The codes are mostly from `scipy.signal.savgol_filter`

```
import numpy as np
from math import factorial
from scipy.linalg import lstsq
def sg_coef(window_length=15, polyorder=2, deriv=1):
# window_length must be odd
# polyorder must be greater than deriv
# window_length = 15
# polyorder = 2
# deriv = 1
m = (window_length - 1) / 2 # 7 by default
x = np.arange(-m, window_length - m, dtype=float)
# [-7, -6, ...,0..., 1, 2, .., 7]
order = np.arange(polyorder + 1).reshape(-1, 1) # [0, 1, 2]
A = x ** order # create a design matrix, size=(polyorder+1, window_length)
"""
A =
[[1, 1, 1, 1, 1, ..., 1, 1, 1, 1, 1]
[-7, -6, -5, ...,0, 1, 2,..., 6, 7]
[49, 36, 25, ...,0, 1, 4, ..., 49]]
"""
y = np.zeros(polyorder + 1) # y= [0.0, 0.0, 0.0]
y[deriv] = float(factorial(deriv)) # y=[0.0, 1.0, 0.0]
coef, _, _, _ = lstsq(A, y) # 最小二乘拟合
# A.dot(coef) = y
return coef
```

Below is a online Python console based on `Jupyterlite`

. You can try the codes above in the console and verify the results.