Given a distance matrix for sorted objects, compute a hierarchical clustering preserving this
order. That is, this is similar to
hclust with the constraint that the result's order is
A distances object (as created by
The clustering method to use (only
If specified, assume the data will be re-ordered by this order.
Optionally, the number of members for each row/column of the distances (by default, one each).
order is specified, assumes that the data will be re-ordered by this order. That is,
the indices in the returned
hclust object will refer to the post-reorder data locations,
**not** to the current data locations.
This can be applied to the results of
slanted_reorder, to give a "plausible"
clustering for the data.
A clustering object (as created by
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