[Numpy-discussion] numpy.filled, again
Thu Jun 13 16:06:52 CDT 2013
On Thu, Jun 13, 2013 at 4:47 PM, Eric Firing <email@example.com> wrote:
> On 2013/06/13 10:36 AM, Benjamin Root wrote:
>> On Thu, Jun 13, 2013 at 9:36 AM, Aldcroft, Thomas
>> <firstname.lastname@example.org <mailto:email@example.com>>
>> On Wed, Jun 12, 2013 at 2:55 PM, Eric Firing <firstname.lastname@example.org
>> <mailto:email@example.com>> wrote:
>> On 2013/06/12 8:13 AM, Warren Weckesser wrote:
>> > That's why I suggested 'filledwith' (add the underscore if
>> you like).
>> > This also allows a corresponding masked implementation,
>> > without clobbering the existing 'ma.filled'.
>> Consensus on np.filled? absolutely not, you do not have a consensus.
>> np.filledwith or filled_with: fine with me, maybe even with
>> everyone--let's see. I would prefer the underscore version.
>> +1 on np.filled_with. It's unique the meaning is extremely obvious.
>> We do use np.ma.filled in astropy so a big -1 on deprecating that
>> (which would then require doing numpy version checks to get the
>> right method). Even when there is an NA dtype the numpy.ma
>> <http://numpy.ma> users won't go away anytime soon.
>> I like np.filled_with(), but just to be devil's advocate, think of the
>> np.filled_with((10, 24), np.nan)
>> As I read that, I am filling the array with (10, 24), not NaNs. Minor
>> issue, for sure, but just thought I raise that.
>> -1 on deprecation of np.ma.filled(). -1 on np.filled() due to collision
>> with np.ma <http://np.ma> (both conceptually and programatically).
>> np.values() might be a decent alternative.
>> Ben Root
> Even if he is representing the devil, Ben raises a good point. To
> summarize, the most recent set of suggestions that seem not to have been
> completely shot down include:
> np.filled_with((10, 24), np.nan)
> np.full((10, 24), np.nan) # analogous to np.empty
> np.values((10, 24), np.nan) # seems clear, concise
> np.initialized((10, 24), np.nan) # a few more characters, but
> # seems clear to me.
> Personally, I like all of the last three better than the first.
sounds also good to me, a noun like np.ones, np.nans, np.infs, np.zeros
I don't like np.initialized because empty also initializes and array
(although) an empty one.
> NumPy-Discussion mailing list
More information about the NumPy-Discussion