Input(3).Name = "Close"
Component.Params.Input(3).Description = "If true then additional faces and if needed vertices will be added to the mesh, covering the complete areas of the existing mesh"
Component.Params.Input(4).Name = "Color [Vertex]"
Component.Params.Input(4).Description = "(If applied to a mesh a list of colors corresponding to each mesh face, if applied to a curve, a list of colors corresponding to each control point plus an additonal color value for the new averaged center"
Component.Params.Output(1).Name = "Mesh"
Component.Params.Output(1).Description = "If successful, a valid mesh"
If G IsNot Nothing Then
Dim bM, bP,bmC,biC As Boolean
bM = g.ObjectType = ObjectType.Mesh
bP = g.ObjectType = ObjectType.Curve
If (bM Or bP) Then
Dim msh As New mesh
Dim crv As curve
Dim av As point3d
Dim ac As color
Dim h,j,jj,k,u,v,w As Integer
Dim cv,cf,ce As Integer
Dim x(),y() As Integer
Dim mv,fv,ep,tv As New list(Of Point3d)
Dim mev As New dictionary(Of String, Integer)
Dim mf As Rhino.Geometry.Collections.MeshFaceList = Nothing
Dim mtv As Rhino.Geometry.Collections.MeshTopologyVertexList = Nothing
Dim mte As Rhino.Geometry.Collections.MeshTopologyEdgeList = Nothing
Dim ev As New list(Of vector3d)
Dim ed,en As New list(Of Double)
Dim mc,ec,tc,cc,fc As New list(Of color)
Dim xf As New list(Of meshface)
If clr.count() = 0 Then clr.add(color.LightGray) Else biC = True
If bm Then
'Start Deconstruct if Mesh
msh = g
If msh.Normals.Count() = 0 Then msh.Normals.ComputeNormals()
If msh.FaceNormals.Count() = 0 Then msh.FaceNormals.ComputeFaceNormals()
If i.count() = 0 Then I = Enumerable.Range(0, msh.Faces.Count()).ToList()
mv = msh.Vertices().ToPoint3dArray().tolist()
mte = msh.TopologyEdges()
mtv = msh.TopologyVertices()
mf = msh.Faces()
cf = I.Count() - 1
ce = mte.count() - 1
'Assign Colors
If msh.VertexColors.Count() < 1 Then
msh.VertexColors.CreateMonotoneMesh(color.LightGray)
bmC = biC
Else
bmC = True
End If
'Assign fake edges
mc = msh.VertexColors().ToArray().ToList()
Else
'Start Deconstruct if Curve
crv = g
I.clear()
I.add(0)
Dim nc As nurbscurve
Dim pc As polyline
Dim nps As Rhino.Geometry.Collections.NurbsCurvePointList
nc = crv.ToNurbsCurve()
nps = nc.Points
pc = nc.Points.ControlPolygon
If (Not pc.IsClosed) Then pc.add(pc(0))
av = pc.CenterPoint
msh.Vertices.AddVertices(pc.ToArray())
msh.faces.addfaces(pc.TriangulateClosedPolyline())
msh.Vertices.Remove(pc.count() - 1, True)
msh.FaceNormals.ComputeFaceNormals()
mv = msh.Vertices.ToPoint3dArray().tolist()
mte = msh.TopologyEdges()
mtv = msh.TopologyVertices()
'Assign Colors
If bic Then bmC = True
mc = clr
If (clr.count() - 1) < (mv.count() - 1) Then mc = matchClr(mc, mv.count() - 1)
ac = avgClr(mc.toarray())
cf = 0
End If
cv = mv.count() - 1
ce = mte.count() - 1
x = appendprepend(cv)
'Match variables and colors to vertex count
If (T0.count() - 1) < cv Then T0 = matchDbl(T0, cv)
If (clr.count() - 1) < cv Then clr = matchClr(clr, cv)
If biC Then fc = clr Else fc = mc
'Edge based vertices
k = 0
For j = 0 To mte.count() - 1 Step 1
If (bm Or (bp And (mte.GetConnectedFaces(j).Count() < 2))) Then
u = mtv.MeshVertexIndices(mte.GetTopologyVertices(j).I)(0)
v = mtv.MeshVertexIndices(mte.GetTopologyVertices(j).J)(0)
ep.add(evalP(mv(u), mv(v), T0(u) / 2))
ec.add(evalC(mc(u), mc(v), T0(u) / 2))
mev.add(u & "," & v & "," & 0, k)
ep.add(evalP(mv(u), mv(v), 0.5))
ec.add(evalC(mc(u), mc(v), 0.5))
mev.add(u & "," & v & "," & 1, k + 1)
mev.add(v & "," & u & "," & 1, k + 1)
ep.add(evalP(mv(v), mv(u), T0(v) / 2))
ec.add(evalC(mc(v), mc(u), T0(v) / 2))
mev.add(v & "," & u & "," & 0, k + 2)
k += 3
End If
Next
'Face based vertices
Dim xv(),mt(),ei() As Integer
Dim xc() As color
Dim xn As Double
ReDim ei(3)
u = 0
v = ep.count() + cf + 1
For jj = 0 To I.count() - 1 Step 1
Dim tcv As New point3d
j = I(jj)
w = v + tv.count()
xn = 0
If bm Then
If mf(j).isquad() Then h = 4 Else h = 3
ReDim xv(h - 1)
ReDim xc(h - 1)
mt = mf.GetTopologicalVertices(j)
For k = 0 To h - 1 Step 1
xv(k) = mtv.MeshVertexIndices(mt(k))(0)
xc(k) = fc(xv(k))
Next
av = mf.GetFaceCenter(j)
ac = avgClr(xc)
Else
h = mv.count()
xv = Enumerable.Range(0, h).ToArray()
End If
y = appendprepend(h - 1)
Dim tev As New list(Of Integer)
For k = 1 To h Step 1
ei(0) = mev.item(xv(y(k)) & "," & xv(y(k + 1)) & "," & 0)
ei(1) = mev.item(xv(y(k)) & "," & xv(y(k + 1)) & "," & 1)
ei(2) = mev.item(xv(y(k + 1)) & "," & xv(y(k)) & "," & 0)
ei(3) = mev.item(xv(y(k)) & "," & xv(y(k - 1)) & "," & 0)
'Define new faces
tev.add(ei(1))
xf.add(New meshface(ei(0), ei(1), ep.count() + jj))
xf.add(New meshface(ei(1), ei(2), ep.count() + jj))
xf.add(New meshface(ei(3), ei(0), ep.count() + jj))
If c Then xf.add(New meshface(ei(0), ei(3), v + xv(y(k))))
Next
fv.add(av)
cc.add(ac)
Next
Dim om As New mesh
om.Vertices.AddVertices(ep.toarray())
If bmC Then om.VertexColors.AppendColors(ec.toarray())
om.Vertices.AddVertices(fv)
If bmC Then om.VertexColors.AppendColors(cc.toarray())
If c Then
om.Vertices.AddVertices(mv)
If bmC Then om.VertexColors.AppendColors(mc.toarray())
End If
om.Faces.AddFaces(xf.toarray())
If i.count() > 1 Then om.Vertices.CullUnused()
A = om
End If
End If
- Imports System.IO
Imports System.Linq
Imports System.Data
Imports System.Drawing
Imports System.Reflection
Imports System.Windows.Forms
Imports System.Xml
Imports System.Xml.Linq
Imports Microsoft.VisualBasic
Imports System.Runtime.InteropServices
Imports Rhino.DocObjects
Imports Rhino.Collections
Imports GH_IO
Imports GH_IO.Serialization
-
11680
30349
72
104
-
11719
30401
- 5
- 84fa917c-1ed8-4db3-8be1-7bdc4a6495a2
- 84fa917c-1ed8-4db3-8be1-7bdc4a6495a2
- 84fa917c-1ed8-4db3-8be1-7bdc4a6495a2
- 84fa917c-1ed8-4db3-8be1-7bdc4a6495a2
- 84fa917c-1ed8-4db3-8be1-7bdc4a6495a2
- 2
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- true
- Script Variable G
- 02277887-37da-43cd-9045-2ab622639ff1
- true
- G
- G
- true
- 0
- true
- 979517f2-242e-4e4d-bb88-dd2fc0fa6486
- 1
- c37956f4-d39c-49c7-af71-1e87f8031b26
-
11682
30351
25
20
-
11694.5
30361
- 1
- true
- Script Variable I
- 8bd25a8a-91d9-4eb6-9e52-e603199172cb
- true
- I
- I
- true
- 1
- true
- 0
- efe48ae7-2987-421b-a33a-1f7be1c3f050
-
11682
30371
25
20
-
11694.5
30381
- 1
- true
- Script Variable T0
- f73ae574-ad64-4c32-ae83-7e8f37868e39
- true
- T0
- T0
- true
- 1
- true
- 0
- 8e991e99-5fb8-41e1-928d-1bba8fb9f7d7
-
11682
30391
25
20
-
11694.5
30401
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_Number
- 0.00390625
- true
- Script Variable C
- 541f6166-b28c-4953-9587-28afbe302f37
- true
- C
- C
- true
- 0
- true
- 0
- 3cda2745-22ac-4244-9b04-97a5255fa60f
-
11682
30411
25
20
-
11694.5
30421
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_Boolean
- false
- 1
- true
- Script Variable clr
- 14fbe32e-4185-4da3-b3dc-3e17bbd88a35
- true
- clr
- clr
- true
- 1
- true
- 0
- 24b1d1a3-ab79-498c-9e44-c5b14607c4d3
-
11682
30431
25
20
-
11694.5
30441
- 1
- Print, Reflect and Error streams
- ee0a4ed3-d78c-40ef-847e-90017eeb7dc0
- true
- out
- out
- false
- 0
-
11731
30351
19
50
-
11740.5
30376
- Output parameter A
- 16e90cf5-2746-46b7-bcf2-2c1b43dfacf2
- true
- A
- A
- false
- 0
-
11731
30401
19
50
-
11740.5
30426
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 5fa3dc85-5552-4797-8ef8-852841306048
- true
- Relay
- false
- e2eb27fa-4759-4c6b-b0e2-999e4b9cb9f0
- 1
-
11840
29979
40
16
-
11860
29987
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- cfcc5b9b-e104-430a-a736-e9cfea660979
- true
- Relay
- false
- 979517f2-242e-4e4d-bb88-dd2fc0fa6486
- 1
-
11684
30532
40
16
-
11704
30540
- f12daa2f-4fd5-48c1-8ac3-5dea476912ca
- Mirror
- Mirror an object.
- true
- 8ca2ca44-079d-4e4e-83d9-78c3dacd6aa1
- true
- Mirror
- Mirror
-
11571
29362
305
61
-
11812
29393
- Base geometry
- f0451bfd-6b26-4476-a72d-80f6e314bf50
- true
- Geometry
- Geometry
- true
- 8ad5c4e2-d150-4afc-a797-fd8b0b4ef95e
- 1
-
11573
29364
227
20
-
11686.5
29374
- Mirror plane
- bdda47f8-b994-4250-b1b5-b26f29b09a23
- true
- Plane
- Plane
- false
- 0
-
11573
29384
227
37
-
11686.5
29402.5
- 1
- 1
- {0}
-
0
0
0
0
1
0
-0.707106781186548
0
0.707106781186547
- Mirrored geometry
- 3b6274c6-0db1-455b-9b83-56ddcc437d14
- true
- Geometry
- Geometry
- false
- 0
-
11824
29364
50
28
-
11849
29378.25
- Transformation data
- c350c7c4-7044-46b5-b160-4695143dbec2
- true
- Transform
- Transform
- false
- 0
-
11824
29392
50
29
-
11849
29406.75
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
- b05b3657-d031-4156-a0f9-5d9aa404e206
- true
- Merge
- Merge
-
11945
29462
90
64
-
11990
29494
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2
- Data stream 1
- 343f6de4-eecf-4785-b593-7aaf75b8cc9e
- true
- false
- Data 1
- D1
- true
- 3b6274c6-0db1-455b-9b83-56ddcc437d14
- 1
-
11947
29464
31
20
-
11962.5
29474
- 2
- Data stream 2
- bd4c1892-0bf0-4db4-a530-98e1456b3833
- true
- false
- Data 2
- D2
- true
- 8ad5c4e2-d150-4afc-a797-fd8b0b4ef95e
- 1
-
11947
29484
31
20
-
11962.5
29494
- 2
- Data stream 3
- d82bb646-e7ea-4620-a4e6-a21543407c90
- true
- false
- Data 3
- D3
- true
- 0
-
11947
29504
31
20
-
11962.5
29514
- 2
- Result of merge
- feee9bed-0a55-4a71-bbe4-7083862058a6
- true
- Result
- Result
- false
- 0
-
12002
29464
31
60
-
12017.5
29494
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- 4b3c5c37-6f6a-4f2d-90a7-ad7b24cb571c
- true
- Polar Array
- Polar Array
-
12065
29346
207
84
-
12192
29388
- Base geometry
- 035d7fb3-c2cf-4600-bfd9-842d930e39d5
- true
- Geometry
- Geometry
- true
- feee9bed-0a55-4a71-bbe4-7083862058a6
- 1
-
12067
29348
113
20
-
12123.5
29358
- Polar array plane
- 1786f70d-6c1f-4d8e-8097-e7d5e5b74c63
- true
- Plane
- Plane
- false
- 8466f10c-3993-400e-8742-e7e3f179651f
- 1
-
12067
29368
113
20
-
12123.5
29378
- 1
- 1
- {0}
-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
- f62765ec-b9fe-48ee-8fff-50fd1b505801
- true
- Count
- Count
- false
- 0
-
12067
29388
113
20
-
12123.5
29398
- 1
- 1
- {0}
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- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
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12204
29388
66
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12229
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- A wire relay object
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11798
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40
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11818
29535
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- Join a number of Breps together
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- Brep Join
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29834
92
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30
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29836
34
20
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13113
29856
34
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13130
29866
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255;255;255;255
- A group of Grasshopper objects
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12602
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40
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- Group
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255;255;255;255
- A group of Grasshopper objects
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- Extract the end points of a curve.
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84
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28471
- Curve to evaluate
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30
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28451
26
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28461
- Curve end point
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28471
26
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13646
28481
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- Create a polyline connecting a number of points.
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28382
116
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50
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28394
- Close polyline
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13592
28404
50
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13617
28414
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- Resulting polyline
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28384
38
40
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13685
28404
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- Create a polyline connecting a number of points.
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13597
28507
116
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13661
28529
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13599
28509
50
20
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13624
28519
- Close polyline
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13599
28529
50
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13624
28539
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13673
28509
38
40
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13692
28529
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
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- Merge a bunch of data streams
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28424
90
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31
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- 2
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31
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31
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13739
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31
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13754.5
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28426
31
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- Join as many curves as possible
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116
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53
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- Preserve direction of input curves
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53
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- Joined curves and individual curves that could not be joined.
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35
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- Measure the length of a list.
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97
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19
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- Number of items in L
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50
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- c75b62fa-0a33-4da7-a5bd-03fd0068fd93
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- Measure the length of a curve.
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92
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- Curve to measure
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30
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- Curve length
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34
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70
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- Item to divide (dividend)
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11
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- Item to divide with (divisor)
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11
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31
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85
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- Item to divide (dividend)
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26
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- Item to divide with (divisor)
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26
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31
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122
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66
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- Pipe radius
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66
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66
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66
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66
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66
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28
120
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150
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- Curve to explode
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57
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57
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65
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65
20
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94
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38
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- Mesh join result
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28
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218
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- The open or closed mesh
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110
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- Weld threshold value for Vertices
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110
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80
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- The constructed mesh
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80
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- The material override
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255;255;255;255
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- Colour of the diffuse channel
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81
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255;255;255;255
- Colour of the specular highlight
- 28cee4bd-1a24-43e1-868f-385a08024a2e
- true
- Specular
- Specular
- false
- 0
-
14332
28344
81
20
-
14372.5
28354
- 1
- 1
- {0}
-
255;255;255;255
- Emissive colour of the material
- ef1c2dee-aefd-4179-97bf-7712dadef0fe
- true
- Emission
- Emission
- false
- 0
-
14332
28364
81
20
-
14372.5
28374
- 1
- 1
- {0}
-
255;0;0;0
- Amount of transparency (0.0 = opaque, 1.0 = transparent
- 426b9a64-97a9-44e8-9e95-0216b51823b8
- true
- Transparency
- Transparency
- false
- 0
-
14332
28384
81
20
-
14372.5
28394
- 1
- 1
- {0}
- 0
- Amount of shinyness (0 = none, 1 = low shine, 100 = max shine
- 1796cfa4-59c9-4dd0-ab45-9d85a728a169
- true
- Shine
- Shine
- false
- 0
-
14332
28404
81
20
-
14372.5
28414
- 1
- 1
- {0}
- 0
- Resulting material
- 326fbc08-dea2-43c0-83cd-c5852522fa30
- true
- Material
- Material
- false
- 0
-
14437
28324
40
100
-
14457
28374
- 12bb406c-41bc-4c8a-9b96-6924df61b6d6
- d2580c41-5c48-4997-87c5-b6333b5e21d7
- Mesh Rebuild Normals
- Rebuilds Mesh Normals
- true
- 4ad1e8d2-5eec-4a0b-ab32-27566d3371b2
- true
- Mesh Rebuild Normals
- Mesh Rebuild Normals
-
14267
28159
84
28
-
14309
28173
- The Input Mesh
- 67d0048a-9807-4193-bec0-59a715e5ae19
- true
- Mesh
- Mesh
- false
- b013ce48-f199-40ec-bce6-4f6f401e0259
- 1
-
14269
28161
28
24
-
14283
28173
- The Mesh with Rebuilt Normals
- 4c36b0a7-9a92-4045-9c7b-9705ffc8e3a1
- true
- Mesh
- Mesh
- false
- 0
-
14321
28161
28
24
-
14335
28173
- 4bfe1bf6-fbc9-4ad2-bf28-a7402e1392ee
- c2ea695e-1a09-6f42-266d-113498879f60
- MultiPipe
- Create a branching pipe around a network of lines/curves
- true
- e65bd057-1477-4024-bf3f-a43c107821f5
- true
- MultiPipe
- MultiPipe
-
14427
27765
186
184
-
14576
27857
- 1
- The curves to pipe. Also accepts meshes
- 9d5ac057-127f-4e4b-b6df-8548a8e2f2de
- true
- Curves
- Curves
- false
- c6bade99-c83e-413c-befb-c3d58ce01183
- 1
-
14429
27767
135
20
-
14504.5
27777
- 1
- Pipe radius. If one value given, it is applied to all. Alternatively, provide a list of radii corresponding to each point in SizePoints
- 8799a98a-0c75-4383-b675-a8bdd2e6b449
- X*65536
- true
- NodeSize
- NodeSize
- false
- d2521a95-eb69-45eb-8202-b014e1e92713
- 1
-
14429
27787
135
20
-
14504.5
27797
- 1
- 1
- {0}
- 0.5
- 1
- If you are supplying multiple radii for NodeSize, these points identify which node to set as which radius. If only some of the nodes have their radius set this way, the values will be interpolated across the shape
- 176f6124-ddbd-40b8-97e7-372416d6976a
- true
- SizePoints
- SizePoints
- true
- 0
-
14429
27807
135
20
-
14504.5
27817
- The distance of the first edge loop away from the node as a multiplier of NodeSize. If this is set to zero, no intermediate edge loop is added, to give a smoother shape.
- 4833559f-205f-4c7b-8c61-5a9d655a6a5d
- true
- EndOffset
- EndOffset
- false
- 0
-
14429
27827
135
20
-
14504.5
27837
- 1
- 1
- {0}
- 1
- The size of the struts between nodes as a multiplier of NodeSize. <1 gives tapering struts, >1 gives bulging struts
- 13260dff-63c9-4a5a-a106-7475f418b115
- true
- StrutSize
- StrutSize
- false
- 0
-
14429
27847
135
20
-
14504.5
27857
- 1
- 1
- {0}
- 1
- Approximate spacing of edge loops along each strut. If set to zero, no additional edge loops are added
- 441666d9-3257-4d33-94db-64e10261e09e
- true
- Segment
- Segment
- false
- 0
-
14429
27867
135
20
-
14504.5
27877
- 1
- 1
- {0}
- 0
- When the input to 'Curves' are smooth curves, this sets the maximum angle between consecutive segments when discretizing
- c77d7fd1-e082-41c9-ae77-a131386c9277
- true
- KinkAngle
- KinkAngle
- false
- 0
-
14429
27887
135
20
-
14504.5
27897
- 1
- 1
- {0}
- 90
- If >0 this attempts to fit a cube at each node. Should be a value between 0 and 1, where 0 = never, and 1 = always, depending on how close to orthogonal its connected lines are.
- 1cdffb78-f04a-4d16-9fed-7de9da78bb39
- true
- CubeFit
- CubeFit
- false
- 0
-
14429
27907
135
20
-
14504.5
27917
- 1
- 1
- {0}
- 0
- Cap option - 0:None, 1:Round, 2:Flat
- 5811a0ea-ed73-4508-ab04-c5f12074a47b
- true
- Caps
- Caps
- true
- 0
-
14429
27927
135
20
-
14504.5
27937
- 1
- 1
- {0}
- 1
- Resulting Pipe SubD
- 1867f002-ba43-453d-9003-2fa07903686d
- true
- Pipe
- Pipe
- false
- 0
-
14588
27767
23
180
-
14599.5
27857
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
- d98270ba-9afb-47d3-9937-cf8259edcdee
- true
- Merge
- Merge
-
13791
28678
90
84
-
13836
28720
- 4
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2
- Data stream 1
- 86ac1872-92ab-4b63-a9e4-484713be52be
- true
- false
- Data 1
- D1
- true
- 960f7236-e5a9-422d-a2d2-dbf7ecde4556
- 1
-
13793
28680
31
20
-
13808.5
28690
- 2
- Data stream 2
- 179555f5-43af-48e9-9fc2-4f3b7acfb0fe
- true
- false
- Data 2
- D2
- true
- 0
-
13793
28700
31
20
-
13808.5
28710
- 2
- Data stream 3
- fcc88034-d9de-4584-9e6a-4b7aaab42489
- true
- false
- Data 3
- D3
- true
- c4c58973-5656-4a93-b5f4-7f922145a19f
- 1
-
13793
28720
31
20
-
13808.5
28730
- 2
- Data stream 4
- 65b533b7-98c2-47f6-a1cd-017b3924e9a2
- true
- false
- Data 4
- D4
- true
- 0
-
13793
28740
31
20
-
13808.5
28750
- 2
- Result of merge
- 64bc1acc-a9db-4735-b25d-7fc33d153fd3
- true
- Result
- Result
- false
- 0
-
13848
28680
31
80
-
13863.5
28720
- 8073a420-6bec-49e3-9b18-367f6fd76ac3
- Join Curves
- Join as many curves as possible
- true
- fd92a202-6283-4250-8b87-a63ec2749b47
- true
- Join Curves
- Join Curves
-
13923
28753
116
44
-
13990
28775
- 1
- Curves to join
- 81a540c7-0c42-4b17-ae37-fcc96a189b33
- true
- Curves
- Curves
- false
- 64bc1acc-a9db-4735-b25d-7fc33d153fd3
- 1
-
13925
28755
53
20
-
13951.5
28765
- Preserve direction of input curves
- 8c16c48d-153e-4180-ab2f-c3f6b58158c7
- true
- Preserve
- Preserve
- false
- 0
-
13925
28775
53
20
-
13951.5
28785
- 1
- 1
- {0}
- false
- 1
- Joined curves and individual curves that could not be joined.
- 54ebf683-fd9d-4ded-8395-0a2c3898d0ef
- true
- Curves
- Curves
- false
- 0
-
14002
28755
35
40
-
14019.5
28775
- c3f9cea5-6fd4-4db5-959b-08cd08ed9fe1
- Simple Mesh
- Create a mesh that represents a Brep as simply as possible
- true
- cdeb0ed4-1a13-4341-9034-684797145956
- true
- Simple Mesh
- Simple Mesh
-
14130
28639
81
28
-
14169
28653
- Brep to mesh, only breps with triangle or quad faces are supported.
- 3948c631-d998-4834-bfdc-3fc92eb3b4ed
- true
- Brep
- Brep
- false
- 0
-
14132
28641
25
24
-
14144.5
28653
- Mesh
- 49844cd2-dce1-4c0c-bd49-b5e0b6dd8e38
- true
- Mesh
- Mesh
- false
- 0
-
14181
28641
28
24
-
14195
28653
- 9266a2bb-918f-4675-9c91-f67d0dd33eac
- Quadrangulate
- Quadrangulate as many triangles as possible in a mesh
- true
- 8665abfd-c7fc-4786-bc40-b494c4bfa4bc
- true
- Quadrangulate
- Quadrangulate
-
14130
28558
148
64
-
14234
28590
- Mesh to quadrangulate
- 2f0e53af-4c1f-4ce1-bb65-8ce06ec8be50
- true
- Mesh
- Mesh
- false
- 54ebf683-fd9d-4ded-8395-0a2c3898d0ef
- 1
-
14132
28560
90
20
-
14177
28570
- Angle threshold. Triangles that exceed this kink-angle will not be merged.
- 7dd61ecc-f1dd-424a-958c-4cdac6b8c9e0
- true
- Angle
- Angle
- false
- 0
-
14132
28580
90
20
-
14177
28590
- 1
- 1
- {0}
- 0.034906585039886591
- Ratio threshold. Quads that have a ratio (shortest diagonal/longest diagonal) that exceed the threshold, will not be considered.
- d6e66e82-f7a2-44db-84b9-4e87f8830fd1
- true
- Ratio
- Ratio
- false
- 0
-
14132
28600
90
20
-
14177
28610
- 1
- 1
- {0}
- 0.875
- Quadrangulated mesh (not all triangles are guaranteed to be converted).
- a7da4a92-991c-4900-b5d1-360021364e54
- true
- Mesh
- Mesh
- false
- 0
-
14246
28560
30
30
-
14261
28575
- Number of triangles that were quadrangulated
- 9700fcbf-be9e-450e-b55e-ba2b4a83e357
- true
- Count
- Count
- false
- 0
-
14246
28590
30
30
-
14261
28605
- 4c0d75e1-4266-45b8-b5b4-826c9ad51ace
- 00000000-0000-0000-0000-000000000000
- Divide Curves on Intersects
- Divide curves on all of their intersects.
- true
- 2f177179-4697-4a93-a401-219c588e7391
- true
- Divide Curves on Intersects
- Divide Curves on Intersects
-
14066
28754
174
44
-
14193
28776
- 1
- curves to be divided
- e220dfce-a878-44d3-8a16-63de991c5b32
- true
- curves
- curves
- false
- 64bc1acc-a9db-4735-b25d-7fc33d153fd3
- 1
-
14068
28756
113
20
-
14124.5
28766
- ZeroTolerance
- 00c0f45e-ba64-4d33-9e88-f6c1deb34897
- true
- Tolerance
- Tolerance
- false
- 0
-
14068
28776
113
20
-
14124.5
28786
- 1
- 1
- {0}
- 4.768E-07
- 1
- aligned curves
- 6da19130-89a1-437b-b23f-cb65a54edfae
- true
- curves
- curves
- false
- 0
-
14205
28756
33
40
-
14221.5
28776
- 59daf374-bc21-4a5e-8282-5504fb7ae9ae
- List Item
- 0
- Retrieve a specific item from a list.
- true
- 2f9c982a-f0ff-467e-ac38-6065e3546417
- true
- List Item
- List Item
-
14137
28811
77
64
-
14194
28843
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- cb95db89-6165-43b6-9c41-5702bc5bf137
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- Base list
- fec5ed95-cdff-42cf-889b-c85d2af22ad9
- true
- List
- List
- false
- 6da19130-89a1-437b-b23f-cb65a54edfae
- 1
-
14139
28813
43
20
-
14160.5
28823
- Item index
- 0e1643b4-dc6c-4a34-9c1e-50d0d823a23e
- true
- Index
- Index
- false
- 0
-
14139
28833
43
20
-
14160.5
28843
- 1
- 1
- {0}
- 0
- Wrap index to list bounds
- 3b1b18e4-5dbf-4177-a14b-2f72fd73de68
- true
- Wrap
- Wrap
- false
- 0
-
14139
28853
43
20
-
14160.5
28863
- 1
- 1
- {0}
- true
- Item at {i'}
- 2f6f0afd-993f-47a5-8a5f-5b97369eb913
- true
- false
- Item
- i
- false
- 0
-
14206
28813
6
60
-
14209
28843
- c3f9cea5-6fd4-4db5-959b-08cd08ed9fe1
- Simple Mesh
- Create a mesh that represents a Brep as simply as possible
- true
- 916b40c9-fae5-4a15-b308-c086513aa6ed
- true
- Simple Mesh
- Simple Mesh
-
13537
28074
81
28
-
13576
28088
- Brep to mesh, only breps with triangle or quad faces are supported.
- a3400c94-1368-45d9-919d-f308d19cb831
- true
- Brep
- Brep
- false
- 02d977a4-4efe-4e2d-8407-51dd988709ae
- 1
-
13539
28076
25
24
-
13551.5
28088
- Mesh
- c141638f-f968-4458-8a65-656377164c14
- true
- Mesh
- Mesh
- false
- 0
-
13588
28076
28
24
-
13602
28088
- 8307c31e-e307-48e9-b7c3-f970591e86d2
- 2cd3c35a-cada-1a81-ddba-5b184219e513
- ggNetworkPolygons
- Polygon from Curve network
- true
- 03dad908-8250-4fe7-9faf-aac50ee62be7
- true
- ggNetworkPolygons
- ggNetworkPolygons
-
13615
28333
134
44
-
13710
28355
- 1
- Input Curves
- 0124ecba-9dc2-4ca3-80ff-7428af38b8cc
- true
- Curves
- Curves
- false
- 4cb9ae17-9c50-4f01-abc2-ce86d43083b0
- 1
-
13617
28335
81
20
-
13657.5
28345
- Number of edges considered to be a void or perimeter location
- 5e4caa1c-831b-487e-bdd5-a88cf6ee8f05
- true
- Perim or Void
- Perim or Void
- true
- 0
-
13617
28355
81
20
-
13657.5
28365
- 1
- 1
- {0}
- 4
- 1
- Resultant Polygons
- c3015044-b271-488b-bb89-63d99aa97c9b
- true
- Cells
- Cells
- false
- 0
-
13722
28335
25
40
-
13734.5
28355
- 3c5edcba-b7a5-4710-b076-4b19a7080a2b
- 08bdcae0-d034-48dd-a145-24a9fcf3d3ff
- Center
- Returns the center of a geometry and the Diameter of it's bounding box as the Dimension
You can Right Click on the component's icon and choose "ForAll" option to have center point of a group of geometries.
Besides You can Right click on the component's icon and choose one of three provided options (Spacial/ Planar/ Basement ) to have Desired type of center.
- true
- 6ec8f57d-f6b6-4f61-9fa6-ea4d3930062b
- true
- Center
- Center
-
13723
28195
129
44
-
13787
28217
- 1
- Geometric
- 25a6dac4-741b-4cf2-b6c4-46916348ea4c
- true
- Geometric
- Geometric
- false
- 83c37836-d997-40ad-b3dd-9f1c8098cd80
- 1
-
13725
28197
50
40
-
13750
28217
- 1
- Center
- 5be92eb5-02c1-4a50-802c-7ab01a573a0e
- true
- Center
- Center
- false
- 0
-
13799
28197
51
20
-
13824.5
28207
- 1
- Diagonal size of geometry's bounding box
- 8fe3d4fd-0f58-4b7a-8a93-086ba2ce3425
- true
- Dimension
- Dimension
- false
- 0
-
13799
28217
51
20
-
13824.5
28227
- 4d2a06bd-4b0f-4c65-9ee0-4220e4c01703
- Scale
- Scale an object uniformly in all directions.
- true
- 22249883-3dfd-42f2-938f-5dbb9209cffb
- true
- Scale
- Scale
-
13523
28138
191
64
-
13650
28170
- Base geometry
- add7ea7e-611e-4934-b67e-62bdab122d97
- true
- Geometry
- Geometry
- true
- 83c37836-d997-40ad-b3dd-9f1c8098cd80
- 1
-
13525
28140
113
20
-
13581.5
28150
- Center of scaling
- 15215e10-f506-4266-8884-84f12e90ff86
- true
- Center
- Center
- false
- 5be92eb5-02c1-4a50-802c-7ab01a573a0e
- 1
-
13525
28160
113
20
-
13581.5
28170
- 1
- 1
- {0}
-
0
0
0
- Scaling factor
- 9bb0c08c-8fbe-4370-9fac-438da46c2bd9
- true
- Factor
- Factor
- false
- 0
-
13525
28180
113
20
-
13581.5
28190
- 1
- 1
- {0}
- 0.33333333333333331
- Scaled geometry
- 02d977a4-4efe-4e2d-8407-51dd988709ae
- true
- Geometry
- Geometry
- false
- 0
-
13662
28140
50
30
-
13687
28155
- Transformation data
- 4354deec-6b6e-4a5c-b887-e54017812829
- true
- Transform
- Transform
- false
- 0
-
13662
28170
50
30
-
13687
28185
- deaf8653-5528-4286-807c-3de8b8dad781
- Surface
- Contains a collection of generic surfaces
- true
- fef8f6d8-5af6-4935-8408-78241f7e4d7b
- true
- Surface
- Surface
- false
- cbd6bf4a-bfcb-42e9-b3ba-b33cb2875e0a
- 1
-
13617
28025
50
24
-
13642.63
28037.84
- ba2d8f57-0738-42b4-b5a5-fe4d853517eb
- Deconstruct Mesh
- Deconstruct a mesh into its component parts.
- true
- 2b056227-09bd-4857-a416-66e816e2af0b
- true
- Deconstruct Mesh
- Deconstruct Mesh
-
13708
28025
97
84
-
13750
28067
- Base mesh
- 2f090a6d-532a-430f-aed9-fb570dbc2522
- true
- Mesh
- Mesh
- false
- c141638f-f968-4458-8a65-656377164c14
- 1
-
13710
28027
28
80
-
13724
28067
- 1
- Mesh vertices
- fd84477c-fe0f-4f05-9828-1aa854d22749
- true
- Vertices
- Vertices
- false
- 0
-
13762
28027
41
20
-
13782.5
28037
- 1
- Mesh faces
- 3a3c7504-af86-4050-b2f7-9453abe99352
- true
- Faces
- Faces
- false
- 0
-
13762
28047
41
20
-
13782.5
28057
- 1
- Mesh vertex colours
- 67e990b8-5886-40d8-8adb-301eb5ef3b69
- true
- Colours
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- Scale an object with non-uniform factors.
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- Scale NU
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- Deconstruct a numeric domain into its component parts.
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108
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11
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31
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64
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60
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44
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- Contains a collection of floating point numbers
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- Evaluate the curvature of a curve at a specified parameter.
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50
30
-
9263
-2362
- Parameter on curve domain to evaluate
- 2b184f5f-60fe-48a2-84af-24f1707371c9
- true
- Parameter
- Parameter
- false
- 9b047484-149a-4c2c-bc3b-133bf8a16042
- 1
-
9238
-2347
50
30
-
9263
-2332
- Point on curve at {t}
- 27d02d99-f186-4f18-959f-fb55050714ad
- true
- Point
- Point
- false
- 0
-
9312
-2377
47
20
-
9335.5
-2367
- Curvature vector at {t}
- aeb40292-7614-4530-8cb6-cb15afc4abd7
- true
- Curvature
- Curvature
- false
- 0
-
9312
-2357
47
20
-
9335.5
-2347
- Curvature circle at {t}
- ac4108b8-b50c-4b2f-9d58-db3abf48d468
- true
- Curvature
- Curvature
- false
- 0
-
9312
-2337
47
20
-
9335.5
-2327
- 2162e72e-72fc-4bf8-9459-d4d82fa8aa14
- Divide Curve
- Divide a curve into equal length segments
- true
- 1c788573-d7bf-4f72-a121-cbf3b62252c6
- true
- Divide Curve
- Divide Curve
-
9237
-2293
123
64
-
9291
-2261
- Curve to divide
- 7bb740f1-89a7-41ba-908d-6172c795d802
- true
- Curve
- Curve
- false
- 8e01634f-6886-4da4-93cc-d84f2949b7f1
- 1
-
9239
-2291
40
20
-
9259
-2281
- Number of segments
- 31973aa3-a6c4-40e2-8334-3d5983744459
- true
- Count
- Count
- false
- 41d4fcae-5924-4999-8519-7d3c327b7aea
- 1
-
9239
-2271
40
20
-
9259
-2261
- 1
- 1
- {0}
- 32
- Split segments at kinks
- f686c8ca-6a0f-4056-b538-82d1db5c6c23
- true
- Kinks
- Kinks
- false
- 0
-
9239
-2251
40
20
-
9259
-2241
- 1
- 1
- {0}
- false
- 1
- Division points
- 6c829d37-82dc-4ac3-941d-503e2491d515
- true
- Points
- Points
- false
- 0
-
9303
-2291
55
20
-
9330.5
-2281
- 1
- Tangent vectors at division points
- 1c759179-d2dd-4f1d-8b1b-e5fb56023536
- true
- Tangents
- Tangents
- false
- 0
-
9303
-2271
55
20
-
9330.5
-2261
- 1
- Parameter values at division points
- 9b047484-149a-4c2c-bc3b-133bf8a16042
- true
- Parameters
- Parameters
- false
- 0
-
9303
-2251
55
20
-
9330.5
-2241
- d5967b9f-e8ee-436b-a8ad-29fdcecf32d5
- Curve
- Contains a collection of generic curves
- true
- 8e01634f-6886-4da4-93cc-d84f2949b7f1
- true
- Curve
- Curve
- false
- 506f2123-b521-4a52-9165-68e803a30009
- 1
-
9282
-811
50
24
-
9307.541
-799.8869
- 23862862-049a-40be-b558-2418aacbd916
- Deconstruct Arc
- Retrieve the base plane, radius and angle domain of an arc.
- true
- f3a56189-a559-47f2-af99-08d4a3d06a47
- true
- Deconstruct Arc
- Deconstruct Arc
-
9248
-2462
102
64
-
9282
-2430
- Arc or Circle to deconstruct
- 6cec1ee5-525e-453b-ad11-20021ffb74ad
- true
- Arc
- Arc
- false
- ac4108b8-b50c-4b2f-9d58-db3abf48d468
- 1
-
9250
-2460
20
60
-
9260
-2430
- Base plane of arc or circle
- b86f8283-6c12-49a0-bd2b-33920875eaa4
- true
- Base Plane
- Base Plane
- false
- 0
-
9294
-2460
54
20
-
9321
-2450
- Radius of arc or circle
- e440447f-77d2-4617-ba70-c50ae59a1c77
- true
- Radius
- Radius
- false
- 0
-
9294
-2440
54
20
-
9321
-2430
- Angle domain (in radians) of arc
- b91b85ff-7309-4c95-aa1c-b70e2d0d927c
- true
- Angle
- Angle
- false
- 0
-
9294
-2420
54
20
-
9321
-2410
- 797d922f-3a1d-46fe-9155-358b009b5997
- One Over X
- Compute one over x.
- true
- e5e088e3-6608-44e6-a7d7-7eb73fb9b2c8
- true
- One Over X
- One Over X
-
9255
-3051
88
28
-
9298
-3037
- Input value
- af3506ed-2063-459e-aa23-5a1fdc8a363f
- true
- Value
- Value
- false
- 2cd82ac7-4de3-4efd-b21c-bb675514f953
- 1
-
9257
-3049
29
24
-
9271.5
-3037
- Output value
- c1491a51-714b-4cb9-85b6-34a38ca75a1f
- true
- Result
- Result
- false
- 0
-
9310
-3049
31
24
-
9325.5
-3037
- 2b69bf71-4e69-43aa-b7be-4f6ce7e45bef
- Quick Graph
- 1
- Display a set of y-values as a graph
- 52fc7e98-c167-43e7-87c2-59064227472a
- true
- Quick Graph
- Quick Graph
- false
- 0
- 9ffa872c-e479-408b-8f5c-98a77c7ef2dd
- 1
-
9232
-3288
150
150
-
9232.541
-3287.887
- -1
- 4c4e56eb-2f04-43f9-95a3-cc46a14f495a
- Line
- Create a line between two points.
- true
- c95358a1-3288-48df-a244-8bf7e0c6385d
- true
- Line
- Line
-
9248
-2987
102
44
-
9314
-2965
- Line start point
- dda79b74-b3e3-445d-8e48-4096cd5b33ec
- true
- Start Point
- Start Point
- false
- 27d02d99-f186-4f18-959f-fb55050714ad
- 1
-
9250
-2985
52
20
-
9276
-2975
- Line end point
- ebc36594-9c20-4f70-988a-0ab4624f67fd
- true
- End Point
- End Point
- false
- b86f8283-6c12-49a0-bd2b-33920875eaa4
- 1
-
9250
-2965
52
20
-
9276
-2955
- Line segment
- 7785f9df-f096-491f-964e-599a2aec932f
- true
- Line
- Line
- false
- 0
-
9326
-2985
22
40
-
9337
-2965
- 4c619bc9-39fd-4717-82a6-1e07ea237bbe
- Line SDL
- Create a line segment defined by start point, tangent and length.}
- true
- 39e437ab-17e0-4324-8544-cb86abbc9e57
- true
- Line SDL
- Line SDL
-
9244
-4871
110
64
-
9318
-4839
- Line start point
- 41670e9e-038a-4b55-9192-201b8ad9b7af
- true
- Start
- Start
- false
- 27d02d99-f186-4f18-959f-fb55050714ad
- 1
-
9246
-4869
60
20
-
9284
-4859
- Line tangent (direction)
- 7a745369-90e9-483d-ae37-86261addbb34
- true
- Direction
- Direction
- false
- 2fcc79ac-e62a-4a44-84e2-59411080f035
- 1
-
9246
-4849
60
20
-
9284
-4839
- 1
- 1
- {0}
-
0
0
1
- Line length
- 8ebf383f-28be-4dbc-9a3f-e05ca0ef3e02
- -X
- true
- Length
- Length
- false
- 37bb12ea-34eb-418f-9b39-ae27a2fe2897
- 1
-
9246
-4829
60
20
-
9284
-4819
- 1
- 1
- {0}
- 1
- Line segment
- 2158b91e-623b-4f9d-8297-f4edb0d6540d
- true
- Line
- Line
- false
- 0
-
9330
-4869
22
60
-
9341
-4839
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- c6073d46-269e-471f-9961-e21811a07752
- true
- Evaluate Length
- Evaluate Length
-
9224
-5784
149
64
-
9309
-5752
- Curve to evaluate
- af95f296-ac3c-495a-9314-f578c0929d0c
- true
- Curve
- Curve
- false
- 88d2e234-202c-4e3b-adb8-c6bf7cc9988f
- 1
-
9226
-5782
71
20
-
9261.5
-5772
- Length factor for curve evaluation
- 082891a2-5a2f-4b4c-b46b-91e2da8ce77d
- true
- Length
- Length
- false
- 0
-
9226
-5762
71
20
-
9261.5
-5752
- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 71ea8ef3-18b4-4e5c-ab66-8d3bbe633f6e
- true
- Normalized
- Normalized
- false
- 0
-
9226
-5742
71
20
-
9261.5
-5732
- 1
- 1
- {0}
- true
- Point at the specified length
- 58715e09-1461-47aa-b311-c9878cbef364
- true
- Point
- Point
- false
- 0
-
9321
-5782
50
20
-
9346
-5772
- Tangent vector at the specified length
- 78cd4516-cf88-4c55-b855-7036ef090b35
- true
- Tangent
- Tangent
- false
- 0
-
9321
-5762
50
20
-
9346
-5752
- Curve parameter at the specified length
- 0351b476-a056-45f8-868d-0f74aeb0b6bd
- true
- Parameter
- Parameter
- false
- 0
-
9321
-5742
50
20
-
9346
-5732
- 2b2a4145-3dff-41d4-a8de-1ea9d29eef33
- Interpolate
- Create an interpolated curve through a set of points.
- true
- 93569eee-4485-4e75-b081-b5a4f7d2e796
- true
- Interpolate
- Interpolate
-
9186
-6115
225
84
-
9359
-6073
- 1
- Interpolation points
- dde1eac0-839e-45a9-a2e5-3f21c6dc288e
- true
- Vertices
- Vertices
- false
- 043ef658-425b-4fc2-a0ed-57be30e7b117
- 1
-
9188
-6113
159
20
-
9267.5
-6103
- Curve degree
- 08e55262-47e4-4f8d-bebd-c3a698f87d4e
- true
- Degree
- Degree
- false
- 0
-
9188
-6093
159
20
-
9267.5
-6083
- 1
- 1
- {0}
- 1
- Periodic curve
- 2ad1ddf0-9cf3-4806-837a-41b2fddf6642
- true
- Periodic
- Periodic
- false
- 0
-
9188
-6073
159
20
-
9267.5
-6063
- 1
- 1
- {0}
- false
- Knot spacing (0=uniform, 1=chord, 2=sqrtchord)
- eae7757e-1299-4541-a34c-bcc676de11c9
- true
- KnotStyle
- KnotStyle
- false
- 0
-
9188
-6053
159
20
-
9267.5
-6043
- 1
- 1
- {0}
- 2
- Resulting nurbs curve
- 098a4c87-ff22-4643-a81f-d1664572e52a
- true
- Curve
- Curve
- false
- 0
-
9371
-6113
38
26
-
9390
-6099.667
- Curve length
- 54263cd0-b37d-47d9-868f-db90f9b3858d
- true
- Length
- Length
- false
- 0
-
9371
-6087
38
27
-
9390
-6073
- Curve domain
- ad91ff97-0733-42e1-ab10-73c9b30777cd
- true
- Domain
- Domain
- false
- 0
-
9371
-6060
38
27
-
9390
-6046.333
- 3e8ca6be-fda8-4aaf-b5c0-3c54c8bb7312
- Number
- Contains a collection of floating point numbers
- 9d77a9be-7ee4-404f-b9d9-0b021cd89431
- true
- Number
- Number
- false
- b22d0187-dac5-4128-a6af-18259df683c4
- 1
-
9282
-6145
50
24
-
9307.541
-6133.887
- d5967b9f-e8ee-436b-a8ad-29fdcecf32d5
- Curve
- Contains a collection of generic curves
- true
- 61019724-eb0d-4b80-ba89-1f6601b8fba6
- true
- Curve
- Curve
- false
- 098a4c87-ff22-4643-a81f-d1664572e52a
- 1
-
9282
-6242
50
24
-
9307.541
-6230.887
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 9ffa872c-e479-408b-8f5c-98a77c7ef2dd
- true
- Relay
-
- false
- c1491a51-714b-4cb9-85b6-34a38ca75a1f
- 1
-
9279
-3070
40
16
-
9299
-3062
- 76975309-75a6-446a-afed-f8653720a9f2
- Create Material
- Create an OpenGL material.
- true
- 09c6c5c2-7cc1-43ae-a3a3-04ac393041d8
- true
- Create Material
- Create Material
-
9223
-5631
152
104
-
9321
-5579
- Colour of the diffuse channel
- f7a4b8b1-069c-43a0-b602-1833de12db7e
- true
- Diffuse
- Diffuse
- false
- 0
-
9225
-5629
84
20
-
9267
-5619
- 1
- 1
- {0}
-
255;248;248;248
- Colour of the specular highlight
- 0cdf7eb3-a2e9-4b8c-80df-5796a2c42d29
- true
- Specular
- Specular
- false
- 0
-
9225
-5609
84
20
-
9267
-5599
- 1
- 1
- {0}
-
255;0;255;255
- Emissive colour of the material
- f9ec374b-4e7e-425e-80dc-7d1913f5d442
- true
- Emission
- Emission
- false
- 0
-
9225
-5589
84
20
-
9267
-5579
- 1
- 1
- {0}
-
255;0;0;0
- Amount of transparency (0.0 = opaque, 1.0 = transparent
- 7d73c7ec-e469-48b9-9f6c-3af7d21e5a0a
- true
- Transparency
- Transparency
- false
- 0
-
9225
-5569
84
20
-
9267
-5559
- 1
- 1
- {0}
- 0.5
- Amount of shinyness (0 = none, 1 = low shine, 100 = max shine
- f29297e6-80ae-4e98-8057-425ad865e68a
- true
- Shine
- Shine
- false
- 0
-
9225
-5549
84
20
-
9267
-5539
- 1
- 1
- {0}
- 100
- Resulting material
- 1ce09a68-c1f4-44f0-990c-4d96308dc9e1
- true
- Material
- Material
- false
- 0
-
9333
-5629
40
100
-
9353
-5579
- 537b0419-bbc2-4ff4-bf08-afe526367b2c
- Custom Preview
- Allows for customized geometry previews
- true
- true
- e286f87e-7fc1-43eb-b9a4-a2366f90ae24
- true
- Custom Preview
- Custom Preview
-
9265
-5701
76
44
-
9327
-5679
- Geometry to preview
- true
- 366ececa-ed22-4724-b989-f09e6937697d
- true
- Geometry
- Geometry
- false
- 88d2e234-202c-4e3b-adb8-c6bf7cc9988f
- 1
-
9267
-5699
48
20
-
9291
-5689
- The material override
- 027c3144-be54-484e-975d-ce396e8b251f
- true
- Material
- Material
- false
- 1ce09a68-c1f4-44f0-990c-4d96308dc9e1
- 1
-
9267
-5679
48
20
-
9291
-5669
- 1
- 1
- {0}
-
255;221;160;221
-
255;66;48;66
- 0.5
-
255;255;255;255
- 0
- 76975309-75a6-446a-afed-f8653720a9f2
- Create Material
- Create an OpenGL material.
- true
- 3f7e06d6-03e2-4aa1-b86d-542eceeb31ee
- true
- Create Material
- Create Material
-
9223
-1711
152
104
-
9321
-1659
- Colour of the diffuse channel
- 7f94db8a-e3ab-4ce3-9b03-f3ec7b4f851b
- true
- Diffuse
- Diffuse
- false
- 0
-
9225
-1709
84
20
-
9267
-1699
- 1
- 1
- {0}
-
255;211;211;211
- Colour of the specular highlight
- 77a29782-5647-44c5-a815-16be8fea0af6
- true
- Specular
- Specular
- false
- 0
-
9225
-1689
84
20
-
9267
-1679
- 1
- 1
- {0}
-
255;0;255;255
- Emissive colour of the material
- 46d73d35-3d8f-4a3a-af59-d7f2aff6c5e4
- true
- Emission
- Emission
- false
- 0
-
9225
-1669
84
20
-
9267
-1659
- 1
- 1
- {0}
-
255;0;0;0
- Amount of transparency (0.0 = opaque, 1.0 = transparent
- fa2a385c-186e-442f-8652-d241044e2bdc
- true
- Transparency
- Transparency
- false
- 0
-
9225
-1649
84
20
-
9267
-1639
- 1
- 1
- {0}
- 0.5
- Amount of shinyness (0 = none, 1 = low shine, 100 = max shine
- a1f22685-5539-4143-83f0-28d6fea1c703
- true
- Shine
- Shine
- false
- 0
-
9225
-1629
84
20
-
9267
-1619
- 1
- 1
- {0}
- 100
- Resulting material
- 71d2a512-f0b5-4c06-9af5-6682789399fe
- true
- Material
- Material
- false
- 0
-
9333
-1709
40
100
-
9353
-1659
- 537b0419-bbc2-4ff4-bf08-afe526367b2c
- Custom Preview
- Allows for customized geometry previews
- true
- true
- fd34a320-94b5-40d0-945e-128f98958485
- true
- Custom Preview
- Custom Preview
-
9270
-1797
76
44
-
9332
-1775
- Geometry to preview
- true
- e50fc350-2355-4f9b-a8ca-f8fa8ee0fe7a
- true
- Geometry
- Geometry
- false
- f1cb17b7-ee0e-49ec-95f6-e24ed89eb56e
- 1
-
9272
-1795
48
20
-
9296
-1785
- The material override
- 88a7d6cf-88b3-401f-879c-b7f3a4cd2820
- true
- Material
- Material
- false
- 71d2a512-f0b5-4c06-9af5-6682789399fe
- 1
-
9272
-1775
48
20
-
9296
-1765
- 1
- 1
- {0}
-
255;221;160;221
-
255;66;48;66
- 0.5
-
255;255;255;255
- 0
- 76975309-75a6-446a-afed-f8653720a9f2
- Create Material
- Create an OpenGL material.
- true
- e2e12ca1-f11f-496f-af7e-060e0185e0e7
- true
- Create Material
- Create Material
-
9223
-6402
152
104
-
9321
-6350
- Colour of the diffuse channel
- aa7be633-bc1c-4774-8b07-82401abd26bf
- true
- Diffuse
- Diffuse
- false
- 0
-
9225
-6400
84
20
-
9267
-6390
- 1
- 1
- {0}
-
255;223;223;223
- Colour of the specular highlight
- 75c45dd2-9c4f-4900-9e26-43c55a421435
- true
- Specular
- Specular
- false
- 0
-
9225
-6380
84
20
-
9267
-6370
- 1
- 1
- {0}
-
255;0;255;255
- Emissive colour of the material
- f5341123-f1a4-4536-a36e-d2cb025ab991
- true
- Emission
- Emission
- false
- 0
-
9225
-6360
84
20
-
9267
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- Amount of transparency (0.0 = opaque, 1.0 = transparent
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- Amount of shinyness (0 = none, 1 = low shine, 100 = max shine
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- Allows for customized geometry previews
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- Custom Preview
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- Geometry to preview
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- The material override
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48
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255;221;160;221
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255;66;48;66
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255;255;255;255
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- Curvature Graph
- Draws Rhino Curvature Graphs.
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- Curvature Graph
- Curvature Graph
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80
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- Curve for Curvature graph display
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- Sampling density of the Graph
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250
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- Remap Numbers
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149
64
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- Value to remap
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- Value
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81
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- Source domain
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81
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81
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- Remapped number
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9331
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40
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9331
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40
30
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- Bounds
- Create a numeric domain which encompasses a list of numbers.
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- Bounds
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110
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- Numbers to include in Bounds
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44
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- Numeric Domain between the lowest and highest numbers in {N}
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- 0
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38
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40
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- A wire relay object
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70
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- First item for multiplication
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11
20
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- Second item for multiplication
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11
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31
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40
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255;255;255;255
- A group of Grasshopper objects
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200
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40
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30
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- Curve length
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34
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- Multiplication
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70
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11
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- Second item for multiplication
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11
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- Result of multiplication
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31
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40
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- Recursive decomposition until all segments are atomic
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- Length factor for curve evaluation
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50
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- Line start point
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60
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- Line tangent (direction)
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60
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0
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- Line length
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60
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22
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- Compute relative differences for a list of data
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116
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- List of data to operate on (numbers or points or vectors allowed)
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9363
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38
26
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9382
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- Curve length
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- Length
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- 0
-
9363
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38
27
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9382
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- Curve domain
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- Domain
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- 0
-
9363
-9805
38
27
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9382
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- 76975309-75a6-446a-afed-f8653720a9f2
- Create Material
- Create an OpenGL material.
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- true
- Create Material
- Create Material
-
9215
-9997
152
104
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9313
-9945
- Colour of the diffuse channel
- 207b8415-27f7-42c6-8c64-3adb873fcfd8
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- false
- 0
-
9217
-9995
84
20
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9259
-9985
- 1
- 1
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-
255;219;219;219
- Colour of the specular highlight
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- true
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- Specular
- false
- 0
-
9217
-9975
84
20
-
9259
-9965
- 1
- 1
- {0}
-
255;0;255;255
- Emissive colour of the material
- 6f9a8ba2-dd2e-4732-95dd-5d9316fff397
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- Emission
- false
- 0
-
9217
-9955
84
20
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9259
-9945
- 1
- 1
- {0}
-
255;0;0;0
- Amount of transparency (0.0 = opaque, 1.0 = transparent
- e715ae77-2790-4464-a60f-20723da9f4a8
- true
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- Transparency
- false
- 0
-
9217
-9935
84
20
-
9259
-9925
- 1
- 1
- {0}
- 0.5
- Amount of shinyness (0 = none, 1 = low shine, 100 = max shine
- 7ce4fc74-7bad-4ffe-8f64-8bef1035495d
- true
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- Shine
- false
- 0
-
9217
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84
20
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9259
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- Resulting material
- 6836f515-706a-4c69-8769-5d7de637fb53
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- 0
-
9325
-9995
40
100
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9345
-9945
- 537b0419-bbc2-4ff4-bf08-afe526367b2c
- Custom Preview
- Allows for customized geometry previews
- true
- true
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- true
- Custom Preview
- Custom Preview
-
9241
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76
44
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9303
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- Geometry to preview
- true
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- Geometry
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- c32bd525-2467-45e9-a83b-330bd9f9b05a
- 1
-
9243
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48
20
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9267
-10056
- The material override
- d553ab6a-7371-4cea-9568-4cd00d85c970
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- 6836f515-706a-4c69-8769-5d7de637fb53
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9243
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48
20
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9267
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- 1
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255;221;160;221
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255;66;48;66
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255;255;255;255
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- Quick Graph
- 1
- Display a set of y-values as a graph
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- Quick Graph
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- dd7ae928-e56d-4423-b7b1-b1999182a279
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-
9223
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150
150
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9223.633
-8189
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- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
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255;255;255;255
- A group of Grasshopper objects
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- Group
- afb96615-c59a-45c9-9cac-e27acb1c7ca0
- Explode
- Explode a curve into smaller segments.
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- true
- Explode
- Explode
-
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-10388
134
44
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9295
-10366
- Curve to explode
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- c32bd525-2467-45e9-a83b-330bd9f9b05a
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9226
-10386
57
20
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9254.5
-10376
- Recursive decomposition until all segments are atomic
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- 0
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9226
-10366
57
20
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9254.5
-10356
- 1
- 1
- {0}
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- 1
- Exploded segments that make up the base curve
- 657f9a26-0555-40a8-85a2-d714bd1df761
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- Segments
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9307
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49
20
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9331.5
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- Vertices of the exploded segments
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- Vertices
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9307
-10366
49
20
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9331.5
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- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 31841e7d-30a7-4a57-896b-1f20e5587acb
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- Evaluate Length
- Evaluate Length
-
9216
-10471
149
64
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9301
-10439
- Curve to evaluate
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9218
-10469
71
20
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9253.5
-10459
- Length factor for curve evaluation
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- true
- Length
- Length
- false
- 0
-
9218
-10449
71
20
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9253.5
-10439
- 1
- 1
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- If True, the Length factor is normalized (0.0 ~ 1.0)
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- true
- Normalized
- Normalized
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9218
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71
20
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9253.5
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- 1
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- Point at the specified length
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- Point
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-
9313
-10469
50
20
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9338
-10459
- Tangent vector at the specified length
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- Tangent
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9313
-10449
50
20
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9338
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- Curve parameter at the specified length
- 572b8234-c8fb-4fcc-b7ec-a320da596eeb
- true
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- Parameter
- false
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-
9313
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50
20
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9338
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- 4c619bc9-39fd-4717-82a6-1e07ea237bbe
- Line SDL
- Create a line segment defined by start point, tangent and length.}
- true
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- true
- Line SDL
- Line SDL
-
9236
-12191
110
64
-
9310
-12159
- Line start point
- c9666999-2358-4b17-8320-a71d84c28fa9
- true
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- Start
- false
- 88e80ba7-d7e1-4739-8bc9-2649e0568988
- 1
-
9238
-12189
60
20
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9276
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- Line tangent (direction)
- 2f910283-5649-449c-be0c-b136a4148d2e
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- Direction
- Direction
- false
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- 1
-
9238
-12169
60
20
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9276
-12159
- 1
- 1
- {0}
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0
0
1
- Line length
- 3f7a29c7-d6dd-43e5-a2bc-9d2174148239
- ABS(X)
- true
- Length
- Length
- false
- 9f9eae92-60c1-4f4c-87f5-b8931d6fd9c9
- 1
-
9238
-12149
60
20
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9276
-12139
- 1
- 1
- {0}
- 0.015625
- Line segment
- f0c191c1-9621-4bbc-8f42-70fddab36b4d
- true
- Line
- Line
- false
- 0
-
9322
-12189
22
60
-
9333
-12159
- dd17d442-3776-40b3-ad5b-5e188b56bd4c
- Relative Differences
- Compute relative differences for a list of data
- true
- d78b1c8d-4c32-45a1-9cd0-3f1c128e80c8
- true
- Relative Differences
- Relative Differences
-
9233
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116
28
-
9280
-10800
- 1
- List of data to operate on (numbers or points or vectors allowed)
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- Values
- Values
- false
- 36b3a4ab-79e8-4ae2-bcf6-59f01b423655
- 1
-
9235
-10812
33
24
-
9251.5
-10800
- 1
- Differences between consecutive items
- 7338c244-af88-4723-b45a-08577283c18b
- true
- Differenced
- Differenced
- false
- 0
-
9292
-10812
55
24
-
9319.5
-10800
- f3230ecb-3631-4d6f-86f2-ef4b2ed37f45
- Replace Nulls
- Replace nulls or invalid data with other data
- true
- 60ac2b1a-ed32-485c-b398-5132c0ce38c7
- true
- Replace Nulls
- Replace Nulls
-
9221
-10758
139
44
-
9316
-10736
- 1
- Items to test for null
- 8b748710-2523-4d4d-a9f8-7949b3dbbaec
- true
- Items
- Items
- false
- 55a89bb9-1cb3-4508-a64e-593c4f56d389
- 1
-
9223
-10756
81
20
-
9263.5
-10746
- 1
- Items to replace nulls with
- 78bf5914-83e2-4bf8-abe7-ef8d3f6c72a5
- true
- Replacements
- Replacements
- false
- 0
-
9223
-10736
81
20
-
9263.5
-10726
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_Integer
- 0
- 1
- List without any nulls
- 36b3a4ab-79e8-4ae2-bcf6-59f01b423655
- true
- Items
- Items
- false
- 0
-
9328
-10756
30
20
-
9343
-10746
- Number of items replaced
- f2ac4a82-0586-43fd-ac95-daa25658f827
- true
- Count
- Count
- false
- 0
-
9328
-10736
30
20
-
9343
-10726
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 55a89bb9-1cb3-4508-a64e-593c4f56d389
- true
- Relay
- false
- d8ad52e1-09c5-4d42-8086-8d7eedd452d8
- 1
-
9271
-10695
40
16
-
9291
-10687
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 7054797c-3a92-4321-8597-127654b4ca6c
- true
- Relay
- false
- 95512bec-3e3b-4a1e-968f-fdd54a0ed3fb
- 1
-
9271
-11059
40
16
-
9291
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- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- d78b1c8d-4c32-45a1-9cd0-3f1c128e80c8
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- a7355444-5015-436e-931d-6d44c0532770
- Group
- 2dc44b22-b1dd-460a-a704-6462d6e91096
- Curve Closest Point
- Find the closest point on a curve.
- true
- dc265006-688d-45d2-a2b8-861a06b4a669
- true
- Curve Closest Point
- Curve Closest Point
-
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108
64
-
9281
-10527
- Point to project onto curve
- 59eb5142-8d20-4b58-9832-b73d38c01f5e
- true
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- Point
- false
- 88e80ba7-d7e1-4739-8bc9-2649e0568988
- 1
-
9239
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30
30
-
9254
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- Curve to project onto
- 4e26aed9-39d5-4a12-91ee-5be2f0b044cb
- true
- Curve
- Curve
- false
- 8e01634f-6886-4da4-93cc-d84f2949b7f1
- 1
-
9239
-10527
30
30
-
9254
-10512
- Point on the curve closest to the base point
- 40443f53-c592-445e-a339-a109be0a51bb
- true
- Point
- Point
- false
- 0
-
9293
-10557
50
20
-
9318
-10547
- Parameter on curve domain of closest point
- a0713c1c-c26e-441e-93b3-f8edf5c233b2
- true
- Parameter
- Parameter
- false
- 0
-
9293
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50
20
-
9318
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- Distance between base point and curve
- b2882fd2-b8b7-4172-8f26-363ace0aa2a4
- true
- Distance
- Distance
- false
- 0
-
9293
-10517
50
20
-
9318
-10507
- 4c4e56eb-2f04-43f9-95a3-cc46a14f495a
- Line
- Create a line between two points.
- true
- a4a2e4fe-4294-43c1-8033-d508439ba3f1
- true
- Line
- Line
-
9240
-10638
102
44
-
9306
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- Line start point
- 223c6b86-f150-4be0-be87-6066ca661b45
- true
- Start Point
- Start Point
- false
- 40443f53-c592-445e-a339-a109be0a51bb
- 1
-
9242
-10636
52
20
-
9268
-10626
- Line end point
- 9b417723-48ba-4f1a-a0a5-971d61bf310e
- true
- End Point
- End Point
- false
- 88e80ba7-d7e1-4739-8bc9-2649e0568988
- 1
-
9242
-10616
52
20
-
9268
-10606
- Line segment
- 509ce120-a6c6-472d-a7ba-325df3973ff0
- true
- Line
- Line
- false
- 0
-
9318
-10636
22
40
-
9329
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- 2fcc2743-8339-4cdf-a046-a1f17439191d
- Remap Numbers
- Remap numbers into a new numeric domain
- true
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- true
- Remap Numbers
- Remap Numbers
-
9214
-11889
154
64
-
9314
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- Value to remap
- 4388d5aa-717b-4e61-958d-f0267b4a896b
- true
- Value
- Value
- false
- ef3c8bc1-7cba-4c60-9fcc-d378b603bd10
- 1
-
9216
-11887
86
20
-
9259
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- Source domain
- 6255db04-e743-411d-bd22-b9b95f602d3c
- true
- Source
- Source
- false
- 94bf725f-3745-4e94-93fa-23d17c538a20
- 1
-
9216
-11867
86
20
-
9259
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- 1
- 1
- {0}
-
0
1
- Target domain
- 5c9dd6aa-a9b2-4bb6-bf8c-c95a44b4a77b
- true
- Target
- Target
- false
- 0
-
9216
-11847
86
20
-
9259
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- 1
- 1
- {0}
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-1
1
- Remapped number
- 7fde5602-5527-4b53-9098-bc2f764c30ec
- true
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- 0
-
9326
-11887
40
30
-
9346
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- Remapped and clipped number
- c83d928d-275e-4779-8baf-744d80d2b95e
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- false
- 0
-
9326
-11857
40
30
-
9346
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- f44b92b0-3b5b-493a-86f4-fd7408c3daf3
- Bounds
- Create a numeric domain which encompasses a list of numbers.
- true
- 8c5b608e-fe4b-4be4-ae7d-a2f8720579a9
- true
- Bounds
- Bounds
-
9236
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110
28
-
9294
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- 1
- Numbers to include in Bounds
- fc76b9e6-26e3-4e91-b5a1-e62e80c88332
- true
- Numbers
- Numbers
- false
- ef3c8bc1-7cba-4c60-9fcc-d378b603bd10
- 1
-
9238
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44
24
-
9260
-11793
- Numeric Domain between the lowest and highest numbers in {N}
- 94bf725f-3745-4e94-93fa-23d17c538a20
- true
- Domain
- Domain
- false
- 0
-
9306
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38
24
-
9325
-11793
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- ef3c8bc1-7cba-4c60-9fcc-d378b603bd10
- true
- Relay
-
- false
- 7054797c-3a92-4321-8597-127654b4ca6c
- 1
-
9271
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40
16
-
9291
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- ce46b74e-00c9-43c4-805a-193b69ea4a11
- Multiplication
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- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 7b233811-8adf-47e6-9487-409c1062dec0
- true
- Evaluate Length
- Evaluate Length
-
9216
-13891
149
64
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9301
-13859
- Curve to evaluate
- 3ba71f4d-c6e6-488f-b9dd-2c03ba6069ba
- true
- Curve
- Curve
- false
- 371443ac-3136-42c3-8360-f83d4c4c61ed
- 1
-
9218
-13889
71
20
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9253.5
-13879
- Length factor for curve evaluation
- 855c025c-5286-44a9-a0a4-0c354b5e7bb8
- true
- Length
- Length
- false
- 0
-
9218
-13869
71
20
-
9253.5
-13859
- 1
- 1
- {0}
- 0.5
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 038af75f-2a62-499e-a4b2-3c06ef0bfa9a
- true
- Normalized
- Normalized
- false
- 0
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9218
-13849
71
20
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9253.5
-13839
- 1
- 1
- {0}
- true
- Point at the specified length
- 6e7b083f-f8f4-48fb-852b-f44d90379368
- true
- Point
- Point
- false
- 0
-
9313
-13889
50
20
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9338
-13879
- Tangent vector at the specified length
- 17de63ad-5524-45df-8781-f5ead83a2f49
- true
- Tangent
- Tangent
- false
- 0
-
9313
-13869
50
20
-
9338
-13859
- Curve parameter at the specified length
- fc254605-90a0-4a19-a769-ae1d5782ef45
- true
- Parameter
- Parameter
- false
- 0
-
9313
-13849
50
20
-
9338
-13839
- 4c619bc9-39fd-4717-82a6-1e07ea237bbe
- Line SDL
- Create a line segment defined by start point, tangent and length.}
- true
- f61e5a6d-a81d-45cf-a7d9-36b9d5fab315
- true
- Line SDL
- Line SDL
-
9236
-15757
110
64
-
9310
-15725
- Line start point
- 4c0b0d3c-c86a-4490-96a1-f64f940d644e
- true
- Start
- Start
- false
- 6e7b083f-f8f4-48fb-852b-f44d90379368
- 1
-
9238
-15755
60
20
-
9276
-15745
- Line tangent (direction)
- 859e964a-4ec0-48de-9c45-4b6c6cf6d6cb
- true
- Direction
- Direction
- false
- a43ca145-0b7a-4245-a9fd-9ee3155f0628
- 1
-
9238
-15735
60
20
-
9276
-15725
- 1
- 1
- {0}
-
0
0
1
- Line length
- 0cd5a2e9-100e-4e88-a8be-29455a703651
- ABS(X)
- true
- Length
- Length
- false
- 25faccb1-b1d4-451a-8577-baa88375614a
- 1
-
9238
-15715
60
20
-
9276
-15705
- 1
- 1
- {0}
- 0.015625
- Line segment
- 0f214bdb-5cad-4d4f-8eee-7b8f3600bdca
- true
- Line
- Line
- false
- 0
-
9322
-15755
22
60
-
9333
-15725
- dd17d442-3776-40b3-ad5b-5e188b56bd4c
- Relative Differences
- Compute relative differences for a list of data
- true
- 5f35fc89-309b-4e17-88a9-16b8cfb9fabb
- true
- Relative Differences
- Relative Differences
-
9233
-14234
116
28
-
9280
-14220
- 1
- List of data to operate on (numbers or points or vectors allowed)
- 5e22cf88-33d8-4bad-930c-c1a842b9fc93
- true
- Values
- Values
- false
- 472f4653-0d63-489f-aa1e-78a685ed3cd5
- 1
-
9235
-14232
33
24
-
9251.5
-14220
- 1
- Differences between consecutive items
- 72af1623-98b2-41a3-b5a9-7e1bda1d7111
- true
- Differenced
- Differenced
- false
- 0
-
9292
-14232
55
24
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9319.5
-14220
- f3230ecb-3631-4d6f-86f2-ef4b2ed37f45
- Replace Nulls
- Replace nulls or invalid data with other data
- true
- 2e7e46e0-8bb4-4ff2-bc33-167650346f6e
- true
- Replace Nulls
- Replace Nulls
-
9221
-14178
139
44
-
9316
-14156
- 1
- Items to test for null
- aa88ba3d-75ba-449c-b1af-976060979fcf
- true
- Items
- Items
- false
- 25c15167-43ce-4ca0-b325-c34d67039fe4
- 1
-
9223
-14176
81
20
-
9263.5
-14166
- 1
- Items to replace nulls with
- 2b4280b4-b88d-4417-a5c2-cd0b4441600d
- true
- Replacements
- Replacements
- false
- 0
-
9223
-14156
81
20
-
9263.5
-14146
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_Integer
- 0
- 1
- List without any nulls
- 472f4653-0d63-489f-aa1e-78a685ed3cd5
- true
- Items
- Items
- false
- 0
-
9328
-14176
30
20
-
9343
-14166
- Number of items replaced
- 0721411f-5db7-4c73-913e-6c87d11faa2e
- true
- Count
- Count
- false
- 0
-
9328
-14156
30
20
-
9343
-14146
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 25c15167-43ce-4ca0-b325-c34d67039fe4
- true
- Relay
- false
- 7054797c-3a92-4321-8597-127654b4ca6c
- 1
-
9271
-14115
40
16
-
9291
-14107
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- bfc69fd4-c68c-40ea-b4e6-b6f9c5550d3e
- true
- Relay
- false
- 5fcafa9d-43c7-4d8e-b1fa-7217ab260d93
- 1
-
9271
-14479
40
16
-
9291
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- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- 5f35fc89-309b-4e17-88a9-16b8cfb9fabb
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- Group
- 2dc44b22-b1dd-460a-a704-6462d6e91096
- Curve Closest Point
- Find the closest point on a curve.
- true
- b9c7f1c6-2f5e-4c3d-b929-a89603c04f14
- true
- Curve Closest Point
- Curve Closest Point
-
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108
64
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9281
-13947
- Point to project onto curve
- eb35bf93-9f3b-47cb-88b9-37c7e236dd69
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- Point
- Point
- false
- 6e7b083f-f8f4-48fb-852b-f44d90379368
- 1
-
9239
-13977
30
30
-
9254
-13962
- Curve to project onto
- db893065-426f-4a58-92a7-236e0193d82c
- true
- Curve
- Curve
- false
- 8e01634f-6886-4da4-93cc-d84f2949b7f1
- 1
-
9239
-13947
30
30
-
9254
-13932
- Point on the curve closest to the base point
- 2d839212-b8d4-4812-98d8-b6368d1ce218
- true
- Point
- Point
- false
- 0
-
9293
-13977
50
20
-
9318
-13967
- Parameter on curve domain of closest point
- 3c21d431-d450-4778-9e83-e0e5c534de56
- true
- Parameter
- Parameter
- false
- 0
-
9293
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50
20
-
9318
-13947
- Distance between base point and curve
- 8ee23322-d45f-45c7-a334-0d6117e065d5
- true
- Distance
- Distance
- false
- 0
-
9293
-13937
50
20
-
9318
-13927
- 4c4e56eb-2f04-43f9-95a3-cc46a14f495a
- Line
- Create a line between two points.
- true
- e95f78aa-eafb-4329-9993-de6cbe543737
- true
- Line
- Line
-
9240
-14058
102
44
-
9306
-14036
- Line start point
- 85df0df4-eafa-4d92-af84-501c0c3f6b89
- true
- Start Point
- Start Point
- false
- 2d839212-b8d4-4812-98d8-b6368d1ce218
- 1
-
9242
-14056
52
20
-
9268
-14046
- Line end point
- 4f8840e6-cde4-4eeb-82fd-27ff532598eb
- true
- End Point
- End Point
- false
- 6e7b083f-f8f4-48fb-852b-f44d90379368
- 1
-
9242
-14036
52
20
-
9268
-14026
- Line segment
- a43ca145-0b7a-4245-a9fd-9ee3155f0628
- true
- Line
- Line
- false
- 0
-
9318
-14056
22
40
-
9329
-14036
- 2fcc2743-8339-4cdf-a046-a1f17439191d
- Remap Numbers
- Remap numbers into a new numeric domain
- true
- 659f6427-1e0c-4b4a-b76b-5960c7fe394d
- true
- Remap Numbers
- Remap Numbers
-
9214
-15455
154
64
-
9314
-15423
- Value to remap
- babfbfbd-b943-43e7-94d0-48b810e96707
- true
- Value
- Value
- false
- b1f209e2-7620-47ec-8679-406efde82380
- 1
-
9216
-15453
86
20
-
9259
-15443
- Source domain
- 7e5a984f-1c76-4f46-9bac-02510837c41c
- true
- Source
- Source
- false
- d6f9116b-a2e0-49bb-840d-45e874d72f8e
- 1
-
9216
-15433
86
20
-
9259
-15423
- 1
- 1
- {0}
-
0
1
- Target domain
- aaa645f7-2720-4872-bd9c-becfeabba234
- true
- Target
- Target
- false
- 0
-
9216
-15413
86
20
-
9259
-15403
- 1
- 1
- {0}
-
-1
1
- Remapped number
- 1470d22a-da01-48d1-9419-1724f78ad190
- true
- Mapped
- Mapped
- false
- 0
-
9326
-15453
40
30
-
9346
-15438
- Remapped and clipped number
- 6942278c-6594-4d60-9732-8e188c38310c
- true
- Clipped
- Clipped
- false
- 0
-
9326
-15423
40
30
-
9346
-15408
- f44b92b0-3b5b-493a-86f4-fd7408c3daf3
- Bounds
- Create a numeric domain which encompasses a list of numbers.
- true
- 8999696a-74f0-4557-97f6-38fc25e0e737
- true
- Bounds
- Bounds
-
9236
-15373
110
28
-
9294
-15359
- 1
- Numbers to include in Bounds
- d965d7d1-9aee-406b-93c4-18f3199264c5
- true
- Numbers
- Numbers
- false
- b1f209e2-7620-47ec-8679-406efde82380
- 1
-
9238
-15371
44
24
-
9260
-15359
- Numeric Domain between the lowest and highest numbers in {N}
- d6f9116b-a2e0-49bb-840d-45e874d72f8e
- true
- Domain
- Domain
- false
- 0
-
9306
-15371
38
24
-
9325
-15359
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- b1f209e2-7620-47ec-8679-406efde82380
- true
- Relay
-
- false
- bfc69fd4-c68c-40ea-b4e6-b6f9c5550d3e
- 1
-
9271
-15326
40
16
-
9291
-15318
- ce46b74e-00c9-43c4-805a-193b69ea4a11
- Multiplication
- Mathematical multiplication
- true
- 2dbc970d-71e3-4f0d-8142-558c895fcd12
- true
- Multiplication
- Multiplication
-
9256
-15654
70
44
-
9281
-15632
- 2
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- First item for multiplication
- a4c5348c-e748-41ef-98ab-8ce70441ac52
- true
- A
- A
- true
- 6a969140-0075-4523-a327-0427abb39edd
- 1
-
9258
-15652
11
20
-
9263.5
-15642
- Second item for multiplication
- a60361f7-90d9-488c-8408-62be9d12b55a
- true
- B
- B
- true
- a2ddf12f-aac3-4d45-a4fd-5a6a2862a019
- 1
-
9258
-15632
11
20
-
9263.5
-15622
- Result of multiplication
- 25faccb1-b1d4-451a-8577-baa88375614a
- true
- Result
- Result
- false
- 0
-
9293
-15652
31
40
-
9308.5
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- ce46b74e-00c9-43c4-805a-193b69ea4a11
- Multiplication
- Mathematical multiplication
- true
- 2b0c3eae-72c9-4057-a9f2-0b7a17dbdaaa
- true
- Multiplication
- Multiplication
-
9256
-15526
70
44
-
9281
-15504
- 2
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- First item for multiplication
- d84fe2b4-a233-4c1f-b392-fb3a114b2e59
- true
- A
- A
- true
- 5828018c-2ca6-4a08-80ec-15d609092e7a
- 1
-
9258
-15524
11
20
-
9263.5
-15514
- Second item for multiplication
- 7f19a3fd-9268-4d35-923b-1f1b4d34063d
- true
- B
- B
- true
- 1470d22a-da01-48d1-9419-1724f78ad190
- 1
-
9258
-15504
11
20
-
9263.5
-15494
- Result of multiplication
- 6a969140-0075-4523-a327-0427abb39edd
- true
- Result
- Result
- false
- 0
-
9293
-15524
31
40
-
9308.5
-15504
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 5828018c-2ca6-4a08-80ec-15d609092e7a
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- Relay
- false
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-
9271
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40
16
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9291
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- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- 659f6427-1e0c-4b4a-b76b-5960c7fe394d
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- b1f209e2-7620-47ec-8679-406efde82380
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- Group
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- d6599ced-fd64-4798-b31a-cfa70f5fa710
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- Group
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- Panel
- A panel for custom notes and text values
- cc56ef11-96b9-4530-972f-8cbc81a613c9
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- 3d034f31-d797-4424-8cef-9499e7099fc1
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- Double click to edit panel content…
-
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185
271
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9205.633
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255;255;255;255
- true
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- Relay
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- A wire relay object
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-
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- cc56ef11-96b9-4530-972f-8cbc81a613c9
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-
9271
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40
16
-
9291
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- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- e9df2d08-5a93-4bb4-9361-d5b6b5a545a5
- true
- Relay
-
- false
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-
9271
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40
16
-
9291
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- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- 07602edd-99d6-4400-93a3-3b8afb259584
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- Group
- 76975309-75a6-446a-afed-f8653720a9f2
- Create Material
- Create an OpenGL material.
- true
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- Create Material
- Create Material
-
9215
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152
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9313
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- Colour of the diffuse channel
- 88a35608-9071-40f7-a0b5-6328887e6dde
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- 0
-
9217
-16475
84
20
-
9259
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- 1
- 1
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255;236;236;236
- Colour of the specular highlight
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9217
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84
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9259
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255;0;255;255
- Emissive colour of the material
- 3c4de844-d373-4abb-bfa6-d5934b78fb76
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9217
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84
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9259
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255;0;0;0
- Amount of transparency (0.0 = opaque, 1.0 = transparent
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9217
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84
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9259
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- Amount of shinyness (0 = none, 1 = low shine, 100 = max shine
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9217
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84
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9259
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- Resulting material
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100
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- 537b0419-bbc2-4ff4-bf08-afe526367b2c
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- Allows for customized geometry previews
- true
- true
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- Custom Preview
- Custom Preview
-
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76
44
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- Geometry to preview
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- The material override
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255;221;160;221
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255;66;48;66
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255;255;255;255
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- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
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- Evaluate Length
- Evaluate Length
-
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149
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- Curve to evaluate
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9218
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- Length factor for curve evaluation
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- Length
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- 0
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9218
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71
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- If True, the Length factor is normalized (0.0 ~ 1.0)
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9218
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71
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-
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- Tangent vector at the specified length
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9313
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50
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- Create an interpolated curve through a set of points.
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- Interpolate
- Interpolate
-
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- Curve degree
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159
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9180
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159
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9259.5
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- Knot spacing (0=uniform, 1=chord, 2=sqrtchord)
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9180
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159
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9259.5
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- Resulting nurbs curve
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38
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- Create an OpenGL material.
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152
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84
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- Colour of the specular highlight
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9217
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84
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9259
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255;0;255;255
- Emissive colour of the material
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9217
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9259
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255;0;0;0
- Amount of transparency (0.0 = opaque, 1.0 = transparent
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9259
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84
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9325
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100
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- Allows for customized geometry previews
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76
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9255
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48
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9279
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255;221;160;221
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255;66;48;66
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255;255;255;255
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- Display a set of y-values as a graph
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150
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255;255;255;255
- A group of Grasshopper objects
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- Explode a curve into smaller segments.
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57
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9254.5
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- Exploded segments that make up the base curve
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9307
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49
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- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
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- Evaluate Length
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9216
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149
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- Curve to evaluate
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71
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- Length factor for curve evaluation
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9218
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71
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9253.5
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9218
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71
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50
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- Line SDL
- Line SDL
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- Line start point
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60
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22
60
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- Replace nulls or invalid data with other data
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139
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81
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- Items to replace nulls with
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9223
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81
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9263.5
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- List without any nulls
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30
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9343
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30
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- A wire relay object
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40
16
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- Relay
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40
16
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255;255;255;255
- A group of Grasshopper objects
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- Find the closest point on a curve.
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108
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- Point to project onto curve
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30
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- Curve to project onto
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- {0}
-
255;221;160;221
-
255;66;48;66
- 0.5
-
255;255;255;255
- 0
- 2b69bf71-4e69-43aa-b7be-4f6ce7e45bef
- Quick Graph
- 1
- Display a set of y-values as a graph
- 09024d99-a87c-4956-b0e1-7bc86894ca46
- true
- Quick Graph
- Quick Graph
- false
- 0
- 9c62f0e6-beef-403c-9c83-e0860071b8af
- 1
-
9223
-18980
150
150
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9223.633
-18980
- -1
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- b5568a68-fe32-424e-8c33-57bdb7be33cd
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- 6fae5acb-1d7f-46ec-a1bd-b4f0011792bd
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- 05be53c1-a657-4588-ae4a-a119edd7ca8d
- Group
- afb96615-c59a-45c9-9cac-e27acb1c7ca0
- Explode
- Explode a curve into smaller segments.
