Merge remote-tracking branch 'origin/dev' into mp-samplers

# Conflicts:
#	examples/src/main/kotlin/kscience/kmath/commons/prob/DistributionBenchmark.kt
#	examples/src/main/kotlin/kscience/kmath/commons/prob/DistributionDemo.kt
#	kmath-coroutines/src/commonMain/kotlin/kscience/kmath/chains/Chain.kt
#	kmath-coroutines/src/commonMain/kotlin/scientifik/kmath/chains/BlockingIntChain.kt
#	kmath-coroutines/src/commonMain/kotlin/scientifik/kmath/chains/BlockingRealChain.kt
#	kmath-prob/build.gradle.kts
#	kmath-prob/src/commonMain/kotlin/kscience/kmath/prob/Distribution.kt
#	kmath-prob/src/commonMain/kotlin/kscience/kmath/prob/samplers/AhrensDieterExponentialSampler.kt
#	kmath-prob/src/commonMain/kotlin/kscience/kmath/prob/samplers/AhrensDieterMarsagliaTsangGammaSampler.kt
#	kmath-prob/src/commonMain/kotlin/kscience/kmath/prob/samplers/AliasMethodDiscreteSampler.kt
#	kmath-prob/src/commonMain/kotlin/kscience/kmath/prob/samplers/BoxMullerNormalizedGaussianSampler.kt
#	kmath-prob/src/commonMain/kotlin/kscience/kmath/prob/samplers/GaussianSampler.kt
#	kmath-prob/src/commonMain/kotlin/kscience/kmath/prob/samplers/InternalGamma.kt
#	kmath-prob/src/commonMain/kotlin/kscience/kmath/prob/samplers/InternalUtils.kt
#	kmath-prob/src/commonMain/kotlin/kscience/kmath/prob/samplers/KempSmallMeanPoissonSampler.kt
#	kmath-prob/src/commonMain/kotlin/kscience/kmath/prob/samplers/LargeMeanPoissonSampler.kt
#	kmath-prob/src/commonMain/kotlin/kscience/kmath/prob/samplers/MarsagliaNormalizedGaussianSampler.kt
#	kmath-prob/src/commonMain/kotlin/kscience/kmath/prob/samplers/NormalizedGaussianSampler.kt
#	kmath-prob/src/commonMain/kotlin/kscience/kmath/prob/samplers/PoissonSampler.kt
#	kmath-prob/src/commonMain/kotlin/kscience/kmath/prob/samplers/SmallMeanPoissonSampler.kt
#	kmath-prob/src/commonMain/kotlin/kscience/kmath/prob/samplers/ZigguratNormalizedGaussianSampler.kt
#	kmath-prob/src/commonMain/kotlin/scientifik/kmath/prob/FactorizedDistribution.kt
#	kmath-prob/src/commonMain/kotlin/scientifik/kmath/prob/RandomChain.kt
#	kmath-prob/src/commonMain/kotlin/scientifik/kmath/prob/RandomGenerator.kt
#	kmath-prob/src/jvmMain/kotlin/kscience/kmath/prob/distributions.kt
#	kmath-prob/src/jvmMain/kotlin/scientifik/kmath/prob/RandomSourceGenerator.kt

.space.kts

@@ -0,0 +1 @@
+job("Build") { gradlew("openjdk:11", "build") }

CHANGELOG.md

@@ -1,6 +1,29 @@
 # KMath
 
 ## [Unreleased]
+### Added
+- `fun` annotation for SAM interfaces in library
+- Explicit `public` visibility for all public APIs
+- Better trigonometric and hyperbolic functions for `AutoDiffField` (https://github.com/mipt-npm/kmath/pull/140).
+- Automatic documentation generation for features (#139)
+
+### Changed
+- Package changed from `scientifik` to `kscience.kmath`.
+- Gradle version: 6.6 -> 6.6.1
+- Minor exceptions refactor (throwing `IllegalArgumentException` by argument checks instead of `IllegalStateException`)
+- `Polynomial` secondary constructor made function.
+
+### Deprecated
+
+### Removed
+- `kmath-koma` module because it doesn't support Kotlin 1.4.
+
+### Fixed
+- `symbol` method in `MstExtendedField` (https://github.com/mipt-npm/kmath/pull/140)
+
+### Security
+
+## [0.1.4]
 
 ### Added
 - Functional Expressions API

README.md

@@ -3,7 +3,7 @@
 
 ![Gradle build](https://github.com/mipt-npm/kmath/workflows/Gradle%20build/badge.svg)
 
-Bintray:        [ ![Download](https://api.bintray.com/packages/mipt-npm/scientifik/kmath-core/images/download.svg) ](https://bintray.com/mipt-npm/scientifik/kmath-core/_latestVersion)
+Bintray:        [ ![Download](https://api.bintray.com/packages/mipt-npm/kscience/kmath-core/images/download.svg) ](https://bintray.com/mipt-npm/kscience/kmath-core/_latestVersion)
 
 Bintray-dev:    [ ![Download](https://api.bintray.com/packages/mipt-npm/dev/kmath-core/images/download.svg) ](https://bintray.com/mipt-npm/dev/kmath-core/_latestVersion)
 
@@ -29,7 +29,7 @@ The Kotlin MATHematics library is intended as a Kotlin-based analog to Python's
 
 ## Features
 
-Actual feature list is [here](doc/features.md)
+Actual feature list is [here](docs/features.md)
 
 * **Algebra**
     * Algebraic structures like rings, spaces and field (**TODO** add example to wiki)
@@ -54,9 +54,6 @@ can be used for a wide variety of purposes from high performance calculations to
                            library in Kotlin code and maybe rewrite some parts to better suit the Kotlin programming paradigm, however there is no fixed roadmap for that. Feel free
                            to submit a feature request if you want something to be done first.
                            
-* **Koma wrapper** [Koma](https://github.com/kyonifer/koma) is a well established numerics library in Kotlin, specifically linear algebra.
-The plan is to have wrappers for koma implementations for compatibility with kmath API.
-
 ## Planned features
 
 * **Messaging** A mathematical notation to support multi-language and multi-node communication for mathematical tasks.
@@ -69,6 +66,29 @@ The plan is to have wrappers for koma implementations for compatibility with kma
 
 * **Fitting** Non-linear curve fitting facilities
 
+## Modules
+
+### [kmath-core](kmath-core)
+ - [algebras](kmath-core/src/commonMain/kotlin/kscience/kmath/operations/Algebra.kt) : Algebraic structures: contexts and elements
+ - [nd](kmath-core/src/commonMain/kotlin/kscience/kmath/structures/NDStructure.kt) : Many-dimensional structures
+ - [buffers](kmath-core/src/commonMain/kotlin/kscience/kmath/structures/Buffers.kt) : One-dimensional structure
+ - [expressions](kmath-core/src/commonMain/kotlin/kscience/kmath/expressions) : Functional Expressions
+ - [domains](kmath-core/src/commonMain/kotlin/kscience/kmath/domains) : Domains
+ - [autodif](kmath-core/src/commonMain/kotlin/kscience/kmath/misc/AutoDiff.kt) : Automatic differentiation
+
+### [kmath-coroutines](kmath-coroutines)
+### [kmath-viktor](kmath-viktor)
+### [kmath-prob](kmath-prob)
+### [kmath-ast](kmath-ast)
+### [kmath-commons](kmath-commons)
+### [kmath-memory](kmath-memory)
+### [kmath-for-real](kmath-for-real)
+### [kmath-functions](kmath-functions)
+### [kmath-dimensions](kmath-dimensions)
+### [kmath-histograms](kmath-histograms)
+### [kmath-geometry](kmath-geometry)
+
+
 ## Multi-platform support
 
 KMath is developed as a multi-platform library, which means that most of interfaces are declared in the [common module](kmath-core/src/commonMain). Implementation is also done in the common module wherever possible. In some cases, features are delegated to platform-specific implementations even if they could be done in the common module for performance reasons. Currently, the JVM is the main focus of development, however Kotlin/Native and Kotlin/JS contributions are also welcome.
@@ -83,12 +103,12 @@ Release artifacts are accessible from bintray with following configuration (see
 
 ```kotlin
 repositories{
-    maven("https://dl.bintray.com/mipt-npm/scientifik")
+    maven("https://dl.bintray.com/mipt-npm/kscience")
 }
 
 dependencies{
-    api("scientifik:kmath-core:${kmathVersion}")
-    //api("scientifik:kmath-core-jvm:${kmathVersion}") for jvm-specific version
+    api("kscience.kmath:kmath-core:0.2.0-dev-1")
+    //api("kscience.kmath:kmath-core-jvm:0.2.0-dev-1") for jvm-specific version
 }
 ```
 

build.gradle.kts

@@ -1,10 +1,10 @@
 plugins {
-    id("scientifik.publish") apply false
+    id("ru.mipt.npm.base")
+    id("org.jetbrains.changelog") version "0.4.0"
 }
 
-val kmathVersion by extra("0.1.4-dev-8")
-
-val bintrayRepo by extra("scientifik")
+val kmathVersion by extra("0.2.0-dev-1")
+val bintrayRepo by extra("kscience")
 val githubProject by extra("kmath")
 
 allprojects {
@@ -14,12 +14,87 @@ allprojects {
         maven("https://dl.bintray.com/hotkeytlt/maven")
     }
 
-    group = "scientifik"
+    group = "kscience.kmath"
     version = kmathVersion
 }
 
 subprojects {
-    if (name.startsWith("kmath")) {
-        apply(plugin = "scientifik.publish")
+    if (name.startsWith("kmath")) apply<ru.mipt.npm.gradle.KSciencePublishPlugin>()
+}
+
+/**
+ * TODO move to base plugin
+ */
+val generateReadme by tasks.creating {
+    group = "documentation"
+
+    fun List<Map<String, Any?>>.generateFeatureString(pathPrefix: String): String = buildString {
+        this@generateFeatureString.forEach { feature ->
+            val id by feature
+            val description by feature
+            val ref by feature
+            appendln(" - [$id]($pathPrefix$ref) : $description")
+        }
+    }
+
+    doLast {
+        val reader = groovy.json.JsonSlurper()
+        val projects = HashMap<String, Map<String, Any?>>()
+
+        project.subprojects {
+            var properties: Map<String, Any?> = mapOf(
+                "name" to this.name,
+                "group" to this.group,
+                "version" to this.version
+            )
+
+            val projectProperties = this.file("docs/kscience-module.json")
+
+            @Suppress("UNCHECKED_CAST")
+            if (projectProperties.exists()) {
+                val customProperties: Map<String, Any?> =
+                    (reader.parse(projectProperties) as? Map<String, Any?> ?: emptyMap()).withDefault { null }
+                val features: List<Map<String, Any?>>? by customProperties
+                val featureString = features?.generateFeatureString("")
+                properties = customProperties + properties + ("featuresString" to featureString)
+            }
+
+            projects[name] = properties.withDefault { null }
+
+            val readmeStub = this.file("docs/README-STUB.md")
+            if (readmeStub.exists()) {
+                val readmeFile = this.file("README.md")
+                readmeFile.writeText(
+                    groovy.text.SimpleTemplateEngine().createTemplate(readmeStub).make(properties).toString()
+                )
+            }
+        }
+
+        val rootReadmeStub = project.file("docs/README-STUB.md")
+
+        val modulesString = buildString {
+            projects.filter { it.key.startsWith("kmath") }.forEach { (name, properties) ->
+                appendln("### [$name]($name)")
+                val features: List<Map<String, Any?>>? by properties
+                if (features != null) {
+                    appendln(features!!.generateFeatureString("$name/"))
+                }
+            }
+        }
+
+        val rootReadmeProperties: Map<String, Any> = mapOf(
+            "name" to project.name,
+            "group" to project.group,
+            "version" to project.version,
+            "modulesString" to modulesString
+        )
+
+        if (rootReadmeStub.exists()) {
+            val readmeFile = project.file("README.md")
+            readmeFile.writeText(
+                groovy.text.SimpleTemplateEngine().createTemplate(rootReadmeStub).make(rootReadmeProperties).toString()
+            )
+        }
+
     }
 }

doc/features.md

@@ -1,17 +0,0 @@
-# Features
-
-* [Algebra](./algebra.md) - [Context-based](./contexts.md) operations on different primitives and structures.
-
-* [NDStructures](./nd-structure.md)
-
-* [Linear algebra](./linear.md) - Matrices, operations and linear equations solving. To be moved to separate module. Currently supports basic
-api and multiple library back-ends.
-
-* [Histograms](./histograms.md) - Multidimensional histogram calculation and operations.
-
-* [Expressions](./expressions.md)
-
-* Commons math integration
-
-* Koma integration
-

docs/README-STUB.md

@@ -0,0 +1,110 @@
+[![JetBrains Research](https://jb.gg/badges/research.svg)](https://confluence.jetbrains.com/display/ALL/JetBrains+on+GitHub)
+[![DOI](https://zenodo.org/badge/129486382.svg)](https://zenodo.org/badge/latestdoi/129486382)
+
+![Gradle build](https://github.com/mipt-npm/kmath/workflows/Gradle%20build/badge.svg)
+
+Bintray:        [ ![Download](https://api.bintray.com/packages/mipt-npm/kscience/kmath-core/images/download.svg) ](https://bintray.com/mipt-npm/kscience/kmath-core/_latestVersion)
+
+Bintray-dev:    [ ![Download](https://api.bintray.com/packages/mipt-npm/dev/kmath-core/images/download.svg) ](https://bintray.com/mipt-npm/dev/kmath-core/_latestVersion)
+
+# KMath
+Could be pronounced as `key-math`.
+The Kotlin MATHematics library is intended as a Kotlin-based analog to Python's `numpy` library. In contrast to `numpy` and `scipy` it is modular and has a lightweight core.
+
+## Publications
+* [A conceptual article about context-oriented design](https://proandroiddev.com/an-introduction-context-oriented-programming-in-kotlin-2e79d316b0a2)
+* [Another article about context-oriented design](https://proandroiddev.com/diving-deeper-into-context-oriented-programming-in-kotlin-3ecb4ec38814)
+* [ACAT 2019 conference paper](https://aip.scitation.org/doi/abs/10.1063/1.5130103)
+
+# Goal
+* Provide a flexible and powerful API to work with mathematics abstractions in Kotlin-multiplatform (JVM and JS for now and Native in future). 
+* Provide basic multiplatform implementations for those abstractions (without significant performance optimization).
+* Provide bindings and wrappers with those abstractions for popular optimized platform libraries.
+
+## Non-goals
+* Be like Numpy. It was the idea at the beginning, but we decided that we can do better in terms of API.
+* Provide best performance out of the box. We have specialized libraries for that. Need only API wrappers for them.
+* Cover all cases as immediately and in one bundle. We will modularize everything and add new features gradually.
+* Provide specialized behavior in the core. API is made generic on purpose, so one needs to specialize for types, like for `Double` in the core. For that we will have specialization modules like `for-real`, which will give better experience for those, who want to work with specific types.
+
+## Features
+
+Actual feature list is [here](docs/features.md)
+
+* **Algebra**
+    * Algebraic structures like rings, spaces and field (**TODO** add example to wiki)
+    * Basic linear algebra operations (sums, products, etc.), backed by the `Space` API.
+    * Complex numbers backed by the `Field` API (meaning that they will be usable in any structure like vectors and N-dimensional arrays).
+    * Advanced linear algebra operations like matrix inversion and LU decomposition.
+
+* **Array-like structures** Full support of many-dimensional array-like structures 
+including mixed arithmetic operations and function operations over arrays and numbers (with the added benefit of static type checking).
+
+* **Expressions** By writing a single mathematical expression
+once, users will be able to apply different types of objects to the expression by providing a context. Expressions
+can be used for a wide variety of purposes from high performance calculations to code generation.
+
+* **Histograms** Fast multi-dimensional histograms.
+
+* **Streaming** Streaming operations on mathematical objects and objects buffers.
+
+* **Type-safe dimensions** Type-safe dimensions for matrix operations.
+
+* **Commons-math wrapper** It is planned to gradually wrap most parts of [Apache commons-math](http://commons.apache.org/proper/commons-math/)
+                           library in Kotlin code and maybe rewrite some parts to better suit the Kotlin programming paradigm, however there is no fixed roadmap for that. Feel free
+                           to submit a feature request if you want something to be done first.
+                           
+## Planned features
+
+* **Messaging** A mathematical notation to support multi-language and multi-node communication for mathematical tasks.
+
+* **Array statistics** 
+
+* **Integration** Univariate and multivariate integration framework.
+
+* **Probability and distributions**
+
+* **Fitting** Non-linear curve fitting facilities
+
+## Modules
+
+$modulesString
+
+## Multi-platform support
+
+KMath is developed as a multi-platform library, which means that most of interfaces are declared in the [common module](kmath-core/src/commonMain). Implementation is also done in the common module wherever possible. In some cases, features are delegated to platform-specific implementations even if they could be done in the common module for performance reasons. Currently, the JVM is the main focus of development, however Kotlin/Native and Kotlin/JS contributions are also welcome.
+
+## Performance
+
+Calculation performance is one of major goals of KMath in the future, but in some cases it is not possible to achieve both performance and flexibility. We expect to focus on creating convenient universal API first and then work on increasing performance for specific cases. We expect the worst KMath benchmarks will perform better than native Python, but worse than optimized native/SciPy (mostly due to boxing operations on primitive numbers). The best performance of optimized parts could be better than SciPy.
+
+### Dependency
+
+Release artifacts are accessible from bintray with following configuration (see documentation for [kotlin-multiplatform](https://kotlinlang.org/docs/reference/multiplatform.html) form more details):
+
+```kotlin
+repositories{
+    maven("https://dl.bintray.com/mipt-npm/kscience")
+}
+
+dependencies{
+    api("kscience.kmath:kmath-core:$version")
+    //api("kscience.kmath:kmath-core-jvm:$version") for jvm-specific version
+}
+```
+
+Gradle `6.0+` is required for multiplatform artifacts.
+
+### Development
+
+Development builds are accessible from the reposirtory 
+```kotlin
+repositories{
+    maven("https://dl.bintray.com/mipt-npm/dev")
+}
+```
+with the same artifact names.
+
+## Contributing
+
+The project requires a lot of additional work. Please feel free to contribute in any way and propose new features.

docs/algebra.md

@@ -5,7 +5,7 @@ operation, say `+`, one needs two objects of a type `T` and an algebra context,
 say `Space<T>`. Next one needs to run the actual operation in the context:
 
 ```kotlin
-import scientifik.kmath.operations.*
+import kscience.kmath.operations.*
 
 val a: T = ...
 val b: T = ...
@@ -47,7 +47,7 @@ but it also holds reference to the `ComplexField` singleton, which allows perfor
 numbers without explicit involving the context like:
 
 ```kotlin
-import scientifik.kmath.operations.*
+import kscience.kmath.operations.*
 
 // Using elements
 val c1 = Complex(1.0, 1.0)
@@ -82,7 +82,7 @@ operations in all performance-critical places. The performance of element operat
 KMath submits both contexts and elements for builtin algebraic structures:
 
 ```kotlin
-import scientifik.kmath.operations.*
+import kscience.kmath.operations.*
 
 val c1 = Complex(1.0, 2.0)
 val c2 = ComplexField.i
@@ -95,7 +95,7 @@ val c3 = ComplexField { c1 + c2 }
 Also, `ComplexField` features special operations to mix complex and real numbers, for example:
 
 ```kotlin
-import scientifik.kmath.operations.*
+import kscience.kmath.operations.*
 
 val c1 = Complex(1.0, 2.0)
 val c2 = ComplexField { c1 - 1.0 } // Returns: Complex(re=0.0, im=2.0)

docs/features.md

@@ -0,0 +1,14 @@
+# Features
+
+* [Algebra](algebra.md) - [Context-based](contexts.md) operations on different primitives and structures.
+
+* [NDStructures](nd-structure.md)
+
+* [Linear algebra](linear.md) - Matrices, operations and linear equations solving. To be moved to separate module. Currently supports basic
+api and multiple library back-ends.
+
+* [Histograms](histograms.md) - Multidimensional histogram calculation and operations.
+
+* [Expressions](expressions.md)
+
+* Commons math integration

examples/build.gradle.kts

@@ -1,58 +1,48 @@
-import org.jetbrains.kotlin.allopen.gradle.AllOpenExtension
 import org.jetbrains.kotlin.gradle.tasks.KotlinCompile
 
 plugins {
     java
     kotlin("jvm")
-    kotlin("plugin.allopen") version "1.3.72"
-    id("kotlinx.benchmark") version "0.2.0-dev-8"
+    kotlin("plugin.allopen") version "1.4.20-dev-3898-14"
+    id("kotlinx.benchmark") version "0.2.0-dev-20"
 }
 
-configure<AllOpenExtension> {
-    annotation("org.openjdk.jmh.annotations.State")
-}
+allOpen.annotation("org.openjdk.jmh.annotations.State")
 
 repositories {
-    maven("http://dl.bintray.com/kyonifer/maven")
-    maven("https://dl.bintray.com/mipt-npm/scientifik")
+    maven("https://dl.bintray.com/mipt-npm/kscience")
     maven("https://dl.bintray.com/mipt-npm/dev")
+    maven("https://dl.bintray.com/kotlin/kotlin-dev/")
     mavenCentral()
 }
 
-sourceSets {
-    register("benchmarks")
-}
+sourceSets.register("benchmarks")
 
 dependencies {
-    implementation(project(":kmath-ast"))
+//    implementation(project(":kmath-ast"))
     implementation(project(":kmath-core"))
     implementation(project(":kmath-coroutines"))
     implementation(project(":kmath-commons"))
     implementation(project(":kmath-prob"))
-    implementation(project(":kmath-koma"))
     implementation(project(":kmath-viktor"))
     implementation(project(":kmath-dimensions"))
-    implementation("com.kyonifer:koma-core-ejml:0.12")
     implementation("org.jetbrains.kotlinx:kotlinx-io-jvm:0.2.0-npm-dev-6")
-    implementation("org.jetbrains.kotlinx:kotlinx.benchmark.runtime:0.2.0-dev-8")
+    implementation("org.jetbrains.kotlinx:kotlinx.benchmark.runtime:0.2.0-dev-20")
     "benchmarksCompile"(sourceSets.main.get().output + sourceSets.main.get().compileClasspath) //sourceSets.main.output + sourceSets.main.runtimeClasspath
 }
 
 // Configure benchmark
 benchmark {
     // Setup configurations
-    targets {
+    targets
         // This one matches sourceSet name above
-        register("benchmarks")
-    }
+        .register("benchmarks")
 
-    configurations {
-        register("fast") {
-            warmups = 5 // number of warmup iterations
-            iterations = 3 // number of iterations
-            iterationTime = 500 // time in seconds per iteration
-            iterationTimeUnit = "ms" // time unity for iterationTime, default is seconds
-        }
+    configurations.register("fast") {
+        warmups = 5 // number of warmup iterations
+        iterations = 3 // number of iterations
+        iterationTime = 500 // time in seconds per iteration
+        iterationTimeUnit = "ms" // time unity for iterationTime, default is seconds
     }
 }
 
@@ -63,9 +53,4 @@ kotlin.sourceSets.all {
     }
 }
 
-tasks.withType<KotlinCompile> {
-    kotlinOptions {
-        jvmTarget = Scientifik.JVM_TARGET.toString()
-        freeCompilerArgs = freeCompilerArgs + "-Xopt-in=kotlin.RequiresOptIn"
-    }
-}
+tasks.withType<KotlinCompile> { kotlinOptions.jvmTarget = "11" }

examples/src/benchmarks/kotlin/kscience/kmath/structures/ArrayBenchmark.kt

@@ -0,0 +1,39 @@
+package kscience.kmath.structures
+
+import org.openjdk.jmh.annotations.Benchmark
+import org.openjdk.jmh.annotations.Scope
+import org.openjdk.jmh.annotations.State
+import java.nio.IntBuffer
+
+@State(Scope.Benchmark)
+class ArrayBenchmark {
+    @Benchmark
+    fun benchmarkArrayRead() {
+        var res = 0
+        for (i in 1.._root_ide_package_.kscience.kmath.structures.ArrayBenchmark.Companion.size) res += _root_ide_package_.kscience.kmath.structures.ArrayBenchmark.Companion.array[_root_ide_package_.kscience.kmath.structures.ArrayBenchmark.Companion.size - i]
+    }
+
+    @Benchmark
+    fun benchmarkBufferRead() {
+        var res = 0
+        for (i in 1.._root_ide_package_.kscience.kmath.structures.ArrayBenchmark.Companion.size) res += _root_ide_package_.kscience.kmath.structures.ArrayBenchmark.Companion.arrayBuffer.get(
+            _root_ide_package_.kscience.kmath.structures.ArrayBenchmark.Companion.size - i)
+    }
+
+    @Benchmark
+    fun nativeBufferRead() {
+        var res = 0
+        for (i in 1.._root_ide_package_.kscience.kmath.structures.ArrayBenchmark.Companion.size) res += _root_ide_package_.kscience.kmath.structures.ArrayBenchmark.Companion.nativeBuffer.get(
+            _root_ide_package_.kscience.kmath.structures.ArrayBenchmark.Companion.size - i)
+    }
+
+    companion object {
+        const val size: Int = 1000
+        val array: IntArray = IntArray(_root_ide_package_.kscience.kmath.structures.ArrayBenchmark.Companion.size) { it }
+        val arrayBuffer: IntBuffer = IntBuffer.wrap(_root_ide_package_.kscience.kmath.structures.ArrayBenchmark.Companion.array)
+
+        val nativeBuffer: IntBuffer = IntBuffer.allocate(_root_ide_package_.kscience.kmath.structures.ArrayBenchmark.Companion.size).also {
+            for (i in 0 until _root_ide_package_.kscience.kmath.structures.ArrayBenchmark.Companion.size) it.put(i, i)
+        }
+    }
+}

examples/src/benchmarks/kotlin/kscience/kmath/structures/BufferBenchmark.kt

@@ -1,10 +1,10 @@
-package scientifik.kmath.structures
+package kscience.kmath.structures
 
+import kscience.kmath.operations.Complex
+import kscience.kmath.operations.complex
 import org.openjdk.jmh.annotations.Benchmark
 import org.openjdk.jmh.annotations.Scope
 import org.openjdk.jmh.annotations.State
-import scientifik.kmath.operations.Complex
-import scientifik.kmath.operations.complex
 
 @State(Scope.Benchmark)
 class BufferBenchmark {

examples/src/benchmarks/kotlin/kscience/kmath/structures/NDFieldBenchmark.kt

@@ -1,10 +1,10 @@
-package scientifik.kmath.structures
+package kscience.kmath.structures
 
+import kscience.kmath.operations.RealField
+import kscience.kmath.operations.invoke
 import org.openjdk.jmh.annotations.Benchmark
 import org.openjdk.jmh.annotations.Scope
 import org.openjdk.jmh.annotations.State
-import scientifik.kmath.operations.RealField
-import scientifik.kmath.operations.invoke
 
 @State(Scope.Benchmark)
 class NDFieldBenchmark {

examples/src/benchmarks/kotlin/kscience/kmath/structures/ViktorBenchmark.kt

@@ -1,12 +1,12 @@
-package scientifik.kmath.structures
+package kscience.kmath.structures
 
+import kscience.kmath.operations.RealField
+import kscience.kmath.operations.invoke
+import kscience.kmath.viktor.ViktorNDField
 import org.jetbrains.bio.viktor.F64Array
 import org.openjdk.jmh.annotations.Benchmark
 import org.openjdk.jmh.annotations.Scope
 import org.openjdk.jmh.annotations.State
-import scientifik.kmath.operations.RealField
-import scientifik.kmath.operations.invoke
-import scientifik.kmath.viktor.ViktorNDField
 
 @State(Scope.Benchmark)
 class ViktorBenchmark {

examples/src/benchmarks/kotlin/kscience/kmath/utils/utils.kt

@@ -1,4 +1,4 @@
-package scientifik.kmath.utils
+package kscience.kmath.utils
 
 import kotlin.contracts.InvocationKind
 import kotlin.contracts.contract

examples/src/benchmarks/kotlin/scientifik/kmath/structures/ArrayBenchmark.kt

@@ -1,48 +0,0 @@
-package scientifik.kmath.structures
-
-import org.openjdk.jmh.annotations.Benchmark
-import org.openjdk.jmh.annotations.Scope
-import org.openjdk.jmh.annotations.State
-import java.nio.IntBuffer
-
-
-@State(Scope.Benchmark)
-class ArrayBenchmark {
-
-    @Benchmark
-    fun benchmarkArrayRead() {
-        var res = 0
-        for (i in 1..size) {
-            res += array[size - i]
-        }
-    }
-
-    @Benchmark
-    fun benchmarkBufferRead() {
-        var res = 0
-        for (i in 1..size) {
-            res += arrayBuffer.get(size - i)
-        }
-    }
-
-    @Benchmark
-    fun nativeBufferRead() {
-        var res = 0
-        for (i in 1..size) {
-            res += nativeBuffer.get(size - i)
-        }
-    }
-
-    companion object {
-        val size = 1000
-
-        val array = IntArray(size) { it }
-        val arrayBuffer = IntBuffer.wrap(array)
-        val nativeBuffer = IntBuffer.allocate(size).also {
-            for (i in 0 until size) {
-                it.put(i, i)
-            }
-
-        }
-    }
-}

examples/src/main/kotlin/kscience/kmath/ast/ExpressionsInterpretersBenchmark.kt

@@ -0,0 +1,70 @@
+//package kscience.kmath.ast
+//
+//import kscience.kmath.asm.compile
+//import kscience.kmath.expressions.Expression
+//import kscience.kmath.expressions.expressionInField
+//import kscience.kmath.expressions.invoke
+//import kscience.kmath.operations.Field
+//import kscience.kmath.operations.RealField
+//import kotlin.random.Random
+//import kotlin.system.measureTimeMillis
+//
+//class ExpressionsInterpretersBenchmark {
+//    private val algebra: Field<Double> = RealField
+//    fun functionalExpression() {
+//        val expr = algebra.expressionInField {
+//            variable("x") * const(2.0) + const(2.0) / variable("x") - const(16.0)
+//        }
+//
+//        invokeAndSum(expr)
+//    }
+//
+//    fun mstExpression() {
+//        val expr = algebra.mstInField {
+//            symbol("x") * number(2.0) + number(2.0) / symbol("x") - number(16.0)
+//        }
+//
+//        invokeAndSum(expr)
+//    }
+//
+//    fun asmExpression() {
+//        val expr = algebra.mstInField {
+//            symbol("x") * number(2.0) + number(2.0) / symbol("x") - number(16.0)
+//        }.compile()
+//
+//        invokeAndSum(expr)
+//    }
+//
+//    private fun invokeAndSum(expr: Expression<Double>) {
+//        val random = Random(0)
+//        var sum = 0.0
+//
+//        repeat(1000000) {
+//            sum += expr("x" to random.nextDouble())
+//        }
+//
+//        println(sum)
+//    }
+//}
+//
+//fun main() {
+//    val benchmark = ExpressionsInterpretersBenchmark()
+//
+//    val fe = measureTimeMillis {
+//        benchmark.functionalExpression()
+//    }
+//
+//    println("fe=$fe")
+//
+//    val mst = measureTimeMillis {
+//        benchmark.mstExpression()
+//    }
+//
+//    println("mst=$mst")
+//
+//    val asm = measureTimeMillis {
+//        benchmark.asmExpression()
+//    }
+//
+//    println("asm=$asm")
+//}

examples/src/main/kotlin/kscience/kmath/commons/prob/DistributionBenchmark.kt

@@ -1,16 +1,16 @@
-package scientifik.kmath.commons.prob
+package kscience.kmath.commons.prob
 
 import kotlinx.coroutines.Dispatchers
 import kotlinx.coroutines.async
 import kotlinx.coroutines.runBlocking
 import org.apache.commons.rng.simple.RandomSource
-import scientifik.kmath.prob.RandomChain
-import scientifik.kmath.prob.RandomGenerator
-import scientifik.kmath.prob.fromSource
+import kscience.kmath.prob.RandomChain
+import kscience.kmath.prob.RandomGenerator
+import kscience.kmath.prob.fromSource
 import java.time.Duration
 import java.time.Instant
 import org.apache.commons.rng.sampling.distribution.ZigguratNormalizedGaussianSampler as ApacheZigguratNormalizedGaussianSampler
-import scientifik.kmath.prob.samplers.ZigguratNormalizedGaussianSampler as KMathZigguratNormalizedGaussianSampler
+import kscience.kmath.prob.samplers.ZigguratNormalizedGaussianSampler as KMathZigguratNormalizedGaussianSampler
 
 private suspend fun runKMathChained(): Duration {
     val generator = RandomGenerator.fromSource(RandomSource.MT, 123L)

examples/src/main/kotlin/kscience/kmath/commons/prob/DistributionDemo.kt

@@ -1,10 +1,10 @@
-package scientifik.kmath.commons.prob
+package kscience.kmath.commons.prob
 
 import kotlinx.coroutines.runBlocking
-import scientifik.kmath.chains.Chain
-import scientifik.kmath.chains.collectWithState
-import scientifik.kmath.prob.RandomGenerator
-import scientifik.kmath.prob.samplers.ZigguratNormalizedGaussianSampler
+import kscience.kmath.chains.Chain
+import kscience.kmath.chains.collectWithState
+import kscience.kmath.prob.RandomGenerator
+import kscience.kmath.prob.samplers.ZigguratNormalizedGaussianSampler
 
 data class AveragingChainState(var num: Int = 0, var value: Double = 0.0)
 
@@ -28,4 +28,4 @@ fun main() {
             }
         }
     }
-}
+}

examples/src/main/kotlin/kscience/kmath/operations/BigIntDemo.kt

@@ -0,0 +1,8 @@
+package kscience.kmath.operations
+
+fun main() {
+    val res = BigIntField {
+        number(1) * 2
+    }
+    println("bigint:$res")
+}

examples/src/main/kotlin/kscience/kmath/operations/ComplexDemo.kt

@@ -1,8 +1,8 @@
-package scientifik.kmath.operations
+package kscience.kmath.operations
 
