Merge pull request #38 from opengridcc/issue19_standby

Finalisation of standby analysis (#19)
opengridcc · Apr 26, 2018 · 151e4a5 · 151e4a5
2 parents 384c1bd + 5da6fc6
commit 151e4a5
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Showing 2 changed files with 15 additions and 12 deletions.
diff --git a/opengrid/library/analysis.py b/opengrid/library/analysis.py
@@ -75,7 +75,7 @@ def standby(df, resolution='24h', time_window=None):
 
     Parameters
     ----------
-    df : Pandas DataFrame
+    df : pandas.DataFrame or pandas.Series
         Electricity Power
     resolution : str, default='d'
         Resolution of the computation.  Data will be resampled to this resolution (as mean) before computation
@@ -91,14 +91,17 @@ def standby(df, resolution='24h', time_window=None):
     df : pandas.Series with DateTimeIndex in the given resolution
     """
 
+    if df.empty:
+        raise EmptyDataFrame()
+
+    df = pd.DataFrame(df)  # if df was a pd.Series, convert to DataFrame
     def parse_time(t):
         if isinstance(t, numbers.Number):
             return pd.Timestamp.utcfromtimestamp(t).time()
         else:
             return pd.Timestamp(t).time()
 
-    if df.empty:
-        raise EmptyDataFrame()
+
     # first filter based on the time-window
     if time_window is not None:
         t_start = parse_time(time_window[0])
@@ -118,7 +121,7 @@ def share_of_standby(df, resolution='24h', time_window=None):
 
     Parameters
     ----------
-    df : Pandas DataFrame
+    df : pandas.DataFrame or pandas.Series
         Power (typically electricity, can be anything)
     resolution : str, default='d'
         Resolution of the computation.  Data will be resampled to this resolution (as mean) before computation
@@ -134,13 +137,13 @@ def share_of_standby(df, resolution='24h', time_window=None):
     fraction : float between 0-1 with the share of the standby consumption
     """
 
-    df_ = pd.DataFrame(df)
-    p_sb = standby(df_, resolution, time_window)
-    df_resampled = df_.resample(resolution).mean()
-    p_tot = df_resampled.sum()
+    p_sb = standby(df, resolution, time_window)
+    df = df.resample(resolution).mean()
+    p_tot = df.sum()
     p_standby = p_sb.sum()
-    share_standby = p_standby/p_tot
-    return share_standby.iloc[0]
+    share_standby = p_standby / p_tot
+    res = share_standby.iloc[0]
+    return res
 
 
 def count_peaks(ts):

diff --git a/opengrid/tests/test_analyses.py b/opengrid/tests/test_analyses.py
@@ -27,11 +27,11 @@ def test_standby_with_time_window(self):
         df = datasets.get('elec_power_min_1sensor')
         res = og.analysis.standby(df, 'D', time_window=('01:00', '06:00'))
         self.assertEqual(res.index.tz.zone, 'Europe/Brussels')
-        self.assertEqual(res.to_json(), '{"1507327200000":61.739999936,"1507413600000":214.9799999222,"1507500000000":53.0399997951,"1507586400000":55.7399999164,"1507672800000":59.94000006,"1507759200000":69.4800002407,"1507845600000":56.8200000236,"1507932000000":54.1799997864,"1508018400000":54.779999801,"1508104800000":54.7199997772,"1508191200000":98.5199999576,"1508277600000":55.6799999066,"1508364000000":53.9399997052,"1508450400000":109.5599999931,"1508536800000":144.3600001093,"1508623200000":52.7999997279}')
+        self.assertEqual(res.squeeze().to_json(), '{"1507327200000":61.739999936,"1507413600000":214.9799999222,"1507500000000":53.0399997951,"1507586400000":55.7399999164,"1507672800000":59.94000006,"1507759200000":69.4800002407,"1507845600000":56.8200000236,"1507932000000":54.1799997864,"1508018400000":54.779999801,"1508104800000":54.7199997772,"1508191200000":98.5199999576,"1508277600000":55.6799999066,"1508364000000":53.9399997052,"1508450400000":109.5599999931,"1508536800000":144.3600001093,"1508623200000":52.7999997279}')
 
         res = og.analysis.standby(df, 'D', time_window=('22:00', '06:00'))
         self.assertEqual(res.index.tz.zone, 'Europe/Brussels')
-        self.assertEqual(res.to_json(), '{"1507327200000":61.739999936,"1507413600000":119.2800000636,"1507500000000":53.0399997951,"1507586400000":55.7399999164,"1507672800000":59.94000006,"1507759200000":69.4800002407,"1507845600000":56.8200000236,"1507932000000":54.1799997864,"1508018400000":54.779999801,"1508104800000":54.7199997772,"1508191200000":98.5199999576,"1508277600000":55.6799999066,"1508364000000":53.9399997052,"1508450400000":96.3000000408,"1508536800000":133.9200000744,"1508623200000":52.7999997279}')
+        self.assertEqual(res.squeeze().to_json(), '{"1507327200000":61.739999936,"1507413600000":119.2800000636,"1507500000000":53.0399997951,"1507586400000":55.7399999164,"1507672800000":59.94000006,"1507759200000":69.4800002407,"1507845600000":56.8200000236,"1507932000000":54.1799997864,"1508018400000":54.779999801,"1508104800000":54.7199997772,"1508191200000":98.5199999576,"1508277600000":55.6799999066,"1508364000000":53.9399997052,"1508450400000":96.3000000408,"1508536800000":133.9200000744,"1508623200000":52.7999997279}')
 
     def test_share_of_standby_1(self):
         df = pd.DataFrame(data={'conso':np.ones(48)},