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// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2006-2010 Benoit Jacob <jacob.benoit.1@gmail.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"
template <typename MatrixType, typename Index, typename Scalar>
std::enable_if_t<!NumTraits<typename MatrixType::Scalar>::IsComplex, typename MatrixType::Scalar> block_real_only(
const MatrixType& m1, Index r1, Index r2, Index c1, Index c2, const Scalar& s1) {
// check cwise-Functions:
VERIFY_IS_APPROX(m1.row(r1).cwiseMax(s1), m1.cwiseMax(s1).row(r1));
VERIFY_IS_APPROX(m1.col(c1).cwiseMin(s1), m1.cwiseMin(s1).col(c1));
VERIFY_IS_APPROX(m1.block(r1, c1, r2 - r1 + 1, c2 - c1 + 1).cwiseMin(s1),
m1.cwiseMin(s1).block(r1, c1, r2 - r1 + 1, c2 - c1 + 1));
VERIFY_IS_APPROX(m1.block(r1, c1, r2 - r1 + 1, c2 - c1 + 1).cwiseMax(s1),
m1.cwiseMax(s1).block(r1, c1, r2 - r1 + 1, c2 - c1 + 1));
return Scalar(0);
}
template <typename MatrixType, typename Index, typename Scalar>
std::enable_if_t<NumTraits<typename MatrixType::Scalar>::IsComplex, typename MatrixType::Scalar> block_real_only(
const MatrixType&, Index, Index, Index, Index, const Scalar&) {
return Scalar(0);
}
// Check at compile-time that T1==T2, and at runtime-time that a==b
template <typename T1, typename T2>
std::enable_if_t<internal::is_same<T1, T2>::value, bool> is_same_block(const T1& a, const T2& b) {
return a.isApprox(b);
}
template <typename MatrixType>
std::enable_if_t<((MatrixType::Flags & RowMajorBit) == 0), void> check_left_top(const MatrixType& m, Index r, Index c,
Index rows, Index /*unused*/) {
if (c > 0) VERIFY_IS_EQUAL(m.leftCols(c).coeff(r + c * rows), m(r, c));
}
template <typename MatrixType>
std::enable_if_t<((MatrixType::Flags & RowMajorBit) != 0), void> check_left_top(const MatrixType& m, Index r, Index c,
Index /*unused*/, Index cols) {
if (r > 0) VERIFY_IS_EQUAL(m.topRows(r).coeff(c + r * cols), m(r, c));
}
template <typename MatrixType>
void block(const MatrixType& m) {
typedef typename MatrixType::Scalar Scalar;
typedef typename MatrixType::RealScalar RealScalar;
typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
typedef Matrix<Scalar, 1, MatrixType::ColsAtCompileTime> RowVectorType;
typedef Matrix<Scalar, Dynamic, Dynamic, MatrixType::IsRowMajor ? RowMajor : ColMajor> DynamicMatrixType;
typedef Matrix<Scalar, Dynamic, 1> DynamicVectorType;
Index rows = m.rows();
Index cols = m.cols();
MatrixType m1 = MatrixType::Random(rows, cols), m1_copy = m1, m2 = MatrixType::Random(rows, cols), m3(rows, cols),
ones = MatrixType::Ones(rows, cols);
VectorType v1 = VectorType::Random(rows);
Scalar s1 = internal::random<Scalar>();
Index r1 = internal::random<Index>(0, rows - 1);
Index r2 = internal::random<Index>(r1, rows - 1);
