differnt way of calculating, adding tsb model
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@@ -743,7 +743,7 @@ class FitnessFitForm(forms.Form):
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initial='rscore',
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label='Workload Metric')
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modelchoices = forms.ChoiceField(required=True,
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modelchoice = forms.ChoiceField(required=True,
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choices=modelchoices,
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initial='tsb',
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label='Model to use')
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@@ -1530,7 +1530,8 @@ def interactive_forcecurve(theworkouts,workstrokesonly=True,plottype='scatter'):
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def fitnessfit_chart(workouts,user,workoutmode='water',startdate=None,
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enddate=None,kfitness=42,kfatigue=7,fitnesstest=20,
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metricchoice='rscore',
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k1=1,k2=1,p0=100):
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k1=1,k2=1,p0=100,
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modelchoice='tsb'):
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TOOLS = 'save,pan,box_zoom,wheel_zoom,reset,tap,hover,crosshair'
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@@ -1598,10 +1599,7 @@ def fitnessfit_chart(workouts,user,workoutmode='water',startdate=None,
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fitnesses.append(np.nan)
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allworkouts = Workout.objects.filter(user=user.rower,date__lte=enddate,
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date__gte=startdate,
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duplicate=False,
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)
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df = pd.DataFrame({
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'date':dates,
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@@ -1613,9 +1611,13 @@ def fitnessfit_chart(workouts,user,workoutmode='water',startdate=None,
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df['testdup'] = df['testpower'].shift(1)
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df['testpower'] = df.apply(lambda x: np.nan if abs(x['testpower'] - x['testdup']) < 4 \
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df['testpower'] = df.apply(lambda x: np.nan if abs(x['testpower'] - x['testdup']) < 1 \
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else x['testpower'],axis=1)
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df['testpower'].iloc[-1] = df['testdup'].iloc[-1]
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dates = [d for d in df['date']]
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testpower = df['testpower'].values.tolist()
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fatigues = df['fatigue'].values.tolist()
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@@ -1623,28 +1625,28 @@ def fitnessfit_chart(workouts,user,workoutmode='water',startdate=None,
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for w in allworkouts:
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# create Fitness and Fatigue number
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fatigue = 0
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fitness = 0
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previousworkouts = Workout.objects.filter(user=user.rower,date__lte=w.date,
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date__gte=startdate,
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duplicate=False)
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for ww in previousworkouts:
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delta = (w.date-ww.date).days
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weight = getattr(ww,metricchoice)
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fatigue += weight*math.exp(-delta/kfatigue)
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fitness += weight*math.exp(-delta/kfitness)
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fatigue = 0
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fitness = 0
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lambda_a = 2/(kfatigue+1)
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lambda_c = 2/(kfitness+1)
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nrdays = (enddate-startdate).days
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for i in range(nrdays):
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date = startdate+datetime.timedelta(days=i)
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ws = Workout.objects.filter(user=user.rower,date=date,duplicate=False)
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weight = 0
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for w in ws:
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weight += getattr(w,metricchoice)
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if modelchoice == 'tsb':
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fatigue = (1-lambda_a)*fatigue+weight*lambda_a
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fitness = (1-lambda_c)*fitness+weight*lambda_c
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else:
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fatigue = fatigue*math.exp(-1./kfatigue) + weight
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fitness = fitness*math.exp(-1./kfitness) + weight
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fatigues.append(fatigue)
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fitnesses.append(fitness)
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dates.append(datetime.datetime.combine(date,datetime.datetime.min.time()))
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testpower.append(np.nan)
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dates.append(
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datetime.datetime.combine(
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w.date,datetime.datetime.min.time())
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)
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df = pd.DataFrame({
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@@ -1654,8 +1656,13 @@ def fitnessfit_chart(workouts,user,workoutmode='water',startdate=None,
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'fitness':fitnesses,
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})
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df['fatigue'] = k2*df['fatigue']
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df['fitness'] = p0+k1*df['fitness']
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if modelchoice == 'banister':
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df['fatigue'] = k2*df['fatigue']
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df['fitness'] = p0+k1*df['fitness']
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df['form'] = df['fitness']-df['fatigue']
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@@ -1713,19 +1720,37 @@ def fitnessfit_chart(workouts,user,workoutmode='water',startdate=None,
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y_range_name = "watermark",
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)
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if modelchoice == 'banister':
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fitlabel = 'PTE (fitness)'
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fatiguelabel = 'NTE (fatigue)'
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formlabel = 'Performance'
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else:
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fitlabel = 'CTL'
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fatiguelabel = 'ATL'
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formlabel = 'TSB'
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plot.circle('date','testpower',source=source,fill_color='green',size=10,
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legend_label='{fitnesstest} min power'.format(fitnesstest=fitnesstest))
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plot.line('date','fitness',source=source,color='yellow',
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legend_label='fitness')
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plot.line('date','fatigue',source=source,color='red',
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legend_label='fatigue')
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plot.line('date','form',source=source,color='green',
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legend_label='form')
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plot.xaxis.axis_label = 'Date'
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plot.yaxis.axis_label = 'Power (W)'
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y2rangemin = df.loc[:,['fitness','fatigue','form']].min().min()
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y2rangemax = df.loc[:,['fitness','fatigue','form']].max().max()
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plot.extra_y_ranges["yax2"] = Range1d(start=y2rangemin,end=y2rangemax)
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plot.add_layout(LinearAxis(y_range_name="yax2",axis_label="Score"),"right")
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plot.line('date','fitness',source=source,color='blue',
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legend_label=fitlabel,y_range_name="yax2")
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plot.line('date','fatigue',source=source,color='red',
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legend_label=fatiguelabel,y_range_name="yax2")
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plot.line('date','form',source=source,color='green',
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legend_label=formlabel,y_range_name="yax2")
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plot.legend.location = "top_left"
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plot.xaxis.formatter = DatetimeTickFormatter(
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@@ -1556,6 +1556,7 @@ def fitness_from_cp_view(request,userid=0,mode='rower',
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kfatigue = 7
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fitnesstest = 20
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metricchoice = 'rscore'
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modelchoice = 'tsb'
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# temp fit parameters
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k1 = 1
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@@ -1576,6 +1577,7 @@ def fitness_from_cp_view(request,userid=0,mode='rower',
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k1 = form.cleaned_data['k1']
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k2 = form.cleaned_data['k2']
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p0 = form.cleaned_data['p0']
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modelchoice = form.cleaned_data['modelchoice']
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else:
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form = FitnessFitForm()
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@@ -1598,7 +1600,8 @@ def fitness_from_cp_view(request,userid=0,mode='rower',
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kfatigue=kfatigue,
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fitnesstest=fitnesstest,
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metricchoice=metricchoice,
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k1=k1,k2=k2,p0=p0
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k1=k1,k2=k2,p0=p0,
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modelchoice=modelchoice,
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)
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breadcrumbs = [
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