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tmap advanced: multiple visual variables

Source: vignettes/adv_multivariate.Rmd
adv_multivariate.Rmd

Multiple visual variables

Usually we specify a data-driven visual variable with one data variable (see vignette about visual variables). However, in several use cases, it is useful to use a few data variables for one visual variables.

There are two ways to use multiple data variables for one visual variable: for creating facets, and for multivariate mapping.

Creating facets

Recall from the vigentte about facets

tm_shape(NLD_muni) +
  tm_polygons(
    fill = c("pop_0_14", "pop_25_44", "pop_65plus"),
    fill.legend = tm_legend("Percentage"),
    fill.free = FALSE)

A facet is create for each specified data variable. More options to select variables are available via the underlying function tm_vars(). For instance, variables 12 to 18 (so columns 12 to 18, disregarding the geometry column)

tm_shape(NLD_muni) +
  tm_polygons(
    fill = tm_vars(12:18))

Or the first 3 variables:

tm_shape(NLD_muni) +
  tm_polygons(
    fill = tm_vars(n = 3))
#> Warning: Number of levels of the variable assigned to the aesthetic "fill" of
#> the layer "polygons" is 345, which is larger than n.max (which is 30), so
#> levels are combined.
#> Warning: Number of levels of the variable assigned to the aesthetic "fill" of
#> the layer "polygons" is 345, which is larger than n.max (which is 30), so
#> levels are combined.
#> [plot mode] fit legend/component: Some legend items or map compoments do not
#> fit well, and are therefore rescaled.
#> ℹ Set the tmap option `component.autoscale = FALSE` to disable rescaling.

  1. For creating facets. This is the standard way.
  2. For multivariate mapping.

These cases can be divived into two g Before going through these cases, there is one important There are two

Multivariate mapping

There are (at least) two use cases:

RGB image 

library(stars)
#> Loading required package: abind
#> Loading required package: sf
#> Linking to GEOS 3.12.1, GDAL 3.8.4, PROJ 9.4.0; sf_use_s2() is TRUE
tif = system.file("tif/L7_ETMs.tif", package = "stars")
(L7 = read_stars(tif))
#> stars object with 3 dimensions and 1 attribute
#> attribute(s):
#>              Min. 1st Qu. Median     Mean 3rd Qu. Max.
#> L7_ETMs.tif     1      54     69 68.91242      86  255
#> dimension(s):
#>      from  to  offset delta                     refsys point x/y
#> x       1 349  288776  28.5 SIRGAS 2000 / UTM zone 25S FALSE [x]
#> y       1 352 9120761 -28.5 SIRGAS 2000 / UTM zone 25S FALSE [y]
#> band    1   6      NA    NA                         NA    NA

Note that the channels are included in the dimenison "band". We can use the argument dimvalues to select them:

tm_shape(L7) +
    tm_rgb(col = tm_vars(dimvalues = 3:1, multivariate = TRUE))

Alternatively, we can split the stars object:

(L7split = split(L7))
#> stars object with 2 dimensions and 6 attributes
#> attribute(s):
#>     Min. 1st Qu. Median     Mean 3rd Qu. Max.
#> X1    47      67     78 79.14772      89  255
#> X2    32      55     66 67.57465      79  255
#> X3    21      49     63 64.35886      77  255
#> X4     9      52     63 59.23541      75  255
#> X5     1      63     89 83.18266     112  255
#> X6     1      32     60 59.97521      88  255
#> dimension(s):
#>   from  to  offset delta                     refsys point x/y
#> x    1 349  288776  28.5 SIRGAS 2000 / UTM zone 25S FALSE [x]
#> y    1 352 9120761 -28.5 SIRGAS 2000 / UTM zone 25S FALSE [y]

and plot it like this:

tm_shape(L7split) +
    tm_rgb(col = tm_vars(3:1, multivariate = TRUE))

Glyphs

Glyph are small charts plotted as symbols. See the [extention package tmap.glyphs.

library(tmap.glyphs)

ZH_muni = NLD_muni[NLD_muni$province == "Zuid-Holland", ]
ZH_muni$income_middle = 100 - ZH_muni$income_high - ZH_muni$income_low

tm_shape(ZH_muni) +
  tm_polygons() +
  tm_donuts(
    parts = tm_vars(c("income_low", "income_middle", "income_high"), multivariate = TRUE),
    fill.scale = tm_scale_categorical(values = "-pu_gn_div"),             
    size = "population",
    size.scale = tm_scale_continuous(ticks = c(50000, 100000, 250000, 500000))) 
#> [plot mode] map layer `tm_donuts` not available for mode "plot" and also not
#> for the other modes

The visual variable parts (introduced in tmap.glyphs) is specified as multivariate visual variable. It specifies the parts (slices) of the donut charts and uses this also for the fill color.