# background - Background modeling¶

## Introduction¶

gammapy.background contains methods to estimate and model background for specral, image based and cube analyses.

Most of the methods implemented are described in [Berge2007]. Section 7.3 “Background subtraction” and Section 7.4 “Acceptance determination and predicted background” in [Naurois2012] describe mostly the same methods as [Berge2007], except for the “2D acceptance model” described in Section 7.4.3.

## Getting Started¶

TODO: example how to read and use a 2D and A 3D background model

## Using gammapy.background¶

If you’d like to learn more about using gammapy.background, read the following sub-pages:

## Reference/API¶

### gammapy.background Package¶

Background estimation and modeling methods.

#### Functions¶

 ring_background_estimate(pos, on_radius, …) Simple ring background estimate.

#### Classes¶

 AdaptiveRingBackgroundEstimator(r_in, …[, …]) Adaptive ring background algorithm. BackgroundEstimate(on_region, on_events, …) Container class for background estimate. PhaseBackgroundEstimator(on_region, …) Background estimation with on and off phases. ReflectedRegionsBackgroundEstimator(…) Reflected Regions background estimator. ReflectedRegionsFinder(region, center[, …]) Find reflected regions. RingBackgroundEstimator(r_in, width[, …]) Ring background method for cartesian coordinates.