def cg_other_est():
"""Test all HSM shear estimators give same value as REGAUSS (default)"""
in_p = cg_fn.LSST_Args()
filt = galsim.Bandpass('data/baseline/total_r.dat',
wave_type='nm').thin(rel_err=1e-4)
in_p.b_SED, in_p.d_SED, in_p.c_SED = cg_fn.get_template_seds(in_p)
gal = cg_fn.get_gal_cg(in_p)
psf_args = cg_fn.psf_params()
meas_args = cg_fn.meas_args(shear_est='KSB')
meas_args.bp = filt
gcg, gnocg = cg_fn.calc_cg_crg(gal, meas_args, psf_args)
# Previously measured value at default galaxy parameters
np.testing.assert_array_almost_equal((gcg / gnocg - 1).T[0],
[0.00106263, 0.00106594],
decimal=5)
meas_args.shear_est = 'BJ'
gcg, gnocg = cg_fn.calc_cg_crg(gal, meas_args, psf_args)
# Previously measured value at default galaxy parameters
np.testing.assert_array_almost_equal((gcg / gnocg - 1).T[0],
[0.00106263, 0.00106594],
decimal=5)
meas_args.shear_est = 'LINEAR'
gcg, gnocg = cg_fn.calc_cg_crg(gal, meas_args, psf_args)
# Previously measured value at default galaxy parameters
np.testing.assert_array_almost_equal((gcg / gnocg - 1).T[0],
[0.00106263, 0.00106594],
decimal=5)
def meas_cg_bias(gal, row, f_name,
rt_g, f_type, npix=360):
"""Computes bias due to color gradient on sahpe measuremnt.
For an input chromatic galaxy with cg, gal an equilvalent galaxy with
no cg is created and the shear recovered from each (with ring test) is
measured.
@gal input galaxy with cg.
@row astropy table row to save measured shear.
@rt_g shaer applied to the galaxy.
@type string to identify the column of row to save measured shear.
"""
print " Measuring CG bias"
filt = galsim.Bandpass('data/baseline/total_%s.dat'%f_name,
wave_type='nm').thin(rel_err=1e-4)
meas_args = cg_fn.meas_args(rt_g=rt_g, npix=npix)
meas_args.bp = filt
psf_args = cg_fn.psf_params()
gcg, gnocg = cg_fn.calc_cg_crg(gal, meas_args, psf_args)
print " Measured CG bias"
if (gcg == "Fail") or (gnocg == "Fail"):
print "HSM FAILED"
g_f = np.ones([2, len(rt_g)]) * -10
gcg, gnocg = g_f, g_f
row[f_type + '_g_cg'] = gcg.T
row[f_type + '_g_no_cg'] = gnocg.T
def same_sed():
"""bulge and disk have same sed, cg bias must be zero"""
in_p = cg_fn.LSST_Args(disk_SED_name='E')
filt = galsim.Bandpass('data/baseline/total_r.dat',
wave_type='nm').thin(rel_err=1e-4)
in_p.b_SED, in_p.d_SED, in_p.c_SED = cg_fn.get_template_seds(in_p)
gal = cg_fn.get_gal_cg(in_p)
meas_args = cg_fn.meas_args()
meas_args.bp = filt
psf_args = cg_fn.psf_params()
gcg, gnocg = cg_fn.calc_cg_crg(gal, meas_args, psf_args)
np.testing.assert_array_almost_equal((gcg / gnocg - 1).T[0], [0, 0],
decimal=5)
def achr_psf():
"""LSST PSF is chromatic, CG bias must be 0"""
in_p = cg_fn.LSST_Args()
filt = galsim.Bandpass('data/baseline/total_r.dat',
wave_type='nm').thin(rel_err=1e-4)
in_p.b_SED, in_p.d_SED, in_p.c_SED = cg_fn.get_template_seds(in_p)
gal = cg_fn.get_gal_cg(in_p)
meas_args = cg_fn.meas_args()
meas_args.bp = filt
psf_args = cg_fn.psf_params(alpha=0)
gcg, gnocg = cg_fn.calc_cg_crg(gal, meas_args, psf_args)
