Learn R Programming

ggplot2 (version 3.3.5)

CoordSf: Visualise sf objects

Description

This set of geom, stat, and coord are used to visualise simple feature (sf) objects. For simple plots, you will only need geom_sf() as it uses stat_sf() and adds coord_sf() for you. geom_sf() is an unusual geom because it will draw different geometric objects depending on what simple features are present in the data: you can get points, lines, or polygons. For text and labels, you can use geom_sf_text() and geom_sf_label().

Usage

coord_sf(
  xlim = NULL,
  ylim = NULL,
  expand = TRUE,
  crs = NULL,
  default_crs = NULL,
  datum = sf::st_crs(4326),
  label_graticule = waiver(),
  label_axes = waiver(),
  lims_method = c("cross", "box", "orthogonal", "geometry_bbox"),
  ndiscr = 100,
  default = FALSE,
  clip = "on"
)

geom_sf( mapping = aes(), data = NULL, stat = "sf", position = "identity", na.rm = FALSE, show.legend = NA, inherit.aes = TRUE, ... )

geom_sf_label( mapping = aes(), data = NULL, stat = "sf_coordinates", position = "identity", ..., parse = FALSE, nudge_x = 0, nudge_y = 0, label.padding = unit(0.25, "lines"), label.r = unit(0.15, "lines"), label.size = 0.25, na.rm = FALSE, show.legend = NA, inherit.aes = TRUE, fun.geometry = NULL )

geom_sf_text( mapping = aes(), data = NULL, stat = "sf_coordinates", position = "identity", ..., parse = FALSE, nudge_x = 0, nudge_y = 0, check_overlap = FALSE, na.rm = FALSE, show.legend = NA, inherit.aes = TRUE, fun.geometry = NULL )

stat_sf( mapping = NULL, data = NULL, geom = "rect", position = "identity", na.rm = FALSE, show.legend = NA, inherit.aes = TRUE, ... )

Arguments

xlim, ylim

Limits for the x and y axes. These limits are specified in the units of the default CRS. By default, this means projected coordinates (default_crs = NULL). How limit specifications translate into the exact region shown on the plot can be confusing when non-linear or rotated coordinate systems are used as the default crs. First, different methods can be preferable under different conditions. See parameter lims_method for details. Second, specifying limits along only one direction can affect the automatically generated limits along the other direction. Therefore, it is best to always specify limits for both x and y. Third, specifying limits via position scales or xlim()/ylim() is strongly discouraged, as it can result in data points being dropped from the plot even though they would be visible in the final plot region.

expand

If TRUE, the default, adds a small expansion factor to the limits to ensure that data and axes don't overlap. If FALSE, limits are taken exactly from the data or xlim/ylim.

crs

The coordinate reference system (CRS) into which all data should be projected before plotting. If not specified, will use the CRS defined in the first sf layer of the plot.

default_crs

The default CRS to be used for non-sf layers (which don't carry any CRS information) and scale limits. The default value of NULL means that the setting for crs is used. This implies that all non-sf layers and scale limits are assumed to be specified in projected coordinates. A useful alternative setting is default_crs = sf::st_crs(4326), which means x and y positions are interpreted as longitude and latitude, respectively, in the World Geodetic System 1984 (WGS84).

datum

CRS that provides datum to use when generating graticules.

label_graticule

Character vector indicating which graticule lines should be labeled where. Meridians run north-south, and the letters "N" and "S" indicate that they should be labeled on their north or south end points, respectively. Parallels run east-west, and the letters "E" and "W" indicate that they should be labeled on their east or west end points, respectively. Thus, label_graticule = "SW" would label meridians at their south end and parallels at their west end, whereas label_graticule = "EW" would label parallels at both ends and meridians not at all. Because meridians and parallels can in general intersect with any side of the plot panel, for any choice of label_graticule labels are not guaranteed to reside on only one particular side of the plot panel. Also, label_graticule can cause labeling artifacts, in particular if a graticule line coincides with the edge of the plot panel. In such circumstances, label_axes will generally yield better results and should be used instead.

