import numpy as np from scipy import signal import matplotlib.pyplot as plt  w_1 = 40  # frequency of the 1st component of the signal (Hz) w_2 = 60  # frequency of the 2nd component of the signal (Hz)  a = 0.5  # magnitude of the 1st component of the signal b = 1.0  # magnitude of the 2nd component of the signal  t = np.array([i for i in range(1, 301)]) / 1000  # time samples (s) fs = 1 / (t[1] - t[0])  # sampling frequency (Hz)  x = a * np.cos(2 * np.pi * w_1 * t) + b * np.sin(2 * np.pi * w_2 * t)  # considered signal n = .2 * np.random.randn(len(t))  # white Gaussian noise y = x + n  windows = [None, 'hamming']  for window in windows:     if window is None:         label = 'rect'     else:         label = window     f, Pxx_den = signal.periodogram(y, fs=fs, scaling='spectrum', nfft=2048, window=window)     plt.semilogy(f[1:200], Pxx_den[1:200], label=label)  plt.ylabel('Spectrum') plt.xlabel('Frequencies (Hz)') plt.title('Periodogram') plt.grid(True) plt.legend() plt.savefig("Periodogram windows.svg")