further cleaning up

rowers/tasks.py

@@ -2182,85 +2182,6 @@ def handle_updateergcp(rower_id,workoutfilenames,debug=False,**kwargs):
 
     return 1
 
-def cp_from_workoutids(workoutids,debug=False):
-    columns = ['power','workoutid','time']
-    df = getsmallrowdata_db(columns,ids=workoutids,debug=debug)
-    df.dropna(inplace=True,axis=0)
-
-    if df.empty: # pragma: no cover
-        # change this
-        return 0,0,0
-
-    # df is not empty. We continue
-    dfgrouped = df.groupby(['workoutid'])
-    maxt = 1.05*df['time'].max()/1000.
-
-    logarr = datautils.getlogarr(maxt)
-    data = []
-
-    for id in workoutids:
-        cpfile = 'media/cpdata_{id}.parquet.gz'.format(id=id)
-        try:
-            df = pd.read_parquet(cpfile)
-            df['workout'] = str(id)
-            data.append(df)
-        except: # pragma: no cover
-            pass # ignore for now
-
-    if len(data) == 0: # pragma: no cover
-        return 0,0,0
-    if len(data)>1: # pragma: no cover
-        df = pd.concat(data,axis=0)
-
-
-    df = df[df['cp'] == df.groupby(['delta'])['cp'].transform('max')]
-    df = df.sort_values(['delta']).reset_index()
-
-    powerdf = pd.DataFrame({
-        'Delta':df['delta'],
-        'CP':df['cp'],
-        })
-
-    powerdf = powerdf[powerdf['CP']>0]
-    powerdf.dropna(axis=0,inplace=True)
-    powerdf.sort_values(['Delta','CP'],ascending=[1,0],inplace=True)
-    powerdf.drop_duplicates(subset='Delta',keep='first',inplace=True)
-
-    p1,fitt,fitpower,ratio = datautils.cpfit(powerdf)
-    # This is code duplication from datautils -- correct asap
-    fitfunc = lambda pars,x: abs(pars[0])/(1+(x/abs(pars[2]))) + abs(pars[1])/(1+(x/abs(pars[3])))
-
-    powerfourmin = fitfunc(p1,240.)
-    powerhour = fitfunc(p1,3600.)
-
-    # 2k power
-    velofourmin = (powerfourmin/2.8)**(1./3.)
-    dfourmin = 240.*velofourmin
-    dratio = 2000./dfourmin
-    pacefourmin = 500./velofourmin
-
-    # assume 5 sec per doubling drop
-    pace2k = pacefourmin + 5.*np.log10(dratio)/np.log10(2.)
-    velo2k = 500./pace2k
-    t2k = 2000./velo2k
-    pwr2k = fitfunc(p1,t2k)
-    velo2 = (pwr2k/2.8)**(1./3.)
-    if np.isnan(velo2) or velo2 <= 0: # pragma: no cover
-        velo2 = 1.0
-
-    t2 = 2000./velo2
-
-    pwr2k = fitfunc(p1,t2)
-
-    velo3 = (pwr2k/2.8)**(1./3.)
-
-    t3 = 2000./velo3
-
-    power2k = fitfunc(p1,t3)
-
-
-    return powerfourmin,power2k,powerhour
-
 
 
 @app.task
@@ -2834,7 +2755,7 @@ def handle_setcp(strokesdf,filename,workoutid,debug=False,**kwargs):
             return 0
         try:
             powermean = strokesdf['power'].mean()
-        except KeyError:
+        except KeyError: # pragma: no cover
             powermean = 0
 
 
@@ -3302,7 +3223,7 @@ def fetch_strava_workout(stravatoken,oauth_data,stravaid,csvfilename,userid,debu
                'resolution': 'medium',}
     url = "https://www.strava.com/api/v3/activities/"+str(stravaid)
     response = requests.get(url,headers=headers)
-    if response.status_code != 200:
+    if response.status_code != 200:  # pragma: no cover
         tstamp = time.localtime()
         timestamp = time.strftime('%b-%d-%Y_%H%M', tstamp)
         with open('strava_webhooks.log','a') as f:
@@ -3329,7 +3250,7 @@ def fetch_strava_workout(stravatoken,oauth_data,stravaid,csvfilename,userid,debu
 
     try:
         startdatetime = workoutsummary['start_date']
-    except KeyError:
+    except KeyError: # pragma: no cover
         startdatetime = timezone.now()
 
     spm = get_strava_stream(None,'cadence',stravaid,authorizationstring=authorizationstring)
@@ -3352,7 +3273,7 @@ def fetch_strava_workout(stravatoken,oauth_data,stravaid,csvfilename,userid,debu
 
     if t is not None:
         nr_rows = len(t)
-    else:
+    else: # pragma: no cover
         try:
             duration = int(workoutsummary['elapsed_time'])
         except KeyError:
@@ -3362,22 +3283,22 @@ def fetch_strava_workout(stravatoken,oauth_data,stravaid,csvfilename,userid,debu
         nr_rows = len(t)
 
