Merge branch 'feature/duplicatesprivate' into develop
This commit is contained in:
Sander Roosendaal
+11
-5
@@ -398,7 +398,8 @@ def save_workout_database(f2,r,dosmooth=True,workouttype='rower',
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notes='',totaldist=0,totaltime=0,
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summary='',
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makeprivate=False,
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oarlength=2.89,inboard=0.88):
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oarlength=2.89,inboard=0.88,
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consistencychecks=True):
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message = None
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powerperc = 100*np.array([r.pw_ut2,
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r.pw_ut1,
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@@ -417,10 +418,13 @@ def save_workout_database(f2,r,dosmooth=True,workouttype='rower',
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for key,value in checks.iteritems():
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if not value:
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allchecks = 0
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a_messages.error(r.user,'Failed consistency check: '+key+', autocorrected')
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if consistencychecks:
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a_messages.error(r.user,'Failed consistency check: '+key+', autocorrected')
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else:
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a_messages.error(r.user,'Failed consistency check: '+key+', not corrected')
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if not allchecks:
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#row.repair()
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if not allchecks and consistencychecks:
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# row.repair()
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pass
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@@ -529,6 +533,7 @@ def save_workout_database(f2,r,dosmooth=True,workouttype='rower',
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user=r)
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if (len(ws) != 0):
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message = "Warning: This workout probably already exists in the database"
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privacy = 'private'
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# checking for inf values
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totaldist = np.nan_to_num(totaldist)
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@@ -781,7 +786,8 @@ def new_workout_from_df(r,df,
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oarlength=oarlength,
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inboard=inboard,
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makeprivate=makeprivate,
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dosmooth=False)
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dosmooth=False,
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consistencychecks=False)
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return (id,message)
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@@ -243,6 +243,7 @@ def save_workout_database(f2,r,dosmooth=True,workouttype='rower',
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user=r)
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if (len(ws) != 0):
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message = "Warning: This workout probably already exists in the database"
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privacy = 'private'
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@@ -596,6 +596,106 @@ def googlemap_chart(lat,lon,name=""):
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return [script,div]
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def interactive_otwcpchart(powerdf,promember=0):
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powerdf = powerdf[~(powerdf == 0).any(axis=1)]
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# plot tools
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if (promember==1):
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TOOLS = 'save,pan,box_zoom,wheel_zoom,reset,tap,hover,resize,crosshair'
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else:
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TOOLS = 'pan,box_zoom,wheel_zoom,reset,tap,hover,crosshair'
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x_axis_type = 'log'
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y_axis_type = 'linear'
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deltas = powerdf['Delta'].apply(lambda x: timedeltaconv(x))
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powerdf['ftime'] = niceformat(deltas)
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source = ColumnDataSource(
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data = powerdf
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)
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# there is no Paul's law for OTW
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# Fit the data to thee parameter CP model
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fitfunc = lambda pars,x: pars[0]/(1+(x/pars[2])) + pars[1]/(1+(x/pars[3]))
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errfunc = lambda pars,x,y: fitfunc(pars,x)-y
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p0 = [500,350,10,8000]
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p1 = p0
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thesecs = powerdf['Delta']
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theavpower = powerdf['CP']
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if len(thesecs)>=4:
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p1, success = optimize.leastsq(errfunc, p0[:], args = (thesecs,theavpower))
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else:
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factor = fitfunc(p0,thesecs.mean())/theavpower.mean()
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p1 = [p0[0]/factor,p0[1]/factor,p0[2],p0[3]]
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fitt = pd.Series(10**(4*np.arange(100)/100.))
