Merge branch 'feature/eff_metric' into develop

rowers/dataprep.py

@@ -211,6 +211,12 @@ def clean_df_stats(datadf,workstrokesonly=True,ignorehr=True,
     except KeyError:
         pass
 
+    try:
+        mask = datadf['efficiency'] < 0.
+        datadf.loc[mask,'efficiency'] = np.nan
+    except KeyError:
+        pass
+        
     try:
         mask = datadf['pace']/1000. < 60.
         datadf.loc[mask,'pace'] = np.nan
@@ -454,7 +460,8 @@ def save_workout_database(f2,r,dosmooth=True,workouttype='rower',
                 if consistencychecks:
                     a_messages.error(r.user,'Failed consistency check: '+key+', autocorrected')
                 else:
-                    a_messages.error(r.user,'Failed consistency check: '+key+', not corrected')
+                    pass
+                    # a_messages.error(r.user,'Failed consistency check: '+key+', not corrected')
     except ZeroDivisionError:
         pass
 
@@ -994,6 +1001,9 @@ def getrowdata_db(id=0,doclean=False):
     else:
         row = Workout.objects.get(id=id)
 
+    if data['efficiency'].mean() == 0 and data['power'].mean() != 0:
+        data = add_efficiency(id=id)
+        
     if doclean:
         data = clean_df_stats(data,ignorehr=True)
 
@@ -1080,6 +1090,7 @@ def read_cols_df_sql(ids,columns):
     # drop columns that are not in offical list
 #    axx = [ax[0] for ax in axes]
     axx = [f.name for f in StrokeData._meta.get_fields()]
+    
     for c in columns:
         if not c in axx:
             columns.remove(c)
@@ -1108,8 +1119,10 @@ def read_cols_df_sql(ids,columns):
             ids = tuple(ids),
         ))
 
+        
     connection = engine.raw_connection()
     df = pd.read_sql_query(query,engine)
+
     df = df.fillna(value=0)
     
     try:
@@ -1253,6 +1266,27 @@ def datafusion(id1,id2,columns,offset):
     
     return df
 
+def add_efficiency(id=0):
+    rowdata,row = getrowdata_db(id=id,doclean=False)
+    power = rowdata['power']
+    pace = rowdata['pace']/1.0e3
+    velo = 500./pace
+    ergpw = 2.8*velo**3
+    efficiency = 100.*ergpw/power
+
+    efficiency = efficiency.replace([-np.inf,np.inf],np.nan)
+    efficiency.fillna(method='ffill')
+    rowdata['efficiency'] = efficiency
+    delete_strokedata(id)
+    if id != 0:
+        rowdata['workoutid'] = id
+        engine = create_engine(database_url, echo=False)
+        with engine.connect() as conn, conn.begin():
+            rowdata.to_sql('strokedata',engine,if_exists='append',index=False)
+        conn.close()
+        engine.dispose()    
+    return rowdata
+
 # This is the main routine.
 # it reindexes, sorts, filters, and smooths the data, then
 # saves it to the stroke_data table in the database
@@ -1394,7 +1428,7 @@ def dataprep(rowdatadf,id=0,bands=True,barchart=True,otwpower=True,
             try:
                 driveenergy = rowdatadf.ix[:,'driveenergy']
             except KeyError:
-                driveenergy = 0*power
+                driveenergy = power*60/spm
         else:
             driveenergy = data['driveenergy']
 
@@ -1423,6 +1457,14 @@ def dataprep(rowdatadf,id=0,bands=True,barchart=True,otwpower=True,
             totalangle = savgol_filter(totalangle,windowsize,3)
             effectiveangle = savgol_filter(effectiveangle,windowsize,3)
 
+        velo = 500./p
+
+        ergpw = 2.8*velo**3
+        efficiency = 100.*ergpw/power
+
+        efficiency = efficiency.replace([-np.inf,np.inf],np.nan)
+        efficiency.fillna(method='ffill')
+            
         data['wash'] = wash
         data['catch'] = catch
         data['slip'] = slip
@@ -1432,6 +1474,7 @@ def dataprep(rowdatadf,id=0,bands=True,barchart=True,otwpower=True,
         data['drivelength'] = drivelength
         data['totalangle'] = totalangle
         data['effectiveangle'] = effectiveangle
+        data['efficiency'] = efficiency
         
     if otwpower:
 	try:

