GitHub Actions build openturns/otbenchmark 10990125294

openturns · Sep 23, 2024 · 1c2dc79 · 1c2dc79
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diff --git a/.../_downloads/011e9011be6c44d1edb1eaeb85a11c55/plot_sensitivity_distribution_ishigami.ipynb b/.../_downloads/011e9011be6c44d1edb1eaeb85a11c55/plot_sensitivity_distribution_ishigami.ipynb
@@ -78,6 +78,28 @@
       "source": [
         "The plot compare two distributions.\n\n- The \"Computed\" distribution is the one computed by OpenTURNS.\n- The \"Sample\" distribution is the one generated by Monte-Carlo sampling.\n\nThe fact that the \"Computed\" distribution is not centered on the true value is an\nexpected property of the way the distribution is computed.\nWhat must be checked, instead, is the the variance of the distribution.\nMore precisely, we check that the asymptotic covariance is correctly computed by the library.\nIn other words, we focus on the spread of the distribution and check that it is consistent with the actual spread.\nThis comparison is, however, restricted by the fact that the re-sampling size has a limited size\nequal to the `numberOfRepetitions` parameter. Increasing this parameter allows the check to be more accurate,\nbut increases the simulation elapsed time.\n\nWe see that these distributions are never far away from each other.\nThis proves that the computation of the distribution is correct, for both the asymptotic and bootstrap options.\n\n"
       ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "otv.View.ShowAll()"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "ot.ResourceMap.Reload()"
+      ]
     }
   ],
   "metadata": {

