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Merge branch 'feature/nostrokedataimport' into develop

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This commit is contained in:
Sander Roosendaal
2018-01-19 17:44:44 +01:00
parent 8e6460eb06 f9ccdd696b
commit e0277da42a
6 changed files with 429 additions and 73 deletions
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94
rowers/c2stuff.py
View File

@@ -7,8 +7,10 @@
import oauth2 as oauth
import cgi
import requests
import arrow
import requests.auth
import json
import iso8601
from django.utils import timezone
from datetime import datetime
from datetime import timedelta
@@ -21,8 +23,8 @@ from django.conf import settings
from django.contrib.auth import authenticate, login, logout
from django.contrib.auth.models import User
from django.contrib.auth.decorators import login_required
import dataprep
import pytz
from rowingdata import rowingdata
import pandas as pd
import numpy as np
@@ -32,8 +34,16 @@ import sys
import urllib
from requests import Request, Session
from utils import myqueue
from rowsandall_app.settings import C2_CLIENT_ID, C2_REDIRECT_URI, C2_CLIENT_SECRET
from rowers.tasks import handle_c2_import_stroke_data
import django_rq
queue = django_rq.get_queue('default')
queuelow = django_rq.get_queue('low')
queuehigh = django_rq.get_queue('low')
# Custom error class - to raise a NoTokenError
class C2NoTokenError(Exception):
def __init__(self,value):
@@ -82,7 +92,87 @@ def c2_open(user):
return thetoken
def add_stroke_data(user,c2id,workoutid,startdatetime,csvfilename):
r = Rower.objects.get(user=user)
if (r.c2token == '') or (r.c2token is None):
return custom_exception_handler(401,s)
s = "Token doesn't exist. Need to authorize"
elif (timezone.now()>r.tokenexpirydate):
s = "Token expired. Needs to refresh."
return custom_exception_handler(401,s)
else:
starttimeunix = arrow.get(startdatetime).timestamp
job = myqueue(queue,
handle_c2_import_stroke_data,
r.c2token,
c2id,
workoutid,
starttimeunix,
csvfilename)
return 1
# get workout metrics, then relay stroke data to an asynchronous task
def create_async_workout(alldata,user,c2id):
data = alldata[c2id]
splitdata = None
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'
# Create CSV file name and save data to CSV file
csvfilename ='media/Import_'+str(c2id)+'.csv.gz'
totaltime = data['time']/10.
duration = dataprep.totaltime_sec_to_string(totaltime)
try:
timezone_str = tz(data['timezone'])
except:
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 = Rower.objects.get(user=user)
w = Workout(
user=r,
workouttype = workouttype,
name = 'Imported workout',
date = workoutdate,
starttime = starttime,
startdatetime = startdatetime,
timezone = timezone_str,
duration = duration,
distance=distance,
weightcategory = weightcategory,
uploadedtoc2 = c2id,
csvfilename = csvfilename,
notes = 'imported from Concept2 log'
)
w.save()
# Check if workout has stroke data, and get the stroke data
result = add_stroke_data(user,c2id,w.id,startdatetime,csvfilename)
return w.id
# convert datetime object to seconds
def makeseconds(t):

56
rowers/dataprep.py
View File

@@ -723,9 +723,35 @@ def create_row_df(r,distance,duration,startdatetime,
return (id, message)
def totaltime_sec_to_string(totaltime):
hours = int(totaltime / 3600.)
if hours > 23:
message = 'Warning: The workout duration was longer than 23 hours. '
hours = 23
minutes = int((totaltime - 3600. * hours) / 60.)
if minutes > 59:
minutes = 59
if not message:
message = 'Warning: there is something wrong with the workout duration'
seconds = int(totaltime - 3600. * hours - 60. * minutes)
if seconds > 59:
seconds = 59
if not message:
message = 'Warning: there is something wrong with the workout duration'
tenths = int(10 * (totaltime - 3600. * hours - 60. * minutes - seconds))
if tenths > 9:
tenths = 9
if not message:
message = 'Warning: there is something wrong with the workout duration'
duration = "%s:%s:%s.%s" % (hours, minutes, seconds, tenths)
return duration
# Processes painsled CSV file to database
def save_workout_database(f2, r, dosmooth=True, workouttype='rower',
dosummary=True, title='Workout',
workoutsource='unknown',
@@ -838,30 +864,6 @@ def save_workout_database(f2, r, dosmooth=True, workouttype='rower',
if np.isnan(totaltime):
totaltime = 0
hours = int(totaltime / 3600.)
if hours > 23:
message = 'Warning: The workout duration was longer than 23 hours. '
hours = 23
minutes = int((totaltime - 3600. * hours) / 60.)
if minutes > 59:
minutes = 59
if not message:
message = 'Warning: there is something wrong with the workout duration'
seconds = int(totaltime - 3600. * hours - 60. * minutes)
if seconds > 59:
seconds = 59
if not message:
message = 'Warning: there is something wrong with the workout duration'
tenths = int(10 * (totaltime - 3600. * hours - 60. * minutes - seconds))
if tenths > 9:
tenths = 9
if not message:
message = 'Warning: there is something wrong with the workout duration'
duration = "%s:%s:%s.%s" % (hours, minutes, seconds, tenths)
if dosummary:
summary = row.allstats()
@@ -897,6 +899,8 @@ def save_workout_database(f2, r, dosmooth=True, workouttype='rower',
except KeyError:
timezone_str = r.defaulttimezone
duration = totaltime_sec_to_string(totaltime)
workoutdate = workoutstartdatetime.astimezone(
pytz.timezone(timezone_str)
).strftime('%Y-%m-%d')