rowers/dataprepnodjango.py

@@ -15,15 +15,32 @@ from sqlalchemy import create_engine
 import sqlalchemy as sa
 
 from rowsandall_app.settings import DATABASES
+#from rowsandall_app.settings_dev import DATABASES
 
 from utils import lbstoN
 
 
-user = DATABASES['default']['USER']
+try:
-password = DATABASES['default']['PASSWORD']
+    user = DATABASES['default']['USER']
-database_name = DATABASES['default']['NAME']
+except KeyError:
-host = DATABASES['default']['HOST']
+    user = ''
-port = DATABASES['default']['PORT']
+try:    
+    password = DATABASES['default']['PASSWORD']
+except KeyError:
+    password = ''
+
+try:
+    database_name = DATABASES['default']['NAME']
+except KeyError:
+    database_name = ''
+try:
+    host = DATABASES['default']['HOST']
+except KeyError:
+    host = ''
+try:
+    port = DATABASES['default']['PORT']
+except KeyError:
+    port = ''
 
 database_url = 'mysql://{user}:{password}@{host}:{port}/{database_name}'.format(
     user=user,
@@ -563,6 +580,10 @@ def smalldataprep(therows,xparam,yparam1,yparam2):
         
 def dataprep(rowdatadf,id=0,bands=True,barchart=True,otwpower=True,
              empower=True,debug=True):
+
+    if rowdatadf.empty:
+        return 0
+    
     rowdatadf.set_index([range(len(rowdatadf))],inplace=True)
     t = rowdatadf.ix[:,'TimeStamp (sec)']
     t = pd.Series(t-rowdatadf.ix[0,'TimeStamp (sec)'])
@@ -576,7 +597,6 @@ def dataprep(rowdatadf,id=0,bands=True,barchart=True,otwpower=True,
     cumdist = rowdatadf.ix[:,'cum_dist']
 
     power = rowdatadf.ix[:,' Power (watts)']
-    
     averageforce = rowdatadf.ix[:,' AverageDriveForce (lbs)']
     drivelength = rowdatadf.ix[:,' DriveLength (meters)']
     try:
@@ -590,7 +610,10 @@ def dataprep(rowdatadf,id=0,bands=True,barchart=True,otwpower=True,
     forceratio = forceratio.fillna(value=0)
     
     f = rowdatadf['TimeStamp (sec)'].diff().mean()
+    if f != 0:
         windowsize = 2*(int(10./(f)))+1
+    else:
+        windowsize = 1
     if windowsize <= 3:
 	windowsize = 5
 
@@ -660,13 +683,48 @@ def dataprep(rowdatadf,id=0,bands=True,barchart=True,otwpower=True,
     if empower:
         try:
             wash = rowdatadf.ix[:,'wash']
+        except KeyError:
+            wash = 0*power
+
+        try:
             catch = rowdatadf.ix[:,'catch']
+        except KeyError:
+            catch = 0*power
+
+        try:
             finish = rowdatadf.ix[:,'finish']
+        except KeyError:
+            finish = 0*power
+
+        try:
             peakforceangle = rowdatadf.ix[:,'peakforceangle']
+        except KeyError:
+            peakforceangle = 0*power
+
+
+        if data['driveenergy'].mean() == 0:
+            try:
                 driveenergy = rowdatadf.ix[:,'driveenergy']
+            except KeyError:
+                driveenergy = power*60/spm
+        else:
+            driveenergy = data['driveenergy']
+
+            
+        arclength = (inboard-0.05)*(np.radians(finish)-np.radians(catch))
+        if arclength.mean()>0:
+            drivelength = arclength
+        elif drivelength.mean() == 0:
             drivelength = driveenergy/(averageforce*4.44822)
+
+        try:
             slip = rowdatadf.ix[:,'slip']
-            if windowsize > 3:
+        except KeyError:
+            slip = 0*power
+        
+        totalangle = finish-catch
+        effectiveangle = finish-wash-catch-slip
+        if windowsize > 3 and windowsize<len(slip):
             wash = savgol_filter(wash,windowsize,3)
             slip = savgol_filter(slip,windowsize,3)
             catch = savgol_filter(catch,windowsize,3)
@@ -674,6 +732,17 @@ def dataprep(rowdatadf,id=0,bands=True,barchart=True,otwpower=True,
             peakforceangle = savgol_filter(peakforceangle,windowsize,3)
             driveenergy = savgol_filter(driveenergy,windowsize,3)
             drivelength = savgol_filter(drivelength,windowsize,3)
+            totalangle = savgol_filter(totalangle,windowsize,3)
+            effectiveangle = savgol_filter(effectiveangle,windowsize,3)
+
+        velo = 500./p
+
+        ergpw = 2.8*velo**3
+        efficiency = 100.*ergpw/power
+
+        efficiency = efficiency.replace([-np.inf,np.inf],np.nan)
+        efficiency.fillna(method='ffill')
+            
         data['wash'] = wash
         data['catch'] = catch
         data['slip'] = slip
@@ -681,10 +750,9 @@ def dataprep(rowdatadf,id=0,bands=True,barchart=True,otwpower=True,
         data['peakforceangle'] = peakforceangle
         data['driveenergy'] = driveenergy
         data['drivelength'] = drivelength
-            data['peakforce'] = peakforce
+        data['totalangle'] = totalangle
-            data['averageforce'] = averageforce
+        data['effectiveangle'] = effectiveangle
-        except KeyError:
+        data['efficiency'] = efficiency
-            pass
         
