The Hamming window is a taper formed by using a weighted cosine
Parameters(numpy.hamming(M)):
M : int Number of points in the output window.
If zero or less, an empty array is returned.
Returns:
out : array
The window, with the maximum value normalized to one (the value one appears only if the number of samples is odd).
Example:
import numpy as np print(np.hamming(12)) |
Output:
[ 0.08 0.15302337 0.34890909 0.60546483 0.84123594 0.98136677 0.98136677 0.84123594 0.60546483 0.34890909 0.15302337 0.08 ]
Plotting the window and its frequency response (requires SciPy and matplotlib):
For Window:
import numpy as np import matplotlib.pyplot as plt from numpy.fft import fft, fftshift window = np.hamming(51) plt.plot(window) plt.title("Hamming window") plt.ylabel("Amplitude") plt.xlabel("Sample") plt.show() |
Output:
For frequency:
import numpy as np import matplotlib.pyplot as plt from numpy.fft import fft, fftshift window = np.hamming(51) plt.figure() A = fft(window, 2048) / 25.5mag = np.abs(fftshift(A)) freq = np.linspace(-0.5, 0.5, len(A)) response = 20 * np.log10(mag) response = np.clip(response, -100, 100) plt.plot(freq, response) plt.title("Frequency response of Hamming window") plt.ylabel("Magnitude [dB]") plt.xlabel("Normalized frequency [cycles per sample]") plt.axis('tight') plt.show() |
Output:
