rowingdata package

Submodules

rowingdata.copystats module

rowingdata.copystats.main()

rowingdata.crewnerdplot module

rowingdata.crewnerdplot.main()

rowingdata.crewnerdplottime module

rowingdata.crewnerdplottime.main()

rowingdata.painsled_desktop_plot module

rowingdata.painsled_desktop_plot.main()

rowingdata.painsled_desktop_toc2 module

rowingdata.painsled_desktop_toc2.main()

rowingdata.painsledplot module

rowingdata.painsledplot.main()

rowingdata.painsledplottime module

rowingdata.painsledplottime.main()

rowingdata.painsledtoc2 module

rowingdata.painsledtoc2.main()

rowingdata.roweredit module

rowingdata.roweredit.main()

rowingdata.rowingdata module

class rowingdata.rowingdata.ErgDataParser(ed_file='ed_test.csv', row_date=datetime.datetime(2016, 11, 6, 19, 48, 41, 357000))

Parser for reading CSV files created by ErgData/Concept2 logbook

Use: data = rowingdata.ErgDataParser(“ergdata.csv”)

data.write_csv(“speedcoach_data_out.csv”)

write_csv(writeFile='example.csv')

Exports data to the CSV format that I use in rowingdata

class rowingdata.rowingdata.ErgStickParser(ed_file='ed_test.csv', row_date=datetime.datetime(2016, 11, 6, 19, 48, 41, 357000))

Parser for reading CSV files created by ErgStick

Use: data = rowingdata.ErgStickParser(“ergdata.csv”)

data.write_csv(“speedcoach_data_out.csv”)

write_csv(writeFile='example.csv')

Exports data to the CSV format that I use in rowingdata

class rowingdata.rowingdata.FITParser(readFile)

write_csv(writeFile='fit_o.csv')

class rowingdata.rowingdata.MysteryParser(Mfile='mystery.csv', row_date=datetime.datetime(2016, 11, 6, 19, 48, 41, 357000))

Parser for reading CSV files created by CrewNerd interval export

Use: data = rowingdata.MysteryParser(“mystery.csv”)

data.write_csv(“mystery.csv”)

write_csv(writeFile='example.csv')

Exports to the CSV format that I use in rowingdata

class rowingdata.rowingdata.RowProParser(RPfile='RPtest.csv', skiprows=14, row_date=datetime.datetime(2016, 11, 6, 19, 48, 41, 357000))

Parser for reading CSV files created by RowPro

Use: data = rowingdata.RowProParser(“RPdata.csv”)

data.write_csv(“RPdata_out.csv”)

write_csv(writeFile='example.csv')

Exports RowPro data to the CSV format that I use in rowingdata

class rowingdata.rowingdata.SpeedCoach2Parser(NKfile='Speedcoach2example.csv', row_date=datetime.datetime(2016, 11, 6, 19, 48, 41, 357000))

Parser for reading CSV files created by SpeedCoach GPS 2

Use: data = rowingdata.SpeedCoach2Parser(“NKGPS2data.csv”)

data.write_csv(“NKGPS2data_out.csv”)

write_csv(writeFile='example.csv')

Exports RowPro data to the CSV format that I use in rowingdata

class rowingdata.rowingdata.TCXParser(tcx_file)

Parser for reading TCX files, e.g. from CrewNerd

Use: data = rowingdata.TCXParser(“crewnerd_data.tcx”)

data.write_csv(“crewnerd_data_out.csv”)

write_csv(writeFile='example.csv', window_size=5)

Exports TCX data to the CSV format that I use in rowingdata

write_nogeo_csv(writeFile='example.csv', window_size=5)

Exports TCX data without position data (indoor) to the CSV format that I use in rowingdata

class rowingdata.rowingdata.TCXParserNoHR(tcx_file)

Parser for reading TCX files, e.g. from CrewNerd

Use: data = rowingdata.TCXParser(“crewnerd_data.tcx”)

data.write_csv(“crewnerd_data_out.csv”)

write_csv(writeFile='example.csv', window_size=5)

