[AstroPy] Running wcs_pix2world for all image pixels

[Thomas Robitaille]

On 16 October 2013 15:58, Maik Riechert <maik.riechert at arcor.de> wrote:
> Hi Tom,
>
> That's exactly what I needed. Thanks!
>
> It takes around 3s on my machine for a 4200x2800 image. Is that to be
> expected or are there some speedup tricks?

To be fair, you *are* converting 12 million positions through a WCS
transformation which is a non-trivial transformation so I'm not sure
if there are any speedups if you need all the values. However, the
question is whether you really need the world coordinates for *all*
pixels. What are you using the values for?

Cheers,
Tom

>
> Maik
>
>
> On 16/10/13 15:15, Thomas Robitaille wrote:
>>
>> Hi Maik,
>>
>> Someone asked a very similar question just yesterday on GitHub:
>>
>> https://github.com/astropy/astropy/issues/1587
>>
>> In short, the solution in your case is:
>>
>> NAXIS1 = 4256
>> NAXIS2 = 2832
>> x = np.arange(NAXIS1)
>> y = np.arange(NAXIS2)
>> X, Y = np.meshgrid(x, y)
>> ra, dec = wcs.wcs_pix2world(X, Y, 0)
>>
>> Any luck?
>>
>> Tom
>>
>>
>>
>>
>> On 16 October 2013 14:48, Maik Riechert <maik.riechert at arcor.de> wrote:
>>>
>>> Hi,
>>>
>>> I'm quite new to python and astropy and got stuck at the following which
>>> probably is extremely easy to do.
>>>
>>> I created a WCS object out of a FITS header and wanted to get the RA/Dec
>>> coordinates of each image pixel. I tried:
>>>
>>> w.wcs_pix2world(np.ndindex(4256, 2832), 0)
>>>
>>> where 4256x2832 are the image dimensions. This returns 'ValueError:
>>> object of too small depth for desired array'. I was trying to avoid
>>> allocating an array with all pixel coordinates and thought an iterator
>>> would work too.
>>>
>>> What would you recommend for my case (translating every pixel)?
>>>
>>> Cheers and thanks,
>>> Maik
>>>
>>>
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>
>