public Probe(Neuron neuron, int width, Color color, int vOffset)
{
buffer = new List<int>();
this.width = width;
this.Neuron = neuron;
this.vOffset = vOffset;
dataPen = new Pen(color);
}
protected void UpdateStudyPlot(DataTable dt)
{
rowNeuronMap.Clear();
studyNeuronPlots.Clear();
pnlScope.ClearProbes();
probeColorIdx = 0;
foreach (DataRow row in dt.Rows)
{
Neuron n = new Neuron();
rowNeuronMap[row] = n;
for (int colIdx = 1; colIdx <= 7; ++colIdx)
{
UpdateNeuronProperty(n, row, colIdx);
}
n.Leakage = row["LKG"].ToString().ToPotential();
pnlScope.AddProbe(n, probeColors[probeColorIdx]);
NeuronPlot np = new NeuronPlot() { Neuron = n, Location = new Point(20 + probeColorIdx * 30, pnlNetwork.Height / 2) };
if (row["Location"] != DBNull.Value)
{
string pos = row["Location"].ToString();
np.Location = new Point(pos.Between('=', ',').to_i(), pos.RightOf(',').Between('=', '}').to_i());
}
studyNeuronPlots.Add(np);
probeColorIdx = (probeColorIdx + 1) % probeColors.Length;
}
pnlNetwork.SetPlots(studyNeuronPlots);
pnlNetwork.Tick();
}
private void UpdateConnections(Neuron n, string val)
{
string[] connections = val.Split(',');
n.Connections.Clear();
foreach (string conn in connections)
{
int nidx = conn.LeftOf('(').to_i();
int psap = conn.Between('(', ')').to_i() << 8;
Neuron targetNeuron = rowNeuronMap[dvStudy[nidx - 1].Row];
n.AddConnection(new Connection(targetNeuron, psap));
}
}
private void UpdateProperty(Neuron n, string propName, string newVal)
{
Type t = n.Config.GetType();
object obj = n.Config;
PropertyInfo pi = t.GetProperty(propName, BindingFlags.Public | BindingFlags.Instance);
pi.SetValue(obj, newVal.ToPotential());
}
protected void UpdateNeuronProperty(Neuron n, DataRow row, int colIdx)
{
string[] colProps = new string[]
{
"RestingPotential",
"ActionPotentialThreshold",
"ActionPotentialValue",
"RefractoryRecoveryRate",
"HyperPolarizationOvershoot",
"RestingPotentialReturnRate",
};
string newVal = row[colIdx].ToString();
switch (colIdx)
{
case 0: // row index is not allowed to be changed
break;
case 1:
case 2:
case 3:
case 4:
case 5:
case 6:
UpdateProperty(n, colProps[colIdx - 1], newVal);
break;
case 7: // Leakage
n.Leakage = newVal.ToPotential();
break;
case 8: // probe color
break;
case 9: // connections
UpdateConnections(n, newVal);
break;
case 10: // we don't support updating locations -- this should be a hidden column
break;
}
}
protected void AddNeuron(Neuron n, DataTable dt, NeuronConfig cfg)
{
DataRow row = dt.NewRow();
row["n"] = dt.Rows.Count + 1;
row["RP"] = cfg.RestingPotential.ToDisplayValue();
row["APT"] = cfg.ActionPotentialThreshold.ToDisplayValue();
row["APV"] = cfg.ActionPotentialValue.ToDisplayValue();
row["RRR"] = cfg.RefractoryRecoveryRate.ToDisplayValue();
row["HPO"] = cfg.HyperPolarizationOvershoot.ToDisplayValue();
row["RPRR"] = cfg.RestingPotentialReturnRate.ToDisplayValue();
row["LKG"] = "0";
row["PCOLOR"] = probeColors[probeColorIdx];
row["Location"] = new Point(20 + probeColorIdx * 30, pnlNetwork.Height / 2);
dt.Rows.Add(row);
rowNeuronMap[row] = n;
}
/// <summary>
/// Add a study neuron using the default neuron config.
