// This file is part of Eigen, a lightweight C++ template library // for linear algebra. // // Copyright (C) 2006-2008 Benoit Jacob // // 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" #include "random_without_cast_overflow.h" template typename internal::enable_if<(MatrixType::RowsAtCompileTime==1 || MatrixType::ColsAtCompileTime==1),void>::type check_index(const MatrixType& m) { VERIFY_RAISES_ASSERT(m[0]); VERIFY_RAISES_ASSERT((m+m)[0]); } template typename internal::enable_if::type check_index(const MatrixType& /*unused*/) {} template void basicStuff(const MatrixType& m) { typedef typename MatrixType::Scalar Scalar; typedef Matrix VectorType; typedef Matrix SquareMatrixType; Index rows = m.rows(); Index cols = m.cols(); // this test relies a lot on Random.h, and there's not much more that we can do // to test it, hence I consider that we will have tested Random.h MatrixType m1 = MatrixType::Random(rows, cols), m2 = MatrixType::Random(rows, cols), m3(rows, cols), mzero = MatrixType::Zero(rows, cols), square = Matrix::Random(rows, rows); VectorType v1 = VectorType::Random(rows), vzero = VectorType::Zero(rows); SquareMatrixType sm1 = SquareMatrixType::Random(rows,rows), sm2(rows,rows); Scalar x = 0; while(x == Scalar(0)) x = internal::random(); Index r = internal::random(0, rows-1), c = internal::random(0, cols-1); m1.coeffRef(r,c) = x; VERIFY_IS_APPROX(x, m1.coeff(r,c)); m1(r,c) = x; VERIFY_IS_APPROX(x, m1(r,c)); v1.coeffRef(r) = x; VERIFY_IS_APPROX(x, v1.coeff(r)); v1(r) = x; VERIFY_IS_APPROX(x, v1(r)); v1[r] = x; VERIFY_IS_APPROX(x, v1[r]); // test fetching with various index types. Index r1 = internal::random(0, numext::mini(Index(127),rows-1)); x = v1(static_cast(r1)); x = v1(static_cast(r1)); x = v1(static_cast(r1)); x = v1(static_cast(r1)); x = v1(static_cast(r1)); x = v1(static_cast(r1)); x = v1(static_cast(r1)); x = v1(static_cast(r1)); x = v1(static_cast(r1)); #if EIGEN_HAS_CXX11 x = v1(static_cast(r1)); x = v1(static_cast(r1)); #endif VERIFY_IS_APPROX( v1, v1); VERIFY_IS_NOT_APPROX( v1, 2*v1); VERIFY_IS_MUCH_SMALLER_THAN( vzero, v1); VERIFY_IS_MUCH_SMALLER_THAN( vzero, v1.squaredNorm()); VERIFY_IS_NOT_MUCH_SMALLER_THAN(v1, v1); VERIFY_IS_APPROX( vzero, v1-v1); VERIFY_IS_APPROX( m1, m1); VERIFY_IS_NOT_APPROX( m1, 2*m1); VERIFY_IS_MUCH_SMALLER_THAN( mzero, m1); VERIFY_IS_NOT_MUCH_SMALLER_THAN(m1, m1); VERIFY_IS_APPROX( mzero, m1-m1); // always test operator() on each read-only expression class, // in order to check const-qualifiers. // indeed, if an expression class (here Zero) is meant to be read-only, // hence has no _write() method, the corresponding MatrixBase method (here zero()) // should return a const-qualified object so that it is the const-qualified // operator() that gets called, which in turn calls _read(). VERIFY_IS_MUCH_SMALLER_THAN(MatrixType::Zero(rows,cols)(r,c), static_cast(1)); // now test copying a row-vector into a (column-)vector and conversely. square.col(r) = square.row(r).eval(); Matrix rv(rows); Matrix cv(rows); rv = square.row(r); cv = square.col(r); VERIFY_IS_APPROX(rv, cv.transpose()); if(cols!=1 && rows!=1 && MatrixType::SizeAtCompileTime!=Dynamic) { VERIFY_RAISES_ASSERT(m1 = (m2.block(0,0, rows-1, cols-1))); } if(cols!