def test_can_sample_range(self):
attributes = {
'example_p': ProbabilityDistribution({
0: 0.01,
1: 0.01,
2.006: 0.01,
3: 0.01,
4: 0.01,
5: 0.01,
6: 0.88,
7: 0.01,
8: 0.01,
9: 0.01,
10: 0.01,
11: 0.01,
12: 0.01,
})
}
dwelling = Dwelling(attributes, self.mock_connection)
dwelling.outputs = {
'example': {
'type': 'numrange',
'sampling': True,
'distribution': 'example_p'
}
}
self.sampling_module.process(dwelling)
# Should take 95% interval by default,
# should round to 2 decimals.
self.assertEqual(str(dwelling.attributes['example']), '[2.01, 10]')
def test_can_sample_boolean(self):
attributes = {
'example_p': 1
}
dwelling = Dwelling(attributes, self.mock_connection)
dwelling.outputs = {
'example': {
'type': 'boolean',
'sampling': True,
'distribution': 'example_p'
}
}
self.sampling_module.process(dwelling)
self.assertTrue(dwelling.attributes['example'])
def test_can_sample_distribution(self):
attributes = {
'example_p': ProbabilityDistribution({
1: 0.5,
2: 0.5
})
}
dwelling = Dwelling(attributes, self.mock_connection)
dwelling.outputs = {
'example': {
'type': 'double precision',
'sampling': True,
'distribution': 'example_p'
}
}
self.sampling_module.process(dwelling)
# Should take mean by default
self.assertAlmostEqual(dwelling.attributes['example'], 1.5)