Index c1 = internal::random<Index>(0, cols - 1);
Index c2 = internal::random<Index>(c1, cols - 1);
block_real_only(m1, r1, r2, c1, c1, s1);
// check row() and col()
VERIFY_IS_EQUAL(m1.col(c1).transpose(), m1.transpose().row(c1));
// check operator(), both constant and non-constant, on row() and col()
m1 = m1_copy;
m1.row(r1) += s1 * m1_copy.row(r2);
VERIFY_IS_APPROX(m1.row(r1), m1_copy.row(r1) + s1 * m1_copy.row(r2));
// check nested block xpr on lhs
m1.row(r1).row(0) += s1 * m1_copy.row(r2);
VERIFY_IS_APPROX(m1.row(r1), m1_copy.row(r1) + Scalar(2) * s1 * m1_copy.row(r2));
m1 = m1_copy;
m1.col(c1) += s1 * m1_copy.col(c2);
VERIFY_IS_APPROX(m1.col(c1), m1_copy.col(c1) + s1 * m1_copy.col(c2));
m1.col(c1).col(0) += s1 * m1_copy.col(c2);
VERIFY_IS_APPROX(m1.col(c1), m1_copy.col(c1) + Scalar(2) * s1 * m1_copy.col(c2));
check_left_top(m1, r1, c1, rows, cols);
// check block()
Matrix<Scalar, Dynamic, Dynamic> b1(1, 1);
b1(0, 0) = m1(r1, c1);
RowVectorType br1(m1.block(r1, 0, 1, cols));
VectorType bc1(m1.block(0, c1, rows, 1));
VERIFY_IS_EQUAL(b1, m1.block(r1, c1, 1, 1));
VERIFY_IS_EQUAL(m1.row(r1), br1);
VERIFY_IS_EQUAL(m1.col(c1), bc1);
// check operator(), both constant and non-constant, on block()
m1.block(r1, c1, r2 - r1 + 1, c2 - c1 + 1) = s1 * m2.block(0, 0, r2 - r1 + 1, c2 - c1 + 1);
m1.block(r1, c1, r2 - r1 + 1, c2 - c1 + 1)(r2 - r1, c2 - c1) = m2.block(0, 0, r2 - r1 + 1, c2 - c1 + 1)(0, 0);
const Index BlockRows = 2;
const Index BlockCols = 5;
if (rows >= 5 && cols >= 8) {
// test fixed block() as lvalue
m1.template block<BlockRows, BlockCols>(1, 1) *= s1;
// test operator() on fixed block() both as constant and non-constant
m1.template block<BlockRows, BlockCols>(1, 1)(0, 3) = m1.template block<2, 5>(1, 1)(1, 2);
// check that fixed block() and block() agree
Matrix<Scalar, Dynamic, Dynamic> b = m1.template block<BlockRows, BlockCols>(3, 3);
VERIFY_IS_EQUAL(b, m1.block(3, 3, BlockRows, BlockCols));
// same tests with mixed fixed/dynamic size
m1.template block<BlockRows, Dynamic>(1, 1, BlockRows, BlockCols) *= s1;
m1.template block<BlockRows, Dynamic>(1, 1, BlockRows, BlockCols)(0, 3) = m1.template block<2, 5>(1, 1)(1, 2);
Matrix<Scalar, Dynamic, Dynamic> b2 = m1.template block<Dynamic, BlockCols>(3, 3, 2, 5);
VERIFY_IS_EQUAL(b2, m1.block(3, 3, BlockRows, BlockCols));
VERIFY(is_same_block(m1.block(3, 3, BlockRows, BlockCols),
m1.block(3, 3, fix<Dynamic>(BlockRows), fix<Dynamic>(BlockCols))));
VERIFY(is_same_block(m1.template block<BlockRows, Dynamic>(1, 1, BlockRows, BlockCols),
m1.block(1, 1, fix<BlockRows>, BlockCols)));
VERIFY(is_same_block(m1.template block<BlockRows, BlockCols>(1, 1, BlockRows, BlockCols),
m1.block(1, 1, fix<BlockRows>(), fix<BlockCols>)));
VERIFY(is_same_block(m1.template block<BlockRows, BlockCols>(1, 1, BlockRows, BlockCols),
