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// 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); VERIFY( row_vector.isApprox(col_vector.transpose(), 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) ); }
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>()) ); } }
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