Fast running maximum-minimum filters implemented in C++.

This code implements the algorithms described in the following paper:

Daniel Lemire, Streaming Maximum-Minimum Filter Using No More than Three Comparisons per Element. Nordic Journal of Computing, 13 (4), pages 328-339, 2006.

Contributors: Daniel Lemire, Kai Wolf

The main algorithm presented in this package is used in Apache Hive.

Usage

To reproduce the numbers from the paper, do the following:

  make
  
  ./unit
  
  ./runningmaxmin --sine 1000000 10000 --windowrange 4 100  --times 1
  
  ./runningmaxmin --white 1000000 --windowrange 4 100  --times 1

Suitability

The new algorithm introduced in the manuscript is most suitable for piecewise monotonic data or when low-latency is required. Otherwise, Gil-Kimmel and van Herk are good choices.

See also

• Julia version: streaming maximum-minimum filter implementation in Julia https://github.com/sairus7/MaxMinFilters.jl
• For a Python version, see https://github.com/lemire/pythonmaxmin
• For an application of this idea to rolling statistics in JavaScript, see https://github.com/shimondoodkin/efficient-rolling-stats
• For an application in Go, please see https://github.com/notnot/movingminmax
• Another C++ library: STL Monotonic Wedge https://github.com/EvanBalster/STL_mono_wedge