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/*=========================================================================
*
* Copyright NumFOCUS
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* https://www.apache.org/licenses/LICENSE-2.0.txt
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
*=========================================================================*/
#include <iostream>
#include "itkGaussianMembershipFunction.h"
#include "itkTestingMacros.h"
int
itkGaussianMembershipFunctionTest(int, char *[])
{
constexpr unsigned int MeasurementVectorSize = 1;
using MeasurementVectorType = itk::FixedArray<float, MeasurementVectorSize>;
using MembershipFunctionType = itk::Statistics::GaussianMembershipFunction<MeasurementVectorType>;
using MeasurementVectorSizeType = MembershipFunctionType::MeasurementVectorSizeType;
auto function = MembershipFunctionType::New();
ITK_EXERCISE_BASIC_OBJECT_METHODS(function, GaussianMembershipFunction, MembershipFunctionBase);
// Test if an exception will be thrown if we try to resize the measurement vector
// size
MeasurementVectorSizeType measurementVector2 = MeasurementVectorSize + 1;
ITK_TRY_EXPECT_EXCEPTION(function->SetMeasurementVectorSize(measurementVector2));
// Test non-square covariance matrix exception
MembershipFunctionType::CovarianceMatrixType covariance;
covariance.SetSize(MeasurementVectorSize, MeasurementVectorSize + 1);
covariance.SetIdentity();
ITK_TRY_EXPECT_EXCEPTION(function->SetCovariance(covariance));
// Test covariance matrix and measurement vector size mismatch exception
covariance.SetSize(MeasurementVectorSize + 1, MeasurementVectorSize + 1);
covariance.SetIdentity();
ITK_TRY_EXPECT_EXCEPTION(function->SetCovariance(covariance));
covariance.SetSize(MeasurementVectorSize, MeasurementVectorSize);
covariance.SetIdentity();
function->SetCovariance(covariance);
ITK_TEST_SET_GET_VALUE(covariance, function->GetCovariance());
ITK_TEST_SET_GET_VALUE(covariance.GetInverse(), function->GetInverseCovariance().GetVnlMatrix());
function->SetMeasurementVectorSize(MeasurementVectorSize);
ITK_TEST_SET_GET_VALUE(MeasurementVectorSize, function->GetMeasurementVectorSize());
// Test if the membership function value computed is correct
MembershipFunctionType::MeanVectorType mean;
itk::NumericTraits<MembershipFunctionType::MeanVectorType>::SetLength(mean, MeasurementVectorSize);
mean[0] = 1.5;
function->SetMean(mean);
constexpr double tolerance = 0.001;
if (itk::Math::abs(function->GetMean()[0] - mean[0]) > tolerance)
{
std::cerr << "Error in GetMean() method" << std::endl;
return EXIT_FAILURE;
}
MeasurementVectorType measurement;
itk::NumericTraits<MeasurementVectorType>::SetLength(measurement, MeasurementVectorSize);
measurement[0] = 1.5;
double trueValue = 0.3989;
double distanceComputed = function->Evaluate(measurement);
if (itk::Math::abs(distanceComputed - trueValue) > tolerance)
{
std::cerr << "Distance computed not correct: "
<< "truevalue= " << trueValue << ", ComputedValue=" << distanceComputed << std::endl;
return EXIT_FAILURE;
}
std::cout << "Test finished." << std::endl;
return EXIT_SUCCESS;
}
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