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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)
add line and two lines problems for sensitivity analysis	0c620f7960399ed8b34e02d663772d0eb34e66f1	I am	2023-01-14 08:30:56
simplex.FullCubatureIntegration.get_sensitivities: do not normalize global gradient	c648c484a5599a00236ab70c36cdf407c24f5306	I am	2023-01-14 04:51:16
simplex: implement sensitivities	65056319c51fd93deb76ce14e52c08869dfc04a2	I am	2023-01-13 11:27:46
mplot.maxes: prepare GRaph plot	68774535915af3deaf6104a0bbe9b3c4d24c0cec	I am	2023-01-12 02:43:20
mplot.mgraph.tri_estimation_plot: use planar vertex estimator	1d300fa56248be9cdab5a4e5b0d4372f68fd5255	I am	2023-01-11 15:48:28
mplot.mart: implement lsf_boundary() contouring	8642d2f0c043f4e71af1cc45b9e25da326afd3ca	I am	2023-01-11 05:20:00
mplot.mart.setup_labels: make labels more adaptive	60cd0b34a67b38df1c730dddc9e0771139818f33	I am	2023-01-11 04:35:47
simplex._SamplingTriangulation: self reference fix	79204ff15cba7c5ca24bb5b48e2073058acf00ae	I am	2023-01-11 03:21:34
testcases.testcases_2D: add pf for rastrigin	4f3b35fe18496fcb9f59860174c876cb7a82749a	I am	2023-01-10 23:39:45
dicebox.circumtri: fix initialization on ED loading. Use simple potential for space filling	c02656e588a164685c4a750ce865c4b50f716563	I am	2023-01-10 23:37:30
simplex.FullCubatureIntegration.get_failure_moments: negative probabilities fix	27dd6bb1e5bb0eb1e28eef88e28913d1eca461da	I am	2023-01-10 20:16:09
add more nD problems from literature	2380cdbdcf17dd5e0af19506c6f7bb1e838de03b	I am	2023-01-10 06:13:56
f_models: implement Norm class	698c3216b1c8a0e2d57bfb33340a7ea8758d4e63	I am	2023-01-09 23:13:48
simplex.FullCabatureIntegration: implement get_failure_moments()	0742ee3d3932d7c3c0b6bbe6e327c92ced04aedd	I am	2023-01-09 19:53:55
simplex._Triangulation: add get_failure_moments() method	3e362970b67a50643c1e486729efbf554cacf03f	I am	2023-01-08 03:26:02
simplex: use advanced indexing instead of isin function	568c8623ad4cfaa343df05ae880d099556037cf0	I am	2023-01-06 13:41:00
dicebox.circumtri: fill in global simplex index only in case of full integration	065668f1810396f55be0860416f1c6ad507a9573	I am	2023-01-04 21:44:57
dicebox.circumtri: implement "holyday", breaks the greatest safe simplex	14f067d43cde14f990e7a4136b61c548f3acde92	I am	2023-01-04 16:28:51
simplex: implement FullCubatureIntegration	072927115a8a641f89b39265085eb6cac27aa492	I am	2023-01-04 16:27:39
dicebox.circumtri: use mixed facet outside nodes as candidates only.	03c1c974dafa8ff041f032c89149da7fc5b90b39	I am	2023-01-03 15:55:57

Commit 0c620f7960399ed8b34e02d663772d0eb34e66f1 - add line and two lines problems for sensitivity analysis
Author: I am
Author date (UTC): 2023-01-14 08:30
Committer name: I am
Committer date (UTC): 2023-01-14 08:30
Parent(s): c648c484a5599a00236ab70c36cdf407c24f5306
Signer:
Signing key:
Signing status: N
Tree: addf67aed9f0593cf70666275578af4723b46f78

File	Lines added	Lines deleted
wellmet/g_models.py	68	0
wellmet/testcases/testcases_nD.py	9	0
wellmet/whitebox.py	49	0

