public static bool Load(ref NeuronHandler theNeuronArray, string fileName)
{
FileStream file = File.Open(fileName, FileMode.Open);
XmlSerializer reader1 = new XmlSerializer(typeof(NA));//, GetModuleTypes());
aNeuronArray = (NA)reader1.Deserialize(file);
file.Close();
XmlDocument xmldoc = new XmlDocument();
XmlNodeList neuronNodes;
FileStream fs = new FileStream(fileName, FileMode.Open, FileAccess.Read);
xmldoc.Load(fs);
fs.Close();
int arraySize = aNeuronArray.arraySize;
theNeuronArray = new NeuronHandler();
theNeuronArray.Initialize(arraySize);
NeuronPartial n1 = theNeuronArray.GetPartialNeuron(1);
neuronNodes = xmldoc.GetElementsByTagName("Neuron");
for (int i = 0; i < neuronNodes.Count; i++)
{
//this is the hard way...we could parse by hand
XmlDocument tempDoc = new XmlDocument();
XmlElement neuronNode = (XmlElement)neuronNodes[i];
XmlNode importNode = tempDoc.ImportNode(neuronNode, true);
tempDoc.AppendChild(importNode);
MemoryStream stream = new MemoryStream();
tempDoc.Save(stream);
stream.Flush();
stream.Position = 0;
XmlSerializer reader = new XmlSerializer(typeof(N));
//reader.UnknownAttribute += Reader_UnknownAttribute;
//reader.UnknownElement += Reader_UnknownElement;
//reader.UnknownNode += Reader_UnknownNode;
//reader.UnreferencedObject += Reader_UnreferencedObject;
N n = (N)reader.Deserialize(stream);
if (n != null)
{
int id = n.Id;
theNeuronArray.SetNeuronCurrentCharge(id, n.CurrentCharge);
if (n.Label != "")
{
theNeuronArray.SetNeuronLabel(id, n.Label);
}
if (n.LeakRate != 0.1f)
{
theNeuronArray.SetNeuronLeakRate(id, n.LeakRate);
}
if (n.Model != modelType.Std)
{
theNeuronArray.SetNeuronModel(id, (int)n.Model);
}
foreach (S s in n.Synapses)
{
theNeuronArray.AddSynapse(id, s.TargetNeuron, s.Weight, s.IsHebbian, false);
}
}
//stream.Position = 0;
//StreamReader sr = new StreamReader(stream);
//string x = sr.ReadToEnd();
}
return(true);
}
private void Button_Click(object sender, RoutedEventArgs e)
{
int neuronCount = 1000000;
int synapsesPerNeuron = 1000;
MessageBox.Show("Starting array allocation");
theNeuronArray = new NeuronHandler();
MessageBox.Show("any existing array removed");
theNeuronArray.Initialize(neuronCount);
MessageBox.Show("array allocation complete");
int test = theNeuronArray.GetArraySize();
int threads = theNeuronArray.GetThreadCount();
theNeuronArray.SetThreadCount(16);
threads = theNeuronArray.GetThreadCount();
theNeuronArray.SetNeuronCurrentCharge(1, 1.4f);
theNeuronArray.SetNeuronCurrentCharge(2, 0.9f);
theNeuronArray.Fire(); //should transfer current chargest to last
float a = theNeuronArray.GetNeuronLastCharge(1);
float b = theNeuronArray.GetNeuronLastCharge(2);
string s0 = theNeuronArray.GetNeuronLabel(1);
theNeuronArray.SetNeuronLabel(1, "Fred");
string s1 = theNeuronArray.GetNeuronLabel(1);
theNeuronArray.SetNeuronLabel(1, "George");
string s2 = theNeuronArray.GetNeuronLabel(1);
theNeuronArray.AddSynapse(2, 4, .75f, 1, false);
List <Synapse> synapses2 = theNeuronArray.GetSynapsesList(2);
theNeuronArray.AddSynapse(1, 2, .5f, 0, false);
List <Synapse> synapses1 = theNeuronArray.GetSynapsesList(1);
theNeuronArray.AddSynapse(1, 3, .6f, 0, false);
synapses1 = theNeuronArray.GetSynapsesList(1);
theNeuronArray.AddSynapse(1, 4, .75f, 1, false);
synapses1 = theNeuronArray.GetSynapsesList(1);
theNeuronArray.AddSynapse(2, 4, .75f, 1, false);
long count = theNeuronArray.GetTotalSynapses();
List <Synapse> synapses0 = theNeuronArray.GetSynapsesList(0);
synapses1 = theNeuronArray.GetSynapsesList(1);
List <Synapse> synapsesFrom = theNeuronArray.GetSynapsesFromList(4);
NeuronPartial n = theNeuronArray.GetPartialNeuron(1);
theNeuronArray.Fire();
long gen = theNeuronArray.GetGeneration();
NeuronPartial n1 = theNeuronArray.GetPartialNeuron(1);
