def test_measureXYZUVW():
"""Check measurements of xyzuvw_now to astrometry occur properly.
Will use extremely dense component as case study as this ensures stars
all have more or less the same true values"""
compact_comp_pars = np.copy(PARS[0])
compact_comp_pars[6] = 1e-15
compact_comp_pars[7] = 1e-15
compact_comp_pars[8] = 1e-15
starcounts = [1000]
sd = SynthData(pars=np.array([compact_comp_pars]),
starcounts=starcounts,
Components=COMPONENTS)
sd.generate_all_init_cartesian()
sd.project_stars()
sd.measure_astrometry()
for colname in SynthData.DEFAULT_ASTR_COLNAMES:
assert np.allclose(sd.GERROR[colname + '_error'],
sd.table[colname + '_error'])
# Check spread of data is similar to Gaia error, we use
# a large tolerance so a small number of stars can be used
assert np.isclose(sd.GERROR[colname + '_error'],
np.std(sd.table[colname]),
rtol=1e-1)
def test_projectStars():
"""Check that the mean of stars after projection matches the mean
of the component after projection"""
starcounts = (int(1e3),)
sd = SynthData(pars=PARS[:1], starcounts=starcounts, Components=COMPONENTS)
sd.generate_all_init_cartesian()
sd.project_stars()
comp_mean_now, comp_covmatrix_now = \
sd.components[0].get_currentday_projection()
final_xyzuvw = sd.extract_data_as_array([dim + '_now' for dim in 'xzyuvw'])
assert np.allclose(comp_mean_now, final_xyzuvw.mean(axis=0), atol=1.)
def test_measureXYZUVW():
"""Check measurements of xyzuvw_now to astrometry occur properly.
Will use extremely dense component as case study as this ensures stars
all have more or less the same true values"""
compact_comp_pars = np.copy(PARS[0])
compact_comp_pars[6] = 1e-15
compact_comp_pars[7] = 1e-15
compact_comp_pars[8] = 1e-15
starcounts = [1000]
sd = SynthData(pars=np.array([compact_comp_pars]), starcounts=starcounts,
Components=COMPONENTS)
sd.generate_all_init_cartesian()
sd.project_stars()
sd.measure_astrometry()
for colname in SynthData.DEFAULT_ASTR_COLNAMES:
assert np.allclose(sd.GERROR[colname + '_error'],
sd.table[colname + '_error'])
# Check spread of data is similar to Gaia error, we use
# a large tolerance so a small number of stars can be used
assert np.isclose(sd.GERROR[colname + '_error'],
np.std(sd.table[colname]),
rtol=1e-1)
