GCMF: A Reference Implementation of General-Purpose Compression via Mathematical Functions

GCMF is a reference encoder and decoder for the General-Purpose Compression via Mathematical Functions lossless format, specified in the Internet-Draft draft-dutta-gcmf-01,which represents a numeric sequence as a compact mathematical function plus a smalldomain descriptor rather than as raw bytes. The reference implementation covers the specification’s LITERAL, predefined-function, CUSTOM (a full 32-opcode bytecode virtual machinewith an automated, bounded-search encoder), and MODULAR representations. It is writtenin dependency-free Python 3, is tested with an automated suite of 34 unit and round-triptests plus a 1,500-trial randomized fuzz run, and is intended for reuse by researchers inminimum-description-length modeling, symbolic regression, and structured-data archival.

Authors

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-09-12
DOI
https://doi.org/10.5281/zenodo.22724280
Primary Topic
Algorithms and Data Compression
Type
preprint
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
preprint

GCMF: A Reference Implementation of General-Purpose Compression via Mathematical Functions

Srijal Dutta
Zenodo (CERN European Organization for Nuclear Research)
Algorithms and Data Compression
preprint

GCMF: A Reference Implementation of General-Purpose Compression via Mathematical Functions

Srijal Dutta
preprint en

Abstract

GCMF is a reference encoder and decoder for the General-Purpose Compression via Mathematical Functions lossless format, specified in the Internet-Draft draft-dutta-gcmf-01,which represents a numeric sequence as a compact mathematical function plus a smalldomain descriptor rather than as raw bytes. The reference implementation covers the specification’s LITERAL, predefined-function, CUSTOM (a full 32-opcode bytecode virtual machinewith an automated, bounded-search encoder), and MODULAR representations. It is writtenin dependency-free Python 3, is tested with an automated suite of 34 unit and round-triptests plus a 1,500-trial randomized fuzz run, and is intended for reuse by researchers inminimum-description-length modeling, symbolic regression, and structured-data archival.

Zenodo (CERN European Organization for Nuclear Research)
Shree Guru Gobind Singh Tricentenary University (IN)
Algorithms and Data Compression
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.