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fitpower = fitfunc(p1,fitt)
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message = ""
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#if len(fitpower[fitpower<0]) > 0:
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# message = "CP model fit didn't give correct results"
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sourcecomplex = ColumnDataSource(
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data = dict(
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power = fitpower,
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duration = fitt
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)
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)
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# making the plot
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plot = Figure(tools=TOOLS,x_axis_type=x_axis_type,
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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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plot.extra_y_ranges = {"watermark": watermarkrange}
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plot.image_url([watermarkurl],1.8*max(thesecs),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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y_range_name = "watermark",
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)
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plot.circle('Delta','CP',source=source,fill_color='red',size=15,
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legend='Power Data')
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plot.xaxis.axis_label = "Duration (seconds)"
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plot.yaxis.axis_label = "Power (W)"
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plot.y_range = Range1d(0,1.5*max(theavpower))
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plot.x_range = Range1d(1,2*max(thesecs))
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plot.legend.orientation = "vertical"
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hover = plot.select(dict(type=HoverTool))
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hover.tooltips = OrderedDict([
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('Duration ','@ftime'),
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||||
('Power (W)','@CP{int}'),
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])
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hover.mode = 'mouse'
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||||
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plot.line('duration','power',source=sourcecomplex,legend="CP Model",
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color='green')
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script, div = components(plot)
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return [script,div,p1,message]
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def interactive_cpchart(thedistances,thesecs,theavpower,
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theworkouts,promember=0):
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+3
-2
@@ -425,7 +425,8 @@ class Workout(models.Model):
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||||
summary = models.TextField(blank=True)
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privacy = models.CharField(default='visible',max_length=30,
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choices=privacychoices)
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rankingpiece = models.BooleanField(default=False,verbose_name='Ranking Piece')
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||||
def __unicode__(self):
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||||
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||||
date = self.date
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@@ -552,7 +553,7 @@ class WorkoutForm(ModelForm):
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||||
duration = forms.TimeInput(format='%H:%M:%S.%f')
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||||
class Meta:
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||||
model = Workout
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||||
fields = ['name','date','starttime','duration','distance','workouttype','notes','privacy','boattype']
|
||||
fields = ['name','date','starttime','duration','distance','workouttype','notes','privacy','rankingpiece','boattype']
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||||
widgets = {
|
||||
'date': DateInput(),
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||||
'notes': forms.Textarea,
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||||
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||||
+16
-12
@@ -245,7 +245,7 @@ def get_strava_workout(user,stravaid):
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return [workoutsummary,df]
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||||
# Generate Workout data for Strava (a TCX file)
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def createstravaworkoutdata(w):
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def createstravaworkoutdata(w,dozip=True):
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filename = w.csvfilename
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row = rowingdata(filename)
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@@ -256,18 +256,22 @@ def createstravaworkoutdata(w):
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newnotes = 'from '+w.workoutsource+' via rowsandall.com'
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|
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row.exporttotcx(tcxfilename,notes=newnotes)
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gzfilename = tcxfilename+'.gz'
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with file(tcxfilename,'rb') as inF:
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s = inF.read()
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with gzip.GzipFile(gzfilename,'wb') as outF:
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outF.write(s)
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if dozip:
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gzfilename = tcxfilename+'.gz'
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with file(tcxfilename,'rb') as inF:
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s = inF.read()
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with gzip.GzipFile(gzfilename,'wb') as outF:
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outF.write(s)
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try:
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os.remove(tcxfilename)
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except WindowError:
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pass
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return gzfilename,""
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try:
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os.remove(tcxfilename)
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except WindowError:
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pass
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return gzfilename,""
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else:
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return tcxfilename,""
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# Upload the TCX file to Strava and set the workout activity type
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@@ -77,8 +77,28 @@
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</div>
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</div>
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<div class="grid_12 alpha">
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<div class="grid_6 alpha">
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<p> </p>
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</div>
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<div class="grid_6 omega">
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<div class="grid_2 suffix_4 alpha">
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<p>
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{% if user.rower.rowerplan == 'pro' or user.rower.rowerplan == 'coach' %}
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<a class="button blue small" href="/rowers/otw-bests">OTW Ranking Pieces</a>
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{% else %}
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<a class="button blue small" href="/rowers/promembership">OTW Ranking Pieces</a>
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{% endif %}
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</p>
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<p>
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Analyse power vs piece duration to make predictions.
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</p>
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</div>
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||||
|
||||
</div>
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</div>
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|
||||
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{% endblock %}
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@@ -147,6 +147,10 @@
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</div>
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{% endif %}
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<div class="grid_1 omega">
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<a href="/rowers/workout/{{ workout.id }}/emailgpx">
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<img src="/static/img/gpx.jpg" alt="GPX Export" width="60" height="60"></a>
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</div>
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||||
</div>
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</div>
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@@ -0,0 +1,207 @@
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{% extends "base.html" %}
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{% load staticfiles %}
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{% load rowerfilters %}
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|
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{% block title %}Workouts{% endblock %}
|
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|
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{% block content %}
|
||||
|
||||
<script type="text/javascript" src="/static/js/bokeh-0.12.3.min.js"></script>
|
||||
<script async="true" type="text/javascript">
|
||||
Bokeh.set_log_level("info");
|
||||
</script>
|
||||
|
||||
{{ interactiveplot |safe }}
|
||||
|
||||
<script>
|
||||
// Set things up to resize the plot on a window resize. You can play with
|
||||
// the arguments of resize_width_height() to change the plot's behavior.