NeuronPartial n2 = theNeuronArray.GetPartialNeuron(2);
NeuronPartial n3 = theNeuronArray.GetPartialNeuron(3);
theNeuronArray.DeleteSynapse(1, 3);
theNeuronArray.DeleteSynapse(1, 2);
MessageBox.Show("allocating synapses");
Parallel.For(0, neuronCount, x =>
{
//for (int x = 0; x < neuronCount; x++)
//{
for (int j = 0; j < synapsesPerNeuron; j++)
{
int target = x + j;
if (target >= theNeuronArray.GetArraySize())
{
target -= theNeuronArray.GetArraySize();
}
if (target < 0)
{
target += theNeuronArray.GetArraySize();
}
theNeuronArray.AddSynapse(x, target, 1.0f, 0, true);
}
});
for (int i = 0; i < neuronCount / 100; i++)
{
theNeuronArray.SetNeuronCurrentCharge(100 * i, 1);
}
MessageBox.Show("synapses and charge complete");
Stopwatch sw = new Stopwatch();
string msg = "";
for (int i = 0; i < 10; i++)
{
sw.Start();
theNeuronArray.Fire();
sw.Stop();
msg += "Gen: " + theNeuronArray.GetGeneration() + " FireCount: " + theNeuronArray.GetFiredCount() + " time: " + sw.Elapsed.Milliseconds.ToString() + "\n";
sw.Reset();
}
sw.Stop();
MessageBox.Show("Done firing 10x\n" + msg);
}
public static bool Save(ref NeuronHandler theNeuronArray, string fileName)
{
string tempFile = System.IO.Path.GetTempFileName();
FileStream file = File.Create(tempFile);
XmlSerializer writer = new XmlSerializer(typeof(NA));//, GetModuleTypes());
writer.Serialize(file, aNeuronArray);
file.Position = 0;;
XmlDocument xmldoc = new XmlDocument();
xmldoc.Load(file);
XmlElement root = xmldoc.DocumentElement;
XmlNode neuronsNode = xmldoc.CreateNode("element", "Neurons", "");
root.AppendChild(neuronsNode);
for (int i = 0; i < theNeuronArray.GetArraySize(); i++)
{
NeuronPartial n = theNeuronArray.GetPartialNeuron(i);
if (n.inUse && n.id != 0)
{
string label = theNeuronArray.GetNeuronLabel(n.id);
List <Synapse> theSynapses = theNeuronArray.GetSynapsesList(i);
//this is needed bacause inUse is true if any synapse points to this neuron--we don't need to bother with
if (theSynapses.Count != 0 || label != "" || n.lastCharge != 0 || n.leakRate != 0.1f ||
n.model != modelType.Std)
{
XmlNode neuronNode = xmldoc.CreateNode("element", "Neuron", "");
neuronsNode.AppendChild(neuronNode);
XmlNode attrNode = xmldoc.CreateNode("element", "Id", "");
attrNode.InnerText = n.id.ToString();
neuronNode.AppendChild(attrNode);
if (n.lastCharge != 0)
{
attrNode = xmldoc.CreateNode("element", "LastCharge", "");
attrNode.InnerText = n.lastCharge.ToString();
neuronNode.AppendChild(attrNode);
}
if (n.leakRate != 0.1f)
{
attrNode = xmldoc.CreateNode("element", "LeakRate", "");
attrNode.InnerText = n.leakRate.ToString();
neuronNode.AppendChild(attrNode);
}
if (n.model != modelType.Std)
{
attrNode = xmldoc.CreateNode("element", "Model", "");
attrNode.InnerText = n.model.ToString();
neuronNode.AppendChild(attrNode);
}
if (label != "")
{
attrNode = xmldoc.CreateNode("element", "Label", "");
attrNode.InnerText = label;
neuronNode.AppendChild(attrNode);
}
if (theSynapses.Count > 0)
{
XmlNode synapsesNode = xmldoc.CreateNode("element", "Synapses", "");
neuronNode.AppendChild(synapsesNode);
foreach (Synapse s in theSynapses)
{
XmlNode synapseNode = xmldoc.CreateNode("element", "Synapse", "");
synapsesNode.AppendChild(synapseNode);
if (s.weight != 1)
{
attrNode = xmldoc.CreateNode("element", "Weight", "");
attrNode.InnerText = s.weight.ToString();
synapseNode.AppendChild(attrNode);
}
attrNode = xmldoc.CreateNode("element", "TargetNeuron", "");
attrNode.InnerText = s.target.ToString();
synapseNode.AppendChild(attrNode);
if (s.isHebbian)
{
attrNode = xmldoc.CreateNode("element", "IsHebbian", "");
attrNode.InnerText = "true";
synapseNode.AppendChild(attrNode);
}
}
}
}
}
}
file.Position = 0;
xmldoc.Save(file);
file.Close();
File.Copy(tempFile, fileName, true);
File.Delete(tempFile);
return(true);
}
