FOVCubeBackgroundModel

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

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()

Compute background_cube from count_cube and livetime_cube.

classmethod define_cube_binning(observation_table, method='default')

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)

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')

Read cube background model from fits file.

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

• table (default and preferred format): all 3 cubes as HDUList of BinTableHDU
• image (alternative format): bg cube saved as PrimaryHDU, with the energy binning stored as BinTableHDU

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)

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()

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)

Write cube to FITS file.

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

• table (default and preferred format): all 3 cubes as HDUList of BinTableHDU
• image (alternative format): bg cube saved as PrimaryHDU, with the energy binning stored as BinTableHDU

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.