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)