- true
- b5568a68-fe32-424e-8c33-57bdb7be33cd
- true
- Explode
- Explode
-
9224
-21025
134
44
-
9295
-21003
- Curve to explode
- c96c9a02-1f26-40a5-9026-8ac73a753ab8
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- Curve
- Curve
- false
- 92df9f80-016f-455d-a9c3-bbe35cffa3bc
- 1
-
9226
-21023
57
20
-
9254.5
-21013
- Recursive decomposition until all segments are atomic
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- true
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- 0
-
9226
-21003
57
20
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9254.5
-20993
- 1
- 1
- {0}
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- 1
- Exploded segments that make up the base curve
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9307
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49
20
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9331.5
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- 1
- Vertices of the exploded segments
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- Vertices
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- 0
-
9307
-21003
49
20
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9331.5
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- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 6f1a677f-deb5-4ba0-84a4-eebb8827de33
- true
- Evaluate Length
- Evaluate Length
-
9216
-21108
149
64
-
9301
-21076
- Curve to evaluate
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- Curve
- Curve
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-
9218
-21106
71
20
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9253.5
-21096
- Length factor for curve evaluation
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- true
- Length
- Length
- false
- 0
-
9218
-21086
71
20
-
9253.5
-21076
- 1
- 1
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- If True, the Length factor is normalized (0.0 ~ 1.0)
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- true
- Normalized
- Normalized
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- 0
-
9218
-21066
71
20
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9253.5
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- 1
- 1
- {0}
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- Point at the specified length
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- Point
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- 0
-
9313
-21106
50
20
-
9338
-21096
- Tangent vector at the specified length
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- Tangent
- Tangent
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-
9313
-21086
50
20
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9338
-21076
- Curve parameter at the specified length
- 1e9137ad-19c0-44de-93b0-ed22758d1b72
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- Parameter
- Parameter
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-
9313
-21066
50
20
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9338
-21056
- 4c619bc9-39fd-4717-82a6-1e07ea237bbe
- Line SDL
- Create a line segment defined by start point, tangent and length.}
- true
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- true
- Line SDL
- Line SDL
-
9236
-22902
110
64
-
9310
-22870
- Line start point
- cccde99e-d1bb-42cb-9308-b60adc13598e
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- Start
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- 1
-
9238
-22900
60
20
-
9276
-22890
- Line tangent (direction)
- 8d269f2f-2e46-408a-b010-ea591ec9a0cd
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- Direction
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-
9238
-22880
60
20
-
9276
-22870
- 1
- 1
- {0}
-
0
0
1
- Line length
- 10f261f6-bdba-47f2-88ae-420dc21f40c9
- ABS(X)
- true
- Length
- Length
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- 1
-
9238
-22860
60
20
-
9276
-22850
- 1
- 1
- {0}
- 0.015625
- Line segment
- 401ad277-e9e4-4f79-8da6-d199f80326f0
- true
- Line
- Line
- false
- 0
-
9322
-22900
22
60
-
9333
-22870
- dd17d442-3776-40b3-ad5b-5e188b56bd4c
- Relative Differences
- Compute relative differences for a list of data
- true
- 865c8066-5247-4b0a-96a1-4424156c0cb8
- true
- Relative Differences
- Relative Differences
-
9233
-21451
116
28
-
9280
-21437
- 1
- List of data to operate on (numbers or points or vectors allowed)
- 22bbf386-4b21-4caa-b85a-18d67d6107e9
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- Values
- Values
- false
- 5be97c92-8ae7-4d99-a8a3-607079460d5e
- 1
-
9235
-21449
33
24
-
9251.5
-21437
- 1
- Differences between consecutive items
- f3da83a8-552c-4482-9825-f165df6fa732
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- Differenced
- Differenced
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- 0
-
9292
-21449
55
24
-
9319.5
-21437
- f3230ecb-3631-4d6f-86f2-ef4b2ed37f45
- Replace Nulls
- Replace nulls or invalid data with other data
- true
- dc8e38ea-6a83-4745-9d49-e94867a156af
- true
- Replace Nulls
- Replace Nulls
-
9221
-21395
139
44
-
9316
-21373
- 1
- Items to test for null
- 8156fbf8-f136-40c5-b535-ed951f9d17f7
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- Items
- Items
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- 362fefaa-7013-4c74-8cf7-e74beaf18bce
- 1
-
9223
-21393
81
20
-
9263.5
-21383
- 1
- Items to replace nulls with
- 5e913941-5ebb-4f96-9c6d-9694825347d8
- true
- Replacements
- Replacements
- false
- 0
-
9223
-21373
81
20
-
9263.5
-21363
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_Integer
- 0
- 1
- List without any nulls
- 5be97c92-8ae7-4d99-a8a3-607079460d5e
- true
- Items
- Items
- false
- 0
-
9328
-21393
30
20
-
9343
-21383
- Number of items replaced
- 2f70f5c7-6a5d-4968-9d65-4ba70ef85dca
- true
- Count
- Count
- false
- 0
-
9328
-21373
30
20
-
9343
-21363
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 362fefaa-7013-4c74-8cf7-e74beaf18bce
- true
- Relay
- false
- 0928c206-a25e-4834-9a06-eb4c248c6ef7
- 1
-
9271
-21332
40
16
-
9291
-21324
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- bced28c6-c3d6-4c77-97c8-51f4de83d178
- true
- Relay
- false
- f63f83de-17f7-454a-bc36-895bc7488c7e
- 1
-
9271
-21696
40
16
-
9291
-21688
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
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- Group
- 2dc44b22-b1dd-460a-a704-6462d6e91096
- Curve Closest Point
- Find the closest point on a curve.
- true
- 096e1e94-cef1-45dd-9170-91b3022799a9
- true
- Curve Closest Point
- Curve Closest Point
-
9237
-21196
108
64
-
9281
-21164
- Point to project onto curve
- bf711b90-da21-4a31-83ef-a5fae2b85980
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- Point
- Point
- false
- c117a95c-6877-440a-be04-f9bf41059d4b
- 1
-
9239
-21194
30
30
-
9254
-21179
- Curve to project onto
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- 8e01634f-6886-4da4-93cc-d84f2949b7f1
- 1
-
9239
-21164
30
30
-
9254
-21149
- Point on the curve closest to the base point
- 26daa500-5e3a-4c10-b67b-5c34dbb5336e
- true
- Point
- Point
- false
- 0
-
9293
-21194
50
20
-
9318
-21184
- Parameter on curve domain of closest point
- 2457c44a-4724-4030-877f-29aa2ae799f0
- true
- Parameter
- Parameter
- false
- 0
-
9293
-21174
50
20
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9318
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- Distance between base point and curve
- c0d86339-7732-4312-a9a6-a9647a257181
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- Distance
- Distance
- false
- 0
-
9293
-21154
50
20
-
9318
-21144
- 4c4e56eb-2f04-43f9-95a3-cc46a14f495a
- Line
- Create a line between two points.
- true
- 1691d791-4089-4e1a-b6a9-744569a38353
- true
- Line
- Line
-
9240
-21275
102
44
-
9306
-21253
- Line start point
- 70841617-86dd-46b4-a70d-871f1e7eb6d5
- true
- Start Point
- Start Point
- false
- 26daa500-5e3a-4c10-b67b-5c34dbb5336e
- 1
-
9242
-21273
52
20
-
9268
-21263
- Line end point
- 8a193f72-6e7c-4093-a705-db8675e7aa97
- true
- End Point
- End Point
- false
- c117a95c-6877-440a-be04-f9bf41059d4b
- 1
-
9242
-21253
52
20
-
9268
-21243
- Line segment
- 9b8925fa-9a9d-4705-8727-ff9576da78bc
- true
- Line
- Line
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- 0
-
9318
-21273
22
40
-
9329
-21253
- 2fcc2743-8339-4cdf-a046-a1f17439191d
- Remap Numbers
- Remap numbers into a new numeric domain
- true
- a1441e70-b9c0-4e1f-8831-9ef3c2ef0635
- true
- Remap Numbers
- Remap Numbers
-
9214
-22600
154
64
-
9314
-22568
- Value to remap
- cad3e760-fb48-4120-9d69-67f35f3611ad
- true
- Value
- Value
- false
- 04af94ae-ad62-46dd-bb3c-5b6585083350
- 1
-
9216
-22598
86
20
-
9259
-22588
- Source domain
- b3b78e1b-c8d1-4754-b6fa-ff02d55ecc97
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- Source
- Source
- false
- 530027ad-30c9-438e-8038-d5cadaa47365
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9216
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86
20
-
9259
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- 1
- 1
- {0}
-
0
1
- Target domain
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- Target
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- 0
-
9216
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86
20
-
9259
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- 1
- 1
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-1
1
- Remapped number
- 74f8d46b-5e69-4fb0-8e31-ece17f0b35f6
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-
9326
-22598
40
30
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9346
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- Remapped and clipped number
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- 0
-
9326
-22568
40
30
-
9346
-22553
- f44b92b0-3b5b-493a-86f4-fd7408c3daf3
- Bounds
- Create a numeric domain which encompasses a list of numbers.
- true
- e3b23a7d-af34-4738-bc62-f9f3409c8db3
- true
- Bounds
- Bounds
-
9236
-22518
110
28
-
9294
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- 1
- Numbers to include in Bounds
- beb8a25a-99b8-4e6f-b2e8-7ea93528c19d
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- Numbers
- Numbers
- false
- 04af94ae-ad62-46dd-bb3c-5b6585083350
- 1
-
9238
-22516
44
24
-
9260
-22504
- Numeric Domain between the lowest and highest numbers in {N}
- 530027ad-30c9-438e-8038-d5cadaa47365
- true
- Domain
- Domain
- false
- 0
-
9306
-22516
38
24
-
9325
-22504
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 04af94ae-ad62-46dd-bb3c-5b6585083350
- true
- Relay
-
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-
9271
-22471
40
16
-
9291
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- ce46b74e-00c9-43c4-805a-193b69ea4a11
- Multiplication
- Mathematical multiplication
- true
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- true
- Multiplication
- Multiplication
-
9256
-22799
70
44
-
9281
-22777
- 2
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- 8ec86459-bf01-4409-baee-174d0d2b13d0
- First item for multiplication
- d88e451c-a221-4a3c-bb80-172596ebe09f
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- A
- A
- true
- f4a5a11b-11a6-4bd1-bad5-e11c598ba2ee
- 1
-
9258
-22797
11
20
-
9263.5
-22787
- Second item for multiplication
- b35a5238-7c06-430d-822d-ed17cada8dd5
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- B
- B
- true
- a2ddf12f-aac3-4d45-a4fd-5a6a2862a019
- 1
-
9258
-22777
11
20
-
9263.5
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- Result of multiplication
- 47728caf-51cd-404e-8626-f3bf6658ad3e
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- 0
-
9293
-22797
31
40
-
9308.5
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- ce46b74e-00c9-43c4-805a-193b69ea4a11
- Multiplication
- Mathematical multiplication
- true
- 3ccaaeb7-75c9-4925-99f4-b7474381c81c
- true
- Multiplication
- Multiplication
-
9256
-22692
70
44
-
9281
-22670
- 2
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- First item for multiplication
- 2e7c606c-8fa0-4a11-862c-21f4feb71673
- true
- A
- A
- true
- 9264f0ff-aad0-4d8f-9480-080924b6c884
- 1
-
9258
-22690
11
20
-
9263.5
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- Second item for multiplication
- ca71652b-8a23-4fd1-ba1a-4ab427df4118
- true
- B
- B
- true
- 74f8d46b-5e69-4fb0-8e31-ece17f0b35f6
- 1
-
9258
-22670
11
20
-
9263.5
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- Result of multiplication
- f4a5a11b-11a6-4bd1-bad5-e11c598ba2ee
- true
- Result
- Result
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- 0
-
9293
-22690
31
40
-
9308.5
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- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 9264f0ff-aad0-4d8f-9480-080924b6c884
- true
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- 1a924b4b-4576-4ca9-9ace-b4586f3dbb90
- 1
-
9271
-22627
40
16
-
9291
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- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- a1441e70-b9c0-4e1f-8831-9ef3c2ef0635
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60
20
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0
0
1
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60
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22
60
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33
24
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139
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81
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- Items to replace nulls with
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81
20
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- List without any nulls
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30
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- Number of items replaced
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30
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40
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40
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255;255;255;255
- A group of Grasshopper objects
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- Find the closest point on a curve.
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- Point to project onto curve
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30
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- Curve to project onto
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30
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- Point on the curve closest to the base point
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50
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- Parameter on curve domain of closest point
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- Line end point
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52
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- Line segment
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- Remap Numbers
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- Value to remap
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- Source domain
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86
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40
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- Remapped and clipped number
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40
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- Create a numeric domain which encompasses a list of numbers.
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- Numbers to include in Bounds
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44
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- Numeric Domain between the lowest and highest numbers in {N}
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38
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- Relay
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- A wire relay object
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- Mathematical multiplication
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11
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- Second item for multiplication
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11
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11
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31
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255;255;255;255
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255;255;255;255
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255;221;160;221
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255;66;48;66
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255;255;255;255
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- Length factor for curve evaluation
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- Tangent vector at the specified length
- d4ad06af-261d-480c-9b76-80b8b35af349
- true
- Tangent
- Tangent
- false
- 0
-
9313
-27149
50
20
-
9338
-27139
- Curve parameter at the specified length
- c971b7a0-0366-4c4c-9464-7f4df888cb5a
- true
- Parameter
- Parameter
- false
- 0
-
9313
-27129
50
20
-
9338
-27119
- 2b2a4145-3dff-41d4-a8de-1ea9d29eef33
- Interpolate
- Create an interpolated curve through a set of points.
- true
- 8fa8d1cd-72e4-49a9-ac87-2091af68c9c5
- true
- Interpolate
- Interpolate
-
9178
-27547
225
84
-
9351
-27505
- 1
- Interpolation points
- 1503e6d5-6140-42c5-a21b-4dba42363436
- true
- Vertices
- Vertices
- false
- 9e6fc360-1810-4da7-a170-2f0668ae3de2
- 1
-
9180
-27545
159
20
-
9259.5
-27535
- Curve degree
- 5f85b622-d830-4a07-bff0-f8530b2c4a57
- true
- Degree
- Degree
- false
- 0
-
9180
-27525
159
20
-
9259.5
-27515
- 1
- 1
- {0}
- 1
- Periodic curve
- 58ad891d-4a3c-47c1-9618-6af0908ce9a4
- true
- Periodic
- Periodic
- false
- 0
-
9180
-27505
159
20
-
9259.5
-27495
- 1
- 1
- {0}
- false
- Knot spacing (0=uniform, 1=chord, 2=sqrtchord)
- 388ab5d7-428d-418b-90c0-96bd92120498
- true
- KnotStyle
- KnotStyle
- false
- 0
-
9180
-27485
159
20
-
9259.5
-27475
- 1
- 1
- {0}
- 2
- Resulting nurbs curve
- ff468b81-65e8-4cdf-b877-b88d817f1f2d
- true
- Curve
- Curve
- false
- 0
-
9363
-27545
38
26
-
9382
-27531.67
- Curve length
- bea94d63-6267-4a46-a8cc-af7392801828
- true
- Length
- Length
- false
- 0
-
9363
-27519
38
27
-
9382
-27505
- Curve domain
- dd30a448-ca31-4e64-90d5-cc9c40a7c8b3
- true
- Domain
- Domain
- false
- 0
-
9363
-27492
38
27
-
9382
-27478.33
- 76975309-75a6-446a-afed-f8653720a9f2
- Create Material
- Create an OpenGL material.
- true
- 5124b1bb-140f-4743-8c53-2e30544ed43f
- true
- Create Material
- Create Material
-
9215
-27674
152
104
-
9313
-27622
- Colour of the diffuse channel
- cc1605ca-daf4-460a-b0a4-67130800bed4
- true
- Diffuse
- Diffuse
- false
- 0
-
9217
-27672
84
20
-
9259
-27662
- 1
- 1
- {0}
-
255;199;199;199
- Colour of the specular highlight
- 626b5cae-5f16-4066-9743-736557a29475
- true
- Specular
- Specular
- false
- 0
-
9217
-27652
84
20
-
9259
-27642
- 1
- 1
- {0}
-
255;0;255;255
- Emissive colour of the material
- 5869d24e-a5b5-410d-82a1-847611623bed
- true
- Emission
- Emission
- false
- 0
-
9217
-27632
84
20
-
9259
-27622
- 1
- 1
- {0}
-
255;0;0;0
- Amount of transparency (0.0 = opaque, 1.0 = transparent
- 3b1b263e-3d61-47b4-95c4-821fcef67b0b
- true
- Transparency
- Transparency
- false
- 0
-
9217
-27612
84
20
-
9259
-27602
- 1
- 1
- {0}
- 0.5
- Amount of shinyness (0 = none, 1 = low shine, 100 = max shine
- d4f5488e-4a4f-4c05-a6b7-8bd31d59b4c7
- true
- Shine
- Shine
- false
- 0
-
9217
-27592
84
20
-
9259
-27582
- 1
- 1
- {0}
- 100
- Resulting material
- 1bed5aa6-f478-4993-a204-8cfa72a07424
- true
- Material
- Material
- false
- 0
-
9325
-27672
40
100
-
9345
-27622
- 537b0419-bbc2-4ff4-bf08-afe526367b2c
- Custom Preview
- Allows for customized geometry previews
- true
- true
- c4521450-b023-4163-9d6b-30e587776f8e
- true
- Custom Preview
- Custom Preview
-
9253
-27740
76
44
-
9315
-27718
- Geometry to preview
- true
- 472a7ba1-052c-4737-85e3-2e7db5b49ee0
- true
- Geometry
- Geometry
- false
- ff468b81-65e8-4cdf-b877-b88d817f1f2d
- 1
-
9255
-27738
48
20
-
9279
-27728
- The material override
- 2808fa60-8978-4b6d-ae88-09a8be1d2563
- true
- Material
- Material
- false
- 1bed5aa6-f478-4993-a204-8cfa72a07424
- 1
-
9255
-27718
48
20
-
9279
-27708
- 1
- 1
- {0}
-
255;221;160;221
-
255;66;48;66
- 0.5
-
255;255;255;255
- 0
- 2b69bf71-4e69-43aa-b7be-4f6ce7e45bef
- Quick Graph
- 1
- Display a set of y-values as a graph
- fd00589e-5724-4407-aa46-ebe1d9f1b38d
- true
- Quick Graph
- Quick Graph
- false
- 0
- 238ccd66-333b-42be-b89d-c7a89f7d43cf
- 1
-
9223
-25917
150
150
-
9223.633
-25917
- -1
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- e55852e6-434c-4d81-ab8c-e702dfd1db4f
- e41c1b6a-7e1e-47d5-ab71-6b7f6f04b606
- 444edb66-366a-4115-b54d-07922398f854
- f6594335-7ff6-4c1e-aeb7-c9c8948883d4
- fd47e2e2-6481-4a34-a847-a0d1a632bc53
- 99c7fe47-7a69-4ff0-8cd8-12aa4d14e36a
- 729637d9-ea91-4c07-8b5a-52ac9c43759a
- a189e3aa-b04e-41b2-af57-783026734fbd
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- 213ef2cd-1c24-4d88-8ee3-8563f616e74b
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- e555088f-a229-4d25-a883-c447edfca1c2
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- ba7905ed-fef6-48c1-8baf-dc7e08645b2a
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- 8fe511eb-1233-498f-a8f7-d34dd4f617ff
- 158188ab-8318-49ab-bbb3-3b4c147e50a1
- 1529fdbf-9759-4d95-a555-19007f500439
- 4ac110ab-0df5-451c-94d6-c95b7b9e23dd
- 1ffd60e1-d5b8-48d2-85e8-77a63ab7786b
- 943c2602-b35d-4dea-b150-9f279be49248
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- 56934943-a19b-4a05-becd-bb3668f0a912
- 607e639e-e8c3-4263-aa73-c9a6384689bc
- 5bd5d6db-12a2-4550-8b71-deb45f3888b0
- 5f214b8c-7d05-4368-8735-afd3d68a4fce
- 87aee7ec-7851-4cc6-8c7c-6d39908c9364
- 33
- a6960d2a-4824-4efb-81eb-96c9415b7919
- Group
- afb96615-c59a-45c9-9cac-e27acb1c7ca0
- Explode
- Explode a curve into smaller segments.
- true
- e55852e6-434c-4d81-ab8c-e702dfd1db4f
- true
- Explode
- Explode
-
9224
-27877
134
44
-
9295
-27855
- Curve to explode
- fde358cc-c101-4588-9436-44d67db87bad
- true
- Curve
- Curve
- false
- ff468b81-65e8-4cdf-b877-b88d817f1f2d
- 1
-
9226
-27875
57
20
-
9254.5
-27865
- Recursive decomposition until all segments are atomic
- 4ce8a128-9d38-4d5f-a8bf-02afc1631152
- true
- Recursive
- Recursive
- false
- 0
-
9226
-27855
57
20
-
9254.5
-27845
- 1
- 1
- {0}
- true
- 1
- Exploded segments that make up the base curve
- cfe0de88-5b8a-4ce6-9bc2-9c9bfa54cc0b
- true
- Segments
- Segments
- false
- 0
-
9307
-27875
49
20
-
9331.5
-27865
- 1
- Vertices of the exploded segments
- 551c18cf-2aef-4fe0-a831-c8f2defa03b1
- true
- Vertices
- Vertices
- false
- 0
-
9307
-27855
49
20
-
9331.5
-27845
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- e41c1b6a-7e1e-47d5-ab71-6b7f6f04b606
- true
- Evaluate Length
- Evaluate Length
-
9216
-27960
149
64
-
9301
-27928
- Curve to evaluate
- 3b337348-6b71-448c-900a-d9054ef19368
- true
- Curve
- Curve
- false
- cfe0de88-5b8a-4ce6-9bc2-9c9bfa54cc0b
- 1
-
9218
-27958
71
20
-
9253.5
-27948
- Length factor for curve evaluation
- 652c5ab2-febc-4340-94df-6611e53df831
- true
- Length
- Length
- false
- 0
-
9218
-27938
71
20
-
9253.5
-27928
- 1
- 1
- {0}
- 0.5
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 9ec37965-bbaa-472e-adc1-1aa463e2e77f
- true
- Normalized
- Normalized
- false
- 0
-
9218
-27918
71
20
-
9253.5
-27908
- 1
- 1
- {0}
- true
- Point at the specified length
- 4078e208-ec63-43ca-9706-3bca2f569fa2
- true
- Point
- Point
- false
- 0
-
9313
-27958
50
20
-
9338
-27948
- Tangent vector at the specified length
- ed55b185-60fb-40cd-ad46-0842867be581
- true
- Tangent
- Tangent
- false
- 0
-
9313
-27938
50
20
-
9338
-27928
- Curve parameter at the specified length
- a5197d5c-aa87-4482-aaba-20779b7b231e
- true
- Parameter
- Parameter
- false
- 0
-
9313
-27918
50
20
-
9338
-27908
- 4c619bc9-39fd-4717-82a6-1e07ea237bbe
- Line SDL
- Create a line segment defined by start point, tangent and length.}
- true
- 444edb66-366a-4115-b54d-07922398f854
- true
- Line SDL
- Line SDL
-
9236
-29740
110
64
-
9310
-29708
- Line start point
- 71f5a683-8e56-4a2f-81f8-5f9808eddf57
- true
- Start
- Start
- false
- 4078e208-ec63-43ca-9706-3bca2f569fa2
- 1
-
9238
-29738
60
20
-
9276
-29728
- Line tangent (direction)
- ec34afb2-cc43-4614-b556-168228e82c6d
- true
- Direction
- Direction
- false
- be3b8f9c-1ae0-439a-bdb8-a5dd226cecc3
- 1
-
9238
-29718
60
20
-
9276
-29708
- 1
- 1
- {0}
-
0
0
1
- Line length
- 45490cfc-ec73-4dfd-a9b5-496410006025
- ABS(X)
- true
- Length
- Length
- false
- 139422c8-a710-487e-bbe0-ea2b6259e8e1
- 1
-
9238
-29698
60
20
-
9276
-29688
- 1
- 1
- {0}
- 0.015625
- Line segment
- 1c102dcf-a427-4f9a-93eb-d8fa6673d9fa
- true
- Line
- Line
- false
- 0
-
9322
-29738
22
60
-
9333
-29708
- dd17d442-3776-40b3-ad5b-5e188b56bd4c
- Relative Differences
- Compute relative differences for a list of data
- true
- f6594335-7ff6-4c1e-aeb7-c9c8948883d4
- true
- Relative Differences
- Relative Differences
-
9233
-28303
116
28
-
9280
-28289
- 1
- List of data to operate on (numbers or points or vectors allowed)
- 043e55bf-142c-4061-bcd6-66fad571d11f
- true
- Values
- Values
- false
- 5f33bac4-8ad0-4ac6-a703-b653e22e896d
- 1
-
9235
-28301
33
24
-
9251.5
-28289
- 1
- Differences between consecutive items
- 2d37b54a-d252-4d91-af08-37f5c09e7e4a
- true
- Differenced
- Differenced
- false
- 0
-
9292
-28301
55
24
-
9319.5
-28289
- f3230ecb-3631-4d6f-86f2-ef4b2ed37f45
- Replace Nulls
- Replace nulls or invalid data with other data
- true
- fd47e2e2-6481-4a34-a847-a0d1a632bc53
- true
- Replace Nulls
- Replace Nulls
-
9221
-28247
139
44
-
9316
-28225
- 1
- Items to test for null
- bcfd659f-ade9-4f4d-b929-0f87d1db74db
- true
- Items
- Items
- false
- 9fba3251-1d1c-4127-a406-05630ef73176
- 1
-
9223
-28245
81
20
-
9263.5
-28235
- 1
- Items to replace nulls with
- a3f4d718-1001-4437-b607-f5fed9eff18a
- true
- Replacements
- Replacements
- false
- 0
-
9223
-28225
81
20
-
9263.5
-28215
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_Integer
- 0
- 1
- List without any nulls
- 5f33bac4-8ad0-4ac6-a703-b653e22e896d
- true
- Items
- Items
- false
- 0
-
9328
-28245
30
20
-
9343
-28235
- Number of items replaced
- 29929c88-87bc-4ed9-a28e-5f9a48da5860
- true
- Count
- Count
- false
- 0
-
9328
-28225
30
20
-
9343
-28215
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 9fba3251-1d1c-4127-a406-05630ef73176
- true
- Relay
- false
- ff917474-e27a-48ee-86c6-2399e98eb9b3
- 1
-
9271
-28184
40
16
-
9291
-28176
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 213ef2cd-1c24-4d88-8ee3-8563f616e74b
- true
- Relay
- false
- d57b5cda-0b57-4731-b527-b630d209be02
- 1
-
9271
-28548
40
16
-
9291
-28540
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- f6594335-7ff6-4c1e-aeb7-c9c8948883d4
- fd47e2e2-6481-4a34-a847-a0d1a632bc53
- 99c7fe47-7a69-4ff0-8cd8-12aa4d14e36a
- 729637d9-ea91-4c07-8b5a-52ac9c43759a
- a189e3aa-b04e-41b2-af57-783026734fbd
- 9fba3251-1d1c-4127-a406-05630ef73176
- 213ef2cd-1c24-4d88-8ee3-8563f616e74b
- ff2559cf-18b3-4cad-b391-315893967bf2
- 8
- 2c7854ff-ba1a-4fcd-9046-0142fe519f22
- Group
- 2dc44b22-b1dd-460a-a704-6462d6e91096
- Curve Closest Point
- Find the closest point on a curve.
- true
- e555088f-a229-4d25-a883-c447edfca1c2
- true
- Curve Closest Point
- Curve Closest Point
-
9237
-28048
108
64
-
9281
-28016
- Point to project onto curve
- 2fc6035a-a04a-413f-baf6-93f6cb789341
- true
- Point
- Point
- false
- 4078e208-ec63-43ca-9706-3bca2f569fa2
- 1
-
9239
-28046
30
30
-
9254
-28031
- Curve to project onto
- 36e46100-a361-4382-a21f-dd07040a60fa
- true
- Curve
- Curve
- false
- 8e01634f-6886-4da4-93cc-d84f2949b7f1
- 1
-
9239
-28016
30
30
-
9254
-28001
- Point on the curve closest to the base point
- 22edc7d2-47d5-4d3c-a9fb-41003038da00
- true
- Point
- Point
- false
- 0
-
9293
-28046
50
20
-
9318
-28036
- Parameter on curve domain of closest point
- 679c843b-31f4-4e05-b990-e840a91b4713
- true
- Parameter
- Parameter
- false
- 0
-
9293
-28026
50
20
-
9318
-28016
- Distance between base point and curve
- 6fa34270-3ef8-41fd-a4a1-154817bd8fb9
- true
- Distance
- Distance
- false
- 0
-
9293
-28006
50
20
-
9318
-27996
- 4c4e56eb-2f04-43f9-95a3-cc46a14f495a
- Line
- Create a line between two points.
- true
- c157fa6a-b9b5-4759-829e-44e742af0c34
- true
- Line
- Line
-
9240
-28127
102
44
-
9306
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- Line start point
- 532c7d06-0798-454c-b064-4aa4fde692f2
- true
- Start Point
- Start Point
- false
- 22edc7d2-47d5-4d3c-a9fb-41003038da00
- 1
-
9242
-28125
52
20
-
9268
-28115
- Line end point
- 3e6668db-752b-441c-b990-86c413d3d4fc
- true
- End Point
- End Point
- false
- 4078e208-ec63-43ca-9706-3bca2f569fa2
- 1
-
9242
-28105
52
20
-
9268
-28095
- Line segment
- be3b8f9c-1ae0-439a-bdb8-a5dd226cecc3
- true
- Line
- Line
- false
- 0
-
9318
-28125
22
40
-
9329
-28105
- 2fcc2743-8339-4cdf-a046-a1f17439191d
- Remap Numbers
- Remap numbers into a new numeric domain
- true
- 4bfb41bf-3699-4f84-abbf-207c269d8b11
- true
- Remap Numbers
- Remap Numbers
-
9214
-29438
154
64
-
9314
-29406
- Value to remap
- aed1de46-96e2-40d5-b0dc-907537d31c19
- true
- Value
- Value
- false
- ea2d8131-d849-464b-991d-b7545490c298
- 1
-
9216
-29436
86
20
-
9259
-29426
- Source domain
- 15c453f5-b34f-4aaf-a5aa-9fba87008cbe
- true
- Source
- Source
- false
- 0fea1294-960c-4c43-acef-e8daa16a43a9
- 1
-
9216
-29416
86
20
-
9259
-29406
- 1
- 1
- {0}
-
0
1
- Target domain
- fef59a1b-601a-49d7-bc54-e0b0a37dd6b1
- true
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- Curve Degree
- Get the degree value of a curve.
- true
- dd4f9b33-eb2f-4c2c-a9da-2d65d6783044
- true
- Curve Degree
- Curve Degree
-
9252
-1079
94
28
-
9296
-1065
- Curve to get the degree value of
- 6a0046e4-5b4d-448f-b2b4-cade479dcad1
- true
- Curve
- Curve
- false
- ee782a63-64f0-4f70-a960-95d38003cbb3
- 1
-
9254
-1077
30
24
-
9269
-1065
- Degree value of the curve
- 272db34b-cb01-4ac1-bae9-e94d23c75f3c
- true
- Degree
- Degree
- false
- 0
-
9308
-1077
36
24
-
9326
-1065
- 9df5e896-552d-4c8c-b9ca-4fc147ffa022
- Expression
- Evaluate an expression
- A-B+1
- true
- d2d17992-1f6a-41ce-a0e5-0a8d83ef92d2
- true
- Expression
- Expression
-
9245
-1275
108
44
-
9289
-1253
- 2
- ba80fd98-91a1-4958-b6a7-a94e40e52bdb
- ba80fd98-91a1-4958-b6a7-a94e40e52bdb
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Expression variable
- 9756e426-55fb-4678-a28c-dee3f43c22e5
- true
- Variable A
- A
- true
- a927a6be-3516-43fe-8365-bf443ef1923b
- 1
-
9247
-1273
11
20
-
9252.5
-1263
- Expression variable
- 211996a5-6e8a-4a9c-88db-d132592dde1e
- true
- Variable B
- B
- true
- 272db34b-cb01-4ac1-bae9-e94d23c75f3c
- 1
-
9247
-1253
11
20
-
9252.5
-1243
- Result of expression
- 82cdb6c5-d11c-4816-899a-ec7feeb75410
- true
- Result
- Result
- false
- 0
-
9320
-1273
31
40
-
9335.5
-1253
- 448de216-3a12-43cf-a135-e3bfafc87744
- B
- Second item for multiplication
- 12e4c4ab-282e-49fd-8fbc-2e50fd9bf37a
- true
- B
- B
- false
- 0
-
9261
-12026
60
24
- 448de216-3a12-43cf-a135-e3bfafc87744
- B
- Second item for multiplication
- fba3b68f-f744-41d4-b4d2-9d899b5a7f88
- true
- B
- B
- false
- 0
-
9261
-15586
60
24
- 448de216-3a12-43cf-a135-e3bfafc87744
- B
- Second item for multiplication
- 8b4a365c-1645-430f-8be6-7fb0019a20f5
- true
- B
- B
- false
- 0
-
9262
-19286
60
24
- 448de216-3a12-43cf-a135-e3bfafc87744
- B
- Second item for multiplication
- 3d196e4e-a427-48b3-a97c-9aae81c0ab45
- true
- B
- B
- false
- 0
-
9261
-22740
60
24
- 448de216-3a12-43cf-a135-e3bfafc87744
- B
- Second item for multiplication
- ab1ac911-2029-4ebc-a2e6-4e954cd90453
- true
- B
- B
- false
- 0
-
9259
-26232
60
24
- 448de216-3a12-43cf-a135-e3bfafc87744
- B
- Second item for multiplication
- 899223b6-df9a-403e-bae3-eb7c226d4aab
- true
- B
- B
- false
- 0
-
9261
-29565
60
24
- a4b285fe-2e13-4204-b65c-189aa6704da5
- Relay
- A wire relay object
- 62804d7b-bdd9-4ed1-b6e5-f970e801b6a3
- true
- Relay
-
- false
- 9c62f0e6-beef-403c-9c83-e0860071b8af
- 1
-
9261
-18356
60
24
- a4b285fe-2e13-4204-b65c-189aa6704da5
- Relay
- A wire relay object
- 55512720-2a0e-47cd-b00a-dc2b37b30de5
- true
- Relay
-
- false
- 7af0cade-f743-4780-907e-050ed9fcd4f9
- 1
-
9261
-21791
60
24
- a4b285fe-2e13-4204-b65c-189aa6704da5
- Relay
- A wire relay object
- a7aa0c22-62a5-48d9-8db9-35e295bd33c0
- true
- Relay
-
- false
- 238ccd66-333b-42be-b89d-c7a89f7d43cf
- 1
-
9261
-25268
60
24
- a4b285fe-2e13-4204-b65c-189aa6704da5
- Relay
- A wire relay object
- 2f70e9a1-868c-4cc1-a692-dd23505afa99
- true
- Relay
-
- false
- 4ac110ab-0df5-451c-94d6-c95b7b9e23dd
- 1
-
9261
-28628
60
24
- 4fdfe351-6c07-47ce-9fb9-be027fb62186
- Shift List
- Offset all items in a list.
- true
- 532c0140-0dbd-4867-a53d-0a5b1e3f1497
- true
- Shift List
-
-
9264
-7434
53
64
-
9297
-7402
- 1
- List to shift
- 7d76ee9a-e8ec-4986-8d85-406e5c4305d4
- true
- List
-
- false
- 0184d168-0386-49c1-b31a-26709654c038
- 1
-
9266
-7432
19
20
-
9275.5
-7422
- Shift offset
- a96c7aa5-08ee-40cc-a832-e9d67163b5a8
- true
- Shift
-
- false
- 0
-
9266
-7412
19
20
-
9275.5
-7402
- 1
- 1
- {0}
- 1
- Wrap values
- 40b4295e-9407-40bf-80d0-c4d99f8a0aeb
- true
- Wrap
-
- false
- 0
-
9266
-7392
19
20
-
9275.5
-7382
- 1
- 1
- {0}
- false
- 1
- Shifted list
- 738d8220-3b26-49b2-a359-0fc4d671538d
- true
- List
-
- false
- 0
-
9309
-7432
6
60
-
9312
-7402
- 4fdfe351-6c07-47ce-9fb9-be027fb62186
- Shift List
- Offset all items in a list.
- true
- 46418f77-df32-4b35-861e-15218fba9785
- true
- Shift List
-
-
9264
-10955
53
64
-
9297
-10923
- 1
- List to shift
- 109e878a-7998-4679-b117-34d7b6cf17de
- true
- List
-
- false
- 7338c244-af88-4723-b45a-08577283c18b
- 1
-
9266
-10953
19
20
-
9275.5
-10943
- Shift offset
- 0544d4a8-798d-4542-bf03-ac1d99f27a76
- true
- Shift
-
- false
- 0
-
9266
-10933
19
20
-
9275.5
-10923
- 1
- 1
- {0}
- 1
- Wrap values
- 2533a264-171f-404e-a1c6-c06a3b9b8e6f
- true
- Wrap
-
- false
- 0
-
9266
-10913
19
20
-
9275.5
-10903
- 1
- 1
- {0}
- false
- 1
- Shifted list
- 95512bec-3e3b-4a1e-968f-fdd54a0ed3fb
- true
- List
-
- false
- 0
-
9309
-10953
6
60
-
9312
-10923
- 4fdfe351-6c07-47ce-9fb9-be027fb62186
- Shift List
- Offset all items in a list.
- true
- 8fd33484-455a-46bc-a886-7e889984cd34
- true
- Shift List
-
-
9264
-14390
53
64
-
9297
-14358
- 1
- List to shift
- be257533-ca89-454e-b4ba-f9b6b4680c16
- true
- List
-
- false
- 72af1623-98b2-41a3-b5a9-7e1bda1d7111
- 1
-
9266
-14388
19
20
-
9275.5
-14378
- Shift offset
- 2d8260d3-7cf6-48ff-a5e8-331b238050bf
- true
- Shift
-
- false
- 0
-
9266
-14368
19
20
-
9275.5
-14358
- 1
- 1
- {0}
- 1
- Wrap values
- 600f582c-be8c-4052-b082-957c3db424ca
- true
- Wrap
-
- false
- 0
-
9266
-14348
19
20
-
9275.5
-14338
- 1
- 1
- {0}
- false
- 1
- Shifted list
- 5fcafa9d-43c7-4d8e-b1fa-7217ab260d93
- true
- List
-
- false
- 0
-
9309
-14388
6
60
-
9312
-14358
- 758d91a0-4aec-47f8-9671-16739a8a2c5d
- Format
- Format some data using placeholders and formatting tags
- true
- 03e206f6-06e3-45a0-bd1b-462b7509ec07
- true
- Format
- Format
-
9234
-2581
130
64
-
9326
-2549
- 3
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- 7fa15783-70da-485c-98c0-a099e6988c3e
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- Text format
- 60aa4b83-1c3e-42c0-a0fc-3958ecd7d990
- true
- Format
- Format
- false
- 0
-
9236
-2579
78
20
-
9275
-2569
- 1
- 1
- {0}
- false
- {0:R}
- Formatting culture
- 961c16c0-6ded-4a47-a9b4-6bac4a3ee77c
- true
- Culture
- Culture
- false
- 0
-
9236
-2559
78
20
-
9275
-2549
- 1
- 1
- {0}
- 127
- Data to insert at {0} placeholders
- a12fa6e2-f7e6-44db-89fd-2ee48c469cd2
- true
- false
- Data 0
- 0
- true
- 2cd82ac7-4de3-4efd-b21c-bb675514f953
- 1
-
9236
-2539
78
20
-
9275
-2529
- Formatted text
- ad720d66-d245-44d9-b76a-dafa2c256b04
- true
- Text
- Text
- false
- 0
-
9338
-2579
24
60
-
9350
-2549
- 758d91a0-4aec-47f8-9671-16739a8a2c5d
- Format
- Format some data using placeholders and formatting tags
- true
- 939ec527-c895-4c10-8020-fc9e4da28bdd
- true
- Format
- Format
-
9234
-3425
130
64
-
9326
-3393
- 3
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- 7fa15783-70da-485c-98c0-a099e6988c3e
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- Text format
- b40b6ba6-8d3b-4054-a253-f920a6f3f288
- true
- Format
- Format
- false
- 0
-
9236
-3423
78
20
-
9275
-3413
- 1
- 1
- {0}
- false
- {0:R}
- Formatting culture
- 6e07828a-1ec4-4e71-8198-90b5c6d06fdd
- true
- Culture
- Culture
- false
- 0
-
9236
-3403
78
20
-
9275
-3393
- 1
- 1
- {0}
- 127
- Data to insert at {0} placeholders
- 2cfebbbe-71fe-4a4a-acdc-4ef62d2bc7f4
- true
- false
- Data 0
- 0
- true
- 94c91859-db24-4e5a-aaa7-9df679d51de2
- 1
-
9236
-3383
78
20
-
9275
-3373
- Formatted text
- 2ee62344-eed2-47d2-aae3-277cb264e100
- true
- Text
- Text
- false
- 0
-
9338
-3423
24
60
-
9350
-3393
- 758d91a0-4aec-47f8-9671-16739a8a2c5d
- Format
- Format some data using placeholders and formatting tags
- true
- f7c23408-ec08-4cd6-9afd-7fd502247d57
- true
- Format
- Format
-
9226
-7698
130
64
-
9318
-7666
- 3
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- 7fa15783-70da-485c-98c0-a099e6988c3e
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- Text format
- 5dc2652c-c8e1-468a-b333-c5da7a8fe3b3
- true
- Format
- Format
- false
- 0
-
9228
-7696
78
20
-
9267
-7686
- 1
- 1
- {0}
- false
- {0:R}
- Formatting culture
- 618ca455-8d0f-4f78-befe-37c22b75ce12
- true
- Culture
- Culture
- false
- 0
-
9228
-7676
78
20
-
9267
-7666
- 1
- 1
- {0}
- 127
- Data to insert at {0} placeholders
- 06eab3da-eb92-49cc-8526-a9f59c60cae8
- true
- false
- Data 0
- 0
- true
- dd7ae928-e56d-4423-b7b1-b1999182a279
- 1
-
9228
-7656
78
20
-
9267
-7646
- Formatted text
- e96b0bfa-693f-4be8-bcb4-c9e4a7df9692
- true
- Text
- Text
- false
- 0
-
9330
-7696
24
60
-
9342
-7666
- 758d91a0-4aec-47f8-9671-16739a8a2c5d
- Format
- Format some data using placeholders and formatting tags
- true
- 318a5c49-4892-4094-b625-e4cbecc814eb
- true
- Format
- Format
-
9226
-11218
130
64
-
9318
-11186
- 3
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- 7fa15783-70da-485c-98c0-a099e6988c3e
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- Text format
- 1c5694f5-cf69-4c42-a1bb-3da554b0635c
- true
- Format
- Format
- false
- 0
-
9228
-11216
78
20
-
9267
-11206
- 1
- 1
- {0}
- false
- {0:R}
- Formatting culture
- c5c61685-06d4-441e-9a4c-b2d1b2631663
- true
- Culture
- Culture
- false
- 0
-
9228
-11196
78
20
-
9267
-11186
- 1
- 1
- {0}
- 127
- Data to insert at {0} placeholders
- 09e97d28-ec29-4afe-8e36-634ce9ae03a8
- true
- false
- Data 0
- 0
- true
- 05a6550e-e7dc-41fc-8983-e7c430ad5012
- 1
-
9228
-11176
78
20
-
9267
-11166
- Formatted text
- 5a745073-b64d-4e12-bfb6-7d824ab5280e
- true
- Text
- Text
- false
- 0
-
9330
-11216
24
60
-
9342
-11186
- 758d91a0-4aec-47f8-9671-16739a8a2c5d
- Format
- Format some data using placeholders and formatting tags
- true
- 8e870804-f0af-411f-a9d2-ed416c5c6187
- true
- Format
- Format
-
9226
-14674
130
64
-
9318
-14642
- 3
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- 7fa15783-70da-485c-98c0-a099e6988c3e
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- Text format
- 520f052e-3f14-4220-ac0e-0b03931a1266
- true
- Format
- Format
- false
- 0
-
9228
-14672
78
20
-
9267
-14662
- 1
- 1
- {0}
- false
- {0:R}
- Formatting culture
- 19f9fdd9-7ac8-42d6-978d-356e3e565021
- true
- Culture
- Culture
- false
- 0
-
9228
-14652
78
20
-
9267
-14642
- 1
- 1
- {0}
- 127
- Data to insert at {0} placeholders
- dd7860ba-e2ad-44a8-a3cf-a0d9a45c0842
- true
- false
- Data 0
- 0
- true
- e9df2d08-5a93-4bb4-9361-d5b6b5a545a5
- 1
-
9228
-14632
78
20
-
9267
-14622
- Formatted text
- 3d034f31-d797-4424-8cef-9499e7099fc1
- true
- Text
- Text
- false
- 0
-
9330
-14672
24
60
-
9342
-14642
- 758d91a0-4aec-47f8-9671-16739a8a2c5d
- Format
- Format some data using placeholders and formatting tags
- true
- 7ce3ce15-850b-45e1-ad59-92f757c03b5c
- true
- Format
- Format
-
9226
-18461
130
64
-
9318
-18429
- 3
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- 7fa15783-70da-485c-98c0-a099e6988c3e
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- Text format
- 40164056-ab05-4230-b49c-dd067f9305d2
- true
- Format
- Format
- false
- 0
-
9228
-18459
78
20
-
9267
-18449
- 1
- 1
- {0}
- false
- {0:R}
- Formatting culture
- 2db5bc1b-d60e-4c5c-8b12-9a60741a0086
- true
- Culture
- Culture
- false
- 0
-
9228
-18439
78
20
-
9267
-18429
- 1
- 1
- {0}
- 127
- Data to insert at {0} placeholders
- de3f0b39-9873-400d-b1b9-85a5e16c03e0
- true
- false
- Data 0
- 0
- true
- 9c62f0e6-beef-403c-9c83-e0860071b8af
- 1
-
9228
-18419
78
20
-
9267
-18409
- Formatted text
- 84721e9b-8e00-4fcb-9746-ae1b23e91d8d
- true
- Text
- Text
- false
- 0
-
9330
-18459
24
60
-
9342
-18429
- 758d91a0-4aec-47f8-9671-16739a8a2c5d
- Format
- Format some data using placeholders and formatting tags
- true
- 1ef06ab7-bb52-421b-9d4f-0f74a7b338d7
- true
- Format
- Format
-
9226
-21883
130
64
-
9318
-21851
- 3
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- 7fa15783-70da-485c-98c0-a099e6988c3e
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- Text format
- c23477a4-43c8-4198-a584-157e995bc70d
- true
- Format
- Format
- false
- 0
-
9228
-21881
78
20
-
9267
-21871
- 1
- 1
- {0}
- false
- {0:R}
- Formatting culture
- abd47b9e-8af3-4412-b330-03721da886d7
- true
- Culture
- Culture
- false
- 0
-
9228
-21861
78
20
-
9267
-21851
- 1
- 1
- {0}
- 127
- Data to insert at {0} placeholders
- 31b965f4-66e2-43d6-bc73-414c25ca61bd
- true
- false
- Data 0
- 0
- true
- 7af0cade-f743-4780-907e-050ed9fcd4f9
- 1
-
9228
-21841
78
20
-
9267
-21831
- Formatted text
- 9ea884c7-deed-4580-b340-ef5d5dc73681
- true
- Text
- Text
- false
- 0
-
9330
-21881
24
60
-
9342
-21851
- 758d91a0-4aec-47f8-9671-16739a8a2c5d
- Format
- Format some data using placeholders and formatting tags
- true
- 3971560d-877c-4cb3-9aad-0356911759f5
- true
- Format
- Format
-
9226
-25385
130
64
-
9318
-25353
- 3
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- 7fa15783-70da-485c-98c0-a099e6988c3e
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- Text format
- ea427ec3-5a35-4520-8ccf-18df23fc6a20
- true
- Format
- Format
- false
- 0
-
9228
-25383
78
20
-
9267
-25373
- 1
- 1
- {0}
- false
- {0:R}
- Formatting culture
- 933deb80-43d7-4dd9-b413-0db54ca26dd1
- true
- Culture
- Culture
- false
- 0
-
9228
-25363
78
20
-
9267
-25353
- 1
- 1
- {0}
- 127
- Data to insert at {0} placeholders
- b0eac621-7855-4073-b49b-fa4116b4784d
- true
- false
- Data 0
- 0
- true
- 238ccd66-333b-42be-b89d-c7a89f7d43cf
- 1
-
9228
-25343
78
20
-
9267
-25333
- Formatted text
- e7099fe1-9f7c-49ca-bf44-6736df5e3b63
- true
- Text
- Text
- false
- 0
-
9330
-25383
24
60
-
9342
-25353
- 758d91a0-4aec-47f8-9671-16739a8a2c5d
- Format
- Format some data using placeholders and formatting tags
- true
- c4c5c32f-2de8-427e-a283-c44a57d51434
- true
- Format
- Format
-
9226
-28732
130
64
-
9318
-28700
- 3
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- 7fa15783-70da-485c-98c0-a099e6988c3e
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- Text format
- bbd9f5ee-62b0-4987-bce7-1fe240ab5162
- true
- Format
- Format
- false
- 0
-
9228
-28730
78
20
-
9267
-28720
- 1
- 1
- {0}
- false
- {0:R}
- Formatting culture
- e20d6918-7775-473e-a0be-b717596cb7dd
- true
- Culture
- Culture
- false
- 0
-
9228
-28710
78
20
-
9267
-28700
- 1
- 1
- {0}
- 127
- Data to insert at {0} placeholders
- ce53e26b-c513-4d62-be4c-647c68ce1540
- true
- false
- Data 0
- 0
- true
- 4ac110ab-0df5-451c-94d6-c95b7b9e23dd
- 1
-
9228
-28690
78
20
-
9267
-28680
- Formatted text
- d93f190c-e272-4223-ac4d-69ddd085d784
- true
- Text
- Text
- false
- 0
-
9330
-28730
24
60
-
9342
-28700
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- 81eaa78b-b49c-4af4-a9e1-8ed2469b4e8c
- a03f91ac-0515-47e3-b1da-acb30c73ba6d
- 72305306-f2af-43c4-9fd0-d3e8e9bc541b
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- 8fa1b443-91a1-419e-a698-39f89d98c35f
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- 33
- 215e0185-7f41-4f11-9037-ea048af906f5
- Group
- afb96615-c59a-45c9-9cac-e27acb1c7ca0
- Explode
- Explode a curve into smaller segments.
- true
- 81eaa78b-b49c-4af4-a9e1-8ed2469b4e8c
- true
- Explode
- Explode
-
9224
-31204
134
44
-
9295
-31182
- Curve to explode
- 757b62fd-392a-4568-8b6b-502c736a7d1a
- true
- Curve
- Curve
- false
- 82d46f90-f3a3-4dc9-bab4-8b7484395e05
- 1
-
9226
-31202
57
20
-
9254.5
-31192
- Recursive decomposition until all segments are atomic
- 0baeb68c-d1b8-42b0-96d5-9fadc48e843b
- true
- Recursive
- Recursive
- false
- 0
-
9226
-31182
57
20
-
9254.5
-31172
- 1
- 1
- {0}
- true
- 1
- Exploded segments that make up the base curve
- fe3f9ab1-bf7b-4288-8d97-e7946294e33c
- true
- Segments
- Segments
- false
- 0
-
9307
-31202
49
20
-
9331.5
-31192
- 1
- Vertices of the exploded segments
- e0fac1f1-e34c-460c-bca6-4d652b5d1e7c
- true
- Vertices
- Vertices
- false
- 0
-
9307
-31182
49
20
-
9331.5
-31172
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- a03f91ac-0515-47e3-b1da-acb30c73ba6d
- true
- Evaluate Length
- Evaluate Length
-
9216
-31287
149
64
-
9301
-31255
- Curve to evaluate
- dd3f8489-93cb-466e-a726-1d6ce1c1fa21
- true
- Curve
- Curve
- false
- fe3f9ab1-bf7b-4288-8d97-e7946294e33c
- 1
-
9218
-31285
71
20
-
9253.5
-31275
- Length factor for curve evaluation
- 71c1961c-f265-4c01-a5d9-26dc87f04220
- true
- Length
- Length
- false
- 0
-
9218
-31265
71
20
-
9253.5
-31255
- 1
- 1
- {0}
- 0.5
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 59c6efa1-7240-4201-bc6c-5c31a378fbcf
- true
- Normalized
- Normalized
- false
- 0
-
9218
-31245
71
20
-
9253.5
-31235
- 1
- 1
- {0}
- true
- Point at the specified length
- f2e837e8-96af-4a0b-b80b-0dac5228b855
- true
- Point
- Point
- false
- 0
-
9313
-31285
50
20
-
9338
-31275
- Tangent vector at the specified length
- 421d155b-e6ee-493b-b76e-514be889455d
- true
- Tangent
- Tangent
- false
- 0
-
9313
-31265
50
20
-
9338
-31255
- Curve parameter at the specified length
- 86747235-7923-4162-bf80-d06ce685768a
- true
- Parameter
- Parameter
- false
- 0
-
9313
-31245
50
20
-
9338
-31235
- 4c619bc9-39fd-4717-82a6-1e07ea237bbe
- Line SDL
- Create a line segment defined by start point, tangent and length.}
- true
- 72305306-f2af-43c4-9fd0-d3e8e9bc541b
- true
- Line SDL
- Line SDL
-
9236
-33067
110
64
-
9310
-33035
- Line start point
- 921670be-6896-4871-8936-b58984df4f0a
- true
- Start
- Start
- false
- f2e837e8-96af-4a0b-b80b-0dac5228b855
- 1
-
9238
-33065
60
20
-
9276
-33055
- Line tangent (direction)
- 73b544b6-a2ee-4c7a-9bdd-d84c5868e8e7
- true
- Direction
- Direction
- false
- b236cb6d-586e-4db4-8608-bc3cfb183bfb
- 1
-
9238
-33045
60
20
-
9276
-33035
- 1
- 1
- {0}
-
0
0
1
- Line length
- 51d28f88-0bc1-4904-8e9f-c19e3e5f0f68
- ABS(X)
- true
- Length
- Length
- false
- 8e9b755e-d14d-45f3-810d-0016d1bc6909
- 1
-
9238
-33025
60
20
-
9276
-33015
- 1
- 1
- {0}
- 0.015625
- Line segment
- 0788f4f1-f5fb-4cbe-9fa5-9ccae96bc71e
- true
- Line
- Line
- false
- 0
-
9322
-33065
22
60
-
9333
-33035
- dd17d442-3776-40b3-ad5b-5e188b56bd4c
- Relative Differences
- Compute relative differences for a list of data
- true
- dd9ded7c-395b-47d9-ac3c-e415673778cb
- true
- Relative Differences
- Relative Differences
-
9233
-31630
116
28
-
9280
-31616
- 1
- List of data to operate on (numbers or points or vectors allowed)
- bbe33525-f6e6-4c7a-ac43-89d73b365178
- true
- Values
- Values
- false
- af79ac58-6083-46fb-bd71-4571d4768b45
- 1
-
9235
-31628
33
24
-
9251.5
-31616
- 1
- Differences between consecutive items
- b0b2a1b6-2a67-466d-9bdf-e8b50dccde48
- true
- Differenced
- Differenced
- false
- 0
-
9292
-31628
55
24
-
9319.5
-31616
- f3230ecb-3631-4d6f-86f2-ef4b2ed37f45
- Replace Nulls
- Replace nulls or invalid data with other data
- true
- 22fcc540-2869-4d46-b91a-7baf5b3b0523
- true
- Replace Nulls
- Replace Nulls
-
9221
-31574
139
44
-
9316
-31552
- 1
- Items to test for null
- 0d06677d-66cc-4a32-8338-5014731a3e32
- true
- Items
- Items
- false
- 43a91f6e-e3b9-4aad-adac-77d060886b47
- 1
-
9223
-31572
81
20
-
9263.5
-31562
- 1
- Items to replace nulls with
- 5531ecac-6e38-48ea-8b2d-03e1ad1d5b28
- true
- Replacements
- Replacements
- false
- 0
-
9223
-31552
81
20
-
9263.5
-31542
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_Integer
- 0
- 1
- List without any nulls
- af79ac58-6083-46fb-bd71-4571d4768b45
- true
- Items
- Items
- false
- 0
-
9328
-31572
30
20
-
9343
-31562
- Number of items replaced
- 5fb3744d-0f50-472a-b0f5-33274cdac75c
- true
- Count
- Count
- false
- 0
-
9328
-31552
30
20
-
9343
-31542
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 43a91f6e-e3b9-4aad-adac-77d060886b47
- true
- Relay
- false
- 213ef2cd-1c24-4d88-8ee3-8563f616e74b
- 1
-
9271
-31511
40
16
-
9291
-31503
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- d519f8f3-6b31-4df4-b45f-1a71a2d468c3
- true
- Relay
- false
- 628a45ae-3f38-4501-9306-b3bfe07a4a69
- 1
-
9271
-31875
40
16
-
9291
-31867
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- dd9ded7c-395b-47d9-ac3c-e415673778cb
- 22fcc540-2869-4d46-b91a-7baf5b3b0523
- 884f7be6-32bb-4a29-903a-e313a43a21a0
- 3b821991-b5a9-4b03-b173-4a07543fc3bf
- 311bc15c-dfda-4a2d-a0a3-be16e5695d2f
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- d519f8f3-6b31-4df4-b45f-1a71a2d468c3
- 27b1909a-f125-4246-82be-4d422422f56c
- 8
- f27ff281-d697-4da1-a47c-31749f573a6d
- Group
- 2dc44b22-b1dd-460a-a704-6462d6e91096
- Curve Closest Point
- Find the closest point on a curve.
- true
- 471229c7-3a45-429f-b0fa-94a45dae9b20
- true
- Curve Closest Point
- Curve Closest Point
-
9237
-31375
108
64
-
9281
-31343
- Point to project onto curve
- a22e5dc2-7aea-41cc-bc34-0af6fd6dff09
- true
- Point
- Point
- false
- f2e837e8-96af-4a0b-b80b-0dac5228b855
- 1
-
9239
-31373
30
30
-
9254
-31358
- Curve to project onto
- fe5ffe52-63f4-4054-b970-a8cd10e33174
- true
- Curve
- Curve
- false
- 8e01634f-6886-4da4-93cc-d84f2949b7f1
- 1
-
9239
-31343
30
30
-
9254
-31328
- Point on the curve closest to the base point
- 47b0dbfd-13d8-4a67-86d8-a24e8f565729
- true
- Point
- Point
- false
- 0
-
9293
-31373
50
20
-
9318
-31363
- Parameter on curve domain of closest point
- 6ac0259f-1c38-4ef5-94f5-eec70f4d8db9
- true
- Parameter
- Parameter
- false
- 0
-
9293
-31353
50
20
-
9318
-31343
- Distance between base point and curve
- c71ef2fb-fa1a-46b7-9f20-bd7f75e661ca
- true
- Distance
- Distance
- false
- 0
-
9293
-31333
50
20
-
9318
-31323
- 4c4e56eb-2f04-43f9-95a3-cc46a14f495a
- Line
- Create a line between two points.
- true
- c354b686-ceeb-4f9b-967c-89b7a10a2e8d
- true
- Line
- Line
-
9240
-31454
102
44
-
9306
-31432
- Line start point
- 6149bcaa-82a0-4690-a0bd-5813e840ea42
- true
- Start Point
- Start Point
- false
- 47b0dbfd-13d8-4a67-86d8-a24e8f565729
- 1
-
9242
-31452
52
20
-
9268
-31442
- Line end point
- 718fc483-7ccd-484f-a141-81ad5db06e46
- true
- End Point
- End Point
- false
- f2e837e8-96af-4a0b-b80b-0dac5228b855
- 1
-
9242
-31432
52
20
-
9268
-31422
- Line segment
- b236cb6d-586e-4db4-8608-bc3cfb183bfb
- true
- Line
- Line
- false
- 0
-
9318
-31452
22
40
-
9329
-31432
- 2fcc2743-8339-4cdf-a046-a1f17439191d
- Remap Numbers
- Remap numbers into a new numeric domain
- true
- 16a99370-5eb6-4fce-aeec-d7680f2fe05d
- true
- Remap Numbers
- Remap Numbers
-
9214
-32765
154
64
-
9314
-32733
- Value to remap
- a6e1fcd6-e49f-46e9-a872-7e47b8af5ea9
- true
- Value
- Value
- false
- b6b279d5-4ed9-47c5-ab20-b7eca939f3fc
- 1
-
9216
-32763
86
20
-
9259
-32753
- Source domain
- af14e9d0-e86c-496c-b6f9-9f6bc2814eef
- true
- Source
- Source
- false
- b22c79a2-0d33-46d7-9284-57f3b4abbb8f
- 1
-
9216
-32743
86
20
-
9259
-32733
- 1
- 1
- {0}
-
0
1
- Target domain
- d4fccc4e-bf36-471c-9b81-ba3f8d701373
- true
- Target
- Target
- false
- 0
-
9216
-32723
86
20
-
9259
-32713
- 1
- 1
- {0}
-
-1
1
- Remapped number
- f42a7e48-9398-409b-8a64-da1367bb2942
- true
- Mapped
- Mapped
- false
- 0
-
9326
-32763
40
30
-
9346
-32748
- Remapped and clipped number
- 689f688b-07fe-4428-9c4e-370f641273b0
- true
- Clipped
- Clipped
- false
- 0
-
9326
-32733
40
30
-
9346
-32718
- f44b92b0-3b5b-493a-86f4-fd7408c3daf3
- Bounds
- Create a numeric domain which encompasses a list of numbers.
- true
- 5fe01426-5385-4a08-b8ea-7640aed5ecfb
- true
- Bounds
- Bounds
-
9236
-32683
110
28
-
9294
-32669
- 1
- Numbers to include in Bounds
- 5554d382-be36-4514-8504-a01372c39b80
- true
- Numbers
- Numbers
- false
- b6b279d5-4ed9-47c5-ab20-b7eca939f3fc
- 1
-
9238
-32681
44
24
-
9260
-32669
- Numeric Domain between the lowest and highest numbers in {N}
- b22c79a2-0d33-46d7-9284-57f3b4abbb8f
- true
- Domain
- Domain
- false
- 0
-
9306
-32681
38
24
-
9325
-32669
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- b6b279d5-4ed9-47c5-ab20-b7eca939f3fc
- true
- Relay
-
- false
- d519f8f3-6b31-4df4-b45f-1a71a2d468c3
- 1
-
9271
-32636
40
16
-
9291
-32628
- ce46b74e-00c9-43c4-805a-193b69ea4a11
- Multiplication
- Mathematical multiplication
- true
- c97695d5-8e09-472d-bde7-20c54a6299fe
- true
- Multiplication
- Multiplication
-
9256
-32964
70
44
-
9281
-32942
- 2
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- First item for multiplication
- 4bcc7d6b-5c4e-4433-b135-a07aa4aa0a5b
- true
- A
- A
- true
- 3946cb2b-8c1a-4e2c-a3b8-0a68992f993b
- 1
-
9258
-32962
11
20
-
9263.5
-32952
- Second item for multiplication
- d30a8b1c-7836-41e1-98be-ea095a5c6c05
- true
- B
- B
- true
- cd09c2ab-8662-4079-bdab-9e16238ac1e2
- 1
-
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9297
-25053
- 1
- List to shift
- 5499e5b9-8cb2-49eb-9c30-f42c02160bb0
- true
- List
-
- false
- 53cd2fb9-04f7-425c-aaa0-2f8eff8d768a
- 1
-
9266
-25083
19
20
-
9275.5
-25073
- Shift offset
- 1729daa5-e944-4ea1-b8b3-d12f2997dc4e
- true
- Shift
-
- false
- 0
-
9266
-25063
19
20
-
9275.5
-25053
- 1
- 1
- {0}
- 1
- Wrap values
- 8d1dfbee-0649-4ac4-af78-b408219fcce4
- true
- Wrap
-
- false
- 0
-
9266
-25043
19
20
-
9275.5
-25033
- 1
- 1
- {0}
- false
- 1
- Shifted list
- ab4f4689-c6b1-486b-8d63-2934c6b34e6f
- true
- List
-
- false
- 0
-
9309
-25083
6
60
-
9312
-25053
- 4fdfe351-6c07-47ce-9fb9-be027fb62186
- Shift List
- Offset all items in a list.
- true
- ff2559cf-18b3-4cad-b391-315893967bf2
- true
- Shift List
-
-
9264
-28449
53
64
-
9297
-28417
- 1
- List to shift
- 273f5044-a2c4-4e53-b232-745a3aba44a6
- true
- List
-
- false
- 2d37b54a-d252-4d91-af08-37f5c09e7e4a
- 1
-
9266
-28447
19
20
-
9275.5
-28437
- Shift offset
- 5b25285d-2173-464a-b270-22bf8a418ba0
- true
- Shift
-
- false
- 0
-
9266
-28427
19
20
-
9275.5
-28417
- 1
- 1
- {0}
- 1
- Wrap values
- 4a0100fa-492c-44ed-8efd-286b52e4296b
- true
- Wrap
-
- false
- 0
-
9266
-28407
19
20
-
9275.5
-28397
- 1
- 1
- {0}
- false
- 1
- Shifted list
- d57b5cda-0b57-4731-b527-b630d209be02
- true
- List
-
- false
- 0
-
9309
-28447
6
60
-
9312
-28417
- 4fdfe351-6c07-47ce-9fb9-be027fb62186
- Shift List
- Offset all items in a list.
- true
- 27b1909a-f125-4246-82be-4d422422f56c
- true
- Shift List
-
-
9264
-31775
53
64
-
9297
-31743
- 1
- List to shift
- bfcc7bea-5c84-4cb4-9ff7-0de9927cd430
- true
- List
-
- false
- b0b2a1b6-2a67-466d-9bdf-e8b50dccde48
- 1
-
9266
-31773
19
20
-
9275.5
-31763
- Shift offset
- 4f2a1b86-0f17-49bd-9fca-cbdc3d33ec14
- true
- Shift
-
- false
- 0
-
9266
-31753
19
20
-
9275.5
-31743
- 1
- 1
- {0}
- 1
- Wrap values
- b943df66-5f34-449f-a95b-f9c2d9811644
- true
- Wrap
-
- false
- 0
-
9266
-31733
19
20
-
9275.5
-31723
- 1
- 1
- {0}
- false
- 1
- Shifted list
- 628a45ae-3f38-4501-9306-b3bfe07a4a69
- true
- List
-
- false
- 0
-
9309
-31773
6
60
-
9312
-31743
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- 55fcfa84-e04c-40ca-ae46-cc937e27bc97
- 3472779d-20db-40dc-8dba-0814a38b261e
- 9b318109-1854-4397-bf67-7f973c203aaa
- 8d65e4f1-504b-4486-8089-12d4064e8ba6
- e027a95f-405b-4d15-be30-520d91dbc5fc
- 884f7be6-32bb-4a29-903a-e313a43a21a0
- 3b821991-b5a9-4b03-b173-4a07543fc3bf
- 311bc15c-dfda-4a2d-a0a3-be16e5695d2f
- 857bb5ff-1ad6-4170-8b10-ee3ac17d9761
- a2874c09-6237-43a6-9770-654bb457fea2
- eef9bfc4-b532-42a0-bd17-b8664766f22d
- dc8cf255-b505-46bc-b318-2ae7c8c46b35
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- 0343763a-82b3-483e-8d95-68ddd2c05938
- 8951eabd-7737-4a9d-88fc-d15ea0349bc1
- 7248ed6f-8fe9-480c-a442-80bf5073e3d3
- 7bc36f90-e59b-4ccb-9ddb-02043549301b
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- 87a2227f-c42b-4756-b84e-5cb0c48ee4fa
- a9701972-e21e-4da9-9c28-b38c5fd5ee91
- c192e380-8d44-4588-9699-871bb46e733f
- 8fe511eb-1233-498f-a8f7-d34dd4f617ff
- ec2ad91e-428d-4859-a2f4-c060e48f0123
- 6cec9000-baec-41ef-973b-b71a94f021fc
- c6ae0cff-05a7-4886-8aec-979f2907fe15
- e255ea20-b4ac-48b1-9e1b-0980e7594d5c
- 4a75522d-3e59-45b0-a235-b3d518b6df35
- cd5303fe-9c39-4150-8623-a6ac735d2876
- 0ef4bcf5-e770-4833-ad57-d7559ac0cfa8
- e328ed3a-fdf2-475b-930e-eac036796207
- 31d327cb-78e9-4772-9b77-ece7f5772c9a
- 4b4766df-9c4a-478a-a5ec-86bcf578667e
- ddda8bc0-631e-4735-96ff-a584cfbe1986
- 33
- 69a821a3-8a73-4cec-baac-b9a13a42017b
- Group
- afb96615-c59a-45c9-9cac-e27acb1c7ca0
- Explode
- Explode a curve into smaller segments.
- true
- 55fcfa84-e04c-40ca-ae46-cc937e27bc97
- true
- Explode
- Explode
-
9224
-34107
134
44
-
9295
-34085
- Curve to explode
- 7da04cc2-bf5d-4d0e-bcab-169bff54c587
- true
- Curve
- Curve
- false
- 88c9d358-2164-494c-93cd-620bfe195f0b
- 1
-
9226
-34105
57
20
-
9254.5
-34095
- Recursive decomposition until all segments are atomic
- 4bf6b70a-6c34-468c-aa86-94afd01fb357
- true
- Recursive
- Recursive
- false
- 0
-
9226
-34085
57
20
-
9254.5
-34075
- 1
- 1
- {0}
- true
- 1
- Exploded segments that make up the base curve
- 6c4a04a3-a43f-457d-983f-5cf6e15c55b3
- true
- Segments
- Segments
- false
- 0
-
9307
-34105
49
20
-
9331.5
-34095
- 1
- Vertices of the exploded segments
- 4cbdd9d2-e4c9-48ca-a29a-60721e988124
- true
- Vertices
- Vertices
- false
- 0
-
9307
-34085
49
20
-
9331.5
-34075
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 3472779d-20db-40dc-8dba-0814a38b261e
- true
- Evaluate Length
- Evaluate Length
-
9216
-34190
149
64
-
9301
-34158
- Curve to evaluate
- 61ed4f99-0318-4550-9b89-e471060e49cd
- true
- Curve
- Curve
- false
- 6c4a04a3-a43f-457d-983f-5cf6e15c55b3
- 1
-
9218
-34188
71
20
-
9253.5
-34178
- Length factor for curve evaluation
- 9f2f27a2-8d4e-4115-b063-8157dc5bc3c7
- true
- Length
- Length
- false
- 0
-
9218
-34168
71
20
-
9253.5
-34158
- 1
- 1
- {0}
- 0.5
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 5a640dfc-16bc-4d45-9299-3990b3d869ea
- true
- Normalized
- Normalized
- false
- 0
-
9218
-34148
71
20
-
9253.5
-34138
- 1
- 1
- {0}
- true
- Point at the specified length
- 83d865c2-6775-4675-9f8a-220e22ddae31
- true
- Point
- Point
- false
- 0
-
9313
-34188
50
20
-
9338
-34178
- Tangent vector at the specified length
- 93b233c7-cc87-47af-a8da-a31536701d3a
- true
- Tangent
- Tangent
- false
- 0
-
9313
-34168
50
20
-
9338
-34158
- Curve parameter at the specified length
- c83c9c3e-20cb-4973-90a0-33613bc0b9bf
- true
- Parameter
- Parameter
- false
- 0
-
9313
-34148
50
20
-
9338
-34138
- 4c619bc9-39fd-4717-82a6-1e07ea237bbe
- Line SDL
- Create a line segment defined by start point, tangent and length.}
- true
- 9b318109-1854-4397-bf67-7f973c203aaa
- true
- Line SDL
- Line SDL
-
9236
-35970
110
64
-
9310
-35938
- Line start point
- 7517af86-db7e-4c90-b088-ebb63aeb9947
- true
- Start
- Start
- false
- 83d865c2-6775-4675-9f8a-220e22ddae31
- 1
-
9238
-35968
60
20
-
9276
-35958
- Line tangent (direction)
- 2a40b560-e61e-43ee-857d-4d109c9e2564
- true
- Direction
- Direction
- false
- d3dbebd8-864a-42c4-a1e6-9bde8c219738
- 1
-
9238
-35948
60
20
-
9276
-35938
- 1
- 1
- {0}
-
0
0
1
- Line length
- 9a51e0da-5a90-4c2f-a539-6f1169e6adcf
- ABS(X)
- true
- Length
- Length
- false
- 7feacf97-94fa-4c5e-b845-893325d06a8a
- 1
-
9238
-35928
60
20
-
9276
-35918
- 1
- 1
- {0}
- 0.015625
- Line segment
- 6760dc6d-999e-4284-b361-b5cb2b5a6f55
- true
- Line
- Line
- false
- 0
-
9322
-35968
22
60
-
9333
-35938
- dd17d442-3776-40b3-ad5b-5e188b56bd4c
- Relative Differences
- Compute relative differences for a list of data
- true
- 8d65e4f1-504b-4486-8089-12d4064e8ba6
- true
- Relative Differences
- Relative Differences
-
9233
-34533
116
28
-
9280
-34519
- 1
- List of data to operate on (numbers or points or vectors allowed)
- 8bdef77b-f99e-4151-baaa-1479ad4fb2a0
- true
- Values
- Values
- false
- cfb237b9-cda4-451f-88cf-681e8c1a12e1
- 1
-
9235
-34531
33
24
-
9251.5
-34519
- 1
- Differences between consecutive items
- 8945d4e1-f472-463e-8ed0-f9b54de13e94
- true
- Differenced
- Differenced
- false
- 0
-
9292
-34531
55
24
-
9319.5
-34519
- f3230ecb-3631-4d6f-86f2-ef4b2ed37f45
- Replace Nulls
- Replace nulls or invalid data with other data
- true
- e027a95f-405b-4d15-be30-520d91dbc5fc
- true
- Replace Nulls
- Replace Nulls
-
9221
-34477
139
44
-
9316
-34455
- 1
- Items to test for null
- 50e47417-d5fa-4fd6-80cb-1cd3825f090d
- true
- Items
- Items
- false
- 857bb5ff-1ad6-4170-8b10-ee3ac17d9761
- 1
-
9223
-34475
81
20
-
9263.5
-34465
- 1
- Items to replace nulls with
- 49bb910e-eb21-4eb7-a7f1-549dcb632f72
- true
- Replacements
- Replacements
- false
- 0
-
9223
-34455
81
20
-
9263.5
-34445
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_Integer
- 0
- 1
- List without any nulls
- cfb237b9-cda4-451f-88cf-681e8c1a12e1
- true
- Items
- Items
- false
- 0
-
9328
-34475
30
20
-
9343
-34465
- Number of items replaced
- a42bf3d3-1e96-403d-b483-d487b33f5cb5
- true
- Count
- Count
- false
- 0
-
9328
-34455
30
20
-
9343
-34445
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 857bb5ff-1ad6-4170-8b10-ee3ac17d9761
- true
- Relay
- false
- d519f8f3-6b31-4df4-b45f-1a71a2d468c3
- 1
-
9271
-34414
40
16
-
9291
-34406
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- a2874c09-6237-43a6-9770-654bb457fea2
- true
- Relay
- false
- f50a8f1c-4788-43be-b2e2-986396a4b91f
- 1
-
9271
-34778
40
16
-
9291
-34770
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- 8d65e4f1-504b-4486-8089-12d4064e8ba6
- e027a95f-405b-4d15-be30-520d91dbc5fc
- 884f7be6-32bb-4a29-903a-e313a43a21a0
- 3b821991-b5a9-4b03-b173-4a07543fc3bf
- 311bc15c-dfda-4a2d-a0a3-be16e5695d2f
- 857bb5ff-1ad6-4170-8b10-ee3ac17d9761
- a2874c09-6237-43a6-9770-654bb457fea2
- cce0cf82-c2e4-4967-b2d7-8d1450f4e4ff
- 8
- eef9bfc4-b532-42a0-bd17-b8664766f22d
- Group
- 2dc44b22-b1dd-460a-a704-6462d6e91096
- Curve Closest Point
- Find the closest point on a curve.
- true
- dc8cf255-b505-46bc-b318-2ae7c8c46b35
- true
- Curve Closest Point
- Curve Closest Point
-
9237
-34278
108
64
-
9281
-34246
- Point to project onto curve
- 9f2045f7-84db-41a3-80a7-b78554fc6dc3
- true
- Point
- Point
- false
- 83d865c2-6775-4675-9f8a-220e22ddae31
- 1
-
9239
-34276
30
30
-
9254
-34261
- Curve to project onto
- 53c74feb-bd8c-4934-b455-c4061c58e591
- true
- Curve
- Curve
- false
- 8e01634f-6886-4da4-93cc-d84f2949b7f1
- 1
-
9239
-34246
30
30
-
9254
-34231
- Point on the curve closest to the base point
- 3800975a-d9c1-4d01-8d3c-5fe396f11ea9
- true
- Point
- Point
- false
- 0
-
9293
-34276
50
20
-
9318
-34266
- Parameter on curve domain of closest point
- 802dfdfc-00c0-4e0d-88cd-b70ffb31a626
- true
- Parameter
- Parameter
- false
- 0
-
9293
-34256
50
20
-
9318
-34246
- Distance between base point and curve
- 3a8aa4d2-6fcc-4120-8b54-3111253d7cb2
- true
- Distance
- Distance
- false
- 0
-
9293
-34236
50
20
-
9318
-34226
- 4c4e56eb-2f04-43f9-95a3-cc46a14f495a
- Line
- Create a line between two points.
- true
- 76231faf-dae2-4926-9f6b-2c8077bcac89
- true
- Line
- Line
-
9240
-34357
102
44
-
9306
-34335
- Line start point
- 2b14c6a3-4ad6-47d8-87b3-1587dd6eecf0
- true
- Start Point
- Start Point
- false
- 3800975a-d9c1-4d01-8d3c-5fe396f11ea9
- 1
-
9242
-34355
52
20
-
9268
-34345
- Line end point
- 1672f208-89e5-473d-a789-52bcc3c501c6
- true
- End Point
- End Point
- false
- 83d865c2-6775-4675-9f8a-220e22ddae31
- 1
-
9242
-34335
52
20
-
9268
-34325
- Line segment
- d3dbebd8-864a-42c4-a1e6-9bde8c219738
- true
- Line
- Line
- false
- 0
-
9318
-34355
22
40
-
9329
-34335
- 2fcc2743-8339-4cdf-a046-a1f17439191d
- Remap Numbers
- Remap numbers into a new numeric domain
- true
- 0343763a-82b3-483e-8d95-68ddd2c05938
- true
- Remap Numbers
- Remap Numbers
-
9214
-35668
154
64
-
9314
-35636
- Value to remap
- fbb75435-dbda-4a99-b5de-a7f860bb107d
- true
- Value
- Value
- false
- 7248ed6f-8fe9-480c-a442-80bf5073e3d3
- 1
-
9216
-35666
86
20
-
9259
-35656
- Source domain
- bda3bd9e-69c4-4252-8fbd-8445a285ec60
- true
- Source
- Source
- false
- 4cc59e7a-388e-4875-939d-e051a56dbf0a
- 1
-
9216
-35646
86
20
-
9259
-35636
- 1
- 1
- {0}
-
0
1
- Target domain
- 6ed6b452-6999-4bc0-9d9b-1edae4d23e5e
- true
- Target
- Target
- false
- 0
-
9216
-35626
86
20
-
9259
-35616
- 1
- 1
- {0}
-
-1
1
- Remapped number
- 0eaed2fe-a667-4ec0-bd86-4b5c20e158fe
- true
- Mapped
- Mapped
- false
- 0
-
9326
-35666
40
30
-
9346
-35651
- Remapped and clipped number
- 43ee08e0-34ae-4987-87d2-49bd6063b895
- true
- Clipped
- Clipped
- false
- 0
-
9326
-35636
40
30
-
9346
-35621
- f44b92b0-3b5b-493a-86f4-fd7408c3daf3
- Bounds
- Create a numeric domain which encompasses a list of numbers.
- true
- 8951eabd-7737-4a9d-88fc-d15ea0349bc1
- true
- Bounds
- Bounds
-
9236
-35586
110
28
-
9294
-35572
- 1
- Numbers to include in Bounds
- b2d1db6e-815f-4c6e-adc4-7c0cdab96b4d
- true
- Numbers
- Numbers
- false
- 7248ed6f-8fe9-480c-a442-80bf5073e3d3
- 1
-
9238
-35584
44
24
-
9260
-35572
- Numeric Domain between the lowest and highest numbers in {N}
- 4cc59e7a-388e-4875-939d-e051a56dbf0a
- true
- Domain
- Domain
- false
- 0
-
9306
-35584
38
24
-
9325
-35572
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 7248ed6f-8fe9-480c-a442-80bf5073e3d3
- true
- Relay
-
- false
- a2874c09-6237-43a6-9770-654bb457fea2
- 1
-
9271
-35539
40
16
-
9291
-35531
- ce46b74e-00c9-43c4-805a-193b69ea4a11
- Multiplication
- Mathematical multiplication
- true
- 7bc36f90-e59b-4ccb-9ddb-02043549301b
- true
- Multiplication
- Multiplication
-
9256
-35867
70
44
-
9281
-35845
- 2
- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- Group
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- Explode
- Explode a curve into smaller segments.
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- Explode
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134
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- Curve to explode
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57
20
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- Recursive decomposition until all segments are atomic
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57
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- Exploded segments that make up the base curve
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49
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- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
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- Evaluate Length
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149
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- Curve to evaluate
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- Length factor for curve evaluation
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71
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- If True, the Length factor is normalized (0.0 ~ 1.0)
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- Point at the specified length
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50
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- Tangent vector at the specified length
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- Curve parameter at the specified length
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- Line SDL
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- Line start point
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- Line tangent (direction)
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60
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0
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60
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- Line segment
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22
60
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- Compute relative differences for a list of data
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116
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- List of data to operate on (numbers or points or vectors allowed)
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- Items to replace nulls with
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81
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9263.5
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- Grasshopper.Kernel.Types.GH_Integer
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- List without any nulls
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30
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- Number of items replaced
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30
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255;255;255;255
- A group of Grasshopper objects
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- Group
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- Curve Closest Point
- Find the closest point on a curve.
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- Point to project onto curve
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- Curve to project onto
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30
30
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- Point on the curve closest to the base point
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- Parameter on curve domain of closest point
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- Distance between base point and curve
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50
20
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- Line
- Create a line between two points.
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- Line
- Line
-
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102
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- Line start point
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52
20
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- Line end point
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52
20
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- Line segment
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9318
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22
40
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- Remap Numbers
- Remap numbers into a new numeric domain
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- Remap Numbers
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154
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9314
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- Value to remap
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86
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- Source domain
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9216
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86
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0
1
- Target domain
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9216
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86
20
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-1
1
- Remapped number
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40
30
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- Remapped and clipped number
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9326
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40
30
-
9346
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- Bounds
- Create a numeric domain which encompasses a list of numbers.
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- Bounds
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110
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- Numbers to include in Bounds
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44
24
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- Numeric Domain between the lowest and highest numbers in {N}
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- Domain
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-
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38
24
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9325
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- Relay
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- A wire relay object
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40
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- ce46b74e-00c9-43c4-805a-193b69ea4a11
- Multiplication
- Mathematical multiplication
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70
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- 2
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- First item for multiplication
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11
20
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- Second item for multiplication
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11
20
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- Result of multiplication
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- Multiplication
- Mathematical multiplication
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70
44
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- 2
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- First item for multiplication
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11
20
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- Second item for multiplication
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11
20
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- Result of multiplication
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31
40
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- A wire relay object
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40
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255;255;255;255
- A group of Grasshopper objects
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255;255;255;255
- A group of Grasshopper objects
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185
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22
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81
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40
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38
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40
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70
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11
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-
255;221;160;221
-
255;66;48;66
- 0.5
-
255;255;255;255
- 0
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 13d1fa05-10a0-4e49-9f5c-d4be788f3bf7
- true
- Evaluate Length
- Evaluate Length
-
9216
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149
64
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9301
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- Curve to evaluate
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- Curve
- Curve
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- 1
-
9218
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71
20
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9253.5
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- Length factor for curve evaluation
- 3d38be95-53d7-42c7-bf78-b328a61d1004
- true
- Length
- Length
- false
- 0
-
9218
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71
20
-
9253.5
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- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 6083f354-e506-4938-8073-5ae19c9a0bcb
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- Normalized
- Normalized
- false
- 0
-
9218
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71
20
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9253.5
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- 1
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- Point at the specified length
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- true
- Point
- Point
- false
- 0
-
9313
-41758
50
20
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9338
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- Tangent vector at the specified length
- ac75852c-1840-42f1-a45c-a1340843b1f6
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- Tangent
- Tangent
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- 0
-
9313
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50
20
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9338
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- Curve parameter at the specified length
- 69a8f266-7c26-4dd5-ae0a-ce7f3038267c
- true
- Parameter
- Parameter
- false
- 0
-
9313
-41718
50
20
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9338
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- 2b2a4145-3dff-41d4-a8de-1ea9d29eef33
- Interpolate
- Create an interpolated curve through a set of points.
- true
- 1f826159-9b93-496e-a901-3569ec3f0529
- true
- Interpolate
- Interpolate
-
9178
-41865
225
84
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9351
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- 1
- Interpolation points
- 845c8ca5-93f1-4359-9c95-2955e582f673
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- Vertices
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- a7f000f7-077a-429b-9fd2-3461a60688ce
- 1
-
9180
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159
20
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9259.5
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- Curve degree
- af999c4e-9762-4d4d-84b3-529b4cdf1786
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- Degree
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- 0
-
9180
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159
20
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9259.5
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- Periodic curve
- 82797a82-ed5b-4939-a849-81dc5005e2f1
- true
- Periodic
- Periodic
- false
- 0
-
9180
-41823
159
20
-
9259.5
-41813
- 1
- 1
- {0}
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- Knot spacing (0=uniform, 1=chord, 2=sqrtchord)
- 0002170b-0e61-4a14-921d-19fcde0ed3c1
- true
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- KnotStyle
- false
- 0
-
9180
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159
20
-
9259.5
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- 1
- {0}
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- Resulting nurbs curve
- 49ba7b32-079b-49b9-b959-c2d6bfd13254
- true
- Curve
- Curve
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- 0
-
9363
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38
26
-
9382
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- Curve length
- 8d874e72-0d60-47cc-a1c0-ecc588d0d3fc
- true
- Length
- Length
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-
9363
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38
27
-
9382
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- Curve domain
- 2a775b02-d107-44ba-858c-2046ed1c6795
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- Domain
- Domain
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-
9363
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38
27
-
9382
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- 76975309-75a6-446a-afed-f8653720a9f2
- Create Material
- Create an OpenGL material.
- true
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- true
- Create Material
- Create Material
-
9215
-41992
152
104
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9313
-41940
- Colour of the diffuse channel
- 558b211b-9805-46c1-ba2c-9ec0d4ddc247
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- Diffuse
- false
- 0
-
9217
-41990
84
20
-
9259
-41980
- 1
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255;138;138;138
- Colour of the specular highlight
- 242fc3cc-4394-4ece-9bc2-200e01d9d80d
- true
- Specular
- Specular
- false
- 0
-
9217
-41970
84
20
-
9259
-41960
- 1
- 1
- {0}
-
255;0;255;255
- Emissive colour of the material
- 1e6c6da7-cc89-4938-998e-31b29107fa58
- true
- Emission
- Emission
- false
- 0
-
9217
-41950
84
20
-
9259
-41940
- 1
- 1
- {0}
-
255;0;0;0
- Amount of transparency (0.0 = opaque, 1.0 = transparent
- a1000b0b-f2eb-48b6-87d4-ce732f817a64
- true
- Transparency
- Transparency
- false
- 0
-
9217
-41930
84
20
-
9259
-41920
- 1
- 1
- {0}
- 0.5
- Amount of shinyness (0 = none, 1 = low shine, 100 = max shine
- b98344ef-66c6-43b0-9504-cbb0bafb4a02
- true
- Shine
- Shine
- false
- 0
-
9217
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84
20
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9259
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- 1
- 1
- {0}
- 100
- Resulting material
- 556a7f51-dac7-4aa7-92e2-bf4ef5bb5c94
- true
- Material
- Material
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- 0
-
9325
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40
100
-
9345
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- 537b0419-bbc2-4ff4-bf08-afe526367b2c
- Custom Preview
- Allows for customized geometry previews
- true
- true
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- true
- Custom Preview
- Custom Preview
-
9253
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76
44
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9315
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- Geometry to preview
- true
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- true
- Geometry
- Geometry
- false
- 49ba7b32-079b-49b9-b959-c2d6bfd13254
- 1
-
9255
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48
20
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9279
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- The material override
- 27318ca8-9375-4bb8-945e-1d98fced9ce8
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- Material
- Material
- false
- 556a7f51-dac7-4aa7-92e2-bf4ef5bb5c94
- 1
-
9255
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48
20
-
9279
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- 1
- 1
- {0}
-
255;221;160;221
-
255;66;48;66
- 0.5
-
255;255;255;255
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- Quick Graph
- 1
- Display a set of y-values as a graph
- 79de9cf0-fcdc-4bba-bc24-572fecdc1cd8
- true
- Quick Graph
- Quick Graph
- false
- 0
- f5764a3d-7ce6-4d28-831b-482fcc350345
- 1
-
9223
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150
150
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9223.633
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- 448de216-3a12-43cf-a135-e3bfafc87744
- B
- Second item for multiplication
- e1a9abe3-f7cd-446d-828c-eb66e5fcbf81
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- B
- B
- false
- 0
-
9261
-41306
60
24
- a4b285fe-2e13-4204-b65c-189aa6704da5
- Relay
- A wire relay object
- 710b7f25-69d0-40c4-8e80-8af6e2e0161c
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-
- false
- f5764a3d-7ce6-4d28-831b-482fcc350345
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-
9261
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60
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- Format
- Format some data using placeholders and formatting tags
- true
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- true
- Format
- Format
-
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130
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- 3ede854e-c753-40eb-84cb-b48008f14fd4
- Text format
- ed06f458-55d6-4614-838f-8cda3f23c651
- true
- Format
- Format
- false
- 0
-
9228
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78
20
-
9267
-40455
- 1
- 1
- {0}
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- {0:R}
- Formatting culture
- bb43e128-d580-4b54-ac41-7398752044d5
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- Culture
- Culture
- false
- 0
-
9228
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78
20
-
9267
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- 1
- 1
- {0}
- 127
- Data to insert at {0} placeholders
- 519b6b8e-3606-4e7a-a870-bafdb95e3276
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- Data 0
- 0
- true
- f5764a3d-7ce6-4d28-831b-482fcc350345
- 1
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9228
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78
20
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9267
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- Formatted text
- 8c3b5a7e-88ac-4a85-aff3-496ee1f2fd94
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- Text
- Text
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- 0
-
9330
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24
60
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9342
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- 4fdfe351-6c07-47ce-9fb9-be027fb62186
- Shift List
- Offset all items in a list.