diff --git a/...mark/master/_downloads/02ebaaff0fbfc2d6c398818b1ca6b2f8/plot_nloscillator_sensitivity.zip b/...mark/master/_downloads/02ebaaff0fbfc2d6c398818b1ca6b2f8/plot_nloscillator_sensitivity.zip
diff --git a/otbenchmark/master/_downloads/07fcc19ba03226cd3d83d4e40ec44385/auto_examples_python.zip b/otbenchmark/master/_downloads/07fcc19ba03226cd3d83d4e40ec44385/auto_examples_python.zip
diff --git a/...nchmark/master/_downloads/09a8c2ecba196a7145cf5887e3bfbf39/plot_dirichlet_sensitivity.zip b/...nchmark/master/_downloads/09a8c2ecba196a7145cf5887e3bfbf39/plot_dirichlet_sensitivity.zip
diff --git a/otbenchmark/master/_downloads/0b4d0577810c77038fc3a798767a76ea/plot_flood_sensitivity.zip b/otbenchmark/master/_downloads/0b4d0577810c77038fc3a798767a76ea/plot_flood_sensitivity.zip
diff --git a/otbenchmark/master/_downloads/0cd6cd41d72a62b46520ec1e64ebcbe3/plot_drawevent.zip b/otbenchmark/master/_downloads/0cd6cd41d72a62b46520ec1e64ebcbe3/plot_drawevent.zip
diff --git a/...mark/master/_downloads/0ee134db52089df8699dbb596527cd27/plot_crosscut_distribution_2d.zip b/...mark/master/_downloads/0ee134db52089df8699dbb596527cd27/plot_crosscut_distribution_2d.zip
diff --git a/otbenchmark/master/_downloads/14a1d6597b0093114c7f5fe62404859d/plot_case_rs.zip b/otbenchmark/master/_downloads/14a1d6597b0093114c7f5fe62404859d/plot_case_rs.zip
diff --git a/otbenchmark/master/_downloads/153905a1bfbf5b34cc296fa934c143aa/plot_rp8.zip b/otbenchmark/master/_downloads/153905a1bfbf5b34cc296fa934c143aa/plot_rp8.zip
diff --git a/...rk/master/_downloads/177f69a01b2091371b1393b3784ee85e/plot_convergence_reliability_mc.zip b/...rk/master/_downloads/177f69a01b2091371b1393b3784ee85e/plot_convergence_reliability_mc.zip
diff --git a/otbenchmark/master/_downloads/1e8c14dcab49e0991ed329fca8991db3/plot_rp57.zip b/otbenchmark/master/_downloads/1e8c14dcab49e0991ed329fca8991db3/plot_rp57.zip
diff --git a/otbenchmark/master/_downloads/23220fd0e4f67e58999879308536164b/plot_rp35.zip b/otbenchmark/master/_downloads/23220fd0e4f67e58999879308536164b/plot_rp35.zip
diff --git a/otbenchmark/master/_downloads/25b0a3b7859426727b8a42df70ce7774/plot_rp22.zip b/otbenchmark/master/_downloads/25b0a3b7859426727b8a42df70ce7774/plot_rp22.zip
diff --git a/otbenchmark/master/_downloads/25e8c1857957286ba5590935942ebdbc/plot_rp53.zip b/otbenchmark/master/_downloads/25e8c1857957286ba5590935942ebdbc/plot_rp53.zip
diff --git a/...ter/_downloads/2ac0b6da649c5a5611308c5bf7215304/plot_sensitivity_distribution_ishigami.py b/...ter/_downloads/2ac0b6da649c5a5611308c5bf7215304/plot_sensitivity_distribution_ishigami.py
@@ -123,3 +123,9 @@
 #
 # We see that these distributions are never far away from each other.
 # This proves that the computation of the distribution is correct, for both the asymptotic and bootstrap options.
+
+# %%
+otv.View.ShowAll()
+
+# %%
+ot.ResourceMap.Reload()
diff --git a/otbenchmark/master/_downloads/31c3dc71daca0ff913405757a374df54/plot_rp111.zip b/otbenchmark/master/_downloads/31c3dc71daca0ff913405757a374df54/plot_rp111.zip
diff --git a/...nchmark/master/_downloads/32aa5c9dcce0dccc2e928a569709118d/plot_reliability_benchmark.zip b/...nchmark/master/_downloads/32aa5c9dcce0dccc2e928a569709118d/plot_reliability_benchmark.zip
diff --git a/...k/master/_downloads/33016ce92fb2acd4d1511228541ab561/plot_print_reliability_benchmark.zip b/...k/master/_downloads/33016ce92fb2acd4d1511228541ab561/plot_print_reliability_benchmark.zip
diff --git a/otbenchmark/master/_downloads/3b7d7d1e5ac85f5851d053b621d84d4d/plot_draw_cross_cuts.zip b/otbenchmark/master/_downloads/3b7d7d1e5ac85f5851d053b621d84d4d/plot_draw_cross_cuts.zip
diff --git a/otbenchmark/master/_downloads/3f2f5008640b2a9bf5fb56d17e3345fe/plot_gsobol_sensitivity.zip b/otbenchmark/master/_downloads/3f2f5008640b2a9bf5fb56d17e3345fe/plot_gsobol_sensitivity.zip
diff --git a/otbenchmark/master/_downloads/546015264311e3d42fe9b9adf5f7d337/plot_rp55.zip b/otbenchmark/master/_downloads/546015264311e3d42fe9b9adf5f7d337/plot_rp55.zip
diff --git a/otbenchmark/master/_downloads/59eec10882101a6404142d6b65774fb1/plot_rp89.zip b/otbenchmark/master/_downloads/59eec10882101a6404142d6b65774fb1/plot_rp89.zip
diff --git a/otbenchmark/master/_downloads/5fab7882172318ff3e3ffcf48ef9eddf/plot_ishigami_sensitivity.zip b/otbenchmark/master/_downloads/5fab7882172318ff3e3ffcf48ef9eddf/plot_ishigami_sensitivity.zip
diff --git a/otbenchmark/master/_downloads/629687dd8581020f5bdda375e12cf702/plot_gaussian_sum.zip b/otbenchmark/master/_downloads/629687dd8581020f5bdda375e12cf702/plot_gaussian_sum.zip
diff --git a/otbenchmark/master/_downloads/6627dfa18643515b598adfd9222193ac/plot_rp31.zip b/otbenchmark/master/_downloads/6627dfa18643515b598adfd9222193ac/plot_rp31.zip
diff --git a/otbenchmark/master/_downloads/66b4d9d63c28c108996cfe858ca9289e/plot_morris_sensitivity.zip b/otbenchmark/master/_downloads/66b4d9d63c28c108996cfe858ca9289e/plot_morris_sensitivity.zip
