A python package for detecting gradual changepoint using Fuzzy Rough CP (roufCP)
Project description
roufcp - Rough Fuzzy Changepoint Detection
Gradual Change-Point Detection Library based on Rough Fuzzy Changepoint Detection algorithm roufcp
.
The package is available in PyPI.
Usage
>> import numpy as np
>> from roufcp import roufCP
>> X = np.concatenate([np.ones(20) * 5, np.zeros(20), np.ones(20) * 10]) + np.random.randn(60)
>> roufCP(delta = 3, w = 3).fit(X, moving_window = 10, k = 2)
Try help(roufCP)
for detailed documentation.
roufCP
is a class for Rough Fuzzy Changepoint Detection with the following attributes and functions.
-
Attributes
delta
:int
, The fuzzyness parameter, typically between 5-100w
:int
, The roughness parameter, typically between 5-100
-
Methods
-
fit_from_regularity_measure(X, regularity_measure, k)
: fit the data X with help of the regularity measure and output the estimated changepoints -
fit(X, moving_window, method, k)
: fit the data X with given regularity measures and output the estimated changepoints. The method argument defaults to kstest, available options are;meandiff
: Two sample mean differencettest
: Two sample t test statistickstest
: Two sample Kolmogorov test statisticmannwhitney
: Two sample Mann Whitney U statisticanderson-darling
: Two sample Anderson Darling test statisticadf
: Augmented Dickey Fuller test of stationarity with linear trendkpss
: Kwiatkowski–Phillips–Schmidt–Shin (KPSS) test of stationarity with linear trend
-
hypothesis_test(cp_list, cp_entropy, mu, sigma, a_delta)
: Performs hypothesis testing of the null hypothesis that there is no changepoint in the data, against the alternative that there is changepoint at the specified indices, and outputs the p-value
-
Authors & Contributors
- Subhrajyoty Roy - https://subroy13.github.io/
- Ritwik Bhaduri - https://github.com/Ritwik-Bhaduri
- Sankar Kumar Pal - https://www.isical.ac.in/~sankar/
License
This code is licensed under MIT License.
Project details
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