diff --git a/examples/RequestedBBRCProblem.ipynb b/examples/RequestedBBRCProblem.ipynb new file mode 100644 index 0000000..ae931a2 --- /dev/null +++ b/examples/RequestedBBRCProblem.ipynb @@ -0,0 +1,124 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# RequestedBBRCProblem class use case\n", + "\n", + "This example presents a simple use of the RequestedBBRCProblem class." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import openturns as ot\n", + "import otbenchmark as otb" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": "RP8\n" + } + ], + "source": [ + "problem = otb.RequestedBBRCProblem(\"testuser\", \"testpass\", -1, 1)\n", + "print(problem.name)" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "event = problem.getEvent()\n", + "g = event.getFunction()" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": "0.0007888456943755395" + }, + "metadata": {}, + "execution_count": 4 + } + ], + "source": [ + "problem.getProbability()" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "# Create the Monte-Carlo algorithm\n", + "algoProb = ot.ProbabilitySimulationAlgorithm(event)\n", + "# MaximumOuterSampling set to a very low value to make a fast example.\n", + "# More realistic parameter value (e.g. 1000).\n", + "algoProb.setMaximumOuterSampling(10)\n", + "algoProb.setMaximumCoefficientOfVariation(0.01)\n", + "algoProb.run()" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": "Number of function calls = 10\nFailure Probability = 0.0000\n" + } + ], + "source": [ + "# Get the results\n", + "resultAlgo = algoProb.getResult()\n", + "neval = g.getEvaluationCallsNumber()\n", + "print(\"Number of function calls = %d\" % (neval))\n", + "# Because of the low value of the maximumOuterSampling, the estimate is not very accurate.\n", + "pf = resultAlgo.getProbabilityEstimate()\n", + "print(\"Failure Probability = %.4f\" % (pf))" + ] + } + ], + "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": "3.7.3-final" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} \ No newline at end of file diff --git a/examples/distributions/beta_results.csv b/examples/distributions/beta_results.csv new file mode 100644 index 0000000..715e6aa --- /dev/null +++ b/examples/distributions/beta_results.csv @@ -0,0 +1,30 @@ +set_id,problem_id,reliability_problem_id,beta +-1,1,8,3.16 +-1,2,22,2.64 +1,1,14,2.42 +1,2,24,2.76 +1,3,28,5.11 +1,4,31,3.58 +1,5,38,2.48 +1,6,53,1.86 +1,7,54,3.09 +1,8,63,3.36 +1,9,75,2.33 +1,10,107,5.0 +1,11,111,4.81 +1,12,201,3.7 +1,13,203,4.92 +1,14,213,3.45 +1,15,300,3.88 +1,16,301,3.81 +2,1,25,4.36 +2,2,33,2.80 +2,3,35,2.70 +2,4,55,-0.15 +2,5,57,1.91 +2,6,60,1.70 +2,7,77,5.0 +2,8,89,2.55 +2,9,91,3.19 +2,10,110,4.0 +2,11,202,3.43 \ No newline at end of file diff --git a/examples/distributions/probabilistic_models.csv b/examples/distributions/probabilistic_models.csv new file mode 100644 index 0000000..410b6da --- /dev/null +++ b/examples/distributions/probabilistic_models.csv @@ -0,0 +1,480 @@ +set_id,problem_id,reliability_problem_id,random_variable,distribution_type,theta_1,theta_2,theta_3,theta_4,mean,std +-1,1,8,1,lognormal,,,,,120,12 +-1,1,8,2,lognormal,,,,,120,12 +-1,1,8,3,lognormal,,,,,120,12 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+2,11,202,222,normal,0.0,1.0,,,0.0,1.0 +2,11,202,223,normal,0.0,1.0,,,0.0,1.0 +2,11,202,224,normal,0.0,1.0,,,0.0,1.0 +2,11,202,225,normal,0.0,1.0,,,0.0,1.0 diff --git a/otbenchmark/BBRCDistribution.py b/otbenchmark/BBRCDistribution.py new file mode 100644 index 0000000..65e113c --- /dev/null +++ b/otbenchmark/BBRCDistribution.py @@ -0,0 +1,82 @@ +#!