Streamlines are paths that are always tangential to a vector field. In the case of a steady field, it's identical to the path of a massless particle that moves with the "flow".
Usage
geom_streamline(
mapping = NULL,
data = NULL,
stat = "streamline",
position = "identity",
...,
L = 5,
min.L = 0,
res = 1,
S = NULL,
dt = NULL,
xwrap = NULL,
ywrap = NULL,
skip = 1,
skip.x = skip,
skip.y = skip,
n = NULL,
nx = n,
ny = n,
jitter = 1,
jitter.x = jitter,
jitter.y = jitter,
arrow.angle = 6,
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 = TRUE,
show.legend = NA,
inherit.aes = TRUE
)
stat_streamline(
mapping = NULL,
data = NULL,
geom = "streamline",
position = "identity",
...,
L = 5,
min.L = 0,
res = 1,
S = NULL,
dt = NULL,
xwrap = NULL,
ywrap = NULL,
skip = 1,
skip.x = skip,
skip.y = skip,
n = NULL,
nx = n,
ny = n,
jitter = 1,
jitter.x = jitter,
jitter.y = jitter,
arrow.angle = 6,
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 = TRUE,
show.legend = NA,
inherit.aes = TRUE
)
Arguments
- mapping
Set of aesthetic mappings created by
aes()
. If specified andinherit.aes = TRUE
(the default), it is combined with the default mapping at the top level of the plot. You must supplymapping
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 toggplot()
.A
data.frame
, or other object, will override the plot data. All objects will be fortified to produce a data frame. Seefortify()
for which variables will be created.A
function
will be called with a single argument, the plot data. The return value must be adata.frame
, and will be used as the layer data. Afunction
can be created from aformula
(e.g.~ head(.x, 10)
).- stat
The statistical transformation to use on the data for this layer. When using a
geom_*()
function to construct a layer, thestat
argument can be used the override the default coupling between geoms and stats. Thestat
argument accepts the following:A
Stat
ggproto subclass, for exampleStatCount
.A string naming the stat. To give the stat as a string, strip the function name of the
stat_
prefix. For example, to usestat_count()
, give the stat as"count"
.For more information and other ways to specify the stat, see the layer stat documentation.
- position
A position adjustment to use on the data for this layer. This can be used in various ways, including to prevent overplotting and improving the display. The
position
argument accepts the following:The result of calling a position function, such as
position_jitter()
. This method allows for passing extra arguments to the position.A string naming the position adjustment. To give the position as a string, strip the function name of the
position_
prefix. For example, to useposition_jitter()
, give the position as"jitter"
.For more information and other ways to specify the position, see the layer position documentation.
- ...
Other arguments passed on to
layer()
'sparams
argument. These arguments broadly fall into one of 4 categories below. Notably, further arguments to theposition
argument, or aesthetics that are required can not be passed through...
. Unknown arguments that are not part of the 4 categories below are ignored.Static aesthetics that are not mapped to a scale, but are at a fixed value and apply to the layer as a whole. For example,
colour = "red"
orlinewidth = 3
. The geom's documentation has an Aesthetics section that lists the available options. The 'required' aesthetics cannot be passed on to theparams
. Please note that while passing unmapped aesthetics as vectors is technically possible, the order and required length is not guaranteed to be parallel to the input data.When constructing a layer using a
stat_*()
function, the...
argument can be used to pass on parameters to thegeom
part of the layer. An example of this isstat_density(geom = "area", outline.type = "both")
. The geom's documentation lists which parameters it can accept.Inversely, when constructing a layer using a
geom_*()
function, the...
argument can be used to pass on parameters to thestat
part of the layer. An example of this isgeom_area(stat = "density", adjust = 0.5)
. The stat's documentation lists which parameters it can accept.The
key_glyph
argument oflayer()
may also be passed on through...
. This can be one of the functions described as key glyphs, to change the display of the layer in the legend.
- L,
typical length of a streamline in x and y units
- min.L
minimum length of segments to show
- res,
resolution parameter (higher numbers increases the resolution)
- S
optional numeric number of timesteps for integration
- dt
optional numeric size "timestep" for integration
- xwrap, ywrap
vector of length two used to wrap the circular dimension.
- skip, skip.x, skip.y
numeric specifying number of gridpoints not to draw in the x and y direction
- n, nx, ny
optional numeric indicating the number of points to draw in the x and y direction (replaces
skip
if notNULL
)- jitter, jitter.x, jitter.y
amount of jitter of the starting points
- arrow.length, arrow.angle, arrow.ends, arrow.type
parameters passed to grid::arrow
- arrow
specification for arrow heads, as created by
grid::arrow()
.- lineend
Line end style (round, butt, square).
