names.remove(names[6])
names_cat.remove(names_cat[6])
print('Select Source', flush=True)
Test_source = 'J1643-1224'
print('Define Simulation Parameters', flush=True)
times_str = np.load('./binarytimestamps/times_%s.npy' %
Test_source).astype(str)
times = Time(times_str)
##Knowns
if not os.path.isfile('%s_params.npy' % Test_source):
try:
query = QueryATNF(psrs=names_cat)
psrs = query.get_pulsars()
cat = True
except:
print('psrqpy not available', flush=True)
sys.exit()
PSR = psrs[Test_source]
dp = PSR.DIST_DM1 * u.kpc
Om_peri = PSR.OM * u.deg
Om_peri_dot = PSR.OMDOT * u.deg / u.year
A1 = PSR.A1 * u.s * const.c
Ecc = PSR.ECC
Pb = PSR.PB * u.day
if str(PSR.T0) == '--':
TASC = Time(PSR.TASC, format='mjd')
T0 = Time(brentq(orbfits.T0_find,
TASC.mjd, (TASC + Pb).mjd,
def __init__(self, name, data=None, sigma=None):
self.name = name
if not os.path.isfile('%s_params.npy' % self.name):
try:
query = QueryATNF(psrs=[self.name])
psrs = query.get_pulsars()
cat = True
except:
print('psrqpy not available', flush=True)
sys.exit()
PSR = psrs[self.name]
self.dp = parameter(PSR.DIST_DM1 * u.kpc)
if not PSR.DIST_DM1_ERR == None:
sig = PSR.DIST_DM1_ERR
self.dp.lnprior = lambda x: np.exp(.5 * (
(x - self.dp.val.value) / sig)**2) / np.sqrt(2 * np.pi *
err**2)
self.dp.fixed = False
self.Om_peri = parameter(PSR.OM * u.deg)
if not PSR.OM_ERR == None:
sig = PSR.OM_ERR
self.Om_peri.lnprior = lambda x: np.exp(.5 * (
(x - self.Om_peri.val.value) / sig)**2) / np.sqrt(2 * np.pi
* err**2)
self.Om_peri.fixed = False
self.Om_peri_dot = parameter(PSR.OMDOT * u.deg / u.year)
if not PSR.OMDOT_ERR == None:
sig = PSR.OMDOT_ERR
self.Om_peri_dot.lnprior = lambda x: np.exp(.5 * (
(x - self.Om_peri_dot.val.value) / sig)**2) / np.sqrt(
2 * np.pi * err**2)
self.Om_peri_dot.fixed = False
self.A1 = parameter(PSR.A1 * u.s * const.c)
if not PSR.A1_ERR == None:
sig = PSR.A1_ERR * const.c.value
self.A1.lnprior = lambda x: np.exp(.5 * (
(x - self.A1.val.value) / sig)**2) / np.sqrt(2 * np.pi *
err**2)
self.A1.fixed = False
self.Ecc = parameter(PSR.ECC)
if not PSR.ECC_ERR == None:
sig = PSR.ECC_ERR
self.Ecc.lnprior = lambda x: np.exp(.5 * (
(x - self.A1.val) / sig)**2) / np.sqrt(2 * np.pi * err**2)
self.Ecc.fixed = False
self.Pb = parameter(PSR.PB * u.day)
if not PSR.PB_ERR == None:
sig = PSR.PB_ERR
self.Pb.lnprior = lambda x: np.exp(.5 * (
(x - self.Pb.val.value) / sig)**2) / np.sqrt(2 * np.pi *
err**2)
self.Pb.fixed = False
if str(PSR.T0) == '--':
TASC = Time(PSR.TASC, format='mjd')
self.T0 = parameter(
Time(brentq(orbfits.T0_find,
TASC.mjd, (TASC + Pb).mjd,
args=(TASC, -Om_peri, Pb, Ecc)),
format='mjd'))
if not PSR.TASC_ERR == None:
sig = PSR.TASC_ERR
self.T0.lnprior = lambda x: np.exp(.5 * (
(x - self.T0.val.mjd) / sig)**2) / np.sqrt(2 * np.pi *
err**2)
self.T0.fixed = False
else:
self.T0 = parameter(Time(PSR.T0, format='mjd'))
if not PSR.T0_ERR == None:
sig = PSR.PB_ERR
self.T0.lnprior = lambda x: np.exp(.5 * (
(x - self.T0.val.mjd) / sig)**2) / np.sqrt(2 * np.pi *
err**2)
self.T0.fixed = False
self.pm_ra = parameter(
(PSR.PMRA * u.mas / u.year).to_value(u.rad / u.s) / u.s)
if not PSR.PMRA_ERR == None:
sig = (PSR.PMRA_ERR * u.mas / u.year).to_value(u.rad / u.s)
self.pm_ra.lnprior = lambda x: np.exp(.5 * (
(x - self.pm_ra.val.value) / sig)**2) / np.sqrt(2 * np.pi *
err**2)
self.pm_ra.fixed = False
self.pm_dec = parameter(
(PSR.PMDec * u.mas / u.year).to_value(u.rad / u.s) / u.s)
if not PSR.PMDec_ERR == None:
sig = (PSR.PMDec_ERR * u.mas / u.year).to_value(u.rad / u.s)
self.pm_dec.lnprior = lambda x: np.exp(.5 * (
(x - self.pm_dec.val.value) / sig)**2) / np.sqrt(2 * np.pi
* err**2)
self.pm_dec.fixed = False
self.srce = SkyCoord.from_name('PSR %s' % Test_source)
np.save(
'%s_params.npy' % Test_source,
np.array([
dp.value, Om_peri.value, Om_peri_dot.value, A1.value, Ecc,
Pb.value, T0.mjd, pm_ra.value, pm_dec.value,
self.srce.ra.to_value(u.deg),
self.srce.dec.to_value(u.deg)
]))
self.Om_orb = parameter(180, lambda x: bound_prior(x, 0, 360))
self.Om_scr = parameter(0,
lambda x: bound_prior(x, -90, 90),
fixed=False)
self.inc = parameter(45, lambda x: bound_prior(x, 0, 1), fixed=False)
self.s = parameter(.5, lambda x: bound_prior(x, 0, 1), fixed=False)
self.data = data
self.sigma = sigma