[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
Numpy internals
Numarray compatibility
Numeric compatibility
Other array subclasses
Scalar base class
Scalar types

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