     if otwpower:
 	try:
@@ -703,11 +771,16 @@ def dataprep(rowdatadf,id=0,bands=True,barchart=True,otwpower=True,
 	ergpace[ergpace == np.inf] = 240.
 	ergpace2 = ergpace.apply(lambda x: timedeltaconv(x))
 
+        efficiency = efficiency.replace([-np.inf,np.inf],np.nan)
+        efficiency.fillna(method='ffill')
+
+
 	data['ergpace'] = ergpace*1e3
 	data['nowindpace'] = nowindpace*1e3
 	data['equivergpower'] = equivergpower
 	data['fergpace'] = nicepaceformat(ergpace2)
 	data['fnowindpace'] = nicepaceformat(nowindpace2)
+        data['efficiency'] = efficiency
 
     data = data.replace([-np.inf,np.inf],np.nan)
     data = data.fillna(method='ffill')

rowers/metrics.py

@@ -22,6 +22,7 @@ axes = (
     ('totalangle', 'Drive Length (deg)',40,140,'pro'),
     ('effectiveangle', 'Effective Drive Length (deg)',40,140,'pro'),
     ('rhythm', 'Stroke Rhythm (%)',20,55,'pro'),
+    ('efficiency', 'OTW efficiency (%)',0,110,'pro'),
      ('None', 'None',0,1,'basic'),
     )
     

rowers/models.py

@@ -536,6 +536,7 @@ class StrokeData(models.Model):
     rhythm = models.FloatField(default=1.0,null=True,verbose_name='Rhythm')
     totalangle = models.FloatField(default=0.0,null=True,verbose_name='Total Stroke Length (deg)')
     effectiveangle = models.FloatField(default=0.0,null=True,verbose_name='Effective Stroke Length (deg)')
+    efficiency = models.FloatField(default=-1,null=True,verbose_name='OTW Efficiency')
     
 # A wrapper around the png files
 class GraphImage(models.Model):

rowers/views.py

@@ -3572,18 +3572,24 @@ def multiflex_view(request,userid=0,
     # prepare data frame
     datadf = dataprep.read_cols_df_sql(ids,fieldlist)
 
+
     datadf = dataprep.clean_df_stats(datadf,workstrokesonly=workstrokesonly)
 
+
     datadf = dataprep.filter_df(datadf,'spm',spmmin,
                                 largerthan=True)
     datadf = dataprep.filter_df(datadf,'spm',spmmax,
                                 largerthan=False)
+
     datadf = dataprep.filter_df(datadf,'driveenergy',workmin,
                                 largerthan=True)
     datadf = dataprep.filter_df(datadf,'driveneergy',workmax,
                                 largerthan=False)
 
+
     datadf.dropna(axis=0,how='any',inplace=True)
+
+
     datemapping = {
         w.id:w.date for w in workouts
     }
@@ -4038,7 +4044,6 @@ def workouts_view(request,message='',successmessage='',
     else:
         activity_enddate = enddate
 
-    print "aap",activity_enddate
         
     if teamid:
         try:
@@ -5631,7 +5636,7 @@ def workout_flexchart3_view(request,*args,**kwargs):
         axchoicespro.pop('totalangle')
         axchoicespro.pop('effectiveangle')
         axchoicespro.pop('peakforceangle')
-        
+        axchoicespro.pop('efficiency')
         
         return render(request,
 		      'flexchart3otw.html',