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)
gmodels.py added boundary for Pareto function e7bc61e9c5854bc4cff0ee05b651b4b7ede4e0a1 Miroslav Vořechovský 2021-02-05 15:14:52
improved estimation of pf for Pareto Example 427602319f6a81e896b7aa50fd8947c5a1a91873 Miroslav Vořechovský 2021-02-05 14:15:41
dicebox.Razitko: little fixes 0e3f9147a40b7008ddec0893c3965136bac7fedf I am 2021-02-05 12:32:27
f_models.UnCorD.sample_pdf: Rn pdf fix 66cf81e4fc0bb2c6dab506cef5309c5da65a7f2c I am 2021-02-05 12:31:22
dicebox.Razitko: TRI_overall_estimations workaround 4b8146b788d0a857330c1894b5cf1c8d332103ce I am 2021-02-05 09:13:16
dicebox.Razitko: new DiceBox d9c1c9cdec94601bce9e81861ce1d4dfb5393481 I am 2021-02-05 08:04:28
simplex.Triangulation: little changes dc1efc3a081073d57be0f7a06330eb97f9634447 I am 2021-02-05 08:02:57
schemes: fix 126ba1c061474b3a9c02ce66d109ef6f8a39703a Alex 2021-02-03 08:28:28
schemes: new module af427a6a8c5e26f5b4a5930af188e40c882f9863 I am 2021-02-03 08:00:06
simplex: rework Triangulation, add FullCubatureTriangulation bdbb5a64a868cbf7c60d2bfeb8729e54bc81d347 I am 2021-02-03 05:14:32
dicebox: empty simplex fix 9b3b24a268a4d238ec6946f33d2c6ffe7d57dbfe Alex 2021-01-28 11:07:32
qt_plot.SimplexErrorGraph: finish 6fce1097d34c86c9b30c749e5b8cc2e4d8e7541d I am 2021-01-26 11:36:13
stm_df: finish get_tri_data_frame() 454bd2725a75f5a3f3851998693c4f85630fb30b I am 2021-01-22 20:43:36
stm_df: WIP bd99b8f3b8623a65c0bf0e3c22d9e67d8bce6a2c Alex 2021-01-21 15:27:11
stm_df: WIP f61a963c04764066bdd2bb9a363c51ec1c4fb389 Alex 2021-01-18 10:01:23
dicebox.Chrt: add design support 7426717fe5b3bbf299e44a92b2aca2672b752042 Alex 2021-01-15 09:30:28
design_proof_of_concept a1c9fc6ce6739e745382bdc1bfc6183a8c2a2f16 Alex 2021-01-14 22:58:01
estimation: rework simplex estimations, add cubature and design support 01dc64d5fa9afeda8326b90a71af71ede46fd8f8 Alex 2021-01-14 21:41:12
simplex.Triangulation: WIP 44bdae7876aac717f3d34c4bc6c818fc4ec65169 Alex 2021-01-13 10:43:59
simplex.Triangulation: WIP 47fe5e817878bc6bfd43db208d256a60ee573f9c Alex 2021-01-12 15:41:32
Commit e7bc61e9c5854bc4cff0ee05b651b4b7ede4e0a1 - gmodels.py added boundary for Pareto function
Author: Miroslav Vořechovský
Author date (UTC): 2021-02-05 15:14
Committer name: Miroslav Vořechovský
Committer date (UTC): 2021-02-05 15:14
Parent(s): 427602319f6a81e896b7aa50fd8947c5a1a91873
Signer:
Signing key:
Signing status: N
Tree: ba6cc23b8676e62ed91331683f30ed4df41d2af4
File Lines added Lines deleted
g_models.py 19 1
File g_models.py changed (mode: 100644) (index 70bab60..60aacc4)
... ... piecewise_2D_linear.get_2D_R_boundary = GetQuadrantBoundary2D(center_point=(4,5)
918 918 piecewise_2D_linear.pf_expression = lambda fm, a=4, b=5: (fm.marginals[0].sf(a) + fm.marginals[1].sf(b) - fm.marginals[0].sf(a)*fm.marginals[1].sf(b), 'exact solution') piecewise_2D_linear.pf_expression = lambda fm, a=4, b=5: (fm.marginals[0].sf(a) + fm.marginals[1].sf(b) - fm.marginals[0].sf(a)*fm.marginals[1].sf(b), 'exact solution')
919 919
920 920
921
921
922 922
923 923 def non_chi_squares(input_sample): def non_chi_squares(input_sample):
924 924 selfnvar = 2 selfnvar = 2
 
... ... def non_chi_squares(input_sample):
929 929 return SampleBox(input_sample, g, 'non_chi_squares') return SampleBox(input_sample, g, 'non_chi_squares')
930 930
931 931
932 # boundary for non_chi_squares (Breitung with pareto tail)
933 def non_chi_squares_R_boundary(nrod=200, *args):
934
935 boundaries = []
936 y = np.linspace(-np.sqrt(52), np.sqrt(52), nrod, endpoint=True)
937 x = + np.sqrt(2*(52-y**2)/3)
938 bound_R_1 = np.vstack(( x, y)).T
939 bound_R_2 = np.vstack((-x, y)).T
940 boundaries.append(Ingot(bound_R_1))
941 boundaries.append(Ingot(bound_R_2))
942 return boundaries
943
944 non_chi_squares.get_2D_R_boundary = non_chi_squares_R_boundary
945
946
947
948
949
932 950
933 951
934 952 def branin_2D(input_sample): def branin_2D(input_sample):
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