def get_phosimVars(self):
"""
Obtain variables sedFilepath to be used to obtain unique filenames
for each SED for phoSim and MagNorm which is also used. Note that aside
from acting as a getter, this also writes spectra to
`self.sn_sedfile_prefix`snid_mjd_band.dat for each observation of
interest
"""
# construct the unique filename
# method: snid_mjd(to 4 places of decimal)_bandpassname
mjd = "_{:0.4f}_".format(self.mjdobs)
mjd += self.obs_metadata.bandpass + '.dat'
fnames = np.array([
self.sn_sedfile_prefix + str(int(elem)) + mjd if isinstance(
elem, numbers.Number) else self.sn_sedfile_prefix + str(elem) +
mjd for elem in self.column_by_name('snid')
],
dtype='str')
c, x1, x0, t0, z = self.column_by_name('c'),\
self.column_by_name('x1'),\
self.column_by_name('x0'),\
self.column_by_name('t0'),\
self.column_by_name('redshift')
bp = Bandpass()
bp.imsimBandpass()
magNorms = np.zeros(len(fnames))
snobject = SNObject()
snobject.rectifySED = True
for i in range(len(self.column_by_name('snid'))):
# if t0 is nan, this was set by the catalog for dim SN, or SN
# outside redshift range, We will not provide a SED file for these
if np.isnan(t0[i]):
magNorms[i] = np.nan
fnames[i] = None
else:
snobject.set(c=c[i], x1=x1[i], x0=x0[i], t0=t0[i], z=z[i])
if snobject.modelOutSideTemporalRange == 'zero':
if self.mjdobs > snobject.maxtime(
) or self.mjdobs < snobject.mintime():
magNorms[i] = np.nan
fnames[i] = None
# SED in rest frame
sed = snobject.SNObjectSourceSED(time=self.mjdobs)
try:
magNorms[i] = sed.calcMag(bandpass=bp)
except:
# sed.flambda = 1.0e-20
magNorms[i] = 1000. # sed.calcMag(bandpass=bp)
if self.writeSedFile:
sed.writeSED(fnames[i])
return (fnames, magNorms)
def get_phosimVars(self):
"""
Obtain variables sedFilepath to be used to obtain unique filenames
for each SED for phoSim and MagNorm which is also used. Note that aside
from acting as a getter, this also writes spectra to
`self.sn_sedfile_prefix`snid_mjd_band.dat for each observation of
interest
"""
# construct the unique filename
# method: snid_mjd(to 4 places of decimal)_bandpassname
mjd = "_{:0.4f}_".format(self.mjdobs)
mjd += self.obs_metadata.bandpass + '.dat'
fnames = np.array([self.sn_sedfile_prefix + str(int(elem)) + mjd
if isinstance(elem, numbers.Number) else
self.sn_sedfile_prefix + str(elem) + mjd
for elem in self.column_by_name('snid')], dtype='str')
c, x1, x0, t0, z = self.column_by_name('c'),\
self.column_by_name('x1'),\
self.column_by_name('x0'),\
self.column_by_name('t0'),\
self.column_by_name('redshift')
bp = Bandpass()
bp.imsimBandpass()
magNorms = np.zeros(len(fnames))
snobject = SNObject()
snobject.rectifySED = True
for i in range(len(self.column_by_name('snid'))):
# if t0 is nan, this was set by the catalog for dim SN, or SN
# outside redshift range, We will not provide a SED file for these
if np.isnan(t0[i]):
magNorms[i] = np.nan
fnames[i] = None
else:
snobject.set(c=c[i], x1=x1[i], x0=x0[i], t0=t0[i],
z=z[i])
if snobject.modelOutSideTemporalRange == 'zero':
if self.mjdobs > snobject.maxtime() or self.mjdobs < snobject.mintime():
magNorms[i] = np.nan
fnames[i] = None
# SED in rest frame
sed = snobject.SNObjectSourceSED(time=self.mjdobs)
try:
magNorms[i] = sed.calcMag(bandpass=bp)
except:
# sed.flambda = 1.0e-20
magNorms[i] = 1000. # sed.calcMag(bandpass=bp)
if self.writeSedFile:
sed.writeSED(fnames[i])
return (fnames, magNorms)
def get_snbrightness(self):
