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Module « scipy.cluster.hierarchy »

Fonction to_tree - module scipy.cluster.hierarchy

Signature de la fonction to_tree

def to_tree(Z, rd=False) 

Description

help(scipy.cluster.hierarchy.to_tree)

Convert a linkage matrix into an easy-to-use tree object.

The reference to the root `ClusterNode` object is returned (by default).

Each `ClusterNode` object has a ``left``, ``right``, ``dist``, ``id``,
and ``count`` attribute. The left and right attributes point to
ClusterNode objects that were combined to generate the cluster.
If both are None then the `ClusterNode` object is a leaf node, its count
must be 1, and its distance is meaningless but set to 0.

*Note: This function is provided for the convenience of the library
user. ClusterNodes are not used as input to any of the functions in this
library.*

Parameters
----------
Z : ndarray
    The linkage matrix in proper form (see the `linkage`
    function documentation).
rd : bool, optional
    When False (default), a reference to the root `ClusterNode` object is
    returned.  Otherwise, a tuple ``(r, d)`` is returned. ``r`` is a
    reference to the root node while ``d`` is a list of `ClusterNode`
    objects - one per original entry in the linkage matrix plus entries
    for all clustering steps. If a cluster id is
    less than the number of samples ``n`` in the data that the linkage
    matrix describes, then it corresponds to a singleton cluster (leaf
    node).
    See `linkage` for more information on the assignment of cluster ids
    to clusters.

Returns
-------
tree : ClusterNode or tuple (ClusterNode, list of ClusterNode)
    If ``rd`` is False, a `ClusterNode`.
    If ``rd`` is True, a list of length ``2*n - 1``, with ``n`` the number
    of samples.  See the description of `rd` above for more details.

See Also
--------
linkage, is_valid_linkage, ClusterNode

Examples
--------
>>> import numpy as np
>>> from scipy.cluster import hierarchy
>>> rng = np.random.default_rng()
>>> x = rng.random((5, 2))
>>> Z = hierarchy.linkage(x)
>>> hierarchy.to_tree(Z)
<scipy.cluster.hierarchy.ClusterNode object at ...
>>> rootnode, nodelist = hierarchy.to_tree(Z, rd=True)
>>> rootnode
<scipy.cluster.hierarchy.ClusterNode object at ...
>>> len(nodelist)
9

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