[2616] | 1 | #region License Information
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| 2 | /* HeuristicLab
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| 3 | * Copyright (C) 2002-2008 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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| 4 | *
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| 5 | * This file is part of HeuristicLab.
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| 6 | *
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| 7 | * HeuristicLab is free software: you can redistribute it and/or modify
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| 8 | * it under the terms of the GNU General Public License as published by
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| 9 | * the Free Software Foundation, either version 3 of the License, or
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| 10 | * (at your option) any later version.
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| 11 | *
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| 12 | * HeuristicLab is distributed in the hope that it will be useful,
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| 13 | * but WITHOUT ANY WARRANTY; without even the implied warranty of
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| 14 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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| 15 | * GNU General Public License for more details.
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| 16 | *
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| 17 | * You should have received a copy of the GNU General Public License
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| 18 | * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
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| 19 | */
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| 20 | #endregion
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| 21 |
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| 22 | using HeuristicLab.GP.StructureIdentification;
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| 23 | using Microsoft.VisualStudio.TestTools.UnitTesting;
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| 24 | using HeuristicLab.DataAnalysis;
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| 25 | using System;
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| 26 | using HeuristicLab.GP.Interfaces;
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| 27 | using HeuristicLab.Random;
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| 28 | using HeuristicLab.GP.Operators;
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| 29 | using System.Collections.Generic;
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| 30 | using System.Text;
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| 31 | using HeuristicLab.GP.StructureIdentification.Networks;
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| 32 | using System.Diagnostics;
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| 33 | namespace HeuristicLab.GP.Test {
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| 34 |
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| 35 |
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| 36 | [TestClass()]
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| 37 | public class NetworkFunctionLibraryTest {
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| 38 | private const int N = 1000;
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| 39 | private TestContext testContextInstance;
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| 40 | private static IFunctionTree[] randomTrees;
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| 41 |
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| 42 | /// <summary>
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| 43 | ///Gets or sets the test context which provides
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| 44 | ///information about and functionality for the current test run.
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| 45 | ///</summary>
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| 46 | public TestContext TestContext {
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| 47 | get {
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| 48 | return testContextInstance;
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| 49 | }
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| 50 | set {
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| 51 | testContextInstance = value;
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| 52 | }
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| 53 | }
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| 54 |
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| 55 | [ClassInitialize()]
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| 56 | public static void CreateRandomNetworks(TestContext testContext) {
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| 57 | MersenneTwister twister = new MersenneTwister();
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| 58 | Dataset ds = Util.CreateRandomDataset(twister, 1, 20);
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| 59 | randomTrees = Util.CreateRandomTrees(twister, ds, FunctionLibraryInjector.Create(true, -3, 0), N, 1, 100);
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| 60 | }
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| 61 |
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| 62 | [TestMethod()]
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| 63 | public void NetworkFunctionLibrarySizeDistributionTest() {
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| 64 | int[] histogram = new int[105 / 5];
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| 65 | for (int i = 0; i < randomTrees.Length; i++) {
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| 66 | histogram[randomTrees[i].GetSize() / 5]++;
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| 67 | }
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| 68 | StringBuilder strBuilder = new StringBuilder();
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| 69 | for (int i = 0; i < histogram.Length; i++) {
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| 70 | strBuilder.Append(Environment.NewLine);
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| 71 | strBuilder.Append("< "); strBuilder.Append((i + 1) * 5);
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| 72 | strBuilder.Append(": "); strBuilder.AppendFormat("{0:#0.00%}", histogram[i] / (double)randomTrees.Length);
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| 73 | }
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| 74 | Assert.Inconclusive("Size distribution of ProbabilisticTreeCreator: " + strBuilder);
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| 75 | }
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| 76 |
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| 77 | [TestMethod()]
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| 78 | public void NetworkFunctionLibraryFunctionDistributionTest() {
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| 79 | Dictionary<IFunction, int> occurances = new Dictionary<IFunction, int>();
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| 80 | double n = 0.0;
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| 81 | for (int i = 0; i < randomTrees.Length; i++) {
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| 82 | foreach (var node in FunctionTreeIterator.IteratePrefix(randomTrees[i])) {
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| 83 | if (node.SubTrees.Count > 0) {
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| 84 | if (!occurances.ContainsKey(node.Function))
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| 85 | occurances[node.Function] = 0;
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| 86 | occurances[node.Function]++;
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| 87 | n++;
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| 88 | }
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| 89 | }
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| 90 | }