|
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var plot_resize_setup = function () {
|
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var plotid = Object.keys(Bokeh.index)[0]; // assume we have just one plot
|
||||
var plot = Bokeh.index[plotid];
|
||||
var plotresizer = function() {
|
||||
// arguments: use width, use height, maintain aspect ratio
|
||||
plot.resize_width_height(true, true, false);
|
||||
};
|
||||
window.addEventListener('resize', plotresizer);
|
||||
plotresizer();
|
||||
};
|
||||
window.addEventListener('load', plot_resize_setup);
|
||||
</script>
|
||||
<style>
|
||||
/* Need this to get the page in "desktop mode"; not having an infinite height.*/
|
||||
html, body {height: 100%; margin:5px;}
|
||||
</style>
|
||||
|
||||
|
||||
<div id="title" class="grid_12 alpha">
|
||||
<div class="grid_10 alpha">
|
||||
{% if theuser %}
|
||||
<h3>{{ theuser.first_name }}'s Ranking Pieces</h3>
|
||||
{% else %}
|
||||
<h3>{{ user.first_name }}'s Ranking Pieces</h3>
|
||||
{% endif %}
|
||||
</div>
|
||||
<div class="grid_2 omega">
|
||||
{% if user.is_authenticated and user|is_manager %}
|
||||
<div class="grid_2 alpha dropdown">
|
||||
<button class="grid_2 alpha button green small dropbtn">
|
||||
Change Rower
|
||||
</button>
|
||||
<div class="dropdown-content">
|
||||
{% for member in user|team_members %}
|
||||
<a class="button green small" href="/rowers/{{ member.id }}/otw-bests/{{ startdate|date:"Y-m-d" }}/{{ enddate|date:"Y-m-d" }}">{{ member.first_name }} {{ member.last_name }}</a>
|
||||
{% endfor %}
|
||||
</div>
|
||||
{% else %}
|
||||
|
||||
{% endif %}
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div id="summary" class="grid_6 alpha">
|
||||
<p>Summary for {{ theuser.first_name }} {{ theuser.last_name }}
|
||||
between {{ startdate|date }} and {{ enddate|date }}</p>
|
||||
|
||||
<p>Direct link for other users:
|
||||
<a href="/rowers/{{ id }}/otw-bests/{{ startdate|date:"Y-m-d" }}/{{ enddate|date:"Y-m-d" }}">https://rowsandall.com/rowers/{{ id }}/otw-bests/{{ startdate|date:"Y-m-d" }}/{{ enddate|date:"Y-m-d" }}</a>
|
||||
</p>
|
||||
|
||||
<p>The table gives the OTW efforts you marked as Ranking Piece.
|
||||
The graph shows the best segments from those pieces, plotted as
|
||||
average power (over the segment) vs the duration of the segment/
|
||||
In other words: How long you can hold that power.
|
||||
</p>
|
||||
<p>At the bottom of the page, you will find predictions derived from the model.</p>
|
||||
</div>
|
||||
<div id="form" class="grid_6 omega">
|
||||
<p>Use this form to select a different date range:</p>
|
||||
<p>
|
||||
Select start and end date for a date range:
|
||||
<div class="grid_4 alpha">
|
||||
|
||||
<form enctype="multipart/form-data" action="" method="post">
|
||||
|
||||
<table>
|
||||
{{ dateform.as_table }}
|
||||
</table>
|
||||
{% csrf_token %}
|
||||
</div>
|
||||
<div class="grid_2 omega">
|
||||
<input name='daterange' class="button green" type="submit" value="Submit"> </form>
|
||||
</div>
|
||||
<div class="grid_4 alpha">
|
||||
<form enctype="multipart/form-data" action="" method="post">
|
||||
Or use the last {{ deltaform }} days.
|
||||
</div>
|
||||
<div class="grid_2 omega">
|
||||
{% csrf_token %}
|
||||
<input name='datedelta' class="button green" type="submit" value="Submit">
|
||||
</form>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
|
||||
|
||||
<div id="theplot" class="grid_12 alpha">
|
||||
|
||||
<h2>Critical Power Plot</h2>
|
||||
|
||||
{{ the_div|safe }}
|
||||
|
||||
</div>
|
||||
|
||||
<div class="grid_12 alpha">
|
||||
|
||||
<h2>Ranking Piece Results</h2>
|
||||
|
||||
{% if rankingworkouts %}
|
||||
|
||||
<table width="70%" class="listtable">
|
||||
<thead>
|
||||
<tr>
|
||||
<th> Distance</th>
|
||||
<th> Duration</th>
|
||||
<th> Avg Power</th>
|
||||
<th> Date</th>
|
||||
<th> Avg HR </th>
|
||||
<th> Max HR </th>
|
||||
<th> Edit</th>
|
||||
<tr>
|
||||
</thead>
|
||||
<tbody>
|
||||
{% for workout in rankingworkouts %}
|
||||
<tr>
|
||||
<td> {{ workout.distance }} m</td>
|
||||
<td> {{ workout.duration |durationprint:"%H:%M:%S.%f" }} </td>
|
||||
<td> {{ avgpower|lookup:workout.id }} W</td>
|
||||
<td> {{ workout.date }} </td>
|
||||
<td> {{ workout.averagehr }} </td>
|
||||
<td> {{ workout.maxhr }} </td>
|
||||
<td>
|
||||
<a href="/rowers/workout/{{ workout.id }}/edit">{{ workout.name }}</a> </td>
|
||||
|
||||
</tr>
|
||||
|
||||
{% endfor %}
|
||||
</tbody>
|
||||
</table>
|
||||
{% else %}
|
||||
<p> No ranking workouts found </p>
|
||||
{% endif %}
|
||||
|
||||
</div>
|
||||
|
||||
<div id="predictions" class="grid_12 alpha">
|
||||
<h2>Pace predictions for Ranking Pieces</h2>
|
||||
|
||||
<p>Add non-ranking piece using the form. The piece will be added in the prediction tables below. </p>
|
||||
|
||||
|
||||
|
||||
<div id="cpmodel" class="grid_6 alpha">
|
||||
<table width="70%" class="listtable">
|
||||
<thead>
|
||||
<tr>
|
||||
<th> Duration</th>
|
||||
<th> Power </th>
|
||||
<tr>
|
||||
</thead>
|
||||
<tbody>
|
||||
{% for pred in cpredictions %}
|
||||
<tr>
|
||||
{% for key, value in pred.items %}
|
||||
{% if key == "power" %}
|
||||
<td> {{ value }} W </td>
|
||||
{% endif %}
|
||||
{% if key == "duration" %}
|
||||
<td> {{ value |deltatimeprint }} </td>
|
||||
{% endif %}
|
||||
{% endfor %}
|
||||
</tr>
|
||||
{% endfor %}
|
||||
</tbody>
|
||||
</table>
|
||||
|
||||
</div>
|
||||
|
||||
<div class="grid_3">
|
||||
<form enctype="multipart/form-data" action="{{ formloc }}" method="post">
|
||||
{{ form.value }} {{ form.pieceunit }}
|
||||
|
||||
{% csrf_token %}
|
||||
</div>
|
||||
<div class="grid_1">
|
||||
minutes
|
||||
</div>
|
||||
<div class="grid_2 omega">
|
||||
<input name="piece" class="button green"
|
||||
formaction="/rowers/{{ id }}/otw-bests/{{ startdate|date:"Y-m-d" }}/{{ enddate|date:"Y-m-d" }}"
|
||||
type="submit" value="Add">
|
||||
</form>
|
||||
</div>
|
||||
|
||||
|
||||
</div>
|
||||
|
||||
{% endblock %}
|
||||
@@ -135,6 +135,12 @@ urlpatterns = [
|
||||
url(r'^ote-bests/(?P<deltadays>\d+)$',views.rankings_view),
|
||||
url(r'^ote-bests/$',views.rankings_view),
|
||||
url(r'^(?P<theuser>\d+)/ote-bests/$',views.rankings_view),
|
||||
url(r'^(?P<theuser>\d+)/otw-bests/(?P<startdatestring>\w+.*)/(?P<enddatestring>\w+.*)$',views.otwrankings_view),
|
||||
url(r'^(?P<theuser>\d+)/otw-bests/(?P<deltadays>\d+)$',views.otwrankings_view),
|
||||
