Offline CP calculations for OTW

A new table in the database with precalculated CP values. The data
are updated through RQ/Celery asynchronous functions

rowers/dataprep.py

@@ -17,6 +17,7 @@ from django.utils import timezone
 from time import strftime, strptime, mktime, time, daylight
 import arrow
 from django.utils.timezone import get_current_timezone
+
 thetimezone = get_current_timezone()
 from rowingdata import (
     TCXParser, RowProParser, ErgDataParser,
@@ -40,7 +41,7 @@ import itertools
 import math
 from tasks import (
     handle_sendemail_unrecognized, handle_sendemail_breakthrough,
-    handle_sendemail_hard
+    handle_sendemail_hard, handle_updatecp
 )
 
 from django.conf import settings
@@ -425,6 +426,112 @@ def paceformatsecs(values):
 
     return out
 
+def getcpdata_sql(rower_id):
+    engine = create_engine(database_url, echo=False)
+    query = sa.text('SELECT delta,cp from cpdata WHERE user={rower_id};'.format(
+        rower_id=rower_id
+        ))
+    connection = engine.raw_connection()
+    df = pd.read_sql_query(query, engine)
+
+    return df
+
+def deletecpdata_sql(rower_id):
+    engine = create_engine(database_url, echo=False)
+    query = sa.text('DELETE from cpdata WHERE user={rower_id};'.format(
+        rower_id=rower_id
+        ))
+    with engine.connect() as conn, conn.begin():
+        try:
+            result = conn.execute(query)
+        except:
+            print "Database locked"
+    conn.close()
+    engine.dispose()
+
+    
+    
+def updatecpdata_sql(rower_id,delta,cp):
+    deletecpdata_sql(rower_id)
+    df = pd.DataFrame(
+        {
+            'delta':delta,
+            'cp':cp,
+            'user':rower_id
+        }
+    )
+
+    engine = create_engine(database_url, echo=False)
+    with engine.connect() as conn, conn.begin():
+        df.to_sql('cpdata', engine, if_exists='append', index=False)
+    conn.close()
+    engine.dispose()
+
+
+def runcpupdate(rower):
+    startdate = timezone.now()-datetime.timedelta(days=365)
+    enddate = timezone.now()+datetime.timedelta(days=5)
+    theworkouts = Workout.objects.filter(user=rower,rankingpiece=True,
+				          workouttype='water',
+				          startdatetime__gte=startdate,
+					  startdatetime__lte=enddate)
+
+    theids = [w.id for w in theworkouts]
+
+
+    if settings.DEBUG:
+        res = handle_updatecp.delay(rower.id,theids,debug=True)
+    else:
+        res = queue.enqueue(handle_updatecp,rower.id,theids)
+
+    
+def fetchcp(rower,theworkouts):
+    # get all power data from database (plus workoutid)
+    theids = [int(w.id) for w in theworkouts]
+    columns = ['power','workoutid','time']
+    df = getsmallrowdata_db(columns,ids=theids)
+
+    dfgrouped = df.groupby(['workoutid'])
+    avgpower2 = dict(dfgrouped.mean()['power'].astype(int))
+
+    cpdf = getcpdata_sql(rower.id)
+
+    if not cpdf.empty:
+        return cpdf['delta'],cpdf['cp'],avgpower2
+    else:
+        if settings.DEBUG:
+            res = handle_updatecp.delay(rower.id,theids,debug=True)
+        else:
+            res = queue.enqueue(handle_updatecp,rower.id,theids)
+        return [],[],avgpower2
+
+    #  below is redundant
+    thesecs = []
+
+    for w in theworkouts:
+        timesecs = 3600*w.duration.hour
+	timesecs += 60*w.duration.minute
+	timesecs += w.duration.second
+	timesecs += 1.e-5*w.duration.microsecond
+	
+	thesecs.append(timesecs)
+
+    if len(thesecs) != 0:
+        maxt = 1.05*pd.Series(thesecs).max()
+    else:
+        maxt = 1000.
+
+        
+    logarr = datautils.getlogarr(maxt)
+
+        
+    delta,cpvalue,avgpower = datautils.getcp(dfgrouped,logarr)
+
+    updatecpdata_sql(rower.id,delta,cpvalue)
+
+    return delta,cpvalue,avgpower2
+
+
 # Processes painsled CSV file to database
 
 

rowers/dataprepnodjango.py

@@ -489,9 +489,9 @@ def testdata(time,distance,pace,spm):
     return t1 and t2 and t3 and t4
 
 
-def getsmallrowdata_db(columns,ids=[]):
+def getsmallrowdata_db(columns,ids=[],debug=False):
 
-    data = read_cols_df_sql(ids,columns)
+    data = read_cols_df_sql(ids,columns,debug=debug)
 
     return data
         
@@ -548,6 +548,44 @@ def read_df_sql(id,debug=False):
     engine.dispose()
     return df
 
+def deletecpdata_sql(rower_id,debug=False):
+    if debug:
+        engine = create_engine(database_url_debug, echo=False)
+    else:
+        engine = create_engine(database_url, echo=False)
+
+    query = sa.text('DELETE from cpdata WHERE user={rower_id};'.format(
+        rower_id=rower_id
+        ))
+    with engine.connect() as conn, conn.begin():
+        try:
+            result = conn.execute(query)
+        except:
+            print "Database locked"
+    conn.close()
+    engine.dispose()
+
+    
+    
+def updatecpdata_sql(rower_id,delta,cp,debug=False):
+    deletecpdata_sql(rower_id,debug=debug)
+    df = pd.DataFrame(
+        {
+            'delta':delta,
+            'cp':cp,
+            'user':rower_id
+        }
+    )
+
+    if debug:
+        engine = create_engine(database_url_debug, echo=False)
+    else:
+        engine = create_engine(database_url, echo=False)
+
+    with engine.connect() as conn, conn.begin():
+        df.to_sql('cpdata', engine, if_exists='append', index=False)
+    conn.close()
+    engine.dispose()
 
