def test_container():
cont = Container("data")
with pytest.raises(AttributeError):
cont.x
with pytest.raises(KeyError):
cont["x"]
with pytest.raises(AttributeError):
cont.x = 10
with pytest.raises(TypeError):
cont['x'] = 10
# test adding an item
cont.add_item('y')
assert cont.y is None
# test adding item with value:
cont.add_item('z', 10)
assert cont.z == 10
assert cont['z'] == 10
# test iteration (turn it into a list)
assert len(list(cont)) == 2
def init_dl1(event):
# Load dl1 container
container = Container("calibrated_hessio_container")
container.add_item("dl1", RawData())
container.meta.add_item('pixel_pos', dict())
container.meta.pixel_pos = event.meta.pixel_pos
return container
def mock_event_source(
geoms,
events=100,
single_tel=False,
n_channels=1,
n_samples=25,
p_trigger=0.3,
):
"""
An event source that produces array
Parameters
----------
geoms : list of CameraGeometry instances
Geometries for the telescopes to simulate
events : int, default: 100
maximum number of events to create
n_channels : int
how many channels per telescope
n_samples : int
how many adc samples per pixel
p_trigger : float
mean trigger probability for the telescopes
"""
n_telescopes = len(geoms)
container = Container("mock_container")
container.meta.add_item('mock__max_events', events)
container.meta.add_item('pixel_pos', dict())
container.add_item("dl0", RawData())
container.add_item("count")
tel_ids = np.arange(n_telescopes)
for event_id in range(events):
n_triggered = np.random.poisson(n_telescopes * 0.3)
if n_triggered > n_telescopes:
n_triggered = n_telescopes
triggered_tels = np.random.choice(tel_ids, n_triggered, replace=False)
container.dl0.event_id = event_id
container.dl0.tels_with_data = triggered_tels
container.count = event_id
# handle single-telescope case (ignore others:
if single_tel:
if single_tel not in container.dl0.tels_with_data:
continue
container.dl0.tels_with_data = [single_tel, ]
container.dl0.tel = dict() # clear the previous telescopes
t = np.arange(n_samples)
for tel_id in container.dl0.tels_with_data:
geom = geoms[tel_id]
# fill pixel position dictionary, if not already done:
if tel_id not in container.meta.pixel_pos:
container.meta.pixel_pos[tel_id] = (
geom.pix_x.value,
geom.pix_y.value,
)
centroid = np.random.uniform(geom.pix_x.min(), geom.pix_y.max(), 2)
length = np.random.uniform(0.02, 0.2)
width = np.random.uniform(0.01, length)
psi = np.random.randint(0, 360)
intensity = np.random.poisson(int(10000 * width * length))
model = mock.generate_2d_shower_model(
centroid,
width,
length,
'{}d'.format(psi)
)
image, _, _ = mock.make_mock_shower_image(
geom,
model.pdf,
intensity,
)
container.dl0.tel[tel_id] = RawCameraData(tel_id)
container.dl0.tel[tel_id].num_channels = n_channels
n_pix = len(geom.pix_id)
samples = np.empty((n_pix, n_samples))
means = np.random.normal(15, 1, (n_pix, 1))
stds = np.random.uniform(3, 6, (n_pix, 1))
samples = image[:, np.newaxis] * norm.pdf(t, means, stds)
for chan in range(n_channels):
container.dl0.tel[tel_id].adc_samples[chan] = samples
container.dl0.tel[tel_id].adc_sums[chan] = image
yield container
def zfits_event_source(url,
data_type='dl0',
max_events=None,
allowed_tels=None):
"""A generator that streams data from an EventIO/HESSIO MC data file
(e.g. a standard CTA data file.)
