I am relatively new in R and its packages. I am using the adehabitatHS package to compute and plot some selectivity data. Nevertheless I am having some troubles, mainly while plotting.
The first one is that by default the program uses the name "habitat" for the x-axis and I need to use "Msp" instead.
The second one is that I need to edit the first (top left) and specially the third (bottom left) plots. Since the legend for the third plot is too big and also I would like to sort the values. Does anyone know how to handle this kind of plots, is it possible to do it?
Please find attached my code, a copy of the dataset and the plot.
Dataset
Code:
library(adehabitatHS)
pse<-read.table("pseudos.txt", header=T)
attach(pse)
names(pse)
head(pse)
(wiRatio <- widesI(Diet, Dis))
png(filename = "plotpseudos3.png", width = 500, height = 500)
opar <- par(mfrow=c(2,2))
plot(wiRatio)
par(opar)
dev.off()
You have several options. You can look at the structure of your wiRatio object using str() function and extract the appropriate elements for plotting.
Or, you can modify the source pretty easily. The labels in the plot method for object of class wi uses names of values from that object (names(wi)) so this is where you need to dig. Here is the modified function, which I renamed to distinguish it from the original.
plotWi <- function (x, caxis = 0.7, clab = 1, ylog = FALSE, errbar = c("CI", "SE"),
main = "Manly selectivity measure", noorder = TRUE,
my.labels, ...)
{
errbar <- match.arg(errbar)
opar <- par(ask = TRUE)
on.exit(par(opar))
if (!inherits(x, "wi"))
stop("x should be of class wi")
eb <- ifelse(errbar == "SE", 1, abs(qnorm(x$alpha/length(x$wi))))
if (noorder)
wi <- sort(x$wi, decreasing = TRUE)
else wi <- x$wi
if ((any(wi == 0)) & (ylog)) {
warning("zero values in x, ylog has been set to FALSE")
ylog <- FALSE
}
logy <- ifelse(ylog, "y", "")
if (noorder)
sewi <- x$se.wi[order(x$wi, decreasing = TRUE)]
else sewi <- x$se.wi
sewi[is.na(sewi)] <- 0
nwi <- names(wi)
rgy <- range(c(wi, wi + eb * sewi, wi - eb * sewi))
textleg <- paste("Selection ratios (+/-", errbar, ")")
if (inherits(x, "wiII") | inherits(x, "wiIII"))
textleg <- paste("Global Selection ratios (+/-", errbar,
")")
if (!ylog)
rgy[1] <- 0
plot(wi, axes = FALSE, ylim = rgy, ty = "n", xlab = "", ylab = textleg,
cex.lab = clab, log = logy, main = main, ...)
axis(side = 1, at = c(1:length(wi)), labels = my.labels,
cex.axis = caxis, las = 2)
axis(side = 2, cex.axis = caxis)
box()
points(c(1:length(wi)), wi, pch = 16)
lines(1:length(wi), wi)
abline(h = 1, lwd = 2)
for (i in 1:length(wi)) {
lines(c(i, i), c(wi[i] - eb * sewi[i], wi[i] + eb * sewi[i]))
lines(c(i - 0.1, i + 0.1), c(wi[i] - eb * sewi[i], wi[i] -
eb * sewi[i]))
lines(c(i - 0.1, i + 0.1), c(wi[i] + eb * sewi[i], wi[i] +
eb * sewi[i]))
}
if (inherits(x, "wiI")) {
if (noorder)
Bi <- x$Bi[order(x$wi, decreasing = TRUE)]
else Bi <- x$Bi
plot(Bi, axes = FALSE, ty = "n", xlab = "", cex.lab = clab,
main = "Scaled selection ratios", ...)
axis(side = 1, at = c(1:length(wi)), labels = my.labels,
cex.axis = caxis, las = 2)
axis(side = 2, cex.axis = caxis)
lines(1:length(wi), Bi)
points(c(1:length(wi)), Bi, pch = 16)
box()
if (noorder) {
ut <- x$used.prop[order(x$wi, decreasing = TRUE)]
seu <- x$se.used[order(x$wi, decreasing = TRUE)]
sea <- x$se.avail[order(x$wi, decreasing = TRUE)]
av <- x$avail.prop[order(x$wi, decreasing = TRUE)]
}
else {
ut <- x$used.prop
seu <- x$se.used
sea <- x$se.avail
av <- x$avail.prop
}
rgy <- range(c(av, ut - eb * seu, ut + eb * seu, av -
eb * sea, av + eb * sea))
rgy <- c(rgy[1], rgy[2] + (rgy[2] - rgy[1])/4)
plot(ut, axes = FALSE, ty = "n", xlab = "", cex.lab = clab,
ylim = rgy, main = "Used and available proportions",
ylab = paste("Porportion (+/-", errbar, ")"), ...)
