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potential <img src="man/figures/logo.png" align="right" width="140"/>

R-CMD-check codecov Project Status: Active – The project has reached a stable, usable
state and is being actively
developed.

This package provides functions to compute the potential model as defined by Stewart (1941). Several options are available to customize the model, for example it is possible to fine-tune the distance friction functions or to use custom distance matrices. Some computations are parallelized to improve their efficiency.

Installation

You can install the released version of potential from CRAN with:

install.packages("potential")

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

# install.packages("remotes")
remotes::install_github("riatelab/potential")

Demo

library(mapsf)
library(potential)
# Display the spatial interaction function
plot_inter(fun = "e", span = 75000, beta = 2, limit = 250000)

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# create a regular grid
y <- create_grid(x = n3_poly, res = 20000)
# compute potentials
pot <- mcpotential(
  x = n3_pt, y = y,
  var = "POP19",
  fun = "e", span = 75000,
  beta = 2, limit = 250000, 
  ncl = 2
)
# Define potential according to the maximum value
y$pot <- pot / max(pot) * 100
# create equipotential areas
bks <- seq(0, 100, length.out = 11)
equipot <- equipotential(y, var = "pot", breaks = bks, mask = n3_poly)
# map potentials
mf_theme("default")
mf_map(x = equipot, var = "min", type = "choro", 
       breaks = bks, 
       pal = hcl.colors(10, 'Teal'),
       border = "#121725", 
       leg_val_rnd = 0,
       lwd = .2, 
       leg_pos = "topright", 
       leg_title = "Potential Intensity")
mf_title(txt = "Potentials of Population")
mf_credits(txt = "© EuroGeographics for the administrative boundaries and © Eurostat for data")

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Note

This package provides access to the revamped potential-related functions initially offered by SpatialPosition.

References

<div id="refs" class="references csl-bib-body hanging-indent"> <div id="ref-STEWART41" class="csl-entry">

Stewart, John Q. 1941. “An Inverse Distance Variation for Certain Social Influences.” Science 93 (2404): 89–90. https://doi.org/10.1126/science.93.2404.89.

</div> </div>