def read_simlib(libfile):
'''function to read snana like simlib file'''
if bench:
print "Reading the simlib file. This might take a few minutes..."
meta, obs = sncosmo.read_snana_simlib(libfile)
for id in obs.keys():
#obs[id].rename_column('FLT', 'band')
obs[id]['band'] = ['desg'] * len(obs[id]['FLT'])
for ii, val in enumerate(obs[id]['FLT']):
if val == 'g': obs[id]['band'][ii] = 'desg'
if val == 'r': obs[id]['band'][ii] = 'desr'
if val == 'i': obs[id]['band'][ii] = 'desi'
if val == 'z': obs[id]['band'][ii] = 'desz'
obs[id].rename_column('MJD', 'time')
obs[id].rename_column('CCD_GAIN', 'gain')
obs[id].rename_column('SKYSIG', 'skynoise')
obs[id].rename_column('ZPTAVG', 'zp')
obs[id]['zpsys'] = ['ab'] * len(obs[id]['gain'])
return meta, obs
def test_read_snana_simlib_noend():
fname = join(dirname(__file__), "data", "snana_simlib_example_noend.dat")
meta, obs_sets = sncosmo.read_snana_simlib(fname)
assert len(obs_sets) == 2
def test_read_snana_simlib_noend():
fname = join(dirname(__file__), "data", "snana_simlib_example_noend.dat")
meta, obs_sets = sncosmo.read_snana_simlib(fname)
assert len(obs_sets) == 2
particular strategy.
"""
simlibfilename = '/home/kushner/src/lsstpipeline/cache/RBtest_opsim.simlib'
# simlibfilename = 'cache/RBtest_opsim.simlib'
# set up bandpasses for LSST
sl.getlsstbandpassobjs(plot=False)
def prefixbandname(prefix, obstable):
_bb = np.array(obstable['FLT'])
_lsst = np.array([prefix]*len(_bb), dtype='S6')
return map ( ''.join, zip(_lsst,_bb))
#Read the simlib file, get the libids which index different fields
meta, obstables = sncosmo.read_snana_simlib(simlibfilename)
print "META\n"
print meta
print "\n\n OBSTABLE LIBIDS \n"
print obstables.keys()
#Choose a field: for example the one indexed by 519
minmjd = obstables[519]['MJD'].min()
maxmjd = obstables[519]['MJD'].max()
obstable = obstables[519]
print "Number of observations in obstable: ", len(obstable)
print "min and max MJD in the set: ", minmjd, maxmjd
#Set SNCosmo model and set its t0 aritificially to values I know are in the above table
model = sncosmo.Model(source='salt2-extended')
params = []
def test_read_snana_simlib_invalid():
"""Test that we fails on simlib files with bad co-add columns."""
fname = join(dirname(__file__), "data", "snana_simlib_example_invalid.dat")
with pytest.raises(ValueError) as e_info:
_ = sncosmo.read_snana_simlib(fname)
def test_read_snana_simlib_coadd():
"""Test when co-added `ID*NEXPOSE` key is used."""
fname = join(dirname(__file__), "data", "snana_simlib_example_coadd.dat")
meta, obs_sets = sncosmo.read_snana_simlib(fname)
assert "NEXPOSE" in obs_sets[0].colnames
def test_read_snana_simlib_doc():
"""Test when DOCANA header is present in simlib"""
fname = join(dirname(__file__), "data", "snana_simlib_example_doc.dat")
meta, _ = sncosmo.read_snana_simlib(fname)
assert "DOCUMENTATION" in meta
lw=2,
bins=zbins)
plt.xlabel('Redshift')
plt.ylabel('Normed PDF')
plt.legend(loc='upper left', frameon=False)
plt.title('Redshift Distribution Before Cuts')
#plt.hist(testz,normed=True)
plt.show()
##PART 2: READING IN THE SIMLIB
##---------------------------------
print 'READING THE SNANA SIMLIB. THIS MIGHT TAKE A FEW MINUTES - BE PATIENT!'