m1.block(1, 1, fix<BlockRows>, fix<BlockCols>(BlockCols))));
}
if (rows > 2) {
// test sub vectors
VERIFY_IS_EQUAL(v1.template head<2>(), v1.block(0, 0, 2, 1));
VERIFY_IS_EQUAL(v1.template head<2>(), v1.head(2));
VERIFY_IS_EQUAL(v1.template head<2>(), v1.segment(0, 2));
VERIFY_IS_EQUAL(v1.template head<2>(), v1.template segment<2>(0));
Index i = rows - 2;
VERIFY_IS_EQUAL(v1.template tail<2>(), v1.block(i, 0, 2, 1));
VERIFY_IS_EQUAL(v1.template tail<2>(), v1.tail(2));
VERIFY_IS_EQUAL(v1.template tail<2>(), v1.segment(i, 2));
VERIFY_IS_EQUAL(v1.template tail<2>(), v1.template segment<2>(i));
i = internal::random<Index>(0, rows - 2);
VERIFY_IS_EQUAL(v1.segment(i, 2), v1.template segment<2>(i));
}
// stress some basic stuffs with block matrices
VERIFY_IS_EQUAL(numext::real(ones.col(c1).sum()), RealScalar(rows));
VERIFY_IS_EQUAL(numext::real(ones.row(r1).sum()), RealScalar(cols));
VERIFY_IS_EQUAL(numext::real(ones.col(c1).dot(ones.col(c2))), RealScalar(rows));
VERIFY_IS_EQUAL(numext::real(ones.row(r1).dot(ones.row(r2))), RealScalar(cols));
// check that linear accessors works on blocks
m1 = m1_copy;
// now test some block-inside-of-block.
// expressions with direct access
VERIFY_IS_EQUAL((m1.block(r1, c1, rows - r1, cols - c1).block(r2 - r1, c2 - c1, rows - r2, cols - c2)),
(m1.block(r2, c2, rows - r2, cols - c2)));
VERIFY_IS_EQUAL((m1.block(r1, c1, r2 - r1 + 1, c2 - c1 + 1).row(0)), (m1.row(r1).segment(c1, c2 - c1 + 1)));
VERIFY_IS_EQUAL((m1.block(r1, c1, r2 - r1 + 1, c2 - c1 + 1).col(0)), (m1.col(c1).segment(r1, r2 - r1 + 1)));
VERIFY_IS_EQUAL((m1.block(r1, c1, r2 - r1 + 1, c2 - c1 + 1).transpose().col(0)),
(m1.row(r1).segment(c1, c2 - c1 + 1)).transpose());
VERIFY_IS_EQUAL((m1.transpose().block(c1, r1, c2 - c1 + 1, r2 - r1 + 1).col(0)),
(m1.row(r1).segment(c1, c2 - c1 + 1)).transpose());
// expressions without direct access
VERIFY_IS_APPROX(((m1 + m2).block(r1, c1, rows - r1, cols - c1).block(r2 - r1, c2 - c1, rows - r2, cols - c2)),
((m1 + m2).block(r2, c2, rows - r2, cols - c2)));
VERIFY_IS_APPROX(((m1 + m2).block(r1, c1, r2 - r1 + 1, c2 - c1 + 1).row(0)),
((m1 + m2).row(r1).segment(c1, c2 - c1 + 1)));
VERIFY_IS_APPROX(((m1 + m2).block(r1, c1, r2 - r1 + 1, c2 - c1 + 1).row(0)),
((m1 + m2).eval().row(r1).segment(c1, c2 - c1 + 1)));
VERIFY_IS_APPROX(((m1 + m2).block(r1, c1, r2 - r1 + 1, c2 - c1 + 1).col(0)),
((m1 + m2).col(c1).segment(r1, r2 - r1 + 1)));
VERIFY_IS_APPROX(((m1 + m2).block(r1, c1, r2 - r1 + 1, c2 - c1 + 1).transpose().col(0)),
((m1 + m2).row(r1).segment(c1, c2 - c1 + 1)).transpose());
VERIFY_IS_APPROX(((m1 + m2).transpose().block(c1, r1, c2 - c1 + 1, r2 - r1 + 1).col(0)),
((m1 + m2).row(r1).segment(c1, c2 - c1 + 1)).transpose());
VERIFY_IS_APPROX(((m1 + m2).template block<Dynamic, 1>(r1, c1, r2 - r1 + 1, 1)),
