# coding: utf-8 from __future__ import unicode_literals from ..util import get_doc from ...tokens import Doc from ...vocab import Vocab import pytest import numpy @pytest.mark.parametrize('text', [["one", "two", "three"]]) def test_doc_api_compare_by_string_position(en_vocab, text): doc = get_doc(en_vocab, text) # Get the tokens in this order, so their ID ordering doesn't match the idx token3 = doc[-1] token2 = doc[-2] token1 = doc[-1] token1, token2, token3 = doc assert token1 < token2 < token3 assert not token1 > token2 assert token2 > token1 assert token2 <= token3 assert token3 >= token1 def test_doc_api_getitem(en_tokenizer): text = "Give it back! He pleaded." tokens = en_tokenizer(text) assert tokens[0].text == 'Give' assert tokens[-1].text == '.' with pytest.raises(IndexError): tokens[len(tokens)] def to_str(span): return '/'.join(token.text for token in span) span = tokens[1:1] assert not to_str(span) span = tokens[1:4] assert to_str(span) == 'it/back/!' span = tokens[1:4:1] assert to_str(span) == 'it/back/!' with pytest.raises(ValueError): tokens[1:4:2] with pytest.raises(ValueError): tokens[1:4:-1] span = tokens[-3:6] assert to_str(span) == 'He/pleaded' span = tokens[4:-1] assert to_str(span) == 'He/pleaded' span = tokens[-5:-3] assert to_str(span) == 'back/!' span = tokens[5:4] assert span.start == span.end == 5 and not to_str(span) span = tokens[4:-3] assert span.start == span.end == 4 and not to_str(span) span = tokens[:] assert to_str(span) == 'Give/it/back/!/He/pleaded/.' span = tokens[4:] assert to_str(span) == 'He/pleaded/.' span = tokens[:4] assert to_str(span) == 'Give/it/back/!' span = tokens[:-3] assert to_str(span) == 'Give/it/back/!' span = tokens[-3:] assert to_str(span) == 'He/pleaded/.' span = tokens[4:50] assert to_str(span) == 'He/pleaded/.' span = tokens[-50:4] assert to_str(span) == 'Give/it/back/!' span = tokens[-50:-40] assert span.start == span.end == 0 and not to_str(span) span = tokens[40:50] assert span.start == span.end == 7 and not to_str(span) span = tokens[1:4] assert span[0].orth_ == 'it' subspan = span[:] assert to_str(subspan) == 'it/back/!' subspan = span[:2] assert to_str(subspan) == 'it/back' subspan = span[1:] assert to_str(subspan) == 'back/!' subspan = span[:-1] assert to_str(subspan) == 'it/back' subspan = span[-2:] assert to_str(subspan) == 'back/!' subspan = span[1:2] assert to_str(subspan) == 'back' subspan = span[-2:-1] assert to_str(subspan) == 'back' subspan = span[-50:50] assert to_str(subspan) == 'it/back/!' subspan = span[50:-50] assert subspan.start == subspan.end == 4 and not to_str(subspan) @pytest.mark.parametrize('text', ["Give it back! He pleaded.", " Give it back! He pleaded. "]) def test_doc_api_serialize(en_tokenizer, text): tokens = en_tokenizer(text) new_tokens = get_doc(tokens.vocab).from_bytes(tokens.to_bytes()) assert tokens.text == new_tokens.text assert [t.text for t in tokens] == [t.text for t in new_tokens] assert [t.orth for t in tokens] == [t.orth for t in new_tokens] def test_doc_api_set_ents(en_tokenizer): text = "I use goggle chrone to surf the web" tokens = en_tokenizer(text) assert len(tokens.ents) == 0 tokens.ents = [(tokens.vocab.strings['PRODUCT'], 2, 4)] assert len(list(tokens.ents)) == 1 assert [t.ent_iob for t in tokens] == [0, 0, 3, 1, 0, 0, 0, 0] assert tokens.ents[0].label_ == 'PRODUCT' assert tokens.ents[0].start == 2 assert tokens.ents[0].end == 4 def test_doc_api_merge(en_tokenizer): text = "WKRO played songs by the beach boys all night" # merge 'The Beach Boys' doc = en_tokenizer(text) assert len(doc) == 9 doc.merge(doc[4].idx, doc[6].idx + len(doc[6]), 'NAMED', 'LEMMA', 'TYPE') assert len(doc) == 7 assert doc[4].text == 'the beach boys' assert doc[4].text_with_ws == 'the beach boys ' assert doc[4].tag_ == 'NAMED' # merge 'all night' doc = en_tokenizer(text) assert len(doc) == 9 doc.merge(doc[7].idx, doc[8].idx + len(doc[8]), 'NAMED', 'LEMMA', 'TYPE') assert len(doc) == 8 assert doc[7].text == 'all night' assert doc[7].text_with_ws == 'all night' def test_doc_api_merge_children(en_tokenizer): """Test that attachments work correctly after merging.""" text = "WKRO played songs by the beach boys all night" doc = en_tokenizer(text) assert len(doc) == 9 doc.merge(doc[4].idx, doc[6].idx + len(doc[6]), 'NAMED', 'LEMMA', 'TYPE') for word in doc: if word.i < word.head.i: assert word in list(word.head.lefts) elif word.i > word.head.i: assert word in list(word.head.rights) def test_doc_api_merge_hang(en_tokenizer): text = "through North and South Carolina" doc = en_tokenizer(text) doc.merge(18, 32, '', '', 'ORG') doc.merge(8, 32, '', '', 'ORG') def test_doc_api_sents_empty_string(en_tokenizer): doc = en_tokenizer("") doc.is_parsed = True sents = list(doc.sents) assert len(sents) == 0 def test_doc_api_runtime_error(en_tokenizer): # Example that caused run-time error while parsing Reddit text = "67% of black households are single parent \n\n72% of all black babies born out of wedlock \n\n50% of all black kids don\u2019t finish high school" deps = ['nsubj', 'prep', 'amod', 'pobj', 'ROOT', 'amod', 'attr', '', 'nummod', 'prep', 'det', 'amod', 'pobj', 'acl', 'prep', 'prep', 'pobj', '', 'nummod', 'prep', 'det', 'amod', 'pobj', 'aux', 'neg', 'ROOT', 'amod', 'dobj'] tokens = en_tokenizer(text) doc = get_doc(tokens.vocab, [t.text for t in tokens], deps=deps) nps = [] for np in doc.noun_chunks: while len(np) > 1 and np[0].dep_ not in ('advmod', 'amod', 'compound'): np = np[1:] if len(np) > 1: nps.append((np.start_char, np.end_char, np.root.tag_, np.text, np.root.ent_type_)) for np in nps: doc.merge(*np) def test_doc_api_right_edge(en_tokenizer): """Test for bug occurring from Unshift action, causing incorrect right edge""" text = "I have proposed to myself, for the sake of such as live under the government of the Romans, to translate those books into the Greek tongue." heads = [2, 1, 0, -1, -1, -3, 15, 1, -2, -1, 1, -3, -1, -1, 1, -2, -1, 1, -2, -7, 1, -19, 1, -2, -3, 2, 1, -3, -26] tokens = en_tokenizer(text) doc = get_doc(tokens.vocab, [t.text for t in tokens], heads=heads) assert doc[6].text == 'for' subtree = [w.text for w in doc[6].subtree] assert subtree == ['for', 'the', 'sake', 'of', 'such', 'as', 'live', 'under', 'the', 'government', 'of', 'the', 'Romans', ','] assert doc[6].right_edge.text == ',' def test_doc_api_has_vector(): vocab = Vocab() vocab.clear_vectors(2) vocab.vectors.add('kitten', numpy.asarray([0., 2.], dtype='f')) doc = Doc(vocab, words=['kitten']) assert doc.has_vector def test_lowest_common_ancestor(en_tokenizer): tokens = en_tokenizer('the lazy dog slept') doc = get_doc(tokens.vocab, [t.text for t in tokens], heads=[2, 1, 1, 0]) lca = doc.get_lca_matrix() assert(lca[1, 1] == 1) assert(lca[0, 1] == 2) assert(lca[1, 2] == 2) def test_parse_tree(en_tokenizer): """Tests doc.print_tree() method.""" text = 'I like New York in Autumn.' heads = [1, 0, 1, -2, -3, -1, -5] tags = ['PRP', 'IN', 'NNP', 'NNP', 'IN', 'NNP', '.'] tokens = en_tokenizer(text) doc = get_doc(tokens.vocab, [t.text for t in tokens], heads=heads, tags=tags) # full method parse_tree(text) is a trivial composition trees = doc.print_tree() assert len(trees) > 0 tree = trees[0] assert all(k in list(tree.keys()) for k in ['word', 'lemma', 'NE', 'POS_fine', 'POS_coarse', 'arc', 'modifiers']) assert tree['word'] == 'like' # check root is correct