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

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

n_jobsint

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

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

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

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.

parallel_backend{‘multiprocessing’, ‘ray’}

Which backend to use for multiprocessing.

Attributes Summary

n_jobs	Number of jobs (int)
offset_max
parallel_backend	Parallel backend (str)
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

n_jobs

Number of jobs (int)

offset_max

parallel_backend

Parallel backend (str)

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 than the observations.

Returns

datasetsDatasets

Datasets