/// </summary>
private void btnAddNeuron_Click(object sender, EventArgs e)
{
Neuron n = new Neuron();
AddNeuron(n, dtStudy, NeuronConfig.DefaultConfiguration);
pnlScope.AddProbe(n, probeColors[probeColorIdx]);
studyNeuronPlots.Add(new NeuronPlot() { Neuron = n, Location = new Point(20 + probeColorIdx * 30, pnlNetwork.Height / 2) });
probeColorIdx = (probeColorIdx + 1) % probeColors.Length;
pnlNetwork.SetPlots(studyNeuronPlots);
pnlNetwork.Tick();
}
protected void CreateNetwork()
{
Cursor = Cursors.WaitCursor;
networkNeuronPlots = new List<NeuronPlot>();
int mx = pnlNetwork.Width / 4;
int my = pnlNetwork.Height / 4;
int c = NetworkConfig.DefaultConfiguration.NumConnections; // # of connections each neuron makes
int d = NetworkConfig.DefaultConfiguration.MaxDistance; // max distance of each connection. Must be multiple of 2
int r = NetworkConfig.DefaultConfiguration.Radius; // radius (as a square) of connections. Must be multiple of 2
int p = NetworkConfig.DefaultConfiguration.Pacemakers; // # of pacemaker neurons
// Initialize an mx x my array of neurons. The edges wrap top-bottom / left-right.
for (int x = 0; x < mx; x++)
{
for (int y = 0; y < my; y++)
{
Neuron n = new Neuron();
networkNeuronPlots.Add(new NeuronPlot() { Neuron = n, Location = new Point(x * 4, y * 4) });
}
}
// Each neuron connects to c other neurons in a localized r x r region at a maximum distance of d from the originating neuron.
foreach (NeuronPlot np in networkNeuronPlots)
{
int x = np.Location.X / 4;
int y = np.Location.Y / 4;
// Note: rnd.Next(min,max) is inclusive of the lower bound and exclusive of the upper bound.
// To avoid introducing bias, we add 1 to the upper bound.
// Target location:
int targetx = x + rnd.Next(-d / 2, (d / 2) + 1);
int targety = y + rnd.Next(-d / 2, (d / 2) + 1);
for (int i = 0; i < c; i++)
{
// Connection location around the target.
int adjx = targetx + rnd.Next(-r / 2, (r / 2) + 1);
int adjy = targety + rnd.Next(-r / 2, (r / 2) + 1);
if (adjx < 0) adjx += mx;
if (adjy < 0) adjy += my;
int qx = adjx % mx;
int qy = adjy % my;
// Find the neuron at this location
NeuronPlot npTarget = networkNeuronPlots.Single(np2 => np2.Location.X == qx * 4 & np2.Location.Y == qy * 4);
np.Neuron.AddConnection(new Connection(npTarget.Neuron));
}
}
// Pick p neurons to be pacemakers at different rates.
for (int i = 0; i < p; i++)
{
Neuron n = networkNeuronPlots[rnd.Next(mx * my)].Neuron;
// You get more interesting patterns when the leakage is randomized so that pacemaker neurons do not all
// fire synchronously.
n.Leakage = 256 + rnd.Next(256);
/*
if (i == 0)
{
pnlScope.AddProbe(n, Color.LightBlue);
// Pick the first connecting neuron for a second trace.
pnlScope.AddProbe(n.Connections[0].Neuron, Color.Red);
}
*/
Cursor = Cursors.Arrow;
}
pnlNetwork.SetPlots(networkNeuronPlots);
/*
pacemakerNeuron = new Neuron();
pacemakerNeuron.Leakage = 2 << 8;
pacemakerNeuron.Integration = 0;
receiverNeuron = new Neuron();
pacemakerNeuron.AddConnection(new Connection(receiverNeuron));
neuronPlots.Add(new NeuronPlot() { Neuron = pacemakerNeuron, Location = new Point(pnlNetwork.Width / 2, pnlNetwork.Height / 2) });
neuronPlots.Add(new NeuronPlot() { Neuron = receiverNeuron, Location = new Point(pnlNetwork.Width / 2 + 20, pnlNetwork.Height / 2) });
pnlScope.AddProbe(pacemakerNeuron, Color.LightBlue);
pnlScope.AddProbe(receiverNeuron, Color.Red);
*/
}
public Connection(Neuron targetNeuron, int psap = 20<<8)
{
Neuron = targetNeuron;
postSynapticActionPotential = psap;
}
public void RemoveProbe(Neuron n)
{
probes.Remove(probes.Single(p => p.Neuron == n));
}
public void AddProbe(Neuron n, Color color)
{
probes.Add(new Probe(n, Width, color, vOffset));
}
public void RemoveProbe(Neuron n)
{
probes.Remove(probes.Single(p => p.Neuron == n));
}
public void AddProbe(Neuron n, Color color)
{
probes.Add(new Probe(n, Width, color, vOffset));
}
protected void CreateNetwork()
{
Cursor = Cursors.WaitCursor;
networkNeuronPlots = new List <NeuronPlot>();
int mx = pnlNetwork.Width / 4;
int my = pnlNetwork.Height / 4;
int c = NetworkConfig.DefaultConfiguration.NumConnections; // # of connections each neuron makes
int d = NetworkConfig.DefaultConfiguration.MaxDistance; // max distance of each connection. Must be multiple of 2
int r = NetworkConfig.DefaultConfiguration.Radius; // radius (as a square) of connections. Must be multiple of 2
int p = NetworkConfig.DefaultConfiguration.Pacemakers; // # of pacemaker neurons
// Initialize an mx x my array of neurons. The edges wrap top-bottom / left-right.
