<gh_stars>1-10

"""
Classes and functions for working with the components of *MRS objects.
"""

import re
import logging
import warnings
from collections import namedtuple, MutableMapping
from itertools import starmap

from delphin.exceptions import (XmrsError, XmrsStructureError)
from .config import (
    IVARG_ROLE, CONSTARG_ROLE, RSTR_ROLE,
    UNKNOWNSORT, HANDLESORT, CVARSORT, QUANTIFIER_POS,
    EQ_POST, HEQ_POST, NEQ_POST, H_POST,
    BARE_EQ_ROLE
)

# The classes below are generally just namedtuples with extra methods.
# The namedtuples sometimes have default values. thanks:
#   http://stackoverflow.com/a/16721002/1441112


# VARIABLES and LNKS

var_re = re.compile(r'^([-\w]*\D)(\d+)$')


def sort_vid_split(vs):
    """Split a valid variable string into the variable sort and id."""
    match = var_re.match(vs)
    if match is None:
        raise ValueError('Invalid variable string: {}'.format(str(vs)))
    else:
        return match.groups()


def var_sort(v):
    """Return the sort of a valid variable string."""
    return sort_vid_split(v)[0]


def var_id(v):
    """Return the integer id of a valid variable string."""
    return int(sort_vid_split(v)[1])


class _VarGenerator(object):
    """
    Simple class to produce variables, incrementing the vid for each
    one.
    """

    def __init__(self, starting_vid=1):
        self.vid = starting_vid
        self.index = {}  # to map vid to created variable
        self.store = {}  # to recall properties from varstrings

    def new(self, sort, properties=None):
        """
        Create a new variable for the given *sort*.
        """
        if sort is None:
            sort = UNKNOWNSORT
        # find next available vid
        vid, index = self.vid, self.index
        while vid in index:
            vid += 1
        varstring = '{}{}'.format(sort, vid)
        index[vid] = varstring
        if properties is None:
            properties = []
        self.store[varstring] = properties
        self.vid = vid + 1
        return (varstring, properties)


class Lnk(namedtuple('Lnk', ('type', 'data'))):
    """
    Lnk objects link predicates to the surface form in one of several
    ways, the most common of which being the character span of the
    original string.

    Args:
        data: the Lnk specifiers, whose quality depends on *type*
        type: the way the Lnk relates the semantics to the surface form

    Note:
        Valid *types* and their associated *data* shown in the table
        below.

        | type      | data                | example   |
        | --------- | ------------------- | --------- |
        | charspan  | surface string span | (0, 5)    |
        | chartspan | chart vertex span   | (0, 5)    |
        | tokens    | token identifiers   | (0, 1, 2) |
        | edge      | edge identifier     | 1         |


    Example:
        Lnk objects should be created using the classmethods:

        >>> Lnk.charspan(0,5)
        '<0:5>'
        >>> Lnk.chartspan(0,5)
        '<0#5>'
        >>> Lnk.tokens([0,1,2])
        '<0 1 2>'
        >>> Lnk.edge(1)
        '<@1>'
    """

    # These types determine how a lnk on an EP or MRS are to be
    # interpreted, and thus determine the data type/structure of the
    # lnk data.
    CHARSPAN = 0  # Character span; a pair of offsets
    CHARTSPAN = 1  # Chart vertex span: a pair of indices
    TOKENS = 2  # Token numbers: a list of indices
    EDGE = 3  # An edge identifier: a number

    def __init__(self, type, data):
        # class methods below use __new__ to instantiate data, so
        # don't do it here
        if type not in (Lnk.CHARSPAN, Lnk.CHARTSPAN, Lnk.TOKENS, Lnk.EDGE):
            raise XmrsError('Invalid Lnk type: {}'.format(type))

    @classmethod
    def charspan(cls, start, end):
        """
        Create a Lnk object for a character span.

        Args:
            start: the initial character position (cfrom)
            end: the final character position (cto)
        """
        return cls(Lnk.CHARSPAN, (int(start), int(end)))

    @classmethod
    def chartspan(cls, start, end):
        """
        Create a Lnk object for a chart span.

        Args:
            start: the initial chart vertex
            end: the final chart vertex
        """
        return cls(Lnk.CHARTSPAN, (int(start), int(end)))

    @classmethod
    def tokens(cls, tokens):
        """
        Create a Lnk object for a token range.

        Args:
            tokens: a list of token identifiers
        """
        return cls(Lnk.TOKENS, tuple(map(int, tokens)))

    @classmethod
    def edge(cls, edge):
        """
        Create a Lnk object for an edge (used internally in generation).

        Args:
            edge: an edge identifier
        """
        return cls(Lnk.EDGE, int(edge))

    def __str__(self):
        if self.type == Lnk.CHARSPAN:
            return '<{}:{}>'.format(self.data[0], self.data[1])
        elif self.type == Lnk.CHARTSPAN:
            return '<{}#{}>'.format(self.data[0], self.data[1])
        elif self.type == Lnk.EDGE:
            return '<@{}>'.format(self.data)
        elif self.type == Lnk.TOKENS:
            return '<{}>'.format(' '.join(map(str, self.data)))

    def __repr__(self):
        return '<Lnk object {} at {}>'.format(str(self), id(self))

    def __eq__(self, other):
        return self.type == other.type and self.data == other.data


class _LnkMixin(object):
    """
    A mixin class for predications ([EPs] or [Nodes]) or full [Xmrs]
    objects, which are the types that can be linked to surface strings.
    This class provides the `cfrom` and `cto` properties so they are
    always available (defaulting to a value of `-1` if there is no lnk
    or if the lnk is not a Lnk.CHARSPAN type).
    """
    @property
    def cfrom(self):
        """
        The initial character position in the surface string. Defaults
        to -1 if there is no valid cfrom value.
        """
        cfrom = -1
        try:
            if self.lnk.type == Lnk.CHARSPAN:
                cfrom = self.lnk.data[0]
        except AttributeError:
            pass  # use default cfrom of -1
        return cfrom

    @property
    def cto(self):
        """
        The final character position in the surface string. Defaults
        to -1 if there is no valid cto value.
        """
        cto = -1
        try:
            if self.lnk.type == Lnk.CHARSPAN:
                cto = self.lnk.data[1]
        except AttributeError:
            pass  # use default cto of -1
        return cto


# LINKS and CONSTRAINTS

class Link(namedtuple('Link', ('start', 'end', 'rargname', 'post'))):
    """
    DMRS-style dependency link.

    Links are a way of representing arguments without variables. A
    Link encodes a start and end node, the argument name, and label
    information (e.g. label equality, qeq, etc).
    """
    def __new__(cls, start, end, rargname, post):
        return super(Link, cls).__new__(
            cls, int(start), int(end), rargname, post
        )

    def __repr__(self):
        return '<Link object (#{} :{}/{}> #{}) at {}>'.format(
            self.start, self.rargname or '', self.post, self.end, id(self)
        )


def links(xmrs):
    """Return the list of [Links] for the *xmrs*."""