diff --git a/otbenchmark/master/_downloads/6b55e1d416c35886a31041a6892cb0f0/plot_borehole_sensitivity.zip b/otbenchmark/master/_downloads/6b55e1d416c35886a31041a6892cb0f0/plot_borehole_sensitivity.zip
diff --git a/otbenchmark/master/_downloads/6cd33e5b383cf8880ecd7227f3faa76a/plot_lognormal_bbrc.zip b/otbenchmark/master/_downloads/6cd33e5b383cf8880ecd7227f3faa76a/plot_lognormal_bbrc.zip
diff --git a/otbenchmark/master/_downloads/6f1e7a639e0699d6164445b55e6c116d/auto_examples_jupyter.zip b/otbenchmark/master/_downloads/6f1e7a639e0699d6164445b55e6c116d/auto_examples_jupyter.zip
diff --git a/otbenchmark/master/_downloads/708113975e29ad6b539ace5031c620f7/plot_rp110.zip b/otbenchmark/master/_downloads/708113975e29ad6b539ace5031c620f7/plot_rp110.zip
diff --git a/otbenchmark/master/_downloads/70b5b02a8766a34d43ea534a7ac293dc/plot_rp25.zip b/otbenchmark/master/_downloads/70b5b02a8766a34d43ea534a7ac293dc/plot_rp25.zip
diff --git a/otbenchmark/master/_downloads/77f4ae231a2201d1efcd30eb9d002a15/plot_rp33.zip b/otbenchmark/master/_downloads/77f4ae231a2201d1efcd30eb9d002a15/plot_rp33.zip
diff --git a/otbenchmark/master/_downloads/7f13a44954884297d4db857bec1ecd92/plot_convergence_ishigami.zip b/otbenchmark/master/_downloads/7f13a44954884297d4db857bec1ecd92/plot_convergence_ishigami.zip
diff --git a/...ark/master/_downloads/8913ec89943b0659c1ae0097203f49c7/plot_compute_reference_rp55_pf.zip b/...ark/master/_downloads/8913ec89943b0659c1ae0097203f49c7/plot_compute_reference_rp55_pf.zip
diff --git a/...ter/_downloads/8ae7a687d57e744b373533a12150bbe4/plot_four_branch_serial_system_waarts.zip b/...ter/_downloads/8ae7a687d57e744b373533a12150bbe4/plot_four_branch_serial_system_waarts.zip
diff --git a/...k/master/_downloads/919d5c34833f060a914b578a7d4532cf/plot_reliability_benchmark_table.zip b/...k/master/_downloads/919d5c34833f060a914b578a7d4532cf/plot_reliability_benchmark_table.zip
diff --git a/...nchmark/master/_downloads/91f30700716a0dd0a964e349dc44e117/plot_borgonovo_sensitivity.zip b/...nchmark/master/_downloads/91f30700716a0dd0a964e349dc44e117/plot_borgonovo_sensitivity.zip
diff --git a/...master/_downloads/966aab35daf3bdeee31dc59712af12c7/plot_benchmark_sensitivity_methods.zip b/...master/_downloads/966aab35daf3bdeee31dc59712af12c7/plot_benchmark_sensitivity_methods.zip
diff --git a/...er/_downloads/978bfcc2a9ccf5ee5332e5f49dc6a141/plot_sensitivity_distribution_ishigami.zip b/...er/_downloads/978bfcc2a9ccf5ee5332e5f49dc6a141/plot_sensitivity_distribution_ishigami.zip
diff --git a/.../master/_downloads/9aafdbfee23b48eed34e7b7fb324d32a/plot_gaussian_product_sensitivity.zip b/.../master/_downloads/9aafdbfee23b48eed34e7b7fb324d32a/plot_gaussian_product_sensitivity.zip
diff --git a/otbenchmark/master/_downloads/9d2407fb1198b3186740d02d8b228f2c/plot_rp28.zip b/otbenchmark/master/_downloads/9d2407fb1198b3186740d02d8b228f2c/plot_rp28.zip
diff --git a/otbenchmark/master/_downloads/ac7f9588f6e96062e9b2eba7b462a673/plot_uncecomp_ot_examples.py b/otbenchmark/master/_downloads/ac7f9588f6e96062e9b2eba7b462a673/plot_uncecomp_ot_examples.py
@@ -183,3 +183,6 @@
 result = algoMC.getResult()
 probability = result.getProbabilityEstimate()
 print("Pf = ", probability)
+
+# %%
+otv.View.ShowAll()
diff --git a/otbenchmark/master/_downloads/ad5bee7bb2be8690218baf3dfdd87f39/plot_crosscut_function.zip b/otbenchmark/master/_downloads/ad5bee7bb2be8690218baf3dfdd87f39/plot_crosscut_function.zip
diff --git a/otbenchmark/master/_downloads/ba720b6b316a0c59544950e9ab67c9dd/plot_rp75.zip b/otbenchmark/master/_downloads/ba720b6b316a0c59544950e9ab67c9dd/plot_rp75.zip
diff --git a/.../_downloads/c6c993e0e01873a6ba6c365bffae93ed/plot_reliability_compute_reference_proba.zip b/.../_downloads/c6c993e0e01873a6ba6c365bffae93ed/plot_reliability_compute_reference_proba.zip
diff --git a/...loads/cea39a76e1f090175bed354fb16c89b5/plot_check_reliability_reference_probabilities.zip b/...loads/cea39a76e1f090175bed354fb16c89b5/plot_check_reliability_reference_probabilities.zip
diff --git a/otbenchmark/master/_downloads/d54ce2324b0b413ac3dffc378d3ed7a8/plot_methodFactory.zip b/otbenchmark/master/_downloads/d54ce2324b0b413ac3dffc378d3ed7a8/plot_methodFactory.zip
diff --git a/otbenchmark/master/_downloads/d7037057d5e03c98cd1142b69d0d0599/plot_rp24.zip b/otbenchmark/master/_downloads/d7037057d5e03c98cd1142b69d0d0599/plot_rp24.zip
diff --git a/...chmark/master/_downloads/ddac97da217abba2437f9a93a32fa7ad/plot_uncecomp_ot_examples.ipynb b/...chmark/master/_downloads/ddac97da217abba2437f9a93a32fa7ad/plot_uncecomp_ot_examples.ipynb
@@ -317,6 +317,17 @@
       "source": [
         "result = algoMC.getResult()\nprobability = result.getProbabilityEstimate()\nprint(\"Pf = \", probability)"
       ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "otv.View.ShowAll()"
+      ]
     }
   ],
   "metadata": {