Exports TCX data to the CSV format that I use in rowingdata

write_nogeo_csv(writeFile='example.csv', window_size=5)

Exports TCX data without position data (indoor) to the CSV format that I use in rowingdata

class rowingdata.rowingdata.TCXParserTester(tcx_file)

getarray(str1, str2='')

rowingdata.rowingdata.addzones(df, ut2, ut1, at, tr, an, mmax)

rowingdata.rowingdata.boatedit(fileName='my1x.txt')

Easy editing or creation of a boat rigging data file. Mainly for using from the windows command line

rowingdata.rowingdata.copytocb(s)

Copy to clipboard for pasting into blog

Doesn’t work on Mac OS X

rowingdata.rowingdata.cumcpdata(rows)

rowingdata.rowingdata.dorowall(readFile='testdata', window_size=20)

Used if you have CrewNerd TCX and summary CSV with the same file name

Creates all the plots and spits out a text summary (and copies it to the clipboard too!)

rowingdata.rowingdata.ewmovingaverage(interval, window_size)

class rowingdata.rowingdata.fitsummarydata(readFile)

setsummary(separator='|')

rowingdata.rowingdata.format_dist_tick(x, pos=None)

rowingdata.rowingdata.format_pace(x, pos=None)

rowingdata.rowingdata.format_pace_tick(x, pos=None)

rowingdata.rowingdata.format_time(x, pos=None)

rowingdata.rowingdata.format_time_tick(x, pos=None)

rowingdata.rowingdata.geo_distance(lat1, lon1, lat2, lon2)

Approximate distance and bearing between two points defined by lat1,lon1 and lat2,lon2 This is a slight underestimate but is close enough for our purposes, We’re never moving more than 10 meters between trackpoints

Bearing calculation fails if one of the points is a pole.

rowingdata.rowingdata.get_file_line(linenr, f)

rowingdata.rowingdata.get_file_type(f)

rowingdata.rowingdata.get_rowpro_footer(f, converters={})

rowingdata.rowingdata.getrigging(fileName='my1x.txt')

Read a rigging object

rowingdata.rowingdata.getrower(fileName='defaultrower.txt', mc=70.0)

Read a rower object

rowingdata.rowingdata.getrowtype()

rowingdata.rowingdata.histodata(rows)

rowingdata.rowingdata.interval_string(nr, totaldist, totaltime, avgpace, avgspm, avghr, maxhr, avgdps, separator='|')

Used to create a nifty text string with the data for the interval

rowingdata.rowingdata.main()

rowingdata.rowingdata.make_cumvalues(xvalues)

Takes a Pandas dataframe with one column as input value. Tries to create a cumulative series.

rowingdata.rowingdata.make_cumvalues_array(xvalues)

Takes a Pandas dataframe with one column as input value. Tries to create a cumulative series.

rowingdata.rowingdata.make_cumvalues_rowingdata(df)

Takes entire dataframe, calculates cumulative distance and cumulative work distance

rowingdata.rowingdata.movingaverage(interval, window_size)

rowingdata.rowingdata.nanstozero(nr)

class rowingdata.rowingdata.painsledDesktopParser(sled_file='sled_test.csv')

Parser for reading CSV files created by Painsled (desktop version)

Use: data = rowingdata.painsledDesktopParser(“sled_data.csv”)

data.write_csv(“sled_data_out.csv”)

time_values()

Converts painsled style time stamps to Unix time stamps

write_csv(writeFile='example.csv')

Exports Painsled (desktop) data to the CSV format that I use in rowingdata

rowingdata.rowingdata.phys_getpower(velo, rower, rigging, bearing, vwind, winddirection, vstream=0)

rowingdata.rowingdata.read_obj(filename)