- true
- 344dc1b1-9c93-405e-b50c-435fc88b1393
- true
- Shift List
-
-
9264
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53
64
-
9297
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- 1
- List to shift
- 38028c4f-01b1-448b-971a-aeac3bdce801
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- List
-
- false
- f1a4fd75-be6b-426f-94b9-028e696a8d4e
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-
9266
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19
20
-
9275.5
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- Shift offset
- fa831690-2c1c-4038-9c05-76b4f05ad5f2
- true
- Shift
-
- false
- 0
-
9266
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19
20
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9275.5
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- 1
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- 1
- Wrap values
- 8eb8ab7b-f0bb-4609-b9db-45bf19bb7513
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- Wrap
-
- false
- 0
-
9266
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19
20
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9275.5
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- 1
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- 1
- Shifted list
- b16fb91f-43f8-48d3-85b5-411ce00f8e92
- true
- List
-
- false
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-
9309
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6
60
-
9312
-40151
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- f12dfdaf-a911-4905-b859-d8a9f4e0eedb
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- Group
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- Explode
- Explode a curve into smaller segments.
- true
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- true
- Explode
- Explode
-
9224
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134
44
-
9295
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- Curve to explode
- 21819ae5-0104-4cd0-b1a2-20a8c9437dac
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- Curve
- false
- 49ba7b32-079b-49b9-b959-c2d6bfd13254
- 1
-
9226
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57
20
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9254.5
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- Recursive decomposition until all segments are atomic
- 9b758182-5867-4d95-a7c9-7ce9ece6d472
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- Recursive
- Recursive
- false
- 0
-
9226
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57
20
-
9254.5
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- 1
- 1
- {0}
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- 1
- Exploded segments that make up the base curve
- 96fd8efe-b267-4f01-ae1d-95fa6f36f03d
- true
- Segments
- Segments
- false
- 0
-
9307
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49
20
-
9331.5
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- 1
- Vertices of the exploded segments
- 89f21f30-c523-446e-a993-0473c39c98b4
- true
- Vertices
- Vertices
- false
- 0
-
9307
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49
20
-
9331.5
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- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- ddec3c63-c1ce-4b98-bd8d-23dd34771bc1
- true
- Evaluate Length
- Evaluate Length
-
9216
-42494
149
64
-
9301
-42462
- Curve to evaluate
- e65aea05-b30b-4426-a83f-27f48a8fc4c9
- true
- Curve
- Curve
- false
- 96fd8efe-b267-4f01-ae1d-95fa6f36f03d
- 1
-
9218
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71
20
-
9253.5
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- Length factor for curve evaluation
- f4853285-4b14-4799-9792-998cce733eb1
- true
- Length
- Length
- false
- 0
-
9218
-42472
71
20
-
9253.5
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- 1
- 1
- {0}
- 0.5
- If True, the Length factor is normalized (0.0 ~ 1.0)
- ae68e25f-27c2-404d-9cea-27e2b3859708
- true
- Normalized
- Normalized
- false
- 0
-
9218
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71
20
-
9253.5
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- 1
- 1
- {0}
- true
- Point at the specified length
- eeb3326c-8c7d-4ee2-b604-1674c4e8b8a8
- true
- Point
- Point
- false
- 0
-
9313
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50
20
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9338
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- Tangent vector at the specified length
- b7be6e78-611a-4818-9515-b244d669269f
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- Tangent
- false
- 0
-
9313
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50
20
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9338
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- Curve parameter at the specified length
- 6349ae4e-3f8f-42c5-8fa4-eca0d9b289bb
- true
- Parameter
- Parameter
- false
- 0
-
9313
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50
20
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9338
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- Line SDL
- Create a line segment defined by start point, tangent and length.}
- true
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- true
- Line SDL
- Line SDL
-
9236
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110
64
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9310
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- Line start point
- 4c1ef802-cc97-4f47-a2fc-8bf547ad8b77
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9238
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60
20
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9276
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- Line tangent (direction)
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- 1
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9238
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60
20
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9276
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0
0
1
- Line length
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- ABS(X)
- true
- Length
- Length
- false
- 24b005f9-d046-4d64-bb62-797fb722cb35
- 1
-
9238
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60
20
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9276
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- 1
- 1
- {0}
- 0.015625
- Line segment
- c7e0c241-90cc-496e-a87d-4b724bc0890a
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- Line
- Line
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- 0
-
9322
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22
60
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9333
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- dd17d442-3776-40b3-ad5b-5e188b56bd4c
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- Compute relative differences for a list of data
- true
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- true
- Relative Differences
- Relative Differences
-
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116
28
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9280
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- List of data to operate on (numbers or points or vectors allowed)
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9235
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33
24
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9251.5
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- 1
- Differences between consecutive items
- 7d62d328-5af4-4783-a10c-8dd6cb2e9a4a
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- 0
-
9292
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55
24
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9319.5
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- Replace Nulls
- Replace nulls or invalid data with other data
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- true
- Replace Nulls
- Replace Nulls
-
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139
44
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9316
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- Items to test for null
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- 1
-
9223
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81
20
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9263.5
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- Items to replace nulls with
- b3c8a56f-0cd4-4c51-a87c-5b8dd989b025
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- 0
-
9223
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81
20
-
9263.5
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- 1
- 1
- {0}
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- 0
- 1
- List without any nulls
- 6ef3022d-c15d-4be5-a48d-24d97fc6c710
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- Items
- Items
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- 0
-
9328
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30
20
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9343
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- Number of items replaced
- 507078d7-5473-44f8-867b-cde6bf18fdb1
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- Count
- Count
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- 0
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9328
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- A group of Grasshopper objects
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52
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9216
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- Numbers to include in Bounds
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38
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- A wire relay object
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- Mathematical multiplication
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31
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255;255;255;255
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- Group
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- A group of Grasshopper objects
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- Emissive colour of the material
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255;255;255;255
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- Length factor for curve evaluation
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- Point at the specified length
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255;130;130;130
- Colour of the specular highlight
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9217
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84
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9259
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255;0;255;255
- Emissive colour of the material
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- Emission
- Emission
- false
- 0
-
9217
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84
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9259
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255;0;0;0
- Amount of transparency (0.0 = opaque, 1.0 = transparent
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- Transparency
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9217
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84
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9259
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- 1
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- Amount of shinyness (0 = none, 1 = low shine, 100 = max shine
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84
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- Resulting material
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9325
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40
100
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- 537b0419-bbc2-4ff4-bf08-afe526367b2c
- Custom Preview
- Allows for customized geometry previews
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- Custom Preview
- Custom Preview
-
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76
44
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9315
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- Geometry to preview
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- Geometry
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- 2ade3e09-9450-4cf7-9dab-808a7e057067
- 1
-
9255
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48
20
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9279
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- The material override
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- Material
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- 4fe71d5e-bfd7-441d-8b41-fe4cb1b2c049
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9255
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48
20
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9279
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255;221;160;221
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255;66;48;66
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255;255;255;255
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- Quick Graph
- 1
- Display a set of y-values as a graph
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150
150
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9223.633
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- 448de216-3a12-43cf-a135-e3bfafc87744
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- Second item for multiplication
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-
9261
-44105
60
24
- a4b285fe-2e13-4204-b65c-189aa6704da5
- Relay
- A wire relay object
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-
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9261
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60
24
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- Format
- Format some data using placeholders and formatting tags
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- Format
- Format
-
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130
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- Text format
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9228
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78
20
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9267
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- Formatting culture
- fdb39509-da56-4023-9d44-518751fa1aae
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- Culture
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-
9228
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78
20
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9267
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- Data to insert at {0} placeholders
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9228
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78
20
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- Formatted text
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9330
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24
60
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9342
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- Offset all items in a list.
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- Shift List
-
-
9264
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53
64
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9297
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- List to shift
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- List
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19
20
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9275.5
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- Shift offset
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-
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9266
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19
20
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- 12352323-c591-443d-bed8-08d75aae23ac
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-
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9266
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19
20
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-
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9309
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6
60
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9312
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- Group
- 1
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255;255;255;255
- A group of Grasshopper objects
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- Group
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- Explode
- Explode a curve into smaller segments.
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- true
- Explode
- Explode
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134
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9295
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- Curve to explode
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-
9226
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57
20
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9254.5
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- Recursive decomposition until all segments are atomic
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9226
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57
20
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9254.5
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- 1
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- 1
- Exploded segments that make up the base curve
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49
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- Vertices of the exploded segments
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9307
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49
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9331.5
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- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
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- true
- Evaluate Length
- Evaluate Length
-
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149
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9301
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- Curve to evaluate
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9218
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71
20
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9253.5
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- Length factor for curve evaluation
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- Length
- Length
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- 0
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9218
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71
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9253.5
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- If True, the Length factor is normalized (0.0 ~ 1.0)
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- Normalized
- Normalized
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9218
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71
20
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9253.5
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- Point at the specified length
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9313
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50
20
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9338
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- Tangent vector at the specified length
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9313
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50
20
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9338
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- Curve parameter at the specified length
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9313
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50
20
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9338
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- Line SDL
- Create a line segment defined by start point, tangent and length.}
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- true
- Line SDL
- Line SDL
-
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110
64
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9310
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- Line start point
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9238
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60
20
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9276
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- Line tangent (direction)
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9238
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60
20
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9276
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0
0
1
- Line length
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- true
- Length
- Length
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- 1
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9238
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60
20
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9276
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- Line segment
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- 0
-
9322
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22
60
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9333
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- dd17d442-3776-40b3-ad5b-5e188b56bd4c
- Relative Differences
- Compute relative differences for a list of data
- true
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- true
- Relative Differences
- Relative Differences
-
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116
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9280
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- 1
- List of data to operate on (numbers or points or vectors allowed)
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- Values
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33
24
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9251.5
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- Differences between consecutive items
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-
9292
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55
24
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9319.5
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- Replace Nulls
- Replace nulls or invalid data with other data
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- Replace Nulls
- Replace Nulls
-
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139
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9316
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- Items to test for null
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81
20
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9263.5
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- Items to replace nulls with
- 8d723b5a-3612-4eab-af73-2e9dda257360
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81
20
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9263.5
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- List without any nulls
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9328
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30
20
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9343
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- Number of items replaced
- 2ef8dbc1-9970-4aed-a294-6c634264040b
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- Count
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- 0
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30
20
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9343
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- A wire relay object
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40
16
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- Relay
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- A wire relay object
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40
16
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255;255;255;255
- A group of Grasshopper objects
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- Group
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- Curve Closest Point
- Find the closest point on a curve.
- true
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- true
- Curve Closest Point
- Curve Closest Point
-
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108
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- Point to project onto curve
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30
30
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- Curve to project onto
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9239
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30
30
-
9254
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- Point on the curve closest to the base point
- 1bb228a2-dc74-42f8-9286-2ea0a61f5541
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- 0
-
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20
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9318
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- Parameter on curve domain of closest point
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- 0
-
9293
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- Distance between base point and curve
- d8765e71-78cd-4bf9-b876-205587255b73
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- false
- 0
-
9293
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50
20
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9318
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- Line
- Create a line between two points.
- true
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- true
- Line
- Line
-
9240
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102
44
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- Line start point
- 58e4e377-468f-4afa-a3a3-179155c40ac4
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- Start Point
- false
- 1bb228a2-dc74-42f8-9286-2ea0a61f5541
- 1
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52
20
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- Line end point
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- false
- 3fc85d3c-c590-41ac-8b1b-785ce2f4dba5
- 1
-
9242
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52
20
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9268
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- Line segment
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- 0
-
9318
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22
40
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9329
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- Remap Numbers
- Remap numbers into a new numeric domain
- true
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- true
- Remap Numbers
- Remap Numbers
-
9214
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154
64
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9314
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- Value to remap
- 7f4d5879-b51d-44a5-bb9a-373af2a4d3e3
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- 3fb5b3a3-cc2e-46cb-b9b3-86a17ddf1e4d
- 1
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9216
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86
20
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- Data 0
- 0
- true
- db990e5a-7101-43fc-8c86-5d17627520de
- 1
-
9228
-46019
78
20
-
9267
-46009
- Formatted text
- 562d6de2-a470-4c87-851a-60f7d73c45ec
- true
- Text
- Text
- false
- 0
-
9330
-46059
24
60
-
9342
-46029
- 4fdfe351-6c07-47ce-9fb9-be027fb62186
- Shift List
- Offset all items in a list.
- true
- a74a9afa-f0e7-461e-8d02-835f7eb99731
- true
- Shift List
-
-
9264
-45777
53
64
-
9297
-45745
- 1
- List to shift
- b3c5bd37-19ee-4b56-9f84-99eeaf530316
- true
- List
-
- false
- e7ce9bba-c98c-4fa4-a826-13e1be5ec64f
- 1
-
9266
-45775
19
20
-
9275.5
-45765
- Shift offset
- 300e0933-a303-4121-98a7-8acbc90708a8
- true
- Shift
-
- false
- 0
-
9266
-45755
19
20
-
9275.5
-45745
- 1
- 1
- {0}
- 1
- Wrap values
- 1468092c-80ba-44ce-aa43-edc3111555c6
- true
- Wrap
-
- false
- 0
-
9266
-45735
19
20
-
9275.5
-45725
- 1
- 1
- {0}
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- 1
- Shifted list
- af081197-1368-48fe-8c47-3880d86c7e8a
- true
- List
-
- false
- 0
-
9309
-45775
6
60
-
9312
-45745
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- fb655f23-53fb-4216-9244-493c145ef300
- 5ee7302e-0432-45a9-b320-4441d0df5f9d
- 13a26b56-0263-46e2-aa96-b8798a43d2c3
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- cd2a4e73-beef-4881-af60-1072c3d132d9
- 05e896ad-741a-401e-ae86-0f19c9494cec
- 33
- 0d3e5c8a-1561-4e11-9e1e-e2fca33efcdb
- Group
- afb96615-c59a-45c9-9cac-e27acb1c7ca0
- Explode
- Explode a curve into smaller segments.
- true
- fb655f23-53fb-4216-9244-493c145ef300
- true
- Explode
- Explode
-
9224
-48076
134
44
-
9295
-48054
- Curve to explode
- 9767cfc5-25e4-4f8a-945a-f881a57c21aa
- true
- Curve
- Curve
- false
- 5dd2e2a9-34a6-4201-8cc9-620d4b4583f6
- 1
-
9226
-48074
57
20
-
9254.5
-48064
- Recursive decomposition until all segments are atomic
- 183a96dc-67cf-47eb-b503-33704d2de613
- true
- Recursive
- Recursive
- false
- 0
-
9226
-48054
57
20
-
9254.5
-48044
- 1
- 1
- {0}
- true
- 1
- Exploded segments that make up the base curve
- 34e69f67-2c8a-4d6b-ab01-779325b2045d
- true
- Segments
- Segments
- false
- 0
-
9307
-48074
49
20
-
9331.5
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- 1
- Vertices of the exploded segments
- 0f682b44-c403-4726-bb64-4d33dc0bd13b
- true
- Vertices
- Vertices
- false
- 0
-
9307
-48054
49
20
-
9331.5
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- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 5ee7302e-0432-45a9-b320-4441d0df5f9d
- true
- Evaluate Length
- Evaluate Length
-
9216
-48159
149
64
-
9301
-48127
- Curve to evaluate
- 9a07bf97-34e2-444a-8e99-64a693f04333
- true
- Curve
- Curve
- false
- 34e69f67-2c8a-4d6b-ab01-779325b2045d
- 1
-
9218
-48157
71
20
-
9253.5
-48147
- Length factor for curve evaluation
- 1e21ec69-139a-4764-8822-04b4e11b8847
- true
- Length
- Length
- false
- 0
-
9218
-48137
71
20
-
9253.5
-48127
- 1
- 1
- {0}
- 0.5
- If True, the Length factor is normalized (0.0 ~ 1.0)
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- true
- Normalized
- Normalized
- false
- 0
-
9218
-48117
71
20
-
9253.5
-48107
- 1
- 1
- {0}
- true
- Point at the specified length
- c9713282-cead-492a-b99c-1e8de818a7e4
- true
- Point
- Point
- false
- 0
-
9313
-48157
50
20
-
9338
-48147
- Tangent vector at the specified length
- 6dc474d9-a129-4a18-904d-35c727af5e6f
- true
- Tangent
- Tangent
- false
- 0
-
9313
-48137
50
20
-
9338
-48127
- Curve parameter at the specified length
- d98fddae-6984-4a43-a07f-a359e67c1f4e
- true
- Parameter
- Parameter
- false
- 0
-
9313
-48117
50
20
-
9338
-48107
- 4c619bc9-39fd-4717-82a6-1e07ea237bbe
- Line SDL
- Create a line segment defined by start point, tangent and length.}
- true
- 13a26b56-0263-46e2-aa96-b8798a43d2c3
- true
- Line SDL
- Line SDL
-
9236
-49939
110
64
-
9310
-49907
- Line start point
- 8ca90ede-8f05-48ff-96b8-962e60d968de
- true
- Start
- Start
- false
- c9713282-cead-492a-b99c-1e8de818a7e4
- 1
-
9238
-49937
60
20
-
9276
-49927
- Line tangent (direction)
- bd0c3312-24f2-4240-adc6-f68e9266b467
- true
- Direction
- Direction
- false
- 24cf92d8-0bb7-4e09-b78a-c442ecd7a305
- 1
-
9238
-49917
60
20
-
9276
-49907
- 1
- 1
- {0}
-
0
0
1
- Line length
- 5864852d-a783-4dfb-9d9b-aac5448bf4c7
- ABS(X)
- true
- Length
- Length
- false
- 387a9351-d494-47cf-851b-b4e757e2966e
- 1
-
9238
-49897
60
20
-
9276
-49887
- 1
- 1
- {0}
- 0.015625
- Line segment
- a60b1219-855c-4105-9d60-d49e4c21af43
- true
- Line
- Line
- false
- 0
-
9322
-49937
22
60
-
9333
-49907
- dd17d442-3776-40b3-ad5b-5e188b56bd4c
- Relative Differences
- Compute relative differences for a list of data
- true
- 5d6eced0-8de4-4481-a643-7bfe45510c30
- true
- Relative Differences
- Relative Differences
-
9233
-48502
116
28
-
9280
-48488
- 1
- List of data to operate on (numbers or points or vectors allowed)
- 28b0ff60-628d-4633-8c52-3036259e9a32
- true
- Values
- Values
- false
- 15c4058c-d4ef-48f0-8cd6-a6e9d66cb373
- 1
-
9235
-48500
33
24
-
9251.5
-48488
- 1
- Differences between consecutive items
- b56f4c54-4961-4b83-92cb-a5fc08f6b38b
- true
- Differenced
- Differenced
- false
- 0
-
9292
-48500
55
24
-
9319.5
-48488
- f3230ecb-3631-4d6f-86f2-ef4b2ed37f45
- Replace Nulls
- Replace nulls or invalid data with other data
- true
- dd157dd8-02bf-451c-92e4-60a66dd76cd9
- true
- Replace Nulls
- Replace Nulls
-
9221
-48446
139
44
-
9316
-48424
- 1
- Items to test for null
- f6c4fa24-bc33-406c-b097-e39a132737fe
- true
- Items
- Items
- false
- 4b41e74f-ded6-4ba6-9d30-a92b8bd882f4
- 1
-
9223
-48444
81
20
-
9263.5
-48434
- 1
- Items to replace nulls with
- 8b3a37a0-c996-4736-88d7-5ab7c63a7236
- true
- Replacements
- Replacements
- false
- 0
-
9223
-48424
81
20
-
9263.5
-48414
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_Integer
- 0
- 1
- List without any nulls
- 15c4058c-d4ef-48f0-8cd6-a6e9d66cb373
- true
- Items
- Items
- false
- 0
-
9328
-48444
30
20
-
9343
-48434
- Number of items replaced
- a2be282f-7c76-48da-8645-5a7224e1ee72
- true
- Count
- Count
- false
- 0
-
9328
-48424
30
20
-
9343
-48414
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 4b41e74f-ded6-4ba6-9d30-a92b8bd882f4
- true
- Relay
- false
- 666594ae-a74c-4919-83c2-fc42803f75a7
- 1
-
9271
-48383
40
16
-
9291
-48375
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 6793e99e-b90c-487a-b317-04ab2dc48de9
- true
- Relay
- false
- 75d25b48-e81a-46a3-9843-ac009cb61913
- 1
-
9271
-48747
40
16
-
9291
-48739
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- 5d6eced0-8de4-4481-a643-7bfe45510c30
- dd157dd8-02bf-451c-92e4-60a66dd76cd9
- 884f7be6-32bb-4a29-903a-e313a43a21a0
- 3b821991-b5a9-4b03-b173-4a07543fc3bf
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- 6793e99e-b90c-487a-b317-04ab2dc48de9
- f9c91711-b3d2-4453-a9eb-775517adcba2
- 8
- d8641b5a-18fd-47ec-99cf-7eb566173a48
- Group
- 2dc44b22-b1dd-460a-a704-6462d6e91096
- Curve Closest Point
- Find the closest point on a curve.
- true
- 3a93d28b-110b-43b0-b8c2-580efd293bb4
- true
- Curve Closest Point
- Curve Closest Point
-
9237
-48247
108
64
-
9281
-48215
- Point to project onto curve
- 86defb83-e045-45c7-ac87-bf491e14b959
- true
- Point
- Point
- false
- c9713282-cead-492a-b99c-1e8de818a7e4
- 1
-
9239
-48245
30
30
-
9254
-48230
- Curve to project onto
- 8a7848dd-9c5d-4065-88cd-d13e51ecd083
- true
- Curve
- Curve
- false
- 8e01634f-6886-4da4-93cc-d84f2949b7f1
- 1
-
9239
-48215
30
30
-
9254
-48200
- Point on the curve closest to the base point
- e097ffc2-4a02-4b14-a35a-099424ff6a9b
- true
- Point
- Point
- false
- 0
-
9293
-48245
50
20
-
9318
-48235
- Parameter on curve domain of closest point
- 58554dae-a515-4393-86fb-82d921c5d519
- true
- Parameter
- Parameter
- false
- 0
-
9293
-48225
50
20
-
9318
-48215
- Distance between base point and curve
- 799ed65d-4182-4ee6-bb81-1758bc6d3f32
- true
- Distance
- Distance
- false
- 0
-
9293
-48205
50
20
-
9318
-48195
- 4c4e56eb-2f04-43f9-95a3-cc46a14f495a
- Line
- Create a line between two points.
- true
- 293f4269-47f2-4643-ba3b-3e13a4fe7883
- true
- Line
- Line
-
9240
-48326
102
44
-
9306
-48304
- Line start point
- 4fb679bc-7f98-4a03-add5-497b6adf005f
- true
- Start Point
- Start Point
- false
- e097ffc2-4a02-4b14-a35a-099424ff6a9b
- 1
-
9242
-48324
52
20
-
9268
-48314
- Line end point
- 4c7dad60-41c8-4994-9282-109ef32dfa79
- true
- End Point
- End Point
- false
- c9713282-cead-492a-b99c-1e8de818a7e4
- 1
-
9242
-48304
52
20
-
9268
-48294
- Line segment
- 24cf92d8-0bb7-4e09-b78a-c442ecd7a305
- true
- Line
- Line
- false
- 0
-
9318
-48324
22
40
-
9329
-48304
- 2fcc2743-8339-4cdf-a046-a1f17439191d
- Remap Numbers
- Remap numbers into a new numeric domain
- true
- a86281e6-4353-4d3f-9eb1-d7653305fca6
- true
- Remap Numbers
- Remap Numbers
-
9214
-49637
154
64
-
9314
-49605
- Value to remap
- 26f31415-96f7-4bd3-b74b-bd5d01d9d20f
- true
- Value
- Value
- false
- 08e55973-3950-4b60-89f4-5a5d6d781df6
- 1
-
9216
-49635
86
20
-
9259
-49625
- Source domain
- ff3e2bfd-dae3-49c4-9eea-ec4da89835ef
- true
- Source
- Source
- false
- a6f1e98e-c654-4b65-9a18-c0d2a1b3b551
- 1
-
9216
-49615
86
20
-
9259
-49605
- 1
- 1
- {0}
-
0
1
- Target domain
- c324c9be-cf72-472a-bdac-be927c4f0854
- true
- Target
- Target
- false
- 0
-
9216
-49595
86
20
-
9259
-49585
- 1
- 1
- {0}
-
-1
1
- Remapped number
- 4f4db73d-5173-4701-a0c5-73cdda611bc9
- true
- Mapped
- Mapped
- false
- 0
-
9326
-49635
40
30
-
9346
-49620
- Remapped and clipped number
- 07e65e72-7094-478b-8fa8-1dd7c589b1f2
- true
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- Clipped
- false
- 0
-
9326
-49605
40
30
-
9346
-49590
- f44b92b0-3b5b-493a-86f4-fd7408c3daf3
- Bounds
- Create a numeric domain which encompasses a list of numbers.
- true
- d727fe22-76d5-43e4-a2ad-e015518775ab
- true
- Bounds
- Bounds
-
9236
-49555
110
28
-
9294
-49541
- 1
- Numbers to include in Bounds
- 937f8b64-1f53-47a0-aace-e59d4558007d
- true
- Numbers
- Numbers
- false
- 08e55973-3950-4b60-89f4-5a5d6d781df6
- 1
-
9238
-49553
44
24
-
9260
-49541
- Numeric Domain between the lowest and highest numbers in {N}
- a6f1e98e-c654-4b65-9a18-c0d2a1b3b551
- true
- Domain
- Domain
- false
- 0
-
9306
-49553
38
24
-
9325
-49541
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 08e55973-3950-4b60-89f4-5a5d6d781df6
- true
- Relay
-
- false
- 6793e99e-b90c-487a-b317-04ab2dc48de9
- 1
-
9271
-49508
40
16
-
9291
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- ce46b74e-00c9-43c4-805a-193b69ea4a11
- Multiplication
- Mathematical multiplication
- true
- a8912d4a-a935-4bad-872b-dc57f88db955
- true
- Multiplication
- Multiplication
-
9256
-49836
70
44
-
9281
-49814
- 2
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- First item for multiplication
- 126229b7-a3c9-48c2-907a-2efa6caee85a
- true
- A
- A
- true
- 40f47511-ffd1-477e-bc85-8e0aba14854a
- 1
-
9258
-49834
11
20
-
9263.5
-49824
- Second item for multiplication
- 63bd6145-31be-4e5b-be6f-5fdcbd3d404b
- true
- B
- B
- true
- 8f638ca0-ed19-449b-9dac-37d0d7994511
- 1
-
9258
-49814
11
20
-
9263.5
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- Result of multiplication
- 387a9351-d494-47cf-851b-b4e757e2966e
- true
- Result
- Result
- false
- 0
-
9293
-49834
31
40
-
9308.5
-49814
- ce46b74e-00c9-43c4-805a-193b69ea4a11
- Multiplication
- Mathematical multiplication
- true
- 0af8b992-3a96-476d-9b99-13e9fc9f049e
- true
- Multiplication
- Multiplication
-
9256
-49729
70
44
-
9281
-49707
- 2
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- First item for multiplication
- c4f9a2d0-ae90-4fbf-9466-3da40c26020b
- true
- A
- A
- true
- 677cfb40-4f5b-4b46-b8c2-bacf32c9f1f3
- 1
-
9258
-49727
11
20
-
9263.5
-49717
- Second item for multiplication
- 0a679f02-4d5e-4855-973a-578b79a2e366
- true
- B
- B
- true
- 4f4db73d-5173-4701-a0c5-73cdda611bc9
- 1
-
9258
-49707
11
20
-
9263.5
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- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
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- Evaluate Length
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- Curve to evaluate
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- Length factor for curve evaluation
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- If True, the Length factor is normalized (0.0 ~ 1.0)
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- Line start point
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- Compute relative differences for a list of data
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- Replace nulls or invalid data with other data
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- Find the closest point on a curve.
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- Point on the curve closest to the base point
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- Line
- Create a line between two points.
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- Line start point
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- Line end point
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- Line segment
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- Remap numbers into a new numeric domain
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- Value to remap
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- Source domain
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- Remapped number
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- Remapped and clipped number
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40
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- Create a numeric domain which encompasses a list of numbers.
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- Numbers to include in Bounds
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- Numeric Domain between the lowest and highest numbers in {N}
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- A wire relay object
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- Mathematical multiplication
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- First item for multiplication
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11
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- Second item for multiplication
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- Second item for multiplication
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- Amount of transparency (0.0 = opaque, 1.0 = transparent
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- Amount of shinyness (0 = none, 1 = low shine, 100 = max shine
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100
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- Allows for customized geometry previews
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- Custom Preview
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255;66;48;66
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255;255;255;255
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- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
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- Evaluate Length
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- Create an OpenGL material.
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- Create Material
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- Emissive colour of the material
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9217
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- Amount of transparency (0.0 = opaque, 1.0 = transparent
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- Amount of shinyness (0 = none, 1 = low shine, 100 = max shine
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255;255;255;255
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- Display a set of y-values as a graph
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- Length
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- Replace nulls or invalid data with other data
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- Replace Nulls
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- Items to replace nulls with
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- List without any nulls
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- A group of Grasshopper objects
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- Find the closest point on a curve.
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- Curve Closest Point
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- Point on the curve closest to the base point
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- Create a line between two points.
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- Line
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- Line segment
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- Remap numbers into a new numeric domain
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- Remap Numbers
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- Value to remap
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- Source domain
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- Create a numeric domain which encompasses a list of numbers.
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- Bounds
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- Numbers to include in Bounds
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- Numeric Domain between the lowest and highest numbers in {N}
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- Relay
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- A wire relay object
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- Multiplication
- Mathematical multiplication
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- Second item for multiplication
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- Multiplication
- Mathematical multiplication
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255;255;255;255
- A group of Grasshopper objects
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255;255;255;255
- A group of Grasshopper objects
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- Panel
- A panel for custom notes and text values
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255;255;255;255
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255;255;255;255
- A group of Grasshopper objects
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255;0;255;255
- Emissive colour of the material
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- Amount of shinyness (0 = none, 1 = low shine, 100 = max shine
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- Resulting material
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- Allows for customized geometry previews
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255;255;255;255
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- Curve to evaluate
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- Length factor for curve evaluation
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- Point at the specified length
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- Tangent vector at the specified length
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28
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9281
-4549
- Boolean value
- 4a19fc6e-2d7a-471b-bcce-d5a1412e0f43
- true
- A
- A
- false
- 80f66cc8-3f0d-4c83-97be-347c0623d535
- 1
-
9258
-4561
11
24
-
9263.5
-4549
- Inverse of {A}
- 802b0d79-1abc-4cd7-ba38-3ade85c28c58
- true
- Result
- Result
- false
- 0
-
9293
-4561
31
24
-
9308.5
-4549
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 0fb387e0-8efc-430a-ad2a-08f863556546
- true
- Stream Filter
- Stream Filter
-
9258
-9145
77
64
-
9297
-9113
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 06399296-3657-4782-9f14-124355221b9f
- true
- Gate
- Gate
- false
- 802b0d79-1abc-4cd7-ba38-3ade85c28c58
- 1
-
9260
-9143
25
20
-
9272.5
-9133
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 3ce03926-3ca1-4b34-9f25-cd3e173de9c7
- true
- false
- Stream 0
- 0
- true
- a09d1915-e012-4d72-94f9-1f234a1c91ef
- 1
-
9260
-9123
25
20
-
9272.5
-9113
- 2
- Input stream at index 1
- 857fca33-c58b-41c7-8da9-c407944e98d0
- true
- false
- Stream 1
- 1
- true
- 6bd020fd-c652-4ed0-a741-6c88bd6ac075
- 1
-
9260
-9103
25
20
-
9272.5
-9093
- 2
- Filtered stream
- f05ffc93-07b8-46d2-ad82-99badcc3922f
- true
- false
- Stream
- S(0)
- false
- 0
-
9309
-9143
24
60
-
9321
-9113
- 6b5812f5-bb36-4d74-97fc-5a1f2f77452d
- Pull Curve
- Pull a curve onto a surface.
- true
- 67c2acc7-61e8-4dc8-a403-e7221b033383
- true
- Pull Curve
- Pull Curve
-
9248
-8754
96
44
-
9300
-8732
- Curve to pull
- bf9a89d7-1a9d-482a-bf2a-6b0992a45c8e
- true
- Curve
- Curve
- false
- a09d1915-e012-4d72-94f9-1f234a1c91ef
- 1
-
9250
-8752
38
20
-
9269
-8742
- Surface that pulls
- b5456d1f-1e8c-44b5-ab48-3f4ff8a70665
- true
- Surface
- Surface
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9250
-8732
38
20
-
9269
-8722
- Curve pulled onto the surface
- f6a8a08e-b879-4b59-a042-87b09c2b6c2b
- true
- Curve
- Curve
- false
- 0
-
9312
-8752
30
40
-
9327
-8732
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 3aa22581-402f-4750-9268-ebe07eb256aa
- true
- Stream Filter
- Stream Filter
-
9252
-6015
77
64
-
9291
-5983
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 0b765458-3919-4cd0-993f-6aa485fe7bf3
- true
- Gate
- Gate
- false
- 802b0d79-1abc-4cd7-ba38-3ade85c28c58
- 1
-
9254
-6013
25
20
-
9266.5
-6003
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 90c1f92c-2d02-411c-9226-2b4827ecba0a
- true
- false
- Stream 0
- 0
- true
- 58715e09-1461-47aa-b311-c9878cbef364
- 1
-
9254
-5993
25
20
-
9266.5
-5983
- 2
- Input stream at index 1
- 37f8811e-d59a-4893-874f-2b9c4546f538
- true
- false
- Stream 1
- 1
- true
- 4a40ed77-eaa2-427a-b632-c4c14ac83a0b
- 1
-
9254
-5973
25
20
-
9266.5
-5963
- 2
- Filtered stream
- 043ef658-425b-4fc2-a0ed-57be30e7b117
- true
- false
- Stream
- S(0)
- false
- 0
-
9303
-6013
24
60
-
9315
-5983
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- cffd2b57-8bcb-4248-b984-bdaff8648b5a
- true
- Pull Point
- Pull Point
-
9218
-5913
139
44
-
9280
-5891
- Point to search from
- fe439557-86d3-43a2-8342-9265ab7171de
- true
- Point
- Point
- false
- 58715e09-1461-47aa-b311-c9878cbef364
- 1
-
9220
-5911
48
20
-
9244
-5901
- 1
- Geometry that pulls
- 9eeef12b-bde5-45d2-bce9-93075540eb20
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9220
-5891
48
20
-
9244
-5881
- Point on [G] closest to [P]
- 4a40ed77-eaa2-427a-b632-c4c14ac83a0b
- true
- Closest Point
- Closest Point
- false
- 0
-
9292
-5911
63
20
-
9323.5
-5901
- Distance between [P] and its projection onto [G]
- c687cd8d-0db6-4027-9696-f010a1126597
- true
- Distance
- Distance
- false
- 0
-
9292
-5891
63
20
-
9323.5
-5881
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 345d893b-ae16-4ece-bd87-af320cd62598
- true
- Stream Filter
- Stream Filter
-
9253
-9703
77
64
-
9292
-9671
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 77af05a8-653a-45bd-830f-5a0030ac485c
- true
- Gate
- Gate
- false
- 802b0d79-1abc-4cd7-ba38-3ade85c28c58
- 1
-
9255
-9701
25
20
-
9267.5
-9691
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- a3a17ee1-6a78-4b93-a151-c427f687d7e9
- true
- false
- Stream 0
- 0
- true
- a87341fb-0950-4665-a5d5-5556809dce9d
- 1
-
9255
-9681
25
20
-
9267.5
-9671
- 2
- Input stream at index 1
- d52d4520-ddac-4ef0-93e6-a0f531a518f5
- true
- false
- Stream 1
- 1
- true
- d93903ee-cfd9-4f91-a642-a9eaaec44230
- 1
-
9255
-9661
25
20
-
9267.5
-9651
- 2
- Filtered stream
- 2b484d46-7738-42ff-b212-eea1c16c05f0
- true
- false
- Stream
- S(0)
- false
- 0
-
9304
-9701
24
60
-
9316
-9671
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- 1da4a747-337d-46d9-818d-512d2d11e43e
- true
- Pull Point
- Pull Point
-
9222
-9617
139
44
-
9284
-9595
- Point to search from
- 5e66e12e-afa5-4667-a021-d5ac897d3938
- true
- Point
- Point
- false
- a87341fb-0950-4665-a5d5-5556809dce9d
- 1
-
9224
-9615
48
20
-
9248
-9605
- 1
- Geometry that pulls
- 54065e6e-a92c-4ad6-99ee-f60600a2edea
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9224
-9595
48
20
-
9248
-9585
- Point on [G] closest to [P]
- d93903ee-cfd9-4f91-a642-a9eaaec44230
- true
- Closest Point
- Closest Point
- false
- 0
-
9296
-9615
63
20
-
9327.5
-9605
- Distance between [P] and its projection onto [G]
- 2e023752-5825-4542-b000-932bfa2ad17b
- true
- Distance
- Distance
- false
- 0
-
9296
-9595
63
20
-
9327.5
-9585
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- a8f38f9e-b3b6-41bd-8db4-16fabd280f08
- true
- Stream Filter
- Stream Filter
-
9240
-12697
77
64
-
9279
-12665
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 765f81d8-ff1a-4ba1-a493-527c32710a12
- true
- Gate
- Gate
- false
- 802b0d79-1abc-4cd7-ba38-3ade85c28c58
- 1
-
9242
-12695
25
20
-
9254.5
-12685
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- cf08a60a-85fc-4f3b-9da2-15233702dcb6
- true
- false
- Stream 0
- 0
- true
- f0c191c1-9621-4bbc-8f42-70fddab36b4d
- 1
-
9242
-12675
25
20
-
9254.5
-12665
- 2
- Input stream at index 1
- 48956a2f-d6d5-40df-a623-85bf867ad2c8
- true
- false
- Stream 1
- 1
- true
- 21adf162-6466-48ed-b0e4-8aa61cab45ec
- 1
-
9242
-12655
25
20
-
9254.5
-12645
- 2
- Filtered stream
- 1e2a7b7f-adc5-4de7-b89a-18f9809254ce
- true
- false
- Stream
- S(0)
- false
- 0
-
9291
-12695
24
60
-
9303
-12665
- 6b5812f5-bb36-4d74-97fc-5a1f2f77452d
- Pull Curve
- Pull a curve onto a surface.
- true
- 99f6eb91-99d8-4603-b7d0-eca216200d71
- true
- Pull Curve
- Pull Curve
-
9243
-12281
96
44
-
9295
-12259
- Curve to pull
- 0fc24e2e-c021-40bb-b392-83f0246cbe7c
- true
- Curve
- Curve
- false
- f0c191c1-9621-4bbc-8f42-70fddab36b4d
- 1
-
9245
-12279
38
20
-
9264
-12269
- Surface that pulls
- d0cd04f6-9e03-4121-8fb3-ce8a508d7d13
- true
- Surface
- Surface
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9245
-12259
38
20
-
9264
-12249
- Curve pulled onto the surface
- 2a1421bd-02db-438e-a5d2-207894cd0bdf
- true
- Curve
- Curve
- false
- 0
-
9307
-12279
30
40
-
9322
-12259
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 27beda7a-8035-4b7f-baa6-07b36b445f36
- true
- Stream Filter
- Stream Filter
-
9249
-13260
77
64
-
9288
-13228
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- eb605005-2673-4e61-ba1f-8c64b2ef9ade
- true
- Gate
- Gate
- false
- 802b0d79-1abc-4cd7-ba38-3ade85c28c58
- 1
-
9251
-13258
25
20
-
9263.5
-13248
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- f7702fdb-1b65-460e-9e74-92dca8113c0c
- true
- false
- Stream 0
- 0
- true
- 042a386a-fcdb-4902-bf3e-1cca2eff73b7
- 1
-
9251
-13238
25
20
-
9263.5
-13228
- 2
- Input stream at index 1
- cfa06fd1-5b9b-4ca9-ad9f-5fb3d360486e
- true
- false
- Stream 1
- 1
- true
- ad599a39-f198-4941-8d4e-7089ae235a5c
- 1
-
9251
-13218
25
20
-
9263.5
-13208
- 2
- Filtered stream
- 33a6314b-e63e-4e80-b5e3-dcd21060daa4
- true
- false
- Stream
- S(0)
- false
- 0
-
9300
-13258
24
60
-
9312
-13228
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- 344c01b0-b3be-4158-b3f3-3e875533be20
- true
- Pull Point
- Pull Point
-
9218
-13174
139
44
-
9280
-13152
- Point to search from
- d8d70767-e3b6-4210-87e4-db9f5422e6d5
- true
- Point
- Point
- false
- 042a386a-fcdb-4902-bf3e-1cca2eff73b7
- 1
-
9220
-13172
48
20
-
9244
-13162
- 1
- Geometry that pulls
- 3e9f1b53-15bb-4e99-8471-f8f99e6dd451
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9220
-13152
48
20
-
9244
-13142
- Point on [G] closest to [P]
- ad599a39-f198-4941-8d4e-7089ae235a5c
- true
- Closest Point
- Closest Point
- false
- 0
-
9292
-13172
63
20
-
9323.5
-13162
- Distance between [P] and its projection onto [G]
- 3619df5e-57e4-4d5b-94ee-4852c16b2c53
- true
- Distance
- Distance
- false
- 0
-
9292
-13152
63
20
-
9323.5
-13142
- a4b285fe-2e13-4204-b65c-189aa6704da5
- CURWE CURWATURE THIRD DIFERENCE COMBS
- CURWE CURWATURE THIRD DIFERENCE COMBS
- CURWE CURWATURE THIRD DIFERENCE COMBS
- CURWE CURWATURE THIRD DIFERENCE COMBS
- CURWE CURWATURE THIRD DIFERENCE COMBS
- 50e1ac8e-1daf-4c52-bfc9-ae6c4c4b5d7f
- true
- CURWE CURWATURE THIRD DIFERENCE COMBS
- CURWE CURWATURE THIRD DIFERENCE COMBS
- false
- e29ca557-b1ee-475d-8cd9-63721b3e955d
- 1
-
9161
-16336
260
24
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 4337397e-3fc7-4255-8ed1-ffd880a2c289
- true
- Stream Filter
- Stream Filter
-
9253
-16279
77
64
-
9292
-16247
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 65692a58-3f42-4520-b6a7-f0151dcc0718
- true
- Gate
- Gate
- false
- 802b0d79-1abc-4cd7-ba38-3ade85c28c58
- 1
-
9255
-16277
25
20
-
9267.5
-16267
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 2468b678-acbf-4073-b3ae-54742b7c16b3
- true
- false
- Stream 0
- 0
- true
- 0f214bdb-5cad-4d4f-8eee-7b8f3600bdca
- 1
-
9255
-16257
25
20
-
9267.5
-16247
- 2
- Input stream at index 1
- f5e32804-3e4e-4b0b-a77b-6482c099a921
- true
- false
- Stream 1
- 1
- true
- fa5104ec-99e6-4c5c-94e7-3b82a0aab230
- 1
-
9255
-16237
25
20
-
9267.5
-16227
- 2
- Filtered stream
- e29ca557-b1ee-475d-8cd9-63721b3e955d
- true
- false
- Stream
- S(0)
- false
- 0
-
9304
-16277
24
60
-
9316
-16247
- 6b5812f5-bb36-4d74-97fc-5a1f2f77452d
- Pull Curve
- Pull a curve onto a surface.
- true
- da88dd80-8efd-4e21-a39e-70ce76cc2119
- true
- Pull Curve
- Pull Curve
-
9248
-15858
96
44
-
9300
-15836
- Curve to pull
- 7d3eb441-b313-4123-b7c6-6acfea0e0451
- true
- Curve
- Curve
- false
- 0f214bdb-5cad-4d4f-8eee-7b8f3600bdca
- 1
-
9250
-15856
38
20
-
9269
-15846
- Surface that pulls
- 35ff5b6f-8d0b-47ef-92d9-7c8f0c53416d
- true
- Surface
- Surface
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9250
-15836
38
20
-
9269
-15826
- Curve pulled onto the surface
- 4ce8f03b-1734-4055-b3e3-dd585ded15d2
- true
- Curve
- Curve
- false
- 0
-
9312
-15856
30
40
-
9327
-15836
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- e63d5bc1-5483-4565-b5c9-382b62dd7532
- true
- Stream Filter
- Stream Filter
-
9251
-16905
77
64
-
9290
-16873
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- ce043f9d-fe44-4b8a-9441-a4276d4b4af8
- true
- Gate
- Gate
- false
- 802b0d79-1abc-4cd7-ba38-3ade85c28c58
- 1
-
9253
-16903
25
20
-
9265.5
-16893
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- dc38c735-e61f-40d1-9269-c26f9f69c8ad
- true
- false
- Stream 0
- 0
- true
- 4c437000-729e-49e9-9151-342e882d2ecc
- 1
-
9253
-16883
25
20
-
9265.5
-16873
- 2
- Input stream at index 1
- 426541d6-3cf4-43c2-8d13-42c3fb62ef71
- true
- false
- Stream 1
- 1
- true
- cdf037a9-f123-4d5a-86f7-16caaac5483f
- 1
-
9253
-16863
25
20
-
9265.5
-16853
- 2
- Filtered stream
- bab303dd-61c9-49e9-a983-cbe9cf957b57
- true
- false
- Stream
- S(0)
- false
- 0
-
9302
-16903
24
60
-
9314
-16873
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- 05d4fb4f-a50c-46d2-9aa5-be6d19680490
- true
- Pull Point
- Pull Point
-
9222
-16801
139
44
-
9284
-16779
- Point to search from
- 0e77c4aa-a22e-4306-beba-f9596e55ae3c
- true
- Point
- Point
- false
- 4c437000-729e-49e9-9151-342e882d2ecc
- 1
-
9224
-16799
48
20
-
9248
-16789
- 1
- Geometry that pulls
- 935e197b-5830-4f82-9942-4df625646cfd
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9224
-16779
48
20
-
9248
-16769
- Point on [G] closest to [P]
- cdf037a9-f123-4d5a-86f7-16caaac5483f
- true
- Closest Point
- Closest Point
- false
- 0
-
9296
-16799
63
20
-
9327.5
-16789
- Distance between [P] and its projection onto [G]
- 83b3f5e8-b221-404e-8d7c-8b3273cef8bd
- true
- Distance
- Distance
- false
- 0
-
9296
-16779
63
20
-
9327.5
-16769
- a4b285fe-2e13-4204-b65c-189aa6704da5
- CURWE CURWATURE SECOND DIFERENCE COMBS
- CURWE CURWATURE SECOND DIFERENCE COMBS
- CURWE CURWATURE SECOND DIFERENCE COMBS
- CURWE CURWATURE SECOND DIFERENCE COMBS
- CURWE CURWATURE SECOND DIFERENCE COMBS
- 30482e7c-7286-4502-a14e-85a6c35b7c79
- true
- CURWE CURWATURE SECOND DIFERENCE COMBS
- CURWE CURWATURE SECOND DIFERENCE COMBS
- false
- 1e2a7b7f-adc5-4de7-b89a-18f9809254ce
- 1
-
9155
-12746
272
24
- 448de216-3a12-43cf-a135-e3bfafc87744
- CURWE INPUT
- CURWE INPUT
- CURWE INPUT
- CURWE INPUT
- CURWE INPUT
- cd5b889e-e4dd-448f-9673-4b231165ae21
- true
- CURWE INPUT
- CURWE INPUT
- false
- 0
-
9248
-599
101
24
- a4b285fe-2e13-4204-b65c-189aa6704da5
- CURWE OUTPUT
- CURWE OUTPUT
- CURWE OUTPUT
- CURWE OUTPUT
- CURWE OUTPUT
- f26535d4-91e9-4d8f-8216-dab8258daddf
- true
- CURWE OUTPUT
- CURWE OUTPUT
- false
- 41be65b0-4832-475b-82e4-72e5cbea050c
- 1
-
9235
-738
112
24
- 448de216-3a12-43cf-a135-e3bfafc87744
- CURWE POINT NUMBER INPUT
- CURWE POINT NUMBER INPUT
- CURWE POINT NUMBER INPUT
- CURWE POINT NUMBER INPUT
- CURWE POINT NUMBER INPUT
- 7821d745-ea35-4b5e-9bc1-0ed25432d936
- true
- CURWE POINT NUMBER INPUT
- CURWE POINT NUMBER INPUT
- false
- 0
-
9210
-2092
178
24
- 3e8ca6be-fda8-4aaf-b5c0-3c54c8bb7312
- Number
- Contains a collection of floating point numbers
- 41d4fcae-5924-4999-8519-7d3c327b7aea
- true
- Number
- Number
- false
- 0
-
9267
-2126
52
24
-
9307.541
-2114.887
- 1
- 1
- {0}
- 256
- a4b285fe-2e13-4204-b65c-189aa6704da5
- CURWE POINT NUMBER OUTPUT
- CURWE POINT NUMBER OUTPUT
- CURWE POINT NUMBER OUTPUT
- CURWE POINT NUMBER OUTPUT
- CURWE POINT NUMBER OUTPUT
- 63995dad-5a38-4819-9bc6-c7368d2aa8c0
- true
- CURWE POINT NUMBER OUTPUT
- CURWE POINT NUMBER OUTPUT
- false
- 41d4fcae-5924-4999-8519-7d3c327b7aea
- 1
-
9204
-2195
189
24
- 3e8ca6be-fda8-4aaf-b5c0-3c54c8bb7312
- Number
- Contains a collection of floating point numbers
- 811f77e7-8403-4ccc-a67a-e88eab309b40
- true
- 2
- Number
- Number
- false
- 0
-
9273
-4115
50
24
-
9306.541
-4103.887
- 1
- 2
- {0}
- 0
- 180
- 448de216-3a12-43cf-a135-e3bfafc87744
- CURWE CURWATURE COMBS TORSION ROTATION ANGLE INPUT
- CURWE CURWATURE COMBS TORSION ROTATION ANGLE INPUT
- CURWE CURWATURE COMBS TORSION ROTATION ANGLE INPUT
- CURWE CURWATURE COMBS TORSION ROTATION ANGLE INPUT
- CURWE CURWATURE COMBS TORSION ROTATION ANGLE INPUT
- 8bb07237-8043-4bfc-9482-36c5f324e171
- true
- CURWE CURWATURE COMBS TORSION ROTATION ANGLE INPUT
- CURWE CURWATURE COMBS TORSION ROTATION ANGLE INPUT
- false
- 0
-
9128
-4086
341
24
- a4b285fe-2e13-4204-b65c-189aa6704da5
- CURWE CURWATURE COMBS TORSION ROTATION ANGLE OUTPUT
- CURWE CURWATURE COMBS TORSION ROTATION ANGLE OUTPUT
- CURWE CURWATURE COMBS TORSION ROTATION ANGLE OUTPUT
- CURWE CURWATURE COMBS TORSION ROTATION ANGLE OUTPUT
- CURWE CURWATURE COMBS TORSION ROTATION ANGLE OUTPUT
- 99e87cc0-6a4b-442b-884b-8221f251b9bf
- true
- CURWE CURWATURE COMBS TORSION ROTATION ANGLE OUTPUT
- CURWE CURWATURE COMBS TORSION ROTATION ANGLE OUTPUT
- false
- 811f77e7-8403-4ccc-a67a-e88eab309b40
- 1
-
9123
-4169
352
24
- 448de216-3a12-43cf-a135-e3bfafc87744
- MAGNET SURFACE INPUT
- MAGNET SURFACE INPUT
- MAGNET SURFACE INPUT
- MAGNET SURFACE INPUT
- MAGNET SURFACE INPUT
- 1bf8b430-d382-4280-aaec-0188aafb741b
- true
- MAGNET SURFACE INPUT
- MAGNET SURFACE INPUT
- false
- 0
-
9210
-4329
156
24
- a4b285fe-2e13-4204-b65c-189aa6704da5
- MAGNET SURFACE OUTPUT
- MAGNET SURFACE OUTPUT
- MAGNET SURFACE OUTPUT
- MAGNET SURFACE OUTPUT
- MAGNET SURFACE OUTPUT
- fd8be7fd-657d-4392-aabd-296e39ed305b
- true
- MAGNET SURFACE OUTPUT
- MAGNET SURFACE OUTPUT
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9220
-4422
167
24
- deaf8653-5528-4286-807c-3de8b8dad781
- Surface
- Contains a collection of generic surfaces
- true
- d2b2d690-7218-44bb-aa7c-3040cab09077
- true
- Surface
- Surface
- false
- 1bf8b430-d382-4280-aaec-0188aafb741b
- 1
-
9271
-4359
50
24
-
9296.633
-4347
- a4b285fe-2e13-4204-b65c-189aa6704da5
- CURWE CURWATURE COMB SCALED LINES
- CURWE CURWATURE COMB SCALED LINES
- CURWE CURWATURE COMB SCALED LINES
- CURWE CURWATURE COMB SCALED LINES
- CURWE CURWATURE COMB SCALED LINES
- d992dcbb-ebd0-41d4-96b3-793a6c463864
- true
- CURWE CURWATURE COMB SCALED LINES
- CURWE CURWATURE COMB SCALED LINES
- false
- 4a88ebb8-f367-4644-9b81-883895d1f5b5
- 1
-
9185
-5503
239
24
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 4a88ebb8-f367-4644-9b81-883895d1f5b5
- true
- Relay
- false
- 88d2e234-202c-4e3b-adb8-c6bf7cc9988f
- 1
-
9272
-5497
40
16
-
9292
-5489
- 448de216-3a12-43cf-a135-e3bfafc87744
- CURWE CURWATURE FIRST DIFERENCE COMB LINES SCALE
- CURWE CURWATURE FIRST DIFERENCE COMB LINES SCALE
- CURWE CURWATURE FIRST DIFERENCE COMB LINES SCALE
- CURWE CURWATURE FIRST DIFERENCE COMB LINES SCALE
- CURWE CURWATURE FIRST DIFERENCE COMB LINES SCALE
- 1bfd648a-9dbf-4c36-aaf1-6faf76bdedb5
- true
- CURWE CURWATURE FIRST DIFERENCE COMB LINES SCALE
- CURWE CURWATURE FIRST DIFERENCE COMB LINES SCALE
- false
- 0
-
9136
-8490
318
24
- a4b285fe-2e13-4204-b65c-189aa6704da5
- CURWE CURWATURE FIRST DIFERENCE COMB SCALED LINES
- CURWE CURWATURE FIRST DIFERENCE COMB SCALED LINES
- CURWE CURWATURE FIRST DIFERENCE COMB SCALED LINES
- CURWE CURWATURE FIRST DIFERENCE COMB SCALED LINES
- CURWE CURWATURE FIRST DIFERENCE COMB SCALED LINES
- 87c359c8-b31a-41d3-b2bd-e7427c264c27
- true
- CURWE CURWATURE FIRST DIFERENCE COMB SCALED LINES
- CURWE CURWATURE FIRST DIFERENCE COMB SCALED LINES
- false
- f05ffc93-07b8-46d2-ad82-99badcc3922f
- 1
-
9138
-9208
325
24
- 11bbd48b-bb0a-4f1b-8167-fa297590390d
- End Points
- Extract the end points of a curve.
- true
- 4ce1f53e-bf61-44f8-95a4-3bf2d4d1053a
- true
- End Points
- End Points
-
9258
-5087
84
44
-
9302
-5065
- Curve to evaluate
- 8dae861f-afe2-42b0-9cb4-014ad80440a7
- true
- Curve
- Curve
- false
- 2158b91e-623b-4f9d-8297-f4edb0d6540d
- 1
-
9260
-5085
30
40
-
9275
-5065
- Curve start point
- 02964a7a-328e-4e32-b6c3-ac54c648bd49
- true
- Start
- Start
- false
- 0
-
9314
-5085
26
20
-
9327
-5075
- Curve end point
- 880ada06-8e88-49d0-a801-f5c9b0f2ca43
- true
- End
- End
- false
- 0
-
9314
-5065
26
20
-
9327
-5055
- 4c4e56eb-2f04-43f9-95a3-cc46a14f495a
- Line
- Create a line between two points.
- true
- 745e50c0-24f0-4225-8841-a5b5f1afa79a
- true
- Line
- Line
-
9252
-5317
102
44
-
9318
-5295
- Line start point
- a5d03a6d-660c-4a71-bd5e-77182badde8d
- true
- Start Point
- Start Point
- false
- b3380cd0-b123-474a-bec6-3ad36c042595
- 1
-
9254
-5315
52
20
-
9280
-5305
- Line end point
- 522b2fbe-2fde-49b8-8c7e-bd72f92ea85a
- true
- End Point
- End Point
- false
- 937ad2f4-5ea8-48a5-a340-e4353478cf5d
- 1
-
9254
-5295
52
20
-
9280
-5285
- Line segment
- 6eec554b-c75f-4491-ab5f-2ae78a628fbd
- true
- Line
- Line
- false
- 0
-
9330
-5315
22
40
-
9341
-5295
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- b0c7518a-4219-4602-839c-235029b1a34d
- true
- Pull Point
- Pull Point
-
9230
-5252
139
44
-
9292
-5230
- Point to search from
- 6420395e-ae10-439c-861f-5521d6b29247
- true
- Point
- Point
- false
- 02964a7a-328e-4e32-b6c3-ac54c648bd49
- 1
-
9232
-5250
48
20
-
9256
-5240
- 1
- Geometry that pulls
- d0a38b31-0118-4144-a9da-672b0ab438fe
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9232
-5230
48
20
-
9256
-5220
- Point on [G] closest to [P]
- b3380cd0-b123-474a-bec6-3ad36c042595
- true
- Closest Point
- Closest Point
- false
- 0
-
9304
-5250
63
20
-
9335.5
-5240
- Distance between [P] and its projection onto [G]
- e90fc0ab-3867-40e6-8233-7a7f6cfaf7ce
- true
- Distance
- Distance
- false
- 0
-
9304
-5230
63
20
-
9335.5
-5220
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- 4a12da5d-898e-4144-8e8d-1b907f89642d
- true
- Pull Point
- Pull Point
-
9230
-5171
139
44
-
9292
-5149
- Point to search from
- 213f65d7-b440-4029-b830-2d5d796c2542
- true
- Point
- Point
- false
- 880ada06-8e88-49d0-a801-f5c9b0f2ca43
- 1
-
9232
-5169
48
20
-
9256
-5159
- 1
- Geometry that pulls
- a05f35ae-e2dc-4338-a49b-4407ac509c21
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9232
-5149
48
20
-
9256
-5139
- Point on [G] closest to [P]
- 937ad2f4-5ea8-48a5-a340-e4353478cf5d
- true
- Closest Point
- Closest Point
- false
- 0
-
9304
-5169
63
20
-
9335.5
-5159
- Distance between [P] and its projection onto [G]
- 933aaf31-a580-4971-99cd-3b6db6bd23a6
- true
- Distance
- Distance
- false
- 0
-
9304
-5149
63
20
-
9335.5
-5139
- 11bbd48b-bb0a-4f1b-8167-fa297590390d
- End Points
- Extract the end points of a curve.
- true
- 3697088f-7b9c-42f6-bd64-2174aa7f816c
- true
- End Points
- End Points
-
9244
-8813
84
44
-
9288
-8791
- Curve to evaluate
- 22caa755-7d7e-430f-9f50-e8a634162200
- true
- Curve
- Curve
- false
- a09d1915-e012-4d72-94f9-1f234a1c91ef
- 1
-
9246
-8811
30
40
-
9261
-8791
- Curve start point
- 9657b5c7-9576-49ed-a6d7-ae032aeec3e9
- true
- Start
- Start
- false
- 0
-
9300
-8811
26
20
-
9313
-8801
- Curve end point
- 3d1c3c8e-ba45-4486-ad01-a0d1d102f456
- true
- End
- End
- false
- 0
-
9300
-8791
26
20
-
9313
-8781
- 4c4e56eb-2f04-43f9-95a3-cc46a14f495a
- Line
- Create a line between two points.
- true
- ca04f8b3-a611-47df-b7e3-410b2099d099
- true
- Line
- Line
-
9235
-9036
102
44
-
9301
-9014
- Line start point
- b67fb9a3-7a4e-4873-9782-0b17a8a5c446
- true
- Start Point
- Start Point
- false
- 3eca4bac-2695-407c-9f4e-de9f268b685e
- 1
-
9237
-9034
52
20
-
9263
-9024
- Line end point
- d59b3a89-55ca-4698-a494-1201157d81dc
- true
- End Point
- End Point
- false
- 829d4ae8-b090-4cbd-84cb-f25ffc968842
- 1
-
9237
-9014
52
20
-
9263
-9004
- Line segment
- 6bd020fd-c652-4ed0-a741-6c88bd6ac075
- true
- Line
- Line
- false
- 0
-
9313
-9034
22
40
-
9324
-9014
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- 8ab55463-0601-4907-8574-cbbcbe9cdf41
- true
- Pull Point
- Pull Point
-
9217
-8971
139
44
-
9279
-8949
- Point to search from
- 0e73b6dc-4f45-4736-bd0e-75ae29de8c32
- true
- Point
- Point
- false
- 9657b5c7-9576-49ed-a6d7-ae032aeec3e9
- 1
-
9219
-8969
48
20
-
9243
-8959
- 1
- Geometry that pulls
- b6589601-2a37-4656-b7c4-890bc1b15999
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9219
-8949
48
20
-
9243
-8939
- Point on [G] closest to [P]
- 3eca4bac-2695-407c-9f4e-de9f268b685e
- true
- Closest Point
- Closest Point
- false
- 0
-
9291
-8969
63
20
-
9322.5
-8959
- Distance between [P] and its projection onto [G]
- e7e57fe1-4371-40f7-8233-7868f5beca3c
- true
- Distance
- Distance
- false
- 0
-
9291
-8949
63
20
-
9322.5
-8939
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- b583d1cf-7a3f-4052-8904-153d81fdfdee
- true
- Pull Point
- Pull Point
-
9217
-8892
139
44
-
9279
-8870
- Point to search from
- 4fffb62b-fa07-4251-9e58-7a65bd99eb48
- true
- Point
- Point
- false
- 3d1c3c8e-ba45-4486-ad01-a0d1d102f456
- 1
-
9219
-8890
48
20
-
9243
-8880
- 1
- Geometry that pulls
- 15fcd9c7-22e4-4b03-bb4d-a4cb0e7ef473
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9219
-8870
48
20
-
9243
-8860
- Point on [G] closest to [P]
- 829d4ae8-b090-4cbd-84cb-f25ffc968842
- true
- Closest Point
- Closest Point
- false
- 0
-
9291
-8890
63
20
-
9322.5
-8880
- Distance between [P] and its projection onto [G]
- 590f8387-cbeb-4dcf-ab7c-2ee9a7c60ed0
- true
- Distance
- Distance
- false
- 0
-
9291
-8870
63
20
-
9322.5
-8860
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- 4ce1f53e-bf61-44f8-95a4-3bf2d4d1053a
- 745e50c0-24f0-4225-8841-a5b5f1afa79a
- b0c7518a-4219-4602-839c-235029b1a34d
- 4a12da5d-898e-4144-8e8d-1b907f89642d
- 4
- d9196d88-f6ed-4b14-bb1c-1f183f4a7723
- Group
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- 3697088f-7b9c-42f6-bd64-2174aa7f816c
- ca04f8b3-a611-47df-b7e3-410b2099d099
- 8ab55463-0601-4907-8574-cbbcbe9cdf41
- b583d1cf-7a3f-4052-8904-153d81fdfdee
- 4
- 772ea870-567a-4c8e-ad36-cc1a3d7ca545
- Group
- 11bbd48b-bb0a-4f1b-8167-fa297590390d
- End Points
- Extract the end points of a curve.
- true
- a4a57a95-519b-4236-a616-ec04d6438608
- true
- End Points
- End Points
-
9240
-12366
84
44
-
9284
-12344
- Curve to evaluate
- d142dd1e-e179-418f-b26a-0b0d1dae7ab5
- true
- Curve
- Curve
- false
- f0c191c1-9621-4bbc-8f42-70fddab36b4d
- 1
-
9242
-12364
30
40
-
9257
-12344
- Curve start point
- 126cde73-2db3-4894-9089-9c82ea8d9b3e
- true
- Start
- Start
- false
- 0
-
9296
-12364
26
20
-
9309
-12354
- Curve end point
- c886c9ca-e196-4a6e-86e8-e74a60881897
- true
- End
- End
- false
- 0
-
9296
-12344
26
20
-
9309
-12334
- 4c4e56eb-2f04-43f9-95a3-cc46a14f495a
- Line
- Create a line between two points.
- true
- 598915a3-e2fc-4bfb-b83f-aae6b06a75b4
- true
- Line
- Line
-
9231
-12589
102
44
-
9297
-12567
- Line start point
- 40d6e324-be45-4d56-b251-3dcff95ccada
- true
- Start Point
- Start Point
- false
- 608f6c3c-fd1f-4abb-ab11-9dbcb84297f7
- 1
-
9233
-12587
52
20
-
9259
-12577
- Line end point
- 1ba5e492-30bf-4985-b02c-c43e3b73f577
- true
- End Point
- End Point
- false
- e3ae76f8-04a9-4f7b-ba81-3036c248ecd0
- 1
-
9233
-12567
52
20
-
9259
-12557
- Line segment
- 21adf162-6466-48ed-b0e4-8aa61cab45ec
- true
- Line
- Line
- false
- 0
-
9309
-12587
22
40
-
9320
-12567
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- 09211b76-ab65-4e72-8300-b36fcf6d33fe
- true
- Pull Point
- Pull Point
-
9213
-12524
139
44
-
9275
-12502
- Point to search from
- ac3a9740-ea3a-4365-ac94-3d1adb5db8c6
- true
- Point
- Point
- false
- 126cde73-2db3-4894-9089-9c82ea8d9b3e
- 1
-
9215
-12522
48
20
-
9239
-12512
- 1
- Geometry that pulls
- 3893bd59-caa5-4dc9-88bd-a5638da7ea20
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9215
-12502
48
20
-
9239
-12492
- Point on [G] closest to [P]
- 608f6c3c-fd1f-4abb-ab11-9dbcb84297f7
- true
- Closest Point
- Closest Point
- false
- 0
-
9287
-12522
63
20
-
9318.5
-12512
- Distance between [P] and its projection onto [G]
- 55874175-aeed-4069-9e8c-1eaaf48001a2
- true
- Distance
- Distance
- false
- 0
-
9287
-12502
63
20
-
9318.5
-12492
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- ef4b781e-70ad-4c5e-a3b3-3c742b04b013
- true
- Pull Point
- Pull Point
-
9213
-12445
139
44
-
9275
-12423
- Point to search from
- cfba421d-b82d-401a-b22a-40856c2c259e
- true
- Point
- Point
- false
- c886c9ca-e196-4a6e-86e8-e74a60881897
- 1
-
9215
-12443
48
20
-
9239
-12433
- 1
- Geometry that pulls
- 087a1959-4b4b-453c-b2bc-a946e32d298d
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9215
-12423
48
20
-
9239
-12413
- Point on [G] closest to [P]
- e3ae76f8-04a9-4f7b-ba81-3036c248ecd0
- true
- Closest Point
- Closest Point
- false
- 0
-
9287
-12443
63
20
-
9318.5
-12433
- Distance between [P] and its projection onto [G]
- e47640d6-f942-4fb8-806e-736ae5daf030
- true
- Distance
- Distance
- false
- 0
-
9287
-12423
63
20
-
9318.5
-12413
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- a4a57a95-519b-4236-a616-ec04d6438608
- 598915a3-e2fc-4bfb-b83f-aae6b06a75b4
- 09211b76-ab65-4e72-8300-b36fcf6d33fe
- ef4b781e-70ad-4c5e-a3b3-3c742b04b013
- 4
- 84271252-bd7b-4112-8561-43533ed4300d
- Group
- 11bbd48b-bb0a-4f1b-8167-fa297590390d
- End Points
- Extract the end points of a curve.
- true
- fcdc1273-4010-457e-80e8-d6d2a5d24510
- true
- End Points
- End Points
-
9252
-15945
84
44
-
9296
-15923
- Curve to evaluate
- 596b6dfd-cafe-4d30-b26e-8cf2395a2f0f
- true
- Curve
- Curve
- false
- 0f214bdb-5cad-4d4f-8eee-7b8f3600bdca
- 1
-
9254
-15943
30
40
-
9269
-15923
- Curve start point
- ad6e4059-cf08-4266-9c07-b1a6d3da3632
- true
- Start
- Start
- false
- 0
-
9308
-15943
26
20
-
9321
-15933
- Curve end point
- 47fbfce5-2649-4fe6-84d2-5ca940b91239
- true
- End
- End
- false
- 0
-
9308
-15923
26
20
-
9321
-15913
- 4c4e56eb-2f04-43f9-95a3-cc46a14f495a
- Line
- Create a line between two points.
- true
- efcfa711-59f2-48c9-bcfb-c0892d3a75e4
- true
- Line
- Line
-
9243
-16168
102
44
-
9309
-16146
- Line start point
- d928da3a-7042-4685-be2a-1b49f40f181d
- true
- Start Point
- Start Point
- false
- 23d52e4e-bbda-4d7f-844c-64c4e07fdc3b
- 1
-
9245
-16166
52
20
-
9271
-16156
- Line end point
- 0699787b-b73a-496f-aeaa-4e621de61a86
- true
- End Point
- End Point
- false
- f476e52c-9f16-4cf9-9dc8-53464df41ada
- 1
-
9245
-16146
52
20
-
9271
-16136
- Line segment
- fa5104ec-99e6-4c5c-94e7-3b82a0aab230
- true
- Line
- Line
- false
- 0
-
9321
-16166
22
40
-
9332
-16146
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- 9961c67c-7b6b-4764-bdd1-a1e48583f369
- true
- Pull Point
- Pull Point
-
9225
-16103
139
44
-
9287
-16081
- Point to search from
- 10023702-d29c-4ed1-a06b-2e077fc9a36e
- true
- Point
- Point
- false
- ad6e4059-cf08-4266-9c07-b1a6d3da3632
- 1
-
9227
-16101
48
20
-
9251
-16091
- 1
- Geometry that pulls
- a5a19b7e-cc7b-472d-af7e-50bd165f0291
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9227
-16081
48
20
-
9251
-16071
- Point on [G] closest to [P]
- 23d52e4e-bbda-4d7f-844c-64c4e07fdc3b
- true
- Closest Point
- Closest Point
- false
- 0
-
9299
-16101
63
20
-
9330.5
-16091
- Distance between [P] and its projection onto [G]
- 340b9418-c6dc-4b6b-b0ff-952302865f58
- true
- Distance
- Distance
- false
- 0
-
9299
-16081
63
20
-
9330.5
-16071
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- 849936c1-69a8-4734-8c4b-cd2e6354bc19
- true
- Pull Point
- Pull Point
-
9225
-16024
139
44
-
9287
-16002
- Point to search from
- 7804dddf-f9e6-4021-aba2-4f4236e58c4d
- true
- Point
- Point
- false
- 47fbfce5-2649-4fe6-84d2-5ca940b91239
- 1
-
9227
-16022
48
20
-
9251
-16012
- 1
- Geometry that pulls
- 52da7787-182c-47ab-b503-dbddb37e317d
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9227
-16002
48
20
-
9251
-15992
- Point on [G] closest to [P]
- f476e52c-9f16-4cf9-9dc8-53464df41ada
- true
- Closest Point
- Closest Point
- false
- 0
-
9299
-16022
63
20
-
9330.5
-16012
- Distance between [P] and its projection onto [G]
- 351ed84f-f1d6-4fc1-b0a9-9295c12aa741
- true
- Distance
- Distance
- false
- 0
-
9299
-16002
63
20
-
9330.5
-15992
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- fcdc1273-4010-457e-80e8-d6d2a5d24510
- efcfa711-59f2-48c9-bcfb-c0892d3a75e4
- 9961c67c-7b6b-4764-bdd1-a1e48583f369
- 849936c1-69a8-4734-8c4b-cd2e6354bc19
- 4
- 20768bee-5b47-4218-ad74-075117bbc07d
- Group
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 22729d4a-b218-4fd7-989a-a31c84d0f10d
- true
- Stream Filter
- Stream Filter
-
9254
-19922
77
64
-
9293
-19890
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 8c435c18-1c44-4dc4-bfc6-2d79f98fdc94
- true
- Gate
- Gate
- false
- 802b0d79-1abc-4cd7-ba38-3ade85c28c58
- 1
-
9256
-19920
25
20
-
9268.5
-19910
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 4b62bba8-d476-48b3-901d-1d8c18192635
- true
- false
- Stream 0
- 0
- true
- b222f383-0934-4242-940d-878ab3058ed4
- 1
-
9256
-19900
25
20
-
9268.5
-19890
- 2
- Input stream at index 1
- c04c446d-807e-48cc-b595-607445751779
- true
- false
- Stream 1
- 1
- true
- 70dbeb6f-403d-4459-9312-a0aa407b68fe
- 1
-
9256
-19880
25
20
-
9268.5
-19870
- 2
- Filtered stream
- e2196bca-51e1-4e30-9af9-41a11d87bd51
- true
- false
- Stream
- S(0)
- false
- 0
-
9305
-19920
24
60
-
9317
-19890
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- db7d019a-d6ff-498f-b514-5ea0e3912544
- true
- Stream Filter
- Stream Filter
-
9221
-20457
77
64
-
9260
-20425
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 613da226-e593-4484-90ed-b34623433f20
- true
- Gate
- Gate
- false
- 802b0d79-1abc-4cd7-ba38-3ade85c28c58
- 1
-
9223
-20455
25
20
-
9235.5
-20445
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 24cf5d70-fc28-4a67-aa22-b6cd66137b41
- true
- false
- Stream 0
- 0
- true
- e4642eb7-9328-471f-b935-fefc6d0913b2
- 1
-
9223
-20435
25
20
-
9235.5
-20425
- 2
- Input stream at index 1
- 18e84f39-6a41-4c97-89b1-a57ebb0eea77
- true
- false
- Stream 1
- 1
- true
- c046a698-34b6-4f2a-8d95-ed65bd2086e5
- 1
-
9223
-20415
25
20
-
9235.5
-20405
- 2
- Filtered stream
- 37e45a94-23d7-420f-b036-38884c3e20f7
- true
- false
- Stream
- S(0)
- false
- 0
-
9272
-20455
24
60
-
9284
-20425
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- 160e178b-42c7-40d2-a1ec-81249c9df8bf
- true
- Pull Point
- Pull Point
-
9215
-20366
139
44
-
9277
-20344
- Point to search from
- 3300ce3f-1a44-48bd-978a-9d57fd4e6e33
- true
- Point
- Point
- false
- e4642eb7-9328-471f-b935-fefc6d0913b2
- 1
-
9217
-20364
48
20
-
9241
-20354
- 1
- Geometry that pulls
- e24d1cb7-7a82-41f9-bb3f-f181c46c8f0c
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9217
-20344
48
20
-
9241
-20334
- Point on [G] closest to [P]
- c046a698-34b6-4f2a-8d95-ed65bd2086e5
- true
- Closest Point
- Closest Point
- false
- 0
-
9289
-20364
63
20
-
9320.5
-20354
- Distance between [P] and its projection onto [G]
- 1c849118-22dd-418b-947c-ff3ddb1925e1
- true
- Distance
- Distance
- false
- 0
-
9289
-20344
63
20
-
9320.5
-20334
- 11bbd48b-bb0a-4f1b-8167-fa297590390d
- End Points
- Extract the end points of a curve.
- true
- 24f73fbe-7c1b-4353-afad-1e194fccfe9e
- true
- End Points
- End Points
-
9245
-19553
84
44
-
9289
-19531
- Curve to evaluate
- 5b6be24b-2758-4b27-9dd3-1ef676245627
- true
- Curve
- Curve
- false
- b222f383-0934-4242-940d-878ab3058ed4
- 1
-
9247
-19551
30
40
-
9262
-19531
- Curve start point
- 12fc18e8-0eb3-49e0-a61c-f9a180f96129
- true
- Start
- Start
- false
- 0
-
9301
-19551
26
20
-
9314
-19541
- Curve end point
- 322a5174-be44-4720-834f-ce33a53f5317
- true
- End
- End
- false
- 0
-
9301
-19531
26
20
-
9314
-19521
- 4c4e56eb-2f04-43f9-95a3-cc46a14f495a
- Line
- Create a line between two points.
- true
- e74a4531-a913-4207-a3ef-b18838106767
- true
- Line
- Line
-
9250
-19803
102
44
-
9316
-19781
- Line start point
- f951e113-ba16-4a17-a9f4-70cc3473f420
- true
- Start Point
- Start Point
- false
- 90645e4b-b95c-4f00-b0f8-9df3301174b9
- 1
-
9252
-19801
52
20
-
9278
-19791
- Line end point
- 657fa111-ec85-4e83-8d58-219a0f05d261
- true
- End Point
- End Point
- false
- adb6ba5c-3705-466e-a86f-e45769a74f16
- 1
-
9252
-19781
52
20
-
9278
-19771
- Line segment
- 70dbeb6f-403d-4459-9312-a0aa407b68fe
- true
- Line
- Line
- false
- 0
-
9328
-19801
22
40
-
9339
-19781
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- 7d6aab00-a74d-4d7c-896c-db710a806431
- true
- Pull Point
- Pull Point
-
9226
-19733
139
44
-
9288
-19711
- Point to search from
- df282230-8696-4d69-9f31-e4c75d98c27d
- true
- Point
- Point
- false
- 12fc18e8-0eb3-49e0-a61c-f9a180f96129
- 1
-
9228
-19731
48
20
-
9252
-19721
- 1
- Geometry that pulls
- 1600942f-2c56-442e-bcdf-d19926b2931e
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9228
-19711
48
20
-
9252
-19701
- Point on [G] closest to [P]
- 90645e4b-b95c-4f00-b0f8-9df3301174b9
- true
- Closest Point
- Closest Point
- false
- 0
-
9300
-19731
63
20
-
9331.5
-19721
- Distance between [P] and its projection onto [G]
- 68d15499-e10c-4cd6-8720-45fa711f5ebe
- true
- Distance
- Distance
- false
- 0
-
9300
-19711
63
20
-
9331.5
-19701
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- fa53342d-6132-4ee6-ae1f-5b8810239bf4
- true
- Pull Point
- Pull Point
-
9228
-19642
139
44
-
9290
-19620
- Point to search from
- 19f00c4a-114d-449c-ab4b-c4f5fabf036c
- true
- Point
- Point
- false
- 322a5174-be44-4720-834f-ce33a53f5317
- 1
-
9230
-19640
48
20
-
9254
-19630
- 1
- Geometry that pulls
- f79da562-35aa-490d-bb37-da7addcb9b3f
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9230
-19620
48
20
-
9254
-19610
- Point on [G] closest to [P]
- adb6ba5c-3705-466e-a86f-e45769a74f16
- true
- Closest Point
- Closest Point
- false
- 0
-
9302
-19640
63
20
-
9333.5
-19630
- Distance between [P] and its projection onto [G]
- c031ba09-9341-4a49-ba56-fc10dba672f2
- true
- Distance
- Distance
- false
- 0
-
9302
-19620
63
20
-
9333.5
-19610
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- 24f73fbe-7c1b-4353-afad-1e194fccfe9e
- e74a4531-a913-4207-a3ef-b18838106767
- 7d6aab00-a74d-4d7c-896c-db710a806431
- fa53342d-6132-4ee6-ae1f-5b8810239bf4
- 4
- ac64e75d-119f-4646-a091-52ab781d96c8
- Group
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- a2a12fdc-a10c-49ea-a720-42d451fd7849
- true
- Stream Filter
- Stream Filter
-
9261
-23368
77
64
-
9300
-23336
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 16540671-f5c3-4dd1-ad0c-ac9d7b999f04
- true
- Gate
- Gate
- false
- 802b0d79-1abc-4cd7-ba38-3ade85c28c58
- 1
-
9263
-23366
25
20
-
9275.5
-23356
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- d10d547d-7027-44d3-a3e8-e872073e8858
- true
- false
- Stream 0
- 0
- true
- 401ad277-e9e4-4f79-8da6-d199f80326f0
- 1
-
9263
-23346
25
20
-
9275.5
-23336
- 2
- Input stream at index 1
- 1f1f4ca7-5552-43a4-8c5c-0e8f3195d14b
- true
- false
- Stream 1
- 1
- true
- 6b2d15eb-786a-4e29-b115-79c493b34b7e
- 1
-
9263
-23326
25
20
-
9275.5
-23316
- 2
- Filtered stream
- 8c57285f-88ad-4e27-b2fe-21dfb8d0c116
- true
- false
- Stream
- S(0)
- false
- 0
-
9312
-23366
24
60
-
9324
-23336
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 950bc8b3-379a-4e82-8f16-299c99da4440
- true
- Stream Filter
- Stream Filter
-
9228
-23957
77
64
-
9267
-23925
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 96968d9c-b897-4ae9-b053-bec42f9ffd50
- true
- Gate
- Gate
- false
- 802b0d79-1abc-4cd7-ba38-3ade85c28c58
- 1
-
9230
-23955
25
20
-
9242.5
-23945
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 6909542d-0bfa-4ebf-a069-5edc7082b3c8
- true
- false
- Stream 0
- 0
- true
- b7c4cf28-434c-49cc-a026-b1e3b810d747
- 1
-
9230
-23935
25
20
-
9242.5
-23925
- 2
- Input stream at index 1
- 8bac3437-c56f-4736-ac60-457e51985cd9
- true
- false
- Stream 1
- 1
- true
- 7d2bec86-c155-449a-9b14-ae71252ef547
- 1
-
9230
-23915
25
20
-
9242.5
-23905
- 2
- Filtered stream
- bb1a355a-6f7f-4b8d-93f7-c629eab0cf46
- true
- false
- Stream
- S(0)
- false
- 0
-
9279
-23955
24
60
-
9291
-23925
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- c105f0d1-4e25-4771-9fbe-af4d0af47e02
- true
- Pull Point
- Pull Point
-
9222
-23866
139
44
-
9284
-23844
- Point to search from
- 4c3753c9-a621-4c2b-9e72-e8913618d3fd
- true
- Point
- Point
- false
- b7c4cf28-434c-49cc-a026-b1e3b810d747
- 1
-
9224
-23864
48
20
-
9248
-23854
- 1
- Geometry that pulls
- 099c64d2-359a-49be-877b-7d89ead7bb5f
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9224
-23844
48
20
-
9248
-23834
- Point on [G] closest to [P]
- 7d2bec86-c155-449a-9b14-ae71252ef547
- true
- Closest Point
- Closest Point
- false
- 0
-
9296
-23864
63
20
-
9327.5
-23854
- Distance between [P] and its projection onto [G]
- 591a4bc7-5055-48dc-83c8-500a6596d1a8
- true
- Distance
- Distance
- false
- 0
-
9296
-23844
63
20
-
9327.5
-23834
- 11bbd48b-bb0a-4f1b-8167-fa297590390d
- End Points
- Extract the end points of a curve.
- true
- 686e2d2d-d42a-4d0e-aed8-49dfb9e864a1
- true
- End Points
- End Points
-
9252
-22999
84
44
-
9296
-22977
- Curve to evaluate
- 5e51f792-f408-446f-907b-08f25ff1d208
- true
- Curve
- Curve
- false
- 401ad277-e9e4-4f79-8da6-d199f80326f0
- 1
-
9254
-22997
30
40
-
9269
-22977
- Curve start point
- f478f996-c502-4760-9e7b-7376bb2984b5
- true
- Start
- Start
- false
- 0
-
9308
-22997
26
20
-
9321
-22987
- Curve end point
- 63430855-8e22-489b-b429-7ba46024fbf4
- true
- End
- End
- false
- 0
-
9308
-22977
26
20
-
9321
-22967
- 4c4e56eb-2f04-43f9-95a3-cc46a14f495a
- Line
- Create a line between two points.
