Workaround for dokka bug: https://github.com/Kotlin/dokka/issues/4001

Move last projects from JVM to MPP.
Update changelog.

.github/workflows/build.yml

@@ -10,15 +10,25 @@ jobs:
     runs-on: windows-latest
     timeout-minutes: 20
     steps:
-      - uses: actions/checkout@v3
-      - uses: actions/setup-java@v3.5.1
+      - uses: actions/checkout@v6
+      - uses: actions/setup-java@v5
         with:
-          java-version: '11'
+          java-version: '21'
           distribution: 'liberica'
           cache: 'gradle'
       - name: Gradle Wrapper Validation
         uses: gradle/wrapper-validation-action@v1.0.4
       - name: Gradle Build
-        uses: gradle/gradle-build-action@v2.4.2
+        uses: gradle/gradle-build-action@v3
         with:
           arguments: test jvmTest
+      - name: Publish Test Report
+        uses: mikepenz/action-junit-report@v6
+        if: ${{ !cancelled() }} # always run even if the previous step fails
+        with:
+          report_paths: '**/test-results/**/TEST-*.xml'
+          annotate_only: true
+          detailed_summary: true
+          flaky_summary: true
+          include_empty_in_summary: false
+          skip_success_summary: true

.github/workflows/pages.yml

@@ -7,25 +7,20 @@ on:
 
 jobs:
   build:
-    runs-on: ubuntu-20.04
+    runs-on: ubuntu-24.04
     timeout-minutes: 40
     steps:
-      - uses: actions/checkout@v3.0.0
-      - uses: actions/setup-java@v3.0.0
+      - uses: actions/checkout@v6
+      - uses: actions/setup-java@v5
         with:
-          java-version: 11
+          java-version: 21
           distribution: liberica
-      - name: Cache konan
-        uses: actions/cache@v3.0.1
+      - name: Gradle Wrapper Validation
+        uses: gradle/wrapper-validation-action@v1.0.4
+      - uses: gradle/gradle-build-action@v3
         with:
-          path: ~/.konan
-          key: ${{ runner.os }}-gradle-${{ hashFiles('*.gradle.kts') }}
-          restore-keys: |
-            ${{ runner.os }}-gradle-
-      - uses: gradle/gradle-build-action@v2.4.2
-        with:
-          arguments: dokkaHtmlMultiModule --no-parallel
-      - uses: JamesIves/github-pages-deploy-action@v4.3.0
+          arguments: dokkaGenerate --no-parallel
+      - uses: JamesIves/github-pages-deploy-action@v4
         with:
           branch: gh-pages
-          folder: build/dokka/htmlMultiModule
+          folder: build/dokka/html

.github/workflows/publish.yml

@@ -1,50 +0,0 @@
-name: Gradle publish
-
-on:
-  workflow_dispatch:
-  release:
-    types: [ created ]
-
-jobs:
-  publish:
-    environment:
-      name: publish
-    strategy:
-      matrix:
-        os: [ macOS-latest, windows-latest ]
-    runs-on: ${{matrix.os}}
-    steps:
-      - uses: actions/checkout@v3.0.0
-      - uses: actions/setup-java@v3.10.0
-        with:
-          java-version: 11
-          distribution: liberica
-      - name: Cache konan
-        uses: actions/cache@v3.0.1
-        with:
-          path: ~/.konan
-          key: ${{ runner.os }}-gradle-${{ hashFiles('*.gradle.kts') }}
-          restore-keys: |
-            ${{ runner.os }}-gradle-
-      - name: Publish Windows Artifacts
-        if: matrix.os == 'windows-latest'
-        uses: gradle/gradle-build-action@v2.4.2
-        with:
-          arguments: |
-            publishAllPublicationsToSpaceRepository
-            -Ppublishing.targets=all
-            -Ppublishing.space.user=${{ secrets.SPACE_APP_ID }}
-            -Ppublishing.space.token=${{ secrets.SPACE_APP_SECRET }}
-      - name: Publish Mac Artifacts
-        if: matrix.os == 'macOS-latest'
-        uses: gradle/gradle-build-action@v2.4.2
-        with:
-          arguments: |
-            publishMacosX64PublicationToSpaceRepository
-            publishMacosArm64PublicationToSpaceRepository
-            publishIosX64PublicationToSpaceRepository
-            publishIosArm64PublicationToSpaceRepository
-            publishIosSimulatorArm64PublicationToSpaceRepository
-            -Ppublishing.targets=all
-            -Ppublishing.space.user=${{ secrets.SPACE_APP_ID }}
-            -Ppublishing.space.token=${{ secrets.SPACE_APP_SECRET }}

.space.kts

@@ -1,48 +0,0 @@
-import kotlin.io.path.readText
-
-val projectName = "kmath"
-
-job("Build") {
-    //Perform only jvm tests
-    gradlew("spc.registry.jetbrains.space/p/sci/containers/kotlin-ci:1.0.3", "test", "jvmTest")
-}
-
-job("Publish") {
-    startOn {
-        gitPush { enabled = false }
-    }
-    container("spc.registry.jetbrains.space/p/sci/containers/kotlin-ci:1.0.3") {
-        env["SPACE_USER"] = "{{ project:space_user }}"
-        env["SPACE_TOKEN"] = "{{ project:space_token }}"
-        kotlinScript { api ->
-
-            val spaceUser = System.getenv("SPACE_USER")
-            val spaceToken = System.getenv("SPACE_TOKEN")
-
-            // write the version to the build directory
-            api.gradlew("version")
-
-            //read the version from build file
-            val version = java.nio.file.Path.of("build/project-version.txt").readText()
-
-            val revisionSuffix = if (version.endsWith("SNAPSHOT")) {
-                "-" + api.gitRevision().take(7)
-            } else {
-                ""
-            }
-
-            api.space().projects.automation.deployments.start(
-                project = api.projectIdentifier(),
-                targetIdentifier = TargetIdentifier.Key(projectName),
-                version = version + revisionSuffix,
-                // automatically update deployment status based on the status of a job
-                syncWithAutomationJob = true
-            )
-            api.gradlew(
-                "publishAllPublicationsToSpaceRepository",
-                "-Ppublishing.space.user=\"$spaceUser\"",
-                "-Ppublishing.space.token=\"$spaceToken\"",
-            )
-        }
-    }
-}

CHANGELOG.md

@@ -14,7 +14,52 @@
 
 ### Security
 
-## 0.4.0-dev-3 - 2024-02-18
+## 0.5.0 - 2026-01-09
+
+### Added
+
+- More statistics functions by @qwazer
+- Fit accessors with Attribute
+
+### Changed
+
+- Flag attributes are replaced with boolean attributes to properly support missing values
+- Upgrade tensorflow version to 1.0.0
+
+### Removed
+
+- Support for ND4J
+
+## 0.4.2 - 2025-01-27
+
+### Added
+
+- Convenient matrix builders for rows, columns, vstacks and hstacks
+- Sparse matrix builder
+
+### Fixed
+
+- Ojalgo conversion bug which made all converted matrices be zero.
+
+## 0.4.1 - 2025-01-12
+
+### Added
+
+- Metropolis-Hastings sampler
+- Ojalgo `LinearSpace` implementation.
+
+### Changed
+
+- attributes-kt moved to a separate project, and the version used is 0.3.0
+- Kotlin 2.1. Now use cross-compilation to deploy macOS targets.
+- Changed `origin` to `cmMatrix` in kmath-commons to avoid property name clash. Expose bidirectional conversion in `CMLinearSpace`
+- (BREAKING CHANGE) Changed implementations in `kmath-ejml` to match CM and ojalgo style. Specifically, provide bidirectional conversion for library types.
+
+### Fixed
+
+- (BREAKING CHANGE) Fix EJML to properly treat vectors as columns
+
+## 0.4.0 - 2024-02-18
 
 ### Added
 
@@ -200,7 +245,7 @@
 - Full autodiff refactoring based on `Symbol`
 - `kmath-prob` renamed to `kmath-stat`
 - Grid generators moved to `kmath-for-real`
-- Use `Point<Double>` instead of specialized type in `kmath-for-real`
+- Use `Point<Float64>` instead of specialized type in `kmath-for-real`
 - Optimized dot product for buffer matrices moved to `kmath-for-real`
 - EjmlMatrix context is an object
 - Matrix LUP `inverse` renamed to `inverseWithLup`

README.md

@@ -2,14 +2,10 @@
 [![DOI](https://zenodo.org/badge/129486382.svg)](https://zenodo.org/badge/latestdoi/129486382)
 ![Gradle build](https://github.com/SciProgCentre/kmath/workflows/Gradle%20build/badge.svg)
 [![Maven Central](https://img.shields.io/maven-central/v/space.kscience/kmath-core.svg?label=Maven%20Central)](https://search.maven.org/search?q=g:%22space.kscience%22)
-[![Space](https://img.shields.io/badge/dynamic/xml?color=orange&label=Space&query=//metadata/versioning/latest&url=https%3A%2F%2Fmaven.pkg.jetbrains.space%2Fmipt-npm%2Fp%2Fsci%2Fmaven%2Fspace%2Fkscience%2Fkmath-core%2Fmaven-metadata.xml)](https://maven.pkg.jetbrains.space/mipt-npm/p/sci/maven/space/kscience/)
 
 # KMath
 
-Could be pronounced as `key-math`. The **K**otlin **Math**ematics library was initially intended as a Kotlin-based
-analog to Python's NumPy library. Later we found that kotlin is much more flexible language and allows superior
-architecture designs. In contrast to `numpy` and `scipy` it is modular and has a lightweight core. The `numpy`-like
-experience could be achieved with [kmath-for-real](/kmath-for-real) extension module.
+Could be pronounced as `key-math`. The **K**otlin **Math**ematics library was initially intended as a Kotlin-based analog to Python's NumPy library. Later we found that kotlin is a much more flexible language and allows superior architecture designs. In contrast to `numpy` and `scipy` it is modular and has a lightweight core. The `numpy`-like experience could be achieved with [kmath-for-real](kmath-for-real) extension module.
 
 [Documentation site](https://SciProgCentre.github.io/kmath/)
 
@@ -35,15 +31,17 @@ experience could be achieved with [kmath-for-real](/kmath-for-real) extension mo
 * Be like NumPy. It was the idea at the beginning, but we decided that we can do better in API.
 * Provide the 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 `kmath-for-real`, which will give better
-  experience for those, who want to work with specific types.
+* Provide specialized behavior in the core. API is made generic on purpose, so one needs to specialize for types, like for `Float64` in the core. For that we will have specialization modules like [kmath-for-real](kmath-for-real), which will give a better experience for those who want to work with specific types.
+
+## Contributing
+
+The project requires a lot of additional work. The most important thing we need is feedback about what features are required the most. Feel free to create feature requests. We are also welcome to code contributions, especially in issues marked with [good first issue](https://github.com/SciProgCentre/kmath/issues?q=is%3Aissue+is%3Aopen+label%3A%22good+first+issue%22) label.
+
+Project roadmap will be available at [GitHub Projects](https://github.com/orgs/SciProgCentre/projects/3).
 
 ## Features and stability
 
-KMath is a modular library. Different modules provide different features with different API stability guarantees. All
-core modules are released with the same version, but with different API change policy. The features are described in
-module definitions below. The module stability could have the following levels:
+KMath is a modular library. Different modules provide different features with different API stability guarantees. All core modules are released with the same version, but with different API change policy. The features are described in module definitions below. The module stability could have the following levels:
 
 * **PROTOTYPE**. On this level there are no compatibility guarantees. All methods and classes form those modules could
   break any moment. You can still use it, but be sure to fix the specific version.
@@ -51,25 +49,16 @@ module definitions below. The module stability could have the following levels:
   with `@UnstableKMathAPI` or other stability warning annotations.
 * **DEVELOPMENT**. API breaking generally follows semantic versioning ideology. There could be changes in minor
   versions, but not in patch versions. API is protected
-  with [binary-compatibility-validator](https://github.com/Kotlin/binary-compatibility-validator) tool.
+  with [binary-compatibility-validator](https://kotlinlang.org/docs/gradle-binary-compatibility-validation.html) tool.
 * **STABLE**. The API stabilized. Breaking changes are allowed only in major releases.
 
 ## Modules
 
 
-### [attributes-kt](attributes-kt)
-> An API and basic implementation for arranging objects in a continuous memory block.
->
-> **Maturity**: DEVELOPMENT
-
 ### [benchmarks](benchmarks)
 >
 > **Maturity**: EXPERIMENTAL
 
-### [examples](examples)
->
-> **Maturity**: EXPERIMENTAL
-
 ### [kmath-ast](kmath-ast)
 >
 > **Maturity**: EXPERIMENTAL
@@ -104,11 +93,9 @@ module definitions below. The module stability could have the following levels:
 > **Features:**
 > - [algebras](kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/Algebra.kt) : Algebraic structures like rings, spaces and fields.
 > - [nd](kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/StructureND.kt) : Many-dimensional structures and operations on them.
-> - [linear](kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/Algebra.kt) : Basic linear algebra operations (sums, products, etc.), backed by the `Space` API. Advanced linear algebra operations like matrix inversion and LU decomposition.
+> - [linear](kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/Algebra.kt) : Basic linear algebra operations (sums, products, etc.), backed by the `Space` API. 
 > - [buffers](kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/Buffers.kt) : One-dimensional structure
-> - [expressions](kmath-core/src/commonMain/kotlin/space/kscience/kmath/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.
+> - [expressions](kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions) : By writing a single mathematical expression once, users will be able to apply different types of
 > - [domains](kmath-core/src/commonMain/kotlin/space/kscience/kmath/domains) : Domains
 > - [autodiff](kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/SimpleAutoDiff.kt) : Automatic differentiation
 > - [Parallel linear algebra](kmath-core/#) : Parallel implementation for `LinearAlgebra`
@@ -167,15 +154,6 @@ One can still use generic algebras though.
 >
 > **Maturity**: PROTOTYPE
 
-### [kmath-jafama](kmath-jafama)
-> Jafama integration module
->
-> **Maturity**: DEPRECATED
->
-> **Features:**
-> - [jafama-double](kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/) : Double ExtendedField implementations based on Jafama
-
-
 ### [kmath-jupyter](kmath-jupyter)
 >
 > **Maturity**: PROTOTYPE
@@ -200,16 +178,10 @@ One can still use generic algebras though.
 >
 > **Maturity**: PROTOTYPE
 
-### [kmath-nd4j](kmath-nd4j)
-> ND4J NDStructure implementation and according NDAlgebra classes
+### [kmath-ojalgo](kmath-ojalgo)
+> Ojalgo bindings for kmath
 >
-> **Maturity**: DEPRECATED
->
-> **Features:**
-> - [nd4jarraystructure](kmath-nd4j/#) : NDStructure wrapper for INDArray
-> - [nd4jarrayrings](kmath-nd4j/#) : Rings over Nd4jArrayStructure of Int and Long
-> - [nd4jarrayfields](kmath-nd4j/#) : Fields over Nd4jArrayStructure of Float and Double
-
+> **Maturity**: PROTOTYPE
 
 ### [kmath-optimization](kmath-optimization)
 >
@@ -251,34 +223,21 @@ One can still use generic algebras though.
 
 ## Multi-platform support
 
-KMath is developed as a multi-platform library, which means that most of the interfaces are declared in the
-[common source sets](/kmath-core/src/commonMain) and implemented there wherever it is possible. In some cases, features
-are delegated to platform-specific implementations even if they could be provided in the common module for performance
-reasons. Currently, Kotlin/JVM is the primary platform, however, Kotlin/Native and Kotlin/JS contributions and
-feedback are also welcome.
+KMath is developed as a multi-platform library, which means that most of the interfaces are declared in common source sets like [common source sets](kmath-core/src/commonMain) and implemented there wherever it is possible. In some cases, features are delegated to platform-specific implementations even if they could be provided in the common module for performance reasons. Currently, Kotlin/JVM is the primary platform, however, Kotlin/Native, Kotlin/JS and Kotlin/Wasm contributions and feedback are also welcome.
 
 ## Performance
 
-Calculation of performance is one of the major goals of KMath in the future, but in some cases it is impossible to
-achieve both
-performance and flexibility.
+Performance of mathematical operations is hard to achieve without a lot of effort. KMath focus is to provide a reasonable performance for common cases, out of the box and good interoperability with optimized libraries for edge cases. For example, one could prototype an algorithm using KMath core implementations and then use Multik or Ojalgo for performance-critical parts just by adding a dependency and algebra context switch.
 
-We expect to focus on creating a 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.
+As for core implementations, we expect to focus on creating a 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.
 
 ## Requirements
 
-KMath currently relies on JDK 11 for compilation and execution of Kotlin-JVM part. We recommend using GraalVM-CE or
-Oracle GraalVM for execution to get better performance.
+KMath currently relies on JDK 21 for compilation and execution of Kotlin-JVM part. 
 
 ### Repositories
 
-Release and development artifacts are accessible from mipt-npm [Space](https://www.jetbrains.com/space/)
-repository `https://maven.pkg.jetbrains.space/mipt-npm/p/sci/maven` (see documentation of
-[Kotlin Multiplatform](https://kotlinlang.org/docs/reference/multiplatform.html) for more details). The repository could
-be reached through [repo.kotlin.link](https://repo.kotlin.link) proxy:
+Intermediate releases are published to [Kotlin.Link](https://repo.kotlin.link) repository.
 
 ```kotlin
 repositories {
@@ -290,11 +249,3 @@ dependencies {
     // api("space.kscience:kmath-core-jvm:$version") for jvm-specific version
 }
 ```
-
-## Contributing
-
-The project requires a lot of additional work. The most important thing we need is feedback about what features are
-required the most. Feel free to create feature requests. We are also welcome to code contributions, especially in issues
-marked
-with [good first issue](hhttps://github.com/SciProgCentre/kmath/issues?q=is%3Aissue+is%3Aopen+label%3A%22good+first+issue%22)
-label.

attributes-kt/README.md

@@ -1,21 +0,0 @@
-# Module attributes-kt
-
-
-
-## Usage
-
-## Artifact:
-
-The Maven coordinates of this project are `space.kscience:attributes-kt:0.1.0`.
-
-**Gradle Kotlin DSL:**
-```kotlin
-repositories {
-    maven("https://repo.kotlin.link")
-    mavenCentral()
-}
-
-dependencies {
-    implementation("space.kscience:attributes-kt:0.1.0")
-}
-```

attributes-kt/api/attributes-kt.api

@@ -1,104 +0,0 @@
-public abstract interface class space/kscience/attributes/Attribute {
-}
-
-public abstract interface class space/kscience/attributes/AttributeContainer {
-	public abstract fun getAttributes ()Lspace/kscience/attributes/Attributes;
-}
-
-public abstract interface class space/kscience/attributes/AttributeScope {
-}
-
-public abstract interface class space/kscience/attributes/AttributeWithDefault : space/kscience/attributes/Attribute {
-	public abstract fun getDefault ()Ljava/lang/Object;
-}
-
-public abstract interface class space/kscience/attributes/Attributes {
-	public static final field Companion Lspace/kscience/attributes/Attributes$Companion;
-	public abstract fun equals (Ljava/lang/Object;)Z
-	public fun get (Lspace/kscience/attributes/Attribute;)Ljava/lang/Object;
-	public abstract fun getContent ()Ljava/util/Map;
-	public fun getKeys ()Ljava/util/Set;
-	public abstract fun hashCode ()I
-	public abstract fun toString ()Ljava/lang/String;
-}
-
-public final class space/kscience/attributes/Attributes$Companion {
-	public final fun equals (Lspace/kscience/attributes/Attributes;Lspace/kscience/attributes/Attributes;)Z
-	public final fun getEMPTY ()Lspace/kscience/attributes/Attributes;
-}
-
-public final class space/kscience/attributes/AttributesBuilder : space/kscience/attributes/Attributes {
-	public final fun add (Lspace/kscience/attributes/SetAttribute;Ljava/lang/Object;)V
-	public final fun build ()Lspace/kscience/attributes/Attributes;
-	public fun equals (Ljava/lang/Object;)Z
-	public fun getContent ()Ljava/util/Map;
-	public fun hashCode ()I
-	public final fun invoke (Lspace/kscience/attributes/Attribute;Ljava/lang/Object;)V
-	public final fun put (Lspace/kscience/attributes/Attribute;Ljava/lang/Object;)V
-	public final fun putAll (Lspace/kscience/attributes/Attributes;)V
-	public final fun remove (Lspace/kscience/attributes/SetAttribute;Ljava/lang/Object;)V
-	public final fun set (Lspace/kscience/attributes/Attribute;Ljava/lang/Object;)V
-	public fun toString ()Ljava/lang/String;
-}
-
-public final class space/kscience/attributes/AttributesBuilderKt {
-	public static final fun Attributes (Lkotlin/jvm/functions/Function1;)Lspace/kscience/attributes/Attributes;
-}
-
-public final class space/kscience/attributes/AttributesKt {
-	public static final fun Attributes (Lspace/kscience/attributes/Attribute;)Lspace/kscience/attributes/Attributes;
-	public static final fun Attributes (Lspace/kscience/attributes/Attribute;Ljava/lang/Object;)Lspace/kscience/attributes/Attributes;
-	public static final fun getOrDefault (Lspace/kscience/attributes/Attributes;Lspace/kscience/attributes/AttributeWithDefault;)Ljava/lang/Object;
-	public static final fun isEmpty (Lspace/kscience/attributes/Attributes;)Z
-	public static final fun modified (Lspace/kscience/attributes/Attributes;Lkotlin/jvm/functions/Function1;)Lspace/kscience/attributes/Attributes;
-	public static final fun plus (Lspace/kscience/attributes/Attributes;Lspace/kscience/attributes/Attributes;)Lspace/kscience/attributes/Attributes;
-	public static final fun withAttribute (Lspace/kscience/attributes/Attributes;Lspace/kscience/attributes/Attribute;)Lspace/kscience/attributes/Attributes;
-	public static final fun withAttribute (Lspace/kscience/attributes/Attributes;Lspace/kscience/attributes/Attribute;Ljava/lang/Object;)Lspace/kscience/attributes/Attributes;
-	public static final fun withAttributeElement (Lspace/kscience/attributes/Attributes;Lspace/kscience/attributes/SetAttribute;Ljava/lang/Object;)Lspace/kscience/attributes/Attributes;
-	public static final fun withoutAttribute (Lspace/kscience/attributes/Attributes;Lspace/kscience/attributes/Attribute;)Lspace/kscience/attributes/Attributes;
-	public static final fun withoutAttributeElement (Lspace/kscience/attributes/Attributes;Lspace/kscience/attributes/SetAttribute;Ljava/lang/Object;)Lspace/kscience/attributes/Attributes;
-}
-
-public abstract interface class space/kscience/attributes/FlagAttribute : space/kscience/attributes/Attribute {
-}
-
-public abstract class space/kscience/attributes/PolymorphicAttribute : space/kscience/attributes/Attribute {
-	public synthetic fun <init> (Lkotlin/reflect/KType;Lkotlin/jvm/internal/DefaultConstructorMarker;)V
-	public fun equals (Ljava/lang/Object;)Z
-	public final fun getType-V0oMfBY ()Lkotlin/reflect/KType;
-	public fun hashCode ()I
-}
-
-public final class space/kscience/attributes/PolymorphicAttributeKt {
-	public static final fun get (Lspace/kscience/attributes/Attributes;Lkotlin/jvm/functions/Function0;)Ljava/lang/Object;
-	public static final fun set (Lspace/kscience/attributes/AttributesBuilder;Lkotlin/jvm/functions/Function0;Ljava/lang/Object;)V
-}
-
-public final class space/kscience/attributes/SafeType {
-	public static final synthetic fun box-impl (Lkotlin/reflect/KType;)Lspace/kscience/attributes/SafeType;
-	public static fun constructor-impl (Lkotlin/reflect/KType;)Lkotlin/reflect/KType;
-	public fun equals (Ljava/lang/Object;)Z
-	public static fun equals-impl (Lkotlin/reflect/KType;Ljava/lang/Object;)Z
-	public static final fun equals-impl0 (Lkotlin/reflect/KType;Lkotlin/reflect/KType;)Z
-	public final fun getKType ()Lkotlin/reflect/KType;
-	public fun hashCode ()I
-	public static fun hashCode-impl (Lkotlin/reflect/KType;)I
-	public fun toString ()Ljava/lang/String;
-	public static fun toString-impl (Lkotlin/reflect/KType;)Ljava/lang/String;
-	public final synthetic fun unbox-impl ()Lkotlin/reflect/KType;
-}
-
-public final class space/kscience/attributes/SafeTypeKt {
-	public static final fun getKClass-X0YbwmU (Lkotlin/reflect/KType;)Lkotlin/reflect/KClass;
-}
-
-public abstract interface class space/kscience/attributes/SetAttribute : space/kscience/attributes/Attribute {
-}
-
-public abstract interface annotation class space/kscience/attributes/UnstableAttributesAPI : java/lang/annotation/Annotation {
-}
-
-public abstract interface class space/kscience/attributes/WithType {
-	public abstract fun getType-V0oMfBY ()Lkotlin/reflect/KType;
-}
-

attributes-kt/build.gradle.kts

@@ -1,20 +0,0 @@
-plugins {
-    id("space.kscience.gradle.mpp")
-    `maven-publish`
-}
-
-version = rootProject.extra.get("attributesVersion").toString()
-
-kscience {
-    jvm()
-    js()
-    native()
-    wasm()
-}
-
-readme {
-    maturity = space.kscience.gradle.Maturity.DEVELOPMENT
-    description = """
-        An API and basic implementation for arranging objects in a continuous memory block.
-    """.trimIndent()
-}

attributes-kt/src/commonMain/kotlin/space/kscience/attributes/Attribute.kt

@@ -1,29 +0,0 @@
-/*
- * Copyright 2018-2023 KMath contributors.
- * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
- */
-
-package space.kscience.attributes
-
-/**
- * A marker interface for an attribute. Attributes are used as keys to access contents of type [T] in the container.
- */
-public interface Attribute<T>
-
-/**
- * An attribute that could be either present or absent
- */
-public interface FlagAttribute : Attribute<Unit>
-
-/**
- * An attribute with a default value
- */
-public interface AttributeWithDefault<T> : Attribute<T> {
-    public val default: T
-}
-
-/**
- * Attribute containing a set of values
- */
-public interface SetAttribute<V> : Attribute<Set<V>>
-

attributes-kt/src/commonMain/kotlin/space/kscience/attributes/AttributeContainer.kt

@@ -1,20 +0,0 @@
-/*
- * Copyright 2018-2023 KMath contributors.
- * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
- */
-
-package space.kscience.attributes
-
-/**
- * A container for [Attributes]
- */
-public interface AttributeContainer {
-    public val attributes: Attributes
-}
-
-/**
- * A scope, where attribute keys could be resolved.
- * [O] is used only to resolve types in compile-time.
- */
-public interface AttributeScope<O>
-

attributes-kt/src/commonMain/kotlin/space/kscience/attributes/Attributes.kt

@@ -1,143 +0,0 @@
-/*
- * Copyright 2018-2023 KMath contributors.
- * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
- */
-
-package space.kscience.attributes
-
-/**
- * A set of attributes. The implementation must guarantee that [content] keys correspond to their value types.
- */
-public interface Attributes {
-    /**
-     * Raw content for this [Attributes]
-     */
-    public val content: Map<out Attribute<*>, Any?>
-
-    /**
-     * Attribute keys contained in this [Attributes]
-     */
-    public val keys: Set<Attribute<*>> get() = content.keys
-
-    /**
-     * Provide an attribute value. Return null if attribute is not present or if its value is null.
-     */
-    @Suppress("UNCHECKED_CAST")
-    public operator fun <T> get(attribute: Attribute<T>): T? = content[attribute] as? T
-
-    override fun toString(): String
-    override fun equals(other: Any?): Boolean
-    override fun hashCode(): Int
-
-    public companion object {
-        public val EMPTY: Attributes = object : Attributes {
-            override val content: Map<out Attribute<*>, Any?> get() = emptyMap()
-
-            override fun toString(): String = "Attributes.EMPTY"
-
-            override fun equals(other: Any?): Boolean = (other as? Attributes)?.isEmpty() ?: false
-
-            override fun hashCode(): Int = Unit.hashCode()
-        }
-
-        public fun equals(a1: Attributes, a2: Attributes): Boolean =
-            a1.keys == a2.keys && a1.keys.all { a1[it] == a2[it] }
-    }
-}
-
-internal class MapAttributes(override val content: Map<out Attribute<*>, Any?>) : Attributes {
-    override fun toString(): String = "Attributes(value=${content.entries})"
-    override fun equals(other: Any?): Boolean = other is Attributes && Attributes.equals(this, other)
-    override fun hashCode(): Int = content.hashCode()
-}
-
-public fun Attributes.isEmpty(): Boolean = keys.isEmpty()
-
-/**
- * Get attribute value or default
- */
-public fun <T> Attributes.getOrDefault(attribute: AttributeWithDefault<T>): T = get(attribute) ?: attribute.default
-
-/**
- * Check if there is an attribute that matches given key by type and adheres to [predicate].
- */
-@Suppress("UNCHECKED_CAST")
-public inline fun <T, reified A : Attribute<T>> Attributes.hasAny(predicate: (value: T) -> Boolean): Boolean =
-    content.any { (mapKey, mapValue) -> mapKey is A && predicate(mapValue as T) }
-
-/**
- * Check if there is an attribute of given type (subtypes included)
- */
-public inline fun <reified A : Attribute<*>> Attributes.hasAny(): Boolean =
-    content.any { (mapKey, _) -> mapKey is A }
-
-/**
- * Check if [Attributes] contains a flag. Multiple keys that are instances of a flag could be present
- */
-public inline fun <reified A : FlagAttribute> Attributes.hasFlag(): Boolean =
-    content.keys.any { it is A }
-
-/**
- * Create [Attributes] with an added or replaced attribute key.
- */
-public fun <T, A : Attribute<T>> Attributes.withAttribute(
-    attribute: A,
-    attrValue: T,
-): Attributes = MapAttributes(content + (attribute to attrValue))
-
-public fun <A : Attribute<Unit>> Attributes.withAttribute(attribute: A): Attributes =
-    withAttribute(attribute, Unit)
-
-/**
- * Create a new [Attributes] by modifying the current one
- */
-public fun <O> Attributes.modified(block: AttributesBuilder<O>.() -> Unit): Attributes = Attributes<O> {
-    putAll(this@modified)
-    block()
-}
-
-/**
- * Create new [Attributes] by removing [attribute] key
- */
-public fun Attributes.withoutAttribute(attribute: Attribute<*>): Attributes = MapAttributes(content.minus(attribute))
-
-/**
- * Add an element to a [SetAttribute]
- */
-public fun <T, A : SetAttribute<T>> Attributes.withAttributeElement(
-    attribute: A,
-    attrValue: T,
-): Attributes {
-    val currentSet: Set<T> = get(attribute) ?: emptySet()
-    return MapAttributes(
-        content + (attribute to (currentSet + attrValue))
-    )
-}
-
-/**
- * Remove an element from [SetAttribute]
- */
-public fun <T, A : SetAttribute<T>> Attributes.withoutAttributeElement(
-    attribute: A,
-    attrValue: T,
-): Attributes {
-    val currentSet: Set<T> = get(attribute) ?: emptySet()
-    return MapAttributes(content + (attribute to (currentSet - attrValue)))
-}
-
-/**
- * Create [Attributes] with a single key
- */
-public fun <T, A : Attribute<T>> Attributes(
-    attribute: A,
-    attrValue: T,
-): Attributes = MapAttributes(mapOf(attribute to attrValue))
-
-/**
- * Create Attributes with a single [Unit] valued attribute
- */
-public fun <A : Attribute<Unit>> Attributes(
-    attribute: A,
-): Attributes = MapAttributes(mapOf(attribute to Unit))
-
-public operator fun Attributes.plus(other: Attributes): Attributes = MapAttributes(content + other.content)

attributes-kt/src/commonMain/kotlin/space/kscience/attributes/AttributesBuilder.kt

@@ -1,68 +0,0 @@
-/*
- * Copyright 2018-2023 KMath contributors.
- * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
- */
-
-package space.kscience.attributes
-
-/**
- * A builder for [Attributes].
- * The builder is not thread safe
- *
- * @param O type marker of an owner object, for which these attributes are made
- */
-public class AttributesBuilder<out O> internal constructor() : Attributes {
-
-    private val map = mutableMapOf<Attribute<*>, Any?>()
-
-    override fun toString(): String = "Attributes(value=${map.entries})"
-    override fun equals(other: Any?): Boolean = other is Attributes && Attributes.equals(this, other)
-    override fun hashCode(): Int = map.hashCode()
-
-    override val content: Map<out Attribute<*>, Any?> get() = map
-
-    public operator fun <T> set(attribute: Attribute<T>, value: T?) {
-        if (value == null) {
-            map.remove(attribute)
-        } else {
-            map[attribute] = value
-        }
-    }
-
-    public operator fun <V> Attribute<V>.invoke(value: V?) {
-        set(this, value)
-    }
-
-    public infix fun <V> Attribute<V>.put(value: V?) {
-        set(this, value)
-    }
-
-    /**
-     * Put all attributes for given [attributes]
-     */
-    public fun putAll(attributes: Attributes) {
-        map.putAll(attributes.content)
-    }
-
-    public infix fun <V> SetAttribute<V>.add(attrValue: V) {
-        val currentSet: Set<V> = get(this) ?: emptySet()
-        map[this] = currentSet + attrValue
-    }
-
-    /**
-     * Remove an element from [SetAttribute]
-     */
-    public infix fun <V> SetAttribute<V>.remove(attrValue: V) {
-        val currentSet: Set<V> = get(this) ?: emptySet()
-        map[this] = currentSet - attrValue
-    }
-
-    public fun build(): Attributes = MapAttributes(map)
-}
-
-/**
- * Create [Attributes] with a given [builder]
- * @param O the type for which attributes are built. The type is used only during compilation phase for static extension dispatch
- */
-public fun <O> Attributes(builder: AttributesBuilder<O>.() -> Unit): Attributes =
-    AttributesBuilder<O>().apply(builder).build()

attributes-kt/src/commonMain/kotlin/space/kscience/attributes/PolymorphicAttribute.kt

@@ -1,34 +0,0 @@
-/*
- * Copyright 2018-2023 KMath contributors.
- * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
- */
-
-package space.kscience.attributes
-
-/**
- * An attribute that has a type parameter for value
- * @param type parameter-type
- */
-public abstract class PolymorphicAttribute<T>(public val type: SafeType<T>) : Attribute<T> {
-    override fun equals(other: Any?): Boolean = other != null &&
-            (this::class == other::class) &&
-            (other as? PolymorphicAttribute<*>)?.type == this.type
-
-    override fun hashCode(): Int = this::class.hashCode() + type.hashCode()
-}
-
-
-/**
- * Get a polymorphic attribute using attribute factory
- */
-@UnstableAttributesAPI
-public operator fun <T> Attributes.get(attributeKeyBuilder: () -> PolymorphicAttribute<T>): T? =
-    get(attributeKeyBuilder())
-
-/**
- * Set a polymorphic attribute using its factory
- */
-@UnstableAttributesAPI
-public operator fun <O, T> AttributesBuilder<O>.set(attributeKeyBuilder: () -> PolymorphicAttribute<T>, value: T) {
-    set(attributeKeyBuilder(), value)
-}

attributes-kt/src/commonMain/kotlin/space/kscience/attributes/SafeType.kt

@@ -1,35 +0,0 @@
-/*
- * Copyright 2018-2023 KMath contributors.
- * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
- */
-
-package space.kscience.attributes
-
-import kotlin.jvm.JvmInline
-import kotlin.reflect.KClass
-import kotlin.reflect.KType
-import kotlin.reflect.typeOf
-
-/**
- * Safe variant ok Kotlin [KType] that ensures that the type parameter is of the same type as [kType]
- *
- * @param kType raw [KType]
- */
-@JvmInline
-public value class SafeType<out T> @PublishedApi internal constructor(public val kType: KType)
-
-public inline fun <reified T> safeTypeOf(): SafeType<T> = SafeType(typeOf<T>())
-
-/**
- * Derive Kotlin [KClass] from this type and fail if the type is not a class (should not happen)
- */
-@Suppress("UNCHECKED_CAST")
-@UnstableAttributesAPI
-public val <T> SafeType<T>.kClass: KClass<T & Any> get() = kType.classifier as KClass<T & Any>
-
-/**
- * An interface containing [type] for dynamic type checking.
- */
-public interface WithType<out T> {
-    public val type: SafeType<T>
-}

attributes-kt/src/commonMain/kotlin/space/kscience/attributes/annotations.kt

@@ -1,17 +0,0 @@
-/*
- * Copyright 2018-2023 KMath contributors.
- * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
- */
-
-package space.kscience.attributes
-
-/**
- * Marks declarations that are still experimental in the Attributes-kt APIs, which means that the design of the corresponding
- * declarations has open issues that may (or may not) lead to their changes in the future. Roughly speaking, there is
- * a chance of those declarations will be deprecated in the future or the semantics of their behavior may change
- * in some way that may break some code.
- */
-@MustBeDocumented
-@Retention(value = AnnotationRetention.BINARY)
-@RequiresOptIn("This API is unstable and could change in future", RequiresOptIn.Level.WARNING)
-public annotation class UnstableAttributesAPI

benchmarks/README.md

@@ -1,4 +1,122 @@
-# Module benchmarks
+# Module KMath-Benchmarks
+
+# BenchmarksResult
+
+## Report for benchmark configuration <code>main</code>
+
+* Run on OpenJDK 64-Bit Server VM (build 21.0.9+10-LTS) with Java process:
+
+```
+C:\Users\altavir\.gradle\jdks\eclipse_adoptium-21-amd64-windows.2\bin\java.exe -Dfile.encoding=UTF-8 -Duser.country=US -Duser.language=en -Duser.variant
+```
+* JMH 1.37 was used in `thrpt` mode with 5 warmup iterations by 10 s and 5 measurement iterations by 10 s.
+### [ArrayBenchmark](src/jvmMain/kotlin/space/kscience/kmath/benchmarks/ArrayBenchmark.kt)
+
+| Benchmark | Score |
+|:---------:|:-----:|
+|`benchmarkArrayRead`|3.9E+06 &plusmn; 1.1E+06 ops/s|
+|`benchmarkBufferRead`|4.0E+06 &plusmn; 2.2E+05 ops/s|
+|`nativeBufferRead`|4.0E+06 &plusmn; 1.7E+05 ops/s|
+### [BigIntBenchmark](src/jvmMain/kotlin/space/kscience/kmath/benchmarks/BigIntBenchmark.kt)
+
+| Benchmark | Score |
+|:---------:|:-----:|
+|`jvmAdd`|2.9E+07 &plusmn; 2.8E+06 ops/s|
+|`jvmAddLarge`|3.8E+04 &plusmn; 6.4E+03 ops/s|
+|`jvmMultiply`|5.3E+07 &plusmn; 6.1E+06 ops/s|
+|`jvmMultiplyLarge`|2.2E+02 &plusmn; 1.9 ops/s|
+|`jvmParsing10`|3.9E+06 &plusmn; 4.7E+05 ops/s|
+|`jvmParsing16`|3.1E+06 &plusmn; 4.6E+05 ops/s|
+|`jvmPower`|24 &plusmn; 1.7 ops/s|
+|`jvmSmallAdd`|4.7E+07 &plusmn; 4.6E+06 ops/s|
+|`kmAdd`|2.3E+07 &plusmn; 5.1E+06 ops/s|
+|`kmAddLarge`|2.6E+04 &plusmn; 3.0E+02 ops/s|
+|`kmMultiply`|3.7E+07 &plusmn; 2.9E+06 ops/s|
+|`kmMultiplyLarge`|34 &plusmn; 2.8 ops/s|
+|`kmParsing10`|2.5E+06 &plusmn; 1.5E+05 ops/s|
+|`kmParsing16`|4.0E+06 &plusmn; 2.4E+05 ops/s|
+|`kmPower`|6.5 &plusmn; 0.69 ops/s|
+|`kmSmallAdd`|1.6E+07 &plusmn; 8.0E+05 ops/s|
+### [BufferBenchmark](src/jvmMain/kotlin/space/kscience/kmath/benchmarks/BufferBenchmark.kt)
+
+| Benchmark | Score |
+|:---------:|:-----:|
+|`bufferViewReadWrite`|5.4E+06 &plusmn; 3.8E+05 ops/s|
+|`bufferViewReadWriteSpecialized`|5.0E+06 &plusmn; 1.2E+06 ops/s|
+|`complexBufferReadWrite`|2.2E+06 &plusmn; 5.7E+04 ops/s|
+|`doubleArrayReadWrite`|6.9E+06 &plusmn; 1.2E+06 ops/s|
+|`doubleBufferReadWrite`|6.6E+06 &plusmn; 1.1E+06 ops/s|
+### [DotBenchmark](src/jvmMain/kotlin/space/kscience/kmath/benchmarks/DotBenchmark.kt)
+
+| Benchmark | Score |
+|:---------:|:-----:|
+|`bufferedDot`|1.2 &plusmn; 0.20 ops/s|
+|`cmDot`|0.36 &plusmn; 0.14 ops/s|
+|`cmDotWithConversion`|0.80 &plusmn; 0.092 ops/s|
+|`ejmlDot`|2.9 &plusmn; 0.61 ops/s|
+|`ejmlDotWithConversion`|2.7 &plusmn; 0.15 ops/s|
+|`multikDot`|23 &plusmn; 2.4 ops/s|
+|`ojalgoDot`|11 &plusmn; 0.79 ops/s|
+|`parallelDot`|9.4 &plusmn; 1.3 ops/s|
+|`tensorDot`|1.0 &plusmn; 0.15 ops/s|
+|`tfDot`|3.9 &plusmn; 0.90 ops/s|
+### [ExpressionsInterpretersBenchmark](src/jvmMain/kotlin/space/kscience/kmath/benchmarks/ExpressionsInterpretersBenchmark.kt)
+
+| Benchmark | Score |
+|:---------:|:-----:|
+|`asmGenericExpression`|15 &plusmn; 1.8 ops/s|
+|`asmPrimitiveExpression`|27 &plusmn; 0.98 ops/s|
+|`asmPrimitiveExpressionArray`|78 &plusmn; 14 ops/s|
+|`functionalExpression`|4.4 &plusmn; 0.25 ops/s|
+|`justCalculate`|79 &plusmn; 5.4 ops/s|
+|`mstExpression`|4.2 &plusmn; 0.93 ops/s|
+|`rawExpression`|25 &plusmn; 5.0 ops/s|
+### [IntegrationBenchmark](src/jvmMain/kotlin/space/kscience/kmath/benchmarks/IntegrationBenchmark.kt)
+
+| Benchmark | Score |
+|:---------:|:-----:|
+|`complexIntegration`|2.2E+03 &plusmn; 3.0E+02 ops/s|
+|`doubleIntegration`|2.3E+03 &plusmn; 6.4E+02 ops/s|
+### [MatrixInverseBenchmark](src/jvmMain/kotlin/space/kscience/kmath/benchmarks/MatrixInverseBenchmark.kt)
+
+| Benchmark | Score |
+|:---------:|:-----:|
+|`cmLUPInversion`|2.0E+03 &plusmn; 1.1E+02 ops/s|
+|`ejmlInverse`|1.2E+03 &plusmn; 29 ops/s|
+|`kmathLupInversion`|3.9E+02 &plusmn; 92 ops/s|
+|`kmathParallelLupInversion`|55 &plusmn; 5.0 ops/s|
+|`ojalgoInverse`|1.7E+03 &plusmn; 35 ops/s|
+### [MinStatisticBenchmark](src/jvmMain/kotlin/space/kscience/kmath/benchmarks/MinStatisticBenchmark.kt)
+
+| Benchmark | Score |
+|:---------:|:-----:|
+|`kotlinArrayMin`|1.6E+03 &plusmn; 3.0E+02 ops/s|
+|`minBlocking`|1.2E+03 &plusmn; 1.2E+02 ops/s|
+### [NDFieldBenchmark](src/jvmMain/kotlin/space/kscience/kmath/benchmarks/NDFieldBenchmark.kt)
+
+| Benchmark | Score |
+|:---------:|:-----:|
+|`boxingFieldAdd`|1.9 &plusmn; 0.089 ops/s|
+|`multikAdd`|6.8 &plusmn; 1.0 ops/s|
+|`multikInPlaceAdd`|32 &plusmn; 4.7 ops/s|
+|`specializedFieldAdd`|6.7 &plusmn; 0.98 ops/s|
+|`tensorAdd`|7.9 &plusmn; 1.1 ops/s|
+|`tensorInPlaceAdd`|11 &plusmn; 3.4 ops/s|
+|`viktorAdd`|6.4 &plusmn; 0.41 ops/s|
+### [ViktorBenchmark](src/jvmMain/kotlin/space/kscience/kmath/benchmarks/ViktorBenchmark.kt)
+
+| Benchmark | Score |
+|:---------:|:-----:|
+|`doubleFieldAddition`|7.3 &plusmn; 1.1 ops/s|
+|`rawViktor`|6.0 &plusmn; 0.88 ops/s|
+|`viktorFieldAddition`|6.7 &plusmn; 0.47 ops/s|
+### [ViktorLogBenchmark](src/jvmMain/kotlin/space/kscience/kmath/benchmarks/ViktorLogBenchmark.kt)
+
+| Benchmark | Score |
+|:---------:|:-----:|
+|`rawViktorLog`|1.3 &plusmn; 0.40 ops/s|
+|`realFieldLog`|1.2 &plusmn; 0.34 ops/s|
+|`viktorFieldLog`|1.3 &plusmn; 0.0073 ops/s|
 
 
 

benchmarks/build.gradle.kts

@@ -1,30 +1,76 @@
-@file:Suppress("UNUSED_VARIABLE")
 
-import org.jetbrains.kotlin.gradle.tasks.KotlinJvmCompile
-import space.kscience.kmath.benchmarks.addBenchmarkProperties
+
+import com.fasterxml.jackson.module.kotlin.jacksonObjectMapper
+import com.fasterxml.jackson.module.kotlin.readValue
+import kotlinx.benchmark.gradle.BenchmarksExtension
+import java.util.*
 
 plugins {
-    kotlin("multiplatform")
+    id("space.kscience.gradle.mpp")
     alias(spclibs.plugins.kotlin.plugin.allopen)
-    id("org.jetbrains.kotlinx.benchmark")
+    alias(spclibs.plugins.kotlinx.benchmark)
 }
 
 allOpen.annotation("org.openjdk.jmh.annotations.State")
-sourceSets.register("benchmarks")
+//sourceSets.register("benchmarks")
 
 repositories {
     mavenCentral()
 }
 
-val multikVersion: String by rootProject.extra
+kscience {
+    maturity = space.kscience.gradle.Maturity.EXPERIMENTAL
 
-kotlin {
     jvm()
 
-    js(IR) {
+    js {
         nodejs()
     }
 
+    commonMain{
+        implementation(project(":kmath-ast"))
+        implementation(project(":kmath-core"))
+        implementation(project(":kmath-coroutines"))
+        implementation(project(":kmath-complex"))
+        implementation(project(":kmath-stat"))
+        implementation(project(":kmath-dimensions"))
+        implementation(project(":kmath-for-real"))
+        implementation(project(":kmath-tensors"))
+        implementation(libs.multik.default)
+        implementation(spclibs.kotlinx.benchmark.runtime)
+    }
+
+    jvmMain {
+        implementation(projects.kmathCommons)
+        implementation(projects.kmathEjml)
+        implementation(projects.kmathKotlingrad)
+        implementation(projects.kmathViktor)
+        implementation(projects.kmathOjalgo)
+        implementation(projects.kmath.kmathTensorflow)
+        implementation(projects.kmathMultik)
+        implementation(libs.tensorflow.core.platform)
+//                implementation(projects.kmathNd4j)
+
+//                implementation(libs.nd4j.native.platform)
+        //    uncomment if your system supports AVX2
+        //    val os = System.getProperty("os.name")
+        //
+        //    if (System.getProperty("os.arch") in arrayOf("x86_64", "amd64")) when {
+        //        os.startsWith("Windows") -> implementation("org.nd4j:nd4j-native:1.0.0-beta7:windows-x86_64-avx2")
+        //        os == "Linux" -> implementation("org.nd4j:nd4j-native:1.0.0-beta7:linux-x86_64-avx2")
+        //        os == "Mac OS X" -> implementation("org.nd4j:nd4j-native:1.0.0-beta7:macosx-x86_64-avx2")
+        //    } else
+        //    implementation("org.nd4j:nd4j-native-platform:1.0.0-beta7")
+    }
+}
+
+kotlin {
+    compilerOptions {
+        optIn.addAll(
+            "space.kscience.kmath.UnstableKMathAPI"
+        )
+    }
+
     sourceSets {
         all {
             languageSettings {
@@ -34,45 +80,6 @@ kotlin {
                 optIn("space.kscience.kmath.UnstableKMathAPI")
             }
         }
-
-        val commonMain by getting {
-            dependencies {
-                implementation(project(":kmath-ast"))
-                implementation(project(":kmath-core"))
-                implementation(project(":kmath-coroutines"))
-                implementation(project(":kmath-complex"))
-                implementation(project(":kmath-stat"))
-                implementation(project(":kmath-dimensions"))
-                implementation(project(":kmath-for-real"))
-                implementation(project(":kmath-tensors"))
-                implementation(project(":kmath-multik"))
-                implementation("org.jetbrains.kotlinx:multik-default:$multikVersion")
-                implementation(spclibs.kotlinx.benchmark.runtime)
-            }
-        }
-
-        val jvmMain by getting {
-            dependencies {
-                implementation(project(":kmath-commons"))
-                implementation(project(":kmath-ejml"))
-                implementation(project(":kmath-nd4j"))
-                implementation(project(":kmath-kotlingrad"))
-                implementation(project(":kmath-viktor"))
-                implementation(project(":kmath-jafama"))
-                implementation(projects.kmath.kmathTensorflow)
-                implementation("org.tensorflow:tensorflow-core-platform:0.4.0")
-                implementation("org.nd4j:nd4j-native:1.0.0-M1")
-                //    uncomment if your system supports AVX2
-                //    val os = System.getProperty("os.name")
-                //
-                //    if (System.getProperty("os.arch") in arrayOf("x86_64", "amd64")) when {
-                //        os.startsWith("Windows") -> implementation("org.nd4j:nd4j-native:1.0.0-beta7:windows-x86_64-avx2")
-                //        os == "Linux" -> implementation("org.nd4j:nd4j-native:1.0.0-beta7:linux-x86_64-avx2")
-                //        os == "Mac OS X" -> implementation("org.nd4j:nd4j-native:1.0.0-beta7:macosx-x86_64-avx2")
-                //    } else
-                //    implementation("org.nd4j:nd4j-native-platform:1.0.0-beta7")
-            }
-        }
     }
 }
 
@@ -81,7 +88,7 @@ benchmark {
     // Setup configurations
     targets {
         register("jvm")
-//        register("js")
+        register("js")
     }
 
     fun kotlinx.benchmark.gradle.BenchmarkConfiguration.commonConfiguration() {
@@ -96,6 +103,11 @@ benchmark {
         include("BufferBenchmark")
     }
 
+    configurations.register("minStatistic") {
+        commonConfiguration()
+        include("MinStatisticBenchmark")
+    }
+
     configurations.register("nd") {
         commonConfiguration()
         include("NDFieldBenchmark")
@@ -152,23 +164,122 @@ benchmark {
     }
 }
 
-kotlin.sourceSets.all {
-    with(languageSettings) {
-        optIn("kotlin.contracts.ExperimentalContracts")
-        optIn("kotlin.ExperimentalUnsignedTypes")
-        optIn("space.kscience.kmath.UnstableKMathAPI")
-    }
-}
 
-tasks.withType<KotlinJvmCompile> {
-    kotlinOptions {
-        jvmTarget = "11"
-        freeCompilerArgs = freeCompilerArgs + "-Xjvm-default=all" + "-Xlambdas=indy"
+private data class JmhReport(
+    val jmhVersion: String,
+    val benchmark: String,
+    val mode: String,
+    val threads: Int,
+    val forks: Int,
+    val jvm: String,
+    val jvmArgs: List<String>,
+    val jdkVersion: String,
+    val vmName: String,
+    val vmVersion: String,
+    val warmupIterations: Int,
+    val warmupTime: String,
+    val warmupBatchSize: Int,
+    val measurementIterations: Int,
+    val measurementTime: String,
+    val measurementBatchSize: Int,
+    val params: Map<String, String> = emptyMap(),
+    val primaryMetric: PrimaryMetric,
+    val secondaryMetrics: Map<String, SecondaryMetric>,
+) {
+    interface Metric {
+        val score: Double
+        val scoreError: Double
+        val scoreConfidence: List<Double>
+        val scorePercentiles: Map<Double, Double>
+        val scoreUnit: String
     }
+
+    data class PrimaryMetric(
+        override val score: Double,
+        override val scoreError: Double,
+        override val scoreConfidence: List<Double>,
+        override val scorePercentiles: Map<Double, Double>,
+        override val scoreUnit: String,
+        val rawDataHistogram: List<List<List<List<Double>>>>? = null,
+        val rawData: List<List<Double>>? = null,
+    ) : Metric
+
+    data class SecondaryMetric(
+        override val score: Double,
+        override val scoreError: Double,
+        override val scoreConfidence: List<Double>,
+        override val scorePercentiles: Map<Double, Double>,
+        override val scoreUnit: String,
+        val rawData: List<List<Double>>,
+    ) : Metric
 }
 
 readme {
-    maturity = space.kscience.gradle.Maturity.EXPERIMENTAL
+
+    val jsonMapper = jacksonObjectMapper()
+
+    fun noun(number: Number, singular: String, plural: String) = if (number.toLong() == 1L) singular else plural
+
+    extensions.findByType(BenchmarksExtension::class.java)?.configurations?.forEach { cfg ->
+        val propertyName =
+            "benchmark${cfg.name.replaceFirstChar { if (it.isLowerCase()) it.titlecase(Locale.getDefault()) else it.toString() }}"
+
+        logger.info("Processing benchmark data from benchmark ${cfg.name} into readme property $propertyName")
+
+        val launches = layout.buildDirectory.dir("reports/benchmarks/${cfg.name}").get().asFile
+        if (!launches.exists()) return@forEach
+
+        property(propertyName) {
+            val resDirectory = launches.listFiles()?.maxByOrNull {
+                it.nameWithoutExtension
+            }
+
+            if (resDirectory == null || !(resDirectory.resolve("jvm.json")).exists()) {
+                "> **Can't find appropriate benchmark data. Try generating readme files after running benchmarks**."
+            } else {
+                val reports: List<JmhReport> =
+                    jsonMapper.readValue<List<JmhReport>>(resDirectory.resolve("jvm.json"))
+
+                buildString {
+                    appendLine("## Report for benchmark configuration <code>${cfg.name}</code>")
+                    appendLine()
+                    val first = reports.first()
+
+                    appendLine("* Run on ${first.vmName} (build ${first.vmVersion}) with Java process:")
+                    appendLine()
+                    appendLine("```")
+                    appendLine(
+                        "${first.jvm} ${
+                            first.jvmArgs.joinToString(" ")
+                        }"
+                    )
+                    appendLine("```")
+
+                    appendLine(
+                        "* JMH ${first.jmhVersion} was used in `${first.mode}` mode with ${first.warmupIterations} warmup ${
+                            noun(first.warmupIterations, "iteration", "iterations")
+                        } by ${first.warmupTime} and ${first.measurementIterations} measurement ${
+                            noun(first.measurementIterations, "iteration", "iterations")
+                        } by ${first.measurementTime}."
+                    )
+
+                    reports.groupBy { it.benchmark.substringBeforeLast(".") }.forEach { (cl, compare) ->
+                        appendLine("### [${cl.substringAfterLast(".")}](src/jvmMain/kotlin/${cl.replace(".", "/")}.kt)")
+                        appendLine()
+                        appendLine("| Benchmark | Score |")
+                        appendLine("|:---------:|:-----:|")
+                        compare.forEach { report ->
+                            val benchmarkName = report.benchmark.substringAfterLast(".")
+                            val score = String.format("%.2G", report.primaryMetric.score)
+                            val error = String.format("%.2G", report.primaryMetric.scoreError)
+
+                            appendLine("|`$benchmarkName`|$score &plusmn; $error ${report.primaryMetric.scoreUnit}|")
+                        }
+                    }
+                }
+            }
+        }
+    }
 }
 
