def _register_filters(self, force: bool = False):
"""Register filters for this survey / data release with SNCosmo
Args:
force: Re-register a band if already registered
"""
data_arr = np.genfromtxt(self._filter_path, skip_header=1)
filt_table = Table(data_arr, names=['wave', 'u', 'g', 'r', 'i', 'z'])
filt_table['wave'] *= 10 # Convert nm to angstroms
# Bands are already registered in sncosmo under a different name.
# We register them using the package standardized name
for new_band_name in self.band_names:
built_in_name = new_band_name.split('_')[-1]
# MEGACAMPSF are radius dependant
if 'MEGACAMPSF' in built_in_name:
trans = filt_table[built_in_name[-1].lower()]
new_band = sncosmo.Bandpass(filt_table['wave'], trans)
else:
built_in_band = sncosmo.get_bandpass(built_in_name)
new_band = sncosmo.Bandpass(built_in_band.wave,
built_in_band.trans)
new_band.name = new_band_name
sncosmo.register(new_band, force=force)
def register_filter_file(file_path: str,
filter_name: str,
force: bool = False):
"""Registers filter profiles with sncosmo if not already registered
Assumes the file at ``file_path`` is a two column, white space delimited
ascii table.
Args:
file_path: Path of ascii table with wavelength (Ang) and transmission
filter_name: The name of the registered filter.
force: Whether to re-register a band if already registered
"""
# Get set of registered builtin and custom band passes
# noinspection PyProtectedMember
available_bands = set(k[0]
for k in sncosmo.bandpasses._BANDPASSES._loaders)
# noinspection PyProtectedMember
available_bands.update(k[0]
for k in sncosmo.bandpasses._BANDPASSES._instances)
# Register the new bandpass
if filter_name not in available_bands:
wave, trans = np.genfromtxt(file_path).T
is_good_data = ~np.isnan(wave) & ~np.isnan(trans)
band = sncosmo.Bandpass(wave[is_good_data], trans[is_good_data])
band.name = filter_name
sncosmo.register(band, force=force)
def sdssrpband():
import sncosmo
from astropy.io import ascii
import astropy.units as u
# https://lco.global/observatory/instruments/filters/sdss-r/
sdssrp = ascii.read(open("sdssrp.txt", "rb"))
sdssrp.rename_columns(['\lambda', '[nm]'], ['lambda [nm]', 'transmission'])
wavelength = sdssrp['lambda [nm]']
transmission = sdssrp['transmission']
band = sncosmo.Bandpass(wavelength,
transmission,
name='sdssrp',
wave_unit=u.nm)
sncosmo.register(band)
#print(band.minwave(),band.maxwave(),band.wave_eff)
plot = False
if plot:
import matplotlib.pyplot as plt
import matplotlib
matplotlib.rcParams.update({'font.size': 15})
fig, ax = plt.subplots(figsize=(10.5, 8.5))
ax.plot(wavelength, transmission)
ax.set_xlabel("Wavelength [nm]")
ax.set_ylabel("Transmission")
ax.set_xlim(525, 725)
plt.savefig('transmission_sdssrp.pdf', bbox_inches='tight')
return band
def test_register():
disp = np.array([4000., 4200., 4400., 4600., 4800., 5000.])
trans = np.array([0., 1., 1., 1., 1., 0.])
# create a band, register it, make sure we can get it back.
band = sncosmo.Bandpass(disp, trans, name='tophatg')
sncosmo.register(band)
assert sncosmo.get_bandpass('tophatg') is band
def test_register_source():
phase = np.linspace(0., 100., 10)
wave = np.linspace(800., 20000., 100)
flux = np.ones((len(phase), len(wave)), dtype=float)
source = sncosmo.TimeSeriesSource(phase, wave, flux, name='test_source')
sncosmo.register(source)
# Retrieving a source makes a copy, so just check that the names are the
# same.
assert sncosmo.get_source('test_source').name == 'test_source'
def register_ztf_bandpass(band):
bandtable = pd.read_csv(os.path.expandvars(
"$SIRAHPIPE_DIR/data/ztf_filters/ZTF_{}.csv".format(band)),
names=['wave', 'trans'],
comment='#')
bandtable = bandtable.drop_duplicates('wave')
bandpass = sncosmo.Bandpass(wave=bandtable.wave,
trans=bandtable.trans,
wave_unit=u.nm)
bandpass.name = 'ztf' + band
sncosmo.register(bandpass, force=True)
def test_register():
disp = np.array([4000., 4200., 4400., 4600., 4800., 5000.])
trans = np.array([0., 1., 1., 1., 1., 0.])
