Squashed 'third_party/eigen/' changes from 61d72f6..cf794d3
Change-Id: I9b814151b01f49af6337a8605d0c42a3a1ed4c72
git-subtree-dir: third_party/eigen
git-subtree-split: cf794d3b741a6278df169e58461f8529f43bce5d
diff --git a/test/sparse_block.cpp b/test/sparse_block.cpp
new file mode 100644
index 0000000..2a0b3b6
--- /dev/null
+++ b/test/sparse_block.cpp
@@ -0,0 +1,317 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2008-2015 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/.
+
+#include "sparse.h"
+
+template<typename T>
+typename Eigen::internal::enable_if<(T::Flags&RowMajorBit)==RowMajorBit, typename T::RowXpr>::type
+innervec(T& A, Index i)
+{
+ return A.row(i);
+}
+
+template<typename T>
+typename Eigen::internal::enable_if<(T::Flags&RowMajorBit)==0, typename T::ColXpr>::type
+innervec(T& A, Index i)
+{
+ return A.col(i);
+}
+
+template<typename SparseMatrixType> void sparse_block(const SparseMatrixType& ref)
+{
+ const Index rows = ref.rows();
+ const Index cols = ref.cols();
+ const Index inner = ref.innerSize();
+ const Index outer = ref.outerSize();
+
+ typedef typename SparseMatrixType::Scalar Scalar;
+ typedef typename SparseMatrixType::StorageIndex StorageIndex;
+
+ double density = (std::max)(8./(rows*cols), 0.01);
+ typedef Matrix<Scalar,Dynamic,Dynamic,SparseMatrixType::IsRowMajor?RowMajor:ColMajor> DenseMatrix;
+ typedef Matrix<Scalar,Dynamic,1> DenseVector;
+ typedef Matrix<Scalar,1,Dynamic> RowDenseVector;
+ typedef SparseVector<Scalar> SparseVectorType;
+
+ Scalar s1 = internal::random<Scalar>();
+ {
+ SparseMatrixType m(rows, cols);
+ DenseMatrix refMat = DenseMatrix::Zero(rows, cols);
+ initSparse<Scalar>(density, refMat, m);
+
+ VERIFY_IS_APPROX(m, refMat);
+
+ // test InnerIterators and Block expressions
+ for (int t=0; t<10; ++t)
+ {
+ Index j = internal::random<Index>(0,cols-2);
+ Index i = internal::random<Index>(0,rows-2);
+ Index w = internal::random<Index>(1,cols-j);
+ Index h = internal::random<Index>(1,rows-i);
+
+ VERIFY_IS_APPROX(m.block(i,j,h,w), refMat.block(i,j,h,w));
+ for(Index c=0; c<w; c++)
+ {
+ VERIFY_IS_APPROX(m.block(i,j,h,w).col(c), refMat.block(i,j,h,w).col(c));
+ for(Index r=0; r<h; r++)
+ {
+ VERIFY_IS_APPROX(m.block(i,j,h,w).col(c).coeff(r), refMat.block(i,j,h,w).col(c).coeff(r));
+ VERIFY_IS_APPROX(m.block(i,j,h,w).coeff(r,c), refMat.block(i,j,h,w).coeff(r,c));
+ }
+ }
+ for(Index r=0; r<h; r++)
+ {
+ VERIFY_IS_APPROX(m.block(i,j,h,w).row(r), refMat.block(i,j,h,w).row(r));
+ for(Index c=0; c<w; c++)
+ {
+ VERIFY_IS_APPROX(m.block(i,j,h,w).row(r).coeff(c), refMat.block(i,j,h,w).row(r).coeff(c));
+ VERIFY_IS_APPROX(m.block(i,j,h,w).coeff(r,c), refMat.block(i,j,h,w).coeff(r,c));
+ }
+ }
+
+ VERIFY_IS_APPROX(m.middleCols(j,w), refMat.middleCols(j,w));
