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added notification to rowing physics

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This commit is contained in:
Sander Roosendaal
2017-06-16 15:41:07 +02:00
parent 81b6d2d919
commit a70a1e98ac
8 changed files with 177 additions and 114 deletions
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125
rowers/dataprep.py
View File

@@ -36,7 +36,7 @@ import pandas as pd
import numpy as np
import itertools
import math
from tasks import handle_sendemail_unrecognized
from tasks import handle_sendemail_unrecognized,handle_sendemail_breakthrough
from django.conf import settings
from sqlalchemy import create_engine
@@ -44,6 +44,7 @@ import sqlalchemy as sa
import sys
import utils
import datautils
from utils import lbstoN
from scipy.interpolate import griddata
@@ -140,107 +141,6 @@ def filter_df(datadf,fieldname,value,largerthan=True):
return datadf
def getsinglecp(df):
thesecs = df['TimeStamp (sec)'].max()-df['TimeStamp (sec)'].min()
if thesecs != 0:
maxt = 2*thesecs
else:
maxt = 1000.
maxlog10 = np.log10(maxt)
logarr = np.arange(50)*maxlog10/50.
logarr = [int(10.**(la)) for la in logarr]
logarr = pd.Series(logarr)
logarr.drop_duplicates(keep='first',inplace=True)
logarr = logarr.values
dfnew = pd.DataFrame({
'time':df['TimeStamp (sec)']-df.ix[0,'TimeStamp (sec)'],
'power':df[' Power (watts)']
})
dfnew['workoutid'] = 0
dfgrouped = dfnew.groupby(['workoutid'])
delta,cpvalue,avgpower = getcp(dfgrouped,logarr)
return delta,cpvalue,avgpower
def getcp(dfgrouped,logarr):
delta = []
cpvalue = []
avgpower = {}
#avgpower[0] = 0
for id,group in dfgrouped:
tt = group['time'].copy()
ww = group['power'].copy()
tmax = tt.max()
newlen = int(tmax/5000.)
if newlen < len(tt):
newt = np.arange(newlen)*tmax/float(newlen)
ww = griddata(tt.values,
ww.values,
newt,method='linear',
rescale=True)
tt = pd.Series(newt)
ww = pd.Series(ww)
try:
avgpower[id] = int(ww.mean())
except ValueError:
avgpower[id] = '---'
if not np.isnan(ww.mean()):
length = len(ww)
dt = []
cpw = []
for i in xrange(length-2):
deltat,wmax = getmaxwattinterval(tt,ww,i)
if not np.isnan(deltat) and not np.isnan(wmax):
dt.append(deltat)
cpw.append(wmax)
dt = pd.Series(dt)
cpw = pd.Series(cpw)
if len(dt):
cpvalues = griddata(dt.values,
cpw.values,
logarr,method='linear',
rescale=True)
for cpv in cpvalues:
cpvalue.append(cpv)
for d in logarr:
delta.append(d)
delta = pd.Series(delta,name='Delta')
cpvalue = pd.Series(cpvalue,name='CP')
return delta,cpvalue,avgpower
def getmaxwattinterval(tt,ww,i):
w_roll = ww.rolling(i+2).mean().dropna()
if len(w_roll):
# now goes with # data points - should be fixed seconds
indexmax = w_roll.idxmax(axis=1)
try:
t_0 = tt.ix[indexmax]
t_1 = tt.ix[indexmax-i]
deltat = 1.0e-3*(t_0-t_1)
wmax = w_roll.ix[indexmax]
except KeyError:
pass
else:
wmax = 0
deltat = 0
return deltat,wmax
def df_resample(datadf):
# time stamps must be in seconds
@@ -527,7 +427,7 @@ def save_workout_database(f2,r,dosmooth=True,workouttype='rower',
isbreakthrough = False
if workouttype == 'water':
delta,cpvalues,avgpower = getsinglecp(row.df)
delta,cpvalues,avgpower = datautils.getsinglecp(row.df)
if utils.isbreakthrough(delta,cpvalues,r.p0,r.p1,r.p2,r.p3):
isbreakthrough = True
@@ -689,16 +589,21 @@ def save_workout_database(f2,r,dosmooth=True,workouttype='rower',
# submit email task to send email about breakthrough workout
if isbreakthrough:
a_messages.info(r.user,'It looks like you have a new breakthrough workout')
if settings.DEBUG:
res = handle_sendemail_breakthrough(w.id,r.user.email,
if settings.DEBUG and r.getemailnotifications:
res = handle_sendemail_breakthrough.delay(w.id,r.user.email,
r.user.first_name,
r.user.last_name)
elif r.getemailnotifications:
try:
res = queuehigh.enqueue(
handle_sendemail_breakthrough(w.id,
r.user.email,
r.user.first_name,
r.user.last_name))
except AttributeError:
pass
else:
res = queuehigh.enqueue(
handle_sendemail_breakthrough(w.id,
r.user.email,
r.user.first_name,
r.user.last_name))
pass
if privacy == 'visible':
ts = Team.objects.filter(rower=r)