- true
- 9f9c8983-e06f-45f2-b028-00b48a4df33f
- true
- Line
- Line
-
9257
-23249
102
44
-
9323
-23227
- Line start point
- 1909a56d-98b4-4f6e-ada0-239af8da5224
- true
- Start Point
- Start Point
- false
- cd8785b9-1101-4044-8df4-c8f682f35708
- 1
-
9259
-23247
52
20
-
9285
-23237
- Line end point
- 024bb59e-b534-41d8-8dac-da2ed1ed48d2
- true
- End Point
- End Point
- false
- 719f0cac-c2d9-4cc7-8323-fea1913404c2
- 1
-
9259
-23227
52
20
-
9285
-23217
- Line segment
- 6b2d15eb-786a-4e29-b115-79c493b34b7e
- true
- Line
- Line
- false
- 0
-
9335
-23247
22
40
-
9346
-23227
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- cefafcd2-5a1f-4a1d-b499-f050365587e0
- true
- Pull Point
- Pull Point
-
9233
-23179
139
44
-
9295
-23157
- Point to search from
- b1b0f3d1-1f96-4a3e-b598-ad4c4ba6d677
- true
- Point
- Point
- false
- f478f996-c502-4760-9e7b-7376bb2984b5
- 1
-
9235
-23177
48
20
-
9259
-23167
- 1
- Geometry that pulls
- 3472d452-c5a8-4af9-9e57-842033d92c4a
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9235
-23157
48
20
-
9259
-23147
- Point on [G] closest to [P]
- cd8785b9-1101-4044-8df4-c8f682f35708
- true
- Closest Point
- Closest Point
- false
- 0
-
9307
-23177
63
20
-
9338.5
-23167
- Distance between [P] and its projection onto [G]
- d0418efe-9d2f-4140-b0a0-6665b510ad18
- true
- Distance
- Distance
- false
- 0
-
9307
-23157
63
20
-
9338.5
-23147
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- e2191903-1f01-4664-a19e-660b79cffb85
- true
- Pull Point
- Pull Point
-
9235
-23088
139
44
-
9297
-23066
- Point to search from
- c859b327-f96f-40b8-b105-2fc1bbe2eb9b
- true
- Point
- Point
- false
- 63430855-8e22-489b-b429-7ba46024fbf4
- 1
-
9237
-23086
48
20
-
9261
-23076
- 1
- Geometry that pulls
- 81e43296-a5f7-406a-b861-f77334fc2b9a
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9237
-23066
48
20
-
9261
-23056
- Point on [G] closest to [P]
- 719f0cac-c2d9-4cc7-8323-fea1913404c2
- true
- Closest Point
- Closest Point
- false
- 0
-
9309
-23086
63
20
-
9340.5
-23076
- Distance between [P] and its projection onto [G]
- 0a0205a7-4b56-4159-bf5d-5817ec1dfbb6
- true
- Distance
- Distance
- false
- 0
-
9309
-23066
63
20
-
9340.5
-23056
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 05b5844e-2d39-4d8c-8fc6-aba933fe2cdf
- true
- Stream Filter
- Stream Filter
-
9252
-26890
77
64
-
9291
-26858
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- a6ea476e-4929-43f8-bff2-318edbd3f6cf
- true
- Gate
- Gate
- false
- 802b0d79-1abc-4cd7-ba38-3ade85c28c58
- 1
-
9254
-26888
25
20
-
9266.5
-26878
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 865683a0-1af5-4472-a1a5-3837f9e5259b
- true
- false
- Stream 0
- 0
- true
- 9a49f9f1-63b1-4713-8686-8e16f1aa6c2b
- 1
-
9254
-26868
25
20
-
9266.5
-26858
- 2
- Input stream at index 1
- 39830d77-e0b2-42c4-bba3-de726f5a643b
- true
- false
- Stream 1
- 1
- true
- 6ca20d94-d8d9-442f-acb2-5009044f939e
- 1
-
9254
-26848
25
20
-
9266.5
-26838
- 2
- Filtered stream
- 04846c6f-286e-480c-9c95-cf2ed46d9350
- true
- false
- Stream
- S(0)
- false
- 0
-
9303
-26888
24
60
-
9315
-26858
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 6f1c9af9-729a-48db-aa0a-03345ee8b37a
- true
- Stream Filter
- Stream Filter
-
9252
-27409
77
64
-
9291
-27377
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 11c13f00-254d-4f21-85ff-63095ff8a336
- true
- Gate
- Gate
- false
- 802b0d79-1abc-4cd7-ba38-3ade85c28c58
- 1
-
9254
-27407
25
20
-
9266.5
-27397
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 1bf9cc42-2433-4a45-b426-0d5040be72e3
- true
- false
- Stream 0
- 0
- true
- b34dac8b-8d64-4e79-82bb-d85237582fc3
- 1
-
9254
-27387
25
20
-
9266.5
-27377
- 2
- Input stream at index 1
- 4b9ef8e6-736a-4b48-a1ce-e900ffef3f62
- true
- false
- Stream 1
- 1
- true
- 0170897e-17f0-4697-8902-62eec306f948
- 1
-
9254
-27367
25
20
-
9266.5
-27357
- 2
- Filtered stream
- 9e6fc360-1810-4da7-a170-2f0668ae3de2
- true
- false
- Stream
- S(0)
- false
- 0
-
9303
-27407
24
60
-
9315
-27377
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- 0ec36096-bea3-4a12-9729-2f5990a754ac
- true
- Pull Point
- Pull Point
-
9221
-27318
139
44
-
9283
-27296
- Point to search from
- be30d659-fb5e-4f47-9d99-ce85f7cebf13
- true
- Point
- Point
- false
- b34dac8b-8d64-4e79-82bb-d85237582fc3
- 1
-
9223
-27316
48
20
-
9247
-27306
- 1
- Geometry that pulls
- 7996147a-6704-4c36-b2db-50e411c5b809
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9223
-27296
48
20
-
9247
-27286
- Point on [G] closest to [P]
- 0170897e-17f0-4697-8902-62eec306f948
- true
- Closest Point
- Closest Point
- false
- 0
-
9295
-27316
63
20
-
9326.5
-27306
- Distance between [P] and its projection onto [G]
- de8be8d3-73d8-425a-a946-31739fec03e9
- true
- Distance
- Distance
- false
- 0
-
9295
-27296
63
20
-
9326.5
-27286
- 11bbd48b-bb0a-4f1b-8167-fa297590390d
- End Points
- Extract the end points of a curve.
- true
- 39d9776d-f76c-4f82-bce1-ae05c71a08cd
- true
- End Points
- End Points
-
9249
-26521
84
44
-
9293
-26499
- Curve to evaluate
- 2b4700db-1406-42ff-aa0c-ce5673a87970
- true
- Curve
- Curve
- false
- 9a49f9f1-63b1-4713-8686-8e16f1aa6c2b
- 1
-
9251
-26519
30
40
-
9266
-26499
- Curve start point
- 94a350bc-140b-421c-bbc4-dbecf9d24995
- true
- Start
- Start
- false
- 0
-
9305
-26519
26
20
-
9318
-26509
- Curve end point
- 431f4190-46e7-4bae-a59d-f8b048d6e94e
- true
- End
- End
- false
- 0
-
9305
-26499
26
20
-
9318
-26489
- 4c4e56eb-2f04-43f9-95a3-cc46a14f495a
- Line
- Create a line between two points.
- true
- ae24f77f-23d9-4cb6-84bd-e53fb80427de
- true
- Line
- Line
-
9240
-26771
102
44
-
9306
-26749
- Line start point
- 5b425db6-b031-410d-a08f-942dcefaa75e
- true
- Start Point
- Start Point
- false
- fd2b2675-0ad3-4ab8-9904-f69a6e4c20ca
- 1
-
9242
-26769
52
20
-
9268
-26759
- Line end point
- 6a96f43e-59c8-42ba-9a55-badc60c11f0e
- true
- End Point
- End Point
- false
- 168acd41-a9b7-4581-a4a4-fe7b47df39e5
- 1
-
9242
-26749
52
20
-
9268
-26739
- Line segment
- 6ca20d94-d8d9-442f-acb2-5009044f939e
- true
- Line
- Line
- false
- 0
-
9318
-26769
22
40
-
9329
-26749
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- cf106e66-67a2-4127-844d-20791dc209f1
- true
- Pull Point
- Pull Point
-
9221
-26701
139
44
-
9283
-26679
- Point to search from
- b3780019-53f1-4c4d-9103-00d1b3599506
- true
- Point
- Point
- false
- 94a350bc-140b-421c-bbc4-dbecf9d24995
- 1
-
9223
-26699
48
20
-
9247
-26689
- 1
- Geometry that pulls
- 70485353-9b85-4e09-957d-2c142f55e863
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9223
-26679
48
20
-
9247
-26669
- Point on [G] closest to [P]
- fd2b2675-0ad3-4ab8-9904-f69a6e4c20ca
- true
- Closest Point
- Closest Point
- false
- 0
-
9295
-26699
63
20
-
9326.5
-26689
- Distance between [P] and its projection onto [G]
- c218ffee-f5fa-4436-a3a7-4119da79bce9
- true
- Distance
- Distance
- false
- 0
-
9295
-26679
63
20
-
9326.5
-26669
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- aabab78d-e59f-4a58-9fec-eb1130dd5718
- true
- Pull Point
- Pull Point
-
9221
-26610
139
44
-
9283
-26588
- Point to search from
- ebd90529-688d-44a2-a7d9-5e296817480e
- true
- Point
- Point
- false
- 431f4190-46e7-4bae-a59d-f8b048d6e94e
- 1
-
9223
-26608
48
20
-
9247
-26598
- 1
- Geometry that pulls
- 9911dff6-d919-4269-a928-c3fccf079da3
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9223
-26588
48
20
-
9247
-26578
- Point on [G] closest to [P]
- 168acd41-a9b7-4581-a4a4-fe7b47df39e5
- true
- Closest Point
- Closest Point
- false
- 0
-
9295
-26608
63
20
-
9326.5
-26598
- Distance between [P] and its projection onto [G]
- 775a7539-c249-4436-a3b1-89387fb4bef0
- true
- Distance
- Distance
- false
- 0
-
9295
-26588
63
20
-
9326.5
-26578
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 04872530-3f20-4b2f-bfcb-1e4ced53d625
- true
- Stream Filter
- Stream Filter
-
9253
-30149
77
64
-
9292
-30117
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- c8c9d780-b51a-4ec1-8a6a-21663989f9e9
- true
- Gate
- Gate
- false
- 802b0d79-1abc-4cd7-ba38-3ade85c28c58
- 1
-
9255
-30147
25
20
-
9267.5
-30137
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 4d7197ec-0f33-4d57-90e4-cafa0f59d5ae
- true
- false
- Stream 0
- 0
- true
- 1c102dcf-a427-4f9a-93eb-d8fa6673d9fa
- 1
-
9255
-30127
25
20
-
9267.5
-30117
- 2
- Input stream at index 1
- 39a3cf2e-702f-41da-9ff5-eed5fb11f062
- true
- false
- Stream 1
- 1
- true
- 0c2f603a-6b91-459a-8d58-dd4d022bde90
- 1
-
9255
-30107
25
20
-
9267.5
-30097
- 2
- Filtered stream
- f3d6514f-fd53-494b-8f2b-098b6dfb4a80
- true
- false
- Stream
- S(0)
- false
- 0
-
9304
-30147
24
60
-
9316
-30117
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 4d5603f1-f731-4e75-a024-ce47a4061cb9
- true
- Stream Filter
- Stream Filter
-
9246
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77
64
-
9285
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- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- cc489051-35d3-4715-a85f-21a4eb5841da
- true
- Gate
- Gate
- false
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- 1
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9248
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25
20
-
9260.5
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- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- e0fbed4f-da0e-410a-b9ca-ed98673715f1
- true
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- Stream 0
- 0
- true
- f0dc78cf-7a27-4e9a-9ea4-ca79a5cff36e
- 1
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9248
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25
20
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9260.5
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- 2
- Input stream at index 1
- 15fd1cf3-6303-4107-b533-1f5d50e629e6
- true
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- Stream 1
- 1
- true
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- 1
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9248
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25
20
-
9260.5
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- 2
- Filtered stream
- 41cf09ce-b46e-4e22-a6db-894178c0dcee
- true
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- Stream
- S(0)
- false
- 0
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9297
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24
60
-
9309
-30627
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- 001727be-06f5-426f-8507-40e7ecd342bc
- true
- Pull Point
- Pull Point
-
9215
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139
44
-
9277
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- Point to search from
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- true
- Point
- Point
- false
- f0dc78cf-7a27-4e9a-9ea4-ca79a5cff36e
- 1
-
9217
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48
20
-
9241
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- 1
- Geometry that pulls
- ed8fea6d-cbc9-40d0-8746-f450fb8ddda9
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9217
-30546
48
20
-
9241
-30536
- Point on [G] closest to [P]
- 5614e1a4-f43f-4919-8c28-c1402f0f9349
- true
- Closest Point
- Closest Point
- false
- 0
-
9289
-30566
63
20
-
9320.5
-30556
- Distance between [P] and its projection onto [G]
- 9277286a-67e0-4309-89e3-bf08dc9ff38b
- true
- Distance
- Distance
- false
- 0
-
9289
-30546
63
20
-
9320.5
-30536
- 11bbd48b-bb0a-4f1b-8167-fa297590390d
- End Points
- Extract the end points of a curve.
- true
- bc56239c-7883-4555-ac8d-d09416fca409
- true
- End Points
- End Points
-
9255
-29815
84
44
-
9299
-29793
- Curve to evaluate
- f0cccf2e-a235-40bc-a9ea-c445d1403a70
- true
- Curve
- Curve
- false
- 1c102dcf-a427-4f9a-93eb-d8fa6673d9fa
- 1
-
9257
-29813
30
40
-
9272
-29793
- Curve start point
- 5340029a-6aea-4c69-a995-99563616299d
- true
- Start
- Start
- false
- 0
-
9311
-29813
26
20
-
9324
-29803
- Curve end point
- d13e35d7-8d6d-4f4b-8437-af04f2ffa2b6
- true
- End
- End
- false
- 0
-
9311
-29793
26
20
-
9324
-29783
- 4c4e56eb-2f04-43f9-95a3-cc46a14f495a
- Line
- Create a line between two points.
- true
- f3fcbb9f-8a7e-4255-af44-a20f3b96ce10
- true
- Line
- Line
-
9246
-30055
102
44
-
9312
-30033
- Line start point
- 660a7b3a-3083-4c73-b850-e4e3fffb762f
- true
- Start Point
- Start Point
- false
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- 1
-
9248
-30053
52
20
-
9274
-30043
- Line end point
- 45133f96-9cb1-486f-91f3-908a569604bf
- true
- End Point
- End Point
- false
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- 1
-
9248
-30033
52
20
-
9274
-30023
- Line segment
- 0c2f603a-6b91-459a-8d58-dd4d022bde90
- true
- Line
- Line
- false
- 0
-
9324
-30053
22
40
-
9335
-30033
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- 87eded33-ce93-4979-a534-f94d375e8e82
- true
- Pull Point
- Pull Point
-
9227
-29985
139
44
-
9289
-29963
- Point to search from
- 258e2c32-c148-4ede-ab5d-c348352d982b
- true
- Point
- Point
- false
- 5340029a-6aea-4c69-a995-99563616299d
- 1
-
9229
-29983
48
20
-
9253
-29973
- 1
- Geometry that pulls
- acf11bb4-950c-4168-81c8-722f4f1a154d
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9229
-29963
48
20
-
9253
-29953
- Point on [G] closest to [P]
- 8ee83929-d92f-483a-9837-e03ee7b9f456
- true
- Closest Point
- Closest Point
- false
- 0
-
9301
-29983
63
20
-
9332.5
-29973
- Distance between [P] and its projection onto [G]
- 1f134c35-2893-42d4-ad8f-1a9c8f21e108
- true
- Distance
- Distance
- false
- 0
-
9301
-29963
63
20
-
9332.5
-29953
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- dac4915d-e17d-4c6d-b68a-449fa14067af
- true
- Pull Point
- Pull Point
-
9227
-29894
139
44
-
9289
-29872
- Point to search from
- 26f301ad-24a9-4f5e-a893-32f3de1d5c6d
- true
- Point
- Point
- false
- d13e35d7-8d6d-4f4b-8437-af04f2ffa2b6
- 1
-
9229
-29892
48
20
-
9253
-29882
- 1
- Geometry that pulls
- 8f7cf039-c2c4-4a45-af0d-e8f95889222b
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9229
-29872
48
20
-
9253
-29862
- Point on [G] closest to [P]
- 097de905-06d0-4aea-936b-314a41c047e9
- true
- Closest Point
- Closest Point
- false
- 0
-
9301
-29892
63
20
-
9332.5
-29882
- Distance between [P] and its projection onto [G]
- c28f4633-b7dd-479f-a71e-82a32547aea0
- true
- Distance
- Distance
- false
- 0
-
9301
-29872
63
20
-
9332.5
-29862
- 448de216-3a12-43cf-a135-e3bfafc87744
- CURWE CURWATURE COMB LINES SCALE
- CURWE CURWATURE COMB LINES SCALE
- CURWE CURWATURE COMB LINES SCALE
- CURWE CURWATURE COMB LINES SCALE
- CURWE CURWATURE COMB LINES SCALE
- bfc5f4ab-3919-4abb-8151-d9a52a9477f3
- true
- CURWE CURWATURE COMB LINES SCALE
- CURWE CURWATURE COMB LINES SCALE
- false
- 0
-
9176
-4724
232
24
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 67705803-aa62-4c69-892f-e4ea4635854a
- Relay
- false
- 0b9f480b-88da-4856-9c83-6d1d5314a585
- 1
-
7635
-3971
40
16
-
7655
-3963
- dc6f76a5-ffd3-4a50-b42b-fcb46a544902
- c6c19589-ab63-4b60-8d7c-2c1b6d60fac7
- True Only Button
- When clicked, the button object only raises recomputation one time.
- False
- True
- 7e76fc74-ba9c-4acb-a67e-289d00443890
- true
- True Only Button
- false
- 0
- neutral,N
-
9494
-1742
66
22
- afb96615-c59a-45c9-9cac-e27acb1c7ca0
- Explode
- Explode a curve into smaller segments.
- true
- 27d5227d-aea4-40b9-9b52-ccdb41c7a034
- true
- Explode
- Explode
-
9954
-1792
134
44
-
10025
-1770
- Curve to explode
- 3ec42eaf-d4bb-48e0-bb83-62ef2d94e876
- true
- Curve
- Curve
- false
- 17eab43d-f378-464e-94b9-16c6b57b57c3
- 1
-
9956
-1790
57
20
-
9984.5
-1780
- Recursive decomposition until all segments are atomic
- 882fd16e-61d1-49b9-a981-48e435d8a579
- true
- Recursive
- Recursive
- false
- 0
-
9956
-1770
57
20
-
9984.5
-1760
- 1
- 1
- {0}
- true
- 1
- Exploded segments that make up the base curve
- 6c67a789-2cb1-47dc-a134-7325a73e6d33
- true
- Segments
- Segments
- false
- 0
-
10037
-1790
49
20
-
10061.5
-1780
- 1
- Vertices of the exploded segments
- bd851341-95b6-403a-b02f-1a061b4e4b4f
- true
- Vertices
- Vertices
- false
- 0
-
10037
-1770
49
20
-
10061.5
-1760
- d5967b9f-e8ee-436b-a8ad-29fdcecf32d5
- Curve
- Contains a collection of generic curves
- true
- d9dd41ea-65dd-49f2-9ef2-87054b73f6a6
- true
- Curve
- Curve
- false
- f1cb17b7-ee0e-49ec-95f6-e24ed89eb56e
- 1
-
9797
-1944
50
24
-
9822.633
-1932
- 1
- 4
- {0;0;1;0;0}
- -1
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
- 00000000-0000-0000-0000-000000000000
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
- 00000000-0000-0000-0000-000000000000
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
- 00000000-0000-0000-0000-000000000000
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ZNx5OJTtGzdwW0pUyJpdQvZ9Z85ZaJNQadFiTyglqSghUVHRor2IFElEWpSrlMiSfWeGdlt7FKr3nuvndT3H+/bH0/P7NI2Z+77u8/x+j+M5fjy8PDw8/6hf3N+5v0T4qH+scvXfvDWYGbxlS/BWHWU335Adm4O32prrGRrrGRkam1hQ/2JgYKijzNwZFLozxNd2q+/O0BDPIB1l551eQZu9l/juWREc6LvV1tTUyMjC0NfS3Nvc1NTU2GAK96fI4jfXW+AbvMU3NGSPntPOEK8dzJ0hYb4C1J9ODfvfT5vuGeLtvznM19hni1DwNt+tW7mvEvDxDPXkvmjatGl83A8qqsHDY0T9fnJcWESIn/qXWdx/CEXz8PCN7ufj+RP1vy819o+PR2LiC8qK3d7gItwkhv7yiB7gVf2yeM4e6XHqz8smXivKP/FC7qfhF+D5f359of2/MuHo/5Up/9/fJb/2uUckup3OpP3v9yLa5dh1fTxfnkz87xe0dUbn9XOsqie8jjbzy8DDm6WNtEj85y20Ty+mb+D1b6etx6/rolVfms+7agZn4vU9NDcrNVe3Na8n/t4b2otrBXN5dd5N/P33NDMx5s+bfz/QhvD79NGu7W144VbfP/FzB2kSHz3P8mYMTbzvZ1pp1i8TN+svE+//hRa+8cmlmxlfJ37ON5qR5CFB3pnfJ37ed1p/5bJgt10/Jn7uT9rVKOm2mz0/J37+MG2tGQd4F49MfI4RmvhgZpZbwa+J7/WbVpm2VTxHfpSWiT/XKC1mlVkEb9wYbQP+fOM0qxl/37h9HqdJ4c/5h/attMwxZ/Vf2iv8ef/Rsncfvctb+o/2DH9uHjA8o3X85mkeuII/Pw/MCDnGdFvMCxH4e/BCn+O3EZ5/vLAKfx8+KNNwy7lZwAfG+HvxQxrfQw83f36Yhb8fP+zrVpDkVRCAAfw9BWDN/eiXN+sFoBx/3ylgevLdPre4KZCOv/cUENu6yIjXWhD24+8vCEMLb72/+VkQ3PF1mAov54pdcMuYCub4ekyFa39Dl/GumQaz8XWZBtHtbfw5M4TgM74+QrC+0Oa+W6kQVOHrNB0sj6cG8e6aDtfx9ZoOkgECKjnawnAAXzdh+Mryb3brEYaN+PqJQI1S9WHe0yJgja+jCGSN6tvlLJoB0vh6zoCDzSe/uf2dAd/xdZ0JnnkjmbwFM6EWX99ZYJvg7p6zaRbcxNd5FogUcOK1Z4rC/663KISnir2O8heduO6i8PEo06alVHTi+ouCW8TOFG0FsYn7IAbP/a9/idolNnE/xMDIrX1xS73YxH0Rg1Sm8DVtHfGJ+yMOMw1t/0XFiU/cJ3HYqxi8pqVHfOJ+zYZ+4bQCbevZE/dtNqz+3TAj+vTsifs3G168F/Bv+Tx74j5KgEmTWan2YomJ+ykBV5/6y0dnSEzcVwkQvX0+rOWvxMT9lYTIi9V12mskJ+6zJAwe/qsVXSA5cb8lYe0ug4MtM6Qm7rsUVPh4cbT9pSbuvxSYuZ6yjC6VmjgHUpBBe3GyRV564jxIg7juryHtXdIT50IaouZoLYyul544H9Lwaeq6qy3aMhPnRAbW/Tw6rh0nM3FeZKDyNXKL7pGZODeyYFH3Na/FSnbi/MhC5uO5wjqnZSfOkSxI3FzpG/1ZduI8zYGYs/GoZdGciXM1B74cfCCrkzFn4nzNgQ07BnZE/50zcc7koNpD4VXLarmJ8yYHVk7LNHUK5CbOnRzcsI6OiZ4hP3H+5EFqfkFXyyb5iXMoD7FS78x0SuUnzqM8fOOXTo6WV5g4lwrg8XXhQEuYwsT5VIBX7HB7nXqFiXOqADbVOVeitRUnzqsiZD9g/245qDhxbhVB5rroCp0exYnzqwRxpxi50VZKE+dYCX5Eh05rPaU0cZ6VwCs400vns9LEuVYGf70g9hM15YnzrQxK8w4mDLgoQwQ+58rQInfZQmq/8sR5V4ZE8XvvIEcZPuBzrwwMoboTge3K8L/5qQy//32kpQiqwEr8HKhA3jDv0BNjFRDBz4MK+A/NOT/goQLP8HOhAopvjRdIHVOB/81dFWjpcPwBxSoTz4kKHKv3TQv8qDLxvKiAfUWkU4qkKqTh50YV/pScGXvCUIU1+PlRhcK7eTcGglVBFD9HqhCU83Kl1CVVKMfPkyqopr/mo1eqwj78XKlC27mx24EjqmCCn6+5cDxJYn2K2tyJ52wuOMTrTn/qMnfieZsL4/sc7g1Ezp147uZCYehGH6mcuRPP31wICNwtRm+fC2X4OZwLyl7JJYGCahCBn0c1aFmdHZhirAaG+LlUg8Rlz2SeeqjBB/x8qgHDoats4KgaXMbPqRr8tvkZIlWsBivx86oGecYzlekf1UAEP7dqsElLoyZQch48w8/vPFCkLmUKYx6E4+d4HjRLr9F4GjwPDPHzPA8SZ4Y0DVycBx/xcz0PmFMSoqUq58EV/HzPg9GxdD36yDxww8+5OuR/e9QZqKYOM/Dzrg7+fc2HUlzU4Tl+7tVBueeT6dNIdYjAz786tLZMfTNwUx2M8BxQh2M1yklS7erQj+eBOtg/t7SlC2pAGp4LGvDnoWt/oLEGrMbzQQMK8gPPpHhowEw8JzQg4EYs6+lRDXiB54UGqF659HXgoQZE4rmhAe2niy5LfdQAEzw/NCApsXYJXVITBvEc0YSFBz7+CmRoQjqeJ5rwbw9vZkqwJqzFc0UT7m6bs/zpRU0QxfNFE4I2GfMMvtSEcjxnNEF1g+MtqRFN2IfnzXxoX+G7lq42H0zx3JkPyUsipwa5zIdBPH/mwwLGmcKUyPmQjufQfPhnkef59OZ8WIvn0Xy4q/9y5mDbfBDFc2k+BKq/LpYS1IJyPJ+0YK7CmD/dWAsi8ZzSgo7ZElJBHlpgiueVFiRN132WclQLBvDc0oIFvA7bnj7Ugqt4fmnBn5ENCoMftGA1nmNaUPhpV6WUpDaI4nmmDUHvknbRGdpQgeeaNqh1ZakFBWtDFJ5v2tDVUFqfclEbLPCc04aTLzsjn77Uhk943mnDoic/tAeHtSEDzz0d4Lk3o11KTQf+l6904P4t9Ti6iw5I4DmoA8EZNOOgSB2owvNQBzQurO5JuakDMXgu6gA7efvRp206YInnow6cPnTEanCKLnzBc1IXHPenf5Ay1oUbeF7qAn/Yo1N0D13YiOemLhQHNdODjupOzE9dCPH+9CnloS7U4DmqC5prp158+kEXDuB5qgscZ+VFgxJ6YIXnqh6cXmA5LMXQg694vuqBo51rOj1YD27gOasHAqaBzkEX9cADz1s9KNaO/ZPyUg+k8NzVgxDVS9lPh/WgBs9ffdCULVo1OFcfDuA5rA+cWbUC0i76YI3nsT6kCH7Mp0fqwzc8l/XB6Q/PxqCb+pCF57M+TPkhK3KmTR888JzWhw07z3X18BlMzGsDePhlnnGYrMHE3DYAqaA7h4UNDOA5nt8GEPLBrifVwQCU8Rw3gFdeVWZm6w1gL57nBqDFXnW0aocBtOG5bgBxa96+8ThiACZ4vhvA66ZtVsOpBpCE57wB2Dn/SUq4ZwCDeN4bwPmqwx+UXxnAQjz3DWDYQcqu6K0BZOD5bwCupVdPLRkzAB6ePmoPGEKurf5Aj5ghrMP7wBCmPyimh2kawn28FwzBz2ThWWGaIUjg/WAIpbebPqWuNIRteE8YgqK2p71ZkCFU431hCOGZQxeqYgxBE+8NQ2hRCf/mcc4QYvH+MASjS4KLhm8bQg/eI4ZwTObklYQXhmCD94kh9J9UGlbuNoSzeK8YgsOsHMei74bwA+8XQ7h6xCJ9yXQjcMZ7xgj+Tin73aNsBDl43xjB2mgX5zBzI5iGuHvHCIrGuzOFnYzAB+8fIxDfHfAn1ccInuA9ZARbvw8vN4swAnm8j4ygcuuB7KpkI9iN95IRqPfP4vW8YQRNeD8ZQYzvxVXDJUZggPeUEbB7NHMTmo0gEe8rI7Bad1dAZdAIPuK9ZQQprXT3Ij5jYOH9ZQzfXF/lL5E1hlS8x4zB6dXaab36xjCO95kxZC/6sCHMwRhW471mDIJlO+4KrzeGQrzfjMELeETSdhiDaCR3zxlDSXGil9kRYwjC+84Y5pjLPqhKNYYKvPeMIezOtVme94xBDe8/Y2jQNfIbrjGGKLwHjUEvq+RRwltj6ML70BiOqC2ZrTJmDBZ4L5rA+yutm4vETOAU3o8mwJDzebJE0wS+4D1pApdTvkj12pmAI96XJjAqtm9L2EoTuIH3pgm4HRV6LhxkAgJV3P1pAnempcxJizEBD7xHTWBmrOp2s3Mm8AjvUxMI+JdbXnXbBGRsuXvVBF6EWyt6vjCBULxfTUB1uDx0uMsE6vCeNYHI7SuqEr6bgA7etybQMdijojLdFA7hvWsKZv5bdhcpm8JbvH9N4cSb36+WmJsC4D1sCp82xM3rXWoKF/E+NoXFHeJ7w3xM4Rfey6aQufJKg3CEKazA+9kU+Oq156clm0Ie3tOmsMHx/n6zG6YgcoS7r03hYTmrparEFPzx3jYFKWa9jmezKTzH+9sUQkrWHxgeMAXlce4eN4VXlv3tCXxmsBfvczPQuhtmoCJrBm14r5tBnAF/fJG+GZjg/W4Gr28e717iYAZJeM+bgZ2GvEnvOjMYxPveDM5fvXEkbIcZLMR73wyGFUx7hY+YQQbe/2bgeu6peVqqGfC0cnOAGeRKOB0zu2cG63AeMIPpSR1vq2rM4D7OBWbgJ7zJ2vOtGUgs4uYDMyiN+548PGoG23BOMAdFvqiPCWLmUI3zgjmE7xOhqWiag2YxNzeYQ8uvs6eL7MwhFucHczAKnTe4ZKU59OAcYQ7HPuczegPNwQbnCXPoD7A7FxZjDmdxrjAHh/eVn4XPmcMPnC/M4arnKoe02+bgjHOGOfztenPR7IU55OC8YQ5rV2/7XtVlDtNSuLnDHIoaxxd5fjcHH5w/zEF82eHUYSELeIJziAVsrZQcSVC2APlp3DxiAZX2V5eqmFvAbpxLLED9qV5G0VILaML5xAJibIpHl/hYgEE4N6dYAPveApfecAtIxHnFAqyMm66HJVvAR5xbLCAl1+Ov8A0LYOH8YgHf5g+tSCuxgFScYyzA6dqem2bNFjCO84wFZCsL8lUPWMBqnGssQPDiidWefJZQiPONJXhJK90elrEE0ZXcnGMJJSduTknUt4QgnHcsYc5Mi3UqDpZQgXOPJYQdfn6naJ0lqJVz848lNAi4CDnusIQonIMsQS+qe2PvYUvownnIEo6MbS4KS7UEC0tuLrKE92HDIiL3LOEUzkeWwPgW451WYwlfcE6yhMtbZj00e2sJjjgvWcLoxwui1aOWcAPnJitw89Hc5ClmBQJXufnJCu5wCh8Pa1iBB85RVjDTnS6RaGcFj3CesoKAlpoAlZVWICPBzVVW8MJl7dOiQCsIxfnKClRr3ks7xlhBHc5ZVhC5cMfW3rNWoBPHzVtW0PHs3/Ow21ZwCOcuKzCjJcqJvLCCtzh/WcGJhzIhaV1WAL+4OcwKPpleqzD7bgUXcR6zgsX5hkrVQtbwC+cya8jUKdnpqWwNK3A+swa+G4urh82sIQ/nNGvYMLdVNXGpNYh4cvOaNTy87L1Hxcca/HFuswapOV9qi8Kt4TnOb9YQcnqvumOyNSg3cnOcNbwSFdrXe90a9uI8Zw1aiacbw0qsoQ3nOmuIm6qqJdJsDSb23HxnDa9jcqPSBqwhCec8a7D7a9VqxmcDgzjv2cD5PeW61TI2sBDnPhsY/rE81lPfBjJw/rMB1209HcP2NsCTy82BNpA7EGSYuM4G1uE8aAPTN/2OV9lhA/dxLrQBv9cH2UWHbUBCmZsPbaB0vbipY6oNbMM50QYU2y8n9BbZQDXOizYQvkL7dViNDWie4OZGG2ipvWch8tYGYnF+tAGjJazjaaM20INzpC0ce1H3zkzMFmwEuHnSFvrp622qNWzhLM6VtuDwuO+Ep50t/MD50hauWoT1Da+wBWecM23hbwEfJAbaQg7Om7awVv94ikqMLUzbws2dtlCULTdUdNYWfHD+tAVx9RtMx9u28ATnUFvYmmZyvrfMFuQ53DxqC5XyT7+EddnCbpxLbUH97NIFIt9toQnnU1uImd1xKU3IDgxcuDnVDtjH/H6YKdtBIs6rdmA1/fviajM7+Ihzqx2kHNyf5rnUDljPuPnVDr7xiPwa9raDVJxj7cBp71mnxHA7GMd51g6yR9SuqSTbwWqca+1AcEf+WNF1OyjE+dYOvD7ZujqW2IGoDjfn2kHJ5sobvU12EITzrh3Meef2L2zADipw7rWDMI83K0X4aKB2mZt/adDQGZyTJkODKJyDaaC3apzPXJ8GXTgP0+BIw6E11fY0sBDl5mIavF8qmee5jgancD6mAeNlmuBICA2+4JxMg8ssvfWJh2ngGMPNyzQYRQ8LVFJpcAPnZhq4WS+Yfq+IBgJ7uPmZBneKGj0ca2jggXM0DWYaedzrfUODRzhP0yDg1uCMXaM0SMS5GsD7lI1R3DQAK5yvAcQaYrrrZgN8xDkbAM16eUhOCSAF522ALUtnmfhpAbBw7gaQS1jJyaPW/TecvwFeVlw4MgYAqTiHA+wSfG3q4AjghPM4wDyWZm/SKoBxnMsBGqO3JnZ6AWTjfA4QjQrN1bcCrMY5HUD/z+jrbXsABOW5eR2g24p+rDgWoBDndoCE3fGWgkkAXji/A1gW1bx1vgAg2szN8QAfvs9OupAJUILzPMBpw7XW7/MBgnCuB2AGp743eAww5xg33wN8zXmfHFEBUIFzPsCVfh3bF40AYTjvAyzV3PFRlAOgtoCb+wHGfB+cdO8HaMD5HyAr/Z9d5k+AKNwDAFb12vd/4aGDHu4DdJiilHjaWoQOXbgX0KFgXQPESdPhCO4HdPA8LzNYp0oHC9wT6DCrbcMZOT06vMd9gQ6PJa8x/CzpcAr3BjoELh8YymPRgYH7Ax1kkw3PjS2jwxfcI+hQ/moXy8GdDpdxn6DDTpGSz0l+dHDEvYIOcxcLXOjcTodR3C/oUB+/2EF9Hx1u4J5Bh/1lSV+3HaKDG+4bdNDlb71YfJIOAqrc3kGHTlBYKHiFDndw/6DD4Ujv787ZdPDAPYQO5o+yLl+4S4eZndw+Qod3vz8vev+EDo9wL6HDSXOznwbVdAjA/YQO9J17UyNa6SBzittT6PD5TumSF6/p8AL3FTpc+jJtRPQTHUJxb6HDEr1lV91/00F1Kbe/0OF34OmlmQIMqMM9hgHXszp/fZnFgEjcZxiw8oNKhrUcA3QEub2GAfzz/JfFqTOgA/cbBuR75Y7WGTLgEO45DNiY+uOanC0DzHDfYcAMtpWL30IGvMW9hwHFctHjecsZcAL3HwZsXlN+fWwDAwD3IAZIn5mx3CGAAZ9wH2JAWdPyv0k7GXAR9yIG7BA/n9UZxYDFuB8xQMW5Z4V6IgN+4Z7EgNqj6jzbzzAgE/clBuyrCrpZfJUBK3BvYoC2UIGbYC4D+DS5/YkB7Q6/eV0eMCAP9ygGxMfSbl14zoANuE8xwLT04Or3tQwQ6eX2Kga8+VfFb9jJgIe4XzEg2Vb8dsR7BvjjnsUAWsTqtS++MkDqPLdvMWDo/uUpYn8Y8Bz3LiZcGH6b5z6NCSG4fzFhkYn2uszZTFBezu1hTBjZvn3qV0UmvMJ9jAnXbt+7Y63FhL24lzFh+dCf9XGmTNAS4fYzJvBqs4TqgQltuKcx4bb/kUI5RybE4b7GhPWZdRv9VjHBBPc2Jgi/lRLO92LCa9zfmPBAZX3R2BYmJOEex4RNG9M9HfYwwQ73OSZIXuoTSY5lwiDudUx41qF/v/M4E87jfseE7TJh3uoXmLAQ9zwmKLk9mrk9kwnDuO8xoeYk38PifCZk4N7HhIj6hb6Cj5ngivsfE+bPOi7qUsEEHj1uD2RCq2Nz8YVGJuTiPsiEg0fkNr1nM2Ed7oVMMK7wFDfsZ8L0D9x+yITeKTceR/xkwn3cE5lwnPnJ/wUPC/xwX2SBbbSJhJgICyRSub2RBQMl4chdmgWluD+y4Nz4k4BMVRZswz2SBQuspkp91WWB4hpun2TBz11Ln1pbsqAa90oWpN89GRTHYkE47pcscPneLl2/jAWa4tyeyYJ/BsrP5NxZ0IL7JgtubfXb6ufHgljcO1ngnpMjm7+dBUa4f7JAqP/b87G9LOjBPZQF9zQstzkcYsEx3EdZ4Ou7Xy75JAtscC9lwez0shedl1nQj/spC572CIeoZ7PgLO6pLAhWdFXYfpcFDrivskBh3dmK4ics+IF7KwuqzrF3CFaz4CruryzY06qm5NLKAmfcY1mgIRlYeeE1C/7iPsuCZtf8ne+HWJCDey0LDiSNKBv+ZsFa3G9ZYPjKtjpCwB6mDXF7rj1whGN3vZhlD0W479rD0UWVqmJy9uCDe689WMeLvnJXtwfxTG7/tYe+5257Mg3t4QnuwfZwhu+S2lcbe9iK+7A92MObWuuF9iC/kduL7eH7vvkRccvtoRL3Y3tIKw5Wr99gD7txT7aHZb/v1ssF2IO6DLcv28Mfs/G9fjvtoQn3Znu4GcrQzI+yhxjcn+1hzZ1DjWMJ9mCAe7Q9TP3yKtLhjD2wcZ+2h7u6klrJV+0hEfdqe/AOdG/uvGUPVrhf24NYVlqU+gN7+Ih7tj2g9x+0tz+3hxTct+1hi5pea3GtPbBw77YHOa/QGMFOe/iG+7c9vLzyUNflvT2k4h5uD7u6edovfLUHJ9zH7WGe3ILY9+P2MI57uQM0rj6qbzjNAbJxP3eA6JTGjojZDrAa93QH0G+SjXuh6ACC37l93QG6xTwMxbQcoBD3dgdIWJbZ5W7qAF64vzuA5dHB+ExwANEcbo93gA+VRsZflzhACe7zDnB62h629SoHCMK93gGYDuhwnJcDzPHl9nsH+Hpgimn9FgeowD3fAa48XdIjt8cBwnDfd4Cl/5IT/GIdQE2R2/sdYMymzSz/uAM04P7////O/e8MTnS5/vv3j/P//XcEAvxBf7ke6O0ZZ73daPLPay7WjXJd+UzyovasJZOuGfD3M3aTY5S7T7qR4jMO11fraIx4IZ9J/3hfsZLrqYcPUK8PnHRHK7HbXDc5MVSjsXj7pK+7ev4Yfp8wKep9Qidd6utDf66P91krXzbZPel+6iG2XO/xXU+9f8SkSzKeiHCd5RUeIqG0f9KPMK+1/KVcQucl9XOjJz1ovsoFrr/Y6OpVJnBg0vu/GK/l+tlDbcNeKHbSc051z+Z6pZd7Ak943KQbCytW/KH8YnaH0mWTQ5N+mPUzjOtO8m6F1p8PT7qChrcy15VDaxa2ZyVMekrCpufjlH/bAt1hPkcnPcqcz5vrai9yt0soHZ/0xBaj8THK5eRF+NuDkibd69uv41xXAzvq+yZP+t2PyxW53p2z5UyYxolJ381hXB/lXgfaec8ygZPk+t97rsV1WsszbYnXxCNHW2/8pnz30v6fXujUpLOrw1W4rhIz40n+xdOTPtCUfeoX5eHOukd4wlMmvWieLx/XmacWrVi26sykt6llBoxQnqjppXjZ5Oyk82/dXDNM+ekPYR8Hxc5Nek9BlhbXj2XH37H+TNz+skfMT8rjF53ae6T6/KRnXItr+sG9/hcuOrRnXZj0rgFxFa4vCk0V1Yy/OOks8bFN3yk3vnGlI8zn0qRPn2Gc9Y1736eezyijX570ju85b79Sftfj+FYJpSuT3ly7eg7X2ZH7LbzHidf4qS3+QvmYhClve1DqpLfwj+34zH1+T2r4RXUSn2tbduYT5Stkpas0FqdNusM9/7tDlG8+yG9Qe594zbvy6kHKy/IHT4VpXJ10/5dPuwe4521nw2+FFOJnbxp+7Kd8+FrhhjKB9EmXaPs00Ed5p9jJZ0E7iE9dUf3xI+WbDm7RlHhN3ObkWfYH7n0sZx4tds6Y9AhthZr3lNedk/zmhYibxSkWvqP88b3XbtP1rk16WpL7ybeUr2nJLs6/SDwq4GjAG8rt0rcorxHOnPTHszdZvqZ8+nOtgzzhxPlkT//roXxjc2/f9Y/Et9EeP+JQLhJwwmnZquvkedeP3MamfNp0m4LhMuL+ysFzuilfaciWvmxyg3yvKKWHnZS/dNq91z6d+INUqWUd3PteKtQ7KJY16WfWN7a1UT7anWx/Kop4YUWVWyvlGpxZ2dafiS9rCKpoplz7W8zMN+uzJ73km6xuE+UVuv0hR6qJtzbqxDZQHpvMajW0vjnpHqM/qusoT+NPtm7PIh4dfE+wlnJfp1dXomRyJl0vINeghvKHCmP8mvHEz/yatriKcsFxSf/an8TPZvW7vKR87jKF6jCfW5Oubha4oJxyzopZBoqNxEu0UuaXUa6j1H+yjJ5LPn9SwEgp5ZpJN0eC8oivO9tx+wl3Dqx0cZdQuj3p+vQqlxLKxd+2lRQfJd4qINFVzL3+22mq3uPEF0dFLn1A+aVfTxgHTfMmXUbxRUYR9/McdPrRFkT89ZMzPQWUux55cU0ng/j2rcn/8ij/OFVjVVQn8eAxOk8u5X9rtkxrEs+f9F/3NHuzuedk99kHGouJWyvcTb1OuX5QRkBENHG7vQ62GZTPqD0mV3ufuECu9t1UygXiVlSrfiGuW3ZV8BLlUnrf9oZp3Jn0tU/b9M9R/kjKR7dyA3F3Vp/eacozrTO7FVKIBy5i8yZTrmBXeHR7DfHT7NuZiZSXrz9sWyZQMOkBPUy5Q5TP2648JGNDXPn+lvUHKI/q3nExaAdxS/lPAZHc63ls35In2cSLG0Poeyg3GDQbnf2auMzeFPYOys0bz97YJFtIXu/SQ9vKnRuHLrgVOxNnjT3z8qf8Qp6ZwKxDxI+uSmN5Ud5C98z3Qv95vdPz1+6U7w0X21A0THxVuo/VSsqlG22mT9e7O+m8NdcWOlFu+bX17npf4ueqU6YvoPzkuRaP/IvEZ0w32kej3CxNW3hKE3Epo/WXzLk5p7uicLVw0aQrSfdt0qc8QurK+hwG8cZTye3qlPd+uTSFJ5z4urA/nxQod+wtyFmeT9xwY0mGBOWK0q9cr38kHlzkPDKde/43t42MKt2b9BOn5N7wUH6F+fiC0yripwu2+Qz/pfb4MV+7q8eIq3sm7hqgfPDCfc7PMuKDIadleii3nnVx/6I/xLNtLjGbKF9c9l3hksn9SZ916MqPcspritMefgkkLn4sRqOY8uMjB1ey0omnfpVqu0V55ubIT2c6iMcVS/OlUp7V6HdwQOwBOeertNKSuZ8zW2YObRFxWjI7L4by66MBOSeiiDufytXZQbmUvZHN+3vEb/f9neVNuac3vLT8TLx3l6KbK+VJPj7Lj6o/nPT9MQ6jQPmywICOnvXElbPPj+hRHnNEboPJaeLLBzUXyXO/V6otO76a+MP0vr5plEsanVzbyV9Mzskh1PTjD/WcMjob9KyJX8zdJdBDeZJWvUNMCHF0+OWOSsr3hugUNWcRv9XnplBIuU16qvL8XuLO4zfHLlIeL999cK/Mo0k/uJQmdJDyD+8T39UuI76ofDsEUS5x0I02N574p/xjF1wpr37WeSKshPiqwioJC8r9Dz3gvPxJXKdpYaY85c2X4ucp6D4m+yhMdDEP5Vui2ry3+RBP2CA9+nqc2kealuefXSDukW+T95zyN3UGFVKNxIO+L/K7Rvm7UhjaPL2E5Drh75IHKV8r/XbaYzrxLHrLfW/K1+07Pkd0D/FC+70L6ZSHjeepeOcRX6q7ukSB8l93bysUfSDetqd89u8xDsrOGJghpIRInpcXZzRS3rv28Vd3N+IOewMYOZQboJ0VuUeJF+4dmhFL+aby9cm8ZcSF469eWku5olHRkhXjxKNORfTrU+5yxT2iUfYJmVdWK4f4KS8wrKjYa0r8+IPhyy2jHLSHt3CGugvx9yLiv65TfvH4rUW1QcRX/2V+3UX5vYN2e3cfIm5uLXHAgXLbYwMZKhnEfYJ+XptN+S9tk2eViHiLs70r5zcH3U860bKjk/ibDseoLMrdd0Sw5UeI6zuDZgjl89+t7ygTfzrpW4NoDEvKA9XTX27VI14Vt/LF31/UeQvPvSm9mLjWwz05pZTnjXbtf+JLXEz0+GAs5Y83H7TfHE3cP9cn0p5ywSm/xsQuER+YWrRGgPJ1bpFXH94nvnmWdtjTEQ4qFXC38G4i/mDL6qq9lOdlvHwk/IV4+EPkbEZ5ffxfvULhUnLO79X+GRrmoDmJ6sfWaRA3P/72ZTrlx/r92gWYxPkkF+asonzrlO5ZtzYQlxYyuihE+RfTywYrw4lrb6hIevCTmv/n7ln9OU38QbRS9CbKbTi6utfyiR/KtPKZTfnC2X8El9YQp4mJGD7+wUGGQTLlPz4Sf++3k+1DuY5UQNBFgWfkPv5Z4D2d8uy/DT+ZysRX69gX3fpOnbcrWl4D1sR3XFV85US5b6Vd3olVxEfuhaUNfaPmakgj23IH8cCyHvUjlPPsvjrYc4z4rz29K9QoR9vd2+KziT8z+qzy6Ct1fnalp+q9IP7RNSTWhfKAAQlWcy/x/gtlIW+/cFA0i/Y04g/xxDizN6GUb2rNlFKVfT7pfRemVPNRbpX6nFFhQvzxK7+5xz5T50RYkLXVmfi7pmiOFOWNT6plJIKIf4oKGb74iXquN29FD+KJP5NbtEGZ8pQIE7ON6cQjS6bPSBviIB/+dRECiDgtJ/+XIuX2gZJHszqIm+XoSp8fpHKCfexmp2Hit7x9NohTriqFZn4XKyN5Nc/wefwAB8nL1Yaf0SWuwOdvN9rPQTLSeTetFxGPKaor3Ux58BznKxwf4vIhOgta+qg8s/T48gNRxPMijJ/SKE9/QHuhfpH4HakU9cyPHJQhOe/ny3vE33SPBwlRrn/sR3dQI3GOgtCRzR+o5zp5ReSsz8T36K/c8eI9ByVf6GrMn/6C5K76UEVlyiX/SXQtVyc+JfZnVNg7qn8VhJ36SSduzt6Q9PItB5mqBI6mrCfO22/EkKU8YWCJsMUe4pw9nxJ833DQ6idez9tOET+1X8g79zWVB+b2qe7JI+7hOfLoey91f22nqclWE3+wVOO4KeW/r7c9v/+B+KGjArU7eqhcZOPFt5q/nMz/puHtuRwOanpzoX1Ykbh+kteWd2wOqvUKXHDaivgx46wiGcqnaV9baOxGfFnMfObCbg7ymi/SUbed+JY22rTQLg4qOu3ya8tR4sPBDmMXOql5VSqROj2LuHnGabEnHVSPGHpdk/mceKhRLPS0U711hnkko4e48O5N+8bbqLl0fc+t7jHi03NPPpag/PdZntW7pSsm3VJ13bBmKwepfJoZLm5M/NCW2QqWLRykfLtpVo4T8fHrwhr2zRzkdGerpH3Af/xcitDSJg76EfQ+rvsgcYmBKQ+dGznI7rmhx8404oZON3WdGzjIg210SeQxcdrNtjVL6qk++/2eZXob8SUOPcaMOmo+KEUYWv4gLvJWIt+kljpvBqpRr2a9nHT+wZcvVF9x0PBeOxVvbeKyh5YHiNRQPzfXUXTEgfjAU8Hkr1UcdC6lcOERL+K1lywNGio56O7fijL5SOJ5xkzb3JfUvt5VHpN7jvhIWcStgxUcxNBpC6fdJR7ZYhO2upyDQnNnZNXWEf9m2Zuo/oLaL5U+0zYOEj86v+z95+dUTnB7fnJoaiU5n8sd9hQ+46DZPH/sI+YSv9b/zDK0lHq+lF/KTqMRryy4rKD/lDrP8dVCp9YSl5CwnPMOUefW5ZSoUhhxG4URtZQSDtqRm6KZlUycc87OmPGYg+SKjRyNbhH3lN1l1VdM9f1FeTsfVhBPHBMySHhIzf+7tCv0t8SV9noJaT7goPbbv0vL/xF3KRkqRvc4SFac0+EoV0X2WtscW9ciDlqZ09ZTZ0b8MmdtDKeQmhuS914tdyV+4bty9KYCqidGGF1u3kL86+LXev35HNQa0r/Q7TBxOZpU9KY8al+U+1Y0ZxAfX222hZNL9eIl4lIrnhAPW1/y0eUWB/3JZmnXdxK3XavTV3KT6nfmFrxLR4g33uHxUc+m9njxzORy8epJf6hb4nToBgf5OdY1gh7xBt7+y28zqT0rHVh6fxHxn2+EF1tfo3K4acFKfV/iFRK59onpVL4K94rLiCJevnV9fGsalUMWyCyVuUg8LzRLQCGVg26vXXP1yD3iDA+1gnWXOWjj1eORYw3EYwy9D6Vc5KAnItM7Aj4RP1nyZ0/leQ6qXDue0yZUM+nOz4/t+3WWgz59jfzMmke8ZKTgkPIZDtqfe+zcbSCeIjMzmXGag84UiaTLrCM+LkBP3HCSg9SWlvBH7SJ+7tX34NBk6nm/5ljw7gRx2/o6w9jjHER7wMpalEvcrupg+dGjHOQ8R7r75kvihSPP1JMTqO9VJe0g8o74PS2wP3aYgwakIjsDeF5NevvnOzIH4znogLfPqXI54sPZbSk7D1L5TbRik6o58Yji7Xc3HqCup+NhxwhX4nZXGQHMaOp8fg+wbNhCXFRL4qbyfmovbxafp3GY+J8TBVtG9lJ5addUwfAM4huffLteHk7NE93ChkpE/OnmG8uSd1PX7alPtGwn8dNOeWtXhFFzafuCaX7DxB8EDZSIhlJze3PQ+jyx2knvsISQF9s5iJ1dFvZLh/g5zvmAncFUv/6svthuIfFj4UOXFLZQufqMfU20N3HhdQZ8KICaVyn3f5ZGEs9x8jq6xp/6nOt/3ec9T/xB9yHTIV8O6nu1QcTuLnGrK3lf9nhzUJyBxrtddcQbo4YK/3lQfUdpq8XtAeKO0u67IzdwUM6zs3+289dNOvoibzjsTuWEZZpiwmLEmX0bmv3WUD3oq339VUXiijEr3evcOKjmMMPCUoe4vrXdA6MVHDT10kZ4ZUn81KeN7466cJDmyto3nguIL9ATbul1onLLwUL5HyuIn08/H63nSP3cPNV3sV7EnbftYO9YxEFCIormEtuIWydPeZPvQOWEhAsiV/cRn8+oPviRSc3tD1Eb9RKIc7ycHkvTOUj0Rsb8B2eJK3QrRtHsOGiD4SsfRiZxd+Hu5xutqR5Xd3d6ZcF/Xq9sGrPbgoOqywUknZ8Sf3a0J/ewKQet8l65r+kV8ZNbM+knjah9NMXYdlUX8SlD7oan9TnI3GqOU1sfceGct6HHdThIumZ31qoR4uv0jflj5nPQ7s5bC5sF6skcYy5qDFKnet+g0DwXceJ1fhZdy+Zy0E7BWvMqJeJx+qqS2srUfq8yCGfqEne/a7HzrzyV05JWvHtgRVztV8n3l7IcJLzHJURvIXGvBUKHjkpRezDFYE7aSuIbs/bNXzSbg07xDTWLeROXZJyqHZ/FQQX8oZejthFnP2jdfkOEOufzrwUN7fvP509/N9VRiIMW73C1XJ1AvO/N1sMfplDzJBj+PDlLvF7C4lM4H9UXfNTzNTKJrxqS1RP8x0ayYblLEwuIb7vGSz88xkYhNTurPj0h/mLtV0WBX2zkXSoyd9kr4qdCeZ6E/WCjdMERx1udxJsF18n3fmGj5/U36UJ9xI+ZLNBhDrFR5cyU317DxHmS5T5e7GOjn0cktjzkbyDzdv+ihZ/esdGjeeGnZokR1zq52t78NRvJ8c3091Ik/rLvQ+suNhs13BfuuaNNfN3h3F+3O9joY0L6Dx5L4qH3I1I5LWw0+8LoJUcH4qUrzSsEG9lIRla76fRy4pa6r/3n1bKRcgzreJcH8YrFKRHWVWzU3LCkXHkr8ZjF8b8XlrORyhPrUK8I4jMz+bqWPmOjzs8Cx9IOEV/zL1h+MaLex/CYCPs08RX+LoW2xWyU9qDwg3Q68UfXmZc077FR8WpH6WV5xNvD/9ZNL2AjswdKJw88Jm7WtGLR21w2aj37xfVuJXFraVOeu9lstFFgt9PbVuIFzlmf92aykc9Jv32i74gzglrFbK6ykXWGT6vlN+LP/Hg9v11iI5Oz4is8/hE/uO9g65VzbPRrltDAAZHGSU9Yyw5mnWYjRc32kxmyxC/bpqv1JLFR6V0Rh1J14p6qh76EJLIRHFD/3WVMfMGb9a/G49moLfFqxg8gfmCN+IN9B9jIw3aYJuREfGxP3s2fkWzEyU4qneNOnB7skeYTzkYijR1z5/sTL8zbdLpyJxvdbjV3N9lJ/KXU/AMa29nou9UUD5sY4mWDan4RQWwUI3dhPv048fp/vyxfbGKj6G2OtxkXib+46TE61ZuNjtpv+ghZxLPfmaTDBjYKGjapti4irsUKMti2ho0GA0ZdjJ8RVxOUu5yygo2CXX9t06gjvlt6x8eCZWyUuzFQWaabOEviuXDFYur6xCaumtJP/PbiCIFGe+p50Ume8XmY+K7iubVNwEbme29aNvM3kfkm6+dfY81G1+KnN94TJX61fFrNIzM2Ej3ZUZeiQPxE6+ffVw3ZaP5Se60QLeKhUxQG9+tQ51M4pGWROfGSwtupyzXYaJZQXLUCi3jewFsJRVU2KrmSwf/J+T/v4yTtwJFno2mHP4c8XE/8uiwyPCPNRj2y8WIHAojvlg9pthdno6KoIy0LdhE3u/NGb0CEjVL5ZR5MiyXuX/zWOn4qGx23W5pXlkTcO8V7VJaPjb56LiiIvER8g3SQf/p4N/LaPveBcTZx4SiN2Lkj3ag25u/9t0XEr4V1LTn/tRsl/fmZlfyMeMz4p8dTB7vR53aNA1Z1xBV9etoC33ejsp471pwu4hcdll140dONFg4UVe7vI35n9wi/TGc3Epm7UkN+mPjY33wxj+ZuNIeRt7CQr5nkQ96dzy7XdiP1xsF5C2cR/1OyXKbpZTe6v92wqFWOOH9k5Cye590oavr1L16axB9HMm6olnQjltye6j4T4r79Qq+t73ejoW/NEEQn3vHU/dGSO91I9usnVv9S4jWVnWauOd3Ip+xXrfda4syIxS7LMrsR5Gq3t/kR3/0mVpiZ2o007j1btWgH8a7Tsb6657uRxTAP8+5+4jOPbtw481Q3Gq/QOCGfSPzprIW/3x3tRmtEo232nyW+4USicWF8N9oUuNayO4O4ecqZmXuiu9Hq7YJRZvnE18Z9PmIS0Y2G+7qmJjwm/iDZLOt9aDcaFbCu6HhJvCpGK+D41m704fiB+/NaiIecynil59+NQrWU6gJfE6exzrU+9+xGG/fsFbz1ifioikyci3s3ur5KdHnfKPH4i0s6m1Z0o9mCbreUp7ZMukz17jYnp24ktqZWZPls4lWW/yLRgm505a3A5igl4pczVtep07vRSfW4Bze0ib99JvMq1qobvc3t+1llTlx26tCeduNuNGZfI9nPJL5k+cVmNd1upCfWIsrvTPzrY8E3furdiO9uHltqHXEf+3kZV5So52Wn2K55/sSH4oTkamW6UeKKwnq9UOJhId2LfopR1013/XujKOIzx18biQt3I9fa1hzDROI6VTva5gl0o+0Sv+S1zxIX+Mhja/CnC/WNnNNTyiDe7ifubTjchUZvpLXPyCN+VWzB0vmfu9CSi2OSI8XEp4qu+Cv9sQtJXrjY2VFOfPSowJ4/PV1oYV206oPG/7ze0/JJe3sXKmzMe53MIX4y52NLTkMXohWYS/gOEDc4qPAkrKoLuY3q3DYaIa53ciTS/HkX2n7v9s1RvtZJv1KYLfX5UReaGfWB9/FM4u8vRx65dLcLNYUIZO+ZQ3xm1KtuRm4XWmpBu2igTlwwdZoEJ7MLTeFrr+s1JF7Pm2sQcqUL0Q/JwVFb4p8EXM3Hz3QhD8E1r40WER8SPK+9L6kLvTQdvN2wgviaKbZiPw9R12GBRVqQB/ExGv+gd3QXOtp9I5cniHh8Zxl6uacLmfHcqTu2i/jd2K1J6iHUfZSs+yd1gHjd7BHP8IAuJNoab3LuGHFksNmizKsLZdH9NkmeJx4x0i091b0L3UrgSU64Rnz2pX0CsJy6nhI/ssbyiM+V3M+3bUkXuub6Ptv3EfGGexpSZ5hdqPxFbOLLcuLuHyuZd6270JO3sQs0GolLPXp5vNK4CwnyZTRFsomrXD3xt0W7C3nBdZ26PuKnhdNOdcztQrm73BfK/SQeIrHPrVmOen/F08oePG0kH+oWLyyf3YVEjA1yLwsTDyobC84T7kILlET7W6SINw331yXxdyHXNKWaaarE/xnCNv+xTvQl19nZRJd42cBjV/PvnUhq7cWgNRbE1RwN9/3p70SbC/nkdjOJJ7C3/3j4uhM53DmyIsmJ+EOm5+Pgjk7kN4MhfnUNcYd3/V1yDZ0INGyX3vIhznuTfzV62YmcBlL+5gcTd7qTZbz2aScyzt+mlBdO/MjUt6GD9zuRidK3G9cPEr/mWaoclteJkMiiU2eTiM/oWWczcr0TbfPN6oi5QPxHZWN18JVOlC6ydKdfJnFpt2WtnJROtP/pjvXM/P98Tr9/HguOdaJ6fu9E2UfE36ySC8482ImKfvuOfXxB/GdVr+CfvZ1orltNen498d0hZ3WXhHaiRfA5ckcXcZvOhI9JgZ1IyUYjTu8D8UcLZtm+8upEjbNb7rz++p/rvH+vAf9a6jqXev49Pk7c/YZxhb5LJ/LeaOplNrWdPC8KF4RWLOxEZcJPW5vFiAssUxoNpnUioZ49q7fKE79/0ejKAbNOdLKzvfufOvG7lkv/HtPtRC7NGz2PGBK3nzkkf0KtEz3Ycrxrhg3xzEuneY7KUd+L7+vCIw7E64Zqc/eLU/clTSz1nzPxtdu1dAOEOtEyvgOdW9yJH/1uEe3I04kSwjt/NPkSD407lac+0oHGRu6+M9lGvDSk88mvoQ50ejT/+tFw4qfm598rfduBWo7vMOHEEn9oXnI+trMDOS5LPzj/OPFEq7xgu4YORF/96VTQOeJSLZY2Xyo6kI+z4Lob6cT9c8QFz6MO5Oad1tR1i/iflSMN1kUdSJMZ/kvoPnFR96wbzTkdKHC+81P9UuLXdT8nbkrvQILt7zWdqom7qp06+PVcB9qXKjjft4W4z07/szuSOtCjdXuLQ3uIHzOiVw3FdSCFvbIde/uJV7F+zfXY14FqeAsj9/0gvt8/6Ebljg60+LB6ethf4jnzozfoBnQgnsXOdP9pHZO+sEfR8ZBHB5oqJ7ncVZx4co7Rrk63DtQQtr7BRJ64347cd+pLO9BgpNSDWerEMzoOXQpgdqCyf4a8b/SJ77R/nJFp2YGcQjMzci2JZ9ct4e2kXvdEKPhSCJP4lGWWD6ZS7+uSnvBObynxBPvjDTrU52ju5tn1xo147Qf35Yupzx01u21JkgdxfYk7dA/qe+7fqLTBNIC4lnNW+lbqulxK67vesIP4mefr9++kriNvjNNc/33Ehyy/dIRS1/1xaEDlzzjiKRJxj4Ko+3Tk8YYzEUnE7V0Waa2n7mvCDpfY3+eIR0T7azlQ58Do4JaE4HTimhVSzzSoc+P66HVmdw7xCy0Jo7zUOUsofVfHLCJe2sff2kSdy/F5efxXEfGWcrQhlTrH1zZEWf6qIH66ROCsD3XuLZrOBTk0EFe5Kn9YhXpO3rxlnUns/M99r15p0Uo9V+2Drwoq3xJfq8ifc5B6Dv86HXnE84n49X8R/TrUc1sR+eqm3gjxIi/50WrqOfcU/hWxgnru/68zy1m9vtRc8M7x1wgRIj6ftjZzhJojMs7xN+LF//P60BfLYqi5E6X95PcpOeLnbo+8mULNKd/qWMnzasR7ej02x1BzTU3XcThFl/imW3vej1Bz8E3liZQEM+Iu20s8/ai5+fBxx5ddNOJL3fJ6a6g5a9Z485/7QuKH1jUH6VFz2eLmycfmLsQlA+8LHaLmuHDrvHnCa4nHefSVdFBzX2hszKDFi3iL2p8T6tSeOPjtbufZQOLxj44mBlJ7xXr4t9LyUOIf11ndyaL2kH5Z6C+BfcSjo69P76X21py69o25B4kn8u2/KEbtOdamN87Ljv3HdbZttab2otCA64sPKcRr2/TjN1B7tPzvl4e7rhD/ELd7KJzauyklR+f/u0581q7pN5KoPe08wjMjMo+4U9nNx1eovR7sqeXx4z7xFQc1TW9QOUCX/VXB6ylxQY6rZDaVGxzuLaCXvyQepM3ve43KGbK9amVzG4iriMton6dyyahdQsauDuKfMsO2HqJyTG/fwY7S18RPxE8320blnp+753tNGSAe+7vskAuVk1wdT5nRvhM/OfXqFh0qV61u/+S6bYw47crlAR4qh/X8Crxzlspl/9fzbpUK1VK5jdd8kfN9YeKGNvK1KVTOm6FWq1E7m/h4whPGaioXGl53MemWI+5uWB04m8qRb1wMtr+eS7xd19ulgsqdaYUt7Wxt4leE8kfDqJy6s/DR5gZj4g8HPm5VonLt2l4/+cfWxJfn2999SuVgWo3f0GUm8Zf805vXU7n5t7d7264lxHO3RDV/p3J2IPNr24LlxHduHXt8gMrlNyXe9M90Jy5xtPn0DCrHL3v3W6jGi/jSzdt9kqncnxA9wygmgPjrKkvDWVRPuPdKYKNeyH/e/24afzzVK0C9JbF+D/GFQWpvfgW2Iqv8+HuB0cTzD9m3+lC9Zflz/c7xQ8Q9eJI/VFI9Z5nNz++xScQDDS7IaVO9qLNj1l/+s8Ql3/NEHKR61HB6xc89V4h7+22a0UH1rjTr8Nb3mcQ3hO7t0KR62ggz+criXOLybsN926led644cfG1u8Q3tp1k3qV64IJ1f5uGHxF/6yz/+RvVG+//PmJNe07c6srGH1pUz2T19IdHVhGX0zFzX0/10kLj/uOFDcQ1P0RpH6F67NGlm3f1thOXYs7fkk/1Xi259XpTeokLGKhoNlI9WSKiNl/pI3ENCW+fz1SvfnqO89fgM/G40q/zBakevmhpqbjlMPFXwW1R0lRvl9lW2m/+5z+f/5rW9rlUz99oRY/VpXr///XVhgL8WoktiPd8UZesMPFWqcN22lEtaObh/K/jYsTn7nmnrRHagpZ7tT1pkSHeE7e0UcG/BYmY9C24rkTcxOuPzax1LahY9GHsVnXiPwQtt48ta0GR6y136ugSP6fnuPs1swWFKW6V7jUmLmp0ZO1z8xaUB7s3J1oR39W3VDlNuwUV9CZt1qMTLzn8u363UgvKODVdqnwB8QVRw7uWzG5BbRkuW9yciMc53p0jO5X6vm6DW7pWEL+56lZp72gzGlSJkFrjTnx/5brd1z41I6nv932rPYmv8lzI8nndjOLWR6w18ye+yG5MT7GlGXk23fmespX46QeC9MaX1Pt0Bxh8CiUeb8B34MDjZvSEVjnLJoJ4dMORP3r5zUjQdHZyVDTxnCDmg+aMZiSanF5QHE9cxKSpZNfZZjR18EfY0FHilsf6pSQTm1Fl+cUOyVPEq9osKm/tb0aMAke2yXnix/XDeuk7mpFQYEP04lTiKYYbfOv9mtH7Eekyt0ziK8ryNqxb24xaKufeWJNDvLbTsOX10mak0CqjvfwOcQnjrCYfejMyzTZzYt4nPiT92uu1STOaGdMuplVCXEHj5mF3zWbk4RkeNvU58VkzW1zq5JrRVdXbeztfErdeYv4cZjWjPYe15mXW/ud8frrWl8PXjDpcH23b1Ez8/KqxSonhJqTIcvFQ6iTe9Ut8++6+JsRn+f1HTQ/xKRKVb1u7mlCzwUv9He+JH4n4p2dc14Q4a6XFZw0SN3I9ufrIsyY0qkK7lPaVuGSVX0B3URMqNkcNWiP/uW597lt0sptQ/2Xjwuxx4mzGyoBdl5pQwN2VTBU+9qTrPDINKElqQk9tx6OPTSXevLRnJ29sE/q1SS7kmwhxrWfmKbCrCf1pfy65VJw4J0KxKSKgCV2+pxF8WZp4rG6YRcH6JvQpKynqvTxxi2tK1e+dm5D2+82O81SJnzs8ekaK1YS0TKyb12oQ/yv/LoNh3oSYP7IU4nWID/4rHgvQakJlans0sw2Jd31fc+24QhN65Xf41zMz4ozLZ7LzRJvQfb72pCZr4k+XLJF4xd+EXg8c+NEJxCsKFg58GG5E5c+eqXfYEzd/5GHxt68ReXd91qpdTHy1raeAWHcjqrDcJ1C8jPhAmcRq5bpGlHrib9GlFcTXb2TY6DxrRLnL1Bx2rSE+w/XWA5OiRsR75NHdBRuIX+qTaLfMol4/tUBoljfxBZYm6dYXG5GAuZhDzab/XOeep8pWxxuRoObfrTFBxJ/XBK81jWlEXw+UHNLbTvz6lIHVujsbUUFM4Zn6ncQlfTrVVP0bkQF7Y2pgOPFCzzcvZrs3IsVn66+PRxKPab2ygM+pEa1F/vmxB4gfLr1+ewga0bFbq5/xHyIeNjVxaotxI5p3WfX1nkTiKmatq4rVG5HF4zbxD0n/ue+OM7IuyVKf0zR77ZLTxGX33uTfJ9KIVom9Kck8R1ypT2Pbmn8NqF5ykPX7EvFv278OG31rQAcuL/7GuErcb1twqtC7BnR9R2r1gUziOft4d3a3NqC3l262F2cTZ5v+25tb2YBUzR2UBnKJt43de7L3cQPSs/BLFysgrvc4ZOHCvAZky1QI0r9HPK5oi7xYegPyDTy7n1X8n+9lwWa1nm5Awr+V3joj4o8Cvrw8f6gBzdWWTl3xjLiaZHmBe0QDCv059mBZOfHHnhHT52xtQK3FfhaMKuJfM+Rbmj0a0Mbp01V1aonzquUpHl/egKoX39k3o5H4zi6DQXuHBjRll73r+xbiro7HHUYtGtCHitLMog7iQ1b5pjnaDejKJkZMJJt4Xsz2p+6KDeig+M8B29fE8zuvfJ0m1oDuv5w78OMdcevrPK8K+BtQdqh+fHof8U2PHDesG65Hb+OSyhcNES83Nczm66tH5VdbCj58+c+5gmUPMjvr0XTrG8v3/SC+vd/65MJX9SjPqDR3+q//nJ+R/bSPT+rR3YiR6uNjxPfmnik7WFCP+gsNikT+EY+/801HJbMe5bwIDInmI///CppN3/c+PFuPJPcXC32aQvxm35dHLgn1yFt3QayrEPGnmUY/3u+rR+M2i/tzRYg/2/ljfvi2evSndjaLX5T4IVcfX2HveuSxRvD8stnED2devXV+JfU5zc78OClFPFi9VEhzYT26v9hpXZ0scan88qgCq3p06VRZu4AC8R79bFlb3XpkUnVjp6Ey8ZDdrp3PlepR9Y9CC7e5xGv0L1QvFq9HP//d096hTrw01/nHK4F6JLQuadWh+cSLPhiscRmpQ97JOmWndYiXLx3gbeirQ4HtR/Zd0Cdu8lj5p3NXHTpWdP/wOSPicr7elq9e1aGRhIZvx02JH7lj1rzoaR1abcpfGmlBvN5mVu2zgjp06PIBHj9r4roFrro2mXVokfv5e/Z2xO9UrRq+c7YOmdEufFGgEz9v7GegmVCHxn++L/zEJF4VVdR7YV8dGr3QP+O+A/FGtRDRmdvq0P5VSlPCFxGX9SwojfSqQ+++CWX8n/bu/J3K/H/geJtJodCMIkshJSFLU8pUGGQpKpGlI6IFJUvWkqaEirKWkp1Qtuzry3Jsh3OoJCWVLSprWZrCfH3qMvfrmj/he72fv52H4z73Ofd9v+/zg+tFUZdyd2WfmUGDZrBz3T7Wt49yVY/uelPNZnCu1/knZD/lnsFFG+uUmiFPvZu1zYDywId9EgqbmsHwaKZdqyHltLBt9EjhZtBQt+uyM0bvq9qWnY2nGXI9XipNmVLudWjz37YLm8HRp+r8FRrl/fN1t8V/agLbmzM5bBbofNhbNGjb3ATB3CcGLh6jnD08TUg+twnEPDo3fbGm3E1uybPxiCbw6jH2Nj9J+QdW0Kp8ryYIh6oRug3lG70Hv5471gRSV/n9xE5TLlkb7yW/pwluOJnpe9qj8y1RKGdgUxNYKYcebHSgfFtGYnwCTxMsZ7Du8TlTni540shkggVtX0UUTFwoj+9yfMnVzoJvh2PFbrtRLlSfqwDAgoufHVyZHpTf8llw9kwCC95y5G2bPo+uo1bOO6v9WXDiS7iDxEXKU2JscmtOs+Bug+omrUuU5y4LfWJ/gAUaJgOO1pcp35zVPc63lQU2rxh6nj6Ui8WGS5X87+90n/Azr/lS7hzf6Gk+jwUne1aNh/hT/m2v3/C8XiYE5HE8Db9O+QXpjJsx9UyIqlA6ExJAuejgEuud6UzYtXXomf9NyvO9/nR7FcyE1V2uXB5BlE+oDT1xdmXCtSWS66xCKG/Z5uHBZcYERyOjdXvCKNcQ3uWRsJsJz8B0lcRtypcmub5UWscEJZtg9pk7lNdFqcYwlzDheqTJvOa7aB1bE99qPtQIdg/4lkZGUp5U7H1l5GkjhDyT2mwZRfmC+AdZF/MbwVt/wQXRGMr3dtRZc0U2QqkY2/fXseh4OXgkR3g3ggB/XE5QPLq+wrdeErduhJPZWjm7EykPfXt0Mk2rEXKE7Bd9TELr8Bll3t9lGuGVoF9GQDLlysITbSW8jXBxPle5VCo6z/OjD6hONoDKXbfd9IeUZ/HLXa1pbwBeiT07jNIoH7X389Aqb4Beje9FPemU/2Vm83tDQgO4ja1g2GVS/svGv8p1/BtA357PaTiL8tJvFiINpxtgTMG/3C6bcomvfxlrHWgAzaGxkp4cyrv+Uj9X83sDrDvd42iUR7md5aib6uoGWBPeM0DPR9fReK5N6T8McDa+skW6kHKVo6n6W3sYIJlkYHSrCB2vcubmzDoGaNP6zYaKKX9vtJhnQxoDnHRa9DVL0XpeKTEZFcQAvhUZf9wro3xYtKf/VxcGrJTikfkIlMsefPfJ32TWWaGbFCso38mXyDazkwH3h5+ruVdSHq2ZuMNBjAFMWUevwirKSzj+COlezAAGi71vjE654LzHPIcG6mFT9HY/qRp0ftoqlFQ310PnZIrdkVp03z/z6vaW3HpgJnyLulZH+Vn51JSEiHpwan0imV1PuYzArQler3rg4m5d+YKB1rfRY5e9LevB7NcMp4kGtM4L9RsMatSDbzPbHh4m5QcZ9fbGUvWgp34lej0LPV8wto2+vB5kzzy/otRE+W7z0RDZsTrQkEhcoNlMeZOCZFJEWx2s4YgR03+C3m953IqFpXXAecTps8FTys3exb+zja0Dto5G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- Scale an object with non-uniform factors.
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- Deconstruct a numeric domain into its component parts.
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- Extract the end points of a curve.
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- Create a rectangle from a base plane and two points
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- Retrieve the base plane and side intervals of a rectangle.
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- Preview a Drawing in canvas.
Note: Right click on the component to save the image or svg
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- Solve oriented geometry bounding boxes.
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- Applies Stroke properties to a Shape
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- Stroke
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210
104
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11206
-659
- A Graphic Plus Shape, or a Curve, Brep, Mesh
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11044
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11119
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11044
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11119
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0;212;212;212
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11044
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11119
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11044
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11119
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- The shape to be used at the end of open path
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11044
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11119
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11234
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- Deconstruct a box into its constituent parts.
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- Deconstruct Box
- Deconstruct Box
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10105
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10150
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10164
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- {x} dimension of box
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10150
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10164
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10150
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10150
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10164
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- Rotate an object in a plane.
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- Rotate
- Rotate
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9865
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9865
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9947
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9865
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9947
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0
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10037
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10062
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- Create an ellipse defined by base plane and two radii.
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10396.5
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0
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10396.5
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10484
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10484
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10504
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10484
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40
26
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10504
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- Deconstruct a numeric domain into its component parts.
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- Deconstruct Domain
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38
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10169
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10156
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42
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10169
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- Deconstruct a numeric domain into its component parts.
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108
44
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10142
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10092
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38
40
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10111
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- Start of domain
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10154
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10167
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- End of domain
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10154
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10167
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- Addition
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70
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10240
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10217
-239
11
20
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10222.5
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- Second item for addition
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10217
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11
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31
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70
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10242
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10219
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10254
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10269.5
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- Applies a Solid Fill color to a Shape
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- Solid Fill
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162
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10601
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10538
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10487
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102
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10538
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255;253;253;253
- A Graphic Plus Shape Object
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10613
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10629
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10546
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210
104
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10710
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- A Graphic Plus Shape, or a Curve, Brep, Mesh
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10548
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10623
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10548
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10623
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0;212;212;212
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10548
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10623
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10548
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10623
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10548
-300
150
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10623
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10722
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10738
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- Merge a bunch of data streams
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11025.5
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11025.5
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11025.5
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10994
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11025.5
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11065
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11080.5
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- Solve oriented geometry bounding boxes.
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10359
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10224
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10285.5
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0
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10381.5
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10371
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10381.5
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- Create a polar array of geometry.
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226
101
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9628
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39.5
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0
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58
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9694
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9784
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9809
73.75
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- Join as many curves as possible
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10015
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- true
- Shape
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10976
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32
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10992
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- Solid Fill
- Applies a Solid Fill color to a Shape
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- Solid Fill
- Solid Fill
-
10469
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162
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10585
-624
- A Graphic Plus Shape, or a Curve, Brep, Mesh
- 23bd9ad5-0ed7-4bd5-9ebf-540a6ef29898
- true
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- Shape / Geometry
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- 459c146e-b950-4487-9814-03c0b98d439f
- 1
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10471
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102
20
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10522
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- The solid fill Color
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- true
- Color
- Color
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- 0
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10471
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10522
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- {0}
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255;255;255;255
- A Graphic Plus Shape Object
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32
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10613
-624
- 030b487b-a566-476f-96a4-a0ae2ad283af
- a48ac930-c378-48dc-84da-26b2af9d8302
- Stroke
- Applies Stroke properties to a Shape
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- Stroke
- Stroke
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9608
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104
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9772
202
- A Graphic Plus Shape, or a Curve, Brep, Mesh
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- true
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- Shape / Geometry
- false
- d5b4aeff-ff26-4ef9-b2e5-496815defd19
- 1
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9610
152
150
20
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9685
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- The stroke color
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- Color
- Color
- true
- 0
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9610
172
150
20
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9685
182
- 1
- 1
- {0}
-
0;212;212;212
- The stroke weight
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- Weight
- Weight
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- 0
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9610
192
150
20
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9685
202
- 1
- 1
- {0}
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- The stroke pattern
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- Pattern
- Pattern
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- 0
-
9610
212
150
20
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9685
222
- The shape to be used at the end of open path
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- true
- End Cap
- End Cap
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- 0
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9610
232
150
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9685
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- 1
- {0}
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- A Graphic Plus Shape Object
- true
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- true
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- Shape
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- 0
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9784
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32
100
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9800
202
- ae8329c9-147c-4440-b557-2977e71e7195
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- Blur
- Applies a Blur Effect to a Shape
- true
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- true
- Blur
- Blur
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10660
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183
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10797
-600
- A Graphic Plus Shape, or a Curve, Brep, Mesh
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- true
- Shape / Geometry
- Shape / Geometry
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- d91d7edd-1058-45d7-83bd-c03acddb095d
- 1
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10662
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123
20
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10723.5
-610
- The radius of the blur effect
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- Blur Radius
- Blur Radius
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- 0
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10662
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123
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10723.5
-590
- 1
- 1
- {0}
- 1873
- A Graphic Plus Shape Object
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- Shape
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10809
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32
40
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10825
-600
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- 08bdcae0-d034-48dd-a145-24a9fcf3d3ff
- GraphMapper+
- External Graph mapper
You can Right click on the Heteromapper's icon and choose "AutoDomain" mode to define Output domain based on input domain interval; otherwise it'll be set to 0-1 in "Normalized" mode.
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- true
- GraphMapper+
- GraphMapper+
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200
155
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-161
- External curve as a graph
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- Curve
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- 1
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- Optional Rectangle boundary. If omitted the curve's would be landed
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- Boundary
- Boundary
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9762.5
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- 1
- List of input numbers
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- Numbers
- Numbers
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9696
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133
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9762.5
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- 9
- {0}
- 0.1
- 0.2
- 0.3
- 0.4
- 0.5
- 0.6
- 0.7
- 0.8
- 0.9
- (Optional) Input Domain
if omitted, it would be 0-1 in "Normalize" mode by default
or be the interval of the input list in case of selecting "AutoDomain" mode
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- Input
- Input
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9696
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133
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9762.5
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- (Optional) Output Domain
if omitted, it would be 0-1 in "Normalize" mode by default
or be the interval of the input list in case of selecting "AutoDomain" mode
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- Output
- Output
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133
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9762.5
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- true
- Merge
- Merge
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- Data stream 1
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- Data 1
- D1
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31
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-278
- 2
- Data stream 2
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- Data 2
- D2
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31
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- 2
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- Data 3
- D3
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31
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9341.5
-238
- 2
- Result of merge
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- Result
- Result
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9381
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31
60
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9396.5
-258
- 8073a420-6bec-49e3-9b18-367f6fd76ac3
- Join Curves
- Join as many curves as possible
- true
- cde9ae79-6dfc-4694-91e2-ee29e1d1dcd7
- true
- Join Curves
- Join Curves
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116
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9495
-183
- 1
- Curves to join
- 7e85ddef-afbe-4a51-8eb9-f1bf04d0e562
- true
- Curves
- Curves
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- dcf72494-3a24-4054-8e57-73ff14e59867
- 1
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9430
-203
53
20
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9456.5
-193
- Preserve direction of input curves
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- true
- Preserve
- Preserve
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- 0
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9430
-183
53
20
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9456.5
-173
- 1
- 1
- {0}
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- 1
- Joined curves and individual curves that could not be joined.
- f110d2a6-04ba-40d1-8ede-576629de1ee0
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- Curves
- Curves
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- 0
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9507
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35
40
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9524.5
-183
- 6da9f120-3ad0-4b6e-9fe0-f8cde3a649b7
- Gradient
- Represents a multiple colour gradient
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- 4ce826ff-60b9-473f-b4eb-19a5a0af2170
- true
- Gradient
- Gradient
- 2
- false
- false
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255;255;255;255
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255;255;255;255
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255;0;0;0
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255;0;0;0
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250
64
- Lower limit of gradient range
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- Lower limit
- Lower limit
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71
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9409.5
-98
- 1
- 1
- {0}
- 0
- Upper limit of gradient range
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- Upper limit
- Upper limit
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- 0
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9374
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71
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9409.5
-78
- 1
- 1
- {0}
- 1
- Parameter along gradient range
- c8a087a3-d6c3-4075-94f5-b6f03f5a18b8
- true
- Parameter
- Parameter
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9374
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71
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9409.5
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- 1
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- {0}
- 0.5
- Colour along gradient at parameter
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- true
- Colour
- Colour
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- 0
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9618
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0
64
- f44b92b0-3b5b-493a-86f4-fd7408c3daf3
- Bounds
- Create a numeric domain which encompasses a list of numbers.
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- 73688d20-ee53-456b-b585-492357d5b4d0
- true
- Bounds
- Bounds
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9431
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9489
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- 1
- Numbers to include in Bounds
- 53f4ce57-ff16-487d-8441-74fef124b562
- true
- Numbers
- Numbers
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- dc1f0f58-8adb-425c-a5a4-72b7549f074b
- 1
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9433
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44
24
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9455
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- Numeric Domain between the lowest and highest numbers in {N}
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- true
- Domain
- Domain
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- 0
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9501
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38
24
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9520
-23
- ae8329c9-147c-4440-b557-2977e71e7195
- a48ac930-c378-48dc-84da-26b2af9d8302
- Blur
- Applies a Blur Effect to a Shape
- true
- e1697a07-a9ef-47c4-be33-bd2577c238b3
- true
- Blur
- Blur
-
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167
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10793
-680
- A Graphic Plus Shape, or a Curve, Brep, Mesh
- 55536ade-da41-411e-869c-66f8f104949a
- true
- Shape / Geometry
- Shape / Geometry
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- 9b545ea8-d3f4-45eb-ab0f-79f46e4a2580
- 1
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10674
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107
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10727.5
-690
- The radius of the blur effect
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- true
- Blur Radius
- Blur Radius
- true
- 0
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10674
-680
107
20
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10727.5
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- 1
- 1
- {0}
- 4
- A Graphic Plus Shape Object
- true
- 8ea3d944-5234-46ce-8de0-309341193327
- true
- Shape
- Shape
- false
- 0
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10805
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32
40
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10821
-680
- e168ff6b-e5c0-48f1-b831-f6996bf3b459
- Interpolate data
- Interpolate a collection of data.
- true
- c38bf768-8e55-4765-a68e-79216a92a01f
- 1
- true
- Interpolate data
- Interp
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11601
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- 1
- Data to interpolate (simple data types only).
- ee7aa4b8-d343-4799-9e97-44326e8b51b2
- true
- Data
- D
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- 1
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11578
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11583.5
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- Normalised interpolation parameter.
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- Parameter
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- 1
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11578
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11583.5
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- Interpolated value.
