Added min/max volume note and skip note detection.
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kpl
parent
c3db8c8ab6
commit
ac9061a72d
127
plot_seq.py
127
plot_seq.py
@ -11,6 +11,49 @@ def is_nanV( xV ):
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return True
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return False
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def find_min_max_peak_index( rmsV, pkIdxL, minDb, maxDbOffs=0.5 ):
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# select only the peaks from rmsV[] to work with
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yV = rmsV[ pkIdxL ]
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# get the max volume note
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max_i = np.argmax( yV )
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maxDb = yV[ max_i ]
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min_i = max_i
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# starting from the max volume peak go backwards
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for i in range( max_i, 0, -1 ):
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# if this peak is within maxDbOffs of the loudest then choose this one instead
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if maxDb - yV[i] < maxDbOffs:
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max_i = i
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# if this peak is less than minDb then the previous note is the min note
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if yV[i] < minDb:
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break
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min_i = i
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assert( min_i < max_i )
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return min_i, max_i
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def find_skip_peaks( rmsV, pkIdxL, min_pk_idx, max_pk_idx ):
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skipPkIdxL = []
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yV = rmsV[pkIdxL]
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refPkDb = yV[min_pk_idx]
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for i in range( min_pk_idx+1, max_pk_idx+1 ):
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if yV[i] > refPkDb:
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refPkDb = yV[i]
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else:
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skipPkIdxL.append(i)
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return skipPkIdxL
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def calc_harm_bins( srate, binHz, midiPitch, harmN ):
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@ -33,9 +76,14 @@ def calc_harm_bins( srate, binHz, midiPitch, harmN ):
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return fund_l_binL, fund_m_binL, fund_u_binL
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def rms_to_db( xV, rms_srate, refWndMs ):
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dbWndN = int(round(refWndMs * rms_srate / 1000.0))
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dbRef = ref = np.mean(xV[0:dbWndN])
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rmsDbV = 20.0 * np.log10( xV / dbRef )
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return rmsDbV
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def audio_rms( srate, xV, rmsWndMs, hopMs ):
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def audio_rms( srate, xV, rmsWndMs, hopMs, refWndMs ):
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wndSmpN = int(round( rmsWndMs * srate / 1000.0))
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hopSmpN = int(round( hopMs * srate / 1000.0))
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@ -60,19 +108,12 @@ def audio_rms( srate, xV, rmsWndMs, hopMs ):
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i += hopSmpN
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j += 1
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return yV, srate / hopSmpN
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def audio_db_rms( srate, xV, rmsWndMs, hopMs, dbRefWndMs ):
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rmsV, rms_srate = audio_rms( srate, xV, rmsWndMs, hopMs )
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dbWndN = int(round(dbRefWndMs * rms_srate / 1000.0))
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dbRef = ref = np.mean(rmsV[0:dbWndN])
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return 20.0 * np.log10( rmsV / dbRef ), rms_srate
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rms_srate = srate / hopSmpN
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return rms_to_db( yV, rms_srate, refWndMs ), rms_srate
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def audio_stft_rms( srate, xV, rmsWndMs, hopMs, spectrumIdx ):
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def audio_stft_rms( srate, xV, rmsWndMs, hopMs, refWndMs, spectrumIdx ):
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wndSmpN = int(round( rmsWndMs * srate / 1000.0))
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hopSmpN = int(round( hopMs * srate / 1000.0))
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@ -88,18 +129,14 @@ def audio_stft_rms( srate, xV, rmsWndMs, hopMs, spectrumIdx ):
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for i in range(xM.shape[1]):
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mV[i] = np.max(np.sqrt(np.abs(xM[:,i])))
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return mV, srate / hopSmpN, specV, specHopIdx, binHz
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def audio_stft_db_rms( srate, xV, rmsWndMs, hopMs, dbRefWndMs, spectrumIdx ):
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rmsV, rms_srate, specV, specHopIdx, binHz = audio_stft_rms( srate, xV, rmsWndMs, hopMs, spectrumIdx )
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dbWndN = int(round(dbRefWndMs * rms_srate / 1000.0))
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dbRef = ref = np.mean(rmsV[0:dbWndN])
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rmsDbV = 20.0 * np.log10( rmsV / dbRef )
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rms_srate = srate / hopSmpN
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mV = rms_to_db( mV, rms_srate, refWndMs )
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return mV, rms_srate, specV, specHopIdx, binHz
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return rmsDbV, rms_srate, specV, specHopIdx, binHz
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def audio_harm_rms( srate, xV, rmsWndMs, hopMs, midiPitch, harmCandN, harmN ):
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def audio_harm_rms( srate, xV, rmsWndMs, hopMs, dbRefWndMs, midiPitch, harmCandN, harmN ):
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wndSmpN = int(round( rmsWndMs * srate / 1000.0))
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hopSmpN = int(round( hopMs * srate / 1000.0))
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@ -125,20 +162,9 @@ def audio_harm_rms( srate, xV, rmsWndMs, hopMs, midiPitch, harmCandN, harmN ):
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return rmsV, srate / hopSmpN, binHz
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def audio_harm_db_rms( srate, xV, rmsWndMs, hopMs, dbRefWndMs, midiPitch, harmCandN, harmN ):
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rmsV, rms_srate, binHz = audio_harm_rms( srate, xV, rmsWndMs, hopMs, midiPitch, harmCandN, harmN )
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dbWndN = int(round(dbRefWndMs * rms_srate / 1000.0))
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dbRef = ref = np.mean(rmsV[0:dbWndN])
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rmsDbV = 20.0 * np.log10( rmsV / dbRef )
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return rmsDbV, rms_srate, binHz
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rms_srate = srate / hopSmpN
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rmsV = rms_to_db( rmsV, rms_srate, dbRefWndMs )
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return rmsV, rms_srate, binHz
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@ -156,7 +182,8 @@ def locate_peak_indexes( xV, xV_srate, eventMsL ):
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def plot_spectrum( ax, srate, binHz, specV, midiPitch, harmN ):
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""" Plot a single spectrum, 'specV' and the harmonic peak location boundaries."""
