[SciPy-dev] More on Summer NumPy Doc Marathon

Ralf Gommers ralf.gommers@googlemail....
Tue Jun 9 13:07:14 CDT 2009


On Tue, Jun 9, 2009 at 12:31 PM, David Goldsmith <d_l_goldsmith@yahoo.com>wrote:

>
> Thanks, Stefan.  The lists you suggest already exist (more or less,
> depending on the "thing," i.e., list of categories, completely, prioritized
> list of individual items, sort of, at least w/in the categories) on the
> Milestones page (that's essentially what the Milestones page is) and the
> list of individual items is far too long to duplicate here, but for
> everyone's convenience I'll provide the list of categories (at least those
> for which the goal has not been, or is not close to being, met, which is
> most of them):
>
> Data type investigation
> Fourier transforms
> Linear algebra
> Error handling
> Financial functions
> Functional operations
> Help routines
> Indexing
> Input/Output
> Logic, comparisons etc.
> Polynomials
> Random number generation
> Other random operations
> Boolean set operations
> Searching
> Sorting
> Statistics
> Comparison
> Window functions
> Sums, interpolation, gradients, etc
> Arithmetic + basic functions I
> Arithmetic + basic functions II
> Arithmetic + basic functions III
> Masked arrays
> Masked arrays, II
> Masked arrays, III
> Masked arrays, IV
> Operations on masks
> Even more MA functions I
> Even more MA functions II
> Numpy internals
> C-types
> Other math
> The matrix library
> Numarray compatibility
> Numeric compatibility
> Other array subclasses
> Matrix subclass
> Ndarray
> Ndarray, II
> Dtypes
> Ufunc
> Scalar base class
> Scalar types
>
> Comments:
>
> 0) The number of individual items in each of these categories varies from
> one to a few dozen or so
>
> 1) Omitted are a few "meta-categories," e.g., "Routines," "Basic Objects,"
> etc.
>
> 2) IMO, there are still too many of these (at least too many to not be
> intimidating in the manner Stefan has implied); I had it in mind to try to
> create an intermediate level of organization, i.e., "meso-categories," but I
> couldn't really justify it on grounds other than there are simply still too
> many categories to be unintimidating, so I was advised against usage of time
> in that endeavor.  However, if there's an outpouring of support for me doing
> that, it would fall on sympathetic ears.
>
> As far as prioritizing individual items, my opinion is that team leads
> should do that (or not, as they deem appropriate) - I wouldn't presume to
> know enough to do that in most cases.  However, if people want to furnish me
> with suggested prioritizations, I'd be happy to be the one to edit the Wiki
> to reflect these.
>
> DG
>


Of this list of categories, there are 14 that are either completely done or
have only one docstring in white / light-gray. So it is a less intimidating
than it looks:) And I like the size of the categories, many of them are
small enough that you can finish them in a weekend.

I don't know if there's a need to prioritize, but I would ask people with
in-depth knowledge of numpy to pick some of the ones that require that
knowledge. Some of these are (basically, stuff towards the bottom of the
page):
Numpy internals
Ufuncs
Dtypes
Numarray compatibility
Numeric compatibility
Other array subclasses
Scalar base class
Scalar types

Cheers,
Ralf
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