#region License Information
/* HeuristicLab
 * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
 *
 * This file is part of HeuristicLab.
 *
 * HeuristicLab is free software: you can redistribute it and/or modify
 * it under the terms of the GNU General Public License as published by
 * the Free Software Foundation, either version 3 of the License, or
 * (at your option) any later version.
 *
 * HeuristicLab is distributed in the hope that it will be useful,
 * but WITHOUT ANY WARRANTY; without even the implied warranty of
 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 * GNU General Public License for more details.
 *
 * You should have received a copy of the GNU General Public License
 * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
 */
#endregion

using System;
using System.Collections.Generic;
using System.Linq;
using HeuristicLab.Common;
using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;

namespace HeuristicLab.Problems.DataAnalysis.Symbolic.ConstantsOptimization {
  public static class Util {
    /// <summary>
    /// Extracts all variable information in a symbolic expression tree. The variable information is necessary to convert a tree in an AutoDiff term.
    /// </summary>
    /// <param name="tree">The tree referencing the variables.</param>
    /// <returns>The data for variables occuring in the tree.</returns>
    public static List<VariableData> ExtractVariables(ISymbolicExpressionTree tree) {
      if (tree == null) throw new ArgumentNullException("tree");

      var variables = new HashSet<VariableData>();
      foreach (var node in tree.IterateNodesPrefix().OfType<IVariableTreeNode>()) {
        string variableName = node.VariableName;
        int lag = 0;
        var laggedNode = node as ILaggedTreeNode;
        if (laggedNode != null) lag = laggedNode.Lag;


        var factorNode = node as FactorVariableTreeNode;
        if (factorNode != null) {
          foreach (var factorValue in factorNode.Symbol.GetVariableValues(variableName)) {
            var data = new VariableData(variableName, factorValue, lag);
            variables.Add(data);
          }
        } else {
          var data = new VariableData(variableName, string.Empty, lag);
          variables.Add(data);
        }
      }
      return variables.ToList();
    }
    /// <summary>
    /// Extract the necessary date for constants optimization with AutoDiff
    /// </summary>
    /// <param name="dataset">The dataset holding the data.</param>
    /// <param name="variables">The variables for which the data from the dataset should be extracted.</param>
    /// <param name="rows">The rows for which the data should be extracted.</param>
    /// <returns>A two-dimensiona double array containing the input data.</returns>
    public static double[,] ExtractData(IDataset dataset, IEnumerable<VariableData> variables, IEnumerable<int> rows) {
      if (dataset == null) throw new ArgumentNullException("dataset");
      if (variables == null) throw new ArgumentNullException("variables");
      if (rows == null) throw new ArgumentNullException("rows");

      var x = new double[rows.Count(), variables.Count()];

      int col = 0;
      foreach (var variable in variables) {
        if (dataset.VariableHasType<double>(variable.variableName)) {
          IEnumerable<double> values;
          if (variable.lag == 0)
            values = dataset.GetDoubleValues(variable.variableName, rows);
          else
            values = dataset.GetDoubleValues(variable.variableName, rows.Select(r => r + variable.lag));

          int row = 0;
          foreach (var value in values) {
            x[row, col] = value;
            row++;
          }
        } else if (dataset.VariableHasType<string>(variable.variableName)) {
          var values = dataset.GetStringValues(variable.variableName, rows);

          int row = 0;
          foreach (var value in values) {
            x[row, col] = value == variable.variableValue ? 1 : 0; ;
            row++;
          }
        } else throw new NotSupportedException("found a variable of unknown type");
        col++;
      }

      return x;
    }

    /// <summary>
    /// Extracts all numeric nodes from a symbolic expression tree that can be optimized by the constants optimization
    /// </summary>
    /// <param name="tree">The tree from which the numeric nodes should be extracted.</param>
    /// <returns>A list containing all nodes with numeric coefficients.</returns>
    public static List<ISymbolicExpressionTreeNode> ExtractNumericNodes(ISymbolicExpressionTree tree) {
      if (tree == null) throw new ArgumentNullException("tree");

      var nodes = new List<ISymbolicExpressionTreeNode>();
      foreach (var node in tree.IterateNodesPrefix().OfType<SymbolicExpressionTreeTerminalNode>()) {
        ConstantTreeNode constantTreeNode = node as ConstantTreeNode;
        VariableTreeNodeBase variableTreeNodeBase = node as VariableTreeNodeBase;
        FactorVariableTreeNode factorVarTreeNode = node as FactorVariableTreeNode;
        if (constantTreeNode != null) nodes.Add(constantTreeNode);
        else if (variableTreeNodeBase != null) nodes.Add(variableTreeNodeBase);
        else if (factorVarTreeNode != null) nodes.Add(variableTreeNodeBase);
        else throw new NotSupportedException(string.Format("Terminal nodes of type {0} are not supported.", node.GetType().GetPrettyName()));
      }
      return nodes;
    }

