[Numpy-discussion] SphinxDocString class in new numpy doc framework
Matt Knox
mattknox_ca@hotmail....
Sun Jun 29 21:17:01 CDT 2008
I guess this question is mostly for Stefan... but I am trying to port the
scikits.timeseries module wiki documentation into a sphinx framework, and
also
trying to follow the numpy doc string standards (which can't be parsed
directly
by sphinx), so I'm trying to use the SphinxDocString class in
docscrape_sphinx.py to pre-process the doc strings. However, the doc strings
do
not seem to be getting processed correctly. I didn't dig deep into the
issue,
but I thought I'd ask first before I go any further in case I am approaching
this incorrectly all together.
If I try to process the numpy.swapaxes docstring for example, I get the
following output (note the formatting of the parameters):
>>> print SphinxDocString(np.swapaxes.__doc__)
Return a view of array a with axis1 and axis2 interchanged.
**Parameters**
``````````````
**a** : array_like
Input array.
axis1 : int
First axis.
axis2 : int
Second axis.
**Examples**
````````````
>>> x = np.array([[1,2,3]])
>>> np.swapaxes(x,0,1)
array([[1],
[2],
[3]])
>>> x = np.array([[[0,1],[2,3]],[[4,5],[6,7]]])
>>> x
array([[[0, 1],
[2, 3]],
[[4, 5],
[6, 7]]])
>>> np.swapaxes(x,0,2)
array([[[0, 4],
[2, 6]],
[[1, 5],
[3, 7]]])
================================================================
I don't know if the SphinxDocString class is even ready for use yet or not,
but
this didn't look right to me.
The other thing I was wondering is if anyone knows how to pre-process doc
strings on the fly such that you can mix them in with your .rst files
similar to
how the autodoc sphinx extension works (rather than just pre-generating a
big
dump of all the doc strings into a single .rst file). This is probably a
question more for the sphinx mailing list, but I thought I'd ask while I'm
on
the topic in case anyone has any quick tricks they can share.
Thanks,
- Matt
--
View this message in context: http://www.nabble.com/SphinxDocString-class-in-new-numpy-doc-framework-tp18187697p18187697.html
Sent from the Numpy-discussion mailing list archive at Nabble.com.
More information about the Numpy-discussion
mailing list