EDispMap#

class gammapy.irf.EDispMap(edisp_map, exposure_map=None)[source]#

Bases: gammapy.irf.core.IRFMap

Energy dispersion map.

Parameters

edisp_mapMap: the input Energy Dispersion Map. Should be a Map with 2 non spatial axes. migra and true energy axes should be given in this specific order.
exposure_mapMap, optional: Associated exposure map. Needs to have a consistent map geometry.

Examples

import numpy as np
from astropy import units as u
from astropy.coordinates import SkyCoord
from gammapy.maps import WcsGeom, MapAxis
from gammapy.irf import EnergyDispersion2D, EffectiveAreaTable2D
from gammapy.makers.utils import make_edisp_map, make_map_exposure_true_energy

# Define energy dispersion map geometry
energy_axis_true = MapAxis.from_edges(np.logspace(-1, 1, 10), unit="TeV", name="energy_true")
migra_axis = MapAxis.from_edges(np.linspace(0, 3, 100), name="migra")
pointing = SkyCoord(0, 0, unit="deg")
geom = WcsGeom.create(
        binsz=0.25 * u.deg,
        width=10 * u.deg,
        skydir=pointing,
        axes=[migra_axis, energy_axis_true],
)

# Extract EnergyDispersion2D from CTA 1DC IRF
filename = "$GAMMAPY_DATA/cta-1dc/caldb/data/cta/1dc/bcf/South_z20_50h/irf_file.fits"
edisp2D = EnergyDispersion2D.read(filename, hdu="ENERGY DISPERSION")
aeff2d = EffectiveAreaTable2D.read(filename, hdu="EFFECTIVE AREA")

# Create the exposure map
exposure_geom = geom.squash(axis_name="migra")
exposure_map = make_map_exposure_true_energy(pointing, "1 h", aeff2d, exposure_geom)

# create the EDispMap for the specified pointing
edisp_map = make_edisp_map(edisp2D, pointing, geom, exposure_map)

# Get an Energy Dispersion (1D) at any position in the image
pos = SkyCoord(2.0, 2.5, unit="deg")
energy_axis = MapAxis.from_energy_bounds(0.1, 10, 5, unit="TeV", name="energy")
edisp = edisp_map.get_edisp_kernel(energy_axis, position=pos)

# Write map to disk
edisp_map.write("edisp_map.fits")

Attributes Summary

`edisp_map`
`mask_safe_image`	Mask safe for the map
`required_axes`
`tag`

Methods Summary

`copy`()	Copy IRF map
`cutout`(position, width[, mode])	Cutout IRF map.
`downsample`(factor[, axis_name, weights])	Downsample the spatial dimension by a given factor.
`from_diagonal_response`(energy_axis_true[, ...])	Create an allsky EDisp map with diagonal response.
`from_geom`(geom)	Create edisp map from geom.
`from_hdulist`(hdulist[, hdu, hdu_bands, ...])	Create from `HDUList`.
`get_edisp_kernel`(energy_axis[, position])	Get energy dispersion at a given position.
`normalize`()	Normalize PSF map
`peek`([figsize])	Quick-look summary plots.
`read`(filename[, format, hdu])	Read an IRF_map from file and create corresponding object"
`sample_coord`(map_coord[, random_state])	Apply the energy dispersion corrections on the coordinates of a set of simulated events.
`slice_by_idx`(slices)	Slice sub dataset.
`stack`(other[, weights, nan_to_num])	Stack IRF map with another one in place.
`to_edisp_kernel_map`(energy_axis)	Convert to map with edisp kernels
`to_hdulist`([format])	Convert to `HDUList`.
`to_region_nd_map`(region)	Extract IRFMap in a given region or position
`write`(filename[, overwrite, format])	Write IRF map to fits

Attributes Documentation

edisp_map#

mask_safe_image#: Mask safe for the map

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

tag = 'edisp_map'#

Methods Documentation

copy()#: Copy IRF map

cutout(position, width, mode='trim')#

Cutout IRF map.

Parameters

positionSkyCoord: Center position of the cutout region.
widthtuple of Angle: Angular sizes of the region in (lon, lat) in that specific order. If only one value is passed, a square region is extracted.
mode{‘trim’, ‘partial’, ‘strict’}: Mode option for Cutout2D, for details see Cutout2D.

