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done all except mapmyfitness

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This commit is contained in:
Sander Roosendaal
2018-06-26 16:01:46 +02:00
parent 39c2c23842
commit bc396e62a1
7 changed files with 883 additions and 606 deletions
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177
rowers/c2stuff.py
View File

@@ -15,6 +15,7 @@ from django.utils import timezone
from datetime import datetime
from datetime import timedelta
import time
from time import strftime
# Django
from django.shortcuts import render_to_response
@@ -25,7 +26,7 @@ from django.contrib.auth.models import User
from django.contrib.auth.decorators import login_required
import dataprep
import pytz
from rowingdata import rowingdata
from rowingdata import rowingdata, make_cumvalues
import pandas as pd
import numpy as np
from rowers.models import Rower,Workout
@@ -36,6 +37,8 @@ from requests import Request, Session
from utils import myqueue,uniqify,isprorower, custom_exception_handler, NoTokenError
from uuid import uuid4
from rowers.types import otwtypes
from rowsandall_app.settings import C2_CLIENT_ID, C2_REDIRECT_URI, C2_CLIENT_SECRET
@@ -540,7 +543,7 @@ def make_authorization_url(request):
return HttpResponseRedirect(url)
# Get workout from C2 ID
def get_c2_workout(user,c2id):
def get_workout(user,c2id):
r = Rower.objects.get(user=user)
if (r.c2token == '') or (r.c2token is None):
s = "Token doesn't exist. Need to authorize"
@@ -557,7 +560,24 @@ def get_c2_workout(user,c2id):
url = "https://log.concept2.com/api/users/me/results/"+str(c2id)
s = requests.get(url,headers=headers)
return s
data = s.json()['data']
splitdata = None
if 'workout' in data:
if 'splits' in data['workout']:
splitdata = data['workout']['splits']
if 'intervals' in data['workout']:
splitdata = data['workout']['intervals']
# Check if workout has stroke data, and get the stroke data
if data['stroke_data']:
res2 = get_c2_workout_strokes(user,c2id)
if res2.status_code == 200:
strokedata = pd.DataFrame.from_dict(res2.json()['data'])
else:
strokedata = pd.DataFrame()
return data,strokedata
# Get stroke data belonging to C2 ID
def get_c2_workout_strokes(user,c2id):
@@ -725,3 +745,154 @@ def rower_c2_token_refresh(user):
else:
return None
# Create workout data from Strava or Concept2
# data and create the associated Workout object and save it
def add_workout_from_data(user,importid,data,strokedata,
source='c2',splitdata=None,
workoutsource='concept2'):
try:
workouttype = data['type']
except KeyError:
workouttype = 'rower'
if workouttype not in [x[0] for x in Workout.workouttypes]:
workouttype = 'other'
try:
comments = data['comments']
except:
comments = ' '
try:
thetimezone = tz(data['timezone'])
except:
thetimezone = 'UTC'
r = Rower.objects.get(user=user)
try:
rowdatetime = iso8601.parse_date(data['date_utc'])
except KeyError:
rowdatetime = iso8601.parse_date(data['start_date'])
except ParseError:
rowdatetime = iso8601.parse_date(data['date'])
try:
c2intervaltype = data['workout_type']
except KeyError:
c2intervaltype = ''
try:
title = data['name']
except KeyError:
title = ""
try:
t = data['comments'].split('\n', 1)[0]
title += t[:20]
except:
title = 'Imported'
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.ix[:,'t']
nr_rows = len(unixtime)
try:
latcoord = strokedata.ix[:,'lat']
loncoord = strokedata.ix[:,'lon']
except:
latcoord = np.zeros(nr_rows)
loncoord = np.zeros(nr_rows)
try:
strokelength = strokedata.ix[:,'strokelength']
except:
strokelength = np.zeros(nr_rows)
dist2 = 0.1*strokedata.ix[:,'d']
try:
spm = strokedata.ix[:,'spm']
except KeyError:
spm = 0*dist2
try:
hr = strokedata.ix[:,'hr']
except KeyError:
hr = 0*spm
pace = strokedata.ix[:,'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:
totaldist = 0
totaltime = 0
else:
totaldist = 0
totaltime = 0
id,message = dataprep.save_workout_database(
csvfilename,r,
workouttype=workouttype,
title=title,notes=comments,
workoutsource=workoutsource,
dosummary=True
)
return id,message

222
rowers/runkeeperstuff.py
View File

@@ -12,6 +12,8 @@ from datetime import datetime
import numpy as np
from dateutil import parser
import time
import dateutil
from time import strftime
import math
from math import sin,cos,atan2,sqrt
import os,sys
@@ -29,7 +31,10 @@ from django.contrib.auth.decorators import login_required
from rowingdata import rowingdata
import pandas as pd
from rowers.models import Rower,Workout,checkworkoutuser
from uuid import uuid4
import iso8601
import arrow
from rowers import types
from rowsandall_app.settings import (
C2_CLIENT_ID, C2_REDIRECT_URI, C2_CLIENT_SECRET,
STRAVA_CLIENT_ID, STRAVA_REDIRECT_URI, STRAVA_CLIENT_SECRET,
@@ -38,6 +43,27 @@ from rowsandall_app.settings import (
from utils import geo_distance,ewmovingaverage,NoTokenError, custom_exception_handler
def splitrunkeeperlatlongdata(lijst,tname,latname,lonname):
t = []
lat = []
lon = []
for d in lijst:
t.append(d[tname])
lat.append(d[latname])
lon.append(d[lonname])
return [np.array(t),np.array(lat),np.array(lon)]
def splitrunkeeperdata(lijst,xname,yname):
x = []
y = []
for d in lijst:
x.append(d[xname])
y.append(d[yname])
return [np.array(x),np.array(y)]
import dataprep
# Checks if user has SportTracks token, renews them if they are expired
def runkeeper_open(user):
@@ -75,7 +101,6 @@ def get_token(code):
def make_authorization_url(request):
# Generate a random string for the state parameter
# Save it for use later to prevent xsrf attacks
from uuid import uuid4
state = str(uuid4())
params = {"client_id": RUNKEEPER_CLIENT_ID,
@@ -105,7 +130,7 @@ def get_runkeeper_workout_list(user):
return s
# Get workout summary data by Runkeeper ID
def get_runkeeper_workout(user,runkeeperid):
def get_workout(user,runkeeperid):
r = Rower.objects.get(user=user)
if (r.runkeepertoken == '') or (r.runkeepertoken is None):
return custom_exception_handler(401,s)
@@ -119,7 +144,16 @@ def get_runkeeper_workout(user,runkeeperid):
url = "https://api.runkeeper.com/fitnessActivities/"+str(runkeeperid)
s = requests.get(url,headers=headers)
return s
try:
data = s.json()
except ValueError:
data = {}
strokedata = pd.DataFrame.from_dict({
key: pd.Series(value) for key, value in data.items()
})
return data,strokedata
# Create Workout Data for upload to SportTracks
def createrunkeeperworkoutdata(w):
@@ -328,3 +362,183 @@ def workout_runkeeper_upload(user,w):
return message, rkid
return message,rkid
# Create workout from RunKeeper Data
def add_workout_from_data(user,importid,data,strokedata,source='runkeeper',
workoutsource='runkeeper'):
# To Do - add utcoffset to time
workouttype = data['type']
if workouttype not in [x[0] for x in Workout.workouttypes]:
workouttype = 'other'
try:
comments = data['notes']
except:
comments = ''
try:
utcoffset = tz(data['utcoffset'])
except:
utcoffset = 0
r = Rower.objects.get(user=user)
try:
rowdatetime = iso8601.parse_date(data['start_time'])
except iso8601.ParseError:
try:
rowdatetime = datetime.strptime(data['start_time'],"%Y-%m-%d %H:%M:%S")
rowdatetime = thetimezone.localize(rowdatetime).astimezone(utc)
except ValueError:
try:
rowdatetime = dateutil.parser.parse(data['start_time'])
#rowdatetime = thetimezone.localize(rowdatetime).astimezone(utc)
except:
rowdatetime = datetime.strptime(data['date'],"%Y-%m-%d %H:%M:%S")
rowdatetime = thetimezone.localize(rowdatetime).astimezone(utc)
starttimeunix = arrow.get(rowdatetime).timestamp
#starttimeunix = mktime(rowdatetime.utctimetuple())
starttimeunix += utcoffset*3600
try:
title = data['name']
except:
title = "Imported data"
res = splitrunkeeperdata(data['distance'],'timestamp','distance')
distance = res[1]
times_distance = res[0]
try:
l = data['path']
res = splitrunkeeperlatlongdata(l,'timestamp','latitude','longitude')
times_location = res[0]
latcoord = res[1]
loncoord = res[2]
except:
times_location = times_distance
latcoord = np.zeros(len(times_distance))
loncoord = np.zeros(len(times_distance))
if workouttype in types.otwtypes:
workouttype = 'rower'
try:
res = splitrunkeeperdata(data['cadence'],'timestamp','cadence')
times_spm = res[0]
spm = res[1]
except KeyError:
times_spm = times_distance
spm = 0*times_distance
try:
res = splitrunkeeperdata(data['heart_rate'],'timestamp','heart_rate')
hr = res[1]
times_hr = res[0]
except KeyError:
times_hr = times_distance
hr = 0*times_distance
# create data series and remove duplicates
distseries = pd.Series(distance,index=times_distance)
distseries = distseries.groupby(distseries.index).first()
latseries = pd.Series(latcoord,index=times_location)
try:
latseries = latseries.groupby(latseries.index).first()
except TypeError:
latseries = 0.0*distseries
lonseries = pd.Series(loncoord,index=times_location)
try:
lonseries = lonseries.groupby(lonseries.index).first()
except TypeError:
lonseries = 0.0*distseries
spmseries = pd.Series(spm,index=times_spm)
spmseries = spmseries.groupby(spmseries.index).first()
hrseries = pd.Series(hr,index=times_hr)
try:
hrseries = hrseries.groupby(hrseries.index).first()
except TypeError:
hrseries = 0*distseries
# Create dicts and big dataframe
d = {
' Horizontal (meters)': distseries,
' latitude': latseries,
' longitude': lonseries,
' Cadence (stokes/min)': spmseries,
' HRCur (bpm)' : hrseries,
}
df = pd.DataFrame(d)
df = df.groupby(level=0).last()
cum_time = df.index.values
df[' ElapsedTime (sec)'] = cum_time
velo = df[' Horizontal (meters)'].diff()/df[' ElapsedTime (sec)'].diff()
df[' Power (watts)'] = 0.0*velo
nr_rows = len(velo.values)
df[' DriveLength (meters)'] = np.zeros(nr_rows)
df[' StrokeDistance (meters)'] = np.zeros(nr_rows)
df[' DriveTime (ms)'] = np.zeros(nr_rows)
df[' StrokeRecoveryTime (ms)'] = np.zeros(nr_rows)
df[' AverageDriveForce (lbs)'] = np.zeros(nr_rows)
df[' PeakDriveForce (lbs)'] = np.zeros(nr_rows)
df[' lapIdx'] = np.zeros(nr_rows)
unixtime = cum_time+starttimeunix
try:
unixtime[0] = starttimeunix
except IndexError:
return (0,'No data to import')
df['TimeStamp (sec)'] = unixtime
dt = np.diff(cum_time).mean()
wsize = round(5./dt)
# velo2 = stravastuff.ewmovingaverage(velo,wsize)
# df[' Stroke500mPace (sec/500m)'] = 500./velo2
df = df.fillna(0)
df.sort_values(by='TimeStamp (sec)',ascending=True)
timestr = strftime("%Y%m%d-%H%M%S")
# csvfilename ='media/Import_'+str(importid)+'.csv'
csvfilename ='media/{code}_{importid}.csv'.format(
importid=importid,
code = uuid4().hex[:16]
)
res = df.to_csv(csvfilename+'.gz',index_label='index',
compression='gzip')
id,message = dataprep.save_workout_database(csvfilename,r,
workouttype=workouttype,
workoutsource='runkeeper',
title=title,
notes=comments)
return (id,message)

209
rowers/sporttracksstuff.py
View File

@@ -17,7 +17,9 @@ from math import sin,cos,atan2,sqrt
import urllib
import c2stuff
import pytz
import iso8601
from uuid import uuid4
import arrow
# Django
from django.shortcuts import render_to_response
from django.http import HttpResponseRedirect, HttpResponse,JsonResponse
@@ -31,10 +33,26 @@ from django.contrib.auth.decorators import login_required
from rowingdata import rowingdata
import pandas as pd
from rowers.models import Rower,Workout,checkworkoutuser
from rowers import types
from rowsandall_app.settings import C2_CLIENT_ID, C2_REDIRECT_URI, C2_CLIENT_SECRET, STRAVA_CLIENT_ID, STRAVA_REDIRECT_URI, STRAVA_CLIENT_SECRET, SPORTTRACKS_CLIENT_SECRET, SPORTTRACKS_CLIENT_ID, SPORTTRACKS_REDIRECT_URI
