Page Menu
Home
c4science
Search
Configure Global Search
Log In
Files
F102456646
product_extra.cpp
No One
Temporary
Actions
Download File
Edit File
Delete File
View Transforms
Subscribe
Mute Notifications
Award Token
Subscribers
None
File Metadata
Details
File Info
Storage
Attached
Created
Thu, Feb 20, 22:34
Size
15 KB
Mime Type
text/x-c++
Expires
Sat, Feb 22, 22:34 (1 d, 23 h)
Engine
blob
Format
Raw Data
Handle
24324407
Attached To
rDLMA Diffusion limited mixed aggregation
product_extra.cpp
View Options
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// 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 product_extra(const MatrixType& m)
{
typedef typename MatrixType::Scalar Scalar;
typedef Matrix<Scalar, 1, Dynamic> RowVectorType;
typedef Matrix<Scalar, Dynamic, 1> ColVectorType;
typedef Matrix<Scalar, Dynamic, Dynamic,
MatrixType::Flags&RowMajorBit> OtherMajorMatrixType;
Index rows = m.rows();
Index cols = m.cols();
MatrixType m1 = MatrixType::Random(rows, cols),
m2 = MatrixType::Random(rows, cols),
m3(rows, cols),
mzero = MatrixType::Zero(rows, cols),
identity = MatrixType::Identity(rows, rows),
square = MatrixType::Random(rows, rows),
res = MatrixType::Random(rows, rows),
square2 = MatrixType::Random(cols, cols),
res2 = MatrixType::Random(cols, cols);
RowVectorType v1 = RowVectorType::Random(rows), vrres(rows);
ColVectorType vc2 = ColVectorType::Random(cols), vcres(cols);
OtherMajorMatrixType tm1 = m1;
Scalar s1 = internal::random<Scalar>(),
s2 = internal::random<Scalar>(),
s3 = internal::random<Scalar>();
VERIFY_IS_APPROX(m3.noalias() = m1 * m2.adjoint(), m1 * m2.adjoint().eval());
VERIFY_IS_APPROX(m3.noalias() = m1.adjoint() * square.adjoint(), m1.adjoint().eval() * square.adjoint().eval());
VERIFY_IS_APPROX(m3.noalias() = m1.adjoint() * m2, m1.adjoint().eval() * m2);
VERIFY_IS_APPROX(m3.noalias() = (s1 * m1.adjoint()) * m2, (s1 * m1.adjoint()).eval() * m2);
VERIFY_IS_APPROX(m3.noalias() = ((s1 * m1).adjoint()) * m2, (numext::conj(s1) * m1.adjoint()).eval() * m2);
VERIFY_IS_APPROX(m3.noalias() = (- m1.adjoint() * s1) * (s3 * m2), (- m1.adjoint() * s1).eval() * (s3 * m2).eval());
VERIFY_IS_APPROX(m3.noalias() = (s2 * m1.adjoint() * s1) * m2, (s2 * m1.adjoint() * s1).eval() * m2);
VERIFY_IS_APPROX(m3.noalias() = (-m1*s2) * s1*m2.adjoint(), (-m1*s2).eval() * (s1*m2.adjoint()).eval());
// a very tricky case where a scale factor has to be automatically conjugated:
VERIFY_IS_APPROX( m1.adjoint() * (s1*m2).conjugate(), (m1.adjoint()).eval() * ((s1*m2).conjugate()).eval());
// test all possible conjugate combinations for the four matrix-vector product cases:
VERIFY_IS_APPROX((-m1.conjugate() * s2) * (s1 * vc2),
(-m1.conjugate()*s2).eval() * (s1 * vc2).eval());
VERIFY_IS_APPROX((-m1 * s2) * (s1 * vc2.conjugate()),
(-m1*s2).eval() * (s1 * vc2.conjugate()).eval());
VERIFY_IS_APPROX((-m1.conjugate() * s2) * (s1 * vc2.conjugate()),
(-m1.conjugate()*s2).eval() * (s1 * vc2.conjugate()).eval());
VERIFY_IS_APPROX((s1 * vc2.transpose()) * (-m1.adjoint() * s2),
