def test_dataPlot_laps(self):
"""
tests dataPlot() by plotting lap data
"""
# import data from csv
file = "run_04-28-18.csv"
device, dataFrame = tools.importData(file)
data = tools.getDataLists(device, dataFrame)
time = data["Time"]
dist = data["Distance"]["imperial"]
speed = data["Speed"]["imperial"]
hr = data["HeartRate"]
time_split = tools.lapData(dist, time)
dist_split = tools.lapData(dist, dist)
speed_split = tools.lapData(dist, speed)
hr_split = tools.lapData(dist, hr)
# plot lap data ----------------------------------
print("Plot Lap Data")
for lap in range(3):
print("lap # ", lap + 1)
x = time_split[lap]
y = hr_split[lap]
tools.dataPlot(x, y, xtitle="X VALUE", ytitle="Y VALUE", title="LAP # {}".format(lap + 1))
def test_importData(self):
"""
tests importData() by reading all csv
files in data folder.
"""
allFiles = os.listdir("..\data")
for file in allFiles:
device, dataFrame = tools.importData(file)
print("-----------------------------------------------")
print(file)
print(device)
print(list(dataFrame.columns))
def test_getDataLists(self):
"""
tests getDataLists() by printing out
data dictionary.
"""
vivofit_file = "run_04-28-18.csv"
garmin_file = "race_10-04-16.csv"
device_v, vivofit_df = tools.importData(vivofit_file)
device_g, garmin_df = tools.importData(garmin_file)
vivo_dataDict = tools.getDataLists(device_v, vivofit_df)
garmin_dataDict = tools.getDataLists(device_g, garmin_df)
dataDict = vivo_dataDict
# print tree of data dict
for key in dataDict:
if isinstance(dataDict[key], dict):
print(key)
subdict = dataDict[key]
for subkey in subdict:
print("....", subkey)
else:
print(key)
def test_plotDistribution_all(self): """ tests plotDistribution() using all data """ # import data from csv file = "run_04-28-18.csv" device, dataFrame = tools.importData(file) # full data data = tools.getDataLists(device, dataFrame) time = data["Time"] dist = data["Distance"]["imperial"] speed = data["Speed"]["imperial"] hr = data["HeartRate"] for i in speed, hr: tools.plotDistribution(i)
def test_dataPlot_all(self):
"""
tests dataPlot() by plotting all data
"""
# import data from csv
file = "run_04-28-18.csv"
device, dataFrame = tools.importData(file)
# plot all data
data = tools.getDataLists(device, dataFrame)
time = data["Time"]
dist = data["Distance"]["imperial"]
speed = data["Speed"]["imperial"]
hr = data["HeartRate"]
# test plotting full data ----------------------
print("Plot Full Data")
tools.dataPlot(time, dist, xtitle="time", ytitle="distance")
tools.dataPlot(time, speed, xtitle="time", ytitle="speed")
tools.dataPlot(time, hr, xtitle="time", ytitle="hr")
def test_lapData(self):
"""
test lapData() by printing out
all lap data.
"""
file = "race_11-15-15.csv"
device, data = tools.importData(file)
dataDict = tools.getDataLists(device, data)
time = dataDict["Time"]
dist_mi = dataDict["Distance"]["imperial"]
dist_km = dataDict["Distance"]["metric"]
speed_mi = dataDict["Speed"]["imperial"]
speed_km = dataDict["Speed"]["metric"]
speed_splits = tools.lapData(dist_km, speed_km)
for i in range(len(speed_splits)):
print("--------------------------")
print("Lap # ", i + 1)
print(speed_splits[i])
def test_getStats_all(self): """ tests getStatistics() on all data """ # import data from csv file = "run_04-28-18.csv" device, dataFrame = tools.importData(file) # full data data = tools.getDataLists(device, dataFrame) time = data["Time"] dist = data["Distance"]["imperial"] speed = data["Speed"]["imperial"] hr = data["HeartRate"] x = speed stats = tools.getStats(x) for key in stats: print(key, stats[key])
def test_getStats_laps(self):
# import data from csv
file = "run_04-28-18.csv"
device, dataFrame = tools.importData(file)
# full data
data = tools.getDataLists(device, dataFrame)
time = data["Time"]
dist = data["Distance"]["imperial"]
speed = data["Speed"]["imperial"]
hr = data["HeartRate"]
time_split = tools.lapData(dist, time)
dist_split = tools.lapData(dist, dist)
speed_split = tools.lapData(dist, speed)
hr_split = tools.lapData(dist, hr)
for i in range(len(speed_split)):
print("--------------------------------")
print("Lap # ", i + 1)
stats = tools.getStats(speed_split[i])
for key in stats:
print(key, stats[key])
if os.path.isfile('results/auxoEcoliGames_all.pk') == False:
# Concatanate the two files
with open('results/auxoEcoliGames_0_20.pk','rb') as inputFile:
games1 = pk.load(inputFile)
with open('results/auxoEcoliGames_21_end.pk','rb') as inputFile:
games2 = pk.load(inputFile)
games = dict(games1.items() + games2.items())
with open('results/auxoEcoliGames_all.pk','wb') as outputFile:
pk.dump(games,outputFile,-1)
else:
with open('results/auxoEcoliGames_all.pk','rb') as inputFile:
games = pk.load(inputFile)
print 'Loading experimental data ...\n'
#--- Load the experimental flux data ---
day1Rep1Inst = importData(inputFile = 'expData/day1Rep1.txt',delType = 'tab',dataType = 'float')
day1Rep1 = day1Rep1Inst.run()
day1Rep2Inst = importData(inputFile = 'expData/day1Rep2.txt',delType = 'tab',dataType = 'float')
day1Rep2 = day1Rep2Inst.run()
day4Rep1Inst = importData(inputFile = 'expData/day4Rep1.txt',delType = 'tab',dataType = 'float')
day4Rep1 = day4Rep1Inst.run()
day4Rep2Inst = importData(inputFile = 'expData/day4Rep2.txt',delType = 'tab',dataType = 'float')
day4Rep2 = day4Rep2Inst.run()
#--- Compute the measured fold change in growth of the pairs ----
print 'Computing the fold change in growth ...\n'
# First find the average over replicates
# Note that the data matrixes should actually be symmetric as (mutant1,mutant2) is the