Added Python unit test

python/test/t_MonteCarloExperiment_std.py

@@ -1,6 +1,9 @@
 #! /usr/bin/env python
 
 import openturns as ot
+import openturns.testing as ott
+import math
+from openturns.usecases import ishigami_function
 
 ot.TESTPREAMBLE()
 
@@ -11,3 +14,34 @@
 sample, weights = experiment.generateWithWeights()
 print("sample = ", repr(sample))
 print("weights = ", repr(weights))
+
+# Test integrate
+im = ishigami_function.IshigamiModel()
+sampleSize = 100000
+experiment = ot.MonteCarloExperiment(im.distributionX, sampleSize)
+approximatedOutputMean = experiment.integrate(im.model)
+rtol = 0.0
+atol = 1.0 / math.sqrt(sampleSize)
+ott.assert_almost_equal(approximatedOutputMean[0], im.expectation, rtol, atol)
+
+# Test computeNorm
+im = ishigami_function.IshigamiModel()
+centeredIshigamiFunction = ot.SymbolicFunction(
+    ['x1', 'x2', 'x3'], 
+    ['sin(x1) + 7 * (sin(x2)) ^ 2 + 0.1 * x3^4 * sin(x1) - 3.5'])
+functionNorm = experiment.computeNorm(centeredIshigamiFunction)
+exactFunctionNorm = math.sqrt(im.variance)
+rtol = 0.0
+atol = 10.0 / math.sqrt(sampleSize)
+ott.assert_almost_equal(functionNorm[0], exactFunctionNorm, rtol, atol)
+
+# Test computeError
+im = ishigami_function.IshigamiModel()
+partOfIshigamiFunction = ot.SymbolicFunction(
+    ['x1', 'x2', 'x3'],
+    ['7 * (sin(x2)) ^ 2 + 0.1 * x3^4 * sin(x1)'])
+functionError = experiment.computeError(im.model, partOfIshigamiFunction)
+exactError = math.sqrt(0.5)
+rtol = 0.0
+atol = 10.0 / math.sqrt(sampleSize)
+ott.assert_almost_equal(functionError[0], exactError, rtol, atol)