+ VERIFY_IS_APPROX(m.middleRows(i,h), refMat.middleRows(i,h));
+ for(Index r=0; r<h; r++)
+ {
+ VERIFY_IS_APPROX(m.middleCols(j,w).row(r), refMat.middleCols(j,w).row(r));
+ VERIFY_IS_APPROX(m.middleRows(i,h).row(r), refMat.middleRows(i,h).row(r));
+ for(Index c=0; c<w; c++)
+ {
+ VERIFY_IS_APPROX(m.col(c).coeff(r), refMat.col(c).coeff(r));
+ VERIFY_IS_APPROX(m.row(r).coeff(c), refMat.row(r).coeff(c));
+
+ VERIFY_IS_APPROX(m.middleCols(j,w).coeff(r,c), refMat.middleCols(j,w).coeff(r,c));
+ VERIFY_IS_APPROX(m.middleRows(i,h).coeff(r,c), refMat.middleRows(i,h).coeff(r,c));
+ if(m.middleCols(j,w).coeff(r,c) != Scalar(0))
+ {
+ VERIFY_IS_APPROX(m.middleCols(j,w).coeffRef(r,c), refMat.middleCols(j,w).coeff(r,c));
+ }
+ if(m.middleRows(i,h).coeff(r,c) != Scalar(0))
+ {
+ VERIFY_IS_APPROX(m.middleRows(i,h).coeff(r,c), refMat.middleRows(i,h).coeff(r,c));
+ }
+ }
+ }
+ for(Index c=0; c<w; c++)
+ {
+ VERIFY_IS_APPROX(m.middleCols(j,w).col(c), refMat.middleCols(j,w).col(c));
+ VERIFY_IS_APPROX(m.middleRows(i,h).col(c), refMat.middleRows(i,h).col(c));
+ }
+ }
+
+ for(Index c=0; c<cols; c++)
+ {
+ VERIFY_IS_APPROX(m.col(c) + m.col(c), (m + m).col(c));
+ VERIFY_IS_APPROX(m.col(c) + m.col(c), refMat.col(c) + refMat.col(c));
+ }
+
+ for(Index r=0; r<rows; r++)
+ {
+ VERIFY_IS_APPROX(m.row(r) + m.row(r), (m + m).row(r));
+ VERIFY_IS_APPROX(m.row(r) + m.row(r), refMat.row(r) + refMat.row(r));
+ }
+ }
+
+ // test innerVector()
+ {
+ DenseMatrix refMat2 = DenseMatrix::Zero(rows, cols);
+ SparseMatrixType m2(rows, cols);
+ initSparse<Scalar>(density, refMat2, m2);
+ Index j0 = internal::random<Index>(0,outer-1);
+ Index j1 = internal::random<Index>(0,outer-1);
+ Index r0 = internal::random<Index>(0,rows-1);
+ Index c0 = internal::random<Index>(0,cols-1);
+
+ VERIFY_IS_APPROX(m2.innerVector(j0), innervec(refMat2,j0));
+ VERIFY_IS_APPROX(m2.innerVector(j0)+m2.innerVector(j1), innervec(refMat2,j0)+innervec(refMat2,j1));
+
+ m2.innerVector(j0) *= Scalar(2);
+ innervec(refMat2,j0) *= Scalar(2);
+ VERIFY_IS_APPROX(m2, refMat2);
+
+ m2.row(r0) *= Scalar(3);
+ refMat2.row(r0) *= Scalar(3);
+ VERIFY_IS_APPROX(m2, refMat2);
+
+ m2.col(c0) *= Scalar(4);
+ refMat2.col(c0) *= Scalar(4);
+ VERIFY_IS_APPROX(m2, refMat2);
+
+ m2.row(r0) /= Scalar(3);
+ refMat2.row(r0) /= Scalar(3);
+ VERIFY_IS_APPROX(m2, refMat2);
+
+ m2.col(c0) /= Scalar(4);
+ refMat2.col(c0) /= Scalar(4);
+ VERIFY_IS_APPROX(m2, refMat2);
+
+ SparseVectorType v1;
+ VERIFY_IS_APPROX(v1 = m2.col(c0) * 4, refMat2.col(c0)*4);
+ VERIFY_IS_APPROX(v1 = m2.row(r0) * 4, refMat2.row(r0).transpose()*4);
+
+ SparseMatrixType m3(rows,cols);
+ m3.reserve(VectorXi::Constant(outer,int(inner/2)));
+ for(Index j=0; j<outer; ++j)
+ for(Index k=0; k<(std::min)(j,inner); ++k)
+ m3.insertByOuterInner(j,k) = internal::convert_index<StorageIndex>(k+1);