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- V
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- 0
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11613
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10
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11618
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- Red
- Colour (palette) swatch
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- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 96f356b4-31d4-4a6c-a021-53224daa73cd
- Relay
- false
- 7fd0d788-1237-49d2-b610-14b9cdecf740
- 1
-
-14148
1393
40
16
-
-14128
1401
- 9df5e896-552d-4c8c-b9ca-4fc147ffa022
- Expression
- Evaluate an expression
- O*256/(2^(1285/256))
- true
- 77885843-cab1-42df-89ef-8ef6f86566c5
- Expression
- Expression
-
-14842
1134
207
28
-
-14736
1148
- 1
- ba80fd98-91a1-4958-b6a7-a94e40e52bdb
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Expression variable
- 1995246f-289e-4ca3-ba04-aced7cd0dd72
- Variable O
- O
- true
- 898a5c5d-3c47-497d-9e6c-94065d0c488f
- 1
-
-14840
1136
11
24
-
-14834.5
1148
- Result of expression
- 5293ab1a-72a3-466f-8acb-12d53fff800e
- Result
- false
- 0
-
-14643
1136
6
24
-
-14640
1148
- 9df5e896-552d-4c8c-b9ca-4fc147ffa022
- Expression
- Evaluate an expression
- O*256/(2^(1423/256))
- true
- 62e50431-70a5-40a1-bbba-f39166ca5d3f
- Expression
- Expression
-
-14842
1083
207
28
-
-14736
1097
- 1
- ba80fd98-91a1-4958-b6a7-a94e40e52bdb
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Expression variable
- e995b869-e468-49a5-8a2d-d6a6c4ee65bb
- Variable O
- O
- true
- 898a5c5d-3c47-497d-9e6c-94065d0c488f
- 1
-
-14840
1085
11
24
-
-14834.5
1097
- Result of expression
- 0c05c4dc-a41d-4f25-8fa8-59904954782e
- Result
- false
- 0
-
-14643
1085
6
24
-
-14640
1097
- 9df5e896-552d-4c8c-b9ca-4fc147ffa022
- Expression
- Evaluate an expression
- O*256/(2^(1488/256))
- true
- 6cddbed6-1dd7-44ed-a9e0-86fb89ef71a3
- Expression
- Expression
-
-14842
1032
207
28
-
-14736
1046
- 1
- ba80fd98-91a1-4958-b6a7-a94e40e52bdb
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Expression variable
- 188ea3f9-3d71-488d-a663-f1aebd24f572
- Variable O
- O
- true
- 898a5c5d-3c47-497d-9e6c-94065d0c488f
- 1
-
-14840
1034
11
24
-
-14834.5
1046
- Result of expression
- b808466f-043c-43c9-872f-0833987d5625
- Result
- false
- 0
-
-14643
1034
6
24
-
-14640
1046
- 9df5e896-552d-4c8c-b9ca-4fc147ffa022
- Expression
- Evaluate an expression
- O*256/(2^(1644/256))
- true
- e469ff08-a104-48ec-9f4e-573c7b3bfe16
- Expression
- Expression
-
-14842
985
207
28
-
-14736
999
- 1
- ba80fd98-91a1-4958-b6a7-a94e40e52bdb
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Expression variable
- e21cd616-c856-435f-b9bb-99df4f859c1a
- Variable O
- O
- true
- 898a5c5d-3c47-497d-9e6c-94065d0c488f
- 1
-
-14840
987
11
24
-
-14834.5
999
- Result of expression
- 88231914-12a4-4ab2-8751-7897fa9c1043
- Result
- false
- 0
-
-14643
987
6
24
-
-14640
999
- 9df5e896-552d-4c8c-b9ca-4fc147ffa022
- Expression
- Evaluate an expression
- O*256/(2^(1709.5/256))
- true
- 20d5d108-2056-41af-930a-8e90a1009dff
- Expression
- Expression
-
-14850
937
223
28
-
-14736
951
- 1
- ba80fd98-91a1-4958-b6a7-a94e40e52bdb
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Expression variable
- b43f180b-fc85-4b05-92b0-c3331dbc3dea
- Variable O
- O
- true
- 898a5c5d-3c47-497d-9e6c-94065d0c488f
- 1
-
-14848
939
11
24
-
-14842.5
951
- Result of expression
- 59be1fbf-4cb3-42fe-8174-bf8b71739b0e
- Result
- false
- 0
-
-14635
939
6
24
-
-14632
951
- 9df5e896-552d-4c8c-b9ca-4fc147ffa022
- Expression
- Evaluate an expression
- O*256/(2^(1794.5/256))
- true
- 87e01a5c-d135-4116-817d-da2496621529
- Expression
- Expression
-
-14850
882
223
28
-
-14736
896
- 1
- ba80fd98-91a1-4958-b6a7-a94e40e52bdb
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Expression variable
- dc9595aa-3dee-4da2-8d0c-c395029d8a6a
- Variable O
- O
- true
- 898a5c5d-3c47-497d-9e6c-94065d0c488f
- 1
-
-14848
884
11
24
-
-14842.5
896
- Result of expression
- 34ff7268-139f-4f7c-918d-a790b243fd03
- Result
- false
- 0
-
-14635
884
6
24
-
-14632
896
- 9df5e896-552d-4c8c-b9ca-4fc147ffa022
- Expression
- Evaluate an expression
- O*256/(2^(1874.5/256))
- true
- 03b98b72-99ad-4536-9e58-90622f9ef991
- Expression
- Expression
-
-14850
827
223
28
-
-14736
841
- 1
- ba80fd98-91a1-4958-b6a7-a94e40e52bdb
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Expression variable
- 5853fbe8-0752-447a-bbce-fb563454ca9e
- Variable O
- O
- true
- 898a5c5d-3c47-497d-9e6c-94065d0c488f
- 1
-
-14848
829
11
24
-
-14842.5
841
- Result of expression
- 47598a96-ccb9-4b95-ba69-e34e2d68ea96
- Result
- false
- 0
-
-14635
829
6
24
-
-14632
841
- 9df5e896-552d-4c8c-b9ca-4fc147ffa022
- Expression
- Evaluate an expression
- O*256/(2^(1910.9609375/256))
- true
- 55a8e211-f823-44ad-b334-d360d90f528a
- Expression
- Expression
-
-14875
777
273
28
-
-14736
791
- 1
- ba80fd98-91a1-4958-b6a7-a94e40e52bdb
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Expression variable
- 350f11e7-3838-41b6-a4ae-3223f4993da3
- Variable O
- O
- true
- 898a5c5d-3c47-497d-9e6c-94065d0c488f
- 1
-
-14873
779
11
24
-
-14867.5
791
- Result of expression
- c8faf00d-35ab-4093-8e9d-f4865d3ec68f
- Result
- false
- 0
-
-14610
779
6
24
-
-14607
791
- f31d8d7a-7536-4ac8-9c96-fde6ecda4d0a
- ⦿옷⦿ᑫᑭ⦿ᗩ⦿ᴥ⦿ᕤᕦ⦿◯⦿ᗝ⦿ᗱᗴ⦿ᑫᑭ⦿ᗩ⦿옷⦿ᔓᔕ⦿◯⦿ᔓᔕ⦿ᗱᗴ⦿ᑐᑕ⦿ИN⦿ᗱᗴ⦿ᴥ⦿ᗱᗴ⦿Θ⦿⊙⦿ᗝ⦿◯⦿ᗱᗴ⦿ᴥ⦿ᑎ⦿✤⦿ᗩ⦿ᗯ⦿ᴥ⦿ᑎ⦿ᑐᑕ⦿◌⦿◌⦿◌⦿◌⦿◌⦿◌⦿◌⦿◌⦿ᑐᑕ⦿ᑎ⦿ᴥ⦿ᗯ⦿ᗩ⦿✤⦿ᑎ⦿ᴥ⦿ᗱᗴ⦿◯⦿ᗝ⦿⊙⦿Θ⦿ᗱᗴ⦿ᴥ⦿ᗱᗴ⦿ИN⦿ᑐᑕ⦿ᗱᗴ⦿ᔓᔕ⦿◯⦿ᔓᔕ⦿옷⦿ᗩ⦿ᑫᑭ⦿ᗱᗴ⦿ᗝ⦿◯⦿ᕤᕦ⦿ᴥ⦿ᗩ⦿ᑫᑭ⦿옷⦿
-
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41
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- Raise 2 to the power of N.
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False for input values inside of the X Axis domain bounds
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False for input values on the X Axis which do not intersect a graph curve
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- 00000000-0000-0000-0000-000000000000
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 3
-
255;255;255;255
- A group of Grasshopper objects
- 0b9f480b-88da-4856-9c83-6d1d5314a585
- 1
- 0208315a-ac5c-4218-a12b-42c843878280
- Group
- ⦿✺⦿✺⦿
- e9eb1dcf-92f6-4d4d-84ae-96222d60f56b
- Move
- Translate (move) an object along a vector.
- true
- a4283709-82ce-4012-a8b5-950c46998f27
- true
- Move
- Move
-
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201
44
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7587
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- Base geometry
- f417dbe0-4a39-4dcf-9737-e57f0d97ada0
- true
- Geometry
- Geometry
- true
- 97a5f791-e1a9-4f20-b7bf-bca497bdd92b
- 1
-
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123
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-
7513.5
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- Translation vector
- 0617d7e2-44db-444c-9bff-d35d80e4d831
- true
- Motion
- Motion
- false
- 0
-
7452
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123
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- 1
- 1
- {0}
-
0
0.5
0
- Translated geometry
- 121da76f-3b82-40b0-a2b6-62365e4ed90d
- true
- Geometry
- Geometry
- false
- 0
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20
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- Transformation data
- 1aa7ddc8-2b2d-47b6-b898-3fd430caa004
- true
- Transform
- Transform
- false
- 0
-
7599
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50
20
-
7624
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- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- 6f1a16f5-76e8-400f-b6d6-b31f775ca595
- 32f809c0-d4e4-46b1-918c-88686e051997
- ecc4fafa-b694-4673-82b0-7ce4302cfe80
- 3
- 2dd6b27d-0ff2-44b8-9abd-26174c019846
- Group
- f31d8d7a-7536-4ac8-9c96-fde6ecda4d0a
- ΘᗩΘ
-
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- Applies Stroke properties to a Shape
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- Stroke
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-
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- Color
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- fb5e6000-65f6-4083-bb75-66522d7a800d
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- The stroke weight
- ee015750-1b36-42fa-a542-c758a2bdf3ff
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- The shape to be used at the end of open path
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- End Cap
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136
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100
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- Removed all null and invalid items from a data tree.
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-
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- Remove Invalid
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- Remove Empty
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- Preview a Drawing in canvas.
Note: Right click on the component to save the image or svg
- true
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- Drawing Viewer
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- Drawings / Shapes / Geometry
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- The PPI (Pixels Per Inch) resolution for the image which must be greater than or equal to 72.
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- Resolution
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- Applies Stroke properties to a Shape
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- Color
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- The stroke weight
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- Removed all null and invalid items from a data tree.
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83
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- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
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- Evaluate Length
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71
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- Length
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71
20
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- Normalized
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71
20
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50
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- Create a polyline connecting a number of points.
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40
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- Close polyline
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- Closed
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40
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- Polyline
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38
40
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- Create a polyline connecting a number of points.
- true
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- PolyLine
- PolyLine
-
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106
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- Vertices
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40
20
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- Close polyline
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- Closed
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40
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- Resulting polyline
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38
40
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- Merge
- Merge a bunch of data streams
- true
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- Merge
-
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90
64
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- D1
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31
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- Data stream 2
- a994094a-2e0c-4d33-bd70-ab048da589ff
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- Data 2
- D2
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31
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- a55f5b2b-59dd-4127-af45-fb2940b84e66
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- Data 3
- D3
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31
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- Result
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31
60
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- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
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- Evaluate Length
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71
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- Length factor for curve evaluation
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- Length
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71
20
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- If True, the Length factor is normalized (0.0 ~ 1.0)
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- Normalized
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71
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- Tangent vector at the specified length
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50
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- Curve parameter at the specified length
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50
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- Create a polyline connecting a number of points.
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- PolyLine
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- Close polyline
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40
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- Create regions from intersected curves
- true
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- Regions
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188
101
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- List of curves
- c60da004-4ca7-4e92-8f7a-a94b7040ad1f
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- Curves
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-
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121
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121
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- Optional points to define regions
- 39ab6238-8513-4e37-9f4e-6e38021c8633
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- Points
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- Combine
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-
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121
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- f1598974-1b3e-4711-8522-739c5a716f57
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39
97
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- Create a polar array of geometry.
- true
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- Polar Array
- Polar Array
-
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210
101
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- Base geometry
- 52366233-bf44-4591-92c0-c1d765ac0b6b
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- Geometry
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132
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132
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-
0
0
0
1
0
0
0
1
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- Number of elements in array.
- e228660b-0381-4064-b83d-8ca570d2b8ed
- Count
- Count
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- a36a42bd-2f18-4380-938f-847c2f934c7b
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132
20
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- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- b2942652-4e75-4d30-be8c-77cf436e1982
- Angle
- Angle
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-
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- 6eaffbb2-3392-441a-8556-2dc126aa8910
- Cull Duplicates
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- Cull Duplicates
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-
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180
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-
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113
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- Proximity tolerance distance
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113
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- Number of input points represented by this output point
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- Flip a matrix-like data tree by swapping rows and columns.
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- Flip Matrix
- Flip Matrix
-
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78
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-
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- 2
- Data matrix to flip
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- Data
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- Create a polar array of geometry.
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- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
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-
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132
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- Cull Duplicates
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-
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- Points to operate on
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-
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- Proximity tolerance distance
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113
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- 1
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- Culled points
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- Number of input points represented by this output point
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- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
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- Flip Matrix
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-
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-
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- Data matrix to flip
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- If True, the Length factor is normalized (0.0 ~ 1.0)
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- Tangent vector at the specified length
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132
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132
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132
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180
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113
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- Number of input points represented by this output point
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- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
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- Flip Matrix
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- Number of elements in array.
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- The value will be false if the line was removed.
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94
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- fca5ad7e-ecac-401d-a357-edda0a251cbc
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132
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132
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-
15689
-1105
116
44
-
15753
-1083
- 1
- Polyline vertex points
- e59e4596-b562-49bf-8335-eefb53af9b9c
- true
- Vertices
- Vertices
- false
- 0
-
15691
-1103
50
20
-
15716
-1093
- 1
- 6
- {0}
-
0.253426732105701
-0.309892456276559
0
-
0.0334255287749989
-0.473981751578464
0
-
0.0516576726974328
0.289337340640768
0
-
0.594975561585963
0.271105196718334
0
-
0.577958893925024
-0.549341279791191
0
-
0.355526738071331
-0.302599598707586
0
- Close polyline
- f1f7d634-b5dd-4c51-9303-fe50639af409
- true
- Closed
- Closed
- false
- 0
-
15691
-1083
50
20
-
15716
-1073
- 1
- 1
- {0}
- false
- Resulting polyline
- 55e2b44c-7595-4da6-bdc2-27211f29bd8b
- true
- Polyline
- Polyline
- false
- 0
-
15765
-1103
38
40
-
15784
-1083
- afb96615-c59a-45c9-9cac-e27acb1c7ca0
- Explode
- Explode a curve into smaller segments.
- true
- 25a32639-1938-49fc-8728-8ad84876e376
- true
- Explode
- Explode
-
15869
-1067
134
44
-
15940
-1045
- Curve to explode
- c3ccf7ec-ba9f-499c-81a1-9d1dc74b42f4
- true
- Curve
- Curve
- false
- 83c38d86-bdbd-4063-9828-467d22d7cc98
- 1
-
15871
-1065
57
20
-
15899.5
-1055
- Recursive decomposition until all segments are atomic
- 0f9cb2f4-802a-4cb2-82c8-2656e9252490
- true
- Recursive
- Recursive
- false
- 0
-
15871
-1045
57
20
-
15899.5
-1035
- 1
- 1
- {0}
- true
- 1
- Exploded segments that make up the base curve
- 1b904cf9-6d07-4371-8794-c811f80ea402
- true
- Segments
- Segments
- false
- 0
-
15952
-1065
49
20
-
15976.5
-1055
- 1
- Vertices of the exploded segments
- 4452f4d1-91d8-4946-88d6-5888c9faa279
- true
- Vertices
- Vertices
- false
- 0
-
15952
-1045
49
20
-
15976.5
-1035
- ccc7b468-e743-4049-891f-299432545898
- Curve Middle
- Get the point in the middle of a curve
- true
- a98d7f24-e9a1-4711-acc6-2d87a7568bd0
- true
- Curve Middle
- Curve Middle
-
16022
-998
117
28
-
16066
-984
- Curve for mid-point.
- 9dad8727-e2b7-4175-a52c-cda81aebda87
- true
- Curve
- Curve
- false
- 1b904cf9-6d07-4371-8794-c811f80ea402
- 1
-
16024
-996
30
24
-
16039
-984
- Point in the middle of the curve
- 716c171e-2e0d-4bde-81a6-268ef5a60530
- true
- 1
- Midpoint
- Midpoint
- false
- 0
-
16078
-996
59
24
-
16099.5
-984
- 11bbd48b-bb0a-4f1b-8167-fa297590390d
- End Points
- Extract the end points of a curve.
- true
- b7292e2d-a04b-41d3-a7b1-6e70cd4b600d
- true
- End Points
- End Points
-
16018
-1126
84
44
-
16062
-1104
- Curve to evaluate
- 07aaae07-05f0-46e9-9bb2-3521d8036832
- true
- Curve
- Curve
- false
- 83c38d86-bdbd-4063-9828-467d22d7cc98
- 1
-
16020
-1124
30
40
-
16035
-1104
- Curve start point
- 179bff57-cd4a-493a-863d-25b9a179d84c
- true
- Start
- Start
- false
- 0
-
16074
-1124
26
20
-
16087
-1114
- Curve end point
- 4b7f86fb-520a-49f8-ab98-37b47b50d332
- true
- End
- End
- false
- 0
-
16074
-1104
26
20
-
16087
-1094
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
- f598445f-c9bb-4632-ae5a-5ced170ec13e
- true
- Merge
- Merge
-
16173
-1112
106
84
-
16218
-1070
- 4
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2
- Data stream 1
- 64df2663-8991-4145-9111-913541e81ca2
- true
- false
- Data 1
- D1
- true
- 179bff57-cd4a-493a-863d-25b9a179d84c
- 1
-
16175
-1110
31
20
-
16190.5
-1100
- 2
- Data stream 2
- 269a8b4a-e4c3-4863-bf1f-0deb0d87ac67
- true
- false
- Data 2
- D2
- true
- 716c171e-2e0d-4bde-81a6-268ef5a60530
- 1
-
16175
-1090
31
20
-
16190.5
-1080
- 2
- Data stream 3
- 16cd3125-c7cc-4272-b383-8acadd92fcfe
- true
- false
- Data 3
- D3
- true
- 4b7f86fb-520a-49f8-ab98-37b47b50d332
- 1
-
16175
-1070
31
20
-
16190.5
-1060
- 2
- Data stream 4
- 6e98d805-d129-410e-9208-7e959562de1b
- true
- false
- Data 4
- D4
- true
- 0
-
16175
-1050
31
20
-
16190.5
-1040
- 2
- Result of merge
- d41ee257-f83f-44a4-b288-3bff9e9da672
- true
- 1
- Result
- Result
- false
- 0
-
16230
-1110
47
80
-
16245.5
-1070
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
- true
- a1cd0866-6775-4e14-9c95-510db4b8326d
- true
- PolyLine
- PolyLine
-
16310
-993
116
44
-
16374
-971
- 1
- Polyline vertex points
- ec7c6dab-9b0d-40fc-8bdc-62f65e696227
- true
- Vertices
- Vertices
- false
- d41ee257-f83f-44a4-b288-3bff9e9da672
- 1
-
16312
-991
50
20
-
16337
-981
- 1
- 6
- {0}
-
0.230849276451111
-0.197502004087453
0
-
0.0662562057590903
-0.223755241522163
0
-
0.0663636407279125
0.199099878871604
0
-
0.609184501908787
0.20516461549513
0
-
0.605827517736367
-0.203827499272069
0
-
0.401731366034673
-0.194413499441869
0
- Close polyline
- 05860923-c6b2-4151-b8ba-800a16aab90b
- true
- Closed
- Closed
- false
- 0
-
16312
-971
50
20
-
16337
-961
- 1
- 1
- {0}
- false
- Resulting polyline
- 99adb399-bb0d-42f7-995a-6b1d6ba6e352
- true
- Polyline
- Polyline
- false
- 0
-
16386
-991
38
40
-
16405
-971
- cc14daa5-911a-4fcc-8b3b-1149bf7f2eeb
- Point List
- Displays details about lists of points
- true
- 47957213-cdcf-4228-a22d-1459dac03b4a
- true
- Point List
- Point List
-
16324
-889
74
44
-
16384
-867
- 1
- Points to display
- true
- f53fe761-7495-41bb-984a-5d00113338bb
- true
- Points
- Points
- true
- 7dfed2fb-2c2d-43fe-80f7-67d25a4cb30d
- 1
-
16326
-887
46
20
-
16349
-877
- Optional text size (in Rhino units)
- 48a722bc-723e-4c9a-8aee-6d0321f04616
- true
- Size
- Size
- true
- 0
-
16326
-867
46
20
-
16349
-857
- 2576f657-2f0d-4e3e-9dfb-c79eb4cd13d7
- 4442bb24-c702-460c-a1e4-fcdd321eb886
- Loop Start
- Start the loop with this one. Double click to rerun.
- true
- dfbb98ef-98e2-40fb-9c5f-4322dc449848
- true
- Loop Start
- Loop Start
-
15824
-1312
118
64
-
15889
-1280
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 3
- 6cc73910-22ac-4eb4-882b-eb9d63b8f3c2
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Number of repeats
- dd387923-9b22-4629-bdb1-d0a610793581
- true
- Repeat
- Repeat
- true
- 0
-
15826
-1310
51
20
-
15851.5
-1300
- 1
- 1
- {0}
- 64
- 2
- If you want trigger loop to restart
- 85885200-e9ee-4621-a0fd-ea1c8eb9e686
- true
- Trigger
- Trigger
- true
- 8922d579-58bd-4f83-b1d2-2f7c1c847b74
- 1
-
15826
-1290
51
20
-
15851.5
-1280
- 2
- Data to loop
- f9b4de04-ed90-4a16-a896-ee43d05682a9
- true
- Data
- Data
- true
- 55e2b44c-7595-4da6-bdc2-27211f29bd8b
- 1
-
15826
-1270
51
20
-
15851.5
-1260
- Connect to Loop End
- 688aaa76-c5c0-437f-bb7b-d2fb2d647152
- true
- >
- >
- false
- 0
-
15901
-1310
39
20
-
15920.5
-1300
- Counter
- 150a773a-5aa8-4e0b-abca-14a9d8ff6e48
- true
- Counter
- Counter
- false
- 0
-
15901
-1290
39
20
-
15920.5
-1280
- 2
- Data to loop
- d5cadfaa-7751-4509-a208-173c2c13ffa1
- true
- Data
- Data
- false
- 0
-
15901
-1270
39
20
-
15920.5
-1260
- 15483310-2ce2-48c6-b803-9dee8cb7cc9b
- 4442bb24-c702-460c-a1e4-fcdd321eb886
- Loop End
- End the loop with this one. Double click to pause the loop.
- true
- 0088c44a-a145-4779-89de-19b000b39a60
- true
- Loop End
- Loop End
- 0
- false
- Constant & Record
-
16231
-1372
104
64
-
16280
-1340
- 3
- 6cc73910-22ac-4eb4-882b-eb9d63b8f3c2
- cb95db89-6165-43b6-9c41-5702bc5bf137
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Connect to Loop Start
- 062f1d0d-2835-4808-a2e1-68ed71c83de0
- true
- <
- <
- false
- 688aaa76-c5c0-437f-bb7b-d2fb2d647152
- 1
-
16233
-1370
35
20
-
16250.5
-1360
- Set to true to exit the loop
- 446153a1-e5fe-4b51-9c06-03f3c8269142
- true
- Exit
- Exit
- true
- 0
-
16233
-1350
35
20
-
16250.5
-1340
- 1
- 1
- {0}
- false
- 2
- Data to loop
- 27320839-2dfa-4799-87b2-f5a27c549120
- true
- Data
- Data
- false
- 613432b1-7d77-4615-b262-15d13c6fc293
- 1
-
16233
-1330
35
20
-
16250.5
-1320
- 2
- Data after the loop
- 869cc8ba-3a74-4469-ae82-c452fd20180b
- true
- 1
- Data
- Data
- false
- 0
-
16292
-1370
41
60
-
16304.5
-1340
- dc6f76a5-ffd3-4a50-b42b-fcb46a544902
- c6c19589-ab63-4b60-8d7c-2c1b6d60fac7
- True Only Button
- When clicked, the button object only raises recomputation one time.
- False
- True
- 8922d579-58bd-4f83-b1d2-2f7c1c847b74
- true
- True Only Button
- True Only Button
- false
- 0
- neutral,N
-
15662
-953
148
22
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 83c38d86-bdbd-4063-9828-467d22d7cc98
- true
- Relay
- false
- 79cee91b-b321-4230-985a-2ae1ec2ad0ef
- 1
-
15965
-1186
40
16
-
15985
-1178
- 7a1e5fd7-b7da-4244-a261-f1da66614992
- Power of 2
- Raise 2 to the power of N.
- true
- a42b481f-1cac-406c-915c-78cd5dc17db5
- true
- Power of 2
- Power of 2
-
15840
-1443
103
28
-
15898
-1429
- Input value
- d2e297c3-b80c-4014-b980-9a8c29f5fcfe
- true
- Value
- Value
- false
- 0
-
15842
-1441
44
24
-
15864
-1429
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_String
- false
- 16
- Output value
- 853f787d-d612-40ed-957d-502a109f80c4
- true
- Result
- Result
- false
- 0
-
15910
-1441
31
24
-
15925.5
-1429
- 4d2a06bd-4b0f-4c65-9ee0-4220e4c01703
- Scale
- Scale an object uniformly in all directions.
- true
- dd01be7a-f004-4f2e-8f95-86bd6510ab44
- true
- Scale
- Scale
-
15798
-1535
201
64
-
15935
-1503
- Base geometry
- 7adec163-1f97-4ba6-9387-2030d32702d0
- true
- Geometry
- Geometry
- true
- d5cadfaa-7751-4509-a208-173c2c13ffa1
- 1
-
15800
-1533
123
20
-
15861.5
-1523
- Center of scaling
- 3b53ddef-ed80-4109-8689-e13f03a7db64
- true
- Center
- Center
- false
- 0
-
15800
-1513
123
20
-
15861.5
-1503
- 1
- 1
- {0}
-
0
0
0
- Scaling factor
- 4deef344-5568-4030-965e-c677619704f7
- true
- Factor
- Factor
- false
- 853f787d-d612-40ed-957d-502a109f80c4
- 1
-
15800
-1493
123
20
-
15861.5
-1483
- 1
- 1
- {0}
- 0.5
- Scaled geometry
- 6830d610-5ef3-4e8b-95f3-a34e4424f6f9
- true
- Geometry
- Geometry
- false
- 0
-
15947
-1533
50
30
-
15972
-1518
- Transformation data
- 937023b7-428d-448e-b8ce-626e522bf593
- true
- Transform
- Transform
- false
- 0
-
15947
-1503
50
30
-
15972
-1488
- 4d2a06bd-4b0f-4c65-9ee0-4220e4c01703
- Scale
- Scale an object uniformly in all directions.
- true
- efd5b6f1-8a95-4da6-a382-798344be96a6
- true
- Scale
- Scale
-
16145
-1516
217
64
-
16298
-1484
- Base geometry
- d8eb3162-4f16-4420-bdb4-08565b3f2b85
- true
- Geometry
- Geometry
- true
- 99adb399-bb0d-42f7-995a-6b1d6ba6e352
- 1
-
16147
-1514
139
20
-
16224.5
-1504
- Center of scaling
- 83ecda89-b6c1-42f0-91b3-f8e168213f81
- true
- Center
- Center
- false
- 0
-
16147
-1494
139
20
-
16224.5
-1484
- 1
- 1
- {0}
-
0
0
0
- Scaling factor
- ce9b475d-ee91-4782-9281-c7430f998752
- 1/X
- true
- Factor
- Factor
- false
- 853f787d-d612-40ed-957d-502a109f80c4
- 1
-
16147
-1474
139
20
-
16224.5
-1464
- 1
- 1
- {0}
- 0.5
- Scaled geometry
- 613432b1-7d77-4615-b262-15d13c6fc293
- true
- Geometry
- Geometry
- false
- 0
-
16310
-1514
50
30
-
16335
-1499
- Transformation data
- 114d69b3-2bae-4eda-9527-28f1b502a88d
- true
- Transform
- Transform
- false
- 0
-
16310
-1484
50
30
-
16335
-1469
- 2162e72e-72fc-4bf8-9459-d4d82fa8aa14
- Divide Curve
- Divide a curve into equal length segments
- true
- 1cff164a-3135-4ae3-a5e4-0381ab2b137c
- true
- Divide Curve
- Divide Curve
-
16223
-808
139
64
-
16293
-776
- Curve to divide
- a7bc0aa0-0e3b-44c5-890d-3ecd63a3928b
- true
- Curve
- Curve
- false
- 79cee91b-b321-4230-985a-2ae1ec2ad0ef
- 1
-
16225
-806
56
20
-
16261
-796
- Number of segments
- d491ebe7-c4d7-4c83-bec9-1f5b25370ad0
- X-1
- true
- Count
- Count
- false
- b62af334-f12b-4c33-a2b7-43592a10d8d0
- 1
-
16225
-786
56
20
-
16261
-776
- 1
- 1
- {0}
- 10
- Split segments at kinks
- 974ce49c-d65c-4c95-8ecb-7d37f65946f8
- true
- Kinks
- Kinks
- false
- 0
-
16225
-766
56
20
-
16261
-756
- 1
- 1
- {0}
- false
- 1
- Division points
- 7dfed2fb-2c2d-43fe-80f7-67d25a4cb30d
- true
- Points
- Points
- false
- 0
-
16305
-806
55
20
-
16332.5
-796
- 1
- Tangent vectors at division points
- fd7f89c6-9b02-4ce7-b568-7d86e954cf39
- true
- Tangents
- Tangents
- false
- 0
-
16305
-786
55
20
-
16332.5
-776
- 1
- Parameter values at division points
- b174f96b-e9d4-4e21-872d-c1ad6297b1eb
- true
- Parameters
- Parameters
- false
- 0
-
16305
-766
55
20
-
16332.5
-756
- ad013215-63f3-46da-8b16-ce3bf593a0c0
- 1c9de8a1-315f-4c56-af06-8f69fee80a7a
- Curve Edit Points
- Extract the edit points on a curve at knot averages, the points an interpolated curve interpolated through.
- true
- c1604d20-1e74-4275-a566-65b937656418
- true
- Curve Edit Points
- Curve Edit Points
-
15871
-807
123
64
-
15925
-775
- Curve to get the edit points of
- da149e96-5071-4803-bb0b-729c3e0c978d
- true
- Curve
- Curve
- false
- 79cee91b-b321-4230-985a-2ae1ec2ad0ef
- 1
-
15873
-805
40
30
-
15893
-790
- If True, only the edit points at knots (span ends) are extracted (the points an interpolated curve interpolated through)
If False, all edit points are extracted which equals the same amount as the curve control points (like Rhino's EditPtOn command)
- d47fd754-782f-4f1f-ae61-b568debe71da
- true
- Knots
- Knots
- false
- 0
-
15873
-775
40
30
-
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136
20
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- 1
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- The stroke pattern
- 7ddc5023-d4dd-4dcd-acfb-7d3d092442a4
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-
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4953
136
20
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- The shape to be used at the end of open path
- 3b2d0b4e-7952-45d4-886b-05e5309579f4
- End Cap
- End Cap
- true
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-
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136
20
-
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- A Graphic Plus Shape Object
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-
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48
100
-
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- 071c3940-a12d-4b77-bb23-42b5d3314a0d
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- Removed all null and invalid items from a data tree.
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- Clean Tree
- Clean Tree
-
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135
84
-
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- Remove null items from the tree.
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- Remove Nulls
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- 0
-
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83
20
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- Remove invalid items from the tree.
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- Remove Invalid
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-
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4889
83
20
-
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- Remove empty branches from the tree.
- 05e7e3a4-06fe-4b37-a97a-5d5a480c4b29
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- Remove Empty
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-
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83
20
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- 1
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- Data tree to clean
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83
20
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- Spotless data tree
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24
80
-
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- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 177ebf54-672d-4201-9e7e-88a2174b5ff2
- Evaluate Length
- Evaluate Length
-
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149
64
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- Curve to evaluate
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- a24a49ab-358e-4f47-b080-236c1ea0aacb
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-
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4880
71
20
-
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- Length factor for curve evaluation
- 46bc8c22-474f-49f1-b450-e269dacf0b1b
- Length
- Length
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- 0
-
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4900
71
20
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- 1
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- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- eb593801-031c-40f0-8db8-091e757e5ec4
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- Normalized
- false
- 0
-
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4920
71
20
-
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- 1
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- Point at the specified length
- 3ddda828-e9c1-4078-b462-64771241dc6d
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- 0
-
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50
20
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- Tangent vector at the specified length
- 922de02f-68ea-4be7-a5e4-fc94b0c23f34
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-
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50
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- Curve parameter at the specified length
- c4c88a0e-d01d-40be-963a-e7eaf6f06a16
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50
20
-
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- 71b5b089-500a-4ea6-81c5-2f960441a0e8
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- Create a polyline connecting a number of points.
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- 1d9a43f1-7bac-4ed2-801e-a9c7a6aac879
- PolyLine
- PolyLine
-
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4879
106
44
-
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- 1
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4881
40
20
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- Close polyline
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40
20
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- a9b4cc96-5e89-49c4-875d-ca718cbdc917
- Polyline
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-
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4881
38
40
-
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4901
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
- true
- 3eade811-6687-448f-a858-7dabb735bb48
- PolyLine
- PolyLine
-
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4947
106
44
-
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- 1
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- 40e9a704-1897-40c9-a62f-c1ca756c1129
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-
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40
20
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- Close polyline
- 06cde97c-8fe8-403a-8a6c-a6a6d3dbf6f6
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- 1
-
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40
20
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- 5c2d1f27-5ef1-43ef-b347-99f836c288f6
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-
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38
40
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- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
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- dc853760-8407-4c2d-9c2a-6157e33088bb
- Merge
- Merge
-
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4907
90
64
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- Data stream 1
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- Data 1
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-
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31
20
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- Data stream 2
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31
20
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-
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31
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31
60
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- fca5ad7e-ecac-401d-a357-edda0a251cbc
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- Create a polar array of geometry.
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- 36b301bc-2889-448a-9d41-4f6d44c6af34
- Polar Array
- Polar Array
-
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210
101
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- Base geometry
- 2b4ac54a-5e7f-401d-a88f-4b659407a6db
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132
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- Polar array plane
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132
37
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-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
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132
20
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- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
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- false
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132
20
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50
48
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-
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50
49
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- Cull Duplicates
- 1
- Cull points that are coincident within tolerance
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- 3bbe3d33-9dcf-4a79-bebf-9ef0a482100d
- Cull Duplicates
- Cull Duplicates
-
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180
64
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- 1
- Points to operate on
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-
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113
30
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- Proximity tolerance distance
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- 0
-
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113
30
-
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- 1
- 1
- {0}
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- Culled points
- 866e7ffc-c040-4eed-bddf-8db76a85ee13
- Points
- Points
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- 0
-
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39
20
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- 1
- Index map of culled points
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-
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4890
39
20
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4900
- 1
- Number of input points represented by this output point
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-
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39
20
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4920
- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
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- c5a71207-a092-4929-bcd7-eed57b82b082
- Flip Matrix
- Flip Matrix
-
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4871
78
28
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- 2
- Data matrix to flip
- b63fec32-bf50-4ab0-a5fa-8e6912769524
- Data
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- 539162c7-ece1-4511-a6b4-f8ff9e54b0dd
- 1
-
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25
24
-
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- 2
- Flipped data matrix
- 2cc55d5c-3f1d-4267-bc1a-472a880b025d
- Data
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-
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4873
25
24
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- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 354476f8-a7f0-403f-8cd6-9c20d0539975
- Evaluate Length
- Evaluate Length
-
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4987
149
64
-
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- Curve to evaluate
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- Curve
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- 0ef550af-5eca-4c66-96df-10fbf47ce3ce
- 1
-
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71
20
-
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- Length factor for curve evaluation
- dadde2e7-02b0-4b9a-a1ce-4765be8dd176
- Length
- Length
- false
- 0
-
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5009
71
20
-
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- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 5529414f-6d9a-4b0f-9552-0fdf3b5adacc
- Normalized
- Normalized
- false
- 0
-
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5029
71
20
-
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- 1
- 1
- {0}
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- Point at the specified length
- 0360efd1-90c7-4136-9ae9-401adc7153a5
- Point
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- 0
-
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50
20
-
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- Tangent vector at the specified length
- bb833425-c617-498c-8bd5-3859afffa905
- Tangent
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- false
- 0
-
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50
20
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- Curve parameter at the specified length
- 5cb98dfa-3161-49a8-8c7c-eca161dc734b
- Parameter
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- 0
-
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50
20
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- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- 8560f4f8-e365-4844-a26a-f82cd9b05b89
- Polar Array
- Polar Array
-
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4987
210
101
-
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- Base geometry
- 85a3d78e-d56f-4116-91fd-86d3810607b6
- Geometry
- Geometry
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- 0360efd1-90c7-4136-9ae9-401adc7153a5
- 1
-
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4989
132
20
-
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- Polar array plane
- 676b7b59-00e0-40d2-af96-5dc6039143cb
- Plane
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-
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5009
132
37
-
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5027.5
- 1
- 1
- {0}
-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
- 989cffd7-42d4-4915-bcaf-19872b7e4d30
- Count
- Count
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- a36a42bd-2f18-4380-938f-847c2f934c7b
- 1
-
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5046
132
20
-
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- 1
- 1
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- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- e2e975e3-a06d-4af1-b298-ee9dbbb0c9ab
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- 0
- false
-
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132
20
-
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- 1
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- 6.2831853071795862
- 1
- Arrayed geometry
- fd011762-3520-48d2-a6fd-14f37f6d119a
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-
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4989
50
48
-
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- Transform
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-
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5037
50
49
-
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5061.75
- 6eaffbb2-3392-441a-8556-2dc126aa8910
- Cull Duplicates
- 1
- Cull points that are coincident within tolerance
- true
- c021a3bf-0177-4b65-aa95-b18ca93e291f
- Cull Duplicates
- Cull Duplicates
-
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4984
180
64
-
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5016
- 1
- Points to operate on
- a09bce55-f62d-4ecd-9500-4a2edf22ee4b
- Points
- Points
- false
- 1a9d7e15-c1be-43de-b0db-779afbd0a4dd
- 1
-
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4986
113
30
-
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- Proximity tolerance distance
- bb4706d5-e7cb-49e1-b0a1-3e09db22f4aa
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- 0
-
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5016
113
30
-
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5031
- 1
- 1
- {0}
- 1.1641532182693481E-10
- 1
- Culled points
- 40e9a704-1897-40c9-a62f-c1ca756c1129
- Points
- Points
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- 0
-
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4986
39
20
-
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- 1
- Index map of culled points
- 3939c402-70d5-458a-ac4f-623402dd4f34
- Indices
- Indices
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- 0
-
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5006
39
20
-
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5016
- 1
- Number of input points represented by this output point
- 9ac7a65a-d317-4483-a0c1-a1a696a79822
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- Valence
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- 0
-
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5026
39
20
-
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5036
- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
- true
- 5723f52f-3856-490b-bb74-1bed6c50fdc9
- Flip Matrix
- Flip Matrix
-
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4999
78
28
-
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5013
- 2
- Data matrix to flip
- c2ec5213-befc-4d81-8e58-70acd9a580bf
- Data
- Data
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- fd011762-3520-48d2-a6fd-14f37f6d119a
- 1
-
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5001
25
24
-
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- 2
- Flipped data matrix
- a2b0532f-503c-41b6-87ab-030285f5949d
- Data
- Data
- false
- 0
-
-9918
5001
25
24
-
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5013
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
- 1017d33b-cbb5-459d-b84c-254beedb00ed
- Merge
- Merge
-
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6262
90
64
-
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6294
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- Data stream 1
- b8844f2c-50e0-4aae-9c5a-3e610a7f5316
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- Data 1
- D1
- true
- 96f72f95-50c1-4167-a4ee-9dd0f5c4d8e3
- 1
-
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6264
31
20
-
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- 2
- Data stream 2
- fbdcee46-13e5-4211-b6da-e208fb91bbbd
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- Data 2
- D2
- true
- f8928777-412d-4924-99a2-19c3fa3f9f18
- 1
-
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6284
31
20
-
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- 2
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- ee96b715-5b35-487d-914c-0c4cd6bbb536
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- Data 3
- D3
- true
- 0
-
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6304
31
20
-
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- 2
- Result of merge
- b0240898-22b6-4015-a2ad-5e69472840fa
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- Result
- false
- 0
-
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- Create a polar array of geometry.
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- Polar Array
- Polar Array
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- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
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- Cull Duplicates
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- Cull points that are coincident within tolerance
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- Cull Duplicates
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180
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- Points to operate on
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- Number of input points represented by this output point
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39
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- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
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- Flip Matrix
- Flip Matrix
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- Data matrix to flip
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- Data
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- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
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- Evaluate Length
- Evaluate Length
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149
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71
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- If True, the Length factor is normalized (0.0 ~ 1.0)
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- Create a polar array of geometry.
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210
101
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132
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50
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50
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180
64
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- Points to operate on
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113
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113
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39
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- Flip a matrix-like data tree by swapping rows and columns.
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- Flip Matrix
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78
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25
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25
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255;255;255;255
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40
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40
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255;255;255;255
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-
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166
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90
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500
- The radius of the blur effect
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- Blur Radius
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90
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188
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- The radius of the shadow effect
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- The offset distance of the shadow effect
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112
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- Removes duplicate lines in a list
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- Flip a matrix-like data tree by swapping rows and columns.
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- Cull Duplicates
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-
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180
64
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113
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113
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39
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- Flip a matrix-like data tree by swapping rows and columns.
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- Flip Matrix
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78
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- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
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- Length factor for curve evaluation
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- If True, the Length factor is normalized (0.0 ~ 1.0)
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101
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180
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255;255;255;255
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136
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255;80;233;0
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136
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136
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136
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48
100
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210
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132
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- Flip a matrix-like data tree by swapping rows and columns.
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- Number of input points represented by this output point
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39
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- Flip a matrix-like data tree by swapping rows and columns.
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- Flip Matrix
- Flip Matrix
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25
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- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
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- If True, the Length factor is normalized (0.0 ~ 1.0)
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180
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- Removes duplicate lines in a list
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- 07903834-2bbc-40bb-b020-682f4ff01256
- Clean Duplicate Lines
- Clean Duplicate Lines
-
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176
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- 1
- Lines to check for duplicates
- 4083c90e-b729-4d61-8504-7e6fc33fcc9f
- Lines
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- Tolerance
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-
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- b461496e-9b06-4abe-a05a-899443bf7ca8
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- Indices
- Indices
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35
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- The value will be false if the line was removed.
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- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
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- Flip Matrix
- Flip Matrix
-
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- Data matrix to flip
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41
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- fca5ad7e-ecac-401d-a357-edda0a251cbc
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- Create a polar array of geometry.
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- Polar Array
- Polar Array
-
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210
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- Base geometry
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- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
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- Removes duplicate lines in a list
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- Clean Duplicate Lines
- Clean Duplicate Lines
-
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- Lines to check for duplicates
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- e6e60adb-d1f6-4df1-b516-096ec1433f4a
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- 4351192c-f761-409a-96d1-d76332ec2e05
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- The value will be false if the line was removed.
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- Status
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- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
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- Flip Matrix
- Flip Matrix
-
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- Applies Stroke properties to a Shape
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- Stroke
- Stroke
-
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- A Graphic Plus Shape, or a Curve, Brep, Mesh
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- Shape / Geometry
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- e9c1950e-8d9b-4856-9995-1c3cb286e74b
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- The stroke color
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- Color
- Color
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- a6fc4669-bbd3-4850-bf79-6f415283923b
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136
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255;21;0;255
- The stroke weight
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- Weight
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- e7c315e7-6046-4360-a3b1-dc1f18620e40
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- Pattern
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- The shape to be used at the end of open path
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- End Cap
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136
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- A Graphic Plus Shape Object
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- Shape
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48
100
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- 071c3940-a12d-4b77-bb23-42b5d3314a0d
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- Removed all null and invalid items from a data tree.
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- Clean Tree
- Clean Tree
-
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135
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- Remove null items from the tree.
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83
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- Remove invalid items from the tree.
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83
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- Remove empty branches from the tree.
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83
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- Data tree to clean
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80
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- 6b021f56-b194-4210-b9a1-6cef3b7d0848
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- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
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- 40e6ee20-282b-41a5-98af-d53b27efbe05
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- Evaluate Length
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- Curve to evaluate
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71
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- Length factor for curve evaluation
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71
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- If True, the Length factor is normalized (0.0 ~ 1.0)
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- Normalized
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- Tangent vector at the specified length
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- Curve parameter at the specified length
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-
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106
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- Closed
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40
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38
40
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- Create a polyline connecting a number of points.
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-
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106
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40
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- Close polyline
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- Closed
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38
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- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
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- Merge a bunch of data streams
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- Merge
- Merge
-
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- Polar Array
-
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- Base geometry
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- Count
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132
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- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
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132
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- Arrayed geometry
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- Geometry
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-
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50
48
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- Transform
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-
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50
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- Cull Duplicates
- 1
- Cull points that are coincident within tolerance
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- Cull Duplicates
- Cull Duplicates
-
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-
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- Points to operate on
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- Proximity tolerance distance
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113
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- 1
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- 1.1641532182693481E-10
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- Culled points
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39
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- 1
- Index map of culled points
- 955a3bb3-9dab-4650-b40b-c77ed72569b1
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39
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- Number of input points represented by this output point
- 489ba8da-2af4-419b-9bfa-f1c487f4c5af
- Valence
- Valence
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- 0
-
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39
20
-
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9378
- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
- true
- f1ff9731-8ea2-44c4-ac3b-9cc6055ed1e7
- Flip Matrix
- Flip Matrix
-
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78
28
-
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- Data matrix to flip
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- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
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- Evaluate Length
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- If True, the Length factor is normalized (0.0 ~ 1.0)
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- Create a polar array of geometry.
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- Flip a matrix-like data tree by swapping rows and columns.
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- Merge a bunch of data streams
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113
30
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- Distance check tolerance
- b25f3c23-a762-4c12-b96d-e082fd28abe2
- Tolerance
- Tolerance
- true
- 0
-
-9258
10805
113
30
-
-9201.5
10820
- 1
- 1
- {0}
- 1.1641532182693481E-10
- 1
- Filtered lines
- f2323476-dc3a-4216-adf0-eaba3b2973c5
- Lines
- Lines
- false
- 0
-
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10775
35
20
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- 1
- Mapped Indices
- c690b836-1a02-4284-842a-0708c47f23a3
- Indices
- Indices
- false
- 0
-
-9121
10795
35
20
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10805
- 1
- The value will be false if the line was removed.
- ab44dcf3-2ade-4f5d-94a0-2131cb15a729
- Status
- Status
- false
- 0
-
-9121
10815
35
20
-
-9103.5
10825
- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
- true
- ea42bb54-fb03-4665-be2c-da03f2e88da4
- Flip Matrix
- Flip Matrix
-
-9969
10776
94
28
-
-9930
10790
- 2
- Data matrix to flip
- f8c79933-13ba-44cb-aa67-0e8cf579350a
- Data
- Data
- false
- 3eaac321-3bbd-4822-9cfe-1f1b585c99de
- 1
-
-9967
10778
25
24
-
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10790
- 2
- Flipped data matrix
- 45dd2659-3327-4e21-90b2-ecdb137cd833
- 1
- Data
- Data
- false
- 0
-
-9918
10778
41
24
-
-9905.5
10790
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- e697eefb-87ad-422d-a21d-1137b7c1e972
- Polar Array
- Polar Array
-
-10927
10893
210
101
-
-10781
10944
- Base geometry
- ae94b400-3755-400d-ad35-1bbcb11b03bc
- Geometry
- Geometry
- true
- 30b06e4d-8646-4a7c-970f-d0368cb36430
- 1
-
-10925
10895
132
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- Polar array plane
- 391dbf1e-6125-4ab4-a209-461987e3f0d5
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- Plane
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132
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0
0
0
1
0
0
0
1
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- Number of elements in array.
- 5715e9a2-c1ad-4c08-a5c1-b2064df88696
- Count
- Count
- false
- a36a42bd-2f18-4380-938f-847c2f934c7b
- 1
-
-10925
10952
132
20
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- 1
- 1
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- 4
- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- 68fdcded-66fe-483d-b0e3-a958f1e182c7
- Angle
- Angle
- false
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- false
-
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132
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- 1
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- 6.2831853071795862
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- Arrayed geometry
- 521c3438-9d00-49a4-9c55-e44ff84f69c2
- Geometry
- Geometry
- false
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10895
50
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- Transformation data
- 9448579d-23fa-4302-9786-54d3209f6b39
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- Transform
- false
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-
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10943
50
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- dc8aee5e-da26-45f0-b2c8-612fcf84157e
- 08b214d9-388c-4ad0-940b-716633b47e45
- Clean Duplicate Lines
- Removes duplicate lines in a list
- true
- 56cf12cb-93cb-4799-97c1-5b4da8f18c3a
- Clean Duplicate Lines
- Clean Duplicate Lines
-
-9260
10902
176
64
-
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10934
- 1
- Lines to check for duplicates
- 406058b1-d198-4e31-b684-c49d1fdbdef4
- Lines
- Lines
- false
- 9878c493-eeff-4143-9e82-fe72a838b843
- 1
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10904
113
30
-
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- Distance check tolerance
- a00024cf-762e-4c59-b724-712c5638305b
- Tolerance
- Tolerance
- true
- 0
-
-9258
10934
113
30
-
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10949
- 1
- 1
- {0}
- 1.1641532182693481E-10
- 1
- Filtered lines
- bc879567-85d4-4dad-80d0-78d6e3a37c55
- Lines
- Lines
- false
- 0
-
-9121
10904
35
20
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10914
- 1
- Mapped Indices
- 1db72078-1077-497d-aa43-9eb502e38cfe
- Indices
- Indices
- false
- 0
-
-9121
10924
35
20
-
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10934
- 1
- The value will be false if the line was removed.
- c66bf3ec-c734-4149-94e0-d50bd08f4c4a
- Status
- Status
- false
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-
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10944
35
20
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- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
- true
- d9c3671f-0dae-46ba-b548-bc0c391248e7
- Flip Matrix
- Flip Matrix
-
-9969
10905
94
28
-
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10919
- 2
- Data matrix to flip
- c76f9827-3168-4b5b-86cb-8bd0494d4802
- Data
- Data
- false
- 521c3438-9d00-49a4-9c55-e44ff84f69c2
- 1
-
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10907
25
24
-
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- 2
- Flipped data matrix
- 9878c493-eeff-4143-9e82-fe72a838b843
- 1
- Data
- Data
- false
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-
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10907
41
24
-
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- 030b487b-a566-476f-96a4-a0ae2ad283af
- a48ac930-c378-48dc-84da-26b2af9d8302
- Stroke
- Applies Stroke properties to a Shape
- true
- 9bf9cad7-6250-4710-920c-44347225fcc7
- Stroke
- Stroke
-
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10524
212
104
-
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10576
- A Graphic Plus Shape, or a Curve, Brep, Mesh
- 26476845-3463-4e30-b838-14d451ac743b
- Shape / Geometry
- Shape / Geometry
- false
- 0d69f67e-72dd-4b79-81cb-d8c17722633e
- 1
-
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10526
136
20
-
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- The stroke color
- 4422378c-96ec-4899-86be-fb32f65e295e
- Color
- Color
- true
- 214c99d0-6148-4a47-a6bb-b3e15350f20b
- 1
-
-5973
10546
136
20
-
-5905
10556
- 1
- 1
- {0}
-
255;21;0;255
- The stroke weight
- 298bb8fa-6ede-46e9-9981-2fde047ca04e
- Weight
- Weight
- true
- e7c315e7-6046-4360-a3b1-dc1f18620e40
- 1
-
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10566
136
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-
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- 1
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- 9
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- The stroke pattern
- 2e29f14b-7f71-4105-b927-c9ce8b7e4b0e
- Pattern
- Pattern
- true
- 0
-
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10586
136
20
-
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10596
- The shape to be used at the end of open path
- 5b8f120e-18c7-4010-b508-1f173fc33f7b
- End Cap
- End Cap
- true
- 0
-
-5973
10606
136
20
-
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10616
- 1
- 1
- {0}
- 2
- A Graphic Plus Shape Object
- true
- 8e672fa7-2874-48a8-83dd-23c69a49627d
- 1
- Shape
- Shape
- false
- 0
-
-5813
10526
48
100
-
-5797
10576
- 071c3940-a12d-4b77-bb23-42b5d3314a0d
- Clean Tree
- Removed all null and invalid items from a data tree.
- true
- 4d0acd62-42f9-4f30-ab24-7bf6079d0af1
- Clean Tree
- Clean Tree
-
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10500
135
84
-
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10542
- 4
- cb95db89-6165-43b6-9c41-5702bc5bf137
- cb95db89-6165-43b6-9c41-5702bc5bf137
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- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Remove null items from the tree.
- 323ae7c9-455f-4087-b80f-487adc139f90
- Remove Nulls
- Remove Nulls
- false
- 0
-
-6807
10502
83
20
-
-6765.5
10512
- 1
- 1
- {0}
- true
- Remove invalid items from the tree.
- 19cbc24c-5e81-454c-9512-06c638f45ce8
- Remove Invalid
- Remove Invalid
- false
- 0
-
-6807
10522
83
20
-
-6765.5
10532
- 1
- 1
- {0}
- true
- Remove empty branches from the tree.
- aaf93b03-12d0-4145-919f-122ae9fac3e3
- Remove Empty
- Remove Empty
- false
- 0
-
-6807
10542
83
20
-
-6765.5
10552
- 1
- 1
- {0}
- true
- 2
- Data tree to clean
- d3a7193f-33f9-47c4-9741-a77b2498bc77
- Tree
- Tree
- false
- 46be9080-af03-498e-8aea-1db208e11c1c
- 1
-
-6807
10562
83
20
-
-6765.5
10572
- 2
- Spotless data tree
- 0d69f67e-72dd-4b79-81cb-d8c17722633e
- Tree
- Tree
- false
- 0
-
-6700
10502
24
80
-
-6688
10542
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 835e1481-19b2-462a-92d8-b19bb04ba708
- Evaluate Length
- Evaluate Length
-
-11820
10466
149
64
-
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10498
- Curve to evaluate
- 40ae8545-0d31-4cf9-b0b0-133e6b9914ac
- Curve
- Curve
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- aaeded99-67a6-45ba-a830-e6f67d3af730
- 1
-
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10468
71
20
-
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10478
- Length factor for curve evaluation
- c87f4ff8-55ee-4c08-b2da-bcf939eab6eb
- Length
- Length
- false
- 0
-
-11818
10488
71
20
-
-11782.5
10498
- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 37fa8fc6-7112-4255-8656-cf368d912b98
- Normalized
- Normalized
- false
- 0
-
-11818
10508
71
20
-
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10518
- 1
- 1
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- Point at the specified length
- df366672-ce88-4283-8d28-f80d442da29e
- Point
- Point
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- 0
-
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10468
50
20
-
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10478
- Tangent vector at the specified length
- be0819a2-3d92-4efe-87bc-eab4bb139328
- Tangent
- Tangent
- false
- 0
-
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10488
50
20
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10498
- Curve parameter at the specified length
- 38112c29-5bd3-42c1-8332-73781e56c94e
- Parameter
- Parameter
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-
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10508
50
20
-
-11698
10518
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
- true
- c3f75100-e08f-4b19-8731-6fb588572721
- PolyLine
- PolyLine
-
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10512
106
44
-
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10534
- 1
- Polyline vertex points
- 5fb43496-a355-4eaf-8463-49a7c59e1c8f
- Vertices
- Vertices
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- 2138d5a5-a00b-43ff-a0ad-aa4822db0145
- 1
-
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10514
40
20
-
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10524
- Close polyline
- f3ebc787-5bcb-42d0-8e75-5106d2b7d125
- Closed
- Closed
- false
- bf9476b7-1f42-4ee8-b1f2-94078732ec74
- 1
-
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10534
40
20
-
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10544
- 1
- 1
- {0}
- true
- Resulting polyline
- 80936a9d-c0ce-4517-8e5a-e3072c18e9a5
- Polyline
- Polyline
- false
- 0
-
-8128
10514
38
40
-
-8109
10534
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
- true
- 762fd39a-467b-4f24-af75-53d880aee254
- PolyLine
- PolyLine
-
-8194
10583
106
44
-
-8140
10605
- 1
- Polyline vertex points
- 8e958efb-6ca0-4048-9e91-7c57b8dc0b40
- Vertices
- Vertices
- false
- 9b4bc001-60b6-4360-bcbe-ee42a7f1e22e
- 1
-
-8192
10585
40
20
-
-8172
10595
- Close polyline
- d8106ca5-1244-4d75-b520-7ac01868ed06
- Closed
- Closed
- false
- bf9476b7-1f42-4ee8-b1f2-94078732ec74
- 1
-
-8192
10605
40
20
-
-8172
10615
- 1
- 1
- {0}
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- Resulting polyline
- 30657e92-cc69-4c53-b2df-8c7ee85b4e4a
- Polyline
- Polyline
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-
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10585
38
40
-
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10605
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
- 66cd0c34-b22e-4d50-81c8-586358999c73
- Merge
- Merge
-
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10540
90
64
-
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10572
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- Data stream 1
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- Data 1
- D1
- true
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- 1
-
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10542
31
20
-
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10552
- 2
- Data stream 2
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- Data 2
- D2
- true
- 30657e92-cc69-4c53-b2df-8c7ee85b4e4a
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-
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10562
31
20
-
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10572
- 2
- Data stream 3
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- Data 3
- D3
- true
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-
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10582
31
20
-
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10592
- 2
- Result of merge
- 46be9080-af03-498e-8aea-1db208e11c1c
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- Result
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- 0
-
-7376
10542
31
60
-
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10572
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- 5a53701a-7b84-4254-9fc0-20b9e62fc9c4
- Polar Array
- Polar Array
-
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10466
210
101
-
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- Base geometry
- f363b1f5-3025-4e9e-a9c5-13c334f8bf9e
- Geometry
- Geometry
- true
- df366672-ce88-4283-8d28-f80d442da29e
- 1
-
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10468
132
20
-
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- Polar array plane
- 08ea3d69-382b-485b-b890-f4fc791f0a31
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- Plane
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-
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10488
132
37
-
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10506.5
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-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
- 0f87e8b2-2ebf-487c-b244-4d5366e6565b
- Count
- Count
- false
- a36a42bd-2f18-4380-938f-847c2f934c7b
- 1
-
-10925
10525
132
20
-
-10859
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- 1
- 1
- {0}
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- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- 3e06e523-8157-41bf-b347-c355666837f5
- Angle
- Angle
- false
- 0
- false
-
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10545
132
20
-
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- 1
- 1
- {0}
- 6.2831853071795862
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- Arrayed geometry
- ac53c8e5-84ec-447a-a023-b73d81c9e8ec
- Geometry
- Geometry
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-
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10468
50
48
-
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10492.25
- 1
- Transformation data
- a5341e3b-f366-4b9f-bed7-9bc13fe9d343
- Transform
- Transform
- false
- 0
-
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10516
50
49
-
-10744
10540.75
- 6eaffbb2-3392-441a-8556-2dc126aa8910
- Cull Duplicates
- 1
- Cull points that are coincident within tolerance
- true
- b0b6dace-83ff-4665-9cd5-b6088764a19e
- Cull Duplicates
- Cull Duplicates
-
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10475
180
64
-
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10507
- 1
- Points to operate on
- 6e1247df-8680-4a2b-bf5c-cf110b2b7a7c
- Points
- Points
- false
- 29d90faf-b068-4670-badb-8456709db8a1
- 1
-
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10477
113
30
-
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10492
- Proximity tolerance distance
- 7a698892-07b7-40b6-ae78-53d7c75fda67
- Tolerance
- Tolerance
- false
- 0
-
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10507
113
30
-
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10522
- 1
- 1
- {0}
- 1.1641532182693481E-10
- 1
- Culled points
- 2138d5a5-a00b-43ff-a0ad-aa4822db0145
- Points
- Points
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- 0
-
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10477
39
20
-
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10487
- 1
- Index map of culled points
- cbb6dc8d-cdd7-4f8f-8a92-03bfaac778d1
- Indices
- Indices
- false
- 0
-
-9123
10497
39
20
-
-9103.5
10507
- 1
- Number of input points represented by this output point
- 82c5849d-ada1-40d6-bfb0-b619cee41fc6
- Valence
- Valence
- false
- 0
-
-9123
10517
39
20
-
-9103.5
10527
- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
- true
- 9c55da62-3de4-48e9-be17-8e9539c901b9
- Flip Matrix
- Flip Matrix
-
-9969
10478
78
28
-
-9930
10492
- 2
- Data matrix to flip
- b2830708-1294-4943-ac9b-cbfaca80efa0
- Data
- Data
- false
- ac53c8e5-84ec-447a-a023-b73d81c9e8ec
- 1
-
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10480
25
24
-
-9954.5
10492
- 2
- Flipped data matrix
- 03e022f8-3fe1-4c18-aef5-bfd78f21620a
- Data
- Data
- false
- 0
-
-9918
10480
25
24
-
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10492
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- eacefcda-50a5-4ae1-ab4a-ee70d2a4029e
- Evaluate Length
- Evaluate Length
-
-11820
10594
149
64
-
-11735
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- Curve to evaluate
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- Flip a matrix-like data tree by swapping rows and columns.
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- Flip a matrix-like data tree by swapping rows and columns.
- true
- 5f6f9b5d-58cd-42a6-8176-39b52af1d509
- Flip Matrix
- Flip Matrix
-
-9949
11936
94
28
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11950
- 2
- Data matrix to flip
- 2072431d-689c-433c-895b-3f63a8635214
- Data
- Data
- false
- a0aa3e0e-3c93-4e68-92ba-2fdd33a20280
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-
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25
24
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- Flipped data matrix
- 52a95820-c937-4b14-941f-6d7d7397fe14
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- Data
- Data
- false
- 0
-
-9898
11938
41
24
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11950
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- 5244dd45-ad3f-4b7d-82f7-c054e23825ee
- Polar Array
- Polar Array
-
-10907
12053
210
101
-
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- Base geometry
- c1c266c3-9498-4d02-8020-f14f446f9792
- Geometry
- Geometry
- true
- b57febb9-de80-4050-97c9-798db961a75f
- 1
-
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12055
132
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- Polar array plane
- 7ba1e3a9-8000-4dd2-a7c0-4ab4e650b30b
- Plane
- Plane
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12075
132
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0
0
0
1
0
0
0
1
0
- Number of elements in array.
- f55bf4a0-c974-4500-9dd0-66e4e33987d2
- Count
- Count
- false
- a36a42bd-2f18-4380-938f-847c2f934c7b
- 1
-
-10905
12112
132
20
-
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- 1
- 1
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- 4
- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- 78468f3a-6bc6-4e7a-bcf6-c3f3e9b4ee98
- Angle
- Angle
- false
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- false
-
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12132
132
20
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12142
- 1
- 1
- {0}
- 6.2831853071795862
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- Arrayed geometry
- 703b7a1e-9642-4134-bebf-f872ec7846bf
- Geometry
- Geometry
- false
- 0
-
-10749
12055
50
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- Transformation data
- 2b97e4f9-7799-446e-8c13-702e2022cc42
- Transform
- Transform
- false
- 0
-
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12103
50
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- dc8aee5e-da26-45f0-b2c8-612fcf84157e
- 08b214d9-388c-4ad0-940b-716633b47e45
- Clean Duplicate Lines
- Removes duplicate lines in a list
- true
- 062a8dcf-22f4-4039-bcaa-62cf727c04e2
- Clean Duplicate Lines
- Clean Duplicate Lines
-
-9240
12062
176
64
-
-9113
12094
- 1
- Lines to check for duplicates
- 24ca0b82-89f1-406a-a607-7d7ed0a788de
- Lines
- Lines
- false
- ba8c40b8-87c5-4333-a820-5c94a2f2195b
- 1
-
-9238
12064
113
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- Distance check tolerance
- 20d50bdb-1853-4cb0-9ef5-d9d8708b40fa
- Tolerance
- Tolerance
- true
- 0
-
-9238
12094
113
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-9181.5
12109
- 1
- 1
- {0}
- 1.1641532182693481E-10
- 1
- Filtered lines
- 39b05f4f-af55-43a0-96fd-7cdc06605701
- Lines
- Lines
- false
- 0
-
-9101
12064
35
20
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12074
- 1
- Mapped Indices
- 97cd3ef8-c9b5-41a1-8b02-d460a5cb8cc8
- Indices
- Indices
- false
- 0
-
-9101
12084
35
20
-
-9083.5
12094
- 1
- The value will be false if the line was removed.
- 9a18b2de-b8b2-4b51-8c6e-af7cdaca2da6
- Status
- Status
- false
- 0
-
-9101
12104
35
20
-
-9083.5
12114
- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
- true
- 004ea8b7-3af1-469e-aa51-929e40b532b2
- Flip Matrix
- Flip Matrix
-
-9949
12065
94
28
-
-9910
12079
- 2
- Data matrix to flip
- d2c18788-502d-44a5-b5c0-25f37746cf81
- Data
- Data
- false
- 703b7a1e-9642-4134-bebf-f872ec7846bf
- 1
-
-9947
12067
25
24
-
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- 2
- Flipped data matrix
- ba8c40b8-87c5-4333-a820-5c94a2f2195b
- 1
- Data
- Data
- false
- 0
-
-9898
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41
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- 030b487b-a566-476f-96a4-a0ae2ad283af
- a48ac930-c378-48dc-84da-26b2af9d8302
- Stroke
- Applies Stroke properties to a Shape
- true
- d3d0a1f7-3657-4151-8f18-270e63656301
- Stroke
- Stroke
-
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11684
212
104
-
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- A Graphic Plus Shape, or a Curve, Brep, Mesh
- f813b03b-bc7a-4342-82b7-a2cc67934e4c
- Shape / Geometry
- Shape / Geometry
- false
- b6749caa-7b90-4824-bc78-e5c27b47f95d
- 1
-
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11686
136
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-
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- The stroke color
- fee869e2-c091-4890-99fc-5d7cd153c7c4
- Color
- Color
- true
- 1597fcb6-8f36-4207-a151-eb0d7474c548
- 1
-
-5953
11706
136
20
-
-5885
11716
- 1
- 1
- {0}
-
255;21;0;255
- The stroke weight
- 262e4331-5d26-4c86-86b5-2ec94cd2f9d9
- Weight
- Weight
- true
- e7c315e7-6046-4360-a3b1-dc1f18620e40
- 1
-
-5953
11726
136
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-
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- 1
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- {0}
- 9
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- The stroke pattern
- 97f3ff38-05b7-453b-8742-56896709c933
- Pattern
- Pattern
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- 0
-
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11746
136
20
-
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- The shape to be used at the end of open path
- c8e8f20c-2a21-4040-b2c3-ee57c1228dd6
- End Cap
- End Cap
- true
- 0
-
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11766
136
20
-
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11776
- 1
- 1
- {0}
- 2
- A Graphic Plus Shape Object
- true
- fad97604-17fc-4325-bcf1-ff5188840485
- 1
- Shape
- Shape
- false
- 0
-
-5793
11686
48
100
-
-5777
11736
- 071c3940-a12d-4b77-bb23-42b5d3314a0d
- Clean Tree
- Removed all null and invalid items from a data tree.
- true
- b0d97a8c-dbee-44dc-b42a-a8d7c228a649
- Clean Tree
- Clean Tree
-
-6789
11660
135
84
-
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11702
- 4
- cb95db89-6165-43b6-9c41-5702bc5bf137
- cb95db89-6165-43b6-9c41-5702bc5bf137
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- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Remove null items from the tree.
- be405693-64bb-4cb2-8874-c7402d113b81
- Remove Nulls
- Remove Nulls
- false
- 0
-
-6787
11662
83
20
-
-6745.5
11672
- 1
- 1
- {0}
- true
- Remove invalid items from the tree.
- 27769a15-df1d-44ae-b71d-ac0be3b5aeff
- Remove Invalid
- Remove Invalid
- false
- 0
-
-6787
11682
83
20
-
-6745.5
11692
- 1
- 1
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- Remove empty branches from the tree.
- fc226a65-355d-4e9d-b606-0392fc97b1dc
- Remove Empty
- Remove Empty
- false
- 0
-
-6787
11702
83
20
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11712
- 1
- 1
- {0}
- true
- 2
- Data tree to clean
- 0110813f-61c4-4e77-a71c-eb9064f92961
- Tree
- Tree
- false
- de1d4127-3ebc-4e96-b709-c138964c9c4a
- 1
-
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11722
83
20
-
-6745.5
11732
- 2
- Spotless data tree
- b6749caa-7b90-4824-bc78-e5c27b47f95d
- Tree
- Tree
- false
- 0
-
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11662
24
80
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11702
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 55db54fd-35cb-4494-b22e-8b00243041c5
- Evaluate Length
- Evaluate Length
-
-11800
11626
149
64
-
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- Curve to evaluate
- b3f16c64-4a35-4549-b3b5-8360735caa91
- Curve
- Curve
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- 0375c488-e806-4ad1-a086-2da4152bef10
- 1
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11628
71
20
-
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- Length factor for curve evaluation
- f7529dff-5612-4a7e-bb35-2337f224168e
- Length
- Length
- false
- 0
-
-11798
11648
71
20
-
-11762.5
11658
- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- a3cb0976-96a3-43b9-a506-a078bec8f622
- Normalized
- Normalized
- false
- 0
-
-11798
11668
71
20
-
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- 1
- 1
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- Point at the specified length
- 58dffd57-f31f-4e4d-9f96-5943d0d979cf
- Point
- Point
- false
- 0
-
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11628
50
20
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- Tangent vector at the specified length
- 787996d9-49cb-4ed1-bee2-703c65ce4736
- Tangent
- Tangent
- false
- 0
-
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50
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- Curve parameter at the specified length
- fe4ad9cc-d5ce-49bc-bc4b-de7e64192269
- Parameter
- Parameter
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- 0
-
-11703
11668
50
20
-
-11678
11678
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
- true
- 35e45fe2-f59e-4fb1-9ccc-0b96dc2155af
- PolyLine
- PolyLine
-
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11672
106
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11694
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- Polyline vertex points
- dcfb4d73-0517-4d12-85f1-d2c20ec185d0
- Vertices
- Vertices
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- aecdad6f-6666-49c9-836e-5e58c7364aad
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11674
40
20
-
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- Close polyline
- 7839dab4-f812-4eaf-bae1-4d712c51a039
- Closed
- Closed
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- 1
-
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11694
40
20
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- 1
- 1
- {0}
- true
- Resulting polyline
- 26090aad-f520-46d6-bc20-d3d0b5abca34
- Polyline
- Polyline
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- 0
-
-8108
11674
38
40
-
-8089
11694
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
- true
- 8000371a-c674-4938-8be1-9853ca521f5f
- PolyLine
- PolyLine
-
-8174
11743
106
44
-
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11765
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- Polyline vertex points
- a8039467-a655-453b-8e33-27e0c8e8d1d3
- Vertices
- Vertices
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- c12a69e6-399c-4909-80b1-7c0a64e86884
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-
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11745
40
20
-
-8152
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- Close polyline
- 12eb4781-ba9a-4c25-ad7b-89fed3038d82
- Closed
- Closed
- false
- bf9476b7-1f42-4ee8-b1f2-94078732ec74
- 1
-
-8172
11765
40
20
-
-8152
11775
- 1
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- Resulting polyline
- f8e5d2c3-f226-4087-89e8-926fdf5c4193
- Polyline
- Polyline
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-
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11745
38
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11765
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
- 82a572e1-d7b4-47c8-a014-d3d9bb56e2be
- Merge
- Merge
-
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11700
90
64
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- Data stream 1
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- Data 1
- D1
- true
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-
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- Data stream 2
- 68c2cac2-9f21-4caa-8480-7c5cb57611ce
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- Data 2
- D2
- true
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- 1
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31
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- Data stream 3
- aed0ff48-d4dc-4151-a137-0824d7cab1b7
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- Data 3
- D3
- true
- 0
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31
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- Result of merge
- de1d4127-3ebc-4e96-b709-c138964c9c4a
- Result
- Result
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- 0
-
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31
60
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- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- d29fff73-a495-4c71-bad6-d22e3561b93e
- Polar Array
- Polar Array
-
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210
101
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- Base geometry
- b5a2fcf6-ae5d-4a25-a801-227f8a384175
- Geometry
- Geometry
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- 58dffd57-f31f-4e4d-9f96-5943d0d979cf
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-
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132
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-
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- Polar array plane
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- Plane
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132
37
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11666.5
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-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
- deab8d0b-6f90-4cb3-92c5-173203a5031d
- Count
- Count
- false
- a36a42bd-2f18-4380-938f-847c2f934c7b
- 1
-
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11685
132
20
-
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- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- 3aacda92-a77b-45dd-9f44-f56a6b37a14b
- Angle
- Angle
- false
- 0
- false
-
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11705
132
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- 1
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- Arrayed geometry
- 4841119b-6919-43e0-9f72-21da2df86cd2
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- Geometry
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- 0
-
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11628
50
48
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- Transformation data
- cb1dbadc-8f74-45d5-928f-a5a2bf83bb4f
- Transform
- Transform
- false
- 0
-
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50
49
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- 6eaffbb2-3392-441a-8556-2dc126aa8910
- Cull Duplicates
- 1
- Cull points that are coincident within tolerance
- true
- 194f3671-9486-483d-9977-608dbabd14c8
- Cull Duplicates
- Cull Duplicates
-
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180
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-
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- 1
- Points to operate on
- c608489f-58cf-4ddd-9cd3-cd408626fed8
- Points
- Points
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-
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113
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- Proximity tolerance distance
- f65c7a2c-5351-46dc-8909-e28a5cc661b9
- Tolerance
- Tolerance
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- 0
-
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113
30
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- 1
- 1
- {0}
- 1.1641532182693481E-10
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- Culled points
- aecdad6f-6666-49c9-836e-5e58c7364aad
- Points
- Points
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- 0
-
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11637
39
20
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- 1
- Index map of culled points
- df89d8c0-9f72-452d-af60-a2c25f317a83
- Indices
- Indices
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- 0
-
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11657
39
20
-
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- 1
- Number of input points represented by this output point
- c1887c30-00f2-4924-a23b-b74b8656bf3c
- Valence
- Valence
- false
- 0
-
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11677
39
20
-
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11687
- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
- true
- 455f0762-2713-4463-9220-4134b05d4f57
- Flip Matrix
- Flip Matrix
-
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11638
78
28
-
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- 2
- Data matrix to flip
- 2523c816-93d0-41ff-984f-d483c8d06d39
- Data
- Data
- false
- 4841119b-6919-43e0-9f72-21da2df86cd2
- 1
-
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25
24
-
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- 2
- Flipped data matrix
- 627175b3-e269-4f62-be01-48fb72a7dc44
- Data
- Data
- false
- 0
-
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25
24
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- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 59b7287b-dfe4-4f42-8db7-c8e67792c667
- Evaluate Length
- Evaluate Length
-
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11754
149
64
-
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- Curve to evaluate
- fe663895-26d1-4cfb-84ca-adc9481f8291
- Curve
- Curve
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-
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71
20
-
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- Length factor for curve evaluation
- 41621117-2021-49ba-b487-d4aedbf29fcc
- Length
- Length
- false
- 0
-
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71
20
-
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- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 6fde47c3-b049-48e7-8b58-c109b354b541
- Normalized
- Normalized
- false
- 0
-
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71
20
-
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- 1
- 1
- {0}
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- Point at the specified length
- 6d5abb8c-34bb-4407-a45c-9ce18f00de6a
- Point
- Point
- false
- 0
-
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50
20
-
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- Tangent vector at the specified length
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- Geometry
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132
20
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- Polar array plane
- a7e8c782-0fb1-4361-8dfb-d316b71ebeb4
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13209
132
37
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-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
- 7faec457-33ed-4073-ac50-10534e3e3c54
- Count
- Count
- false
- a36a42bd-2f18-4380-938f-847c2f934c7b
- 1
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-10945
13246
132
20
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- 4
- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- 9f783047-67af-46e7-ae93-6ca2e6e77d8b
- Angle
- Angle
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- false
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13266
132
20
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- Arrayed geometry
- 2f599679-2169-44a6-ad8d-2177463a5007
- Geometry
- Geometry
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13189
50
48
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- Transformation data
- 40c04821-f11e-48c9-a448-1d17afb03091
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- Transform
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50
49
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13261.75
- dc8aee5e-da26-45f0-b2c8-612fcf84157e
- 08b214d9-388c-4ad0-940b-716633b47e45
- Clean Duplicate Lines
- Removes duplicate lines in a list
- true
- 37ea340c-c4b6-41c0-b9c3-0af409e1b462
- Clean Duplicate Lines
- Clean Duplicate Lines
-
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13196
176
64
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13228
- 1
- Lines to check for duplicates
- 2acd1072-3a2c-4004-a403-1ebeea0fc86d
- Lines
- Lines
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13198
113
30
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- Distance check tolerance
- 79c4a1e0-1cff-49f2-b1fb-a3786cee7fab
- Tolerance
- Tolerance
- true
- 0
-
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13228
113
30
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13243
- 1
- 1
- {0}
- 1.1641532182693481E-10
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- Filtered lines
- 8b5e702e-fe66-451c-9d6f-7d420bedd33f
- Lines
- Lines
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- 0
-
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13198
35
20
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- 1
- Mapped Indices
- 9011f340-ae92-43f4-a4fb-968ae4580415
- Indices
- Indices
- false
- 0
-
-9141
13218
35
20
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-9123.5
13228
- 1
- The value will be false if the line was removed.
- da5155c9-1172-46c4-b4a9-07b1097720a4
- Status
- Status
- false
- 0
-
-9141
13238
35
20
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13248
- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
- true
- cf17a6b1-9c69-4bea-8df9-aad3926d8a47
- Flip Matrix
- Flip Matrix
-
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13199
94
28
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13213
- 2
- Data matrix to flip
- c9416a33-92e7-4e2a-80fe-f44883ffe9a1
- Data
- Data
- false
- 2f599679-2169-44a6-ad8d-2177463a5007
- 1
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13201
25
24
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- 2
- Flipped data matrix
- 6f6badfc-3548-443d-9915-3e528056c5b5
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- Data
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13201
41
24
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13213
- 030b487b-a566-476f-96a4-a0ae2ad283af
- a48ac930-c378-48dc-84da-26b2af9d8302
- Stroke
- Applies Stroke properties to a Shape
- true
- 5fe91bb1-4581-49ee-840e-15dde9daa1ec
- Stroke
- Stroke
-
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12818
212
104
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12870
- A Graphic Plus Shape, or a Curve, Brep, Mesh
- 34b44bad-c225-4b90-b038-e617f66ae7fc
- Shape / Geometry
- Shape / Geometry
- false
- d9b8d3cd-38bf-4578-839b-0a5ece250025
- 1
-
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12820
136
20
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12830
- The stroke color
- d912eabb-dfeb-4a6a-b312-3f8c3bf774ab
- Color
- Color
- true
- 6b1ee9b3-d527-4f0a-92bd-29a66feb6eb4
- 1
-
-5993
12840
136
20
-
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12850
- 1
- 1
- {0}
-
255;21;0;255
- The stroke weight
- 4f659f4c-b3dc-4f09-8c77-586f57958c2d
- Weight
- Weight
- true
- e7c315e7-6046-4360-a3b1-dc1f18620e40
- 1
-
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12860
136
20
-
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12870
- 1
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- {0}
- 9
- 1
- The stroke pattern
- ef45aa1c-d7c6-4913-b5e1-161fe8dcf0ef
- Pattern
- Pattern
- true
- 0
-
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12880
136
20
-
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12890
- The shape to be used at the end of open path
- e2318e1e-0fc0-4106-b936-440f351dc506
- End Cap
- End Cap
- true
- 0
-
-5993
12900
136
20
-
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12910
- 1
- 1
- {0}
- 2
- A Graphic Plus Shape Object
- true
- efce6428-f614-45c9-a29d-22fe028a15cc
- 1
- Shape
- Shape
- false
- 0
-
-5833
12820
48
100
-
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12870
- 071c3940-a12d-4b77-bb23-42b5d3314a0d
- Clean Tree
- Removed all null and invalid items from a data tree.
- true
- 8d6e19cf-5301-40e0-9013-0f3c19973e8d
- Clean Tree
- Clean Tree
-
-6829
12794
135
84
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12836
- 4
- cb95db89-6165-43b6-9c41-5702bc5bf137
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- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Remove null items from the tree.
- 37690dac-ffe2-4835-91c1-6066f9d76ce6
- Remove Nulls
- Remove Nulls
- false
- 0
-
-6827
12796
83
20
-
-6785.5
12806
- 1
- 1
- {0}
- true
- Remove invalid items from the tree.
- 5f89493f-76d6-4ac4-adc7-86ed0ddc2372
- Remove Invalid
- Remove Invalid
- false
- 0
-
-6827
12816
83
20
-
-6785.5
12826
- 1
- 1
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- Remove empty branches from the tree.
- 23999a55-d9d8-4b4a-a9ee-dbc53c88822f
- Remove Empty
- Remove Empty
- false
- 0
-
-6827
12836
83
20
-
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12846
- 1
- 1
- {0}
- true
- 2
- Data tree to clean
- 5ed0643b-cc55-4597-aa6e-00dabf7f5245
- Tree
- Tree
- false
- 86daba70-2a3b-4a1c-a39a-106f8460fa2c
- 1
-
-6827
12856
83
20
-
-6785.5
12866
- 2
- Spotless data tree
- d9b8d3cd-38bf-4578-839b-0a5ece250025
- Tree
- Tree
- false
- 0
-
-6720
12796
24
80
-
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12836
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 1d88f662-fdb9-46e3-aba0-0600f05c556e
- Evaluate Length
- Evaluate Length
-
-11840
12760
149
64
-
-11755
12792
- Curve to evaluate
- 71194947-2b03-49f9-ab5d-65d964bcd2b9
- Curve
- Curve
- false
- 360e3c71-f39a-4344-9b0b-f76f6040e9a5
- 1
-
-11838
12762
71
20
-
-11802.5
12772
- Length factor for curve evaluation
- d94423ca-039f-488d-9398-40cffcfd5922
- Length
- Length
- false
- 0
-
-11838
12782
71
20
-
-11802.5
12792
- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 31c42d3d-1753-4b35-943e-43531dc22aa7
- Normalized
- Normalized
- false
- 0
-
-11838
12802
71
20
-
-11802.5
12812
- 1
- 1
- {0}
- true
- Point at the specified length
- 191da902-2fe2-4d59-8b2c-16c5826ea944
- Point
- Point
- false
- 0
-
-11743
12762
50
20
-
-11718
12772
- Tangent vector at the specified length
- 07a10d0e-6b2c-44ef-8a93-6203590c3610
- Tangent
- Tangent
- false
- 0
-
-11743
12782
50
20
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-11718
12792
- Curve parameter at the specified length
- 7e2d691f-777b-4ec3-aae8-d55f21baabc7
- Parameter
- Parameter
- false
- 0
-
-11743
12802
50
20
-
-11718
12812
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
- true
- a4cfa61c-6315-48e5-9748-41e6bff9dd13
- PolyLine
- PolyLine
-
-8214
12806
106
44
-
-8160
12828
- 1
- Polyline vertex points
- c12fcf9b-f7e1-4c33-8bed-749adaf240f8
- Vertices
- Vertices
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- 18c0a921-f72f-4e37-b0bb-7a27a6f1a621
- 1
-
-8212
12808
40
20
-
-8192
12818
- Close polyline
- ab68209f-a1ff-4f85-b7ea-656a5a0329f4
- Closed
- Closed
- false
- bf9476b7-1f42-4ee8-b1f2-94078732ec74
- 1
-
-8212
12828
40
20
-
-8192
12838
- 1
- 1
- {0}
- true
- Resulting polyline
- cd6a97f5-0587-4a71-8611-22fa2aaa3840
- Polyline
- Polyline
- false
- 0
-
-8148
12808
38
40
-
-8129
12828
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
- true
- a3b55592-fb58-4505-8d3e-ab1d2a9afc89
- PolyLine
- PolyLine
-
-8214
12877
106
44
-
-8160
12899
- 1
- Polyline vertex points
- 3874fd28-3057-4ffb-ba94-3127f375a64f
- Vertices
- Vertices
- false
- b85a0de9-2fc9-4d83-b473-65417e5818a7
- 1
-
-8212
12879
40
20
-
-8192
12889
- Close polyline
- b26490d5-64cf-465f-828d-9f73b4aaa9fd
- Closed
- Closed
- false
- bf9476b7-1f42-4ee8-b1f2-94078732ec74
- 1
-
-8212
12899
40
20
-
-8192
12909
- 1
- 1
- {0}
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- Resulting polyline
- 76e975c9-0859-4963-aa3d-d26213287614
- Polyline
- Polyline
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- 0
-
-8148
12879
38
40
-
-8129
12899
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
- 11da8026-3f02-41e4-9eb5-39a041af1bc2
- Merge
- Merge
-
-7453
12834
90
64
-
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12866
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- Data stream 1
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- Data 1
- D1
- true
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- 1
-
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12836
31
20
-
-7435.5
12846
- 2
- Data stream 2
- ba5eb681-4804-4efe-99dc-e0aba500cae3
- false
- Data 2
- D2
- true
- 76e975c9-0859-4963-aa3d-d26213287614
- 1
-
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12856
31
20
-
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12866
- 2
- Data stream 3
- 1462617e-c980-43e5-aaaf-c5eb62f9d386
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- Data 3
- D3
- true
- 0
-
-7451
12876
31
20
-
-7435.5
12886
- 2
- Result of merge
- 86daba70-2a3b-4a1c-a39a-106f8460fa2c
- Result
- Result
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- 0
-
-7396
12836
31
60
-
-7380.5
12866
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- 46c45a5b-1d60-4374-9874-2f46a8395bfd
- Polar Array
- Polar Array
-
-10947
12760
210
101
-
-10801
12811
- Base geometry
- 79e27294-499c-48b8-b416-6eb8a231dc2d
- Geometry
- Geometry
- true
- 191da902-2fe2-4d59-8b2c-16c5826ea944
- 1
-
-10945
12762
132
20
-
-10879
12772
- Polar array plane
- bd66c505-b444-499f-9a5c-b744cf382212
- Plane
- Plane
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- 0
-
-10945
12782
132
37
-
-10879
12800.5
- 1
- 1
- {0}
-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
- b0a02c9a-7404-49e4-aeb1-880997243f13
- Count
- Count
- false
- a36a42bd-2f18-4380-938f-847c2f934c7b
- 1
-
-10945
12819
132
20
-
-10879
12829
- 1
- 1
- {0}
- 4
- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- 6b988194-31d4-4a16-bff3-69f35e94bfb3
- Angle
- Angle
- false
- 0
- false
-
-10945
12839
132
20
-
-10879
12849
- 1
- 1
- {0}
- 6.2831853071795862
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- Arrayed geometry
- 5f8c5ef7-ad16-42a2-9646-930141e9f464
- Geometry
- Geometry
- false
- 0
-
-10789
12762
50
48
-
-10764
12786.25
- 1
- Transformation data
- 07080f9d-e2dc-4146-85a8-d6b8d2c26ccc
- Transform
- Transform
- false
- 0
-
-10789
12810
50
49
-
-10764
12834.75
- 6eaffbb2-3392-441a-8556-2dc126aa8910
- Cull Duplicates
- 1
- Cull points that are coincident within tolerance
- true
- f2a326c1-b3a7-4936-920d-cbeb331af976
- Cull Duplicates
- Cull Duplicates
-
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12769
180
64
-
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12801
- 1
- Points to operate on
- 7dd1da8a-1ac4-405f-ba33-3ffa8d49bced
- Points
- Points
- false
- 38ab9026-f5cf-4466-9caf-c97b7ae5e9fd
- 1
-
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12771
113
30
-
-9223.5
12786
- Proximity tolerance distance
- 516ab31e-150a-4206-ac59-d027de7e7dc9
- Tolerance
- Tolerance
- false
- 0
-
-9280
12801
113
30
-
-9223.5
12816
- 1
- 1
- {0}
- 1.1641532182693481E-10
- 1
- Culled points
- 18c0a921-f72f-4e37-b0bb-7a27a6f1a621
- Points
- Points
- false
- 0
-
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12771
39
20
-
-9123.5
12781
- 1
- Index map of culled points
- 03482fd5-7707-4c90-a892-c48c8986bf4d
- Indices
- Indices
- false
- 0
-
-9143
12791
39
20
-
-9123.5
12801
- 1
- Number of input points represented by this output point
- bb151dbc-c2c0-4200-900b-e7f3fda48e26
- Valence
- Valence
- false
- 0
-
-9143
12811
39
20
-
-9123.5
12821
- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
- true
- a8d83d35-138a-41e7-93a1-22679fbc2439
- Flip Matrix
- Flip Matrix
-
-9989
12772
78
28
-
-9950
12786
- 2
- Data matrix to flip
- 6a2d23e5-4524-4315-aa03-8d7a304f84df
- Data
- Data
- false
- 5f8c5ef7-ad16-42a2-9646-930141e9f464
- 1
-
-9987
12774
25
24
-
-9974.5
12786
- 2
- Flipped data matrix
- 260ef8d4-4714-4379-8975-e217a4b3e16f
- Data
- Data
- false
- 0
-
-9938
12774
25
24
-
-9925.5
12786
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 33d80a7b-276c-4f76-bef1-be6388f7eb34
- Evaluate Length
- Evaluate Length
-
-11840
12888
149
64
-
-11755
12920
- Curve to evaluate
- f32669f8-7f9d-44f8-acec-3061277735c3
- Curve
- Curve
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- 0f7d41df-0b88-413c-bf09-4b93aebfd26f
- 1
-
-11838
12890
71
20
-
-11802.5
12900
- Length factor for curve evaluation
- d8d5579c-f745-42c3-a9d0-85590e33ca5d
- Length
- Length
- false
- 0
-
-11838
12910
71
20
-
-11802.5
12920
- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 27bdb2b4-cd9c-4657-bef0-d7aca6df4452
- Normalized
- Normalized
- false
- 0
-
-11838
12930
71
20
-
-11802.5
12940
- 1
- 1
- {0}
- true
- Point at the specified length
- e4bc4020-8141-4a7d-b4cb-85d0f43fc123
- Point
- Point
- false
- 0
-
-11743
12890
50
20
-
-11718
12900
- Tangent vector at the specified length
- c6d2c933-7f36-46d4-89e5-f4c6e5ecc676
- Tangent
- Tangent
- false
- 0
-
-11743
12910
50
20
-
-11718
12920
- Curve parameter at the specified length
- 5d82cdc3-80d2-4fed-911b-2b37c1ba5ff5
- Parameter
- Parameter
- false
- 0
-
-11743
12930
50
20
-
-11718
12940
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- 656f3f38-f138-4399-bd8e-f76e210d93db
- Polar Array
- Polar Array
-
-10947
12888
210
101
-
-10801
12939
- Base geometry
- 74d9afb7-f715-4f56-9e7c-4befd1ec6bec
- Geometry
- Geometry
- true
- e4bc4020-8141-4a7d-b4cb-85d0f43fc123
- 1
-
-10945
12890
132
20
-
-10879
12900
- Polar array plane
- 13e96852-2bc7-42aa-bea0-f7014624b7ad
- Plane
- Plane
- false
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- 6.2831853071795862
- 1
- Arrayed geometry
- 3fc82d5e-7989-4464-a1f2-e35bc71b39be
- Geometry
- Geometry
- false
- 0
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50
48
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- Transformation data
- c2cf4656-f293-4432-a8a2-c5908d06faae
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- Transform
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50
49
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14431.75
- dc8aee5e-da26-45f0-b2c8-612fcf84157e
- 08b214d9-388c-4ad0-940b-716633b47e45
- Clean Duplicate Lines
- Removes duplicate lines in a list
- true
- a91d1b7d-9d8e-48be-ae93-1739dd0f5998
- Clean Duplicate Lines
- Clean Duplicate Lines
-
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14366
176
64
-
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14398
- 1
- Lines to check for duplicates
- 7ca0d81f-f0f4-4b9d-8ff1-b3f72e7b9687
- Lines
- Lines
- false
- 476dc671-a77d-48fd-b913-946bc603a6d2
- 1
-
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113
30
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- Distance check tolerance
- e66ee9e6-9c8a-4a42-84ab-c3d0c0b61d34
- Tolerance
- Tolerance
- true
- 0
-
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14398
113
30
-
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14413
- 1
- 1
- {0}
- 1.1641532182693481E-10
- 1
- Filtered lines
- b878599a-93df-47ad-8ccb-3fb6666ef98a
- Lines
- Lines
- false
- 0
-
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14368
35
20
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- 1
- Mapped Indices
- 2b1d52f6-8468-482f-93ae-9a4fb9d1dfc6
- Indices
- Indices
- false
- 0
-
-9141
14388
35
20
-
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14398
- 1
- The value will be false if the line was removed.
