Python code for creating zebra finch spectrograms

spectrogram.py

# Looking for a decent spectrogram? Check out resin.
#
# https://github.com/kylerbrown/resin
#
# Resin creates multi-taper spectrograms and spectral derivative spectrograms
#
# old code below...

import matplotlib.pyplot as plt
import matplotlib.cm as cm
def spectrogram(data, sr, start, stop, ms_nfft=10, 
                ax=None, osc=True, cmap=cm.inferno, **kwargs):
    """
    data : a vector of samples, first sample starts at time = 0
    sr : sampling rate
    start : start time to slice data, units: seconds
    stop : stop time to slice data, units: seconds
    ms_nfft : width of fourier transform in milliseconds
    decent colormaps: cm.viridis, cm.inferno, cm.magma, cm.plasma
    
    extra arguments are sent to plt.specgram
    """
    nfft = int(ms_nfft / 1000. * sr)
    start_samp = int(start*sr) - nfft//2
    stop_samp = int(stop*sr) - nfft//2
    x = data[start_samp:stop_samp]
    if ax is None:
        ax = plt.gca()
    plt.sca(ax)
    plt.specgram(x, Fs=sr, NFFT=nfft, noverlap=nfft-(int(sr*.001)), cmap=cmap, **kwargs)
    if osc:
        plt.plot(np.arange(len(x))/sr, data[int(start*sr):int(stop*sr)]/np.max(x)*1000+6000)
    plt.ylim(300, 8000)

Just wondering, why are you using plt.specgram instead of scipy.signal.spectrogram?