├── .gitignore ├── LICENSE ├── README.md ├── bin └── env.py ├── data ├── eight.m ├── eight.mat ├── eight.pkl ├── eight.vtk ├── torus.m ├── torus.mat └── torus.vtk ├── hello ├── requirements.txt ├── scripts ├── m2mat.py ├── m2vtk.py └── mat2vtk.py ├── src ├── ccgeom │ ├── __init__.py │ └── manifold.py ├── demo │ ├── __init__.py │ └── wildfire.py └── tools │ ├── __init__.py │ ├── converter.py │ └── viewer.py ├── test └── tests │ ├── __init__.py │ └── test_manifold.py └── zh_CN └── 2020lecture └── exc_20200705.ipynb /.gitignore: -------------------------------------------------------------------------------- 1 | # Byte-compiled / optimized / DLL files 2 | __pycache__/ 3 | *.py[cod] 4 | *$py.class 5 | 6 | # C extensions 7 | *.so 8 | 9 | # Distribution / packaging 10 | .Python 11 | env/ 12 | build/ 13 | develop-eggs/ 14 | dist/ 15 | downloads/ 16 | eggs/ 17 | .eggs/ 18 | lib/ 19 | lib64/ 20 | parts/ 21 | sdist/ 22 | var/ 23 | *.egg-info/ 24 | .installed.cfg 25 | *.egg 26 | 27 | # PyInstaller 28 | # Usually these files are written by a python script from a template 29 | # before PyInstaller builds the exe, so as to inject date/other infos into it. 30 | *.manifest 31 | *.spec 32 | 33 | # Installer logs 34 | pip-log.txt 35 | pip-delete-this-directory.txt 36 | 37 | # Unit test / coverage reports 38 | htmlcov/ 39 | .tox/ 40 | .coverage 41 | .coverage.* 42 | .cache 43 | nosetests.xml 44 | coverage.xml 45 | *,cover 46 | .hypothesis/ 47 | 48 | # Translations 49 | *.mo 50 | *.pot 51 | 52 | # Django stuff: 53 | *.log 54 | local_settings.py 55 | 56 | # Flask stuff: 57 | instance/ 58 | .webassets-cache 59 | 60 | # Scrapy stuff: 61 | .scrapy 62 | 63 | # Sphinx documentation 64 | docs/_build/ 65 | 66 | # PyBuilder 67 | target/ 68 | 69 | # IPython Notebook 70 | .ipynb_checkpoints 71 | 72 | # pyenv 73 | .python-version 74 | 75 | # celery beat schedule file 76 | celerybeat-schedule 77 | 78 | # dotenv 79 | .env 80 | 81 | # virtualenv 82 | venv/ 83 | ENV/ 84 | 85 | # Spyder project settings 86 | .spyderproject 87 | 88 | # Rope project settings 89 | .ropeproject 90 | 91 | 92 | .idea/ 93 | 94 | .py/ 95 | -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | CC0 1.0 Universal 2 | 3 | Statement of Purpose 4 | 5 | The laws of most jurisdictions throughout the world automatically confer 6 | exclusive Copyright and Related Rights (defined below) upon the creator and 7 | subsequent owner(s) (each and all, an "owner") of an original work of 8 | authorship and/or a database (each, a "Work"). 9 | 10 | Certain owners wish to permanently relinquish those rights to a Work for the 11 | purpose of contributing to a commons of creative, cultural and scientific 12 | works ("Commons") that the public can reliably and without fear of later 13 | claims of infringement build upon, modify, incorporate in other works, reuse 14 | and redistribute as freely as possible in any form whatsoever and for any 15 | purposes, including without limitation commercial purposes. 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Affirmer understands and acknowledges that Creative Commons is not a 112 | party to this document and has no duty or obligation with respect to this 113 | CC0 or use of the Work. 114 | 115 | For more information, please see 116 | 117 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Jupyter Notes on Computational Conformal Geometry 2 | 3 | How to start 4 | ------------- 5 | 6 | To view the book, just issue below commands in your terminal 7 | 8 | in bash: 9 | ```bash 10 | . hello 11 | jupyter notebook 12 | ``` 13 | 14 | or in zsh: 15 | ```bash 16 | . ./hello 17 | jupyter notebook 18 | ``` 19 | 20 | 21 | 22 | 23 | -------------------------------------------------------------------------------- /bin/env.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env python3.6 2 | # -*- coding: utf-8 -*- 3 | 4 | import sys 5 | import os 6 | import virtualenv as venv 7 | 8 | """ 9 | Colorful output 10 | """ 11 | 12 | HEADER = '\033[95m' 13 | OKBLUE = '\033[94m' 14 | OKGREEN = '\033[92m' 15 | WARNING = '\033[93m' 16 | FAIL = '\033[91m' 17 | ENDC = '\033[0m' 18 | BOLD = "\033[1m" 19 | 20 | def head(msg): 21 | print(HEADER + msg + ENDC) 22 | 23 | def info(msg): 24 | print(msg) 25 | 26 | def infog(msg): 27 | print(OKGREEN + msg + ENDC) 28 | 29 | def infob(msg): 30 | print(OKBLUE + msg + ENDC) 31 | 32 | def warn(msg): 33 | print(WARNING + msg + ENDC) 34 | 35 | def err(msg): 36 | print(FAIL + msg + ENDC) 37 | 38 | """ 39 | Welcome message 40 | """ 41 | 42 | head("Welcome!") 43 | 44 | """ 45 | Check python version 46 | """ 47 | 48 | info("checking python version...") 49 | 50 | req_version = (3, 7) 51 | cur_version = sys.version_info 52 | 53 | if cur_version < req_version: 54 | err("Your Python interpreter is too old. Please consider upgrading to 3.6 or above.") 55 | sys.exit(-1) 56 | 57 | """ 58 | Check virtual enviroment 59 | """ 60 | 61 | if not os.path.exists(".py"): 62 | if cur_version >= (3, 7, 7): 63 | sys.argv = ['.py'] 64 | venv.cli_run(sys.argv) 65 | #else: 66 | #sys.argv = ['virtualenv', '.py'] 67 | #venv.main() 68 | -------------------------------------------------------------------------------- /data/eight.mat: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/ccgeom/ccg-notes/6fade9e0ebbbe747d0f07457aa8047470d15ca1b/data/eight.mat -------------------------------------------------------------------------------- /data/eight.pkl: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/ccgeom/ccg-notes/6fade9e0ebbbe747d0f07457aa8047470d15ca1b/data/eight.pkl -------------------------------------------------------------------------------- /data/eight.vtk: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/ccgeom/ccg-notes/6fade9e0ebbbe747d0f07457aa8047470d15ca1b/data/eight.vtk -------------------------------------------------------------------------------- /data/torus.m: -------------------------------------------------------------------------------- 1 | Vertex 1 25.8158 -0.13335 -0.00428593 2 | Vertex 2 24.1204 4.82474 0.751529 3 | Vertex 3 20.204 7.32086 1.91223 4 | Vertex 4 15.8411 6.84558 1.3424 5 | Vertex 5 24.519 -4.08549 -2.39398 6 | Vertex 6 24.5399 -3.9877 2.80013 7 | Vertex 7 20.549 -5.25224 11.9263 8 | Vertex 8 15.2411 -6.55743 -1.72405 9 | Vertex 9 20.8439 -7.14888 -1.2672 10 | Vertex 10 23.9358 -5.03955 -0.851327 11 | Vertex 11 20.8731 -0.0575917 -15.2084 12 | Vertex 12 19.9651 4.87363 -13.4823 13 | Vertex 13 -19.3462 -7.41224 -4.34218 14 | Vertex 14 13.2104 6.62804 -8.00313 15 | Vertex 15 23.452 -3.89752 7.90726 16 | Vertex 16 25.7413 0.472653 1.88689 17 | 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5.77005 1326 | Vertex 1326 -8.79692 2.95552 8.56543 1327 | Vertex 1327 -12.2661 -4.19128 4.05588 1328 | Vertex 1328 -13.2901 -5.06122 2.67399 1329 | Vertex 1329 -16.8139 -7.48484 7.22183 1330 | Vertex 1330 7.45051 -6.10177 12.6093 1331 | Vertex 1331 -14.3141 -6.55644 5.51675 1332 | Vertex 1332 -13.9819 -7.43017 13.8262 1333 | Vertex 1333 -20.046 -6.78097 8.44155 1334 | Vertex 1334 -22.7438 -4.37215 8.98056 1335 | Vertex 1335 19.8317 1.11596 -16.4118 1336 | Vertex 1336 -16.533 -6.37678 15.1646 1337 | Vertex 1337 -23.5916 -2.8738 8.98706 1338 | Vertex 1338 -24.2952 0.472674 8.65498 1339 | Vertex 1339 -22.4896 -5.36905 7.26473 1340 | Vertex 1340 -19.3043 -2.197 16.6569 1341 | Vertex 1341 -14.5812 2.41009 20.8034 1342 | Vertex 1342 -13.8805 5.48851 18.9899 1343 | Vertex 1343 -15.8524 -0.469506 20.3489 1344 | Vertex 1344 -6.73636 2.89967 24.3267 1345 | Vertex 1345 2.21533 2.29401 11.8465 1346 | Vertex 1346 22.8084 1.04222 -11.9467 1347 | Vertex 1347 -15.58 4.49878 18.7237 1348 | Vertex 1348 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1371 | Vertex 1371 -8.28273 -6.47529 12.7438 1372 | Vertex 1372 -3.20334 -7.43119 19.3909 1373 | Vertex 1373 -11.2718 -6.79042 18.5812 1374 | Vertex 1374 -13.1629 -4.28926 20.6819 1375 | Vertex 1375 25.6973 -0.745979 -1.89579 1376 | Vertex 1376 -4.51448 -6.37845 21.9718 1377 | Vertex 1377 -13.8302 -2.72227 21.2082 1378 | Vertex 1378 -14.5507 0.698159 21.2599 1379 | Vertex 1379 -13.9926 -5.20489 19.247 1380 | Vertex 1380 -5.9197 -2.18806 24.8044 1381 | Vertex 1381 0.405461 2.35851 25.4225 1382 | Vertex 1382 -0.114852 5.33507 23.67 1383 | Vertex 1383 -0.917661 -0.502557 25.7805 1384 | Vertex 1384 8.87108 2.94451 23.6082 1385 | Vertex 1385 -0.512434 6.30587 22.547 1386 | Vertex 1386 24.8029 0.930264 -6.91624 1387 | Vertex 1387 -1.72401 4.34996 24.4126 1388 | Vertex 1388 7.10096 6.74999 20.6237 1389 | Vertex 1389 -0.0701456 7.43645 19.6104 1390 | Vertex 1390 -0.121483 6.77108 15.7149 1391 | Vertex 1391 -1.80887 7.32448 20.1596 1392 | Vertex 1392 6.74971 7.49589 17.5237 1393 | Vertex 1393 -12.2153 6.65952 9.58752 1394 | Vertex 1394 2.27729 5.90799 -14.259 1395 | Vertex 1395 -10.8612 5.67333 9.11087 1396 | Vertex 1396 3.91701 5.0755 12.9753 1397 | Vertex 1397 0.0488021 2.57536 12.1291 1398 | Vertex 1398 0.733991 3.41191 -12.4585 1399 | Vertex 1399 -6.67265 7.27334 19.3288 1400 | Vertex 1400 4.09649 2.00102 11.2494 1401 | Vertex 1401 0.476943 -1.49332 11.8341 1402 | Vertex 1402 4.27196 6.33564 -14.3655 1403 | Vertex 1403 -0.36328 0.0379965 11.7007 1404 | Vertex 1404 4.55741 -2.20416 11.1338 1405 | Vertex 1405 1.654 -5.01142 13.3934 1406 | Vertex 1406 20.5167 5.34117 -11.8089 1407 | Vertex 1407 0.0767224 -4.07184 12.8273 1408 | Vertex 1408 3.56222 5.19686 -13.2042 1409 | Vertex 1409 1.69799 -7.47072 18.0624 1410 | Vertex 1410 8.7849 -1.86832 8.05609 1411 | Vertex 1411 0.769501 -6.4732 15.1766 1412 | Vertex 1412 8.79157 -7.42878 17.5996 1413 | Vertex 1413 1.77501 -6.78868 21.6647 1414 | Vertex 1414 1.475 -4.29301 24.4677 1415 | Vertex 1415 23.6137 3.65459 -7.93036 1416 | Vertex 1416 9.25595 -6.36582 20.4527 1417 | Vertex 1417 1.24384 -2.73259 25.2835 1418 | Vertex 1418 0.694304 0.664574 25.7598 1419 | Vertex 1419 -0.0484385 -5.20824 23.7916 1420 | Vertex 1420 9.80084 -2.15247 23.5582 1421 | Vertex 1421 15.2362 2.40885 20.3298 1422 | Vertex 1422 13.672 5.47538 19.1608 1423 | Vertex 1423 14.404 -0.451397 21.3969 1424 | Vertex 1424 21.0722 2.93742 13.8622 1425 | Vertex 1425 12.6277 6.60842 18.0951 1426 | Vertex 1426 25.5644 0.392794 -3.48695 1427 | Vertex 1427 12.8866 4.55295 20.6241 1428 | Vertex 1428 17.7366 6.81329 12.4734 1429 | Vertex 1429 4.68346 -2.16046 25.081 1430 | Vertex 1430 9.32152 6.85889 12.8822 1431 | Vertex 1431 2.52213 -1.82948 11.6508 1432 | Vertex 1432 15.2278 7.49882 10.6056 1433 | Vertex 1433 3.50116 -3.20083 11.8831 1434 | Vertex 1434 -6.45453 7.39969 -18.8378 1435 | Vertex 1435 -10.6366 7.32764 13.573 1436 | Vertex 1436 10.5984 4.86768 8.1837 1437 | Vertex 1437 7.10047 2.53654 9.81804 1438 | Vertex 1438 25.3298 2.12289 -3.15668 1439 | Vertex 1439 25.5414 -0.673211 3.49086 1440 | Vertex 1440 9.86661 1.83249 6.7113 1441 | Vertex 1441 7.24661 -1.5221 9.3819 1442 | Vertex 1442 -13.9125 7.46532 13.5309 1443 | Vertex 1443 6.49775 0.0102532 9.73268 1444 | Vertex 1444 10.1556 -2.23964 6.4847 1445 | Vertex 1445 9.1447 -5.02942 9.95449 1446 | Vertex 1446 -6.70555 5.81119 22.2053 1447 | Vertex 1447 7.51874 -4.09174 10.4238 1448 | Vertex 1448 1.637 7.46123 -19.3736 1449 | Vertex 1449 11.9693 -7.47074 13.6368 1450 | Vertex 1450 -19.9746 7.15214 5.9661 1451 | Vertex 1451 9.50713 -6.48167 11.8771 1452 | Vertex 1452 17.377 -7.43974 9.01954 1453 | Vertex 1453 14.1584 -6.78643 16.4991 1454 | Vertex 1454 15.5743 -4.28165 18.9394 1455 | Vertex 1455 25.2267 -2.38073 3.16298 1456 | Vertex 1456 19.4606 -6.4079 11.0641 1457 | Vertex 1457 15.8689 -2.71434 19.7339 1458 | Vertex 1458 15.6888 0.702134 20.4335 1459 | Vertex 1459 13.9431 -5.19452 19.2942 1460 | Vertex 1460 21.7705 -2.20476 13.2663 1461 | Vertex 1461 24.3811 2.19948 7.4359 1462 | Vertex 1462 22.603 5.19043 7.4959 1463 | Vertex 1463 24.2396 -0.602353 8.78352 1464 | Vertex 1464 25.2929 2.72419 -1.29618 1465 | Vertex 1465 21.2417 6.36736 7.27719 1466 | Vertex 1466 19.7898 -1.0352 16.4931 1467 | Vertex 1467 22.7047 4.33816 9.15686 1468 | Vertex 1468 21.6634 6.82409 -0.624935 1469 | Vertex 1469 18.2015 7.47574 6.2268 1470 | Vertex 1470 14.6217 6.65225 5.0835 1471 | Vertex 1471 18.3541 7.37019 8.06264 1472 | Vertex 1472 18.3891 7.49055 -1.06418 1473 | Vertex 1473 -11.1013 5.85176 20.2966 1474 | Vertex 1474 -14.8898 -6.86623 -5.59472 1475 | Vertex 1475 -19.2313 4.36094 15.138 1476 | Vertex 1476 