from utils import NoTokenError, custom_exception_handler
from utils import NoTokenError, custom_exception_handler, ewmovingaverage
from time import strftime
import dataprep
# Splits SportTracks data which is one long sequence of
# [t,[lat,lon],t2,[lat2,lon2] ...]
# to [t,t2,t3, ...], [[lat,long],[lat2,long2],...
def splitstdata(lijst):
t = []
latlong = []
while len(lijst)>=2:
t.append(lijst[0])
latlong.append(lijst[1])
lijst = lijst[2:]
return [np.array(t),np.array(latlong)]
# Checks if user has SportTracks token, renews them if they are expired
@@ -125,7 +143,7 @@ def get_token(code):
def make_authorization_url(request):
# Generate a random string for the state parameter
# Save it for use later to prevent xsrf attacks
from uuid import uuid4
state = str(uuid4())
params = {"client_id": SPORTTRACKS_CLIENT_ID,
@@ -178,7 +196,7 @@ def get_sporttracks_workout_list(user):
return s
# Get workout summary data by SportTracks ID
def get_sporttracks_workout(user,sporttracksid):
def get_workout(user,sporttracksid):
r = Rower.objects.get(user=user)
if (r.sporttrackstoken == '') or (r.sporttrackstoken is None):
return custom_exception_handler(401,s)
@@ -195,7 +213,13 @@ def get_sporttracks_workout(user,sporttracksid):
url = "https://api.sporttracks.mobi/api/v2/fitnessActivities/"+str(sporttracksid)
s = requests.get(url,headers=headers)
return s
data = s.json()
strokedata = pd.DataFrame.from_dict({
key: pd.Series(value) for key, value in data.items()
})
return data,strokedata
# Create Workout Data for upload to SportTracks
def createsporttracksworkoutdata(w):
@@ -366,3 +390,176 @@ def workout_sporttracks_upload(user,w):
return message,stid
return message,stid
# Create workout from SportTracks Data, which are slightly different
# than Strava or Concept2 data
def add_workout_from_data(user,importid,data,strokedata,source='sporttracks',
workoutsource='sporttracks'):
try:
workouttype = data['type']
except KeyError:
workouttype = 'other'
if workouttype not in [x[0] for x in Workout.workouttypes]:
workouttype = 'other'
try:
comments = data['comments']
except:
comments = ''
r = Rower.objects.get(user=user)
try:
rowdatetime = iso8601.parse_date(data['start_time'])
except iso8601.ParseError:
try:
rowdatetime = datetime.datetime.strptime(data['start_time'],"%Y-%m-%d %H:%M:%S")
rowdatetime = thetimezone.localize(rowdatetime).astimezone(utc)
except:
try:
rowdatetime = dateutil.parser.parse(data['start_time'])
rowdatetime = thetimezone.localize(rowdatetime).astimezone(utc)
except:
rowdatetime = datetime.datetime.strptime(data['date'],"%Y-%m-%d %H:%M:%S")
rowdatetime = thetimezone.localize(rowdatetime).astimezone(utc)
starttimeunix = arrow.get(rowdatetime).timestamp
try:
title = data['name']
except:
title = "Imported data"
try:
res = splitstdata(data['distance'])
distance = res[1]
times_distance = res[0]
except KeyError:
try:
res = splitstdata(data['heartrate'])
times_distance = res[0]
distance = 0*times_distance
except KeyError:
return (0,"No distance or heart rate data in the workout")
try:
l = data['location']
res = splitstdata(l)
times_location = res[0]
latlong = res[1]
latcoord = []
loncoord = []
for coord in latlong:
lat = coord[0]
lon = coord[1]
latcoord.append(lat)
loncoord.append(lon)
except:
times_location = times_distance
latcoord = np.zeros(len(times_distance))
loncoord = np.zeros(len(times_distance))
if workouttype in types.otwtypes:
workouttype = 'rower'
try:
res = splitstdata(data['cadence'])
times_spm = res[0]
spm = res[1]
except KeyError:
times_spm = times_distance
spm = 0*times_distance
try:
res = splitstdata(data['heartrate'])
hr = res[1]
times_hr = res[0]
except KeyError:
times_hr = times_distance
hr = 0*times_distance
# create data series and remove duplicates
distseries = pd.Series(distance,index=times_distance)
distseries = distseries.groupby(distseries.index).first()
latseries = pd.Series(latcoord,index=times_location)
latseries = latseries.groupby(latseries.index).first()
lonseries = pd.Series(loncoord,index=times_location)
lonseries = lonseries.groupby(lonseries.index).first()
spmseries = pd.Series(spm,index=times_spm)
spmseries = spmseries.groupby(spmseries.index).first()
hrseries = pd.Series(hr,index=times_hr)
hrseries = hrseries.groupby(hrseries.index).first()
# Create dicts and big dataframe
d = {
' Horizontal (meters)': distseries,
' latitude': latseries,
' longitude': lonseries,
' Cadence (stokes/min)': spmseries,
' HRCur (bpm)' : hrseries,
}
df = pd.DataFrame(d)
df = df.groupby(level=0).last()
cum_time = df.index.values
df[' ElapsedTime (sec)'] = cum_time
velo = df[' Horizontal (meters)'].diff()/df[' ElapsedTime (sec)'].diff()
df[' Power (watts)'] = 0.0*velo
nr_rows = len(velo.values)
df[' DriveLength (meters)'] = np.zeros(nr_rows)
df[' StrokeDistance (meters)'] = np.zeros(nr_rows)
df[' DriveTime (ms)'] = np.zeros(nr_rows)
df[' StrokeRecoveryTime (ms)'] = np.zeros(nr_rows)
df[' AverageDriveForce (lbs)'] = np.zeros(nr_rows)
df[' PeakDriveForce (lbs)'] = np.zeros(nr_rows)
df[' lapIdx'] = np.zeros(nr_rows)
unixtime = cum_time+starttimeunix
unixtime[0] = starttimeunix
df['TimeStamp (sec)'] = unixtime
dt = np.diff(cum_time).mean()
