estimators - High level estimators

gammapy.estimators Package

Estimators.

Classes

ASmoothMapEstimator([scales, kernel, ...])	Adaptively smooth counts image.
Estimator()	Abstract estimator base class.
ExcessMapEstimator([correlation_radius, ...])	Computes correlated excess, significance and error maps from a map dataset.
FluxMaps(data, reference_model[, meta, gti, ...])	A flux map / points container.
FluxPoints(data, reference_model[, meta, ...])	Flux points container.
FluxPointsEstimator([energy_edges, ...])	Flux points estimator.
FluxProfileEstimator(regions[, spectrum])	Estimate flux profiles.
ImageProfile(table)	Image profile class.
ImageProfileEstimator([x_edges, method, ...])	Estimate profile from image.
LightCurveEstimator([time_intervals, atol])	Estimate light curve.
ParameterEstimator([n_sigma, n_sigma_ul, ...])	Model parameter estimator.
SensitivityEstimator([spectrum, n_sigma, ...])	Estimate sensitivity.
TSMapEstimator([model, kernel_width, ...])	Compute test statistic map from a MapDataset using different optimization methods.
EnergyDependentMorphologyEstimator(energy_edges)	Test if there is any energy-dependent morphology in a map dataset for a given set of energy bins.
FluxMetaData(*, sed_type, sed_type_init, ...)	Metadata containing information about the FluxPoints and FluxMaps.

Variables

ESTIMATOR_REGISTRY

Registry of estimator classes in Gammapy.

gammapy.estimators.utils Module

Functions

estimate_exposure_reco_energy(dataset[, ...])	Estimate an exposure map in reconstructed energy.
find_peaks(image, threshold[, min_distance])	Find local peaks in an image.
resample_energy_edges(dataset[, conditions])	Return energy edges that satisfy given condition on the per bin statistics.
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.
find_peaks_in_flux_map(maps, threshold[, ...])	Find local test statistic peaks for a given Map.
get_rebinned_axis(fluxpoint[, axis_name, method])	Get the rebinned axis for resampling