-addBenchmarkProperties()
+kotlin.explicitApi = org.jetbrains.kotlin.gradle.dsl.ExplicitApiMode.Disabled

benchmarks/docs/README-TEMPLATE.md

@@ -0,0 +1,7 @@
+# Module KMath-Benchmarks
+
+# BenchmarksResult
+
+${benchmarkMain}
+
+

benchmarks/src/jsMain/kotlin/space/kscience/kmath/benchmarks/ExpressionsInterpretersBenchmark.kt

@@ -14,6 +14,7 @@ import space.kscience.kmath.expressions.*
 import space.kscience.kmath.operations.Float64Field
 import space.kscience.kmath.operations.bindSymbol
 import space.kscience.kmath.operations.invoke
+import space.kscience.kmath.structures.Float64
 import kotlin.math.sin
 import kotlin.random.Random
 import space.kscience.kmath.estree.compileToExpression as estreeCompileToExpression
@@ -34,13 +35,13 @@ class ExpressionsInterpretersBenchmark {
     fun mstExpression(blackhole: Blackhole) = invokeAndSum(mst, blackhole)
 
     /**
-     * Benchmark case for [Expression] created with [compileToExpression].
+     * Benchmark case for [Expression] created with [space.kscience.kmath.estree.compileToExpression].
      */
     @Benchmark
     fun wasmExpression(blackhole: Blackhole) = invokeAndSum(wasm, blackhole)
 
     /**
-     * Benchmark case for [Expression] created with [compileToExpression].
+     * Benchmark case for [Expression] created with [space.kscience.kmath.estree.compileToExpression].
      */
     @Benchmark
     fun estreeExpression(blackhole: Blackhole) = invokeAndSum(estree, blackhole)
@@ -67,7 +68,7 @@ class ExpressionsInterpretersBenchmark {
         blackhole.consume(sum)
     }
 
-    private fun invokeAndSum(expr: Expression<Double>, blackhole: Blackhole) {
+    private fun invokeAndSum(expr: Expression<Float64>, blackhole: Blackhole) {
         val random = Random(0)
         var sum = 0.0
         val m = HashMap<Symbol, Double>()
@@ -99,7 +100,7 @@ class ExpressionsInterpretersBenchmark {
         private val wasm = node.wasmCompileToExpression(Float64Field)
         private val estree = node.estreeCompileToExpression(Float64Field)
 
-        private val raw = Expression<Double> { args ->
+        private val raw = Expression<Float64> { args ->
             val x = args.getValue(x)
             x * 2.0 + 2.0 / x - 16.0 / sin(x)
         }

benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/DotBenchmark.kt

@@ -14,6 +14,8 @@ import space.kscience.kmath.ejml.EjmlLinearSpaceDDRM
 import space.kscience.kmath.linear.Float64ParallelLinearSpace
 import space.kscience.kmath.linear.invoke
 import space.kscience.kmath.linear.linearSpace
+import space.kscience.kmath.ojalgo.Ojalgo
+import space.kscience.kmath.ojalgo.linearSpace
 import space.kscience.kmath.operations.Float64Field
 import space.kscience.kmath.tensorflow.produceWithTF
 import space.kscience.kmath.tensors.core.tensorAlgebra
@@ -56,13 +58,13 @@ internal class DotBenchmark {
     }
 
     @Benchmark
-    fun cmDot(blackhole: Blackhole) = CMLinearSpace {
-        blackhole.consume(cmMatrix1 dot cmMatrix2)
+    fun cmDot(blackhole: Blackhole): Unit = CMLinearSpace {
+        blackhole.consume(cmMatrix1.asMatrix() dot cmMatrix2.asMatrix())
     }
 
     @Benchmark
-    fun ejmlDot(blackhole: Blackhole) = EjmlLinearSpaceDDRM {
-        blackhole.consume(ejmlMatrix1 dot ejmlMatrix2)
+    fun ejmlDot(blackhole: Blackhole): Unit = EjmlLinearSpaceDDRM {
+        blackhole.consume(ejmlMatrix1.asMatrix() dot ejmlMatrix2.asMatrix())
     }
 
     @Benchmark
@@ -70,6 +72,11 @@ internal class DotBenchmark {
         blackhole.consume(matrix1 dot matrix2)
     }
 
+    @Benchmark
+    fun ojalgoDot(blackhole: Blackhole) = Ojalgo.R064.linearSpace {
+        blackhole.consume(matrix1 dot matrix2)
+    }
+
     @Benchmark
     fun multikDot(blackhole: Blackhole) = with(multikAlgebra) {
         blackhole.consume(matrix1 dot matrix2)

benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/ExpressionsInterpretersBenchmark.kt

@@ -15,6 +15,7 @@ import space.kscience.kmath.operations.Algebra
 import space.kscience.kmath.operations.Float64Field
 import space.kscience.kmath.operations.bindSymbol
 import space.kscience.kmath.operations.invoke
+import space.kscience.kmath.structures.Float64
 import kotlin.math.sin
 import kotlin.random.Random
 
@@ -83,7 +84,7 @@ internal class ExpressionsInterpretersBenchmark {
         blackhole.consume(sum)
     }
 
-    private fun invokeAndSum(expr: Expression<Double>, blackhole: Blackhole) {
+    private fun invokeAndSum(expr: Expression<Float64>, blackhole: Blackhole) {
         val random = Random(0)
         var sum = 0.0
         val m = HashMap<Symbol, Double>()
@@ -114,9 +115,9 @@ internal class ExpressionsInterpretersBenchmark {
         private val asmPrimitive = node.compileToExpression(Float64Field)
         private val xIdx = asmPrimitive.indexer.indexOf(x)
 
-        private val asmGeneric = node.compileToExpression(Float64Field as Algebra<Double>)
+        private val asmGeneric = node.compileToExpression(Float64Field as Algebra<Float64>)
 
-        private val raw = Expression<Double> { args ->
+        private val raw = Expression<Float64> { args ->
             val x = args[x]!!
             x * 2.0 + 2.0 / x - 16.0 / sin(x)
         }

benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/JafamaBenchmark.kt

@@ -1,39 +0,0 @@
-/*
- * Copyright 2018-2024 KMath contributors.
- * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
- */
-
-package space.kscience.kmath.benchmarks
-
-import kotlinx.benchmark.Blackhole
-import org.openjdk.jmh.annotations.Benchmark
-import org.openjdk.jmh.annotations.Scope
-import org.openjdk.jmh.annotations.State
-import space.kscience.kmath.jafama.JafamaDoubleField
-import space.kscience.kmath.jafama.StrictJafamaDoubleField
-import space.kscience.kmath.operations.Float64Field
-import space.kscience.kmath.operations.invoke
-import kotlin.random.Random
-
-@State(Scope.Benchmark)
-internal class JafamaBenchmark {
-    @Benchmark
-    fun jafama(blackhole: Blackhole) = invokeBenchmarks(blackhole) { x ->
-        JafamaDoubleField { x * power(x, 4) * exp(x) / cos(x) + sin(x) }
-    }
-
-    @Benchmark
-    fun core(blackhole: Blackhole) = invokeBenchmarks(blackhole) { x ->
-        Float64Field { x * power(x, 4) * exp(x) / cos(x) + sin(x) }
-    }
-
-    @Benchmark
-    fun strictJafama(blackhole: Blackhole) = invokeBenchmarks(blackhole) { x ->
-        StrictJafamaDoubleField { x * power(x, 4) * exp(x) / cos(x) + sin(x) }
-    }
-}
-
-private inline fun invokeBenchmarks(blackhole: Blackhole, expr: (Double) -> Double) {
-    val rng = Random(0)
-    repeat(1000000) { blackhole.consume(expr(rng.nextDouble())) }
-}

benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/MatrixInverseBenchmark.kt

@@ -12,10 +12,9 @@ import kotlinx.benchmark.State
 import space.kscience.kmath.commons.linear.CMLinearSpace
 import space.kscience.kmath.commons.linear.lupSolver
 import space.kscience.kmath.ejml.EjmlLinearSpaceDDRM
-import space.kscience.kmath.linear.invoke
-import space.kscience.kmath.linear.linearSpace
-import space.kscience.kmath.linear.lupSolver
-import space.kscience.kmath.linear.parallel
+import space.kscience.kmath.linear.*
+import space.kscience.kmath.ojalgo.Ojalgo
+import space.kscience.kmath.ojalgo.linearSpace
 import space.kscience.kmath.operations.algebra
 import kotlin.random.Random
 
@@ -48,10 +47,14 @@ internal class MatrixInverseBenchmark {
         blackhole.consume(lupSolver().inverse(matrix))
     }
 
-
     @Benchmark
     fun ejmlInverse(blackhole: Blackhole) = EjmlLinearSpaceDDRM {
-        blackhole.consume(matrix.toEjml().inverted())
+        blackhole.consume(matrix.inverted())
+    }
+
+    @Benchmark
+    fun ojalgoInverse(blackhole: Blackhole) = Ojalgo.R064.linearSpace {
+        blackhole.consume(matrix.getOrComputeAttribute(Inverted))
     }
 
 }

benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/MinStatisticBenchmark.kt

@@ -0,0 +1,44 @@
+/*
+ * Copyright 2018-2025 KMath contributors.
+ * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
+ */
+
+package space.kscience.kmath.benchmarks
+
+import kotlinx.benchmark.Benchmark
+import kotlinx.benchmark.Blackhole
+import kotlinx.benchmark.Scope
+import kotlinx.benchmark.State
+import kotlinx.coroutines.runBlocking
+import space.kscience.kmath.operations.Float64Field
+import space.kscience.kmath.stat.min
+import space.kscience.kmath.structures.*
+
+@State(Scope.Benchmark)
+internal class MinStatisticBenchmark {
+
+    @Benchmark
+    fun kotlinArrayMin(blackhole: Blackhole) {
+        val array = DoubleArray(size) { it.toDouble() }
+        var res = 0.0
+        (0 until size).forEach {
+            res += array.min()
+        }
+        blackhole.consume(res)
+    }
+
+    @Benchmark
+    fun minBlocking(blackhole: Blackhole) {
+        val buffer = Float64Buffer(size) { it.toDouble() }
+        var res = 0.0
+        (0 until size).forEach {
+            res += Float64Field.min.evaluateBlocking(buffer)
+        }
+        blackhole.consume(res)
+    }
+
+
+    private companion object {
+        private const val size = 1000
+    }
+}

benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/NDFieldBenchmark.kt

@@ -15,8 +15,8 @@ import org.jetbrains.kotlinx.multik.ndarray.data.DN
 import org.jetbrains.kotlinx.multik.ndarray.data.DataType
 import space.kscience.kmath.UnsafeKMathAPI
 import space.kscience.kmath.nd.*
-import space.kscience.kmath.nd4j.nd4j
 import space.kscience.kmath.operations.Float64Field
+import space.kscience.kmath.structures.Float64
 import space.kscience.kmath.tensors.core.DoubleTensor
 import space.kscience.kmath.tensors.core.one
 import space.kscience.kmath.tensors.core.tensorAlgebra
@@ -31,34 +31,33 @@ internal class NDFieldBenchmark {
         private val shape = ShapeND(dim, dim)
         private val specializedField = Float64Field.ndAlgebra
         private val genericField = BufferedFieldOpsND(Float64Field)
-        private val nd4jField = Float64Field.nd4j
         private val viktorField = Float64Field.viktorAlgebra
     }
 
     @Benchmark
     fun specializedFieldAdd(blackhole: Blackhole) = with(specializedField) {
-        var res: StructureND<Double> = one(shape)
+        var res: StructureND<Float64> = one(shape)
         repeat(n) { res += 1.0 }
         blackhole.consume(res)
     }
 
     @Benchmark
     fun boxingFieldAdd(blackhole: Blackhole) = with(genericField) {
-        var res: StructureND<Double> = one(shape)
+        var res: StructureND<Float64> = one(shape)
         repeat(n) { res += 1.0 }
         blackhole.consume(res)
     }
 
     @Benchmark
     fun multikAdd(blackhole: Blackhole) = with(multikAlgebra) {
-        var res: StructureND<Double> = one(shape)
+        var res: StructureND<Float64> = one(shape)
         repeat(n) { res += 1.0 }
         blackhole.consume(res)
     }
 
     @Benchmark
     fun viktorAdd(blackhole: Blackhole) = with(viktorField) {
-        var res: StructureND<Double> = one(shape)
+        var res: StructureND<Float64> = one(shape)
         repeat(n) { res += 1.0 }
         blackhole.consume(res)
     }
@@ -87,7 +86,7 @@ internal class NDFieldBenchmark {
 
 //    @Benchmark
 //    fun nd4jAdd(blackhole: Blackhole) = with(nd4jField) {
-//        var res: StructureND<Double> = one(dim, dim)
+//        var res: StructureND<Float64> = one(dim, dim)
 //        repeat(n) { res += 1.0 }
 //        blackhole.consume(res)
 //    }

benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/TensorAlgebraBenchmark.kt

@@ -9,8 +9,8 @@ import kotlinx.benchmark.Benchmark
 import kotlinx.benchmark.Blackhole
 import kotlinx.benchmark.Scope
 import kotlinx.benchmark.State
+import space.kscience.kmath.linear.MatrixBuilder
 import space.kscience.kmath.linear.linearSpace
-import space.kscience.kmath.linear.matrix
 import space.kscience.kmath.linear.symmetric
 import space.kscience.kmath.operations.Float64Field
 import space.kscience.kmath.tensors.core.symEigJacobi
@@ -24,7 +24,7 @@ internal class TensorAlgebraBenchmark {
         private val random = Random(12224)
         private const val dim = 30
 
-        private val matrix = Float64Field.linearSpace.matrix(dim, dim).symmetric { _, _ -> random.nextDouble() }
+        private val matrix = Float64Field.linearSpace.MatrixBuilder(dim, dim).symmetric { _, _ -> random.nextDouble() }
     }
 
     @Benchmark

benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/ViktorBenchmark.kt

@@ -15,6 +15,7 @@ import space.kscience.kmath.nd.StructureND
 import space.kscience.kmath.nd.ndAlgebra
 import space.kscience.kmath.nd.one
 import space.kscience.kmath.operations.Float64Field
+import space.kscience.kmath.structures.Float64
 import space.kscience.kmath.viktor.ViktorFieldND
 
 @State(Scope.Benchmark)
@@ -23,7 +24,7 @@ internal class ViktorBenchmark {
     @Benchmark
     fun doubleFieldAddition(blackhole: Blackhole) {
         with(doubleField) {
-            var res: StructureND<Double> = one(shape)
+            var res: StructureND<Float64> = one(shape)
             repeat(n) { res += 1.0 }
             blackhole.consume(res)
         }

build.gradle.kts

@@ -1,13 +1,12 @@
+import org.jetbrains.kotlin.gradle.dsl.abi.ExperimentalAbiValidation
 import space.kscience.gradle.useApache2Licence
 import space.kscience.gradle.useSPCTeam
 
 plugins {
-    id("space.kscience.gradle.project")
-    id("org.jetbrains.kotlinx.kover") version "0.7.6"
+    alias(spclibs.plugins.kscience.project)
+    alias(spclibs.plugins.kotlinx.kover)
 }
 
-val attributesVersion by extra("0.2.0")
-
 allprojects {
     repositories {
         maven("https://repo.kotlin.link")
@@ -16,30 +15,49 @@ allprojects {
     }
 
     group = "space.kscience"
-    version = "0.4.1-dev"
+    version = "0.5.0"
+}
+
+dependencies {
+    subprojects.forEach {
+        dokka(it)
+    }
+}
+
+dokka {
+    dokkaSourceSets.configureEach {
+        val readmeFile = projectDir.resolve("README.md")
+        if (readmeFile.exists()) includes.from(readmeFile)
+    }
 }
 
 subprojects {
     if (name.startsWith("kmath")) apply<MavenPublishPlugin>()
 
     plugins.withId("org.jetbrains.dokka") {
-        tasks.withType<org.jetbrains.dokka.gradle.DokkaTaskPartial> {
-            dependsOn(tasks["assemble"])
-
-            dokkaSourceSets.all {
-                val readmeFile = this@subprojects.projectDir.resolve("README.md")
+        dokka {
+            dokkaSourceSets.configureEach {
+                val readmeFile = projectDir.resolve("README.md")
                 if (readmeFile.exists()) includes.from(readmeFile)
                 val kotlinDirPath = "src/$name/kotlin"
                 val kotlinDir = file(kotlinDirPath)
 
                 if (kotlinDir.exists()) sourceLink {
                     localDirectory.set(kotlinDir)
-
-                    remoteUrl.set(
-                        uri("https://github.com/SciProgCentre/kmath/tree/master/${this@subprojects.name}/$kotlinDirPath").toURL()
+                    remoteUrl(
+                        "https://github.com/SciProgCentre/kmath/tree/master/${name}/$kotlinDirPath"
                     )
                 }
 
+                fun externalDocumentationLink(url: String, packageListUrl: String? = null) {
+                    externalDocumentationLinks.register(url) {
+                        url(url)
+                        packageListUrl?.let {
+                            packageListUrl(it)
+                        }
+                    }
+                }
+
                 externalDocumentationLink("https://commons.apache.org/proper/commons-math/javadocs/api-3.6.1/")
                 externalDocumentationLink("https://deeplearning4j.org/api/latest/")
                 externalDocumentationLink("https://axelclk.bitbucket.io/symja/javadoc/")
@@ -50,25 +68,35 @@ subprojects {
                 )
 
                 externalDocumentationLink(
-                    "https://breandan.net/kotlingrad/kotlingrad/",
-                    "https://breandan.net/kotlingrad/kotlingrad/kotlingrad/package-list",
+                    "https://breandan.net/kotlingrad/kotlingrad",
+                    "https://breandan.net/kotlingrad/package-list",
                 )
             }
         }
+
+    }
+}
+
+kscienceProject {
+    readme.readmeTemplate = file("docs/templates/README-TEMPLATE.md")
+
+
+    pom("https://github.com/SciProgCentre/kmath") {
+        useApache2Licence()
+        useSPCTeam()
+    }
+    publishTo("spc", "https://maven.sciprog.center/kscience")
+    publishToCentral()
+
+    @OptIn(ExperimentalAbiValidation::class)
+    abiValidation {
+        filters {
+            excluded {
+                annotatedWith.add("space.kscience.kmath.UnstableKMathAPI")
+            }
+        }
     }
 }
 
-readme.readmeTemplate = file("docs/templates/README-TEMPLATE.md")
 
-ksciencePublish {
-    pom("https://github.com/SciProgCentre/kmath") {
-        useApache2Licence()
-        useSPCTeam()
-    }
-    repository("spc", "https://maven.sciprog.center/kscience")
-    sonatype("https://oss.sonatype.org")
-}
 
-apiValidation.nonPublicMarkers.add("space.kscience.kmath.UnstableKMathAPI")
-
-val multikVersion by extra("0.2.3")

buildSrc/build.gradle.kts

@@ -1,35 +0,0 @@
-plugins {
-    kotlin("jvm") version "1.9.23"
-    `kotlin-dsl`
-    `version-catalog`
-}
-
-repositories {
-    mavenLocal()
-    maven("https://repo.kotlin.link")
-    mavenCentral()
-    gradlePluginPortal()
-}
-
-val toolsVersion = spclibs.versions.tools.get()
-val kotlinVersion = spclibs.versions.kotlin.asProvider().get()
-val benchmarksVersion = spclibs.versions.kotlinx.benchmark.get()
-
-dependencies {
-    api("space.kscience:gradle-tools:$toolsVersion")
-    //plugins form benchmarks
-    api("org.jetbrains.kotlinx:kotlinx-benchmark-plugin:$benchmarksVersion")
-    //api("org.jetbrains.kotlin:kotlin-allopen:$kotlinVersion")
-    //to be used inside build-script only
-    //implementation(spclibs.kotlinx.serialization.json)
-    implementation("com.fasterxml.jackson.module:jackson-module-kotlin:2.14.+")
-}
-
-kotlin {
-    jvmToolchain {
-        languageVersion.set(JavaLanguageVersion.of(11))
-    }
-    sourceSets.all {
-        languageSettings.optIn("kotlin.OptIn")
-    }
-}

buildSrc/settings.gradle.kts

@@ -1,38 +0,0 @@
-/*
- * Copyright 2018-2021 KMath contributors.
- * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
- */
-
-enableFeaturePreview("TYPESAFE_PROJECT_ACCESSORS")
-
-plugins {
-    id("org.gradle.toolchains.foojay-resolver-convention") version "0.8.0"
-}
-
-dependencyResolutionManagement {
-    val projectProperties = java.util.Properties()
-    file("../gradle.properties").inputStream().use {
-        projectProperties.load(it)
-    }
-
-    projectProperties.forEach { key, value ->
-        extra.set(key.toString(), value)
-    }
-
-
-    val toolsVersion: String = projectProperties["toolsVersion"].toString()
-
-    @Suppress("UnstableApiUsage")
-    repositories {
-        mavenLocal()
-        maven("https://repo.kotlin.link")
-        mavenCentral()
-        gradlePluginPortal()
-    }
-
-    versionCatalogs {
-        create("spclibs") {
-            from("space.kscience:version-catalog:$toolsVersion")
-        }
-    }
-}

buildSrc/src/main/kotlin/space/kscience/kmath/benchmarks/JmhReport.kt

@@ -1,55 +0,0 @@
-/*
- * Copyright 2018-2024 KMath contributors.
- * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
- */
-
-package space.kscience.kmath.benchmarks
-
-data class JmhReport(
-    val jmhVersion: String,
-    val benchmark: String,
-    val mode: String,
-    val threads: Int,
-    val forks: Int,
-    val jvm: String,
-    val jvmArgs: List<String>,
-    val jdkVersion: String,
-    val vmName: String,
-    val vmVersion: String,
-    val warmupIterations: Int,
-    val warmupTime: String,
-    val warmupBatchSize: Int,
-    val measurementIterations: Int,
-    val measurementTime: String,
-    val measurementBatchSize: Int,
-    val params: Map<String, String> = emptyMap(),
-    val primaryMetric: PrimaryMetric,
-    val secondaryMetrics: Map<String, SecondaryMetric>,
-) {
-    interface Metric {
-        val score: Double
-        val scoreError: Double
-        val scoreConfidence: List<Double>
-        val scorePercentiles: Map<Double, Double>
-        val scoreUnit: String
-    }
-
-    data class PrimaryMetric(
-        override val score: Double,
-        override val scoreError: Double,
-        override val scoreConfidence: List<Double>,
-        override val scorePercentiles: Map<Double, Double>,
-        override val scoreUnit: String,
-        val rawDataHistogram: List<List<List<List<Double>>>>? = null,
-        val rawData: List<List<Double>>? = null,
-    ) : Metric
-
-    data class SecondaryMetric(
-        override val score: Double,
-        override val scoreError: Double,
-        override val scoreConfidence: List<Double>,
-        override val scorePercentiles: Map<Double, Double>,
-        override val scoreUnit: String,
-        val rawData: List<List<Double>>,
-    ) : Metric
-}

buildSrc/src/main/kotlin/space/kscience/kmath/benchmarks/addBenchmarkProperties.kt

@@ -1,110 +0,0 @@
-/*
- * Copyright 2018-2024 KMath contributors.
- * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
- */
-
-package space.kscience.kmath.benchmarks
-
-import com.fasterxml.jackson.module.kotlin.jacksonObjectMapper
-import com.fasterxml.jackson.module.kotlin.readValue
-import kotlinx.benchmark.gradle.BenchmarksExtension
-import org.gradle.api.Project
-import space.kscience.gradle.KScienceReadmeExtension
-import java.time.LocalDateTime
-import java.time.ZoneId
-import java.time.format.DateTimeFormatter
-import java.time.format.DateTimeFormatterBuilder
-import java.time.format.SignStyle
-import java.time.temporal.ChronoField.*
-import java.util.*
-
-private val ISO_DATE_TIME: DateTimeFormatter = DateTimeFormatterBuilder().run {
-    parseCaseInsensitive()
-    appendValue(YEAR, 4, 10, SignStyle.EXCEEDS_PAD)
-    appendLiteral('-')
-    appendValue(MONTH_OF_YEAR, 2)
-    appendLiteral('-')
-    appendValue(DAY_OF_MONTH, 2)
-    appendLiteral('T')
-    appendValue(HOUR_OF_DAY, 2)
-    appendLiteral('.')
-    appendValue(MINUTE_OF_HOUR, 2)
-    optionalStart()
-    appendLiteral('.')
-    appendValue(SECOND_OF_MINUTE, 2)
-    optionalStart()
-    appendFraction(NANO_OF_SECOND, 0, 9, true)
-    optionalStart()
-    appendOffsetId()
-    optionalStart()
-    appendLiteral('[')
-    parseCaseSensitive()
-    appendZoneRegionId()
-    appendLiteral(']')
-    toFormatter()
-}
-
-private fun noun(number: Number, singular: String, plural: String) = if (number.toLong() == 1L) singular else plural
-
-private val jsonMapper = jacksonObjectMapper()
-
-fun Project.addBenchmarkProperties() {
-    val benchmarksProject = this
-    rootProject.subprojects.forEach { p ->
-        p.extensions.findByType(KScienceReadmeExtension::class.java)?.run {
-            benchmarksProject.extensions.findByType(BenchmarksExtension::class.java)?.configurations?.forEach { cfg ->
-                property("benchmark${cfg.name.replaceFirstChar { if (it.isLowerCase()) it.titlecase(Locale.getDefault()) else it.toString() }}") {
-                    val launches = benchmarksProject.layout.buildDirectory.dir("reports/benchmarks/${cfg.name}").get()
-
-                    val resDirectory = launches.files().maxByOrNull {
-                        LocalDateTime.parse(it.name, ISO_DATE_TIME).atZone(ZoneId.systemDefault()).toInstant()
-                    }
-
-                    if (resDirectory == null || !(resDirectory.resolve("jvm.json")).exists()) {
-                        "> **Can't find appropriate benchmark data. Try generating readme files after running benchmarks**."
-                    } else {
-                        val reports: List<JmhReport> =
-                            jsonMapper.readValue<List<JmhReport>>(resDirectory.resolve("jvm.json"))
-
-                        buildString {
-                            appendLine("<details>")
-                            appendLine("<summary>")
-                            appendLine("Report for benchmark configuration <code>${cfg.name}</code>")
-                            appendLine("</summary>")
-                            appendLine()
-                            val first = reports.first()
-
-                            appendLine("* Run on ${first.vmName} (build ${first.vmVersion}) with Java process:")
-                            appendLine()
-                            appendLine("```")
-                            appendLine(
-                                "${first.jvm} ${
-                                    first.jvmArgs.joinToString(" ")
-                                }"
-                            )
-                            appendLine("```")
-
-                            appendLine(
-                                "* JMH ${first.jmhVersion} was used in `${first.mode}` mode with ${first.warmupIterations} warmup ${
-                                    noun(first.warmupIterations, "iteration", "iterations")
-                                } by ${first.warmupTime} and ${first.measurementIterations} measurement ${
-                                    noun(first.measurementIterations, "iteration", "iterations")
-                                } by ${first.measurementTime}."
-                            )
-
-                            appendLine()
-                            appendLine("| Benchmark | Score |")
-                            appendLine("|:---------:|:-----:|")
-
-                            reports.forEach { report ->
-                                appendLine("|`${report.benchmark}`|${report.primaryMetric.score} &plusmn; ${report.primaryMetric.scoreError} ${report.primaryMetric.scoreUnit}|")
-                            }
-
-                            appendLine("</details>")
-                        }
-                    }
-                }
-            }
-        }
-    }
-}

docs/nd-structure.md

@@ -31,7 +31,7 @@ The code to run this looks like:
 
 ```kotlin
     specializedField.run {
-        var res: NDBuffer<Double> = one
+        var res: NDBuffer<Float64> = one
         repeat(n) {
             res += 1.0
         }
@@ -103,7 +103,7 @@ The boxing field produced by
 
