[Numpy-discussion] [numpy] argmin in multidimensional arrays
Glen W. Mabey
Sat Mar 3 16:32:24 CST 2007
On Sat, Mar 03, 2007 at 03:09:35PM -0600, Robert Kern wrote:
> 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.
Okay, I see the reasoning. I am glad that functions like sum, max, and
min return a single value, unless axis is specified.
However, it seems to me that the arg* functions are inherently
different. After all, it is an index that is sought instead of a value,
and when this result cannot be directly applied to the original array,
then at first glance it appears to be ... less than intuitive.
Thanks for your reply.
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