13.2439 4.67146 0.443434 1477 | Vertex 1477 11.4519 2.27769 3.71363 1478 | Vertex 1478 1.09911 7.11356 -16.4738 1479 | Vertex 1479 -14.9783 5.83052 17.661 1480 | Vertex 1480 11.8487 1.53719 -0.426662 1481 | Vertex 1481 11.4063 -1.70432 3.39965 1482 | Vertex 1482 22.7723 -1.10646 11.9914 1483 | Vertex 1483 10.9669 -0.185961 4.05373 1484 | Vertex 1484 12.185 -2.71915 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6.7543 -9.15431 1508 | Vertex 1508 -7.66325 5.73726 -21.9802 1509 | Vertex 1509 -17.6785 5.31861 15.7845 1510 | Vertex 1510 17.2103 7.35854 2.53123 1511 | Vertex 1511 16.6501 7.49773 -8.47191 1512 | Vertex 1512 14.5618 6.861 -6.36351 1513 | Vertex 1513 -16.8295 6.47959 14.6192 1514 | Vertex 1514 12.7537 4.16434 1.77735 1515 | Vertex 1515 -6.5595 1.22466 24.8618 1516 | Vertex 1516 -3.05153 5.72654 -23.0706 1517 | Vertex 1517 -11.5389 1.27711 22.9527 1518 | Vertex 1518 11.6779 0.412465 0.821215 1519 | Vertex 1519 10.5146 1.83154 -5.64218 1520 | Vertex 1520 -19.7303 -0.517403 16.6409 1521 | Vertex 1521 -16.0112 1.26046 20.0899 1522 | Vertex 1522 12.5879 -3.69184 0.966649 1523 | Vertex 1523 10.5897 -2.28252 -5.76079 1524 | Vertex 1524 -9.71572 5.43963 21.4851 1525 | Vertex 1525 14.1315 -5.98417 -3.2081 1526 | Vertex 1526 -14.372 4.03124 20.0419 1527 | Vertex 1527 11.2867 -5.09337 -7.57811 1528 | Vertex 1528 12.1524 -6.24718 -8.59566 1529 | Vertex 1529 6.68523 4.39015 -23.5214 1530 | Vertex 1530 19.753 -7.42512 0.509248 1531 | Vertex 1531 16.6491 -7.49901 -9.21191 1532 | Vertex 1532 18.4221 -5.62625 14.4179 1533 | Vertex 1533 22.6756 -5.92355 -4.14173 1534 | Vertex 1534 23.1357 -5.85312 0.630297 1535 | Vertex 1535 19.1232 -6.44476 -11.5637 1536 | Vertex 1536 20.3734 -5.427 -11.9045 1537 | Vertex 1537 25.392 -1.34975 -3.77098 1538 | Vertex 1538 25.6502 -1.27108 1.59407 1539 | Vertex 1539 22.2342 -2.39627 -12.3177 1540 | Vertex 1540 22.6928 -0.692926 -12.2221 1541 | Vertex 1541 18.2708 3.87981 -16.7259 1542 | Vertex 1542 21.3463 3.86046 -12.5905 1543 | Vertex 1543 11.5275 2.83785 -22.4811 1544 | Vertex 1544 11.3778 4.39319 -21.6316 1545 | Vertex 1545 15.4843 7.09722 -14.1976 1546 | Vertex 1546 2.00899 5.66793 -23.2595 1547 | Vertex 1547 10.6762 6.77822 -18.9438 1548 | Vertex 1548 -3.32437 7.27719 -20.1628 1549 | Vertex 1549 -18.6376 0.642678 17.8187 1550 | Vertex 1550 14.7529 7.23952 -8.20235 1551 | Vertex 1551 8.77246 7.49501 -16.4917 1552 | Vertex 1552 8.36218 6.88779 -13.5723 1553 | Vertex 1553 -18.5879 2.32554 17.3795 1554 | Vertex 1554 -19.1556 7.47302 2.35467 1555 | Vertex 1555 -18.6173 -3.79103 16.4266 1556 | Vertex 1556 20.9054 -5.74443 10.1699 1557 | Vertex 1557 -21.6258 -3.80934 12.1722 1558 | Vertex 1558 9.96009 0.278397 -6.11883 1559 | Vertex 1559 5.17486 1.80328 -10.7448 1560 | Vertex 1560 -23.3847 -5.50112 2.50346 1561 | Vertex 1561 -23.5793 -3.98888 7.31658 1562 | Vertex 1562 10.7386 -3.72939 -6.6759 1563 | Vertex 1563 5.13873 -2.32666 -10.9195 1564 | Vertex 1564 -21.9617 0.568457 13.5457 1565 | Vertex 1565 9.55132 -6.02847 -10.9634 1566 | Vertex 1566 -24.1138 -1.22948 8.88303 1567 | Vertex 1567 4.66536 -5.13218 -12.8046 1568 | Vertex 1568 4.80796 -6.28029 -14.1306 1569 | Vertex 1569 5.0005 5.34358 -23.1408 1570 | Vertex 1570 16.361 -7.41486 -11.236 1571 | Vertex 1571 8.17559 -7.49571 -17.2315 1572 | Vertex 1572 20.5214 -7.23867 1.75868 1573 | Vertex 1573 15.999 -5.79016 -16.8008 1574 | Vertex 1574 19.0656 -5.80768 -13.2165 1575 | Vertex 1575 8.75402 -6.42061 -20.5991 1576 | Vertex 1576 9.55172 -5.38654 -21.6173 1577 | Vertex 1577 18.3277 -1.19259 -18.0345 1578 | Vertex 1578 21.6733 -1.23447 -13.8295 1579 | Vertex 1579 10.7988 -2.31915 -23.045 1580 | Vertex 1580 11.2249 -0.600216 -23.223 1581 | Vertex 1581 4.99665 3.89204 -24.2539 1582 | Vertex 1582 9.9047 3.91114 -22.6818 1583 | Vertex 1583 -3.83501 2.81754 -24.9818 1584 | Vertex 1584 -3.44341 4.37353 -24.2137 1585 | Vertex 1585 4.28837 7.11068 -20.5267 1586 | Vertex 1586 5.0403 6.38483 -21.8634 1587 | Vertex 1587 -2.36511 6.76604 -21.6378 1588 | Vertex 1588 -9.40325 1.07379 -23.9695 1589 | Vertex 1589 -23.947 -4.59435 4.06445 1590 | Vertex 1590 7.41743 7.23613 -15.1785 1591 | Vertex 1591 -2.40079 7.49656 -18.5133 1592 | Vertex 1592 -1.08337 6.88062 -15.8817 1593 | Vertex 1593 -24.8759 -3.00142 3.93361 1594 | Vertex 1594 -1.31533 -6.08787 14.5627 1595 | Vertex 1595 -15.4404 -7.12174 14.1421 1596 | Vertex 1596 -4.20814 1.12423 -25.3847 1597 | Vertex 1597 18.7828 -7.49823 2.35049 1598 | Vertex 1598 4.42472 0.242327 -10.8204 1599 | Vertex 1599 -2.10921 1.83455 -11.7453 1600 | Vertex 1600 6.15544 -0.603443 -25.0512 1601 | Vertex 1601 -19.9123 -7.10317 6.62517 1602 | Vertex 1602 4.72757 -3.7702 -11.7507 1603 | Vertex 1603 -2.37697 -2.36951 -11.8441 1604 | Vertex 1604 -20.4334 -4.28313 13.5755 1605 | Vertex 1605 1.27129 -6.05745 -14.519 1606 | Vertex 1606 -21.5665 -5.67875 8.88892 1607 | Vertex 1607 -3.76495 -5.25371 -13.2029 1608 | Vertex 1608 -4.51631 -6.3827 -14.3673 1609 | Vertex 1609 1.13406 1.14647 -25.6947 1610 | Vertex 1610 6.73318 -7.41075 -18.7 1611 | Vertex 1611 -3.42374 -7.49326 -18.7935 1612 | Vertex 1612 -4.17346 -7.11455 -20.5398 1613 | Vertex 1613 3.14787 -5.78007 -22.9949 1614 | Vertex 1614 7.73088 -5.78382 -21.8984 1615 | Vertex 1615 -4.95726 -6.3951 -21.8637 1616 | Vertex 1616 -4.92412 -5.36932 -23.13 1617 | Vertex 1617 4.28072 -1.18162 -25.3571 1618 | Vertex 1618 9.45664 -1.1768 -23.9241 1619 | Vertex 1619 -4.76962 -2.32688 -24.9953 1620 | Vertex 1620 -4.52789 -0.615928 -25.3899 1621 | Vertex 1621 -10.1746 3.7798 -22.6592 1622 | Vertex 1622 -5.25979 3.88805 -24.2011 1623 | Vertex 1623 -17.6791 2.99777 -17.9415 1624 | Vertex 1624 -16.8048 4.62357 -17.5158 1625 | Vertex 1625 -8.20017 7.21762 -18.9671 1626 | Vertex 1626 -4.76884 5.35744 -23.1739 1627 | Vertex 1627 -14.4866 7.04326 -15.4634 1628 | Vertex 1628 -0.0934188 3.96063 -24.7098 1629 | Vertex 1629 15.7734 -7.39242 12.2626 1630 | Vertex 1630 -2.76879 7.22136 -16.6397 1631 | Vertex 1631 -13.2315 7.47712 -14.0402 1632 | Vertex 1632 -10.4231 7.08887 -12.716 1633 | Vertex 1633 -21.2278 -6.85014 4.03542 1634 | Vertex 1634 -4.08162 -3.19593 11.6945 1635 | Vertex 1635 -11.9491 -7.22123 11.9073 1636 | Vertex 1636 4.59872 0.559968 -25.3885 1637 | Vertex 1637 -15.4528 -7.18304 6.40111 1638 | Vertex 1638 -2.77622 0.252004 -11.3553 1639 | Vertex 1639 -8.65091 1.80724 -8.21337 1640 | Vertex 1640 10.0085 -7.47089 -16.5719 1641 | Vertex 1641 -18.3647 -7.38755 7.83668 1642 | Vertex 1642 -3.11029 -3.8185 -12.3042 1643 | Vertex 1643 -9.04604 -2.29895 -7.97291 1644 | Vertex 1644 -15.5916 -6.97088 4.17522 1645 | Vertex 1645 -7.66085 -6.10123 -12.4699 1646 | Vertex 1646 -18.3138 -7.49723 3.86302 1647 | Vertex 1647 -10.9265 -5.09296 -8.08184 1648 | Vertex 1648 -12.0951 -6.27769 -8.76203 1649 | Vertex 1649 4.83794 2.27673 -25.0035 1650 | Vertex 1650 -5.37395 -7.39978 -19.2181 1651 | Vertex 1651 -13.8875 -7.49414 -13.1239 1652 | Vertex 1652 -15.4731 -7.09524 -14.2183 1653 | Vertex 1653 -10.8995 -5.86491 -20.383 1654 | Vertex 1654 -6.57805 -5.7773 -22.2781 1655 | Vertex 1655 -16.8785 -6.3184 -14.9285 1656 | Vertex 1656 -17.5921 -5.26152 -15.9585 1657 | Vertex 1657 -11.4241 -1.23525 -23.0229 1658 | Vertex 1658 -6.37819 -1.2026 -24.9149 1659 | Vertex 1659 -18.5391 -2.19342 -17.51 1660 | Vertex 1660 -18.5553 -0.47293 -17.9338 1661 | Vertex 1661 -21.4846 3.88392 -12.328 1662 | Vertex 1662 -18.3526 4.01394 -16.5088 1663 | Vertex 1663 -24.954 2.81529 -4.01613 1664 | Vertex 1664 -24.1003 4.37684 -4.14334 1665 | Vertex 1665 8.67483 2.18373 8.32012 1666 | Vertex 1666 5.33533 -3.94913 -24.1424 1667 | Vertex 1667 -21.3917 6.76468 -4.08628 1668 | Vertex 1668 -19.8362 7.32147 -4.07763 1669 | Vertex 1669 -9.13217 -4.95631 9.88012 1670 | Vertex 1670 -12.1611 7.38243 -12.6358 1671 | Vertex 1671 -18.3339 7.49743 -3.36351 1672 | Vertex 1672 -15.6507 6.96065 -3.87525 1673 | Vertex 1673 -12.5494 -3.80526 1.84249 1674 | Vertex 1674 -9.14219 4.1098 -9.01979 1675 | Vertex 1675 10.2208 -3.93559 -22.5237 1676 | Vertex 1676 17.4421 -5.43066 -15.8802 1677 | Vertex 1677 -13.382 -7.16481 9.93424 1678 | Vertex 1678 -9.02106 0.343294 -7.45292 1679 | Vertex 1679 -11.8638 2.03929 -1.61233 1680 | Vertex 1680 -13.0085 -6.09512 6.73792 1681 | Vertex 1681 14.5953 -4.01551 -19.8935 1682 | Vertex 1682 2.87701 0.827082 11.4003 1683 | Vertex 1683 -11.9574 -2.19196 -1.25391 1684 | Vertex 1684 9.77494 0.564604 -23.881 1685 | Vertex 1685 -13.5993 -6.10951 -5.42971 1686 | Vertex 1686 -11.6494 0.107568 1.22864 1687 | Vertex 1687 -14.0155 -5.5546 -0.416323 1688 | Vertex 1688 -15.2835 -6.52231 -0.00694731 1689 | Vertex 1689 14.2011 -1.19141 -21.4295 1690 | Vertex 1690 -15.6675 -7.39226 -12.4295 1691 | Vertex 1691 -19.0247 -7.48692 -2.32975 1692 | Vertex 1692 -20.722 -7.169 -1.87966 1693 | Vertex 1693 -20.8973 -5.73604 -10.2064 1694 | Vertex 1694 -18.4681 -5.61967 -14.3732 1695 | Vertex 1695 -22.3143 -6.38757 -2.23093 1696 | Vertex 1696 -23.6244 -5.25262 -2.54588 1697 | Vertex 1697 -22.7797 -1.08232 -11.9913 1698 | Vertex 1698 -19.7891 -1.03923 -16.4931 1699 | Vertex 1699 -25.2699 -2.25916 -3.21887 1700 | Vertex 1700 -25.5554 -0.573805 -3.53661 1701 | Vertex 1701 -24.708 3.7369 2.78972 1702 | Vertex 1702 -24.6735 3.84873 -2.41065 1703 | Vertex 1703 -22.5904 2.74959 11.4069 1704 | Vertex 1704 -21.9981 4.29746 10.8183 1705 | Vertex 1705 -20.8906 7.11332 1.79059 1706 | Vertex 1706 -20.1176 7.3285 -2.48917 1707 | Vertex 1707 -19.7205 6.73513 9.36294 1708 | Vertex 1708 -18.4435 7.30287 8.53958 1709 | Vertex 1709 14.8627 -6.23265 0.224495 1710 | Vertex 1710 -16.865 7.28169 -2.49168 1711 | Vertex 1711 -16.8383 7.49342 8.26297 1712 | Vertex 1712 -15.1984 7.03384 5.89496 1713 | Vertex 1713 -10.2931 -4.58162 8.2276 1714 | Vertex 1714 -16.293 7.19917 4.01685 1715 | Vertex 1715 -11.2326 -3.04453 5.04005 1716 | Vertex 1716 16.9971 -4.44058 -17.5145 1717 | Vertex 1717 -11.6295 -1.38301 2.07706 1718 | Vertex 1718 -11.6877 0.485423 -0.811147 1719 | Vertex 1719 -10.5134 2.09168 5.76016 1720 | Vertex 1720 -9.71543 4.3572 8.67908 1721 | Vertex 1721 13.5528 -5.06275 0.60158 1722 | Vertex 1722 -12.5379 -3.55037 -0.464345 1723 | Vertex 1723 -10.3002 -1.9558 6.05435 1724 | Vertex 1724 -25.328 2.13861 3.13703 1725 | Vertex 1725 -14.3986 -6.20187 3.37887 1726 | Vertex 1726 17.7781 -2.88619 -17.918 1727 | Vertex 1727 -11.626 -5.44453 7.62252 1728 | Vertex 1728 -12.3931 -6.45574 8.74267 1729 | Vertex 1729 8.55665 -7.13561 -19.0682 1730 | Vertex 1730 -20.0186 -7.38228 -0.568938 1731 | Vertex 1731 -16.8511 -7.48236 9.23858 1732 | Vertex 1732 -17.8817 -7.15992 10.6904 1733 | Vertex 1733 -22.655 -5.94785 4.09841 1734 | Vertex 1734 -23.3369 -5.66631 -0.768063 1735 | Vertex 1735 -19.3479 -6.37501 11.3794 1736 | Vertex 1736 -20.6095 -5.22363 11.8851 1737 | Vertex 1737 -25.4122 -1.30183 3.72402 1738 | Vertex 1738 -25.674 -1.17454 -1.63504 1739 | Vertex 1739 -22.347 -2.24261 12.2427 1740 | Vertex 1740 -22.7636 -0.585425 12.1363 1741 | Vertex 1741 -18.2676 3.90915 16.7011 1742 | Vertex 1742 -21.4093 3.812 12.5477 1743 | Vertex 1743 -11.5747 2.96179 22.3903 1744 | Vertex 1744 -11.4279 4.50962 21.5071 1745 | Vertex 1745 -15.733 7.25472 13.1898 1746 | Vertex 1746 -17.633 7.32765 10.0052 1747 | Vertex 1747 -10.3078 6.93068 18.8046 1748 | Vertex 1748 -4.40728 -1.0799 25.364 1749 | Vertex 1749 -10.8604 0.931331 4.4749 1750 | Vertex 1750 -15.4148 7.33264 7.81514 1751 | Vertex 1751 -9.27763 7.43922 17.2871 1752 | Vertex 1752 -8.69315 7.21 14.3941 1753 | Vertex 1753 -12.0577 2.6765 1.72206 1754 | Vertex 1754 -11.4614 4.29442 6.07828 1755 | Vertex 1755 -13.7304 6.3107 5.94007 1756 | Vertex 1756 14.5108 -7.30581 -14.24 1757 | Vertex 1757 -16.7085 7.17821 -0.0724707 1758 | Vertex 1758 -9.90368 0.664803 6.30525 1759 | Vertex 1759 -5.1631 2.27422 10.8835 1760 | Vertex 1760 -14.4473 6.07358 2.25455 1761 | Vertex 1761 13.3713 -6.04268 5.75004 1762 | Vertex 1762 -10.2138 -3.27422 7.07142 1763 | Vertex 1763 -4.74778 -1.83787 10.9402 1764 | Vertex 1764 -12.237 3.67328 3.05159 1765 | Vertex 1765 -9.63109 -6.10156 11.0289 1766 | Vertex 1766 -15.1694 6.45892 0.331813 1767 | Vertex 1767 -4.89495 -5.39286 12.9479 1768 | Vertex 1768 -4.857 -6.42089 14.3034 1769 | Vertex 1769 8.42373 -4.43125 -22.9227 1770 | Vertex 1770 -16.5482 -7.38367 11.2722 1771 | Vertex 1771 -8.14185 -7.48927 17.3319 1772 | Vertex 1772 -8.1913 -7.16705 19.1331 1773 | Vertex 1773 -16.1407 -5.69406 16.8105 1774 | Vertex 1774 -19.3627 -5.61981 13.1439 1775 | Vertex 1775 -9.01714 -6.37762 20.5496 1776 | Vertex 1776 -9.76241 -5.2156 21.7026 1777 | Vertex 1777 -18.4097 -1.07114 17.998 1778 | Vertex 1778 -21.7543 -1.11675 13.7617 1779 | Vertex 1779 -10.9437 -2.16591 23.0458 1780 | Vertex 1780 -11.3286 -0.456512 23.1845 1781 | Vertex 1781 -5.11898 3.90643 24.2212 1782 | Vertex 1782 -9.94761 4.02408 22.5832 1783 | Vertex 1783 3.77602 2.96881 24.9175 1784 | Vertex 1784 3.35156 4.53317 24.1057 1785 | Vertex 1785 -4.93031 7.28067 19.8317 1786 | Vertex 1786 -8.4648 7.16156 19.0286 1787 | Vertex 1787 2.73236 6.94723 21.2337 1788 | Vertex 1788 4.84379 -5.20812 23.3063 1789 | Vertex 1789 -13.8212 5.38847 0.707008 1790 | Vertex 1790 -8.11363 7.44249 15.9703 1791 | Vertex 1791 2.84533 7.44862 19.3137 1792 | Vertex 1792 1.62861 7.17742 16.6181 1793 | Vertex 1793 -16.3908 7.37586 11.4645 1794 | Vertex 1794 -5.73104 4.49209 11.8065 1795 | Vertex 1795 12.033 -5.71444 -19.9453 1796 | Vertex 1796 14.5978 -6.81226 -16.0219 1797 | Vertex 1797 -25.5722 0.434571 3.45451 1798 | Vertex 1798 -4.32925 0.81274 10.9315 1799 | Face 1 589 571 537 1800 | Face 2 919 45 900 1801 | Face 3 25 1556 899 1802 | Face 4 1497 1494 300 1803 | Face 5 1244 993 174 1804 | Face 6 1439 411 898 1805 | Face 7 907 876 1476 1806 | Face 8 1100 1463 299 1807 | Face 9 83 880 1480 1808 | Face 10 7 432 100 1809 | Face 11 444 884 1484 1810 | Face 12 432 1460 860 1811 | Face 13 913 111 1488 1812 | Face 14 27 44 19 1813 | Face 15 892 616 315 1814 | Face 16 916 529 1129 1815 | Face 17 990 1390 795 1816 | Face 18 27 675 85 1817 | Face 19 485 23 631 1818 | Face 20 1485 6 894 1819 | Face 21 321 504 1104 1820 | Face 22 1098 1499 297 1821 | Face 23 323 508 1108 1822 | Face 24 36 188 988 1823 | Face 25 512 1112 325 1824 | Face 26 467 1456 856 1825 | Face 27 927 516 1116 1826 | Face 28 385 19 1670 1827 | Face 29 1519 520 1120 1828 | Face 30 1096 37 295 1829 | Face 31 1523 524 1124 1830 | Face 32 1266 1505 511 1831 | Face 33 933 131 1128 1832 | Face 34 36 675 1270 1833 | Face 35 335 532 1132 1834 | Face 36 936 569 1169 1835 | Face 37 337 536 1136 1836 | Face 38 1670 19 44 1837 | Face 39 339 540 1140 1838 | Face 40 23 94 138 1839 | Face 41 341 544 1144 1840 | Face 42 1642 1204 973 1841 | Face 43 343 548 1148 1842 | Face 44 637 1432 485 1843 | Face 45 552 1152 345 1844 | Face 46 1318 1315 505 1845 | Face 47 947 556 1156 1846 | Face 48 903 427 868 1847 | Face 49 1559 560 1160 1848 | Face 50 407 905 867 1849 | Face 51 1563 564 1164 1850 | Face 52 1465 1462 284 1851 | Face 53 953 151 1168 1852 | Face 54 126 676 1007 1853 | Face 55 355 572 1172 1854 | Face 56 956 609 1209 1855 | Face 57 357 576 1176 1856 | Face 58 1084 1471 283 1857 | Face 59 359 580 1180 1858 | Face 60 390 674 92 1859 | Face 61 361 584 1184 1860 | Face 62 674 1428 828 1861 | Face 63 363 588 1188 1862 | Face 64 1438 1426 501 1863 | Face 65 592 1192 365 1864 | Face 66 901 16 864 1865 | Face 67 967 596 1196 1866 | Face 68 430 1482 863 1867 | Face 69 1599 600 1200 1868 | Face 70 1461 1498 282 1869 | Face 71 1603 604 1204 1870 | Face 72 871 389 862 1871 | Face 73 973 603 1208 1872 | Face 74 1082 1467 281 1873 | Face 75 612 519 375 1874 | Face 76 976 649 1249 1875 | Face 77 377 39 1216 1876 | Face 78 412 714 91 1877 | Face 79 379 620 1220 1878 | Face 80 714 1424 824 1879 | Face 81 381 624 1224 1880 | Face 82 26 25 897 1881 | Face 83 383 628 803 1882 | Face 84 1099 472 860 1883 | Face 85 632 1232 385 1884 | Face 86 452 1085 859 1885 | Face 87 987 636 1236 1886 | Face 88 1457 1454 280 1887 | Face 89 1639 640 1240 1888 | Face 90 924 717 858 1889 | Face 91 1643 644 1244 1890 | Face 92 1080 1423 279 1891 | Face 93 993 1288 1248 1892 | Face 94 447 754 90 1893 | Face 95 652 1252 395 1894 | Face 96 996 689 1289 1895 | Face 97 397 656 1256 1896 | Face 98 754 1420 820 1897 | Face 99 399 660 1260 1898 | Face 100 465 29 158 1899 | Face 101 401 664 1264 1900 | Face 102 1602 1164 953 1901 | Face 103 403 668 1268 1902 | Face 104 76 187 988 1903 | Face 105 158 29 84 1904 | Face 106 445 33 1790 1905 | Face 107 1007 676 1276 1906 | Face 108 1025 434 854 1907 | Face 109 1679 680 1280 1908 | Face 110 1078 1459 277 1909 | Face 111 1683 684 1284 1910 | Face 112 1562 1124 933 1911 | Face 113 413 1328 1725 1912 | Face 114 794 1416 816 1913 | Face 115 692 1292 415 1914 | Face 116 1016 729 1329 1915 | Face 117 417 696 1296 1916 | Face 118 1790 33 74 1917 | Face 119 419 700 1300 1918 | Face 120 1076 471 275 1919 | Face 121 421 704 1304 1920 | Face 122 425 35 1750 1921 | Face 123 423 708 1308 1922 | Face 124 85 44 27 1923 | Face 125 1522 1484 913 1924 | Face 126 1635 732 1677 1925 | Face 127 1027 716 1316 1926 | Face 128 560 1559 130 1927 | Face 129 1719 720 1320 1928 | Face 130 1116 520 110 1929 | Face 131 1723 724 1324 1930 | Face 132 971 1392 465 1931 | Face 133 433 1669 1765 1932 | Face 134 409 407 865 1933 | Face 135 732 1332 435 1934 | Face 136 1036 769 1369 1935 | Face 137 437 736 1336 1936 | Face 138 1083 728 828 1937 | Face 139 439 740 1340 1938 | Face 140 710 1185 827 1939 | Face 141 441 744 1344 1940 | Face 142 1425 1422 264 1941 | Face 143 949 248 1390 1942 | Face 144 85 95 636 1943 | Face 145 114 130 1157 1944 | Face 146 1433 517 910 1945 | Face 147 1047 756 1356 1946 | Face 148 681 994 82 1947 | Face 149 1759 760 1360 1948 | Face 150 994 1388 788 1949 | Face 151 1763 764 1364 1950 | Face 152 431 430 861 1951 | Face 153 453 1199 1594 1952 | Face 154 1081 450 824 1953 | Face 155 772 1372 455 1954 | Face 156 1056 809 1409 1955 | Face 157 457 776 1376 1956 | Face 158 750 1005 823 1957 | Face 159 459 780 1380 1958 | Face 160 1421 1458 262 1959 | Face 161 461 784 1384 1960 | Face 162 958 677 822 1961 | Face 163 761 1376 424 1962 | Face 164 1062 1427 261 1963 | Face 165 1677 216 726 1964 | Face 166 721 1031 81 1965 | Face 167 1067 796 1396 1966 | Face 168 1031 1384 784 1967 | Face 169 1345 800 1400 1968 | Face 170 454 452 857 1969 | Face 171 1431 804 1404 1970 | Face 172 1079 808 820 1971 | Face 173 473 870 1330 1972 | Face 174 790 424 819 1973 | Face 175 812 1412 475 1974 | Face 176 1076 849 1449 1975 | Face 177 477 816 1416 1976 | Face 178 1417 1414 260 1977 | Face 179 479 820 1420 1978 | Face 180 1228 1032 818 1979 | Face 181 481 824 1424 1980 | Face 182 1060 1383 259 1981 | Face 183 1213 1077 443 1982 | Face 184 761 1069 80 1983 | Face 185 1635 68 1193 1984 | Face 186 1069 1380 780 1985 | Face 187 1087 836 1436 1986 | Face 188 564 132 1598 1987 | Face 189 1665 840 1440 1988 | Face 190 49 129 1157 1989 | Face 191 1410 844 1444 1990 | Face 192 95 187 1236 1991 | Face 193 493 514 1761 1992 | Face 194 1750 35 64 1993 | Face 195 852 1452 495 1994 | Face 196 1096 889 1489 1995 | Face 197 497 856 1456 1996 | Face 198 1788 757 814 1997 | Face 199 499 860 1460 1998 | Face 200 1058 1419 257 1999 | Face 201 126 188 1270 2000 | Face 202 1313 1107 1102 2001 | Face 203 554 1138 1103 2002 | Face 204 1092 1376 776 2003 | Face 205 49 132 1163 2004 | Face 206 1106 1226 511 2005 | Face 207 1415 1102 1107 2006 | Face 208 1056 807 255 2007 | Face 209 1109 306 906 2008 | Face 210 305 63 1510 2009 | Face 211 929 520 1116 2010 | Face 212 512 325 1511 2011 | Face 213 676 54 1766 2012 | Face 214 950 74 33 2013 | Face 215 65 129 1120 2014 | Face 216 1116 110 927 2015 | Face 217 107 131 1124 2016 | Face 218 53 405 1706 2017 | Face 219 1399 1352 445 2018 | Face 220 713 710 825 2019 | Face 221 1063 1050 788 2020 | Face 222 1029 1781 787 2021 | Face 223 558 189 1240 2022 | Face 224 1385 1382 244 2023 | Face 225 187 640 1236 2024 | Face 226 1044 1391 243 2025 | Face 227 1010 1446 72 2026 | Face 228 1128 333 933 2027 | Face 229 1446 1348 748 2028 | Face 230 556 24 1402 2029 | Face 231 753 750 821 2030 | Face 232 335 935 532 2031 | Face 233 1061 768 784 2032 | Face 234 518 1139 1134 2033 | Face 235 1135 679 530 2034 | Face 236 1052 1748 783 2035 | Face 237 1381 1418 242 2036 | Face 238 1386 1103 1138 2037 | Face 239 639 1134 1139 2038 | Face 240 1784 1009 782 2039 | Face 241 1042 1387 241 2040 | Face 242 247 1147 1142 2041 | Face 243 1689 1178 1143 2042 | Face 244 1034 1515 71 2043 | Face 245 1515 1344 744 2044 | Face 246 1146 147 551 2045 | Face 247 364 1142 1147 2046 | Face 248 793 790 817 2047 | Face 249 1149 326 926 2048 | Face 250 1059 1119 780 2049 | Face 251 1339 1018 1606 2050 | Face 252 552 345 1551 2051 | Face 253 1090 1773 779 2052 | Face 254 1377 1374 240 2053 | Face 255 1780 1517 778 2054 | Face 256 1156 130 947 2055 | Face 257 1040 1343 239 2056 | Face 258 1510 63 4 2057 | Face 259 1071 1555 70 2058 | Face 260 1555 1340 740 2059 | Face 261 79 128 1150 2060 | Face 262 79 556 947 2061 | Face 263 89 14 1550 2062 | Face 264 559 192 1283 2063 | Face 265 137 573 1179 2064 | Face 266 1776 1070 774 2065 | Face 267 1038 1379 237 2066 | Face 268 1168 353 953 2067 | Face 269 126 54 676 2068 | Face 270 89 555 127 2069 | Face 271 1595 1336 736 2070 | Face 272 355 955 572 2071 | Face 273 99 128 928 2072 | Face 274 1681 1179 1174 2073 | Face 275 1175 1640 570 2074 | Face 276 1036 1115 235 2075 | Face 277 1765 1371 1193 2076 | Face 278 314 1143 1178 2077 | Face 279 1795 1174 1179 2078 | Face 280 126 1270 1672 2079 | Face 281 99 555 1150 2080 | Face 282 1546 1187 1182 2081 | Face 283 965 1218 1183 2082 | Face 284 1557 1736 1604 2083 | Face 285 1677 732 1035 2084 | Face 286 1186 1448 591 2085 | Face 287 1628 1182 1187 2086 | Face 288 1793 1312 425 2087 | Face 289 1189 346 946 2088 | Face 290 1030 1029 785 2089 | Face 291 114 929 928 2090 | Face 292 592 365 1591 2091 | Face 293 1043 1524 748 2092 | Face 294 1509 1741 747 2093 | Face 295 1486 1342 224 2094 | Face 296 1196 150 967 2095 | Face 297 135 185 986 2096 | Face 298 135 1270 675 2097 | Face 299 1024 1351 223 2098 | Face 300 1475 178 62 2099 | Face 301 178 1308 708 2100 | Face 302 1054 1052 781 2101 | Face 303 127 14 89 2102 | Face 304 1041 1074 744 2103 | Face 305 1549 1777 743 2104 | Face 306 1341 1378 222 2105 | Face 307 1744 1473 742 2106 | Face 308 1208 373 973 2107 | Face 309 1022 1347 221 2108 | Face 310 127 134 516 2109 | Face 311 1520 648 61 2110 | Face 312 375 975 612 2111 | Face 313 648 1304 704 2112 | Face 314 945 1219 1214 2113 | Face 315 1215 1154 610 2114 | Face 316 1091 1090 777 2115 | Face 317 1039 1604 740 2116 | Face 318 1609 1183 1218 2117 | Face 319 1073 1214 1219 2118 | Face 320 1589 1733 739 2119 | Face 321 1337 1334 220 2120 | Face 322 829 1227 1222 2121 | Face 323 470 1258 1223 2122 | Face 324 1740 278 738 2123 | Face 325 1020 1303 219 2124 | Face 326 1765 68 433 2125 | Face 327 883 1222 1227 2126 | Face 328 1560 1239 60 2127 | Face 329 1229 366 966 2128 | Face 330 1239 1300 700 2129 | Face 331 839 1229 786 2130 | Face 332 385 838 632 2131 | Face 333 134 929 1116 2132 | Face 334 1233 772 1055 2133 | Face 335 559 189 1277 2134 | Face 336 1236 1674 987 2135 | Face 337 1233 236 766 2136 | Face 338 155 185 1232 2137 | Face 339 1736 1557 734 2138 | Face 340 1018 1339 217 2139 | Face 341 155 671 1271 2140 | Face 342 796 84 633 2141 | Face 343 684 192 1718 2142 | Face 344 154 562 565 2143 | Face 345 1016 1601 215 2144 | Face 346 93 1440 97 2145 | Face 347 52 668 349 2146 | Face 348 1248 393 993 2147 | Face 349 154 131 1161 2148 | Face 350 1146 1149 147 2149 | Face 351 219 737 1020 2150 | Face 352 395 995 652 2151 | Face 353 79 24 556 2152 | Face 354 436 1259 1254 2153 | Face 355 1255 593 650 2154 | Face 356 1272 405 53 2155 | Face 357 1513 1509 745 2156 | Face 358 878 1223 1258 2157 | Face 359 531 1254 1259 2158 | Face 360 1023 73 708 2159 | Face 361 1370 1701 707 2160 | Face 362 214 1267 1262 2161 | Face 363 830 1298 1263 2162 | Face 364 1305 1302 204 2163 | Face 365 349 1003 175 2164 | Face 366 270 468 258 2165 | Face 367 356 1262 1267 2166 | Face 368 1004 1311 203 2167 | Face 369 1269 386 986 2168 | Face 370 115 166 52 2169 | Face 371 234 1269 1271 2170 | Face 372 79 1150 1552 2171 | Face 373 166 1268 668 2172 | Face 374 1553 1549 741 2173 | Face 375 1021 1564 704 2174 | Face 376 1276 190 1007 2175 | Face 377 1797 1737 703 2176 | Face 378 76 190 1277 2177 | Face 379 1301 1338 202 2178 | Face 380 1704 123 702 2179 | Face 381 1002 1307 201 2180 | Face 382 238 309 51 2181 | Face 383 1661 254 194 2182 | Face 384 309 1264 664 2183 | Face 385 1593 1589 737 2184 | Face 386 1019 59 700 2185 | Face 387 797 1693 699 2186 | Face 388 1262 1265 214 2187 | Face 389 1297 1294 200 2188 | Face 390 167 125 926 2189 | Face 391 1700 316 698 2190 | Face 392 415 1015 692 2191 | Face 393 1000 1263 199 2192 | Face 394 930 1299 1294 2193 | Face 395 13 1293 69 2194 | Face 396 1012 392 50 2195 | Face 397 392 1260 660 2196 | Face 398 336 1263 1298 2197 | Face 399 43 1294 1299 2198 | Face 400 167 1150 555 2199 | Face 401 1239 1560 1589 2200 | Face 402 1194 1307 1302 2201 | Face 403 1566 1338 1303 2202 | Face 404 207 125 1112 2203 | Face 405 97 289 1483 2204 | Face 406 1155 772 1233 2205 | Face 407 218 1302 1307 2206 | Face 408 1696 1094 694 2207 | Face 409 1309 406 1006 2208 | Face 410 998 1299 197 2209 | Face 411 1450 1309 1311 2210 | Face 412 207 551 147 2211 | Face 413 1236 640 1674 2212 | Face 414 509 1256 656 2213 | Face 415 1303 1020 1566 2214 | Face 416 1316 1754 1027 2215 | Face 417 996 69 195 2216 | Face 418 1271 984 234 2217 | Face 419 1554 1705 203 2218 | Face 420 680 1679 190 2219 | Face 421 22 548 327 2220 | Face 422 278 1740 1564 2221 | Face 423 803 194 254 2222 | Face 424 327 943 227 2223 | Face 425 632 106 671 2224 | Face 426 1290 1370 705 2225 | Face 427 1003 349 668 2226 | Face 428 183 665 984 2227 | Face 429 254 1661 667 2228 | Face 430 1334 1337 1561 2229 | Face 431 1265 1262 184 2230 | Face 432 435 1035 732 2231 | Face 433 683 191 1244 2232 | Face 434 1561 1339 1334 2233 | Face 435 1641 1333 1601 2234 | Face 436 984 1271 183 2235 | Face 437 194 803 42 2236 | Face 438 198 1303 1338 2237 | Face 439 1606 1334 1339 2238 | Face 440 468 268 1087 2239 | Face 441 1724 1797 701 2240 | Face 442 1479 1347 1342 2241 | Face 443 1089 1378 1343 2242 | Face 444 1001 896 664 2243 | Face 445 367 1697 663 2244 | Face 446 1026 1351 1349 2245 | Face 447 1526 1342 1347 2246 | Face 448 1261 1298 182 2247 | Face 449 1349 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3586 | Face 1788 825 263 713 3587 | Face 1789 295 893 55 3588 | Face 1790 824 91 714 3589 | Face 1791 823 279 1423 3590 | Face 1792 706 169 1237 3591 | Face 1793 1460 432 26 3592 | Face 1794 822 264 1422 3593 | Face 1795 898 500 1439 3594 | Face 1796 821 261 753 3595 | Face 1797 899 897 25 3596 | Face 1798 820 90 754 3597 | Face 1799 819 257 1419 3598 | Face 1800 571 589 5 3599 | Face 1801 818 242 1418 3600 | Face 1802 885 411 901 3601 | Face 1803 1101 1415 902 3602 | Face 1804 817 259 793 3603 | Face 1805 1637 1331 726 3604 | Face 1806 751 389 903 3605 | Face 1807 1555 1071 1090 3606 | Face 1808 706 172 1243 3607 | Face 1809 3 370 711 3608 | Face 1810 370 286 711 3609 | Face 1811 906 306 1247 3610 | Face 1812 906 105 1266 3611 | Face 1813 907 1514 488 3612 | Face 1814 907 288 332 3613 | Face 1815 908 308 1162 3614 | Face 1816 908 312 1167 3615 | Face 1817 814 260 1414 3616 | Face 1818 1278 600 1196 3617 | Face 1819 1117 1519 991 3618 | Face 1820 1117 109 1033 3619 | Face 1821 813 257 833 3620 | Face 1822 292 1518 884 3621 | Face 1823 1121 1523 872 3622 | Face 1824 1121 111 909 3623 | Face 1825 913 313 1721 3624 | Face 1826 913 1721 1522 3625 | Face 1827 522 1527 789 3626 | Face 1828 522 113 525 3627 | Face 1829 92 481 390 3628 | Face 1830 915 296 86 3629 | Face 1831 1129 679 916 3630 | Face 1832 916 535 688 3631 | Face 1833 465 918 971 3632 | Face 1834 1495 1572 917 3633 | Face 1835 1130 639 1139 3634 | Face 1836 992 243 1391 3635 | Face 1837 788 82 994 3636 | Face 1838 1455 6 919 3637 | Face 1839 1137 554 920 3638 | Face 1840 787 241 1387 3639 | Face 1841 763 692 1234 3640 | Face 1842 1503 1346 921 3641 | Face 1843 1141 364 922 3642 | Face 1844 785 243 1030 3643 | Face 1845 784 81 1031 3644 | Face 1846 1507 1295 923 3645 | Face 1847 1343 1040 1089 3646 | Face 1848 783 259 1383 3647 | Face 1849 1511 1314 512 3648 | Face 1850 1314 1511 506 3649 | Face 1851 926 326 167 3650 | Face 1852 926 125 207 3651 | Face 1853 927 110 308 3652 | Face 1854 927 108 1125 3653 | Face 1855 928 328 114 3654 | Face 1856 928 929 134 3655 | Face 1857 782 244 1382 3656 | Face 1858 718 169 1200 3657 | Face 1859 1157 1559 49 3658 | Face 1860 1157 129 65 3659 | Face 1861 781 241 1054 3660 | Face 1862 763 58 1644 3661 | Face 1863 1161 1563 154 3662 | Face 1864 1161 131 107 3663 | Face 1865 933 333 1527 3664 | Face 1866 933 1527 1562 3665 | Face 1867 562 1567 792 3666 | Face 1868 562 133 565 3667 | Face 1869 780 80 1069 3668 | Face 1870 935 116 775 3669 | Face 1871 1169 1640 936 3670 | Face 1872 936 575 1132 3671 | Face 1873 779 237 1379 3672 | Face 1874 1535 590 937 3673 | Face 1875 1170 1795 1179 3674 | Face 1876 778 222 1378 3675 | Face 1877 777 239 1091 3676 | Face 1878 1539 487 939 3677 | Face 1879 1177 1689 940 3678 | Face 1880 151 953 1164 3679 | Face 1881 636 44 85 3680 | Face 1882 1543 294 941 3681 | Face 1883 1181 1628 942 3682 | Face 1884 774 240 1374 3683 | Face 1885 773 237 1153 3684 | Face 1886 1547 227 943 3685 | Face 1887 390 1424 905 3686 | Face 1888 1466 450 924 3687 | Face 1889 1551 253 552 3688 | Face 1890 253 1551 546 3689 | Face 1891 946 346 1478 3690 | Face 1892 946 145 1492 3691 | Face 1893 947 130 328 3692 | Face 1894 947 128 79 3693 | Face 1895 948 348 1398 3694 | Face 1896 948 47 1408 3695 | Face 1897 445 1786 1399 3696 | Face 1898 197 693 998 3697 | Face 1899 1197 1599 1319 3698 | Face 1900 1197 149 1354 3699 | Face 1901 1442 223 1351 3700 | Face 1902 723 168 1230 3701 | Face 1903 1201 1603 1242 3702 | Face 1904 1201 151 1274 3703 | Face 1905 953 353 1567 3704 | Face 1906 953 1567 1602 3705 | Face 1907 602 1607 1206 3706 | Face 1908 602 153 605 3707 | Face 1909 748 72 1446 3708 | Face 1910 955 136 799 3709 | Face 1911 1209 1154 956 3710 | Face 1912 956 615 1172 3711 | Face 1913 747 221 1347 3712 | Face 1914 1575 1729 957 3713 | Face 1915 1210 1073 1219 3714 | Face 1916 723 636 987 3715 | Face 1917 745 223 1513 3716 | Face 1918 1579 1675 959 3717 | Face 1919 1217 965 960 3718 | Face 1920 744 71 1515 3719 | Face 1921 743 239 1343 3720 | Face 1922 1583 1596 961 3721 | Face 1923 1221 883 962 3722 | Face 1924 742 224 1342 3723 | Face 1925 741 221 1553 3724 | Face 1926 1587 1516 963 3725 | Face 1927 1225 839 964 3726 | Face 1928 740 70 1555 3727 | Face 1929 1591 1548 592 3728 | Face 1930 1548 1591 586 3729 | Face 1931 966 366 798 3730 | Face 1932 966 165 801 3731 | Face 1933 967 150 348 3732 | Face 1934 967 148 1362 3733 | Face 1935 968 368 749 3734 | Face 1936 968 1278 759 3735 | Face 1937 739 217 1339 3736 | Face 1938 735 34 1630 3737 | Face 1939 1237 1639 706 3738 | Face 1940 1237 169 718 3739 | Face 1941 738 202 1338 3740 | Face 1942 735 635 758 3741 | Face 1943 1241 1643 666 3742 | Face 1944 1241 171 678 3743 | Face 1945 973 373 1607 3744 | Face 1946 973 1607 1642 3745 | Face 1947 1245 1647 629 3746 | Face 1948 1245 173 645 3747 | Face 1949 737 219 1593 3748 | Face 1950 975 156 1198 3749 | Face 1951 1249 593 976 3750 | Face 1952 976 655 599 3751 | Face 1953 872 111 1121 3752 | Face 1954 1615 1612 977 3753 | Face 1955 1250 531 1259 3754 | Face 1956 746 168 968 3755 | Face 1957 734 220 1334 3756 | Face 1958 1619 925 979 3757 | Face 1959 1257 470 980 3758 | Face 1960 949 796 1067 3759 | Face 1961 1517 1780 1074 3760 | Face 1962 1623 869 981 3761 | Face 1963 1261 356 982 3762 | Face 1964 425 1746 1793 3763 | Face 1965 1374 1377 1072 3764 | Face 1966 1627 815 983 3765 | Face 1967 1265 234 984 3766 | Face 1968 708 62 178 3767 | Face 1969 838 385 1631 3768 | Face 1970 1631 626 1627 3769 | Face 1971 986 386 135 3770 | Face 1972 986 185 155 3771 | Face 1973 987 1674 368 3772 | Face 1974 987 168 723 3773 | Face 1975 988 388 76 3774 | Face 1976 988 187 95 3775 | Face 1977 707 201 1307 3776 | Face 1978 746 635 1230 3777 | Face 1979 1277 1679 559 3778 | Face 1980 1277 189 558 3779 | Face 1981 749 1278 968 3780 | Face 1982 872 522 525 3781 | Face 1983 1281 1683 709 3782 | Face 1984 1281 191 683 3783 | Face 1985 993 393 1647 3784 | Face 1986 280 480 1457 3785 | Face 1987 1773 1090 1071 3786 | Face 1988 262 462 1421 3787 | Face 1989 705 203 1290 3788 | Face 1990 995 176 611 3789 | Face 1991 1289 13 996 3790 | Face 1992 996 195 1358 3791 | Face 1993 704 61 648 3792 | Face 1994 1655 1652 997 3793 | Face 1995 1293 43 998 3794 | Face 1996 703 219 1303 3795 | Face 1997 702 204 1302 3796 | Face 1998 1659 396 999 3797 | Face 1999 1297 830 1000 3798 | Face 2000 701 201 1724 3799 | Face 2001 700 60 1239 3800 | Face 2002 1663 316 1001 3801 | Face 2003 1301 218 1002 3802 | Face 2004 699 197 1299 3803 | Face 2005 698 182 1298 3804 | Face 2006 1667 175 1003 3805 | Face 2007 1305 1450 1004 3806 | Face 2008 697 199 712 3807 | Face 2009 1706 405 1671 3808 | Face 2010 1671 186 1668 3809 | Face 2011 1006 406 1714 3810 | Face 2012 1006 205 1554 3811 | Face 2013 1007 190 388 3812 | Face 2014 1007 188 126 3813 | Face 2015 1008 408 1764 3814 | Face 2016 1008 669 1789 3815 | Face 2017 1355 755 1393 3816 | Face 2018 758 34 735 3817 | Face 2019 1317 1719 1749 3818 | Face 2020 1317 209 1753 3819 | Face 2021 758 759 596 3820 | Face 2022 759 1278 1196 3821 | Face 2023 1321 1723 1715 3822 | Face 2024 1321 211 1717 3823 | Face 2025 1299 998 43 3824 | Face 2026 413 1687 719 3825 | Face 2027 1325 1727 1680 3826 | Face 2028 725 1325 1680 3827 | Face 2029 694 200 1294 3828 | Face 2030 1015 196 1234 3829 | Face 2031 1329 1641 1016 3830 | Face 2032 1016 215 1646 3831 | Face 2033 693 197 695 3832 | Face 2034 1695 1692 1017 3833 | Face 2035 1333 1606 1018 3834 | Face 2036 81 479 721 3835 | Face 2037 53 96 1272 3836 | Face 2038 1699 1094 1019 3837 | Face 2039 1337 1566 1020 3838 | Face 2040 671 183 1271 3839 | Face 2041 668 52 166 3840 | Face 2042 1703 278 1021 3841 | Face 2043 1341 1526 1022 3842 | Face 2044 667 181 1267 3843 | Face 2045 1094 1696 59 3844 | Face 2046 1707 123 1023 3845 | Face 2047 912 251 1364 3846 | Face 2048 665 183 274 3847 | Face 2049 1746 425 1711 3848 | Face 2050 1711 206 1708 3849 | Face 2051 1026 426 1435 3850 | Face 2052 1026 225 1442 3851 | Face 2053 1027 1754 408 3852 | Face 2054 1027 208 1755 3853 | Face 2055 1028 428 1366 3854 | Face 2056 1028 1720 1395 3855 | Face 2057 664 51 309 3856 | Face 2058 35 1355 1393 3857 | Face 2059 1357 1759 1322 3858 | Face 2060 1357 229 1326 3859 | Face 2061 663 199 1263 3860 | Face 2062 1119 1059 1070 3861 | Face 2063 1361 1763 1279 3862 | Face 2064 1361 231 1282 3863 | Face 2065 909 111 1484 3864 | Face 2066 433 1727 1713 3865 | Face 2067 1365 1767 1235 3866 | Face 2068 765 1365 1235 3867 | Face 2069 662 184 1262 3868 | Face 2070 1035 216 1677 3869 | Face 2071 1369 1166 1036 3870 | Face 2072 1036 235 1195 3871 | Face 2073 661 181 376 3872 | Face 2074 1735 1732 1037 3873 | Face 2075 1373 1122 1038 3874 | Face 2076 660 50 392 3875 | Face 2077 659 177 1259 3876 | Face 2078 1739 1557 1039 3877 | Face 2079 1377 1089 1040 3878 | Face 2080 658 162 1258 3879 | Face 2081 657 179 496 3880 | Face 2082 1743 1517 1041 3881 | Face 2083 1381 1051 1042 3882 | Face 2084 1353 756 1047 3883 | Face 2085 1353 228 1350 3884 | Face 2086 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628 879 3984 | Face 2186 493 1285 557 3985 | Face 2187 882 1721 87 3986 | Face 2188 882 293 1487 3987 | Face 2189 587 141 1187 3988 | Face 2190 1095 276 527 3989 | Face 2191 1489 66 1096 3990 | Face 2192 1096 295 75 3991 | Face 2193 392 1012 797 3992 | Face 2194 1045 1133 1097 3993 | Face 2195 1493 46 1098 3994 | Face 2196 969 74 950 3995 | Face 2197 584 31 1588 3996 | Face 2198 944 434 1099 3997 | Face 2199 1497 17 1100 3998 | Face 2200 583 159 1183 3999 | Face 2201 902 1386 1101 4000 | Face 2202 582 144 1182 4001 | Face 2203 104 502 1295 4002 | Face 2204 581 141 1649 4003 | Face 2205 119 503 1537 4004 | Face 2206 580 30 1666 4005 | Face 2207 579 137 1179 4006 | Face 2208 372 1541 1104 4007 | Face 2209 1111 1313 1105 4008 | Face 2210 578 122 1178 4009 | Face 2211 879 983 815 4010 | Face 2212 577 139 1726 4011 | Face 2213 101 507 1501 4012 | Face 2214 756 74 969 4013 | Face 2215 1263 1000 830 4014 | Face 2216 273 1545 1108 4015 | Face 2217 906 1226 1109 4016 | Face 2218 1109 506 1511 4017 | Face 2219 574 140 1174 4018 | Face 2220 1110 108 1127 4019 | Face 2221 103 511 1505 4020 | Face 2222 573 137 1796 4021 | Face 2223 570 338 1170 4022 | Face 2224 1112 125 89 4023 | Face 2225 908 1167 1127 4024 | Face 2226 908 108 308 4025 | Face 2227 524 112 1558 4026 | Face 2228 1621 843 826 4027 | Face 2229 551 545 1151 4028 | Face 2230 515 105 1247 4029 | Face 2231 1116 