points(1:length(wi) - 0.05, av, pch = 16)
points(1:length(wi) + 0.05, ut, pch = 2)
for (i in 1:length(wi)) {
lines(c(i, i) + 0.05, c(ut[i] - eb * seu[i], ut[i] +
eb * seu[i]))
lines(c(i - 0.02, i + 0.02) + 0.05, c(ut[i] - eb *
seu[i], ut[i] - eb * seu[i]))
lines(c(i - 0.02, i + 0.02) + 0.05, c(ut[i] + eb *
seu[i], ut[i] + eb * seu[i]))
}
if (!x$avknown) {
for (i in 1:length(wi)) {
lines(c(i, i) - 0.05, c(av[i] - eb * sea[i],
av[i] + eb * sea[i]))
lines(c(i - 0.02, i + 0.02) - 0.05, c(av[i] -
eb * sea[i], av[i] - eb * sea[i]))
lines(c(i - 0.02, i + 0.02) - 0.05, c(av[i] +
eb * sea[i], av[i] + eb * sea[i]))
}
}
axis(side = 1, at = c(1:length(wi)), labels = my.labels,
cex.axis = caxis, las = 2)
axis(side = 2, cex.axis = caxis)
box()
legend(1, rgy[2], c("Available", "Used"), pch = c(16,
2), cex = clab)
}
else {
if (noorder)
wij <- x$wij[, order(x$wi, decreasing = TRUE)]
else wij <- x$wij
iii <- as.vector(wij)
rgy <- range(iii[!is.na(iii)])
plot(1, ty = "n", ylim = rgy, xlim = c(1, ncol(wij)),
xlab = "", ylab = paste("Selection ratios"), cex.lab = clab,
log = logy, axes = FALSE, main = main, ...)
axis(side = 1, at = c(1:length(wi)), labels = names(wi),
cex.axis = caxis, las = 2)
axis(side = 2, cex.axis = caxis)
box()
pt <- seq(-0.1, 0.1, by = 0.2/nrow(wij))
for (j in 1:nrow(wij)) {
points(c(1:length(wi)), wij[j, ], pch = 16, col = j)
lines(1:length(wi), wij[j, ], col = j)
abline(h = 1, lwd = 2)
}
rgx <- ncol(wij)/5
legend(ncol(wij) - rgx, rgy[1] + 19 * (rgy[2] - rgy[1])/20,
legend = row.names(wij), pch = 16, col = 1:nrow(wij),
lwd = 1, cex = clab)
}
}
I pass custom labels to the my.labels argument.
ploWi(wiRatio, noorder = FALSE, my.labels = paste("bugabuga", 1:16, sep = ""))
I will leave you as an exercise to modify the above function to tweak the legend.
Regarding the sorting of values, just use noorder = FALSE (as in my above example).
Related
I have 5 variables which want to plot and export in one pdf. However, I have some trouble wiht the for-loop I am running,
parC <-list(unit = 100,labelx = "Time",labely = "Time",cols = "black",
pcex = .01, pch = 1,las = 1,
labax = seq(0,nrow(RP),100),
labay = seq(0,nrow(RP),100))
pdf("filename.pdf", onefile=TRUE)
for (i in RP_values){ # the values that are plotted
for (j in name) { # name is a list of names, so that the title changes dynamically
plotting(i, parC, j)
}
}
dev.off()
RP_values = list of values that is plotted
name = list of names to dynamically change the plotting title
plotting = an adjusted version from the plotRP() function of the crqa package. Here I added a main title to the plot.
The code for the plotting() function:
plotting <- function(RP, par, x){
if (exists("par") == FALSE){ # we use some defaults
## default values
unit = 2; labelx = "Time"; labely = "Time"
cols = "black"; pcex = .3; pch = 1; las = 0;
labax = seq(0, nrow(RP), unit); labay = seq(0, nrow(RP), unit);
} else { # we load the values that we desire
for (v in 1:length(par)) assign(names(par)[v], par[[v]])
}
xdim = nrow(RP)
ydim = ncol(RP)
RP = matrix(as.numeric(RP), nrow = xdim, ncol = ydim) # transform it for plotting
ind = which(RP == 1, arr.ind = T)
tstamp = seq(0, xdim, unit)
par(mar = c(5,5, 1, 3), font.axis = 2, cex.axis = 1,
font.lab = 2, cex.lab = 1.2)
plot(tstamp, tstamp, type = "n", xlab = "", ylab = "", xaxt = "n", yaxt = "n", main = x)
matpoints(ind[,1], ind[,2], cex = pcex, col = cols, pch = pch)
mtext(labelx, at = mean(tstamp), side = 1, line = 2.2, cex = 1.2, font = 2)
mtext(labely, at = mean(tstamp), side = 2, line = 2.2, cex = 1.2, font = 2)
# if (is.numeric(labax)){ ## it means there is some default
# mtext(labax, at = seq(1, nrow(RP), nrow(RP)/10), side = 1, line = .5, cex = 1, font = 2)
# mtext(labay, at = seq(1, nrow(RP), nrow(RP)/10), side = 2, line = .5, cex = 1, font = 2)
# } else{
mtext(labax, at = tstamp, side = 1, line = .5, cex = .8, font = 2, las = las)
mtext(labay, at = tstamp, side = 2, line = .5, cex = .8, font = 2, las = las)
# }
}
My problem is instead of 5 plots I get 25, where each plot appears 5 times, but with a different title. If I do not include the "j" part everything works fine, but of course do not have any main title for each plot.
