This is a follow-up question to this other with the same title (I did a major edit to it, but I was told it should be another question - and I can't think of another title).
I am using Intel's MKL LAPACKE and CBLAS to calculate
yn = trans(a)*inv(zt)*a + trans(b)*inv(zl)*b
Where a and b are m-by-n real matrices, zt and zl are m-by-m complex matrices. The resulting complex matrix yn is n-by-n.
Here is how I am doing it:
zt <- inv(zt)
zl <- inv(zl)
c <- zt*a
yn <- trans(a)*c
c <- zl*b
yn <- trans(b)*c + yn
The C code:
#include <math.h>
#include <complex.h>
#include <stdlib.h>
#include <stdio.h>
#include <mkl_types.h>
#define MKL_Complex16 _Complex double //overwrite type
#include <mkl.h>
#include <mkl_lapacke.h>
int print_zmatrix_file(int m, int n, _Complex double* a, int lda, FILE* fp)
{
int i, j;
for( i = 0; i < m; i++ )
{
for( j = 0; j < n; j++ )
{
fprintf(fp, "(%.6f%+.6fj)", creal(a[i*lda+j]), cimag(a[i*lda+j]) );
if (j < n - 1) fprintf(fp, ",");
}
fprintf(fp, "\n");
}
return 0;
}
int calc_yn(
_Complex double* yn, double* a, double *b, _Complex double* zl,
_Complex double* zt, int m, int n)
{
lapack_int* ipiv = (MKL_INT*) malloc(sizeof(lapack_int)*m);
LAPACKE_zgetrf(LAPACK_ROW_MAJOR, m, m, zt, m, ipiv);
LAPACKE_zgetri(LAPACK_ROW_MAJOR, m, zt, m, ipiv);
LAPACKE_zgetrf(LAPACK_ROW_MAJOR, m, m, zl, m, ipiv);
LAPACKE_zgetri(LAPACK_ROW_MAJOR, m, zl, m, ipiv);
free(ipiv);
const double alpha = 1.0;
const double beta = 0.0;
lapack_complex_double* c = (lapack_complex_double*) malloc(
sizeof(lapack_complex_double)*(m*n));
// c <- zt*a
cblas_zgemm(CblasRowMajor, CblasNoTrans, CblasNoTrans,
m, n, m,
&alpha, zt, m, a, n,
&beta, c, n);
FILE* fp = fopen("c1.csv", "w");
print_zmatrix_file(m, n, c, n, fp);
fclose(fp);
// yn <- aT*c
cblas_zgemm(CblasRowMajor, CblasTrans, CblasNoTrans,
n, n, m,
&alpha, a, n, c, n,
&beta, yn, n);
// c <- zl*b
cblas_zgemm(CblasRowMajor, CblasNoTrans, CblasNoTrans,
m, n, m,
&alpha, zl, m, b, n,
&beta, c, n);
FILE* fp2 = fopen("c2.csv", "w");
print_zmatrix_file(m, n, c, n, fp2);
fclose(fp2);
// yn <- bT*c + yn
cblas_zgemm(CblasRowMajor, CblasTrans, CblasNoTrans,
n, n, m,
&alpha, b, n, c, n,
&alpha, yn, n);
free(c);
return 0;
}
int main()
{
int m = 2;
int n = 3;
_Complex double* yn = (_Complex double*) malloc(sizeof(_Complex double)*(n*n));
double a[] = {
0.5, 0.0, 0.5,
0.5, 0.5, 0.0
};
double b[] = {
1.0, 0.0, -1.0,
1.0, -1.0, 0.0
};
_Complex double zt[] = {
(0.004 + 0.09*I), (-0.004 - 0.12*I),
(-0.004 - 0.12*I), (0.005 + 0.11*I)
};
_Complex double zl[] = {
(0.1 + 2.13*I), (-124.004 - 800.12*I),
(-124.004 - 800.12*I), (0.4 + 4.08*I)
};
calc_yn(yn, a, b, zl, zt, m, n);
FILE* fp = fopen("yn.csv", "w");
print_zmatrix_file(n, n, yn, n, fp);
fclose(fp);
free(yn);
return 0;
}
// compile command (MKLROOT is defined by a bash script that is shipped together with intel's MKL):
//gcc -std=c11 -DMKL_ILP64 -m64 -g -o test.a test.c -L${MKLROOT}/lib/intel64 -Wl,--no-as-needed -lmkl_intel_ilp64 -lmkl_intel_thread -lmkl_core -liomp5 -lpthread -lm -ldl
The code in the previous question had an error in the malloc to yn (it was using sizeof(_Complex double*) instead of sizeof(_Complex double)). Having that error corrected, the code compiles and runs successfully. After running it, I compared the results with the ones I get with SciPy. They do not agree.
import numpy
from scipy import linalg
a = numpy.array([[0.5, 0.0, 0.5],
[0.5, 0.5, 0.0]])
b = numpy.array([[1.0, 0.0, -1.0],
[1.0, -1.0, 0.0]])
zt = numpy.array([[0.004 + 0.09j, -0.004 - 0.12j],
[-0.004 - 0.12j, 0.005 + 0.11j]])
zl = numpy.array([[0.1 + 2.13j, 124.004 - 800.12j],
[124.004 - 800.12j, 0.4 + 4.08j]])
c1 = numpy.matmul(linalg.inv(zt), a)
m1 = numpy.matmul(a.T, c1)
c2 = numpy.matmul(linalg.inv(zl), b)
m2 = numpy.matmul(b.T, c2)
yn = m1 + m2
yn_file = numpy.genfromtxt('yn.csv', delimiter=',', dtype=numpy.complex128)
c1_file = numpy.genfromtxt('c1.csv', delimiter=',', dtype=numpy.complex128)
c2_file = numpy.genfromtxt('c2.csv', delimiter=',', dtype=numpy.complex128)
numpy.max(numpy.abs(yn)) #0.004958820819049211
numpy.max(numpy.abs(yn_file)) #60.4590237745794
numpy.max(numpy.abs(c1)) #25.549314567403204
numpy.max(numpy.abs(c1_file)) #41.278805716697306
numpy.max(numpy.abs(c2)) #0.0012411403762584482
numpy.max(numpy.abs(c2_file)) #0.03292682468747935
There is something wrong either in my C code or in the Python one. Why I am getting different results?
Edit: further testing as per @Bwebb suggestion. He noticed a copy-paste error where -124.004 - 800.12i appears as +124.004 - 800.12i in the Python code. Correcting that does not change the results
To make it easier to test, I used the matrices:
a = numpy.array([[1.0, 0.0],
[0.0, 1.0]])
b = numpy.array([[0.0, -1.0],
[-1.0, 0.0]])
zt = a
zl = b
Which results in
yn = [[1.0, -1.0]
[-1.0, 1.0]]
The Python code gives that result, but the C one gives
yn = [[0.0 + 2.0j, 1.0 + 2.0j]
[-1.0 + 2.0j, 0.0 + 0.0j]]
That makes me conclude that the C code is wrong, but I do not know where.
