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# Copyright (C) 2009 by Eric Talevich (eric.talevich@gmail.com)
# This code is part of the Biopython distribution and governed by its
# license. Please see the LICENSE file that should have been included
# as part of this package.

"""Base classes for Bio.Phylo objects.

All object representations for phylogenetic trees should derive from these base
classes in order to use the common methods defined on them.
__docformat__ = "epytext en"

import collections
import copy
import itertools
import random
import re
import warnings
import Bio

from Bio.Phylo import _sugar

# General tree-traversal algorithms

def _level_traverse(root, get_children):
    """Traverse a tree in breadth-first (level) order."""
    Q = collections.deque([root])
    while Q:
        v = Q.popleft()
        yield v

def _preorder_traverse(root, get_children):
    """Traverse a tree in depth-first pre-order (parent before children)."""
    def dfs(elem):
        yield elem
        for v in get_children(elem):
            for u in dfs(v):
                yield u
    for elem in dfs(root):
        yield elem

def _postorder_traverse(root, get_children):
    """Traverse a tree in depth-first post-order (children before parent)."""
    def dfs(elem):
        for v in get_children(elem):
            for u in dfs(v):
                yield u
        yield elem
    for elem in dfs(root):
        yield elem

def _sorted_attrs(elem):
    """Get a flat list of elem's attributes, sorted for consistency."""
    singles = []
    lists = []
    # Sort attributes for consistent results
    for attrname, child in sorted(elem.__dict__.iteritems(),
                                  key=lambda kv: kv[0]):
        if child is None:
        if isinstance(child, list):
    return (x for x in singles + lists
            if isinstance(x, TreeElement))

# Factory functions to generalize searching for clades/nodes

def _identity_matcher(target):
    """Match a node to the target object by identity."""
    def match(node):
        return (node is target)
    return match

def _class_matcher(target_cls):
    """Match a node if it's an instance of the given class."""
    def match(node):
        return isinstance(node, target_cls)
    return match

def _string_matcher(target):
    def match(node):
        return unicode(node) == target
    return match

def _attribute_matcher(kwargs):
    """Match a node by specified attribute values.

    'terminal' is a special case: True restricts the search to external (leaf)
    nodes, False restricts to internal nodes, and None allows all tree elements
    to be searched, including phyloXML annotations.

    Otherwise, for a tree element to match the specification (i.e. for the
    function produced by _attribute_matcher to return True when given a tree
    element), it must have each of the attributes specified by the keys and
    match each of the corresponding values -- think 'and', not 'or', for
    multiple keys.
    def match(node):
        if 'terminal' in kwargs:
            # Special case: restrict to internal/external/any nodes
            kwa_copy = kwargs.copy()
            pattern = kwa_copy.pop('terminal')
            if (pattern is not None and
                (not hasattr(node, 'is_terminal') or
                    node.is_terminal() != pattern)):
                return False
            kwa_copy = kwargs
        for key, pattern in kwa_copy.iteritems():
            # Nodes must match all other specified attributes
            if not hasattr(node, key):
                return False
            target = getattr(node, key)
            if isinstance(pattern, basestring):
                return (isinstance(target, basestring) and
                        re.match(pattern+'$', target))
            if isinstance(pattern, bool):
                return (pattern == bool(target))
            if isinstance(pattern, int):
                return (pattern == target)
            if pattern is None:
                return (target is None)
            raise TypeError('invalid query type: %s' % type(pattern))
        return True
    return match

def _function_matcher(matcher_func):
    """Safer attribute lookup -- returns False instead of raising an error."""
    def match(node):
            return matcher_func(node)
        except (LookupError, AttributeError, ValueError, TypeError):
            return False
    return match

def _object_matcher(obj):
    """Retrieve a matcher function by passing an arbitrary object.

    i.e. passing a TreeElement such as a Node or Tree instance returns an
    identity matcher, passing a type such as the PhyloXML.Taxonomy class returns
    a class matcher, and passing a dictionary returns an attribute matcher.

