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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.

"""Utilities for handling, displaying and exporting Phylo trees.

Third-party libraries are loaded when the corresponding function is called.
__docformat__ = "epytext en"

import math
import sys

def to_networkx(tree):
    """Convert a Tree object to a networkx graph.

    The result is useful for graph-oriented analysis, and also interactive
    plotting with pylab, matplotlib or pygraphviz, though the resulting diagram
    is usually not ideal for displaying a phylogeny.

    Requires NetworkX version 0.99 or 1.0.
        import networkx
    except ImportError:
        from Bio import MissingPythonDependencyError
        raise MissingPythonDependencyError(
                "Install NetworkX if you want to use to_networkx.")

    def add_edge(graph, n1, n2):
        # NB (1/2010): the networkx API congealed recently
        # Ubuntu Lucid uses v0.99, newest is v1.0.1, let's support both
        if networkx.__version__ >= '1.0':
            graph.add_edge(n1, n2, weight=str(n2.branch_length or 1.0))
            # Copy branch color value as hex, if available
            if hasattr(n2, 'color') and n2.color is not None:
                graph[n1][n2]['color'] = n2.color.to_hex()
            elif hasattr(n1, 'color') and n1.color is not None:
                # Cascading color attributes
                graph[n1][n2]['color'] = n1.color.to_hex()
                n2.color = n1.color
            # Copy branch weight value (float) if available
            if hasattr(n2, 'width') and n2.width is not None:
                graph[n1][n2]['width'] = n2.width
            elif hasattr(n1, 'width') and n1.width is not None:
                # Cascading width attributes
                graph[n1][n2]['width'] = n1.width
                n2.width = n1.width
        elif networkx.__version__ >= '0.99':
            graph.add_edge(n1, n2, (n2.branch_length or 1.0))
            graph.add_edge(n1, n2)

    def build_subgraph(graph, top):
        """Walk down the Tree, building graphs, edges and nodes."""
        for clade in top:
            add_edge(graph, top.root, clade.root)
            build_subgraph(graph, clade)

    if tree.rooted:
        G = networkx.DiGraph()
        G = networkx.Graph()
    build_subgraph(G, tree.root)
    return G

def draw_graphviz(tree, label_func=str, prog='twopi', args='',
        node_color='#c0deff', **kwargs):
    """Display a tree or clade as a graph, using the graphviz engine.

    Requires NetworkX, matplotlib, Graphviz and either PyGraphviz or pydot.


        >>> import pylab
        >>> from Bio import Phylo
        >>> tree = Phylo.read('ex/apaf.xml', 'phyloxml')
        >>> Phylo.draw_graphviz(tree)
        >>> pylab.show()
        >>> pylab.savefig('apaf.png')

    The third and fourth parameters apply to Graphviz, and the remaining
    arbitrary keyword arguments are passed directly to networkx.draw(), which
    in turn mostly wraps matplotlib/pylab.  See the documentation for Graphviz
    and networkx for detailed explanations.

    The NetworkX/matplotlib parameters are described in the docstrings for
    networkx.draw() and pylab.scatter(), but the most reasonable options to try
    are: I{ alpha, node_color, node_size, node_shape, edge_color, style,
    font_size, font_color, font_weight, font_family }

    @param label_func: A function to extract a label from a node. By default
        this is str(), but you can use a different function to select another
        string associated with each node. If this function returns None for a
        node, no label will be shown for that node.

        The label will also be silently skipped if the throws an exception
        related to ordinary attribute access (LookupError, AttributeError,
        ValueError); all other exception types will still be raised. This
        means you can use a lambda expression that simply attempts to look up
        the desired value without checking if the intermediate attributes are

            >>> Phylo.draw_graphviz(tree, lambda n: n.taxonomies[0].code)

    @param prog: The Graphviz program to use when rendering the graph. 'twopi'
        behaves the best for large graphs, reliably avoiding crossing edges, but
        for moderate graphs 'neato' looks a bit nicer.  For small directed
        graphs, 'dot' may produce the most normal-looking phylogram, but will
        cross and distort edges in larger graphs. (The programs 'circo' and
        'fdp' are not recommended.)

    @param args: String of options passed to the external graphviz program.
        Normally not needed, but offered here for completeness.
        import networkx
    except ImportError:
        from Bio import MissingPythonDependencyError
        raise MissingPythonDependencyError(
                "Install NetworkX if you want to use to_networkx.")

