Glen W. Mabey wrote: > Does anyone else find this behavior counter-intuitive? > > It seems to me that one of the great design features of numpy is the > n-dim generality it provides, and argmin is one function in this breaks > down, IMHO.
Not at all. It consistently applies the simple rule: if the method operates over an axis, it takes an axis= keyword argument. The default for the axis= argument is None, which means that it operates over the flattened array. Other axes need to be specified explicitly. See .sum(), .mean(), .var(), .repeat(), .min(), etc. -- Robert Kern "I have come to believe that the whole world is an enigma, a harmless enigma that is made terrible by our own mad attempt to interpret it as though it had an underlying truth." -- Umberto Eco _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
