def test_wcsndmap_downsample_axis():
axis = MapAxis.from_edges([1, 2, 3, 4, 5], name="test")
geom = WcsGeom.create(npix=(4, 4), axes=[axis])
m = WcsNDMap(geom, unit="m2")
m.data += 1
m2 = m.downsample(2, preserve_counts=True, axis_name="test")
assert m2.data.shape == (2, 4, 4)
def test_wcsndmap_downsample(npix, binsz, frame, proj, skydir, axes):
geom = WcsGeom.create(npix=npix, binsz=binsz, proj=proj, frame=frame, axes=axes)
m = WcsNDMap(geom, unit="m2")
# Check whether we can downsample
if np.all(np.mod(geom.npix[0], 2) == 0) and np.all(np.mod(geom.npix[1], 2) == 0):
m2 = m.downsample(2, preserve_counts=True)
assert_allclose(np.nansum(m.data), np.nansum(m2.data))
assert m.unit == m2.unit
def make_map_background_irf(pointing, ontime, bkg, geom, oversampling=None):
"""Compute background map from background IRFs.
Parameters
----------
pointing : `~gammapy.data.FixedPointingInfo` or `~astropy.coordinates.SkyCoord`
Observation pointing
- If a ``FixedPointingInfo`` is passed, FOV coordinates are properly computed.
- If a ``SkyCoord`` is passed, FOV frame rotation is not taken into account.
ontime : `~astropy.units.Quantity`
Observation ontime. i.e. not corrected for deadtime
see https://gamma-astro-data-formats.readthedocs.io/en/stable/irfs/full_enclosure/bkg/index.html#notes)
bkg : `~gammapy.irf.Background3D`
Background rate model
geom : `~gammapy.maps.WcsGeom`
Reference geometry
oversampling: int
Oversampling factor in energy, used for the background model evaluation.
Returns
-------
background : `~gammapy.maps.WcsNDMap`
Background predicted counts sky cube in reco energy
"""
# TODO:
# This implementation can be improved in two ways:
# 1. Create equal time intervals between TSTART and TSTOP and sum up the
# background IRF for each interval. This is instead of multiplying by
# the total ontime. This then handles the rotation of the FoV.
# 2. Use the pointing table (does not currently exist in CTA files) to
# obtain the RA DEC and time for each interval. This then considers that
# the pointing might change slightly over the observation duration
# Get altaz coords for map
if oversampling is not None:
geom = geom.upsample(factor=oversampling, axis="energy")
map_coord = geom.to_image().get_coord()
sky_coord = map_coord.skycoord
if isinstance(pointing, FixedPointingInfo):
altaz_coord = sky_coord.transform_to(pointing.altaz_frame)
# Compute FOV coordinates of map relative to pointing
fov_lon, fov_lat = sky_to_fov(altaz_coord.az, altaz_coord.alt,
pointing.altaz.az, pointing.altaz.alt)
else:
# Create OffsetFrame
frame = SkyOffsetFrame(origin=pointing)
pseudo_fov_coord = sky_coord.transform_to(frame)
fov_lon = pseudo_fov_coord.lon
fov_lat = pseudo_fov_coord.lat
energies = geom.get_axis_by_name("energy").edges
bkg_de = bkg.evaluate_integrate(
fov_lon=fov_lon,
fov_lat=fov_lat,
energy_reco=energies[:, np.newaxis, np.newaxis],
)
d_omega = geom.to_image().solid_angle()
data = (bkg_de * d_omega * ontime).to_value("")
bkg_map = WcsNDMap(geom, data=data)
if oversampling is not None:
bkg_map = bkg_map.downsample(factor=oversampling, axis="energy")
return bkg_map
