On Fri, Aug 21, 2009 at 3:10 PM, Dokuro<[email protected]> wrote:
> miren lo que se esta haciendo desde la comunidad de SciPY y Numpy
>
>
> ---------- Forwarded message ----------
> From: Pauli Virtanen <[email protected]>
> Date: Sat, Aug 22, 2009 at 3:00 PM
> Subject: [SciPy-dev] NumPy User Guide table of contents
> To: [email protected]
>
>
> Hi all,
>
> It's great to see that people are interested in contributing
> narrative documentation to Numpy! I think this effort will be
> accelerated much if we have a table of contents for the final
> manual we want, to guide the writing.
>
> One suggestion is listed below. It's also on this wiki page:
>
>        http://scipy.org/Developer_Zone/UG_Toc
>
> It's not complete or final, but should already serve at least
> as a starting point. I think it would be best if we agreed on
> this first, fleshing out what should go where, and what each
> chapter should contain, before spending too much time on
> writing actual content.
>
> So, please chip in: look at the suggestion below, and criticize
> it and fill in additions and ideas.
>
> Cheers,
> Pauli
>
>    ***
>
> ************
> Numpy Manual
> ************
>
> The aim here is to write narrative documentation that illustrates how
> Numpy is best used in practice, demonstrating various features it
> offers, with examples and enlightened discussion.
>
> Below, a draft for the table of contents is listed. It is formed by
> looking at
>
> - `Numeric manual <http://numpy.scipy.org/numpydoc/numdoc.htm>`__
> - `Guide to Numpy <http://www.tramy.us/>`__
>
> and stealing whatever seemed good to include. It's a rough draft, and
> probably needs tuning at various points. Also, I'm aware not all of
> Numpy is there now, so additions should also be made.
>
>
> #. Introduction to Numpy
>   #. What it is
>   #. What is there: a very high-level overview
>   #. Conventions in this manual
> #. Installing Numpy
>   #. Instructions for getting binaries
>   #. Instructions for building from source, on different platforms
> #. Basics of arrays
>  #. What is an array
>  #. Storing data in arrays
>     #. Arrays as literals
>     #. Creating arrays: empty, zeros, ones, ...
>     #. Saving/loading to a file: text, npz  -> point to other IO routines
>  #. Extracting data from arrays
>     #. Basic indexing and slicing
>     #. Simple fancy indexing
>     #. Finding items in arrays
>        #. comparisons, logic operations, indexing based on them
>        #. where, searchsorted
>     #. Advanced indexing on arrays: ellipsis, newaxis
>  #. Views and copies of arrays
>     #. Demonstrate that slicing in general creates views
>  #. Modifying contents of arrays
>     #. Setting data in arrays via indexing
>     #. add, multiply subtract
>     #. in-place operations (+ the common indexing caveat!)
>     #. sum, mean, min, max, ...
>     #. remark on ufuncs: common methods
>     #. Operating on an axis of an array
>  #. Broadcasting
>  #. Joining, splitting arrays and changing their shape
>     #. *stack, *split
>     #. reshape
>     #. resize
>  #. Working with different types of data: integers, floats, complex, 
> strings...
>     #. Basic creation of arrays with certain data types
>     #. Building up data type objects
>     #. Casting and converting array data, automatic casting, coercion
>  #. Advanced data types and structured arrays
>     #. Creating structured arrays
>     #. Defining them: literals, loading from files
>     #. Accessing data in them
> #. Other topics
>   #. Working with missing data
>      #. NaNs as masking
>      #. Masked arrays
>   #. Linear algebra and matrices
>   #. Working with polynomials
>   #. Floating point issues: errors, error handling, inaccuracy, etc.
>   #. Fourier transforms
>   #. Generating random numbers
>   #. Building and testing packages using Numpy
>   #. Financial calculations with Numpy
> #. Extending Numpy
>   #. Subclassing numpy arrays
>   #. Array interface
>   #. Ctypes support in Numpy
>   #. Cython? Pyrex? F2Py?
>   #. Writing C extensions using Numpy
>      #. Basics
>      #. Iteration
>      #. Ufuncs
>      #. Data types
>      #. Subclassing in C
> #. Numpy internals
>   #. Memory model
>   #. Data type stuff
>   #. Ufuncs
>   #. etc?
>
> #. Reference
>   <insert our current "reference manual" here as-is and factor out
>   any duplication later on>
>

¿Algún avance de parte de NumPy? Pregunto porque vi esto:
http://www.nabble.com/documentation-translation-td24961372.html y por
lo que veo ellos están de acuerdo con que procedamos.

Saludos,

-- 
Muammar El Khatib.
Linux user: 403107.
GPG Key = 127029F1
http://muammar.me | http://proyectociencia.org
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