-import scientifik.kmath.structures.NDElement
-import scientifik.kmath.structures.NDField
-import scientifik.kmath.structures.complex
+import kscience.kmath.structures.NDElement
+import kscience.kmath.structures.NDField
+import kscience.kmath.structures.complex
 
 fun main() {
     val element = NDElement.complex(2, 2) { index: IntArray ->

examples/src/main/kotlin/kscience/kmath/structures/ComplexND.kt

@@ -1,9 +1,9 @@
-package scientifik.kmath.structures
+package kscience.kmath.structures
 
-import scientifik.kmath.linear.transpose
-import scientifik.kmath.operations.Complex
-import scientifik.kmath.operations.ComplexField
-import scientifik.kmath.operations.invoke
+import kscience.kmath.linear.transpose
+import kscience.kmath.operations.Complex
+import kscience.kmath.operations.ComplexField
+import kscience.kmath.operations.invoke
 import kotlin.system.measureTimeMillis
 
 fun main() {

examples/src/main/kotlin/kscience/kmath/structures/NDField.kt

@@ -1,9 +1,8 @@
-package scientifik.kmath.structures
+package kscience.kmath.structures
 
 import kotlinx.coroutines.GlobalScope
-import scientifik.kmath.operations.RealField
-import scientifik.kmath.operations.invoke
-import kotlin.contracts.ExperimentalContracts
+import kscience.kmath.operations.RealField
+import kscience.kmath.operations.invoke
 import kotlin.contracts.InvocationKind
 import kotlin.contracts.contract
 import kotlin.system.measureTimeMillis

examples/src/main/kotlin/kscience/kmath/structures/StructureReadBenchmark.kt

@@ -1,8 +1,8 @@
-package scientifik.kmath.structures
+package kscience.kmath.structures
 
 import kotlin.system.measureTimeMillis
 
-fun main(args: Array<String>) {
+fun main() {
     val n = 6000
 
     val array = DoubleArray(n * n) { 1.0 }

examples/src/main/kotlin/kscience/kmath/structures/StructureWriteBenchmark.kt

@@ -1,10 +1,8 @@
-package scientifik.kmath.structures
+package kscience.kmath.structures
 
 import kotlin.system.measureTimeMillis
 
-
-fun main(args: Array<String>) {
-
+fun main() {
     val n = 6000
 
     val structure = NDStructure.build(intArrayOf(n, n), Buffer.Companion::auto) { 1.0 }

examples/src/main/kotlin/kscience/kmath/structures/typeSafeDimensions.kt

@@ -1,10 +1,10 @@
-package scientifik.kmath.structures
+package kscience.kmath.structures
 
-import scientifik.kmath.dimensions.D2
-import scientifik.kmath.dimensions.D3
-import scientifik.kmath.dimensions.DMatrixContext
-import scientifik.kmath.dimensions.Dimension
-import scientifik.kmath.operations.RealField
+import kscience.kmath.dimensions.D2
+import kscience.kmath.dimensions.D3
+import kscience.kmath.dimensions.DMatrixContext
+import kscience.kmath.dimensions.Dimension
+import kscience.kmath.operations.RealField
 
 fun DMatrixContext<Double, RealField>.simple() {
     val m1 = produce<D2, D3> { i, j -> (i + j).toDouble() }

examples/src/main/kotlin/scientifik/kmath/ast/ExpressionsInterpretersBenchmark.kt

@@ -1,70 +0,0 @@
-package scientifik.kmath.ast
-
-import scientifik.kmath.asm.compile
-import scientifik.kmath.expressions.Expression
-import scientifik.kmath.expressions.expressionInField
-import scientifik.kmath.expressions.invoke
-import scientifik.kmath.operations.Field
-import scientifik.kmath.operations.RealField
-import kotlin.random.Random
-import kotlin.system.measureTimeMillis
-
-class ExpressionsInterpretersBenchmark {
-    private val algebra: Field<Double> = RealField
-    fun functionalExpression() {
-        val expr = algebra.expressionInField {
-            variable("x") * const(2.0) + const(2.0) / variable("x") - const(16.0)
-        }
-
-        invokeAndSum(expr)
-    }
-
-    fun mstExpression() {
-        val expr = algebra.mstInField {
-            symbol("x") * number(2.0) + number(2.0) / symbol("x") - number(16.0)
-        }
-
-        invokeAndSum(expr)
-    }
-
-    fun asmExpression() {
-        val expr = algebra.mstInField {
-            symbol("x") * number(2.0) + number(2.0) / symbol("x") - number(16.0)
-        }.compile()
-
-        invokeAndSum(expr)
-    }
-
-    private fun invokeAndSum(expr: Expression<Double>) {
-        val random = Random(0)
-        var sum = 0.0
-
-        repeat(1000000) {
-            sum += expr("x" to random.nextDouble())
-        }
-
-        println(sum)
-    }
-}
-
-fun main() {
-    val benchmark = ExpressionsInterpretersBenchmark()
-
-    val fe = measureTimeMillis {
-        benchmark.functionalExpression()
-    }
-
-    println("fe=$fe")
-
-    val mst = measureTimeMillis {
-        benchmark.mstExpression()
-    }
-
-    println("mst=$mst")
-
-    val asm = measureTimeMillis {
-        benchmark.asmExpression()
-    }
-
-    println("asm=$asm")
-}

examples/src/main/kotlin/scientifik/kmath/linear/LinearAlgebraBenchmark.kt

@@ -1,55 +0,0 @@
-package scientifik.kmath.linear
-
-import koma.matrix.ejml.EJMLMatrixFactory
-import scientifik.kmath.commons.linear.CMMatrixContext
-import scientifik.kmath.commons.linear.inverse
-import scientifik.kmath.commons.linear.toCM
-import scientifik.kmath.operations.RealField
-import scientifik.kmath.operations.invoke
-import scientifik.kmath.structures.Matrix
-import kotlin.contracts.ExperimentalContracts
-import kotlin.random.Random
-import kotlin.system.measureTimeMillis
-
-@ExperimentalContracts
-fun main() {
-    val random = Random(1224)
-    val dim = 100
-    //creating invertible matrix
-    val u = Matrix.real(dim, dim) { i, j -> if (i <= j) random.nextDouble() else 0.0 }
-    val l = Matrix.real(dim, dim) { i, j -> if (i >= j) random.nextDouble() else 0.0 }
-    val matrix = l dot u
-
-    val n = 5000 // iterations
-
-    MatrixContext.real {
-        repeat(50) { val res = inverse(matrix) }
-        val inverseTime = measureTimeMillis { repeat(n) { val res = inverse(matrix) } }
-        println("[kmath] Inversion of $n matrices $dim x $dim finished in $inverseTime millis")
-    }
-
-    //commons-math
-
-    val commonsTime = measureTimeMillis {
-        CMMatrixContext {
-            val cm = matrix.toCM()             //avoid overhead on conversion
-            repeat(n) { val res = inverse(cm) }
-        }
-    }
-
-
-    println("[commons-math] Inversion of $n matrices $dim x $dim finished in $commonsTime millis")
-
-    //koma-ejml
-
-    val komaTime = measureTimeMillis {
-        (KomaMatrixContext(EJMLMatrixFactory(), RealField)) {
-            val km = matrix.toKoma()      //avoid overhead on conversion
-            repeat(n) {
-                val res = inverse(km)
-            }
-        }
-    }
-
-    println("[koma-ejml] Inversion of $n matrices $dim x $dim finished in $komaTime millis")
-}

examples/src/main/kotlin/scientifik/kmath/linear/MultiplicationBenchmark.kt

@@ -1,49 +0,0 @@
-package scientifik.kmath.linear
-
-import koma.matrix.ejml.EJMLMatrixFactory
-import scientifik.kmath.commons.linear.CMMatrixContext
-import scientifik.kmath.commons.linear.toCM
-import scientifik.kmath.operations.RealField
-import scientifik.kmath.operations.invoke
-import scientifik.kmath.structures.Matrix
-import kotlin.random.Random
-import kotlin.system.measureTimeMillis
-
-fun main() {
-    val random = Random(12224)
-    val dim = 1000
-    //creating invertible matrix
-    val matrix1 = Matrix.real(dim, dim) { i, j -> if (i <= j) random.nextDouble() else 0.0 }
-    val matrix2 = Matrix.real(dim, dim) { i, j -> if (i <= j) random.nextDouble() else 0.0 }
-
-//    //warmup
-//    matrix1 dot matrix2
-
-    CMMatrixContext {
-        val cmMatrix1 = matrix1.toCM()
-        val cmMatrix2 = matrix2.toCM()
-
-        val cmTime = measureTimeMillis {
-            cmMatrix1 dot cmMatrix2
-        }
-
-        println("CM implementation time: $cmTime")
-    }
-
-    (KomaMatrixContext(EJMLMatrixFactory(), RealField)) {
-        val komaMatrix1 = matrix1.toKoma()
-        val komaMatrix2 = matrix2.toKoma()
-
-        val komaTime = measureTimeMillis {
-            komaMatrix1 dot komaMatrix2
-        }
-
-        println("Koma-ejml implementation time: $komaTime")
-    }
-
-    val genericTime = measureTimeMillis {
-        val res = matrix1 dot matrix2
-    }
-
-    println("Generic implementation time: $genericTime")
-}

gradle/wrapper/gradle-wrapper.properties

@@ -1,5 +1,5 @@
 distributionBase=GRADLE_USER_HOME
 distributionPath=wrapper/dists
-distributionUrl=https\://services.gradle.org/distributions/gradle-6.5.1-bin.zip
+distributionUrl=https\://services.gradle.org/distributions/gradle-6.6.1-bin.zip
 zipStoreBase=GRADLE_USER_HOME
 zipStorePath=wrapper/dists

gradlew

@@ -130,7 +130,7 @@ fi
 if [ "$cygwin" = "true" -o "$msys" = "true" ] ; then
     APP_HOME=`cygpath --path --mixed "$APP_HOME"`
     CLASSPATH=`cygpath --path --mixed "$CLASSPATH"`
-    
+
     JAVACMD=`cygpath --unix "$JAVACMD"`
 
     # We build the pattern for arguments to be converted via cygpath

gradlew.bat

@@ -40,7 +40,7 @@ if defined JAVA_HOME goto findJavaFromJavaHome
 
 set JAVA_EXE=java.exe
 %JAVA_EXE% -version >NUL 2>&1
-if "%ERRORLEVEL%" == "0" goto init
+if "%ERRORLEVEL%" == "0" goto execute
 
 echo.
 echo ERROR: JAVA_HOME is not set and no 'java' command could be found in your PATH.
@@ -54,7 +54,7 @@ goto fail
 set JAVA_HOME=%JAVA_HOME:"=%
 set JAVA_EXE=%JAVA_HOME%/bin/java.exe
 
-if exist "%JAVA_EXE%" goto init
+if exist "%JAVA_EXE%" goto execute
 
 echo.
 echo ERROR: JAVA_HOME is set to an invalid directory: %JAVA_HOME%
@@ -64,21 +64,6 @@ echo location of your Java installation.
 
 goto fail
 
-:init
-@rem Get command-line arguments, handling Windows variants
-
-if not "%OS%" == "Windows_NT" goto win9xME_args
-
-:win9xME_args
-@rem Slurp the command line arguments.
-set CMD_LINE_ARGS=
-set _SKIP=2
-
-:win9xME_args_slurp
-if "x%~1" == "x" goto execute
-
-set CMD_LINE_ARGS=%*
-
 :execute
 @rem Setup the command line
 
@@ -86,7 +71,7 @@ set CLASSPATH=%APP_HOME%\gradle\wrapper\gradle-wrapper.jar
 
 
 @rem Execute Gradle
-"%JAVA_EXE%" %DEFAULT_JVM_OPTS% %JAVA_OPTS% %GRADLE_OPTS% "-Dorg.gradle.appname=%APP_BASE_NAME%" -classpath "%CLASSPATH%" org.gradle.wrapper.GradleWrapperMain %CMD_LINE_ARGS%
+"%JAVA_EXE%" %DEFAULT_JVM_OPTS% %JAVA_OPTS% %GRADLE_OPTS% "-Dorg.gradle.appname=%APP_BASE_NAME%" -classpath "%CLASSPATH%" org.gradle.wrapper.GradleWrapperMain %*
 
 :end
 @rem End local scope for the variables with windows NT shell

kmath-ast/README.md

@@ -8,32 +8,32 @@ This subproject implements the following features:
 - Evaluating expressions by traversing MST.
 
 > #### Artifact:
-> This module is distributed in the artifact `scientifik:kmath-ast:0.1.4-dev-8`.
+> This module is distributed in the artifact `kscience.kmath:kmath-ast:0.1.4-dev-8`.
 > 
 > **Gradle:**
 >
 > ```gradle
 > repositories {
->     maven { url 'https://dl.bintray.com/mipt-npm/scientifik' }
+>     maven { url 'https://dl.bintray.com/mipt-npm/kscience' }
 >     maven { url 'https://dl.bintray.com/mipt-npm/dev' }
 >     maven { url https://dl.bintray.com/hotkeytlt/maven' }
 > }
 > 
 > dependencies {
->     implementation 'scientifik:kmath-ast:0.1.4-dev-8'
+>     implementation 'kscience.kmath:kmath-ast:0.1.4-dev-8'
 > }
 > ```
 > **Gradle Kotlin DSL:**
 >
 > ```kotlin
 > repositories {
->     maven("https://dl.bintray.com/mipt-npm/scientifik")
+>     maven("https://dl.bintray.com/mipt-npm/kscience")
 >     maven("https://dl.bintray.com/mipt-npm/dev")
 >     maven("https://dl.bintray.com/hotkeytlt/maven")
 > }
 > 
 > dependencies {
->     implementation("scientifik:kmath-ast:0.1.4-dev-8")
+>     implementation("kscience.kmath:kmath-ast:0.1.4-dev-8")
 > }
 > ```
 >
@@ -52,12 +52,12 @@ RealField.mstInField { symbol("x") + 2 }.compile()
 … leads to generation of bytecode, which can be decompiled to the following Java class: 
 
 ```java
-package scientifik.kmath.asm.generated;
+package kscience.kmath.asm.generated;
 
 import java.util.Map;
-import scientifik.kmath.asm.internal.MapIntrinsics;
-import scientifik.kmath.expressions.Expression;
-import scientifik.kmath.operations.RealField;
+import kscience.kmath.asm.internal.MapIntrinsics;
+import kscience.kmath.expressions.Expression;
+import kscience.kmath.operations.RealField;
 
 public final class AsmCompiledExpression_1073786867_0 implements Expression<Double> {
     private final RealField algebra;

kmath-ast/build.gradle.kts

@@ -1,12 +1,11 @@
-plugins { id("scientifik.mpp") }
+plugins {
+    id("ru.mipt.npm.mpp")
+}
 
 kotlin.sourceSets {
-    all { languageSettings.useExperimentalAnnotation("kotlin.contracts.ExperimentalContracts") }
-
     commonMain {
         dependencies {
             api(project(":kmath-core"))
-            implementation("com.github.h0tk3y.betterParse:better-parse:0.4.0")
         }
     }
 
@@ -14,7 +13,8 @@ kotlin.sourceSets {
         dependencies {
             implementation("org.ow2.asm:asm:8.0.1")
             implementation("org.ow2.asm:asm-commons:8.0.1")
+            implementation("com.github.h0tk3y.betterParse:better-parse:0.4.0")
             implementation(kotlin("reflect"))
         }
     }
-}
+}

kmath-ast/src/commonMain/kotlin/kscience/kmath/ast/MST.kt

@@ -1,26 +1,28 @@
-package scientifik.kmath.ast
+package kscience.kmath.ast
 
-import scientifik.kmath.operations.Algebra
-import scientifik.kmath.operations.NumericAlgebra
-import scientifik.kmath.operations.RealField
+import kscience.kmath.operations.Algebra
+import kscience.kmath.operations.NumericAlgebra
+import kscience.kmath.operations.RealField
 
 /**
  * A Mathematical Syntax Tree node for mathematical expressions.
+ *
+ * @author Alexander Nozik
  */
-sealed class MST {
+public sealed class MST {
     /**
      * A node containing raw string.
      *
      * @property value the value of this node.
      */
-    data class Symbolic(val value: String) : MST()
+    public data class Symbolic(val value: String) : MST()
 
     /**
      * A node containing a numeric value or scalar.
      *
      * @property value the value of this number.
      */
-    data class Numeric(val value: Number) : MST()
+    public data class Numeric(val value: Number) : MST()
 
     /**
      * A node containing an unary operation.
@@ -28,9 +30,7 @@ sealed class MST {
      * @property operation the identifier of operation.
      * @property value the argument of this operation.
      */
-    data class Unary(val operation: String, val value: MST) : MST() {
-        companion object
-    }
+    public data class Unary(val operation: String, val value: MST) : MST()
 
     /**
      * A node containing binary operation.
@@ -39,9 +39,7 @@ sealed class MST {
      * @property left the left operand.
      * @property right the right operand.
      */
-    data class Binary(val operation: String, val left: MST, val right: MST) : MST() {
-        companion object
-    }
+    public data class Binary(val operation: String, val left: MST, val right: MST) : MST()
 }
 
 // TODO add a function with named arguments
@@ -52,8 +50,9 @@ sealed class MST {
  * @receiver the algebra that provides operations.
  * @param node the node to evaluate.
  * @return the value of expression.
+ * @author Alexander Nozik
  */
-fun <T> Algebra<T>.evaluate(node: MST): T = when (node) {
+public fun <T> Algebra<T>.evaluate(node: MST): T = when (node) {
     is MST.Numeric -> (this as? NumericAlgebra<T>)?.number(node.value)
         ?: error("Numeric nodes are not supported by $this")
     is MST.Symbolic -> symbol(node.value)
@@ -84,4 +83,4 @@ fun <T> Algebra<T>.evaluate(node: MST): T = when (node) {
  * @param algebra the algebra that provides operations.
  * @return the value of expression.
  */
-fun <T> MST.interpret(algebra: Algebra<T>): T = algebra.evaluate(this)
+public fun <T> MST.interpret(algebra: Algebra<T>): T = algebra.evaluate(this)

kmath-ast/src/commonMain/kotlin/kscience/kmath/ast/MstAlgebra.kt

@@ -1,11 +1,11 @@
-package scientifik.kmath.ast
+package kscience.kmath.ast
 
-import scientifik.kmath.operations.*
+import kscience.kmath.operations.*
 
 /**
  * [Algebra] over [MST] nodes.
  */
-object MstAlgebra : NumericAlgebra<MST> {
+public object MstAlgebra : NumericAlgebra<MST> {
     override fun number(value: Number): MST = MST.Numeric(value)
 
     override fun symbol(value: String): MST = MST.Symbolic(value)
@@ -20,7 +20,7 @@ object MstAlgebra : NumericAlgebra<MST> {
 /**
  * [Space] over [MST] nodes.
  */
-object MstSpace : Space<MST>, NumericAlgebra<MST> {
+public object MstSpace : Space<MST>, NumericAlgebra<MST> {
     override val zero: MST = number(0.0)
 
     override fun number(value: Number): MST = MstAlgebra.number(value)
@@ -37,8 +37,9 @@ object MstSpace : Space<MST>, NumericAlgebra<MST> {
 /**
  * [Ring] over [MST] nodes.
  */
-object MstRing : Ring<MST>, NumericAlgebra<MST> {
-    override val zero: MST = number(0.0)
+public object MstRing : Ring<MST>, NumericAlgebra<MST> {
+    override val zero: MST
+        get() = MstSpace.zero
     override val one: MST = number(1.0)
 
     override fun number(value: Number): MST = MstSpace.number(value)
@@ -58,18 +59,21 @@ object MstRing : Ring<MST>, NumericAlgebra<MST> {
 /**
  * [Field] over [MST] nodes.
  */
-object MstField : Field<MST> {
-    override val zero: MST = number(0.0)
-    override val one: MST = number(1.0)
+public object MstField : Field<MST> {
+    public override val zero: MST
+        get() = MstRing.zero
 
-    override fun symbol(value: String): MST = MstRing.symbol(value)
-    override fun number(value: Number): MST = MstRing.number(value)
-    override fun add(a: MST, b: MST): MST = MstRing.add(a, b)
-    override fun multiply(a: MST, k: Number): MST = MstRing.multiply(a, k)
-    override fun multiply(a: MST, b: MST): MST = MstRing.multiply(a, b)
-    override fun divide(a: MST, b: MST): MST = binaryOperation(FieldOperations.DIV_OPERATION, a, b)
+    public override val one: MST
+        get() = MstRing.one
 
-    override fun binaryOperation(operation: String, left: MST, right: MST): MST =
+    public override fun symbol(value: String): MST = MstRing.symbol(value)
+    public override fun number(value: Number): MST = MstRing.number(value)
+    public override fun add(a: MST, b: MST): MST = MstRing.add(a, b)
+    public override fun multiply(a: MST, k: Number): MST = MstRing.multiply(a, k)
+    public override fun multiply(a: MST, b: MST): MST = MstRing.multiply(a, b)
+    public override fun divide(a: MST, b: MST): MST = binaryOperation(FieldOperations.DIV_OPERATION, a, b)
+
+    public override fun binaryOperation(operation: String, left: MST, right: MST): MST =
         MstRing.binaryOperation(operation, left, right)
 
     override fun unaryOperation(operation: String, arg: MST): MST = MstRing.unaryOperation(operation, arg)
@@ -78,15 +82,26 @@ object MstField : Field<MST> {
 /**
  * [ExtendedField] over [MST] nodes.
  */
-object MstExtendedField : ExtendedField<MST> {
-    override val zero: MST = number(0.0)
-    override val one: MST = number(1.0)
+public object MstExtendedField : ExtendedField<MST> {
+    override val zero: MST
+        get() = MstField.zero
 
+    override val one: MST
+        get() = MstField.one
+
+    override fun symbol(value: String): MST = MstField.symbol(value)
     override fun sin(arg: MST): MST = unaryOperation(TrigonometricOperations.SIN_OPERATION, arg)
     override fun cos(arg: MST): MST = unaryOperation(TrigonometricOperations.COS_OPERATION, arg)
+    override fun tan(arg: MST): MST = unaryOperation(TrigonometricOperations.TAN_OPERATION, arg)
     override fun asin(arg: MST): MST = unaryOperation(TrigonometricOperations.ASIN_OPERATION, arg)
     override fun acos(arg: MST): MST = unaryOperation(TrigonometricOperations.ACOS_OPERATION, arg)
     override fun atan(arg: MST): MST = unaryOperation(TrigonometricOperations.ATAN_OPERATION, arg)
+    override fun sinh(arg: MST): MST = unaryOperation(HyperbolicOperations.SINH_OPERATION, arg)
+    override fun cosh(arg: MST): MST = unaryOperation(HyperbolicOperations.COSH_OPERATION, arg)
+    override fun tanh(arg: MST): MST = unaryOperation(HyperbolicOperations.TANH_OPERATION, arg)
+    override fun asinh(arg: MST): MST = unaryOperation(HyperbolicOperations.ASINH_OPERATION, arg)
+    override fun acosh(arg: MST): MST = unaryOperation(HyperbolicOperations.ACOSH_OPERATION, arg)
+    override fun atanh(arg: MST): MST = unaryOperation(HyperbolicOperations.ATANH_OPERATION, arg)
     override fun add(a: MST, b: MST): MST = MstField.add(a, b)
     override fun multiply(a: MST, k: Number): MST = MstField.multiply(a, k)
     override fun multiply(a: MST, b: MST): MST = MstField.multiply(a, b)

kmath-ast/src/commonMain/kotlin/kscience/kmath/ast/MstExpression.kt

@@ -1,8 +1,7 @@
-package scientifik.kmath.ast
+package kscience.kmath.ast
 
-import scientifik.kmath.expressions.*
-import scientifik.kmath.operations.*
-import kotlin.contracts.ExperimentalContracts
+import kscience.kmath.expressions.*
+import kscience.kmath.operations.*
 import kotlin.contracts.InvocationKind
 import kotlin.contracts.contract
 
@@ -12,8 +11,9 @@ import kotlin.contracts.contract
  *
  * @property algebra the algebra that provides operations.
  * @property mst the [MST] node.
+ * @author Alexander Nozik
  */
-class MstExpression<T>(val algebra: Algebra<T>, val mst: MST) : Expression<T> {
+public class MstExpression<T>(public val algebra: Algebra<T>, public val mst: MST) : Expression<T> {
     private inner class InnerAlgebra(val arguments: Map<String, T>) : NumericAlgebra<T> {
         override fun symbol(value: String): T = arguments[value] ?: algebra.symbol(value)
         override fun unaryOperation(operation: String, arg: T): T = algebra.unaryOperation(operation, arg)
@@ -32,72 +32,92 @@ class MstExpression<T>(val algebra: Algebra<T>, val mst: MST) : Expression<T> {
 
 /**
  * Builds [MstExpression] over [Algebra].
+ *
+ * @author Alexander Nozik
  */
-inline fun <reified T : Any, A : Algebra<T>, E : Algebra<MST>> A.mst(
+public inline fun <reified T : Any, A : Algebra<T>, E : Algebra<MST>> A.mst(
     mstAlgebra: E,
     block: E.() -> MST
 ): MstExpression<T> = MstExpression(this, mstAlgebra.block())
 
 /**
  * Builds [MstExpression] over [Space].
+ *
+ * @author Alexander Nozik
  */
-inline fun <reified T : Any> Space<T>.mstInSpace(block: MstSpace.() -> MST): MstExpression<T> {
+public inline fun <reified T : Any> Space<T>.mstInSpace(block: MstSpace.() -> MST): MstExpression<T> {
     contract { callsInPlace(block, InvocationKind.EXACTLY_ONCE) }
     return MstExpression(this, MstSpace.block())
 }
 
 /**
  * Builds [MstExpression] over [Ring].
+ *
+ * @author Alexander Nozik
  */
-inline fun <reified T : Any> Ring<T>.mstInRing(block: MstRing.() -> MST): MstExpression<T> {
+public inline fun <reified T : Any> Ring<T>.mstInRing(block: MstRing.() -> MST): MstExpression<T> {
     contract { callsInPlace(block, InvocationKind.EXACTLY_ONCE) }
     return MstExpression(this, MstRing.block())
 }
 
 /**
  * Builds [MstExpression] over [Field].
+ *
+ * @author Alexander Nozik
  */
-inline fun <reified T : Any> Field<T>.mstInField(block: MstField.() -> MST): MstExpression<T> {
+public inline fun <reified T : Any> Field<T>.mstInField(block: MstField.() -> MST): MstExpression<T> {
     contract { callsInPlace(block, InvocationKind.EXACTLY_ONCE) }
     return MstExpression(this, MstField.block())
 }
 
 /**
  * Builds [MstExpression] over [ExtendedField].
+ *
+ * @author Iaroslav Postovalov
  */
-inline fun <reified T : Any> Field<T>.mstInExtendedField(block: MstExtendedField.() -> MST): MstExpression<T> {
+public inline fun <reified T : Any> Field<T>.mstInExtendedField(block: MstExtendedField.() -> MST): MstExpression<T> {
     contract { callsInPlace(block, InvocationKind.EXACTLY_ONCE) }
     return MstExpression(this, MstExtendedField.block())
 }
 
 /**
  * Builds [MstExpression] over [FunctionalExpressionSpace].
+ *
+ * @author Alexander Nozik
  */
-inline fun <reified T : Any, A : Space<T>> FunctionalExpressionSpace<T, A>.mstInSpace(block: MstSpace.() -> MST): MstExpression<T> {
+public inline fun <reified T : Any, A : Space<T>> FunctionalExpressionSpace<T, A>.mstInSpace(block: MstSpace.() -> MST): MstExpression<T> {
     contract { callsInPlace(block, InvocationKind.EXACTLY_ONCE) }
     return algebra.mstInSpace(block)
 }
 
 /**
  * Builds [MstExpression] over [FunctionalExpressionRing].
+ *
+ * @author Alexander Nozik
  */
-inline fun <reified T : Any, A : Ring<T>> FunctionalExpressionRing<T, A>.mstInRing(block: MstRing.() -> MST): MstExpression<T> {
+public inline fun <reified T : Any, A : Ring<T>> FunctionalExpressionRing<T, A>.mstInRing(block: MstRing.() -> MST): MstExpression<T> {
     contract { callsInPlace(block, InvocationKind.EXACTLY_ONCE) }
     return algebra.mstInRing(block)
 }
 
 /**
  * Builds [MstExpression] over [FunctionalExpressionField].
+ *
+ * @author Alexander Nozik
  */
-inline fun <reified T : Any, A : Field<T>> FunctionalExpressionField<T, A>.mstInField(block: MstField.() -> MST): MstExpression<T> {
+public inline fun <reified T : Any, A : Field<T>> FunctionalExpressionField<T, A>.mstInField(block: MstField.() -> MST): MstExpression<T> {
     contract { callsInPlace(block, InvocationKind.EXACTLY_ONCE) }
     return algebra.mstInField(block)
 }
 
 /**
  * Builds [MstExpression] over [FunctionalExpressionExtendedField].
+ *
+ * @author Iaroslav Postovalov
  */
-inline fun <reified T : Any, A : ExtendedField<T>> FunctionalExpressionExtendedField<T, A>.mstInExtendedField(block: MstExtendedField.() -> MST): MstExpression<T> {
+public inline fun <reified T : Any, A : ExtendedField<T>> FunctionalExpressionExtendedField<T, A>.mstInExtendedField(
+    block: MstExtendedField.() -> MST
+): MstExpression<T> {
     contract { callsInPlace(block, InvocationKind.EXACTLY_ONCE) }
     return algebra.mstInExtendedField(block)
 }

kmath-ast/src/jvmMain/kotlin/kscience/kmath/asm/asm.kt

@@ -0,0 +1,71 @@
+package kscience.kmath.asm
+
+import kscience.kmath.asm.internal.AsmBuilder
+import kscience.kmath.asm.internal.MstType
+import kscience.kmath.asm.internal.buildAlgebraOperationCall
+import kscience.kmath.asm.internal.buildName
+import kscience.kmath.ast.MST
+import kscience.kmath.ast.MstExpression
+import kscience.kmath.expressions.Expression
+import kscience.kmath.operations.Algebra
+import kotlin.reflect.KClass
+
+/**
+ * Compiles given MST to an Expression using AST compiler.
+ *
+ * @param type the target type.
+ * @param algebra the target algebra.
+ * @return the compiled expression.
+ * @author Alexander Nozik
+ */
+public fun <T : Any> MST.compileWith(type: KClass<T>, algebra: Algebra<T>): Expression<T> {
+    fun AsmBuilder<T>.visit(node: MST): Unit = when (node) {
+        is MST.Symbolic -> {
+            val symbol = try {
+                algebra.symbol(node.value)
+            } catch (ignored: Throwable) {
+                null
+            }
+
+            if (symbol != null)
+                loadTConstant(symbol)
+            else
+                loadVariable(node.value)
+        }
+
+        is MST.Numeric -> loadNumeric(node.value)
+
+        is MST.Unary -> buildAlgebraOperationCall(
+            context = algebra,
+            name = node.operation,
+            fallbackMethodName = "unaryOperation",
+            parameterTypes = arrayOf(MstType.fromMst(node.value))
+        ) { visit(node.value) }
+
+        is MST.Binary -> buildAlgebraOperationCall(
+            context = algebra,
+            name = node.operation,
+            fallbackMethodName = "binaryOperation",
+            parameterTypes = arrayOf(MstType.fromMst(node.left), MstType.fromMst(node.right))
+        ) {
+            visit(node.left)
+            visit(node.right)
+        }
+    }
+
+    return AsmBuilder(type, algebra, buildName(this)) { visit(this@compileWith) }.getInstance()
+}
+
+/**
+ * Compiles an [MST] to ASM using given algebra.
+ *
+ * @author Alexander Nozik.
+ */
+public inline fun <reified T : Any> Algebra<T>.expression(mst: MST): Expression<T> = mst.compileWith(T::class, this)
+
+/**
+ * Optimizes performance of an [MstExpression] using ASM codegen.
+ *
+ * @author Alexander Nozik.
+ */
+public inline fun <reified T : Any> MstExpression<T>.compile(): Expression<T> = mst.compileWith(T::class, algebra)

kmath-ast/src/jvmMain/kotlin/kscience/kmath/asm/internal/AsmBuilder.kt

@@ -1,13 +1,13 @@
-package scientifik.kmath.asm.internal
+package kscience.kmath.asm.internal
 
+import kscience.kmath.asm.internal.AsmBuilder.ClassLoader
+import kscience.kmath.ast.MST
+import kscience.kmath.expressions.Expression
+import kscience.kmath.operations.Algebra
+import kscience.kmath.operations.NumericAlgebra
 import org.objectweb.asm.*
 import org.objectweb.asm.Opcodes.*
 import org.objectweb.asm.commons.InstructionAdapter
-import scientifik.kmath.asm.internal.AsmBuilder.ClassLoader
-import scientifik.kmath.ast.MST
-import scientifik.kmath.expressions.Expression
-import scientifik.kmath.operations.Algebra
-import scientifik.kmath.operations.NumericAlgebra
 import java.util.*
 import java.util.stream.Collectors
 import kotlin.reflect.KClass
@@ -20,6 +20,7 @@ import kotlin.reflect.KClass
  * @property algebra the algebra the applied AsmExpressions use.
  * @property className the unique class name of new loaded class.
  * @property invokeLabel0Visitor the function to apply to this object when generating invoke method, label 0.
+ * @author Iaroslav Postovalov
  */
 internal class AsmBuilder<T> internal constructor(
     private val classOfT: KClass<*>,
@@ -563,6 +564,6 @@ internal class AsmBuilder<T> internal constructor(
         /**
          * ASM type for MapIntrinsics.
          */
-        internal val MAP_INTRINSICS_TYPE: Type by lazy { Type.getObjectType("scientifik/kmath/asm/internal/MapIntrinsics") }
+        internal val MAP_INTRINSICS_TYPE: Type by lazy { Type.getObjectType("kscience/kmath/asm/internal/MapIntrinsics") }
     }
 }

kmath-ast/src/jvmMain/kotlin/kscience/kmath/asm/internal/MstType.kt

@@ -1,7 +1,10 @@
-package scientifik.kmath.asm.internal
+package kscience.kmath.asm.internal
 
-import scientifik.kmath.ast.MST
+import kscience.kmath.ast.MST
 
+/**
+ * Represents types known in [MST], numbers and general values.
+ */
 internal enum class MstType {
     GENERAL,
     NUMBER;

kmath-ast/src/jvmMain/kotlin/kscience/kmath/asm/internal/codegenUtils.kt

@@ -1,33 +1,42 @@
-package scientifik.kmath.asm.internal
+package kscience.kmath.asm.internal
 
+import kscience.kmath.ast.MST
+import kscience.kmath.expressions.Expression
+import kscience.kmath.operations.Algebra
+import kscience.kmath.operations.FieldOperations
+import kscience.kmath.operations.RingOperations
+import kscience.kmath.operations.SpaceOperations
 import org.objectweb.asm.*
 import org.objectweb.asm.Opcodes.INVOKEVIRTUAL
 import org.objectweb.asm.commons.InstructionAdapter
-import scientifik.kmath.ast.MST
-import scientifik.kmath.expressions.Expression
-import scientifik.kmath.operations.Algebra
 import java.lang.reflect.Method
-import kotlin.contracts.ExperimentalContracts
 import kotlin.contracts.InvocationKind
 import kotlin.contracts.contract
 import kotlin.reflect.KClass
 
 private val methodNameAdapters: Map<Pair<String, Int>, String> by lazy {
     hashMapOf(
-        "+" to 2 to "add",
-        "*" to 2 to "multiply",
-        "/" to 2 to "divide",
-        "+" to 1 to "unaryPlus",
-        "-" to 1 to "unaryMinus",
-        "-" to 2 to "minus"
+        SpaceOperations.PLUS_OPERATION to 2 to "add",
+        RingOperations.TIMES_OPERATION to 2 to "multiply",
+        FieldOperations.DIV_OPERATION to 2 to "divide",
+        SpaceOperations.PLUS_OPERATION to 1 to "unaryPlus",
+        SpaceOperations.MINUS_OPERATION to 1 to "unaryMinus",
+        SpaceOperations.MINUS_OPERATION to 2 to "minus"
     )
 }
 
+/**
+ * Returns ASM [Type] for given [KClass].
+ *
+ * @author Iaroslav Postovalov
+ */
 internal val KClass<*>.asm: Type
     get() = Type.getType(java)
 
 /**
  * Returns singleton array with this value if the [predicate] is true, returns empty array otherwise.
+ *
+ * @author Iaroslav Postovalov
  */
 internal inline fun <reified T> T.wrapToArrayIf(predicate: (T) -> Boolean): Array<T> {
     contract { callsInPlace(predicate, InvocationKind.EXACTLY_ONCE) }
@@ -36,11 +45,15 @@ internal inline fun <reified T> T.wrapToArrayIf(predicate: (T) -> Boolean): Arra
 
 /**
  * Creates an [InstructionAdapter] from this [MethodVisitor].
+ *
+ * @author Iaroslav Postovalov
  */
 private fun MethodVisitor.instructionAdapter(): InstructionAdapter = InstructionAdapter(this)
 
 /**
  * Creates an [InstructionAdapter] from this [MethodVisitor] and applies [block] to it.
+ *
+ * @author Iaroslav Postovalov
  */
 internal inline fun MethodVisitor.instructionAdapter(block: InstructionAdapter.() -> Unit): InstructionAdapter {
     contract { callsInPlace(block, InvocationKind.EXACTLY_ONCE) }
@@ -49,6 +62,8 @@ internal inline fun MethodVisitor.instructionAdapter(block: InstructionAdapter.(
 
 /**
  * Constructs a [Label], then applies it to this visitor.
+ *
+ * @author Iaroslav Postovalov
  */
 internal fun MethodVisitor.label(): Label = Label().also { visitLabel(it) }
 
@@ -57,9 +72,11 @@ internal fun MethodVisitor.label(): Label = Label().also { visitLabel(it) }
  *
  * This methods helps to avoid collisions of class name to prevent loading several classes with the same name. If there
  * is a colliding class, change [collision] parameter or leave it `0` to check existing classes recursively.
+ *
+ * @author Iaroslav Postovalov
  */
 internal tailrec fun buildName(mst: MST, collision: Int = 0): String {
-    val name = "scientifik.kmath.asm.generated.AsmCompiledExpression_${mst.hashCode()}_$collision"
+    val name = "kscience.kmath.asm.generated.AsmCompiledExpression_${mst.hashCode()}_$collision"
 
     try {
         Class.forName(name)
@@ -76,6 +93,11 @@ internal inline fun ClassWriter(flags: Int, block: ClassWriter.() -> Unit): Clas
     return ClassWriter(flags).apply(block)
 }
 
+/**
+ * Invokes [visitField] and applies [block] to the [FieldVisitor].
+ *
+ * @author Iaroslav Postovalov
+ */
 internal inline fun ClassWriter.visitField(
     access: Int,
     name: String,
@@ -105,7 +127,7 @@ private fun <T> AsmBuilder<T>.findSpecific(context: Algebra<T>, name: String, pa
  * Checks if the target [context] for code generation contains a method with needed [name] and arity, also builds
  * type expectation stack for needed arity.
  *
- * @return `true` if contains, else `false`.
+ * @author Iaroslav Postovalov
  */
 private fun <T> AsmBuilder<T>.buildExpectationStack(
     context: Algebra<T>,
@@ -137,7 +159,7 @@ private fun <T> AsmBuilder<T>.mapTypes(method: Method, parameterTypes: Array<Mst
  * Checks if the target [context] for code generation contains a method with needed [name] and arity and inserts
  * [AsmBuilder.invokeAlgebraOperation] of this method.
  *
- * @return `true` if contains, else `false`.
+ * @author Iaroslav Postovalov
  */
 private fun <T> AsmBuilder<T>.tryInvokeSpecific(
     context: Algebra<T>,
@@ -161,7 +183,9 @@ private fun <T> AsmBuilder<T>.tryInvokeSpecific(
 }
 
 /**
- * Builds specialized algebra call with option to fallback to generic algebra operation accepting String.
+ * Builds specialized [context] call with option to fallback to generic algebra operation accepting [String].
+ *
+ * @author Iaroslav Postovalov
  */
 internal inline fun <T> AsmBuilder<T>.buildAlgebraOperationCall(
     context: Algebra<T>,

kmath-ast/src/jvmMain/kotlin/kscience/kmath/asm/internal/mapIntrinsics.kt

@@ -1,7 +1,12 @@
 @file:JvmName("MapIntrinsics")
 
-package scientifik.kmath.asm.internal
+package kscience.kmath.asm.internal
 
+/**
+ * Gets value with given [key] or throws [IllegalStateException] whenever it is not present.
+ *
+ * @author Iaroslav Postovalov
+ */
 @JvmOverloads
 internal fun <K, V> Map<K, V>.getOrFail(key: K, default: V? = null): V =
     this[key] ?: default ?: error("Parameter not found: $key")

kmath-ast/src/jvmMain/kotlin/kscience/kmath/ast/parser.kt

@@ -1,4 +1,4 @@
-package scientifik.kmath.ast
+package kscience.kmath.ast
 
 import com.github.h0tk3y.betterParse.combinators.*
 import com.github.h0tk3y.betterParse.grammar.Grammar
@@ -10,15 +10,16 @@ import com.github.h0tk3y.betterParse.lexer.TokenMatch
 import com.github.h0tk3y.betterParse.lexer.regexToken
 import com.github.h0tk3y.betterParse.parser.ParseResult
 import com.github.h0tk3y.betterParse.parser.Parser
-import scientifik.kmath.operations.FieldOperations
-import scientifik.kmath.operations.PowerOperations
-import scientifik.kmath.operations.RingOperations
-import scientifik.kmath.operations.SpaceOperations
+import kscience.kmath.operations.FieldOperations
+import kscience.kmath.operations.PowerOperations
+import kscience.kmath.operations.RingOperations
+import kscience.kmath.operations.SpaceOperations
 
 /**
- * TODO move to core
+ * TODO move to common after IR version is released
+ * @author Alexander Nozik and Iaroslav Postovalov
  */
-object ArithmeticsEvaluator : Grammar<MST>() {
+public object ArithmeticsEvaluator : Grammar<MST>() {
     // TODO replace with "...".toRegex() when better-parse 0.4.1 is released
     private val num: Token by regexToken("[\\d.]+(?:[eE][-+]?\\d+)?")
     private val id: Token by regexToken("[a-z_A-Z][\\da-z_A-Z]*")
@@ -35,23 +36,23 @@ object ArithmeticsEvaluator : Grammar<MST>() {
     private val number: Parser<MST> by num use { MST.Numeric(text.toDouble()) }
     private val singular: Parser<MST> by id use { MST.Symbolic(text) }
 
-    private val unaryFunction: Parser<MST> by (id and skip(lpar) and parser(::subSumChain) and skip(rpar))
+    private val unaryFunction: Parser<MST> by (id and -lpar and parser(ArithmeticsEvaluator::subSumChain) and -rpar)
         .map { (id, term) -> MST.Unary(id.text, term) }
 
     private val binaryFunction: Parser<MST> by id
-        .and(skip(lpar))
-        .and(parser(::subSumChain))
-        .and(skip(comma))
-        .and(parser(::subSumChain))
-        .and(skip(rpar))
+        .and(-lpar)
+        .and(parser(ArithmeticsEvaluator::subSumChain))
+        .and(-comma)
+        .and(parser(ArithmeticsEvaluator::subSumChain))
+        .and(-rpar)
         .map { (id, left, right) -> MST.Binary(id.text, left, right) }
 
     private val term: Parser<MST> by number
         .or(binaryFunction)
         .or(unaryFunction)
         .or(singular)
-        .or(skip(minus) and parser(::term) map { MST.Unary(SpaceOperations.MINUS_OPERATION, it) })
-        .or(skip(lpar) and parser(::subSumChain) and skip(rpar))
+        .or(-minus and parser(ArithmeticsEvaluator::term) map { MST.Unary(SpaceOperations.MINUS_OPERATION, it) })
+        .or(-lpar and parser(ArithmeticsEvaluator::subSumChain) and -rpar)
 
     private val powChain: Parser<MST> by leftAssociative(term = term, operator = pow) { a, _, b ->
         MST.Binary(PowerOperations.POW_OPERATION, a, b)
@@ -85,13 +86,15 @@ object ArithmeticsEvaluator : Grammar<MST>() {
  *
  * @receiver the string to parse.
  * @return the [MST] node.
+ * @author Alexander Nozik
  */
-fun String.tryParseMath(): ParseResult<MST> = ArithmeticsEvaluator.tryParseToEnd(this)
+public fun String.tryParseMath(): ParseResult<MST> = ArithmeticsEvaluator.tryParseToEnd(this)
 
 /**
  * Parses the string into [MST].
  *
  * @receiver the string to parse.
  * @return the [MST] node.
+ * @author Alexander Nozik
  */
-fun String.parseMath(): MST = ArithmeticsEvaluator.parseToEnd(this)
+public fun String.parseMath(): MST = ArithmeticsEvaluator.parseToEnd(this)

kmath-ast/src/jvmMain/kotlin/scientifik/kmath/asm/asm.kt

@@ -1,64 +0,0 @@
-package scientifik.kmath.asm
-
-import scientifik.kmath.asm.internal.AsmBuilder
-import scientifik.kmath.asm.internal.MstType
-import scientifik.kmath.asm.internal.buildAlgebraOperationCall
-import scientifik.kmath.asm.internal.buildName
-import scientifik.kmath.ast.MST
-import scientifik.kmath.ast.MstExpression
-import scientifik.kmath.expressions.Expression
-import scientifik.kmath.operations.Algebra
-import kotlin.reflect.KClass
-
-/**
- * Compile given MST to an Expression using AST compiler
- */
-fun <T : Any> MST.compileWith(type: KClass<T>, algebra: Algebra<T>): Expression<T> {
-    fun AsmBuilder<T>.visit(node: MST) {
-        when (node) {
-            is MST.Symbolic -> {
-                val symbol = try {
-                    algebra.symbol(node.value)
-                } catch (ignored: Throwable) {
-                    null
-                }
-
-                if (symbol != null)
-                    loadTConstant(symbol)
-                else
-                    loadVariable(node.value)
-            }
-
-            is MST.Numeric -> loadNumeric(node.value)
-
-            is MST.Unary -> buildAlgebraOperationCall(
-                context = algebra,
-                name = node.operation,
-                fallbackMethodName = "unaryOperation",
-                parameterTypes = arrayOf(MstType.fromMst(node.value))
-            ) { visit(node.value) }
-
-            is MST.Binary -> buildAlgebraOperationCall(
-                context = algebra,
-                name = node.operation,
-                fallbackMethodName = "binaryOperation",
-                parameterTypes = arrayOf(MstType.fromMst(node.left), MstType.fromMst(node.right))
-            ) {
-                visit(node.left)
-                visit(node.right)
-            }
-        }
-    }
-
-    return AsmBuilder(type, algebra, buildName(this)) { visit(this@compileWith) }.getInstance()
-}
-
-/**
- * Compile an [MST] to ASM using given algebra
- */
-inline fun <reified T : Any> Algebra<T>.expression(mst: MST): Expression<T> = mst.compileWith(T::class, this)
-
-/**
- * Optimize performance of an [MstExpression] using ASM codegen
- */
-inline fun <reified T : Any> MstExpression<T>.compile(): Expression<T> = mst.compileWith(T::class, algebra)

kmath-ast/src/jvmTest/kotlin/scietifik/kmath/asm/TestAsmAlgebras.kt

@@ -1,12 +1,12 @@
 package scietifik.kmath.asm
 
-import scientifik.kmath.asm.compile
-import scientifik.kmath.ast.mstInField
-import scientifik.kmath.ast.mstInRing
-import scientifik.kmath.ast.mstInSpace
-import scientifik.kmath.expressions.invoke
-import scientifik.kmath.operations.ByteRing
-import scientifik.kmath.operations.RealField
+import kscience.kmath.asm.compile
+import kscience.kmath.ast.mstInField
+import kscience.kmath.ast.mstInRing
+import kscience.kmath.ast.mstInSpace
+import kscience.kmath.expressions.invoke
+import kscience.kmath.operations.ByteRing
+import kscience.kmath.operations.RealField
 import kotlin.test.Test
 import kotlin.test.assertEquals
 

kmath-ast/src/jvmTest/kotlin/scietifik/kmath/asm/TestAsmExpressions.kt

@@ -1,10 +1,10 @@
 package scietifik.kmath.asm
 
-import scientifik.kmath.asm.compile
-import scientifik.kmath.ast.mstInField
-import scientifik.kmath.ast.mstInSpace
-import scientifik.kmath.expressions.invoke
-import scientifik.kmath.operations.RealField
+import kscience.kmath.asm.compile
+import kscience.kmath.ast.mstInField
+import kscience.kmath.ast.mstInSpace
+import kscience.kmath.expressions.invoke
+import kscience.kmath.operations.RealField
 import kotlin.test.Test
 import kotlin.test.assertEquals
 

kmath-ast/src/jvmTest/kotlin/scietifik/kmath/asm/TestAsmSpecialization.kt

@@ -1,9 +1,9 @@
 package scietifik.kmath.asm
 
-import scientifik.kmath.asm.compile
-import scientifik.kmath.ast.mstInField
-import scientifik.kmath.expressions.invoke
-import scientifik.kmath.operations.RealField
+import kscience.kmath.asm.compile
+import kscience.kmath.ast.mstInField
+import kscience.kmath.expressions.invoke
+import kscience.kmath.operations.RealField
 import kotlin.test.Test
 import kotlin.test.assertEquals
 

kmath-ast/src/jvmTest/kotlin/scietifik/kmath/asm/TestAsmVariables.kt

@@ -1,8 +1,8 @@
 package scietifik.kmath.asm
 
-import scientifik.kmath.ast.mstInRing
-import scientifik.kmath.expressions.invoke
-import scientifik.kmath.operations.ByteRing
+import kscience.kmath.ast.mstInRing
+import kscience.kmath.expressions.invoke
+import kscience.kmath.operations.ByteRing
 import kotlin.test.Test
 import kotlin.test.assertEquals
 import kotlin.test.assertFailsWith

kmath-ast/src/jvmTest/kotlin/scietifik/kmath/ast/AsmTest.kt

@@ -1,12 +1,12 @@
 package scietifik.kmath.ast
 
-import scientifik.kmath.asm.compile
-import scientifik.kmath.asm.expression
-import scientifik.kmath.ast.mstInField
-import scientifik.kmath.ast.parseMath
-import scientifik.kmath.expressions.invoke
-import scientifik.kmath.operations.Complex
-import scientifik.kmath.operations.ComplexField
+import kscience.kmath.asm.compile
+import kscience.kmath.asm.expression
+import kscience.kmath.ast.mstInField
+import kscience.kmath.ast.parseMath
+import kscience.kmath.expressions.invoke
+import kscience.kmath.operations.Complex
+import kscience.kmath.operations.ComplexField
 import kotlin.test.Test
 import kotlin.test.assertEquals
 

kmath-ast/src/jvmTest/kotlin/scietifik/kmath/ast/ParserPrecedenceTest.kt

@@ -1,9 +1,9 @@
 package scietifik.kmath.ast
 
-import scientifik.kmath.ast.evaluate
-import scientifik.kmath.ast.parseMath
-import scientifik.kmath.operations.Field
-import scientifik.kmath.operations.RealField
+import kscience.kmath.ast.evaluate
+import kscience.kmath.ast.parseMath
+import kscience.kmath.operations.Field
+import kscience.kmath.operations.RealField
 import kotlin.test.Test
 import kotlin.test.assertEquals
 

kmath-ast/src/jvmTest/kotlin/scietifik/kmath/ast/ParserTest.kt

@@ -1,13 +1,13 @@
 package scietifik.kmath.ast
 
-import scientifik.kmath.ast.evaluate
-import scientifik.kmath.ast.mstInField
-import scientifik.kmath.ast.parseMath
-import scientifik.kmath.expressions.invoke
-import scientifik.kmath.operations.Algebra
-import scientifik.kmath.operations.Complex
-import scientifik.kmath.operations.ComplexField
-import scientifik.kmath.operations.RealField
+import kscience.kmath.ast.evaluate
+import kscience.kmath.ast.mstInField
+import kscience.kmath.ast.parseMath
+import kscience.kmath.expressions.invoke
+import kscience.kmath.operations.Algebra
+import kscience.kmath.operations.Complex
+import kscience.kmath.operations.ComplexField
+import kscience.kmath.operations.RealField
 import kotlin.test.Test
 import kotlin.test.assertEquals
 

kmath-commons/build.gradle.kts

@@ -1,12 +1,12 @@
-plugins { id("scientifik.jvm") }
+plugins {
+    id("ru.mipt.npm.jvm")
+}
 description = "Commons math binding for kmath"
 
 dependencies {
     api(project(":kmath-core"))
     api(project(":kmath-coroutines"))
     api(project(":kmath-prob"))
-    api(project(":kmath-functions"))
+//    api(project(":kmath-functions"))
     api("org.apache.commons:commons-math3:3.6.1")
 }
-
-kotlin.sourceSets.all { languageSettings.useExperimentalAnnotation("kotlin.contracts.ExperimentalContracts") }

kmath-commons/src/main/kotlin/kscience/kmath/commons/expressions/DiffExpression.kt

@@ -0,0 +1,128 @@
+package kscience.kmath.commons.expressions
+
+import kscience.kmath.expressions.Expression
+import kscience.kmath.expressions.ExpressionAlgebra
+import kscience.kmath.operations.ExtendedField
+import kscience.kmath.operations.Field
+import kscience.kmath.operations.invoke
+import org.apache.commons.math3.analysis.differentiation.DerivativeStructure
+import kotlin.properties.ReadOnlyProperty
+
+/**
+ * A field wrapping commons-math derivative structures
+ */
+public class DerivativeStructureField(
+    public val order: Int,
+    public val parameters: Map<String, Double>
+) : ExtendedField<DerivativeStructure> {
+    public override val zero: DerivativeStructure by lazy { DerivativeStructure(order, parameters.size) }
+    public override val one: DerivativeStructure by lazy { DerivativeStructure(order, parameters.size, 1.0) }
+
+    private val variables: Map<String, DerivativeStructure> = parameters.mapValues { (key, value) ->
+        DerivativeStructure(parameters.size, order, parameters.keys.indexOf(key), value)
+    }
+
+    public val variable: ReadOnlyProperty<Any?, DerivativeStructure> = ReadOnlyProperty { _, property ->
+        variables[property.name] ?: error("A variable with name ${property.name} does not exist")
+    }
+
+    public fun variable(name: String, default: DerivativeStructure? = null): DerivativeStructure =
+        variables[name] ?: default ?: error("A variable with name $name does not exist")
+
+    public fun Number.const(): DerivativeStructure = DerivativeStructure(order, parameters.size, toDouble())
+
+    public fun DerivativeStructure.deriv(parName: String, order: Int = 1): Double {
+        return deriv(mapOf(parName to order))
+    }
+
+    public fun DerivativeStructure.deriv(orders: Map<String, Int>): Double {
+        return getPartialDerivative(*parameters.keys.map { orders[it] ?: 0 }.toIntArray())
+    }
+
+    public fun DerivativeStructure.deriv(vararg orders: Pair<String, Int>): Double = deriv(mapOf(*orders))
+    public override fun add(a: DerivativeStructure, b: DerivativeStructure): DerivativeStructure = a.add(b)
+
+    public override fun multiply(a: DerivativeStructure, k: Number): DerivativeStructure = when (k) {
+        is Double -> a.multiply(k)
+        is Int -> a.multiply(k)
+        else -> a.multiply(k.toDouble())
+    }
+
+    public override fun multiply(a: DerivativeStructure, b: DerivativeStructure): DerivativeStructure = a.multiply(b)
+    public override fun divide(a: DerivativeStructure, b: DerivativeStructure): DerivativeStructure = a.divide(b)
+    public override fun sin(arg: DerivativeStructure): DerivativeStructure = arg.sin()
+    public override fun cos(arg: DerivativeStructure): DerivativeStructure = arg.cos()
+    public override fun tan(arg: DerivativeStructure): DerivativeStructure = arg.tan()
+    public override fun asin(arg: DerivativeStructure): DerivativeStructure = arg.asin()
+    public override fun acos(arg: DerivativeStructure): DerivativeStructure = arg.acos()
+    public override fun atan(arg: DerivativeStructure): DerivativeStructure = arg.atan()
+    public override fun sinh(arg: DerivativeStructure): DerivativeStructure = arg.sinh()
+    public override fun cosh(arg: DerivativeStructure): DerivativeStructure = arg.cosh()
+    public override fun tanh(arg: DerivativeStructure): DerivativeStructure = arg.tanh()
+    public override fun asinh(arg: DerivativeStructure): DerivativeStructure = arg.asinh()
+    public override fun acosh(arg: DerivativeStructure): DerivativeStructure = arg.acosh()
+    public override fun atanh(arg: DerivativeStructure): DerivativeStructure = arg.atanh()
+
+    public override fun power(arg: DerivativeStructure, pow: Number): DerivativeStructure = when (pow) {
+        is Double -> arg.pow(pow)
+        is Int -> arg.pow(pow)
+        else -> arg.pow(pow.toDouble())
+    }
+
+    public fun power(arg: DerivativeStructure, pow: DerivativeStructure): DerivativeStructure = arg.pow(pow)
+    public override fun exp(arg: DerivativeStructure): DerivativeStructure = arg.exp()
+    public override fun ln(arg: DerivativeStructure): DerivativeStructure = arg.log()
+
+    public override operator fun DerivativeStructure.plus(b: Number): DerivativeStructure = add(b.toDouble())
+    public override operator fun DerivativeStructure.minus(b: Number): DerivativeStructure = subtract(b.toDouble())
+    public override operator fun Number.plus(b: DerivativeStructure): DerivativeStructure = b + this
