Reduced data stream to cum_flex

rowers/dataprep.py

@@ -79,6 +79,38 @@ def getrowdata(id=0):
 
     return rowdata,row
 
+
+
+def smalldataprep(therows,xparam,yparam1,yparam2):
+    df = pd.DataFrame()
+    if yparam2 == 'None':
+        yparam2 = 'power'
+    df[xparam] = []
+    df[yparam1] = []
+    df[yparam2] = []
+    df['distance'] = []
+    df['spm'] = []
+    for workout in therows:
+        f1 = workout.csvfilename
+
+        try:
+            rowdata = dataprep(rrdata(f1).df)
+        
+            rowdata = pd.DataFrame({xparam: rowdata[xparam],
+                                    yparam1: rowdata[yparam1],
+                                    yparam2: rowdata[yparam2],
+                                    'distance': rowdata['distance'],
+                                    'spm': rowdata['spm'],
+            }
+            )
+            df = pd.concat([df,rowdata],ignore_index=True)
+        except IOError:
+            pass
+
+    return df
+        
+        
+    
 def dataprep(rowdatadf,bands=False,barchart=False,otwpower=False):
     rowdatadf.set_index([range(len(rowdatadf))],inplace=True)
     t = rowdatadf.ix[:,'TimeStamp (sec)']
@@ -113,7 +145,10 @@ def dataprep(rowdatadf,bands=False,barchart=False,otwpower=False):
 	drivelength = savgol_filter(drivelength,windowsize,3)
         forceratio = savgol_filter(forceratio,windowsize,3)
 
-    t2 = t.fillna(method='ffill').apply(lambda x: timedeltaconv(x))
+    try:
+        t2 = t.fillna(method='ffill').apply(lambda x: timedeltaconv(x))
+    except TypeError:
+        t2 = 0*t
 
     
     p2 = p.fillna(method='ffill').apply(lambda x: timedeltaconv(x))