Zmiany

package next

import org.apache.commons.math3.linear.Array2DRowRealMatrix
import org.apache.commons.math3.linear.RealMatrix
import java.util.*

class Network(private val size: Int) {

    private var stableCount = 10000
    var neurons: Array<Neuron> = Array(size, { _ -> Neuron(size) })
    private val random = Random()

    fun learn(examples: Array<DoubleArray>) {
        var example: RealMatrix
        var result: RealMatrix = Array2DRowRealMatrix(size, size)

        for (e in examples) {
            example = Array2DRowRealMatrix(e)
            result = result.add(example.multiply(example.transpose()))
        }
        println("Learning done")

        for ( (i,row) in result.data.withIndex()) {
            neurons[i].weights = row
        }
    }


    fun recognizeImage(image: DoubleArray): Array<Boolean> {

        var correctCounter = 0

        for (i in 0 until size) {
            neurons[i].spin = image[i]
        }

        while (correctCounter < stableCount) {
            val randomNeuron = random.nextInt(size - 1)
            val spins = neurons.map({ i -> i.spin })
            correctCounter++
            if (neurons[randomNeuron].updateSpin(spins)) {
                correctCounter = 0
            }
        }

        return neurons.map { i -> i.spin == 1.0 }.toTypedArray()
    }
}