annotate Syncopation models/LHL.py @ 33:f5abd2e8cafe

update models

'''
Author: Chunyang Song
Institution: Centre for Digital Music, Queen Mary University of London
'''

from basic_functions import concatenate, repeat, subdivide, ceiling, get_rhythm_category
from parameter_setter import are_parameters_valid

terminalNodes = []		# Global variable, storing all the terminal nodes from recursive tree structure in time order

# Each terminnal node contains two properties: its node type (note or rest) and its metrical weight.
class Node:
	def __init__(self,nodeType,metricalWeight):
		self.nodeType = nodeType
		self.metricalWeight = metricalWeight

# This function will recurse the tree for a binary sequence and return a sequence containing the terminal nodes in time order.
def recursive_tree(binarySequence, subdivisionSequence, weightSequence, metricalWeight, level):
	# If matching to a Note type, add to terminal nodes
	if binarySequence == concatenate([1],repeat([0],len(binarySequence)-1)):	
		terminalNodes.append(Node('N',metricalWeight))

	# If matching to a Rest type, add to terminal nodes
	elif binarySequence == repeat([0],len(binarySequence)):					
		terminalNodes.append(Node('R',metricalWeight))

	# Keep subdividing by the subdivisor of the next level
	else:													
		subBinarySequences = subdivide(binarySequence, subdivisionSequence[level+1])	
		subWeightSequences = concatenate([metricalWeight],repeat([weightSequence[level+1]],subdivisionSequence[level+1]-1))
		for a in range(len(subBinarySequences)):
			recursive_tree(subBinarySequences[a], subdivisionSequence, weightSequence, subWeightSequences[a], level+1)


def get_syncopation(bar, parameters = None):
	del terminalNodes[:]
	syncopation = None

	binarySequence = bar.get_binary_sequence()
	subdivisionSequence = bar.get_subdivision_sequence()

	# LHL can only measure monorhythms
	if get_rhythm_category(binarySequence, subdivisionSequence) == 'poly':
		print 'Warning: LHL model detects polyrhythms so returning None.'
	else:
		# set defaults
		Lmax = 5
		weightSequence = range(0,-Lmax-1,-1)
		# if parameters are specified by users, check their validities and update parameters if valid		
		if parameters!= None:
			if 'Lmax' in parameters:
				Lmax = parameters['Lmax']				
			if 'W' in parameters:
				weightSequence = parameters['W']

		if not are_parameters_valid(Lmax, weightSequence, subdivisionSequence):
			print 'Error: the given parameters are not valid.'
		else:
			# If there is rhythm in previous bar, process its tree structure
			if bar.get_previous_bar() != None:
				prebarBinarySequence = bar.get_previous_bar().get_binary_sequence()
				recursive_tree(ceiling(prebarBinarySequence), subdivisionSequence, weightSequence, weightSequence[0],0)
				
				# Only keep the last note-type node
				while terminalNodes[-1].nodeType != 'N':
					del terminalNodes[-1]
				del terminalNodes[0:-1]

			# For the rhythm in the current bar, process its tree structure and store the terminal nodes 
			recursive_tree(ceiling(binarySequence), subdivisionSequence, weightSequence, weightSequence[0],0)
			
			# for t in terminalNodes:
			# 	print '<', t.nodeType, t.metricalWeight, '>'

			# Search for the NR pairs that contribute to syncopation,then add the weight-difference to the NRpairSyncopation list
			NRpairSyncopation = []
			for i in range(len(terminalNodes)-1,0,-1):
				if terminalNodes[i].nodeType == 'R':
					for j in range(i-1, -1, -1):
						if (terminalNodes[j].nodeType == 'N') & (terminalNodes[i].metricalWeight >= terminalNodes[j].metricalWeight):
							NRpairSyncopation.append(terminalNodes[i].metricalWeight - terminalNodes[j].metricalWeight)
							break
			#print NRpairSyncopation

			# If there are syncopation, sum all the local syncopation values stored in NRpairSyncopation list	
			if len(NRpairSyncopation) != 0:
				syncopation = sum(NRpairSyncopation)
			# If no syncopation, the value is -1; 	
			elif len(terminalNodes) != 0:
				syncopation = -1

	return syncopation