183
rowers/dataprepnodjango.py
View File

@@ -1,10 +1,10 @@
# This is Data prep used for testing purposes (no Django environment)
# Uses the debug SQLite database for stroke data
from rowingdata import rowingdata as rrdata
from rowingdata import make_cumvalues
from rowingdata import rower as rrower
from rowingdata import main as rmain
from time import strftime
from pandas import DataFrame,Series
import pandas as pd
@@ -131,6 +131,185 @@ def rdata(file,rower=rrower()):
return res
def totaltime_sec_to_string(totaltime):
hours = int(totaltime / 3600.)
if hours > 23:
message = 'Warning: The workout duration was longer than 23 hours. '
hours = 23
minutes = int((totaltime - 3600. * hours) / 60.)
if minutes > 59:
minutes = 59
if not message:
message = 'Warning: there is something wrong with the workout duration'
seconds = int(totaltime - 3600. * hours - 60. * minutes)
if seconds > 59:
seconds = 59
if not message:
message = 'Warning: there is something wrong with the workout duration'
tenths = int(10 * (totaltime - 3600. * hours - 60. * minutes - seconds))
if tenths > 9:
tenths = 9
if not message:
message = 'Warning: there is something wrong with the workout duration'
duration = "%s:%s:%s.%s" % (hours, minutes, seconds, tenths)
return duration
# Creates C2 stroke data
def create_c2_stroke_data_db(
distance,duration,workouttype,
workoutid,starttimeunix,csvfilename,debug=False):
nr_strokes = int(distance/10.)
totalseconds = duration.hour*3600.
totalseconds += duration.minute*60.
totalseconds += duration.second
totalseconds += duration.microsecond/1.e6
spm = 60.*nr_strokes/totalseconds
step = totalseconds/float(nr_strokes)
elapsed = np.arange(nr_strokes)*totalseconds/(float(nr_strokes-1))
dstep = distance/float(nr_strokes)
d = np.arange(nr_strokes)*distance/(float(nr_strokes-1))
unixtime = starttimeunix + elapsed
pace = 500.*totalseconds/distance
if workouttype in ['rower','slides','dynamic']:
velo = distance/totalseconds
power = 2.8*velo**3
else:
power = 0
df = pd.DataFrame({
'TimeStamp (sec)': unixtime,
' Horizontal (meters)': d,
' Cadence (stokes/min)': spm,
' Stroke500mPace (sec/500m)':pace,
' ElapsedTime (sec)':elapsed,
' Power (watts)':power,
' HRCur (bpm)':np.zeros(nr_strokes),
' longitude':np.zeros(nr_strokes),
' latitude':np.zeros(nr_strokes),
' DragFactor':np.zeros(nr_strokes),
' DriveLength (meters)':np.zeros(nr_strokes),
' StrokeDistance (meters)':np.zeros(nr_strokes),
' 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),
'cum_dist': d
})
timestr = strftime("%Y%m%d-%H%M%S")
df[' ElapsedTime (sec)'] = df['TimeStamp (sec)']
res = df.to_csv(csvfilename,index_label='index',
compression='gzip')
data = dataprep(df,id=workoutid,bands=False,debug=debug)
return data
# Saves C2 stroke data to CSV and database
def add_c2_stroke_data_db(strokedata,workoutid,starttimeunix,csvfilename,
debug=False):
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,
'cum_dist': dist2
})
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
res = df.to_csv(csvfilename,index_label='index',
compression='gzip')
data = dataprep(df,id=workoutid,bands=False,debug=debug)
return data
# Processes painsled CSV file to database
def save_workout_database(f2,r,dosmooth=True,workouttype='rower',
dosummary=True,title='Workout',

