how to speedup this code?

[Ognen Duzlevski]

Hi all,

I have rewritten a C program to solve a bioinformatics problem. Portion where most of the time is spent is:

def DynAlign(scoremat,insertmat,delmat,tseq,qseq,tlen,qlen):
    global ONEINDELPENALTY,OPENGAPPENALTY

    for ndx1 in range(1,tlen+1):
        for ndx2 in range(1,qlen+1):
            delmat[ndx1][ndx2] = Min(delmat[ndx1-1][ndx2]+ONEINDELPENALTY, \
                             Min(scoremat[ndx1-1][ndx2]+OPENGAPPENALTY+ONEINDELPENALTY, \
                             insertmat[ndx1-1][ndx2]+OPENGAPPENALTY+ONEINDELPENALTY))
            insertmat[ndx1][ndx2] = Min(insertmat[ndx1][ndx2-1]+ONEINDELPENALTY, \
                            Min(scoremat[ndx1][ndx2-1]+OPENGAPPENALTY+ONEINDELPENALTY, \
                            delmat[ndx1][ndx2-1]+OPENGAPPENALTY+ONEINDELPENALTY))
            scoremat[ndx1][ndx2] = Min(scoremat[ndx1-1][ndx2-1], \
                            Min(delmat[ndx1-1][ndx2-1], insertmat[ndx1-1][ndx2-1])) + \
                            GetFitnessScore(tseq,ndx1-1,qseq,ndx2-1)

def Min(a,b):
	if a< b:
		return a
	else:
		return b

In C this is not a big deal, delmat, scoremat and insertmat are int matrices dynamically allocated and the 
loop-inside-a-loop is pretty fast. However, on python (2.3) it is very slow. So for comparison, my C version takes 8 
seconds to execute and the python version takes around 730 seconds. I have narrowed down through visual observation 
(print before and print after entry into the above nested loop) that most of the time is spent in there. I have also 
tried the Numeric package with their arrays. It speeded things up somewhat but not considerably.

Any suggestions?

Thank you,
Ognen