def test_fitselector():
# WB
par = os.path.join(datadir, "B1855+09_NANOGrav_12yv3.wb.gls.par")
tim = os.path.join(datadir, "B1855+09_NANOGrav_12yv3.wb.tim")
m, t = get_model_and_toas(par, tim)
f = fitter.Fitter.auto(t, m, downhill=True)
assert isinstance(f, fitter.WidebandDownhillFitter)
f = fitter.Fitter.auto(t, m, downhill=False)
assert isinstance(f, fitter.WidebandTOAFitter)
# correlated errors
m, t = get_model_and_toas(
os.path.join(datadir, "J0023+0923_NANOGrav_11yv0.gls.par"),
os.path.join(datadir, "J0023+0923_NANOGrav_11yv0.tim"),
)
f = fitter.Fitter.auto(t, m, downhill=True)
assert isinstance(f, fitter.DownhillGLSFitter)
f = fitter.Fitter.auto(t, m, downhill=False)
assert isinstance(f, fitter.GLSFitter)
# uncorrelated errors
m, t = get_model_and_toas(os.path.join(datadir, "NGC6440E.par"),
os.path.join(datadir, "NGC6440E.tim"))
f = fitter.Fitter.auto(t, m, downhill=True)
assert isinstance(f, fitter.DownhillWLSFitter)
f = fitter.Fitter.auto(t, m, downhill=False)
assert isinstance(f, fitter.WLSFitter)
def test_random_models(fitter):
# Get model and TOAs
m, t = get_model_and_toas(os.path.join(datadir, "NGC6440E.par"),
os.path.join(datadir, "NGC6440E.tim"))
f = fitter(toas=t, model=m)
# Do a 4-parameter fit
f.model.free_params = ("F0", "F1", "RAJ", "DECJ")
f.fit_toas()
# this contains TOAs up through 54200
# make new ones starting there
tnew = simulation.make_fake_toas_uniform(54200, 59000, 59000 - 54200,
f.model)
dphase, mrand = simulation.calculate_random_models(f, tnew, Nmodels=30)
# this is a bit stochastic, but I see typically < 0.14 cycles
# for the uncertainty at 59000
assert np.all(dphase.std(axis=0) < 0.2)
# redo it with only F0 free
dphase_F, mrand_F = simulation.calculate_random_models(f,
tnew,
Nmodels=100,
params=["F0"])
# this should be less than the fully free version
assert dphase_F.std(axis=0).max() < dphase.std(axis=0).max()
def test_CHI2():
"""Should be present after fit in PINT, not in TEMPO/TEMPO2"""
m, t = get_model_and_toas(os.path.join(datadir, "NGC6440E.par"),
os.path.join(datadir, "NGC6440E.tim"))
f = fitter.WLSFitter(toas=t, model=m)
assert "CHI2" in f.model.as_parfile()
assert not ("CHI2" in f.model.as_parfile(format="tempo2"))
assert not ("CHI2" in f.model.as_parfile(format="tempo"))
def test_fitsummary_binary():
"""Test fitter print_summary() when an ELL1 binary is fit"""
par = os.path.join(datadir, "B1855+09_NANOGrav_12yv3.wb.gls.par")
tim = os.path.join(datadir, "B1855+09_NANOGrav_dfg+12.tim")
m, t = get_model_and_toas(par, tim)
f = fitter.WLSFitter(t, m)
f.model.free_params = ["PB", "A1", "SINI"]
f.fit_toas()
f.print_summary()
def test_no_planet(self):
"""Test exception when incorrect par(tim) file given."""
with self.assertRaises(ValueError) as context:
model, toas = get_model_and_toas(
datadir + "/J0030+0451_NANOGrav_9yv1.gls.par",
datadir + "/J0030+0451_NANOGrav_9yv1.tim",
planets=False)
Pulsar(model, toas, planets=True)
msg = "obs_earth_pos is not in toas.table.colnames. Either "
msg += "`planet` flag is not True in `toas` or further Pint "
msg += "development to add additional planets is needed."
