Private
Public Access
1
0

solved losing Empower data

This commit is contained in:
Sander Roosendaal
2017-05-19 13:27:09 +02:00
parent a84ddf73d9
commit 3bf512179c
3 changed files with 70 additions and 43 deletions

View File

@@ -730,11 +730,11 @@ def new_workout_from_df(r,df,
csvfilename ='media/Fusion_'+timestr+'.csv'
df.rename(columns = columndict,inplace=True)
starttimeunix = mktime(startdatetime.utctimetuple())
df[' ElapsedTime (sec)'] = df['TimeStamp (sec)']
df['TimeStamp (sec)'] = df['TimeStamp (sec)']+starttimeunix
print df.info()
row = rrdata(df=df)
row.write_csv(csvfilename,gzip=True)
@@ -888,8 +888,9 @@ def getrowdata_db(id=0,doclean=False):
if doclean:
data = clean_df_stats(data,ignorehr=True)
data['averageforce'] = data['averageforce']
data['peakforce'] = data['peakforce']
# these two lines seem redundant ??
#data['averageforce'] = data['averageforce']
#data['peakforce'] = data['peakforce']
return data,row
@@ -1106,10 +1107,13 @@ def datafusion(id1,id2,columns,offset):
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')
@@ -1134,7 +1138,7 @@ def dataprep(rowdatadf,id=0,bands=True,barchart=True,otwpower=True,
empower=True,inboard=0.88):
if rowdatadf.empty:
return 0
rowdatadf.set_index([range(len(rowdatadf))],inplace=True)
t = rowdatadf.ix[:,'TimeStamp (sec)']
t = pd.Series(t-rowdatadf.ix[0,'TimeStamp (sec)'])
@@ -1246,40 +1250,62 @@ def dataprep(rowdatadf,id=0,bands=True,barchart=True,otwpower=True,
if empower:
try:
wash = rowdatadf.ix[:,'wash']
catch = rowdatadf.ix[:,'catch']
finish = rowdatadf.ix[:,'finish']
peakforceangle = rowdatadf.ix[:,'peakforceangle']
driveenergy = rowdatadf.ix[:,'driveenergy']
arclength = (inboard-0.05)*(np.radians(finish)-np.radians(catch))
if arclength.mean()>0:
drivelength = arclength
else:
drivelength = driveenergy/(averageforce*4.44822)
slip = rowdatadf.ix[:,'slip']
totalangle = finish-catch
effectiveangle = finish-wash-catch-slip
if windowsize > 3 and windowsize<len(slip):
wash = savgol_filter(wash,windowsize,3)
slip = savgol_filter(slip,windowsize,3)
catch = savgol_filter(catch,windowsize,3)
finish = savgol_filter(finish,windowsize,3)
peakforceangle = savgol_filter(peakforceangle,windowsize,3)
driveenergy = savgol_filter(driveenergy,windowsize,3)
drivelength = savgol_filter(drivelength,windowsize,3)
totalangle = savgol_filter(totalangle,windowsize,3)
effectiveangle = savgol_filter(effectiveangle,windowsize,3)
data['wash'] = wash
data['catch'] = catch
data['slip'] = slip
data['finish'] = finish
data['peakforceangle'] = peakforceangle
data['driveenergy'] = driveenergy
data['drivelength'] = drivelength
data['totalangle'] = totalangle
data['effectiveangle'] = effectiveangle
except KeyError:
pass
wash = 0*power
try:
catch = rowdatadf.ix[:,'catch']
except KeyError:
catch = 0*power
try:
finish = rowdatadf.ix[:,'finish']
except KeyError:
finish = 0*power
try:
peakforceangle = rowdatadf.ix[:,'peakforceangle']
except KeyError:
peakforceangle = 0*power
try:
driveenergy = rowdatadf.ix[:,'driveenergy']
except KeyError:
driveenergy = 0*power
arclength = (inboard-0.05)*(np.radians(finish)-np.radians(catch))
if arclength.mean()>0:
drivelength = arclength
else:
drivelength = driveenergy/(averageforce*4.44822)
try:
slip = rowdatadf.ix[:,'slip']
except KeyError:
slip = 0*power
totalangle = finish-catch
effectiveangle = finish-wash-catch-slip
if windowsize > 3 and windowsize<len(slip):
wash = savgol_filter(wash,windowsize,3)
slip = savgol_filter(slip,windowsize,3)
catch = savgol_filter(catch,windowsize,3)
finish = savgol_filter(finish,windowsize,3)
peakforceangle = savgol_filter(peakforceangle,windowsize,3)
driveenergy = savgol_filter(driveenergy,windowsize,3)
drivelength = savgol_filter(drivelength,windowsize,3)
totalangle = savgol_filter(totalangle,windowsize,3)
effectiveangle = savgol_filter(effectiveangle,windowsize,3)
data['wash'] = wash
data['catch'] = catch
data['slip'] = slip
data['finish'] = finish
data['peakforceangle'] = peakforceangle
data['driveenergy'] = driveenergy
data['drivelength'] = drivelength
data['totalangle'] = totalangle
data['effectiveangle'] = effectiveangle
if otwpower:
try:

View File

@@ -343,6 +343,7 @@ class FusionMetricChoiceForm(ModelForm):
def __init__(self, *args, **kwargs):
super(FusionMetricChoiceForm, self).__init__(*args, **kwargs)
formaxlabels2 = formaxlabels.copy()
# need to add code to remove "empty" fields
if self.instance.id is not None:
@@ -350,14 +351,14 @@ class FusionMetricChoiceForm(ModelForm):
df = dataprep.getrowdata_db(id=id)[0]
labeldict = {key:value for key,value in self.fields['columns'].choices}
for label in labeldict:
if df.ix[:,label].std() == 0:
try:
formaxlabels.pop(label)
formaxlabels2.pop(label)
except KeyError:
pass
metricchoices = list(sorted(formaxlabels.items(), key = lambda x:x[1]))
metricchoices = list(sorted(formaxlabels2.items(), key = lambda x:x[1]))
self.fields['columns'].choices = metricchoices

View File

@@ -925,8 +925,6 @@ def add_workout_from_underarmourdata(user,importid,data):
times_distance = res[0]
print distance[0:5]
print times_distance[0:5]
try:
l = timeseries['position']
@@ -6941,7 +6939,9 @@ def workout_fusion_view(request,id1=0,id2=1):
posneg = cd['posneg']
if posneg == 'neg':
timeoffset = -timeoffset
df = dataprep.datafusion(id1,id2,columns,timeoffset)
idnew,message = dataprep.new_workout_from_df(r,df,
title='Fused data',
parent=w1)