protot/3rdparty/fcl/test/eigen_matrix_compare.h

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/*
* Software License Agreement (BSD License)
*
* Copyright (c) 2018. Toyota Research Institute
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// This code was taken from Drake.
// https://github.com/RobotLocomotion/drake/blob/master/common/test_utilities/eigen_matrix_compare.h
#ifndef FCL_EIGEN_MATRIX_COMPARE_H
#define FCL_EIGEN_MATRIX_COMPARE_H
#include <algorithm>
#include <cmath>
#include <limits>
#include <Eigen/Dense>
#include <gtest/gtest.h>
namespace fcl {
enum class MatrixCompareType { absolute, relative };
/**
* Compares two matrices to determine whether they are equal to within a certain
* threshold.
*
* @param m1 The first matrix to compare.
* @param m2 The second matrix to compare.
* @param tolerance The tolerance for determining equivalence.
* @param compare_type Whether the tolerance is absolute or relative.
* @return true if the two matrices are equal based on the specified tolerance.
*/
template <typename DerivedA, typename DerivedB>
::testing::AssertionResult CompareMatrices(
const Eigen::MatrixBase<DerivedA>& m1,
const Eigen::MatrixBase<DerivedB>& m2, double tolerance = 0.0,
MatrixCompareType compare_type = MatrixCompareType::absolute) {
if (m1.rows() != m2.rows() || m1.cols() != m2.cols()) {
return ::testing::AssertionFailure()
<< "Matrix size mismatch: (" << m1.rows() << " x " << m1.cols()
<< " vs. " << m2.rows() << " x " << m2.cols() << ")";
}
for (int ii = 0; ii < m1.rows(); ii++) {
for (int jj = 0; jj < m1.cols(); jj++) {
// First handle the corner cases of positive infinity, negative infinity,
// and NaN
const auto both_positive_infinity =
m1(ii, jj) == std::numeric_limits<double>::infinity() &&
m2(ii, jj) == std::numeric_limits<double>::infinity();
const auto both_negative_infinity =
m1(ii, jj) == -std::numeric_limits<double>::infinity() &&
m2(ii, jj) == -std::numeric_limits<double>::infinity();
using std::isnan;
const auto both_nan = isnan(m1(ii, jj)) && isnan(m2(ii, jj));
if (both_positive_infinity || both_negative_infinity || both_nan)
continue;
// Check for case where one value is NaN and the other is not
if ((isnan(m1(ii, jj)) && !isnan(m2(ii, jj))) ||
(!isnan(m1(ii, jj)) && isnan(m2(ii, jj)))) {
return ::testing::AssertionFailure() << "NaN missmatch at (" << ii
<< ", " << jj << "):\nm1 =\n"
<< m1 << "\nm2 =\n"
<< m2;
}
// Determine whether the difference between the two matrices is less than
// the tolerance.
using std::abs;
const auto delta = abs(m1(ii, jj) - m2(ii, jj));
if (compare_type == MatrixCompareType::absolute) {
// Perform comparison using absolute tolerance.
if (delta > tolerance) {
return ::testing::AssertionFailure()
<< "Values at (" << ii << ", " << jj
<< ") exceed tolerance: " << m1(ii, jj) << " vs. "
<< m2(ii, jj) << ", diff = " << delta
<< ", tolerance = " << tolerance << "\nm1 =\n"
<< m1 << "\nm2 =\n"
<< m2 << "\ndelta=\n"
<< (m1 - m2);
}
} else {
// Perform comparison using relative tolerance, see:
// http://realtimecollisiondetection.net/blog/?p=89
using std::max;
const auto max_value = max(abs(m1(ii, jj)), abs(m2(ii, jj)));
const auto relative_tolerance =
tolerance * max(decltype(max_value){1}, max_value);
if (delta > relative_tolerance) {
return ::testing::AssertionFailure()
<< "Values at (" << ii << ", " << jj
<< ") exceed tolerance: " << m1(ii, jj) << " vs. "
<< m2(ii, jj) << ", diff = " << delta
<< ", tolerance = " << tolerance
<< ", relative tolerance = " << relative_tolerance
<< "\nm1 =\n"
<< m1 << "\nm2 =\n"
<< m2 << "\ndelta=\n"
<< (m1 - m2);
}
}
}
}
return ::testing::AssertionSuccess() << "m1 =\n"
<< m1
<< "\nis approximately equal to m2 =\n"
<< m2;
}
} // namespace fcl
#endif // FCL_EIGEN_MATRIX_COMPARE_H