    # Links exist for every non-intrinsic argument that has a variable
    # that is the intrinsic variable of some other predicate, as well
    # as for label equalities when no argument link exists (even
    # considering transitivity).
    links = []
    prelinks = []

    _eps = xmrs._eps
    _hcons = xmrs._hcons
    _vars = xmrs._vars

    lsh = xmrs.labelset_heads
    lblheads = {v: lsh(v) for v, vd in _vars.items() if 'LBL' in vd['refs']}

    top = xmrs.top
    if top is not None:
        prelinks.append((0, top, None, top, _vars[top]))

    for nid, ep in _eps.items():
        for role, val in ep[3].items():
            if role == IVARG_ROLE or val not in _vars:
                continue
            prelinks.append((nid, ep[2], role, val, _vars[val]))

    for src, srclbl, role, val, vd in prelinks:
        if IVARG_ROLE in vd['refs']:
            tgtnids = [n for n in vd['refs'][IVARG_ROLE]
                       if not _eps[n].is_quantifier()]
            if len(tgtnids) == 0:
                continue  # maybe some bad MRS with a lonely quantifier
            tgt = tgtnids[0]  # what do we do if len > 1?
            tgtlbl = _eps[tgt][2]
            post = EQ_POST if srclbl == tgtlbl else NEQ_POST
        elif val in _hcons:
            lbl = _hcons[val][2]
            if lbl not in lblheads or len(lblheads[lbl]) == 0:
                continue  # broken MRS; log this?
            tgt = lblheads[lbl][0]  # sorted list; first item is most "heady"
            post = H_POST
        elif 'LBL' in vd['refs']:
            if val not in lblheads or len(lblheads[val]) == 0:
                continue  # broken MRS; log this?
            tgt = lblheads[val][0]  # again, should be sorted already
            post = HEQ_POST
        else:
            continue  # CARGs, maybe?
        links.append(Link(src, tgt, role, post))

    # now EQ links unattested by arg links
    for lbl, heads in lblheads.items():
        # I'm pretty sure this does what we want
        if len(heads) > 1:
            first = heads[0]
            for other in heads[1:]:
                links.append(Link(other, first, BARE_EQ_ROLE, EQ_POST))
        # If not, something like this is more explicit
        # lblset = self.labelset(lbl)
        # sg = g.subgraph(lblset)
        # ns = [nid for nid, deg in sg.degree(lblset).items() if deg == 0]
        # head = self.labelset_head(lbl)
        # for n in ns:
        #     links.append(Link(head, n, post=EQ_POST))
    return sorted(links)#, key=lambda link: (link.start, link.end))


class HandleConstraint(
        namedtuple('HandleConstraint', ('hi', 'relation', 'lo'))):
    """A relation between two handles."""

    QEQ = 'qeq'  # Equality modulo Quantifiers
    LHEQ = 'lheq'  # Label-Handle Equality
    OUTSCOPES = 'outscopes'  # Outscopes

    @classmethod
    def qeq(cls, hi, lo):
        return cls(hi, HandleConstraint.QEQ, lo)

    def __repr__(self):
        return '<HandleConstraint object ({} {} {}) at {}>'.format(
               str(self.hi), self.relation, str(self.lo), id(self)
        )


def hcons(xmrs):
    """Return the list of all [HandleConstraints] in *xmrs*."""
    return [
        HandleConstraint(hi, reln, lo)
        for hi, reln, lo in sorted(xmrs.hcons(), key=lambda hc: var_id(hc[0]))
    ]


IndividualConstraint = namedtuple('IndividualConstraint',
                                  ['left', 'relation', 'right'])


def icons(xmrs):
    """Return the list of all [IndividualConstraints] in *xmrs*."""
    return [
        IndividualConstraint(left, reln, right)
        for left, reln, right in sorted(xmrs.icons(),
                                        key=lambda ic: var_id(ic[0]))
    ]


# PREDICATES AND PREDICATIONS


class Pred(namedtuple('Pred', ('type', 'lemma', 'pos', 'sense', 'string'))):
    """
    A semantic predicate.

    **Abstract** predicates don't begin with an underscore, and they
    generally are defined as types in a grammar. **Surface**
    predicates always begin with an underscore (ignoring possible
    quotes), and are often defined as strings in a lexicon.

    In PyDelphin, Preds are equivalent if they have the same lemma,
    pos, and sense, and are both abstract or both surface preds.
    Other factors are ignored for comparison, such as their being
    string-, grammar-, or real-preds, whether they are quoted or not,
    whether they end with `_rel` or not, or differences in
    capitalization. Hashed Pred objects (e.g., in a dict or set) also
    use the normalized form. However, unlike with equality comparisons,
    Pred-formatted strings are not treated as equivalent in a hash.

    Args:
        type: the type of predicate; valid values are
            Pred.GRAMMARPRED, Pred.REALPRED, and Pred.STRINGPRED,
            although in practice Preds are instantiated via
            classmethods that select the type
        lemma: the lemma of the predicate
        pos: the part-of-speech; a single, lowercase character
        sense: the (often omitted) sense of the predicate
    Returns:
        a Pred object

    Example:
        Preds are compared using their string representations.
        Surrounding quotes (double or single) are ignored, and
        capitalization doesn't matter. In addition, preds may be
        compared directly to their string representations:

        >>> p1 = Pred.stringpred('_dog_n_1_rel')
        >>> p2 = Pred.realpred(lemma='dog', pos='n', sense='1')
        >>> p3 = Pred.grammarpred('dog_n_1_rel')
        >>> p1 == p2
        True
        >>> p1 == '_dog_n_1_rel'
        True
        >>> p1 == p3
        False
    """
    pred_re = re.compile(
        r'_?(?P<lemma>.*?)_'  # match until last 1 or 2 parts
        r'((?P<pos>[a-z])_)?'  # pos is always only 1 char
        r'((?P<sense>([^_\\]|(?:\\.))+)_)?'  # no unescaped _s
        r'(?P<end>rel)$',
        re.IGNORECASE
    )
    # Pred types (used mainly in input/output, not internally in pyDelphin)
    GRAMMARPRED = 0  # only a string allowed (quoted or not)
    REALPRED = 1  # may explicitly define lemma, pos, sense
    STRINGPRED = 2  # quoted string form of realpred

    def __eq__(self, other):
        if other is None:
            return False
        if not isinstance(other, Pred):
            other = Pred.stringpred(other)
        return self.short_form().lower() == other.short_form().lower()

    def __str__ (self):
        return self.string

    def __repr__(self):
        return '<Pred object {} at {}>'.format(self.string, id(self))

    def __hash__(self):
        return hash(self.short_form())

    @classmethod
    def stringpred(cls, predstr):
        """Return a Pred from its quoted string representation."""
        lemma, pos, sense, end = split_pred_string(predstr)
        return cls(Pred.STRINGPRED, lemma, pos, sense, predstr)

    @classmethod
    def grammarpred(cls, predstr):
        """Return a Pred from its symbol string."""
        lemma, pos, sense, end = split_pred_string(predstr)
        return cls(Pred.GRAMMARPRED, lemma, pos, sense, predstr)

    @staticmethod
    def string_or_grammar_pred(predstr):
        """Return a Pred from either its string or grammar symbol."""
        if predstr.strip('"').lstrip("'").startswith('_'):
            return Pred.stringpred(predstr)
        else:
            return Pred.grammarpred(predstr)

    @classmethod
    def realpred(cls, lemma, pos, sense=None):
        """Return a Pred from its components."""
        string_tokens = [lemma, pos]
        if sense is not None:
            sense = str(sense)
            string_tokens.append(sense)
        predstr = '_'.join([''] + string_tokens + ['rel'])
        return cls(Pred.REALPRED, lemma, pos, sense, predstr)

    def short_form(self):
        """
        Return the pred string without quotes or a _rel suffix.