File wellmet/g_models.py changed (mode: 100644) (index aadb119..b8d7311)
...	...	class Linear_nD:
176	176	return (Ingot(bound_R),)	return (Ingot(bound_R),)
177	177
178	178
	179		class X1:
	180		"""
	181		suma velicin plus beta*sqrt(Nvar. )
	182		Pro IID Gaussian ma tohle ind. spol. beta = beta
	183		The same as Linear_nD, but defined via
	184		beta in sense of reliability index
	185		"""
	186		def __init__(self, beta_exact):
	187		self._beta_exact = beta_exact
	188
	189		# sign
	190		def __repr__(self):
	191		return 'X1(%s)' % repr(self._beta_exact)
	192
	193		def __call__(self, input_sample):
	194		# očekávam, že get_R_coordinates mně vrátí 2D pole
	195		sample = get_R_coordinates(input_sample)
	196		g = -sample[:, 0] + self._beta_exact
	197		return SampleBox(input_sample, g, repr(self))
	198
	199		# Fence off!
	200		def get_2D_R_boundary(self, nrod=100, xlim=(-5,5), ylim=(-5,5), *args):
	201		"""
	202		Fence off!
	203		nrod - number of rods in fencing
	204		"""
	205
	206		bound_R = np.empty((nrod, 2))
	207		bound_R[:, 0] = self._beta_exact
	208		bound_R[:, 1] = np.linspace(ylim[0], ylim[1], nrod, endpoint=True)
	209		# tuple of tuple
	210		return (Ingot(bound_R),)
	211
	212
	213		class AbsX1:
	214		"""
	215		suma velicin plus beta*sqrt(Nvar. )
	216		Pro IID Gaussian ma tohle ind. spol. beta = beta
	217		The same as Linear_nD, but defined via
	218		beta in sense of reliability index
	219		"""
	220		def __init__(self, beta_exact):
	221		self._beta_exact = beta_exact
	222
	223		# sign
	224		def __repr__(self):
	225		return 'X1(%s)' % repr(self._beta_exact)
	226
	227		def __call__(self, input_sample):
	228		# očekávam, že get_R_coordinates mně vrátí 2D pole
	229		sample = get_R_coordinates(input_sample)
	230		g = -np.abs(sample[:, 0]) + self._beta_exact
	231		return SampleBox(input_sample, g, repr(self))
	232
	233		# Fence off!
	234		def get_2D_R_boundary(self, nrod=100, xlim=(-5,5), ylim=(-5,5), *args):
	235		"""
	236		Fence off!
	237		nrod - number of rods in fencing
	238		"""
	239
	240		bound_R = np.empty((nrod, 2))
	241		bound_R[:, 0] = self._beta_exact
	242		bound_R[:, 1] = np.linspace(ylim[0], ylim[1], nrod, endpoint=True)
	243		# tuple of tuple
	244		return (Ingot(bound_R), Ingot(-bound_R))
	245
	246
179	247	class Z_sum:	class Z_sum:
180	248	"""	"""
181	249	suma velicin plus beta*sqrt(Nvar. )	suma velicin plus beta*sqrt(Nvar. )

File wellmet/testcases/testcases_nD.py changed (mode: 100644) (index 4600f59..63ffbe6)
...	...	def snorm_neverfall(ndim):
30	30	return whitebox.WhiteBox(f_models.SNorm(ndim), gm.neverfall)	return whitebox.WhiteBox(f_models.SNorm(ndim), gm.neverfall)
31	31
32	32
	33		add('snorm_line_pf6')
	34		def snorm_line_pf6(ndim):
	35		return whitebox.Line(ndim, -stats.norm.ppf(1e-6))
	36
	37		add('snorm_twoline_pf6')
	38		def snorm_twoline_pf6(ndim):
	39		return whitebox.TwoLine(ndim, -stats.norm.ppf(1e-6 / 2))
	40
	41
33	42	# HyperRovina, куда ж без неё?	# HyperRovina, куда ж без неё?
34	43	# Gauß	# Gauß
35	44	add('hyperplane_pf3')	add('hyperplane_pf3')

File wellmet/whitebox.py changed (mode: 100644) (index 3699614..9b87bb9)
...	...	class HyperPlane(WhiteBox): # куда ж без него...
287	287
288	288	def __repr__(wt):	def __repr__(wt):
289	289	return 'HyperPlane(%s)' % repr(wt._betas)	return 'HyperPlane(%s)' % repr(wt._betas)
	290
	291
	292		class Line(WhiteBox):
	293		def __init__(self, nvar=2, beta=5):
	294		"""
	295		Class takes for inicialization tuple of betas
	296		Betas are coeffitients in sense of Regression Analysis (well, not really)
	297		g= aX1 + bX2 + c
	298		betas=(a,b,c)
	299		"""
	300		self.beta_exact = beta
	301		self.gm = g_models.X1(beta)
	302		self.f = f_models.SNorm(nvar)
	303		# na začatku nemáme vzorky - pouze rozdělení a podpís
	304		self.sample_box = SampleBox(self.f(), gm_signature=self.gm_signature)
	305
	306		self.pf_exact = stats.norm.cdf(-beta)
	307		self.pf_exact_method = 'FORM (exact solution)' # Ang, Tang and Pythagoras
	308
	309
	310		def __str__(wt):
	311		return 'Line%sD' % wt.f.nvar
	312
	313		def __repr__(wt):
	314		return 'Line(%s, %s)' % repr(wt.f.nvar, wt.beta_exact)
	315
	316		class TwoLine(WhiteBox):
	317		def __init__(self, nvar=2, beta=5):
	318		"""
	319		Class takes for inicialization tuple of betas
	320		Betas are coeffitients in sense of Regression Analysis (well, not really)
	321		g= aX1 + bX2 + c
	322		betas=(a,b,c)
	323		"""
	324		self.beta = beta
	325		self.gm = g_models.AbsX1(beta)
	326		self.f = f_models.SNorm(nvar)
	327		# na začatku nemáme vzorky - pouze rozdělení a podpís
	328		self.sample_box = SampleBox(self.f(), gm_signature=self.gm_signature)
	329
	330		self.pf_exact = stats.norm.cdf(-beta) * 2
	331		self.pf_exact_method = '2FORM (exact solution)' # Ang, Tang and Pythagoras
	332
	333
	334		def __str__(wt):
	335		return 'TwoLine%sD' % wt.f.nvar
	336
	337		def __repr__(wt):
	338		return 'TwoLine(%s, %s)' % repr(wt.f.nvar, wt.beta)
290	339
291	340
292	341	class Gaussian_Z_sum(WhiteBox): #ё куда ж без этого...	class Gaussian_Z_sum(WhiteBox): #ё куда ж без этого...

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