url(r'^otw-bests/(?P<startdatestring>\w+.*)/(?P<enddatestring>\w+.*)$',views.otwrankings_view),
|
||||
url(r'^otw-bests/(?P<deltadays>\d+)$',views.otwrankings_view),
|
||||
url(r'^otw-bests/$',views.otwrankings_view),
|
||||
url(r'^(?P<theuser>\d+)/otw-bests/$',views.otwrankings_view),
|
||||
url(r'^(?P<theuser>\d+)/flexall/(?P<xparam>\w+.*)/(?P<yparam1>\w+.*)/(?P<yparam2>\w+.*)/(?P<startdatestring>\w+.*)/(?P<enddatestring>\w+.*)$',views.cum_flex),
|
||||
url(r'^flexall/(?P<xparam>\w+.*)/(?P<yparam1>\w+.*)/(?P<yparam2>\w+.*)/(?P<startdatestring>\w+.*)/(?P<enddatestring>\w+.*)$',views.cum_flex),
|
||||
url(r'^flexall/(?P<xparam>\w+.*)/(?P<yparam1>\w+.*)/(?P<yparam2>\w+.*)$',views.cum_flex),
|
||||
@@ -169,6 +175,7 @@ urlpatterns = [
|
||||
url(r'^workout/(?P<id>\d+)/export$',views.workout_export_view),
|
||||
url(r'^workout/(?P<id>\d+)/comment$',views.workout_comment_view),
|
||||
url(r'^workout/(?P<id>\d+)/emailtcx$',views.workout_tcxemail_view),
|
||||
url(r'^workout/(?P<id>\d+)/emailgpx$',views.workout_gpxemail_view),
|
||||
url(r'^workout/(?P<id>\d+)/emailcsv$',views.workout_csvemail_view),
|
||||
url(r'^workout/(?P<id>\d+)/csvtoadmin$',views.workout_csvtoadmin_view),
|
||||
url(r'^workout/compare/(?P<id>\d+)/$',views.workout_comparison_list),
|
||||
|
||||
+327
-9
@@ -138,6 +138,8 @@ from scipy.special import lambertw
|
||||
|
||||
from dataprep import timedeltaconv
|
||||
|
||||
from scipy.interpolate import griddata
|
||||
|
||||
LOCALTIMEZONE = tz('Etc/UTC')
|
||||
USER_LANGUAGE = 'en-US'
|
||||
|
||||
@@ -290,14 +292,11 @@ def iscoachmember(user):
|
||||
return result
|
||||
|
||||
def getrower(user):
|
||||
if not user.is_anonymous():
|
||||
try:
|
||||
r = Rower.objects.get(user=user)
|
||||
except Rower.DoesNotExist:
|
||||
r = Rower(user=user)
|
||||
r.save()
|
||||
else:
|
||||
raise PermissionDenied("You need to log in to use this function")
|
||||
try:
|
||||
r = Rower.objects.get(user=user)
|
||||
except Rower.DoesNotExist:
|
||||
r = Rower(user=user)
|
||||
r.save()
|
||||
|
||||
return r
|
||||
|
||||
@@ -1086,7 +1085,7 @@ def workout_tcxemail_view(request,id=0):
|
||||
raise Http404("Workout doesn't exist")
|
||||
if (checkworkoutuser(request.user,w)):
|
||||
try:
|
||||
tcxfile,tcxmessg = stravastuff.createstravaworkoutdata(w)
|
||||
tcxfile,tcxmessg = stravastuff.createstravaworkoutdata(w,dozip=False)
|
||||
if tcxfile == 0:
|
||||
message = "Something went wrong (TCX export) "+tcxmessg
|
||||
messages.error(request,message)
|
||||
@@ -1138,6 +1137,51 @@ def workout_tcxemail_view(request,id=0):
|
||||
|
||||
return response
|
||||
|
||||
# Export workout to GPX and send to user's email address
|
||||
@login_required()
|
||||
def workout_gpxemail_view(request,id=0):
|
||||
message = ""
|
||||
successmessage = ""
|
||||
r = Rower.objects.get(user=request.user)
|
||||
try:
|
||||
w = Workout.objects.get(id=id)
|
||||
except Workout.DoesNotExist:
|
||||
raise Http404("Workout doesn't exist")
|
||||
if (checkworkoutuser(request.user,w)):
|
||||
filename = w.csvfilename
|
||||
row = rdata(filename)
|
||||
gpxfilename = filename[:-4]+'.gpx'
|
||||
row.exporttogpx(gpxfilename)
|
||||
if settings.DEBUG:
|
||||
res = handle_sendemailtcx.delay(r.user.first_name,
|
||||
r.user.last_name,
|
||||
r.user.email,gpxfilename)
|
||||
|
||||
else:
|
||||
res = queuehigh.enqueue(handle_sendemailtcx,r.user.first_name,
|
||||
r.user.last_name,
|
||||
r.user.email,gpxfilename)
|
||||
|
||||
successmessage = "The GPX file was sent to you per email"
|
||||
messages.info(request,successmessage)
|
||||
url = reverse(workout_export_view,
|
||||
kwargs = {
|
||||
'id':str(w.id),
|
||||
})
|
||||
|
||||
response = HttpResponseRedirect(url)
|
||||
|
||||
else:
|
||||
message = "You are not allowed to export this workout"
|
||||
messages.error(request,message)
|
||||
url = reverse(workout_export_view,
|
||||
kwargs = {
|
||||
'id':str(w.id),
|
||||
})
|
||||
response = HttpResponseRedirect(url)
|
||||
|
||||
return response
|
||||
|
||||
# Get Workout CSV file and send it to user's email address
|
||||
@login_required()
|
||||
def workout_csvemail_view(request,id=0):
|
||||
@@ -2730,6 +2774,274 @@ def rankings_view(request,theuser=0,
|
||||
'teams':get_my_teams(request.user),
|
||||
})
|
||||
|
||||
# Show ranking distances including predicted paces
|
||||
@login_required()
|
||||
def otwrankings_view(request,theuser=0,
|
||||
startdate=timezone.now()-datetime.timedelta(days=365),
|
||||
enddate=timezone.now(),
|
||||
deltadays=-1,
|
||||
startdatestring="",
|
||||
enddatestring=""):
|
||||
|
||||
if deltadays>0:
|
||||
startdate = enddate-datetime.timedelta(days=int(deltadays))
|
||||
|
||||
if startdatestring != "":
|
||||
startdate = iso8601.parse_date(startdatestring)
|
||||
|
||||
if enddatestring != "":
|
||||
enddate = iso8601.parse_date(enddatestring)
|
||||
|
||||
if enddate < startdate:
|
||||
s = enddate
|
||||
enddate = startdate
|
||||
startdate = s
|
||||
|
||||
if theuser == 0:
|
||||
theuser = request.user.id
|
||||
|
||||
promember=0
|
||||
if not request.user.is_anonymous():
|
||||
r = Rower.objects.get(user=request.user)
|
||||
result = request.user.is_authenticated() and ispromember(request.user)
|
||||
if result:
|
||||
promember=1
|
||||
|
||||
# get all OTW rows in date range
|
||||
|
||||
# process form
|
||||
if request.method == 'POST' and "daterange" in request.POST:
|
||||
dateform = DateRangeForm(request.POST)
|
||||
deltaform = DeltaDaysForm(request.POST)
|
||||
if dateform.is_valid():
|
||||
startdate = dateform.cleaned_data['startdate']
|
||||
enddate = dateform.cleaned_data['enddate']
|
||||
if startdate > enddate:
|
||||
s = enddate
|
||||
enddate = startdate
|
||||
startdate = s
|
||||
elif request.method == 'POST' and "datedelta" in request.POST:
|
||||
deltaform = DeltaDaysForm(request.POST)
|
||||
if deltaform.is_valid():
|
||||
deltadays = deltaform.cleaned_data['deltadays']
|
||||
if deltadays:
|
||||
enddate = timezone.now()
|
||||
startdate = enddate-datetime.timedelta(days=deltadays)
|
||||
if startdate > enddate:
|
||||
s = enddate
|
||||
enddate = startdate
|
||||
startdate = s
|
||||
dateform = DateRangeForm(initial={
|
||||
'startdate': startdate,
|
||||
'enddate': enddate,
|
||||
})
|
||||
else:
|
||||
dateform = DateRangeForm()
|
||||
deltaform = DeltaDaysForm()
|
||||
|
||||
else:
|
||||
dateform = DateRangeForm(initial={
|
||||
'startdate': startdate,
|
||||
'enddate': enddate,
|
||||
})
|
||||
deltaform = DeltaDaysForm()
|
||||
|
||||
