Background3D

class gammapy.irf.Background3D(energy_lo, energy_hi, fov_lon_lo, fov_lon_hi, fov_lat_lo, fov_lat_hi, data, meta=None, interp_kwargs=None)[source]

Bases: object

Background 3D.

Data format specification: BKG_3D

Parameters:

energy_lo, energy_hi : Quantity

Energy binning

fov_lon_lo, fov_lon_hi : Quantity

FOV coordinate X-axis binning, in AltAz frame.

fov_lat_lo, fov_lat_hi : Quantity

FOV coordinate Y-axis binning, in AltAz frame.

data : Quantity

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

Examples

Here’s an example you can use to learn about this class:

>>> from gammapy.irf import Background3D
>>> filename = '$GAMMAPY_DATA/cta-1dc/caldb/data/cta/1dc/bcf/South_z20_50h/irf_file.fits'
>>> bkg_3d = Background3D.read(filename, hdu='BACKGROUND')
>>> print(bkg_3d)
Background3D
NDDataArray summary info
energy         : size =    21, min =  0.016 TeV, max = 158.489 TeV
fov_lon           : size =    36, min = -5.833 deg, max =  5.833 deg
fov_lat           : size =    36, min = -5.833 deg, max =  5.833 deg
Data           : size = 27216, min =  0.000 1 / (MeV s sr), max =  0.421 1 / (MeV s sr)

Attributes Summary

default_interp_kwargs Default Interpolation kwargs for NDDataArray.

Methods Summary

evaluate(fov_lon, fov_lat, energy_reco[, method]) Evaluate at given FOV position and energy.
from_hdulist(hdulist[, hdu]) Create from HDUList.
from_table(table) Read from Table.
integrate_on_energy_range(fov_lon, fov_lat, …) Integrate over an energy range.
read(filename[, hdu]) Read from file.
to_2d() Convert to Background2D.
to_fits([name]) Convert to BinTableHDU.
to_table() Convert to Table.

Attributes Documentation

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

Default Interpolation kwargs for NDDataArray. Extrapolate.

Methods Documentation

evaluate(fov_lon, fov_lat, energy_reco, method='linear', **kwargs)[source]

Evaluate at given FOV position and energy.

Parameters:

fov_lon, fov_lat : Angle

FOV coordinates expecting in AltAz frame.

energy_reco : Quantity

energy on which you want to interpolate. Same dimension than fov_lat and fov_lat

method : str {‘linear’, ‘nearest’}, optional

Interpolation method

kwargs : dict

option for interpolation for RegularGridInterpolator
Returns:

array : Quantity

Interpolated values, axis order is the same as for the NDData array
classmethod from_hdulist(hdulist, hdu='BACKGROUND')[source]

Create from HDUList.

classmethod from_table(table)[source]

Read from Table.

integrate_on_energy_range(fov_lon, fov_lat, energy_range, n_integration_bins=1, method='linear', **kwargs)[source]

Integrate over an energy range.

Parameters:

fov_lon, fov_lat : Angle

FOV coordinates expecting in AltAz frame.

energy_range: `~astropy.units.Quantity`

Energy range

n_integration_bins : int

Number of bins in the energy range

method : {‘linear’, ‘nearest’}, optional

Interpolation method

kwargs : dict
Returns:

array : Quantity

Returns 2D array with axes fov_lon, fov_lat
classmethod read(filename, hdu='BACKGROUND')[source]

Read from file.

to_2d()[source]

Convert to Background2D.

This takes the values at Y = 0 and X >= 0.

to_fits(name='BACKGROUND')[source]

Convert to BinTableHDU.

to_table()[source]

Convert to Table.