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Construct a continuous area cartogram by a rubber sheet distortion algorithm (Dougenik et al. 1985)

Usage

cartogram_cont(
  x,
  weight,
  itermax = 15,
  maxSizeError = 1.0001,
  prepare = "adjust",
  threshold = 0.05,
  verbose = FALSE
)

# S3 method for SpatialPolygonsDataFrame
cartogram_cont(
  x,
  weight,
  itermax = 15,
  maxSizeError = 1.0001,
  prepare = "adjust",
  threshold = 0.05,
  verbose = FALSE
)

# S3 method for sf
cartogram_cont(
  x,
  weight,
  itermax = 15,
  maxSizeError = 1.0001,
  prepare = "adjust",
  threshold = 0.05,
  verbose = FALSE
)

Arguments

x

a polygon or multiplogyon sf object

weight

Name of the weighting variable in x

itermax

Maximum iterations for the cartogram transformation, if maxSizeError ist not reached

maxSizeError

Stop if meanSizeError is smaller than maxSizeError

prepare

Weighting values are adjusted to reach convergence much earlier. Possible methods are "adjust", adjust values to restrict the mass vector to the quantiles defined by threshold and 1-threshold (default), "remove", remove features with values lower than quantile at threshold, "none", don't adjust weighting values

threshold

Define threshold for data preparation

verbose

print meanSizeError on each iteration

Value

An object of the same class as x

References

Dougenik, J. A., Chrisman, N. R., & Niemeyer, D. R. (1985). An Algorithm To Construct Continuous Area Cartograms. In The Professional Geographer, 37(1), 75-81.

Examples

library(sf)
#> Linking to GEOS 3.10.2, GDAL 3.4.1, PROJ 8.2.1; sf_use_s2() is TRUE
library(cartogram)

nc = st_read(system.file("shape/nc.shp", package="sf"), quiet = TRUE)

# transform to NAD83 / UTM zone 16N
nc_utm <- st_transform(nc, 26916)

# Create cartogram
nc_utm_carto <- cartogram_cont(nc_utm, weight = "BIR74", itermax = 5)

# Plot 
par(mfrow=c(2,1))
plot(nc[,"BIR74"], main="original", key.pos = NULL, reset = FALSE)
plot(nc_utm_carto[,"BIR74"], main="distorted", key.pos = NULL, reset = FALSE)