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Setting to use vanilla selection graphics
Property to change Add search bar to seer dialog Cleanup BiasedLevenshtein functions
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,77 +1,82 @@ | ||
| package mindustry.client.utils; | ||
| @file:Suppress("NAME_SHADOWING") | ||
|
|
||
| public class BiasedLevenshtein { | ||
| package mindustry.client.utils | ||
|
|
||
| public static float biasedLevenshtein(String x, String y) { | ||
| int[][] dp = new int[x.length() + 1][y.length() + 1]; | ||
| import arc.math.* | ||
| import kotlin.math.* | ||
|
|
||
| for(int i = 0; i <= x.length(); i++){ | ||
| for(int j = 0; j <= y.length(); j++){ | ||
| if(i == 0){ | ||
| dp[i][j] = j; | ||
| }else if(j == 0){ | ||
| dp[i][j] = i; | ||
| }else{ | ||
| dp[i][j] = Math.min(Math.min(dp[i - 1][j - 1] | ||
| + (x.charAt(i - 1) == y.charAt(j - 1) ? 0 : 1), | ||
| dp[i - 1][j] + 1), | ||
| dp[i][j - 1] + 1); | ||
| object BiasedLevenshtein { | ||
| @JvmOverloads @JvmStatic | ||
| fun biasedLevenshtein(x: String, y: String, caseSensitive: Boolean = false, lengthIndependent: Boolean = false): Float { | ||
| var x = x | ||
| var y = y | ||
| if (!caseSensitive) { | ||
| x = x.lowercase() | ||
| y = y.lowercase() | ||
| } | ||
| if (lengthIndependent) return biasedLevenshteinLengthIndependent(x, y) | ||
|
|
||
| val dp = Array(x.length + 1) { IntArray(y.length + 1) } | ||
| for (i in 0..x.length) { | ||
| for (j in 0..y.length) { | ||
| if (i == 0) { | ||
| dp[i][j] = j | ||
| } else if (j == 0) { | ||
| dp[i][j] = i | ||
| } else { | ||
| dp[i][j] = minOf( | ||
| (dp[i - 1][j - 1] + if (x[i - 1] == y[j - 1]) 0 else 1), | ||
| (dp[i - 1][j] + 1), | ||
| (dp[i][j - 1] + 1) | ||
| ) | ||
| } | ||
| } | ||
| } | ||
|
|
||
| int output = dp[x.length()][y.length()]; | ||
| val output = dp[x.length][y.length] | ||
| if (y.startsWith(x) || x.startsWith(y)) { | ||
| return output / 3f; | ||
| return output / 3f | ||
| } | ||
| if (y.contains(x) || x.contains(y)) { | ||
| return output / 1.5f; | ||
| } | ||
| return output; | ||
| } | ||
|
|
||
| public static float biasedLevenshteinInsensitive(String x, String y) { | ||
| return biasedLevenshtein(x.toLowerCase(), y.toLowerCase()); | ||
| return if (y.contains(x) || x.contains(y)) { | ||
| output / 1.5f | ||
| } else output.toFloat() | ||
| } | ||
|
|
||
| public static float biasedLevenshteinLengthIndependent(String x, String y) { | ||
| if (x.length() > y.length()){ | ||
| String temp = x; | ||
| x = y; | ||
| y = temp; | ||
| } | ||
| int xl = x.length(), yl = y.length(); | ||
| int yw = yl + 1; | ||
| int[] dp = new int[2 * yw]; | ||
| // FINISHME: This should be merged with the function above. I can't be bothered to figure out what the differences between the two are now though | ||
| private fun biasedLevenshteinLengthIndependent(x: String, y: String): Float { | ||
| var x = x | ||
| var y = y | ||
| if (x.length > y.length) x = y.apply { y = x } // Y will be the longer of the two | ||
|
|
||
| for(int j=0; j <= yl; ++j){ | ||
| dp[j] = 0; // Insertions at the beginning are free | ||
| } | ||
| int prev = yw, curr = 0, temp; | ||
| for(int i = 1; i <= xl; i++){ | ||
| temp = prev; | ||
| prev = curr; | ||
| curr = temp; | ||
| dp[curr] = i; | ||
| for(int j = 1; j <= yl; j++){ | ||
| dp[curr + j] = Math.min(dp[prev + j - 1] + (x.charAt(i - 1) == y.charAt(j - 1) ? 0 : 1), | ||
| Math.min(dp[prev + j], dp[curr + j - 1]) + 1); | ||
| val xl = x.length | ||
| val yl = y.length | ||
| val yw = yl + 1 | ||
| val dp = IntArray(2 * yw) | ||
| for (j in 0..yl) dp[j] = 0 // Insertions at the beginning are free | ||
| var prev = yw | ||
| var curr = 0 | ||
| var temp: Int | ||
| for (i in 1..xl) { | ||
| temp = prev | ||
| prev = curr | ||
| curr = temp | ||
| dp[curr] = i | ||
| for (j in 1..yl) { | ||
| dp[curr + j] = minOf( | ||
| dp[prev + j - 1] + Mathf.num(x[i - 1] != y[j - 1]), | ||
| dp[prev + j] + 1, | ||
| dp[curr + j - 1] + 1, | ||
| ) | ||
| } | ||
| } | ||
|
|
||
| // startsWith | ||
| if(dp[curr + xl] == 0) return 0f; | ||
| if (dp[curr + xl] == 0) return 0f | ||
| // Disregard insertions at the end - if it made it it made it | ||
| int output = xl; | ||
| for(int i = curr; i < curr + yl; ++i){ | ||
| output = Math.min(output, dp[i]); | ||
| var output = xl | ||
| for (i in curr until curr + yl) { | ||
| output = min(output, dp[i]) | ||
| } | ||
| // contains | ||
| if (output == 0) return 0.5f; // Prefer startsWith | ||
| return output; | ||
| } | ||
|
|
||
| public static float biasedLevenshteinLengthIndependentInsensitive(String x, String y) { | ||
| return biasedLevenshteinLengthIndependent(x.toLowerCase(), y.toLowerCase()); | ||
| return if (output == 0) 0.5f else output.toFloat() // Prefer startsWith | ||
| } | ||
| } |
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