Merge branch 'feature/goldmedals' into develop

rowers/dataprep.py

@@ -1111,6 +1111,8 @@ def calculate_goldmedalstandard(rower,workout,recurrance=True):
 
     if df.empty and recurrance:
         df, delta, cpvalues = setcp(workout,recurrance=False)
+        if df.empty:
+            return 0,0
 
     age = calculate_age(rower.birthdate,today=workout.date)
 
@@ -1209,9 +1211,15 @@ def setcp(workout,background=False,recurrance=True):
     filename = 'media/cpdata_{id}.parquet.gz'.format(id=workout.id)
 
     strokesdf = getsmallrowdata_db(['power','workoutid','time'],ids = [workout.id])
+    try:
+        if strokesdf['power'].std()==0:
+            return pd.DataFrame(),pd.Series(),pd.Series()
+    except KeyError:
+        return pd.DataFrame(),pd.Series(),pd.Series()
+    
     if background:
         job = myqueue(queuelow,handle_setcp,strokesdf,filename,workout.id)
-        return job.id
+        return pd.DataFrame({'delta':[],'cp':[]}),pd.Series(),pd.Series()
 
 
     if not strokesdf.empty:
@@ -1492,7 +1500,6 @@ def checkduplicates(r,workoutdate,workoutstartdatetime,workoutenddatetime):
         t = ww.duration
         delta = datetime.timedelta(hours=t.hour, minutes=t.minute, seconds=t.second)
         enddatetime = ww.startdatetime+delta
-        print(enddatetime,workoutstartdatetime)
         if enddatetime > workoutstartdatetime:
             ws2.append(ww)
 

rowers/interactiveplots.py

@@ -171,7 +171,7 @@ def build_goldmedalstandards(workouts,kfitness):
         else:
             goldmedalstandards.append(0)
             goldmedaldurations.append(0)
-        workoutdt.append(arrow.get(w.startdatetime).datetime)
+        workoutdt.append(arrow.get(w.date).datetime)
 
     df = pd.DataFrame({
         'workout':ids,
@@ -180,8 +180,6 @@ def build_goldmedalstandards(workouts,kfitness):
         'goldmedalduration':goldmedaldurations,
         })
 
-
-
     df.sort_values(['workoutdt'],inplace=True)
 
     #for id, row in df.iterrows():
@@ -203,6 +201,7 @@ def build_goldmedalstandards(workouts,kfitness):
         ids = [w.id for w in workouts.filter(date__gte=w.date-datetime.timedelta(days=90),
                                              date__lte=w.date)]
 
+
         powerdf = df[df['workout'].isin(ids)]
         indexmax = powerdf['goldmedalstandard'].idxmax()
         theid = powerdf.loc[indexmax,'workout']
@@ -1837,6 +1836,7 @@ def goldmedalscorechart(user,startdate=None,enddate=None):
     mask = df['testpower'].isnull()
     dates = df.mask(mask)['date'].dropna().values
     testpower = df.mask(mask)['testpower'].dropna().values
+    ids = df.mask(mask)['id'].dropna().values
 
     outids = df.mask(mask)['id'].dropna().unique()
 
@@ -1854,8 +1854,11 @@ def goldmedalscorechart(user,startdate=None,enddate=None):
     previous = 0
 
     for i in range(len(dates)):
+        id = ids[i]
+        w = Workout.objects.get(id=id)
         dd = str(dates[i])
-        td.append(arrow.get(dd).datetime)
+        #td.append(arrow.get(dd).datetime)
+        td.append(arrow.get(w.date).datetime)
         markerscore.append(testpower[i])
         markerduration.append(testduration[i])
         score.append(np.nan)
@@ -1875,6 +1878,7 @@ def goldmedalscorechart(user,startdate=None,enddate=None):
         markerduration.append(np.nan)
         duration.append(np.nan)
 
+
     df = pd.DataFrame({
         'markerscore':markerscore,
         'markerduration':markerduration,