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/py39/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/py39/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)