I appreciate any help.
Best,
Johnson
From your description and comments, it appears you need an elementwise loop and not a nested loop. Consider retrieving all pairwise combinations of names and RP_values with expand.grid and iterate through them with mapply. Also, since parC depends on nrows of corresponding RP, have parC defined inside function for only two parameters (with more informative names like title instead of x):
plotting <- function(RP, title) {
parC <- list(unit=100, labelx="Time", labely="Time",
cols="black", pcex=.01, pch=1, las=1,
labax=seq(0, nrow(RP), 100),
labay=seq(0, nrow(RP), 100))
...
plot(tstamp, tstamp, type="n", xlab="", ylab="",
xaxt="n", yaxt="n", main=title)
...
}
params <- expand.grid(RP_values=RP_values, name=name)
out <- mapply(plotting, RP=params$RP_values, title=params$name)
I am using biwavelet package to conduct wavelet analysis. However, when I want to adjust the label size for axis using cex.axis, the label size does not changed. On the other hand, cex.lab and cex.main are working well. Is this a bug? The following gives a reproducible example.
library(biwavelet)
t1 <- cbind(1:100, rnorm(100))
t2 <- cbind(1:100, rnorm(100))
# Continuous wavelet transform
wt.t1 <- wt(t1)
par(oma = c(0, 0.5, 0, 0), mar = c(4, 2, 2, 4))
plot(wt.t1,plot.cb = T,plot.phase = T,type = 'power.norm',
xlab = 'Time(year)',ylab = 'Period(year)',mgp=c(2,1,0),
main='Winter station 1',cex.main=0.8,cex.lab=0.8,cex.axis=0.8)
Edit
There was a previous question on this site a month ago: Wavelets plot: changing x-, y- axis, and color plot, but not solved. Any help this time? Thank you!
Yeah, it is a bug. Here is patched version: my.plot.biwavelet()
This version accepts argument cex.axis (defaults to 1), and you can change it when needed. I will briefly explain to you what the problem is, in the "explanation" section in the end.
my.plot.biwavelet <- function (x, ncol = 64, fill.cols = NULL, xlab = "Time", ylab = "Period",
tol = 1, plot.cb = FALSE, plot.phase = FALSE, type = "power.corr.norm",
plot.coi = TRUE, lwd.coi = 1, col.coi = "white", lty.coi = 1,
alpha.coi = 0.5, plot.sig = TRUE, lwd.sig = 4, col.sig = "black",
lty.sig = 1, bw = FALSE, legend.loc = NULL, legend.horiz = FALSE,
arrow.len = min(par()$pin[2]/30, par()$pin[1]/40), arrow.lwd = arrow.len *
0.3, arrow.cutoff = 0.9, arrow.col = "black", xlim = NULL,
ylim = NULL, zlim = NULL, xaxt = "s", yaxt = "s", form = "%Y", cex.axis = 1,
...) {
if (is.null(fill.cols)) {
if (bw) {
fill.cols <- c("black", "white")
}
else {
fill.cols <- c("#00007F", "blue", "#007FFF",
"cyan", "#7FFF7F", "yellow", "#FF7F00", "red",
"#7F0000")
}
}
col.pal <- colorRampPalette(fill.cols)
fill.colors <- col.pal(ncol)
types <- c("power.corr.norm", "power.corr", "power.norm",
"power", "wavelet", "phase")
type <- match.arg(tolower(type), types)
if (type == "power.corr" | type == "power.corr.norm") {
if (x$type == "wtc" | x$type == "xwt") {
x$power <- x$power.corr
x$wave <- x$wave.corr
}
else {
x$power <- x$power.corr
}
}
if (type == "power.norm" | type == "power.corr.norm") {
if (x$type == "xwt") {
zvals <- log2(x$power)/(x$d1.sigma * x$d2.sigma)
if (is.null(zlim)) {
zlim <- range(c(-1, 1) * max(zvals))
}
zvals[zvals < zlim[1]] <- zlim[1]
locs <- pretty(range(zlim), n = 5)
leg.lab <- 2^locs
}
else if (x$type == "wtc" | x$type == "pwtc") {
zvals <- x$rsq
zvals[!is.finite(zvals)] <- NA
if (is.null(zlim)) {
zlim <- range(zvals, na.rm = TRUE)
}
zvals[zvals < zlim[1]] <- zlim[1]
locs <- pretty(range(zlim), n = 5)
leg.lab <- locs
}
else {
zvals <- log2(abs(x$power/x$sigma2))
if (is.null(zlim)) {
zlim <- range(c(-1, 1) * max(zvals))
}
zvals[zvals < zlim[1]] <- zlim[1]
locs <- pretty(range(zlim), n = 5)
leg.lab <- 2^locs
}
}
else if (type == "power" | type == "power.corr") {
zvals <- log2(x$power)
if (is.null(zlim)) {
zlim <- range(c(-1, 1) * max(zvals))
}
zvals[zvals < zlim[1]] <- zlim[1]
locs <- pretty(range(zlim), n = 5)
leg.lab <- 2^locs
}
else if (type == "wavelet") {
zvals <- (Re(x$wave))
if (is.null(zlim)) {
zlim <- range(zvals)
}
locs <- pretty(range(zlim), n = 5)
leg.lab <- locs
}
else if (type == "phase") {
zvals <- x$phase
if (is.null(zlim)) {
zlim <- c(-pi, pi)
}
locs <- pretty(range(zlim), n = 5)
leg.lab <- locs
}
if (is.null(xlim)) {
xlim <- range(x$t)
}
yvals <- log2(x$period)
if (is.null(ylim)) {
ylim <- range(yvals)
}
else {
ylim <- log2(ylim)
}
image(x$t, yvals, t(zvals), zlim = zlim, xlim = xlim,
ylim = rev(ylim), xlab = xlab, ylab = ylab, yaxt = "n",
xaxt = "n", col = fill.colors, ...)
