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| 1 | +package network.aika.network; |
| 2 | + |
| 3 | +import network.aika.Document; |
| 4 | +import network.aika.Model; |
| 5 | +import network.aika.neuron.INeuron; |
| 6 | +import network.aika.neuron.Neuron; |
| 7 | +import network.aika.neuron.Synapse; |
| 8 | +import network.aika.neuron.range.Range; |
| 9 | +import org.junit.Assert; |
| 10 | +import org.junit.Ignore; |
| 11 | +import org.junit.Test; |
| 12 | + |
| 13 | +public class AsymmetricSuppression { |
| 14 | + |
| 15 | + |
| 16 | + @Ignore |
| 17 | + @Test |
| 18 | + public void testAsymmetricSuppression() { |
| 19 | + Model m = new Model(); |
| 20 | + |
| 21 | + Neuron inA = m.createNeuron("A"); |
| 22 | + |
| 23 | + Neuron inB = m.createNeuron("B"); |
| 24 | + |
| 25 | + Neuron outN = Neuron.init(m.createNeuron("OUT"), |
| 26 | + 0.0, |
| 27 | + INeuron.Type.EXCITATORY, |
| 28 | + new Synapse.Builder() |
| 29 | + .setSynapseId(0) |
| 30 | + .setNeuron(inA) |
| 31 | + .setWeight(10.0) |
| 32 | + .setBias(0.0) |
| 33 | + .setRecurrent(false) |
| 34 | + .setRangeOutput(Range.Output.DIRECT), |
| 35 | + new Synapse.Builder() |
| 36 | + .setSynapseId(1) |
| 37 | + .setNeuron(inB) |
| 38 | + .setWeight(-100.0) |
| 39 | + .setBias(0.0) |
| 40 | + .setRecurrent(true) |
| 41 | + .setRangeOutput(Range.Output.DIRECT) |
| 42 | + ); |
| 43 | + |
| 44 | + Document doc = m.createDocument("a"); |
| 45 | + |
| 46 | + inA.addInput(doc, 0, 1); |
| 47 | + inB.addInput(doc, 0, 1); |
| 48 | + |
| 49 | + doc.process(); |
| 50 | + |
| 51 | + System.out.println(doc.activationsToString(true, false, true)); |
| 52 | + |
| 53 | + Assert.assertTrue(outN.getActivations(doc, true).isEmpty()); |
| 54 | + |
| 55 | + doc.clearActivations(); |
| 56 | + } |
| 57 | +} |
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