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: 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
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
Commit eaaf410b48988c53ca31dee1203654dfef1adb06 - mplot.mgraph: add tri_estimation_plot
Author: Aleksei Gerasimov
Author date (UTC): 2021-11-23 09:36
Committer name: Aleksei Gerasimov
Committer date (UTC): 2021-11-23 09:36
Parent(s): 94cee6efca47351093d49b5c801e410e1375a5c7
Signer:
Signing key:
Signing status: N
Tree: c28de110b6df27dc9eef4fd6a3316415e5d4a7c5
File Lines added Lines deleted
mplot/mgraph.py 30 12
File mplot/mgraph.py changed (mode: 100644) (index 0a6661b..e6b67b9)
13 13
14 14 #č sehnaní datarámu necháme uživateli #č sehnaní datarámu necháme uživateli
15 15 def tri_estimation_fill(ax, df): def tri_estimation_fill(ax, df):
16 # some default values
17 if not ax.get_xlabel():
18 ax.set_xlabel('Number of simulations')
19 if not ax.get_ylabel():
20 ax.set_ylabel('Probability measure')
21
22 16 #xkcd_green = (167, 255, 181) # xkcd:light seafoam green #a7ffb5 #xkcd_green = (167, 255, 181) # xkcd:light seafoam green #a7ffb5
23 17 green = "#A7FFB5" green = "#A7FFB5"
24 18 #xkcd_red = (253, 193, 197) # xkcd: pale rose (#fdc1c5) #xkcd_red = (253, 193, 197) # xkcd: pale rose (#fdc1c5)
 
... ... def tri_estimation_fill(ax, df):
36 30 return ax.stackplot(df.index, f, m, o, s, labels=labels, colors=colors) return ax.stackplot(df.index, f, m, o, s, labels=labels, colors=colors)
37 31
38 32
33
34
39 35 #č sehnaní datarámu necháme uživateli #č sehnaní datarámu necháme uživateli
40 36 # inverted # inverted
41 37 def trii_estimation_fill(ax, df): def trii_estimation_fill(ax, df):
42 # some default values
43 if not ax.get_xlabel():
44 ax.set_xlabel('Number of simulations')
45 if not ax.get_ylabel():
46 ax.set_ylabel('Probability measure')
47
48 38 #xkcd_green = (167, 255, 181) # xkcd:light seafoam green #a7ffb5 #xkcd_green = (167, 255, 181) # xkcd:light seafoam green #a7ffb5
49 39 green = "#A7FFB5" green = "#A7FFB5"
50 40 #xkcd_red = (253, 193, 197) # xkcd: pale rose (#fdc1c5) #xkcd_red = (253, 193, 197) # xkcd: pale rose (#fdc1c5)
 
... ... def trii_estimation_fill(ax, df):
62 52 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)
63 53
64 54
55 #č ok, tak uděláme všecko dohromady
56 #č datarám, jako vždy, uživatel donese svůj vlastní
57 def tri_estimation_plot(ax, df, pf_exact=None, pf_exact_method="$p_f$"):
58 # some default values
59 # if not ax.get_xlabel():
60 # ax.set_xlabel('Number of simulations')
61 # if not ax.get_ylabel():
62 # ax.set_ylabel('Probability measure')
63
64 # fill
65 tri_estimation_fill(ax, df)
66
67 if pf_exact is not None:
68 ax.axhline(pf_exact, c='b', label=pf_exact_method)
69
70 #č teď čáry
71 v = df['vertex_estimation'].to_numpy()
72 wv = df['weighted_vertex_estimation'].to_numpy()
73 ax.plot(df.index, v, '-m', label="simple $p_f$ estimation")
74 ax.plot(df.index, wv, '-r', label="weighted $p_f$ estimation")
75
76
77
65 78
66 79 #č ok, tak uděláme všecko dohromady #č ok, tak uděláme všecko dohromady
67 80 #č datarám, jako vždy, uživatel donese svůj vlastní #č datarám, jako vždy, uživatel donese svůj vlastní
68 81 def trii_estimation_plot(ax, df, pf_exact=None, pf_exact_method="$p_f$"): def trii_estimation_plot(ax, df, pf_exact=None, pf_exact_method="$p_f$"):
82 # some default values
83 # if not ax.get_xlabel():
84 # ax.set_xlabel('Number of simulations')
85 # if not ax.get_ylabel():
86 # ax.set_ylabel('Probability measure')
69 87 # fill # fill
70 88 trii_estimation_fill(ax, df) trii_estimation_fill(ax, df)
71 89
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