# Natural Language Toolkit: Lexical Functional Grammar
#
# Author: Dan Garrette <dhgarrette@gmail.com>
#
# Copyright (C) 2001-2021 NLTK Project
# URL: <http://nltk.org/>
# For license information, see LICENSE.TXT

from itertools import chain

from nltk.internals import Counter


class FStructure(dict):
    def safeappend(self, key, item):
        """
        Append 'item' to the list at 'key'.  If no list exists for 'key', then
        construct one.
        """
        if key not in self:
            self[key] = []
        self[key].append(item)

    def __setitem__(self, key, value):
        dict.__setitem__(self, key.lower(), value)

    def __getitem__(self, key):
        return dict.__getitem__(self, key.lower())

    def __contains__(self, key):
        return dict.__contains__(self, key.lower())

    def to_glueformula_list(self, glue_dict):
        depgraph = self.to_depgraph()
        return glue_dict.to_glueformula_list(depgraph)

    def to_depgraph(self, rel=None):
        from nltk.parse.dependencygraph import DependencyGraph

        depgraph = DependencyGraph()
        nodes = depgraph.nodes

        self._to_depgraph(nodes, 0, "ROOT")

        # Add all the dependencies for all the nodes
        for address, node in nodes.items():
            for n2 in (n for n in nodes.values() if n["rel"] != "TOP"):
                if n2["head"] == address:
                    relation = n2["rel"]
                    node["deps"].setdefault(relation, [])
                    node["deps"][relation].append(n2["address"])

        depgraph.root = nodes[1]

        return depgraph

    def _to_depgraph(self, nodes, head, rel):
        index = len(nodes)

        nodes[index].update(
            {
                "address": index,
                "word": self.pred[0],
                "tag": self.pred[1],
                "head": head,
                "rel": rel,
            }
        )

        for feature in sorted(self):
            for item in sorted(self[feature]):
                if isinstance(item, FStructure):
                    item._to_depgraph(nodes, index, feature)
                elif isinstance(item, tuple):
                    new_index = len(nodes)
                    nodes[new_index].update(
                        {
                            "address": new_index,
                            "word": item[0],
                            "tag": item[1],
                            "head": index,
                            "rel": feature,
                        }
                    )
                elif isinstance(item, list):
                    for n in item:
                        n._to_depgraph(nodes, index, feature)
                else:
                    raise Exception(
                        "feature %s is not an FStruct, a list, or a tuple" % feature
                    )

    @staticmethod
    def read_depgraph(depgraph):
        return FStructure._read_depgraph(depgraph.root, depgraph)

    @staticmethod
    def _read_depgraph(node, depgraph, label_counter=None, parent=None):
        if not label_counter:
            label_counter = Counter()

        if node["rel"].lower() in ["spec", "punct"]:
            # the value of a 'spec' entry is a word, not an FStructure
            return (node["word"], node["tag"])

        else:
            fstruct = FStructure()
            fstruct.pred = None
            fstruct.label = FStructure._make_label(label_counter.get())

            fstruct.parent = parent

            word, tag = node["word"], node["tag"]
            if tag[:2] == "VB":
                if tag[2:3] == "D":
                    fstruct.safeappend("tense", ("PAST", "tense"))
                fstruct.pred = (word, tag[:2])

            if not fstruct.pred:
                fstruct.pred = (word, tag)

            children = [depgraph.nodes[idx] for idx in
                        chain.from_iterable(node["deps"].values())]
            for child in children:
                fstruct.safeappend(
                    child["rel"],
                    FStructure._read_depgraph(child, depgraph, label_counter, fstruct),
                )

            return fstruct

    @staticmethod
    def _make_label(value):
        """
        Pick an alphabetic character as identifier for an entity in the model.

        :param value: where to index into the list of characters
        :type value: int
        """
        letter = [
            "f",
            "g",
            "h",
            "i",
            "j",
            "k",
            "l",
            "m",
            "n",
            "o",
            "p",
            "q",
            "r",
            "s",
            "t",
            "u",
            "v",
            "w",
            "x",
            "y",
            "z",
            "a",
            "b",
            "c",
            "d",
            "e",
        ][value - 1]
        num = int(value) // 26
        if num > 0:
            return letter + str(num)
        else:
            return letter

    def __repr__(self):
        return self.__str__().replace("\n", "")

    def __str__(self):
        return self.pretty_format()

    def pretty_format(self, indent=3):
        try:
            accum = "%s:[" % self.label
        except NameError:
            accum = "["
        try:
            accum += "pred '%s'" % (self.pred[0])
        except NameError:
            pass

        for feature in sorted(self):
            for item in self[feature]:
                if isinstance(item, FStructure):
                    next_indent = indent + len(feature) + 3 + len(self.label)
                    accum += "\n%s%s %s" % (
                        " " * (indent),
                        feature,
                        item.pretty_format(next_indent),
                    )
                elif isinstance(item, tuple):
                    accum += "\n%s%s '%s'" % (" " * (indent), feature, item[0])
                elif isinstance(item, list):
                    accum += "\n%s%s {%s}" % (
                        " " * (indent),
                        feature,
                        ("\n%s" % (" " * (indent + len(feature) + 2))).join(item),
                    )
                else:  # ERROR
                    raise Exception(
                        "feature %s is not an FStruct, a list, or a tuple" % feature
                    )
        return accum + "]"


def demo_read_depgraph():
    from nltk.parse.dependencygraph import DependencyGraph

    dg1 = DependencyGraph(
        """\
Esso       NNP     2       SUB
said       VBD     0       ROOT
the        DT      5       NMOD
Whiting    NNP     5       NMOD
field      NN      6       SUB
started    VBD     2       VMOD
production NN      6       OBJ
Tuesday    NNP     6       VMOD
"""
    )
    dg2 = DependencyGraph(
        """\
John    NNP     2       SUB
sees    VBP     0       ROOT
Mary    NNP     2       OBJ
"""
    )
    dg3 = DependencyGraph(
        """\
a       DT      2       SPEC
man     NN      3       SUBJ
walks   VB      0       ROOT
"""
    )
    dg4 = DependencyGraph(
        """\
every   DT      2       SPEC
girl    NN      3       SUBJ
chases  VB      0       ROOT
a       DT      5       SPEC
dog     NN      3       OBJ
"""
    )

    depgraphs = [dg1, dg2, dg3, dg4]
    for dg in depgraphs:
        print(FStructure.read_depgraph(dg))


if __name__ == "__main__":
    demo_read_depgraph()
