Merge branch 'dev' into feature/advanced-optimization

# Conflicts:
#	kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/CMOptimization.kt
#	kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/cmFit.kt
#	kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/DifferentiableExpression.kt
#	kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/FunctionOptimization.kt
#	kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/XYFit.kt

CHANGELOG.md

@@ -45,6 +45,7 @@
 - MSTExpression
 - Expression algebra builders
 - Complex and Quaternion no longer are elements.
+- Second generic from DifferentiableExpression
 
 ### Fixed
 - Ring inherits RingOperations, not GroupOperations

kmath-commons/src/main/kotlin/space/kscience/kmath/commons/expressions/DerivativeStructureExpression.kt

@@ -106,7 +106,7 @@ public class DerivativeStructureField(
 
     public companion object :
         AutoDiffProcessor<Double, DerivativeStructure, DerivativeStructureField, Expression<Double>> {
-        public override fun process(function: DerivativeStructureField.() -> DerivativeStructure): DifferentiableExpression<Double, Expression<Double>> =
+        public override fun process(function: DerivativeStructureField.() -> DerivativeStructure): DifferentiableExpression<Double> =
             DerivativeStructureExpression(function)
     }
 }
@@ -116,7 +116,7 @@ public class DerivativeStructureField(
  */
 public class DerivativeStructureExpression(
     public val function: DerivativeStructureField.() -> DerivativeStructure,
-) : DifferentiableExpression<Double, Expression<Double>> {
+) : DifferentiableExpression<Double> {
     public override operator fun invoke(arguments: Map<Symbol, Double>): Double =
         DerivativeStructureField(0, arguments).function().value
 

kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/CMOptimization.kt

@@ -15,6 +15,7 @@ import space.kscience.kmath.expressions.derivative
 import space.kscience.kmath.expressions.withSymbols
 import space.kscience.kmath.misc.UnstableKMathAPI
 import space.kscience.kmath.optimization.*
+import kotlin.collections.set
 import kotlin.reflect.KClass
 
 public operator fun PointValuePair.component1(): DoubleArray = point

kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/cmFit.kt

@@ -22,7 +22,7 @@ public fun FunctionOptimization.Companion.chiSquaredExpression(
     y: Buffer<Double>,
     yErr: Buffer<Double>,
     model: DerivativeStructureField.(x: DerivativeStructure) -> DerivativeStructure,
-): DifferentiableExpression<Double, Expression<Double>> = chiSquaredExpression(DerivativeStructureField, x, y, yErr, model)
+): DifferentiableExpression<Double> = chiSquaredExpression(DerivativeStructureField, x, y, yErr, model)
 
 /**
  * Generate a chi squared expression from given x-y-sigma data and inline model. Provides automatic differentiation
@@ -32,7 +32,7 @@ public fun FunctionOptimization.Companion.chiSquaredExpression(
     y: Iterable<Double>,
     yErr: Iterable<Double>,
     model: DerivativeStructureField.(x: DerivativeStructure) -> DerivativeStructure,
-): DifferentiableExpression<Double, Expression<Double>> = chiSquaredExpression(
+): DifferentiableExpression<Double> = chiSquaredExpression(
     DerivativeStructureField,
     x.toList().asBuffer(),
     y.toList().asBuffer(),
@@ -56,12 +56,12 @@ public suspend fun Expression<Double>.optimize(
 /**
  * Optimize differentiable expression
  */
-public suspend fun DifferentiableExpression<Double, Expression<Double>>.optimize(
+public suspend fun DifferentiableExpression<Double>.optimize(
     vararg symbols: Symbol,
     configuration: CMOptimization.() -> Unit,
 ): OptimizationResult<Double> = optimizeWith(CMOptimization, symbols = symbols, configuration)
 
-public suspend fun DifferentiableExpression<Double, Expression<Double>>.minimize(
+public suspend fun DifferentiableExpression<Double>.minimize(
     vararg startPoint: Pair<Symbol, Double>,
     configuration: CMOptimization.() -> Unit = {},
 ): OptimizationResult<Double> {

kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/DifferentiableExpression.kt

@@ -11,35 +11,51 @@ package space.kscience.kmath.expressions
  * @param T the type this expression takes as argument and returns.
  * @param R the type of expression this expression can be differentiated to.
  */
-public interface DifferentiableExpression<T, out R : Expression<T>> : Expression<T> {
+public interface DifferentiableExpression<T> : Expression<T> {
     /**
      * Differentiates this expression by ordered collection of [symbols].
      *
      * @param symbols the symbols.
      * @return the derivative or `null`.
      */
-    public fun derivativeOrNull(symbols: List<Symbol>): R?
+    public fun derivativeOrNull(symbols: List<Symbol>): Expression<T>?
 }
 
-public fun <T, R : Expression<T>> DifferentiableExpression<T, R>.derivative(symbols: List<Symbol>): R =
+public fun <T> DifferentiableExpression<T>.derivative(symbols: List<Symbol>): Expression<T> =
     derivativeOrNull(symbols) ?: error("Derivative by symbols $symbols not provided")
 
