update sparse*sparse product: the default is now a conservative algorithm preserving symbolic non zeros. The previous with auto pruning of the small value is avaible doing: (A*B).pruned() or (A*B).pruned(ref) or (A*B).pruned(ref,eps)

1 files changed, 6 insertions, 0 deletions

diff --git a/test/sparse_product.cpp b/test/sparse_product.cpp
index ac1dac5f5..ce7480471 100644
--- a/test/sparse_product.cpp
+++ b/test/sparse_product.cpp
@@ -94,6 +94,7 @@ template<typename SparseMatrixType> void sparse_product()
 
 //     int c = internal::random<int>(0,depth-1);
 
+    // sparse * sparse
     VERIFY_IS_APPROX(m4=m2*m3, refMat4=refMat2*refMat3);
     VERIFY_IS_APPROX(m4=m2t.transpose()*m3, refMat4=refMat2t.transpose()*refMat3);
     VERIFY_IS_APPROX(m4=m2t.transpose()*m3t.transpose(), refMat4=refMat2t.transpose()*refMat3t.transpose());
@@ -103,6 +104,11 @@ template<typename SparseMatrixType> void sparse_product()
     VERIFY_IS_APPROX(m4 = m2*m3*s1, refMat4 = refMat2*refMat3*s1);
     VERIFY_IS_APPROX(m4 = s2*m2*m3*s1, refMat4 = s2*refMat2*refMat3*s1);
 
+    VERIFY_IS_APPROX(m4=(m2*m3).pruned(0), refMat4=refMat2*refMat3);
+    VERIFY_IS_APPROX(m4=(m2t.transpose()*m3).pruned(0), refMat4=refMat2t.transpose()*refMat3);
+    VERIFY_IS_APPROX(m4=(m2t.transpose()*m3t.transpose()).pruned(0), refMat4=refMat2t.transpose()*refMat3t.transpose());
+    VERIFY_IS_APPROX(m4=(m2*m3t.transpose()).pruned(0), refMat4=refMat2*refMat3t.transpose());
+
     // sparse * dense
     VERIFY_IS_APPROX(dm4=m2*refMat3, refMat4=refMat2*refMat3);
     VERIFY_IS_APPROX(dm4=m2*refMat3t.transpose(), refMat4=refMat2*refMat3t.transpose());