private static SnapshotSpan AsSnapshotSpan(OneSClassifier.Region region, ITextSnapshot snapshot)
{
ITextSnapshotLine lineFromLineNumber = snapshot.GetLineFromLineNumber(region.StartLine);
ITextSnapshotLine textSnapshotLine = region.StartLine == region.EndLine ? lineFromLineNumber : snapshot.GetLineFromLineNumber(region.EndLine);
return(new SnapshotSpan(lineFromLineNumber.Start + region.StartOffset, textSnapshotLine.End));
}
private void ReParse(object sender, EventArgs args)
{
ITextSnapshot newSnapshot = this._buffer.CurrentSnapshot;
List <OneSClassifier.Region> source = new List <OneSClassifier.Region>();
foreach (Match match in new Regex(this.Subs, RegexOptions.IgnoreCase | RegexOptions.Singleline).Matches(newSnapshot.GetText()))
{
ITextSnapshotLine lineFromPosition1 = newSnapshot.GetLineFromPosition(match.Index);
ITextSnapshotLine lineFromPosition2 = newSnapshot.GetLineFromPosition(match.Index + match.Length);
if (lineFromPosition1.LineNumber != lineFromPosition2.LineNumber)
{
if (lineFromPosition1.GetText().Contains("Далее"))
{
int num = Math.Max(match.Value.LastIndexOf("Функция"), match.Value.LastIndexOf("Процедура"));
lineFromPosition1 = newSnapshot.GetLineFromPosition(match.Index + num);
}
List <OneSClassifier.Region> regionList = source;
OneSClassifier.Region region1 = new OneSClassifier.Region();
region1.Level = 1;
region1.StartLine = lineFromPosition1.LineNumber;
region1.StartOffset = lineFromPosition1.Length;
region1.EndLine = lineFromPosition2.LineNumber;
region1.HoverText = newSnapshot.GetText(lineFromPosition1.Start.Position, lineFromPosition2.End.Position - lineFromPosition1.Start.Position);
OneSClassifier.Region region2 = region1;
regionList.Add(region2);
}
}
List <Span> spanList1 = new List <Span>(this.regions.Select <OneSClassifier.Region, Span>((Func <OneSClassifier.Region, Span>)(r => OneSClassifier.AsSnapshotSpan(r, this.snapshot).TranslateTo(newSnapshot, SpanTrackingMode.EdgeExclusive).Span)));
List <Span> spanList2 = new List <Span>(source.Select <OneSClassifier.Region, Span>((Func <OneSClassifier.Region, Span>)(r => OneSClassifier.AsSnapshotSpan(r, newSnapshot).Span)));
NormalizedSpanCollection normalizedSpanCollection = NormalizedSpanCollection.Difference(new NormalizedSpanCollection((IEnumerable <Span>)spanList1), new NormalizedSpanCollection((IEnumerable <Span>)spanList2));
int num1 = int.MaxValue;
int num2 = -1;
if (normalizedSpanCollection.Count > 0)
{
num1 = normalizedSpanCollection[0].Start;
num2 = normalizedSpanCollection[normalizedSpanCollection.Count - 1].End;
}
if (spanList2.Count > 0)
{
num1 = Math.Min(num1, spanList2[0].Start);
num2 = Math.Max(num2, spanList2[spanList2.Count - 1].End);
}
this.snapshot = newSnapshot;
this.regions = source;
if (num1 > num2 || this.TagsChanged == null)
{
return;
}
this.TagsChanged((object)this, new SnapshotSpanEventArgs(new SnapshotSpan(this.snapshot, Span.FromBounds(num1, num2))));
}
