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Merge branch 'develop' into feature/revisedimports

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This commit is contained in:
Sander Roosendaal
2018-06-29 23:31:29 +02:00
parent 9ab9734fb9 200ff3c43f
commit b68187df87
2 changed files with 138 additions and 278 deletions
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274
rowers/stravastuff.py
View File

@@ -1,3 +1,9 @@
# All the functionality needed to connect to Strava
from scipy import optimize
from scipy.signal import savgol_filter
from django_mailbox.models import Message,Mailbox,MessageAttachment
import django_rq
queue = django_rq.get_queue('default')
@@ -12,7 +18,7 @@ from stravalib.exc import ActivityUploadFailed,TimeoutExceeded
from iso8601 import ParseError
from rowers.tasks import handle_strava_import_stroke_data
from rowsandall_app.settings import (
C2_CLIENT_ID, C2_REDIRECT_URI, C2_CLIENT_SECRET,
@@ -78,7 +84,7 @@ def make_authorization_url(request):
return HttpResponseRedirect(url)
# Get list of workouts available on Strava
def get_strava_workout_list(user):
def get_strava_workout_list(user,limit_n=0):
r = Rower.objects.get(user=user)
if (r.stravatoken == '') or (r.stravatoken is None):
s = "Token doesn't exist. Need to authorize"
@@ -89,8 +95,15 @@ def get_strava_workout_list(user):
headers = {'Authorization': authorizationstring,
'user-agent': 'sanderroosendaal',
'Content-Type': 'application/json'}
url = "https://www.strava.com/api/v3/athlete/activities"
s = requests.get(url,headers=headers)
if limit_n==0:
params = {}
else:
params = {'per_page':limit_n}
s = requests.get(url,headers=headers,params=params)
return s
@@ -101,7 +114,7 @@ def get_strava_workouts(rower):
if not isprorower(rower):
return 0
res = get_strava_workout_list(rower.user)
res = get_strava_workout_list(rower.user,limit_n=10)
if (res.status_code != 200):
return 0
@@ -117,6 +130,7 @@ def get_strava_workouts(rower):
])
newids = [stravaid for stravaid in stravaids if not stravaid in knownstravaids]
for stravaid in newids:
result = create_async_workout(alldata,rower.user,stravaid)
@@ -182,40 +196,24 @@ def create_async_workout(alldata,user,stravaid,debug=False):
weightcategory = 'hwt'
# Create CSV file name and save data to CSV file
csvfilename ='media/{code}_{importid}.csv'.format(
csvfilename ='media/mailbox_attachments/{code}_{importid}.csv'.format(
importid=stravaid,
code = uuid4().hex[:16]
)
# w = Workout(
# user=r,
# workouttype = workouttype,
# name = title,
# date = workoutdate,
# starttime = starttime,
# startdatetime = rowdatetime,
# timezone = thetimezone,
# duration = duration,
# distance=distance,
# weightcategory = weightcategory,
# uploadedtostrava = stravaid,
# csvfilename = csvfilename,
# notes = ''
# )
# Check if workout has stroke data, and get the stroke data
starttimeunix = arrow.get(rowdatetime).timestamp
job = myqueue(queue,
handle_strava_import_stroke_data,
title,
user.email,
r.stravatoken,
stravaid,
starttimeunix,
csvfilename,
result = handle_strava_import_stroke_data(
title,
user.email,
r.stravatoken,
stravaid,
starttimeunix,
csvfilename,
)
return 1
@@ -454,141 +452,145 @@ def workout_strava_upload(user,w):
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'
def handle_strava_import_stroke_data(title,
useremail,
stravatoken,
stravaid,
starttimeunix,
csvfilename,debug=True,**kwargs):
# ready to fetch. Hurray
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'])
fetchresolution = 'high'
series_type = 'time'
authorizationstring = str('Bearer ' + stravatoken)
headers = {'Authorization': authorizationstring,
'user-agent': 'sanderroosendaal',
'Content-Type': 'application/json',
'resolution': 'medium',}
url = "https://www.strava.com/api/v3/activities/"+str(stravaid)
workoutsummary = requests.get(url,headers=headers).json()
workoutsummary['timezone'] = "Etc/UTC"
startdatetime = workoutsummary['start_date']
r = type('Rower', (object,), {"stravatoken": stravatoken})
spmjson = get_strava_stream(r,'cadence',stravaid)
hrjson = get_strava_stream(r,'heartrate',stravaid)
timejson = get_strava_stream(r,'time',stravaid)
velojson = get_strava_stream(r,'velocity_smooth',stravaid)
distancejson = get_strava_stream(r,'distance',stravaid)
latlongjson = get_strava_stream(r,'latlng',stravaid)
wattsjson = get_strava_stream(r,'watts',stravaid)
try:
intervaltype = data['workout_type']
t = np.array(timejson.json()[0]['data'])
nr_rows = len(t)
d = np.array(distancejson.json()[1]['data'])
if nr_rows == 0:
return 0
except IndexError:
d = 0*t
# return (0,"Error: No Distance information in the Strava data")
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)
return 0
try:
latcoord = strokedata.ix[:,'lat']
loncoord = strokedata.ix[:,'lon']
spm = np.array(spmjson.json()[1]['data'])
except:
latcoord = np.zeros(nr_rows)
loncoord = np.zeros(nr_rows)
spm = np.zeros(nr_rows)
try:
strokelength = strokedata.ix[:,'strokelength']
watts = np.array(wattsjson.json()[1]['data'])
except:
strokelength = np.zeros(nr_rows)
dist2 = 0.1*strokedata.ix[:,'d']
watts = np.zeros(nr_rows)
try:
spm = strokedata.ix[:,'spm']
hr = np.array(hrjson.json()[1]['data'])
except IndexError:
hr = np.zeros(nr_rows)
except KeyError:
spm = 0*dist2
hr = np.zeros(nr_rows)
try:
velo = np.array(velojson.json()[1]['data'])
except IndexError:
velo = np.zeros(nr_rows)
except KeyError:
velo = np.zeros(nr_rows)
f = np.diff(t).mean()
if f != 0:
windowsize = 2*(int(10./(f)))+1
else:
windowsize = 1
if windowsize > 3 and windowsize < len(velo):
velo2 = savgol_filter(velo,windowsize,3)
else:
velo2 = velo
coords = np.array(latlongjson.json()[0]['data'])
try:
hr = strokedata.ix[:,'hr']
lat = coords[:,0]
lon = coords[:,1]
except IndexError:
lat = np.zeros(len(t))
lon = np.zeros(len(t))
except KeyError:
hr = 0*spm
pace = strokedata.ix[:,'p']/10.
pace = np.clip(pace,0,1e4)
pace = pace.replace(0,300)
lat = np.zeros(len(t))
lon = np.zeros(len(t))
velo = 500./pace
strokelength = velo*60./(spm)
strokelength[np.isinf(strokelength)] = 0.0
power = 2.8*velo**3
pace = 500./(1.0*velo2)
pace[np.isinf(pace)] = 0.0
unixtime = starttimeunix+t
strokedistance = 60.*velo2/spm
# save csv
# Create data frame with all necessary data to write to csv
nr_strokes = len(t)
df = pd.DataFrame({'TimeStamp (sec)':unixtime,
' Horizontal (meters)': dist2,
' ElapsedTime (sec)':t,
' Horizontal (meters)':d,
' Stroke500mPace (sec/500m)':pace,
' 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),
' latitude':lat,
' longitude':lon,
' 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
})
'cum_dist':d,
' DragFactor':np.zeros(nr_strokes),
' DriveLength (meters)':np.zeros(nr_strokes),
' StrokeDistance (meters)':strokedistance,
' DriveTime (ms)':np.zeros(nr_strokes),
' StrokeRecoveryTime (ms)':np.zeros(nr_strokes),
' AverageDriveForce (lbs)':np.zeros(nr_strokes),
' PeakDriveForce (lbs)':np.zeros(nr_strokes),
' lapIdx':np.zeros(nr_strokes),
' Power (watts)':watts,
})
df.sort_values(by='TimeStamp (sec)',ascending=True)
timestr = strftime("%Y%m%d-%H%M%S")
res = df.to_csv(csvfilename,index_label='index')
# Create CSV file name and save data to CSV file
csvfilename ='media/{code}_{importid}.csv'.format(
importid=importid,
code = uuid4().hex[:16]
)
workoutsbox = Mailbox.objects.filter(name='workouts')[0]
res = df.to_csv(csvfilename+'.gz',index_label='index',
compression='gzip')
body = 'stravaid {stravaid}'.format(stravaid=stravaid)
msg = Message(mailbox=workoutsbox,
from_header=useremail,
subject=title,
body=body)
msg.save()
a = MessageAttachment(message=msg,document=csvfilename[6:])
a.save()
id,message = dataprep.save_workout_database(
csvfilename,r,
workouttype=workouttype,
title=title,notes=comments,
workoutsource=workoutsource,
dosummary=True
)
return id,message
return res

142
rowers/tasks.py
View File

@@ -82,148 +82,6 @@ def add(x, y):
return x + y
@app.task
def handle_strava_import_stroke_data(title,
useremail,
stravatoken,
stravaid,
starttimeunix,
csvfilename,debug=True,**kwargs):
# ready to fetch. Hurray
fetchresolution = 'high'
series_type = 'time'
authorizationstring = str('Bearer ' + stravatoken)
headers = {'Authorization': authorizationstring,
'user-agent': 'sanderroosendaal',
'Content-Type': 'application/json',
'resolution': 'medium',}
url = "https://www.strava.com/api/v3/activities/"+str(stravaid)
workoutsummary = requests.get(url,headers=headers).json()
workoutsummary['timezone'] = "Etc/UTC"
startdatetime = workoutsummary['start_date']
r = type('Rower', (object,), {"stravatoken": stravatoken})
spmjson = get_strava_stream(r,'cadence',stravaid)
hrjson = get_strava_stream(r,'heartrate',stravaid)
timejson = get_strava_stream(r,'time',stravaid)
velojson = get_strava_stream(r,'velocity_smooth',stravaid)
distancejson = get_strava_stream(r,'distance',stravaid)
latlongjson = get_strava_stream(r,'latlng',stravaid)
wattsjson = get_strava_stream(r,'watts',stravaid)
try:
t = np.array(timejson.json()[0]['data'])
nr_rows = len(t)
d = np.array(distancejson.json()[1]['data'])
if nr_rows == 0:
return 0
except IndexError:
d = 0*t
# return (0,"Error: No Distance information in the Strava data")
except KeyError:
return 0
try:
spm = np.array(spmjson.json()[1]['data'])
except:
spm = np.zeros(nr_rows)
try:
watts = np.array(wattsjson.json()[1]['data'])
except:
watts = np.zeros(nr_rows)
try:
hr = np.array(hrjson.json()[1]['data'])
except IndexError:
hr = np.zeros(nr_rows)
except KeyError:
hr = np.zeros(nr_rows)
try:
velo = np.array(velojson.json()[1]['data'])
except IndexError:
velo = np.zeros(nr_rows)
except KeyError:
velo = np.zeros(nr_rows)
f = np.diff(t).mean()
if f != 0:
windowsize = 2*(int(10./(f)))+1
else:
windowsize = 1
if windowsize > 3 and windowsize < len(velo):
velo2 = savgol_filter(velo,windowsize,3)
else:
velo2 = velo
coords = np.array(latlongjson.json()[0]['data'])
try:
lat = coords[:,0]
lon = coords[:,1]
except IndexError:
lat = np.zeros(len(t))
lon = np.zeros(len(t))
except KeyError:
lat = np.zeros(len(t))
lon = np.zeros(len(t))
strokelength = velo*60./(spm)
strokelength[np.isinf(strokelength)] = 0.0
pace = 500./(1.0*velo2)
pace[np.isinf(pace)] = 0.0
unixtime = starttimeunix+t
strokedistance = 60.*velo2/spm
nr_strokes = len(t)
df = pd.DataFrame({'TimeStamp (sec)':unixtime,
' ElapsedTime (sec)':t,
' Horizontal (meters)':d,
' Stroke500mPace (sec/500m)':pace,
' Cadence (stokes/min)':spm,
' HRCur (bpm)':hr,
' latitude':lat,
' longitude':lon,
' StrokeDistance (meters)':strokelength,
'cum_dist':d,
' DragFactor':np.zeros(nr_strokes),
' DriveLength (meters)':np.zeros(nr_strokes),
' StrokeDistance (meters)':strokedistance,
' DriveTime (ms)':np.zeros(nr_strokes),
' StrokeRecoveryTime (ms)':np.zeros(nr_strokes),
' AverageDriveForce (lbs)':np.zeros(nr_strokes),
' PeakDriveForce (lbs)':np.zeros(nr_strokes),
' lapIdx':np.zeros(nr_strokes),
' Power (watts)':watts,
})
df.sort_values(by='TimeStamp (sec)',ascending=True)
res = df.to_csv(csvfilename,index_label='index')
d = {
'stravaid':stravaid
}
res = send_template_email(useremail,[workoutemailbox],
title,'workoutemail.html',
d,
attach_file=csvfilename)
time.sleep(1)
os.remove(csvfilename)
return res
@app.task