def test_load_and_save_events(self):
events = EventList([0, 2, 3.], pi=[1, 2, 3], mjdref=54385.3254923845,
gti = np.longdouble([[-0.5, 3.5]]))
events.energy = np.array([3., 4., 5.])
save_to_intermediate_file(events, self.dum)
ds = load_dataset_from_intermediate_file(self.dum)
assert ds
def test_load_and_save_events(self):
events = EventList([0, 2, 3.], pi=[1, 2, 3], mjdref=54385.3254923845,
gti = np.longdouble([[-0.5, 3.5]]))
events.energy = np.array([3., 4., 5.])
save_events(events, self.dum)
events2 = load_events(self.dum)
assert np.allclose(events.time, events2.time)
assert np.allclose(events.pi, events2.pi)
assert np.allclose(events.mjdref, events2.mjdref)
assert np.allclose(events.gti, events2.gti)
assert np.allclose(events.energy, events2.energy)
def setup_class(cls):
from ..simulator import Simulator
dt = 0.01
cls.time_lag = 5.
data = np.load(os.path.join(datadir, "sample_variable_lc.npy"))
flux = data
times = np.arange(data.size) * dt
maxfreq = 0.25 / cls.time_lag
roll_amount = int(cls.time_lag // dt)
good = slice(roll_amount, roll_amount + int(200 // dt))
rolled_flux = np.array(np.roll(flux, roll_amount))
times, flux, rolled_flux = times[good], flux[good], rolled_flux[good]
length = times[-1] - times[0]
test_lc1 = Lightcurve(times,
flux,
err_dist="gauss",
dt=dt,
skip_checks=True)
test_lc2 = Lightcurve(test_lc1.time,
rolled_flux,
err_dist=test_lc1.err_dist,
dt=dt)
test_ev1, test_ev2 = EventList(), EventList()
test_ev1.simulate_times(test_lc1)
test_ev2.simulate_times(test_lc2)
test_ev1.energy = np.random.uniform(0.3, 9, len(test_ev1.time))
test_ev2.energy = np.random.uniform(9, 12, len(test_ev2.time))
cls.lag = LagEnergySpectrum(
test_ev1,
freq_interval=[0, maxfreq],
energy_spec=(0.3, 9, 1, "lin"),
ref_band=[9, 12],
bin_time=dt / 2,
segment_size=length,
events2=test_ev2,
)
# Make single event list
test_ev = test_ev1.join(test_ev2)
cls.lag_same = LagEnergySpectrum(
test_ev,
freq_interval=[0, maxfreq],
energy_spec=(0.3, 9, 1, "lin"),
ref_band=[9, 12],
bin_time=dt / 2,
segment_size=length,
)
def setup_class(cls):
from ..simulator.simulator import Simulator
simulator = Simulator(0.1, 1000, rms=0.4, mean=200)
test_lc = simulator.simulate(1)
test_ev1, test_ev2 = EventList(), EventList()
test_ev1.simulate_times(test_lc)
test_ev2.simulate_times(test_lc)
test_ev1.energy = np.random.uniform(0.3, 12, len(test_ev1.time))
test_ev2.energy = np.random.uniform(0.3, 12, len(test_ev2.time))
cls.rms = RmsEnergySpectrum(test_ev1, [0., 100], (0.3, 12, 5, "lin"),
bin_time=0.01,
segment_size=100,
events2=test_ev2)
def test_filter_for_deadtime_evlist():
"""Test dead time filter, non-paralyzable case."""
