def get_synchrony(sequences):
	"""
	Computes the normalised synchrony between a two or more sequences. 
	Synchrony here refers to positions with identical elements, e.g. two identical sequences have a synchrony of 1, two completely different sequences have a synchrony of 0.
	The value is normalised by dividing by the number of positions compared.
	This computation is defined in Cornwell's 2015 book on social sequence analysis, page 230.
	
	Example
	--------
	>>> s1 = [1,1,2,2,3]
	>>> s2 = [1,2,2,3,3]
	>>> sequences = [s1,s2]
	>>> ps.get_synchrony(sequences)
	0.6
	
	"""
	
	shortest_sequence = min([len(s) for s in sequences])
	
	same_elements = []
	for position in range(shortest_sequence):
	
		elements_at_this_position = []
		for sequence in sequences:
			elements_at_this_position.append(sequence[position])
			
		same_elements.append(elements_at_this_position.count(elements_at_this_position[0]) == len(elements_at_this_position))
		
	return same_elements.count(True) / shortest_sequence