comparison Syncopation models/WNBD.py @ 0:76ce27beba95

Have uploaded the syncopation dataset and audio wavefies.

+'''
+Author: Chunyang Song
+Institution: Centre for Digital Music, Queen Mary University of London
+
+** Weighted Note-to-Beat Distance Model (WNBD) **
+
+Algorithm:
+
+Calculate the distance (d) of onset to the nearest strong beat;
+Calculate the WNBD measure (w) of each onset;
+Syncopation is the sum of WNBD measures divided by the number of onsets.
+
+'''
+
+from MeterStructure import MeterStructure
+
+def WNBD(rhythm, time_sig, category, bar):
+
+	ms = MeterStructure(time_sig)
+	beat = ms.getBeats(bar) + [len(rhythm)] # the "beat" array include all "strong-beat" positions across all bars, and the downbeat position of the following bar 
+	if len(beat)!=0:
+		unit = beat[1]-beat[0]  # how many digits to represent the length of one beat
+
+		onsetPos = []		# The onset positions
+		d = []				# The distances of each onset to its nearest strong beat
+		beatToLeft = []		# The beat indexes of the beats that are to the left of or coincide with each onset
+		wnbdMeasures = []   # the un-normalized measures of wnbd
+		
+		# Calculate the distance of each onset to the nearest strong beat
+		l = len(rhythm) 
+		for i in range(l):
+			if rhythm[i] == 1:    # onset detected
+				onsetPos.append(i)
+				
+				# find its distance to the nearest strong beat
+				for j in range(len(beat)-1):
+					if beat[j]<= i < beat[j+1]:
+						d1 = abs(i-beat[j])
+						d2 = abs(i-beat[j+1])
+						d.append( min(d1,d2)/float(unit) ) # Normalize the distance to beat-level
+						beatToLeft.append(j)
+					else:
+						continue
+		
+		#Calculate the WNBD measure of each onset
+		n = len(onsetPos)
+		for i in range(n):
+			if d[i] ==0:	# If on-beat, measure is 0
+				wnbdMeasures.append(0)
+			else:
+				if i == n-1: # The last note, then 
+					if beatToLeft[i] == beat[-3]/unit:	# if the last note has more than 1- but less than 2-beat distance to the next bar
+						wnbdMeasures.append(2.0/d[i])	# measure is 2/d, else 1/d
+					else:
+						wnbdMeasures.append(1.0/d[i])	
+
+				else:        # if its not the last note
+					if beatToLeft[i+1] == beatToLeft[i] or (beatToLeft[i+1]-beatToLeft[i]==1 and d[i+1]==0): # if this note is no more than 1-beat distance away from the next note
+						wnbdMeasures.append(1.0/d[i])
+					elif beatToLeft[i+1] - beatToLeft[i] == 1 or (beatToLeft[i+1]-beatToLeft[i]==2 and d[i+1]==0):  # if this note is no more than 2-beat distance away from the next
+						wnbdMeasures.append(2.0/d[i])
+					else:								# if the note is more than 2-beat distance away from the next note
+						wnbdMeasures.append(1.0/d[i])
+
+		syncopation = sum(wnbdMeasures)/float(n)
+		return syncopation
+	
+	else:
+		return -1
+
+
+# Retrieve the stimuli
+f = file('stimuli.txt')
+#f = file('stimuli_34only.txt')
+
+#Calculate syncopation for each rhythm pattern
+while True:
+	line = f.readline().split(';')
+	if len(line) == 1:
+		 break
+	else:
+		sti_name = line[0]
+		rhythmString = line[1].split()
+		time_sig = line[2]
+		category = line[3]
+		bar = int(line[4])
+		
+		rhythm = map(int,rhythmString[0].split(','))
+
+		print sti_name, WNBD(rhythm, time_sig, category, bar)