0 2 2 1 0 7 2d7e6abd-318e-44d3-90ed-f36ccf41d56b Shaded 0 255;178;178;178 255;168;168;168 638437511938834599 XHG..GHX 0 -757 -499 1 0 0 7 Kangaroo2Component, Version=2.5.3.0, Culture=neutral, PublicKeyToken=794d913993c0f82d 2.5.3.0 Daniel Piker c2ea695e-1a09-6f42-266d-113498879f60 Kangaroo2 Components 2.5.3 Bengesht, Version=3.3.0.0, Culture=neutral, PublicKeyToken=null 3.3.0.0 00000000-0000-0000-0000-000000000000 CORE.Toolbox.Grasshopper, Version=1.0.0.0, Culture=neutral, PublicKeyToken=null 1.0.0.0 Thornton Tomasetti | CORE studio 08b214d9-388c-4ad0-940b-716633b47e45 CORE.Toolbox.Grasshopper BullantGH, Version=1.5.8.0, Culture=neutral, PublicKeyToken=null 1.5.8.0 Geometry Gym Pty Ltd 2cd3c35a-cada-1a81-ddba-5b184219e513 BullAnt CurvePlus, Version=1.3.0.0, Culture=neutral, PublicKeyToken=null 1.3.0.0 David Mans ab81fea9-8d16-4caf-af89-2736c660f36d CurvePlus 1.2.0.0 Anemone, Version=0.4.0.0, Culture=neutral, PublicKeyToken=null 0.4.0.0 Mateusz Zwierzycki 4442bb24-c702-460c-a1e4-fcdd321eb886 Anemone 0.4 Pufferfish, Version=3.0.0.0, Culture=neutral, PublicKeyToken=null 3.0.0.0 Michael Pryor 1c9de8a1-315f-4c56-af06-8f69fee80a7a Pufferfish 3.0.0.0 35 a412ddf4-4899-4456-8325-f3f9a8134a25 c2ea695e-1a09-6f42-266d-113498879f60 interconnectPoints Draws one line between every pair of points in a list true b7c9e6cb-4bb9-4371-9266-c5153a7f8365 interconnectPoints interconnectPoints 287 125 123 28 319 139 1 list of points to interconnect 9c9ce252-f9cc-4627-841b-a146d82ffb23 pts pts false c3463bd2-7be6-4ccd-a904-ef1db82b5b5c 1 289 127 18 24 298 139 1 interconnection lines 89099b9a-c316-428a-b85d-887b11512d54 interconnections interconnections false 0 331 127 77 24 369.5 139 717a1e25-a075-4530-bc80-d43ecc2500d9 Square 2D grid with square cells true e276bd82-4179-4dd0-bcda-e12f8c2e9fe5 Square Square 61 65 202 101 202 116 Base plane for grid 476cb35f-b09f-4b34-8b0b-2ed6d62a7d5e Plane Plane false 0 63 67 127 37 126.5 85.5 1 1 {0} 0 0 0 1 0 0 0 1 0 Size of grid cells 74a0ffe3-5ee6-444f-bf0b-df90c935f2dd Size Size false b4bd3dcc-b047-4786-9195-75f776ceebda 1 63 104 127 20 126.5 114 1 1 {0} 1 Number of grid cells in base plane x direction 2ed05fe6-71ff-47eb-8c8f-85c6130b2e65 Extent X Extent X false 0 63 124 127 20 126.5 134 1 1 {0} 2 Number of grid cells in base plane y direction 77ec3307-a57f-4b0a-a586-f2a2c2c026ea Extent Y Extent Y false 0 63 144 127 20 126.5 154 1 1 {0} 2 Grid cell outlines bf3d7fc7-870f-4fa4-b273-a6186a46a8a8 Cells Cells false 0 214 67 47 48 229.5 91.25 2 Points at grid corners true c3463bd2-7be6-4ccd-a904-ef1db82b5b5c 1 Points Points false 0 214 115 47 49 229.5 139.75 59daf374-bc21-4a5e-8282-5504fb7ae9ae List Item 0 Retrieve a specific item from a list. true 60d04b76-c516-43d1-9233-507bfab1c389 List Item List Item 478 56 72 64 530 88 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 1c757269-c29c-442a-a953-e7beb2472db3 List List false 89099b9a-c316-428a-b85d-887b11512d54 1 480 58 38 20 499 68 Item index 388db8e7-6270-4bf5-8eb7-0f288b3083ed Index Index false b12c9165-401a-469b-94ae-a2900d9e0e5b 