Title:	Thematic Cartography
Version:	3.1.4
Description:	Create and integrate maps in your R workflow. This package helps to design cartographic representations such as proportional symbols, choropleth, typology, flows or discontinuities maps. It also offers several features that improve the graphic presentation of maps, for instance, map palettes, layout elements (scale, north arrow, title...), labels or legends. See Giraud and Lambert (2017) <doi:10.1007/978-3-319-57336-6_13>.
License:	GPL-3
URL:	https://github.com/riatelab/cartography/
BugReports:	https://github.com/riatelab/cartography/issues/
LazyData:	true
Depends:	R (≥ 3.5.0)
Imports:	classInt, curl, graphics, methods, png, raster, Rcpp, sf, sp, stats, utils, grDevices
Suggests:	lwgeom, SpatialPosition, knitr, rmarkdown, tinytest, covr
LinkingTo:	Rcpp
VignetteBuilder:	knitr
Encoding:	UTF-8
RoxygenNote:	7.2.3
NeedsCompilation:	yes
Packaged:	2023-09-14 09:18:06 UTC; tim
Author:	Timothée Giraud [cre, aut], Nicolas Lambert [aut], Diego Hernangómez [ctb], Ian Fellows [cph] (no overlap algorithm for labels, from wordcloud package)
Maintainer:	Timothée Giraud <timothee.giraud@cnrs.fr>
Repository:	CRAN
Date/Publication:	2023-09-14 10:40:07 UTC

Cartography Package

Description

This package helps to design cartographic representations such as proportional symbols, choropleth, typology, flows or discontinuities maps. It also offers several features that improve the graphic presentation of maps, for instance, map palettes, layout elements (scale, north arrow, title...), labels or legends.

A vignette contains commented scripts on how to create various maps:
vignette(topic = "cartography", package = "cartography")
A cheat sheet displays a quick overview of cartography's main features:
vignette(topic = "cheatsheet" , package = "cartography")

Consider mapsf

There are no plans for new features or enhancements in cartography. Basic maintenance and support will continue indefinitely. Existing projects that use cartography can safely continue to use cartography. The mapsf R package is the successor of cartography and it is friendlier, lighter and more robust. See mapsf vignette (https://riatelab.github.io/mapsf/articles/mapsf.html) to migrate from cartography to mapsf.

Symbology

These functions build cartographic layers.

• Proportional symbols layer (propSymbolsLayer, propSymbolsChoroLayer, propSymbolsTypoLayer, propTrianglesLayer)

• Choropleth layer (choroLayer)

• Typology layer (typoLayer)

• Flows layer (propLinkLayer, gradLinkLayer, gradLinkTypoLayer)

• Discontinuities layer (discLayer)

• Access to cartographic OpenStreetMap APIs (tilesLayer)

• Dot density layer (tilesLayer)

• Labels layer (labelLayer)

• Smooth layer (smoothLayer)

• png layer (pngLayer)

• Hatched/pattern layer (hatchedLayer)

• Tag (or word) cloud layer (wordcloudLayer)

Transformations

These functions transform or create spatial objects.

• Extract polygons borders (getBorders, getOuterBorders)

• Build a regular grid layer (getGridLayer)

• Create a links layer from a data.frame of links (getLinkLayer)

• Create a png layer (getPngLayer)

• Create a pencil layer (getPencilLayer)

• Get tiles from OpenStreetMap servers (getTiles)

Map Layout

These functions are dedicated to the map layout design.

• Scale bar (barscale)

• Get figure dimensions (getFigDim)

• Layout layer (layoutLayer)

• North arrow (north)

Color Palettes

Use these function to build custom color palettes.

• Build cartographic palettes (carto.pal)

Legends

These functions create legends.

• Legends (legendBarsSymbols, legendChoro, legendCirclesSymbols, legendGradLines, legendPropLines, legendPropTriangles, legendSquaresSymbols, legendTypo, legendHatched)

Classification

This function uses classification methods for binning data.

• Classification (getBreaks)

Author(s)

Maintainer: Timothée Giraud timothee.giraud@cnrs.fr (ORCID)

Authors:

• Nicolas Lambert nicolas.lambert@cnrs.fr

Other contributors:

• Diego Hernangómez (ORCID) [contributor]

• Ian Fellows (no overlap algorithm for labels, from wordcloud package) [copyright holder]

See Also

Useful links:

• https://github.com/riatelab/cartography/

• Report bugs at https://github.com/riatelab/cartography/issues/

Scale Bar

Description

Plot a scale bar.

Usage

barscale(
  size,
  lwd = 1.5,
  cex = 0.6,
  pos = "bottomright",
  style = "pretty",
  unit = "km"
)

Arguments

Note

This scale bar is not accurate on unprojected (long/lat) maps.

See Also

layoutLayer

Examples

library(sf)
mtq <- st_read(system.file("gpkg/mtq.gpkg", package="cartography"))
plot(st_geometry(mtq), col = "grey60", border = "grey20")
barscale(size = 5)
barscale(size = 5, lwd = 2, cex = .9, pos = c(714000, 1596000))

Build Cartographic Palettes

Description

carto.pal builds sequential, diverging and qualitative color palettes. Diverging color palettes can be dissymmetric (different number of colors in each of the two gradients).

carto.pal.info displays the names of all color palettes.

display.carto.pal displays one color palette.

display.carto.all displays all the available color palettes.

Usage

carto.pal(
  pal1,
  n1,
  pal2 = NULL,
  n2 = NULL,
  middle = FALSE,
  transparency = FALSE
)

carto.pal.info()

display.carto.pal(name)

display.carto.all(n = 10)

Arguments

Details

Sequential palettes: "blue.pal", "orange.pal", "red.pal", "brown.pal", "green.pal", "purple.pal", "pink.pal", "wine.pal", "grey.pal", "turquoise.pal", "sand.pal", "taupe.pal", "kaki.pal" or "harmo.pal".

Qualitative palettes: "pastel.pal" or "multi.pal".

Value

carto.pal returns a vector of colors.

carto.pal.info returns a vector of color palettes names.

References

Qualitative palettes were generated with "i want hue" (https://medialab.github.io/iwanthue/) by Mathieu Jacomy at the Sciences-Po Medialab.

Examples

# Simple gradient: blue
carto.pal(pal1 = "blue.pal" ,n1 = 20)

# Double gradient: blue & red
carto.pal(pal1 = "blue.pal", n1 = 10, pal2 = "red.pal", n2 = 10)

# Adding a neutral color
carto.pal(pal1 = "blue.pal", n1 = 10, pal2 = "red.pal", n2 = 10, middle = TRUE)

# Enhancing contrasts with transparency
carto.pal(pal1="blue.pal", n1 = 10, pal2 = "red.pal", n2 = 10, middle = TRUE,
          transparency = TRUE)

# The double gradient can be asymetric
carto.pal(pal1 = "blue.pal", n1 = 5, pal2 = "red.pal", n2 = 15, middle = TRUE,
          transparency = TRUE)

# Build and display a palette
mypal <- carto.pal(pal1 = "blue.pal", n1 = 5, pal2 = "red.pal", n2 = 15,
                   middle = TRUE, transparency = TRUE)
k <- length(mypal)
image(1:k, 1, as.matrix(1:k), col =mypal, xlab = paste(k," classes",sep=""),
      ylab = "", xaxt = "n", yaxt = "n",bty = "n")
carto.pal.info()
display.carto.pal("orange.pal")
display.carto.all(8)

Choropleth Layer

Description

Plot a choropleth layer.

Usage

choroLayer(
  x,
  spdf,
  df,
  spdfid = NULL,
  dfid = NULL,
  var,
  breaks = NULL,
  method = "quantile",
  nclass = NULL,
  col = NULL,
  border = "grey20",
  lwd = 1,
  colNA = "white",
  legend.pos = "bottomleft",
  legend.title.txt = var,
  legend.title.cex = 0.8,
  legend.values.cex = 0.6,
  legend.values.rnd = 0,
  legend.nodata = "no data",
  legend.frame = FALSE,
  legend.border = "black",
  legend.horiz = FALSE,
  add = FALSE
)

Arguments

Details

The optimum number of class depends on the number of geographical objects. If nclass is not defined, an automatic method inspired by Sturges (1926) is used : nclass = 1+3.3*log10(N), where nclass is the number of class and N is the variable length.

