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Move eigen to third party (#282)
* remove useless statement * Add eigen to third_party dir * remove reducdant lines
This commit is contained in:
Jack Zhou
215
third_party/eigen/test/permutationmatrices.cpp
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215
third_party/eigen/test/permutationmatrices.cpp
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// This file is part of Eigen, a lightweight C++ template library
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// for linear algebra.
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//
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// Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@gmail.com>
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//
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// This Source Code Form is subject to the terms of the Mozilla
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// Public License v. 2.0. If a copy of the MPL was not distributed
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// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
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#define TEST_ENABLE_TEMPORARY_TRACKING
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#include "main.h"
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using namespace std;
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template <typename MatrixType>
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void permutationmatrices(const MatrixType& m) {
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typedef typename MatrixType::Scalar Scalar;
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enum {
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Rows = MatrixType::RowsAtCompileTime,
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Cols = MatrixType::ColsAtCompileTime,
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Options = MatrixType::Options
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};
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typedef PermutationMatrix<Rows> LeftPermutationType;
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typedef Transpositions<Rows> LeftTranspositionsType;
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typedef Matrix<int, Rows, 1> LeftPermutationVectorType;
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typedef Map<LeftPermutationType> MapLeftPerm;
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typedef PermutationMatrix<Cols> RightPermutationType;
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typedef Transpositions<Cols> RightTranspositionsType;
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typedef Matrix<int, Cols, 1> RightPermutationVectorType;
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typedef Map<RightPermutationType> MapRightPerm;
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Index rows = m.rows();
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Index cols = m.cols();
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MatrixType m_original = MatrixType::Random(rows, cols);
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LeftPermutationVectorType lv;
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randomPermutationVector(lv, rows);
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LeftPermutationType lp(lv);
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RightPermutationVectorType rv;
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randomPermutationVector(rv, cols);
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RightPermutationType rp(rv);
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LeftTranspositionsType lt(lv);
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RightTranspositionsType rt(rv);
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MatrixType m_permuted = MatrixType::Random(rows, cols);
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VERIFY_EVALUATION_COUNT(m_permuted = lp * m_original * rp,
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1); // 1 temp for sub expression "lp * m_original"
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for (int i = 0; i < rows; i++)
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for (int j = 0; j < cols; j++)
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VERIFY_IS_APPROX(m_permuted(lv(i), j), m_original(i, rv(j)));
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Matrix<Scalar, Rows, Rows> lm(lp);
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Matrix<Scalar, Cols, Cols> rm(rp);
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VERIFY_IS_APPROX(m_permuted, lm * m_original * rm);
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m_permuted = m_original;
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VERIFY_EVALUATION_COUNT(m_permuted = lp * m_permuted * rp, 1);
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VERIFY_IS_APPROX(m_permuted, lm * m_original * rm);
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LeftPermutationType lpi;
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lpi = lp.inverse();
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VERIFY_IS_APPROX(lpi * m_permuted, lp.inverse() * m_permuted);
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VERIFY_IS_APPROX(lp.inverse() * m_permuted * rp.inverse(), m_original);
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VERIFY_IS_APPROX(
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lv.asPermutation().inverse() * m_permuted * rv.asPermutation().inverse(),
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m_original);
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VERIFY_IS_APPROX(MapLeftPerm(lv.data(), lv.size()).inverse() * m_permuted *
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MapRightPerm(rv.data(), rv.size()).inverse(),
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m_original);
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VERIFY((lp * lp.inverse()).toDenseMatrix().isIdentity());
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VERIFY((lv.asPermutation() * lv.asPermutation().inverse())
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.toDenseMatrix()
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.isIdentity());
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VERIFY((MapLeftPerm(lv.data(), lv.size()) *
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MapLeftPerm(lv.data(), lv.size()).inverse())
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.toDenseMatrix()
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.isIdentity());
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LeftPermutationVectorType lv2;
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randomPermutationVector(lv2, rows);
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LeftPermutationType lp2(lv2);
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Matrix<Scalar, Rows, Rows> lm2(lp2);
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VERIFY_IS_APPROX((lp * lp2).toDenseMatrix().template cast<Scalar>(),
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lm * lm2);
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VERIFY_IS_APPROX((lv.asPermutation() * lv2.asPermutation())
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.toDenseMatrix()
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.template cast<Scalar>(),
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lm * lm2);
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VERIFY_IS_APPROX(
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(MapLeftPerm(lv.data(), lv.size()) * MapLeftPerm(lv2.data(), lv2.size()))
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.toDenseMatrix()
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.template cast<Scalar>(),
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lm * lm2);
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LeftPermutationType identityp;
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identityp.setIdentity(rows);
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VERIFY_IS_APPROX(m_original, identityp * m_original);
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// check inplace permutations
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m_permuted = m_original;
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VERIFY_EVALUATION_COUNT(m_permuted.noalias() = lp.inverse() * m_permuted,
