estimators - High level estimators#

gammapy.estimators Package#

Estimators.

`ASmoothMapEstimator`	Adaptively smooth counts image.
`Estimator`	Abstract estimator base class.
`ExcessMapEstimator`	Computes correlated excess, significance, flux and error maps, and optionally upper limits or sensitivity from a map dataset.
`FluxMaps`	A flux map / points container.
`FluxPoints`	Flux points container.
`FluxPointsEstimator`	Flux points estimator.
`FluxProfileEstimator`	Estimate flux profiles.
`ImageProfile`	Image profile class.
`ImageProfileEstimator`	Estimate profile from image.
`LightCurveEstimator`	Estimate light curve.
`ParameterEstimator`	Model parameter estimator.
`SensitivityEstimator`	Estimate sensitivity.
`ParameterSensitivityEstimator`	Estimate the sensitivity to a given parameter.
`TSMapEstimator`	Compute test statistic map from a MapDataset using different optimization methods.
`EnergyDependentMorphologyEstimator`	Test if there is any energy-dependent morphology in a map dataset for a given set of energy bins.
`FluxMetaData`	Metadata containing information about the FluxPoints and FluxMaps.

Registry of estimator classes in Gammapy.

`combine_flux_maps`(maps[, method, ...])	Create a FluxMaps by combining a list of flux maps with the same geometry.
`combine_significance_maps`(maps)	Compute excess and significance for a set of datasets.
`estimate_exposure_reco_energy`(dataset[, ...])	Estimate an exposure map in reconstructed energy.
`find_peaks`(image, threshold[, min_distance])	Find local peaks in an image.
`find_peaks_in_flux_map`(maps, threshold[, ...])	Find local test statistic peaks for a given Map.
`resample_energy_edges`(dataset[, conditions])	Return energy edges that satisfy given condition on the per bin statistics.
`get_rebinned_axis`(fluxpoint[, axis_name, method])	Get the rebinned axis for resampling the flux point object along the mentioned axis.
`get_combined_flux_maps`(estimator, datasets)	Create a `FluxMaps` by combining a list of flux maps with the same geometry.
`get_combined_significance_maps`(estimator, ...)	Compute excess and significance for a set of datasets.
`compute_lightcurve_fvar`(lightcurve[, ...])	Compute the fractional excess variance of the input lightcurve.
`compute_lightcurve_fpp`(lightcurve[, ...])	Compute the point-to-point excess variance of the input lightcurve.
`compute_lightcurve_doublingtime`(lightcurve)	Compute the minimum characteristic flux doubling and halving time for the input lightcurve.
`compute_lightcurve_discrete_correlation`(...)	Compute the discrete correlation function for two lightcurves, or the discrete autocorrelation if only one lightcurve is provided.