If breaks is used then nclass and method are not.

If breaks is defined as c(2, 5, 10, 15, 20) intervals will be: [2 - 5[, [5 - 10[, [10 - 15[, [15 - 20].

References

Herbert A. Sturges, « The Choice of a Class Interval », Journal of the American Statistical Association, vol. 21, n° 153, mars 1926, p. 65-66.

See Also

getBreaks, carto.pal, legendChoro, propSymbolsChoroLayer

Examples

library(sf)
mtq <- st_read(system.file("gpkg/mtq.gpkg", package="cartography"))
# Population density
mtq$POPDENS <- 1e6 * mtq$POP / st_area(x = mtq)

# Default
choroLayer(x = mtq, var = "POPDENS")

# With parameters 
choroLayer(x = mtq, var = "POPDENS",
           method = "quantile", nclass = 5,
           col = carto.pal(pal1 = "sand.pal", n1 = 5),
           border = "grey40",
           legend.pos = "topright", legend.values.rnd = 0,
           legend.title.txt = "Population Density\n(people per km2)")

# Layout
layoutLayer(title = "Population Distribution in Martinique, 2015")

Coastline of Europe

Description

Coastline of Europe.

Format

SpatialLinesDataFrame.

Source

UMS RIATE - http://riate.cnrs.fr/

Countries in the European Area

Description

Countries in the European area.

Format

SpatialPolygonsDataFrame.

Source

UMS RIATE - http://riate.cnrs.fr/

Discontinuities Layer

Description

This function computes and plots spatial discontinuities. The discontinuities are plotted over the layer outputted by the getBorders function. The line widths reflect the ratio or the difference between values of an indicator in two neighbouring units.

Usage

discLayer(
  x,
  df,
  dfid = NULL,
  var,
  method = "quantile",
  nclass = 4,
  threshold = 0.75,
  type = "rel",
  sizemin = 1,
  sizemax = 10,
  col = "red",
  legend.pos = "bottomleft",
  legend.title.txt = "legend title",
  legend.title.cex = 0.8,
  legend.values.cex = 0.6,
  legend.values.rnd = 2,
  legend.frame = FALSE,
  add = TRUE
)

Arguments

Details

The "rel" type of discontinuity is the result of pmax(value unit 1 / value unit 2, value unit 2 / value unit 1).
The "abs" type of discontinuity is the result of pmax(value unit 1 - value unit 2, value unit 2 - value unit 1).

Value

An invisible sf object (MULTISTRING) with the discontinuity measures is returned.

See Also

getBorders, gradLinkLayer, legendGradLines

Examples

library(sf)
mtq <- st_read(system.file("gpkg/mtq.gpkg", package="cartography"))
# Get borders
mtq.borders <- getBorders(x = mtq)
# Median Income 
choroLayer(x = mtq, var = "MED", border = "grey", lwd = 0.5, 
           method = 'equal', nclass = 6, legend.pos = "topleft",
           legend.title.txt = "Median Income\n(in euros)" )
# Discontinuities
discLayer(x = mtq.borders, df = mtq,
          var = "MED", col="red4", nclass=3,
          method="equal", threshold = 0.4, sizemin = 0.5,
          sizemax = 10, type = "abs",legend.values.rnd = 0,
          legend.title.txt = "Discontinuities\n(absolute difference)",
          legend.pos = "bottomleft", add=TRUE)

Dot Density Layer

Description

Plot a dot density layer.

Usage

dotDensityLayer(
  x,
  spdf,
  df,
  spdfid = NULL,
  dfid = NULL,
  var,
  n = NULL,
  pch = 1,
  cex = 0.15,
  type = "random",
  col = "black",
  legend.pos = "topright",
  legend.txt = NULL,
  legend.cex = 0.6,
  legend.col = "black",
  legend.frame = TRUE,
  add = TRUE
)

Arguments

Details

The type parameters is defined within the st_sample function.

See Also

propSymbolsLayer

Examples

## Not run: 
library(sf)
mtq <- st_read(system.file("gpkg/mtq.gpkg", package="cartography"))
plot(st_geometry(mtq), col = "#B8704D50")
dotDensityLayer(x = mtq,  var="POP", pch=20, col = "red4", n = 200)
layoutLayer(title = "Population Distribution in Martinique, 2015")

## End(Not run)

Frame around Europe

Description

Frame around European countries.

Format

SpatialPolygonsDataFrame.

Source

UMS RIATE - http://riate.cnrs.fr/

Extract Polygons Borders

Description

Extract borders between polygons.

Outer borders are non-contiguous polygons borders (e.g. maritime borders).

Usage

getBorders(x, id)

getOuterBorders(x, id, res = NULL, width = NULL)

Arguments

Value

An sf object (MULTILINESTRING) of borders is returned. This object has three id variables: id, id1 and id2. id1 and id2 are ids of units that neighbour a border; id is the concatenation of id1 and id2 (with "_" as separator).

Note

getBorders and getOuterBorders can be combined with rbind.

See Also

discLayer

Examples

library(sf)
## Not run: 
mtq <- st_read(system.file("gpkg/mtq.gpkg", package="cartography"))
# extract
m <- mtq[c(5, 29, 9), ]
# Get borders
m_borders <- getBorders(x = m)
# Plot polygons
plot(st_geometry(m), border = NA, col = "grey60")
# Plot borders
plot(st_geometry(m_borders),
     col = sample(x = rainbow(nrow(m_borders))),
     lwd = 2 * c(4, 3, 2, 1), add = TRUE)

## End(Not run)
library(sf)
## Not run: 
mtq <- st_read(system.file("gpkg/mtq.gpkg", package="cartography"))
# extract
m <- mtq[c(29, 9), ]
# Get borders
m_borders <- getOuterBorders(x = m)
# Plot polygons
plot(st_geometry(m))
# Plot borders
plot(st_geometry(m_borders),
     col = sample(x = rainbow(nrow(m_borders))),
     lwd = c(4, 1), add = TRUE)

## End(Not run)

Classification

Description

A function to classify continuous variables.

Usage

getBreaks(v, nclass = NULL, method = "quantile", k = 1, middle = FALSE, ...)

Arguments

Details

"fixed", "sd", "equal", "pretty", "quantile", "kmeans", "hclust", "bclust", "fisher", "jenks" and "dpih" are classIntervals methods. You may need to pass additional arguments for some of them.

Jenks ("jenks" method) and Fisher-Jenks ("fisher" method) algorithms are based on the same principle and give quite similar results but Fisher-Jenks is much faster.

The "q6" method uses the following quantile probabilities: 0, 0.05, 0.275, 0.5, 0.725, 0.95, 1.

The "geom" method is based on a geometric progression along the variable values.

The "arith" method is based on an arithmetic progression along the variable values.

The "em" method is based on nested averages computation.

The "msd" method is based on the mean and the standard deviation of a numeric vector. The nclass parameter is not relevant, use k and middle instead. k indicates the extent of each class in share of standard deviation. If middle=TRUE then the mean value is the center of a class else the mean is a break value.

Value

A numeric vector of breaks

Note

This function is mainly a wrapper of classIntervals + "arith", "em", "q6", "geom" and "msd" methods.

