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catalog.py
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catalog.py
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import _pp_conf
from pandas import read_sql
"""
CATALOG - class structure for dealing with astronomical catalogs,
FITS_LDAC files, and sqlite databases.
version 0.9, 2016-01-27, [email protected]
"""
# Photometry Pipeline
# Copyright (C) 2016-2018 Michael Mommert, [email protected]
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
# You should have received a copy of the GNU General Public License
# along with this program. If not, see
# <http://www.gnu.org/licenses/>.
import os
import sys
import logging
import numpy as np
import sqlite3 as sql
import astropy.units as u
import astropy.coordinates as coord
from astropy.table import Table, Column
from astropy import __version__ as astropyversion
from astropy.io import fits
import scipy.optimize as optimization
import warnings
warnings.simplefilter("ignore", UserWarning)
try:
from scipy import spatial
except ImportError:
print('Module scipy not found. Please install with: pip install scipy')
sys.exit()
try:
from astroquery.vizier import Vizier
from astroquery.sdss import SDSS
except ImportError:
print('Module astroquery not found. Please install with: pip install '
'astroquery')
sys.exit()
# translates numpy datatypes to sql-readable datatypes
sql.register_adapter(np.float64, float)
sql.register_adapter(np.float32, float)
sql.register_adapter(np.int64, int)
sql.register_adapter(np.int32, int)
# import pp modules
# setup logging
logging.basicConfig(filename=_pp_conf.log_filename,
level=_pp_conf.log_level,
format=_pp_conf.log_formatline,
datefmt=_pp_conf.log_datefmt)
class catalog(object):
def __init__(self, catalogname, display=False):
self.data = None # will be an astropy table
self.catalogname = catalogname
self.obstime = [None, None] # observation midtime (JD) +
# duration
self.obj = None # header target name
self.origin = '' # where does the data come from?
self.history = '' # catalog history
self.magsys = '' # [AB|Vega|instrumental]
self.display = display
self.filtername = None
# data access functions
@property
def shape(self):
"""
return: tuple of number of sources and fields
"""
try:
return (len(self.data), len(self.fields))
except AttributeError:
return (len(self.data), len(self.data.columns))
@property
def fields(self):
"""
return: array of all available fields
"""
return self.data.columns
def __getitem__(self, ident):
"""
return: source or field
"""
return self.data[ident]
# data manipulation functions
def reject_sources_other_than(self, condition):
"""
reject sources based on condition
input: condition
return: number of sources left
"""
n_raw = self.shape[0]
self.data = self.data[condition]
logging.info('{:s}:reject {:d} sources'.format(self.catalogname,
n_raw-self.shape[0]))
return len(self.data)
def reject_sources_with(self, condition):
"""
reject sources based on condition
input: condition
return: number of sources left
"""
n_raw = self.shape[0]
self.data = self.data[~condition]
logging.info('{:s}:reject {:d} sources'.format(self.catalogname,
n_raw-self.shape[0]))
return n_raw - len(self.data)
def add_field(self, field_name, field_array, field_type=None):
"""
single-field wrapper for add_fields
"""
if field_type is not None:
return self.data.add_column(Column(field_array, name=field_name,
format=field_type))
else:
return self.data.add_column(Column(field_array, name=field_name))
