fcmconfr
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Repository
Basic Info
- Host: GitHub
- Owner: bhroston
- License: gpl-3.0
- Language: R
- Default Branch: main
- Homepage: https://bhroston.github.io/fcmconfr/
- Size: 10.1 MB
Statistics
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 1
- Releases: 6
Created about 2 years ago
· Last pushed 11 months ago
Metadata Files
Readme
Changelog
Contributing
License
Citation
Codemeta
README.Rmd
---
output: github_document
# output: rmarkdown::pdf_document
---
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
```
# fcmconfr 
[](https://www.repostatus.org/#wip) [](https://codecov.io/gh/bhroston/fcmconfr) [](https://github.com/bhroston/fcmconfr.git/actions?query=workflow%3Apkgcheck) [](https://github.com/bhroston/fcmconfr/actions/workflows/R-CMD-check.yaml) [](https://www.gnu.org/licenses/gpl-3.0) [](https://dl.circleci.com/status-badge/redirect/circleci/6RNT3swTFpzTbGeainwSv6/SKx6MdvSmGtHet5jY8bLfs/tree/main)
`fcmconfr` (pronounced "FCM Confer") streamlines the process of conducting dynamic simulations using Fuzzy Cognitive Maps (FCMs). The package supports multiple FCM types (conventional, Interval-Value Fuzzy Number (IVFN) and Triangular Fuzzy Number (TFN)) and provides tools for model aggregation and the propagation of uncertainty from individual FCMs through to the aggregate.
`fcmconfr` includes a variety of supporting functions that make working with FCMs easier, including functions for creating IVFN and TFN adjacency matrices from standard .xlsx and .csv files, functions for stramlining parameter selection to facilitate model convergence, and functions for visualizing FCM networks and simulation outputs. The package was developed with a strong focus on accessibility (ease-of-use) and features both an interactive GUI and standard function commands.
## Installation
Users can install the development version of `fcmconfr` from [GitHub](https://github.com/) with:
``` r
# install.packages("pak")
pak::pak("bhroston/fcmconfr")
# Or
remotes::install_github("bhroston/fcmconfr")
```
Note: `fcmconfr` requires the following packages for GUI-based functions: visNetwork, shiny, shinyWidgets, bslib.
## Example
A typical `fcmconfr` workflow includes the following four steps:
1. Import FCMs
2. Set simulation parameters using `fcmconfr_gui()`
3. Run simulations using `fcmconfr()`
4. Explore outputs using `get_inferences()` and `plot()`
See `vignette("fcmconfr", package = "fcmconfr")` for a detailed description of each step.
### 1. Import FCMs
FCMs are matrix objects that can be imported into R using `readxl::read_excel()` and `read.csv()`. The best approach for importing an FCM into R depends on the type of FCM being imported.
See `vignette("Importing_FCMs", package = "fcmconfr")` for a detailed guide on importing different FCM types, including conventional FCMs, FCMs with edge weights represented as IVFNs (IVFN-FCMs), and FCMs with edge weights represented as TFNs (TFN-FCMs).
### 2. Set Simulation Parameters using `fcmconfr_gui()`
`fcmconfr()` is the central function of the package and requires specifying many parameters. To guide users through that process, the package procides an easy to use GUI that can be accessed by `fcmconfr_gui()`.
::: {style="text-align: center;"}
{width="70%"}
:::
Calling `fcmconfr_gui()` launches a Shiny app that lets users interactively select parameters and outputs a corresponding call to `fcmconfr()` that users can copy-and-paste to run in their own scripts.
A brief summary of each parameter within the `fcmconfr_gui()` is provided in a glossary stored in a side tab within the GUI. The side tab can be opened by clicking the arrow symbol in the top-right-hand-corner of the GUI.
### 3. Run Simulations using `fcmconfr()`
To run `fcmconfr()`, execute the output script created by \`fcmconfr_gui(). The following call uses an example FCM from the `sample_fcms` data included in the package.
