def main(argv):
statistics = StatisticsClass()
if sys.argv[1] == '-h':
print('How to run file: main.py -i <inputfile> <algorithm>')
elif sys.argv[1] == '-i':
coordX = []
coordY = []
parsedFile, statistics.ImportAndConvertFileStatistic = createObjectsFromFile(sys.argv[2])
measurementFixations = []
if (sys.argv[4] == '-d'):
statistics.ImportDataToDatabase = initialize_db(parsedFile)
print('Converting file time: %s' % statistics.ImportAndConvertFileStatistic)
parsedMeasurements = []
if sys.argv[4] == '-f':
parsedMeasurements = parsedFile
elif sys.argv[4] == '-d':
parsedMeasurements, statistics.ImportAndConvertDatabaseStatistic = getFromDatabase()
else:
parsedMeasurements = parsedFile
if sys.argv[3] == 'I-DT':
print('Starting measurement using I-DT algorithm')
for e, measurement in enumerate(parsedMeasurements):
if measurement.Type == 'SS':
plt.plot(measurement.CoordX, measurement.CoordY, 'ko', markersize=10, label='Eye-tracker points' if e == 0 else "")
coordX, coordY, statistics.AlgorithmRunTimeStatistic, statistics.NumberOfFixationsCount, fixations, statistics.SaccadeCount, newPointList, summaryList = idt.calculateIdtAlgorithm(parsedMeasurements)
measurementFixations.append(fixations)
plt.plot(coordX, coordY, 'wo', markersize=5, markeredgecolor='r', label='Calculated fixations')
print('Ending measurement using I-DT algorithm')
plt.legend(bbox_to_anchor=(0., 1.02, 1., .102), loc=3, ncol=2, mode="expand", borderaxespad=0.)
elif sys.argv[3] == 'I-VT':
print('Starting measurement using I-VT algorithm')
for e, measurement in enumerate(parsedMeasurements):
if measurement.Type == 'SS':
plt.plot(measurement.CoordX, measurement.CoordY, 'ko', markersize=10, label='Eye-tracker points' if e == 0 else "")
plt.plot(measurement.CoordX, measurement.CoordY,'ko', color='green', markersize=6)
coordX, coordY, statistics.AlgorithmRunTimeStatistic, statistics.NumberOfFixationsCount, fixations, statistics.SaccadeCount, newPointList, summaryList = ivt.calculateIvtAlgorithm(parsedMeasurements)
measurementFixations.append(newPointList)
#plt.plot(coordX, coordY, 'wo', markersize=5, markeredgecolor='r', label='Calculated fixations')
print('Ending measurement using I-VT algorithm')
plt.legend(bbox_to_anchor=(0., 1.02, 1., .102), loc=3, ncol=2, mode="expand", borderaxespad=0.)
elif sys.argv[3] == 'ML':
print('Starting measurement using Machine Learning algorithm')
for i, item in enumerate(parsedMeasurements):
if item.Type == 'SS':
plt.plot(item.CoordX, item.CoordY, 'ko', markersize=10, label='Eye-tracker points' if i == 0 else "")
fixations = ivt.prepareDataIvt(parsedMeasurements)
points = ml.calculateMlHelper(fixations)
coordX, coordY, fixationsForPoint, timealgorithm, ite, fixations, saccades, newPointList, summaryList = ml.calculateML(points)
plt.plot(coordX, coordY, 'wo', markersize=5, markeredgecolor='r', label='Calculated fixations')
statistics.NumberOfFixationsCount = fixationsForPoint
statistics.AlgorithmRunTimeStatistic = timealgorithm
statistics.MLPrecision = ite
statistics.SaccadeCount = len(saccades)
measurementFixations.append(newPointList)
print('Ending measurement using Machine Learning algorithm')
plt.legend(bbox_to_anchor=(0., 1.02, 1., .102), loc=3, ncol=2, mode="expand", borderaxespad=0.)
else:
print('INCORRECT ALGORITHM')
print('Number of fixations: %s, Algorithm runtime: %s s, Saccades %s' % (statistics.NumberOfFixationsCount, statistics.AlgorithmRunTimeStatistic, statistics.SaccadeCount))
fig1 = plt.gcf()
plt.show()
plt.draw()
fig1.savefig('result/' + sys.argv[2] + sys.argv[3] + '.png', dpi=100)
createExitFile(sys.argv[2], statistics, sys.argv[3])
createExitFixationFile(sys.argv[2], measurementFixations, sys.argv[3])
createSummaryFile(sys.argv[2], summaryList, sys.argv[3])
elif sys.argv[1] == '-a':
print('Available algorithms: "I-DT", "I-VT", "ML"')
else:
print('How to run file: main.py -i <inputfile> <algorithm>')
