问题描述
我写了以下代码：
from scipy.interpolate import interp1d
from scipy.signal import medfilt
z = medfilt(derivation,3)
diff = abs(derivation-z) #shows the difference between the smoothed array and the original one.
new_smootheddata = np.where(diff>3,z,derivation)
x=np.arange(0,len(x_values[:-2]))
f = interp1d(x,new_smootheddata,kind="linear")
xnew = np.arange(0,len(x_values[:-3]),0.01)
ynew = f(xnew)
plt.plot(x,"o",xnew,ynew,"-")
x_values 是以下数组：
[0.,0.01,0.02,0.03,0.04,0.05,0.06,0.07,0.08,0.09,0.1,0.11,0.12,0.13,0.14,0.15,0.16,0.17,0.18,0.19,0.2,0.21,0.22,0.23,0.24,0.25,0.26,0.27,0.28,0.29,0.3,0.31,0.32,0.33,0.34,0.35,0.36,0.37,0.38,0.39,0.4,0.41,0.42,0.43,0.44,0.45,0.46,0.47,0.48,0.49,0.5,0.51,0.52,0.53,0.54,0.55,0.56,0.57,0.58,0.59,0.6,0.61,0.62,0.63,0.64,0.65,0.66,0.67,0.68,0.69,0.7,0.71,0.72,0.73,0.74,0.75,0.76,0.77,0.78,0.79,0.8,0.81,0.82,0.83,0.84,0.85,0.86,0.87,0.88,0.89,0.9,0.91,0.92,0.93,0.94,0.95,0.96,0.97,0.98,0.99,1.,1.01,1.02,1.03,1.04,1.05,1.06,1.07,1.08,1.09,1.1,1.11,1.12,1.13,1.14,1.15,1.16,1.17,1.18,1.19,1.2,1.21,1.22,1.23,1.24,1.25,1.26,1.27,1.28,1.29,1.3,1.31,1.32,1.33,1.34,1.35,1.36,1.37,1.38,1.39,1.4,1.41,1.42,1.43,1.44,1.45,1.46,1.47,1.48,1.49,1.5 ]
和 derivation 是以下数组：
[9.88,-2.12,29.88,9.88,16.88,4.88,10.88,3.88,15.88,22.88,34.88,41.88,53.88,60.88,72.88,84.88,97.88,110.88,128.88,141.88,159.88,172.88,191.88,203.88,222.88,241.88,266.88,272.88,297.88,303.88,322.88,279.88,240.88,166.88,-46.12,-64.12,-90.12,-139.12,-134.12,-164.12,-190.12,-202.12,-226.12,-221.12,-227.12,-234.12,-214.12,-215.12,-208.12,-196.12,-189.12,-183.12,-184.12,-177.12,-165.12,-152.12,-146.12,-170.12,-171.12,-159.12,-133.12,-108.12,-77.12,-52.12,-27.12,-8.12,21.88,47.88,73.88,91.88,109.88,122.88,103.88,78.88,66.88,-15.12,-9.12,-9.12]
我使用中值过滤器编写了代码。我想用带通滤波器做同样的事情，但我找不到 Python 的函数。 任何人都可以帮我转换代码以使用带通滤波器而不是中值滤波器吗？
注意： 这是 plot
解决方法
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