central rscore approx

rowers/datautils.py

@@ -32,6 +32,7 @@ def rscore_approx(row):
         else:
             dd = 3600*row['duration'].hour+60*row['duration'].minute+row['duration'].second
             dd = dd/3600
+            print(row['rpe'],dd,rpetotss[row['rpe']])
             return rpetotss[row['rpe']]*dd
     if row['rscore'] < 0:
         w = Workout.objects.get(id=row['id'])
@@ -41,7 +42,11 @@ def rscore_approx(row):
             dd = 3600*row['duration'].hour+60*row['duration'].minute+row['duration'].second
             dd = dd/3600
             return rpetotss[row['rpe']]*dd
+        else:  # pragma: no cover
+            minutes = row['duration'].hour*60+row['duration'].minute
+            return minutes
 
+    print('boer')
     return 0
 
 def updatecp(delta, cpvalues, r, workouttype='water'):  # pragma: no cover

rowers/interactiveplots.py

@@ -1507,21 +1507,8 @@ def weightfromrecord(row,metricchoice):
     vv = row[metricchoice]
     if vv > 0:
         return vv
-    if vv == 0:
-        if metricchoice == 'rscore' and row['hrtss'] > 0:  # pragma: no cover
-            return row['hrtss']
-        else:
-            dd = 3600*row['duration'].hour+60*row['duration'].minute+row['duration'].second
-            dd = dd/3600
-            return rpetotss[row['rpe']]*dd
-    if vv < 0:
-        w = Workout.objects.get(id=row['id'])
-        trimp, hrtss = dataprep.workout_trimp(w)
-        rscore, normp = dataprep.workout_rscore(w)
-        if row['rpe'] and row['rpe'] > 0:  # pragma: no cover
-            dd = 3600*row['duration'].hour+60*row['duration'].minute+row['duration'].second
-            dd = dd/3600
-            return rpetotss[row['rpe']]*dd
+    if metricchoice == 'rscore':
+        return rscore_approx(row)
 
     return 0
 

rowers/plannedsessions.py

@@ -257,13 +257,16 @@ def get_execution_report(rower, startdate, enddate, plan=None):
             plannedsession=None,
             date__gte=mm.startdate, date__lte=mm.enddate).exclude(duplicate=True)
         for w in unmatchedworkouts:
-            if w.rscore != 0:
-                actualscore += w.rscore
-            elif w.hrtss != 0:  # pragma: no cover
-                actualscore += w.hrtss
-            else:  # pragma: no cover
-                minutes = w.duration.hour*60+w.duration.minute
-                actualscore += minutes
+            row = {
+                'rscore': w.rscore,
+                'hrtss': w.hrtss,
+                'rpe': w.rpe,
+                'duration': w.duration,
+                'id': w.id
+            }
+            rscore = datautils.rscore_approx(row)
+            actualscore += rscore
+
         for ps in sps:  # pragma: no cover
             ratio, status, cdate = is_session_complete(rower, ps)
             if ps.sessionmode == 'rScore':
@@ -576,11 +579,15 @@ def get_session_metrics(ps):
                 durationv += timefield_to_seconds_duration(w.duration)
                 thetrimp, hrtss = dataprep.workout_trimp(w)
                 trimpv += thetrimp
-                tss = dataprep.workout_rscore(w)[0]
-                if not np.isnan(tss) and tss != 0:
-                    rscorev += tss
-                elif tss == 0:  # pragma: no cover
-                    rscorev += hrtss
+                row = {
+                    'rscore': w.rscore,
+                    'hrtss': w.hrtss,
+                    'rpe': w.rpe,
+                    'duration': w.duration,
+                    'id': w.id
+                }
+                tss = datautils.rscore_approx(row)
+                rscorev += tss
 
             ratio, statusv, completiondate = is_session_complete_ws(ws, ps)
             try:
@@ -674,13 +681,15 @@ def is_session_complete_ws(ws, ps):
             trimp, hrtss = dataprep.workout_trimp(w)
             score += trimp
         elif ps.sessionmode == 'rScore':
-            rscore = dataprep.workout_rscore(w)[0]
-            if not np.isnan(rscore) and rscore != 0:
-                score += rscore
-            elif rscore == 0:  # pragma: no cover
-                trimp, hrtss = dataprep.workout_trimp(w)
-                score += hrtss
-
+            row = {
+                'rscore': w.rscore,
+                'hrtss': w.hrtss,
+                'rpe': w.rpe,
+                'duration': w.duration,
+                'id': w.id
+            }
+            rscore = datautils.rscore_approx(row)
+            score += rscore
         if not completiondate and score >= cratiomin*value:
             completiondate = w.date