box()
if (class(x$xaxis)[1] == "Date" | class(x$xaxis)[1] ==
"POSIXct") {
if (xaxt != "n") {
xlocs <- pretty(x$t) + 1
axis(side = 1, at = xlocs, labels = format(x$xaxis[xlocs],
form))
}
}
else {
if (xaxt != "n") {
xlocs <- axTicks(1)
axis(side = 1, at = xlocs, cex.axis = cex.axis)
}
}
if (yaxt != "n") {
axis.locs <- axTicks(2)
yticklab <- format(2^axis.locs, dig = 1)
axis(2, at = axis.locs, labels = yticklab, cex.axis = cex.axis)
}
if (plot.coi) {
polygon(x = c(x$t, rev(x$t)), lty = lty.coi, lwd = lwd.coi,
y = c(log2(x$coi), rep(max(log2(x$coi), na.rm = TRUE),
length(x$coi))), col = adjustcolor(col.coi,
alpha.f = alpha.coi), border = col.coi)
}
if (plot.sig & length(x$signif) > 1) {
if (x$type %in% c("wt", "xwt")) {
contour(x$t, yvals, t(x$signif), level = tol,
col = col.sig, lwd = lwd.sig, add = TRUE, drawlabels = FALSE)
}
else {
tmp <- x$rsq/x$signif
contour(x$t, yvals, t(tmp), level = tol, col = col.sig,
lwd = lwd.sig, add = TRUE, drawlabels = FALSE)
}
}
if (plot.phase) {
a <- x$phase
locs.phases <- which(zvals < quantile(zvals, arrow.cutoff))
a[locs.phases] <- NA
phase.plot(x$t, log2(x$period), a, arrow.len = arrow.len,
arrow.lwd = arrow.lwd, arrow.col = arrow.col)
}
box()
if (plot.cb) {
fields::image.plot(x$t, yvals, t(zvals), zlim = zlim, ylim = rev(range(yvals)),
xlab = xlab, ylab = ylab, col = fill.colors,
smallplot = legend.loc, horizontal = legend.horiz,
legend.only = TRUE, axis.args = list(at = locs,
labels = format(leg.lab, dig = 2)), xpd = NA)
}
}
Test
library(biwavelet)
t1 <- cbind(1:100, rnorm(100))
t2 <- cbind(1:100, rnorm(100))
# Continuous wavelet transform
wt.t1 <- wt(t1)
par(oma = c(0, 0.5, 0, 0), mar = c(4, 2, 2, 4))
my.plot.biwavelet(wt.t1,plot.cb = T,plot.phase = T,type = 'power.norm',
xlab = 'Time(year)',ylab = 'Period(year)',mgp=c(2,1,0),
main='Winter station 1',cex.main=0.8,cex.lab=0.8,cex.axis=0.8)
As expected, it is working.
Explanation
In plot.biwavelet(), why passing cex.axis via ... does not work?
plot.biwavelet() generates the your final plot mainly in 3 stages:
image(..., xaxt = "n", yaxt = "n") for generating basic plot;
axis(1, at = atTicks(1)); axis(2, at = atTicks(2)) for adding axis;
fields::image.plot() for displaying colour legend strip.
Now, although this function takes ..., they are only fed to the first image() call, while the following axis(), (including polygon(), contour(), phase.plot()) and image.plot() take none from .... When later calling axis(), no flexible specification with respect to axis control are supported.
I guess during package development time, problem described as in: Giving arguments from “…” argument to right function in R had been encountered. Maybe the author did not realize this potential issue, leaving a bug here. My answer to that post, as well as Roland's comments, points toward a robust fix.
I am not the package author so can not decide how he will fix this. My fix is brutal, but works for you temporary need: just add the cex.axis argument to axis() call. I have reached Tarik (package author) with an email, and I believe he will give you a much better explanation and solution.