    The resulting 'match' function returns True when given an object matching
    the specification (identity, type or attribute values), otherwise False.
    This is useful for writing functions that search the tree, and probably
    shouldn't be used directly by the end user.
    if isinstance(obj, TreeElement):
        return _identity_matcher(obj)
    if isinstance(obj, type):
        return _class_matcher(obj)
    if isinstance(obj, basestring):
        return _string_matcher(obj)
    if isinstance(obj, dict):
        return _attribute_matcher(obj)
    if callable(obj):
        return _function_matcher(obj)
    raise ValueError("%s (type %s) is not a valid type for comparison."
                     % (obj, type(obj)))

def _combine_matchers(target, kwargs, require_spec):
    """Merge target specifications with keyword arguments.

    Dispatch the components to the various matcher functions, then merge into a
    single boolean function.
    if not target:
        if not kwargs:
            if require_spec:
                raise ValueError("you must specify a target object or keyword "
            return lambda x: True
        return _attribute_matcher(kwargs)
    match_obj = _object_matcher(target)
    if not kwargs:
        return match_obj
    match_kwargs = _attribute_matcher(kwargs)
    return (lambda x: match_obj(x) and match_kwargs(x))

def _combine_args(first, *rest):
    """Convert [targets] or *targets arguments to a single iterable.

    This helps other functions work like the built-in functions `max` and
    # Background: is_monophyletic takes a single list or iterable (like the
    # same method in Bio.Nexus.Trees); root_with_outgroup and common_ancestor
    # take separate arguments. This mismatch was in the initial release and I
    # didn't notice the inconsistency until after Biopython 1.55. I can think
    # of cases where either style is more convenient, so let's support both
    # (for backward compatibility and consistency between methods).
    if hasattr(first, '__iter__') and not (isinstance(first, TreeElement) or
            isinstance(first, type) or isinstance(first, basestring) or
            isinstance(first, dict)):
        # `terminals` is an iterable of targets
        if rest:
            raise ValueError("Arguments must be either a single list of "
                    "targets, or separately specified targets "
                    "(e.g. foo(t1, t2, t3)), but not both.")
        return first
    # `terminals` is a single target -- wrap in a container
    return itertools.chain([first], rest)

# Class definitions

00214 class TreeElement(object):
    """Base class for all Bio.Phylo classes."""

00217     def __repr__(self):
        """Show this object's constructor with its primitive arguments."""
        def pair_as_kwarg_string(key, val):
            if isinstance(val, basestring):
                return "%s='%s'" % (key, _sugar.trim_str(unicode(val)))
            return "%s=%s" % (key, val)
        return u'%s(%s)' % (self.__class__.__name__,
                            ', '.join(pair_as_kwarg_string(key, val)
                                  for key, val in self.__dict__.iteritems()
                                  if val is not None and
                                  type(val) in (str, int, float, bool, unicode)

    __str__ = __repr__

00233 class TreeMixin(object):
    """Methods for Tree- and Clade-based classes.

    This lets Tree and Clade support the same traversal and searching
    operations without requiring Clade to inherit from Tree, so Clade isn't
    required to have all of Tree's attributes -- just 'root' (a Clade
    instance) and 'is_terminal()'.
    # Traversal methods

00243     def _filter_search(self, filter_func, order, follow_attrs):
        """Perform a BFS or DFS traversal through all elements in this tree.

        @return: generator of all elements for which 'filter_func' is True.
        order_opts = {'preorder': _preorder_traverse,
                      'postorder': _postorder_traverse,
                      'level': _level_traverse}
            order_func = order_opts[order]
        except KeyError:
            raise ValueError("Invalid order '%s'; must be one of: %s"
                             % (order, tuple(order_opts.keys())))
        if follow_attrs:
            get_children = _sorted_attrs
            root = self
            get_children = lambda elem: elem.clades
            root = self.root
        return itertools.ifilter(filter_func, order_func(root, get_children))

00264     def find_any(self, *args, **kwargs):
        """Return the first element found by find_elements(), or None.

