PSFMap#

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

Bases: 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, FixedPointingInfo
from gammapy.irf import load_irf_dict_from_file
from gammapy.makers import MapDatasetMaker

# Define observation
pointing_position = SkyCoord(0, 0, unit="deg", frame="galactic")
pointing = FixedPointingInfo(
    fixed_icrs=pointing_position.icrs,
)
filename = "$GAMMAPY_DATA/cta-1dc/caldb/data/cta/1dc/bcf/South_z20_50h/irf_file.fits"
irfs = load_irf_dict_from_file(filename)
obs = Observation.create(pointing=pointing, irfs=irfs, livetime="1h")

# 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")

# Create WcsGeom
geom = WcsGeom.create(
    binsz=0.25, width="5 deg", skydir=pointing_position, 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
upsample_geom = geom.upsample(factor=10).drop("rad")
psf_kernel = psf.get_psf_kernel(geom=upsample_geom)

Attributes Summary

energy_name

has_single_spatial_bin

mask_safe_image

Mask safe for the map.

psf_map

required_axes

tag

Methods Summary

containment(rad, energy_true[, position])

Containment at given coordinates.

containment_radius(fraction, energy_true[, ...])

Containment at given coordinates.

containment_radius_map(energy_true[, fraction])

Containment radius map.

copy()

Copy IRF map.

cutout(position, width[, mode, min_npix])

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 geometry.

from_hdulist(hdulist[, hdu, hdu_bands, ...])

Create from HDUList.

get_psf_kernel(geom[, position, max_radius, ...])

Return 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, checksum])

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([spectral_model, keepdims])

Reduce to a 2D 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, checksum])

Write IRF map to fits.

Attributes Documentation

energy_name#
has_single_spatial_bin#
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 coordinates.

Parameters:
radQuantity

Rad value.

energy_trueQuantity

Energy true value.

positionSkyCoord, optional

Sky position. If None, the center of the map is chosen. Default is None.

Returns:
containmentQuantity

Containment values.

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

Containment at given coordinates.

Parameters:
fractionfloat

Containment fraction.

energy_trueQuantity

Energy true value.

positionSkyCoord, optional

Sky position. If None, the center of the map is chosen. Default is None.

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, optional

Containment fraction (range: 0 to 1). Default is 0.68.

Returns:
containment_radius_mapMap

Containment radius map.

copy()#

Copy IRF map.

cutout(position, width, mode='trim', min_npix=3)#

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’}, optional

Mode option for Cutout2D, for details see Cutout2D. Default is “trim”.

min_npixbool, optional

Force width to a minimmum number of pixels. Default is 3. The default is 3 pixels so interpolation is done correctly if the binning of the IRF is larger than the width of the analysis region.

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

Axis to downsample. By default, spatial axes are downsampled.

weightsMap, optional

Map with weights downsampling. Default is None.

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 all-sky geometry is created.

Returns:
psf_mapPSFMap

Point spread function map.

classmethod from_geom(geom)[source]#

Create PSF map from geometry.

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, optional

Name or index of the HDU with the IRF map. Default is None.

hdu_bandsstr, optional

Name or index of the HDU with the IRF map BANDS table. Default is None.

exposure_hdustr, optional

Name or index of the HDU with the exposure map data. Default is None.

exposure_hdu_bandsstr, optional

Name or index of the HDU with the exposure map BANDS table. Default is None.

format{“gadf”, “gtpsf”}, optional

File format. Default is “gadf”.

Returns:
irf_mapIRFMap

IRF map.

get_psf_kernel(geom, position=None, max_radius=None, containment=0.999, precision_factor=12)[source]#

Return 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, optional

Target position. Should be a single coordinate. By default, the center position is used.

max_radiusAngle, optional

Maximum angular size of the kernel map. Default is None and it will be computed for the containment fraction set.

containmentfloat, optional

Containment fraction to use as size of the kernel. The radius can be overwritten using the max_radius argument. Default is 0.999.

precision_factorint, optional

Factor between the bin half-width of the geom and the median R68% containment radius. Used only for the oversampling method. Default is 10.

Returns:
kernelPSFKernel or list of PSFKernel

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, optional

Matplotlib axes. Default is None.

fractionlist of float or ndarray

Containment fraction between 0 and 1.

**kwargsdict

Keyword arguments passed to plot

Returns:
axAxes

Matplotlib axes.

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, optional

Matplotlib axes. Default is None.

energyQuantity

Energies where to plot the PSF.

**kwargsdict

Keyword arguments pass to plot.

Returns:
axAxes

Matplotlib axes.

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

Read an IRF_map from file and create corresponding object.

Parameters:
filenamestr or Path

File name.

format{“gadf”, “gtpsf”}, optional

File format. Default is “gadf”.

hdustr or int

HDU location. Default is None.

checksumbool

If True checks both DATASUM and CHECKSUM cards in the file headers. Default is False.

Returns:
irf_mapPSFMap, EDispMap or EDispKernelMap

IRF map.

sample_coord(map_coord, random_state=0, chunk_size=10000)[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}, optional

Defines random number generator initialisation. Passed to get_random_state. Default is 0.

chunk_sizeint

If set, this will slice the input MapCoord into smaller chunks of chunk_size elements. Default is 10000.

Returns:
corr_coordMapCoord

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

Dictionary 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 dictionary 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, optional

Map with stacking weights. Default is None.

nan_to_num: bool, optional

Non-finite values are replaced by zero if True. Default is True.

to_hdulist(format='gadf')#

Convert to HDUList.

Parameters:
format{“gadf”, “gtpsf”}, optional

File format. Default is “gadf”.

Returns:
hdu_listHDUList

HDU list.

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

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

Parameters:
spectral_modelSpectralModel, 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', checksum=False)#

Write IRF map to fits.

Parameters:
filenamestr or Path

Filename to write to.

overwritebool, optional

Overwrite existing file. Default is False.

format{“gadf”, “gtpsf”}, optional

File format. Default is “gadf”.

checksumbool, optional

When True adds both DATASUM and CHECKSUM cards to the headers written to the file. Default is False.