Read an object (e.g. your rower, including passwords) from a file Usage: john = rowingdata.read_obj(“john.txt”)

class rowingdata.rowingdata.rower(hrut2=142, hrut1=146, hrat=160, hrtr=167, hran=180, hrmax=192, c2username='', c2password='', weightcategory='hwt', mc=72.5, strokelength=1.35)

This class contains all the personal data about the rower

• HR threshold values
• C2 logbook username and password
• weight category

write(fileName)

rowingdata.rowingdata.roweredit(fileName='defaultrower.txt')

Easy editing or creation of a rower file. Mainly for using from the windows command line

class rowingdata.rowingdata.rowingdata(readFile, rower=<rowingdata.rowingdata.rower instance>, rowtype='Indoor Rower')

This is the main class. Read the data from the csv file and do all kinds of cool stuff with it.

Usage: row = rowingdata.rowingdata(“testdata.csv”,rowtype = “Indoor Rower”)

row.plotmeters_all()

The default rower looks for a defaultrower.txt file. If it is not found, it reverts to some arbitrary rower.

add_bearing(window_size=20)

Adds bearing. Only works if long and lat values are known

add_stream(vstream, units='m')

add_wind(vwind, winddirection, units='m')

allstats(separator='|')

Creates a nice text summary, both overall summary and a one line per interval summary

Works for painsled (both iOS and desktop)

Also copies the string to the clipboard (handy!)

bokehpaceplot()

erg_recalculatepower()

exporttotcx(fileName, notes='Exported by Rowingdata')

get_metersplot_erg(title)

get_metersplot_erg2(title)

get_metersplot_otw(title)

get_pacehrplot(title)

get_paceplot(title)

get_piechart(title)

Figure 3 - Heart Rate Time in band. This is not as simple as just totalling up the hits for each band of HR. Since each data point represents a different increment of time. This loop scans through the HR data and adds that incremental time in each band

get_time_otwpower(title)

get_timeplot_erg(title)

get_timeplot_erg2(title)

get_timeplot_otw(title)

getcp()

getvalues(keystring)

Just a tool to get a column of the row data as a numpy array

You can also just access row.df[keystring] to get a pandas Series

intervalstats(separator='|')

Used to create a nifty text summary, one row for each interval

Also copies the string to the clipboard (handy!)

Works for painsled (both iOS and desktop version) because they use the lapIdx column

intervalstats_painsled(separator='|')

Used to create a nifty text summary, one row for each interval

Also copies the string to the clipboard (handy!)

Works for painsled (both iOS and desktop version) because they use the lapIdx column

intervalstats_values()

Used to create a nifty text summary, one row for each interval

Also copies the string to the clipboard (handy!)

Works for painsled (both iOS and desktop version) because they use the lapIdx column

otw_setpower(skiprows=0, rg=<rowingphysics.rigging.rigging instance>, mc=70.0)

Adds power from rowing physics calculations to OTW result

For now, works only in singles

otw_setpower_silent(skiprows=0, rg=<rowingphysics.rigging.rigging instance at 0x081202D8>, mc=70.0)

Adds power from rowing physics calculations to OTW result

For now, works only in singles

otw_setpower_verbose(skiprows=0, rg=<rowingphysics.rigging.rigging instance at 0x081204B8>, mc=70.0)

Adds power from rowing physics calculations to OTW result

For now, works only in singles

otw_testphysics(rg=<rowingphysics.rigging.rigging instance at 0x081204E0>, mc=70.0, p=120.0, spm=30.0)

Check if erg pace is in right order

For now, works only in singles

piechart()

Figure 3 - Heart Rate Time in band. This is not as simple as just totalling up the hits for each band of HR. Since each data point represents a different increment of time. This loop scans through the HR data and adds that incremental time in each band

plotcp()

plotmeters_erg()

Creates two images containing interesting plots

x-axis is distance

Used with painsled (erg) data

plotmeters_otw()

Creates two images containing interesting plots

x-axis is distance

Used with OTW data (no Power plot)

plototwergpower()

plottime_erg()

