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.maxes: add candidates sampling (rejection-like) plot 5a15e10a9a462dd409e0627528bcb8910df77c7e I am 2022-01-06 09:40:38
mplot.maxes: add candidates plot 11e156edc351ca84fde742edf7ea1d85c3b0bc38 I am 2022-01-06 08:15:43
mplot.maxes: polish tri plots a little bit 9a4e0a18061e2d9f48c0c32c200bd1a408ceb77f I am 2022-01-05 13:15:00
mplot.mart: add plot_points() function 2c799e22d9f45b825a7f8a795ce6b9fe5fbd9c76 I am 2022-01-05 13:14:12
mplot.maxes: add convergence diagrams 813b1e8e9dd9d1e51951c51234910cdf2281cde8 I am 2022-01-05 09:07:18
mplot.mgraph: hračky s legendou 198cc40947d48b2a3cde990254def7d57c1535a6 I am 2022-01-05 09:04:23
mplot: apply default settings to figures 765d830e0230b3d85f079eb26c6eddfdb624b859 I am 2022-01-05 09:03:15
simplex: try garbage collection 45148d2665eea195c05de5852b15485d83cb7223 I am 2022-01-05 06:10:46
testcases: add Gaussian Z_min testcase 50bc3f27365e60db67f100c89ebc49b52e948645 I am 2022-01-04 13:55:59
whitebox: add Gaussian Z_min whitebox e989c87895d681920056558a0b9473b93c3b299b I am 2022-01-04 13:54:37
schemes: přídat pár komentářů k schematům e8f1665d43cfb70e89716f591852538df0e27d8c I am 2022-01-04 09:00:36
mplot.maxes: tri_nodes_plot is almost ready. Zbyvá to udělat hezky 251a0f4b7909a5468453cfb518c2bbb4064cce51 I am 2022-01-04 06:42:36
mplot.maxes: add complete tri plots 08c6e421188c4251cae1aa664a69bdc3a0afb314 I am 2022-01-04 05:45:21
mplot.mart: add tri_plot() function aace2f9d02b7744651a089c164af9b7b5824729e I am 2022-01-04 05:44:14
simplex: fix use before initialization ff8be3dcc679c4893948d7d1dc6c45402ccee81b I am 2022-01-04 05:43:17
mplot.maxes: prepare convex_hull_plot() function 732f16a441c1a5f1160b45d91a050683ee70ff5d I am 2022-01-03 15:26:59
mplot.mart: comment out old convex plot function, prepare qhull_plot instead 59de205056903adf87f84c5c1b022c3c83fa9c57 I am 2022-01-03 15:24:30
mplot.mgraph: prepare orth graph routines 74e30ed99fcc6e68c6b3bf7e55bbd93fe8f26d13 I am 2022-01-02 11:18:11
convex_hull: complicate orth estimator ba5f40eaf0f5f4012ef07f5684d58481cefbfe09 I am 2021-12-28 13:56:19
reader: explicitly use utf-8 encoding. (Nemělo by to nic pokazit.. Pitomé nastavení ve Windows) 17bc8a9692695c22f78f8a39ed8aaddd4bfa4808 I am 2021-12-26 22:59:41
Commit 5a15e10a9a462dd409e0627528bcb8910df77c7e - mplot.maxes: add candidates sampling (rejection-like) plot
Author: I am
Author date (UTC): 2022-01-06 09:40
Committer name: I am
Committer date (UTC): 2022-01-06 09:40
Parent(s): 11e156edc351ca84fde742edf7ea1d85c3b0bc38
Signer:
Signing key:
Signing status: N
Tree: f4eaabb4f49554cab0967d56593718e6132edd55
File Lines added Lines deleted
mplot/maxes.py 36 1
File mplot/maxes.py changed (mode: 100644) (index 201c029..4e13b7b)
... ... from . import mgraph
19 19
20 20 # it is mostly for qt_plot, it offers availiable options to user # it is mostly for qt_plot, it offers availiable options to user
21 21 __all__ = [ __all__ = [
22 'candidates_plot',
22 'candidates_plot', 'candidates_sampling_plot',
23 23 'convex_hull_plot', 'tri_plot', 'tri_nodes_plot', 'convex_hull_plot', 'tri_plot', 'tri_nodes_plot',
24 24 'tri_R_plot', 'tri_GK_plot', 'tri_R_plot', 'tri_GK_plot',
25 25 'tri_R_nodes_plot', 'tri_GK_nodes_plot', 'tri_R_nodes_plot', 'tri_GK_nodes_plot',
 
... ... __all__ = [
34 34 ] ]
35 35
36 36
37 def candidates_sampling_plot(ax, linewidths=[0.7, 0.5, 0.4, 0.3, 0.2, 0.1]):
38 from .. import simplex as six
39 from .. import estimation as stm
40
41 def _stm_draw_nodes(*args, **kwargs):
42 #č v tomto plot bude šilený bordel v tom, kdo kolbek spouští
43 #č a kdo mu co tam posílá. Na event a na nodes spolehat ale můžeme
44 #
45 # callback's signature: sx, indices=, simplex=, nodes=, cell_stats=
46 # positional "sx" is Tri object itself
47 # "indices" are numbers of simplex vertices
48 # "simplex" are vertices itself
49 # "nodes" is what we really want to draw
50
51 event = kwargs['cell_stats']['event']
52
53 if event in ('mix', 'outside'):
54 mart.plot_sample(ax, kwargs['nodes'], ls='', marker='.',\
55 mec="#00007E", mfc="#00007E", ms=1.5, alpha=0.5)
56
57 data = stm.fast_simplex_estimation(ax.sample_box, model_space=ax.space,\
58 sampling_space=ax.space, \
59 weighting_space=ax.space,\
60 outside_budget=1000, \
61 simplex_budget=100,\
62 callback=_stm_draw_nodes, design=None)
63
64 mart.setup(ax)
65 mart.curly(ax, linewidths=linewidths)
66 mart.triplot(ax, color="#B2B2B2", lw=0.5, zorder=1000)
67 mart.plot_points(ax, ms=5, zorder=100500)
68 try:
69 mart.plot_boundaries(ax, lw=0.7, zorder=10500)
70 except:
71 pass
37 72
38 73 def candidates_plot(ax): def candidates_plot(ax):
39 74 tri_plot(ax, tri_space=None, linewidths=[0.7, 0.5, 0.4, 0.3]) tri_plot(ax, tri_space=None, linewidths=[0.7, 0.5, 0.4, 0.3])
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