Add SparseVector::conservativeResize() method.
diff --git a/test/sparse_vector.cpp b/test/sparse_vector.cpp
index d3975b9..d95f301 100644
--- a/test/sparse_vector.cpp
+++ b/test/sparse_vector.cpp
@@ -9,14 +9,14 @@
#include "sparse.h"
-template<typename Scalar,typename Index> void sparse_vector(int rows, int cols)
+template<typename Scalar,typename StorageIndex> 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;
+ typedef SparseVector<Scalar,0,StorageIndex> SparseVectorType;
+ typedef SparseMatrix<Scalar,0,StorageIndex> SparseMatrixType;
Scalar eps = 1e-6;
SparseMatrixType m1(rows,rows);
@@ -87,8 +87,10 @@
VERIFY_IS_APPROX(m1*v2, refM1*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)));
+ {
+ 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());
@@ -111,15 +113,51 @@
VERIFY_IS_APPROX(refV3 = v1.transpose(),v1.toDense());
VERIFY_IS_APPROX(DenseVector(v1),v1.toDense());
+ // test conservative resize
+ {
+ std::vector<StorageIndex> inc;
+ if(rows > 3)
+ inc.push_back(-3);
+ inc.push_back(0);
+ inc.push_back(3);
+ inc.push_back(1);
+ inc.push_back(10);
+
+ for(std::size_t i = 0; i< inc.size(); i++) {
+ StorageIndex incRows = inc[i];
+ SparseVectorType vec1(rows);
+ DenseVector refVec1 = DenseVector::Zero(rows);
+ initSparse<Scalar>(densityVec, refVec1, vec1);
+
+ vec1.conservativeResize(rows+incRows);
+ refVec1.conservativeResize(rows+incRows);
+ if (incRows > 0) refVec1.tail(incRows).setZero();
+
+ VERIFY_IS_APPROX(vec1, refVec1);
+
+ // Insert new values
+ if (incRows > 0)
+ vec1.insert(vec1.rows()-1) = refVec1(refVec1.rows()-1) = 1;
+
+ VERIFY_IS_APPROX(vec1, refVec1);
+ }
+ }
+
}
void test_sparse_vector()
{
for(int i = 0; i < g_repeat; i++) {
+ int r = Eigen::internal::random<int>(1,500), c = Eigen::internal::random<int>(1,500);
+ 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_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) ));
+ CALL_SUBTEST_2(( sparse_vector<std::complex<double>, int>(r, c) ));
+ CALL_SUBTEST_1(( sparse_vector<double,long int>(r, c) ));
+ CALL_SUBTEST_1(( sparse_vector<double,short>(r, c) ));
}
}