102 lines
2.2 KiB
C#
102 lines
2.2 KiB
C#
using Godot;
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using Rokojori.Extensions;
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namespace Rokojori;
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public class LevenshteinFuzzyMatch
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{
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public int lowestDistance;
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public int index;
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}
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public class LevenshteinDistance
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{
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protected static int[,] GetMatrix( int aLength, int bLength )
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{
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var matrix = new int[ aLength + 1, bLength + 1];
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for ( var i = 0; i <= aLength; i++ )
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{
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matrix[ i, 0 ] = i;
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}
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for ( var j = 0; j <= bLength; j++ )
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{
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matrix[ 0, j ] = j;
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}
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return matrix;
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}
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public static LevenshteinFuzzyMatch ComputeFuzzyMatch( string value, string matcher )
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{
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var result = new LevenshteinFuzzyMatch();
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if ( matcher.Length >= value.Length )
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{
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result.index = 0;
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result.lowestDistance = LevenshteinDistance.Compute( value, matcher );
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}
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else
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{
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var offsets = value.Length - matcher.Length;
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for ( var i = 0; i < offsets; i++ )
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{
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var subValue = value.Substring( i, matcher.Length );
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var distance = LevenshteinDistance.Compute( subValue, matcher );
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if ( i == 0 )
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{
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result.index = 0;
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result.lowestDistance = distance;
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continue;
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}
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if ( distance < result.lowestDistance )
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{
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result.index = i;
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result.lowestDistance = distance;
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}
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}
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}
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return result;
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}
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public static int Compute( string a, string b )
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{
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var aLength = a.Length;
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var bLength = b.Length;
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if ( aLength == 0 ) { return bLength; }
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if ( bLength == 0 ) { return aLength; }
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var evaluationMatrix = LevenshteinDistance.GetMatrix( aLength, bLength );
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for ( var i = 1; i <= aLength; i++ )
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{
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for ( var j = 1; j <= bLength; j++ )
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{
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var isSame = b[ j - 1 ] == a[ i - 1 ];
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var isDifferentCost = isSame ? 0 : 1;
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var insertionCost = evaluationMatrix[ i - 1, j ] + 1;
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var deletionCost = evaluationMatrix[ i , j - 1 ] + 1;
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var substitutionCost = evaluationMatrix[ i - 1, j - 1 ] + isDifferentCost;
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evaluationMatrix[ i , j ] = Mathf.Min( Mathf.Min( insertionCost, deletionCost ), substitutionCost );
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}
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}
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return evaluationMatrix[ aLength, bLength ];
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}
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}
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