516 134 4030 | Face 2232 991 109 1117 4031 | Face 2233 1117 1033 1162 4032 | Face 2234 1117 110 1519 4033 | Face 2235 1222 1225 829 4034 | Face 2236 991 112 1123 4035 | Face 2237 548 22 213 4036 | Face 2238 316 1700 896 4037 | Face 2239 1120 520 65 4038 | Face 2240 1120 129 642 4039 | Face 2241 1121 909 1123 4040 | Face 2242 1121 112 1523 4041 | Face 2243 547 121 1147 4042 | Face 2244 312 880 1476 4043 | Face 2245 1294 1297 930 4044 | Face 2246 1123 109 991 4045 | Face 2247 1124 524 107 4046 | Face 2248 463 810 847 4047 | Face 2249 786 964 839 4048 | Face 2250 1326 229 1320 4049 | Face 2251 1693 797 1012 4050 | Face 2252 526 116 672 4051 | Face 2253 82 461 681 4052 | Face 2254 525 111 872 4053 | Face 2255 1128 131 565 4054 | Face 2256 1128 133 1565 4055 | Face 2257 1129 529 672 4056 | Face 2258 1129 116 1531 4057 | Face 2259 318 530 590 4058 | Face 2260 544 21 287 4059 | Face 2261 543 139 1143 4060 | Face 2262 1131 113 789 4061 | Face 2263 1132 1756 335 4062 | Face 2264 1756 1132 575 4063 | Face 2265 80 780 1119 4064 | Face 2266 542 124 1142 4065 | Face 2267 120 534 487 4066 | Face 2268 541 121 372 4067 | Face 2269 1508 826 843 4068 | Face 2270 540 20 469 4069 | Face 2271 539 117 1139 4070 | Face 2272 1796 1573 1136 4071 | Face 2273 920 518 1137 4072 | Face 2274 538 102 1138 4073 | Face 2275 102 538 1346 4074 | Face 2276 537 119 589 4075 | Face 2277 117 539 1533 4076 | Face 2278 1033 109 1480 4077 | Face 2279 59 1019 1094 4078 | Face 2280 1726 1577 1140 4079 | Face 2281 922 314 1141 4080 | Face 2282 534 120 1134 4081 | Face 2283 124 542 227 4082 | Face 2284 533 117 643 4083 | Face 2285 139 543 1577 4084 | Face 2286 530 318 1130 4085 | Face 2287 1720 720 1316 4086 | Face 2288 1649 1581 1144 4087 | Face 2289 1151 247 1142 4088 | Face 2290 511 103 1111 4089 | Face 2291 60 700 59 4090 | Face 2292 508 12 1273 4091 | Face 2293 121 547 1541 4092 | Face 2294 507 101 1107 4093 | Face 2295 163 625 964 4094 | Face 2296 1586 1585 1148 4095 | Face 2297 926 147 1149 4096 | Face 2298 1149 546 1551 4097 | Face 2299 505 103 1318 4098 | Face 2300 1150 128 99 4099 | Face 2301 545 551 1545 4100 | Face 2302 504 11 1335 4101 | Face 2303 503 119 1103 4102 | Face 2304 1152 145 1368 4103 | Face 2305 928 134 99 4104 | Face 2306 928 128 328 4105 | Face 2307 502 104 1102 4106 | Face 2308 201 701 1002 4107 | Face 2309 501 101 1438 4108 | Face 2310 555 125 167 4109 | Face 2311 1156 556 1408 4110 | Face 2312 516 14 127 4111 | Face 2313 1157 65 114 4112 | Face 2314 1157 130 1559 4113 | Face 2315 41 624 456 4114 | Face 2316 1322 232 1363 4115 | Face 2317 500 300 1455 4116 | Face 2318 309 238 1797 4117 | 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Face 3085 122 322 1141 4884 | Face 3086 87 886 1491 4885 | Face 3087 1675 1576 1769 4886 | Face 3088 1582 327 1544 4887 | Face 3089 1205 1108 1545 4888 | Face 3090 293 1761 514 4889 | Face 3091 512 323 1205 4890 | Face 3092 832 884 1518 4891 | Face 3093 124 324 1142 4892 | Face 3094 1394 595 1190 4893 | Face 3095 884 444 292 4894 | Face 3096 716 64 1393 4895 | Face 3097 89 325 1112 4896 | Face 3098 89 125 555 4897 | Face 3099 1550 325 89 4898 | Face 3100 1550 14 1512 4899 | Face 3101 1551 326 1149 4900 | Face 3102 97 844 93 4901 | Face 3103 1552 326 1590 4902 | Face 3104 1552 24 79 4903 | Face 3105 1138 1101 1386 4904 | Face 3106 1398 47 948 4905 | Face 3107 1246 724 1758 4906 | Face 3108 932 252 1403 4907 | Face 3109 1483 292 1481 4908 | Face 3110 328 128 947 4909 | Face 3111 453 78 1768 4910 | Face 3112 1402 24 1368 4911 | Face 3113 1402 1408 556 4912 | Face 3114 642 129 1163 4913 | Face 3115 1558 1120 642 4914 | Face 3116 1408 47 1156 4915 | Face 3117 310 291 1481 4916 | Face 3118 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876 4 1165 4950 | Face 3152 1614 1769 1576 4951 | Face 3153 307 1140 1577 4952 | Face 3154 332 288 1470 4953 | Face 3155 11 339 307 4954 | Face 3156 332 876 907 4955 | Face 3157 140 340 1177 4956 | Face 3158 334 94 23 4957 | Face 3159 334 875 351 4958 | Face 3160 1618 1684 1580 4959 | Face 3161 1529 1144 1581 4960 | Face 3162 347 288 1088 4961 | Face 3163 22 341 1529 4962 | Face 3164 347 875 1470 4963 | Face 3165 142 342 1181 4964 | Face 3166 1362 34 596 4965 | Face 3167 350 568 1088 4966 | Face 3168 1622 1626 1584 4967 | Face 3169 146 1148 1585 4968 | Face 3170 1565 18 333 4969 | Face 3171 552 343 146 4970 | Face 3172 351 94 334 4971 | Face 3173 144 344 1182 4972 | Face 3174 351 352 836 4973 | Face 3175 352 568 1436 4974 | Face 3176 1362 1190 1592 4975 | Face 3177 1368 345 1152 4976 | Face 3178 1368 145 595 4977 | Face 3179 1590 345 1368 4978 | Face 3180 1590 24 1552 4979 | Face 3181 1591 346 1189 4980 | Face 3182 3 305 370 4981 | Face 3183 1592 346 1630 4982 | Face 3184 1592 34 1362 4983 | Face 3185 765 1371 1765 4984 | Face 3186 1478 145 946 4985 | Face 3187 1478 1190 595 4986 | Face 3188 1195 769 1036 4987 | Face 3189 101 501 902 4988 | Face 3190 348 148 967 4989 | Face 3191 139 577 940 4990 | Face 3192 1538 16 1439 4991 | Face 3193 332 4 876 4992 | Face 3194 1238 149 1203 4993 | Face 3195 1598 1160 1238 4994 | Face 3196 332 1470 298 4995 | Face 3197 371 285 1086 4996 | Face 3198 371 1470 875 4997 | Face 3199 1367 765 1669 4998 | Face 3200 374 285 1432 4999 | Face 3201 243 785 1044 5000 | Face 3202 1677 726 1728 5001 | Face 3203 1446 1010 1029 5002 | Face 3204 2 868 427 5003 | Face 3205 427 903 389 5004 | Face 3206 905 407 390 5005 | Face 3207 1462 1465 391 5006 | Face 3208 1235 766 1371 5007 | Face 3209 1605 353 1168 5008 | Face 3210 1605 153 1211 5009 | Face 3211 1492 145 1152 5010 | Face 3212 353 28 1568 5011 | Face 3213 1471 1084 394 5012 | Face 3214 300 500 1497 5013 | Face 3215 1608 1607 373 5014 | Face 3216 1608 38 1198 5015 | Face 3217 1492 591 1448 5016 | Face 3218 674 390 407 5017 | Face 3219 576 355 1013 5018 | Face 3220 283 865 1084 5019 | Face 3221 1611 610 1154 5020 | Face 3222 1611 156 975 5021 | Face 3223 1 864 16 5022 | Face 3224 1650 977 1612 5023 | Face 3225 931 1176 1613 5024 | Face 3226 16 901 411 5025 | Face 3227 30 357 931 5026 | Face 3228 1482 430 412 5027 | Face 3229 951 248 1048 5028 | Face 3230 1498 1461 414 5029 | Face 3231 389 871 427 5030 | Face 3232 1654 1053 1616 5031 | Face 3233 1600 1180 1617 5032 | Face 3234 1467 1082 429 5033 | Face 3235 21 359 1600 5034 | Face 3236 714 412 430 5035 | Face 3237 160 360 1217 5036 | Face 3238 281 861 1082 5037 | Face 3239 100 860 472 5038 | Face 3240 1658 952 1620 5039 | Face 3241 826 1184 1621 5040 | Face 3242 472 1099 434 5041 | Face 3243 32 361 826 5042 | Face 3244 1085 452 447 5043 | Face 3245 162 362 1221 5044 | Face 3246 1454 1457 449 5045 | Face 3247 717 924 450 5046 | Face 3248 1662 879 1624 5047 | Face 3249 1434 1188 1625 5048 | Face 3250 1423 1080 451 5049 | Face 3251 592 363 1434 5050 | Face 3252 754 447 452 5051 | Face 3253 1235 1371 765 5052 | Face 3254 279 857 1080 5053 | Face 3255 91 499 412 5054 | Face 3256 1764 210 1317 5055 | Face 3257 735 365 1192 5056 | Face 3258 735 165 635 5057 | Face 3259 1630 365 735 5058 | Face 3260 1630 34 1592 5059 | Face 3261 366 1229 626 5060 | Face 3262 1233 766 1768 5061 | Face 3263 1632 366 1670 5062 | Face 3264 1632 44 723 5063 | Face 3265 412 1460 1482 5064 | Face 3266 32 588 1626 5065 | Face 3267 1534 45 1485 5066 | Face 3268 954 250 1397 5067 | Face 3269 1391 1044 1014 5068 | Face 3270 368 168 987 5069 | Face 3271 170 368 1674 5070 | Face 3272 434 1025 472 5071 | Face 3273 1459 1078 474 5072 | Face 3274 641 169 1243 5073 | Face 3275 1638 1200 641 5074 | Face 3276 1626 963 1516 5075 | Face 3277 277 853 1078 5076 | Face 3278 490 98 67 5077 | Face 3279 490 852 527 5078 | Face 3280 527 276 846 5079 | Face 3281 527 852 1095 5080 | Face 3282 603 171 645 5081 | Face 3283 1713 1669 433 5082 | Face 3284 1330 88 473 5083 | Face 3285 1330 1451 510 5084 | Face 3286 491 276 1449 5085 | Face 3287 491 1451 846 5086 | Face 3288 1276 680 190 5087 | Face 3289 1645 373 1208 5088 | Face 3290 1645 173 1251 5089 | Face 3291 1233 78 1155 5090 | Face 3292 373 38 1608 5091 | Face 3293 471 1076 494 5092 | Face 3294 1647 174 993 5093 | Face 3295 1648 1647 393 5094 | Face 3296 1648 48 611 5095 | Face 3297 1581 1569 1529 5096 | Face 3298 510 88 1330 5097 | Face 3299 39 375 519 5098 | Face 3300 510 849 834 5099 | Face 3301 1651 650 593 5100 | Face 3302 1651 176 995 5101 | Face 3303 513 849 1076 5102 | Face 3304 1690 997 1652 5103 | Face 3305 416 1216 1653 5104 | Face 3306 514 77 1487 5105 | Face 3307 40 377 416 5106 | Face 3308 557 1285 842 5107 | Face 3309 1034 1380 1748 5108 | Face 3310 557 514 493 5109 | Face 3311 1065 808 1788 5110 | Face 3312 1694 523 1656 5111 | Face 3313 874 1220 1657 5112 | Face 3314 720 1719 210 5113 | Face 3315 31 379 874 5114 | Face 3316 1445 1447 842 5115 | Face 3317 180 380 1257 5116 | Face 3318 527 98 490 5117 | Face 3319 527 846 1253 5118 | Face 3320 1698 456 1660 5119 | Face 3321 194 1224 1661 5120 | Face 3322 528 1451 845 5121 | Face 3323 42 381 194 5122 | Face 3324 528 846 1451 5123 | Face 3325 182 382 1261 5124 | Face 3326 1447 845 870 5125 | Face 3327 845 1451 1330 5126 | Face 3328 1702 349 1664 5127 | Face 3329 1433 1404 517 5128 | Face 3330 1365 1367 762 5129 | Face 3331 632 383 106 5130 | Face 3332 213 1529 1569 5131 | Face 3333 184 384 1265 5132 | Face 3334 844 1410 272 5133 | Face 3335 553 804 1682 5134 | Face 3336 517 271 1447 5135 | Face 3337 1232 27 19 5136 | Face 3338 27 185 675 5137 | Face 3339 19 385 1232 5138 | Face 3340 1670 44 1632 5139 | Face 3341 386 1269 186 5140 | Face 3342 1717 211 1284 5141 | Face 3343 1672 386 1710 5142 | Face 3344 1672 54 126 5143 | Face 3345 890 498 1493 5144 | Face 3346 950 795 969 5145 | Face 3347 1443 272 1441 5146 | Face 3348 1674 640 170 5147 | Face 3349 1715 722 1327 5148 | Face 3350 388 188 1007 5149 | Face 3351 1709 1721 313 5150 | Face 3352 557 77 514 5151 | Face 3353 557 842 1490 5152 | Face 3354 1114 189 1283 5153 | Face 3355 1678 1240 1114 5154 | Face 3356 561 271 1441 5155 | Face 3357 561 842 1447 5156 | Face 3358 31 584 952 5157 | Face 3359 567 271 1404 5158 | Face 3360 1715 211 1321 5159 | Face 3361 952 961 1596 5160 | Face 3362 1288 191 709 5161 | Face 3363 993 1244 191 5162 | Face 3364 840 1665 270 5163 | Face 3365 1396 800 118 5164 | Face 3366 799 572 955 5165 | Face 3367 630 270 1437 5166 | Face 3368 1722 1673 719 5167 | Face 3369 1685 393 1248 5168 | Face 3370 1685 1287 1291 5169 | Face 3371 1713 722 1762 5170 | Face 3372 393 48 1648 5171 | Face 3373 844 272 93 5172 | Face 3374 1617 1636 1600 5173 | Face 3375 1688 1687 413 5174 | Face 3376 1688 58 1234 5175 | Face 3377 509 1252 695 5176 | Face 3378 594 269 1437 5177 | Face 3379 656 395 509 5178 | Face 3380 594 272 1443 5179 | Face 3381 1691 690 13 5180 | Face 3382 1691 196 1015 5181 | Face 3383 914 800 1396 5182 | Face 3384 1730 1017 1692 5183 | Face 3385 1012 1256 1693 5184 | Face 3386 597 269 1400 5185 | Face 3387 50 397 1012 5186 | Face 3388 836 94 351 5187 | Face 3389 690 398 1293 5188 | Face 3390 601 268 1430 5189 | Face 3391 601 836 1087 5190 | Face 3392 1734 59 1696 5191 | Face 3393 329 1260 1697 5192 | Face 3394 607 84 29 5193 | Face 3395 41 399 329 5194 | Face 3396 607 835 633 5195 | Face 3397 200 400 1297 5196 | Face 3398 608 268 1068 5197 | Face 3399 608 835 1430 5198 | Face 3400 1738 896 1700 5199 | Face 3401 115 1264 1701 5200 | Face 3402 1218 1181 1609 5201 | Face 3403 52 401 115 5202 | Face 3404 630 914 1068 5203 | Face 3405 202 402 1301 5204 | Face 3406 100 497 7 5205 | Face 3407 633 84 607 5206 | Face 3408 1742 73 1704 5207 | Face 3409 96 1268 1705 5208 | Face 3410 633 634 796 5209 | Face 3411 53 403 96 5210 | Face 3412 634 914 1396 5211 | Face 3413 204 404 1305 5212 | Face 3414 1382 1385 1011 5213 | Face 3415 1713 1202 1669 5214 | Face 3416 1781 1029 1010 5215 | Face 3417 1757 405 1272 5216 | Face 3418 1757 205 715 5217 | Face 3419 1710 405 1757 5218 | Face 3420 1710 54 1672 5219 | Face 3421 406 1309 206 5220 | Face 3422 799 136 566 5221 | Face 3423 1712 406 1750 5222 | Face 3424 1712 64 1755 5223 | Face 3425 7 1456 1556 5224 | Face 3426 1516 1584 1626 5225 | Face 3427 1530 917 1572 5226 | Face 3428 1634 1364 873 5227 | Face 3429 601 94 836 5228 | Face 3430 408 208 1027 5229 | Face 3431 210 408 1754 5230 | Face 3432 601 1430 138 5231 | Face 3433 651 265 1066 5232 | Face 3434 1686 209 1323 5233 | Face 3435 1718 1280 1686 5234 | Face 3436 651 1430 