Parameters
----------
url : str
path to file to open
max_events : int, optional
maximum number of events to read
allowed_tels : list[int]
select only a subset of telescope, if None, all are read. This can
be used for example emulate the final CTA data format, where there
would be 1 telescope per file (whereas in current monte-carlo,
they are all interleaved into one file)
"""
try:
zfits = protozfitsreader.ZFile(url)
except:
raise RuntimeError(
"zfits_event_source failed to open '{}'".format(url))
if data_type == 'dl0':
counter = 0
eventstream = zfits.move_to_next_event()
container = Container("zfits_container")
container.meta.add_item('zfits__input', url)
container.meta.add_item('zfits__max_events', max_events)
container.meta.add_item('pixel_pos', dict())
container.add_item("dl0", RawData())
container.add_item("trig", CentralTriggerData())
container.add_item("count")
for run_id, event_id in eventstream:
container.dl0.run_id = run_id
container.dl0.event_id = event_id
#container.dl0.event_num = zfits.get_event_number()
# We assume we are in the single-telescope case always:
container.dl0.tels_with_data = [
zfits.event.telescopeID,
]
container.trig.tels_with_trigger = container.dl0.tels_with_data
time_s, time_ns = zfits.get_central_event_gps_time()
container.trig.gps_time = Time(time_s * u.s,
time_ns * u.ns,
format='gps',
scale='utc')
container.count = counter
t = np.arange(n_samples)
container.dl0.tel = dict() # clear the previous telescopes
# Depecrated loop, we keep it for clarity (similar structure than hessio and mock modules)
for tel_id in container.dl0.tels_with_data:
# fill pixel position dictionary, if not already done:
#TODO: tel_id here is a dummy parameter, we are dealing with single-telescope data!. TBR.
if tel_id not in container.meta.pixel_pos:
container.meta.pixel_pos[tel_id] = \
zfits.get_pixel_position(tel_id) * u.m
nchans = zfits.get_num_channels(tel_id)
container.dl0.tel[tel_id] = RawCameraData(tel_id)
container.dl0.tel[tel_id].num_channels = nchans
for chan in range(nchans):
samples = zfits.get_adc_sample(channel=chan,
telescope_id=tel_id)
integrated = zfits.get_adc_sum(channel=chan,
telescope_id=tel_id)
container.dl0.tel[tel_id].pixel_samples[
chan] = samples.keys()
mask = np.zeros(zfits.get_number_of_pixels(), dtype=bool)
mask[np.array(samples.keys())] = True
container.dl0.tel[tel_id].adc_samples[chan] = \
ma.array(np.array(samples.values()),mask=mask)
mask = np.zeros(zfits.get_number_of_pixels(), dtype=bool)
mask[np.array(integrated.keys())] = True
container.dl0.tel[tel_id].adc_integrated[chan] = \
ma.array(np.array(integrated.values()),mask=mask)
yield container
counter += 1
if data_type == 'r1':
'''
Fill container with r1 data type
'''
counter = 0
eventstream = zfits.move_to_next_event()
## The container
container = Container("zfits_container")
container.meta.add_item('zfits__input', url)
container.meta.add_item('zfits__max_events', max_events)
container.add_item("r1", RawData())
container.add_item("count")
for run_id, event_id in eventstream:
container.r1.run_id = run_id
container.r1.event_id = event_id
container.r1.tels_with_data = [
zfits.event.telescopeID,
]
container.count = counter
n_samples = zfits._get_numpyfield(
zfits.event.hiGain.waveforms.samples
).shape[0] // zfits._get_numpyfield(
zfits.event.hiGain.waveforms.pixelsIndices).shape[0]
t = np.arange(n_samples)
container.r1.tel = dict() # clear the previous telescopes
for tel_id in container.r1.tels_with_data:
# Create the camera raw data container
container.r1.tel[tel_id] = RawCameraData(tel_id)
# Fill it with original fields
container.r1.tel[tel_id].num_channels = zfits.event.num_gains
container.r1.tel[tel_id].num_pixels = zfits._get_numpyfield(
zfits.event.hiGain.waveforms.pixelsIndices).shape[0]
container.r1.tel[tel_id].num_samples = n_samples
container.r1.tel[tel_id].adc_samples = zfits.get_adcs_samples(
telescope_id=tel_id)
# Add extra relevant fields
# container.r1.tel[tel_id].add_item("pixel_flags")
# container.r1.tel[tel_id].pixel_flags = zfits.get_pixel_flags(telescope_id=tel_id)
yield container
counter += 1
if max_events is not None and counter > max_events:
return
"""
peds, gains = get_mc_calibration_coeffs(tel_id)
return (adcs - peds) * gains
if __name__ == '__main__':
parser = argparse.ArgumentParser(description='Perform simple Hillas Reco')
parser.add_argument('filename', metavar='EVENTIO_FILE', nargs='?',
default=get_example_simtelarray_file())
args = parser.parse_args()
source = hessio_event_source(args.filename)
container = Container("hessio_container")
container.meta.add_item('pixel_pos', dict())
container.add_item("dl0", RawData())
container.add_item("mc", MCShowerData())
container.add_item("trig", CentralTriggerData())
container.add_item("count")
tel,cam,opt = ID.load(filename=args.filename)
ev = 0
efficiency = list()
efficiency.append(list())
efficiency.append(list())
efficiency.append(list())
efficiency.append(list())
impact = list()
def zfits_event_source(url, max_events=None):
"""A generator that streams data from an EventIO/HESSIO MC data file
(e.g. a standard CTA data file.)
