Make plotintervals more rational (dataprep) - continue at cum_flex
This commit is contained in:
sanderroosendaal
File diff suppressed because it is too large
Load Diff
142
rowers/dataprep.py
Normal file
142
rowers/dataprep.py
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@@ -0,0 +1,142 @@
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from rowers.models import Workout, User, Rower
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from rowingdata import rowingdata as rrdata
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from rowingdata import rower as rrower
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from rowingdata import main as rmain
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from pandas import DataFrame,Series
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import pandas as pd
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import numpy as np
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from scipy.signal import savgol_filter
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import datetime
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def niceformat(values):
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out = []
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for v in values:
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formattedv = strfdelta(v)
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out.append(formattedv)
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return out
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def strfdelta(tdelta):
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try:
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minutes,seconds = divmod(tdelta.seconds,60)
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tenths = int(tdelta.microseconds/1e5)
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except AttributeError:
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minutes,seconds = divmod(tdelta.view(np.int64),60e9)
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seconds,rest = divmod(seconds,1e9)
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tenths = int(rest/1e8)
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res = "{minutes:0>2}:{seconds:0>2}.{tenths:0>1}".format(
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minutes=minutes,
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seconds=seconds,
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tenths=tenths,
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)
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return res
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def nicepaceformat(values):
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out = []
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for v in values:
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formattedv = strfdelta(v)
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out.append(formattedv)
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return out
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def timedeltaconv(x):
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dt = datetime.timedelta(seconds=x)
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return dt
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def rdata(file,rower=rrower()):
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try:
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res = rrdata(file,rower=rower)
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except IOError:
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res = 0
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return res
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def getrowdata(id=0):
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# check if valid ID exists (workout exists)
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row = Workout.objects.get(id=id)
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f1 = row.csvfilename
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# get user
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r = row.user
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u = r.user
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rr = rrower(hrmax=r.max,hrut2=r.ut2,
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hrut1=r.ut1,hrat=r.at,
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hrtr=r.tr,hran=r.an)
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rowdata = rdata(f1,rower=rr)
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return rowdata,row
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def dataprep(rowdatadf):
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rowdatadf.set_index([range(len(rowdatadf))],inplace=True)
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t = rowdatadf.ix[:,'TimeStamp (sec)']
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t = pd.Series(t-rowdatadf.ix[0,'TimeStamp (sec)'])
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row_index = rowdatadf.ix[:,' Stroke500mPace (sec/500m)'] > 3000
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rowdatadf.loc[row_index,' Stroke500mPace (sec/500m)'] = 3000.
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p = rowdatadf.ix[:,' Stroke500mPace (sec/500m)']
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hr = rowdatadf.ix[:,' HRCur (bpm)']
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spm = rowdatadf.ix[:,' Cadence (stokes/min)']
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cumdist = rowdatadf.ix[:,'cum_dist']
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power = rowdatadf.ix[:,' Power (watts)']
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averageforce = rowdatadf.ix[:,' AverageDriveForce (lbs)']
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drivelength = rowdatadf.ix[:,' DriveLength (meters)']
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peakforce = rowdatadf.ix[:,' PeakDriveForce (lbs)']
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f = rowdatadf['TimeStamp (sec)'].diff().mean()
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windowsize = 2*(int(10./(f)))+1
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if windowsize <= 3:
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windowsize = 5
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if windowsize > 3:
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spm = savgol_filter(spm,windowsize,3)
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hr = savgol_filter(hr,windowsize,3)
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drivelength = savgol_filter(drivelength,windowsize,3)
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t2 = t.fillna(method='ffill').apply(lambda x: timedeltaconv(x))
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p2 = p.fillna(method='ffill').apply(lambda x: timedeltaconv(x))
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drivespeed = drivelength/rowdatadf[' DriveTime (ms)']*1.0e3
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driveenergy = drivelength*averageforce*4.44822
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distance = rowdatadf.ix[:,'cum_dist']
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data = DataFrame(
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dict(