(s1 * vc2.transpose()).eval() * (-m1.adjoint()*s2).eval());
VERIFY_IS_APPROX((s1 * vc2.adjoint()) * (-m1.transpose() * s2),
(s1 * vc2.adjoint()).eval() * (-m1.transpose()*s2).eval());
VERIFY_IS_APPROX((s1 * vc2.adjoint()) * (-m1.adjoint() * s2),
(s1 * vc2.adjoint()).eval() * (-m1.adjoint()*s2).eval());
VERIFY_IS_APPROX((-m1.adjoint() * s2) * (s1 * v1.transpose()),
(-m1.adjoint()*s2).eval() * (s1 * v1.transpose()).eval());
VERIFY_IS_APPROX((-m1.transpose() * s2) * (s1 * v1.adjoint()),
(-m1.transpose()*s2).eval() * (s1 * v1.adjoint()).eval());
VERIFY_IS_APPROX((-m1.adjoint() * s2) * (s1 * v1.adjoint()),
(-m1.adjoint()*s2).eval() * (s1 * v1.adjoint()).eval());
VERIFY_IS_APPROX((s1 * v1) * (-m1.conjugate() * s2),
(s1 * v1).eval() * (-m1.conjugate()*s2).eval());
VERIFY_IS_APPROX((s1 * v1.conjugate()) * (-m1 * s2),
(s1 * v1.conjugate()).eval() * (-m1*s2).eval());
VERIFY_IS_APPROX((s1 * v1.conjugate()) * (-m1.conjugate() * s2),
(s1 * v1.conjugate()).eval() * (-m1.conjugate()*s2).eval());
VERIFY_IS_APPROX((-m1.adjoint() * s2) * (s1 * v1.adjoint()),
(-m1.adjoint()*s2).eval() * (s1 * v1.adjoint()).eval());
// test the vector-matrix product with non aligned starts
Index i = internal::random<Index>(0,m1.rows()-2);
Index j = internal::random<Index>(0,m1.cols()-2);
Index r = internal::random<Index>(1,m1.rows()-i);
Index c = internal::random<Index>(1,m1.cols()-j);
Index i2 = internal::random<Index>(0,m1.rows()-1);
Index j2 = internal::random<Index>(0,m1.cols()-1);
VERIFY_IS_APPROX(m1.col(j2).adjoint() * m1.block(0,j,m1.rows(),c), m1.col(j2).adjoint().eval() * m1.block(0,j,m1.rows(),c).eval());
VERIFY_IS_APPROX(m1.block(i,0,r,m1.cols()) * m1.row(i2).adjoint(), m1.block(i,0,r,m1.cols()).eval() * m1.row(i2).adjoint().eval());
// test negative strides
{
Map<MatrixType,Unaligned,Stride<Dynamic,Dynamic> > map1(&m1(rows-1,cols-1), rows, cols, Stride<Dynamic,Dynamic>(-m1.outerStride(),-1));
Map<MatrixType,Unaligned,Stride<Dynamic,Dynamic> > map2(&m2(rows-1,cols-1), rows, cols, Stride<Dynamic,Dynamic>(-m2.outerStride(),-1));
Map<RowVectorType,Unaligned,InnerStride<-1> > mapv1(&v1(v1.size()-1), v1.size(), InnerStride<-1>(-1));
Map<ColVectorType,Unaligned,InnerStride<-1> > mapvc2(&vc2(vc2.size()-1), vc2.size(), InnerStride<-1>(-1));
VERIFY_IS_APPROX(MatrixType(map1), m1.reverse());
VERIFY_IS_APPROX(MatrixType(map2), m2.reverse());
VERIFY_IS_APPROX(m3.noalias() = MatrixType(map1) * MatrixType(map2).adjoint(), m1.reverse() * m2.reverse().adjoint());
VERIFY_IS_APPROX(m3.noalias() = map1 * map2.adjoint(), m1.reverse() * m2.reverse().adjoint());
VERIFY_IS_APPROX(map1 * vc2, m1.reverse() * vc2);
VERIFY_IS_APPROX(m1 * mapvc2, m1 * mapvc2);
VERIFY_IS_APPROX(map1.adjoint() * v1.transpose(), m1.adjoint().reverse() * v1.transpose());
VERIFY_IS_APPROX(m1.adjoint() * mapv1.transpose(), m1.adjoint() * v1.reverse().transpose());
}
// regression test
MatrixType tmp = m1 * m1.adjoint() * s1;
VERIFY_IS_APPROX(tmp, m1 * m1.adjoint() * s1);
// regression test for bug 1343, assignment to arrays
