Background estimation (background)

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_alpha(theta, r_in, r_out) Compute ring alpha, the inverse area factor.
ring_area_factor(theta, r_in, r_out) Compute ring area factor.
ring_background_estimate(pos, on_radius, …) Simple ring background estimate.
ring_r_out(theta, r_in, area_factor) Compute ring outer radius.

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.