        Example:

            >>> p = Pred.stringpred('"_cat_n_1_rel"')
            >>> p.short_form()
            '_cat_n_1'
        """
        return normalize_pred_string(self.string)

    def is_quantifier(self):
        """
        Return `True` if the predicate has a quantifier part-of-speech.

        *Deprecated since v0.6.0*
        """
        warnings.warn(
            'Deprecated; try checking xmrs.nodeids(quantifier=True)',
            DeprecationWarning
        )
        return self.pos == QUANTIFIER_POS


def split_pred_string(predstr):
    """
    Extract the components from a pred string and log errors for any
    malformedness.

    Args:
        predstr: a predicate string

    Examples:

        >>> Pred.split_pred_string('_dog_n_1_rel')
        ('dog', 'n', '1', 'rel')
        >>> Pred.split_pred_string('quant_rel')
        ('quant', None, None, 'rel')
    """
    predstr = predstr.strip('"\'')  # surrounding quotes don't matter
    rel_added = False
    if not predstr.lower().endswith('_rel'):
        logging.debug('Predicate does not end in "_rel": {}'
                      .format(predstr))
        rel_added = True
        predstr += '_rel'
    match = Pred.pred_re.search(predstr)
    if match is None:
        logging.debug('Unexpected predicate string: {}'.format(predstr))
        return (predstr, None, None, None)
    # _lemma_pos(_sense)?_end
    return (match.group('lemma'), match.group('pos'),
            match.group('sense'), None if rel_added else match.group('end'))


def is_valid_pred_string(predstr):
    """
    Return `True` if the given predicate string represents a valid
    Pred, `False` otherwise.
    """
    predstr = predstr.strip('"').lstrip("'")
    # this is a stricter regex than in Pred, but doesn't check POS
    return re.match(
        r'_([^ _\\]|\\.)+_[a-z](_([^ _\\]|\\.)+)?(_rel)?$'
        r'|[^_]([^ \\]|\\.)+(_rel)?$',
        predstr
    ) is not None


def normalize_pred_string(predstr):
    """
    Make pred strings more consistent by removing quotes and the _rel
    suffix, and by lowercasing them.
    """
    tokens = [t for t in split_pred_string(predstr)[:3] if t is not None]
    if predstr.lstrip('\'"')[:1] == '_':
        tokens = [''] + tokens
    return '_'.join(tokens).lower()


class Node(
    namedtuple('Node', ('nodeid', 'pred', 'sortinfo',
                        'lnk', 'surface', 'base', 'carg')),
    _LnkMixin):
    """
    A very simple predication for DMRSs. Nodes don't have arguments
    or labels like [ElementaryPredication] objects, but they do have
    a property for CARGs and contain their variable sort and
    properties in sortinfo.

    Args:
        nodeid: node identifier
        pred: node's Pred
        sortinfo: node properties (with cvarsort)
        lnk: Lnk object associated with the pred
        surface: surface string
        base: base form
        carg: constant argument string
    """

    def __new__(cls, nodeid, pred, sortinfo=None,
                 lnk=None, surface=None, base=None, carg=None):
        if sortinfo is None:
            sortinfo = {}
        elif not isinstance(sortinfo, MutableMapping):
            sortinfo = dict(sortinfo)
        return super(Node, cls).__new__(
            cls, nodeid, pred, sortinfo, lnk, surface, base, carg
        )

    def __repr__(self):
        lnk = ''
        if self.lnk is not None:
            lnk = str(self.lnk)
        return '<Node object ({} [{}{}]) at {}>'.format(
            self.nodeid, self.pred.string, lnk, id(self)
        )

    # note: without overriding __eq__, comparisons of sortinfo will be
    #       be different if they are OrderedDicts and not in the same
    #       order. Maybe this isn't a big deal?
    # def __eq__(self, other):
    #     # not doing self.__dict__ == other.__dict__ right now, because
    #     # functions like self.get_property show up there
    #     snid = self.nodeid
    #     onid = other.nodeid
    #     return ((None in (snid, onid) or snid == onid) and
    #             self.pred == other.pred and
    #             # make one side a regular dict for unordered comparison
    #             dict(self.sortinfo.items()) == other.sortinfo and
    #             self.lnk == other.lnk and
    #             self.surface == other.surface and
    #             self.base == other.base and
    #             self.carg == other.carg)

    def __lt__(self, other):
        warnings.warn("Deprecated", DeprecationWarning)
        x1 = (self.cfrom, self.cto, self.pred.pos != QUANTIFIER_POS,
              self.pred.lemma)
        try:
            x2 = (other.cfrom, other.cto, other.pred.pos != QUANTIFIER_POS,
                  other.pred.lemma)
            return x1 < x2
        except AttributeError:
            return NotImplemented

    @property
    def cvarsort(self):
        """
        The sortal type of the predicate.
        """
        return self.sortinfo.get(CVARSORT)

    @cvarsort.setter
    def cvarsort(self, value):
        self.sortinfo[CVARSORT] = value

    @property
    def properties(self):
        d = dict(self.sortinfo)
        if CVARSORT in d:
            del d[CVARSORT]
        return d

    def is_quantifier(self):
        """
        Return `True` if the Node's [Pred] appears to be a quantifier.

        *Deprecated since v0.6.0*
        """
        warnings.warn(
            'Deprecated; try checking xmrs.nodeids(quantifier=True)',
            DeprecationWarning
        )
        return self.pred.is_quantifier()


def nodes(xmrs):
    """Return the list of Nodes for *xmrs*."""
    nodes = []
    _props = xmrs.properties
    varsplit = sort_vid_split
    for p in xmrs.eps():
        sortinfo = None
        iv = p.intrinsic_variable
        if iv is not None:
            sort, _ = varsplit(iv)
            sortinfo = _props(iv)
            sortinfo[CVARSORT] = sort
        nodes.append(
            Node(p.nodeid, p.pred, sortinfo, p.lnk, p.surface, p.base, p.carg)
        )
    return nodes


class ElementaryPredication(
    namedtuple('ElementaryPredication',
               ('nodeid', 'pred', 'label', 'args', 'lnk', 'surface', 'base')),
    _LnkMixin):
    """
    An elementary predication (EP) combines a predicate with various
    structural semantic properties.

