Hi,
On 01/17/2012 08:57 PM, Dmitrey wrote:
On 01/17/2012 08:35 PM, Maciej Fijalkowski wrote:
On Tue, Jan 17, 2012 at 8:22 PM, Dmitrey<[email protected]> wrote:
Well, it doesn't matter essentially, from the code I just see it parses
dir(numpypy) and doesn't provide information on the funcs been
worked on,
thus maybe my own efforts to port a func will be just a waste of time,
because someone other will make it done before me.
I guess the main point why it does that is that it can be fully
automatic. It's impossible to keep track manually marking those
functions.
There are lots of free online tables and spreadsheets, e.g. google or
my favorite zoho.com, with many other convenient stuff. A NumPyPy
state info datasheet could be created with 1st column - implemented
funcs, next several columns - triples like (funcname,
person_working_on_it, estimated_finish_date), or something like that,
filled by the persons. Potential NumPyPy users or contributors could
review current state of numpypy development without having to download
and install each latest night pypy build and, possibly, propose their
own contributions or financial support to implement funcs they need
and still miss. I guess it's not so difficult to create and maintain,
but, of course, you could select any other approach.
-----------------------
Regards, D.
http://openopt.org/Dmitrey
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I have compared contains of numpy and numpypy, numpy has 551 entries
(and some of them are modules with lots of other funcs, like linalg or
fft), while nympypy has only 121 entry - thus, I guess, numpypy still is
too far from full numpy port. Well, some of numpy funcs are used very
rarely and thus can be omitted for now.
I have reviewed difference of the modules, and IMHO currently these
funcs are most important:
array_equal nanargmax hstack diag nanmin sinh atleast_1d asscalar eye
zeros_like logical_or tile cosh empty_like array_equiv asfarray
nanargmin asarray log2 vstack logical_xor nansum rot90 copy savetxt
logical_not ceil median where isfinite isnan diff tanh cross flipud
isscalar insert logical_and nanmax ones_like log log10 arccosh isinf
My skills and current possibilities allow me to work only on limited
subset of the funcs mentioned above, if noone mind, during several next
days I intend to work on he following funcs - maybe very simple to be
ported, but very important:
array_equal diag asscalar eye zeros_like empty_like array_equiv flipud
isscalar ones_like
BTW you mentioned [nan][arg]min/max works on a nightly build (except of
axis parameter)
(http://morepypy.blogspot.com/2012/01/numpypy-progress-report-running.html?showComment=1326227233044#c7372676427534170441),
but I didn't see them at all, as well as numpypy.nan number at all.
Maybe they are present in a mercurial branch, that was forgotten to be
committed to main trunc?
As for the table, if you think it's hard to create and maintain, I could
create it by myself, fill by currently done functions, share edit
permission with you, and you will share it with other volunteers, to
keep them and other people of numpy funcs that are done and under
development. I just thought you would prefer to be creator and single
owner of the table and that it doesn't take much time to be done, that's
why I had proposed it to be done by you. Also, maybe it would be a good
idea to provide link to the table from main pypy.org webpage.
-----------------------
Regards, D.
http://openopt.org/Dmitrey
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