Provides basic functions that many of the persistors will need.
상속: IPersistor
        /// <summary>
        /// Save the specified Encog object to an XML writer.
        /// </summary>
        /// <param name="obj">The object to save.</param>
        /// <param name="xmlOut">The XML writer to save to.</param>
        public void Save(IEncogPersistedObject obj, WriteXML xmlOut)
        {
            PersistorUtil.BeginEncogObject(
                EncogPersistedCollection.TYPE_CONTEXT_LAYER, xmlOut, obj, false);
            ContextLayer layer = (ContextLayer)obj;

            xmlOut.AddProperty(BasicLayerPersistor.PROPERTY_NEURONS, layer
                               .NeuronCount);
            xmlOut.AddProperty(BasicLayerPersistor.PROPERTY_X, layer.X);
            xmlOut.AddProperty(BasicLayerPersistor.PROPERTY_Y, layer.Y);

            if (layer.HasBias)
            {
                StringBuilder result = new StringBuilder();
                NumberList.ToList(CSVFormat.EG_FORMAT, result, layer.BiasWeights);
                xmlOut.AddProperty(BasicLayerPersistor.PROPERTY_THRESHOLD, result
                                   .ToString());
            }

            StringBuilder ctx = new StringBuilder();

            NumberList.ToList(CSVFormat.EG_FORMAT, ctx, layer.Context.Data);
            xmlOut.AddProperty(PROPERTY_CONTEXT, ctx.ToString());


            xmlOut.AddProperty(BasicLayerPersistor.PROPERTY_BIAS_ACTIVATION, layer.BiasActivation);
            BasicLayerPersistor.SaveActivationFunction(layer.ActivationFunction, xmlOut);

            xmlOut.EndTag();
        }
        /// <summary>
        /// Load the specified Encog object from an XML reader.
        /// </summary>
        /// <param name="xmlIn">The XML reader to use.</param>
        /// <returns>The loaded object.</returns>
        public IEncogPersistedObject Load(ReadXML xmlIn)
        {
            int    neuronCount             = 0;
            int    x                       = 0;
            int    y                       = 0;
            double biasActivation          = 1;
            String threshold               = null;
            IActivationFunction activation = null;
            String end                     = xmlIn.LastTag.Name;
            String context                 = null;

            while (xmlIn.ReadToTag())
            {
                if (xmlIn.IsIt(BasicLayerPersistor.TAG_ACTIVATION, true))
                {
                    xmlIn.ReadToTag();
                    String type = xmlIn.LastTag.Name;
                    activation = BasicLayerPersistor.LoadActivation(type, xmlIn);
                }
                else if (xmlIn.IsIt(BasicLayerPersistor.PROPERTY_NEURONS, true))
                {
                    neuronCount = xmlIn.ReadIntToTag();
                }
                else if (xmlIn.IsIt(BasicLayerPersistor.PROPERTY_X, true))
                {
                    x = xmlIn.ReadIntToTag();
                }
                else if (xmlIn.IsIt(BasicLayerPersistor.PROPERTY_Y, true))
                {
                    y = xmlIn.ReadIntToTag();
                }
                else if (xmlIn.IsIt(BasicLayerPersistor.PROPERTY_THRESHOLD, true))
                {
                    threshold = xmlIn.ReadTextToTag();
                }
                else if (xmlIn.IsIt(PROPERTY_CONTEXT, true))
                {
                    context = xmlIn.ReadTextToTag();
                }
                else if (xmlIn.IsIt(BasicLayerPersistor.PROPERTY_BIAS_ACTIVATION, true))
                {
                    biasActivation = double.Parse(xmlIn.ReadTextToTag());
                }
                else if (xmlIn.IsIt(end, false))
                {
                    break;
                }
            }

            if (neuronCount > 0)
            {
                ContextLayer layer;

                if (threshold == null)
                {
                    layer = new ContextLayer(activation, false, neuronCount);
                }
                else
                {
                    double[] t = NumberList.FromList(CSVFormat.EG_FORMAT, threshold);
                    layer = new ContextLayer(activation, true, neuronCount);
                    for (int i = 0; i < t.Length; i++)
                    {
                        layer.BiasWeights[i] = t[i];
                    }
                }

                if (context != null)
                {
                    double[] c = NumberList.FromList(CSVFormat.EG_FORMAT, context);

                    for (int i = 0; i < c.Length; i++)
                    {
                        layer.Context[i] = c[i];
                    }
                }

                layer.X = x;
                layer.Y = y;
                layer.BiasActivation = biasActivation;

                return(layer);
            }
            return(null);
        }