74
rowers/tasks.py
View File

@@ -13,6 +13,9 @@ import rowingdata
from rowingdata import rowingdata as rdata
from celery import app
import datetime
import pytz
import iso8601
from matplotlib.backends.backend_agg import FigureCanvas
#from matplotlib.backends.backend_cairo import FigureCanvasCairo as FigureCanvas
@@ -32,7 +35,9 @@ from utils import deserialize_list
from rowers.dataprepnodjango import (
update_strokedata, new_workout_from_file,
getsmallrowdata_db, updatecpdata_sql,
update_agegroup_db,fitnessmetric_to_sql
update_agegroup_db,fitnessmetric_to_sql,
add_c2_stroke_data_db,totaltime_sec_to_string,
create_c2_stroke_data_db
)
from django.core.mail import send_mail, EmailMessage
@@ -40,8 +45,9 @@ from django.db.utils import OperationalError
import datautils
import utils
import requests
import longtask
import arrow
# testing task
@@ -50,6 +56,70 @@ import longtask
def add(x, y):
return x + y
@app.task
def handle_c2_import_stroke_data(c2token,
c2id,workoutid,
starttimeunix,
csvfilename,debug=True):
authorizationstring = str('Bearer ' + c2token)
headers = {'Authorization': authorizationstring,
'user-agent': 'sanderroosendaal',
'Content-Type': 'application/json'}
url = "https://log.concept2.com/api/users/me/results/"+str(c2id)+"/strokes"
s = requests.get(url,headers=headers)
if s.status_code == 200:
strokedata = pd.DataFrame.from_dict(s.json()['data'])
result = add_c2_stroke_data_db(
strokedata,workoutid,starttimeunix,
csvfilename,debug=debug,
)
return 1
else:
url = "https://log.concept2.com/api/users/me/results/"+str(c2id)
s = requests.get(url,headers=headers)
if s.status_code == 200:
workoutdata = s.json()['data']
distance = workoutdata['distance']
c2id = workoutdata['id']
workouttype = workoutdata['type']
verified = workoutdata['verified']
startdatetime = iso8601.parse_date(workoutdata['date'])
weightclass = workoutdata['weight_class']
weightcategory = 'hwt'
if weightclass == "L":
weightcategory = 'lwt'
totaltime = workoutdata['time']/10.
duration = totaltime_sec_to_string(totaltime)
duration = datetime.datetime.strptime(duration,'%H:%M:%S.%f').time()
try:
timezone_str = tz(workoutdata['timezone'])
except:
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')
result = create_c2_stroke_data_db(
distance,duration,workouttype,
workoutid,starttimeunix,
csvfilename,debug=debug,
)
return 1
return 0
return 0
def getagegrouprecord(age,sex='male',weightcategory='hwt',
distance=2000,duration=None,indf=pd.DataFrame()):

9
rowers/templates/c2_list_import2.html
View File

@@ -46,11 +46,7 @@
{% for workout in workouts %}
<tr>
<td>
{% if workout|lookup:'source' != 'Web' %}
<a href="/rowers/workout/c2import/{{ workout|lookup:'id' }}/">Import</a></td>
{% else %}
&nbsp;
{% endif %}
<td>{{ workout|lookup:'starttime' }}</td>
<td>{{ workout|lookup:'duration' }}</td>
<td>{{ workout|lookup:'distance' }}</td>
@@ -58,11 +54,8 @@
<td>{{ workout|lookup:'source' }}</td>
<td>{{ workout|lookup:'comment' }}</td>
<td>
{% if workout|lookup:'source' != 'Web' %}
{{ workout|lookup:'new' }}
{% else %}
&nbsp;
{% endif %}</td>
</td>
</tr>
{% endfor %}

86
rowers/views.py
View File

@@ -3190,7 +3190,6 @@ def addmanual_view(request):
)
print duration,'aap'
id,message = dataprep.create_row_df(r,
distance,
duration,startdatetime,
@@ -9109,40 +9108,19 @@ def workout_getc2workout_all(request,page=1,message=""):
messages.error(request,message)
else:
r = getrower(request.user)
c2ids = [item['id'] for item in res.json()['data'] if item['source'] != 'Web']
c2ids = [item['id'] for item in res.json()['data']]
alldata = {}
for item in res.json()['data']:
alldata[item['id']] = item
knownc2ids = uniqify([
w.uploadedtoc2 for w in Workout.objects.filter(user=r)
])
newids = [c2id for c2id in c2ids if not c2id in knownc2ids]
for c2id in newids:
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)
# We have stroke data
if res2.status_code == 200:
strokedata = pd.DataFrame.from_dict(res2.json()['data'])
# create the workout
try:
id,message = add_workout_from_strokedata(
request.user,c2id,data,strokedata,
source='c2')
w = Workout.objects.get(id=id)
w.uploadedtoc2=c2id
w.save()
if message:
messages.error(request,message)
except KeyError:
pass
for c2id in newids:
workoutid = c2stuff.create_async_workout(alldata,
request.user,c2id)
url = reverse(workouts_view)
return HttpResponseRedirect(url)
@@ -9393,9 +9371,51 @@ def workout_getc2workout_view(request,c2id):
if data['stroke_data']:
res2 = c2stuff.get_c2_workout_strokes(request.user,c2id)
else:
message = "This workout does not have any stroke data associated with it"
messages.error(request,message)
url = reverse(workout_c2import_view)
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 = tz(data['timezone'])
except:
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.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