See Also

classIntervals

Examples

library(sf)
mtq <- st_read(system.file("gpkg/mtq.gpkg", package="cartography"))
var <- mtq$MED
# Histogram
hist(var, probability = TRUE, breaks = 20)
rug(var)
moy <- mean(var)
med <- median(var)
abline(v = moy, col = "red", lwd = 3)
abline(v = med, col = "blue", lwd = 3)

# Quantile intervals
breaks <- getBreaks(v = var, nclass = 6, method = "quantile")
hist(var, probability = TRUE, breaks = breaks, col = "#F0D9F9")
rug(var)
med <- median(var)
abline(v = med, col = "blue", lwd = 3)

# Pretty breaks
breaks <- getBreaks(v = var, nclass = 4, method = "pretty")
hist(var, probability = TRUE, breaks = breaks, col = "#F0D9F9", axes = FALSE)
rug(var)
axis(1, at = breaks)
axis(2)
abline(v = med, col = "blue", lwd = 6)

# kmeans method
breaks <- getBreaks(v = var, nclass = 4, method = "kmeans")
hist(var, probability = TRUE, breaks = breaks, col = "#F0D9F9")
rug(var)
abline(v = med, col = "blue", lwd = 6)

# Geometric intervals
breaks <- getBreaks(v = var, nclass = 8, method = "geom")
hist(var, probability = TRUE, breaks = breaks, col = "#F0D9F9")
rug(var)

# Mean and standard deviation (msd)
breaks <- getBreaks(v = var, method = "msd", k = 1, middle = TRUE)
hist(var, probability = TRUE, breaks = breaks, col = "#F0D9F9")
rug(var)
moy <- mean(var)
sd <- sd(var)
abline(v = moy, col = "red", lwd = 3)
abline(v = moy + 0.5 * sd, col = "blue", lwd = 3)
abline(v = moy - 0.5 * sd, col = "blue", lwd = 3)

Get Figure Dimensions

Description

Give the dimension of a map figure to be exported in raster or vector format.
Output dimension are based on a spatial object dimension ratio, margins of the figure, a targeted width or height and a resolution.

Usage

getFigDim(x, width = NULL, height = NULL, mar = par("mar"), res = 72)

Arguments

Details

The function can be used to export vector or raster files (see examples).

Value

A vector of width and height in pixels is returned.

Examples

## Not run: 
library(sf)
mtq <- st_read(system.file("gpkg/mtq.gpkg", package="cartography"))

## PNG export
# get figure dimension
sizes <- getFigDim(x = mtq, width = 450, mar = c(0,0,1.2,0))
# export the map
png(filename = "mtq.png", width = sizes[1], height = sizes[2])
par(mar = c(0,0,1.2,0))
plot(st_geometry(mtq), col = "#D1914D", border = "white", bg = "#A6CAE0")
title("Madinina")
dev.off()

## PDF export
# get figure dimension
sizes <- getFigDim(x = mtq, width = 450, mar = c(1,1,2.2,1))
# export the map
pdf(file = "mtq.pdf", width = sizes[1]/72, height = sizes[2]/72)
par(mar = c(1,1,2.2,1))
plot(st_geometry(mtq), col = "#D1914D", border = "white", bg = "#A6CAE0")
title("Madinina")
dev.off()

## End(Not run)

Build a Regular Grid Layer

Description

Build a regular grid based on an sf object or a SpatialPolygonsDataFrame.

Usage

getGridLayer(x, cellsize, type = "regular", var)

Arguments

Value

A grid is returned as an sf object.

Examples

library(sf)
mtq <- st_read(system.file("gpkg/mtq.gpkg", package="cartography"))
# Plot dentsity of population
mtq$POPDENS <- 1e6 * mtq$POP / st_area(mtq) 
bks <- getBreaks(v = mtq$POPDENS, method = "geom", 5)
cols <- carto.pal(pal1 = "taupe.pal", n1 = 5)
opar <- par(mfrow = c(1,2), mar = c(0,0,0,0))
choroLayer(x = mtq, var = "POPDENS", breaks = bks,
           border = "burlywood3", col = cols,
           legend.pos = "topright", legend.values.rnd = 0,
           legend.title.txt = "Population density")

mygrid <- getGridLayer(x = mtq, cellsize = 3e7,
                       type = "hexagonal", var = "POP")
## conversion from square meter to square kilometers
mygrid$POPDENSG <- 1e6 * mygrid$POP / mygrid$gridarea 
choroLayer(x = mygrid, var = "POPDENSG", breaks = bks,
           border = "burlywood3", col = cols,
           legend.pos = "n", legend.values.rnd = 1,
           legend.title.txt = "Population density")
par(opar)

Create a Links Layer from a Data Frame of Links.

Description

Create a links layer from a data frame of links.

Usage

getLinkLayer(x, xid = NULL, df, dfid = NULL)

Arguments

Value

An sf LINESTRING is returned, it contains two variables (origins and destinations).

See Also

gradLinkLayer, propLinkLayer

Examples

library(sf)
mtq <- st_read(system.file("gpkg/mtq.gpkg", package="cartography"))
mob <- read.csv(system.file("csv/mob.csv", package="cartography"))
# Select links from Fort-de-France (97209))
mob_97209 <- mob[mob$i == 97209, ]
# Create a link layer
mob.sf <- getLinkLayer(x = mtq, df = mob_97209, dfid = c("i", "j"))
# Plot the links1
plot(st_geometry(mtq), col = "grey")
plot(st_geometry(mob.sf), col = "red4", lwd = 2, add = TRUE)

Pencil Layer

Description

Create a pencil layer. This function transforms a POLYGON or MULTIPOLYGON sf object into a MULTILINESTRING one.

Usage

getPencilLayer(x, size = 100, buffer = 1000, lefthanded = TRUE)

Arguments

Value

A MULTILINESTRING sf object is returned.

Examples

library(sf)
mtq <- st_read(system.file("gpkg/mtq.gpkg", package="cartography"))
mtq_pencil <- getPencilLayer(x = mtq)
plot(st_geometry(mtq_pencil), col = 1:8)
plot(st_geometry(mtq), add = TRUE)

typoLayer(x = mtq_pencil, var="STATUS", 
          col = c("aquamarine4", "yellow3","wheat"),
          legend.values.order = c("Prefecture",
                                  "Sub-prefecture", 
                                  "Simple municipality"),
          legend.pos = "topright",
          legend.title.txt = "Status")
plot(st_geometry(mtq), add = TRUE, ldy=2)
layoutLayer(title = "Municipality Status")

.png Layer

Description

Get a RasterBrick from a .png image cut using the shape of a spatial object. The .png file could be either a local file or extracted from a given url.

Usage

getPngLayer(
  x,
  pngpath,
  align = "center",
  margin = 0,
  crop = FALSE,
  mask = TRUE,
  inverse = FALSE,
  dwmode = "curl",
  ...
)

Arguments

Details

The effect of align would differ depending of the aspect ratio of x and pngpath. To obtain a fitted tile from pngpath given that x is the tile to fit, set margin = 0 , crop = TRUE.

Value

A RasterBrick object is returned.

Note

The accuracy of the final plot would depend on the quality of the .png file, the scale of x and the resolution setup of the graphic device. Exporting to svg is highly recommended.

Author(s)

dieghernan, https://github.com/dieghernan/

See Also

pngLayer

Examples

library(sf)
mtq <- st_read(system.file("gpkg/mtq.gpkg", package = "cartography"))
#Local file
dirpng <- system.file("img/LogoMartinique.png", package = "cartography")
mask <- getPngLayer(mtq, dirpng)

## Not run: 
#Remote file
urlpng <- "https://i.imgur.com/gePiDvB.png"
masksea <- getPngLayer(mtq, urlpng, mode = "wb", inverse = TRUE)

## End(Not run)

Defunct Get Tiles from Open Map Servers

Description

This function is defunct. Use 'maptiles::get_tiles()' instead.

Usage

getTiles(
  x,
  type = "OpenStreetMap",
  zoom = NULL,
  crop = FALSE,
  verbose = FALSE,
  apikey = NA,
  cachedir = FALSE,
  forceDownload = FALSE
)

Arguments

Details

Zoom levels are described on the OpenStreetMap wiki: https://wiki.openstreetmap.org/wiki/Zoom_levels.

Full list of providers:

Value

A RasterBrick is returned.

References

https://leaflet-extras.github.io/leaflet-providers/preview/

See Also

tilesLayer

Examples

# install.packages('maptiles')

Plot a Ghost Layer

Description

Plot an invisible layer with the extent of a spatial object.

