source: branches/2994-AutoDiffForIntervals/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Interpreter/VectorEvaluator.cs @ 17295

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

namespace HeuristicLab.Problems.DataAnalysis.Symbolic {
  public sealed class VectorEvaluator : Interpreter<AlgebraicDoubleVector> {
    private const int BATCHSIZE = 128;
    [ThreadStatic]
    private Dictionary<string, double[]> cachedData;

    [ThreadStatic]
    private IDataset dataset;

    [ThreadStatic]
    private int rowIndex;

    [ThreadStatic]
    private int[] rows;

    private void InitCache(IDataset dataset) {
      this.dataset = dataset;
      cachedData = new Dictionary<string, double[]>();
      foreach (var v in dataset.DoubleVariables) {
        cachedData[v] = dataset.GetReadOnlyDoubleValues(v).ToArray();
      }
    }

    public double[] Evaluate(ISymbolicExpressionTree tree, IDataset dataset, int[] rows) {
      if (cachedData == null || this.dataset != dataset) {
        InitCache(dataset);
      }

      this.rows = rows;
      var code = Compile(tree);
      var remainingRows = rows.Length % BATCHSIZE;
      var roundedTotal = rows.Length - remainingRows;

      var result = new double[rows.Length];

      for (rowIndex = 0; rowIndex < roundedTotal; rowIndex += BATCHSIZE) {
        Evaluate(code);
        code[0].value.CopyTo(result, rowIndex, BATCHSIZE);
      }

      if (remainingRows > 0) {
        Evaluate(code);
        code[0].value.CopyTo(result, roundedTotal, remainingRows);
      }

      return result;
    }

    protected override void InitializeTerminalInstruction(ref Instruction instruction, ConstantTreeNode constant) {
      instruction.dblVal = constant.Value;
      instruction.value = new AlgebraicDoubleVector(BATCHSIZE);
      instruction.value.AssignConstant(instruction.dblVal);
    }

    protected override void InitializeTerminalInstruction(ref Instruction instruction, VariableTreeNode variable) {
      instruction.dblVal = variable.Weight;
      instruction.value = new AlgebraicDoubleVector(BATCHSIZE);
      if (cachedData.ContainsKey(variable.VariableName)) {
        instruction.data = cachedData[variable.VariableName];
      } else {
        instruction.data = dataset.GetDoubleValues(variable.VariableName).ToArray();
        cachedData[variable.VariableName] = (double[])instruction.data;
      }
    }

    protected override void InitializeInternalInstruction(ref Instruction instruction, ISymbolicExpressionTreeNode node) {
      instruction.value = new AlgebraicDoubleVector(BATCHSIZE);
    }

    protected override void LoadVariable(Instruction a) {
      var data = (double[])a.data;
      for (int i = rowIndex; i < rows.Length && i - rowIndex < BATCHSIZE; i++) a.value[i - rowIndex] = data[rows[i]];
      a.value.Scale(a.dblVal);
    }
  }
}