iam-git / WellMet (public) (License: MIT) (since 2021-08-31) (hash sha1)
WellMet is pure Python framework for spatial structural reliability analysis. Or, more specifically, for "failure probability estimation and detection of failure surfaces by adaptive sequential decomposition of the design domain".
List of commits:
Subject Hash Author Date (UTC)
dicebox.Goal: add additional stats. Jsou to věci, které člověk by chtěl vědět. 45e8296c954705ca30c311e43e570c82c2f5113d I am 2021-12-20 02:49:15
dicebox: pochybná optimizace výběru kandidatů s použitím vlastního slovníku. Pořádně bych musel překopat celý DiceBox. 0f30c4301a1f2b40556a9c84ee4b8c53638a6571 I am 2021-12-19 20:33:43
simplex: bottleneck optimization. Překopal jsem triangulation.update() 3a110baebb237b3f99ec338c2b19f375cdcb5819 Aleksei Gerasimov 2021-12-13 15:31:38
convex_hull: improve orth estimator. Brat ndim nejbližších hyperrovin. Funguje dobře. Co vidím, numpy hlídá ortogonalitu, za mě cajk. e29b374abde5e3e35dd22f327dc709927411a7b5 I am 2021-12-13 00:09:59
simplex: optimize simplex validation a little bit 1473f72432e93bc349e34c1a7a8ed25ce96c08fd I am 2021-12-11 22:05:10
mplot: apply recommened tex settings 48b0ce9931157494afd340d9bf02a763c75b65ec I am 2021-12-05 13:23:15
qt_gui.qt_plot: rework cubature selection 17691c7770acdef9e862e21d62b4abbd4fee391c Aleksei Gerasimov 2021-11-30 13:36:34
qt_plot: import cubature schemes (regression fix) e9fe073ebd2da613e834cda1fc154d8ed7455cad Aleksei Gerasimov 2021-11-30 12:30:48
qt_gui: show tree space instead of just (unclear even for me) "potential space" 98b485ab34d7c47e3d4bcbb827589b86d0356538 Aleksei Gerasimov 2021-11-30 12:27:32
dicebox: print P coordinates of orphan candidates ac5ea313e0e542436cb8685a2cff3e241bd57e59 Aleksei Gerasimov 2021-11-30 12:26:36
simplex: check cubatures for non finite values (nan) e41838b1350e256e32ab2e6014c594bec873c973 Aleksei Gerasimov 2021-11-30 12:24:29
ghull: fix orth estimator for non-Gaussian distributions ceae4981fa46cc770cdedb84bc59f4802a657364 Aleksei Gerasimov 2021-11-30 09:25:02
mplot.misc: enable latex 633721276f8f61aa7f82b37443f5a304a85c2f84 Aleksei Gerasimov 2021-11-29 13:45:58
ghull: limit memory consuption to 1/10 of RAM f5c173be56dff7811f799551d2261aac0f719c72 I am 2021-11-28 08:53:55
qt_gui: add missing comma d56fa172be68d963105dd36c1cf0b1536fe6f080 I am 2021-11-28 08:14:29
mplot.mgraph: add outside line to tri_estimation_plot de5fb9d7d6fe6fd930ec7541c82fd4cf2e7d5794 Aleksei Gerasimov 2021-11-25 14:13:35
mplot.mgraph: add tri_estimation_plot eaaf410b48988c53ca31dee1203654dfef1adb06 Aleksei Gerasimov 2021-11-23 09:36:19
mplot.mgraph: do not use ax.sample_box 94cee6efca47351093d49b5c801e410e1375a5c7 Aleksei Gerasimov 2021-11-16 17:12:08
testcases: sball testcase fix 7878752fffa54bda772a5a6768bddbf05357ae73 Aleksei Gerasimov 2021-11-10 14:06:14
dicebox: replace tabs afe3b91d0b1ee621f0e605a28b12405e15ce9a22 I am 2021-11-07 16:44:44
Commit 45e8296c954705ca30c311e43e570c82c2f5113d - dicebox.Goal: add additional stats. Jsou to věci, které člověk by chtěl vědět.
Author: I am
Author date (UTC): 2021-12-20 02:49
Committer name: I am
Committer date (UTC): 2021-12-20 02:49
Parent(s): 0f30c4301a1f2b40556a9c84ee4b8c53638a6571
Signer:
Signing key:
Signing status: N
Tree: dd56dd32da83a99baad544849784500ba1dc3eef
File Lines added Lines deleted
dicebox.py 14 2
simplex.py 14 0
File dicebox.py changed (mode: 100644) (index b440c6f..bf30e0e)
... ... class Goal(DiceBox):
1635 1635 #č takže musíme sami lepit nové etikety #č takže musíme sami lepit nové etikety
1636 1636 bx.global_stats['nsim'] = bx.nsim bx.global_stats['nsim'] = bx.nsim
1637 1637
1638 failsi = bx.failsi
1639
1638 1640 if 'tri' in dir(bx): if 'tri' in dir(bx):
1639 1641 #č Tri.get_pf_estimation() vrací: #č Tri.get_pf_estimation() vrací:
1640 1642 # 'TRI_estimation': tri_estimation, 'global_stats': {mix, failure}, \ # 'TRI_estimation': tri_estimation, 'global_stats': {mix, failure}, \
 
