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-rw-r--r--eigen/test/product_syrk.cpp135
1 files changed, 135 insertions, 0 deletions
diff --git a/eigen/test/product_syrk.cpp b/eigen/test/product_syrk.cpp
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--- /dev/null
+++ b/eigen/test/product_syrk.cpp
@@ -0,0 +1,135 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2008-2009 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 "main.h"
+
+template<typename MatrixType> void syrk(const MatrixType& m)
+{
+ typedef typename MatrixType::Index Index;
+ typedef typename MatrixType::Scalar Scalar;
+ typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::ColsAtCompileTime, RowMajor> RMatrixType;
+ typedef Matrix<Scalar, MatrixType::ColsAtCompileTime, Dynamic> Rhs1;
+ typedef Matrix<Scalar, Dynamic, MatrixType::RowsAtCompileTime> Rhs2;
+ typedef Matrix<Scalar, MatrixType::ColsAtCompileTime, Dynamic,RowMajor> Rhs3;
+
+ Index rows = m.rows();
+ Index cols = m.cols();
+
+ MatrixType m1 = MatrixType::Random(rows, cols),
+ m2 = MatrixType::Random(rows, cols),
+ m3 = MatrixType::Random(rows, cols);
+ RMatrixType rm2 = MatrixType::Random(rows, cols);
+
+ Rhs1 rhs1 = Rhs1::Random(internal::random<int>(1,320), cols); Rhs1 rhs11 = Rhs1::Random(rhs1.rows(), cols);
+ Rhs2 rhs2 = Rhs2::Random(rows, internal::random<int>(1,320)); Rhs2 rhs22 = Rhs2::Random(rows, rhs2.cols());
+ Rhs3 rhs3 = Rhs3::Random(internal::random<int>(1,320), rows);
+
+ Scalar s1 = internal::random<Scalar>();
+
+ Index c = internal::random<Index>(0,cols-1);
+
+ m2.setZero();
+ VERIFY_IS_APPROX((m2.template selfadjointView<Lower>().rankUpdate(rhs2,s1)._expression()),
+ ((s1 * rhs2 * rhs2.adjoint()).eval().template triangularView<Lower>().toDenseMatrix()));
+ m2.setZero();
+ VERIFY_IS_APPROX(((m2.template triangularView<Lower>() += s1 * rhs2 * rhs22.adjoint()).nestedExpression()),
+ ((s1 * rhs2 * rhs22.adjoint()).eval().template triangularView<Lower>().toDenseMatrix()));
+
+
+ m2.setZero();
+ VERIFY_IS_APPROX(m2.template selfadjointView<Upper>().rankUpdate(rhs2,s1)._expression(),
+ (s1 * rhs2 * rhs2.adjoint()).eval().template triangularView<Upper>().toDenseMatrix());
+ m2.setZero();
+ VERIFY_IS_APPROX((m2.template triangularView<Upper>() += s1 * rhs22 * rhs2.adjoint()).nestedExpression(),
+ (s1 * rhs22 * rhs2.adjoint()).eval().template triangularView<Upper>().toDenseMatrix());
+
+
+ m2.setZero();
+ VERIFY_IS_APPROX(m2.template selfadjointView<Lower>().rankUpdate(rhs1.adjoint(),s1)._expression(),
+ (s1 * rhs1.adjoint() * rhs1).eval().template triangularView<Lower>().toDenseMatrix());
+ m2.setZero();
+ VERIFY_IS_APPROX((m2.template triangularView<Lower>() += s1 * rhs11.adjoint() * rhs1).nestedExpression(),
+ (s1 * rhs11.adjoint() * rhs1).eval().template triangularView<Lower>().toDenseMatrix());
+
+
+ m2.setZero();
+ VERIFY_IS_APPROX(m2.template selfadjointView<Upper>().rankUpdate(rhs1.adjoint(),s1)._expression(),
+ (s1 * rhs1.adjoint() * rhs1).eval().template triangularView<Upper>().toDenseMatrix());
+ VERIFY_IS_APPROX((m2.template triangularView<Upper>() = s1 * rhs1.adjoint() * rhs11).nestedExpression(),
+ (s1 * rhs1.adjoint() * rhs11).eval().template triangularView<Upper>().toDenseMatrix());
+
+
+ m2.setZero();
+ VERIFY_IS_APPROX(m2.template selfadjointView<Lower>().rankUpdate(rhs3.adjoint(),s1)._expression(),
+ (s1 * rhs3.adjoint() * rhs3).eval().template triangularView<Lower>().toDenseMatrix());
+
+ m2.setZero();
+ VERIFY_IS_APPROX(m2.template selfadjointView<Upper>().rankUpdate(rhs3.adjoint(),s1)._expression(),
