On Thu, Jun 13, 2013 at 5:06 PM, <josef.pktd@gmail.com> wrote:

On Thu, Jun 13, 2013 at 4:47 PM, Eric Firing <efiring@hawaii.edu> wrote:

On 2013/06/13 10:36 AM, Benjamin Root wrote:

On Thu, Jun 13, 2013 at 9:36 AM, Aldcroft, Thomas <aldcroft@head.cfa.harvard.edu <mailto:aldcroft@head.cfa.harvard.edu>> wrote:

On Wed, Jun 12, 2013 at 2:55 PM, Eric Firing <efiring@hawaii.edu <mailto:efiring@hawaii.edu>> 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, 'ma.filledwith', > 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 syntax:

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.

Cheers! 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.

What about: np.filled_array((10, 24), np.nan) If I just saw np.values(..) in some code I would never guess what it is doing from the name, and beyond that I would guess that I can put in multiple "values" in the second arg. np.initialized() is more obvious to me. - Tom

np.values 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.

Josef

Eric

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