[AstroPy] Question re. astropy.table
Brian York
york at stsci.edu
Thu Feb 25 14:56:11 EST 2016
Greetings,
I have a number of situations where I'm reading data from a (rather large)
table in order to add that data into a separate numpy array (sample code
below):
t = Table.read(name, format)
x_locations = t['X']
y_locations = t['Y']
fluxes = t['FLUX']
image_data[y_locations, x_locations] += fluxes
Now, this works well for relatively short tables (~100,000 rows), but
sometimes I end up with considerably longer tables (~5-10 million rows),
and there tends to be a fairly high memory overhead in loading the table
in those circumstances (especially given that the table has more than just
the three columns -- the above code is an example, not exactly what I'm
doing).
Is there any way to load a table N rows at a time? Or some other way to
reduce the memory footprint?
Thank you,
-Brian York
More information about the AstroPy
mailing list