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Merge branch 'release/v10.42'

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This commit is contained in:
Sander Roosendaal
2019-10-31 15:15:35 +01:00
parent 469fbc166a 37024296c0
commit 09b57b930c
2 changed files with 135 additions and 104 deletions
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113
rowers/c2stuff.py
View File

@@ -120,7 +120,7 @@ def c2_open(user):
if (timezone.now()>r.tokenexpirydate):
res = rower_c2_token_refresh(user)
if res == None:
raise NoTokenError("User has no token")
raise NoTokenError("User has no token")
if res[0] != None:
thetoken = res[0]
else:
@@ -156,7 +156,7 @@ def get_c2_workouts(rower):
if not isprorower(rower):
return 0
try:
thetoken = c2_open(rower.user)
except NoTokenError:
@@ -181,7 +181,7 @@ def get_c2_workouts(rower):
]
knownc2ids = uniqify(knownc2ids+tombstones)
newids = [c2id for c2id in c2ids if not c2id in knownc2ids]
for c2id in newids:
@@ -267,7 +267,7 @@ def c2wc(weightclass):
# Concept2 logbook sends over split data for each interval
# We use it here to generate a custom summary
# Some users complained about small differences
# Some users complained about small differences
def summaryfromsplitdata(splitdata,data,filename,sep='|'):
totaldist = data['distance']
@@ -310,17 +310,17 @@ def summaryfromsplitdata(splitdata,data,filename,sep='|'):
restvelo = restdistance/resttime
except (ZeroDivisionError,OverflowError):
restvelo = 0
restpower = 2.8*restvelo**(3.0)
try:
avgdps = totaldist/data['stroke_count']
except (ZeroDivisionError,OverflowError,KeyError):
avgdps = 0
from rowingdata import summarystring,workstring,interval_string
sums = summarystring(totaldist,totaltime,avgpace,spm,avghr,maxhr,
avgdps,avgpower,readFile=filename,
separator=sep)
@@ -336,16 +336,16 @@ def summaryfromsplitdata(splitdata,data,filename,sep='|'):
sums += '#-{sep}SDist{sep}-Split-{sep}-SPace-{sep}-Pwr-{sep}SPM-{sep}AvgHR{sep}MaxHR{sep}DPS-\n'.format(
sep=sep
)
intervalnr=0
sa = []
results = []
try:
timebased = data['workout_type'] in ['FixedTimeSplits','FixedTimeInterval']
except KeyError:
timebased = False
for interval in splitdata:
idist = interval['distance']
itime = interval['time']/10.
@@ -373,7 +373,7 @@ def summaryfromsplitdata(splitdata,data,filename,sep='|'):
if timebased:
iarr = [itime,'seconds','work']
resarr = [idist]
if irest_time > 0:
iarr += [irest_time,'seconds','rest']
try:
@@ -390,7 +390,7 @@ def summaryfromsplitdata(splitdata,data,filename,sep='|'):
else:
ivelo = 0
ipower = 0
sums += interval_string(intervalnr,idist,itime,ipace,ispm,
iavghr,imaxhr,0,ipower,separator=sep)
intervalnr+=1
@@ -398,14 +398,14 @@ def summaryfromsplitdata(splitdata,data,filename,sep='|'):
