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-rw-r--r--test/nullary.cpp225
1 files changed, 199 insertions, 26 deletions
diff --git a/test/nullary.cpp b/test/nullary.cpp
index fbc721a1a..acd55506e 100644
--- a/test/nullary.cpp
+++ b/test/nullary.cpp
@@ -2,6 +2,7 @@
// for linear algebra.
//
// Copyright (C) 2010-2011 Jitse Niesen <jitse@maths.leeds.ac.uk>
+// Copyright (C) 2016 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
@@ -12,7 +13,6 @@
template<typename MatrixType>
bool equalsIdentity(const MatrixType& A)
{
- typedef typename MatrixType::Index Index;
typedef typename MatrixType::Scalar Scalar;
Scalar zero = static_cast<Scalar>(0);
@@ -30,13 +30,41 @@ bool equalsIdentity(const MatrixType& A)
bool diagOK = (A.diagonal().array() == 1).all();
return offDiagOK && diagOK;
+
+}
+
+template<typename VectorType>
+void check_extremity_accuracy(const VectorType &v, const typename VectorType::Scalar &low, const typename VectorType::Scalar &high)
+{
+ typedef typename VectorType::Scalar Scalar;
+ typedef typename VectorType::RealScalar RealScalar;
+
+ RealScalar prec = internal::is_same<RealScalar,float>::value ? NumTraits<RealScalar>::dummy_precision()*10 : NumTraits<RealScalar>::dummy_precision()/10;
+ Index size = v.size();
+
+ if(size<20)
+ return;
+
+ for (int i=0; i<size; ++i)
+ {
+ if(i<5 || i>size-6)
+ {
+ Scalar ref = (low*RealScalar(size-i-1))/RealScalar(size-1) + (high*RealScalar(i))/RealScalar(size-1);
+ if(std::abs(ref)>1)
+ {
+ if(!internal::isApprox(v(i), ref, prec))
+ std::cout << v(i) << " != " << ref << " ; relative error: " << std::abs((v(i)-ref)/ref) << " ; required precision: " << prec << " ; range: " << low << "," << high << " ; i: " << i << "\n";
+ VERIFY(internal::isApprox(v(i), (low*RealScalar(size-i-1))/RealScalar(size-1) + (high*RealScalar(i))/RealScalar(size-1), prec));
+ }
+ }
+ }
}
template<typename VectorType>
void testVectorType(const VectorType& base)
{
- typedef typename internal::traits<VectorType>::Index Index;
- typedef typename internal::traits<VectorType>::Scalar Scalar;
+ typedef typename VectorType::Scalar Scalar;
+ typedef typename VectorType::RealScalar RealScalar;
const Index size = base.size();
@@ -44,36 +72,61 @@ void testVectorType(const VectorType& base)
Scalar low = (size == 1 ? high : internal::random<Scalar>(-500,500));
if (low>high) std::swap(low,high);
+ // check low==high
+ if(internal::random<float>(0.f,1.f)<0.05f)
+ low = high;
+ // check abs(low) >> abs(high)
+ else if(size>2 && std::numeric_limits<RealScalar>::max_exponent10>0 && internal::random<float>(0.f,1.f)<0.1f)
+ low = -internal::random<Scalar>(1,2) * RealScalar(std::pow(RealScalar(10),std::numeric_limits<RealScalar>::max_exponent10/2));
+
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;
+ if(!NumTraits<Scalar>::IsInteger)
+ {
+ VectorType n(size);
+ for (int i=0; i<size; ++i)
+ n(i) = low+i*step;
+ VERIFY_IS_APPROX(m,n);
- VERIFY_IS_APPROX(m,n);
+ CALL_SUBTEST( check_extremity_accuracy(m, low, high) );
+ }
- // random access version
- m = VectorType::LinSpaced(size,low,high);
- VERIFY_IS_APPROX(m,n);
+ if((!NumTraits<Scalar>::IsInteger) || ((high-low)>=size && (Index(high-low)%(size-1))==0) || (Index(high-low+1)<size && (size%Index(high-low+1))==0))
+ {
+ VectorType n(size);
+ if((!NumTraits<Scalar>::IsInteger) || (high-low>=size))
+ for (int i=0; i<size; ++i)
+ n(i) = size==1 ? low : (low + ((high-low)*Scalar(i))/(size-1));
+ else
+ for (int i=0; i<size; ++i)
+ n(i) = size==1 ? low : low + Scalar((double(high-low+1)*double(i))/double(size));
+ 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() );
+ // random access version
+ m = VectorType::LinSpaced(size,low,high);
+ VERIFY_IS_APPROX(m,n);
+ VERIFY( internal::isApprox(m(m.size()-1),high) );
+ VERIFY( size==1 || internal::isApprox(m(0),low) );
+ VERIFY_IS_EQUAL(m(m.size()-1) , high);
+ if(!NumTraits<Scalar>::IsInteger)
+ CALL_SUBTEST( check_extremity_accuracy(m, low, high) );
+ }
- // These guys sometimes fail! This is not good. Any ideas how to fix them!?
