[14843] | 1 | #region License Information
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| 2 | /* HeuristicLab
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| 3 | * Copyright (C) 2002-2016 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 System;
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| 23 | using System.Collections.Generic;
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| 24 | using System.Linq;
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| 25 | using AutoDiff;
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| 26 | using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
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| 27 |
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| 28 | namespace HeuristicLab.Problems.DataAnalysis.Symbolic {
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| 29 |
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| 30 | /// static class which provides methods for all converters for trees for convenience
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| 31 | public static class Convert {
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| 32 | public static void ConvertToAutoDiff(ISymbolicExpressionTree tree, bool makeVariableWeightsVariable,
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| 33 | out List<TreeToAutoDiffTermConverter.DataForVariable> parameters, out double[] initialConstants,
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| 34 | out TreeToAutoDiffTermConverter.ParametricFunction func,
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| 35 | out TreeToAutoDiffTermConverter.ParametricFunctionGradient func_grad) {
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| 36 | var success = TreeToAutoDiffTermConverter.TryConvertToAutoDiff(tree, makeVariableWeightsVariable, out parameters,
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| 37 | out initialConstants, out func, out func_grad);
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| 38 | if (!success) throw new ArgumentException("Cannot convert tree to AutoDiff term.");
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| 39 | }
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| 40 |
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| 41 | public static ISymbolicExpressionTree Simplify(ISymbolicExpressionTree tree) {
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| 42 | var simplifier = new TreeSimplifier();
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| 43 | return simplifier.Simplify(tree);
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| 44 | }
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| 45 |
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| 46 | public static ISymbolicExpressionTree CreateLinearModel(string[] variableNames, double[] coefficients,
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| 47 | double @const = 0) {
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| 48 | return LinearModelToTreeConverter.CreateTree(variableNames, coefficients, @const);
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| 49 | }
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| 50 | public static ISymbolicExpressionTree CreateLinearModel(string[] variableNames, int[] lags, double[] coefficients,
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| 51 | double @const = 0) {
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| 52 | return LinearModelToTreeConverter.CreateTree(variableNames, coefficients, @const);
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| 53 | }
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| 54 | }
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| 55 | }
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