Usage

ghostLayer(x, bg)

Arguments

Examples

library(sf)
mtq <- st_read(system.file("gpkg/mtq.gpkg", package="cartography"))
target <- mtq[30,]
ghostLayer(target, bg = "lightblue")
plot(st_geometry(mtq), add = TRUE, col = "gold2")
plot(st_geometry(target), add = TRUE, col = "red")
# overly complicated label placement trick:
labelLayer(x = suppressWarnings(st_intersection(mtq, st_buffer(target, 2000))), 
           txt = "LIBGEO", halo = TRUE, cex = .9, r = .14, font = 2, 
           bg = "grey20", col= "white")

Graduated Links Layer

Description

Plot a layer of graduated links. Links are plotted according to discrete classes of widths.

Usage

gradLinkLayer(
  x,
  df,
  xid = NULL,
  dfid = NULL,
  var,
  breaks = getBreaks(v = df[, var], nclass = 4, method = "quantile"),
  lwd = c(1, 2, 4, 6),
  col = "red",
  legend.pos = "bottomleft",
  legend.title.txt = var,
  legend.title.cex = 0.8,
  legend.values.cex = 0.6,
  legend.values.rnd = 0,
  legend.frame = FALSE,
  add = TRUE
)

Arguments

Note

Unlike most of cartography functions, identifiers fields are mandatory.

See Also

getLinkLayer, propLinkLayer, legendGradLines

Examples

library(sf)
mtq <- st_read(system.file("gpkg/mtq.gpkg", package="cartography"))
mob <- read.csv(system.file("csv/mob.csv", package="cartography"))
# Create a link layer - work mobilities to Fort-de-France (97209)
mob.sf <- getLinkLayer(x = mtq, df = mob[mob$j==97209,], dfid = c("i", "j"))
# Plot the links - Work mobility
plot(st_geometry(mtq), col = "grey60",border = "grey20")
gradLinkLayer(x = mob.sf, df = mob,
              legend.pos = "topright",
              var = "fij", 
              breaks = c(109,500,1000,2000,4679), 
              lwd = c(1,2,4,10),
              col = "#92000090", add = TRUE)

Graduated and Colored Links Layer

Description

Plot a layer of colored and graduated links. Links are plotted according to discrete classes of widths. Colors depend on a discrete variable of categories.

Usage

gradLinkTypoLayer(
  x,
  df,
  xid = NULL,
  dfid = NULL,
  var,
  breaks = getBreaks(v = df[, var], nclass = 4, method = "quantile"),
  lwd = c(1, 2, 4, 6),
  var2,
  col = NULL,
  colNA = "white",
  legend.title.cex = 0.8,
  legend.values.cex = 0.6,
  legend.values.rnd = 0,
  legend.var.pos = "bottomleft",
  legend.var.title.txt = var,
  legend.var.frame = FALSE,
  legend.var2.pos = "topright",
  legend.var2.title.txt = var2,
  legend.var2.values.order = NULL,
  legend.var2.nodata = "no data",
  legend.var2.frame = FALSE,
  add = TRUE
)

Arguments

Note

Unlike most of cartography functions, identifiers variables are mandatory.

See Also

getLinkLayer, propLinkLayer, legendGradLines, gradLinkLayer

Examples

library(sf)
mtq <- st_read(system.file("gpkg/mtq.gpkg", package="cartography"))
mob <- read.csv(system.file("csv/mob.csv", package="cartography"))
# Create a link layer - work mobilities to Fort-de-France (97209) and 
# Le Lamentin (97213)
mob.sf <- getLinkLayer(x = mtq, df = mob[mob$j %in% c(97209, 97213),], 
                       dfid = c("i", "j"))
# Plot the links - Work mobility
plot(st_geometry(mtq), col = "grey60",border = "grey20")
gradLinkTypoLayer(x = mob.sf, df = mob,
                  var = "fij", 
                  breaks = c(109,500,1000,2000,4679), 
                  lwd = c(1,2,4,10),
                  var2='j', add = TRUE)

Graticule around Europe

Description

Graticule around Europe.

Format

SpatialLines.

Source

UMS RIATE - http://riate.cnrs.fr/

Hatched Layer

Description

Plot a hatched layer with several different patterns. Suitable for b/w print maps.

Usage

hatchedLayer(x, pattern = "dot", density = 1, txt = "a", ...)

Arguments

Details

Possible values are:

Value

When passing mode='sfc' an 'sf' object (either MULTLINESTRING or MULTIPOINT) is returned.

Author(s)

dieghernan, https://github.com/dieghernan/

See Also

legendHatched

Examples

library(sf)
mtq <- st_read(system.file("gpkg/mtq.gpkg", package = "cartography"))
par(mar=c(1,1,1,1))
hatchedLayer(mtq, "dot")
title("dot")
plot(st_geometry(mtq), border = NA, col="grey80")
hatchedLayer(mtq, "text", txt = "Y", add=TRUE)
title("text")
hatchedLayer(mtq, "diamond", density = 0.5)
plot(st_union(st_geometry(mtq)), add = TRUE)
title("diamond")
hatchedLayer(mtq, "grid", lwd = 1.5)
title("grid")
hatchedLayer(mtq, "hexagon", col = "blue")
title("hexagon")
hatchedLayer(mtq, "horizontal", lty = 5)
title("horizontal")
hatchedLayer(mtq, "vertical")
title("vertical")
hatchedLayer(mtq, "left2right")
title("left2right")
hatchedLayer(mtq, "right2left")
title("right2left")
hatchedLayer(mtq, "zigzag",cellsize=5000)
title("zigzag")
hatchedLayer(mtq, "circle")
title("circle")

Label Layer

Description

Put labels on a map.

Usage

labelLayer(
  x,
  spdf,
  df,
  spdfid = NULL,
  dfid = NULL,
  txt,
  col = "black",
  cex = 0.7,
  overlap = TRUE,
  show.lines = TRUE,
  halo = FALSE,
  bg = "white",
  r = 0.1,
  ...
)

Arguments

See Also

layoutLayer

Examples

library(sf)
opar <- par(mar = c(0,0,0,0))
mtq <- st_read(system.file("gpkg/mtq.gpkg", package="cartography"))
plot(st_geometry(mtq), col = "darkseagreen3", border = "darkseagreen4", 
     bg = "#A6CAE0")
labelLayer(x = mtq, txt = "LIBGEO", col= "black", cex = 0.7, font = 4,
           halo = TRUE, bg = "white", r = 0.1, 
           overlap = FALSE, show.lines = FALSE)
par(opar)

Layout Layer

Description

Plot a layout layer.

Usage

layoutLayer(
  title = "Title of the map, year",
  sources = "",
  author = "",
  horiz = TRUE,
  col = "black",
  coltitle = "white",
  theme = NULL,
  bg = NULL,
  scale = "auto",
  posscale = "bottomright",
  frame = TRUE,
  north = FALSE,
  south = FALSE,
  extent = NULL,
  tabtitle = FALSE,
  postitle = "left"
)

Arguments

Details

If extent is not set, plot.new has to be called first.
The size of the title box in layoutLayer is fixed to 1.2 lines height.

See Also

labelLayer

Examples

library(sf)
mtq <- st_read(system.file("gpkg/mtq.gpkg", package="cartography"))
plot(st_geometry(mtq), col = "#D1914D", border = "white", bg = "#A6CAE0")
# Layout plot
layoutLayer()

plot(st_geometry(mtq), col = "#D1914D", border = "white", bg = "#A6CAE0")
# Layout plot
layoutLayer(title = "Martinique",
            author =  paste0("cartography ", packageVersion("cartography")),
            tabtitle = TRUE, scale = 5, north = TRUE, frame = FALSE,
            theme = "sand.pal")

Legend for Proportional Bars Maps

Description

Plot legend for proportional bars maps

Usage

legendBarsSymbols(
  pos = "topleft",
  title.txt = "Title of the legend",
  title.cex = 0.8,
  cex = 1,
  border = "black",
  lwd = 1,
  values.cex = 0.6,
  var,
  inches,
  col = "red",
  frame = FALSE,
  values.rnd = 0,
  style = "c"
)

Arguments

Examples

library(sf)
mtq <- st_read(system.file("gpkg/mtq.gpkg", package="cartography"))
plot(st_geometry(mtq))
box()
legendBarsSymbols(pos = "topleft", title.txt = "Title of\nthe legend",
                     title.cex = 0.8, values.cex = 0.6,cex = 1,
                     var = c(min(mtq$POP),max(mtq$POP)),
                     inches = 0.5,
                     col = "purple",
                     values.rnd=0, style ="e")

Legend for Choropleth Maps

Description

Plot legend for choropleth maps.

