I'm trying to port a "C" code to Python, this is what I coded:
scale = 1.0 / (rows * cols)
RemoveConstantBiasFrom(rarray, scale)
zarray = rarray[:]
zarray = DCT(zarray, rows, cols)
zarray = zarray.flatten()
beta = np.dot(rarray, zarray)
if iloop == 0:
parray = zarray[:]
else:
btemp = beta / beta_prev
parray = zarray + btemp * parray
RemoveConstantBiasFrom(parray, scale)
beta_prev = beta
for j in range(rows):
for i in range(cols):
k = j * rows + i
k1 = k + 1 if i < cols - 1 else k - 1
k2 = k - 1 if i > 0 else k + 1
k3 = k + cols if j < rows - 1 else k - cols
k4 = k - cols if j > 0 else k + cols
w1 = SIMIN(wts[k], wts[k1])
w2 = SIMIN(wts[k], wts[k2])
w3 = SIMIN(wts[k], wts[k3])
w4 = SIMIN(wts[k], wts[k4])
A = (w1 + w2 + w3 + w4) * parray[k]
B = (w1 * parray[k1] + w2 * parray[k2])
C = (w3 * parray[k3] + w4 * parray[k4])
zarray[k] = A - (B + C)
wts
and parray
are two flattened arrays with 262144 values (a 512x512 matrix). When I'm perfoming this operation I get:
test.py:152: RuntimeWarning: overflow encountered in double_scalars
B = (w1 * parray[k1] + w2 * parray[k2])
test.py:154: RuntimeWarning: overflow encountered in double_scalars
C = (w3 * parray[k3] + w4 * parray[k4])
test.py:155: RuntimeWarning: overflow encountered in double_scalars
zarray[k] = A - B + C
So, I started to "debug" the code.
1) I put a print
to max(parray)
before the loops and I obtained:
Maximum value for parray 15.2665322926
2) I added an if statement inside the loop to watch parray[k1]
behavior if parray[k1] > maxparray: print k1
and I obtained a lot of "k1's":
...
251902
252414
252926
253438
253950
254462
254974
255486
255998
256510
257022
257534
258046
258558
259070
259582
260094
260606
261118
261630
262142
So, the question: If I never changed "parray" why I'm getting different values exceeding max(parray)
?
This is the C code:
int i, j, k;
int k1, k2, k3, k4;
double sum, w1, w2, w3, w4, btemp, delta, avg, scale;
float *wts;
scale = 1.0/(xsize*ysize);
/* remove constant bias from rarray */
for (k=0, avg=0.0; k<xsize*ysize; k++) avg += rarray[k];
avg *= scale;
for (k=0; k<xsize*ysize; k++) rarray[k] -= avg;
/* compute cosine transform solution of Laplacian in rarray */
for (k=0; k<xsize*ysize; k++) {
zarray[k] = rarray[k];
}
DCT(zarray, xsize, ysize, xcos, ycos);
/* calculate beta and parray */
for (k=0, *beta=0.0; k<xsize*ysize; k++) {
*beta += rarray[k]*zarray[k];
}
printf("beta = %lf\n", *beta);
if (iloop == 0) {
for (k=0; k<xsize*ysize; k++) {
parray[k] = zarray[k];
}
}
else {
btemp = (*beta)/(*beta_prev);
for (k=0; k<xsize*ysize; k++) {
parray[k] = zarray[k] + btemp*parray[k];
}
}
/* remove constant bias from parray */
for (k=0, avg=0.0; k<xsize*ysize; k++) avg += parray[k];
avg *= scale;
for (k=0; k<xsize*ysize; k++) parray[k] -= avg;
*beta_prev = *beta;
/* calculate Qp */
for (j=0; j<ysize; j++) {
for (i=0; i<xsize; i++) {
k = j*xsize + i;
k1 = (i<xsize-1) ? k + 1 : k - 1;
k2 = (i>0) ? k - 1 : k + 1;
k3 = (j<ysize-1) ? k + xsize : k - xsize;
k4 = (j>0) ? k - xsize : k + xsize;
if (dxwts==NULL && dywts==NULL) { /* unweighted */
w1 = w2 = w3 = w4 = 1.0;
}
else if (dxwts==NULL || dywts==NULL) { /* one set of wts */
wts = (dxwts) ? dxwts : dywts;
w1 = SIMIN(wts[k], wts[k1]);
w2 = SIMIN(wts[k], wts[k2]);
w3 = SIMIN(wts[k], wts[k3]);
w4 = SIMIN(wts[k], wts[k4]);
}
else { /* dxwts and dywts are both supplied */
w1 = dxwts[k];
w2 = (i>0) ? dxwts[k-1] : dxwts[k];
w3 = dywts[k];
w4 = (j>0) ? dywts[k-xsize] : dywts[k];
}
zarray[k] = (w1 + w2 + w3 + w4)*parray[k]
- (w1*parray[k1] + w2*parray[k2]
+ w3*parray[k3] + w4*parray[k4]);
}
}
I'm just passing dxwts
(one set of weights) so the others are not needed, that's why I'm using one if statement, where SIMIN is:
#define SIMIN(x,y) (((x)*(x) < (y)*(y)) ? (x)*(x) : (y)*(y))
The problem is the way I'm copying the arrays, the correct way is: