Unit tests for daily seasonality (Py)

python/fbprophet/tests/data.csv

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python/fbprophet/tests/data2.csv

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python/fbprophet/tests/test_prophet.py

@@ -10,10 +10,7 @@ from __future__ import division
 from __future__ import print_function
 from __future__ import unicode_literals
 
-try:
-    from StringIO import StringIO
-except ImportError:
-    from io import StringIO
+import os
 
 import numpy as np
 import pandas as pd
@@ -24,6 +21,15 @@ from fbprophet import Prophet
 # fb-block 1 end
 # fb-block 2
 
+DATA = pd.read_csv(
+    os.path.join(os.path.dirname(__file__), 'data.csv'),
+    parse_dates=['ds'],
+)
+DATA2 = pd.read_csv(
+    os.path.join(os.path.dirname(__file__), 'data2.csv'),
+    parse_dates=['ds'],
+)
+
 class TestProphet(TestCase):
 
     def test_fit_predict(self):
@@ -298,517 +304,25 @@ class TestProphet(TestCase):
         m.fit(DATA)
         self.assertEqual(m.seasonalities['yearly'], (365.25, 7))
 
-
-DATA = pd.read_csv(StringIO("""
-ds,y
-2012-05-18,38.23
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-2013-06-19,24.31
-2013-06-20,23.9
-2013-06-21,24.53
-2013-06-24,23.94
-2013-06-25,24.25
-2013-06-26,24.16
-2013-06-27,24.66
-2013-06-28,24.88
-2013-07-01,24.81
-2013-07-02,24.41
-2013-07-03,24.52
-2013-07-05,24.37
-2013-07-08,24.71
-2013-07-09,25.48
-2013-07-10,25.8
-2013-07-11,25.81
-2013-07-12,25.91
-2013-07-15,26.28
-2013-07-16,26.32
-2013-07-17,26.65
-2013-07-18,26.18
-2013-07-19,25.88
-2013-07-22,26.05
-2013-07-23,26.13
-2013-07-24,26.51
-2013-07-25,34.36
-2013-07-26,34.01
-2013-07-29,35.43
-2013-07-30,37.63
-2013-07-31,36.8
-2013-08-01,37.49
-2013-08-02,38.05
-2013-08-05,39.19
-2013-08-06,38.55
-2013-08-07,38.87
-2013-08-08,38.54
-2013-08-09,38.5
-2013-08-12,38.22
-2013-08-13,37.02
-2013-08-14,36.65
-2013-08-15,36.56
-2013-08-16,37.08
-2013-08-19,37.81
-2013-08-20,38.41
-2013-08-21,38.32
-2013-08-22,38.55
-2013-08-23,40.55
-2013-08-26,41.34
-2013-08-27,39.64
-2013-08-28,40.55
-2013-08-29,41.28
-2013-08-30,41.29
-2013-09-03,41.87
-2013-09-04,41.78
-2013-09-05,42.66
-2013-09-06,43.95
-2013-09-09,44.04
-2013-09-10,43.6
-2013-09-11,45.04
-2013-09-12,44.75
-2013-09-13,44.31
-2013-09-16,42.51
-2013-09-17,45.07
-2013-09-18,45.23
-2013-09-19,45.98
-2013-09-20,47.49
-2013-09-23,47.19
-2013-09-24,48.45
-2013-09-25,49.46
-2013-09-26,50.39
-2013-09-27,51.24
-2013-09-30,50.23
-2013-10-01,50.42
-2013-10-02,50.28
-2013-10-03,49.18
-2013-10-04,51.04
-2013-10-07,50.52
-2013-10-08,47.14
-2013-10-09,46.77
-2013-10-10,49.05
-2013-10-11,49.11
-2013-10-14,49.51
-2013-10-15,49.5
-2013-10-16,51.14
-2013-10-17,52.21
-2013-10-18,54.22
-2013-10-21,53.85
-2013-10-22,52.68
-2013-10-23,51.9
-2013-10-24,52.45
-2013-10-25,51.95
-2013-10-28,50.23
-2013-10-29,49.4
-2013-10-30,49.01
-2013-10-31,50.21
-2013-11-01,49.75
-2013-11-04,48.22
-2013-11-05,50.11
-2013-11-06,49.12
-2013-11-07,47.56
-2013-11-08,47.53
-2013-11-11,46.2
-2013-11-12,46.61
-2013-11-13,48.71
-2013-11-14,48.99
-2013-11-15,49.01
-2013-11-18,45.83
-2013-11-19,46.36
-2013-11-20,46.43
-2013-11-21,46.7
-2013-11-22,46.23
