focus

focus is a high-performance package for online changepoint detection in univariate and multivariate data streams. It provides efficient C++ implementations of the FOCUS, MD-FOCUS and NP-FOCUS algorithms, with R and Python interfaces for real-time monitoring and offline analysis.

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Features

• Multiple distributions — supports a range of models for Gaussian change-in-mean, Poisson change-in-rate, Gamma/Exponential change-in-scale, Bernoulli change-in-probability, as well as Non-parametric detectors. New models and cost functions are easy to implement!
• Univariate and multivariate detection — detect changes in univariate or multivariate sequences
• Known or unknown pre-change parameters — flexible modeling of both the likelihood-ratio test (unknown pre-change) and the Page–CUSUM test (known pre-change)
• One-sided test statistics (univariate only) — detects increases or decreases in the parameters, or both
• Easy to access C++ backend — Language agnostic backend optimized for speed and scalability

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Interfaces

The same C++ backend is shared across both interfaces:

• R interface → focus/ → See detailed documentation in focus/README.md

• Python interface → focus_cpt/ → See detailed documentation in focus_cpt/README

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Installation

R

# from source
devtools::install_github("gtromano/unified_focus", subdir = "focus")

Python

# cloning the repo
# pip install focus_cpt
# or directly from GitHub
pip install git+https://github.com/gtromano/unified_focus.git#subdirectory=focus_cpt

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Example (R)

library(focus)
set.seed(45)
Y <- c(rnorm(1000, mean = 0), rnorm(500, mean = -1))

res <- focus_offline(Y, threshold = 20, type = "univariate", family = "gaussian")

cat("Detection time:", res$detection_time, "\n")

Detection time: 1035 

cat("Estimated changepoint:", res$detected_changepoint, "\n")

Estimated changepoint: 991 

Example (Python)

import numpy as np
from focus_cpt import focus_offline
Y = np.concatenate([np.random.normal(0, 1, 1000), np.random.normal(-1, 1, 500)])

res = focus_offline(Y, threshold=20, type="univariate", family="gaussian")
print("Detection time:", res["detection_time"])
print("Estimated changepoint:", res["detected_changepoint"])

Detection time: 1023
Estimated changepoint: 1008

Authors and Contributors

• Gaetano Romano: email (Author) (Maintainer) (Creator) (Translator)

• Kes Ward: email (Author)

• Yuntang Fan: email (Author)

• Guillem Rigaill: email (Author)

• Vincent Runge: email (Author)

• Paul Fearnhead: email (Author)

• Idris A. Eckley: email (Author)

External libraries

• The R package version of this software bundles code from code from Qhull (http://www.qhull.org/), from C.B. Barber and The Geometry Center. Qhull is free software and may be obtained via http from www.qhull.org. For details, see focus/inst/COPYRIGHTS/qhull

• The Python package depends on installation of the Qhull library. If not found, the user will be notified with instructions to install.