integrator.hdf5 module#

integrator.hdf5.get_string(str_or_bytes)#
integrator.hdf5.get_h5obj_value(h5_obj, name, default=None)#
integrator.hdf5.is_dataset_entry(entry)#
integrator.hdf5.list_datasets(fname)#

List the entries in the form X.1 in a file

integrator.hdf5.list_datasets_with_attributes(fname, attrs, default=None)#
integrator.hdf5.get_data_sources(fname, data_path)#
class integrator.hdf5.HDF5Dataset(fname, entry=None, detector_name=None, logger=None)#

Bases: object

A simple class for parsing (ESRF) HDF5 datasets

Build a Dataset object. Each object is tied to only one entry.

fname: str

Path to the HDF5 file.

entry: str, optional

HDF5 entry. If not provided, the first entry is taken.

detector_name: str, optional

Detector name

logger: Logger, optional

Logging object

property exposure_time#

Get the exposure time in seconds

class integrator.hdf5.ID15Dataset(fname, entry=None, detector_name=None, logger=None)#

Bases: integrator.hdf5.HDF5Dataset

Build a Dataset object. Each object is tied to only one entry.

fname: str

Path to the HDF5 file.

entry: str, optional

HDF5 entry. If not provided, the first entry is taken.

detector_name: str, optional

Detector name

logger: Logger, optional

Logging object

get_virtual_sources()#

Return a dict with the virtual sources of the current dataset.

get_stack_size(use_file_n=0)#

Get the current dataset stack size

Parameters

use_file_n (integer) – Which file to take to get stack size. Default is first file.

get_all_stacks_sizes()#
class integrator.hdf5.ID11Dataset(fname, entry=None, detector_name=None, logger=None)#

Bases: integrator.hdf5.HDF5Dataset

Build a Dataset object. Each object is tied to only one entry.

fname: str

Path to the HDF5 file.

entry: str, optional

HDF5 entry. If not provided, the first entry is taken.

detector_name: str, optional

Detector name

logger: Logger, optional

Logging object

integrator.hdf5.guess_detector_name(fname, entry)#
integrator.hdf5.get_metadata_for_tomography_reconstruction_id15a(dataset, on_error='print')#

Get the necessary metadata to perform a XRD-CT reconstruction

Parameters

  • dataset (ID15Dataset) – Data structure containing information on the current dataset

  • on_error (str) – What to do when an error occurs (eg. missing metadata). Possible values are “print”, “raise”, “ignore”

Returns

  • can_perform_tomo (bool) – Whether a tomography reconstruction can be performed based on the obtained metadata

  • common_params (dict) – Dictionary with parameters common to all acquisition types

  • fscan_params (dict) – Dictionary with parameters specific to the current scan type