DatasetsMaker

class gammapy.makers.DatasetsMaker(makers, stack_datasets=True, n_jobs=None, cutout_mode='trim', cutout_width=None, parallel_backend=None)

Bases: gammapy.makers.core.Maker, gammapy.utils.parallel.ParallelMixin

Run makers in a chain.

Parameters

makerslist of Maker objects

Makers.

stack_datasetsbool, optional

If True, stack into the reference dataset (see run method arguments). Default is True.

n_jobsint, optional

Number of processes to run in parallel. Default is one, unless N_JOBS_DEFAULT was modified.

cutout_mode{‘trim’, ‘partial’, ‘strict’}, optional

Used only to cutout the reference MapDataset around each processed observation. Mode is an option for Cutout2D, for details see Cutout2D. Default is “trim”.

cutout_widthtuple of Angle, optional

Angular sizes of the region in (lon, lat) in that specific order. If only one value is passed, a square region is extracted. If None it returns an error, except if the list of makers includes a SafeMaskMaker with the offset-max method defined. In that case it is set to two times offset_max. Default is None.

parallel_backend{‘multiprocessing’, ‘ray’}, optional

Which backend to use for multiprocessing. Default is None.

Attributes Summary

offset_max
safe_mask_maker
tag

Methods Summary

callback(dataset)
error_callback(dataset)
make_dataset(dataset, observation)	Make single dataset.
run(dataset, observations[, datasets])	Run data reduction.

Attributes Documentation

offset_max

safe_mask_maker

tag = 'DatasetsMaker'

Methods Documentation

callback(dataset)

error_callback(dataset)

make_dataset(dataset, observation)

Make single dataset.

Parameters

datasetMapDataset

Reference dataset.

observationObservation

Observation.

run(dataset, observations, datasets=None)

Run data reduction.

Parameters

datasetMapDataset

Reference dataset (used only for stacking if datasets are provided).

observationsObservations

Observations.

datasetsDatasets

Base datasets, if provided its length must be the same as the observations.

Returns

datasetsDatasets

Datasets.