Usage

legendChoro(
  pos = "topleft",
  title.txt = "Title of the legend",
  title.cex = 0.8,
  values.cex = 0.6,
  breaks,
  col,
  cex = 1,
  values.rnd = 2,
  nodata = TRUE,
  nodata.txt = "No data",
  nodata.col = "white",
  frame = FALSE,
  symbol = "box",
  border = "black",
  horiz = FALSE
)

Arguments

Examples

library(sf)
mtq <- st_read(system.file("gpkg/mtq.gpkg", package="cartography"))
plot(st_geometry(mtq))
box()
legendChoro(pos = "bottomleft", title.txt = "Title of the legend", title.cex = 0.8,
            values.cex = 0.6, breaks = c(1,2,3,4,10.27,15.2),
            col = carto.pal(pal1 = "orange.pal",n1 = 5), values.rnd =2,
            nodata = TRUE, nodata.txt = "No data available", frame = TRUE, symbol="box")
legendChoro(pos = "bottomright", title.txt = "Title of the legend", title.cex = 0.8,
            values.cex = 0.6, breaks = c(1,2,5,7,10,15.27),
            col = carto.pal(pal1 = "wine.pal",n1 = 5), values.rnd = 0,
            nodata = TRUE, nodata.txt = "NA",nodata.col = "black",
            frame = TRUE, symbol="line")
legendChoro(pos = "topright", title.txt = "Title of the legend", title.cex = 0.8,
            values.cex = 0.6,
            breaks = c(0,"two","100","1 000","10,000", "1 Million"),
            col = carto.pal(pal1 = "orange.pal",n1 = 5), values.rnd =2,
            nodata = TRUE, nodata.txt = "No data available", frame = TRUE,
            symbol="box")

Legend for Proportional Circles Maps

Description

Plot legend for proportional circles maps

Usage

legendCirclesSymbols(
  pos = "topleft",
  title.txt = "Title of the legend",
  title.cex = 0.8,
  cex = 1,
  border = "black",
  lwd = 1,
  values.cex = 0.6,
  var,
  inches,
  col = "#E84923",
  frame = FALSE,
  values.rnd = 0,
  style = "c"
)

Arguments

Examples

library(sf)
mtq <- st_read(system.file("gpkg/mtq.gpkg", package="cartography"))
plot(st_geometry(mtq))
box()

propSymbolsLayer(x = mtq, var = "POP",
                 inches = 0.2, legend.pos = "n")

legendCirclesSymbols(pos = "topleft", inches = 0.2,
                     var = c(min(mtq$POP), max(mtq$POP)))
legendCirclesSymbols(pos = "left",
                     var = c(min(mtq$POP), max(mtq$POP)),
                     inches = 0.2, style = "e")
legendCirclesSymbols(pos = "bottomleft",
                     var = c(600, 12000, 40000, max(mtq$POP)),
                     inches = 0.2, style = "c")
legendCirclesSymbols(pos = "topright", cex = 2,
                     var = c(600, 30000,max(mtq$POP)),
                     inches = 0.2, style = "e", frame = TRUE)
legendCirclesSymbols(pos = c(736164.4, 1596658),
                     var = c(min(mtq$POP),max(mtq$POP)),
                     inches = 0.2, frame = TRUE)

Legend for Graduated Size Lines Maps

Description

Plot legend for graduated size lines maps.

Usage

legendGradLines(
  pos = "topleft",
  title.txt = "Title of the legend",
  title.cex = 0.8,
  cex = 1,
  values.cex = 0.6,
  breaks,
  lwd,
  col,
  values.rnd = 2,
  frame = FALSE
)

Arguments

Examples

library(sf)
mtq <- st_read(system.file("gpkg/mtq.gpkg", package="cartography"))
plot(st_geometry(mtq))
box()
legendGradLines(title.txt = "Title of the legend", 
                pos = "topright",
                title.cex = 0.8,
                values.cex = 0.6, breaks = c(1,2,3,4,10.2,15.2),
                lwd = c(0.2,2,4,5,10),
                col ="blue", values.rnd =2)

Legend for Hatched Maps

Description

Plot legend for hatched maps.

Usage

legendHatched(
  pos = "topleft",
  title.txt = "Title of the legend",
  title.cex = 0.8,
  values.cex = 0.6,
  categ,
  patterns,
  ptrn.bg = "white",
  ptrn.text = "X",
  dot.cex = 0.5,
  text.cex = 0.5,
  cex = 1,
  frame = FALSE,
  ...
)

Arguments

Note

It is also possible to create solid legends, by setting col and ptrn.bg to the same color. Parameters would honour the order of the categ variable.

Author(s)

dieghernan, https://github.com/dieghernan/

See Also

hatchedLayer, legendTypo

Examples

library(sf)
mtq <-  st_read(system.file("gpkg/mtq.gpkg", package = "cartography"))
typoLayer(mtq,  var = "STATUS",  legend.pos = "n",
          legend.values.order = c("Prefecture","Sub-prefecture",
                                  "Simple municipality"),
          col = c("grey10", "grey50", "grey80"),border = NA)
mtq$Patts = cut(mtq$MED,c(-Inf,15700,Inf), labels=FALSE)
hatchedLayer(mtq[mtq$Patts == 1,],"left2right",
             density = 2,  col = "white",  add = TRUE,  pch = 3,  cex = 0.6)
hatchedLayer(mtq[mtq$Patts == 2, ],"left2right",
             density = 4, col = "white", add = TRUE)
legendHatched(pos = "bottomleft",
              cex = 1.5,
              values.cex = 0.8,
              title.txt = "Median Income\n(in thousand of euros)",
              categ = c("11.9 - 15.7","14.7 - 21.8",
                        "Prefecture", "Sub-prefecture",
                        "Simple municipality"),
              patterns = c("left2right"), density = c(1, 2),
              col = c(rep("black", 2), "grey10", "grey50", "grey80"),
              ptrn.bg = c(rep("white", 2), "grey10", "grey50", "grey80"),
              pch = 3)
plot(st_geometry(st_union(mtq)), add = TRUE)

Legend for Proportional Lines Maps

Description

Plot legend for proportional lines maps

Usage

legendPropLines(
  pos = "topleft",
  title.txt = "Title of the legend",
  title.cex = 0.8,
  cex = 1,
  values.cex = 0.6,
  var,
  lwd,
  col = "red",
  frame = FALSE,
  values.rnd = 0
)

Arguments

Examples

library(sf)
mtq <- st_read(system.file("gpkg/mtq.gpkg", package="cartography"))
plot(st_geometry(mtq))
box()
legendPropLines(pos = "topleft", title.txt = "Title",
                title.cex = 0.8, values.cex = 0.6, cex = 1,
                var = c(10,100),
                lwd = 15,
                col="red", frame=TRUE, values.rnd=0)

Legend for Double Proportional Triangles Maps

Description

Plot legends for double proportional triangles maps.

