# coding: utf-8
from __future__ import unicode_literals

import pytest
from spacy.vocab import Vocab
from spacy.tokens import Doc

from ..util import get_doc


def test_doc_split(en_vocab):
    words = ["LosAngeles", "start", "."]
    heads = [1, 1, 0]
    doc = get_doc(en_vocab, words=words, heads=heads)
    assert len(doc) == 3
    assert len(str(doc)) == 19
    assert doc[0].head.text == "start"
    assert doc[1].head.text == "."
    with doc.retokenize() as retokenizer:
        attrs = {"tag": "NNP", "lemma": "Los Angeles", "ent_type": "GPE"}
        retokenizer.split(doc[0], ["Los", "Angeles"], [1, 0], attrs=attrs)
    assert len(doc) == 4
    assert doc[0].text == "Los"
    assert doc[0].head.text == "Angeles"
    assert doc[0].idx == 0
    assert doc[1].idx == 3
    assert doc[1].text == "Angeles"
    assert doc[1].head.text == "start"
    assert doc[2].text == "start"
    assert doc[2].head.text == "."
    assert doc[3].text == "."
    assert doc[3].head.text == "."
    assert len(str(doc)) == 19


def test_split_dependencies(en_vocab):
    doc = Doc(en_vocab, words=["LosAngeles", "start", "."])
    dep1 = doc.vocab.strings.add("amod")
    dep2 = doc.vocab.strings.add("subject")
    with doc.retokenize() as retokenizer:
        retokenizer.split(doc[0], ["Los", "Angeles"], [1, 0], [dep1, dep2])
    assert doc[0].dep == dep1
    assert doc[1].dep == dep2


def test_split_heads_error(en_vocab):
    doc = Doc(en_vocab, words=["LosAngeles", "start", "."])
    # Not enough heads
    with pytest.raises(ValueError):
        with doc.retokenize() as retokenizer:
            retokenizer.split(doc[0], ["Los", "Angeles"], [0])

    # Too many heads
    with pytest.raises(ValueError):
        with doc.retokenize() as retokenizer:
            retokenizer.split(doc[0], ["Los", "Angeles"], [1, 1, 0])

    # No token head
    with pytest.raises(ValueError):
        with doc.retokenize() as retokenizer:
            retokenizer.split(doc[0], ["Los", "Angeles"], [1, 1])

    # Several token heads
    with pytest.raises(ValueError):
        with doc.retokenize() as retokenizer:
            retokenizer.split(doc[0], ["Los", "Angeles"], [0, 0])


@pytest.mark.xfail
def test_split_heads_out_of_bounds(en_vocab):
    """Test that the retokenizer raises an error for out-of-bounds heads. The
    indices are relative, so head 1 for "Angeles" would be the token following
    it, which is out-of-bounds. Previously, the retokenizer would accept this
    and spaCy would then fail later.
    """
    doc = Doc(en_vocab, words=["Start", "LosAngeles"])
    with pytest.raises(ValueError):
        with doc.retokenize() as retokenizer:
            retokenizer.split(doc[1], ["Los", "Angeles"], [0, 1])


def test_spans_entity_merge_iob():
    # Test entity IOB stays consistent after merging
    words = ["abc", "d", "e"]
    doc = Doc(Vocab(), words=words)
    doc.ents = [(doc.vocab.strings.add("ent-abcd"), 0, 2)]
    assert doc[0].ent_iob_ == "B"
    assert doc[1].ent_iob_ == "I"
    with doc.retokenize() as retokenizer:
        retokenizer.split(doc[0], ["a", "b", "c"], [1, 1, 0])
    assert doc[0].ent_iob_ == "B"
    assert doc[1].ent_iob_ == "I"
    assert doc[2].ent_iob_ == "I"
    assert doc[3].ent_iob_ == "I"


def test_spans_sentence_update_after_merge(en_vocab):
    # fmt: off
    words = ["StewartLee", "is", "a", "stand", "up", "comedian", ".", "He",
             "lives", "in", "England", "and", "loves", "JoePasquale", "."]
    heads = [1, 0, 1, 2, -1, -4, -5, 1, 0, -1, -1, -3, -4, 1, -2]
    deps = ["nsubj", "ROOT", "det", "amod", "prt", "attr", "punct", "nsubj",
            "ROOT", "prep", "pobj", "cc", "conj", "compound", "punct"]
    # fmt: on
    doc = get_doc(en_vocab, words=words, heads=heads, deps=deps)
    sent1, sent2 = list(doc.sents)
    init_len = len(sent1)
    init_len2 = len(sent2)
    with doc.retokenize() as retokenizer:
        retokenizer.split(doc[0], ["Stewart", "Lee"], [1, 0])
        retokenizer.split(doc[14], ["Joe", "Pasquale"], [1, 0])
    sent1, sent2 = list(doc.sents)
    assert len(sent1) == init_len + 1
    assert len(sent2) == init_len2 + 1

@@ -4114,12 +4114,650 @@
 it_len2 + 1%0A
+%0A%0A@pytest.mark.xfail%0Adef test_split_orths_mismatch(en_vocab):%0A    %22%22%22Test that the regular retokenizer.split raises an error if the orths%0A    don't match the original token text. There might still be a method that%0A    allows this, but for the default use cases, merging and splitting should%0A    always conform with spaCy's non-destructive tokenization policy. Otherwise,%0A    it can lead to very confusing and unexpected results.%0A    %22%22%22%0A    doc = Doc(en_vocab, words=%5B%22LosAngeles%22, %22start%22, %22.%22%5D)%0A    with pytest.raises(ValueError):%0A        with doc.retokenize() as retokenizer:%0A            retokenizer.split(doc%5B0%5D, %5B%22L%22, %22A%22%5D, %5B0, -1%5D)%0A

Add xfailing test for orth mismatch in retokenizer.split