def process_table(table, epochs, band, blind=True,quiet=True, report=False):
print 'Removing large boxes'
too_large_rows=np.where(table['stamp_size']>100)[0]
table.remove_rows(too_large_rows)
print "Lower casing"
lowercase(table)
lowercase(epochs)
print "Sorting and grouping"
epochs.sort(["id", "expnum"])
table.sort("identifier")
print 'Adding chi2_pixel'
chi2 = -2 * table['likelihood']
effective_npix = table['stamp_size']**2 * table['n_exposure'] * (1-table['mean_mask_fraction'])
chi2_pixel = chi2 / effective_npix
col = astropy.table.Column(name='chi2_pixel', data=chi2_pixel)
table.add_column(col)
print 'Renaming identifier->coadd_objects_ids'
table.rename_column("identifier", "coadd_objects_id")
epochs.rename_column('id', 'coadd_objects_id')
#print 'NOT NOT NOT NOT NOT NOT NOT Adding extra columns flags'
print "adding new columns"
extra_columns.add_standard_cols(table)
print 'Flagging'
#error cuts
cuts = cut_data.error_cuts + getattr(cut_data, "error_cuts_%s"%band)
flags, fractions = cut_data.compute_flags(table, cuts, verb=not quiet)
col = astropy.table.Column(name='error_flag', data=flags)
table.add_column(col)
if report:
print "INFO CUTS"
cut_data.report(cuts)
#info cuts
cuts = cut_data.info_cuts1 + getattr(cut_data, "info_cuts_%s"%band) + cut_data.info_cuts2
flags, fractions = cut_data.compute_flags(table, cuts, verb=not quiet)
col = astropy.table.Column(name='info_flag', data=flags)
table.add_column(col)
if report:
print "ERROR CUTS"
cut_data.report(cuts)
return table, epochs
#blinding
if blind:
print 'Blinding'
e1,e2 = blind_catalog.blind_arrays(table['e1'],table['e2'])
table['e1'][:] = e1
table['e2'][:] = e2
print "Reticulating splines"
return table, epochs
def _prepare_table(self, raw_catalog):
"""Carries operations to generate a standardized table."""
table = deepcopy(raw_catalog)
# make notation for 'ra' and 'dec' standard across code.
table.rename_column("RA", "ra")
table.rename_column("DEC", "dec")
table.rename_column("MAG", "ref_mag")
index = np.arange(0, len(table))
# convert ra dec from degrees to arcsec in catalog.
table["ra"] *= 3600
table["dec"] *= 3600
size = raw_catalog["flux_radius"] * raw_catalog["PIXEL_SCALE"]
table["btk_size"] = size
table["btk_index"] = index
return table
def _prepare_table(self):
table = deepcopy(self._raw_catalog)
# make notation for 'ra' and 'dec' standard across code.
table.rename_column("RA", "ra")
table.rename_column("DEC", "dec")
table.rename_column("MAG", "ref_mag")
index = np.where(t["IDENT_1"] == self._raw_catalog["IDENT_1"]
for t in table)
# convert ra dec from degrees to arcsec in catalog.
table["ra"] *= 3600
table["dec"] *= 3600
size = self._raw_catalog["flux_radius"] * self._raw_catalog[
"PIXEL_SCALE"]
table["btk_size"] = size
table["btk_index"] = index
# ADds the extra columns to both catalogs just to be sure
self._raw_catalog["ref_mag"] = self._raw_catalog["MAG"]
self._raw_catalog["btk_size"] = size
return table
def lowercase(table):
for col in table.colnames[:]:
if col!=col.lower():
table.rename_column(col, col.lower())
