added add_effiency and eff calc added to otw_physics

rowers/dataprep.py

@@ -460,7 +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
 
@@ -1259,6 +1260,27 @@ 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

rowers/dataprepnodjango.py

@@ -14,16 +14,33 @@ import itertools
 from sqlalchemy import create_engine
 import sqlalchemy as sa
 
-from rowsandall_app.settings import DATABASES
+#from rowsandall_app.settings import DATABASES
+from rowsandall_app.settings_dev import DATABASES
 
 from utils import lbstoN
 
 
-user = DATABASES['default']['USER']
-password = DATABASES['default']['PASSWORD']
-database_name = DATABASES['default']['NAME']
-host = DATABASES['default']['HOST']
-port = DATABASES['default']['PORT']
+try:
+    user = DATABASES['default']['USER']
+except KeyError:
+    user = ''
+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()
-    windowsize = 2*(int(10./(f)))+1
+    if f != 0:
+        windowsize = 2*(int(10./(f)))+1
+    else:
+        windowsize = 1
     if windowsize <= 3:
 	windowsize = 5
 
@@ -674,6 +697,7 @@ 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)
+
             data['wash'] = wash
             data['catch'] = catch
             data['slip'] = slip
@@ -703,11 +727,21 @@ def dataprep(rowdatadf,id=0,bands=True,barchart=True,otwpower=True,
 	ergpace[ergpace == np.inf] = 240.
 	ergpace2 = ergpace.apply(lambda x: timedeltaconv(x))
 
+        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['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')