kopia lustrzana https://github.com/vsamy/DiFipp
All tests ok.
Vincent Samy
rodzic
6ab21d6145
commit
a26692666f
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@ -36,8 +36,10 @@ T GenericFilter<T>::stepFilter(const T& data)
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assert(m_status == FilterStatus::READY);
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// Slide data (can't use SIMD, but should be small)
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m_rawData.tail(m_rawData.size() - 1) = m_rawData.head(m_rawData.size() - 1);
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m_filteredData.tail(m_filteredData.size() - 1) = m_filteredData.head(m_filteredData.size() - 1);
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for (Eigen::Index i = m_rawData.size() - 1; i > 0; --i)
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m_rawData(i) = m_rawData(i - 1);
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for (Eigen::Index i = m_filteredData.size() - 1; i > 0; --i)
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m_filteredData(i) = m_filteredData(i - 1);
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m_rawData[0] = data;
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m_filteredData[0] = 0;
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@ -1,6 +1,7 @@
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#define BOOST_TEST_MODULE ButterworthFilterTests
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#include "fratio"
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#include "test_functions.h"
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#include "warning_macro.h"
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#include <boost/test/unit_test.hpp>
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@ -12,87 +13,46 @@ struct System {
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int order = 5;
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T fc = 10;
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T fs = 100;
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fratio::vectX_t<T> aCoeffRes = (fratio::vectX_t<T>(6) << 1.000000000000000, -2.975422109745684, 3.806018119320413, -2.545252868330468, 0.881130075437837, -0.125430622155356).finished();
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fratio::vectX_t<T> bCoeffRes = (fratio::vectX_t<T>(6) << 0.001282581078961, 0.006412905394803, 0.012825810789607, 0.012825810789607, 0.006412905394803, 0.001282581078961).finished();
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fratio::vectX_t<T> results = (fratio::vectX_t<T>(8) << 0.001282581078961, 0.012794287652606, 0.062686244350084, 0.203933712825708, 0.502244959135609, 1.010304217144175, 1.744652693589064, 2.678087381460197).finished();
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// LP
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fratio::vectX_t<T> lpACoeffRes = (fratio::vectX_t<T>(6) << 1, -2.975422109745684, 3.806018119320413, -2.545252868330468, 0.881130075437837, -0.125430622155356).finished();
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fratio::vectX_t<T> lpBCoeffRes = (fratio::vectX_t<T>(6) << 0.001282581078961, 0.006412905394803, 0.012825810789607, 0.012825810789607, 0.006412905394803, 0.001282581078961).finished();
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fratio::vectX_t<T> lpResults = (fratio::vectX_t<T>(8) << 0.001282581078961, 0.012794287652606, 0.062686244350084, 0.203933712825708, 0.502244959135609, 1.010304217144175, 1.744652693589064, 2.678087381460197).finished();
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// HP
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fratio::vectX_t<T> hpACoeffRes = (fratio::vectX_t<T>(6) << 1, -2.975422109745683, 3.806018119320411, -2.545252868330467, 0.8811300754378368, -0.1254306221553557).finished();
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fratio::vectX_t<T> hpBCoeffRes = (fratio::vectX_t<T>(6) << 0.3541641810934298, -1.770820905467149, 3.541641810934299, -3.541641810934299, 1.770820905467149, -0.3541641810934298).finished();
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fratio::vectX_t<T> hpResults = (fratio::vectX_t<T>(8) << 0.3541641810934298, -0.008704608374924483, -0.3113626313910076, -0.3460321436983160, -0.1787600153274098, 0.04471440201428267, 0.2059279258827846, 0.2533941579793959).finished();
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};
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DISABLE_CONVERSION_WARNING_END
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BOOST_FIXTURE_TEST_CASE(BUTTERWORTH_FILTER_FLOAT, System<float>)
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BOOST_FIXTURE_TEST_CASE(BUTTERWORTH_LP_FILTER_FLOAT, System<float>)
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{
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auto bf = fratio::Butterworthf(order, fc, fs);
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std::vector<float> filteredData;
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fratio::vectX_t<float> aCoeff, bCoeff;
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bf.getCoeffs(aCoeff, bCoeff);
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BOOST_REQUIRE_EQUAL(aCoeff.size(), aCoeffRes.size());
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BOOST_REQUIRE_EQUAL(bCoeff.size(), bCoeffRes.size());
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BOOST_REQUIRE_EQUAL(aCoeff.size(), bCoeffRes.size());
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for (Eigen::Index i = 0; i < aCoeff.size(); ++i) {
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BOOST_CHECK_SMALL(std::abs(aCoeff(i) - aCoeffRes(i)), 1e-6f);
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BOOST_CHECK_SMALL(std::abs(bCoeff(i) - bCoeffRes(i)), 1e-6f);
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}
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for (Eigen::Index i = 0; i < data.size(); ++i)
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filteredData.push_back(bf.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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bf.resetFilter();
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Eigen::VectorXf fData = bf.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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auto bf2 = fratio::Butterworthf();
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bf2.setFilterParameters(order, fc, fs);
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filteredData.clear();
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for (Eigen::Index i = 0; i < data.size(); ++i)
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filteredData.push_back(bf2.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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BOOST_REQUIRE_EQUAL(bf.aOrder(), bf.bOrder());
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test_coeffs(lpACoeffRes, lpBCoeffRes, bf);
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test_results(lpResults, data, bf);
