Appendix 2 - choH (python version)

13. Appendix 2 - choH (python version)#

13.1. Background#

choH (Klingon change), is a toy changepoint dection method implemented here in python.

13.2. Dependencies#

import scipy
from math import log
from functools import reduce

13.2.1. Utilities#

def compose(*funcs):
    return reduce(lambda f,g : lambda x : f(g(x)), funcs, lambda x : x)

13.3. Method#

def choH(data) : return list(map(compose(float,log,lambda i : scipy.stats.kstest(data[-i:],data[:-i]).pvalue),range(1,len(data))))

13.4. Examples#

import numpy
import matplotlib.pyplot as plt

13.4.1. Example 1 - no change#

numpy.random.seed(0)
X = [float(x) for x in list(numpy.random.normal(0,1,1000)) + list(numpy.random.normal(0,1,1000))]
plt.plot(X)
plt.plot(choH(X))

[<matplotlib.lines.Line2D at 0x72577687fc50>]
_images/2d66f95a5c911acce750e35e70de06e4764f2c046be38e3dc74c51769ed6ff58.png

13.4.2. Example 2 - single change#

# change at t = 1001
numpy.random.seed(0)
X = [float(x) for x in list(numpy.random.normal(0,1,1000)) + list(numpy.random.normal(0.3,1,1000))]
plt.plot(X)
plt.plot(choH(X))

[<matplotlib.lines.Line2D at 0x72577625bb10>]
_images/4957ffdd942f9829c402b991fcc1d68c5b9848f8966d1ff5162fe40c1f805039.png 
res = choH(X)

res.index(min(res))

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