=1 && rows!=1) { check_index(m1); } VERIFY_IS_APPROX(m3 = m1,m1); MatrixType m4; VERIFY_IS_APPROX(m4 = m1,m1); m3.real() = m1.real(); VERIFY_IS_APPROX(static_cast(m3).real(), static_cast(m1).real()); VERIFY_IS_APPROX(static_cast(m3).real(), m1.real()); // check == / != operators VERIFY(m1==m1); VERIFY(m1!=m2); VERIFY(!(m1==m2)); VERIFY(!(m1!=m1)); m1 = m2; VERIFY(m1==m2); VERIFY(!(m1!=m2)); // check automatic transposition sm2.setZero(); for(Index i=0;i(0,10)>5; m3 = b ? m1 : m2; if(b) VERIFY_IS_APPROX(m3,m1); else VERIFY_IS_APPROX(m3,m2); m3 = b ? -m1 : m2; if(b) VERIFY_IS_APPROX(m3,-m1); else VERIFY_IS_APPROX(m3,m2); m3 = b ? m1 : -m2; if(b) VERIFY_IS_APPROX(m3,m1); else VERIFY_IS_APPROX(m3,-m2); } } template void basicStuffComplex(const MatrixType& m) { typedef typename MatrixType::Scalar Scalar; typedef typename NumTraits::Real RealScalar; typedef Matrix RealMatrixType; Index rows = m.rows(); Index cols = m.cols(); Scalar s1 = internal::random(), s2 = internal::random(); VERIFY(numext::real(s1)==numext::real_ref(s1)); VERIFY(numext::imag(s1)==numext::imag_ref(s1)); numext::real_ref(s1) = numext::real(s2); numext::imag_ref(s1) = numext::imag(s2); VERIFY(internal::isApprox(s1, s2, NumTraits::epsilon())); // extended precision in Intel FPUs means that s1 == s2 in the line above is not guaranteed. RealMatrixType rm1 = RealMatrixType::Random(rows,cols), rm2 = RealMatrixType::Random(rows,cols); MatrixType cm(rows,cols); cm.real() = rm1; cm.imag() = rm2; VERIFY_IS_APPROX(static_cast(cm).real(), rm1); VERIFY_IS_APPROX(static_cast(cm).imag(), rm2); rm1.setZero(); rm2.setZero(); rm1 = cm.real(); rm2 = cm.imag(); VERIFY_IS_APPROX(static_cast(cm).real(), rm1); VERIFY_IS_APPROX(static_cast(cm).imag(), rm2); cm.real().setZero(); VERIFY(static_cast(cm).real().isZero()); VERIFY(!static_cast(cm).imag().isZero()); } template struct casting_test { static void run() { Matrix m; for (int i=0; i::value(); } } Matrix n = m.template cast(); for (int i=0; i(m(i, j)))); } } } }; template struct casting_test_runner { static void run() { casting_test::run(); casting_test::run(); casting_test::run(); casting_test::run(); casting_test::run(); casting_test::run(); casting_test::run(); #if EIGEN_HAS_CXX11 casting_test::run(); casting_test::run(); #endif casting_test::run(); casting_test::run(); casting_test::run(); casting_test::run(); casting_test >::run(); casting_test >::run(); } }; template struct casting_test_runner::IsComplex)>::type> { static void run() { // Only a few casts from std::complex are defined. casting_test::run(); casting_test::run(); casting_test >::run(); casting_test >::run(); } }; void casting_all() { casting_test_runner::run(); casting_test_runner::run(); casting_test_runner::run(); casting_test_runner::run(); casting_test_runner::run(); casting_test_runner::run(); casting_test_runner::run(); #if EIGEN_HAS_CXX11 casting_test_runner::run(); casting_test_runner::run(); #endif casting_test_runner::run(); casting_test_runner::run(); casting_test_runner::run(); casting_test_runner::run(); casting_test_runner >::run(); casting_test_runner >::run(); } template void fixedSizeMatrixConstruction() { Scalar raw[4]; for(int k=0; k<4; ++k) raw[k] = internal::random(); { Matrix