# function to call the main analysis/synthesis functions in software/models/sineModel.py

import numpy as np
import matplotlib.pyplot as plt
from scipy.signal import get_window
import os, sys
sys.path.append(os.path.join(os.path.dirname(os.path.realpath(__file__)), '../models/'))
import utilFunctions as UF
import sineModel as SM

def main(inputFile='../../sounds/bendir.wav', window='hamming', M=2001, N=2048, t=-80, minSineDur=0.02, 
					maxnSines=150, freqDevOffset=10, freqDevSlope=0.001):
	"""
	Perform analysis/synthesis using the sinusoidal model
	inputFile: input sound file (monophonic with sampling rate of 44100)
	window: analysis window type (rectangular, hanning, hamming, blackman, blackmanharris)	
	M: analysis window size; N: fft size (power of two, bigger or equal than M)
	t: magnitude threshold of spectral peaks; minSineDur: minimum duration of sinusoidal tracks
	maxnSines: maximum number of parallel sinusoids
	freqDevOffset: frequency deviation allowed in the sinusoids from frame to frame at frequency 0   
	freqDevSlope: slope of the frequency deviation, higher frequencies have bigger deviation
	"""
		
	# size of fft used in synthesis
	Ns = 512

	# hop size (has to be 1/4 of Ns)
	H = 128

	# read input sound
	fs, x = UF.wavread(inputFile)

	# compute analysis window
	w = get_window(window, M)

	# analyze the sound with the sinusoidal model
	tfreq, tmag, tphase = SM.sineModelAnal(x, fs, w, N, H, t, maxnSines, minSineDur, freqDevOffset, freqDevSlope)

	# synthesize the output sound from the sinusoidal representation
	y = SM.sineModelSynth(tfreq, tmag, tphase, Ns, H, fs)

	# output sound file name
	outputFile = 'output_sounds/' + os.path.basename(inputFile)[:-4] + '_sineModel.wav'

	# write the synthesized sound obtained from the sinusoidal synthesis
	UF.wavwrite(y, fs, outputFile)

	# create figure to show plots
	plt.figure(figsize=(12, 9))

	# frequency range to plot
	maxplotfreq = 5000.0

	# plot the input sound
	plt.subplot(3,1,1)
	plt.plot(np.arange(x.size)/float(fs), x)
	plt.axis([0, x.size/float(fs), min(x), max(x)])
	plt.ylabel('amplitude')
	plt.xlabel('time (sec)')
	plt.title('input sound: x')
				
	# plot the sinusoidal frequencies
	plt.subplot(3,1,2)
	if (tfreq.shape[1] > 0):
		numFrames = tfreq.shape[0]
		frmTime = H*np.arange(numFrames)/float(fs)
		tfreq[tfreq<=0] = np.nan
		plt.plot(frmTime, tfreq)
		plt.axis([0, x.size/float(fs), 0, maxplotfreq])
		plt.title('frequencies of sinusoidal tracks')

	# plot the output sound
	plt.subplot(3,1,3)
	plt.plot(np.arange(y.size)/float(fs), y)
	plt.axis([0, y.size/float(fs), min(y), max(y)])
	plt.ylabel('amplitude')
	plt.xlabel('time (sec)')
	plt.title('output sound: y')

	plt.tight_layout()
	plt.show()


if __name__ == "__main__":
	main()

