Source code for astroNN.datasets.apogee_distances
# ---------------------------------------------------------#
# astroNN.datasets.apogee_distances: APOGEE Distances
# ---------------------------------------------------------#
import numpy as np
from astropy import units as u
from astropy.io import fits
from astroNN.apogee import allstar
from astroNN.apogee.downloader import apogee_distances
from astroNN.gaia import mag_to_absmag, mag_to_fakemag, extinction_correction
# noinspection PyUnresolvedReferences
[docs]def load_apogee_distances(dr=None, metric='distance', cuts=True, extinction=True, keepdims=False):
"""
Load apogee distances (absolute magnitude from stellar model)
:param dr: Apogee DR
:type dr: int
:param metric: which metric you want to get back
- "absmag" for absolute magnitude
- "fakemag" for fake magnitude
- "distance" for distance in parsec
:type metric: string
:param cuts: Whether to cut bad data (negative parallax and percentage error more than 20%), or a float to set the threshold
:type cuts: Union[boolean, float]
:param extinction: Whether to take extinction into account, only affect when metric is NOT 'distance'
:type extinction: bool
:param keepdims: Whether to preserve indices the same as APOGEE allstar DR14, no effect when cuts=False, set to -9999 for bad indices when cuts=True keepdims=True
:type keepdims: boolean
:return: numpy array of ra, dec, metrics_array, metrics_err_array
:rtype: ndarrays
:History: 2018-Jan-25 - Written - Henry Leung (University of Toronto)
"""
fullfilename = apogee_distances(dr=dr)
with fits.open(fullfilename) as F:
hdulist = F[1].data
# Convert kpc to pc
distance = hdulist['BPG_dist50'] * 1000
dist_err = (hdulist['BPG_dist84'] - hdulist['BPG_dist16']) * 1000
allstarfullpath = allstar(dr=dr)
with fits.open(allstarfullpath) as F:
k_mag = F[1].data['K']
if extinction:
k_mag = extinction_correction(k_mag, F[1].data['AK_TARG'])
ra = F[1].data['RA']
dec = F[1].data['DEC']
# Bad index refers to nan index
bad_index = np.argwhere(np.isnan(distance))
if metric == 'distance':
# removed astropy units because of -9999. is dimensionless, will have issues
output = distance
output_err = dist_err
elif metric == 'absmag':
absmag, absmag_err = mag_to_absmag(k_mag, 1 / distance * u.arcsec, (1 / distance) * (dist_err / distance))
output = absmag
output_err = absmag_err
elif metric == 'fakemag':
# fakemag requires parallax (mas)
fakemag, fakemag_err = mag_to_fakemag(k_mag, 1000 / distance * u.mas, (1000 / distance) * (dist_err / distance))
output = fakemag
output_err = fakemag_err
else:
raise ValueError('Unknown metric')
# Set the nan index to -9999. as they are bad and unknown. Not magic_number as this is an APOGEE dataset
output[bad_index], output_err[bad_index] = -9999., -9999.
if cuts is False:
pass
else:
distance[bad_index], dist_err[bad_index] = -9999., -9999.
good_idx = ((dist_err / distance < (0.2 if cuts is True else cuts)) & (distance != -9999.))
if not keepdims:
ra = ra[good_idx]
dec = dec[good_idx]
output = output[good_idx]
output_err = output_err[good_idx]
else:
output[(dist_err / distance > (0.2 if cuts is True else cuts))] = -9999.
output_err[(dist_err / distance > (0.2 if cuts is True else cuts))] = -9999.
return ra, dec, output, output_err