def test_generalized_gaussian_io(): model = GeneralizedGaussianSpatialModel() assert isinstance(model.to_region(), EllipseSkyRegion) new_model = GeneralizedGaussianSpatialModel.from_dict(model.to_dict()) assert isinstance(new_model, GeneralizedGaussianSpatialModel)
def test_generalized_gaussian(eta, r_0, e): reval = 6 dr = 0.01 geom = WcsGeom.create( skydir=(0, 0), binsz=dr, width=(2 * reval, 2 * reval), frame="galactic", ) # check normalization is robust for a large set of values model = GeneralizedGaussianSpatialModel(eta=eta, r_0=r_0 * u.deg, e=e, frame="galactic") eval_geom = model.evaluate_geom(geom) integ_geom = model.integrate_geom(geom) assert eval_geom.unit.is_equivalent("sr-1") assert integ_geom.unit.is_equivalent("") assert_allclose(integ_geom.data.sum(), 1.0, atol=3e-2) assert isinstance(model.to_region(), EllipseSkyRegion) new_model = GeneralizedGaussianSpatialModel.from_dict(model.to_dict()) assert isinstance(new_model, GeneralizedGaussianSpatialModel) assert_allclose( new_model.integrate_geom(geom).data.sum(), integ_geom.data.sum())
def test_generalized_gaussian_io(): model = GeneralizedGaussianSpatialModel(e=0.5) reg = model.to_region() assert isinstance(reg, EllipseSkyRegion) assert_allclose(reg.width.value, 1.73205, rtol=1e-5) new_model = GeneralizedGaussianSpatialModel.from_dict(model.to_dict()) assert isinstance(new_model, GeneralizedGaussianSpatialModel)