View source: R/cpp_functions.R
hctree_sort | R Documentation |
This function applies a hierarchical clustering tree (HCT) sorting algorithm to reorder rows of a proximity matrix. It supports external ordering constraints, different linkage-based order types, and optional flipping for optimal layout.
hctree_sort(distance_matrix, externalOrder = NULL, orderType, flipType)
distance_matrix |
A square numeric proximity matrix (either n × n or p × p) representing pairwise distances between items. |
externalOrder |
An integer vector specifying an initial or external ordering of the items (can be empty or NULL if not used). |
orderType |
An integer indicating the type of hierarchical clustering order to apply. |
flipType |
An integer indicating the flipping methods. |
distance_matrix
The input matrix must represent pairwise distances between items.
If you start with a similarity matrix (e.g., a correlation matrix), you must convert it to a dissimilarity matrix before use.
For example, for correlation-based similarities,
use as.matrix(as.dist(1 - cor_matrix))
or other appropriate transformations to convert it to a proper distance matrix.
The matrix should also be symmetric and non-negative.
orderType
Specifies the linkage method used for hierarchical clustering:
0
: Single-linkage
1
: Complete-linkage
2
: Average-linkage (UPGMA)
flipType
Controls how the branches of the clustering tree are flipped:
1
: Flip based on externalOrder
This option should be used only when externalOrder
is provided.
2
: Uncle-flipping
3
: Grandpa-flipping
Important:
Do not specify both flipType = 1
and a NULL
or missing externalOrder
.
When using flipType = 1
, externalOrder
must be a valid integer vector.
A list representing a dendrogram tree structure, containing:
left
, right
, and height
for tree construction,
and order
for the optimal leaf order.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.