This parameter can be used alone or in combination with label_axes.

label_axes

Character vector or named list of character values specifying which graticule lines (meridians or parallels) should be labeled on which side of the plot. Meridians are indicated by "E" (for East) and parallels by "N" (for North). Default is "--EN", which specifies (clockwise from the top) no labels on the top, none on the right, meridians on the bottom, and parallels on the left. Alternatively, this setting could have been specified with list(bottom = "E", left = "N").

This parameter can be used alone or in combination with label_graticule.

lims_method

Method specifying how scale limits are converted into limits on the plot region. Has no effect when default_crs = NULL. For a very non-linear CRS (e.g., a perspective centered around the North pole), the available methods yield widely differing results, and you may want to try various options. Methods currently implemented include "cross" (the default), "box", "orthogonal", and "geometry_bbox". For method "cross", limits along one direction (e.g., longitude) are applied at the midpoint of the other direction (e.g., latitude). This method avoids excessively large limits for rotated coordinate systems but means that sometimes limits need to be expanded a little further if extreme data points are to be included in the final plot region. By contrast, for method "box", a box is generated out of the limits along both directions, and then limits in projected coordinates are chosen such that the entire box is visible. This method can yield plot regions that are too large. Finally, method "orthogonal" applies limits separately along each axis, and method "geometry_bbox" ignores all limit information except the bounding boxes of any objects in the geometry aesthetic.

ndiscr

Number of segments to use for discretising graticule lines; try increasing this number when graticules look incorrect.

default

Is this the default coordinate system? If FALSE (the default), then replacing this coordinate system with another one creates a message alerting the user that the coordinate system is being replaced. If TRUE, that warning is suppressed.

clip

Should drawing be clipped to the extent of the plot panel? A setting of "on" (the default) means yes, and a setting of "off" means no. In most cases, the default of "on" should not be changed, as setting clip = "off" can cause unexpected results. It allows drawing of data points anywhere on the plot, including in the plot margins. If limits are set via xlim and ylim and some data points fall outside those limits, then those data points may show up in places such as the axes, the legend, the plot title, or the plot margins.

mapping

Set of aesthetic mappings created by aes() or aes_(). If specified and inherit.aes = TRUE (the default), it is combined with the default mapping at the top level of the plot. You must supply mapping if there is no plot mapping.

data

The data to be displayed in this layer. There are three options:

If NULL, the default, the data is inherited from the plot data as specified in the call to ggplot().

A data.frame, or other object, will override the plot data. All objects will be fortified to produce a data frame. See fortify() for which variables will be created.

A function will be called with a single argument, the plot data. The return value must be a data.frame, and will be used as the layer data. A function can be created from a formula (e.g. ~ head(.x, 10)).

stat

The statistical transformation to use on the data for this layer, as a string.

position

Position adjustment, either as a string, or the result of a call to a position adjustment function.

na.rm

If FALSE, the default, missing values are removed with a warning. If TRUE, missing values are silently removed.

show.legend

logical. Should this layer be included in the legends? NA, the default, includes if any aesthetics are mapped. FALSE never includes, and TRUE always includes.

You can also set this to one of "polygon", "line", and "point" to override the default legend.

inherit.aes

If FALSE, overrides the default aesthetics, rather than combining with them. This is most useful for helper functions that define both data and aesthetics and shouldn't inherit behaviour from the default plot specification, e.g. borders().

...

Other arguments passed on to layer(). These are often aesthetics, used to set an aesthetic to a fixed value, like colour = "red" or size = 3. They may also be parameters to the paired geom/stat.

parse

If TRUE, the labels will be parsed into expressions and displayed as described in ?plotmath.

nudge_x

Horizontal and vertical adjustment to nudge labels by. Useful for offsetting text from points, particularly on discrete scales. Cannot be jointly specified with position.

nudge_y

Horizontal and vertical adjustment to nudge labels by. Useful for offsetting text from points, particularly on discrete scales. Cannot be jointly specified with position.

label.padding

Amount of padding around label. Defaults to 0.25 lines.

label.r

Radius of rounded corners. Defaults to 0.15 lines.

label.size

Size of label border, in mm.

fun.geometry

A function that takes a sfc object and returns a sfc_POINT with the same length as the input. If NULL, function(x) sf::st_point_on_surface(sf::st_zm(x)) will be used. Note that the function may warn about the incorrectness of the result if the data is not projected, but you can ignore this except when you really care about the exact locations.

check_overlap

If TRUE, text that overlaps previous text in the same layer will not be plotted. check_overlap happens at draw time and in the order of the data. Therefore data should be arranged by the label column before calling geom_text(). Note that this argument is not supported by geom_label().

geom

The geometric object to use display the data

Geometry aesthetic

geom_sf() uses a unique aesthetic: geometry, giving an column of class sfc containing simple features data. There are three ways to supply the geometry aesthetic:

  • Do nothing: by default geom_sf() assumes it is stored in the geometry column.

