GitHub Actions build openturns/otbenchmark 10943979829

otbenchmark/master/_downloads/018bebf23004eb4c852157b01b94c189/plot_borgonovo_sensitivity.ipynb

@@ -0,0 +1,235 @@
+{
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "\n# Benchmark the Borgonovo test function\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "import openturns as ot\nimport otbenchmark as otb\nimport openturns.viewer as otv"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "problem = otb.BorgonovoSensitivity()\nprint(problem)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "distribution = problem.getInputDistribution()\nmodel = problem.getFunction()"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "Exact first and total order\n\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "exact_first_order = problem.getFirstOrderIndices()\nexact_first_order"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "exact_total_order = problem.getTotalOrderIndices()\nexact_total_order"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## Plot the function\n\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "Create X/Y data\n\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "ot.RandomGenerator.SetSeed(0)\nsize = 200\ninputDesign = ot.MonteCarloExperiment(distribution, size).generate()\noutputDesign = model(inputDesign)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "dimension = distribution.getDimension()\nfull_sample = ot.Sample(size, 1 + dimension)\nfull_sample[:, range(dimension)] = inputDesign\nfull_sample[:, dimension] = outputDesign\nfull_description = list(inputDesign.getDescription())\nfull_description.append(outputDesign.getDescription()[0])\nfull_sample.setDescription(full_description)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "marginal_distribution = ot.ComposedDistribution(\n    [\n        ot.KernelSmoothing().build(full_sample.getMarginal(i))\n        for i in range(1 + dimension)\n    ]\n)\nclouds = ot.VisualTest.DrawPairsMarginals(full_sample, marginal_distribution)\n_ = otv.View(clouds, figure_kw={\"figsize\": (6.0, 6.0)})"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "output_distribution = ot.KernelSmoothing().build(outputDesign)\n_ = otv.View(output_distribution.drawPDF())"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## Perform sensitivity analysis\n\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "Create X/Y data\n\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "ot.RandomGenerator.SetSeed(0)\nsize = 10000\ninputDesign = ot.SobolIndicesExperiment(distribution, size).generate()\noutputDesign = model(inputDesign)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "Compute first order indices using the Saltelli estimator\n\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "sensitivityAnalysis = ot.SaltelliSensitivityAlgorithm(inputDesign, outputDesign, size)\ncomputed_first_order = sensitivityAnalysis.getFirstOrderIndices()\ncomputed_total_order = sensitivityAnalysis.getTotalOrderIndices()"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "Compare with exact results\n\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "print(\"Sample size : \", size)\n# First order\n# Compute absolute error (the LRE cannot be computed,\n# because S can be zero)\nprint(\"Computed first order = \", computed_first_order)\nprint(\"Exact first order = \", exact_first_order)\n# Total order\nprint(\"Computed total order = \", computed_total_order)\nprint(\"Exact total order = \", exact_total_order)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "_ = otv.View(sensitivityAnalysis.draw())"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "otv.View.ShowAll()"
+      ]
+    }
+  ],
+  "metadata": {
+    "kernelspec": {
+      "display_name": "Python 3",
+      "language": "python",
+      "name": "python3"
+    },
+    "language_info": {
+      "codemirror_mode": {
+        "name": "ipython",
+        "version": 3
+      },
+      "file_extension": ".py",
+      "mimetype": "text/x-python",
+      "name": "python",
+      "nbconvert_exporter": "python",
+      "pygments_lexer": "ipython3",
+      "version": "3.9.20"
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 0
+}