    EPs must have the `nodeid`, `pred`, and `label`, arguments,
    while the others are optional. MRS does not use nodeids, so it's
    fine to use `None`. Whenever an EP is used in an Xmrs, it gets
    assigned a nodeid. Generally EPs will have an ARG0 on their `args`
    dictionary to indicate their intrinisic variable, but it is not
    required.

    Args:
        nodeid: an int nodeid
        pred: The Pred of the EP
        label: label handle
        args: a mapping of role-argument names to values
        lnk: Lnk object associated with the pred
        surface: surface string
        base: base form
    """

    def __new__(cls, nodeid, pred, label, args=None,
                 lnk=None, surface=None, base=None):
        if args is None:
            args = {}
        if nodeid is not None:
            nodeid = int(nodeid)
        # else:
        #     args = dict((a.rargname, a) for a in args)
        return super(ElementaryPredication, cls).__new__(
            cls, nodeid, pred, label, args, lnk, surface, base
        )

    def __repr__(self):
        return '<ElementaryPredication object ({} ({})) at {}>'.format(
            self.pred.string, str(self.iv or '?'), id(self)
        )

    def __lt__(self, other):
        warnings.warn("Deprecated", DeprecationWarning)
        x1 = (self.cfrom, self.cto, -self.is_quantifier(), self.pred.lemma)
        try:
            x2 = (other.cfrom, other.cto, -other.is_quantifier(),
                  other.pred.lemma)
            return x1 < x2
        except AttributeError:
            return NotImplemented

    # these properties are specific to the EP's qualities

    @property
    def intrinsic_variable(self):
        """
        The value of the intrinsic argument (ARG0).
        """
        if IVARG_ROLE in self.args:
            return self.args[IVARG_ROLE]
        return None

    #: A synonym for ElementaryPredication.intrinsic_variable
    iv = intrinsic_variable

    @property
    def carg(self):
        """
        The value of the constant argument.
        """
        return self.args.get(CONSTARG_ROLE, None)

    def is_quantifier(self):
        """
        Return `True` if the EP is a quantifier predication.
        """
        return RSTR_ROLE in self.args


def elementarypredications(xmrs):
    """Return the list of [ElementaryPredication] objects in *xmrs*."""
    return list(starmap(ElementaryPredication, xmrs.eps()))


def elementarypredication(xmrs, nodeid):
    """
    Retrieve the EP with the given nodeid, or raises KeyError if no
    EP matches.

    Args:
        nodeid: The nodeid of the EP to return.
    Returns:
        An ElementaryPredication.
    """
    return ElementaryPredication(*xmrs.ep(nodeid))

"""
Classes and functions for working with the components of *MRS objects.
"""

import re
import logging
import warnings
from collections import namedtuple, MutableMapping
from itertools import starmap

from delphin.exceptions import (XmrsError, XmrsStructureError)
from .config import (
    IVARG_ROLE, CONSTARG_ROLE, RSTR_ROLE,
    UNKNOWNSORT, HANDLESORT, CVARSORT, QUANTIFIER_POS,
    EQ_POST, HEQ_POST, NEQ_POST, H_POST,
    BARE_EQ_ROLE
)

# The classes below are generally just namedtuples with extra methods.
# The namedtuples sometimes have default values. thanks:
#   http://stackoverflow.com/a/16721002/1441112


# VARIABLES and LNKS

var_re = re.compile(r'^([-\w]*\D)(\d+)$')


def sort_vid_split(vs):
    """Split a valid variable string into the variable sort and id."""
    match = var_re.match(vs)
    if match is None:
        raise ValueError('Invalid variable string: {}'.format(str(vs)))
    else:
        return match.groups()


def var_sort(v):
    """Return the sort of a valid variable string."""
    return sort_vid_split(v)[0]


def var_id(v):
    """Return the integer id of a valid variable string."""
    return int(sort_vid_split(v)[1])


class _VarGenerator(object):
    """
    Simple class to produce variables, incrementing the vid for each
    one.
    """

    def __init__(self, starting_vid=1):
        self.vid = starting_vid
        self.index = {}  # to map vid to created variable
        self.store = {}  # to recall properties from varstrings

    def new(self, sort, properties=None):
        """
        Create a new variable for the given *sort*.
        """
        if sort is None:
            sort = UNKNOWNSORT
        # find next available vid
        vid, index = self.vid, self.index
        while vid in index:
            vid += 1
        varstring = '{}{}'.format(sort, vid)
        index[vid] = varstring
        if properties is None:
            properties = []
        self.store[varstring] = properties
        self.vid = vid + 1
        return (varstring, properties)


class Lnk(namedtuple('Lnk', ('type', 'data'))):
    """
    Lnk objects link predicates to the surface form in one of several
    ways, the most common of which being the character span of the
    original string.

    Args:
        data: the Lnk specifiers, whose quality depends on *type*
        type: the way the Lnk relates the semantics to the surface form

    Note:
        Valid *types* and their associated *data* shown in the table
        below.

        | type      | data                | example   |
        | --------- | ------------------- | --------- |
        | charspan  | surface string span | (0, 5)    |
        | chartspan | chart vertex span   | (0, 5)    |
        | tokens    | token identifiers   | (0, 1, 2) |
        | edge      | edge identifier     | 1         |


    Example:
        Lnk objects should be created using the classmethods:

        >>> Lnk.charspan(0,5)
        '<0:5>'
        >>> Lnk.chartspan(0,5)
        '<0#5>'
        >>> Lnk.tokens([0,1,2])
        '<0 1 2>'
        >>> Lnk.edge(1)
        '<@1>'
    """

    # These types determine how a lnk on an EP or MRS are to be
    # interpreted, and thus determine the data type/structure of the
    # lnk data.
    CHARSPAN = 0  # Character span; a pair of offsets
    CHARTSPAN = 1  # Chart vertex span: a pair of indices
    TOKENS = 2  # Token numbers: a list of indices
    EDGE = 3  # An edge identifier: a number

    def __init__(self, type, data):
        # class methods below use __new__ to instantiate data, so
        # don't do it here
        if type not in (Lnk.CHARSPAN, Lnk.CHARTSPAN, Lnk.TOKENS, Lnk.EDGE):
            raise XmrsError('Invalid Lnk type: {}'.format(type))

    @classmethod
    def charspan(cls, start, end):
        """
        Create a Lnk object for a character span.

        Args:
            start: the initial character position (cfrom)
            end: the final character position (cto)
        """
        return cls(Lnk.CHARSPAN, (int(start), int(end)))

    @classmethod
    def chartspan(cls, start, end):
        """
        Create a Lnk object for a chart span.

        Args:
            start: the initial chart vertex
            end: the final chart vertex
        """
        return cls(Lnk.CHARTSPAN, (int(start), int(end)))

    @classmethod
    def tokens(cls, tokens):
        """
        Create a Lnk object for a token range.

        Args:
            tokens: a list of token identifiers
        """
        return cls(Lnk.TOKENS, tuple(map(int, tokens)))

    @classmethod
    def edge(cls, edge):
        """
        Create a Lnk object for an edge (used internally in generation).