m(raw); Array a(raw); for(int k=0; k<4; ++k) VERIFY(m(k) == raw[k]); for(int k=0; k<4; ++k) VERIFY(a(k) == raw[k]); VERIFY_IS_EQUAL(m,(Matrix(raw[0],raw[1],raw[2],raw[3]))); VERIFY((a==(Array(raw[0],raw[1],raw[2],raw[3]))).all()); } { Matrix m(raw); Array a(raw); for(int k=0; k<3; ++k) VERIFY(m(k) == raw[k]); for(int k=0; k<3; ++k) VERIFY(a(k) == raw[k]); VERIFY_IS_EQUAL(m,(Matrix(raw[0],raw[1],raw[2]))); VERIFY((a==Array(raw[0],raw[1],raw[2])).all()); } { Matrix m(raw), m2( (DenseIndex(raw[0])), (DenseIndex(raw[1])) ); Array a(raw), a2( (DenseIndex(raw[0])), (DenseIndex(raw[1])) ); for(int k=0; k<2; ++k) VERIFY(m(k) == raw[k]); for(int k=0; k<2; ++k) VERIFY(a(k) == raw[k]); VERIFY_IS_EQUAL(m,(Matrix(raw[0],raw[1]))); VERIFY((a==Array(raw[0],raw[1])).all()); for(int k=0; k<2; ++k) VERIFY(m2(k) == DenseIndex(raw[k])); for(int k=0; k<2; ++k) VERIFY(a2(k) == DenseIndex(raw[k])); } { Matrix m(raw), m2( (DenseIndex(raw[0])), (DenseIndex(raw[1])) ), m3( (int(raw[0])), (int(raw[1])) ), m4( (float(raw[0])), (float(raw[1])) ); Array a(raw), a2( (DenseIndex(raw[0])), (DenseIndex(raw[1])) ); for(int k=0; k<2; ++k) VERIFY(m(k) == raw[k]); for(int k=0; k<2; ++k) VERIFY(a(k) == raw[k]); VERIFY_IS_EQUAL(m,(Matrix(raw[0],raw[1]))); VERIFY((a==Array(raw[0],raw[1])).all()); for(int k=0; k<2; ++k) VERIFY(m2(k) == DenseIndex(raw[k])); for(int k=0; k<2; ++k) VERIFY(a2(k) == DenseIndex(raw[k])); for(int k=0; k<2; ++k) VERIFY(m3(k) == int(raw[k])); for(int k=0; k<2; ++k) VERIFY((m4(k)) == Scalar(float(raw[k]))); } { Matrix m(raw), m1(raw[0]), m2( (DenseIndex(raw[0])) ), m3( (int(raw[0])) ); Array a(raw), a1(raw[0]), a2( (DenseIndex(raw[0])) ); VERIFY(m(0) == raw[0]); VERIFY(a(0) == raw[0]); VERIFY(m1(0) == raw[0]); VERIFY(a1(0) == raw[0]); VERIFY(m2(0) == DenseIndex(raw[0])); VERIFY(a2(0) == DenseIndex(raw[0])); VERIFY(m3(0) == int(raw[0])); VERIFY_IS_EQUAL(m,(Matrix(raw[0]))); VERIFY((a==Array(raw[0])).all()); } } EIGEN_DECLARE_TEST(basicstuff) { for(int i = 0; i < g_repeat; i++) { CALL_SUBTEST_1( basicStuff(Matrix()) ); CALL_SUBTEST_2( basicStuff(Matrix4d()) ); CALL_SUBTEST_3( basicStuff(MatrixXcf(internal::random(1,EIGEN_TEST_MAX_SIZE), internal::random(1,EIGEN_TEST_MAX_SIZE))) ); CALL_SUBTEST_4( basicStuff(MatrixXi(internal::random(1,EIGEN_TEST_MAX_SIZE), internal::random(1,EIGEN_TEST_MAX_SIZE))) ); CALL_SUBTEST_5( basicStuff(MatrixXcd(internal::random(1,EIGEN_TEST_MAX_SIZE), internal::random(1,EIGEN_TEST_MAX_SIZE))) ); CALL_SUBTEST_6( basicStuff(Matrix()) ); CALL_SUBTEST_7( basicStuff(Matrix(internal::random(1,EIGEN_TEST_MAX_SIZE),internal::random(1,EIGEN_TEST_MAX_SIZE))) ); CALL_SUBTEST_8( casting_all() ); CALL_SUBTEST_3( basicStuffComplex(MatrixXcf(internal::random(1,EIGEN_TEST_MAX_SIZE), internal::random(1,EIGEN_TEST_MAX_SIZE))) ); CALL_SUBTEST_5( basicStuffComplex(MatrixXcd(internal::random(1,EIGEN_TEST_MAX_SIZE), internal::random(1,EIGEN_TEST_MAX_SIZE))) ); } CALL_SUBTEST_1(fixedSizeMatrixConstruction()); CALL_SUBTEST_1(fixedSizeMatrixConstruction()); CALL_SUBTEST_1(fixedSizeMatrixConstruction()); CALL_SUBTEST_1(fixedSizeMatrixConstruction()); CALL_SUBTEST_1(fixedSizeMatrixConstruction()); CALL_SUBTEST_1(fixedSizeMatrixConstruction()); }