... ... class Goal(DiceBox):
1653 1655 estimations['ghull_estimation'] = bx.ghull_estimation estimations['ghull_estimation'] = bx.ghull_estimation
1654 1656
1655 1657 #č hrozně důležitý. Těšíme se na csv-čko. #č hrozně důležitý. Těšíme se na csv-čko.
1656 bx.global_stats = {**bx.global_stats, **estimations['global_stats']}
1658 bx.global_stats.update(estimations['global_stats'])
1659 bx.global_stats['success_points'] = len(failsi[~failsi])
1660 bx.global_stats['failure_points'] = len(failsi[failsi])
1657 1661 bx.global_stats['success'] = tri_estimation[0] bx.global_stats['success'] = tri_estimation[0]
1658
1662 bx.global_stats['candidates_sets'] = len(bx.candidates_index)
1659 1663 return estimations return estimations
1660 1664
1661 1665
 
... ... class Goal(DiceBox):
1674 1678
1675 1679 global_stats = bx.global_stats global_stats = bx.global_stats
1676 1680 # outside dodá Ghull # outside dodá Ghull
1681 global_stats['success_points'] = len(failsi[~failsi])
1682 global_stats['failure_points'] = len(failsi[failsi])
1677 1683 global_stats['success'] = tri_estimation[0] global_stats['success'] = tri_estimation[0]
1678 1684 global_stats['failure'] = tri_estimation[1] global_stats['failure'] = tri_estimation[1]
1679 1685 global_stats['mix'] = tri_estimation[2] global_stats['mix'] = tri_estimation[2]
1680 1686 global_stats['vertex_estimation'] = vertex_estimation global_stats['vertex_estimation'] = vertex_estimation
1681 1687 global_stats['weighted_vertex_estimation'] = weighted_vertex_estimation global_stats['weighted_vertex_estimation'] = weighted_vertex_estimation
1682 1688 global_stats['nsimplex'] = 0 global_stats['nsimplex'] = 0
1689 global_stats['tn_scheme'] = bx.scheme.name
1690 global_stats['tn_scheme_points'] = bx.scheme.points.shape[1]
1691 global_stats['newly_invalidated'] = 0
1692 global_stats['newly_estimated'] = 0
1693 global_stats['simplex_stats'] = 0
1694 global_stats['candidates_sets'] = len(bx.candidates_index)
1683 1695 global_stats['ncoplanar'] = 0 global_stats['ncoplanar'] = 0
1684 1696
1685 1697 return {'TRI_overall_estimations': tri_estimation, \ return {'TRI_overall_estimations': tri_estimation, \
File simplex.py changed (mode: 100644) (index 4fc9e55..4f221bd)
... ... class _Triangulation:
254 254 #č ty množiny jsou tak trošku overkill, ale budiž #č ty množiny jsou tak trošku overkill, ale budiž
255 255 sx.simplices_set = set() sx.simplices_set = set()
256 256
257 sx.newly_estimated = 0
258 sx.newly_invalidated = 0
259
257 260 # create .tri triangulation # create .tri triangulation
258 261 #č tri - Deloneho triangulace #č tri - Deloneho triangulace
259 262 #č žádné chyby nechytám #č žádné chyby nechytám
 
... ... class _Triangulation:
339 342 to_estimate = new_simplices_set - sx.simplices_set to_estimate = new_simplices_set - sx.simplices_set
340 343 to_invalidate = new_simplices_set - to_estimate to_invalidate = new_simplices_set - to_estimate
341 344
345 sx.newly_estimated = len(to_estimate)
346 sx.newly_invalidated = len(to_invalidate)
347
342 348 #č invalidace #č invalidace
343 349 # difference_update # difference_update
344 350 sx.simplices_set -= to_invalidate sx.simplices_set -= to_invalidate
 
... ... class JustCubatureTriangulation(_FastTriangulation, _CubatureTriangulation):
844 850 #ё так, для красоты #ё так, для красоты
845 851 global_stats = dict() global_stats = dict()
846 852 # outside dodá Ghull # outside dodá Ghull
853 global_stats['success_points'] = None #č další kód musí to přepsat
854 global_stats['failure_points'] = None #č další kód musí to přepsat
847 855 global_stats['success'] = None #č další kód musí to přepsat global_stats['success'] = None #č další kód musí to přepsat
848 856 global_stats['failure'] = tri_estimation[1] global_stats['failure'] = tri_estimation[1]
849 857 global_stats['mix'] = tri_estimation[2] global_stats['mix'] = tri_estimation[2]
850 858 global_stats['vertex_estimation'] = vertex_estimation global_stats['vertex_estimation'] = vertex_estimation
851 859 global_stats['weighted_vertex_estimation'] = weighted_vertex_estimation global_stats['weighted_vertex_estimation'] = weighted_vertex_estimation
852 860 global_stats['nsimplex'] = sx.tri.nsimplex global_stats['nsimplex'] = sx.tri.nsimplex
861 global_stats['tn_scheme'] = sx.tn_scheme.name
862 global_stats['tn_scheme_points'] = sx.tn_scheme.points.shape[1]
863 global_stats['newly_invalidated'] = sx.newly_invalidated
864 global_stats['newly_estimated'] = sx.newly_estimated
865 global_stats['simplex_stats'] = len(sx.simplex_stats)
866 global_stats['candidates_sets'] = None #č další kód musí to přepsat
853 867 global_stats['ncoplanar'] = len(sx.tri.coplanar) global_stats['ncoplanar'] = len(sx.tri.coplanar)
854 868
855 869 return {'TRI_estimation': tri_estimation, 'global_stats': global_stats, \ return {'TRI_estimation': tri_estimation, 'global_stats': global_stats, \
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