1 480 78 38 20 499 88 1 1 {0} 3 Wrap index to list bounds 96cdfa6b-8e05-4cb3-9b8a-d3c6da337e5b Wrap Wrap false 0 480 98 38 20 499 108 1 1 {0} true Item at {i'} 7701d83b-c949-494f-8aa5-0c880ee94505 false Item i false 0 542 58 6 60 545 88 33bcf975-a0b2-4b54-99fd-585c893b9e88 Digit Scroller Numeric scroller for single numbers b12c9165-401a-469b-94ae-a2900d9e0e5b Digit Scroller Digit Scroller false 0 12 Digit Scroller 11 1.0 88 283 250 20 88.6507 283.048 4c0d75e1-4266-45b8-b5b4-826c9ad51ace 00000000-0000-0000-0000-000000000000 Divide Curves on Intersects Divide curves on all of their intersects. true adda5a6b-96fb-48be-90cc-5cbab44d2dce Divide Curves on Intersects Divide Curves on Intersects -44 320 174 44 83 342 1 curves to be divided 9a67e5a7-0450-4c73-9099-b5081ecb3d09 curves curves false d35a32c8-d648-4f3e-bf1e-67f34192b7ac 1 -42 322 113 20 14.5 332 ZeroTolerance 520ac281-a9af-4472-a46c-daed86e961ca Tolerance Tolerance false 0 -42 342 113 20 14.5 352 1 1 {0} 1E-10 1 aligned curves 225b2e81-bb3c-40b3-9329-93ce337b321e curves curves false 0 95 322 33 40 111.5 342 dc8aee5e-da26-45f0-b2c8-612fcf84157e 08b214d9-388c-4ad0-940b-716633b47e45 Clean Duplicate Lines Removes duplicate lines in a list true 0d09dc8c-f43f-4672-9da2-1c3860312253 Clean Duplicate Lines Clean Duplicate Lines -37 406 176 64 90 438 1 Lines to check for duplicates c8a413e3-366b-499a-a6df-f2b02f2216d8 Lines Lines false 225b2e81-bb3c-40b3-9329-93ce337b321e 1 -35 408 113 30 21.5 423 Distance check tolerance a7d4f1fd-0a13-475e-9b47-2eaa8cc3bdbb Tolerance Tolerance true 0 -35 438 113 30 21.5 453 1 1 {0} 1E-10 1 Filtered lines 7a40ed94-4034-4baf-9d52-28b709afe67f Lines Lines false 0 102 408 35 20 119.5 418 1 Mapped Indices aa5b2555-e8f1-4991-b842-6aff1bb4207b Indices Indices false 0 102 428 35 20 119.5 438 1 The value will be false if the line was removed. 729e2add-f50f-414c-8805-b41c4551375c Status Status false 0 102 448 35 20 119.5 458 8307c31e-e307-48e9-b7c3-f970591e86d2 2cd3c35a-cada-1a81-ddba-5b184219e513 ggNetworkPolygons Polygon from Curve network 6259c7b3-8821-4465-983f-0047ce3e407e ggNetworkPolygons ggNetworkPolygons 359 240 134 44 454 262 1 Input Curves 03fb8fdb-652c-43aa-9a5f-1e45f5198d49 Curves Curves false 0914e9a9-0860-462f-a9a9-8fd802b53dbd 1 361 242 81 20 401.5 252 Number of edges considered to be a void or perimeter location e8f731ae-a988-4e99-8b31-65b261bb43bc Perim or Void Perim or Void true 0 361 262 81 20 401.5 272 1 1 {0} 5 1 Resultant Polygons 998f0269-1acc-48ed-9365-92d8ce09be2d Cells Cells false 0 466 242 25 40 478.5 262 d6d9b934-83b2-452d-ab0c-87fc73a03ac5 ab81fea9-8d16-4caf-af89-2736c660f36d Smooth Corners Smooth the corners of a segmented curve by unitized parameter true bb26af02-1ab6-4b01-9780-2641a985a95f Smooth Corners Smooth Corners 603 199 222 64 728 231 Curve to Smooth Corners a80c8268-0ed7-4c16-b891-e57a3cb53997 Curve Curve false 5adc9ffe-2560-45aa-8c0b-07f8c3e65be5 1 605 201 111 20 660.5 211 A unitized curve parameter between 0-1 171f4205-905f-4693-ba0a-33a6827d93f7 Parameter