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Add minimizeModel to orx-gradient-descent

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This commit is contained in:
Edwin Jakobs
2019-09-24 20:07:54 +02:00
parent c49f14fd54
commit d7eadc172c
3 changed files with 84 additions and 5 deletions
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19
orx-gradient-descent/src/main/kotlin/GradientDescent.kt
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@@ -96,7 +96,7 @@ fun dot(x: Array<DoubleArray>, y: DoubleArray): DoubleArray = DoubleArray(x.size
class MinimizationResult(val solution: DoubleArray, val value: Double, val gradient: DoubleArray,
val inverseHessian: Array<DoubleArray>, val iterations: Int)
fun minimize(_x0: DoubleArray, endOnLineSearch: Boolean = true, tol: Double = 1e-8, maxIterations: Int = 1000, f: (DoubleArray) -> Double): MinimizationResult {
fun minimize(_x0: DoubleArray, endOnLineSearch: Boolean = false, tol: Double = 1e-8, maxIterations: Int = 1000, f: (DoubleArray) -> Double): MinimizationResult {
val grad = { a: DoubleArray -> gradient(a, f) }
var x0 = _x0.copyOf()
var g0 = grad(x0)
@@ -108,8 +108,8 @@ fun minimize(_x0: DoubleArray, endOnLineSearch: Boolean = true, tol: Double = 1e
while (iteration < maxIterations) {
require(g0.all { it == it && it != Double.POSITIVE_INFINITY && it != Double.NEGATIVE_INFINITY })
val pstep = dot(H1, g0)
require(pstep.all { it == it }) { "pstep contains NaNs"}
require(pstep.all { it != Double.POSITIVE_INFINITY && it != Double.NEGATIVE_INFINITY }) { "pstep contains infs" }
require(pstep.all { it == it }) { "pstep contains NaNs" }
require(pstep.all { it != Double.POSITIVE_INFINITY && it != Double.NEGATIVE_INFINITY }) { "pstep contains infs" }
val step = neg(pstep)
val nstep = norm2(step)
@@ -127,7 +127,7 @@ fun minimize(_x0: DoubleArray, endOnLineSearch: Boolean = true, tol: Double = 1e
x1 = add(x0, s)
f1 = f(x1)
require(f1 == f1) { "f1 is NaN"}
require(f1 == f1) { "f1 is NaN" }
if (!(f1 - f0 >= 0.1 * t * df0)) {
break
}
@@ -144,7 +144,7 @@ fun minimize(_x0: DoubleArray, endOnLineSearch: Boolean = true, tol: Double = 1e
require(g1.all { it == it })
val y = sub(g1, g0)
val ys = dot(y, s)
if (ys==0.0) {
if (ys == 0.0) {
break
}
val Hy = dot(H1, y)
@@ -172,3 +172,12 @@ fun minimize(_x0: DoubleArray, endOnLineSearch: Boolean = true, tol: Double = 1e
return MinimizationResult(x0, f0, g0, H1, iteration)
}
fun <T : Any> minimizeModel(model: T, endOnLineSearch: Boolean = false, tol: Double = 1e-8, maxIterations: Int = 1000, function: (T) -> Double) {
val doubles = modelToArray(model)
val solution = minimize(doubles, endOnLineSearch, tol, maxIterations) {
arrayToModel(it, model)
function(model)
}
arrayToModel(solution.solution, model)
}