fix

rowers/interactiveplots.py

@@ -1528,7 +1528,7 @@ def interactive_forcecurve(theworkouts,workstrokesonly=True,plottype='scatter'):
     return [script,div,js_resources,css_resources]
 
 def fitnessfit_chart(workouts,user,workoutmode='water',startdate=None,
-                     enddate=None,nrdays=1):
+                     enddate=None,nrdays=20):
 
     TOOLS = 'save,pan,box_zoom,wheel_zoom,reset,tap,hover,crosshair'
 
@@ -1537,23 +1537,58 @@ def fitnessfit_chart(workouts,user,workoutmode='water',startdate=None,
     hourpower = []
 
     workouts = workouts.order_by('date')
+    data = []
 
     for w in workouts:
-        delta,cpvalue,avgpower,workoutnames = dataprep.fetchcp_new(user.rower,[w])
+        cpfile = 'media/cpdata_{id}.parquet.gz'.format(id=w.id)
-        powerdf = pd.DataFrame({
+        try:
-            'Delta':delta,
+            df = pd.read_parquet(cpfile)
-            'CP':cpvalue,
+            df['workout'] = w.id
-            'workout':workoutnames,
+            data.append(df)
-        })
+        except:
-        powerdf = powerdf[powerdf['CP']>0]
+            pass
-        powerdf.dropna(axis=0,inplace=True)
+
-        powerdf.sort_values(['Delta','CP'],ascending=[1,0],inplace=True)
+    if len(data) == 0:
-        powerdf.drop_duplicates(subset='Delta',keep='first',inplace=True)
+        return pd.Series(),pd.Series(),0,pd.Series()
-        p1,fitt,fitpower,ratio = datautils.cpfit(powerdf)
+    if len(data)>1:
-        fitfunc = lambda pars,x: abs(pars[0])/(1+(x/abs(pars[2]))) + abs(pars[1])/(1+(x/abs(pars[3])))
+        df = pd.concat(data,axis=0)
+
+    fitfunc = lambda pars,x: abs(pars[0])/(1+(x/abs(pars[2]))) + abs(pars[1])/(1+(x/abs(pars[3])))
+    errfunc = lambda pars,x,y: fitfunc(pars,x)-y
+
+    for w in workouts:
+        ids = [w.id for w in workouts.filter(date__gte=w.date-datetime.timedelta(days=nrdays),
+                                             date__lte=w.date)]
+
+        powerdf = df[df['workout'].isin(ids)]
+
+        powerdf = powerdf[powerdf['cp'] == powerdf.groupby(['delta'])['cp'].transform('max')]
+        powerdf = powerdf.sort_values(['delta']).reset_index()
+
+
+        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)
+
+
+        # p1,fitt,fitpower,ratio = datautils.cpfit(powerdf)
+        if len(powerdf['delta'])>= 4:
+            thesecs = powerdf['delta'].values
+            theavpower = powerdf['cp'].values
+
+            if thesecs.min() < 240 and thesecs.max() > 240:
+                ww = griddata(thesecs,theavpower,np.arange(239,241,1),method='linear',rescale=True)
+                powerfourmin = ww[1]
+            else:
+                powerfourmin = np.nan
+
+            if thesecs.min() < 3600 and thesecs.max() > 3600:
+                ww = griddata(thesecs,theavpower,np.arange(3599,3601,1),method='linear',rescale=True)
+                powerhour = ww[1]
+            else:
+                powerhour = np.nan
 
-        powerfourmin = fitfunc(p1,240.)
-        powerhour = fitfunc(p1,3600)
             dates.append(datetime.datetime.combine(w.date,datetime.datetime.min.time()))
             fourminpower.append(powerfourmin)
             hourpower.append(powerhour)
@@ -1564,6 +1599,7 @@ def fitnessfit_chart(workouts,user,workoutmode='water',startdate=None,
         'hourpower':hourpower,
     })
 
+
     df.sort_values(['date'],inplace=True)
 
     df['hourdup'] = df['hourpower'].shift(1)
@@ -1576,6 +1612,7 @@ def fitnessfit_chart(workouts,user,workoutmode='water',startdate=None,
 
 
 
+
     source = ColumnDataSource(
         data = dict(
             fourminpower = df['fourminpower'],
@@ -1653,7 +1690,10 @@ def fitnessfit_chart(workouts,user,workoutmode='water',startdate=None,
         ('Date','@fdate')
     ])
 
+    try:
         script,div = components(plot)
+    except:
+        return '','Insufficient Data'
 
     return [script,div]