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)
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
dicebox: walk throw candidates in reversed order cadf89d0efc973d540b4ee6b337eb175ae962ee8 I am 2021-12-24 21:03:00
schemes: exclude walkington 5 and 7 (2D and 3D schemes) from offer in higher dimensions 4d7b7e249c18c41f9220c778ada21116cca02aa0 I am 2021-12-23 23:52:07
simplex: implement fallback integration 9a1048540d803a76cba8c92ca67efc16c932f1a9 I am 2021-12-23 22:36:38
schemes: oprava komentaře bfa1fd1f1e1fe2e86838ee2f63f43fab50d0d115 I am 2021-12-22 13:40:45
schemes: send degree parameter as is to quadpy. a1758193a21bf47031e376612418c26c1eb1d289 I am 2021-12-22 11:53:30
qt_gui: allow zero degree for cubature schemes ed4cf50cdbf382999ef9e161dbec0e97ed508739 I am 2021-12-22 11:52:03
simplex: teď budeme hlídát aby vysledek integrace nebyl záporný 173727edac0fb6611aaa2da2ed0d200a7377a2a4 I am 2021-12-22 08:31:01
dicebox: comment out our favorite print debug 2963588b1d47a8c35a0c3ae8c611427ecbb3a843 I am 2021-12-22 08:30:16
mplot.mart: use fancy arrows instead of triangle markers ac42eaf4b8e12037720601d2335d44ae0b057feb I am 2021-12-22 04:32:06
Commit e989c87895d681920056558a0b9473b93c3b299b - whitebox: add Gaussian Z_min whitebox
Author: I am
Author date (UTC): 2022-01-04 13:54
Committer name: I am
Committer date (UTC): 2022-01-04 13:54
Parent(s): e8f1665d43cfb70e89716f591852538df0e27d8c
Signer:
Signing key:
Signing status: N
Tree: 95a574806b965fe8b33354c9eb973e03100a8819
File Lines added Lines deleted
whitebox.py 33 0
File whitebox.py changed (mode: 100644) (index 1f864d2..1a28174)
... ... from scipy import stats
24 24 from scipy import special # for S_ball from scipy import special # for S_ball
25 25 from scipy import integrate # for S_ball from scipy import integrate # for S_ball
26 26
27 import mpmath # for Gaussian_Z_min
28
29 mpmath.mp.dps = 325 # to cover anything that double-presigion float can handle
30
27 31 from .samplebox import SampleBox from .samplebox import SampleBox
28 32
29 33 from . import f_models from . import f_models
 
... ... class Lognormal_Z_prod(WhiteBox): #č ověřím to moje odvození...
331 335 return 'Lognormal_Z_prod(nvar=%s, %s, %s)' % (wt.f.nvar, wt.beta_exact, wt.sign) return 'Lognormal_Z_prod(nvar=%s, %s, %s)' % (wt.f.nvar, wt.beta_exact, wt.sign)
332 336
333 337
338 class Gaussian_Z_min(WhiteBox):
339 def __init__(self, ndim=2, **kwargs):
340 "je třeba zadat buď pf_exact, nebo konštantu u funkce minima Z_min"
341
342 self.f = f_models.SNorm(ndim)
343 self.ndim = ndim
344
345
346 self.pf_exact_method = 'exact solution'
347 if 'pf_exact' in kwargs:
348 self.pf_exact = kwargs['pf_exact']
349 sf = 1 - mpmath.root(1 - mpmath.mpf(self.pf_exact), ndim)
350 self.const = stats.norm.isf(float(sf))
351 elif 'const' in kwargs:
352 self.const = kwargs['const']
353 self.pf_exact = float(1 - mpmath.ncdf(self.const)**ndim)
354 else:
355 raise ValueError
356 self.gm = g_models.Z_min(self.const) # min(X1, X2, XN) + const
357 # na začatku nemáme vzorky - pouze rozdělení a podpís
358 self.sample_box = SampleBox(self.f(), gm_signature=self.gm_signature)
359
360 def __str__(self):
361 return 'Gaussian_Z_min%sD'%(self.ndim)
362
363 def __repr__(self):
364 return 'Gaussian_Z_min(%s, pf_exact=%s)' % (repr(self.ndim), repr(self.pf_exact))
365
366
334 367 class Weibull_Z_min(WhiteBox): class Weibull_Z_min(WhiteBox):
335 368 def __init__(self, wb_scales=(1.,1.), shape=5, **kwargs): def __init__(self, wb_scales=(1.,1.), shape=5, **kwargs):
336 369 """ """
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