diff --git a/otbenchmark/master/_downloads/e2b15a528a6607cd91fa376cbffc2002/plot_print_problems.zip b/otbenchmark/master/_downloads/e2b15a528a6607cd91fa376cbffc2002/plot_print_problems.zip
diff --git a/...mark/master/_downloads/e6be8e01cd20ccf3d5e4421802d81703/plot_crosscut_distribution_3d.zip b/...mark/master/_downloads/e6be8e01cd20ccf3d5e4421802d81703/plot_crosscut_distribution_3d.zip
diff --git a/...mark/master/_downloads/e9685936f0e9649b1b8ff6dcb9f0fc2b/plot_oakleyohagan_sensitivity.zip b/...mark/master/_downloads/e9685936f0e9649b1b8ff6dcb9f0fc2b/plot_oakleyohagan_sensitivity.zip
diff --git a/...hmark/master/_downloads/ec0ff8d4227300984974007a42210da0/plot_conditionaldistribution.zip b/...hmark/master/_downloads/ec0ff8d4227300984974007a42210da0/plot_conditionaldistribution.zip
diff --git a/otbenchmark/master/_downloads/f39cf51dedec1a2665fece4c28cd07db/plot_uncecomp_ot_examples.zip b/otbenchmark/master/_downloads/f39cf51dedec1a2665fece4c28cd07db/plot_uncecomp_ot_examples.zip
diff --git a/otbenchmark/master/_images/sphx_glr_plot_case_rs_004.png b/otbenchmark/master/_images/sphx_glr_plot_case_rs_004.png
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diff --git a/otbenchmark/master/_images/sphx_glr_plot_compute_reference_rp55_pf_001.png b/otbenchmark/master/_images/sphx_glr_plot_compute_reference_rp55_pf_001.png
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diff --git a/otbenchmark/master/_images/sphx_glr_plot_convergence_ishigami_004.png b/otbenchmark/master/_images/sphx_glr_plot_convergence_ishigami_004.png
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diff --git a/otbenchmark/master/_images/sphx_glr_plot_convergence_reliability_mc_001.png b/otbenchmark/master/_images/sphx_glr_plot_convergence_reliability_mc_001.png
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diff --git a/otbenchmark/master/_images/sphx_glr_plot_sensitivity_distribution_ishigami_002.png b/otbenchmark/master/_images/sphx_glr_plot_sensitivity_distribution_ishigami_002.png
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diff --git a/otbenchmark/master/_images/sphx_glr_plot_sensitivity_distribution_ishigami_029.png b/otbenchmark/master/_images/sphx_glr_plot_sensitivity_distribution_ishigami_029.png
diff --git a/otbenchmark/master/_images/sphx_glr_plot_sensitivity_distribution_ishigami_030.png b/otbenchmark/master/_images/sphx_glr_plot_sensitivity_distribution_ishigami_030.png
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diff --git a/otbenchmark/master/_images/sphx_glr_plot_sensitivity_distribution_ishigami_032.png b/otbenchmark/master/_images/sphx_glr_plot_sensitivity_distribution_ishigami_032.png
diff --git a/...chmark/master/_images/sphx_glr_plot_sensitivity_distribution_ishigami_thumb.png b/...chmark/master/_images/sphx_glr_plot_sensitivity_distribution_ishigami_thumb.png
diff --git a/otbenchmark/master/_images/sphx_glr_plot_uncecomp_ot_examples_001.png b/otbenchmark/master/_images/sphx_glr_plot_uncecomp_ot_examples_001.png
diff --git a/otbenchmark/master/_images/sphx_glr_plot_uncecomp_ot_examples_002.png b/otbenchmark/master/_images/sphx_glr_plot_uncecomp_ot_examples_002.png
diff --git a/otbenchmark/master/_images/sphx_glr_plot_uncecomp_ot_examples_003.png b/otbenchmark/master/_images/sphx_glr_plot_uncecomp_ot_examples_003.png
diff --git a/otbenchmark/master/_images/sphx_glr_plot_uncecomp_ot_examples_004.png b/otbenchmark/master/_images/sphx_glr_plot_uncecomp_ot_examples_004.png
diff --git a/otbenchmark/master/_images/sphx_glr_plot_uncecomp_ot_examples_005.png b/otbenchmark/master/_images/sphx_glr_plot_uncecomp_ot_examples_005.png
diff --git a/otbenchmark/master/_images/sphx_glr_plot_uncecomp_ot_examples_thumb.png b/otbenchmark/master/_images/sphx_glr_plot_uncecomp_ot_examples_thumb.png
diff --git a/...aster/_sources/auto_examples/plot_check_reliability_reference_probabilities.rst b/...aster/_sources/auto_examples/plot_check_reliability_reference_probabilities.rst
@@ -644,7 +644,7 @@ in absolute value, to the Monte-Carlo estimator.
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 0.246 seconds)
+   **Total running time of the script:** (0 minutes 0.498 seconds)
 
