offline background cp chart creation

rowers/dataprep.py

@@ -23,7 +23,7 @@ from rowingdata import (
     get_file_type, get_empower_rigging,get_empower_firmware
     )
 
-from rowers.tasks import handle_sendemail_unrecognized
+from rowers.tasks import handle_sendemail_unrecognized,handle_setcp
 from rowers.tasks import handle_zip_file
 
 from pandas import DataFrame, Series
@@ -1044,8 +1044,14 @@ def fetchcp_new(rower,workouts):
 
     return df['delta'],df['cp'],0,df['workout']
 
-def setcp(workout):
+def setcp(workout,background=False):
+    filename = 'media/cpdata_{id}.parquet.gz'.format(id=workout.id)
+
     strokesdf = getsmallrowdata_db(['power','workoutid','time'],ids = [workout.id])
+    if background:
+        job = myqueue(queuelow,handle_setcp,strokesdf,filename,workout.id)
+        return job.id
+
     if not strokesdf.empty:
         totaltime = strokesdf['time'].max()
         try:
@@ -1061,7 +1067,7 @@ def setcp(workout):
                 logarr = datautils.getlogarr(maxt)
                 dfgrouped = strokesdf.groupby(['workoutid'])
                 delta, cpvalues, avgpower = datautils.getcp(dfgrouped, logarr)
-                filename = 'media/cpdata_{id}.parquet.gz'.format(id=workout.id)
+
                 df = pd.DataFrame({
                     'delta':delta,
                     'cp':cpvalues,

rowers/tasks.py

@@ -2704,6 +2704,38 @@ def handle_sendemail_invite_reject(email, name, teamname, managername,
     return 1
 
 
+@app.task
+def handle_setcp(strokesdf,filename,workoutid,debug=False,**kwargs):
+    try:
+        os.remove(filename)
+    except FileNotFoundError:
+        pass
+    if not strokesdf.empty:
+        totaltime = strokesdf['time'].max()
+        try:
+            powermean = strokesdf['power'].mean()
+        except KeyError:
+            powermean = 0
+
+        if powermean != 0:
+            thesecs = totaltime
+            maxt = 1.05 * thesecs
+
+            if maxt > 0:
+                logarr = datautils.getlogarr(maxt)
+                dfgrouped = strokesdf.groupby(['workoutid'])
+                delta, cpvalues, avgpower = datautils.getcp(dfgrouped, logarr)
+
+                df = pd.DataFrame({
+                    'delta':delta,
+                    'cp':cpvalues,
+                    'id':workoutid,
+                })
+                df.to_parquet(filename,engine='fastparquet',compression='GZIP')
+                return 1
+
+    return 1
+
 @app.task
 def handle_sendemail_invite_accept(email, name, teamname, managername,
                                    debug=False,**kwargs):

rowers/views/analysisviews.py

@@ -5035,6 +5035,7 @@ def history_view_data(request,userid=0):
             ddict['hrmax'] = ddf['hr'].max().astype(int)
         except ValueError:
             ddict['hrmax'] = 0
+
         ddict['powermean'] = int(wavg(df,'power','deltat'))
         ddict['powermax'] = ddf['power'].max().astype(int)
         ddict['nrworkouts'] = a_workouts.count()