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time = t2,
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hr = hr,
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pace = p2,
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spm = spm,
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cumdist = cumdist,
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ftime = niceformat(t2),
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fpace = nicepaceformat(p2),
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driveenergy=driveenergy,
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power=power,
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averageforce=averageforce,
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drivelength=drivelength,
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peakforce=peakforce,
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distance=distance,
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drivespeed=drivespeed
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)
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)
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return data
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@@ -4,8 +4,6 @@ from rowingdata import main as rmain
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from rowingdata import cumcpdata,histodata
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from rowingdata import rowingdata as rrdata
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from rowingdata import TCXParser,RowProParser,ErgDataParser
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from rowingdata import painsledDesktopParser,speedcoachParser,ErgStickParser
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from bokeh.plotting import figure, ColumnDataSource, Figure,curdoc
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from bokeh.models import CustomJS,Slider
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@@ -45,14 +43,8 @@ from scipy.signal import savgol_filter
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import stravastuff
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def rdata(file,rower=rrower()):
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try:
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res = rrdata(file,rower=rower)
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except IOError:
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res = 0
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return res
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from rowers.dataprep import rdata
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import rowers.dataprep as dataprep
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def tailwind(bearing,vwind,winddir):
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""" Calculates head-on head/tailwind in direction of rowing
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@@ -68,42 +60,9 @@ def tailwind(bearing,vwind,winddir):
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return vtail
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def niceformat(values):
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out = []
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for v in values:
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formattedv = strfdelta(v)
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out.append(formattedv)
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return out
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def strfdelta(tdelta):
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minutes,seconds = divmod(tdelta.seconds,60)
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tenths = int(tdelta.microseconds/1e5)
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res = "{minutes:0>2}:{seconds:0>2}.{tenths:0>1}".format(
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minutes=minutes,
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seconds=seconds,
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tenths=tenths,
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)
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return res
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def nicepaceformat(values):
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out = []
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for v in values:
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formattedv = strfdelta(v)
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out.append(formattedv)
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return out
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def timedeltaconv(x):
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# if x<=0 or x>1e9:
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# x=0
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dt = datetime.timedelta(seconds=x)
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return dt
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from rowers.dataprep import nicepaceformat,niceformat
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from rowers.dataprep import timedeltaconv
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def interactive_histoall(theworkouts):
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@@ -535,66 +494,14 @@ def interactive_chart(id=0,promember=0):
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else:
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TOOLS = 'pan,box_zoom,wheel_zoom,reset,tap,hover,crosshair'
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# check if valid ID exists (workout exists)
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row = Workout.objects.get(id=id)
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# g = GraphImage.objects.filter(workout=row).order_by("-creationdatetime")
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f1 = row.csvfilename
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# create interactive plot
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# get user
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# u = User.objects.get(id=row.user.id)
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r = row.user
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u = r.user
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rr = rrower(hrmax=r.max,hrut2=r.ut2,
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hrut1=r.ut1,hrat=r.at,
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hrtr=r.tr,hran=r.an)
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rowdata = rdata(f1,rower=rr)
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rowdata,row = dataprep.getrowdata(id=id)
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if rowdata == 0:
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return "","CSV Data File Not Found"
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t = rowdata.df.ix[:,'TimeStamp (sec)']
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t = pd.Series(t-rowdata.df.ix[0,'TimeStamp (sec)'])
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row_index = rowdata.df.ix[:,' Stroke500mPace (sec/500m)'] > 3000
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rowdata.df.loc[row_index,' Stroke500mPace (sec/500m)'] = 3000.
