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
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List of commits:
Subject Hash Author Date (UTC)
simplex.FullCubatureIntegration.get_sensitivities: do not normalize global gradient c648c484a5599a00236ab70c36cdf407c24f5306 I am 2023-01-14 04:51:16
simplex: implement sensitivities 65056319c51fd93deb76ce14e52c08869dfc04a2 I am 2023-01-13 11:27:46
mplot.maxes: prepare GRaph plot 68774535915af3deaf6104a0bbe9b3c4d24c0cec I am 2023-01-12 02:43:20
mplot.mgraph.tri_estimation_plot: use planar vertex estimator 1d300fa56248be9cdab5a4e5b0d4372f68fd5255 I am 2023-01-11 15:48:28
mplot.mart: implement lsf_boundary() contouring 8642d2f0c043f4e71af1cc45b9e25da326afd3ca I am 2023-01-11 05:20:00
mplot.mart.setup_labels: make labels more adaptive 60cd0b34a67b38df1c730dddc9e0771139818f33 I am 2023-01-11 04:35:47
simplex._SamplingTriangulation: self reference fix 79204ff15cba7c5ca24bb5b48e2073058acf00ae I am 2023-01-11 03:21:34
testcases.testcases_2D: add pf for rastrigin 4f3b35fe18496fcb9f59860174c876cb7a82749a I am 2023-01-10 23:39:45
dicebox.circumtri: fix initialization on ED loading. Use simple potential for space filling c02656e588a164685c4a750ce865c4b50f716563 I am 2023-01-10 23:37:30
simplex.FullCubatureIntegration.get_failure_moments: negative probabilities fix 27dd6bb1e5bb0eb1e28eef88e28913d1eca461da I am 2023-01-10 20:16:09
add more nD problems from literature 2380cdbdcf17dd5e0af19506c6f7bb1e838de03b I am 2023-01-10 06:13:56
f_models: implement Norm class 698c3216b1c8a0e2d57bfb33340a7ea8758d4e63 I am 2023-01-09 23:13:48
simplex.FullCabatureIntegration: implement get_failure_moments() 0742ee3d3932d7c3c0b6bbe6e327c92ced04aedd I am 2023-01-09 19:53:55
simplex._Triangulation: add get_failure_moments() method 3e362970b67a50643c1e486729efbf554cacf03f I am 2023-01-08 03:26:02
simplex: use advanced indexing instead of isin function 568c8623ad4cfaa343df05ae880d099556037cf0 I am 2023-01-06 13:41:00
dicebox.circumtri: fill in global simplex index only in case of full integration 065668f1810396f55be0860416f1c6ad507a9573 I am 2023-01-04 21:44:57
dicebox.circumtri: implement "holyday", breaks the greatest safe simplex 14f067d43cde14f990e7a4136b61c548f3acde92 I am 2023-01-04 16:28:51
simplex: implement FullCubatureIntegration 072927115a8a641f89b39265085eb6cac27aa492 I am 2023-01-04 16:27:39
dicebox.circumtri: use mixed facet outside nodes as candidates only. 03c1c974dafa8ff041f032c89149da7fc5b90b39 I am 2023-01-03 15:55:57
shell: use query() method of the convex hull 321a3fab33684cb9bef3c2344200c6519b595bb0 I am 2023-01-03 15:54:45
Commit c648c484a5599a00236ab70c36cdf407c24f5306 - simplex.FullCubatureIntegration.get_sensitivities: do not normalize global gradient
Author: I am
Author date (UTC): 2023-01-14 04:51
Committer name: I am
Committer date (UTC): 2023-01-14 04:51
Parent(s): 65056319c51fd93deb76ce14e52c08869dfc04a2
Signer:
Signing key:
Signing status: N
Tree: 23661134e944e435c71909b864047cf9c31e3e0d
File Lines added Lines deleted
wellmet/simplex.py 4 3
File wellmet/simplex.py changed (mode: 100644) (index 3cda360..979004b)
... ... class FullCubatureIntegration(_Triangulation):
1413 1413 global_gradient += gradient * p_mixed global_gradient += gradient * p_mixed
1414 1414 sensitivities += gradient**2 * p_mixed sensitivities += gradient**2 * p_mixed
1415 1415
1416 length = np.sqrt(np.inner(global_gradient, global_gradient))
1417 global_gradient = global_gradient / length
1416 #length = np.sqrt(np.inner(global_gradient, global_gradient))
1417 #global_gradient = global_gradient / length
1418 1418
1419 sensitivities = sensitivities / p_mix
1419 global_gradient /= p_mix
1420 sensitivities /= p_mix
1420 1421
1421 1422 return p_mix, global_gradient, sensitivities return p_mix, global_gradient, sensitivities
1422 1423
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