Check for segment length in all models (#127)

analytics/models/drop_model.py

@@ -39,7 +39,9 @@ class DropModel(Model):
                 segment_from_index = utils.timestamp_to_index(dataframe, pd.to_datetime(segment['from']))
                 segment_to_index = utils.timestamp_to_index(dataframe, pd.to_datetime(segment['to']))
 
-                segment_data = data[segment_from_index : segment_to_index + 1].reset_index(drop=True)
+                segment_data = data[segment_from_index: segment_to_index + 1]
+                if len(segment_data) == 0:
+                    continue
                 segment_min = min(segment_data)
                 segment_max = max(segment_data)
                 confidences.append(0.20 * (segment_max - segment_min))

analytics/models/jump_model.py

@@ -42,7 +42,9 @@ class JumpModel(Model):
                 segment_from_index = utils.timestamp_to_index(dataframe, pd.to_datetime(segment['from']))
                 segment_to_index = utils.timestamp_to_index(dataframe, pd.to_datetime(segment['to']))
 
-                segment_data = data.loc[segment_from_index : segment_to_index + 1].reset_index(drop=True)
+                segment_data = data[segment_from_index: segment_to_index + 1]
+                if len(segment_data) == 0:
+                    continue
                 segment_min = min(segment_data)
                 segment_max = max(segment_data)
                 confidences.append(0.20 * (segment_max - segment_min))

analytics/models/peak_model.py

@@ -38,6 +38,8 @@ class PeakModel(Model):
                 segment_to_index = utils.timestamp_to_index(dataframe, pd.to_datetime(segment['to']))
 
                 segment_data = data[segment_from_index: segment_to_index + 1]
+                if len(segment_data) == 0:
+                    continue
                 segment_min = min(segment_data)
                 segment_max = max(segment_data)
                 confidences.append(0.2 * (segment_max - segment_min))

analytics/models/reverse_peak_model.py

@@ -37,6 +37,8 @@ class ReversePeakModel(Model):
                 segment_to_index = utils.timestamp_to_index(dataframe, pd.to_datetime(segment['to']))
 
                 segment_data = data[segment_from_index: segment_to_index + 1]
+                if len(segment_data) == 0:
+                    continue
                 segment_min = min(segment_data)
                 segment_max = max(segment_data)
                 confidences.append(0.2 * (segment_max - segment_min))