# get all 2k (if any) - this rower, in date range
|
||||
try:
|
||||
r = Rower.objects.get(user=theuser)
|
||||
except Rower.DoesNotExist:
|
||||
allergworkouts = []
|
||||
r=0
|
||||
|
||||
|
||||
try:
|
||||
uu = User.objects.get(id=theuser)
|
||||
except User.DoesNotExist:
|
||||
uu = ''
|
||||
|
||||
|
||||
# test to fix bug
|
||||
startdate = datetime.datetime.combine(startdate,datetime.time())
|
||||
enddate = datetime.datetime.combine(enddate,datetime.time(23,59,59))
|
||||
enddate = enddate+datetime.timedelta(days=1)
|
||||
|
||||
|
||||
rankingdurations = []
|
||||
rankingdurations.append(datetime.time(minute=1))
|
||||
rankingdurations.append(datetime.time(minute=4))
|
||||
rankingdurations.append(datetime.time(minute=30))
|
||||
rankingdurations.append(datetime.time(hour=1))
|
||||
|
||||
thedistances = []
|
||||
theworkouts = []
|
||||
thesecs = []
|
||||
|
||||
theworkouts = Workout.objects.filter(user=r,rankingpiece=True,
|
||||
workouttype='water',
|
||||
startdatetime__gte=startdate,
|
||||
startdatetime__lte=enddate)
|
||||
|
||||
|
||||
# get all power data from database (plus workoutid)
|
||||
theids = [w.id for w in theworkouts]
|
||||
columns = ['power','workoutid','time']
|
||||
df = dataprep.getsmallrowdata_db(columns,ids=theids)
|
||||
|
||||
thesecs = []
|
||||
|
||||
for w in theworkouts:
|
||||
timesecs = 3600*w.duration.hour
|
||||
timesecs += 60*w.duration.minute
|
||||
timesecs += w.duration.second
|
||||
timesecs += 1.e-5*w.duration.microsecond
|
||||
|
||||
thesecs.append(timesecs)
|
||||
|
||||
if len(thesecs) != 0:
|
||||
maxt = pd.Series(thesecs).max()
|
||||
else:
|
||||
maxt = 1000.
|
||||
|
||||
maxlog10 = np.log10(maxt)
|
||||
logarr = np.arange(100)*maxlog10/100.
|
||||
logarr = [int(10.**(la)) for la in logarr]
|
||||
logarr = pd.Series(logarr)
|
||||
logarr.drop_duplicates(keep='first',inplace=True)
|
||||
logarr = logarr.values
|
||||
|
||||
delta = []
|
||||
cpvalue = []
|
||||
avgpower = {}
|
||||
|
||||
dfgrouped = df.groupby(['workoutid'])
|
||||
for id,group in dfgrouped:
|
||||
tt = group['time']
|
||||
ww = group['power']
|
||||
try:
|
||||
avgpower[id] = int(ww.mean())
|
||||
except ValueError:
|
||||
avgpower[id] = '---'
|
||||
if not np.isnan(ww.mean()):
|
||||
length = len(ww)
|
||||
dt = []
|
||||
cpw = []
|
||||
for i in range(length-2):
|
||||
w_roll = ww.rolling(i+2,min_periods=2).mean()
|
||||
# now goes with # data points - should be fixed seconds
|
||||
indexmax = w_roll.idxmax(axis=1)
|
||||
try:
|
||||
t_0 = tt.ix[indexmax]
|
||||
t_1 = tt.ix[indexmax-i-2]
|
||||
deltat = 1.0e-3*(t_0-t_1)
|
||||
wmax = w_roll.ix[indexmax]
|
||||
dt.append(deltat)
|
||||
cpw.append(wmax)
|
||||
except KeyError:
|
||||
pass
|
||||
|
||||
dt = pd.Series(dt)
|
||||
cpw = pd.Series(cpw)
|
||||
cpvalues = griddata(dt.values,
|
||||
cpw.values,
|
||||
logarr,method='linear',fill_value=0)
|
||||
|
||||
for cpv in cpvalues:
|
||||
cpvalue.append(cpv)
|
||||
for d in logarr:
|
||||
delta.append(d)
|
||||
|
||||
print avgpower
|
||||
dt = pd.Series(delta,name='Delta')
|
||||
cpvalue = pd.Series(cpvalue,name='CP')
|
||||
|
||||
|
||||
powerdf = pd.DataFrame({
|
||||
'Delta':delta,
|
||||
'CP':cpvalue,
|
||||
})
|
||||
|
||||
powerdf = powerdf[powerdf['CP']>0]
|
||||
