def test_fit_works_with_scatterer(self):
function_result = fit(DATA, SPHERE)
function_result.time = None
model = make_default_model(SPHERE, None)
object_result = model.fit(DATA)
object_result.time = None
self.assertEqual(function_result, object_result)
def test_fit_works_with_scatterer_and_parameters(self):
function_result = fit(DATA, SPHERE, ['n', 'x'])
function_result.time = None
model = make_default_model(SPHERE, ['n', 'x'])
object_result = model.fit(DATA)
object_result.time = None
self.assertEqual(function_result, object_result)
def test_parameterize_scatterer_spheres(self):
sphere = Sphere(r=0.5, n=1, center=[0, 0, 0])
model = make_default_model(Spheres([sphere, sphere], warn=False))
expected = {
'0:n', '1:n', '0:r', '1:r', 'alpha', '0:x', '0:y', '0:z', '1:x',
'1:y', '1:z'
}
self.assertEqual(set(model.parameters.keys()), expected)
def test_parameterize_scatterer_spheres_by_given(self):
s1 = Sphere(r=0.5, n=1, center=[0, 0, 0])
s2 = Sphere(r=0.5, n=1, center=[1, 1, 1])
model = make_default_model(Spheres([s1, s2]), ['0:r', '1:x'])
e1 = Sphere(r=prior.Uniform(0, np.inf, 0.5, '0:r'),
n=1,
center=[0, 0, 0])
e2 = Sphere(r=0.5,
n=1,
center=[prior.Uniform(-np.inf, np.inf, 1, '1:x'), 1, 1])
self.assertEqual(model.scatterer, Spheres([e1, e2]))
def test_passing_model_and_parameters_gives_warning(self):
model = make_default_model(SPHERE, None)
self.assertWarns(UserWarning, fit, DATA, model, ['r', 'y'])
def test_model_takes_precendence_over_parameters(self):
model = make_default_model(SPHERE, ['n', 'x'])
with warnings.catch_warnings():
warnings.simplefilter('ignore', UserWarning)
result = fit(DATA, model, ['r', 'y'])
self.assertEqual(result._names, ['n', 'center.0', 'alpha'])
def test_make_default_model_construction(self):
model = make_default_model(Sphere(), None)
self.assertEqual(model.noise_sd, 1)
self.assertTrue(isinstance(model, AlphaModel))
def test_make_default_model_with_parameters(self):
model = make_default_model(SPHERE, ['r'])
self.assertEqual(set(model.parameters.keys()), {'r', 'alpha'})
def test_make_default_model_with_no_parameters(self):
model = make_default_model(SPHERE, None)
expected_parameters = SPHERE.parameters
expected_parameters['alpha'] = None
self.assertEqual(model.parameters.keys(), expected_parameters.keys())
def test_parameterize_scatterer_spheres_minval(self):
sphere = Sphere(r=0.5, n=1, center=[0, 0, 0])
model = make_default_model(Spheres([sphere, sphere], warn=False))
self.assertEqual(model.parameters['0:n'].lower_bound, 0)
self.assertEqual(model.parameters['1:n'].lower_bound, 0)
def test_make_default_model_with_no_parameters(self):
model = make_default_model(SPHERE, None)
expected = {'n', 'r', 'alpha', 'x', 'y', 'z'}
self.assertEqual(set(model.parameters.keys()), expected)
