image2D extends R's image function. Input can be a matrix (2-D) or an array (3-D) or a list.
contour2D extends R's contour function.
image2D (z, ...)
contour2D (z, x = seq(0, 1, length.out = nrow(z)),
y = seq(0, 1, length.out = ncol(z)), ...,
col = NULL, NAcol = NULL,
colkey = NULL, resfac = 1,
clab = NULL, add = FALSE, plot = TRUE)# S3 method for matrix
image2D(z, x = seq(0, 1, length.out = nrow(z)),
y = seq(0, 1, length.out = ncol(z)), colvar = z, ...,
col = NULL, NAcol = "white", breaks = NULL,
border = NA, facets = TRUE, contour = FALSE,
colkey = NULL, resfac = 1, clab = NULL,
lighting = FALSE, shade = NA, ltheta = -135, lphi = 0,
theta = 0, rasterImage = FALSE,
add = FALSE, plot = TRUE)
# S3 method for array
image2D(z, margin = c(1, 2), subset, ask = NULL, ...)
# S3 method for list
image2D(z, ...)
Returns nothing.
Matrix (2-D) or array (3-D) or a list with matrices or arrays,
with z-values. By default colvar is equal to z, hence
z also defines the variable used to color the image.
Only when shade or lighting is toggled on does it make
sense to use z different from colvar.
Vectors or matrix with x and y values.
If a vector x should be of length equal to nrow(z) and
y should be of length equal to ncol(z).
If a matrix (only for image2D), they should have
the same dimension as z or be of dimension = dim(z)+1.
Only used when shade or lighting is toggled on.
The variable used to color the image.
Color palette to be used for the image function or for the contours. See details.
Color to be used for NA values of z; for image2D, the default is ``white'',
for contour2D, the default is to do nothing.
a set of finite numeric breakpoints for the colors; must have one more breakpoint than color and be in increasing order. Unsorted vectors will be sorted, with a warning.
If TRUE, then a contour plot will be
added to the image plot, unless x, y are a matrix.
Also allowed is to pass a list with arguments for the
contour function.
A logical, NULL (default), or a list with parameters
for the color key (legend). List parameters should be one of
side, plot, length, width, dist, shift, addlines, col.clab, cex.clab,
side.clab, line.clab, adj.clab, font.clab
and the axis parameters at, labels, tick, line, pos, outer, font, lty, lwd,
lwd.ticks, col.box, col.axis, col.ticks, hadj, padj, cex.axis, mgp, tck, tcl, las.
The defaults for the parameters are side = 4, plot = TRUE, length = 1, width = 1,
dist = 0, shift = 0, addlines = FALSE, col.clab = NULL, cex.clab = par("cex.lab"),
side.clab = NULL, line.clab = NULL, adj.clab = NULL, font.clab = NULL)
See colkey.
The default is to draw the color key on side = 4, i.e. in the right margin.
If colkey = NULL then a color key will be added only if col is a vector.
Setting colkey = list(plot = FALSE) will create room for the color key
without drawing it.
if colkey = FALSE, no color key legend will be added.
Only if colkey is not NULL or FALSE,
the label to be written on top of the color key.
The label will be written at the same level as the main title.
To lower it, clab can be made a vector, with the first values empty
strings.
Resolution factor, one value or a vector of two numbers, for
the x and y- values respectively. A value > 1 will increase the
resolution. For instance, if resfac equals 3 then for each
adjacent pair of x- and y-values, z will be interpolated to two intermediary points.
This uses simple linear interpolation. If resfac is one number then
the resolution will be increased similarly in x and y-direction.
If not FALSE the facets will be illuminated, and colors may
appear more bright. To switch on lighting, the argument lighting
should be either set to TRUE (using default settings) or it can be a
list with specifications of one of the following:
ambient, diffuse, specular, exponent, sr and alpha.
Will overrule shade not equal to NA.
See examples in jet.col.
the degree of shading of the surface facets. Values of shade close to one yield shading similar to a point light source model and values close to zero produce no shading. Values in the range 0.5 to 0.75 provide an approximation to daylight illumination. See persp.
if finite values are specified for ltheta and
lphi, the surface is shaded as though it was being illuminated from
the direction specified by azimuth ltheta and colatitude lphi.
See persp.
The angle defining the azimuthal direction. Implemented for consistency with the other functions based on persp.
The color of the lines drawn around the surface facets.
The default, NA, will disable the drawing of borders.
If TRUE, then col denotes the color of the surface facets.
If FALSE, then the surface facets are colored ``white'' and the border
will be colored as specified by col. If NA then the facets will be
transparent.
It is usually faster to draw with facets = FALSE.
