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_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 _set_plugins(self):
"""
Set the plugins using the saved background hdf5 files
:return:
"""
det_ts = []
det_rsp = []
for det in self._use_dets:
# set up responses
tte_file = f"{base_dir}/{self._grb_name}/tte/data/glg_tte_{det}_bn{self._grb_name[3:]}_{self._version}.fit"
cspec_file = f"{base_dir}/{self._grb_name}/tte/data/glg_cspec_{det}_bn{self._grb_name[3:]}_{self._version}.pha"
rsp = drm.DRMGenTTE(tte_file=tte_file,
trigdat=self._trigdat_file,
mat_type=2,
cspecfile=cspec_file,
occult=True)
det_rsp.append(rsp)
# Time Series
gbm_tte_file = GBMTTEFile(tte_file)
event_list = EventListWithDeadTime(
arrival_times=gbm_tte_file.arrival_times -
gbm_tte_file.trigger_time,
measurement=gbm_tte_file.energies,
n_channels=gbm_tte_file.n_channels,
start_time=gbm_tte_file.tstart - gbm_tte_file.trigger_time,
stop_time=gbm_tte_file.tstop - gbm_tte_file.trigger_time,
dead_time=gbm_tte_file.deadtime,
first_channel=0,
instrument=gbm_tte_file.det_name,
mission=gbm_tte_file.mission,
verbose=True,
)
success_restore = False
i = 0
while not success_restore:
try:
ts = TimeSeriesBuilder(
det,
event_list,
response=BALROG_DRM(rsp, 0.0, 0.0),
unbinned=False,
verbose=True,
container_type=BinnedSpectrumWithDispersion,
restore_poly_fit=self._bkg_fit_files[det],
)
success_restore = True
i = 0
except:
time.sleep(1)
i += 1
if i == 50:
raise AssertionError("Can not restore background fit...")
ts.set_active_time_interval(
f"{self._active_time_start}-{self._active_time_stop}")
det_ts.append(ts)
# Mean of active time
rsp_time = (float(self._active_time_start) +
float(self._active_time_stop)) / 2
# Spectrum Like
det_sl = []
# set up energy range
for series in det_ts:
if series._name != "b0" and series._name != "b1":
sl = series.to_spectrumlike()
sl.set_active_measurements("8.1-700")
det_sl.append(sl)
else:
sl = series.to_spectrumlike()
sl.set_active_measurements("350-25000")
det_sl.append(sl)
# Make Balrog Like
det_bl = []
for i, det in enumerate(self._use_dets):
det_bl.append(
drm.BALROGLike.from_spectrumlike(det_sl[i],
rsp_time,
det_rsp[i],
free_position=True))
self._data_list = DataList(*det_bl)
def from_gbm_tte(cls,
name,
tte_file,
rsp_file,
restore_background=None,
trigger_time=None,
poly_order=-1,
unbinned=True,
verbose=True):
"""
A plugin to natively bin, view, and handle Fermi GBM TTE data.
A TTE event file are required as well as the associated response
Background selections are specified as
a comma separated string e.g. "-10-0,10-20"
Initial source selection is input as a string e.g. "0-5"
One can choose a background polynomial order by hand (up to 4th order)
or leave it as the default polyorder=-1 to decide by LRT test
:param name: name for your choosing
:param tte_file: GBM tte event file
:param rsp_file: Associated TTE CSPEC response file
:param trigger_time: trigger time if needed
:param poly_order: 0-4 or -1 for auto
:param unbinned: unbinned likelihood fit (bool)
:param verbose: verbose (bool)
"""
# self._default_unbinned = unbinned
# Load the relevant information from the TTE file
gbm_tte_file = GBMTTEFile(tte_file)
# Set a trigger time if one has not been set
if trigger_time is not None:
gbm_tte_file.trigger_time = trigger_time
# Create the the event list
event_list = EventListWithDeadTime(
arrival_times=gbm_tte_file.arrival_times -
gbm_tte_file.trigger_time,
measurement=gbm_tte_file.energies,
n_channels=gbm_tte_file.n_channels,
start_time=gbm_tte_file.tstart - gbm_tte_file.trigger_time,
stop_time=gbm_tte_file.tstop - gbm_tte_file.trigger_time,
dead_time=gbm_tte_file.deadtime,
first_channel=0,
instrument=gbm_tte_file.det_name,
mission=gbm_tte_file.mission,
verbose=verbose,
)
if isinstance(rsp_file, str) or isinstance(rsp_file, unicode):
# we need to see if this is an RSP2
test = re.match('^.*\.rsp2$', rsp_file)
# some GBM RSPs that are not marked RSP2 are in fact RSP2s
# we need to check
if test is None:
with fits.open(rsp_file) as f:
# there should only be a header, ebounds and one spec rsp extension
if len(f) > 3:
# make test a dummy value to trigger the nest loop
test = -1
custom_warnings.warn(
'The RSP file is marked as a single response but in fact has multiple matrices. We will treat it as an RSP2'
)
if test is not None:
rsp = InstrumentResponseSet.from_rsp2_file(
rsp2_file=rsp_file,
counts_getter=event_list.counts_over_interval,
exposure_getter=event_list.exposure_over_interval,
reference_time=gbm_tte_file.trigger_time)
else:
rsp = OGIPResponse(rsp_file)
else:
assert isinstance(
rsp_file, InstrumentResponse
), 'The provided response is not a 3ML InstrumentResponse'
rsp = rsp_file
# pass to the super class
return cls(name,
event_list,
response=rsp,
poly_order=poly_order,
unbinned=unbinned,
verbose=verbose,
restore_poly_fit=restore_background,
container_type=BinnedSpectrumWithDispersion)
def _build_bkg_plugins(self):
"""
Build the background plugins for all dets
:return:
"""
# Time selection from yaml file
with open(self._time_selection_file_path, "r") as f:
data = yaml.safe_load(f)
active_time = (
f"{data['active_time']['start']}-{data['active_time']['stop']}"
)
background_time_neg = f"{data['background_time']['before']['start']}-{data['background_time']['before']['stop']}"
background_time_pos = f"{data['background_time']['after']['start']}-{data['background_time']['after']['stop']}"
poly_order = data["poly_order"]
det_ts = []
for det in _gbm_detectors:
# Response Setup
rsp = BALROG_DRM(
drm.DRMGenTTE(
tte_file=self._tte_files[det],
trigdat=self._trigdat_file,
mat_type=2,
cspecfile=self._cspec_files[det],
),
0.0,
0.0,
)
# Time Series
gbm_tte_file = GBMTTEFile(self._tte_files[det])
event_list = EventListWithDeadTime(
arrival_times=gbm_tte_file.arrival_times -
gbm_tte_file.trigger_time,
measurement=gbm_tte_file.energies,
n_channels=gbm_tte_file.n_channels,
start_time=gbm_tte_file.tstart - gbm_tte_file.trigger_time,
stop_time=gbm_tte_file.tstop - gbm_tte_file.trigger_time,
dead_time=gbm_tte_file.deadtime,
first_channel=0,
instrument=gbm_tte_file.det_name,
mission=gbm_tte_file.mission,
verbose=True,
)
ts = TimeSeriesBuilder(
det,
event_list,
response=rsp,
poly_order=poly_order,
unbinned=False,
verbose=True,
container_type=BinnedSpectrumWithDispersion,
)
ts.set_background_interval(background_time_neg,
background_time_pos)
ts.set_active_time_interval(active_time)
det_ts.append(ts)
self._ts = det_ts