format header of motif.py and test_motif.py

MaxBenChrist · MaxBenChrist · commit 080c73f932c3 · 2017-08-18T17:37:20.000+02:00
diff --git a/tests/feature_extraction/test_motifs.py b/tests/feature_extraction/test_motifs.py
@@ -2,12 +2,12 @@
 # This file as well as the whole tsfresh package are licenced under the MIT licence (see the LICENCE.txt)
 # This module Ezekiel Kruglick 2017
 
-from __future__ import absolute_import, division
-from __future__ import print_function
+from __future__ import absolute_import, division, print_function
+
 import unittest
+import six
 import numpy as np
 from tsfresh.feature_extraction import motifs
-import six
 
 sample_array1 = np.array([9., -63., 5., 157., -21., -20., 27., -72., -123.,
                           94., 154., -57., -48., 18., -5., 14., 5., -7.,
diff --git a/tsfresh/feature_extraction/motifs.py b/tsfresh/feature_extraction/motifs.py
@@ -1,10 +1,18 @@
-import numpy as np
-from six.moves import range
+# -*- coding: utf-8 -*-
+# This file as well as the whole tsfresh package are licenced under the MIT licence (see the LICENCE.txt)
+# Maximilian Christ (maximilianchrist.com), Blue Yonder Gmbh, 2016
+
 """
-Functions and support for finding, grooming, and filtering time series data motifs
+Functions and support for finding, grooming, and filtering time series motifs.
+A motif is a characteristic subsequence of the inspected time series.
+
 by Ezekiel Kruglick
 """
 
+import numpy as np
+from six.moves import range
+
+
 
 def distance(x, y):
     """
