def plot_phot_compare():
""" make a comparison plot showing aperture and psf photometry """
from matplotlib import pyplot as pl
import sncosmo
import numpy as np
from .import _ALPHA2FILTER
datadir='/Users/rodney/Dropbox/Papers/snTomas/LCFIT/'
ap = sncosmo.read_snana_ascii( datadir+'HST_FFSN_tomas.snana_apphot.dat')
psf = sncosmo.read_snana_ascii(datadir+'HST_FFSN_tomas.snana_psfphot.dat')
apdat = ap[1]['OBS']
psfdat = psf[1]['OBS']
fig = pl.gcf()
pl.clf()
iax = 0
for band, color in zip( ['Y','J','N','H'],
['c','r','g','m'] ):
iax += 1
fig.add_subplot( 2, 2, iax )
for dat,marker,c in zip( [apdat,psfdat], ['o','D'], ['k',color]):
iband = np.where( dat['FLT']==band )
pl.errorbar( dat['MJD'][iband], dat['FLUXCAL'][iband],
dat['FLUXCALERR'][iband],
marker=marker, color=c, ms=10, alpha=0.5 )
ax = pl.gca()
pl.text(0.95,0.95,_ALPHA2FILTER[band],color=c,ha='right',va='top',transform=ax.transAxes)
pl.draw()
def plot_lightcurve_snana():
from matplotlib import pyplot as pl
import sncosmo
import numpy as np
from .import _ALPHA2FILTER
datadir='/Users/rodney/Dropbox/Papers/snTomas/LCFIT/'
dat = sncosmo.read_snana_ascii( datadir+'HST_FFSN_tomas.snana.dat')
obsdat = dat[1]['OBS']
fig = pl.gcf()
pl.clf()
iax = 0
marker='o'
for band, color in zip( ['B','V','I','Y','J','N','H'],
['c','g','r','c','g','r','k'] ):
iax += 1
fig.add_subplot( 2, 4, iax )
iband = np.where( obsdat['FLT']==band )
pl.errorbar( obsdat['MJD'][iband], obsdat['FLUXCAL'][iband],
obsdat['FLUXCALERR'][iband],
marker=marker, color=color, ms=10, alpha=0.5 )
ax = pl.gca()
pl.text(0.95,0.95,_ALPHA2FILTER[band],color=color,ha='right',va='top',transform=ax.transAxes)
pl.draw()
def read_snana_datafile(datafile):
""" Read in a SN data table that was written in the old
SNANA format, modify it, and return an astropy Table object
that can be handled by sncosmo functions.
"""
metadata, datatable = sncosmo.read_snana_ascii(datafile,
default_tablename='OBS')
sntable = standardize_snana_data(datatable['OBS'])
return sntable
def test_read_snana_ascii():
fname = join(dirname(__file__), "data", "snana_ascii_example.dat")
meta, tables = sncosmo.read_snana_ascii(fname, default_tablename="OBS")
# only 1 table
assert len(tables) == 1
data = tables["OBS"]
assert len(data) == 4 # 4 rows.
assert len(data.colnames) == 13 # 13 columns.
def test_read_snana_ascii():
fname = join(dirname(__file__), "data", "snana_ascii_example.dat")
meta, tables = sncosmo.read_snana_ascii(fname, default_tablename="OBS")
# test a few different types of metadata
assert meta['SURVEY'] == 'DES'
assert meta['FAKE'] == 0
assert_allclose(meta['REDSHIFT_HELIO'], 0.3614)
# only 1 table
assert len(tables) == 1
data = tables["OBS"]
assert len(data) == 4 # 4 rows.
assert len(data.colnames) == 13 # 13 columns.
def test_read_snana_ascii():
fname = join(dirname(__file__), "data", "snana_ascii_example.dat")
meta, tables = sncosmo.read_snana_ascii(fname, default_tablename="OBS")
# test a few different types of metadata
assert meta['SURVEY'] == 'DES'
assert meta['FAKE'] == 0
assert_allclose(meta['REDSHIFT_HELIO'], 0.3614)
# only 1 table
assert len(tables) == 1
data = tables["OBS"]
assert len(data) == 4 # 4 rows.
assert len(data.colnames) == 13 # 13 columns.
