kopia lustrzana https://github.com/vsamy/DiFipp
44 wiersze
1.5 KiB
C++
44 wiersze
1.5 KiB
C++
#define BOOST_TEST_MODULE MovingAverageFilterTests
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#include "fratio.h"
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#include <boost/test/unit_test.hpp>
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template <typename T>
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struct System {
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Eigen::VectorX<T> data = (Eigen::VectorX<T>(6) << 1, 2, 3, 4, 5, 6).finished();
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size_t windowSize = 4;
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Eigen::VectorX<T> results = (Eigen::VectorX<T>(6) << 0.25, 0.75, 1.5, 2.5, 3.5, 4.5).finished();
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};
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BOOST_FIXTURE_TEST_CASE(MOVING_AVERAGE_FLOAT, System<float>)
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{
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auto maf = fratio::MovingAveragef(windowSize);
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std::vector<float> filteredData;
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for (Eigen::Index i = 0; i < data.size(); ++i)
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filteredData.push_back(maf.stepFilter(data(i)));
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for (size_t i = 0; i < filteredData.size(); ++i)
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BOOST_CHECK_SMALL(std::abs(filteredData[i] - results[i]), 1e-6f);
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maf.resetFilter();
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Eigen::VectorXf fData = maf.filter(data);
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for (Eigen::Index i = 0; i < fData.size(); ++i)
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BOOST_CHECK_SMALL(std::abs(fData(i) - results(i)), 1e-6f);
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}
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BOOST_FIXTURE_TEST_CASE(MOVING_AVERAGE_DOUBLE, System<double>)
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{
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auto maf = fratio::MovingAveraged(windowSize);
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std::vector<double> filteredData;
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for (Eigen::Index i = 0; i < data.size(); ++i)
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filteredData.push_back(maf.stepFilter(data(i)));
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for (size_t i = 0; i < filteredData.size(); ++i)
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BOOST_CHECK_SMALL(std::abs(filteredData[i] - results[i]), 1e-14);
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maf.resetFilter();
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Eigen::VectorXd fData = maf.filter(data);
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for (Eigen::Index i = 0; i < fData.size(); ++i)
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BOOST_CHECK_SMALL(std::abs(fData(i) - results(i)), 1e-14);
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}
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