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