simlandr provides a set of tools for constructing potential landscape for dynamic systems using Monte-Carlo simulation, especially for psychological formal models. It can help to:

1. Run batch simulations for different parameter values;
2. Store large simulation outputs into hard drive by the reusable hash_big.matrix class, and perform out-of-memory calculation;
3. Check convergence of the simulations;
4. Construct 2d, 3d, 4d potential landscapes based on the simulation outputs;
5. Calculate the minimal energy path and barrier height for transitions between states.

## Installation

You can install the development version from GitHub with:

install.packages("devtools")
devtools::install_github("Sciurus365/simlandr")
devtools::install_github("Sciurus365/simlandr", build_vignettes = TRUE) # Use this command if you want to build vignettes

## Example

library(simlandr)

# Simulation

## Single simulation

## Batch simulation: simulate a set of models with different parameter values
arg_name = "parameter", ele_name = "a",
start = -6, end = -1, by = 1
)
default_list = list(
initial = list(x = 0, y = 0),
parameter = list(a = -4, b = 0, c = 0, sigmasq = 1)
),
length = 1e4,
seed = 1614,
bigmemory = FALSE
)

#> Output(s) from 6 simulations.

# Construct landscapes

## Example 1. 2D landscape
x = "x",
from = -2, to = 2, adjust = 2
)
plot(l_single_grad_2d)

## Example 2. 3D (x, y, color) plot matrix with two varying parameters
x = "x", y = "y",
lims = c(-2, 2, -2, 2), h = 0.05,
kde_fun = "ks"
)
#> Calculating the smooth distribution...
#> Done!
#> Making the plot...
#> Done!
#> Making the 2d plot...
#> Done!
plot(l_single_grad_3d, 2)

# Calculate energy barriers
## Example 1. Energy barrier for the 2D landscape
start_location_value = -1, end_location_value = 1,
start_r = 0.3, end_r = 0.3
)
#> delta_U_start   delta_U_end
#>      1.877958      1.771488

plot(l_single_grad_2d) + get_geom(b_single_grad_2d)

## Example 2. Energy barrier for the 3D landscape
plot(l_single_grad_3d, 2) + get_geom(b_single_grad_3d)
See the vignettes of this package (browseVignettes("simlandr")) for more examples and explanations.