Usage

legendPropTriangles(
  pos = "topleft",
  title.txt,
  var.txt,
  var2.txt,
  title.cex = 0.8,
  cex = 1,
  values.cex = 0.6,
  var,
  var2,
  r,
  r2,
  col = "red",
  col2 = "blue",
  frame = FALSE,
  values.rnd = 0,
  style = "c"
)

Arguments

Examples

library(sf)
mtq <- st_read(system.file("gpkg/mtq.gpkg", package="cartography"))
plot(st_geometry(mtq))
box()
var <- runif(10, 0,100)
var2 <- runif(10, 0,100)
r <- sqrt(var)*1000
r2 <- sqrt(var2)*1000
legendPropTriangles(pos = "topright", var.txt = "population 1",
                    var2.txt = "population 2", title.txt="Population totale",
                    title.cex = 0.8, values.cex = 0.6, cex = 1,
                    var = var, var2 = var2, r = r, r2 = r2,
                    col="green", col2="yellow", frame=TRUE, values.rnd=2,
                    style="c")

Legend for Proportional Squares Maps

Description

Plot legend for proportional squares maps

Usage

legendSquaresSymbols(
  pos = "topleft",
  title.txt = "Title of the legend",
  title.cex = 0.8,
  cex = 1,
  border = "black",
  lwd = 1,
  values.cex = 0.6,
  var,
  inches,
  col = "red",
  frame = FALSE,
  values.rnd = 0,
  style = "c"
)

Arguments

Examples

library(sf)
mtq <- st_read(system.file("gpkg/mtq.gpkg", package="cartography"))
plot(st_geometry(mtq))
box()
legendSquaresSymbols(pos = "bottomright", title.txt = "Title of\nthe legend ",
                     title.cex = 0.8, values.cex = 0.6,
                     var = c(max(mtq$POP), min(mtq$POP)),
                     inches = 0.5,
                     col="red",  
                     frame=TRUE, values.rnd=0, style ="c")

Legend for Typology Maps

Description

Plot legend for typology maps.

Usage

legendTypo(
  pos = "topleft",
  title.txt = "Title of the legend",
  title.cex = 0.8,
  values.cex = 0.6,
  col,
  categ,
  cex = 1,
  nodata = TRUE,
  nodata.txt = "No data",
  nodata.col = "white",
  frame = FALSE,
  symbol = "box"
)

Arguments

Examples

library(sf)
mtq <- st_read(system.file("gpkg/mtq.gpkg", package="cartography"))
plot(st_geometry(mtq))
box()

# Define labels and colors
someLabels <- c("red color", "yellow color", "green color", "black color")
someColors <- c("red", "yellow", "green", "black")

# plot legend
legendTypo(pos = "bottomleft", title.txt = "Title of the legend", title.cex = 0.8,
           values.cex = 0.6, col = someColors, categ = someLabels, 
           cex = 0.75,
           nodata = TRUE, nodata.txt = "no data", frame = TRUE, symbol="box")
legendTypo(pos = "topright", title.txt = "", 
           title.cex = 1.5, cex = 1.25,
           values.cex = 1, col = someColors, categ = someLabels, 
           nodata = FALSE, frame = FALSE, symbol="line")

Legend for Typology Maps

Description

Plot legend for typology maps.

Usage

legendWaffle(
  pos = "topleft",
  title.txt = "Title of the legend",
  title.cex = 0.8,
  values.cex = 0.6,
  categ,
  cex = 1,
  cell.txt = "1 cell = ...",
  col,
  cell.size,
  border = "white",
  lwd = 0.2,
  frame = FALSE
)

Arguments

Examples

library(sf)
mtq <- st_read(system.file("gpkg/mtq.gpkg", package="cartography"))
plot(st_geometry(mtq))
box()

# Define labels and colors
someLabels <- c("red color", "yellow color", "green color", "black color")
someColors <- c("red", "yellow", "green", "black")
legendWaffle(categ = someLabels, col = someColors, cell.size = 750)

North Arrow

Description

Plot a north arrow.

Usage

north(pos = "topright", col = "grey20", south = FALSE, x = NULL)

Arguments

See Also

layoutLayer

Examples

library(sf)
mtq <- st_read(system.file("gpkg/mtq.gpkg", package="cartography"))
plot(st_geometry(mtq))
box()
for (i in list("topleft", "top", "topright", "right", "bottomright", 
               "bottom", "bottomleft", "left", c(746368, 1632993))){
  north(i, south = TRUE)
}

Nuts0 Dataset

Description

This dataset contains some socio-economic data

Details

This data frame can be used with the SpatialPolygonsDataFrame nuts0.spdf

Fields

id

Unique nuts id (character)

emp2008

Active population in employment in 2008 (thousands persons) (numeric)

act2008

Active population in 2008 (thousands persons) (numeric)

unemp2008

Active population unemployed in 2008 (thousands persons) (numeric)

birth_2008

Number of birth in 2008 (live birth) (numeric)

death_2008

Number of death in 2008 (death) (numeric)

gdppps1999

Gross domestic product (Purchasing Power Standards) in 1999 (million euros) (numeric)

gdppps2008

Gross domestic product (Purchasing Power Standards) in 2008 (million euros) (numeric)

pop1999

Total population in 1999 (inhabitants) (numeric)

pop2008

Total population in 2008 (inhabitants) (numeric)

Source

UMS RIATE - Data extraction: 2011; data validity: 2008.

Nuts0 Regions

Description

Delineations of EU administrative units (level 0, 2006 version).

Format

SpatialPolygonsDataFrame.

Details

This SpatialPolygonsDataFrame can be used with the nuts0.df data frame

Fields

id

Unique nuts id (character)

Source

UMS RIATE - http://riate.cnrs.fr/

Nuts1 Dataset

Description

This dataset contains some socio-economic data

Details

This data frame can be used with the SpatialPolygonsDataFrame nuts1.spdf

Fields

id

Unique nuts id (character)

emp2008

Active population in employment in 2008 (thousands persons) (numeric)

act2008

Active population in 2008 (thousands persons) (numeric)

unemp2008

Active population unemployed in 2008 (thousands persons) (numeric)

birth_2008

Number of birth in 2008 (live birth) (numeric)

death_2008

Number of death in 2008 (death) (numeric)

gdppps1999

Gross domestic product (Purchasing Power Standards) in 1999 (million euros) (numeric)

gdppps2008

Gross domestic product (Purchasing Power Standards) in 2008 (million euros) (numeric)

pop1999

Total population in 1999 (inhabitants) (numeric)

pop2008

Total population in 2008 (inhabitants) (numeric)

Source

UMS RIATE - Data extraction: 2011; data validity: 2008.

Nuts1 Regions

Description

Delineations of EU administrative units (level 1, 2006 version).

Format

SpatialPolygonsDataFrame.

Details

This SpatialPolygonsDataFrame can be used with the nuts1.df data frame

Fields

id

Unique nuts id (character)

Source

UMS RIATE - http://riate.cnrs.fr/

Nuts2 Dataset

Description

This dataset contains some socio-economic data

Details

This data frame can be used with the SpatialPolygonsDataFrame nuts2.spdf

Fields

id

Unique nuts id (character)

emp2008

Active population in employment in 2008 (thousands persons) (numeric)

act2008

Active population in 2008 (thousands persons) (numeric)

unemp2008

Active population unemployed in 2008 (thousands persons) (numeric)

birth_2008

Number of birth in 2008 (live birth) (numeric)

death_2008

Number of death in 2008 (death) (numeric)

gdppps1999

Gross domestic product (Purchasing Power Standards) in 1999 (million euros) (numeric)

gdppps2008

Gross domestic product (Purchasing Power Standards) in 2008 (million euros) (numeric)

pop1999

Total population in 1999 (inhabitants) (numeric)

pop2008

Total population in 2008 (inhabitants) (numeric)

Source

UMS RIATE - Data extraction: 2011; data validity: 2008.

Nuts2 Regions

Description

Delineations of EU administrative units (level 2, 2006 version).

Format

SpatialPolygonsDataFrame.

