Hi Greg, I don't know how specific it is to NumPy, but that's definitely the correct way to talk about it in NumPy, and your understanding in your example is spot-on. This is true of many NumPy functions.
Juan. On 30 Dec. 2016, 9:08 AM +1100, greg g <[email protected]>, wrote: > Thanks > Is this a numpy specific terminology ? > For a multidimensionnal array with dimension=n and size l1 x l2 x ... x ln, > does "along axis=0" mean that l2 x..x ln operations are performed scrolling > first dimension, each operation on l1 elements, and that an array with > dimension n-1 and size l2 x..x ln containing the operations results is > returned? > ( Finally I'm not sure this sentence really clarify ... ;-) ) > > De : scikit-learn <[email protected]> de la > part de Jacob Schreiber <[email protected]> > Envoyé : jeudi 29 décembre 2016 20:22 > À : Scikit-learn user and developer mailing list > Objet : Re: [scikit-learn] numpy.amin behaviour with multidimensionnal arrays > > It means that instead of returning the minimum value anywhere in the entire > matrix, it will return the minimum value for each column or each row > depending on which axis you put in, so a vector instead of a scalar. > > > On Thu, Dec 29, 2016 at 6:00 AM, greg g <[email protected]> wrote: > > > Hi, > > > I would like to understand the behaviour of the scipy.spatial.kdtree > > > class that uses numpy.amin function. > > > In the numpy.amin description, we find that it returns the "minimum value > > > along a given axis" > > > What does it mean exactly ? > > > > > > Thanks for any help > > > Gregory > > > > > > > > > _______________________________________________ > > > scikit-learn mailing list > > > [email protected] > > > https://mail.python.org/mailman/listinfo/scikit-learn > > > > > _______________________________________________ > scikit-learn mailing list > [email protected] > https://mail.python.org/mailman/listinfo/scikit-learn
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