 
 .. _sphx_glr_download_auto_examples_plot_check_reliability_reference_probabilities.py:

diff --git a/otbenchmark/master/_sources/auto_examples/plot_conditionaldistribution.rst b/otbenchmark/master/_sources/auto_examples/plot_conditionaldistribution.rst
@@ -242,7 +242,7 @@ Create a Punk distribution
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 2.467 seconds)
+   **Total running time of the script:** (0 minutes 4.500 seconds)
 
 
 .. _sphx_glr_download_auto_examples_plot_conditionaldistribution.py:

diff --git a/otbenchmark/master/_sources/auto_examples/plot_convergence_reliability_mc.rst b/otbenchmark/master/_sources/auto_examples/plot_convergence_reliability_mc.rst
diff --git a/otbenchmark/master/_sources/auto_examples/plot_crosscut_distribution_2d.rst b/otbenchmark/master/_sources/auto_examples/plot_crosscut_distribution_2d.rst
@@ -152,7 +152,7 @@ Plot cross-cuts of the distribution
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 1.982 seconds)
+   **Total running time of the script:** (0 minutes 2.020 seconds)
 
 
 .. _sphx_glr_download_auto_examples_plot_crosscut_distribution_2d.py:

diff --git a/otbenchmark/master/_sources/auto_examples/plot_crosscut_distribution_3d.rst b/otbenchmark/master/_sources/auto_examples/plot_crosscut_distribution_3d.rst
@@ -146,7 +146,7 @@ Print the iso-values of the distribution
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 7.550 seconds)
+   **Total running time of the script:** (0 minutes 8.155 seconds)
 
 
 .. _sphx_glr_download_auto_examples_plot_crosscut_distribution_3d.py:

diff --git a/otbenchmark/master/_sources/auto_examples/plot_crosscut_function.rst b/otbenchmark/master/_sources/auto_examples/plot_crosscut_function.rst
@@ -213,7 +213,7 @@ Let :math:`\bar{x}\in\mathbb{R}^3` be the reference point.
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 1.100 seconds)
+   **Total running time of the script:** (0 minutes 1.145 seconds)
 
 
 .. _sphx_glr_download_auto_examples_plot_crosscut_function.py:

diff --git a/otbenchmark/master/_sources/auto_examples/plot_draw_cross_cuts.rst b/otbenchmark/master/_sources/auto_examples/plot_draw_cross_cuts.rst
@@ -359,7 +359,7 @@ See https://github.com/mbaudin47/otbenchmark/issues/47 for details.
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 10.372 seconds)
+   **Total running time of the script:** (0 minutes 10.592 seconds)
 
 
 .. _sphx_glr_download_auto_examples_plot_draw_cross_cuts.py:

diff --git a/otbenchmark/master/_sources/auto_examples/plot_drawevent.rst b/otbenchmark/master/_sources/auto_examples/plot_drawevent.rst
@@ -446,7 +446,7 @@ In this case, we can use the `drawInputOutputSample` method.
  .. code-block:: none
 