+ for(Index j=0; j<(std::min)(outer, inner); ++j)
+ {
+ VERIFY(j==numext::real(m3.innerVector(j).nonZeros()));
+ if(j>0)
+ VERIFY(j==numext::real(m3.innerVector(j).lastCoeff()));
+ }
+ m3.makeCompressed();
+ for(Index j=0; j<(std::min)(outer, inner); ++j)
+ {
+ VERIFY(j==numext::real(m3.innerVector(j).nonZeros()));
+ if(j>0)
+ VERIFY(j==numext::real(m3.innerVector(j).lastCoeff()));
+ }
+
+ VERIFY(m3.innerVector(j0).nonZeros() == m3.transpose().innerVector(j0).nonZeros());
+
+// m2.innerVector(j0) = 2*m2.innerVector(j1);
+// refMat2.col(j0) = 2*refMat2.col(j1);
+// VERIFY_IS_APPROX(m2, refMat2);
+ }
+
+ // test innerVectors()
+ {
+ DenseMatrix refMat2 = DenseMatrix::Zero(rows, cols);
+ SparseMatrixType m2(rows, cols);
+ initSparse<Scalar>(density, refMat2, m2);
+ if(internal::random<float>(0,1)>0.5f) m2.makeCompressed();
+ Index j0 = internal::random<Index>(0,outer-2);
+ Index j1 = internal::random<Index>(0,outer-2);
+ Index n0 = internal::random<Index>(1,outer-(std::max)(j0,j1));
+ if(SparseMatrixType::IsRowMajor)
+ VERIFY_IS_APPROX(m2.innerVectors(j0,n0), refMat2.block(j0,0,n0,cols));
+ else
+ VERIFY_IS_APPROX(m2.innerVectors(j0,n0), refMat2.block(0,j0,rows,n0));
+ if(SparseMatrixType::IsRowMajor)
+ VERIFY_IS_APPROX(m2.innerVectors(j0,n0)+m2.innerVectors(j1,n0),
+ refMat2.middleRows(j0,n0)+refMat2.middleRows(j1,n0));
+ else
+ VERIFY_IS_APPROX(m2.innerVectors(j0,n0)+m2.innerVectors(j1,n0),
+ refMat2.block(0,j0,rows,n0)+refMat2.block(0,j1,rows,n0));
+
+ VERIFY_IS_APPROX(m2, refMat2);
+
+ VERIFY(m2.innerVectors(j0,n0).nonZeros() == m2.transpose().innerVectors(j0,n0).nonZeros());
+
+ m2.innerVectors(j0,n0) = m2.innerVectors(j0,n0) + m2.innerVectors(j1,n0);
+ if(SparseMatrixType::IsRowMajor)
+ refMat2.middleRows(j0,n0) = (refMat2.middleRows(j0,n0) + refMat2.middleRows(j1,n0)).eval();
+ else
+ refMat2.middleCols(j0,n0) = (refMat2.middleCols(j0,n0) + refMat2.middleCols(j1,n0)).eval();
+
+ VERIFY_IS_APPROX(m2, refMat2);
+ }
+
+ // test generic blocks
+ {
+ DenseMatrix refMat2 = DenseMatrix::Zero(rows, cols);
+ SparseMatrixType m2(rows, cols);
+ initSparse<Scalar>(density, refMat2, m2);
+ Index j0 = internal::random<Index>(0,outer-2);
+ Index j1 = internal::random<Index>(0,outer-2);
+ Index n0 = internal::random<Index>(1,outer-(std::max)(j0,j1));
+ if(SparseMatrixType::IsRowMajor)
+ VERIFY_IS_APPROX(m2.block(j0,0,n0,cols), refMat2.block(j0,0,n0,cols));
+ else
+ VERIFY_IS_APPROX(m2.block(0,j0,rows,n0), refMat2.block(0,j0,rows,n0));
+
+ if(SparseMatrixType::IsRowMajor)
+ VERIFY_IS_APPROX(m2.block(j0,0,n0,cols)+m2.block(j1,0,n0,cols),
+ refMat2.block(j0,0,n0,cols)+refMat2.block(j1,0,n0,cols));
+ else
+ VERIFY_IS_APPROX(m2.block(0,j0,rows,n0)+m2.block(0,j1,rows,n0),
+ refMat2.block(0,j0,rows,n0)+refMat2.block(0,j1,rows,n0));
+
