Hi! I have had a look at the list of numpy.loadtxt tickets. I have never contributed to numpy before, so I may be doing stupid things - don't be afraid to let me know!
My opinions are my own, and in detail, they are:
1752:
I attach a possible patch. FWIW, I agree with the request. The patch is
written to be compatible with the fix in ticket #1562, but I did not test that
yet.
1731:
This seems like a rather trivial feature enhancement. I attach a possible
patch.
1616:
The suggested patch seems reasonable to me, but I do not have a full list
of what objects loadtxt supports today as opposed to what this patch will
support.
1562:
I attach a possible patch. This could also be the default behavior to my
mind, since the function caller can simply call numpy.squeeze if needed.
Changing default behavior would probably break old code, however.
1458:
The fix suggested in the ticket seems reasonable, but I have never used
record arrays, so I am not sure of this.
1445:
Adding this functionality could break old code, as some old datafiles may
have empty lines which are now simply ignored. I do not think the feature is a
good idea. It could rather be implemented as a separate function.
1107:
I do not see the need for this enhancement. In my eyes, the usecols kwarg
does this and more. Perhaps I am misunderstanding something here.
1071:
It is not clear to me whether loadtxt is supposed to support missing
values in the fashion indicated in the ticket.
1163:
1565:
These tickets seem to have the same origin of the problem. I attach one
possible patch. The previously suggested patches that I've seen will not
correctly convert floats to ints, which I believe my patch will.
I hope you find this useful! Is there some way of submitting the patches for
review in a more convenient fashion than e-mail?
Cheers,
Paul.
1562.patch
Description: Binary data
1163.patch
Description: Binary data
1731.patch
Description: Binary data
1752.patch
Description: Binary data
On 25. mars 2011, at 16.06, Charles R Harris wrote: > Hi All, > > Could someone with an interest in loadtxt/savetxt look through the associated > tickets? A search on the tickets using either of those keys will return > fairly lengthy lists. > > Chuck > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion
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