        Args:
            edge: an edge identifier
        """
        return cls(Lnk.EDGE, int(edge))

    def __str__(self):
        if self.type == Lnk.CHARSPAN:
            return '<{}:{}>'.format(self.data[0], self.data[1])
        elif self.type == Lnk.CHARTSPAN:
            return '<{}#{}>'.format(self.data[0], self.data[1])
        elif self.type == Lnk.EDGE:
            return '<@{}>'.format(self.data)
        elif self.type == Lnk.TOKENS:
            return '<{}>'.format(' '.join(map(str, self.data)))

    def __repr__(self):
        return '<Lnk object {} at {}>'.format(str(self), id(self))

    def __eq__(self, other):
        return self.type == other.type and self.data == other.data


class _LnkMixin(object):
    """
    A mixin class for predications ([EPs] or [Nodes]) or full [Xmrs]
    objects, which are the types that can be linked to surface strings.
    This class provides the `cfrom` and `cto` properties so they are
    always available (defaulting to a value of `-1` if there is no lnk
    or if the lnk is not a Lnk.CHARSPAN type).
    """
    @property
    def cfrom(self):
        """
        The initial character position in the surface string. Defaults
        to -1 if there is no valid cfrom value.
        """
        cfrom = -1
        try:
            if self.lnk.type == Lnk.CHARSPAN:
                cfrom = self.lnk.data[0]
        except AttributeError:
            pass  # use default cfrom of -1
        return cfrom

    @property
    def cto(self):
        """
        The final character position in the surface string. Defaults
        to -1 if there is no valid cto value.
        """
        cto = -1
        try:
            if self.lnk.type == Lnk.CHARSPAN:
                cto = self.lnk.data[1]
        except AttributeError:
            pass  # use default cto of -1
        return cto


# LINKS and CONSTRAINTS

class Link(namedtuple('Link', ('start', 'end', 'rargname', 'post'))):
    """
    DMRS-style dependency link.

    Links are a way of representing arguments without variables. A
    Link encodes a start and end node, the argument name, and label
    information (e.g. label equality, qeq, etc).
    """
    def __new__(cls, start, end, rargname, post):
        return super(Link, cls).__new__(
            cls, int(start), int(end), rargname, post
        )

    def __repr__(self):
        return '<Link object (#{} :{}/{}> #{}) at {}>'.format(
            self.start, self.rargname or '', self.post, self.end, id(self)
        )


def links(xmrs):
    """Return the list of [Links] for the *xmrs*."""

    # Links exist for every non-intrinsic argument that has a variable
    # that is the intrinsic variable of some other predicate, as well
    # as for label equalities when no argument link exists (even
    # considering transitivity).
    links = []
    prelinks = []

    _eps = xmrs._eps
    _hcons = xmrs._hcons
    _vars = xmrs._vars

    lsh = xmrs.labelset_heads
    lblheads = {v: lsh(v) for v, vd in _vars.items() if 'LBL' in vd['refs']}

    top = xmrs.top
    if top is not None:
        prelinks.append((0, top, None, top, _vars[top]))

    for nid, ep in _eps.items():
        for role, val in ep[3].items():
            if role == IVARG_ROLE or val not in _vars:
                continue
            prelinks.append((nid, ep[2], role, val, _vars[val]))

    for src, srclbl, role, val, vd in prelinks:
        if IVARG_ROLE in vd['refs']:
            tgtnids = [n for n in vd['refs'][IVARG_ROLE]
                       if not _eps[n].is_quantifier()]
            if len(tgtnids) == 0:
                continue  # maybe some bad MRS with a lonely quantifier
            tgt = tgtnids[0]  # what do we do if len > 1?
            tgtlbl = _eps[tgt][2]
            post = EQ_POST if srclbl == tgtlbl else NEQ_POST
        elif val in _hcons:
            lbl = _hcons[val][2]
            if lbl not in lblheads or len(lblheads[lbl]) == 0:
                continue  # broken MRS; log this?
            tgt = lblheads[lbl][0]  # sorted list; first item is most "heady"
            post = H_POST
        elif 'LBL' in vd['refs']:
            if val not in lblheads or len(lblheads[val]) == 0:
                continue  # broken MRS; log this?
            tgt = lblheads[val][0]  # again, should be sorted already
            post = HEQ_POST
        else:
            continue  # CARGs, maybe?
        links.append(Link(src, tgt, role, post))

    # now EQ links unattested by arg links
    for lbl, heads in lblheads.items():
        # I'm pretty sure this does what we want
        if len(heads) > 1:
            first = heads[0]
            for other in heads[1:]:
                links.append(Link(other, first, BARE_EQ_ROLE, EQ_POST))
        # If not, something like this is more explicit
        # lblset = self.labelset(lbl)
        # sg = g.subgraph(lblset)
        # ns = [nid for nid, deg in sg.degree(lblset).items() if deg == 0]
        # head = self.labelset_head(lbl)
        # for n in ns:
        #     links.append(Link(head, n, post=EQ_POST))
    return sorted(links)#, key=lambda link: (link.start, link.end))


class HandleConstraint(
        namedtuple('HandleConstraint', ('hi', 'relation', 'lo'))):
    """A relation between two handles."""

    QEQ = 'qeq'  # Equality modulo Quantifiers
    LHEQ = 'lheq'  # Label-Handle Equality
    OUTSCOPES = 'outscopes'  # Outscopes

    @classmethod
    def qeq(cls, hi, lo):
        return cls(hi, HandleConstraint.QEQ, lo)

    def __repr__(self):
        return '<HandleConstraint object ({} {} {}) at {}>'.format(
               str(self.hi), self.relation, str(self.lo), id(self)
        )


def hcons(xmrs):
    """Return the list of all [HandleConstraints] in *xmrs*."""
    return [
        HandleConstraint(hi, reln, lo)
        for hi, reln, lo in sorted(xmrs.hcons(), key=lambda hc: var_id(hc[0]))
    ]


IndividualConstraint = namedtuple('IndividualConstraint',
                                  ['left', 'relation', 'right'])


def icons(xmrs):
    """Return the list of all [IndividualConstraints] in *xmrs*."""
    return [
        IndividualConstraint(left, reln, right)
        for left, reln, right in sorted(xmrs.icons(),
                                        key=lambda ic: var_id(ic[0]))
    ]


# PREDICATES AND PREDICATIONS


class Pred(namedtuple('Pred', ('type', 'lemma', 'pos', 'sense', 'string'))):
    """
    A semantic predicate.

    **Abstract** predicates don't begin with an underscore, and they
    generally are defined as types in a grammar. **Surface**
    predicates always begin with an underscore (ignoring possible
    quotes), and are often defined as strings in a lexicon.

    In PyDelphin, Preds are equivalent if they have the same lemma,
    pos, and sense, and are both abstract or both surface preds.
    Other factors are ignored for comparison, such as their being
    string-, grammar-, or real-preds, whether they are quoted or not,
    whether they end with `_rel` or not, or differences in
    capitalization. Hashed Pred objects (e.g., in a dict or set) also
    use the normalized form. However, unlike with equality comparisons,
    Pred-formatted strings are not treated as equivalent in a hash.