((m1 + m2).eval().col(c1).eval().segment(r1, r2 - r1 + 1)));
VERIFY_IS_APPROX(((m1 + m2).template block<1, Dynamic>(r1, c1, 1, c2 - c1 + 1)),
((m1 + m2).eval().row(r1).eval().segment(c1, c2 - c1 + 1)));
VERIFY_IS_APPROX(((m1 + m2).transpose().template block<1, Dynamic>(c1, r1, 1, r2 - r1 + 1)),
((m1 + m2).eval().col(c1).eval().segment(r1, r2 - r1 + 1)).transpose());
VERIFY_IS_APPROX((m1 + m2).row(r1).eval(), (m1 + m2).eval().row(r1));
VERIFY_IS_APPROX((m1 + m2).adjoint().col(r1).eval(), (m1 + m2).adjoint().eval().col(r1));
VERIFY_IS_APPROX((m1 + m2).adjoint().row(c1).eval(), (m1 + m2).adjoint().eval().row(c1));
VERIFY_IS_APPROX((m1 * 1).row(r1).segment(c1, c2 - c1 + 1).eval(), m1.row(r1).eval().segment(c1, c2 - c1 + 1).eval());
VERIFY_IS_APPROX(m1.col(c1).reverse().segment(r1, r2 - r1 + 1).eval(),
m1.col(c1).reverse().eval().segment(r1, r2 - r1 + 1).eval());
VERIFY_IS_APPROX((m1 * 1).topRows(r1), m1.topRows(r1));
VERIFY_IS_APPROX((m1 * 1).leftCols(c1), m1.leftCols(c1));
VERIFY_IS_APPROX((m1 * 1).transpose().topRows(c1), m1.transpose().topRows(c1));
VERIFY_IS_APPROX((m1 * 1).transpose().leftCols(r1), m1.transpose().leftCols(r1));
VERIFY_IS_APPROX((m1 * 1).transpose().middleRows(c1, c2 - c1 + 1), m1.transpose().middleRows(c1, c2 - c1 + 1));
VERIFY_IS_APPROX((m1 * 1).transpose().middleCols(r1, r2 - r1 + 1), m1.transpose().middleCols(r1, r2 - r1 + 1));
// evaluation into plain matrices from expressions with direct access (stress MapBase)
DynamicMatrixType dm;
DynamicVectorType dv;
dm.setZero();
dm = m1.block(r1, c1, rows - r1, cols - c1).block(r2 - r1, c2 - c1, rows - r2, cols - c2);
VERIFY_IS_EQUAL(dm, (m1.block(r2, c2, rows - r2, cols - c2)));
dm.setZero();
dv.setZero();
dm = m1.block(r1, c1, r2 - r1 + 1, c2 - c1 + 1).row(0).transpose();
dv = m1.row(r1).segment(c1, c2 - c1 + 1);
VERIFY_IS_EQUAL(dv, dm);
dm.setZero();
dv.setZero();
dm = m1.col(c1).segment(r1, r2 - r1 + 1);
dv = m1.block(r1, c1, r2 - r1 + 1, c2 - c1 + 1).col(0);
VERIFY_IS_EQUAL(dv, dm);
dm.setZero();
dv.setZero();
dm = m1.block(r1, c1, r2 - r1 + 1, c2 - c1 + 1).transpose().col(0);
dv = m1.row(r1).segment(c1, c2 - c1 + 1);
VERIFY_IS_EQUAL(dv, dm);
dm.setZero();
dv.setZero();
dm = m1.row(r1).segment(c1, c2 - c1 + 1).transpose();
dv = m1.transpose().block(c1, r1, c2 - c1 + 1, r2 - r1 + 1).col(0);
VERIFY_IS_EQUAL(dv, dm);
VERIFY_IS_EQUAL((m1.template block<Dynamic, 1>(1, 0, 0, 1)), m1.block(1, 0, 0, 1));
VERIFY_IS_EQUAL((m1.template block<1, Dynamic>(0, 1, 1, 0)), m1.block(0, 1, 1, 0));
VERIFY_IS_EQUAL(((m1 * 1).template block<Dynamic, 1>(1, 0, 0, 1)), m1.block(1, 0, 0, 1));
VERIFY_IS_EQUAL(((m1 * 1).template block<1, Dynamic>(0, 1, 1, 0)), m1.block(0, 1, 1, 0));
VERIFY_IS_EQUAL(m1.template subVector<Horizontal>(r1), m1.row(r1));
