First version of gold medal chart

rowers/interactiveplots.py

@@ -123,6 +123,29 @@ def newtestpowerid(x):
 
     return x['id']
 
+def newtestpowerdate(x):
+    try:
+        if np.isnan(x['testpower']):
+            return np.nan
+    except (AttributeError,TypeError):
+        return np.nan
+
+    return x['date']
+
+def all_goldmedalstandards(workouts,startdate,enddate):
+    dates = []
+    testpowers = []
+    testduration = []
+
+    for w in workouts:
+        goldmedalstandard, goldmedalseconds = dataprep.workout_goldmedalstandard(w)
+        if goldmedalseconds > 60:
+            dates.append(arrow.get(w.date).datetime)
+            testpowers.append(goldmedalstandard)
+            testduration.append(goldmedalseconds)
+
+    return dates,testpowers,testduration
+
 def build_goldmedalstandards(workouts,kfitness):
     dates = []
     testpower = []
@@ -1778,6 +1801,162 @@ def getfatigues(
 
     return fatigues,fitnesses,dates,testpower,testduration,impulses
 
+def goldmedalscorechart(user,startdate=None,enddate=None):
+    # to avoid data mess later on
+    startdate = arrow.get(startdate).datetime.replace(hour=0,minute=0,second=0,microsecond=0)
+    enddate = enddate+datetime.timedelta(days=1)
+    enddate = arrow.get(enddate).datetime.replace(hour=0,minute=0,second=0,microsecond=0)
+
+    TOOLS = 'save,pan,box_zoom,wheel_zoom,reset,tap,hover,crosshair'
+
+    workouts = Workout.objects.filter(user=user.rower,date__gte=startdate,
+                                      date__lte=enddate,
+                                      workouttype__in=mytypes.rowtypes,
+                                      duplicate=False)
+
+    # marker workouts
+    dates,testpower,testduration,fatigues,fitnesses,impulses, outids = build_goldmedalstandards(
+        workouts,42
+    )
+
+    df = pd.DataFrame({
+        'date':dates,
+        'testpower':testpower,
+        'testduration':testduration,
+    })
+    df.sort_values(['date'],inplace=True)
+
+    df['testdup'] = df['testpower'].shift(1)
+    df['testpower'] = df.apply(lambda x: newtestpower(x),axis=1)
+    #df['date'] = df.apply(lambda x: newtestpowerdate(x), axis=1)
+
+    mask = df['testpower'].isnull()
+    dates = df.mask(mask)['date'].dropna().values
+    testpower = df.mask(mask)['testpower'].dropna().values
+
+    # all workouts
+    alldates,alltestpower,allduration = all_goldmedalstandards(workouts,startdate,enddate)
+
+    nrdays = (enddate-startdate).days
+
+    td = []
+    markerscore = []
+    score = []
+    markerduration = []
+    duration = []
+
+    previous = 0
+
+    for i in range(len(dates)):
+        dd = str(dates[i])
+        td.append(arrow.get(dd).datetime)
+        markerscore.append(testpower[i])
+        markerduration.append(testduration[i])
+        score.append(np.nan)
+        duration.append(np.nan)
+
+    for i in range(len(alldates)):
+        td.append(arrow.get(alldates[i]).datetime)
+        markerscore.append(np.nan)
+        score.append(alltestpower[i])
+        markerduration.append(np.nan)
+        duration.append(allduration[i])
+
+    for i in range(nrdays+1):
+        td.append(arrow.get(startdate+datetime.timedelta(days=i)).datetime)
+        markerscore.append(np.nan)
+        score.append(np.nan)
+        markerduration.append(np.nan)
+        duration.append(np.nan)
+
+    df = pd.DataFrame({
+        'markerscore':markerscore,
+        'markerduration':markerduration,
+        'score':score,
+        'duration':duration,
+        'date':td,
+    })
+
+
+    df.sort_values(['date'],inplace=True)
+
+    df = df.groupby(['date']).max()
+    df['date'] = df.index.values
+
+
+    source = ColumnDataSource(
+        data = dict(
+            markerscore = df['markerscore'],
+            score = df['score'],
+            markerduration = df['markerduration'].apply(lambda x:totaltime_sec_to_string(x,shorten=True)),
+            duration = df['duration'].apply(lambda x:totaltime_sec_to_string(x,shorten=True)),
+            date = df['date'],
+            fdate = df['date'].map(lambda x: x.strftime('%d-%m-%Y')),
+        )
+    )
+
+    plot = Figure(tools=TOOLS,x_axis_type='datetime',
+                  plot_width=900,plot_height=600,
+                  toolbar_location='above',
+                  toolbar_sticky=False)
+
+    # add watermark
+    watermarkurl = "/static/img/logo7.png"
+    watermarksource = ColumnDataSource(dict(
+        url = [watermarkurl],))
+
+    watermarkrange = Range1d(start=0,end=1)
+    watermarkalpha = 0.6
+    watermarkx = 0.99
+    watermarky = 0.01
+    watermarkw = 184
+    watermarkh = 35
+    watermarkanchor = 'bottom_right'
+    plot.extra_y_ranges = {"watermark": watermarkrange}
+    plot.extra_x_ranges = {"watermark": watermarkrange}
+
+    plot.image_url([watermarkurl],watermarkx,watermarky,
+                   watermarkw,watermarkh,
+                   global_alpha=watermarkalpha,
+                   w_units='screen',
+                   h_units='screen',
+                   anchor=watermarkanchor,
+                   dilate=True,
+                   x_range_name = "watermark",
+                   y_range_name = "watermark",
+                   )
+
+    plot.xaxis.axis_label = 'Date'
+    plot.yaxis.axis_label = 'Gold Medal Score'
+
+    plot.circle('date','score',source=source,fill_color='blue',
+                size=10,
+                legend_label='Workouts')
+
+    plot.circle('date','markerscore',source=source,fill_color='red',
+                size=10,
+                legend_label='Marker Workouts')
+
+    plot.legend.location = "top_left"
+
+    plot.x_range = Range1d(
+        startdate,enddate+datetime.timedelta(days=5),
+    )
+
+    hover = plot.select(dict(type=HoverTool))
+
+    hover.tooltips = OrderedDict([
+        ('Marker','@markerscore{int}'),
+        ('Test', '@markerduration'),
+        ('Score','@score{int}'),
+        ('Duration', '@duration'),
+        ('Date','@fdate'),
+    ])
+
+    script, div = components(plot)
+
+    return script, div
+
 def performance_chart(user,startdate=None,enddate=None,kfitness=42,kfatigue=7,
                       metricchoice='trimp',doform=False,dofatigue=False,
                       showtests=False):