From fc23750731ce9ec8777777ee69e5d5456f48ace3 Mon Sep 17 00:00:00 2001
From: Sander Roosendaal <roosendaalsander@gmail.com>
Date: Tue, 8 Aug 2017 11:51:41 +0200
Subject: [PATCH] corrected work per stroke error (wasn't calculated when it
 could)

---
 rowers/dataprep.py         |  7 ++-
 rowers/dataprepnodjango.py | 99 ++++++++++++++++++++++++++------------
 rowers/views.py            |  8 ++-
 3 files changed, 81 insertions(+), 33 deletions(-)

diff --git a/rowers/dataprep.py b/rowers/dataprep.py
index f5456122..c1e4684e 100644
--- a/rowers/dataprep.py
+++ b/rowers/dataprep.py
@@ -1090,6 +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)
@@ -1118,10 +1119,12 @@ 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)
 
+    df = df.fillna(value=0)
+    
     try:
         df['peakforce'] = df['peakforce']*lbstoN
     except KeyError:
@@ -1425,7 +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']
 
diff --git a/rowers/dataprepnodjango.py b/rowers/dataprepnodjango.py
index e24580d5..e985de1c 100644
--- a/rowers/dataprepnodjango.py
+++ b/rowers/dataprepnodjango.py
@@ -683,32 +683,76 @@ def dataprep(rowdatadf,id=0,bands=True,barchart=True,otwpower=True,
     if empower:
         try:
             wash = rowdatadf.ix[:,'wash']
-            catch = rowdatadf.ix[:,'catch']
-            finish = rowdatadf.ix[:,'finish']
-            peakforceangle = rowdatadf.ix[:,'peakforceangle']
-            driveenergy = rowdatadf.ix[:,'driveenergy']
-            drivelength = driveenergy/(averageforce*4.44822)
-            slip = rowdatadf.ix[:,'slip']
-            if windowsize > 3:
-                wash = savgol_filter(wash,windowsize,3)
-                slip = savgol_filter(slip,windowsize,3)
-                catch = savgol_filter(catch,windowsize,3)
-                finish = savgol_filter(finish,windowsize,3)
-                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
-            data['finish'] = finish
-            data['peakforceangle'] = peakforceangle
-            data['driveenergy'] = driveenergy
-            data['drivelength'] = drivelength
-            data['peakforce'] = peakforce
-            data['averageforce'] = averageforce
         except KeyError:
-            pass
+            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']
+        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)
+            finish = savgol_filter(finish,windowsize,3)
+            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
+        data['finish'] = finish
+        data['peakforceangle'] = peakforceangle
+        data['driveenergy'] = driveenergy
+        data['drivelength'] = drivelength
+        data['totalangle'] = totalangle
+        data['effectiveangle'] = effectiveangle
+        data['efficiency'] = efficiency
         
     if otwpower:
 	try:
@@ -727,11 +771,6 @@ 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')
 
diff --git a/rowers/views.py b/rowers/views.py
index 00ed647d..e4b00c9c 100644
--- a/rowers/views.py
+++ b/rowers/views.py
@@ -3564,19 +3564,25 @@ 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
     }