skbio.tree.TreeNode

class skbio.tree.TreeNode(name=None, length=None, parent=None, children=None)[source]

Representation of a node within a tree

A TreeNode instance stores links to its parent and optional children nodes. In addition, the TreeNode can represent a length (e.g., a branch length) between itself and its parent. Within this object, the use of “children” and “descendants” is frequent in the documentation. A child is a direct descendant of a node, while descendants are all nodes that are below a given node (e.g., grand-children, etc).

Parameters:

name : str or None

A node can have a name. It is common for tips in particular to have names, for instance, in a phylogenetic tree where the tips correspond to species.

length : float, int, or None

Distances between nodes can be used to represent evolutionary distances, time, etc.

parent : TreeNode or None

Connect this node to a parent

children : list of TreeNode or None

Connect this node to existing children

Attributes

name  
length  
parent  
children  
id  

Methods

copy.copy(tree) Returns a copy of self using an iterative approach
copy.deepcopy(tree) Returns a copy of self using an iterative approach
tree[x] Node delegates slicing to children.
iter(tree) Node iter iterates over the children.
len(tree) State: Experimental as of 0.4.0.
str(tree) Returns string version of self, with names and distances
accumulate_to_ancestor(ancestor) Return the sum of the distance between self and ancestor
ancestors() Returns all ancestors back to the root
append(node) Appends a node to children, in-place, cleaning up refs
ascii_art([show_internal, compact]) Returns a string containing an ascii drawing of the tree
assign_ids() Assign topologically stable unique ids to self
bifurcate([insert_length]) Reorders the tree into a bifurcating tree.
cache_attr(func, cache_attrname[, cache_type]) Cache attributes on internal nodes of the tree
compare_rfd(other[, proportion]) Calculates the Robinson and Foulds symmetric difference
compare_subsets(other[, exclude_absent_taxa]) Returns fraction of overlapping subsets where self and other differ.
compare_tip_distances(other[, sample, …]) Compares self to other using tip-to-tip distance matrices.
copy() Returns a copy of self using an iterative approach
count([tips]) Get the count of nodes in the tree
create_caches() Construct an internal lookups to facilitate searching by name
deepcopy() Returns a copy of self using an iterative approach
descending_branch_length([tip_subset]) Find total descending branch length from self or subset of self tips
distance(other) Return the distance between self and other
extend(nodes) Append a list of TreeNode to self.
find(name) Find a node by name.
find_all(name) Find all nodes that match name
find_by_func(func) Find all nodes given a function
find_by_id(node_id) Find a node by id.
from_linkage_matrix(linkage_matrix, id_list) Return tree from SciPy linkage matrix.
from_taxonomy(lineage_map) Construct a tree from a taxonomy
get_max_distance() Returns the max tip tip distance between any pair of tips
has_children() Returns True if the node has children.
index_tree() Index a tree for rapid lookups within a tree array
invalidate_caches([attr]) Delete lookup and attribute caches
is_root() Returns True if the current is a root, i.e.
is_tip() Returns True if the current node has no children.
lca(tipnames) Lowest common ancestor for a list of tips
levelorder([include_self]) Performs levelorder iteration over tree
lowest_common_ancestor(tipnames) Lowest common ancestor for a list of tips
neighbors([ignore]) Returns all nodes that are connected to self
non_tips([include_self]) Iterates over nontips descended from self
observed_node_counts(tip_counts) Returns counts of node observations from counts of tip observations
pop([index]) Remove a TreeNode from self.
postorder([include_self]) Performs postorder iteration over tree.
pre_and_postorder([include_self]) Performs iteration over tree, visiting node before and after
preorder([include_self]) Performs preorder iteration over tree
prune() Reconstructs correct topology after nodes have been removed.
read(file[, format]) Create a new TreeNode instance from a file.
remove(node) Remove a node from self
remove_deleted(func) Delete nodes in which func(node) evaluates True.
root() Returns root of the tree self is in
root_at(node) Return a new tree rooted at the provided node.
root_at_midpoint() Return a new tree rooted at midpoint of the two tips farthest apart
shear(names) Lop off tips until the tree just has the desired tip names.
shuffle([k, names, shuffle_f, n]) Yield trees with shuffled tip names
siblings() Returns all nodes that are children of self parent.
subset() Returns set of names that descend from specified node
subsets() Return all sets of names that come from self and its descendants
subtree([tip_list]) Make a copy of the subtree
tip_tip_distances([endpoints]) Returns distance matrix between pairs of tips, and a tip order.
tips([include_self]) Iterates over tips descended from self.
to_array([attrs, nan_length_value]) Return an array representation of self
to_taxonomy([allow_empty, filter_f]) Returns a taxonomy representation of self
traverse([self_before, self_after, include_self]) Returns iterator over descendants
unrooted_copy([parent]) Walks the tree unrooted-style and returns a copy
unrooted_deepcopy([parent]) Walks the tree unrooted-style and returns a new copy
write(file[, format]) Write an instance of TreeNode to a file.