 ```kotlin
     genericField.run {
-        var res: NDBuffer<Double> = one
+        var res: NDBuffer<Float64> = one
         repeat(n) {
             res += 1.0
         }

docs/readme.md

@@ -11,4 +11,6 @@
 
 * [Expressions](expressions.md)
 
+* [Statistics](statistics.md): statistical functions on data [Buffers](buffers.md)
+
 * Commons math integration

docs/statistics.md

@@ -0,0 +1,34 @@
+# Statistics
+
+Mathematically speaking, a statistic is a measurable numerical function of sample data.
+In KMath, a statistic is a function that operates on a [Buffer](buffers.md) and is implemented as the `evaluate` method
+of the `Statistic` interface.
+There are two subinterfaces of the `Statistic` interface:
+
+* `BlockingStatistic` – A statistic that is computed in a synchronous blocking mode
+* `ComposableStatistic` – A statistic tha could be computed separately on different blocks of data and then composed
+
+
+## Common statistics and Implementation Status
+
+| Category         | Statistic         | Description                        | Implementation Status          |
+|------------------|-------------------|------------------------------------|--------------------------------|
+| **Basic**        | Min               | Minimum value                      | ✅ `ComposableStatistic`        |
+|                  | Max               | Maximum value                      | ✅ `ComposableStatistic`        |
+|                  | Mean              | Arithmetic mean                    | ✅ `ComposableStatistic`        |
+|                  | Sum               | Sum of all values                  | 🚧 Not yet implemented         |
+|                  | Product           | Product of all values              | 🚧 Not yet implemented         |
+| **Distribution** | Median            | Median (50th percentile)           | ✅ `BlockingStatistic`          |
+|                  | Quantile          | Quantile and percentile            | ✅ `BlockingStatistic`          |
+|                  | Variance          | Unbiased sample variance           | ✅ `BlockingStatistic`          |
+|                  | StandardDeviation | Population standard deviation (σ)  | ✅ `BlockingStatistic`          |
+|                  | Skewness          | Measure of distribution asymmetry  | 🚧 *(Requires `ThirdMoment`)*  |
+|                  | Kurtosis          | Measure of distribution tailedness | 🚧 *(Requires `FourthMoment`)* |
+| **Advanced**     | GeometricMean     | Nth root of product of values      | ✅ `ComposableStatistic`        |
+|                  | SumOfLogs         | Sum of natural logarithms          | Does not planned               |
+|                  | SumOfSquares      | Sum of squared values              | 🚧 *(Blocks `Variance`)*       |
+| **Moments**      | FirstMoment       | Mean (same as `Mean`)              | ✅ *(Alias for `Mean`)*         |
+|                  | SecondMoment      | Variance (same as `Variance`)      | ✅ *(Alias for `Variance`)*     |
+|                  | ThirdMoment       | Used in skewness calculation       | 🚧 Not yet implemented         |
+|                  | FourthMoment      | Used in kurtosis calculation       | 🚧 Not yet implemented         |
+| **Risk Metrics** | SemiVariance      | Downside variance                  | 🚧 *(Depends on `Variance`)*   |

docs/templates/README-TEMPLATE.md

@@ -2,14 +2,10 @@
 [![DOI](https://zenodo.org/badge/129486382.svg)](https://zenodo.org/badge/latestdoi/129486382)
 ![Gradle build](https://github.com/SciProgCentre/kmath/workflows/Gradle%20build/badge.svg)
 [![Maven Central](https://img.shields.io/maven-central/v/space.kscience/kmath-core.svg?label=Maven%20Central)](https://search.maven.org/search?q=g:%22space.kscience%22)
-[![Space](https://img.shields.io/badge/dynamic/xml?color=orange&label=Space&query=//metadata/versioning/latest&url=https%3A%2F%2Fmaven.pkg.jetbrains.space%2Fmipt-npm%2Fp%2Fsci%2Fmaven%2Fspace%2Fkscience%2Fkmath-core%2Fmaven-metadata.xml)](https://maven.pkg.jetbrains.space/mipt-npm/p/sci/maven/space/kscience/)
 
 # KMath
 
-Could be pronounced as `key-math`. The **K**otlin **Math**ematics library was initially intended as a Kotlin-based
-analog to Python's NumPy library. Later we found that kotlin is much more flexible language and allows superior
-architecture designs. In contrast to `numpy` and `scipy` it is modular and has a lightweight core. The `numpy`-like
-experience could be achieved with [kmath-for-real](/kmath-for-real) extension module.
+Could be pronounced as `key-math`. The **K**otlin **Math**ematics library was initially intended as a Kotlin-based analog to Python's NumPy library. Later we found that kotlin is a much more flexible language and allows superior architecture designs. In contrast to `numpy` and `scipy` it is modular and has a lightweight core. The `numpy`-like experience could be achieved with [kmath-for-real](kmath-for-real) extension module.
 
 [Documentation site](https://SciProgCentre.github.io/kmath/)
 
@@ -35,15 +31,17 @@ experience could be achieved with [kmath-for-real](/kmath-for-real) extension mo
 * Be like NumPy. It was the idea at the beginning, but we decided that we can do better in API.
 * Provide the 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 `kmath-for-real`, which will give better
-  experience for those, who want to work with specific types.
+* Provide specialized behavior in the core. API is made generic on purpose, so one needs to specialize for types, like for `Float64` in the core. For that we will have specialization modules like [kmath-for-real](kmath-for-real), which will give a better experience for those who want to work with specific types.
+
+## Contributing
+
+The project requires a lot of additional work. The most important thing we need is feedback about what features are required the most. Feel free to create feature requests. We are also welcome to code contributions, especially in issues marked with [good first issue](https://github.com/SciProgCentre/kmath/issues?q=is%3Aissue+is%3Aopen+label%3A%22good+first+issue%22) label.
+
+Project roadmap will be available at [GitHub Projects](https://github.com/orgs/SciProgCentre/projects/3).
 
 ## Features and stability
 
-KMath is a modular library. Different modules provide different features with different API stability guarantees. All
-core modules are released with the same version, but with different API change policy. The features are described in
-module definitions below. The module stability could have the following levels:
+KMath is a modular library. Different modules provide different features with different API stability guarantees. All core modules are released with the same version, but with different API change policy. The features are described in module definitions below. The module stability could have the following levels:
 
 * **PROTOTYPE**. On this level there are no compatibility guarantees. All methods and classes form those modules could
   break any moment. You can still use it, but be sure to fix the specific version.
@@ -51,7 +49,7 @@ module definitions below. The module stability could have the following levels:
   with `@UnstableKMathAPI` or other stability warning annotations.
 * **DEVELOPMENT**. API breaking generally follows semantic versioning ideology. There could be changes in minor
   versions, but not in patch versions. API is protected
-  with [binary-compatibility-validator](https://github.com/Kotlin/binary-compatibility-validator) tool.
+  with [binary-compatibility-validator](https://kotlinlang.org/docs/gradle-binary-compatibility-validation.html) tool.
 * **STABLE**. The API stabilized. Breaking changes are allowed only in major releases.
 
 ## Modules
@@ -60,34 +58,21 @@ ${modules}
 
 ## Multi-platform support
 
-KMath is developed as a multi-platform library, which means that most of the interfaces are declared in the
-[common source sets](/kmath-core/src/commonMain) and implemented there wherever it is possible. In some cases, features
-are delegated to platform-specific implementations even if they could be provided in the common module for performance
-reasons. Currently, Kotlin/JVM is the primary platform, however, Kotlin/Native and Kotlin/JS contributions and
-feedback are also welcome.
+KMath is developed as a multi-platform library, which means that most of the interfaces are declared in common source sets like [common source sets](kmath-core/src/commonMain) and implemented there wherever it is possible. In some cases, features are delegated to platform-specific implementations even if they could be provided in the common module for performance reasons. Currently, Kotlin/JVM is the primary platform, however, Kotlin/Native, Kotlin/JS and Kotlin/Wasm contributions and feedback are also welcome.
 
 ## Performance
 
-Calculation of performance is one of the major goals of KMath in the future, but in some cases it is impossible to
-achieve both
-performance and flexibility.
+Performance of mathematical operations is hard to achieve without a lot of effort. KMath focus is to provide a reasonable performance for common cases, out of the box and good interoperability with optimized libraries for edge cases. For example, one could prototype an algorithm using KMath core implementations and then use Multik or Ojalgo for performance-critical parts just by adding a dependency and algebra context switch.
 
-We expect to focus on creating a 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.
+As for core implementations, we expect to focus on creating a 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.
 
 ## Requirements
 
-KMath currently relies on JDK 11 for compilation and execution of Kotlin-JVM part. We recommend using GraalVM-CE or
-Oracle GraalVM for execution to get better performance.
+KMath currently relies on JDK 21 for compilation and execution of Kotlin-JVM part. 
 
 ### Repositories
 
-Release and development artifacts are accessible from mipt-npm [Space](https://www.jetbrains.com/space/)
-repository `https://maven.pkg.jetbrains.space/mipt-npm/p/sci/maven` (see documentation of
-[Kotlin Multiplatform](https://kotlinlang.org/docs/reference/multiplatform.html) for more details). The repository could
-be reached through [repo.kotlin.link](https://repo.kotlin.link) proxy:
+Intermediate releases are published to [Kotlin.Link](https://repo.kotlin.link) repository.
 
 ```kotlin
 repositories {
@@ -99,11 +84,3 @@ dependencies {
     // api("${group}:kmath-core-jvm:$version") for jvm-specific version
 }
 ```
-
-## Contributing
-
-The project requires a lot of additional work. The most important thing we need is feedback about what features are
-required the most. Feel free to create feature requests. We are also welcome to code contributions, especially in issues
-marked
-with [good first issue](hhttps://github.com/SciProgCentre/kmath/issues?q=is%3Aissue+is%3Aopen+label%3A%22good+first+issue%22)
-label.

examples/build.gradle.kts

@@ -10,8 +10,6 @@ repositories {
     maven("https://maven.pkg.jetbrains.space/kotlin/p/kotlin/kotlin-js-wrappers")
 }
 
-val multikVersion: String by rootProject.extra
-
 dependencies {
     implementation(project(":kmath-ast"))
     implementation(project(":kmath-kotlingrad"))
@@ -25,20 +23,18 @@ dependencies {
     implementation(project(":kmath-viktor"))
     implementation(project(":kmath-dimensions"))
     implementation(project(":kmath-ejml"))
-    implementation(project(":kmath-nd4j"))
     implementation(project(":kmath-tensors"))
     implementation(project(":kmath-symja"))
     implementation(project(":kmath-for-real"))
-    //jafama
-    implementation(project(":kmath-jafama"))
     //multik
     implementation(project(":kmath-multik"))
-    implementation("org.jetbrains.kotlinx:multik-default:$multikVersion")
+    implementation(libs.multik.default)
 
     //datetime
-    implementation("org.jetbrains.kotlinx:kotlinx-datetime:0.4.0")
+    implementation(spclibs.kotlinx.datetime)
 
-    implementation("org.nd4j:nd4j-native:1.0.0-beta7")
+//    implementation(project(":kmath-nd4j"))
+//    implementation("org.nd4j:nd4j-native:1.0.0-beta7")
 
 //    uncomment if your system supports AVX2
 //    val os = System.getProperty("os.name")
@@ -48,7 +44,7 @@ dependencies {
 //        os == "Linux" -> implementation("org.nd4j:nd4j-native:1.0.0-beta7:linux-x86_64-avx2")
 //        os == "Mac OS X" -> implementation("org.nd4j:nd4j-native:1.0.0-beta7:macosx-x86_64-avx2")
 //    } else
-    implementation("org.nd4j:nd4j-native-platform:1.0.0-beta7")
+//    implementation("org.nd4j:nd4j-native-platform:1.0.0-beta7")
 
     implementation("org.slf4j:slf4j-simple:1.7.32")
     // plotting
@@ -56,7 +52,7 @@ dependencies {
 }
 
 kotlin {
-    jvmToolchain(11)
+    jvmToolchain(21)
     sourceSets.all {
         languageSettings {
             optIn("kotlin.contracts.ExperimentalContracts")
@@ -68,10 +64,6 @@ kotlin {
 
 tasks.withType<KotlinJvmCompile> {
     compilerOptions {
-        freeCompilerArgs.addAll("-Xjvm-default=all", "-Xopt-in=kotlin.RequiresOptIn", "-Xlambdas=indy")
+        freeCompilerArgs.addAll("-Xopt-in=kotlin.RequiresOptIn")
     }
-}
-
-readme {
-    maturity = space.kscience.gradle.Maturity.EXPERIMENTAL
-}
+}

examples/src/main/kotlin/space/kscience/kmath/fit/chiSquared.kt

@@ -9,16 +9,21 @@ import kotlinx.html.br
 import kotlinx.html.h3
 import space.kscience.kmath.commons.optimization.CMOptimizer
 import space.kscience.kmath.distributions.NormalDistribution
+import space.kscience.kmath.expressions.DifferentiableExpression
 import space.kscience.kmath.expressions.autodiff
 import space.kscience.kmath.expressions.symbol
 import space.kscience.kmath.operations.asIterable
 import space.kscience.kmath.operations.toList
-import space.kscience.kmath.optimization.*
+import space.kscience.kmath.optimization.minimize
+import space.kscience.kmath.optimization.optimizeWith
+import space.kscience.kmath.optimization.result
+import space.kscience.kmath.optimization.resultValue
 import space.kscience.kmath.random.RandomGenerator
 import space.kscience.kmath.real.DoubleVector
 import space.kscience.kmath.real.map
 import space.kscience.kmath.real.step
 import space.kscience.kmath.stat.chiSquaredExpression
+import space.kscience.kmath.structures.Float64
 import space.kscience.plotly.*
 import space.kscience.plotly.models.ScatterMode
 import space.kscience.plotly.models.TraceValues
@@ -64,7 +69,7 @@ suspend fun main() {
     val yErr = y.map { sqrt(it) }//RealVector.same(x.size, sigma)
 
     // compute differentiable chi^2 sum for given model ax^2 + bx + c
-    val chi2 = Double.autodiff.chiSquaredExpression(x, y, yErr) { arg ->
+    val chi2: DifferentiableExpression<Float64> = Double.autodiff.chiSquaredExpression(x, y, yErr) { arg ->
         //bind variables to autodiff context
         val a = bindSymbol(a)
         val b = bindSymbol(b)
@@ -77,9 +82,10 @@ suspend fun main() {
     val result = chi2.optimizeWith(
         CMOptimizer,
         mapOf(a to 1.5, b to 0.9, c to 1.0),
-    ) {
-        FunctionOptimizationTarget(OptimizationDirection.MINIMIZE)
-    }
+        attributesBuilder = {
+            minimize()
+        }
+    )
 
     //display a page with plot and numerical results
     val page = Plotly.page {

examples/src/main/kotlin/space/kscience/kmath/fit/qowFit.kt

@@ -7,7 +7,6 @@ package space.kscience.kmath.fit
 
 import kotlinx.html.br
 import kotlinx.html.h3
-import space.kscience.attributes.Attributes
 import space.kscience.kmath.data.XYErrorColumnarData
 import space.kscience.kmath.distributions.NormalDistribution
 import space.kscience.kmath.expressions.Symbol
@@ -65,7 +64,9 @@ suspend fun main() {
         QowOptimizer,
         Double.autodiff,
         mapOf(a to 0.9, b to 1.2, c to 2.0, e to 1.0, d to 1.0, e to 0.0),
-        attributes = Attributes(OptimizationParameters, listOf(a, b, c, d))
+        attributesBuilder = {
+            freeParameters(a, b, c, d)
+        },
     ) { arg ->
         //bind variables to autodiff context
         val a by binding

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

@@ -14,11 +14,12 @@ import space.kscience.kmath.integration.gaussIntegrator
 import space.kscience.kmath.integration.integrate
 import space.kscience.kmath.integration.value
 import space.kscience.kmath.operations.Float64Field
+import space.kscience.kmath.structures.Float64
 import kotlin.math.pow
 
 fun main() {
     //Define a function
-    val function: Function1D<Double> = { x -> 3 * x.pow(2) + 2 * x + 1 }
+    val function: Function1D<Float64> = { x -> 3 * x.pow(2) + 2 * x + 1 }
 
     //get the result of the integration
     val result = Float64Field.gaussIntegrator.integrate(0.0..10.0, function = function)

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

@@ -8,6 +8,7 @@ package space.kscience.kmath.functions
 import space.kscience.kmath.interpolation.SplineInterpolator
 import space.kscience.kmath.interpolation.interpolatePolynomials
 import space.kscience.kmath.operations.Float64Field
+import space.kscience.kmath.structures.Float64
 import space.kscience.plotly.Plotly
 import space.kscience.plotly.UnstablePlotlyAPI
 import space.kscience.plotly.makeFile
@@ -23,7 +24,7 @@ fun main() {
         x to sin(x)
     }
 
-    val polynomial: PiecewisePolynomial<Double> = SplineInterpolator(Float64Field).interpolatePolynomials(data)
+    val polynomial: PiecewisePolynomial<Float64> = SplineInterpolator(Float64Field).interpolatePolynomials(data)
 
     val function = polynomial.asFunction(Float64Field, 0.0)
 

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

@@ -10,6 +10,7 @@ import space.kscience.kmath.interpolation.splineInterpolator
 import space.kscience.kmath.operations.Float64Field
 import space.kscience.kmath.real.map
 import space.kscience.kmath.real.step
+import space.kscience.kmath.structures.Float64
 import space.kscience.plotly.Plotly
 import space.kscience.plotly.UnstablePlotlyAPI
 import space.kscience.plotly.makeFile
@@ -18,7 +19,7 @@ import space.kscience.plotly.scatter
 
 @OptIn(UnstablePlotlyAPI::class)
 fun main() {
-    val function: Function1D<Double> = { x ->
+    val function: Function1D<Float64> = { x ->
         if (x in 30.0..50.0) {
             1.0
         } else {
@@ -28,7 +29,7 @@ fun main() {
     val xs = 0.0..100.0 step 0.5
     val ys = xs.map(function)
 
-    val polynomial: PiecewisePolynomial<Double> = Float64Field.splineInterpolator.interpolatePolynomials(xs, ys)
+    val polynomial: PiecewisePolynomial<Float64> = Float64Field.splineInterpolator.interpolatePolynomials(xs, ys)
 
     val polyFunction = polynomial.asFunction(Float64Field, 0.0)
 

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

@@ -12,6 +12,7 @@ import space.kscience.kmath.nd.StructureND
 import space.kscience.kmath.nd.structureND
 import space.kscience.kmath.nd.withNdAlgebra
 import space.kscience.kmath.operations.algebra
+import space.kscience.kmath.structures.Float64
 import kotlin.math.pow
 
 fun main(): Unit = Double.algebra.withNdAlgebra(2, 2) {
@@ -22,7 +23,7 @@ fun main(): Unit = Double.algebra.withNdAlgebra(2, 2) {
     }
 
     //Define a function in a nd space
-    val function: (Double) -> StructureND<Double> = { x: Double -> 3 * x.pow(2) + 2 * diagonal(x) + 1 }
+    val function: (Double) -> StructureND<Float64> = { x: Double -> 3 * x.pow(2) + 2 * diagonal(x) + 1 }
 
     //get the result of the integration
     val result = gaussIntegrator.integrate(0.0..10.0, function = function)

examples/src/main/kotlin/space/kscience/kmath/jafama/JafamaDemo.kt

@@ -1,15 +0,0 @@
-/*
- * Copyright 2018-2024 KMath contributors.
- * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
- */
-
-package space.kscience.kmath.jafama
-
-import space.kscience.kmath.operations.invoke
-
-fun main() {
-    val a = 2.0
-    val b = StrictJafamaDoubleField { exp(a) }
-    println(JafamaDoubleField { b + a })
-    println(StrictJafamaDoubleField { ln(b) })
-}

examples/src/main/kotlin/space/kscience/kmath/linear/eigenValueDecomposition.kt

@@ -0,0 +1,42 @@
+/*
+ * Copyright 2018-2024 KMath contributors.
+ * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
+ */
+
+package space.kscience.kmath.linear
+
+import space.kscience.kmath.PerformancePitfall
+import space.kscience.kmath.commons.linear.CMLinearSpace
+import space.kscience.kmath.ejml.EjmlLinearSpaceDDRM
+import space.kscience.kmath.nd.StructureND
+import space.kscience.kmath.operations.algebra
+import space.kscience.kmath.structures.Float64
+import kotlin.random.Random
+
+@OptIn(PerformancePitfall::class)
+fun main() {
+    val dim = 46
+
+    val random = Random(123)
+
+    val u = Float64.algebra.linearSpace.buildMatrix(dim, dim) { i, j -> if (i <= j) random.nextDouble() else 0.0 }
+
+    listOf(CMLinearSpace, EjmlLinearSpaceDDRM).forEach { algebra ->
+        with(algebra) {
+            //create a symmetric matrix
+            val matrix = buildMatrix(dim, dim) { row, col ->
+                if (row >= col) u[row, col] else u[col, row]
+            }
+            val eigen = matrix.getOrComputeAttribute(EIG) ?: error("Failed to compute eigenvalue decomposition")
+            check(
+                StructureND.contentEquals(
+                    matrix,
+                    eigen.v dot eigen.d dot eigen.v.transposed(),
+                    1e-4
+                )
+            ) { "$algebra decomposition failed" }
+            println("$algebra eigenvalue decomposition complete and checked" )
+        }
+    }
+
+}

examples/src/main/kotlin/space/kscience/kmath/linear/gradient.kt

@@ -6,18 +6,19 @@
 package space.kscience.kmath.linear
 
 import space.kscience.kmath.real.*
+import space.kscience.kmath.structures.Float64
 import space.kscience.kmath.structures.Float64Buffer
 
 fun main() {
     val x0 = DoubleVector(0.0, 0.0, 0.0)
     val sigma = DoubleVector(1.0, 1.0, 1.0)
 
-    val gaussian: (Point<Double>) -> Double = { x ->
+    val gaussian: (Point<Float64>) -> Double = { x ->
         require(x.size == x0.size)
         kotlin.math.exp(-((x - x0) / sigma).square().sum())
     }
 
-    fun ((Point<Double>) -> Double).grad(x: Point<Double>): Point<Double> {
+    fun ((Point<Float64>) -> Double).grad(x: Point<Float64>): Point<Float64> {
         require(x.size == x0.size)
         return Float64Buffer(x.size) { i ->
             val h = sigma[i] / 5

examples/src/main/kotlin/space/kscience/kmath/operations/mixedNDOperations.kt

@@ -6,21 +6,21 @@
 package space.kscience.kmath.operations
 
 import space.kscience.kmath.commons.linear.CMLinearSpace
-import space.kscience.kmath.linear.matrix
+import space.kscience.kmath.linear.MatrixBuilder
+import space.kscience.kmath.linear.fill
 import space.kscience.kmath.nd.Float64BufferND
 import space.kscience.kmath.nd.Structure2D
 import space.kscience.kmath.nd.mutableStructureND
 import space.kscience.kmath.nd.ndAlgebra
+import space.kscience.kmath.structures.Float64
 import space.kscience.kmath.viktor.viktorAlgebra
-import kotlin.collections.component1
-import kotlin.collections.component2
 
 fun main() {
     val viktorStructure = Float64Field.viktorAlgebra.mutableStructureND(2, 2) { (i, j) ->
         if (i == j) 2.0 else 0.0
     }
 
-    val cmMatrix: Structure2D<Double> = CMLinearSpace.matrix(2, 2)(0.0, 1.0, 0.0, 3.0)
+    val cmMatrix: Structure2D<Float64> = CMLinearSpace.MatrixBuilder(2, 2).fill(0.0, 1.0, 0.0, 3.0)
 
     val res: Float64BufferND = Float64Field.ndAlgebra {
         exp(viktorStructure) + 2.0 * cmMatrix

examples/src/main/kotlin/space/kscience/kmath/series/DateTimeSeries.kt

@@ -5,11 +5,13 @@
 
 package space.kscience.kmath.series
 
-import kotlinx.datetime.Instant
 import space.kscience.kmath.operations.algebra
 import space.kscience.kmath.operations.bufferAlgebra
 import kotlin.time.Duration
+import kotlin.time.ExperimentalTime
+import kotlin.time.Instant
 
+@OptIn(ExperimentalTime::class)
 fun SeriesAlgebra.Companion.time(zero: Instant, step: Duration) = MonotonicSeriesAlgebra(
     bufferAlgebra = Double.algebra.bufferAlgebra,
     offsetToLabel = { zero + step * it },

examples/src/main/kotlin/space/kscience/kmath/series/analyzeDif.kt

@@ -14,6 +14,7 @@ import space.kscience.kmath.operations.toList
 import space.kscience.kmath.stat.KMComparisonResult
 import space.kscience.kmath.stat.ksComparisonStatistic
 import space.kscience.kmath.structures.Buffer
+import space.kscience.kmath.structures.Float64
 import space.kscience.kmath.structures.slice
 import space.kscience.plotly.*
 import kotlin.math.PI
@@ -24,7 +25,7 @@ fun Double.Companion.seriesAlgebra() = Double.algebra.bufferAlgebra.seriesAlgebr
 fun main() = with(Double.seriesAlgebra()) {
 
 
-    fun Plot.plotSeries(name: String, buffer: Buffer<Double>) {
+    fun Plot.plotSeries(name: String, buffer: Buffer<Float64>) {
         scatter {
             this.name = name
             x.numbers = buffer.labels
@@ -37,10 +38,10 @@ fun main() = with(Double.seriesAlgebra()) {
 
     val s2 = s1.slice(20..50).moveTo(40)
 