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| 91 | StringBuilder strBuilder = new StringBuilder();
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| 92 | foreach (var function in occurances.Keys) {
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| 93 | strBuilder.Append(Environment.NewLine);
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| 94 | strBuilder.Append(function.Name); strBuilder.Append(": ");
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| 95 | strBuilder.AppendFormat("{0:#0.00%}", occurances[function] / n);
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| 96 | }
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| 97 | Assert.Inconclusive("Function distribution of ProbabilisticTreeCreator: " + strBuilder);
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| 98 | }
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| 99 |
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| 100 | [TestMethod()]
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| 101 | public void NetworkFunctionLibraryNumberOfSubTreesDistributionTest() {
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| 102 | Dictionary<int, int> occurances = new Dictionary<int, int>();
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| 103 | double n = 0.0;
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| 104 | for (int i = 0; i < randomTrees.Length; i++) {
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| 105 | foreach (var node in FunctionTreeIterator.IteratePrefix(randomTrees[i])) {
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| 106 | if (!occurances.ContainsKey(node.SubTrees.Count))
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| 107 | occurances[node.SubTrees.Count] = 0;
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| 108 | occurances[node.SubTrees.Count]++;
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| 109 | n++;
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| 110 | }
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| 111 | }
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| 112 | StringBuilder strBuilder = new StringBuilder();
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| 113 | foreach (var arity in occurances.Keys) {
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| 114 | strBuilder.Append(Environment.NewLine);
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| 115 | strBuilder.Append(arity); strBuilder.Append(": ");
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| 116 | strBuilder.AppendFormat("{0:#0.00%}", occurances[arity] / n);
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| 117 | }
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| 118 | Assert.Inconclusive("Distribution of function arities of ProbabilisticTreeCreator: " + strBuilder);
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| 119 | }
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| 120 |
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| 121 |
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| 122 | [TestMethod()]
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| 123 | public void NetworkFunctionLibraryTerminalDistributionTest() {
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| 124 | Dictionary<IFunction, int> occurances = new Dictionary<IFunction, int>();
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| 125 | double n = 0.0;
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| 126 | for (int i = 0; i < randomTrees.Length; i++) {
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| 127 | foreach (var node in FunctionTreeIterator.IteratePrefix(randomTrees[i])) {
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| 128 | if (node.SubTrees.Count == 0) {
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| 129 | if (!occurances.ContainsKey(node.Function))
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| 130 | occurances[node.Function] = 0;
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| 131 | occurances[node.Function]++;
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| 132 | n++;
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| 133 | }
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| 134 | }
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| 135 | }
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| 136 | StringBuilder strBuilder = new StringBuilder();
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| 137 | foreach (var function in occurances.Keys) {
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| 138 | strBuilder.Append(Environment.NewLine);
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| 139 | strBuilder.Append(function.Name); strBuilder.Append(": ");
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| 140 | strBuilder.AppendFormat("{0:#0.00%}", occurances[function] / n);
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| 141 | }
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| 142 | Assert.Inconclusive("Terminal distribution of ProbabilisticTreeCreator: " + strBuilder);
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| 143 | }
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| 144 |
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| 145 | [TestMethod()]
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| 146 | public void NetworkFunctionLibraryOpenParametersDistributionTest() {
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| 147 | Dictionary<int, int> occurances = new Dictionary<int, int>();
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| 148 |
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| 149 | for (int i = 0; i < randomTrees.Length; i++) {
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| 150 | int nParameters = CountParameters(randomTrees[i]);
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| 151 |
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| 152 | if (!occurances.ContainsKey(nParameters))
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| 153 | occurances[nParameters] = 1;
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| 154 | occurances[nParameters]++;
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| 155 | }
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| 156 | StringBuilder strBuilder = new StringBuilder();
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| 157 | foreach (var nParameters in occurances.Keys) {
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| 158 | strBuilder.Append(Environment.NewLine);
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| 159 | strBuilder.Append(nParameters); strBuilder.Append(": ");
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| 160 | strBuilder.AppendFormat("{0:#0.00%}", occurances[nParameters] / (double)randomTrees.Length);
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| 161 | }
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| 162 | Assert.Inconclusive("Number of parameters distribution of ProbabilisticTreeCreator: " + strBuilder);
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| 163 | }
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| 164 |
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| 165 | private int CountParameters(IFunctionTree tree) {
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| 166 | if (tree.SubTrees.Count == 0) {
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| 167 | if (tree.Function is OpenParameter) return 1;
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| 168 | else return 0;
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| 169 | } else {
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| 170 | int n = 0;
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| 171 | foreach (var subTree in tree.SubTrees) {
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| 172 | n += CountParameters(subTree);
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| 173 | }
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| 174 | return n;
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| 175 | }
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| 176 | }
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| 177 | }
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| 178 | }
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