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p = rowdata.df.ix[:,' Stroke500mPace (sec/500m)']
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hr = rowdata.df.ix[:,' HRCur (bpm)']
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spm = rowdata.df.ix[:,' Cadence (stokes/min)']
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cumdist = rowdata.df.ix[:,'cum_dist']
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f = rowdata.df['TimeStamp (sec)'].diff().mean()
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windowsize = 2*(int(10./(f)))+1
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if windowsize <= 3:
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windowsize = 5
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if windowsize > 3:
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spm = savgol_filter(spm,windowsize,3)
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t2 = t.fillna(method='ffill').apply(lambda x: timedeltaconv(x))
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p2 = p.fillna(method='ffill').apply(lambda x: timedeltaconv(x))
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datadf = dataprep.dataprep(rowdata.df)
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source = ColumnDataSource(
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data = dict(
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x=t2,
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y=hr,
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y2=p2,
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tf = niceformat(t2),
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pace = nicepaceformat(p2),
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heartrate = hr,
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spm=spm,
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spmc=np.rint(10*spm)/10.,
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cumdist=cumdist,
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)
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datadf
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)
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@@ -605,7 +512,7 @@ def interactive_chart(id=0,promember=0):
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toolbar_sticky=False,
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tools=TOOLS)
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plot.line('x','y2',source=source,legend="Pace")
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plot.line('time','pace',source=source,legend="Pace")
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plot.title.text = row.name
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plot.title.text_font_size=value("1.0em")
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plot.xaxis.axis_label = "Time"
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@@ -636,17 +543,17 @@ def interactive_chart(id=0,promember=0):
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hover.tooltips = OrderedDict([
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('Time','@tf'),
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('Pace','@pace'),
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('HR','@heartrate'),
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('SPM','@spmc{1.1}'),
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('Time','@ftime'),
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('Pace','@fpace'),
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('HR','@hr'),
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('SPM','@spm{1.1}'),
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('Distance','@cumdist{1.1}'),
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])
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hover.mode = 'mouse'
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plot.extra_y_ranges = {"hr": Range1d(start=100,end=200)}
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plot.line('x','y',source=source,color="red",
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plot.line('time','hr',source=source,color="red",
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y_range_name="hr", legend="Heart Rate")
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plot.add_layout(LinearAxis(y_range_name="hr",axis_label="HR"),'right')
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@@ -672,19 +579,6 @@ def interactive_cum_flex_chart(theworkouts,promember=0,
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thedata = pd.concat(therows)
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csvcolumns = {
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'time': 'TimeStamp (sec)',
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'distance': 'cum_dist',
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'hr': ' HRCur (bpm)',
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'spm': ' Cadence (stokes/min)',
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'pace': ' Stroke500mPace (sec/500m)',
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'power': ' Power (watts)',
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'averageforce': ' AverageDriveForce (lbs)',
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'drivelength': ' DriveLength (meters)',
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'peakforce': ' PeakDriveForce (lbs)',
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'driveenergy': 'driveenergy',
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'drivespeed': 'drivespeed',
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}
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axlabels = {
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'time': 'Time',
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@@ -729,47 +623,29 @@ def interactive_cum_flex_chart(theworkouts,promember=0,
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}
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thedata['driveenergy'] = thedata[' DriveLength (meters)']*thedata[' AverageDriveForce (lbs)']*4.44822
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datadf = dataprep.dataprep(thedata)
