ggplot2 Version of Figures in “Lattice: Multivariate Data Visualization with R” (Part 8)

This is the 8th post in a series attempting to recreate the figures in Lattice: Multivariate Data Visualization with R (R code available here) with ggplot2.

Previous parts in this series: Part 1, Part 2, Part 3, Part 4, Part 5, Part 6, Part 7.

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Chapter 8 – Plot Coordinates and Axis Annotation

Topics covered:

• Packets
• The prepanel function, axis limits, and aspect ratio
• Axis annotation
• The scales argument

Figure 8.1

> library(lattice) > library(ggplot2)

lattice

> pl <- stripplot(depth ~ factor(mag), data = quakes, jitter.data = TRUE, + scales = list(y = "free", rot = 0), prepanel = function(x, + y, ...) list(ylim = rev(range(y))), xlab = "Magnitude (Richter scale)") > print(pl)

ggplot2

> p <- ggplot(quakes, aes(factor(mag), depth)) > pg <- p + geom_point(position = position_jitter(width = 0.15), + alpha = 0.6, shape = 1) + xlab("Magnitude (Richter)") + + ylab("Depth (km)") + theme_bw() + scale_y_reverse() > print(pg)

Note	Compare to Figure 3.16. Y-Axes reversed.

Figure 8.2

> data(biocAccess, package = "latticeExtra")

lattice

> pl <- xyplot(counts/1000 ~ time | equal.count(as.numeric(time), + 9, overlap = 0.1), biocAccess, type = "l", aspect = "xy", + strip = FALSE, ylab = "Numer of accesses (thousands)", + xlab = "", scales = list(x = list(relation = "sliced", + axs = "i"), y = list(alternating = FALSE))) > print(pl)

ggplot2

> fn <- function(data = quakes$mag, number = 4, ...) { + intrv <<- as.data.frame(co.intervals(data, number, + ...)) + mag <- sort(unique(data)) + intervals <- ldply(mag, function(x) { + t(as.numeric(x < intrv$V2 & x > intrv$V1)) + }) + tmp <- melt(cbind(mag, intervals), id.var = 1) + tmp[tmp$value > 0, 1:2] + } > biocAccess <- merge(biocAccess[, c("time", "counts")], + fn(data = as.numeric(biocAccess$time), number = 9, + overlap = 0.1), by.x = "time", by.y = "mag")

Note	Using custom function fn(), first defined in Figure 5.5.

> pg <- ggplot(biocAccess, aes(time, counts/1000)) + geom_line() + + facet_wrap(~variable, scales = "free_x", ncol = 1) + + ylab("Numer of accesses (thousands)") + xlab("") + + opts(strip.background = theme_blank(), strip.text.x = theme_blank()) + + opts(panel.margin = unit(-0.25, "lines")) > print(pg)

Figure 8.3

> data(Earthquake, package = "MEMSS")

lattice

> pl <- xyplot(accel ~ distance, data = Earthquake, prepanel = prepanel.loess, + aspect = "xy", type = c("p", "g", "smooth"), scales = list(log = 2), + xlab = "Distance From Epicenter (km)", ylab = "Maximum Horizontal Acceleration (g)") > print(pl)

ggplot2

> pg <- ggplot(Earthquake, aes(distance, accel)) + geom_point() + + geom_smooth(method = "loess", se = FALSE) + scale_x_log2() + + scale_y_log2() + xlab("Distance From Epicenter (km)") + + ylab("Maximum Horizontal Acceleration (g)") > print(pg)

Note	ggplot2 doesn’t have the equivalent of aspect="xy" in lattice, which “tries to compute the aspect based on the 45 degree banking rule”.

Figure 8.4

lattice

> yscale.components.log2 <- function(...) { + ans <- yscale.components.default(...) + ans$right <- ans$left + ans$left$labels$labels <- parse(text = ans$left$labels$labels) + ans$right$labels$labels <- MASS::fractions(2^(ans$right$labels$at)) + ans + } > logTicks <- function(lim, loc = c(1, 5)) { + ii <- floor(log10(range(lim))) + c(-1, 2) + main <- 10^(ii[1]:ii[2]) + r <- as.numeric(outer(loc, main, "*")) + r[lim[1] <= r & r <= lim[2]] + } > xscale.components.log2 <- function(lim, ...) { + ans <- xscale.components.default(lim = lim, ...) + tick.at <- logTicks(2^lim, loc = c(1, 3)) + ans$bottom$ticks$at <- log(tick.at, 2) + ans$bottom$labels$at <- log(tick.at, 2) + ans$bottom$labels$labels <- as.character(tick.at) + ans + }

