Masterarbeit/TF/Main.scala

import breeze.stats.distributions.Uniform
import breeze.stats.distributions.Gaussian
import scala.language.postfixOps

object Activation {
  def apply(x: Double): Double = math.max(0, x)

  def d(x: Double): Double = if (x > 0) 1 else 0
}

class RSNN(val n: Int, val gamma: Double = 0.001) {
  val g = Uniform(-10, 10)
  val g_1 = Uniform(-5, 5)//scala.math.exp(1))
  val g_3 = Gaussian(0, 5)

  val xis = g.sample(n)
  val vs = g_3.sample(n)
  val bs = xis zip vs map {case(xi, v) => xi * v}
  //val vs = g_1.sample(n)
  //val bs = g.sample(n)

  def computeL1(x: Double) = (bs zip vs) map { case (b, v) => Activation(b + v * x) }

  def computeL2(l1: Seq[Double], ws: Seq[Double]): Double =
    (l1 zip ws) map { case (l, w) => w * l } sum

  def output(ws: Seq[Double])(x: Double): Double = computeL2(computeL1(x), ws)

  def learn(data: Seq[(Double, Double)], ws: Seq[Double], lambda: Double, gamma: Double): Seq[Double] = {
    // data: N \times 2
    // ws: n \times 1

    lazy val deltas = data.map {
      case (x, y) =>
        val l1 = computeL1(x) // n
        val out = computeL2(l1, ws) // 1
        (l1 zip ws) map {case (l1, w) => (l1 * 2 * (out - y) + lambda * 2 * w)  * gamma * -1} // n
    }
    // deltas: N × n

    deltas.foldRight(ws)(
      (delta, ws) => // delta: n
        ws zip (delta) map { case (w, d) => w + d } // n
    )// map (w => w - lambda * gamma * 2 * w)

  }

  def train(data: Seq[(Double, Double)], iter: Int, lambda: Double, gamma: Double = gamma): (Seq[Double], Double => Double)= {
    val ws = (1 to iter).foldRight((1 to n).map(_ => 0.0) :Seq[Double])((i, w) => {
      println(s"Training iteration $i")
      println(w.sum/w.length)
      learn(data, w, lambda, gamma / 10)
    })
    (ws, output(ws))
  }
}

object Main {

  def main(args: Array[String]): Unit = {
    val nn = new RSNN(10, gamma = 0.0001)
    val data = (1 to 100) map (_ * 0.01) map (t => (t, math.sin(t)))
    val (ws, evaluate) = nn.train(data, iter = 1000, lambda = 0.8)

    val results = data.map(_._1).map(evaluate(_))
    data zip results foreach {
      println(_)
    }
  }

}

object EqSeq {
  def apply(left: Double, right: Double, steps: Int): Seq[Double] =
    (0 to steps) map (_ * (right - left) / steps + left)
}