-    val s3: Buffer<Double> = s1.zip(s2) { l, r -> l + r } //s1 + s2
+    val s3: Buffer<Float64> = s1.zip(s2) { l, r -> l + r } //s1 + s2
     val s4 = s3.map { ln(it) }
 
-    val kmTest: KMComparisonResult<Double> = ksComparisonStatistic(s1, s2)
+    val kmTest: KMComparisonResult<Float64> = ksComparisonStatistic(s1, s2)
 
     Plotly.page {
         h1 { +"This is my plot" }

examples/src/main/kotlin/space/kscience/kmath/series/seriesBuilder.kt

@@ -6,10 +6,7 @@
 package space.kscience.kmath.series
 
 
-import space.kscience.kmath.structures.Buffer
-import space.kscience.kmath.structures.Float64Buffer
-import space.kscience.kmath.structures.asBuffer
-import space.kscience.kmath.structures.toDoubleArray
+import space.kscience.kmath.structures.*
 import space.kscience.plotly.*
 import space.kscience.plotly.models.Scatter
 import space.kscience.plotly.models.ScatterMode
@@ -22,7 +19,7 @@ fun main(): Unit = with(Double.seriesAlgebra()) {
     val arrayOfRandoms = DoubleArray(20) { random.nextDouble() }
 
     val series1: Float64Buffer = arrayOfRandoms.asBuffer()
-    val series2: Series<Double> = series1.moveBy(3)
+    val series2: Series<Float64> = series1.moveBy(3)
 
     val res = series2 - series1
 
@@ -30,7 +27,7 @@ fun main(): Unit = with(Double.seriesAlgebra()) {
 
     println(res)
 
-    fun Plot.series(name: String, buffer: Buffer<Double>, block: Scatter.() -> Unit = {}) {
+    fun Plot.series(name: String, buffer: Buffer<Float64>, block: Scatter.() -> Unit = {}) {
         scatter {
             this.name = name
             x.numbers = buffer.offsetIndices

examples/src/main/kotlin/space/kscience/kmath/stat/DistributionBenchmark.kt

@@ -36,8 +36,28 @@ private suspend fun runKMathChained(): Duration {
     return Duration.between(startTime, Instant.now())
 }
 
+private fun runKMathBlocking(): Duration {
+    val generator = RandomGenerator.fromSource(RandomSource.MT, 123L)
+    val normal = GaussianSampler(7.0, 2.0)
+    val chain = normal.sample(generator)
+    val startTime = Instant.now()
+    var sum = 0.0
+
+    repeat(10000001) { counter ->
+        sum += chain.nextBlocking()
+
+        if (counter % 100000 == 0) {
+            val duration = Duration.between(startTime, Instant.now())
+            val meanValue = sum / counter
+            println("Chain sampler completed $counter elements in $duration: $meanValue")
+        }
+    }
+
+    return Duration.between(startTime, Instant.now())
+}
+
 private fun runCMDirect(): Duration {
-    val rng = RandomSource.create(RandomSource.MT, 123L)
+    val rng = RandomSource.MT.create(123L)
 
     val sampler = CMGaussianSampler.of(
         BoxMullerNormalizedGaussianSampler.of(rng),
@@ -67,6 +87,8 @@ private fun runCMDirect(): Duration {
 fun main(): Unit = runBlocking(Dispatchers.Default) {
     val directJob = async { runCMDirect() }
     val chainJob = async { runKMathChained() }
+    val blockingJob = async { runKMathBlocking() }
     println("KMath Chained: ${chainJob.await()}")
+    println("KMath Blocking: ${blockingJob.await()}")
     println("Apache Direct: ${directJob.await()}")
 }

examples/src/main/kotlin/space/kscience/kmath/stat/DistributionDemo.kt

@@ -10,13 +10,14 @@ import space.kscience.kmath.chains.Chain
 import space.kscience.kmath.chains.combineWithState
 import space.kscience.kmath.distributions.NormalDistribution
 import space.kscience.kmath.random.RandomGenerator
+import space.kscience.kmath.structures.Float64
 
 private data class AveragingChainState(var num: Int = 0, var value: Double = 0.0)
 
 /**
  * Averaging.
  */
-private fun Chain<Double>.mean(): Chain<Double> = combineWithState(AveragingChainState(), { it.copy() }) { chain ->
+private fun Chain<Float64>.mean(): Chain<Float64> = combineWithState(AveragingChainState(), { it.copy() }) { chain ->
     val next = chain.next()
     num++
     value += next

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

@@ -26,7 +26,7 @@ fun main() {
 
     val realTime = measureTimeMillis {
         realField {
-            var res: StructureND<Double> = one
+            var res: StructureND<Float64> = one
             repeat(n) {
                 res += 1.0
             }

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

@@ -7,9 +7,7 @@ package space.kscience.kmath.structures
 
 import kotlinx.coroutines.DelicateCoroutinesApi
 import kotlinx.coroutines.GlobalScope
-import org.nd4j.linalg.factory.Nd4j
 import space.kscience.kmath.nd.*
-import space.kscience.kmath.nd4j.nd4j
 import space.kscience.kmath.operations.Float64Field
 import space.kscience.kmath.operations.invoke
 import space.kscience.kmath.viktor.ViktorFieldND
@@ -26,7 +24,6 @@ internal inline fun measureAndPrint(title: String, block: () -> Unit) {
 @OptIn(DelicateCoroutinesApi::class)
 fun main() {
     // initializing Nd4j
-    Nd4j.zeros(0)
     val dim = 1000
     val n = 1000
     val shape = ShapeND(dim, dim)
@@ -36,8 +33,6 @@ fun main() {
     val doubleField = Float64Field.ndAlgebra
     //A generic field. It should be used for objects, not primitives.
     val genericField = BufferedFieldOpsND(Float64Field)
-    // Nd4j specialized field.
-    val nd4jField = Float64Field.nd4j
     //viktor field
     val viktorField = ViktorFieldND(dim, dim)
     //parallel processing based on Java Streams
@@ -45,35 +40,28 @@ fun main() {
 
     measureAndPrint("Boxing addition") {
         genericField {
-            var res: StructureND<Double> = one(shape)
+            var res: StructureND<Float64> = one(shape)
             repeat(n) { res += 1.0 }
         }
     }
 
     measureAndPrint("Specialized addition") {
         doubleField {
-            var res: StructureND<Double> = one(shape)
-            repeat(n) { res += 1.0 }
-        }
-    }
-
-    measureAndPrint("Nd4j specialized addition") {
-        nd4jField {
-            var res: StructureND<Double> = one(shape)
+            var res: StructureND<Float64> = one(shape)
             repeat(n) { res += 1.0 }
         }
     }
 
     measureAndPrint("Viktor addition") {
         viktorField {
-            var res: StructureND<Double> = one
+            var res: StructureND<Float64> = one
             repeat(n) { res += 1.0 }
         }
     }
 
     measureAndPrint("Parallel stream addition") {
         parallelField {
-            var res: StructureND<Double> = one
+            var res: StructureND<Float64> = one
             repeat(n) { res += 1.0 }
         }
     }

examples/src/main/kotlin/space/kscience/kmath/structures/StreamDoubleFieldND.kt

@@ -19,23 +19,23 @@ import java.util.stream.IntStream
  * execution.
  */
 class StreamDoubleFieldND(override val shape: ShapeND) : FieldND<Double, Float64Field>,
-    NumbersAddOps<StructureND<Double>>,
-    ExtendedField<StructureND<Double>> {
+    NumbersAddOps<StructureND<Float64>>,
+    ExtendedField<StructureND<Float64>> {
 
     private val strides = ColumnStrides(shape)
     override val elementAlgebra: Float64Field get() = Float64Field
-    override val zero: BufferND<Double> by lazy { structureND(shape) { zero } }
-    override val one: BufferND<Double> by lazy { structureND(shape) { one } }
+    override val zero: BufferND<Float64> by lazy { structureND(shape) { zero } }
+    override val one: BufferND<Float64> by lazy { structureND(shape) { one } }
 
-    override fun number(value: Number): BufferND<Double> {
+    override fun number(value: Number): BufferND<Float64> {
         val d = value.toDouble() // minimize conversions
         return structureND(shape) { d }
     }
 
     @OptIn(PerformancePitfall::class)
-    private val StructureND<Double>.buffer: Float64Buffer
+    private val StructureND<Float64>.buffer: Float64Buffer
         get() = when {
-            !shape.contentEquals(this@StreamDoubleFieldND.shape) -> throw ShapeMismatchException(
+            shape != this@StreamDoubleFieldND.shape -> throw ShapeMismatchException(
                 this@StreamDoubleFieldND.shape,
                 shape
             )
@@ -44,7 +44,7 @@ class StreamDoubleFieldND(override val shape: ShapeND) : FieldND<Double, Float64
             else -> Float64Buffer(strides.linearSize) { offset -> get(strides.index(offset)) }
         }
 
-    override fun structureND(shape: ShapeND, initializer: Float64Field.(IntArray) -> Double): BufferND<Double> {
+    override fun structureND(shape: ShapeND, initializer: Float64Field.(IntArray) -> Double): BufferND<Float64> {
         val array = IntStream.range(0, strides.linearSize).parallel().mapToDouble { offset ->
             val index = strides.index(offset)
             Float64Field.initializer(index)
@@ -56,7 +56,7 @@ class StreamDoubleFieldND(override val shape: ShapeND) : FieldND<Double, Float64
     override fun mutableStructureND(
         shape: ShapeND,
         initializer: DoubleField.(IntArray) -> Double,
-    ): MutableBufferND<Double> {
+    ): MutableBufferND<Float64> {
         val array = IntStream.range(0, strides.linearSize).parallel().mapToDouble { offset ->
             val index = strides.index(offset)
             DoubleField.initializer(index)
@@ -66,17 +66,17 @@ class StreamDoubleFieldND(override val shape: ShapeND) : FieldND<Double, Float64
     }
 
     @OptIn(PerformancePitfall::class)
-    override fun StructureND<Double>.map(
+    override fun StructureND<Float64>.map(
         transform: Float64Field.(Double) -> Double,
-    ): BufferND<Double> {
+    ): BufferND<Float64> {
         val array = Arrays.stream(buffer.array).parallel().map { Float64Field.transform(it) }.toArray()
         return BufferND(strides, array.asBuffer())
     }
 
     @OptIn(PerformancePitfall::class)
-    override fun StructureND<Double>.mapIndexed(
+    override fun StructureND<Float64>.mapIndexed(
         transform: Float64Field.(index: IntArray, Double) -> Double,
-    ): BufferND<Double> {
+    ): BufferND<Float64> {
         val array = IntStream.range(0, strides.linearSize).parallel().mapToDouble { offset ->
             Float64Field.transform(
                 strides.index(offset),
@@ -89,39 +89,39 @@ class StreamDoubleFieldND(override val shape: ShapeND) : FieldND<Double, Float64
 
     @OptIn(PerformancePitfall::class)
     override fun zip(
-        left: StructureND<Double>,
-        right: StructureND<Double>,
+        left: StructureND<Float64>,
+        right: StructureND<Float64>,
         transform: Float64Field.(Double, Double) -> Double,
-    ): BufferND<Double> {
+    ): BufferND<Float64> {
         val array = IntStream.range(0, strides.linearSize).parallel().mapToDouble { offset ->
             Float64Field.transform(left.buffer.array[offset], right.buffer.array[offset])
         }.toArray()
         return BufferND(strides, array.asBuffer())
     }
 
-    override fun StructureND<Double>.unaryMinus(): StructureND<Double> = map { -it }
+    override fun StructureND<Float64>.unaryMinus(): StructureND<Float64> = map { -it }
 
-    override fun scale(a: StructureND<Double>, value: Double): StructureND<Double> = a.map { it * value }
+    override fun scale(a: StructureND<Float64>, value: Double): StructureND<Float64> = a.map { it * value }
 
-    override fun power(arg: StructureND<Double>, pow: Number): BufferND<Double> = arg.map { power(it, pow) }
+    override fun power(arg: StructureND<Float64>, pow: Number): BufferND<Float64> = arg.map { power(it, pow) }
 
-    override fun exp(arg: StructureND<Double>): BufferND<Double> = arg.map { exp(it) }
+    override fun exp(arg: StructureND<Float64>): BufferND<Float64> = arg.map { exp(it) }
 
-    override fun ln(arg: StructureND<Double>): BufferND<Double> = arg.map { ln(it) }
+    override fun ln(arg: StructureND<Float64>): BufferND<Float64> = arg.map { ln(it) }
 
-    override fun sin(arg: StructureND<Double>): BufferND<Double> = arg.map { sin(it) }
-    override fun cos(arg: StructureND<Double>): BufferND<Double> = arg.map { cos(it) }
-    override fun tan(arg: StructureND<Double>): BufferND<Double> = arg.map { tan(it) }
-    override fun asin(arg: StructureND<Double>): BufferND<Double> = arg.map { asin(it) }
-    override fun acos(arg: StructureND<Double>): BufferND<Double> = arg.map { acos(it) }
-    override fun atan(arg: StructureND<Double>): BufferND<Double> = arg.map { atan(it) }
+    override fun sin(arg: StructureND<Float64>): BufferND<Float64> = arg.map { sin(it) }
+    override fun cos(arg: StructureND<Float64>): BufferND<Float64> = arg.map { cos(it) }
+    override fun tan(arg: StructureND<Float64>): BufferND<Float64> = arg.map { tan(it) }
+    override fun asin(arg: StructureND<Float64>): BufferND<Float64> = arg.map { asin(it) }
+    override fun acos(arg: StructureND<Float64>): BufferND<Float64> = arg.map { acos(it) }
+    override fun atan(arg: StructureND<Float64>): BufferND<Float64> = arg.map { atan(it) }
 
-    override fun sinh(arg: StructureND<Double>): BufferND<Double> = arg.map { sinh(it) }
-    override fun cosh(arg: StructureND<Double>): BufferND<Double> = arg.map { cosh(it) }
-    override fun tanh(arg: StructureND<Double>): BufferND<Double> = arg.map { tanh(it) }
-    override fun asinh(arg: StructureND<Double>): BufferND<Double> = arg.map { asinh(it) }
-    override fun acosh(arg: StructureND<Double>): BufferND<Double> = arg.map { acosh(it) }
-    override fun atanh(arg: StructureND<Double>): BufferND<Double> = arg.map { atanh(it) }
+    override fun sinh(arg: StructureND<Float64>): BufferND<Float64> = arg.map { sinh(it) }
+    override fun cosh(arg: StructureND<Float64>): BufferND<Float64> = arg.map { cosh(it) }
+    override fun tanh(arg: StructureND<Float64>): BufferND<Float64> = arg.map { tanh(it) }
+    override fun asinh(arg: StructureND<Float64>): BufferND<Float64> = arg.map { asinh(it) }
+    override fun acosh(arg: StructureND<Float64>): BufferND<Float64> = arg.map { acosh(it) }
+    override fun atanh(arg: StructureND<Float64>): BufferND<Float64> = arg.map { atanh(it) }
 }
 
 fun Float64Field.ndStreaming(vararg shape: Int): StreamDoubleFieldND = StreamDoubleFieldND(ShapeND(shape))

examples/src/main/kotlin/space/kscience/kmath/structures/mutableNd.kt

@@ -11,7 +11,7 @@ import space.kscience.kmath.operations.algebra
 
 @OptIn(PerformancePitfall::class)
 fun main(): Unit = with(Double.algebra.ndAlgebra) {
-    val structure: MutableStructure2D<Double> = mutableStructureND(ShapeND(2, 2)) { (i, j) ->
+    val structure: MutableStructure2D<Float64> = mutableStructureND(ShapeND(2, 2)) { (i, j) ->
         i.toDouble() + j.toDouble()
     }.as2D()
 

examples/src/main/kotlin/space/kscience/kmath/tensors/LevenbergMarquardt/StreamingLm/streamLm.kt

@@ -12,6 +12,7 @@ import space.kscience.kmath.nd.MutableStructure2D
 import space.kscience.kmath.nd.ShapeND
 import space.kscience.kmath.nd.as2D
 import space.kscience.kmath.nd.component1
+import space.kscience.kmath.structures.Float64
 import space.kscience.kmath.tensors.LevenbergMarquardt.StartDataLm
 import space.kscience.kmath.tensors.core.BroadcastDoubleTensorAlgebra.zeros
 import space.kscience.kmath.tensors.core.DoubleTensorAlgebra
@@ -20,9 +21,9 @@ import space.kscience.kmath.tensors.core.levenbergMarquardt
 import kotlin.random.Random
 
 fun streamLm(
-    lm_func: (MutableStructure2D<Double>, MutableStructure2D<Double>, Int) -> (MutableStructure2D<Double>),
+    lm_func: (MutableStructure2D<Float64>, MutableStructure2D<Float64>, Int) -> (MutableStructure2D<Float64>),
     startData: StartDataLm, launchFrequencyInMs: Long, numberOfLaunches: Int,
-): Flow<MutableStructure2D<Double>> = flow {
+): Flow<MutableStructure2D<Float64>> = flow {
 
     var example_number = startData.example_number
     var p_init = startData.p_init
@@ -64,7 +65,7 @@ fun streamLm(
     }
 }
 
-fun generateNewYDat(y_dat: MutableStructure2D<Double>, delta: Double): MutableStructure2D<Double> {
+fun generateNewYDat(y_dat: MutableStructure2D<Float64>, delta: Double): MutableStructure2D<Float64> {
     val n = y_dat.shape.component1()
     val y_dat_new = zeros(ShapeND(intArrayOf(n, 1))).as2D()
     for (i in 0 until n) {

examples/src/main/kotlin/space/kscience/kmath/tensors/LevenbergMarquardt/functionsToOptimize.kt

@@ -9,6 +9,7 @@ import space.kscience.kmath.nd.MutableStructure2D
 import space.kscience.kmath.nd.ShapeND
 import space.kscience.kmath.nd.as2D
 import space.kscience.kmath.nd.component1
+import space.kscience.kmath.structures.Float64
 import space.kscience.kmath.tensors.core.BroadcastDoubleTensorAlgebra
 import space.kscience.kmath.tensors.core.BroadcastDoubleTensorAlgebra.div
 import space.kscience.kmath.tensors.core.DoubleTensorAlgebra
@@ -19,24 +20,24 @@ import space.kscience.kmath.tensors.core.DoubleTensorAlgebra.Companion.times
 import space.kscience.kmath.tensors.core.asDoubleTensor
 
 public data class StartDataLm(
-    var lm_matx_y_dat: MutableStructure2D<Double>,
+    var lm_matx_y_dat: MutableStructure2D<Float64>,
     var example_number: Int,
-    var p_init: MutableStructure2D<Double>,
-    var t: MutableStructure2D<Double>,
-    var y_dat: MutableStructure2D<Double>,
+    var p_init: MutableStructure2D<Float64>,
+    var t: MutableStructure2D<Float64>,
+    var y_dat: MutableStructure2D<Float64>,
     var weight: Double,
-    var dp: MutableStructure2D<Double>,
-    var p_min: MutableStructure2D<Double>,
-    var p_max: MutableStructure2D<Double>,
-    var consts: MutableStructure2D<Double>,
+    var dp: MutableStructure2D<Float64>,
+    var p_min: MutableStructure2D<Float64>,
+    var p_max: MutableStructure2D<Float64>,
+    var consts: MutableStructure2D<Float64>,
     var opts: DoubleArray,
 )
 
 fun funcEasyForLm(
-    t: MutableStructure2D<Double>,
-    p: MutableStructure2D<Double>,
+    t: MutableStructure2D<Float64>,
+    p: MutableStructure2D<Float64>,
     exampleNumber: Int,
-): MutableStructure2D<Double> {
+): MutableStructure2D<Float64> {
     val m = t.shape.component1()
     var y_hat = DoubleTensorAlgebra.zeros(ShapeND(intArrayOf(m, 1)))
 
@@ -59,10 +60,10 @@ fun funcEasyForLm(
 }
 
 fun funcMiddleForLm(
-    t: MutableStructure2D<Double>,
-    p: MutableStructure2D<Double>,
+    t: MutableStructure2D<Float64>,
+    p: MutableStructure2D<Float64>,
     exampleNumber: Int,
-): MutableStructure2D<Double> {
+): MutableStructure2D<Float64> {
     val m = t.shape.component1()
     var y_hat = DoubleTensorAlgebra.zeros(ShapeND(intArrayOf(m, 1)))
 
@@ -79,10 +80,10 @@ fun funcMiddleForLm(
 }
 
 fun funcDifficultForLm(
-    t: MutableStructure2D<Double>,
-    p: MutableStructure2D<Double>,
+    t: MutableStructure2D<Float64>,
+    p: MutableStructure2D<Float64>,
     exampleNumber: Int,
-): MutableStructure2D<Double> {
+): MutableStructure2D<Float64> {
     val m = t.shape.component1()
     var y_hat = DoubleTensorAlgebra.zeros(ShapeND(intArrayOf(m, 1)))
 

examples/src/main/kotlin/space/kscience/kmath/tensors/OLSWithSVD.kt

@@ -6,7 +6,6 @@
 package space.kscience.kmath.tensors
 
 import space.kscience.kmath.nd.ShapeND
-import space.kscience.kmath.nd.contentEquals
 import space.kscience.kmath.operations.invoke
 import space.kscience.kmath.tensors.core.DoubleTensor
 import space.kscience.kmath.tensors.core.DoubleTensorAlgebra
@@ -62,7 +61,7 @@ fun main() {
         // figure out MSE of approximation
         fun mse(yTrue: DoubleTensor, yPred: DoubleTensor): Double {
             require(yTrue.shape.size == 1)
-            require(yTrue.shape contentEquals yPred.shape)
+            require(yTrue.shape == yPred.shape)
 
             val diff = yTrue - yPred
             return sqrt(diff.dot(diff)).value()

examples/src/main/kotlin/space/kscience/kmath/tensors/multik.kt

@@ -10,12 +10,13 @@ import org.jetbrains.kotlinx.multik.api.ndarray
 import org.jetbrains.kotlinx.multik.default.DefaultEngine
 import space.kscience.kmath.multik.MultikDoubleAlgebra
 import space.kscience.kmath.nd.one
+import space.kscience.kmath.structures.Float64
 
 
 val multikAlgebra = MultikDoubleAlgebra(DefaultEngine())
 
 fun main(): Unit = with(multikAlgebra) {
-    val a = Multik.ndarray(intArrayOf(1, 2, 3)).asType<Double>().wrap()
+    val a = Multik.ndarray(intArrayOf(1, 2, 3)).asType<Float64>().wrap()
     val b = Multik.ndarray(doubleArrayOf(1.0, 2.0, 3.0)).wrap()
     one(a.shape) - a + b * 3.0
 }

examples/src/main/kotlin/space/kscience/kmath/tensors/neuralNetwork.kt

@@ -6,7 +6,6 @@
 package space.kscience.kmath.tensors
 
 import space.kscience.kmath.nd.ShapeND
-import space.kscience.kmath.nd.contentEquals
 import space.kscience.kmath.operations.asIterable
 import space.kscience.kmath.operations.invoke
 import space.kscience.kmath.tensors.core.*
@@ -94,7 +93,7 @@ class Dense(
 
 // simple accuracy equal to the proportion of correct answers
 fun accuracy(yPred: DoubleTensor, yTrue: DoubleTensor): Double {
-    check(yPred.shape contentEquals yTrue.shape)
+    check(yPred.shape == yTrue.shape)
     val n = yPred.shape[0]
     var correctCnt = 0
     for (i in 0 until n) {

gradle.properties

@@ -2,14 +2,14 @@
 # Copyright 2018-2021 KMath contributors.
 # Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
 #
-kotlin.code.style=official
-kotlin.mpp.stability.nowarn=true
-kotlin.native.ignoreDisabledTargets=true
-org.gradle.configureondemand=true
 org.gradle.jvmargs=-Xmx4096m
 org.gradle.parallel=true
 org.gradle.workers.max=4
 
-toolsVersion=0.15.2-kotlin-2.0.0-RC2
-#kotlin.experimental.tryK2=true
-#kscience.wasm.disabled=true
+kotlin.code.style=official
+kotlin.mpp.stability.nowarn=true
+kotlin.native.ignoreDisabledTargets=true
+org.jetbrains.dokka.experimental.gradle.pluginMode=V2Enabled
+kotlin.native.enableKlibsCrossCompilation=true
+
+toolsVersion=0.20.2-kotlin-2.3.0

gradle/libs.versions.toml

@@ -0,0 +1,28 @@
+[versions]
+
+commons-rng = "1.6"
+multik = "0.2.3"
+nd4j = "1.0.0-M2.1"
+tensorflow = "1.1.0"
+
+[libraries]
+attributes = "space.kscience:attributes-kt:0.4.0"
+
+commons-math = "org.apache.commons:commons-math3:3.6.1"
+
+commons-rng-simple = { module = "org.apache.commons:commons-rng-simple", version.ref = "commons-rng" }
+commons-rng-sampling = { module = "org.apache.commons:commons-rng-sampling", version.ref = "commons-rng" }
+
+multik-core = { module = "org.jetbrains.kotlinx:multik-core", version.ref = "multik" }
+multik-default = { module = "org.jetbrains.kotlinx:multik-default", version.ref = "multik" }
+
+nd4j-api = { module = "org.nd4j:nd4j-api", version.ref = "nd4j" }
+nd4j-native-platform = { module = "org.nd4j:nd4j-native-platform", version.ref = "nd4j" }
+
+ojalgo = "org.ojalgo:ojalgo:56.2.0"
+
+
+tensorflow-core-api = {module = "org.tensorflow:tensorflow-core-api", version.ref="tensorflow"}
+tensorflow-core-platform = {module = "org.tensorflow:tensorflow-core-platform", version.ref="tensorflow"}
+
+[plugins]

gradle/wrapper/gradle-wrapper.properties

@@ -1,5 +1,5 @@
 distributionBase=GRADLE_USER_HOME
 distributionPath=wrapper/dists
-distributionUrl=https\://services.gradle.org/distributions/gradle-8.7-bin.zip
+distributionUrl=https\://services.gradle.org/distributions/gradle-9.2.1-bin.zip
 zipStoreBase=GRADLE_USER_HOME
 zipStorePath=wrapper/dists

kmath-ast/README.md

@@ -10,7 +10,7 @@ Extensions to MST API: transformations, dynamic compilation and visualization.
 
 ## Artifact:
 
-The Maven coordinates of this project are `space.kscience:kmath-ast:0.4.0`.
+The Maven coordinates of this project are `space.kscience:kmath-ast:0.5.0`.
 
