def test_get_ebv_from_map():
"""Try get_ebv_from_map."""
mapdir = join(dirname(__file__), "data", "dust_subsection")
# coordinate that is in the dust subsection map
coords = (204., -30.)
coords2 = SkyCoord(204.0, -30.0, frame='icrs', unit='deg')
# value from http://irsa.ipac.caltech.edu/applications/DUST/
# with input "204.0 -30.0 J2000"
true_ebv = 0.0477
# Use interpolate=False to match IRSA value
ebv = sncosmo.get_ebv_from_map(coords, mapdir=mapdir, interpolate=False)
assert_allclose(ebv, true_ebv, rtol=0.01)
ebv2 = sncosmo.get_ebv_from_map(coords2, mapdir=mapdir, interpolate=False)
assert_allclose(ebv2, true_ebv, rtol=0.01)
def getTargetMag(self, dataSlice, filter):
# fainten the extragalactic magnitude due to Galactic dust
dec=numpy.maximum(dataSlice['fieldDec'][0],-numpy.pi/2)
co = coord.ICRS(ra=dataSlice['fieldRA'][0], dec=dec, unit=(u.rad, u.rad))
ebv=sncosmo.get_ebv_from_map(co, mapdir='../data',cache=True)
#np=ephem.Equatorial(dataSlice['fieldRA'][0],dataSlice['fieldDec'][0])
#g=ephem.Galactic(np)
#ebv=map.generateEbv(g.lon,g.lat)
self.ccm.set(ebv=ebv)
av=-2.5*numpy.log10(self.ccm.propagate(numpy.array([self.filterinfo[filter]['wave']*10]),numpy.array([1])))
# print co, ccm.parameters, av
# return self.filterinfo[filter]['targetMag']+av
return self.filterinfo[filter]['targetMag']+av
def getTargetMag(self, dataSlice, filter):
# fainten the extragalactic magnitude due to Galactic dust
dec = numpy.maximum(dataSlice['fieldDec'][0], -numpy.pi / 2)
co = coord.ICRS(ra=dataSlice['fieldRA'][0],
dec=dec,
unit=(u.rad, u.rad))
ebv = sncosmo.get_ebv_from_map(co, mapdir='../data', cache=True)
#np=ephem.Equatorial(dataSlice['fieldRA'][0],dataSlice['fieldDec'][0])
#g=ephem.Galactic(np)
#ebv=map.generateEbv(g.lon,g.lat)
self.ccm.set(ebv=ebv)
av = -2.5 * numpy.log10(
self.ccm.propagate(
numpy.array([self.filterinfo[filter]['wave'] * 10]),
numpy.array([1])))
# print co, ccm.parameters, av
# return self.filterinfo[filter]['targetMag']+av
return self.filterinfo[filter]['targetMag'] + av
def setUp(self):
"""
Setup the objects used in this test suite class. snObject objs are
required to have a SN sed namely ra, dec, and SALT model parameters
x0, x1,c and the redshift of the supernova z
Store objects:
# NO MW Extinction objects from catsim and SNCosmo
self.SNnoMW : SN with said parameters, unexincted in MW
self.SNCosmo_nomw :
# objects with MW extinction
self.SNmw : SN with said parameters, exincted in MW
self.SNCosmo_mw :
"""
ra = 204.
dec = -30.
mjdobs = 571203.
# Setup SN object of different kinds we want to check
# In order to compare SN light curves between SNCosmo and Catsim
# we need to set them up separately
# Check case with no MW extinction
SNnoMW = SNObject()
SNnoMW.set(x0=1.847e-6, x1=0.1, c=0., z=0.2)
SNnoMW.set_MWebv(0.)
self.SNnoMW = SNnoMW
dust = sncosmo.OD94Dust()
SNCosmo_nomw = sncosmo.Model(source='salt2-extended',
effects=[dust, dust],
effect_names=['host', 'mw'],
effect_frames=['rest', 'obs'])
SNCosmo_nomw.set(x0=1.847e-6, x1=0.1, c=0., z=0.2)
SNCosmo_nomw.set(mwebv=0.)
self.SNCosmo_nomw = SNCosmo_nomw
### SNCosmo Model object with MW extinction. Store in self.SNCosmo_mw
# Object of SNObject class with MW extinction
SN = SNObject(ra, dec)
SN.set(x0=1.847e-6, x1=0.1, c=0., z=0.2)
SNnoMW.set_MWebv(0.)
self.SNmw = SN
SNCosmo = sncosmo.Model(source='salt2-extended',
effects=[dust, dust],
effect_names=['host', 'mw'],
effect_frames=['rest', 'obs'])
SNCosmo.set(x0=1.847e-6, x1=0.1, c=0., z=0.2)
skycoords = SkyCoord(ra, dec, unit='deg')
t_mwebv = sncosmo.get_ebv_from_map(skycoords,
mapdir=map_dir,
interpolate=False)
# Now Set the value of mwebv
SNCosmo.set(mwebv=t_mwebv)
self.SNCosmo_mw = SNCosmo
CCMdust = sncosmo.CCM89Dust()
SNCosmo_float = sncosmo.Model(source='salt2-extended',
effects=[CCMdust, CCMdust],
effect_names=['host', 'mw'],
effect_frames=['rest', 'obs'])
SNCosmo_float.set(x0=1.847e-6, x1=0.1, c=0., z=0.2)
SNCosmo_float.set(mwebv=t_mwebv)
self.SNCosmo_float = SNCosmo_float
# Load LSST sofware bandpass objects for magnitude calculation
self.bandPassList = ['u', 'g', 'r', 'i', 'z', 'y']
pbase = PhotometryBase()
pbase.loadBandpassesFromFiles(self.bandPassList)
pbase.setupPhiArray_dict()
self.pbase = pbase
self.lsstbands = pbase.bandpassDict
self.times = numpy.arange(-20., 50., 1.0)
# Load SNCosmo bandpass objects for comparison test
thisshouldbeNone = tu.getlsstbandpassobjs(self.bandPassList,
loadcatsim=False,
plot=False)
self.sncosmobands = ['LSST' + band for band in self.bandPassList]
# Standardize data
data = standardize_data(data)
# Get min and max data times
dtmin = np.min(data['time'])
dtmax = np.max(data['time'])
# Cut LC based on S/N ratio
mask = data['flux'] / data['fluxerr'] > 5.
if (len(np.unique(data['band'][mask])) < 2):
print "Fails SNR cut"
ncut += 1
continue
# get mwebv
mwebv = sncosmo.get_ebv_from_map((meta['ra'], meta['dec']),
mapdir='/home/kyle/Data/dust')
# Evaluate evidence for each model
for name, m in models.iteritems():
# Set t0 bounds (its OK that we keep overwriting this dict)
m['model'].set(z=0.)
t0off = m['model'].get('t0') - m['model'].mintime() # t0 offset from
# mintime
t0min = dtmin - 30. + t0off
t0max = dtmax - 30. + t0off
m['bounds']['t0'] = (t0min, t0max)
# Set mwebv of model.
m['model'].set(mwebv=mwebv)
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
