https://github.com/axsk/innocentmotmo
Scripts for the analysis of the innocent agent rates from the MoTMo model.
https://github.com/axsk/innocentmotmo
ajc pcca visualization zib
Last synced: 3 months ago
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Scripts for the analysis of the innocent agent rates from the MoTMo model.
- Host: GitHub
- URL: https://github.com/axsk/innocentmotmo
- Owner: axsk
- Created: 2023-08-29T14:46:19.000Z (almost 3 years ago)
- Default Branch: main
- Last Pushed: 2023-08-29T15:03:31.000Z (almost 3 years ago)
- Last Synced: 2024-03-24T06:10:17.205Z (about 2 years ago)
- Topics: ajc, pcca, visualization, zib
- Language: Julia
- Homepage:
- Size: 18.6 KB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# InnocentMoTMo
Scripts for the analysis of the innocent agent rates from the MoTMo model.
Application of the Augmented Jump Chain (AJC), PCCA+ and the shortest path problem to extract the most likely transition path between metastable clusters in a nonautonomous setting.
# Contents
- `clusterQtxt.jl`: read the sparse single timestep matrix `ratesStep01.txt` and compute the Schur/PCCA $\chi$ function
- `plot.jl`: Visualization of the 4-dimensional $\chi$ function on the 3-simplex / tetrahedron.
- `shortestpath.jl`: Compute the most likely (shortest in inverse rates) path between two clusters / vertices.
- `presentation.jl`: Reconstruct the plot from the presentation (transition paths of the AJC).
# Installation
- Besides the packages in the `Project.toml` it requires the non-published [PCCA.jl](https://github.com/axsk/PCCA.jl): \
`using Pkg; Pkg.add("https://github.com/axsk/PCCA.jl")`
- Also, depending on the usage it requires the whole AJC matrix `Q_matrix.mat` and `chi4.mat` or the single timestep rate matrix `ratesStep01.txt`.