- 5ad77074-97fc-4dbb-b9e4-b3d9597dd378
- Status
- Status
- false
- 0
-
-9141
14408
35
20
-
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14418
- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
- true
- ca92eeb5-0c1f-4fdb-8882-fcb7e9eed882
- Flip Matrix
- Flip Matrix
-
-9989
14369
94
28
-
-9950
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- 2
- Data matrix to flip
- 6fe0510d-52f1-4682-b8e2-55283346ca39
- Data
- Data
- false
- 3fc82d5e-7989-4464-a1f2-e35bc71b39be
- 1
-
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25
24
-
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- 2
- Flipped data matrix
- 476dc671-a77d-48fd-b913-946bc603a6d2
- 1
- Data
- Data
- false
- 0
-
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14371
41
24
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14383
- 030b487b-a566-476f-96a4-a0ae2ad283af
- a48ac930-c378-48dc-84da-26b2af9d8302
- Stroke
- Applies Stroke properties to a Shape
- true
- d9bae896-445c-4f81-909c-3e75cff0dee7
- Stroke
- Stroke
-
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13988
212
104
-
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14040
- A Graphic Plus Shape, or a Curve, Brep, Mesh
- 5227eb0b-46ca-49c2-aa4a-62b85816bf74
- Shape / Geometry
- Shape / Geometry
- false
- 986a4ea2-6d71-45b5-9958-cb0ff67dcc00
- 1
-
-5993
13990
136
20
-
-5925
14000
- The stroke color
- 4cab67c0-dd40-4838-90b1-7d135e74022f
- Color
- Color
- true
- bb795819-a6c6-4e55-a863-d50b1c8f2040
- 1
-
-5993
14010
136
20
-
-5925
14020
- 1
- 1
- {0}
-
255;21;0;255
- The stroke weight
- 1692da24-7c26-4ac1-b9d4-5a848ee2e055
- Weight
- Weight
- true
- e7c315e7-6046-4360-a3b1-dc1f18620e40
- 1
-
-5993
14030
136
20
-
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14040
- 1
- 1
- {0}
- 9
- 1
- The stroke pattern
- ee818197-99d6-4bff-9b99-ad9871e7514a
- Pattern
- Pattern
- true
- 0
-
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14050
136
20
-
-5925
14060
- The shape to be used at the end of open path
- 36c8692e-b4aa-40d8-80ef-840011193383
- End Cap
- End Cap
- true
- 0
-
-5993
14070
136
20
-
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14080
- 1
- 1
- {0}
- 2
- A Graphic Plus Shape Object
- true
- 17e7981a-444d-404f-8e9c-f8a208a76a17
- 1
- Shape
- Shape
- false
- 0
-
-5833
13990
48
100
-
-5817
14040
- 071c3940-a12d-4b77-bb23-42b5d3314a0d
- Clean Tree
- Removed all null and invalid items from a data tree.
- true
- 1699dbef-9b40-4a59-89b2-d575c6368831
- Clean Tree
- Clean Tree
-
-6829
13964
135
84
-
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14006
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- cb95db89-6165-43b6-9c41-5702bc5bf137
- cb95db89-6165-43b6-9c41-5702bc5bf137
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- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Remove null items from the tree.
- 82022d82-52cb-4ae7-a2a4-6cb10355572a
- Remove Nulls
- Remove Nulls
- false
- 0
-
-6827
13966
83
20
-
-6785.5
13976
- 1
- 1
- {0}
- true
- Remove invalid items from the tree.
- 425eefb3-38bd-43a4-b684-54e7df9d61c7
- Remove Invalid
- Remove Invalid
- false
- 0
-
-6827
13986
83
20
-
-6785.5
13996
- 1
- 1
- {0}
- true
- Remove empty branches from the tree.
- 087a5d61-135f-4c98-8922-7c44e9c1852b
- Remove Empty
- Remove Empty
- false
- 0
-
-6827
14006
83
20
-
-6785.5
14016
- 1
- 1
- {0}
- true
- 2
- Data tree to clean
- 95c1bf20-b4f3-4e52-a270-b8458219a044
- Tree
- Tree
- false
- 89600b18-6607-4de2-a6a1-41f9e72185f2
- 1
-
-6827
14026
83
20
-
-6785.5
14036
- 2
- Spotless data tree
- 986a4ea2-6d71-45b5-9958-cb0ff67dcc00
- Tree
- Tree
- false
- 0
-
-6720
13966
24
80
-
-6708
14006
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 2a568e96-3e71-4a50-9fd1-3e4ce13e70f5
- Evaluate Length
- Evaluate Length
-
-11840
13930
149
64
-
-11755
13962
- Curve to evaluate
- 4c239629-3b78-433c-9285-5438917e626c
- Curve
- Curve
- false
- 609b5d6e-7b75-4e1a-8a12-faf652c3c682
- 1
-
-11838
13932
71
20
-
-11802.5
13942
- Length factor for curve evaluation
- 6feaf1a9-b8e6-4c02-b75f-cc8982d91726
- Length
- Length
- false
- 0
-
-11838
13952
71
20
-
-11802.5
13962
- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 573b8081-cb2c-4cd2-b6be-ed5a8fbd352b
- Normalized
- Normalized
- false
- 0
-
-11838
13972
71
20
-
-11802.5
13982
- 1
- 1
- {0}
- true
- Point at the specified length
- f9679928-c7a3-4d10-94a2-003b0737b7c6
- Point
- Point
- false
- 0
-
-11743
13932
50
20
-
-11718
13942
- Tangent vector at the specified length
- 2efa796c-48c3-4be3-92b6-4fe5af425c3b
- Tangent
- Tangent
- false
- 0
-
-11743
13952
50
20
-
-11718
13962
- Curve parameter at the specified length
- 95fd76a4-439d-4d69-852d-8097fac143e9
- Parameter
- Parameter
- false
- 0
-
-11743
13972
50
20
-
-11718
13982
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
- true
- 962f300e-d13a-4cfb-8775-3332be224a3b
- PolyLine
- PolyLine
-
-8214
13976
106
44
-
-8160
13998
- 1
- Polyline vertex points
- eb63dc90-64a2-4093-83ed-e8aeacb0a275
- Vertices
- Vertices
- false
- d88c6a85-1583-416c-834b-da43cc4b6ff9
- 1
-
-8212
13978
40
20
-
-8192
13988
- Close polyline
- df21ddec-7724-4a3d-a7a2-7cc64268a33c
- Closed
- Closed
- false
- bf9476b7-1f42-4ee8-b1f2-94078732ec74
- 1
-
-8212
13998
40
20
-
-8192
14008
- 1
- 1
- {0}
- true
- Resulting polyline
- 22e94c20-c8b5-422f-ad04-0b643f130e29
- Polyline
- Polyline
- false
- 0
-
-8148
13978
38
40
-
-8129
13998
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
- true
- 543bb0df-8039-457a-aa73-cedeb032ee5c
- PolyLine
- PolyLine
-
-8214
14047
106
44
-
-8160
14069
- 1
- Polyline vertex points
- a4af2146-6a13-4cc3-9bcc-8866e2bf66c1
- Vertices
- Vertices
- false
- 302ea92b-a67e-4cda-af4d-800b4f829f22
- 1
-
-8212
14049
40
20
-
-8192
14059
- Close polyline
- be2b82c1-1411-4f86-9681-02d93a113ff2
- Closed
- Closed
- false
- bf9476b7-1f42-4ee8-b1f2-94078732ec74
- 1
-
-8212
14069
40
20
-
-8192
14079
- 1
- 1
- {0}
- false
- Resulting polyline
- 660bf03b-9848-4309-bb76-41f35d76729e
- Polyline
- Polyline
- false
- 0
-
-8148
14049
38
40
-
-8129
14069
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
- 18c4dff3-a6c4-4b00-a9d7-b6caf73180f0
- Merge
- Merge
-
-7453
14004
90
64
-
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14036
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2
- Data stream 1
- a1d0bbe6-b200-40ce-bbea-0fac78383987
- false
- Data 1
- D1
- true
- 22e94c20-c8b5-422f-ad04-0b643f130e29
- 1
-
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14006
31
20
-
-7435.5
14016
- 2
- Data stream 2
- d6695219-64fc-4e9d-9bd2-d27ff3ece270
- false
- Data 2
- D2
- true
- 660bf03b-9848-4309-bb76-41f35d76729e
- 1
-
-7451
14026
31
20
-
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14036
- 2
- Data stream 3
- 1852818a-0863-4c53-838f-65738bb00e53
- false
- Data 3
- D3
- true
- 0
-
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14046
31
20
-
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14056
- 2
- Result of merge
- 89600b18-6607-4de2-a6a1-41f9e72185f2
- Result
- Result
- false
- 0
-
-7396
14006
31
60
-
-7380.5
14036
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- eded538d-9e14-4b3b-8511-012d710a4202
- Polar Array
- Polar Array
-
-10947
13930
210
101
-
-10801
13981
- Base geometry
- 25ef12c1-95e7-4f96-82d7-df17d6607e32
- Geometry
- Geometry
- true
- f9679928-c7a3-4d10-94a2-003b0737b7c6
- 1
-
-10945
13932
132
20
-
-10879
13942
- Polar array plane
- 2b96e6d5-9614-40b1-acf2-34b19ce4ca4f
- Plane
- Plane
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- 0
-
-10945
13952
132
37
-
-10879
13970.5
- 1
- 1
- {0}
-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
- 58eccda3-d61f-4806-9e7b-4cac97b391c3
- Count
- Count
- false
- a36a42bd-2f18-4380-938f-847c2f934c7b
- 1
-
-10945
13989
132
20
-
-10879
13999
- 1
- 1
- {0}
- 4
- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- b9d8fa57-8017-48c7-b39b-951608e6d413
- Angle
- Angle
- false
- 0
- false
-
-10945
14009
132
20
-
-10879
14019
- 1
- 1
- {0}
- 6.2831853071795862
- 1
- Arrayed geometry
- 99daf0cc-a43f-450a-b90f-272d1153ba8a
- Geometry
- Geometry
- false
- 0
-
-10789
13932
50
48
-
-10764
13956.25
- 1
- Transformation data
- 7768115b-1c42-4ff7-b6fe-8ba943768f3e
- Transform
- Transform
- false
- 0
-
-10789
13980
50
49
-
-10764
14004.75
- 6eaffbb2-3392-441a-8556-2dc126aa8910
- Cull Duplicates
- 1
- Cull points that are coincident within tolerance
- true
- 53dadc15-5b5d-4d86-a82b-9c99c687e599
- Cull Duplicates
- Cull Duplicates
-
-9282
13939
180
64
-
-9155
13971
- 1
- Points to operate on
- d5a21377-8e13-40ca-87b6-c3ce316d4284
- Points
- Points
- false
- 7a082c6f-007d-4f4d-88ae-98d6d5d1f17a
- 1
-
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13941
113
30
-
-9223.5
13956
- Proximity tolerance distance
- ea47d601-9b7a-485a-aafe-60fe26ddaae6
- Tolerance
- Tolerance
- false
- 0
-
-9280
13971
113
30
-
-9223.5
13986
- 1
- 1
- {0}
- 1.1641532182693481E-10
- 1
- Culled points
- d88c6a85-1583-416c-834b-da43cc4b6ff9
- Points
- Points
- false
- 0
-
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13941
39
20
-
-9123.5
13951
- 1
- Index map of culled points
- cd46575f-a154-4a06-a33b-9c164ea46ccc
- Indices
- Indices
- false
- 0
-
-9143
13961
39
20
-
-9123.5
13971
- 1
- Number of input points represented by this output point
- 52a6aaa7-6e75-4b91-9c70-46767f1da2b5
- Valence
- Valence
- false
- 0
-
-9143
13981
39
20
-
-9123.5
13991
- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
- true
- 39875cab-f112-4d5e-8493-bea84926f5e6
- Flip Matrix
- Flip Matrix
-
-9989
13946
78
28
-
-9950
13960
- 2
- Data matrix to flip
- 3d6273bb-a233-47ac-b046-6c1b482618bd
- Data
- Data
- false
- 99daf0cc-a43f-450a-b90f-272d1153ba8a
- 1
-
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13948
25
24
-
-9974.5
13960
- 2
- Flipped data matrix
- b8290ff5-cc18-4aed-b419-0380c7314516
- Data
- Data
- false
- 0
-
-9938
13948
25
24
-
-9925.5
13960
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 9646f763-5f33-4816-a637-889100b707fe
- Evaluate Length
- Evaluate Length
-
-11840
14058
149
64
-
-11755
14090
- Curve to evaluate
- 7d56b35b-39f2-4ff4-9691-a2043e2af748
- Curve
- Curve
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- 68ed2259-a880-4020-a4fa-5102d6548b24
- 1
-
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14060
71
20
-
-11802.5
14070
- Length factor for curve evaluation
- ace16953-c438-4ca0-ba26-fc3f7c426e21
- Length
- Length
- false
- 0
-
-11838
14080
71
20
-
-11802.5
14090
- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- d0d762db-efb7-4e56-a6cc-c8251bf47a0a
- Normalized
- Normalized
- false
- 0
-
-11838
14100
71
20
-
-11802.5
14110
- 1
- 1
- {0}
- true
- Point at the specified length
- 3224f531-fcc0-4069-98d6-72111ade37c7
- Point
- Point
- false
- 0
-
-11743
14060
50
20
-
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14070
- Tangent vector at the specified length
- ebb51016-99ab-421c-be6c-e0ccc7108e15
- Tangent
- Tangent
- false
- 0
-
-11743
14080
50
20
-
-11718
14090
- Curve parameter at the specified length
- e3ea3454-734c-453f-8949-03fc9323b976
- Parameter
- Parameter
- false
- 0
-
-11743
14100
50
20
-
-11718
14110
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- 6477d210-711d-4699-93a8-6bde781c3f7a
- Polar Array
- Polar Array
-
-10947
14058
210
101
-
-10801
14109
- Base geometry
- 5494aaf9-a934-4696-bab5-ff2557ead832
- Geometry
- Geometry
- true
- 3224f531-fcc0-4069-98d6-72111ade37c7
- 1
-
-10945
14060
132
20
-
-10879
14070
- Polar array plane
- 2e21f5f8-44c0-43a3-ab9f-91911709aba1
- Plane
- Plane
- false
- 0
-
-10945
14080
132
37
-
-10879
14098.5
- 1
- 1
- {0}
-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
- f3bae605-ca2c-4b34-9ab3-182d03df58f9
- Count
- Count
- false
- a36a42bd-2f18-4380-938f-847c2f934c7b
- 1
-
-10945
14117
132
20
-
-10879
14127
- 1
- 1
- {0}
- 4
- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- e4f278f6-967a-45ed-8b63-cbdd1fa95005
- Angle
- Angle
- false
- 0
- false
-
-10945
14137
132
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-
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14147
- 1
- 1
- {0}
- 6.2831853071795862
- 1
- Arrayed geometry
- a2b0bb3c-0097-402a-a4da-133df59b5297
- Geometry
- Geometry
- false
- 0
-
-10789
14060
50
48
-
-10764
14084.25
- 1
- Transformation data
- 9bd95ff5-7cf4-41aa-bb33-086c3c6f832c
- Transform
- Transform
- false
- 0
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- Indices
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35
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- The value will be false if the line was removed.
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- Status
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-
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35
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- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
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- Flip Matrix
- Flip Matrix
-
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94
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- Data matrix to flip
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- 030b487b-a566-476f-96a4-a0ae2ad283af
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- Applies Stroke properties to a Shape
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- Stroke
- Stroke
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- A Graphic Plus Shape, or a Curve, Brep, Mesh
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136
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- The stroke color
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- Color
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15089
136
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-
255;21;0;255
- The stroke weight
- 5d3df0ae-99af-4eb3-8f55-5439e25d08bb
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- Weight
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- e7c315e7-6046-4360-a3b1-dc1f18620e40
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- The stroke pattern
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136
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- The shape to be used at the end of open path
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136
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48
100
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- 071c3940-a12d-4b77-bb23-42b5d3314a0d
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- Removed all null and invalid items from a data tree.
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- Clean Tree
-
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135
84
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- Remove null items from the tree.
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83
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- Remove invalid items from the tree.
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83
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- Remove empty branches from the tree.
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83
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- Data tree to clean
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83
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- Spotless data tree
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24
80
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- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
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- Evaluate Length
- Evaluate Length
-
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15009
149
64
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- Curve to evaluate
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15011
71
20
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- Length factor for curve evaluation
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- Length
- Length
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-
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15031
71
20
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- If True, the Length factor is normalized (0.0 ~ 1.0)
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- Normalized
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-
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15051
71
20
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- Point at the specified length
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- Point
- Point
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50
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- Tangent vector at the specified length
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- Curve parameter at the specified length
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50
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- 71b5b089-500a-4ea6-81c5-2f960441a0e8
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- Create a polyline connecting a number of points.
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- PolyLine
- PolyLine
-
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106
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40
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- Close polyline
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40
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- Resulting polyline
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- Polyline
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-
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15057
38
40
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- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
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- PolyLine
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-
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15126
106
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40
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- Close polyline
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40
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- Resulting polyline
- 5a89161b-d07b-4559-aad8-0c85fd87afc4
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38
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- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
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- Merge a bunch of data streams
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- Merge
- Merge
-
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90
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- Data stream 1
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- Data stream 2
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31
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31
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- fca5ad7e-ecac-401d-a357-edda0a251cbc
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- Create a polar array of geometry.
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- Polar Array
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-
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- Base geometry
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132
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- Polar array plane
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132
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0
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0
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- Number of elements in array.
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- a36a42bd-2f18-4380-938f-847c2f934c7b
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-
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132
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- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
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- false
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132
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- Arrayed geometry
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-
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50
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- Transformation data
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- Transform
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-
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50
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- Cull Duplicates
- 1
- Cull points that are coincident within tolerance
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- Cull Duplicates
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-
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180
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- Points to operate on
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-
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113
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- Proximity tolerance distance
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- 0
-
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113
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- 1
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-
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39
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- Index map of culled points
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39
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-
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- Number of input points represented by this output point
- 31775788-8e35-466b-9c61-4bd7db70d4d2
- Valence
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-
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39
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- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
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- Flip Matrix
- Flip Matrix
-
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78
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- 2
- Data matrix to flip
- e161da66-411b-49e5-a5c4-241e250daa13
- Data
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-
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25
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- 2
- Flipped data matrix
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-
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25
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- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
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- Evaluate Length
- Evaluate Length
-
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149
64
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- Curve to evaluate
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-
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71
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- Length factor for curve evaluation
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- Length
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-
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71
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- If True, the Length factor is normalized (0.0 ~ 1.0)
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- Normalized
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-
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71
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-
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- Tangent vector at the specified length
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-
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- Curve parameter at the specified length
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50
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- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
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- f812766a-18a1-4288-8d6e-7dcd02316302
- Polar Array
- Polar Array
-
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210
101
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- Base geometry
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-
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132
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- Polar array plane
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-
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132
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-
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-
0
0
0
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0
0
0
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- Number of elements in array.
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- Count
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- a36a42bd-2f18-4380-938f-847c2f934c7b
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-
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132
20
-
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- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
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132
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-
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50
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- 6eaffbb2-3392-441a-8556-2dc126aa8910
- Cull Duplicates
- 1
- Cull points that are coincident within tolerance
- true
- 438847c3-266b-464a-b75f-f7f717333f9f
- Cull Duplicates
- Cull Duplicates
-
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15134
180
64
-
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- Points to operate on
- 84319d3c-f942-4ab8-800d-a053b27f4f8f
- Points
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- 2c9cd1a3-de48-4ce5-be20-36b483914987
- 1
-
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113
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- Proximity tolerance distance
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113
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- 1
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- {0}
- 1.1641532182693481E-10
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- false
- 0
-
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16530
35
20
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-9123.5
16540
- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
- true
- ae556089-e277-4e01-aeed-a4880d8dc2ad
- Flip Matrix
- Flip Matrix
-
-9989
16491
94
28
-
-9950
16505
- 2
- Data matrix to flip
- 8ffea371-ed13-48e7-880f-74b30789f15e
- Data
- Data
- false
- d51b821f-a8b8-48bf-8607-af0de2b157a6
- 1
-
-9987
16493
25
24
-
-9974.5
16505
- 2
- Flipped data matrix
- ee9b6e00-5fdf-479b-85f8-490a96da5593
- 1
- Data
- Data
- false
- 0
-
-9938
16493
41
24
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-9925.5
16505
- 030b487b-a566-476f-96a4-a0ae2ad283af
- a48ac930-c378-48dc-84da-26b2af9d8302
- Stroke
- Applies Stroke properties to a Shape
- true
- 97ad3468-8c1b-4978-8267-6befe3fc5c22
- Stroke
- Stroke
-
-5995
16110
212
104
-
-5845
16162
- A Graphic Plus Shape, or a Curve, Brep, Mesh
- d173172d-7b48-480e-b296-8adbbcad4256
- Shape / Geometry
- Shape / Geometry
- false
- 30e8295c-3a26-49df-aef1-101d48a13c2b
- 1
-
-5993
16112
136
20
-
-5925
16122
- The stroke color
- 592109e0-df36-4b5c-94a0-cbd7baf26a6b
- Color
- Color
- true
- 6c6fb177-f0ba-4860-8ebe-5a36c08f4a14
- 1
-
-5993
16132
136
20
-
-5925
16142
- 1
- 1
- {0}
-
255;21;0;255
- The stroke weight
- fd4f3b5f-203a-4333-b50e-b9209eee2034
- Weight
- Weight
- true
- e7c315e7-6046-4360-a3b1-dc1f18620e40
- 1
-
-5993
16152
136
20
-
-5925
16162
- 1
- 1
- {0}
- 9
- 1
- The stroke pattern
- 5ae57219-d11a-4fc8-b9fd-b79e756353f0
- Pattern
- Pattern
- true
- 0
-
-5993
16172
136
20
-
-5925
16182
- The shape to be used at the end of open path
- 35002325-80cb-42cd-ab96-b47be73fd80b
- End Cap
- End Cap
- true
- 0
-
-5993
16192
136
20
-
-5925
16202
- 1
- 1
- {0}
- 2
- A Graphic Plus Shape Object
- true
- 9e12c21c-2e26-4f4c-9f08-61fe6812af57
- 1
- Shape
- Shape
- false
- 0
-
-5833
16112
48
100
-
-5817
16162
- 071c3940-a12d-4b77-bb23-42b5d3314a0d
- Clean Tree
- Removed all null and invalid items from a data tree.
- true
- 34879ece-4417-40d3-aeed-ab5ce1ef32db
- Clean Tree
- Clean Tree
-
-6829
16086
135
84
-
-6732
16128
- 4
- cb95db89-6165-43b6-9c41-5702bc5bf137
- cb95db89-6165-43b6-9c41-5702bc5bf137
- cb95db89-6165-43b6-9c41-5702bc5bf137
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Remove null items from the tree.
- 09ff579e-ffeb-4ffc-aa55-759e5e193f50
- Remove Nulls
- Remove Nulls
- false
- 0
-
-6827
16088
83
20
-
-6785.5
16098
- 1
- 1
- {0}
- true
- Remove invalid items from the tree.
- d0961bf5-04f9-4781-a961-e55a0a67b97d
- Remove Invalid
- Remove Invalid
- false
- 0
-
-6827
16108
83
20
-
-6785.5
16118
- 1
- 1
- {0}
- true
- Remove empty branches from the tree.
- 0a9d932d-83ff-428b-86a5-943c1d0e8dd5
- Remove Empty
- Remove Empty
- false
- 0
-
-6827
16128
83
20
-
-6785.5
16138
- 1
- 1
- {0}
- true
- 2
- Data tree to clean
- 9950c6f4-47d2-4cdc-b0d7-7d1f51ee7e3c
- Tree
- Tree
- false
- 5f0869c0-9bc2-45ba-b9bc-7bd6ce42b320
- 1
-
-6827
16148
83
20
-
-6785.5
16158
- 2
- Spotless data tree
- 30e8295c-3a26-49df-aef1-101d48a13c2b
- Tree
- Tree
- false
- 0
-
-6720
16088
24
80
-
-6708
16128
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- a1ee8a14-8a22-497a-8572-ee31d0c10743
- Evaluate Length
- Evaluate Length
-
-11840
16052
149
64
-
-11755
16084
- Curve to evaluate
- 7ff01179-ea77-4869-ad68-0c9536995559
- Curve
- Curve
- false
- b7cf406c-d92d-4328-9b8e-d0e00d9cb12a
- 1
-
-11838
16054
71
20
-
-11802.5
16064
- Length factor for curve evaluation
- b3590d82-b7a8-40b8-adec-cee0fef3d24e
- Length
- Length
- false
- 0
-
-11838
16074
71
20
-
-11802.5
16084
- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 80ea4189-9088-46a2-9b7e-85ab6608bc9b
- Normalized
- Normalized
- false
- 0
-
-11838
16094
71
20
-
-11802.5
16104
- 1
- 1
- {0}
- true
- Point at the specified length
- 8139e3a6-7ad0-46d9-9244-0ef47834cdd8
- Point
- Point
- false
- 0
-
-11743
16054
50
20
-
-11718
16064
- Tangent vector at the specified length
- fabfec87-a549-4543-a177-dfd67fb18d4d
- Tangent
- Tangent
- false
- 0
-
-11743
16074
50
20
-
-11718
16084
- Curve parameter at the specified length
- aa5bc4ba-a857-4868-b36d-46b8926f3f6d
- Parameter
- Parameter
- false
- 0
-
-11743
16094
50
20
-
-11718
16104
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
- true
- 34133586-fdfd-447f-8e4c-9fc9bdf5f0e4
- PolyLine
- PolyLine
-
-8214
16098
106
44
-
-8160
16120
- 1
- Polyline vertex points
- 96f12eda-fc94-4baf-bb18-9e67bc34d3d0
- Vertices
- Vertices
- false
- 3fe4e5ef-c18f-4e75-b445-569590545a8e
- 1
-
-8212
16100
40
20
-
-8192
16110
- Close polyline
- 13e0205c-351a-499d-b36c-dd55a61bf7c2
- Closed
- Closed
- false
- bf9476b7-1f42-4ee8-b1f2-94078732ec74
- 1
-
-8212
16120
40
20
-
-8192
16130
- 1
- 1
- {0}
- true
- Resulting polyline
- 8db4425b-83e2-40c4-87be-14b2cc962742
- Polyline
- Polyline
- false
- 0
-
-8148
16100
38
40
-
-8129
16120
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
- true
- 54552803-fcb7-47e3-85b6-f8522ddca3a7
- PolyLine
- PolyLine
-
-8214
16169
106
44
-
-8160
16191
- 1
- Polyline vertex points
- a7f94eda-da8a-4121-a5d9-4d6fec2c6da4
- Vertices
- Vertices
- false
- 374bcae9-a010-466e-9d02-a93c7753a60d
- 1
-
-8212
16171
40
20
-
-8192
16181
- Close polyline
- 39f77415-45d3-4a69-b629-5b6a3423aeff
- Closed
- Closed
- false
- bf9476b7-1f42-4ee8-b1f2-94078732ec74
- 1
-
-8212
16191
40
20
-
-8192
16201
- 1
- 1
- {0}
- false
- Resulting polyline
- 1292e96a-373f-4615-878b-73b06199438a
- Polyline
- Polyline
- false
- 0
-
-8148
16171
38
40
-
-8129
16191
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
- 55428555-7510-47e7-b34a-f9e35f2c711d
- Merge
- Merge
-
-7453
16126
90
64
-
-7408
16158
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- Data stream 1
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- false
- Data 1
- D1
- true
- 8db4425b-83e2-40c4-87be-14b2cc962742
- 1
-
-7451
16128
31
20
-
-7435.5
16138
- 2
- Data stream 2
- 330680e9-fb57-4a38-8d98-f9a023615dc6
- false
- Data 2
- D2
- true
- 1292e96a-373f-4615-878b-73b06199438a
- 1
-
-7451
16148
31
20
-
-7435.5
16158
- 2
- Data stream 3
- b6c59f4a-7a29-43c4-9880-663646ed73c7
- false
- Data 3
- D3
- true
- 0
-
-7451
16168
31
20
-
-7435.5
16178
- 2
- Result of merge
- 5f0869c0-9bc2-45ba-b9bc-7bd6ce42b320
- Result
- Result
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- 0
-
-7396
16128
31
60
-
-7380.5
16158
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- 16f260a6-3bfa-4177-9700-dbd2b19bd644
- Polar Array
- Polar Array
-
-10947
16052
210
101
-
-10801
16103
- Base geometry
- 8ca529ad-ddb5-459f-b521-fa1dfb48965c
- Geometry
- Geometry
- true
- 8139e3a6-7ad0-46d9-9244-0ef47834cdd8
- 1
-
-10945
16054
132
20
-
-10879
16064
- Polar array plane
- 82ce54f1-9164-4aad-accc-a41175a73316
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- Plane
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- 0
-
-10945
16074
132
37
-
-10879
16092.5
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- 1
- {0}
-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
- 3a48ed06-c501-413e-8978-b8dc1375db5e
- Count
- Count
- false
- a36a42bd-2f18-4380-938f-847c2f934c7b
- 1
-
-10945
16111
132
20
-
-10879
16121
- 1
- 1
- {0}
- 4
- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- fcc69342-30ed-45ed-8833-c6aba74d4db8
- Angle
- Angle
- false
- 0
- false
-
-10945
16131
132
20
-
-10879
16141
- 1
- 1
- {0}
- 6.2831853071795862
- 1
- Arrayed geometry
- 1ff37f60-11fa-4998-b09a-100ed37fa4b5
- Geometry
- Geometry
- false
- 0
-
-10789
16054
50
48
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-10764
16078.25
- 1
- Transformation data
- a6adc338-b316-4e18-a5aa-0992c712727d
- Transform
- Transform
- false
- 0
-
-10789
16102
50
49
-
-10764
16126.75
- 6eaffbb2-3392-441a-8556-2dc126aa8910
- Cull Duplicates
- 1
- Cull points that are coincident within tolerance
- true
- f9de9d1c-9d35-4a4f-981b-2fa481c0d868
- Cull Duplicates
- Cull Duplicates
-
-9282
16061
180
64
-
-9155
16093
- 1
- Points to operate on
- f2f14759-281c-41b9-82df-a03f03285868
- Points
- Points
- false
- e87642af-d7f4-4c8a-badf-e9466bf0b858
- 1
-
-9280
16063
113
30
-
-9223.5
16078
- Proximity tolerance distance
- 0353c331-b4a5-43b1-a20e-7a0b43bfd2e5
- Tolerance
- Tolerance
- false
- 0
-
-9280
16093
113
30
-
-9223.5
16108
- 1
- 1
- {0}
- 1.1641532182693481E-10
- 1
- Culled points
- 3fe4e5ef-c18f-4e75-b445-569590545a8e
- Points
- Points
- false
- 0
-
-9143
16063
39
20
-
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16073
- 1
- Index map of culled points
- 9fde27e7-a677-4304-a18f-c2676737d8b0
- Indices
- Indices
- false
- 0
-
-9143
16083
39
20
-
-9123.5
16093
- 1
- Number of input points represented by this output point
- 6f6bcb5e-d048-436c-aa76-f32f093b621e
- Valence
- Valence
- false
- 0
-
-9143
16103
39
20
-
-9123.5
16113
- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
- true
- af6b5adb-149b-4459-9dbf-137428ec716c
- Flip Matrix
- Flip Matrix
-
-9989
16064
78
28
-
-9950
16078
- 2
- Data matrix to flip
- 4728b728-dde9-45ad-a962-6b8d3dc26dd4
- Data
- Data
- false
- 1ff37f60-11fa-4998-b09a-100ed37fa4b5
- 1
-
-9987
16066
25
24
-
-9974.5
16078
- 2
- Flipped data matrix
- 82f35a99-14e7-47ff-900d-a54c896b2c78
- Data
- Data
- false
- 0
-
-9938
16066
25
24
-
-9925.5
16078
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- e5d41782-59e3-422f-8dc1-39d1a4c31f64
- Evaluate Length
- Evaluate Length
-
-11840
16180
149
64
-
-11755
16212
- Curve to evaluate
- fdab1e59-e8a6-4ca8-a6fb-ffc5e907e94c
- Curve
- Curve
- false
- 11ceca9b-30b2-4213-b35d-85e5be45643a
- 1
-
-11838
16182
71
20
-
-11802.5
16192
- Length factor for curve evaluation
- 5e598139-29f5-4d32-9b67-673c1e882f4e
- Length
- Length
- false
- 0
-
-11838
16202
71
20
-
-11802.5
16212
- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 2e3a9590-1657-41a4-b518-a093017be771
- Normalized
- Normalized
- false
- 0
-
-11838
16222
71
20
-
-11802.5
16232
- 1
- 1
- {0}
- true
- Point at the specified length
- 473b46fc-6cd7-4a94-8ca5-b05277cc1d8b
- Point
- Point
- false
- 0
-
-11743
16182
50
20
-
-11718
16192
- Tangent vector at the specified length
- 52a87992-e8a0-4f0f-8c05-55153f97d863
- Tangent
- Tangent
- false
- 0
-
-11743
16202
50
20
-
-11718
16212
- Curve parameter at the specified length
- b130efa6-1671-4814-8eb7-15fed1ab4d7d
- Parameter
- Parameter
- false
- 0
-
-11743
16222
50
20
-
-11718
16232
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- e09ba9cc-f215-4476-a87b-f3262cdad00d
- Polar Array
- Polar Array
-
-10947
16180
210
101
-
-10801
16231
- Base geometry
- 08a3a0e5-ab76-4f85-9791-6ef4be0b9757
- Geometry
- Geometry
- true
- 473b46fc-6cd7-4a94-8ca5-b05277cc1d8b
- 1
-
-10945
16182
132
20
-
-10879
16192
- Polar array plane
- 4437a4ce-48b8-4487-86a8-909e6464789d
- Plane
- Plane
- false
- 0
-
-10945
16202
132
37
-
-10879
16220.5
- 1
- 1
- {0}
-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
- cecf5e04-5877-483f-b076-ffa1ae57d765
- Count
- Count
- false
- a36a42bd-2f18-4380-938f-847c2f934c7b
- 1
-
-10945
16239
132
20
-
-10879
16249
- 1
- 1
- {0}
- 4
- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- 7ec85d43-0d12-4cf3-9654-7e21d2143d62
- Angle
- Angle
- false
- 0
- false
-
-10945
16259
132
20
-
-10879
16269
- 1
- 1
- {0}
- 6.2831853071795862
- 1
- Arrayed geometry
- 81827009-40cb-4a9d-81cd-2bdaedb2032c
- Geometry
- Geometry
- false
- 0
-
-10789
16182
50
48
-
-10764
16206.25
- 1
- Transformation data
- 1dfc6ef3-24e3-4422-8c65-70641f970550
- Transform
- Transform
- false
- 0
-
-10789
16230
50
49
-
-10764
16254.75
- 6eaffbb2-3392-441a-8556-2dc126aa8910
- Cull Duplicates
- 1
- Cull points that are coincident within tolerance
- true
- fe0fc6e9-e5f7-4110-a364-f3890ca938b3
- Cull Duplicates
- Cull Duplicates
-
-9282
16177
180
64
-
-9155
16209
- 1
- Points to operate on
- a3e211f7-c4ad-4867-8204-98cdbb3340d2
- Points
- Points
- false
- 0156a723-76fc-4a7c-8320-97d012f1e76e
- 1
-
-9280
16179
113
30
-
-9223.5
16194
- Proximity tolerance distance
- f068b07d-0de1-42d7-8d2f-b5669a2a9a29
- Tolerance
- Tolerance
- false
- 0
-
-9280
16209
113
30
-
-9223.5
16224
- 1
- 1
- {0}
- 1.1641532182693481E-10
- 1
- Culled points
- 374bcae9-a010-466e-9d02-a93c7753a60d
- Points
- Points
- false
- 0
-
-9143
16179
39
20
-
-9123.5
16189
- 1
- Index map of culled points
- a878cb80-e1bb-449d-8caf-1900890ade4e
- Indices
- Indices
- false
- 0
-
-9143
16199
39
20
-
-9123.5
16209
- 1
- Number of input points represented by this output point
- 7f3f23e9-8b29-441d-86b2-02da645e2b58
- Valence
- Valence
- false
- 0
-
-9143
16219
39
20
-
-9123.5
16229
- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
- true
- e35cce34-d103-45dc-93d5-42459738908e
- Flip Matrix
- Flip Matrix
-
-9989
16192
78
28
-
-9950
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- Stroke
- Applies Stroke properties to a Shape
- true
- f6e61e3a-a382-4f5c-9492-122915e38592
- Stroke
- Stroke
-
-5995
17281
212
104
-
-5845
17333
- A Graphic Plus Shape, or a Curve, Brep, Mesh
- 0b430a89-5c68-4b7e-9f4c-5b801713e699
- Shape / Geometry
- Shape / Geometry
- false
- bc172503-953b-42d6-9f6c-01e9cdbf6da9
- 1
-
-5993
17283
136
20
-
-5925
17293
- The stroke color
- 41e2b278-73d3-4577-b3ff-d52999f2df92
- Color
- Color
- true
- 5d585ae3-4a99-4be5-a4d5-4354c3267ffe
- 1
-
-5993
17303
136
20
-
-5925
17313
- 1
- 1
- {0}
-
255;21;0;255
- The stroke weight
- b3028dec-57fe-46a7-8d26-9b740b41f34c
- Weight
- Weight
- true
- e7c315e7-6046-4360-a3b1-dc1f18620e40
- 1
-
-5993
17323
136
20
-
-5925
17333
- 1
- 1
- {0}
- 9
- 1
- The stroke pattern
- e06b7cea-813c-493a-b99d-44255dc7076b
- Pattern
- Pattern
- true
- 0
-
-5993
17343
136
20
-
-5925
17353
- The shape to be used at the end of open path
- ac47fdcd-c4a0-47fe-934c-7abccec6e33a
- End Cap
- End Cap
- true
- 0
-
-5993
17363
136
20
-
-5925
17373
- 1
- 1
- {0}
- 2
- A Graphic Plus Shape Object
- true
- e8350921-bce9-4dab-befe-7c6e8c133aeb
- 1
- Shape
- Shape
- false
- 0
-
-5833
17283
48
100
-
-5817
17333
- 071c3940-a12d-4b77-bb23-42b5d3314a0d
- Clean Tree
- Removed all null and invalid items from a data tree.
- true
- d995efc2-7519-4417-ae0a-d36bf296b9f7
- Clean Tree
- Clean Tree
-
-6829
17257
135
84
-
-6732
17299
- 4
- cb95db89-6165-43b6-9c41-5702bc5bf137
- cb95db89-6165-43b6-9c41-5702bc5bf137
- cb95db89-6165-43b6-9c41-5702bc5bf137
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Remove null items from the tree.
- 6782aa1f-a2bf-49dd-b7f4-cc4138a697d5
- Remove Nulls
- Remove Nulls
- false
- 0
-
-6827
17259
83
20
-
-6785.5
17269
- 1
- 1
- {0}
- true
- Remove invalid items from the tree.
- ee053123-99d9-4c17-9a85-9dd25085669a
- Remove Invalid
- Remove Invalid
- false
- 0
-
-6827
17279
83
20
-
-6785.5
17289
- 1
- 1
- {0}
- true
- Remove empty branches from the tree.
- 6c263a19-fcf7-42c1-a05f-6297b0615acd
- Remove Empty
- Remove Empty
- false
- 0
-
-6827
17299
83
20
-
-6785.5
17309
- 1
- 1
- {0}
- true
- 2
- Data tree to clean
- 0786fe94-2693-4e2f-a530-ba3f25454d65
- Tree
- Tree
- false
- 91b737a8-c046-47f6-8f04-9f251cd03527
- 1
-
-6827
17319
83
20
-
-6785.5
17329
- 2
- Spotless data tree
- bc172503-953b-42d6-9f6c-01e9cdbf6da9
- Tree
- Tree
- false
- 0
-
-6720
17259
24
80
-
-6708
17299
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 02737097-b8b1-41db-98c1-fc50380663f5
- Evaluate Length
- Evaluate Length
-
-11840
17223
149
64
-
-11755
17255
- Curve to evaluate
- 2a5446b7-932d-41bb-aad7-99f4765a1b0c
- Curve
- Curve
- false
- 2f545125-747a-4904-9cb7-05bc0727e11d
- 1
-
-11838
17225
71
20
-
-11802.5
17235
- Length factor for curve evaluation
- 97db9dfb-d83f-43bc-aa6c-74315e99c866
- Length
- Length
- false
- 0
-
-11838
17245
71
20
-
-11802.5
17255
- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- b97a0607-d9c4-424b-bf06-962419323acb
- Normalized
- Normalized
- false
- 0
-
-11838
17265
71
20
-
-11802.5
17275
- 1
- 1
- {0}
- true
- Point at the specified length
- f264c5ca-1559-4c36-92b0-2d97232c46ad
- Point
- Point
- false
- 0
-
-11743
17225
50
20
-
-11718
17235
- Tangent vector at the specified length
- 8a1eee52-af70-4242-b077-63631f092dd9
- Tangent
- Tangent
- false
- 0
-
-11743
17245
50
20
-
-11718
17255
- Curve parameter at the specified length
- 2f54eb4c-185e-4cf1-a1fd-9e1135d4fa77
- Parameter
- Parameter
- false
- 0
-
-11743
17265
50
20
-
-11718
17275
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
- true
- e0561d63-9b13-44a4-b9ea-99a9cb1c13e2
- PolyLine
- PolyLine
-
-8214
17269
106
44
-
-8160
17291
- 1
- Polyline vertex points
- 528e6586-6ecf-40b3-a743-0d6f9fe0bfbb
- Vertices
- Vertices
- false
- 1c9cf092-7009-4949-8f7f-f9236794e9fe
- 1
-
-8212
17271
40
20
-
-8192
17281
- Close polyline
- d00b5e18-77f2-45e7-9369-4182df4cb587
- Closed
- Closed
- false
- bf9476b7-1f42-4ee8-b1f2-94078732ec74
- 1
-
-8212
17291
40
20
-
-8192
17301
- 1
- 1
- {0}
- true
- Resulting polyline
- ced6c00c-4ac4-4fb8-8f0e-7f436ffdab13
- Polyline
- Polyline
- false
- 0
-
-8148
17271
38
40
-
-8129
17291
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
- true
- dbe88505-9526-40fb-9e1b-1d78e902c27b
- PolyLine
- PolyLine
-
-8214
17340
106
44
-
-8160
17362
- 1
- Polyline vertex points
- 1c49aba5-694f-462f-a831-11170af53bec
- Vertices
- Vertices
- false
- 9349eef4-58b8-408a-a0c5-e579ddf40767
- 1
-
-8212
17342
40
20
-
-8192
17352
- Close polyline
- 8233a329-2e4f-44bd-96f8-223124a1bc74
- Closed
- Closed
- false
- bf9476b7-1f42-4ee8-b1f2-94078732ec74
- 1
-
-8212
17362
40
20
-
-8192
17372
- 1
- 1
- {0}
- false
- Resulting polyline
- 1207f491-dbbb-4093-b3ad-3c374a18a952
- Polyline
- Polyline
- false
- 0
-
-8148
17342
38
40
-
-8129
17362
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
- b45fdf0c-87e6-4bba-86a6-8fed07429172
- Merge
- Merge
-
-7453
17297
90
64
-
-7408
17329
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2
- Data stream 1
- 485cb551-bbd8-419d-8466-46125ba0477f
- false
- Data 1
- D1
- true
- ced6c00c-4ac4-4fb8-8f0e-7f436ffdab13
- 1
-
-7451
17299
31
20
-
-7435.5
17309
- 2
- Data stream 2
- 25ff9633-f2c4-4e2e-9a91-bc534e46c8cc
- false
- Data 2
- D2
- true
- 1207f491-dbbb-4093-b3ad-3c374a18a952
- 1
-
-7451
17319
31
20
-
-7435.5
17329
- 2
- Data stream 3
- 038257c2-b3a0-4434-aaa7-dda6c93c1836
- false
- Data 3
- D3
- true
- 0
-
-7451
17339
31
20
-
-7435.5
17349
- 2
- Result of merge
- 91b737a8-c046-47f6-8f04-9f251cd03527
- Result
- Result
- false
- 0
-
-7396
17299
31
60
-
-7380.5
17329
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- 7c40bd65-f93b-4501-8448-a9384bf4ddce
- Polar Array
- Polar Array
-
-10947
17223
210
101
-
-10801
17274
- Base geometry
- 09e1489a-38c3-4586-a46e-83107b7f002a
- Geometry
- Geometry
- true
- f264c5ca-1559-4c36-92b0-2d97232c46ad
- 1
-
-10945
17225
132
20
-
-10879
17235
- Polar array plane
- 764fb3a2-368f-4b97-93ef-08ec580daf72
- Plane
- Plane
- false
- 0
-
-10945
17245
132
37
-
-10879
17263.5
- 1
- 1
- {0}
-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
- f82733ea-5617-4886-bc83-2fe7b3095cdc
- Count
- Count
- false
- a36a42bd-2f18-4380-938f-847c2f934c7b
- 1
-
-10945
17282
132
20
-
-10879
17292
- 1
- 1
- {0}
- 4
- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- 6800c134-8e8f-44a1-9722-8a746870d50a
- Angle
- Angle
- false
- 0
- false
-
-10945
17302
132
20
-
-10879
17312
- 1
- 1
- {0}
- 6.2831853071795862
- 1
- Arrayed geometry
- 23d7f84a-bc05-46db-b2ea-0f7b23826746
- Geometry
- Geometry
- false
- 0
-
-10789
17225
50
48
-
-10764
17249.25
- 1
- Transformation data
- 7722b4a9-f344-48f8-b43d-c047dcd621a7
- Transform
- Transform
- false
- 0
-
-10789
17273
50
49
-
-10764
17297.75
- 6eaffbb2-3392-441a-8556-2dc126aa8910
- Cull Duplicates
- 1
- Cull points that are coincident within tolerance
- true
- 9887bd44-97bb-4024-9f89-c1252834018a
- Cull Duplicates
- Cull Duplicates
-
-9282
17232
180
64
-
-9155
17264
- 1
- Points to operate on
- e79e43c6-1e2b-46be-8454-f2a5d0a9e7a3
- Points
- Points
- false
- d3503a0a-25d4-40f9-b392-12c89e516f16
- 1
-
-9280
17234
113
30
-
-9223.5
17249
- Proximity tolerance distance
- 26c15905-27a6-4859-83f1-faa8fec300f6
- Tolerance
- Tolerance
- false
- 0
-
-9280
17264
113
30
-
-9223.5
17279
- 1
- 1
- {0}
- 1.1641532182693481E-10
- 1
- Culled points
- 1c9cf092-7009-4949-8f7f-f9236794e9fe
- Points
- Points
- false
- 0
-
-9143
17234
39
20
-
-9123.5
17244
- 1
- Index map of culled points
- 7359f5b0-78b4-4f91-80f2-ac08726f8f96
- Indices
- Indices
- false
- 0
-
-9143
17254
39
20
-
-9123.5
17264
- 1
- Number of input points represented by this output point
- a8c0bb0c-fdc4-47b0-b658-845db3b475f1
- Valence
- Valence
- false
- 0
-
-9143
17274
39
20
-
-9123.5
17284
- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
- true
- b5d93ecd-2ef1-4b68-b74f-be0a5cca1d2b
- Flip Matrix
- Flip Matrix
-
-9989
17235
78
28
-
-9950
17249
- 2
- Data matrix to flip
- 32e8694b-97fc-455a-9d25-12c6106e2bec
- Data
- Data
- false
- 23d7f84a-bc05-46db-b2ea-0f7b23826746
- 1
-
-9987
17237
25
24
-
-9974.5
17249
- 2
- Flipped data matrix
- 6de70eee-64cc-4d17-ad90-5e27d252e6e5
- Data
- Data
- false
- 0
-
-9938
17237
25
24
-
-9925.5
17249
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- e44419a3-3e7b-451b-ad2b-befe815a1642
- Evaluate Length
- Evaluate Length
-
-11840
17351
149
64
-
-11755
17383
- Curve to evaluate
- f21d970a-0a31-4084-abcd-1f722bb29097
- Curve
- Curve
- false
- 29946d34-0db3-4cc0-bbb0-27c79f7c8eb9
- 1
-
-11838
17353
71
20
-
-11802.5
17363
- Length factor for curve evaluation
- 7d649dc5-fa68-41b5-aa84-d93b3189a6d1
- Length
- Length
- false
- 0
-
-11838
17373
71
20
-
-11802.5
17383
- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 39b0d8c4-19df-4207-ad20-b62f10657d75
- Normalized
- Normalized
- false
- 0
-
-11838
17393
71
20
-
-11802.5
17403
- 1
- 1
- {0}
- true
- Point at the specified length
- e2dea9a1-a097-4340-b25a-e37176bd7740
- Point
- Point
- false
- 0
-
-11743
17353
50
20
-
-11718
17363
- Tangent vector at the specified length
- c761ff1f-1345-4339-b98a-8f8a9a16ae44
- Tangent
- Tangent
- false
- 0
-
-11743
17373
50
20
-
-11718
17383
- Curve parameter at the specified length
- 81533d08-e4df-4b3d-b9b6-a85448cf8ead
- Parameter
- Parameter
- false
- 0
-
-11743
17393
50
20
-
-11718
17403
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- af57175f-b87d-4d4b-865c-8de67eb6f48c
- Polar Array
- Polar Array
-
-10947
17351
210
101
-
-10801
17402
- Base geometry
- f22d30c8-4b4b-4cea-9ec0-0edbc8672688
- Geometry
- Geometry
- true
- e2dea9a1-a097-4340-b25a-e37176bd7740
- 1
-
-10945
17353
132
20
-
-10879
17363
- Polar array plane
- 99756a04-f589-4b3d-9f05-522affd1de67
- Plane
- Plane
- false
- 0
-
-10945
17373
132
37
-
-10879
17391.5
- 1
- 1
- {0}
-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
- 840959dc-1048-4e82-9559-88d1802886bb
- Count
- Count
- false
- a36a42bd-2f18-4380-938f-847c2f934c7b
- 1
-
-10945
17410
132
20
-
-10879
17420
- 1
- 1
- {0}
- 4
- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- 31487356-e2ba-44a1-a310-e5120d4ff151
- Angle
- Angle
- false
- 0
- false
-
-10945
17430
132
20
-
-10879
17440
- 1
- 1
- {0}
- 6.2831853071795862
- 1
- Arrayed geometry
- 90282863-2ca2-4350-a4f0-8ba50b257398
- Geometry
- Geometry
- false
- 0
-
-10789
17353
50
48
-
-10764
17377.25
- 1
- Transformation data
- b7364e57-5ffd-4559-9ef0-07aedc662109
- Transform
- Transform
- false
- 0
-
-10789
17401
50
49
-
-10764
17425.75
- 6eaffbb2-3392-441a-8556-2dc126aa8910
- Cull Duplicates
- 1
- Cull points that are coincident within tolerance
- true
- a2446556-35a4-42a2-992b-4c5465def5ca
- Cull Duplicates
- Cull Duplicates
-
-9282
17348
180
64
-
-9155
17380
- 1
- Points to operate on
- 176aa800-b998-4c0a-9503-57c602bcda9e
- Points
- Points
- false
- 4dfda7fb-90ae-4f9e-9305-08baf23c2d50
- 1
-
-9280
17350
113
30
-
-9223.5
17365
- Proximity tolerance distance
- cb095ab5-a871-4ea2-ae23-443a1fbeee58
- Tolerance
- Tolerance
- false
- 0
-
-9280
17380
113
30
-
-9223.5
17395
- 1
- 1
- {0}
- 1.1641532182693481E-10
- 1
- Culled points
- 9349eef4-58b8-408a-a0c5-e579ddf40767
- Points
- Points
- false
- 0
-
-9143
17350
39
20
-
-9123.5
17360
- 1
- Index map of culled points
- 26dd8312-d3ae-477c-9e0c-1009f60f5c95
- Indices
- Indices
- false
- 0
-
-9143
17370
39
20
-
-9123.5
17380
- 1
- Number of input points represented by this output point
- c419d320-3140-47d8-8d0d-fc6df26eece9
- Valence
- Valence
- false
- 0
-
-9143
17390
39
20
-
-9123.5
17400
- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
- true
- 14074e3a-0c4f-43d3-8ef6-6d6fa0d55c7b
- Flip Matrix
- Flip Matrix
-
-9989
17363
78
28
-
-9950
17377
- 2
- Data matrix to flip
- 4bf40f1b-5da2-40d3-a958-12d3c3d9ad5e
- Data
- Data
- false
- 90282863-2ca2-4350-a4f0-8ba50b257398
- 1
-
-9987
17365
25
24
-
-9974.5
17377
- 2
- Flipped data matrix
- 87fdae07-bcf5-489b-89b1-aec57ffa9c17
- Data
- Data
- false
- 0
-
-9938
17365
25
24
-
-9925.5
17377
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 2f545125-747a-4904-9cb7-05bc0727e11d
- Relay
- false
- 598eec7f-8923-45a9-bb06-9d39462f5b42
- 1
-
-12721
17241
40
16
-
-12701
17249
- b6236720-8d88-4289-93c3-ac4c99f9b97b
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18424
136
20
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18434
- 1
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- {0}
- 9
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- The stroke pattern
- 1c98149e-e677-40ca-aaec-c82501e35e88
- Pattern
- Pattern
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-
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18444
136
20
-
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18454
- The shape to be used at the end of open path
- 82225c16-8dba-42a0-9a33-7130e468373b
- End Cap
- End Cap
- true
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-
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18464
136
20
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18474
- 1
- 1
- {0}
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- A Graphic Plus Shape Object
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- 0e15a768-0ee5-4b2c-8524-5d790cc8917d
- 1
- Shape
- Shape
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- 0
-
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18384
48
100
-
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18434
- 071c3940-a12d-4b77-bb23-42b5d3314a0d
- Clean Tree
- Removed all null and invalid items from a data tree.
- true
- b78ab8de-5b2e-4309-9c68-2222a272421b
- Clean Tree
- Clean Tree
-
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18358
135
84
-
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18400
- 4
- cb95db89-6165-43b6-9c41-5702bc5bf137
- cb95db89-6165-43b6-9c41-5702bc5bf137
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- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Remove null items from the tree.
- e4c683fe-95ce-4292-867b-df623aa4a2b6
- Remove Nulls
- Remove Nulls
- false
- 0
-
-6827
18360
83
20
-
-6785.5
18370
- 1
- 1
- {0}
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- Remove invalid items from the tree.
- bfa076b6-fb4b-40d6-be9f-67fb884e8d6c
- Remove Invalid
- Remove Invalid
- false
- 0
-
-6827
18380
83
20
-
-6785.5
18390
- 1
- 1
- {0}
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- Remove empty branches from the tree.
- 329824a3-1ac9-4d57-9735-a29b88f515c5
- Remove Empty
- Remove Empty
- false
- 0
-
-6827
18400
83
20
-
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18410
- 1
- 1
- {0}
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- 2
- Data tree to clean
- a38d6fc8-c43a-4b4a-9553-733995115f34
- Tree
- Tree
- false
- 625c9542-af93-4f62-aed4-573bb02b38ee
- 1
-
-6827
18420
83
20
-
-6785.5
18430
- 2
- Spotless data tree
- 60a0df0e-bd21-4cdf-a3f4-16fb4176c3ae
- Tree
- Tree
- false
- 0
-
-6720
18360
24
80
-
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18400
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- fd943d99-68a3-4898-b506-68be67cd4cf2
- Evaluate Length
- Evaluate Length
-
-11840
18324
149
64
-
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18356
- Curve to evaluate
- 21446a6b-2f2d-4abc-a8c3-b71cb39432c9
- Curve
- Curve
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- 1504e2b4-e091-439c-ace1-a3e70d52839d
- 1
-
-11838
18326
71
20
-
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18336
- Length factor for curve evaluation
- 80653072-e8be-483c-a4a2-f30d6bd332e8
- Length
- Length
- false
- 0
-
-11838
18346
71
20
-
-11802.5
18356
- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- ced79bb1-e361-42a4-89f7-a85a93ea6d28
- Normalized
- Normalized
- false
- 0
-
-11838
18366
71
20
-
-11802.5
18376
- 1
- 1
- {0}
- true
- Point at the specified length
- 7b21e7c4-e20e-484d-818d-a663768d8508
- Point
- Point
- false
- 0
-
-11743
18326
50
20
-
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18336
- Tangent vector at the specified length
- c4a0d5f8-e9f9-4097-afb7-0f148a2fc879
- Tangent
- Tangent
- false
- 0
-
-11743
18346
50
20
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- Curve parameter at the specified length
- 74969c75-1dd5-4e4d-ad34-4225f6ae85e0
- Parameter
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-
-11743
18366
50
20
-
-11718
18376
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
- true
- a2436e8a-9975-43b5-8abc-89e175cb9bcd
- PolyLine
- PolyLine
-
-8214
18370
106
44
-
-8160
18392
- 1
- Polyline vertex points
- 5062ab4b-7936-4329-a512-9a867699e9d8
- Vertices
- Vertices
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- efa1592b-bbf9-4d3b-9415-7562319eaad4
- 1
-
-8212
18372
40
20
-
-8192
18382
- Close polyline
- e11365c4-bde5-47cf-845b-e1c75c83629b
- Closed
- Closed
- false
- bf9476b7-1f42-4ee8-b1f2-94078732ec74
- 1
-
-8212
18392
40
20
-
-8192
18402
- 1
- 1
- {0}
- true
- Resulting polyline
- 4713e6bd-a9c4-4e05-984f-ea9377a0e684
- Polyline
- Polyline
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- 0
-
-8148
18372
38
40
-
-8129
18392
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
- true
- fb1f3eff-3a65-4bda-9df9-54842bb38cd9
- PolyLine
- PolyLine
-
-8214
18441
106
44
-
-8160
18463
- 1
- Polyline vertex points
- 4bd91e38-4208-49d6-bc7c-3b81596309b1
- Vertices
- Vertices
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- ffd681a6-6a65-4c1f-9085-7033988b0b32
- 1
-
-8212
18443
40
20
-
-8192
18453
- Close polyline
- 02d0af90-446c-49a4-af64-6a50853b6df9
- Closed
- Closed
- false
- bf9476b7-1f42-4ee8-b1f2-94078732ec74
- 1
-
-8212
18463
40
20
-
-8192
18473
- 1
- 1
- {0}
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- Resulting polyline
- d0ac4694-9cbb-408e-a7c4-fe13ed702009
- Polyline
- Polyline
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- 0
-
-8148
18443
38
40
-
-8129
18463
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
- a8f9a73d-06ad-4ff7-a9f6-5af2990ec6f6
- Merge
- Merge
-
-7453
18398
90
64
-
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18430
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- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- Data stream 1
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- Data 1
- D1
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- 4713e6bd-a9c4-4e05-984f-ea9377a0e684
- 1
-
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18400
31
20
-
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18410
- 2
- Data stream 2
- 8a35825f-12c6-4369-b4a8-095ea5853786
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- Data 2
- D2
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- d0ac4694-9cbb-408e-a7c4-fe13ed702009
- 1
-
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18420
31
20
-
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18430
- 2
- Data stream 3
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- Data 3
- D3
- true
- 0
-
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18440
31
20
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18450
- 2
- Result of merge
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-
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18400
31
60
-
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18430
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- c605e62b-d6b6-4e76-91bb-368d21f313f5
- Polar Array
- Polar Array
-
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18324
210
101
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18375
- Base geometry
- 9e87d25c-f926-4f0e-9456-35e638186c1d
- Geometry
- Geometry
- true
- 7b21e7c4-e20e-484d-818d-a663768d8508
- 1
-
-10945
18326
132
20
-
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18336
- Polar array plane
- 697e3b87-e310-46b2-807a-5dab2983da65
- Plane
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-
-10945
18346
132
37
-
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18364.5
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- 1
- {0}
-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
- 50e55b22-9ec1-4670-b88a-e1f7bcdf83c0
- Count
- Count
- false
- a36a42bd-2f18-4380-938f-847c2f934c7b
- 1
-
-10945
18383
132
20
-
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18393
- 1
- 1
- {0}
- 4
- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- 574e6b39-ce22-4257-b82d-a817ecf2b838
- Angle
- Angle
- false
- 0
- false
-
-10945
18403
132
20
-
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18413
- 1
- 1
- {0}
- 6.2831853071795862
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- Arrayed geometry
- 2b5ab43a-bf29-46b7-97f8-b9a1e5f5505d
- Geometry
- Geometry
- false
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-
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18326
50
48
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18350.25
- 1
- Transformation data
- 9d851bcf-7c36-4420-a968-df9aea2eeabe
- Transform
- Transform
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-
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18374
50
49
-
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18398.75
- 6eaffbb2-3392-441a-8556-2dc126aa8910
- Cull Duplicates
- 1
- Cull points that are coincident within tolerance
- true
- 22c8303a-ab41-4056-b0f0-d75617008c03
- Cull Duplicates
- Cull Duplicates
-
-9282
18333
180
64
-
-9155
18365
- 1
- Points to operate on
- db3726a7-ccba-464a-9d6c-4365a485eaa6
- Points
- Points
- false
- 3b0f4ca8-63aa-4144-82ce-e47ac4bbb7e5
- 1
-
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18335
113
30
-
-9223.5
18350
- Proximity tolerance distance
- 10e85b55-fe13-40a0-b8a2-043f1dddde10
- Tolerance
- Tolerance
- false
- 0
-
-9280
18365
113
30
-
-9223.5
18380
- 1
- 1
- {0}
- 1.1641532182693481E-10
- 1
- Culled points
- efa1592b-bbf9-4d3b-9415-7562319eaad4
- Points
- Points
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- 0
-
-9143
18335
39
20
-
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18345
- 1
- Index map of culled points
- 3aca07e1-b1b8-44f0-81b1-8d23b1d0bb0f
- Indices
- Indices
- false
- 0
-
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18355
39
20
-
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18365
- 1
- Number of input points represented by this output point
- 50ed2f1f-0e8b-46b5-b32e-bdbe742f4fc2
- Valence
- Valence
- false
- 0
-
-9143
18375
39
20
-
-9123.5
18385
- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
- true
- ddafa6fc-5d20-4aaa-86d7-657fc631898f
- Flip Matrix
- Flip Matrix
-
-9989
18336
78
28
-
-9950
18350
- 2
- Data matrix to flip
- 4a24e956-c5f1-4b2a-9f10-68d207dcd243
- Data
- Data
- false
- 2b5ab43a-bf29-46b7-97f8-b9a1e5f5505d
- 1
-
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18338
25
24
-
-9974.5
18350
- 2
- Flipped data matrix
- 7e35038d-d7b3-4169-a2e1-ee147c9aa897
- Data
- Data
- false
- 0
-
-9938
18338
25
24
-
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18350
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- b06ef032-a6e7-4452-9651-12a4aa2e7cec
- Evaluate Length
- Evaluate Length
-
-11840
18452
149
64
-
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18484
- Curve to evaluate
- 2c14f2cf-46ba-4918-8f1c-b3272ba74995
- Curve
- Curve
- false
- 587de0b9-9f06-4d87-bf93-b93668a84499
- 1
-
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18454
71
20
-
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- Length factor for curve evaluation
- de6d2a10-b91a-4a82-a095-c0c9229e0510
- Length
- Length
- false
- 0
-
-11838
18474
71
20
-
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18484
- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 32924ee0-ca83-49e6-845a-57621ca8781b
- Normalized
- Normalized
- false
- 0
-
-11838
18494
71
20
-
-11802.5
18504
- 1
- 1
- {0}
- true
- Point at the specified length
- ab1cebea-9440-45d3-b22a-729e57d3f393
- Point
- Point
- false
- 0
-
-11743
18454
50
20
-
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18464
- Tangent vector at the specified length
- c4f283c6-130d-4973-b31d-0b4e1e300c93
- Tangent
- Tangent
- false
- 0
-
-11743
18474
50
20
-
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18484
- Curve parameter at the specified length
- f8e517ea-def4-4d7a-b176-d494f464103b
- Parameter
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- false
- 0
-
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18494
50
20
-
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18504
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- 613d5bca-f997-48a6-99da-2794f7a3babf
- Polar Array
- Polar Array
-
-10947
18452
210
101
-
-10801
18503
- Base geometry
- 863bdee8-d814-4028-a927-080f2ae9d329
- Geometry
- Geometry
- true
- ab1cebea-9440-45d3-b22a-729e57d3f393
- 1
-
-10945
18454
132
20
-
-10879
18464
- Polar array plane
- af140e57-5203-44d4-b935-2c282782fc2f
- Plane
- Plane
- false
- 0
-
-10945
18474
132
37
-
-10879
18492.5
- 1
- 1
- {0}
-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
- f07b7b89-6eed-4d38-bbd7-03d43ae2b722
- Count
- Count
- false
- a36a42bd-2f18-4380-938f-847c2f934c7b
- 1
-
-10945
18511
132
20
-
-10879
18521
- 1
- 1
- {0}
- 4
- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- 4334bf6d-2032-41a4-94b1-ab89a78e6cb8
- Angle
- Angle
- false
- 0
- false
-
-10945
18531
132
20
-
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18541
- 1
- 1
- {0}
- 6.2831853071795862
- 1
- Arrayed geometry
- 5b1d4834-80d0-4db9-ac90-af4511687158
- Geometry
- Geometry
- false
- 0
-
-10789
18454
50
48
-
-10764
18478.25
- 1
- Transformation data
- e5d1d1bc-46cb-4015-8dfd-098bb74775d3
- Transform
- Transform
- false
- 0
-
-10789
18502
50
49
-
-10764
18526.75
- 6eaffbb2-3392-441a-8556-2dc126aa8910
- Cull Duplicates
- 1
- Cull points that are coincident within tolerance
- true
- 7da63af0-39d5-4057-9777-ed62661c16b2
- Cull Duplicates
- Cull Duplicates
-
-9282
18449
180
64
-
-9155
18481
- 1
- Points to operate on
- 38f185c5-7c31-409b-abb8-cca7ff4ae1ac
- Points
- Points
- false
- 7415449f-d53b-4906-8899-d2695a78b338
- 1
-
-9280
18451
113
30
-
-9223.5
18466
- Proximity tolerance distance
- a1c113c7-5886-4257-a65f-cc641c5d5e71
- Tolerance
- Tolerance
- false
- 0
-
-9280
18481
113
30
-
-9223.5
18496
- 1
- 1
- {0}
- 1.1641532182693481E-10
- 1
- Culled points
- ffd681a6-6a65-4c1f-9085-7033988b0b32
- Points
- Points
- false
- 0
-
-9143
18451
39
20
-
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18461
- 1
- Index map of culled points
- b9843477-48d7-4054-b06a-b93861e7f600
- Indices
- Indices
- false
- 0
-
-9143
18471
39
20
-
-9123.5
18481
- 1
- Number of input points represented by this output point
- 37d80b0c-37cc-4b41-8b86-0405fac43c2d
- Valence
- Valence
- false
- 0
-
-9143
18491
39
20
-
-9123.5
18501
- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
- true
- d3afd561-a88c-4672-82f5-740dd875dd98
- Flip Matrix
- Flip Matrix
-
-9989
18464
78
28
-
-9950
18478
- 2
- Data matrix to flip
- f0fd6251-e51b-4d26-a996-a53e51e57a84
- Data
- Data
- false
- 5b1d4834-80d0-4db9-ac90-af4511687158
- 1
-
-9987
18466
25
24
-
-9974.5
18478
- 2
- Flipped data matrix
- eb27fc67-93d3-4155-93e7-01f56e95a084
- Data
- Data
- false
- 0
-
-9938
18466
25
24
-
-9925.5
18478
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 1504e2b4-e091-439c-ace1-a3e70d52839d
- Relay
- false
- 56e8bb2d-4b74-4665-8007-49becf882746
- 1
-
-12721
18345
40
16
-
-12701
18353
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 587de0b9-9f06-4d87-bf93-b93668a84499
- Relay
- false
- 4106a4b6-ae1e-4c1a-aa13-89f01b1f0d6e
- 1
-
-12721
18493
40
16
-
-12701
18501
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- 1504e2b4-e091-439c-ace1-a3e70d52839d
- 587de0b9-9f06-4d87-bf93-b93668a84499
- 2
- 653f1ce8-71ff-4bd6-8b5b-9fd09ed2f5ac
- Group
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
- 876934e9-655e-4c18-8ecc-1f5a9916c57f
- Merge
- Merge
-
-5154
18529
106
84
-
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18571
- 4
- 8ec86459-bf01-4409-baee-174d0d2b13d0
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19861
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19576
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- Clean Tree
- Clean Tree
-
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19500
135
84
-
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19542
- 4
- cb95db89-6165-43b6-9c41-5702bc5bf137
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- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Remove null items from the tree.
- 0f9342ec-919d-4b4c-a28b-d12739f46578
- Remove Nulls
- Remove Nulls
- false
- 0
-
-6827
19502
83
20
-
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19512
- 1
- 1
- {0}
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- Remove invalid items from the tree.
- 0c3fecef-2554-4bfa-adc7-e0de3a33ea8a
- Remove Invalid
- Remove Invalid
- false
- 0
-
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19522
83
20
-
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19532
- 1
- 1
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- Remove empty branches from the tree.
- 7371a2b2-d381-459e-affc-3d53ad85deb8
- Remove Empty
- Remove Empty
- false
- 0
-
-6827
19542
83
20
-
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19552
- 1
- 1
- {0}
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- 2
- Data tree to clean
- b9a404d9-8458-4fe8-abe1-ed12c7d32048
- Tree
- Tree
- false
- 160c7d88-f5b0-4294-bfa1-649a8ee28944
- 1
-
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19562
83
20
-
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19572
- 2
- Spotless data tree
- 44d4ba80-f520-479f-8909-f0d56df54de0
- Tree
- Tree
- false
- 0
-
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19502
24
80
-
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19542
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- fa291861-d949-4bce-b86b-6a37fa2376ef
- Evaluate Length
- Evaluate Length
-
-11840
19466
149
64
-
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19498
- Curve to evaluate
- 7798e05f-f37b-4bad-bd28-0692dc3524f4
- Curve
- Curve
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- 49eeb6cb-33ad-4c36-b3da-903f4f48a3dc
- 1
-
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19468
71
20
-
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19478
- Length factor for curve evaluation
- 606142ac-ca1e-4256-abb7-6816d1878fce
- Length
- Length
- false
- 0
-
-11838
19488
71
20
-
-11802.5
19498
- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 14d537d2-cda1-49e1-b5f6-1c4b41224094
- Normalized
- Normalized
- false
- 0
-
-11838
19508
71
20
-
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19518
- 1
- 1
- {0}
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- Point at the specified length
- f10c4e95-dbce-468a-9c4e-100f931a3443
- Point
- Point
- false
- 0
-
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19468
50
20
-
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19478
- Tangent vector at the specified length
- 315b4d59-1f34-4249-9641-c9da074f79ed
- Tangent
- Tangent
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- 0
-
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19488
50
20
-
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19498
- Curve parameter at the specified length
- 514bac3d-628b-44d0-98f0-6f1bef253852
- Parameter
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- false
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-
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19508
50
20
-
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19518
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
- true
- da18f131-7a27-40bc-b68d-7f901b717384
- PolyLine
- PolyLine
-
-8214
19512
106
44
-
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19534
- 1
- Polyline vertex points
- 6f49cf12-1468-4634-813e-de6e70e9612f
- Vertices
- Vertices
- false
- 3606ae1a-a45f-48d1-a992-4ac71a0775e4
- 1
-
-8212
19514
40
20
-
-8192
19524
- Close polyline
- 694a68d4-97a8-4a7d-84cd-0664b93e4c50
- Closed
- Closed
- false
- bf9476b7-1f42-4ee8-b1f2-94078732ec74
- 1
-
-8212
19534
40
20
-
-8192
19544
- 1
- 1
- {0}
- true
- Resulting polyline
- 52b4596b-5174-4b48-af16-45f55b685c27
- Polyline
- Polyline
- false
- 0
-
-8148
19514
38
40
-
-8129
19534
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
- true
- c34fa604-6cdc-4331-84e4-5f9370955b30
- PolyLine
- PolyLine
-
-8214
19583
106
44
-
-8160
19605
- 1
- Polyline vertex points
- d5d9eae5-8d8d-460d-a0b3-58cf1135a14f
- Vertices
- Vertices
- false
- 24b409ff-5abd-4ba7-9d16-73e6c5e16e28
- 1
-
-8212
19585
40
20
-
-8192
19595
- Close polyline
- c8ed8166-34f1-462d-8911-718cfdb56a67
- Closed
- Closed
- false
- bf9476b7-1f42-4ee8-b1f2-94078732ec74
- 1
-
-8212
19605
40
20
-
-8192
19615
- 1
- 1
- {0}
- false
- Resulting polyline
- 5d541f70-e0c5-4828-8290-1655d1ce11b3
- Polyline
- Polyline
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- 0
-
-8148
19585
38
40
-
-8129
19605
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
- 4c517ba1-39e4-45fa-9c9c-a8787379bb0a
- Merge
- Merge
-
-7453
19540
90
64
-
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19572
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- Data stream 1
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- Data 1
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- 52b4596b-5174-4b48-af16-45f55b685c27
- 1
-
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19542
31
20
-
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19552
- 2
- Data stream 2
- 9398cba2-7a4e-4fc2-91d8-b33acb298ec7
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- Data 2
- D2
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- 5d541f70-e0c5-4828-8290-1655d1ce11b3
- 1
-
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19562
31
20
-
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19572
- 2
- Data stream 3
- 0ce5fac0-dced-4a1a-96da-0f97013002f3
- false
- Data 3
- D3
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- 0
-
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19582
31
20
-
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19592
- 2
- Result of merge
- 160c7d88-f5b0-4294-bfa1-649a8ee28944
- Result
- Result
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-
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19542
31
60
-
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19572
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- 020d7e9b-2333-4de8-bef4-92bdc9ea1505
- Polar Array
- Polar Array
-
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19466
210
101
-
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19517
- Base geometry
- b1b2e24f-e9ab-4202-b7fa-96d1c47258be
- Geometry
- Geometry
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- f10c4e95-dbce-468a-9c4e-100f931a3443
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-
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19468
132
20
-
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19478
- Polar array plane
- 1558e996-4d1c-4d72-a912-95d6ba270793
- Plane
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-
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19488
132
37
-
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19506.5
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- {0}
-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
- f10a5f6c-fe96-4f15-a391-fe9821719d93
- Count
- Count
- false
- a36a42bd-2f18-4380-938f-847c2f934c7b
- 1
-
-10945
19525
132
20
-
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19535
- 1
- 1
- {0}
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- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- fcb77176-dad3-411b-877d-8fa9e333a25c
- Angle
- Angle
- false
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- false
-
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19545
132
20
-
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19555
- 1
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- {0}
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- Arrayed geometry
- e71be443-1b77-45d9-ae18-84613f8b4029
- Geometry
- Geometry
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-
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19468
50
48
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19492.25
- 1
- Transformation data
- ad05cb55-2f01-43f4-8630-44893b918056
- Transform
- Transform
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-
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19516
50
49
-
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19540.75
- 6eaffbb2-3392-441a-8556-2dc126aa8910
- Cull Duplicates
- 1
- Cull points that are coincident within tolerance
- true
- e47c18b0-9fa8-4d6c-a3c0-d9ca99a4865e
- Cull Duplicates
- Cull Duplicates
-
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19475
180
64
-
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19507
- 1
- Points to operate on
- c862758d-3903-4936-81fe-d6730676a207
- Points
- Points
- false
- 08b1439d-5ab5-4767-9432-dd21bf667ba5
- 1
-
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19477
113
30
-
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19492
- Proximity tolerance distance
- 436718b0-ca7f-463e-916b-c9fad0ca224c
- Tolerance
- Tolerance
- false
- 0
-
-9280
19507
113
30
-
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19522
- 1
- 1
- {0}
- 1.1641532182693481E-10
- 1
- Culled points
- 3606ae1a-a45f-48d1-a992-4ac71a0775e4
- Points
- Points
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- 0
-
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19477
39
20
-
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19487
- 1
- Index map of culled points
- 165d9449-6ac3-4b99-9dbd-cb4d0b8edfa2
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-
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19497
39
20
-
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19507
- 1
- Number of input points represented by this output point
- ae042c2a-c410-49ce-bd53-aa52fe251b49
- Valence
- Valence
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- 0
-
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19517
39
20
-
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19527
- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
- true
- 5e48da67-4f4c-4f6b-899a-232a45af31c8
- Flip Matrix
- Flip Matrix
-
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19478
78
28
-
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19492
- 2
- Data matrix to flip
- 6fa3c829-5595-410c-885e-e4ec87bba766
- Data
- Data
- false
- e71be443-1b77-45d9-ae18-84613f8b4029
- 1
-
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19480
25
24
-
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19492
- 2
- Flipped data matrix
- 182d589b-76e3-4b99-9fab-733f3b63b534
- Data
- Data
- false
- 0
-
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19480
25
24
-
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19492
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 14c26d48-70db-4b8d-a885-c903820dbcbd
- Evaluate Length
- Evaluate Length
-
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19594
149
64
-
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19626
- Curve to evaluate
- c8e5f47e-3dcc-4823-b70c-326b478f5f10
- Curve
- Curve
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- 85657344-165d-4b95-8882-7df5de611f5a
- 1
-
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19596
71
20
-
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- Length factor for curve evaluation
- e2d71b00-17d4-4805-ad48-2c5d2349e590
- Length
- Length
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- 0
-
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19616
71
20
-
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19626
- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 1dcc704e-9a5e-42c4-8915-fb927f6256e1
- Normalized
- Normalized
- false
- 0
-
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19636
71
20
-
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19646
- 1
- 1
- {0}
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- Point at the specified length
- 764527b5-a4ab-4375-84e1-78fdfca5bc18
- Point
- Point
- false
- 0
-
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19596
50
20
-
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19606
- Tangent vector at the specified length
- dac01bff-d24b-4b5d-81b8-6390f46353fc
- Tangent
- Tangent
- false
- 0
-
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19616
50
20
-
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19626
- Curve parameter at the specified length
- 86533b7f-b99b-417c-89c5-7db154976f73
- Parameter
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- false
- 0
-
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19636
50
20
-
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19646
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- 455db4d3-55f1-4a45-a6c6-14452ce61cd6
- Polar Array
- Polar Array
-
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19594
210
101
-
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19645
- Base geometry
- aba03caf-73d4-462b-87a7-77fcae1169e4
- Geometry
- Geometry
- true
- 764527b5-a4ab-4375-84e1-78fdfca5bc18
- 1
-
-10945
19596
132
20
-
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19606
- Polar array plane
- d7b9fc96-aa90-4327-bf29-df24962e56fb
- Plane
- Plane
- false
- 0
-
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19616
132
37
-
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19634.5
- 1
- 1
- {0}
-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
- 06b2eedb-e668-4526-bca3-de09f0cf93e4
- Count
- Count
- false
- a36a42bd-2f18-4380-938f-847c2f934c7b
- 1
-
-10945
19653
132
20
-
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19663
- 1
- 1
- {0}
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- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- 4e358a14-df07-4921-a06d-e6243d39310b
- Angle
- Angle
- false
- 0
- false
-
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19673
132
20
-
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19683
- 1
- 1
- {0}
- 6.2831853071795862
- 1
- Arrayed geometry
- b5b94566-1972-4613-ab99-a41b4fd22467
- Geometry
- Geometry
- false
- 0
-
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19596
50
48
-
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19620.25
- 1
- Transformation data
- 3bb3440a-70d3-436d-906f-aabceabeeda8
- Transform
- Transform
- false
- 0
-
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19644
50
49
-
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19668.75
- 6eaffbb2-3392-441a-8556-2dc126aa8910
- Cull Duplicates
- 1
- Cull points that are coincident within tolerance
- true
- baed7f70-ba6d-49b2-a182-9e1f41050dbb
- Cull Duplicates
- Cull Duplicates
-
-9282
19591
180
64
-
-9155
19623
- 1
- Points to operate on
- 773057f2-6fb9-4926-b702-2375bf405cb2
- Points
- Points
- false
- 4fef4eb8-0fc3-486e-9c41-26f4afe1b295
- 1
-
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19593
113
30
-
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19608
- Proximity tolerance distance
- 5ed74f67-042e-48f6-8a09-afb04b819fde
- Tolerance
- Tolerance
- false
- 0
-
-9280
19623
113
30
-
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19638
- 1
- 1
- {0}
- 1.1641532182693481E-10
- 1
- Culled points
- 24b409ff-5abd-4ba7-9d16-73e6c5e16e28
- Points
- Points
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- 0
-
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19593
39
20
-
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19603
- 1
- Index map of culled points
- 290ddc15-14b9-47aa-a4ae-b3d4225cf59e
- Indices
- Indices
- false
- 0
-
-9143
19613
39
20
-
-9123.5
19623
- 1
- Number of input points represented by this output point
- 3c5fc8b1-ebf1-47b4-9142-659c4acdc232
- Valence
- Valence
- false
- 0
-
-9143
19633
39
20
-
-9123.5
19643
- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
- true
- ee15d0c7-57af-49f4-8399-91ebb54d3fbd
- Flip Matrix
- Flip Matrix
-
-9989
19606
78
28
-
-9950
19620
- 2
- Data matrix to flip
- 9e6fff63-efc4-46b4-bd2f-e80500468b8b
- Data
- Data
- false
- b5b94566-1972-4613-ab99-a41b4fd22467
- 1
-
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19608
25
24
-
-9974.5
19620
- 2
- Flipped data matrix
- 62d6ed83-3071-4687-a5e0-09c3b2be03ec
- Data
- Data
- false
- 0
-
-9938
19608
25
24
-
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19620
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 49eeb6cb-33ad-4c36-b3da-903f4f48a3dc
- Relay
- false
- 0aa97910-040a-4b31-a691-e832adf11984
- 1
-
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19484
40
16
-
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19492
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 85657344-165d-4b95-8882-7df5de611f5a
- Relay
- false
- 09bd24b2-9b17-46e1-bb2c-fbfcd0cef0c7
- 1
-
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19632
40
16
-
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19640
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- 49eeb6cb-33ad-4c36-b3da-903f4f48a3dc
- 85657344-165d-4b95-8882-7df5de611f5a
- 2
- 82e45e7a-9d1d-412d-ab28-00d4da49847b
- Group
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
- 5e63a198-8193-43a2-9211-a843baa5ebae
- Merge
- Merge
-
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19671
106
84
-
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19713
- 4
- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2
- Data stream 1
- 536bf0e9-9cc6-4b01-bc21-84aaf9ac43f0
- false
- Data 1
- D1
- true
- b355f109-25fc-4ac1-95af-11e2b44904eb
- 1
-
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19673
31
20
-
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19683
- 2
- Data stream 2
- f588e906-9559-4e3b-afce-057921253f2e
- false
- Data 2
- D2
- true
- 7d7e65fd-a768-498d-9278-b4230ff815a3
- 1
-
-5152
19693
31
20
-
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19703
- 2
- Data stream 3
- 3e89e829-ae01-4af2-a652-0fc8d1a41536
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- Data 3
- D3
- true
- 6d3ecdf0-e5c6-4a72-931a-2496e3cbe29a
- 1
-
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19713
31
20
-
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19723
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83
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24
80
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- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
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-
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149
64
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- Curve to evaluate
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20546
71
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- Length factor for curve evaluation
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71
20
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- If True, the Length factor is normalized (0.0 ~ 1.0)
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71
20
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- Point at the specified length
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50
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- Tangent vector at the specified length
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50
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- Curve parameter at the specified length
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50
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- 71b5b089-500a-4ea6-81c5-2f960441a0e8
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- Create a polyline connecting a number of points.