wsize = round(5./dt)
velo2 = ewmovingaverage(velo,wsize)
df[' Stroke500mPace (sec/500m)'] = 500./velo2
df = df.fillna(0)
df.sort_values(by='TimeStamp (sec)',ascending=True)
timestr = strftime("%Y%m%d-%H%M%S")
# csvfilename ='media/Import_'+str(importid)+'.csv'
csvfilename ='media/{code}_{importid}.csv'.format(
importid=importid,
code = uuid4().hex[:16]
)
res = df.to_csv(csvfilename+'.gz',index_label='index',
compression='gzip')
id,message = dataprep.save_workout_database(csvfilename,r,
workouttype=workouttype,
title=title,
notes=comments,
workoutsource='sporttracks')
return (id,message)

145
rowers/stravastuff.py
View File

@@ -11,6 +11,7 @@ from datetime import datetime
import numpy as np
from dateutil import parser
import time
from time import strftime,strptime
import math
from math import sin,cos,atan2,sqrt
import os,sys
@@ -35,6 +36,7 @@ queuehigh = django_rq.get_queue('low')
# Project
# from .models import Profile
from rowingdata import rowingdata
from rowingdata import make_cumvalues
import pandas as pd
from rowers.models import Rower,Workout
from rowers.models import checkworkoutuser
@@ -252,7 +254,7 @@ def create_async_workout(alldata,user,stravaid):
from utils import get_strava_stream
# Get a Strava workout summary data and stroke data by ID
def get_strava_workout(user,stravaid):
def get_workout(user,stravaid):
r = Rower.objects.get(user=user)
if (r.stravatoken == '') or (r.stravatoken is None):
s = "Token doesn't exist. Need to authorize"
@@ -347,7 +349,7 @@ def get_strava_workout(user,stravaid):
# startdatetime = datetime.datetime.strptime(startdatetime,"%Y-%m-%d-%H:%M:%S")
return [workoutsummary,df]
# Generate Workout data for Strava (a TCX file)
def createstravaworkoutdata(w,dozip=True):
filename = w.csvfilename
@@ -482,3 +484,142 @@ def workout_strava_upload(user,w):
return message,stravaid
return message,stravaid
return message,stravaid
# Create workout data from Strava or Concept2
# data and create the associated Workout object and save it
def add_workout_from_data(user,importid,data,strokedata,
source='strava',splitdata=None,
workoutsource='strava'):
try:
workouttype = data['type']
except KeyError:
workouttype = 'rower'
if workouttype not in [x[0] for x in Workout.workouttypes]:
workouttype = 'other'
try:
comments = data['comments']
except:
comments = ' '
try:
thetimezone = tz(data['timezone'])
except:
thetimezone = 'UTC'
r = Rower.objects.get(user=user)
try:
rowdatetime = iso8601.parse_date(data['date_utc'])
except KeyError:
rowdatetime = iso8601.parse_date(data['start_date'])
except ParseError:
rowdatetime = iso8601.parse_date(data['date'])
try:
intervaltype = data['workout_type']
except KeyError:
intervaltype = ''
try:
title = data['name']
except KeyError:
title = ""
try:
t = data['comments'].split('\n', 1)[0]
title += t[:20]
except:
title = 'Imported'
starttimeunix = arrow.get(rowdatetime).timestamp
res = make_cumvalues(0.1*strokedata['t'])
cum_time = res[0]
lapidx = res[1]
unixtime = cum_time+starttimeunix
seconds = 0.1*strokedata.ix[:,'t']
nr_rows = len(unixtime)
try:
latcoord = strokedata.ix[:,'lat']
loncoord = strokedata.ix[:,'lon']
except:
latcoord = np.zeros(nr_rows)
loncoord = np.zeros(nr_rows)
try:
strokelength = strokedata.ix[:,'strokelength']
except:
strokelength = np.zeros(nr_rows)
dist2 = 0.1*strokedata.ix[:,'d']
try:
spm = strokedata.ix[:,'spm']
except KeyError:
spm = 0*dist2
try:
hr = strokedata.ix[:,'hr']
except KeyError:
hr = 0*spm
pace = strokedata.ix[:,'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')
id,message = dataprep.save_workout_database(
csvfilename,r,
workouttype=workouttype,
title=title,notes=comments,
workoutsource=workoutsource,
dosummary=True
)
return id,message

8
rowers/urls.py
View File

@@ -321,17 +321,17 @@ urlpatterns = [
url(r'^workout/c2list/$',views.workout_c2import_view),
url(r'^workout/c2list/(?P<page>\d+)$',views.workout_c2import_view),
url(r'^workout/stravaimport/$',views.workout_stravaimport_view),
url(r'^workout/c2import/(?P<c2id>\d+)/$',views.workout_getc2workout_view),
# url(r'^workout/c2import/(?P<c2id>\d+)/$',views.workout_getc2workout_view),
url(r'^workout/c2import/all/$',views.workout_getc2workout_all),
url(r'^workout/c2import/all/(?P<page>\d+)$',views.workout_getc2workout_all),
url(r'^workout/stravaimport/(?P<stravaid>\d+)/$',views.workout_getstravaworkout_view),
# url(r'^workout/stravaimport/(?P<stravaid>\d+)/$',views.workout_getstravaworkout_view),
url(r'^workout/(?P<source>\w+.*)import/(?P<externalid>\d+)/$',views.workout_getimportview),
url(r'^workout/stravaimport/all/$',views.workout_getstravaworkout_all),
url(r'^workout/sporttracksimport/$',views.workout_sporttracksimport_view),
url(r'^workout/sporttracksimport/(?P<sporttracksid>\d+)/$',views.workout_getsporttracksworkout_view),
url(r'^workout/sporttracksimport/all/$',views.workout_getsporttracksworkout_all),
url(r'^workout/polarimport/$',views.workout_polarimport_view),
url(r'^workout/runkeeperimport/$',views.workout_runkeeperimport_view),
url(r'^workout/runkeeperimport/(?P<runkeeperid>\d+)/$',views.workout_getrunkeeperworkout_view),