Parameter true d49629e2-dca4-428c-9dfd-e1563a8c54bd 1 605 221 111 20 660.5 231 1 1 {0} 0.5 Blend Continuity Type 6a84a4d6-5b4f-4cb8-9925-7b1f44a36900 Continuity Continuity true 0 605 241 111 20 660.5 251 1 1 {0} 1 The smoothed polycurve dcb47632-c0dc-43b3-af1b-1f3bd7133adf Compound Curve Compound Curve false 0 740 201 83 60 781.5 231 57da07bd-ecab-415d-9d86-af36d7073abc Number Slider Numeric slider for single values d49629e2-dca4-428c-9dfd-e1563a8c54bd Number Slider Number Slider false 0 261 211 275 20 261.2587 211.7214 8 1 0 1 0 0 1 7cd2f235-466e-4d30-bd3c-3b9573ac7dda 4442bb24-c702-460c-a1e4-fcdd321eb886 Fast Loop Start Loop Start true 40090408-1902-4d05-a2d3-edf4720c8d9d Fast Loop Start Fast Loop Start 571 347 112 64 630 379 2 2e3ab970-8545-46bb-836c-1c11e5610bce 8ec86459-bf01-4409-baee-174d0d2b13d0 3 6cc73910-22ac-4eb4-882b-eb9d63b8f3c2 2e3ab970-8545-46bb-836c-1c11e5610bce 8ec86459-bf01-4409-baee-174d0d2b13d0 Loop iterations ee795da6-4920-41c2-8c96-7c5e8c49f5b4 Iterations Iterations false 048914a0-5152-43c2-afd1-faa9d7147aef 1 573 349 45 30 595.5 364 1 1 {0} 3 2 Data to loop db208c9c-84ef-4afd-b24b-5f42ae733c7b Data Data true 998f0269-1acc-48ed-9365-92d8ce09be2d 1 573 379 45 30 595.5 394 Connect to Loop End bf4a2645-019e-480b-afee-8fb72cebb472 > > false 0 642 349 39 20 661.5 359 Counter 2ec5e5c0-0ead-41cd-a44a-b277774aae7d Counter Counter false 0 642 369 39 20 661.5 379 2 Data to loop 5adc9ffe-2560-45aa-8c0b-07f8c3e65be5 Data Data false 0 642 389 39 20 661.5 399 4e5b891f-3e8d-4b3d-b677-996c63b3ac70 4442bb24-c702-460c-a1e4-fcdd321eb886 Fast Loop End Loop End 1cd2d97c-20c4-4041-841c-c610b7ddbbda Fast Loop End Fast Loop End false 0 855 304 88 64 904 336 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 2c10f295-343b-4fec-9b8d-348258c268a4 < < false bf4a2645-019e-480b-afee-8fb72cebb472 1 857 306 35 20 874.5 316 Set to true to exit the loop b7603821-ebca-433f-8887-eac5688ae8a0 Exit Exit true 0 857 326 35 20 874.5 336 1 1 {0} false 2 Data to loop 5f1d7de0-5a2a-4e59-987c-4aeff92e2fc8 Data Data false a3400721-adb8-4b7f-b6bd-5f04a6dcbd57 1 857 346 35 20 874.5 356 2 Data to loop 715f6ab9-fbde-4be9-929d-c73fac2e4d22 Data Data false 0 916 306 25 60 928.5 336 31de0644-5f01-4706-ab19-dc148215029c 1c9de8a1-315f-4c56-af06-8f69fee80a7a Prude Curve Removes the kinky parts of a curve (discontinuities) by blending the curve segments togther, if curve already has no kinks it will output with no change. true c4c6005c-f1fb-460f-8409-2ef3b6e044a8 Prude Curve Prude Curve 694 387 169 84 778 429 Curve to remove kinks from 5cb0c477-3c5d-4ddb-ae03-7a105f57e638 Curve Curve false 5adc9ffe-2560-45aa-8c0b-07f8c3e65be5 1 696 389 70 20 731 399 Length along curve from kink to blend start (if omitted document tolerance is used) 86428436-67f4-46a3-95c0-aad729aca2c2 Length Length false d49629e2-dca4-428c-9dfd-e1563a8c54bd 1 696 409 70 20 731 419 1 1 {0} 0.001 Determines how kinks are blended 0 = Tangency 1 = Curvature 8e253715-5f17-4946-a61b-2a1040e76ff4 Blend Type Blend Type false 0 696 429 70 20 731 439 1 1 {0} 0 Bulge factor for kink blend 7b912783-106d-44e1-9060-a7d055c344ea Bulge Bulge false 92c0f547-396e-4d79-9b0b-35f56346016b 1 696 449 70 20 731 459 1 1 {0} 0.5 Resulting curve without kinks a3400721-adb8-4b7f-b6bd-5f04a6dcbd57 Prude Prude false 0 790 389 71 40 825.5 409 True if kinks were removed from curve, False if curve already had no kinks f7840439-a0dd-4897-81b9-a0839807c482 Result Boolean Result Boolean false 0 790 429 71 40 825.5 449 ae669eaf-5e14-43f2-b944-5d7c8e02759e ab81fea9-8d16-4caf-af89-2736c660f36d Smooth Corners by Distance Smooth the corners of a segmented curve by distance true 2565d5d0-c744-431f-b36a-d6aa73677c72 Smooth Corners by Distance Smooth Corners by Distance 605 107 221 64 729 139 Curve to Smooth Corners 5cc39e71-06ea-4f04-b509-64de7b91c3fe Curve Curve false 5adc9ffe-2560-45aa-8c0b-07f8c3e65be5 1 607 109 110 20 662 119 The distance from the corners to blend from cf88f582-04d7-4060-85b4-b59ebf7fee7b Distance Distance true d49629e2-dca4-428c-9dfd-e1563a8c54bd 1 607 129 110 20 662 139 1 1 {0} 0.1 Blend Continuity Type b0a93e2c-1251-489c-a556-26268c0c6541 Continuity Continuity true 0 607 149 110 20 662 159 1 1 {0} 1 The smoothed polycurve 377af979-cc7e-4e0d-8b02-881bb99aa27c Compound Curve Compound Curve false 0 741 109 83 60 782.5 139 57da07bd-ecab-415d-9d86-af36d7073abc Number Slider Numeric slider for single values 92c0f547-396e-4d79-9b0b-35f56346016b Number Slider Number Slider false 0 367 433 275 20 367.0751 433.3469 8 1 0 1 0 0 0.5 d114323a-e6ee-4164-946b-e4ca0ce15efa Circle CNR Create a circle defined by center, normal and radius. b2a5d0b5-bf1d-4e92-9ebc-64e96e806704 Circle CNR Circle CNR -14 516 184 64 127 548 Center point 342c9633-17f5-472f-acad-6294286aa6ec Center Center false c3463bd2-7be6-4ccd-a904-ef1db82b5b5c 1 -12 518 127 20 59.5 528 Normal vector of circle plane 9d4f7b5a-2594-48f5-a94a-e29cbd535dba Normal Normal false 0 -12 538 127 20 59.5 548 1 1 {0} 0 0 1 Radius of circle 205432ec-6b03-4d76-91ad-f1ddae434098 X/4 Radius Radius false b4bd3dcc-b047-4786-9195-75f776ceebda 1 -12 558 127 20 59.5 568 1 1 {0} 1 Resulting circle 6a6a3dee-b2d6-4507-98dd-2dcbc639e090 Circle Circle false 0 139 518 29 60 153.5 548 57da07bd-ecab-415d-9d86-af36d7073abc Number Slider Numeric slider for single values b4bd3dcc-b047-4786-9195-75f776ceebda Number Slider Number Slider false 0 -186 7 275 20 -185.5392 7.568115 0 1 0 1 0 0 1 b6236720-8d88-4289-93c3-ac4c99f9b97b Relay 2 A wire relay object d35a32c8-d648-4f3e-bf1e-67f34192b7ac Relay false 89099b9a-c316-428a-b85d-887b11512d54 1 -51 249 40 16 -31 257 3cadddef-1e2b-4c09-9390-0e8f78f7609f Merge Merge a bunch of data streams true af3c0e57-c456-48d1-a214-80453d85cf89 Merge Merge 279 495 90 64 324 527 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 f7863fc3-5e60-4dfb-84eb-c47c688e549c false Data 1 D1 true 7a40ed94-4034-4baf-9d52-28b709afe67f 1 281 497 31 20 296.5 507 2 Data stream 2 63e7b12f-83b0-4ef2-a6d6-6bfc88cf97e2 false Data 2 D2 true 6a6a3dee-b2d6-4507-98dd-2dcbc639e090 1 281 517 31 20 296.5 527 2 Data stream 