# Copyright 2001 by Tarjei Mikkelsen.  All rights reserved.
# 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.

# get set abstraction for graph representation

from functools import reduce


# TODO - Subclass graph?
class MultiGraph(object):
    """A directed multigraph abstraction with labeled edges."""

    def __init__(self, nodes=()):
        """Initializes a new MultiGraph object."""
        self._adjacency_list = {}    # maps parent -> set of (child, label) pairs
        for n in nodes:
            self._adjacency_list[n] = set()
        self._label_map = {}         # maps label -> set of (parent, child) pairs

    def __eq__(self, g):
        """Returns true if g is equal to this graph."""
        return isinstance(g, MultiGraph) and \
               (self._adjacency_list == g._adjacency_list) and \
               (self._label_map == g._label_map)

    def __ne__(self, g):
        """Returns true if g is not equal to this graph."""
        return not self.__eq__(g)

    def __repr__(self):
        """Returns a unique string representation of this graph."""
        s = "<MultiGraph: "
        for key in sorted(self._adjacency_list):
            values = sorted(self._adjacency_list[key])
            s += "(%r: %s)" % (key, ",".join(repr(v) for v in values))
        return s + ">"

    def __str__(self):
        """Returns a concise string description of this graph."""
        nodenum = len(self._adjacency_list)
        edgenum = reduce(lambda x, y: x + y,
                         [len(v) for v in self._adjacency_list.values()])
        labelnum = len(self._label_map)
        return "<MultiGraph: " + \
               str(nodenum) + " node(s), " + \
               str(edgenum) + " edge(s), " + \
               str(labelnum) + " unique label(s)>"

    def add_node(self, node):
        """Adds a node to this graph."""
        if node not in self._adjacency_list:
            self._adjacency_list[node] = set()

    def add_edge(self, source, to, label=None):
        """Adds an edge to this graph."""
        if source not in self._adjacency_list:
            raise ValueError("Unknown <from> node: " + str(source))
        if to not in self._adjacency_list:
            raise ValueError("Unknown <to> node: " + str(to))
        edge = (to, label)
        self._adjacency_list[source].add(edge)
        if label not in self._label_map:
            self._label_map[label] = set()
        self._label_map[label].add((source, to))

    def child_edges(self, parent):
        """Returns a list of (child, label) pairs for parent."""
        if parent not in self._adjacency_list:
            raise ValueError("Unknown <parent> node: " + str(parent))
        return sorted(self._adjacency_list[parent])

    def children(self, parent):
        """Returns a list of unique children for parent."""
        return sorted(set(x[0] for x in self.child_edges(parent)))

    def edges(self, label):
        """Returns a list of all the edges with this label."""
        if label not in self._label_map:
            raise ValueError("Unknown label: " + str(label))
        return sorted(self._label_map[label])

    def labels(self):
        """Returns a list of all the edge labels in this graph."""
        return list(self._label_map.keys())

    def nodes(self):
        """Returns a list of the nodes in this graph."""
        return list(self._adjacency_list.keys())

    def parent_edges(self, child):
        """Returns a list of (parent, label) pairs for child."""
        if child not in self._adjacency_list:
            raise ValueError("Unknown <child> node: " + str(child))
        parents = []
        for parent, children in self._adjacency_list.items():
            for x in children:
                if x[0] == child:
                    parents.append((parent, x[1]))
        return sorted(parents)

    def parents(self, child):
        """Returns a list of unique parents for child."""
        return sorted(set(x[0] for x in self.parent_edges(child)))

    def remove_node(self, node):
        """Removes node and all edges connected to it."""
        if node not in self._adjacency_list:
            raise ValueError("Unknown node: " + str(node))
        # remove node (and all out-edges) from adjacency list
        del self._adjacency_list[node]
        # remove all in-edges from adjacency list
        for n in self._adjacency_list:
            self._adjacency_list[n] = set(x for x in self._adjacency_list[n]
                                          if x[0] != node)
        # remove all referring pairs in label map
        for label in list(self._label_map.keys()):  # we're editing this!
            lm = set(x for x in self._label_map[label]
                     if (x[0] != node) and (x[1] != node))
            # remove the entry completely if the label is now unused
            if lm:
                self._label_map[label] = lm
            else:
                del self._label_map[label]

    def remove_edge(self, parent, child, label):
        """Removes edge. -- NOT IMPLEMENTED"""
        # hm , this is a multigraph - how should this be implemented?
        raise NotImplementedError("remove_edge is not yet implemented")

# auxiliary graph functions


def df_search(graph, root=None):
    """Depth first search of g.

    Returns a list of all nodes that can be reached from the root node
    in depth-first order.

    If root is not given, the search will be rooted at an arbitrary node.
    """
    seen = {}
    search = []
    if len(graph.nodes()) < 1:
        return search
    if root is None:
        root = (graph.nodes())[0]
    seen[root] = 1
    search.append(root)
    current = graph.children(root)
    while len(current) > 0:
        node = current[0]
        current = current[1:]
        if node not in seen:
            search.append(node)
            seen[node] = 1
            current = graph.children(node) + current
    return search


def bf_search(graph, root=None):
    """Breadth first search of g.

    Returns a list of all nodes that can be reached from the root node
    in breadth-first order.

    If root is not given, the search will be rooted at an arbitrary node.
    """
    seen = {}
    search = []
    if len(graph.nodes()) < 1:
        return search
    if root is None:
        root = (graph.nodes())[0]
    seen[root] = 1
    search.append(root)
    current = graph.children(root)
    while len(current) > 0:
        node = current[0]
        current = current[1:]
        if node not in seen:
            search.append(node)
            seen[node] = 1
            current.extend(graph.children(node))
    return search