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)
estimation: little enhancement 694db9ebd144ee5e0fba0b068e8c73b5e06a4b98 Олёш 2020-09-02 01:14:20
estimation: new simlex_estimation added be2a9b65df74e9c3d4c03d30530d50796604f431 Олёш 2020-09-01 23:23:22
f_models: little refactoring, performance boost is not almost visible, though a34473ad2ef19973c69bde8b8c6aa29eb1614399 Олёш 2020-08-23 21:52:43
candybox: little fix 65cbd8d0fdbfd80cfa46d2fd7d87d2226b7b2c12 Олёш 2020-08-22 23:50:26
f_models, SNorm: little fix at .add_sample, a little bit better performance 49e808b07d199e8c97d7dfcda24428e8c2a081ec Олёш 2020-08-22 23:48:09
blackbox, OptimizedCensoredSampling: little refactoring, a little better performance 9825bf5531f52acb2af3bdc3b10b4c8c67101300 Олёш 2020-08-22 23:45:44
g_models: four_branch_2D refactored into the class FourBranch2D 5c60519a95121530e97e0a452b2c4ab8926c46fd I am 2020-08-21 21:45:14
LHS turned off, new test function 'Sball' 22057718d681144478dc5ea2b4e94c60394eb4c9 Miroslav Vořechovský 2020-08-13 15:53:55
gl_plot: ready 4c52875c06ecd32dddbbcb9d3638033ece5fb34b Alex 2020-08-11 01:42:53
gl_plot: SimplexEstimationWidget now almost works d25a5a4048d55090c53d63368882f3ae4027236f Alex 2020-08-10 23:34:29
gl_plot: už je to hustý ebcbd27e880f61bece09e126617cf46554f3a41d Alex 2020-08-10 18:26:44
gl_plot: WIP e9032c2b108b42630e8ae894ab9badf4ac4d2064 Alex 2020-08-10 07:27:45
gl_plot: WIP b746a2b7f175681bafbbabb4de8eaae673afdf9b Alex 2020-08-10 01:28:45
blackbox: optimized MinEnergy 6fc8e8bdf4ef1bfd2ae2a02a9b1231310794c0f2 Олёш 2020-08-08 00:09:10
blackbox: MinEnergyCensoredSampling: čístění -2 52ee13ca64742637edf6d05fd8c704f7bfd91cbe Олёш 2020-08-07 03:18:11
blackbox: MinEnergyCensoredSampling: candidates reworked to be more transparent 75018f40179a33136230a58bc03da52951e51f55 Олёш 2020-08-07 01:07:07
blackbox: little fix of p_outside in MinEnergyBlaBlaCensoringSampling f9defafad5f773f7715ed652a69434d5f06c48a3 Олёш 2020-08-06 22:10:32
qt_plot: CandidatesWidget added 1ae7241fe13df91c6df48324cd55774e8243c812 Олёш 2020-08-06 18:38:51
blackbox: KechatoTwoPointLukiskon added 2f2bb89e4a57742a7caf34375d5ce1b237d482c7 Олёш 2020-08-06 10:49:57
candybox: SettingWithCopyWarning disabled ac6951c3e667d3ba1cd128b1596955284439d53e Олёш 2020-08-06 10:46:10
Commit 694db9ebd144ee5e0fba0b068e8c73b5e06a4b98 - estimation: little enhancement
Author: Олёш
Author date (UTC): 2020-09-02 01:14
Committer name: Олёш
Committer date (UTC): 2020-09-02 01:14
Parent(s): be2a9b65df74e9c3d4c03d30530d50796604f431
Signer:
Signing key:
Signing status: N
Tree: 091602a2442bf2e75b50cd8950ff662c2eed76ed
File Lines added Lines deleted
estimation.py 9 14
File estimation.py changed (mode: 100644) (index e120ed4..7f1a639)
... ... def simplex_estimation(sample_box, model_space='Rn', sampling_space=None, weight
675 675 # 0=success, 1=failure, 2=mix # 0=success, 1=failure, 2=mix
676 676 event_ids = six.get_events(sample_box, tri.simplices) event_ids = six.get_events(sample_box, tri.simplices)
677 677
678 #č není nutno, zda se, že simplex s_ball opravdu nepotřebuje
679 #č ale určité vyrovnaní mezi tvarem simplexu a kruřnice je stale na místě
680 # s_ball = sball.Sball(f.nvar)
681 # base_r = s_ball.get_r(0.5)
682 # #č aspoň tak zatím. Ať nebudou 85% mimo
683 # d = (base_r**2) * (nvar+2)
678 684
679 685 #č zde postupně v cyklu prochazíme všemi simplexy #č zde postupně v cyklu prochazíme všemi simplexy
680 686 #č tynhlenstím zajišťujeme disjunktnost #č tynhlenstím zajišťujeme disjunktnost
 
... ... def simplex_estimation(sample_box, model_space='Rn', sampling_space=None, weight
696 702 h_plan_model = getattr(h_plan, model_space) h_plan_model = getattr(h_plan, model_space)
697 703 vertices_model = getattr(vertices, model_space) vertices_model = getattr(vertices, model_space)
698 704
699 #č budeme pokažde sestavovat triangulaci z jedného simplexu
705 #č budeme pokažde sestavovat ConvexHull z jedného simplexu
700 706 #č a rešit jen zda naši bodíky "inside or outside" #č a rešit jen zda naši bodíky "inside or outside"
701 707 #č (s narustajícím nsim tohle brzy se stavá rychlejším než bežný dotaz) #č (s narustajícím nsim tohle brzy se stavá rychlejším než bežný dotaz)
702 found_simplices = spatial.Delaunay(vertices_model).find_simplex(h_plan_model)
703
704 #č ten simplex nic neznamená, asi nebudu jej použivat
705 h_plan.simplex = found_simplices
706
707 #č uvnitř simplexu - mel by tam bejt pouze jeden, "nulový" simplex
708 mask = found_simplices == 0
709
708 convex_hull = spatial.ConvexHull(vertices_model)
709 mask = ~six.is_outside(convex_hull, h_plan_model)
710 710
711 711 #čs necháme ISSI trapit sa pravděpodobnostma #čs necháme ISSI trapit sa pravděpodobnostma
712 712 siss.add_single_event_data(h_plan.w[mask], event=simplex_id, nis=simplex_budget) siss.add_single_event_data(h_plan.w[mask], event=simplex_id, nis=simplex_budget)
713 713
714 714
715
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720 715 # -1 = 'outside', 0=success, 1=failure, 2=mix # -1 = 'outside', 0=success, 1=failure, 2=mix
721 716 if event_id == 0: if event_id == 0:
722 717 event = 'success' event = 'success'
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