return sums,sa,results
# Not used now. Could be used to add workout split data to Concept2
# logbook but needs to be reviewed.
# logbook but needs to be reviewed.
def createc2workoutdata_as_splits(w):
filename = w.csvfilename
row = rowingdata(csvfile=filename)
# resize per minute
df = row.df.groupby(lambda x:x/60).mean()
averagehr = int(df[' HRCur (bpm)'].mean())
maxhr = int(df[' HRCur (bpm)'].max())
@@ -443,7 +443,7 @@ def createc2workoutdata_as_splits(w):
wtype = w.workouttype
if wtype in otwtypes:
wtype = 'water'
data = {
"type": wtype,
"date": w.startdatetime.isoformat(),
@@ -467,7 +467,7 @@ def createc2workoutdata_as_splits(w):
def createc2workoutdata(w):
filename = w.csvfilename
try:
row = rowingdata(filename)
row = rowingdata(csvfile=filename)
except IOError:
return 0
@@ -478,19 +478,45 @@ def createc2workoutdata(w):
averagehr = 0
maxhr = 0
# Calculate intervalstats
itime, idist, itype = row.intervalstats_values()
lapnames = row.df[' lapIdx'].unique()
nrintervals = len(itime)
if len(lapnames != nrintervals):
newlapnames = []
for name in lapnames:
newlapnames += [name,name]
lapnames = newlapnames
intervaldata = []
for i in range(nrintervals):
if itime[i]>0:
mask = (row.df[' lapIdx'] == lapnames[i]) & (row.df[' WorkoutState'] == itype[i])
spmav = int(row.df[' Cadence (stokes/min)'][mask].mean().astype(int))
hrav = int(row.df[' HRCur (bpm)'][mask].mean().astype(int))
intervaldict = {
'type': 'distance',
'time': int(10*itime[i]),
'distance': int(idist[i]),
'heart_rate': {
'average':hrav,
},
'stroke_rate': spmav,
}
intervaldata.append(intervaldict)
# adding diff, trying to see if this is valid
t = 10*row.df.loc[:,'TimeStamp (sec)'].values-10*row.df.loc[:,'TimeStamp (sec)'].iloc[0]
try:
t[0] = t[1]
except IndexError:
pass
d = 10*row.df.loc[:,' Horizontal (meters)'].values
try:
d[0] = d[1]
except IndexError:
pass
p = abs(10*row.df.loc[:,' Stroke500mPace (sec/500m)'].values)
p = np.clip(p,0,3600)
if w.workouttype == 'bike':
@@ -516,7 +542,7 @@ def createc2workoutdata(w):
p = p.tolist()
spm = spm.tolist()
hr = hr.tolist()
for i in range(len(t)):
thisrecord = {"t":t[i],
"d":d[i],
@@ -542,19 +568,24 @@ def createc2workoutdata(w):
data = {
"type": mytypes.c2mapping[workouttype],
"date": w.startdatetime.isoformat(),
"stroke_count": int(row.stroke_count),
"timezone": w.timezone,
"distance": int(w.distance),
"time": int(10*makeseconds(durationstr)),
"weight_class": c2wc(w.weightcategory),
"comments": w.notes,
'stroke_rate': int(row.df[' Cadence (stokes/min)'].mean()),
'drag_factor': int(row.dragfactor),
"heart_rate": {
"average": averagehr,
"max": maxhr,
},
"stroke_data": stroke_data,
'workout': {
'splits': intervaldata,
}
}
return data
# Refresh Concept2 authorization token
@@ -570,7 +601,7 @@ def do_refresh_token(refreshtoken):
url = "https://log.concept2.com/oauth/access_token"
s = Session()
req = Request('POST',url, data=post_data, headers=headers)
prepped = req.prepare()
prepped.body+="&scope="
prepped.body+=scope
@@ -672,7 +703,7 @@ def get_workout(user,c2id):
url = "https://log.concept2.com/api/users/me/results/"+str(c2id)
s = requests.get(url,headers=headers)
data = s.json()['data']
splitdata = None
@@ -694,7 +725,7 @@ def get_workout(user,c2id):
strokedata = pd.DataFrame()
else:
strokedata = pd.DataFrame()
return data,strokedata
# Get stroke data belonging to C2 ID
@@ -740,7 +771,7 @@ def get_c2_workout_list(user,page=1):