If TRUE, the function rasterImage will be
used for plotting rather than image or polygon. This requires
the x and y to be a vector with equally spaced elements.
Note that by default, rasterImage linearly interpolates the image,
so it will appear smoother.
Logical. If TRUE, then the points will be added to the current plot.
If FALSE a new plot is started.
Logical. If TRUE (default), a plot is created,
otherwise (for 3D plots) the viewing transformation matrix is returned (as invisible).
A vector giving the subscripts which the image
function will be applied over.
The image function will loop over the index that is not in margin.
For instance, c(1, 2), indicates to plot rows(x) and columns(y) and to
loop over index 3;
c(2, 1) will do the same but the image will be transposed.
margin should be a vector with two numbers inbetween 1, and 3.
A logical; if TRUE, the user is asked before each plot,
if NULL the user is only asked if more than one page of plots is
necessary and the current graphics device is set interactive,
see par(ask) and dev.interactive.
Either a logical expression indicating over which elements to loop,
or a vector or integers denoting the indices of the elements over which to loop.
Missing values are taken as FALSE.
additional arguments passed to the plotting methods image, rasterImage, polygon and contour.
alpha can be given a value inbetween 0 and 1 to make colors transparent.
The arguments after ... must be matched exactly.
Karline Soetaert <karline.soetaert@nioz.nl>
image2D is an extension to the default image plot that has
the possibility to add a color key and contourlines, and to increase the
resolution in order to make smoother images. It also uses a different color
scheme, it can deal with decreasing x- and y- values and x and y can be
a matrix. In the latter case, the image will be drawn as a set of polygons;
if x and y are a vector, either R-function image or
rasterImage will be used.
image2D.array and image2D.list are versions that
accept a 3 dimensional array respectively a list with z-matrices
as their first argument to produce multiple plots.
For argument col of the image2D function,
both NA and NULL are allowed,
in which case the color will be white, and no color key will be drawn.
To set the ranges of the z-variable, both arguments zlim (as in image)
and clim (as in the other plot3D functions) are accepted.
Upon returning from the image2D and contour2D functions, the figure coordinates are defined
by the main figure (excluding the color key). Thus, one can safely add other
plotting elements.
# save plotting parameters
pm <- par("mfrow")
## =======================================================================
## Difference between x or y a vector/matrix and rasterImage
## =======================================================================
par(mfrow = c(2, 2))
x <- y <- 1:3
z <- matrix (nrow = 3, ncol = 3, data = 1:9)
image2D(z, x, y, border = "black")
image2D(z, x, y, rasterImage = TRUE, border = "black")
image2D(z, x = matrix(nrow = 3, ncol = 3, data = rep(x, times = 3)),
y, border = "black")
image2D(z, x, y, border = "black", theta = 45)
## =======================================================================
## shading, light, adding contours, points and lines
## =======================================================================
par(mfrow = c(2, 2))
nr <- nrow(volcano)
nc <- ncol(volcano)
image2D(volcano, x = 1:nr, y = 1:nc, lighting = TRUE,
main = "volcano", clab = "height, m")
abline(v = seq(10, 80, by = 10))
abline(h = seq(10, 60, by = 10))
points(50, 30, pch = 3, cex = 5, lwd = 3, col = "white")
image2D(z = volcano, x = 1:nr, y = 1:nc, lwd = 2, shade = 0.2,
main = "volcano", clab = "height, m")
image2D(volcano, x = 1:nr, y = 1:nc, contour = TRUE, shade = 0.5, lphi = 0,
col = "lightblue", main = "volcano")
breaks <- seq(90, 200, by = 10)
image2D(volcano, x = 1:nr, y = 1:nc, col = jet.col(length(breaks)-1),
main = "volcano", clab = "height, m", breaks = breaks)
## =======================================================================
## Contour plots
## =======================================================================
par(mfrow = c(2, 2))
V <- volcano - 150
# default, no color key
contour2D(z = V, colkey = FALSE, lwd = 2)
# imposed levels
contour2D(z = V, lwd = 2, levels = seq(-40, 40, by = 20))
# negative levels dashed
contour2D(z = V, col = "black", lwd = 2,
levels = seq(0, 40, by = 20))
contour2D(z = V, col = "black", lwd = 2, lty = 2,
levels = seq(-40, -20, by = 20), add = TRUE)
