def test_set_cuts_clear():
flow = CutFlow("TestFlow")
flow.set_cut("smaller5", smaller5)
flow.set_cuts(OrderedDict([("smaller3", smaller3),
("smaller2", smaller2)]),
clear=True)
assert flow.cuts == OrderedDict([("smaller3", [smaller3, 0]),
("smaller2", [smaller2, 0])])
def test_set_cuts_clear():
flow = CutFlow("TestFlow")
flow.set_cut("smaller5", smaller5)
flow.set_cuts(OrderedDict([
("smaller3", smaller3),
("smaller2", smaller2)
]), clear=True)
assert flow.cuts == OrderedDict([
("smaller3", [smaller3, 0]),
("smaller2", [smaller2, 0])
])
def test_set_cuts_no_clear():
with warns(FutureWarning):
flow = CutFlow("TestFlow")
flow.set_cut("smaller5", smaller5)
flow.set_cuts(OrderedDict([("smaller3", smaller3),
("smaller2", smaller2)]),
clear=False)
assert flow.cuts == OrderedDict([
("smaller5", [smaller5, 0]),
("smaller3", [smaller3, 0]),
("smaller2", [smaller2, 0]),
])
class SimpleEventWriter(Tool):
name = 'ctapipe-simple-event-writer'
description = Unicode(__doc__)
infile = Unicode(help='input file to read', default='').tag(config=True)
outfile = Unicode(help='output file name',
default_value='output.h5').tag(config=True)
progress = Bool(help='display progress bar',
default_value=True).tag(config=True)
aliases = Dict({
'infile': 'EventSource.input_url',
'outfile': 'SimpleEventWriter.outfile',
'max-events': 'EventSource.max_events',
'progress': 'SimpleEventWriter.progress'
})
classes = List([EventSource, CameraCalibrator, CutFlow])
def setup(self):
self.log.info('Configure EventSource...')
self.event_source = self.add_component(
EventSource.from_config(config=self.config, parent=self))
self.calibrator = self.add_component(CameraCalibrator(parent=self))
self.writer = self.add_component(
HDF5TableWriter(filename=self.outfile,
group_name='image_infos',
overwrite=True))
# Define Pre-selection for images
preselcuts = self.config['Preselect']
self.image_cutflow = CutFlow('Image preselection')
self.image_cutflow.set_cuts(
dict(no_sel=None,
n_pixel=lambda s: np.count_nonzero(s) < preselcuts['n_pixel'][
'min'],
image_amplitude=lambda q: q < preselcuts['image_amplitude'][
'min']))
# Define Pre-selection for events
self.event_cutflow = CutFlow('Event preselection')
self.event_cutflow.set_cuts(dict(no_sel=None))
def start(self):
self.log.info('Loop on events...')
for event in tqdm(self.event_source,
desc='EventWriter',
total=self.event_source.max_events,
disable=~self.progress):
self.event_cutflow.count('no_sel')
self.calibrator(event)
for tel_id in event.dl0.tels_with_data:
self.image_cutflow.count('no_sel')
camera = event.inst.subarray.tel[tel_id].camera
dl1_tel = event.dl1.tel[tel_id]
# Image cleaning
image = dl1_tel.image # Waiting for automatic gain selection
mask = tailcuts_clean(camera,
image,
picture_thresh=10,
boundary_thresh=5)
cleaned = image.copy()
cleaned[~mask] = 0
# Preselection cuts
if self.image_cutflow.cut('n_pixel', cleaned):
continue
if self.image_cutflow.cut('image_amplitude', np.sum(cleaned)):
continue
# Image parametrisation
params = hillas_parameters(camera, cleaned)
# Save Ids, MC infos and Hillas informations
self.writer.write(camera.cam_id, [event.r0, event.mc, params])
def finish(self):
self.log.info('End of job.')
self.image_cutflow()
self.event_cutflow()
self.writer.close()
class SimpleEventWriter(Tool):
name = 'ctapipe-simple-event-writer'
description = Unicode(__doc__)
infile = Unicode(help='input file to read', default='').tag(config=True)
outfile = Unicode(help='output file name', default_value='output.h5').tag(config=True)
progress = Bool(help='display progress bar', default_value=True).tag(config=True)
aliases = Dict({
'infile': 'EventSourceFactory.input_url',
'outfile': 'SimpleEventWriter.outfile',
'max-events': 'EventSourceFactory.max_events',
'progress': 'SimpleEventWriter.progress'
})
classes = List([EventSourceFactory, CameraCalibrator, CutFlow])
def setup(self):
self.log.info('Configure EventSourceFactory...')
self.event_source = EventSourceFactory.produce(
config=self.config, tool=self, product='SimTelEventSource'
)
self.event_source.allowed_tels = self.config['Analysis']['allowed_tels']
self.calibrator = CameraCalibrator(
config=self.config, tool=self, eventsource=self.event_source
)
self.writer = HDF5TableWriter(
filename=self.outfile, group_name='image_infos', overwrite=True
)
# Define Pre-selection for images
preselcuts = self.config['Preselect']
self.image_cutflow = CutFlow('Image preselection')
self.image_cutflow.set_cuts(dict(
no_sel=None,
n_pixel=lambda s: np.count_nonzero(s) < preselcuts['n_pixel']['min'],
image_amplitude=lambda q: q < preselcuts['image_amplitude']['min']
))
# Define Pre-selection for events
self.event_cutflow = CutFlow('Event preselection')
self.event_cutflow.set_cuts(dict(
no_sel=None
))
def start(self):
self.log.info('Loop on events...')
for event in tqdm(
self.event_source,
desc='EventWriter',
total=self.event_source.max_events,
disable=~self.progress):
self.event_cutflow.count('no_sel')
self.calibrator.calibrate(event)
for tel_id in event.dl0.tels_with_data:
self.image_cutflow.count('no_sel')
camera = event.inst.subarray.tel[tel_id].camera
dl1_tel = event.dl1.tel[tel_id]
# Image cleaning
image = dl1_tel.image[0] # Waiting for automatic gain selection
mask = tailcuts_clean(camera, image, picture_thresh=10, boundary_thresh=5)
cleaned = image.copy()
cleaned[~mask] = 0
# Preselection cuts
if self.image_cutflow.cut('n_pixel', cleaned):
continue
if self.image_cutflow.cut('image_amplitude', np.sum(cleaned)):
continue
# Image parametrisation
params = hillas_parameters(camera, cleaned)
# Save Ids, MC infos and Hillas informations
self.writer.write(camera.cam_id, [event.r0, event.mc, params])
def finish(self):
self.log.info('End of job.')
self.image_cutflow()
self.event_cutflow()
self.writer.close()