-
Analyze your Concept2 ranking pieces over a date range and predict your pace on other pieces.
+The dashed lines are based on the + Concept2 + rankings for your age, gender + and weight category. World class means within 5% of + + World Record in terms + of power. + The percentile lines are estimates of where the percentiles + of the Concept2 rankings historically are for those of exactly + your age, gender and weight class. +
+{% endif %}| + 100m + + | +
| + 500m + + | +
| + 1000m + + | +
| + 2000m + + | +
| + 5000m + + | +
| + 6000m + + | +
| + 10000m + + | +
| + Half Marathon + + | +
| + Full Marathon + + | +
| + 1 minute + + | +
| + 4 minutes + + | +
| + 30 minutes + + | +
| + 1 hour + + | +
No ranking pieces found.
' + paulslope = 1 + paulintercept = 1 + p1 = [1,1,1,1] + message = "" + + + if request.method == 'POST' and "piece" in request.POST: + form = PredictedPieceForm(request.POST) + if form.is_valid(): + value = form.cleaned_data['value'] + hourvalue,value = divmod(value,60) + if hourvalue >= 24: + hourvalue = 23 + pieceunit = form.cleaned_data['pieceunit'] + if pieceunit == 'd': + rankingdistances.append(value) + else: + rankingdurations.append(datetime.time(minute=int(value),hour=int(hourvalue))) + else: + form = PredictedPieceForm() + + rankingdistances.sort() + rankingdurations.sort() + + + predictions = [] + cpredictions = [] + + + for rankingdistance in rankingdistances: + # Paul's model + p = paulslope*np.log10(rankingdistance)+paulintercept + velo = 500./p + t = rankingdistance/velo + pwr = 2.8*(velo**3) + a = {'distance':rankingdistance, + 'duration':timedeltaconv(t), + 'pace':timedeltaconv(p), + 'power':int(pwr)} + predictions.append(a) + + # CP model - + pwr2 = p1[0]/(1+t/p1[2]) + pwr2 += p1[1]/(1+t/p1[3]) + + if pwr2 <= 0: + pwr2 = 50. + + velo2 = (pwr2/2.8)**(1./3.) + + if np.isnan(velo2) or velo2 <= 0: + velo2 = 1.0 + + t2 = rankingdistance/velo2 + + pwr3 = p1[0]/(1+t2/p1[2]) + pwr3 += p1[1]/(1+t2/p1[3]) + + if pwr3 <= 0: + pwr3 = 50. + + velo3 = (pwr3/2.8)**(1./3.) + if np.isnan(velo3) or velo3 <= 0: + velo3 = 1.0 + + t3 = rankingdistance/velo3 + p3 = 500./velo3 + + a = {'distance':rankingdistance, + 'duration':timedeltaconv(t3), + 'pace':timedeltaconv(p3), + 'power':int(pwr3)} + cpredictions.append(a) + + + + + for rankingduration in rankingdurations: + t = 3600.*rankingduration.hour + t += 60.*rankingduration.minute + t += rankingduration.second + t += rankingduration.microsecond/1.e6 + + # Paul's model + ratio = paulintercept/paulslope + + u = ((2**(2+ratio))*(5.**(3+ratio))*t*np.log(10))/paulslope + + d = 500*t*np.log(10.) + d = d/(paulslope*lambertw(u)) + d = d.real + + velo = d/t + p = 500./velo + pwr = 2.8*(velo**3) + a = {'distance':int(d), + 'duration':timedeltaconv(t), + 'pace':timedeltaconv(p), + 'power':int(pwr)} + predictions.append(a) + + # CP model + pwr = p1[0]/(1+t/p1[2]) + pwr += p1[1]/(1+t/p1[3]) + + if pwr <= 0: + pwr = 50. + + velo = (pwr/2.8)**(1./3.) + + if np.isnan(velo) or velo <=0: + velo = 1.0 + + d = t*velo + p = 500./velo + a = {'distance':int(d), + 'duration':timedeltaconv(t), + 'pace':timedeltaconv(p), + 'power':int(pwr)} + cpredictions.append(a) + + + messages.error(request,message) + return render(request, 'rankings.html', + {'rankingworkouts':theworkouts, + 'interactiveplot':script, + 'the_div':div, + 'predictions':predictions, + 'cpredictions':cpredictions, + 'nrdata':len(thedistances), + 'form':form, + 'dateform':dateform, + 'deltaform':deltaform, + 'id': theuser, + 'theuser':uu, + 'age':age, + 'sex':r.sex, + 'weightcategory':r.weightcategory, + 'startdate':startdate, + 'enddate':enddate, + 'teams':get_my_teams(request.user), + }) + @user_passes_test(ispromember,login_url="/",redirect_field_name=None) def workout_update_cp_view(request,id=0): try: @@ -7556,7 +7920,10 @@ def workout_flexchart3_view(request,*args,**kwargs): rowdata = rdata(row.csvfilename) - additionalmetrics = rowdata.get_additional_metrics() + try: + additionalmetrics = rowdata.get_additional_metrics() + except AttributeError: + additionalmetrics = [] extrametrics = {m.replace('/','_slsh_'):m for m in additionalmetrics} @@ -10917,3 +11284,53 @@ def team_members_stats_view(request,id): }) return response + +from rowers.models import C2WorldClassAgePerformance + +def agegroupcpview(request,age,normalize=0): + script,div = interactive_agegroupcpchart(age,normalized=normalize) + + response = render(request,'agegroupcp.html', + { + 'interactiveplot':script, + 'the_div':div, + } + ) + + return response + +def agegrouprecordview(request,sex='male',weightcategory='hwt', + distance=2000,duration=None): + if not duration: + df = pd.DataFrame( + list( + C2WorldClassAgePerformance.objects.filter( + distance=distance, + sex=sex, + weightcategory=weightcategory + ).values() + ) + ) + else: + duration = int(duration)*60 + df = pd.DataFrame( + list( + C2WorldClassAgePerformance.objects.filter( + duration=duration, + sex=sex, + weightcategory=weightcategory + ).values() + ) + ) + + + script,div = interactive_agegroup_plot(df,sex=sex,distance=distance, + duration=duration, + weightcategory=weightcategory) + + return render(request, 'agegroupchart.html', + { + 'interactiveplot':script, + 'the_div':div, + }) +