+    public override operator fun Number.minus(b: DerivativeStructure): DerivativeStructure = b - this
+}
+
+/**
+ * A constructs that creates a derivative structure with required order on-demand
+ */
+public class DiffExpression(public val function: DerivativeStructureField.() -> DerivativeStructure) :
+    Expression<Double> {
+    public override operator fun invoke(arguments: Map<String, Double>): Double = DerivativeStructureField(
+        0,
+        arguments
+    ).function().value
+
+    /**
+     * Get the derivative expression with given orders
+     * TODO make result [DiffExpression]
+     */
+    public fun derivative(orders: Map<String, Int>): Expression<Double> = Expression { arguments ->
+        (DerivativeStructureField(orders.values.max() ?: 0, arguments)) { function().deriv(orders) }
+    }
+
+    //TODO add gradient and maybe other vector operators
+}
+
+public fun DiffExpression.derivative(vararg orders: Pair<String, Int>): Expression<Double> = derivative(mapOf(*orders))
+public fun DiffExpression.derivative(name: String): Expression<Double> = derivative(name to 1)
+
+/**
+ * A context for [DiffExpression] (not to be confused with [DerivativeStructure])
+ */
+public object DiffExpressionAlgebra : ExpressionAlgebra<Double, DiffExpression>, Field<DiffExpression> {
+    public override val zero: DiffExpression = DiffExpression { 0.0.const() }
+    public override val one: DiffExpression = DiffExpression { 1.0.const() }
+
+    public override fun variable(name: String, default: Double?): DiffExpression =
+        DiffExpression { variable(name, default?.const()) }
+
+    public override fun const(value: Double): DiffExpression = DiffExpression { value.const() }
+
+    public override fun add(a: DiffExpression, b: DiffExpression): DiffExpression =
+        DiffExpression { a.function(this) + b.function(this) }
+
+    public override fun multiply(a: DiffExpression, k: Number): DiffExpression = DiffExpression { a.function(this) * k }
+
+    public override fun multiply(a: DiffExpression, b: DiffExpression): DiffExpression =
+        DiffExpression { a.function(this) * b.function(this) }
+
+    public override fun divide(a: DiffExpression, b: DiffExpression): DiffExpression =
+        DiffExpression { a.function(this) / b.function(this) }
+}

kmath-commons/src/main/kotlin/kscience/kmath/commons/linear/CMMatrix.kt

@@ -0,0 +1,93 @@
+package kscience.kmath.commons.linear
+
+import kscience.kmath.linear.*
+import kscience.kmath.structures.Matrix
+import kscience.kmath.structures.NDStructure
+import org.apache.commons.math3.linear.*
+
+public class CMMatrix(public val origin: RealMatrix, features: Set<MatrixFeature>? = null) :
+    FeaturedMatrix<Double> {
+    public override val rowNum: Int get() = origin.rowDimension
+    public override val colNum: Int get() = origin.columnDimension
+
+    public override val features: Set<MatrixFeature> = features ?: sequence<MatrixFeature> {
+        if (origin is DiagonalMatrix) yield(DiagonalFeature)
+    }.toHashSet()
+
+    public override fun suggestFeature(vararg features: MatrixFeature): CMMatrix =
+        CMMatrix(origin, this.features + features)
+
+    public override operator fun get(i: Int, j: Int): Double = origin.getEntry(i, j)
+
+    public override fun equals(other: Any?): Boolean {
+        return NDStructure.equals(this, other as? NDStructure<*> ?: return false)
+    }
+
+    public override fun hashCode(): Int {
+        var result = origin.hashCode()
+        result = 31 * result + features.hashCode()
+        return result
+    }
+}
+
+public fun Matrix<Double>.toCM(): CMMatrix = if (this is CMMatrix) {
+    this
+} else {
+    //TODO add feature analysis
+    val array = Array(rowNum) { i -> DoubleArray(colNum) { j -> get(i, j) } }
+    CMMatrix(Array2DRowRealMatrix(array))
+}
+
+public fun RealMatrix.asMatrix(): CMMatrix = CMMatrix(this)
+
+public class CMVector(public val origin: RealVector) : Point<Double> {
+    public override val size: Int get() = origin.dimension
+
+    public override operator fun get(index: Int): Double = origin.getEntry(index)
+
+    public override operator fun iterator(): Iterator<Double> = origin.toArray().iterator()
+}
+
+public fun Point<Double>.toCM(): CMVector = if (this is CMVector) this else {
+    val array = DoubleArray(size) { this[it] }
+    CMVector(ArrayRealVector(array))
+}
+
+public fun RealVector.toPoint(): CMVector = CMVector(this)
+
+public object CMMatrixContext : MatrixContext<Double> {
+    public override fun produce(rows: Int, columns: Int, initializer: (i: Int, j: Int) -> Double): CMMatrix {
+        val array = Array(rows) { i -> DoubleArray(columns) { j -> initializer(i, j) } }
+        return CMMatrix(Array2DRowRealMatrix(array))
+    }
+
+    public override fun Matrix<Double>.dot(other: Matrix<Double>): CMMatrix =
+        CMMatrix(toCM().origin.multiply(other.toCM().origin))
+
+    public override fun Matrix<Double>.dot(vector: Point<Double>): CMVector =
+        CMVector(toCM().origin.preMultiply(vector.toCM().origin))
+
+    public override operator fun Matrix<Double>.unaryMinus(): CMMatrix =
+        produce(rowNum, colNum) { i, j -> -get(i, j) }
+
+    public override fun add(a: Matrix<Double>, b: Matrix<Double>): CMMatrix =
+        CMMatrix(a.toCM().origin.multiply(b.toCM().origin))
+
+    public override operator fun Matrix<Double>.minus(b: Matrix<Double>): CMMatrix =
+        CMMatrix(toCM().origin.subtract(b.toCM().origin))
+
+    public override fun multiply(a: Matrix<Double>, k: Number): CMMatrix =
+        CMMatrix(a.toCM().origin.scalarMultiply(k.toDouble()))
+
+    public override operator fun Matrix<Double>.times(value: Double): Matrix<Double> =
+        produce(rowNum, colNum) { i, j -> get(i, j) * value }
+}
+
+public operator fun CMMatrix.plus(other: CMMatrix): CMMatrix =
+    CMMatrix(origin.add(other.origin))
+
+public operator fun CMMatrix.minus(other: CMMatrix): CMMatrix =
+    CMMatrix(origin.subtract(other.origin))
+
+public infix fun CMMatrix.dot(other: CMMatrix): CMMatrix =
+    CMMatrix(origin.multiply(other.origin))

kmath-commons/src/main/kotlin/kscience/kmath/commons/linear/CMSolver.kt

@@ -0,0 +1,41 @@
+package kscience.kmath.commons.linear
+
+import kscience.kmath.linear.Point
+import kscience.kmath.structures.Matrix
+import org.apache.commons.math3.linear.*
+
+public enum class CMDecomposition {
+    LUP,
+    QR,
+    RRQR,
+    EIGEN,
+    CHOLESKY
+}
+
+public fun CMMatrixContext.solver(
+    a: Matrix<Double>,
+    decomposition: CMDecomposition = CMDecomposition.LUP
+): DecompositionSolver = when (decomposition) {
+    CMDecomposition.LUP -> LUDecomposition(a.toCM().origin).solver
+    CMDecomposition.RRQR -> RRQRDecomposition(a.toCM().origin).solver
+    CMDecomposition.QR -> QRDecomposition(a.toCM().origin).solver
+    CMDecomposition.EIGEN -> EigenDecomposition(a.toCM().origin).solver
+    CMDecomposition.CHOLESKY -> CholeskyDecomposition(a.toCM().origin).solver
+}
+
+public fun CMMatrixContext.solve(
+    a: Matrix<Double>,
+    b: Matrix<Double>,
+    decomposition: CMDecomposition = CMDecomposition.LUP
+): CMMatrix = solver(a, decomposition).solve(b.toCM().origin).asMatrix()
+
+public fun CMMatrixContext.solve(
+    a: Matrix<Double>,
+    b: Point<Double>,
+    decomposition: CMDecomposition = CMDecomposition.LUP
+): CMVector = solver(a, decomposition).solve(b.toCM().origin).toPoint()
+
+public fun CMMatrixContext.inverse(
+    a: Matrix<Double>,
+    decomposition: CMDecomposition = CMDecomposition.LUP
+): CMMatrix = solver(a, decomposition).inverse.asMatrix()

kmath-commons/src/main/kotlin/kscience/kmath/commons/random/CMRandomGeneratorWrapper.kt

@@ -0,0 +1,33 @@
+package kscience.kmath.commons.random
+
+import kscience.kmath.prob.RandomGenerator
+
+public class CMRandomGeneratorWrapper(public val factory: (IntArray) -> RandomGenerator) :
+    org.apache.commons.math3.random.RandomGenerator {
+    private var generator: RandomGenerator = factory(intArrayOf())
+
+    public override fun nextBoolean(): Boolean = generator.nextBoolean()
+    public override fun nextFloat(): Float = generator.nextDouble().toFloat()
+
+    public override fun setSeed(seed: Int) {
+        generator = factory(intArrayOf(seed))
+    }
+
+    public override fun setSeed(seed: IntArray) {
+        generator = factory(seed)
+    }
+
+    public override fun setSeed(seed: Long) {
+        setSeed(seed.toInt())
+    }
+
+    public override fun nextBytes(bytes: ByteArray) {
+        generator.fillBytes(bytes)
+    }
+
+    public override fun nextInt(): Int = generator.nextInt()
+    public override fun nextInt(n: Int): Int = generator.nextInt(n)
+    public override fun nextGaussian(): Double = TODO()
+    public override fun nextDouble(): Double = generator.nextDouble()
+    public override fun nextLong(): Long = generator.nextLong()
+}

kmath-commons/src/main/kotlin/kscience/kmath/commons/transform/Transformations.kt

@@ -1,20 +1,19 @@
-package scientifik.kmath.commons.transform
+package kscience.kmath.commons.transform
 
 import kotlinx.coroutines.FlowPreview
 import kotlinx.coroutines.flow.Flow
 import kotlinx.coroutines.flow.map
+import kscience.kmath.operations.Complex
+import kscience.kmath.streaming.chunked
+import kscience.kmath.streaming.spread
+import kscience.kmath.structures.*
 import org.apache.commons.math3.transform.*
-import scientifik.kmath.operations.Complex
-import scientifik.kmath.streaming.chunked
-import scientifik.kmath.streaming.spread
-import scientifik.kmath.structures.*
 
 
 /**
  * Streaming and buffer transformations
  */
-object Transformations {
-
+public object Transformations {
     private fun Buffer<Complex>.toArray(): Array<org.apache.commons.math3.complex.Complex> =
         Array(size) { org.apache.commons.math3.complex.Complex(get(it).re, get(it).im) }
 
@@ -32,35 +31,35 @@ object Transformations {
         Complex(value.real, value.imaginary)
     }
 
-    fun fourier(
+    public fun fourier(
         normalization: DftNormalization = DftNormalization.STANDARD,
         direction: TransformType = TransformType.FORWARD
     ): SuspendBufferTransform<Complex, Complex> = {
         FastFourierTransformer(normalization).transform(it.toArray(), direction).asBuffer()
     }
 
-    fun realFourier(
+    public fun realFourier(
         normalization: DftNormalization = DftNormalization.STANDARD,
         direction: TransformType = TransformType.FORWARD
     ): SuspendBufferTransform<Double, Complex> = {
         FastFourierTransformer(normalization).transform(it.asArray(), direction).asBuffer()
     }
 
-    fun sine(
+    public fun sine(
         normalization: DstNormalization = DstNormalization.STANDARD_DST_I,
         direction: TransformType = TransformType.FORWARD
     ): SuspendBufferTransform<Double, Double> = {
         FastSineTransformer(normalization).transform(it.asArray(), direction).asBuffer()
     }
 
-    fun cosine(
+    public fun cosine(
         normalization: DctNormalization = DctNormalization.STANDARD_DCT_I,
         direction: TransformType = TransformType.FORWARD
     ): SuspendBufferTransform<Double, Double> = {
         FastCosineTransformer(normalization).transform(it.asArray(), direction).asBuffer()
     }
 
-    fun hadamard(
+    public fun hadamard(
         direction: TransformType = TransformType.FORWARD
     ): SuspendBufferTransform<Double, Double> = {
         FastHadamardTransformer().transform(it.asArray(), direction).asBuffer()
@@ -71,7 +70,7 @@ object Transformations {
  * Process given [Flow] with commons-math fft transformation
  */
 @FlowPreview
-fun Flow<Buffer<Complex>>.FFT(
+public fun Flow<Buffer<Complex>>.FFT(
     normalization: DftNormalization = DftNormalization.STANDARD,
     direction: TransformType = TransformType.FORWARD
 ): Flow<Buffer<Complex>> {
@@ -81,7 +80,7 @@ fun Flow<Buffer<Complex>>.FFT(
 
 @FlowPreview
 @JvmName("realFFT")
-fun Flow<Buffer<Double>>.FFT(
+public fun Flow<Buffer<Double>>.FFT(
     normalization: DftNormalization = DftNormalization.STANDARD,
     direction: TransformType = TransformType.FORWARD
 ): Flow<Buffer<Complex>> {
@@ -90,20 +89,18 @@ fun Flow<Buffer<Double>>.FFT(
 }
 
 /**
- * Process a continous flow of real numbers in FFT splitting it in chunks of [bufferSize].
+ * Process a continuous flow of real numbers in FFT splitting it in chunks of [bufferSize].
  */
 @FlowPreview
 @JvmName("realFFT")
-fun Flow<Double>.FFT(
+public fun Flow<Double>.FFT(
     bufferSize: Int = Int.MAX_VALUE,
     normalization: DftNormalization = DftNormalization.STANDARD,
     direction: TransformType = TransformType.FORWARD
-): Flow<Complex> {
-    return chunked(bufferSize).FFT(normalization,direction).spread()
-}
+): Flow<Complex> = chunked(bufferSize).FFT(normalization, direction).spread()
 
 /**
  * Map a complex flow into real flow by taking real part of each number
  */
 @FlowPreview
-fun Flow<Complex>.real(): Flow<Double> = map{it.re}
+public fun Flow<Complex>.real(): Flow<Double> = map { it.re }

kmath-commons/src/main/kotlin/scientifik/kmath/commons/expressions/DiffExpression.kt

@@ -1,137 +0,0 @@
-package scientifik.kmath.commons.expressions
-
-import org.apache.commons.math3.analysis.differentiation.DerivativeStructure
-import scientifik.kmath.expressions.Expression
-import scientifik.kmath.expressions.ExpressionAlgebra
-import scientifik.kmath.operations.ExtendedField
-import scientifik.kmath.operations.Field
-import scientifik.kmath.operations.invoke
-import kotlin.properties.ReadOnlyProperty
-import kotlin.reflect.KProperty
-
-/**
- * A field wrapping commons-math derivative structures
- */
-class DerivativeStructureField(
-    val order: Int,
-    val parameters: Map<String, Double>
-) : ExtendedField<DerivativeStructure> {
-    override val zero: DerivativeStructure by lazy { DerivativeStructure(order, parameters.size) }
-    override val one: DerivativeStructure by lazy { DerivativeStructure(order, parameters.size, 1.0) }
-
-    private val variables: Map<String, DerivativeStructure> = parameters.mapValues { (key, value) ->
-        DerivativeStructure(parameters.size, order, parameters.keys.indexOf(key), value)
-    }
-
-    val variable: ReadOnlyProperty<Any?, DerivativeStructure> = object : ReadOnlyProperty<Any?, DerivativeStructure> {
-        override fun getValue(thisRef: Any?, property: KProperty<*>): DerivativeStructure =
-            variables[property.name] ?: error("A variable with name ${property.name} does not exist")
-    }
-
-    fun variable(name: String, default: DerivativeStructure? = null): DerivativeStructure =
-        variables[name] ?: default ?: error("A variable with name $name does not exist")
-
-    fun Number.const(): DerivativeStructure = DerivativeStructure(order, parameters.size, toDouble())
-
-    fun DerivativeStructure.deriv(parName: String, order: Int = 1): Double {
-        return deriv(mapOf(parName to order))
-    }
-
-    fun DerivativeStructure.deriv(orders: Map<String, Int>): Double {
-        return getPartialDerivative(*parameters.keys.map { orders[it] ?: 0 }.toIntArray())
-    }
-
-    fun DerivativeStructure.deriv(vararg orders: Pair<String, Int>): Double = deriv(mapOf(*orders))
-
-    override fun add(a: DerivativeStructure, b: DerivativeStructure): DerivativeStructure = a.add(b)
-
-    override fun multiply(a: DerivativeStructure, k: Number): DerivativeStructure = when (k) {
-        is Double -> a.multiply(k)
-        is Int -> a.multiply(k)
-        else -> a.multiply(k.toDouble())
-    }
-
-    override fun multiply(a: DerivativeStructure, b: DerivativeStructure): DerivativeStructure = a.multiply(b)
-
-    override fun divide(a: DerivativeStructure, b: DerivativeStructure): DerivativeStructure = a.divide(b)
-
-    override fun sin(arg: DerivativeStructure): DerivativeStructure = arg.sin()
-    override fun cos(arg: DerivativeStructure): DerivativeStructure = arg.cos()
-    override fun tan(arg: DerivativeStructure): DerivativeStructure = arg.tan()
-    override fun asin(arg: DerivativeStructure): DerivativeStructure = arg.asin()
-    override fun acos(arg: DerivativeStructure): DerivativeStructure = arg.acos()
-    override fun atan(arg: DerivativeStructure): DerivativeStructure = arg.atan()
-
-    override fun sinh(arg: DerivativeStructure): DerivativeStructure = arg.sinh()
-    override fun cosh(arg: DerivativeStructure): DerivativeStructure = arg.cosh()
-    override fun tanh(arg: DerivativeStructure): DerivativeStructure = arg.tanh()
-    override fun asinh(arg: DerivativeStructure): DerivativeStructure = arg.asinh()
-    override fun acosh(arg: DerivativeStructure): DerivativeStructure = arg.acosh()
-    override fun atanh(arg: DerivativeStructure): DerivativeStructure = arg.atanh()
-
-    override fun power(arg: DerivativeStructure, pow: Number): DerivativeStructure = when (pow) {
-        is Double -> arg.pow(pow)
-        is Int -> arg.pow(pow)
-        else -> arg.pow(pow.toDouble())
-    }
-
-    fun power(arg: DerivativeStructure, pow: DerivativeStructure): DerivativeStructure = arg.pow(pow)
-    override fun exp(arg: DerivativeStructure): DerivativeStructure = arg.exp()
-    override fun ln(arg: DerivativeStructure): DerivativeStructure = arg.log()
-
-    override operator fun DerivativeStructure.plus(b: Number): DerivativeStructure = add(b.toDouble())
-    override operator fun DerivativeStructure.minus(b: Number): DerivativeStructure = subtract(b.toDouble())
-    override operator fun Number.plus(b: DerivativeStructure): DerivativeStructure = b + this
-    override operator fun Number.minus(b: DerivativeStructure): DerivativeStructure = b - this
-}
-
-/**
- * A constructs that creates a derivative structure with required order on-demand
- */
-class DiffExpression(val function: DerivativeStructureField.() -> DerivativeStructure) : Expression<Double> {
-    override operator fun invoke(arguments: Map<String, Double>): Double = DerivativeStructureField(
-        0,
-        arguments
-    ).run(function).value
-
-    /**
-     * Get the derivative expression with given orders
-     * TODO make result [DiffExpression]
-     */
-    fun derivative(orders: Map<String, Int>): Expression<Double> = object : Expression<Double> {
-        override operator fun invoke(arguments: Map<String, Double>): Double =
-            (DerivativeStructureField(orders.values.max() ?: 0, arguments)) { function().deriv(orders) }
-    }
-
-    //TODO add gradient and maybe other vector operators
-}
-
-fun DiffExpression.derivative(vararg orders: Pair<String, Int>): Expression<Double> = derivative(mapOf(*orders))
-fun DiffExpression.derivative(name: String): Expression<Double> = derivative(name to 1)
-
-/**
- * A context for [DiffExpression] (not to be confused with [DerivativeStructure])
- */
-object DiffExpressionAlgebra : ExpressionAlgebra<Double, DiffExpression>, Field<DiffExpression> {
-    override fun variable(name: String, default: Double?): DiffExpression =
-        DiffExpression { variable(name, default?.const()) }
-
-    override fun const(value: Double): DiffExpression =
-        DiffExpression { value.const() }
-
-    override fun add(a: DiffExpression, b: DiffExpression): DiffExpression =
-        DiffExpression { a.function(this) + b.function(this) }
-
-    override val zero: DiffExpression = DiffExpression { 0.0.const() }
-
-    override fun multiply(a: DiffExpression, k: Number): DiffExpression =
-        DiffExpression { a.function(this) * k }
-
-    override val one: DiffExpression = DiffExpression { 1.0.const() }
-
-    override fun multiply(a: DiffExpression, b: DiffExpression): DiffExpression =
-        DiffExpression { a.function(this) * b.function(this) }
-
-    override fun divide(a: DiffExpression, b: DiffExpression): DiffExpression =
-        DiffExpression { a.function(this) / b.function(this) }
-}

kmath-commons/src/main/kotlin/scientifik/kmath/commons/linear/CMMatrix.kt

@@ -1,93 +0,0 @@
-package scientifik.kmath.commons.linear
-
-import org.apache.commons.math3.linear.*
-import scientifik.kmath.linear.*
-import scientifik.kmath.structures.Matrix
-import scientifik.kmath.structures.NDStructure
-
-class CMMatrix(val origin: RealMatrix, features: Set<MatrixFeature>? = null) :
-    FeaturedMatrix<Double> {
-    override val rowNum: Int get() = origin.rowDimension
-    override val colNum: Int get() = origin.columnDimension
-
-    override val features: Set<MatrixFeature> = features ?: sequence<MatrixFeature> {
-        if (origin is DiagonalMatrix) yield(DiagonalFeature)
-    }.toHashSet()
-
-    override fun suggestFeature(vararg features: MatrixFeature): CMMatrix =
-        CMMatrix(origin, this.features + features)
-
-    override operator fun get(i: Int, j: Int): Double = origin.getEntry(i, j)
-
-    override fun equals(other: Any?): Boolean {
-        return NDStructure.equals(this, other as? NDStructure<*> ?: return false)
-    }
-
-    override fun hashCode(): Int {
-        var result = origin.hashCode()
-        result = 31 * result + features.hashCode()
-        return result
-    }
-}
-
-fun Matrix<Double>.toCM(): CMMatrix = if (this is CMMatrix) {
-    this
-} else {
-    //TODO add feature analysis
-    val array = Array(rowNum) { i -> DoubleArray(colNum) { j -> get(i, j) } }
-    CMMatrix(Array2DRowRealMatrix(array))
-}
-
-fun RealMatrix.asMatrix(): CMMatrix = CMMatrix(this)
-
-class CMVector(val origin: RealVector) : Point<Double> {
-    override val size: Int get() = origin.dimension
-
-    override operator fun get(index: Int): Double = origin.getEntry(index)
-
-    override operator fun iterator(): Iterator<Double> = origin.toArray().iterator()
-}
-
-fun Point<Double>.toCM(): CMVector = if (this is CMVector) this else {
-    val array = DoubleArray(size) { this[it] }
-    CMVector(ArrayRealVector(array))
-}
-
-fun RealVector.toPoint(): CMVector = CMVector(this)
-
-object CMMatrixContext : MatrixContext<Double> {
-    override fun produce(rows: Int, columns: Int, initializer: (i: Int, j: Int) -> Double): CMMatrix {
-        val array = Array(rows) { i -> DoubleArray(columns) { j -> initializer(i, j) } }
-        return CMMatrix(Array2DRowRealMatrix(array))
-    }
-
-    override fun Matrix<Double>.dot(other: Matrix<Double>): CMMatrix =
-        CMMatrix(this.toCM().origin.multiply(other.toCM().origin))
-
-    override fun Matrix<Double>.dot(vector: Point<Double>): CMVector =
-        CMVector(this.toCM().origin.preMultiply(vector.toCM().origin))
-
-    override operator fun Matrix<Double>.unaryMinus(): CMMatrix =
-        produce(rowNum, colNum) { i, j -> -get(i, j) }
-
-    override fun add(a: Matrix<Double>, b: Matrix<Double>): CMMatrix =
-        CMMatrix(a.toCM().origin.multiply(b.toCM().origin))
-
-    override operator fun Matrix<Double>.minus(b: Matrix<Double>): CMMatrix =
-        CMMatrix(this.toCM().origin.subtract(b.toCM().origin))
-
-    override fun multiply(a: Matrix<Double>, k: Number): CMMatrix =
-        CMMatrix(a.toCM().origin.scalarMultiply(k.toDouble()))
-
-    override operator fun Matrix<Double>.times(value: Double): Matrix<Double> =
-        produce(rowNum, colNum) { i, j -> get(i, j) * value }
-}
-
-operator fun CMMatrix.plus(other: CMMatrix): CMMatrix =
-    CMMatrix(this.origin.add(other.origin))
-
-operator fun CMMatrix.minus(other: CMMatrix): CMMatrix =
-    CMMatrix(this.origin.subtract(other.origin))
-
-infix fun CMMatrix.dot(other: CMMatrix): CMMatrix =
-    CMMatrix(this.origin.multiply(other.origin))

kmath-commons/src/main/kotlin/scientifik/kmath/commons/linear/CMSolver.kt

@@ -1,40 +0,0 @@
-package scientifik.kmath.commons.linear
-
-import org.apache.commons.math3.linear.*
-import scientifik.kmath.linear.Point
-import scientifik.kmath.structures.Matrix
-
-enum class CMDecomposition {
-    LUP,
-    QR,
-    RRQR,
-    EIGEN,
-    CHOLESKY
-}
-
-
-fun CMMatrixContext.solver(a: Matrix<Double>, decomposition: CMDecomposition = CMDecomposition.LUP) =
-    when (decomposition) {
-        CMDecomposition.LUP -> LUDecomposition(a.toCM().origin).solver
-        CMDecomposition.RRQR -> RRQRDecomposition(a.toCM().origin).solver
-        CMDecomposition.QR -> QRDecomposition(a.toCM().origin).solver
-        CMDecomposition.EIGEN -> EigenDecomposition(a.toCM().origin).solver
-        CMDecomposition.CHOLESKY -> CholeskyDecomposition(a.toCM().origin).solver
-    }
-
-fun CMMatrixContext.solve(
-    a: Matrix<Double>,
-    b: Matrix<Double>,
-    decomposition: CMDecomposition = CMDecomposition.LUP
-) = solver(a, decomposition).solve(b.toCM().origin).asMatrix()
-
-fun CMMatrixContext.solve(
-    a: Matrix<Double>,
-    b: Point<Double>,
-    decomposition: CMDecomposition = CMDecomposition.LUP
-) = solver(a, decomposition).solve(b.toCM().origin).toPoint()
-
-fun CMMatrixContext.inverse(
-    a: Matrix<Double>,
-    decomposition: CMDecomposition = CMDecomposition.LUP
-) = solver(a, decomposition).inverse.asMatrix()

kmath-commons/src/main/kotlin/scientifik/kmath/commons/random/CMRandomGeneratorWrapper.kt

@@ -1,33 +0,0 @@
-package scientifik.kmath.commons.random
-
-import scientifik.kmath.prob.RandomGenerator
-
-class CMRandomGeneratorWrapper(val factory: (IntArray) -> RandomGenerator) :
-    org.apache.commons.math3.random.RandomGenerator {
-    private var generator: RandomGenerator = factory(intArrayOf())
-
-    override fun nextBoolean(): Boolean = generator.nextBoolean()
-    override fun nextFloat(): Float = generator.nextDouble().toFloat()
-
-    override fun setSeed(seed: Int) {
-        generator = factory(intArrayOf(seed))
-    }
-
-    override fun setSeed(seed: IntArray) {
-        generator = factory(seed)
-    }
-
-    override fun setSeed(seed: Long) {
-        setSeed(seed.toInt())
-    }
-
-    override fun nextBytes(bytes: ByteArray) {
-        generator.fillBytes(bytes)
-    }
-
-    override fun nextInt(): Int = generator.nextInt()
-    override fun nextInt(n: Int): Int = generator.nextInt(n)
-    override fun nextGaussian(): Double = TODO()
-    override fun nextDouble(): Double = generator.nextDouble()
-    override fun nextLong(): Long = generator.nextLong()
-}

kmath-commons/src/test/kotlin/kscience/kmath/commons/expressions/AutoDiffTest.kt

@@ -1,17 +1,21 @@
-package scientifik.kmath.commons.expressions
+package kscience.kmath.commons.expressions
 
-import scientifik.kmath.expressions.invoke
+import kscience.kmath.expressions.invoke
 import kotlin.contracts.InvocationKind
 import kotlin.contracts.contract
 import kotlin.test.Test
 import kotlin.test.assertEquals
 
-inline fun <R> diff(order: Int, vararg parameters: Pair<String, Double>, block: DerivativeStructureField.() -> R): R {
+internal inline fun <R> diff(
+    order: Int,
+    vararg parameters: Pair<String, Double>,
+    block: DerivativeStructureField.() -> R
+): R {
     contract { callsInPlace(block, InvocationKind.EXACTLY_ONCE) }
     return DerivativeStructureField(order, mapOf(*parameters)).run(block)
 }
 
-class AutoDiffTest {
+internal class AutoDiffTest {
     @Test
     fun derivativeStructureFieldTest() {
         val res = diff(3, "x" to 1.0, "y" to 1.0) {
@@ -33,4 +37,4 @@ class AutoDiffTest {
         assertEquals(10.0, f("x" to 1.0, "y" to 2.0))
         assertEquals(6.0, f.derivative("x")("x" to 1.0, "y" to 2.0))
     }
-}
+}

kmath-core/README.md

@@ -1,40 +1,40 @@
 # The Core Module (`kmath-core`)
 
 The core features of KMath:
+ - [algebras](src/commonMain/kotlin/kscience/kmath/operations/Algebra.kt) : Algebraic structures: contexts and elements
+ - [nd](src/commonMain/kotlin/kscience/kmath/structures/NDStructure.kt) : Many-dimensional structures
+ - [buffers](src/commonMain/kotlin/kscience/kmath/structures/Buffers.kt) : One-dimensional structure
+ - [expressions](src/commonMain/kotlin/kscience/kmath/expressions) : Functional Expressions
+ - [domains](src/commonMain/kotlin/kscience/kmath/domains) : Domains
+ - [autodif](src/commonMain/kotlin/kscience/kmath/misc/AutoDiff.kt) : Automatic differentiation
 
-- Algebraic structures: contexts and elements.
-- ND structures.
-- Buffers.
-- Functional Expressions.
-- Domains.
-- Automatic differentiation.
 
 > #### Artifact:
-> This module is distributed in the artifact `scientifik:kmath-core:0.1.4-dev-8`.
+> This module artifact: `kscience.kmath:kmath-core:0.2.0-dev-1`.
 > 
 > **Gradle:**
 >
 > ```gradle
 > repositories {
->     maven { url 'https://dl.bintray.com/mipt-npm/scientifik' }
+>     maven { url 'https://dl.bintray.com/mipt-npm/kscience' }
 >     maven { url 'https://dl.bintray.com/mipt-npm/dev' }
 >     maven { url https://dl.bintray.com/hotkeytlt/maven' }
 > }
 > 
 > dependencies {
->     implementation 'scientifik:kmath-core:0.1.4-dev-8'
+>     implementation 'kscience.kmath:kmath-core:0.2.0-dev-1'
 > }
 > ```
 > **Gradle Kotlin DSL:**
 >
 > ```kotlin
 > repositories {
->     maven("https://dl.bintray.com/mipt-npm/scientifik")
+>     maven("https://dl.bintray.com/mipt-npm/kscience")
 >     maven("https://dl.bintray.com/mipt-npm/dev")
 >     maven("https://dl.bintray.com/hotkeytlt/maven")
 > }
 > 
-> dependencies {``
->     implementation("scientifik:kmath-core:0.1.4-dev-8")
+> dependencies {
+>     implementation("kscience.kmath:kmath-core:0.2.0-dev-1")
 > }
 > ```

kmath-core/build.gradle.kts

@@ -1,6 +1,7 @@
-plugins { id("scientifik.mpp") }
+plugins { id("ru.mipt.npm.mpp") }
 
-kotlin.sourceSets {
-    all { languageSettings.useExperimentalAnnotation("kotlin.contracts.ExperimentalContracts") }
-    commonMain { dependencies { api(project(":kmath-memory")) } }
+kotlin.sourceSets.commonMain {
+    dependencies {
+        api(project(":kmath-memory"))
+    }
 }

kmath-core/docs/README-STUB.md

@@ -0,0 +1,34 @@
+# The Core Module (`kmath-core`)
+
+The core features of KMath:
+$featuresString
+
+> #### Artifact:
+> This module artifact: `$group:kmath-core:$version`.
+> 
+> **Gradle:**
+>
+> ```gradle
+> repositories {
+>     maven { url 'https://dl.bintray.com/mipt-npm/kscience' }
+>     maven { url 'https://dl.bintray.com/mipt-npm/dev' }
+>     maven { url https://dl.bintray.com/hotkeytlt/maven' }
+> }
+> 
+> dependencies {
+>     implementation '$group:kmath-core:$version'
+> }
+> ```
+> **Gradle Kotlin DSL:**
+>
+> ```kotlin
+> repositories {
+>     maven("https://dl.bintray.com/mipt-npm/kscience")
+>     maven("https://dl.bintray.com/mipt-npm/dev")
+>     maven("https://dl.bintray.com/hotkeytlt/maven")
+> }
+> 
+> dependencies {
+>     implementation("$group:kmath-core:$version")
+> }
+> ```

kmath-core/docs/kscience-module.json

@@ -0,0 +1,36 @@
+{
+  "description": "Core classes, algebra definitions, basic linear algebra",
+  "maturity": "development",
+  "features": [
+    {
+      "id": "algebras",
+      "description": "Algebraic structures: contexts and elements",
+      "ref": "src/commonMain/kotlin/kscience/kmath/operations/Algebra.kt"
+    },
+    {
+      "id": "nd",
+      "description": "Many-dimensional structures",
+      "ref": "src/commonMain/kotlin/kscience/kmath/structures/NDStructure.kt"
+    },
+    {
+      "id": "buffers",
+      "description": "One-dimensional structure",
+      "ref": "src/commonMain/kotlin/kscience/kmath/structures/Buffers.kt"
+    },
+    {
+      "id": "expressions",
+      "description": "Functional Expressions",
+      "ref": "src/commonMain/kotlin/kscience/kmath/expressions"
+    },
+    {
+      "id": "domains",
+      "description": "Domains",
+      "ref": "src/commonMain/kotlin/kscience/kmath/domains"
+    },
+    {
+      "id": "autodif",
+      "description": "Automatic differentiation",
+      "ref": "src/commonMain/kotlin/kscience/kmath/misc/AutoDiff.kt"
+    }
+  ]
+}

kmath-core/src/commonMain/kotlin/kscience/kmath/domains/Domain.kt

@@ -1,20 +1,20 @@
-package scientifik.kmath.domains
+package kscience.kmath.domains
 
-import scientifik.kmath.linear.Point
+import kscience.kmath.linear.Point
 
 /**
  * A simple geometric domain.
  *
  * @param T the type of element of this domain.
  */
-interface Domain<T : Any> {
+public interface Domain<T : Any> {
     /**
      * Checks if the specified point is contained in this domain.
      */
-    operator fun contains(point: Point<T>): Boolean
+    public operator fun contains(point: Point<T>): Boolean
 
     /**
      * Number of hyperspace dimensions.
      */
-    val dimension: Int
+    public val dimension: Int
 }

kmath-core/src/commonMain/kotlin/kscience/kmath/domains/HyperSquareDomain.kt

@@ -13,11 +13,11 @@
  * See the License for the specific language governing permissions and
  * limitations under the License.
  */
-package scientifik.kmath.domains
+package kscience.kmath.domains
 
-import scientifik.kmath.linear.Point
-import scientifik.kmath.structures.RealBuffer
-import scientifik.kmath.structures.indices
+import kscience.kmath.linear.Point
+import kscience.kmath.structures.RealBuffer
+import kscience.kmath.structures.indices
 
 /**
  *
@@ -25,23 +25,22 @@ import scientifik.kmath.structures.indices
  *
  * @author Alexander Nozik
  */
-class HyperSquareDomain(private val lower: RealBuffer, private val upper: RealBuffer) : RealDomain {
+public class HyperSquareDomain(private val lower: RealBuffer, private val upper: RealBuffer) : RealDomain {
+    public override val dimension: Int get() = lower.size
 
-    override operator fun contains(point: Point<Double>): Boolean = point.indices.all { i ->
+    public override operator fun contains(point: Point<Double>): Boolean = point.indices.all { i ->
         point[i] in lower[i]..upper[i]
     }
 
-    override val dimension: Int get() = lower.size
+    public override fun getLowerBound(num: Int, point: Point<Double>): Double? = lower[num]
 
-    override fun getLowerBound(num: Int, point: Point<Double>): Double? = lower[num]
+    public override fun getLowerBound(num: Int): Double? = lower[num]
 
-    override fun getLowerBound(num: Int): Double? = lower[num]
+    public override fun getUpperBound(num: Int, point: Point<Double>): Double? = upper[num]
 
-    override fun getUpperBound(num: Int, point: Point<Double>): Double? = upper[num]
+    public override fun getUpperBound(num: Int): Double? = upper[num]
 
-    override fun getUpperBound(num: Int): Double? = upper[num]
-
-    override fun nearestInDomain(point: Point<Double>): Point<Double> {
+    public override fun nearestInDomain(point: Point<Double>): Point<Double> {
         val res = DoubleArray(point.size) { i ->
             when {
                 point[i] < lower[i] -> lower[i]
@@ -53,16 +52,14 @@ class HyperSquareDomain(private val lower: RealBuffer, private val upper: RealBu
         return RealBuffer(*res)
     }
 
-    override fun volume(): Double {
+    public override fun volume(): Double {
         var res = 1.0
+
         for (i in 0 until dimension) {
-            if (lower[i].isInfinite() || upper[i].isInfinite()) {
-                return Double.POSITIVE_INFINITY
-            }
-            if (upper[i] > lower[i]) {
-                res *= upper[i] - lower[i]
-            }
+            if (lower[i].isInfinite() || upper[i].isInfinite()) return Double.POSITIVE_INFINITY
+            if (upper[i] > lower[i]) res *= upper[i] - lower[i]
         }
+
         return res
     }
 }

kmath-core/src/commonMain/kotlin/kscience/kmath/domains/RealDomain.kt

@@ -13,17 +13,17 @@
  * See the License for the specific language governing permissions and
  * limitations under the License.
  */
-package scientifik.kmath.domains
+package kscience.kmath.domains
 
-import scientifik.kmath.linear.Point
+import kscience.kmath.linear.Point
 
 /**
  * n-dimensional volume
  *
  * @author Alexander Nozik
  */
-interface RealDomain : Domain<Double> {
-    fun nearestInDomain(point: Point<Double>): Point<Double>
+public interface RealDomain : Domain<Double> {
+    public fun nearestInDomain(point: Point<Double>): Point<Double>
 
     /**
      * The lower edge for the domain going down from point
@@ -31,7 +31,7 @@ interface RealDomain : Domain<Double> {
      * @param point
      * @return
      */
-    fun getLowerBound(num: Int, point: Point<Double>): Double?
+    public fun getLowerBound(num: Int, point: Point<Double>): Double?
 
     /**
      * The upper edge of the domain going up from point
@@ -39,25 +39,25 @@ interface RealDomain : Domain<Double> {
      * @param point
      * @return
      */
-    fun getUpperBound(num: Int, point: Point<Double>): Double?
+    public fun getUpperBound(num: Int, point: Point<Double>): Double?
 
     /**
      * Global lower edge
      * @param num
      * @return
      */
-    fun getLowerBound(num: Int): Double?
+    public fun getLowerBound(num: Int): Double?
 
     /**
      * Global upper edge
      * @param num
      * @return
      */
-    fun getUpperBound(num: Int): Double?
+    public fun getUpperBound(num: Int): Double?
 
     /**
      * Hyper volume
      * @return
      */
-    fun volume(): Double
+    public fun volume(): Double
 }

kmath-core/src/commonMain/kotlin/kscience/kmath/domains/UnconstrainedDomain.kt

@@ -0,0 +1,34 @@
+/* 
+ * Copyright 2015 Alexander Nozik.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package kscience.kmath.domains
+
+import kscience.kmath.linear.Point
+
+public class UnconstrainedDomain(public override val dimension: Int) : RealDomain {
+    public override operator fun contains(point: Point<Double>): Boolean = true
+
+    public override fun getLowerBound(num: Int, point: Point<Double>): Double? = Double.NEGATIVE_INFINITY
+
+    public override fun getLowerBound(num: Int): Double? = Double.NEGATIVE_INFINITY
+
+    public override fun getUpperBound(num: Int, point: Point<Double>): Double? = Double.POSITIVE_INFINITY
+
+    public override fun getUpperBound(num: Int): Double? = Double.POSITIVE_INFINITY
+
+    public override fun nearestInDomain(point: Point<Double>): Point<Double> = point
+
+    public override fun volume(): Double = Double.POSITIVE_INFINITY
+}

kmath-core/src/commonMain/kotlin/kscience/kmath/domains/UnivariateDomain.kt

@@ -0,0 +1,49 @@
+package kscience.kmath.domains
+
+import kscience.kmath.linear.Point
+import kscience.kmath.structures.asBuffer
+
+public inline class UnivariateDomain(public val range: ClosedFloatingPointRange<Double>) : RealDomain {
+    public override val dimension: Int
+        get() = 1
+
+    public operator fun contains(d: Double): Boolean = range.contains(d)
+
+    public override operator fun contains(point: Point<Double>): Boolean {
+        require(point.size == 0)
+        return contains(point[0])
+    }
+
+    public override fun nearestInDomain(point: Point<Double>): Point<Double> {
+        require(point.size == 1)
+        val value = point[0]
+
+        return when {
+            value in range -> point
+            value >= range.endInclusive -> doubleArrayOf(range.endInclusive).asBuffer()
+            else -> doubleArrayOf(range.start).asBuffer()
+        }
+    }
+
+    public override fun getLowerBound(num: Int, point: Point<Double>): Double? {
+        require(num == 0)
+        return range.start
+    }
+
+    public override fun getUpperBound(num: Int, point: Point<Double>): Double? {
+        require(num == 0)
+        return range.endInclusive
+    }
+
+    public override fun getLowerBound(num: Int): Double? {
+        require(num == 0)
+        return range.start
+    }
+
+    public override fun getUpperBound(num: Int): Double? {
+        require(num == 0)
+        return range.endInclusive
+    }
+
+    public override fun volume(): Double = range.endInclusive - range.start
+}

kmath-core/src/commonMain/kotlin/kscience/kmath/expressions/Expression.kt

@@ -0,0 +1,41 @@
+package kscience.kmath.expressions
+
+import kscience.kmath.operations.Algebra
+
+/**
+ * An elementary function that could be invoked on a map of arguments
+ */
+public fun interface Expression<T> {
+    /**
+     * Calls this expression from arguments.
+     *
+     * @param arguments the map of arguments.
+     * @return the value.
+     */
+    public operator fun invoke(arguments: Map<String, T>): T
+
+    public companion object
+}
+
+/**
+ * Calls this expression from arguments.
+ *
+ * @param pairs the pair of arguments' names to values.
+ * @return the value.
+ */
+public operator fun <T> Expression<T>.invoke(vararg pairs: Pair<String, T>): T = invoke(mapOf(*pairs))
+
+/**
+ * A context for expression construction
+ */
+public interface ExpressionAlgebra<T, E> : Algebra<E> {
+    /**
+     * Introduce a variable into expression context
+     */
+    public fun variable(name: String, default: T? = null): E
+
+    /**
+     * A constant expression which does not depend on arguments
+     */
+    public fun const(value: T): E
+}

kmath-core/src/commonMain/kotlin/kscience/kmath/expressions/FunctionalExpressionAlgebra.kt

@@ -0,0 +1,171 @@
+package kscience.kmath.expressions
+
+import kscience.kmath.operations.*
+
+internal class FunctionalUnaryOperation<T>(val context: Algebra<T>, val name: String, private val expr: Expression<T>) :
+    Expression<T> {
+    public override operator fun invoke(arguments: Map<String, T>): T =
