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.
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
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.
- 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