public void onDeactiveZone()
{
lastActiveNeuron = 0;
active = 0;
zone.onDeactive();
}
public void HW4()
{
string dbgout = "";
DebugLog.Log("HW4 - Motor");
InputMatrix in1 = new InputMatrix(5);
SubZone sz1 = new SubZone(5);
OutputMatrix out1 = new OutputMatrix(5);
in1.setUpSubZone(sz1);
sz1.setDownSubZones(in1);
sz1.setUpSubZone(out1);
out1.setDownSubZones(sz1);
out1.addInputs(sz1);
DebugLog.Log("Learn");
bool[][] in_p2 = new bool[][] {
new bool[] { false, false, true, true, false },
new bool[] { false, false, false, true, true },
};
for (int i = 0; i < in_p2.Length; i++)
{
in1.setBooleans(in_p2[i]);
sz1.setColumnNeurons(1, in1.inputs);
}
bool[][] in_p3 = new bool[][] {
new bool[] { false, false, true, true, false },
new bool[] { false, true, true, false, false },
new bool[] { true, true, false, false, false },
};
for (int i = 0; i < in_p3.Length; i++)
{
in1.setBooleans(in_p3[i]);
sz1.setColumnNeurons(2, in1.inputs);
}
bool[][] in_p = new bool[][] {
new bool[] { false, false, false, true, false }, // _
new bool[] { false, false, true, true, false }, // 2,3
};
for (int n = 0; n < in_p.Length; n++)
{
DebugLog.Log("Analyse " + n + " pattern");
in1.setBooleans(in_p[n]);
dbgout = "";
for (int i = 0; i < in1.inputs.Length; i++)
{
dbgout += (in1.inputs[i].active > 0.8f ? "A" : "_") + " ";
}
DebugLog.Log("Pattern : " + dbgout);
in1.sendSignals();
sz1.analyze();
dbgout = "";
for (int i = 0; i < out1.inputs.Length; i++)
{
dbgout += (out1.inputsActives[i] > 0.8f ? "A" : "_") + " ";
}
DebugLog.Log("Columns : " + dbgout);
dbgout = "";
for (int i = 0; i < out1.inputs.Length; i++)
{
dbgout += (in1.inputs[i].prediction >= 0.5f ? "A" : "_") + " ";
}
DebugLog.Log("Prediction : " + dbgout);
for (int p = 0; p < 5; p++)
{
DebugLog.Log("Motor " + p + " pattern");
out1.outSignalMotor(p);
dbgout = "";
for (int i = 0; i < in1.inputs.Length; i++)
{
dbgout += (in1.getMotorValues()[i] >= 0.5f ? "A" : "_") + " ";
}
DebugLog.Log("Motor : " + dbgout);
in1.reset();
}
out1.reset();
}
sz1.onDeactive();
}