Details

This SpatialPolygonsDataFrame can be used with the nuts2.df data frame

Fields

id

Unique nuts id (character)

Source

UMS RIATE - http://riate.cnrs.fr/

Nuts3 Dataset

Description

This dataset contains some socio-economic data

Details

This data frame can be used with the SpatialPolygonsDataFrame nuts3.spdf

Fields

id

Unique nuts id (character)

birth_2008

Number of birth in 2008 (live birth) (numeric)

death_2008

Number of death in 2008 (death) (numeric)

gdppps1999

Gross domestic product (Purchasing Power Standards) in 1999 (million euros) (numeric)

gdppps2008

Gross domestic product (Purchasing Power Standards) in 2008 (million euros) (numeric)

pop1999

Total population in 1999 (inhabitants) (numeric)

pop2008

Total population in 2008 (inhabitants) (numeric)

Source

UMS RIATE - Data extraction: 2011; data validity: 2008.

Nuts3 Regions

Description

Delineations of EU administrative units (level 3, 2006 version).

Format

SpatialPolygonsDataFrame.

Details

This SpatialPolygonsDataFrame can be used with the nuts3.df data frame

Fields

id

Unique nuts id (character)

Source

UMS RIATE - http://riate.cnrs.fr/

Proportional Links Layer

Description

Plot a layer of proportional links. Links widths are directly proportional to values of a variable.

Usage

propLinkLayer(
  x,
  df,
  xid = NULL,
  dfid = NULL,
  var,
  maxlwd = 40,
  col,
  legend.pos = "bottomleft",
  legend.title.txt = var,
  legend.title.cex = 0.8,
  legend.values.cex = 0.6,
  legend.values.rnd = 0,
  legend.frame = FALSE,
  add = TRUE
)

Arguments

Note

Unlike most of cartography functions, identifiers variables are mandatory.

See Also

gradLinkLayer, getLinkLayer, legendPropLines

Examples

library(sf)
mtq <- st_read(system.file("gpkg/mtq.gpkg", package="cartography"))
mob <- read.csv(system.file("csv/mob.csv", package="cartography"))
# Create a link layer - work mobilities to Fort-de-France (97209)
mob.sf <- getLinkLayer(x = mtq, df = mob[mob$j==97209,], dfid = c("i", "j"))
# Plot the links - Work mobility
plot(st_geometry(mtq), col = "grey60",border = "grey20")
propLinkLayer(x = mob.sf, df = mob,
              maxlwd = 10,
              legend.pos = "topright",
              var = "fij",
              col = "#92000090", add = TRUE)

Proportional and Choropleth Symbols Layer

Description

Plot a proportional symbols layer with colors based on a quantitative data classification

Usage

propSymbolsChoroLayer(
  x,
  spdf,
  df,
  spdfid = NULL,
  dfid = NULL,
  var,
  inches = 0.3,
  fixmax = NULL,
  symbols = "circle",
  border = "grey20",
  lwd = 1,
  var2,
  breaks = NULL,
  method = "quantile",
  nclass = NULL,
  col = NULL,
  colNA = "white",
  legend.title.cex = 0.8,
  legend.values.cex = 0.6,
  legend.var.pos = "right",
  legend.var.title.txt = var,
  legend.var.values.rnd = 0,
  legend.var.style = "c",
  legend.var.frame = FALSE,
  legend.var2.pos = "topright",
  legend.var2.title.txt = var2,
  legend.var2.values.rnd = 2,
  legend.var2.nodata = "no data",
  legend.var2.frame = FALSE,
  legend.var2.border = "black",
  legend.var2.horiz = FALSE,
  add = TRUE
)

Arguments

See Also

legendBarsSymbols, legendChoro, legendCirclesSymbols, legendSquaresSymbols, choroLayer, propSymbolsLayer

Examples

library(sf)
mtq <- st_read(system.file("gpkg/mtq.gpkg", package="cartography"))
plot(st_geometry(mtq), col = "grey60",border = "white",
     lwd=0.4, bg = "lightsteelblue1")
propSymbolsChoroLayer(x = mtq, var = "POP", var2 = "MED",
                      col = carto.pal(pal1 = "blue.pal", n1 = 3,
                                      pal2 = "red.pal", n2 = 3),
                      inches = 0.2, method = "q6",
                      border = "grey50", lwd = 1,
                      legend.var.pos = "topright", 
                      legend.var2.pos = "left",
                      legend.var2.values.rnd = -2,
                      legend.var2.title.txt = "Median Income\n(in euros)",
                      legend.var.title.txt = "Total Population",
                      legend.var.style = "e")
# First layout
layoutLayer(title="Population and Wealth in Martinique, 2015")

Proportional Symbols Layer

Description

Plot a proportional symbols layer.

Usage

propSymbolsLayer(
  x,
  spdf,
  df,
  spdfid = NULL,
  dfid = NULL,
  var,
  inches = 0.3,
  fixmax = NULL,
  symbols = "circle",
  col = "#E84923",
  border = "black",
  lwd = 1,
  legend.pos = "bottomleft",
  legend.title.txt = var,
  legend.title.cex = 0.8,
  legend.values.cex = 0.6,
  legend.values.rnd = 0,
  legend.style = "c",
  legend.frame = FALSE,
  add = TRUE
)

Arguments

Details

Two maps with the same inches and fixmax parameters will be comparable.

See Also

legendBarsSymbols, legendCirclesSymbols, legendSquaresSymbols, propSymbolsChoroLayer, propSymbolsTypoLayer

Examples

library(sf)
mtq <- st_read(system.file("gpkg/mtq.gpkg", package="cartography"))
plot(st_geometry(mtq))
propSymbolsLayer(x = mtq, var = "POP")

plot(st_geometry(mtq), col = "lightblue4",border = "lightblue3", 
     bg = "lightblue1")
# Population plot on proportional symbols
propSymbolsLayer(x = mtq, var = "POP",
                 symbols = "circle", col =  "white",
                 legend.pos = "right", border = "grey",
                 legend.title.txt = "Total\nPopulation",
                 legend.style = "c")
# Layout plot
layoutLayer(title = "Population Distribution in Martinique, 2015")

Proportional Symbols Typo Layer

Description

Plot a proportional symbols layer with colors based on qualitative data.

Usage

propSymbolsTypoLayer(
  x,
  spdf,
  df,
  spdfid = NULL,
  dfid = NULL,
  var,
  inches = 0.3,
  fixmax = NULL,
  symbols = "circle",
  border = "grey20",
  lwd = 1,
  var2,
  col = NULL,
  colNA = "white",
  legend.title.cex = 0.8,
  legend.values.cex = 0.6,
  legend.var.pos = "bottomleft",
  legend.var.title.txt = var,
  legend.values.rnd = 0,
  legend.var.style = "c",
  legend.var.frame = FALSE,
  legend.var2.pos = "topright",
  legend.var2.title.txt = var2,
  legend.var2.values.order = NULL,
  legend.var2.nodata = "no data",
  legend.var2.frame = FALSE,
  add = TRUE
)

Arguments

See Also

legendBarsSymbols, legendTypo, legendCirclesSymbols, legendSquaresSymbols, typoLayer, propSymbolsLayer

Examples

library(sf)
mtq <- st_read(system.file("gpkg/mtq.gpkg", package="cartography"))
# Countries plot
plot(st_geometry(mtq), col = "lightblue4",border = "lightblue3", 
     bg = "lightblue1")
# Population plot on proportional symbols
propSymbolsTypoLayer(x = mtq, var = "POP", var2 = "STATUS",
                     symbols = "circle",
                     col = c("aquamarine4", "yellow3","wheat"),
                     legend.var2.values.order = c("Prefecture",
                                                  "Sub-prefecture",
                                                  "Simple municipality"),
                     legend.var.pos = "right", border = "grey",
                     legend.var.title.txt = "Total\nPopulation")
layoutLayer(title = "Population Distribution in Martinique, 2015")

Double Proportional Triangle Layer

Description

Plot a double proportional triangles layer.

Usage

propTrianglesLayer(
  x,
  spdf,
  df,
  spdfid = NULL,
  dfid = NULL,
  var1,
  col1 = "#E84923",
  var2,
  col2 = "#7DC437",
  k = 0.02,
  legend.pos = "topright",
  legend.title.txt = paste(var1, var2, sep = " / "),
  legend.title.cex = 0.8,
  legend.var1.txt = var1,
  legend.var2.txt = var2,
  legend.values.cex = 0.6,
  legend.values.rnd = 0,
  legend.style = "c",
  legend.frame = FALSE,
  add = TRUE
)

Arguments

See Also

legendPropTriangles

Examples

library(sf)
mtq <- st_read(system.file("gpkg/mtq.gpkg", package="cartography"))
# Employed Active Population 
mtq$OCC <- mtq$ACT-mtq$CHOM
plot(st_geometry(mtq), col = "lightblue4",border = "lightblue3",
     bg = "lightblue1")
propTrianglesLayer(x = mtq, var1 = "OCC", var2 = "CHOM", 
                   col1="green4",col2="red4",k = 0.1)
layoutLayer(title = "Active Population in Martinique, 2015")

Smooth Layer

Description

This function is deprecated. Please use the 'potential' package instead (https://riatelab.github.io/potential/).

Plot a layer of smoothed data. It can also compute a ratio of potentials.

This function is a wrapper around the quickStewart function in SpatialPosition package.

The SpatialPosition package also provides:

• vignettes to explain the computation of potentials;

• more customizable inputs and outputs (custom distance matrix, raster output...);

• other functions related to spatial interactions (Reilly and Huff catchment areas).

Usage

smoothLayer(
  x,
  spdf,
  df,
  spdfid = NULL,
  dfid = NULL,
  var,
  var2 = NULL,
  typefct = "exponential",
  span,
  beta,
  resolution = NULL,
  mask = NULL,
  nclass = 8,
  breaks = NULL,
  col = NULL,
  border = "grey20",
  lwd = 1,
  legend.pos = "bottomleft",
  legend.title.txt = "Potential",
  legend.title.cex = 0.8,
  legend.values.cex = 0.6,
  legend.values.rnd = 0,
  legend.frame = FALSE,
  add = FALSE
)

Arguments

Details

If var2 is provided the ratio between the potentials of var (numerator) and var2 (denominator) is computed.

Value

An invisible sf object (MULTIPOLYGONs) is returned (see quickStewart).

See Also

quickStewart, SpatialPosition, choroLayer

Examples

# install.packages('potential')

Plot a Raster Object

Description

Plot a raster object over a map. It can be used to plot images from getPngLayer.

Usage

tilesLayer(x, add = FALSE, ...)

pngLayer(x, add = FALSE, ...)

Arguments

Note

This function is a wrapper for plotRGB from the raster package. The accuracy of the final plot depends on the quality of the *.png file, the scale of x and the resolution setup of the graphic device.

Author(s)

dieghernan, https://github.com/dieghernan/

See Also

getPngLayer

Examples

library(sf)
mtq <- st_read(system.file("gpkg/mtq.gpkg", package = "cartography"))

# Local image
dirpng <- system.file("img/LogoMartinique.png", package = "cartography")
mask <- getPngLayer(mtq, dirpng, crop = TRUE, margin = 0.5)
par(mar = c(0,0,0,0))
ghostLayer(mtq)
pngLayer(mask, add = TRUE)

## Not run: 
# Remote image
urlpng = "https://i.imgur.com/gePiDvB.png"
masksea <- getPngLayer(mtq, urlpng, mode = "wb", inverse = TRUE, margin = 0.5)
#Combine
par(mar = c(0,0,0,0))
ghostLayer(mtq)
pngLayer(mask, add = TRUE)
pngLayer(masksea, add = TRUE)
plot(st_geometry(mtq), border="orange", add=TRUE)

## End(Not run)

Twin Cities Dataset

Description

This dataset contains the number of international twinning agreements between cities. Agreements are aggregated at nuts2 level.

Details

This data frame can be used with the SpatialPolygonsDataFrame nuts2.spdf

Fields

i

nuts2 identifier

j

nuts2 identifier

fij

number of agreements

Source

Adam Ploszaj - Centre for European Regional and Local Studies EUROREG, University of Warsaw, Poland. Primary source: Wikipedia, 2011.

Typology Layer

Description

Plot a typology layer.

Usage

typoLayer(
  x,
  spdf,
  df,
  spdfid = NULL,
  dfid = NULL,
  var,
  col = NULL,
  border = "grey20",
  lwd = 1,
  colNA = "white",
  legend.pos = "bottomleft",
  legend.title.txt = var,
  legend.title.cex = 0.8,
  legend.values.cex = 0.6,
  legend.values.order = NULL,
  legend.nodata = "no data",
  legend.frame = FALSE,
  add = FALSE
)

Arguments

See Also

propSymbolsTypoLayer, typoLayer, legendTypo

Examples

library(sf)
mtq <- st_read(system.file("gpkg/mtq.gpkg", package="cartography"))
typoLayer(x = mtq, var="STATUS",  
          col = c("aquamarine4", "yellow3","wheat"),
          legend.values.order = c("Prefecture",
                                  "Sub-prefecture", 
                                  "Simple municipality"),
          legend.pos = "topright",
          legend.title.txt = "Status")
layoutLayer(title = "Municipality Status")

Waffle Layer

Description

Plot a waffle layer.

Usage

waffleLayer(
  x,
  var,
  cellvalue,
  cellsize,
  cellrnd = "ceiling",
  celltxt = paste0("1 cell = ", cellvalue),
  labels,
  ncols,
  col,
  border = "white",
  lwd = 0.2,
  legend.pos = "bottomleft",
  legend.title.txt = "legend title",
  legend.title.cex = 0.8,
  legend.values.cex = 0.6,
  legend.frame = FALSE,
  add = TRUE
)

Arguments

Examples

library(sf)
mtq <- st_read(system.file("gpkg/mtq.gpkg", package = "cartography"),
               quiet = TRUE)
# number of employed persons
mtq$EMP <- mtq$ACT - mtq$CHOM

plot(st_geometry(mtq),
     col = "#f2efe9",
     border = "#b38e43",
     lwd = 0.5)
waffleLayer(
  x = mtq,
  var = c("EMP", "CHOM"),
  cellvalue = 100,
  cellsize = 400,
  cellrnd = "ceiling",
  celltxt = "1 cell represents 100 persons",
  labels = c("Employed", "Unemployed"),
  ncols = 6,
  col = c("tomato1", "lightblue"),
  border = "#f2efe9",
  legend.pos = "topright",
  legend.title.cex = 1,
  legend.title.txt = "Active Population",
  legend.values.cex = 0.8,
  add = TRUE
)

layoutLayer(
  title = "Structure of the Active Population",
  col = "tomato4",
  tabtitle = TRUE,
  scale = FALSE,
  sources =  paste0("cartography ", packageVersion("cartography")),
  author = "Sources: Insee and IGN, 2018",
)

Wordcloud Layer

Description

Plot a word cloud adjusted to an sf object.

Usage

wordcloudLayer(
  x,
  txt,
  freq,
  max.words = NULL,
  cex.maxmin = c(1, 0.5),
  rot.per = 0.1,
  col = NULL,
  fittopol = FALSE,
  use.rank = FALSE,
  add = FALSE,
  breaks = NULL,
  method = "quantile",
  nclass = NULL
)

Arguments

Author(s)

dieghernan, https://github.com/dieghernan/

References

Ian Fellows (2018). wordcloud: Word Clouds.

R package version 2.6. https://CRAN.R-project.org/package=wordcloud

See Also

choroLayer, legendChoro

Examples

library(sf) 
mtq <- st_read(system.file("gpkg/mtq.gpkg", package = "cartography"))
par(mar=c(0,0,0,0))
plot(st_geometry(mtq),
     col = "white",
     bg = "grey95",
     border = NA)
wordcloudLayer(
  x = mtq,
  txt = "LIBGEO",
  freq = "POP",
  add = TRUE,
  nclass = 5
)
legendChoro(
  title.txt = "Population",
  breaks = getBreaks(mtq$POP, nclass = 5, method = "quantile"),
  col = carto.pal("blue.pal", 5),
  nodata = FALSE
)

World Background

Description

World background.

Format

SpatialPolygonsDataFrame.

Source

UMS RIATE - http://riate.cnrs.fr/