def test_summary(self):
row = rowingdata.rowingdata(csvfile='testdata/testdata.csv')
summary = row.summary()
emptysummary = len(summary) == 0
assert_equal(emptysummary, False)
want = """Workout Summary - testdata/summarytest.csv
--|Total|-Total----|--Avg--|-Avg-|Avg-|-Avg-|-Max-|-Avg
--|Dist-|-Time-----|-Pace--|-Pwr-|SPM-|-HR--|-HR--|-DPS
--|12743|00:57:35.9|02:15.6|000.0|22.5|000.0|000.0|09.8
W-|07410|00:29:55.0|02:01.1|000.0|25.8|000.0|000.0|09.6
R-|05335|00:27:41.3|02:35.7|000.0|19.0|000.0|000.0|11.4
Workout Details
#-|SDist|-Split-|-SPace-|-Pwr-|SPM-|AvgHR|MaxHR|DPS-
01|02579|10:18.8|02:00.0|000.0|26.7|000.0|0.0|09.4
02|02431|09:46.4|02:00.6|000.0|25.7|000.0|0.0|09.7
03|02400|09:49.8|02:02.9|000.0|25.0|000.0|0.0|09.8
"""
r = rowingdata.rowingdata(csvfile='testdata/summarytest.csv')
got = r.allstats()
assert_equal.__self__.maxDiff = None
assert_equal(want, got)
def test_cumcp(self):
row1 = rowingdata.rowingdata(csvfile='testdata/testdata.csv')
row2 = rowingdata.rowingdata(csvfile='testdata/testdata.csv')
df = rowingdata.cumcpdata([row1, row2])
isempty = df.empty
assert_equal(isempty, False)
def test_histo(self):
row1 = rowingdata.rowingdata(csvfile='testdata/testdata.csv')
row2 = rowingdata.rowingdata(csvfile='testdata/testdata.csv')
power = rowingdata.histodata([row1,row2])
isempty = len(power)==0
assert_equals(isempty,False)
def test_cumcp(self):
row1 = rowingdata.rowingdata(csvfile='testdata/testdata.csv')
row2 = rowingdata.rowingdata(csvfile='testdata/testdata.csv')
df = rowingdata.cumcpdata([row1,row2])
isempty = df.empty
assert_equals(isempty,False)
def test_histo(self):
row1 = rowingdata.rowingdata(csvfile='testdata/testdata.csv')
row2 = rowingdata.rowingdata(csvfile='testdata/testdata.csv')
power = rowingdata.histodata([row1, row2])
isempty = len(power) == 0
assert_equal(isempty, False)
def test_addition(self):
row1 = rowingdata.rowingdata(csvfile='testdata/testdata_part1.csv')
row2 = rowingdata.rowingdata(csvfile='testdata/testdata_part2.csv')
row = row1 + row2
len1 = len(row2)
len2 = len(row1)
assert_equal(len(row), len1 + len2)
def test_add_overlap(self):
row1 = rowingdata.rowingdata(csvfile='testdata/testdata.csv')
row2 = rowingdata.rowingdata(csvfile='testdata/testdata.csv')
row = row1+row2
len1 = len(row)
len2 = len(row1)
assert_equals(len1,len2)
def test_add_overlap(self):
row1 = rowingdata.rowingdata(csvfile='testdata/testdata.csv')
row2 = rowingdata.rowingdata(csvfile='testdata/testdata.csv')
row = row1 + row2
len1 = len(row)
len2 = len(row1)
assert_equal(len1, len2)
def testtcxexport(self):
csvfile='testdata/Speedcoach2example.csv'
assert_equals(rowingdata.get_file_type(csvfile),'speedcoach2')
r=rowingdata.SpeedCoach2Parser(csvfile=csvfile)
summarystring = r.summary()
row=rowingdata.rowingdata(df=r.df)
assert_equals(row.number_of_rows,97)
tcxfile = 'testdata/testtcx.tcx'
row.exporttotcx(tcxfile)
assert_equals(rowingdata.get_file_type(tcxfile),'tcx')
r2 = rowingdata.TCXParser(tcxfile)
row=rowingdata.rowingdata(df=r.df)
assert_equals(row.number_of_rows,97)