Array<Scalar,Dynamic,1> a1 = m1 * vc2;
VERIFY_IS_APPROX(a1.matrix(),m1*vc2);
Array<Scalar,Dynamic,1> a2 = s1 * (m1 * vc2);
VERIFY_IS_APPROX(a2.matrix(),s1*m1*vc2);
Array<Scalar,1,Dynamic> a3 = v1 * m1;
VERIFY_IS_APPROX(a3.matrix(),v1*m1);
Array<Scalar,Dynamic,Dynamic> a4 = m1 * m2.adjoint();
VERIFY_IS_APPROX(a4.matrix(),m1*m2.adjoint());
}
// Regression test for bug reported at http://forum.kde.org/viewtopic.php?f=74&t=96947
void mat_mat_scalar_scalar_product()
{
Eigen::Matrix2Xd dNdxy(2, 3);
dNdxy << -0.5, 0.5, 0,
-0.3, 0, 0.3;
double det = 6.0, wt = 0.5;
VERIFY_IS_APPROX(dNdxy.transpose()*dNdxy*det*wt, det*wt*dNdxy.transpose()*dNdxy);
}
template <typename MatrixType>
void zero_sized_objects(const MatrixType& m)
{
typedef typename MatrixType::Scalar Scalar;
const int PacketSize = internal::packet_traits<Scalar>::size;
const int PacketSize1 = PacketSize>1 ? PacketSize-1 : 1;
Index rows = m.rows();
Index cols = m.cols();
{
MatrixType res, a(rows,0), b(0,cols);
VERIFY_IS_APPROX( (res=a*b), MatrixType::Zero(rows,cols) );
VERIFY_IS_APPROX( (res=a*a.transpose()), MatrixType::Zero(rows,rows) );
VERIFY_IS_APPROX( (res=b.transpose()*b), MatrixType::Zero(cols,cols) );
VERIFY_IS_APPROX( (res=b.transpose()*a.transpose()), MatrixType::Zero(cols,rows) );
}
{
MatrixType res, a(rows,cols), b(cols,0);
res = a*b;
VERIFY(res.rows()==rows && res.cols()==0);
b.resize(0,rows);
res = b*a;
VERIFY(res.rows()==0 && res.cols()==cols);
}
{
Matrix<Scalar,PacketSize,0> a;
Matrix<Scalar,0,1> b;
Matrix<Scalar,PacketSize,1> res;
VERIFY_IS_APPROX( (res=a*b), MatrixType::Zero(PacketSize,1) );
VERIFY_IS_APPROX( (res=a.lazyProduct(b)), MatrixType::Zero(PacketSize,1) );
}
{
Matrix<Scalar,PacketSize1,0> a;
Matrix<Scalar,0,1> b;
Matrix<Scalar,PacketSize1,1> res;
VERIFY_IS_APPROX( (res=a*b), MatrixType::Zero(PacketSize1,1) );
VERIFY_IS_APPROX( (res=a.lazyProduct(b)), MatrixType::Zero(PacketSize1,1) );
}
{
Matrix<Scalar,PacketSize,Dynamic> a(PacketSize,0);
Matrix<Scalar,Dynamic,1> b(0,1);
Matrix<Scalar,PacketSize,1> res;
VERIFY_IS_APPROX( (res=a*b), MatrixType::Zero(PacketSize,1) );
VERIFY_IS_APPROX( (res=a.lazyProduct(b)), MatrixType::Zero(PacketSize,1) );
}
{
Matrix<Scalar,PacketSize1,Dynamic> a(PacketSize1,0);
Matrix<Scalar,Dynamic,1> b(0,1);
Matrix<Scalar,PacketSize1,1> res;
VERIFY_IS_APPROX( (res=a*b), MatrixType::Zero(PacketSize1,1) );
VERIFY_IS_APPROX( (res=a.lazyProduct(b)), MatrixType::Zero(PacketSize1,1) );
}
}
template<int>
void bug_127()
{
// Bug 127
//
// a product of the form lhs*rhs with
//
// lhs:
// rows = 1, cols = 4
// RowsAtCompileTime = 1, ColsAtCompileTime = -1
// MaxRowsAtCompileTime = 1, MaxColsAtCompileTime = 5
//
// rhs:
// rows = 4, cols = 0
// RowsAtCompileTime = -1, ColsAtCompileTime = -1
// MaxRowsAtCompileTime = 5, MaxColsAtCompileTime = 1
//
// was failing on a runtime assertion, because it had been mis-compiled as a dot product because Product.h was using the
// max-sizes to detect size 1 indicating vectors, and that didn't account for 0-sized object with max-size 1.
