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".
Clone URLs: https://rocketgit.com/user/iam-git/WellMet ssh://rocketgit@ssh.rocketgit.com/user/iam-git/WellMet git://git.rocketgit.com/user/iam-git/WellMet
release trunk
List of commits:
Subject Hash Author Date (UTC)
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
dicebox: prepare KickPointVoronoi 9543e93d56d9724a91f1e2d443fdb8f4cbaf60e6 Aleksei Gerasimov 2021-11-04 14:13:23
dicebox: remove old FullSimpleX class. d7e21f9fcaa3d037c35169695713a7bdc0f39cc3 Aleksei Gerasimov 2021-11-03 13:41:40
testcases: add testcases_nD module f48a46042f77bcaa070cca367c5d93ba8d2d779d I am 2021-10-31 02:24:54
Commit e29b374abde5e3e35dd22f327dc709927411a7b5 - convex_hull: improve orth estimator. Brat ndim nejbližších hyperrovin. Funguje dobře. Co vidím, numpy hlídá ortogonalitu, za mě cajk.
Author: I am
Author date (UTC): 2021-12-13 00:09
Committer name: I am
Committer date (UTC): 2021-12-13 00:09
Parent(s): 1473f72432e93bc349e34c1a7a8ed25ce96c08fd
Signer:
Signing key:
Signing status: N
Tree: 41a8f703902388f14a8b45e63bf4238d4fcae3fd
File Lines added Lines deleted
convex_hull.py 20 3
File convex_hull.py changed (mode: 100644) (index 5acc5a7..aace25c)
... ... def fire(hull, ns, use_MC=False):
144 144 def _orth_helper(hull): def _orth_helper(hull):
145 145 # supposed hull.space == 'G' # supposed hull.space == 'G'
146 146 hull._update() hull._update()
147 to_fire = np.nanargmax(hull.b)
148 a = hull.A[to_fire]
149 147
150 orth_basis = get_orth_basis(a)
148 b = hull.b
149 dim = hull.sample.nvar
150 #č vzít ndim nejbližších ke středu hyperrovin
151 #č (hledáme zde tedy ndim největších čísel)
152 index = np.argpartition(b, -dim)[-dim:]
153 # sort
154 #č dostaneme index indexů
155 #č argsort třídí od nějměnšího k většímu
156 index2 = np.argsort(-b[index])
157 #č pomocí indexu indexů z normálových (směrových) vektorů uděláme maticu
158 basis = hull.A[index[index2]]
159
160 #č QR rozklad jede po sloupcich
161 #č co jsem viděl, numpy matici Q normalizuje
162 #č a první sloupec zůstavá (skoro) tím samým, co byl před tím
163 Q, __R = np.linalg.qr(basis.T)
164 # yep. Numpy sometimes inverts sign of the first Q matrix vector
165 #č ale na znáky kašleme. To je důležité pro kandidaty,
166 #č zde nám ale jde o basis
167 orth_basis = Q.T
151 168
152 169 #č musí tam bejt G coordinates #č musí tam bejt G coordinates
153 170 A = orth_basis @ hull.points.T A = orth_basis @ hull.points.T
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