integrator.base module#

class integrator.base.ClusterConfiguration(workers: int = 1, cores: int = 8, processes: int = 1, memory: str = '100GB', project: str = 'azimuthal_integration', walltime: str = '01:00:00', queue: str = 'nice', scheduler_options: Any = None, python: str = '/home/pierre/.venv/python39/bin/python3', job_extra: Any = None)#

Bases: object

workers: int = 1#
cores: int = 8#
processes: int = 1#
memory: str = '100GB'#
project: str = 'azimuthal_integration'#
walltime: str = '01:00:00'#
queue: str = 'nice'#
scheduler_options: Any = None#
python: str = '/home/pierre/.venv/python39/bin/python3'#
job_extra: Any = None#
class integrator.base.DistributedIntegrator(ai_config, resources, dataset=None, output_file=None, n_images_per_integrator='auto', logger=None, extra_options=None, **integrator_kwargs)#

Bases: object

A base class for distributing StackIntegrator.

Initialize a DistributedStackIntegrator.

Parameters

  • ai_config (AIConfiguration) – Azimuthal Integration configuration

  • processing_resources (any) – Data structure describing computational resources

  • dataset (DatasetParser, optional) – XRD dataset information object. If not provided, set_new_dataset() will have to be called prior to integrate_dataset().

  • output_file (str, optional) – Path where the integrated data will be stored (hdf5 file)

  • n_images_per_integrator (int, optional) – Number of images to process at each stack. By default it is automatically inferred by inspecting the dataset file

  • logger (Logger) – Logger object

  • extra_options (dict, optional) –

    Dictionary of advanced options. Current values are:
    • ”create_h5_subfolders”: True

      Whether to create a sub-directory to store files that contain the result of each integrated stack

    • ”scan_num_as_h5_entry”: False

      Whether to use the current scan number as HDF5 entry.

  • class. (The other named arguments (**kwargs) are passed to the StackIntegrator) –

set_new_dataset(dataset, output_file)#