def dummy_constituent_tree(token_yield,
                           full_token_yield,
                           dummy_label,
                           dummy_root,
                           label=None):
    """
    :param token_yield: connected yield of a parse tree
    :type token_yield: list[ConstituentTerminal]
    :param full_token_yield: full yield of the parse tree
    :type full_token_yield: list[ConstituentTerminal]
    :return: dummy constituent tree
    :rtype: ConstituentTree
    generates a dummy tree for a given yield using dummy_label as inner node symbol
    """
    tree = ConstituentTree(label)

    # create all leaves and punctuation
    for token in full_token_yield:
        if token not in token_yield:
            tree.add_punct(full_token_yield.index(token), token.pos(),
                           token.form())
        else:
            tree.add_leaf(full_token_yield.index(token), token.pos(),
                          token.form())

    # generate root node
    root_id = 'n0'
    tree.add_node(root_id, ConstituentCategory(dummy_root))
    tree.add_to_root(root_id)

    parent = root_id

    if len(token_yield) > 1:
        i = 1
        # generate inner nodes of branching tree
        for token in token_yield[:-2]:
            node = ConstituentCategory(str(dummy_label))
            tree.add_node('n' + str(i), node)
            tree.add_child(parent, 'n' + str(i))
            tree.add_child(parent, full_token_yield.index(token))
            parent = 'n' + str(i)
            i += 1

        token = token_yield[len(token_yield) - 2]
        tree.add_child(parent, full_token_yield.index(token))
        token = token_yield[len(token_yield) - 1]
        tree.add_child(parent, full_token_yield.index(token))
    elif len(token_yield) == 1:
        tree.add_child(parent, full_token_yield.index(token_yield[0]))

    return tree
def main():
    # train_path = '../res/SPMRL_SHARED_2014_NO_ARABIC/GERMAN_SPMRL/gold/xml/train/train.German.gold.xml'
    # corpus = sentence_names_to_hybridtrees(["s" + str(i) for i in range(1, 10)], file_name=train_path, hold=False)

    train_path = '../res/SPMRL_SHARED_2014_NO_ARABIC/GERMAN_SPMRL/gold/xml/dev/dev.German.gold.xml'
    names = ["s" + str(i) for i in range(40675, 40700)]
    names = ['s40564']
    corpus = sentence_names_to_hybridtrees(names, path=train_path, hold=False)

    cp = TreeComparator()

    tree_sys = ConstituentTree()
    tree_sys.add_node('0', ConstituentCategory('PN'))
    tree_sys.add_node('1', corpus[0].token_yield()[0], order=True)
    tree_sys.add_punct("3", '$.', '.')
    tree_sys.add_to_root('0')
    tree_sys.add_child('0', '1')

    param = build_param()

    for i, hybridtree in enumerate(corpus):
        print(i)

        # discotree = convert_tree(hybridtree)
        tree, sent = convert_tree(hybridtree)
        tree2, sent2 = convert_tree(tree_sys)

        if i == 11:
            pass

        # print(discotree)

        # print(discotree.draw())

        # print(DrawTree(discotree, discotree.sent))
        print(DrawTree(tree, sent))

        print(' '.join(map(lambda x: x.form(), hybridtree.full_token_yield())))

        print(DrawTree(tree2, sent2))

        print(tree[::-1])

        print('POS', tree.pos())

        result = TreePairResult(i, tree, sent, tree2, sent2, param)
        print(result.scores())

        print("Comparator: ", cp.compare_hybridtrees(hybridtree, hybridtree))
Beispiel #3
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 def tree2():
     tree = ConstituentTree("1")
     for i, t in enumerate(["a", "b", "d", "c"]):
         tree.add_leaf(str(i), "P" + t, t)
     tree.set_label('r0', 'C')
     tree.set_label('r1', 'A')
     tree.set_label('r2', 'B')
     tree.add_to_root('r0')
     tree.add_child('r0', 'r1')
     tree.add_child('r0', 'r2')
     tree.add_child('r1', '0')
     tree.add_child('r1', '3')
     tree.add_child('r2', '1')
     tree.add_child('r2', '2')
     print(tree, tree.word_yield())
     return tree
Beispiel #4
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def constituent_tree_1_pos_stripped():
    tree = ConstituentTree("s1")
    tree.add_leaf("f1", "--", "hat")
    tree.add_leaf("f2", "--", "schnell")
    tree.add_leaf("f3", "--", "gearbeitet")
    tree.add_punct("f4", "--", ".")

