csong@0: '''
csong@0: Author: Chunyang Song
csong@0: Institution: Centre for Digital Music, Queen Mary University of London
csong@0: 
csong@0: '''
csong@0: 
csong@2: from BasicFuncs import get_H, get_min_timeSpan
csong@0: 
csong@1: def get_syncopation(seq, subdivision_seq, weight_seq, L_max, rhythm_category):
csong@1: 	syncopation = None
csong@1: 	if rhythm_category == 'poly':
csong@1: 		print 'Error: SG model cannot deal with polyrhythms.'
csong@0: 	else:
csong@1: 		
csong@1: 		seq = get_min_timeSpan(seq)	# converting to the minimum time-span format
csong@1: 		
csong@1: 		# checking whether the given L_max is enough to analyse the given sequence, if not, request a bigger L_max
csong@1: 		new_L_max = True
csong@1: 		matching_level = L_max
csong@1: 		while matching_level >= 0:
csong@1: 			if len(get_H(weight_seq,subdivision_seq, matching_level)) == len(seq):
csong@1: 				new_L_max = False
csong@1: 				break
csong@1: 			else:
csong@1: 				matching_level = matching_level - 1
csong@0: 
csong@1: 		if new_L_max == True:
csong@1: 			print 'Error: needs a bigger L_max (i.e. the lowest metrical level) to match the given rhythm sequence.'
csong@0: 
csong@1: 		else:
csong@1: 			syncopation = 0
csong@1: 			# generate the metrical weights of the lowest level
csong@1: 			H = get_H(weight_seq,subdivision_seq, matching_level)
csong@0: 
csong@1: 			# The aveDif_neighbours function calculates the (weighted) average of the difference between the note at a certain index and its neighbours in a certain metrical level
csong@1: 			def aveDif_neighbours(index, level):
csong@0: 				averages = []
csong@1: 				parameter_garma = 0.8
csong@0: 				
csong@1: 				# The findPre function is to calculate the index of the previous neighbour at a certain metrical level.
csong@1: 				def findPre(index, level):
csong@1: 					pre_index = (index - 1)%len(H)
csong@1: 					while(H[pre_index] > level):
csong@1: 						pre_index = (pre_index - 1)%len(H)
csong@0: 					return pre_index
csong@0: 
csong@1: 				# The findPost function is to calculate the index of the next neighbour at a certain metrical level.
csong@1: 				def findPost(index, level):
csong@1: 					post_index = (index + 1)%len(H)
csong@1: 					while(H[post_index] > level):
csong@1: 						post_index = (post_index + 1)%len(H)
csong@0: 					return post_index
csong@0: 				
csong@1: 				# The dif function is to calculate a difference level factor between two notes (at note position index1 and index 2) in velocity sequence
csong@0: 				def dif(index1,index2):
csong@0: 					parameter_beta = 0.5
csong@1: 					dif_v = seq[index1]-seq[index2]
csong@1: 					dif_h = abs(H[index1]-H[index2])
csong@0: 					dif = dif_v*(parameter_beta*dif_h/4+1-parameter_beta)
csong@0: 					return dif
csong@0: 
csong@1: 				# From the highest to the lowest metrical levels where the current note resides, calculate the difference between the note and its neighbours at that level
csong@1: 				for l in range(level, max(H)+1):
csong@1: 					ave = ( parameter_garma*dif(index,findPre(index,l))+dif(index,findPost(index,l)) )/(1+parameter_garma)
csong@0: 					averages.append(ave)
csong@0: 				return averages
csong@0: 
csong@1: 			# Calculate the syncopation value for each note
csong@1: 			for index in range(len(seq)):
csong@1: 				if seq[index] != 0: # Onset detected
csong@1: 					h = H[index]
csong@1: 					potential = 1 - pow(0.5,h) # Syncopation potential according to its metrical level, which is equal to the metrical weight
csong@1: 					level = h 		# Metrical weight happens to be equal to its metrical level
csong@1: 					syncopation += min(aveDif_neighbours(index, h))*potential
csong@1: 			
csong@1: 	return syncopation