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#! /usr/bin/env python
from __future__ import print_function
from openturns import *
from math import *
TESTPREAMBLE()
RandomGenerator.SetSeed(0)
try:
PlatformInfo.SetNumericalPrecision(4)
coll1 = DistributionCollection(0)
coll1.add(Normal(1.0, 2.5))
coll1.add(Gamma(1.5, 3.0))
pointLow = NumericalPoint(0)
pointLow.add(coll1[0].computeQuantile(0.25)[0])
pointLow.add(coll1[1].computeQuantile(0.25)[0])
pointHigh = NumericalPoint(0)
pointHigh.add(coll1[0].computeQuantile(0.75)[0])
pointHigh.add(coll1[1].computeQuantile(0.75)[0])
coll2 = DistributionCollection(0)
coll2.add(Gamma(2.5, 2.0))
coll2.add(Normal(3.0, 1.5))
# First, check the old constructor
evaluation = MarginalTransformationEvaluation(coll1)
transformation = MarginalTransformationHessian(evaluation)
print("transformation=", repr(transformation))
print("transformation.hessian(", repr(pointLow), ")=",
repr(transformation.hessian(pointLow)))
print("finite difference hessian(", repr(pointLow), ")=", repr(
CenteredFiniteDifferenceHessian(1.0e-4, evaluation).hessian(pointLow)))
print("transformation.hessian(", repr(pointHigh), ")=",
repr(transformation.hessian(pointHigh)))
print("finite difference hessian(", repr(pointHigh), ")=", repr(
CenteredFiniteDifferenceHessian(1.0e-4, evaluation).hessian(pointHigh)))
print("input dimension=", transformation.getInputDimension())
print("output dimension=", transformation.getOutputDimension())
# Second, check the constructor for old inverse transformation
evaluation = MarginalTransformationEvaluation(
coll1, MarginalTransformationEvaluation.TO)
transformation = MarginalTransformationHessian(evaluation)
print("transformation=", repr(transformation))
uLow = NumericalPoint(coll1.getSize(), 0.25)
uHigh = NumericalPoint(coll1.getSize(), 0.75)
print("transformation.hessian(", repr(uLow), ")=",
repr(transformation.hessian(uLow)))
print("finite difference hessian(", repr(uLow), ")=", repr(
CenteredFiniteDifferenceHessian(1.0e-4, evaluation).hessian(uLow)))
print("transformation.hessian(", repr(uHigh), ")=",
repr(transformation.hessian(uHigh)))
print("finite difference hessian(", repr(uHigh), ")=", repr(
CenteredFiniteDifferenceHessian(1.0e-4, evaluation).hessian(uHigh)))
print("input dimension=", transformation.getInputDimension())
print("output dimension=", transformation.getOutputDimension())
# Third, check the constructor for the new transformation
evaluation = MarginalTransformationEvaluation(coll1, coll2)
transformation = MarginalTransformationHessian(evaluation)
print("transformation=", repr(transformation))
print("transformation.hessian(", repr(pointLow), ")=",
repr(transformation.hessian(pointLow)))
print("finite difference hessian(", repr(pointLow), ")=", repr(
CenteredFiniteDifferenceHessian(1.0e-4, evaluation).hessian(pointLow)))
print("transformation.hessian(", repr(pointHigh), ")=",
repr(transformation.hessian(pointHigh)))
print("finite difference hessian(", repr(pointHigh), ")=", repr(
CenteredFiniteDifferenceHessian(1.0e-4, evaluation).hessian(pointHigh)))
print("input dimension=", transformation.getInputDimension())
print("output dimension=", transformation.getOutputDimension())
except:
import sys
print("t_MarginalTransformationHessian_std.py",
sys.exc_info()[0], sys.exc_info()[1])
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