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

profile_background_estimate(pos, on_radius, …)

Simple profile background estimation

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.