> pl <- xyplot(accel ~ distance | cut(Richter, c(4.9, 5.5, + 6.5, 7.8)), data = Earthquake, type = c("p", "g"), + scales = list(log = 2, y = list(alternating = 3)), + xlab = "Distance From Epicenter (km)", ylab = "Maximum Horizontal Acceleration (g)", + xscale.components = xscale.components.log2, yscale.components = yscale.components.log2) > print(pl)

ggplot2

> Earthquake$magnitude <- cut(Earthquake$Richter, c(4.9, + 5.5, 6.5, 7.8)) > ticks <- logTicks(range(Earthquake$distance), loc = c(1, + 3)) > pg <- ggplot(Earthquake, aes(distance, accel)) + geom_point() + + facet_grid(~magnitude) + scale_y_log2() + scale_x_log2(breaks = ticks, + labels = ticks) + xlab("Distance From Epicenter (km)") + + ylab("Maximum Horizontal Acceleration (g)") > print(pg)

Note	ggplot2 does not support the addition of a secondary axes.

Figure 8.5

> xscale.components.log10 <- function(lim, ...) { + ans <- xscale.components.default(lim = lim, ...) + tick.at <- logTicks(10^lim, loc = 1:9) + tick.at.major <- logTicks(10^lim, loc = 1) + major <- tick.at %in% tick.at.major + ans$bottom$ticks$at <- log(tick.at, 10) + ans$bottom$ticks$tck <- ifelse(major, 1.5, 0.75) + ans$bottom$labels$at <- log(tick.at, 10) + ans$bottom$labels$labels <- as.character(tick.at) + ans$bottom$labels$labels[!major] <- "" + ans$bottom$labels$check.overlap <- FALSE + ans + }

lattice

> pl <- xyplot(accel ~ distance, data = Earthquake, prepanel = prepanel.loess, + aspect = "xy", type = c("p", "g"), scales = list(log = 10), + xlab = "Distance From Epicenter (km)", ylab = "Maximum Horizontal Acceleration (g)", + xscale.components = xscale.components.log10) > print(pl)

ggplot2

> ticks <- logTicks(range(Earthquake$distance), loc = c(1, + 10)) > pg <- ggplot(Earthquake, aes(distance, accel)) + geom_point() + + scale_y_log10() + scale_x_log10(breaks = ticks, labels = ticks) + + xlab("Distance From Epicenter (km)") + ylab("Maximum Horizontal Acceleration (g)") > print(pg)

Note	ggplot2 doesn’t have the equivalent of aspect="xy" in lattice, which “tries to compute the aspect based on the 45 degree banking rule”.

Figure 8.6

lattice

> axis.CF <- function(side, ...) { + if (side == "right") { + F2C <- function(f) 5 * (f - 32)/9 + C2F <- function(c) 32 + 9 * c/5 + ylim <- current.panel.limits()$ylim + prettyF <- pretty(ylim) + prettyC <- pretty(F2C(ylim)) + panel.axis(side = side, outside = TRUE, at = prettyF, + tck = 5, line.col = "grey65", text.col = "grey35") + panel.axis(side = side, outside = TRUE, at = C2F(prettyC), + labels = as.character(prettyC), tck = 1, + line.col = "black", text.col = "black") + } + else axis.default(side = side, ...) + }

> pl <- xyplot(nhtemp ~ time(nhtemp), aspect = "xy", type = "o", + scales = list(y = list(alternating = 2, tck = c(1, + 5))), axis = axis.CF, xlab = "Year", ylab = "Temperature", + main = "Yearly temperature in New Haven, CT", key = list(text = list(c("(Celcius)", + "(Fahrenheit)"), col = c("black", "grey35")), + columns = 2)) > print(pl)

ggplot2

> temp <- data.frame(nhtemp) > temp$year <- seq(1912, 1971) > pg <- ggplot(temp, aes(year, nhtemp)) + geom_line() + + xlab("Year") + ylab("Temperature") + opts(title = "Yearly temperature in New Haven, CT") > print(pg)

Note	ggplot2 doesn’t support the addition of secondary axes.