def test_known_regression(self):
# prevent regression of known bug
self.assertEqual(mag_to_absmag(1., MAGIC_NUMBER), MAGIC_NUMBER)
self.assertEqual(mag_to_absmag(MAGIC_NUMBER, MAGIC_NUMBER), MAGIC_NUMBER)
self.assertEqual(
np.all(mag_to_absmag(MAGIC_NUMBER, MAGIC_NUMBER, 1.) == (MAGIC_NUMBER, MAGIC_NUMBER)), True)
self.assertEqual(
np.all(mag_to_fakemag(MAGIC_NUMBER, MAGIC_NUMBER, 1.) == (MAGIC_NUMBER, MAGIC_NUMBER)), True)
self.assertEqual(mag_to_fakemag(1., MAGIC_NUMBER), MAGIC_NUMBER)
self.assertEqual(mag_to_fakemag(MAGIC_NUMBER, MAGIC_NUMBER), MAGIC_NUMBER)
self.assertEqual(fakemag_to_pc(1., MAGIC_NUMBER).value, MAGIC_NUMBER)
self.assertEqual(fakemag_to_pc(-1., 2.).value, MAGIC_NUMBER)
self.assertEqual(absmag_to_pc(1., MAGIC_NUMBER).value, MAGIC_NUMBER)
def load_apogee_rc(dr=None, unit='distance', extinction=True):
"""
Load apogee red clumps (absolute magnitude measurement)
:param dr: Apogee DR
:type dr: int
:param unit: which unit you want to get back
- "absmag" for k-band absolute magnitude
- "fakemag" for k-band fake magnitude
- "distance" for distance in parsec
:type unit: string
:param extinction: Whether to take extinction into account, only affect when unit is NOT 'distance'
:type extinction: bool
:return: numpy array of ra, dec, array
:rtype: ndarrays
:History:
| 2018-Jan-21 - Written - Henry Leung (University of Toronto)
| 2018-May-12 - Updated - Henry Leung (University of Toronto)
"""
fullfilename = apogee_rc(dr=dr)
with fits.open(fullfilename) as F:
hdulist = F[1].data
ra = hdulist['RA']
dec = hdulist['DEC']
rc_dist = hdulist['RC_DIST']
rc_parallax = (1 / rc_dist) * u.mas # Convert kpc to parallax in mas
k_mag = hdulist['K']
if extinction:
k_mag = extinction_correction(k_mag, hdulist['AK_TARG'])
if unit == 'distance':
output = rc_dist * 1000
elif unit == 'absmag':
absmag = mag_to_absmag(k_mag, rc_parallax)
output = absmag
elif unit == 'fakemag':
# fakemag requires parallax (mas)
fakemag = mag_to_fakemag(k_mag, rc_parallax)
output = fakemag
else:
raise ValueError('Unknown unit')
return ra, dec, output
def load_apogee_distances(dr=None,
metric='distance',
cuts=True,
extinction=False):
"""
Load apogee distances (absolute magnitude from stellar model)
:param dr: Apogee DR
:type dr: int
:param metric: which metric you want ot get back
- "absmag" for absolute magnitude
- "fakemag" for fake magnitude
- "distance" for distance
: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
:type extinction: bool
: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.)]
ra = ra[good_idx]
dec = dec[good_idx]
output = output[good_idx]
output_err = output_err[good_idx]
return ra, dec, output, output_err
def test_astrometry_conversion(self):
# Example data of [Vega, Sirius]
absmag = np.array([0.582, 1.42])
mag = np.array([0.026, -1.46])
parallax = np.array([130.23, 379.21])
parallax_err = np.array([0.36, 1.58])
# Absmag related test
pc = absmag_to_pc(absmag, mag)
npt.assert_almost_equal(pc.value, 1000 / parallax, decimal=1)
npt.assert_almost_equal(mag_to_absmag(mag, parallax * u.mas),
absmag,
decimal=1)
self.assertEqual(
np.any(absmag_to_fakemag(MAGIC_NUMBER) == MAGIC_NUMBER), True)
absmag_test, absmag_err_test = mag_to_absmag(mag, parallax * u.mas,
parallax_err)
absmag_test_uniterr, absmag_err_test_uniterr = mag_to_absmag(
mag, parallax * u.mas, parallax_err / 1000 * u.arcsec)
absmag_test_arc, absmag_err_test_arc = mag_to_absmag(
mag, parallax / 1000 * u.arcsec, parallax_err / 1000)
absmag_test_unitless, absmag_err_test_unitless = mag_to_absmag(
mag, parallax, parallax_err)
# make sure unitless same as using astropy unit
npt.assert_almost_equal(absmag_test, absmag_test_unitless)
npt.assert_almost_equal(absmag_test, absmag_test_unitless)
npt.assert_almost_equal(absmag_err_test, absmag_err_test_uniterr)
# make sure astropy unit conversion works fine
npt.assert_almost_equal(absmag_test, absmag_test_arc)
npt.assert_almost_equal(absmag_err_test, absmag_err_test_arc)
# =================== Fakemag related test ===================#
# make sure these function did identity transform
npt.assert_almost_equal(fakemag_to_absmag(absmag_to_fakemag(absmag)),
absmag,
decimal=1)
# we can tests this after identity transformation confirmed
npt.assert_almost_equal(fakemag_to_pc(absmag_to_fakemag(absmag),
mag).value,
1000 / parallax,
decimal=1)
npt.assert_almost_equal(fakemag_to_pc(
mag_to_fakemag(mag, parallax * u.mas), mag).value,
1000 / parallax,
decimal=1)
fakemag_test, fakemag_err_test = mag_to_fakemag(
mag, parallax * u.mas, parallax_err)
fakemag_test_uniterr, fakemag_err_test_uniterr = mag_to_fakemag(
mag, parallax * u.mas, parallax_err / 1000 * u.arcsec)
fakemag_test_unitless, fakemag_err_test_unitless = mag_to_fakemag(
mag, parallax, parallax_err)
fakemag_test_arc, fakemag_err_test_arc = mag_to_fakemag(
mag, parallax / 1000 * u.arcsec, parallax_err / 1000)
pc_result, pc_result_err = fakemag_to_pc(fakemag_test, mag,
fakemag_err_test)
pc_result_arc, pc_result_err_arc = fakemag_to_pc(
fakemag_test_arc, mag, fakemag_err_test_arc)
# Analytically solution checkung
npt.assert_almost_equal(pc_result_err.value,
(parallax_err / parallax) * pc.value,
decimal=1)
# make sure unitless same as using astropy unit
npt.assert_almost_equal(fakemag_test, fakemag_test_unitless)
npt.assert_almost_equal(fakemag_err_test, fakemag_err_test_uniterr)
npt.assert_almost_equal(fakemag_err_test, fakemag_err_test_unitless)
# make sure astropy unit conversion works fine
npt.assert_almost_equal(fakemag_test, fakemag_test_arc)
npt.assert_almost_equal(fakemag_err_test, fakemag_err_test_arc)
npt.assert_almost_equal(pc_result.value, pc_result_arc.value)
npt.assert_almost_equal(pc_result_err.value, pc_result_err_arc.value)
# check gaia default dr
dr = gaia_default_dr()
self.assertEqual(dr, 1)
dr = gaia_default_dr(dr=3)
self.assertEqual(dr, 3)
