annotate 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)