more foundation work for scoring

rowers/admin.py

@@ -11,7 +11,7 @@ from .models import (
     Team,TeamInvite,TeamRequest,
     WorkoutComment,C2WorldClassAgePerformance,PlannedSession,
     GeoCourse,GeoPolygon,GeoPoint,VirtualRace,VirtualRaceResult,
-    PaidPlan,IndoorVirtualRaceResult,ShareKey
+    PaidPlan,IndoorVirtualRaceResult,ShareKey, CourseStandard,StandardCollection,
     )
 
 # Register your models here so you can use them in the Admin module
@@ -141,6 +141,12 @@ class IndoorVirtualRaceResultAdmin(admin.ModelAdmin):
 class PaidPlanAdmin(admin.ModelAdmin):
     list_display = ('name','shortname','price','paymenttype','paymentprocessor','external_id')
 
+class StandardCollectionAdmin(admin.ModelAdmin):
+    list_display = ('name','manager')
+
+class CourseStandardAdmin(admin.ModelAdmin):
+    list_display = ('name','standardcollection')
+
 admin.site.unregister(User)
 admin.site.register(User,UserAdmin)
 admin.site.register(Workout,WorkoutAdmin)
@@ -160,3 +166,5 @@ admin.site.register(VirtualRaceResult, VirtualRaceResultAdmin)
 admin.site.register(IndoorVirtualRaceResult, IndoorVirtualRaceResultAdmin)
 admin.site.register(PaidPlan,PaidPlanAdmin)
 admin.site.register(ShareKey,ShareKeyAdmin)
+admin.site.register(CourseStandard,CourseStandardAdmin)
+admin.site.register(StandardCollection,StandardCollectionAdmin)

rowers/courseutils.py

@@ -2,6 +2,11 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 from __future__ import unicode_literals
+
+
+
+
+
 # low level methods
 def coordinate_in_path(latitude,longitude, p):
 
@@ -18,12 +23,12 @@ def time_in_path(df,p,maxmin='max',getall=False):
 
     if df.empty:
         return 0
-    
+
     latitude = df.latitude
     longitude = df.longitude
 
     f = lambda x: coordinate_in_path(x['latitude'],x['longitude'],p)
-    
+
     df['inpolygon'] = df.apply(f,axis=1)
 
     if maxmin=='max':
@@ -40,7 +45,7 @@ def time_in_path(df,p,maxmin='max',getall=False):
 
     raise InvalidTrajectoryError("Trajectory doesn't go through path")
 
-    
+
     return 0
 
 
@@ -64,7 +69,7 @@ def coursetime_paths(data,paths,finalmaxmin='min'):
     entrytime = data['time'].max()
     entrydistance = data['cum_dist'].max()
     coursecompleted = False
-    
+
     # corner case - empty list of paths
     if len(paths) == 0:
         return 0,True

rowers/models.py

@@ -2196,6 +2196,10 @@ from django.core.validators import RegexValidator,validate_email
 
 class StandardCollection(models.Model):
     name = models.CharField(max_length=150)
+    manager = models.ForeignKey(User, null=True,on_delete=models.CASCADE)
+
+    def __str__(self):
+        return self.name
 
 class CourseStandard(models.Model):
     name = models.CharField(max_length=150)
@@ -2211,6 +2215,14 @@ class CourseStandard(models.Model):
     skillclass = models.CharField(max_length=150)
     standardcollection = models.ForeignKey(StandardCollection,on_delete=models.CASCADE)
 
+    class Meta:
+        unique_together = ('name','sex','agemin',
+                           'agemax','boatclass','boattype','weightclass','adaptiveclass',
+                           'skillclass','standardcollection')
+
+    def __str__(self):
+        return self.name
+
 registerchoices = (
     ('windowstart','Start of challenge Window'),
     ('windowend','End of challenge Window'),

rowers/scoring.py

@@ -0,0 +1,102 @@
+from rowers.models import StandardCollection,CourseStandard
+
+import pandas as pd
+import arrow
+import datetime
+
+def save_scoring(name,user,filename,id=0):
+    if id==0:
+        collection = StandardCollection(name=name,manager=user)
+        collection.save()
+        standards = CourseStandard.objects.filter(standardcollection=collection)
+        for standard in standards:
+            standard.delete()
+    else:
+        try:
+            collection = StandardCollection.objects.get(id=id)
+            collection.name = name
+            collection.save()
+
+        except StandardCollection.DoesNotExist:
+            return 0
+
+    try:
+        df = pd.read_csv(filename)
+    except:
+        return 0
+
+    df = df.drop_duplicates(['Name'])
+
+    for index, row in df.iterrows():
+        try:
+            name = row['Name']
+        except KeyError:
+            continue
+
+        try:
+            coursedistance = row['CourseDistance']
+            coursetime = row['CourseStandard']
+            t = datetime.datetime.strptime(coursetime,'%M:%S.%f')
+            delta = datetime.timedelta(hours=t.hour, minutes=t.minute, seconds=t.second,microseconds=t.microsecond)
+            seconds = delta.total_seconds()
+
+            coursestandard = coursedistance/seconds
+        except KeyError:
+            continue
+
+        try:
+            agemin = row['MinAge']
+            agemax = row['MaxAge']
+            agemin = int(agemin)
+            agemax = int(agemax)
+        except KeyError:
+            agemin = 0
+            agemax = 120
+
+        try:
+            boatclass = row['BoatClass']
+        except KeyError:
+            boatclass = 'water'
+
+        try:
+            boattype = row['BoatType']
+        except KeyError:
+            boattype = '1x'
+
+        try:
+            sex = row['Gender']
+        except KeyError:
+            sex = 'F'
+
+        try:
+            weightclass = row['WeightClass']
+        except KeyError:
+            weightclass = 'hwt'
+
+        try:
+            adaptiveclass = row['AdaptiveClass']
+        except KeyError:
+            adaptiveclass = None
+
+        try:
+            skillclass = row['SkillClass']
+        except KeyError:
+            skillclass = 'Open'
+
+        # some testing
+        standard = CourseStandard(
+            name=name,
+            coursedistance=coursedistance,
+            coursestandard=coursestandard,
+            agemin=agemin,
+            agemax=agemax,
+            boatclass=boatclass,
+            boattype=boattype,
+            sex=sex,
+            weightclass=weightclass,
+            adaptiveclass=adaptiveclass,
+            skillclass=skillclass,
+            standardcollection = collection,
+        )
+
+        standard.save()