Hello, I am trying to translate some Matlab code to NumPy. I started reading the NumPy book and, yeah it's a very long read :-/ One thing I am completely confused about are the concpets of "basic" vs. "advanced" indexing. Are there some good examples out there where for the same piece of code - Matlab and NumPy are compared? I feel looking at those maybe more helpful to get me started than an in-depth study of the book. I already read "Numpy for Matlab users" and at a glance it doesn't seem to contain equivalents to all the common indexing operations you'd do in Matlab.
Some concrete problems/questions I have right now: - Am I correct in assuming that all arrays have to be initialized to their final number of elements in NumPy (using empty/zero for instance)? - Given a matrix R, is there an equvialent to the Matlab operation R(:,j) = [] (which removes column j and "shrinks" the matrix? - For (basic ?) indexing of an ndarray - is there any reason to prefer A[i,j] over A[i][j]? - Is it "pythonic" to initialize vectors to 2 dimensions so that vec.shape== (len(vec), 1) instead of vec.shape == (len(vec),)? Alright, Thanks for now, David
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