109
rowers/datautils.py Normal file
View File

@@ -0,0 +1,109 @@
import pandas as pd
import numpy as np
from scipy.interpolate import griddata
def getsinglecp(df):
thesecs = df['TimeStamp (sec)'].max()-df['TimeStamp (sec)'].min()
if thesecs != 0:
maxt = 2*thesecs
else:
maxt = 1000.
maxlog10 = np.log10(maxt)
logarr = np.arange(50)*maxlog10/50.
logarr = [int(10.**(la)) for la in logarr]
logarr = pd.Series(logarr)
logarr.drop_duplicates(keep='first',inplace=True)
logarr = logarr.values
dfnew = pd.DataFrame({
'time':1000*(df['TimeStamp (sec)']-df.ix[0,'TimeStamp (sec)']),
'power':df[' Power (watts)']
})
dfnew['workoutid'] = 0
dfgrouped = dfnew.groupby(['workoutid'])
delta,cpvalue,avgpower = getcp(dfgrouped,logarr)
return delta,cpvalue,avgpower
def getcp(dfgrouped,logarr):
delta = []
cpvalue = []
avgpower = {}
#avgpower[0] = 0
for id,group in dfgrouped:
tt = group['time'].copy()
ww = group['power'].copy()
tmax = tt.max()
if tmax > 500000:
newlen = int(tmax/5000.)
else:
newlen = len(tt)
if newlen < len(tt):
newt = np.arange(newlen)*tmax/float(newlen)
ww = griddata(tt.values,
ww.values,
newt,method='linear',
rescale=True)
tt = pd.Series(newt)
ww = pd.Series(ww)
try:
avgpower[id] = int(ww.mean())
except ValueError:
avgpower[id] = '---'
if not np.isnan(ww.mean()):
length = len(ww)
dt = []
cpw = []
for i in xrange(length-2):
deltat,wmax = getmaxwattinterval(tt,ww,i)
if not np.isnan(deltat) and not np.isnan(wmax):
dt.append(deltat)
cpw.append(wmax)
dt = pd.Series(dt)
cpw = pd.Series(cpw)
if len(dt):
cpvalues = griddata(dt.values,
cpw.values,
logarr,method='linear',
rescale=True)
for cpv in cpvalues:
cpvalue.append(cpv)
for d in logarr:
delta.append(d)
delta = pd.Series(delta,name='Delta')
cpvalue = pd.Series(cpvalue,name='CP')
return delta,cpvalue,avgpower
def getmaxwattinterval(tt,ww,i):
w_roll = ww.rolling(i+2).mean().dropna()
if len(w_roll):
# now goes with # data points - should be fixed seconds
indexmax = w_roll.idxmax(axis=1)
try:
t_0 = tt.ix[indexmax]
t_1 = tt.ix[indexmax-i]
deltat = 1.0e-3*(t_0-t_1)
wmax = w_roll.ix[indexmax]
except KeyError:
pass
else:
wmax = 0
deltat = 0
return deltat,wmax

5
rowers/models.py
View File

@@ -232,6 +232,9 @@ class Rower(models.Model):
('hidden','Hidden'),
)
getemailnotifications = models.BooleanField(default=True,
verbose_name='Receive email notifications')
rowerplan = models.CharField(default='basic',max_length=30,
choices=plans)
@@ -746,7 +749,7 @@ class RowerPowerZonesForm(ModelForm):
class AccountRowerForm(ModelForm):
class Meta:
model = Rower
fields = ['weightcategory']
fields = ['weightcategory','getemailnotifications']
class UserForm(ModelForm):
class Meta:

11
rowers/tasks.py
View File

@@ -69,6 +69,8 @@ def handle_sendemail_breakthrough(workoutid,useremail,userfirstname,userlastname
message += str(workoutid)
message += "/updatecp\n\n"
message += "To opt out of these email notifications, deselect the checkbox on your Profile page under Account Information.\n\n"
message += "Best Regards, the Rowsandall Team"
email = EmailMessage(subject, message,
@@ -79,7 +81,6 @@ def handle_sendemail_breakthrough(workoutid,useremail,userfirstname,userlastname
res = email.send()
# remove tcx file
os.remove(unrecognizedfile)
return 1
@@ -177,7 +178,7 @@ def handle_sendemailcsv(first_name,last_name,email,csvfile):
# Calculate wind and stream corrections for OTW rowing
@app.task
def handle_otwsetpower(f1,boattype,weightvalue,
first_name,last_name,email,workoutid,
first_name,last_name,email,workoutid,ps=[1,1,1,1],
debug=False):
try:
rowdata = rdata(f1)
@@ -219,6 +220,12 @@ def handle_otwsetpower(f1,boattype,weightvalue,
rowdata.write_csv(f1,gzip=True)
update_strokedata(workoutid,rowdata.df,debug=debug)
delta,cpvalues,avgpower = datautils.getsinglecp(rowdata.df)
if utils.isbreakthrough(delta,cpvalues,ps[0],ps[1],ps[2],ps[3]):
handle_sendemail_breakthrough(workoutid,email,
first_name,
last_name)
# send email
fullemail = first_name + " " + last_name + " " + "<" + email + ">"
subject = "Your Rowsandall OTW calculations are ready"

