yazko / sigplan-carbon-analysis Goto Github PK

Hi!

What do I have to do to get countries like New Zealand and South Korea to work? United Kingdom seems fine, and so are the United States. Thank you! :)

Example entry:

Looking for GPS coordinates of Seoul
'NoneType' object has no attribute 'alpha_2'
WARNING: in the list of participants, entry Data: (20170105,Seoul,None,South Korea,GECCO,2017) cannot be processed and has been ignored

The script currently outputs csv files of data.
We (as in Crista really) have been manually producing (via Excel usually) our visual representation of those.
Ideally, each analysis / the relevant analyses would come with both the csv file, and a default visualization generated via panda/mathplotlib, or something higher level such as seaborn.
A first easy step could also be to add some meta-data (such as captions) to the output files and automate the generation of their TeX table via csvautotabular.

The set of years and conferences analyzed should be computed from source, it's currently hard-wired in 'parameters.py'.
We should retain the option to restrict the analysis to a subset, but work with all the ones provided by the conference file by default.

The cache is currently case-sensitive, leading to superfluous cache-misses. Adding a bit of normalization would be an easy way to improve the situation when processing new data that followed different conventions when retrieved.

North America is big enough and has sufficiently many researchers that working at a finer grained level than just "North America" could be beneficial.

It should essentially reduce to hard coding a list of US states and Canadian Counties that we judge as being "west".

(Following @ineol's suggesting)

I still debug with prints everywhere. I started sprinkling a bit of logging in the script, it should be generalized.

Thank you for this great work!

I think I have found a small mistake in the draft. In section 3.2 [1], it is written that the conference with the lowest average per-participant carbon emission is PLDI'18 in Philadelphia with 0.9, but ICFP'12 and ICFP'14 are lower at 0.88.

(this comes from the draft at Yannick's web page)

[1] https://github.com/YaZko/acm-climate/blob/master/paper/sigplan_climate/footprint.tex#L108