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/eigen2/eigen2_adjoint.cpp b/test/eigen2/eigen2_adjoint.cpp
new file mode 100644
index 0000000..c0f8114
--- /dev/null
+++ b/test/eigen2/eigen2_adjoint.cpp
@@ -0,0 +1,99 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra. Eigen itself is part of the KDE project.
+//
+// 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 "main.h"
+
+template<typename MatrixType> void adjoint(const MatrixType& m)
+{
+ /* this test covers the following files:
+ Transpose.h Conjugate.h Dot.h
+ */
+
+ typedef typename MatrixType::Scalar Scalar;
+ typedef typename NumTraits<Scalar>::Real RealScalar;
+ typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
+ typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime> SquareMatrixType;
+ int rows = m.rows();
+ int cols = m.cols();
+
+ RealScalar largerEps = test_precision<RealScalar>();
+ if (ei_is_same_type<RealScalar,float>::ret)
+ largerEps = RealScalar(1e-3f);
+
+ MatrixType m1 = MatrixType::Random(rows, cols),
+ m2 = MatrixType::Random(rows, cols),
+ m3(rows, cols),
+ square = SquareMatrixType::Random(rows, rows);
+ VectorType v1 = VectorType::Random(rows),
+ v2 = VectorType::Random(rows),
+ v3 = VectorType::Random(rows),
+ vzero = VectorType::Zero(rows);
+
+ Scalar s1 = ei_random<Scalar>(),
+ s2 = ei_random<Scalar>();
+
+ // check basic compatibility of adjoint, transpose, conjugate
+ VERIFY_IS_APPROX(m1.transpose().conjugate().adjoint(), m1);
+ VERIFY_IS_APPROX(m1.adjoint().conjugate().transpose(), m1);
+
+ // check multiplicative behavior
+ VERIFY_IS_APPROX((m1.adjoint() * m2).adjoint(), m2.adjoint() * m1);
+ VERIFY_IS_APPROX((s1 * m1).adjoint(), ei_conj(s1) * m1.adjoint());
+
+ // check basic properties of dot, norm, norm2
+ typedef typename NumTraits<Scalar>::Real RealScalar;
+ VERIFY(ei_isApprox((s1 * v1 + s2 * v2).eigen2_dot(v3), s1 * v1.eigen2_dot(v3) + s2 * v2.eigen2_dot(v3), largerEps));
+ VERIFY(ei_isApprox(v3.eigen2_dot(s1 * v1 + s2 * v2), ei_conj(s1)*v3.eigen2_dot(v1)+ei_conj(s2)*v3.eigen2_dot(v2), largerEps));
+ VERIFY_IS_APPROX(ei_conj(v1.eigen2_dot(v2)), v2.eigen2_dot(v1));
+ VERIFY_IS_APPROX(ei_real(v1.eigen2_dot(v1)), v1.squaredNorm());
+ if(NumTraits<Scalar>::HasFloatingPoint)
+ VERIFY_IS_APPROX(v1.squaredNorm(), v1.norm() * v1.norm());
+ VERIFY_IS_MUCH_SMALLER_THAN(ei_abs(vzero.eigen2_dot(v1)), static_cast<RealScalar>(1));
+ if(NumTraits<Scalar>::HasFloatingPoint)
+ VERIFY_IS_MUCH_SMALLER_THAN(vzero.norm(), static_cast<RealScalar>(1));
+
+ // check compatibility of dot and adjoint
+ VERIFY(ei_isApprox(v1.eigen2_dot(square * v2), (square.adjoint() * v1).eigen2_dot(v2), largerEps));
+
+ // like in testBasicStuff, test operator() to check const-qualification
+ int r = ei_random<int>(0, rows-1),
+ c = ei_random<int>(0, cols-1);
+ VERIFY_IS_APPROX(m1.conjugate()(r,c), ei_conj(m1(r,c)));
+ VERIFY_IS_APPROX(m1.adjoint()(c,r), ei_conj(m1(r,c)));
+
+ if(NumTraits<Scalar>::HasFloatingPoint)
+ {
+ // check that Random().normalized() works: tricky as the random xpr must be evaluated by
+ // normalized() in order to produce a consistent result.
+ VERIFY_IS_APPROX(VectorType::Random(rows).normalized().norm(), RealScalar(1));
+ }
+
+ // check inplace transpose
+ m3 = m1;
+ m3.transposeInPlace();
+ VERIFY_IS_APPROX(m3,m1.transpose());
+ m3.transposeInPlace();
+ VERIFY_IS_APPROX(m3,m1);
+
+}
+
+void test_eigen2_adjoint()
+{
+ for(int i = 0; i < g_repeat; i++) {
+ CALL_SUBTEST_1( adjoint(Matrix<float, 1, 1>()) );
+ CALL_SUBTEST_2( adjoint(Matrix3d()) );
+ CALL_SUBTEST_3( adjoint(Matrix4f()) );
+ CALL_SUBTEST_4( adjoint(MatrixXcf(4, 4)) );
+ CALL_SUBTEST_5( adjoint(MatrixXi(8, 12)) );
+ CALL_SUBTEST_6( adjoint(MatrixXf(21, 21)) );
+ }
+ // test a large matrix only once
+ CALL_SUBTEST_7( adjoint(Matrix<float, 100, 100>()) );
+}
+