def snana_to_sncosmo( snanafile='HST_FFSN_tomas_snana_ab.dat') :
""" make the SN Tomas light curve fit figure"""
import sncosmo
import numpy as np
from . import _ALPHA2FILTER
snanadat = sncosmo.read_snana_ascii(snanafile)
mjd = snanadat[1]['OBS']['MJD']
band = snanadat[1]['OBS']['FLT']
fluxcal = snanadat[1]['OBS']['FLUXCAL']
fluxcalerr = snanadat[1]['OBS']['FLUXCALERR']
mag = snanadat[1]['OBS']['MAG']
magerr = snanadat[1]['OBS']['MAGERR']
zptab = snanadat[1]['OBS']['ZPTAB']
flux = fluxcal * 10**(-0.4*(27.5-zptab))
fluxerr = fluxcalerr * 10**(-0.4*(27.5-zptab))
magab = -2.5*np.log10( flux ) + zptab
magaberr = 1.0857 * fluxerr / flux
filter = [ _ALPHA2FILTER[b] for b in band ]
fout = open('HST_FFSN_tomas.sncosmo.dat','w')
print >> fout, "# mjd filter flux fluxerr mag magerr zpt magsys"
for i in range(len(mjd)) :
if flux[i]>0 :
print >> fout, "%8.2f %6s %8.3f %8.3f %8.2f %6.2f %7.3f AB"%(
mjd[i], filter[i], flux[i], fluxerr[i], magab[i], magaberr[i], zptab[i]
)
else :
print >> fout, "%8.2f %6s %8.3f %8.3f %8.2f %6.2f %7.3f AB"%(
mjd[i], filter[i], flux[i], fluxerr[i],
-2.5*np.log10(3*fluxerr[i]) + zptab[i], -9.0, zptab[i]
)
fout.close()
def convert_light_curve_file( ):
""" read in the SNANA-style light curve file (from D.Scolnic)
and convert it into normal fluxes (not SNANA fluxcal) and
AB and Vega mags
:return:
"""
import sncosmo
import numpy as np
from .import _ALPHA2FILTER
from hstphot import hstzpt
from astropy import table
from astropy.utils import OrderedDict
import sys
import os
thisfile = sys.argv[0]
if 'ipython' in thisfile :
thisfile = __file__
thisdir = os.path.dirname( os.path.abspath(thisfile))
datadir = os.path.join(thisdir,'data/')
dat = sncosmo.read_snana_ascii( datadir+'HST_FFSN_tomas.snana.dat')
obsdat = dat[1]['OBS']
filtname= np.array([_ALPHA2FILTER[obsdat['FLT'][i]].lower()
for i in range(len(obsdat))])
iIR = np.array([ i for i in range(len(obsdat))
if filtname[i].startswith('f1') ] )
iACS = np.array([ i for i in range(len(obsdat))
if not filtname[i].startswith('f1') ] )
zpt = np.ones(len(obsdat))
zpt[iIR] = hstzpt.getzptWFC3IR(filtname[iIR],'AB')
zpt[iACS] = hstzpt.getzptACS(filtname[iACS],'AB')
zptsys = ['AB' for i in range(len(obsdat))]
zptVega = np.ones(len(obsdat))
zptVega[iIR] = hstzpt.getzptWFC3IR(filtname[iIR],'Vega')
zptVega[iACS] = hstzpt.getzptACS(filtname[iACS],'Vega')
fAB = obsdat['FLUXCAL'] * 10**(0.4*(27.5-zpt))
ferrAB = obsdat['FLUXCALERR'] * 10**(0.4*(27.5-zpt))
mAB = np.where( fAB>0, -2.5*np.log10(fAB)+zpt,
-2.5*np.log10(3*np.abs(ferrAB))+zpt,)
merr = np.where( fAB>0, 1.0857*(ferrAB/fAB), -9*np.ones(len(fAB)))
fcalVega = obsdat['FLUXCAL'] * 10**(0.4*(zpt-zptVega))
fcalerrVega = obsdat['FLUXCALERR'] * 10**(0.4*(zpt-zptVega))
mVega = np.where( fcalVega>0, -2.5*np.log10(fcalVega)+27.5,
-2.5*np.log10(3*np.abs(fcalerrVega))+27.5,)
data=OrderedDict(
[ ['mjd',obsdat['MJD']],
['filter',filtname],
['flux',fAB],
['fluxerr',ferrAB],
['mag',mAB],
['magerr',merr],
['zpt',zpt],
['zptsys',zptsys],
['fluxcalVega',fcalVega],
['fluxcalerrVega',fcalerrVega],
['magVega',mVega],
['zptVega',zptVega],
])
outdat = table.Table(data=data)
outdat['mjd'].format='%.1f'
for colname in ['flux','fluxerr','fluxcalVega','fluxcalerrVega']:
outdat[colname].format='%8.5f'
for colname in ['mag','magerr','magVega']:
outdat[colname].format='%8.3f'
outdat.write( datadir+'HST_FFSN_tomas.dat',
format='ascii.fixed_width')
# format='ascii.commented_header')
return(outdat)