# url(r'^workout/runkeeperimport/(?P<runkeeperid>\d+)/$',views.workout_getrunkeeperworkout_view),
url(r'^workout/underarmourimport/$',views.workout_underarmourimport_view),
url(r'^workout/underarmourimport/(?P<underarmourid>\d+)/$',views.workout_getunderarmourworkout_view),
url(r'^workout/(?P<id>\d+)/deleteconfirm$',views.workout_delete_confirm_view),

4
rowers/utils.py
View File

@@ -435,8 +435,8 @@ def get_strava_stream(r,metric,stravaid,series_type='time',fetchresolution='high
'Content-Type': 'application/json',
'resolution': 'medium',}
url = "https://www.strava.com/api/v3/activities/{stravaid}/streams/{metric}?resolution={fetchresolutions}&series_type={series_type}".format(
stravaid=stravid,
url = "https://www.strava.com/api/v3/activities/{stravaid}/streams/{metric}?resolution={fetchresolution}&series_type={series_type}".format(
stravaid=stravaid,
fetchresolution=fetchresolution,
series_type=series_type,
metric=metric

724
rowers/views.py
View File

@@ -839,6 +839,12 @@ def get_time(second):
def getidfromsturi(uri,length=8):
return uri[len(uri)-length:]
import re
def getidfromuri(uri):
m = re.search('/(\w.*)\/(\d+)',uri)
return m.group(2)
def splituadata(lijst):
t = []
y = []
@@ -848,38 +854,6 @@ def splituadata(lijst):
return np.array(t),np.array(y)
def splitrunkeeperlatlongdata(lijst,tname,latname,lonname):
t = []
lat = []
lon = []
for d in lijst:
t.append(d[tname])
lat.append(d[latname])
lon.append(d[lonname])
return [np.array(t),np.array(lat),np.array(lon)]
def splitrunkeeperdata(lijst,xname,yname):
x = []
y = []
for d in lijst:
x.append(d[xname])
y.append(d[yname])
return [np.array(x),np.array(y)]
# Splits SportTracks data which is one long sequence of
# [t,[lat,lon],t2,[lat2,lon2] ...]
# to [t,t2,t3, ...], [[lat,long],[lat2,long2],...
def splitstdata(lijst):
t = []
latlong = []
while len(lijst)>=2:
t.append(lijst[0])
latlong.append(lijst[1])
lijst = lijst[2:]
return [np.array(t),np.array(latlong)]
from utils import (
geo_distance,serialize_list,deserialize_list,uniqify,
@@ -1268,353 +1242,8 @@ def add_workout_from_strokedata(user,importid,data,strokedata,
return id,message
# Create workout from RunKeeper Data
def add_workout_from_runkeeperdata(user,importid,data):
# To Do - add utcoffset to time
workouttype = data['type']
if workouttype not in [x[0] for x in Workout.workouttypes]:
workouttype = 'other'
try:
comments = data['notes']
except:
comments = ''
try:
utcoffset = tz(data['utcoffset'])
except:
utcoffset = 0
r = getrower(user)
try:
rowdatetime = iso8601.parse_date(data['start_time'])
except iso8601.ParseError:
try:
rowdatetime = datetime.datetime.strptime(data['start_time'],"%Y-%m-%d %H:%M:%S")
rowdatetime = thetimezone.localize(rowdatetime).astimezone(utc)
except:
try:
rowdatetime = dateutil.parser.parse(data['start_time'])
#rowdatetime = thetimezone.localize(rowdatetime).astimezone(utc)
except:
rowdatetime = datetime.datetime.strptime(data['date'],"%Y-%m-%d %H:%M:%S")
rowdatetime = thetimezone.localize(rowdatetime).astimezone(utc)
starttimeunix = arrow.get(rowdatetime).timestamp
#starttimeunix = mktime(rowdatetime.utctimetuple())
starttimeunix += utcoffset*3600
try:
title = data['name']
except:
title = "Imported data"
res = splitrunkeeperdata(data['distance'],'timestamp','distance')
distance = res[1]
times_distance = res[0]
try:
l = data['path']
res = splitrunkeeperlatlongdata(l,'timestamp','latitude','longitude')
times_location = res[0]
latcoord = res[1]
loncoord = res[2]
except:
times_location = times_distance
latcoord = np.zeros(len(times_distance))
loncoord = np.zeros(len(times_distance))
if workouttype in types.otwtypes:
workouttype = 'rower'
try:
res = splitrunkeeperdata(data['cadence'],'timestamp','cadence')
times_spm = res[0]
spm = res[1]
except KeyError:
times_spm = times_distance
spm = 0*times_distance
try:
res = splitrunkeeperdata(data['heart_rate'],'timestamp','heart_rate')
hr = res[1]
times_hr = res[0]
except KeyError:
times_hr = times_distance
hr = 0*times_distance
# create data series and remove duplicates
distseries = pd.Series(distance,index=times_distance)
distseries = distseries.groupby(distseries.index).first()
latseries = pd.Series(latcoord,index=times_location)
try:
latseries = latseries.groupby(latseries.index).first()
except TypeError:
latseries = 0.0*distseries
lonseries = pd.Series(loncoord,index=times_location)
try:
lonseries = lonseries.groupby(lonseries.index).first()
except TypeError:
lonseries = 0.0*distseries
spmseries = pd.Series(spm,index=times_spm)
spmseries = spmseries.groupby(spmseries.index).first()
hrseries = pd.Series(hr,index=times_hr)
try:
hrseries = hrseries.groupby(hrseries.index).first()
except TypeError:
hrseries = 0*distseries
# Create dicts and big dataframe
d = {
' Horizontal (meters)': distseries,
' latitude': latseries,
' longitude': lonseries,
' Cadence (stokes/min)': spmseries,
' HRCur (bpm)' : hrseries,
}
df = pd.DataFrame(d)
df = df.groupby(level=0).last()
cum_time = df.index.values
df[' ElapsedTime (sec)'] = cum_time
velo = df[' Horizontal (meters)'].diff()/df[' ElapsedTime (sec)'].diff()
df[' Power (watts)'] = 0.0*velo
nr_rows = len(velo.values)
df[' DriveLength (meters)'] = np.zeros(nr_rows)
df[' StrokeDistance (meters)'] = np.zeros(nr_rows)
df[' DriveTime (ms)'] = np.zeros(nr_rows)
df[' StrokeRecoveryTime (ms)'] = np.zeros(nr_rows)
df[' AverageDriveForce (lbs)'] = np.zeros(nr_rows)
df[' PeakDriveForce (lbs)'] = np.zeros(nr_rows)
df[' lapIdx'] = np.zeros(nr_rows)
unixtime = cum_time+starttimeunix
try:
unixtime[0] = starttimeunix
except IndexError:
return (0,'No data to import')
df['TimeStamp (sec)'] = unixtime
dt = np.diff(cum_time).mean()
wsize = round(5./dt)
# velo2 = stravastuff.ewmovingaverage(velo,wsize)
# df[' Stroke500mPace (sec/500m)'] = 500./velo2
df = df.fillna(0)
df.sort_values(by='TimeStamp (sec)',ascending=True)
timestr = strftime("%Y%m%d-%H%M%S")
# csvfilename ='media/Import_'+str(importid)+'.csv'
csvfilename ='media/{code}_{importid}.csv'.format(
importid=importid,
code = uuid4().hex[:16]
)
res = df.to_csv(csvfilename+'.gz',index_label='index',
compression='gzip')
id,message = dataprep.save_workout_database(csvfilename,r,
workouttype=workouttype,
workoutsource='runkeeper',
title=title,
notes=comments)
return (id,message)
# Create workout from SportTracks Data, which are slightly different
# than Strava or Concept2 data
def add_workout_from_stdata(user,importid,data):
workouttype = data['type']
if workouttype not in [x[0] for x in Workout.workouttypes]:
workouttype = 'other'
try:
comments = data['comments']
except:
comments = ''
r = getrower(user)
try:
rowdatetime = iso8601.parse_date(data['start_time'])
except iso8601.ParseError:
try:
rowdatetime = datetime.datetime.strptime(data['start_time'],"%Y-%m-%d %H:%M:%S")
rowdatetime = thetimezone.localize(rowdatetime).astimezone(utc)
except:
try:
rowdatetime = dateutil.parser.parse(data['start_time'])
rowdatetime = thetimezone.localize(rowdatetime).astimezone(utc)
except:
rowdatetime = datetime.datetime.strptime(data['date'],"%Y-%m-%d %H:%M:%S")
rowdatetime = thetimezone.localize(rowdatetime).astimezone(utc)
starttimeunix = arrow.get(rowdatetime).timestamp
try:
title = data['name']
except:
title = "Imported data"
try:
res = splitstdata(data['distance'])
distance = res[1]
times_distance = res[0]
except KeyError:
try:
res = splitstdata(data['heartrate'])
times_distance = res[0]
distance = 0*times_distance
except KeyError:
return (0,"No distance or heart rate data in the workout")
try:
l = data['location']
res = splitstdata(l)
times_location = res[0]
latlong = res[1]
latcoord = []
loncoord = []
for coord in latlong:
lat = coord[0]
lon = coord[1]
latcoord.append(lat)
loncoord.append(lon)
except:
times_location = times_distance
latcoord = np.zeros(len(times_distance))
loncoord = np.zeros(len(times_distance))
if workouttype in types.otwtypes:
workouttype = 'rower'
try:
res = splitstdata(data['cadence'])
times_spm = res[0]
spm = res[1]
except KeyError:
times_spm = times_distance
spm = 0*times_distance
try:
res = splitstdata(data['heartrate'])
hr = res[1]
times_hr = res[0]
except KeyError:
times_hr = times_distance
hr = 0*times_distance
# create data series and remove duplicates
distseries = pd.Series(distance,index=times_distance)
distseries = distseries.groupby(distseries.index).first()
latseries = pd.Series(latcoord,index=times_location)
latseries = latseries.groupby(latseries.index).first()
lonseries = pd.Series(loncoord,index=times_location)
lonseries = lonseries.groupby(lonseries.index).first()
spmseries = pd.Series(spm,index=times_spm)
spmseries = spmseries.groupby(spmseries.index).first()
hrseries = pd.Series(hr,index=times_hr)
hrseries = hrseries.groupby(hrseries.index).first()
# Create dicts and big dataframe
d = {
' Horizontal (meters)': distseries,
' latitude': latseries,
' longitude': lonseries,
' Cadence (stokes/min)': spmseries,
' HRCur (bpm)' : hrseries,
}
df = pd.DataFrame(d)
df = df.groupby(level=0).last()
cum_time = df.index.values
df[' ElapsedTime (sec)'] = cum_time
velo = df[' Horizontal (meters)'].diff()/df[' ElapsedTime (sec)'].diff()
df[' Power (watts)'] = 0.0*velo
nr_rows = len(velo.values)
df[' DriveLength (meters)'] = np.zeros(nr_rows)
df[' StrokeDistance (meters)'] = np.zeros(nr_rows)
df[' DriveTime (ms)'] = np.zeros(nr_rows)
df[' StrokeRecoveryTime (ms)'] = np.zeros(nr_rows)
df[' AverageDriveForce (lbs)'] = np.zeros(nr_rows)
df[' PeakDriveForce (lbs)'] = np.zeros(nr_rows)
df[' lapIdx'] = np.zeros(nr_rows)
unixtime = cum_time+starttimeunix
unixtime[0] = starttimeunix
df['TimeStamp (sec)'] = unixtime
dt = np.diff(cum_time).mean()
wsize = round(5./dt)
velo2 = stravastuff.ewmovingaverage(velo,wsize)
df[' Stroke500mPace (sec/500m)'] = 500./velo2
df = df.fillna(0)
df.sort_values(by='TimeStamp (sec)',ascending=True)
timestr = strftime("%Y%m%d-%H%M%S")
# csvfilename ='media/Import_'+str(importid)+'.csv'
csvfilename ='media/{code}_{importid}.csv'.format(
importid=importid,
code = uuid4().hex[:16]
)
res = df.to_csv(csvfilename+'.gz',index_label='index',
compression='gzip')
id,message = dataprep.save_workout_database(csvfilename,r,
workouttype=workouttype,
title=title,
notes=comments,
workoutsource='sporttracks')
return (id,message)
# Create workout from SportTracks Data, which are slightly different
# than Strava or Concept2 data
@@ -9781,12 +9410,13 @@ def workout_runkeeperimport_view(request,message=""):
workouts = []
for item in res.json()['items']:
d = int(float(item['total_distance']))
i = getidfromsturi(item['uri'],length=9)
i = getidfromuri(item['uri'])
ttot = str(datetime.timedelta(seconds=int(float(item['duration']))))
s = item['start_time']
r = item['type']
keys = ['id','distance','duration','starttime','type']
values = [i,d,ttot,s,r]
res = dict(zip(keys,values))
workouts.append(res)
return render(request,'runkeeper_list_import.html',
@@ -9906,14 +9536,14 @@ def workout_sporttracksimport_view(request,message=""):
else:
workouts = []
r = getrower(request.user)
stids = [int(getidfromsturi(item['uri'])) for item in res.json()['items']]
stids = [int(getidfromuri(item['uri'])) for item in res.json()['items']]
knownstids = uniqify([
w.uploadedtosporttracks for w in Workout.objects.filter(user=r)
])
newids = [stid for stid in stids if not stid in knownstids]
for item in res.json()['items']:
d = int(float(item['total_distance']))
i = int(getidfromsturi(item['uri']))
i = int(getidfromuri(item['uri']))
if i in knownstids:
nnn = ''
else:
@@ -10060,63 +9690,151 @@ def workout_c2import_view(request,page=1,message=""):
'page':page,
})
# Import a workout from Strava
importsources = {
'c2':c2stuff,
'strava':stravastuff,
'polar':polarstuff,
'ownapi':ownapistuff,
'runkeeper':runkeeperstuff,
'sporttracks':sporttracksstuff,
'trainingpeaks':tpstuff,
'underarmour':underarmourstuff
}
@login_required()
def workout_getstravaworkout_view(request,stravaid):
res = stravastuff.get_strava_workout(request.user,stravaid)
def workout_getimportview(request,externalid,source = 'c2'):
res = importsources[source].get_workout(request.user,externalid)
if not res[0]:
messages.error(request,res[1])
return imports_view(request)
strokedata = res[1]
data = res[0]
id,message = add_workout_from_strokedata(request.user,stravaid,data,strokedata,
source='strava',
workoutsource='strava')
# Now works only for C2
if strokedata.empty:
distance = data['distance']
c2id = data['id']
workouttype = data['type']
verified = data['verified']
startdatetime = iso8601.parse_date(data['date'])
weightclass = data['weight_class']
weightcategory = 'hwt'
if weightclass == "L":
weightcategory = 'lwt'
totaltime = data['time']/10.
duration = dataprep.totaltime_sec_to_string(totaltime)
duration = datetime.datetime.strptime(duration,'%H:%M:%S.%f').time()
try:
timezone_str = data['timezone']
except:
timezone_str = 'UTC'
if timezone_str is None:
timezone_str = 'UTC'
workoutdate = startdatetime.astimezone(
pytz.timezone(timezone_str)
).strftime('%Y-%m-%d')
starttime = startdatetime.astimezone(
pytz.timezone(timezone_str)
).strftime('%H:%M:%S')
r = getrower(request.user)
id, message = dataprep.create_row_df(r,
distance,
duration,
startdatetime,
workouttype=workouttype)
w = Workout.objects.get(id=id)
w.uploadedtoc2 = c2id
w.name = 'Imported from C2'
w.workouttype = 'rower'
w.save()
message = "This workout does not have any stroke data associated with it. We created synthetic stroke data."
messages.info(request,message)
url = reverse(r.defaultlandingpage,
kwargs = {
'id':int(id),
})
return HttpResponseRedirect(url)
# strokdata not empty - continue
id,message = importsources[source].add_workout_from_data(
request.user,
externalid,data,
strokedata,
source=source,
workoutsource=source)
w = get_workout(id)
w.uploadedtostrava=stravaid
if 'workout' in data:
if 'splits' in data['workout']:
splitdata = data['workout']['splits']
if 'intervals' in data['workout']:
splitdata = data['workout']['intervals']
else:
splitdata = False
# splitdata (only for C2)
if splitdata:
w.summary,sa,results = c2stuff.summaryfromsplitdata(splitdata,data,w.csvfilename)
w.save()
from rowingdata.trainingparser import getlist
# set stroke data in CSV file
if sa:
values = getlist(sa)
units = getlist(sa,sel='unit')
types = getlist(sa,sel='type')
rowdata = rdata(w.csvfilename)
if rowdata:
rowdata.updateintervaldata(values,
units,types,results)
rowdata.write_csv(w.csvfilename,gzip=True)
dataprep.update_strokedata(w.id,rowdata.df)
if source == 'strava':
w.uploadedtostrava = externalid
elif source == 'c2':
w.uploadedtoc2 = externalid
elif source == 'polar':
w.uploadedtopolar = externalid
elif source == 'runkeeper':
w.uploadedtorunkeeper = externalid
elif source == 'sporttracks':
w.uploadedtosporttracks = externalid
elif source == 'trainingpeaks':
w.uploadedtotp = externalid
elif source == 'underarmour':
w.uploadedtounderarmour = externalid
w.save()
if message:
messages.error(request,message)
r = getrower(request.user)
url = reverse(r.defaultlandingpage,
kwargs = {
'id':int(id),
})
return HttpResponseRedirect(url)
# Imports a workout from Runkeeper
@login_required()
def workout_getrunkeeperworkout_view(request,runkeeperid):
res = runkeeperstuff.get_runkeeper_workout(request.user,runkeeperid)
try:
data = res.json()
except ValueError:
messages.error(request,'Error getting workout from Runkeeper')
url = reverse(workout_runkeeperimport_view)
return HttpResponseRedirect(url)
id,message = add_workout_from_runkeeperdata(request.user,runkeeperid,data)
w = Workout.objects.get(id=id)
w.uploadedtorunkeeper=runkeeperid