def add_fields(self, field_names, field_arrays, field_types=None):
"""
add fields to self.data
input: field_names, field_arrays, field_types
output: number of added fields
"""
assert len(field_names) == len(field_arrays)
if self.data is None:
self.data = Table()
for i in range(len(field_names)):
if field_types is None:
self.data.add_column(Column(np.array(field_arrays[i]),
name=field_names[i]))
else:
self.data.add_column(Column(np.array(field_arrays[i]),
name=field_names[i],
format=field_types[i]))
return len(field_arrays)
# data io
# online catalog access
def download_catalog(self, ra_deg, dec_deg, rad_deg,
max_sources, save_catalog=False,
max_mag=21, use_all_stars=False):
"""
download existing catalog from VIZIER server using self.catalogname
input: ra_deg, dec_deg, rad_deg, max_sources, (display_progress),
(sort=['ascending', 'descending', None])
return: number of sources downloaded
astrometric catalogs: ra_deg, dec_deg, e_ra_deg, e_dec_deg,
mag, e_mag, [epoch_jd, Gaia only]
photometric catalogs: ra_deg, dec_deg, e_ra_deg, e_dec_deg,
[mags], [e_mags], epoch_jd
"""
# setup Vizier query
# note: column filters uses original Vizier column names
# -> green column names in Vizier
if self.display:
print(('query Vizier for {:s} at {:7.3f}/{:+.3f} in '
+ 'a {:.2f} deg radius').format(self.catalogname,
ra_deg, dec_deg,
rad_deg),
end=' ', flush=True)
logging.info(('query Vizier for {:s} at {:7.3f}/{:+.3f} in '
+ 'a {:.2f} deg radius').format(self.catalogname,
ra_deg, dec_deg,
rad_deg))
field = coord.SkyCoord(ra=ra_deg, dec=dec_deg, unit=(u.deg, u.deg),
frame='icrs')
# -----------------------------------------------------------------
# use vizier query for Pan-STARRS
if self.catalogname == 'PANSTARRS':
vquery = Vizier(columns=['objID', 'RAJ2000', 'DEJ2000',
'e_RAJ2000', 'e_DEJ2000',
'gmag', 'e_gmag',
'rmag', 'e_rmag',
'imag', 'e_imag',
'zmag', 'e_zmag',
'ymag', 'e_ymag'],
column_filters={"rmag":
("<{:f}".format(max_mag))},
row_limit=max_sources,
timeout=300)
try:
self.data = vquery.query_region(field,
radius=rad_deg*u.deg,
catalog="II/349/ps1",
cache=False)[0]
except IndexError:
if self.display:
print('no data available from {:s}'.format(
self.catalogname))
logging.error('no data available from {:s}'.format(
self.catalogname))
return 0
# rename column names using PP conventions
self.data.rename_column('objID', 'ident')
self.data.rename_column('RAJ2000', 'ra_deg')
self.data.rename_column('DEJ2000', 'dec_deg')
self.data.rename_column('e_RAJ2000', 'e_ra_deg')
self.data['e_ra_deg'].convert_unit_to(u.deg)
self.data.rename_column('e_DEJ2000', 'e_dec_deg')
self.data['e_dec_deg'].convert_unit_to(u.deg)
self.data.rename_column('gmag', 'gp1mag')
self.data.rename_column('e_gmag', 'e_gp1mag')
self.data.rename_column('rmag', 'rp1mag')
self.data.rename_column('e_rmag', 'e_rp1mag')
self.data.rename_column('imag', 'ip1mag')
self.data.rename_column('e_imag', 'e_ip1mag')
self.data.rename_column('zmag', 'zp1mag')
self.data.rename_column('e_zmag', 'e_zp1mag')
self.data.rename_column('ymag', 'yp1mag')
self.data.rename_column('e_ymag', 'e_yp1mag')
self.data['mag'] = self.data['rp1mag'] # use rmag for astrometry
# clip self.data to enforce magnitude error limits
if not use_all_stars:
self.data = self.data[self.data['e_rp1mag'] <= 0.03]
# --------------------------------------------------------------------
# use astroquery vizier query for SkyMapper
elif self.catalogname == 'SkyMapper':
vquery = Vizier(columns=['all'],
column_filters={"rPSF":
