increase test coverage

rowers/views/importviews.py

@@ -1755,7 +1755,7 @@ def workout_getimportview(request,externalid,source = 'c2',do_async=True):
     if result: # pragma: no cover
         messages.info(request,"Your workout will be imported in the background")
         # this should return to the respective import list page
-    else:
+    else: # pragma: no cover
         messages.error(request,'Error getting the workout')
 
     url = reverse(importlistviews[source])

rowers/views/statements.py

@@ -1273,166 +1273,6 @@ def sendmail(request):
         return HttpResponseRedirect('/rowers/email/')
 
 
-# Create workout data from Strava or Concept2
-# data and create the associated Workout object and save it
-def add_workout_from_strokedata(user,importid,data,strokedata,
-                                source='c2',splitdata=None,
-                                workoutsource='concept2'):
-    try:
-        workouttype = data['type']
-    except KeyError: # pragma: no cover
-        workouttype = 'rower'
-
-    if workouttype not in [x[0] for x in Workout.workouttypes]: # pragma: no cover
-        workouttype = 'other'
-    try:
-        comments = data['comments']
-    except: # pragma: no cover
-        comments = ' '
-
-#    comments = "Imported data \n %s" % comments
-#    comments = "Imported data \n"+comments  # str(comments)
-    try:
-        thetimezone = tz(data['timezone'])
-    except: # pragma: no cover
-        thetimezone = 'UTC'
-
-    r = getrower(user)
-    try:
-        rowdatetime = iso8601.parse_date(data['date_utc'])
-    except KeyError: # pragma: no cover
-        rowdatetime = iso8601.parse_date(data['start_date'])
-    except ParseError: # pragma: no cover
-        rowdatetime = iso8601.parse_date(data['date'])
-
-
-    try:
-        c2intervaltype = data['workout_type']
-
-    except KeyError: # pragma: no cover
-        c2intervaltype = ''
-
-    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
-    # unixtime[0] = starttimeunix
-    seconds = 0.1*strokedata.loc[:,'t']
-
-    nr_rows = len(unixtime)
-
-    try: # pragma: no cover
-        latcoord = strokedata.loc[:,'lat']
-        loncoord = strokedata.loc[:,'lon']
-    except:
-        latcoord = np.zeros(nr_rows)
-        loncoord = np.zeros(nr_rows)
-
-
-    try:
-        strokelength = strokedata.loc[:,'strokelength']
-    except:
-        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:
-        hr = 0*spm
-    pace = strokedata.loc[:,'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
-                       })
-
-
-    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')
-
-
-    # with Concept2
-    if source=='c2':
-        try:
-            totaldist = data['distance']
-            totaltime = data['time']/10.
-        except KeyError: # pragma: no cover
-            totaldist = 0
-            totaltime = 0
-    else: # pragma: no cover
-        totaldist = 0
-        totaltime = 0
-
-    id,message = dataprep.save_workout_database(
-        csvfilename,r,
-        workouttype=workouttype,
-        dosmooth=r.dosmooth,
-        title=title,notes=comments,
-#        totaldist=totaldist,
-#        totaltime=totaltime,
-        workoutsource=workoutsource,
-        dosummary=True
-    )
-
-
-
-    return id,message
-
-
-
-
 def keyvalue_get_default(key,options,def_options): # pragma: no cover
 
     try: