changed to exponential function

rowers/interactiveplots.py

@@ -53,6 +53,7 @@ import stravastuff
 
 from rowers.dataprep import rdata
 import rowers.dataprep as dataprep
+import rowers.metrics as metrics
 
 from rowers.metrics import axes,axlabels,yaxminima,yaxmaxima
 
@@ -1069,24 +1070,38 @@ def interactive_otwcpchart(powerdf,promember=0):
 
     return [script,div,p1,ratio,message]
 
-def interactive_agegroup_plot(df):
+def interactive_agegroup_plot(df,distance=2000,duration=None,
+                              sex='male',weightcategory='hwt'):
 
     age = df['age']
     power = df['power']
     name = df['name']
     season = df['season']
 
-    poly_coefficients = np.polyfit(age,power,6)
+#    poly_coefficients = np.polyfit(age,power,6)
 
     age2 = np.linspace(11,95)
-    poly_vals = np.polyval(poly_coefficients,age2)
+#    poly_vals = np.polyval(poly_coefficients,age2)
+#    poly_vals = 0.5*(np.abs(poly_vals)+poly_vals)
+
+    fitfunc = lambda pars, x: np.abs(pars[0])*(1-x/max(120,pars[1]))-np.abs(pars[2])*np.exp(-x/np.abs(pars[3]))+np.abs(pars[4])*(np.sin(np.pi*x/max(50,pars[5])))
+    errfunc = lambda pars, x,y: fitfunc(pars,x)-y
+
+    p0 = [700,120,700,10,100,100]
+
+    p1, success = optimize.leastsq(errfunc,p0[:],
+                                   args = (age,power))
+
+    expo_vals = fitfunc(p1, age2)
+    expo_vals = 0.5*(np.abs(expo_vals)+expo_vals)
+    
 
     source = ColumnDataSource(
         data = dict(
             age = age,
             power = power,
             age2 = age2,
-            poly_vals = poly_vals,
+            expo_vals = expo_vals,
             season = season,
             name=name,
             )
@@ -1097,9 +1112,10 @@ def interactive_agegroup_plot(df):
     plot = Figure(tools=TOOLS,plot_width=900)
     plot.circle('age','power',source=source,fill_color='red',size=15,
                 legend='World Record')
-    plot.line(age2,poly_vals)
+
+    plot.line(age2,expo_vals)
     plot.xaxis.axis_label = "Age"
-    plot.yaxis.axis_label = "Concept2 2k power"
+    plot.yaxis.axis_label = "Concept2 power"
 
     hover = plot.select(dict(type=HoverTool))
 

rowers/metrics.py

@@ -2,6 +2,7 @@ from utils import lbstoN
 import numpy as np
 from models import C2WorldClassAgePerformance
 import pandas as pd
+from scipy import optimize
 
 rowingmetrics = (
     ('time',{
@@ -347,9 +348,20 @@ def getagegrouprecord(age,sex='male',weightcategory='hwt',
         ages = df['age']
         powers = df['power']
 
-        poly_coefficients = np.polyfit(ages,powers,6)
+        #poly_coefficients = np.polyfit(ages,powers,6)
+        fitfunc = lambda pars, x: np.abs(pars[0])*(1-x/max(120,pars[1]))-np.abs(pars[2])*np.exp(-x/np.abs(pars[3]))+np.abs(pars[4])*(np.sin(np.pi*x/max(50,pars[5])))
+        errfunc = lambda pars, x,y: fitfunc(pars,x)-y
 
-        power = np.polyval(poly_coefficients,age)
+        p0 = [700,120,700,10,100,100]
+
+        p1, success = optimize.leastsq(errfunc,p0[:],
+                                       args = (ages,powers))
+
+        power = fitfunc(p1, float(age))
+
+        #power = np.polyval(poly_coefficients,age)
+
+        power = 0.5*(np.abs(power)+power)
     else:
         power = 0
 

rowers/views.py

@@ -11312,7 +11312,9 @@ def agegrouprecordview(request,sex='male',weightcategory='hwt',
         )
         
 
-    script,div = interactive_agegroup_plot(df)
+    script,div = interactive_agegroup_plot(df,sex=sex,distance=distance,
+                                           duration=duration,
+                                           weightcategory=weightcategory)
     
     return render(request, 'agegroupchart.html',
 		  {