EnergyDispersion2D

class gammapy.irf.EnergyDispersion2D(axes, data=0, unit='', is_pointlike=False, fov_alignment=FoVAlignment.RADEC, meta=None, interp_kwargs=None)

Bases: gammapy.irf.core.IRF

Offset-dependent energy dispersion matrix.

Data format specification: EDISP_2D

Parameters

energy_axis_trueMapAxis

True energy axis

migra_axisMapAxis

Energy migration axis

offset_axisMapAxis

Field of view offset axis

datandarray

Energy dispersion probability density

See also

EnergyDispersion

Examples

Read energy dispersion IRF from disk:

>>> from gammapy.maps import MapAxis
>>> from gammapy.irf import EnergyDispersion2D
>>> filename = '$GAMMAPY_DATA/hess-dl3-dr1/data/hess_dl3_dr1_obs_id_020136.fits.gz'
>>> edisp2d = EnergyDispersion2D.read(filename, hdu="EDISP")

Create energy dispersion matrix (EnergyDispersion) for a given field of view offset and energy binning:

>>> energy = MapAxis.from_bounds(0.1, 20, nbin=60, unit="TeV", interp="log").edges
>>> edisp = edisp2d.to_edisp_kernel(offset='1.2 deg', energy=energy, energy_true=energy)

Attributes Summary

axes	MapAxes
data
default_interp_kwargs
default_unit
fov_alignment	Alignment of the field of view coordinate axes, see FoVAlignment
has_offset_axis	Whether the IRF explicitly 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_gauss(energy_axis_true, migra_axis, ...)	Create Gaussian energy dispersion matrix (EnergyDispersion2D).
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
is_allclose(other[, rtol_axes, atol_axes])	Compare two data IRFs for equivalency
normalize()	Normalise energy dispersion
pad(pad_width, axis_name, **kwargs)	Pad irf along a given axis.
peek([figsize])	Quick-look summary plots.
plot_bias([ax, offset, add_cbar])	Plot migration as a function of true energy for a given offset.
plot_migration([ax, offset, energy_true])	Plot energy dispersion for given offset and true energy.
read(filename[, hdu, format])	Read from file.
to_edisp_kernel(offset[, energy_true, energy])	Detector response R(Delta E_reco, Delta E_true)
to_hdulist([format])
to_table([format])	Convert to table
to_table_hdu([format])	Convert to BinTableHDU.
to_unit(unit)	Convert irf to different unit
write(filename, *args, **kwargs)	Write IRF to fits.

Attributes Documentation

axes

MapAxes

data

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

default_unit = Unit(dimensionless)

fov_alignment

Alignment of the field of view coordinate axes, see FoVAlignment

has_offset_axis

Whether the IRF explicitly depends on offset

is_pointlike

Whether the IRF is pointlike of full containment.

quantity

Quantity

required_axes = ['energy_true', 'migra', 'offset']

tag = 'edisp_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_gauss(energy_axis_true, migra_axis, offset_axis, bias, sigma, pdf_threshold=1e-06)

Create Gaussian energy dispersion matrix (EnergyDispersion2D).

The output matrix will be Gaussian in (energy_true / energy).

The bias and sigma should be either floats or arrays of same dimension than energy_true. bias refers to the mean value of the migra distribution minus one, i.e. bias=0 means no bias.

Note that, the output matrix is flat in offset.

Parameters

energy_axis_trueMapAxis

True energy axis

migra_axisQuantity

Migra axis

offset_axisQuantity

Bin edges of offset

biasfloat or ndarray

Center of Gaussian energy dispersion, bias

sigmafloat or ndarray

RMS width of Gaussian energy dispersion, resolution.

pdf_thresholdfloat, optional

Zero suppression threshold

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 irf data

format{“gadf-dl3”}

Format specification

Returns

irfIRF

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

is_allclose(other, rtol_axes=0.001, atol_axes=1e-06, **kwargs)

Compare two data IRFs for equivalency

Parameters

othergammapy.irfs.IRF

The irf to compare against

rtol_axesfloat

Relative tolerance for the axes comparison.

atol_axesfloat

Relative tolerance for the axes comparison.

**kwargsdict

keywords passed to numpy.allclose

Returns

is_allclosebool

Whether the IRF is all close.

normalize()

Normalise energy dispersion

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=(15, 5))

Quick-look summary plots.

Parameters

figsize(float, float)

Size of the resulting plot

plot_bias(ax=None, offset=None, add_cbar=False, **kwargs)

Plot migration as a function of true energy for a given offset.

Parameters

axAxes, optional

Axis

offsetAngle, optional

Offset

add_cbarbool

Add a colorbar to the plot.

kwargsdict

Keyword arguments passed to pcolormesh.

Returns

axAxes

Axis

plot_migration(ax=None, offset=None, energy_true=None, **kwargs)

Plot energy dispersion for given offset and true energy.

Parameters

axAxes, optional

Axis

offsetAngle, optional

Offset

energy_trueQuantity, optional

True energy

**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_edisp_kernel(offset, energy_true=None, energy=None)

Detector response R(Delta E_reco, Delta E_true)

Probability to reconstruct an energy in a given true energy band in a given reconstructed energy band

Parameters

offsetAngle

Offset

energy_trueQuantity, None

True energy axis

energyQuantity

Reconstructed energy axis

Returns

edispEDispKernel

Energy dispersion matrix

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

to_unit(unit)

Convert irf to different unit

Parameters

unitUnit or str

New unit

Returns

irfIRF

IRF with new unit and converted data

write(filename, *args, **kwargs)

Write IRF to fits.

Calls writeto, forwarding all arguments.