def test_excess_map_estimator_map_dataset_on_off_reco_exposure(
simple_dataset_on_off, ):
# TODO: this has never worked...
model = SkyModel(
PowerLawSpectralModel(amplitude="1e-9 cm-2 s-1TeV-1"),
GaussianSpatialModel(lat_0=0.0 * u.deg,
lon_0=0.0 * u.deg,
sigma=0.1 * u.deg,
frame="icrs"),
name="sky_model",
)
simple_dataset_on_off.models = [model]
spectral_model = PowerLawSpectralModel(index=15)
estimator_mod = ExcessMapEstimator(
0.11 * u.deg,
correlate_off=True,
spectral_model=spectral_model,
)
result_mod = estimator_mod.run(simple_dataset_on_off)
assert result_mod["flux"].unit == "cm-2s-1"
assert_allclose(result_mod["flux"].data.sum(), 5.254442e-06, rtol=1e-3)
reco_exposure = estimate_exposure_reco_energy(
simple_dataset_on_off, spectral_model=spectral_model)
assert_allclose(reco_exposure.data.sum(), 7.977796e12, rtol=0.001)
def test_significance_map_estimator_map_dataset_on_off_with_correlation(
simple_dataset_on_off, ):
exposure = simple_dataset_on_off.exposure
exposure.data += 1e6
# First without exposure
simple_dataset_on_off.exposure = None
estimator = ExcessMapEstimator(0.11 * u.deg,
energy_edges=[0.1, 1, 10] * u.TeV,
correlate_off=True)
result = estimator.run(simple_dataset_on_off)
assert result["counts"].data.shape == (2, 20, 20)
assert_allclose(result["counts"].data[:, 10, 10], 194)
assert_allclose(result["excess"].data[:, 10, 10], 97)
assert_allclose(result["background"].data[:, 10, 10], 97)
assert_allclose(result["sqrt_ts"].data[:, 10, 10], 5.741116, atol=1e-5)
assert_allclose(result["flux"].data[:, 10, 10], np.nan)
# Test with exposure
simple_dataset_on_off.exposure = exposure
estimator_image = ExcessMapEstimator(0.11 * u.deg,
energy_edges=[0.1, 1] * u.TeV,
correlate_off=True)
result_image = estimator_image.run(simple_dataset_on_off)
assert result_image["counts"].data.shape == (1, 20, 20)
assert_allclose(result_image["counts"].data[0, 10, 10], 194)
assert_allclose(result_image["excess"].data[0, 10, 10], 97)
assert_allclose(result_image["background"].data[0, 10, 10], 97)
assert_allclose(result_image["sqrt_ts"].data[0, 10, 10],
5.741116,
atol=1e-3)
assert_allclose(result_image["flux"].data[:, 10, 10], 9.7e-9, atol=1e-5)
# Test with mask fit
mask_fit = Map.from_geom(
simple_dataset_on_off._geom,
data=np.ones(simple_dataset_on_off.counts.data.shape, dtype=bool),
)
mask_fit.data[:, :, 10] = False
mask_fit.data[:, 10, :] = False
simple_dataset_on_off.mask_fit = mask_fit
estimator_image = ExcessMapEstimator(0.11 * u.deg,
apply_mask_fit=True,
correlate_off=True)
result_image = estimator_image.run(simple_dataset_on_off)
assert result_image["counts"].data.shape == (1, 20, 20)
assert_allclose(result_image["sqrt_ts"].data[0, 10, 10], np.nan, atol=1e-3)
assert_allclose(result_image["counts"].data[0, 10, 10], np.nan)
assert_allclose(result_image["excess"].data[0, 10, 10], np.nan)
assert_allclose(result_image["background"].data[0, 10, 10], np.nan)
assert_allclose(result_image["sqrt_ts"].data[0, 9, 9], 7.186745, atol=1e-3)
assert_allclose(result_image["counts"].data[0, 9, 9], 304)
assert_allclose(result_image["excess"].data[0, 9, 9], 152)
assert_allclose(result_image["background"].data[0, 9, 9], 152)
assert result_image["flux"].unit == u.Unit("cm-2s-1")
assert_allclose(result_image["flux"].data[0, 9, 9], 1.52e-8, rtol=1e-3)
simple_dataset_on_off.psf = None
# TODO: this has never worked...
model = SkyModel(
PowerLawSpectralModel(amplitude="1e-9 cm-2 s-1TeV-1"),
GaussianSpatialModel(lat_0=0.0 * u.deg,
lon_0=0.0 * u.deg,
sigma=0.1 * u.deg,
frame="icrs"),
name="sky_model",
)
simple_dataset_on_off.models = [model]
estimator_mod = ExcessMapEstimator(0.11 * u.deg,
apply_mask_fit=False,
correlate_off=True)
result_mod = estimator_mod.run(simple_dataset_on_off)
assert result_mod["counts"].data.shape == (1, 20, 20)
assert_allclose(result_mod["sqrt_ts"].data[0, 10, 10], 8.899278, atol=1e-3)
assert_allclose(result_mod["counts"].data[0, 10, 10], 388)
assert_allclose(result_mod["excess"].data[0, 10, 10], 190.68057)
assert_allclose(result_mod["background"].data[0, 10, 10], 197.31943)
assert result_mod["flux"].unit == "cm-2s-1"
assert_allclose(result_mod["flux"].data[0, 10, 10],
1.906806e-08,
rtol=1e-3)
assert_allclose(result_mod["flux"].data.sum(), 5.920642e-06, rtol=1e-3)
spectral_model = PowerLawSpectralModel(index=15)
estimator_mod = ExcessMapEstimator(
0.11 * u.deg,
apply_mask_fit=False,
correlate_off=True,
spectral_model=spectral_model,
)
result_mod = estimator_mod.run(simple_dataset_on_off)
assert result_mod["flux"].unit == "cm-2s-1"
assert_allclose(result_mod["flux"].data.sum(), 5.920642e-06, rtol=1e-3)
reco_exposure = estimate_exposure_reco_energy(
simple_dataset_on_off, spectral_model=spectral_model)
assert_allclose(reco_exposure.data.sum(), 7.977796e+12, rtol=0.001)