def test_read_write_spectrum(tmpdir):
sfile = "spectrum_test.dat"
tmp_file = "{}/{}".format(tmpdir, sfile)
wl = np.linspace(1.1, 1.7, 7) * 1e-4
spectrum = np.ones(7)
io.write_spectrum(wl,
spectrum,
filename=tmp_file,
type='transit',
wlunits='um')
# Take a look at the output file:
assert sfile in os.listdir(str(tmpdir))
with open(tmp_file, 'r') as f:
assert f.readline() == '# Wavelength (Rp/Rs)**2\n'
assert f.readline() == '# um unitless\n'
wn, flux = io.read_spectrum(tmp_file)
np.testing.assert_allclose(wn,
np.array([
9090.90909091, 8333.33333333, 7692.30769231,
7142.85714286, 6666.66666667, 6250.,
5882.35294118
]),
rtol=1e-7)
np.testing.assert_equal(flux, np.ones(7))
wl, flux = io.read_spectrum(tmp_file, wn=False)
np.testing.assert_allclose(wl, np.linspace(1.1, 1.7, 7))
np.testing.assert_equal(flux, np.ones(7))
def test_band_integrate():
wn = np.arange(1500, 5000.1, 1.0)
sflux = ps.bbflux(wn, 1800.0)
wn1, irac1 = io.read_spectrum(
pc.ROOT+"pyratbay/data/filters/spitzer_irac1_sa.dat")
wn2, irac2 = io.read_spectrum(
pc.ROOT+"pyratbay/data/filters/spitzer_irac2_sa.dat")
bandfluxes = ps.band_integrate(sflux, wn, [irac1,irac2], [wn1, wn2])
np.testing.assert_allclose(bandfluxes, [98527.148526, 84171.417692])
def test_band_integrate_multiple():
wn = np.arange(1500, 5000.1, 1.0)
signal = np.ones_like(wn)
wn1, irac1 = io.read_spectrum(
pc.ROOT+"pyratbay/data/filters/spitzer_irac1_sa.dat")
wn2, irac2 = io.read_spectrum(
pc.ROOT+"pyratbay/data/filters/spitzer_irac2_sa.dat")
bandflux = ps.band_integrate(signal, wn, [irac1, irac2], [wn1, wn2])
np.testing.assert_allclose(bandflux, [1.0, 1.0])
def test_read_spectrum_custom_header(tmpdir, header):
ffile = 'filter_test.dat'
tmp_file = "{}/{}".format(tmpdir, ffile)
data = '1.0 1.0\n2.0 1.5\n4.0 1.0\n'
with open(tmp_file, 'w') as f:
f.write(header + data)
wn, spec = io.read_spectrum(tmp_file)
np.testing.assert_allclose(wn, np.array([10000.0, 5000.0, 2500.0]))
def test_read_write_spectrum_filter(tmpdir):
ffile = 'filter_test.dat'
tmp_file = "{}/{}".format(tmpdir, ffile)
# Assert write:
wl = np.linspace(1.4, 1.5, 20)
transmission = np.array(np.abs(wl - 1.45) < 0.035, np.double)
io.write_spectrum(wl * pc.um, transmission, tmp_file, 'filter')
assert ffile in os.listdir(str(tmpdir))
with open(tmp_file, 'r') as f:
assert f.readline() == '# Wavelength transmission\n'
assert f.readline() == '# um unitless\n'
# Assert read:
wn, trans = io.read_spectrum(tmp_file)
np.testing.assert_equal(trans, transmission)
np.testing.assert_allclose(1e4 / wn,
np.array([
1.4, 1.40526, 1.41053, 1.41579, 1.42105,
1.42632, 1.43158, 1.43684, 1.44211, 1.44737,
1.45263, 1.45789, 1.46316, 1.46842, 1.47368,
1.47895, 1.48421, 1.48947, 1.49474, 1.5
]),
atol=1e-7)
if __name__ == "__main__":
# Prep up TauREx:
setup_cache()
# Prep up ARIEL filters:
filter_dir = '../inputs/filters/'
filters = [
f'{filter_dir}{ffile}' for ffile in os.listdir(filter_dir)
if ffile.startswith('ARIEL')
]
bin_wl = [ffile.split('_')[-1].split('um')[0] for ffile in filters]
wn_sort = np.argsort(np.array(bin_wl, float))
filters = [filters[idx] for idx in wn_sort]
band_trans, band_wn = [], []
for filter_file in filters:
bwn, btrans = io.read_spectrum(filter_file)
band_trans.append(btrans)
band_wn.append(bwn)
# Generate synthetic ARIEL transmission observations with TauREx:
planet_data = np.loadtxt('../inputs/retrieval_benchmark_transmission.txt',
dtype=str)
planets = planet_data[:, 0]
sys_params = np.array(planet_data[:, 1:7], np.double)
qplanets = np.array(planet_data[:, 7:11], np.double)
pclouds = np.array(planet_data[:, 11], np.double)
noise_floor = 10**np.array(planet_data[:, 12], np.double)
nplanets = len(planets)
sim_file = open('ariel_taurex_synthetic_transmission.dat', 'w')
for i in range(nplanets):
'NIRSpec G395H',
# 'NIRCam F322W2',
# 'NIRCam F444W',
]
# SOSS gives lower noise than PRISM
# PRISM reaches 0.6 um, but there's too little flux already.
# G395H is enough to complement SOSS
# So, I'll stitch those two
filters = sorted([
f'../inputs/filters/{filt}' for filt in os.listdir('../inputs/filters')
if filt.startswith('JWST')
])
filter_wn, filter_trans = [], []
for filt in filters:
wn, trans = io.read_spectrum(filt)
filter_wn.append(wn)
filter_trans.append(trans)
nwave_obs = len(filters)
flux_ratio = spectra / starflux * rprs**2
noiseless_flux_ratio = np.zeros((nmodels, nphase, nwave_obs))
for i in range(nmodels):
for j in range(nphase):
noiseless_flux_ratio[i, j] = ps.band_integrate(flux_ratio[i,
j], 1e4 / wl,
filter_trans, filter_wn)
# Note, pandexo's resolution is R = 0.5 * lambda/dlambda
resolution = 100.0