"""
getters for brightness related parameters of sn
"""
if self._sn_object_cache is None or len(
self._sn_object_cache) > 1000000:
self._sn_object_cache = {}
c, x1, x0, t0, _z, ra, dec = self.column_by_name('c'),\
self.column_by_name('x1'),\
self.column_by_name('x0'),\
self.column_by_name('t0'),\
self.column_by_name('redshift'),\
self.column_by_name('raJ2000'),\
self.column_by_name('decJ2000')
raDeg = np.degrees(ra)
decDeg = np.degrees(dec)
ebv = self.column_by_name('EBV')
id_list = self.column_by_name('snid')
bandname = self.obs_metadata.bandpass
if isinstance(bandname, list):
raise ValueError('bandname expected to be string, but is list\n')
bandpass = self.lsstBandpassDict[bandname]
# Initialize return array so that it contains the values you would get
# if you passed through a t0=self.badvalues supernova
vals = np.array([[0.0] * len(t0), [np.inf] * len(t0),
[np.nan] * len(t0), [np.inf] * len(t0),
[0.0] * len(t0)]).transpose()
for i in np.where(
np.logical_and(
np.isfinite(t0),
np.abs(self.mjdobs - t0) < self.maxTimeSNVisible))[0]:
if id_list[i] in self._sn_object_cache:
SNobject = self._sn_object_cache[id_list[i]]
else:
SNobject = SNObject()
SNobject.set(z=_z[i], c=c[i], x1=x1[i], t0=t0[i], x0=x0[i])
SNobject.setCoords(ra=raDeg[i], dec=decDeg[i])
SNobject.set_MWebv(ebv[i])
self._sn_object_cache[id_list[i]] = SNobject
if self.mjdobs <= SNobject.maxtime(
) and self.mjdobs >= SNobject.mintime():
# Calculate fluxes
fluxinMaggies = SNobject.catsimBandFlux(
time=self.mjdobs, bandpassobject=bandpass)
mag = SNobject.catsimBandMag(time=self.mjdobs,
fluxinMaggies=fluxinMaggies,
bandpassobject=bandpass)
vals[i, 0] = fluxinMaggies
vals[i, 1] = mag
flux_err = SNobject.catsimBandFluxError(
time=self.mjdobs,
bandpassobject=bandpass,
m5=self.obs_metadata.m5[bandname],
photParams=self.photometricparameters,
fluxinMaggies=fluxinMaggies,
magnitude=mag)
mag_err = SNobject.catsimBandMagError(
time=self.mjdobs,
bandpassobject=bandpass,
m5=self.obs_metadata.m5[bandname],
photParams=self.photometricparameters,
magnitude=mag)
sed = SNobject.SNObjectSED(time=self.mjdobs,
bandpass=self.lsstBandpassDict,
applyExtinction=True)
adu = sed.calcADU(bandpass,
photParams=self.photometricparameters)
vals[i, 2] = flux_err
vals[i, 3] = mag_err
vals[i, 4] = adu
return (vals[:, 0], vals[:, 1], vals[:, 2], vals[:, 3], vals[:, 4])
def _light_curves_from_query(self, cat_dict, query_result, grp, lc_per_field=None):
t_dict = {}
gamma_dict = {}
m5_dict = {}
t_min = None
t_max = None
for bp_name in cat_dict:
self.lsstBandpassDict[bp_name].sbTophi()
# generate a 2-D numpy array containing MJDs, m5, and photometric gamma values
# for each observation in the given bandpass
raw_array = np.array([[obs.mjd.TAI, obs.m5[bp_name],
calcGamma(self.lsstBandpassDict[bp_name],
obs.m5[obs.bandpass],
self.phot_params)]
for obs in grp if obs.bandpass == bp_name]).transpose()
if len(raw_array) > 0:
t_dict[bp_name] = raw_array[0]
m5_dict[bp_name] = raw_array[1]
gamma_dict[bp_name] = raw_array[2]
local_t_min = t_dict[bp_name].min()
local_t_max = t_dict[bp_name].max()
if t_min is None or local_t_min < t_min:
t_min = local_t_min
if t_max is None or local_t_max > t_max:
t_max = local_t_max
snobj = SNObject()
cat = cat_dict[list(cat_dict.keys())[0]] # does not need to be associated with a bandpass
dummy_sed = Sed()
n_actual_sn = 0 # how many SN have we actually delivered?
