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https://github.com/jandraor/readsdr
Translate System Dynamics models (Stella, Vensim) into R
https://github.com/jandraor/readsdr
r stan system-dynamics
Last synced: 3 months ago
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Translate System Dynamics models (Stella, Vensim) into R
- Host: GitHub
- URL: https://github.com/jandraor/readsdr
- Owner: jandraor
- License: other
- Created: 2019-08-29T15:15:30.000Z (about 5 years ago)
- Default Branch: master
- Last Pushed: 2024-05-25T19:33:35.000Z (6 months ago)
- Last Synced: 2024-07-30T01:53:25.114Z (3 months ago)
- Topics: r, stan, system-dynamics
- Language: R
- Homepage:
- Size: 592 KB
- Stars: 16
- Watchers: 6
- Forks: 5
- Open Issues: 2
-
Metadata Files:
- Readme: README.Rmd
- License: LICENSE
Awesome Lists containing this project
README
---
output: github_document
---
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
```
# readsdr
[](https://app.codecov.io/gh/jandraor/readsdr?branch=master)
[](https://CRAN.R-project.org/package=readsdr)
[](https://github.com/jandraor/readsdr/actions/workflows/R-CMD-check.yaml)
## Overview
The goal of readsdr is to bridge the design capabilities from specialised
System Dynamics software with the powerful numerical tools offered by R
libraries. The package accomplishes this goal by parsing .xmile files
(Vensim and [Stella](https://www.iseesystems.com/) models) into R objects to
construct [networks](https://igraph.org) (graph theory), ODE functions for
[deSolve](http://desolve.r-forge.r-project.org/) and
[Stan](https://mc-stan.org/).
## Installation
You can install the released version of readsdr from [CRAN](https://CRAN.R-project.org) with:
``` r
install.packages("readsdr")
```
And the development version from [GitHub](https://github.com/) with:
``` r
# install.packages("devtools")
devtools::install_github("jandraor/readsdr")
```
## Usage
```{r example}
library(readsdr)
filepath <- system.file("models/", "SIR.stmx", package = "readsdr")
mdl <- read_xmile(filepath)
```
Vensim models can only be read if they are exported in the .xmile format.
Sometimes, Vensim .xmile files can be problematic, where **some stocks may not
have flows**, and flow equations are put as initial values. One way to address
this issue is by copying the .mdl file to a different folder and exporting the
.xmile file again. If you encounter this issue, please let the developers know
at Vensim's [forum](https://www.ventanasystems.co.uk/forum).
## Tutorials
For information on how to use this package, please check:
* [Basics](https://jandraor.github.io/tutorials/Basics.html)
* [Inference](https://jandraor.github.io/tutorials/Inference.html)
## Supported builtins
* **Stella**
+ Comparison operators (`=`, `<>`)
+ Logical operators (`AND`, `OR`, `NOT`)
+ `If Else Then`
+ Inequality operators (`<`, `>`)
+ `Pulse` ^1^
+ `Step` ^1^
+ Endogenous table functions
+ Smoothing functions^2^: `SMTH1`, `SMTH3`, `SMTHN`
+ Delay functions: `DELAYN`
+ Limited support to *uni-dimensional* arrays. *Apply all* translation is restricted to numeric values.
+ Math functions: `ABS`, `EXP`, `SQRT`
+ Stats functions: `NORMAL`^3^
* **Vensim**
+ Comparison operators (`=`, `<>`)
+ Logical operators (`:AND:`, `:OR:`, `:NOT:`)
+ `IF_THEN_ELSE`
+ Inequality operators (`<`, `>`)
+ `Pulse` ^1^
+ `Pulse Train` ^1^
+ `Step` ^1^
+ Endogenous table functions
+ Smoothing functions^2^: `SMOOTH`, `SMOOTH3`, `SMOOTH3I`, `SMOOTHI`
+ Delay functions: `DELAY N`
+ Math functions: `ABS`, `EXP`, `SQRT`
+ Limited support to *bi-dimensional* arrays.
+ Stats functions: `RANDOM NORMAL`^3^
^1^ Restricted to Euler integration.
^2^ These functions cannot be part of more complex mathematical expressions. That is, the auxiliary variable must only contain one smoothing function and **nothing else**.
^3^ Seed is ignored.
## Notes
* *uniflow* and *non-negative* stock features from _Stella_ are **not** supported.
* No built-in is supported for translations to _Stan_ code.
* Modules from _Stella_ are **not** supported.
## Applications
This package has been instrumental in the following works:
* [Andrade et al (2024)](https://doi.org/10.1002/sdr.1775). _Preparing for pandemic response in the context of limited resources_. **System Dynamics Review**.
* [Andrade & Duggan (2023)](https://doi.org/10.1098/rsos.230515). _Anchoring the mean generation time in the SEIR to mitigate biases in_ $\Re_0$ _estimates due to uncertainty in the distribution of the epidemiological delays_. **Royal Society Open Science**.
* [Andrade & Duggan (2022)](https://doi.org/10.1371/journal.pcbi.1010206). _Inferring the effective reproductive number from deterministic and semi-deterministic compartmental models using incidence and mobility data_. **PLOS Computational Biology**.
* [Andrade & Duggan (2021)](https://doi.org/10.1002/sdr.1693). _A Bayesian approach to calibrate system dynamics models using Hamiltonian Monte Carlo_. **System Dynamics Review**.
* [Andrade & Duggan (2020)](https://doi.org/10.1016/j.epidem.2020.100415). _An evaluation of Hamiltonian Monte Carlo performance to calibrate age-structured compartmental SEIR models to incidence data_. **Epidemics**.
## Acknowledgments
Thanks to:
* [Rogelio Oliva](http://people.tamu.edu/~roliva/) for advocating the need to
create an open-source tool for the System Dynamics community and push forward
this endeavour.
* Sergey Naumov for his ideas to implement several functions in this package.
* [Jim Duggan](https://github.com/JimDuggan)
from whom I borrowed ideas to implement this package.
## References
[Duggan, J. (2016). *System Dynamics Modeling with R*. Springer.](https://link.springer.com/book/10.1007/978-3-319-34043-2)