def testtcxexport(self):
csvfile = 'testdata/Speedcoach2example.csv'
assert_equal(rowingdata.get_file_type(csvfile), 'speedcoach2')
r = rowingdata.SpeedCoach2Parser(csvfile=csvfile)
summarystring = r.summary()
row = rowingdata.rowingdata(df=r.df)
assert_equal(row.number_of_rows, 97)
tcxfile = 'testdata/testtcx.tcx'
row.exporttotcx(tcxfile)
assert_equal(rowingdata.get_file_type(tcxfile), 'tcx')
r2 = rowingdata.TCXParser(tcxfile)
row = rowingdata.rowingdata(df=r.df)
assert_equal(row.number_of_rows, 97)
def testpainsled(self):
csvfile = 'testdata/PainsledForce.csv'
row = rowingdata.rowingdata(csvfile=csvfile)
averageforce_lbs = int(row.df[' AverageDriveForce (lbs)'].mean())
averageforce_N = int(row.df[' AverageDriveForce (N)'].mean())
assert_equal(averageforce_N, 398)
assert_equal(averageforce_lbs, 89)
def testspeedcoach(self):
csvfile = 'testdata/EmpowerSpeedCoachForce.csv'
r = rowingdata.SpeedCoach2Parser(csvfile=csvfile)
row = rowingdata.rowingdata(df=r.df)
averageforce_lbs = int(row.df[' AverageDriveForce (lbs)'].mean())
averageforce_N = int(row.df[' AverageDriveForce (N)'].mean())
assert_equal(averageforce_N, 263)
assert_equal(averageforce_lbs, 59)
def test_getpower(self):
velo = 4.0
r = rowingdata.getrower()
rg = rowingdata.getrigging()
row = rowingdata.SpeedCoach2Parser('testdata/SpeedCoach2v2.12.csv')
row = rowingdata.rowingdata(df=row.df)
result = row.otw_setpower_silent(skiprows=40)
assert_equals(result,1)
def test_getpower(self):
velo = 4.0
r = rowingdata.getrower()
rg = rowingdata.getrigging()
row = rowingdata.SpeedCoach2Parser('testdata/SpeedCoach2v2.12.csv')
row = rowingdata.rowingdata(df=row.df)
result = row.otw_setpower_silent(skiprows=40)
assert_equal(result, 1)
def test_bearing(self):
velo = 4.0
r = rowingdata.getrower()
rg = rowingdata.getrigging()
row = rowingdata.SpeedCoach2Parser('testdata/SpeedCoach2v2.12.csv')
row = rowingdata.rowingdata(df=row.df)
result = row.add_bearing()
assert_equals(result,1)
def test_bearing(self):
velo = 4.0
r = rowingdata.getrower()
rg = rowingdata.getrigging()
row = rowingdata.SpeedCoach2Parser('testdata/SpeedCoach2v2.12.csv')
row = rowingdata.rowingdata(df=row.df)
result = row.add_bearing()
assert_equal(result, 1)
def testcurvedata(self):
file = 'testdata/rp3_curve.csv'
r = rowingdata.RowPerfectParser(file)
row = rowingdata.rowingdata(df=r.df)
df = row.get_instroke_data('curve_data')
assert_equals(len(df),468)
cs = row.get_instroke_columns()
assert_equals(len(cs),1)
assert_equals(cs[0],'curve_data')
file = 'testdata/quiske_per_stroke_left.csv'
r = rowingdata.QuiskeParser(file)
row = rowingdata.rowingdata(df=r.df)
df = row.get_instroke_data('oar angle velocity curve')
assert_equals(len(df),25)
cs = row.get_instroke_columns()
assert_equals(len(cs),2)
assert_equals(cs[0],'boat accelerator curve')
def test_repair(self):
row = rowingdata.rowingdata(csvfile='testdata/testdata.csv')
len1 = len(row)
row.repair()
len2 = len(row)
assert_equal(len1, len2)
def test_repair(self):
row = rowingdata.rowingdata(csvfile='testdata/testdata.csv')
