# Licensed under a 3-clause BSD style license - see LICENSE.rst
from __future__ import absolute_import, division, print_function, unicode_literals
import numpy as np
import astropy.units as u
from astropy.coordinates import Angle
from ..irf import EnergyDependentTablePSF
from ..maps import Map
from ..cube import PSFKernel
__all__ = ["make_psf_map", "PSFMap"]
[docs]def make_psf_map(psf, pointing, geom, max_offset):
"""Make a psf map for a single observation
Expected axes : rad and true energy in this specific order
The name of the rad MapAxis is expected to be 'rad'
Parameters
----------
psf : `~gammapy.irf.PSF3D`
the PSF IRF
pointing : `~astropy.coordinates.SkyCoord`
the pointing direction
geom : `~gammapy.maps.MapGeom`
the map geom to be used. It provides the target geometry.
rad and true energy axes should be given in this specific order.
max_offset : `~astropy.coordinates.Angle`
maximum offset w.r.t. fov center
Returns
-------
psfmap : `~gammapy.cube.PSFMap`
the resulting PSF map
"""
energy_axis = geom.get_axis_by_name("energy")
energy = energy_axis.center * energy_axis.unit
rad_axis = geom.get_axis_by_name("theta")
rad = Angle(rad_axis.center, unit=rad_axis.unit)
# Compute separations with pointing position
separations = pointing.separation(geom.to_image().get_coord().skycoord)
valid = np.where(separations < max_offset)
# Compute PSF values
psf_values = psf.evaluate(offset=separations[valid], energy=energy, rad=rad)
# Re-order axes to be consistent with expected geometry
psf_values = np.transpose(psf_values, axes=(2, 0, 1))
# Create Map and fill relevant entries
psfmap = Map.from_geom(geom, unit="sr-1")
psfmap.data[:, :, valid[0], valid[1]] += psf_values.to(psfmap.unit).value
return PSFMap(psfmap)
[docs]class PSFMap(object):
"""Class containing the Map of PSFs and allowing to interact with it.
Parameters
----------
psf_map : `~gammapy.maps.Map`
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.
Examples
--------
.. code:: python
import numpy as np
from gammapy.maps import Map, WcsGeom, MapAxis
from gammapy.irf import EnergyDependentMultiGaussPSF
from gammapy.cube import make_psf_map, PSFMap
from astropy import units as u
from astropy.coordinates import SkyCoord
# Define energy axis. Note that the name is fixed.
energy_axis = MapAxis.from_edges(np.logspace(-1., 1., 4), unit='TeV', name='energy')
# Define rad axis. Again note the axis name
rads = np.linspace(0., 0.5, 100) * u.deg
rad_axis = MapAxis.from_edges(rads, unit='deg', name='theta')
# Define parameters
pointing = SkyCoord(0., 0., unit='deg')
max_offset = 4 * u.deg
# Create WcsGeom
geom = WcsGeom.create(binsz=0.25*u.deg, width=10*u.deg, skydir=pointing, axes=[rad_axis, energy_axis])
# Extract EnergyDependentTablePSF from CTA 1DC IRF
filename = '$GAMMAPY_DATA/cta-1dc/caldb/data/cta/1dc/bcf/South_z20_50h/irf_file.fits'
psf = EnergyDependentMultiGaussPSF.read(filename, hdu='POINT SPREAD FUNCTION')
psf3d = psf.to_psf3d(rads)
# create the PSFMap for the specified pointing
psf_map = make_psf_map(psf3d, pointing, geom, max_offset)
# Get an EnergyDependentTablePSF at any position in the image
psf_table = psf_map.get_energy_dependent_table_psf(SkyCoord(2., 2.5, unit='deg'))
# Write map to disk
psf_map.write('psf_map.fits')
"""
def __init__(self, psf_map):
if psf_map.geom.axes[1].name.upper() != "ENERGY":
raise ValueError("Incorrect energy axis position in input Map")
if psf_map.geom.axes[0].name.upper() != "THETA":
raise ValueError("Incorrect theta axis position in input Map")
self._psf_map = psf_map
@property
def psf_map(self):
"""the PSFMap itself (`~gammapy.maps.Map`)"""
return self._psf_map
@property
def data(self):
"""the PSFMap data"""
return self._psf_map.data
@property
def quantity(self):
"""the PSFMap data as a quantity"""
return self._psf_map.quantity
@property
def geom(self):
"""The PSFMap MapGeom object"""
return self._psf_map.geom
[docs] @classmethod
def read(cls, filename, **kwargs):
"""Read a psf_map from file and create a PSFMap object"""
psfmap = Map.read(filename, **kwargs)
return cls(psfmap)
[docs] def write(self, *args, **kwargs):
"""Write the Map object containing the PSF Library map."""
self._psf_map.write(*args, **kwargs)
[docs] def get_energy_dependent_table_psf(self, position):
""" Returns EnergyDependentTable PSF at a given position
Parameters
----------
position : `~astropy.coordinates.SkyCoord`
the target position. Should be a single coordinates
Returns
-------
psf_table : `~gammapy.irf.EnergyDependentTablePSF`
the table PSF
"""
if position.size != 1:
raise ValueError(
"EnergyDependentTablePSF can be extracted at one single position only."
)
# axes ordering fixed. Could be changed.
pix_ener = np.arange(self.geom.axes[1].nbin)
pix_rad = np.arange(self.geom.axes[0].nbin)
# Convert position to pixels
pix_lon, pix_lat = self.psf_map.geom.to_image().coord_to_pix(position)
# Build the pixels tuple
pix = np.meshgrid(pix_lon, pix_lat, pix_rad, pix_ener)
# Interpolate in the PSF map. Squeeze to remove dimensions of length 1
psf_values = np.squeeze(
self.psf_map.interp_by_pix(pix) * u.Unit(self.psf_map.unit)
)
energies = self.psf_map.geom.axes[1].center * self.psf_map.geom.axes[1].unit
rad = self.psf_map.geom.axes[0].center * self.psf_map.geom.axes[0].unit
# Beware. Need to revert rad and energies to follow the TablePSF scheme.
return EnergyDependentTablePSF(energy=energies, rad=rad, psf_value=psf_values.T)
[docs] def get_psf_kernel(self, position, geom, max_radius=None, factor=4):
"""Returns a PSF kernel at the given position.
The PSF is returned in the form a WcsNDMap defined by the input MapGeom.
Parameters
----------
position : `~astropy.coordinates.SkyCoord`
the target position. Should be a single coordinate
geom : `~gammapy.maps.MapGeom`
the target geometry to use
max_radius : `~astropy.coordinates.Angle`
maximum angular size of the kernel map
factor : int
oversampling factor to compute the PSF
Returns
-------
kernel : `~gammapy.cube.PSFKernel`
the resulting kernel
"""
table_psf = self.get_energy_dependent_table_psf(position)
return PSFKernel.from_table_psf(table_psf, geom, max_radius, factor)
[docs] def containment_radius_map(self, energy, fraction=0.68):
"""Containment radius map.
Parameters
----------
energy : `~astropy.units.Quantity`
Scalar energy at which to compute the containment radius
fraction : float
the containment fraction (range: 0 to 1)
Returns
-------
containment_radius_map : `~gammapy.maps.Map`
Containment radius map
"""
coords = self.geom.to_image().get_coord().skycoord.flatten()
m = Map.from_geom(self.geom.to_image(), unit="deg")
for coord in coords:
psf_table = self.get_energy_dependent_table_psf(coord)
containment_radius = psf_table.containment_radius(energy, fraction)
m.fill_by_coord(coord, containment_radius)
return m