using upper limit for OTW breakthrough detection
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@@ -428,7 +428,7 @@ def save_workout_database(f2,r,dosmooth=True,workouttype='rower',
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isbreakthrough = False
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if workouttype == 'water':
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delta,cpvalues,avgpower = datautils.getsinglecp(row.df)
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if utils.isbreakthrough(delta,cpvalues,r.p0,r.p1,r.p2,r.p3):
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if utils.isbreakthrough(delta,cpvalues,r.p0,r.p1,r.p2,r.p3,r.cpratio):
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isbreakthrough = True
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res = datautils.updatecp(delta,cpvalues,r)
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@@ -27,6 +27,7 @@ def updatecp(delta,cpvalues,r):
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r.p1 = p1[1]
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r.p2 = p1[2]
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r.p3 = p1[3]
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r.cpratio = res[3]
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r.save()
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@@ -131,7 +131,7 @@ class PredictedPieceForm(forms.Form):
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)
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pieceunit = forms.ChoiceField(required=True,choices=unitchoices,
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initial='t',label='Unit')
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value = forms.IntegerField(initial=10,label='Value')
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value = forms.FloatField(initial=10,label='Value')
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class Meta:
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fields = ['value','pieceunit']
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@@ -687,7 +687,7 @@ def interactive_otwcpchart(powerdf,promember=0):
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script, div = components(plot)
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return [script,div,p1,message]
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return [script,div,p1,ratio,message]
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def interactive_cpchart(thedistances,thesecs,theavpower,
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theworkouts,promember=0):
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@@ -178,6 +178,7 @@ class Rower(models.Model):
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p1 = models.FloatField(default=1.0,verbose_name="CP p2")
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p2 = models.FloatField(default=1.0,verbose_name="CP p3")
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p3 = models.FloatField(default=1.0,verbose_name="CP p4")
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cpratio = models.FloatField(default=1.0,verbose_name="CP fit ratio")
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otwslack = models.IntegerField(default=0,verbose_name="OTW Power slack")
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@@ -164,14 +164,15 @@
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<thead>
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<tr>
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<th> Duration</th>
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<th> Power </th>
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<th> Power (upper)</th>
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<th> Power</th>
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<tr>
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</thead>
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<tbody>
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{% for pred in cpredictions %}
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<tr>
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{% for key, value in pred.items %}
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{% if key == "power" %}
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{% if key == "power" or key == "upper" %}
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<td> {{ value }} W </td>
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{% endif %}
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{% if key == "duration" %}
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@@ -76,11 +76,13 @@ def geo_distance(lat1,lon1,lat2,lon2):
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return [distance,bearing]
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def isbreakthrough(delta,cpvalues,p0,p1,p2,p3):
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def isbreakthrough(delta,cpvalues,p0,p1,p2,p3,ratio):
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pwr = p0/(1+delta/p2)
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pwr += p1/(1+delta/p3)
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pwr *= ratio
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res = np.sum(cpvalues>pwr)
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return res>1
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@@ -2955,14 +2955,16 @@ def otwrankings_view(request,theuser=0,
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script = res[0]
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div = res[1]
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p1 = res[2]
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ratio = res[3]
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r.p0 = p1[0]
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r.p1 = p1[1]
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r.p2 = p1[2]
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r.p3 = p1[3]
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r.cpratio = ratio
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r.save()
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paulslope = 1
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paulintercept = 1
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message = res[3]
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message = res[4]
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else:
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script = ''
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div = '<p>No ranking pieces found.</p>'
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@@ -2977,18 +2979,20 @@ def otwrankings_view(request,theuser=0,
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clean = form.is_valid()
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value = form.cleaned_data['value']
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hourvalue,value = divmod(value,60)
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hourvalue = int(hourvalue)
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minutevalue = int(value)
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value = int(60*(value-minutevalue))
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if hourvalue >= 24:
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hourvalue = 23
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rankingdurations.append(datetime.time(minute=value,hour=hourvalue))
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rankingdurations.append(datetime.time(minute=minutevalue,
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hour=hourvalue,
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second=value))
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else:
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form = PredictedPieceForm()
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predictions = []
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cpredictions = []
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for rankingduration in rankingdurations:
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t = 3600.*rankingduration.hour
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t += 60.*rankingduration.minute
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@@ -3000,13 +3004,17 @@ def otwrankings_view(request,theuser=0,
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pwr = p1[0]/(1+t/p1[2])
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pwr += p1[1]/(1+t/p1[3])
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if pwr <= 0:
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pwr = 50.
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if not np.isnan(pwr):
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pwr2 = pwr*ratio
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a = {
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'duration':timedeltaconv(t),
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'power':int(pwr)}
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'power':int(pwr),
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'upper':int(pwr2)}
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cpredictions.append(a)
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@@ -3017,7 +3025,6 @@ def otwrankings_view(request,theuser=0,
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{'rankingworkouts':theworkouts,
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'interactiveplot':script,
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'the_div':div,
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'predictions':predictions,
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'cpredictions':cpredictions,
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'avgpower':avgpower,
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'form':form,
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