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Merge branch 'develop' into feature/opaqueid

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This commit is contained in:
Sander Roosendaal
2019-02-13 17:14:33 +01:00
parent dd633076f1 82d6b09224
commit f148b8494e
119 changed files with 116778 additions and 10192 deletions
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83
rowers/dataprep.py
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@@ -115,14 +115,19 @@ def get_latlon(id):
except Workout.DoesNotExist:
return False
rowdata = rdata(w.csvfilename)
if rowdata.df.empty:
return [pd.Series([]), pd.Series([])]
try:
try:
latitude = rowdata.df.ix[:, ' latitude']
longitude = rowdata.df.ix[:, ' longitude']
latitude = rowdata.df.loc[:, ' latitude']
longitude = rowdata.df.loc[:, ' longitude']
except KeyError:
latitude = 0 * rowdata.df.ix[:, 'TimeStamp (sec)']
longitude = 0 * rowdata.df.ix[:, 'TimeStamp (sec)']
latitude = 0 * rowdata.df.loc[:, 'TimeStamp (sec)']
longitude = 0 * rowdata.df.loc[:, 'TimeStamp (sec)']
return [latitude, longitude]
except AttributeError:
return [pd.Series([]), pd.Series([])]
@@ -964,7 +969,7 @@ def save_workout_database(f2, r, dosmooth=True, workouttype='rower',
totaltime = row.df['TimeStamp (sec)'].max(
) - row.df['TimeStamp (sec)'].min()
try:
totaltime = totaltime + row.df.ix[0, ' ElapsedTime (sec)']
totaltime = totaltime + row.df.loc[:, ' ElapsedTime (sec)'].iloc[0]
except KeyError:
pass
@@ -2077,37 +2082,37 @@ def dataprep(rowdatadf, id=0, bands=True, barchart=True, otwpower=True,
return 0
rowdatadf.set_index([range(len(rowdatadf))], inplace=True)
t = rowdatadf.ix[:, 'TimeStamp (sec)']
t = pd.Series(t - rowdatadf.ix[0, 'TimeStamp (sec)'])
t = rowdatadf.loc[:, 'TimeStamp (sec)']
t = pd.Series(t - rowdatadf.loc[:, 'TimeStamp (sec)'].iloc[0])
row_index = rowdatadf.ix[:, ' Stroke500mPace (sec/500m)'] > 3000
row_index = rowdatadf.loc[:, ' Stroke500mPace (sec/500m)'] > 3000
rowdatadf.loc[row_index, ' Stroke500mPace (sec/500m)'] = 3000.
p = rowdatadf.ix[:, ' Stroke500mPace (sec/500m)']
p = rowdatadf.loc[:, ' Stroke500mPace (sec/500m)']
try:
velo = rowdatadf.ix[:,' AverageBoatSpeed (m/s)']
velo = rowdatadf.loc[:,' AverageBoatSpeed (m/s)']
except KeyError:
velo = 500./p
hr = rowdatadf.ix[:, ' HRCur (bpm)']
spm = rowdatadf.ix[:, ' Cadence (stokes/min)']
cumdist = rowdatadf.ix[:, 'cum_dist']
power = rowdatadf.ix[:, ' Power (watts)']
averageforce = rowdatadf.ix[:, ' AverageDriveForce (lbs)']
drivelength = rowdatadf.ix[:, ' DriveLength (meters)']
hr = rowdatadf.loc[:, ' HRCur (bpm)']
spm = rowdatadf.loc[:, ' Cadence (stokes/min)']
cumdist = rowdatadf.loc[:, 'cum_dist']
power = rowdatadf.loc[:, ' Power (watts)']
averageforce = rowdatadf.loc[:, ' AverageDriveForce (lbs)']
drivelength = rowdatadf.loc[:, ' DriveLength (meters)']
try:
workoutstate = rowdatadf.ix[:, ' WorkoutState']
workoutstate = rowdatadf.loc[:, ' WorkoutState']
except KeyError:
workoutstate = 0 * hr
peakforce = rowdatadf.ix[:, ' PeakDriveForce (lbs)']
peakforce = rowdatadf.loc[:, ' PeakDriveForce (lbs)']
forceratio = averageforce / peakforce
forceratio = forceratio.fillna(value=0)
try:
drivetime = rowdatadf.ix[:, ' DriveTime (ms)']
recoverytime = rowdatadf.ix[:, ' StrokeRecoveryTime (ms)']