    Args:
        type: the type of predicate; valid values are
            Pred.GRAMMARPRED, Pred.REALPRED, and Pred.STRINGPRED,
            although in practice Preds are instantiated via
            classmethods that select the type
        lemma: the lemma of the predicate
        pos: the part-of-speech; a single, lowercase character
        sense: the (often omitted) sense of the predicate
    Returns:
        a Pred object

    Example:
        Preds are compared using their string representations.
        Surrounding quotes (double or single) are ignored, and
        capitalization doesn't matter. In addition, preds may be
        compared directly to their string representations:

        >>> p1 = Pred.stringpred('_dog_n_1_rel')
        >>> p2 = Pred.realpred(lemma='dog', pos='n', sense='1')
        >>> p3 = Pred.grammarpred('dog_n_1_rel')
        >>> p1 == p2
        True
        >>> p1 == '_dog_n_1_rel'
        True
        >>> p1 == p3
        False
    """
    pred_re = re.compile(
        r'_?(?P<lemma>.*?)_'  # match until last 1 or 2 parts
        r'((?P<pos>[a-z])_)?'  # pos is always only 1 char
        r'((?P<sense>([^_\\]|(?:\\.))+)_)?'  # no unescaped _s
        r'(?P<end>rel)$',
        re.IGNORECASE
    )
    # Pred types (used mainly in input/output, not internally in pyDelphin)
    GRAMMARPRED = 0  # only a string allowed (quoted or not)
    REALPRED = 1  # may explicitly define lemma, pos, sense
    STRINGPRED = 2  # quoted string form of realpred

    def __eq__(self, other):
        if other is None:
            return False
        if not isinstance(other, Pred):
            other = Pred.stringpred(other)
        return self.short_form().lower() == other.short_form().lower()

    def __str__ (self):
        return self.string

    def __repr__(self):
        return '<Pred object {} at {}>'.format(self.string, id(self))

    def __hash__(self):
        return hash(self.short_form())

    @classmethod
    def stringpred(cls, predstr):
        """Return a Pred from its quoted string representation."""
        lemma, pos, sense, end = split_pred_string(predstr)
        return cls(Pred.STRINGPRED, lemma, pos, sense, predstr)

    @classmethod
    def grammarpred(cls, predstr):
        """Return a Pred from its symbol string."""
        lemma, pos, sense, end = split_pred_string(predstr)
        return cls(Pred.GRAMMARPRED, lemma, pos, sense, predstr)

    @staticmethod
    def string_or_grammar_pred(predstr):
        """Return a Pred from either its string or grammar symbol."""
        if predstr.strip('"').lstrip("'").startswith('_'):
            return Pred.stringpred(predstr)
        else:
            return Pred.grammarpred(predstr)

    @classmethod
    def realpred(cls, lemma, pos, sense=None):
        """Return a Pred from its components."""
        string_tokens = [lemma, pos]
        if sense is not None:
            sense = str(sense)
            string_tokens.append(sense)
        predstr = '_'.join([''] + string_tokens + ['rel'])
        return cls(Pred.REALPRED, lemma, pos, sense, predstr)

    def short_form(self):
        """
        Return the pred string without quotes or a _rel suffix.

        Example:

            >>> p = Pred.stringpred('"_cat_n_1_rel"')
            >>> p.short_form()
            '_cat_n_1'
        """
        return normalize_pred_string(self.string)

    def is_quantifier(self):
        """
        Return `True` if the predicate has a quantifier part-of-speech.

        *Deprecated since v0.6.0*
        """
        warnings.warn(
            'Deprecated; try checking xmrs.nodeids(quantifier=True)',
            DeprecationWarning
        )
        return self.pos == QUANTIFIER_POS


def split_pred_string(predstr):
    """
    Extract the components from a pred string and log errors for any
    malformedness.

    Args:
        predstr: a predicate string

    Examples:

        >>> Pred.split_pred_string('_dog_n_1_rel')
        ('dog', 'n', '1', 'rel')
        >>> Pred.split_pred_string('quant_rel')
        ('quant', None, None, 'rel')
    """
    predstr = predstr.strip('"\'')  # surrounding quotes don't matter
    rel_added = False
    if not predstr.lower().endswith('_rel'):
        logging.debug('Predicate does not end in "_rel": {}'
                      .format(predstr))
        rel_added = True
        predstr += '_rel'
    match = Pred.pred_re.search(predstr)
    if match is None:
        logging.debug('Unexpected predicate string: {}'.format(predstr))
        return (predstr, None, None, None)
    # _lemma_pos(_sense)?_end
    return (match.group('lemma'), match.group('pos'),
            match.group('sense'), None if rel_added else match.group('end'))


def is_valid_pred_string(predstr):
    """
    Return `True` if the given predicate string represents a valid
    Pred, `False` otherwise.
    """
    predstr = predstr.strip('"').lstrip("'")
    # this is a stricter regex than in Pred, but doesn't check POS
    return re.match(
        r'_([^ _\\]|\\.)+_[a-z](_([^ _\\]|\\.)+)?(_rel)?$'
        r'|[^_]([^ \\]|\\.)+(_rel)?$',
        predstr
    ) is not None


def normalize_pred_string(predstr):
    """
    Make pred strings more consistent by removing quotes and the _rel
    suffix, and by lowercasing them.
    """
    tokens = [t for t in split_pred_string(predstr)[:3] if t is not None]
    if predstr.lstrip('\'"')[:1] == '_':
        tokens = [''] + tokens
    return '_'.join(tokens).lower()


class Node(
    namedtuple('Node', ('nodeid', 'pred', 'sortinfo',
                        'lnk', 'surface', 'base', 'carg')),
    _LnkMixin):
    """
    A very simple predication for DMRSs. Nodes don't have arguments
    or labels like [ElementaryPredication] objects, but they do have
    a property for CARGs and contain their variable sort and
    properties in sortinfo.

    Args:
        nodeid: node identifier
        pred: node's Pred
        sortinfo: node properties (with cvarsort)
        lnk: Lnk object associated with the pred
        surface: surface string
        base: base form
        carg: constant argument string
    """

    def __new__(cls, nodeid, pred, sortinfo=None,
                 lnk=None, surface=None, base=None, carg=None):
        if sortinfo is None:
            sortinfo = {}
        elif not isinstance(sortinfo, MutableMapping):
            sortinfo = dict(sortinfo)
        return super(Node, cls).__new__(
            cls, nodeid, pred, sortinfo, lnk, surface, base, carg
        )

    def __repr__(self):
        lnk = ''
        if self.lnk is not None:
            lnk = str(self.lnk)
        return '<Node object ({} [{}{}]) at {}>'.format(
            self.nodeid, self.pred.string, lnk, id(self)
        )

    # note: without overriding __eq__, comparisons of sortinfo will be
    #       be different if they are OrderedDicts and not in the same
    #       order. Maybe this isn't a big deal?
    # def __eq__(self, other):
    #     # not doing self.__dict__ == other.__dict__ right now, because
    #     # functions like self.get_property show up there
    #     snid = self.nodeid
    #     onid = other.nodeid
    #     return ((None in (snid, onid) or snid == onid) and
    #             self.pred == other.pred and
    #             # make one side a regular dict for unordered comparison
    #             dict(self.sortinfo.items()) == other.sortinfo and
    #             self.lnk == other.lnk and
    #             self.surface == other.surface and
    #             self.base == other.base and
    #             self.carg == other.carg)

    def __lt__(self, other):
        warnings.warn("Deprecated", DeprecationWarning)
        x1 = (self.cfrom, self.cto, self.pred.pos != QUANTIFIER_POS,
              self.pred.lemma)
        try:
            x2 = (other.cfrom, other.cto, other.pred.pos != QUANTIFIER_POS,
                  other.pred.lemma)
            return x1 < x2
        except AttributeError:
            return NotImplemented

    @property
    def cvarsort(self):
        """
        The sortal type of the predicate.
        """
        return self.sortinfo.get(CVARSORT)

    @cvarsort.setter
    def cvarsort(self, value):
        self.sortinfo[CVARSORT] = value

    @property
    def properties(self):
        d = dict(self.sortinfo)
        if CVARSORT in d:
            del d[CVARSORT]
        return d

    def is_quantifier(self):
        """
        Return `True` if the Node's [Pred] appears to be a quantifier.

        *Deprecated since v0.6.0*
        """
        warnings.warn(
            'Deprecated; try checking xmrs.nodeids(quantifier=True)',
            DeprecationWarning
        )
        return self.pred.is_quantifier()


def nodes(xmrs):
    """Return the list of Nodes for *xmrs*."""
    nodes = []
    _props = xmrs.properties
    varsplit = sort_vid_split
    for p in xmrs.eps():
        sortinfo = None
        iv = p.intrinsic_variable
        if iv is not None:
            sort, _ = varsplit(iv)
            sortinfo = _props(iv)
            sortinfo[CVARSORT] = sort
        nodes.append(
            Node(p.nodeid, p.pred, sortinfo, p.lnk, p.surface, p.base, p.carg)
        )
    return nodes


class ElementaryPredication(
    namedtuple('ElementaryPredication',
               ('nodeid', 'pred', 'label', 'args', 'lnk', 'surface', 'base')),
    _LnkMixin):
    """
    An elementary predication (EP) combines a predicate with various
    structural semantic properties.

    EPs must have the `nodeid`, `pred`, and `label`, arguments,
    while the others are optional. MRS does not use nodeids, so it's
    fine to use `None`. Whenever an EP is used in an Xmrs, it gets
    assigned a nodeid. Generally EPs will have an ARG0 on their `args`
    dictionary to indicate their intrinisic variable, but it is not
    required.

    Args:
        nodeid: an int nodeid
        pred: The Pred of the EP
        label: label handle
        args: a mapping of role-argument names to values
        lnk: Lnk object associated with the pred
        surface: surface string
        base: base form
    """

    def __new__(cls, nodeid, pred, label, args=None,
                 lnk=None, surface=None, base=None):
        if args is None:
            args = {}
        if nodeid is not None:
            nodeid = int(nodeid)
        # else:
        #     args = dict((a.rargname, a) for a in args)
        return super(ElementaryPredication, cls).__new__(
            cls, nodeid, pred, label, args, lnk, surface, base
        )

    def __repr__(self):
        return '<ElementaryPredication object ({} ({})) at {}>'.format(
            self.pred.string, str(self.iv or '?'), id(self)
        )

    def __lt__(self, other):
        warnings.warn("Deprecated", DeprecationWarning)
        x1 = (self.cfrom, self.cto, -self.is_quantifier(), self.pred.lemma)
        try:
            x2 = (other.cfrom, other.cto, -other.is_quantifier(),
                  other.pred.lemma)
            return x1 < x2
        except AttributeError:
            return NotImplemented

    # these properties are specific to the EP's qualities

    @property
    def intrinsic_variable(self):
        """
        The value of the intrinsic argument (ARG0).
        """
        if IVARG_ROLE in self.args:
            return self.args[IVARG_ROLE]
        return None

    #: A synonym for ElementaryPredication.intrinsic_variable
    iv = intrinsic_variable

    @property
    def carg(self):
        """
        The value of the constant argument.
        """
        return self.args.get(CONSTARG_ROLE, None)

    def is_quantifier(self):
        """
        Return `True` if the EP is a quantifier predication.
        """
        return RSTR_ROLE in self.args


def elementarypredications(xmrs):
    """Return the list of [ElementaryPredication] objects in *xmrs*."""
    return list(starmap(ElementaryPredication, xmrs.eps()))


def elementarypredication(xmrs, nodeid):
    """
    Retrieve the EP with the given nodeid, or raises KeyError if no
    EP matches.

