[Numpy-discussion] downsample vector with averaging

[Scott Ransom]

How about this:

---------------------------------------------
import numpy as Num

def downsample(vector, factor):
    """
    downsample(vector, factor):
        Downsample (by averaging) a vector by an integer factor.
    """
    if (len(vector) % factor):
        print "Length of 'vector' is not divisible by 'factor'=%d!" % factor
        return 0
    vector.shape = (len(vector)/factor, factor)
    return Num.mean(vector, axis=1)
---------------------------------------------

Scott


On Mon, May 08, 2006 at 01:17:16PM -0400, Ryan Krauss wrote:
> I need to downsample some data while averaging it.  Basically, I have
> a vector and I want to take for example every ten points and average
> them together so that the new vector would be made up of
> newvect[0]=oldvect[0:9].mean()
> newvect[1]=oldevect[10:19].mean()
> ....
> 
> Is there a built-in or vectorized way to do this?  I default to
> thinking in for loops, but that can lead to slow code.
> 
> Thanks,
> 
> Ryan
> 
> 
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Scott M. Ransom            Address:  NRAO
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