Vignettes are long form documentation commonly included in packages. Because they are part of the distribution of the package, they need to be as compact as possible. The html_vignette
output type provides a custom style sheet (and tweaks some options) to ensure that the resulting html is as small as possible. The html_vignette
format:
data(iris) library(ggplot2) library(drewcurves) library(tidyr) library(dplyr) ## Show first elements of dataset head(iris) ## Andrews plot with no group. drewcurves(iris[, -5]) ## Andrews plot with species as group. drewcurves(iris, group = 5) ## Return dataframe instead of plot. drewcurves(iris, group = 5, return_dataframe = TRUE) %>% head() ## Modify the x limits (as long as the interval length is 2pi). drewcurves(iris, group = 5, xlim = c(0, 2*pi)) ## Add other elements from ggplot to the plot drewcurves(iris, group = 5) + ylim(c(-1, 3)) + ggtitle("Andrews plot", sub = "This is a subtitle") + theme_bw() + scale_colour_brewer(palette = "Set1")
Temp text.
data(iris) library(ggplot2) library(drewcurves) library(andrews) library(tidyr) library(dplyr) ## Show first elements of dataset head(iris) ## Andrews plot with no group. drewcurves(iris[, -5]) ## Andrews plot with species as group. drewcurves(iris, group = 5) ## Return dataframe instead of plot. drewcurves(iris, group = 5, return_dataframe = TRUE) %>% head() ## Modify the x limits (as long as the interval length is 2pi). drewcurves(iris, group = 5, xlim = c(0, 2*pi)) ## Add other elements from ggplot to the plot drewcurves(iris, group = 5) + ylim(c(-1, 3)) + ggtitle("Andrews plot", sub = "This is a subtitle") + theme_bw() + scale_colour_brewer(palette = "Set1") drewcurves(iris[, c(sample(4), 5)], group = 5) head(iris) drewcurves(iris[, -5]) drewcurves(iris, group = 5) drewcurves(iris, group = 5, xlim = c(0, 2*pi)) drewcurves(iris, group = 5) + ylim(c(-1, 3)) drewcurves(iris[, c(sample(4), 5)], group = 5) str(iris) iris[, names(iris)[5]] head(iris[, "Species"]) select(iris, Species) ## ------------------------------------------ X <- iris[, -5] Y <- apply(X, 2, function(x) (x - min(x))/(max(x) - min(x))) t <- seq(-pi, pi, len = 100) group <- iris$Species andrews(iris, clr = 5, ymax = 2.5) Z <- compute_fourier_series(Y, t, 1) Z %>% as.data.frame() %>% # tbl_df() %>% mutate(t = t) %>% gather(key, value, -t) %>% mutate(group = rep(group, each = nrow(Z))) %>% ggplot(aes(t, value, group = key)) + geom_line(aes(color = group)) dim(Z)
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