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dlma/eigen-3.4.0/test/array_reverse.cpp
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array_reverse.cpp
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// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
// Copyright (C) 2009 Ricard Marxer <email@ricardmarxer.com>
//
// This Source Code Form is subject to the terms of the Mozilla
// Public License v. 2.0. If a copy of the MPL was not distributed
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
#include "main.h"
#include <iostream>
using namespace std;
template<typename MatrixType> void reverse(const MatrixType& m)
{
typedef typename MatrixType::Scalar Scalar;
typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
Index rows = m.rows();
Index cols = m.cols();
// this test relies a lot on Random.h, and there's not much more that we can do
// to test it, hence I consider that we will have tested Random.h
MatrixType m1 = MatrixType::Random(rows, cols), m2;
VectorType v1 = VectorType::Random(rows);
MatrixType m1_r = m1.reverse();
// Verify that MatrixBase::reverse() works
for ( int i = 0; i < rows; i++ ) {
for ( int j = 0; j < cols; j++ ) {
VERIFY_IS_APPROX(m1_r(i, j), m1(rows - 1 - i, cols - 1 - j));
}
}
Reverse<MatrixType> m1_rd(m1);
// Verify that a Reverse default (in both directions) of an expression works
for ( int i = 0; i < rows; i++ ) {
for ( int j = 0; j < cols; j++ ) {
VERIFY_IS_APPROX(m1_rd(i, j), m1(rows - 1 - i, cols - 1 - j));
}
}
Reverse<MatrixType, BothDirections> m1_rb(m1);
// Verify that a Reverse in both directions of an expression works
for ( int i = 0; i < rows; i++ ) {
for ( int j = 0; j < cols; j++ ) {
VERIFY_IS_APPROX(m1_rb(i, j), m1(rows - 1 - i, cols - 1 - j));
}
}
Reverse<MatrixType, Vertical> m1_rv(m1);
// Verify that a Reverse in the vertical directions of an expression works
for ( int i = 0; i < rows; i++ ) {
for ( int j = 0; j < cols; j++ ) {
VERIFY_IS_APPROX(m1_rv(i, j), m1(rows - 1 - i, j));
}
}
Reverse<MatrixType, Horizontal> m1_rh(m1);
// Verify that a Reverse in the horizontal directions of an expression works
for ( int i = 0; i < rows; i++ ) {
for ( int j = 0; j < cols; j++ ) {
VERIFY_IS_APPROX(m1_rh(i, j), m1(i, cols - 1 - j));
}
}
VectorType v1_r = v1.reverse();
// Verify that a VectorType::reverse() of an expression works
for ( int i = 0; i < rows; i++ ) {
VERIFY_IS_APPROX(v1_r(i), v1(rows - 1 - i));
}
MatrixType m1_cr = m1.colwise().reverse();
// Verify that PartialRedux::reverse() works (for colwise())
for ( int i = 0; i < rows; i++ ) {
for ( int j = 0; j < cols; j++ ) {
VERIFY_IS_APPROX(m1_cr(i, j), m1(rows - 1 - i, j));
}
}
MatrixType m1_rr = m1.rowwise().reverse();
// Verify that PartialRedux::reverse() works (for rowwise())
for ( int i = 0; i < rows; i++ ) {
for ( int j = 0; j < cols; j++ ) {
VERIFY_IS_APPROX(m1_rr(i, j), m1(i, cols - 1 - j));
}
}
Scalar x = internal::random<Scalar>();
Index r = internal::random<Index>(0, rows-1),
c = internal::random<Index>(0, cols-1);
