1 files changed, 64 insertions, 0 deletions
diff --git a/test/product_large.cpp b/test/product_large.cpp
new file mode 100644
index 000000000..03d7bd8ed
--- /dev/null
+++ b/test/product_large.cpp
@@ -0,0 +1,64 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
+//
+// 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 "product.h"
+
+void test_product_large()
+{
+  for(int i = 0; i < g_repeat; i++) {
+    CALL_SUBTEST_1( product(MatrixXf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
+    CALL_SUBTEST_2( product(MatrixXd(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
+    CALL_SUBTEST_3( product(MatrixXi(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
+    CALL_SUBTEST_4( product(MatrixXcf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2), internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2))) );
+    CALL_SUBTEST_5( product(Matrix<float,Dynamic,Dynamic,RowMajor>(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
+  }
+
+#if defined EIGEN_TEST_PART_6
+  {
+    // test a specific issue in DiagonalProduct
+    int N = 1000000;
+    VectorXf v = VectorXf::Ones(N);
+    MatrixXf m = MatrixXf::Ones(N,3);
+    m = (v+v).asDiagonal() * m;
+    VERIFY_IS_APPROX(m, MatrixXf::Constant(N,3,2));
+  }
+
+  {
+    // test deferred resizing in Matrix::operator=
+    MatrixXf a = MatrixXf::Random(10,4), b = MatrixXf::Random(4,10), c = a;
+    VERIFY_IS_APPROX((a = a * b), (c * b).eval());
+  }
+
+  {
+    // check the functions to setup blocking sizes compile and do not segfault
+    // FIXME check they do what they are supposed to do !!
+    std::ptrdiff_t l1 = internal::random<int>(10000,20000);
+    std::ptrdiff_t l2 = internal::random<int>(1000000,2000000);
+    setCpuCacheSizes(l1,l2);
+    VERIFY(l1==l1CacheSize());
+    VERIFY(l2==l2CacheSize());
+    std::ptrdiff_t k1 = internal::random<int>(10,100)*16;
+    std::ptrdiff_t m1 = internal::random<int>(10,100)*16;
+    std::ptrdiff_t n1 = internal::random<int>(10,100)*16;
+    // only makes sure it compiles fine
+    internal::computeProductBlockingSizes<float,float>(k1,m1,n1);
+  }
+
+  {
+    // test regression in row-vector by matrix (bad Map type)
+    MatrixXf mat1(10,32); mat1.setRandom();
+    MatrixXf mat2(32,32); mat2.setRandom();
+    MatrixXf r1 = mat1.row(2)*mat2.transpose();
+    VERIFY_IS_APPROX(r1, (mat1.row(2)*mat2.transpose()).eval());
+
+    MatrixXf r2 = mat1.row(2)*mat2;
+    VERIFY_IS_APPROX(r2, (mat1.row(2)*mat2).eval());
+  }
+#endif
+}