PIG 19 - Gammapy package structure follow up#

  • Author: Axel Donath, Régis Terrier

  • Created: Jan 16, 2020

  • Accepted: Feb 24, 2020

  • Status: accepted

  • Discussion: GH 2720

Abstract#

Following the proposal in PIG 16 - Gammapy package structure the subpackages gammapy.image and gammapy.background were removed and a new gammapy.modeling sub-package was introduced. These changes followed the general idea of rather giving up the separation between 1D, 2D and 3D analysis use-cases and instead structuring the package by concept. In this sense gammapy.modeling now contains all models, including base classes (Model) a container classes (SkyModels), a registry object MODELS and many sub-classes. A previous step in this direction was made by introducing the gammapy.maps sub-package which resolved the distinction between the 2D and 3D data structures and replaced it with a general ND map structure. The outlook in PIG 16 - Gammapy package structure already proposed the possibility to make further changes to the package structure leading in the same direction. This PIG now proposes these changes in more detail, especially introducing new gammapy.datasets, gammapy.makers and gammapy.estimators sub-packages. This restructuring of the package will also reflect the general API and data analysis workflow in a better way.

Proposal#

Introduce gammapy.datasets#

The Dataset abstraction is now the central data container for any likelihood based analysis in Gammapy. It includes a base-class (Dataset) a container class (Datasets) and many specific implementations such as the MapDataset, SpectrumDataset or FluxPointsDataset. Currently the different sub-classes are implemented in different sub-packages gammapy.cube, gammapy.spectrum while the base and container class are defined in gammapy.modeling, where also a dataset registry is defined.

This scattered implementation of the sub-classes seems non-intuitive and leads to practical problems such as circular imports. Currently the dataset registry (defined in gammapy.modeling.serialize) imports from gammapy.spectrum and gammapy.cube, while the latter sub-modules import the Dataset base class from gammapy.modeling. Another minor problem occurs in documentation, where there is no obvious place to document the concept of a dataset.

For this reason we propose to introduce a gammapy.datasets sub-package and move the base class, the container class, the registry, existing implementations of sub-classes and I/O related functionality there.

Introduce gammapy.makers#

In the past year we introduced a configurable and flexible Maker system for data reduction in gammapy, currently implemented in gammapy.spectrum and gammapy.cube. A common SafeMaskMaker is implemented in gammapy.cube but used for spectral data reduction as well. The documentation is currently split between gammapy.cube and gammapy.spectrum and partly duplicated in multiple tutorials. While already being in use, the system is not yet fully developed. A common Maker base class, a container class such as Makers and a MAKERS registry is still missing.

In analogy to the datasets we propose to introduce a gammapy.makers sub-package as a common namespace for all data-reduction related functionality. This gives again an obvious place to define a common API using base classes and defining registry and container class as well. All existing Maker classes should be moved there. Later a common base class, a registry and a container class as well as common configuration and serialisation handling can be moved there.

Introduce gammapy.estimators#

Gammapy already defines a number of Estimator classes. In general an estimator can be seen as a higher level maker class, taking a dataset on input and computing derived outputs from it, mostly based on likelihood fits. This includes spectral points, lightcurves, significance maps etc. Again those classes are split among multiple sub-packages, such as gammapy.spectrum, gammapy.time, gammapy.detect and gammapy.maps.

The existing estimator classes can be mainly divided into two groups;

  • Flux estimators such as the LightCurveEstimator and FluxPointsEstimator where the output is a table like object.

  • Map estimators such as the TSMapEstimator or the ASmoothEstimator where the output is a Map or dict of Map object.

No clear API definition via a common base class, nor a registry for such estimators exists. Already now there is code duplication between the LightCurveEstimator and FluxPointsEstimator, which could be resolved by a common FluxEstimator base class (see GH 2555).

For this reason we propose to introduce a gammapy.estimators sub-package to group all existing estimator classes into the same namespace. This provides the possibility in future to define a common API via base classes, introducing general higher level estimators and a common configuration system.

Introduce gammapy.visualization#

To group plotting and data visualisation related functionality in a single namespace we propose to introduce gammapy.visualization. The model of a separate sub-package for plotting was adopted by many other large astronomical python packages, such as astropy, sunpy, ctapipe and sherpa. So far the plotting functionality in Gammapy is limited and mostly attached to data objects such as datasets, maps and irfs. Introducing gammapy.visualization would be a possibility to maintain plotting related code independently and move existing functionality such as MapPanelPlotter or colormap_hess etc. to a common namespace.

Resolve gammapy.detect#

If we introduce gammapy.estimators and the TSMapEstimator, LiMaMapEstimator, ASmoothMapEstimator and KernelBackgroundMapEstimator have been moved the gammapy.detect package can be resolved.

Minor changes#

In addition we propose to move the PSFKernel, EDispMap and PSFMap classes to gammapy.irf. Those classes represent a “reduced” IRF and are therefore similar to the existing EnergyDependentTablePSF or TablePSF classes.

Alternatives#

An alternative approach could be to introduce a gammapy.core sub-package that contains all base-classes, container classes and registries. For each sub-package an subpackage/plotting.py file, could be introduced where plotting related functionality lives.

Outlook#

Once the functionality on data reduction, datasets and estimators has been removed to the corresponding sub-packages, the gammapy.cube and gammapy.spectrum packages can possibly be resolved.

Decision#

This PIG received only little feedback, but there was general agreement in GH 2720 on the introduction of the gammapy.datasets and gammapy.makers sub-packages as well as the location of irf maps. Those changes will be introduced first. There was some concern about the gammapy.estimators sub-package. For this reason the implementation of this will be delayed and can be re-discussed at the next Gammapy coding sprint in person. A final review announced on the Gammapy and CC mailing list did not yield any additional comments. Therefore the PIG was accepted on Feb 24, 2020.