85 lines
3.6 KiB
C++
85 lines
3.6 KiB
C++
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///-------------------------------------------------------------------------------------------------
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///
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/// \file test_Geodesics.hpp
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/// \brief Tests for Geodesic Functions.
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/// \author Thibaut Monseigne (Inria).
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/// \version 1.0.
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/// \date 09/01/2019.
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/// \copyright <a href="https://choosealicense.com/licenses/agpl-3.0/">GNU Affero General Public License v3.0</a>.
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///
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///-------------------------------------------------------------------------------------------------
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#pragma once
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#include "gtest/gtest.h"
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#include "misc.hpp"
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#include "init.hpp"
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#include <geometry/Geodesic.hpp>
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//---------------------------------------------------------------------------------------------------
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class Tests_Geodesic : public testing::Test
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{
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protected:
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std::vector<Eigen::MatrixXd> m_dataSet;
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void SetUp() override { m_dataSet = Geometry::Vector2DTo1D(InitCovariance::LWF::Reference()); }
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};
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//---------------------------------------------------------------------------------------------------
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//---------------------------------------------------------------------------------------------------
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TEST_F(Tests_Geodesic, Euclidian)
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{
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const std::vector<Eigen::MatrixXd> ref = InitGeodesics::Euclidian::Reference();
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const Eigen::MatrixXd mean = InitMeans::Euclidian::Reference();
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for (size_t i = 0; i < m_dataSet.size(); ++i)
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{
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Eigen::MatrixXd calc;
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Geodesic(mean, m_dataSet[i], calc, Geometry::EMetric::Euclidian, 0.5);
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EXPECT_TRUE(isAlmostEqual(ref[i], calc)) << ErrorMsg("Geodesic Euclidian Sample [" + std::to_string(i) + "]", ref[i], calc);
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}
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}
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//---------------------------------------------------------------------------------------------------
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//---------------------------------------------------------------------------------------------------
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TEST_F(Tests_Geodesic, LogEuclidian)
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{
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const std::vector<Eigen::MatrixXd> ref = InitGeodesics::LogEuclidian::Reference();
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const Eigen::MatrixXd mean = InitMeans::LogEuclidian::Reference();
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for (size_t i = 0; i < m_dataSet.size(); ++i)
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{
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Eigen::MatrixXd calc;
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Geodesic(mean, m_dataSet[i], calc, Geometry::EMetric::LogEuclidian, 0.5);
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EXPECT_TRUE(isAlmostEqual(ref[i], calc)) << ErrorMsg("Geodesic LogEuclidian Sample [" + std::to_string(i) + "]", ref[i], calc);
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}
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}
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//---------------------------------------------------------------------------------------------------
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//---------------------------------------------------------------------------------------------------
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TEST_F(Tests_Geodesic, Riemann)
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{
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const std::vector<Eigen::MatrixXd> ref = InitGeodesics::Riemann::Reference();
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const Eigen::MatrixXd mean = InitMeans::Riemann::Reference();
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for (size_t i = 0; i < m_dataSet.size(); ++i)
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{
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Eigen::MatrixXd calc;
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Geodesic(mean, m_dataSet[i], calc, Geometry::EMetric::Riemann, 0.5);
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EXPECT_TRUE(isAlmostEqual(ref[i], calc)) << ErrorMsg("Geodesic Riemann Sample [" + std::to_string(i) + "]", ref[i], calc);
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}
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}
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//---------------------------------------------------------------------------------------------------
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//---------------------------------------------------------------------------------------------------
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TEST_F(Tests_Geodesic, Identity)
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{
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const Eigen::MatrixXd mean = InitMeans::Riemann::Reference(), ref = Eigen::MatrixXd::Identity(NB_CHAN, NB_CHAN);
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for (size_t i = 0; i < m_dataSet.size(); ++i)
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{
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Eigen::MatrixXd calc;
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Geodesic(mean, m_dataSet[i], calc, Geometry::EMetric::Identity, 0.5);
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EXPECT_TRUE(isAlmostEqual(ref, calc)) << ErrorMsg("Geodesic Identity Sample [" + std::to_string(i) + "]", ref, calc);
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}
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}
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//---------------------------------------------------------------------------------------------------
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