Background2D

class gammapy.irf.Background2D(axes, data=0, unit='', meta=None, interp_kwargs=None)

Bases: gammapy.irf.background.BackgroundIRF

Background 2D.

Data format specification: BKG_2D

Parameters

axeslist of MapAxis or MapAxes object

Required data axes: [“energy”, “offset”] in the given order.

datandarray

Data array.

unitstr or Unit

Data unit usually s^-1 MeV^-1 sr^-1

metadict

Meta data

Attributes Summary

axes	MapAxes
data
default_interp_kwargs	Default Interpolation kwargs.
is_offset_dependent	Whether the IRF depends on offset
is_pointlike	Whether the IRF is pointlike of full containment.
quantity	Quantity
required_axes
tag
unit	Map unit (Unit)

Methods Summary

cumsum(axis_name)	Compute cumsum along a given axis
evaluate([method])	Evaluate IRF
from_hdulist(hdulist[, hdu, format])	Create from HDUList.
from_table(table[, format])	Read from Table.
integral(axis_name, **kwargs)	Compute integral along a given axis
integrate_log_log(axis_name, **kwargs)	Integrate along a given axis.
interp_missing_data(axis_name)	Interpolate missing data along a given axis
normalize(axis_name)	Normalise data in place along a given axis.
pad(pad_width, axis_name, **kwargs)	Pad irf along a given axis.
peek([figsize])	Quick-look summary plots.
plot([ax, add_cbar])	Plot energy offset dependence of the background model.
plot_at_energy([energy, ax, add_cbar, ncols])	Plot the background rate in Field of view coordinates at a given energy.
plot_energy_dependence([ax, offset])	Plot background rate versus energy for a given offset.
plot_offset_dependence([ax, energy])	Plot background rate versus offset for a given energy.
plot_spectrum([ax])	Plot angle integrated background rate versus energy.
read(filename[, hdu, format])	Read from file.
to_3d()	“Convert to Background3D
to_hdulist([format])
to_table([format])	Convert to table
to_table_hdu([format])	Convert to BinTableHDU.
write(filename, *args, **kwargs)	Write IRF to fits.

Attributes Documentation

axes

MapAxes

data

default_interp_kwargs = {'bounds_error': False, 'fill_value': 0.0}

Default Interpolation kwargs.

is_offset_dependent

Whether the IRF depends on offset

is_pointlike

Whether the IRF is pointlike of full containment.

quantity

Quantity

required_axes = ['energy', 'offset']

tag = 'bkg_2d'

unit

Map unit (Unit)

Methods Documentation

cumsum(axis_name)

Compute cumsum along a given axis

Parameters

axis_namestr

Along which axis to integrate.

Returns

irfIRF

Cumsum IRF

evaluate(method=None, **kwargs)

Evaluate IRF

Parameters

**kwargsdict

Coordinates at which to evaluate the IRF

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

Interpolation method

Returns

arrayQuantity

Interpolated values

classmethod from_hdulist(hdulist, hdu=None, format='gadf-dl3')

Create from HDUList.

Parameters

hdulistHDUList

HDU list

hdustr

HDU name

format{“gadf-dl3”}

Format specification

Returns

irfIRF

IRF class

classmethod from_table(table, format='gadf-dl3')

Read from Table.

Parameters

tableTable

Table with background data

format{“gadf-dl3”}

Format specification

Returns

bkgBackground2D or Background2D

Background IRF class.

integral(axis_name, **kwargs)

Compute integral along a given axis

This method uses interpolation of the cumulative sum.

Parameters

axis_namestr

Along which axis to integrate.

**kwargsdict

Coordinates at which to evaluate the IRF

Returns

arrayQuantity

Returns 2D array with axes offset

integrate_log_log(axis_name, **kwargs)

Integrate along a given axis.

This method uses log-log trapezoidal integration.

Parameters

axis_namestr

Along which axis to integrate.

**kwargsdict

Coordinates at which to evaluate the IRF

Returns

arrayQuantity

Returns 2D array with axes offset

interp_missing_data(axis_name)

Interpolate missing data along a given axis

normalize(axis_name)

Normalise data in place along a given axis.

Parameters

axis_namestr

Along which axis to normalize.

pad(pad_width, axis_name, **kwargs)

Pad irf along a given axis.

Parameters

pad_width{sequence, array_like, int}

Number of pixels padded to the edges of each axis.

axis_namestr

Which axis to downsample. By default spatial axes are padded.

**kwargsdict

Keyword argument forwarded to pad

Returns

irfIRF

Padded irf

peek(figsize=(10, 8))

Quick-look summary plots.

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

Plot energy offset dependence of the background model.

plot_at_energy(energy=None, ax=None, add_cbar=True, ncols=3, **kwargs)

Plot the background rate in Field of view coordinates at a given energy.

Parameters

energyQuantity

list of Energy

ax: `~matplotlib.axes.Axes`, optional

Axis

add_cbarbool

Add color bar?

ncolsint

Number of columns to plot

**kwargsdict

Keyword arguments passed to pcolormesh.

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

Plot background rate versus energy for a given offset.

Parameters

axAxes, optional

Axis

offsetAngle

Offset

kwargsdict

Forwarded tp plt.plot()

Returns

axAxes

Axis

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

Plot background rate versus offset for a given energy.

Parameters

axAxes, optional

Axis

energyQuantity

Energy

Returns

axAxes

Axis

plot_spectrum(ax=None, **kwargs)

Plot angle integrated background rate versus energy.

Parameters

axAxes, optional

Axis

**kwargsdict

Keyword arguments forwarded to plot

Returns

axAxes

Axis

classmethod read(filename, hdu=None, format='gadf-dl3')

Read from file.

Parameters

filenamestr or Path

Filename

hdustr

HDU name

format{“gadf-dl3”}

Format specification

Returns

irfIRF

IRF class

to_3d()

“Convert to Background3D

to_hdulist(format='gadf-dl3')

to_table(format='gadf-dl3')

Convert to table

Parameters

format{“gadf-dl3”}

Format specification

Returns

tableTable

IRF data table

to_table_hdu(format='gadf-dl3')

Convert to BinTableHDU.

Parameters

format{“gadf-dl3”}

Format specification

Returns

hduBinTableHDU

IRF data table hdu

write(filename, *args, **kwargs)

Write IRF to fits.

Calls writeto, forwarding all arguments.