len1 = len(row)
row.repair()
len2 = len(row)
assert_equals(len1,len2)
def testcurvedata(self):
file = 'testdata/rp3_curve.csv'
r = rowingdata.RowPerfectParser(file)
row = rowingdata.rowingdata(df=r.df)
df = row.get_instroke_data('curve_data')
assert_equal(len(df), 468)
cs = row.get_instroke_columns()
assert_equal(len(cs), 1)
assert_equal(cs[0], 'curve_data')
file = 'testdata/quiske_per_stroke_left.csv'
r = rowingdata.QuiskeParser(file)
row = rowingdata.rowingdata(df=r.df)
df = row.get_instroke_data('oar angle velocity curve')
assert_equal(len(df), 25)
cs = row.get_instroke_columns()
assert_equal(len(cs), 2)
assert_equal(cs[0], 'boat accelerator curve')
class TestAddPowerZones:
row = rowingdata.rowingdata(csvfile='testdata/testdata.csv')
def test_bearing(self):
r = rowingdata.getrower()
rg = rowingdata.getrigging()
row = rowingdata.SpeedCoach2Parser('testdata/SpeedCoach2v2.12.csv')
row = rowingdata.rowingdata(df=row.df)
result = rowingdata.addpowerzones(row.df, 225, [23, 53, 76, 87, 91])
def testmystery(self):
csvfile='testdata/mystery.csv'
assert_equals(rowingdata.get_file_type(csvfile),'mystery')
r=rowingdata.MysteryParser(csvfile=csvfile)
row=rowingdata.rowingdata(df=r.df)
assert_equals(row.number_of_rows,4550)
totaldist=row.df['cum_dist'].max()
assert_equals(totaldist,7478)
totaltime=row.df['TimeStamp (sec)'].max()-row.df['TimeStamp (sec)'].min()
assert_equals(int(totaltime),2325)
checks = row.check_consistency()
assert_equals(checks['velo_time_distance'],True)
def testergdata(self):
csvfile='testdata/ergdata_example.csv'
assert_equals(rowingdata.get_file_type(csvfile),'ergdata')
r=rowingdata.ErgDataParser(csvfile=csvfile)
row=rowingdata.rowingdata(df=r.df)
assert_equals(row.number_of_rows,180)
totaldist=row.df['cum_dist'].max()
assert_equals(totaldist,1992)
totaltime=row.df['TimeStamp (sec)'].max()-row.df['TimeStamp (sec)'].min()
assert_equals(int(totaltime),520)
checks = row.check_consistency()
assert_equals(checks['velo_time_distance'],True)
def testspeedcoach(self):
csvfile='testdata/speedcoachexample.csv'
assert_equals(rowingdata.get_file_type(csvfile),'speedcoach')
r=rowingdata.speedcoachParser(csvfile=csvfile)
row=rowingdata.rowingdata(df=r.df)
assert_equals(row.number_of_rows,476)
totaldist=row.df['cum_dist'].max()
assert_equals(totaldist,9520)
totaltime=row.df['TimeStamp (sec)'].max()-row.df['TimeStamp (sec)'].min()
assert_equals(totaltime,3176.5)
checks = row.check_consistency()
assert_equals(checks['velo_time_distance'],True)
def testergstick(self):
csvfile='testdata/ergstick.csv'
assert_equals(rowingdata.get_file_type(csvfile),'ergstick')
r=rowingdata.ErgStickParser(csvfile=csvfile)
row=rowingdata.rowingdata(df=r.df)
assert_equals(row.number_of_rows,2400)
totaldist=row.df['cum_dist'].max()
assert_equals(int(totaldist),4959)
totaltime=row.df['TimeStamp (sec)'].max()-row.df['TimeStamp (sec)'].min()
assert_equals(int(totaltime),1201)
checks = row.check_consistency()
assert_equals(checks['velo_time_distance'],True)
def testrowpro(self):
csvfile='testdata/RP_testdata.csv'