 **Gradle Kotlin DSL:**
 ```kotlin
@@ -20,7 +20,7 @@ repositories {
 }
 
 dependencies {
-    implementation("space.kscience:kmath-ast:0.4.0")
+    implementation("space.kscience:kmath-ast:0.5.0")
 }
 ```
 

kmath-ast/build.gradle.kts

@@ -4,7 +4,24 @@ plugins {
 
 kscience {
     jvm()
-    js()
+    js{
+        nodejs {
+            testTask {
+                useMocha {
+                    timeout = "0"
+                }
+            }
+        }
+
+        browser {
+            useCommonJs()
+            testTask {
+                useMocha {
+                    timeout = "0"
+                }
+            }
+        }
+    }
     native()
 
     dependencies {
@@ -18,30 +35,17 @@ kscience {
 
     dependencies(jsMain) {
         implementation(npm("astring", "1.7.5"))
-        implementation(npm("binaryen", "101.0.0"))
+        implementation(npm("binaryen", "117.0.0"))
         implementation(npm("js-base64", "3.6.1"))
     }
 
     dependencies(jvmMain) {
-        implementation("org.ow2.asm:asm-commons:9.2")
+        implementation("org.ow2.asm:asm-commons:9.7.1")
     }
 
 }
 
 kotlin {
-    js {
-        nodejs {
-            testTask {
-                useMocha().timeout = "0"
-            }
-        }
-
-        browser {
-            testTask {
-                useMocha().timeout = "0"
-            }
-        }
-    }
 
     sourceSets {
         filter { it.name.contains("test", true) }
@@ -50,7 +54,7 @@ kotlin {
     }
 }
 
-if (System.getProperty("space.kscience.kmath.ast.dump.generated.classes") == "1") {
+if (project.properties["space.kscience.kmath.ast.dump.generated.classes"] == "1") {
     tasks.withType<org.jetbrains.kotlin.gradle.targets.jvm.tasks.KotlinJvmTest> {
         jvmArgs("-Dspace.kscience.kmath.ast.dump.generated.classes=1")
     }

kmath-ast/src/commonTest/kotlin/space/kscience/kmath/ast/TestFolding.kt

@@ -9,6 +9,7 @@ import space.kscience.kmath.operations.Float64Field
 import space.kscience.kmath.operations.Int32Ring
 import space.kscience.kmath.operations.Int8Ring
 import space.kscience.kmath.operations.pi
+import space.kscience.kmath.structures.Float64
 import kotlin.test.Test
 import kotlin.test.assertEquals
 import kotlin.test.fail
@@ -41,7 +42,7 @@ internal class TestFolding {
     @Test
     fun foldSymbol() = assertEquals(
         Float64Field.pi,
-        ("pi".parseMath().evaluateConstants(Float64Field) as? TypedMst.Constant<Double> ?: fail()).value,
+        ("pi".parseMath().evaluateConstants(Float64Field) as? TypedMst.Constant<Float64> ?: fail()).value,
     )
 
     @Test

kmath-ast/src/commonTest/kotlin/space/kscience/kmath/ast/utils.kt

@@ -10,12 +10,13 @@ import space.kscience.kmath.expressions.MST
 import space.kscience.kmath.expressions.Symbol
 import space.kscience.kmath.operations.Float64Field
 import space.kscience.kmath.operations.Int32Ring
+import space.kscience.kmath.structures.Float64
 
 internal interface CompilerTestContext {
     fun MST.compileToExpression(algebra: Int32Ring): Expression<Int>
     fun MST.compile(algebra: Int32Ring, arguments: Map<Symbol, Int>): Int
     fun MST.compile(algebra: Int32Ring, vararg arguments: Pair<Symbol, Int>): Int = compile(algebra, mapOf(*arguments))
-    fun MST.compileToExpression(algebra: Float64Field): Expression<Double>
+    fun MST.compileToExpression(algebra: Float64Field): Expression<Float64>
     fun MST.compile(algebra: Float64Field, arguments: Map<Symbol, Double>): Double
 
     fun MST.compile(algebra: Float64Field, vararg arguments: Pair<Symbol, Double>): Double =

kmath-ast/src/jsMain/kotlin/space/kscience/kmath/wasm/internal/WasmBuilder.kt

@@ -11,6 +11,7 @@ import space.kscience.kmath.expressions.*
 import space.kscience.kmath.internal.binaryen.*
 import space.kscience.kmath.internal.webassembly.Instance
 import space.kscience.kmath.operations.*
+import space.kscience.kmath.structures.Float64
 import space.kscience.kmath.internal.binaryen.Module as BinaryenModule
 import space.kscience.kmath.internal.webassembly.Module as WasmModule
 
@@ -85,13 +86,13 @@ internal sealed class WasmBuilder<T : Number, out E : Expression<T>>(
 }
 
 @UnstableKMathAPI
-internal class DoubleWasmBuilder(target: TypedMst<Double>) :
+internal class DoubleWasmBuilder(target: TypedMst<Float64>) :
     WasmBuilder<Double, DoubleExpression>(f64, Float64Field, target) {
     override val instance by lazy {
         object : DoubleExpression {
             override val indexer = SimpleSymbolIndexer(keys)
 
-            override fun invoke(arguments: DoubleArray) = spreader(executable, arguments).unsafeCast<Double>()
+            override fun invoke(arguments: DoubleArray) = spreader(executable, arguments).unsafeCast<Float64>()
         }
     }
 
@@ -99,7 +100,7 @@ internal class DoubleWasmBuilder(target: TypedMst<Double>) :
 
     override fun visitNumber(number: Number) = ctx.f64.const(number.toDouble())
 
-    override fun visitUnary(node: TypedMst.Unary<Double>): ExpressionRef = when (node.operation) {
+    override fun visitUnary(node: TypedMst.Unary<Float64>): ExpressionRef = when (node.operation) {
         GroupOps.MINUS_OPERATION -> ctx.f64.neg(visit(node.value))
         GroupOps.PLUS_OPERATION -> visit(node.value)
         PowerOperations.SQRT_OPERATION -> ctx.f64.sqrt(visit(node.value))
@@ -120,7 +121,7 @@ internal class DoubleWasmBuilder(target: TypedMst<Double>) :
         else -> super.visitUnary(node)
     }
 
-    override fun visitBinary(mst: TypedMst.Binary<Double>): ExpressionRef = when (mst.operation) {
+    override fun visitBinary(mst: TypedMst.Binary<Float64>): ExpressionRef = when (mst.operation) {
         GroupOps.PLUS_OPERATION -> ctx.f64.add(visit(mst.left), visit(mst.right))
         GroupOps.MINUS_OPERATION -> ctx.f64.sub(visit(mst.left), visit(mst.right))
         RingOps.TIMES_OPERATION -> ctx.f64.mul(visit(mst.left), visit(mst.right))

kmath-ast/src/jsMain/kotlin/space/kscience/kmath/wasm/wasm.kt

@@ -13,6 +13,7 @@ import space.kscience.kmath.ast.evaluateConstants
 import space.kscience.kmath.expressions.*
 import space.kscience.kmath.operations.Float64Field
 import space.kscience.kmath.operations.Int32Ring
+import space.kscience.kmath.structures.Float64
 import space.kscience.kmath.wasm.internal.DoubleWasmBuilder
 import space.kscience.kmath.wasm.internal.IntWasmBuilder
 
@@ -58,7 +59,7 @@ public fun MST.compile(algebra: Int32Ring, vararg arguments: Pair<Symbol, Int>):
  * @author Iaroslav Postovalov
  */
 @UnstableKMathAPI
-public fun MST.compileToExpression(algebra: Float64Field): Expression<Double> {
+public fun MST.compileToExpression(algebra: Float64Field): Expression<Float64> {
     val typed = evaluateConstants(algebra)
 
     return if (typed is TypedMst.Constant) object : DoubleExpression {

kmath-ast/src/jsTest/kotlin/space/kscience/kmath/ast/utils.kt

@@ -13,6 +13,7 @@ import space.kscience.kmath.expressions.MST
 import space.kscience.kmath.expressions.Symbol
 import space.kscience.kmath.operations.Float64Field
 import space.kscience.kmath.operations.Int32Ring
+import space.kscience.kmath.structures.Float64
 import kotlin.contracts.InvocationKind
 import kotlin.contracts.contract
 import space.kscience.kmath.estree.compile as estreeCompile
@@ -21,19 +22,19 @@ import space.kscience.kmath.wasm.compile as wasmCompile
 import space.kscience.kmath.wasm.compileToExpression as wasmCompileToExpression
 
 @OptIn(UnstableKMathAPI::class)
-private object WasmCompilerTestContext : CompilerTestContext {
+internal object WasmCompilerTestContext : CompilerTestContext {
     override fun MST.compileToExpression(algebra: Int32Ring): Expression<Int> = wasmCompileToExpression(algebra)
     override fun MST.compile(algebra: Int32Ring, arguments: Map<Symbol, Int>): Int = wasmCompile(algebra, arguments)
-    override fun MST.compileToExpression(algebra: Float64Field): Expression<Double> = wasmCompileToExpression(algebra)
+    override fun MST.compileToExpression(algebra: Float64Field): Expression<Float64> = wasmCompileToExpression(algebra)
 
     override fun MST.compile(algebra: Float64Field, arguments: Map<Symbol, Double>): Double =
         wasmCompile(algebra, arguments)
 }
 
-private object ESTreeCompilerTestContext : CompilerTestContext {
+internal object ESTreeCompilerTestContext : CompilerTestContext {
     override fun MST.compileToExpression(algebra: Int32Ring): Expression<Int> = estreeCompileToExpression(algebra)
     override fun MST.compile(algebra: Int32Ring, arguments: Map<Symbol, Int>): Int = estreeCompile(algebra, arguments)
-    override fun MST.compileToExpression(algebra: Float64Field): Expression<Double> = estreeCompileToExpression(algebra)
+    override fun MST.compileToExpression(algebra: Float64Field): Expression<Float64> = estreeCompileToExpression(algebra)
 
     override fun MST.compile(algebra: Float64Field, arguments: Map<Symbol, Double>): Double =
         estreeCompile(algebra, arguments)

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

@@ -19,7 +19,7 @@ internal abstract class AsmBuilder {
 
     protected val classLoader = ByteArrayClassLoader(javaClass.classLoader)
 
-    protected companion object {
+    companion object {
         /**
          * ASM type for [Expression].
          */

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

@@ -5,11 +5,16 @@
 
 package space.kscience.kmath.asm.internal
 
-import org.objectweb.asm.*
+import org.objectweb.asm.ClassWriter
+import org.objectweb.asm.FieldVisitor
 import org.objectweb.asm.Opcodes.*
+import org.objectweb.asm.Type
 import org.objectweb.asm.Type.*
 import org.objectweb.asm.commons.InstructionAdapter
-import space.kscience.kmath.expressions.*
+import space.kscience.kmath.expressions.Expression
+import space.kscience.kmath.expressions.MST
+import space.kscience.kmath.expressions.Symbol
+import space.kscience.kmath.expressions.invoke
 import java.lang.invoke.MethodHandles
 import java.lang.invoke.MethodType
 import java.nio.file.Paths
@@ -24,6 +29,7 @@ import kotlin.io.path.writeBytes
  * @property expressionResultCallback the function to apply to this object when generating expression value.
  * @author Iaroslav Postovalov
  */
+@Suppress("PLATFORM_CLASS_MAPPED_TO_KOTLIN")
 internal class GenericAsmBuilder<T>(
     classOfT: Class<*>,
     private val className: String,

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

@@ -15,6 +15,7 @@ import space.kscience.kmath.UnstableKMathAPI
 import space.kscience.kmath.ast.TypedMst
 import space.kscience.kmath.expressions.*
 import space.kscience.kmath.operations.*
+import space.kscience.kmath.structures.Float64
 import java.lang.invoke.MethodHandles
 import java.lang.invoke.MethodType
 import java.nio.file.Paths
@@ -74,7 +75,7 @@ internal sealed class PrimitiveAsmBuilder<T : Number, out E : Expression<T>>(
     val instance: E by lazy {
         val classWriter = ClassWriter(ClassWriter.COMPUTE_FRAMES) {
             visit(
-                V1_8,
+                V11,
                 ACC_PUBLIC or ACC_FINAL or ACC_SUPER,
                 classType.internalName,
                 "${OBJECT_TYPE.descriptor}${expressionParentType.descriptor}",
@@ -371,17 +372,17 @@ internal sealed class PrimitiveAsmBuilder<T : Number, out E : Expression<T>>(
         /**
          * ASM type for [java.lang.Number].
          */
-        val NUMBER_TYPE: Type = getObjectType("java/lang/Number")
+        val NUMBER_TYPE: Type = getType(Number::class.java)
 
         /**
          * ASM type for [SymbolIndexer].
          */
-        val SYMBOL_INDEXER_TYPE: Type = getObjectType("space/kscience/kmath/expressions/SymbolIndexer")
+        val SYMBOL_INDEXER_TYPE: Type = getType(SymbolIndexer::class.java)
     }
 }
 
 @UnstableKMathAPI
-internal class DoubleAsmBuilder(target: TypedMst<Double>) : PrimitiveAsmBuilder<Double, DoubleExpression>(
+internal class DoubleAsmBuilder(target: TypedMst<Float64>) : PrimitiveAsmBuilder<Double, DoubleExpression>(
     Float64Field,
     java.lang.Double::class.java,
     java.lang.Double.TYPE,
@@ -410,7 +411,7 @@ internal class DoubleAsmBuilder(target: TypedMst<Double>) : PrimitiveAsmBuilder<
         false,
     )
 
-    override fun visitUnary(node: TypedMst.Unary<Double>) {
+    override fun visitUnary(node: TypedMst.Unary<Float64>) {
         super.visitUnary(node)
 
         when (node.operation) {
@@ -435,7 +436,7 @@ internal class DoubleAsmBuilder(target: TypedMst<Double>) : PrimitiveAsmBuilder<
         }
     }
 
-    override fun visitBinary(node: TypedMst.Binary<Double>) {
+    override fun visitBinary(node: TypedMst.Binary<Float64>) {
         super.visitBinary(node)
 
         when (node.operation) {

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

@@ -73,7 +73,6 @@ internal tailrec fun buildName(marker: String, collision: Int = 0): String {
     return buildName(marker, collision + 1)
 }
 
-@Suppress("FunctionName")
 internal inline fun ClassWriter(flags: Int, block: ClassWriter.() -> Unit): ClassWriter {
     contract { callsInPlace(block, InvocationKind.EXACTLY_ONCE) }
     return ClassWriter(flags).apply(block)

kmath-ast/src/jvmTest/kotlin/space/kscience/kmath/ast/utils.kt

@@ -12,28 +12,29 @@ import space.kscience.kmath.expressions.Symbol
 import space.kscience.kmath.operations.Algebra
 import space.kscience.kmath.operations.Float64Field
 import space.kscience.kmath.operations.Int32Ring
+import space.kscience.kmath.structures.Float64
 import space.kscience.kmath.asm.compile as asmCompile
 import space.kscience.kmath.asm.compileToExpression as asmCompileToExpression
 
-private object GenericAsmCompilerTestContext : CompilerTestContext {
+internal object GenericAsmCompilerTestContext : CompilerTestContext {
     override fun MST.compileToExpression(algebra: Int32Ring): Expression<Int> =
         asmCompileToExpression(algebra as Algebra<Int>)
 
     override fun MST.compile(algebra: Int32Ring, arguments: Map<Symbol, Int>): Int =
         asmCompile(algebra as Algebra<Int>, arguments)
 
-    override fun MST.compileToExpression(algebra: Float64Field): Expression<Double> =
-        asmCompileToExpression(algebra as Algebra<Double>)
+    override fun MST.compileToExpression(algebra: Float64Field): Expression<Float64> =
+        asmCompileToExpression(algebra as Algebra<Float64>)
 
     override fun MST.compile(algebra: Float64Field, arguments: Map<Symbol, Double>): Double =
-        asmCompile(algebra as Algebra<Double>, arguments)
+        asmCompile(algebra as Algebra<Float64>, arguments)
 }
 
 @OptIn(UnstableKMathAPI::class)
-private object PrimitiveAsmCompilerTestContext : CompilerTestContext {
+internal object PrimitiveAsmCompilerTestContext : CompilerTestContext {
     override fun MST.compileToExpression(algebra: Int32Ring): Expression<Int> = asmCompileToExpression(algebra)
     override fun MST.compile(algebra: Int32Ring, arguments: Map<Symbol, Int>): Int = asmCompile(algebra, arguments)
-    override fun MST.compileToExpression(algebra: Float64Field): Expression<Double> = asmCompileToExpression(algebra)
+    override fun MST.compileToExpression(algebra: Float64Field): Expression<Float64> = asmCompileToExpression(algebra)
 
     override fun MST.compile(algebra: Float64Field, arguments: Map<Symbol, Double>): Double =
         asmCompile(algebra, arguments)

kmath-commons/README.md

@@ -6,7 +6,7 @@ Commons math binding for kmath
 
 ## Artifact:
 
-The Maven coordinates of this project are `space.kscience:kmath-commons:0.4.0`.
+The Maven coordinates of this project are `space.kscience:kmath-commons:0.5.0`.
 
 **Gradle Kotlin DSL:**
 ```kotlin
@@ -16,6 +16,6 @@ repositories {
 }
 
 dependencies {
-    implementation("space.kscience:kmath-commons:0.4.0")
+    implementation("space.kscience:kmath-commons:0.5.0")
 }
 ```

kmath-commons/build.gradle.kts

@@ -13,7 +13,7 @@ kscience {
         api(projects.kmathOptimization)
         api(projects.kmathStat)
         api(projects.kmathFunctions)
-        api("org.apache.commons:commons-math3:3.6.1")
+        api(libs.commons.math)
     }
 }
 

kmath-commons/src/jvmMain/kotlin/space/kscience/kmath/commons/expressions/CmDsExpression.kt

@@ -14,6 +14,7 @@ import space.kscience.kmath.expressions.*
 import space.kscience.kmath.operations.DoubleField
 import space.kscience.kmath.operations.ExtendedField
 import space.kscience.kmath.operations.NumbersAddOps
+import space.kscience.kmath.structures.Float64
 import space.kscience.kmath.structures.MutableBufferFactory
 
 /**
@@ -132,9 +133,9 @@ public object CmDsProcessor : AutoDiffProcessor<Double, DerivativeStructure, CmD
 @Deprecated("Use generic DSAlgebra from the core")
 public class CmDsExpression(
     public val function: CmDsField.() -> DerivativeStructure,
-) : DifferentiableExpression<Double> {
+) : DifferentiableExpression<Float64> {
 
-    override val type: SafeType<Double> get() = DoubleField.type
+    override val type: SafeType<Float64> get() = DoubleField.type
 
     override operator fun invoke(arguments: Map<Symbol, Double>): Double =
         CmDsField(0, arguments).function().value
@@ -142,7 +143,7 @@ public class CmDsExpression(
     /**
      * Get the derivative expression with given orders
      */
-    override fun derivativeOrNull(symbols: List<Symbol>): Expression<Double> = Expression(type) { arguments ->
+    override fun derivativeOrNull(symbols: List<Symbol>): Expression<Float64> = Expression(type) { arguments ->
         with(CmDsField(symbols.size, arguments)) { function().derivative(symbols) }
     }
 }

kmath-commons/src/jvmMain/kotlin/space/kscience/kmath/commons/integration/CMGaussRuleIntegrator.kt

@@ -7,6 +7,7 @@ package space.kscience.kmath.commons.integration
 import org.apache.commons.math3.analysis.integration.gauss.GaussIntegrator
 import org.apache.commons.math3.analysis.integration.gauss.GaussIntegratorFactory
 import space.kscience.kmath.integration.*
+import space.kscience.kmath.structures.Float64
 
 /**
  * A simple one-pass integrator based on Gauss rule
@@ -14,9 +15,9 @@ import space.kscience.kmath.integration.*
 public class CMGaussRuleIntegrator(
     private val numpoints: Int,
     private var type: GaussRule = GaussRule.LEGENDRE,
-) : UnivariateIntegrator<Double> {
+) : UnivariateIntegrator<Float64> {
 
-    override fun integrate(integrand: UnivariateIntegrand<Double>): UnivariateIntegrand<Double> {
+    override fun integrate(integrand: UnivariateIntegrand<Float64>): UnivariateIntegrand<Float64> {
         val range = integrand[IntegrationRange]
             ?: error("Integration range is not provided")
         val integrator: GaussIntegrator = getIntegrator(range)
@@ -28,7 +29,7 @@ public class CMGaussRuleIntegrator(
         }
     }
 
-    private fun getIntegrator(range: ClosedRange<Double>): GaussIntegrator {
+    private fun getIntegrator(range: ClosedRange<Float64>): GaussIntegrator {
         return when (type) {
             GaussRule.LEGENDRE -> factory.legendre(
                 numpoints,
@@ -77,7 +78,7 @@ public class CMGaussRuleIntegrator(
         private val factory: GaussIntegratorFactory = GaussIntegratorFactory()
 
         public fun integrate(
-            range: ClosedRange<Double>,
+            range: ClosedRange<Float64>,
             numPoints: Int = 100,
             type: GaussRule = GaussRule.LEGENDRE,
             function: (Double) -> Double,

kmath-commons/src/jvmMain/kotlin/space/kscience/kmath/commons/integration/CMIntegrator.kt

@@ -10,6 +10,7 @@ import org.apache.commons.math3.analysis.integration.SimpsonIntegrator
 import space.kscience.attributes.Attributes
 import space.kscience.kmath.UnstableKMathAPI
 import space.kscience.kmath.integration.*
+import space.kscience.kmath.structures.Float64
 import org.apache.commons.math3.analysis.integration.UnivariateIntegrator as CMUnivariateIntegrator
 
 /**
@@ -17,10 +18,10 @@ import org.apache.commons.math3.analysis.integration.UnivariateIntegrator as CMU
  */
 public class CMIntegrator(
     private val defaultMaxCalls: Int = 200,
-    public val integratorBuilder: (Integrand<Double>) -> CMUnivariateIntegrator,
-) : UnivariateIntegrator<Double> {
+    public val integratorBuilder: (Integrand<Float64>) -> CMUnivariateIntegrator,
+) : UnivariateIntegrator<Float64> {
 
-    override fun integrate(integrand: UnivariateIntegrand<Double>): UnivariateIntegrand<Double> {
+    override fun integrate(integrand: UnivariateIntegrand<Float64>): UnivariateIntegrand<Float64> {
         val integrator = integratorBuilder(integrand)
         val maxCalls = integrand[IntegrandMaxCalls] ?: defaultMaxCalls
         val remainingCalls = maxCalls - integrand.calls

kmath-commons/src/jvmMain/kotlin/space/kscience/kmath/commons/linear/CMLinearSpace.kt

@@ -0,0 +1,167 @@
+/*
+ * Copyright 2018-2024 KMath contributors.
+ * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
+ */
+
+package space.kscience.kmath.commons.linear
+
+import org.apache.commons.math3.linear.*
+import space.kscience.attributes.SafeType
+import space.kscience.kmath.UnstableKMathAPI
+import space.kscience.kmath.linear.*
+import space.kscience.kmath.linear.CholeskyDecomposition
+import space.kscience.kmath.linear.EigenDecomposition
+import space.kscience.kmath.linear.QRDecomposition
+import space.kscience.kmath.nd.Structure2D
+import space.kscience.kmath.nd.StructureAttribute
+import space.kscience.kmath.operations.DoubleField
+import space.kscience.kmath.operations.Float64Field
+import space.kscience.kmath.structures.Buffer
+import space.kscience.kmath.structures.Float64
+import space.kscience.kmath.structures.IntBuffer
+import space.kscience.kmath.structures.asBuffer
+
+@JvmInline
+public value class CMMatrix(public val cmMatrix: RealMatrix) : Matrix<Float64> {
+
+    override val rowNum: Int get() = cmMatrix.rowDimension
+    override val colNum: Int get() = cmMatrix.columnDimension
+
+    override operator fun get(i: Int, j: Int): Double = cmMatrix.getEntry(i, j)
+}
+
+@JvmInline
+public value class CMVector(public val cmVector: RealVector) : Point<Float64> {
+    override val size: Int get() = cmVector.dimension
+
+    override operator fun get(index: Int): Double = cmVector.getEntry(index)
+
+    override operator fun iterator(): Iterator<Float64> = cmVector.toArray().iterator()
+
+    override fun toString(): String = Buffer.toString(this)
+}
+
+public object CMLinearSpace : LinearSpace<Double, Float64Field> {
+    override val elementAlgebra: Float64Field get() = Float64Field
+
+    override val type: SafeType<Float64> get() = DoubleField.type
+
+    override fun buildMatrix(
+        rows: Int,
+        columns: Int,
+        initializer: Float64Field.(i: Int, j: Int) -> Double,
+    ): CMMatrix {
+        val array = Array(rows) { i -> DoubleArray(columns) { j -> Float64Field.initializer(i, j) } }
+        return CMMatrix(Array2DRowRealMatrix(array))
+    }
+
+    @OptIn(UnstableKMathAPI::class)
+    public fun Matrix<Float64>.toCM(): RealMatrix = when (val matrix = origin) {
+        is CMMatrix -> matrix.cmMatrix
+        else -> {
+            //TODO add feature analysis
+            val array = Array(rowNum) { i -> DoubleArray(colNum) { j -> get(i, j) } }
+            Array2DRowRealMatrix(array)
+        }
+    }
+
+    public fun Point<Float64>.toCM(): RealVector = if (this is CMVector) cmVector else {
+        val array = DoubleArray(size) { get(it) }
+        ArrayRealVector(array)
+    }
+
+    public fun RealMatrix.asMatrix(): CMMatrix = CMMatrix(this)
+    public fun RealVector.asVector(): CMVector = CMVector(this)
+
+    override fun buildVector(size: Int, initializer: Float64Field.(Int) -> Double): Point<Float64> =
+        ArrayRealVector(DoubleArray(size) { Float64Field.initializer(it) }).asVector()
+
+    override fun Matrix<Float64>.plus(other: Matrix<Float64>): CMMatrix =
+        toCM().add(other.toCM()).asMatrix()
+
+    override fun Point<Float64>.plus(other: Point<Float64>): CMVector =
+        toCM().add(other.toCM()).asVector()
+
+    override fun Point<Float64>.minus(other: Point<Float64>): CMVector =
+        toCM().subtract(other.toCM()).asVector()
+
+    override fun Matrix<Float64>.dot(other: Matrix<Float64>): CMMatrix =
+        toCM().multiply(other.toCM()).asMatrix()
+
+    override fun Matrix<Float64>.dot(vector: Point<Float64>): CMVector =
+        toCM().preMultiply(vector.toCM()).asVector()
+
+    override operator fun Matrix<Float64>.minus(other: Matrix<Float64>): CMMatrix =
+        toCM().subtract(other.toCM()).asMatrix()
+
+    override operator fun Matrix<Float64>.times(value: Double): CMMatrix =
+        toCM().scalarMultiply(value).asMatrix()
+
+    override fun Double.times(m: Matrix<Float64>): CMMatrix =
+        m * this
+
+    override fun Point<Float64>.times(value: Double): CMVector =
+        toCM().mapMultiply(value).asVector()
+
+    override fun Double.times(v: Point<Float64>): CMVector =
+        v * this
+
+    @OptIn(UnstableKMathAPI::class)
+    override fun <V, A : StructureAttribute<V>> computeAttribute(structure: Structure2D<Float64>, attribute: A): V? {
+
+        val origin = structure.toCM()
+
+        val raw: Any? = when (attribute) {
+            IsDiagonal -> if (origin is DiagonalMatrix) Unit else null
+            Determinant -> org.apache.commons.math3.linear.LUDecomposition(origin).determinant
+
+            Inverted -> org.apache.commons.math3.linear.LUDecomposition(origin).solver.inverse.asMatrix()
+
+            LUP -> object : LupDecomposition<Float64> {
+                val lup by lazy { org.apache.commons.math3.linear.LUDecomposition(origin) }
+                override val pivot: IntBuffer get() = lup.pivot.asBuffer()
+                override val l: Matrix<Float64> get() = lup.l.asMatrix().withAttribute(LowerTriangular)
+                override val u: Matrix<Float64> get() = lup.u.asMatrix().withAttribute(UpperTriangular)
+            }
+
+            Cholesky -> object : CholeskyDecomposition<Float64> {
+                val cmCholesky by lazy { org.apache.commons.math3.linear.CholeskyDecomposition(origin) }
+                override val l: Matrix<Float64> get() = cmCholesky.l.asMatrix()
+            }
+
+            QR -> object : QRDecomposition<Float64> {
+                val cmQr by lazy { org.apache.commons.math3.linear.QRDecomposition(origin) }
+                override val q: Matrix<Float64> get() = cmQr.q.asMatrix().withAttribute(OrthogonalAttribute)
+                override val r: Matrix<Float64> get() = cmQr.r.asMatrix().withAttribute(UpperTriangular)
+            }
+
+            SVD -> object : space.kscience.kmath.linear.SingularValueDecomposition<Float64> {
+                val cmSvd by lazy { org.apache.commons.math3.linear.SingularValueDecomposition(origin) }
+
+                override val u: Matrix<Float64> get() = cmSvd.u.asMatrix()
+                override val s: Matrix<Float64> get() = cmSvd.s.asMatrix()
+                override val v: Matrix<Float64> get() = cmSvd.v.asMatrix()
+                override val singularValues: Point<Float64> get() = cmSvd.singularValues.asBuffer()
+
+            }
+
+            EIG -> object : EigenDecomposition<Float64> {
+                val cmEigen by lazy { org.apache.commons.math3.linear.EigenDecomposition(origin) }
+
+                override val v: Matrix<Float64> get() = cmEigen.v.asMatrix()
+                override val d: Matrix<Float64> get() = cmEigen.d.asMatrix()
+            }
+
+            else -> null
+        }
+        @Suppress("UNCHECKED_CAST")
+        return raw as V?
+    }
+
+}
+
+public operator fun CMMatrix.plus(other: CMMatrix): CMMatrix = CMMatrix(cmMatrix.add(other.cmMatrix))
+
+public operator fun CMMatrix.minus(other: CMMatrix): CMMatrix = CMMatrix(cmMatrix.subtract(other.cmMatrix))
+
+public infix fun CMMatrix.dot(other: CMMatrix): CMMatrix = CMMatrix(cmMatrix.multiply(other.cmMatrix))

kmath-commons/src/jvmMain/kotlin/space/kscience/kmath/commons/linear/CMMatrix.kt

@@ -1,159 +0,0 @@
-/*
- * Copyright 2018-2024 KMath contributors.
- * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
- */
-
-package space.kscience.kmath.commons.linear
-
-import org.apache.commons.math3.linear.*
-import org.apache.commons.math3.linear.LUDecomposition
-import org.apache.commons.math3.linear.SingularValueDecomposition
-import space.kscience.attributes.SafeType
-import space.kscience.kmath.UnstableKMathAPI
-import space.kscience.kmath.linear.*
-import space.kscience.kmath.linear.CholeskyDecomposition
-import space.kscience.kmath.linear.QRDecomposition
-import space.kscience.kmath.nd.Structure2D
-import space.kscience.kmath.nd.StructureAttribute
-import space.kscience.kmath.operations.DoubleField
-import space.kscience.kmath.operations.Float64Field
-import space.kscience.kmath.structures.Buffer
-import space.kscience.kmath.structures.Float64
-import space.kscience.kmath.structures.IntBuffer
-import space.kscience.kmath.structures.asBuffer
-
-public class CMMatrix(public val origin: RealMatrix) : Matrix<Double> {
-
-    override val rowNum: Int get() = origin.rowDimension
-    override val colNum: Int get() = origin.columnDimension
-
-    override operator fun get(i: Int, j: Int): Double = origin.getEntry(i, j)
-}
-
-@JvmInline
-public value class CMVector(public 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()
-
-    override fun toString(): String = Buffer.toString(this)
-}
-
-public fun RealVector.toPoint(): CMVector = CMVector(this)
-
-public object CMLinearSpace : LinearSpace<Double, Float64Field> {
-    override val elementAlgebra: Float64Field get() = Float64Field
-
-    override val type: SafeType<Double> get() = DoubleField.type
-
-    override fun buildMatrix(
-        rows: Int,
-        columns: Int,
-        initializer: Float64Field.(i: Int, j: Int) -> Double,
-    ): CMMatrix {
-        val array = Array(rows) { i -> DoubleArray(columns) { j -> Float64Field.initializer(i, j) } }
-        return CMMatrix(Array2DRowRealMatrix(array))
-    }
-
-    @OptIn(UnstableKMathAPI::class)
-    public fun Matrix<Double>.toCM(): CMMatrix = when (val matrix = origin) {
-        is CMMatrix -> matrix
-        else -> {
-            //TODO add feature analysis
-            val array = Array(rowNum) { i -> DoubleArray(colNum) { j -> get(i, j) } }
-            Array2DRowRealMatrix(array).wrap()
-        }
-    }
-
-    public fun Point<Double>.toCM(): CMVector = if (this is CMVector) this else {
-        val array = DoubleArray(size) { this[it] }
-        ArrayRealVector(array).wrap()
-    }
-
-    internal fun RealMatrix.wrap(): CMMatrix = CMMatrix(this)
-    internal fun RealVector.wrap(): CMVector = CMVector(this)
-
-    override fun buildVector(size: Int, initializer: Float64Field.(Int) -> Double): Point<Double> =
-        ArrayRealVector(DoubleArray(size) { Float64Field.initializer(it) }).wrap()
-
-    override fun Matrix<Double>.plus(other: Matrix<Double>): CMMatrix =
-        toCM().origin.add(other.toCM().origin).wrap()
-
-    override fun Point<Double>.plus(other: Point<Double>): CMVector =
-        toCM().origin.add(other.toCM().origin).wrap()
-
-    override fun Point<Double>.minus(other: Point<Double>): CMVector =
-        toCM().origin.subtract(other.toCM().origin).wrap()
-
-    override fun Matrix<Double>.dot(other: Matrix<Double>): CMMatrix =
-        toCM().origin.multiply(other.toCM().origin).wrap()
-
-    override fun Matrix<Double>.dot(vector: Point<Double>): CMVector =
-        toCM().origin.preMultiply(vector.toCM().origin).wrap()
-
-    override operator fun Matrix<Double>.minus(other: Matrix<Double>): CMMatrix =
-        toCM().origin.subtract(other.toCM().origin).wrap()
-
-    override operator fun Matrix<Double>.times(value: Double): CMMatrix =
-        toCM().origin.scalarMultiply(value).wrap()
-
-    override fun Double.times(m: Matrix<Double>): CMMatrix =
-        m * this
-
-    override fun Point<Double>.times(value: Double): CMVector =
-        toCM().origin.mapMultiply(value).wrap()
-
-    override fun Double.times(v: Point<Double>): CMVector =
-        v * this
-
-    override fun <V, A : StructureAttribute<V>> computeAttribute(structure: Structure2D<Double>, attribute: A): V? {
-
-        val origin = structure.toCM().origin
-
-        val raw: Any? = when (attribute) {
-            IsDiagonal -> if (origin is DiagonalMatrix) Unit else null
-            Determinant -> LUDecomposition(origin).determinant
-
-            LUP -> object : LupDecomposition<Float64> {
-                val lup by lazy { LUDecomposition(origin) }
-                override val pivot: IntBuffer get() = lup.pivot.asBuffer()
-                override val l: Matrix<Float64> get() = lup.l.wrap()
-                override val u: Matrix<Float64> get() = lup.u.wrap()
-            }
-
-            Cholesky -> object : CholeskyDecomposition<Float64> {
-                val cmCholesky by lazy { org.apache.commons.math3.linear.CholeskyDecomposition(origin) }
-                override val l: Matrix<Double> get() = cmCholesky.l.wrap()
-            }
-
-            QR -> object : QRDecomposition<Float64> {
-                val cmQr by lazy { org.apache.commons.math3.linear.QRDecomposition(origin) }
-                override val q: Matrix<Float64> get() = cmQr.q.wrap().withAttribute(OrthogonalAttribute)
-                override val r: Matrix<Float64> get() = cmQr.r.wrap().withAttribute(UpperTriangular)
-            }
-
-            SVD -> object : space.kscience.kmath.linear.SingularValueDecomposition<Float64> {
-                val cmSvd by lazy { SingularValueDecomposition(origin) }
-
-                override val u: Matrix<Float64> get() = cmSvd.u.wrap()
-                override val s: Matrix<Float64> get() = cmSvd.s.wrap()
-                override val v: Matrix<Float64> get() = cmSvd.v.wrap()
-                override val singularValues: Point<Float64> get() = cmSvd.singularValues.asBuffer()
-
-            }
-
-            else -> null
-        }
-        @Suppress("UNCHECKED_CAST")
-        return raw as V?
-    }
-
-}
-
-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/jvmMain/kotlin/space/kscience/kmath/commons/linear/CMSolver.kt

@@ -9,6 +9,7 @@ import org.apache.commons.math3.linear.*
 import space.kscience.kmath.linear.LinearSolver
 import space.kscience.kmath.linear.Matrix
 import space.kscience.kmath.linear.Point
+import space.kscience.kmath.structures.Float64
 
 public enum class CMDecomposition {
     LUP,
@@ -18,43 +19,44 @@ public enum class CMDecomposition {
     CHOLESKY
 }
 
-private fun CMLinearSpace.solver(
-    a: Matrix<Double>,
+private fun CMLinearSpace.cmSolver(
+    a: Matrix<Float64>,
     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
+    CMDecomposition.LUP -> LUDecomposition(a.toCM()).solver
+    CMDecomposition.RRQR -> RRQRDecomposition(a.toCM()).solver
+    CMDecomposition.QR -> QRDecomposition(a.toCM()).solver
+    CMDecomposition.EIGEN -> EigenDecomposition(a.toCM()).solver
+    CMDecomposition.CHOLESKY -> CholeskyDecomposition(a.toCM()).solver
 }
 
 public fun CMLinearSpace.solve(
-    a: Matrix<Double>,
-    b: Matrix<Double>,
+    a: Matrix<Float64>,
+    b: Matrix<Float64>,
     decomposition: CMDecomposition = CMDecomposition.LUP,
-): CMMatrix = solver(a, decomposition).solve(b.toCM().origin).wrap()
+): CMMatrix = cmSolver(a, decomposition).solve(b.toCM()).asMatrix()
 
 public fun CMLinearSpace.solve(
-    a: Matrix<Double>,
-    b: Point<Double>,
+    a: Matrix<Float64>,
+    b: Point<Float64>,
     decomposition: CMDecomposition = CMDecomposition.LUP,
-): CMVector = solver(a, decomposition).solve(b.toCM().origin).toPoint()
+): CMVector = cmSolver(a, decomposition).solve(b.toCM()).asVector()
 
 public fun CMLinearSpace.inverse(
-    a: Matrix<Double>,
+    a: Matrix<Float64>,
     decomposition: CMDecomposition = CMDecomposition.LUP,
-): CMMatrix = solver(a, decomposition).inverse.wrap()
+): CMMatrix = cmSolver(a, decomposition).inverse.asMatrix()
 
 
-public fun CMLinearSpace.solver(decomposition: CMDecomposition): LinearSolver<Double> = object : LinearSolver<Double> {
-    override fun solve(a: Matrix<Double>, b: Matrix<Double>): Matrix<Double> =
-        solver(a, decomposition).solve(b.toCM().origin).wrap()
+public fun CMLinearSpace.solver(decomposition: CMDecomposition): LinearSolver<Float64> =
+    object : LinearSolver<Float64> {
+        override fun solve(a: Matrix<Float64>, b: Matrix<Float64>): Matrix<Float64> =
+            cmSolver(a, decomposition).solve(b.toCM()).asMatrix()
 
-    override fun solve(a: Matrix<Double>, b: Point<Double>): Point<Double> =
-        solver(a, decomposition).solve(b.toCM().origin).toPoint()
+        override fun solve(a: Matrix<Float64>, b: Point<Float64>): Point<Float64> =
+            cmSolver(a, decomposition).solve(b.toCM()).asVector()
 
-    override fun inverse(matrix: Matrix<Double>): Matrix<Double> = solver(matrix, decomposition).inverse.wrap()
-}
+        override fun inverse(matrix: Matrix<Float64>): Matrix<Float64> = cmSolver(matrix, decomposition).inverse.asMatrix()
+    }
 
-public fun CMLinearSpace.lupSolver(): LinearSolver<Double> = solver((CMDecomposition.LUP))
+public fun CMLinearSpace.lupSolver(): LinearSolver<Float64> = solver((CMDecomposition.LUP))

kmath-commons/src/jvmMain/kotlin/space/kscience/kmath/commons/optimization/CMOptimizer.kt

@@ -22,7 +22,7 @@ import space.kscience.kmath.expressions.SymbolIndexer
 import space.kscience.kmath.expressions.derivative
 import space.kscience.kmath.expressions.withSymbols
 import space.kscience.kmath.optimization.*
-import kotlin.collections.set
+import space.kscience.kmath.structures.Float64
 import kotlin.reflect.KClass
 
 public operator fun PointValuePair.component1(): DoubleArray = point
@@ -33,8 +33,8 @@ public object CMOptimizerEngine : OptimizationAttribute<() -> MultivariateOptimi
 /**
  * Specify a Commons-maths optimization engine
  */
-public fun AttributesBuilder<FunctionOptimization<Double>>.cmEngine(optimizerBuilder: () -> MultivariateOptimizer) {
-    set(CMOptimizerEngine, optimizerBuilder)
+public fun AttributesBuilder<FunctionOptimization<Float64>>.cmEngine(optimizerBuilder: () -> MultivariateOptimizer) {
+    CMOptimizerEngine(optimizerBuilder)
 }
 
 public object CMOptimizerData : SetAttribute<SymbolIndexer.() -> OptimizationData>
@@ -42,18 +42,18 @@ public object CMOptimizerData : SetAttribute<SymbolIndexer.() -> OptimizationDat
 /**
  * Specify Commons-maths optimization data.
  */
-public fun AttributesBuilder<FunctionOptimization<Double>>.cmOptimizationData(data: SymbolIndexer.() -> OptimizationData) {
+public fun AttributesBuilder<FunctionOptimization<Float64>>.cmOptimizationData(data: SymbolIndexer.() -> OptimizationData) {
     CMOptimizerData add data
 }
 
-public fun AttributesBuilder<FunctionOptimization<Double>>.simplexSteps(vararg steps: Pair<Symbol, Double>) {
+public fun AttributesBuilder<FunctionOptimization<Float64>>.simplexSteps(vararg steps: Pair<Symbol, Double>) {
     //TODO use convergence checker from features
     cmEngine { SimplexOptimizer(CMOptimizer.defaultConvergenceChecker) }
     cmOptimizationData { NelderMeadSimplex(mapOf(*steps).toDoubleArray()) }
 }
 
 @OptIn(UnstableKMathAPI::class)
-public object CMOptimizer : Optimizer<Double, FunctionOptimization<Double>> {
+public object CMOptimizer : Optimizer<Double, FunctionOptimization<Float64>> {
 
     public const val DEFAULT_RELATIVE_TOLERANCE: Double = 1e-4
     public const val DEFAULT_ABSOLUTE_TOLERANCE: Double = 1e-4
@@ -67,12 +67,12 @@ public object CMOptimizer : Optimizer<Double, FunctionOptimization<Double>> {
 
 
     override suspend fun optimize(
-        problem: FunctionOptimization<Double>,
-    ): FunctionOptimization<Double> {
+        problem: FunctionOptimization<Float64>,
+    ): FunctionOptimization<Float64> {
         val startPoint = problem.startPoint
 
         val parameters = problem.attributes[OptimizationParameters]
-            ?: problem.attributes[OptimizationStartPoint<Double>()]?.keys
+            ?: problem.attributes[OptimizationStartPoint<Float64>()]?.keys
             ?: startPoint.keys
 
 

kmath-commons/src/jvmMain/kotlin/space/kscience/kmath/commons/transform/Transformations.kt

@@ -77,7 +77,7 @@ public fun Flow<Buffer<Complex>>.fft(
 }
 
 @JvmName("realFFT")
-public fun Flow<Buffer<Double>>.fft(
+public fun Flow<Buffer<Float64>>.fft(
     normalization: DftNormalization = DftNormalization.STANDARD,
     direction: TransformType = TransformType.FORWARD,
 ): Flow<Buffer<Complex>> {
@@ -89,7 +89,7 @@ public fun Flow<Buffer<Double>>.fft(
  * Process a continuous flow of real numbers in FFT splitting it in chunks of [bufferSize].
  */
 @JvmName("realFFT")
-public fun Flow<Double>.fft(
+public fun Flow<Float64>.fft(
     bufferSize: Int = Int.MAX_VALUE,
     normalization: DftNormalization = DftNormalization.STANDARD,
     direction: TransformType = TransformType.FORWARD,
@@ -99,4 +99,4 @@ public fun Flow<Double>.fft(
  * Map a complex flow into real flow by taking real part of each number
  */
 @FlowPreview
-public fun Flow<Complex>.real(): Flow<Double> = map { it.re }
+public fun Flow<Complex>.real(): Flow<Float64> = map { it.re }

kmath-commons/src/jvmTest/kotlin/space/kscience/kmath/commons/optimization/OptimizeTest.kt

@@ -18,6 +18,7 @@ import space.kscience.kmath.operations.Float64Field
 import space.kscience.kmath.optimization.*
 import space.kscience.kmath.random.RandomGenerator
 import space.kscience.kmath.stat.chiSquaredExpression
+import space.kscience.kmath.structures.Float64
 import space.kscience.kmath.structures.Float64Buffer
 import space.kscience.kmath.structures.asBuffer
 import kotlin.test.Test
@@ -70,7 +71,7 @@ internal class OptimizeTest {
             bindSymbol(a) * arg.pow(2) + bindSymbol(b) * arg + cWithDefault
         }
 
-        val result: FunctionOptimization<Double> = chi2.optimizeWith(
+        val result: FunctionOptimization<Float64> = chi2.optimizeWith(
             CMOptimizer,
             mapOf(a to 1.5, b to 0.9, c to 1.0),
         ) {

kmath-complex/README.md

@@ -8,7 +8,7 @@ Complex and hypercomplex number systems in KMath.
 
 ## Artifact:
 
-The Maven coordinates of this project are `space.kscience:kmath-complex:0.4.0`.
+The Maven coordinates of this project are `space.kscience:kmath-complex:0.5.0`.
 
 **Gradle Kotlin DSL:**
 ```kotlin
@@ -18,6 +18,6 @@ repositories {
 }
 
 dependencies {
-    implementation("space.kscience:kmath-complex:0.4.0")
+    implementation("space.kscience:kmath-complex:0.5.0")
 }
 ```

kmath-complex/build.gradle.kts

@@ -6,7 +6,7 @@ kscience {
     jvm()
     js()
     native()
-    wasm()
+    wasmJs()
 
     dependencies {
         api(projects.kmathCore)

kmath-complex/src/commonMain/kotlin/space/kscience/kmath/complex/Quaternion.kt

@@ -11,6 +11,7 @@ import space.kscience.kmath.UnstableKMathAPI
 import space.kscience.kmath.memory.*
 import space.kscience.kmath.operations.*
 import space.kscience.kmath.structures.Buffer
+import space.kscience.kmath.structures.Float64
 import space.kscience.kmath.structures.MutableBuffer
 import space.kscience.kmath.structures.MutableBufferFactory
 import kotlin.math.*
@@ -28,7 +29,7 @@ public class Quaternion(
     public val x: Double,
     public val y: Double,
     public val z: Double,
-) : Buffer<Double> {
+) : Buffer<Float64> {
     init {
         require(!w.isNaN()) { "w-component of quaternion is not-a-number" }
         require(!x.isNaN()) { "x-component of quaternion is not-a-number" }
@@ -51,7 +52,7 @@ public class Quaternion(
         else -> error("Index $index out of bounds [0,3]")
     }
 
-    override fun iterator(): Iterator<Double> = listOf(w, x, y, z).iterator()
+    override fun iterator(): Iterator<Float64> = listOf(w, x, y, z).iterator()
 
     override fun equals(other: Any?): Boolean {
         if (this === other) return true

kmath-core/README.md

@@ -4,11 +4,9 @@ The core interfaces of KMath.
 
  - [algebras](src/commonMain/kotlin/space/kscience/kmath/operations/Algebra.kt) : Algebraic structures like rings, spaces and fields.
  - [nd](src/commonMain/kotlin/space/kscience/kmath/structures/StructureND.kt) : Many-dimensional structures and operations on them.
- - [linear](src/commonMain/kotlin/space/kscience/kmath/operations/Algebra.kt) : Basic linear algebra operations (sums, products, etc.), backed by the `Space` API. Advanced linear algebra operations like matrix inversion and LU decomposition.
+ - [linear](src/commonMain/kotlin/space/kscience/kmath/operations/Algebra.kt) : Basic linear algebra operations (sums, products, etc.), backed by the `Space` API. 
  - [buffers](src/commonMain/kotlin/space/kscience/kmath/structures/Buffers.kt) : One-dimensional structure
- - [expressions](src/commonMain/kotlin/space/kscience/kmath/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.
+ - [expressions](src/commonMain/kotlin/space/kscience/kmath/expressions) : By writing a single mathematical expression once, users will be able to apply different types of
  - [domains](src/commonMain/kotlin/space/kscience/kmath/domains) : Domains
  - [autodiff](src/commonMain/kotlin/space/kscience/kmath/expressions/SimpleAutoDiff.kt) : Automatic differentiation
  - [Parallel linear algebra](#) : Parallel implementation for `LinearAlgebra`
@@ -16,7 +14,7 @@ performance calculations to code generation.
 
 ## Artifact:
 
-The Maven coordinates of this project are `space.kscience:kmath-core:0.4.0`.
+The Maven coordinates of this project are `space.kscience:kmath-core:0.5.0`.
 
 **Gradle Kotlin DSL:**
 ```kotlin
@@ -26,6 +24,6 @@ repositories {
 }
 
 dependencies {
-    implementation("space.kscience:kmath-core:0.4.0")
+    implementation("space.kscience:kmath-core:0.5.0")
 }
 ```

kmath-core/api/kmath-core.api

@@ -9,15 +9,9 @@ public abstract interface annotation class space/kscience/kmath/UnsafeKMathAPI :
 public abstract interface annotation class space/kscience/kmath/UnstableKMathAPI : java/lang/annotation/Annotation {
 }
 
-public final class space/kscience/kmath/data/ColumnarDataKt {
-}
-
 public final class space/kscience/kmath/data/XYColumnarData$Companion {
 }
 
-public final class space/kscience/kmath/data/XYColumnarDataKt {
-}
-
 public final class space/kscience/kmath/data/XYErrorColumnarData$Companion {
 	public final fun of (Lspace/kscience/kmath/structures/Buffer;Lspace/kscience/kmath/structures/Buffer;Lspace/kscience/kmath/structures/Buffer;)Lspace/kscience/kmath/data/XYErrorColumnarData;
 }
@@ -27,9 +21,6 @@ public abstract interface class space/kscience/kmath/domains/Domain {
 	public abstract fun getDimension ()I
 }
 
-public final class space/kscience/kmath/domains/Domain1DKt {
-}
-
 public abstract interface class space/kscience/kmath/expressions/AutoDiffProcessor {
 	public abstract fun differentiate (Lkotlin/jvm/functions/Function1;)Lspace/kscience/kmath/expressions/DifferentiableExpression;
 }
@@ -39,9 +30,6 @@ public class space/kscience/kmath/expressions/AutoDiffValue {
 	public final fun getValue ()Ljava/lang/Object;
 }
 
-public final class space/kscience/kmath/expressions/DSAlgebraKt {
-}
-
 public final class space/kscience/kmath/expressions/DSCompiler {
 	public final fun getAlgebra ()Lspace/kscience/kmath/operations/Algebra;
 	public final fun getFreeParameters ()I
@@ -412,34 +400,6 @@ public final class space/kscience/kmath/expressions/MstRing : space/kscience/kma
 	public fun unaryPlus (Lspace/kscience/kmath/expressions/MST;)Lspace/kscience/kmath/expressions/MST$Unary;
 }
 
-public final class space/kscience/kmath/expressions/NamedMatrix : space/kscience/kmath/nd/Structure2D {
-	public static final field Companion Lspace/kscience/kmath/expressions/NamedMatrix$Companion;
-	public fun <init> (Lspace/kscience/kmath/nd/Structure2D;Lspace/kscience/kmath/expressions/SymbolIndexer;)V
-	public fun elements ()Lkotlin/sequences/Sequence;
-	public fun get (II)Ljava/lang/Object;
-	public final fun get (Lspace/kscience/kmath/expressions/Symbol;Lspace/kscience/kmath/expressions/Symbol;)Ljava/lang/Object;
-	public fun get ([I)Ljava/lang/Object;
-	public fun getAttributes ()Lspace/kscience/attributes/Attributes;
-	public fun getColNum ()I
-	public fun getColumns ()Ljava/util/List;
-	public fun getDimension ()I
-	public final fun getIndexer ()Lspace/kscience/kmath/expressions/SymbolIndexer;
-	public fun getIndices ()Lspace/kscience/kmath/nd/ShapeIndexer;
-	public fun getRowNum ()I
-	public fun getRows ()Ljava/util/List;
-	public fun getShape-IIYLAfE ()[I
-	public final fun getValues ()Lspace/kscience/kmath/nd/Structure2D;
-}
-
-public final class space/kscience/kmath/expressions/NamedMatrix$Companion {
-	public final fun toStringWithSymbols (Lspace/kscience/kmath/nd/Structure2D;Lspace/kscience/kmath/expressions/SymbolIndexer;)Ljava/lang/String;
-}
-
-public final class space/kscience/kmath/expressions/NamedMatrixKt {
-	public static final fun named (Lspace/kscience/kmath/nd/Structure2D;Ljava/util/List;)Lspace/kscience/kmath/expressions/NamedMatrix;
-	public static final fun named (Lspace/kscience/kmath/nd/Structure2D;Lspace/kscience/kmath/expressions/SymbolIndexer;)Lspace/kscience/kmath/expressions/NamedMatrix;
-}
-
 public final class space/kscience/kmath/expressions/SimpleAutoDiffExpression : space/kscience/kmath/expressions/FirstDerivativeExpression {
 	public fun <init> (Lspace/kscience/kmath/operations/Field;Lkotlin/jvm/functions/Function1;)V
 	public fun derivativeOrNull (Lspace/kscience/kmath/expressions/Symbol;)Lspace/kscience/kmath/expressions/Expression;
@@ -565,9 +525,6 @@ public final class space/kscience/kmath/expressions/Symbol$Companion {
 	public final fun getZError ()Lspace/kscience/kmath/expressions/Symbol;
 }
 
-public final class space/kscience/kmath/expressions/SymbolIndexerKt {
-}
-
 public final class space/kscience/kmath/expressions/SymbolKt {
 	public static final fun Symbol (Ljava/lang/String;)Lspace/kscience/kmath/expressions/Symbol;
 	public static final fun get (Ljava/util/Map;Ljava/lang/String;)Ljava/lang/Object;
@@ -679,7 +636,7 @@ public final class space/kscience/kmath/linear/Inverted : space/kscience/attribu
 	public fun <init> ()V
 }
 
-public abstract interface class space/kscience/kmath/linear/IsDiagonal : space/kscience/attributes/FlagAttribute, space/kscience/kmath/linear/MatrixAttribute {
+public abstract interface class space/kscience/kmath/linear/IsDiagonal : space/kscience/kmath/linear/Symmetric {
 	public static final field Companion Lspace/kscience/kmath/linear/IsDiagonal$Companion;
 }
 
@@ -786,24 +743,15 @@ public final class space/kscience/kmath/linear/MatrixAttributesKt {
 	public static final fun getSVD (Lspace/kscience/kmath/linear/MatrixScope;)Lspace/kscience/kmath/linear/SVDAttribute;
 }
 