VERIFY_IS_APPROX((m1 + m1).template subVector<Horizontal>(r1), (m1 + m1).row(r1));
VERIFY_IS_EQUAL(m1.template subVector<Vertical>(c1), m1.col(c1));
VERIFY_IS_APPROX((m1 + m1).template subVector<Vertical>(c1), (m1 + m1).col(c1));
VERIFY_IS_EQUAL(m1.template subVectors<Horizontal>(), m1.rows());
VERIFY_IS_EQUAL(m1.template subVectors<Vertical>(), m1.cols());
if (rows >= 2 || cols >= 2) {
VERIFY_IS_EQUAL(int(m1.middleCols(0, 0).IsRowMajor), int(m1.IsRowMajor));
VERIFY_IS_EQUAL(m1.middleCols(0, 0).outerSize(), m1.IsRowMajor ? rows : 0);
VERIFY_IS_EQUAL(m1.middleCols(0, 0).innerSize(), m1.IsRowMajor ? 0 : rows);
VERIFY_IS_EQUAL(int(m1.middleRows(0, 0).IsRowMajor), int(m1.IsRowMajor));
VERIFY_IS_EQUAL(m1.middleRows(0, 0).outerSize(), m1.IsRowMajor ? 0 : cols);
VERIFY_IS_EQUAL(m1.middleRows(0, 0).innerSize(), m1.IsRowMajor ? cols : 0);
}
}
template <typename MatrixType>
std::enable_if_t<MatrixType::IsVectorAtCompileTime, void> compare_using_data_and_stride(const MatrixType& m) {
Index rows = m.rows();
Index cols = m.cols();
Index size = m.size();
Index innerStride = m.innerStride();
Index rowStride = m.rowStride();
Index colStride = m.colStride();
const typename MatrixType::Scalar* data = m.data();
for (int j = 0; j < cols; ++j)
for (int i = 0; i < rows; ++i) VERIFY(m.coeff(i, j) == data[i * rowStride + j * colStride]);
VERIFY(innerStride == int((&m.coeff(1)) - (&m.coeff(0))));
for (int i = 0; i < size; ++i) VERIFY(m.coeff(i) == data[i * innerStride]);
}
template <typename MatrixType>
std::enable_if_t<!MatrixType::IsVectorAtCompileTime, void> compare_using_data_and_stride(const MatrixType& m) {
Index rows = m.rows();
Index cols = m.cols();
Index innerStride = m.innerStride();
Index outerStride = m.outerStride();
Index rowStride = m.rowStride();
Index colStride = m.colStride();
const typename MatrixType::Scalar* data = m.data();
for (int j = 0; j < cols; ++j)
for (int i = 0; i < rows; ++i) VERIFY(m.coeff(i, j) == data[i * rowStride + j * colStride]);
for (int j = 0; j < cols; ++j)
for (int i = 0; i < rows; ++i)
VERIFY(m.coeff(i, j) == data[(MatrixType::Flags & RowMajorBit) ? i * outerStride + j * innerStride
: j * outerStride + i * innerStride]);
}
template <typename MatrixType>
void data_and_stride(const MatrixType& m) {
Index rows = m.rows();
Index cols = m.cols();
Index r1 = internal::random<Index>(0, rows - 1);
Index r2 = internal::random<Index>(r1, rows - 1);
Index c1 = internal::random<Index>(0, cols - 1);
Index c2 = internal::random<Index>(c1, cols - 1);
MatrixType m1 = MatrixType::Random(rows, cols);
compare_using_data_and_stride(m1.block(r1, c1, r2 - r1 + 1, c2 - c1 + 1));
compare_using_data_and_stride(m1.transpose().block(c1, r1, c2 - c1 + 1, r2 - r1 + 1));
compare_using_data_and_stride(m1.row(r1));
