spkit.sineModel_analysis

spkit.sineModel_analysis(x, fs, winlen, overlap=None, window='blackmanharris', nfft=None, thr=-10, maxn_sines=100, minDur=0.01, freq_devOffset=20, freq_devSlope=0.01)

Analysis of a signal x using the sinusoidal model

Analysis of a signal x using the sinusoidal model

• Decomposing a signal x into sine waves tracks over the time

Parameters:

xinput signal - 1d-array of shape (n,)

fs: sampling frequency

winlenwindow length for analysis

overlap: overlap of windows

: if None overlap = winlen//4

windowwindow type (default = ‘blackmanharris’) e.g. hann,ham

nfft: FFT-points used for analysis, should be >=winlen and should be of power of 2

: if None, than nfft = ceil[2**log2(winlen)]

thrthreshold in negative dB for selecting sine tracks

maxn_sines: maximum number of sines per frame

minDurminimum duration of sines in seconds

freq_devOffset: minimum frequency deviation

freq_devSlopeslope increase of minimum frequency deviation

Returns:

fXtfrequencies

mXtmagnitudes

pXt: phases of sinusoidal tracks

See also

dft_analysis

Discreet Fourier Transform - DFT

dft_synthesis

Inverse Discreet Fourier Transform - iDFT

stft_analysis

Short-Time Fourier Transform - STFT

stft_synthesis

Inverse Short-Time Fourier Transform - iSTFT

frft

Fractional Frourier Transform - FRFT

ifrft

Inverse Fractional Frourier Transform - iFRFT

sineModel_analysis

Sinasodal Model Decomposition

sineModel_synthesis

Sinasodal Model Synthesis

Notes

#TODO

Examples

    import requests
    from scipy.io import wavfile
    import numpy as np
    import matplotlib.pyplot as plt
    import spkit as sp
    path = 'https://github.com/MLEndDatasets/samples/raw/main/HWD_HP_hum_1.wav?raw=True'
    req = requests.get(path)
    with open('downloaded_file.wav', 'wb') as f:
            f.write(req.content)
    fs, x = wavfile.read('downloaded_file.wav')
    t = np.arange(x.shape[0])/fs
    N=10
    fXst, mXst, pXst = sp.sineModel_analysis(x,fs,winlen=3001,overlap=750,
                            window='blackmanharris', nfft=None, thr=-10,
                            maxn_sines=N,minDur=0.01, freq_devOffset=10,freq_devSlope=0.1)
    xr = sp.sineModel_synthesis(fXst, mXst, pXst,fs,overlap=750,crop_end=False)
    mXt, pXt = sp.stft_analysis(x,winlen=3001,overlap=750,plot=False)
    fXt1 = (fXst.copy())*(mXst>0)
    fXt1[fXt1==0]=np.nan
    tx = t[-1]*np.arange(fXt1.shape[0])/fXt1.shape[0]
    fig, (ax1, ax2,ax3) = plt.subplots(3, 1, gridspec_kw={'height_ratios': [1,2,1]},figsize=(10,6))
    ax1.plot(t,x)
    ax1.set_xlim([t[0],t[-1]])
    ax1.set_ylabel('X: input')
    ax1.grid()
    ax1.set_xticklabels('')
    ax2.imshow(mXt.T,aspect='auto',origin='lower',cmap='jet',extent=[t[0],t[-1],0,fs/2],interpolation='bilinear')
    ax2.plot(tx,fXt1,color='k',lw=1,label='sin-tracks')
    ax2.set_ylabel('STFT(x)
Frequency (Hz)')
    ax2.set_xticklabels('')
    ax2.set_ylim([0,10000])
    ax2.legend([f'sine-tracks (N={N})'])
    ax3.plot(t,xr[:len(t)])
    ax3.set_xlim([t[0],t[-1]])
    ax3.set_ylabel('XR: recon')
    ax3.grid()
    ax3.set_xlabel('Time (s)')
    fig.suptitle('Sinusoidal Model: Analysis and Synthesis')
    plt.tight_layout()
    plt.show()

Examples using spkit.sineModel_analysis

Analysis and Synthesis Models

Analysis and Synthesis Models

Sinusoidal Model : Synthesis : Audio

Sinusoidal Model : Synthesis : Audio

Sinusoidal Model: Analysis and Synthesis

Sinusoidal Model: Analysis and Synthesis