np.testing.assert_array_almost_equal((gcg / gnocg - 1).T[0],
[0, 0],
decimal=5)
def with_cg():
"""Raise error if no cg bias in default setting"""
in_p = cg_fn.LSST_Args()
filt = galsim.Bandpass('data/baseline/total_r.dat',
wave_type='nm').thin(rel_err=1e-4)
in_p.b_SED, in_p.d_SED, in_p.c_SED = cg_fn.get_template_seds(in_p)
gal = cg_fn.get_gal_cg(in_p)
meas_args = cg_fn.meas_args()
meas_args.bp = filt
psf_args = cg_fn.psf_params()
gcg, gnocg = cg_fn.calc_cg_crg(gal, meas_args, psf_args)
np.testing.assert_raises(AssertionError,
np.testing.assert_array_almost_equal,
(gcg / gnocg - 1).T[0], [0, 0], decimal=5)
# Previously measured value at default galaxy parameters
np.testing.assert_array_almost_equal((gcg / gnocg - 1).T[0],
[0.00106263, 0.00106594],
decimal=5)
def with_CRG():
"""Raise error if no cg bias in default setting"""
in_p = cg_fn.LSST_Args()
filt = galsim.Bandpass('data/baseline/total_r.dat',
wave_type='nm').thin(rel_err=1e-4)
in_p.b_SED, in_p.d_SED, in_p.c_SED = cg_fn.get_template_seds(in_p)
gal = cg_fn.get_gal_cg(in_p)
meas_args = cg_fn.meas_args()
meas_args.bp = filt
psf_args = cg_fn.psf_params()
CRG1, CRG2 = cg_fn.get_CRG_basic(gal, in_p)
gcg1, gnocg1 = cg_fn.calc_cg_crg(CRG1, meas_args, psf_args)
gcg2, gnocg2 = cg_fn.calc_cg_crg(CRG2, meas_args, psf_args)
# Previously measured value at default galaxy parameters
np.testing.assert_array_almost_equal((gcg1 / gnocg1 - 1).T[0],
[0.00128506, 0.0012862],
decimal=5)
np.testing.assert_array_almost_equal((gcg2 / gnocg2 - 1).T[0],
[0.00106303, 0.00106446],
decimal=5)
def main(Args):
"""Creates galaxy and psf images with different parametrs
and measures cg bias. Varying LSST PSF size"""
# Set disk SED name
e_s = [0.3, 0.3]
filt = Args.filter
g = np.linspace(0.005, 0.01, 2)
rt_g = np.array([g, g]).T
npix = 360
SNRs = get_rand_SNR(int(Args.size))
num = int(Args.size)
rng = galsim.BaseDeviate(int(Args.file_num))
index_table = get_table(num)
indexs = range(int(Args.file_num) * num, (int(Args.file_num) + 1) * num)
col = Column(np.ones(num) * -10, name='psf_sigma')
index_table.add_column(col)
dSED = Args.disk_SED_name
for n in range(num):
print "Computing for noise realization {0} in {1} band".format(n, filt)
index_table['NUMBER'][n] = indexs[n]
input_p = cg_fn.Eu_Args(scale=0.03,
disk_SED_name=dSED,
bulge_e=e_s,
disk_e=e_s,
psf_sig_o=0.071,
psf_w_o=806)
index_table['redshift'][n] = input_p.redshift
CRG1 = get_CRG(input_p, SNRs[n], index_table[n], rng)
# Compute CG bias
meas_args = cg_fn.meas_args(rt_g=rt_g, npix=npix)
meas_args.bp = galsim.Bandpass('data/baseline/total_%s.dat' % filt,
wave_type='nm').thin(rel_err=1e-4)
psf_args = cg_fn.psf_params()
meas_cg_bias(CRG1, index_table[n], meas_args, psf_args, 'CRG')
path = 'results/'
# path = "/nfs/slac/g/ki/ki19/deuce/AEGIS/cg_results/ref_gal_results/with_aeg_noise_all/"
op_file = path + 'ref_gal_cg_bias_{0}_band_var_noise_{1}.fits'.format(
filt, Args.file_num)
index_table.write(op_file, format='fits', overwrite=True)
print "Saving output at", op_file