devtools/eigen
1
0
Fork 0
mirror of https://gitlab.com/libeigen/eigen.git synced 2026-04-10 11:34:33 +08:00
Code Issues Packages Projects Releases Wiki Activity

finally directly calling the low-level products is faster

Browse Source
This commit is contained in:
Gael Guennebaud
2009-07-10 10:41:26 +02:00
parent 8885d56928
commit 1a1b2e9f27
12 changed files with 111 additions and 146 deletions
Download Patch File Download Diff File Expand all files Collapse all files

53
test/product_extra.cpp
View File

@@ -47,8 +47,6 @@ template<typename MatrixType> void product_extra(const MatrixType& m)
square2 = MatrixType::Random(cols, cols),
res2 = MatrixType::Random(cols, cols);
RowVectorType v1 = RowVectorType::Random(rows), vrres(rows);
// v2 = RowVectorType::Random(rows),
// vzero = RowVectorType::Zero(rows);
ColVectorType vc2 = ColVectorType::Random(cols), vcres(cols);
OtherMajorMatrixType tm1 = m1;
@@ -56,14 +54,14 @@ template<typename MatrixType> void product_extra(const MatrixType& m)
s2 = ei_random<Scalar>(),
s3 = ei_random<Scalar>();
int c0 = ei_random<int>(0,cols/2-1),
c1 = ei_random<int>(cols/2,cols),
r0 = ei_random<int>(0,rows/2-1),
r1 = ei_random<int>(rows/2,rows);
// int c0 = ei_random<int>(0,cols/2-1),
// c1 = ei_random<int>(cols/2,cols),
// r0 = ei_random<int>(0,rows/2-1),
// r1 = ei_random<int>(rows/2,rows);
// all the expressions in this test should be compiled as a single matrix product
// TODO: add internal checks to verify that
/*
VERIFY_IS_APPROX(m1 * m2.adjoint(), m1 * m2.adjoint().eval());
VERIFY_IS_APPROX(m1.adjoint() * square.adjoint(), m1.adjoint().eval() * square.adjoint().eval());
VERIFY_IS_APPROX(m1.adjoint() * m2, m1.adjoint().eval() * m2);
@@ -111,49 +109,14 @@ template<typename MatrixType> void product_extra(const MatrixType& m)
VERIFY_IS_APPROX((-m1.adjoint() * s2) * (s1 * v1.adjoint()),
(-m1.adjoint()*s2).eval() * (s1 * v1.adjoint()).eval());
*/
// test with sub matrices
m2 = m1;
m3 = m1;
// std::cerr << (m1.block(r0,c0, r1-r0, c1-c0) * vc2.segment(c0,c1-c0)).rows() << " " << (m1.block(r0,c0, r1-r0, c1-c0) * vc2.segment(c0,c1-c0)).cols() << " == " << vrres.segment(r0,r1-r0).rows() << " " << vrres.segment(r0,r1-r0).cols() << "\n";
// m2.col(c0).segment(0,r1-r0) += (m1.block(r0,c0, r1-r0, c1-c0) * vc2.segment(c0,c1-c0)).lazy();
// m3.col(c0).segment(0,r1-r0) += (m1.block(r0,c0, r1-r0, c1-c0) * vc2.segment(c0,c1-c0)).eval();
Matrix<Scalar,Dynamic,1> a = m2.col(c0), b = a;
a.segment(5,r1-r0) += (m1.block(r0,c0, r1-r0, c1-c0) * vc2.segment(c0,c1-c0)).lazy();
b.segment(5,r1-r0) += (m1.block(r0,c0, r1-r0, c1-c0) * vc2.segment(c0,c1-c0)).eval();
// m2.col(c0).segment(0,r1-r0) += (m1.block(r0,c0, r1-r0, c1-c0) * vc2.segment(c0,c1-c0)).lazy();
// m3.col(c0).segment(0,r1-r0) += (m1.block(r0,c0, r1-r0, c1-c0) * vc2.segment(c0,c1-c0)).eval();
// if (!m2.isApprox(m3))
std::cerr << (a-b).cwise().abs().maxCoeff() << "\n";
VERIFY_IS_APPROX(a,b);
// VERIFY_IS_APPROX( vrres.segment(0,r1-r0).transpose().eval(),
// v1.segment(0,r1-r0).transpose() + m1.block(r0,c0, r1-r0, c1-c0).eval() * (vc2.segment(c0,c1-c0)).eval());
}
void test_product_extra()
{
for(int i = 0; i < g_repeat; i++) {
int rows = ei_random<int>(2,10);
int cols = ei_random<int>(2,10);
int c0 = ei_random<int>(0,cols/2-1),
c1 = ei_random<int>(cols/2,cols),
r0 = ei_random<int>(0,rows/2-1),
r1 = ei_random<int>(rows/2,rows);
MatrixXf m1 = MatrixXf::Random(rows,cols), m2 = m1;
Matrix<float,Dynamic,1> a = m2.col(c0), b = a;
Matrix<float,Dynamic,1> vc2 = Matrix<float,Dynamic,1>::Random(cols);
if (1+r1-r0<rows) {
a.segment(1,r1-r0) += (m1.block(r0,c0, r1-r0, c1-c0) * vc2.segment(c0,c1-c0)).lazy();
b.segment(1,r1-r0) += (m1.block(r0,c0, r1-r0, c1-c0) * vc2.segment(c0,c1-c0)).eval();
VERIFY_IS_APPROX(a,b);
}
// CALL_SUBTEST( product_extra(MatrixXf(ei_random<int>(1,320), ei_random<int>(1,320))) );
// CALL_SUBTEST( product_extra(MatrixXd(ei_random<int>(1,320), ei_random<int>(1,320))) );
// CALL_SUBTEST( product(MatrixXi(ei_random<int>(1,320), ei_random<int>(1,320))) );
// CALL_SUBTEST( product_extra(MatrixXcf(ei_random<int>(50,50), ei_random<int>(50,50))) );
// CALL_SUBTEST( product(Matrix<float,Dynamic,Dynamic,RowMajor>(ei_random<int>(1,320), ei_random<int>(1,320))) );
CALL_SUBTEST( product_extra(MatrixXf(ei_random<int>(1,320), ei_random<int>(1,320))) );
CALL_SUBTEST( product_extra(MatrixXcf(ei_random<int>(50,50), ei_random<int>(50,50))) );
CALL_SUBTEST( product_extra(Matrix<std::complex<double>,Dynamic,Dynamic,RowMajor>(ei_random<int>(1,50), ei_random<int>(1,50))) );
}
}