        This is also useful for checking whether any matching element exists in
        the tree, and can be used in a conditional expression.
        hits = self.find_elements(*args, **kwargs)
            return hits.next()
        except StopIteration:
            return None

00276     def find_elements(self, target=None, terminal=None, order='preorder',
        """Find all tree elements matching the given attributes.

        The arbitrary keyword arguments indicate the attribute name of the
        sub-element and the value to match: string, integer or boolean. Strings
        are evaluated as regular expression matches; integers are compared
        directly for equality, and booleans evaluate the attribute's truth value
        (True or False) before comparing. To handle nonzero floats, search with
        a boolean argument, then filter the result manually.

        If no keyword arguments are given, then just the class type is used for

        The result is an iterable through all matching objects, by depth-first
        search. (Not necessarily the same order as the elements appear in the
        source file!)


            >>> from Bio.Phylo.IO import PhyloXMIO
            >>> phx = PhyloXMLIO.read('phyloxml_examples.xml')
            >>> matches = phx.phylogenies[5].find_elements(code='OCTVU')
            >>> matches.next()
            Taxonomy(code='OCTVU', scientific_name='Octopus vulgaris')

        @param target: 
            Specifies the characteristics to search for. (The default,
            TreeElement, matches any standard Bio.Phylo type.)
        @type target: TreeElement instance, type, dict, or callable

        @param terminal:
            A boolean value to select for or against terminal nodes (a.k.a. leaf
            nodes). True searches for only terminal nodes, False excludes
            terminal nodes, and the default, None, searches both terminal and
            non-terminal nodes, as well as any tree elements lacking the
            'is_terminal' method.
        @type terminal: bool

        @param order:
            Tree traversal order: 'preorder' (default) is depth-first search,
            'postorder' is DFS with child nodes preceding parents, and 'level'
            is breadth-first search.
        @type order: string ('preorder'|'postorder'|'level')
        if terminal is not None:
            kwargs['terminal'] = terminal
        is_matching_elem = _combine_matchers(target, kwargs, False)
        return self._filter_search(is_matching_elem, order, True)

00326     def find_clades(self, target=None, terminal=None, order='preorder',
        """Find each clade containing a matching element.

        That is, find each element as with find_elements(), but return the
        corresponding clade object. (This is usually what you want.)

        The result is an iterable through all matching objects, searching
        depth-first (preorder) by default.
        def match_attrs(elem):
            orig_clades = elem.__dict__.pop('clades')
            found = elem.find_any(target, **kwargs)
            elem.clades = orig_clades
            return (found is not None)
        if terminal is None:
            is_matching_elem = match_attrs
            def is_matching_elem(elem):
                return ((elem.is_terminal() == terminal) and
        return self._filter_search(is_matching_elem, order, False)

00349     def get_path(self, target=None, **kwargs):
        """List the clades directly between this root and the given target.

        Returns a list of all clade objects along this path, ending with
        the given target, but excluding the root clade.
        # Only one path will work -- ignore weights and visits
        path = []
        match = _combine_matchers(target, kwargs, True)
        def check_in_path(v):
            if match(v):
                return True
            elif v.is_terminal():
                return False
            for child in v:
                if check_in_path(child):
                    return True
            return False
        if not check_in_path(self.root):
            return None
        return path[-2::-1]

00373     def get_nonterminals(self, order='preorder'):
        """Get a list of all of this tree's nonterminal (internal) nodes."""
        return list(self.find_clades(terminal=False, order=order))

00377     def get_terminals(self, order='preorder'):
        """Get a list of all of this tree's terminal (leaf) nodes."""
        return list(self.find_clades(terminal=True, order=order))

00381     def trace(self, start, finish):
        """List of all clade object between two targets in this tree.

        Excluding start, including finish.
        mrca = self.common_ancestor(start, finish)
        fromstart = mrca.get_path(start)[-2::-1]
        to = mrca.get_path(finish)
        return fromstart + [mrca] + to

    # Information methods

00393     def common_ancestor(self, targets, *more_targets):
        """Most recent common ancestor (clade) of all the given targets.

