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.
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