assert_equals(rowingdata.get_file_type(csvfile),'rp')
r=rowingdata.RowProParser(csvfile=csvfile)
row=rowingdata.rowingdata(df=r.df)
assert_equals(row.number_of_rows,988)
totaldist=row.df['cum_dist'].max()
assert_equals(totaldist,10000)
assert_equals(row.rowdatetime,datetime.datetime(2016,3,15,19,49,48,863000,utc))
totaltime=row.df['TimeStamp (sec)'].max()-row.df['TimeStamp (sec)'].min()
assert_equals(int(10*totaltime),22653)
checks = row.check_consistency()
assert_equals(checks['velo_time_distance'],True)
def testpainsleddesktop(self):
csvfile='testdata/painsled_desktop_example.csv'
assert_equals(rowingdata.get_file_type(csvfile),'painsleddesktop')
r=rowingdata.painsledDesktopParser(csvfile=csvfile)
row=rowingdata.rowingdata(df=r.df)
assert_equals(row.number_of_rows,638)
totaldist=row.df['cum_dist'].max()
assert_equals(totaldist,7097)
assert_equals(row.rowdatetime,datetime.datetime(2016,3,29,17,41,27,93000,utc))
totaltime=row.df['TimeStamp (sec)'].max()-row.df['TimeStamp (sec)'].min()
assert_equals(int(totaltime),1802)
checks = row.check_consistency()
assert_equals(checks['velo_time_distance'],True)
def test_plot_otw(self, mock_fig, mock_Fig):
row = rowingdata.SpeedCoach2Parser(csvfile='testdata/Speedcoach2example.csv')
row = rowingdata.rowingdata(df=row.df)
row.plotmeters_otw()
row.plottime_otw()
row.plottime_otwpower()
fig = row.get_timeplot_otw('aap')
fig = row.get_metersplot_otw('aap')
fig = row.get_time_otwpower('aap')
fig = row.get_metersplot_otwpower('aap')
fig = row.get_timeplot_otwempower('aap')
fig = row.get_metersplot_otwempower('aap')
def testrowprointervals(self):
csvfile='testdata/RP_interval.csv'
assert_equals(rowingdata.get_file_type(csvfile),'rp')
r=rowingdata.RowProParser(csvfile=csvfile)
row=rowingdata.rowingdata(df=r.df)
assert_equals(row.number_of_rows,1674)
totaldist=row.df['cum_dist'].max()
assert_equals(int(totaldist),19026)
assert_equals(row.rowdatetime,datetime.datetime(2016,1,12,19,23,10,878000,utc))
totaltime=row.df['TimeStamp (sec)'].max()-row.df['TimeStamp (sec)'].min()
assert_equals(int(totaltime),4800)
checks = row.check_consistency()
assert_equals(checks['velo_time_distance'],True)
def testspeedcoach2(self):
csvfile='testdata/Speedcoach2example.csv'
assert_equals(rowingdata.get_file_type(csvfile),'speedcoach2')
r=rowingdata.SpeedCoach2Parser(csvfile=csvfile)
row=rowingdata.rowingdata(df=r.df)
assert_equals(row.number_of_rows,97)
totaldist=row.df['cum_dist'].max()
assert_equals(int(10*totaldist),7516)
assert_equals(row.rowdatetime,datetime.datetime(2016,7,28,11,35,1,500000,utc))
totaltime=row.df['TimeStamp (sec)'].max()-row.df['TimeStamp (sec)'].min()
assert_equals(int(totaltime),170)
checks = row.check_consistency()
assert_equals(checks['velo_time_distance'],True)
def testboatcoach(self):
csvfile='testdata/boatcoach.csv'
assert_equals(rowingdata.get_file_type(csvfile),'boatcoach')
r=rowingdata.BoatCoachParser(csvfile=csvfile)
row=rowingdata.rowingdata(df=r.df)
assert_equals(row.number_of_rows,119)
totaldist=row.df['cum_dist'].max()
