Python implementation of smoothed z-score algorithm version 2, from http://stackoverflow.com/a/22640362/6029703

ThresholdingAlgo2.py

from numba.decorators import jit
import numpy as np

#The original version is here: https://gist.github.com/ximeg/587011a65d05f067a29ce9c22894d1d2
#I made small changes and used numba to do it faster.
  
@jit
def thresholding_algo2(y, lag, threshold, influence):
    signals = np.zeros(len(y))
    filteredY = np.array(y)
    avgFilter = np.zeros(len(y))
    stdFilter = np.zeros(len(y))
    avgFilter[lag - 1] = np.mean(y[0:lag])
    stdFilter[lag - 1] = np.std(y[0:lag])
    for i in range(lag, len(y) - 1):
        if abs(y[i] - avgFilter[i-1]) > threshold * stdFilter [i-1]:
            if y[i] > avgFilter[i-1]:
                signals[i] = 1
            else:
                signals[i] = -1

            filteredY[i] = influence * y[i] + (1 - influence) * filteredY[i-1]
            avgFilter[i] = np.mean(filteredY[(i-lag):i])
            stdFilter[i] = np.std(filteredY[(i-lag):i])
        else:
            signals[i] = 0
            filteredY[i] = y[i]
            avgFilter[i] = np.mean(filteredY[(i-lag):i])
            stdFilter[i] = np.std(filteredY[(i-lag):i])

    return dict(signals = np.asarray(signals),
                avgFilter = np.asarray(avgFilter),
                stdFilter = np.asarray(stdFilter))