    /// <summary>
    /// Extracts all numeric constants from a symbolic expression tree.
    /// </summary>
    /// <param name="tree">The tree from which the numeric constants should be extracted.</param>
    /// <param name="addLinearScalingConstants">Flag to determine whether constants for linear scaling have to be added at the end.
    /// α *f(x) + β, α = 1.0,  β = 0.0 </param>
    /// <returns> An array containing the numeric constants.</returns>
    public static double[] ExtractConstants(ISymbolicExpressionTree tree, bool addLinearScalingConstants) {
      if (tree == null) throw new ArgumentNullException("tree");
      return ExtractConstants(tree.IterateNodesPrefix().OfType<SymbolicExpressionTreeTerminalNode>(), addLinearScalingConstants);
    }

    /// <summary>
    /// Extracts all numeric constants from a list of nodes.
    /// </summary>
    /// <param name="nodes">The list of nodes for which the numeric constants should be extracted.</param>
    /// <param name="addLinearScalingConstants">Flag to determine whether constants for linear scaling have to be added at the end.
    /// α *f(x) + β, α = 1.0,  β = 0.0 </param>
    /// <returns> An array containing the numeric constants.</returns>
    public static double[] ExtractConstants(IEnumerable<ISymbolicExpressionTreeNode> nodes, bool addLinearScalingConstants) {
      if (nodes == null) throw new ArgumentNullException("nodes");

      var constants = new List<double>();
      foreach (var node in nodes) {
        ConstantTreeNode constantTreeNode = node as ConstantTreeNode;
        VariableTreeNodeBase variableTreeNodeBase = node as VariableTreeNodeBase;
        FactorVariableTreeNode factorVarTreeNode = node as FactorVariableTreeNode;
        if (constantTreeNode != null)
          constants.Add(constantTreeNode.Value);
        else if (variableTreeNodeBase != null)
          constants.Add(variableTreeNodeBase.Weight);
        else if (factorVarTreeNode != null) {
          for (int j = 0; j < factorVarTreeNode.Weights.Length; j++)
            constants.Add(factorVarTreeNode.Weights[j]);
        } else throw new NotSupportedException(string.Format("Nodes of type {0} are not supported.", node.GetType().GetPrettyName()));
      }
      if (addLinearScalingConstants) {
        constants.Add(1.0);
        constants.Add(0.0);
      }
      return constants.ToArray();
    }

    /// <summary>
    /// Sets the numeric constants of the nodes to the provided values.
    /// </summary>
    /// <param name="nodes">The nodes whose constants should be updated.</param>
    /// <param name="constants">The numeric constants which should be set. </param>
    public static void UpdateConstants(IEnumerable<ISymbolicExpressionTreeNode> nodes, double[] constants) {
      if (nodes == null) throw new ArgumentNullException("nodes");
      if (constants == null) throw new ArgumentNullException("constants");

      int i = 0;
      foreach (var node in nodes) {
        ConstantTreeNode constantTreeNode = node as ConstantTreeNode;
        VariableTreeNodeBase variableTreeNodeBase = node as VariableTreeNodeBase;
        FactorVariableTreeNode factorVarTreeNode = node as FactorVariableTreeNode;
        if (constantTreeNode != null)
          constantTreeNode.Value = constants[i++];
        else if (variableTreeNodeBase != null)
          variableTreeNodeBase.Weight = constants[i++];
        else if (factorVarTreeNode != null) {
          for (int j = 0; j < factorVarTreeNode.Weights.Length; j++)
            factorVarTreeNode.Weights[j] = constants[i++];
        } else throw new NotSupportedException(string.Format("Terminal nodes of type {0} are not supported.", node.GetType().GetPrettyName()));
      }
    }

    /// <summary>
    /// Sets all numeric constants of the symbolic expression tree to the provided values.
    /// </summary>
    /// <param name="tree">The tree for which the numeric constants should be updated.</param>
    /// <param name="constants">The numeric constants which should be set.</param>
    public static void UpdateConstants(ISymbolicExpressionTree tree, double[] constants) {
      if (tree == null) throw new ArgumentNullException("tree");
      if (constants == null) throw new ArgumentNullException("constants");
      UpdateConstants(tree.IterateNodesPrefix().OfType<SymbolicExpressionTreeTerminalNode>(), constants);
    }
  }
}