```{r eval=FALSE}
# This call to fcmconfr() was generated from fcmconfr_gui()!
# Store the output in a variable to explore it later
fcmconfr_obj <- fcmconfr(
adj_matrices = sample_fcms$simple_fcms$conventional_fcms,
# Aggregation and Monte Carlo Sampling
agg_function = 'mean',
num_mc_fcms = 1000,
# Simulation
initial_state_vector = c(1, 1, 1, 1, 1, 1, 1),
clamping_vector = c(1, 0, 0, 0, 0, 0, 0),
activation = 'rescale',
squashing = 'sigmoid',
lambda = 1,
point_of_inference = 'final',
max_iter = 100,
min_error = 1e-05,
# Inference Estimation (bootstrap)
ci_centering_function = 'mean',
confidence_interval = 0.95,
num_ci_bootstraps = 1000,
# Runtime Options
show_progress = TRUE,
parallel = TRUE,
n_cores = 2,
# Additional Options
run_agg_calcs = TRUE,
run_mc_calcs = TRUE,
run_ci_calcs = TRUE,
include_zeroes_in_sampling = FALSE,
include_sims_in_output = FALSE
)
```
### 4. Explore `fcmconfr()` Results
`fcmconfr()` generates a large object with many concepts, the most important of which are simulation inferences (individual, aggregate, Monte Carlo). Inferences indicate how much each node in an FCM is influenced by a particular change or action. The `get_inferences()` function gives users access to that data without having to interact with the `fcmconfr()` object directly.
```{r eval=FALSE}
fcmconfr_inferences <- get_inferences(fcmconfr_obj)
```
A plot of all inferences can be generated using `plot()`. Documentation for `plot()` can be accessed via `?plot.fcmconfr` (`?plot` *returns the documentation for the Base R version of the function*).
```{r eval=FALSE}
plot(fcmconfr_obj)
```
::: {style="text-align: center;"}
{width="90%"}
:::
## Related Packages
- [MentalModeler](https://www.mentalmodeler.com/) is a web-based platform to build FCMs with features for "what-if" analysis.
- [`fcm`](https://cran.r-project.org/web/packages/fcm/index.html) is an R package that includes functions for simulating individual conventional FCMs.
- [`InCognitive`](https://github.com/ThemisKoutsellis/InCognitive) is a Python package that for simulating conventional FCMs with lambda optimization and Monte Carlo analysis.
- [`FCMpy`](https://github.com/SamvelMK/FCMpy) is a Python package that supports translation of linguistic terms to quantitative edge weights, FCM simulation and genetic learning algorithms.
- [`PyFCM`](https://github.com/payamaminpour/PyFCM) is a Python package that includes functions for FCM simulation and aggregation.
- [`jFCM`](https://github.com/megadix/jfcm?tab=readme-ov-file) is a java-based suite of functions to simulate FCMs.
## Contributing
Please note that this package is released with a [Contributor Code of Conduct](https://ropensci.org/code-of-conduct/). By contributing to this project, you agree to abide by its terms.
- If you think you have encountered a bug, please [submit an issue](https://github.com/bhroston/fcmconfr/issues).
- Please include a [reprex](https://reprex.tidyverse.org/articles/articles/learn-reprex.html) (a minimal, reproducible example) to clearly communicate about your code.
Owner
- Name: benroston
- Login: bhroston
- Kind: user
- Repositories: 1
- Profile: https://github.com/bhroston
Citation (CITATION.cff)
# --------------------------------------------
# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
# --------------------------------------------
cff-version: 1.2.0
message: 'To cite package "fcmconfr" in publications use:'
type: software
license: GPL-3.0-or-later
title: 'fcmconfr: Fuzzy Cognitive Map Analysis in R'
version: 0.2.3
abstract: fcmconfr streamlines the process of conducting dynamic simulations using
Fuzzy Cognitive Maps (FCMs). The package supports multiple FCM types (conventional,
Interval-Value Fuzzy Number (IVFN) and Triangular Fuzzy Number (TFN)) and provides
tools for model aggregation and the propagation of uncertainty from individual FCMs
through to the aggregate.