        Edge cases: 

            - If no target is given, returns self.root
            - If 1 target is given, returns the target
            - If any target is not found in this tree, raises a ValueError
        paths = [self.get_path(t)
                 for t in _combine_args(targets, *more_targets)]
        # Validation -- otherwise izip throws a spooky error below
        for p, t in zip(paths, targets):
            if p is None:
                raise ValueError("target %s is not in this tree" % repr(t))
        mrca = self.root
        for level in itertools.izip(*paths):
            ref = level[0]
            for other in level[1:]:
                if ref is not other:
                mrca = ref
            if ref is not mrca:
        return mrca

00420     def count_terminals(self):
        """Counts the number of terminal (leaf) nodes within this tree."""
        return _sugar.iterlen(self.find_clades(terminal=True))

00424     def depths(self, unit_branch_lengths=False):
        """Create a mapping of tree clades to depths (by branch length).

        The result is a dictionary where the keys are all of the Clade instances
        in the tree, and the values are the distance from the root to each clade
        (including terminals).
        By default the distance is the cumulative branch length leading to the
        clade. With the unit_branch_lengths=True option, only the number of
        branches (levels in the tree) is counted.

        @return: dict of {clade: depth}
        if unit_branch_lengths:
            depth_of = lambda c: 1
            depth_of = lambda c: c.branch_length or 0
        depths = {}
        def update_depths(node, curr_depth):
            depths[node] = curr_depth
            for child in node.clades:
                new_depth = curr_depth + depth_of(child)
                update_depths(child, new_depth)
        update_depths(self.root, 0)
        return depths

00450     def distance(self, target1, target2=None):
        """Calculate the sum of the branch lengths between two targets.

        If only one target is specified, the other is the root of this tree.
        if target2 is None:
            return sum(n.branch_length for n in self.get_path(target1)
                       if n.branch_length is not None)
        mrca = self.common_ancestor(target1, target2)
        return mrca.distance(target1) + mrca.distance(target2)

00461     def is_bifurcating(self):
        """Return True if tree downstream of node is strictly bifurcating.
        I.e., all nodes have either 2 or 0 children (internal or external,
        respectively). The root may have 3 descendents and still be considered
        part of a bifurcating tree, because it has no ancestor.
        # Root can be trifurcating
        if isinstance(self, Tree) and len(self.root) == 3:
            return (self.root.clades[0].is_bifurcating() and
                    self.root.clades[1].is_bifurcating() and
        if len(self.root) == 2:
            return (self.root.clades[0].is_bifurcating() and
        if len(self.root) == 0:
            return True
        return False

00480     def is_monophyletic(self, terminals, *more_terminals):
        """MRCA of terminals if they comprise a complete subclade, or False.

        I.e., there exists a clade such that its terminals are the same set as
        the given targets.

        The given targets must be terminals of the tree.

        To match both Bio.Nexus.Trees and the other multi-target methods in
        Bio.Phylo, arguments to this method can be specified either of two ways:
        (i) as a single list of targets, or (ii) separately specified targets,
        e.g. is_monophyletic(t1, t2, t3) -- but not both.

        For convenience, this method returns the common ancestor (MCRA) of the
        targets if they are monophyletic (instead of the value True), and False

        @return: common ancestor if terminals are monophyletic, otherwise False.
        target_set = set(_combine_args(terminals, *more_terminals))
        current = self.root
        while True:
            if set(current.get_terminals()) == target_set:
                return current
            # Try a narrower subclade
            for subclade in current.clades:
                if set(subclade.get_terminals()).issuperset(target_set):
                    current = subclade
                return False

00512     def is_parent_of(self, target=None, **kwargs):
        """True if target is a descendent of this tree.

        Not required to be a direct descendent.
        To check only direct descendents of a clade, simply use list membership
        testing: "if subclade in clade: ..."
        return self.get_path(target, **kwargs) is not None

00522     def is_preterminal(self):
        """True if all direct descendents are terminal."""
        if self.root.is_terminal():
            return False
        for clade in self.root.clades:
            if not clade.is_terminal():
                return False
        return True

00531     def total_branch_length(self):
        """Calculate the sum of all the branch lengths in this tree."""
        return sum(node.branch_length
                   for node in self.find_clades(branch_length=True))

    # Tree manipulation methods

00538     def collapse(self, target=None, **kwargs):
        """Deletes target from the tree, relinking its children to its parent.

