added agegroupcp

rowers/interactiveplots.py

@@ -977,6 +977,255 @@ def googlemap_chart(lat,lon,name=""):
 
     return [script,div]
 			    
+def interactive_agegroupcpchart(age,normalized=False):
+    durations = [1,4,30,60]
+    distances = [100,500,1000,2000,5000,6000,10000,21097,42195]
+
+    fhduration = []
+    fhpower = []
+    
+    for distance in distances:
+        worldclasspower = metrics.getagegrouprecord(
+            age,
+            sex='female',
+            distance=distance,
+            weightcategory='hwt'
+        )
+        velo = (worldclasspower/2.8)**(1./3.)
+        try:
+            duration = distance/velo
+            fhduration.append(duration)
+            fhpower.append(worldclasspower)
+        except ZeroDivisionError:
+            pass
+    for duration in durations:
+        worldclasspower = metrics.getagegrouprecord(
+            age,
+            sex='female',
+            duration=duration,
+            weightcategory='hwt'
+            )
+        try:
+            velo = (worldclasspower/2.8)**(1./3.)
+            distance = int(60*duration*velo)
+            fhduration.append(60.*duration)
+            fhpower.append(worldclasspower)
+        except ValueError:
+            pass
+
+    flduration = []
+    flpower = []
+    
+    for distance in distances:
+        worldclasspower = metrics.getagegrouprecord(
+            age,
+            sex='female',
+            distance=distance,
+            weightcategory='lwt'
+        )
+        velo = (worldclasspower/2.8)**(1./3.)
+        try:
+            duration = distance/velo
+            flduration.append(duration)
+            flpower.append(worldclasspower)
+        except ZeroDivisionError:
+            pass
+    for duration in durations:
+        worldclasspower = metrics.getagegrouprecord(
+            age,
+            sex='female',
+            duration=duration,
+            weightcategory='lwt'
+            )
+        try:
+            velo = (worldclasspower/2.8)**(1./3.)
+            distance = int(60*duration*velo)
+            flduration.append(60.*duration)
+            flpower.append(worldclasspower)
+        except ValueError:
+            pass
+
+    mlduration = []
+    mlpower = []
+    
+    for distance in distances:
+        worldclasspower = metrics.getagegrouprecord(
+            age,
+            sex='male',
+            distance=distance,
+            weightcategory='lwt'
+        )
+        velo = (worldclasspower/2.8)**(1./3.)
+        try:
+            duration = distance/velo
+            mlduration.append(duration)
+            mlpower.append(worldclasspower)
+        except ZeroDivisionError:
+            pass
+    for duration in durations:
+        worldclasspower = metrics.getagegrouprecord(
+            age,
+            sex='male',
+            duration=duration,
+            weightcategory='lwt'
+            )
+        try:
+            velo = (worldclasspower/2.8)**(1./3.)
+            distance = int(60*duration*velo)
+            mlduration.append(60.*duration)
+            mlpower.append(worldclasspower)
+        except ValueError:
+            pass
+        
+
+    mhduration = []
+    mhpower = []
+    
+    for distance in distances:
+        worldclasspower = metrics.getagegrouprecord(
+            age,
+            sex='male',
+            distance=distance,
+            weightcategory='hwt'
+        )
+        velo = (worldclasspower/2.8)**(1./3.)
+        try:
+            duration = distance/velo
+            mhduration.append(duration)
+            mhpower.append(worldclasspower)
+        except ZeroDivisionError:
+            pass
+    for duration in durations:
+        worldclasspower = metrics.getagegrouprecord(
+            age,
+            sex='male',
+            duration=duration,
+            weightcategory='hwt'
+            )
+        try:
+            velo = (worldclasspower/2.8)**(1./3.)
+            distance = int(60*duration*velo)
+            mhduration.append(60.*duration)
+            mhpower.append(worldclasspower)
+        except ValueError:
+            pass
+        
+
+        
+    fitfunc = lambda pars,x: pars[0]/(1+(x/pars[2])) + pars[1]/(1+(x/pars[3]))
+    errfunc = lambda pars,x,y: fitfunc(pars,x)-y
+
+    p0 = [500,350,10,8000]
+
+    # fitting WC data to three parameter CP model
+    if len(fhduration)>=4:
+        p1fh, success = optimize.leastsq(errfunc, p0[:],
+                                       args = (fhduration,fhpower))
+    else:
+        p1fh = None
+
+    # fitting WC data to three parameter CP model
+    if len(flduration)>=4:
+        p1fl, success = optimize.leastsq(errfunc, p0[:],
+                                       args = (flduration,flpower))
+    else:
+        p1fl = None
+
+    # fitting WC data to three parameter CP model
+    if len(mlduration)>=4:
+        p1ml, success = optimize.leastsq(errfunc, p0[:],
+                                       args = (mlduration,mlpower))
+    else:
+        p1ml = None
+        
+    if len(mhduration)>=4:
+        p1mh, success = optimize.leastsq(errfunc, p0[:],
+                                       args = (mhduration,mhpower))
+    else:
+        p1mh = None
+        
+    fitt = pd.Series(10**(4*np.arange(100)/100.))
+
+    fitpowerfh = fitfunc(p1fh,fitt)
+    fitpowerfl = fitfunc(p1fl,fitt)
+    fitpowerml = fitfunc(p1ml,fitt)
+    fitpowermh = fitfunc(p1mh,fitt)
+
+    if normalized:
+        facfh = fitfunc(p1fh,60)
+        facfl = fitfunc(p1fl,60)
+        facml = fitfunc(p1ml,60)
+        facmh = fitfunc(p1mh,60)
+        fitpowerfh /= facfh
+        fitpowerfl /= facfl
+        fitpowermh /= facmh
+        fitpowerml /= facml
+        fhpower /= facfh
+        flpower /= facfl
+        mlpower /= facml
+        mhpower /= facmh
+
+
+        
+    source = ColumnDataSource(
+        data = dict(
+            duration = fitt,
+            fitpowerfh = fitpowerfh,
+            fitpowerfl = fitpowerfl,
+            fitpowerml = fitpowerml,
+            fitpowermh = fitpowermh,
+            flduration = flduration,
+            flpower = flpower,
+            fhduration = fhduration,
+            fhpower = fhpower,
+            mlduration = mlduration,
+            mlpower = mlpower,
+            mhduration = mhduration,
+            mhpower = mhpower,
+            )
+        )
+
+    x_axis_type = 'log'
+    y_axis_type = 'linear'
+
+    plot = Figure(plot_width=900,x_axis_type=x_axis_type)
+
+    plot.line('duration','fitpowerfh',source=source,
+              legend='Female HW',color='blue')
+    plot.line('duration','fitpowerfl',source=source,
+              legend='Female LW',color='red')
+
+    plot.line('duration','fitpowerml',source=source,
+              legend='Male LW',color='green')
+
+    plot.line('duration','fitpowermh',source=source,
+              legend='Male HW',color='orange')
+
+
+    plot.circle('flduration','flpower',source=source,
+                fill_color='red',size=15)
+
+    plot.circle('fhduration','fhpower',source=source,
+                fill_color='blue',size=15)
+
+    plot.circle('mlduration','mlpower',source=source,
+                fill_color='green',size=15)
+
+    plot.circle('mhduration','mhpower',source=source,
+                fill_color='orange',size=15)
+
+    plot.title.text = 'age '+str(age)
+
+    plot.xaxis.axis_label = "Duration (seconds)"
+    if normalized:
+        plot.yaxis.axis_label = "Power (normalized)"        
+    else:
+        plot.yaxis.axis_label = "Power (W)"
+
+    script,div = components(plot)
+
+    return script,div
+
 
 def interactive_otwcpchart(powerdf,promember=0):
     powerdf = powerdf[~(powerdf == 0).any(axis=1)]