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// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2011-2015 Gael Guennebaud <gael.guennebaud@inria.fr>
//
// 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/.
static long int nb_transposed_copies;
#define EIGEN_SPARSE_TRANSPOSED_COPY_PLUGIN {nb_transposed_copies++;}
#define VERIFY_TRANSPOSITION_COUNT(XPR,N) {\
nb_transposed_copies = 0; \
XPR; \
if(nb_transposed_copies!=N) std::cerr << "nb_transposed_copies == " << nb_transposed_copies << "\n"; \
VERIFY( (#XPR) && nb_transposed_copies==N ); \
}
template<typename T>
bool is_sorted(const T& mat) {
for(Index k = 0; k<mat.outerSize(); ++k)
{
Index prev = -1;
for(typename T::InnerIterator it(mat,k); it; ++it)
{
if(prev>=it.index())
return false;
prev = it.index();
}
}
return true;
}
template<typename T>
typename internal::nested_eval<T,1>::type eval(const T &xpr)
VERIFY( int(internal::nested_eval<T,1>::type::Flags&RowMajorBit) == int(internal::evaluator<T>::Flags&RowMajorBit) );
return xpr;
}
template<int OtherStorage, typename SparseMatrixType> void sparse_permutations(const SparseMatrixType& ref)
{
const Index rows = ref.rows();
const Index cols = ref.cols();
typedef typename SparseMatrixType::Scalar Scalar;
typedef typename SparseMatrixType::StorageIndex StorageIndex;
typedef SparseMatrix<Scalar, OtherStorage, StorageIndex> OtherSparseMatrixType;
typedef Matrix<StorageIndex,Dynamic,1> VectorI;
// bool IsRowMajor1 = SparseMatrixType::IsRowMajor;
// bool IsRowMajor2 = OtherSparseMatrixType::IsRowMajor;
double density = (std::max)(8./(rows*cols), 0.01);
SparseMatrixType mat(rows, cols), up(rows,cols), lo(rows,cols);
OtherSparseMatrixType res;
DenseMatrix mat_d = DenseMatrix::Zero(rows, cols), up_sym_d, lo_sym_d, res_d;
initSparse<Scalar>(density, mat_d, mat, 0);
up = mat.template triangularView<Upper>();
lo = mat.template triangularView<Lower>();
up_sym_d = mat_d.template selfadjointView<Upper>();
lo_sym_d = mat_d.template selfadjointView<Lower>();
VERIFY_IS_APPROX(mat, mat_d);
VERIFY_IS_APPROX(up, DenseMatrix(mat_d.template triangularView<Upper>()));
VERIFY_IS_APPROX(lo, DenseMatrix(mat_d.template triangularView<Lower>()));
PermutationMatrix<Dynamic> p, p_null;
VectorI pi;
randomPermutationVector(pi, cols);
p.indices() = pi;
VERIFY( is_sorted( ::eval(mat*p) ));
VERIFY( is_sorted( res = mat*p ));
VERIFY_TRANSPOSITION_COUNT( ::eval(mat*p), 0);
//VERIFY_TRANSPOSITION_COUNT( res = mat*p, IsRowMajor ? 1 : 0 );
VERIFY( is_sorted( ::eval(p*mat) ));
VERIFY( is_sorted( res = p*mat ));
VERIFY_TRANSPOSITION_COUNT( ::eval(p*mat), 0);
VERIFY( is_sorted( (mat*p).eval() ));
VERIFY( is_sorted( res = mat*p.inverse() ));
VERIFY_TRANSPOSITION_COUNT( ::eval(mat*p.inverse()), 0);
res_d = mat*p.inverse();
VERIFY(res.isApprox(res_d) && "mat*inv(p)");
VERIFY( is_sorted( (p*mat+p*mat).eval() ));
VERIFY( is_sorted( res = p.inverse()*mat ));
VERIFY_TRANSPOSITION_COUNT( ::eval(p.inverse()*mat), 0);
res_d = p.inverse()*mat_d;
VERIFY(res.isApprox(res_d) && "inv(p)*mat");
VERIFY( is_sorted( (p * mat * p.inverse()).eval() ));