I fixed this issue by passing the ... argument to axis in plot.biwavelet. Your code should now work as desired. Note that changes to cex.axis and other axis arguments will affect all three axes (x, y, z).
You can download the new version (0.20.8) of biwavelet from GitHub by issuing the following command at the R console (this assumes that you have the package devtools already installed): devtools::install_github("tgouhier/biwavelet")
Thanks for pointing out the bug!
I am trying to visualize the results of a PCoA{ape} by making a biplot in R.
The axes now get the default labels axis 1 and axis 2, but I want to edit this.
This is the code I have tried:
biplot(pcoa.ntK, Y=NULL, plot.axes=c(1,2), rn=ntnames,
xlabs="PC1 (%)", ylabs="PC2 (%)")
But the labels don't change.
Can someone tell me what I'm doing wrong here?
And I also would like to edit the title, anyone tips for this?
My data:
ntK <- matrix(
c(0.00000, 0.01500, 0.01832, 0.02061, 0.01902, 0.01270, 0.02111, 0.01655, 0.01520, 0.01691,
0.01667, 0.00000, 0.01175, 0.01911, 0.01759, 0.01127, 0.01854, 0.01041, 0.00741, 0.02007,
0.02432, 0.01404, 0.00000, 0.02551, 0.01972, 0.01838, 0.02505, 0.01484, 0.01391, 0.02687,
0.01501, 0.01252, 0.01399, 0.00000, 0.01442, 0.01294, 0.01402, 0.01132, 0.01239, 0.01455,
0.02343, 0.01951, 0.01830, 0.02440, 0.00000, 0.01727, 0.02470, 0.02021, 0.01699, 0.02482,
0.01320, 0.01054, 0.01439, 0.01847, 0.01457, 0.00000, 0.01818, 0.01366, 0.00977, 0.01394,
0.02468, 0.01950, 0.02206, 0.02251, 0.02343, 0.02040, 0.00000, 0.02028, 0.01875, 0.02558,
0.02254, 0.01276, 0.01522, 0.02117, 0.02234, 0.01790, 0.02363, 0.00000, 0.01152, 0.02557,
0.01804, 0.00792, 0.01244, 0.02019, 0.01637, 0.01116, 0.01904, 0.01004, 0.00000, 0.02099,
0.01862, 0.01988, 0.02227, 0.02200, 0.02218, 0.01476, 0.02408, 0.02066, 0.01947, 0.00000),
nrow=10,
ncol=10)
library(ape)
ntnames <- c("A","B","C","D","E","F","G","H","I","J")
pcoa.ntK <- pcoa(ntK)
biplot is a generic function. The default method and the method for use with objects that come from using the prcomp function in the stats package do allow you to specify axis labels and a title, but for some reason the person that wrote the method that is called with objects of class pcoa hasn't allowed you to specify them. I think your only option would be to write your own version of biplot.pcoa (or ask the package maintainer to add this option).
This is a very quick and dirty hack of the function in the ape package that might do what you want, but no promises that it won't have broken something else!
biplot.pcoa <- function (x, Y = NULL, plot.axes = c(1, 2), dir.axis1 = 1, dir.axis2 = 1,
rn = NULL, xlabs = NULL, ylabs = NULL, main = NULL, ...)
{
k <- ncol(x$vectors)
if (k < 2)
stop("There is a single eigenvalue. No plot can be produced.")
if (k < plot.axes[1])
stop("Axis", plot.axes[1], "does not exist.")
if (k < plot.axes[2])
stop("Axis", plot.axes[2], "does not exist.")
if (!is.null(rn))
rownames(x$vectors) <- rn
labels = colnames(x$vectors[, plot.axes])
if (!is.null(xlabs)) labels[1] <- xlabs
if (!is.null(ylabs)) labels[2] <- ylabs
diag.dir <- diag(c(dir.axis1, dir.axis2))
x$vectors[, plot.axes] <- x$vectors[, plot.axes] %*% diag.dir
if (is.null(Y)) {
limits <- apply(x$vectors[, plot.axes], 2, range)
ran.x <- limits[2, 1] - limits[1, 1]
ran.y <- limits[2, 2] - limits[1, 2]
xlim <- c((limits[1, 1] - ran.x/10), (limits[2, 1] +
ran.x/5))
ylim <- c((limits[1, 2] - ran.y/10), (limits[2, 2] +
ran.y/10))
par(mai = c(1, 1, 1, 0.5))
plot(x$vectors[, plot.axes], xlab = labels[1], ylab = labels[2],
xlim = xlim, ylim = ylim, asp = 1)
text(x$vectors[, plot.axes], labels = rownames(x$vectors),
pos = 4, cex = 1, offset = 0.5)
if (is.null(main)){
title(main = "PCoA ordination", line = 2.5)
} else title(main = main, line = 2.5)
}
else {
n <- nrow(Y)
points.stand <- scale(x$vectors[, plot.axes])
S <- cov(Y, points.stand)
U <- S %*% diag((x$values$Eigenvalues[plot.axes]/(n -
1))^(-0.5))
colnames(U) <- colnames(x$vectors[, plot.axes])
par(mai = c(1, 0.5, 1.4, 0))
biplot(x$vectors[, plot.axes], U, xlab = labels[1], ylab = labels[2])
if (is.null(main)) {
title(main = c("PCoA biplot", "Response variables projected",
"as in PCA with scaling 1"), line = 4)
} else title(main = main, line = 4)
}
invisible()
}
biplot(pcoa.ntK, xlabs = 'My x label', ylabs = 'My y label', main = 'My title')
You can check the source code of biplot.pcoa and you'll see it's not that hard to modify. The author of the package decided to hard-code the axis labels based on the input and also the main title of the plot. Here's a modified version that will first check if values for xlab, ylab and main were used before using the pre-defined ones:
biplot.pcoa <- function (x, Y = NULL, plot.axes = c(1, 2), dir.axis1 = 1, dir.axis2 = 1,
rn = NULL, ...)
