#!/bin/python

################################################################################
#
#	MarkovSamp - Joe Mariglio <www.joemariglio.com>
#
#===============================================================================
#
#	reads in a .wav file (mono only, atm)
#	analyzes samples and generates a transition table using a memory depth of
#	<depth> and generates a markov chain of length <length> * <depth> * <reps> 
#	samps
#	outputs a .wav file
#
################################################################################
import re, sys, string, os.path, getopt, random, math, wave, array
dic = {}
def parse(infile):
	bytes = infile.readframes(infile.getnframes())
	ints = array.array('h',bytes)
	output = []
	it = iter(ints)
	for i in it:
		output.append(i)
	return output
def iter_flatten(iterable):
	it = iter(iterable)
	for e in it:
		if isinstance(e, (list, tuple)):
			for f in iter_flatten(e):
			        yield f
		else:
			yield e
def flatten(signal):
	return [i for i in iter_flatten(signal)]
def analyze(array, depth):
	i = 0
	for item in array:
		print int(100*(float(i) / len(array)))
		context = []
		end = i + depth +1
		if item in dic.keys():		
			for j in range(i+1,end):
				context.append(array[j%len(array)])
			addContext(item, context)
		else:
			for j in range(i+1,end):
				context.append(array[j%len(array)])				
			dic[item] = [context]
		i = i + 1
def addContext(token, context):
	it = 1
	for item in context:
		dic[token].append(context[0:it])
		it = it + 1
#		print context[0:it]
def generate(depth, length, reps):
	start = random.choice(dic.keys())
	output = []
	for i in range(0,length):
#		print "start = " 
#		print start
		value = random.choice(dic[start])
#		print "value = " 
#		print value
#		print "dic[start] = "
#		print dic[start]
		start = value[len(value)-1]
#		print "new start = " 
#		print start
		for j in range(0, reps):
			output.append(value)
	print "flattening sample matrix..."
	output = flatten(output)
	return output
def main(argv):
	if len(sys.argv) == 6:
		inpath = sys.argv[1]
		infile = wave.open(inpath, "rb")
		outpath = sys.argv[5]
		depth = int(sys.argv[2])
		length = int(sys.argv[3])
		reps = int(sys.argv[4])
		lines = parse(infile)
		print "building transition tables for:"
		analyze(lines, depth)
		print "generating markov chain..."
		output = generate(depth, length, reps)
		print "writing output to file..."
		signal = ''
		for i in range(len(output)):
			signal += wave.struct.pack('h',output[i])
		outfile = wave.open(str(outpath), "wb")
		outfile.setnchannels(infile.getnchannels())
		outfile.setsampwidth(infile.getsampwidth())
		outfile.setframerate(infile.getframerate())
		outfile.setnframes(length*depth)
		outfile.writeframes(signal)
		infile.close()
		outfile.close()
		#print output
	else:
		print "usage: markovSamp.py <inFile> <depth> <length> <reps> <outFile>"
		print "where <depth> is maximum number of samples per unit,"
		print "<length> is the output length in units,"
		print "and <reps> is the number of repeats per unit." 
if __name__ == '__main__':
	import re, sys, string, os.path, getopt, random, math
	main(sys.argv[1:])