Background2D

class gammapy.irf.Background2D(energy_lo, energy_hi, offset_lo, offset_hi, data, meta=None, interp_kwargs=None)

Bases: object

Background 2D.

Data format specification: BKG_2D

Parameters

energy_lo, energy_hiQuantity

Energy binning

offset_lo, offset_hiQuantity

FOV coordinate offset-axis binning

dataQuantity

Background rate (usually: s^-1 MeV^-1 sr^-1)

Attributes Summary

default_interp_kwargs

Default Interpolation kwargs for NDDataArray.

Methods Summary

evaluate(self, fov_lon, fov_lat, energy_reco)	Evaluate at a given FOV position and energy.
evaluate_integrate(self, fov_lon, fov_lat, …)	Evaluate at given FOV position and energy, by integrating over the energy range.
from_hdulist(hdulist[, hdu])	Create from HDUList.
from_table(table)	Read from Table.
peek(self[, figsize])	Quick-look summary plots.
plot(self[, ax, add_cbar])	Plot energy offset dependence of the background model.
plot_energy_dependence(self[, ax, offset, …])	Plot background rate versus energy for a given offset.
plot_offset_dependence(self[, ax, offset, …])	Plot background rate versus offset for a given energy.
plot_spectrum(self[, ax])	Plot angle integrated background rate versus energy.
read(filename[, hdu])	Read from file.
to_3d(self)	Convert to Background3D.
to_fits(self[, name])	Convert to BinTableHDU.
to_table(self)	Convert to Table.

Attributes Documentation

default_interp_kwargs = {'bounds_error': False, 'fill_value': None}

Default Interpolation kwargs for NDDataArray. Extrapolate.

Methods Documentation

evaluate(self, fov_lon, fov_lat, energy_reco, method='linear', **kwargs)

Evaluate at a given FOV position and energy.

The fov_lon, fov_lat, energy_reco has to have the same shape since this is a set of points on which you want to evaluate.

To have the same API than background 3D for the background evaluation, the offset is fov_altaz_lon.

Parameters

fov_lon, fov_latAngle

FOV coordinates expecting in AltAz frame, same shape than energy_reco

energy_recoQuantity

Reconstructed energy, same dimension than fov_lat and fov_lat

methodstr {‘linear’, ‘nearest’}, optional

Interpolation method

kwargsdict

option for interpolation for RegularGridInterpolator

Returns

arrayQuantity

Interpolated values, axis order is the same as for the NDData array

evaluate_integrate(self, fov_lon, fov_lat, energy_reco, method='linear')

Evaluate at given FOV position and energy, by integrating over the energy range.

Parameters

fov_lon, fov_latAngle

FOV coordinates expecting in AltAz frame.

energy_reco: `~astropy.units.Quantity`

Reconstructed energy edges.

method{‘linear’, ‘nearest’}, optional

Interpolation method

Returns

arrayQuantity

Returns 2D array with axes offset

classmethod from_hdulist(hdulist, hdu='BACKGROUND')

Create from HDUList.

classmethod from_table(table)

Read from Table.

peek(self, figsize=(10, 8))

Quick-look summary plots.

plot(self, ax=None, add_cbar=True, **kwargs)

Plot energy offset dependence of the background model.

plot_energy_dependence(self, ax=None, offset=None, energy=None, **kwargs)

Plot background rate versus energy for a given offset.

Parameters

axAxes, optional

Axis

offsetAngle

Offset

energyQuantity

Energy axis

kwargsdict

Forwarded tp plt.plot()

Returns

axAxes

Axis

plot_offset_dependence(self, ax=None, offset=None, energy=None, **kwargs)

Plot background rate versus offset for a given energy.

Parameters

axAxes, optional

Axis

offsetAngle

Offset axis

energyQuantity

Energy

Returns

axAxes

Axis

plot_spectrum(self, ax=None, **kwargs)

Plot angle integrated background rate versus energy.

Parameters

axAxes, optional

Axis

kwargsdict

Forwarded tp plt.plot()

Returns

axAxes

Axis

classmethod read(filename, hdu='BACKGROUND')

Read from file.

to_3d(self)

Convert to Background3D.

Fill in a radially symmetric way.

to_fits(self, name='BACKGROUND')

Convert to BinTableHDU.

to_table(self)

Convert to Table.