def __init__(self, file_path, *, gain_file="", pedestal_file=""):
with h5py.File(file_path, "r") as h5f:
detector_name = h5f["/general/detector_name"][()].decode()
self.handler = JFDataHandler(detector_name)
if "module_map" in h5f[f"/data/{detector_name}"]:
# Pick only the first row (module_map of the first frame), because it is not
# expected that module_map ever changes during a run. In fact, it is forseen in the
# future that this data will be saved as a single row for the whole run.
module_map = h5f[f"/data/{detector_name}/module_map"][0, :]
else:
module_map = None
self.handler.module_map = module_map
# TODO: Here we use daq_rec only of the first pulse within an hdf5 file, however its
# value can be different for later pulses and this needs to be taken care of.
daq_rec = h5f[f"/data/{detector_name}/daq_rec"][0]
self.handler.highgain = daq_rec & 0b1
# Gain file
if not gain_file:
gain_file = locate_gain_file(file_path)
self.handler.gain_file = gain_file
# Pedestal file (with a pixel mask)
if not pedestal_file:
pedestal_file = locate_pedestal_file(file_path)
self.handler.pedestal_file = pedestal_file
def __init__(
self,
file_path,
*,
gain_file="",
pedestal_file="",
conversion=True,
mask=True,
gap_pixels=True,
double_pixels="keep",
geometry=True,
parallel=True,
):
self.file_path = Path(file_path)
self.file = h5py.File(self.file_path, "r")
self.handler = JFDataHandler(
self.file["general/detector_name"][()].decode())
self._conversion = conversion
self._mask = mask
self._gap_pixels = gap_pixels
self._double_pixels = double_pixels
self._geometry = geometry
self._parallel = parallel
# No need for any further setup if the file is already processed
if self._processed:
return
# Gain file
if not gain_file:
gain_file = locate_gain_file(file_path)
self.handler.gain_file = gain_file
# Pedestal file (with a pixel mask)
if not pedestal_file:
pedestal_file = locate_pedestal_file(file_path)
self.handler.pedestal_file = pedestal_file
if "module_map" in self.file[f"data/{self.detector_name}"]:
# Pick only the first row (module_map of the first frame), because it is not expected
# that module_map ever changes during a run. In fact, it is forseen in the future that
# this data will be saved as a single row for the whole run.
module_map = self.file[f"data/{self.detector_name}/module_map"][
0, :]
else:
module_map = None
self.handler.module_map = module_map
# TODO: Here we use daq_rec only of the first pulse within an hdf5 file, however its
# value can be different for later pulses and this needs to be taken care of. Currently,
# _allow_n_images decorator applies a function in a loop, making it impossible to change
# highgain for separate images in a 3D stack.
daq_rec = self.file[f"data/{self.detector_name}/daq_rec"][0]
self.handler.highgain = daq_rec & 0b1
def __init__(
self,
file_path,
gain_file="",
pedestal_file="",
conversion=True,
mask=True,
gap_pixels=True,
geometry=True,
parallel=True,
):
"""Create a new Jungfrau file wrapper.
Args:
file_path (str): Path to Jungfrau file
gain_file (str, optional): Path to gain file. Auto-locate if empty. Defaults to ''.
pedestal_file (str, optional): Path to pedestal file. Auto-locate if empty.
Defaults to ''.
conversion (bool, optional): Apply gain conversion and pedestal correction.
Defaults to True.
mask (bool, optional): Perform masking of bad pixels (assign them to 0).
Defaults to True.
gap_pixels (bool, optional): Add gap pixels between detector chips.
Defaults to True.
geometry (bool, optional): Apply geometry correction. Defaults to True.
parallel (bool, optional): Use parallelized processing. Defaults to True.
"""
self.file_path = Path(file_path)
self.file = h5py.File(self.file_path, "r")
self.handler = JFDataHandler(self.file["/general/detector_name"][()].decode())
self._conversion = conversion
self._mask = mask
self._gap_pixels = gap_pixels
self._geometry = geometry
self._parallel = parallel
# Gain file
if not gain_file:
gain_file = locate_gain_file(file_path)
self.handler.gain_file = gain_file
# Pedestal file (with a pixel mask)
if not pedestal_file:
pedestal_file = locate_pedestal_file(file_path)
self.handler.pedestal_file = pedestal_file
if "module_map" in self.file[f"/data/{self.detector_name}"]:
# Pick only the first row (module_map of the first frame), because it is not expected
# that module_map ever changes during a run. In fact, it is forseen in the future that
# this data will be saved as a single row for the whole run.
module_map = self.file[f"/data/{self.detector_name}/module_map"][0, :]
else:
module_map = None
self.handler.module_map = module_map
# TODO: Here we use daq_rec only of the first pulse within an hdf5 file, however its
# value can be different for later pulses and this needs to be taken care of. Currently,
# _allow_n_images decorator applies a function in a loop, making it impossible to change
# highgain for separate images in a 3D stack.
daq_rec = self.file[f"/data/{self.detector_name}/daq_rec"][0]
self.handler.highgain = daq_rec & 0b1