return s
# Get username, having access token.
# Handy for checking if the API access is working
def get_username(access_token):
@@ -751,7 +782,7 @@ def get_username(access_token):
import urllib
url = "https://log.concept2.com/api/users/me"
response = requests.get(url,headers=headers)
me_json = response.json()
@@ -776,14 +807,14 @@ def get_userid(access_token):
response = requests.get(url,headers=headers)
except:
return 0
me_json = response.json()
try:
res = me_json['data']['id']
except KeyError:
res = 0
return res
# For debugging purposes
@@ -799,7 +830,7 @@ def process_callback(request):
return HttpResponse("got a user name: %s" % username)
def default(o):
if isinstance(o, numpy.int64): return int(o)
if isinstance(o, numpy.int64): return int(o)
raise TypeError
# Uploading workout
@@ -810,7 +841,7 @@ def workout_c2_upload(user,w):
return "This workout type cannot be uploaded to Concept2",0
except KeyError:
return "This workout type cannot be uploaded to Concept2",0
thetoken = c2_open(user)
r = Rower.objects.get(user=user)
@@ -825,7 +856,7 @@ def workout_c2_upload(user,w):
if data == 0:
return "Error: No data file. Contact info@rowsandall.com if the problem persists",0
authorizationstring = str('Bearer ' + r.c2token)
headers = {'Authorization': authorizationstring,
'user-agent': 'sanderroosendaal',
@@ -849,7 +880,7 @@ def workout_c2_upload(user,w):
else:
message = "Something went wrong in workout_c2_upload_view. Response code 200/201 but C2 sync failed: "+response.text
c2id = 0
return message,c2id
@@ -882,7 +913,7 @@ def add_workout_from_data(user,importid,data,strokedata,
workouttype = mytypes.c2mappinginv[data['type']]
except KeyError:
workouttype = 'rower'
if workouttype not in [x[0] for x in Workout.workouttypes]:
workouttype = 'other'
try:
@@ -902,14 +933,14 @@ def add_workout_from_data(user,importid,data,strokedata,
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:
@@ -951,7 +982,7 @@ def add_workout_from_data(user,importid,data,strokedata,
spm = strokedata.loc[:,'spm']
except KeyError:
spm = 0*dist2
try:
hr = strokedata.loc[:,'hr']
except KeyError:
@@ -966,7 +997,7 @@ def add_workout_from_data(user,importid,data,strokedata,
velo = 1000./pace
pace = 500./velo
# save csv
# Create data frame with all necessary data to write to csv
df = pd.DataFrame({'TimeStamp (sec)':unixtime,
@@ -988,9 +1019,9 @@ def add_workout_from_data(user,importid,data,strokedata,
' ElapsedTime (sec)':seconds
})
df.sort_values(by='TimeStamp (sec)',ascending=True)
timestr = strftime("%Y%m%d-%H%M%S")
@@ -1024,6 +1055,6 @@ def add_workout_from_data(user,importid,data,strokedata,
dosummary=True
)
return id,message

126
rowers/dataprepnodjango.py
View File

@@ -33,7 +33,7 @@ try:
user = DATABASES['default']['USER']
except KeyError:
user = ''
try:
try:
password = DATABASES['default']['PASSWORD']
except KeyError:
password = ''
@@ -98,7 +98,7 @@ def niceformat(values):
for v in values:
formattedv = strfdelta(v)
out.append(formattedv)
return out
def strfdelta(tdelta):
@@ -114,7 +114,7 @@ def strfdelta(tdelta):
seconds=seconds,
tenths=tenths,
)
return res
def nicepaceformat(values):
@@ -122,7 +122,7 @@ def nicepaceformat(values):
for v in values:
formattedv = strfdelta(v)
out.append(formattedv)
return out
@@ -131,8 +131,8 @@ def timedeltaconv(x):
dt = datetime.timedelta(seconds=x)
else:
dt = datetime.timedelta(seconds=350.)
return dt
def rdata(file,rower=rrower()):
@@ -167,7 +167,7 @@ def create_c2_stroke_data_db(
spm = 60.*nr_strokes/totalseconds
except ZeroDivisionError:
spm = 20*zeros(nr_strokes)
step = totalseconds/float(nr_strokes)
elapsed = np.arange(nr_strokes)*totalseconds/(float(nr_strokes-1))
@@ -186,7 +186,7 @@ def create_c2_stroke_data_db(
else:
power = 0
df = pd.DataFrame({
'TimeStamp (sec)': unixtime,
' Horizontal (meters)': d,
@@ -252,7 +252,7 @@ def add_c2_stroke_data_db(strokedata,workoutid,starttimeunix,csvfilename,
spm = strokedata.loc[:,'spm']
except KeyError:
spm = 0*dist2
try:
hr = strokedata.loc[:,'hr']
except KeyError:
@@ -268,7 +268,7 @@ def add_c2_stroke_data_db(strokedata,workoutid,starttimeunix,csvfilename,
velo = 1000./pace
# save csv
# Create data frame with all necessary data to write to csv
df = pd.DataFrame({'TimeStamp (sec)':unixtime,
@@ -291,11 +291,11 @@ def add_c2_stroke_data_db(strokedata,workoutid,starttimeunix,csvfilename,
'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
@@ -307,7 +307,7 @@ def add_c2_stroke_data_db(strokedata,workoutid,starttimeunix,csvfilename,
data = dataprep(df,id=workoutid,bands=False,debug=debug)
except:
return 0
return data
# Processes painsled CSV file to database
@@ -341,7 +341,7 @@ def save_workout_database(f2,r,dosmooth=True,workouttype='rower',
#row.repair()
pass
if row == 0:
return (0,'Error: CSV data file not found')
@@ -349,7 +349,7 @@ def save_workout_database(f2,r,dosmooth=True,workouttype='rower',
# auto smoothing
pace = row.df[' Stroke500mPace (sec/500m)'].values
velo = 500./pace
f = row.df['TimeStamp (sec)'].diff().mean()
if f !=0:
windowsize = 2*(int(10./(f)))+1
@@ -366,9 +366,9 @@ def save_workout_database(f2,r,dosmooth=True,workouttype='rower',
velo3 = pd.Series(velo2)
velo3 = velo3.replace([-np.inf,np.inf],np.nan)
velo3 = velo3.fillna(method='ffill')
pace2 = 500./abs(velo3)
row.df[' Stroke500mPace (sec/500m)'] = pace2
row.df = row.df.fillna(0)
@@ -378,7 +378,7 @@ def save_workout_database(f2,r,dosmooth=True,workouttype='rower',
os.remove(f2)
except:
pass
# recalculate power data
if workouttype == 'rower' or workouttype == 'dynamic' or workouttype == 'slides':
try:
@@ -386,10 +386,10 @@ def save_workout_database(f2,r,dosmooth=True,workouttype='rower',
row.write_csv(f2,gzip=True)
except:
pass
averagehr = row.df[' HRCur (bpm)'].mean()
maxhr = row.df[' HRCur (bpm)'].max()
if totaldist == 0:
totaldist = row.df['cum_dist'].max()
if totaltime == 0:
@@ -408,7 +408,7 @@ def save_workout_database(f2,r,dosmooth=True,workouttype='rower',
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
@@ -420,7 +420,7 @@ def save_workout_database(f2,r,dosmooth=True,workouttype='rower',
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:
@@ -444,7 +444,7 @@ def save_workout_database(f2,r,dosmooth=True,workouttype='rower',
message = "Warning: This workout probably already exists in the database"
privacy = 'private'
w = Workout(user=r,name=title,date=workoutdate,
workouttype=workouttype,
@@ -481,7 +481,7 @@ def handle_nonpainsled(f2,fileformat,summary=''):
# handle TCX
if (fileformat == 'tcx'):
row = TCXParser(f2)
# handle Mystery
if (fileformat == 'mystery'):
row = MysteryParser(f2)
@@ -489,7 +489,7 @@ def handle_nonpainsled(f2,fileformat,summary=''):
# handle RowPerfect
if (fileformat == 'rowperfect3'):
row = RowPerfectParser(f2)
# handle ErgData
if (fileformat == 'ergdata'):
row = ErgDataParser(f2)
@@ -501,7 +501,7 @@ def handle_nonpainsled(f2,fileformat,summary=''):
# handle Mike
if (fileformat == 'bcmike'):
row = BoatCoachAdvancedParser(f2)
# handle BoatCoach OTW
if (fileformat == 'boatcoachotw'):
row = BoatCoachOTWParser(f2)
@@ -518,7 +518,7 @@ def handle_nonpainsled(f2,fileformat,summary=''):
if (fileformat == 'speedcoach'):
row = speedcoachParser(f2)
# handle speed coach GPS 2
# handle speed coach GPS 2
if (fileformat == 'speedcoach2'):
row = SpeedCoach2Parser(f2)
try:
@@ -531,7 +531,7 @@ def handle_nonpainsled(f2,fileformat,summary=''):
# handle ErgStick
if (fileformat == 'ergstick'):
row = ErgStickParser(f2)
# handle FIT
if (fileformat == 'fit'):
row = FITParser(f2)
@@ -544,7 +544,7 @@ def handle_nonpainsled(f2,fileformat,summary=''):
# should delete file
f2 = f2[:-4]+'o.csv'
row.write_csv(f2,gzip=True)
#os.remove(f2)
try:
os.remove(f_to_be_deleted)
@@ -573,7 +573,7 @@ def new_workout_from_file(r,f2,
for fname in z.namelist():
f3 = z.extract(fname,path='media/')
id,message,f2 = new_workout_from_file(r,f3,
workouttype=workouttype,
workouttype=workouttype,
makeprivate=makeprivate,
title = title,
notes='')
@@ -590,7 +590,7 @@ def new_workout_from_file(r,f2,
os.remove(f2)
message = "It looks like this file doesn't contain stroke data."
