increase test coverage

rowers/stravastuff.py

@@ -468,162 +468,6 @@ def handle_stravaexport(f2,workoutname,stravatoken,description='',
 
     return (res.id,message)
 
-# Create workout data from Strava or Concept2
-# data and create the associated Workout object and save it
-def add_workout_from_data(user,importid,data,strokedata,
-                          source='strava',splitdata=None,
-                          workoutsource='strava'):
-    try:
-        workouttype = mytypes.stravamappinginv[data['type']]
-    except KeyError: # pragma: no cover
-        workouttype = 'other'
-
-    if workouttype.lower() == 'rowing': # pragma: no cover
-        workouttype = 'rower'
-
-    if 'summary_polyline' in data['map'] and workouttype=='rower': # pragma: no cover
-        workouttype = 'water'
-
-    if workouttype not in [x[0] for x in Workout.workouttypes]: # pragma: no cover
-        workouttype = 'other'
-    try:
-        comments = data['comments']
-    except:
-        comments = ' '
-
-    try:
-        thetimezone = tz(data['timezone'])
-    except:
-        thetimezone = 'UTC'
-
-    r = Rower.objects.get(user=user)
-    try:
-        rowdatetime = iso8601.parse_date(data['date_utc'])
-    except KeyError:
-        rowdatetime = iso8601.parse_date(data['start_date'])
-    except ParseError: # pragma: no cover
-        rowdatetime = iso8601.parse_date(data['date'])
-
-
-    try:
-        intervaltype = data['workout_type']
-
-    except KeyError:
-        intervaltype = ''
-
-    try:
-        title = data['name']
-    except KeyError: # pragma: no cover
-        title = ""
-        try:
-            t = data['comments'].split('\n', 1)[0]
-            title += t[:20]
-        except:
-            title = ''
-
-    starttimeunix = arrow.get(rowdatetime).timestamp()
-
-    res = make_cumvalues(0.1*strokedata['t'])
-    cum_time = res[0]
-    lapidx = res[1]
-
-    unixtime = cum_time+starttimeunix
-    seconds = 0.1*strokedata.loc[:,'t']
-
-    nr_rows = len(unixtime)
-
-    try:
-        latcoord = strokedata.loc[:,'lat']
-        loncoord = strokedata.loc[:,'lon']
-        if latcoord.std() == 0 and loncoord.std() == 0 and workouttype == 'water': # pragma: no cover
-            workouttype = 'rower'
-    except: # pragma: no cover
-        latcoord = np.zeros(nr_rows)
-        loncoord = np.zeros(nr_rows)
-        if workouttype == 'water':
-            workouttype = 'rower'
-
-
-
-    try:
-        strokelength = strokedata.loc[:,'strokelength']
-    except: # pragma: no cover
-        strokelength = np.zeros(nr_rows)
-
-    dist2 = 0.1*strokedata.loc[:,'d']
-
-    try:
-        spm = strokedata.loc[:,'spm']
-    except KeyError: # pragma: no cover
-        spm = 0*dist2
-
-    try:
-        hr = strokedata.loc[:,'hr']
-    except KeyError: # pragma: no cover
-        hr = 0*spm
-    pace = strokedata.loc[:,'p']/10.
-    pace = np.clip(pace,0,1e4)
-    pace = pace.replace(0,300)
-
-    velo = 500./pace
-
-    try:
-        power = strokedata.loc[:,'power']
-    except KeyError: # pragma: no cover
-        power = 2.8*velo**3
-
-    #if power.std() == 0 and power.mean() == 0:
-    #    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
-                       })
-
-
-    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
-    csvfilename ='media/{code}_{importid}.csv'.format(
-        importid=importid,
-        code = uuid4().hex[:16]
-        )
-
-    res =  df.to_csv(csvfilename+'.gz',index_label='index',
-                     compression='gzip')
-
-
-    id,message = dataprep.save_workout_database(
-        csvfilename,r,
-        dosmooth=r.dosmooth,
-        workouttype=workouttype,
-        title=title,notes=comments,
-        workoutsource=workoutsource,
-        dosummary=True
-    )
-
-
-    return id,message
 
 def workout_strava_upload(user,w, quick=False,asynchron=True):
     try: