numpy.
blackman
返回布莱克曼窗口。
布莱克曼窗是一个锥度形成使用前三项的余弦和。它的设计是为了尽可能减少泄漏。它接近最佳状态，只比凯撒窗稍差一点。
输出窗口中的点数。如果小于或等于零，则返回空数组。
最大值规范化为1的窗口（只有当样本数为奇数时，才会显示值1）。
参见
bartlett
hamming
hanning
kaiser
笔记
Blackman窗口定义为
System Message: WARNING/2 (W（n）=0.42-0.5 \cos（2 \pi n/m）+0.08 \cos（4 \pi n/m）)
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大多数对Blackman窗口的引用来自信号处理文献，在那里它被用作平滑值的许多窗口函数之一。它也被称为变迹（意思是“消除脚”，即在采样信号的开始和结束处平滑不连续）或渐缩函数。它被称为“近似最优”的渐缩函数，几乎和凯撒窗一样好。
工具书类
Blackman，R.B.和Tukey，J.W.，（1958）功率谱测量，多佛出版社，纽约。
Oppenheim，A.V.和R.W.Schafer。离散时间信号处理。新泽西州上萨德尔河：普伦蒂斯霍尔，1999年，第468-471页。
实例
>>> import matplotlib.pyplot as plt >>> np.blackman(12) array([-1.38777878e-17, 3.26064346e-02, 1.59903635e-01, # may vary 4.14397981e-01, 7.36045180e-01, 9.67046769e-01, 9.67046769e-01, 7.36045180e-01, 4.14397981e-01, 1.59903635e-01, 3.26064346e-02, -1.38777878e-17])
绘制窗口和频率响应：
>>> from numpy.fft import fft, fftshift >>> window = np.blackman(51) >>> plt.plot(window) [<matplotlib.lines.Line2D object at 0x...>] >>> plt.title("Blackman window") Text(0.5, 1.0, 'Blackman window') >>> plt.ylabel("Amplitude") Text(0, 0.5, 'Amplitude') >>> plt.xlabel("Sample") Text(0.5, 0, 'Sample') >>> plt.show()
>>> plt.figure() <Figure size 640x480 with 0 Axes> >>> A = fft(window, 2048) / 25.5 >>> mag = np.abs(fftshift(A)) >>> freq = np.linspace(-0.5, 0.5, len(A)) >>> with np.errstate(divide='ignore', invalid='ignore'): ... response = 20 * np.log10(mag) ... >>> response = np.clip(response, -100, 100) >>> plt.plot(freq, response) [<matplotlib.lines.Line2D object at 0x...>] >>> plt.title("Frequency response of Blackman window") Text(0.5, 1.0, 'Frequency response of Blackman window') >>> plt.ylabel("Magnitude [dB]") Text(0, 0.5, 'Magnitude [dB]') >>> plt.xlabel("Normalized frequency [cycles per sample]") Text(0.5, 0, 'Normalized frequency [cycles per sample]') >>> _ = plt.axis('tight') >>> plt.show()