thetoken = runkeeper_open(request.user)
w.save()
if message:
messages.error(request,message)
r = getrower(request.user)
url = reverse(r.defaultlandingpage,
kwargs = {
'id':int(id),
})
'id':int(id)
})
return HttpResponseRedirect(url)
# Imports a workout from Underarmour
@login_required()
@@ -10141,30 +9859,6 @@ def workout_getunderarmourworkout_view(request,underarmourid):
# Imports a workout from SportTracks
@login_required()
def workout_getsporttracksworkout_view(request,sporttracksid):
res = sporttracksstuff.get_sporttracks_workout(request.user,sporttracksid)
data = res.json()
id,message = add_workout_from_stdata(request.user,sporttracksid,data)
if id==0:
messages.error(request,message)
url = reverse(workouts_view)
return HttpResponseRedirect(url)
w = Workout.objects.get(id=id)
w.uploadedtosporttracks=sporttracksid
w.save()
if message:
messages.error(request,message)
r = getrower(request.user)
url = reverse(r.defaultlandingpage,
kwargs = {
'id':int(id),
})
return HttpResponseRedirect(url)
# Imports all new workouts from SportTracks
@login_required()
@@ -10172,7 +9866,7 @@ def workout_getsporttracksworkout_all(request):
res = sporttracksstuff.get_sporttracks_workout_list(request.user)
if (res.status_code == 200):
r = getrower(request.user)
stids = [int(getidfromsturi(item['uri'])) for item in res.json()['items']]
stids = [int(getidfromuri(item['uri'])) for item in res.json()['items']]
knownstids = uniqify([
w.uploadedtosporttracks for w in Workout.objects.filter(user=r)
])
@@ -10235,146 +9929,6 @@ def workout_getstravaworkout_all(request):
# Imports a workout from Concept2
@login_required()
def workout_getc2workout_view(request,c2id):
try:
thetoken = c2_open(request.user)
except NoTokenError:
return HttpResponseRedirect("/rowers/me/c2authorize/")
res = c2stuff.get_c2_workout(request.user,c2id)
if (res.status_code == 200):
data = res.json()['data']
splitdata = None
if 'workout' in data:
if 'splits' in data['workout']:
splitdata = data['workout']['splits']
if 'intervals' in data['workout']:
splitdata = data['workout']['intervals']
# Check if workout has stroke data, and get the stroke data
if data['stroke_data']:
res2 = c2stuff.get_c2_workout_strokes(request.user,c2id)
else:
distance = data['distance']
c2id = data['id']
workouttype = data['type']
verified = data['verified']
startdatetime = iso8601.parse_date(data['date'])
weightclass = data['weight_class']
weightcategory = 'hwt'
if weightclass == "L":
weightcategory = 'lwt'
totaltime = data['time']/10.
duration = dataprep.totaltime_sec_to_string(totaltime)
duration = datetime.datetime.strptime(duration,'%H:%M:%S.%f').time()
try:
timezone_str = data['timezone']
except:
timezone_str = 'UTC'
if timezone_str is None:
timezone_str = 'UTC'
workoutdate = startdatetime.astimezone(
pytz.timezone(timezone_str)
).strftime('%Y-%m-%d')
starttime = startdatetime.astimezone(
pytz.timezone(timezone_str)
).strftime('%H:%M:%S')
r = getrower(request.user)
id, message = dataprep.create_row_df(r,
distance,
duration,
startdatetime,
# title = 'Imported from C2',
workouttype=workouttype)
w = Workout.objects.get(id=id)
w.uploadedtoc2 = c2id
w.name = 'Imported from C2'
w.workouttype = 'rower'
w.save()
message = "This workout does not have any stroke data associated with it. We created synthetic stroke data."
messages.info(request,message)
url = reverse(r.defaultlandingpage,
kwargs = {
'id':int(id),
})
return HttpResponseRedirect(url)
# We have stroke data
if res2.status_code == 200:
strokedata = pd.DataFrame.from_dict(res2.json()['data'])
# create the workout
id,message = add_workout_from_strokedata(request.user,c2id,data,strokedata,
source='c2')
w = Workout.objects.get(id=id)
w.uploadedtoc2=c2id
# If we have split data, update the stroke data so they
# match exactly (some users are anal about this)
if splitdata:
try:
w.summary,sa,results = c2stuff.summaryfromsplitdata(splitdata,data,w.csvfilename)
except:
sa = []
results = []
with open("media/c2splitdata.log","a") as errorlog:
errorstring = str(sys.exc_info()[0])
timestr = strftime("%Y%m%d-%H%M%S")
errorlog.write(timestr+errorstring+"\r\n")
errorlog.write("views.py line 952\r\n")
w.save()
from rowingdata.trainingparser import getlist
# set stroke data in CSV file
if sa:
values = getlist(sa)
units = getlist(sa,sel='unit')
types = getlist(sa,sel='type')
rowdata = rdata(w.csvfilename)
if rowdata:
rowdata.updateintervaldata(values,
units,types,results)
rowdata.write_csv(w.csvfilename,gzip=True)
dataprep.update_strokedata(w.id,rowdata.df)
if message:
messages.error(request,message)
r = getrower(request.user)
url = reverse(r.defaultlandingpage,
kwargs = {
'id':int(id),
})
return HttpResponseRedirect(url)
else:
# message = json.loads(s.text)['message']
message = json.loads(res2.text)['message']
messages.error(request,message)
url = reverse(workout_c2import_view)
return HttpResponseRedirect(url)
else:
message = "Received error code from Concept2"
messages.error(request,message)
if settings.DEBUG:
return HttpResponse(res)
else:
url = reverse(workout_c2import_view)
return HttpResponseRedirect(url)
@login_required
def workout_toggle_ranking(request,id=0):