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".
List of commits:
Subject Hash Author Date (UTC)
sball.Shell.rvs(): inverse linspace (wouldn't produce NaNs) 58452888a47230ab30c56bc33f5e3c780e60c752 I am 2021-04-18 03:26:21
convex_hull: move QHull from simplex module e5c67ce54fa4c9f3ce15714ebeff7d363d918494 I am 2021-04-17 19:04:00
schemes: comment out dups 8d22480a42926c3a78e62a07be4418e1f8ba350f I am 2021-04-16 23:35:53
convex_hull: split DirectHull into simplified DirectHull itself and CompleteHull b109bbdc325a2a88bf22e9893fa162690bf190f9 I am 2021-04-16 23:26:03
rework convex hull 60185dce0403ba941e849a60b5e43da6ce1fffd4 I am 2021-04-12 17:09:25
sball: add .get_random_directions() function d41131f28937e40eb853a30047de3cfc43cf5fa8 I am 2021-03-24 03:24:41
mplot: plot2D swithed to matplotlib 366326fb53bcbc54d7e6fb108b9dc256833bf679 I am 2021-03-18 01:44:07
three-ways image WIP a2987cde393c4e795342f6dc40d5920760b468d4 I am 2021-03-17 16:37:18
Ghull is ready e1a49fe0cb390ce9664e8f892c1da6d30231cc99 I am 2021-03-16 14:29:09
simplex: finish Ghull 5cb6d06a1c77cdb0cc1d3e83cfb217924b2345f1 I am 2021-03-03 23:06:13
simplex.Ghull: WIP 043724e7d4fe0c25ac698becf6498bc2abb8bf29 I am 2021-03-03 17:06:08
sball: je naimplementována třída Shell b335ba64be48582ca2f31baf035d0f5c6c75090c I am 2021-03-03 13:45:02
sball: new gamma-based solution. Keep the old version as well b6ac51b6b08ca2e7d5c398fa56c5a9a0832ab301 I am 2021-02-24 10:55:11
mart: add convergence plot 85a9ef727d15fc6567b7b0a594ed52cef9fe5680 I am 2021-02-22 23:32:34
mart: add basic plot and scatter functions 20e04c27db7ee3ac3a6418300eb4fc1ef532a1c7 I am 2021-02-22 14:45:31
mart: add convex hull related functions 5284e4c1c747fe25d220e7e3a6a9803d8bc6d4a1 I am 2021-02-21 20:57:52
axes3d_: draw only bottom pane 5a24020e052a7adbc17485b4c9c74d7eea801765 Alex 2021-02-12 20:50:09
mart3d: tri surface fix 2f1889070cea6c97937e00d76ce029744c9f8d07 Alex 2021-02-12 10:01:59
mart3d: add plot_wireframe 8b21a8ca659e4f2146459ea5f4cc006535f51308 I am 2021-02-12 04:45:56
mart and mart3d: add new functions fdbfd002214bf7ab7be8df8e90d6b96b62c82d13 I am 2021-02-10 17:18:02
Commit 58452888a47230ab30c56bc33f5e3c780e60c752 - sball.Shell.rvs(): inverse linspace (wouldn't produce NaNs)
Author: I am
Author date (UTC): 2021-04-18 03:26
Committer name: I am
Committer date (UTC): 2021-04-18 03:26
Parent(s): e5c67ce54fa4c9f3ce15714ebeff7d363d918494
Signer:
Signing key:
Signing status: N
Tree: c7043ab58926a8d4d82cf5c2d228ad4367892a35
File Lines added Lines deleted
sball.py 2 2
File sball.py changed (mode: 100644) (index a952106..90f4252)
... ... class Shell(Radial):
163 163 # rand_dir: prepare ns random directions on a unit d-sphere # rand_dir: prepare ns random directions on a unit d-sphere
164 164 rand_dir = get_random_directions(ns, self.sball.nvar) #random directions rand_dir = get_random_directions(ns, self.sball.nvar) #random directions
165 165
166 #generate random dampling probabilites
167 p = np.linspace(0, 1, ns, endpoint=False) # probabilities for the radius
166 # generate sampling probabilites
167 p = np.linspace(1, 0, ns, endpoint=False) # probabilities for the radius
168 168
169 169 # convert probabilitites into random radii # convert probabilitites into random radii
170 170 # (distances from origin that are greater than r and less than R) # (distances from origin that are greater than r and less than R)
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