Vihren Atlas

heuristicSequenceOptimizations.ts ×1

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unlabeled · c_9c1d926634a8

28 tests · 8874 LOC · 52 files · introduces 0 tests · 20 LOC · 1 file

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Code
1 range20 lines · 1 files
Tests
0 tests

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1502 ranges8874 lines · 52 files · Browse complete extent
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1 file ranked by introduced lines: 20 introduced LOC across 1 ranges. Expand a file to inspect source; the > gutter marks introduced lines.

src/vs/editor/common/diff/defaultLinesDiffComputer/heuristicSequenceOptimizations.ts 20 introduced LOC · 1 range

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401 return false;
402 }
403 > heuristicSequenceOptimizations.ts
404 > const beforeLineCount1 = sequence1.countLinesIn(before.seq1Range);
405 > const beforeSeq1Length = before.seq1Range.length;
406 > const beforeLineCount2 = sequence2.countLinesIn(before.seq2Range);
407 > const beforeSeq2Length = before.seq2Range.length;
408 >
409 > const afterLineCount1 = sequence1.countLinesIn(after.seq1Range);
410 > const afterSeq1Length = after.seq1Range.length;
411 > const afterLineCount2 = sequence2.countLinesIn(after.seq2Range);
412 > const afterSeq2Length = after.seq2Range.length;
413 >
414 > // TODO: Maybe a neural net can be used to derive the result from these numbers
415 >
416 > const max = 2 * 40 + 50;
417 > function cap(v: number): number {
418 > return Math.min(v, max);
419 > }
420 >
421 > if (Math.pow(Math.pow(cap(beforeLineCount1 * 40 + beforeSeq1Length), 1.5) + Math.pow(cap(beforeLineCount2 * 40 + beforeSeq2Length), 1.5), 1.5)
422 > + Math.pow(Math.pow(cap(afterLineCount1 * 40 + afterSeq1Length), 1.5) + Math.pow(cap(afterLineCount2 * 40 + afterSeq2Length), 1.5), 1.5) > ((max ** 1.5) ** 1.5) * 1.3) {
423 return true;
424 }

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