def test_estimator_reduce_l2(self):
real_weights = [0.66470588, 0.33529412]
conv = CSVDataConverter(TEST_WEATHER_PATH)
est = StandardEstimator(*conv.convert(KEY_MAP))
est.reduce()
for d, r in zip(est.weights['temperature'].T[0], real_weights):
self.assertAlmostEqual(d, r)
def test_to_list(self):
conv = CSVDataConverter(TEST_WEATHER_PATH)
est = StandardEstimator(*conv.convert(KEY_MAP))
est.reduce()
data = to_list(est.produce(conv.predict)['data'])
for v in data.values():
self.assertTrue(isinstance(v, list))
def test_estimator_reduce_l1(self):
real_weights = [0.57777778, 0.42222222]
conv = CSVDataConverter(TEST_WEATHER_PATH)
est = StandardEstimator(*conv.convert(KEY_MAP))
est.reduce(MinkowskiReducer())
for d, r in zip(est.weights['temperature'].T[0], real_weights):
self.assertAlmostEqual(d, r)
class TestTestDataConverter(unittest.TestCase):
def setUp(self):
self.conv = CSVDataConverter(TEST_WEATHER_PATH)
def test_convert(self):
predict, real = self.conv.convert(KEY_MAP)
self.assertEqual(predict['data']['temperature'].shape, (2, 20))
self.assertEqual(real['data']['temperature'].shape, (1, 20))
def test_service_names(self):
services = {'gismeteo': 1, 'meteoprog': 1}
self.assertListEqual(list(services.keys()),
self.conv.service_names().tolist())
def test_from_converter(self):
real_weights = [0.57777778, 0.42222222]
est = StandardEstimator.from_converter(
CSVDataConverter(TEST_WEATHER_PATH), KEY_MAP)
est.reduce(MinkowskiReducer())
for d, r in zip(est.weights['temperature'].T[0], real_weights):
self.assertAlmostEqual(d, r)
def test_estimator_produce(self):
test_temp_list = numpy.array([-3, 7, -4, 6]).reshape(2, 2)
data = {
'data': {
'temperature': test_temp_list,
},
'slots': ['one', 'two'],
'labels': [i for i in range(test_temp_list.shape[1])]
}
conv = CSVDataConverter(TEST_WEATHER_PATH)
est = StandardEstimator(*conv.convert(KEY_MAP))
est.reduce(EuclideanReducer())
w = est.weights['temperature']
res = est.produce(data)['data']['temperature']
test_res = w.T.dot(test_temp_list)
self.assertEqual(test_res[0, 0], res[0, 0])
self.assertEqual(test_res[0, 1], res[0, 1])
def test_estimator_type_error_raise(self):
conv = CSVDataConverter(TEST_WEATHER_PATH)
pred, real = conv.convert(KEY_MAP)
del pred['slots']
with self.assertRaises(KeyError):
StandardEstimator(pred, real)
def setUp(self):
self.conv = CSVDataConverter(TEST_WEATHER_PATH)