.. include:: ../references.txt

.. _fov_background:

**************
FoV background
**************

.. currentmodule:: gammapy.makers

Overview
--------

Background models stored in IRF might not predict accurately the actual number of background counts.
To correct the predicted counts, one can use the data themselves in regions deprived of gamma-ray signal.
The field-of-view background technique is used to adjust the predicted counts on the measured ones outside
an exclusion mask. This technique is recommended for 3D analysis, in particular when stacking `Datasets`.

Gammapy provides the `~gammapy.makers.FoVBackgroundMaker`. The latter creates a
`~gammapy.modeling.models.FoVBackgroundModel` which combines the `background` predicted number of counts
and a `~gammapy.modeling.models.NormSpectralModel` which allows to renormalize the background cube, and
possibly to change its spectral distribution. By default, only the `norm` parameter of a
`~gammapy.modeling.models.PowerLaWNormSpectralModel` is left free. If needed the spectral parameters
can be unfrozen.

.. testcode::

	from gammapy.makers import MapDatasetMaker, FoVBackgroundMaker, SafeMaskMaker
	from gammapy.datasets import MapDataset
	from gammapy.data import DataStore
	from gammapy.maps import MapAxis, WcsGeom, Map
	from regions import CircleSkyRegion
	from astropy import units as u

	data_store = DataStore.from_dir("$GAMMAPY_DATA/hess-dl3-dr1")
	observations = data_store.get_observations([23592, 23559])

	energy_axis = MapAxis.from_energy_bounds("0.5 TeV", "10 TeV", nbin=5)
	energy_axis_true = MapAxis.from_energy_bounds("0.3 TeV", "20 TeV", nbin=20, name="energy_true")

	geom = WcsGeom.create(skydir=(83.63, 22.01), axes=[energy_axis], width=5, binsz=0.02)

	stacked = MapDataset.create(geom, energy_axis_true=energy_axis_true)

	maker = MapDatasetMaker()
	safe_mask_maker = SafeMaskMaker(
		methods=["aeff-default", "offset-max"], offset_max="2.5 deg"
	)

	circle = CircleSkyRegion(center=geom.center_skydir, radius=0.2 * u.deg)
	exclusion_mask = geom.region_mask([circle], inside=False)

	fov_bkg_maker = FoVBackgroundMaker(method="fit", exclusion_mask=exclusion_mask)

	for obs in observations:
		dataset = maker.run(stacked, obs)
		dataset = safe_mask_maker.run(dataset, obs)
		dataset = fov_bkg_maker.run(dataset)
		stacked.stack(dataset)

The following notebooks shows examples using
`~gammapy.makers.FoVBackgroundMaker` to perform 3D data extraction and fitting:

.. nbgallery::

   ../tutorials/starting/analysis_2.ipynb
   ../tutorials/analysis/3D/analysis_3d.ipynb