public AnimatedReceptor(Receptor r, AnimatedNeuron n, int wall)
{
receptor = r;
neuron = n;
this.wall = wall;
radius = Constant.Radius * 2 / 3;
//0-góra, 1-lewo, 2-prawo, 3-dół
switch (wall)
{
case 0:
circle = new Circle(new PointF(n.Position.X, 0), radius);
n.Position = new PointF(n.Position.X, 2 * Constant.Radius);
break;
case 1:
circle = new Circle(new PointF(0, n.Position.Y), radius);
n.Position = new PointF(2 * Constant.Radius, n.Position.Y);
break;
case 2:
circle = new Circle(new PointF(size.Width - 1, n.Position.Y), radius);
n.Position = new PointF(2 * Constant.Radius, n.Position.Y);
break;
case 3:
circle = new Circle(new PointF(n.Position.X, size.Height - 1), radius);
n.Position = new PointF(n.Position.X, 2 * Constant.Radius);
break;
}
position = circle.Center;
}
public void addQuery(String[] words, int interval, float intensivity)
{
int index = 0;
frame = 0;
frameChanged(frame, null);
query.clear();
foreach (String word in words)
{
AnimatedNeuron an = neurons.Find(k => k.Name == word);
if (an == null)
{
continue;
}
Receptor receptor = brain.Receptors.Find(k => k.Name == word);
Synapse synapse = brain.Synapses.Find(k => k.Pre == receptor);
receptor.initialize(interval, interval - index - 1, intensivity);
new SequenceReceptor(query, receptor);
AnimatedReceptor ar = new AnimatedReceptor(receptor, an, index++ % 4);
synapses.Add(new AnimatedSynapse(ar, an, synapse));
receptors.Add(ar);
}
query.arrange();
}
public Dictionary <object, object> loadFrame(CreationFrame frame, int index)
{
Dictionary <object, object> result = new Dictionary <object, object>();
Random random = new Random();
bool added = false;
Neuron neuron = frame.Neuron.Neuron;
if (neurons.Find(k => k.Neuron == neuron) == null)
{
PointF position = randomPoint(random);
AnimatedNeuron an = new AnimatedNeuron(neuron, position);
CreatedNeuron cn = new CreatedNeuron(an);
neurons.Add(an);
result.Add(neuron, cn);
added = true;
}
else
{
result.Add(neuron, true);
}
foreach (CreationData data in frame.Data)
{
if (data.Synapse.Changes.First <CreationData>() == data)
{
AnimatedNeuron pre = neurons.Find(k => data.Synapse.Pre == k.Neuron);
AnimatedNeuron post = neurons.Find(k => data.Synapse.Post == k.Neuron);
AnimatedSynapse synapse = synapses.Find(k => pre == k.Pre && post == k.Post);
if (synapse == null)
{
AnimatedSynapse syn = new AnimatedSynapse(pre, post, data.Synapse);
CreatedSynapse cs = new CreatedSynapse(syn);
synapses.Add(syn);
result.Add(syn.Synapse, cs);
if (syn.isDuplex())
{
result.Add(syn.Duplex, cs);
}
}
else
{
synapse.setDuplex(data.Synapse);
}
}
}
if (added)
{
balance();
}
return(result);
}
public ShiftedNeuron(AnimatedNeuron neuron, PointF click, List <AnimatedNeuron> neurons)
{
this.click = click;
this.neuron = neuron;
this.neurons = neurons;
shift = new PointF();
original = new PointF(neuron.Position.X, neuron.Position.Y);
neuron.activate(true);
moved = false;
}
public AnimatedSynapse(AnimatedNeuron pre, AnimatedNeuron post, Synapse syn)
{
this.pre = pre;
this.post = post;
duplex = null;
vector = new AnimatedVector(pre, post);
synapse = new AnimatedState(syn, vector);
pre.Output.Add(this);
post.Input.Add(this);
changePosition();
}
public BalancedNeuron(AnimatedNeuron neuron)
{
this.neuron = neuron;
shift = new PointF(0, 0);
position = new PointF(neuron.Position.X, neuron.Position.Y);
input = new List <AnimatedVector>();
output = new List <AnimatedVector>();
vectors = new List <AnimatedVector>();
foreach (AnimatedSynapse synapse in neuron.Input)
{
input.Add(synapse.Vector);
}
foreach (AnimatedSynapse synapse in neuron.Output)
{
output.Add(synapse.Vector);
}
}
public CreatedNeuron(AnimatedNeuron neuron)
{
this.neuron = neuron;
created = false;
}