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1); // 1 temp to allocate the mask
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VERIFY_IS_APPROX(m_permuted, lp.inverse() * m_original);
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m_permuted = m_original;
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VERIFY_EVALUATION_COUNT(m_permuted.noalias() = m_permuted * rp.inverse(),
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1); // 1 temp to allocate the mask
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VERIFY_IS_APPROX(m_permuted, m_original * rp.inverse());
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m_permuted = m_original;
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VERIFY_EVALUATION_COUNT(m_permuted.noalias() = lp * m_permuted,
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1); // 1 temp to allocate the mask
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VERIFY_IS_APPROX(m_permuted, lp * m_original);
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m_permuted = m_original;
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VERIFY_EVALUATION_COUNT(m_permuted.noalias() = m_permuted * rp,
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1); // 1 temp to allocate the mask
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VERIFY_IS_APPROX(m_permuted, m_original * rp);
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if (rows > 1 && cols > 1) {
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lp2 = lp;
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Index i = internal::random<Index>(0, rows - 1);
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Index j;
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do
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j = internal::random<Index>(0, rows - 1);
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while (j == i);
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lp2.applyTranspositionOnTheLeft(i, j);
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lm = lp;
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lm.row(i).swap(lm.row(j));
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VERIFY_IS_APPROX(lm, lp2.toDenseMatrix().template cast<Scalar>());
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RightPermutationType rp2 = rp;
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i = internal::random<Index>(0, cols - 1);
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do
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j = internal::random<Index>(0, cols - 1);
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while (j == i);
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rp2.applyTranspositionOnTheRight(i, j);
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rm = rp;
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rm.col(i).swap(rm.col(j));
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VERIFY_IS_APPROX(rm, rp2.toDenseMatrix().template cast<Scalar>());
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}
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{
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// simple compilation check
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Matrix<Scalar, Cols, Cols> A = rp;
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Matrix<Scalar, Cols, Cols> B = rp.transpose();
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VERIFY_IS_APPROX(A, B.transpose());
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}
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m_permuted = m_original;
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lp = lt;
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rp = rt;
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VERIFY_EVALUATION_COUNT(m_permuted = lt * m_permuted * rt, 1);
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VERIFY_IS_APPROX(m_permuted, lp * m_original * rp.transpose());
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VERIFY_IS_APPROX(lt.inverse() * m_permuted * rt.inverse(), m_original);
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// Check inplace transpositions
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m_permuted = m_original;
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VERIFY_IS_APPROX(m_permuted = lt * m_permuted, lp * m_original);
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m_permuted = m_original;
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VERIFY_IS_APPROX(m_permuted = lt.inverse() * m_permuted,
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lp.inverse() * m_original);
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m_permuted = m_original;
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VERIFY_IS_APPROX(m_permuted = m_permuted * rt, m_original * rt);
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m_permuted = m_original;
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VERIFY_IS_APPROX(m_permuted = m_permuted * rt.inverse(),
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m_original * rt.inverse());
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}
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template <typename T>
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void bug890() {
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typedef Matrix<T, Dynamic, Dynamic> MatrixType;
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typedef Matrix<T, Dynamic, 1> VectorType;
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typedef Stride<Dynamic, Dynamic> S;
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typedef Map<MatrixType, Aligned, S> MapType;
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typedef PermutationMatrix<Dynamic> Perm;
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VectorType v1(2), v2(2), op(4), rhs(2);
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v1 << 666, 667;
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op << 1, 0, 0, 1;
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rhs << 42, 42;
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Perm P(2);
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P.indices() << 1, 0;
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MapType(v1.data(), 2, 1, S(1, 1)) = P * MapType(rhs.data(), 2, 1, S(1, 1));
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VERIFY_IS_APPROX(v1, (P * rhs).eval());
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MapType(v1.data(), 2, 1, S(1, 1)) =
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P.inverse() * MapType(rhs.data(), 2, 1, S(1, 1));
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VERIFY_IS_APPROX(v1, (P.inverse() * rhs).eval());
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}
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EIGEN_DECLARE_TEST(permutationmatrices) {
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for (int i = 0; i < g_repeat; i++) {
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CALL_SUBTEST_1(permutationmatrices(Matrix<float, 1, 1>()));
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CALL_SUBTEST_2(permutationmatrices(Matrix3f()));
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CALL_SUBTEST_3(permutationmatrices(Matrix<double, 3, 3, RowMajor>()));
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CALL_SUBTEST_4(permutationmatrices(Matrix4d()));
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CALL_SUBTEST_5(permutationmatrices(Matrix<double, 40, 60>()));
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CALL_SUBTEST_6(
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permutationmatrices(Matrix<double, Dynamic, Dynamic, RowMajor>(
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internal::random<int>(1, EIGEN_TEST_MAX_SIZE),
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internal::random<int>(1, EIGEN_TEST_MAX_SIZE))));
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CALL_SUBTEST_7(permutationmatrices(
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MatrixXcf(internal::random<int>(1, EIGEN_TEST_MAX_SIZE),
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internal::random<int>(1, EIGEN_TEST_MAX_SIZE))));
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}
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CALL_SUBTEST_5(bug890<double>());
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}
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