self.assertTrue(msg in context.exception)
def Pulsar(*args, **kwargs):
ephem = kwargs.get("ephem", None)
clk = kwargs.get("clk", None)
bipm_version = kwargs.get("bipm_version", None)
planets = kwargs.get("planets", True)
sort = kwargs.get("sort", True)
drop_t2pulsar = kwargs.get("drop_t2pulsar", True)
drop_pintpsr = kwargs.get("drop_pintpsr", True)
timing_package = kwargs.get("timing_package", "tempo2")
if pint is not None:
toas = [x for x in args if isinstance(x, TOAs)]
model = [x for x in args if isinstance(x, TimingModel)]
if t2 is not None:
t2pulsar = [x for x in args if isinstance(x, t2.tempopulsar)]
parfile = [
x for x in args if isinstance(x, str) and x.split(".")[-1] == "par"
]
timfile = [
x for x in args
if isinstance(x, str) and x.split(".")[-1] in ["tim", "toa"]
]
if pint and toas and model:
return PintPulsar(toas[0],
model[0],
sort=sort,
drop_pintpsr=drop_pintpsr,
planets=planets)
elif t2 and t2pulsar:
return Tempo2Pulsar(t2pulsar[0],
sort=sort,
drop_t2pulsar=drop_t2pulsar,
planets=planets)
elif parfile and timfile:
# Check whether the two files exist
if not os.path.isfile(parfile[0]) or not os.path.isfile(timfile[0]):
msg = "Cannot find parfile {0} or timfile {1}!".format(
parfile[0], timfile[0])
raise IOError(msg)
# Obtain the directory name of the timfile, and change to it
timfiletup = os.path.split(timfile[0])
dirname = timfiletup[0] or "./"
reltimfile = timfiletup[-1]
relparfile = os.path.relpath(parfile[0], dirname)
# get current directory
cwd = os.getcwd()
# Change directory to the base directory of the tim-file to deal with
# INCLUDE statements in the tim-file
os.chdir(dirname)
if timing_package.lower() == "pint":
if (clk is not None) and (bipm_version is None):
bipm_version = clk.split("(")[1][:-1]
model, toas = get_model_and_toas(relparfile,
reltimfile,
ephem=ephem,
bipm_version=bipm_version,
planets=planets)
os.chdir(cwd)
return PintPulsar(toas,
model,
sort=sort,
drop_pintpsr=drop_pintpsr,
planets=planets)
elif timing_package.lower() == "tempo2":
# hack to set maxobs
maxobs = get_maxobs(reltimfile) + 100
t2pulsar = t2.tempopulsar(relparfile,
reltimfile,
maxobs=maxobs,
ephem=ephem,
clk=clk)
os.chdir(cwd)
return Tempo2Pulsar(t2pulsar,
sort=sort,
drop_t2pulsar=drop_t2pulsar,
planets=planets)
raise ValueError("Unknown arguments {}".format(args))
import pint.fitter
import pint.residuals
import pint.toa
from pint.models import get_model, get_model_and_toas
# %%
import pint.config
parfile = pint.config.examplefile("NGC6440E.par")
timfile = pint.config.examplefile("NGC6440E.tim")
assert os.path.exists(parfile)
assert os.path.exists(timfile)
# %%
# Read the timing model and the TOAs
m, t = get_model_and_toas(parfile, timfile)
# %% [markdown]
# If we wanted to do things separately we could do
# ```python
# # Define the timing model
# m = get_model(parfile)
# # Read in the TOAs, using the solar system epemeris and other things from the model
# t = pint.toa.get_TOAs(timfile, model=m)
# ```
# %% [markdown]
# If we wanted to select some subset of the TOAs, there are tools to do that. Most easily
# you make a new TOAs object containing the subset you care about (we will make but not use
# them):
def test_bipm_default():
m, t = get_model_and_toas(StringIO(simplepar.replace("BIPM2017", "BIPM")),
"test1.tim")
assert t.clock_corr_info["bipm_version"] == "BIPM"
def test_model_override_override2():
parstr = StringIO(simplepar)
m, y = get_model_and_toas(parstr, "test1.tim", ephem="DE405")
assert y.ephem == "DE405"
def test_model_override2():
parstr = StringIO(simplepar)
m, y = get_model_and_toas(parstr, "test1.tim")
assert y.ephem == "DE436"
assert y.planets is True
assert y.clock_corr_info["bipm_version"] == "BIPM2017"
import astropy.units as u
import matplotlib.pyplot as plt
from astropy.visualization import quantity_support
from pint.fitter import WidebandTOAFitter
from pint.models import get_model_and_toas
from pint.toa import get_TOAs
quantity_support()
# %% [markdown]
# ## Set up your inputs
# %%
model, toas = get_model_and_toas("J1614-2230_NANOGrav_12yv3.wb.gls.par",
"J1614-2230_NANOGrav_12yv3.wb.tim")
# %% [markdown]
# The DM and its uncertainty are recorded as flags, `pp_dm` and `pp_dme` on the TOAs that have them, They are not currently available as Columns in the Astropy object. On the other hand, it is not necessary that every observation have a measured DM.
#
# (The name, `pp_dm`, refers to the fact that they are obtained using "phase portraits", like profiles but in one more dimension.)
# %%
print(open(toas.filename).readlines()[-1])
# %%
toas.table[-1]
# %%
toas.table["flags"][0]
import matplotlib.pyplot as plt
from astropy.visualization import quantity_support
from pint.fitter import WidebandTOAFitter
from pint.models import get_model_and_toas
from pint.toa import get_TOAs
import pint.config
quantity_support()
# %% [markdown]
# ## Set up your inputs
# %%
model, toas = get_model_and_toas(
pint.config.examplefile("J1614-2230_NANOGrav_12yv3.wb.gls.par"),
pint.config.examplefile("J1614-2230_NANOGrav_12yv3.wb.tim"),
)
# %% [markdown]
# The DM and its uncertainty are recorded as flags, `pp_dm` and `pp_dme` on the TOAs that have them, They are not currently available as Columns in the Astropy object. On the other hand, it is not necessary that every observation have a measured DM.
#
# (The name, `pp_dm`, refers to the fact that they are obtained using "phase portraits", like profiles but in one more dimension.)
# %%
print(open(toas.filename).readlines()[-1])
# %%
toas.table[-1]
# %%
toas.table["flags"][0]
