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Parametrization of ggplot2::geom_segment either by location and displacement
or by magnitude and angle with default arrows. geom_arrow() is the same as
geom_vector() but defaults to preserving the direction under coordinate
transformation and different plot ratios.
geom_arrow(
mapping = NULL,
data = NULL,
stat = "arrow",
position = "identity",
...,
start = 0,
direction = c("ccw", "cw"),
pivot = 0.5,
preserve.dir = TRUE,
min.mag = 0,
skip = 0,
skip.x = skip,
skip.y = skip,
arrow.angle = 15,
arrow.length = 0.5,
arrow.ends = "last",
arrow.type = "closed",
arrow = grid::arrow(arrow.angle, grid::unit(arrow.length, "lines"), ends =
arrow.ends, type = arrow.type),
lineend = "butt",
na.rm = FALSE,
show.legend = NA,
inherit.aes = TRUE
)geom_vector(
mapping = NULL,
data = NULL,
stat = "arrow",
position = "identity",
...,
start = 0,
direction = c("ccw", "cw"),
pivot = 0.5,
preserve.dir = FALSE,
min.mag = 0,
skip = 0,
skip.x = skip,
skip.y = skip,
arrow.angle = 15,
arrow.length = 0.5,
arrow.ends = "last",
arrow.type = "closed",
arrow = grid::arrow(arrow.angle, grid::unit(arrow.length, "lines"), ends =
arrow.ends, type = arrow.type),
lineend = "butt",
na.rm = FALSE,
show.legend = NA,
inherit.aes = TRUE
)
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)).
The statistical transformation to use on the data for this layer, as a string.
Position adjustment, either as a string, or the result of a call to a position adjustment function.
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.
starting angle for rotation in degrees
direction of rotation (counter-clockwise or clockwise)
numeric indicating where to pivot the arrow where 0 means at the beginning and 1 means at the end.
logical indicating whether to preserve direction or not
minimum magnitude for plotting vectors
numeric specifying number of gridpoints not to draw in the x and y direction
parameters passed to grid::arrow
specification for arrow heads, as created by arrow().
Line end style (round, butt, square).
If FALSE, the default, missing values are removed with
a warning. If TRUE, missing values are silently removed.
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.
It can also be a named logical vector to finely select the aesthetics to
display.
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().
geom_vector understands the following aesthetics (required aesthetics are in bold)
x
y
either mag and angle, or dx and dy
alpha
colour
linetype
size
lineend
Direction and start allows to work with different standards. For the
meteorological standard, for example, use star = -90 and direction = "cw".
Other ggplot2 helpers:
DivideTimeseries(),
MakeBreaks(),
WrapCircular(),
geom_contour2(),
geom_contour_fill(),
geom_label_contour(),
geom_relief(),
geom_streamline(),
guide_colourstrip(),
map_labels,
reverselog_trans(),
scale_divergent,
scale_longitude,
stat_na(),
stat_subset()
# NOT RUN {
library(data.table)
library(ggplot2)
data(seals)
# If the velocity components are in the same units as the axis,
# geom_vector() (or geom_arrow(preserve.dir = TRUE)) might be a better option
ggplot(seals, aes(long, lat)) +
geom_arrow(aes(dx = delta_long, dy = delta_lat), skip = 1, color = "red") +
geom_vector(aes(dx = delta_long, dy = delta_lat), skip = 1) +
scale_mag()
data(geopotential)
geopotential <- copy(geopotential)[date == date[1]]
geopotential[, gh.z := Anomaly(gh), by = .(lat)]
geopotential[, c("u", "v") := GeostrophicWind(gh.z, lon, lat)]
(g <- ggplot(geopotential, aes(lon, lat)) +
geom_arrow(aes(dx = dlon(u, lat), dy = dlat(v)), skip.x = 3, skip.y = 2,
color = "red") +
geom_vector(aes(dx = dlon(u, lat), dy = dlat(v)), skip.x = 3, skip.y = 2) +
scale_mag(max_size = 2, guide = "none"))
# A dramatic illustration of the difference between arrow and vector
g + coord_polar()
# When plotting winds in a lat-lon grid, a good way to have both
# the correct direction and an interpretable magnitude is to define
# the angle by the longitud and latitude displacement and the magnitude
# by the wind velocity. That way arrows are always parallel to streamlines
# and their magnitude are in the correct units.
ggplot(geopotential, aes(lon, lat)) +
geom_contour(aes(z = gh.z)) +
geom_vector(aes(angle = atan2(dlat(v), dlon(u, lat))*180/pi,
mag = Mag(v, u)), skip = 1, pivot = 0.5) +
scale_mag()
# Sverdrup transport
library(data.table)
b <- 10
d <- 10
grid <- as.data.table(expand.grid(x = seq(1, d, by = 0.5),
y = seq(1, b, by = 0.5)))
grid[, My := -sin(pi*y/b)*pi/b]
grid[, Mx := -pi^2/b^2*cos(pi*y/b)*(d - x)]
ggplot(grid, aes(x, y)) +
geom_arrow(aes(dx = Mx, dy = My))
# Due to limitations in ggplot2 (see: https://github.com/tidyverse/ggplot2/issues/4291),
# if you define the vector with the dx and dy aesthetics, you need
# to explicitly add scale_mag() in order to show the arrow legend.
ggplot(grid, aes(x, y)) +
geom_arrow(aes(dx = Mx, dy = My)) +
scale_mag()
# Alternative, use Mag and Angle.
ggplot(grid, aes(x, y)) +
geom_arrow(aes(mag = Mag(Mx, My), angle = Angle(Mx, My)))
# }
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