fitness-fit has now right algo

rowers/interactiveplots.py

@@ -25,6 +25,8 @@ import itertools
 from bokeh.plotting import figure, ColumnDataSource, Figure,curdoc
 from bokeh.models import CustomJS,Slider, TextInput,BoxAnnotation, Band
 
+import arrow
+
 from rowers.utils import myqueue, totaltime_sec_to_string
 import django_rq
 queue = django_rq.get_queue('default')
@@ -102,6 +104,16 @@ import rowers.datautils as datautils
 
 from pandas.core.groupby.groupby import DataError
 
+def newtestpower(x):
+    try:
+        if abs(x['testpower'] - x['testdup']) < 1:
+            return np.nan
+    except (AttributeError,TypeError):
+        return np.nan
+
+
+    return x['testpower']
+
 def build_goldmedalstandards(workouts,kfitness):
     dates = []
     testpower = []
@@ -113,20 +125,48 @@ def build_goldmedalstandards(workouts,kfitness):
     goldmedalstandards = []
     goldmedaldurations = []
     ids = []
+    workoutdt = []
     for w in workouts:
         goldmedalstandard,goldmedalseconds = dataprep.workout_goldmedalstandard(w)
         ids.append(w.id)
-        goldmedalstandards.append(goldmedalstandard)
-        goldmedaldurations.append(goldmedalseconds)
+        if w.workouttype in mytypes.otwtypes:
+            goldmedalstandard = goldmedalstandard / (1.-w.user.otwslack/100.)
+        if goldmedalseconds > 60:
+            goldmedalstandards.append(goldmedalstandard)
+            goldmedaldurations.append(goldmedalseconds)
+        else:
+            goldmedalstandards.append(0)
+            goldmedaldurations.append(0)
+        workoutdt.append(arrow.get(w.startdatetime).datetime)
 
     df = pd.DataFrame({
         'workout':ids,
+        'workoutdt': workoutdt,
         'goldmedalstandard':goldmedalstandards,
         'goldmedalduration':goldmedaldurations,
         })
 
+
+
+    df.sort_values(['workoutdt'],inplace=True)
+
+    #for id, row in df.iterrows():
+    #    d = row['workoutdt']
+    #    dd = d-datetime.timedelta(days=90)
+    #    mask = df['workoutdt']>dd
+    #    mask2 = df['workoutdt']<=d
+    #    df2 = df.where(mask & mask2)
+    #    powertest = df2['goldmedalstandard'].max()
+    #    idx = df2['goldmedalstandard'].argmax()
+    #    durationtest = df2['goldmedalduration'].values[idx]
+    #    dates.append(d)
+    #    testpower.append(powertest)
+    #    testduration.append(durationtest)
+    #    fatigues.append(np.nan)
+    #    fitnesses.append(np.nan)
+
     for w in workouts:
-        ids = [w.id for w in workouts.filter(date__gte=w.date-datetime.timedelta(days=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)]
@@ -134,9 +174,14 @@ def build_goldmedalstandards(workouts,kfitness):
         powertest = powerdf['goldmedalstandard'].max()
         durationtest = powerdf.loc[indexmax,'goldmedalduration']
 
-        dates.append(datetime.datetime.combine(w.date,datetime.datetime.min.time()))
-        testpower.append(powertest)
-        testduration.append(durationtest)
+
+        dates.append(arrow.get(w.date).datetime)
+        if powertest > 0:
+            testpower.append(powertest)
+            testduration.append(durationtest)
+        else:
+            testpower.append(np.nan)
+            testduration.append(np.nan)
 
         fatigues.append(np.nan)
         fitnesses.append(np.nan)
@@ -156,7 +201,7 @@ def get_testpower(workouts,fitnesstestsecs,kfitness):
         try:
             df = pd.read_parquet(cpfile)
             df['workout'] = w.id
-            df['workoutdate'] = w.date.strftime('%d-%m-%Y')
+            df['workoutdate'] = arrow.get(w.date.strftime('%d-%m-%Y')).datetime
             data.append(df)
         except:
             strokesdf = dataprep.getsmallrowdata_db(['power','workoutid','time'],ids=[w.id])
@@ -203,7 +248,7 @@ def get_testpower(workouts,fitnesstestsecs,kfitness):
 
 
 
-            dates.append(datetime.datetime.combine(w.date,datetime.datetime.min.time()))
+            dates.append(arrow.get(w.date).datetime)
             testpower.append(powertest)
             testduration.append(fitnesstestsecs)
             fatigues.append(np.nan)
@@ -1710,7 +1755,7 @@ def getfatigues(
 
         fatigues.append(fatigue)
         fitnesses.append(fitness)
-        dates.append(datetime.datetime.combine(date,datetime.datetime.min.time()))
+        dates.append(arrow.get(date).datetime)
         testpower.append(np.nan)
         testduration.append(np.nan)
 
@@ -1978,8 +2023,7 @@ def fitnessfit_chart(workouts,user,workoutmode='water',startdate=None,
 
 
     df['testdup'] = df['testpower'].shift(1)
-    df['testpower'] = df.apply(lambda x: np.nan if abs(x['testpower'] - x['testdup']) < 1 \
-                               else x['testpower'],axis=1)
+    df['testpower'] = df.apply(lambda x: newtestpower(x),axis=1)
 
     try:
         df['testpower'].iloc[-1] = df['testdup'].iloc[-1]

rowers/views/analysisviews.py

@@ -1678,13 +1678,9 @@ def fitness_from_cp_view(request,userid=0,mode='rower',
 
     workouts = Workout.objects.filter(user=therower,date__gte=startdate,
                                       date__lte=enddate,
-                                      workouttype__in=mytypes.otwtypes,
+                                      workouttype__in=mytypes.rowtypes,
                                       duplicate=False)
-    if mode == 'rower':
-        workouts = Workout.objects.filter(user=therower,date__gte=startdate,
-                                          date__lte=enddate,workouttype__in=mytypes.otetypes,
-                                          duplicate=False)
-
+    
 
 
     script,thediv = fitnessfit_chart(