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# thedata['driveenergy'] = thedata[' DriveLength (meters)']*thedata[' AverageDriveForce (lbs)']*4.44822
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# throw out zeros from dataframe
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thedata = thedata[thedata[csvcolumns[yparam1]] > 0]
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thedata = thedata[thedata[csvcolumns[xparam]] > 0]
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#thedata = thedata[thedata[csvcolumns[yparam1]] > 0]
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#thedata = thedata[thedata[csvcolumns[xparam]] > 0]
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datadf = datadf[datadf[yparam1] > 0]
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datadf = datadf[datadf[xparam] > 0]
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if yparam2 != 'None':
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thedata = thedata[thedata[csvcolumns[yparam2]] > 0]
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#thedata = thedata[thedata[csvcolumns[yparam2]] > 0]
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datadf = datadf[thedata[yparam2] > 0]
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# check if dataframe not empty
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if thedata.empty:
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if datadf.empty:
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return ['','<p>No non-zero data in selection</p>','','']
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spm = thedata.ix[:,csvcolumns['spm']]
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x1 = datadf.ix[:,xparam]
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f = thedata['TimeStamp (sec)'].diff().mean()
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if not np.isnan(f):
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windowsize = 2*(int(10./(f)))+1
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else:
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windowsize = 5
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if windowsize <= 3:
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windowsize = 5
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if windowsize > 3:
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spm = savgol_filter(spm,windowsize,3)
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thedata[' Cadence (stokes/min)'] = spm
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drivelength = thedata[' DriveLength (meters)']
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if windowsize > 3:
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drivelength = savgol_filter(drivelength,windowsize,3)
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thedata[' DriveLength (meters)'] = drivelength
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thedata['drivespeed'] = drivelength/thedata[' DriveTime (ms)']*1.0e3
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x1 = thedata.ix[:,csvcolumns[xparam]]
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y1 = thedata.ix[:,csvcolumns[yparam1]]
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y1 = datadf.ix[:,yparam1]
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if yparam2 != 'None':
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y2 = thedata.ix[:,csvcolumns[yparam2]]
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y2 = datadf.ix[:,yparam2]
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else:
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y2 = y1
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@@ -811,18 +687,14 @@ def interactive_cum_flex_chart(theworkouts,promember=0,
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y1 = y1.fillna(method='ffill').apply(lambda x: timedeltaconv(x))
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time = thedata.ix[:,csvcolumns['time']]
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hr = thedata.ix[:,csvcolumns['hr']]
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if windowsize > 3:
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hr = savgol_filter(hr,windowsize,3)
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pace = thedata.ix[:,csvcolumns['pace']]
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distance = thedata.ix[:,csvcolumns['distance']]
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power = thedata.ix[:,csvcolumns['power']]
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time = datadf.ix[:,'time']
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hr = datadf.ix[:,'hr']
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pace = datadf.ix[:,'pace']
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distance = datadf.ix[:,'distance']
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power = datadf.ix[:,'power']
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ftime = datadf.ix[:,'ftime']
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fpace = datadf.ix[:,'fpace']
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spm = datadf.ix[:,'spm']
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# Add hover to this comma-separated string and see what changes
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@@ -853,34 +725,25 @@ def interactive_cum_flex_chart(theworkouts,promember=0,
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x1=x1,
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y1=y1,
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y2=y2,
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time=niceformat(
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time.fillna(method='ffill').apply(lambda x: timedeltaconv(x))
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),
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pace=nicepaceformat(
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pace.fillna(method='ffill').apply(lambda x: timedeltaconv(x))
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),
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time=ftime,
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pace=fpace,
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hr = hr,
