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)
g_models: fix quartic name, add parabola b80e98134d7a5c91ad9e44ad9b58e76ac0a3bb64 I am 2023-05-31 16:54:39
qt_gui.qt_gui: little tweaks 73c027858135753f99d2eabb3f080e936c4ff18d I am 2023-05-30 16:53:59
reader forgets Udmurt, learns English instead :'( 640ac860613b0d93fc037490c3a02da251eb8aca I am 2023-05-30 15:23:31
testcases: add __init__ file 0b942cd9028c3c5baea43aff61526b75c2f3ee43 I am 2023-05-28 14:04:55
mplot: add quiver plots a32b3d850fef99d6798b778140867416e17c16db I am 2023-03-30 13:21:30
mplot.mart: add simplex_vectors() function 7a90003e40bd459d2a3ef45a4867dfa392bd3fc8 I am 2023-03-30 13:20:10
simplex: use shares instead of probabilities in sinsitivity analysis 75ff4258b95fd568d1b4d163cdc04d40952e0029 I am 2023-03-16 18:46:44
whitebox.get_sensitivities: mask nans and infinities 1a754c51b3a1ef535e86b5b4cb6b75fe9e90840f I am 2023-03-14 22:33:52
simplex.SeparationAxis: fix previous commit 61abd70e69d2fecd74535738c96e74a634af0ad1 I am 2023-03-12 16:49:22
simplex.SeparationAxis: print linprog solution in case of an unexpected status af1aaac1dce3fbc51dc48418685d948a27cf72c6 I am 2023-03-12 15:18:07
g_models: add hyperbola LSF 5f6df35b4280a11c0df1d3cd110250305805ce66 I am 2023-03-12 15:07:20
simplex._Sense: implement piece of postprocessing to get unique vectors 4088852e703947643a8388b2ba8839a694211566 I am 2023-03-10 17:22:29
simplex.SeparationAxis: in case of an unexpected linprog status print result message too 1c9346233693533afb07022c78308b3be6ea9ec7 I am 2023-03-10 15:40:06
whitebox: implement method to .get_sensitivities() from 2D boundary 5729723cfe5c93658c3739fbfec384e135b44073 I am 2023-03-09 22:14:27
simplex.SeparationAxis: make an perfectionism-driven change 8278c48915c326e7731f1934732550c5b9c18e64 I am 2023-03-09 21:51:18
simplex.SeparationAxis: little fix for an hypotetical issue 838e476387c31f9c6847cf7ae8a2a01514038a03 I am 2023-03-09 15:19:48
simplex._Sense: bugfix 3ae53e8b178107b8beb6ad960ec683c8d38a3b3c I am 2023-03-07 23:23:36
simplex._Sense: totally rework, finalized vectors are introduced 829ba58a93481541a58cd4a9f6dae0ba9fb611c6 I am 2023-03-07 13:33:38
simplex: preliminary commit of an _Sense's auxiliary class - brand new SeparationAxis c0bbb714400df48abf7a398e018c5626803bf024 I am 2023-03-04 10:17:12
simplex._Sense: one more optimization a51f4ba65ad4a55ecc74fd82a6e011a4eeed8a5d I am 2023-02-26 15:21:23
Commit b80e98134d7a5c91ad9e44ad9b58e76ac0a3bb64 - g_models: fix quartic name, add parabola
Author: I am
Author date (UTC): 2023-05-31 16:54
Committer name: I am
Committer date (UTC): 2023-05-31 16:54
Parent(s): 73c027858135753f99d2eabb3f080e936c4ff18d
Signer:
Signing key:
Signing status: N
Tree: 81fa9dc2ac957a2e2ce64118da56113a5baa6199
File Lines added Lines deleted
wellmet/g_models.py 34 4
File wellmet/g_models.py changed (mode: 100644) (index 9043bae..545c204)
... ... class PassiveVehicleSuspension:
1161 1161 # #
1162 1162
1163 1163
1164 def quadratic(input_sample):
1164
1165 def parabola_2D(input_sample):
1166 # očekávam, že get_R_coordinates mně vrátí 2D pole
1167 sample = gm.get_R_coordinates(input_sample)
1168 X, Y = sample.T
1169 g = - Y + 2.5 + 10.1*(X-1)**2
1170 return SampleBox(input_sample, g, 'parabola_2D')
1171
1172 def parabola_boundary(nrod=100, xlim=(-5,5), *args):
1173 """
1174 Fence off!
1175 nrod - number of rods in fencing
1176 """
1177
1178 xbound = np.linspace(xlim[0], xlim[1], nrod, endpoint=True)
1179
1180 bound_y = 10.1*(xbound-1)**2 + 2.5
1181
1182 # sample compatible
1183 # малы транспонировать кароно? Озьы кулэ!
1184 bound_R = np.array((xbound, bound_y)).T
1185 # tuple of samples
1186 return (f_models.Ingot(bound_R),)
1187
1188
1189 parabola_2D.get_2D_R_boundary = parabola_boundary
1190
1191
1192
1193
1194 def quartic(input_sample):
1165 1195 selfnvar = 2 selfnvar = 2
1166 1196 # očekávam, že get_R_coordinates mně vrátí 2D pole # očekávam, že get_R_coordinates mně vrátí 2D pole
1167 1197 sample = get_R_coordinates(input_sample, selfnvar) sample = get_R_coordinates(input_sample, selfnvar)
1168 1198 x1, x2 = sample[:,0], sample[:,1] x1, x2 = sample[:,0], sample[:,1]
1169 1199 g = 3 - x1**4/33 - x2 g = 3 - x1**4/33 - x2
1170 return SampleBox(input_sample, g, 'quadratic')
1200 return SampleBox(input_sample, g, 'quartic')
1171 1201
1172 def quadratic_R_boundary(nrod=210, xlim=(-5,5), *args):
1202 def quartic_R_boundary(nrod=210, xlim=(-5,5), *args):
1173 1203 boundaries = [] boundaries = []
1174 1204 x_min, x_max = xlim x_min, x_max = xlim
1175 1205 x1 = np.linspace(x_min, x_max, nrod, endpoint=True) x1 = np.linspace(x_min, x_max, nrod, endpoint=True)
 
... ... def quadratic_R_boundary(nrod=210, xlim=(-5,5), *args):
1179 1209 boundaries.append(Ingot(bound_R_1)) boundaries.append(Ingot(bound_R_1))
1180 1210 return boundaries return boundaries
1181 1211
1182 quadratic.get_2D_R_boundary = quadratic_R_boundary
1212 quartic.get_2D_R_boundary = quartic_R_boundary
1183 1213
1184 1214
1185 1215
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