csong@0: '''
csong@0: Author: Chunyang Song
csong@0: Institution: Centre for Digital Music, Queen Mary University of London
csong@0: 
csong@0: ** Toussaint's Metric Complexity Model **
csong@0: 
csong@0: Algorithm:
csong@0: 
csong@0: Only applicable to monorhythms.
csong@0: 
csong@0: Define metrical hierarchy by given time signature;
csong@0: Calculate how many onsets and determine Maximum Metricality Max_Metric;
csong@0: Calculate the Metrical Simplicity - the weights of all onsets;
csong@0: Syncopation = Max_Metric - Metric_simplicity.
csong@0: Output the predicted syncopation score; -1 indicates non-applicable
csong@0: 
csong@0: '''
csong@0: 
csong@0: from MeterStructure import MeterStructure
csong@0: 
csong@0: def metricalModel(rhythm, time_sig, category, bar):
csong@0: 	ms = MeterStructure(time_sig)
csong@0: 	meter = ms.getLJWeights(bar)
csong@0: 	if len(meter) !=0:
csong@0: 		
csong@0: 		metricalSimplicity = 0  # sum of weights of onsets per bar
csong@0: 		maxMetrical = 0 	 # maximum metricity per bar
csong@0: 		onsetCount = 0		 # The number of onsets per bar
csong@0: 	
csong@0: 		if 'poly' in category:  # not applicable to polyrhythms
csong@0: 			return -1
csong@0: 	
csong@0: 		# Calculate metricalSimplicity
csong@0: 		else:
csong@0: 			l = len(rhythm)
csong@0: 			for i in range(l):
csong@0: 				if rhythm[i] == 1: # onset detected
csong@0: 					pos = int((float(i)/l) *len(meter)) # looking for the metrical position where this note locates
csong@0: 					metricalSimplicity = metricalSimplicity+meter[pos]
csong@0: 					onsetCount = onsetCount+1
csong@0: 		
csong@0: 			# Calculate max metricity
csong@0: 			meter.sort(reverse=True)
csong@0: 			for i in range(0,onsetCount):
csong@0: 				maxMetrical = maxMetrical+meter[i]
csong@0: 			
csong@0: 			#print 'test', onsetCount, maxMetrical, metricalSimplicity
csong@0: 			syncopation = (maxMetrical - metricalSimplicity)
csong@0: 	
csong@0: 			return syncopation	
csong@0: 	else:
csong@0: 		return -1
csong@0: 
csong@0: # Retrieve the stimuli
csong@0: f = file('stimuli.txt')
csong@0: #f = file('stimuli_34only.txt')
csong@0: 
csong@0: #Calculate syncopation for each rhythm pattern
csong@0: while True:
csong@0: 	line = f.readline().split(';')
csong@0: 	if len(line) == 1:
csong@0: 		 break
csong@0: 	else:
csong@0: 		sti_name = line[0]
csong@0: 		rhythmString = line[1].split()
csong@0: 		time_sig = line[2]
csong@0: 		category = line[3]
csong@0: 		bar = int(line[4])
csong@0: 		
csong@0: 		rhythm = map(int,rhythmString[0].split(','))
csong@0: 
csong@0: 		print sti_name, metricalModel(rhythm, time_sig, category, bar)