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spm = spm,
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spmc=np.rint(10*spm)/10.,
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distance=distance,
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power=power,
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)
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)
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source2 = ColumnDataSource(
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data = dict(
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x1=x1,
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y1=y1,
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y2=y2,
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time=niceformat(
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time.fillna(method='ffill').apply(lambda x: timedeltaconv(x))
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),
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pace=nicepaceformat(
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pace.fillna(method='ffill').apply(lambda x: timedeltaconv(x))
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),
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time=ftime,
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pace=fpace,
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hr = hr,
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spm = spm,
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spmc=np.rint(10*spm)/10.,
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distance=distance,
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power=power,
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)
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@@ -947,7 +810,7 @@ def interactive_cum_flex_chart(theworkouts,promember=0,
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('Time','@time'),
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('Pace','@pace'),
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('HR','@hr'),
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('SPM','@spmc{1.1}'),
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('SPM','@spm{1.1}'),
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('Power','@power{int}'),
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])
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@@ -966,7 +829,6 @@ def interactive_cum_flex_chart(theworkouts,promember=0,
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var time1 = data['time']
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var pace1 = data['pace']
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var hr1 = data['hr']
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var spmc1 = data['spmc']
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var distance1 = data['distance']
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var power1 = data['power']
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|
||||
@@ -985,7 +847,6 @@ def interactive_cum_flex_chart(theworkouts,promember=0,
|
||||
data2['time'] = []
|
||||
data2['pace'] = []
|
||||
data2['hr'] = []
|
||||
data2['spmc'] = []
|
||||
data2['distance'] = []
|
||||
data2['power'] = []
|
||||
data2['x1mean'] = []
|
||||
@@ -1005,7 +866,6 @@ def interactive_cum_flex_chart(theworkouts,promember=0,
|
||||
data2['time'].push(time1[i])
|
||||
data2['pace'].push(pace1[i])
|
||||
data2['hr'].push(hr1[i])
|
||||
data2['spmc'].push(spmc1[i])
|
||||
data2['distance'].push(distance1[i])
|
||||
data2['power'].push(power1[i])
|
||||
|
||||
@@ -1129,20 +989,7 @@ def interactive_flex_chart2(id=0,promember=0,
|
||||
'drivespeed':4,
|
||||
}
|
||||
|
||||
# check if valid ID exists (workout exists)
|
||||
row = Workout.objects.get(id=id)
|
||||
# g = GraphImage.objects.filter(workout=row).order_by("-creationdatetime")
|
||||
|
||||
f1 = row.csvfilename
|
||||
|
||||
r = row.user
|
||||
u = r.user
|
||||
|
||||
rr = rrower(hrmax=r.max,hrut2=r.ut2,
|
||||
hrut1=r.ut1,hrat=r.at,
|
||||
hrtr=r.tr,hran=r.an)
|
||||
|
||||
rowdata = rdata(f1,rower=rr)
|
||||
rowdata,row = dataprep.getrowdata(id=id)
|
||||
if rowdata == 0:
|
||||
return "","CSV Data File Not Found"
|
||||
|
||||
@@ -1521,22 +1368,7 @@ def interactive_flex_chart2(id=0,promember=0,
|
||||
|
||||
def interactive_bar_chart(id=0,promember=0):
|
||||
# check if valid ID exists (workout exists)
|
||||
row = Workout.objects.get(id=id)
|
||||
|
||||
f1 = row.csvfilename
|
||||
|
||||
# create interactive plot
|
||||
plot = Figure(plot_width=400,plot_height=300)
|
||||
# get user
|
||||
# u = User.objects.get(id=row.user.id)
|
||||
r = row.user
|
||||
u = r.user
|
||||
|
||||
rr = rrower(hrmax=r.max,hrut2=r.ut2,
|
||||
hrut1=r.ut1,hrat=r.at,
|
||||
hrtr=r.tr,hran=r.an)
|
||||
|
||||
rowdata = rdata(f1,rower=rr)
|
||||
rowdata,row = dataprep.getrowdata(id=id)
|
||||
if rowdata == 0:
|
||||
return "","CSV Data File Not Found"
|
||||
|
||||
@@ -1716,18 +1548,11 @@ def interactive_comparison_chart(id1=0,id2=0,xparam='distance',yparam='spm',
|
||||
|
||||
|
||||
# check if valid ID exists (workout exists)
|
||||
row1 = Workout.objects.get(id=id1)
|
||||
row2 = Workout.objects.get(id=id2)
|
||||
|
||||
f1 = row1.csvfilename
|
||||
f2 = row2.csvfilename
|
||||
|
||||
|
||||
rowdata1 = rdata(f1)
|
||||
rowdata1,row1 = dataprep.getrowdata(id=id1)
|
||||
rowdata2,row2 = dataprep.getrowdata(id=id1)
|
||||
if rowdata1 == 0:
|
||||
return "","CSV Data File Not Found"
|
||||
|
||||
rowdata2 = rdata(f2)
|
||||
if rowdata2 == 0:
|
||||
return "","CSV Data File Not Found"
|
||||
|
||||
@@ -1924,17 +1749,7 @@ def interactive_comparison_chart(id1=0,id2=0,xparam='distance',yparam='spm',
|
||||
|
||||
def interactive_otw_advanced_pace_chart(id=0,promember=0):
|
||||
# check if valid ID exists (workout exists)
|
||||
row = Workout.objects.get(id=id)
|
||||
|
||||
f1 = row.csvfilename
|
||||
|
||||
|
||||
# get user
|
||||
# u = User.objects.get(id=row.user.id)
|
||||
r = row.user
|
||||
u = r.user
|
||||
|
||||
rowdata = rdata(f1)
|
||||
rowdata,row = dataprep.getrowdata(id=id)
|
||||
if rowdata == 0:
|
||||
return "","CSV Data File Not Found"
|
||||
|
||||
|
||||
Reference in New Issue
Block a user