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Merge branch 'feature/eff_metric' into develop

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This commit is contained in:
Sander Roosendaal
2017-08-08 12:03:25 +02:00
parent 981075fd68 fc23750731
commit b59ead6094
5 changed files with 160 additions and 37 deletions
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49
rowers/dataprep.py
View File

@@ -210,6 +210,12 @@ def clean_df_stats(datadf,workstrokesonly=True,ignorehr=True,
datadf.loc[mask,'pace'] = np.nan
except KeyError:
pass
try:
mask = datadf['efficiency'] < 0.
datadf.loc[mask,'efficiency'] = np.nan
except KeyError:
pass
try:
mask = datadf['pace']/1000. < 60.
@@ -454,7 +460,8 @@ def save_workout_database(f2,r,dosmooth=True,workouttype='rower',
if consistencychecks:
a_messages.error(r.user,'Failed consistency check: '+key+', autocorrected')
else:
a_messages.error(r.user,'Failed consistency check: '+key+', not corrected')
pass
# a_messages.error(r.user,'Failed consistency check: '+key+', not corrected')
except ZeroDivisionError:
pass
@@ -994,6 +1001,9 @@ def getrowdata_db(id=0,doclean=False):
else:
row = Workout.objects.get(id=id)
if data['efficiency'].mean() == 0 and data['power'].mean() != 0:
data = add_efficiency(id=id)
if doclean:
data = clean_df_stats(data,ignorehr=True)
@@ -1080,6 +1090,7 @@ def read_cols_df_sql(ids,columns):
# drop columns that are not in offical list
# axx = [ax[0] for ax in axes]
axx = [f.name for f in StrokeData._meta.get_fields()]
for c in columns:
if not c in axx:
columns.remove(c)
@@ -1108,10 +1119,12 @@ def read_cols_df_sql(ids,columns):
ids = tuple(ids),
))
connection = engine.raw_connection()
df = pd.read_sql_query(query,engine)
df = df.fillna(value=0)
df = df.fillna(value=0)
try:
df['peakforce'] = df['peakforce']*lbstoN
except KeyError:
@@ -1253,6 +1266,27 @@ def datafusion(id1,id2,columns,offset):
return df
def add_efficiency(id=0):
rowdata,row = getrowdata_db(id=id,doclean=False)
power = rowdata['power']
pace = rowdata['pace']/1.0e3
velo = 500./pace
ergpw = 2.8*velo**3
efficiency = 100.*ergpw/power
efficiency = efficiency.replace([-np.inf,np.inf],np.nan)
efficiency.fillna(method='ffill')
rowdata['efficiency'] = efficiency
delete_strokedata(id)
if id != 0:
rowdata['workoutid'] = id
engine = create_engine(database_url, echo=False)
with engine.connect() as conn, conn.begin():
rowdata.to_sql('strokedata',engine,if_exists='append',index=False)
conn.close()
engine.dispose()
return rowdata
# This is the main routine.
# it reindexes, sorts, filters, and smooths the data, then
# saves it to the stroke_data table in the database
@@ -1394,7 +1428,7 @@ def dataprep(rowdatadf,id=0,bands=True,barchart=True,otwpower=True,
try:
driveenergy = rowdatadf.ix[:,'driveenergy']
except KeyError:
driveenergy = 0*power
driveenergy = power*60/spm
else:
driveenergy = data['driveenergy']
@@ -1423,6 +1457,14 @@ def dataprep(rowdatadf,id=0,bands=True,barchart=True,otwpower=True,
totalangle = savgol_filter(totalangle,windowsize,3)
effectiveangle = savgol_filter(effectiveangle,windowsize,3)
velo = 500./p
ergpw = 2.8*velo**3
efficiency = 100.*ergpw/power
efficiency = efficiency.replace([-np.inf,np.inf],np.nan)
efficiency.fillna(method='ffill')
data['wash'] = wash
data['catch'] = catch
data['slip'] = slip
@@ -1432,6 +1474,7 @@ def dataprep(rowdatadf,id=0,bands=True,barchart=True,otwpower=True,
data['drivelength'] = drivelength
data['totalangle'] = totalangle
data['effectiveangle'] = effectiveangle
data['efficiency'] = efficiency
if otwpower:
try:

135
rowers/dataprepnodjango.py
View File

@@ -15,15 +15,32 @@ from sqlalchemy import create_engine
import sqlalchemy as sa
from rowsandall_app.settings import DATABASES
#from rowsandall_app.settings_dev import DATABASES
from utils import lbstoN
user = DATABASES['default']['USER']
password = DATABASES['default']['PASSWORD']
database_name = DATABASES['default']['NAME']
host = DATABASES['default']['HOST']
port = DATABASES['default']['PORT']
try:
user = DATABASES['default']['USER']
except KeyError:
user = ''
try:
password = DATABASES['default']['PASSWORD']
except KeyError:
password = ''
try:
database_name = DATABASES['default']['NAME']
except KeyError:
database_name = ''
try:
host = DATABASES['default']['HOST']
except KeyError:
host = ''
try:
port = DATABASES['default']['PORT']
except KeyError:
port = ''
database_url = 'mysql://{user}:{password}@{host}:{port}/{database_name}'.format(
user=user,
@@ -563,6 +580,10 @@ def smalldataprep(therows,xparam,yparam1,yparam2):
def dataprep(rowdatadf,id=0,bands=True,barchart=True,otwpower=True,
empower=True,debug=True):
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)'])
@@ -576,7 +597,6 @@ def dataprep(rowdatadf,id=0,bands=True,barchart=True,otwpower=True,
cumdist = rowdatadf.ix[:,'cum_dist']
power = rowdatadf.ix[:,' Power (watts)']
averageforce = rowdatadf.ix[:,' AverageDriveForce (lbs)']
drivelength = rowdatadf.ix[:,' DriveLength (meters)']
try:
@@ -590,7 +610,10 @@ def dataprep(rowdatadf,id=0,bands=True,barchart=True,otwpower=True,
forceratio = forceratio.fillna(value=0)
f = rowdatadf['TimeStamp (sec)'].diff().mean()
windowsize = 2*(int(10./(f)))+1
if f != 0:
windowsize = 2*(int(10./(f)))+1
else:
windowsize = 1
if windowsize <= 3:
windowsize = 5
@@ -660,31 +683,76 @@ 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']
drivelength = driveenergy/(averageforce*4.44822)
slip = rowdatadf.ix[:,'slip']
if windowsize > 3:
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)
data['wash'] = wash
data['catch'] = catch
data['slip'] = slip
data['finish'] = finish
data['peakforceangle'] = peakforceangle
data['driveenergy'] = driveenergy
data['drivelength'] = drivelength
data['peakforce'] = peakforce
data['averageforce'] = averageforce
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
if data['driveenergy'].mean() == 0:
try:
driveenergy = rowdatadf.ix[:,'driveenergy']
except KeyError:
driveenergy = power*60/spm
else:
driveenergy = data['driveenergy']
arclength = (inboard-0.05)*(np.radians(finish)-np.radians(catch))
if arclength.mean()>0:
drivelength = arclength
elif drivelength.mean() == 0:
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)
velo = 500./p
ergpw = 2.8*velo**3
efficiency = 100.*ergpw/power
efficiency = efficiency.replace([-np.inf,np.inf],np.nan)
efficiency.fillna(method='ffill')
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
data['efficiency'] = efficiency
if otwpower:
try:
@@ -703,11 +771,16 @@ def dataprep(rowdatadf,id=0,bands=True,barchart=True,otwpower=True,
ergpace[ergpace == np.inf] = 240.
ergpace2 = ergpace.apply(lambda x: timedeltaconv(x))
efficiency = efficiency.replace([-np.inf,np.inf],np.nan)
efficiency.fillna(method='ffill')
data['ergpace'] = ergpace*1e3
data['nowindpace'] = nowindpace*1e3
data['equivergpower'] = equivergpower
data['fergpace'] = nicepaceformat(ergpace2)
data['fnowindpace'] = nicepaceformat(nowindpace2)
data['efficiency'] = efficiency
data = data.replace([-np.inf,np.inf],np.nan)
data = data.fillna(method='ffill')

1
rowers/metrics.py
View File

@@ -22,6 +22,7 @@ axes = (
('totalangle', 'Drive Length (deg)',40,140,'pro'),
('effectiveangle', 'Effective Drive Length (deg)',40,140,'pro'),
('rhythm', 'Stroke Rhythm (%)',20,55,'pro'),
('efficiency', 'OTW efficiency (%)',0,110,'pro'),
('None', 'None',0,1,'basic'),
)

1
rowers/models.py
View File

@@ -536,6 +536,7 @@ class StrokeData(models.Model):
rhythm = models.FloatField(default=1.0,null=True,verbose_name='Rhythm')
totalangle = models.FloatField(default=0.0,null=True,verbose_name='Total Stroke Length (deg)')
effectiveangle = models.FloatField(default=0.0,null=True,verbose_name='Effective Stroke Length (deg)')
efficiency = models.FloatField(default=-1,null=True,verbose_name='OTW Efficiency')
# A wrapper around the png files
class GraphImage(models.Model):

11
rowers/views.py
View File

@@ -3571,19 +3571,25 @@ def multiflex_view(request,userid=0,
# prepare data frame
datadf = dataprep.read_cols_df_sql(ids,fieldlist)
datadf = dataprep.clean_df_stats(datadf,workstrokesonly=workstrokesonly)
datadf = dataprep.filter_df(datadf,'spm',spmmin,
largerthan=True)
datadf = dataprep.filter_df(datadf,'spm',spmmax,
largerthan=False)
datadf = dataprep.filter_df(datadf,'driveenergy',workmin,
largerthan=True)
datadf = dataprep.filter_df(datadf,'driveneergy',workmax,
largerthan=False)
datadf.dropna(axis=0,how='any',inplace=True)
datemapping = {
w.id:w.date for w in workouts
}
@@ -4038,7 +4044,6 @@ def workouts_view(request,message='',successmessage='',
else:
activity_enddate = enddate
print "aap",activity_enddate
if teamid:
try:
@@ -5631,7 +5636,7 @@ def workout_flexchart3_view(request,*args,**kwargs):
axchoicespro.pop('totalangle')
axchoicespro.pop('effectiveangle')
axchoicespro.pop('peakforceangle')
axchoicespro.pop('efficiency')
return render(request,
'flexchart3otw.html',