3 6177d5ac-0927-4593-a79e-849371c44ad9 false Data 3 D3 true 0 281 537 31 20 296.5 547 2 Result of merge dfd3bc1f-d28f-4b24-af34-1a9f10ff293c Result Result false 0 336 497 31 60 351.5 527 4c0d75e1-4266-45b8-b5b4-826c9ad51ace 00000000-0000-0000-0000-000000000000 Divide Curves on Intersects Divide curves on all of their intersects. true 165b557f-d908-472c-b448-9ef9d68a4852 Divide Curves on Intersects Divide Curves on Intersects 225 370 190 44 368 392 1 curves to be divided 1a23e81d-4390-458f-92e5-6659ca0997b6 1 curves curves false dfd3bc1f-d28f-4b24-af34-1a9f10ff293c 1 227 372 129 20 299.5 382 ZeroTolerance 4620c361-569f-4bd0-990c-41a5e8a26aa8 Tolerance Tolerance false 0 227 392 129 20 299.5 402 1 1 {0} 1.1641532182693481E-10 1 aligned curves 0914e9a9-0860-462f-a9a9-8fd802b53dbd curves curves false 0 380 372 33 40 396.5 392 8073a420-6bec-49e3-9b18-367f6fd76ac3 Join Curves Join as many curves as possible true 8651991b-123a-4c65-94ed-d3d970905907 Join Curves Join Curves 453 497 116 44 520 519 1 Curves to join 50d7257a-12af-4a94-aff0-7187ef3e9be2 Curves Curves false 0914e9a9-0860-462f-a9a9-8fd802b53dbd 1 455 499 53 20 481.5 509 Preserve direction of input curves dfb5a32a-ec78-44f6-9532-e44e43fcca46 Preserve Preserve false 0 455 519 53 20 481.5 529 1 1 {0} false 1 Joined curves and individual curves that could not be joined. a99cf68c-4a59-42e8-ba70-98734e713f5a Curves Curves false 0 532 499 35 40 549.5 519 33bcf975-a0b2-4b54-99fd-585c893b9e88 Digit Scroller Numeric scroller for single numbers 048914a0-5152-43c2-afd1-faa9d7147aef Digit Scroller Digit Scroller false 0 12 Digit Scroller 11 0.0 230 322 250 20 230.917 322.4928 1a38d325-98de-455c-93f1-bca431bc1243 Offset Curve Offset a curve with a specified distance. true cc464d02-c936-49ff-9085-3f60a88c5b0b Offset Curve Offset Curve 1042 282 178 101 1176 333 Curve to offset ba28349f-96cd-4a99-b9bb-f0dc9c46a234 Curve Curve false 715f6ab9-fbde-4be9-929d-c73fac2e4d22 1 1044 284 120 20 1104 294 Offset distance f33be44e-391d-4985-b711-70628e351f5b Distance Distance false 0 1044 304 120 20 1104 314 1 1 {0} -0.0215 Plane for offset operation 564b3925-6047-4abc-8d10-88a517c8b7aa Plane Plane true 0 1044 324 120 37 1104 342.5 Corner type flag. Possible values: none = 0 sharp = 1 round = 2 smooth = 3 chamfer = 4 aab422d4-2a13-440e-ab95-7dca53260739 Corners Corners false 0 1044 361 120 20 1104 371 1 1 {0} 3 1 Resulting offsets 6b3a87a6-ec83-4756-b96e-f9556b83fd1d Curve Curve false 0 1188 284 30 97 1203 332.5 f31d8d7a-7536-4ac8-9c96-fde6ecda4d0a Offset Variable Offsets a curve with a range of values 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SEEDstudio | www.studioseed.net dga_3@hotmail.com Daniel Abalde www.studioseed.net 5 136cd262-6d48-4ea6-a0c3-4555985ee4a7 4a01e956-0f0c-4fb0-81ed-ebda47c67c71 a6ebcf17-257e-4646-8072-832bcef5f64a aae36a7e-2197-4fdd-872a-b5491ba6162c bb62dbd9-0b73-4fa3-9e35-c501055bd576 261eab82-69bd-4137-9d16-b788119e9933 a8bf6877-fd31-4755-b4f0-71f4b92e8d05 866ed8a7-7f60-45b9-b36c-4904756b215f 2d62955f-50ea-45d1-9d40-e52b3700f860 