I want to use Eigen for sparse matrix multiplications, where in each iteration I want to remove all entries below a certain threshold. It seems to me that Eigen only removes elements exactly equal zero.
I am running Eigen 3.3.7, compiling with g++.
#include <Eigen/Sparse>
#include <Eigen/Dense>
#include <iostream>
using namespace Eigen;
typedef SparseMatrix<double> CscMat;
typedef SparseMatrix<double,RowMajor> CsrMat;
int N = 4;
CsrMat S, S2;
MatrixXd D(N, N), D2(N,N);
D << 1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16;
D *= 0.1;
S = D.sparseView(0.5);
std::cout << D << std::endl;
std::cout << S.nonZeros() << std::endl;
D2 = D;
D2 = (D2.array() < 0.5).select(0, D2);
S2 = D2.sparseView();
std::cout << D << std::endl;
std::cout << S2.nonZeros() << std::endl;
In the above S.nonzeros() returns 16, instead of expected 12 like in S2.nonzeros().
The output is:
0.1 0.2 0.3 0.4
0.5 0.6 0.7 0.8
0.9 1 1.1 1.2
1.3 1.4 1.5 1.6
16
0 0 0 0
0.5 0.6 0.7 0.8
0.9 1 1.1 1.2
1.3 1.4 1.5 1.6
12
There is a second parameter to sparseView
which is reference
. In the end, the product of the two will determine the threshold, so you should use the line:
S = D.sparseView(0.5, 1.0 - std::numeric_limits<double>::epsilon());
to obtain what you seem to want.
The actual code that does the evaluation is in MathFunctions.h
static inline bool isMuchSmallerThan(const Scalar& x, const OtherScalar& y,
const RealScalar& prec)
{
return numext::abs(x) <= numext::abs(y) * prec;
}
where the default prec
of type double is (currently) 1e-12
.