如何在python中平滑曲线
我有一条熵曲线(1d numpy数组),但这条曲线有很多噪音。 我想用平滑法删除噪声 这是我的曲线图: 我曾尝试使用Kaiser-Bessel滤波器制作卷积产品来解决此问题:如何在python中平滑曲线,python,numpy,signal-processing,gaussian,smoothing,Python,Numpy,Signal Processing,Gaussian,Smoothing,我有一条熵曲线(1d numpy数组),但这条曲线有很多噪音。 我想用平滑法删除噪声 这是我的曲线图: 我曾尝试使用Kaiser-Bessel滤波器制作卷积产品来解决此问题: gaussian_curve = window_kaiser(windowLength, beta=20) # kaiser filter gaussian_curve = gaussian_curve / sum(gaussian_curve) for i in range(0, windows_number):
gaussian_curve = window_kaiser(windowLength, beta=20) # kaiser filter
gaussian_curve = gaussian_curve / sum(gaussian_curve)
for i in range(0, windows_number):
start = (i * step) + 1
end = (i * step) + windowLength
convolution[i] = (np.convolve(entropy[start:end + 1], gaussian_curve, mode='valid'))
entropy[i] = convolution[i][0]
但此代码返回以下错误:
File "/usr/lib/python2.7/dist-packages/numpy/core/numeric.py", line 822, in convolve
raise ValueError('v cannot be empty')
ValueError: v cannot be empty
具有“valid”模式的运算符返回重叠中的中心元素,但在本例中返回空元素
有没有一种简单的方法来应用平滑
谢谢 好的,我解决了。
我采用了另一种方法:
守则:
def savitzky_golay(y, window_size, order, deriv=0, rate=1):
import numpy as np
from math import factorial
try:
window_size = np.abs(np.int(window_size))
order = np.abs(np.int(order))
except ValueError, msg:
raise ValueError("window_size and order have to be of type int")
if window_size % 2 != 1 or window_size < 1:
raise TypeError("window_size size must be a positive odd number")
if window_size < order + 2:
raise TypeError("window_size is too small for the polynomials order")
order_range = range(order+1)
half_window = (window_size -1) // 2
# precompute coefficients
b = np.mat([[k**i for i in order_range] for k in range(-half_window, half_window+1)])
m = np.linalg.pinv(b).A[deriv] * rate**deriv * factorial(deriv)
# pad the signal at the extremes with
# values taken from the signal itself
firstvals = y[0] - np.abs( y[1:half_window+1][::-1] - y[0] )
lastvals = y[-1] + np.abs(y[-half_window-1:-1][::-1] - y[-1])
y = np.concatenate((firstvals, y, lastvals))
return np.convolve( m[::-1], y, mode='valid')
结果是:
FYI:scipy 0.14.0(即将发布)在scipy.signal.savgol_过滤器中实现了Savitzky-Golay过滤器
。可能与
entropy = np.array(entropy)
entropy = savitzky_golay(entropy, 51, 3) # window size 51, polynomial order 3