for chunk in query_result:
if lc_per_field is not None and n_actual_sn >= lc_per_field:
break
t_start_chunk = time.time()
for sn in cat.iter_catalog(query_cache=[chunk]):
sn_rng = self.sn_universe.getSN_rng(sn[1])
sn_t0 = self.sn_universe.drawFromT0Dist(sn_rng)
if sn[5] <= self.z_cutoff and np.isfinite(sn_t0) and \
sn_t0 < t_max + cat.maxTimeSNVisible and \
sn_t0 > t_min - cat.maxTimeSNVisible:
sn_c = self.sn_universe.drawFromcDist(sn_rng)
sn_x1 = self.sn_universe.drawFromx1Dist(sn_rng)
sn_x0 = self.sn_universe.drawFromX0Dist(sn_rng, sn_x1, sn_c, sn[4])
snobj.set(t0=sn_t0, c=sn_c, x1=sn_x1, x0=sn_x0, z=sn[5])
for bp_name in t_dict:
t_list = t_dict[bp_name]
m5_list = m5_dict[bp_name]
gamma_list = gamma_dict[bp_name]
bandpass = self.lsstBandpassDict[bp_name]
if len(t_list) == 0:
continue
if snobj.maxtime() >= t_list[0] and snobj.mintime() <= t_list[-1]:
active_dexes = np.where(np.logical_and(t_list >= snobj.mintime(),
t_list <= snobj.maxtime()))
t_active = t_list[active_dexes]
m5_active = m5_list[active_dexes]
gamma_active = gamma_list[active_dexes]
if len(t_active) > 0:
wave_ang = bandpass.wavelen*10.0
mask = np.logical_and(wave_ang > snobj.minwave(),
wave_ang < snobj.maxwave())
wave_ang = wave_ang[mask]
snobj.set(mwebv=sn[6])
sn_ff_buffer = snobj.flux(time=t_active, wave=wave_ang)*10.0
flambda_grid = np.zeros((len(t_active), len(bandpass.wavelen)))
for ff, ff_sn in zip(flambda_grid, sn_ff_buffer):
ff[mask] = np.where(ff_sn > 0.0, ff_sn, 0.0)
fnu_grid = flambda_grid*bandpass.wavelen* \
bandpass.wavelen*dummy_sed._physParams.nm2m* \
dummy_sed._physParams.ergsetc2jansky/dummy_sed._physParams.lightspeed
flux_list = \
(fnu_grid*bandpass.phi).sum(axis=1)*(bandpass.wavelen[1]-bandpass.wavelen[0])
acceptable = np.where(flux_list>0.0)
flux_error_list = flux_list[acceptable]/ \
calcSNR_m5(dummy_sed.magFromFlux(flux_list[acceptable]),
bandpass,
m5_active[acceptable], self.phot_params,
gamma=gamma_active[acceptable])
if len(acceptable) > 0:
n_actual_sn += 1
if lc_per_field is not None and n_actual_sn > lc_per_field:
break
if sn[0] not in self.truth_dict:
self.truth_dict[sn[0]] = {}
self.truth_dict[sn[0]]['t0'] = sn_t0
self.truth_dict[sn[0]]['x1'] = sn_x1
self.truth_dict[sn[0]]['x0'] = sn_x0
self.truth_dict[sn[0]]['c'] = sn_c
self.truth_dict[sn[0]]['z'] = sn[5]
self.truth_dict[sn[0]]['E(B-V)'] = sn[6]
if sn[0] not in self.mjd_dict:
self.mjd_dict[sn[0]] = {}
self.bright_dict[sn[0]] = {}
self.sig_dict[sn[0]] = {}
if bp_name not in self.mjd_dict[sn[0]]:
self.mjd_dict[sn[0]][bp_name] = []
self.bright_dict[sn[0]][bp_name] = []
self.sig_dict[sn[0]][bp_name] = []