    Args:
        nodeid: The nodeid of the EP to return.
    Returns:
        An ElementaryPredication.
    """
    return ElementaryPredication(*xmrs.ep(nodeid))
Classes and functions for working with the components of *MRS objects. # The classes below are generally just namedtuples with extra methods. # The namedtuples sometimes have default values. thanks: #   http://stackoverflow.com/a/16721002/1441112 # VARIABLES and LNKS Split a valid variable string into the variable sort and id. Return the sort of a valid variable string. Return the integer id of a valid variable string. Simple class to produce variables, incrementing the vid for each     one. # to map vid to created variable # to recall properties from varstrings Create a new variable for the given *sort*. # find next available vid Lnk objects link predicates to the surface form in one of several     ways, the most common of which being the character span of the     original string.      Args:         data: the Lnk specifiers, whose quality depends on *type*         type: the way the Lnk relates the semantics to the surface form      Note:         Valid *types* and their associated *data* shown in the table         below.          | type      | data                | example   |         | --------- | ------------------- | --------- |         | charspan  | surface string span | (0, 5)    |         | chartspan | chart vertex span   | (0, 5)    |         | tokens    | token identifiers   | (0, 1, 2) |         | edge      | edge identifier     | 1         |       Example:         Lnk objects should be created using the classmethods:          >>> Lnk.charspan(0,5)         '<0:5>'         >>> Lnk.chartspan(0,5)         '<0#5>'         >>> Lnk.tokens([0,1,2])         '<0 1 2>'         >>> Lnk.edge(1)         '<@1>' # These types determine how a lnk on an EP or MRS are to be # interpreted, and thus determine the data type/structure of the # lnk data. # Character span; a pair of offsets # Chart vertex span: a pair of indices # Token numbers: a list of indices # An edge identifier: a number # class methods below use __new__ to instantiate data, so # don't do it here Create a Lnk object for a character span.          Args:             start: the initial character position (cfrom)             end: the final character position (cto) Create a Lnk object for a chart span.          Args:             start: the initial chart vertex             end: the final chart vertex Create a Lnk object for a token range.          Args:             tokens: a list of token identifiers Create a Lnk object for an edge (used internally in generation).          Args:             edge: an edge identifier #{}>'.format(self.data[0], self.data[1]) A mixin class for predications ([EPs] or [Nodes]) or full [Xmrs]     objects, which are the types that can be linked to surface strings.     This class provides the `cfrom` and `cto` properties so they are     always available (defaulting to a value of `-1` if there is no lnk     or if the lnk is not a Lnk.CHARSPAN type). The initial character position in the surface string. Defaults         to -1 if there is no valid cfrom value. # use default cfrom of -1 The final character position in the surface string. Defaults         to -1 if there is no valid cto value. # use default cto of -1 # LINKS and CONSTRAINTS DMRS-style dependency link.      Links are a way of representing arguments without variables. A     Link encodes a start and end node, the argument name, and label     information (e.g. label equality, qeq, etc). #{} :{}/{}> #{}) at {}>'.format( Return the list of [Links] for the *xmrs*. # Links exist for every non-intrinsic argument that has a variable # that is the intrinsic variable of some other predicate, as well # as for label equalities when no argument link exists (even # considering transitivity). # maybe some bad MRS with a lonely quantifier # what do we do if len > 1? # broken MRS; log this? # sorted list; first item is most "heady" # broken MRS; log this? # again, should be sorted already # CARGs, maybe? # now EQ links unattested by arg links # I'm pretty sure this does what we want # If not, something like this is more explicit # lblset = self.labelset(lbl) # sg = g.subgraph(lblset) # ns = [nid for nid, deg in sg.degree(lblset).items() if deg == 0] # head = self.labelset_head(lbl) # for n in ns: #     links.append(Link(head, n, post=EQ_POST)) #, key=lambda link: (link.start, link.end)) A relation between two handles. # Equality modulo Quantifiers # Label-Handle Equality # Outscopes Return the list of all [HandleConstraints] in *xmrs*. Return the list of all [IndividualConstraints] in *xmrs*. # PREDICATES AND PREDICATIONS A semantic predicate.      **Abstract** predicates don't begin with an underscore, and they     generally are defined as types in a grammar. **Surface**     predicates always begin with an underscore (ignoring possible     quotes), and are often defined as strings in a lexicon.      In PyDelphin, Preds are equivalent if they have the same lemma,     pos, and sense, and are both abstract or both surface preds.     Other factors are ignored for comparison, such as their being     string-, grammar-, or real-preds, whether they are quoted or not,     whether they end with `_rel` or not, or differences in     capitalization. Hashed Pred objects (e.g., in a dict or set) also     use the normalized form. However, unlike with equality comparisons,     Pred-formatted strings are not treated as equivalent in a hash.      Args:         type: the type of predicate; valid values are             Pred.GRAMMARPRED, Pred.REALPRED, and Pred.STRINGPRED,             although in practice Preds are instantiated via             classmethods that select the type         lemma: the lemma of the predicate         pos: the part-of-speech; a single, lowercase character         sense: the (often omitted) sense of the predicate     Returns:         a Pred object      Example:         Preds are compared using their string representations.         Surrounding quotes (double or single) are ignored, and         capitalization doesn't matter. In addition, preds may be         compared directly to their string representations:          >>> p1 = Pred.stringpred('_dog_n_1_rel')         >>> p2 = Pred.realpred(lemma='dog', pos='n', sense='1')         >>> p3 = Pred.grammarpred('dog_n_1_rel')         >>> p1 == p2         True         >>> p1 == '_dog_n_1_rel'         True         >>> p1 == p3         False # match until last 1 or 2 parts # pos is always only 1 char # no unescaped _s # Pred types (used mainly in input/output, not internally in pyDelphin) # only a string allowed (quoted or not) # may explicitly define lemma, pos, sense # quoted string form of realpred Return a Pred from its quoted string representation. Return a Pred from its symbol string. Return a Pred from either its string or grammar symbol. Return a Pred from its components. Return the pred string without quotes or a _rel suffix.          Example:              >>> p = Pred.stringpred('"_cat_n_1_rel"')             >>> p.short_form()             '_cat_n_1' Return `True` if the predicate has a quantifier part-of-speech.          *Deprecated since v0.6.0* Extract the components from a pred string and log errors for any     malformedness.      Args:         predstr: a predicate string      Examples:          >>> Pred.split_pred_string('_dog_n_1_rel')         ('dog', 'n', '1', 'rel')         >>> Pred.split_pred_string('quant_rel')         ('quant', None, None, 'rel') # surrounding quotes don't matter # _lemma_pos(_sense)?_end Return `True` if the given predicate string represents a valid     Pred, `False` otherwise. # this is a stricter regex than in Pred, but doesn't check POS Make pred strings more consistent by removing quotes and the _rel     suffix, and by lowercasing them. A very simple predication for DMRSs. Nodes don't have arguments     or labels like [ElementaryPredication] objects, but they do have     a property for CARGs and contain their variable sort and     properties in sortinfo.      Args:         nodeid: node identifier         pred: node's Pred         sortinfo: node properties (with cvarsort)         lnk: Lnk object associated with the pred         surface: surface string         base: base form         carg: constant argument string # note: without overriding __eq__, comparisons of sortinfo will be #       be different if they are OrderedDicts and not in the same #       order. Maybe this isn't a big deal? # def __eq__(self, other): #     # not doing self.__dict__ == other.__dict__ right now, because #     # functions like self.get_property show up there #     snid = self.nodeid #     onid = other.nodeid #     return ((None in (snid, onid) or snid == onid) and #             self.pred == other.pred and #             # make one side a regular dict for unordered comparison #             dict(self.sortinfo.items()) == other.sortinfo and #             self.lnk == other.lnk and #             self.surface == other.surface and #             self.base == other.base and #             self.carg == other.carg) The sortal type of the predicate. Return `True` if the Node's [Pred] appears to be a quantifier.          *Deprecated since v0.6.0* Return the list of Nodes for *xmrs*. An elementary predication (EP) combines a predicate with various     structural semantic properties.      EPs must have the `nodeid`, `pred`, and `label`, arguments,     while the others are optional. MRS does not use nodeids, so it's     fine to use `None`. Whenever an EP is used in an Xmrs, it gets     assigned a nodeid. Generally EPs will have an ARG0 on their `args`     dictionary to indicate their intrinisic variable, but it is not     required.      Args:         nodeid: an int nodeid         pred: The Pred of the EP         label: label handle         args: a mapping of role-argument names to values         lnk: Lnk object associated with the pred         surface: surface string         base: base form # else: #     args = dict((a.rargname, a) for a in args) # these properties are specific to the EP's qualities The value of the intrinsic argument (ARG0). #: A synonym for ElementaryPredication.intrinsic_variable The value of the constant argument. Return `True` if the EP is a quantifier predication. Return the list of [ElementaryPredication] objects in *xmrs*. Retrieve the EP with the given nodeid, or raises KeyError if no     EP matches.      Args:         nodeid: The nodeid of the EP to return.     Returns:         An ElementaryPredication.