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- PolyLine
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-
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20590
106
44
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- Polyline vertex points
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40
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20602
- Close polyline
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20612
40
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20592
38
40
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20612
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
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- Create a polyline connecting a number of points.
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20661
106
44
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20663
40
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- Close polyline
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40
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- 94c19071-e38a-4b13-9af9-048665b18ff3
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20663
38
40
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20683
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
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- Merge
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-
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20618
90
64
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20620
31
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- Data stream 2
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31
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31
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20620
31
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- Create a polar array of geometry.
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- Polar Array
- Polar Array
-
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20544
210
101
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- Base geometry
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132
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- Polar array plane
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132
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- Number of elements in array.
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132
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- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
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20623
132
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50
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50
49
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- Cull Duplicates
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- Cull points that are coincident within tolerance
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- Cull Duplicates
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180
64
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- Points to operate on
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113
30
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- Proximity tolerance distance
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113
30
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- Culled points
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39
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- 1
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39
20
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- Number of input points represented by this output point
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20595
39
20
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- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
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- Flip a matrix-like data tree by swapping rows and columns.
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- Flip Matrix
- Flip Matrix
-
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20556
78
28
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- 2
- Data matrix to flip
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- Data
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25
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- 2
- Flipped data matrix
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25
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- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
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- Evaluate Length
- Evaluate Length
-
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20672
149
64
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- Curve to evaluate
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71
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- Length factor for curve evaluation
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- Length
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71
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- If True, the Length factor is normalized (0.0 ~ 1.0)
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71
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50
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- Tangent vector at the specified length
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50
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- Curve parameter at the specified length
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50
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- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
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- Polar Array
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-
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20672
210
101
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- Base geometry
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132
20
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- Polar array plane
- a656c790-d5b5-4f87-a651-7e130d661606
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132
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-
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132
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- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
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20751
132
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20674
50
48
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50
49
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- Cull Duplicates
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- Cull Duplicates
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-
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20669
180
64
-
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20701
- 1
- Points to operate on
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- Points
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-
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20671
113
30
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- Proximity tolerance distance
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20701
113
30
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- 1
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- Culled points
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39
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- Index map of culled points
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39
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- 1
- Number of input points represented by this output point
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39
20
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- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
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- Flip Matrix
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-
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78
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- Data matrix to flip
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- Data
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25
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- Flipped data matrix
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-
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20686
25
24
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- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
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- A wire relay object
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40
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- Relay
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- A wire relay object
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40
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255;255;255;255
- A group of Grasshopper objects
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- Merge a bunch of data streams
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47
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- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
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- If True, the Length factor is normalized (0.0 ~ 1.0)
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- Sort a list of numeric keys.
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- Sort List
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- Compute Euclidean distance between two point coordinates.
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0
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255;255;255;255
- A group of Grasshopper objects
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- Evaluate Wolfram Language code
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- The Wolfram Language expression to execute
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5623
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31
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- Text Split
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49
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- Text to split.
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- FabiusF::usage="FabiusF[x] gives the value of the Fabius function F(x) for a non-negative real argument x.";
Macros`SetArgumentCount[FabiusF,1];
SyntaxInformation[FabiusF]={"ArgumentsPattern"->{_}};
SetAttributes[FabiusF,{NumericFunction,Listable}];
Derivative[n_Integer][FabiusF]:=2^(n (n+1)/2) FabiusF[2^n #]&
(*https://mathematica.stackexchange.com/a/13245*)
powerOfTwoQ[n_]:=IntegerQ[n]&&BitAnd[n,n-1]==0
FabiusF[Infinity]=Interval[{-1,1}];
FabiusF[x_?NumberQ]/;If[0<=Re[x]&&Im[x]==0,powerOfTwoQ[Denominator[x]],Message[FabiusF::realnn,x];False]:=iFabiusF[x]
ariasD[0]=1;
ariasD[n_Integer?Positive]:=ariasD[n]=Sum[2^((k (k-1)-n (n-1))/2) ariasD[k]/(n-k+1)!,{k,0,n-1}]/(2^n-1);
tri[x_]:=Piecewise[{{2-x,x>1}},x]
iFabiusF[x_]:=Module[{prec=Precision[x],s=1,y=0,z=SetPrecision[x,Infinity],n,p,q,tol,w},z=If[0<=z<=2,tri[z],q=Quotient[z,2];
(*can replace ThueMorse[] with the implementation in https://mathematica.stackexchange.com/a/89351*)If[ThueMorse[q]==1,s=-1];tri[z-2 q]];
tol=10^(-prec);
While[z>0,n=-Floor[RealExponent[z,2]];p=2^n;z-=1/p;w=1;
Do[w=ariasD[m]+p z w/(n-m+1);p/=2,{m,n}];
y=w-y;
If[Abs[w]<Abs[y] tol,Break[]]];
SetPrecision[s Abs[y],prec]];
ᐱ=1;
ƧS=16;
ᔓᔕ={ImageSize-> Full,AspectRatio-> 1/16,MaxRecursion->0,PlotPoints-> 1+2^(Log[ƧS]/Log[2]) };
ꗳ={Abs[FabiusF[x*2*ᐱ]]};
Plot[ꗳ,{x,0,1},Evaluate[ᔓᔕ]];
N[(Log[ƧS]/Log[2])];
StringReplace[
ToString[
Table[
N[
Evaluate[SetPrecision[SetAccuracy[ꗳ,Infinity],Infinity]]
]
,{x,Flatten[Range[0,ƧS]/ƧS]}]
,InputForm]
,{"{"-> "","}"-> ""," "-> "","*^"-> "*10^"}]
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255;255;255;255
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- Replace Text
- Replace all occurences of a specific text fragment with another
- true
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- true
- Replace Text
- Replace Text
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- Text to operate on.
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- Text
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- Find
- Find
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-
5622
-3743
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 0e3d5ec1-8fa7-4002-9434-37c9a26ef80d
- true
- Gate
- Gate
- false
- 0
-
5570
-3773
40
20
-
5590
-3763
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- dddb3d20-af6d-4e00-8270-25008d01bdcc
- true
- false
- Stream 0
- 0
- true
- 67a89d9d-9c53-46e9-9e3f-3e39885aabe6
- 1
-
5570
-3753
40
20
-
5590
-3743
- 2
- Input stream at index 1
- 11f89342-c3fd-4efd-8cd9-023be367ae59
- true
- false
- Stream 1
- 1
- true
- c392a01f-be44-46c9-b4b8-97692db5ba6a
- 1
-
5570
-3733
40
20
-
5590
-3723
- 2
- Filtered stream
- 2e80dba7-8ea9-4746-89bb-af50ebc1a23f
- true
- false
- Stream
- S(0)
- false
- 0
-
5634
-3773
24
60
-
5646
-3743
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- daf2bda9-7f56-4f78-8ca0-4010ff8841e3
- true
- Stream Filter
- Stream Filter
-
5568
-2304
92
64
-
5622
-2272
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 3a46a533-d39a-4446-b923-8921005cb645
- true
- Gate
- Gate
- false
- 0
-
5570
-2302
40
20
-
5590
-2292
- 1
- 1
- {0}
- 1
- 2
- Input stream at index 0
- cdbdb7cf-4d36-4f5c-afa1-21cd4773d7e5
- true
- false
- Stream 0
- 0
- true
- 0
-
5570
-2282
40
20
-
5590
-2272
- 2
- Input stream at index 1
- 0d26362b-b98e-4fd1-9f2e-069c5b52ef3a
- true
- false
- Stream 1
- 1
- true
- 20eec82c-3638-4068-b8ec-f7754f44d1d0
- 1
-
5570
-2262
40
20
-
5590
-2252
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_String
- false
- 1
- 2
- Filtered stream
- aa6e20b3-ed69-4615-8194-b0e2c46ede90
- true
- false
- Stream
- S(1)
- false
- 0
-
5634
-2302
24
60
-
5646
-2272
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 2d1fa5b0-bc84-4c71-a356-02c3ae09bc4c
- true
- Stream Filter
- Stream Filter
-
5568
-3204
92
64
-
5622
-3172
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 4263c740-37b0-49a0-abf2-6d797694626c
- true
- Gate
- Gate
- false
- 25de4f3d-bbbe-4d69-a2f8-eafb39ed11c3
- 1
-
5570
-3202
40
20
-
5590
-3192
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 403a03e8-2056-460d-811a-7288a41cfbaa
- true
- false
- Stream 0
- 0
- true
- 0
-
5570
-3182
40
20
-
5590
-3172
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_String
- false
- 1
- 2
- Input stream at index 1
- b0bfffc4-ceeb-44e9-b31c-fb638dd0a66c
- true
- false
- Stream 1
- 1
- true
- 8e2c479f-1986-4a29-ac9c-d76908386441
- 1
-
5570
-3162
40
20
-
5590
-3152
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_String
- false
- 1
- 2
- Filtered stream
- 7ec9447f-503b-4550-a46d-b2f1773da413
- true
- false
- Stream
- S(1)
- false
- 0
-
5634
-3202
24
60
-
5646
-3172
- cb2c7d3c-41b4-4c6d-a6bd-9235bd2851bb
- Gate Not
- Perform boolean negation (NOT gate).
- true
- de03810f-58b7-4c2c-89d6-49cb00614695
- true
- Gate Not
- Gate Not
-
5574
-3099
80
28
-
5609
-3085
- Boolean value
- a0efc076-2674-4a8e-966a-cd6ff8b2cfb5
- true
- A
- A
- false
- 0
-
5576
-3097
21
24
-
5586.5
-3085
- 1
- 1
- {0}
- false
- Inverse of {A}
- 25de4f3d-bbbe-4d69-a2f8-eafb39ed11c3
- true
- Result
- Result
- false
- 0
-
5621
-3097
31
24
-
5636.5
-3085
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 88726205-2a30-44c4-8e25-19521cf91261
- true
- Stream Filter
- Stream Filter
-
5568
-2219
92
64
-
5622
-2187
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 0b8d4ebb-ff0a-438f-873f-ac724eb994b3
- true
- Gate
- Gate
- false
- 0
-
5570
-2217
40
20
-
5590
-2207
- 1
- 1
- {0}
- 1
- 2
- Input stream at index 0
- e1375ca2-bad5-46e1-83e4-8bcf1f144b8e
- true
- false
- Stream 0
- 0
- true
- 0
-
5570
-2197
40
20
-
5590
-2187
- 2
- Input stream at index 1
- d7733ad1-9026-423d-8042-4e6431d6e982
- true
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- Stream 1
- 1
- true
- 051df130-9b07-4484-aee6-c11038f9920f
- 1
-
5570
-2177
40
20
-
5590
-2167
- 2
- Filtered stream
- 20eec82c-3638-4068-b8ec-f7754f44d1d0
- true
- false
- Stream
- S(1)
- false
- 0
-
5634
-2217
24
60
-
5646
-2187
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- e84dba12-64d4-4086-bd66-0d891880a38b
- true
- Stream Filter
- Stream Filter
-
5568
-3038
92
64
-
5622
-3006
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- cde52939-d91f-48c0-852f-d1d931c679d1
- true
- Gate
- Gate
- false
- 0
-
5570
-3036
40
20
-
5590
-3026
- 1
- 1
- {0}
- 1
- 2
- Input stream at index 0
- 30fb0819-1aec-45bd-86ad-db3341956079
- true
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- Stream 0
- 0
- true
- 0
-
5570
-3016
40
20
-
5590
-3006
- 2
- Input stream at index 1
- fb00641f-71e1-43db-ad33-197aac2070b3
- true
- false
- Stream 1
- 1
- true
- 26b600f6-cf65-413e-ae98-aa04c9baea3f
- 1
-
5570
-2996
40
20
-
5590
-2986
- 2
- Filtered stream
- 8e2c479f-1986-4a29-ac9c-d76908386441
- true
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- Stream
- S(1)
- false
- 0
-
5634
-3036
24
60
-
5646
-3006
- 7a1e5fd7-b7da-4244-a261-f1da66614992
- Power of 2
- Raise 2 to the power of N.
- true
- 722c82cf-9886-4262-9816-99e5cd56678c
- true
- Power of 2
- Power of 2
-
5599
-592
49
28
-
5628
-578
- Input value
- ee9c09b1-533c-4d4a-be2d-82b761176c38
- true
- Value
- false
- 0
-
5601
-590
15
24
-
5608.5
-578
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_String
- false
- 4
- Output value
- c24a11ca-4b56-465e-a295-4d23379c5a82
- true
- Result
- false
- 0
-
5640
-590
6
24
-
5643
-578
- 2b69bf71-4e69-43aa-b7be-4f6ce7e45bef
- Quick Graph
- 1
- Display a set of y-values as a graph
- 6dde463b-8ec4-4fed-8469-a81cead81ceb
- true
- Quick Graph
- Quick Graph
- false
- 0
- 67a89d9d-9c53-46e9-9e3f-3e39885aabe6
- 1
-
5545
-3668
150
150
-
5545.936
-3667.635
- -1
- 2b69bf71-4e69-43aa-b7be-4f6ce7e45bef
- Quick Graph
- 1
- Display a set of y-values as a graph
- a13feeb8-9203-4a56-91d0-bffa77e0adec
- true
- Quick Graph
- Quick Graph
- false
- 0
- c392a01f-be44-46c9-b4b8-97692db5ba6a
- 1
-
5544
-2734
150
150
-
5544.146
-2733.611
- -1
- d5967b9f-e8ee-436b-a8ad-29fdcecf32d5
- Curve
- Contains a collection of generic curves
- true
- 13394695-7838-4186-a49f-10abd5475f71
- true
- Curve
- Curve
- false
- 7fd0d788-1237-49d2-b610-14b9cdecf740
- 1
-
5856
-861
50
24
-
5881.943
-849.5875
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 293ffb2b-17b1-499c-ab83-ca4b6b12d7cc
- true
- Evaluate Length
- Evaluate Length
-
5992
-1067
158
64
-
6086
-1035
- Curve to evaluate
- cae78a03-2530-469e-8072-6dc15a29e5de
- true
- Curve
- Curve
- false
- 13394695-7838-4186-a49f-10abd5475f71
- 1
-
5994
-1065
80
20
-
6042
-1055
- Length factor for curve evaluation
- c6389f43-3849-4238-a5f7-cd2e422f9150
- (((1-X)+.25)%1)*0+X
- true
- Length
- Length
- false
- ef28f44c-dbc6-4685-a989-6732ef0bb7c2
- 1
-
5994
-1045
80
20
-
6042
-1035
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 92dc2b87-a073-4931-ae5c-34b2de2739af
- true
- Normalized
- Normalized
- false
- 0
-
5994
-1025
80
20
-
6042
-1015
- 1
- 1
- {0}
- true
- Point at the specified length
- 7591450a-f055-4d21-a585-f8ae56edcd48
- true
- Point
- Point
- false
- 0
-
6098
-1065
50
20
-
6123
-1055
- Tangent vector at the specified length
- 17858ac8-32f7-44d6-b6f8-2d508ecaa5fd
- true
- Tangent
- Tangent
- false
- 0
-
6098
-1045
50
20
-
6123
-1035
- Curve parameter at the specified length
- 49590bed-a20e-4773-8468-19bcd687b41d
- true
- Parameter
- Parameter
- false
- 0
-
6098
-1025
50
20
-
6123
-1015
- d27b55c6-9d5f-4d05-be7b-b91009aad383
- c2ea695e-1a09-6f42-266d-113498879f60
- DotDisplay
- Show points as round dots
- true
- 7eb88e78-1c37-4abe-86a2-1d9a5462c467
- true
- DotDisplay
- DotDisplay
-
6260
-1030
55
28
-
6301
-1016
- Points to display
- 1269a20e-0305-403a-89e4-6ce870afc658
- true
- Point
- Point
- false
- 7591450a-f055-4d21-a585-f8ae56edcd48
- 1
-
6262
-1028
27
24
-
6275.5
-1016
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 2b49245c-cda0-4c54-82f2-915c2c2d3104
- true
- Relay
- false
- c392a01f-be44-46c9-b4b8-97692db5ba6a
- 1
-
5856
-1105
40
16
-
5876
-1097
- 4fdfe351-6c07-47ce-9fb9-be027fb62186
- Shift List
- Offset all items in a list.
- true
- a032b96c-6401-439f-b3f3-904dda76193d
- true
- Shift List
- Shift List
-
5971
-796
85
64
-
6023
-764
- 1
- List to shift
- 59903599-7e96-4aa6-bbc0-1dd19bc6b732
- true
- List
- List
- false
- 7685ddf3-078a-480f-99b7-862e703168f0
- 1
-
5973
-794
38
20
-
5992
-784
- Shift offset
- fa55991b-de79-429a-9f60-49f921ce5b6c
- true
- Shift
- Shift
- false
- 8b406b6e-1939-4eca-b757-fee45c7bdd1a
- 1
-
5973
-774
38
20
-
5992
-764
- 1
- 1
- {0}
- 1
- Wrap values
- 87a68ae4-9a06-4490-a950-0b2e160b1389
- true
- Wrap
- Wrap
- false
- 0
-
5973
-754
38
20
-
5992
-744
- 1
- 1
- {0}
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- 1
- Shifted list
- 23a6c8c0-0b37-4d13-a7e3-8809dcbe6e24
- true
- List
- List
- false
- 0
-
6035
-794
19
60
-
6044.5
-764
- 9c85271f-89fa-4e9f-9f4a-d75802120ccc
- Division
- Mathematical division
- true
- 7763af33-af48-446f-a61a-b14eef73d6b4
- true
- Division
- Division
-
5903
-1211
85
44
-
5943
-1189
- Item to divide (dividend)
- e8d7559e-d7e9-47c0-a40f-d442f2b00caf
- true
- A
- A
- false
- 2b49245c-cda0-4c54-82f2-915c2c2d3104
- 1
-
5905
-1209
26
20
-
5918
-1199
- Item to divide with (divisor)
- 4d7f72d4-79ff-494e-9a40-70f92811487e
- true
- B
- B
- false
- 0
-
5905
-1189
26
20
-
5918
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- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_Integer
- 2
- The result of the Division
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- Result
- Result
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- 0
-
5955
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31
40
-
5970.5
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- Subtraction
- Mathematical subtraction
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- true
- Subtraction
- Subtraction
-
6107
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85
44
-
6147
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- 2
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- First operand for subtraction
- 0b42fc02-1e42-476d-82b8-58fa966fb336
- true
- A
- A
- true
- 0
-
6109
-762
26
20
-
6122
-752
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_String
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- 1
- Second operand for subtraction
- b2d244ff-2a5e-40ff-b002-3fd8100dfaa7
- true
- B
- B
- true
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- 1
-
6109
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26
20
-
6122
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- Result of subtraction
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- 0
-
6159
-762
31
40
-
6174.5
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- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
- 9ae96cdd-eee0-4568-afce-7d59699d1545
- true
- Merge
- Merge
-
6271
-905
106
64
-
6316
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- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- Data stream 1
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- true
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- Data 1
- D1
- true
- 8ac10f4f-35e5-4926-b1ad-69680a469255
- 1
-
6273
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31
20
-
6288.5
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- 2
- Data stream 2
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- Data 2
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- c1a886a6-a389-4bef-92a8-675272355ed7
- 1
-
6273
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31
20
-
6288.5
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- 2
- Data stream 3
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- Data 3
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-
6273
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31
20
-
6288.5
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- Result of merge
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-
6328
-903
47
60
-
6343.5
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- 059b72b0-9bb3-4542-a805-2dcd27493164
- Cloud Display
- Draw a collection of points as a fuzzy cloud
- true
- 824f4431-dcb9-474b-a2f2-5c55348e3898
- true
- Cloud Display
- Cloud Display
- 1
-
6352
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119
64
-
6457
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- 1
- Location for each blob
- true
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- true
- 2
- Points
- Points
- true
- 7591450a-f055-4d21-a585-f8ae56edcd48
- 1
-
6354
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91
20
-
6417.5
-1055
- 1
- Colour for each blob
- ca51359a-3873-47c3-bcac-fb0729baa349
- true
- Colours
- Colours
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- 0
-
6354
-1045
91
20
-
6417.5
-1035
- 1
- 1
- {0}
-
255;0;244;124
- Size for each blob
- a73e21b3-0789-4f1e-be52-243347a3b340
- X/64
- true
- 2
- Size
- Size
- true
- 0
-
6354
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91
20
-
6417.5
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101
64
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42
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100
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237
84
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170
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170
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92
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40
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92
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40
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40
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24
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92
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40
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40
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24
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255;255;255;255
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92
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40
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40
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40
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- Stream Filter
- Stream Filter
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92
64
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6215
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40
20
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40
20
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40
20
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24
60
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255;255;255;255
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- Filters a collection of input streams
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- Stream Filter
- Stream Filter
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92
64
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7394
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40
20
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40
20
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40
20
-
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7364
24
60
-
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7394
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
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- Stream Filter
- Stream Filter
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92
64
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40
20
-
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40
20
-
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40
20
-
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- Filtered stream
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24
60
-
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-
255;255;255;255
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- Group
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- Filters a collection of input streams
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- Stream Filter
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92
64
-
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8670
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8640
40
20
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40
20
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8680
40
20
-
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8640
24
60
-
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8670
- eeafc956-268e-461d-8e73-ee05c6f72c01
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- Stream Filter
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92
64
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40
20
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40
20
-
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40
20
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24
60
-
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8543
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
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-
255;255;255;255
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9739
92
64
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9771
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9741
40
20
-
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9751
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40
20
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9781
40
20
-
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9791
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9741
24
60
-
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9771
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
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- Stream Filter
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9612
92
64
-
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-
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9614
40
20
-
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9624
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9634
40
20
-
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9644
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-
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9654
40
20
-
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9664
- 2
- Filtered stream
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9614
24
60
-
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9644
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
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-
255;255;255;255
- A group of Grasshopper objects
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- Group
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- Stream Filter
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-
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10898
92
64
-
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10930
- 3
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- Index of Gate stream
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-
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10900
40
20
-
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10910
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10920
40
20
-
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10930
- 2
- Input stream at index 1
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-
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10940
40
20
-
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10950
- 2
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-
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10900
24
60
-
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10930
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
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- Stream Filter
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-
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10771
92
64
-
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- 2e3ab970-8545-46bb-836c-1c11e5610bce
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- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
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-
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10773
40
20
-
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-
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10793
40
20
-
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10803
- 2
- Input stream at index 1
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- true
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-
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10813
40
20
-
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- 2
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-
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24
60
-
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10803
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
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-
255;255;255;255
- A group of Grasshopper objects
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88
271
155
-
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166
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-
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90
196
20
-
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100
- An optional frame for the drawing. If blank, the shapes bounding box will be used
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-
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110
196
71
-
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145.5
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-
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181
196
20
-
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191
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- {0}
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-
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201
196
20
-
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211
- 1
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- {0}
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- An optional background color
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-
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221
196
20
-
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231
- 1
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- {0}
-
0;255;255;255
- A Graphic Plus Drawing Object
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-
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90
47
75
-
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127.75
- The bounding rectangle
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-
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165
47
76
-
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203.25
- eeafc956-268e-461d-8e73-ee05c6f72c01
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92
64
-
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- 1
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- Index of Gate stream
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- Gate
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-
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12079
40
20
-
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40
20
-
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- 2
- Input stream at index 1
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- true
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40
20
-
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- 2
- Filtered stream
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24
60
-
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- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 6aca94d8-afdf-4e43-9aec-6c6b8d8bd741
- Stream Filter
- Stream Filter
-
-11187
11950
92
64
-
-11133
11982
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 98509d08-f026-438c-b89f-2eb6ec90cb1a
- Gate
- Gate
- false
- 17741e82-4e3d-4b9f-9969-9d69c7808425
- 1
-
-11185
11952
40
20
-
-11165
11962
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- bf002089-c5b9-4416-9f6c-5fe17fd01f1e
- false
- Stream 0
- 0
- true
- 0
-
-11185
11972
40
20
-
-11165
11982
- 2
- Input stream at index 1
- a56bdc29-a764-4fb7-a967-e87314bc4dd0
- false
- Stream 1
- 1
- true
- 0375c488-e806-4ad1-a086-2da4152bef10
- 1
-
-11185
11992
40
20
-
-11165
12002
- 2
- Filtered stream
- 6a68f77b-051c-4818-852a-84702d6a3fcb
- false
- Stream
- S(0)
- false
- 0
-
-11121
11952
24
60
-
-11109
11982
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- fa81a8b4-cf5f-45a2-87c3-3995dfc08e89
- 6aca94d8-afdf-4e43-9aec-6c6b8d8bd741
- 2
- 14b30f5b-f7e1-48df-a27f-19c0ea0559a6
- Group
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 2afd3edb-d771-40ba-9e12-ae84a3d2c52b
- Stream Filter
- Stream Filter
-
-11227
13196
92
64
-
-11173
13228
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- ce0052fb-c8b6-402a-bccf-0ecc6ebf441c
- Gate
- Gate
- false
- 17741e82-4e3d-4b9f-9969-9d69c7808425
- 1
-
-11225
13198
40
20
-
-11205
13208
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- dc35d3b8-24b9-4476-aa26-4045c6111021
- false
- Stream 0
- 0
- true
- 0
-
-11225
13218
40
20
-
-11205
13228
- 2
- Input stream at index 1
- 42c2fd41-52b1-46a2-b9eb-39d5d4b30ba9
- false
- Stream 1
- 1
- true
- 0f7d41df-0b88-413c-bf09-4b93aebfd26f
- 1
-
-11225
13238
40
20
-
-11205
13248
- 2
- Filtered stream
- c275b6a1-118d-4ab6-9708-51c158efd69c
- false
- Stream
- S(0)
- false
- 0
-
-11161
13198
24
60
-
-11149
13228
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 97dc2833-b406-498f-8847-89d4d247ff99
- Stream Filter
- Stream Filter
-
-11227
13069
92
64
-
-11173
13101
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- f67731f9-a091-40ee-aac8-252fde956cc9
- Gate
- Gate
- false
- 17741e82-4e3d-4b9f-9969-9d69c7808425
- 1
-
-11225
13071
40
20
-
-11205
13081
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 664f2c9c-c93a-4673-b7c2-0db2519483c4
- false
- Stream 0
- 0
- true
- 0
-
-11225
13091
40
20
-
-11205
13101
- 2
- Input stream at index 1
- 2a419803-185f-4277-895c-31b5e3a9ab90
- false
- Stream 1
- 1
- true
- 360e3c71-f39a-4344-9b0b-f76f6040e9a5
- 1
-
-11225
13111
40
20
-
-11205
13121
- 2
- Filtered stream
- f71f118e-dff3-449b-8eb8-77a6b5272af6
- false
- Stream
- S(0)
- false
- 0
-
-11161
13071
24
60
-
-11149
13101
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- 2afd3edb-d771-40ba-9e12-ae84a3d2c52b
- 97dc2833-b406-498f-8847-89d4d247ff99
- 2
- 7fe95677-b648-4e7c-af60-2ac98b6280e5
- Group
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- c319f1fd-9a2f-4e3e-b41a-462b6183ff1f
- Stream Filter
- Stream Filter
-
-11227
14366
92
64
-
-11173
14398
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- c744c5fd-cb6e-4fef-8386-ddde37a92a96
- Gate
- Gate
- false
- 17741e82-4e3d-4b9f-9969-9d69c7808425
- 1
-
-11225
14368
40
20
-
-11205
14378
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- bc4c971e-516e-458d-9bd8-d9e361610a32
- false
- Stream 0
- 0
- true
- 0
-
-11225
14388
40
20
-
-11205
14398
- 2
- Input stream at index 1
- 49be4b2e-7253-4819-a896-eca1a5b70d13
- false
- Stream 1
- 1
- true
- 68ed2259-a880-4020-a4fa-5102d6548b24
- 1
-
-11225
14408
40
20
-
-11205
14418
- 2
- Filtered stream
- 27bc95ad-0ae8-4000-9aff-03a94c23bb45
- false
- Stream
- S(0)
- false
- 0
-
-11161
14368
24
60
-
-11149
14398
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- b23a953e-f5fe-490d-b4e1-4836f77bf220
- Stream Filter
- Stream Filter
-
-11227
14239
92
64
-
-11173
14271
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 2b1b6ad2-d1bc-4881-bdc4-6b4113ab2662
- Gate
- Gate
- false
- 17741e82-4e3d-4b9f-9969-9d69c7808425
- 1
-
-11225
14241
40
20
-
-11205
14251
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 6f575b6a-e190-4cac-aaeb-3ba7716f3380
- false
- Stream 0
- 0
- true
- 0
-
-11225
14261
40
20
-
-11205
14271
- 2
- Input stream at index 1
- dccef9cf-5d4b-443b-be87-4160cd59f0f9
- false
- Stream 1
- 1
- true
- 609b5d6e-7b75-4e1a-8a12-faf652c3c682
- 1
-
-11225
14281
40
20
-
-11205
14291
- 2
- Filtered stream
- d3e6f2a9-2986-4d0e-9d6d-14be9dfd713f
- false
- Stream
- S(0)
- false
- 0
-
-11161
14241
24
60
-
-11149
14271
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- c319f1fd-9a2f-4e3e-b41a-462b6183ff1f
- b23a953e-f5fe-490d-b4e1-4836f77bf220
- 2
- f2403d64-acca-4fec-8df9-48668cb8aada
- Group
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 21885950-be69-465c-9d96-960f153c1764
- Stream Filter
- Stream Filter
-
-11227
15471
92
64
-
-11173
15503
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- e55bda3b-8bbe-4404-9461-64492dce29bb
- Gate
- Gate
- false
- 17741e82-4e3d-4b9f-9969-9d69c7808425
- 1
-
-11225
15473
40
20
-
-11205
15483
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 5aa6f597-e792-4a71-975e-df7a2cd6a126
- false
- Stream 0
- 0
- true
- 0
-
-11225
15493
40
20
-
-11205
15503
- 2
- Input stream at index 1
- bceaa58d-d972-4d19-8468-d1e80f9fb6ef
- false
- Stream 1
- 1
- true
- 0ba93922-a608-4ac3-8ad6-de58e4e01a8f
- 1
-
-11225
15513
40
20
-
-11205
15523
- 2
- Filtered stream
- 367d9c37-ecf5-4adb-a85a-2bdcd57e2092
- false
- Stream
- S(0)
- false
- 0
-
-11161
15473
24
60
-
-11149
15503
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 269cc0bb-67ab-43ed-a590-db3e7b6ab08f
- Stream Filter
- Stream Filter
-
-11227
15344
92
64
-
-11173
15376
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 4dc57c65-7ba5-4cd5-a06e-202a19c48e94
- Gate
- Gate
- false
- 17741e82-4e3d-4b9f-9969-9d69c7808425
- 1
-
-11225
15346
40
20
-
-11205
15356
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- ee9327d4-ebf1-4450-8c01-edff53e474b5
- false
- Stream 0
- 0
- true
- 0
-
-11225
15366
40
20
-
-11205
15376
- 2
- Input stream at index 1
- 2c4e6896-5d80-416c-a893-d11cea4c865d
- false
- Stream 1
- 1
- true
- 589e948c-d0d2-4b05-9c56-6855d5c435b4
- 1
-
-11225
15386
40
20
-
-11205
15396
- 2
- Filtered stream
- a6314d11-f0d5-419c-bc82-24c2862d0c35
- false
- Stream
- S(0)
- false
- 0
-
-11161
15346
24
60
-
-11149
15376
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- 21885950-be69-465c-9d96-960f153c1764
- 269cc0bb-67ab-43ed-a590-db3e7b6ab08f
- 2
- b718a122-9098-4399-a42f-a974dc783cd7
- Group
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- a740a9fc-8b55-4c5c-a871-f76e1efb3a41
- Stream Filter
- Stream Filter
-
-11227
16495
92
64
-
-11173
16527
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 1bac5d72-7374-401e-bbea-792f52769d0f
- Gate
- Gate
- false
- 17741e82-4e3d-4b9f-9969-9d69c7808425
- 1
-
-11225
16497
40
20
-
-11205
16507
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 7fdefbf2-2487-451b-99fe-444e9f9a1b96
- false
- Stream 0
- 0
- true
- 0
-
-11225
16517
40
20
-
-11205
16527
- 2
- Input stream at index 1
- ecac3ee8-866c-4c84-adc9-06193c3e68a8
- false
- Stream 1
- 1
- true
- 11ceca9b-30b2-4213-b35d-85e5be45643a
- 1
-
-11225
16537
40
20
-
-11205
16547
- 2
- Filtered stream
- c0cb4ede-8eab-4fd5-9c53-b62df174b453
- false
- Stream
- S(0)
- false
- 0
-
-11161
16497
24
60
-
-11149
16527
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 074a7f4a-bb6e-4134-9cbd-8a3674cd6458
- Stream Filter
- Stream Filter
-
-11227
16368
92
64
-
-11173
16400
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 21e3aca0-77dd-499a-99b5-265b7782e734
- Gate
- Gate
- false
- 17741e82-4e3d-4b9f-9969-9d69c7808425
- 1
-
-11225
16370
40
20
-
-11205
16380
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 1c62efb8-aa5e-432e-a3ce-d919a2e82c28
- false
- Stream 0
- 0
- true
- 0
-
-11225
16390
40
20
-
-11205
16400
- 2
- Input stream at index 1
- 84fe6fe7-3c54-4b99-a392-fae62be28538
- false
- Stream 1
- 1
- true
- b7cf406c-d92d-4328-9b8e-d0e00d9cb12a
- 1
-
-11225
16410
40
20
-
-11205
16420
- 2
- Filtered stream
- bec1d112-916e-46f3-aec4-8d3439e35c7f
- false
- Stream
- S(0)
- false
- 0
-
-11161
16370
24
60
-
-11149
16400
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- a740a9fc-8b55-4c5c-a871-f76e1efb3a41
- 074a7f4a-bb6e-4134-9cbd-8a3674cd6458
- 2
- d0cbf364-bbd3-443f-baf9-ddf9faa06c95
- Group
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- ca8ca783-f945-428f-a2f3-e0f01c9d6b16
- Stream Filter
- Stream Filter
-
-11227
17675
92
64
-
-11173
17707
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 90ecef0b-9236-441c-a23f-6a5ab3009534
- Gate
- Gate
- false
- 17741e82-4e3d-4b9f-9969-9d69c7808425
- 1
-
-11225
17677
40
20
-
-11205
17687
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- f0caa3d9-32b1-4924-902e-592380384fda
- false
- Stream 0
- 0
- true
- 0
-
-11225
17697
40
20
-
-11205
17707
- 2
- Input stream at index 1
- e2dae74c-9f51-441d-a4fb-3cd6933b04c7
- false
- Stream 1
- 1
- true
- 29946d34-0db3-4cc0-bbb0-27c79f7c8eb9
- 1
-
-11225
17717
40
20
-
-11205
17727
- 2
- Filtered stream
- c1a066d8-bd60-41c5-aa56-6f9a6e46db6f
- false
- Stream
- S(0)
- false
- 0
-
-11161
17677
24
60
-
-11149
17707
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 5a1f7027-0875-4c99-9a72-e52c18b199e4
- Stream Filter
- Stream Filter
-
-11227
17548
92
64
-
-11173
17580
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- b6110d43-b2e8-4417-b027-d4c7f9597bc7
- Gate
- Gate
- false
- 17741e82-4e3d-4b9f-9969-9d69c7808425
- 1
-
-11225
17550
40
20
-
-11205
17560
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 9560843a-4de3-4059-a942-481ddeac3fbb
- false
- Stream 0
- 0
- true
- 0
-
-11225
17570
40
20
-
-11205
17580
- 2
- Input stream at index 1
- 800847d4-b720-4cb9-97f6-f12f98eb114e
- false
- Stream 1
- 1
- true
- 2f545125-747a-4904-9cb7-05bc0727e11d
- 1
-
-11225
17590
40
20
-
-11205
17600
- 2
- Filtered stream
- 5f27d6a1-8003-43a4-bbbb-1f5ca0d473f0
- false
- Stream
- S(0)
- false
- 0
-
-11161
17550
24
60
-
-11149
17580
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- ca8ca783-f945-428f-a2f3-e0f01c9d6b16
- 5a1f7027-0875-4c99-9a72-e52c18b199e4
- 2
- 1c15b9f5-09dc-4725-ac96-59ef9df1e148
- Group
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 677fd46b-d68b-4325-99d3-40ba2c3fc641
- Stream Filter
- Stream Filter
-
-11227
18772
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35
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35
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- Join as many curves as possible
- true
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- Join Curves
- Join Curves
-
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11215
116
44
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- Curves to join
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- Curves
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11217
53
20
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- Preserve direction of input curves
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11237
53
20
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11247
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- Joined curves and individual curves that could not be joined.
- 252f1c3f-6fc8-4917-8dd0-94db4732630f
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11217
35
40
-
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11237
- 11bbd48b-bb0a-4f1b-8167-fa297590390d
- End Points
- Extract the end points of a curve.
- true
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- End Points
- End Points
-
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11306
84
44
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- Curve to evaluate
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30
40
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11328
- Curve start point
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11308
26
20
-
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11318
- Curve end point
- 7c1105cd-2318-447f-9da8-3eb4eb70d003
- End
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-
-6747
11328
26
20
-
-6734
11338
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
- true
- 3057c49e-c715-48a8-945f-ab1ba287f4eb
- PolyLine
- PolyLine
-
-6682
11262
116
44
-
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11284
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- Polyline vertex points
- 7bd72467-17ac-43cb-89d0-3e1966317539
- Vertices
- Vertices
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- 99b49a50-1180-41c8-98ff-999646aa6fdb
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-
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11264
50
20
-
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11274
- Close polyline
- 29233423-c1d8-4734-99e4-62031de5df08
- Closed
- Closed
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- 0
-
-6680
11284
50
20
-
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11294
- 1
- 1
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- Resulting polyline
- a88ea8e4-8dc1-49ff-88c5-bfcffa9ffd98
- Polyline
- Polyline
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-
-6606
11264
38
40
-
-6587
11284
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
- true
- 40eff6df-43e2-4273-89c6-4d66e4411591
- PolyLine
- PolyLine
-
-6680
11330
116
44
-
-6616
11352
- 1
- Polyline vertex points
- 1d491ee3-a1e1-4401-a5a2-69806a9b5545
- Vertices
- Vertices
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- 7c1105cd-2318-447f-9da8-3eb4eb70d003
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-
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11332
50
20
-
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11342
- Close polyline
- 939a8f70-dfd8-4bd4-a1f1-5a6009613711
- Closed
- Closed
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- 0
-
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11352
50
20
-
-6653
11362
- 1
- 1
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- Resulting polyline
- 171fa47b-0baf-47f9-9d51-2aae46e4cff7
- Polyline
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-
-6604
11332
38
40
-
-6585
11352
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
- bfb01cde-bb5d-40b9-9058-1797527e27db
- Merge
- Merge
-
-6523
11251
90
64
-
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11283
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- Data stream 1
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- Data 1
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- a88ea8e4-8dc1-49ff-88c5-bfcffa9ffd98
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11253
31
20
-
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11263
- 2
- Data stream 2
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- Data 2
- D2
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- 171fa47b-0baf-47f9-9d51-2aae46e4cff7
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-
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11273
31
20
-
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11283
- 2
- Data stream 3
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- D3
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-
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11293
31
20
-
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11303
- 2
- Result of merge
- 2a124133-a96d-4211-a9e7-d9fceab6c6f7
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- 0
-
-6466
11253
31
60
-
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11283
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
- b804ee13-9eb7-4c78-b50c-24c2f5b176fd
- Merge
- Merge
-
-6404
11215
90
64
-
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11247
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- Data stream 1
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- false
- Data 1
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- 0fcbb7cd-41b7-4f75-bee4-2d5cf119870c
- 1
-
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11217
31
20
-
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11227
- 2
- Data stream 2
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- Data 2
- D2
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- 2a124133-a96d-4211-a9e7-d9fceab6c6f7
- 1
-
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11237
31
20
-
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11247
- 2
- Data stream 3
- a7cca129-c07a-42d5-b9fa-8b933e14afc1
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- Data 3
- D3
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- 0
-
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11257
31
20
-
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11267
- 2
- Result of merge
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-
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11217
31
60
-
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11247
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
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- A wire relay object
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- Relay
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11219
40
16
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11227
- 030b487b-a566-476f-96a4-a0ae2ad283af
- a48ac930-c378-48dc-84da-26b2af9d8302
- Stroke
- Applies Stroke properties to a Shape
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- f3342543-967b-46cf-bbd7-a19edb70f7ce
- Stroke
- Stroke
-
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11236
196
104
-
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11288
- A Graphic Plus Shape, or a Curve, Brep, Mesh
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- Shape / Geometry
- Shape / Geometry
- false
- 02dee0d8-7e0a-44d2-992b-0e056be801e8
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11238
136
20
-
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11248
- The stroke color
- 3611d5a3-5f84-44fe-b1f2-382d473ad18f
- Color
- Color
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-
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11258
136
20
-
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11268
- 1
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0;255;255;255
- The stroke weight
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- Weight
- Weight
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-
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11278
136
20
-
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11288
- 1
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- {0}
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- The stroke pattern
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- Pattern
- Pattern
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-
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11298
136
20
-
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11308
- The shape to be used at the end of open path
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- End Cap
- End Cap
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-
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11318
136
20
-
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11328
- 1
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- A Graphic Plus Shape Object
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- Shape
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-
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11238
32
100
-
-5808
11288
- 071c3940-a12d-4b77-bb23-42b5d3314a0d
- Clean Tree
- Removed all null and invalid items from a data tree.
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- Clean Tree
- Clean Tree
-
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11192
135
84
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11234
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- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Remove null items from the tree.
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- Remove Nulls
- Remove Nulls
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-
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11194
83
20
-
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11204
- 1
- 1
- {0}
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- Remove invalid items from the tree.
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- Remove Invalid
- Remove Invalid
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- 0
-
-6144
11214
83
20
-
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11224
- 1
- 1
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- Remove empty branches from the tree.
- bdf19c87-1119-4338-9614-e2afcb76095b
- Remove Empty
- Remove Empty
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- 0
-
-6144
11234
83
20
-
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11244
- 1
- 1
- {0}
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- Data tree to clean
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- Tree
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- 1
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11254
83
20
-
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11264
- 2
- Spotless data tree
- 02dee0d8-7e0a-44d2-992b-0e056be801e8
- Tree
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-
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11194
24
80
-
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11234
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
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255;255;255;255
- A group of Grasshopper objects
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- Group
- ■
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- Group
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-
255;255;255;255
- A group of Grasshopper objects
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- Group
- |
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- Expression
- Evaluate an expression
- O*256/(2^(1585/256))*0
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- 7a5ab99c-b17d-469e-9e8a-739765d8ece7
- Expression
- Expression
-
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596
223
28
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- Expression variable
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- Variable O
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598
11
24
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610
- Result of expression
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- Result
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-
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598
6
24
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610
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
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- 76fff1ec-1dbb-4f02-bcff-14b23a6bc957
- Merge
- Merge
-
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12275
126
64
-
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12307
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- Data 1
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67
20
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12287
- 2
- Data stream 2
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- Data 2
- D2
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67
20
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- Data 3
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12317
67
20
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12327
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- Result of merge
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-
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12277
31
60
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12307
- 5881d944-0281-4fc8-b203-ce6a55dbf2a6
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- Solid Fill
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-
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12337
166
44
-
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- A Graphic Plus Shape, or a Curve, Brep, Mesh
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90
20
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- The solid fill Color
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12359
90
20
-
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12369
- 1
- 1
- {0}
-
255;255;0;255
- A Graphic Plus Shape Object
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- 1
- Shape
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-
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12339
48
40
-
-5638
12359
- 8073a420-6bec-49e3-9b18-367f6fd76ac3
- Join Curves
- Join as many curves as possible
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- Join Curves
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12276
116
44
-
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12298
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- Curves to join
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12278
53
20
-
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12288
- Preserve direction of input curves
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-
-6385
12298
53
20
-
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12308
- 1
- 1
- {0}
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- Joined curves and individual curves that could not be joined.
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-
-6308
12278
35
40
-
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12298
- 11bbd48b-bb0a-4f1b-8167-fa297590390d
- End Points
- Extract the end points of a curve.
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- End Points
- End Points
-
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12367
84
44
-
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- Curve to evaluate
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- Curve
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-
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12369
30
40
-
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12389
- Curve start point
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-
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12369
26
20
-
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12379
- Curve end point
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-
-6844
12389
26
20
-
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12399
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
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- Create a polyline connecting a number of points.
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- a9ddeba9-bd41-4677-afa5-74ea8e0b2ce7
- PolyLine
- PolyLine
-
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12323
116
44
-
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12345
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- Polyline vertex points
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- Vertices
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- 41b42479-5f36-4474-987e-1bbd6b26a896
- 1
-
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12325
50
20
-
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12335
- Close polyline
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- Closed
- Closed
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- 0
-
-6777
12345
50
20
-
-6752
12355
- 1
- 1
- {0}
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- Resulting polyline
- 29aeb07e-85b9-473a-939b-8b16d18898c5
- Polyline
- Polyline
- false
- 0
-
-6703
12325
38
40
-
-6684
12345
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
- true
- 7d8a6ade-d0ba-40d7-85e5-2ca97cf49158
- PolyLine
- PolyLine
-
-6777
12391
116
44
-
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12413
- 1
- Polyline vertex points
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- Vertices
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- a55efd16-52de-4d42-9544-8d71af4bd8f5
- 1
-
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12393
50
20
-
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12403
- Close polyline
- a1b04df4-dc9e-468e-88eb-f5291cdf2b92
- Closed
- Closed
- false
- 0
-
-6775
12413
50
20
-
-6750
12423
- 1
- 1
- {0}
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- Resulting polyline
- b2a06bea-86fc-4dd0-8bfe-850bf7df6c4e
- Polyline
- Polyline
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- 0
-
-6701
12393
38
40
-
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12413
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
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- 3c1bc4dd-1cda-4c81-884b-2fc6a072b80b
- Merge
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-
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12312
90
64
-
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12344
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116
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35
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- d877597c-2f26-4a27-b4fc-6235f9374e04
- false
- Stream 0
- 0
- true
- 0
-
-6999
11217
40
20
-
-6979
11227
- 2
- Input stream at index 1
- 04ea4ce4-b469-43fb-974a-e3deda460b53
- false
- Stream 1
- 1
- true
- 83090ea2-cf17-4a67-8116-52ffd5b88d8f
- 1
-
-6999
11237
40
20
-
-6979
11247
- 2
- Filtered stream
- e0d9dc3c-a861-43f9-91f6-3db048f151b6
- false
- Stream
- S(0)
- false
- 0
-
-6935
11197
24
60
-
-6923
11227
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 5bd7e8d1-8354-4393-a409-e505ccf86e90
- Stream Filter
- Stream Filter
-
-7077
12265
92
64
-
-7023
12297
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 99af0755-0d84-453a-a8f0-15a402ce3130
- Gate
- Gate
- false
- 92dfb677-4945-46c1-ba10-6d9d2f3a170e
- 1
-
-7075
12267
40
20
-
-7055
12277
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 381db23c-40f2-4021-afd3-85010a193c00
- false
- Stream 0
- 0
- true
- 0
-
-7075
12287
40
20
-
-7055
12297
- 2
- Input stream at index 1
- f24880ec-3c8b-4ef8-8553-fadec6b85d96
- false
- Stream 1
- 1
- true
- c6e722f2-92b0-4558-beb1-fba620419e63
- 1
-
-7075
12307
40
20
-
-7055
12317
- 2
- Filtered stream
- aeb61ff0-bd0a-4098-9475-efec72c7673e
- false
- Stream
- S(0)
- false
- 0
-
-7011
12267
24
60
-
-6999
12297
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- f0e96c3f-e779-44a4-9862-315edd179c43
- Stream Filter
- Stream Filter
-
-7017
13503
92
64
-
-6963
13535
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 1e78bad0-2df3-443c-b14f-9b6f48e3a96d
- Gate
- Gate
- false
- 92dfb677-4945-46c1-ba10-6d9d2f3a170e
- 1
-
-7015
13505
40
20
-
-6995
13515
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 29b9ee40-fa7c-434a-8169-183398e57a15
- false
- Stream 0
- 0
- true
- 0
-
-7015
13525
40
20
-
-6995
13535
- 2
- Input stream at index 1
- 47b12ec4-d344-4d33-b2d9-05e633a6fdca
- false
- Stream 1
- 1
- true
- 27e7c501-931a-4323-ba95-c1dcd8638c1d
- 1
-
-7015
13545
40
20
-
-6995
13555
- 2
- Filtered stream
- 4b0cab58-d257-4fb7-b9a9-1b04f696e2d2
- false
- Stream
- S(0)
- false
- 0
-
-6951
13505
24
60
-
-6939
13535
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- b017d256-9aa7-4060-98d9-5e784a0a7cd9
- Stream Filter
- Stream Filter
-
-6997
14676
92
64
-
-6943
14708
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 451ee843-75ac-4d73-998b-164ece4342a3
- Gate
- Gate
- false
- 92dfb677-4945-46c1-ba10-6d9d2f3a170e
- 1
-
-6995
14678
40
20
-
-6975
14688
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- cfcf9154-9cae-495b-a03b-6698625fad23
- false
- Stream 0
- 0
- true
- 0
-
-6995
14698
40
20
-
-6975
14708
- 2
- Input stream at index 1
- ceb29de5-b1a3-4559-8146-d37078b28f88
- false
- Stream 1
- 1
- true
- 87166262-f90e-4df6-bfdc-8d5ff0afe20e
- 1
-
-6995
14718
40
20
-
-6975
14728
- 2
- Filtered stream
- 5c35a26d-0d9c-4676-a3af-c45b854148ca
- false
- Stream
- S(0)
- false
- 0
-
-6931
14678
24
60
-
-6919
14708
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- b664df6a-5160-42e7-87b8-af9f0ea1ee2b
- Stream Filter
- Stream Filter
-
-7012
15752
92
64
-
-6958
15784
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 9213edc5-888d-469e-aee2-74bad8a0a83d
- Gate
- Gate
- false
- 92dfb677-4945-46c1-ba10-6d9d2f3a170e
- 1
-
-7010
15754
40
20
-
-6990
15764
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 0b82203c-37e3-4e34-a3b8-904d9d892742
- false
- Stream 0
- 0
- true
- 0
-
-7010
15774
40
20
-
-6990
15784
- 2
- Input stream at index 1
- f8052ad8-4ad0-41de-a504-d9e881240d73
- false
- Stream 1
- 1
- true
- 55a9b8da-f51b-46f7-9956-1cfce98363c7
- 1
-
-7010
15794
40
20
-
-6990
15804
- 2
- Filtered stream
- d9c00061-44f3-4e23-ba0c-cc1b7e5671df
- false
- Stream
- S(0)
- false
- 0
-
-6946
15754
24
60
-
-6934
15784
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 4704d271-59ce-4af9-94e5-1a62eceb5448
- Stream Filter
- Stream Filter
-
-6953
16755
92
64
-
-6899
16787
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 97f7d4c6-2d9f-497c-bfe7-9b442195f935
- Gate
- Gate
- false
- 92dfb677-4945-46c1-ba10-6d9d2f3a170e
- 1
-
-6951
16757
40
20
-
-6931
16767
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 8014dc77-ab2a-45db-86b8-56d8e2730d32
- false
- Stream 0
- 0
- true
- 0
-
-6951
16777
40
20
-
-6931
16787
- 2
- Input stream at index 1
- 0e3e51de-66ab-4127-b872-4ef8c2ef2b67
- false
- Stream 1
- 1
- true
- 1149d574-8501-435b-a0b2-df2ba22f96e8
- 1
-
-6951
16797
40
20
-
-6931
16807
- 2
- Filtered stream
- 45c7a574-b387-4fe3-ae3e-00a14add492e
- false
- Stream
- S(0)
- false
- 0
-
-6887
16757
24
60
-
-6875
16787
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 94d38037-9a7a-4ac3-a117-fac9adb58793
- Stream Filter
- Stream Filter
-
-6962
17884
92
64
-
-6908
17916
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 0ad6ae3a-a3a2-4866-b3e0-f27eac6c76a3
- Gate
- Gate
- false
- 92dfb677-4945-46c1-ba10-6d9d2f3a170e
- 1
-
-6960
17886
40
20
-
-6940
17896
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 40d0ebce-b00e-4be8-aaf8-1eb5645b63d0
- false
- Stream 0
- 0
- true
- 0
-
-6960
17906
40
20
-
-6940
17916
- 2
- Input stream at index 1
- 98d5a932-b282-41b4-8424-cc6528fc2c5c
- false
- Stream 1
- 1
- true
- be615a1b-b5ca-456f-9216-7ca55cad191c
- 1
-
-6960
17926
40
20
-
-6940
17936
- 2
- Filtered stream
- e232eef0-15de-49e4-b844-a2a662441091
- false
- Stream
- S(0)
- false
- 0
-
-6896
17886
24
60
-
-6884
17916
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- ae977cc2-007b-4819-aab1-607bc574da3d
- Stream Filter
- Stream Filter
-
-6908
19040
92
64
-
-6854
19072
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 4ee2ac55-a2ce-4aa3-a2c4-3ae4de5c9a12
- Gate
- Gate
- false
- 92dfb677-4945-46c1-ba10-6d9d2f3a170e
- 1
-
-6906
19042
40
20
-
-6886
19052
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 2f671999-2df2-49bd-a78a-0968fb4e4704
- false
- Stream 0
- 0
- true
- 0
-
-6906
19062
40
20
-
-6886
19072
- 2
- Input stream at index 1
- 43ec97a6-501d-4840-b451-153ff951bf39
- false
- Stream 1
- 1
- true
- 424c8d2f-e0fa-482b-81a1-f7c2a6375ff5
- 1
-
-6906
19082
40
20
-
-6886
19092
- 2
- Filtered stream
- 6cf5bfc7-cc33-45ca-add3-e4f38a61d380
- false
- Stream
- S(0)
- false
- 0
-
-6842
19042
24
60
-
-6830
19072
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 40d0d220-c1df-41fe-a4ac-5d725e326324
- Stream Filter
- Stream Filter
-
-6871
20179
92
64
-
-6817
20211
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 915699c1-b62b-42ae-90b0-0885d42ed97d
- Gate
- Gate
- false
- 92dfb677-4945-46c1-ba10-6d9d2f3a170e
- 1
-
-6869
20181
40
20
-
-6849
20191
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 64c59ebc-ffa2-49d1-8621-423b5b4f03a6
- false
- Stream 0
- 0
- true
- 0
-
-6869
20201
40
20
-
-6849
20211
- 2
- Input stream at index 1
- 286cdb93-f769-441f-a32f-c56ca6656fde
- false
- Stream 1
- 1
- true
- df097d69-a4f5-4ef7-ab1f-1a0727ff6f06
- 1
-
-6869
20221
40
20
-
-6849
20231
- 2
- Filtered stream
- 7c3b70d3-ffab-4356-a42b-31da084be03a
- false
- Stream
- S(0)
- false
- 0
-
-6805
20181
24
60
-
-6793
20211
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 3
-
255;255;255;255
- A group of Grasshopper objects
- 38e33091-5805-4830-b960-f7b95e820fd2
- 1
- a1ac0900-3dd8-44d2-860f-83352b920fda
- Group
- ᗱᗴ
- 59e0b89a-e487-49f8-bab8-b5bab16be14c
- Panel
- A panel for custom notes and text values
- 87daaa5c-75e3-464f-ac08-f6f513799ccb
- Panel
- #
- false
- 0
- 0
- 1024
-
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156
160
100
- 0
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- 0
-
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156.4436
-
255;255;255;255
- true
- true
- true
- false
- false
- true
- 3e8ca6be-fda8-4aaf-b5c0-3c54c8bb7312
- Number
- Contains a collection of floating point numbers
- e2d5421d-793a-4786-9e3b-7530f182e59f
- Number
- Number
- false
- 0
-
-4530
86
49
24
-
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98.35362
- 59e0b89a-e487-49f8-bab8-b5bab16be14c
- Panel
- A panel for custom notes and text values
- 1e42e4ee-225b-427d-95a0-827d03bae077
- Panel
- ⊚
- false
- 0
- e7c315e7-6046-4360-a3b1-dc1f18620e40
- 1
-
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779
147
55
- 0
- 0
- 0
-
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779.59
- 2
-
255;255;255;255
- false
- false
- true
- false
- false
- true
- c74efd0e-7fe3-4c2d-8c9d-295c5672fb13
- Null Item
- Test a data item for null or invalidity
- true
- 35cc33c8-2ec6-4de4-82f7-cbdc643d1827
- Null Item
- Null Item
-
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12168
128
64
-
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12200
- Item to test
- a17212d0-4c05-4c33-8e3d-389e5333f6de
- Item
- Item
- true
- c6e722f2-92b0-4558-beb1-fba620419e63
- 1
-
-7091
12170
24
60
-
-7079
12200
- True if item is Null
- 24b97ec9-2c74-4757-aca7-87fb8d388365
- 1
- Null Flags
- Null Flags
- false
- 0
-
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12170
76
20
-
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12180
- True if item is Invalid
- bf5046cf-2155-4f6e-aa97-c7c55ce87f98
- Invalid Flags
- Invalid Flags
- false
- 0
-
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12190
76
20
-
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12200
- A textual description of the object state
- a10398c8-44c9-4840-97e2-4a47e8b317c9
- Description
- Description
- false
- 0
-
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12210
76
20
-
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12220
- 7c9d9882-545d-434b-9850-2f3c6b01296b
- 08bdcae0-d034-48dd-a145-24a9fcf3d3ff
- Min / Max
- Extract the minimum and the maximum value of a list of numbers
- true
- 72339650-e0db-4bb9-9c0e-29a807d12cb2
- Min / Max
- Min / Max
-
-6929
12168
115
44
-
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12190
- 1
- Set of Numbers
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- Number
- Number
- false
- 24b97ec9-2c74-4757-aca7-87fb8d388365
- 1
-
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12170
39
40
-
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12190
- Minimum
- 3043b375-5d68-4163-b9ad-80de0cb16839
- Minimum
- Minimum
- false
- 0
-
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12170
48
20
-
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12180
- Maximum
- 907cc860-6b5a-4cb7-95ec-26a204048c14
- Maximum
- Maximum
- false
- 0
-
-6864
12190
48
20
-
-6840
12200
- cb2c7d3c-41b4-4c6d-a6bd-9235bd2851bb
- Gate Not
- Perform boolean negation (NOT gate).
- true
- bf0f2a74-6bf4-4cf8-a0a2-02cb0de8c4fe
- Gate Not
- Gate Not
-
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12172
70
28
-
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12186
- Boolean value
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- A
- A
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- 1
-
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12174
11
24
-
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12186
- Inverse of {A}
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- Result
- Result
- false
- 0
-
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12174
31
24
-
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12186
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- f1109cf8-3e0b-4391-afe5-5fcd61c8a0de
- Stream Filter
- Stream Filter
-
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12307
92
64
-
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12339
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 91ab83a0-f6c5-46ec-b2e7-1d708acac6ab
- Gate
- Gate
- false
- 25111c3d-21ca-4ffb-afd0-0f0c756e1d39
- 1
-
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12309
40
20
-
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12319
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 4ef35a03-9705-4eb0-9f68-1816dc541ae1
- false
- Stream 0
- 0
- true
- 0
-
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12329
40
20
-
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12339
- 2
- Input stream at index 1
- 2bba781c-6a7b-4152-a92f-e9f1714f5686
- false
- Stream 1
- 1
- true
- 0f119f9f-261b-4425-b9ac-cb6a8fa58f56
- 1
-
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12349
40
20
-
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12359
- 2
- Filtered stream
- fa4bc97d-3c82-4a5a-8b8b-dd5445560a7c
- false
- Stream
- S(1)
- false
- 0
-
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12309
24
60
-
-5499
12339
- c74efd0e-7fe3-4c2d-8c9d-295c5672fb13
- Null Item
- Test a data item for null or invalidity
- true
- 3f2325cf-9510-4d9c-b4b7-a3f70c723cd9
- Null Item
- Null Item
-
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3541
128
64
-
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3573
- Item to test
- e61d4284-20de-4b87-9616-b0ae87afc3d0
- Item
- Item
- true
- d040adbf-b17a-4020-beba-bdab4bcf43d5
- 1
-
-7745
3543
24
60
-
-7733
3573
- True if item is Null
- a70c3c9f-2f96-442b-beec-394a2663079b
- 1
- Null Flags
- Null Flags
- false
- 0
-
-7697
3543
76
20
-
-7667
3553
- True if item is Invalid
- 4513738e-8338-47f0-8028-43fc37ad03ba
- Invalid Flags
- Invalid Flags
- false
- 0
-
-7697
3563
76
20
-
-7667
3573
- A textual description of the object state
- 9127bce0-f88e-4b9b-8325-b682b0d2be9a
- Description
- Description
- false
- 0
-
-7697
3583
76
20
-
-7667
3593
- 7c9d9882-545d-434b-9850-2f3c6b01296b
- 08bdcae0-d034-48dd-a145-24a9fcf3d3ff
- Min / Max
- Extract the minimum and the maximum value of a list of numbers
- true
- 4013bb1a-8a06-4b2a-a77a-11ec68c8c8bb
- Min / Max
- Min / Max
-
-7597
3531
115
44
-
-7544
3553
- 1
- Set of Numbers
- d09b6ab3-e05e-43ef-beb3-af650ad843fa
- Number
- Number
- false
- a70c3c9f-2f96-442b-beec-394a2663079b
- 1
-
-7595
3533
39
40
-
-7575.5
3553
- Minimum
- 330c5023-18e8-4911-af46-8bb9d7a1fdf4
- Minimum
- Minimum
- false
- 0
-
-7532
3533
48
20
-
-7508
3543
- Maximum
- 0b1b7c6e-4ca1-4bcd-b0f9-21d2409f20bd
- Maximum
- Maximum
- false
- 0
-
-7532
3553
48
20
-
-7508
3563
- cb2c7d3c-41b4-4c6d-a6bd-9235bd2851bb
- Gate Not
- Perform boolean negation (NOT gate).
- true
- 189dd2a9-82f7-49c4-878c-0e52bb36583f
- Gate Not
- Gate Not
-
-7459
3549
70
28
-
-7434
3563
- Boolean value
- 901f909c-7bb2-417a-97ff-4963637a9801
- A
- A
- false
- 0b1b7c6e-4ca1-4bcd-b0f9-21d2409f20bd
- 1
-
-7457
3551
11
24
-
-7451.5
3563
- Inverse of {A}
- 538bcd17-2e47-46da-b7c8-d30390ab8c9c
- Result
- Result
- false
- 0
-
-7422
3551
31
24
-
-7406.5
3563
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- ac4eb0e1-0629-423d-86d3-698fe1fbe3be
- Stream Filter
- Stream Filter
-
-5795
3585
92
64
-
-5741
3617
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 33978c7b-0a2d-46eb-b2d9-63c16f7a391c
- Gate
- Gate
- false
- 538bcd17-2e47-46da-b7c8-d30390ab8c9c
- 1
-
-5793
3587
40
20
-
-5773
3597
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- e146e615-c617-4312-a7d2-08ee2a1b3ab3
- false
- Stream 0
- 0
- true
- 0
-
-5793
3607
40
20
-
-5773
3617
- 2
- Input stream at index 1
- 64d60379-b575-4112-bc03-90d913bcd4c1
- false
- Stream 1
- 1
- true
- cc39f9f6-c9c7-4df2-b57d-b44bce6c64c0
- 1
-
-5793
3627
40
20
-
-5773
3637
- 2
- Filtered stream
- 75fc82ae-e535-43d8-8cea-21b2a580a62e
- false
- Stream
- S(1)
- false
- 0
-
-5729
3587
24
60
-
-5717
3617
- c74efd0e-7fe3-4c2d-8c9d-295c5672fb13
- Null Item
- Test a data item for null or invalidity
- true
- a8094a18-bafe-447f-a1e5-d50f443f6c8d
- Null Item
- Null Item
-
-7219
4517
128
64
-
-7181
4549
- Item to test
- 82a62292-6bc5-47d6-b336-1369d94ba43a
- Item
- Item
- true
- bf02b6a7-2c32-4838-9324-0fa547efef5e
- 1
-
-7217
4519
24
60
-
-7205
4549
- True if item is Null
- c3a4ae0a-d5e9-483b-a4dc-2ea16ff547d4
- 1
- Null Flags
- Null Flags
- false
- 0
-
-7169
4519
76
20
-
-7139
4529
- True if item is Invalid
- 86d204a4-ec45-4555-ad20-960e96e72291
- Invalid Flags
- Invalid Flags
- false
- 0
-
-7169
4539
76
20
-
-7139
4549
- A textual description of the object state
- 1a0611c8-0f02-4920-bb42-ecae33d37518
- Description
- Description
- false
- 0
-
-7169
4559
76
20
-
-7139
4569
- 7c9d9882-545d-434b-9850-2f3c6b01296b
- 08bdcae0-d034-48dd-a145-24a9fcf3d3ff
- Min / Max
- Extract the minimum and the maximum value of a list of numbers
- true
- be452c49-8669-4366-becd-7b6bb0edf3ce
- Min / Max
- Min / Max
-
-7055
4517
115
44
-
-7002
4539
- 1
- Set of Numbers
- fe9cc553-c348-415d-a674-35ca07f8cb3f
- Number
- Number
- false
- c3a4ae0a-d5e9-483b-a4dc-2ea16ff547d4
- 1
-
-7053
4519
39
40
-
-7033.5
4539
- Minimum
- 8208d769-9be0-477f-8940-4b5859bf4c22
- Minimum
- Minimum
- false
- 0
-
-6990
4519
48
20
-
-6966
4529
- Maximum
- d598ed14-f257-4d9b-a5f3-99946b1fbb4d
- Maximum
- Maximum
- false
- 0
-
-6990
4539
48
20
-
-6966
4549
- cb2c7d3c-41b4-4c6d-a6bd-9235bd2851bb
- Gate Not
- Perform boolean negation (NOT gate).
- true
- d646942a-7636-44c6-98e1-f72444dfd831
- Gate Not
- Gate Not
-
-6904
4521
70
28
-
-6879
4535
- Boolean value
- 8ab5f103-6967-4002-8173-15d9a6fe2d8e
- A
- A
- false
- d598ed14-f257-4d9b-a5f3-99946b1fbb4d
- 1
-
-6902
4523
11
24
-
-6896.5
4535
- Inverse of {A}
- 5fa81d7b-ae98-4e4a-bfdb-9ada698cf631
- Result
- Result
- false
- 0
-
-6867
4523
31
24
-
-6851.5
4535
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 2df6c65e-08c7-4660-9cc8-f4a18301d889
- Stream Filter
- Stream Filter
-
-5777
4573
92
64
-
-5723
4605
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 16406ef3-d8bd-4150-be29-dead03773ad7
- Gate
- Gate
- false
- 5fa81d7b-ae98-4e4a-bfdb-9ada698cf631
- 1
-
-5775
4575
40
20
-
-5755
4585
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 93e1a8fc-06ec-42ce-b0ab-e189211ba4d3
- false
- Stream 0
- 0
- true
- 0
-
-5775
4595
40
20
-
-5755
4605
- 2
- Input stream at index 1
- 120144d8-961e-4ffc-87b7-f4de9a43fe62
- false
- Stream 1
- 1
- true
- b67db8b0-4ac4-430d-be27-39be205c7d61
- 1
-
-5775
4615
40
20
-
-5755
4625
- 2
- Filtered stream
- 9fcffae3-3a3f-4651-a205-1f89243e9353
- false
- Stream
- S(1)
- false
- 0
-
-5711
4575
24
60
-
-5699
4605
- c74efd0e-7fe3-4c2d-8c9d-295c5672fb13
- Null Item
- Test a data item for null or invalidity
- true
- d7f3135f-1177-4b0f-8b05-6ce46940feb4
- Null Item
- Null Item
-
-7147
5451
128
64
-
-7109
5483
- Item to test
- 7a5e3346-84c6-4356-96e0-47a3a51f957e
- Item
- Item
- true
- 9aa9fdf5-c248-4bf6-afe3-b324ca007251
- 1
-
-7145
5453
24
60
-
-7133
5483
- True if item is Null
- 53617fcd-cb0c-43ea-a0e9-9a35a5ee4099
- 1
- Null Flags
- Null Flags
- false
- 0
-
-7097
5453
76
20
-
-7067
5463
- True if item is Invalid
- b78284f8-37d3-4341-ad05-89a04047fe05
- Invalid Flags
- Invalid Flags
- false
- 0
-
-7097
5473
76
20
-
-7067
5483
- A textual description of the object state
- 058b65a1-c2e5-4625-8df7-3570ebf8e99f
- Description
- Description
- false
- 0
-
-7097
5493
76
20
-
-7067
5503
- 7c9d9882-545d-434b-9850-2f3c6b01296b
- 08bdcae0-d034-48dd-a145-24a9fcf3d3ff
- Min / Max
- Extract the minimum and the maximum value of a list of numbers
- true
- 00ceb525-9e87-4db3-9802-667580ba1078
- Min / Max
- Min / Max
-
-6983
5451
115
44
-
-6930
5473
- 1
- Set of Numbers
- c3315609-f58f-4506-b8ef-5b499ee91f26
- Number
- Number
- false
- 53617fcd-cb0c-43ea-a0e9-9a35a5ee4099
- 1
-
-6981
5453
39
40
-
-6961.5
5473
- Minimum
- 6eecbe0a-786e-4500-9023-e0036260ce84
- Minimum
- Minimum
- false
- 0
-
-6918
5453
48
20
-
-6894
5463
- Maximum
- 93be164d-631d-4706-aaa0-61f1c643d2e6
- Maximum
- Maximum
- false
- 0
-
-6918
5473
48
20
-
-6894
5483
- cb2c7d3c-41b4-4c6d-a6bd-9235bd2851bb
- Gate Not
- Perform boolean negation (NOT gate).
- true
- f3c88c5d-9ab5-4a48-8e2b-b86ef9537f38
- Gate Not
- Gate Not
-
-6832
5455
70
28
-
-6807
5469
- Boolean value
- 9af6d155-d97a-4a53-a1e5-d55dcbf2dca3
- A
- A
- false
- 93be164d-631d-4706-aaa0-61f1c643d2e6
- 1
-
-6830
5457
11
24
-
-6824.5
5469
- Inverse of {A}
- fbb890a1-5183-4102-944f-95013c6261bd
- Result
- Result
- false
- 0
-
-6795
5457
31
24
-
-6779.5
5469
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 17755101-7062-42de-ba3b-de5fe2af1944
- Stream Filter
- Stream Filter
-
-5677
5501
92
64
-
-5623
5533
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- f49fe484-3cfc-47b0-aadd-80e2434a514a
- Gate
- Gate
- false
- fbb890a1-5183-4102-944f-95013c6261bd
- 1
-
-5675
5503
40
20
-
-5655
5513
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- b0223655-9b78-4e47-ace1-2cc5ed775f3a
- false
- Stream 0
- 0
- true
- 0
-
-5675
5523
40
20
-
-5655
5533
- 2
- Input stream at index 1
- e1e8c4b5-f1e0-4114-a673-f363d5af642c
- false
- Stream 1
- 1
- true
- 25d8da2c-a18b-475a-87f0-e332861fb3b3
- 1
-
-5675
5543
40
20
-
-5655
5553
- 2
- Filtered stream
- e49badfa-457c-44b7-a041-d1654e42fc37
- false
- Stream
- S(1)
- false
- 0
-
-5611
5503
24
60
-
-5599
5533
- c74efd0e-7fe3-4c2d-8c9d-295c5672fb13
- Null Item
- Test a data item for null or invalidity
- true
- 6cb3cdab-825d-4a25-b6d7-c8ce93e6b860
- Null Item
- Null Item
-
-7063
6463
128
64
-
-7025
6495
- Item to test
- 05d22590-dfa4-487b-b9fc-40746c5187e9
- Item
- Item
- true
- 14273b4c-e52e-48ca-b8ab-682e73fe2600
- 1
-
-7061
6465
24
60
-
-7049
6495
- True if item is Null
- 9f954724-61fd-4f30-bf3b-5be741d2ad38
- 1
- Null Flags
- Null Flags
- false
- 0
-
-7013
6465
76
20
-
-6983
6475
- True if item is Invalid
- e5ac74b2-2304-49c2-ab3b-e514ffb5d702
- Invalid Flags
- Invalid Flags
- false
- 0
-
-7013
6485
76
20
-
-6983
6495
- A textual description of the object state
- 3f775720-99c8-4d87-8082-1a114e50fb73
- Description
- Description
- false
- 0
-
-7013
6505
76
20
-
-6983
6515
- 7c9d9882-545d-434b-9850-2f3c6b01296b
- 08bdcae0-d034-48dd-a145-24a9fcf3d3ff
- Min / Max
- Extract the minimum and the maximum value of a list of numbers
- true
- 072e65b2-2f5a-4a67-ba98-de57ff321e0a
- Min / Max
- Min / Max
-
-6899
6463
115
44
-
-6846
6485
- 1
- Set of Numbers
- 3ee8b196-b2a7-43bd-87fa-c9d70c55996f
- Number
- Number
- false
- 9f954724-61fd-4f30-bf3b-5be741d2ad38
- 1
-
-6897
6465
39
40
-
-6877.5
6485
- Minimum
- f4b55248-208f-4228-ab11-054e59d08b2a
- Minimum
- Minimum
- false
- 0
-
-6834
6465
48
20
-
-6810
6475
- Maximum
- e4b0b066-26b0-448e-a5c8-f4e5c3b4bcc8
- Maximum
- Maximum
- false
- 0
-
-6834
6485
48
20
-
-6810
6495
- cb2c7d3c-41b4-4c6d-a6bd-9235bd2851bb
- Gate Not
- Perform boolean negation (NOT gate).
- true
- 01823b6f-3915-46e2-bb6c-45ee2f0b1d75
- Gate Not
- Gate Not
-
-6748
6467
70
28
-
-6723
6481
- Boolean value
- 0927c3b9-4aa8-43e1-9078-1096f8ec3895
- A
- A
- false
- e4b0b066-26b0-448e-a5c8-f4e5c3b4bcc8
- 1
-
-6746
6469
11
24
-
-6740.5
6481
- Inverse of {A}
- d3d8423d-b76c-460e-8176-3ebcb3be397d
- Result
- Result
- false
- 0
-
-6711
6469
31
24
-
-6695.5
6481
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 87135cf1-b079-4cb3-bf64-3722c5ca823e
- Stream Filter
- Stream Filter
-
-5593
6513
92
64
-
-5539
6545
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 204e91b7-8b54-469d-8ad1-fb4ff58123c3
- Gate
- Gate
- false
- d3d8423d-b76c-460e-8176-3ebcb3be397d
- 1
-
-5591
6515
40
20
-
-5571
6525
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 453b8df4-ff60-46ce-88f0-6efb394b4562
- false
- Stream 0
- 0
- true
- 0
-
-5591
6535
40
20
-
-5571
6545
- 2
- Input stream at index 1
- 3b3e7dd0-c139-49fb-a308-7abf58d2d736
- false
- Stream 1
- 1
- true
- 51de33f0-e511-4a37-8537-cce5e8deb152
- 1
-
-5591
6555
40
20
-
-5571
6565
- 2
- Filtered stream
- e9c7e654-d046-48b6-9a42-23807c78b8a8
- false
- Stream
- S(1)
- false
- 0
-
-5527
6515
24
60
-
-5515
6545
- c74efd0e-7fe3-4c2d-8c9d-295c5672fb13
- Null Item
- Test a data item for null or invalidity
- true
- 4f25cec0-7e3f-43b9-a363-1b7cd2747a9f
- Null Item
- Null Item
-
-7060
7610
128
64
-
-7022
7642
- Item to test
- f993cfcd-d680-46b8-a928-2bfb242ea0d7
- Item
- Item
- true
- 43c898bd-1523-42e9-9485-b3cd42382016
- 1
-
-7058
7612
24
60
-
-7046
7642
- True if item is Null
- 71caca59-5a1d-4b88-9d15-ba7633f6f69a
- 1
- Null Flags
- Null Flags
- false
- 0
-
-7010
7612
76
20
-
-6980
7622
- True if item is Invalid
- dfc56233-4395-44f5-be6e-afcaff8f8714
- Invalid Flags
- Invalid Flags
- false
- 0
-
-7010
7632
76
20
-
-6980
7642
- A textual description of the object state
- 3b681b16-66d2-4e3b-b309-b5b35b58583d
- Description
- Description
- false
- 0
-
-7010
7652
76
20
-
-6980
7662
- 7c9d9882-545d-434b-9850-2f3c6b01296b
- 08bdcae0-d034-48dd-a145-24a9fcf3d3ff
- Min / Max
- Extract the minimum and the maximum value of a list of numbers
- true
- 4bec467c-e348-430f-a67d-ad4288ebf902
- Min / Max
- Min / Max
-
-6896
7610
115
44
-
-6843
7632
- 1
- Set of Numbers
- 3bb95461-355d-431f-b4d5-6a0dcee3139d
- Number
- Number
- false
- 71caca59-5a1d-4b88-9d15-ba7633f6f69a
- 1
-
-6894
7612
39
40
-
-6874.5
7632
- Minimum
- 1fd4fb0a-fd07-4924-a15e-e0cb43abe349
- Minimum
- Minimum
- false
- 0
-
-6831
7612
48
20
-
-6807
7622
- Maximum
- 1a36e77a-f207-41a8-8a48-ef7fb3367cdd
- Maximum
- Maximum
- false
- 0
-
-6831
7632
48
20
-
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7642
- cb2c7d3c-41b4-4c6d-a6bd-9235bd2851bb
- Gate Not
- Perform boolean negation (NOT gate).
- true
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- Gate Not
- Gate Not
-
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7614
70
28
-
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7628
- Boolean value
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- A
- A
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- 1
-
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7616
11
24
-
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7628
- Inverse of {A}
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- Result
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- 0
-
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7616
31
24
-
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7628
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 2c24899b-2b57-4192-8893-96e535b58ccd
- Stream Filter
- Stream Filter
-
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7670
92
64
-
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7702
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
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- Index of Gate stream
- b7ef675f-fcb5-4e9f-811a-9ae9707687ed
- Gate
- Gate
- false
- d7a5e523-7978-46d0-9ffe-8254a2b71250
- 1
-
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7672
40
20
-
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7682
- 1
- 1
- {0}
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- Input stream at index 0
- a2af7d81-1e5d-4c0c-931d-b7e2fbf931c8
- false
- Stream 0
- 0
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-
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7692
40
20
-
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7702
- 2
- Input stream at index 1
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- false
- Stream 1
- 1
- true
- 6c97f623-62c8-4828-a8bf-06f573b3a0c5
- 1
-
-5535
7712
40
20
-
-5515
7722
- 2
- Filtered stream
- 2188b720-4c97-42ae-9fcb-7e1a982bad49
- false
- Stream
- S(1)
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- 0
-
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7672
24
60
-
-5459
7702
- c74efd0e-7fe3-4c2d-8c9d-295c5672fb13
- Null Item
- Test a data item for null or invalidity
- true
- 37488903-bcf2-4b36-a4bf-5cc30a0b9a3c
- Null Item
- Null Item
-
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8735
128
64
-
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8767
- Item to test
- 525d82a8-491f-434d-a0a1-6246a0a543db
- Item
- Item
- true
- 5bc7a3d5-b08a-4185-93b3-ed22b830d52b
- 1
-
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8737
24
60
-
-7068
8767
- True if item is Null
- ddaf865a-6a4f-4207-8f3b-9c3d651c3962
- 1
- Null Flags
- Null Flags
- false
- 0
-
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8737
76
20
-
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8747
- True if item is Invalid
- 7665f0dc-1418-4dc5-8995-e4ea104a0578
- Invalid Flags
- Invalid Flags
- false
- 0
-
-7032
8757
76
20
-
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8767
- A textual description of the object state
- 0f3fb516-7a33-40f7-8a9d-b275f97d5e0a
- Description
- Description
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- 0
-
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8777
76
20
-
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8787
- 7c9d9882-545d-434b-9850-2f3c6b01296b
- 08bdcae0-d034-48dd-a145-24a9fcf3d3ff
- Min / Max
- Extract the minimum and the maximum value of a list of numbers
- true
- 85ad36ee-61e0-44af-961f-930419003d84
- Min / Max
- Min / Max
-
-6918
8735
115
44
-
-6865
8757
- 1
- Set of Numbers
- 77ad5e58-68af-4019-a7c0-ede669fa6eb4
- Number
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- false
- ddaf865a-6a4f-4207-8f3b-9c3d651c3962
- 1
-
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8737
39
40
-
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8757
- Minimum
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- Minimum
- Minimum
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- 0
-
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8737
48
20
-
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8747
- Maximum
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- Maximum
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- 0
-
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8757
48
20
-
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8767
- cb2c7d3c-41b4-4c6d-a6bd-9235bd2851bb
- Gate Not
- Perform boolean negation (NOT gate).
- true
- ab5ce525-5bd9-49a2-a408-5d8a2814337b
- Gate Not
- Gate Not
-
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8739
70
28
-
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8753
- Boolean value
- 2fa61665-e02f-4437-bbf9-078109a99136
- A
- A
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- a6df61a9-5d42-4b23-8a4f-5b3b2a19750d
- 1
-
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8741
11
24
-
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- Inverse of {A}
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- Result
- Result
- false
- 0
-
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8741
31
24
-
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8753
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 204e7fe9-7a7e-479a-b489-4892b355619f
- Stream Filter
- Stream Filter
-
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8795
92
64
-
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8827
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
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- Gate
- Gate
- false
- b16f4576-fb27-4f10-9fe6-0e4da0596c1a
- 1
-
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8797
40
20
-
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8807
- 1
- 1
- {0}
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- Input stream at index 0
- 83bd125d-6fc5-42ce-9201-07e195f5a9a0
- false
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8817
40
20
-
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8827
- 2
- Input stream at index 1
- 8789779f-0f56-4994-8d3a-befb8c2533dc
- false
- Stream 1
- 1
- true
- 04d3379a-0378-4c82-ae41-61eb01f18331
- 1
-
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8837
40
20
-
-5537
8847
- 2
- Filtered stream
- 7d5a3f05-11af-425b-82e5-419e541ce9a6
- false
- Stream
- S(1)
- false
- 0
-
-5493
8797
24
60
-
-5481
8827
- c74efd0e-7fe3-4c2d-8c9d-295c5672fb13
- Null Item
- Test a data item for null or invalidity
- true
- 2c8bcb43-7b73-46d0-96e4-219adbe7c087
- Null Item
- Null Item
-
-7065
9941
128
64
-
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9973
- Item to test
- 6eeec69a-a1d4-4858-898f-e498b382e12b
- Item
- Item
- true
- 183384e9-0dcf-4b35-adf3-b86f942908d0
- 1
-
-7063
9943
24
60
-
-7051
9973
- True if item is Null
- 2b4a67fb-ae7c-4ba1-bc65-027125293f34
- 1
- Null Flags
- Null Flags
- false
- 0
-
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9943
76
20
-
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9953
- True if item is Invalid
- 0d2c0dc8-f3ea-431e-9788-c6837d202db8
- Invalid Flags
- Invalid Flags
- false
- 0
-
-7015
9963
76
20
-
-6985
9973
- A textual description of the object state
- bdb6013c-1541-4765-a267-1cf5d8d4a3ad
- Description
- Description
- false
- 0
-
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9983
76
20
-
-6985
9993
- 7c9d9882-545d-434b-9850-2f3c6b01296b
- 08bdcae0-d034-48dd-a145-24a9fcf3d3ff
- Min / Max
- Extract the minimum and the maximum value of a list of numbers
- true
- d7f23d19-54d1-4799-831a-57a3a7ec8ba4
- Min / Max
- Min / Max
-
-6901
9941
115
44
-
-6848
9963
- 1
- Set of Numbers
- 7dbcddeb-55b6-416d-a06e-76e11fb3c1cd
- Number
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- false
- 2b4a67fb-ae7c-4ba1-bc65-027125293f34
- 1
-
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9943
39
40
-
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9963
- Minimum
- fbdd786e-1ab7-417e-a127-b398583e8ed3
- Minimum
- Minimum
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- 0
-
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9943
48
20
-
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9953
- Maximum
- 8eea0321-eced-40bb-ab55-6bed6726c9ba
- Maximum
- Maximum
- false
- 0
-
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9963
48
20
-
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9973
- cb2c7d3c-41b4-4c6d-a6bd-9235bd2851bb
- Gate Not
- Perform boolean negation (NOT gate).