assert_equals(totaldist,499)
assert_equals(row.rowdatetime,datetime.datetime(2016,11,28,8,37,2,0,utc))
totaltime=row.df['TimeStamp (sec)'].max()-row.df['TimeStamp (sec)'].min()
assert_equals(int(totaltime),118)
checks = row.check_consistency()
assert_equals(checks['velo_time_distance'],True)
def testfit(self):
fitfile='testdata/3x250m.fit'
assert_equals(rowingdata.get_file_type(fitfile),'fit')
r=rowingdata.FITParser(fitfile)
row=rowingdata.rowingdata(df=r.df)
assert_equals(row.number_of_rows,94)
totaldist=row.df['cum_dist'].max()
assert_equals(int(totaldist),750)
assert_equals(row.rowdatetime,datetime.datetime(2016,7,28,9,35,29,0,utc))
totaltime=row.df['TimeStamp (sec)'].max()-row.df['TimeStamp (sec)'].min()
assert_equals(int(10*totaltime),4870)
checks = row.check_consistency()
assert_equals(checks['velo_time_distance'],False)
def testspeedcoach2v127(self):
csvfile='testdata/SpeedCoach2Linkv1.27.csv'
assert_equals(rowingdata.get_file_type(csvfile),'speedcoach2')
r=rowingdata.SpeedCoach2Parser(csvfile=csvfile)
row=rowingdata.rowingdata(df=r.df)
assert_equals(row.number_of_rows,1408)
totaldist=row.df['cum_dist'].max()
assert_equals(totaldist,14344.5)
assert_equals(row.rowdatetime,datetime.datetime(2016,11,5,9,2,3,200000,utc))
totaltime=row.df['TimeStamp (sec)'].max()-row.df['TimeStamp (sec)'].min()
assert_equals(int(10*totaltime),45018)
checks = row.check_consistency()
assert_equals(checks['velo_time_distance'],True)
def test_plot_erg(self,mock_fig, mock_Fig):
row = rowingdata.rowingdata(csvfile='testdata/testdata.csv')
row.plotmeters_erg()
row.plottime_erg()
fig = row.get_metersplot_erg2('aap')
fig = row.get_timeplot_erg2('aap')
fig = row.get_pacehrplot('aap')
fig = row.get_paceplot('aap')
fig = row.get_metersplot_erg('aap')
fig = row.get_timeplot_erg('aap')
row.plottime_hr()
row.piechart()
row.power_piechart()
fig = row.get_power_piechart('aap')
fig = row.get_piechart('aap')
def test_plot_erg(self, mock_fig, mock_Fig):
row = rowingdata.rowingdata(csvfile='testdata/testdata.csv')
row.plotmeters_erg()
row.plottime_erg()
fig = row.get_metersplot_erg2('aap')
fig = row.get_timeplot_erg2('aap')
fig = row.get_pacehrplot('aap')
fig = row.get_paceplot('aap')
fig = row.get_metersplot_erg('aap')
fig = row.get_timeplot_erg('aap')
row.plottime_hr()
row.piechart()
row.power_piechart()
fig = row.get_power_piechart('aap')
fig = row.get_piechart('aap')
def test_write_tcx(self):
row = rowingdata.rowingdata()
filename = os.getcwd() + '/test_write.gpx`'
try:
row.exporttogpx(filename)
with open(filename) as f:
contents = f.read()
finally:
# NOTE: To retain the tempfile if the test fails, remove
# the try-finally clauses
try:
os.remove(filename)
except FileNotFoundError:
pass
assert_equal(len(contents), 822)
def main():
readFile = argv[1]
try:
rowerFile = argv[2]
except IndexError:
rowerFile = "defaultrower.txt"
rower = rowingdata.getrower(rowerFile)
row = rowingdata.rowingdata(readFile, rowtype="Indoor Rower", rower=rower)
print(row.allstats())
row.plotmeters_erg()
print("done " + readFile)
