def testSetVariationalParameters(self):
gc = gaussian_contributors.GaussianContributors()
gc.SetVariationalParameters(TEST_DATA)
# Check that gc was set to something sane:
contributors = set(['c1', 'c2', 'c3'])
self.assertSetEqual(contributors, set(gc.bias.keys()))
self.assertSetEqual(contributors, set(gc.precision.keys()))
def testResolveQuestion(self):
gc = gaussian_contributors.GaussianContributors()
gc.bias = {'worker1': -0.5, 'worker2': 0.8}
gc.precision = {'worker1': 1.0 / 0.3, 'worker2': 1.0 / 0.2}
expected = {
gaussian_contributors.MEAN: 2.32,
gaussian_contributors.VARIANCE: 0.12
}
resolution_map = gc.ResolveQuestion([('worker1', 2.0, {}),
('worker2', 3.0, {})])
test_util.AssertMapsAlmostEqual(self,
expected,
resolution_map,
label='variable')
# Now try with infinite-precision contributors:
gc.bias = {'worker1': 1.0, 'worker2': 2.0, 'worker3': 3.0}
gc.precision = {
'worker1': 1.0,
'worker2': gaussian_contributors.INFINITY,
'worker3': gaussian_contributors.INFINITY
}
expected = {
gaussian_contributors.MEAN: -2.5,
gaussian_contributors.VARIANCE: 0.25
}
resolution_map = gc.ResolveQuestion([('worker1', 0.0, {}),
('worker2', 0.0, {}),
('worker3', 0.0, {})])
test_util.AssertMapsAlmostEqual(self,
expected,
resolution_map,
label='variable')
# Check that non-numeric judgments cause a TypeError:
self.assertRaises(TypeError, gc.ResolveQuestion,
[('worker1', 'WTF', {})])
def testIterateUntilConvergence(self):
# Initialize a Gaussian model and an EM object:
gc = gaussian_contributors.GaussianContributors()
em = alternating_resolution.ExpectationMaximization()
# Use the judgments from the Dawid & Skene example:
data = test_util.DS_DATA
gc.InitializeResolutions(data)
# The algorithm converges slowly because EPSILON is small:
self.assertFalse(em.IterateUntilConvergence(data, gc, max_iterations=1000))
expected = {}
for question in data:
expected[question] = dict([
(gaussian_contributors.MEAN, EXPECTED_MEAN[question]),
(gaussian_contributors.VARIANCE, EXPECTED_VARIANCE)])
result = gc.ExtractResolutions(data)
test_util.AssertResolutionsAlmostEqual(self, expected, result)