ValueAndErrorField

CHANGELOG.md

@@ -19,6 +19,7 @@
 - Complex power
 - Separate methods for UInt, Int and Number powers. NaN safety.
 - Tensorflow prototype
+- `ValueAndErrorField`
 
 ### Changed
 - Exponential operations merged with hyperbolic functions
@@ -50,6 +51,7 @@
 - Tensor algebra takes read-only structures as input and inherits AlgebraND
 - `UnivariateDistribution` renamed to `Distribution1D`
 - Rework of histograms.
+- `UnivariateFunction` -> `Function1D`, `MultivariateFunction` -> `FunctionND`
 
 ### Deprecated
 - Specialized `DoubleBufferAlgebra`

examples/src/main/kotlin/space/kscience/kmath/functions/integrate.kt

@@ -13,7 +13,7 @@ import kotlin.math.pow
 
 fun main() {
     //Define a function
-    val function: UnivariateFunction<Double> = { x -> 3 * x.pow(2) + 2 * x + 1 }
+    val function: Function1D<Double> = { x -> 3 * x.pow(2) + 2 * x + 1 }
 
     //get the result of the integration
     val result = DoubleField.gaussIntegrator.integrate(0.0..10.0, function = function)

examples/src/main/kotlin/space/kscience/kmath/functions/interpolateSquare.kt

@@ -18,7 +18,7 @@ import space.kscience.plotly.scatter
 
 @OptIn(UnstablePlotlyAPI::class)
 fun main() {
-    val function: UnivariateFunction<Double> = { x ->
+    val function: Function1D<Double> = { x ->
         if (x in 30.0..50.0) {
             1.0
         } else {

kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BufferAlgebra.kt

@@ -5,7 +5,6 @@
 
 package space.kscience.kmath.operations
 
-import space.kscience.kmath.misc.UnstableKMathAPI
 import space.kscience.kmath.structures.Buffer
 import space.kscience.kmath.structures.BufferFactory
 import space.kscience.kmath.structures.DoubleBuffer
@@ -53,7 +52,7 @@ public interface BufferAlgebra<T, out A : Algebra<T>> : Algebra<Buffer<T>> {
  */
 private inline fun <T, A : Algebra<T>> BufferAlgebra<T, A>.mapInline(
     buffer: Buffer<T>,
-    crossinline block: A.(T) -> T
+    crossinline block: A.(T) -> T,
 ): Buffer<T> = bufferFactory(buffer.size) { elementAlgebra.block(buffer[it]) }
 
 /**
@@ -61,7 +60,7 @@ private inline fun <T, A : Algebra<T>> BufferAlgebra<T, A>.mapInline(
  */
 private inline fun <T, A : Algebra<T>> BufferAlgebra<T, A>.mapIndexedInline(
     buffer: Buffer<T>,
-    crossinline block: A.(index: Int, arg: T) -> T
+    crossinline block: A.(index: Int, arg: T) -> T,
 ): Buffer<T> = bufferFactory(buffer.size) { elementAlgebra.block(it, buffer[it]) }
 
 /**
@@ -70,7 +69,7 @@ private inline fun <T, A : Algebra<T>> BufferAlgebra<T, A>.mapIndexedInline(
 private inline fun <T, A : Algebra<T>> BufferAlgebra<T, A>.zipInline(
     l: Buffer<T>,
     r: Buffer<T>,
-    crossinline block: A.(l: T, r: T) -> T
+    crossinline block: A.(l: T, r: T) -> T,
 ): Buffer<T> {
     require(l.size == r.size) { "Incompatible buffer sizes. left: ${l.size}, right: ${r.size}" }
     return bufferFactory(l.size) { elementAlgebra.block(l[it], r[it]) }
@@ -127,13 +126,13 @@ public fun <T, A : ExponentialOperations<T>> BufferAlgebra<T, A>.atanh(arg: Buff
     mapInline(arg) { atanh(it) }
 
 public fun <T, A : PowerOperations<T>> BufferAlgebra<T, A>.pow(arg: Buffer<T>, pow: Number): Buffer<T> =
-    mapInline(arg) {it.pow(pow) }
+    mapInline(arg) { it.pow(pow) }
 
