A multi-resolution sinusoidal model

sineModelMulti.py

import sys
import math

import numpy as np
eps = np.finfo(float).eps  # epsilon, minimum float value in python

from scipy.fftpack import fft, ifft
from scipy.signal import triang, get_window, blackmanharris

sys.path.append("../../software/models/")
import utilFunctions as UF
import dftModel as DFT
import sineModel as SM


def sineModelMultiRes(x, fs, ws, Ns, Bs, t):
    Ms = np.array([w.size for w in ws])
    M_max = np.max(Ms)                                         # get largest window size
    hM1_max = int(math.floor((M_max+1)/2))                     # half analysis window size by rounding
    Nsy = 512                                                  # FFT size for synthesis (even)
    H = Nsy/4                                                  # Hop size used for analysis and synthesis
    hNsy = Nsy/2                                               # half of synthesis FFT size
    pin = max(hNsy, hM1_max)                                   # init sound pointer in middle of anal window
    pend = x.size - max(hNsy, hM1_max)                         # last sample to start a frame
    yw = np.zeros(Nsy)                                         # initialize output sound frame
    y = np.zeros(x.size)                                       # initialize output array
    w = w / sum(w)                                             # normalize analysis window
    sw = np.zeros(Nsy)                                         # initialize synthesis window
    ow = triang(2*H)                                           # triangular window
    sw[hNsy-H:hNsy+H] = ow                                     # add triangular window
    bh = blackmanharris(Nsy)                                   # blackmanharris window
    bh = bh / sum(bh)                                          # normalized blackmanharris window
    sw[hNsy-H:hNsy+H] = sw[hNsy-H:hNsy+H] / bh[hNsy-H:hNsy+H]  # normalized synthesis window

    while pin < pend:
        ipfreqs  = np.array([])
        ipmags   = np.array([])
        ipphases = np.array([])
        # - analysis -----------------
        for w, N, B in zip(ws, Ns, Bs):                           # for each band
            M = w.size
            hM1 = int(math.floor((M + 1) / 2))
            hM2 = int(math.floor(M / 2))

            x1 = x[pin-hM1:pin+hM2]                               # select frame
            mX, pX = DFT.dftAnal(x1, w, N)                        # compute dft
            ploc = UF.peakDetection(mX, t)                        # detect locations of peaks
            iploc, ipmag, ipphase = UF.peakInterp(mX, pX, ploc)   # refine peak values by interpolation
            ipfreq = fs*iploc/float(N)                            # convert peak locations to Hertz

            filt = np.where((ipfreq >= B[0]) & (ipfreq < B[1]))   # bandfilter peaks
            ipfreq  = np.take(ipfreq, filt)[0]
            ipmag   = np.take(ipmag, filt)[0]
            ipphase = np.take(ipphase, filt)[0]
            ipfreqs  = np.append(ipfreqs, ipfreq)                 # merge bands
            ipmags   = np.append(ipmags, ipmag)
            ipphases = np.append(ipphases, ipphase)

        # - reconstruction -----------
        frame = int(pin / float(H))
        Y = UF.genSpecSines(ipfreqs, ipmags, ipphases, Nsy, fs)   # generate sines in the spectrum
        fftbuffer = np.real(ifft(Y))                              # compute inverse FFT
        yw[:hNsy-1] = fftbuffer[hNsy+1:]                          # undo zero-phase window
        yw[hNsy-1:] = fftbuffer[:hNsy+1]
        y[pin-hNsy:pin+hNsy] += sw*yw                             # overlap-add and apply a synthesis window

        pin += H                                                  # next frame

    return y

I have an Error That says SineModel no such Module Found could you please Help me out

This was part of my homework for the "Audio Signal Processing for Music Application" course run by Prof Xavier Serra and Prof Julius Smith.

The missing modules come from the sms-tools repository which is used in the course.

You can find it here on Prof Serra's GitHub:

https://github.com/MTG/sms-tools

The course is very good and I highly recommend it:

https://www.coursera.org/learn/audio-signal-processing