VERIFY( is_sorted( res = mat.twistedBy(p) ));
VERIFY_TRANSPOSITION_COUNT( ::eval(p * mat * p.inverse()), 0);
res_d = (p * mat_d) * p.inverse();
VERIFY(res.isApprox(res_d) && "p*mat*inv(p)");
VERIFY( is_sorted( res = mat.template selfadjointView<Upper>().twistedBy(p_null) ));
res_d = up_sym_d;
VERIFY(res.isApprox(res_d) && "full selfadjoint upper to full");
VERIFY( is_sorted( res = mat.template selfadjointView<Lower>().twistedBy(p_null) ));
res_d = lo_sym_d;
VERIFY(res.isApprox(res_d) && "full selfadjoint lower to full");
VERIFY( is_sorted( res = up.template selfadjointView<Upper>().twistedBy(p_null) ));
res_d = up_sym_d;
VERIFY(res.isApprox(res_d) && "upper selfadjoint to full");
VERIFY( is_sorted( res = lo.template selfadjointView<Lower>().twistedBy(p_null) ));
res_d = lo_sym_d;
VERIFY(res.isApprox(res_d) && "lower selfadjoint full");
VERIFY( is_sorted( res = mat.template selfadjointView<Upper>() ));
res_d = up_sym_d;
VERIFY(res.isApprox(res_d) && "full selfadjoint upper to full");
VERIFY( is_sorted( res = mat.template selfadjointView<Lower>() ));
res_d = lo_sym_d;
VERIFY(res.isApprox(res_d) && "full selfadjoint lower to full");
VERIFY( is_sorted( res = up.template selfadjointView<Upper>() ));
res_d = up_sym_d;
VERIFY(res.isApprox(res_d) && "upper selfadjoint to full");
VERIFY( is_sorted( res = lo.template selfadjointView<Lower>() ));
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res_d = lo_sym_d;
VERIFY(res.isApprox(res_d) && "lower selfadjoint full");
res.template selfadjointView<Upper>() = mat.template selfadjointView<Upper>();
res_d = up_sym_d.template triangularView<Upper>();
VERIFY(res.isApprox(res_d) && "full selfadjoint upper to upper");
res.template selfadjointView<Lower>() = mat.template selfadjointView<Upper>();
res_d = up_sym_d.template triangularView<Lower>();
VERIFY(res.isApprox(res_d) && "full selfadjoint upper to lower");
res.template selfadjointView<Upper>() = mat.template selfadjointView<Lower>();
res_d = lo_sym_d.template triangularView<Upper>();
VERIFY(res.isApprox(res_d) && "full selfadjoint lower to upper");
res.template selfadjointView<Lower>() = mat.template selfadjointView<Lower>();
res_d = lo_sym_d.template triangularView<Lower>();
VERIFY(res.isApprox(res_d) && "full selfadjoint lower to lower");
res.template selfadjointView<Upper>() = mat.template selfadjointView<Upper>().twistedBy(p);
res_d = ((p * up_sym_d) * p.inverse()).eval().template triangularView<Upper>();
VERIFY(res.isApprox(res_d) && "full selfadjoint upper twisted to upper");
res.template selfadjointView<Upper>() = mat.template selfadjointView<Lower>().twistedBy(p);
res_d = ((p * lo_sym_d) * p.inverse()).eval().template triangularView<Upper>();
VERIFY(res.isApprox(res_d) && "full selfadjoint lower twisted to upper");
res.template selfadjointView<Lower>() = mat.template selfadjointView<Lower>().twistedBy(p);
res_d = ((p * lo_sym_d) * p.inverse()).eval().template triangularView<Lower>();
VERIFY(res.isApprox(res_d) && "full selfadjoint lower twisted to lower");
res.template selfadjointView<Lower>() = mat.template selfadjointView<Upper>().twistedBy(p);
