[Numpy-discussion] Help!!! Docstrings overrun by markup crap.

Charles R Harris charlesr.harris at gmail.com
Sun Mar 21 10:23:09 EDT 2010

On Sun, Mar 21, 2010 at 8:01 AM, Ralf Gommers
<ralf.gommers at googlemail.com>wrote:

> On Sun, Mar 21, 2010 at 9:58 PM, Ralf Gommers <ralf.gommers at googlemail.com
> > wrote:
>> On Sun, Mar 21, 2010 at 9:51 PM, Alan G Isaac <aisaac at american.edu>wrote:
>>> On 3/21/2010 12:54 AM, Ralf Gommers wrote:
>>> > too many blank lines are needed
>>> Please define "need" after seeing the compact example I posted.
>>> You need 4 blank lines in your example. Now I tried adding a description
>> for the first argument (q) like this:
>> q, r if mode = 'full' :
>>    - q : ndarray of float or complex, shape (M, K)
>>           Description of `q`.
>>    - r : ndarray of float or complex, shape (K, N)
>> That doesn't work, you need yet more blank lines (try this in the wiki
>> editor).
>> I just changed the docstring to the following, looks much better in both
>> plain text and html imho:
>> q : ndarray of float or complex, optional
>>     The orthonormal matrix, of shape (M, K). Only returned if
>>     ``mode='full'``.
>> r : ndarray of float or complex, optional
>>     The upper-triangular matrix, of shape (K, N) with K = min(M, N).
>>     Only returned when ``mode='full'`` or ``mode='r'``.
>> a2 : ndarray of float or complex, optional
>>     Array of shape (M, N), only returned when ``mode='economic``'.
>>     The  diagonal and the upper triangle of `a2` contains `r`, while
>>     the rest of the matrix is undefined.
> This line in the code is fairly amusing by the way:
> #  economic mode. Isn't actually economic.
> Economic mode is very similar to 'r' mode anyway, what's the point?
Economic mode is what the low level algorithm likely returns, it contains
the info needed to contruct q if  needed, or to efficiently apply q to
different vectors without constructing q; constructing q adds to the
computational and memory costs, as does pulling r out of the economic
return. The situation is analogous to the LU decomposition where the natural
form is to store both L and U in the original matrix. Other algorithms can
then use that compact form to solve equations with different right hand

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