71a856c1-c6f6-4f47-9691-d3fd8d633906 993 590 127 84 1076 632 4 d5967b9f-e8ee-436b-a8ad-29fdcecf32d5 3e8ca6be-fda8-4aaf-b5c0-3c54c8bb7312 cb95db89-6165-43b6-9c41-5702bc5bf137 3e8ca6be-fda8-4aaf-b5c0-3c54c8bb7312 1 d5967b9f-e8ee-436b-a8ad-29fdcecf32d5 Curve to offset true aae36a7e-2197-4fdd-872a-b5491ba6162c Curve Curve true 715f6ab9-fbde-4be9-929d-c73fac2e4d22 1 995 592 69 20 1029.5 602 Distance values 4a01e956-0f0c-4fb0-81ed-ebda47c67c71 Values Values true 0 995 612 69 20 1029.5 622 1 1 {0} 1 Set true to offset on both sides a6ebcf17-257e-4646-8072-832bcef5f64a Both sides Both sides true 0 995 632 69 20 1029.5 642 1 1 {0} false Bulge factor for connecting both sides (set a negative value to separate parts) 136cd262-6d48-4ea6-a0c3-4555985ee4a7 Bulge Bulge true 0 995 652 69 20 1029.5 662 1 1 {0} 0.5 Resulting curve bb62dbd9-0b73-4fa3-9e35-c501055bd576 Curve Curve false 0 1088 592 30 80 1103 632 424eb433-2b3a-4859-beaf-804d8af0afd7 Control Points Extract the nurbs control points and knots of a curve. true c6268300-16ed-404c-b9e4-1cafcd9a4301 Control Points Control Points 1028 963 98 64 1072 995 Curve to evaluate ac3c66ce-9074-4965-ae99-a1e5070f194c Curve Curve false 2c068412-dd41-452e-bac9-91d566047990 1 1030 965 30 60 1045 995 1 Control points of the Nurbs-form. 0ba8daa0-b028-4ef0-8f07-fda191983808 Points Points false 0 1084 965 40 20 1104 975 1 Weights of control points. 669a348d-ad69-4069-a8cf-7f2e574bd958 Weights Weights false 0 1084 985 40 20 1104 995 1 Knot vector of Nurbs-form. 6d0eb073-301d-4827-8d9f-43782ee2170c Knots Knots false 0 1084 1005 40 20 1104 1015 66d2a68e-2f1d-43d2-a53b-c6a4d17e627b Control Polygon Extract the nurbs control polygon of a curve. true d1249164-5d5a-47ee-adb4-1fe17d436eb5 Control Polygon Control Polygon 881 917 98 44 925 939 Curve to evaluate f663a06d-983e-49d2-824e-0d163288a9b4 Curve Curve false 2c068412-dd41-452e-bac9-91d566047990 1 883 919 30 40 898 939 Control polygon curve for input curve adjusted for periodicity. 71d0392e-7b4b-455e-8234-b8bcbca30fce Polygon Polygon false 0 937 919 40 20 957 929 1 Control polygon points. 228338cd-48fa-4a87-b8b2-23e31c213f7a Points Points false 0 937 939 40 20 957 949 dde71aef-d6ed-40a6-af98-6b0673983c82 Nurbs Curve Construct a nurbs curve from control points. true b2c754fa-cf3f-4949-8aca-642420263184 Nurbs Curve Nurbs Curve 1097 808 121 64 1166 840 1 Curve control points 66c45323-5749-458d-bd6e-7183c8e3c429 Vertices Vertices false a01f047a-f95f-4ccf-8851-4aad1d51ef64 1 1099 810 55 20 1126.5 820 Curve degree 39574908-c6e0-487b-bbb0-a41759c07372 Degree Degree false 0 1099 830 55 20 1126.5 840 1 1 {0} 2 Periodic curve 66339c9d-8fb2-45e3-b839-eb7e4611557a Periodic Periodic false 0 1099 850 55 20 1126.5 860 1 1 {0} true Resulting nurbs curve 41c339cc-3142-4326-b45a-76517b852b94 Curve Curve false 0 1178 810 38 20 1197 820 Curve length 32424e54-590c-416f-9d71-b2a2ef48303b Length Length false 0 1178 830 38 20 1197 840 Curve domain ebb9be39-a81a-44a6-a311-2a170079fcf1 Domain Domain false 0 1178 850 38 20 1197 860 