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2 #!/usr/bin/python
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3 #
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4 # processCSV.py: analyse the results and return results breakdown for a given question type
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5 #
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6 # Usage: processCSV.py questionType intonationPattern
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7 # If no intonation pattern or question type is given, then all results are presented.
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8 #
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9 # Example: processCSV.py
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10 # Example: processCSV.py 'Wh'
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11 # Example: processCSV.py 'Wh' 'F'
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12 # Possible Questions: 'Echo', 'Wh', 'YN'
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13 # Possible Intonations: 'RF', 'FR', 'F', 'R', 'H'
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14
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15
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16
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17 import csv
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18 import sys
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19 import matplotlib.pyplot as plt
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20 import numpy as np
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21
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22
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23 if __name__=="__main__":
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24 #Load Command Line Parameters
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25 intPattern = None;
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26 qType = None;
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27
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28 if len(sys.argv) > 2:
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29 intPattern = [sys.argv[2]]
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30 else:
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31 intPattern = ['RF', 'FR', 'F', 'R', 'H']
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32 if len(sys.argv) > 1:
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33 qType = [sys.argv[1]]
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34 else:
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35 qType = ['Echo', 'Wh', 'YN']
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36
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37 #print(intPattern)
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38 #print(qType)
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39
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40
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41 reader = csv.DictReader(open('DataSetSummary.csv'))
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42
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43 result = {}
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44 for row in reader:
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45 for column, value in row.iteritems():
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46 result.setdefault(column, []).append(value)
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47 #print result['QType']
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48
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49 for q in qType:
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50 qList = [j for j, x in enumerate(result['QType']) if x == q]
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51 # print "%s count = %d" % (q, len(qList))
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52 for i in intPattern:
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53 iList = [j for j, x in enumerate(result['Intonation']) if x == i]
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54 count = 0
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55 tracks = []
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56 if (iList) != None:
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57 for il in iList:
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58 if il in qList:
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59 count +=1
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60 tracks.append(il)
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61 # print (i + ' vs. '+q+'=%d', count)
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62 # if count > 0:
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63 print "%s vs. %s = %d" % (q, i, count)
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64 print tracks
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65 # for t in tracks:
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66 # trackName = "T%d/01.csv" % (t)
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67 # trackReader = csv.reader(open(trackName))
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68 # xList = []
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69 # yList = []
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70 # for r in trackReader:
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71 ## print "In trackReader"
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72 ## print(r)
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73 ## print(r[1])
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74 # xList.append(r[0])
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75 ## xList = [float(x) for x in xList]
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76 # yList.append(r[1])
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77 ## yList = [float(y) for y in yList]
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78 # # Apply some smoothing and scaling
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79 # # Vertical
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80 # print yList
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81 # print min(yList)
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82 # yList = np.subtract(yList, min(yList))
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83 # print yList
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84 # yList = np.divide(yList, max(yList))
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85 # print yList
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86 # # Horizontal
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87 # xList = np.subtract(xList, min(xList))
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88 # xList = np.divide(xList, max(xList))
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89 #
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90 #
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91 # plt.plot(xList,yList)
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92 # plt.show()
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93
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94 #result = {}
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95 #for row in reader:
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96 # print(row)
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97 # key = row[1]
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98 ## if key in result:
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99 ## # implement your duplicate row handling here
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100 ## pass
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101 # result[key] = row[1:]
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102 #print result
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