simple performance chart
This commit is contained in:
Sander Roosendaal
@@ -1631,6 +1631,238 @@ def interactive_forcecurve(theworkouts,workstrokesonly=True,plottype='scatter'):
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return [script,div,js_resources,css_resources]
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def getfatigues(
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fatigues,fitnesses,dates,testpower,
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startdate,enddate,user,metricchoice,kfatigue,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 getattr(w,metricchoice) == 0:
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if metricchoice == 'rscore' and w.hrtss != 0:
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weight+= w.hrtss
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else:
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trimp,hrtss = dataprep.workout_trimp(w)
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rscore,normp = dataprep.workout_rscore(w)
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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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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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return fatigues,fitnesses,dates,testpower
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def performance_chart(user,startdate=None,enddate=None,kfitness=42,kfatigue=7,
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metricchoice='trimp',doform=False,dofatigue=False):
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TOOLS = 'save,pan,box_zoom,wheel_zoom,reset,tap,hover,crosshair'
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fatigues = []
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fitnesses = []
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dates = []
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testpower = []
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modelchoice = 'coggan'
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p0 = 0
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k1 = 1
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k2 = 1
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fatigues,fitnesses,dates,testpower = getfatigues(fatigues,
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fitnesses,
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dates,
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testpower,
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startdate,enddate,
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user,metricchoice,
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kfatigue,kfitness)
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df = pd.DataFrame({
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'date':dates,
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'testpower':testpower,
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'fatigue':fatigues,
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'fitness':fitnesses,
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})
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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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df.sort_values(['date'],inplace=True)
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df = df.groupby(['date']).max()
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df['date'] = df.index.values
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source = ColumnDataSource(
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data = dict(
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testpower = df['testpower'],
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date = df['date'],
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fdate = df['date'].map(lambda x: x.strftime('%d-%m-%Y')),
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fitness = df['fitness'],
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fatigue = df['fatigue'],
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form = df['form'],
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)
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)
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plot = Figure(tools=TOOLS,x_axis_type='datetime',
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plot_width=900,
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toolbar_location="above",
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toolbar_sticky=False)
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# add watermark
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watermarkurl = "/static/img/logo7.png"
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watermarksource = ColumnDataSource(dict(
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url = [watermarkurl],))
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watermarkrange = Range1d(start=0,end=1)
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watermarkalpha = 0.6
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watermarkx = 0.99
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watermarky = 0.01
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watermarkw = 184
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watermarkh = 35
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watermarkanchor = 'bottom_right'
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plot.extra_y_ranges = {"watermark": watermarkrange}
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plot.extra_x_ranges = {"watermark": watermarkrange}
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plot.image_url([watermarkurl],watermarkx,watermarky,
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watermarkw,watermarkh,
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global_alpha=watermarkalpha,
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w_units='screen',
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h_units='screen',
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anchor=watermarkanchor,
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dilate=True,
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x_range_name = "watermark",
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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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rightaxlabel = 'NTE'
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if doform:
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yaxlabel = 'PTE/Performance'
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else:
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yaxlabel = 'PTE'
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else:
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fitlabel = 'Fitness'
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fatiguelabel = 'Fatigue'
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formlabel = 'Freshness'
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rightaxlabel = 'Fatigue'
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if doform:
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yaxlabel = 'Fitness/Freshness'
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else:
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yaxlabel = 'Fitness'
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#plot.circle('date','testpower',source=source,fill_color='green',size=10,
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# legend_label=legend_label.format(fitnesstest=fitnesstest))
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plot.xaxis.axis_label = 'Date'
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plot.yaxis.axis_label = yaxlabel
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y2rangemin = df.loc[:,['form']].min().min()
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y2rangemax = df.loc[:,['form']].max().max()
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if dofatigue:
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y1rangemin = df.loc[:,['fitness','fatigue']].min().min()
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y1rangemax = df.loc[:,['fitness','fatigue']].max().max()
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else:
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y1rangemin = df.loc[:,['fitness']].min().min()
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y1rangemax = df.loc[:,['fitness']].max().max()
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if doform:
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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=rightaxlabel),"right")
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plot.line('date','fitness',source=source,color='blue',
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legend_label=fitlabel)
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band = Band(base='date', upper='fitness', source=source, level='underlay',
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fill_alpha=0.2, fill_color='blue')
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plot.add_layout(band)
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if dofatigue:
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plot.line('date','fatigue',source=source,color='red',
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legend_label=fatiguelabel)
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if doform:
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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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days=["%d %B %Y"],
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months=["%d %B %Y"],
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years=["%d %B %Y"],
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)
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plot.xaxis.major_label_orientation = pi/4
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plot.sizing_mode = 'stretch_both'
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#plot.y_range = Range1d(0,1.5*max(df['testpower']))
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startdate = datetime.datetime.combine(startdate,datetime.datetime.min.time())
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enddate = datetime.datetime.combine(enddate,datetime.datetime.min.time())
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plot.x_range = Range1d(
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startdate,enddate+datetime.timedelta(days=5),
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)
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plot.y_range = Range1d(
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start=0,end=y1rangemax,
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)
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plot.title.text = 'Performance Manager '+user.first_name
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hover = plot.select(dict(type=HoverTool))
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hover.tooltips = OrderedDict([
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#(legend_label,'@testpower'),
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('Date','@fdate'),
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(fitlabel,'@fitness'),
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(fatiguelabel,'@fatigue'),
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(formlabel,'@form')
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])
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try:
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script,div = components(plot)
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except Exception as e:
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df.dropna(inplace=True,axis=0,how='any')
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return (
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'',
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'Something went wrong with the chart ({nrworkouts} workouts, {nrdata} datapoints, error {e})'.format(
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nrworkouts = workouts.count(),
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nrdata = len(df),
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e = e,
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)
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)
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return [script,div]
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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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@@ -1681,34 +1913,10 @@ def fitnessfit_chart(workouts,user,workoutmode='water',startdate=None,
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fatigues = df['fatigue'].values.tolist()
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fitnesses = df['fitness'].values.tolist()
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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 getattr(w,metricchoice) == 0:
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if metricchoice == 'rscore' and w.hrtss != 0:
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weight+= w.hrtss
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else:
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trimp,hrtss = dataprep.workout_trimp(w)
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rscore,normp = dataprep.workout_rscore(w)
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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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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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fatigues,fitnesses,dates,testpower = getfatigues(
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fatigues,fitnesses,dates,testpower,
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startdate,enddate,user,metricchoice,kfatigue,kfitness
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)
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df = pd.DataFrame({
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