m1.reverse()(r, c) = x;
VERIFY_IS_APPROX(x, m1(rows - 1 - r, cols - 1 - c));
m2 = m1;
m2.reverseInPlace();
VERIFY_IS_APPROX(m2,m1.reverse().eval());
m2 = m1;
m2.col(0).reverseInPlace();
VERIFY_IS_APPROX(m2.col(0),m1.col(0).reverse().eval());
m2 = m1;
m2.row(0).reverseInPlace();
VERIFY_IS_APPROX(m2.row(0),m1.row(0).reverse().eval());
m2 = m1;
m2.rowwise().reverseInPlace();
VERIFY_IS_APPROX(m2,m1.rowwise().reverse().eval());
m2 = m1;
m2.colwise().reverseInPlace();
VERIFY_IS_APPROX(m2,m1.colwise().reverse().eval());
m1.colwise().reverse()(r, c) = x;
VERIFY_IS_APPROX(x, m1(rows - 1 - r, c));
m1.rowwise().reverse()(r, c) = x;
VERIFY_IS_APPROX(x, m1(r, cols - 1 - c));
}
template<int>
void array_reverse_extra()
{
Vector4f x; x << 1, 2, 3, 4;
Vector4f y; y << 4, 3, 2, 1;
VERIFY(x.reverse()[1] == 3);
VERIFY(x.reverse() == y);
}
// Simpler version of reverseInPlace leveraging a bug
// in clang 6/7 with -O2 and AVX or AVX512 enabled.
// This simpler version ensure that the clang bug is not simply hidden
// through mis-inlining of reverseInPlace or other minor changes.
template<typename MatrixType>
EIGEN_DONT_INLINE
void bug1684_job1(MatrixType& m1, MatrixType& m2)
{
m2 = m1;
m2.col(0).swap(m2.col(3));
m2.col(1).swap(m2.col(2));
}
template<typename MatrixType>
EIGEN_DONT_INLINE
void bug1684_job2(MatrixType& m1, MatrixType& m2)
{
m2 = m1; // load m1/m2 in AVX registers
m1.col(0) = m2.col(3); // perform 128 bits moves
m1.col(1) = m2.col(2);
m1.col(2) = m2.col(1);
m1.col(3) = m2.col(0);
}
template<typename MatrixType>
EIGEN_DONT_INLINE
void bug1684_job3(MatrixType& m1, MatrixType& m2)
{
m2 = m1;
Vector4f tmp;
tmp = m2.col(0);
m2.col(0) = m2.col(3);
m2.col(3) = tmp;
tmp = m2.col(1);
m2.col(1) = m2.col(2);
m2.col(2) = tmp;
}
template<int>
void bug1684()
{
Matrix4f m1 = Matrix4f::Random();
Matrix4f m2 = Matrix4f::Random();
bug1684_job1(m1,m2);
VERIFY_IS_APPROX(m2, m1.rowwise().reverse().eval());
bug1684_job2(m1,m2);
VERIFY_IS_APPROX(m2, m1.rowwise().reverse().eval());
// This one still fail after our swap's workaround,
// but I expect users not to implement their own swap.
// bug1684_job3(m1,m2);
// VERIFY_IS_APPROX(m2, m1.rowwise().reverse().eval());
}
EIGEN_DECLARE_TEST(array_reverse)
{
for(int i = 0; i < g_repeat; i++) {
CALL_SUBTEST_1( reverse(Matrix<float, 1, 1>()) );
CALL_SUBTEST_2( reverse(Matrix2f()) );
CALL_SUBTEST_3( reverse(Matrix4f()) );
CALL_SUBTEST_4( reverse(Matrix4d()) );
CALL_SUBTEST_5( reverse(MatrixXcf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
CALL_SUBTEST_6( reverse(MatrixXi(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
CALL_SUBTEST_7( reverse(MatrixXcd(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
CALL_SUBTEST_8( reverse(Matrix<float, 100, 100>()) );
CALL_SUBTEST_9( reverse(Matrix<float,Dynamic,Dynamic,RowMajor>(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
CALL_SUBTEST_3( bug1684<0>() );
}
CALL_SUBTEST_3( array_reverse_extra<0>() );
}
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