def _format_obs_history(obs_history, field_ids, save_to_disk=None):
obs_history = obs_history.loc[obs_history['Field_fieldID'].isin(
field_ids)].copy()
# Some unit conversion and column renaming
obs_history['Ixx_PSF'] = units.fwhm_to_sigma(
obs_history['finSeeing'].values)**2.0
obs_history['apFluxErr'] = units.mag_to_flux(
obs_history['fiveSigmaDepth'].values - 22.5) / 5.0
obs_history = obs_history.rename(
{
'filtSkyBrightness': 'sky',
'obsHistID': 'ccdVisitId'
}, axis=1)
# Only keep columns we'll need
obs_keep_cols = [
'ccdVisitId',
'Field_fieldID',
'expMJD',
'Ixx_PSF',
'apFluxErr',
'sky',
'filter',
]
obs_history = obs_history[obs_keep_cols]
if save_to_disk is not None:
obs_history.to_csv(save_to_disk, index=False)
return obs_history
def _format_truth_catalog(point_neighbors, save_to_disk=None):
# Point-source neighbors
point_neighbors[['ra', 'dec'
]] = units.deg_to_arcsec(point_neighbors[['ra', 'dec']])
for bp in 'ugrizy':
point_neighbors['flux_%s' % bp] = units.mag_to_flux(
point_neighbors[bp].values, to_unit='nMgy')
if save_to_disk is not None:
point_neighbors.to_csv(save_to_disk, index=False)
return point_neighbors
def _format_obs_history(obs_history, field, save_to_disk=None):
"""
Parameters
----------
obs_history : Pandas.DataFrame
field : Pandas.DataFrame
save_to_disk : str
Note
----
We use the dithered RA, Dec and express all positions in arcsec.
Returns
-------
DataFrame obs_history, formatted with new column conventions and units
"""
# Join with Field table
obs_history = pd.merge(obs_history,
field,
left_on='Field_fieldID',
right_on='fieldID')
# Some unit conversion and column renaming
# NOTE: OpSim DB defines dithered positions as offset from the field center.
obs_history['ditheredRA'] = units.deg_to_arcsec(
obs_history['ditheredRA'].values + obs_history['fieldRA'].values)
obs_history['ditheredDec'] = units.deg_to_arcsec(
obs_history['ditheredDec'].values + obs_history['fieldDec'].values)
obs_history['Ixx_PSF'] = units.fwhm_to_sigma(
obs_history['finSeeing'].values)**2.0
obs_history['apFluxErr'] = units.mag_to_flux(
obs_history['fiveSigmaDepth'].values - 22.5) / 5.0
obs_history = obs_history.rename(
{
'filtSkyBrightness': 'sky',
'obsHistID': 'ccdVisitId'
}, axis=1)
# Only keep columns we'll need
obs_keep_cols = [
'ccdVisitId',
'Field_fieldID',
'expMJD',
'ditheredRA',
'ditheredDec',
'Ixx_PSF',
'apFluxErr',
'sky',
'filter',
]
obs_history = obs_history[obs_keep_cols]
obs_history['ccdVisitId'] = obs_history['ccdVisitId'].astype(np.int64)
if save_to_disk is not None:
obs_history.to_csv(save_to_disk, index=False)
return obs_history
def _format_extragal_catalog(galaxies, save_to_disk=None):
# Unit conversion and column renaming
filters = list('ugrizy')
galaxies.columns = map(str.lower, galaxies.columns)
galaxies[['ra',
'dec']] = units.deg_to_arcsec(galaxies[['ra_true', 'dec_true']])
galaxies['phi_bulge'] = units.e1e2_to_phi(
e1=galaxies['ellipticity_1_bulge_true'].values,
e2=galaxies['ellipticity_2_bulge_true'].values)
galaxies['phi_disk'] = units.e1e2_to_phi(
e1=galaxies['ellipticity_1_disk_true'].values,
e2=galaxies['ellipticity_2_disk_true'].values)
galaxies['disk_to_total_ratio'] = 1.0 - galaxies['bulge_to_total_ratio_i']
for bp in 'ugrizy':
galaxies['flux_%s' % bp] = units.mag_to_flux(
galaxies['mag_true_%s_lsst' % bp].values, to_unit='nMgy')
galaxies['flux_disk_%s' % bp] = galaxies[
'flux_%s' % bp].values * galaxies['disk_to_total_ratio'].values
galaxies['flux_bulge_%s' % bp] = galaxies[
'flux_%s' % bp].values * galaxies['bulge_to_total_ratio_i'].values
for component in ['disk', 'bulge']:
galaxies['ra_%s' % component] = galaxies['ra'].values
galaxies['dec_%s' % component] = galaxies['dec'].values
galaxies['size_circular_%s' % component] = (
galaxies['size_minor_%s_true' % component].values *
galaxies['size_%s_true' % component].values)**0.5
galaxies['e_%s' % component] = galaxies['ellipticity_%s_true' %
component]
# Only keep columns we'll use
galaxies_cols_to_keep = ['galaxy_id', 'ra',
'dec'] # 'agn', 'sprinkled', 'star']
galaxies_cols_to_keep += [
'ra_bulge', 'dec_bulge', 'size_circular_bulge', 'e_bulge', 'phi_bulge'
]
galaxies_cols_to_keep += [
'ra_disk', 'dec_disk', 'size_circular_disk', 'e_disk', 'phi_disk'
]
galaxies_cols_to_keep += [
prop + '_' + bp
for prop, bp in product(['flux_bulge', 'flux_disk'], filters)
]
galaxies = galaxies[galaxies_cols_to_keep]
if save_to_disk is not None:
galaxies.to_csv(save_to_disk, index=False)
return galaxies