+        context.unaryOperation(name, expr.invoke(arguments))
+}
+
+internal class FunctionalBinaryOperation<T>(
+    val context: Algebra<T>,
+    val name: String,
+    val first: Expression<T>,
+    val second: Expression<T>
+) : Expression<T> {
+    public override operator fun invoke(arguments: Map<String, T>): T =
+        context.binaryOperation(name, first.invoke(arguments), second.invoke(arguments))
+}
+
+internal class FunctionalVariableExpression<T>(val name: String, val default: T? = null) : Expression<T> {
+    public override operator fun invoke(arguments: Map<String, T>): T =
+        arguments[name] ?: default ?: error("Parameter not found: $name")
+}
+
+internal class FunctionalConstantExpression<T>(val value: T) : Expression<T> {
+    public override operator fun invoke(arguments: Map<String, T>): T = value
+}
+
+internal class FunctionalConstProductExpression<T>(
+    val context: Space<T>,
+    private val expr: Expression<T>,
+    val const: Number
+) : Expression<T> {
+    public override operator fun invoke(arguments: Map<String, T>): T = context.multiply(expr.invoke(arguments), const)
+}
+
+/**
+ * A context class for [Expression] construction.
+ *
+ * @param algebra The algebra to provide for Expressions built.
+ */
+public abstract class FunctionalExpressionAlgebra<T, A : Algebra<T>>(public val algebra: A) :
+    ExpressionAlgebra<T, Expression<T>> {
+    /**
+     * Builds an Expression of constant expression which does not depend on arguments.
+     */
+    public override fun const(value: T): Expression<T> = FunctionalConstantExpression(value)
+
+    /**
+     * Builds an Expression to access a variable.
+     */
+    public override fun variable(name: String, default: T?): Expression<T> = FunctionalVariableExpression(name, default)
+
+    /**
+     * Builds an Expression of dynamic call of binary operation [operation] on [left] and [right].
+     */
+    public override fun binaryOperation(operation: String, left: Expression<T>, right: Expression<T>): Expression<T> =
+        FunctionalBinaryOperation(algebra, operation, left, right)
+
+    /**
+     * Builds an Expression of dynamic call of unary operation with name [operation] on [arg].
+     */
+    public override fun unaryOperation(operation: String, arg: Expression<T>): Expression<T> =
+        FunctionalUnaryOperation(algebra, operation, arg)
+}
+
+/**
+ * A context class for [Expression] construction for [Space] algebras.
+ */
+public open class FunctionalExpressionSpace<T, A : Space<T>>(algebra: A) :
+    FunctionalExpressionAlgebra<T, A>(algebra), Space<Expression<T>> {
+    public override val zero: Expression<T> get() = const(algebra.zero)
+
+    /**
+     * Builds an Expression of addition of two another expressions.
+     */
+    public override fun add(a: Expression<T>, b: Expression<T>): Expression<T> =
+        binaryOperation(SpaceOperations.PLUS_OPERATION, a, b)
+
+    /**
+     * Builds an Expression of multiplication of expression by number.
+     */
+    public override fun multiply(a: Expression<T>, k: Number): Expression<T> =
+        FunctionalConstProductExpression(algebra, a, k)
+
+    public operator fun Expression<T>.plus(arg: T): Expression<T> = this + const(arg)
+    public operator fun Expression<T>.minus(arg: T): Expression<T> = this - const(arg)
+    public operator fun T.plus(arg: Expression<T>): Expression<T> = arg + this
+    public operator fun T.minus(arg: Expression<T>): Expression<T> = arg - this
+
+    public override fun unaryOperation(operation: String, arg: Expression<T>): Expression<T> =
+        super<FunctionalExpressionAlgebra>.unaryOperation(operation, arg)
+
+    public override fun binaryOperation(operation: String, left: Expression<T>, right: Expression<T>): Expression<T> =
+        super<FunctionalExpressionAlgebra>.binaryOperation(operation, left, right)
+}
+
+public open class FunctionalExpressionRing<T, A>(algebra: A) : FunctionalExpressionSpace<T, A>(algebra),
+    Ring<Expression<T>> where  A : Ring<T>, A : NumericAlgebra<T> {
+    public override val one: Expression<T>
+        get() = const(algebra.one)
+
+    /**
+     * Builds an Expression of multiplication of two expressions.
+     */
+    public override fun multiply(a: Expression<T>, b: Expression<T>): Expression<T> =
+        binaryOperation(RingOperations.TIMES_OPERATION, a, b)
+
+    public operator fun Expression<T>.times(arg: T): Expression<T> = this * const(arg)
+    public operator fun T.times(arg: Expression<T>): Expression<T> = arg * this
+
+    public override fun unaryOperation(operation: String, arg: Expression<T>): Expression<T> =
+        super<FunctionalExpressionSpace>.unaryOperation(operation, arg)
+
+    public override fun binaryOperation(operation: String, left: Expression<T>, right: Expression<T>): Expression<T> =
+        super<FunctionalExpressionSpace>.binaryOperation(operation, left, right)
+}
+
+public open class FunctionalExpressionField<T, A>(algebra: A) :
+    FunctionalExpressionRing<T, A>(algebra),
+    Field<Expression<T>> where A : Field<T>, A : NumericAlgebra<T> {
+    /**
+     * Builds an Expression of division an expression by another one.
+     */
+    public override fun divide(a: Expression<T>, b: Expression<T>): Expression<T> =
+        binaryOperation(FieldOperations.DIV_OPERATION, a, b)
+
+    public operator fun Expression<T>.div(arg: T): Expression<T> = this / const(arg)
+    public operator fun T.div(arg: Expression<T>): Expression<T> = arg / this
+
+    public override fun unaryOperation(operation: String, arg: Expression<T>): Expression<T> =
+        super<FunctionalExpressionRing>.unaryOperation(operation, arg)
+
+    public override fun binaryOperation(operation: String, left: Expression<T>, right: Expression<T>): Expression<T> =
+        super<FunctionalExpressionRing>.binaryOperation(operation, left, right)
+}
+
+public open class FunctionalExpressionExtendedField<T, A>(algebra: A) :
+    FunctionalExpressionField<T, A>(algebra),
+    ExtendedField<Expression<T>> where A : ExtendedField<T>, A : NumericAlgebra<T> {
+    public override fun sin(arg: Expression<T>): Expression<T> = unaryOperation(TrigonometricOperations.SIN_OPERATION, arg)
+    public override fun cos(arg: Expression<T>): Expression<T> = unaryOperation(TrigonometricOperations.COS_OPERATION, arg)
+    public override fun asin(arg: Expression<T>): Expression<T> = unaryOperation(TrigonometricOperations.ASIN_OPERATION, arg)
+    public override fun acos(arg: Expression<T>): Expression<T> = unaryOperation(TrigonometricOperations.ACOS_OPERATION, arg)
+    public override fun atan(arg: Expression<T>): Expression<T> = unaryOperation(TrigonometricOperations.ATAN_OPERATION, arg)
+
+    public override fun power(arg: Expression<T>, pow: Number): Expression<T> =
+        binaryOperation(PowerOperations.POW_OPERATION, arg, number(pow))
+
+    public override fun exp(arg: Expression<T>): Expression<T> = unaryOperation(ExponentialOperations.EXP_OPERATION, arg)
+    public override fun ln(arg: Expression<T>): Expression<T> = unaryOperation(ExponentialOperations.LN_OPERATION, arg)
+
+    public override fun unaryOperation(operation: String, arg: Expression<T>): Expression<T> =
+        super<FunctionalExpressionField>.unaryOperation(operation, arg)
+
+    public override fun binaryOperation(operation: String, left: Expression<T>, right: Expression<T>): Expression<T> =
+        super<FunctionalExpressionField>.binaryOperation(operation, left, right)
+}
+
+public inline fun <T, A : Space<T>> A.expressionInSpace(block: FunctionalExpressionSpace<T, A>.() -> Expression<T>): Expression<T> =
+    FunctionalExpressionSpace(this).block()
+
+public inline fun <T, A : Ring<T>> A.expressionInRing(block: FunctionalExpressionRing<T, A>.() -> Expression<T>): Expression<T> =
+    FunctionalExpressionRing(this).block()
+
+public inline fun <T, A : Field<T>> A.expressionInField(block: FunctionalExpressionField<T, A>.() -> Expression<T>): Expression<T> =
+    FunctionalExpressionField(this).block()
+
+public inline fun <T, A : ExtendedField<T>> A.expressionInExtendedField(block: FunctionalExpressionExtendedField<T, A>.() -> Expression<T>): Expression<T> =
+    FunctionalExpressionExtendedField(this).block()

kmath-core/src/commonMain/kotlin/kscience/kmath/expressions/expressionBuilders.kt

@@ -1,17 +1,16 @@
-package scientifik.kmath.expressions
+package kscience.kmath.expressions
 
-import scientifik.kmath.operations.ExtendedField
-import scientifik.kmath.operations.Field
-import scientifik.kmath.operations.Ring
-import scientifik.kmath.operations.Space
-import kotlin.contracts.ExperimentalContracts
+import kscience.kmath.operations.ExtendedField
+import kscience.kmath.operations.Field
+import kscience.kmath.operations.Ring
+import kscience.kmath.operations.Space
 import kotlin.contracts.InvocationKind
 import kotlin.contracts.contract
 
 /**
  * Creates a functional expression with this [Space].
  */
-inline fun <T> Space<T>.spaceExpression(block: FunctionalExpressionSpace<T, Space<T>>.() -> Expression<T>): Expression<T> {
+public inline fun <T> Space<T>.spaceExpression(block: FunctionalExpressionSpace<T, Space<T>>.() -> Expression<T>): Expression<T> {
     contract { callsInPlace(block, InvocationKind.EXACTLY_ONCE) }
     return FunctionalExpressionSpace(this).block()
 }
@@ -19,7 +18,7 @@ inline fun <T> Space<T>.spaceExpression(block: FunctionalExpressionSpace<T, Spac
 /**
  * Creates a functional expression with this [Ring].
  */
-inline fun <T> Ring<T>.ringExpression(block: FunctionalExpressionRing<T, Ring<T>>.() -> Expression<T>): Expression<T> {
+public inline fun <T> Ring<T>.ringExpression(block: FunctionalExpressionRing<T, Ring<T>>.() -> Expression<T>): Expression<T> {
     contract { callsInPlace(block, InvocationKind.EXACTLY_ONCE) }
     return FunctionalExpressionRing(this).block()
 }
@@ -27,7 +26,7 @@ inline fun <T> Ring<T>.ringExpression(block: FunctionalExpressionRing<T, Ring<T>
 /**
  * Creates a functional expression with this [Field].
  */
-inline fun <T> Field<T>.fieldExpression(block: FunctionalExpressionField<T, Field<T>>.() -> Expression<T>): Expression<T> {
+public inline fun <T> Field<T>.fieldExpression(block: FunctionalExpressionField<T, Field<T>>.() -> Expression<T>): Expression<T> {
     contract { callsInPlace(block, InvocationKind.EXACTLY_ONCE) }
     return FunctionalExpressionField(this).block()
 }
@@ -35,7 +34,7 @@ inline fun <T> Field<T>.fieldExpression(block: FunctionalExpressionField<T, Fiel
 /**
  * Creates a functional expression with this [ExtendedField].
  */
-inline fun <T> ExtendedField<T>.extendedFieldExpression(block: FunctionalExpressionExtendedField<T, ExtendedField<T>>.() -> Expression<T>): Expression<T> {
+public inline fun <T> ExtendedField<T>.extendedFieldExpression(block: FunctionalExpressionExtendedField<T, ExtendedField<T>>.() -> Expression<T>): Expression<T> {
     contract { callsInPlace(block, InvocationKind.EXACTLY_ONCE) }
     return FunctionalExpressionExtendedField(this).block()
 }

kmath-core/src/commonMain/kotlin/kscience/kmath/linear/BufferMatrix.kt

@@ -0,0 +1,113 @@
+package kscience.kmath.linear
+
+import kscience.kmath.operations.RealField
+import kscience.kmath.operations.Ring
+import kscience.kmath.structures.*
+
+/**
+ * Basic implementation of Matrix space based on [NDStructure]
+ */
+public class BufferMatrixContext<T : Any, R : Ring<T>>(
+    public override val elementContext: R,
+    private val bufferFactory: BufferFactory<T>
+) : GenericMatrixContext<T, R> {
+    public override fun produce(rows: Int, columns: Int, initializer: (i: Int, j: Int) -> T): BufferMatrix<T> {
+        val buffer = bufferFactory(rows * columns) { offset -> initializer(offset / columns, offset % columns) }
+        return BufferMatrix(rows, columns, buffer)
+    }
+
+    public override fun point(size: Int, initializer: (Int) -> T): Point<T> = bufferFactory(size, initializer)
+
+    public companion object
+}
+
+@Suppress("OVERRIDE_BY_INLINE")
+public object RealMatrixContext : GenericMatrixContext<Double, RealField> {
+    public override val elementContext: RealField
+        get() = RealField
+
+    public override inline fun produce(
+        rows: Int,
+        columns: Int,
+        initializer: (i: Int, j: Int) -> Double
+    ): Matrix<Double> {
+        val buffer = RealBuffer(rows * columns) { offset -> initializer(offset / columns, offset % columns) }
+        return BufferMatrix(rows, columns, buffer)
+    }
+
+    public override inline fun point(size: Int, initializer: (Int) -> Double): Point<Double> =
+        RealBuffer(size, initializer)
+}
+
+public class BufferMatrix<T : Any>(
+    public override val rowNum: Int,
+    public override val colNum: Int,
+    public val buffer: Buffer<out T>,
+    public override val features: Set<MatrixFeature> = emptySet()
+) : FeaturedMatrix<T> {
+    override val shape: IntArray
+        get() = intArrayOf(rowNum, colNum)
+
+    init {
+        require(buffer.size == rowNum * colNum) { "Dimension mismatch for matrix structure" }
+    }
+
+    public override fun suggestFeature(vararg features: MatrixFeature): BufferMatrix<T> =
+        BufferMatrix(rowNum, colNum, buffer, this.features + features)
+
+    public override operator fun get(index: IntArray): T = get(index[0], index[1])
+    public override operator fun get(i: Int, j: Int): T = buffer[i * colNum + j]
+
+    public override fun elements(): Sequence<Pair<IntArray, T>> = sequence {
+        for (i in 0 until rowNum) for (j in 0 until colNum) yield(intArrayOf(i, j) to get(i, j))
+    }
+
+    public override fun equals(other: Any?): Boolean {
+        if (this === other) return true
+
+        return when (other) {
+            is NDStructure<*> -> return NDStructure.equals(this, other)
+            else -> false
+        }
+    }
+
+    public override fun hashCode(): Int {
+        var result = buffer.hashCode()
+        result = 31 * result + features.hashCode()
+        return result
+    }
+
+    public override fun toString(): String {
+        return if (rowNum <= 5 && colNum <= 5)
+            "Matrix(rowsNum = $rowNum, colNum = $colNum, features=$features)\n" +
+                    rows.asSequence().joinToString(prefix = "(", postfix = ")", separator = "\n ") { buffer ->
+                        buffer.asSequence().joinToString(separator = "\t") { it.toString() }
+                    }
+        else "Matrix(rowsNum = $rowNum, colNum = $colNum, features=$features)"
+    }
+}
+
+/**
+ * Optimized dot product for real matrices
+ */
+public infix fun BufferMatrix<Double>.dot(other: BufferMatrix<Double>): BufferMatrix<Double> {
+    require(colNum == other.rowNum) { "Matrix dot operation dimension mismatch: ($rowNum, $colNum) x (${other.rowNum}, ${other.colNum})" }
+    val array = DoubleArray(this.rowNum * other.colNum)
+
+    //convert to array to insure there is not memory indirection
+    fun Buffer<out Double>.unsafeArray() = if (this is RealBuffer)
+        array
+    else
+        DoubleArray(size) { get(it) }
+
+    val a = this.buffer.unsafeArray()
+    val b = other.buffer.unsafeArray()
+
+    for (i in (0 until rowNum))
+        for (j in (0 until other.colNum))
+            for (k in (0 until colNum))
+                array[i * other.colNum + j] += a[i * colNum + k] * b[k * other.colNum + j]
+
+    val buffer = RealBuffer(array)
+    return BufferMatrix(rowNum, other.colNum, buffer)
+}

kmath-core/src/commonMain/kotlin/kscience/kmath/linear/FeaturedMatrix.kt

@@ -0,0 +1,82 @@
+package kscience.kmath.linear
+
+import kscience.kmath.operations.Ring
+import kscience.kmath.structures.Matrix
+import kscience.kmath.structures.Structure2D
+import kscience.kmath.structures.asBuffer
+import kotlin.math.sqrt
+
+/**
+ * A 2d structure plus optional matrix-specific features
+ */
+public interface FeaturedMatrix<T : Any> : Matrix<T> {
+    override val shape: IntArray get() = intArrayOf(rowNum, colNum)
+    public val features: Set<MatrixFeature>
+
+    /**
+     * Suggest new feature for this matrix. The result is the new matrix that may or may not reuse existing data structure.
+     *
+     * The implementation does not guarantee to check that matrix actually have the feature, so one should be careful to
+     * add only those features that are valid.
+     */
+    public fun suggestFeature(vararg features: MatrixFeature): FeaturedMatrix<T>
+
+    public companion object
+}
+
+public inline fun Structure2D.Companion.real(rows: Int, columns: Int, initializer: (Int, Int) -> Double): Matrix<Double> =
+    MatrixContext.real.produce(rows, columns, initializer)
+
+/**
+ * Build a square matrix from given elements.
+ */
+public fun <T : Any> Structure2D.Companion.square(vararg elements: T): FeaturedMatrix<T> {
+    val size: Int = sqrt(elements.size.toDouble()).toInt()
+    require(size * size == elements.size) { "The number of elements ${elements.size} is not a full square" }
+    val buffer = elements.asBuffer()
+    return BufferMatrix(size, size, buffer)
+}
+
+public val Matrix<*>.features: Set<MatrixFeature> get() = (this as? FeaturedMatrix)?.features ?: emptySet()
+
+/**
+ * Check if matrix has the given feature class
+ */
+public inline fun <reified T : Any> Matrix<*>.hasFeature(): Boolean =
+    features.find { it is T } != null
+
+/**
+ * Get the first feature matching given class. Does not guarantee that matrix has only one feature matching the criteria
+ */
+public inline fun <reified T : Any> Matrix<*>.getFeature(): T? =
+    features.filterIsInstance<T>().firstOrNull()
+
+/**
+ * Diagonal matrix of ones. The matrix is virtual no actual matrix is created
+ */
+public fun <T : Any, R : Ring<T>> GenericMatrixContext<T, R>.one(rows: Int, columns: Int): FeaturedMatrix<T> =
+    VirtualMatrix(rows, columns, DiagonalFeature) { i, j ->
+        if (i == j) elementContext.one else elementContext.zero
+    }
+
+
+/**
+ * A virtual matrix of zeroes
+ */
+public fun <T : Any, R : Ring<T>> GenericMatrixContext<T, R>.zero(rows: Int, columns: Int): FeaturedMatrix<T> =
+    VirtualMatrix(rows, columns) { _, _ -> elementContext.zero }
+
+public class TransposedFeature<T : Any>(public val original: Matrix<T>) : MatrixFeature
+
+/**
+ * Create a virtual transposed matrix without copying anything. `A.transpose().transpose() === A`
+ */
+public fun <T : Any> Matrix<T>.transpose(): Matrix<T> {
+    return getFeature<TransposedFeature<T>>()?.original ?: VirtualMatrix(
+        colNum,
+        rowNum,
+        setOf(TransposedFeature(this))
+    ) { i, j -> get(j, i) }
+}
+
+public infix fun Matrix<Double>.dot(other: Matrix<Double>): Matrix<Double> = with(MatrixContext.real) { dot(other) }

kmath-core/src/commonMain/kotlin/kscience/kmath/linear/LUPDecomposition.kt

@@ -1,25 +1,25 @@
-package scientifik.kmath.linear
+package kscience.kmath.linear
 
-import scientifik.kmath.operations.Field
-import scientifik.kmath.operations.RealField
-import scientifik.kmath.operations.Ring
-import scientifik.kmath.operations.invoke
-import scientifik.kmath.structures.BufferAccessor2D
-import scientifik.kmath.structures.Matrix
-import scientifik.kmath.structures.Structure2D
+import kscience.kmath.operations.Field
+import kscience.kmath.operations.RealField
+import kscience.kmath.operations.Ring
+import kscience.kmath.operations.invoke
+import kscience.kmath.structures.BufferAccessor2D
+import kscience.kmath.structures.Matrix
+import kscience.kmath.structures.Structure2D
 import kotlin.reflect.KClass
 
 /**
  * Common implementation of [LUPDecompositionFeature]
  */
-class LUPDecomposition<T : Any>(
-    val context: GenericMatrixContext<T, out Field<T>>,
-    val lu: Structure2D<T>,
-    val pivot: IntArray,
+public class LUPDecomposition<T : Any>(
+    public val context: GenericMatrixContext<T, out Field<T>>,
+    public val lu: Structure2D<T>,
+    public val pivot: IntArray,
     private val even: Boolean
 ) : LUPDecompositionFeature<T>, DeterminantFeature<T> {
-
-    val elementContext: Field<T> get() = context.elementContext
+    public val elementContext: Field<T>
+        get() = context.elementContext
 
     /**
      * Returns the matrix L of the decomposition.
@@ -44,7 +44,6 @@ class LUPDecomposition<T : Any>(
         if (j >= i) lu[i, j] else elementContext.zero
     }
 
-
     /**
      * Returns the P rows permutation matrix.
      *
@@ -55,7 +54,6 @@ class LUPDecomposition<T : Any>(
         if (j == pivot[i]) elementContext.one else elementContext.zero
     }
 
-
     /**
      * Return the determinant of the matrix
      * @return determinant of the matrix
@@ -66,22 +64,18 @@ class LUPDecomposition<T : Any>(
 
 }
 
-fun <T : Comparable<T>, F : Field<T>> GenericMatrixContext<T, F>.abs(value: T): T =
+public fun <T : Comparable<T>, F : Field<T>> GenericMatrixContext<T, F>.abs(value: T): T =
     if (value > elementContext.zero) value else elementContext { -value }
 
-
 /**
  * Create a lup decomposition of generic matrix
  */
-fun <T : Comparable<T>, F : Field<T>> GenericMatrixContext<T, F>.lup(
+public inline fun <T : Comparable<T>, F : Field<T>> GenericMatrixContext<T, F>.lup(
     type: KClass<T>,
     matrix: Matrix<T>,
     checkSingular: (T) -> Boolean
 ): LUPDecomposition<T> {
-    if (matrix.rowNum != matrix.colNum) {
-        error("LU decomposition supports only square matrices")
-    }
-
+    require(matrix.rowNum == matrix.colNum) { "LU decomposition supports only square matrices" }
     val m = matrix.colNum
     val pivot = IntArray(matrix.rowNum)
 
@@ -154,15 +148,15 @@ fun <T : Comparable<T>, F : Field<T>> GenericMatrixContext<T, F>.lup(
     }
 }
 
-inline fun <reified T : Comparable<T>, F : Field<T>> GenericMatrixContext<T, F>.lup(
+public inline fun <reified T : Comparable<T>, F : Field<T>> GenericMatrixContext<T, F>.lup(
     matrix: Matrix<T>,
-    noinline checkSingular: (T) -> Boolean
+    checkSingular: (T) -> Boolean
 ): LUPDecomposition<T> = lup(T::class, matrix, checkSingular)
 
-fun GenericMatrixContext<Double, RealField>.lup(matrix: Matrix<Double>): LUPDecomposition<Double> =
+public fun GenericMatrixContext<Double, RealField>.lup(matrix: Matrix<Double>): LUPDecomposition<Double> =
     lup(Double::class, matrix) { it < 1e-11 }
 
-fun <T : Any> LUPDecomposition<T>.solve(type: KClass<T>, matrix: Matrix<T>): Matrix<T> {
+public fun <T : Any> LUPDecomposition<T>.solve(type: KClass<T>, matrix: Matrix<T>): Matrix<T> {
     require(matrix.rowNum == pivot.size) { "Matrix dimension mismatch. Expected ${pivot.size}, but got ${matrix.colNum}" }
 
     BufferAccessor2D(type, matrix.rowNum, matrix.colNum).run {
@@ -207,27 +201,27 @@ fun <T : Any> LUPDecomposition<T>.solve(type: KClass<T>, matrix: Matrix<T>): Mat
     }
 }
 
-inline fun <reified T : Any> LUPDecomposition<T>.solve(matrix: Matrix<T>): Matrix<T> = solve(T::class, matrix)
+public inline fun <reified T : Any> LUPDecomposition<T>.solve(matrix: Matrix<T>): Matrix<T> = solve(T::class, matrix)
 
 /**
  * Solve a linear equation **a*x = b**
  */
-inline fun <reified T : Comparable<T>, F : Field<T>> GenericMatrixContext<T, F>.solve(
+public inline fun <reified T : Comparable<T>, F : Field<T>> GenericMatrixContext<T, F>.solve(
     a: Matrix<T>,
     b: Matrix<T>,
-    noinline checkSingular: (T) -> Boolean
+    checkSingular: (T) -> Boolean
 ): Matrix<T> {
     // Use existing decomposition if it is provided by matrix
     val decomposition = a.getFeature() ?: lup(T::class, a, checkSingular)
     return decomposition.solve(T::class, b)
 }
 
-fun RealMatrixContext.solve(a: Matrix<Double>, b: Matrix<Double>): Matrix<Double> = solve(a, b) { it < 1e-11 }
+public fun RealMatrixContext.solve(a: Matrix<Double>, b: Matrix<Double>): Matrix<Double> = solve(a, b) { it < 1e-11 }
 
-inline fun <reified T : Comparable<T>, F : Field<T>> GenericMatrixContext<T, F>.inverse(
+public inline fun <reified T : Comparable<T>, F : Field<T>> GenericMatrixContext<T, F>.inverse(
     matrix: Matrix<T>,
-    noinline checkSingular: (T) -> Boolean
+    checkSingular: (T) -> Boolean
 ): Matrix<T> = solve(matrix, one(matrix.rowNum, matrix.colNum), checkSingular)
 
-fun RealMatrixContext.inverse(matrix: Matrix<Double>): Matrix<Double> =
+public fun RealMatrixContext.inverse(matrix: Matrix<Double>): Matrix<Double> =
     solve(matrix, one(matrix.rowNum, matrix.colNum)) { it < 1e-11 }

kmath-core/src/commonMain/kotlin/kscience/kmath/linear/LinearAlgebra.kt

@@ -0,0 +1,27 @@
+package kscience.kmath.linear
+
+import kscience.kmath.structures.Buffer
+import kscience.kmath.structures.Matrix
+import kscience.kmath.structures.VirtualBuffer
+
+public typealias Point<T> = Buffer<T>
+
+/**
+ * A group of methods to resolve equation A dot X = B, where A and B are matrices or vectors
+ */
+public interface LinearSolver<T : Any> {
+    public fun solve(a: Matrix<T>, b: Matrix<T>): Matrix<T>
+    public fun solve(a: Matrix<T>, b: Point<T>): Point<T> = solve(a, b.asMatrix()).asPoint()
+    public fun inverse(a: Matrix<T>): Matrix<T>
+}
+
+/**
+ * Convert matrix to vector if it is possible
+ */
+public fun <T : Any> Matrix<T>.asPoint(): Point<T> =
+    if (this.colNum == 1)
+        VirtualBuffer(rowNum) { get(it, 0) }
+    else
+        error("Can't convert matrix with more than one column to vector")
+
+public fun <T : Any> Point<T>.asMatrix(): VirtualMatrix<T> = VirtualMatrix(size, 1) { i, _ -> get(i) }

kmath-core/src/commonMain/kotlin/kscience/kmath/linear/MatrixBuilder.kt

@@ -1,12 +1,12 @@
-package scientifik.kmath.linear
+package kscience.kmath.linear
 
-import scientifik.kmath.structures.Buffer
-import scientifik.kmath.structures.BufferFactory
-import scientifik.kmath.structures.Structure2D
-import scientifik.kmath.structures.asBuffer
+import kscience.kmath.structures.Buffer
+import kscience.kmath.structures.BufferFactory
+import kscience.kmath.structures.Structure2D
+import kscience.kmath.structures.asBuffer
 
-class MatrixBuilder(val rows: Int, val columns: Int) {
-    operator fun <T : Any> invoke(vararg elements: T): FeaturedMatrix<T> {
+public class MatrixBuilder(public val rows: Int, public val columns: Int) {
+    public operator fun <T : Any> invoke(vararg elements: T): FeaturedMatrix<T> {
         require(rows * columns == elements.size) { "The number of elements ${elements.size} is not equal $rows * $columns" }
         val buffer = elements.asBuffer()
         return BufferMatrix(rows, columns, buffer)
@@ -15,14 +15,14 @@ class MatrixBuilder(val rows: Int, val columns: Int) {
     //TODO add specific matrix builder functions like diagonal, etc
 }
 
-fun Structure2D.Companion.build(rows: Int, columns: Int): MatrixBuilder = MatrixBuilder(rows, columns)
+public fun Structure2D.Companion.build(rows: Int, columns: Int): MatrixBuilder = MatrixBuilder(rows, columns)
 
-fun <T : Any> Structure2D.Companion.row(vararg values: T): FeaturedMatrix<T> {
+public fun <T : Any> Structure2D.Companion.row(vararg values: T): FeaturedMatrix<T> {
     val buffer = values.asBuffer()
     return BufferMatrix(1, values.size, buffer)
 }
 
-inline fun <reified T : Any> Structure2D.Companion.row(
+public inline fun <reified T : Any> Structure2D.Companion.row(
     size: Int,
     factory: BufferFactory<T> = Buffer.Companion::auto,
     noinline builder: (Int) -> T
@@ -31,12 +31,12 @@ inline fun <reified T : Any> Structure2D.Companion.row(
     return BufferMatrix(1, size, buffer)
 }
 
-fun <T : Any> Structure2D.Companion.column(vararg values: T): FeaturedMatrix<T> {
+public fun <T : Any> Structure2D.Companion.column(vararg values: T): FeaturedMatrix<T> {
     val buffer = values.asBuffer()
     return BufferMatrix(values.size, 1, buffer)
 }
 
-inline fun <reified T : Any> Structure2D.Companion.column(
+public inline fun <reified T : Any> Structure2D.Companion.column(
     size: Int,
     factory: BufferFactory<T> = Buffer.Companion::auto,
     noinline builder: (Int) -> T

kmath-core/src/commonMain/kotlin/kscience/kmath/linear/MatrixContext.kt

@@ -1,41 +1,42 @@
-package scientifik.kmath.linear
+package kscience.kmath.linear
 
-import scientifik.kmath.operations.Ring
-import scientifik.kmath.operations.SpaceOperations
-import scientifik.kmath.operations.invoke
-import scientifik.kmath.operations.sum
-import scientifik.kmath.structures.Buffer
-import scientifik.kmath.structures.BufferFactory
-import scientifik.kmath.structures.Matrix
-import scientifik.kmath.structures.asSequence
+import kscience.kmath.operations.Ring
+import kscience.kmath.operations.SpaceOperations
+import kscience.kmath.operations.invoke
+import kscience.kmath.operations.sum
+import kscience.kmath.structures.Buffer
+import kscience.kmath.structures.BufferFactory
+import kscience.kmath.structures.Matrix
+import kscience.kmath.structures.asSequence
 
 /**
  * Basic operations on matrices. Operates on [Matrix]
  */
-interface MatrixContext<T : Any> : SpaceOperations<Matrix<T>> {
+public interface MatrixContext<T : Any> : SpaceOperations<Matrix<T>> {
     /**
      * Produce a matrix with this context and given dimensions
      */
-    fun produce(rows: Int, columns: Int, initializer: (i: Int, j: Int) -> T): Matrix<T>
+    public fun produce(rows: Int, columns: Int, initializer: (i: Int, j: Int) -> T): Matrix<T>
 
-    infix fun Matrix<T>.dot(other: Matrix<T>): Matrix<T>
+    public infix fun Matrix<T>.dot(other: Matrix<T>): Matrix<T>
 
-    infix fun Matrix<T>.dot(vector: Point<T>): Point<T>
+    public infix fun Matrix<T>.dot(vector: Point<T>): Point<T>
 
-    operator fun Matrix<T>.times(value: T): Matrix<T>
+    public operator fun Matrix<T>.times(value: T): Matrix<T>
 
-    operator fun T.times(m: Matrix<T>): Matrix<T> = m * this
+    public operator fun T.times(m: Matrix<T>): Matrix<T> = m * this
 
-    companion object {
+    public companion object {
         /**
          * Non-boxing double matrix
          */
-        val real: RealMatrixContext = RealMatrixContext
+        public val real: RealMatrixContext
+            get() = RealMatrixContext
 
         /**
          * A structured matrix with custom buffer
          */
-        fun <T : Any, R : Ring<T>> buffered(
+        public fun <T : Any, R : Ring<T>> buffered(
             ring: R,
             bufferFactory: BufferFactory<T> = Buffer.Companion::boxing
         ): GenericMatrixContext<T, R> = BufferMatrixContext(ring, bufferFactory)
@@ -43,21 +44,21 @@ interface MatrixContext<T : Any> : SpaceOperations<Matrix<T>> {
         /**
          * Automatic buffered matrix, unboxed if it is possible
          */
-        inline fun <reified T : Any, R : Ring<T>> auto(ring: R): GenericMatrixContext<T, R> =
+        public inline fun <reified T : Any, R : Ring<T>> auto(ring: R): GenericMatrixContext<T, R> =
             buffered(ring, Buffer.Companion::auto)
     }
 }
 
-interface GenericMatrixContext<T : Any, R : Ring<T>> : MatrixContext<T> {
+public interface GenericMatrixContext<T : Any, R : Ring<T>> : MatrixContext<T> {
     /**
      * The ring context for matrix elements
      */
-    val elementContext: R
+    public val elementContext: R
 
     /**
      * Produce a point compatible with matrix space
      */
-    fun point(size: Int, initializer: (Int) -> T): Point<T>
+    public fun point(size: Int, initializer: (Int) -> T): Point<T>
 
     override infix fun Matrix<T>.dot(other: Matrix<T>): Matrix<T> {
         //TODO add typed error
@@ -102,7 +103,7 @@ interface GenericMatrixContext<T : Any, R : Ring<T>> : MatrixContext<T> {
     override fun multiply(a: Matrix<T>, k: Number): Matrix<T> =
         produce(a.rowNum, a.colNum) { i, j -> elementContext { a[i, j] * k } }
 
-    operator fun Number.times(matrix: FeaturedMatrix<T>): Matrix<T> = matrix * this
+    public operator fun Number.times(matrix: FeaturedMatrix<T>): Matrix<T> = matrix * this
 
     override operator fun Matrix<T>.times(value: T): Matrix<T> =
         produce(rowNum, colNum) { i, j -> elementContext { get(i, j) * value } }

kmath-core/src/commonMain/kotlin/kscience/kmath/linear/MatrixFeatures.kt

@@ -0,0 +1,62 @@
+package kscience.kmath.linear
+
+/**
+ * A marker interface representing some matrix feature like diagonal, sparse, zero, etc. Features used to optimize matrix
+ * operations performance in some cases.
+ */
+public interface MatrixFeature
+
+/**
+ * The matrix with this feature is considered to have only diagonal non-null elements
+ */
+public object DiagonalFeature : MatrixFeature
+
+/**
+ * Matrix with this feature has all zero elements
+ */
+public object ZeroFeature : MatrixFeature
+
+/**
+ * Matrix with this feature have unit elements on diagonal and zero elements in all other places
+ */
+public object UnitFeature : MatrixFeature
+
+/**
+ * Inverted matrix feature
+ */
+public interface InverseMatrixFeature<T : Any> : MatrixFeature {
+    public val inverse: FeaturedMatrix<T>
+}
+
+/**
+ * A determinant container
+ */
+public interface DeterminantFeature<T : Any> : MatrixFeature {
+    public val determinant: T
+}
+
+@Suppress("FunctionName")
+public fun <T : Any> DeterminantFeature(determinant: T): DeterminantFeature<T> = object : DeterminantFeature<T> {
+    override val determinant: T = determinant
+}
+
+/**
+ * Lower triangular matrix
+ */
+public object LFeature : MatrixFeature
+
+/**
+ * Upper triangular feature
+ */
+public object UFeature : MatrixFeature
+
+/**
+ * TODO add documentation
+ */
+public interface LUPDecompositionFeature<T : Any> : MatrixFeature {
+    public val l: FeaturedMatrix<T>
+    public val u: FeaturedMatrix<T>
+    public val p: FeaturedMatrix<T>
+}
+
+//TODO add sparse matrix feature

kmath-core/src/commonMain/kotlin/kscience/kmath/linear/VectorSpace.kt

@@ -1,21 +1,21 @@
-package scientifik.kmath.linear
+package kscience.kmath.linear
 
-import scientifik.kmath.operations.RealField
-import scientifik.kmath.operations.Space
-import scientifik.kmath.operations.invoke
-import scientifik.kmath.structures.Buffer
-import scientifik.kmath.structures.BufferFactory
+import kscience.kmath.operations.RealField
+import kscience.kmath.operations.Space
+import kscience.kmath.operations.invoke
+import kscience.kmath.structures.Buffer
+import kscience.kmath.structures.BufferFactory
 
 /**
  * A linear space for vectors.
  * Could be used on any point-like structure
  */
-interface VectorSpace<T : Any, S : Space<T>> : Space<Point<T>> {
-    val size: Int
-    val space: S
+public interface VectorSpace<T : Any, S : Space<T>> : Space<Point<T>> {
+    public val size: Int
+    public val space: S
     override val zero: Point<T> get() = produce { space.zero }
 
-    fun produce(initializer: (Int) -> T): Point<T>
+    public fun produce(initializer: (Int) -> T): Point<T>
 
     /**
      * Produce a space-element of this vector space for expressions
@@ -28,13 +28,13 @@ interface VectorSpace<T : Any, S : Space<T>> : Space<Point<T>> {
 
     //TODO add basis
 
-    companion object {
+    public companion object {
         private val realSpaceCache: MutableMap<Int, BufferVectorSpace<Double, RealField>> = hashMapOf()
 
         /**
          * Non-boxing double vector space
          */
-        fun real(size: Int): BufferVectorSpace<Double, RealField> = realSpaceCache.getOrPut(size) {
+        public fun real(size: Int): BufferVectorSpace<Double, RealField> = realSpaceCache.getOrPut(size) {
             BufferVectorSpace(
                 size,
                 RealField,
@@ -45,7 +45,7 @@ interface VectorSpace<T : Any, S : Space<T>> : Space<Point<T>> {
         /**
          * A structured vector space with custom buffer
          */
-        fun <T : Any, S : Space<T>> buffered(
+        public fun <T : Any, S : Space<T>> buffered(
             size: Int,
             space: S,
             bufferFactory: BufferFactory<T> = Buffer.Companion::boxing
@@ -54,16 +54,16 @@ interface VectorSpace<T : Any, S : Space<T>> : Space<Point<T>> {
         /**
          * Automatic buffered vector, unboxed if it is possible
          */
-        inline fun <reified T : Any, S : Space<T>> auto(size: Int, space: S): VectorSpace<T, S> =
+        public inline fun <reified T : Any, S : Space<T>> auto(size: Int, space: S): VectorSpace<T, S> =
             buffered(size, space, Buffer.Companion::auto)
     }
 }
 
 
-class BufferVectorSpace<T : Any, S : Space<T>>(
+public class BufferVectorSpace<T : Any, S : Space<T>>(
     override val size: Int,
     override val space: S,
-    val bufferFactory: BufferFactory<T>
+    public val bufferFactory: BufferFactory<T>
 ) : VectorSpace<T, S> {
     override fun produce(initializer: (Int) -> T): Buffer<T> = bufferFactory(size, initializer)
     //override fun produceElement(initializer: (Int) -> T): Vector<T, S> = BufferVector(this, produce(initializer))

kmath-core/src/commonMain/kotlin/kscience/kmath/linear/VirtualMatrix.kt

@@ -1,15 +1,19 @@
-package scientifik.kmath.linear
+package kscience.kmath.linear
 
-import scientifik.kmath.structures.Matrix
+import kscience.kmath.structures.Matrix
 
-class VirtualMatrix<T : Any>(
+public class VirtualMatrix<T : Any>(
     override val rowNum: Int,
     override val colNum: Int,
     override val features: Set<MatrixFeature> = emptySet(),
-    val generator: (i: Int, j: Int) -> T
+    public val generator: (i: Int, j: Int) -> T
 ) : FeaturedMatrix<T> {
-
-    constructor(rowNum: Int, colNum: Int, vararg features: MatrixFeature, generator: (i: Int, j: Int) -> T) : this(
+    public constructor(
+        rowNum: Int,
+        colNum: Int,
+        vararg features: MatrixFeature,
+        generator: (i: Int, j: Int) -> T
+    ) : this(
         rowNum,
         colNum,
         setOf(*features),
@@ -42,18 +46,15 @@ class VirtualMatrix<T : Any>(
     }
 
 
-    companion object {
+    public companion object {
         /**
          * Wrap a matrix adding additional features to it
          */
-        fun <T : Any> wrap(matrix: Matrix<T>, vararg features: MatrixFeature): FeaturedMatrix<T> {
-            return if (matrix is VirtualMatrix) {
+        public fun <T : Any> wrap(matrix: Matrix<T>, vararg features: MatrixFeature): FeaturedMatrix<T> {
+            return if (matrix is VirtualMatrix)
                 VirtualMatrix(matrix.rowNum, matrix.colNum, matrix.features + features, matrix.generator)
-            } else {
-                VirtualMatrix(matrix.rowNum, matrix.colNum, matrix.features + features) { i, j ->
-                    matrix[i, j]
-                }
-            }
+            else
+                VirtualMatrix(matrix.rowNum, matrix.colNum, matrix.features + features) { i, j -> matrix[i, j] }
         }
     }
 }

kmath-core/src/commonMain/kotlin/kscience/kmath/misc/AutoDiff.kt

@@ -1,12 +1,11 @@
-package scientifik.kmath.misc
+package kscience.kmath.misc
 
-import scientifik.kmath.linear.Point
-import scientifik.kmath.operations.ExtendedField
-import scientifik.kmath.operations.Field
-import scientifik.kmath.operations.invoke
-import scientifik.kmath.operations.sum
-import scientifik.kmath.structures.asBuffer
-import kotlin.contracts.ExperimentalContracts
+import kscience.kmath.linear.Point
+import kscience.kmath.operations.ExtendedField
+import kscience.kmath.operations.Field
+import kscience.kmath.operations.invoke
+import kscience.kmath.operations.sum
+import kscience.kmath.structures.asBuffer
 import kotlin.contracts.InvocationKind
 import kotlin.contracts.contract
 
@@ -19,24 +18,24 @@ import kotlin.contracts.contract
  * Differentiable variable with value and derivative of differentiation ([deriv]) result
  * with respect to this variable.
  */
-open class Variable<T : Any>(val value: T)
+public open class Variable<T : Any>(public val value: T)
 
-class DerivationResult<T : Any>(
+public class DerivationResult<T : Any>(
     value: T,
-    val deriv: Map<Variable<T>, T>,
-    val context: Field<T>
+    public val deriv: Map<Variable<T>, T>,
+    public val context: Field<T>
 ) : Variable<T>(value) {
-    fun deriv(variable: Variable<T>): T = deriv[variable] ?: context.zero
+    public fun deriv(variable: Variable<T>): T = deriv[variable] ?: context.zero
 
     /**
      * compute divergence
      */
-    fun div(): T = context { sum(deriv.values) }
+    public fun div(): T = context { sum(deriv.values) }
 
     /**
      * Compute a gradient for variables in given order
      */
-    fun grad(vararg variables: Variable<T>): Point<T> {
+    public fun grad(vararg variables: Variable<T>): Point<T> {
         check(variables.isNotEmpty()) { "Variable order is not provided for gradient construction" }
         return variables.map(::deriv).asBuffer()
     }
@@ -55,7 +54,7 @@ class DerivationResult<T : Any>(
  * assertEquals(9.0, x.d)  // dy/dx
  * ```
  */
-inline fun <T : Any, F : Field<T>> F.deriv(body: AutoDiffField<T, F>.() -> Variable<T>): DerivationResult<T> {
+public inline fun <T : Any, F : Field<T>> F.deriv(body: AutoDiffField<T, F>.() -> Variable<T>): DerivationResult<T> {
     contract { callsInPlace(body, InvocationKind.EXACTLY_ONCE) }
 