835 5235 | Face 3437 1275 1199 453 5236 | Face 3438 673 265 1392 5237 | Face 3439 1050 1063 1009 5238 | Face 3440 92 828 728 5239 | Face 3441 728 1083 677 5240 | Face 3442 1673 211 1327 5241 | Face 3443 1722 1284 1673 5242 | Face 3444 1185 710 681 5243 | Face 3445 1422 1425 687 5244 | Face 3446 1187 942 1628 5245 | Face 3447 873 251 1407 5246 | Face 3448 1762 1202 1713 5247 | Face 3449 1323 212 1321 5248 | Face 3450 1597 296 915 5249 | Face 3451 994 681 710 5250 | Face 3452 413 58 1688 5251 | Face 3453 263 825 1064 5252 | Face 3454 287 1600 1636 5253 | Face 3455 1728 1727 433 5254 | Face 3456 1728 68 1677 5255 | Face 3457 1296 1292 1633 5256 | Face 3458 91 824 450 5257 | Face 3459 696 415 1296 5258 | Face 3460 450 1081 717 5259 | Face 3461 1731 730 1641 5260 | Face 3462 1731 216 1035 5261 | Face 3463 1005 750 721 5262 | Face 3464 1770 1037 1732 5263 | Face 3465 1560 1296 1733 5264 | Face 3466 1458 1421 727 5265 | Face 3467 60 417 1560 5266 | Face 3468 677 958 728 5267 | Face 3469 730 418 1333 5268 | Face 3470 1427 1062 731 5269 | Face 3471 1031 721 750 5270 | Face 3472 1774 1604 1736 5271 | Face 3473 238 1300 1737 5272 | Face 3474 261 821 1062 5273 | Face 3475 51 419 238 5274 | Face 3476 90 820 808 5275 | Face 3477 220 420 1337 5276 | Face 3478 808 1079 757 5277 | Face 3479 424 790 761 5278 | Face 3480 1778 1564 1740 5279 | Face 3481 1475 1304 1741 5280 | Face 3482 1414 1417 767 5281 | Face 3483 62 421 1475 5282 | Face 3484 1032 1228 768 5283 | Face 3485 222 422 1341 5284 | Face 3486 1383 1060 771 5285 | Face 3487 1069 761 790 5286 | Face 3488 1782 1524 1744 5287 | Face 3489 1793 1308 1745 5288 | Face 3490 259 817 1060 5289 | Face 3491 1746 423 1793 5290 | Face 3492 1597 890 66 5291 | Face 3493 1677 68 1635 5292 | Face 3494 1275 1767 762 5293 | Face 3495 1686 684 1718 5294 | Face 3496 82 788 1050 5295 | Face 3497 1355 425 1312 5296 | Face 3498 1355 225 755 5297 | Face 3499 35 425 1355 5298 | Face 3500 1750 64 1712 5299 | Face 3501 426 1349 226 5300 | Face 3502 992 245 1352 5301 | Face 3503 1752 426 1790 5302 | Face 3504 1752 74 1353 5303 | Face 3505 856 495 467 5304 | Face 3506 141 581 942 5305 | Face 3507 757 1788 808 5306 | Face 3508 1754 720 210 5307 | Face 3509 1419 1058 811 5308 | Face 3510 428 228 1047 5309 | Face 3511 230 428 1794 5310 | Face 3512 724 1723 212 5311 | Face 3513 257 813 1058 5312 | Face 3514 1246 229 1363 5313 | Face 3515 1758 1320 1246 5314 | Face 3516 834 88 510 5315 | Face 3517 834 812 877 5316 | Face 3518 877 256 806 5317 | Face 3519 877 812 1075 5318 | Face 3520 1594 78 453 5319 | Face 3521 1594 1411 848 5320 | Face 3522 1202 231 1367 5321 | Face 3523 1762 1324 1202 5322 | Face 3524 837 256 1409 5323 | Face 3525 837 1411 806 5324 | Face 3526 1199 873 1407 5325 | Face 3527 807 1056 847 5326 | Face 3528 1634 873 1275 5327 | Face 3529 30 580 1769 5328 | Face 3530 467 1452 55 5329 | Face 3531 848 78 1594 5330 | Face 3532 433 68 1728 5331 | Face 3533 848 809 1155 5332 | Face 3534 1769 959 1675 5333 | Face 3535 1768 1767 453 5334 | Face 3536 1768 78 1233 5335 | Face 3537 1595 1332 1153 5336 | Face 3538 851 809 1056 5337 | Face 3539 736 435 1595 5338 | Face 3540 870 517 1447 5339 | Face 3541 1771 770 1166 5340 | Face 3542 1771 236 1055 5341 | Face 3543 910 841 802 5342 | Face 3544 483 1057 1772 5343 | Face 3545 1071 1336 1773 5344 | Face 3546 910 870 473 5345 | Face 3547 70 437 1071 5346 | Face 3548 1573 1716 1676 5347 | Face 3549 770 438 1373 5348 | Face 3550 1174 1177 1681 5349 | Face 3551 1405 1407 802 5350 | Face 3552 733 1119 1776 5351 | Face 3553 1520 1340 1777 5352 | Face 3554 877 88 834 5353 | Face 3555 61 439 1520 5354 | Face 3556 877 806 752 5355 | Face 3557 240 440 1377 5356 | Face 3558 881 1411 805 5357 | Face 3559 881 806 1411 5358 | Face 3560 1506 1074 1780 5359 | Face 3561 1010 1344 1781 5360 | Face 3562 1407 805 1199 5361 | Face 3563 72 441 1010 5362 | Face 3564 805 1411 1594 5363 | Face 3565 242 442 1381 5364 | Face 3566 725 1331 1725 5365 | Face 3567 1327 725 1328 5366 | Face 3568 1145 1050 1784 5367 | Face 3569 1399 1348 1785 5368 | Face 3570 804 1431 252 5369 | Face 3571 1786 748 1399 5370 | Face 3572 891 764 1798 5371 | Face 3573 1356 760 1794 5372 | Face 3574 294 1580 1684 5373 | Face 3575 1403 252 1401 5374 | Face 3576 1682 1400 553 5375 | Face 3577 1352 950 33 5376 | Face 3578 950 245 795 5377 | Face 3579 33 445 1352 5378 | Face 3580 1790 74 1752 5379 | Face 3581 446 1389 246 5380 | Face 3582 1143 940 1689 5381 | Face 3583 1792 446 158 5382 | Face 3584 1792 84 949 5383 | Face 3585 1709 8 86 5384 | Face 3586 1680 726 1331 5385 | Face 3587 910 517 870 5386 | Face 3588 1794 760 230 5387 | Face 3589 910 802 1433 5388 | Face 3590 448 248 1067 5389 | Face 3591 250 448 118 5390 | Face 3592 911 251 1401 5391 | Face 3593 911 802 1407 5392 | Face 3594 891 249 1403 5393 | Face 3595 1798 1360 891 5394 | Face 3596 469 1676 1716 5395 | -------------------------------------------------------------------------------- /data/torus.mat: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/ccgeom/ccg-notes/6fade9e0ebbbe747d0f07457aa8047470d15ca1b/data/torus.mat -------------------------------------------------------------------------------- /data/torus.vtk: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/ccgeom/ccg-notes/6fade9e0ebbbe747d0f07457aa8047470d15ca1b/data/torus.vtk -------------------------------------------------------------------------------- /hello: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env bash 2 | 3 | CLR_NOR="\x1b[0m" # back to NORMAL 4 | CLR_BOLD="\x1b[1m" # BOLD text 5 | CLR_RED="\x1b[31m" # RED text 6 | CLR_GRN="\x1b[32m" # GREEN text 7 | CLR_YLW="\x1b[33m" # YELLOW text 8 | 9 | export PRJ_HOME=`pwd` 10 | 11 | echo -e "${CLR_YLW}Checking Python version......${CLR_NOR}" 12 | PYV=`python -c "import sys;t='{v[0]}.{v[1]}'.format(v=list(sys.version_info[:2]));sys.stdout.write(t)";` 13 | if [[ $PYV == 2.7 ]] 14 | then 15 | PY=python3; 16 | PIP=pip3; 17 | PIP_INST="pip3 install -i https://pypi.douban.com/simple/"; 18 | NTB="ipython3 notebook"; 19 | TEST="nosetests" 20 | fi 21 | if [[ $PYV == 3* ]] 22 | then 23 | PY=python; 24 | PIP=pip; 25 | PIP_INST="pip install"; 26 | NTB="jupyter notebook"; 27 | TEST="nosetests" 28 | fi 29 | if (eval "${PY} -V"); then 30 | echo -e "${CLR_YLW}Python version checked......${CLR_NOR}${CLR_GRN}OK${CLR_NOR}" 31 | else 32 | echo -e "${CLR_YLW}Python version checked......${CLR_NOR}${CLR_RED}Failed${CLR_NOR}" 33 | exit -1 34 | fi 35 | 36 | echo -e "${CLR_YLW}Setting Python path to user local......${CLR_NOR}${CLR_GRN}Done${CLR_NOR}" 37 | export PYTHONPATH=$PRJ_HOME/.py/lib/$PY/site-packages/:$PRJ_HOME/src:$PRJ_HOME/test 38 | 39 | if (eval "$PY -c 'import virtualenv as venv'"); then 40 | echo -e "${CLR_YLW}Checking virtualenv......${CLR_NOR}${CLR_GRN}OK${CLR_NOR}" 41 | else 42 | echo -e "${CLR_YLW}Checking virtualenv......${CLR_NOR}${CLR_RED}Failed${CLR_NOR}" 43 | echo -e "${CLR_YLW}Reinstalling virtualenv......${CLR_NOR}" 44 | eval "${PIP} uninstall virtualenv" 45 | eval "${PIP_INST} virtualenv" 46 | echo -e "${CLR_YLW}Reinstalling virtualenv......${CLR_NOR}${CLR_GRN}Done${CLR_NOR}" 47 | fi 48 | 49 | if (eval "${PY} bin/env.py"); then 50 | source .py/bin/activate 51 | 52 | echo -e "${CLR_YLW}Installing numpy......${CLR_NOR}" 53 | eval "${PIP_INST} numpy" 54 | echo -e "${CLR_YLW}Installing numpy......${CLR_NOR}${CLR_GRN}OK${CLR_NOR}" 55 | 56 | echo -e "${CLR_YLW}Installing scipy......${CLR_NOR}" 57 | eval "${PIP_INST} scipy" 58 | echo -e "${CLR_YLW}Installing scipy......${CLR_NOR}${CLR_GRN}OK${CLR_NOR}" 59 | 60 | echo -e "${CLR_YLW}Installing Pillow......${CLR_NOR}" 61 | eval "${PIP_INST} Pillow" 62 | echo -e "${CLR_YLW}Installing Pillow......${CLR_NOR}${CLR_GRN}OK${CLR_NOR}" 63 | 64 | echo -e "${CLR_YLW}Installing matplotlib......${CLR_NOR}" 65 | eval "${PIP_INST} matplotlib" 66 | echo -e "${CLR_YLW}Installing matplotlib......${CLR_NOR}${CLR_GRN}OK${CLR_NOR}" 67 | 68 | echo -e "${CLR_YLW}Installing pyzmq......${CLR_NOR}" 69 | eval "${PIP_INST} pyzmq" 70 | echo -e "${CLR_YLW}Installing pyzmq......${CLR_NOR}${CLR_GRN}OK${CLR_NOR}" 71 | 72 | echo -e "${CLR_YLW}Installing jinja2......${CLR_NOR}" 73 | eval "${PIP_INST} jinja2" 74 | echo -e "${CLR_YLW}Installing jinja2......${CLR_NOR}${CLR_GRN}OK${CLR_NOR}" 75 | 76 | echo -e "${CLR_YLW}Installing tornado......${CLR_NOR}" 77 | eval "${PIP_INST} tornado" 78 | echo -e "${CLR_YLW}Installing tornado......${CLR_NOR}${CLR_GRN}OK${CLR_NOR}" 79 | 80 | echo -e "${CLR_YLW}Installing jsonschema......${CLR_NOR}" 81 | eval "${PIP_INST} jsonschema" 82 | echo -e "${CLR_YLW}Installing jsonschema......${CLR_NOR}${CLR_GRN}OK${CLR_NOR}" 83 | 84 | echo -e "${CLR_YLW}Installing terminado......${CLR_NOR}" 85 | eval "${PIP_INST} terminado" 86 | echo -e "${CLR_YLW}Installing terminado......${CLR_NOR}${CLR_GRN}OK${CLR_NOR}" 87 | 88 | echo -e "${CLR_YLW}Installing ipython......${CLR_NOR}" 89 | eval "${PIP_INST} ipython" 90 | echo -e "${CLR_YLW}Installing ipython......${CLR_NOR}${CLR_GRN}OK${CLR_NOR}" 91 | 92 | echo -e "${CLR_YLW}Installing nose......${CLR_NOR}" 93 | eval "${PIP_INST} nose" 94 | echo -e "${CLR_YLW}Installing nose......${CLR_NOR}${CLR_GRN}OK${CLR_NOR}" 95 | 96 | echo -e "${CLR_YLW}Installing jupyter......${CLR_NOR}" 97 | eval "${PIP_INST} jupyter" 98 | echo -e "${CLR_YLW}Installing jupyter......${CLR_NOR}${CLR_GRN}OK${CLR_NOR}" 99 | 100 | echo -e "${CLR_YLW}Installing dependencies......${CLR_NOR}" 101 | eval "${PIP_INST} -r requirements.txt" 102 | echo -e "${CLR_YLW}Installing dependencies......${CLR_NOR}${CLR_GRN}OK${CLR_NOR}" 103 | 104 | eval "${PIP_INST} -r requirements.txt" 105 | 106 | if [[ $PRJ_ENV ]] 107 | then 108 | echo -e "${CLR_YLW}Current environment: ${CLR_NOR}${CLR_RED}$PRJ_ENV${CLR_NOR}" 109 | else 110 | export PRJ_ENV="dev" 111 | echo -e "${CLR_YLW}Current environment: ${CLR_NOR}${CLR_RED}$PRJ_ENV${CLR_NOR}" 112 | fi 113 | 114 | export PATH="$PATH:${PRJ_HOME}/bin/" 115 | fi 116 | 117 | -------------------------------------------------------------------------------- /requirements.txt: -------------------------------------------------------------------------------- 1 | pyvista # 3D visualization toolkit 2 | panel 3 | alive-progress 4 | -------------------------------------------------------------------------------- /scripts/m2mat.py: -------------------------------------------------------------------------------- 1 | from glob import glob 2 | from tools.converter import m2mat 3 | 4 | if __name__ == '__main__': 5 | for mfile in glob('data/*.m'): 6 | matfile = mfile.replace('.m', '.mat') 7 | m2mat(mfile, matfile) 8 | print(mfile, '->', matfile) 9 | print('finished') 10 | -------------------------------------------------------------------------------- /scripts/m2vtk.py: -------------------------------------------------------------------------------- 1 | from glob import glob 2 | from tools.converter import m2vtk 3 | 4 | if __name__ == '__main__': 5 | for mfile in glob('data/*.m'): 6 | vfile = mfile.replace('.m', '.vtk') 7 | m2vtk(mfile, vfile) 8 | print(mfile, '->', vfile) 9 | print('finished') 10 | -------------------------------------------------------------------------------- /scripts/mat2vtk.py: -------------------------------------------------------------------------------- 1 | from glob import glob 2 | from tools.converter import mat2vtk 3 | 4 | if __name__ == '__main__': 5 | for mfile in glob('data/*.mat'): 6 | vfile = mfile.replace('.mat', '.vtk') 7 | mat2vtk(mfile, vfile) 8 | print(mfile, '->', vfile) 9 | print('finished') 10 | -------------------------------------------------------------------------------- /src/ccgeom/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/ccgeom/ccg-notes/6fade9e0ebbbe747d0f07457aa8047470d15ca1b/src/ccgeom/__init__.py -------------------------------------------------------------------------------- /src/ccgeom/manifold.py: -------------------------------------------------------------------------------- 1 | 2 | import numpy as np 3 | 4 | # following the idea of halfedge data structure on David Gu's lecture 5 | # https://www3.cs.stonybrook.edu/~gu/lectures/lecture_8_halfedge_data_structure.pdf 6 | # and adapt it to a numpy friendly representatives 7 | # * vertexes: all position of each vertex 8 | # * faces: all position of each centroid of faces 9 | # * edges: all position of each centroid of edges 10 | # * halfedges: all vectors of each halfedge 11 | # * vertexes2vertexes 12 | 13 | 14 | class Manifold: 15 | def __init__(self, vtk_mesh=None): 16 | if vtk_mesh != None: 17 | self.mesh = vtk_mesh # a VTK mesh structure 18 | 19 | self.n_vertexes = vtk_mesh.n_points 20 | self.n_faces = vtk_mesh.n_cells 21 | 22 | cells = np.array(self.mesh.cells).copy() 23 | self.vertexes = np.array(self.mesh.points).copy() 24 | self.faces, cells_begin, cells_end = make_dual(self.n_faces, self.vertexes, cells) 25 | self.edges, self.halfedges = make_edges(self.n_faces, self.vertexes, cells, cells_begin, cells_end) 26 | self.n_edges = self.edges.shape[0] 27 | self.n_halfedges = self.halfedges.shape[0] 28 | 29 | self.adjacency_vertexes = None 30 | self.adjacency_faces = None 31 | self.adjacency_edges = None 32 | self.adjacency_halfedges = None 33 | 34 | self.adjacency_vertexes2faces = None 35 | self.adjacency_vertexes2edges = None 36 | self.adjacency_vertexes2halfedges = None 37 | 38 | self.adjacency_faces2vertexes = None 39 | self.adjacency_faces2edges = None 40 | self.adjacency_faces2halfedges = None 41 | 42 | self.adjacency_edges2vertexes = None 43 | self.adjacency_edges2faces = None 44 | self.adjacency_edges2halfedges = None 45 | 46 | self.adjacency_halfedges2vertexes = None 47 | self.adjacency_halfedges2faces = None 48 | self.adjacency_halfedges2edges = None 49 | 50 | self.orientation = None 51 | 52 | def __getstate__(self): 53 | state = self.