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}
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BOOST_FIXTURE_TEST_CASE(BUTTERWORTH_FILTER_DOUBLE, System<double>)
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BOOST_FIXTURE_TEST_CASE(BUTTERWORTH_LP_FILTER_DOUBLE, System<double>)
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{
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auto bf = fratio::Butterworthd(order, fc, fs);
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std::vector<double> filteredData;
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fratio::vectX_t<double> aCoeff, bCoeff;
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bf.getCoeffs(aCoeff, bCoeff);
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BOOST_REQUIRE_EQUAL(aCoeff.size(), aCoeffRes.size());
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BOOST_REQUIRE_EQUAL(bCoeff.size(), bCoeffRes.size());
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BOOST_REQUIRE_EQUAL(aCoeff.size(), bCoeffRes.size());
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for (Eigen::Index i = 0; i < aCoeff.size(); ++i) {
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BOOST_CHECK_SMALL(std::abs(aCoeff(i) - aCoeffRes(i)), 1e-14);
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BOOST_CHECK_SMALL(std::abs(bCoeff(i) - bCoeffRes(i)), 1e-14);
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}
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for (Eigen::Index i = 0; i < data.size(); ++i)
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filteredData.push_back(bf.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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bf.resetFilter();
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Eigen::VectorXd fData = bf.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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auto bf2 = fratio::Butterworthd();
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bf2.setFilterParameters(order, fc, fs);
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filteredData.clear();
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for (Eigen::Index i = 0; i < data.size(); ++i)
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filteredData.push_back(bf2.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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BOOST_REQUIRE_EQUAL(bf.aOrder(), bf.bOrder());
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test_coeffs(lpACoeffRes, lpBCoeffRes, bf);
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test_results(lpResults, data, bf);
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}
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BOOST_FIXTURE_TEST_CASE(BUTTERWORTH_HP_FILTER_FLOAT, System<float>)
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{
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auto bf = fratio::Butterworthf(order, fc, fs, fratio::Butterworthf::Type::HighPass);
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BOOST_REQUIRE_EQUAL(bf.aOrder(), bf.bOrder());
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test_coeffs(hpACoeffRes, hpBCoeffRes, bf);
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test_results(hpResults, data, bf);
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}
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BOOST_FIXTURE_TEST_CASE(BUTTERWORTH_HP_FILTER_DOUBLE, System<double>)
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{
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auto bf = fratio::Butterworthd(order, fc, fs, fratio::Butterworthd::Type::HighPass);
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BOOST_REQUIRE_EQUAL(bf.aOrder(), bf.bOrder());
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test_coeffs(hpACoeffRes, hpBCoeffRes, bf);
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test_results(hpResults, data, bf);
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}
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@ -24,4 +24,4 @@ addTest(GenericFilterTests)
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addTest(polynome_functions_tests)
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addTest(DigitalFilterTests)
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addTest(MovingAverageFilterTests)
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# addTest(ButterWorthFilterTests)
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addTest(ButterWorthFilterTests)
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@ -12,9 +12,9 @@ void test_coeffs(const fratio::vectX_t<T>& aCoeff, const fratio::vectX_t<T>& bCo
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fratio::vectX_t<T> faCoeff, fbCoeff;
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filter.getCoeffs(faCoeff, fbCoeff);
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for (Eigen::Index i = 0; i < faCoeff.size(); ++i)
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BOOST_REQUIRE_SMALL(std::abs(aCoeff(i) - faCoeff(i)), std::numeric_limits<T>::epsilon() * 2);
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BOOST_REQUIRE_SMALL(std::abs(aCoeff(i) - faCoeff(i)), std::numeric_limits<T>::epsilon() * 10);
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for (Eigen::Index i = 0; i < fbCoeff.size(); ++i)
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BOOST_REQUIRE_SMALL(std::abs(bCoeff(i) - fbCoeff(i)), std::numeric_limits<T>::epsilon() * 2);
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BOOST_REQUIRE_SMALL(std::abs(bCoeff(i) - fbCoeff(i)), std::numeric_limits<T>::epsilon() * 10);
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}
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template <typename T>
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@ -26,10 +26,10 @@ void test_results(const fratio::vectX_t<T>& results, const fratio::vectX_t<T>& d
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filteredData(i) = filter.stepFilter(data(i));
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for (Eigen::Index i = 0; i < filteredData.size(); ++i)
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BOOST_REQUIRE_SMALL(std::abs(filteredData(i) - results(i)), std::numeric_limits<T>::epsilon() * 100);
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BOOST_REQUIRE_SMALL(std::abs(filteredData(i) - results(i)), std::numeric_limits<T>::epsilon() * 1000);
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filter.resetFilter();
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filteredData = filter.filter(data);
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for (Eigen::Index i = 0; i < filteredData.size(); ++i)
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BOOST_REQUIRE_SMALL(std::abs(filteredData(i) - results(i)), std::numeric_limits<T>::epsilon() * 100);
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BOOST_REQUIRE_SMALL(std::abs(filteredData(i) - results(i)), std::numeric_limits<T>::epsilon() * 1000);
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}
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