597ae33645d1a8a0e2e87e8bec05232594d5c447,pyAudioAnalysis/ShortTermFeatures.py,,chromagram,#,305

Before Change

    cur_position = 0
    count_fr = 0
    num_fft = int(window / 2)
    chromogram = np.zeros((int((num_samples-step-window) / step), 12),
                          dtype=np.float64)

    while cur_position + window - 1 < num_samples:
        count_fr += 1
        x = signal[cur_position:cur_position + window]
        cur_position = cur_position + step
        X = abs(fft(x))
        X = X[0:num_fft]
        X = X / len(X)
        chroma_names, chroma_feature_matrix = chroma_features(X, sampling_rate,
                                                              num_fft)
        chroma_feature_matrix = chroma_feature_matrix[:, 0]
        chromogram[count_fr-1, :] = chroma_feature_matrix.T
    freq_axis = chroma_names
    time_axis = [(t * step) / sampling_rate
                 for t in range(chromogram.shape[0])]

    if plot:
        fig, ax = plt.subplots()
        chromogram_plot = chromogram.transpose()[::-1, :]
        ratio = int(chromogram_plot.shape[1] / (3 * chromogram_plot.shape[0]))
        if ratio < 1:
            ratio = 1
        chromogram_plot = np.repeat(chromogram_plot, ratio, axis=0)
        imgplot = plt.imshow(chromogram_plot)

        ax.set_yticks(range(int(ratio / 2), len(freq_axis) * ratio, ratio))
        ax.set_yticklabels(freq_axis[::-1])

After Change

    num_samples = len(signal)  // total number of signals
    count_fr = 0
    num_fft = int(window / 2)
    chromogram = np.zeros((int((num_samples-step-window) / step) + 1, 12),
                          dtype=np.float64)
    for cur_p in tqdm(range(window, num_samples - step, step),
                      disable=not show_progress):
        count_fr += 1
        x = signal[cur_p:cur_p + window]
        X = abs(fft(x))
        X = X[0:num_fft]
        X = X / len(X)
        chroma_names, chroma_feature_matrix = chroma_features(X, sampling_rate,
                                                              num_fft)
        chroma_feature_matrix = chroma_feature_matrix[:, 0]
        chromogram[count_fr-1, :] = chroma_feature_matrix.T
    freq_axis = chroma_names
    time_axis = [(t * step) / sampling_rate
                 for t in range(chromogram.shape[0])]

    if plot:
        fig, ax = plt.subplots()
        chromogram_plot = chromogram.transpose()[::-1, :]
        ratio = int(chromogram_plot.shape[1] / (3 * chromogram_plot.shape[0]))
        if ratio < 1:
            ratio = 1
        chromogram_plot = np.repeat(chromogram_plot, ratio, axis=0)
        imgplot = plt.imshow(chromogram_plot)

        ax.set_yticks(range(int(ratio / 2), len(freq_axis) * ratio, ratio))
        ax.set_yticklabels(freq_axis[::-1])

Instances