def test_get_filter_info():
nrc = spec.get_filter_info(['nircam_f444w_magnitude'], 'abmag')
assert nrc == {'nircam_f444w_magnitude': (6.6928e-22 * FLAMBDA_CGS_UNITS, 4.3637e-31 * FNU_CGS_UNITS, 27.3004,
4.4212 * u.micron)}
nis = spec.get_filter_info(['niriss_f200w_magnitude'], 'vegamag')
assert nis == {'niriss_f200w_magnitude': (2.173398e-21 * FLAMBDA_CGS_UNITS, 2.879494e-31 * FNU_CGS_UNITS,
26.04898, 1.9930 * u.micron)}
fgs = spec.get_filter_info(['fgs_magnitude'], 'stmag')
assert fgs == {'fgs_magnitude': (1.593395e-22 * FLAMBDA_CGS_UNITS, 3.324736e-32 * FNU_CGS_UNITS, 33.39426,
2.5011 * u.micron)}
def test_get_filter_info():
nrc = spec.get_filter_info(['nircam_f444w_magnitude'], 'abmag')
assert nrc == {
'nircam_f444w_magnitude':
(5.584676852068291e-22 * FLAMBDA_CGS_UNITS,
3.641228911284274e-31 * FNU_CGS_UNITS, 27.496928286774455,
4.421150698281195 * u.micron)
}
nis = spec.get_filter_info(['niriss_f200w_magnitude'], 'vegamag')
assert nis == {
'niriss_f200w_magnitude':
(2.173398e-21 * FLAMBDA_CGS_UNITS, 2.879494e-31 * FNU_CGS_UNITS,
26.04898, 1.9930 * u.micron)
}
fgs = spec.get_filter_info(['fgs_magnitude'], 'stmag')
assert fgs == {
'fgs_magnitude':
(1.593395e-22 * FLAMBDA_CGS_UNITS, 3.324736e-32 * FNU_CGS_UNITS,
33.39426, 2.5011 * u.micron)
}
def test_spectra_rescaling():
"""Test the functionality for rescaling input spectra to a given
magnitude in a given filter
"""
# JWST primary mirror area in cm^2. Needed for countrate check
# at the end
primary_area = 25.326 * (u.m * u.m)
# Create spectrum: one source to be normalized
# and the other should not be
waves = np.arange(0.4, 5.6, 0.01)
flux = np.repeat(1e-16, len(waves))
flux2 = np.repeat(4.24242424242e-18, len(waves)) # arbitrary value
spectra = {
1: {
"wavelengths": waves * u.micron,
"fluxes": flux * u.pct
},
2: {
"wavelengths": waves * u.micron,
"fluxes": flux2 * units.FLAM
}
}
# Create source catalog containing scaling info
catalog = Table()
catalog['index'] = [1, 2]
catalog['nircam_f322w2_magnitude'] = [18.] * 2
catalog['niriss_f090w_magnitude'] = [18.] * 2
#catalog['fgs_magnitude'] = [18.] * 2
# Instrument info
instrument = ['nircam', 'niriss'] # , 'fgs']
filter_name = ['F322W2', 'F090W'] # , 'N/A']
module = ['B', 'N'] # , 'F']
detector = ['NRCA1', 'NIS'] # , 'GUIDER1']
# Magnitude systems of renormalization magnitudes
mag_sys = ['vegamag', 'abmag', 'stmag']
# Loop over options and test each
for inst, filt, mod, det in zip(instrument, filter_name, module, detector):
# Extract the appropriate column from the catalog information
magcol = [col for col in catalog.colnames if inst in col]
sub_catalog = catalog['index', magcol[0]]
# Filter throughput files
filter_thru_file = get_filter_throughput_file(instrument=inst,
filter_name=filt,
nircam_module=mod,
fgs_detector=det)
# Retrieve the correct gain value that goes with the fluxcal info
if inst == 'nircam':
gain = MEAN_GAIN_VALUES['nircam']['lwb']
elif inst == 'niriss':
gain = MEAN_GAIN_VALUES['niriss']
elif inst == 'fgs':
gain = MEAN_GAIN_VALUES['fgs'][det.lower()]
# Create filter bandpass object, to be used in the final
# comparison
filter_tp = ascii.read(filter_thru_file)
bp_waves = filter_tp['Wavelength_microns'].data * u.micron
thru = filter_tp['Throughput'].data
bandpass = SpectralElement(
Empirical1D, points=bp_waves, lookup_table=thru) / gain
# Check the renormalization in all photometric systems
for magsys in mag_sys:
rescaled_spectra = spec.rescale_normalized_spectra(
spectra, sub_catalog, magsys, filter_thru_file, gain)
# Calculate the countrate associated with the renormalized
# spectrum through the requested filter
for dataset in rescaled_spectra:
if dataset == 1:
# This block is for the spectra that are rescaled
rescaled_spectrum = SourceSpectrum(
Empirical1D,
points=rescaled_spectra[dataset]['wavelengths'],
lookup_table=rescaled_spectra[dataset]['fluxes'])
obs = Observation(rescaled_spectrum,
bandpass,
binset=bandpass.waveset)
renorm_counts = obs.countrate(area=primary_area)
# Calculate the countrate associated with an object of
# matching magnitude
if inst != 'fgs':
mag_col = '{}_{}_magnitude'.format(
inst.lower(), filt.lower())
else:
mag_col = 'fgs_magnitude'
filt_info = spec.get_filter_info([mag_col], magsys)
magnitude = catalog[mag_col][dataset - 1]
photflam, photfnu, zeropoint, pivot = filt_info[mag_col]
check_counts = magnitude_to_countrate(
'imaging',
magsys,
magnitude,
photfnu=photfnu.value,
photflam=photflam.value,
vegamag_zeropoint=zeropoint)
if magsys != 'vegamag':
# As long as the correct gain is used, AB mag and ST mag
# count rates agree very well
tolerance = 0.0005
else:
# Vegamag count rates for NIRISS have a sligtly larger
# disagreement. Zeropoints were derived assuming Vega = 0.02
# magnitudes. This offset has been added to the rescaling
# function, but may not be exact.
tolerance = 0.0015
# This dataset has been rescaled, so check that the
# countrate from the rescaled spectrum matches that from
# the magnitude it was rescaled to
if isinstance(check_counts, u.quantity.Quantity):
check_counts = check_counts.value
if isinstance(renorm_counts, u.quantity.Quantity):
renorm_counts = renorm_counts.value
print(inst, filt, magsys, renorm_counts, check_counts,
renorm_counts / check_counts)
assert np.isclose(renorm_counts, check_counts, atol=0, rtol=tolerance), \
print('Failed assertion: ', inst, filt, magsys, renorm_counts, check_counts,
renorm_counts / check_counts)
elif dataset == 2:
# Not rescaled. In this case Mirage ignores the magnitude
# value in the catalog, so we can't check against check_counts.
# Just make sure that the rescaling function did not
# change the spectrum at all
assert np.all(spectra[dataset]['fluxes'] ==
rescaled_spectra[dataset]['fluxes'])