[orx-gradient-descent] convert to MPP

orx-gradient-descent/src/commonMain/kotlin/GradientDescent.kt

@@ -175,12 +175,3 @@ fun minimize(_x0: DoubleArray,
     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 weights = DoubleArray(doubles.size) { 1.0 }
-    val solution = minimize(doubles, weights, endOnLineSearch, tol, maxIterations) {
-        arrayToModel(it, model)
-        function(model)
-    }
-    arrayToModel(solution.solution, model)
-}

orx-gradient-descent/src/jvmMain/kotlin/GradientDescent.kt

@@ -0,0 +1,12 @@
+@file:JvmName("GradientDescentJvmKt")
+package org.openrndr.extra.gradientdescent
+
+fun <T : Any> minimizeModel(model: T, endOnLineSearch: Boolean = false, tol: Double = 1e-8, maxIterations: Int = 1000, function: (T) -> Double) {
+    val doubles = modelToArray(model)
+    val weights = DoubleArray(doubles.size) { 1.0 }
+    val solution = minimize(doubles, weights, endOnLineSearch, tol, maxIterations) {
+        arrayToModel(it, model)
+        function(model)
+    }
+    arrayToModel(solution.solution, model)
+}