authors:
- family-names: Roston
given-names: Ben
email: bhroston@vt.edu
orcid: https://orcid.org/0000-0001-9201-7579
- family-names: Rippy
given-names: Meg
email: mrippy@vt.edu
orcid: https://orcid.org/0000-0002-0575-8342
repository-code: https://github.com/bhroston/fcmconfr
url: https://github.com/bhroston/fcmconfr
contact:
- family-names: Roston
given-names: Ben
email: bhroston@vt.edu
orcid: https://orcid.org/0000-0001-9201-7579
references:
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title: covr
abstract: 'covr: Test Coverage for Packages'
notes: Suggests
url: https://covr.r-lib.org
repository: https://CRAN.R-project.org/package=covr
authors:
- family-names: Hester
given-names: Jim
email: james.f.hester@gmail.com
year: '2025'
doi: 10.32614/CRAN.package.covr
version: '>= 3.6.4'
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title: knitr
abstract: 'knitr: A General-Purpose Package for Dynamic Report Generation in R'
notes: Suggests
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authors:
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given-names: Yihui
email: xie@yihui.name
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year: '2025'
doi: 10.32614/CRAN.package.knitr
version: '>= 1.44'
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title: rmarkdown
abstract: 'rmarkdown: Dynamic Documents for R'
notes: Suggests
url: https://pkgs.rstudio.com/rmarkdown/
repository: https://CRAN.R-project.org/package=rmarkdown
authors:
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given-names: JJ
email: jj@posit.co
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email: xie@yihui.name
orcid: https://orcid.org/0000-0003-0645-5666
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email: cderv@posit.co
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given-names: Richard
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year: '2025'
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version: '>= 2.25'
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abstract: 'testthat: Unit Testing for R'
notes: Suggests
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notes: Suggests
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email: kirill@cynkra.com
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notes: Suggests
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institution:
name: R Foundation for Statistical Computing
address: Vienna, Austria
year: '2025'
version: '>= 4.3.2'
- type: software
title: vdiffr
abstract: 'vdiffr: Visual Regression Testing and Graphical Diffing'
notes: Suggests
url: https://vdiffr.r-lib.org/
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authors:
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email: lionel@posit.co
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- family-names: Csárdi
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repository: https://CRAN.R-project.org/package=checkmate
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given-names: Michel
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abstract: 'R: A Language and Environment for Statistical Computing'
notes: Imports
authors:
- name: R Core Team
institution:
name: R Foundation for Statistical Computing
address: Vienna, Austria
year: '2025'
version: '>= 4.2.1'
- type: software
title: stats
abstract: 'R: A Language and Environment for Statistical Computing'
notes: Imports
authors:
- name: R Core Team
institution:
name: R Foundation for Statistical Computing
address: Vienna, Austria
year: '2025'
version: '>= 4.2.1'
- type: software
title: parallel
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notes: Imports
authors:
- name: R Core Team
institution:
name: R Foundation for Statistical Computing
address: Vienna, Austria
year: '2025'
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notes: Imports
url: https://github.com/psolymos/pbapply
repository: https://CRAN.R-project.org/package=pbapply
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given-names: Stefan Milton
email: stefan@stefanbache.dk
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abstract: 'tidyr: Tidy Messy Data'
notes: Imports
url: https://tidyr.tidyverse.org
repository: https://CRAN.R-project.org/package=tidyr
authors:
- family-names: Wickham
given-names: Hadley
email: hadley@posit.co
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notes: Imports
url: https://ggplot2.tidyverse.org
repository: https://CRAN.R-project.org/package=ggplot2
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- family-names: Pedersen
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orcid: https://orcid.org/0000-0002-3385-7233
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version: '>= 3.4.2'
- type: software
title: igraph
abstract: 'igraph: Network Analysis and Visualization'
notes: Imports
url: https://r.igraph.org/
repository: https://CRAN.R-project.org/package=igraph
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given-names: Gábor
email: csardi.gabor@gmail.com
orcid: https://orcid.org/0000-0001-7098-9676
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given-names: Tamás
email: ntamas@gmail.com
orcid: https://orcid.org/0000-0002-1451-338X
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orcid: https://orcid.org/0000-0003-3170-3879
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email: fabio.zanini@unsw.edu.au
