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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