7cd2f235-466e-4d30-bd3c-3b9573ac7dda 4442bb24-c702-460c-a1e4-fcdd321eb886 Fast Loop Start Loop Start true 1a6062cc-c8b8-41f3-b6a7-6bc74f196946 Fast Loop Start Fast Loop Start 816 691 112 64 875 723 2 2e3ab970-8545-46bb-836c-1c11e5610bce 8ec86459-bf01-4409-baee-174d0d2b13d0 3 6cc73910-22ac-4eb4-882b-eb9d63b8f3c2 2e3ab970-8545-46bb-836c-1c11e5610bce 8ec86459-bf01-4409-baee-174d0d2b13d0 Loop iterations 132f9abf-3d0f-4258-b1ee-07ff3f1039fc Iterations Iterations false d99d28cb-b887-446e-b3e6-b8d85e42901a 1 818 693 45 30 840.5 708 1 1 {0} 3 2 Data to loop 4d512fe3-1b2f-420c-b993-00193967c569 Data Data true 715f6ab9-fbde-4be9-929d-c73fac2e4d22 1 818 723 45 30 840.5 738 Connect to Loop End 7883f413-d1a3-4d27-b054-023ea5b7a296 > > false 0 887 693 39 20 906.5 703 Counter 52f33e11-cdd1-4e85-97d2-6354e07fb596 Counter Counter false 0 887 713 39 20 906.5 723 2 Data to loop 2c068412-dd41-452e-bac9-91d566047990 Data Data false 0 887 733 39 20 906.5 743 4e5b891f-3e8d-4b3d-b677-996c63b3ac70 4442bb24-c702-460c-a1e4-fcdd321eb886 Fast Loop End Loop End a0450a96-2f3f-423a-b0d0-c573fed46d11 Fast Loop End Fast Loop End false 0 1332 691 88 64 1381 723 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 2696cb58-00e5-402f-b136-7d9cf5d8bab4 < < false 7883f413-d1a3-4d27-b054-023ea5b7a296 1 1334 693 35 20 1351.5 703 Set to true to exit the loop ae3e94c2-052d-44f4-8e43-e278fae6f6e2 Exit Exit true 0 1334 713 35 20 1351.5 723 1 1 {0} false 2 Data to loop 59c75084-f5c5-43ea-9e15-a8071312b985 Data Data false 41c339cc-3142-4326-b45a-76517b852b94 1 1334 733 35 20 1351.5 743 2 Data to loop ff6f0453-468e-46a0-86d1-880be7129d67 Data Data false 0 1393 693 25 60 1405.5 723 33bcf975-a0b2-4b54-99fd-585c893b9e88 Digit Scroller Numeric scroller for single numbers d99d28cb-b887-446e-b3e6-b8d85e42901a Digit Scroller Digit Scroller false 0 12 Digit Scroller 11 19.0 501 742 250 20 501.917 742.4928 1f8e1ff7-8278-4421-b39d-350e71d85d37 Nurbs Curve PWK Construct a nurbs curve from control points, weights and knots. true 28b9b087-718f-4c32-9cb6-f78b272b1eb5 Nurbs Curve PWK Nurbs Curve PWK 1441 929 106 64 1495 961 1 Curve control points 25b10084-1c94-448f-9224-3977e629a0d8 Points Points false 0ba8daa0-b028-4ef0-8f07-fda191983808 1 1443 931 40 20 1463 941 1 Optional control point weights 8196b657-af31-4b03-bf6d-8da72032b957 Weights Weights true 669a348d-ad69-4069-a8cf-7f2e574bd958 1 1443 951 40 20 1463 961 1 Nurbs knot vector f04f6009-48e4-49eb-a355-5176f003cafa Knots Knots false 004bed2a-750e-4ca5-a5d3-235b2ca4509f 1 1443 971 40 20 1463 981 Resulting nurbs curve 575c396c-7fda-4a45-a27a-521d2bf247ae Curve Curve false 0 1507 931 38 20 1526 941 Curve length 22a68347-5b78-4c64-9a10-cb1c5c53eaa4 Length Length false 0 1507 951 38 20 1526 961 Curve domain 352f7ada-ed53-4b96-ab04-bb1fc1403a66 Domain Domain false 0 1507 971 38 20 1526 981 846470bd-4918-4d00-9388-7e022b2cba73 Knot Vector Construct a nurbs curve knot vector. 