[SciPy-User] Avoiding lambda functions

David MacQuigg macquigg@ece.arizona....
Mon Oct 18 19:08:46 CDT 2010


> Reply to all. 

Many thanks to Robert and Zachary.  I see now we don't even need the 
gaussianfilter function.  We can just use gauss directly.  Code modifications 
below.

Thanks also to Stefan.  I'll check out py4science.

> from numpy import exp, indices  # numpy package from scipy.org
> img0 = imread('Lena.pgm')    # a 200 by 200 greyscale image
> shape = img0.shape           # (200, 200)
> 
> def gauss(i,j,sigma,shape):  # a 2D gaussian function
>     x = -1.0 + 2.0*i/shape[0]
>     y = -1.0 + 2.0*j/shape[1]
>     return exp(-(x*x+y*y)/(2*sigma*sigma))

iray, jray = indices(shape)
filter = gauss(iray, jray, 0.1, shape)






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