Split layout by k-means clustering groups.
align_kmeans(centers, ..., data = NULL, set_context = FALSE, name = NULL)A new Align object.
either the number of clusters, say \(k\), or a set of
initial (distinct) cluster centres. If a number, a random set of
(distinct) rows in x is chosen as the initial centres.
Arguments passed on to stats::kmeans
iter.maxthe maximum number of iterations allowed.
nstartif centers is a number, how many random sets
should be chosen?
algorithmcharacter: may be abbreviated. Note that
"Lloyd" and "Forgy" are alternative names for one
algorithm.
tracelogical or integer number, currently only used in the
default method ("Hartigan-Wong"): if positive (or true),
tracing information on the progress of the algorithm is
produced. Higher values may produce more tracing information.
A matrix, data frame, or a simple vector. If an atomic vector is
provided, it will be converted into a one-column matrix. When data = NULL,
the internal layout data will be used by default. Additionally, data can
be a function (including purrr-like lambdas), which will be applied to the
layout data.
It is important to note that we consider the rows as the observations. It
means the NROW(data) must return the same number with the specific layout
axis (meaning the x-axis for vertical stack layout, or y-axis for horizontal
stack layout).
heatmap_layout(): for column annotation, the layout data will be
transposed before using (If data is a function, it will be applied with
the transposed matrix). This is necessary because column annotation uses
heatmap columns as observations, but we need rows.
stack_layout(): the layout data will be used as it is since we place
all plots along a single axis.
A single boolean value indicates whether to set the active
context to current plot. If TRUE, all subsequent ggplot elements will be
added into this plot.
A string of the plot name. Used to switch the active context in
hmanno() or stack_active().
ggheatmap(matrix(rnorm(81), nrow = 9)) +
hmanno("t") +
align_kmeans(3L)
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