Ejemplo n.º 1
0
        private static BlackBoxProbe CreateBlackBoxProbe(IFunction fn, ParamSamplingInfo paramSamplingInfo)
        {
            // Determine the mid output value of the function (over the specified sample points) and a scaling factor
            // to apply the to neural network response for it to be able to recreate the function (because the neural net
            // output range is [0,1] when using the logistic function as the neuron activation function).
            FnRegressionUtils.CalcFunctionMidAndScale(fn, paramSamplingInfo, out double mid, out double scale);

            var blackBoxProbe = new BlackBoxProbe(paramSamplingInfo, mid, scale);

            return(blackBoxProbe);
        }
Ejemplo n.º 2
0
        /// <summary>
        /// Constructs with the details of the function regression problem to be visualized.
        /// </summary>
        /// <param name="fn">The function being regressed.</param>
        /// <param name="generativeMode">Indicates that blackbox has no inputs; it will generate a waveform as a function of time.</param>
        /// <param name="paramSamplingInfo">Parameter sampling info.</param>
        /// <param name="genomeDecoder">Genome decoder.</param>
        public FnRegressionView2D(IFunction fn, ParamSamplingInfo paramSamplingInfo, bool generativeMode, IGenomeDecoder <NeatGenome, IBlackBox> genomeDecoder)
        {
            InitializeComponent();
            InitGraph(string.Empty, string.Empty, string.Empty);

            _fn = fn;
            _paramSamplingInfo = paramSamplingInfo;
            _generativeMode    = generativeMode;
            _genomeDecoder     = genomeDecoder;

            // Determine the mid output value of the function (over the specified sample points) and a scaling factor
            // to apply the to neural network response for it to be able to recreate the function (because the neural net
            // output range is [0,1] when using the logistic function as the neuron activation function).
            double mid, scale;

            FnRegressionUtils.CalcFunctionMidAndScale(fn, paramSamplingInfo, out mid, out scale);
            if (generativeMode)
            {
                _blackBoxProbe = new GenerativeBlackBoxProbe(paramSamplingInfo, mid, scale);
            }
            else
            {
                _blackBoxProbe = new BlackBoxProbe(paramSamplingInfo, mid, scale);
            }

            _yArrTarget = new double[paramSamplingInfo._sampleCount];

            // Pre-build plot point objects.
            _plotPointListTarget   = new PointPairList();
            _plotPointListResponse = new PointPairList();

            double[] xArr = paramSamplingInfo._xArr;
            for (int i = 0; i < xArr.Length; i++)
            {
                double x = xArr[i];
                _plotPointListTarget.Add(x, _fn.GetValue(x));
                _plotPointListResponse.Add(x, 0.0);
            }

            // Bind plot points to graph.
            zed.GraphPane.AddCurve("Target", _plotPointListTarget, Color.Black, SymbolType.None);
            zed.GraphPane.AddCurve("Network Response", _plotPointListResponse, Color.Red, SymbolType.None);
        }