def test_doc_from_array_heads_in_bounds(en_vocab): """Test that Doc.from_array doesn't set heads that are out of bounds.""" words = ["This", "is", "a", "sentence", "."] doc = Doc(en_vocab, words=words) for token in doc: token.head = doc[0] # correct arr = doc.to_array(["HEAD"]) doc_from_array = Doc(en_vocab, words=words) doc_from_array.from_array(["HEAD"], arr) # head before start arr = doc.to_array(["HEAD"]) arr[0] = -1 doc_from_array = Doc(en_vocab, words=words) with pytest.raises(ValueError): doc_from_array.from_array(["HEAD"], arr) # head after end arr = doc.to_array(["HEAD"]) arr[0] = 5 doc_from_array = Doc(en_vocab, words=words) with pytest.raises(ValueError): doc_from_array.from_array(["HEAD"], arr)
def test_doc_from_array_sent_starts(en_vocab): # fmt: off words = ["I", "live", "in", "New", "York", ".", "I", "like", "cats", "."] heads = [0, 0, 0, 0, 0, 0, 6, 6, 6, 6] deps = ["ROOT", "dep", "dep", "dep", "dep", "dep", "ROOT", "dep", "dep", "dep"] # fmt: on doc = Doc(en_vocab, words=words, heads=heads, deps=deps) # HEAD overrides SENT_START without warning attrs = [SENT_START, HEAD] arr = doc.to_array(attrs) new_doc = Doc(en_vocab, words=words) new_doc.from_array(attrs, arr) # no warning using default attrs attrs = doc._get_array_attrs() arr = doc.to_array(attrs) with pytest.warns(None) as record: new_doc.from_array(attrs, arr) assert len(record) == 0 # only SENT_START uses SENT_START attrs = [SENT_START] arr = doc.to_array(attrs) new_doc = Doc(en_vocab, words=words) new_doc.from_array(attrs, arr) assert [t.is_sent_start for t in doc] == [t.is_sent_start for t in new_doc] assert not new_doc.has_annotation("DEP") # only HEAD uses HEAD attrs = [HEAD, DEP] arr = doc.to_array(attrs) new_doc = Doc(en_vocab, words=words) new_doc.from_array(attrs, arr) assert [t.is_sent_start for t in doc] == [t.is_sent_start for t in new_doc] assert new_doc.has_annotation("DEP")
def test_doc_from_array_sent_starts(en_vocab): words = ["I", "live", "in", "New", "York", ".", "I", "like", "cats", "."] heads = [0, 0, 0, 0, 0, 0, 6, 6, 6, 6] # fmt: off deps = ["ROOT", "dep", "dep", "dep", "dep", "dep", "ROOT", "dep", "dep", "dep", "dep"] # fmt: on doc = Doc(en_vocab, words=words) for i, (dep, head) in enumerate(zip(deps, heads)): doc[i].dep_ = dep doc[i].head = doc[head] if head == i: doc[i].is_sent_start = True doc.is_parsed attrs = [SENT_START, HEAD] arr = doc.to_array(attrs) new_doc = Doc(en_vocab, words=words) with pytest.raises(ValueError): new_doc.from_array(attrs, arr) attrs = [SENT_START, DEP] arr = doc.to_array(attrs) new_doc = Doc(en_vocab, words=words) new_doc.from_array(attrs, arr) assert [t.is_sent_start for t in doc] == [t.is_sent_start for t in new_doc] assert not new_doc.is_parsed attrs = [HEAD, DEP] arr = doc.to_array(attrs) new_doc = Doc(en_vocab, words=words) new_doc.from_array(attrs, arr) assert [t.is_sent_start for t in doc] == [t.is_sent_start for t in new_doc] assert new_doc.is_parsed
def test_doc_stringy_array_attr_of_token(en_vocab): doc = Doc(en_vocab, words=["An", "example", "sentence"]) example = doc.vocab["example"] assert example.orth != example.shape feats_array = doc.to_array((ORTH, SHAPE)) feats_array_stringy = doc.to_array(("ORTH", "SHAPE")) assert feats_array_stringy[0][0] == feats_array[0][0] assert feats_array_stringy[0][1] == feats_array[0][1]
def test_doc_stringy_array_attr_of_token(en_vocab): doc = Doc(en_vocab, words=["An", "example", "sentence"]) example = doc.vocab["example"] assert example.orth != example.shape feats_array = doc.to_array((ORTH, SHAPE)) feats_array_stringy = doc.to_array(("ORTH", "SHAPE")) assert feats_array_stringy[0][0] == feats_array[0][0] assert feats_array_stringy[0][1] == feats_array[0][1]
def test_doc_array_to_from_string_attrs(en_vocab, attrs): """Test that both Doc.to_array and Doc.from_array accept string attrs, as well as single attrs and sequences of attrs. """ words = ["An", "example", "sentence"] doc = Doc(en_vocab, words=words) Doc(en_vocab, words=words).from_array(attrs, doc.to_array(attrs))
def get_doc(vocab, words, pos, heads, deps): assert len(pos) == len(words) assert len(heads) == len(words) assert len(deps) == len(words) headings = [] values = [] annotations = [pos, heads, deps] possible_headings = [POS, HEAD, DEP] for a, annot in enumerate(annotations): headings.append(possible_headings[a]) if annot is not heads: values.extend(annot) for value in values: vocab.strings.add(value) doc = Doc(vocab, words=words) attrs = doc.to_array(headings) j = 0 for annot in annotations: if annot is heads: for i in range(len(words)): attrs[i, j] = heads[i] else: for i in range(len(words)): attrs[i, j] = doc.vocab.strings[annot[i]] j += 1 doc.from_array(headings, attrs) return doc
def get_doc(vocab, words=[], pos=None, heads=None, deps=None, tags=None, ents=None): """Create Doc object from given vocab, words and annotations.""" pos = pos or [""] * len(words) tags = tags or [""] * len(words) heads = heads or [0] * len(words) deps = deps or [""] * len(words) for value in deps + tags + pos: vocab.strings.add(value) doc = Doc(vocab, words=words) attrs = doc.to_array([POS, HEAD, DEP]) for i, (p, head, dep) in enumerate(zip(pos, heads, deps)): attrs[i, 0] = doc.vocab.strings[p] attrs[i, 1] = head attrs[i, 2] = doc.vocab.strings[dep] doc.from_array([POS, HEAD, DEP], attrs) if ents: doc.ents = [ Span(doc, start, end, label=doc.vocab.strings[label]) for start, end, label in ents ] if tags: for token in doc: token.tag_ = tags[token.i] return doc
def test_doc_array_to_from_string_attrs(en_vocab, attrs): """Test that both Doc.to_array and Doc.from_array accept string attrs, as well as single attrs and sequences of attrs. """ words = ["An", "example", "sentence"] doc = Doc(en_vocab, words=words) Doc(en_vocab, words=words).from_array(attrs, doc.to_array(attrs))
def get_doc(self, words=[], pos=None, heads=None, deps=None, tags=None, ents=None): """Create Doc object from given vocab, words and annotations.""" vocab = Vocab() pos = pos or [""] * len(words) tags = tags or [""] * len(words) heads = heads or [0] * len(words) deps = deps or [""] * len(words) for value in deps + tags + pos: vocab.strings.add(value) doc = Doc(vocab, words=words) attrs = doc.to_array([POS, HEAD, DEP]) for i, (p, head, dep) in enumerate(zip(pos, heads, deps)): attrs[i, 0] = doc.vocab.strings[p] attrs[i, 1] = head attrs[i, 2] = doc.vocab.strings[dep] doc.from_array([POS, HEAD, DEP], attrs) if ents: doc.ents = [ Span(doc, start, end, label=doc.vocab.strings[label]) for start, end, label in ents ] if tags: for token in doc: token.tag_ = tags[token.i] return doc
def test_doc_array_dep(en_vocab): words = ["A", "nice", "sentence", "."] deps = ["det", "amod", "ROOT", "punct"] doc = Doc(en_vocab, words=words, deps=deps) feats_array = doc.to_array((ORTH, DEP)) assert feats_array[0][1] == doc[0].dep assert feats_array[1][1] == doc[1].dep assert feats_array[2][1] == doc[2].dep assert feats_array[3][1] == doc[3].dep
def get_doc(vocab, words=[], pos=None, heads=None, deps=None, tags=None, ents=None, lemmas=None): """Create Doc object from given vocab, words and annotations.""" if deps and not heads: heads = [0] * len(deps) headings = [] values = [] annotations = [pos, heads, deps, lemmas, tags] possible_headings = [POS, HEAD, DEP, LEMMA, TAG] for a, annot in enumerate(annotations): if annot is not None: if len(annot) != len(words): raise ValueError(Errors.E189) headings.append(possible_headings[a]) if annot is not heads: values.extend(annot) for value in values: vocab.strings.add(value) doc = Doc(vocab, words=words) # if there are any other annotations, set them if headings: attrs = doc.to_array(headings) j = 0 for annot in annotations: if annot: if annot is heads: for i in range(len(words)): if attrs.ndim == 1: attrs[i] = heads[i] else: attrs[i, j] = heads[i] else: for i in range(len(words)): if attrs.ndim == 1: attrs[i] = doc.vocab.strings[annot[i]] else: attrs[i, j] = doc.vocab.strings[annot[i]] j += 1 doc.from_array(headings, attrs) # finally, set the entities if ents: doc.ents = [ Span(doc, start, end, label=doc.vocab.strings[label]) for start, end, label in ents ] return doc
def test_doc_array_tag(en_vocab): words = ["A", "nice", "sentence", "."] pos = ["DET", "ADJ", "NOUN", "PUNCT"] doc = Doc(en_vocab, words=words, pos=pos) assert doc[0].pos != doc[1].pos != doc[2].pos != doc[3].pos feats_array = doc.to_array((ORTH, POS)) assert feats_array[0][1] == doc[0].pos assert feats_array[1][1] == doc[1].pos assert feats_array[2][1] == doc[2].pos assert feats_array[3][1] == doc[3].pos
def test_doc_from_array_morph(en_vocab): # fmt: off words = ["I", "live", "in", "New", "York", "."] morphs = ["Feat1=A", "Feat1=B", "Feat1=C", "Feat1=A|Feat2=D", "Feat2=E", "Feat3=F"] # fmt: on doc = Doc(en_vocab, words=words, morphs=morphs) attrs = [MORPH] arr = doc.to_array(attrs) new_doc = Doc(en_vocab, words=words) new_doc.from_array(attrs, arr) assert [str(t.morph) for t in new_doc] == morphs assert [str(t.morph) for t in doc] == [str(t.morph) for t in new_doc]
def test_doc_array_morph(en_vocab): words = ["Eat", "blue", "ham"] morph = ["Feat=V", "Feat=J", "Feat=N"] doc = Doc(en_vocab, words=words, morphs=morph) assert morph[0] == str(doc[0].morph) assert morph[1] == str(doc[1].morph) assert morph[2] == str(doc[2].morph) feats_array = doc.to_array((ORTH, MORPH)) assert feats_array[0][1] == doc[0].morph.key assert feats_array[1][1] == doc[1].morph.key assert feats_array[2][1] == doc[2].morph.key
def doc_cleaning(doc: Doc): np_array = doc.to_array( [LEMMA, LOWER, POS, TAG, ENT_TYPE, IS_ALPHA, DEP, HEAD, SPACY]) words = [t.text for i, t in enumerate(doc)] cleaned_words = list() for w in words: if w != 'PairDrug1' and w != 'PairDrug2': w = number_substitution(w) if w == '%': w = ' ' cleaned_words.append(w) doc2 = Doc(doc.vocab, words=cleaned_words) doc2.from_array( [LEMMA, LOWER, POS, TAG, ENT_TYPE, IS_ALPHA, DEP, HEAD, SPACY], np_array) return doc2
def test_issue2203(en_vocab): """Test that lemmas are set correctly in doc.from_array.""" words = ["I", "'ll", "survive"] tags = ["PRP", "MD", "VB"] lemmas = ["-PRON-", "will", "survive"] tag_ids = [en_vocab.strings.add(tag) for tag in tags] lemma_ids = [en_vocab.strings.add(lemma) for lemma in lemmas] doc = Doc(en_vocab, words=words) # Work around lemma corrpution problem and set lemmas after tags doc.from_array("TAG", numpy.array(tag_ids, dtype="uint64")) doc.from_array("LEMMA", numpy.array(lemma_ids, dtype="uint64")) assert [t.tag_ for t in doc] == tags assert [t.lemma_ for t in doc] == lemmas # We need to serialize both tag and lemma, since this is what causes the bug doc_array = doc.to_array(["TAG", "LEMMA"]) new_doc = Doc(doc.vocab, words=words).from_array(["TAG", "LEMMA"], doc_array) assert [t.tag_ for t in new_doc] == tags assert [t.lemma_ for t in new_doc] == lemmas
def test_issue2203(en_vocab): """Test that lemmas are set correctly in doc.from_array.""" words = ["I", "'ll", "survive"] tags = ["PRP", "MD", "VB"] lemmas = ["-PRON-", "will", "survive"] tag_ids = [en_vocab.strings.add(tag) for tag in tags] lemma_ids = [en_vocab.strings.add(lemma) for lemma in lemmas] doc = Doc(en_vocab, words=words) # Work around lemma corrpution problem and set lemmas after tags doc.from_array("TAG", numpy.array(tag_ids, dtype="uint64")) doc.from_array("LEMMA", numpy.array(lemma_ids, dtype="uint64")) assert [t.tag_ for t in doc] == tags assert [t.lemma_ for t in doc] == lemmas # We need to serialize both tag and lemma, since this is what causes the bug doc_array = doc.to_array(["TAG", "LEMMA"]) new_doc = Doc(doc.vocab, words=words).from_array(["TAG", "LEMMA"], doc_array) assert [t.tag_ for t in new_doc] == tags assert [t.lemma_ for t in new_doc] == lemmas
def substitution(doc: Doc, index: int, value: int) -> Doc: np_array = doc.to_array( [LEMMA, LOWER, POS, TAG, ENT_TYPE, IS_ALPHA, DEP, HEAD, SPACY]) words = [t.text for i, t in enumerate(doc)] #print(words[index]) if value == -1: item = 'NoPair' if value == 0: item = "Drug" if value == 1: item = "PairDrug1" if value == 2: item = "PairDrug2" words.__setitem__(index, item) doc2 = Doc(doc.vocab, words=words) doc2.from_array( [LEMMA, LOWER, POS, TAG, ENT_TYPE, IS_ALPHA, DEP, HEAD, SPACY], np_array) return doc2
def test_issue3012(en_vocab): """Test that the is_tagged attribute doesn't get overwritten when we from_array without tag information.""" words = ["This", "is", "10", "%", "."] tags = ["DT", "VBZ", "CD", "NN", "."] pos = ["DET", "VERB", "NUM", "NOUN", "PUNCT"] ents = ["O", "O", "B-PERCENT", "I-PERCENT", "O"] doc = Doc(en_vocab, words=words, tags=tags, pos=pos, ents=ents) assert doc.has_annotation("TAG") expected = ("10", "NUM", "CD", "PERCENT") assert (doc[2].text, doc[2].pos_, doc[2].tag_, doc[2].ent_type_) == expected header = [ENT_IOB, ENT_TYPE] ent_array = doc.to_array(header) doc.from_array(header, ent_array) assert (doc[2].text, doc[2].pos_, doc[2].tag_, doc[2].ent_type_) == expected # Serializing then deserializing doc_bytes = doc.to_bytes() doc2 = Doc(en_vocab).from_bytes(doc_bytes) assert (doc2[2].text, doc2[2].pos_, doc2[2].tag_, doc2[2].ent_type_) == expected
def test_doc_scalar_attr_of_token(en_vocab): doc = Doc(en_vocab, words=["An", "example", "sentence"]) example = doc.vocab["example"] assert example.orth != example.shape feats_array = doc.to_array(ORTH) assert feats_array.shape == (3,)
def test_doc_scalar_attr_of_token(en_vocab): doc = Doc(en_vocab, words=["An", "example", "sentence"]) example = doc.vocab["example"] assert example.orth != example.shape feats_array = doc.to_array(ORTH) assert feats_array.shape == (3,)