I would like to smooth time series data. For this I would like to use Python.
Now I have already found the function scipy.ndimage.gaussian_filter1d.
For this, the array and a sigma value must be passed.
Now to my question:
Is the sigma value equal to the filter length? I would like to run a filter of length 365 over the data. Would it then be the correct procedure to set this sigma value to 365 or am I confusing things?
sigma
defines how your Gaussian filter are spread around its mean. You can create gaussian filter with a specific size like below.
import numpy as np
import matplotlib.pyplot as plt
sigma1 = 3
sigma2 = 50
def gaussian_filter1d(size,sigma):
filter_range = np.linspace(-int(size/2),int(size/2),size)
gaussian_filter = [1 / (sigma * np.sqrt(2*np.pi)) * np.exp(-x**2/(2*sigma**2)) for x in filter_range]
return gaussian_filter
fig,ax = plt.subplots(1,2)
ax[0].plot(gaussian_filter1d(size=365,sigma=sigma1))
ax[0].set_title(f'sigma= {sigma1}')
ax[1].plot(gaussian_filter1d(size=365,sigma=sigma2))
ax[1].set_title(f'sigma= {sigma2}')
plt.show()
Here is the effect of sigma
on the Gaussian filter.
Later, you might convolve your signal with your Gaussian filter.