 
 

rowers/datautils.py

@@ -107,6 +107,7 @@ def getsinglecp(df):
 
     return delta,cpvalue,avgpower
 
+
 def getcp(dfgrouped,logarr):
     delta = []
     cpvalue = []
@@ -206,3 +207,4 @@ def getmaxwattinterval(tt,ww,i):
         deltat = 0
 
     return deltat,wmax
+

rowers/models.py

@@ -641,7 +641,18 @@ attrs.update(strokedatafields)
 StrokeData = type(str('StrokeData'), (models.Model,),
                   attrs
                   )
-    
+
+# Storing data for the OTW CP chart
+class cpdata(models.Model):
+    delta = models.IntegerField(default=0)
+    cp = models.FloatField(default=0)
+    user = models.IntegerField(default=0)
+
+    class Meta:
+        db_table = 'cpdata'
+        index_together = ['user']
+        app_label = 'rowers'
+
 # A wrapper around the png files
 class GraphImage(models.Model):
     filename = models.CharField(default='',max_length=150,blank=True,null=True)

rowers/tasks.py

@@ -26,7 +26,7 @@ from utils import deserialize_list
 
 from rowers.dataprepnodjango import (
     update_strokedata, new_workout_from_file,
-    getsmallrowdata_db, 
+    getsmallrowdata_db, updatecpdata_sql
 )
 
 from django.core.mail import send_mail, EmailMessage
@@ -402,7 +402,26 @@ def handle_otwsetpower(f1, boattype, weightvalue,
 
 # This function generates all the static (PNG image) plots
 
+@app.task
+def handle_updatecp(rower_id,workoutids,debug=False):
+    columns = ['power','workoutid','time']
+    df = getsmallrowdata_db(columns,ids=workoutids,debug=debug)
+    dfgrouped = df.groupby(['workoutid'])
 
+    if not df.empty:
+        maxt = 1.05*df['time'].max()/1000.
+    else:
+        maxt = 1000.
+
+    logarr = datautils.getlogarr(maxt)
+
+        
+    delta,cpvalue,avgpower = datautils.getcp(dfgrouped,logarr)
+
+    updatecpdata_sql(rower_id,delta,cpvalue,debug=debug)
+
+    return 1
+        
 @app.task
 def handle_makeplot(f1, f2, t, hrdata, plotnr, imagename):
 

rowers/views.py

@@ -98,7 +98,8 @@ from rowers.rows import handle_uploaded_file
 from rowers.tasks import handle_makeplot,handle_otwsetpower,handle_sendemailtcx,handle_sendemailcsv
 from rowers.tasks import (
     handle_sendemail_unrecognized,handle_sendemailnewcomment,
-    handle_sendemailnewresponse, handle_updatedps
+    handle_sendemailnewresponse, handle_updatedps,
+    handle_updatecp
     )
 
 from scipy.signal import savgol_filter
@@ -2977,6 +2978,10 @@ def workout_update_cp_view(request,id=0):
     row.rankingpiece = True
     row.save()
 
+    r = getrower(request.user)
+
+    dataprep.runcpupdate(r)
+    
     url = reverse(otwrankings_view)
 
     return HttpResponseRedirect(url)
@@ -3089,39 +3094,12 @@ def otwrankings_view(request,theuser=0,
 					  startdatetime__lte=enddate)
 
 
-    # get all power data from database (plus workoutid)
+    delta,cpvalue,avgpower = dataprep.fetchcp(r,theworkouts)
-    theids = [int(w.id) for w in theworkouts]
-    columns = ['power','workoutid','time']
-    df = dataprep.getsmallrowdata_db(columns,ids=theids)
-
-    thesecs = []
-    
-    for w in theworkouts:
-        timesecs = 3600*w.duration.hour
-	timesecs += 60*w.duration.minute
-	timesecs += w.duration.second
-	timesecs += 1.e-5*w.duration.microsecond
-	
-	thesecs.append(timesecs)
-
-
-    if len(thesecs) != 0:
-        maxt = 1.05*pd.Series(thesecs).max()
-    else:
-        maxt = 1000.
-
-        
-    logarr = datautils.getlogarr(maxt)
-
-    dfgrouped = df.groupby(['workoutid'])
-    delta,cpvalue,avgpower = datautils.getcp(dfgrouped,logarr)
     
     powerdf = pd.DataFrame({
         'Delta':delta,
         'CP':cpvalue,
         })
-
-
     
     powerdf = powerdf[powerdf['CP']>0]
     powerdf.dropna(axis=0,inplace=True)
@@ -3203,7 +3181,7 @@ def otwrankings_view(request,theuser=0,
 
 
     del form.fields["pieceunit"]
-            
+
     messages.error(request,message)
     return render(request, 'otwrankings.html',
 		  {'rankingworkouts':theworkouts,
@@ -6655,6 +6633,10 @@ def workout_edit_view(request,id=0,message="",successmessage=""):
                 r.write_csv(row.csvfilename,gzip=True)
                 dataprep.update_strokedata(id,r.df)
                 successmessage = "Changes saved"
+
+                if rankingpiece:
+                    dataprep.runcpupdate(row.user)
+                
                 messages.info(request,successmessage)
                 url = reverse(workout_edit_view,
                               kwargs = {