- //VERIFY( m(m.size()-1) == high );
- //VERIFY( m(0) == low );
+ VERIFY( m(m.size()-1) <= high );
+ VERIFY( (m.array() <= high).all() );
+ VERIFY( (m.array() >= low).all() );
- // 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 );
+ VERIFY( m(m.size()-1) >= low );
+ if(size>=1)
+ {
+ VERIFY( internal::isApprox(m(0),low) );
+ VERIFY_IS_EQUAL(m(0) , low);
+ }
// check whether everything works with row and col major vectors
Matrix<Scalar,Dynamic,1> row_vector(size);
@@ -95,23 +148,77 @@ void testVectorType(const VectorType& base)
VERIFY_IS_APPROX( ScalarMatrix::LinSpaced(1,low,high), ScalarMatrix::Constant(high) );
// regression test for bug 526 (linear vectorized transversal)
- if (size > 1) {
+ if (size > 1 && (!NumTraits<Scalar>::IsInteger)) {
m.tail(size-1).setLinSpaced(low, high);
VERIFY_IS_APPROX(m(size-1), high);
}
+
+ // regression test for bug 1383 (LinSpaced with empty size/range)
+ {
+ Index n0 = VectorType::SizeAtCompileTime==Dynamic ? 0 : VectorType::SizeAtCompileTime;
+ low = internal::random<Scalar>();
+ m = VectorType::LinSpaced(n0,low,low-1);
+ VERIFY(m.size()==n0);
+
+ if(VectorType::SizeAtCompileTime==Dynamic)
+ {
+ VERIFY_IS_EQUAL(VectorType::LinSpaced(n0,0,Scalar(n0-1)).sum(),Scalar(0));
+ VERIFY_IS_EQUAL(VectorType::LinSpaced(n0,low,low-1).sum(),Scalar(0));
+ }
+
+ m.setLinSpaced(n0,0,Scalar(n0-1));
+ VERIFY(m.size()==n0);
+ m.setLinSpaced(n0,low,low-1);
+ VERIFY(m.size()==n0);
+
+ // empty range only:
+ VERIFY_IS_APPROX(VectorType::LinSpaced(size,low,low),VectorType::Constant(size,low));
+ m.setLinSpaced(size,low,low);
+ VERIFY_IS_APPROX(m,VectorType::Constant(size,low));
+
+ if(NumTraits<Scalar>::IsInteger)
+ {
+ VERIFY_IS_APPROX( VectorType::LinSpaced(size,low,Scalar(low+size-1)), VectorType::LinSpaced(size,Scalar(low+size-1),low).reverse() );
+
+ if(VectorType::SizeAtCompileTime==Dynamic)
+ {
+ // Check negative multiplicator path:
+ for(Index k=1; k<5; ++k)
+ VERIFY_IS_APPROX( VectorType::LinSpaced(size,low,Scalar(low+(size-1)*k)), VectorType::LinSpaced(size,Scalar(low+(size-1)*k),low).reverse() );
+ // Check negative divisor path:
+ for(Index k=1; k<5; ++k)
+ VERIFY_IS_APPROX( VectorType::LinSpaced(size*k,low,Scalar(low+size-1)), VectorType::LinSpaced(size*k,Scalar(low+size-1),low).reverse() );
+ }
+ }
+ }
}
template<typename MatrixType>
void testMatrixType(const MatrixType& m)
{
- typedef typename MatrixType::Index Index;
+ using std::abs;
const Index rows = m.rows();
const Index cols = m.cols();
+ typedef typename MatrixType::Scalar Scalar;
+ typedef typename MatrixType::RealScalar RealScalar;
+
+ Scalar s1;
+ do {
+ s1 = internal::random<Scalar>();
+ } while(abs(s1)<RealScalar(1e-5) && (!NumTraits<Scalar>::IsInteger));
MatrixType A;
A.setIdentity(rows, cols);
VERIFY(equalsIdentity(A));
VERIFY(equalsIdentity(MatrixType::Identity(rows, cols)));
+
+
+ A = MatrixType::Constant(rows,cols,s1);
+ Index i = internal::random<Index>(0,rows-1);
+ Index j = internal::random<Index>(0,cols-1);
+ VERIFY_IS_APPROX( MatrixType::Constant(rows,cols,s1)(i,j), s1 );
+ VERIFY_IS_APPROX( MatrixType::Constant(rows,cols,s1).coeff(i,j), s1 );
+ VERIFY_IS_APPROX( A(i,j), s1 );
}
void test_nullary()
@@ -120,12 +227,78 @@ void test_nullary()
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))) );
+ for(int i = 0; i < g_repeat*10; i++) {