{
k <- ncol(x$vectors)
if (k < 2)
stop("There is a single eigenvalue. No plot can be produced.")
if (k < plot.axes[1])
stop("Axis", plot.axes[1], "does not exist.")
if (k < plot.axes[2])
stop("Axis", plot.axes[2], "does not exist.")
if (!is.null(rn))
rownames(x$vectors) <- rn
args <- list(...)
labels = ifelse(c("xlab", "ylab") %in% names(args), c(args$xlab, args$ylab), colnames(x$vectors[, plot.axes]))
diag.dir <- diag(c(dir.axis1, dir.axis2))
x$vectors[, plot.axes] <- x$vectors[, plot.axes] %*% diag.dir
if (is.null(Y)) {
limits <- apply(x$vectors[, plot.axes], 2, range)
ran.x <- limits[2, 1] - limits[1, 1]
ran.y <- limits[2, 2] - limits[1, 2]
xlim <- c((limits[1, 1] - ran.x/10), (limits[2, 1] +
ran.x/5))
ylim <- c((limits[1, 2] - ran.y/10), (limits[2, 2] +
ran.y/10))
par(mai = c(1, 1, 1, 0.5))
title <- ifelse("main" %in% names(args), args$main, "PCoA ordination")
plot(x$vectors[, plot.axes], xlab = labels[1], ylab = labels[2],
xlim = xlim, ylim = ylim, asp = 1,
main = title)
text(x$vectors[, plot.axes], labels = rownames(x$vectors),
pos = 4, cex = 1, offset = 0.5)
#title(main = "PCoA ordination", line = 2.5)
}
else {
n <- nrow(Y)
points.stand <- scale(x$vectors[, plot.axes])
S <- cov(Y, points.stand)
U <- S %*% diag((x$values$Eigenvalues[plot.axes]/(n -
1))^(-0.5))
colnames(U) <- colnames(x$vectors[, plot.axes])
par(mai = c(1, 0.5, 1.4, 0))
title <- ifelse("main" %in% names(args), args$main, c("PCoA biplot", "Response variables projected",
"as in PCA with scaling 1"))
biplot(x$vectors[, plot.axes], U, xlab = labels[1], ylab = labels[2], main = title)
# title(main = c("PCoA biplot", "Response variables projected",
# "as in PCA with scaling 1"), line = 4)
}
invisible()
}
Then:
biplot(pcoa.ntK, Y=NULL, plot.axes=c(1,2), rn=ntnames,
xlab="PC1 (%)", main = "Main Title")
Keep in mind this won't change the original function, so you'll need to load this modified version every time you load the package and need wish to set the labels like this.
I want to create major and minor ticks in my date-formatted x-axis, so that for every 3rd tick (representing every 3 months) I have a major tick and a label.
This is a reproducible example of what I have so far, which currently has uniform ticks.
month<-c("2010-08-01", "2010-09-01", "2010-10-01", "2010-12-01", "2011-01-01", "2011-02-01",
"2011-03-01", "2011-04-01", "2011-05-01", "2011-06-01", "2011-07-01", "2011-09-01",
"2011-11-01", "2012-01-01", "2012-02-01", "2012-03-01", "2012-05-01", "2012-07-01",
"2012-08-01")
prevalence<-c(10,7.5,5.2,3.5,6.4,2.7,5.8,13.2,4.3,4.7,6.4,4.4,5.2,3.3,1.0,3.1,9.9,33.3,1.0)
df<-data.frame(month, prevalence)
df$month<-as.Date(df$month)
plot(df$month, df$prevalence,lwd = 1.8, ylim=c(0,40),pch=16, bty='n', xaxt='n',
ylab="Prevalence (%)", xlab="Month",col='black',cex=1,cex.lab=1.0,cex.axis=1.0)
at <- seq(from = min(df$month), to = max(df$month), by = "month") # produces a regular sequence of dates
axis.Date(side = 1, at = at, labels = FALSE, tck=-0.04)
axis(side=2, at=c(0,10,20,30,40,50), labels=c("", "", "", "", "", ""), tck=-0.04)
lines(df$month, df$prevalence, col='black', lwd=1.8)
I have tried using the package magicaxis, but it does not seem to allow for date-formatted axes.
