• Set the figure size and adjust the padding between and around the subplots.
  • Initialize a variable, dt.
  • C">

    Plotting power spectral density in Matplotlib



    To plot Power Spectral Density in Matplotlib, we can take the following steps −

    • Set the figure size and adjust the padding between and around the subplots.
    • Initialize a variable, dt.
    • Create t, nse , r, cnse, s, and r data points using numpy
    • Create a figure and a set of subplots.
    • Plot t and s data using plot() method.
    • Plot the power spectral density.
    • To display the figure, use show() method.

    Example

    import matplotlib.pyplot as plt
    import numpy as np
    
    plt.rcParams["figure.figsize"] = [7.50, 3.50]
    plt.rcParams["figure.autolayout"] = True
    
    dt = 0.01
    t = np.arange(0, 10, dt)
    nse = np.random.randn(len(t))
    r = np.exp(-t / 0.05)
    cnse = np.convolve(nse, r) * dt
    cnse = cnse[:len(t)]
    s = 0.1 * np.sin(2 * np.pi * t) + cnse
    
    fig, (ax0, ax1) = plt.subplots(2, 1)
    ax0.plot(t, s)
    ax1.psd(s, 512, 1 / dt)
    
    plt.show()

    Output

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