experiments/STT-tensorflow
1
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity

Fix "estimator" spelling in contrib/timeseries/examples/known_anomaly.py

Browse Source 
PiperOrigin-RevId: 210407945
This commit is contained in:
A. Unique TensorFlower 2018-08-27 12:09:26 -07:00 committed by TensorFlower Gardener
parent dbdf0ec5b3
commit 918ec0d12f
2 changed files with 6 additions and 6 deletions
tensorflow/contrib/timeseries/examples
known_anomaly.pyknown_anomaly_test.py

8
tensorflow/contrib/timeseries/examples/known_anomaly.py
View File

@ -41,7 +41,7 @@ _MODULE_PATH = path.dirname(__file__)
_DATA_FILE = path.join(_MODULE_PATH, "data/changepoints.csv")
def state_space_esitmator(exogenous_feature_columns):
def state_space_estimator(exogenous_feature_columns):
"""Constructs a StructuralEnsembleRegressor."""
def _exogenous_update_condition(times, features):
@ -68,7 +68,7 @@ def state_space_esitmator(exogenous_feature_columns):
4, 64)
def autoregressive_esitmator(exogenous_feature_columns):
def autoregressive_estimator(exogenous_feature_columns):
input_window_size = 8
output_window_size = 2
return (
@ -169,10 +169,10 @@ def main(unused_argv):
"Please install matplotlib to generate a plot from this example.")
make_plot("Ignoring a known anomaly (state space)",
*train_and_evaluate_exogenous(
estimator_fn=state_space_esitmator))
estimator_fn=state_space_estimator))
make_plot("Ignoring a known anomaly (autoregressive)",
*train_and_evaluate_exogenous(
estimator_fn=autoregressive_esitmator, train_steps=3000))
estimator_fn=autoregressive_estimator, train_steps=3000))
pyplot.show()

4
tensorflow/contrib/timeseries/examples/known_anomaly_test.py
View File

@ -28,7 +28,7 @@ class KnownAnomalyExampleTest(test.TestCase):
def test_shapes_and_variance_structural_ar(self):
(times, observed, all_times, mean, upper_limit, lower_limit,
anomaly_locations) = known_anomaly.train_and_evaluate_exogenous(
train_steps=1, estimator_fn=known_anomaly.autoregressive_esitmator)
train_steps=1, estimator_fn=known_anomaly.autoregressive_estimator)
self.assertAllEqual(
anomaly_locations,
[25, 50, 75, 100, 125, 150, 175, 249])
@ -40,7 +40,7 @@ class KnownAnomalyExampleTest(test.TestCase):
def test_shapes_and_variance_structural_ssm(self):
(times, observed, all_times, mean, upper_limit, lower_limit,
anomaly_locations) = known_anomaly.train_and_evaluate_exogenous(
train_steps=50, estimator_fn=known_anomaly.state_space_esitmator)
train_steps=50, estimator_fn=known_anomaly.state_space_estimator)
self.assertAllEqual(
anomaly_locations,
[25, 50, 75, 100, 125, 150, 175, 249])