def test_parameter_in_bounds(model):
"""Test parameter in bounds method."""
x = np.array([0, 0.5, 1, 3])
model.names = ['x', 'y']
model.bounds = {'x': [0, 1], 'y': [0, 4]}
val = Model.parameter_in_bounds(model, x, 'x')
np.testing.assert_array_equal(val, np.array([True, True, True, False]))
def test_new_point_log_prob(model):
"""Test the log prob for new points.
Should be zero.
"""
x = numpy_array_to_live_points(np.random.randn(2, 1), ['x'])
log_prob = Model.new_point_log_prob(model, x)
assert log_prob.size == 2
assert (log_prob == 0).all()
def test_in_bounds(model):
"""Test the `in_bounds` method.
Tests both finite and infinite prior bounds.
"""
x = numpy_array_to_live_points(np.array([[0.5, 1], [2, 1]]), ['x', 'y'])
model.names = ['x', 'y']
model.bounds = {'x': [0, 1], 'y': [-np.inf, np.inf]}
val = Model.in_bounds(model, x)
np.testing.assert_array_equal(val, np.array([True, False]))
def test_single_new_point(model):
"""Test the method that draw one point within the prior bounds"""
model.names = ['x', 'y']
model.bounds = {'x': [-1, 1], 'y': [-2, 2]}
model.lower_bounds = np.array([-1, -2])
model.upper_bounds = np.array([1, 2])
model.log_prior = MagicMock(return_value=0)
model.dims = 2
x = Model._single_new_point(model)
assert ((x['x'] >= -1) & (x['x'] <= 1))
assert ((x['y'] >= -2) & (x['y'] <= 2))
def test_likelihood_evaluations(model):
"""
Test `evaluate_log_likelihood` and ensure the counter increases.
"""
x = 1
model.likelihood_evaluations = 0
model.log_likelihood = MagicMock(return_value=2)
log_l = Model.evaluate_log_likelihood(model, x)
model.log_likelihood.assert_called_once_with(x)
assert log_l == 2
assert model.likelihood_evaluations == 1
def test_multiple_new_points(model):
"""Test the method that draws multiple points within the prior bounds"""
n = 10
model.names = ['x', 'y']
model.bounds = {'x': [-1, 1], 'y': [-2, 2]}
model.lower_bounds = np.array([-1, -2])
model.upper_bounds = np.array([1, 2])
model.log_prior = MagicMock(return_value=np.zeros(10))
model.dims = 2
x = Model._multiple_new_points(model, N=n)
assert x.size == n
assert ((x['x'] >= -1) & (x['x'] <= 1)).all()
assert ((x['y'] >= -2) & (x['y'] <= 2)).all()
def test_log_likelihood(model):
"""Verify the log likelihood raises a NotImplementedError"""
with pytest.raises(NotImplementedError):
Model.log_likelihood(model, 1)
def test_log_prior(model):
"""Verify the log prior raises a NotImplementedError"""
with pytest.raises(NotImplementedError):
Model.log_prior(model, 1)
def test_new_point_multiple(model):
"""Test the new point when asking for multiple points"""
model._multiple_new_points = MagicMock()
Model.new_point(model, N=10)
model._multiple_new_points.assert_called_once_with(10)
def test_new_point_single(model):
"""Test the new point when asking for 1 point"""
model._single_new_point = MagicMock()
Model.new_point(model, N=1)
model._single_new_point.assert_called_once()
def test_sample_parameter(model):
"""Assert an error is raised."""
with pytest.raises(NotImplementedError) as excinfo:
Model.sample_parameter(model, 'x', n=2)
assert 'User must implement this method!' in str(excinfo.value)