Reorders layout observations based on specific statistics.

Usage

align_order2(
  stat,
  ...,
  reverse = FALSE,
  strict = TRUE,
  data = NULL,
  active = NULL
)

Arguments

stat: A statistical function which accepts a data and returns the statistic, which we'll call order2() to extract the ordering information.
...: <dyn-dots> Additional arguments passed to function provided in stat argument.
reverse: A boolean value. Should the sort order be in reverse?
strict: A boolean value indicates whether the order should be strict. If previous groups has been established, and strict is FALSE, this will reorder the observations in each group.
data: A matrix, data frame, or atomic vector used as the input for the stat function. Alternatively, you can specify a function (including purrr-like lambda syntax) that will be applied to the layout matrix, transforming it as necessary for statistic calculations. By default, it will inherit from the layout matrix.
active: A active() object that defines the context settings when added to a layout.

Details

The align_order2() function differs from align_order() in that the weights argument in align_order() must return atomic weights for each observation. In contrast, the stat argument in align_order2() can return more complex structures, such as hclust or dendrogram, among others.

Typically, you can achieve the functionality of align_order2() using align_order() by manually extracting the ordering information from the statistic.

Discrete Axis Alignment

It is important to note that we consider rows as observations, meaning vec_size(data)/NROW(data) must match the number of observations along the axis used for alignment (x-axis for a vertical stack layout, y-axis for a horizontal stack layout).

Examples

ggheatmap(matrix(rnorm(81), nrow = 9)) +
    anno_left() +
    align_order2(hclust2)
#> → heatmap built with `geom_tile()`