setcp function

rowers/dataprep.py

@@ -1026,6 +1026,22 @@ def fetchcp_new(rower,workouts):
             data.append(df)
         except OSError:
             # CP data file doesn't exist yet. has to be created
+            data.append(setcp(workout)[0])
+
+
+    if len(data) == 0:
+        return pd.Series(),pd.Series(),0
+    if len(data)>1:
+        df = pd.concat(data,axis=0)
+
+    df = df.groupby(['delta']).max()
+
+
+    df = df.sort_values(['delta']).reset_index()
+
+    return df['delta'],df['cp'],0
+
+def setcp(workout):
     strokesdf = getsmallrowdata_db(['power','workoutid','time'],ids = [workout.id])
     if not strokesdf.empty:
         totaltime = strokesdf['time'].max()
@@ -1049,20 +1065,10 @@ def fetchcp_new(rower,workouts):
                     'id':workout.id,
                 })
                 df.to_parquet(filename,engine='fastparquet',compression='GZIP')
-                        data.append(df)
+                return df,delta,cpvalues
 
+    return pd.DataFrame(),pd.Series(),pd.Series()
 
-    if len(data) == 0:
-        return pd.Series(),pd.Series(),0
-    if len(data)>1:
-        df = pd.concat(data,axis=0)
-
-    df = df.groupby(['delta']).max()
-
-
-    df = df.sort_values(['delta']).reset_index()
-
-    return df['delta'],df['cp'],0
 
 def fetchcp(rower,theworkouts,table='cpdata'):
     # get all power data from database (plus workoutid)
@@ -1482,27 +1488,8 @@ def save_workout_database(f2, r, dosmooth=True, workouttype='rower',
     isbreakthrough = False
     ishard = False
     if workouttype in rowtypes:
-        df = getsmallrowdata_db(['power', 'workoutid', 'time'], ids=[w.id])
-        try:
-            powermean = df['power'].mean()
-        except KeyError:
-            powermean = 0
-
-        if powermean != 0:
-            thesecs = totaltime
-            maxt = 1.05 * thesecs
-            if maxt > 0:
-                logarr = datautils.getlogarr(maxt)
-                dfgrouped = df.groupby(['workoutid'])
-                delta, cpvalues, avgpower = datautils.getcp(dfgrouped, logarr)
-                filename = 'media/cpdata_{id}.parquet.gz'.format(id=w.id)
-                cpdf = pd.DataFrame({
-                    'delta':delta,
-                    'cp':cpvalues,
-                    'id':w.id,
-                })
-                cpdf.to_parquet(filename,engine='fastparquet',compression='GZIP')
-
+        cpdf,delta,cpvalues = setcp(w)
+        if not cpdf.empty:
             if workouttype in otwtypes:
                 res, btvalues, res2 = utils.isbreakthrough(
                     delta, cpvalues, r.p0, r.p1, r.p2, r.p3, r.cpratio)