integrator.multiproc_integration module

class integrator.multiproc_integration.MultiprocIntegrator(ai_config, resources, dataset=None, output_file=None, n_images_per_integrator='auto', logger=None, extra_options=None, **integrator_kwargs)

Bases: integrator.base.DistributedIntegrator

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) –

device_type = 'gpu'

set_new_dataset(datasets, output_files)

set_workers_name_prefix(name_prefix=None)

distribute_integration_tasks()

close_processes(timeout=None)

integrator.multiproc_integration.worker_scan(worker_name, ai_config, n_threads, datasets, output_files, output_dirs, extra_options=None)

integrator.multiproc_integration.mp_integrate_datasets(ai_config, resources, datasets, output_files, worker_id, **kwargs)