-public fun <T, R : Expression<T>> DifferentiableExpression<T, R>.derivative(vararg symbols: Symbol): R =
+public fun <T> DifferentiableExpression<T>.derivative(vararg symbols: Symbol):  Expression<T> =
     derivative(symbols.toList())
 
-public fun <T, R : Expression<T>> DifferentiableExpression<T, R>.derivative(name: String): R =
+public fun <T> DifferentiableExpression<T>.derivative(name: String):  Expression<T> =
+    derivative(StringSymbol(name))
+
+/**
+ * A special type of [DifferentiableExpression] which returns typed expressions as derivatives
+ */
+public interface SpecialDifferentiableExpression<T, R: Expression<T>>: DifferentiableExpression<T> {
+    override fun derivativeOrNull(symbols: List<Symbol>): R?
+}
+
+public fun <T, R : Expression<T>> SpecialDifferentiableExpression<T, R>.derivative(symbols: List<Symbol>): R =
+    derivativeOrNull(symbols) ?: error("Derivative by symbols $symbols not provided")
+
+public fun <T, R : Expression<T>> SpecialDifferentiableExpression<T, R>.derivative(vararg symbols: Symbol): R =
+    derivative(symbols.toList())
+
+public fun <T, R : Expression<T>> SpecialDifferentiableExpression<T, R>.derivative(name: String): R =
     derivative(StringSymbol(name))
 
 /**
  * A [DifferentiableExpression] that defines only first derivatives
  */
-public abstract class FirstDerivativeExpression<T, R : Expression<T>> : DifferentiableExpression<T, R> {
+public abstract class FirstDerivativeExpression<T> : DifferentiableExpression<T> {
     /**
      * Returns first derivative of this expression by given [symbol].
      */
-    public abstract fun derivativeOrNull(symbol: Symbol): R?
+    public abstract fun derivativeOrNull(symbol: Symbol):  Expression<T>?
 
-    public final override fun derivativeOrNull(symbols: List<Symbol>): R? {
+    public final override fun derivativeOrNull(symbols: List<Symbol>):  Expression<T>? {
         val dSymbol = symbols.firstOrNull() ?: return null
         return derivativeOrNull(dSymbol)
     }
@@ -49,5 +65,5 @@ public abstract class FirstDerivativeExpression<T, R : Expression<T>> : Differen
  * A factory that converts an expression in autodiff variables to a [DifferentiableExpression]
  */
 public fun interface AutoDiffProcessor<T, I, A : ExpressionAlgebra<T, I>, out R : Expression<T>> {
-    public fun process(function: A.() -> I): DifferentiableExpression<T, R>
+    public fun process(function: A.() -> I): DifferentiableExpression<T>
 }

kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/SimpleAutoDiff.kt

@@ -232,7 +232,7 @@ public fun <T : Any, F : Field<T>> F.simpleAutoDiff(
 public class SimpleAutoDiffExpression<T : Any, F : Field<T>>(
     public val field: F,
     public val function: SimpleAutoDiffField<T, F>.() -> AutoDiffValue<T>,
-) : FirstDerivativeExpression<T, Expression<T>>() {
+) : FirstDerivativeExpression<T>() {
     public override operator fun invoke(arguments: Map<Symbol, T>): T {
         //val bindings = arguments.entries.map { it.key.bind(it.value) }
         return SimpleAutoDiffField(field, arguments).function().value

kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/KotlingradExpression.kt

@@ -24,7 +24,7 @@ import space.kscience.kmath.operations.NumericAlgebra
 public class KotlingradExpression<T : Number, A : NumericAlgebra<T>>(
     public val algebra: A,
     public val mst: MST,
-) : DifferentiableExpression<T, KotlingradExpression<T, A>> {
+) : SpecialDifferentiableExpression<T, KotlingradExpression<T, A>> {
     public override fun invoke(arguments: Map<Symbol, T>): T = mst.interpret(algebra, arguments)
 
     public override fun derivativeOrNull(symbols: List<Symbol>): KotlingradExpression<T, A> =

kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/FunctionOptimization.kt

@@ -22,7 +22,7 @@ public enum class FunctionOptimizationTarget : OptimizationFeature {
 
 public class FunctionOptimization<T>(
     override val features: FeatureSet<OptimizationFeature>,
-    public val expression: DifferentiableExpression<T, Expression<T>>,
+    public val expression: DifferentiableExpression<T>,
 ) : OptimizationProblem{
 
     public companion object{
@@ -35,7 +35,7 @@ public class FunctionOptimization<T>(
             y: Buffer<T>,
             yErr: Buffer<T>,
             model: A.(I) -> I,
-        ): DifferentiableExpression<T, Expression<T>> where A : ExtendedField<I>, A : ExpressionAlgebra<T, I> {
+        ): DifferentiableExpression<T> where A : ExtendedField<I>, A : ExpressionAlgebra<T, I> {
             require(x.size == y.size) { "X and y buffers should be of the same size" }
             require(y.size == yErr.size) { "Y and yErr buffer should of the same size" }