__dict__.copy() 54 | del state["mesh"] 55 | return state 56 | 57 | def __setstate__(self, state): 58 | self.__dict__.update(state) 59 | self.mesh = None 60 | 61 | 62 | def make_dual(n_faces, points, faces): 63 | ix, cur = 0, 0 64 | centroid = [] 65 | faces_begin = [] 66 | faces_end = [] 67 | while ix < n_faces: 68 | sz = faces[cur] 69 | assert sz > 2 70 | ps = points[faces[cur + 1:cur + sz]] 71 | assert ps.shape[1] == sz 72 | centroid.append(np.mean(ps, axis=0)) 73 | faces_begin.append(cur + 1) 74 | faces_end.append(cur + sz) 75 | cur = cur + sz + 1 76 | ix += 1 77 | assert cur == faces.shape[0] 78 | return np.array(centroid), np.array(faces_begin), np.array(faces_end) 79 | 80 | 81 | def make_edges(n_faces, vertexes, cells, cells_begin, cells_end): 82 | total = 0 83 | for ix in range(n_faces): 84 | begin, end = cells_begin[ix], cells_end[ix] 85 | sz = end - begin + 1 86 | total += sz 87 | 88 | cur = 0 89 | edges = np.array([total, 3], dtype=np.float64) 90 | halfedges = np.array([2 * total, 3], dtype=np.float64) 91 | for ix in range(n_faces): 92 | begin, end = cells_begin[ix], cells_end[ix] 93 | sz = end - begin + 1 94 | pxs = vertexes[cells[begin:end]] 95 | for p in range(sz): 96 | src, tgt = pxs[p - 1], pxs[p] 97 | edges[cur] = (src + tgt) / 2 98 | halfedges[2 * cur] = tgt - src 99 | halfedges[2 * cur + 1] = src - tgt 100 | cur += 1 101 | 102 | return edges, halfedges -------------------------------------------------------------------------------- /src/demo/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/ccgeom/ccg-notes/6fade9e0ebbbe747d0f07457aa8047470d15ca1b/src/demo/__init__.py -------------------------------------------------------------------------------- /src/demo/wildfire.py: -------------------------------------------------------------------------------- 1 | import numpy as np 2 | import pyvista as pv 3 | 4 | from scipy.spatial.distance import cdist 5 | from alive_progress import alive_bar 6 | 7 | 8 | # 在下同调的语言里，引入一个差分算子 \delta = x_i - x_{i-1}，用来刻画演化问题。 9 | # 在火烧法里，引入记号 f 表示火头线， B 表示火体面，t 表示火尾线. 10 | # f_i = \delta \partial \delta^+ B_i, f_0 = 0 11 | # t_i = \delta \partial \delta^- B_i, t_0 = 0 12 | # \delta^+ B_i 表示进入火体的面 13 | # \delta^- B_i 表示离开火体的面 14 | 15 | 16 | class Manifold: 17 | def __init__(self, mesh=None): 18 | if mesh != None: 19 | self.mesh = mesh 20 | self.n_points = mesh.n_points 21 | self.n_faces = mesh.n_cells 22 | self.center = mesh.center 23 | self.area = mesh.area 24 | self.volume = mesh.volume 25 | self.bounds = mesh.bounds 26 | 27 | print('copy points...') 28 | self.points = np.array(mesh.points).copy() 29 | 30 | print('constructing faces...') 31 | self.faces = np.array(mesh.faces).copy() 32 | self.face_normals = np.array(mesh.face_normals).copy() 33 | self.faces_centroid, self.faces_begin, self.faces_end = self.build_faces(self.points, self.faces, self.n_faces) 34 | 35 | print('indexing point2faces...') 36 | self.point2faces = self.index_point2faces(self.faces, self.n_faces, self.n_points) 37 | 38 | print('build neighbor index...') 39 | with alive_bar(3) as bar: 40 | self.neighbor_points = self.build_neighbors(self.points, self.n_points, self.points, self.n_points, 0.05) 41 | bar() 42 | self.neighbor_faces = self.build_neighbors(self.faces_centroid, self.n_faces, self.faces_centroid, self.n_faces, 0.05) 43 | bar() 44 | self.neighbor_point2face = self.build_neighbors(self.points, self.n_points, self.faces_centroid, self.n_faces, 0.05) 45 | bar() 46 | 47 | #print('sort orientation...') 48 | #self.sort_orientation() 49 | 50 | def __getstate__(self): 51 | state = self.__dict__.copy() 52 | del state["mesh"] 53 | return state 54 | 55 | def __setstate__(self, state): 56 | self.__dict__.update(state) 57 | self.mesh = None 58 | 59 | def edges(self, face): 60 | begin = self.faces_begin[face] 61 | end = self.faces_end[face] 62 | return self.faces[begin:end+1] 63 | 64 | def index_point2faces(self, faces, n_faces, n_points): 65 | ix, cur = 0, 0 66 | point2faces = [[] for _ in range(n_points)] 67 | 68 | with alive_bar(n_faces) as bar: 69 | while ix < n_faces: 70 | sz = faces[cur] 71 | assert sz > 2 72 | for p in faces[cur + 1:cur + sz]: 73 | point2faces[p].append(ix) 74 | cur = cur + sz + 1 75 | ix += 1 76 | bar() 77 | assert cur == faces.shape[0] 78 | return point2faces 79 | 80 | def build_faces(self, points, faces, n_faces): 81 | ix, cur = 0, 0 82 | centroid = [] 83 | faces_begin = [] 84 | faces_end = [] 85 | with alive_bar(n_faces) as bar: 86 | while ix < n_faces: 87 | sz = faces[cur] 88 | assert sz > 2 89 | ps = points[faces[cur + 1:cur + sz]] 90 | assert ps.shape[1] == sz 91 | centroid.append(np.mean(ps, axis=0)) 92 | faces_begin.append(cur + 1) 93 | faces_end.append(cur + sz) 94 | assert np.max(faces[cur + 1:cur + sz]) < self.n_points 95 | cur = cur + sz + 1 96 | ix += 1 97 | bar() 98 | assert cur == faces.shape[0] 99 | return np.array(centroid, dtype=np.float32), np.array(faces_begin, dtype=np.int64), np.array(faces_end, dtype=np.int64) 100 | 101 | def build_neighbors(self, points1, n_points1, points2, n_points2, thrshold): 102 | dmatrix = cdist(points1, points2, metric='euclidean') 103 | neighbors = [[] for _ in range(n_points1)] 104 | flag = len(points1) != len(points2) or (points1 != points2).any() 105 | for i in range(n_points1): 106 | for j in range(n_points2): 107 | d = dmatrix[i, j] 108 | if d < thrshold: 109 | if flag: 110 | neighbors[i].append(j) 111 | else: 112 | if i != j: 113 | neighbors[i].append(j) 114 | return neighbors 115 | 116 | def sort_orientation(self): 117 | checker = EvolvingBoundary(self) 118 | checked = set() 119 | candidate = set([0]) 120 | flips = np.zeros(self.n_faces, dtype=np.int8) 121 | with alive_bar(self.n_faces) as bar: 122 | while len(checked) < self.n_faces: 123 | while len(candidate) > 0: 124 | face = candidate.pop() 125 | try: 126 | ps = self.edges(face) 127 | checker.begin() 128 | checker.insert(ps) 129 | checker.commit() 130 | checked.add(face) 131 | bar() 132 | except AssertionError: 133 | begin, end = self.faces_begin[face], self.faces_end[face] + 1 134 | reversed(self.faces[begin:end]) 135 | flips[face] += 1 136 | for p in ps: 137 | fs = self.point2faces[p] 138 | for f in fs: 139 | if f not in checked: 140 | candidate.add(f) 141 | 142 | print(checker.cycles) 143 | return np.sum(flips) 144 | 145 | 146 | class EvolvingBoundary: 147 | def __init__(self, manifold): 148 | self.manifold = manifold 149 | self.cycles = [] 150 | self.working_area = {} 151 | 152 | def begin(self): 153 | self.working_area.clear() 154 | for c in self.cycles: 155 | r = c[::-1] 156 | l = len(r) 157 | for ix in range(l): 158 | a = r[ix - 1] 159 | b = r[ix] 160 | if a < b: 161 | key, sgn = (a, b), 1 162 | if a > b: 163 | key, sgn = (b, a), -1 164 | if key not in self.working_area: 165 | self.working_area[key] = 0 166 | self.working_area[key] = self.working_area[key] + sgn 167 | 168 | def commit(self): 169 | next = {} 170 | for (a, b), val in self.working_area.items(): 171 | if val > 0: 172 | #assert val == 1 173 | next[a] = b 174 | if val < 0: 175 | #assert val == -1 176 | next[b] = a 177 | paths = [] 178 | while len(next) > 0: 179 | path = [] 180 | key = next.keys().__iter__().__next__() 181 | while key in next: 182 | path.append(key) 183 | temp = next[key] 184 | next.pop(key) 185 | key = temp 186 | paths.append(np.array(path, dtype=np.int64)) 187 | self.cycles = paths 188 | self.working_area.clear() 189 | 190 | def insert(self, edges): 191 | sz = len(edges) 192 | assert sz > 2 193 | for ix in range(sz): 194 | a = edges[ix] 195 | b = edges[(ix + 1) % sz] 196 | if a < b: 197 | key, sgn = (a, b), 1 198 | if a > b: 199 | key, sgn = (b, a), -1 200 | 201 | if key not in self.working_area: 202 | self.working_area[key] = 0 203 | val = self.working_area[key] + sgn 204 | #assert np.abs(val) < 2.0 205 | if val == 0: 206 | self.working_area.pop(key) 207 | else: 208 | self.working_area[key] = val 209 | 210 | 211 | class FireFront(EvolvingBoundary): 212 | def __init__(self, manifold, start_face): 213 | super().__init__(manifold) 214 | self.begin() 215 | self.insert(self.manifold.edges(start_face)) 216 | self.commit() 217 | 218 | 219 | class FireTail(EvolvingBoundary): 220 | def __init__(self, manifold): 221 | super().__init__(manifold) 222 | 223 | 224 | class FireBulk: 225 | name = 'firebulk' 226 | 227 | def __init__(self, manifold, start_face): 228 | self.manifold = manifold 229 | self.bulk = set() 230 | self.listeners = [] 231 | 232 | self.values = np.ones([manifold.mesh.n_cells]) * 0.7 # 绿色的森林 233 | self.values[0] = 0.0 # 强制把色阶拉回去的 workaround 234 | self.values[1] = 1.0 # 强制把色阶拉回去的 workaround 235 | self.values[start_face] = 1.0 # 初始着火处 236 | manifold.mesh.cell_data[self.name] = self.values 237 | 238 | def add_vanish_listener(self, lstnr): 239 | self.listeners.append(lstnr) 240 | 241 | def on_vanish(self, face): 242 | for lstnr in self.listeners: 243 | lstnr.on_firebulk_vanished(face) 244 | 245 | def add(self, face): 246 | self.values[face] = 1.0 247 | self.bulk.add(face) 248 | 249 | def minus(self, face): 250 | self.bulk.remove(face) 251 | self.on_vanish(face) 252 | 253 | def contains(self, face): 254 | return face in self.bulk 255 | 256 | def step(self): 257 | for face in self.bulk.copy(): 258 | val = self.values[face] 259 | if val * 0.9 < 0.7: 260 | self.values[face] = 0.5 261 | self.minus(face) 262 | else: 263 | self.values[face] = val * 0.9 264 | self.values[0] = 0.0 # 强制把色阶拉回去的 workaround 265 | self.values[1] = 1.0 # 强制把色阶拉回去的 workaround 266 | 267 | 268 | class CutLocus: 269 | def __init__(self, manifold): 270 | self.manifold = manifold 271 | self.points = set() 272 | self.path = [] 273 | 274 | def add(self, point): 275 | self.points.add(point) 276 | self.path = list(self.points) 277 | 278 | def minus(self, point): 279 | self.points.remove(point) 280 | self.path = list(self.points) 281 | 282 | 283 | class WildFireSweepingMethod: 284 | def __init__(self, manifold, start_face): 285 | self.manifold = manifold 286 | self.start_face = start_face 287 | self.cutlocus = CutLocus(manifold) 288 | self.firebulk = FireBulk(manifold, start_face) 289 | self.firefront = FireFront(manifold, start_face) 290 | self.firetail = FireTail(manifold) 291 | self.firebulk.add_vanish_listener(self) 292 | 293 | def on_firebulk_vanished(self, face): 294 | self.firetail.insert(manifold.edges(face)) 295 | 296 | def begin(self): 297 | self.firefront.begin() 298 | self.firetail.begin() 299 | 300 | def commit(self): 301 | self.firefront.commit() 302 | self.firetail.commit() 303 | 304 | def step(self): 305 | counter = 0 306 | firefront_cycles = self.firefront.cycles 307 | self.begin() 308 | for cycle in firefront_cycles: 309 | for point in cycle: 310 | for fngbr in self.manifold.neighbor_point2face[point]: 311 | if not self.firebulk.contains(fngbr): 312 | self.firebulk.add(fngbr) 313 | self.firefront.insert(manifold.edges(fngbr)) 314 | counter += 1 315 | self.commit() 316 | #self.begin() 317 | self.firebulk.step() 318 | #self.commit() 319 | 320 | return counter 321 | 322 | 323 | if __name__ == '__main__': 324 | import pathlib 325 | import pickle 326 | 327 | vtk_file = 'data/eight.vtk' 328 | pkl_file = 'data/eight.pkl' 329 | 330 | mf = pathlib.Path(pkl_file) 331 | if mf.exists(): 332 | print('reading manifold...') 