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added calcdps routine

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This commit is contained in:
Sander Roosendaal
2017-09-20 11:18:42 +02:00
parent d95ac01172
commit e689955802
5 changed files with 225 additions and 63 deletions
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156
rowers/dataprepnodjango.py
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@@ -15,7 +15,7 @@ from sqlalchemy import create_engine
import sqlalchemy as sa
from rowsandall_app.settings import DATABASES
#from rowsandall_app.settings_dev import DATABASES
from rowsandall_app.settings_dev import DATABASES as DEV_DATABASES
from utils import lbstoN
@@ -50,8 +50,9 @@ database_url = 'mysql://{user}:{password}@{host}:{port}/{database_name}'.format(
port=port,
)
database_name_dev = DEV_DATABASES['default']['NAME']
database_url_debug = 'sqlite:///'+database_name
database_url_debug = 'sqlite:///'+database_name_dev
# mapping the DB column names to the CSV file column names
columndict = {
@@ -70,6 +71,7 @@ columndict = {
'wash':'wash',
'slip':'wash',
'workoutstate':' WorkoutState',
'cumdist':'cum_dist',
}
from scipy.signal import savgol_filter
@@ -471,8 +473,12 @@ def delete_strokedata(id,debug=True):
def update_strokedata(id,df,debug=True):
delete_strokedata(id)
if debug:
print "updating ",id
rowdata = dataprep(df,id=id,bands=True,barchart=True,otwpower=True,
debug=debug)
return rowdata
def testdata(time,distance,pace,spm):
t1 = np.issubdtype(time,np.number)
@@ -529,11 +535,15 @@ def read_cols_df_sql(ids,columns,debug=True):
def read_df_sql(id,debug=True):
if debug:
engine = create_engine(database_url_debug, echo=False)
print "read_df",id
print database_url_debug
else:
engine = create_engine(database_url, echo=False)
df = pd.read_sql_query(sa.text('SELECT * FROM strokedata WHERE workoutid={id}'.format(
id=id)), engine)
df = pd.read_sql_query(sa.text(
'SELECT * FROM strokedata WHERE workoutid={id}'.format(
id=id
)), engine)
engine.dispose()
return df
@@ -583,10 +593,15 @@ def smalldataprep(therows,xparam,yparam1,yparam2):
def dataprep(rowdatadf,id=0,bands=True,barchart=True,otwpower=True,
empower=True,debug=True,inboard=0.88):
empower=True,debug=True,inboard=0.88,forceunit='lbs'):
if rowdatadf.empty:
if debug:
print "empty"
return 0
if debug:
print "dataprep",id
rowdatadf.set_index([range(len(rowdatadf))],inplace=True)
t = rowdatadf.ix[:,'TimeStamp (sec)']
@@ -613,6 +628,14 @@ def dataprep(rowdatadf,id=0,bands=True,barchart=True,otwpower=True,
forceratio = averageforce/peakforce
forceratio = forceratio.fillna(value=0)
try:
drivetime = rowdatadf.ix[:,' DriveTime (ms)']
recoverytime = rowdatadf.ix[:,' StrokeRecoveryTime (ms)']
rhythm = 100.*drivetime/(recoverytime+drivetime)
rhythm = rhythm.fillna(value=0)
except:
rhythm = 0.0*forceratio
f = rowdatadf['TimeStamp (sec)'].diff().mean()
if f != 0:
windowsize = 2*(int(10./(f)))+1
@@ -635,12 +658,30 @@ def dataprep(rowdatadf,id=0,bands=True,barchart=True,otwpower=True,
p2 = p.fillna(method='ffill').apply(lambda x: timedeltaconv(x))
drivespeed = drivelength/rowdatadf[' DriveTime (ms)']*1.0e3
try:
drivespeed = drivelength/rowdatadf[' DriveTime (ms)']*1.0e3
