PSFMap#

class gammapy.irf.PSFMap(psf_map, exposure_map=None)[source]#

Bases: gammapy.irf.core.IRFMap

Class containing the Map of PSFs and allowing to interact with it.

Parameters

psf_mapMap: the input PSF Map. Should be a Map with 2 non spatial axes. rad and true energy axes should be given in this specific order.
exposure_mapMap: Associated exposure map. Needs to have a consistent map geometry.

Examples

from astropy.coordinates import SkyCoord
from gammapy.maps import WcsGeom, MapAxis
from gammapy.data import Observation
from gammapy.irf import load_cta_irfs
from gammapy.makers import MapDatasetMaker

# Define observation
pointing = SkyCoord("0d", "0d")
filename = "$GAMMAPY_DATA/cta-1dc/caldb/data/cta/1dc/bcf/South_z20_50h/irf_file.fits"
irfs = load_cta_irfs(filename)
obs = Observation.create(pointing=pointing, irfs=irfs, livetime="1h")

# Create WcsGeom
# Define energy axis. Note that the name is fixed.
energy_axis = MapAxis.from_energy_bounds("0.1 TeV", "10 TeV", nbin=3, name="energy_true")

# Define rad axis. Again note the axis name
rad_axis = MapAxis.from_bounds(0, 0.5, nbin=100, name="rad", unit="deg")

geom = WcsGeom.create(
    binsz=0.25, width="5 deg", skydir=pointing, axes=[rad_axis, energy_axis]
)

maker = MapDatasetMaker()

psf = maker.make_psf(geom=geom, observation=obs)

# Get a PSF kernel at the center of the image
geom=exposure_geom.upsample(factor=10).drop("rad")
psf_kernel = psf_map.get_psf_kernel(geom=geom)

Attributes Summary

`energy_name`
`mask_safe_image`	Mask safe for the map
`psf_map`
`required_axes`
`tag`

Methods Summary

`containment`(rad, energy_true[, position])	Containment at given coords
`containment_radius`(fraction, energy_true[, ...])	Containment at given coords
`containment_radius_map`(energy_true[, fraction])	Containment radius map.
`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_gauss`(energy_axis_true[, rad_axis, ...])	Create all -sky PSF map from Gaussian width.
`from_geom`(geom)	Create psf map from geom.
`from_hdulist`(hdulist[, hdu, hdu_bands, ...])	Create from `HDUList`.
`get_psf_kernel`(geom[, position, max_radius, ...])	Returns a PSF kernel at the given position.
`normalize`()	Normalize PSF map
`peek`([figsize])	Quick-look summary plots.
`plot_containment_radius_vs_energy`([ax, fraction])	Plot containment fraction as a function of energy.
`plot_psf_vs_rad`([ax, energy_true])	Plot PSF vs radius.
`read`(filename[, format, hdu])	Read an IRF_map from file and create corresponding object"
`sample_coord`(map_coord[, random_state])	Apply PSF 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_hdulist`([format])	Convert to `HDUList`.
`to_image`([spectrum, keepdims])	Reduce to a 2-D map after weighing with the associated exposure and a spectrum
`to_region_nd_map`(region)	Extract IRFMap in a given region or position
`write`(filename[, overwrite, format])	Write IRF map to fits

Attributes Documentation

energy_name#

mask_safe_image#: Mask safe for the map

psf_map#

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

tag = 'psf_map'#

Methods Documentation

containment(rad, energy_true, position=None)[source]#

Containment at given coords

Parameters

radQuantity: Rad value
energy_trueQuantity: Energy true value
positionSkyCoord: Sky position. By default the center of the map is chosen

Returns

containmentQuantity: Containment values

containment_radius(fraction, energy_true, position=None)[source]#

Containment at given coords

Parameters

fractionfloat: Containment fraction
energy_trueQuantity: Energy true value
positionSkyCoord: Sky position. By default the center of the map is chosen

Returns

containmentQuantity: Containment values

containment_radius_map(energy_true, fraction=0.68)[source]#

Containment radius map.

Parameters

energy_trueQuantity: Energy true at which to compute the containment radius
fractionfloat: Containment fraction (range: 0 to 1)

Returns

containment_radius_mapMap: Containment radius map

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_gauss(energy_axis_true, rad_axis=None, sigma=<Quantity 0.1 deg>, geom=None)[source]#

Create all -sky PSF map from Gaussian width.

This is used for testing and examples.

The width can be the same for all energies or be an array with one value per energy node. It does not depend on position.

Parameters

energy_axis_trueMapAxis: True energy axis.
rad_axisMapAxis: Offset angle wrt source position axis.
sigmaAngle: Gaussian width.
geomGeom: Image geometry. By default an allsky geometry is created.

Returns

psf_mapPSFMap: Point spread function map.

classmethod from_geom(geom)[source]#

Create psf map from geom.

Parameters

geomGeom: PSF map geometry.

Returns

psf_mapPSFMap: Point spread function 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_psf_kernel(geom, position=None, max_radius=None, containment=0.999, factor=4)[source]#

Returns a PSF kernel at the given position.

The PSF is returned in the form a WcsNDMap defined by the input Geom.

Parameters

geomGeom: Target geometry to use
positionSkyCoord: Target position. Should be a single coordinate. By default the center position is used.
max_radiusAngle: maximum angular size of the kernel map
containmentfloat: Containment fraction to use as size of the kernel. The max. radius across all energies is used. The radius can be overwritten using the max_radius argument.
factorint: oversampling factor to compute the PSF

Returns

kernelPSFKernel: the resulting kernel

normalize()[source]#: Normalize PSF map

peek(figsize=(12, 10))[source]#

Quick-look summary plots.

Parameters

figsizetuple: Size of figure.

plot_containment_radius_vs_energy(ax=None, fraction=(0.68, 0.95), **kwargs)[source]#

Plot containment fraction as a function of energy.

The method plots the containment radius at the center of the map.

Parameters

axAxes: Axes to plot on.
fractionlist of float or ndarray: Containment fraction between 0 and 1.
**kwargsdict: Keyword arguments passed to plot

Returns

axAxes: Axes to plot on.

plot_psf_vs_rad(ax=None, energy_true=<Quantity [ 0.1, 1., 10. ] TeV>, **kwargs)[source]#

Plot PSF vs radius.

The method plots the profile at the center of the map.

Parameters

axAxes: Axes to plot on.
energyQuantity: Energies where to plot the PSF.
**kwargsdict: Keyword arguments pass to plot.

Returns

axAxes: Axes to plot on.

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 PSF 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

corr_coordMapCoord object.: Sequence of PSF-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_hdulist(format='gadf')#

Convert to HDUList.

Parameters

format{“gadf”, “gtpsf”}: File format

Returns

hdu_listHDUList: HDU list.

to_image(spectrum=None, keepdims=True)[source]#

Reduce to a 2-D map after weighing with the associated exposure and a spectrum

Parameters

spectrumSpectralModel, optional: Spectral model to compute the weights. Default is power-law with spectral index of 2.
keepdimsbool, optional: If True, the energy axis is kept with one bin. If False, the axis is removed

Returns

psf_outPSFMap: PSFMap with the energy axis summed over

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