### Navigation

- index
- modules |
- home|
- examples|
- tutorials|
- pyplot|
- docs »

# Specgram Demo

    import matplotlib.pyplot as plt
    import numpy as np

    # Fixing random state for reproducibility
    np.random.seed(19680801)

    dt = 0.0005
    t = np.arange(0.0, 20.0, dt)
    s1 = np.sin(2*np.pi*100*t)
    s2 = 2*np.sin(2*np.pi*400*t)

    # create a transient "chirp"
    mask = np.where(np.logical_and(t > 10, t < 12), 1.0, 0.0)
    s2 = s2 * mask

    # add some noise into the mix
    nse = 0.01*np.random.random(size=len(t))

    x = s1 + s2 + nse  # the signal
    NFFT = 1024       # the length of the windowing segments
    Fs = int(1.0/dt)  # the sampling frequency

    # Pxx is the segments x freqs array of instantaneous power, freqs is
    # the frequency vector, bins are the centers of the time bins in which
    # the power is computed, and im is the matplotlib.image.AxesImage
    # instance

    ax1 = plt.subplot(211)
    plt.plot(t, x)
    plt.subplot(212, sharex=ax1)
    Pxx, freqs, bins, im = plt.specgram(x, NFFT=NFFT, Fs=Fs, noverlap=900)
    plt.show()

Total running time of the script: ( 0 minutes 0.070 seconds)

Generated by Sphinx-Gallery