def test_unbinned_fit(event_time_series):
start, stop = 0, 50
poly = [1]
arrival_times = event_time_series
evt_list = EventListWithDeadTime(
arrival_times=arrival_times,
measurement=np.zeros_like(arrival_times),
n_channels=1,
start_time=arrival_times[0],
stop_time=arrival_times[-1],
dead_time=np.zeros_like(arrival_times),
)
evt_list.set_polynomial_fit_interval("%f-%f" % (start + 1, stop - 1),
unbinned=True)
results = evt_list.get_poly_info()["coefficients"]
evt_list.set_active_time_intervals("0-1")
assert evt_list.time_intervals == TimeIntervalSet.from_list_of_edges(
[0, 1])
assert evt_list._poly_counts.sum() > 0
evt_list.__repr__()
def test_binned_fit():
with within_directory(datasets_dir):
start, stop = 0, 50
poly = [1]
arrival_times = np.loadtxt('test_event_data.txt')
evt_list = EventListWithDeadTime(
arrival_times=arrival_times,
measurement=np.zeros_like(arrival_times),
n_channels=1,
start_time=arrival_times[0],
stop_time=arrival_times[-1],
dead_time=np.zeros_like(arrival_times))
evt_list.set_polynomial_fit_interval("%f-%f" % (start + 1, stop - 1),
unbinned=False)
evt_list.set_active_time_intervals("0-1")
results = evt_list.get_poly_info()['coefficients']
assert evt_list.time_intervals == TimeIntervalSet.from_list_of_edges(
[0, 1])
assert evt_list._poly_counts.sum() > 0
evt_list.__repr__()
def test_binned_fit():
with within_directory(datasets_dir):
start, stop = 0, 50
poly = [1]
arrival_times = np.loadtxt('test_event_data.txt')
evt_list = EventListWithDeadTime(arrival_times=arrival_times,
measurement=np.zeros_like(arrival_times),
n_channels=1,
start_time=arrival_times[0],
stop_time=arrival_times[-1],
dead_time=np.zeros_like(arrival_times)
)
evt_list.set_polynomial_fit_interval("%f-%f" % (start + 1, stop - 1), unbinned=False)
evt_list.set_active_time_intervals("0-1")
results = evt_list.get_poly_info()['coefficients']
assert evt_list.time_intervals == TimeIntervalSet.from_list_of_edges([0,1])
assert evt_list._poly_counts.sum() > 0
evt_list.__repr__()