        @return: the parent clade.
        path = self.get_path(target, **kwargs)
        if not path:
            raise ValueError("couldn't collapse %s in this tree"
                             % (target or kwargs))
        if len(path) == 1:
            parent = self.root
            parent = path[-2]
        popped = parent.clades.pop(parent.clades.index(path[-1]))
        extra_length = popped.branch_length or 0
        for child in popped:
            child.branch_length += extra_length
        return parent

00558     def collapse_all(self, target=None, **kwargs):
        """Collapse all the descendents of this tree, leaving only terminals.

        Total branch lengths are preserved, i.e. the distance to each terminal
        stays the same.

        For example, this will safely collapse nodes with poor bootstrap

            >>> tree.collapse_all(lambda c: c.confidence is not None and
            ...                   c.confidence < 70)

        This implementation avoids strange side-effects by using level-order
        traversal and testing all clade properties (versus the target
        specification) up front. In particular, if a clade meets the target
        specification in the original tree, it will be collapsed.  For example,
        if the condition is:

            >>> tree.collapse_all(lambda c: c.branch_length < 0.1)

        Collapsing a clade's parent node adds the parent's branch length to the
        child, so during the execution of collapse_all, a clade's branch_length
        may increase. In this implementation, clades are collapsed according to
        their properties in the original tree, not the properties when tree
        traversal reaches the clade. (It's easier to debug.) If you want the
        other behavior (incremental testing), modifying the source code of this
        function is straightforward.
        # Read the iterable into a list to protect against in-place changes
        internals = list(self.find_clades(target, False, 'level', **kwargs))
        # Skip the root node -- it can't be collapsed
        if internals[0] == self.root:
        for clade in internals:

00594     def ladderize(self, reverse=False):
        """Sort clades in-place according to the number of terminal nodes.

        Deepest clades are last by default. Use reverse=True to sort clades
        self.root.clades.sort(key=lambda c: c.count_terminals(),
        for subclade in self.root.clades:

00605     def prune(self, target=None, **kwargs):
        """Prunes a terminal clade from the tree.

        If taxon is from a bifurcation, the connecting node will be collapsed
        and its branch length added to remaining terminal node. This might be no
        longer be a meaningful value.

        @return: parent clade of the pruned target
        if 'terminal' in kwargs and kwargs['terminal']:
            raise ValueError("target must be terminal")
        path = self.get_path(target, terminal=True, **kwargs)
        if not path:
            raise ValueError("can't find a matching target below this root")
        if len(path) == 1:
            parent = self.root
            parent = path[-2]
        if len(parent) == 1:
            # We deleted a branch from a bifurcation
            if parent == self.root:
                # If we're at the root, move the root upwards
                # NB: This loses the length of the original branch
                newroot = parent.clades[0]
                newroot.branch_length = None
                parent = self.root = newroot
                # If we're not at the root, collapse this parent
                child = parent.clades[0]
                if child.branch_length is not None:
                    child.branch_length += (parent.branch_length or 0.0)
                if len(path) < 3:
                    grandparent = self.root
                    grandparent = path[-3]
                # Replace parent with child at the same place in grandparent
                index = grandparent.clades.index(parent)
                grandparent.clades.insert(index, child)
                parent = grandparent
        return parent

00648     def split(self, n=2, branch_length=1.0):
        """Generate n (default 2) new descendants.

        In a species tree, this is a speciation event.

        New clades have the given branch_length and the same name as this
        clade's root plus an integer suffix (counting from 0). For example,
        splitting a clade named "A" produces sub-clades named "A0" and "A1".
        clade_cls = type(self.root)
        base_name = self.root.name or ''
        for i in range(n):
            clade = clade_cls(name=base_name+str(i),

00665 class Tree(TreeElement, TreeMixin):
    """A phylogenetic tree, containing global info for the phylogeny.

    The structure and node-specific data is accessible through the 'root'
    clade attached to the Tree instance.

