def test_raises_error(self):
MP = ModelParameters()
MP.add_model_parameter('aa', 0, minimum=-10., maximum=10)
MP.add_model_parameter('bb', 5, minimum=100., maximum=10)
MP._openparameterstructure(nbatch=1)
with self.assertRaises(SystemExit, msg='Min > Max'):
MP._check_parameter_limits()
def test_initial_parameter_outside(self):
MP = ModelParameters()
MP.add_model_parameter('aa', 0, minimum = -10., maximum = 10)
MP.add_model_parameter('bb', 11, minimum = -10., maximum = 10)
MP._openparameterstructure(nbatch=1)
with self.assertRaises(SystemExit, msg = 'Initial value outside of bounds.'):
MP._check_initial_values_wrt_parameter_limits()
def test_scan_for_local_variables_with_sample_false(self):
MP = ModelParameters()
MP.add_model_parameter(name='m', theta0=0.2, local=0, sample=False)
MP.add_model_parameter(name='b', theta0=-0.5, local=1)
local = MP.scan_for_local_variables(nbatch=2, parameters=MP.parameters)
self.assertTrue(np.array_equal(local, np.array([1, 2])),
msg=str('Expect arrays to match: {} neq {}'.format(
local, np.array([1, 2]))))
def standard_check(self, theta0=1.0, name='$p_{0}$'):
MP = ModelParameters()
MP.add_model_parameter(name=name, theta0=theta0)
self.assertEqual(MP.parameters[0]['theta0'], theta0)
self.assertEqual(MP.parameters[0]['name'], name)
self.assertEqual(MP.parameters[0]['minimum'], -np.inf)
self.assertEqual(MP.parameters[0]['maximum'], np.inf)
self.assertEqual(MP.parameters[0]['prior_mu'], np.zeros([1]))
self.assertEqual(MP.parameters[0]['prior_sigma'], np.inf)
self.assertEqual(MP.parameters[0]['sample'], 1)
self.assertEqual(MP.parameters[0]['local'], 0)
def test_get_parameter_features(self):
MP = ModelParameters()
MP.add_model_parameter(name='a1', theta0=0.1, minimum=0, maximum=1)
MP.add_model_parameter(name='a2', theta0=0.2, minimum=0, maximum=1)
MP.add_model_parameter(name='a3', theta0=0.3, minimum=0, maximum=1)
npar, low_lim, upp_lim = get_parameter_features(MP.parameters)
self.assertEqual(npar, 3, msg='Expect to find 3 parameters')
self.assertTrue(np.array_equal(low_lim, np.zeros([3])),
msg=str('Expect low_lim all zero: {} neq {}'.format(
low_lim, np.zeros([3]))))
self.assertTrue(np.array_equal(upp_lim, np.ones([3])),
msg=str('Expect upp_lim all one: {} neq {}'.format(
upp_lim, np.ones([3]))))
def test_results_to_params(self):
MP = ModelParameters()
MP.add_model_parameter('aa', 0)
MP._openparameterstructure(nbatch=1)
# define minimal results dictionary
results = {'parind': MP._parind, 'names': MP._names, 'local': MP._local, 'theta': [1.2]}
# initialize default options
SO = SimulationOptions()
SO.define_simulation_options(verbosity=0)
MP.display_parameter_settings(verbosity = SO.verbosity, no_adapt = MP._no_adapt)
MP._results_to_params(results, 1)
MP._openparameterstructure(nbatch=1)
MP.display_parameter_settings(verbosity = SO.verbosity, no_adapt = MP._no_adapt)
self.assertEqual(MP.parameters[0]['theta0'], results['theta'][0])
def test_parameter_display_set_2(self):
MP = ModelParameters()
MP.add_model_parameter(name = 'm', theta0 = 2., minimum = -10, maximum = np.inf, sample = True)
MP.add_model_parameter(name = 'b', theta0 = -5., minimum = -10, maximum = 100, sample = False)
MP.add_model_parameter(name = 'b2', theta0 = -5.3e6, minimum = -1e7, maximum = 1e6, sample = True)
MP._openparameterstructure(nbatch = 1)
MP.display_parameter_settings(verbosity = None, no_adapt = None)
def test_get_parameter_features_with_inf_bounds(self):
MP = ModelParameters()
MP.add_model_parameter(name='a1',
theta0=0.1,
minimum=-np.inf,
maximum=1)
MP.add_model_parameter(name='a2', theta0=0.2, minimum=0, maximum=1)
MP.add_model_parameter(name='a3',
theta0=0.3,
minimum=0,
maximum=np.inf)
npar, low_lim, upp_lim = get_parameter_features(MP.parameters)
expect_low_lim = np.array([0.1 - 100 * 0.1, 0, 0])
expect_upp_lim = np.array([1, 1, 0.3 + 100 * 0.3])
self.assertEqual(npar, 3, msg='Expect to find 3 parameters')
self.assertTrue(np.array_equal(low_lim, expect_low_lim),
msg=str('Expect low_lim finite: {} neq {}'.format(
low_lim, expect_low_lim)))
self.assertTrue(np.array_equal(upp_lim, expect_upp_lim),
msg=str('Expect upp_lim finite: {} neq {}'.format(
upp_lim, expect_upp_lim)))
def test_initial_parameter_okay(self):
MP = ModelParameters()
MP.add_model_parameter('aa', 0, minimum=-10., maximum=10)
MP.add_model_parameter('bb', 9, minimum=-10., maximum=10)
MP._openparameterstructure(nbatch=1)
self.assertTrue(MP._check_initial_values_wrt_parameter_limits())