Dear Nikos, Can you give us a bit more context? What is it you want to achieve? How are you using r.stats and what is it you want to do with the output?
Personally, I am not too familiar with performance implications of NumPy vs. plain Python, but rather use NumPy for convenience in matrix/table operations (avoiding pandas)... Cheers Stefan -----Original Message----- From: Nikos Alexandris <[email protected]> Sent: onsdag 22. august 2018 17:57 To: Stefan Blumentrath <[email protected]> Cc: GRASS-GIS development mailing list <[email protected]> Subject: Re: [GRASS-dev] Parsing output of r.category which includes labels Stefan, a somewhat irrelevant question to the original subject: do you think the NumPy way is worth to collage a series of `r.stats` outputs? Imagine administrative boundaries and one `r.stats` call for each. They may be tenths, or hundreds, or thousands as the script is meant to cover European wide extents. Or should I just work this out using native Python? Thank you for any thoughts, Nikos * Stefan Blumentrath <[email protected]> [2018-08-20 10:48:34 +0000]: >Hi Nikos, > >You could use numpy and genfromtxt() to parse the output string... >genfromtxt() requires an StringIO object (or file) and StringIO (from io) >requires unicode()... > >So you could do: > >from io import StringIO >import numpy as np >output = >np.genfromtxt(StringIO(unicode(grass.read_command('r.category', >map=base))) , delimiter='\t', dtype=None, names=['cat', 'label']) > >That causes however some overhead [1]. So if it makes sense depends on what >you want to do with the data in the further processing chain... > >Cheers >Stefan > >1: https://docs.scipy.org/doc/numpy/user/basics.io.genfromtxt.html [rest deleted] _______________________________________________ grass-dev mailing list [email protected] https://lists.osgeo.org/mailman/listinfo/grass-dev
