// This file is part of Eigen, a lightweight C++ template library // for linear algebra. // // Copyright (C) 2010-2011 Jitse Niesen <jitse@maths.leeds.ac.uk> // // 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> bool equalsIdentity(const MatrixType& A) { typedef typename MatrixType::Index Index; typedef typename MatrixType::Scalar Scalar; Scalar zero = static_cast<Scalar>(0); bool offDiagOK = true; for (Index i = 0; i < A.rows(); ++i) { for (Index j = i+1; j < A.cols(); ++j) { offDiagOK = offDiagOK && (A(i,j) == zero); } } for (Index i = 0; i < A.rows(); ++i) { for (Index j = 0; j < (std::min)(i, A.cols()); ++j) { offDiagOK = offDiagOK && (A(i,j) == zero); } } bool diagOK = (A.diagonal().array() == 1).all(); return offDiagOK && diagOK; } template<typename VectorType> void testVectorType(const VectorType& base) { typedef typename internal::traits<VectorType>::Index Index; typedef typename internal::traits<VectorType>::Scalar Scalar; const Index size = base.size(); Scalar high = internal::random<Scalar>(-500,500); Scalar low = (size == 1 ? high : internal::random<Scalar>(-500,500)); if (low>high) std::swap(low,high); const Scalar step = ((size == 1) ? 1 : (high-low)/(size-1)); // check whether the result yields what we expect it to do VectorType m(base); m.setLinSpaced(size,low,high); VectorType n(size); for (int i=0; i<size; ++i) n(i) = low+i*step; VERIFY_IS_APPROX(m,n); // random access version m = VectorType::LinSpaced(size,low,high); VERIFY_IS_APPROX(m,n); // Assignment of a RowVectorXd to a MatrixXd (regression test for bug #79). VERIFY( (MatrixXd(RowVectorXd::LinSpaced(3, 0, 1)) - RowVector3d(0, 0.5, 1)).norm() < std::numeric_limits<Scalar>::epsilon() ); // These guys sometimes fail! This is not good. Any ideas how to fix them!? //VERIFY( m(m.size()-1) == high ); //VERIFY( m(0) == low ); // sequential access version m = VectorType::LinSpaced(Sequential,size,low,high); VERIFY_IS_APPROX(m,n); // These guys sometimes fail! This is not good. Any ideas how to fix them!? //VERIFY( m(m.size()-1) == high ); //VERIFY( m(0) == low ); // check whether everything works with row and col major vectors Matrix<Scalar,Dynamic,1> row_vector(size); Matrix<Scalar,1,Dynamic> col_vector(size); row_vector.setLinSpaced(size,low,high); col_vector.setLinSpaced(size,low,high); // when using the extended precision (e.g., FPU) the relative error might exceed 1 bit // when computing the squared sum in isApprox, thus the 2x factor. VERIFY( row_vector.isApprox(col_vector.transpose(), Scalar(2)*NumTraits<Scalar>::epsilon())); Matrix<Scalar,Dynamic,1> size_changer(size+50); size_changer.setLinSpaced(size,low,high); VERIFY( size_changer.size() == size ); typedef Matrix<Scalar,1,1> ScalarMatrix; ScalarMatrix scalar; scalar.setLinSpaced(1,low,high); VERIFY_IS_APPROX( scalar, ScalarMatrix::Constant(high) ); VERIFY_IS_APPROX( ScalarMatrix::LinSpaced(1,low,high), ScalarMatrix::Constant(high) ); // regression test for bug 526 (linear vectorized transversal) if (size > 1) { m.tail(size-1).setLinSpaced(low, high); VERIFY_IS_APPROX(m(size-1), high); } } template<typename MatrixType> void testMatrixType(const MatrixType& m) { typedef typename MatrixType::Index Index; const Index rows = m.rows(); const Index cols = m.cols(); MatrixType A; A.setIdentity(rows, cols); VERIFY(equalsIdentity(A)); VERIFY(equalsIdentity(MatrixType::Identity(rows, cols))); } void test_nullary() { CALL_SUBTEST_1( testMatrixType(Matrix2d()) ); CALL_SUBTEST_2( testMatrixType(MatrixXcf(internal::random<int>(1,300),internal::random<int>(1,300))) ); CALL_SUBTEST_3( testMatrixType(MatrixXf(internal::random<int>(1,300),internal::random<int>(1,300))) ); for(int i = 0; i < g_repeat; i++) { CALL_SUBTEST_4( testVectorType(VectorXd(internal::random<int>(1,300))) ); CALL_SUBTEST_5( testVectorType(Vector4d()) ); // regression test for bug 232 CALL_SUBTEST_6( testVectorType(Vector3d()) ); CALL_SUBTEST_7( testVectorType(VectorXf(internal::random<int>(1,300))) ); CALL_SUBTEST_8( testVectorType(Vector3f()) ); CALL_SUBTEST_8( testVectorType(Matrix<float,1,1>()) ); } }