return (0,message,f2)
# Some people try to upload RowPro summary logs
if fileformat == 'rowprolog':
os.remove(f2)
@@ -603,7 +603,7 @@ def new_workout_from_file(r,f2,
# worth supporting
if fileformat == 'unknown':
message = "We couldn't recognize the file type"
if settings.DEBUG:
if settings.DEBUG:
res = handle_sendemail_unrecognized.delay(f2,
r.user.email)
@@ -611,7 +611,7 @@ def new_workout_from_file(r,f2,
res = queuehigh.enqueue(handle_sendemail_unrecognized,
f2,r.user.email)
return (0,message,f2)
# handle non-Painsled by converting it to painsled compatible CSV
if (fileformat != 'csv'):
try:
@@ -670,7 +670,7 @@ def update_empower(id, inboard, oarlength, boattype, df, f1, debug=False):
success = False
try:
df['power empower old'] = df[' Power (watts)']
df['power empower old'] = df[' Power (watts)']
df[' Power (watts)'] = df[' Power (watts)'] * corr_factor
df['driveenergy empower old'] = df['driveenergy']
df['driveenergy'] = df['driveenergy'] * corr_factor
@@ -687,7 +687,7 @@ def update_empower(id, inboard, oarlength, boattype, df, f1, debug=False):
if debug:
print("not updated ",id)
rowdata = dataprep(df,id=id,bands=True,barchart=True,otwpower=True,
debug=debug)
@@ -708,7 +708,7 @@ def testdata(time,distance,pace,spm):
def getsmallrowdata_db(columns,ids=[],debug=False):
csvfilenames = ['media/strokedata_{id}.parquet'.format(id=id) for id in ids]
csvfilenames = ['media/strokedata_{id}.parquet.gz'.format(id=id) for id in ids]
data = []
columns = [c for c in columns if c != 'None']
@@ -720,14 +720,14 @@ def getsmallrowdata_db(columns,ids=[],debug=False):
except OSError:
pass
df = pd.concat(data,axis=0)
else:
df = pd.read_parquet(csvfilenames[0],columns=columns,engine='pyarrow')
return df
def fitnessmetric_to_sql(m,table='powertimefitnessmetric',debug=False,
doclean=False):
# test if nan among values
@@ -736,12 +736,12 @@ def fitnessmetric_to_sql(m,table='powertimefitnessmetric',debug=False,
m[key] = -1
if 'inf' in str(m[key]):
m[key] = -1
if debug:
engine = create_engine(database_url_debug, echo=False)
else:
engine = create_engine(database_url, echo=False)
columns = ', '.join(m.keys())
if use_sqlite:
placeholders = ", ".join(["?"] * len(m))
@@ -795,7 +795,7 @@ def read_cols_df_sql(ids,columns,debug=False):
df = pd.concat(data,axis=0)
return df
def read_df_sql(id,debug=False):
try:
@@ -860,15 +860,15 @@ def delete_agegroup_db(age,sex,weightcategory,debug=False):
print("Database locked")
conn.close()
engine.dispose()
def update_agegroup_db(age,sex,weightcategory,wcdurations,wcpower,
debug=False):
delete_agegroup_db(age,sex,weightcategory,debug=debug)
wcdurations = [None if type(y) is float and np.isnan(y) else y for y in wcdurations]
wcpower = [None if type(y) is float and np.isnan(y) else y for y in wcpower]
df = pd.DataFrame(
{
'duration':wcdurations,
@@ -893,7 +893,7 @@ def update_agegroup_db(age,sex,weightcategory,wcdurations,wcpower,
conn.close()
engine.dispose()
def updatecpdata_sql(rower_id,delta,cp,table='cpdata',distance=pd.Series([]),debug=False):
deletecpdata_sql(rower_id,table=table,debug=debug)
df = pd.DataFrame(
@@ -918,8 +918,8 @@ def updatecpdata_sql(rower_id,delta,cp,table='cpdata',distance=pd.Series([]),deb
engine.dispose()
def smalldataprep(therows,xparam,yparam1,yparam2):
