3)>>>y6 =gaussian_filter1d(x,6)>>>plt.plot(x,'k', label='original data')>>>plt.plot(y3,'--', label='filtered, sigma=3')>>>plt.plot(y6,':', label='filtered, sigma=
count_y, bins = np.histogram (a=data, bins= np.linspace (min, max, nbins))# Remove last bin from labelscount_x = bins[1:]# Smooth results with a gaussian filterifsmooth_sigma: count_y =gaussian_filter1d(count_y, sigma=smooth_sigma)# Convert to python listcount_x = [float(i)for...
又s=\sigma+j\omega, 忽略衰减项,写个4阶近似: e^{\frac{\omega^2}{2a_0}}=e^{-\frac{s^2}{2a_0}}\approx1+(-\frac{s^2}{2a_0})+\frac{(-\frac{s^2}{2a_0})^2}{2!}+\frac{(-\frac{s^3}{2a_0})^3}{3!}+\frac{(-\frac{s^2}{2a_0})^4}{4!} 观察一下,e^{-...
from scipy.ndimage import gaussian_filter1d import numpy as np import matplotlib.pyplot as plt # 创建一个一维数组 x = np.linspace(0, 10, 100) y = np.sin(x) + np.random.normal(0, 0.1, x.shape) # 添加一些噪声 # 应用高斯滤波 sigma = 1 # 标准差 y_smooth = gaussian_filter1d(y,...
stack(motion, axis=2) if smooth: motion = gaussian_filter1d(motion, sigma=2, axis=-1) motion = motion * scale return motion Example #3Source File: reggui.py From suite2p with GNU General Public License v3.0 6 votes def load_zstack(self): name = QtGui.QFileDialog.getOpenFileName(...
# 需要导入模块: from scipy.ndimage import filters [as 别名]# 或者: from scipy.ndimage.filters importgaussian_filter1d[as 别名]defpick_peaks(nc, L=16):"""Obtain peaks from a novelty curve using an adaptive threshold."""offset = nc.mean() /20.nc = filters.gaussian_filter1d(nc, sigma=...