Doing saves

rowers/dataprep.py

@@ -1506,9 +1506,70 @@ def save_workout_database(f2, r, dosmooth=True, workouttype='rower',
                 if workouttype in otwtypes:
                     res, btvalues, res2 = utils.isbreakthrough(
                         delta, cpvalues, r.p0, r.p1, r.p2, r.p3, r.cpratio)
+                    cprange = r.cprange
+                    firstdate = datetime.date.today()-datetime.timedelta(days=cprange)
+
+                    workouts = Workout.objects.filter(
+                        date__gte=firstdate,
+                        workouttype__in=otwtypes,
+                    )
+
+                    dd,cpcp,avgpower = fetchcp_new(r,workouts)
+
+                    powerdf = pd.DataFrame({
+                        'Delta':dd,
+                        'CP':cpcp,
+                    })
+
+                    if powerdf.empty:
+                        return('','<p>No valid data found</p>')
+
+                    powerdf = powerdf[powerdf['CP']>0]
+                    powerdf.dropna(axis=0,inplace=True)
+                    powerdf.sort_values(['Delta','CP'],ascending=[1,0],inplace=True)
+                    powerdf.drop_duplicates(subset='Delta',keep='first',inplace=True)
+
+                    res = datautils.cpfit(powerdf)
+                    if len(powerdf) != 0:
+                        p1 = res[0]
+                        r.p0 = p1[0]
+                        r.p1 = p1[1]
+                        r.p2 = p1[2]
+                        r.p3 = p1[3]
+                        r.cpratio = res[3]
+                        r.save()
+
                 elif workouttype in otetypes:
                     res, btvalues, res2 = utils.isbreakthrough(
                         delta, cpvalues, r.ep0, r.ep1, r.ep2, r.ep3, r.ecpratio)
+                    cprange = r.cprange
+                    firstdate = datetime.date.today()-datetime.timedelta(days=cprange)
+                    workouts = Workout.objects.filter(
+                        date__gte=firstdate,
+                        workouttype__in=otetypes,
+                    )
+                    dd,cpcp,avgpower = fetchcp_new(r,workouts)
+                    powerdf = pd.DataFrame({
+                        'Delta':dd,
+                        'CP':cpcp,
+                    })
+                    if powerdf.empty:
+                        return('','<p>No valid data found</p>')
+
+                    powerdf = powerdf[powerdf['CP']>0]
+                    powerdf.dropna(axis=0,inplace=True)
+                    powerdf.sort_values(['Delta','CP'],ascending=[1,0],inplace=True)
+                    powerdf.drop_duplicates(subset='Delta',keep='first',inplace=True)
+                    res = datautils.cpfit(powerdf)
+                    if len(powerdf) != 0:
+                        res = datautils.cpfit(powerdf)
+                        p1 = res[0]
+                        r.ep0 = p1[0]
+                        r.ep1 = p1[1]
+                        r.ep2 = p1[2]
+                        r.ep3 = p1[3]
+                        r.ecpratio = res[3]
+                        r.save()
             else:
                 res = 0
                 res2 = 0
@@ -1764,7 +1825,7 @@ def new_workout_from_file(r, f2,
     # for me to check if it is a bug, or a new file type
     # worth supporting
     if fileformat == 'gpx':
-        print('aap')
+
         os.remove(f2)
         message = "GPX files support is on our roadmap. Check back soon."
         return (0, message, f2)
@@ -2624,7 +2685,7 @@ def fix_newtons(id=0, limit=3000):
         peakforce = rowdata['peakforce']
         if peakforce.mean() > limit:
             w = Workout.objects.get(id=id)
-            print("fixing ", id)
+
             rowdata = rdata(w.csvfilename)
             if rowdata and len(rowdata.df):
                 update_strokedata(w.id, rowdata.df)