package app.predict;import ga.*;import gep.num.*;/** * 直接預(yù)測的評價器 */public class DirectPredictEvaluator implements Evaluator{	private NFitness fitnessFunction;	// 適應(yīng)度函數(shù)	private double[][] parameters;		// 訓(xùn)練數(shù)據(jù)的參數(shù)		private int size;					// 數(shù)據(jù)集的大小	private int history;				// 歷史長度	private int future;					// 未來長度		private double[] values;			// 臨時變量	private double[] buffer;			//		public DirectPredictEvaluator(Fitness fitnessFunction, NDataSet dataSet)	{		this.fitnessFunction = (NFitness) fitnessFunction;		this.parameters = dataSet.getParameters();		this.size = parameters.length;		this.history = parameters[0].length;				double[] targets = dataSet.getTargets();		future = targets.length / size;				values = new double[size*future];		buffer = new double[history];	}	public double evaluate(Protein protein)	{		NEvaluable evaluable = (NEvaluable) protein;		// 計算每一個樣本的值		try		{			int s = 0;			for (int i=0; i<size; i++)			{				for (int j=0; j<history; j++)				{					buffer[j] = parameters[i][j];				}					for (int j=0; j<future; j++)				{								double value = evaluable.evaluate(buffer);										// 利用剛剛計算出來的值進(jìn)行下一步預(yù)測					for (int k=1; k<history; k++)					{						buffer[k-1] = buffer[k];					}					buffer[history-1] = value; 										values[s++] = value;				}			}		}		catch (Exception e)		{			return fitnessFunction.getMinFitness();		}				// 計算適應(yīng)度		double f = fitnessFunction.calculate(values);		// TODO 測試"世界簡單性原理"//		if (false) f += 1/((Formula) protein).getComplex();				return f;	}		public String toString()	{		return getClass().getName();	}}