# 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