Hampel filter implementation in Python using numba

hampel_filter_forloop_numba.py

# Based on https://gist.github.com/erykml/9b07b916ceee78c207d14fa2548b8f6f#file-hampel_filter_forloop_numba-py

import numpy as np
from numba import jit

@jit(nopython=True)
def hampel_filter_forloop_numba(input_series, window_length, n_sigmas=3):
  if window_length % 2 == 0:
    raise ValueError('window_length should be odd')

  h = int(window_length/2)
  n = len(input_series)
  new_series = input_series.copy()
  k = 1.4826022185056018 # scale factor for Gaussian distribution
  indices = []

  for i in range((h),(n - h + 1)):
    x0 = np.nanmedian(input_series[(i - h):(i + h + 1)])
    S0 = k * np.nanmedian(np.abs(input_series[(i - h):(i + h + 1)] - x0))
    if (np.abs(input_series[i] - x0) > n_sigmas * S0):
        new_series[i] = x0
        indices.append(i)

  return new_series, indices