  • Explicitly pass an sf object to the data argument. This will use the primary geometry column, no matter what it's called.

  • Supply your own using aes(geometry = my_column)

Unlike other aesthetics, geometry will never be inherited from the plot.

CRS

coord_sf() ensures that all layers use a common CRS. You can either specify it using the crs param, or coord_sf() will take it from the first layer that defines a CRS.

Combining sf layers and regular geoms

Most regular geoms, such as geom_point(), geom_path(), geom_text(), geom_polygon() etc. will work fine with coord_sf(). However when using these geoms, two problems arise. First, what CRS should be used for the x and y coordinates used by these non-sf geoms? The CRS applied to non-sf geoms is set by the default_crs parameter, and it defaults to NULL, which means positions for non-sf geoms are interpreted as projected coordinates in the coordinate system set by the crs parameter. This setting allows you complete control over where exactly items are placed on the plot canvas, but it may require some understanding of how projections work and how to generate data in projected coordinates. As an alternative, you can set default_crs = sf::st_crs(4326), the World Geodetic System 1984 (WGS84). This means that x and y positions are interpreted as longitude and latitude, respectively. You can also specify any other valid CRS as the default CRS for non-sf geoms.

The second problem that arises for non-sf geoms is how straight lines should be interpreted in projected space when default_crs is not set to NULL. The approach coord_sf() takes is to break straight lines into small pieces (i.e., segmentize them) and then transform the pieces into projected coordinates. For the default setting where x and y are interpreted as longitude and latitude, this approach means that horizontal lines follow the parallels and vertical lines follow the meridians. If you need a different approach to handling straight lines, then you should manually segmentize and project coordinates and generate the plot in projected coordinates.

See Also

stat_sf_coordinates()

Examples

Run this code
# NOT RUN {
if (requireNamespace("sf", quietly = TRUE)) {
nc <- sf::st_read(system.file("shape/nc.shp", package = "sf"), quiet = TRUE)
ggplot(nc) +
  geom_sf(aes(fill = AREA))

# If not supplied, coord_sf() will take the CRS from the first layer
# and automatically transform all other layers to use that CRS. This
# ensures that all data will correctly line up
nc_3857 <- sf::st_transform(nc, 3857)
ggplot() +
  geom_sf(data = nc) +
  geom_sf(data = nc_3857, colour = "red", fill = NA)

# Unfortunately if you plot other types of feature you'll need to use
# show.legend to tell ggplot2 what type of legend to use
nc_3857$mid <- sf::st_centroid(nc_3857$geometry)
ggplot(nc_3857) +
  geom_sf(colour = "white") +
  geom_sf(aes(geometry = mid, size = AREA), show.legend = "point")

# You can also use layers with x and y aesthetics. To have these interpreted
# as longitude/latitude you need to set the default CRS in coord_sf()
ggplot(nc_3857) +
  geom_sf() +
  annotate("point", x = -80, y = 35, colour = "red", size = 4) +
  coord_sf(default_crs = sf::st_crs(4326))

# Thanks to the power of sf, a geom_sf nicely handles varying projections
# setting the aspect ratio correctly.
library(maps)
world1 <- sf::st_as_sf(map('world', plot = FALSE, fill = TRUE))
ggplot() + geom_sf(data = world1)

world2 <- sf::st_transform(
  world1,
  "+proj=laea +y_0=0 +lon_0=155 +lat_0=-90 +ellps=WGS84 +no_defs"
)
ggplot() + geom_sf(data = world2)

# To add labels, use geom_sf_label().
ggplot(nc_3857[1:3, ]) +
   geom_sf(aes(fill = AREA)) +
   geom_sf_label(aes(label = NAME))
}
# }

Run the code above in your browser using DataLab