Returns

cutoutIRFMap: Cutout IRF map.

downsample(factor, axis_name=None, weights=None)#

Downsample the spatial dimension by a given factor.

Parameters

factorint: Downsampling factor.
axis_namestr: Which axis to downsample. By default spatial axes are downsampled.
weightsMap: Map with weights downsampling.

Returns

mapIRFMap: Downsampled irf map.

classmethod from_diagonal_response(energy_axis_true, migra_axis=None)[source]#

Create an allsky EDisp map with diagonal response.

Parameters

energy_axis_trueMapAxis: True energy axis
migra_axisMapAxis: Migra axis

Returns

edisp_mapEDispMap: Energy dispersion map.

classmethod from_geom(geom)[source]#

Create edisp map from geom.

By default a diagonal edisp matrix is created.

Parameters

geomGeom: Edisp map geometry.

Returns

edisp_mapEDispMap: Energy dispersion map.

classmethod from_hdulist(hdulist, hdu=None, hdu_bands=None, exposure_hdu=None, exposure_hdu_bands=None, format='gadf')#

Create from HDUList.

Parameters

hdulistHDUList: HDU list.
hdustr: Name or index of the HDU with the IRF map.
hdu_bandsstr: Name or index of the HDU with the IRF map BANDS table.
exposure_hdustr: Name or index of the HDU with the exposure map data.
exposure_hdu_bandsstr: Name or index of the HDU with the exposure map BANDS table.
format{“gadf”, “gtpsf”}: File format

Returns

irf_mapIRFMap: IRF map.

get_edisp_kernel(energy_axis, position=None)[source]#

Get energy dispersion at a given position.

Parameters

energy_axisMapAxis: Reconstructed energy axis
positionSkyCoord: the target position. Should be a single coordinates

Returns

edispEnergyDispersion: the energy dispersion (i.e. rmf object)

normalize()[source]#: Normalize PSF map

peek(figsize=(15, 5))[source]#

Quick-look summary plots. Plots corresponding to the center of the map.

Parameters

figsizetuple: Size of figure.

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

Read an IRF_map from file and create corresponding object”

Parameters

filenamestr or Path: File name
format{“gadf”, “gtpsf”}: File format
hdustr or int: HDU location

Returns

irf_mapPSFMap, EDispMap or EDispKernelMap: IRF map

sample_coord(map_coord, random_state=0)[source]#

Apply the energy dispersion corrections on the coordinates of a set of simulated events.

Parameters

map_coordMapCoord object.: Sequence of coordinates and energies of sampled events.
random_state{int, ‘random-seed’, ‘global-rng’, RandomState}: Defines random number generator initialisation. Passed to get_random_state.

Returns

MapCoord.: Sequence of Edisp-corrected coordinates of the input map_coord map.

slice_by_idx(slices)#

Slice sub dataset.

The slicing only applies to the maps that define the corresponding axes.

Parameters

slicesdict: Dict of axes names and integers or slice object pairs. Contains one element for each non-spatial dimension. For integer indexing the corresponding axes is dropped from the map. Axes not specified in the dict are kept unchanged.

Returns

map_outIRFMap: Sliced irf map object.

stack(other, weights=None, nan_to_num=True)#

Stack IRF map with another one in place.

Parameters

otherIRFMap: IRF map to be stacked with this one.
weightsMap: Map with stacking weights.
nan_to_num: bool: Non-finite values are replaced by zero if True (default).

to_edisp_kernel_map(energy_axis)[source]#

Convert to map with edisp kernels

Parameters

energy_axisMapAxis: Reconstructed energy axis.

Returns

edispEDispKernelMap: Energy dispersion kernel map.

to_hdulist(format='gadf')#

Convert to HDUList.

Parameters

format{“gadf”, “gtpsf”}: File format

Returns

hdu_listHDUList: HDU list.

to_region_nd_map(region)#

Extract IRFMap in a given region or position

If a region is given a mean IRF is computed, if a position is given the IRF is interpolated.

Parameters

regionSkyRegion or SkyCoord: Region or position where to get the map.

Returns

irfIRFMap: IRF map with region geometry.

write(filename, overwrite=False, format='gadf')#

Write IRF map to fits

Parameters

filenamestr or Path: Filename to write to
overwritebool: Whether to overwrite
format{“gadf”, “gtpsf”}: File format