powerdf.dropna(axis=0,inplace=True)
|
||||
powerdf.sort_values(['Delta','CP'],ascending=[1,0],inplace=True)
|
||||
powerdf.drop_duplicates(subset='Delta',keep='first',inplace=True)
|
||||
|
||||
|
||||
# create interactive plot
|
||||
if len(powerdf) !=0 :
|
||||
res = interactive_otwcpchart(powerdf,promember=promember)
|
||||
script = res[0]
|
||||
div = res[1]
|
||||
p1 = res[2]
|
||||
paulslope = 1
|
||||
paulintercept = 1
|
||||
message = res[3]
|
||||
else:
|
||||
script = ''
|
||||
div = '<p>No ranking pieces found.</p>'
|
||||
paulslope = 1
|
||||
paulintercept = 1
|
||||
p1 = [1,1,1,1]
|
||||
message = ""
|
||||
|
||||
|
||||
if request.method == 'POST' and "piece" in request.POST:
|
||||
form = PredictedPieceForm(request.POST)
|
||||
clean = form.is_valid()
|
||||
value = form.cleaned_data['value']
|
||||
hourvalue,value = divmod(value,60)
|
||||
if hourvalue >= 24:
|
||||
hourvalue = 23
|
||||
rankingdurations.append(datetime.time(minute=value,hour=hourvalue))
|
||||
else:
|
||||
form = PredictedPieceForm()
|
||||
|
||||
|
||||
predictions = []
|
||||
cpredictions = []
|
||||
|
||||
|
||||
|
||||
for rankingduration in rankingdurations:
|
||||
t = 3600.*rankingduration.hour
|
||||
t += 60.*rankingduration.minute
|
||||
t += rankingduration.second
|
||||
t += rankingduration.microsecond/1.e6
|
||||
|
||||
|
||||
# CP model
|
||||
pwr = p1[0]/(1+t/p1[2])
|
||||
pwr += p1[1]/(1+t/p1[3])
|
||||
|
||||
if pwr <= 0:
|
||||
pwr = 50.
|
||||
|
||||
if not np.isnan(pwr):
|
||||
a = {
|
||||
'duration':timedeltaconv(t),
|
||||
'power':int(pwr)}
|
||||
cpredictions.append(a)
|
||||
|
||||
|
||||
del form.fields["pieceunit"]
|
||||
|
||||
messages.error(request,message)
|
||||
return render(request, 'otwrankings.html',
|
||||
{'rankingworkouts':theworkouts,
|
||||
'interactiveplot':script,
|
||||
'the_div':div,
|
||||
'predictions':predictions,
|
||||
'cpredictions':cpredictions,
|
||||
'avgpower':avgpower,
|
||||
'form':form,
|
||||
'dateform':dateform,
|
||||
'deltaform':deltaform,
|
||||
'id': theuser,
|
||||
'theuser':uu,
|
||||
'startdate':startdate,
|
||||
'enddate':enddate,
|
||||
'teams':get_my_teams(request.user),
|
||||
})
|
||||
|
||||
# Reload the workout and calculate the summary from the stroke data (lapIDx)
|
||||
@login_required()
|
||||
def workout_recalcsummary_view(request,id=0):
|
||||
@@ -5207,6 +5519,11 @@ def workout_edit_view(request,id=0,message="",successmessage=""):
|
||||
privacy = request.POST['privacy']
|
||||
except KeyError:
|
||||
privacy = Workout.objects.get(id=id).privacy
|
||||
try:
|
||||
rankingpiece = form.cleaned_data['rankingpiece']
|
||||
except KeyError:
|
||||
rankingpiece =- Workout.objects.get(id=id).rankingpiece
|
||||
|
||||
startdatetime = (str(date) + ' ' + str(starttime))
|
||||
startdatetime = datetime.datetime.strptime(startdatetime,
|
||||
"%Y-%m-%d %H:%M:%S")
|
||||
@@ -5223,6 +5540,7 @@ def workout_edit_view(request,id=0,message="",successmessage=""):
|
||||
row.distance = distance
|
||||
row.boattype = boattype
|
||||
row.privacy = privacy
|
||||
row.rankingpiece = rankingpiece
|
||||
try:
|
||||
row.save()
|
||||
except IntegrityError:
|
||||
|
||||
Binary file not shown.
|
After Width: | Height: | Size: 27 KiB |
Reference in New Issue
Block a user