[Numpy-discussion] users point of view and ufuncs

Sasha ndarray at mac.com
Thu Aug 24 22:10:24 CDT 2006

On 8/24/06, Bill Baxter <wbaxter at gmail.com> wrote:
> Hey Sasha.  Your defnition may be more correct, but I have to confess
> I don't understand it.
>    "Universal function. Universal functions follow similar rules for
> broadcasting, coercion and "element-wise operation"."
> What is "coercion"? (Who or what is being coerced to do what?) and
> what does it mean to "follow similar rules for ... coercion"?  Similar
> to what?

This is not my definition, I just rephrased the introductory paragraph
from the ufunc section of the "Numerical Python"
<http://numpy.scipy.org/numpydoc/numpy-7.html#pgfId-36127>.  Feel free
to edit it so that it makes more sense.

Please note that I originally intended the "Numpy Glossary" not as a
place to learn new terms, but as a guide for those who know more than
one meaning of the terms or more than one way to call something. (See
the preamble.)   This may explain why I did not include "ufunc" to
begin with.  (I remember deciding not to include "ufunc", but I don't
remember the exact reason anymore.)

I would welcome an effort to make the glossary more novice friendly,
but not at the expense of oversimplifying things.

BTW, do you think "Rank ... (2) number of orthogonal dimensions of a
matrix" is clear?  Considering that matrix is defined a "an array of
rank 2"?  Is "rank" in  linear algebra sense common enough in numpy
documentation to be included in the glossary?

For comparison, here are a few alternative formulations of matrix rank

"The rank of a matrix or a linear map is the dimension of the image of
the matrix or the linear map, corresponding to the number of linearly
independent rows or columns of the matrix, or to the number of nonzero
singular values of the map."

"In linear algebra, the column rank (row rank respectively) of a
matrix A with entries in some field is defined to be the maximal
number of columns (rows respectively) of A which are linearly

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