SelectStars.py

import numpy as np
import pandas as pd
import glob

varcat = pd.read_table('varcat.txt', comment='#', header=0, skip_blank_lines=True, usecols=[0,1,2], dtype={'ID': np.str, 'Campaign': np.str})
all_bad = varcat[(varcat.Class != 'Noise ') & (varcat.Class != 'OTHPER')].ID.values
print 'No. of variables & EBs:', len(all_bad)
np.savetxt('k2/k2mdwarfs/vars.ls', all_bad, fmt='%9s')

camps = glob.glob('exofop*csv')
for camp in camps:
	all_stars = pd.read_csv(camp, comment='\\', header=0, dtype={'EPIC ID': np.str})
	planets = all_stars[all_stars['Poss_pc'] == 'Y']
	planets = planets['EPIC ID'].values
	print 'No. of planet hosts:', len(planets)
	all_bad = np.append(all_bad, planets)
print len(all_bad)

targlist = glob.glob('k2/K2Campaign*targets.csv')
mdwarf_props = 'GO3001|GO3011|GO3013|GO3016|GO3031|GO3034|GO3045|GO3069|GO3073|GO3094|GO3106|GO3107|GO3114'
mdwarfs = np.array([])
for camp in targlist:
	data = pd.read_csv(camp, header=0, index_col=False, usecols=[0,4], na_values='null', dtype={'EPIC ID': np.str, 'Investigation IDs': np.str})

	md = data[data['Investigation IDs'].str.contains(mdwarf_props)]
	good_md = md.loc[~md['EPIC ID'].isin(all_bad)]
	good_md = good_md['EPIC ID'].values.astype('str')

	mdwarfs = np.append(mdwarfs, good_md)

np.savetxt('k2/k2mdwarfs/mdwarfs.ls', mdwarfs, fmt='%9s')
np.savetxt('k2/k2mdwarfs/planets.ls', planets, fmt='%9s')