 
-    if nr_rows == 0:
+    if nr_rows == 0: # pragma: no cover
         return 0
 
-    if d is None:
+    if d is None: # pragma: no cover
         d = 0*t
 
-    if spm is None:
+    if spm is None: # pragma: no cover
         spm = np.zeros(nr_rows)
 
-    if power is None:
+    if power is None: # pragma: no cover
         power = np.zeros(nr_rows)
 
-    if hr is None:
+    if hr is None: # pragma: no cover
         hr = np.zeros(nr_rows)
 
-    if velo is None:
+    if velo is None: # pragma: no cover
         velo = np.zeros(nr_rows)
 
     dt = np.diff(t).mean()
@@ -3389,10 +3310,10 @@ def fetch_strava_workout(stravatoken,oauth_data,stravaid,csvfilename,userid,debu
         try:
             lat = coords[:,0]
             lon = coords[:,1]
-        except IndexError:
+        except IndexError: # pragma: no cover
             lat = np.zeros(len(t))
             lon = np.zeros(len(t))
-    else:
+    else: # pragma: no cover
         lat = np.zeros(len(t))
         lon = np.zeros(len(t))
 
@@ -3419,13 +3340,13 @@ def fetch_strava_workout(stravatoken,oauth_data,stravaid,csvfilename,userid,debu
 
     try:
         workouttype = mytypes.stravamappinginv[workoutsummary['type']]
-    except KeyError:
+    except KeyError: # pragma: no cover
         workouttype = 'other'
 
-    if workouttype.lower() == 'rowing':
+    if workouttype.lower() == 'rowing': # pragma: no cover
         workouttype = 'rower'
 
-    if 'summary_polyline' in workoutsummary['map'] and workouttype=='rower':
+    if 'summary_polyline' in workoutsummary['map'] and workouttype=='rower': # pragma: no cover
         workouttype = 'water'
 
     try:
@@ -3442,7 +3363,7 @@ def fetch_strava_workout(stravatoken,oauth_data,stravaid,csvfilename,userid,debu
         rowdatetime = iso8601.parse_date(workoutsummary['date_utc'])
     except KeyError:
         rowdatetime = iso8601.parse_date(workoutsummary['start_date'])
-    except ParseError:
+    except ParseError: # pragma: no cover
         rowdatetime = iso8601.parse_date(workoutsummary['date'])
 
 
@@ -3454,7 +3375,7 @@ def fetch_strava_workout(stravatoken,oauth_data,stravaid,csvfilename,userid,debu
 
     try:
         title = workoutsummary['name']
-    except KeyError:
+    except KeyError: # pragma: no cover
         title = ""
         try:
             t = data['comments'].split('\n', 1)[0]
@@ -3476,9 +3397,9 @@ def fetch_strava_workout(stravatoken,oauth_data,stravaid,csvfilename,userid,debu
     try:
         latcoord = strokedata.loc[:,'lat']
         loncoord = strokedata.loc[:,'lon']
-        if latcoord.std() == 0 and loncoord.std() == 0 and workouttype == 'water':
+        if latcoord.std() == 0 and loncoord.std() == 0 and workouttype == 'water': # pragma: no cover
             workouttype = 'rower'
-    except:
+    except: # pragma: no cover
         latcoord = np.zeros(nr_rows)
         loncoord = np.zeros(nr_rows)
         if workouttype == 'water':
@@ -3488,19 +3409,19 @@ def fetch_strava_workout(stravatoken,oauth_data,stravaid,csvfilename,userid,debu
 
     try:
         strokelength = strokedata.loc[:,'strokelength']
-    except:
+    except: # pragma: no cover
         strokelength = np.zeros(nr_rows)
 
     dist2 = 0.1*strokedata.loc[:,'d']
 
     try:
         spm = strokedata.loc[:,'spm']
-    except KeyError:
+    except KeyError: # pragma: no cover
         spm = 0*dist2
 
     try:
         hr = strokedata.loc[:,'hr']
-    except KeyError:
+    except KeyError: # pragma: no cover
         hr = 0*spm
     pace = strokedata.loc[:,'p']/10.
     pace = np.clip(pace,0,1e4)