comparison processCSV.py @ 0:26494c0d9ffd

Repo Creation

+
+#!/usr/bin/python
+#
+# processCSV.py: analyse the results and return results breakdown for a given question type
+#
+# Usage: processCSV.py questionType intonationPattern
+# If no intonation pattern or question type is given, then all results are presented.
+#
+# Example: processCSV.py
+# Example: processCSV.py 'Wh'
+# Example: processCSV.py 'Wh' 'F'
+# Possible Questions: 'Echo', 'Wh', 'YN'
+# Possible Intonations: 'RF', 'FR', 'F', 'R', 'H'
+
+
+
+import csv
+import sys
+import matplotlib.pyplot as plt
+import numpy as np
+
+
+if __name__=="__main__":
+    #Load Command Line Parameters
+    intPattern = None;
+    qType = None;
+    
+    if len(sys.argv) > 2:
+        intPattern = [sys.argv[2]]
+    else:
+        intPattern = ['RF', 'FR', 'F', 'R', 'H']
+    if len(sys.argv) > 1:
+        qType = [sys.argv[1]]
+    else:
+        qType = ['Echo', 'Wh', 'YN']
+
+#print(intPattern)
+#print(qType)
+
+
+reader = csv.DictReader(open('DataSetSummary.csv'))
+
+result = {}
+for row in reader:
+    for column, value in row.iteritems():
+        result.setdefault(column, []).append(value)
+#print result['QType']
+
+for q in qType:
+    qList = [j for j, x in enumerate(result['QType']) if x == q]
+#    print "%s count = %d" % (q, len(qList))
+    for i in intPattern:
+        iList = [j for j, x in enumerate(result['Intonation']) if x == i]
+        count = 0
+        tracks = []
+        if (iList) != None:
+            for il in iList:
+                if il in qList:
+                    count +=1
+                    tracks.append(il)
+#        print (i + ' vs. '+q+'=%d', count)
+#        if count > 0:
+            print "%s vs. %s = %d" % (q, i, count)
+            print tracks
+#            for t in tracks:
+#                trackName = "T%d/01.csv" % (t)
+#                trackReader = csv.reader(open(trackName))
+#                xList = []
+#                yList = []
+#                for r in trackReader:
+##                    print "In trackReader"
+##                    print(r)
+##                    print(r[1])
+#                    xList.append(r[0])
+##                    xList = [float(x) for x in xList]
+#                    yList.append(r[1])
+##                    yList = [float(y) for y in yList]
+#            #   Apply some smoothing and scaling
+#            #   Vertical
+#                print yList
+#                print min(yList)
+#                yList = np.subtract(yList, min(yList))
+#                print yList
+#                yList = np.divide(yList, max(yList))
+#                print yList
+#            #   Horizontal
+#                xList = np.subtract(xList, min(xList))
+#                xList = np.divide(xList, max(xList))
+#                
+#                
+#                plt.plot(xList,yList)
+#            plt.show()
+
+#result = {}
+#for row in reader:
+#    print(row)
+#    key = row[1]
+##    if key in result:
+##        # implement your duplicate row handling here
+##        pass
+#    result[key] = row[1:]
+#print result