# create a band, register it, make sure we can get it back.
band = sncosmo.Bandpass(disp, trans, name='tophatg')
sncosmo.register(band)
assert sncosmo.get_bandpass('tophatg') is band
# test deprecated path to registry
band = sncosmo.Bandpass(disp, trans, name='tophatg2')
sncosmo.registry.register(band)
assert sncosmo.get_bandpass('tophatg2') is band
def register_sncosmo_filter(wave: np.array, trans: np.array, name: str, force: bool = False) -> None:
"""Register a filter profile with sncosmo
Args:
wave: Array of wavelength values in Angstroms
trans: Array of transmission values between 0 and 1
name: Name of the filter to register
force: Whether to overwrite an existing filter with the given name
"""
# Specifying the name argument in the constructor seems to not work in
# at least some sncosmo versions, so we set it after instantiation
sncosmo_ccd = sncosmo.Bandpass(wave, trans)
sncosmo_ccd.name = name
sncosmo.register(sncosmo_ccd, force=force)
def register_filter(f: str, instrument: str = 'FORS2'):
data = p.filter_params(instrument=instrument, f=f)
bandpass = sncosmo.Bandpass(data['wavelengths_filter_only'], data['transmissions_filter_only'])
sncosmo.register(bandpass, f)
# phaseN wlsN flux
## We need to adapt the format to build the sncosmo class TimeSeriesSource
for tmpl in tmpl_host_extinction_corrected[:]:
tmpl_name = tmpl.replace('.SED', '')
phase_raw, wls_raw, flux_raw = np.genfromtxt(
pycoco_dir + 'Templates_HostCorrected/' + tmpl, unpack=True)
wls = np.unique(wls_raw)
phase = phase_raw[::len(wls)]
flux_reshaped = flux_raw.reshape(len(phase), len(wls))
source = sncosmo.TimeSeriesSource(phase,
wls,
flux_reshaped,
zero_before=True,
name=tmpl_name)
sncosmo.register(source, name=tmpl_name)
print(
tmpl_name,
'(type %s) registered!' % name2type[tmpl_name.replace('pycoco_', '')])
for tmpl in tmpl_host_extinction_NOTcorrected[:]:
tmpl_name = tmpl.replace('.SED', '')
phase_raw, wls_raw, flux_raw = np.genfromtxt(
pycoco_dir + 'Templates_noHostCorr/' + tmpl, unpack=True)
wls = np.unique(wls_raw)
phase = phase_raw[::len(wls)]
flux_reshaped = flux_raw.reshape(len(phase), len(wls))
source = sncosmo.TimeSeriesSource(phase,
wls,
flux_reshaped,
zero_before=True,
def test_register_invalid():
with pytest.raises(ValueError):
sncosmo.register("invalid")
def test_register_magsystem():
magsys = sncosmo.get_magsystem('ab')
sncosmo.register(magsys, name='test_magsys')
assert sncosmo.get_magsystem('test_magsys') is magsys
import sncosmo
#Change band names to ones used in P60 dataframe
band_g = sncosmo.get_bandpass('sdssg')
band_g.name = 'g'
sncosmo.register(band_g)
band_r = sncosmo.get_bandpass('sdssr')
band_r.name = 'r'
sncosmo.register(band_r)
band_i = sncosmo.get_bandpass('sdssi')
band_i.name = 'i'
sncosmo.register(band_i)
band_u = sncosmo.get_bandpass('sdssu')
band_u.name = 'u'
sncosmo.register(band_u)
def extract_features(meta: pd.DataFrame,
lc: pd.DataFrame,
source: str,
normalize: bool = False,
snr: int = 3,
zbounds: str = 'estimated',
skip: int = 0,
end: int = -1,
clip_bounds: bool = False,
t_bounds: bool = False,
columns: List[str] = None):
if normalize:
try:
for band in ['g', 'i', 'r', 'u', 'y', 'z']:
b = read_bandpass('lsst/total_{}.dat'.format(band),
wave_unit=u.nm,
trim_level=0.001,
name='lsst{}_n'.format(band),
normalize=True)
sncosmo.register(b, 'lsst{}_n'.format(band))
except:
raise
pass
with timer('dropping meta'):
meta = meta[meta.object_id.isin(lc.object_id)].reset_index(drop=True)
print('shape(meta): {}'.format(meta.shape))
if 'object_id' in meta:
meta.set_index('object_id', inplace=True)
if normalize:
passbands = [
'lsstu_n', 'lsstg_n', 'lsstr_n', 'lssti_n', 'lsstz_n', 'lssty_n'
]
else:
passbands = ['lsstu', 'lsstg', 'lsstr', 'lssti', 'lsstz', 'lssty']
with timer('prep'):
lc['band'] = lc['passband'].apply(lambda x: passbands[x])
lc['zpsys'] = 'ab'
lc['zp'] = 25.0
# create a model
model = Model(source=source)
params = model.param_names
if columns:
ret = pd.DataFrame(columns=columns)
else:
columns = ['chisq', 'ncall'] + [source + '_' + c for c in params] + [
source + '_' + c + '_err' for c in params
]
ret = pd.DataFrame(columns=columns)
prefix = source
if zbounds == 'fixed':
prefix += '_f_'
else:
prefix += '_p_'
prefix += 'sn{}_'.format(snr)
if normalize:
prefix += 'n_'
ret.columns = [prefix + c for c in ret.columns]
n_errors = 0
n_loop = len(meta)
if end > 0:
n_loop = end
for i in tqdm(range(skip, n_loop)):
object_id = meta.index[i]
try:
ret.loc[object_id] = fit_lc(model, meta, lc, object_id, zbounds,
clip_bounds, t_bounds, snr)
except:
n_errors += 1
if i == 30 and n_errors == 31:
print('All 30 first attempts were failed. stopped')
raise
print('total {} data processed. {} data was skipped'.format(
len(meta), n_errors))
ret.reset_index(inplace=True)
ret.rename(columns={'index': 'object_id'}, inplace=True)
return ret
