def read_phot_files(file):
parts = re.split('\.',file)
if len(parts) == 2:
extension = '.%s' %(parts[1])
elif len(parts) == 3:
extension = '.%s.%s' %(parts[1],parts[2])
if extension == '.prob':
#if re.search('and09',file):
# pdb.set_trace()
# ID X Y RA DEC D D_err M M_err T T_err Chi Sharp Flag Stell r l b EBmV EMmT EMmD A_m gprob gerr xerr serr
ra, dec, gprob = np.genfromtxt(file, usecols = (3,4,22), unpack=True)
good = (gprob > 0.5) & (np.isfinite(gprob))
return ra[good], dec[good]
elif (extension == '.RICNgood') | (extension == '.RICNradec'):
rh,rm,rs, dh,dm,ds = np.genfromtxt(file, usecols = (1,2,3,4,5,6), unpack=True)
ra_hms = ['%02d:%02d:%5.2f' %(r1,r2,r3) for r1,r2,r3 in zip(rh,rm,rs)]
dec_hms = ['%02d:%02d:%5.2f' %(d1,d2,d3) for d1,d2,d3 in zip(dh,dm,ds)]
ra = np.array([hms2deg(r,d)[0] for r,d in zip(ra_hms, dec_hms)])
dec = np.array([hms2deg(r,d)[1] for r,d in zip(ra_hms, dec_hms)])
return ra, dec
elif extension == '.selVI':
ra,dec = np.genfromtxt(file, usecols=(1,2), unpack=True)
return ra, dec
elif extension == '.vimag.fits':
hdu = fits.open(file)
data = hdu[1].data
return data.RA1, data.DEC1
elif extension == '.rawcalib':
ra_hms, dec_hms = np.genfromtxt(file, usecols = (1,2), dtype=str, unpack=True)
ra = np.array([hms2deg(r,d)[0] for r,d in zip(ra_hms, dec_hms)])
dec = np.array([hms2deg(r,d)[1] for r,d in zip(ra_hms, dec_hms)])
return ra, dec
else:
raise AttributeError('Unrecognized extension')
def matchDUSTiNGS(type, ra, dec, masks):
if type == 'dsph':
table = np.genfromtxt('/Users/khamren/M31_Research/splash_data/DUSTiNGS/dsph_goodcat.tsv', delimiter=';', dtype=str, filling_values='9999')
elif type == 'de':
table = np.genfromtxt('/Users/khamren/M31_Research/splash_data/DUSTiNGS/ngc_goodcat.tsv', delimiter=';', dtype=str, filling_values='9999')
else:
raise AttributeError('Input type should be dsph or de')
dust_fields = np.array([convert_to_mask(m) for m in table[:,0]])
dust_ra = np.array([hms2deg(':'.join(r.strip().split()),':'.join(d.strip().split()))[0]
for r,d in zip(table[:,1],table[:,2])])
dust_dec = np.array([hms2deg(':'.join(r.strip().split()),':'.join(d.strip().split()))[1]
for r,d in zip(table[:,1],table[:,2])])
n = len(ra)
m36 = np.empty(n)
em36 = np.empty(n)
m45 = np.empty(n)
em45 = np.empty(n)
splash_fields = np.array([re.split('_',m)[0].lower() for m in masks])
for i,r,d,m in zip(range(n),ra, dec,splash_fields):
if m == 'd7bi':
m = 'd7'
dist = np.array([3600*np.sqrt(((r-rv)*cosdg(d))**2 + (d-dv)**2)
for rv, dv in zip(dust_ra[dust_fields == m], dust_dec[dust_fields == m])])
try:
if (len(dist) == 0) or (min(dist) > 0.5):
m36[i] = np.nan
em36[i] = np.nan
m45[i] = np.nan
em45[i] = np.nan
else:
j = np.argwhere(dist == min(dist))[0][0]
try:
m36[i] =(table[j,3].astype(float))
em36[i] =(table[j,4].astype(float))
m45[i] =(table[j,9].astype(float))
em45[i] =(table[j,10].astype(float))
except:
try:
m36[i] =(table[j,5].astype(float))
em36[i] =(table[j,6].astype(float))
m45[i] =(table[j,11].astype(float))
em45[i] =(table[j,12].astype(float))
except:
try:
m36[i] =(table[j,7].astype(float))
em36[i] =(table[j,8].astype(float))
m45[i] =(table[j,13].astype(float))
em45[i] =(table[j,14].astype(float))
except:
m36[i] = np.nan
em36[i] = np.nan
m45[i] = np.nan
em45[i] = np.nan
except:
pdb.set_trace()
return np.array(m36), np.array(em36), np.array(m45), np.array(em45)
