[AstroPy] astropy table to numpy array

[Derek Homeier]

On 16.05.2014, at 1:43AM, Perry Greenfield <stsci.perry at gmail.com> wrote:

>> I’m trying to convert an astropy.table.table.Table object (named out) to a numpy array, but it will convert each row to a tuple.
>> Also the type for the array is strange. I copy a snippet of what I’m trying to do below: 
>> 
>> np.array(out)
>> Out[77]:
>> array([(1, 9642.374, 41.886, 1.109, 2.45, 0.718),
>>     (2, 1430.236, 57.642, 1.277, 2.33, 0.51),
>>     (3, 638.677, 77.257, 1.254, 5.18, 0.784), ...,
>>     (6762, 1211.064, 937.82, 907.38, 1.81, 0.25),
>>     (6763, 1090.107, 911.179, 906.314, 2.68, 0.353),
>>     (6764, 2348.992, 333.94, 899.355, 3.67, 0.591)], 
>>    dtype=[('NUMBER', '<i8'), ('FLUX_APER', '<f8'), ('X_IMAGE', '<f8'), ('Y_IMAGE', '<f8'), ('FWHM_IMAGE', '<f8'), ('ELLIPTICITY', '<f8')])
>> 
>> 
>> Does anyone know how to get a 2D numpy array of all floats from an astropy table? 
> 
> Actually it is a numpy array, just not a simple one. It's a array of records or structs.
> 
> You'll first have to realize that nothing  can do that generally, particularly if some of the columns of the table aren't floats, and particularly if they aren't numbers at all. In this case they aren't all floats, but at least they are numbers.
> 
> You could do it the safest way by inserting each column into the appropriately sized numpy array one column at a time in a loop (what I would recommend unless someone knows a better solution). One can essentially equivalence all but the first column to a 2d float array, but that is a bit tricky and unless you need the performance, I wouldn't recommend it.

This should do it in one go (no idea if it's memory-efficient though):

out = np.array([input[c] for c in input.columns if input[c].dtype==np.dtype('>f8')])

(you can cut the … if input[c].dtype part if you want to convert your integer columns to float).

Does anyone know the difference between columns and colnames BTW?
I would have expected input.columns to directly give me 
[input[c] for c in input.colnames]
in the above example, but both seem to return just the names.

Cheers,
						Derek