for tt, ff, ee in zip(t_active[acceptable], flux_list[acceptable],
flux_error_list[0]):
self.mjd_dict[sn[0]][bp_name].append(tt)
self.bright_dict[sn[0]][bp_name].append(ff/3631.0)
self.sig_dict[sn[0]][bp_name].append(ee/3631.0)
print("chunk of ", len(chunk), " took ", time.time()-t_start_chunk)
def get_snbrightness(self):
"""
getters for brightness related parameters of sn
"""
if self._sn_object_cache is None or len(self._sn_object_cache) > 1000000:
self._sn_object_cache = {}
c, x1, x0, t0, _z, ra, dec = self.column_by_name('c'),\
self.column_by_name('x1'),\
self.column_by_name('x0'),\
self.column_by_name('t0'),\
self.column_by_name('redshift'),\
self.column_by_name('raJ2000'),\
self.column_by_name('decJ2000')
raDeg = np.degrees(ra)
decDeg = np.degrees(dec)
ebv = self.column_by_name('EBV')
id_list = self.column_by_name('snid')
bandname = self.obs_metadata.bandpass
if isinstance(bandname, list):
raise ValueError('bandname expected to be string, but is list\n')
bandpass = self.lsstBandpassDict[bandname]
# Initialize return array so that it contains the values you would get
# if you passed through a t0=self.badvalues supernova
vals = np.array([[0.0]*len(t0), [np.inf]*len(t0),
[np.nan]*len(t0), [np.inf]*len(t0),
[0.0]*len(t0)]).transpose()
for i in np.where(np.logical_and(np.isfinite(t0),
np.abs(self.mjdobs - t0) < self.maxTimeSNVisible))[0]:
if id_list[i] in self._sn_object_cache:
SNobject = self._sn_object_cache[id_list[i]]
else:
SNobject = SNObject()
SNobject.set(z=_z[i], c=c[i], x1=x1[i], t0=t0[i], x0=x0[i])
SNobject.setCoords(ra=raDeg[i], dec=decDeg[i])
SNobject.set_MWebv(ebv[i])
self._sn_object_cache[id_list[i]] = SNobject
if self.mjdobs <= SNobject.maxtime() and self.mjdobs >= SNobject.mintime():
# Calculate fluxes
fluxinMaggies = SNobject.catsimBandFlux(time=self.mjdobs,
bandpassobject=bandpass)
mag = SNobject.catsimBandMag(time=self.mjdobs,
fluxinMaggies=fluxinMaggies,
bandpassobject=bandpass)
vals[i, 0] = fluxinMaggies
vals[i, 1] = mag
flux_err = SNobject.catsimBandFluxError(time=self.mjdobs,
bandpassobject=bandpass,
m5=self.obs_metadata.m5[
bandname],
photParams=self.photometricparameters,
fluxinMaggies=fluxinMaggies,
magnitude=mag)
mag_err = SNobject.catsimBandMagError(time=self.mjdobs,
bandpassobject=bandpass,
m5=self.obs_metadata.m5[
bandname],
photParams=self.photometricparameters,
magnitude=mag)
sed = SNobject.SNObjectSED(time=self.mjdobs,
bandpass=self.lsstBandpassDict,
applyExtinction=True)
adu = sed.calcADU(bandpass, photParams=self.photometricparameters)
vals[i, 2] = flux_err
vals[i, 3] = mag_err
vals[i, 4] = adu
return (vals[:, 0], vals[:, 1], vals[:, 2], vals[:, 3], vals[:, 4])