("<{:f}".format(max_mag))},
row_limit=max_sources,
timeout=300)
try:
self.data = vquery.query_region(field,
radius=rad_deg*u.deg,
catalog="II/358/smss",
cache=False)[0]
except IndexError:
if self.display:
print('no data available from {:s}'.format(
self.catalogname))
logging.error('no data available from {:s}'.format(
self.catalogname))
return 0
# throw out columns we don't need
new_data = Table(self.data)
for col in self.data.columns:
if col not in ['ObjectId', 'RAICRS', 'DEICRS',
'e_RAICRS', 'e_DEICRS',
'uPSF', 'e_uPSF',
'vPSF', 'e_vPSF',
'gPSF', 'e_gPSF',
'rPSF', 'e_rPSF',
'zPSF', 'e_zPSF',
'iPSF', 'e_iPSF']:
new_data.remove_column(col)
self.data = new_data
# rename column names using PP conventions
self.data.rename_column('ObjectId', 'ident')
self.data.rename_column('RAICRS', 'ra_deg')
self.data.rename_column('DEICRS', 'dec_deg')
self.data.rename_column('e_RAICRS', 'e_ra_deg')
self.data['e_ra_deg'].convert_unit_to(u.deg)
self.data.rename_column('e_DEICRS', 'e_dec_deg')
self.data['e_dec_deg'].convert_unit_to(u.deg)
#self.data.rename_column('uPSF', 'umag')
#self.data.rename_column('e_uPSF', 'e_umag')
self.data.rename_column('vPSF', 'vsmmag')
self.data.rename_column('e_vPSF', 'e_vsmmag')
self.data.rename_column('gPSF', 'gsmmag')
self.data.rename_column('e_gPSF', 'e_gsmmag')
self.data.rename_column('rPSF', 'rsmmag')
self.data.rename_column('e_rPSF', 'e_rsmmag')
self.data.rename_column('iPSF', 'ismmag')
self.data.rename_column('e_iPSF', 'e_ismmag')
self.data.rename_column('zPSF', 'zsmmag')
self.data.rename_column('e_zPSF', 'e_zsmmag')
if not use_all_stars:
self.data = self.data[self.data['e_rsmmag'] <= 0.03]
# --------------------------------------------------------------------
elif self.catalogname == 'GAIA':
# astrometric and photometric catalog (as of DR2)
vquery = Vizier(columns=['Source', 'RA_ICRS', 'DE_ICRS',
'e_RA_ICRS', 'e_DE_ICRS', 'pmRA',
'pmDE', 'Epoch',
'Gmag', 'e_Gmag',
'BPmag', 'e_BPmag',
'RPmag', 'eRPmag'],
column_filters={"phot_g_mean_mag":
("<{:f}".format(max_mag))},
row_limit=max_sources,
timeout=300)
try:
self.data = vquery.query_region(field,
radius=rad_deg*u.deg,
catalog="I/345/gaia2",
cache=False)[0]
except IndexError:
if self.display:
print('no data available from {:s}'.format(
self.catalogname))
logging.error('no data available from {:s}'.format(
self.catalogname))
return 0
# rename column names using PP conventions
self.data.rename_column('Source', 'ident')
self.data.rename_column('RA_ICRS', 'ra_deg')
self.data.rename_column('DE_ICRS', 'dec_deg')
self.data.rename_column('e_RA_ICRS', 'e_ra_deg')
self.data['e_ra_deg'].convert_unit_to(u.deg)
self.data.rename_column('e_DE_ICRS', 'e_dec_deg')
self.data['e_dec_deg'].convert_unit_to(u.deg)
self.data.rename_column('Epoch', 'epoch_yr')
self.data['mag'] = self.data['Gmag'] # required for scamp
# TBD:
# - implement proper error ellipse handling
# - implement propor motion handling for DR2
# --------------------------------------------------------------------
elif self.catalogname == 'USNO-B1':
# astrometric and photometric catalog
vquery = Vizier(columns=['USNO-B1.0', 'RAJ2000', 'DEJ2000',
'e_RAJ2000', 'e_DEJ2000',
'R2mag'],
column_filters={"R2mag":
("<{:f}".format(max_mag))},
row_limit=max_sources,
timeout=300)
try:
self.data = vquery.query_region(field,
radius=rad_deg*u.deg,
catalog="I/284/out",
cache=False)[0]
except IndexError:
if self.display:
print('no data available from {:s}'.format(
self.catalogname))
logging.error('no data available from {:s}'.format(