except KeyError:
drivespeed = 0.0*rowdatadf['TimeStamp (sec)']
except TypeError:
drivespeed = 0.0*rowdatadf['TimeStamp (sec)']
drivespeed = drivespeed.fillna(value=0)
driveenergy = drivelength*averageforce*lbstoN
try:
driveenergy = rowdatadf['driveenergy']
except KeyError:
if forceunit == 'lbs':
driveenergy = drivelength*averageforce*lbstoN
else:
drivenergy = drivelength*averageforce
distance = rowdatadf.ix[:,'cum_dist']
velo = 500./p
distanceperstroke = 60.*velo/spm
if debug:
print distanceperstroke.mean()
@@ -654,6 +695,7 @@ def dataprep(rowdatadf,id=0,bands=True,barchart=True,otwpower=True,
ftime = niceformat(t2),
fpace = nicepaceformat(p2),
driveenergy=driveenergy,
distanceperstroke=distanceperstroke,
power=power,
workoutstate=workoutstate,
averageforce=averageforce,
@@ -675,6 +717,12 @@ def dataprep(rowdatadf,id=0,bands=True,barchart=True,otwpower=True,
data['hr_max'] = rowdatadf.ix[:,'hr_max']
data['hr_bottom'] = 0.0*data['hr']
try:
tel = rowdatadf.ix[:,' ElapsedTime (sec)']
except KeyError:
rowdatadf[' ElapsedTime (sec)'] = rowdatadf['TimeStamp (sec)']
if barchart:
# time increments for bar chart
time_increments = rowdatadf.ix[:,' ElapsedTime (sec)'].diff()
@@ -688,22 +736,22 @@ def dataprep(rowdatadf,id=0,bands=True,barchart=True,otwpower=True,
try:
wash = rowdatadf.ix[:,'wash']
except KeyError:
wash = 0*power
wash = 0*t
try:
catch = rowdatadf.ix[:,'catch']
except KeyError:
catch = 0*power
catch = 0*t
try:
finish = rowdatadf.ix[:,'finish']
except KeyError:
finish = 0*power
finish = 0*t
try:
peakforceangle = rowdatadf.ix[:,'peakforceangle']
except KeyError:
peakforceangle = 0*power
peakforceangle = 0*t
if data['driveenergy'].mean() == 0:
@@ -724,20 +772,53 @@ def dataprep(rowdatadf,id=0,bands=True,barchart=True,otwpower=True,
try:
slip = rowdatadf.ix[:,'slip']
except KeyError:
slip = 0*power
totalangle = finish-catch
effectiveangle = finish-wash-catch-slip
slip = 0*t
try:
totalangle = finish-catch
effectiveangle = finish-wash-catch-slip
except ValueError:
totalangle = 0*t
effectiveangle = 0*t
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)
try:
wash = savgol_filter(wash,windowsize,3)
except TypeError:
pass
try:
slip = savgol_filter(slip,windowsize,3)
except TypeError:
pass
try:
catch = savgol_filter(catch,windowsize,3)
except TypeError:
pass
try:
finish = savgol_filter(finish,windowsize,3)
except TypeError:
pass
try:
peakforceangle = savgol_filter(peakforceangle,windowsize,3)
except TypeError:
pass
try:
driveenergy = savgol_filter(driveenergy,windowsize,3)
except TypeError:
pass
try:
drivelength = savgol_filter(drivelength,windowsize,3)
except TypeError:
pass
try:
totalangle = savgol_filter(totalangle,windowsize,3)
except TypeError:
pass
try:
effectiveangle = savgol_filter(effectiveangle,windowsize,3)
except TypeError:
pass
velo = 500./p
@@ -746,18 +827,21 @@ def dataprep(rowdatadf,id=0,bands=True,barchart=True,otwpower=True,
efficiency = efficiency.replace([-np.inf,np.inf],np.nan)
efficiency.fillna(method='ffill')
try:
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
except ValueError:
pass
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:
nowindpace = rowdatadf.ix[:,'nowindpace']