ess.reflectometry.tools.batch_processor

ess.reflectometry.tools.batch_processor(workflow, runs)

Creates a collection of sciline workflows from the provided runs.

Example:

` :rtype: :sphinx_autodoc_typehints_type:`\:py\:class\:\`\~ess.reflectometry.tools.BatchProcessor\

from ess.reflectometry import amor, tools

workflow = amor.AmorWorkflow()

runs = {

‘608’: {

SampleRotationOffset[SampleRun]: sc.scalar(0.05, unit=’deg’), Filename[SampleRun]: “file_608.hdf”,

}, ‘609’: {

SampleRotationOffset[SampleRun]: sc.scalar(0.05, unit=’deg’), Filename[SampleRun]: “file_609.hdf”,

}, ‘610’: {

SampleRotationOffset[SampleRun]: sc.scalar(0.05, unit=’deg’), Filename[SampleRun]: “file_610.hdf”,

}, ‘611’: {

SampleRotationOffset[SampleRun]: sc.scalar(0.05, unit=’deg’), Filename[SampleRun]: “file_611.hdf”,

},

}

batch = tools.batch_processor(workflow, runs)

results = batch.compute(ReflectivityOverQ) ```

Additionally, if a list of filenames is provided for Filename[SampleRun], the events from the files will be concatenated into a single event list before processing.

Example:

``` runs = {

‘608’: {

Filename[SampleRun]: “file_608.hdf”,

}, ‘609+610’: {

Filename[SampleRun]: [“file_609.hdf”, “file_610.hdf”],

},

}

type workflow:

Pipeline

param workflow:

The sciline workflow used to compute the targets for each of the runs.

type runs:

Mapping[Any, Mapping[type, Any]]

param runs:

The sciline parameters to be used for each run. Should be a mapping where the keys are the names of the runs and the values are mappings of type to value pairs. In addition, if one of the values for Filename[SampleRun] is a list or a tuple, then the events from the files will be concatenated into a single event list.