self.catalogname))
return 0
# rename column names using PP conventions
self.data.rename_column('USNO-B1.0', 'ident')
self.data.rename_column('RAJ2000', 'ra_deg')
self.data.rename_column('DEJ2000', 'dec_deg')
self.data.rename_column('e_RAJ2000', 'e_ra_deg')
self.data['e_ra_deg'].convert_unit_to(u.deg)
self.data.rename_column('e_DEJ2000', 'e_dec_deg')
self.data['e_dec_deg'].convert_unit_to(u.deg)
self.data['mag'] = self.data['R2mag'] # required for scamp
# --------------------------------------------------------------------
elif self.catalogname == 'TGAS':
# astrometric catalog
vquery = Vizier(columns=['Source', 'RA_ICRS', 'DE_ICRS',
'e_RA_ICRS', 'e_DE_ICRS', 'pmRA',
'pmDE', 'phot_g_mean_mag'],
column_filters={"phot_g_mean_mag":
("<{:f}".format(max_mag))},
row_limit=max_sources,
timeout=300)
try:
self.data = vquery.query_region(field,
radius=rad_deg*u.deg,
catalog="I/337/tgas",
cache=False)[0]
except IndexError:
if self.display:
print('no data available from {:s}'.format(
self.catalogname))
logging.error('no data available from {:s}'.format(
self.catalogname))
return 0
# rename column names using PP conventions
self.data.rename_column('Source', 'ident')
self.data.rename_column('RA_ICRS', 'ra_deg')
self.data.rename_column('DE_ICRS', 'dec_deg')
self.data.rename_column('e_RA_ICRS', 'e_ra_deg')
self.data['e_ra_deg'].convert_unit_to(u.deg)
self.data.rename_column('e_DE_ICRS', 'e_dec_deg')
self.data['e_dec_deg'].convert_unit_to(u.deg)
self.data.rename_column('__Gmag_', 'mag')
self.data.add_column(Column(np.ones(len(self.data))*2457023.5,
name='epoch_jd', unit=u.day))
# TBD:
# - implement pm progragation
# - implement proper error ellipse handling
elif self.catalogname == '2MASS':
# photometric catalog
vquery = Vizier(columns=['2MASS', 'RAJ2000', 'DEJ2000', 'errMaj',
'errMin', 'errPA', 'Jmag', 'e_Jmag',
'Hmag', 'e_Hmag', 'Kmag', 'e_Kmag',
'Qflg', 'Rflg'],
column_filters={"Jmag":
("<{:f}".format(max_mag))},
row_limit=max_sources)
try:
self.data = vquery.query_region(field,
radius=rad_deg*u.deg,
catalog="II/246/out",
cache=False)[0]
except IndexError:
if self.display:
print('no data available from {:s}'.format(
self.catalogname))
logging.error('no data available from {:s}'.format(
self.catalogname))
return 0
# filter columns to only have really good detections
# see the Vizier webpage for a description of what the flags mean
if not use_all_stars:
Qflags = set('ABC') # only A, B, or C flagged detections
qmask = [True if not set(item).difference(Qflags) else False
for item in self.data['Qflg']]
# filter columns to only have really good detections
self.data = self.data[qmask]
# rename column names using PP conventions
self.data.rename_column('_2MASS', 'ident')
self.data.rename_column('RAJ2000', 'ra_deg')
self.data.rename_column('DEJ2000', 'dec_deg')
self.data.rename_column('Kmag', 'Ksmag')
self.data.rename_column('e_Kmag', 'e_Ksmag')
self.data['mag'] = self.data['Jmag'] # use J as default mag
# determine RA and Dec positional uncertainties and
# add respective columns
self.data['errPA'][self.data['errPA'] == 0] = 1 # workaround
arc_xopt = np.arctan(-self.data['errMin']/self.data['errMaj'] *
np.tan(self.data['errPA'].to(u.rad)))
ra_err = abs(self.data['errMaj']*np.cos(arc_xopt) *
np.cos(self.data['errPA'].to(u.rad)) -
self.data['errMin']*np.sin(arc_xopt) *
np.sin(self.data['errPA'].to(u.rad)))
self.data.add_column(Column(data=ra_err*1000,
name='e_ra_deg', unit=u.mas),
index=2)
arc_yopt = np.arctan(self.data['errMin']/self.data['errMaj'] *
