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)
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
qt_gui: add add_random_points() method 1c1819745a854889b6d3ae9e62e9735441523ec9 I am 2021-10-31 02:23:14
qt_gui: rearrange functions within qt_gui, add file menu d267357cdbfe805db5ef358e6e1acb24c88b5638 I am 2021-10-30 21:02:17
whitebox: implement run_sample() 576ca55be17e6f14500e70d97536e0b53a57f029 I am 2021-10-30 21:01:07
qt_gui: implement dicebox setup 09a7074b12e46d0554b2c4f73b6a8b672d0b4428 I am 2021-10-30 15:12:33
schemes: small fix 934b2269e5b08930e23fd67df07234251b123153 I am 2021-10-30 15:11:39
qt_gui: prepare setup Goal setup dialog e53197a0b5d5a994dddbcbfb02042c5383f79ec7 Aleksei Gerasimov 2021-10-29 16:47:09
schemes: add conventional functions for tn schemes 9a32048dc342604291f1b7d17efc71be755d3810 Aleksei Gerasimov 2021-10-29 16:45:24
reader: make Reader callable 5cdd55d11ff846f9116fb0e00f54a7830ef3c276 Aleksei Gerasimov 2021-10-27 16:30:05
make WellMet standalone runnable 1fe983d633d7194a64cf6928044082936790ce4d Aleksei Gerasimov 2021-10-27 16:21:51
qt_gui: prepare qt_box_functions module c500fcd20e7b296262a0566d04aabb7bd1ae9cfa Aleksei Gerasimov 2021-10-25 15:39:56
shapeshare: keep empty file to reserve the name b11f17e13dafc3d58db5ad9f101c0126e0bfd871 Aleksei Gerasimov 2021-10-21 14:48:03
delete sball_old :( 792d9d83fde0f38e7396162788ec8aa922b0fd0c Aleksei Gerasimov 2021-10-21 14:47:06
whitebox: add Z_sum, Z_prod, small clean up faec934bb03c20906c9091fc196cc0daf824b54f Aleksei Gerasimov 2021-10-21 13:48:07
g_models: add neverfall, add sign parameter to Z_prod 129abf19da15a5dfcb5a02614d92a233f914d146 Aleksei Gerasimov 2021-10-21 13:45:47
Commit 94cee6efca47351093d49b5c801e410e1375a5c7 - mplot.mgraph: do not use ax.sample_box
Author: Aleksei Gerasimov
Author date (UTC): 2021-11-16 17:12
Committer name: Aleksei Gerasimov
Committer date (UTC): 2021-11-16 17:12
Parent(s): 7878752fffa54bda772a5a6768bddbf05357ae73
Signer:
Signing key:
Signing status: N
Tree: 795ec0e93c5ba4d0f583ed74ee4344427dbe1bc3
File Lines added Lines deleted
mplot/mgraph.py 9 4
File mplot/mgraph.py changed (mode: 100644) (index faac09f..0a6661b)
5 5 #č nazvy proměnných jsou v angličtině #č nazvy proměnných jsou v angličtině
6 6 #č Ale komenty teda ne) #č Ale komenty teda ne)
7 7
8 #č otázkou je, kdo je uživatelem modulu.
9 #č zatím ho potřebujou jenom vnejší skripty,
10 #č které dostávájí data z csv souborů a žádné skřiňky nevytveřejí.
11 #č Proto funkce v tomto modulu zatím-prozátím nebudou spolehát na
12 #č ax.sample_box
8 13
9 14 #č sehnaní datarámu necháme uživateli #č sehnaní datarámu necháme uživateli
10 15 def tri_estimation_fill(ax, df): def tri_estimation_fill(ax, df):
 
... ... def trii_estimation_fill(ax, df):
53 58 f = df['failure'].to_numpy() f = df['failure'].to_numpy()
54 59 m = df['mix'].to_numpy() m = df['mix'].to_numpy()
55 60 labels = ("out of sampling domain estimation", "failure domain estimation",\ labels = ("out of sampling domain estimation", "failure domain estimation",\
56 "mixed simplices measure", "success domain estimation")
61 "mixed simplices measure", "success domain estimation")
57 62 return ax.stackplot(df.index, o, f, m, s, labels=labels, colors=colors) return ax.stackplot(df.index, o, f, m, s, labels=labels, colors=colors)
58 63
59 64
60 65
61 66 #č ok, tak uděláme všecko dohromady #č ok, tak uděláme všecko dohromady
62 67 #č datarám, jako vždy, uživatel donese svůj vlastní #č datarám, jako vždy, uživatel donese svůj vlastní
63 def trii_estimation_plot(ax, df):
68 def trii_estimation_plot(ax, df, pf_exact=None, pf_exact_method="$p_f$"):
64 69 # fill # fill
65 70 trii_estimation_fill(ax, df) trii_estimation_fill(ax, df)
66 71
 
... ... def trii_estimation_plot(ax, df):
75 80 ax.plot(df.index[mask], vo, '-m', label="simple $p_f$ estimation") ax.plot(df.index[mask], vo, '-m', label="simple $p_f$ estimation")
76 81 ax.plot(df.index[mask], wvo, '-r', label="weighted $p_f$ estimation") ax.plot(df.index[mask], wvo, '-r', label="weighted $p_f$ estimation")
77 82
78 # pf_exact - povinné :)
79 ax.axhline(ax.sample_box.pf_exact, c='b', label=ax.sample_box.pf_exact_method)
83 if pf_exact is not None:
84 ax.axhline(pf_exact, c='b', label=pf_exact_method)
80 85
81 86
82 87
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