12
rowers/tests.py
View File

@@ -68,6 +68,9 @@ class C2Objects(DjangoTestCase):
u = User.objects.create_user('john',
'sander@ds.ds',
'koeinsloot')
u.first_name = 'John'
u.last_name = 'Sander'
u.save()
r = Rower.objects.create(user=u)
res = add_workout_from_strokedata(u,1,data,strokedata,source='c2')
@@ -88,6 +91,9 @@ class C2Objects(DjangoTestCase):
u = User.objects.create_user('john',
'sander@ds.ds',
'koeinsloot')
u.first_name = 'John'
u.last_name = 'Sander'
u.save()
r = Rower.objects.create(user=u)
res = add_workout_from_strokedata(u,1,data,strokedata,source='c2')
@@ -162,6 +168,9 @@ class StravaObjects(DjangoTestCase):
u = User.objects.create_user('john',
'sander@ds.ds',
'koeinsloot')
u.first_name = 'John'
u.last_name = 'Sander'
u.save()
r = Rower.objects.create(user=u)
res = add_workout_from_strokedata(u,1,workoutsummary,strokedata,
@@ -235,6 +244,9 @@ class StravaObjects(DjangoTestCase):
u = User.objects.create_user('john',
'sander@ds.ds',
'koeinsloot')
u.first_name = 'John'
u.last_name = 'Sander'
u.save()
r = Rower.objects.create(user=u)
res = add_workout_from_strokedata(u,1,workoutsummary,strokedata,

1
rowers/urls.py
View File

@@ -183,6 +183,7 @@ urlpatterns = [
url(r'^workout/compare/(?P<id>\d+)/(?P<startdatestring>\d+-\d+-\d+)/(?P<enddatestring>\w+.*)$',views.workout_comparison_list),
url(r'^workout/(?P<id>\d+)/edit$',views.workout_edit_view),
url(r'^workout/(?P<id>\d+)/setprivate$',views.workout_setprivate_view),
url(r'^workout/(?P<id>\d+)/updatecp$',views.workout_update_cp_view),
url(r'^workout/(?P<id>\d+)/makepublic$',views.workout_makepublic_view),
url(r'^workout/(?P<id>\d+)/geeky$',views.workout_geeky_view),
url(r'^workout/(?P<id>\d+)/advanced$',views.workout_advanced_view),

1
rowers/utils.py
View File

@@ -77,6 +77,7 @@ def geo_distance(lat1,lon1,lat2,lon2):
def isbreakthrough(delta,cpvalues,p0,p1,p2,p3):
pwr = p0/(1+delta/p2)
pwr += p1/(1+delta/p3)

27
rowers/views.py
View File

@@ -274,6 +274,8 @@ from utils import (
str2bool
)
import datautils
from rowers.models import checkworkoutuser
# Check if a user is a Coach member
@@ -2778,6 +2780,27 @@ def rankings_view(request,theuser=0,
'teams':get_my_teams(request.user),
})
@user_passes_test(ispromember,login_url="/",redirect_field_name=None)
def workout_update_cp_view(request,id=0):
try:
row = Workout.objects.get(id=id)
except Workout.DoesNotExist:
raise Http404("Workout doesn't exist")
if (checkworkoutuser(request.user,row)==False):
message = "You are not allowed to edit this workout"
messages.error(request,message)
url = reverse(workouts_view)
return HttpResponseRedirect(url)
row.rankingpiece = True
row.save()
url = reverse(otwrankings_view)
return HttpResponseRedirect(url)
# Show ranking distances including predicted paces
@user_passes_test(ispromember,login_url="/",redirect_field_name=None)
def otwrankings_view(request,theuser=0,
@@ -2919,7 +2942,7 @@ def otwrankings_view(request,theuser=0,
dfgrouped = df.groupby(['workoutid'])
delta,cpvalue,avgpower = dataprep.getcp(dfgrouped,logarr)
delta,cpvalue,avgpower = datautils.getcp(dfgrouped,logarr)
powerdf = pd.DataFrame({
@@ -7779,6 +7802,7 @@ def rower_edit_view(request,message=""):
last_name = ucd['last_name']
email = ucd['email']
weightcategory = cd['weightcategory']
getemailnotifications = cd['getemailnotifications']
u = request.user
if len(first_name):
u.first_name = first_name
@@ -7788,6 +7812,7 @@ def rower_edit_view(request,message=""):
u.save()
r = getrower(u)
r.weightcategory = weightcategory
r.getemailnotifications = getemailnotifications
r.save()
form = RowerForm(instance=r)
powerform = RowerPowerForm(instance=r)