sander/rowsandall
Private
Public Access
1
0
Fork 0
Code Activity

data fusion now working ...

Browse Source
This commit is contained in:
Sander Roosendaal
2017-03-09 17:56:48 +01:00
parent ba8c9dfddb
commit 39b80b6716
4 changed files with 47 additions and 22 deletions
Download Patch File Download Diff File Expand all files Collapse all files

25
rowers/dataprep.py
View File

@@ -959,35 +959,41 @@ def smalldataprep(therows,xparam,yparam1,yparam2):
# data fusion
def datafusion(id1,id2,columns,offset):
df1,w1 = getrowdata_db(id=id1)
df1 = df1.drop(['cumdist',
df1 = df1.drop([#'cumdist',
'hr_ut2',
'hr_ut1',
'hr_at',
'hr_tr',
'hr_an',
'hr_max',],
'hr_max',
'ftime',
'fpace',
'workoutid',
'id'],
1,errors='ignore')
columns = ['time']+columns
df2 = getsmallrowdata_db(columns,ids=[id2],doclean=False)
print df1['pace'].mean()/1000.,'mies'
df2 = getsmallrowdata_db(['time']+columns,ids=[id2],doclean=False)
offsetmillisecs = offset.seconds*1000+offset.microseconds/1000.
offsetmillisecs += offset.days*(3600*24*1000)
df2['time'] = df2['time']+offsetmillisecs
keep1 = {c:c for c in set(df1.columns)}
for c in columns:
keep1.pop(c)
for c in df1.columns:
if not c in keep1:
df1 = df1.drop(c,1,errors='ignore')
df = pd.concat([df1,df2],ignore_index=True)
df = df.sort_values(['time'])
df = df.interpolate(method='linear',axis=0,limit_direction='both')
df = df.interpolate(method='linear',axis=0,limit_direction='both',
limit=10)
df.fillna(method='bfill',inplace=True)
df['time'] = df['time']/1000.
df['pace'] = df['pace']/1000.
print df['pace'].mean(),'noot'
df['cum_dist'] = df['cumdist']
return df
@@ -1005,7 +1011,6 @@ def dataprep(rowdatadf,id=0,bands=True,barchart=True,otwpower=True,
rowdatadf.loc[row_index,' Stroke500mPace (sec/500m)'] = 3000.
p = rowdatadf.ix[:,' Stroke500mPace (sec/500m)']
print p.mean(),'aap'
hr = rowdatadf.ix[:,' HRCur (bpm)']
spm = rowdatadf.ix[:,' Cadence (stokes/min)']
cumdist = rowdatadf.ix[:,'cum_dist']