    tree.set_label("V", "V")
    tree.add_child("V", "f1")
    tree.add_child("V", "f3")

    tree.set_label("ADV", "ADV")
    tree.add_child("ADV", "f2")

    tree.set_label("VP", "VP")
    tree.add_child("VP", "V")
    tree.add_child("VP", "ADV")

    tree.add_to_root("VP")

    return tree
def flat_dummy_constituent_tree(token_yield,
                                full_token_yield,
                                dummy_label,
                                dummy_root,
                                label=None,
                                gold_pos=True):
    """
    :param token_yield: connected yield of a parse tree
    :type token_yield: list[ConstituentTerminal]
    :param full_token_yield: full yield of the parse tree
    :type full_token_yield: list[ConstituentTerminal]
    :return: dummy constituent tree
    :rtype: ConstituentTree
    generates a flat dummy tree for a given yield where all nodes are attached under the root
    """
    tree = ConstituentTree(label)

    # generate root node
    root_id = 'n_root'
    tree.add_node(root_id, ConstituentCategory(dummy_root))
    tree.add_to_root(root_id)

    parent = root_id

    # create all leaves and punctuation
    for token in full_token_yield:
        pos = token.pos() if gold_pos else '--'
        if token not in token_yield:
            tree.add_punct(full_token_yield.index(token), pos, token.form())
        else:
            idx = full_token_yield.index(token)
            tree.add_leaf(idx,
                          pos,
                          token.form(),
                          morph=token.morph_feats(),
                          lemma=token.lemma())

            tree.add_child(parent, idx)

    return tree
Beispiel #6
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def constituent_tree_2():
    tree = ConstituentTree("s2")
    tree.add_leaf("l1", "N", "John")
    tree.add_leaf("l2", "V", "hit")
    tree.add_leaf("l3", "D", "the")
    tree.add_leaf("l4", "N", "Ball")
    tree.add_punct("l5", "PUNC", ".")

    tree.set_label("NP", "NP")
    tree.add_child("NP", "l3")
    tree.add_child("NP", "l4")

    tree.set_label("VP", "VP")
    tree.add_child("VP", "l2")
    tree.add_child("VP", "NP")

    tree.set_label("S", "S")
    tree.add_child("S", "l1")
    tree.add_child("S", "VP")

    tree.add_to_root("S")

    return tree
    def setUp(self):
        tree = ConstituentTree("s1")
        tree.add_leaf("f1",
                      "VAFIN",
                      "hat",
                      morph=[("number", "Sg"), ("person", "3"),
                             ("tense", "Past"), ("mood", "Ind")])
        tree.add_leaf("f2", "ADV", "schnell", morph=[("degree", "Pos")])
        tree.add_leaf("f3", "VVPP", "gearbeitet")
        tree.add_punct("f4", "PUNC", ".")

        tree.add_child("VP2", "f1")
        tree.add_child("VP2", "f3")
        tree.add_child("ADVP", "f2")

        tree.add_child("VP1", "VP2")
        tree.add_child("VP1", "ADVP")

        tree.set_label("VP2", "VP")
        tree.set_label("VP1", "VP")
        tree.set_label("ADVP", "ADVP")

        self.tree = tree

        tree2 = ConstituentTree("s2")
        tree2.add_leaf("f1",
                       "VAFIN",
                       "haben",
                       morph=[("number", "Pl"), ("person", "3"),
                              ("tense", "Past"), ("mood", "Ind")])
        tree2.add_leaf("f2", "ADV", "gut", morph=[("degree", "Pos")])
        tree2.add_leaf("f3", "VVPP", "gekocht")
        tree2.add_punct("f4", "PUNC", ".")