- na.rm
If
FALSE
, the default, missing values are removed with a warning. IfTRUE
, 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, andTRUE
always includes. It can also be a named logical vector to finely select the aesthetics to display.- 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()
.- geom
The geometric object to use to display the data for this layer. When using a
stat_*()
function to construct a layer, thegeom
argument can be used to override the default coupling between stats and geoms. Thegeom
argument accepts the following:A
Geom
ggproto subclass, for exampleGeomPoint
.A string naming the geom. To give the geom as a string, strip the function name of the
geom_
prefix. For example, to usegeom_point()
, give the geom as"point"
.For more information and other ways to specify the geom, see the layer geom documentation.
Details
Streamlines are computed by simple integration with a forward Euler method.
By default, stat_streamline()
computes dt
and S
from L
, res
,
the resolution of the grid and the mean magnitude of the field. S
is
then defined as the number of steps necessary to make a streamline of length
L
under an uniform mean field and dt
is chosen so that each step is no
larger than the resolution of the data (divided by the res
parameter). Be
aware that this rule of thumb might fail in field with very skewed distribution
of magnitudes.
Alternatively, L
and/or res
are ignored if S
and/or dt
are specified
explicitly. This not only makes it possible to fine-tune the result but also
divorces the integration parameters from the properties of the data and makes
it possible to compare streamlines between different fields.
The starting grid is a semi regular grid defined, either by the resolution of the
field and the skip.x
and skip.y
parameters o the nx
and ny
parameters,
jittered by an amount proportional to the resolution of the data and the
jitter.x
and jitter.y
parameters.
It might be important that the units of the vector field are compatible to the units
of the x and y dimensions. For example, passing dx
and dy
in m/s on a
longitude-latitude grid will might misleading results (see spherical).
Missing values are not permitted and the field must be defined on a regular grid, for now.
Aesthetics
stat_streamline
understands the following aesthetics (required aesthetics are in bold)
x
y
dx
dy
alpha
colour
linetype
size
Computed variables
- step
step in the simulation
- dx
dx at each location of the streamline
- dy
dy at each location of the streamline
See also
Other ggplot2 helpers:
MakeBreaks()
,
WrapCircular()
,
geom_arrow()
,
geom_contour2()
,
geom_contour_fill()
,
geom_label_contour()
,
geom_relief()
,
guide_colourstrip()
,
map_labels
,
reverselog_trans()
,
scale_divergent
,
scale_longitude
,
stat_na()
,
stat_subset()
Examples
if (FALSE) { # \dontrun{
library(data.table)
library(ggplot2)
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_contour2(aes(z = gh.z), xwrap = c(0, 360)) +
geom_streamline(aes(dx = dlon(u, lat), dy = dlat(v)), L = 60,
xwrap = c(0, 360)))
# The circular parameter is particularly important for polar coordinates
g + coord_polar()
# If u and v are not converted into degrees/second, the resulting
# streamlines have problems, specially near the pole.
ggplot(geopotential, aes(lon, lat)) +
geom_contour(aes(z = gh.z)) +
geom_streamline(aes(dx = u, dy = v), L = 50)
# The step variable can be mapped to size or alpha to
# get cute "drops". It's important to note that after_stat(dx) (the calculated variable)
# is NOT the same as dx (from the data).
ggplot(geopotential, aes(lon, lat)) +
geom_streamline(aes(dx = dlon(u, lat), dy = dlat(v), alpha = after_stat(step),
color = sqrt(after_stat(dx^2) + after_stat(dy^2)),
size = after_stat(step)),
L = 40, xwrap = c(0, 360), res = 2, arrow = NULL,
lineend = "round") +
scale_size(range = c(0, 0.6))
# Using topographic information to simulate "rivers" from slope
topo <- GetTopography(295, -55+360, -30, -42, res = 1/20) # needs internet!
topo[, c("dx", "dy") := Derivate(h ~ lon + lat)]
topo[h <= 0, c("dx", "dy") := 0]
# See how in this example the integration step is too coarse in the
# western montanous region where the slope is much higher than in the
# flatlands of La Pampa at in the east.
ggplot(topo, aes(lon, lat)) +
geom_relief(aes(z = h), interpolate = TRUE, data = topo[h >= 0]) +
geom_contour(aes(z = h), breaks = 0, color = "black") +
geom_streamline(aes(dx = -dx, dy = -dy), L = 10, skip = 3, arrow = NULL,
color = "#4658BD") +
coord_quickmap()
} # }