     return (AutoDiffContext(this)) {
@@ -66,15 +65,14 @@ inline fun <T : Any, F : Field<T>> F.deriv(body: AutoDiffField<T, F>.() -> Varia
     }
 }
 
-
-abstract class AutoDiffField<T : Any, F : Field<T>> : Field<Variable<T>> {
-    abstract val context: F
+public abstract class AutoDiffField<T : Any, F : Field<T>> : Field<Variable<T>> {
+    public abstract val context: F
 
     /**
      * A variable accessing inner state of derivatives.
      * Use this function in inner builders to avoid creating additional derivative bindings
      */
-    abstract var Variable<T>.d: T
+    public abstract var Variable<T>.d: T
 
     /**
      * Performs update of derivative after the rest of the formula in the back-pass.
@@ -87,11 +85,11 @@ abstract class AutoDiffField<T : Any, F : Field<T>> : Field<Variable<T>> {
      * }
      * ```
      */
-    abstract fun <R> derive(value: R, block: F.(R) -> Unit): R
+    public abstract fun <R> derive(value: R, block: F.(R) -> Unit): R
 
-    abstract fun variable(value: T): Variable<T>
+    public abstract fun variable(value: T): Variable<T>
 
-    inline fun variable(block: F.() -> T): Variable<T> = variable(context.block())
+    public inline fun variable(block: F.() -> T): Variable<T> = variable(context.block())
 
     // Overloads for Double constants
 
@@ -153,7 +151,6 @@ internal class AutoDiffContext<T : Any, F : Field<T>>(override val context: F) :
 
     // Basic math (+, -, *, /)
 
-
     override fun add(a: Variable<T>, b: Variable<T>): Variable<T> = derive(variable { a.value + b.value }) { z ->
         a.d += z.d
         b.d += z.d
@@ -177,35 +174,73 @@ internal class AutoDiffContext<T : Any, F : Field<T>>(override val context: F) :
 // Extensions for differentiation of various basic mathematical functions
 
 // x ^ 2
-fun <T : Any, F : Field<T>> AutoDiffField<T, F>.sqr(x: Variable<T>): Variable<T> =
+public fun <T : Any, F : Field<T>> AutoDiffField<T, F>.sqr(x: Variable<T>): Variable<T> =
     derive(variable { x.value * x.value }) { z -> x.d += z.d * 2 * x.value }
 
 // x ^ 1/2
-fun <T : Any, F : ExtendedField<T>> AutoDiffField<T, F>.sqrt(x: Variable<T>): Variable<T> =
+public fun <T : Any, F : ExtendedField<T>> AutoDiffField<T, F>.sqrt(x: Variable<T>): Variable<T> =
     derive(variable { sqrt(x.value) }) { z -> x.d += z.d * 0.5 / z.value }
 
 // x ^ y (const)
-fun <T : Any, F : ExtendedField<T>> AutoDiffField<T, F>.pow(x: Variable<T>, y: Double): Variable<T> =
+public fun <T : Any, F : ExtendedField<T>> AutoDiffField<T, F>.pow(x: Variable<T>, y: Double): Variable<T> =
     derive(variable { power(x.value, y) }) { z -> x.d += z.d * y * power(x.value, y - 1) }
 
-fun <T : Any, F : ExtendedField<T>> AutoDiffField<T, F>.pow(x: Variable<T>, y: Int): Variable<T> = pow(x, y.toDouble())
+public fun <T : Any, F : ExtendedField<T>> AutoDiffField<T, F>.pow(x: Variable<T>, y: Int): Variable<T> =
+    pow(x, y.toDouble())
 
 // exp(x)
-fun <T : Any, F : ExtendedField<T>> AutoDiffField<T, F>.exp(x: Variable<T>): Variable<T> =
+public fun <T : Any, F : ExtendedField<T>> AutoDiffField<T, F>.exp(x: Variable<T>): Variable<T> =
     derive(variable { exp(x.value) }) { z -> x.d += z.d * z.value }
 
 // ln(x)
-fun <T : Any, F : ExtendedField<T>> AutoDiffField<T, F>.ln(x: Variable<T>): Variable<T> =
+public fun <T : Any, F : ExtendedField<T>> AutoDiffField<T, F>.ln(x: Variable<T>): Variable<T> =
     derive(variable { ln(x.value) }) { z -> x.d += z.d / x.value }
 
 // x ^ y (any)
-fun <T : Any, F : ExtendedField<T>> AutoDiffField<T, F>.pow(x: Variable<T>, y: Variable<T>): Variable<T> =
+public fun <T : Any, F : ExtendedField<T>> AutoDiffField<T, F>.pow(x: Variable<T>, y: Variable<T>): Variable<T> =
     exp(y * ln(x))
 
 // sin(x)
-fun <T : Any, F : ExtendedField<T>> AutoDiffField<T, F>.sin(x: Variable<T>): Variable<T> =
+public fun <T : Any, F : ExtendedField<T>> AutoDiffField<T, F>.sin(x: Variable<T>): Variable<T> =
     derive(variable { sin(x.value) }) { z -> x.d += z.d * cos(x.value) }
 
 // cos(x)
-fun <T : Any, F : ExtendedField<T>> AutoDiffField<T, F>.cos(x: Variable<T>): Variable<T> =
+public fun <T : Any, F : ExtendedField<T>> AutoDiffField<T, F>.cos(x: Variable<T>): Variable<T> =
     derive(variable { cos(x.value) }) { z -> x.d -= z.d * sin(x.value) }
+
+public fun <T : Any, F : ExtendedField<T>> AutoDiffField<T, F>.tan(x: Variable<T>): Variable<T> =
+    derive(variable { tan(x.value) }) { z ->
+        val c = cos(x.value)
+        x.d += z.d / (c * c)
+    }
+
+public fun <T : Any, F : ExtendedField<T>> AutoDiffField<T, F>.asin(x: Variable<T>): Variable<T> =
+    derive(variable { asin(x.value) }) { z -> x.d += z.d / sqrt(one - x.value * x.value) }
+
+public fun <T : Any, F : ExtendedField<T>> AutoDiffField<T, F>.acos(x: Variable<T>): Variable<T> =
+    derive(variable { acos(x.value) }) { z -> x.d -= z.d / sqrt(one - x.value * x.value) }
+
+public fun <T : Any, F : ExtendedField<T>> AutoDiffField<T, F>.atan(x: Variable<T>): Variable<T> =
+    derive(variable { atan(x.value) }) { z -> x.d += z.d / (one + x.value * x.value) }
+
+public fun <T : Any, F : ExtendedField<T>> AutoDiffField<T, F>.sinh(x: Variable<T>): Variable<T> =
+    derive(variable { sin(x.value) }) { z -> x.d += z.d * cosh(x.value) }
+
+public fun <T : Any, F : ExtendedField<T>> AutoDiffField<T, F>.cosh(x: Variable<T>): Variable<T> =
+    derive(variable { cos(x.value) }) { z -> x.d += z.d * sinh(x.value) }
+
+public fun <T : Any, F : ExtendedField<T>> AutoDiffField<T, F>.tanh(x: Variable<T>): Variable<T> =
+    derive(variable { tan(x.value) }) { z ->
+        val c = cosh(x.value)
+        x.d += z.d / (c * c)
+    }
+
+public fun <T : Any, F : ExtendedField<T>> AutoDiffField<T, F>.asinh(x: Variable<T>): Variable<T> =
+    derive(variable { asinh(x.value) }) { z -> x.d += z.d / sqrt(one + x.value * x.value) }
+
+public fun <T : Any, F : ExtendedField<T>> AutoDiffField<T, F>.acosh(x: Variable<T>): Variable<T> =
+    derive(variable { acosh(x.value) }) { z -> x.d += z.d / (sqrt((x.value - one) * (x.value + one))) }
+
+public fun <T : Any, F : ExtendedField<T>> AutoDiffField<T, F>.atanh(x: Variable<T>): Variable<T> =
+    derive(variable { atanh(x.value) }) { z -> x.d += z.d / (one - x.value * x.value) }
+

kmath-core/src/commonMain/kotlin/kscience/kmath/misc/Grids.kt

@@ -1,4 +1,4 @@
-package scientifik.kmath.misc
+package kscience.kmath.misc
 
 import kotlin.math.abs
 
@@ -10,17 +10,21 @@ import kotlin.math.abs
  *
  * If step is negative, the same goes from upper boundary downwards
  */
-fun ClosedFloatingPointRange<Double>.toSequenceWithStep(step: Double): Sequence<Double> = when {
+public fun ClosedFloatingPointRange<Double>.toSequenceWithStep(step: Double): Sequence<Double> = when {
     step == 0.0 -> error("Zero step in double progression")
+
     step > 0 -> sequence {
         var current = start
+
         while (current <= endInclusive) {
             yield(current)
             current += step
         }
     }
+
     else -> sequence {
         var current = endInclusive
+
         while (current >= start) {
             yield(current)
             current += step
@@ -31,7 +35,7 @@ fun ClosedFloatingPointRange<Double>.toSequenceWithStep(step: Double): Sequence<
 /**
  * Convert double range to sequence with the fixed number of points
  */
-fun ClosedFloatingPointRange<Double>.toSequenceWithPoints(numPoints: Int): Sequence<Double> {
+public fun ClosedFloatingPointRange<Double>.toSequenceWithPoints(numPoints: Int): Sequence<Double> {
     require(numPoints > 1) { "The number of points should be more than 2" }
     return toSequenceWithStep(abs(endInclusive - start) / (numPoints - 1))
 }
@@ -40,7 +44,7 @@ fun ClosedFloatingPointRange<Double>.toSequenceWithPoints(numPoints: Int): Seque
  * Convert double range to array of evenly spaced doubles, where the size of array equals [numPoints]
  */
 @Deprecated("Replace by 'toSequenceWithPoints'")
-fun ClosedFloatingPointRange<Double>.toGrid(numPoints: Int): DoubleArray {
+public fun ClosedFloatingPointRange<Double>.toGrid(numPoints: Int): DoubleArray {
     require(numPoints >= 2) { "Can't create generic grid with less than two points" }
     return DoubleArray(numPoints) { i -> start + (endInclusive - start) / (numPoints - 1) * i }
 }

kmath-core/src/commonMain/kotlin/kscience/kmath/misc/cumulative.kt

@@ -0,0 +1,74 @@
+package kscience.kmath.misc
+
+import kscience.kmath.operations.Space
+import kscience.kmath.operations.invoke
+import kotlin.jvm.JvmName
+
+/**
+ * Generic cumulative operation on iterator.
+ *
+ * @param T the type of initial iterable.
+ * @param R the type of resulting iterable.
+ * @param initial lazy evaluated.
+ */
+public inline fun <T, R> Iterator<T>.cumulative(initial: R, crossinline operation: (R, T) -> R): Iterator<R> =
+    object : Iterator<R> {
+        var state: R = initial
+
+        override fun hasNext(): Boolean = this@cumulative.hasNext()
+
+        override fun next(): R {
+            state = operation(state, this@cumulative.next())
+            return state
+        }
+    }
+
+public inline fun <T, R> Iterable<T>.cumulative(initial: R, crossinline operation: (R, T) -> R): Iterable<R> =
+    Iterable { this@cumulative.iterator().cumulative(initial, operation) }
+
+public inline fun <T, R> Sequence<T>.cumulative(initial: R, crossinline operation: (R, T) -> R): Sequence<R> =
+    Sequence { this@cumulative.iterator().cumulative(initial, operation) }
+
+public fun <T, R> List<T>.cumulative(initial: R, operation: (R, T) -> R): List<R> =
+    iterator().cumulative(initial, operation).asSequence().toList()
+
+//Cumulative sum
+
+/**
+ * Cumulative sum with custom space
+ */
+public fun <T> Iterable<T>.cumulativeSum(space: Space<T>): Iterable<T> =
+    space { cumulative(zero) { element: T, sum: T -> sum + element } }
+
+@JvmName("cumulativeSumOfDouble")
+public fun Iterable<Double>.cumulativeSum(): Iterable<Double> = cumulative(0.0) { element, sum -> sum + element }
+
+@JvmName("cumulativeSumOfInt")
+public fun Iterable<Int>.cumulativeSum(): Iterable<Int> = cumulative(0) { element, sum -> sum + element }
+
+@JvmName("cumulativeSumOfLong")
+public fun Iterable<Long>.cumulativeSum(): Iterable<Long> = cumulative(0L) { element, sum -> sum + element }
+
+public fun <T> Sequence<T>.cumulativeSum(space: Space<T>): Sequence<T> =
+    space { cumulative(zero) { element: T, sum: T -> sum + element } }
+
+@JvmName("cumulativeSumOfDouble")
+public fun Sequence<Double>.cumulativeSum(): Sequence<Double> = cumulative(0.0) { element, sum -> sum + element }
+
+@JvmName("cumulativeSumOfInt")
+public fun Sequence<Int>.cumulativeSum(): Sequence<Int> = cumulative(0) { element, sum -> sum + element }
+
+@JvmName("cumulativeSumOfLong")
+public fun Sequence<Long>.cumulativeSum(): Sequence<Long> = cumulative(0L) { element, sum -> sum + element }
+
+public fun <T> List<T>.cumulativeSum(space: Space<T>): List<T> =
+    space { cumulative(zero) { element: T, sum: T -> sum + element } }
+
+@JvmName("cumulativeSumOfDouble")
+public fun List<Double>.cumulativeSum(): List<Double> = cumulative(0.0) { element, sum -> sum + element }
+
+@JvmName("cumulativeSumOfInt")
+public fun List<Int>.cumulativeSum(): List<Int> = cumulative(0) { element, sum -> sum + element }
+
+@JvmName("cumulativeSumOfLong")
+public fun List<Long>.cumulativeSum(): List<Long> = cumulative(0L) { element, sum -> sum + element }

kmath-core/src/commonMain/kotlin/kscience/kmath/operations/Algebra.kt

@@ -1,31 +1,31 @@
-package scientifik.kmath.operations
+package kscience.kmath.operations
 
 /**
  * Stub for DSL the [Algebra] is.
  */
 @DslMarker
-annotation class KMathContext
+public annotation class KMathContext
 
 /**
  * Represents an algebraic structure.
  *
  * @param T the type of element of this structure.
  */
-interface Algebra<T> {
+public interface Algebra<T> {
     /**
      * Wrap raw string or variable
      */
-    fun symbol(value: String): T = error("Wrapping of '$value' is not supported in $this")
+    public fun symbol(value: String): T = error("Wrapping of '$value' is not supported in $this")
 
     /**
      * Dynamic call of unary operation with name [operation] on [arg]
      */
-    fun unaryOperation(operation: String, arg: T): T
+    public fun unaryOperation(operation: String, arg: T): T
 
     /**
      * Dynamic call of binary operation [operation] on [left] and [right]
      */
-    fun binaryOperation(operation: String, left: T, right: T): T
+    public fun binaryOperation(operation: String, left: T, right: T): T
 }
 
 /**
@@ -33,29 +33,30 @@ interface Algebra<T> {
  *
  * @param T the type of element of this structure.
  */
-interface NumericAlgebra<T> : Algebra<T> {
+public interface NumericAlgebra<T> : Algebra<T> {
     /**
      * Wraps a number.
      */
-    fun number(value: Number): T
+    public fun number(value: Number): T
 
     /**
      * Dynamic call of binary operation [operation] on [left] and [right] where left element is [Number].
      */
-    fun leftSideNumberOperation(operation: String, left: Number, right: T): T =
+    public fun leftSideNumberOperation(operation: String, left: Number, right: T): T =
         binaryOperation(operation, number(left), right)
 
     /**
      * Dynamic call of binary operation [operation] on [left] and [right] where right element is [Number].
      */
-    fun rightSideNumberOperation(operation: String, left: T, right: Number): T =
+    public fun rightSideNumberOperation(operation: String, left: T, right: Number): T =
         leftSideNumberOperation(operation, right, left)
 }
 
 /**
  * Call a block with an [Algebra] as receiver.
  */
-inline operator fun <A : Algebra<*>, R> A.invoke(block: A.() -> R): R = run(block)
+// TODO add contract when KT-32313 is fixed
+public inline operator fun <A : Algebra<*>, R> A.invoke(block: A.() -> R): R = block()
 
 /**
  * Represents "semispace", i.e. algebraic structure with associative binary operation called "addition" as well as
@@ -63,7 +64,7 @@ inline operator fun <A : Algebra<*>, R> A.invoke(block: A.() -> R): R = run(bloc
  *
  * @param T the type of element of this semispace.
  */
-interface SpaceOperations<T> : Algebra<T> {
+public interface SpaceOperations<T> : Algebra<T> {
     /**
      * Addition of two elements.
      *
@@ -71,7 +72,7 @@ interface SpaceOperations<T> : Algebra<T> {
      * @param b the augend.
      * @return the sum.
      */
-    fun add(a: T, b: T): T
+    public fun add(a: T, b: T): T
 
     /**
      * Multiplication of element by scalar.
@@ -80,7 +81,7 @@ interface SpaceOperations<T> : Algebra<T> {
      * @param k the multiplicand.
      * @return the produce.
      */
-    fun multiply(a: T, k: Number): T
+    public fun multiply(a: T, k: Number): T
 
     // Operations to be performed in this context. Could be moved to extensions in case of KEEP-176
 
@@ -90,7 +91,7 @@ interface SpaceOperations<T> : Algebra<T> {
      * @receiver this value.
      * @return the additive inverse of this value.
      */
-    operator fun T.unaryMinus(): T = multiply(this, -1.0)
+    public operator fun T.unaryMinus(): T = multiply(this, -1.0)
 
     /**
      * Returns this value.
@@ -98,7 +99,7 @@ interface SpaceOperations<T> : Algebra<T> {
      * @receiver this value.
      * @return this value.
      */
-    operator fun T.unaryPlus(): T = this
+    public operator fun T.unaryPlus(): T = this
 
     /**
      * Addition of two elements.
@@ -107,7 +108,7 @@ interface SpaceOperations<T> : Algebra<T> {
      * @param b the augend.
      * @return the sum.
      */
-    operator fun T.plus(b: T): T = add(this, b)
+    public operator fun T.plus(b: T): T = add(this, b)
 
     /**
      * Subtraction of two elements.
@@ -116,7 +117,7 @@ interface SpaceOperations<T> : Algebra<T> {
      * @param b the subtrahend.
      * @return the difference.
      */
-    operator fun T.minus(b: T): T = add(this, -b)
+    public operator fun T.minus(b: T): T = add(this, -b)
 
     /**
      * Multiplication of this element by a scalar.
@@ -125,7 +126,7 @@ interface SpaceOperations<T> : Algebra<T> {
      * @param k the multiplicand.
      * @return the product.
      */
-    operator fun T.times(k: Number): T = multiply(this, k.toDouble())
+    public operator fun T.times(k: Number): T = multiply(this, k.toDouble())
 
     /**
      * Division of this element by scalar.
@@ -134,7 +135,7 @@ interface SpaceOperations<T> : Algebra<T> {
      * @param k the divisor.
      * @return the quotient.
      */
-    operator fun T.div(k: Number): T = multiply(this, 1.0 / k.toDouble())
+    public operator fun T.div(k: Number): T = multiply(this, 1.0 / k.toDouble())
 
     /**
      * Multiplication of this number by element.
@@ -143,7 +144,7 @@ interface SpaceOperations<T> : Algebra<T> {
      * @param b the multiplicand.
      * @return the product.
      */
-    operator fun Number.times(b: T): T = b * this
+    public operator fun Number.times(b: T): T = b * this
 
     override fun unaryOperation(operation: String, arg: T): T = when (operation) {
         PLUS_OPERATION -> arg
@@ -157,18 +158,16 @@ interface SpaceOperations<T> : Algebra<T> {
         else -> error("Binary operation $operation not defined in $this")
     }
 
-    companion object {
+    public companion object {
         /**
          * The identifier of addition.
          */
-        const val PLUS_OPERATION: String = "+"
+        public const val PLUS_OPERATION: String = "+"
 
         /**
          * The identifier of subtraction (and negation).
          */
-        const val MINUS_OPERATION: String = "-"
-
-        const val NOT_OPERATION: String = "!"
+        public const val MINUS_OPERATION: String = "-"
     }
 }
 
@@ -178,11 +177,11 @@ interface SpaceOperations<T> : Algebra<T> {
  *
  * @param T the type of element of this group.
  */
-interface Space<T> : SpaceOperations<T> {
+public interface Space<T> : SpaceOperations<T> {
     /**
      * The neutral element of addition.
      */
-    val zero: T
+    public val zero: T
 }
 
 /**
@@ -191,14 +190,14 @@ interface Space<T> : SpaceOperations<T> {
  *
  * @param T the type of element of this semiring.
  */
-interface RingOperations<T> : SpaceOperations<T> {
+public interface RingOperations<T> : SpaceOperations<T> {
     /**
      * Multiplies two elements.
      *
      * @param a the multiplier.
      * @param b the multiplicand.
      */
-    fun multiply(a: T, b: T): T
+    public fun multiply(a: T, b: T): T
 
     /**
      * Multiplies this element by scalar.
@@ -206,18 +205,18 @@ interface RingOperations<T> : SpaceOperations<T> {
      * @receiver the multiplier.
      * @param b the multiplicand.
      */
-    operator fun T.times(b: T): T = multiply(this, b)
+    public operator fun T.times(b: T): T = multiply(this, b)
 
     override fun binaryOperation(operation: String, left: T, right: T): T = when (operation) {
         TIMES_OPERATION -> multiply(left, right)
         else -> super.binaryOperation(operation, left, right)
     }
 
-    companion object {
+    public companion object {
         /**
          * The identifier of multiplication.
          */
-        const val TIMES_OPERATION: String = "*"
+        public const val TIMES_OPERATION: String = "*"
     }
 }
 
@@ -227,11 +226,11 @@ interface RingOperations<T> : SpaceOperations<T> {
  *
  * @param T the type of element of this ring.
  */
-interface Ring<T> : Space<T>, RingOperations<T>, NumericAlgebra<T> {
+public interface Ring<T> : Space<T>, RingOperations<T>, NumericAlgebra<T> {
     /**
      * neutral operation for multiplication
      */
-    val one: T
+    public val one: T
 
     override fun number(value: Number): T = one * value.toDouble()
 
@@ -255,7 +254,7 @@ interface Ring<T> : Space<T>, RingOperations<T>, NumericAlgebra<T> {
      * @receiver the addend.
      * @param b the augend.
      */
-    operator fun T.plus(b: Number): T = this + number(b)
+    public operator fun T.plus(b: Number): T = this + number(b)
 
     /**
      * Addition of scalar and element.
@@ -263,7 +262,7 @@ interface Ring<T> : Space<T>, RingOperations<T>, NumericAlgebra<T> {
      * @receiver the addend.
      * @param b the augend.
      */
-    operator fun Number.plus(b: T): T = b + this
+    public operator fun Number.plus(b: T): T = b + this
 
     /**
      * Subtraction of element from number.
@@ -272,7 +271,7 @@ interface Ring<T> : Space<T>, RingOperations<T>, NumericAlgebra<T> {
      * @param b the subtrahend.
      * @receiver the difference.
      */
-    operator fun T.minus(b: Number): T = this - number(b)
+    public operator fun T.minus(b: Number): T = this - number(b)
 
