Construct a non-contiguous area cartogram (Olson 1976).
Usage
cartogram_ncont(
x,
weight,
k = 1,
inplace = TRUE,
n_cpu = "respect_future_plan",
show_progress = TRUE
)
# S3 method for class 'SpatialPolygonsDataFrame'
cartogram_ncont(
x,
weight,
k = 1,
inplace = TRUE,
n_cpu = "respect_future_plan",
show_progress = TRUE
)
# S3 method for class 'sf'
cartogram_ncont(
x,
weight,
k = 1,
inplace = TRUE,
n_cpu = "respect_future_plan",
show_progress = TRUE
)Arguments
- x
a polygon or multiplogyon sf object
- weight
Name of the weighting variable in x
- k
Factor expansion for the unit with the greater value
- inplace
If TRUE, each polygon is modified in its original place, if FALSE multi-polygons are centered on their initial centroid
- n_cpu
Number of cores to use. Defaults to "respect_future_plan". Available options are: * "respect_future_plan" - By default, the function will run on a single core, unless the user specifies the number of cores using
plan(e.g. `future::plan(future::multisession, workers = 4)`) before running the `cartogram_ncont` function. * "auto" - Use all except available cores (identified withavailableCores) except 1, to keep the system responsive. * a `numeric` value - Use the specified number of cores. In this case `cartogram_ncont` will use set the specified number of cores internally with `future::plan(future::multisession, workers = n_cpu)` and revert that back by switching the plan back to whichever plan might have been set before by the user. If only 1 core is set, the function will not require `future` and `future.apply` and will run on a single core.- show_progress
A `logical` value. If TRUE, show progress bar. Defaults to TRUE.
References
Olson, J. M. (1976). Noncontiguous Area Cartograms. In The Professional Geographer, 28(4), 371-380.
Examples
# ========= Basic example =========
library(sf)
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_ncont(nc_utm, weight = "BIR74")
#>
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# Plot
par(mfrow=c(2,1))
plot(nc[,"BIR74"], main="original", key.pos = NULL, reset = FALSE)
plot(st_geometry(nc_utm), main="distorted", reset = FALSE)
plot(nc_utm_carto[,"BIR74"], add =TRUE)
# ========= Advanced example 1 =========
# Faster cartogram using multiple CPU cores
# using n_cpu parameter
library(sf)
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 using 2 CPU cores on local machine
nc_utm_carto <- cartogram_ncont(nc_utm, weight = "BIR74", n_cpu = 2)
#> Error in globalCallingHandlers(condition = global_progression_handler): should not be called with handlers on the stack
# Plot
par(mfrow=c(2,1))
plot(nc[,"BIR74"], main="original", key.pos = NULL, reset = FALSE)
plot(st_geometry(nc_utm), main="distorted", reset = FALSE)
plot(nc_utm_carto[,"BIR74"], add =TRUE)
# ========= Advanced example 2 =========
# Faster cartogram using multiple CPU cores
# using future package plan
library(sf)
library(cartogram)
library(future)
nc = st_read(system.file("shape/nc.shp", package="sf"), quiet = TRUE)
# transform to NAD83 / UTM zone 16N
nc_utm <- st_transform(nc, 26916)
# Set the future plan with 2 CPU local cores
# You can of course use any other plans, not just multisession
future::plan(future::multisession, workers = 2)
# Create cartogram with multiple CPU cores
# The cartogram_cont() will respect the plan set above
nc_utm_carto <- cartogram_ncont(nc_utm, weight = "BIR74")
#> Error in globalCallingHandlers(condition = global_progression_handler): should not be called with handlers on the stack
# Shutdown the R processes that were created by the future plan
future::plan(future::sequential)
# Plot
par(mfrow=c(2,1))
plot(nc[,"BIR74"], main="original", key.pos = NULL, reset = FALSE)
plot(st_geometry(nc_utm), main="distorted", reset = FALSE)
plot(nc_utm_carto[,"BIR74"], add =TRUE)
