piccal/rms_analysis.py

import os,types,json
from scipy.io import wavfile
from scipy.signal import stft
import numpy as np


def calc_harm_bins( srate, binHz, midiPitch, harmN ):

    semi_tone     = 1.0/12
    quarter_tone  = 1.0/24
    eigth_tone    = 1.0/48
    band_width_st = 3.0/48  # 3/8 tone
    
    fundHz     = (13.75 * pow(2.0,(-9.0/12.0))) * pow(2.0,(midiPitch / 12))
    fund_l_binL   = [int(round(fundHz * pow(2.0,-band_width_st) * i/binHz)) for i in range(1,harmN+1)]
    fund_m_binL   = [int(round(fundHz *         i/binHz)) for i in range(1,harmN+1)]
    fund_u_binL   = [int(round(fundHz * pow(2.0, band_width_st) * i/binHz)) for i in range(1,harmN+1)]

    for i in range(len(fund_m_binL)):
        if fund_l_binL[i] >= fund_m_binL[i] and fund_l_binL[i] > 0:
            fund_l_binL[i] = fund_m_binL[i] - 1

        if fund_u_binL[i] <= fund_m_binL[i] and fund_u_binL[i] < len(fund_u_binL)-1:
            fund_u_binL[i] = fund_m_binL[i] + 1
    
    return fund_l_binL, fund_m_binL, fund_u_binL
    
def rms_to_db( xV, rms_srate, refWndMs ):
    dbWndN = int(round(refWndMs * rms_srate / 1000.0))
    dbRef = ref = np.mean(xV[0:dbWndN])
    rmsDbV = 20.0 * np.log10( xV / dbRef )

    return rmsDbV

def audio_rms( srate, xV, rmsWndMs, hopMs, refWndMs  ):

    wndSmpN = int(round( rmsWndMs * srate / 1000.0))
    hopSmpN = int(round( hopMs    * srate / 1000.0))

    xN   = xV.shape[0]
    yN   = int(((xN - wndSmpN) / hopSmpN) + 1)
    assert( yN > 0)
    yV   = np.zeros( (yN, ) )

    assert( wndSmpN > 1 )

    i = 0
    j = 0
    while i < xN and j < yN:

        if i == 0:
            yV[j] = np.sqrt(xV[0]*xV[0])
        elif i < wndSmpN:
            yV[j] = np.sqrt( np.mean( xV[0:i] * xV[0:i] ) )
        else:
            yV[j] = np.sqrt( np.mean( xV[i-wndSmpN:i] * xV[i-wndSmpN:i] ) )

        i += hopSmpN
        j += 1

    rms_srate = srate / hopSmpN
    return rms_to_db( yV, rms_srate, refWndMs ), rms_srate


def audio_stft_rms( srate, xV, rmsWndMs, hopMs, refWndMs, spectrumIdx ):
    
    wndSmpN = int(round( rmsWndMs * srate / 1000.0))
    hopSmpN = int(round( hopMs    * srate / 1000.0))
    binHz   = srate / wndSmpN
    
    f,t,xM = stft( xV, fs=srate, window="hann", nperseg=wndSmpN, noverlap=wndSmpN-hopSmpN, return_onesided=True )

    specHopIdx = int(round( spectrumIdx ))    
    specV = np.sqrt(np.abs(xM[:, specHopIdx ]))
    
    mV = np.zeros((xM.shape[1]))

    for i in range(xM.shape[1]):
        mV[i] = np.max(np.sqrt(np.abs(xM[:,i])))


    rms_srate = srate / hopSmpN
    mV = rms_to_db( mV, rms_srate, refWndMs )
        
    return mV, rms_srate, specV, specHopIdx, binHz


def audio_harm_rms( srate, xV, rmsWndMs, hopMs, dbRefWndMs, midiPitch, harmCandN, harmN  ):

    wndSmpN   = int(round( rmsWndMs * srate / 1000.0))
    hopSmpN   = int(round( hopMs    * srate / 1000.0))

    binHz   = srate / wndSmpN
    
    f,t,xM = stft( xV, fs=srate, window="hann", nperseg=wndSmpN, noverlap=wndSmpN-hopSmpN, return_onesided=True )

    harmLBinL,harmMBinL,harmUBinL = calc_harm_bins( srate, binHz, midiPitch, harmCandN )
    
    rmsV = np.zeros((xM.shape[1],))


    for i in range(xM.shape[1]):
        mV = np.sqrt(np.abs(xM[:,i]))

        pV = np.zeros((len(harmLBinL,)))
        
        for j,(b0i,b1i) in enumerate(zip( harmLBinL, harmUBinL )):
            pV[j] = np.max(mV[b0i:b1i])

        rmsV[i] = np.mean( sorted(pV)[-harmN:] )
            
            
        
    rms_srate = srate / hopSmpN
    rmsV = rms_to_db( rmsV, rms_srate, dbRefWndMs )
    return rmsV, rms_srate, binHz
    
    
               
def locate_peak_indexes( xV, xV_srate, eventMsL ):

    pkIdxL = []
    for begMs, endMs in eventMsL:

        begSmpIdx = int(begMs * xV_srate / 1000.0)
        endSmpIdx = int(endMs * xV_srate / 1000.0)

        pkIdxL.append( begSmpIdx + np.argmax( xV[begSmpIdx:endSmpIdx] ) )

    return pkIdxL





def rms_analysis_main( inDir, midi_pitch, rmsWndMs=300, rmsHopMs=30, dbRefWndMs=500, harmCandN=5, harmN=3 ):

    seqFn     = os.path.join( inDir, "seq.json")
    audioFn   = os.path.join( inDir, "audio.wav")
    

    with open( seqFn, "rb") as f:
        r = json.load(f)
    
    
    srate, signalM  = wavfile.read(audioFn)
    sigV  = signalM / float(0x7fff)

    tdRmsDbV, rms0_srate = audio_rms( srate, sigV, rmsWndMs, rmsHopMs, dbRefWndMs )

    rmsDbV, rms_srate, binHz = audio_harm_rms( srate, sigV, rmsWndMs, rmsHopMs, dbRefWndMs, midi_pitch, harmCandN, harmN  )
    
    pkIdxL = locate_peak_indexes( rmsDbV, rms_srate, r['eventTimeL'] )

    r = types.SimpleNamespace(**{
        "audio_srate":srate,
        "tdRmsDbV": tdRmsDbV,
        "binHz": binHz,
        "rmsDbV":rmsDbV,
        "rms_srate":rms_srate,
        "pkIdxL":pkIdxL,            # pkIdxL[ len(pulsUsL) ] - indexes into rmsDbV[] of peaks
        #"min_pk_idx":min_pk_idx,
        #"max_pk_idx":max_pk_idx,
        "eventTimeL":r['eventTimeL'],
        'pkDbL': [ rmsDbV[ i ] for i in pkIdxL ],
        'pkUsL':r['pulseUsL'] })

    return r