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binN = specV.shape[0]
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harmLBinL,harmMBinL,harmUBinL = calc_harm_bins( srate, binHz, midiPitch, harmN )
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@ -178,7 +205,8 @@ def plot_spectrum( ax, srate, binHz, specV, midiPitch, harmN ):
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ax.set_ylabel(str(midiPitch))
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def plot_spectral_ranges( inDir, pitchL, rmsWndMs=300, rmsHopMs=30, harmN=5, dbRefWndMs=500 ):
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""" Plot the spectrum from one note (7th from last) in each attack pulse length sequence referred to by pitchL."""
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plotN = len(pitchL)
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fig,axL = plt.subplots(plotN,1)
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@ -197,7 +225,7 @@ def plot_spectral_ranges( inDir, pitchL, rmsWndMs=300, rmsHopMs=30, harmN=5, dbR
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sigV = signalM / float(0x7fff)
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# calc. the RMS envelope in the time domain
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rms0DbV, rms0_srate = audio_db_rms( srate, sigV, rmsWndMs, rmsHopMs, dbRefWndMs )
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rms0DbV, rms0_srate = audio_rms( srate, sigV, rmsWndMs, rmsHopMs, dbRefWndMs )
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# locate the sample index of the peak of each note attack
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pkIdx0L = locate_peak_indexes( rms0DbV, rms0_srate, r['eventTimeL'] )
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@ -211,7 +239,7 @@ def plot_spectral_ranges( inDir, pitchL, rmsWndMs=300, rmsHopMs=30, harmN=5, dbR
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# calc. the RMS envelope by taking the max spectral peak in each STFT window
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rmsDbV, rms_srate, specV, specHopIdx, binHz = audio_stft_db_rms( srate, sigV, rmsWndMs, rmsHopMs, dbRefWndMs, spectrumSmpIdx)
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rmsDbV, rms_srate, specV, specHopIdx, binHz = audio_stft_rms( srate, sigV, rmsWndMs, rmsHopMs, dbRefWndMs, spectrumSmpIdx)
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# specV[] is the spectrum of the note at spectrumSmpIdx
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@ -222,12 +250,12 @@ def plot_spectral_ranges( inDir, pitchL, rmsWndMs=300, rmsHopMs=30, harmN=5, dbR
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def do_td_plot( inDir ):
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rmsWndMs = 300
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rmsHopMs = 30
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dbRefWndMs = 500
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harmCandN = 5
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harmN = 3
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minAttkDb = 5.0
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seqFn = os.path.join( inDir, "seq.json")
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audioFn = os.path.join( inDir, "audio.wav")
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@ -241,12 +269,17 @@ def do_td_plot( inDir ):
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srate, signalM = wavfile.read(audioFn)
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sigV = signalM / float(0x7fff)
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rms0DbV, rms0_srate = audio_db_rms( srate, sigV, rmsWndMs, rmsHopMs, dbRefWndMs )
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rms0DbV, rms0_srate = audio_rms( srate, sigV, rmsWndMs, rmsHopMs, dbRefWndMs )
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rmsDbV, rms_srate, binHz = audio_harm_db_rms( srate, sigV, rmsWndMs, rmsHopMs, dbRefWndMs, midiPitch, harmCandN, harmN )
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rmsDbV, rms_srate, binHz = audio_harm_rms( srate, sigV, rmsWndMs, rmsHopMs, dbRefWndMs, midiPitch, harmCandN, harmN )
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pkIdxL = locate_peak_indexes( rmsDbV, rms_srate, r['eventTimeL'] )
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min_pk_idx, max_pk_idx = find_min_max_peak_index( rmsDbV, pkIdxL, minAttkDb )
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skipPkIdxL = find_skip_peaks( rmsDbV, pkIdxL, min_pk_idx, max_pk_idx )
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fig,ax = plt.subplots()
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fig.set_size_inches(18.5, 10.5, forward=True)
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@ -255,13 +288,17 @@ def do_td_plot( inDir ):
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ax.plot( secV, rmsDbV )
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ax.plot( np.arange(0,len(rms0DbV)) / rms0_srate, rms0DbV, color="black" )
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for begMs, endMs in r['eventTimeL']:
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# print beg/end boundaries
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for i,(begMs, endMs) in enumerate(r['eventTimeL']):
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ax.axvline( x=begMs/1000.0, color="green")
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ax.axvline( x=endMs/1000.0, color="red")
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ax.text(begMs/1000.0, 20.0, str(i) )
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# plot peak markers
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for i,pki in enumerate(pkIdxL):
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ax.plot( [pki / rms_srate], [ rmsDbV[pki] ], marker='.', color="black")
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marker = "o" if i==min_pk_idx or i==max_pk_idx else "."
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color = "red" if i in skipPkIdxL else "black"
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ax.plot( [pki / rms_srate], [ rmsDbV[pki] ], marker=marker, color=color)
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plt.show()
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