Ordering observations based on summary weights or a specified ordering character or integer index.
align_order(
weights = rowMeans,
...,
reverse = FALSE,
strict = TRUE,
data = NULL,
active = NULL
)
A summary function which accepts a data and returns the
weights for each observations. Alternatively, you can provide an ordering
index as either an integer or a character. Since characters have been
designated as character indices, if you wish to specify a function name as a
string, you must enclose it with I()
.
<dyn-dots> Additional arguments passed to
function provided in weights
argument.
A boolean value. Should the sort order be in reverse?
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.
A matrix
, data frame
, or atomic vector used as the input for
the weights
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 weight calculations. By default, it
will inherit from the layout matrix.
A active()
object that defines the context settings when
added to a layout.
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).
ggheatmap(matrix(rnorm(81), nrow = 9)) +
anno_left() +
align_order(I("rowMeans"))
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