moving age group records to c2stuff

rowers/c2stuff.py

@@ -29,6 +29,70 @@ queue = django_rq.get_queue('default')
 queuelow = django_rq.get_queue('low')
 queuehigh = django_rq.get_queue('low')
 from rowers.utils import myqueue
+from rowers.models import C2WorldClassAgePerformance
+
+def getagegrouprecord(age,sex='male',weightcategory='hwt',
+                      distance=2000,duration=None,indf=pd.DataFrame()):
+
+    if not indf.empty:
+        if not duration:
+            df = indf[indf['distance'] == distance]
+        else:
+            duration = 60*int(duration)
+            df = indf[indf['duration'] == duration]
+    else:
+        if not duration:
+            df = pd.DataFrame(
+                list(
+                    C2WorldClassAgePerformance.objects.filter(
+                        distance=distance,
+                        sex=sex,
+                        weightcategory=weightcategory
+                    ).values()
+                )
+            )
+        else:
+            duration=60*int(duration)
+            df = pd.DataFrame(
+                list(
+                    C2WorldClassAgePerformance.objects.filter(
+                        duration=duration,
+                        sex=sex,
+                        weightcategory=weightcategory
+                    ).values()
+                )
+            )
+
+    if not df.empty:
+        ages = df['age']
+        powers = df['power']
+
+        #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
+
+        p0 = [700,120,700,10,100,100]
+
+        try:
+            p1, success = optimize.leastsq(errfunc,p0[:],
+                                       args = (ages,powers))
+        except:
+            p1 = p0
+            success = 0
+
+        if success:
+            power = fitfunc(p1, float(age))
+
+            #power = np.polyval(poly_coefficients,age)
+
+            power = 0.5*(np.abs(power)+power)
+        else:
+            power = 0
+    else:
+        power = 0
+
+    return power
+
 
 oauth_data = {
     'client_id': C2_CLIENT_ID,

rowers/metrics.py

@@ -6,7 +6,7 @@ from __future__ import unicode_literals
 from __future__ import absolute_import
 from rowers.utils import lbstoN
 import numpy as np
-from rowers.models import C2WorldClassAgePerformance
+
 import pandas as pd
 from scipy import optimize
 from django.utils import timezone
@@ -397,64 +397,3 @@ def calc_trimp(df,sex,hrmax,hrmin,hrftp):
     return trimp,hrtss
 
 
-def getagegrouprecord(age,sex='male',weightcategory='hwt',
-                      distance=2000,duration=None,indf=pd.DataFrame()):
-
-    if not indf.empty:
-        if not duration:
-            df = indf[indf['distance'] == distance]
-        else:
-            duration = 60*int(duration)
-            df = indf[indf['duration'] == duration]
-    else:
-        if not duration:
-            df = pd.DataFrame(
-                list(
-                    C2WorldClassAgePerformance.objects.filter(
-                        distance=distance,
-                        sex=sex,
-                        weightcategory=weightcategory
-                    ).values()
-                )
-            )
-        else:
-            duration=60*int(duration)
-            df = pd.DataFrame(
-                list(
-                    C2WorldClassAgePerformance.objects.filter(
-                        duration=duration,
-                        sex=sex,
-                        weightcategory=weightcategory
-                    ).values()
-                )
-            )
-
-    if not df.empty:
-        ages = df['age']
-        powers = df['power']
-
-        #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
-
-        p0 = [700,120,700,10,100,100]
-
-        try:
-            p1, success = optimize.leastsq(errfunc,p0[:],
-                                       args = (ages,powers))
-        except:
-            p1 = p0
-            success = 0
-
-        if success:
-            power = fitfunc(p1, float(age))
-
-            #power = np.polyval(poly_coefficients,age)
-
-            power = 0.5*(np.abs(power)+power)
-        else:
-            power = 0
-    else:
-        power = 0
-
-    return power