comparison Syncopation models/basic_functions.py @ 26:d9d22e6f396d

fixed SG!

 	else:
 		for odd in range(3, int(math.sqrt(number) + 1), 2):
 			if number % odd == 0:
 				isPrime = False
 	return isPrime
+
+# upsample a velocity sequence to certain length, e.g. [1,1] to [1,0,0,0,1,0,0,0]
+def upsample_velocity_sequence(velocitySequence, length):
+	upsampledVelocitySequence = [0]*length
+	if length%len(velocitySequence) != 0:
+		print 'Error: the velocity sequence can only be upsampled to the interger times of its length.'
+	else:
+		scalingFactor = length/len(velocitySequence)
+		for index in range(len(velocitySequence)):
+			upsampledVelocitySequence[index*scalingFactor] = velocitySequence[index]
+	return upsampledVelocitySequence
+
 
 # convert a velocity sequence to its minimum time-span representation
 def velocity_sequence_to_min_timespan(velocitySequence):
 	minTimeSpanVelocitySeq = [1]
 	for divisors in find_divisor(len(velocitySequence)):

 		note.duration = note.duration/delta_t
 
 	return noteSequence
 
 
-
 # get_note_indices returns all the indices of all the notes in this velocity_sequence
 def get_note_indices(velocitySequence):
 	noteIndices = []
 
 	for index in range(len(velocitySequence)):

 	For monorhythms, all prime factors of the length of minimum time-span representation of this sequence are
 	elements of its subdivision_seq, otherwise it is polyrhythm; 
 	e.g. prime_factors of polyrhythm 100100101010 in 4/4 is [2,3] but subdivision_seq = [1,2,2] for 4/4 
 	'''
 	rhythmCategory = 'mono'
-	for f in find_prime_factors(len(get_min_timeSpan(velocitySequence))):
+	for f in find_prime_factors(len(velocity_sequence_to_min_timespan(velocitySequence))):
 		if not (f in subdivisionSequence): 
 			rhythmCategory = 'poly'
 			break
 	return rhythmCategory