c2stuff.create_async_workout start

works but is not async yet

rowers/dataprepnodjango.py

@@ -1,10 +1,10 @@
 # This is Data prep used for testing purposes (no Django environment)
 # Uses the debug SQLite database for stroke data
 from rowingdata import rowingdata as rrdata
-
+from rowingdata import make_cumvalues
 from rowingdata import rower as rrower
 from rowingdata import main as rmain
-
+from time import strftime
 from pandas import DataFrame,Series
 
 import pandas as pd
@@ -131,6 +131,89 @@ def rdata(file,rower=rrower()):
 
     return res
 
+# Saves C2 stroke data to CSV and database
+def add_c2_stroke_data_db(strokedata,workoutid,starttimeunix,csvfilename,
+                          debug=False):
+
+    res = make_cumvalues(0.1*strokedata['t'])
+    cum_time = res[0]
+    lapidx = res[1]
+
+    unixtime = cum_time+starttimeunix
+    # unixtime[0] = starttimeunix
+    seconds = 0.1*strokedata.ix[:,'t']
+
+    nr_rows = len(unixtime)
+
+    try:
+	latcoord = strokedata.ix[:,'lat']
+	loncoord = strokedata.ix[:,'lon']
+    except:
+	latcoord = np.zeros(nr_rows)
+	loncoord = np.zeros(nr_rows)
+
+
+    try:
+	strokelength = strokedata.ix[:,'strokelength']
+    except:
+	strokelength = np.zeros(nr_rows)
+
+    dist2 = 0.1*strokedata.ix[:,'d']
+
+    try:
+        spm = strokedata.ix[:,'spm']
+    except KeyError:
+        spm = 0*dist2
+        
+    try:
+        hr = strokedata.ix[:,'hr']
+    except KeyError:
+        hr = 0*spm
+    pace = strokedata.ix[:,'p']/10.
+    pace = np.clip(pace,0,1e4)
+    pace = pace.replace(0,300)
+
+    velo = 500./pace
+
+    power = 2.8*velo**3
+    
+    # save csv
+    # Create data frame with all necessary data to write to csv
+    df = pd.DataFrame({'TimeStamp (sec)':unixtime,
+		       ' Horizontal (meters)': dist2,
+		       ' Cadence (stokes/min)':spm,
+		       ' HRCur (bpm)':hr,
+		       ' longitude':loncoord,
+		       ' latitude':latcoord,
+		       ' Stroke500mPace (sec/500m)':pace,
+		       ' Power (watts)':power,
+		       ' DragFactor':np.zeros(nr_rows),
+		       ' DriveLength (meters)':np.zeros(nr_rows),
+		       ' StrokeDistance (meters)':strokelength,
+		       ' DriveTime (ms)':np.zeros(nr_rows),
+		       ' StrokeRecoveryTime (ms)':np.zeros(nr_rows),
+		       ' AverageDriveForce (lbs)':np.zeros(nr_rows),
+		       ' PeakDriveForce (lbs)':np.zeros(nr_rows),
+		       ' lapIdx':lapidx,
+		       ' ElapsedTime (sec)':seconds,
+                       'cum_dist': dist2
+		       })
+
+    
+    df.sort_values(by='TimeStamp (sec)',ascending=True)
+	
+    timestr = strftime("%Y%m%d-%H%M%S")
+    
+
+    # Create CSV file name and save data to CSV file
+
+    res =  df.to_csv(csvfilename,index_label='index',
+                     compression='gzip')
+
+    data = dataprep(df,id=workoutid,bands=False,debug=debug)
+
+    return data
+
 # Processes painsled CSV file to database
 def save_workout_database(f2,r,dosmooth=True,workouttype='rower',
                           dosummary=True,title='Workout',