gg.SpatialPixelsDataFrame: Geom for SpatialPixelsDataFrame objects

In inlabru-org/inlabru: Bayesian Latent Gaussian Modelling using INLA and Extensions

Geom for SpatialPixelsDataFrame objects

Description

Coerces input SpatialPixelsDataFrame to data.frame and uses geom_tile to plot it. Requires the ggplot2 package.

Usage

## S3 method for class 'SpatialPixelsDataFrame'
gg(data, mapping = NULL, crs = NULL, mask = NULL, ...)

Arguments

data	A SpatialPixelsDataFrame object.
mapping	Aesthetic mappings created by aes used to update the default mapping. The default mapping is ggplot2::aes(x = .data[[coordnames(data)[1]]], y = .data[[coordnames(data)[2]]], fill = .data[[names(data)[[1]]]]).
crs	A CRS object defining the coordinate system to project the data to before plotting.
mask	A SpatialPolygon defining the region that is plotted.
...	Arguments passed on to geom_tile.

Value

A geom_tile return value.

See Also

Other geomes for spatial data: gg(), gg.SpatRaster(), gg.SpatialGridDataFrame(), gg.SpatialLines(), gg.SpatialPixels(), gg.SpatialPoints(), gg.SpatialPolygons(), gg.sf(), gm()

Examples

  if (require(ggplot2, quietly = TRUE) &&
      bru_safe_sp() &&
      require("sp")) {
    # Load Gorilla data

    data("gorillas", package = "inlabru")

    # Plot Gorilla elevation covariate provided as SpatialPixelsDataFrame.
    # The same syntax applies to SpatialGridDataFrame objects.

    ggplot() +
      gg(gorillas$gcov$elevation)

    # Add Gorilla survey boundary and nest sightings

    ggplot() +
      gg(gorillas$gcov$elevation) +
      gg(gorillas$boundary) +
      gg(gorillas$nests)

    # Load pantropical dolphin data

    data("mexdolphin", package = "inlabru")

    # Plot the pantropical survey boundary, ship transects and dolphin sightings

    ggplot() +
      gg(mexdolphin$ppoly) + # survey boundary as SpatialPolygon
      gg(mexdolphin$samplers) + # ship transects as SpatialLines
      gg(mexdolphin$points) # dolphin sightings as SpatialPoints

    # Change color

    ggplot() +
      gg(mexdolphin$ppoly, color = "green") + # survey boundary as SpatialPolygon
      gg(mexdolphin$samplers, color = "red") + # ship transects as SpatialLines
      gg(mexdolphin$points, color = "blue") # dolphin sightings as SpatialPoints


    # Visualize data annotations: line width by segment number

    names(mexdolphin$samplers) # 'seg' holds the segment number
    ggplot() +
      gg(mexdolphin$samplers, aes(color = seg))

    # Visualize data annotations: point size by dolphin group size

    names(mexdolphin$points) # 'size' holds the group size
    ggplot() +
      gg(mexdolphin$points, aes(size = size))
  }

inlabru-org/inlabru documentation built on April 15, 2024, 3:53 a.m.