correcting bugs in gold medal score

rowers/interactiveplots.py

@@ -144,6 +144,7 @@ def all_goldmedalstandards(workouts,startdate,enddate):
     dates = []
     testpowers = []
     testduration = []
+    ids = []
 
     for w in workouts:
         goldmedalstandard, goldmedalseconds = dataprep.workout_goldmedalstandard(w)
@@ -151,8 +152,9 @@ def all_goldmedalstandards(workouts,startdate,enddate):
             dates.append(arrow.get(w.date).datetime)
             testpowers.append(goldmedalstandard)
             testduration.append(goldmedalseconds)
+            ids.append(w.id)
 
-    return dates,testpowers,testduration
+    return dates,testpowers,testduration,ids
 
 def build_goldmedalstandards(workouts,kfitness):
     dates = []
@@ -1831,8 +1833,8 @@ def goldmedalscorechart(user,startdate=None,enddate=None):
     outids = df.mask(mask)['id'].dropna().unique()
 
     # all workouts
-    alldates,alltestpower,allduration = all_goldmedalstandards(workouts,startdate,enddate)
+    alldates,alltestpower,allduration,allids = all_goldmedalstandards(workouts,startdate,enddate)
-    allids = [w.id for w in workouts]
+    
 
     nrdays = (enddate-startdate).days
 
@@ -1853,8 +1855,8 @@ def goldmedalscorechart(user,startdate=None,enddate=None):
         td.append(arrow.get(w.date).datetime)
         markerscore.append(testpower[i])
         markerduration.append(testduration[i])
-        score.append(np.nan)
+        score.append(testpower[i])
-        duration.append(np.nan)
+        duration.append(testduration[i])
         workoutid.append(id)
 
     for i in range(len(alldates)):
@@ -1883,14 +1885,19 @@ def goldmedalscorechart(user,startdate=None,enddate=None):
         'id':workoutid,
     })
 
+    df['url'] = df['id'].apply(lambda x:settings.SITE_URL+'/rowers/workout/{id}/'.format(id=encoder.encode_hex(x)))
+    df['workout'] = df['id'].apply(lambda x:workoutname(x))
+
 
     df.sort_values(['date'],inplace=True)
 
-    df = df.groupby(['date']).max()
+    # find index values where score is max
-    df['date'] = df.index.values
+    idx = df.groupby(['date'])['score'].transform(max) == df['score']
+    df = df[idx]
+
+    #df = df.groupby(['date']).max()
+    #df['date'] = df.index.values
 
-    df['url'] = df['id'].apply(lambda x:settings.SITE_URL+'/rowers/workout/{id}/'.format(id=encoder.encode_hex(x)))
-    df['workout'] = df['id'].apply(lambda x:workoutname(x))
 
 
     source = ColumnDataSource(

rowers/templates/analysis.html

@@ -98,14 +98,15 @@
     </p>
   </li>
   <li class="rounder">
-    <h2>Power Progress</h2>
+    <h2>Marker Workouts</h2>
-      <a href="/rowers/fitness-progress/">
+      <a href="/rowers/goldmedalscores/">
       <div class="vignet">
-        <img src="/static/img/powerprogress.png" alt="Power Progress">
+        <img src="/static/img/goldmedalscores.png" alt="Gold Medal Scores">
       </div>
       </a>
     <p>
-      Monitoring power duration evidence from all your workouts. Feel free to explore.
+      See which of your workouts are markers of your fitness, and how your scores
+			evolve over time.
     </p>
   </li>
   <li class="rounder">