        tree2.add_child("VP2", "f1")
        tree2.add_child("VP2", "f3")
        tree2.add_child("ADVP", "f2")

        tree2.add_child("VP1", "VP2")
        tree2.add_child("VP1", "ADVP")

        tree2.set_label("VP2", "VP")
        tree2.set_label("VP1", "VP")
        tree2.set_label("ADVP", "ADVP")
        tree2.add_to_root("VP1")
        self.tree2 = tree2

        self.tree3 = ConstituentTree("s3")
        self.tree3.add_leaf("f1",
                            "ADJA",
                            "Allgemeiner",
                            edge="NK",
                            morph=[("number", "Sg")])
        self.tree3.add_leaf("f2",
                            "ADJA",
                            "Deutscher",
                            edge="NK",
                            morph=[("degree", "Pos"), ("number", "Sg")])
        self.tree3.add_leaf("f3",
                            "NN",
                            "Fahrrad",
                            edge="NK",
                            morph=[("number", "Sg"), ("gender", "Neut")])
        self.tree3.add_leaf("f4",
                            "NN",
                            "Club",
                            edge="NK",
                            morph=[("number", "Sg"), ("gender", "Neut")])
        for i in range(1, 5):
            self.tree3.add_child("NP", "f" + str(i))
        self.tree3.set_label("NP", "NP")
        self.tree3.add_to_root("NP")
class ConstituentTreeTest(unittest.TestCase):
    def test_something(self):
        tree = self.tree
        print("rooted", tree.root)
        tree.add_to_root("VP1")
        print("rooted", tree.root)

        print(tree)

        print("sent label", tree.sent_label())

        print("leaves", tree.leaves())

        print("is leaf (leaves)",
              [(x, tree.is_leaf(x)) for (x, _, _) in tree.leaves()])
        print("is leaf (internal)", [(x, tree.is_leaf(x)) for x in tree.ids()])
        print("leaf index",
              [(x, tree.leaf_index(x)) for x in ["f1", "f2", "f3"]])

        print("pos yield", tree.pos_yield())
        print("word yield", tree.word_yield())

        # reentrant
        # parent

        print("ids", tree.ids())

        # reorder
        print("n nodes", tree.n_nodes())
        print("n gaps", tree.n_gaps())

        print("fringe VP", tree.fringe("VP"))
        print("fringe V", tree.fringe("V"))

        print("empty fringe", tree.empty_fringe())

        print("complete?", tree.complete())

        print("max n spans", tree.max_n_spans())

        print("unlabelled structure", tree.unlabelled_structure())

        print("labelled spans", tree.labelled_spans())

    def test_induction(self):
        naming = 'child'

        def rec_part(tree):
            return left_branching_partitioning(len(tree.id_yield()))
            # return fanout_k_left_to_right(tree, 1)

        tree = self.tree
        tree.add_to_root("VP1")

        feature_log1 = defaultdict(lambda: 0)

        grammar = fringe_extract_lcfrs(tree,
                                       rec_part(tree),
                                       feature_logging=feature_log1,
                                       naming=naming)

        for key in feature_log1:
            print(key, feature_log1[key])

        print(grammar)

        feats = defaultdict(lambda: 0)
        grammar_ = fringe_extract_lcfrs(tree,
                                        rec_part(tree),
                                        isolate_pos=True,
                                        feature_logging=feats,
                                        naming=naming)

        print(grammar_)

        for key in feats:
            print(key, feats[key])

        print("Adding 2nd grammar to first")

        grammar.add_gram(grammar_, feature_logging=(feature_log1, feats))
        for idx in range(0, len(grammar.rules())):
            print(idx, grammar.rule_index(idx))

        print("Adding 3rd grammar to first")
        feats3 = defaultdict(lambda: 0)
        grammar3 = fringe_extract_lcfrs(self.tree2,
                                        rec_part(self.tree2),
                                        isolate_pos=True,
                                        feature_logging=feats3,
                                        naming=naming)
        grammar.add_gram(grammar3, feature_logging=(feature_log1, feats3))