compare_using_data_and_stride(m1.col(c1));
compare_using_data_and_stride(m1.row(r1).transpose());
compare_using_data_and_stride(m1.col(c1).transpose());
}
template <typename BaseXpr, typename Xpr = BaseXpr, int Depth = 0>
struct unwind_test_impl {
static void run(Xpr& xpr) {
Index startRow = internal::random<Index>(0, xpr.rows() / 5);
Index startCol = internal::random<Index>(0, xpr.cols() / 6);
Index rows = xpr.rows() / 3;
Index cols = xpr.cols() / 2;
// test equivalence of const expressions
const Block<const Xpr> constNestedBlock(xpr, startRow, startCol, rows, cols);
const Block<const BaseXpr> constUnwoundBlock = constNestedBlock.unwind();
VERIFY_IS_CWISE_EQUAL(constNestedBlock, constUnwoundBlock);
// modify a random element in each representation and test equivalence of non-const expressions
Block<Xpr> nestedBlock(xpr, startRow, startCol, rows, cols);
Block<BaseXpr> unwoundBlock = nestedBlock.unwind();
Index r1 = internal::random<Index>(0, rows - 1);
Index c1 = internal::random<Index>(0, cols - 1);
Index r2 = internal::random<Index>(0, rows - 1);
Index c2 = internal::random<Index>(0, cols - 1);
nestedBlock.coeffRef(r1, c1) = internal::random<typename DenseBase<Xpr>::Scalar>();
unwoundBlock.coeffRef(r2, c2) = internal::random<typename DenseBase<Xpr>::Scalar>();
VERIFY_IS_CWISE_EQUAL(nestedBlock, unwoundBlock);
unwind_test_impl<BaseXpr, Block<Xpr>, Depth + 1>::run(nestedBlock);
}
};
template <typename BaseXpr, typename Xpr>
struct unwind_test_impl<BaseXpr, Xpr, 4> {
static void run(const Xpr&) {}
};
template <typename BaseXpr>
void unwind_test(const BaseXpr&) {
BaseXpr xpr = BaseXpr::Random(100, 100);
unwind_test_impl<BaseXpr>::run(xpr);
}
EIGEN_DECLARE_TEST(block) {
for (int i = 0; i < g_repeat; i++) {
CALL_SUBTEST_1(block(Matrix<float, 1, 1>()));
CALL_SUBTEST_1(block(Matrix<float, 1, Dynamic>(internal::random(2, 50))));
CALL_SUBTEST_1(block(Matrix<float, Dynamic, 1>(internal::random(2, 50))));
CALL_SUBTEST_2(block(Matrix4d()));
CALL_SUBTEST_3(block(MatrixXcf(internal::random(2, 50), internal::random(2, 50))));
CALL_SUBTEST_4(block(MatrixXi(internal::random(2, 50), internal::random(2, 50))));
CALL_SUBTEST_5(block(MatrixXcd(internal::random(2, 50), internal::random(2, 50))));
CALL_SUBTEST_6(block(MatrixXf(internal::random(2, 50), internal::random(2, 50))));
CALL_SUBTEST_7(block(Matrix<int, Dynamic, Dynamic, RowMajor>(internal::random(2, 50), internal::random(2, 50))));
CALL_SUBTEST_8(block(Matrix<float, Dynamic, 4>(3, 4)));
CALL_SUBTEST_9(unwind_test(MatrixXf()));
#ifndef EIGEN_DEFAULT_TO_ROW_MAJOR
CALL_SUBTEST_6(data_and_stride(MatrixXf(internal::random(5, 50), internal::random(5, 50))));
CALL_SUBTEST_7(
data_and_stride(Matrix<int, Dynamic, Dynamic, RowMajor>(internal::random(5, 50), internal::random(5, 50))));
#endif
}
}