Add rolling averaging option to timeseries report

bmsapp/data_util.py

@@ -6,6 +6,7 @@ from datetime import datetime
 import pytz, calendar, time, math
 from dateutil import parser
 import numpy as np
+import pandas as pd
 from django.conf import settings
 
 
@@ -94,7 +95,7 @@ def histogram_from_series(pandas_series):
     # to 4 significant figures
     return list(zip(avg_bins, cts))
 
-def resample_timeseries(pandas_dataframe, averaging_hours, drop_na=True):
+def resample_timeseries(pandas_dataframe, averaging_hours, use_rolling_averaging=False, drop_na=True):
     '''
     Returns a new pandas dataframe that is resampled at the specified "averaging_hours"
     interval.  If the 'averaging_hours' parameter is fractional, the averaging time 
@@ -117,7 +118,20 @@ def resample_timeseries(pandas_dataframe, averaging_hours, drop_na=True):
         }
     params = interval_lookup.get(averaging_hours, {'rule':str(int(averaging_hours * 60)) + 'min', 'loffset':str(int(averaging_hours * 30)) + 'min'})
 
+    if not use_rolling_averaging:
         new_df = pandas_dataframe.resample(rule=params['rule'], loffset=params['loffset'],label='left').mean()
+    else:
+        # resample to consistent interval
+        original_interval = pandas_dataframe.index.to_series().diff().quantile(.05)
+        new_df = pandas_dataframe.resample(rule=original_interval).median()
+
+        # apply the rolling averaging
+        new_df = new_df.rolling(int(pd.Timedelta(hours=averaging_hours) / original_interval),center=True,min_periods=1).mean()
+
+        # downsample the result if there are more than 1000 values
+        if len(new_df) > 1000:
+            new_df = new_df.resample(rule=(pandas_dataframe.index[-1] - pandas_dataframe.index[0]) / 1000).mean()
+
     if drop_na:
         new_df = new_df.dropna()
 

bmsapp/reports/timeseries.py

@@ -10,7 +10,7 @@ class TimeSeries(basechart.BaseChart):
     """
 
     # see BaseChart for definition of these constants
-    CTRLS = 'refresh, ctrl_sensor, ctrl_avg, ctrl_occupied, time_period_group, get_embed_link'
+    CTRLS = 'refresh, ctrl_sensor, ctrl_avg, ctrl_use_rolling_averaging, ctrl_occupied, time_period_group, get_embed_link'
     MULTI_SENSOR = 1
 
     def result(self):
@@ -28,8 +28,15 @@ class TimeSeries(basechart.BaseChart):
         # get the requested averaging interval in hours
         if 'averaging_time' in self.request_params:
             averaging_hours = float(self.request_params['averaging_time'])
+            if 'use_rolling_averaging' in self.request_params:
+                use_rolling_averaging = True
+            else:
+                use_rolling_averaging = False
         else:
             averaging_hours = 0
+            use_rolling_averaging = False
+
+
 
         # determine the start time for selecting records and loop through the selected
         # records to get the needed dataset
@@ -51,7 +58,7 @@ class TimeSeries(basechart.BaseChart):
             if not df.empty:
                 # perform average (if requested)
                 if averaging_hours:
-                    df = bmsapp.data_util.resample_timeseries(df,averaging_hours)
+                    df = bmsapp.data_util.resample_timeseries(df,averaging_hours,use_rolling_averaging)
 
                 # create lists for plotly
                 if np.absolute(df.val.values).max() < 10000:

bmsapp/static/bmsapp/scripts/reports.coffee

@@ -108,7 +108,7 @@ process_chart_change = ->
     # start by hiding all input controls
   set_visibility(['refresh', 'ctrl_sensor', 'ctrl_avg', 'ctrl_avg_export',
     'ctrl_normalize', 'ctrl_occupied', 'xy_controls', 'time_period_group', 
-    'download_many', 'get_embed_link'], false)
+    'download_many', 'get_embed_link','ctrl_use_rolling_averaging'], false)
 
   # get the chart option control that is selected.  Then use the data
   # attributes of that option element to configure the user interface.
@@ -320,7 +320,7 @@ $ ->
   $("#select_chart").change process_chart_change
 
   # Set up change handlers for inputs.
-  ctrls = ['averaging_time', 'averaging_time_export', 'normalize', 'show_occupied', 
+  ctrls = ['averaging_time', 'averaging_time_export', 'normalize', 'use_rolling_averaging', 'show_occupied', 
     'select_sensor', 'select_sensor_x', 'select_sensor_y', 'averaging_time_xy', 'div_date',
     'start_date', 'end_date']
   $("##{ctrl}").change inputs_changed for ctrl in ctrls

bmsapp/static/bmsapp/scripts/reports.js

@@ -101,7 +101,7 @@
 
   process_chart_change = function () {
     var multi, selected_chart_option, sensor_val, single, vis_ctrls;
-    set_visibility(['refresh', 'ctrl_sensor', 'ctrl_avg', 'ctrl_avg_export', 'ctrl_normalize', 'ctrl_occupied', 'xy_controls', 'time_period_group', 'download_many', 'get_embed_link'], false);
+    set_visibility(['refresh', 'ctrl_sensor', 'ctrl_avg', 'ctrl_avg_export', 'ctrl_normalize', 'ctrl_use_rolling_averaging', 'ctrl_occupied', 'xy_controls', 'time_period_group', 'download_many', 'get_embed_link'], false);
     selected_chart_option = $("#select_chart").find("option:selected");
     vis_ctrls = selected_chart_option.data("ctrls").split(",");
     set_visibility(vis_ctrls, true);
@@ -299,7 +299,7 @@
     $("#select_group").change(update_bldg_list);
     $("#select_bldg").change(update_chart_sensor_lists);
     $("#select_chart").change(process_chart_change);
-    ctrls = ['averaging_time', 'averaging_time_export', 'normalize', 'show_occupied', 'select_sensor', 'select_sensor_x', 'select_sensor_y', 'averaging_time_xy', 'div_date', 'start_date', 'end_date'];
+    ctrls = ['averaging_time', 'averaging_time_export', 'normalize', 'use_rolling_averaging', 'show_occupied', 'select_sensor', 'select_sensor_x', 'select_sensor_y', 'averaging_time_xy', 'div_date', 'start_date', 'end_date'];
     for (i = 0, len = ctrls.length; i < len; i++) {
       ctrl = ctrls[i];
       $("#" + ctrl).change(inputs_changed);

bmsapp/templates/bmsapp/reports.html

@@ -91,6 +91,13 @@
                     Shade Occupied Periods
                 </label>
             </div>
+            <div id="ctrl_use_rolling_averaging" class="form-check mb-4 ml-3">
+                <input class="form-check-input" type="checkbox" value="" id="use_rolling_averaging"
+                    name="use_rolling_averaging">
+                <label class="form-check-label" for="use_rolling_averaging">
+                    Use Rolling Averaging
+                </label>
+            </div>
             <div id="ctrl_normalize" class="form-check mb-4 ml-3">
                 <input class="form-check-input" type="checkbox" value="" id="normalize"
                     name="normalize">