 
-public open class BufferRingOps<T, A: Ring<T>>(
+public open class BufferRingOps<T, A : Ring<T>>(
     override val elementAlgebra: A,
     override val bufferFactory: BufferFactory<T>,
-) : BufferAlgebra<T, A>, RingOps<Buffer<T>>{
+) : BufferAlgebra<T, A>, RingOps<Buffer<T>> {
 
     override fun add(left: Buffer<T>, right: Buffer<T>): Buffer<T> = zipInline(left, right) { l, r -> l + r }
     override fun multiply(left: Buffer<T>, right: Buffer<T>): Buffer<T> = zipInline(left, right) { l, r -> l * r }
@@ -152,10 +151,11 @@ public val ShortRing.bufferAlgebra: BufferRingOps<Short, ShortRing>
 public open class BufferFieldOps<T, A : Field<T>>(
     elementAlgebra: A,
     bufferFactory: BufferFactory<T>,
-) : BufferRingOps<T, A>(elementAlgebra, bufferFactory), BufferAlgebra<T, A>, FieldOps<Buffer<T>>, ScaleOperations<Buffer<T>> {
+) : BufferRingOps<T, A>(elementAlgebra, bufferFactory), BufferAlgebra<T, A>, FieldOps<Buffer<T>>,
+    ScaleOperations<Buffer<T>> {
 
-    override fun add(left: Buffer<T>, right: Buffer<T>): Buffer<T> = zipInline(left, right) { l, r -> l + r }
+//    override fun add(left: Buffer<T>, right: Buffer<T>): Buffer<T> = zipInline(left, right) { l, r -> l + r }
-    override fun multiply(left: Buffer<T>, right: Buffer<T>): Buffer<T> = zipInline(left, right) { l, r -> l * r }
+//    override fun multiply(left: Buffer<T>, right: Buffer<T>): Buffer<T> = zipInline(left, right) { l, r -> l * r }
     override fun divide(left: Buffer<T>, right: Buffer<T>): Buffer<T> = zipInline(left, right) { l, r -> l / r }
 
     override fun scale(a: Buffer<T>, value: Double): Buffer<T> = a.map { scale(it, value) }
@@ -168,7 +168,7 @@ public open class BufferFieldOps<T, A : Field<T>>(
 public class BufferField<T, A : Field<T>>(
     elementAlgebra: A,
     bufferFactory: BufferFactory<T>,
-    override val size: Int
+    override val size: Int,
 ) : BufferFieldOps<T, A>(elementAlgebra, bufferFactory), Field<Buffer<T>>, WithSize {
 
     override val zero: Buffer<T> = bufferFactory(size) { elementAlgebra.zero }

kmath-functions/src/commonMain/kotlin/space/kscience/kmath/functions/functionTypes.kt

@@ -7,6 +7,6 @@ package space.kscience.kmath.functions
 
 import space.kscience.kmath.structures.Buffer
 
-public typealias UnivariateFunction<T> = (T) -> T
+public typealias Function1D<T> = (T) -> T
 
-public typealias MultivariateFunction<T> = (Buffer<T>) -> T
+public typealias FunctionND<T> = (Buffer<T>) -> T

kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/ValueAndErrorField.kt

@@ -0,0 +1,56 @@
+/*
+ * Copyright 2018-2021 KMath contributors.
+ * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
+ */
+
+package space.kscience.kmath.stat
+
+import space.kscience.kmath.operations.Field
+import kotlin.math.pow
+import kotlin.math.sqrt
+
+/**
+ * A combination of a random [value] and its [dispersion].
+ *
+ * [dispersion] must be positive.
+ */
+public data class ValueAndError(val value: Double, val dispersion: Double) {
+    init {
+        require(dispersion >= 0) { "Dispersion must be non-negative" }
+    }
+
+    val error: Double get() = sqrt(dispersion)
+}
+
+/**
+ * An algebra for double value + its error combination. The multiplication assumes linear error propagation
+ */
+public object ValueAndErrorField : Field<ValueAndError> {
+
+    override val zero: ValueAndError = ValueAndError(0.0, 0.0)
+
+    override val one: ValueAndError = ValueAndError(1.0, 0.0)
+
+    override fun add(left: ValueAndError, right: ValueAndError): ValueAndError =
+        ValueAndError(left.value + right.value, left.dispersion + right.dispersion)
+
+    override fun ValueAndError.unaryMinus(): ValueAndError =
+        ValueAndError(-value, dispersion)
+
+    //TODO study performance impact of pow(2). On JVM it does not exist: https://stackoverflow.com/questions/29144275/xx-vs-math-powx-2-java-performance
+
+    override fun multiply(left: ValueAndError, right: ValueAndError): ValueAndError {
+        val value = left.value * right.value
+        val dispersion = (left.dispersion / left.value.pow(2) + right.dispersion / right.value.pow(2)) * value.pow(2)
+        return ValueAndError(value, dispersion)
+    }
+
+    override fun divide(left: ValueAndError, right: ValueAndError): ValueAndError {
+        val value = left.value / right.value
+        val dispersion = (left.dispersion / left.value.pow(2) + right.dispersion / right.value.pow(2)) * value.pow(2)
+        return ValueAndError(value, dispersion)
+    }
+
+    override fun scale(a: ValueAndError, value: Double): ValueAndError =
+        ValueAndError(a.value * value, a.dispersion * value.pow(2))
+}