events = np.array([1, 1.05, 1.07, 1.08, 1.1, 2, 2.2, 3, 3.1, 3.2])
events = EventList(events)
events.pi=np.array([1, 2, 2, 2, 2, 1, 1, 1, 2, 1])
events.energy=np.array([1, 2, 2, 2, 2, 1, 1, 1, 2, 1])
events.mjdref = 10
filt_events = filter_for_deadtime(events, 0.11)
expected = np.array([1, 2, 2.2, 3, 3.2])
assert np.allclose(filt_events.time, expected), \
"Wrong: {} vs {}".format(filt_events, expected)
assert np.allclose(filt_events.pi, 1)
assert np.allclose(filt_events.energy, 1)
def setup_class(cls):
from ..simulator.simulator import Simulator
simulator = Simulator(0.1, 1000, rms=0.4, mean=200)
test_lc = simulator.simulate(1)
test_ev1, test_ev2 = EventList(), EventList()
test_ev1.simulate_times(test_lc)
test_ev2.simulate_times(test_lc)
test_ev1.energy = np.random.uniform(0.3, 12, len(test_ev1.time))
test_ev2.energy = np.random.uniform(0.3, 12, len(test_ev2.time))
cls.rms = RmsEnergySpectrum(test_ev1, [0., 100],
(0.3, 12, 5, "lin"),
bin_time=0.01,
segment_size=100,
events2=test_ev2)
def load_events(fname):
"""Load events from a file."""
if get_file_format(fname) == 'pickle':
out = _load_data_pickle(fname)
elif get_file_format(fname) == 'nc':
out = _load_data_nc(fname)
eventlist = EventList()
eventlist.time = out['time']
eventlist.gti = out['gti']
eventlist.pi = out['pi']
eventlist.mjdref = out['mjdref']
if 'instr' in list(out.keys()):
eventlist.instr = out["instr"]
if 'energy' in list(out.keys()):
eventlist.energy = out["energy"]
if 'header' in list(out.keys()):
eventlist.header = out["header"]
return eventlist
def setup_class(cls):
from ..simulator.simulator import Simulator
dt = 0.1
simulator = Simulator(dt, 1000, rms=0.4, mean=200)
test_lc1 = simulator.simulate(2)
test_lc2 = Lightcurve(test_lc1.time,
np.array(np.roll(test_lc1.counts, 2)),
err_dist=test_lc1.err_dist,
dt=dt)
test_ev1, test_ev2 = EventList(), EventList()
test_ev1.simulate_times(test_lc1)
test_ev2.simulate_times(test_lc2)
test_ev1.energy = np.random.uniform(0.3, 9, len(test_ev1.time))
test_ev2.energy = np.random.uniform(9, 12, len(test_ev2.time))
cls.lag = LagEnergySpectrum(test_ev1, [0., 0.5], (0.3, 9, 4, "lin"),
[9, 12],
bin_time=0.1,
segment_size=30,
events2=test_ev2)
def setup_class(cls):
from ..simulator.simulator import Simulator
dt = 0.1
simulator = Simulator(dt, 1000, rms=0.4, mean=200)
test_lc1 = simulator.simulate(2)
test_lc2 = Lightcurve(test_lc1.time,
np.array(np.roll(test_lc1.counts, 2)),
err_dist=test_lc1.err_dist,
dt=dt)
test_ev1, test_ev2 = EventList(), EventList()
test_ev1.simulate_times(test_lc1)
test_ev2.simulate_times(test_lc2)
test_ev1.energy = np.random.uniform(0.3, 9, len(test_ev1.time))
test_ev2.energy = np.random.uniform(9, 12, len(test_ev2.time))
cls.lag = LagEnergySpectrum(test_ev1, [0., 0.5],
(0.3, 9, 4, "lin"), [9, 12],
bin_time=0.1,
segment_size=30,
events2=test_ev2)
def setup_class(cls):
cls.pulse_frequency = 1 / 0.101
cls.tstart = 0
cls.tend = 25.25
cls.tseg = cls.tend - cls.tstart
cls.dt = 0.00606
cls.times = np.arange(cls.tstart, cls.tend, cls.dt) + cls.dt / 2
cls.counts = \
100 + 20 * np.cos(2 * np.pi * cls.times * cls.pulse_frequency)
lc = Lightcurve(cls.times, cls.counts, gti=[[cls.tstart, cls.tend]])
events = EventList()
events.simulate_times(lc)
cls.event_times = events.time
cls.dum_noe = 'events_noe' + HEN_FILE_EXTENSION
save_events(events, cls.dum_noe)
events.pi = np.random.uniform(0, 1000, len(events.time))
cls.dum_pi = 'events_pi' + HEN_FILE_EXTENSION
save_events(events, cls.dum_pi)
events.energy = np.random.uniform(3, 79, len(events.time))
cls.dum = 'events' + HEN_FILE_EXTENSION
save_events(events, cls.dum)
