Squashed 'third_party/eigen/' content from commit 61d72f6
Change-Id: Iccc90fa0b55ab44037f018046d2fcffd90d9d025
git-subtree-dir: third_party/eigen
git-subtree-split: 61d72f6383cfa842868c53e30e087b0258177257
diff --git a/test/sparse_vector.cpp b/test/sparse_vector.cpp
new file mode 100644
index 0000000..0c94768
--- /dev/null
+++ b/test/sparse_vector.cpp
@@ -0,0 +1,110 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2008-2011 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 Scalar,typename Index> void sparse_vector(int rows, int cols)
+{
+ double densityMat = (std::max)(8./(rows*cols), 0.01);
+ double densityVec = (std::max)(8./float(rows), 0.1);
+ typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix;
+ typedef Matrix<Scalar,Dynamic,1> DenseVector;
+ typedef SparseVector<Scalar,0,Index> SparseVectorType;
+ typedef SparseMatrix<Scalar,0,Index> SparseMatrixType;
+ Scalar eps = 1e-6;
+
+ SparseMatrixType m1(rows,rows);
+ SparseVectorType v1(rows), v2(rows), v3(rows);
+ DenseMatrix refM1 = DenseMatrix::Zero(rows, rows);
+ DenseVector refV1 = DenseVector::Random(rows),
+ refV2 = DenseVector::Random(rows),
+ refV3 = DenseVector::Random(rows);
+
+ std::vector<int> zerocoords, nonzerocoords;
+ initSparse<Scalar>(densityVec, refV1, v1, &zerocoords, &nonzerocoords);
+ initSparse<Scalar>(densityMat, refM1, m1);
+
+ initSparse<Scalar>(densityVec, refV2, v2);
+ initSparse<Scalar>(densityVec, refV3, v3);
+
+ Scalar s1 = internal::random<Scalar>();
+
+ // test coeff and coeffRef
+ for (unsigned int i=0; i<zerocoords.size(); ++i)
+ {
+ VERIFY_IS_MUCH_SMALLER_THAN( v1.coeff(zerocoords[i]), eps );
+ //VERIFY_RAISES_ASSERT( v1.coeffRef(zerocoords[i]) = 5 );
+ }
+ {
+ VERIFY(int(nonzerocoords.size()) == v1.nonZeros());
+ int j=0;
+ for (typename SparseVectorType::InnerIterator it(v1); it; ++it,++j)
+ {
+ VERIFY(nonzerocoords[j]==it.index());
+ VERIFY(it.value()==v1.coeff(it.index()));
+ VERIFY(it.value()==refV1.coeff(it.index()));
+ }
+ }
+ VERIFY_IS_APPROX(v1, refV1);
+
+ v1.coeffRef(nonzerocoords[0]) = Scalar(5);
+ refV1.coeffRef(nonzerocoords[0]) = Scalar(5);
+ VERIFY_IS_APPROX(v1, refV1);
+
+ VERIFY_IS_APPROX(v1+v2, refV1+refV2);
+ VERIFY_IS_APPROX(v1+v2+v3, refV1+refV2+refV3);
+
+ VERIFY_IS_APPROX(v1*s1-v2, refV1*s1-refV2);
+
+ VERIFY_IS_APPROX(v1*=s1, refV1*=s1);
+ VERIFY_IS_APPROX(v1/=s1, refV1/=s1);
+
+ VERIFY_IS_APPROX(v1+=v2, refV1+=refV2);
+ VERIFY_IS_APPROX(v1-=v2, refV1-=refV2);
+
+ VERIFY_IS_APPROX(v1.dot(v2), refV1.dot(refV2));
+ VERIFY_IS_APPROX(v1.dot(refV2), refV1.dot(refV2));
+
+ VERIFY_IS_APPROX(v1.dot(m1*v2), refV1.dot(refM1*refV2));
+ int i = internal::random<int>(0,rows-1);
+ VERIFY_IS_APPROX(v1.dot(m1.col(i)), refV1.dot(refM1.col(i)));
+
+
+ VERIFY_IS_APPROX(v1.squaredNorm(), refV1.squaredNorm());
+
+ VERIFY_IS_APPROX(v1.blueNorm(), refV1.blueNorm());
+
+ // test aliasing
+ VERIFY_IS_APPROX((v1 = -v1), (refV1 = -refV1));
+ VERIFY_IS_APPROX((v1 = v1.transpose()), (refV1 = refV1.transpose().eval()));
+ VERIFY_IS_APPROX((v1 += -v1), (refV1 += -refV1));
+
+ // sparse matrix to sparse vector
+ SparseMatrixType mv1;
+ VERIFY_IS_APPROX((mv1=v1),v1);
+ VERIFY_IS_APPROX(mv1,(v1=mv1));
+ VERIFY_IS_APPROX(mv1,(v1=mv1.transpose()));
+
+ // check copy to dense vector with transpose
+ refV3.resize(0);
+ VERIFY_IS_APPROX(refV3 = v1.transpose(),v1.toDense());
+ VERIFY_IS_APPROX(DenseVector(v1),v1.toDense());
+
+}
+
+void test_sparse_vector()
+{
+ for(int i = 0; i < g_repeat; i++) {
+ CALL_SUBTEST_1(( sparse_vector<double,int>(8, 8) ));
+ CALL_SUBTEST_2(( sparse_vector<std::complex<double>, int>(16, 16) ));
+ CALL_SUBTEST_1(( sparse_vector<double,long int>(299, 535) ));
+ CALL_SUBTEST_1(( sparse_vector<double,short>(299, 535) ));
+ }
+}
+