Matrix<float,1,Dynamic,RowMajor,1,5> a(1,4);
Matrix<float,Dynamic,Dynamic,ColMajor,5,1> b(4,0);
a*b;
}
template<int> void bug_817()
{
ArrayXXf B = ArrayXXf::Random(10,10), C;
VectorXf x = VectorXf::Random(10);
C = (x.transpose()*B.matrix());
B = (x.transpose()*B.matrix());
VERIFY_IS_APPROX(B,C);
}
template<int>
void unaligned_objects()
{
// Regression test for the bug reported here:
// http://forum.kde.org/viewtopic.php?f=74&t=107541
// Recall the matrix*vector kernel avoid unaligned loads by loading two packets and then reassemble then.
// There was a mistake in the computation of the valid range for fully unaligned objects: in some rare cases,
// memory was read outside the allocated matrix memory. Though the values were not used, this might raise segfault.
for(int m=450;m<460;++m)
{
for(int n=8;n<12;++n)
{
MatrixXf M(m, n);
VectorXf v1(n), r1(500);
RowVectorXf v2(m), r2(16);
M.setRandom();
v1.setRandom();
v2.setRandom();
for(int o=0; o<4; ++o)
{
r1.segment(o,m).noalias() = M * v1;
VERIFY_IS_APPROX(r1.segment(o,m), M * MatrixXf(v1));
r2.segment(o,n).noalias() = v2 * M;
VERIFY_IS_APPROX(r2.segment(o,n), MatrixXf(v2) * M);
}
}
}
}
template<typename T>
EIGEN_DONT_INLINE
Index test_compute_block_size(Index m, Index n, Index k)
{
Index mc(m), nc(n), kc(k);
internal::computeProductBlockingSizes<T,T>(kc, mc, nc);
return kc+mc+nc;
}
template<typename T>
Index compute_block_size()
{
Index ret = 0;
ret += test_compute_block_size<T>(0,1,1);
ret += test_compute_block_size<T>(1,0,1);
ret += test_compute_block_size<T>(1,1,0);
ret += test_compute_block_size<T>(0,0,1);
ret += test_compute_block_size<T>(0,1,0);
ret += test_compute_block_size<T>(1,0,0);
ret += test_compute_block_size<T>(0,0,0);
return ret;
}
template<typename>
void aliasing_with_resize()
{
Index m = internal::random<Index>(10,50);
Index n = internal::random<Index>(10,50);
MatrixXd A, B, C(m,n), D(m,m);
VectorXd a, b, c(n);
C.setRandom();
D.setRandom();
c.setRandom();
double s = internal::random<double>(1,10);
A = C;
B = A * A.transpose();
A = A * A.transpose();
VERIFY_IS_APPROX(A,B);
A = C;
B = (A * A.transpose())/s;
A = (A * A.transpose())/s;
VERIFY_IS_APPROX(A,B);
A = C;
B = (A * A.transpose()) + D;
A = (A * A.transpose()) + D;
VERIFY_IS_APPROX(A,B);
A = C;
B = D + (A * A.transpose());
A = D + (A * A.transpose());
VERIFY_IS_APPROX(A,B);
A = C;
B = s * (A * A.transpose());
A = s * (A * A.transpose());
VERIFY_IS_APPROX(A,B);
A = C;
a = c;
b = (A * a)/s;
a = (A * a)/s;
VERIFY_IS_APPROX(a,b);
}
template<int>
void bug_1308()
{
int n = 10;
MatrixXd r(n,n);
VectorXd v = VectorXd::Random(n);
r = v * RowVectorXd::Ones(n);
VERIFY_IS_APPROX(r, v.rowwise().replicate(n));
r = VectorXd::Ones(n) * v.transpose();
VERIFY_IS_APPROX(r, v.rowwise().replicate(n).transpose());
Matrix4d ones44 = Matrix4d::Ones();
