[AstroPy] Question re. astropy.table

Brian York york at stsci.edu
Thu Feb 25 14:56:11 EST 2016


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

  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

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

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