Creates two images containing interesting plots

x-axis is time

Used with painsled (erg) data

plottime_hr()

Creates a HR vs time plot

plottime_otw()

Creates two images containing interesting plots

x-axis is time

Used with OTW data (no Power plot)

plottime_otwpower()

Creates two images containing interesting plots

x-axis is time

Used with painsled (erg) data

restoreintervaldata()

spm_fromtimestamps()

summary(separator='|')

Creates a nifty text string that contains the key data for the row and copies it to the clipboard

update_stream(stream1, stream2, dist1, dist2, units='m')

update_wind(vwind1, vwind2, winddirection1, winddirection2, dist1, dist2, units='m')

updateinterval_string(s)

updateintervaldata(ivalues, iunits, itypes, iresults=[])

Edits the intervaldata. For example a 2x2000m values = [2000,120,2000,120] units = [‘meters’,’seconds’,’meters’,’seconds’] types = [‘work’,’rest’,’work’,’rest’]

uploadtoc2(comment='uploaded by rowingdata tool\n', rowerFile='defaultrower.txt')

Upload your row to the Concept2 logbook

Will ask for username and password if not known Will offer to store username and password locally for you. This is not mandatory

This just fills the online logbook form. It may break if Concept2 changes their website. I am waiting for a Concept2 Logbook API

write_csv(writeFile)

rowingdata.rowingdata.running_mean(x)

rowingdata.rowingdata.skip_variable_footer(f)

rowingdata.rowingdata.skip_variable_header(f)

class rowingdata.rowingdata.speedcoachParser(sc_file='sc_test.csv', row_date=datetime.datetime(2016, 11, 6, 19, 48, 41, 357000))

Parser for reading CSV files created by SpeedCoach

Use: data = rowingdata.speedcoachParser(“speedcoachdata.csv”)

data.write_csv(“speedcoach_data_out.csv”)

write_csv(writeFile='example.csv')

Exports SpeedCoach CSV data to the CSV format that I use in rowingdata

rowingdata.rowingdata.spm_toarray(l)

class rowingdata.rowingdata.summarydata(readFile)

This is used to create nice summary texts from CrewNerd’s summary CSV

Usage: sumd = rowingdata.summarydata(“crewnerdsummary.CSV”)

sumd.allstats()

sumd.shortstats()

allstats(separator='|')

shortstats()

rowingdata.rowingdata.summarystring(totaldist, totaltime, avgpace, avgspm, avghr, maxhr, avgdps, readFile='', separator='|')

Used to create a nifty string summarizing your entire row

rowingdata.rowingdata.tailwind(bearing, vwind, winddir, vstream=0)

Calculates head-on head/tailwind in direction of rowing

positive numbers are tail wind

rowingdata.rowingdata.totimestamp(dt, epoch=datetime.datetime(1970, 1, 1, 0, 0))

rowingdata.rowingdata.workstring(totaldist, totaltime, avgpace, avgspm, avghr, maxhr, avgdps, separator='|', symbol='W')

rowingdata.rowingdata.write_obj(obj, filename)

Save an object (e.g. your rower) to a file

rowingdata.rowingdata.y_axis_range(ydata, miny=0, padding=0.1, ultimate=[-1000000000.0, 1000000000.0])

rowingdata.speedcoachplot module

rowingdata.speedcoachplot.main()

rowingdata.speedcoachplottime module

rowingdata.speedcoachplottime.main()

rowingdata.speedcoachtoc2 module

rowingdata.speedcoachtoc2.main()

rowingdata.tcxplot module

rowingdata.tcxplot.main()

rowingdata.tcxplot_nogeo module

rowingdata.tcxplot_nogeo.main()

rowingdata.tcxplottime module

rowingdata.tcxplottime.main()

rowingdata.tcxplottime_nogeo module

rowingdata.tcxplottime_nogeo.main()

rowingdata.tcxtoc2 module

rowingdata.tcxtoc2.main()

Module contents