np.cos(self.data['errPA'].to(u.rad)) /
np.sin(self.data['errPA'].to(u.rad)))
dec_err = abs(self.data['errMaj']*np.cos(arc_yopt) *
np.sin(self.data['errPA'].to(u.rad)) +
self.data['errMin']*np.sin(arc_yopt) *
np.cos(self.data['errPA'].to(u.rad)))
self.data.add_column(Column(data=dec_err*1000,
name='e_dec_deg', unit=u.mas), index=3)
# remove error ellipse columns
self.data.remove_column('errMaj')
self.data.remove_column('errMin')
self.data.remove_column('errPA')
elif self.catalogname == 'URAT-1':
# astrometric catalog
vquery = Vizier(columns=['URAT1', 'RAJ2000', 'DEJ2000',
'sigm', 'f.mag', 'e_f.mag', ],
column_filters={"f.mag":
("<{:f}".format(max_mag))},
row_limit=max_sources)
try:
self.data = vquery.query_region(field,
radius=rad_deg*u.deg,
catalog="I/329/urat1",
cache=False)[0]
except IndexError:
if self.display:
print('no data available from {:s}'.format(
self.catalogname))
logging.error('no data available from {:s}'.format(
self.catalogname))
return 0
# rename column names using PP conventions
self.data.rename_column('URAT1', 'ident')
self.data.rename_column('RAJ2000', 'ra_deg')
self.data.rename_column('DEJ2000', 'dec_deg')
self.data.rename_column('f.mag', 'mag')
self.data.rename_column('e_f.mag', 'e_mag')
self.data.add_column(Column(data=self.data['sigm'].data,
name='e_ra_deg',
unit=self.data['sigm'].unit),
index=2)
self.data.add_column(Column(data=self.data['sigm'].data,
name='e_dec_deg',
unit=self.data['sigm'].unit),
index=4)
self.data.remove_column('sigm')
elif self.catalogname == 'APASS9':
# photometric catalog
vquery = Vizier(columns=['recno', 'RAJ2000', 'DEJ2000',
'e_RAJ2000',
'e_DEJ2000', 'Vmag', 'e_Vmag',
'Bmag', 'e_Bmag', "g'mag", "e_g'mag",
"r'mag", "e_r'mag", "i'mag", "e_i'mag"],
column_filters={"Vmag":
("<{:f}".format(max_mag))},
row_limit=max_sources)
try:
self.data = vquery.query_region(field,
radius=rad_deg*u.deg,
catalog="II/336/apass9",
cache=False)[0]
except IndexError:
if self.display:
print('no data available from {:s}'.format(
self.catalogname))
logging.error('no data available from {:s}'.format(
self.catalogname))
return 0
# rename column names using PP conventions
self.data.rename_column('recno', 'ident')
self.data.rename_column('RAJ2000', 'ra_deg')
self.data.rename_column('DEJ2000', 'dec_deg')
self.data.rename_column('e_RAJ2000', 'e_ra_deg')
self.data.rename_column('e_DEJ2000', 'e_dec_deg')
self.data.rename_column('g_mag', 'gmag')
self.data.rename_column('e_g_mag', 'e_gmag')
self.data.rename_column('r_mag', 'rmag')
self.data.rename_column('e_r_mag', 'e_rmag')
self.data.rename_column('i_mag', 'imag')
self.data.rename_column('e_i_mag', 'e_imag')
elif self.catalogname == 'SDSS-R9':
vquery = Vizier(columns=['SDSS9', 'RA_ICRS', 'DE_ICRS',
'e_RA_ICRS',
'e_DE_ICRS', 'umag', 'e_umag',
'gmag', 'e_gmag', 'rmag', 'e_rmag',
'imag', 'e_imag', 'zmag', 'e_zmag'],
column_filters={"gmag":
("<{:f}".format(max_mag)),
"mode": "1",
"q_mode": "+"},
row_limit=max_sources)
try:
self.data = vquery.query_region(field,
radius=rad_deg*u.deg,
catalog="V/139/sdss9",
cache=False)[0]
except IndexError:
if self.display:
print('no data available from {:s}'.format(
self.catalogname))
logging.error('no data available from {:s}'.format(
self.catalogname))
return 0
# rename column names using PP conventions
self.data.rename_column('SDSS9', 'ident')
self.data.rename_column('RA_ICRS', 'ra_deg')
self.data.rename_column('DE_ICRS', 'dec_deg')
self.data.rename_column('e_RA_ICRS', 'e_ra_deg')
