Spectrograms with Scipy and Matplotlib

spectrograms.py

import matplotlib.colors as colors
import matplotlib.pyplot as plt
import numpy as np
from scipy import signal
from scipy.io import wavfile

BASEDIR = './'
OUTDIR = BASEDIR + 'spectrograms/'

def save_spectrogram(voice_name):
    sample_rate, samples = wavfile.read(BASEDIR + 'samples/' + voice_name + '.wav')
    # average all channels
    avg = np.add(samples[:,0],samples[:,0])/2
    # generate spectrogram
    f, t, Sxx = signal.spectrogram(avg, sample_rate)

    # make a figure without borders or padding
    fig=plt.figure(frameon=False)
    fig.set_size_inches(512/32,512/32) # 512 pixels, 32 dpi
    mesh = fig.add_subplot(1,1,1)
    mesh.pcolormesh(t, f, Sxx,
                    norm=colors.SymLogNorm(linthresh=0.00001), # magic value threshold set so it looks good
                    cmap='Greys')
    plt.axis('off')
    mesh.axes.get_xaxis().set_visible(False)
    mesh.axes.get_yaxis().set_visible(False)
    fig.subplots_adjust(bottom = 0)
    fig.subplots_adjust(top = 1)
    fig.subplots_adjust(right = 1)
    fig.subplots_adjust(left = 0)
    fig.savefig(OUTDIR + voice_name + '.png', transparent=True, dpi = 32)