 
-    class=Graph name=Points X s.t. g(X) < 0.0 implementation=class=GraphImplementation name=Points X s.t. g(X) < 0.0 title=Points X s.t. g(X) < 0.0 xTitle=x1 yTitle=x2 axes=ON grid=ON legendposition=topright legendFontSize=1 drawables=[class=Drawable name=In implementation=class=Cloud name=In derived from class=DrawableImplementation name=In legend=In data=class=Sample name=Unnamed implementation=class=SampleImplementation name=Unnamed size=40 dimension=2 data=[[1.71237,2.85486],[1.66792,2.31783],[2.69441,1.34366],[1.86644,2.24982],[2.02031,1.92003],[1.37012,2.49056],[2.09796,1.7934],[1.51539,2.21068],[1.65414,2.24108],[2.38439,1.58069],[2.09313,1.52526],[1.88487,2.12252],[1.53307,3.17321],[3.35848,1.22148],[1.73253,2.64634],[2.53091,1.47052],[1.76564,1.90677],[2.22299,1.66299],[2.72437,1.52226],[1.87608,1.75339],[1.20151,2.79605],[1.61561,1.94388],[1.97895,2.3215],[1.45782,3.05815],[1.98593,1.87883],[2.16331,1.7884],[0.998138,3.66056],[2.15616,1.83874],[1.47851,2.3263],[2.55846,1.62646],[3.36152,1.47219],[2.65572,2.43453],[2.02096,1.72365],[1.94358,2.18157],[1.99646,2.14285],[3.05755,1.43522],[2.17683,2.15387],[1.77961,2.17732],[1.32333,3.19999],[2.03815,1.59132]] color=lightsalmon3 isColorExplicitlySet=true fillStyle=solid lineStyle=solid pointStyle=fsquare lineWidth=1,class=Drawable name=Out implementation=class=Cloud name=Out derived from class=DrawableImplementation name=Out legend=Out data=class=Sample name=Unnamed implementation=class=SampleImplementation name=Unnamed size=9960 dimension=2 data=[[-0.173501,-0.0297064],[-1.61099,1.88273],[0.280493,-1.76397],...,[-0.501814,-2.23713],[1.12524,0.218319],[-1.00681,0.0682829]] color=darkseagreen3 isColorExplicitlySet=true fillStyle=solid lineStyle=solid pointStyle=fsquare lineWidth=1]
+    class=Graph name=Points X s.t. g(X) < 0.0 implementation=class=GraphImplementation name=Points X s.t. g(X) < 0.0 title=Points X s.t. g(X) < 0.0 xTitle=x1 yTitle=x2 axes=ON grid=ON legendposition=topright legendFontSize=1 drawables=[class=Drawable name=In implementation=class=Cloud name=In derived from class=DrawableImplementation name=In legend=In data=class=Sample name=Unnamed implementation=class=SampleImplementation name=Unnamed size=48 dimension=2 data=[[1.75206,2.1331],[2.65402,1.25186],[3.05344,1.37844],[1.51339,2.51736],[2.54761,1.37642],[2.12316,2.55392],[2.9651,1.10725],[1.56455,2.53366],[1.25938,2.77634],[1.23662,2.82189],[2.59475,1.45159],[1.99746,2.53124],[2.14658,1.89942],[2.13898,1.76489],[2.80095,1.14849],[1.42333,2.50344],[1.99307,1.70834],[2.23565,2.336],[2.30481,2.06017],[2.76317,2.07778],[2.05894,1.8149],[2.06568,1.57253],[2.00174,1.65279],[1.83384,2.53628],[2.2881,1.73489],[1.22935,2.86777],[1.72694,2.19741],[2.66474,1.49464],[1.95762,1.64623],[2.33063,1.58673],[2.5289,1.45325],[1.91649,2.14158],[1.37821,2.3388],[1.32028,2.72169],[1.97745,1.67481],[2.35367,1.72189],[1.94211,2.20454],[2.44141,2.16931],[1.88873,1.90417],[3.05892,2.42918],[2.10954,2.835],[1.74686,1.89147],[1.31915,3.10624],[1.46469,2.3849],[2.32639,1.46009],[2.85151,1.6471],[2.47383,2.06196],[2.64109,1.62487]] color=lightsalmon3 isColorExplicitlySet=true fillStyle=solid lineStyle=solid pointStyle=fsquare lineWidth=1,class=Drawable name=Out implementation=class=Cloud name=Out derived from class=DrawableImplementation name=Out legend=Out data=class=Sample name=Unnamed implementation=class=SampleImplementation name=Unnamed size=9952 dimension=2 data=[[0.83378,-1.49686],[-1.03462,-0.611822],[2.66921,-0.140542],...,[1.3881,-0.559157],[-1.22664,0.216045],[0.683437,0.589782]] color=darkseagreen3 isColorExplicitlySet=true fillStyle=solid lineStyle=solid pointStyle=fsquare lineWidth=1]
 
 
 
@@ -465,7 +465,7 @@ In this case, we can use the `drawInputOutputSample` method.
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 7.739 seconds)
+   **Total running time of the script:** (0 minutes 9.512 seconds)
 
 
 .. _sphx_glr_download_auto_examples_plot_drawevent.py:

diff --git a/otbenchmark/master/_sources/auto_examples/plot_lognormal_bbrc.rst b/otbenchmark/master/_sources/auto_examples/plot_lognormal_bbrc.rst
@@ -453,7 +453,7 @@ This corresponds to the following code and comments:
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 0.240 seconds)
+   **Total running time of the script:** (0 minutes 0.293 seconds)
 
 
 .. _sphx_glr_download_auto_examples_plot_lognormal_bbrc.py:

diff --git a/otbenchmark/master/_sources/auto_examples/plot_methodFactory.rst b/otbenchmark/master/_sources/auto_examples/plot_methodFactory.rst
@@ -331,7 +331,7 @@ Create a LHS algorithm
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 9.459 seconds)
+   **Total running time of the script:** (0 minutes 5.246 seconds)
 
 
 .. _sphx_glr_download_auto_examples_plot_methodFactory.py:

diff --git a/otbenchmark/master/_sources/auto_examples/plot_uncecomp_ot_examples.rst b/otbenchmark/master/_sources/auto_examples/plot_uncecomp_ot_examples.rst
@@ -455,7 +455,7 @@ ThresholdEvent
 
 
 
-.. GENERATED FROM PYTHON SOURCE LINES 183-186
+.. GENERATED FROM PYTHON SOURCE LINES 183-187
 
 .. code-block:: Python
 
@@ -466,19 +466,32 @@ ThresholdEvent
 
 
 
