> Alan G Isaac schrieb: >> >>> X[1] >> array([3,4]) >> >>> X[1,:] >> matrix([[3, 4]])
>> But again the point is: >> indexing for submatrices should produce matrices. >> Normal Python indexing should access the constituent arrays. On Mon, 26 Mar 2007, Sven Schreiber apparently wrote: > I think this is a tricky business. > There's also the rule "indexing reduces the rank, slicing preserves it". > Numpy-matrices form an exception to this rule, always being 2d, but the > exception is consistently enforced. > Now it seems you want to have an exception from the exception, correct? What I want: the best design. I did not claim that the current design is flawed, only to suspect it. Why I wrote: current behavior feels wrong -> suspect design flaw. What feels wrong: iterating over a container does not give access to the contained objects. This is not Pythonic. *Symptom* of the underlying problem: for matrix M, M[0] returns a matrix. Would the change I suggest mean that the behavior of the matrix class deviates less from the array class: yes. Does this mean the matrix class behavior would be less "consistent"? I have tried to explain why the answer is "no". hth, Alan Isaac _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
