Hi all.

 

i work mainly with “volume” (3d) images, and numpy.ndarray answers most of my needs (addition of images, etc.). The problem I’m faced now with is that I have images of matrices and vectors and would like that when I do image_of_matrices * image_of_vector is does the dot product of each of my matrices with all of my vectors, and when I do image_of_matrices.mean() it gives me the mean matrix. Basically, I want the same functionalities that are currently provided with scalars, but applied to matrices.

 

It seems that a nice way of doing this is to have and ndarray of numpy.matrix, but this isn’t supported it seems. Can anyone recommend a good way of implementing this? I’m new with the numpy thing and I’m not sure if subclassing ndarray is a good idea since I’ll have to overload all the operators and i don’t believe this will result in a very fast implementation, but I might be mistaken. Another possibility may be to create a new dtype for numpy.matrix, but I don’t know if this is possible. Anyone have recommandations?

 

Thx for any help.

 

Alex.


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