FOVCubeBackgroundModel

class gammapy.background.FOVCubeBackgroundModel(counts_cube=None, livetime_cube=None, background_cube=None)[source]

Bases: object

Field of view (FOV) cube background model.

Container class for cube background model (X, Y, energy). (X, Y) are detector coordinates (a.k.a. nominal system coordinates). This class defines 3 cubes of type FOVCube:

  • counts_cube: to store the counts (a.k.a. events) that participate in the model creation.
  • livetime_cube: to store the livetime correction.
  • background_cube: to store the background model.

The class defines methods to define the binning, fill and smooth of the background cube models.

Parameters:

counts_cube : FOVCube, optional

FOVCube to store counts.

livetime_cube : FOVCube, optional

FOVCube to store livetime correction.

background_cube : FOVCube, optional

FOVCube to store background model.

Methods Summary

compute_rate() Compute background_cube from count_cube and livetime_cube.
define_cube_binning(observation_table[, method]) Define cube binning (E, Y, X).
fill_obs(observation_table, data_store) Fill events and compute corresponding livetime.
read(filename[, format]) Read cube background model from fits file.
set_cube_binning(detx_edges, dety_edges, ...) Set cube binning from function parameters.
smooth() Smooth background cube model.
write(outfile[, format]) Write cube to FITS file.

Methods Documentation

compute_rate()[source]

Compute background_cube from count_cube and livetime_cube.

classmethod define_cube_binning(observation_table, method='default')[source]

Define cube binning (E, Y, X).

The shape of the cube (number of bins on each axis) depends on the number of observations. The binning is slightly altered in case a different method as the default one is used. In the michi method:

  • Minimum energy (i.e. lower boundary of cube energy binning) is equal to minimum energy threshold of all observations in the group.
Parameters:

observation_table : ObservationTable

Observation list to use for the michi binning.

data_dir : str

Data directory

method : {‘default’, ‘michi’}, optional

Bg cube model calculation method to apply.

Returns:

bg_cube_model : FOVCubeBackgroundModel

FOVCube background model object.

fill_obs(observation_table, data_store)[source]

Fill events and compute corresponding livetime.

Get data files corresponding to the observation list, histogram the counts and the livetime and fill the corresponding cube containers.

Parameters:

observation_table : ObservationTable

Observation list to use for the histogramming.

data_store : DataStore

Data store

classmethod read(filename, format='table')[source]

Read cube background model from fits file.

Several input formats are accepted, depending on the value of the format parameter:

The counts and livetime cubes are optional.

This method calls read, forwarding all arguments.

Parameters:

filename : str

Name of file with the cube.

format : str, optional

Format of the cube to read.

Returns:

bg_cube_model : FOVCubeBackgroundModel

FOVCube background model object.

classmethod set_cube_binning(detx_edges, dety_edges, energy_edges)[source]

Set cube binning from function parameters.

Parameters:

detx_edges : Angle

Spatial bin edges vector (low and high) for the cubes. X coordinate.

dety_edges : Angle

Spatial bin edges vector (low and high) for the cubes. Y coordinate.

energy_edges : Quantity

Energy bin edges vector (low and high) for the cubes.

Returns:

bg_cube_model : FOVCubeBackgroundModel

FOVCube background model object.

smooth()[source]

Smooth background cube model.

Smooth method:

  1. slice model in energy bins: 1 image per energy bin

  2. calculate integral of the image

  3. determine times to smooth (N) depending on number of entries (counts) used to fill the cube

  4. smooth image N times with root TH2::Smooth default smoothing kernel: k5a

    k5a = [ [ 0, 0, 1, 0, 0 ],
            [ 0, 2, 2, 2, 0 ],
            [ 1, 2, 5, 2, 1 ],
            [ 0, 2, 2, 2, 0 ],
            [ 0, 0, 1, 0, 0 ] ]
    

    Reference: https://root.cern.ch/root/html/TH2.html#TH2:Smooth

  5. scale with the cocient of the old integral div by the new integral

  6. fill the values of the image back in the cube

write(outfile, format='table', **kwargs)[source]

Write cube to FITS file.

Several output formats are accepted, depending on the value of the format parameter:

The counts and livetime cubes are optional.

This method calls writeto, forwarding the kwargs arguments.

Parameters:

outfile : str

Name of file to write.

format : str, optional

Format of the cube to write.

kwargs

Extra arguments for the corresponding astropy.io.fits writeto method.