`Isinglandr`: Landscape Construction and Simulation for Ising Networks

A toolbox for constructing potential landscapes for Ising networks. The parameters of the networks can be directly supplied by users or estimated by the IsingFit package by van Borkulo and Epskamp (2016) https://CRAN.R-project.org/package=IsingFit from empirical data. The Ising model’s Boltzmann distribution is preserved for the potential landscape function. The landscape functions can be used for quantifying and visualizing the stability of network states, as well as visualizing the simulation process.

Installation

You can install the development version of Isinglandr from GitHub with:

# install.packages("devtools")
devtools::install_github("Sciurus365/Isinglandr")

Example

Landscape construction

library(Isinglandr)
#> Registered S3 method overwritten by 'Isinglandr':
#>   method          from    
#>   print.landscape simlandr
#  A toy network and its landscape
Nvar <- 10
m <- rep(0, Nvar)
w <- matrix(0.1, Nvar, Nvar)
diag(w) <- 0

result1 <- make_2d_Isingland(m, w)
plot(result1)


## What if the network becomes denser?
result2 <- make_2d_Isingland(m, 1.5 * w)
plot(result2)


## What if the thresholds become lower?
result3 <- make_2d_Isingland(m - 0.5, w)
plot(result3)


## Multiple networks together
result4 <- make_Ising_grid(
  all_thresholds(seq(-0.1, 0.1, 0.1), .f = `+`),
  whole_weiadj(seq(0.5, 1.5, 0.5)),
  m, w
) %>% make_2d_Isingland_matrix()
plot(result4)
#> Scale for x is already present.
#> Adding another scale for x, which will replace the existing scale.

Simulation on landscapes

set.seed(1614)
sim1 <- simulate_Isingland(result1, initial = 5)
plot(sim1)


set.seed(1614)
sim4 <- simulate_Isingland(result4, initial = 5)
plot(sim4)

Shiny app