49bdc8aa-2bc2-4a2c-9583-e2b4c031e5d6 Knot Vector Knot Vector 1273 991 112 64 1341 1023 Control point count. a6d82057-339b-42f2-b648-23edce66a807 Count Count false 9590eea3-57ae-496a-a7bd-7161070d75a2 1 1275 993 54 20 1302 1003 Curve Degree. e007705d-0549-442e-994f-641ed55115b6 Degree Degree false 0 1275 1013 54 20 1302 1023 1 1 {0} 11 Curve periodicity c491de45-b8c8-40f1-8d12-5ed20ed68d80 Periodic Periodic false 0 1275 1033 54 20 1302 1043 1 1 {0} true 1 Nurbs Knot Vector. 004bed2a-750e-4ca5-a5d3-235b2ca4509f Knots Knots false 0 1353 993 30 60 1368 1023 1817fd29-20ae-4503-b542-f0fb651e67d7 List Length Measure the length of a list. ff5fe1a0-acc1-4386-bf74-8831ac810f77 List Length List Length 1160 989 81 28 1193 1003 1 Base list 5531829d-f1c1-4758-8980-6d242d8cc08d List List false 228338cd-48fa-4a87-b8b2-23e31c213f7a 1 1162 991 19 24 1171.5 1003 Number of items in L 9590eea3-57ae-496a-a7bd-7161070d75a2 Length Length false 0 1205 991 34 24 1222 1003 a79ce08b-5ca6-4d75-aeab-d735a5acaa18 ab81fea9-8d16-4caf-af89-2736c660f36d Greyville Points Returns the Greyville Points and associated parameters a882c09e-29da-43e1-9e31-57c08b448024 Greyville Points Greyville Points 1038 726 113 44 1082 748 A nurbs curve c689b322-78c0-4a48-82ab-a9b7e4e5ec7f Curve Curve false 2c068412-dd41-452e-bac9-91d566047990 1 1040 728 30 40 1055 748 1 The greyville points of the curve e50ae107-9b12-43d5-9bd1-94647c3a6508 Points Points false 0 1094 728 55 20 1121.5 738 1 The greyville parameters of the curve 9b71a82d-df97-4421-a5d5-0cfb773c9384 Parameters Parameters false 0 1094 748 55 20 1121.5 758 269eaa85-9997-4d77-a9ba-4c58cb45c9d3 Discontinuity Find all discontinuities along a curve. 00dd3ebc-8787-41a2-903d-9a8488f064b2 Discontinuity Discontinuity 1025 511 191 44 1147 533 Curve to analyze 10998773-96dc-4c67-b0c2-a131fc5cbc03 Curve Curve false 2c068412-dd41-452e-bac9-91d566047990 1 1027 513 108 20 1081 523 Level of discontinuity to test for (1=C1, 2=C2, 3=Cinfinite) 090ccc0d-0e16-4ba4-bb8b-465342585f23 Level Level false 0 1027 533 108 20 1081 543 1 1 {0} 3 1 Points at discontinuities cee1e4a0-44d1-4f3b-a086-dba624b4efaa Points Points false 0 1159 513 55 20 1186.5 523 1 Curve parameters at discontinuities 76babd58-bd12-43e2-a96a-18d9a812cdff Parameters Parameters false 0 1159 533 55 20 1186.5 543 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. 0feb05f2-8bd6-4fd0-ab0d-f86448fed30b Curve Edit Points Curve Edit Points 849 793 123 64 903 825 Curve to get the edit points of f41cc918-1c76-4b49-9752-6fd79a0b8416 Curve Curve false 2c068412-dd41-452e-bac9-91d566047990 1 851 795 40 30 871 810 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) 4ee9ddd4-6900-4c5b-9143-cb03c39320f3 Knots Knots false 0 851 825 40 30 871 840 1 1 {0} true 1 Edit points on the curve a01f047a-f95f-4ccf-8851-4aad1d51ef64 Points Points false 0 915 795 55 20 942.5 805 1 Tangent vectors at edit points e525749e-a168-487c-bef9-5f8da9944cfc Tangents Tangents false 0 915 815 55 20 942.5 825 1 Parameter values at edit points 49a10ba7-6d08-474e-b8b4-0feeb3d3c4a2 Parameters Parameters false 0 915 835 55 20 942.5 845 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