Parameters
----------
url : str
path to file to open
max_events : int, optional
maximum number of events to read
"""
try:
zfits = protozfitsreader.ZFile(url)
except:
raise RuntimeError(
"zfits_event_source failed to open '{}'".format(url))
counter = 0
eventstream = zfits.move_to_next_event()
container = Container()
container.meta.add_item('zfits__input', url)
container.meta.add_item('zfits__max_events', events)
container.meta.add_item('pixel_pos', dict())
container.add_item("r0", R0Container())
container.add_item("trig", CentralTriggerData())
container.add_item("count")
for obs_id, event_id in eventstream:
container.dl0.obs_id = obs_id
container.dl0.event_id = event_id
# container.r0.event_num = zfits.get_event_number()
# We assume we are in the single-telescope case always:
container.dl0.tels_with_data = [
zfits.get_telescope_id(),
]
container.trig.tels_with_trigger = container.dl0.tels_with_data
time_s, time_ns = zfits.get_central_event_gps_time()
container.trig.gps_time = Time(time_s * u.s,
time_ns * u.ns,
format='gps',
scale='utc')
container.count = counter
container.dl0.tel = dict() # clear the previous telescopes
# Depecrated loop, we keep it for clarity (similar structure than hessio
# and toymodel modules)
for tel_id in container.dl0.tels_with_data:
# fill pixel position dictionary, if not already done:
# TODO: tel_id here is a dummy parameter, we are dealing with
# single-telescope data!. TBR.
nchans = zfits.get_num_channels(tel_id)
for chan in range(nchans):
tel = container.dl0.tel[tel_id]
samples = zfits.get_adc_sample(channel=chan,
telescope_id=tel_id)
integrated = zfits.get_adc_sum(channel=chan,
telescope_id=tel_id)
tel.pixel_samples[chan] = samples.keys()
mask = np.zeros(zfits.get_number_of_pixels(), dtype=bool)
mask[np.array(samples.keys())] = True
tel.waveform[chan] = ma.array(np.array(samples.values()),
mask=mask)
mask = np.zeros(zfits.get_number_of_pixels(), dtype=bool)
mask[np.array(integrated.keys())] = True
tel.adc_integrated[chan] = ma.array(np.array(
integrated.values()),
mask=mask)
yield container
counter += 1
if max_events is not None and counter > max_events:
return
def test_container_metadata():
cont = Container("data")
cont.meta.add_item("version", 2.0)
assert cont.meta.version == 2.0
def hessio_event_source(url, max_events=None, single_tel=None):
"""A generator that streams data from an EventIO/HESSIO MC data file
(e.g. a standard CTA data file.)
Parameters
----------
url : str
path to file to open
max_events : int, optional
maximum number of events to read
single_tel : int
select only a single telescope, if None, all are read. This is
to emulate the final CTA data format, where there would be 1
telescope per file (whereas in current monte-carlo, they are
all interleaved into one file)
"""
ret = hessio.file_open(url)
if ret is not 0:
raise RuntimeError(
"hessio_event_source failed to open '{}'".format(url))
counter = 0
eventstream = hessio.move_to_next_event()
container = Container("hessio_container")
container.meta.add_item('hessio__input', url)
container.meta.add_item('hessio__max_events', max_events)
container.meta.add_item('pixel_pos', dict())
container.add_item("dl0", RawData())
container.add_item("count")
for run_id, event_id in eventstream:
container.dl0.run_id = run_id
container.dl0.event_id = event_id
container.dl0.tels_with_data = hessio.get_teldata_list()
container.count = counter
# handle single-telescope case (ignore others:
if single_tel is not None:
if single_tel not in container.dl0.tels_with_data:
continue
container.dl0.tels_with_data = [
single_tel,
]
# this should be done in a nicer way to not re-allocate the
# data each time (right now it's just deleted and garbage
# collected)
container.dl0.tel = dict() # clear the previous telescopes
for tel_id in container.dl0.tels_with_data:
# fill pixel position dictionary, if not already done:
if tel_id not in container.meta.pixel_pos:
container.meta.pixel_pos[tel_id] = hessio.get_pixel_position(
tel_id)
nchans = hessio.get_num_channel(tel_id)
container.dl0.tel[tel_id] = RawCameraData(tel_id)
container.dl0.tel[tel_id].num_channels = nchans
# load the data per telescope/chan
for chan in range(nchans):
container.dl0.tel[tel_id].adc_samples[chan] \
= hessio.get_adc_sample(channel=chan,
telescope_id=tel_id)
container.dl0.tel[tel_id].adc_sums[chan] \
= hessio.get_adc_sum(channel=chan,
telescope_id=tel_id)
yield container
counter += 1
if max_events is not None and counter > max_events:
return
def hessio_event_source(url, max_events=None, allowed_tels=None):
"""A generator that streams data from an EventIO/HESSIO MC data file
(e.g. a standard CTA data file.)