    G = to_networkx(tree)
    Gi = networkx.convert_node_labels_to_integers(G, discard_old_labels=False)
        posi = networkx.pygraphviz_layout(Gi, prog, args=args)
    except ImportError:
            posi = networkx.pydot_layout(Gi, prog)
        except ImportError:
            raise MissingPythonDependencyError(
                    "Install PyGraphviz or Pydot if you want to use "
    posn = dict((n, posi[Gi.node_labels[n]]) for n in G)

    def get_label_mapping(G, selection):
        for node in G.nodes():
            if (selection is None) or (node in selection):
                    label = label_func(node)
                    if label not in (None, node.__class__.__name__):
                        yield (node, label)
                except (LookupError, AttributeError, ValueError):

    if 'nodelist' in kwargs:
        labels = dict(get_label_mapping(G, set(kwargs['nodelist'])))
        labels = dict(get_label_mapping(G, None))
    kwargs['nodelist'] = labels.keys()
    if 'edge_color' not in kwargs:
        kwargs['edge_color'] = [isinstance(e[2], dict) and
                                e[2].get('color', 'k') or 'k'
                                for e in G.edges(data=True)]
    if 'width' not in kwargs:
        kwargs['width'] = [isinstance(e[2], dict) and
                           e[2].get('width', 1.0) or 1.0
                           for e in G.edges(data=True)]
    networkx.draw(G, posn, labels=labels, node_color=node_color, **kwargs)

def draw_ascii(tree, file=sys.stdout, column_width=80):
    """Draw an ascii-art phylogram of the given tree.

    The printed result looks like::

                                        _________ Orange
                        |              |______________ Tangerine
         |              |          _________________________ Grapefruit
        _|              |_________|
         |                        |______________ Pummelo
         |__________________________________ Apple

    @param file: File handle opened for writing the output drawing.
    @param column_width: Total number of text columns used by the drawing.
    taxa = tree.get_terminals()
    # Some constants for the drawing calculations
    max_label_width = max(len(str(taxon)) for taxon in taxa)
    drawing_width = column_width - max_label_width - 1
    drawing_height = 2 * len(taxa) - 1

    def get_col_positions(tree):
        """Create a mapping of each clade to its column position."""
        depths = tree.depths()
        # If there are no branch lengths, assume unit branch lengths
        if not max(depths.itervalues()):
            depths = tree.depths(unit_branch_lengths=True)
        # Potential drawing overflow due to rounding -- 1 char per tree layer
        fudge_margin = int(math.ceil(math.log(len(taxa), 2)))
        cols_per_branch_unit = ((drawing_width - fudge_margin)
                                / float(max(depths.itervalues())))
        return dict((clade, int(round(blen*cols_per_branch_unit + 0.5)))
                    for clade, blen in depths.iteritems())

    def get_row_positions(tree):
        positions = dict((taxon, 2*idx) for idx, taxon in enumerate(taxa))
        def calc_row(clade):
            for subclade in clade:
                if subclade not in positions:
            positions[clade] = (positions[clade.clades[0]] +
                                positions[clade.clades[-1]]) / 2
        return positions

    col_positions = get_col_positions(tree)
    row_positions = get_row_positions(tree)
    char_matrix = [[' ' for x in range(drawing_width)]
                    for y in range(drawing_height)]

    def draw_clade(clade, startcol):
        thiscol = col_positions[clade]
        thisrow = row_positions[clade]
        # Draw a horizontal line
        for col in range(startcol, thiscol):
            char_matrix[thisrow][col] = '_'
        if clade.clades:
            # Draw a vertical line
            toprow = row_positions[clade.clades[0]]
            botrow = row_positions[clade.clades[-1]]
            for row in range(toprow+1, botrow+1):
                char_matrix[row][thiscol] = '|'
            # NB: Short terminal branches need something to stop rstrip()
            if (col_positions[clade.clades[0]] - thiscol) < 2:
                char_matrix[toprow][thiscol] = ','
            # Draw descendents
            for child in clade:
                draw_clade(child, thiscol+1)

    draw_clade(tree.root, 0)
    # Print the complete drawing
    for idx, row in enumerate(char_matrix):
        line = ''.join(row).rstrip()
        # Add labels for terminal taxa in the right margin
        if idx % 2 == 0:
            line += ' ' + str(taxa[idx/2])
        file.write(line + '\n')

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