computeSpectrogram.py

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# -*- coding: utf-8 -*-
 
import numpy as np
 
from pyACA.ToolPreprocAudio import ToolPreprocAudio
from pyACA.ToolComputeHann import ToolComputeHann
from pyACA.ToolBlockAudio import ToolBlockAudio
 
 
 
def computeSpectrogram(x, f_s, afWindow=None, iBlockLength=4096, iHopLength=2048, bNormalize=True, bMagnitude=True):
 
    iBlockLength = np.int_(iBlockLength)
    iHopLength = np.int_(iHopLength)
 
    # Pre-process: down-mix, normalize
    x = ToolPreprocAudio(x, bNormalize)
 
    if afWindow is None:
        # Compute window function for FFT
        afWindow = ToolComputeHann(iBlockLength)
 
    assert(afWindow.shape[0] == iBlockLength), "parameter error: invalid window dimension"
 
    # block audio data
    x_b, t = ToolBlockAudio(x, iBlockLength, iHopLength, f_s)
    
    # allocate memory
    iSpecDim = np.int_([(x_b.shape[1] / 2 + 1), x_b.shape[0]])
    X = np.zeros(iSpecDim)
    if not bMagnitude:
        X = X.astype(complex)
 
    norm = 2 / x_b.shape[1]
 
    for n in range(0, x_b.shape[0]):
        # windowed fft
        tmp = np.fft.fft(x_b[n, :] * afWindow) * norm
 
        # remove redundant spectrum parts
        if bMagnitude:
            X[:, n] = abs(tmp[range(iSpecDim[0])])
        else:
            X[:, n] = tmp[range(iSpecDim[0])]
 
    # let's be pedantic about normalization
    X[[0, iSpecDim[0]-1], :] = X[[0, iSpecDim[0]-1], :] / np.sqrt(2)
 
    f = np.arange(0, iSpecDim[0]) * f_s / iBlockLength
 
    return X, f, t
 
 
def computeSpectrogramCl(cPath):
    from pyACA.ToolReadAudio import ToolReadAudio
 
    # read audio file
    [f_s, x] = ToolReadAudio(cPath)
    
    # for debugging
    iBlockLength = 4096
    iHopLength = 2048
 
    # compute feature
    [X, f, t] = computeSpectrogram(x, f_s, None, iBlockLength, iHopLength)
 
    return X, f, t
 
 
if __name__ == "__main__":
    import argparse
 
    # add command line args and parse them
    parser = argparse.ArgumentParser(description='Compute key of wav file')
    parser.add_argument('--infile', metavar='path', required=False,
                        help='path to input audio file')
 
    # retrieve command line args
    args = parser.parse_args()
    cPath = args.infile
 
    # only for debugging
    if __debug__:
        if not cPath:
            cPath = "../ACA-Plots/audio/sax_example.wav"
 
    # call the function
    computeSpectrogramCl(cPath)