snana_simlib_file = 'DES_DIFFIMG.SIMLIB'
snana_simlib_meta, snana_simlib_obs_sets = sncosmo.read_snana_simlib(
snana_simlib_file)
#NOTE: THE SIMLIB INDEX STARTS AT 1, NOT 0#
#print snana_simlib_obs_sets.keys()
#print snana_simlib_obs_sets[1].meta
#print snana_simlib_obs_sets[1].colnames
##PART 3: GENERATING THE COLOR
## AND STRETCH DISTRIBUTIONS
##---------------------------------
print 'DRAWING THE COLOR AND STRETCH'
## LET'S ASSUME WE JUST WANT TO DRAW COLOR AND STRETCH
## FROM INDEPENDENT NORMAL DISTRIBUTIONS
simxmean, simxscale = 0.5, 1.2
simcmean, simcscale = -0.05, 0.15
def simulate_simlib(simlibfile, snmodelsource, outfile="LC/simulatedlc.dat", restrict=10):
"""
Simulate SN based on the simlibfile using SNCosmo SALT models
Parameters
----------
simlibfile :
snmodelsource:
outfile:
Returns
-------
"""
from astropy.units import Unit
from astropy.coordinates import SkyCoord
# read the simlibfile into obstables
meta, obstables = sncosmo.read_snana_simlib(simlibfilename)
# set the SNCosmo model source
dustmaproot = os.getenv("SIMS_DUSTMAPS_DIR")
map_dir = os.path.join(dustmaproot, "DustMaps")
dust = sncosmo.CCM89Dust()
model = Model(
source=snmodelsource, effects=[dust, dust], effect_frames=["rest", "obs"], effect_names=["host", "mw"]
)
maxSNperField = restrict
# Different fields in SIMLIB are indexed by libids
libids = obstables.keys()
lcs = []
for libid in libids:
# Get the obstable corresponding to each field
obstable = obstables[libid]
manipulateObsTable(obstable)
# Need Area from PixSize
ra = obstable.meta["RA"]
dec = obstable.meta["DECL"]
area = obstable.meta["PIXSIZE"]
maxmjd = obstable["time"].max()
minmjd = obstable["time"].min()
rangemjd = maxmjd - minmjd
skycoords = SkyCoord(ra, dec, unit="deg")
t_mwebv = sncosmo.get_ebv_from_map(skycoords, mapdir=map_dir, interpolate=False)
model.set(mwebv=t_mwebv)
params = []
# col = Table.Column(obstable['SEARCH'].size*['ab'], name='zpsys')
# obstable['FLT'].name = 'band'
# obstable['MJD'].name = 'time'
# obstable['ZPTAVG'].name = 'zp'
# obstable['CCD_GAIN'].name = 'gain'
# obstable['SKYSIG'].name = 'skynoise'
# obstable.add_column(col)
redshifts = list(sncosmo.zdist(0.0, 1.2, ratefunc=cosmoRate, time=rangemjd, area=area))
print "num SN generated ", len(redshifts)
for i, z in enumerate(redshifts):
mabs = normal(-19.3, 0.3)
model.set(z=z)
model.set_source_peakabsmag(mabs, "bessellb", "ab")
x0 = model.get("x0")
# RB: really should not be min, max but done like in catalogs
p = {"z": z, "t0": uniform(minmjd, maxmjd), "x0": x0, "x1": normal(0.0, 1.0), "c": normal(0.0, 0.1)}
params.append(p)
if maxSNperField is not None:
if i == maxSNperField:
break
print "realizing SN"
lcslib = sncosmo.realize_lcs(obstable, model, params, trim_observations=True)
lcs.append(lcslib)
# alllcsintables = vstack(lcslib)
# print alllcsintables[0]
# print alllcsintables[MJD].size
# write light curves to disk
for i, field in enumerate(lcs):
for snid, lc in enumerate(field):
sncosmo.write_lc(lc, fname=outfile + "_" + str(i) + "_" + str(snid) + ".dat", format="ascii")
return lcs