for (int x = 0; x < mx; x++)
{
for (int y = 0; y < my; y++)
{
Neuron n = new Neuron();
networkNeuronPlots.Add(new NeuronPlot()
{
Neuron = n, Location = new Point(x * 4, y * 4)
});
}
}
// Each neuron connects to c other neurons in a localized r x r region at a maximum distance of d from the originating neuron.
foreach (NeuronPlot np in networkNeuronPlots)
{
int x = np.Location.X / 4;
int y = np.Location.Y / 4;
// Note: rnd.Next(min,max) is inclusive of the lower bound and exclusive of the upper bound.
// To avoid introducing bias, we add 1 to the upper bound.
// Target location:
int targetx = x + rnd.Next(-d / 2, (d / 2) + 1);
int targety = y + rnd.Next(-d / 2, (d / 2) + 1);
for (int i = 0; i < c; i++)
{
// Connection location around the target.
int adjx = targetx + rnd.Next(-r / 2, (r / 2) + 1);
int adjy = targety + rnd.Next(-r / 2, (r / 2) + 1);
if (adjx < 0)
{
adjx += mx;
}
if (adjy < 0)
{
adjy += my;
}
int qx = adjx % mx;
int qy = adjy % my;
// Find the neuron at this location
NeuronPlot npTarget = networkNeuronPlots.Single(np2 => np2.Location.X == qx * 4 & np2.Location.Y == qy * 4);
np.Neuron.AddConnection(new Connection(npTarget.Neuron));
}
}
// Pick p neurons to be pacemakers at different rates.
for (int i = 0; i < p; i++)
{
Neuron n = networkNeuronPlots[rnd.Next(mx * my)].Neuron;
// You get more interesting patterns when the leakage is randomized so that pacemaker neurons do not all
// fire synchronously.
n.Leakage = 256 + rnd.Next(256);
/*
* if (i == 0)
* {
* pnlScope.AddProbe(n, Color.LightBlue);
* // Pick the first connecting neuron for a second trace.
* pnlScope.AddProbe(n.Connections[0].Neuron, Color.Red);
* }
*/
Cursor = Cursors.Arrow;
}
pnlNetwork.SetPlots(networkNeuronPlots);
/*
* pacemakerNeuron = new Neuron();
* pacemakerNeuron.Leakage = 2 << 8;
* pacemakerNeuron.Integration = 0;
*
* receiverNeuron = new Neuron();
*
* pacemakerNeuron.AddConnection(new Connection(receiverNeuron));
*
* neuronPlots.Add(new NeuronPlot() { Neuron = pacemakerNeuron, Location = new Point(pnlNetwork.Width / 2, pnlNetwork.Height / 2) });
* neuronPlots.Add(new NeuronPlot() { Neuron = receiverNeuron, Location = new Point(pnlNetwork.Width / 2 + 20, pnlNetwork.Height / 2) });
*
* pnlScope.AddProbe(pacemakerNeuron, Color.LightBlue);
* pnlScope.AddProbe(receiverNeuron, Color.Red);
*/
}
public void Fire()
{
Neuron.PostSynapticAction(postSynapticActionPotential);
}
public Connection(Neuron targetNeuron, int psap = 20 << 8)
{
Neuron = targetNeuron;
postSynapticActionPotential = psap;
}