+ (s1 * rhs3.adjoint() * rhs3).eval().template triangularView<Upper>().toDenseMatrix());
+
+ m2.setZero();
+ VERIFY_IS_APPROX((m2.template selfadjointView<Lower>().rankUpdate(m1.col(c),s1)._expression()),
+ ((s1 * m1.col(c) * m1.col(c).adjoint()).eval().template triangularView<Lower>().toDenseMatrix()));
+
+ m2.setZero();
+ VERIFY_IS_APPROX((m2.template selfadjointView<Upper>().rankUpdate(m1.col(c),s1)._expression()),
+ ((s1 * m1.col(c) * m1.col(c).adjoint()).eval().template triangularView<Upper>().toDenseMatrix()));
+ rm2.setZero();
+ VERIFY_IS_APPROX((rm2.template selfadjointView<Upper>().rankUpdate(m1.col(c),s1)._expression()),
+ ((s1 * m1.col(c) * m1.col(c).adjoint()).eval().template triangularView<Upper>().toDenseMatrix()));
+ m2.setZero();
+ VERIFY_IS_APPROX((m2.template triangularView<Upper>() += s1 * m3.col(c) * m1.col(c).adjoint()).nestedExpression(),
+ ((s1 * m3.col(c) * m1.col(c).adjoint()).eval().template triangularView<Upper>().toDenseMatrix()));
+ rm2.setZero();
+ VERIFY_IS_APPROX((rm2.template triangularView<Upper>() += s1 * m1.col(c) * m3.col(c).adjoint()).nestedExpression(),
+ ((s1 * m1.col(c) * m3.col(c).adjoint()).eval().template triangularView<Upper>().toDenseMatrix()));
+
+ m2.setZero();
+ VERIFY_IS_APPROX((m2.template selfadjointView<Lower>().rankUpdate(m1.col(c).conjugate(),s1)._expression()),
+ ((s1 * m1.col(c).conjugate() * m1.col(c).conjugate().adjoint()).eval().template triangularView<Lower>().toDenseMatrix()));
+
+ m2.setZero();
+ VERIFY_IS_APPROX((m2.template selfadjointView<Upper>().rankUpdate(m1.col(c).conjugate(),s1)._expression()),
+ ((s1 * m1.col(c).conjugate() * m1.col(c).conjugate().adjoint()).eval().template triangularView<Upper>().toDenseMatrix()));
+
+
+ m2.setZero();
+ VERIFY_IS_APPROX((m2.template selfadjointView<Lower>().rankUpdate(m1.row(c),s1)._expression()),
+ ((s1 * m1.row(c).transpose() * m1.row(c).transpose().adjoint()).eval().template triangularView<Lower>().toDenseMatrix()));
+ rm2.setZero();
+ VERIFY_IS_APPROX((rm2.template selfadjointView<Lower>().rankUpdate(m1.row(c),s1)._expression()),
+ ((s1 * m1.row(c).transpose() * m1.row(c).transpose().adjoint()).eval().template triangularView<Lower>().toDenseMatrix()));
+ m2.setZero();
+ VERIFY_IS_APPROX((m2.template triangularView<Lower>() += s1 * m3.row(c).transpose() * m1.row(c).transpose().adjoint()).nestedExpression(),
+ ((s1 * m3.row(c).transpose() * m1.row(c).transpose().adjoint()).eval().template triangularView<Lower>().toDenseMatrix()));
+ rm2.setZero();
+ VERIFY_IS_APPROX((rm2.template triangularView<Lower>() += s1 * m3.row(c).transpose() * m1.row(c).transpose().adjoint()).nestedExpression(),
+ ((s1 * m3.row(c).transpose() * m1.row(c).transpose().adjoint()).eval().template triangularView<Lower>().toDenseMatrix()));
+
+
+ m2.setZero();
+ VERIFY_IS_APPROX((m2.template selfadjointView<Upper>().rankUpdate(m1.row(c).adjoint(),s1)._expression()),
+ ((s1 * m1.row(c).adjoint() * m1.row(c).adjoint().adjoint()).eval().template triangularView<Upper>().toDenseMatrix()));
+}
+
+void test_product_syrk()
+{
+ for(int i = 0; i < g_repeat ; i++)
+ {
+ int s;
+ s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE);
+ CALL_SUBTEST_1( syrk(MatrixXf(s, s)) );
+ s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE);
+ CALL_SUBTEST_2( syrk(MatrixXd(s, s)) );
+ s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2);
+ CALL_SUBTEST_3( syrk(MatrixXcf(s, s)) );
+ s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2);
+ CALL_SUBTEST_4( syrk(MatrixXcd(s, s)) );
+ }
+}