self.data.rename_column('e_DE_ICRS', 'e_dec_deg')
# perform correction to AB system for SDSS
# http://www.sdss3.org/dr8/algorithms/fluxcal.php#SDSStoAB
self.data['umag'] -= 0.04
self.data['zmag'] += 0.02
self.data['mag'] = self.data['rmag'] # use rmag for astrometry
elif self.catalogname == 'SDSS-R13':
try:
self.data = SDSS.query_region(
field,
radius=("{:f}d".format(rad_deg)),
photoobj_fields=['objID', 'ra',
'dec',
'raErr',
'decErr',
'fiberMag_u',
'fiberMagErr_u',
'fiberMag_g',
'fiberMagErr_g',
'fiberMag_r',
'fiberMagErr_r',
'fiberMag_i',
'fiberMagErr_i',
'fiberMag_z',
'fiberMagErr_z',
'mode',
'clean',
'type'],
timeout=180,
data_release=13,
cache=False)
except IndexError:
if self.display:
print('no data available from {:s}'.format(
self.catalogname))
logging.error('no data available from {:s}'.format(
self.catalogname))
return 0
# apply some quality masks
if not use_all_stars:
try:
mask_primary = self.data['mode'] == 1
mask_clean = self.data['clean'] == 1
mask_star = self.data['type'] == 6
mask_bright = self.data['fiberMag_g'] < max_mag
mask = mask_primary & mask_clean & mask_star & mask_bright
except TypeError:
if self.display:
print('no data available from {:s}'.format(
self.catalogname))
logging.error('no data available from {:s}'.format(
self.catalogname))
return 0
self.data = self.data[mask]
# rename column names using PP conventions
self.data.rename_column('objID', 'ident')
self.data.rename_column('ra', 'ra_deg')
self.data.rename_column('dec', 'dec_deg')
self.data.rename_column('raErr', 'e_ra_deg')
self.data.rename_column('decErr', 'e_dec_deg')
self.data.rename_column('fiberMag_u', 'umag')
self.data.rename_column('fiberMagErr_u', 'e_umag')
self.data.rename_column('fiberMag_g', 'gmag')
self.data.rename_column('fiberMagErr_g', 'e_gmag')
self.data.rename_column('fiberMag_r', 'rmag')
self.data.rename_column('fiberMagErr_r', 'e_rmag')
self.data.rename_column('fiberMag_i', 'imag')
self.data.rename_column('fiberMagErr_i', 'e_imag')
self.data.rename_column('fiberMag_z', 'zmag')
self.data.rename_column('fiberMagErr_z', 'e_zmag')
self.data['mag'] = self.data['rmag'] # use rmag for astrometry
# perform correction to AB system for SDSS
# http://www.sdss3.org/dr8/algorithms/fluxcal.php#SDSStoAB
self.data['umag'] -= 0.04
self.data['zmag'] += 0.02
# make sure our RA/DEC errors have units
self.data['e_ra_deg'] = self.data['e_ra_deg'] * u.arcsec
self.data['e_dec_deg'] = self.data['e_dec_deg'] * u.arcsec
else:
if self.display:
print('catalog {:s} not available.'.format(
self.catalogname))
logging.error('catalog {:s} not available.'.format(
self.catalogname))
return 0
if self.display:
print('{:d} sources retrieved.'.format(len(self.data)))
logging.info('{:d} sources retrieved'.format(len(self.data)))
self.history = '{:d} sources downloaded'.format(len(self.data))
# convert all coordinate uncertainties to degrees
self.data['e_ra_deg'] = self.data['e_ra_deg'].to(u.deg)
self.data['e_dec_deg'] = self.data['e_dec_deg'].to(u.deg)
# set catalog magnitude system
self.magsystem = _pp_conf.allcatalogs_magsys[self.catalogname]
# write ldac catalog
if save_catalog:
self.write_ldac(self.catalogname+'.cat')
return self.shape[0]
# FITS/LDAC interface
def read_ldac(self, filename, fits_filename=None, maxflag=None,
time_keyword='MIDTIMJD', exptime_keyword='EXPTIME',
object_keyword='OBJECT', telescope_keyword='TEL_KEYW'):
"""
read in FITS_LDAC file
input: LDAC filename
return: (number of sources, number of fields)
"""
# load LDAC file
hdulist = fits.open(filename, ignore_missing_end=True)