+
 .. rst-class:: sphx-glr-script-out
 
  .. code-block:: none
 
-    Pf =  0.15821596244131447
+    Pf =  0.1497584541062803
+
+
+
+
+.. GENERATED FROM PYTHON SOURCE LINES 188-189
+
+.. code-block:: Python
+
+    otv.View.ShowAll()
+
+
+
 
 
 
 
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (1 minutes 35.870 seconds)
+   **Total running time of the script:** (1 minutes 40.251 seconds)
 
 
 .. _sphx_glr_download_auto_examples_plot_uncecomp_ot_examples.py:

diff --git a/otbenchmark/master/_sources/auto_examples/reliability_problems/plot_case_rs.rst b/otbenchmark/master/_sources/auto_examples/reliability_problems/plot_case_rs.rst
@@ -138,8 +138,8 @@ Get the results
  .. code-block:: none
 
     Number of function calls = 1000
-    Failure Probability = 0.0760
-    95.0 % confidence interval :[0.0596,0.0924] 
+    Failure Probability = 0.0880
+    95.0 % confidence interval :[0.0704,0.1056] 
 
 
 
@@ -438,7 +438,7 @@ Fill the event domain with a color
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 1.688 seconds)
+   **Total running time of the script:** (0 minutes 1.764 seconds)
 
 
 .. _sphx_glr_download_auto_examples_reliability_problems_plot_case_rs.py:

diff --git a/.../_sources/auto_examples/reliability_problems/plot_compute_reference_rp55_pf.rst b/.../_sources/auto_examples/reliability_problems/plot_compute_reference_rp55_pf.rst
@@ -418,9 +418,9 @@ From integration
       <tr><td></td><th>y0</th></tr>
       <tr><th>0</th><td>0.25</td></tr>
       <tr><th>1</th><td>0.25</td></tr>
-      <tr><th>2</th><td>0</td></tr>
-      <tr><th>3</th><td>0</td></tr>
-      <tr><th>4</th><td>0.25</td></tr>
+      <tr><th>2</th><td>0.25</td></tr>
+      <tr><th>3</th><td>0.25</td></tr>
+      <tr><th>4</th><td>0</td></tr>
     </table>
     </div>
     <br />
@@ -1049,7 +1049,7 @@ The area of each polygon is computed based on the shapely module.
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 3.622 seconds)
+   **Total running time of the script:** (0 minutes 3.814 seconds)
 
 
 .. _sphx_glr_download_auto_examples_reliability_problems_plot_compute_reference_rp55_pf.py:

diff --git a/...es/auto_examples/reliability_problems/plot_four_branch_serial_system_waarts.rst b/...es/auto_examples/reliability_problems/plot_four_branch_serial_system_waarts.rst
@@ -238,7 +238,7 @@ Fill the event domain with a color
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 1.156 seconds)
+   **Total running time of the script:** (0 minutes 1.355 seconds)
 
 
 .. _sphx_glr_download_auto_examples_reliability_problems_plot_four_branch_serial_system_waarts.py:

diff --git a/...sources/auto_examples/reliability_problems/plot_print_reliability_benchmark.rst b/...sources/auto_examples/reliability_problems/plot_print_reliability_benchmark.rst
@@ -261,7 +261,7 @@ Print a reliability benchmark problem
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 0.003 seconds)
+   **Total running time of the script:** (0 minutes 0.004 seconds)
 
 
 .. _sphx_glr_download_auto_examples_reliability_problems_plot_print_reliability_benchmark.py:

diff --git a/...ster/_sources/auto_examples/reliability_problems/plot_reliability_benchmark.rst b/...ster/_sources/auto_examples/reliability_problems/plot_reliability_benchmark.rst
@@ -246,7 +246,7 @@ The LHS method
  .. code-block:: none
 
 
-    'computedProbability = 0.0007000000000000013\nexactProbability = 0.0007897927545597477\nabsoluteError = 8.979275455974639e-05\nnumberOfCorrectDigits = 0.9442718507112124\nnumberOfFunctionEvaluations = 10000\nnumberOfDigitsPerEvaluation = 9.442718507112124e-05'
+    'computedProbability = 0.0006999999999999989\nexactProbability = 0.0007897927545597477\nabsoluteError = 8.979275455974877e-05\nnumberOfCorrectDigits = 0.9442718507112009\nnumberOfFunctionEvaluations = 10000\nnumberOfDigitsPerEvaluation = 9.442718507112009e-05'
 
 
 
@@ -271,7 +271,7 @@ The MonteCarloSampling method
  .. code-block:: none
 
 
-    'computedProbability = 0.0006999999999999989\nexactProbability = 0.0007897927545597477\nabsoluteError = 8.979275455974877e-05\nnumberOfCorrectDigits = 0.9442718507112009\nnumberOfFunctionEvaluations = 10000\nnumberOfDigitsPerEvaluation = 9.442718507112009e-05'
+    'computedProbability = 0.0006000000000000008\nexactProbability = 0.0007897927545597477\nabsoluteError = 0.00018979275455974687\nnumberOfCorrectDigits = 0.619233516283543\nnumberOfFunctionEvaluations = 10000\nnumberOfDigitsPerEvaluation = 6.192335162835429e-05'
 