    @param root:
        The starting node of the tree. If the tree is rooted, this will usually
        be the root node.
    @type root: Clade

    @param rooted:
        Whether or not the tree is rooted. By default, a tree is assumed to be
    @type rooted: bool

    @param id: The identifier of the tree, if there is one.
    @type id: str

    @param name: The name of the tree, in essence a label.
    @type name: str
    def __init__(self, root=None, rooted=True, id=None, name=None):
        self.root = root or Clade()
        self.rooted = rooted
        self.id = id
        self.name = name

00694     def from_clade(cls, clade, **kwargs):
        """Create a new Tree object given a clade.

        Keyword arguments are the usual Tree constructor parameters.
        root = copy.deepcopy(clade)
        return cls(root, **kwargs)

00703     def randomized(cls, taxa, branch_length=1.0, branch_stdev=None):
        """Create a randomized bifurcating tree given a list of taxa.

        @param taxa: Either an integer specifying the number of taxa to create
            (automatically named taxon#), or an iterable of taxon names, as

        @return: a tree of the same type as this class.
        if isinstance(taxa, int):
            taxa = ['taxon%s' % (i+1) for i in range(taxa)]
        elif hasattr(taxa, '__iter__'):
            taxa = list(taxa)
            raise TypeError("taxa argument must be integer (# taxa) or "
                            "iterable of taxon names.")
        rtree = cls()
        terminals = [rtree.root]
        while len(terminals) < len(taxa):
            newsplit = random.choice(terminals)
            newterms = newsplit.split(branch_length=branch_length)
            if branch_stdev:
                # Add some noise to the branch lengths
                for nt in newterms:
                    nt.branch_length = max(0,
                            random.gauss(branch_length, branch_stdev))
        # Distribute taxon labels randomly
        for node, name in zip(terminals, taxa):
            node.name = name
        return rtree

00738     def clade(self):
        """The first clade in this tree (not itself)."""
        return self.root

00742     def as_phyloxml(self, **kwargs):
        """Convert this tree to a PhyloXML-compatible Phylogeny.

        This lets you use the additional annotation types PhyloXML defines, and
        save this information when you write this tree as 'phyloxml'.
        from Bio.Phylo.PhyloXML import Phylogeny
        return Phylogeny.from_tree(self, **kwargs)

00751     def root_with_outgroup(self, outgroup_targets, *more_targets):
        """Reroot this tree with the outgroup clade containing outgroup_targets.

        Operates in-place.

        Edge cases:

         - If outgroup == self.root, no change
         - If outgroup is terminal, create new bifurcating root node with a
           0-length branch to the outgroup
         - If outgroup is internal, use the given outgroup node as the new
           trifurcating root, keeping branches the same
         - If the original root was bifurcating, drop it from the tree,
           preserving total branch lengths
        # This raises a ValueError if any target is not in this tree
        # Otherwise, common_ancestor guarantees outgroup is in this tree
        outgroup = self.common_ancestor(outgroup_targets, *more_targets)
        outgroup_path = self.get_path(outgroup)
        if len(outgroup_path) == 0:
            # Outgroup is the current root -- no change

        prev_blen = outgroup.branch_length
        if outgroup.is_terminal():
            # Create a new root with a 0-length branch to the outgroup
            outgroup.branch_length = 0.0
            new_root = self.root.__class__(
                    branch_length=self.root.branch_length, clades=[outgroup])
            # The first branch reversal (see the upcoming loop) is modified
            if len(outgroup_path) == 1:
                # Trivial tree like '(A,B);
                new_parent = new_root
                parent = outgroup_path.pop(-2)
                prev_blen, parent.branch_length = parent.branch_length, prev_blen
                new_root.clades.insert(0, parent)
                new_parent = parent
            # Use the given outgroup node as the new (trifurcating) root
            new_root = outgroup
            new_root.branch_length = self.root.branch_length
            new_parent = new_root

