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)
mart3d: add scatter_points() 26644c64e3b996b68e1ee133e4531380d4e00090 I am 2021-02-08 18:03:51
mart3d: new matplotlib-support module 8b6b13937a0694998e0b4de7b8a96d89abecc64a I am 2021-02-08 13:47:56
gmodels: increased no of discretization points in boundary for Pareto function 7f12597e2d15b2564d612a014fd75492663043dd Miroslav Vořechovský 2021-02-05 15:28:32
gmodels.py added boundary for Pareto function e7bc61e9c5854bc4cff0ee05b651b4b7ede4e0a1 Miroslav Vořechovský 2021-02-05 15:14:52
improved estimation of pf for Pareto Example 427602319f6a81e896b7aa50fd8947c5a1a91873 Miroslav Vořechovský 2021-02-05 14:15:41
dicebox.Razitko: little fixes 0e3f9147a40b7008ddec0893c3965136bac7fedf I am 2021-02-05 12:32:27
f_models.UnCorD.sample_pdf: Rn pdf fix 66cf81e4fc0bb2c6dab506cef5309c5da65a7f2c I am 2021-02-05 12:31:22
dicebox.Razitko: TRI_overall_estimations workaround 4b8146b788d0a857330c1894b5cf1c8d332103ce I am 2021-02-05 09:13:16
dicebox.Razitko: new DiceBox d9c1c9cdec94601bce9e81861ce1d4dfb5393481 I am 2021-02-05 08:04:28
simplex.Triangulation: little changes dc1efc3a081073d57be0f7a06330eb97f9634447 I am 2021-02-05 08:02:57
schemes: fix 126ba1c061474b3a9c02ce66d109ef6f8a39703a Alex 2021-02-03 08:28:28
schemes: new module af427a6a8c5e26f5b4a5930af188e40c882f9863 I am 2021-02-03 08:00:06
simplex: rework Triangulation, add FullCubatureTriangulation bdbb5a64a868cbf7c60d2bfeb8729e54bc81d347 I am 2021-02-03 05:14:32
dicebox: empty simplex fix 9b3b24a268a4d238ec6946f33d2c6ffe7d57dbfe Alex 2021-01-28 11:07:32
qt_plot.SimplexErrorGraph: finish 6fce1097d34c86c9b30c749e5b8cc2e4d8e7541d I am 2021-01-26 11:36:13
stm_df: finish get_tri_data_frame() 454bd2725a75f5a3f3851998693c4f85630fb30b I am 2021-01-22 20:43:36
stm_df: WIP bd99b8f3b8623a65c0bf0e3c22d9e67d8bce6a2c Alex 2021-01-21 15:27:11
stm_df: WIP f61a963c04764066bdd2bb9a363c51ec1c4fb389 Alex 2021-01-18 10:01:23
dicebox.Chrt: add design support 7426717fe5b3bbf299e44a92b2aca2672b752042 Alex 2021-01-15 09:30:28
design_proof_of_concept a1c9fc6ce6739e745382bdc1bfc6183a8c2a2f16 Alex 2021-01-14 22:58:01
Commit 26644c64e3b996b68e1ee133e4531380d4e00090 - mart3d: add scatter_points()
Author: I am
Author date (UTC): 2021-02-08 18:03
Committer name: I am
Committer date (UTC): 2021-02-08 18:03
Parent(s): 8b6b13937a0694998e0b4de7b8a96d89abecc64a
Signer:
Signing key:
Signing status: N
Tree: 9ed0a70862b861060849326ff8ea6e559a6ffe15
File Lines added Lines deleted
mart3d.py 35 0
File mart3d.py changed (mode: 100644) (index f8020af..3057cb4)
... ... def get_g_model_wireframe_data(shape_share, limits, space='R', ngrid=50):
42 42 # ax.space and ax.sample_box attributes should (expected to) be set up! # ax.space and ax.sample_box attributes should (expected to) be set up!
43 43
44 44
45 def scatter_points(ax3d, zs=None, **kwargs):
46 sample = getattr(ax3d.sample_box, ax3d.space)
47 nsim = len(sample)
48 if (zs is None) and (ax3d.sample_box.nvar == 2):
49 x, y = sample[:,:2].T
50 #zs = ax3d.sample_box.pdf(ax3d.space)
51 zs = ax3d.sample_box.g_values
52 elif zs is None:
53 x, y, zs = sample[:,:3].T
54
55 failsi = ax3d.sample_box.failsi
56
57 try: # proxy denotes to implicitly-known values
58 proxy = ax3d.sample_box.proxy
59 except AttributeError:
60 proxy = np.full(nsim, False, dtype=np.bool)
61
62
63 mask = np.all((~failsi, ~proxy), axis=0)
64 success = ax3d.scatter(x[mask], y[mask], zs=zs[mask], c='g', marker='P', **kwargs)
65
66 mask = np.all((failsi, ~proxy), axis=0)
67 failures = ax3d.scatter(x[mask], y[mask], zs=zs[mask], c='r', marker='X', **kwargs)
68
69 mask = np.all((~failsi, proxy), axis=0)
70 proxy_successes = ax3d.scatter(x[mask], y[mask], zs=zs[mask],\
71 c='#77AC30', marker='h', **kwargs)
72
73 mask = np.all((failsi, proxy), axis=0)
74 proxy_failures = ax3d.scatter(x[mask], y[mask], zs=zs[mask],\
75 c='#D95319', marker='H', **kwargs)
76
77 return success, failures, proxy_successes, proxy_failures
78
79
45 80 def limit_state_surface(ax3d, **kwargs): def limit_state_surface(ax3d, **kwargs):
46 81 xmin, xmax = ax3d.get_xlim() xmin, xmax = ax3d.get_xlim()
47 82 ymin, ymax = ax3d.get_ylim() ymin, ymax = ax3d.get_ylim()
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