@@ -936,7 +936,7 @@ def smalldataprep(therows,xparam,yparam1,yparam2):
try:
rowdata = dataprep(rrdata(f1).df)
rowdata = pd.DataFrame({xparam: rowdata[xparam],
yparam1: rowdata[yparam1],
yparam2: rowdata[yparam2],
@@ -960,8 +960,8 @@ def smalldataprep(therows,xparam,yparam1,yparam2):
pass
return df
def dataprep(rowdatadf,id=0,bands=True,barchart=True,otwpower=True,
empower=True,debug=False,inboard=0.88,forceunit='lbs'):
@@ -972,7 +972,7 @@ def dataprep(rowdatadf,id=0,bands=True,barchart=True,otwpower=True,
if debug:
print("dataprep",id)
# rowdatadf.set_index([range(len(rowdatadf))],inplace=True)
t = rowdatadf.loc[:,'TimeStamp (sec)']
t = pd.Series(t-rowdatadf.loc[:,'TimeStamp (sec)'].iloc[0])
@@ -985,7 +985,7 @@ def dataprep(rowdatadf,id=0,bands=True,barchart=True,otwpower=True,
velo = rowdatadf.loc[:,' AverageBoatSpeed (m/s)']
except KeyError:
velo = 500./p
hr = rowdatadf.loc[:,' HRCur (bpm)']
spm = rowdatadf.loc[:,' Cadence (stokes/min)']
cumdist = rowdatadf.loc[:,'cum_dist']
@@ -997,12 +997,12 @@ def dataprep(rowdatadf,id=0,bands=True,barchart=True,otwpower=True,
workoutstate = rowdatadf.loc[:,' WorkoutState']
except KeyError:
workoutstate = 0*hr
peakforce = rowdatadf.loc[:,' PeakDriveForce (lbs)']
forceratio = averageforce/peakforce
forceratio = forceratio.fillna(value=0)
try:
drivetime = rowdatadf.loc[:,' DriveTime (ms)']
recoverytime = rowdatadf.loc[:,' StrokeRecoveryTime (ms)']
@@ -1033,7 +1033,7 @@ def dataprep(rowdatadf,id=0,bands=True,barchart=True,otwpower=True,
except TypeError:
t2 = 0*t
p2 = p.fillna(method='ffill').apply(lambda x: timedeltaconv(x))
try:
@@ -1042,7 +1042,7 @@ def dataprep(rowdatadf,id=0,bands=True,barchart=True,otwpower=True,
drivespeed = 0.0*rowdatadf['TimeStamp (sec)']
except TypeError:
drivespeed = 0.0*rowdatadf['TimeStamp (sec)']
drivespeed = drivespeed.fillna(value=0)
try:
@@ -1100,7 +1100,7 @@ def dataprep(rowdatadf,id=0,bands=True,barchart=True,otwpower=True,
tel = rowdatadf.loc[:,' ElapsedTime (sec)']
except KeyError:
rowdatadf[' ElapsedTime (sec)'] = rowdatadf['TimeStamp (sec)']
if empower:
try:
@@ -1132,7 +1132,7 @@ def dataprep(rowdatadf,id=0,bands=True,barchart=True,otwpower=True,
else:
driveenergy = data['driveenergy']
arclength = (inboard-0.05)*(np.radians(finish)-np.radians(catch))
if arclength.mean()>0:
drivelength = arclength
@@ -1151,7 +1151,7 @@ def dataprep(rowdatadf,id=0,bands=True,barchart=True,otwpower=True,
totalangle = 0*t
effectiveangle = 0*t
if windowsize > 3 and windowsize<len(slip):
try:
wash = savgol_filter(wash,windowsize,3)
@@ -1211,7 +1211,7 @@ def dataprep(rowdatadf,id=0,bands=True,barchart=True,otwpower=True,
data['efficiency'] = efficiency
except ValueError:
pass
if otwpower:
try:
nowindpace = rowdatadf.loc[:,'nowindpace']
@@ -1221,7 +1221,7 @@ def dataprep(rowdatadf,id=0,bands=True,barchart=True,otwpower=True,
equivergpower = rowdatadf.loc[:,'equivergpower']
except KeyError:
equivergpower = 0*p+50.
nowindpace2 = nowindpace.apply(lambda x: timedeltaconv(x))
ergvelo = (equivergpower/2.8)**(1./3.)
@@ -1244,7 +1244,7 @@ def dataprep(rowdatadf,id=0,bands=True,barchart=True,otwpower=True,
data.dropna(axis=0,inplace=True,how='all')
data.dropna(axis=1,inplace=True,how='any')
# write data if id given
if id != 0:
data['workoutid'] = id