        print()
        for idx in range(0, len(grammar.rules())):
            print(idx, grammar.rule_index(idx))
        print()
        print("New feature log")
        print()
        for key in feature_log1:
            print(key, feature_log1[key])
        grammar.make_proper()

        build_nont_splits_dict(grammar,
                               feature_log1,
                               nonterminals=Enumerator())

        print(grammar.rule_index(0))
        print(grammar.rule_index(2))

    def test_markovized_induction(self):
        naming = 'strict-markov-v-2-h-0'

        def rec_part(tree):
            return left_branching_partitioning(len(tree.id_yield()))
            # return fanout_k_left_to_right(tree, 1)

        tree = self.tree
        tree.add_to_root("VP1")

        print(tree)

        grammar = fringe_extract_lcfrs(tree,
                                       rec_part(tree),
                                       naming=naming,
                                       isolate_pos=True)
        print(grammar)

    def test_induction_2(self):
        def rec_part(tree):
            return left_branching_partitioning(len(tree.id_yield()))

        features = defaultdict(lambda: 0)
        grammar = fringe_extract_lcfrs(self.tree3,
                                       rec_part(self.tree3),
                                       naming="child",
                                       feature_logging=features,
                                       isolate_pos=True)
        grammar.make_proper()

        if False:
            for idx in range(0, len(grammar.rules())):
                print(grammar.rule_index(idx))
                for key in features:
                    if key[0] == idx:
                        print(key, features[key])
                print()
            for key in features:
                if type(key[0]) == int:
                    continue
                print(key, features[key])

        nont_splits, root_weights, rule_weights, _ = build_nont_splits_dict(
            grammar,
            features,
            nonterminals=Enumerator(),
            feat_function=pos_cat_feats,
            debug=True)
        print(nont_splits)
        print(root_weights)
        print(rule_weights)

    def setUp(self):
        tree = ConstituentTree("s1")
        tree.add_leaf("f1",
                      "VAFIN",
                      "hat",
                      morph=[("number", "Sg"), ("person", "3"),
                             ("tense", "Past"), ("mood", "Ind")])
        tree.add_leaf("f2", "ADV", "schnell", morph=[("degree", "Pos")])
        tree.add_leaf("f3", "VVPP", "gearbeitet")
        tree.add_punct("f4", "PUNC", ".")

        tree.add_child("VP2", "f1")
        tree.add_child("VP2", "f3")
        tree.add_child("ADVP", "f2")

        tree.add_child("VP1", "VP2")
        tree.add_child("VP1", "ADVP")

        tree.set_label("VP2", "VP")
        tree.set_label("VP1", "VP")
        tree.set_label("ADVP", "ADVP")

        self.tree = tree

        tree2 = ConstituentTree("s2")
        tree2.add_leaf("f1",
                       "VAFIN",
                       "haben",
                       morph=[("number", "Pl"), ("person", "3"),
                              ("tense", "Past"), ("mood", "Ind")])
        tree2.add_leaf("f2", "ADV", "gut", morph=[("degree", "Pos")])
        tree2.add_leaf("f3", "VVPP", "gekocht")
        tree2.add_punct("f4", "PUNC", ".")

        tree2.add_child("VP2", "f1")
        tree2.add_child("VP2", "f3")
        tree2.add_child("ADVP", "f2")

        tree2.add_child("VP1", "VP2")
        tree2.add_child("VP1", "ADVP")

        tree2.set_label("VP2", "VP")
        tree2.set_label("VP1", "VP")
        tree2.set_label("ADVP", "ADVP")
        tree2.add_to_root("VP1")
        self.tree2 = tree2

        self.tree3 = ConstituentTree("s3")
        self.tree3.add_leaf("f1",
                            "ADJA",
                            "Allgemeiner",
                            edge="NK",
                            morph=[("number", "Sg")])
        self.tree3.add_leaf("f2",
                            "ADJA",
                            "Deutscher",
                            edge="NK",
                            morph=[("degree", "Pos"), ("number", "Sg")])
        self.tree3.add_leaf("f3",
                            "NN",
                            "Fahrrad",
                            edge="NK",
                            morph=[("number", "Sg"), ("gender", "Neut")])
        self.tree3.add_leaf("f4",
                            "NN",
                            "Club",
                            edge="NK",
                            morph=[("number", "Sg"), ("gender", "Neut")])
        for i in range(1, 5):
            self.tree3.add_child("NP", "f" + str(i))
        self.tree3.set_label("NP", "NP")
        self.tree3.add_to_root("NP")
class ConstituentTreeTest(unittest.TestCase):
    def test_basic_tree_methods(self):
        tree = self.tree
        print("rooted", tree.root)
        tree.add_to_root("VP1")
        print("rooted", tree.root)

        print(tree)

        print("sent label", tree.sent_label())

        print("leaves", tree.leaves())

        print("is leaf (leaves)",
              [(x, tree.is_leaf(x)) for (x, _, _) in tree.leaves()])
        print("is leaf (internal)", [(x, tree.is_leaf(x)) for x in tree.ids()])
        print("leaf index",
              [(x, tree.leaf_index(x)) for x in ["f1", "f2", "f3"]])

        print("pos yield", tree.pos_yield())
        print("word yield", tree.word_yield())

        # reentrant
        # parent

        print("ids", tree.ids())

        # reorder
        print("n nodes", tree.n_nodes())
        print("n gaps", tree.n_gaps())

        print("fringe VP", tree.fringe("VP"))
        print("fringe V", tree.fringe("V"))

        print("empty fringe", tree.empty_fringe())

        print("complete?", tree.complete())

        print("max n spans", tree.max_n_spans())

        print("unlabelled structure", tree.unlabelled_structure())

        print("labelled spans", tree.labelled_spans())

    def test_induction(self):
        naming = 'child'

        def rec_part(tree):
            return left_branching_partitioning(len(tree.id_yield()))
            # return fanout_k_left_to_right(tree, 1)

        tree = self.tree
        tree.add_to_root("VP1")

        feature_log1 = defaultdict(lambda: 0)

        grammar = fringe_extract_lcfrs(tree,
                                       rec_part(tree),
                                       feature_logging=feature_log1,
                                       naming=naming)

        for key in feature_log1:
            print(key, feature_log1[key])

        print(grammar)

        feats = defaultdict(lambda: 0)
        grammar_ = fringe_extract_lcfrs(tree,
                                        rec_part(tree),
                                        isolate_pos=True,
                                        feature_logging=feats,
                                        naming=naming)

        print(grammar_)

        for key in feats:
            print(key, feats[key])

        print("Adding 2nd grammar to first")

        grammar.add_gram(grammar_, feature_logging=(feature_log1, feats))
        for idx in range(0, len(grammar.rules())):
            print(idx, grammar.rule_index(idx))

        print("Adding 3rd grammar to first")
        feats3 = defaultdict(lambda: 0)
        grammar3 = fringe_extract_lcfrs(self.tree2,
                                        rec_part(self.tree2),
                                        isolate_pos=True,
                                        feature_logging=feats3,
                                        naming=naming)
        grammar.add_gram(grammar3, feature_logging=(feature_log1, feats3))

        print()
        for idx in range(0, len(grammar.rules())):
            print(idx, grammar.rule_index(idx))
        print()
        print("New feature log")
        print()
        for key in feature_log1:
            print(key, feature_log1[key])
        grammar.make_proper()

        build_nont_splits_dict(grammar,
                               feature_log1,
                               nonterminals=Enumerator())

        print(grammar.rule_index(0))
        print(grammar.rule_index(2))

    def test_markovized_induction(self):
        naming = 'strict-markov-v-2-h-0'

        def rec_part(tree):
            return left_branching_partitioning(len(tree.id_yield()))
            # return fanout_k_left_to_right(tree, 1)

        tree = self.tree
        tree.add_to_root("VP1")

        print(tree)

        grammar = fringe_extract_lcfrs(tree,
                                       rec_part(tree),
                                       naming=naming,
                                       isolate_pos=True)
        print(grammar)

    def test_induction_and_parsing_with_pos_recovery(self):
        naming = 'child'

        def rec_part(tree):
            return left_branching_partitioning(len(tree.id_yield()))

        tree = self.tree
        tree.add_to_root("VP1")

        print(tree)

        grammar = fringe_extract_lcfrs(tree,
                                       rec_part(tree),
                                       naming=naming,
                                       isolate_pos=True,
                                       term_labeling=FormTerminals())
        print(grammar)

        parser = LCFRS_parser(grammar)
        parser.set_input([token.form() for token in tree.token_yield()])
        parser.parse()
        self.assertTrue(parser.recognized())
        derivation = parser.best_derivation_tree()
        e = DCP_evaluator(derivation)
        dcp_term = e.getEvaluation()
        print(str(dcp_term[0]))
        t = ConstituentTree()
        dcp_to_hybridtree(
            t,
            dcp_term, [
                construct_constituent_token(token.form(), '--', True)
                for token in tree.token_yield()
            ],
            ignore_punctuation=False,
            construct_token=construct_constituent_token)
        print(t)
        self.assertEqual(len(tree.token_yield()), len(t.token_yield()))
        for tok1, tok2 in zip(tree.token_yield(), t.token_yield()):
            self.assertEqual(tok1.form(), tok2.form())
            self.assertEqual(tok1.pos(), tok2.pos())

    def test_stanford_unking_scheme(self):
        naming = 'child'

        def rec_part(tree):
            return left_branching_partitioning(len(tree.id_yield()))

        tree = self.tree
        tree.add_to_root("VP1")

        print(tree)

        terminal_labeling = StanfordUNKing([tree])

        grammar = fringe_extract_lcfrs(tree,
                                       rec_part(tree),
                                       naming=naming,
                                       isolate_pos=True,
                                       term_labeling=terminal_labeling)
        print(grammar)

        parser = LCFRS_parser(grammar)
        parser.set_input([token.form() for token in tree.token_yield()])
        parser.parse()
        self.assertTrue(parser.recognized())
        derivation = parser.best_derivation_tree()
        e = DCP_evaluator(derivation)
        dcp_term = e.getEvaluation()
        print(str(dcp_term[0]))
        t = ConstituentTree()
        dcp_to_hybridtree(
            t,
            dcp_term, [
                construct_constituent_token(token.form(), '--', True)
                for token in tree.token_yield()
            ],
            ignore_punctuation=False,
            construct_token=construct_constituent_token)
        print(t)
        self.assertEqual(len(tree.token_yield()), len(t.token_yield()))
        for tok1, tok2 in zip(tree.token_yield(), t.token_yield()):
            self.assertEqual(tok1.form(), tok2.form())
            self.assertEqual(tok1.pos(), tok2.pos())

        rules = terminal_labeling.create_smoothed_rules()
        print(rules)

        new_rules = {}

        for rule in grammar.rules():
            if rule.rhs() == []:
                assert len(rule.dcp()) == 1
                dcp = rule.dcp()[0]
                assert len(dcp.rhs()) == 1
                term = dcp.rhs()[0]
                head = term.head()
                pos = head.pos()

                for tag, form in rules:
                    if tag == pos:
                        lhs = LCFRS_lhs(rule.lhs().nont())
                        lhs.add_arg([form])
                        new_rules[lhs, dcp] = rules[tag, form]

        for lhs, dcp in new_rules:
            print(str(lhs), str(dcp), new_rules[(lhs, dcp)])

        tokens = [
            construct_constituent_token('hat', '--', True),
            construct_constituent_token('HAT', '--', True)
        ]
        self.assertEqual(terminal_labeling.token_label(tokens[0]), 'hat')
        self.assertEqual(terminal_labeling.token_label(tokens[1]), '_UNK')
        terminal_labeling.test_mode = True
        self.assertEqual(terminal_labeling.token_label(tokens[0]), 'hat')
        self.assertEqual(terminal_labeling.token_label(tokens[1]), 'hat')