def test_write_csv(self):
row = rowingdata.rowingdata(csvfile='testdata/testdata.csv',
absolutetimestamps=False)
filename = os.getcwd() + '/test_write.csv'
try:
row.write_csv(filename)
with open(filename) as f:
contents = f.read()
finally:
# NOTE: To retain the tempfile if the test fails, remove
# the try-finally clauses
try:
os.remove(filename)
except FileNotFoundError:
pass
assert_equal(True, len(contents) > 30000)
class TestCorrectedRowingData:
row = rowingdata.rowingdata(csvfile='testdata/correctedpainsled.csv')
def test_filetype(self):
assert_equal(rowingdata.get_file_type('testdata/testdata.csv'), 'csv')
def test_basic_rowingdata(self):
assert_equal(self.row.rowtype, 'Indoor Rower')
assert_equal(self.row.dragfactor, 95.8808988764045)
assert_equal(self.row.number_of_rows, 445)
assert_equal(self.row.rowdatetime,
datetime.datetime(2017, 5, 30, 19, 4, 16, 383211, utc))
totaldist = self.row.df['cum_dist'].max()
totaltime = self.row.df['TimeStamp (sec)'].max(
) - self.row.df['TimeStamp (sec)'].min()
totaltime = totaltime + self.row.df.loc[0, ' ElapsedTime (sec)']
assert_equal(int(totaltime), 1309)
assert_equal(totaldist, 5000)
assert_equal(self.row.df[' Cadence (stokes/min)'].mean(),
20.339325842696628)
def main():
readFile = argv[1]
try:
rowerFile = argv[2]
except IndexError:
rowerFile = "defaultrower.txt"
rower = rowingdata.getrower(rowerFile)
row = rowingdata.rowingdata(readFile,rowtype="Indoor Rower",
rower=rower)
print(row.allstats())
row.plotmeters_erg()
print("done "+readFile)
def test_getvalues(self):
row = rowingdata.rowingdata(csvfile='testdata/testdata.csv')
spm = row.getvalues(' Cadence (stokes/min)')
assert_equals(len(row),len(spm))
def test_spmfromtimestamp(self):
row = rowingdata.rowingdata(csvfile='testdata/testdata.csv')
row.spm_fromtimestamps()
def test_summary(self):
row = rowingdata.rowingdata(csvfile='testdata/testdata.csv')
summary = row.summary()
emptysummary = len(summary) == 0
assert_equals(emptysummary,False)
def test_bearing(self):
r = rowingdata.getrower()
rg = rowingdata.getrigging()
row = rowingdata.SpeedCoach2Parser('testdata/SpeedCoach2v2.12.csv')
row = rowingdata.rowingdata(df=row.df)
result = rowingdata.addpowerzones(row.df, 225, [23,53,76,87,91])
def checkfile(f2, verbose=False):
fileformat = rowingdata.get_file_type(f2)
summary = 'a'
notread = 1
if verbose:
print(fileformat)
if len(fileformat) == 3 and fileformat[0] == 'zip':
with zipfile.ZipFile(f2) as z:
f = z.extract(z.namelist()[0], path='C:/Downloads')
fileformat = fileformat[2]
os.remove(f_to_be_deleted)
if fileformat == 'unknown':
return 0
# handle non-Painsled
if (fileformat != 'csv'):
# handle RowPro:
if (fileformat == 'rp'):
row = rowingdata.RowProParser(f2)
# handle TCX
if (fileformat == 'tcx'):
row = rowingdata.TCXParser(f2)
row.write_csv(f2 + 'o.csv')
row = rowingdata.rowingdata(csvfile=f2 + 'o.csv')
os.remove(f2 + 'o.csv')
notread = 0
# handle Mystery
if (fileformat == 'mystery'):
row = rowingdata.MysteryParser(f2)
# handle Quiske
if (fileformat == 'quiske'):
