Hi there - quick suggestion on Xmas morning - others are much more
familar.
You do not want to use a loop to do the matrix multiply, you want to
use the intrinsic functions assoicated with matrix.
So you want something like
res = Math.abs( matmul(arrayone, arraytwo) )
note - that is not real code, just symbolic code. I am sure this is
easily found in the documentation.
cheers!
Lou
On Dec 25, 2007, at 8:47 AM, [EMAIL PROTECTED] wrote:
hi
i am doing some maths calculations involving matrices of double values
using numpy.matrix ,
java code for this is something like
int items=25;
int sample=5;
int totalcols=8100;
double[][]dblarrayone=new double[items][totalcols];
double[][]dblarraytwo=new double[items][totalcols];
//their elements are set elsewhere before calculation
double[][] resultarray = new double[items][sample];
for(int i=0;i<items;i++){
for(int j=0;j<sample;j++){
double tval=0.0;
for(int p=0;p<totalcols;p++)
tval+=dblarrayone[j][p] * dblarraytwo[i][p];
resultarray[i][j]=Math.abs(tval);
}
}
so I wanted to do the same in python..(may be this code is not in the
recommended way..)
i am storing the filled matrices and other values as instance variable
of a class and access them by self.whatever...
self.items=25
self.sample=5
self.totalcols=8100
#self.matrixone,self.matrixtwo are numply matix objects with already
filled elements
#but for testing i filled it with zeros
self.matrixone=matrix(zeros((items,totalcols)))
self.matrixtwo=matrix(zeros((items,totalcols)))
resultmatrix=matrix(zeros((self.items,self.sample)))
for i in range(self.items):
for j in range(self.sample):
tval=0.0
for p in range(self.totalcols):
tval +=self.matrixone[ j , p ] * self.matrixtwo[ i , p ]
resultmatrix[ i, j ]=abs(tval)
here I found that while the java code takes barely 110 milliseconds to
execute the code ,the
python code takes something like 53 secs to execute !!..I am baffled
by this ..can anyone advise me how i can improve this? (i want to code
in python so I can't use c,c++ , java)
dn
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