    def test_induction_with_spans(self):
        naming = 'child-spans'

        def rec_part(tree):
            return left_branching_partitioning(len(tree.id_yield()))
            # return fanout_k_left_to_right(tree, 1)

        tree = self.tree
        tree.add_to_root("VP1")

        print(tree)

        grammar = fringe_extract_lcfrs(tree,
                                       rec_part(tree),
                                       naming=naming,
                                       isolate_pos=True)
        print(grammar)

    def test_induction_2(self):
        def rec_part(tree):
            return left_branching_partitioning(len(tree.id_yield()))

        features = defaultdict(lambda: 0)
        grammar = fringe_extract_lcfrs(self.tree3,
                                       rec_part(self.tree3),
                                       naming="child",
                                       feature_logging=features,
                                       isolate_pos=True)
        grammar.make_proper()

        if False:
            for idx in range(0, len(grammar.rules())):
                print(grammar.rule_index(idx))
                for key in features:
                    if key[0] == idx:
                        print(key, features[key])
                print()
            for key in features:
                if type(key[0]) == int:
                    continue
                print(key, features[key])

        nont_splits, root_weights, rule_weights, _ = build_nont_splits_dict(
            grammar,
            features,
            nonterminals=Enumerator(),
            feat_function=pos_cat_feats,
            debug=True)
        print(nont_splits)
        print(root_weights)
        print(rule_weights)

    def setUp(self):
        tree = ConstituentTree("s1")
        tree.add_leaf("f1",
                      "VAFIN",
                      "hat",
                      morph=[("number", "Sg"), ("person", "3"),
                             ("tense", "Past"), ("mood", "Ind")])
        tree.add_leaf("f2", "ADV", "schnell", morph=[("degree", "Pos")])
        tree.add_leaf("f3", "VVPP", "gearbeitet")
        tree.add_punct("f4", "PUNC", ".")

        tree.add_child("VP2", "f1")
        tree.add_child("VP2", "f3")
        tree.add_child("ADVP", "f2")

        tree.add_child("VP1", "VP2")
        tree.add_child("VP1", "ADVP")

        tree.set_label("VP2", "VP")
        tree.set_label("VP1", "VP")
        tree.set_label("ADVP", "ADVP")

        self.tree = tree

        tree2 = ConstituentTree("s2")
        tree2.add_leaf("f1",
                       "VAFIN",
                       "haben",
                       morph=[("number", "Pl"), ("person", "3"),
                              ("tense", "Past"), ("mood", "Ind")])
        tree2.add_leaf("f2", "ADV", "gut", morph=[("degree", "Pos")])
        tree2.add_leaf("f3", "VVPP", "gekocht")
        tree2.add_punct("f4", "PUNC", ".")

        tree2.add_child("VP2", "f1")
        tree2.add_child("VP2", "f3")
        tree2.add_child("ADVP", "f2")

        tree2.add_child("VP1", "VP2")
        tree2.add_child("VP1", "ADVP")

        tree2.set_label("VP2", "VP")
        tree2.set_label("VP1", "VP")
        tree2.set_label("ADVP", "ADVP")
        tree2.add_to_root("VP1")
        self.tree2 = tree2

        self.tree3 = ConstituentTree("s3")
        self.tree3.add_leaf("f1",
                            "ADJA",
                            "Allgemeiner",
                            edge="NK",
                            morph=[("number", "Sg")])
        self.tree3.add_leaf("f2",
                            "ADJA",
                            "Deutscher",
                            edge="NK",
                            morph=[("degree", "Pos"), ("number", "Sg")])
        self.tree3.add_leaf("f3",
                            "NN",
                            "Fahrrad",
                            edge="NK",
                            morph=[("number", "Sg"), ("gender", "Neut")])
        self.tree3.add_leaf("f4",
                            "NN",
                            "Club",
                            edge="NK",
                            morph=[("number", "Sg"), ("gender", "Neut")])
        for i in range(1, 5):
            self.tree3.add_child("NP", "f" + str(i))
        self.tree3.set_label("NP", "NP")
        self.tree3.add_to_root("NP")