gmn · PyPI

Generative Manifold Networks (GMN)

Generative Manifold Networks is a generalization of nonlinear dynamical systems from a single state-space with a manifold operator, to an interconnected network of operators on the state-space(s) see: Park et al.

GMN is developed at the Biological Nonlinear Dynamics Data Science Unit, OIST

Installation

Python Package Index (PyPI) gmn.

pip install gmn

Documentation

GMN documentation.

Usage

Example usage at the python prompt in directory gmn/config:

>>> import gmn
>>> G = gmn.GMN( configFile = './default.cfg' )
>>> G.Generate()
>>> G.DataOut.tail()
     Time       A       C       D         B       Out
295   996 -0.2487 -0.5018  0.7500  0.985236 -0.979370
296   997 -0.1874 -0.4708  0.7937  0.985842 -0.991504
297   998 -0.1253 -0.4248  0.8177  0.965066 -0.973041
298   999 -0.0628 -0.3671  0.8224  0.923630 -0.931681
299  1000  0.0000 -0.3016  0.8090  0.862222 -0.871642

References

Experimentally testable whole brain manifolds that recapitulate behavior

Explainable prediction and simulation of complex system dynamics through networks of manifolds

Release files for gmn 2.0.1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for gmn 2.0.1
File	Size	Uploaded
gmn-2.0.1.tar.gz	191.2 kB	Aug 25, 2026	Details

Built distribution (wheel)

Table of built distributions (wheels) for gmn 2.0.1
File	Interpreter	ABI	Platform	Reset
gmn-2.0.1-py3-none-any.whl 185.2 kB Aug 25, 2026	Python 3	none	any	Details

Total release size: 376.4 kB

Release files / gmn-2.0.1.tar.gz

Download URL	gmn-2.0.1.tar.gz
Size	191.2 kB
Tags	Source
SHA-256 checksum How to use checksums	`add63bc0dbd5b445d825c861b58cad0230741b9801fdcfa04766d7bd276c0d98`
BLAKE2b-256 checksum How to use checksums	`069f08a14a5955cdaabbc7b4fc06610795d25b0c4715202ba867408ef458e7fe`
Upload date	Aug 25, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/6.1.0 CPython/3.13.6`

Release files / gmn-2.0.1-py3-none-any.whl

Download URL	gmn-2.0.1-py3-none-any.whl
Size	185.2 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`adb5086636a03b96d2a24369ac724abeb25a2b641e60d16af923ed365cf1869f`
BLAKE2b-256 checksum How to use checksums	`736cb9accfc470488792d3dd834bb7bec91e76541cb495c1f5b231a0984d7517`
Upload date	Aug 25, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/6.1.0 CPython/3.13.6`