As a quick fix you could use repeat axis.Date calls.
at1 <- at[c(TRUE, TRUE, FALSE)]
axis.Date(side = 1, at = at1, labels = FALSE, tck=-0.02)
at2 <- at[c(FALSE, FALSE, TRUE)]
axis.Date(side = 1, at = at2, labels = TRUE, tck=-0.04)
The TRUE and FALSE are used to subset the vector at
I don't know if this is still a problem for someone, but I made a general purpose function for axes with minor ticks, based on the base axis() function, and with similar arguments. It's available in the StratigrapheR package under minorAxis()
minorAxis <- function(side, n = NULL, at.maj = NULL, at.min = NULL, range = NULL,
tick.ratio = 0.5, labels.maj = TRUE, line = NA, pos = NA,
outer = FALSE, font = NA, lty = "solid", lwd = 1,
lwd.ticks = lwd, col = NULL, col.ticks = NULL, hadj = NA,
padj = NA, extend = FALSE, tcl = NA, ...)
{
if(side == 1 | side == 3){
tick.pos <- par("xaxp")
} else if (side == 2 | side == 4) {
tick.pos <- par("yaxp")
}
# Define the positions of major ticks ----
if(is.null(at.maj)) {
# nat.int <- (tick.pos[2] - tick.pos[1])/tick.pos[3]
at.maj <- seq(tick.pos[1], tick.pos[2],
by = (tick.pos[2] - tick.pos[1])/tick.pos[3])
}
# Define range, exclude at.maj values if necessary ----
if(length(range) != 0){
eff.range <- range
r1 <- at.maj - min(range)
r2 <- at.maj - max(range)
p1 <- which.min(abs(r1))
p2 <- which.min(abs(r2))
if(!(abs(r1[p1]/min(range)) < 1.5e-8) & r1[p1] < 0) p1 <- p1 + 1
if(!(abs(r2[p2]/max(range)) < 1.5e-8) & r2[p2] > 0) p2 <- p2 - 1
at.maj <- at.maj[p1:p2]
} else {
if(side == 1 | side == 3){
eff.range <- par("usr")[1:2]
} else if (side == 2 | side == 4) {
eff.range <- par("usr")[3:4]
}
}
# Define limits ----
if(!extend) {
if(!is.null(at.min) & length(range) == 0){
limits <- c(min(c(at.min, at.maj)), max(c(at.min, at.maj)))
} else {
limits <- c(min(at.maj), max(at.maj))
}
} else {
limits <- eff.range
}
# Standard axis when n and at.min are not given ----
if(is.null(n) & is.null(at.min)){
axis(side, at = limits, labels = FALSE, tick = TRUE, line = line,
pos = pos, outer = outer, lty = lty, lwd = lwd, lwd.ticks = 0,
col = col,...)
axis(side, at = at.maj, labels = labels.maj, tick = TRUE, line = line,
pos = pos, outer = outer, font = font, lty = lty,
lwd = 0, lwd.ticks = lwd.ticks, col = col, col.ticks = col.ticks,
hadj = hadj, padj = padj, tcl = tcl,...)
} else {
# Work the minor ticks: check regularity ----
mina <- min(at.maj)
maxa <- max(at.maj)
difa <- maxa - mina
na <- difa / (length(at.maj) - 1)
if(is.null(at.min))
{
# n realm ----
# Checks----
sia <- seq(mina,maxa,by = na)
if(!isTRUE(all.equal(sort(sia),sort(at.maj)))) {
stop("at.maj is irregular, use at.min for minor ticks (not n)")
}
if(!(is.numeric(n) & length(n) == 1)){
stop("n should be a numeric of length one")
}
# Work it ----
tick.pos <- c(mina,maxa,difa/na)
nat.int <- (tick.pos[2] - tick.pos[1])/tick.pos[3]
# Define the position of minor ticks ----
distance.between.minor <- nat.int/n
p <- seq(min(at.maj), max(at.maj), by = distance.between.minor)
q <- sort(every_nth(p,n,empty=FALSE))
# Extend outside of major ticks range if necessary ----
if(!extend) {
tick.seq <- q
} else {
possible.low.minors <- min(at.maj) - (n:1) * distance.between.minor
possible.hi.minors <- max(at.maj) + (1:n) * distance.between.minor
r3 <- possible.low.minors - min(eff.range)
r4 <- possible.hi.minors - max(eff.range)
p3 <- which.min(abs(r3))
p4 <- which.min(abs(r4))
if(!(abs(r3[p3]/min(eff.range)) < 1.5e-8) & r3[p3] < 0) p3 <- p3 + 1
if(!(abs(r4[p4]/max(eff.range)) < 1.5e-8) & r4[p4] > 0) p4 <- p4 - 1
if(p3 < length(possible.low.minors + 1)){
low.candidates <- seq(p3, length(possible.low.minors), 1)
low.laureates <- possible.low.minors[low.candidates]
} else {