 
 
@@ -296,7 +296,7 @@ The FORM - Importance Sampling method
  .. code-block:: none
 
 
-    'computedProbability = 0.0007629026630847465\nexactProbability = 0.0007897927545597477\nabsoluteError = 2.6890091475001193e-05\nnumberOfCorrectDigits = 1.4679208656529377\nnumberOfFunctionEvaluations = 380\nnumberOfDigitsPerEvaluation = 0.003862949646455099'
+    'computedProbability = 0.0007687158730375458\nexactProbability = 0.0007897927545597477\nabsoluteError = 2.1076881522201886e-05\nnumberOfCorrectDigits = 1.5737067909975317\nnumberOfFunctionEvaluations = 335\nnumberOfDigitsPerEvaluation = 0.004697632211932931'
 
 
 
@@ -321,7 +321,7 @@ The Subset method
  .. code-block:: none
 
 
-    'computedProbability = 0.0005690000000000008\nexactProbability = 0.0007897927545597477\nabsoluteError = 0.00022079275455974686\nnumberOfCorrectDigits = 0.5535283275966657\nnumberOfFunctionEvaluations = 4000\nnumberOfDigitsPerEvaluation = 0.00013838208189916642'
+    'computedProbability = 0.0007543799999999997\nexactProbability = 0.0007897927545597477\nabsoluteError = 3.541275455974798e-05\nnumberOfCorrectDigits = 1.3483534358601093\nnumberOfFunctionEvaluations = 4000\nnumberOfDigitsPerEvaluation = 0.00033708835896502734'
 
 
 
@@ -450,10 +450,10 @@ In addition, it returns the performance of these methods.
     Exact probability: 0.0007897927545597477
     ------------------------------------------------------------------
     SubsetSampling
-    Estimated probability: 0.0007430000000000004
+    Estimated probability: 0.0007590000000000005
     Number of function calls: 4000
-    Number of correct digits=1.2
-    Performance=3.07e-04 (correct digits/evaluation)
+    Number of correct digits=1.4
+    Performance=3.52e-04 (correct digits/evaluation)
     ------------------------------------------------------------------
     FORM
     Estimated probability: 0.000659887791408224
@@ -468,36 +468,36 @@ In addition, it returns the performance of these methods.
     Performance=2.65e-01 (correct digits/evaluation)
     ------------------------------------------------------------------
     FORM-IS
-    Estimated probability: 0.0008395999875129127
-    Number of function calls: 338
-    Number of correct digits=1.2
-    Performance=3.55e-03 (correct digits/evaluation)
+    Estimated probability: 0.0008521464618589394
+    Number of function calls: 362
+    Number of correct digits=1.1
+    Performance=3.05e-03 (correct digits/evaluation)
     ------------------------------------------------------------------
     MonteCarloSampling
-    Estimated probability: 0.0006999999999999957
+    Estimated probability: 0.0011000000000000005
     Number of function calls: 10000
-    Number of correct digits=0.9
-    Performance=9.44e-05 (correct digits/evaluation)
+    Number of correct digits=0.4
+    Performance=4.06e-05 (correct digits/evaluation)
     ------------------------------------------------------------------
     LHS
-    Estimated probability: 0.0
+    Estimated probability: 0.001999999999999997
     Number of function calls: 1000
     Number of correct digits=0.0
     Performance=0.00e+00 (correct digits/evaluation)
     ------------------------------------------------------------------------
     Scoring by number of correct digits
     5 : LHS (0.0)
+    4 : MonteCarloSampling (0.4)
     1 : FORM (0.8)
-    4 : MonteCarloSampling (0.9)
-    3 : FORM-IS (1.2)
-    0 : SubsetSampling (1.2)
+    3 : FORM-IS (1.1)
+    0 : SubsetSampling (1.4)
     2 : SORM (2.1)
     ------------------------------------------------------------------------
     Scoring by performance (digits/evaluation)
     5 : LHS (0.0e+00)
-    4 : MonteCarloSampling (9.4e-05)
-    0 : SubsetSampling (3.1e-04)
-    3 : FORM-IS (3.6e-03)
+    4 : MonteCarloSampling (4.1e-05)
+    0 : SubsetSampling (3.5e-04)
+    3 : FORM-IS (3.0e-03)
     1 : FORM (9.8e-02)
     2 : SORM (2.7e-01)
 
@@ -518,7 +518,7 @@ Remarks
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 2.735 seconds)
+   **Total running time of the script:** (0 minutes 1.466 seconds)
 
 
 .. _sphx_glr_download_auto_examples_reliability_problems_plot_reliability_benchmark.py: