spencermountain--compromise
wehub-resource-sync
42 行
1.4 KiB
JavaScript
42 行
1.4 KiB
JavaScript
import test from 'tape'
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import nlp from '../_lib.js'
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const here = '[three/sentence] '
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test('get full sentence:', function (t) {
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const doc = nlp('one two foo four five. i saw foo house. I ate a sandwhich. Foo was nice')
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const m = doc.match('foo')
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let str = m.eq(0).sentences().text()
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t.equal(str, doc.sentences(0).text(), here + 'first-full-sentence')
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str = m.eq(1).sentences().text()
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t.equal(str, doc.sentences(1).text(), here + 'second-full-sentence')
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str = m.eq(2).sentences().text()
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t.equal(str, doc.sentences(3).text(), here + 'third-full-sentence')
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t.end()
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})
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test('get multiple-copies of one sentence:', function (t) {
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const doc = nlp('John Smith was cool. I am missing. Cindy Lauper and Carl Sagan here. I am also missing.')
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const m = doc.match('#Person+')
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const matches = m.sentences()
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const arr = matches.out('array')
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t.equal(arr.length, 3, here + 'two sentences into three results')
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t.equal(arr[0], 'John Smith was cool.', here + 'one person sentence #1')
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t.equal(arr[1], 'Cindy Lauper and Carl Sagan here.', here + 'two person sentence #1')
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t.equal(arr[2], 'Cindy Lauper and Carl Sagan here.', here + 'two person sentence #2')
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t.end()
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})
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test('sentence append:', function (t) {
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const doc = nlp('"Good bye," he said.')
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doc.sentences().forEach((match) => {
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match.append('and left')
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})
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t.equal(doc.text(), `"Good bye," he said and left.`, here + 'sentence-append')
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t.end()
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})
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