cube - Map cube analysis¶

Introduction¶

The gammapy.cube sub-package contains functions and classes to make maps (counts, exposure, background), as well as to compute an effective PSF and energy dispersion for a given set of observations.

It also contains classes that represent cube models (sky maps with an energy axis), and classes to evaluate and fit those models to data.

Getting Started¶

TODO: what to show here?

Using gammapy.cube¶

Gammapy tutorial notebooks that show examples using gammapy.cube:

Reference/API¶

gammapy.cube Package¶

Sky cubes (3-dimensional: energy, lon, lat).

Functions¶

 fill_map_counts(counts_map, events) Fill events into a counts map. make_map_background_irf(pointing, ontime, …) Compute background map from background IRFs. make_map_exposure_true_energy(pointing, …) Compute exposure map. make_psf_map(psf, pointing, geom, max_offset) Make a psf map for a single observation

Classes¶

 MapEvaluator([model, exposure, background, …]) Sky model evaluation on maps. MapFit(model, counts, exposure[, …]) Perform sky model likelihood fit on maps. MapMaker(geom, offset_max[, geom_true, …]) Make maps from IACT observations. MapMakerObs(observation, geom[, geom_true, …]) Make maps for a single IACT observation. PSFKernel(psf_kernel_map) PSF kernel for Map. PSFMap(psf_map) Class containing the Map of PSFs and allowing to interact with it.

gammapy.cube.models Module¶

Classes¶

 SkyModelBase Sky model base class SkyModels(skymodels) Collection of SkyModel SkyModel(spatial_model, spectral_model[, name]) Sky model component. CompoundSkyModel(model1, model2, operator) Represents the algebraic combination of two SkyModel SkyDiffuseCube(map[, norm, meta, interp_kwargs]) Cube sky map template model (3D). BackgroundModel(background[, norm, tilt, …]) Background model