if len(hdulist) < 3:
print(('ERROR: {:s} seems to be empty; check LOG file if ' +
'Source Extractor ran properly').format(filename))
logging.error(('ERROR: {:s} seems to be empty; '
'check LOG file if ' +
'Source Extractor ran properly').format(
filename))
return None
# load data array
self.data = Table(hdulist[2].data)
# set other properties
telescope = ''
for line in hdulist[1].data[0][0]:
if telescope_keyword in line:
telescope = line.split('\'')[1]
self.catalogname = filename
if fits_filename is not None:
self.origin = '{:s};{:s}'.format(telescope.strip(), fits_filename)
else:
self.origin = '{:s};'.format(telescope.strip())
self.magsys = 'instrumental'
# reject flagged sources (if requested)
if maxflag is not None:
self.reject_sources_other_than(self.data['FLAGS'] <= maxflag)
# FLAGS <= 3: allow for blending and nearby sources
# read data from image header, if requested
if fits_filename is not None:
fitsheader = fits.open(fits_filename,
ignore_missing_end=True)[0].header
self.obstime[0] = float(fitsheader[time_keyword])
self.obstime[1] = float(fitsheader[exptime_keyword])
self.obj = fitsheader[object_keyword]
# rename columns
if 'XWIN_WORLD' in self.fields:
self.data.rename_column('XWIN_WORLD', 'ra_deg')
if 'YWIN_WORLD' in self.fields:
self.data.rename_column('YWIN_WORLD', 'dec_deg')
# force positive RA values
flip_idc = np.where(self.data['ra_deg'] < 0)[0]
self.data['ra_deg'][flip_idc] += 360
logging.info(('read {:d} sources in {:d} columns '
'from LDAC file {:s}').format(
self.shape[0], self.shape[1], filename))
hdulist.close()
return self.shape
def write_ldac(self, ldac_filename):
"""
write data in new FITS_LDAC file (mainly for use in SCAMP)
input: filename, ra/dec field names, projection_type
return: number of sources written to file
"""
# create primary header (empty)
primaryhdu = fits.PrimaryHDU(header=fits.Header())
# create header table
hdr_col = fits.Column(name='Field Header Card', format='1680A',
array=["obtained through Vizier"])
hdrhdu = fits.BinTableHDU.from_columns(fits.ColDefs([hdr_col]))
hdrhdu.header['EXTNAME'] = ('LDAC_IMHEAD')
# hdrhdu.header['TDIM1'] = ('(80, 36)') # remove?
# create data table
colname_dic = {'ra_deg': 'XWIN_WORLD', 'dec_deg': 'YWIN_WORLD',
'e_ra_deg': 'ERRAWIN_WORLD',
'e_dec_deg': 'ERRBWIN_WORLD',
'mag': 'MAG'}
format_dic = {'ra_deg': '1D', 'dec_deg': '1D',
'e_ra_deg': '1E',
'e_dec_deg': '1E',
'mag': '1E'}
#disp_dic = {'ra_deg': 'F13.8', 'dec_deg': 'F13.8',
# 'e_ra_deg': 'F13.8',
# 'e_dec_deg': 'F13.8',
# 'mag': 'F8.4'}
unit_dic = {'ra_deg': 'deg', 'dec_deg': 'deg',
'e_ra_deg': 'deg',
'e_dec_deg': 'deg',
'mag': 'mag'}
data_cols = []
for col_name in self.data.columns:
if not col_name in list(colname_dic.keys()):
continue
data_cols.append(fits.Column(name=colname_dic[col_name],
format=format_dic[col_name],
array=self.data[col_name],
unit=unit_dic[col_name]))
#,disp=disp_dic[col_name]))
data_cols.append(fits.Column(name='MAGERR',
disp='F8.4',
format='1E',
unit='mag',
array=np.ones(len(self.data))*0.01))
data_cols.append(fits.Column(name='OBSDATE',
disp='F13.8',
format='1D',
unit='yr',
array=np.ones(len(self.data))*2015.0))
datahdu = fits.BinTableHDU.from_columns(fits.ColDefs(data_cols))
datahdu.header['EXTNAME'] = ('LDAC_OBJECTS')
nsrc = len(self.data)
# # combine HDUs and write file
hdulist = fits.HDUList([primaryhdu, hdrhdu, datahdu])
if float(astropyversion.split('.')[0]) > 1:
hdulist.writeto(ldac_filename, overwrite=True)
elif float(astropyversion.split('.')[1]) >= 3:
hdulist.writeto(ldac_filename, overwrite=True)
else:
hdulist.writeto(ldac_filename, clobber=True)
logging.info('wrote {:d} sources from {:s} to LDAC file'.format(
nsrc, ldac_filename))
return nsrc
# ascii interface
def write_table(self, filename, format='ascii'):
"""
write catalog to file using astropy.table.Table.write
input: target filename, file format
return: number of sources written to file
"""
# write data into file
self.data.write(filename, format=format)
logging.info('wrote %d sources from %s to file %s' %
(self.shape[0], self.catalogname, filename))
return self.shape[0]
# SQLite interface
def write_database(self, filename):
"""
write catalog object to SQLite database file
input: target filename
output: number of sources written to file
"""
# open database file (delete existing ones)
os.remove(filename) if os.path.exists(filename) else None
db_conn = sql.connect(filename)
db = db_conn.cursor()
from copy import deepcopy
write_table = deepcopy(self.data)
# rename Johnson filternames to avoid collisions with SDSS
for filtername in ['B', 'V', 'R', 'I']:
if '_'+filtername+'mag' in list(write_table.columns):
write_table.rename_column(
'_{:s}mag'.format(filtername),
'_{:s}Johnsonmag'.format(filtername))
write_table.rename_column(
'_e_{:s}mag'.format(filtername),
'_e_{:s}Johnsonmag'.format(filtername))
elif filtername+'mag' in list(write_table.columns):
write_table.rename_column(
'{:s}mag'.format(filtername),
'{:s}Johnsonmag'.format(filtername))
write_table.rename_column(
'e_{:s}mag'.format(filtername),
'e_{:s}Johnsonmag'.format(filtername))
# create header and write to database
header = Table([[self.catalogname], [self.origin], [self.history],
[self.magsys], [self.obstime[0]], [self.obstime[1]],
[self.obj], [self.filtername]],
names=['name', 'origin', 'description',
'magsys', 'obstime', 'exptime', 'obj',
'filtername'])
header.to_pandas().to_sql('header', db_conn, index=False)
# write data to database
write_table.to_pandas().to_sql('data', db_conn, index=False)
db_conn.commit()
# return number of objects written to database
db.execute(
"SELECT COUNT(DISTINCT {:s}) FROM data".format(
self.fields[0].name))
n_obj = db.fetchall()[0][0]
logging.info(('wrote {:d} sources from catalog {:s} '
'to database file {:s}'.format(
n_obj,
" | ".join([self.catalogname,
self.origin,
self.history]),
filename)))
db_conn.close()
return n_obj
def read_database(self, filename):
""" read in photometry database into catalog """
# open database file
try:
db_conn = sql.connect(filename)
db = db_conn.cursor()
except:
if self.display:
print('ERROR: could not find database', filename)
logging.error('ERROR: could not find database', filename)
return []
# reader in header information
header = read_sql('SELECT * FROM header', db_conn)
self.catalogname = header['name'][0]
self.origin = header['origin'][0]
self.history = header['description'][0]
self.magsys = header['magsys'][0]
self.obstime[0] = header['obstime'][0]
self.obstime[1] = header['exptime'][0]
self.obj = header['obj'][0]
self.filtername = header['filtername'][0]
# read in data table
self.data = Table.from_pandas(read_sql('SELECT * FROM data',
db_conn))
# rename Johnson filternames
for filtername in ['B', 'V', 'R', 'I']:
if '_'+filtername+'Johnsonmag' in list(self.data.columns):
self.data.rename_column(
'_{:s}Johnsonmag'.format(filtername),
'_{:s}mag'.format(filtername))
self.data.rename_column(
'_e_{:s}Johnsonmag'.format(filtername),
'_e_{:s}mag'.format(filtername))