/usr/bin/python +# coding:utf-8 +# Copyright 2020 EDF +"""Class to create an OpenTURNS distribution out of a Black Box Reliability Challenge + problem""" + +import openturns as ot +import numpy as np + + +class BBRCDistribution: + """Class to create an OpenTURNS distribution out of a Black Box Reliability + Challenge problem""" + + def __init__(self, set_id, problem_id): + """ + Creates an ot.ComposedDistribution from the BBRC 2019 distribution table. + + References + ---------- + https://rprepo.readthedocs.io/en/latest/ + + Parameters + ---------- + set_id: int + First item defining the reliability problem selected. + problem_id: int + Second item defining the reliability problem selected. + """ + self.set_id = set_id + self.problem_id = problem_id + return None + + def build_composed_dist(self): + """ + Builds an ot.ComposedDistribution from the BBRC 2019 distribution table for the + corresponding set_id and problem_id defined in the constructor. + """ + + def switch_build_dist(dist_name, a, b, mean, std): + if dist_name == "uniform": + a_dist = ot.Uniform(a, b) + elif dist_name == "exponential": + a_dist = ot.Exponential(a) + elif dist_name == "normal": + a_dist = ot.Normal(a, b) + elif dist_name == "gumbel_max": + a_dist = ot.ParametrizedDistribution(ot.GumbelMuSigma(mean, std)) + elif dist_name == "lognormal": + a_dist = ot.ParametrizedDistribution(ot.LogNormalMuSigma(mean, std)) + else: + raise ValueError( + "Distribution not defined correctly in \ + probabilistic_models.csv file" + ) + return a_dist + + types = ["i4", "i4", "i4", "i4", "U15", "f8", "f8", "f8", "f8", "f8", "f8"] + bbrc_dist_table = np.genfromtxt( + "otbenchmark/distributions/probabilistic_models.csv", + dtype=types, + delimiter=",", + names=True, + ) + my_dist_table = bbrc_dist_table[ + (bbrc_dist_table["problem_id"] == self.problem_id) + & (bbrc_dist_table["set_id"] == self.set_id) + ] + + ot_dist_list = [] + for raw in my_dist_table: + ot_dist_list.append( + switch_build_dist( + raw["distribution_type"], + raw["theta_1"], + raw["theta_2"], + raw["mean"], + raw["std"], + ) + ) + composed_dist = ot.ComposedDistribution(ot_dist_list) + return composed_dist diff --git a/otbenchmark/RequestedBBRCProblem.py b/otbenchmark/RequestedBBRCProblem.py new file mode 100644 index 0000000..c493452 --- /dev/null +++ b/otbenchmark/RequestedBBRCProblem.py @@ -0,0 +1,73 @@ +#!/usr/bin/python +# coding:utf-8 +# Copyright 2020 EDF +"""Class to define a benchmark problem using http requests from the BBRC 2019 server.""" + +from otbenchmark.ReliabilityBenchmarkProblem import ReliabilityBenchmarkProblem +from otbenchmark.BBRCDistribution import BBRCDistribution +from otbenchmark import evaluate +import openturns as ot +import numpy as np + + +class RequestedBBRCProblem(ReliabilityBenchmarkProblem): + def __init__(self, username, password, set_id, problem_id): + """ + Creates a ot.PythonFunction requesting a BBRC 2019 function using http requests. + + References + ---------- + https://rprepo.readthedocs.io/en/latest/ + + Parameters + ---------- + username: str + Username required to login the BBRC challenge. + password: str + Password required to login the BBRC challenge. + set_id: int + First item defining the reliability problem selected. + problem_id: int + Second item defining the reliability problem selected. + """ + self.username = username + self.password = password + self.set_id = set_id + self.problem_id = problem_id + + def g_fun(x): + x = np.array(x) + g_val_sys, g_val_comp, msg = evaluate.evaluate( + self.username, self.password, self.set_id, self.problem_id, x + ) + return g_val_comp + + # BBRCDistribution + my_dist = BBRCDistribution(self.set_id, self.problem_id) + inputDistribution = my_dist.build_composed_dist() + inputRandomVector = ot.RandomVector(inputDistribution) + input_dim = inputDistribution.getDimension() + # BBRCResults + types = ["i4", "i4", "i4", "f8"] + bbrc_result_table = np.genfromtxt( + "otbenchmark/distributions/beta_results.csv", + dtype=types, + delimiter=",", + names=True, + ) + my_result = bbrc_result_table[ + (bbrc_result_table["problem_id"] == self.problem_id) + & (bbrc_result_table["set_id"] == self.set_id) + ] + name = "RP" + str(my_result["reliability_problem_id"][0]) + beta = my_result["beta"][0] + limitStateFunction = ot.PythonFunction(input_dim, 1, g_fun) + outputRandomVector = ot.CompositeRandomVector( + limitStateFunction, inputRandomVector + ) + thresholdEvent = ot.ThresholdEvent(outputRandomVector, ot.Less(), 0.0) + + probability = ot.Normal().computeComplementaryCDF(beta) + super(RequestedBBRCProblem, self).__init__(name, thresholdEvent, probability) + + return None diff --git a/otbenchmark/__init__.py b/otbenchmark/__init__.py index 0aa0115..54f3316 100644 --- a/otbenchmark/__init__.py +++ b/otbenchmark/__init__.py @@ -26,6 +26,8 @@ from .ReliabilityProblem107 import ReliabilityProblem107 from .ReliabilityProblem91 import ReliabilityProblem91 from .ReliabilityProblem63 import ReliabilityProblem63 +from .RequestedBBRCProblem import RequestedBBRCProblem +from .BBRCDistribution import BBRCDistribution from .ReliabilityProblem60 import ReliabilityProblem60 from .ReliabilityProblem77 import ReliabilityProblem77 from .ReliabilityLibrary import ComputeLogRelativeError @@ -79,6 +81,8 @@ "ReliabilityProblem107", "ReliabilityProblem91", "ReliabilityProblem63", + "RequestedBBRCProblem", + "BBRCDistribution", "ReliabilityProblem60", "ReliabilityProblem77", "FORM", diff --git a/otbenchmark/distributions/beta_results.csv b/otbenchmark/distributions/beta_results.csv new file mode 100644 index 0000000..715e6aa --- /dev/null +++ b/otbenchmark/distributions/beta_results.csv @@ -0,0 +1,30 @@ +set_id,problem_id,reliability_problem_id,beta +-1,1,8,3.16 +-1,2,22,2.64 +1,1,14,2.42 +1,2,24,2.76 +1,3,28,5.11 +1,4,31,3.58 +1,5,38,2.48 +1,6,53,1.86 +1,7,54,3.09 +1,8,63,3.36 +1,9,75,2.33 +1,10,107,5.0 +1,11,111,4.81 +1,12,201,3.7 +1,13,203,4.92 +1,14,213,3.45 +1,15,300,3.88 +1,16,301,3.81 +2,1,25,4.36 +2,2,33,2.80 +2,3,35,2.70 +2,4,55,-0.15 +2,5,57,1.91 +2,6,60,1.70 +2,7,77,5.0 +2,8,89,2.55 +2,9,91,3.19 +2,10,110,4.0 +2,11,202,3.43 \ No newline at end of file diff --git a/otbenchmark/distributions/probabilistic_models.csv b/otbenchmark/distributions/probabilistic_models.csv new file mode 100644 index 0000000..410b6da --- /dev/null +++ b/otbenchmark/distributions/probabilistic_models.csv @@ -0,0 +1,480 @@ +set_id,problem_id,reliability_problem_id,random_variable,distribution_type,theta_1,theta_2,theta_3,theta_4,mean,std +-1,1,8,1,lognormal,,,,,120,12 +-1,1,8,2,lognormal,,,,,120,12 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ot.ParametrizedDistribution(ot.LogNormalMuSigma(120, 12)), + ot.ParametrizedDistribution(ot.LogNormalMuSigma(120, 12)), + ot.ParametrizedDistribution(ot.LogNormalMuSigma(120, 12)), + ot.ParametrizedDistribution(ot.LogNormalMuSigma(120, 12)), + ot.ParametrizedDistribution(ot.LogNormalMuSigma(50, 10)), + ot.ParametrizedDistribution(ot.LogNormalMuSigma(40, 8)), + ] + ) + exact_cdf_value = exact_dist.computeCDF([150] * 6) + inputDistribution = my_dist.build_composed_dist() + tested_cdf_value = inputDistribution.computeCDF([150] * 6) + np.testing.assert_allclose(exact_cdf_value, tested_cdf_value, rtol=1.0e-15) + + +if __name__ == "__main__": + unittest.main() diff --git a/tests/test_ReliabilityProblem28.py b/tests/test_ReliabilityProblem28.py index 5b81931..d08145c 100644 --- a/tests/test_ReliabilityProblem28.py +++ b/tests/test_ReliabilityProblem28.py @@ -84,5 +84,6 @@ def test_UseCaseFORMIS(self): ) + if __name__ == "__main__": unittest.main() diff --git a/tests/test_ReliabilityProblem55.py b/tests/test_ReliabilityProblem55.py index ac733f1..1f6ec5b 100644 --- a/tests/test_ReliabilityProblem55.py +++ b/tests/test_ReliabilityProblem55.py @@ -58,6 +58,5 @@ def test_UseCaseMonteCarlo(self): atol = 1.0e2 / np.sqrt(samplesize) np.testing.assert_allclose(computed_pf, exact_pf, atol=atol) - if __name__ == "__main__": unittest.main() diff --git a/tests/test_RequestedBBRCProblem.py b/tests/test_RequestedBBRCProblem.py new file mode 100644 index 0000000..a4025b9 --- /dev/null +++ b/tests/test_RequestedBBRCProblem.py @@ -0,0 +1,31 @@ +# -*- coding: utf-8 -*- +""" +Test for RequestedBBRCProblem class. +""" +import otbenchmark as otb +import unittest +import numpy as np +import openturns as ot + + +class CheckRequestedBBRCProblem(unittest.TestCase): + def test_RequestedBBRCProblem(self): + problem = otb.RequestedBBRCProblem("testuser", "testpass", -1, 1) + print(problem) + + # Check probability + pf = problem.getProbability() + pf_exacte = 0.0007888456943755395 + np.testing.assert_allclose(pf, pf_exacte, rtol=1.0e-15) + + # Check function + event = problem.getEvent() + function = event.getFunction() + X = [0.0] * 6 + Y = function(X) + assert type(Y) is ot.Point + np.testing.assert_allclose(Y[0], 0) + + +if __name__ == "__main__": + unittest.main()