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Sander Roosendaal
2022-02-15 08:05:12 +01:00
parent 5b3d7fcf2c
commit 8af7ac8af4
71 changed files with 19992 additions and 19476 deletions
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132
rowers/alerts.py
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@@ -1,25 +1,27 @@
from rowers.models import Alert, Condition, User, Rower, Workout
from rowers.teams import coach_getcoachees
from rowers.dataprep import getsmallrowdata_db,getrowdata_db
from rowers.dataprep import getsmallrowdata_db, getrowdata_db
import datetime
## BASIC operations
# BASIC operations
# create alert
def create_alert(manager, rower, measured,period=7, emailalert=True,
reststrokes=False, workouttype='water',boattype='1x',
name='',**kwargs):
def create_alert(manager, rower, measured, period=7, emailalert=True,
reststrokes=False, workouttype='water', boattype='1x',
name='', **kwargs):
# check if manager is coach of rower. If not return 0
if manager.rower != rower: # pragma: no cover
if manager.rower != rower: # pragma: no cover
if rower not in coach_getcoachees(manager.rower):
return 0,'You are not allowed to create this alert'
return 0, 'You are not allowed to create this alert'
m = Condition(
metric = measured['metric'],
value1 = measured['value1'],
value2 = measured['value2'],
metric=measured['metric'],
value1=measured['value1'],
value2=measured['value2'],
condition=measured['condition']
)
)
m.save()
@@ -41,23 +43,21 @@ def create_alert(manager, rower, measured,period=7, emailalert=True,
for f in filters:
if f['metric'] and f['condition']:
m = Condition(
metric = f['metric'],
value1 = f['value1'],
value2 = f['value2'],
condition = f['condition']
metric=f['metric'],
value1=f['value1'],
value2=f['value2'],
condition=f['condition']
)
m.save()
alert.filter.add(m)
return alert.id,'Your alert was created'
return alert.id, 'Your alert was created'
# update alert
def alert_add_filters(alert,filters):
def alert_add_filters(alert, filters):
for f in alert.filter.all():
alert.filter.remove(f)
f.delete()
@@ -70,10 +70,10 @@ def alert_add_filters(alert,filters):
if condition and metric and value1:
m = Condition(
metric = f['metric'],
value1 = f['value1'],
value2 = f['value2'],
condition = f['condition']
metric=f['metric'],
value1=f['value1'],
value2=f['value2'],
condition=f['condition']
)
m.save()
@@ -85,77 +85,79 @@ def alert_add_filters(alert,filters):
# get alert stats
# nperiod = 0: current period, i.e. next_run - n days to today
# nperiod = 1: 1 period ago , i.e. next_run -2n days to next_run -n days
def alert_get_stats(alert,nperiod=0): # pragma: no cover
def alert_get_stats(alert, nperiod=0): # pragma: no cover
# get strokes
workstrokesonly = not alert.reststrokes
startdate = (alert.next_run - datetime.timedelta(days=(nperiod+1)*alert.period-1))
startdate = (alert.next_run -
datetime.timedelta(days=(nperiod+1)*alert.period-1))
enddate = alert.next_run - datetime.timedelta(days=(nperiod)*alert.period)
columns = [alert.measured.metric]
for condition in alert.filter.all():
columns += condition.metric
workouts = Workout.objects.filter(date__gte=startdate,date__lte=enddate,user=alert.rower,
workouttype=alert.workouttype,duplicate=False,
workouts = Workout.objects.filter(date__gte=startdate, date__lte=enddate, user=alert.rower,
workouttype=alert.workouttype, duplicate=False,
boattype=alert.boattype)
ids = [w.id for w in workouts]
df = getsmallrowdata_db(columns,ids=ids,doclean=True,workstrokesonly=workstrokesonly)
df = getsmallrowdata_db(columns, ids=ids, doclean=True,
workstrokesonly=workstrokesonly)
if df.empty:
return {
'workouts':workouts.count(),
'startdate':startdate,
'enddate':enddate,
'nr_strokes':0,
'nr_strokes_qualifying':0,
'percentage':0,
'nperiod':nperiod,
'workouts': workouts.count(),
'startdate': startdate,
'enddate': enddate,
'nr_strokes': 0,
'nr_strokes_qualifying': 0,
'percentage': 0,
'nperiod': nperiod,
'median': 0,
'median_q': 0,
'standard_dev': 0,
}
# check if filters are in columns list
pdcolumns = set(df.columns) # pragma: no cover
pdcolumns = set(df.columns) # pragma: no cover
# drop strokes through filter
if set(columns) <= pdcolumns: # pragma: no cover
if set(columns) <= pdcolumns: # pragma: no cover
for condition in alert.filter.all():
if condition.condition == '>':
mask = df[condition.metric] > condition.value1
df.loc[mask,alert.measured.metric] = np.nan
df.loc[mask, alert.measured.metric] = np.nan
elif condition.condition == '<':
mask = df[condition.metric] < condition.value1
df.loc[mask,alert.measured.metric] = np.nan
df.loc[mask, alert.measured.metric] = np.nan
elif condition.condition == 'between':
mask = df[condition.metric] > condition.value1
mask2 = df[condition.metric] < condition.value2
df.loc[mask & mask2,alert.measured.metric] = np.nan
df.loc[mask & mask2, alert.measured.metric] = np.nan
elif condition.condition == '=':
mask = df[condition.metric] == condition.value1
df.loc[mask,alert.measured.metric] = np.nan
df.loc[mask, alert.measured.metric] = np.nan
df.dropna(inplace=True,axis=0)
else: # pragma: no cover
df.dropna(inplace=True, axis=0)
else: # pragma: no cover
return {
'workouts':workouts.count(),
'startdate':startdate,
'enddate':enddate,
'nr_strokes':0,
'nr_strokes_qualifying':0,
'percentage':0,
'nperiod':nperiod,
'workouts': workouts.count(),
'startdate': startdate,
'enddate': enddate,
'nr_strokes': 0,
'nr_strokes_qualifying': 0,
'percentage': 0,
'nperiod': nperiod,
'median': 0,
'median_q': 0,
'standard_dev': 0,
}
# count strokes
nr_strokes = len(df)
# count qualifying
if alert.measured.condition == '>':
mask = df[alert.measured.metric] > alert.measured.value1
@@ -183,24 +185,26 @@ def alert_get_stats(alert,nperiod=0): # pragma: no cover
std = df[alert.measured.metric].std()
return {
'workouts':workouts.count(),
'startdate':startdate,
'enddate':enddate,
'nr_strokes':nr_strokes,
'nr_strokes_qualifying':nr_strokes_qualifying,
'workouts': workouts.count(),
'startdate': startdate,
'enddate': enddate,
'nr_strokes': nr_strokes,
'nr_strokes_qualifying': nr_strokes_qualifying,
'percentage': percentage,
'nperiod':nperiod,
'median':median,
'median_q':median_q,
'standard_dev':std,
'nperiod': nperiod,
'median': median,
'median_q': median_q,
'standard_dev': std,
}
# run alert report
# check alert permission
def checkalertowner(alert,user):
def checkalertowner(alert, user):
if alert.manager == user:
return True
if alert.rower.user == user: # pragma: no cover
if alert.rower.user == user: # pragma: no cover
return True
return False # pragma: no cover
return False # pragma: no cover