Parameters
----------
url : str
path to file to open
max_events : int, optional
maximum number of events to read
allowed_tels : list[int]
select only a subset of telescope, if None, all are read. This can
be used for example emulate the final CTA data format, where there
would be 1 telescope per file (whereas in current monte-carlo,
they are all interleaved into one file)
"""
ret = pyhessio.file_open(url)
if ret is not 0:
raise RuntimeError(
"hessio_event_source failed to open '{}'".format(url))
counter = 0
eventstream = pyhessio.move_to_next_event()
if allowed_tels is not None:
allowed_tels = set(allowed_tels)
container = Container("hessio_container")
container.meta.add_item('hessio__input', url)
container.meta.add_item('hessio__max_events', max_events)
container.meta.add_item('pixel_pos', dict())
container.meta.add_item('optical_foclen', dict())
container.add_item("dl0", RawData())
container.add_item("mc", MCShowerData())
container.add_item("trig", CentralTriggerData())
container.add_item("count")
for run_id, event_id in eventstream:
container.dl0.run_id = run_id
container.dl0.event_id = event_id
container.dl0.tels_with_data = set(pyhessio.get_teldata_list())
# handle telescope filtering by taking the intersection of
# tels_with_data and allowed_tels
if allowed_tels is not None:
selected = container.dl0.tels_with_data & allowed_tels
if len(selected) == 0:
continue # skip event
container.dl0.tels_with_data = selected
container.trig.tels_with_trigger \
= pyhessio.get_central_event_teltrg_list()
time_s, time_ns = pyhessio.get_central_event_gps_time()
container.trig.gps_time = Time(time_s * u.s,
time_ns * u.ns,
format='gps',
scale='utc')
container.mc.energy = pyhessio.get_mc_shower_energy() * u.TeV
container.mc.alt = Angle(pyhessio.get_mc_shower_altitude(), u.rad)
container.mc.az = Angle(pyhessio.get_mc_shower_azimuth(), u.rad)
container.mc.core_x = pyhessio.get_mc_event_xcore() * u.m
container.mc.core_y = pyhessio.get_mc_event_ycore() * u.m
container.count = counter
# this should be done in a nicer way to not re-allocate the
# data each time (right now it's just deleted and garbage
# collected)
container.dl0.tel = dict() # clear the previous telescopes
for tel_id in container.dl0.tels_with_data:
# fill pixel position dictionary, if not already done:
if tel_id not in container.meta.pixel_pos:
container.meta.pixel_pos[tel_id] \
= pyhessio.get_pixel_position(tel_id) * u.m
container.meta.optical_foclen[
tel_id] = pyhessio.get_optical_foclen(tel_id) * u.m
nchans = pyhessio.get_num_channel(tel_id)
container.dl0.tel[tel_id] = RawCameraData(tel_id)
container.dl0.tel[tel_id].num_channels = nchans
# load the data per telescope/chan
for chan in range(nchans):
container.dl0.tel[tel_id].adc_samples[chan] \
= pyhessio.get_adc_sample(channel=chan,
telescope_id=tel_id)
container.dl0.tel[tel_id].adc_sums[chan] \
= pyhessio.get_adc_sum(channel=chan,
telescope_id=tel_id)
yield container
counter += 1
if max_events is not None and counter > max_events:
return