- true
- 8cd4a1d2-ace0-4a5e-b868-df7b83f2402a
- Gate Not
- Gate Not
-
-6750
9945
70
28
-
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9959
- Boolean value
- d753f1c2-cfd4-47e6-96c0-0234fa1a2988
- A
- A
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- 8eea0321-eced-40bb-ab55-6bed6726c9ba
- 1
-
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9947
11
24
-
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9959
- Inverse of {A}
- f95d28f9-5c1b-4737-880d-d56ef8853fd9
- Result
- Result
- false
- 0
-
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9947
31
24
-
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9959
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- ccbe8cdf-717b-4b38-a4b0-d2265f7b5b4d
- Stream Filter
- Stream Filter
-
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10001
92
64
-
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10033
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- cf8f1d40-481a-4a0f-b880-52074d3f28d5
- Gate
- Gate
- false
- f95d28f9-5c1b-4737-880d-d56ef8853fd9
- 1
-
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10003
40
20
-
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10013
- 1
- 1
- {0}
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- Input stream at index 0
- 893def05-ac6b-49ca-9d84-5f626fe4fcf6
- false
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- 0
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-
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10023
40
20
-
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10033
- 2
- Input stream at index 1
- 4ae4fde1-8026-4227-ba5d-04b145dbda87
- false
- Stream 1
- 1
- true
- ad549466-4ec2-4830-aced-c029153ed38a
- 1
-
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10043
40
20
-
-5520
10053
- 2
- Filtered stream
- ce57a692-0419-4a89-a644-041b170de089
- false
- Stream
- S(1)
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- 0
-
-5476
10003
24
60
-
-5464
10033
- c74efd0e-7fe3-4c2d-8c9d-295c5672fb13
- Null Item
- Test a data item for null or invalidity
- true
- ef845926-e270-4238-9c31-7826bcd7dc35
- Null Item
- Null Item
-
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11109
128
64
-
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11141
- Item to test
- 26cdc6fc-da24-482d-9fc1-0a8bde92164c
- Item
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- true
- 83090ea2-cf17-4a67-8116-52ffd5b88d8f
- 1
-
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11111
24
60
-
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11141
- True if item is Null
- f24a96ec-f551-424d-b26a-072846e268de
- 1
- Null Flags
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- 0
-
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11111
76
20
-
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11121
- True if item is Invalid
- 0663b653-456a-4146-93ca-64ca58e64262
- Invalid Flags
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- false
- 0
-
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11131
76
20
-
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11141
- A textual description of the object state
- f8cb1f09-78c3-4b9f-94af-5b7bb63e1fb9
- Description
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-
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11151
76
20
-
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11161
- 7c9d9882-545d-434b-9850-2f3c6b01296b
- 08bdcae0-d034-48dd-a145-24a9fcf3d3ff
- Min / Max
- Extract the minimum and the maximum value of a list of numbers
- true
- bfeb3fd9-9103-4fd0-95ac-022b5a5f48c1
- Min / Max
- Min / Max
-
-6859
11109
115
44
-
-6806
11131
- 1
- Set of Numbers
- e6f63a9c-2422-4f1b-ab10-3931a44cbea1
- Number
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- false
- f24a96ec-f551-424d-b26a-072846e268de
- 1
-
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11111
39
40
-
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11131
- Minimum
- ea7d8250-db50-42c3-b883-81505d9a4d09
- Minimum
- Minimum
- false
- 0
-
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11111
48
20
-
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11121
- Maximum
- 5a85cc1f-6412-43ab-9da8-073b8bf971a4
- Maximum
- Maximum
- false
- 0
-
-6794
11131
48
20
-
-6770
11141
- cb2c7d3c-41b4-4c6d-a6bd-9235bd2851bb
- Gate Not
- Perform boolean negation (NOT gate).
- true
- 192df5d3-f93a-4aef-a40e-cbad90f6d75b
- Gate Not
- Gate Not
-
-6708
11113
70
28
-
-6683
11127
- Boolean value
- 1505cf56-234b-45ad-bc75-ef43fab88efb
- A
- A
- false
- 5a85cc1f-6412-43ab-9da8-073b8bf971a4
- 1
-
-6706
11115
11
24
-
-6700.5
11127
- Inverse of {A}
- 6aa859da-faad-431e-8679-ca71bf8af6fe
- Result
- Result
- false
- 0
-
-6671
11115
31
24
-
-6655.5
11127
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 25c75de0-e074-469e-af87-ed42c1e4189a
- Stream Filter
- Stream Filter
-
-5500
11169
92
64
-
-5446
11201
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- c9427943-f9a8-4d48-8a43-7797e98aa96a
- Gate
- Gate
- false
- 6aa859da-faad-431e-8679-ca71bf8af6fe
- 1
-
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11171
40
20
-
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11181
- 1
- 1
- {0}
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- 2
- Input stream at index 0
- 7a2c1e3d-a216-4034-9974-967db57e4d3f
- false
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- 0
- true
- 0
-
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11191
40
20
-
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11201
- 2
- Input stream at index 1
- 9979f7c5-ee42-4ff1-91fe-d3b6929249b4
- false
- Stream 1
- 1
- true
- 0de2eaa7-c2bc-4cbc-b548-271df3bcf16a
- 1
-
-5498
11211
40
20
-
-5478
11221
- 2
- Filtered stream
- ba724b87-59f4-42c1-b032-80d0e7a043b6
- false
- Stream
- S(1)
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- 0
-
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11171
24
60
-
-5422
11201
- c74efd0e-7fe3-4c2d-8c9d-295c5672fb13
- Null Item
- Test a data item for null or invalidity
- true
- 6fe9ab0f-7fbf-4f24-b49d-8304568d8891
- Null Item
- Null Item
-
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13390
128
64
-
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13422
- Item to test
- 0657d3b2-41e9-4609-9ab0-562af0750fc2
- Item
- Item
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- 27e7c501-931a-4323-ba95-c1dcd8638c1d
- 1
-
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13392
24
60
-
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13422
- True if item is Null
- 82ba3565-15cc-43a6-bdb7-bb0c8ae0ea70
- 1
- Null Flags
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- false
- 0
-
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13392
76
20
-
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13402
- True if item is Invalid
- c11ab35c-f6a2-455a-a926-c8fae612bbfd
- Invalid Flags
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- false
- 0
-
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13412
76
20
-
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13422
- A textual description of the object state
- e42c47ed-b240-43f9-8c39-4fc406defff3
- Description
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-
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13432
76
20
-
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13442
- 7c9d9882-545d-434b-9850-2f3c6b01296b
- 08bdcae0-d034-48dd-a145-24a9fcf3d3ff
- Min / Max
- Extract the minimum and the maximum value of a list of numbers
- true
- a5b1c0c0-ed53-4928-9e19-8b13e166f8f5
- Min / Max
- Min / Max
-
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13390
115
44
-
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13412
- 1
- Set of Numbers
- 23cdb5f2-8684-4c36-8b48-513a3f5fe399
- Number
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- false
- 82ba3565-15cc-43a6-bdb7-bb0c8ae0ea70
- 1
-
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13392
39
40
-
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13412
- Minimum
- a6a165b8-0196-4899-85c2-2530b99211c8
- Minimum
- Minimum
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- 0
-
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13392
48
20
-
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13402
- Maximum
- 95d42b9f-4d49-4210-81a8-27c77c8defdb
- Maximum
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- 0
-
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13412
48
20
-
-6800
13422
- cb2c7d3c-41b4-4c6d-a6bd-9235bd2851bb
- Gate Not
- Perform boolean negation (NOT gate).
- true
- f7ba651d-d70d-496b-a389-a5b02e0b590b
- Gate Not
- Gate Not
-
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13394
70
28
-
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13408
- Boolean value
- 84082a0b-436f-4eff-9826-68e040df03b5
- A
- A
- false
- 95d42b9f-4d49-4210-81a8-27c77c8defdb
- 1
-
-6736
13396
11
24
-
-6730.5
13408
- Inverse of {A}
- 7e03e96a-60c3-44b8-8508-4a0249f6e5a0
- Result
- Result
- false
- 0
-
-6701
13396
31
24
-
-6685.5
13408
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- d7bbe7be-7e27-4e12-8d82-e69c3c3513bb
- Stream Filter
- Stream Filter
-
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13450
92
64
-
-5476
13482
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 406127bb-7c1f-41d0-8cb8-dcbdb5d6ffe8
- Gate
- Gate
- false
- 7e03e96a-60c3-44b8-8508-4a0249f6e5a0
- 1
-
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13452
40
20
-
-5508
13462
- 1
- 1
- {0}
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- Input stream at index 0
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13472
40
20
-
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13482
- 2
- Input stream at index 1
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- false
- Stream 1
- 1
- true
- 1bebc86d-5784-4955-910d-2d5169d1baac
- 1
-
-5528
13492
40
20
-
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13502
- 2
- Filtered stream
- e53053d4-d564-44a6-beee-0050818b6f00
- false
- Stream
- S(1)
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- 0
-
-5464
13452
24
60
-
-5452
13482
- c74efd0e-7fe3-4c2d-8c9d-295c5672fb13
- Null Item
- Test a data item for null or invalidity
- true
- ee7da382-815b-415a-9861-1675753f8b17
- Null Item
- Null Item
-
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14579
128
64
-
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14611
- Item to test
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- Item
- Item
- true
- 87166262-f90e-4df6-bfdc-8d5ff0afe20e
- 1
-
-7014
14581
24
60
-
-7002
14611
- True if item is Null
- 1648d712-ddcb-484f-86a6-3bf455dc71bf
- 1
- Null Flags
- Null Flags
- false
- 0
-
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14581
76
20
-
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14591
- True if item is Invalid
- 46a8e847-c729-4b2b-a671-abcb1f8f1882
- Invalid Flags
- Invalid Flags
- false
- 0
-
-6966
14601
76
20
-
-6936
14611
- A textual description of the object state
- 58a3745f-6e95-4031-9372-871e1a3230e4
- Description
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-
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14621
76
20
-
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14631
- 7c9d9882-545d-434b-9850-2f3c6b01296b
- 08bdcae0-d034-48dd-a145-24a9fcf3d3ff
- Min / Max
- Extract the minimum and the maximum value of a list of numbers
- true
- 2c4de2de-7fd1-4247-920b-e4e4d985f902
- Min / Max
- Min / Max
-
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14579
115
44
-
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14601
- 1
- Set of Numbers
- a3dbc77a-bf20-4311-b2ed-f205798a4147
- Number
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- false
- 1648d712-ddcb-484f-86a6-3bf455dc71bf
- 1
-
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14581
39
40
-
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14601
- Minimum
- 644f30e6-cd45-4fa5-bcb1-d2f3ec0088c0
- Minimum
- Minimum
- false
- 0
-
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14581
48
20
-
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14591
- Maximum
- f554aac2-085e-4c30-b33b-9feebb9269ae
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-
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14601
48
20
-
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14611
- cb2c7d3c-41b4-4c6d-a6bd-9235bd2851bb
- Gate Not
- Perform boolean negation (NOT gate).
- true
- 869a7ab1-6d37-4602-997f-d7610372f50e
- Gate Not
- Gate Not
-
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14583
70
28
-
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14597
- Boolean value
- 32e3041b-5ee5-409a-b83f-7f221bf3158f
- A
- A
- false
- f554aac2-085e-4c30-b33b-9feebb9269ae
- 1
-
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14585
11
24
-
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14597
- Inverse of {A}
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- Result
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- false
- 0
-
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14585
31
24
-
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14597
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 2dc62a4f-fa9a-4d00-9304-565cbbb21053
- Stream Filter
- Stream Filter
-
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14642
92
64
-
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14674
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
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- Index of Gate stream
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- Gate
- Gate
- false
- f5241e2f-e3b9-4b92-a0a2-bb5535a30bc5
- 1
-
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14644
40
20
-
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14654
- 1
- 1
- {0}
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- Input stream at index 0
- a3bbb5c5-ecca-4e4a-88e8-6a12ec936b83
- false
- Stream 0
- 0
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-
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14664
40
20
-
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14674
- 2
- Input stream at index 1
- 62df6a11-051f-4b24-9ace-aa4802a9bda6
- false
- Stream 1
- 1
- true
- 429f2160-9c55-4489-9f07-6fc421633a0f
- 1
-
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14684
40
20
-
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14694
- 2
- Filtered stream
- 371e8722-687f-4b56-97c4-03bfd4ba7a21
- false
- Stream
- S(1)
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- 0
-
-5371
14644
24
60
-
-5359
14674
- c74efd0e-7fe3-4c2d-8c9d-295c5672fb13
- Null Item
- Test a data item for null or invalidity
- true
- bc8a43f9-69f8-416a-97c3-5e6fb9733f5e
- Null Item
- Null Item
-
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15652
128
64
-
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15684
- Item to test
- 0ea97718-8927-4b3b-b427-e9da7cd6e334
- Item
- Item
- true
- 55a9b8da-f51b-46f7-9956-1cfce98363c7
- 1
-
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15654
24
60
-
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15684
- True if item is Null
- c72b0ed7-9c5d-47da-a98f-4953bbef1271
- 1
- Null Flags
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-
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15654
76
20
-
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15664
- True if item is Invalid
- a1cf6f25-d078-429b-9e50-5d148274fe7b
- Invalid Flags
- Invalid Flags
- false
- 0
-
-6986
15674
76
20
-
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15684
- A textual description of the object state
- 7accc688-6afc-4a9b-8d14-e2ce628d350e
- Description
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-
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15694
76
20
-
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15704
- 7c9d9882-545d-434b-9850-2f3c6b01296b
- 08bdcae0-d034-48dd-a145-24a9fcf3d3ff
- Min / Max
- Extract the minimum and the maximum value of a list of numbers
- true
- acfba1bb-b50c-4af6-a793-334e02358a94
- Min / Max
- Min / Max
-
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15652
115
44
-
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15674
- 1
- Set of Numbers
- 7304bb6d-12d4-4be8-9f55-d2a0ee349bc6
- Number
- Number
- false
- c72b0ed7-9c5d-47da-a98f-4953bbef1271
- 1
-
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15654
39
40
-
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15674
- Minimum
- e705aece-6cd6-4c26-9f72-1b586d5c7a5e
- Minimum
- Minimum
- false
- 0
-
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15654
48
20
-
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15664
- Maximum
- 0b7e60b9-9058-4d68-80e5-3d388446894a
- Maximum
- Maximum
- false
- 0
-
-6807
15674
48
20
-
-6783
15684
- cb2c7d3c-41b4-4c6d-a6bd-9235bd2851bb
- Gate Not
- Perform boolean negation (NOT gate).
- true
- 1b86b70a-3104-4e2b-9ea8-e7b621f91e72
- Gate Not
- Gate Not
-
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15656
70
28
-
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15670
- Boolean value
- 143deb72-368b-4a20-bf86-6ab0afed5bcb
- A
- A
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- 0b7e60b9-9058-4d68-80e5-3d388446894a
- 1
-
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15658
11
24
-
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15670
- Inverse of {A}
- 1cc96b60-6c9d-4b5a-952b-d87e0f026373
- Result
- Result
- false
- 0
-
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15658
31
24
-
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15670
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 7a50b3ba-d956-42c7-85ae-020294238131
- Stream Filter
- Stream Filter
-
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15639
92
64
-
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15671
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 6c3c0a55-54ee-48bc-933d-5f10e406781f
- Gate
- Gate
- false
- 1cc96b60-6c9d-4b5a-952b-d87e0f026373
- 1
-
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15641
40
20
-
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15651
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- afb7c341-6a0d-49ee-9fe7-8bfe8897afe5
- false
- Stream 0
- 0
- true
- 0
-
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15661
40
20
-
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15671
- 2
- Input stream at index 1
- eab2eb72-06e3-4ad5-b3a5-80d0b1552cfd
- false
- Stream 1
- 1
- true
- 498b7dc4-3bbe-40d4-94f3-8a7fd2ddd8cb
- 1
-
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15681
40
20
-
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15691
- 2
- Filtered stream
- 7be70df7-f6d7-45a4-acba-b061356bcd53
- false
- Stream
- S(1)
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- 0
-
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15641
24
60
-
-5299
15671
- c74efd0e-7fe3-4c2d-8c9d-295c5672fb13
- Null Item
- Test a data item for null or invalidity
- true
- 69a6a8b7-8a4c-461d-a8e3-38b25f1090de
- Null Item
- Null Item
-
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16657
128
64
-
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16689
- Item to test
- 8e171002-c9c5-40fa-94a1-1001311e625d
- Item
- Item
- true
- 1149d574-8501-435b-a0b2-df2ba22f96e8
- 1
-
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16659
24
60
-
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16689
- True if item is Null
- d86c8275-c6b6-49f3-8e58-8b6a74aacae9
- 1
- Null Flags
- Null Flags
- false
- 0
-
-6924
16659
76
20
-
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16669
- True if item is Invalid
- f3ff0523-ef2a-4496-9a34-d44373395db9
- Invalid Flags
- Invalid Flags
- false
- 0
-
-6924
16679
76
20
-
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16689
- A textual description of the object state
- b75efb85-ddd2-4c87-9141-e5f4c1331f1e
- Description
- Description
- false
- 0
-
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16699
76
20
-
-6894
16709
- 7c9d9882-545d-434b-9850-2f3c6b01296b
- 08bdcae0-d034-48dd-a145-24a9fcf3d3ff
- Min / Max
- Extract the minimum and the maximum value of a list of numbers
- true
- df4df02e-61f8-4247-b4ae-e627c2119ddb
- Min / Max
- Min / Max
-
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16657
115
44
-
-6757
16679
- 1
- Set of Numbers
- 180b7c54-6a7e-486f-9082-88a8b1879e13
- Number
- Number
- false
- d86c8275-c6b6-49f3-8e58-8b6a74aacae9
- 1
-
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16659
39
40
-
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16679
- Minimum
- dc5521b1-348f-45e2-815d-692347349b5c
- Minimum
- Minimum
- false
- 0
-
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16659
48
20
-
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16669
- Maximum
- 51b0ebbf-b611-45ce-9ca3-e7db982d471a
- Maximum
- Maximum
- false
- 0
-
-6745
16679
48
20
-
-6721
16689
- cb2c7d3c-41b4-4c6d-a6bd-9235bd2851bb
- Gate Not
- Perform boolean negation (NOT gate).
- true
- 4d572279-4b57-4ccb-9b17-4cf6a61cddfb
- Gate Not
- Gate Not
-
-6659
16661
70
28
-
-6634
16675
- Boolean value
- db135412-13b1-494a-9e44-f2a298e2a893
- A
- A
- false
- 51b0ebbf-b611-45ce-9ca3-e7db982d471a
- 1
-
-6657
16663
11
24
-
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16675
- Inverse of {A}
- e5221d87-c7c5-441c-b2a0-f5d656b5e19f
- Result
- Result
- false
- 0
-
-6622
16663
31
24
-
-6606.5
16675
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 8c75690a-9909-4a23-b4bd-03ea933c5c1b
- Stream Filter
- Stream Filter
-
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16644
92
64
-
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16676
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 4b34dd7b-a876-46ea-bcee-2d2e42db6605
- Gate
- Gate
- false
- e5221d87-c7c5-441c-b2a0-f5d656b5e19f
- 1
-
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16646
40
20
-
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16656
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 8e44a545-9b16-42f4-a5bf-929298a5975b
- false
- Stream 0
- 0
- true
- 0
-
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16666
40
20
-
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16676
- 2
- Input stream at index 1
- a8e94b10-1280-48b2-8c43-a75c4c94a665
- false
- Stream 1
- 1
- true
- 17cd7088-f1b9-4fd0-a76a-67c8e527f68b
- 1
-
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16686
40
20
-
-5293
16696
- 2
- Filtered stream
- ff5ee03c-6fb6-4999-ba11-3c9add44a863
- false
- Stream
- S(1)
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- 0
-
-5249
16646
24
60
-
-5237
16676
- c74efd0e-7fe3-4c2d-8c9d-295c5672fb13
- Null Item
- Test a data item for null or invalidity
- true
- a3813988-9a7d-44cb-bb48-1e51bfd8122c
- Null Item
- Null Item
-
-6991
17788
128
64
-
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17820
- Item to test
- 02fb06c2-1fc1-4719-a1c0-19e6f6320810
- Item
- Item
- true
- be615a1b-b5ca-456f-9216-7ca55cad191c
- 1
-
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17790
24
60
-
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17820
- True if item is Null
- 54d595a2-8560-4ac7-b251-1c1614234d33
- 1
- Null Flags
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- false
- 0
-
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17790
76
20
-
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17800
- True if item is Invalid
- 3ca9f52a-60ea-41dd-8091-248edad96e5b
- Invalid Flags
- Invalid Flags
- false
- 0
-
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17810
76
20
-
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17820
- A textual description of the object state
- 248cb7c4-9def-47e7-a8b6-793822c6f00d
- Description
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- 0
-
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17830
76
20
-
-6911
17840
- 7c9d9882-545d-434b-9850-2f3c6b01296b
- 08bdcae0-d034-48dd-a145-24a9fcf3d3ff
- Min / Max
- Extract the minimum and the maximum value of a list of numbers
- true
- 595f90c7-3ca3-4d10-8958-7f8fa2e74a29
- Min / Max
- Min / Max
-
-6827
17788
115
44
-
-6774
17810
- 1
- Set of Numbers
- 32637777-e83c-4c23-b669-258135f86f6d
- Number
- Number
- false
- 54d595a2-8560-4ac7-b251-1c1614234d33
- 1
-
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17790
39
40
-
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17810
- Minimum
- 00364658-7a30-463d-9002-9917505e5b1a
- Minimum
- Minimum
- false
- 0
-
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17790
48
20
-
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17800
- Maximum
- 26c41fcb-0fcc-4ec1-9bd4-79abb98e013c
- Maximum
- Maximum
- false
- 0
-
-6762
17810
48
20
-
-6738
17820
- cb2c7d3c-41b4-4c6d-a6bd-9235bd2851bb
- Gate Not
- Perform boolean negation (NOT gate).
- true
- 3b77b2f4-e654-4020-829d-ef86cca75bcf
- Gate Not
- Gate Not
-
-6676
17792
70
28
-
-6651
17806
- Boolean value
- e6521ab1-bd41-4cfc-81e4-9e57473d1419
- A
- A
- false
- 26c41fcb-0fcc-4ec1-9bd4-79abb98e013c
- 1
-
-6674
17794
11
24
-
-6668.5
17806
- Inverse of {A}
- 56f940ac-dac3-4e7c-ae76-4c5d06f6a203
- Result
- Result
- false
- 0
-
-6639
17794
31
24
-
-6623.5
17806
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 4ed3b515-31a0-4a8a-ac08-7a94b811e048
- Stream Filter
- Stream Filter
-
-5332
17775
92
64
-
-5278
17807
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- b677065e-0f8e-4e53-838f-96e373aa2f38
- Gate
- Gate
- false
- 56f940ac-dac3-4e7c-ae76-4c5d06f6a203
- 1
-
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17777
40
20
-
-5310
17787
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 0463558b-f3ba-4e8e-9375-4a54ed58ee17
- false
- Stream 0
- 0
- true
- 0
-
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17797
40
20
-
-5310
17807
- 2
- Input stream at index 1
- fbebdd51-24e2-4e04-8bad-2a46a7d9649c
- false
- Stream 1
- 1
- true
- a9429e5a-d32c-4087-b07f-09998c87b547
- 1
-
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17817
40
20
-
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17827
- 2
- Filtered stream
- 659efc47-65df-4ea8-8eae-843b8943b7ff
- false
- Stream
- S(1)
- false
- 0
-
-5266
17777
24
60
-
-5254
17807
- c74efd0e-7fe3-4c2d-8c9d-295c5672fb13
- Null Item
- Test a data item for null or invalidity
- true
- b579c9d7-271d-457f-bd33-499bb0a04854
- Null Item
- Null Item
-
-6952
18917
128
64
-
-6914
18949
- Item to test
- bcb8b65d-4922-46cf-956d-7c4a16ea0146
- Item
- Item
- true
- 424c8d2f-e0fa-482b-81a1-f7c2a6375ff5
- 1
-
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18919
24
60
-
-6938
18949
- True if item is Null
- 06fb23ec-2d77-4414-bf96-2c966bd4481f
- 1
- Null Flags
- Null Flags
- false
- 0
-
-6902
18919
76
20
-
-6872
18929
- True if item is Invalid
- 27a182c5-33a4-4ae8-a00c-055fbca81d40
- Invalid Flags
- Invalid Flags
- false
- 0
-
-6902
18939
76
20
-
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24
40
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7031
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77
64
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25
20
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25
20
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25
20
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24
60
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255;255;255;255
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- Flatten a data tree by removing all branching information.
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94
44
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42
20
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7182
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42
20
-
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24
40
-
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7192
- eeafc956-268e-461d-8e73-ee05c6f72c01
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77
64
-
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7122
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7092
25
20
-
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7102
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25
20
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- 2
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25
20
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24
60
-
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7122
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- Group
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255;255;255;255
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- Flatten a data tree by removing all branching information.
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- Flatten Tree
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8270
94
44
-
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8292
- 2
- Data tree to flatten
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8272
42
20
-
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8282
- Path of flattened tree
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8292
42
20
-
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8302
- 1
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- Tree
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8272
24
40
-
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8292
- eeafc956-268e-461d-8e73-ee05c6f72c01
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77
64
-
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8222
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- Gate
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-
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8192
25
20
-
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8202
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- true
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-
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25
20
-
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- 2
- Input stream at index 1
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8232
25
20
-
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-
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8192
24
60
-
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8222
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
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-
255;255;255;255
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- Flatten a data tree by removing all branching information.
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- Flatten Tree
- Flatten Tree
-
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94
44
-
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8459
- 2
- Data tree to flatten
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8439
42
20
-
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8449
- Path of flattened tree
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- Path
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-
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8459
42
20
-
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8469
- 1
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- Flattened data tree
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-
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8439
24
40
-
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8459
- eeafc956-268e-461d-8e73-ee05c6f72c01
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- Stream Filter
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-
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77
64
-
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8389
- 3
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- Index of Gate stream
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- Gate
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-
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8359
25
20
-
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8369
- 1
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- Input stream at index 0
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8379
25
20
-
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8389
- 2
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-
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8399
25
20
-
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8409
- 2
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-
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8359
24
60
-
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8389
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
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-
255;255;255;255
- A group of Grasshopper objects
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- Flatten a data tree by removing all branching information.
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- Flatten Tree
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-
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9409
94
44
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- 2
- Data tree to flatten
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42
20
-
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9421
- Path of flattened tree
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42
20
-
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9441
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- Flattened data tree
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24
40
-
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9431
- eeafc956-268e-461d-8e73-ee05c6f72c01
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-
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9329
77
64
-
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9361
- 3
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- Index of Gate stream
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- Gate
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-
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9331
25
20
-
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- 1
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- true
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25
20
-
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- 2
- Input stream at index 1
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- true
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25
20
-
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- 2
- Filtered stream
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-
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24
60
-
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9361
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- Group
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-
255;255;255;255
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94
44
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- 2
- Data tree to flatten
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9567
42
20
-
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9577
- Path of flattened tree
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-
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42
20
-
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9597
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9567
24
40
-
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9587
- eeafc956-268e-461d-8e73-ee05c6f72c01
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-
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77
64
-
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- Index of Gate stream
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9487
25
20
-
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25
20
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25
20
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24
60
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-
255;255;255;255
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94
44
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42
20
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- Path of flattened tree
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42
20
-
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24
40
-
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77
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- Index of Gate stream
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25
20
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25
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- 2
- Input stream at index 1
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- true
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25
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255;255;255;255
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44
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10738
- 2
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42
20
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24
40
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10738
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77
64
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10668
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10638
25
20
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25
20
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25
20
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24
60
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255;255;255;255
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- Flatten a data tree by removing all branching information.
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94
44
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11726
- 2
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11706
42
20
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11716
- Path of flattened tree
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11726
42
20
-
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11736
- 1
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11706
24
40
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11726
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77
64
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11656
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11626
25
20
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11646
25
20
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11656
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25
20
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11626
24
60
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11656
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11876
94
44
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11898
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42
20
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42
20
-
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11908
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11878
24
40
-
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11898
- eeafc956-268e-461d-8e73-ee05c6f72c01
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77
64
-
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11828
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11798
25
20
-
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11808
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25
20
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11828
- 2
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25
20
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- 2
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-
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24
60
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11828
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
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255;255;255;255
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- Flatten Tree
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94
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- 2
- Data tree to flatten
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42
20
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- Path of flattened tree
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-
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12851
42
20
-
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- 1
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- Flattened data tree
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-
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12831
24
40
-
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12851
- eeafc956-268e-461d-8e73-ee05c6f72c01
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77
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-
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12781
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- Index of Gate stream
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- Gate
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12751
25
20
-
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12761
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25
20
-
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12781
- 2
- Input stream at index 1
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- true
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-
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25
20
-
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- 2
- Filtered stream
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-
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24
60
-
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12781
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
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-
255;255;255;255
- A group of Grasshopper objects
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- Flatten Tree
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-
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94
44
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- 2
- Data tree to flatten
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-
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42
20
-
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13024
- Path of flattened tree
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-
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13034
42
20
-
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13044
- 1
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- Flattened data tree
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-
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13014
24
40
-
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13034
- eeafc956-268e-461d-8e73-ee05c6f72c01
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- Stream Filter
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-
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77
64
-
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12964
- 3
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- Index of Gate stream
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-
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12934
25
20
-
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12944
- 1
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- Input stream at index 0
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- true
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25
20
-
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12964
- 2
- Input stream at index 1
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-
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12974
25
20
-
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-
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12934
24
60
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12964
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- Group
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-
255;255;255;255
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- Flatten Tree
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-
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94
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- 2
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42
20
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14032
- Path of flattened tree
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-
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14042
42
20
-
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24
40
-
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77
64
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13972
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25
20
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25
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25
20
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42
20
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- Path of flattened tree
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-
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14202
42
20
-
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- Flattened data tree
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24
40
-
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- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
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- Stream Filter
- Stream Filter
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14100
77
64
-
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14132
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- Index of Gate stream
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- Gate
- Gate
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-
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14102
25
20
-
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14112
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- true
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-
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14122
25
20
-
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14132
- 2
- Input stream at index 1
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- true
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-
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14142
25
20
-
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14152
- 2
- Filtered stream
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- Stream
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- 0
-
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14102
24
60
-
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14132
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
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- Group
- f80cfe18-9510-4b89-8301-8e58faf423bb
- Flatten Tree
- Flatten a data tree by removing all branching information.
- true
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- Flatten Tree
- Flatten Tree
-
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15103
94
44
-
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15125
- 2
- Data tree to flatten
- a45aa960-b409-4c9c-b164-ab98d77fa811
- Tree
- Tree
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-
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15105
42
20
-
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15115
- Path of flattened tree
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- Path
- Path
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-
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15125
42
20
-
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15135
- 1
- 1
- {0}
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- Flattened data tree
- 0d5a1f9a-318a-4234-984b-02d7a5227892
- Tree
- Tree
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- 0
-
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15105
24
40
-
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15125
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
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- Stream Filter
- Stream Filter
-
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15023
77
64
-
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15055
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
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- Index of Gate stream
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- Gate
- Gate
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- 1
-
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15025
25
20
-
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15035
- 1
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- {0}
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- Input stream at index 0
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- Stream 0
- 0
- true
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- 1
-
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15045
25
20
-
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15055
- 2
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- Stream 1
- 1
- true
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- 1
-
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15065
25
20
-
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15075
- 2
- Filtered stream
- 50866164-631f-4e5d-97a6-38052c2a1f58
- false
- Stream
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- 0
-
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15025
24
60
-
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15055
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
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- Group
- f80cfe18-9510-4b89-8301-8e58faf423bb
- Flatten Tree
- Flatten a data tree by removing all branching information.
- true
- bd2cff48-e6f8-489d-84eb-e5f8453a1ce2
- Flatten Tree
- Flatten Tree
-
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15255
94
44
-
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15277
- 2
- Data tree to flatten
- 78d2c535-7407-4746-94e1-222ab5277b5b
- Tree
- Tree
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- 1
-
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15257
42
20
-
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15267
- Path of flattened tree
- 14246816-df87-4b99-b3ed-3971032eb630
- Path
- Path
- false
- 0
-
-9740
15277
42
20
-
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15287
- 1
- 1
- {0}
- {0}
- 2
- Flattened data tree
- 17c2fa1d-80d9-4ba6-a5e5-7271d56f0aa2
- Tree
- Tree
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- 0
-
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15257
24
40
-
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15277
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 3c27f3f2-cffd-4cd2-bd3a-7dee06966287
- Stream Filter
- Stream Filter
-
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15175
77
64
-
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15207
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
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- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- d091faa8-a2db-452e-ae21-61b5457e55ce
- Gate
- Gate
- false
- d4a3053e-492d-459f-b24d-a486603f6732
- 1
-
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15177
25
20
-
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15187
- 1
- 1
- {0}
- 1
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- Input stream at index 0
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- false
- Stream 0
- 0
- true
- dff4cfd5-06dd-4644-a8fa-9833eff92395
- 1
-
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15197
25
20
-
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15207
- 2
- Input stream at index 1
- b89664d2-d57e-4cec-b3d8-bcbee474db65
- false
- Stream 1
- 1
- true
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- 1
-
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15217
25
20
-
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15227
- 2
- Filtered stream
- 2c9cd1a3-de48-4ce5-be20-36b483914987
- false
- Stream
- S(1)
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- 0
-
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15177
24
60
-
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15207
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
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- Group
- f80cfe18-9510-4b89-8301-8e58faf423bb
- Flatten Tree
- Flatten a data tree by removing all branching information.
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- 40f3f649-28c4-4dd1-8d03-fe79b3a61218
- Flatten Tree
- Flatten Tree
-
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16133
94
44
-
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16155
- 2
- Data tree to flatten
- c2596fcd-b45d-4447-a8cc-62a9fa0d6542
- Tree
- Tree
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- 1
-
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16135
42
20
-
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16145
- Path of flattened tree
- 85dfc1a0-4a4d-4bdb-90b4-0527380f9565
- Path
- Path
- false
- 0
-
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16155
42
20
-
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16165
- 1
- 1
- {0}
- {0}
- 2
- Flattened data tree
- 1c0f4ea3-98e7-4928-bbe9-4b1f42d8c904
- Tree
- Tree
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- 0
-
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16135
24
40
-
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16155
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 27a383ad-8bcb-4777-9f6f-433e68b4bf02
- Stream Filter
- Stream Filter
-
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16053
77
64
-
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16085
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- cfac2511-561b-4977-afbc-7130888309e9
- Gate
- Gate
- false
- d4a3053e-492d-459f-b24d-a486603f6732
- 1
-
-9752
16055
25
20
-
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16065
- 1
- 1
- {0}
- 1
- 2
- Input stream at index 0
- b1d14263-646f-42ec-99ce-735724dc0e82
- false
- Stream 0
- 0
- true
- 82f35a99-14e7-47ff-900d-a54c896b2c78
- 1
-
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16075
25
20
-
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16085
- 2
- Input stream at index 1
- 4f444ff3-ff4e-4b5b-a8a3-9f1110b9bff4
- false
- Stream 1
- 1
- true
- 1c0f4ea3-98e7-4928-bbe9-4b1f42d8c904
- 1
-
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16095
25
20
-
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16105
- 2
- Filtered stream
- e87642af-d7f4-4c8a-badf-e9466bf0b858
- false
- Stream
- S(1)
- false
- 0
-
-9703
16055
24
60
-
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16085
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
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- 2
- 4b79f999-e986-4b4e-b521-7e8afcd91e83
- Group
- f80cfe18-9510-4b89-8301-8e58faf423bb
- Flatten Tree
- Flatten a data tree by removing all branching information.
- true
- eafcf1eb-de31-48ae-96e9-a31a5648a08a
- Flatten Tree
- Flatten Tree
-
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16304
94
44
-
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16326
- 2
- Data tree to flatten
- 690a9973-a06b-4c15-99e0-3d97b3fdccf1
- Tree
- Tree
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- 1
-
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16306
42
20
-
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16316
- Path of flattened tree
- 8c976a06-2cf2-4e03-98b9-1c8f1b7a7244
- Path
- Path
- false
- 0
-
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16326
42
20
-
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16336
- 1
- 1
- {0}
- {0}
- 2
- Flattened data tree
- 66f2a9d6-153a-446e-bcda-ef81bac878c3
- Tree
- Tree
- false
- 0
-
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16306
24
40
-
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16326
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 40d05bdf-aa00-4b00-a946-8411fa96e9a9
- Stream Filter
- Stream Filter
-
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16224
77
64
-
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16256
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 59006d26-82a3-4cf0-ac23-d8384a6a50ca
- Gate
- Gate
- false
- d4a3053e-492d-459f-b24d-a486603f6732
- 1
-
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16226
25
20
-
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16236
- 1
- 1
- {0}
- 1
- 2
- Input stream at index 0
- 3b1611a6-7144-46ad-9be5-c24368f34f9e
- false
- Stream 0
- 0
- true
- 535c49a7-eac1-4cc0-b695-b51aef04808e
- 1
-
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16246
25
20
-
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16256
- 2
- Input stream at index 1
- 3a38a898-df07-4fb0-89f1-77c597e8a5df
- false
- Stream 1
- 1
- true
- 66f2a9d6-153a-446e-bcda-ef81bac878c3
- 1
-
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16266
25
20
-
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16276
- 2
- Filtered stream
- 0156a723-76fc-4a7c-8320-97d012f1e76e
- false
- Stream
- S(1)
- false
- 0
-
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16226
24
60
-
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16256
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- eafcf1eb-de31-48ae-96e9-a31a5648a08a
- 40d05bdf-aa00-4b00-a946-8411fa96e9a9
- 2
- b5e48ff4-a4e0-489c-b793-89b79b7f7992
- Group
- f80cfe18-9510-4b89-8301-8e58faf423bb
- Flatten Tree
- Flatten a data tree by removing all branching information.
- true
- d33f5346-f62e-4d82-87ac-174c836d814e
- Flatten Tree
- Flatten Tree
-
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17311
94
44
-
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17333
- 2
- Data tree to flatten
- 5ece3755-0475-4480-b1fa-d89397728417
- Tree
- Tree
- false
- 6de70eee-64cc-4d17-ad90-5e27d252e6e5
- 1
-
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17313
42
20
-
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17323
- Path of flattened tree
- c29f8dcf-1c9b-4d98-8591-9d43c1e86e66
- Path
- Path
- false
- 0
-
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17333
42
20
-
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17343
- 1
- 1
- {0}
- {0}
- 2
- Flattened data tree
- 679d2e91-fa27-4ccb-b44d-365f3bbea2eb
- Tree
- Tree
- false
- 0
-
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17313
24
40
-
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17333
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 28fc51b3-790c-4602-8eb8-8f320335323d
- Stream Filter
- Stream Filter
-
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17231
77
64
-
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17263
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 79f4d009-bf54-46d7-a99f-bf9a7467e491
- Gate
- Gate
- false
- d4a3053e-492d-459f-b24d-a486603f6732
- 1
-
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17233
25
20
-
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17243
- 1
- 1
- {0}
- 1
- 2
- Input stream at index 0
- 2adf4b98-d7aa-4f67-ab63-d8621af51ed8
- false
- Stream 0
- 0
- true
- 6de70eee-64cc-4d17-ad90-5e27d252e6e5
- 1
-
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17253
25
20
-
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17263
- 2
- Input stream at index 1
- ea998311-e0ed-4639-ac92-79e2f0b6aadb
- false
- Stream 1
- 1
- true
- 679d2e91-fa27-4ccb-b44d-365f3bbea2eb
- 1
-
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17273
25
20
-
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17283
- 2
- Filtered stream
- d3503a0a-25d4-40f9-b392-12c89e516f16
- false
- Stream
- S(1)
- false
- 0
-
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17233
24
60
-
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17263
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
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- 2
- e141dc0a-30ac-484b-ae2e-44b1a74729c4
- Group
- f80cfe18-9510-4b89-8301-8e58faf423bb
- Flatten Tree
- Flatten a data tree by removing all branching information.
- true
- 8c1e158d-7334-4dd1-b6a2-8a67d337a0e4
- Flatten Tree
- Flatten Tree
-
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17477
94
44
-
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17499
- 2
- Data tree to flatten
- 5ec536be-57ee-44e8-9f87-fb708c7d45fc
- Tree
- Tree
- false
- 87fdae07-bcf5-489b-89b1-aec57ffa9c17
- 1
-
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17479
42
20
-
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17489
- Path of flattened tree
- 441d093b-88ee-44ed-a10a-0fc1ea6d1fc6
- Path
- Path
- false
- 0
-
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17499
42
20
-
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17509
- 1
- 1
- {0}
- {0}
- 2
- Flattened data tree
- 57fa38b0-5e0c-4990-ad3a-70ab8fd6f13a
- Tree
- Tree
- false
- 0
-
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17479
24
40
-
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17499
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- e884606f-0e12-4361-b99c-de945016ca3e
- Stream Filter
- Stream Filter
-
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17397
77
64
-
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17429
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 3059c6ca-30de-4165-96cd-b69abb9182e3
- Gate
- Gate
- false
- d4a3053e-492d-459f-b24d-a486603f6732
- 1
-
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17399
25
20
-
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17409
- 1
- 1
- {0}
- 1
- 2
- Input stream at index 0
- ea58797c-a1d6-4dec-9635-c92180f62f31
- false
- Stream 0
- 0
- true
- 87fdae07-bcf5-489b-89b1-aec57ffa9c17
- 1
-
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17419
25
20
-
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17429
- 2
- Input stream at index 1
- ec901e21-d674-4c43-97bf-5c75be692802
- false
- Stream 1
- 1
- true
- 57fa38b0-5e0c-4990-ad3a-70ab8fd6f13a
- 1
-
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17439
25
20
-
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17449
- 2
- Filtered stream
- 4dfda7fb-90ae-4f9e-9305-08baf23c2d50
- false
- Stream
- S(1)
- false
- 0
-
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17399
24
60
-
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- false
- 3cbad971-5468-4bd5-9b90-f8973ca0b914
- 1
-
-14842
2561
40
30
-
-14822
2576
- If True, only the edit points at knots (span ends) are extracted (the points an interpolated curve interpolated through)
If False, all edit points are extracted which equals the same amount as the curve control points (like Rhino's EditPtOn command)
- 89aa3b5a-bb05-45c3-a750-883746c704f5
- Knots
- Knots
- false
- 0
-
-14842
2591
40
30
-
-14822
2606
- 1
- 1
- {0}
- true
- 1
- Edit points on the curve
- e06dd9df-a7d8-4bdb-a08c-51b698b9b4c3
- Points
- Points
- false
- 0
-
-14778
2561
55
20
-
-14750.5
2571
- 1
- Tangent vectors at edit points
- 6fdd5be7-610f-4cb8-b8a4-ba4b9bff6164
- Tangents
- Tangents
- false
- 0
-
-14778
2581
55
20
-
-14750.5
2591
- 1
- Parameter values at edit points
- 04b392e1-0727-4121-a5cb-a38e5feedefb
- Parameters
- Parameters
- false
- 0
-
-14778
2601
55
20
-
-14750.5
2611
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- eef8edbe-e4ee-4cf2-a326-5f8cce8113d1
- Polar Array
- Polar Array
-
-14887
2741
210
101
-
-14741
2792
- Base geometry
- e0070f7c-e938-4dfc-ba0c-31d44a6caa2b
- Geometry
- Geometry
- true
- fbb8f0e6-1282-4e1a-b4a3-80e1608a15df
- 1
-
-14885
2743
132
20
-
-14819
2753
- Polar array plane
- b5ea8a1b-5ee6-41d7-b904-9a271e549cb5
- Plane
- Plane
- false
- 0
-
-14885
2763
132
37
-
-14819
2781.5
- 1
- 1
- {0}
-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
- e0f1df9d-d108-4df1-a760-d962ab3d9507
- Count
- Count
- false
- 0
-
-14885
2800
132
20
-
-14819
2810
- 1
- 1
- {0}
- 4
- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- c6d29f73-4b44-43ea-8246-93fbb58e73d5
- Angle
- Angle
- false
- 0
- false
-
-14885
2820
132
20
-
-14819
2830
- 1
- 1
- {0}
- 6.2831853071795862
- 1
- Arrayed geometry
- c6fb46b1-1866-46f0-be66-9ac6e5dfb0af
- Geometry
- Geometry
- false
- 0
-
-14729
2743
50
48
-
-14704
2767.25
- 1
- Transformation data
- e2c99aaf-9122-491c-9432-64200f092724
- Transform
- Transform
- false
- 0
-
-14729
2791
50
49
-
-14704
2815.75
- 8073a420-6bec-49e3-9b18-367f6fd76ac3
- Join Curves
- Join as many curves as possible
- true
- fa1a9b8a-4a9c-4e3a-9549-594347e8dfff
- Join Curves
- Join Curves
-
-14840
2678
116
44
-
-14773
2700
- 1
- Curves to join
- ec691f47-58ca-47ce-a7a6-1e7acaf74712
- Curves
- Curves
- false
- c6fb46b1-1866-46f0-be66-9ac6e5dfb0af
- 1
-
-14838
2680
53
20
-
-14811.5
2690
- Preserve direction of input curves
- 8aaf9a24-f246-40b3-b4cf-3e7c6e528bb0
- Preserve
- Preserve
- false
- 0
-
-14838
2700
53
20
-
-14811.5
2710
- 1
- 1
- {0}
- false
- 1
- Joined curves and individual curves that could not be joined.
- ad08be32-aeff-4d9e-9dd1-ff711b64e372
- Curves
- Curves
- false
- 0
-
-14761
2680
35
40
-
-14743.5
2700
- 758d91a0-4aec-47f8-9671-16739a8a2c5d
- Format
- Format some data using placeholders and formatting tags
- true
- c4469cbb-a39a-4c43-af1e-4faecfb8864d
- Format
- Format
-
-14855
2259
146
64
-
-14763
2291
- 3
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- 7fa15783-70da-485c-98c0-a099e6988c3e
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- Text format
- c49e68bd-a224-4de9-a250-6a3da3a9fb8e
- Format
- Format
- false
- 0b268425-222c-4453-a899-699f40674ff4
- 1
-
-14853
2261
78
20
-
-14814
2271
- 1
- 1
- {0}
- false
- {0:R}
- Formatting culture
- 0fc2f53d-2aac-4bf5-8972-e9a7007be4f3
- Culture
- Culture
- false
- 0
-
-14853
2281
78
20
-
-14814
2291
- 1
- 1
- {0}
- 127
- Data to insert at {0} placeholders
- fee4b943-bcf9-44f8-b7c0-37bfa4a38767
- false
- Data 0
- 0
- true
- 060f32c2-ea2f-456e-aad4-6c9bb28a90b2
- 1
-
-14853
2301
78
20
-
-14814
2311
- Formatted text
- 541d0d6c-df63-4f01-9506-cb4a72d23811
- 2
- Text
- Text
- false
- 0
-
-14751
2261
40
60
-
-14739
2291
- 9abae6b7-fa1d-448c-9209-4a8155345841
- Deconstruct
- Deconstruct a point into its component parts.
- true
- 1e018a09-e2a3-4569-96c1-3257bd22c324
- Deconstruct
- Deconstruct
-
-14842
2476
120
64
-
-14801
2508
- Input point
- 4f47bc26-f7db-4404-b778-ad8e48926b2c
- Point
- Point
- false
- e06dd9df-a7d8-4bdb-a08c-51b698b9b4c3
- 1
-
-14840
2478
27
60
-
-14826.5
2508
- Point {x} component
- 060f32c2-ea2f-456e-aad4-6c9bb28a90b2
- X component
- X component
- false
- 0
-
-14789
2478
65
20
-
-14756.5
2488
- Point {y} component
- bd2a4a67-1536-4e02-8c08-f9a7a3765cb6
- Y component
- Y component
- false
- 0
-
-14789
2498
65
20
-
-14756.5
2508
- Point {z} component
- 64bbd7ed-d13d-48a3-be41-ac6f76836944
- Z component
- Z component
- false
- 0
-
-14789
2518
65
20
-
-14756.5
2528
- 758d91a0-4aec-47f8-9671-16739a8a2c5d
- Format
- Format some data using placeholders and formatting tags
- true
- 6879624e-fbcc-4c8c-bdbd-f9287e280cec
- Format
- Format
-
-14855
2344
146
64
-
-14763
2376
- 3
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- 7fa15783-70da-485c-98c0-a099e6988c3e
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- Text format
- ed7899d9-4180-427d-924d-30c3cef5329e
- Format
- Format
- false
- 0b268425-222c-4453-a899-699f40674ff4
- 1
-
-14853
2346
78
20
-
-14814
2356
- 1
- 1
- {0}
- false
- {0:R}
- Formatting culture
- 792c5ea8-e1f3-407d-9ca6-9de8ad941e5b
- Culture
- Culture
- false
- 0
-
-14853
2366
78
20
-
-14814
2376
- 1
- 1
- {0}
- 127
- Data to insert at {0} placeholders
- 0938cd93-00a1-4f6f-94b1-dea868e5c2b0
- false
- Data 0
- 0
- true
- bd2a4a67-1536-4e02-8c08-f9a7a3765cb6
- 1
-
-14853
2386
78
20
-
-14814
2396
- Formatted text
- 9b974061-e57a-4a80-8861-ffeadbb0275a
- 2
- Text
- Text
- false
- 0
-
-14751
2346
40
60
-
-14739
2376
- 2013e425-8713-42e2-a661-b57e78840337
- Concatenate
- Concatenate some fragments of text
- true
- 930ffbc3-265e-4ecc-9f04-802ad846776c
- Concatenate
- Concatenate
-
-14827
2173
90
64
-
-14798
2205
- 3
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- 1
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- First text fragment
- 44d9c67a-f971-450c-b31c-7c858742f299
- Fragment A
- true
- 541d0d6c-df63-4f01-9506-cb4a72d23811
- 1
-
-14825
2175
15
20
-
-14817.5
2185
- Second text fragment
- 978913a3-6f63-4056-817d-e84ece6db176
- Fragment B
- true
- 0
-
-14825
2195
15
20
-
-14817.5
2205
- 1
- 1
- {0}
- false
- ,
- Third text fragment
- e73062cc-3cbb-4a32-9414-235f9f87324c
- Fragment A
- true
- 9b974061-e57a-4a80-8861-ffeadbb0275a
- 1
-
-14825
2215
15
20
-
-14817.5
2225
- Resulting text consisting of all the fragments
- 7f02dbf4-1b80-4114-b1b3-9c97154ee670
- 1
- Result
- Result
- false
- 0
-
-14786
2175
47
60
-
-14770.5
2205
- 079bd9bd-54a0-41d4-98af-db999015f63d
- VB Script
- A VB.NET scriptable component
- true
- eebd514c-d423-4813-b326-d8174e48bd4e
- VB Script
- TxtWriter
- true
- 0
- If activate Then
Dim i As Integer
Dim aryText(4) As String
aryText(0) = "Mary WriteLine"
aryText(1) = "Had"
aryText(2) = "Another"
aryText(3) = "Little"
aryText(4) = "One"
' the data is appended to the file. If file doesnt exist, a new file is created
Dim objWriter As New System.IO.StreamWriter(filePath, append)
For i = 0 To data.Count - 1
objWriter.WriteLine(data(i))
Next
objWriter.Close()
End If
If clearFile Then
Dim objWriter As New System.IO.StreamWriter(filePath, False)
objWriter.Close()
End If
-
-14831
1961
97
104
-
-14767
2013
- 5
- 84fa917c-1ed8-4db3-8be1-7bdc4a6495a2
- 84fa917c-1ed8-4db3-8be1-7bdc4a6495a2
- 84fa917c-1ed8-4db3-8be1-7bdc4a6495a2
- 84fa917c-1ed8-4db3-8be1-7bdc4a6495a2
- 84fa917c-1ed8-4db3-8be1-7bdc4a6495a2
- 2
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- true
- Script Variable filePath
- d8c8a31b-86c7-4c77-9356-1ac9f3dbcc74
- filePath
- filePath
- true
- 0
- true
- 3c61ebe6-576a-4b99-8639-fa340b5c3d83
- 1
- abf1fd1b-dbe5-4be6-9832-d8dc105e207f
-
-14829
1963
50
20
-
-14804
1973
- 1
- true
- Script Variable data
- c5a355c2-ce60-4cbc-aad0-5458f0713979
- data
- data
- true
- 1
- true
- 7f02dbf4-1b80-4114-b1b3-9c97154ee670
- 1
- abf1fd1b-dbe5-4be6-9832-d8dc105e207f
-
-14829
1983
50
20
-
-14804
1993
- true
- Script Variable append
- 7d7dc609-f4ec-48b8-b096-50213567cd05
- append
- append
- true
- 0
- true
- 0
- 3cda2745-22ac-4244-9b04-97a5255fa60f
-
-14829
2003
50
20
-
-14804
2013
- true
- Script Variable activate
- 32675416-633b-4860-864d-e3b2ee660bc2
- activate
- activate
- true
- 0
- true
- 5d68cd90-e0f9-46f9-adda-c411113d8be5
- 1
- 3cda2745-22ac-4244-9b04-97a5255fa60f
-
-14829
2023
50
20
-
-14804
2033
- true
- Script Variable clearFile
- ac135355-ac4a-45fd-8cb0-5f7fcd922a10
- clearFile
- clearFile
- true
- 0
- true
- 0
- 3cda2745-22ac-4244-9b04-97a5255fa60f
-
-14829
2043
50
20
-
-14804
2053
- Print, Reflect and Error streams
- d49f9c66-0d71-4828-b0a3-544a31f35e15
- out
- out
- false
- 0
-
-14755
1963
19
50
-
-14745.5
1988
- Output parameter A
- da00d88a-1b39-4027-8236-71269d4d6db4
- A
- A
- false
- 0
-
-14755
2013
19
50
-
-14745.5
2038
- 06953bda-1d37-4d58-9b38-4b3c74e54c8f
- File Path
- Contains a collection of file paths
- false
- All files|*.*
- 3c61ebe6-576a-4b99-8639-fa340b5c3d83
- File Path
- File Path
- false
- 0
-
-14989
2127
469
24
-
-14532.57
2139.582
- 1
- 1
- {0}
- false
- C:\VƧϽ.XHꓨ.⚪⠿ⵈ⸭⸭⠿✤Ⓞᙁᑫᑭᗱᗴᙁᑐᑕᴥꖴᑎ¤ᔓᔕ▢ᔓᔕᑎꖴ⚭ᗩꗳ⚪⚪⚪⚪ꗳᗩ⚭ꖴᑎᔓᔕ▢ᔓᔕ¤ᑎꖴᴥᑐᑕᙁᗱᗴᑫᑭᙁⓄ✤⠿⸭⸭ⵈ⠿⚪.GHX.CSV
- a8b97322-2d53-47cd-905e-b932c3ccd74e
- Button
- Button object with two values
- False
- True
- 5d68cd90-e0f9-46f9-adda-c411113d8be5
- Button
- false
- 0
-
-14815
2085
66
22
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- fbb8f0e6-1282-4e1a-b4a3-80e1608a15df
- Relay
- false
- a4e47d08-a584-482d-aba8-2d9193c005ff
- 1
-
-14802
3403
40
16
-
-14782
3411
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 3cbad971-5468-4bd5-9b90-f8973ca0b914
- Relay
- false
- ad08be32-aeff-4d9e-9dd1-ff711b64e372
- 1
-
-14802
2643
40
16
-
-14782
2651
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- a3072b3b-491d-42b9-b571-d09ce1edc911
- eef8edbe-e4ee-4cf2-a326-5f8cce8113d1
- fa1a9b8a-4a9c-4e3a-9549-594347e8dfff
- c4469cbb-a39a-4c43-af1e-4faecfb8864d
- 1e018a09-e2a3-4569-96c1-3257bd22c324
- 6879624e-fbcc-4c8c-bdbd-f9287e280cec
- 930ffbc3-265e-4ecc-9f04-802ad846776c
- eebd514c-d423-4813-b326-d8174e48bd4e
- 3c61ebe6-576a-4b99-8639-fa340b5c3d83
- 5d68cd90-e0f9-46f9-adda-c411113d8be5
- fbb8f0e6-1282-4e1a-b4a3-80e1608a15df
- 3cbad971-5468-4bd5-9b90-f8973ca0b914
- 0b268425-222c-4453-a899-699f40674ff4
- 13
- 67fd36a5-4c3b-44c9-9b0b-779982391eac
- Group
- 932b9817-fcc6-4ac3-b5fd-c0e8eeadc53f
- Cull Nth
- Cull (remove) every Nth element in a list.
- true
- 974f2124-cd03-4c4d-85ca-ee04d37b421d
- Cull Nth
- Cull Nth
-
-14477
2511
130
44
-
-14380
2533
- 1
- List to cull
- e43860a0-c581-4dd2-9e12-dcc22592348c
- List
- List
- false
- 49f3d6a1-f8e0-4c12-9abd-af5782ebafab
- 1
-
-14475
2513
83
20
-
-14433.5
2523
- 1
- 5
- {0}
- Grasshopper.Kernel.Types.GH_Integer
- 0
- Grasshopper.Kernel.Types.GH_Integer
- 1
- Grasshopper.Kernel.Types.GH_Integer
- 2
- Grasshopper.Kernel.Types.GH_Integer
- 3
- Grasshopper.Kernel.Types.GH_Integer
- 4
- Cull frequency
- e5ca9f54-58c9-4c0f-8da1-1e6edb8d6037
- Cull frequency
- Cull frequency
- false
- 0
-
-14475
2533
83
20
-
-14433.5
2543
- 1
- 1
- {0}
- 2
- 1
- Culled list
- 0e2c164c-4e9e-427b-997b-16cbc0ed0c74
- List
- List
- false
- 0
-
-14368
2513
19
40
-
-14358.5
2533
- 932b9817-fcc6-4ac3-b5fd-c0e8eeadc53f
- Cull Nth
- Cull (remove) every Nth element in a list.
- true
- 39466ca3-d029-4cfc-a63d-6f7550e0c638
- Cull Nth
- Cull Nth
-
-14477
2579
130
44
-
-14380
2601
- 1
- List to cull
- 03a8fd49-0132-4964-b3d5-5ef81e30fb6d
- List
- List
- false
- e06dd9df-a7d8-4bdb-a08c-51b698b9b4c3
- 1
-
-14475
2581
83
20
-
-14433.5
2591
- 1
- 5
- {0}
- Grasshopper.Kernel.Types.GH_Integer
- 0
- Grasshopper.Kernel.Types.GH_Integer
- 1
- Grasshopper.Kernel.Types.GH_Integer
- 2
- Grasshopper.Kernel.Types.GH_Integer
- 3
- Grasshopper.Kernel.Types.GH_Integer
- 4
- Cull frequency
- a0647155-0402-4593-a132-9595e6c7e28b
- Cull frequency
- Cull frequency
- false
- 0
-
-14475
2601
83
20
-
-14433.5
2611
- 1
- 1
- {0}
- 2
- 1
- Culled list
- 49f3d6a1-f8e0-4c12-9abd-af5782ebafab
- List
- List
- false
- 0
-
-14368
2581
19
40
-
-14358.5
2601
- 59e0b89a-e487-49f8-bab8-b5bab16be14c
- Panel
- A panel for custom notes and text values
- 0b268425-222c-4453-a899-699f40674ff4
- Panel
- false
- 0
- 0
- {0:R}
-
-14859
2430
160
20
- 0
- 0
- 0
-
-14858.53
2430.334
-
255;255;255;255
- true
- true
- true
- false
- false
- true
- 932b9817-fcc6-4ac3-b5fd-c0e8eeadc53f
- Cull Nth
- Cull (remove) every Nth element in a list.
- true
- 4a263f28-e86c-4136-adba-f399581985c6
- Cull Nth
- Cull Nth
-
-14477
2373
130
44
-
-14380
2395
- 1
- List to cull
- cd595781-061a-4b72-8a05-b230c9b6925d
- List
- List
- false
- 9afcd14f-59fa-4c15-831e-fcd26b5512b5
- 1
-
-14475
2375
83
20
-
-14433.5
2385
- 1
- 5
- {0}
- Grasshopper.Kernel.Types.GH_Integer
- 0
- Grasshopper.Kernel.Types.GH_Integer
- 1
- Grasshopper.Kernel.Types.GH_Integer
- 2
- Grasshopper.Kernel.Types.GH_Integer
- 3
- Grasshopper.Kernel.Types.GH_Integer
- 4
- Cull frequency
- b9151842-57b9-4d16-8fc4-a8dc4cfd080d
- Cull frequency
- Cull frequency
- false
- 0
-
-14475
2395
83
20
-
-14433.5
2405
- 1
- 1
- {0}
- 2
- 1
- Culled list
- 505237c7-accc-4309-97d2-bd12c1f8ac45
- List
- List
- false
- 0
-
-14368
2375
19
40
-
-14358.5
2395
- 932b9817-fcc6-4ac3-b5fd-c0e8eeadc53f
- Cull Nth
- Cull (remove) every Nth element in a list.
- true
- b5e1834b-fb49-4790-b5d5-0cb2b107a7e5
- Cull Nth
- Cull Nth
-
-14477
2441
130
44
-
-14380
2463
- 1
- List to cull
- 72b45001-f8ea-4fb9-ba55-664aefff7fa3
- List
- List
- false
- 0e2c164c-4e9e-427b-997b-16cbc0ed0c74
- 1
-
-14475
2443
83
20
-
-14433.5
2453
- 1
- 5
- {0}
- Grasshopper.Kernel.Types.GH_Integer
- 0
- Grasshopper.Kernel.Types.GH_Integer
- 1
- Grasshopper.Kernel.Types.GH_Integer
- 2
- Grasshopper.Kernel.Types.GH_Integer
- 3
- Grasshopper.Kernel.Types.GH_Integer
- 4
- Cull frequency
- d457d4e5-326f-4f1e-ba7c-97d1a7b539f8
- Cull frequency
- Cull frequency
- false
- 0
-
-14475
2463
83
20
-
-14433.5
2473
- 1
- 1
- {0}
- 2
- 1
- Culled list
- 9afcd14f-59fa-4c15-831e-fcd26b5512b5
- List
- List
- false
- 0
-
-14368
2443
19
40
-
-14358.5
2463
- 8073a420-6bec-49e3-9b18-367f6fd76ac3
- Join Curves
- Join as many curves as possible
- true
- 3b09c427-6126-48d2-a0ec-c6444a4c88c3
- Join Curves
- Join Curves
-
9699
27870
116
44
-
9766
27892
- 1
- Curves to join
- ca242732-720a-4e98-9dbb-732ff1ddf14a
- Curves
- Curves
- false
- 9f7378b6-9894-4b84-998a-f5226749112f
- 1
-
9701
27872
53
20
-
9727.5
27882
- Preserve direction of input curves
- 0b08aec8-52b6-4885-9405-283adde61272
- Preserve
- Preserve
- false
- 0
-
9701
27892
53
20
-
9727.5
27902
- 1
- 1
- {0}
- true
- 1
- Joined curves and individual curves that could not be joined.
- 924a3307-6def-4577-8262-7531f1451274
- Curves
- Curves
- false
- 0
-
9778
27872
35
40
-
9795.5
27892
- 33bcf975-a0b2-4b54-99fd-585c893b9e88
- Digit Scroller
- Numeric scroller for single numbers
- d2a56b44-2207-4c9b-be02-a2565f8a2092
- Digit Scroller
- *
- false
- 0
- 12
- *
- 2
- 0.0037560302
-
7402
29798
250
20
-
7402.908
29798.28
- 9df5e896-552d-4c8c-b9ca-4fc147ffa022
- Expression
- Evaluate an expression
- O*256/(2^(1285/256))
- true
- 612d0fc7-2e84-4abd-a69f-f604e5738c79
- Expression
- Expression
-
6759
29737
207
28
-
6865
29751
- 1
- ba80fd98-91a1-4958-b6a7-a94e40e52bdb
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Expression variable
- 2e74a4c2-df77-46dc-b828-efbc72da5ad4
- Variable O
- O
- true
- d2a56b44-2207-4c9b-be02-a2565f8a2092
- 1
-
6761
29739
11
24
-
6766.5
29751
- Result of expression
- cd6ab750-a4f9-45be-b00b-ca9565e37623
- Result
- false
- 0
-
6958
29739
6
24
-
6961
29751
- 9df5e896-552d-4c8c-b9ca-4fc147ffa022
- Expression
- Evaluate an expression
- O*256/(2^(1423/256))
- true
- 0d03249a-2dc1-4dd6-a125-0ad6bbbbd179
- Expression
- Expression
-
6759
29686
207
28
-
6865
29700
- 1
- ba80fd98-91a1-4958-b6a7-a94e40e52bdb
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Expression variable
- c0b492e3-6fa9-46a2-92b9-529de5bbc25d
- Variable O
- O
- true
- d2a56b44-2207-4c9b-be02-a2565f8a2092
- 1
-
6761
29688
11
24
-
6766.5
29700
- Result of expression
- d1738e97-52cd-43dc-b899-679275c29c8b
- Result
- false
- 0
-
6958
29688
6
24
-
6961
29700
- 9df5e896-552d-4c8c-b9ca-4fc147ffa022
- Expression
- Evaluate an expression
- O*256/(2^(1488/256))
- true
- 263ce242-571b-42ba-bf51-7c55fd2b8670
- true
- Expression
- Expression
-
6759
29635
207
28
-
6865
29649
- 1
- ba80fd98-91a1-4958-b6a7-a94e40e52bdb
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Expression variable
- 8651d529-7f9b-4513-8a3b-1e1d16a7ec86
- true
- Variable O
- O
- true
- d2a56b44-2207-4c9b-be02-a2565f8a2092
- 1
-
6761
29637
11
24
-
6766.5
29649
- Result of expression
- e66c7ef1-4be2-45f2-b9d3-1641d499000c
- true
- Result
- false
- 0
-
6958
29637
6
24
-
6961
29649
- 9df5e896-552d-4c8c-b9ca-4fc147ffa022
- Expression
- Evaluate an expression
- O*256/(2^(1644/256))
- true
- d18b0707-d8a4-4b7b-8099-c7811c51e69c
- true
- Expression
- Expression
-
6759
29588
207
28
-
6865
29602
- 1
- ba80fd98-91a1-4958-b6a7-a94e40e52bdb
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Expression variable
- ee7043ab-02ed-4a87-839b-a12cce911bc8
- true
- Variable O
- O
- true
- d2a56b44-2207-4c9b-be02-a2565f8a2092
- 1
-
6761
29590
11
24
-
6766.5
29602
- Result of expression
- e0d15916-96e7-404c-acf4-bb92b20c7f22
- true
- Result
- false
- 0
-
6958
29590
6
24
-
6961
29602
- 9df5e896-552d-4c8c-b9ca-4fc147ffa022
- Expression
- Evaluate an expression
- O*256/(2^(1709.5/256))
- true
- 8cd8a85d-dd7a-4f19-ae57-ae730f2a54b7
- true
- Expression
- Expression
-
6751
29540
223
28
-
6865
29554
- 1
- ba80fd98-91a1-4958-b6a7-a94e40e52bdb
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Expression variable
- 612c5125-7b95-426b-afde-f1d1b9550d19
- true
- Variable O
- O
- true
- d2a56b44-2207-4c9b-be02-a2565f8a2092
- 1
-
6753
29542
11
24
-
6758.5
29554
- Result of expression
- 39c3628b-d316-41fd-aa92-8fb59c8f4b93
- true
- Result
- false
- 0
-
6966
29542
6
24
-
6969
29554
- 9df5e896-552d-4c8c-b9ca-4fc147ffa022
- Expression
- Evaluate an expression
- O*256/(2^(1794.5/256))
- true
- 11ddf5d8-c432-479f-908e-c4f10696d2ac
- true
- Expression
- Expression
-
6751
29485
223
28
-
6865
29499
- 1
- ba80fd98-91a1-4958-b6a7-a94e40e52bdb
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Expression variable
- f9ea3221-b8b2-4675-a479-e7615871ed8c
- true
- Variable O
- O
- true
- d2a56b44-2207-4c9b-be02-a2565f8a2092
- 1
-
6753
29487
11
24
-
6758.5
29499
- Result of expression
- 0329d89d-6760-447b-8dca-4e48f21d279c
- true
- Result
- false
- 0
-
6966
29487
6
24
-
6969
29499
- 9df5e896-552d-4c8c-b9ca-4fc147ffa022
- Expression
- Evaluate an expression
- O*256/(2^(1874.5/256))
- true
- f6e26e76-755b-48e9-b7bd-f62015e2d0f8
- true
- Expression
- Expression
-
6751
29430
223
28
-
6865
29444
- 1
- ba80fd98-91a1-4958-b6a7-a94e40e52bdb
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Expression variable
- 5db2238c-b131-4d6e-8277-12ff438cf44b
- true
- Variable O
- O
- true
- d2a56b44-2207-4c9b-be02-a2565f8a2092
- 1
-
6753
29432
11
24
-
6758.5
29444
- Result of expression
- adebd33e-d944-4449-9288-01f865f7a75c
- true
- Result
- false
- 0
-
6966
29432
6
24
-
6969
29444
- 9df5e896-552d-4c8c-b9ca-4fc147ffa022
- Expression
- Evaluate an expression
- O*256/(2^(1910.9609375/256))
- true
- 509efe09-a32c-40ea-b499-9d5bcf86d4e5
- true
- Expression
- Expression
-
6726
29380
273
28
-
6865
29394
- 1
- ba80fd98-91a1-4958-b6a7-a94e40e52bdb
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Expression variable
- c75e4571-abbc-41b6-a28a-3e6790990621
- true
- Variable O
- O
- true
- d2a56b44-2207-4c9b-be02-a2565f8a2092
- 1
-
6728
29382
11
24
-
6733.5
29394
- Result of expression
- ef577d9b-1e12-4acf-8032-537d137899ac
- true
- Result
- false
- 0
-
6991
29382
6
24
-
6994
29394
- 9df5e896-552d-4c8c-b9ca-4fc147ffa022
- Expression
- Evaluate an expression
- O*256/(2^(1585/256))*0
- true
- 6a9bc7b2-7363-4bdb-8081-729fe41b4263
- true
- Expression
- Expression
-
6782
29199
223
28
-
6896
29213
- 1
- ba80fd98-91a1-4958-b6a7-a94e40e52bdb
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Expression variable
- 334d1014-bb27-4cfe-8927-cfe484db0e13
- true
- Variable O
- O
- true
- d2a56b44-2207-4c9b-be02-a2565f8a2092
- 1
-
6784
29201
11
24
-
6789.5
29213
- Result of expression
- b6cd4614-1c10-4bec-87e8-ee95bc27c5ef
- true
- Result
- false
- 0
-
6997
29201
6
24
-
7000
29213
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 5ca22202-f374-413d-9eaa-70bb337aa05e
- Relay
- false
- 9f7378b6-9894-4b84-998a-f5226749112f
- 1
-
5604
30266
40
16
-
5624
30274
- d5967b9f-e8ee-436b-a8ad-29fdcecf32d5
- Curve
- Contains a collection of generic curves
- true
- 71be7197-d861-4bd1-ac6d-f9aee6f82211
- Curve
- Curve
- false
- 5ca22202-f374-413d-9eaa-70bb337aa05e
- 1
-
5736
30312
50
24
-
5761.079
30324.1
- 33bcf975-a0b2-4b54-99fd-585c893b9e88
- Digit Scroller
- Numeric scroller for single numbers
- 7e01dcbb-c16b-477c-9d2b-2c44b18b6cc8
- Digit Scroller
-
- false
- 0
- 12
-
- 11
- 6.0
-
5263
30783
250
20
-
5263.371
30783.46
- 7a1e5fd7-b7da-4244-a261-f1da66614992
- Power of 2
- Raise 2 to the power of N.
- true
- 6d15cf6d-12a8-4e06-8ab8-2c1849e3ee10
- Power of 2
- Power of 2
-
5423
30716
88
28
-
5466
30730
- Input value
- 39007c7f-c129-4ca8-9792-8060fed4c69b
- Value
- Value
- false
- 7e01dcbb-c16b-477c-9d2b-2c44b18b6cc8
- 1
-
5425
30718
29
24
-
5439.5
30730
- Output value
- 79deae85-cf4e-4143-a299-0a48fc6c9df1
- Result
- Result
- false
- 0
-
5478
30718
31
24
-
5493.5
30730
- 9df5e896-552d-4c8c-b9ca-4fc147ffa022
- Expression
- Evaluate an expression
- tan(((4*atan(1))*(O-2))/(4*((O))))^2
- true
- 1eb9bfd8-1e33-41dc-b28e-9eae2093be8d
- Expression
- Expression
-
5589
30656
364
28
-
5761
30670
- 1
- ba80fd98-91a1-4958-b6a7-a94e40e52bdb
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Expression variable
- 71ca25bc-2d23-4c0d-9bea-7be743acb3c4
- Variable O
- O
- true
- 79deae85-cf4e-4143-a299-0a48fc6c9df1
- 1
-
5591
30658
11
24
-
5596.5
30670
- Result of expression
- 2b473fd3-078c-4a44-b40d-2f6ff04a97b5
- Result
- Result
- false
- 0
-
5920
30658
31
24
-
5935.5
30670
- 9c85271f-89fa-4e9f-9f4a-d75802120ccc
- Division
- Mathematical division
- true
- 340c109f-59f8-4516-8ccf-5c01759ede3a
- Division
- Division
-
5425
30647
85
44
-
5465
30669
- Item to divide (dividend)
- 6e30154c-3911-45cd-b00c-0a9982151241
- A
- A
- false
- 79deae85-cf4e-4143-a299-0a48fc6c9df1
- 1
-
5427
30649
26
20
-
5440
30659
- Item to divide with (divisor)
- 52fff268-b256-44e3-bc43-d8430a8cdb38
- B
- B
- false
- 0
-
5427
30669
26
20
-
5440
30679
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_String
- false
- 4
- The result of the Division
- 63784ff3-69e9-47a6-ab38-b44ab4afd7a9
- Result
- Result
- false
- 0
-
5477
30649
31
40
-
5492.5
30669
- 9c85271f-89fa-4e9f-9f4a-d75802120ccc
- Division
- Mathematical division
- true
- b2e4e57e-f481-4a45-a05c-014fb31066d3
- Division
- Division
-
5422
30582
95
44
-
5472
30604
- Item to divide (dividend)
- aa50572b-a352-4a62-a274-18f777880adb
- A
- A
- false
- 0
-
5424
30584
36
20
-
5442
30594
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_String
- false
- 1050
- Item to divide with (divisor)
- b68e9aff-8b0d-43ca-99d2-feb33258622b
- B
- B
- false
- 0
-
5424
30604
36
20
-
5442
30614
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_String
- false
- 1680
- The result of the Division
- 96a7879b-7591-41a7-888d-c783ef61de3c
- Result
- Result
- false
- 0
-
5484
30584
31
40
-
5499.5
30604
- ce46b74e-00c9-43c4-805a-193b69ea4a11
- Multiplication
- Mathematical multiplication
- true
- 6fc33595-e84c-4150-9b94-2ac606465426
- Multiplication
- Multiplication
-
5434
30517
70
44
-
5459
30539
- 2
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- First item for multiplication
- a12db0b1-0781-4064-9b17-2d644a08573d
- A
- A
- true
- 63784ff3-69e9-47a6-ab38-b44ab4afd7a9
- 1
-
5436
30519
11
20
-
5441.5
30529
- Second item for multiplication
- 5f060c5f-31fc-47a8-b287-6cfbf6708371
- B
- B
- true
- 96a7879b-7591-41a7-888d-c783ef61de3c
- 1
-
5436
30539
11
20
-
5441.5
30549
- Result of multiplication
- aec64dce-0e01-4c20-b1f6-0f53bbb2c9d0
- Result
- Result
- false
- 0
-
5471
30519
31
40
-
5486.5
30539
- a0d62394-a118-422d-abb3-6af115c75b25
- Addition
- Mathematical addition
- true
- 6bf2e39c-4653-4a8a-884d-4e5020da92e9
- Addition
- Addition
-
5427
30449
85
44
-
5467
30471
- 2
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- First item for addition
- 927b0f2a-d432-4583-b60f-cc50463156b8
- A
- A
- true
- aec64dce-0e01-4c20-b1f6-0f53bbb2c9d0
- 1
-
5429
30451
26
20
-
5442
30461
- Second item for addition
- be35f3b4-01b0-4a51-bbbc-1e6c66ce0601
- B
- B
- true
- 0
-
5429
30471
26
20
-
5442
30481
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_Integer
- 1
- Result of addition
- 79f5d049-f3de-4c58-862f-0bb176b86702
- Result
- Result
- false
- 0
-
5479
30451
31
40
-
5494.5
30471
- e64c5fb1-845c-4ab1-8911-5f338516ba67
- Series
- Create a series of numbers.
- true
- 85ebccc2-561f-46b4-8154-30e69b535999
- Series
- Series
-
5416
30352
106
64
-
5477
30384
- First number in the series
- afa6aa04-f117-4c87-8797-1b5a98cb69f1
- Start
- Start
- false
- 0
-
5418
30354
47
20
-
5441.5
30364
- 1
- 1
- {0}
- 0
- Step size for each successive number
- 41bd815b-329e-451c-ad37-38a29d92edcb
- Step
- Step
- false
- 0
-
5418
30374
47
20
-
5441.5
30384
- 1
- 1
- {0}
- 1
- Number of values in the series
- c265cc54-ad6a-47a1-b9ea-1a0e32a79457
- Count
- Count
- false
- 79f5d049-f3de-4c58-862f-0bb176b86702
- 1
-
5418
30394
47
20
-
5441.5
30404
- 1
- 1
- {0}
- 10
- 1
- Series of numbers
- 2355d9c6-42ec-4fe3-8b31-6b072a7decfc
- Series
- Series
- false
- 0
-
5489
30354
31
60
-
5504.5
30384
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- Power
- Raise a value to a power.
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- Power
- Power
-
5553
30396
70
44
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5578
30418
- The item to be raised
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- A
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5555
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11
20
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5560.5
30408
- The exponent
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5555
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11
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5560.5
30428
- A raised to the B power
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5590
30398
31
40
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5605.5
30418
- 4d2a06bd-4b0f-4c65-9ee0-4220e4c01703
- Scale
- Scale an object uniformly in all directions.
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- Scale
- Scale
-
5701
30412
201
64
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5838
30444
- Base geometry
- bc307f0f-822f-4ae8-a829-cb9b6668df85
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- Geometry
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5703
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123
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5764.5
30424
- Center of scaling
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- Center
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5703
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123
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0
0
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5703
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123
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5764.5
30464
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5850
30414
50
30
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5875
30429
- Transformation data
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- Transform
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5850
30444
50
30
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5875
30459
- 59daf374-bc21-4a5e-8282-5504fb7ae9ae
- List Item
- 1
- Retrieve a specific item from a list.
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- b2bb9feb-52ea-41ad-b3c7-1f928c79e703
- List Item
- List Item
-
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86
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- Base list
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- Item index
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15
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15
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- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
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- Merge
- Merge
-
6141
30361
90
64
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30393
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31
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31
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-
6143
30403
31
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31
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- 030b487b-a566-476f-96a4-a0ae2ad283af
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- Stroke
- Applies Stroke properties to a Shape
- true
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- Stroke
- Stroke
-
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2915
228
104
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- A Graphic Plus Shape, or a Curve, Brep, Mesh
- b4d45d51-54b4-4acb-8dfa-640a8378176f
- Shape / Geometry
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- 05a8af90-beea-4c68-be26-1a555839ef5e
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152
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- The stroke color
- caf46852-3c5c-4333-93cf-19068fd1c5a7
- Color
- Color
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152
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255;255;0;0
- The stroke weight
- a9bca7d4-dbb8-4305-b5a1-05867f9bd842
- X*2
- Weight
- Weight
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152
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- Pattern
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152
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- The shape to be used at the end of open path
- 98830ed8-ef1e-4ee6-8a98-68c4832b7118
- End Cap
- End Cap
- true
- 0
-
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2997
152
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3007
- 1
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- A Graphic Plus Shape Object
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48
100
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- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
- 3b4c39fb-3e3d-4d21-91b5-984cf27bf8e2
- Merge
- Merge
-
-7569
2942
90
44
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2964
- 2
- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- e8530082-703c-4b0e-838c-e953ea848c67
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- Data 1
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2944
31
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- D2
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- 0
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2964
31
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- 0
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-7512
2944
31
40
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2964
- 071c3940-a12d-4b77-bb23-42b5d3314a0d
- Clean Tree
- Removed all null and invalid items from a data tree.
- true
- 9926d1c8-4a18-475d-ac3e-0eb39dcada3f
- Clean Tree
- Clean Tree
-
-6933
2925
135
84
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- 4
- cb95db89-6165-43b6-9c41-5702bc5bf137
- cb95db89-6165-43b6-9c41-5702bc5bf137
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- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Remove null items from the tree.
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- Remove Nulls
- Remove Nulls
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- 0
-
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2927
83
20
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2937
- 1
- 1
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- Remove invalid items from the tree.
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- Remove Invalid
- Remove Invalid
- false
- 0
-
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2947
83
20
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2957
- 1
- 1
- {0}
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- Remove empty branches from the tree.
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- Remove Empty
- Remove Empty
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2967
83
20
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- 1
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- Data tree to clean
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- Tree
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- 1
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2987
83
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2997
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- Spotless data tree
- 05a8af90-beea-4c68-be26-1a555839ef5e
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2927
24
80
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- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- d2fc56c8-8d46-4365-9ece-62f3b5c0bdb2
- Evaluate Length
- Evaluate Length
-
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2935
149
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- Curve to evaluate
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71
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- Length factor for curve evaluation
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- Length
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71
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- 1
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- If True, the Length factor is normalized (0.0 ~ 1.0)
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- Normalized
- Normalized
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71
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- 1
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- Point at the specified length
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- Point
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50
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- Tangent vector at the specified length
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50
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- Curve parameter at the specified length
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- Parameter
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50
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- 71b5b089-500a-4ea6-81c5-2f960441a0e8
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- Create a polyline connecting a number of points.
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- PolyLine
-
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2945
106
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40
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- Close polyline
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- Closed
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40
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- Resulting polyline
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- Polyline
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2947
38
40
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- fca5ad7e-ecac-401d-a357-edda0a251cbc
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- Create a polar array of geometry.
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- Polar Array
- Polar Array
-
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2917
210
101
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- Base geometry
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- Geometry
- Geometry
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132
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- Polar array plane
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132
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0
0
0
1
0
0
0
1
0
- Number of elements in array.
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- Count
- Count
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132
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- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
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- false
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2996
132
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50
48
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50
49
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- Cull Duplicates
- 1
- Cull points that are coincident within tolerance
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- Cull Duplicates
- Cull Duplicates
-
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180
64
-
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- 1
- Points to operate on
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- Points
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113
30
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- Proximity tolerance distance
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- Tolerance
- Tolerance
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- 0
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113
30
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- 1
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- {0}
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- Culled points
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2937
39
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- 1
- Index map of culled points
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39
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- Number of input points represented by this output point
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- Valence
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-
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39
20
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- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
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- Flip Matrix
- Flip Matrix
-
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2953
78
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- Data matrix to flip
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- Data
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25
24
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- 2
- Flipped data matrix
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- Data
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-
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25
24
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- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
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255;255;255;255
- A group of Grasshopper objects
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- Group
- Ⓞ
- f80cfe18-9510-4b89-8301-8e58faf423bb
- Flatten Tree
- Flatten a data tree by removing all branching information.
- true
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- Flatten Tree
- Flatten Tree
-
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2986
94
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- 2
- Data tree to flatten
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42
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- Path of flattened tree
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-
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3008
42
20
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- Flattened data tree
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-
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24
40
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3008
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 9d32acc6-285c-4614-be9d-e9a1a8f957bb
- Stream Filter
- Stream Filter
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- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- de7df531-12a3-4c6a-9b89-fd86861e4559
- Gate
- Gate
- false
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- {0}
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- Input stream at index 0
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- Stream 0
- 0
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- Input stream at index 1
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- false
- Stream 1
- 1
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- Filtered stream
- e7f722d4-1d38-40a8-b32e-ed0fe3189f41
- false
- Stream
- S(1)
- false
- 0
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- Group
- 1
-
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- A group of Grasshopper objects
- cdab9bd5-5004-4cab-bf81-dd46b06a67fb
- 9d32acc6-285c-4614-be9d-e9a1a8f957bb
- 2
- b200ada4-02c6-4b58-979a-db33270c2ca5
- Group
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
- 59863f21-924c-48c8-9ea9-6f80009b80a0
- Merge
- Merge
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- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2
- Data stream 1
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- false
- Data 1
- D1
- true
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- 1
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- 2
- Data stream 2
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- false
- Data 2
- D2
- true
- 142b2c2b-80ff-4dec-98d4-c417e6df8713
- 1
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- 2
- Data stream 3
- e86a26b3-b123-48ba-a2f2-0b911b009767
- false
- Data 3
- D3
- true
- 0
-
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- 2
- Data stream 4
- 1959b07a-d793-4831-8c70-58428325c1c8
- false
- Data 4
- D4
- true
- 0
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- 2
- Result of merge
- 6143368a-4eb6-4ee7-9fd1-57c58d116c86
- 1
- Result
- Result
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- 0
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80
-
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- 807b86e3-be8d-4970-92b5-f8cdcb45b06b
- Circle
- Create a circle defined by base plane and radius.
- 5ea2225a-6dda-48f7-9f0d-4402516699d9
- Circle
- Circle
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- Base plane of circle
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- Plane
- Plane
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- 0
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- {0}
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0
0
0
1
0
0
0
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- Radius of circle
- 84704917-287c-4e66-b80d-b9c9517881df
- Radius
- Radius
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- 0
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- 1
- 1
- {0}
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- Resulting circle
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- Circle
- Circle
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- 0
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- Relay
- 2
- A wire relay object
- a718fa55-8c5b-4640-912f-7d6cf7d4a7ca
- Relay
- false
- bd3f43b4-4857-4411-9d9d-79db4140d003
- 1
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- 758d91a0-4aec-47f8-9671-16739a8a2c5d
- Format
- Format some data using placeholders and formatting tags
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- Format
- Format
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- 1
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- Text format
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- Format
- Format
- false
- 0
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- 1
- 1
- {0}
- false
- {0:R}
- Formatting culture
- 97eca3d1-5afa-4094-9cca-19cf451f200c
- Culture
- Culture
- false
- 0
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- 1
- 1
- {0}
- 127
- Data to insert at {0} placeholders
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- false
- Data 0
- 0
- true
- aefd6959-402c-452d-bc8b-534eaab0f704
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- Formatted text
- 3ce32cd2-32f4-4b81-9739-bd10d3a37a44
- Text
- Text
- false
- 0
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- Panel
- A panel for custom notes and text values
- bd1a14a2-cd4f-46ec-9e1a-3b8efce967b6
- Panel
- false
- 0
- 3ce32cd2-32f4-4b81-9739-bd10d3a37a44
- 1
- Double click to edit panel content…
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255;255;255;255
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