import numpy as np
import AnalysisToolForSingleSet as AT
if __name__ == "__main__":
# should have more varriable REMEMBER: DON'T CHANGE THIS CODE FIRST, CHANGE THE CODE FOR CONVERTING DATA FROM SRT TO SVN FIRST IF YOU DECIDE TO COMBINING CATEGORIES
Start = 0
End = 9000
inpath = "Input/"
nameFiles = np.loadtxt("NameFile.txt", dtype='S')
print nameFiles
title = ["Dyad", "Cov", "Time", "Gaze", "Talking Hawking", "Talking Shake"]
ori1 = AT.getOverallResult(inpath, Start, End, nameFiles, False)
name = "Output/OverallData_EndTime_5min.csv"
AT.printResult(ori1, title, name)
ori1 = AT.getOverallResult(inpath, Start, End, nameFiles, True)
name = "Output/OverallData_EndTime_Actual.csv"
AT.printResult(ori1, title, name)
]
SpeakType = [
"NoSpeak_", "Typing_", "Speaking_", "SSS_", "Hovering_", "Sound_",
"NoSound_"
]
Person = ["H_", "S_"]
Character = ["Mean", "Median", "PopularSD", "Frequency", "Max", "Min"]
inpath = "Input/"
nameFiles = np.loadtxt("NameFile.txt", dtype='S')
print nameFiles
title1 = ["Dyad", "Cov"]
nameOutput1 = "Output/DiscriptiveData_5mins.csv"
title1 = getTitle(title1, GazeType, SpeakType, Person, Character)
ori1 = AT.getDiscriptiveData(inpath, Start, End, nameFiles, False)
AT.printResult(ori1, title1, nameOutput1)
title2 = ["Dyad", "Cov", "StartFrame"]
nameOutput2 = "Output/DiscriptiveData_100secs.csv"
title2 = getTitle(title2, GazeType, SpeakType, Person, Character)
ori2 = AT.getDiscriptiveDataWithWidth(inpath, Start, End, nameFiles, False,
3000)
AT.printResult(ori2, title2, nameOutput2)
title3 = ["Dyad", "Cov", "StartFrame"]
nameOutput3 = "Output/DiscriptiveData_60secs.csv"
title3 = getTitle(title3, GazeType, SpeakType, Person, Character)
ori3 = AT.getDiscriptiveDataWithWidth(inpath, Start, End, nameFiles, False,
1800)
AT.printResult(ori3, title3, nameOutput3)
inpath = "Input/"
nameFiles = np.loadtxt("NameFile.txt", dtype='S')
title = [
"Dyad", "Cov", "SectionStartTime", "TalkID", "Start", "End",
"Duration", "TalkType"
]
TalkType = (1, 2, 3, 4, 5)
Person = "H"
PersonTile = "S_"
nameOutput1 = "Output/CombinedOneLayer/Talk/DiscriptiveData_5talks_H_5mins.csv"
title1 = getTitle(title, GazeType, SpeakType, PersonTile, Character)
ori1 = AMS.getDiscriptiveTalkWithWidth(inpath, Start, End, nameFiles,
False, 9000, TalkType, Person)
ATS.printResult(ori1, title1, nameOutput1)
nameOutput2 = "Output/CombinedOneLayer/Talk/DiscriptiveData_5talks_H_100sec.csv"
title2 = getTitle(title, GazeType, SpeakType, PersonTile, Character)
ori2 = AMS.getDiscriptiveTalkWithWidth(inpath, Start, End, nameFiles,
False, 3000, TalkType, Person)
ATS.printResult(ori2, title2, nameOutput2)
Person = "S"
PersonTile = "H_"
nameOutput3 = "Output/CombinedOneLayer/Talk/DiscriptiveData_S_5mins.csv"
title3 = getTitle(title, GazeType, SpeakType, PersonTile, Character)
ori3 = AMS.getDiscriptiveTalkWithWidth(inpath, Start, End, nameFiles,
False, 9000, TalkType, Person)
ATS.printResult(ori3, title3, nameOutput3)
End = 9000
SpeakType = ["NoSound_", "Sound_"]
GazeType = [
"Around_", "Monitor_", "Keyboard_", "Face_", "NoFace_", "CompOnly_",
"BodyOnly_"
]
Character = ["Mean", "Median", "PopularSD", "Frequency", "Max", "Min"]
inpath = "Input/"
nameFiles = np.loadtxt("NameFile.txt", dtype='S')
GoT = 0
nameOutput1 = "Output/CombinedTwoLayer/DiscriptiveData_Gaze_Sound_5mins.csv"
title1 = getTitle(GoT, GazeType, SpeakType, Character)
ori1 = AMS.getDiscriptiveTwoTalkWithWidth(inpath, Start, End, nameFiles,
False, 9000, GoT)
ATS.printResult(ori1, title1, nameOutput1)
nameOutput2 = "Output/CombinedTwoLayer/DiscriptiveData_Gaze_Sound_100secs.csv"
title2 = getTitle(GoT, GazeType, SpeakType, Character)
ori2 = AMS.getDiscriptiveTwoTalkWithWidth(inpath, Start, End, nameFiles,
False, 3000, GoT)
ATS.printResult(ori2, title2, nameOutput2)
GoT = 1
nameOutput3 = "Output/CombinedTwoLayer/DiscriptiveData_Sound_Gaze_5mins.csv"
title3 = getTitle(GoT, GazeType, SpeakType, Character)
ori3 = AMS.getDiscriptiveTwoTalkWithWidth(inpath, Start, End, nameFiles,
False, 9000, GoT)
ATS.printResult(ori3, title3, nameOutput3)
nameOutput4 = "Output/CombinedTwoLayer/DiscriptiveData_Sound_Gaze_100secs.csv"