low.laureates <- NULL
}
if(p4 > 0){
hi.candidates <- seq(1, p4, 1)
hi.laureates <- possible.hi.minors[ hi.candidates]
} else {
hi.laureates <- NULL
}
tick.seq <- c(low.laureates,q,hi.laureates)
}
} else {
# at.min realm ----
tick.pos <- c(mina,maxa,na)
tick.seq <- sort(at.min)
if(length(range) != 0){
r3 <- tick.seq - min(eff.range)
r4 <- tick.seq - max(eff.range)
p3 <- which.min(abs(r3))
p4 <- which.min(abs(r4))
if(!(abs(r3[p3]/min(eff.range)) < 1.5e-8) & r3[p3] < 0) p3 <- p3 + 1
if(!(abs(r4[p4]/max(eff.range)) < 1.5e-8) & r4[p4] > 0) p4 <- p4 - 1
tick.seq <- tick.seq [p3:p4]
}
}
# Define the length of ticks ----
if(is.na(tcl)) maj.tcl <- par()$tcl else if (!is.na(tcl)) maj.tcl <- tcl
min.tcl <- maj.tcl*tick.ratio
# Plot the axes ----
axis(side, at = limits, labels = FALSE, tick = TRUE, line = line,
pos = pos, outer = outer, lty = lty, lwd = lwd, lwd.ticks = 0,
col = col,...)
axis(side, at = at.maj, labels = labels.maj, tick = TRUE, line = line,
pos = pos, outer = outer, font = font, lty = lty,
lwd = 0, lwd.ticks = lwd.ticks, col = col, col.ticks = col.ticks,
hadj = hadj, padj = padj, tcl = maj.tcl,...)
axis(side, at = tick.seq, labels = FALSE, tick = TRUE, line = line,
pos = pos, outer = outer, lwd = 0, lwd.ticks = lwd.ticks, col = col,
col.ticks = col.ticks, tcl = min.tcl,...)
}
}
# Run this as example:
plot(c(0,1), c(0,1), axes = FALSE, type = "n", xlab = "", ylab = "")
minorAxis(1, n = 10, range = c(0.12,0.61))
minorAxis(3, n = 10, extend=FALSE)
How might one add labels to an archmap from the archetypes package? Or alternatively, would it be possible to recreate the archmap output in ggplot?
Using code from the SportsAnalytics demo (I hope this isn't bad form)
library("SportsAnalytics")
library("archetypes")
data("NBAPlayerStatistics0910")
dat <- subset(NBAPlayerStatistics0910,
select = c(Team, Name, Position,
TotalMinutesPlayed, FieldGoalsMade))
mat <- as.matrix(subset(dat, select = c(TotalMinutesPlayed, FieldGoalsMade)))
a3 <- archetypes(mat, 3)
archmap(a3)
I'd like the player names ( NBAPlayerStatistics0910$Name ) over the points on the chart. Something like below but more readable.
If you don't mind tweaking things a bit, you can start with the archmap() function base, toss in an extra parameter and add a text() call:
amap2 <- function (object, a.names, projection = simplex_projection, projection_args = list(),
rotate = 0, cex = 1.5, col = 1, pch = 1, xlab = "", ylab = "",
axes = FALSE, asp = TRUE, ...)
{
stopifnot("archetypes" %in% class(object))
stopifnot(is.function(projection))
k <- object$k
if (k < 3) {
stop("Need at least 3 archetypes.\n")
}
cmds <- do.call(projection, c(list(parameters(object)), projection_args))
if (rotate != 0) {
a <- pi * rotate/180
A <- matrix(c(cos(a), -sin(a), sin(a), cos(a)), ncol = 2)
cmds <- cmds %*% A
}
hmds <- chull(cmds)
active <- 1:k %in% hmds
plot(cmds, type = "n", xlab = xlab, ylab = ylab, axes = axes,
asp = asp, ...)
points(coef(object) %*% cmds, col = col, pch = pch)
######################
# PLAY WITH THIS BIT #
######################
text(coef(object) %*% cmds, a.names, pos=4)
######################
rad <- ceiling(log10(k)) + 1.5
polygon(cmds[hmds, ])
points(cmds[active, ], pch = 21, cex = rad * cex, bg = "grey")
text(cmds[active, ], labels = (1:k)[active], cex = cex)
if (any(!active)) {
points(cmds[!active, , drop = FALSE], pch = 21, cex = rad *
cex, bg = "white", fg = "grey")
text(cmds[!active, , drop = FALSE], labels = (1:k)[!active],
cex = cex, col = "grey20")
}
invisible(cmds)
}
amap2(a3, dat$Name)
Obviously, my completely quick stab is not the end result you're looking for, but it should help you get on your way (if I read what you want to do correctly).