Please explain the code and predict the output:
import numpy as np
import matplotlib.pyplot as plt
from scipy import signal
rhp - spectral noise density unit/SQRT(Hz)
sr - sample rate
n - no of points
mu - mean value, optional
n points of noise signal with spectral noise density of rho
def white_noise(rho, sr, n, mu=0):
sigma = rho * np.sqrt(sr/2)
noise = np.random.normal(mu, sigma, n)
rho = 1
sr = 1000
n = 1000
period = n/sr
time = np.linspace(0, period, n)
signal_pure = 100*np.sin(2*np.pi*13*time)
noise = white_noise(rho, sr, n)
signal_with_noise = signal_pure + noise
f, psd = signal.periodogram(signal_with_noise, sr)
print("Mean spectral noise density = ",np.sqrt(np.mean(psd[50:])), "arb.u/SQRT(Hz)")
#plt.axvline(13, ls="dashed", color="g")
plt.axhline(rho, ls="dashed", color="r")
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