[Numpy-discussion] any better way to normalise a matrix

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in my code i am trying to normalise a matrix as below

mymatrix=matrix(..# items are of double type..can be negative
values....)
numrows,numcols=mymatrix.shape

for i in range(numrows):
	temp=mymatrix[i].max()
	for j in range(numcols):
		mymatrix[i,j]=abs(mymatrix[i,j]/temp)

# i am using abs() to make neg vals positive

this way the code takes too much time to run for a case of
numrows=25, and numcols=8100 etc..
being a beginner in numpy and python ,i would like to know if this can
be done more efficiently..can anyone advise?

thanx
dn