     /**
      * Subtraction of number from element.
@@ -281,7 +280,7 @@ interface Ring<T> : Space<T>, RingOperations<T>, NumericAlgebra<T> {
      * @param b the subtrahend.
      * @receiver the difference.
      */
-    operator fun Number.minus(b: T): T = -b + this
+    public operator fun Number.minus(b: T): T = -b + this
 }
 
 /**
@@ -290,7 +289,7 @@ interface Ring<T> : Space<T>, RingOperations<T>, NumericAlgebra<T> {
  *
  * @param T the type of element of this semifield.
  */
-interface FieldOperations<T> : RingOperations<T> {
+public interface FieldOperations<T> : RingOperations<T> {
     /**
      * Division of two elements.
      *
@@ -298,7 +297,7 @@ interface FieldOperations<T> : RingOperations<T> {
      * @param b the divisor.
      * @return the quotient.
      */
-    fun divide(a: T, b: T): T
+    public fun divide(a: T, b: T): T
 
     /**
      * Division of two elements.
@@ -307,18 +306,18 @@ interface FieldOperations<T> : RingOperations<T> {
      * @param b the divisor.
      * @return the quotient.
      */
-    operator fun T.div(b: T): T = divide(this, b)
+    public operator fun T.div(b: T): T = divide(this, b)
 
     override fun binaryOperation(operation: String, left: T, right: T): T = when (operation) {
         DIV_OPERATION -> divide(left, right)
         else -> super.binaryOperation(operation, left, right)
     }
 
-    companion object {
+    public companion object {
         /**
          * The identifier of division.
          */
-        const val DIV_OPERATION: String = "/"
+        public const val DIV_OPERATION: String = "/"
     }
 }
 
@@ -328,7 +327,7 @@ interface FieldOperations<T> : RingOperations<T> {
  *
  * @param T the type of element of this semifield.
  */
-interface Field<T> : Ring<T>, FieldOperations<T> {
+public interface Field<T> : Ring<T>, FieldOperations<T> {
     /**
      * Division of element by scalar.
      *
@@ -336,5 +335,5 @@ interface Field<T> : Ring<T>, FieldOperations<T> {
      * @param b the divisor.
      * @return the quotient.
      */
-    operator fun Number.div(b: T): T = this * divide(one, b)
+    public operator fun Number.div(b: T): T = this * divide(one, b)
 }

kmath-core/src/commonMain/kotlin/kscience/kmath/operations/AlgebraElements.kt

@@ -1,15 +1,15 @@
-package scientifik.kmath.operations
+package kscience.kmath.operations
 
 /**
  * The generic mathematics elements which is able to store its context
  *
  * @param C the type of mathematical context for this element.
  */
-interface MathElement<C> {
+public interface MathElement<C> {
     /**
      * The context this element belongs to.
      */
-    val context: C
+    public val context: C
 }
 
 /**
@@ -18,16 +18,16 @@ interface MathElement<C> {
  * @param T the type wrapped by this wrapper.
  * @param I the type of this wrapper.
  */
-interface MathWrapper<T, I> {
+public interface MathWrapper<T, I> {
     /**
      * Unwraps [I] to [T].
      */
-    fun unwrap(): T
+    public fun unwrap(): T
 
     /**
      * Wraps [T] to [I].
      */
-    fun T.wrap(): I
+    public fun T.wrap(): I
 }
 
 /**
@@ -37,14 +37,14 @@ interface MathWrapper<T, I> {
  * @param I self type of the element. Needed for static type checking.
  * @param S the type of space.
  */
-interface SpaceElement<T, I : SpaceElement<T, I, S>, S : Space<T>> : MathElement<S>, MathWrapper<T, I> {
+public interface SpaceElement<T, I : SpaceElement<T, I, S>, S : Space<T>> : MathElement<S>, MathWrapper<T, I> {
     /**
      * Adds element to this one.
      *
      * @param b the augend.
      * @return the sum.
      */
-    operator fun plus(b: T): I = context.add(unwrap(), b).wrap()
+    public operator fun plus(b: T): I = context.add(unwrap(), b).wrap()
 
     /**
      * Subtracts element from this one.
@@ -52,7 +52,7 @@ interface SpaceElement<T, I : SpaceElement<T, I, S>, S : Space<T>> : MathElement
      * @param b the subtrahend.
      * @return the difference.
      */
-    operator fun minus(b: T): I = context.add(unwrap(), context.multiply(b, -1.0)).wrap()
+    public operator fun minus(b: T): I = context.add(unwrap(), context.multiply(b, -1.0)).wrap()
 
     /**
      * Multiplies this element by number.
@@ -60,7 +60,7 @@ interface SpaceElement<T, I : SpaceElement<T, I, S>, S : Space<T>> : MathElement
      * @param k the multiplicand.
      * @return the product.
      */
-    operator fun times(k: Number): I = context.multiply(unwrap(), k.toDouble()).wrap()
+    public operator fun times(k: Number): I = context.multiply(unwrap(), k.toDouble()).wrap()
 
     /**
      * Divides this element by number.
@@ -68,7 +68,7 @@ interface SpaceElement<T, I : SpaceElement<T, I, S>, S : Space<T>> : MathElement
      * @param k the divisor.
      * @return the quotient.
      */
-    operator fun div(k: Number): I = context.multiply(unwrap(), 1.0 / k.toDouble()).wrap()
+    public operator fun div(k: Number): I = context.multiply(unwrap(), 1.0 / k.toDouble()).wrap()
 }
 
 /**
@@ -78,14 +78,14 @@ interface SpaceElement<T, I : SpaceElement<T, I, S>, S : Space<T>> : MathElement
  * @param I self type of the element. Needed for static type checking.
  * @param R the type of space.
  */
-interface RingElement<T, I : RingElement<T, I, R>, R : Ring<T>> : SpaceElement<T, I, R> {
+public interface RingElement<T, I : RingElement<T, I, R>, R : Ring<T>> : SpaceElement<T, I, R> {
     /**
      * Multiplies this element by another one.
      *
      * @param b the multiplicand.
      * @return the product.
      */
-    operator fun times(b: T): I = context.multiply(unwrap(), b).wrap()
+    public operator fun times(b: T): I = context.multiply(unwrap(), b).wrap()
 }
 
 /**
@@ -95,7 +95,7 @@ interface RingElement<T, I : RingElement<T, I, R>, R : Ring<T>> : SpaceElement<T
  * @param I self type of the element. Needed for static type checking.
  * @param F the type of field.
  */
-interface FieldElement<T, I : FieldElement<T, I, F>, F : Field<T>> : RingElement<T, I, F> {
+public interface FieldElement<T, I : FieldElement<T, I, F>, F : Field<T>> : RingElement<T, I, F> {
     override val context: F
 
     /**
@@ -104,5 +104,5 @@ interface FieldElement<T, I : FieldElement<T, I, F>, F : Field<T>> : RingElement
      * @param b the divisor.
      * @return the quotient.
      */
-    operator fun div(b: T): I = context.divide(unwrap(), b).wrap()
+    public operator fun div(b: T): I = context.divide(unwrap(), b).wrap()
 }

kmath-core/src/commonMain/kotlin/kscience/kmath/operations/AlgebraExtensions.kt

@@ -1,4 +1,4 @@
-package scientifik.kmath.operations
+package kscience.kmath.operations
 
 /**
  * Returns the sum of all elements in the iterable in this [Space].
@@ -7,7 +7,7 @@ package scientifik.kmath.operations
  * @param data the iterable to sum up.
  * @return the sum.
  */
-fun <T> Space<T>.sum(data: Iterable<T>): T = data.fold(zero) { left, right -> add(left, right) }
+public fun <T> Space<T>.sum(data: Iterable<T>): T = data.fold(zero) { left, right -> add(left, right) }
 
 /**
  * Returns the sum of all elements in the sequence in this [Space].
@@ -16,7 +16,7 @@ fun <T> Space<T>.sum(data: Iterable<T>): T = data.fold(zero) { left, right -> ad
  * @param data the sequence to sum up.
  * @return the sum.
  */
-fun <T> Space<T>.sum(data: Sequence<T>): T = data.fold(zero) { left, right -> add(left, right) }
+public fun <T> Space<T>.sum(data: Sequence<T>): T = data.fold(zero) { left, right -> add(left, right) }
 
 /**
  * Returns an average value of elements in the iterable in this [Space].
@@ -24,8 +24,9 @@ fun <T> Space<T>.sum(data: Sequence<T>): T = data.fold(zero) { left, right -> ad
  * @receiver the algebra that provides addition and division.
  * @param data the iterable to find average.
  * @return the average value.
+ * @author Iaroslav Postovalov
  */
-fun <T> Space<T>.average(data: Iterable<T>): T = sum(data) / data.count()
+public fun <T> Space<T>.average(data: Iterable<T>): T = sum(data) / data.count()
 
 /**
  * Returns an average value of elements in the sequence in this [Space].
@@ -33,8 +34,9 @@ fun <T> Space<T>.average(data: Iterable<T>): T = sum(data) / data.count()
  * @receiver the algebra that provides addition and division.
  * @param data the sequence to find average.
  * @return the average value.
+ * @author Iaroslav Postovalov
  */
-fun <T> Space<T>.average(data: Sequence<T>): T = sum(data) / data.count()
+public fun <T> Space<T>.average(data: Sequence<T>): T = sum(data) / data.count()
 
 /**
  * Returns the sum of all elements in the iterable in provided space.
@@ -43,7 +45,7 @@ fun <T> Space<T>.average(data: Sequence<T>): T = sum(data) / data.count()
  * @param space the algebra that provides addition.
  * @return the sum.
  */
-fun <T> Iterable<T>.sumWith(space: Space<T>): T = space.sum(this)
+public fun <T> Iterable<T>.sumWith(space: Space<T>): T = space.sum(this)
 
 /**
  * Returns the sum of all elements in the sequence in provided space.
@@ -52,7 +54,7 @@ fun <T> Iterable<T>.sumWith(space: Space<T>): T = space.sum(this)
  * @param space the algebra that provides addition.
  * @return the sum.
  */
-fun <T> Sequence<T>.sumWith(space: Space<T>): T = space.sum(this)
+public fun <T> Sequence<T>.sumWith(space: Space<T>): T = space.sum(this)
 
 /**
  * Returns an average value of elements in the iterable in this [Space].
@@ -60,8 +62,9 @@ fun <T> Sequence<T>.sumWith(space: Space<T>): T = space.sum(this)
  * @receiver the iterable to find average.
  * @param space the algebra that provides addition and division.
  * @return the average value.
+ * @author Iaroslav Postovalov
  */
-fun <T> Iterable<T>.averageWith(space: Space<T>): T = space.average(this)
+public fun <T> Iterable<T>.averageWith(space: Space<T>): T = space.average(this)
 
 /**
  * Returns an average value of elements in the sequence in this [Space].
@@ -69,8 +72,9 @@ fun <T> Iterable<T>.averageWith(space: Space<T>): T = space.average(this)
  * @receiver the sequence to find average.
  * @param space the algebra that provides addition and division.
  * @return the average value.
+ * @author Iaroslav Postovalov
  */
-fun <T> Sequence<T>.averageWith(space: Space<T>): T = space.average(this)
+public fun <T> Sequence<T>.averageWith(space: Space<T>): T = space.average(this)
 
 //TODO optimized power operation
 
@@ -82,7 +86,7 @@ fun <T> Sequence<T>.averageWith(space: Space<T>): T = space.average(this)
  * @param power the exponent.
  * @return the base raised to the power.
  */
-fun <T> Ring<T>.power(arg: T, power: Int): T {
+public fun <T> Ring<T>.power(arg: T, power: Int): T {
     require(power >= 0) { "The power can't be negative." }
     require(power != 0 || arg != zero) { "The $zero raised to $power is not defined." }
     if (power == 0) return one
@@ -98,8 +102,9 @@ fun <T> Ring<T>.power(arg: T, power: Int): T {
  * @param arg the base.
  * @param power the exponent.
  * @return the base raised to the power.
+ * @author Iaroslav Postovalov
  */
-fun <T> Field<T>.power(arg: T, power: Int): T {
+public fun <T> Field<T>.power(arg: T, power: Int): T {
     require(power != 0 || arg != zero) { "The $zero raised to $power is not defined." }
     if (power == 0) return one
     if (power < 0) return one / (this as Ring<T>).power(arg, -power)

kmath-core/src/commonMain/kotlin/kscience/kmath/operations/BigInt.kt

@@ -1,24 +1,22 @@
-package scientifik.kmath.operations
+package kscience.kmath.operations
 
-import scientifik.kmath.operations.BigInt.Companion.BASE
-import scientifik.kmath.operations.BigInt.Companion.BASE_SIZE
-import scientifik.kmath.structures.*
-import kotlin.contracts.ExperimentalContracts
-import kotlin.contracts.contract
+import kscience.kmath.operations.BigInt.Companion.BASE
+import kscience.kmath.operations.BigInt.Companion.BASE_SIZE
+import kscience.kmath.structures.*
 import kotlin.math.log2
 import kotlin.math.max
 import kotlin.math.min
 import kotlin.math.sign
 
-typealias Magnitude = UIntArray
-typealias TBase = ULong
+public typealias Magnitude = UIntArray
+public typealias TBase = ULong
 
 /**
  * Kotlin Multiplatform implementation of Big Integer numbers (KBigInteger).
  *
  * @author Robert Drynkin (https://github.com/robdrynkin) and Peter Klimai (https://github.com/pklimai)
  */
-object BigIntField : Field<BigInt> {
+public object BigIntField : Field<BigInt> {
     override val zero: BigInt = BigInt.ZERO
     override val one: BigInt = BigInt.ONE
 
@@ -29,113 +27,92 @@ object BigIntField : Field<BigInt> {
 
     override fun multiply(a: BigInt, b: BigInt): BigInt = a.times(b)
 
-    operator fun String.unaryPlus(): BigInt = this.parseBigInteger() ?: error("Can't parse $this as big integer")
+    public operator fun String.unaryPlus(): BigInt = this.parseBigInteger() ?: error("Can't parse $this as big integer")
 
-    operator fun String.unaryMinus(): BigInt =
+    public operator fun String.unaryMinus(): BigInt =
         -(this.parseBigInteger() ?: error("Can't parse $this as big integer"))
 
     override fun divide(a: BigInt, b: BigInt): BigInt = a.div(b)
 }
 
-class BigInt internal constructor(
+public class BigInt internal constructor(
     private val sign: Byte,
     private val magnitude: Magnitude
 ) : Comparable<BigInt> {
+    public override fun compareTo(other: BigInt): Int = when {
+        (sign == 0.toByte()) and (other.sign == 0.toByte()) -> 0
+        sign < other.sign -> -1
+        sign > other.sign -> 1
+        else -> sign * compareMagnitudes(magnitude, other.magnitude)
+    }
 
-    override fun compareTo(other: BigInt): Int {
-        return when {
-            (this.sign == 0.toByte()) and (other.sign == 0.toByte()) -> 0
-            this.sign < other.sign -> -1
-            this.sign > other.sign -> 1
-            else -> this.sign * compareMagnitudes(this.magnitude, other.magnitude)
+    public override fun equals(other: Any?): Boolean =
+        if (other is BigInt) compareTo(other) == 0 else error("Can't compare KBigInteger to a different type")
+
+    public override fun hashCode(): Int = magnitude.hashCode() + sign
+
+    public fun abs(): BigInt = if (sign == 0.toByte()) this else BigInt(1, magnitude)
+
+    public operator fun unaryMinus(): BigInt =
+        if (this.sign == 0.toByte()) this else BigInt((-this.sign).toByte(), this.magnitude)
+
+    public operator fun plus(b: BigInt): BigInt = when {
+        b.sign == 0.toByte() -> this
+        sign == 0.toByte() -> b
+        this == -b -> ZERO
+        sign == b.sign -> BigInt(sign, addMagnitudes(magnitude, b.magnitude))
+
+        else -> {
+            val comp = compareMagnitudes(magnitude, b.magnitude)
+
+            if (comp == 1)
+                BigInt(sign, subtractMagnitudes(magnitude, b.magnitude))
+            else
+                BigInt((-sign).toByte(), subtractMagnitudes(b.magnitude, magnitude))
         }
     }
 
-    override fun equals(other: Any?): Boolean {
-        if (other is BigInt) {
-            return this.compareTo(other) == 0
-        } else error("Can't compare KBigInteger to a different type")
-    }
+    public operator fun minus(b: BigInt): BigInt = this + (-b)
 
-    override fun hashCode(): Int {
-        return magnitude.hashCode() + this.sign
-    }
-
-    fun abs(): BigInt = if (sign == 0.toByte()) this else BigInt(1, magnitude)
-
-    operator fun unaryMinus(): BigInt {
-        return if (this.sign == 0.toByte()) this else BigInt((-this.sign).toByte(), this.magnitude)
-    }
-
-    operator fun plus(b: BigInt): BigInt {
-        return when {
-            b.sign == 0.toByte() -> this
-            this.sign == 0.toByte() -> b
-            this == -b -> ZERO
-            this.sign == b.sign -> BigInt(this.sign, addMagnitudes(this.magnitude, b.magnitude))
-            else -> {
-                val comp: Int = compareMagnitudes(this.magnitude, b.magnitude)
-
-                if (comp == 1) {
-                    BigInt(this.sign, subtractMagnitudes(this.magnitude, b.magnitude))
-                } else {
-                    BigInt((-this.sign).toByte(), subtractMagnitudes(b.magnitude, this.magnitude))
-                }
-            }
-        }
-    }
-
-    operator fun minus(b: BigInt): BigInt {
-        return this + (-b)
-    }
-
-    operator fun times(b: BigInt): BigInt {
-        return when {
-            this.sign == 0.toByte() -> ZERO
-            b.sign == 0.toByte() -> ZERO
+    public operator fun times(b: BigInt): BigInt = when {
+        this.sign == 0.toByte() -> ZERO
+        b.sign == 0.toByte() -> ZERO
 //          TODO: Karatsuba
-            else -> BigInt((this.sign * b.sign).toByte(), multiplyMagnitudes(this.magnitude, b.magnitude))
-        }
+        else -> BigInt((this.sign * b.sign).toByte(), multiplyMagnitudes(this.magnitude, b.magnitude))
     }
 
-    operator fun times(other: UInt): BigInt {
-        return when {
-            this.sign == 0.toByte() -> ZERO
-            other == 0U -> ZERO
-            else -> BigInt(this.sign, multiplyMagnitudeByUInt(this.magnitude, other))
-        }
+    public operator fun times(other: UInt): BigInt = when {
+        sign == 0.toByte() -> ZERO
+        other == 0U -> ZERO
+        else -> BigInt(sign, multiplyMagnitudeByUInt(magnitude, other))
     }
 
-    operator fun times(other: Int): BigInt {
-        return if (other > 0)
-            this * kotlin.math.abs(other).toUInt()
-        else
-            -this * kotlin.math.abs(other).toUInt()
-    }
+    public operator fun times(other: Int): BigInt = if (other > 0)
+        this * kotlin.math.abs(other).toUInt()
+    else
+        -this * kotlin.math.abs(other).toUInt()
 
-    operator fun div(other: UInt): BigInt {
-        return BigInt(this.sign, divideMagnitudeByUInt(this.magnitude, other))
-    }
+    public operator fun div(other: UInt): BigInt = BigInt(this.sign, divideMagnitudeByUInt(this.magnitude, other))
 
-    operator fun div(other: Int): BigInt {
-        return BigInt(
-            (this.sign * other.sign).toByte(),
-            divideMagnitudeByUInt(this.magnitude, kotlin.math.abs(other).toUInt())
-        )
-    }
+    public operator fun div(other: Int): BigInt = BigInt(
+        (this.sign * other.sign).toByte(),
+        divideMagnitudeByUInt(this.magnitude, kotlin.math.abs(other).toUInt())
+    )
 
     private fun division(other: BigInt): Pair<BigInt, BigInt> {
         // Long division algorithm:
         //     https://en.wikipedia.org/wiki/Division_algorithm#Integer_division_(unsigned)_with_remainder
         // TODO: Implement more effective algorithm
-        var q: BigInt = ZERO
-        var r: BigInt = ZERO
+        var q = ZERO
+        var r = ZERO
 
         val bitSize =
             (BASE_SIZE * (this.magnitude.size - 1) + log2(this.magnitude.lastOrNull()?.toFloat() ?: 0f + 1)).toInt()
+
         for (i in bitSize downTo 0) {
             r = r shl 1
             r = r or ((abs(this) shr i) and ONE)
+
             if (r >= abs(other)) {
                 r -= abs(other)
                 q += (ONE shl i)
@@ -145,99 +122,84 @@ class BigInt internal constructor(
         return Pair(BigInt((this.sign * other.sign).toByte(), q.magnitude), r)
     }
 
-    operator fun div(other: BigInt): BigInt {
-        return this.division(other).first
-    }
+    public operator fun div(other: BigInt): BigInt = division(other).first
 
-    infix fun shl(i: Int): BigInt {
+    public infix fun shl(i: Int): BigInt {
         if (this == ZERO) return ZERO
         if (i == 0) return this
-
         val fullShifts = i / BASE_SIZE + 1
         val relShift = i % BASE_SIZE
         val shiftLeft = { x: UInt -> if (relShift >= 32) 0U else x shl relShift }
         val shiftRight = { x: UInt -> if (BASE_SIZE - relShift >= 32) 0U else x shr (BASE_SIZE - relShift) }
+        val newMagnitude = Magnitude(magnitude.size + fullShifts)
 
-        val newMagnitude: Magnitude = Magnitude(this.magnitude.size + fullShifts)
-
-        for (j in this.magnitude.indices) {
+        for (j in magnitude.indices) {
             newMagnitude[j + fullShifts - 1] = shiftLeft(this.magnitude[j])
-            if (j != 0) {
+
+            if (j != 0)
                 newMagnitude[j + fullShifts - 1] = newMagnitude[j + fullShifts - 1] or shiftRight(this.magnitude[j - 1])
-            }
         }
 
-        newMagnitude[this.magnitude.size + fullShifts - 1] = shiftRight(this.magnitude.last())
-
+        newMagnitude[magnitude.size + fullShifts - 1] = shiftRight(magnitude.last())
         return BigInt(this.sign, stripLeadingZeros(newMagnitude))
     }
 
-    infix fun shr(i: Int): BigInt {
+    public infix fun shr(i: Int): BigInt {
         if (this == ZERO) return ZERO
         if (i == 0) return this
-
         val fullShifts = i / BASE_SIZE
         val relShift = i % BASE_SIZE
         val shiftRight = { x: UInt -> if (relShift >= 32) 0U else x shr relShift }
         val shiftLeft = { x: UInt -> if (BASE_SIZE - relShift >= 32) 0U else x shl (BASE_SIZE - relShift) }
-        if (this.magnitude.size - fullShifts <= 0) {
-            return ZERO
-        }
-        val newMagnitude: Magnitude = Magnitude(this.magnitude.size - fullShifts)
+        if (this.magnitude.size - fullShifts <= 0) return ZERO
+        val newMagnitude: Magnitude = Magnitude(magnitude.size - fullShifts)
 
-        for (j in fullShifts until this.magnitude.size) {
-            newMagnitude[j - fullShifts] = shiftRight(this.magnitude[j])
-            if (j != this.magnitude.size - 1) {
-                newMagnitude[j - fullShifts] = newMagnitude[j - fullShifts] or shiftLeft(this.magnitude[j + 1])
-            }
+        for (j in fullShifts until magnitude.size) {
+            newMagnitude[j - fullShifts] = shiftRight(magnitude[j])
+
+            if (j != magnitude.size - 1)
+                newMagnitude[j - fullShifts] = newMagnitude[j - fullShifts] or shiftLeft(magnitude[j + 1])
         }
 
         return BigInt(this.sign, stripLeadingZeros(newMagnitude))
     }
 
-    infix fun or(other: BigInt): BigInt {
+    public infix fun or(other: BigInt): BigInt {
         if (this == ZERO) return other
         if (other == ZERO) return this
-        val resSize = max(this.magnitude.size, other.magnitude.size)
+        val resSize = max(magnitude.size, other.magnitude.size)
         val newMagnitude: Magnitude = Magnitude(resSize)
+
         for (i in 0 until resSize) {
-            if (i < this.magnitude.size) {
-                newMagnitude[i] = newMagnitude[i] or this.magnitude[i]
-            }
-            if (i < other.magnitude.size) {
-                newMagnitude[i] = newMagnitude[i] or other.magnitude[i]
-            }
+            if (i < magnitude.size) newMagnitude[i] = newMagnitude[i] or magnitude[i]
+            if (i < other.magnitude.size) newMagnitude[i] = newMagnitude[i] or other.magnitude[i]
         }
+
         return BigInt(1, stripLeadingZeros(newMagnitude))
     }
 
-    infix fun and(other: BigInt): BigInt {
+    public infix fun and(other: BigInt): BigInt {
         if ((this == ZERO) or (other == ZERO)) return ZERO
         val resSize = min(this.magnitude.size, other.magnitude.size)
         val newMagnitude: Magnitude = Magnitude(resSize)
-        for (i in 0 until resSize) {
-            newMagnitude[i] = this.magnitude[i] and other.magnitude[i]
-        }
+        for (i in 0 until resSize) newMagnitude[i] = this.magnitude[i] and other.magnitude[i]
         return BigInt(1, stripLeadingZeros(newMagnitude))
     }
 
-    operator fun rem(other: Int): Int {
+    public operator fun rem(other: Int): Int {
         val res = this - (this / other) * other
         return if (res == ZERO) 0 else res.sign * res.magnitude[0].toInt()
     }
 
-    operator fun rem(other: BigInt): BigInt {
-        return this - (this / other) * other
-    }
+    public operator fun rem(other: BigInt): BigInt = this - (this / other) * other
 
-    fun modPow(exponent: BigInt, m: BigInt): BigInt {
-        return when {
-            exponent == ZERO -> ONE
-            exponent % 2 == 1 -> (this * modPow(exponent - ONE, m)) % m
-            else -> {
-                val sqRoot = modPow(exponent / 2, m)
-                (sqRoot * sqRoot) % m
-            }
+    public fun modPow(exponent: BigInt, m: BigInt): BigInt = when {
+        exponent == ZERO -> ONE
+        exponent % 2 == 1 -> (this * modPow(exponent - ONE, m)) % m
+
+        else -> {
+            val sqRoot = modPow(exponent / 2, m)
+            (sqRoot * sqRoot) % m
         }
     }
 
@@ -261,11 +223,11 @@ class BigInt internal constructor(
         return res
     }
 
-    companion object {
-        const val BASE: ULong = 0xffffffffUL
-        const val BASE_SIZE: Int = 32
-        val ZERO: BigInt = BigInt(0, uintArrayOf())
-        val ONE: BigInt = BigInt(1, uintArrayOf(1u))
+    public companion object {
+        public const val BASE: ULong = 0xffffffffUL
+        public const val BASE_SIZE: Int = 32
+        public val ZERO: BigInt = BigInt(0, uintArrayOf())
+        public val ONE: BigInt = BigInt(1, uintArrayOf(1u))
 
         private val hexMapping: HashMap<UInt, String> = hashMapOf(
             0U to "0", 1U to "1", 2U to "2", 3U to "3",
@@ -292,9 +254,9 @@ class BigInt internal constructor(
         }
 
         private fun addMagnitudes(mag1: Magnitude, mag2: Magnitude): Magnitude {
-            val resultLength: Int = max(mag1.size, mag2.size) + 1
+            val resultLength = max(mag1.size, mag2.size) + 1
             val result = Magnitude(resultLength)
-            var carry: TBase = 0UL
+            var carry = 0uL
 
             for (i in 0 until resultLength - 1) {
                 val res = when {
@@ -302,20 +264,22 @@ class BigInt internal constructor(
                     i >= mag2.size -> mag1[i].toULong() + carry
                     else -> mag1[i].toULong() + mag2[i].toULong() + carry
                 }
+
                 result[i] = (res and BASE).toUInt()
                 carry = (res shr BASE_SIZE)
             }
+
             result[resultLength - 1] = carry.toUInt()
             return stripLeadingZeros(result)
         }
 
         private fun subtractMagnitudes(mag1: Magnitude, mag2: Magnitude): Magnitude {
-            val resultLength: Int = mag1.size
+            val resultLength = mag1.size
             val result = Magnitude(resultLength)
             var carry = 0L
 
             for (i in 0 until resultLength) {
-                var res: Long =
+                var res =
                     if (i < mag2.size) mag1[i].toLong() - mag2[i].toLong() - carry
                     else mag1[i].toLong() - carry
 
@@ -329,9 +293,9 @@ class BigInt internal constructor(
         }
 
         private fun multiplyMagnitudeByUInt(mag: Magnitude, x: UInt): Magnitude {
-            val resultLength: Int = mag.size + 1
+            val resultLength = mag.size + 1
             val result = Magnitude(resultLength)
-            var carry: ULong = 0UL
+            var carry = 0uL
 
             for (i in mag.indices) {
                 val cur: ULong = carry + mag[i].toULong() * x.toULong()
@@ -344,16 +308,18 @@ class BigInt internal constructor(
         }
 
         private fun multiplyMagnitudes(mag1: Magnitude, mag2: Magnitude): Magnitude {
-            val resultLength: Int = mag1.size + mag2.size
+            val resultLength = mag1.size + mag2.size
             val result = Magnitude(resultLength)
 
             for (i in mag1.indices) {
-                var carry: ULong = 0UL
+                var carry = 0uL
+
                 for (j in mag2.indices) {
                     val cur: ULong = result[i + j].toULong() + mag1[i].toULong() * mag2[j].toULong() + carry
                     result[i + j] = (cur and BASE.toULong()).toUInt()
                     carry = cur shr BASE_SIZE
                 }
+
                 result[i + mag2.size] = (carry and BASE).toUInt()
             }
 
@@ -361,48 +327,46 @@ class BigInt internal constructor(
         }
 
         private fun divideMagnitudeByUInt(mag: Magnitude, x: UInt): Magnitude {
-            val resultLength: Int = mag.size
+            val resultLength = mag.size
             val result = Magnitude(resultLength)
-            var carry: ULong = 0UL
+            var carry = 0uL
 
             for (i in mag.size - 1 downTo 0) {
                 val cur: ULong = mag[i].toULong() + (carry shl BASE_SIZE)
                 result[i] = (cur / x).toUInt()
                 carry = cur % x
             }
+
             return stripLeadingZeros(result)
         }
-
     }
-
 }
 
-
 private fun stripLeadingZeros(mag: Magnitude): Magnitude {
-    if (mag.isEmpty() || mag.last() != 0U) {
-        return mag
-    }
-    var resSize: Int = mag.size - 1
+    if (mag.isEmpty() || mag.last() != 0U) return mag
+    var resSize = mag.size - 1
+
     while (mag[resSize] == 0U) {
-        if (resSize == 0)
-            break
+        if (resSize == 0) break
         resSize -= 1
     }
+
     return mag.sliceArray(IntRange(0, resSize))
 }
 
-fun abs(x: BigInt): BigInt = x.abs()
+public fun abs(x: BigInt): BigInt = x.abs()
 
 /**
  * Convert this [Int] to [BigInt]
  */
-fun Int.toBigInt(): BigInt = BigInt(sign.toByte(), uintArrayOf(kotlin.math.abs(this).toUInt()))
+public fun Int.toBigInt(): BigInt = BigInt(sign.toByte(), uintArrayOf(kotlin.math.abs(this).toUInt()))
 
 /**
  * Convert this [Long] to [BigInt]
  */
-fun Long.toBigInt(): BigInt = BigInt(
-    sign.toByte(), stripLeadingZeros(
+public fun Long.toBigInt(): BigInt = BigInt(
+    sign.toByte(),
+    stripLeadingZeros(
         uintArrayOf(
             (kotlin.math.abs(this).toULong() and BASE).toUInt(),
             ((kotlin.math.abs(this).toULong() shr BASE_SIZE) and BASE).toUInt()
@@ -413,12 +377,12 @@ fun Long.toBigInt(): BigInt = BigInt(
 /**
  * Convert UInt to [BigInt]
  */
-fun UInt.toBigInt(): BigInt = BigInt(1, uintArrayOf(this))
+public fun UInt.toBigInt(): BigInt = BigInt(1, uintArrayOf(this))
 
 /**
  * Convert ULong to [BigInt]
  */
-fun ULong.toBigInt(): BigInt = BigInt(
+public fun ULong.toBigInt(): BigInt = BigInt(
     1,
     stripLeadingZeros(
         uintArrayOf(
@@ -431,12 +395,12 @@ fun ULong.toBigInt(): BigInt = BigInt(
 /**
  * Create a [BigInt] with this array of magnitudes with protective copy
  */
-fun UIntArray.toBigInt(sign: Byte): BigInt {
+public fun UIntArray.toBigInt(sign: Byte): BigInt {
     require(sign != 0.toByte() || !isNotEmpty())
     return BigInt(sign, copyOf())
 }
 
-val hexChToInt: MutableMap<Char, Int> = hashMapOf(
+private val hexChToInt: MutableMap<Char, Int> = hashMapOf(
     '0' to 0, '1' to 1, '2' to 2, '3' to 3,
     '4' to 4, '5' to 5, '6' to 6, '7' to 7,
     '8' to 8, '9' to 9, 'A' to 10, 'B' to 11,
@@ -446,9 +410,10 @@ val hexChToInt: MutableMap<Char, Int> = hashMapOf(
 /**
  * Returns null if a valid number can not be read from a string
  */
-fun String.parseBigInteger(): BigInt? {
+public fun String.parseBigInteger(): BigInt? {
     val sign: Int
     val sPositive: String
+
     when {
         this[0] == '+' -> {
             sign = +1
@@ -463,43 +428,42 @@ fun String.parseBigInteger(): BigInt? {
             sign = +1
         }
     }
+
     var res = BigInt.ZERO
     var digitValue = BigInt.ONE
     val sPositiveUpper = sPositive.toUpperCase()
+
     if (sPositiveUpper.startsWith("0X")) {  // hex representation
         val sHex = sPositiveUpper.substring(2)
+
         for (ch in sHex.reversed()) {
             if (ch == '_') continue
             res += digitValue * (hexChToInt[ch] ?: return null)
             digitValue *= 16.toBigInt()
         }
-    } else { // decimal representation
-        for (ch in sPositiveUpper.reversed()) {
-            if (ch == '_') continue
-            if (ch !in '0'..'9') {
-                return null
-            }
-            res += digitValue * (ch.toInt() - '0'.toInt())
-            digitValue *= 10.toBigInt()
+    } else for (ch in sPositiveUpper.reversed()) {
+        // decimal representation
+        if (ch == '_') continue
+        if (ch !in '0'..'9') {
+            return null
         }
+        res += digitValue * (ch.toInt() - '0'.toInt())
+        digitValue *= 10.toBigInt()
     }
+
     return res * sign
 }
 
