[17134] | 1 | using HEAL.Attic;
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| 2 | using HeuristicLab.Data;
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| 3 | using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
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| 4 | using HeuristicLab.Problems.DataAnalysis.Symbolic;
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| 5 | using System.Collections.Generic;
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| 6 | using System.IO;
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| 7 | using System.Linq;
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| 8 |
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| 9 | namespace HeuristicLab.Algorithms.EvolvmentModelsOfModels {
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| 10 | class FileComuncations {
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| 11 | public static void DoubleMatrixPrint(string fileName, double[,] matrix, int size) {
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| 12 | using (var sw = new StreamWriter(fileName)) {
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| 13 | for (int i = 0; i < size; i++) {
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| 14 | for (int j = 0; j < size; j++) {
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| 15 | sw.Write($"{matrix[i, j]}");
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| 16 | if (j < size - 1)
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| 17 | sw.Write(" ");
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| 18 | }
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| 19 | sw.WriteLine();
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| 20 | }
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| 21 | }
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| 22 | }
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| 23 | public static void DoubleMatrixPrint(string fileName, DoubleMatrix matrix) {
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| 24 | using (var sw = new StreamWriter(fileName)) {
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| 25 | for (int i = 0; i < matrix.Rows; i++) {
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| 26 | for (int j = 0; j < matrix.Columns; j++) {
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| 27 | sw.Write($"{matrix[i, j]}");
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| 28 | if (j < matrix.Columns - 1)
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| 29 | sw.Write(" ");
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| 30 | }
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| 31 | sw.WriteLine();
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| 32 | }
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| 33 | }
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| 34 | }
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| 35 | public static void DoubleMatrixPrint(string fileName, List<List<double>> matrix) {
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| 36 | using (var sw = new StreamWriter(fileName)) {
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| 37 | for (int i = 0; i < matrix.Count; i++) {
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| 38 | for (int j = 0; j < matrix[i].Count; j++) {
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| 39 | sw.Write($"{matrix[i][j]}");
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| 40 | if (j < matrix[i].Count - 1)
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| 41 | sw.Write(" ");
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| 42 | }
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| 43 | sw.WriteLine();
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| 44 | }
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| 45 | }
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| 46 | }
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| 47 | public static void DoubleMatrixSerialize(string fileName, double[,] matrix) {
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| 48 | var obj = new DoubleMatrix(matrix);
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| 49 | var proto = new ProtoBufSerializer();
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| 50 | proto.Serialize(obj, fileName);
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| 51 | }
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| 52 | public static void IntMatrixSerialize(string fileName, int[,] matrix) {
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| 53 | var obj = new IntMatrix(matrix);
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| 54 | var proto = new ProtoBufSerializer();
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| 55 | proto.Serialize(obj, fileName);
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| 56 | }
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| 57 | public static void IntMatrixSerialize(string fileName, IntMatrix matrix) {
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| 58 | var proto = new ProtoBufSerializer();
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| 59 | proto.Serialize(matrix, fileName);
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| 60 | }
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| 61 | public static void DoubleMatrixSerialize(string fileName, DoubleMatrix matrix) {
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| 62 | var proto = new ProtoBufSerializer();
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| 63 | proto.Serialize(matrix, fileName);
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| 64 | }
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| 65 | public static double[,] DoubleMatrixDeserialize(string fileName) {
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| 66 | var proto = new ProtoBufSerializer();
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| 67 | var m = (DoubleMatrix)proto.Deserialize(fileName);
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| 68 | double[,] matrix = m.CloneAsMatrix();
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| 69 | return matrix;
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| 70 | }
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| 71 | public static int[,] IntFromDeserialize(string fileName, int size) {
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| 72 | var proto = new ProtoBufSerializer();
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| 73 | var m = (IntMatrix)proto.Deserialize(fileName);
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| 74 | int[,] matrix = m.CloneAsMatrix();
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| 75 | return matrix;
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| 76 | }
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| 77 | public static List<List<int>> IntMatrixFromFileRead(string fileName) {
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| 78 | string input = File.ReadAllText(fileName);
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| 79 | var temp = new List<List<int>>();
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| 80 | int i = 0;
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| 81 | foreach (var row in input.Split('\n')) {
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| 82 | temp.Add(new List<int>());
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| 83 | foreach (var col in row.Trim().Split(' ')) {
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| 84 | temp[i].Add(int.Parse(col.Trim()));
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| 85 | }
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| 86 | i++;
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| 87 | }
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| 88 | return temp;
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| 89 | }
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| 90 | public static List<List<double>> DoubleMatrixFromFileRead(string fileName) {
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| 91 | string input = File.ReadAllText(fileName);
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| 92 | var temp = new List<List<double>>();
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| 93 | int i = 0;
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| 94 | foreach (var row in input.Split('\n')) {
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| 95 | temp.Add(new List<double>());
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| 96 | foreach (var col in row.Trim().Split(' ')) {
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| 97 | temp[i].Add(double.Parse(col.Trim()));
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| 98 | }
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| 99 | i++;
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| 100 | }
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| 101 | return temp;
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| 102 | }
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| 103 | public static double[,] DoubleMatrixFromFileRead(string fileName, int size) {
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| 104 | var matrix = new double[size, size];
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| 105 | string input = File.ReadAllText(fileName);
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| 106 | int i = 0, j = 0;
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| 107 | foreach (var row in input.Split('\n')) {
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| 108 | foreach (var col in row.Trim().Split(' ')) {
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| 109 | matrix[i, j] = double.Parse(col.Trim());
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| 110 | j++;
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| 111 | }
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| 112 | i++;
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| 113 | }
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| 114 | return matrix;
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| 115 | }
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| 116 | public static void TreesEvoluationResultsToTxtFile(ISymbolicDataAnalysisSingleObjectiveProblem problem, List<ISymbolicExpressionTree> trees) {
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| 117 | var problemData = problem.ProblemData;
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| 118 | var dataset = problemData.Dataset;
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| 119 | var rows = problemData.TrainingIndices;
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| 120 | var interpreter = problem.SymbolicExpressionTreeInterpreter;
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| 121 | string[] toWrite = new string[trees.Count()];
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| 122 | int i = 0;
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| 123 | foreach (var tree in trees) {
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| 124 | var estimatedValues = interpreter.GetSymbolicExpressionTreeValues(tree, dataset, rows);
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| 125 | string str = "";
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| 126 | foreach (var value in estimatedValues) {
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| 127 | str += value.ToString() + " ";
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| 128 | }
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| 129 | toWrite[i] = str;
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| 130 | i++;
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| 131 | }
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| 132 | File.WriteAllLines("evolv.txt", toWrite);
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| 133 | }
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| 134 | }
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| 135 | }
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