res_d = ((p * up_sym_d) * p.inverse()).eval().template triangularView<Lower>();
VERIFY(res.isApprox(res_d) && "full selfadjoint upper twisted to lower");
res.template selfadjointView<Upper>() = up.template selfadjointView<Upper>().twistedBy(p);
res_d = ((p * up_sym_d) * p.inverse()).eval().template triangularView<Upper>();
VERIFY(res.isApprox(res_d) && "upper selfadjoint twisted to upper");
res.template selfadjointView<Upper>() = lo.template selfadjointView<Lower>().twistedBy(p);
res_d = ((p * lo_sym_d) * p.inverse()).eval().template triangularView<Upper>();
VERIFY(res.isApprox(res_d) && "lower selfadjoint twisted to upper");
res.template selfadjointView<Lower>() = lo.template selfadjointView<Lower>().twistedBy(p);
res_d = ((p * lo_sym_d) * p.inverse()).eval().template triangularView<Lower>();
VERIFY(res.isApprox(res_d) && "lower selfadjoint twisted to lower");
res.template selfadjointView<Lower>() = up.template selfadjointView<Upper>().twistedBy(p);
res_d = ((p * up_sym_d) * p.inverse()).eval().template triangularView<Lower>();
VERIFY(res.isApprox(res_d) && "upper selfadjoint twisted to lower");
VERIFY( is_sorted( res = mat.template selfadjointView<Upper>().twistedBy(p) ));
res_d = (p * up_sym_d) * p.inverse();
VERIFY(res.isApprox(res_d) && "full selfadjoint upper twisted to full");
VERIFY( is_sorted( res = mat.template selfadjointView<Lower>().twistedBy(p) ));
res_d = (p * lo_sym_d) * p.inverse();
VERIFY(res.isApprox(res_d) && "full selfadjoint lower twisted to full");
VERIFY( is_sorted( res = up.template selfadjointView<Upper>().twistedBy(p) ));
res_d = (p * up_sym_d) * p.inverse();
VERIFY(res.isApprox(res_d) && "upper selfadjoint twisted to full");
VERIFY( is_sorted( res = lo.template selfadjointView<Lower>().twistedBy(p) ));
res_d = (p * lo_sym_d) * p.inverse();
VERIFY(res.isApprox(res_d) && "lower selfadjoint twisted to full");
}
template<typename Scalar> void sparse_permutations_all(int size)
{
CALL_SUBTEST(( sparse_permutations<ColMajor>(SparseMatrix<Scalar, ColMajor>(size,size)) ));
CALL_SUBTEST(( sparse_permutations<ColMajor>(SparseMatrix<Scalar, RowMajor>(size,size)) ));
CALL_SUBTEST(( sparse_permutations<RowMajor>(SparseMatrix<Scalar, ColMajor>(size,size)) ));
CALL_SUBTEST(( sparse_permutations<RowMajor>(SparseMatrix<Scalar, RowMajor>(size,size)) ));
}
void test_sparse_permutations()
{
for(int i = 0; i < g_repeat; i++) {
int s = Eigen::internal::random<int>(1,50);
CALL_SUBTEST_1(( sparse_permutations_all<double>(s) ));
CALL_SUBTEST_2(( sparse_permutations_all<std::complex<double> >(s) ));
}
VERIFY((internal::is_same<internal::permutation_matrix_product<SparseMatrix<double>,OnTheRight,false,SparseShape>::ReturnType,
internal::nested_eval<Product<SparseMatrix<double>,PermutationMatrix<Dynamic,Dynamic>,AliasFreeProduct>,1>::type>::value));
VERIFY((internal::is_same<internal::permutation_matrix_product<SparseMatrix<double>,OnTheLeft,false,SparseShape>::ReturnType,
internal::nested_eval<Product<PermutationMatrix<Dynamic,Dynamic>,SparseMatrix<double>,AliasFreeProduct>,1>::type>::value));