-2013-11-25,44.82
-2013-11-26,45.89
-2013-11-27,46.49
-2013-11-29,47.01
-2013-12-02,47.06
-2013-12-03,46.73
-2013-12-04,48.62
-2013-12-05,48.34
-2013-12-06,47.94
-2013-12-09,48.84
-2013-12-10,50.25
-2013-12-11,49.38
-2013-12-12,51.83
-2013-12-13,53.32
-2013-12-16,53.81
-2013-12-17,54.86
-2013-12-18,55.57
-2013-12-19,55.05
-2013-12-20,55.12
-2013-12-23,57.77
-2013-12-24,57.96
-2013-12-26,57.73
-2013-12-27,55.44
-2013-12-30,53.71
-2013-12-31,54.65
-2014-01-02,54.71
-2014-01-03,54.56
-2014-01-06,57.2
-2014-01-07,57.92
-2014-01-08,58.23
-2014-01-09,57.22
-2014-01-10,57.94
-2014-01-13,55.91
-2014-01-14,57.74
-2014-01-15,57.6
-2014-01-16,57.19
-2014-01-17,56.3
-2014-01-21,58.51
-2014-01-22,57.51
-2014-01-23,56.63
-2014-01-24,54.45
-2014-01-27,53.55
-2014-01-28,55.14
-2014-01-29,53.53
-2014-01-30,61.08
-2014-01-31,62.57
-2014-02-03,61.48
-2014-02-04,62.75
-2014-02-05,62.19
-2014-02-06,62.16
-2014-02-07,64.32
-2014-02-10,63.55
-2014-02-11,64.85
-2014-02-12,64.45
-2014-02-13,67.33
-2014-02-14,67.09
-2014-02-18,67.3
-2014-02-19,68.06
-2014-02-20,69.63
-2014-02-21,68.59
-2014-02-24,70.78
-2014-02-25,69.85
-2014-02-26,69.26
-2014-02-27,68.94
-2014-02-28,68.46
-2014-03-03,67.41
-2014-03-04,68.8
-2014-03-05,71.57
-2014-03-06,70.84
-2014-03-07,69.8
-2014-03-10,72.03
-2014-03-11,70.1
-2014-03-12,70.88
-2014-03-13,68.83
-2014-03-14,67.72
-2014-03-17,68.74
-2014-03-18,69.19
-2014-03-19,68.24
-2014-03-20,66.97
-2014-03-21,67.24
-2014-03-24,64.1
-2014-03-25,64.89
-2014-03-26,60.39
-2014-03-27,60.97
-2014-03-28,60.01
-2014-03-31,60.24
-2014-04-01,62.62
-2014-04-02,62.72
-2014-04-03,59.49
-2014-04-04,56.75
-2014-04-07,56.95
-2014-04-08,58.19
-2014-04-09,62.41
-2014-04-10,59.16
-2014-04-11,58.53
-2014-04-14,58.89
-2014-04-15,59.09
-2014-04-16,59.72
-2014-04-17,58.94
-2014-04-21,61.24
-2014-04-22,63.03
-2014-04-23,61.36
-2014-04-24,60.87
-2014-04-25,57.71
-2014-04-28,56.14
-2014-04-29,58.15
-2014-04-30,59.78
-2014-05-01,61.15
-2014-05-02,60.46
-2014-05-05,61.22
-2014-05-06,58.53
-2014-05-07,57.39
-2014-05-08,56.76
-2014-05-09,57.24
-2014-05-12,59.83
-2014-05-13,59.83
-2014-05-14,59.23
-2014-05-15,57.92
-2014-05-16,58.02
-2014-05-19,59.21
-2014-05-20,58.56
-2014-05-21,60.49
-2014-05-22,60.52
-2014-05-23,61.35
-2014-05-27,63.48
-2014-05-28,63.51
-2014-05-29,63.83
-2014-05-30,63.30
-"""), parse_dates=['ds'])
+    def test_auto_daily_seasonality(self):
+        # Should be enabled
+        m = Prophet()
+        self.assertEqual(m.yearly_seasonality, 'auto')
+        m.fit(DATA2)
+        self.assertIn('daily', m.seasonalities)
+        self.assertEqual(m.seasonalities['daily'], (1, 4))
+        # Should be disabled due to too short history
+        N = 430
+        train = DATA2.head(N)
+        m = Prophet()
+        m.fit(train)
+        self.assertNotIn('daily', m.seasonalities)
+        m = Prophet(daily_seasonality=True)
+        m.fit(train)
+        self.assertIn('daily', m.seasonalities)
+        m = Prophet(daily_seasonality=7)
+        m.fit(DATA2)
+        self.assertEqual(m.seasonalities['daily'], (1, 7))
+        m = Prophet()
+        m.fit(DATA)
+        self.assertNotIn('daily', m.seasonalities)