333 | manifold = pickle.load(mf.open(mode='rb')) 334 | #print('check orientation...') 335 | #if manifold.sort_orientation() > 0: 336 | # pickle.dump(manifold, mf.open(mode='wb')) 337 | mesh = pv.read(vtk_file) 338 | manifold.mesh = mesh 339 | else: 340 | print('reading mesh...') 341 | mesh = pv.read(vtk_file) 342 | print('constructing manifold...') 343 | manifold = Manifold(mesh) 344 | print('writing manifold...') 345 | pickle.dump(manifold, mf.open(mode='wb')) 346 | 347 | wildfire = WildFireSweepingMethod(manifold, start_face=3000) 348 | 349 | print('evolving...') 350 | counter, ix = 1, 1 351 | while counter != 0: 352 | print(ix, counter) 353 | counter = wildfire.step() 354 | 355 | plt = pv.Plotter() 356 | manifold.mesh.cell_data[wildfire.firebulk.name][:] = wildfire.firebulk.values 357 | plt.add_mesh(manifold.mesh, scalars=wildfire.firebulk.name) 358 | 359 | for cycle in wildfire.firefront.cycles: 360 | plt.add_mesh(manifold.mesh.extract_points(cycle), color='red') 361 | #for cycle in wildfire.firetail.cycles: 362 | # plt.add_mesh(manifold.mesh.extract_points(cycle), color='blue') 363 | cutlocus = wildfire.cutlocus.path 364 | if len(cutlocus) > 1: 365 | plt.add_mesh(manifold.mesh.extract_points(cutlocus), color='black') 366 | 367 | plt.show(screenshot='data/wildfire_%03d.png' % ix, interactive=False) 368 | ix += 1 369 | -------------------------------------------------------------------------------- /src/tools/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/ccgeom/ccg-notes/6fade9e0ebbbe747d0f07457aa8047470d15ca1b/src/tools/__init__.py -------------------------------------------------------------------------------- /src/tools/converter.py: -------------------------------------------------------------------------------- 1 | import numpy as np 2 | import scipy.io 3 | import vedo 4 | 5 | 6 | def mread(mfile): 7 | vertexes, faces = [], [] 8 | remap = {} 9 | with open(mfile) as f: 10 | for lnn, lnt in enumerate(f): 11 | fields = lnt.strip().replace('\t', ' ').replace(' ', ' ').split(' ') 12 | if len(fields) == 0: 13 | continue 14 | elif fields[0] == '#': 15 | continue 16 | else: 17 | typ, idx, d1, d2, d3 = fields 18 | if typ == 'Vertex': 19 | vertexes.append([float(d1), float(d2), float(d3)]) 20 | remap[int(idx)] = len(vertexes) 21 | elif typ == 'Face': 22 | faces.append([remap[int(d1)], remap[int(d2)], remap[int(d3)]]) 23 | return vertexes, faces 24 | 25 | 26 | def m2mat(mfile, matfile): 27 | vertexes, faces = mread(mfile) 28 | scipy.io.savemat(matfile, {'node': vertexes, 'elem': faces}) 29 | 30 | 31 | def m2vtk(mfile, vfile): 32 | vertexes, faces = mread(mfile) 33 | node = np.array(vertexes, dtype=np.float64) 34 | cell = np.array(faces, dtype=np.int_) - 1 35 | mesh = vedo.Mesh([node, cell]) 36 | vedo.io.write(mesh, vfile) 37 | 38 | 39 | def mat2vtk(matfile, vfile): 40 | data = scipy.io.loadmat(matfile) 41 | node = np.array(data['node'], dtype=np.float64) 42 | cell = np.array(data['elem'] - 1, dtype=np.int_) 43 | mesh = vedo.Mesh([node, cell]) 44 | vedo.io.write(mesh, vfile) 45 | 46 | 47 | 48 | 49 | -------------------------------------------------------------------------------- /src/tools/viewer.py: -------------------------------------------------------------------------------- 1 | import pyvista as pv 2 | 3 | mesh = pv.read('data/eight.vtk') 4 | mesh.plot(screenshot='data/eight.png') 5 | -------------------------------------------------------------------------------- /test/tests/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/ccgeom/ccg-notes/6fade9e0ebbbe747d0f07457aa8047470d15ca1b/test/tests/__init__.py -------------------------------------------------------------------------------- /test/tests/test_manifold.py: -------------------------------------------------------------------------------- 1 | import unittest 2 | import pyvista as pv 3 | 4 | from ccgeom.manifold import Manifold 5 | 6 | 7 | class TestDiff(unittest.TestCase): 8 | 9 | def setUp(self): 10 | self.poly = pv.Polygon() 11 | self.disc = pv.Disc() 12 | self.box = pv.Box() 13 | self.cone = pv.Cone() 14 | 15 | def tearDown(self): 16 | pass 17 | 18 | def test_poly(self): 19 | m = Manifold(self.poly) 20 | 21 | def test_disc(self): 22 | m = Manifold(self.disc) 23 | 24 | def test_box(self): 25 | m = Manifold(self.box) 26 | 27 | def test_cone(self): 28 | m = Manifold(self.cone) 29 | -------------------------------------------------------------------------------- /zh_CN/2020lecture/exc_20200705.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "markdown", 5 | "metadata": { 6 | "pycharm": { 7 | "name": "#%% md\n" 8 | } 9 | }, 10 | "source": [ 11 | "# 7月5日课程作业" 12 | ] 13 | }, 14 | { 15 | "cell_type": "code", 16 | "execution_count": 1, 17 | "metadata": { 18 | "pycharm": { 19 | "name": "#%%\n" 20 | } 21 | }, 22 | "outputs": [], 23 | "source": [ 24 | "import numpy as np\n", 25 | "import pyvista as pv" 26 | ] 27 | }, 28 | { 29 | "cell_type": "markdown", 30 | "metadata": { 31 | "pycharm": { 32 | "name": "#%% md\n" 33 | } 34 | }, 35 | "source": [ 36 | "首先加载并可视化一个双环面，如下所示：" 37 | ] 38 | }, 39 | { 40 | "cell_type": "code", 41 | "execution_count": 2, 42 | "metadata": { 43 | "pycharm": { 44 | "name": "#%%\n" 45 | } 46 | }, 47 | "outputs": [ 48 | { 49 | "data": { 50 | "application/vnd.jupyter.widget-view+json": { 51 | "model_id": "814ac2edc79345aba45d0e01d87023d9", 52 | "version_major": 2, 53 | "version_minor": 0 54 | }, 55 | "text/plain": [ 56 | "ViewInteractiveWidget(height=768, layout=Layout(height='auto', width='100%'), width=1024)" 57 | ] 58 | }, 59 | "metadata": {}, 60 | "output_type": "display_data" 61 | } 62 | ], 63 | "source": [ 64 | "mesh = pv.read('../../data/eight.vtk')\n", 65 | "mesh.plot(screenshot='../../data/eight.png')" 66 | ] 67 | }, 68 | { 69 | "cell_type": "markdown", 70 | "metadata": { 71 | "pycharm": { 72 | "name": "#%% md\n" 73 | } 74 | }, 75 | "source": [ 76 | "mesh 有一定的结构，我们可以看到其中的所有顶点，如下：" 77 | ] 78 | }, 79 | { 80 | "cell_type": "code", 81 | "execution_count": 3, 82 | "metadata": { 83 | "pycharm": { 84 | "name": "#%%\n" 85 | } 86 | }, 87 | "outputs": [ 88 | { 89 | "data": { 90 | "text/plain": [ 91 | "pyvista_ndarray([[ 0.455366 , 0.0513531 , -1.06708 ],\n", 92 | " [-0.518601 , 0.0590061 , -0.972111 ],\n", 93 | " [ 0.274258 , 0.13664 , 0.446718 ],\n", 94 | " ...,\n", 95 | " [ 0.160425 , 0.177281 , 1.00846 ],\n", 96 | " [ 0.311929 , -0.19437 , 0.106358 ],\n", 97 | " [ 0.325351 , -0.178119 , 0.00863976]])" 98 | ] 99 | }, 100 | "execution_count": 3, 101 | "metadata": {}, 102 | "output_type": "execute_result" 103 | } 104 | ], 105 | "source": [ 106 | "mesh.points" 107 | ] 108 | }, 109 | { 110 | "cell_type": "code", 111 | "execution_count": 4, 112 | "metadata": { 113 | "pycharm": { 114 | "name": "#%%\n" 115 | } 116 | }, 117 | "outputs": [ 118 | { 119 | "data": { 120 | "text/plain": [ 121 | "(pyvista_ndarray(-0.262132), pyvista_ndarray(0.260431))" 122 | ] 123 | }, 124 | "execution_count": 4, 125 | "metadata": {}, 126 | "output_type": "execute_result" 127 | } 128 | ], 129 | "source": [ 130 | "mesh.points[:, 1].min(), mesh.points[:, 1].max()" 131 | ] 132 | }, 133 | { 134 | "cell_type": "code", 135 | "execution_count": 5, 136 | "metadata": { 137 | "pycharm": { 138 | "name": "#%%\n" 139 | } 140 | }, 141 | "outputs": [ 142 | { 143 | "data": { 144 | "text/plain": [ 145 | "(pyvista_ndarray(-1.26972), pyvista_ndarray(1.27079))" 146 | ] 147 | }, 148 | "execution_count": 5, 149 | "metadata": {}, 150 | "output_type": "execute_result" 151 | } 152 | ], 153 | "source": [ 154 | "mesh.points[:, 2].min(), mesh.points[:, 2].max()" 155 | ] 156 | }, 157 | { 158 | "cell_type": "code", 159 | "execution_count": null, 160 | "metadata": { 161 | "pycharm": { 162 | "name": "#%%\n" 163 | } 164 | }, 165 | "outputs": [], 166 | "source": [ 167 | "我们可以试试染色，效果如下" 168 | ] 169 | }, 170 | { 171 | "cell_type": "code", 172 | "execution_count": 14, 173 | "metadata": { 174 | "pycharm": { 175 | "name": "#%%\n" 176 | } 177 | }, 178 | "outputs": [ 179 | { 180 | "data": { 181 | "application/vnd.jupyter.widget-view+json": { 182 | "model_id": "02ae1ac8c36240ae9a5cab6deae0a7ff", 183 | "version_major": 2, 184 | "version_minor": 0 185 | }, 186 | "text/plain": [ 187 | "ViewInteractiveWidget(height=768, layout=Layout(height='auto', width='100%'), width=1024)" 188 | ] 189 | }, 190 | "metadata": {}, 191 | "output_type": "display_data" 192 | } 193 | ], 194 | "source": [ 195 | "mesh.point_data['pvalues'] = np.linspace(0.0, 1.0, mesh.n_points)\n", 196 | "mesh.plot(scalars='pvalues', show_edges=True, screenshot='points_coloring.png')" 197 | ] 198 | }, 199 | { 200 | "cell_type": "markdown", 201 | "metadata": { 202 | "pycharm": { 203 | "name": "#%% md\n" 204 | } 205 | }, 206 | "source": [ 207 | "基于上面的 API，让我们试验一下一个双环面上一个燃烧的过程，火从一点开始向外蔓延，遇到已经燃烧过的就停下蔓延，我们把停止蔓延处的点都记录下来。" 208 | ] 209 | }, 210 | { 211 | "cell_type": "markdown", 212 | "metadata": { 213 | "pycharm": { 214 | "name": "#%% md\n" 215 | } 216 | }, 217 | "source": [ 218 | "初始时刻，只有第 0 点处在着火，其他点全部是未着火的状态。" 219 | ] 220 | }, 221 | { 222 | "cell_type": "code", 223 | "execution_count": 17, 224 | "metadata": { 225 | "pycharm": { 226 | "name": "#%%\n" 227 | } 228 | }, 229 | "outputs": [ 230 | { 231 | "data": { 232 | "application/vnd.jupyter.widget-view+json": { 233 | "model_id": "68000de439a2483eaca55ef3e926e682", 234 | "version_major": 2, 235 | "version_minor": 0 236 | }, 237 | "text/plain": [ 238 | "ViewInteractiveWidget(height=768, layout=Layout(height='auto', width='100%'), width=1024)" 239 | ] 240 | }, 241 | "metadata": {}, 242 | "output_type": "display_data" 243 | } 244 | ], 245 | "source": [ 246 | "mesh.point_data['pvalues'] = np.ones([mesh.n_points]) * 0.7 # 绿色的森林\n", 247 | "mesh.point_data['pvalues'][0] = 0.0 # 强制把色阶拉回去的 workaround\n", 248 | "mesh.point_data['pvalues'][3497] = 1.0 # 着火处\n", 249 | "mesh.plot(scalars='pvalues', show_edges=True, screenshot='points_coloring.png')" 250 | ] 251 | }, 252 | { 253 | "cell_type": "code", 254 | "execution_count": 18, 255 | "metadata": { 256 | "pycharm": { 257 | "name": "#%%\n" 258 | } 259 | }, 260 | "outputs": [], 261 | "source": [ 262 | "def step():\n", 263 | " for i in range(mesh.n_points):\n", 264 | " p = mesh.points[i]\n", 265 | " pval = mesh.point_arrays['pvalues'][i]\n", 266 | " if pval > 0.75: # 如果 p 点正在燃烧\n", 267 | " for j in range(mesh.n_points):\n", 268 | " q = mesh.points[j]\n", 269 | " qval = mesh.point_arrays['pvalues'][j]\n", 270 | " d = np.sqrt(np.sum((p - q) * (p - q)))\n", 271 | " meet_cond = False\n", 272 | " if d < 0.05:\n", 273 | " if qval == 0.7: # 如果 q 点尚未燃烧过\n", 274 | " mesh.point_arrays['pvalues'][j] = 1.0\n", 275 | " meet_cond = False\n", 276 | " elif qval > 0.75 or qval == 0.0: # 如果 q 点也在燃烧\n", 277 | " meet_cond = meet_cond and (pval > qval)\n", 278 | "\n", 279 | " mesh.point_arrays['pvalues'][i] = mesh.point_arrays['pvalues'][i] * 0.9\n", 280 | " if 0.7 < mesh.point_arrays['pvalues'][i] < 0.75:\n", 281 | " mesh.point_arrays['pvalues'][i] = 0.5\n", 282 | "\n", 283 | " if meet_cond:\n", 284 | " mesh.point_arrays['pvalues'][i] = 0.0\n", 285 | "\n", 286 | " mesh.point_arrays['pvalues'][0] = 0.0" 287 | ] 288 | }, 289 | { 290 | "cell_type": "code", 291 | "execution_count": null, 292 | "metadata": { 293 | "pycharm": { 294 | "name": "#%%\n" 295 | } 296 | }, 297 | "outputs": [], 298 | "source": [ 299 | "step()" 300 | ] 301 | } 302 | ], 303 | "metadata": { 304 | "kernelspec": { 305 | "display_name": "Python 3 (ipykernel)", 306 | "language": "python", 307 | "name": "python3" 308 | }, 309 | "language_info": { 310 | "codemirror_mode": { 311 | "name": "ipython", 312 | "version": 3 313 | }, 314 | "file_extension": ".py", 315 | "mimetype": "text/x-python", 316 | "name": "python", 317 | "nbconvert_exporter": "python", 318 | "pygments_lexer": "ipython3", 319 | "version": "3.10.2" 320 | } 321 | }, 322 | "nbformat": 4, 323 | "nbformat_minor": 1 324 | } --------------------------------------------------------------------------------