drivetime = rowdatadf.loc[:, ' DriveTime (ms)']
recoverytime = rowdatadf.loc[:, ' StrokeRecoveryTime (ms)']
rhythm = 100. * drivetime / (recoverytime + drivetime)
rhythm = rhythm.fillna(value=0)
except:
@@ -2152,7 +2157,7 @@ def dataprep(rowdatadf, id=0, bands=True, barchart=True, otwpower=True,
else:
drivenergy = drivelength * averageforce
distance = rowdatadf.ix[:, 'cum_dist']
distance = rowdatadf.loc[:, 'cum_dist']
velo = 500. / p
distanceperstroke = 60. * velo / spm
@@ -2184,26 +2189,26 @@ def dataprep(rowdatadf, id=0, bands=True, barchart=True, otwpower=True,
if bands:
# HR bands
data['hr_ut2'] = rowdatadf.ix[:, 'hr_ut2']
data['hr_ut1'] = rowdatadf.ix[:, 'hr_ut1']
data['hr_at'] = rowdatadf.ix[:, 'hr_at']
data['hr_tr'] = rowdatadf.ix[:, 'hr_tr']
data['hr_an'] = rowdatadf.ix[:, 'hr_an']
data['hr_max'] = rowdatadf.ix[:, 'hr_max']
data['hr_ut2'] = rowdatadf.loc[:, 'hr_ut2']
data['hr_ut1'] = rowdatadf.loc[:, 'hr_ut1']
data['hr_at'] = rowdatadf.loc[:, 'hr_at']
data['hr_tr'] = rowdatadf.loc[:, 'hr_tr']
data['hr_an'] = rowdatadf.loc[:, 'hr_an']
data['hr_max'] = rowdatadf.loc[:, 'hr_max']
data['hr_bottom'] = 0.0 * data['hr']
try:
tel = rowdatadf.ix[:, ' ElapsedTime (sec)']
tel = rowdatadf.loc[:, ' ElapsedTime (sec)']
except KeyError:
rowdatadf[' ElapsedTime (sec)'] = rowdatadf['TimeStamp (sec)']
if barchart:
# time increments for bar chart
time_increments = rowdatadf.ix[:, ' ElapsedTime (sec)'].diff()
time_increments = rowdatadf.loc[:, ' ElapsedTime (sec)'].diff()
try:
time_increments.ix[0] = time_increments.ix[1]
time_increments.iloc[0] = time_increments.iloc[1]
except KeyError:
time_increments.ix[0] = 1.
time_increments.iloc[0] = 1.
time_increments = 0.5 * time_increments + 0.5 * np.abs(time_increments)
x_right = (t2 + time_increments.apply(lambda x: timedeltaconv(x)))
@@ -2212,28 +2217,28 @@ def dataprep(rowdatadf, id=0, bands=True, barchart=True, otwpower=True,
if empower:
try:
wash = rowdatadf.ix[:, 'wash']
wash = rowdatadf.loc[:, 'wash']
except KeyError:
wash = 0 * power
try:
catch = rowdatadf.ix[:, 'catch']
catch = rowdatadf.loc[:, 'catch']
except KeyError:
catch = 0 * power
try:
finish = rowdatadf.ix[:, 'finish']
finish = rowdatadf.loc[:, 'finish']
except KeyError:
finish = 0 * power
try:
peakforceangle = rowdatadf.ix[:, 'peakforceangle']
peakforceangle = rowdatadf.loc[:, 'peakforceangle']
except KeyError:
peakforceangle = 0 * power
if data['driveenergy'].mean() == 0:
try:
driveenergy = rowdatadf.ix[:, 'driveenergy']
driveenergy = rowdatadf.loc[:, 'driveenergy']
except KeyError:
driveenergy = power * 60 / spm
else:
@@ -2246,7 +2251,7 @@ def dataprep(rowdatadf, id=0, bands=True, barchart=True, otwpower=True,
drivelength = driveenergy / (averageforce * 4.44822)
try:
slip = rowdatadf.ix[:, 'slip']
slip = rowdatadf.loc[:, 'slip']
except KeyError:
slip = 0 * power
@@ -2319,11 +2324,11 @@ def dataprep(rowdatadf, id=0, bands=True, barchart=True, otwpower=True,
if otwpower:
try:
nowindpace = rowdatadf.ix[:, 'nowindpace']
nowindpace = rowdatadf.loc[:, 'nowindpace']
except KeyError:
nowindpace = p
try:
equivergpower = rowdatadf.ix[:, 'equivergpower']
equivergpower = rowdatadf.loc[:, 'equivergpower']
except KeyError:
equivergpower = 0 * p + 50.