sander/rowsandall
Private
Public Access
1
0
Fork 0
Code Activity

does Alternative OTE ranking

Browse Source 
added an OTE ranking piece calculator based on manually added ranking
instead of automatically detected ranking
This commit is contained in:
Sander Roosendaal
2017-10-26 22:53:02 +02:00
parent 0f5c49de62
commit 29243516ae
8 changed files with 295 additions and 18 deletions
Download Patch File Download Diff File Expand all files Collapse all files

43
rowers/dataprep.py
View File

@@ -473,21 +473,37 @@ def updatecpdata_sql(rower_id,delta,cp,table='cpdata',distance=[]):
engine.dispose()
def runcpupdate(rower):
def runcpupdate(rower,type='water'):
startdate = timezone.now()-datetime.timedelta(days=365)
enddate = timezone.now()+datetime.timedelta(days=5)
theworkouts = Workout.objects.filter(user=rower,rankingpiece=True,
workouttype='water',
startdatetime__gte=startdate,
startdatetime__lte=enddate)
if type == 'water':
theworkouts = Workout.objects.filter(
user=rower,rankingpiece=True,
workouttype='water',
startdatetime__gte=startdate,
startdatetime__lte=enddate
)
table = 'cpdata'
else:
theworkouts = Workout.objects.filter(
user=rower,rankingpiece=True,
workouttype__in=[
'rower',
'dynamic',
'slides'
],
startdatetime__gte=startdate,
startdatetime__lte=enddate
)
table = 'cpergdata'
theids = [w.id for w in theworkouts]
if settings.DEBUG:
res = handle_updatecp.delay(rower.id,theids,debug=True)
res = handle_updatecp.delay(rower.id,theids,debug=True,table=table)
else:
res = queue.enqueue(handle_updatecp,rower.id,theids)
res = queue.enqueue(handle_updatecp,rower.id,theids,table=table)
def fetchcperg(rower,theworkouts):
theids = [int(w.id) for w in theworkouts]
@@ -502,24 +518,29 @@ def fetchcperg(rower,theworkouts):
return cpdf
def fetchcp(rower,theworkouts):
def fetchcp(rower,theworkouts,table='cpdata'):
# get all power data from database (plus workoutid)
theids = [int(w.id) for w in theworkouts]
columns = ['power','workoutid','time']
df = getsmallrowdata_db(columns,ids=theids)
if df.empty:
avgpower2 = {}
for id in theids:
avgpower2[id] = 0
return pd.Series([]),pd.Series([]),avgpower2
dfgrouped = df.groupby(['workoutid'])
avgpower2 = dict(dfgrouped.mean()['power'].astype(int))
cpdf = getcpdata_sql(rower.id)
cpdf = getcpdata_sql(rower.id,table=table)
if not cpdf.empty:
return cpdf['delta'],cpdf['cp'],avgpower2
else:
if settings.DEBUG:
res = handle_updatecp.delay(rower.id,theids,debug=True)
res = handle_updatecp.delay(rower.id,theids,debug=True,table=table)
else:
res = queue.enqueue(handle_updatecp,rower.id,theids)
res = queue.enqueue(handle_updatecp,rower.id,theids,table=table)
return [],[],avgpower2