courses defined by spline and other improvements

rowers/interactiveplots.py

@@ -43,6 +43,8 @@ from courses import (
     polygon_coord_center
     )
 
+from rowers.models import course_spline
+
 import datetime
 import math
 import numpy as np
@@ -853,6 +855,8 @@ def course_map(course):
     latmean,lonmean,coordinates = course_coord_center(course)
     lat_min, lat_max, long_min, long_max = course_coord_maxmin(course)
 
+    coordinates = course_spline(coordinates)
+    
     scoordinates = "["
 
     for index,row in coordinates.iterrows():

rowers/models.py

@@ -18,6 +18,9 @@ import twitter
 import re
 import pytz
 
+from scipy.interpolate import splprep, splev, CubicSpline
+import numpy as np
+
 from django.conf import settings
 from sqlalchemy import create_engine
 import sqlalchemy as sa
@@ -377,6 +380,32 @@ def coordinate_in_path(latitude,longitude, p):
 
     return p.contains_points([(latitude,longitude)])[0]
 
+def course_spline(coordinates):
+    latitudes = coordinates['latitude'].values
+    longitudes = coordinates['longitude'].values
+    
+    # spline parameters
+    s = 1.0
+    k = min([5,len(latitudes)-1])
+    nest = -1
+
+    t = np.linspace(0,1,len(latitudes))
+    tnew = np.linspace(0,1,100)
+    
+    latnew = CubicSpline(t,latitudes,bc_type='clamped')(tnew)
+    lonnew = CubicSpline(t,longitudes,bc_type='clamped')(tnew)
+#    latnew = CubicSpline(t,latitudes,bc_type='natural')(tnew)
+#    lonnew = CubicSpline(t,longitudes,bc_type='natural')(tnew)
+
+#    tckp,u = splprep([t,latitudes,longitudes],s=s,k=k,nest=nest)
+#    tnew,latnew,lonnew = splev(np.linspace(0,1,100),tckp)
+
+    newcoordinates = pd.DataFrame({
+        'latitude':latnew,
+        'longitude':lonnew,
+        })
+
+    return newcoordinates
         
 def course_coord_center(course):
 
@@ -393,11 +422,13 @@ def course_coord_center(course):
     latitude = pd.Series(latitudes).median()
     longitude = pd.Series(longitudes).median()
 
+    
     coordinates = pd.DataFrame({
         'latitude':latitudes,
         'longitude':longitudes,
         })
 
+    
     return latitude,longitude,coordinates
 
 def course_coord_maxmin(course):
@@ -868,7 +899,7 @@ class GeoPolygon(models.Model):
         
         return u'{coursename} - {name}'.format(
             name=name,
-            course=coursename
+            coursename=coursename
         )
     
     
@@ -1157,9 +1188,12 @@ registerchoices = (
 
 class VirtualRace(PlannedSession):
 #    has_registration = models.BooleanField(default=False)
-    registration_form = models.CharField(max_length=100,
+    registration_form = models.CharField(
-                                         default='windowstart',
+        max_length=100,
-                                         choices=registerchoices)
+        default='windowstart',
+        choices=registerchoices,
+        verbose_name='Registration Closure Quick Selector'
+    )
     registration_closure = models.DateTimeField(blank=True,null=True)
     evaluation_closure = models.DateTimeField(blank=True,null=True)
     start_time = models.TimeField(blank=True,null=True)
@@ -1348,6 +1382,12 @@ class VirtualRaceForm(ModelForm):
         if startdatetime > enddatetime:
             raise forms.ValidationError("The Start of the Race Window should be before the End of the Race Window")
 
+        try:
+            evaluation_closure = cd['evaluation_closure']
+        except KeyError:
+            evaluation_closure = enddatetime+datetime.timedelta(days=1)
+            cd['evaluation_closure'] = evaluation_closure
+
         if cd['evaluation_closure'] <= enddatetime:
             raise forms.ValidationError("Evaluation closure deadline should be after the Race Window closes")
 
@@ -1355,7 +1395,7 @@ class VirtualRaceForm(ModelForm):
             raise forms.ValidationError("Evaluation closure cannot be in the past")
         
 
-        return cleaned_data
+        return cd
 
 class PlannedSessionFormSmall(ModelForm):
     

rowers/utils.py

@@ -253,8 +253,9 @@ def isbreakthrough(delta,cpvalues,p0,p1,p2,p3,ratio):
   pwr *= ratio
 
   
-  delta = delta.values
+  delta = delta.values.astype(int)
-  cpvalues = cpvalues.values
+  cpvalues = cpvalues.values.astype(int)
+  pwr = pwr.astype(int)
 
   res = np.sum(cpvalues>pwr)
   res2 = np.sum(cpvalues>pwr2)