Matrix4d m44 = Matrix4d::Ones() * Matrix4d::Ones();
VERIFY_IS_APPROX(m44,Matrix4d::Constant(4));
VERIFY_IS_APPROX(m44.noalias()=ones44*Matrix4d::Ones(), Matrix4d::Constant(4));
VERIFY_IS_APPROX(m44.noalias()=ones44.transpose()*Matrix4d::Ones(), Matrix4d::Constant(4));
VERIFY_IS_APPROX(m44.noalias()=Matrix4d::Ones()*ones44, Matrix4d::Constant(4));
VERIFY_IS_APPROX(m44.noalias()=Matrix4d::Ones()*ones44.transpose(), Matrix4d::Constant(4));
typedef Matrix<double,4,4,RowMajor> RMatrix4d;
RMatrix4d r44 = Matrix4d::Ones() * Matrix4d::Ones();
VERIFY_IS_APPROX(r44,Matrix4d::Constant(4));
VERIFY_IS_APPROX(r44.noalias()=ones44*Matrix4d::Ones(), Matrix4d::Constant(4));
VERIFY_IS_APPROX(r44.noalias()=ones44.transpose()*Matrix4d::Ones(), Matrix4d::Constant(4));
VERIFY_IS_APPROX(r44.noalias()=Matrix4d::Ones()*ones44, Matrix4d::Constant(4));
VERIFY_IS_APPROX(r44.noalias()=Matrix4d::Ones()*ones44.transpose(), Matrix4d::Constant(4));
VERIFY_IS_APPROX(r44.noalias()=ones44*RMatrix4d::Ones(), Matrix4d::Constant(4));
VERIFY_IS_APPROX(r44.noalias()=ones44.transpose()*RMatrix4d::Ones(), Matrix4d::Constant(4));
VERIFY_IS_APPROX(r44.noalias()=RMatrix4d::Ones()*ones44, Matrix4d::Constant(4));
VERIFY_IS_APPROX(r44.noalias()=RMatrix4d::Ones()*ones44.transpose(), Matrix4d::Constant(4));
// RowVector4d r4;
m44.setOnes();
r44.setZero();
VERIFY_IS_APPROX(r44.noalias() += m44.row(0).transpose() * RowVector4d::Ones(), ones44);
r44.setZero();
VERIFY_IS_APPROX(r44.noalias() += m44.col(0) * RowVector4d::Ones(), ones44);
r44.setZero();
VERIFY_IS_APPROX(r44.noalias() += Vector4d::Ones() * m44.row(0), ones44);
r44.setZero();
VERIFY_IS_APPROX(r44.noalias() += Vector4d::Ones() * m44.col(0).transpose(), ones44);
}
EIGEN_DECLARE_TEST(product_extra)
{
for(int i = 0; i < g_repeat; i++) {
CALL_SUBTEST_1( product_extra(MatrixXf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
CALL_SUBTEST_2( product_extra(MatrixXd(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
CALL_SUBTEST_2( mat_mat_scalar_scalar_product() );
CALL_SUBTEST_3( product_extra(MatrixXcf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2), internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2))) );
CALL_SUBTEST_4( product_extra(MatrixXcd(internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2), internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2))) );
CALL_SUBTEST_1( zero_sized_objects(MatrixXf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
}
CALL_SUBTEST_5( bug_127<0>() );
CALL_SUBTEST_5( bug_817<0>() );
CALL_SUBTEST_5( bug_1308<0>() );
CALL_SUBTEST_6( unaligned_objects<0>() );
CALL_SUBTEST_7( compute_block_size<float>() );
CALL_SUBTEST_7( compute_block_size<double>() );
CALL_SUBTEST_7( compute_block_size<std::complex<double> >() );
CALL_SUBTEST_8( aliasing_with_resize<void>() );
}
Event Timeline
Log In to Comment