Delete melbank.py

melbank.py

@@ -1,151 +0,0 @@
-"""This module implements a Mel Filter Bank.
-In other words it is a filter bank with triangular shaped bands
-arnged on the mel frequency scale.
-An example ist shown in the following figure:
-.. plot::
-    from pylab import plt
-    import melbank
-    f1, f2 = 1000, 8000
-    melmat, (melfreq, fftfreq) = melbank.compute_melmat(6, f1, f2, num_fft_bands=4097)
-    fig, ax = plt.subplots(figsize=(8, 3))
-    ax.plot(fftfreq, melmat.T)
-    ax.grid(True)
-    ax.set_ylabel('Weight')
-    ax.set_xlabel('Frequency / Hz')
-    ax.set_xlim((f1, f2))
-    ax2 = ax.twiny()
-    ax2.xaxis.set_ticks_position('top')
-    ax2.set_xlim((f1, f2))
-    ax2.xaxis.set_ticks(melbank.mel_to_hertz(melfreq))
-    ax2.xaxis.set_ticklabels(['{:.0f}'.format(mf) for mf in melfreq])
-    ax2.set_xlabel('Frequency / mel')
-    plt.tight_layout()
-    fig, ax = plt.subplots()
-    ax.matshow(melmat)
-    plt.axis('equal')
-    plt.axis('tight')
-    plt.title('Mel Matrix')
-    plt.tight_layout()
-Functions
----------
-"""
-
-from numpy import abs, append, arange, insert, linspace, log10, round, zeros
-
-
-def hertz_to_mel(freq):
-    """Returns mel-frequency from linear frequency input.
-    Parameter
-    ---------
-    freq : scalar or ndarray
-        Frequency value or array in Hz.
-    Returns
-    -------
-    mel : scalar or ndarray
-        Mel-frequency value or ndarray in Mel
-    """
-    return 2595.0 * log10(1 + (freq / 700.0))
-
-
-def mel_to_hertz(mel):
-    """Returns frequency from mel-frequency input.
-    Parameter
-    ---------
-    mel : scalar or ndarray
-        Mel-frequency value or ndarray in Mel
-    Returns
-    -------
-    freq : scalar or ndarray
-        Frequency value or array in Hz.
-    """
-    return 700.0 * (10**(mel / 2595.0)) - 700.0
-
-
-def melfrequencies_mel_filterbank(num_bands, freq_min, freq_max, num_fft_bands):
-    """Returns centerfrequencies and band edges for a mel filter bank
-    Parameters
-    ----------
-    num_bands : int
-        Number of mel bands.
-    freq_min : scalar
-        Minimum frequency for the first band.
-    freq_max : scalar
-        Maximum frequency for the last band.
-    num_fft_bands : int
-        Number of fft bands.
-    Returns
-    -------
-    center_frequencies_mel : ndarray
-    lower_edges_mel : ndarray
-    upper_edges_mel : ndarray
-    """
-
-    mel_max = hertz_to_mel(freq_max)
-    mel_min = hertz_to_mel(freq_min)
-    delta_mel = abs(mel_max - mel_min) / (num_bands + 1.0)
-    frequencies_mel = mel_min + delta_mel * arange(0, num_bands + 2)
-    lower_edges_mel = frequencies_mel[:-2]
-    upper_edges_mel = frequencies_mel[2:]
-    center_frequencies_mel = frequencies_mel[1:-1]
-    return center_frequencies_mel, lower_edges_mel, upper_edges_mel
-
-
-def compute_melmat(num_mel_bands=12, freq_min=64, freq_max=8000,
-                   num_fft_bands=513, sample_rate=16000):
-    """Returns tranformation matrix for mel spectrum.
-    Parameters
-    ----------
-    num_mel_bands : int
-        Number of mel bands. Number of rows in melmat.
-        Default: 24
-    freq_min : scalar
-        Minimum frequency for the first band.
-        Default: 64
-    freq_max : scalar
-        Maximum frequency for the last band.
-        Default: 8000
-    num_fft_bands : int
-        Number of fft-frequenc bands. This ist NFFT/2+1 !
-        number of columns in melmat.
-        Default: 513   (this means NFFT=1024)
-    sample_rate : scalar
-        Sample rate for the signals that will be used.
-        Default: 44100
-    Returns
-    -------
-    melmat : ndarray
-        Transformation matrix for the mel spectrum.
-        Use this with fft spectra of num_fft_bands_bands length
-        and multiply the spectrum with the melmat
-        this will tranform your fft-spectrum
-        to a mel-spectrum.
-    frequencies : tuple (ndarray <num_mel_bands>, ndarray <num_fft_bands>)
-        Center frequencies of the mel bands, center frequencies of fft spectrum.
-    """
-    center_frequencies_mel, lower_edges_mel, upper_edges_mel =  \
-        melfrequencies_mel_filterbank(
-            num_mel_bands,
-            freq_min,
-            freq_max,
-            num_fft_bands
-        )
-
-    center_frequencies_hz = mel_to_hertz(center_frequencies_mel)
-    lower_edges_hz = mel_to_hertz(lower_edges_mel)
-    upper_edges_hz = mel_to_hertz(upper_edges_mel)
-    freqs = linspace(0.0, sample_rate / 2.0, num_fft_bands)
-    melmat = zeros((num_mel_bands, num_fft_bands))
-
-    for imelband, (center, lower, upper) in enumerate(zip(
-            center_frequencies_hz, lower_edges_hz, upper_edges_hz)):
-
-        left_slope = (freqs >= lower) == (freqs <= center)
-        melmat[imelband, left_slope] = (
-            (freqs[left_slope] - lower) / (center - lower)
-        )
-
-        right_slope = (freqs >= center) == (freqs <= upper)
-        melmat[imelband, right_slope] = (
-            (upper - freqs[right_slope]) / (upper - center)
-        )
-    return melmat, (center_frequencies_mel, freqs)