N = 1024
freq = 8000


f1 = 500
f2 = 1200
n = np.arange(N)
w = np.random.normal(0,1,N)
s = 0.5*np.sin(2*np.pi*n*f1/freq) + np.sin(2*np.pi*n*f2/freq)
y = s + 0.1*w
pw = signal.hann(N) * w
ps = signal.hann(N) * s
py = signal.hann(N) * y

plt.figure(figsize = (20,15))

plt.subplot(3,2,1)
plt.title("Periodogram Power Spectral Density Estimate")
plt.xlabel("Normalized Frequency")
plt.xlim(0,1)
plt.psd(w, N)

plt.subplot(3,2,3)
plt.title("Periodogram Power Spectral Density Estimate")
plt.xlabel("Normalized Frequency")
plt.xlim(0,1)
plt.psd(s, N)

plt.subplot(3,2,5)
plt.title("Periodogram Power Spectral Density Estimate")
plt.xlabel("Normalized Frequency")
plt.xlim(0,1)
plt.psd(y, N)

plt.subplot(3,2,2)
plt.title("Periodogram Power Spectral Density Estimate")
plt.xlabel("Normalized Frequency")
plt.xlim(0,1)
plt.psd(pw, N)

plt.subplot(3,2,4)
plt.title("Periodogram Power Spectral Density Estimate")
plt.xlabel("Normalized Frequency")
plt.xlim(0,1)
plt.psd(ps, N)

plt.subplot(3,2,6)
plt.title("Periodogram Power Spectral Density Estimate")
plt.xlabel("Normalized Frequency")
plt.xlim(0,1)
plt.psd(py, N)
plt.show()