-inline fun Buffer.Companion.bigInt(size: Int, initializer: (Int) -> BigInt): Buffer<BigInt> {
-    contract { callsInPlace(initializer) }
-    return boxing(size, initializer)
-}
+public inline fun Buffer.Companion.bigInt(size: Int, initializer: (Int) -> BigInt): Buffer<BigInt> =
+    boxing(size, initializer)
 
-inline fun MutableBuffer.Companion.bigInt(size: Int, initializer: (Int) -> BigInt): MutableBuffer<BigInt> {
-    contract { callsInPlace(initializer) }
-    return boxing(size, initializer)
-}
+public inline fun MutableBuffer.Companion.bigInt(size: Int, initializer: (Int) -> BigInt): MutableBuffer<BigInt> =
+    boxing(size, initializer)
 
-fun NDAlgebra.Companion.bigInt(vararg shape: Int): BoxingNDRing<BigInt, BigIntField> =
+public fun NDAlgebra.Companion.bigInt(vararg shape: Int): BoxingNDRing<BigInt, BigIntField> =
     BoxingNDRing(shape, BigIntField, Buffer.Companion::bigInt)
 
-fun NDElement.Companion.bigInt(
+public fun NDElement.Companion.bigInt(
     vararg shape: Int,
     initializer: BigIntField.(IntArray) -> BigInt
 ): BufferedNDRingElement<BigInt, BigIntField> = NDAlgebra.bigInt(*shape).produce(initializer)

kmath-core/src/commonMain/kotlin/kscience/kmath/operations/Complex.kt

@@ -1,25 +1,23 @@
-package scientifik.kmath.operations
+package kscience.kmath.operations
 
-import scientifik.kmath.structures.Buffer
-import scientifik.kmath.structures.MemoryBuffer
-import scientifik.kmath.structures.MutableBuffer
-import scientifik.memory.MemoryReader
-import scientifik.memory.MemorySpec
-import scientifik.memory.MemoryWriter
-import kotlin.contracts.ExperimentalContracts
-import kotlin.contracts.contract
+import kscience.kmath.structures.Buffer
+import kscience.kmath.structures.MemoryBuffer
+import kscience.kmath.structures.MutableBuffer
+import kscience.memory.MemoryReader
+import kscience.memory.MemorySpec
+import kscience.memory.MemoryWriter
 import kotlin.math.*
 
 /**
  * This complex's conjugate.
  */
-val Complex.conjugate: Complex
+public val Complex.conjugate: Complex
     get() = Complex(re, -im)
 
 /**
  * This complex's reciprocal.
  */
-val Complex.reciprocal: Complex
+public val Complex.reciprocal: Complex
     get() {
         val scale = re * re + im * im
         return Complex(re / scale, -im / scale)
@@ -28,13 +26,13 @@ val Complex.reciprocal: Complex
 /**
  * Absolute value of complex number.
  */
-val Complex.r: Double
+public val Complex.r: Double
     get() = sqrt(re * re + im * im)
 
 /**
  * An angle between vector represented by complex number and X axis.
  */
-val Complex.theta: Double
+public val Complex.theta: Double
     get() = atan(im / re)
 
 private val PI_DIV_2 = Complex(PI / 2, 0)
@@ -42,14 +40,14 @@ private val PI_DIV_2 = Complex(PI / 2, 0)
 /**
  * A field of [Complex].
  */
-object ComplexField : ExtendedField<Complex>, Norm<Complex, Complex> {
+public object ComplexField : ExtendedField<Complex>, Norm<Complex, Complex> {
     override val zero: Complex = 0.0.toComplex()
     override val one: Complex = 1.0.toComplex()
 
     /**
      * The imaginary unit.
      */
-    val i: Complex = Complex(0.0, 1.0)
+    public val i: Complex = Complex(0.0, 1.0)
 
     override fun add(a: Complex, b: Complex): Complex = Complex(a.re + b.re, a.im + b.im)
 
@@ -117,7 +115,7 @@ object ComplexField : ExtendedField<Complex>, Norm<Complex, Complex> {
      * @param c the augend.
      * @return the sum.
      */
-    operator fun Double.plus(c: Complex): Complex = add(this.toComplex(), c)
+    public operator fun Double.plus(c: Complex): Complex = add(this.toComplex(), c)
 
     /**
      * Subtracts complex number from real one.
@@ -126,7 +124,7 @@ object ComplexField : ExtendedField<Complex>, Norm<Complex, Complex> {
      * @param c the subtrahend.
      * @return the difference.
      */
-    operator fun Double.minus(c: Complex): Complex = add(this.toComplex(), -c)
+    public operator fun Double.minus(c: Complex): Complex = add(this.toComplex(), -c)
 
     /**
      * Adds real number to complex one.
@@ -135,7 +133,7 @@ object ComplexField : ExtendedField<Complex>, Norm<Complex, Complex> {
      * @param d the augend.
      * @return the sum.
      */
-    operator fun Complex.plus(d: Double): Complex = d + this
+    public operator fun Complex.plus(d: Double): Complex = d + this
 
     /**
      * Subtracts real number from complex one.
@@ -144,7 +142,7 @@ object ComplexField : ExtendedField<Complex>, Norm<Complex, Complex> {
      * @param d the subtrahend.
      * @return the difference.
      */
-    operator fun Complex.minus(d: Double): Complex = add(this, -d.toComplex())
+    public operator fun Complex.minus(d: Double): Complex = add(this, -d.toComplex())
 
     /**
      * Multiplies real number by complex one.
@@ -153,7 +151,7 @@ object ComplexField : ExtendedField<Complex>, Norm<Complex, Complex> {
      * @param c the multiplicand.
      * @receiver the product.
      */
-    operator fun Double.times(c: Complex): Complex = Complex(c.re * this, c.im * this)
+    public operator fun Double.times(c: Complex): Complex = Complex(c.re * this, c.im * this)
 
     override fun norm(arg: Complex): Complex = sqrt(arg.conjugate * arg)
 
@@ -166,8 +164,9 @@ object ComplexField : ExtendedField<Complex>, Norm<Complex, Complex> {
  * @property re The real part.
  * @property im The imaginary part.
  */
-data class Complex(val re: Double, val im: Double) : FieldElement<Complex, Complex, ComplexField>, Comparable<Complex> {
-    constructor(re: Number, im: Number) : this(re.toDouble(), im.toDouble())
+public data class Complex(val re: Double, val im: Double) : FieldElement<Complex, Complex, ComplexField>,
+    Comparable<Complex> {
+    public constructor(re: Number, im: Number) : this(re.toDouble(), im.toDouble())
 
     override val context: ComplexField get() = ComplexField
 
@@ -177,7 +176,7 @@ data class Complex(val re: Double, val im: Double) : FieldElement<Complex, Compl
 
     override fun compareTo(other: Complex): Int = r.compareTo(other.r)
 
-    companion object : MemorySpec<Complex> {
+    public companion object : MemorySpec<Complex> {
         override val objectSize: Int = 16
 
         override fun MemoryReader.read(offset: Int): Complex =
@@ -196,14 +195,10 @@ data class Complex(val re: Double, val im: Double) : FieldElement<Complex, Compl
  * @receiver the real part.
  * @return the new complex number.
  */
-fun Number.toComplex(): Complex = Complex(this, 0.0)
+public fun Number.toComplex(): Complex = Complex(this, 0.0)
 
-inline fun Buffer.Companion.complex(size: Int, crossinline init: (Int) -> Complex): Buffer<Complex> {
-    contract { callsInPlace(init) }
-    return MemoryBuffer.create(Complex, size, init)
-}
+public inline fun Buffer.Companion.complex(size: Int, init: (Int) -> Complex): Buffer<Complex> =
+    MemoryBuffer.create(Complex, size, init)
 
-inline fun MutableBuffer.Companion.complex(size: Int, crossinline init: (Int) -> Complex): Buffer<Complex> {
-    contract { callsInPlace(init) }
-    return MemoryBuffer.create(Complex, size, init)
-}
+public inline fun MutableBuffer.Companion.complex(size: Int, init: (Int) -> Complex): Buffer<Complex> =
+    MemoryBuffer.create(Complex, size, init)

kmath-core/src/commonMain/kotlin/kscience/kmath/operations/NumberAlgebra.kt

@@ -0,0 +1,266 @@
+package kscience.kmath.operations
+
+import kotlin.math.abs
+import kotlin.math.pow as kpow
+
+/**
+ * Advanced Number-like semifield that implements basic operations.
+ */
+public interface ExtendedFieldOperations<T> :
+    FieldOperations<T>,
+    TrigonometricOperations<T>,
+    HyperbolicOperations<T>,
+    PowerOperations<T>,
+    ExponentialOperations<T> {
+    public override fun tan(arg: T): T = sin(arg) / cos(arg)
+    public override fun tanh(arg: T): T = sinh(arg) / cosh(arg)
+
+    public override fun unaryOperation(operation: String, arg: T): T = when (operation) {
+        TrigonometricOperations.COS_OPERATION -> cos(arg)
+        TrigonometricOperations.SIN_OPERATION -> sin(arg)
+        TrigonometricOperations.TAN_OPERATION -> tan(arg)
+        TrigonometricOperations.ACOS_OPERATION -> acos(arg)
+        TrigonometricOperations.ASIN_OPERATION -> asin(arg)
+        TrigonometricOperations.ATAN_OPERATION -> atan(arg)
+        HyperbolicOperations.COSH_OPERATION -> cosh(arg)
+        HyperbolicOperations.SINH_OPERATION -> sinh(arg)
+        HyperbolicOperations.TANH_OPERATION -> tanh(arg)
+        HyperbolicOperations.ACOSH_OPERATION -> acosh(arg)
+        HyperbolicOperations.ASINH_OPERATION -> asinh(arg)
+        HyperbolicOperations.ATANH_OPERATION -> atanh(arg)
+        PowerOperations.SQRT_OPERATION -> sqrt(arg)
+        ExponentialOperations.EXP_OPERATION -> exp(arg)
+        ExponentialOperations.LN_OPERATION -> ln(arg)
+        else -> super.unaryOperation(operation, arg)
+    }
+}
+
+/**
+ * Advanced Number-like field that implements basic operations.
+ */
+public interface ExtendedField<T> : ExtendedFieldOperations<T>, Field<T> {
+    public override fun sinh(arg: T): T = (exp(arg) - exp(-arg)) / 2
+    public override fun cosh(arg: T): T = (exp(arg) + exp(-arg)) / 2
+    public override fun tanh(arg: T): T = (exp(arg) - exp(-arg)) / (exp(-arg) + exp(arg))
+    public override fun asinh(arg: T): T = ln(sqrt(arg * arg + one) + arg)
+    public override fun acosh(arg: T): T = ln(arg + sqrt((arg - one) * (arg + one)))
+    public override fun atanh(arg: T): T = (ln(arg + one) - ln(one - arg)) / 2
+
+    public override fun rightSideNumberOperation(operation: String, left: T, right: Number): T = when (operation) {
+        PowerOperations.POW_OPERATION -> power(left, right)
+        else -> super.rightSideNumberOperation(operation, left, right)
+    }
+}
+
+/**
+ * Real field element wrapping double.
+ *
+ * @property value the [Double] value wrapped by this [Real].
+ *
+ * TODO inline does not work due to compiler bug. Waiting for fix for KT-27586
+ */
+public inline class Real(public val value: Double) : FieldElement<Double, Real, RealField> {
+    public override val context: RealField
+        get() = RealField
+
+    public override fun unwrap(): Double = value
+    public override fun Double.wrap(): Real = Real(value)
+
+    public companion object
+}
+
+/**
+ * A field for [Double] without boxing. Does not produce appropriate field element.
+ */
+@Suppress("EXTENSION_SHADOWED_BY_MEMBER", "OVERRIDE_BY_INLINE", "NOTHING_TO_INLINE")
+public object RealField : ExtendedField<Double>, Norm<Double, Double> {
+    public override val zero: Double
+        get() = 0.0
+
+    public override val one: Double
+        get() = 1.0
+
+    public override fun binaryOperation(operation: String, left: Double, right: Double): Double = when (operation) {
+        PowerOperations.POW_OPERATION -> left pow right
+        else -> super.binaryOperation(operation, left, right)
+    }
+
+    public override inline fun add(a: Double, b: Double): Double = a + b
+    public override inline fun multiply(a: Double, k: Number): Double = a * k.toDouble()
+
+    public override inline fun multiply(a: Double, b: Double): Double = a * b
+
+    public override inline fun divide(a: Double, b: Double): Double = a / b
+
+    public override inline fun sin(arg: Double): Double = kotlin.math.sin(arg)
+    public override inline fun cos(arg: Double): Double = kotlin.math.cos(arg)
+    public override inline fun tan(arg: Double): Double = kotlin.math.tan(arg)
+    public override inline fun acos(arg: Double): Double = kotlin.math.acos(arg)
+    public override inline fun asin(arg: Double): Double = kotlin.math.asin(arg)
+    public override inline fun atan(arg: Double): Double = kotlin.math.atan(arg)
+
+    public override inline fun sinh(arg: Double): Double = kotlin.math.sinh(arg)
+    public override inline fun cosh(arg: Double): Double = kotlin.math.cosh(arg)
+    public override inline fun tanh(arg: Double): Double = kotlin.math.tanh(arg)
+    public override inline fun asinh(arg: Double): Double = kotlin.math.asinh(arg)
+    public override inline fun acosh(arg: Double): Double = kotlin.math.acosh(arg)
+    public override inline fun atanh(arg: Double): Double = kotlin.math.atanh(arg)
+
+    public override inline fun power(arg: Double, pow: Number): Double = arg.kpow(pow.toDouble())
+    public override inline fun exp(arg: Double): Double = kotlin.math.exp(arg)
+    public override inline fun ln(arg: Double): Double = kotlin.math.ln(arg)
+
+    public override inline fun norm(arg: Double): Double = abs(arg)
+
+    public override inline fun Double.unaryMinus(): Double = -this
+    public override inline fun Double.plus(b: Double): Double = this + b
+    public override inline fun Double.minus(b: Double): Double = this - b
+    public override inline fun Double.times(b: Double): Double = this * b
+    public override inline fun Double.div(b: Double): Double = this / b
+}
+
+/**
+ * A field for [Float] without boxing. Does not produce appropriate field element.
+ */
+@Suppress("EXTENSION_SHADOWED_BY_MEMBER", "OVERRIDE_BY_INLINE", "NOTHING_TO_INLINE")
+public object FloatField : ExtendedField<Float>, Norm<Float, Float> {
+    public override val zero: Float
+        get() = 0.0f
+
+    public override val one: Float
+        get() = 1.0f
+
+    public override fun binaryOperation(operation: String, left: Float, right: Float): Float = when (operation) {
+        PowerOperations.POW_OPERATION -> left pow right
+        else -> super.binaryOperation(operation, left, right)
+    }
+
+    public override inline fun add(a: Float, b: Float): Float = a + b
+    public override inline fun multiply(a: Float, k: Number): Float = a * k.toFloat()
+
+    public override inline fun multiply(a: Float, b: Float): Float = a * b
+
+    public override inline fun divide(a: Float, b: Float): Float = a / b
+
+    public override inline fun sin(arg: Float): Float = kotlin.math.sin(arg)
+    public override inline fun cos(arg: Float): Float = kotlin.math.cos(arg)
+    public override inline fun tan(arg: Float): Float = kotlin.math.tan(arg)
+    public override inline fun acos(arg: Float): Float = kotlin.math.acos(arg)
+    public override inline fun asin(arg: Float): Float = kotlin.math.asin(arg)
+    public override inline fun atan(arg: Float): Float = kotlin.math.atan(arg)
+
+    public override inline fun sinh(arg: Float): Float = kotlin.math.sinh(arg)
+    public override inline fun cosh(arg: Float): Float = kotlin.math.cosh(arg)
+    public override inline fun tanh(arg: Float): Float = kotlin.math.tanh(arg)
+    public override inline fun asinh(arg: Float): Float = kotlin.math.asinh(arg)
+    public override inline fun acosh(arg: Float): Float = kotlin.math.acosh(arg)
+    public override inline fun atanh(arg: Float): Float = kotlin.math.atanh(arg)
+
+    public override inline fun power(arg: Float, pow: Number): Float = arg.kpow(pow.toFloat())
+    public override inline fun exp(arg: Float): Float = kotlin.math.exp(arg)
+    public override inline fun ln(arg: Float): Float = kotlin.math.ln(arg)
+
+    public override inline fun norm(arg: Float): Float = abs(arg)
+
+    public override inline fun Float.unaryMinus(): Float = -this
+    public override inline fun Float.plus(b: Float): Float = this + b
+    public override inline fun Float.minus(b: Float): Float = this - b
+    public override inline fun Float.times(b: Float): Float = this * b
+    public override inline fun Float.div(b: Float): Float = this / b
+}
+
+/**
+ * A field for [Int] without boxing. Does not produce corresponding ring element.
+ */
+@Suppress("EXTENSION_SHADOWED_BY_MEMBER", "OVERRIDE_BY_INLINE", "NOTHING_TO_INLINE")
+public object IntRing : Ring<Int>, Norm<Int, Int> {
+    public override val zero: Int
+        get() = 0
+
+    public override val one: Int
+        get() = 1
+
+    public override inline fun add(a: Int, b: Int): Int = a + b
+    public override inline fun multiply(a: Int, k: Number): Int = k.toInt() * a
+
+    public override inline fun multiply(a: Int, b: Int): Int = a * b
+
+    public override inline fun norm(arg: Int): Int = abs(arg)
+
+    public override inline fun Int.unaryMinus(): Int = -this
+    public override inline fun Int.plus(b: Int): Int = this + b
+    public override inline fun Int.minus(b: Int): Int = this - b
+    public override inline fun Int.times(b: Int): Int = this * b
+}
+
+/**
+ * A field for [Short] without boxing. Does not produce appropriate ring element.
+ */
+@Suppress("EXTENSION_SHADOWED_BY_MEMBER", "OVERRIDE_BY_INLINE", "NOTHING_TO_INLINE")
+public object ShortRing : Ring<Short>, Norm<Short, Short> {
+    public override val zero: Short
+        get() = 0
+
+    public override val one: Short
+        get() = 1
+
+    public override inline fun add(a: Short, b: Short): Short = (a + b).toShort()
+    public override inline fun multiply(a: Short, k: Number): Short = (a * k.toShort()).toShort()
+
+    public override inline fun multiply(a: Short, b: Short): Short = (a * b).toShort()
+
+    public override fun norm(arg: Short): Short = if (arg > 0) arg else (-arg).toShort()
+
+    public override inline fun Short.unaryMinus(): Short = (-this).toShort()
+    public override inline fun Short.plus(b: Short): Short = (this + b).toShort()
+    public override inline fun Short.minus(b: Short): Short = (this - b).toShort()
+    public override inline fun Short.times(b: Short): Short = (this * b).toShort()
+}
+
+/**
+ * A field for [Byte] without boxing. Does not produce appropriate ring element.
+ */
+@Suppress("EXTENSION_SHADOWED_BY_MEMBER", "OVERRIDE_BY_INLINE", "NOTHING_TO_INLINE")
+public object ByteRing : Ring<Byte>, Norm<Byte, Byte> {
+    public override val zero: Byte
+        get() = 0
+
+    public override val one: Byte
+        get() = 1
+
+    public override inline fun add(a: Byte, b: Byte): Byte = (a + b).toByte()
+    public override inline fun multiply(a: Byte, k: Number): Byte = (a * k.toByte()).toByte()
+
+    public override inline fun multiply(a: Byte, b: Byte): Byte = (a * b).toByte()
+
+    public override fun norm(arg: Byte): Byte = if (arg > 0) arg else (-arg).toByte()
+
+    public override inline fun Byte.unaryMinus(): Byte = (-this).toByte()
+    public override inline fun Byte.plus(b: Byte): Byte = (this + b).toByte()
+    public override inline fun Byte.minus(b: Byte): Byte = (this - b).toByte()
+    public override inline fun Byte.times(b: Byte): Byte = (this * b).toByte()
+}
+
+/**
+ * A field for [Double] without boxing. Does not produce appropriate ring element.
+ */
+@Suppress("EXTENSION_SHADOWED_BY_MEMBER", "OVERRIDE_BY_INLINE", "NOTHING_TO_INLINE")
+public object LongRing : Ring<Long>, Norm<Long, Long> {
+    public override val zero: Long
+        get() = 0
+
+    public override val one: Long
+        get() = 1
+
+    public override inline fun add(a: Long, b: Long): Long = a + b
+    public override inline fun multiply(a: Long, k: Number): Long = a * k.toLong()
+
+    public override inline fun multiply(a: Long, b: Long): Long = a * b
+
+    public override fun norm(arg: Long): Long = abs(arg)
+
+    public override inline fun Long.unaryMinus(): Long = (-this)
+    public override inline fun Long.plus(b: Long): Long = (this + b)
+    public override inline fun Long.minus(b: Long): Long = (this - b)
+    public override inline fun Long.times(b: Long): Long = (this * b)
+}

kmath-core/src/commonMain/kotlin/kscience/kmath/operations/OptionalOperations.kt

@@ -1,234 +1,234 @@
-package scientifik.kmath.operations
+package kscience.kmath.operations
 
 /**
  * A container for trigonometric operations for specific type.
  *
  * @param T the type of element of this structure.
  */
-interface TrigonometricOperations<T> : Algebra<T> {
+public interface TrigonometricOperations<T> : Algebra<T> {
     /**
      * Computes the sine of [arg].
      */
-    fun sin(arg: T): T
+    public fun sin(arg: T): T
 
     /**
      * Computes the cosine of [arg].
      */
-    fun cos(arg: T): T
+    public fun cos(arg: T): T
 
     /**
      * Computes the tangent of [arg].
      */
-    fun tan(arg: T): T
+    public fun tan(arg: T): T
 
     /**
      * Computes the inverse sine of [arg].
      */
-    fun asin(arg: T): T
+    public fun asin(arg: T): T
 
     /**
      * Computes the inverse cosine of [arg].
      */
-    fun acos(arg: T): T
+    public fun acos(arg: T): T
 
     /**
      * Computes the inverse tangent of [arg].
      */
-    fun atan(arg: T): T
+    public fun atan(arg: T): T
 
-    companion object {
+    public companion object {
         /**
          * The identifier of sine.
          */
-        const val SIN_OPERATION: String = "sin"
+        public const val SIN_OPERATION: String = "sin"
 
         /**
          * The identifier of cosine.
          */
-        const val COS_OPERATION: String = "cos"
+        public const val COS_OPERATION: String = "cos"
 
         /**
          * The identifier of tangent.
          */
-        const val TAN_OPERATION: String = "tan"
+        public const val TAN_OPERATION: String = "tan"
 
         /**
          * The identifier of inverse sine.
          */
-        const val ASIN_OPERATION: String = "asin"
+        public const val ASIN_OPERATION: String = "asin"
 
         /**
          * The identifier of inverse cosine.
          */
-        const val ACOS_OPERATION: String = "acos"
+        public const val ACOS_OPERATION: String = "acos"
 
         /**
          * The identifier of inverse tangent.
          */
-        const val ATAN_OPERATION: String = "atan"
+        public const val ATAN_OPERATION: String = "atan"
     }
 }
 
 /**
  * Computes the sine of [arg].
  */
-fun <T : MathElement<out TrigonometricOperations<T>>> sin(arg: T): T = arg.context.sin(arg)
+public fun <T : MathElement<out TrigonometricOperations<T>>> sin(arg: T): T = arg.context.sin(arg)
 
 /**
  * Computes the cosine of [arg].
  */
-fun <T : MathElement<out TrigonometricOperations<T>>> cos(arg: T): T = arg.context.cos(arg)
+public fun <T : MathElement<out TrigonometricOperations<T>>> cos(arg: T): T = arg.context.cos(arg)
 
 /**
  * Computes the tangent of [arg].
  */
-fun <T : MathElement<out TrigonometricOperations<T>>> tan(arg: T): T = arg.context.tan(arg)
+public fun <T : MathElement<out TrigonometricOperations<T>>> tan(arg: T): T = arg.context.tan(arg)
 
 /**
  * Computes the inverse sine of [arg].
  */
-fun <T : MathElement<out TrigonometricOperations<T>>> asin(arg: T): T = arg.context.asin(arg)
+public fun <T : MathElement<out TrigonometricOperations<T>>> asin(arg: T): T = arg.context.asin(arg)
 
 /**
  * Computes the inverse cosine of [arg].
  */
-fun <T : MathElement<out TrigonometricOperations<T>>> acos(arg: T): T = arg.context.acos(arg)
+public fun <T : MathElement<out TrigonometricOperations<T>>> acos(arg: T): T = arg.context.acos(arg)
 
 /**
  * Computes the inverse tangent of [arg].
  */
-fun <T : MathElement<out TrigonometricOperations<T>>> atan(arg: T): T = arg.context.atan(arg)
+public fun <T : MathElement<out TrigonometricOperations<T>>> atan(arg: T): T = arg.context.atan(arg)
 
 /**
  * A container for hyperbolic trigonometric operations for specific type.
  *
  * @param T the type of element of this structure.
  */
-interface HyperbolicOperations<T> : Algebra<T> {
+public interface HyperbolicOperations<T> : Algebra<T> {
     /**
      * Computes the hyperbolic sine of [arg].
      */
-    fun sinh(arg: T): T
+    public fun sinh(arg: T): T
 
     /**
      * Computes the hyperbolic cosine of [arg].
      */
-    fun cosh(arg: T): T
+    public fun cosh(arg: T): T
 
     /**
      * Computes the hyperbolic tangent of [arg].
      */
-    fun tanh(arg: T): T
+    public fun tanh(arg: T): T
 
     /**
      * Computes the inverse hyperbolic sine of [arg].
      */
-    fun asinh(arg: T): T
+    public fun asinh(arg: T): T
 
     /**
      * Computes the inverse hyperbolic cosine of [arg].
      */
-    fun acosh(arg: T): T
+    public fun acosh(arg: T): T
 
     /**
      * Computes the inverse hyperbolic tangent of [arg].
      */
-    fun atanh(arg: T): T
+    public fun atanh(arg: T): T
 
-    companion object {
+    public companion object {
         /**
          * The identifier of hyperbolic sine.
          */
-        const val SINH_OPERATION: String = "sinh"
+        public const val SINH_OPERATION: String = "sinh"
 
         /**
          * The identifier of hyperbolic cosine.
          */
-        const val COSH_OPERATION: String = "cosh"
+        public const val COSH_OPERATION: String = "cosh"
 
         /**
          * The identifier of hyperbolic tangent.
          */
-        const val TANH_OPERATION: String = "tanh"
+        public const val TANH_OPERATION: String = "tanh"
 
         /**
          * The identifier of inverse hyperbolic sine.
          */
-        const val ASINH_OPERATION: String = "asinh"
+        public const val ASINH_OPERATION: String = "asinh"
 
         /**
          * The identifier of inverse hyperbolic cosine.
          */
-        const val ACOSH_OPERATION: String = "acosh"
+        public const val ACOSH_OPERATION: String = "acosh"
 
         /**
          * The identifier of inverse hyperbolic tangent.
          */
-        const val ATANH_OPERATION: String = "atanh"
+        public const val ATANH_OPERATION: String = "atanh"
     }
 }
 
 /**
  * Computes the hyperbolic sine of [arg].
  */
-fun <T : MathElement<out HyperbolicOperations<T>>> sinh(arg: T): T = arg.context.sinh(arg)
+public fun <T : MathElement<out HyperbolicOperations<T>>> sinh(arg: T): T = arg.context.sinh(arg)
 
 /**
  * Computes the hyperbolic cosine of [arg].
  */
-fun <T : MathElement<out HyperbolicOperations<T>>> cosh(arg: T): T = arg.context.cosh(arg)
+public fun <T : MathElement<out HyperbolicOperations<T>>> cosh(arg: T): T = arg.context.cosh(arg)
 
 /**
  * Computes the hyperbolic tangent of [arg].
  */
-fun <T : MathElement<out HyperbolicOperations<T>>> tanh(arg: T): T = arg.context.tanh(arg)
+public fun <T : MathElement<out HyperbolicOperations<T>>> tanh(arg: T): T = arg.context.tanh(arg)
 
 /**
  * Computes the inverse hyperbolic sine of [arg].
  */
-fun <T : MathElement<out HyperbolicOperations<T>>> asinh(arg: T): T = arg.context.asinh(arg)
+public fun <T : MathElement<out HyperbolicOperations<T>>> asinh(arg: T): T = arg.context.asinh(arg)
 
 /**
  * Computes the inverse hyperbolic cosine of [arg].
  */
-fun <T : MathElement<out HyperbolicOperations<T>>> acosh(arg: T): T = arg.context.acosh(arg)
+public fun <T : MathElement<out HyperbolicOperations<T>>> acosh(arg: T): T = arg.context.acosh(arg)
 
 /**
  * Computes the inverse hyperbolic tangent of [arg].
  */
-fun <T : MathElement<out HyperbolicOperations<T>>> atanh(arg: T): T = arg.context.atanh(arg)
+public fun <T : MathElement<out HyperbolicOperations<T>>> atanh(arg: T): T = arg.context.atanh(arg)
 
 /**
  * A context extension to include power operations based on exponentiation.
  *
  * @param T the type of element of this structure.
  */
-interface PowerOperations<T> : Algebra<T> {
+public interface PowerOperations<T> : Algebra<T> {
     /**
      * Raises [arg] to the power [pow].
      */
-    fun power(arg: T, pow: Number): T
+    public fun power(arg: T, pow: Number): T
 
     /**
      * Computes the square root of the value [arg].
      */
-    fun sqrt(arg: T): T = power(arg, 0.5)
+    public fun sqrt(arg: T): T = power(arg, 0.5)
 
     /**
      * Raises this value to the power [pow].
      */
-    infix fun T.pow(pow: Number): T = power(this, pow)
+    public infix fun T.pow(pow: Number): T = power(this, pow)
 
-    companion object {
+    public companion object {
         /**
          * The identifier of exponentiation.
          */
-        const val POW_OPERATION: String = "pow"
+        public const val POW_OPERATION: String = "pow"
 
         /**
          * The identifier of square root.
          */
-        const val SQRT_OPERATION: String = "sqrt"
+        public const val SQRT_OPERATION: String = "sqrt"
     }
 }
 
@@ -239,56 +239,56 @@ interface PowerOperations<T> : Algebra<T> {
  * @param power the exponent.
  * @return the base raised to the power.
  */
-infix fun <T : MathElement<out PowerOperations<T>>> T.pow(power: Double): T = context.power(this, power)
+public infix fun <T : MathElement<out PowerOperations<T>>> T.pow(power: Double): T = context.power(this, power)
 
 /**
  * Computes the square root of the value [arg].
  */
-fun <T : MathElement<out PowerOperations<T>>> sqrt(arg: T): T = arg pow 0.5
+public fun <T : MathElement<out PowerOperations<T>>> sqrt(arg: T): T = arg pow 0.5
 
 /**
  * Computes the square of the value [arg].
  */
-fun <T : MathElement<out PowerOperations<T>>> sqr(arg: T): T = arg pow 2.0
+public fun <T : MathElement<out PowerOperations<T>>> sqr(arg: T): T = arg pow 2.0
 
 /**
  * A container for operations related to `exp` and `ln` functions.
  *
  * @param T the type of element of this structure.
  */
-interface ExponentialOperations<T> : Algebra<T> {
+public interface ExponentialOperations<T> : Algebra<T> {
     /**
      * Computes Euler's number `e` raised to the power of the value [arg].
      */
-    fun exp(arg: T): T
+    public fun exp(arg: T): T
 
     /**
      * Computes the natural logarithm (base `e`) of the value [arg].
      */
-    fun ln(arg: T): T
+    public fun ln(arg: T): T
 
-    companion object {
+    public companion object {
         /**
          * The identifier of exponential function.
          */
-        const val EXP_OPERATION: String = "exp"
+        public const val EXP_OPERATION: String = "exp"
 
         /**
          * The identifier of natural logarithm.
          */
-        const val LN_OPERATION: String = "ln"
+        public const val LN_OPERATION: String = "ln"
     }
 }
 
 /**
  * The identifier of exponential function.
  */
-fun <T : MathElement<out ExponentialOperations<T>>> exp(arg: T): T = arg.context.exp(arg)
+public fun <T : MathElement<out ExponentialOperations<T>>> exp(arg: T): T = arg.context.exp(arg)
 
 /**
  * The identifier of natural logarithm.
  */
-fun <T : MathElement<out ExponentialOperations<T>>> ln(arg: T): T = arg.context.ln(arg)
+public fun <T : MathElement<out ExponentialOperations<T>>> ln(arg: T): T = arg.context.ln(arg)
 
 /**
  * A container for norm functional on element.
@@ -296,14 +296,14 @@ fun <T : MathElement<out ExponentialOperations<T>>> ln(arg: T): T = arg.context.
  * @param T the type of element having norm defined.
  * @param R the type of norm.
  */
-interface Norm<in T : Any, out R> {
+public interface Norm<in T : Any, out R> {
     /**
      * Computes the norm of [arg] (i.e. absolute value or vector length).
      */
-    fun norm(arg: T): R
+    public fun norm(arg: T): R
 }
 
 /**
  * Computes the norm of [arg] (i.e. absolute value or vector length).
  */
-fun <T : MathElement<out Norm<T, R>>, R> norm(arg: T): R = arg.context.norm(arg)
+public fun <T : MathElement<out Norm<T, R>>, R> norm(arg: T): R = arg.context.norm(arg)