+ Index i = internal::random<Index>(0,m2.outerSize()-1);
+ if(SparseMatrixType::IsRowMajor) {
+ m2.innerVector(i) = m2.innerVector(i) * s1;
+ refMat2.row(i) = refMat2.row(i) * s1;
+ VERIFY_IS_APPROX(m2,refMat2);
+ } else {
+ m2.innerVector(i) = m2.innerVector(i) * s1;
+ refMat2.col(i) = refMat2.col(i) * s1;
+ VERIFY_IS_APPROX(m2,refMat2);
+ }
+
+ Index r0 = internal::random<Index>(0,rows-2);
+ Index c0 = internal::random<Index>(0,cols-2);
+ Index r1 = internal::random<Index>(1,rows-r0);
+ Index c1 = internal::random<Index>(1,cols-c0);
+
+ VERIFY_IS_APPROX(DenseVector(m2.col(c0)), refMat2.col(c0));
+ VERIFY_IS_APPROX(m2.col(c0), refMat2.col(c0));
+
+ VERIFY_IS_APPROX(RowDenseVector(m2.row(r0)), refMat2.row(r0));
+ VERIFY_IS_APPROX(m2.row(r0), refMat2.row(r0));
+
+ VERIFY_IS_APPROX(m2.block(r0,c0,r1,c1), refMat2.block(r0,c0,r1,c1));
+ VERIFY_IS_APPROX((2*m2).block(r0,c0,r1,c1), (2*refMat2).block(r0,c0,r1,c1));
+
+ if(m2.nonZeros()>0)
+ {
+ VERIFY_IS_APPROX(m2, refMat2);
+ SparseMatrixType m3(rows, cols);
+ DenseMatrix refMat3(rows, cols); refMat3.setZero();
+ Index n = internal::random<Index>(1,10);
+ for(Index k=0; k<n; ++k)
+ {
+ Index o1 = internal::random<Index>(0,outer-1);
+ Index o2 = internal::random<Index>(0,outer-1);
+ if(SparseMatrixType::IsRowMajor)
+ {
+ m3.innerVector(o1) = m2.row(o2);
+ refMat3.row(o1) = refMat2.row(o2);
+ }
+ else
+ {
+ m3.innerVector(o1) = m2.col(o2);
+ refMat3.col(o1) = refMat2.col(o2);
+ }
+ if(internal::random<bool>())
+ m3.makeCompressed();
+ }
+ if(m3.nonZeros()>0)
+ VERIFY_IS_APPROX(m3, refMat3);
+ }
+ }
+}
+
+void test_sparse_block()
+{
+ for(int i = 0; i < g_repeat; i++) {
+ int r = Eigen::internal::random<int>(1,200), c = Eigen::internal::random<int>(1,200);
+ if(Eigen::internal::random<int>(0,4) == 0) {
+ r = c; // check square matrices in 25% of tries
+ }
+ EIGEN_UNUSED_VARIABLE(r+c);
+ CALL_SUBTEST_1(( sparse_block(SparseMatrix<double>(1, 1)) ));
+ CALL_SUBTEST_1(( sparse_block(SparseMatrix<double>(8, 8)) ));
+ CALL_SUBTEST_1(( sparse_block(SparseMatrix<double>(r, c)) ));
+ CALL_SUBTEST_2(( sparse_block(SparseMatrix<std::complex<double>, ColMajor>(r, c)) ));
+ CALL_SUBTEST_2(( sparse_block(SparseMatrix<std::complex<double>, RowMajor>(r, c)) ));
+
+ CALL_SUBTEST_3(( sparse_block(SparseMatrix<double,ColMajor,long int>(r, c)) ));
+ CALL_SUBTEST_3(( sparse_block(SparseMatrix<double,RowMajor,long int>(r, c)) ));
+
+ r = Eigen::internal::random<int>(1,100);
+ c = Eigen::internal::random<int>(1,100);
+ if(Eigen::internal::random<int>(0,4) == 0) {
+ r = c; // check square matrices in 25% of tries
+ }
+
+ CALL_SUBTEST_4(( sparse_block(SparseMatrix<double,ColMajor,short int>(short(r), short(c))) ));
+ CALL_SUBTEST_4(( sparse_block(SparseMatrix<double,RowMajor,short int>(short(r), short(c))) ));
+ }
+}