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# [numarray] mean vector of 2d matrix

 P: n/a Hi all, I was wondering what is the best way to compute the mean vector of a matrix. Currently I'm doing this: data.shape (117027, 8) mean = (numarray.add.reduce(data, axis=1))/(data.shape[1]) but maybe there is a faster way? cheers Jul 18 '05 #1
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 P: n/a Curzio Basso wrote in message news:<40********@maser.urz.unibas.ch>... Hi all, I was wondering what is the best way to compute the mean vector of a matrix. Currently I'm doing this: With Numeric, one can use the 'average' function to compute the average along an axis, or the average of all elements when the axis argument is set to None. See p317 of Martelli's "Python in a Nutshell" book. For example, the code from Numeric import zeros,Float,average nr = 3 nc = 2 xx = zeros([nr,nc],Float) for i in range(nr): for j in range(nc): xx[i,j] = i + 10.0*j print xx for i in [None,0,1]: print "\n",i,average(xx,axis=i) produces output [[ 0. 10.] [ 1. 11.] [ 2. 12.]] None 6.0 0 [ 1. 11.] 1 [ 5. 6. 7.] Jul 18 '05 #2

 P: n/a be*******@aol.com wrote: With Numeric, one can use the 'average' function to compute the average along an axis, or the average of all elements when the axis argument is set to None. See p317 of Martelli's "Python in a Nutshell" book. For example, the code However, it looks like in numarray no average() is provided. Now I found out there is an average() function provided by the MA (Masked Arrays) module, but I do not really understand why there is an average() function for a masked array and not for a generic array... Anyway, thanks for the tip! Jul 18 '05 #3

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