row = rowingdata.QuiskeParser(f2)
# handle RitmoTime
if (fileformat == 'ritmotime'):
row = rowingdata.RitmoTimeParser(f2)
# handle TCX no HR
if (fileformat == 'tcxnohr'):
row = rowingdata.TCXParserNoHR(f2)
row.write_csv(f2 + 'o.csv')
row = rowingdata.rowingdata(csvfile=f2 + 'o.csv')
os.remove(f2 + 'o.csv')
notread = 0
# handle ErgData
if (fileformat == 'ergdata'):
row = rowingdata.ErgDataParser(f2)
# handle CoxMate
if (fileformat == 'coxmate'):
row = rowingdata.CoxMateParser(f2)
# handle BoatCoachOTW
if (fileformat == 'boatcoachotw'):
row = rowingdata.BoatCoachOTWParser(f2)
# handle BoatCoach
if (fileformat == 'boatcoach'):
row = rowingdata.BoatCoachParser(f2)
# handle painsled desktop
if (fileformat == 'painsleddesktop'):
row = rowingdata.painsledDesktopParser(f2)
# handle speed coach GPS
if (fileformat == 'speedcoach'):
row = rowingdata.speedcoachParser(f2)
# handle speed coach GPS 2
if (fileformat == 'speedcoach2'):
row = rowingdata.SpeedCoach2Parser(f2)
summary = row.allstats()
v = rowingdata.get_empower_firmware(f2)
rig = rowingdata.get_empower_rigging(f2)
if (fileformat == 'rowperfect3'):
row = rowingdata.RowPerfectParser(f2)
# handle ErgStick
if (fileformat == 'ergstick'):
row = rowingdata.ErgStickParser(f2)
# handle Kinomap
if (fileformat == 'kinomap'):
row = rowingdata.KinoMapParser(f2)
# handle FIT
if (fileformat == 'fit'):
row = rowingdata.FITParser(f2)
row.write_csv(f2 + 'o.csv')
row = rowingdata.rowingdata(csvfile=f2 + 'o.csv')
os.remove(f2 + 'o.csv')
notread = 0
# handle Humon
if (fileformat == 'humon'):
row = rowingdata.HumonParser(f2)
row.write_csv(f2 + 'o.csv')
row = rowingdata.rowingdata(csvfile=f2 + 'o.csv')
os.remove(f2 + 'o.csv')
notread = 0
# handle workout log (no stroke data)
if (fileformat == 'c2log'):
return 0
if notread:
row = rowingdata.rowingdata(df=row.df)
else:
row = rowingdata.rowingdata(csvfile=f2)
nr_of_rows = row.number_of_rows
distmax = row.df['cum_dist'].max()
timemax = row.df['TimeStamp (sec)'].max() - row.df['TimeStamp (sec)'].min()
nrintervals = len(row.df[' lapIdx'].unique())
mintime = row.df['TimeStamp (sec)'].min()
maxtime = row.df['TimeStamp (sec)'].max()
if verbose:
print(("nr lines", row.number_of_rows))
print(("data ", row.rowdatetime))
print(("dist ", distmax))
print(("Time ", timemax))
print(("Nr intervals ", nrintervals))
print(("Min time ",mintime))
print(("Max time ",maxtime))
res = row.intervalstats_values()
int1time = res[0][0]
int1dist = res[1][0]
if verbose:
print(("Interval 1 time ", int1time))
print(("Interval 1 dist ", int1dist))
y = row.rowdatetime.year
m = row.rowdatetime.month
d = row.rowdatetime.day
h = row.rowdatetime.hour
tz = row.rowdatetime.tzname()
minute = row.rowdatetime.minute
sec = row.rowdatetime.second
results = {
'type': fileformat,
'nr_lines': nr_of_rows,
'year': y,
'month': m,
'day': d,
'hour': h,
'minute': minute,
'second': sec,
'dist': int(distmax),
'seconds': int(timemax),
'nrintervals': nrintervals,
'lap 1 time': int(int1time),
'lap 1 dist': int(int1dist),
'timezone': tz,
'summary':summary,
}
return results