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version: '>= 1.5.1'
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title: visNetwork
abstract: 'visNetwork: Network Visualization using ''vis.js'' Library'
notes: Imports
url: https://datastorm-open.github.io/visNetwork/
repository: https://CRAN.R-project.org/package=visNetwork
authors:
- name: Almende B.V. and Contributors
website: https://visjs.org/
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given-names: Benoit
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notes: Imports
url: https://shiny.posit.co/
repository: https://CRAN.R-project.org/package=shiny
authors:
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email: winston@posit.co
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year: '2025'
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version: '>= 1.7.5'
- type: software
title: shinyWidgets
abstract: 'shinyWidgets: Custom Inputs Widgets for Shiny'
notes: Imports
url: https://dreamrs.github.io/shinyWidgets/
repository: https://CRAN.R-project.org/package=shinyWidgets
authors:
- family-names: Perrier
given-names: Victor
email: victor.perrier@dreamrs.fr
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- type: software
title: bslib
abstract: 'bslib: Custom ''Bootstrap'' ''Sass'' Themes for ''shiny'' and ''rmarkdown'''
notes: Imports
url: https://rstudio.github.io/bslib/
repository: https://CRAN.R-project.org/package=bslib
authors:
- family-names: Sievert
given-names: Carson
email: carson@posit.co
orcid: https://orcid.org/0000-0002-4958-2844
- family-names: Cheng
given-names: Joe
email: joe@posit.co
- family-names: Aden-Buie
given-names: Garrick
email: garrick@posit.co
orcid: https://orcid.org/0000-0002-7111-0077
year: '2025'
doi: 10.32614/CRAN.package.bslib
version: '>= 0.8.0'
- type: software
title: 'R: A Language and Environment for Statistical Computing'
notes: Depends
url: https://www.R-project.org/
authors:
- name: R Core Team
institution:
name: R Foundation for Statistical Computing
address: Vienna, Austria
year: '2025'
version: '>= 2.10'
CodeMeta (codemeta.json)
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"identifier": "fcmconfr",
"description": "Create and analyse fuzzy cognitive maps.",
"name": "fcmconfr: Fuzzy Cognitive Map Analysis in R",
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"version": "0.2.3",
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}GitHub Events
Total
- Create event: 7
- Release event: 1
- Issues event: 14
- Watch event: 2
- Delete event: 11
- Issue comment event: 13
- Public event: 2
- Push event: 158
- Gollum event: 1
- Pull request event: 44
Last Year
- Create event: 7
- Release event: 1
- Issues event: 14
- Watch event: 2
- Delete event: 11
- Issue comment event: 13
- Public event: 2
- Push event: 158
- Gollum event: 1
- Pull request event: 44
Issues and Pull Requests
Last synced: 6 months ago
All Time
- Total issues: 9
- Total pull requests: 22
- Average time to close issues: 26 days
- Average time to close pull requests: about 3 hours
- Total issue authors: 2
- Total pull request authors: 1
- Average comments per issue: 0.89
- Average comments per pull request: 0.0
- Merged pull requests: 20
- Bot issues: 2
- Bot pull requests: 0
Past Year
- Issues: 9
- Pull requests: 22
- Average time to close issues: 26 days
- Average time to close pull requests: about 3 hours
- Issue authors: 2
- Pull request authors: 1
- Average comments per issue: 0.89
- Average comments per pull request: 0.0
- Merged pull requests: 20
- Bot issues: 2
- Bot pull requests: 0
Top Authors
Issue Authors
- bhroston (8)
- github-actions[bot] (3)
Pull Request Authors
- bhroston (23)
Top Labels
Issue Labels
Pull Request Labels
Dependencies
.github/workflows/check-standard.yaml
actions
- actions/checkout v3 composite
- r-lib/actions/check-r-package v2 composite
- r-lib/actions/setup-pandoc v2 composite
- r-lib/actions/setup-r v2 composite
- r-lib/actions/setup-r-dependencies v2 composite
.github/workflows/pkgcheck.yaml
actions
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.github/workflows/pkgdown.yaml
actions
- JamesIves/github-pages-deploy-action v4.5.0 composite
- actions/checkout v4 composite
- r-lib/actions/setup-pandoc v2 composite
- r-lib/actions/setup-r v2 composite
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.github/workflows/pr-commands.yaml
actions
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- r-lib/actions/pr-fetch v2 composite
- r-lib/actions/pr-push v2 composite
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.github/workflows/test-coverage.yaml
actions
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- codecov/codecov-action v4 composite
- r-lib/actions/setup-r v2 composite
- r-lib/actions/setup-r-dependencies v2 composite
DESCRIPTION
cran
- R >= 2.10 depends
- Matrix >= 1.6.1.1 imports
- Rdpack >= 2.6.1 imports
- bslib >= 0.8.0 imports
- data.table >= 1.15.4 imports
- doSNOW >= 1.0.20 imports
- foreach >= 1.5.2 imports
- ggplot2 >= 3.4.2 imports
- methods >= 4.3.2 imports
- parallel >= 4.3.2 imports
- pbapply >= 1.7.2 imports
- shiny >= 1.7.5 imports
- shinyWidgets >= 0.8.7 imports
- stats >= 4.3.2 imports
- tibble >= 3.2.1 imports
- tidyr >= 1.3.0 imports
- utils >= 4.3.2 imports
- covr >= 3.6.4 suggests
- knitr >= 1.44 suggests
- rmarkdown >= 2.25 suggests
- testthat >= 3.0.0 suggests