# no labels, imposed number of levels, colorkey
contour2D(z = V, lwd = 2, nlevels = 20, drawlabels = FALSE,
colkey = list(at = seq(-40, 40, by = 20)))
## =======================================================================
## A large data set, input is an array
## =======================================================================
par(mfrow = c(1, 1))
image2D(z = Oxsat$val[, , 1], x = Oxsat$lon, y = Oxsat$lat,
main = "surface oxygen saturation data 2005", NAcol = "black",
clab = c("","","%"))
# images at first 9 depths - use subset to select them
image2D(z = Oxsat$val, subset = 1:9,
x = Oxsat$lon, y = Oxsat$lat,
margin = c(1, 2), NAcol = "black",
xlab = "longitude", ylab = "latitude",
zlim = c(0, 115),
main = paste("depth ", Oxsat$depth[1:9], " m"),
mfrow = c(3, 3))
# images at latitude - depth section - increase resolution
z <- Oxsat$val[, Oxsat$lat > - 5 & Oxsat$lat < 5, ]
image2D(z = z, x = Oxsat$lon, y = Oxsat$depth,
margin = c(1, 3), NAcol = "black",
resfac = 3, ylim = c(5000, 0))
# show position of transects
image2D(z = Oxsat$val[ , ,1],
x = Oxsat$lon, y = Oxsat$lat,
NAcol = "black")
abline(h = Oxsat$lat[Oxsat$lat > - 5 & Oxsat$lat < 5])
## =======================================================================
## Image of a list of matrices
## =======================================================================
listvolcano <- list(volcano = volcano, logvolcano = log(volcano))
image2D(listvolcano, x = 1:nr, y = 1:nc, contour = TRUE,
main = c("volcano", "log(volcano)"),
clab = list("height, m", "log(m)"),
zlim = list(c(80, 200), c(4.4, 5.5)))
## =======================================================================
## Image of a list of arrays
## =======================================================================
if (FALSE) {
# crude conversion from oxsat to oxygen
listoxygen <- list(Oxsat$val, Oxsat$val/100 * 360)
image2D(z = listoxygen,
x = Oxsat$lon, y = Oxsat$lat,
margin = c(1, 2), NAcol = "black",
main = c("Oxygen saturation ", " Oxygen concentration"),
mtext = paste("depth ", Oxsat$depth, " m")
)
}
## =======================================================================
## 'x', 'y' and 'z' are matrices
## =======================================================================
par(mfrow = c(2, 1))
# tilted x- and y-coordinates of 'volcano'
volcx <- matrix(nrow = 87, ncol = 61, data = rep(1:87, times=61))
volcx <- volcx + matrix(nrow = 87, ncol = 61, byrow = TRUE,
data = rep(seq(0., 15, length.out=61), times=87))
volcy <- matrix(ncol = 87, nrow = 61, data = rep(1:61, times=87))
volcy <- t(volcy + matrix(ncol = 87, nrow = 61, byrow = TRUE,
data = rep(seq(0., 25, length.out=87), times=61)))
image2D(volcano, x = volcx, y = volcy)
# x and y can also be of dimension dim(z)+1:
if (FALSE) {
# tilted x- and y-coordinates of 'volcano'
volcx <- matrix(nrow = 88, ncol = 62, data = rep(1:88, times=62))
volcx <- volcx + matrix(nrow = 88, ncol = 62, byrow = TRUE,
data = rep(seq(0., 15, length.out=62), times=88))
volcy <- matrix(ncol = 88, nrow = 62, data = rep(1:62, times=88))
volcy <- t(volcy + matrix(ncol = 88, nrow = 62, byrow = TRUE,
data = rep(seq(0., 25, length.out=88), times=62)))
image2D(volcano, x = volcx, y = volcy)
}
# use of panel function
image2D(volcano, x = volcx, y = volcy, NAcol = "black",
panel.first = substitute(box(col = "lightgrey", lwd = 30)))
## =======================================================================
## Image with NAs and logs
## =======================================================================
par(mfrow = c(2, 2))
# normal volcano
image2D(volcano, clab = c("height", "m"))
# logarithmic z-axis
image2D(volcano, log = "z", clab = c("height", "m"),
main = "log='z'")
# Including NAs
VOLC <- volcano - 110
VOLC [VOLC <= 0] <- NA
image2D(VOLC, main = "including NAs and rescaled")
# both
image2D(VOLC, NAcol = "black", log = "z", zlim = c(1, 100),
main = "NAs and log = 'z'")
## =======================================================================
## Image with contour specification (alpha sets the transparency)
## =======================================================================
par(mfrow = c(1, 1))
image2D(volcano, shade = 0.2, rasterImage = TRUE,
contour = list(col = "white", labcex = 0.8, lwd = 3, alpha = 0.5))
# same:
if (FALSE) {
image2D(z = volcano, shade = 0.2, rasterImage = TRUE)
contour2D(z = volcano, col = "white", labcex = 0.8,
lwd = 3, alpha = 0.5, add = TRUE)
}
# reset plotting parameters
par(mfrow = pm)
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