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.
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(…[, binsz]) |
Reflected Regions background estimator. |
ReflectedRegionsFinder(region, center[, …]) |
Find reflected regions. |
RingBackgroundEstimator(r_in, width) |
Ring background method for cartesian coordinates. |