        # Tracing the outgroup lineage backwards, reattach the subclades under a
        # new root clade. Reverse the branches directly above the outgroup in
        # the tree, but keep the descendants of those clades as they are.
        for parent in outgroup_path[-2::-1]:
            prev_blen, parent.branch_length = parent.branch_length, prev_blen
            new_parent.clades.insert(0, parent)
            new_parent = parent

        # Finally, handle the original root according to number of descendents
        old_root = self.root
        if outgroup in old_root.clades:
            assert len(outgroup_path) == 1
        if len(old_root) == 1:
            # Delete the old bifurcating root & add branch lengths
            ingroup = old_root.clades[0]
            if ingroup.branch_length:
                ingroup.branch_length += prev_blen
                ingroup.branch_length = prev_blen
            new_parent.clades.insert(0, ingroup)
            # ENH: If annotations are attached to old_root, do... something.
            # Keep the old trifurcating/polytomous root as an internal node
            old_root.branch_length = prev_blen
            new_parent.clades.insert(0, old_root)

        self.root = new_root
        self.rooted = True

    # Method assumed by TreeMixin

00832     def is_terminal(self):
        """True if the root of this tree is terminal."""
        return (not self.root.clades)

    # Convention from SeqRecord and Alignment classes  

00838     def __format__(self, format_spec):
        """Serialize the tree as a string in the specified file format.

        This method supports the format() built-in function added in Python
        2.6/3.0. The format_spec should be a lower case string supported by
        Bio.Phylo.write as an output file format. 
        if format_spec:
            from StringIO import StringIO
            from Bio.Phylo import _io
            handle = StringIO()
            _io.write([self], handle, format_spec)
            return handle.getvalue()
            # Follow python convention and default to using __str__
            return str(self)

00855     def format(self, format):
        """Serialize the tree as a string in the specified file format.

        This duplicates the __format__ magic method for pre-2.6 Pythons.
        return self.__format__(format)

    # Pretty-printer for the entire tree hierarchy

00864     def __str__(self):
        """String representation of the entire tree.

        Serializes each sub-clade recursively using repr() to create a summary
        of the object structure.
        TAB = '    '
        textlines = []
        def print_tree(obj, indent):
            """Recursively serialize sub-elements.

            This closes over textlines and modifies it in-place.
            textlines.append(TAB*indent + repr(obj))
            indent += 1
            for attr in obj.__dict__:
                child = getattr(obj, attr)
                if isinstance(child, TreeElement):
                    print_tree(child, indent)
                elif isinstance(child, list):
                    for elem in child:
                        if isinstance(elem, TreeElement):
                            print_tree(elem, indent)
        print_tree(self, 0)
        return '\n'.join(textlines)

00891 class Clade(TreeElement, TreeMixin):
    """A recursively defined sub-tree.

    @param branch_length:
        The length of the branch leading to the root node of this clade.
    @type branch_length: str

    @param name: The clade's name (a label).
    @type name: str

    @param clades: Sub-trees rooted directly under this tree's root.
    @type clades: list
    def __init__(self, branch_length=None, name=None, clades=None,
        self.branch_length = branch_length
        self.name = name
        self.clades = clades or []
        self.confidence = confidence

00912     def root(self):
        """Allow TreeMixin methods to traverse clades properly."""
        return self

00916     def is_terminal(self):
        """True if this is a terminal (leaf) node."""
        return (not self.clades)

    # Sequence-type behavior methods

00922     def __getitem__(self, index):
        """Get clades by index (integer or slice)."""
        if isinstance(index, int) or isinstance(index, slice):
            return self.clades[index]
        ref = self
        for idx in index:
            ref = ref[idx]
        return ref

00931     def __iter__(self):
        """Iterate through this tree's direct descendent clades (sub-trees)."""
        return iter(self.clades)

00935     def __len__(self):
        """Number of clades directy under the root."""
        return len(self.clades)

00939     def __nonzero__(self):
        """Boolean value of an instance of this class.

        NB: If this method is not defined, but __len__  is, then the object is
        considered true if the result of __len__() is nonzero. We want Clade
        instances to always be considered true.
        return True

    def __str__(self):
        if self.name:
            return _sugar.trim_str(self.name, maxlen=40)
        return self.__class__.__name__

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