better calculation of world class record

rowers/dataprep.py

@@ -1026,6 +1026,14 @@ from rowers.datautils import p0
 from rowers.utils import calculate_age
 from scipy import optimize
 
+def workout_goldmedalstandard(workout):
+    if workout.goldmedalstandard > 0:
+        return workout.goldmedalstandard
+    goldmedalstandard,goldmedalduration = fitscore(workout.user,workout)
+    workout.goldmedalstandard = goldmedalstandard
+    workout.save()
+    return goldmedalstandard
+
 def fitscore(rower,workout):
     cpfile = 'media/cpdata_{id}.parquet.gz'.format(id=workout.id)
     try:
@@ -1033,21 +1041,30 @@ def fitscore(rower,workout):
     except:
         df, delta, cpvalues = setcp(workout)
 
+    if df.empty:
+        df, delta, cpvalues = setcp(workout)
+
     age = calculate_age(rower.birthdate,today=workout.date)
+
     agerecords = CalcAgePerformance.objects.filter(
         age=age,
         sex=rower.sex,
         weightcategory = rower.weightcategory
     )
+
     wcdurations = []
     wcpower = []
+    getrecords = len(agerecords) == 0
     for record in agerecords:
-        wcdurations.append(record.duration)
-        wcpower.append(record.power)
+        if record.power > 0:
+            wcdurations.append(record.duration)
+            wcpower.append(record.power)
+        else:
+            getrecords = True
 
-    if len(agerecords)==0:
-        durations = [1,4,10,20,30,60]
-        distances = []
+    if getrecords:
+        durations = [1,4,30,60]
+        distances = [100,500,1000,2000,5000,6000,10000,21097,42195]
         df2 = pd.DataFrame(
             list(
                 C2WorldClassAgePerformance.objects.filter(
@@ -1066,12 +1083,13 @@ def fitscore(rower,workout):
     fitfunc = lambda pars,x: pars[0]/(1+(x/pars[2])) + pars[1]/(1+(x/pars[3]))
     errfunc = lambda pars,x,y: fitfunc(pars,x)-y
 
-    if len(wcdurations)>4:
+    if len(wcdurations)>=4:
         p1wc, success = optimize.leastsq(errfunc, p0[:],args=(wcdurations,wcpower))
     else:
         factor = fitfunc(p0,wcdurations.mean()/wcpower.mean())
         p1wc = [p0[0]/factor,p0[1]/factor,p0[2],p0[3]]
         success = 0
+        return 0,0
 
 
     times = df['delta']
@@ -1079,6 +1097,7 @@ def fitscore(rower,workout):
     wcpowers = fitfunc(p1wc,times)
     scores = 100.*powers/wcpowers
 
+
     try:
         indexmax = scores.idxmax()
         delta = df.loc[indexmax,'delta']
@@ -1127,7 +1146,6 @@ def setcp(workout,background=False):
         return job.id
 
 
-
     if not strokesdf.empty:
         totaltime = strokesdf['time'].max()
         try: