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import io
from django.test import TestCase
from seqeval.metrics.sequence_labeling import get_entities
from ..models import Label, Document
from ..utils import BaseStorage, ClassificationStorage, SequenceLabelingStorage, Seq2seqStorage, CoNLLParser
from ..utils import iterable_to_io
class TestBaseStorage(TestCase):
def test_extract_label(self):
data = [{'labels': ['positive']}, {'labels': ['negative']}]
actual = BaseStorage.extract_label(data)
self.assertEqual(actual, [['positive'], ['negative']])
def test_exclude_created_labels(self):
labels = ['positive', 'negative']
created = {'positive': Label(text='positive')}
actual = BaseStorage.exclude_created_labels(labels, created)
self.assertEqual(actual, ['negative'])
def test_to_serializer_format(self):
labels = ['positive']
created = {}
actual = BaseStorage.to_serializer_format(labels, created)
self.assertEqual(len(actual), 1)
self.assertEqual(actual[0]['text'], 'positive')
self.assertIsNone(actual[0]['prefix_key'])
self.assertEqual(actual[0]['suffix_key'], 'p')
self.assertIsNotNone(actual[0]['background_color'])
self.assertIsNotNone(actual[0]['text_color'])
def test_get_shortkey_without_existing_shortkey(self):
label = 'positive'
created = {}
actual = BaseStorage.get_shortkey(label, created)
self.assertEqual(actual, ('p', None))
def test_get_shortkey_with_existing_shortkey(self):
label = 'positive'
created = {('p', None)}
actual = BaseStorage.get_shortkey(label, created)
self.assertEqual(actual, ('p', 'ctrl'))
def test_update_saved_labels(self):
saved = {'positive': Label(text='positive', text_color='#000000')}
new = [Label(text='positive', text_color='#ffffff')]
actual = BaseStorage.update_saved_labels(saved, new)
self.assertEqual(actual['positive'].text_color, '#ffffff')
class TestClassificationStorage(TestCase):
def test_extract_unique_labels(self):
labels = [['positive'], ['positive', 'negative'], ['negative']]
actual = ClassificationStorage.extract_unique_labels(labels)
self.assertCountEqual(actual, ['positive', 'negative'])
def test_make_annotations(self):
docs = [Document(text='a', id=1), Document(text='b', id=2), Document(text='c', id=3)]
labels = [['positive'], ['positive', 'negative'], ['negative']]
saved_labels = {'positive': Label(text='positive', id=1), 'negative': Label(text='negative', id=2)}
actual = ClassificationStorage.make_annotations(docs, labels, saved_labels)
self.assertCountEqual(actual, [
{'document': 1, 'label': 1},
{'document': 2, 'label': 1},
{'document': 2, 'label': 2},
{'document': 3, 'label': 2},
])
class TestSequenceLabelingStorage(TestCase):
def test_extract_unique_labels(self):
labels = [[[0, 1, 'LOC']], [[3, 4, 'ORG']]]
actual = SequenceLabelingStorage.extract_unique_labels(labels)
self.assertCountEqual(actual, ['LOC', 'ORG'])
def test_make_annotations(self):
docs = [Document(text='a', id=1), Document(text='b', id=2)]
labels = [[[0, 1, 'LOC']], [[3, 4, 'ORG']]]
saved_labels = {'LOC': Label(text='LOC', id=1), 'ORG': Label(text='ORG', id=2)}
actual = SequenceLabelingStorage.make_annotations(docs, labels, saved_labels)
self.assertEqual(actual, [
{'document': 1, 'label': 1, 'start_offset': 0, 'end_offset': 1},
{'document': 2, 'label': 2, 'start_offset': 3, 'end_offset': 4},
])
class TestSeq2seqStorage(TestCase):
def test_make_annotations(self):
docs = [Document(text='a', id=1), Document(text='b', id=2)]
labels = [['Hello!'], ['How are you?', "What's up?"]]
actual = Seq2seqStorage.make_annotations(docs, labels)
self.assertEqual(actual, [
{'document': 1, 'text': 'Hello!'},
{'document': 2, 'text': 'How are you?'},
{'document': 2, 'text': "What's up?"},
])
class TestCoNLLParser(TestCase):
def test_calc_char_offset(self):
f = io.BytesIO(
b"EU\tORG\n"
b"rejects\t_\n"
b"German\tMISC\n"
b"call\t_\n"
)
actual = next(CoNLLParser().parse(f))[0]
self.assertEqual(actual, {
'text': 'EU rejects German call',
'labels': [[0, 2, 'ORG'], [11, 17, 'MISC']]
})
class TestIterableToIO(TestCase):
def test(self):
def iterable():
yield b'fo'
yield b'o\nbar\n'
yield b'baz\nrest'
stream = iterable_to_io(iterable())
stream = io.TextIOWrapper(stream)
self.assertEqual(stream.readlines(), ['foo\n', 'bar\n', 'baz\n', 'rest'])