+ CALL_SUBTEST_4( testVectorType(VectorXd(internal::random<int>(1,30000))) );
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_7( testVectorType(VectorXf(internal::random<int>(1,30000))) );
CALL_SUBTEST_8( testVectorType(Vector3f()) );
+ CALL_SUBTEST_8( testVectorType(Vector4f()) );
+ CALL_SUBTEST_8( testVectorType(Matrix<float,8,1>()) );
CALL_SUBTEST_8( testVectorType(Matrix<float,1,1>()) );
+
+ CALL_SUBTEST_9( testVectorType(VectorXi(internal::random<int>(1,10))) );
+ CALL_SUBTEST_9( testVectorType(VectorXi(internal::random<int>(9,300))) );
+ CALL_SUBTEST_9( testVectorType(Matrix<int,1,1>()) );
+ }
+
+#ifdef EIGEN_TEST_PART_6
+ // 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<double>::epsilon() );
+#endif
+
+#ifdef EIGEN_TEST_PART_9
+ // Check possible overflow issue
+ {
+ int n = 60000;
+ ArrayXi a1(n), a2(n);
+ a1.setLinSpaced(n, 0, n-1);
+ for(int i=0; i<n; ++i)
+ a2(i) = i;
+ VERIFY_IS_APPROX(a1,a2);
+ }
+#endif
+
+#ifdef EIGEN_TEST_PART_10
+ // check some internal logic
+ VERIFY(( internal::has_nullary_operator<internal::scalar_constant_op<double> >::value ));
+ VERIFY(( !internal::has_unary_operator<internal::scalar_constant_op<double> >::value ));
+ VERIFY(( !internal::has_binary_operator<internal::scalar_constant_op<double> >::value ));
+ VERIFY(( internal::functor_has_linear_access<internal::scalar_constant_op<double> >::ret ));
+
+ VERIFY(( !internal::has_nullary_operator<internal::scalar_identity_op<double> >::value ));
+ VERIFY(( !internal::has_unary_operator<internal::scalar_identity_op<double> >::value ));
+ VERIFY(( internal::has_binary_operator<internal::scalar_identity_op<double> >::value ));
+ VERIFY(( !internal::functor_has_linear_access<internal::scalar_identity_op<double> >::ret ));
+
+ VERIFY(( !internal::has_nullary_operator<internal::linspaced_op<float,float> >::value ));
+ VERIFY(( internal::has_unary_operator<internal::linspaced_op<float,float> >::value ));
+ VERIFY(( !internal::has_binary_operator<internal::linspaced_op<float,float> >::value ));
+ VERIFY(( internal::functor_has_linear_access<internal::linspaced_op<float,float> >::ret ));
+
+ // Regression unit test for a weird MSVC bug.
+ // Search "nullary_wrapper_workaround_msvc" in CoreEvaluators.h for the details.
+ // See also traits<Ref>::match.
+ {
+ MatrixXf A = MatrixXf::Random(3,3);
+ Ref<const MatrixXf> R = 2.0*A;
+ VERIFY_IS_APPROX(R, A+A);
+
+ Ref<const MatrixXf> R1 = MatrixXf::Random(3,3)+A;
+
+ VectorXi V = VectorXi::Random(3);
+ Ref<const VectorXi> R2 = VectorXi::LinSpaced(3,1,3)+V;
+ VERIFY_IS_APPROX(R2, V+Vector3i(1,2,3));
+
+ VERIFY(( internal::has_nullary_operator<internal::scalar_constant_op<float> >::value ));
+ VERIFY(( !internal::has_unary_operator<internal::scalar_constant_op<float> >::value ));
+ VERIFY(( !internal::has_binary_operator<internal::scalar_constant_op<float> >::value ));
+ VERIFY(( internal::functor_has_linear_access<internal::scalar_constant_op<float> >::ret ));
+
+ VERIFY(( !internal::has_nullary_operator<internal::linspaced_op<int,int> >::value ));
+ VERIFY(( internal::has_unary_operator<internal::linspaced_op<int,int> >::value ));
+ VERIFY(( !internal::has_binary_operator<internal::linspaced_op<int,int> >::value ));
+ VERIFY(( internal::functor_has_linear_access<internal::linspaced_op<int,int> >::ret ));
}
+#endif
}