-public final class space/kscience/kmath/linear/MatrixBuilder : space/kscience/attributes/WithType {
-	public fun <init> (Lspace/kscience/kmath/linear/LinearSpace;II)V
-	public final fun getColumns ()I
-	public final fun getLinearSpace ()Lspace/kscience/kmath/linear/LinearSpace;
-	public final fun getRows ()I
-	public fun getType-V0oMfBY ()Lkotlin/reflect/KType;
-	public final fun invoke ([Ljava/lang/Object;)Lspace/kscience/kmath/nd/Structure2D;
-}
-
-public final class space/kscience/kmath/linear/MatrixBuilderKt {
-	public static final fun column (Lspace/kscience/kmath/linear/LinearSpace;ILkotlin/jvm/functions/Function1;)Lspace/kscience/kmath/nd/Structure2D;
+public final class space/kscience/kmath/linear/MatrixBuildersKt {
+	public static final fun column (Lspace/kscience/kmath/linear/LinearSpace;ILkotlin/jvm/functions/Function2;)Lspace/kscience/kmath/nd/Structure2D;
 	public static final fun column (Lspace/kscience/kmath/linear/LinearSpace;[Ljava/lang/Object;)Lspace/kscience/kmath/nd/Structure2D;
-	public static final fun row (Lspace/kscience/kmath/linear/LinearSpace;ILkotlin/jvm/functions/Function1;)Lspace/kscience/kmath/nd/Structure2D;
+	public static final fun row (Lspace/kscience/kmath/linear/LinearSpace;ILkotlin/jvm/functions/Function2;)Lspace/kscience/kmath/nd/Structure2D;
 	public static final fun row (Lspace/kscience/kmath/linear/LinearSpace;[Ljava/lang/Object;)Lspace/kscience/kmath/nd/Structure2D;
-	public static final fun symmetric (Lspace/kscience/kmath/linear/MatrixBuilder;Lkotlin/jvm/functions/Function2;)Lspace/kscience/kmath/nd/Structure2D;
+	public static final fun vector (Lspace/kscience/kmath/linear/LinearSpace;[Ljava/lang/Object;)Lspace/kscience/kmath/structures/Buffer;
 }
 
-public abstract interface class space/kscience/kmath/linear/MatrixScope : space/kscience/attributes/AttributeScope, space/kscience/attributes/WithType {
+public abstract interface class space/kscience/kmath/linear/MatrixScope : space/kscience/attributes/WithType {
 }
 
 public final class space/kscience/kmath/linear/MatrixWrapper : space/kscience/kmath/nd/Structure2D {
@@ -818,7 +766,7 @@ public final class space/kscience/kmath/linear/MatrixWrapper : space/kscience/km
 	public final fun getOrigin ()Lspace/kscience/kmath/nd/Structure2D;
 	public fun getRowNum ()I
 	public fun getRows ()Ljava/util/List;
-	public fun getShape-IIYLAfE ()[I
+	public fun getShape ()Lspace/kscience/kmath/nd/ShapeND;
 	public fun toString ()Ljava/lang/String;
 }
 
@@ -854,8 +802,11 @@ public abstract interface class space/kscience/kmath/linear/SingularValueDecompo
 	public abstract fun getV ()Lspace/kscience/kmath/nd/Structure2D;
 }
 
-public final class space/kscience/kmath/linear/Symmetric : space/kscience/attributes/FlagAttribute, space/kscience/kmath/linear/MatrixAttribute {
-	public static final field INSTANCE Lspace/kscience/kmath/linear/Symmetric;
+public abstract interface class space/kscience/kmath/linear/Symmetric : space/kscience/attributes/FlagAttribute, space/kscience/kmath/linear/MatrixAttribute {
+	public static final field Companion Lspace/kscience/kmath/linear/Symmetric$Companion;
+}
+
+public final class space/kscience/kmath/linear/Symmetric$Companion : space/kscience/kmath/linear/Symmetric {
 }
 
 public final class space/kscience/kmath/linear/TransposedKt {
@@ -883,12 +834,6 @@ public final class space/kscience/kmath/linear/VirtualMatrix : space/kscience/km
 	public fun getColNum ()I
 	public final fun getGenerator ()Lkotlin/jvm/functions/Function2;
 	public fun getRowNum ()I
-	public fun getShape-IIYLAfE ()[I
-}
-
-public final class space/kscience/kmath/linear/VirtualMatrixKt {
-	public static final fun virtual (Lspace/kscience/kmath/linear/MatrixBuilder;Lspace/kscience/attributes/Attributes;Lkotlin/jvm/functions/Function2;)Lspace/kscience/kmath/linear/VirtualMatrix;
-	public static synthetic fun virtual$default (Lspace/kscience/kmath/linear/MatrixBuilder;Lspace/kscience/attributes/Attributes;Lkotlin/jvm/functions/Function2;ILjava/lang/Object;)Lspace/kscience/kmath/linear/VirtualMatrix;
 }
 
 public final class space/kscience/kmath/misc/CollectionsKt {
@@ -944,14 +889,66 @@ public final class space/kscience/kmath/misc/SortingKt {
 	public static final fun sortedWith (Lspace/kscience/kmath/structures/Buffer;Ljava/util/Comparator;)Lspace/kscience/kmath/structures/Buffer;
 }
 
+public final class space/kscience/kmath/named/NamedBuffer : space/kscience/kmath/structures/Buffer {
+	public fun <init> (Lspace/kscience/kmath/structures/Buffer;Lspace/kscience/kmath/expressions/SymbolIndexer;)V
+	public fun get (I)Ljava/lang/Object;
+	public final fun get (Lspace/kscience/kmath/expressions/Symbol;)Ljava/lang/Object;
+	public final fun getIndexer ()Lspace/kscience/kmath/expressions/SymbolIndexer;
+	public fun getSize ()I
+	public final fun getValues ()Lspace/kscience/kmath/structures/Buffer;
+	public fun iterator ()Ljava/util/Iterator;
+	public fun toString ()Ljava/lang/String;
+}
+
+public final class space/kscience/kmath/named/NamedMatrix : space/kscience/kmath/nd/Structure2D {
+	public static final field Companion Lspace/kscience/kmath/named/NamedMatrix$Companion;
+	public fun <init> (Lspace/kscience/kmath/nd/Structure2D;Lspace/kscience/kmath/expressions/SymbolIndexer;)V
+	public fun elements ()Lkotlin/sequences/Sequence;
+	public fun get (II)Ljava/lang/Object;
+	public final fun get (Lspace/kscience/kmath/expressions/Symbol;Lspace/kscience/kmath/expressions/Symbol;)Ljava/lang/Object;
+	public fun get ([I)Ljava/lang/Object;
+	public fun getAttributes ()Lspace/kscience/attributes/Attributes;
+	public fun getColNum ()I
+	public fun getColumns ()Ljava/util/List;
+	public fun getDimension ()I
+	public final fun getIndexer ()Lspace/kscience/kmath/expressions/SymbolIndexer;
+	public fun getIndices ()Lspace/kscience/kmath/nd/ShapeIndexer;
+	public fun getRowNum ()I
+	public fun getRows ()Ljava/util/List;
+	public fun getShape ()Lspace/kscience/kmath/nd/ShapeND;
+	public final fun getValues ()Lspace/kscience/kmath/nd/Structure2D;
+}
+
+public final class space/kscience/kmath/named/NamedMatrix$Companion {
+	public final fun toStringWithSymbols (Lspace/kscience/kmath/nd/Structure2D;Lspace/kscience/kmath/expressions/SymbolIndexer;)Ljava/lang/String;
+}
+
+public final class space/kscience/kmath/named/NamedMatrixKt {
+	public static final fun named (Lspace/kscience/kmath/nd/Structure2D;Ljava/util/List;)Lspace/kscience/kmath/named/NamedMatrix;
+	public static final fun named (Lspace/kscience/kmath/nd/Structure2D;Lspace/kscience/kmath/expressions/SymbolIndexer;)Lspace/kscience/kmath/named/NamedMatrix;
+}
+
+public final class space/kscience/kmath/named/NamedMutableBuffer : space/kscience/kmath/structures/MutableBuffer {
+	public fun <init> (Lspace/kscience/kmath/structures/MutableBuffer;Lspace/kscience/kmath/expressions/SymbolIndexer;)V
+	public fun get (I)Ljava/lang/Object;
+	public final fun get (Lspace/kscience/kmath/expressions/Symbol;)Ljava/lang/Object;
+	public final fun getIndexer ()Lspace/kscience/kmath/expressions/SymbolIndexer;
+	public fun getSize ()I
+	public final fun getValues ()Lspace/kscience/kmath/structures/MutableBuffer;
+	public fun iterator ()Ljava/util/Iterator;
+	public fun set (ILjava/lang/Object;)V
+	public final fun set (Lspace/kscience/kmath/expressions/Symbol;Ljava/lang/Object;)V
+	public fun toString ()Ljava/lang/String;
+}
+
 public abstract interface class space/kscience/kmath/nd/AlgebraND : space/kscience/kmath/operations/Algebra {
 	public static final field Companion Lspace/kscience/kmath/nd/AlgebraND$Companion;
 	public abstract fun getElementAlgebra ()Lspace/kscience/kmath/operations/Algebra;
 	public fun invoke (Lkotlin/jvm/functions/Function1;Lspace/kscience/kmath/nd/StructureND;)Lspace/kscience/kmath/nd/StructureND;
 	public fun map (Lspace/kscience/kmath/nd/StructureND;Lkotlin/jvm/functions/Function2;)Lspace/kscience/kmath/nd/StructureND;
 	public fun mapIndexed (Lspace/kscience/kmath/nd/StructureND;Lkotlin/jvm/functions/Function3;)Lspace/kscience/kmath/nd/StructureND;
-	public abstract fun mutableStructureND-qL90JFI ([ILkotlin/jvm/functions/Function2;)Lspace/kscience/kmath/nd/MutableStructureND;
-	public fun structureND-qL90JFI ([ILkotlin/jvm/functions/Function2;)Lspace/kscience/kmath/nd/StructureND;
+	public abstract fun mutableStructureND (Lspace/kscience/kmath/nd/ShapeND;Lkotlin/jvm/functions/Function2;)Lspace/kscience/kmath/nd/MutableStructureND;
+	public fun structureND (Lspace/kscience/kmath/nd/ShapeND;Lkotlin/jvm/functions/Function2;)Lspace/kscience/kmath/nd/StructureND;
 	public fun zip (Lspace/kscience/kmath/nd/StructureND;Lspace/kscience/kmath/nd/StructureND;Lkotlin/jvm/functions/Function3;)Lspace/kscience/kmath/nd/StructureND;
 }
 
@@ -960,10 +957,10 @@ public final class space/kscience/kmath/nd/AlgebraND$Companion {
 
 public final class space/kscience/kmath/nd/AlgebraNDExtentionsKt {
 	public static final fun mutableStructureND (Lspace/kscience/kmath/nd/AlgebraND;I[ILkotlin/jvm/functions/Function2;)Lspace/kscience/kmath/nd/MutableStructureND;
-	public static final fun one-waz_sdI (Lspace/kscience/kmath/nd/AlgebraND;[I)Lspace/kscience/kmath/nd/StructureND;
+	public static final fun one (Lspace/kscience/kmath/nd/AlgebraND;Lspace/kscience/kmath/nd/ShapeND;)Lspace/kscience/kmath/nd/StructureND;
 	public static final fun oneVarArg (Lspace/kscience/kmath/nd/AlgebraND;I[I)Lspace/kscience/kmath/nd/StructureND;
 	public static final fun structureND (Lspace/kscience/kmath/nd/AlgebraND;I[ILkotlin/jvm/functions/Function2;)Lspace/kscience/kmath/nd/StructureND;
-	public static final fun zero-waz_sdI (Lspace/kscience/kmath/nd/AlgebraND;[I)Lspace/kscience/kmath/nd/StructureND;
+	public static final fun zero (Lspace/kscience/kmath/nd/AlgebraND;Lspace/kscience/kmath/nd/ShapeND;)Lspace/kscience/kmath/nd/StructureND;
 	public static final fun zeroVarArg (Lspace/kscience/kmath/nd/AlgebraND;I[I)Lspace/kscience/kmath/nd/StructureND;
 }
 
@@ -976,10 +973,10 @@ public abstract interface class space/kscience/kmath/nd/BufferAlgebraND : space/
 	public synthetic fun map (Lspace/kscience/kmath/nd/StructureND;Lkotlin/jvm/functions/Function2;)Lspace/kscience/kmath/nd/StructureND;
 	public fun mapIndexed (Lspace/kscience/kmath/nd/StructureND;Lkotlin/jvm/functions/Function3;)Lspace/kscience/kmath/nd/BufferND;
 	public synthetic fun mapIndexed (Lspace/kscience/kmath/nd/StructureND;Lkotlin/jvm/functions/Function3;)Lspace/kscience/kmath/nd/StructureND;
-	public fun mutableStructureND-qL90JFI ([ILkotlin/jvm/functions/Function2;)Lspace/kscience/kmath/nd/MutableBufferND;
-	public synthetic fun mutableStructureND-qL90JFI ([ILkotlin/jvm/functions/Function2;)Lspace/kscience/kmath/nd/MutableStructureND;
-	public fun structureND-qL90JFI ([ILkotlin/jvm/functions/Function2;)Lspace/kscience/kmath/nd/BufferND;
-	public synthetic fun structureND-qL90JFI ([ILkotlin/jvm/functions/Function2;)Lspace/kscience/kmath/nd/StructureND;
+	public fun mutableStructureND (Lspace/kscience/kmath/nd/ShapeND;Lkotlin/jvm/functions/Function2;)Lspace/kscience/kmath/nd/MutableBufferND;
+	public synthetic fun mutableStructureND (Lspace/kscience/kmath/nd/ShapeND;Lkotlin/jvm/functions/Function2;)Lspace/kscience/kmath/nd/MutableStructureND;
+	public fun structureND (Lspace/kscience/kmath/nd/ShapeND;Lkotlin/jvm/functions/Function2;)Lspace/kscience/kmath/nd/BufferND;
+	public synthetic fun structureND (Lspace/kscience/kmath/nd/ShapeND;Lkotlin/jvm/functions/Function2;)Lspace/kscience/kmath/nd/StructureND;
 	public fun toBufferND (Lspace/kscience/kmath/nd/StructureND;)Lspace/kscience/kmath/nd/BufferND;
 	public fun zip (Lspace/kscience/kmath/nd/StructureND;Lspace/kscience/kmath/nd/StructureND;Lkotlin/jvm/functions/Function3;)Lspace/kscience/kmath/nd/BufferND;
 	public synthetic fun zip (Lspace/kscience/kmath/nd/StructureND;Lspace/kscience/kmath/nd/StructureND;Lkotlin/jvm/functions/Function3;)Lspace/kscience/kmath/nd/StructureND;
@@ -1004,7 +1001,7 @@ public class space/kscience/kmath/nd/BufferND : space/kscience/kmath/nd/Structur
 	public fun get ([I)Ljava/lang/Object;
 	public fun getBuffer ()Lspace/kscience/kmath/structures/Buffer;
 	public fun getIndices ()Lspace/kscience/kmath/nd/ShapeIndexer;
-	public fun getShape-IIYLAfE ()[I
+	public fun getShape ()Lspace/kscience/kmath/nd/ShapeND;
 	public fun toString ()Ljava/lang/String;
 }
 
@@ -1034,10 +1031,10 @@ public class space/kscience/kmath/nd/BufferedRingOpsND : space/kscience/kmath/nd
 
 public final class space/kscience/kmath/nd/ColumnStrides : space/kscience/kmath/nd/Strides {
 	public static final field Companion Lspace/kscience/kmath/nd/ColumnStrides$Companion;
-	public synthetic fun <init> ([ILkotlin/jvm/internal/DefaultConstructorMarker;)V
+	public fun <init> (Lspace/kscience/kmath/nd/ShapeND;)V
 	public fun equals (Ljava/lang/Object;)Z
 	public fun getLinearSize ()I
-	public fun getShape-IIYLAfE ()[I
+	public fun getShape ()Lspace/kscience/kmath/nd/ShapeND;
 	public fun hashCode ()I
 	public fun index (I)[I
 }
@@ -1107,9 +1104,9 @@ public abstract class space/kscience/kmath/nd/Floa64FieldOpsND : space/kscience/
 	public synthetic fun multiply (Ljava/lang/Object;Ljava/lang/Object;)Ljava/lang/Object;
 	public fun multiply (Lspace/kscience/kmath/nd/StructureND;Lspace/kscience/kmath/nd/StructureND;)Lspace/kscience/kmath/nd/Float64BufferND;
 	public synthetic fun multiply (Lspace/kscience/kmath/nd/StructureND;Lspace/kscience/kmath/nd/StructureND;)Lspace/kscience/kmath/nd/StructureND;
-	public fun mutableStructureND-qL90JFI ([ILkotlin/jvm/functions/Function2;)Lspace/kscience/kmath/nd/Float64BufferND;
-	public synthetic fun mutableStructureND-qL90JFI ([ILkotlin/jvm/functions/Function2;)Lspace/kscience/kmath/nd/MutableBufferND;
-	public synthetic fun mutableStructureND-qL90JFI ([ILkotlin/jvm/functions/Function2;)Lspace/kscience/kmath/nd/MutableStructureND;
+	public fun mutableStructureND (Lspace/kscience/kmath/nd/ShapeND;Lkotlin/jvm/functions/Function2;)Lspace/kscience/kmath/nd/Float64BufferND;
+	public synthetic fun mutableStructureND (Lspace/kscience/kmath/nd/ShapeND;Lkotlin/jvm/functions/Function2;)Lspace/kscience/kmath/nd/MutableBufferND;
+	public synthetic fun mutableStructureND (Lspace/kscience/kmath/nd/ShapeND;Lkotlin/jvm/functions/Function2;)Lspace/kscience/kmath/nd/MutableStructureND;
 	public fun plus (DLspace/kscience/kmath/nd/StructureND;)Lspace/kscience/kmath/nd/StructureND;
 	public synthetic fun plus (Ljava/lang/Object;Ljava/lang/Object;)Ljava/lang/Object;
 	public synthetic fun plus (Ljava/lang/Object;Lspace/kscience/kmath/nd/StructureND;)Lspace/kscience/kmath/nd/StructureND;
@@ -1159,7 +1156,7 @@ public final class space/kscience/kmath/nd/Float64BufferND : space/kscience/kmat
 }
 
 public final class space/kscience/kmath/nd/Float64FieldND : space/kscience/kmath/nd/Floa64FieldOpsND, space/kscience/kmath/nd/FieldND, space/kscience/kmath/operations/ExtendedField, space/kscience/kmath/operations/NumbersAddOps {
-	public synthetic fun <init> ([ILkotlin/jvm/internal/DefaultConstructorMarker;)V
+	public fun <init> (Lspace/kscience/kmath/nd/ShapeND;)V
 	public synthetic fun acosh (Ljava/lang/Object;)Ljava/lang/Object;
 	public fun acosh (Lspace/kscience/kmath/nd/StructureND;)Lspace/kscience/kmath/nd/Float64BufferND;
 	public synthetic fun asinh (Ljava/lang/Object;)Ljava/lang/Object;
@@ -1168,7 +1165,7 @@ public final class space/kscience/kmath/nd/Float64FieldND : space/kscience/kmath
 	public fun atanh (Lspace/kscience/kmath/nd/StructureND;)Lspace/kscience/kmath/nd/Float64BufferND;
 	public synthetic fun cosh (Ljava/lang/Object;)Ljava/lang/Object;
 	public fun cosh (Lspace/kscience/kmath/nd/StructureND;)Lspace/kscience/kmath/nd/Float64BufferND;
-	public fun getShape-IIYLAfE ()[I
+	public fun getShape ()Lspace/kscience/kmath/nd/ShapeND;
 	public synthetic fun number (Ljava/lang/Number;)Ljava/lang/Object;
 	public fun number (Ljava/lang/Number;)Lspace/kscience/kmath/nd/Float64BufferND;
 	public synthetic fun power (Ljava/lang/Object;I)Ljava/lang/Object;
@@ -1186,8 +1183,8 @@ public final class space/kscience/kmath/nd/Float64FieldND : space/kscience/kmath
 
 public final class space/kscience/kmath/nd/Float64FieldNDKt {
 	public static final fun getNdAlgebra (Lspace/kscience/kmath/operations/Float64Field;)Lspace/kscience/kmath/nd/Floa64FieldOpsND;
+	public static final fun ndAlgebra (Lspace/kscience/kmath/operations/Float64Field;Lspace/kscience/kmath/nd/ShapeND;)Lspace/kscience/kmath/nd/Float64FieldND;
 	public static final fun ndAlgebra (Lspace/kscience/kmath/operations/Float64Field;[I)Lspace/kscience/kmath/nd/Float64FieldND;
-	public static final fun ndAlgebra-waz_sdI (Lspace/kscience/kmath/operations/Float64Field;[I)Lspace/kscience/kmath/nd/Float64FieldND;
 }
 
 public abstract interface class space/kscience/kmath/nd/GroupND : space/kscience/kmath/nd/GroupOpsND, space/kscience/kmath/nd/WithShape, space/kscience/kmath/operations/Group {
@@ -1210,14 +1207,14 @@ public final class space/kscience/kmath/nd/GroupOpsND$Companion {
 }
 
 public final class space/kscience/kmath/nd/IndexOutOfShapeException : java/lang/RuntimeException {
-	public synthetic fun <init> ([I[ILkotlin/jvm/internal/DefaultConstructorMarker;)V
+	public fun <init> (Lspace/kscience/kmath/nd/ShapeND;[I)V
 	public final fun getIndex ()[I
-	public final fun getShape-IIYLAfE ()[I
+	public final fun getShape ()Lspace/kscience/kmath/nd/ShapeND;
 }
 
 public final class space/kscience/kmath/nd/Int16RingND : space/kscience/kmath/nd/Int16RingOpsND, space/kscience/kmath/nd/RingND, space/kscience/kmath/operations/NumbersAddOps {
-	public synthetic fun <init> ([ILkotlin/jvm/internal/DefaultConstructorMarker;)V
-	public fun getShape-IIYLAfE ()[I
+	public fun <init> (Lspace/kscience/kmath/nd/ShapeND;)V
+	public fun getShape ()Lspace/kscience/kmath/nd/ShapeND;
 	public synthetic fun number (Ljava/lang/Number;)Ljava/lang/Object;
 	public fun number (Ljava/lang/Number;)Lspace/kscience/kmath/nd/BufferND;
 }
@@ -1241,8 +1238,8 @@ public final class space/kscience/kmath/nd/IntBufferND : space/kscience/kmath/nd
 }
 
 public final class space/kscience/kmath/nd/IntRingND : space/kscience/kmath/nd/IntRingOpsND, space/kscience/kmath/nd/RingND, space/kscience/kmath/operations/NumbersAddOps {
-	public synthetic fun <init> ([ILkotlin/jvm/internal/DefaultConstructorMarker;)V
-	public fun getShape-IIYLAfE ()[I
+	public fun <init> (Lspace/kscience/kmath/nd/ShapeND;)V
+	public fun getShape ()Lspace/kscience/kmath/nd/ShapeND;
 	public synthetic fun number (Ljava/lang/Number;)Ljava/lang/Object;
 	public fun number (Ljava/lang/Number;)Lspace/kscience/kmath/nd/BufferND;
 }
@@ -1253,9 +1250,9 @@ public final class space/kscience/kmath/nd/IntRingNDKt {
 
 public abstract class space/kscience/kmath/nd/IntRingOpsND : space/kscience/kmath/nd/BufferedRingOpsND {
 	public static final field Companion Lspace/kscience/kmath/nd/IntRingOpsND$Companion;
-	public synthetic fun structureND-qL90JFI ([ILkotlin/jvm/functions/Function2;)Lspace/kscience/kmath/nd/BufferND;
-	public fun structureND-qL90JFI ([ILkotlin/jvm/functions/Function2;)Lspace/kscience/kmath/nd/IntBufferND;
-	public synthetic fun structureND-qL90JFI ([ILkotlin/jvm/functions/Function2;)Lspace/kscience/kmath/nd/StructureND;
+	public synthetic fun structureND (Lspace/kscience/kmath/nd/ShapeND;Lkotlin/jvm/functions/Function2;)Lspace/kscience/kmath/nd/BufferND;
+	public fun structureND (Lspace/kscience/kmath/nd/ShapeND;Lkotlin/jvm/functions/Function2;)Lspace/kscience/kmath/nd/IntBufferND;
+	public synthetic fun structureND (Lspace/kscience/kmath/nd/ShapeND;Lkotlin/jvm/functions/Function2;)Lspace/kscience/kmath/nd/StructureND;
 }
 
 public final class space/kscience/kmath/nd/IntRingOpsND$Companion : space/kscience/kmath/nd/IntRingOpsND {
@@ -1302,12 +1299,12 @@ public final class space/kscience/kmath/nd/OperationsNDKt {
 }
 
 public final class space/kscience/kmath/nd/PermutedMutableStructureND : space/kscience/kmath/nd/MutableStructureND {
-	public synthetic fun <init> (Lspace/kscience/kmath/nd/MutableStructureND;[ILkotlin/jvm/functions/Function1;ILkotlin/jvm/internal/DefaultConstructorMarker;)V
-	public synthetic fun <init> (Lspace/kscience/kmath/nd/MutableStructureND;[ILkotlin/jvm/functions/Function1;Lkotlin/jvm/internal/DefaultConstructorMarker;)V
+	public fun <init> (Lspace/kscience/kmath/nd/MutableStructureND;Lspace/kscience/kmath/nd/ShapeND;Lkotlin/jvm/functions/Function1;)V
+	public synthetic fun <init> (Lspace/kscience/kmath/nd/MutableStructureND;Lspace/kscience/kmath/nd/ShapeND;Lkotlin/jvm/functions/Function1;ILkotlin/jvm/internal/DefaultConstructorMarker;)V
 	public fun get ([I)Ljava/lang/Object;
 	public final fun getOrigin ()Lspace/kscience/kmath/nd/MutableStructureND;
 	public final fun getPermutation ()Lkotlin/jvm/functions/Function1;
-	public fun getShape-IIYLAfE ()[I
+	public fun getShape ()Lspace/kscience/kmath/nd/ShapeND;
 	public fun set ([ILjava/lang/Object;)V
 }
 
@@ -1316,13 +1313,13 @@ public final class space/kscience/kmath/nd/PermutedStructureND : space/kscience/
 	public fun get ([I)Ljava/lang/Object;
 	public final fun getOrigin ()Lspace/kscience/kmath/nd/StructureND;
 	public final fun getPermutation ()Lkotlin/jvm/functions/Function1;
-	public fun getShape-IIYLAfE ()[I
+	public fun getShape ()Lspace/kscience/kmath/nd/ShapeND;
 }
 
 public final class space/kscience/kmath/nd/PermutedStructureNDKt {
+	public static final fun permute (Lspace/kscience/kmath/nd/MutableStructureND;Lspace/kscience/kmath/nd/ShapeND;Lkotlin/jvm/functions/Function1;)Lspace/kscience/kmath/nd/PermutedMutableStructureND;
 	public static final fun permute (Lspace/kscience/kmath/nd/StructureND;Lkotlin/jvm/functions/Function1;)Lspace/kscience/kmath/nd/PermutedStructureND;
-	public static final fun permute-_A0By-k (Lspace/kscience/kmath/nd/MutableStructureND;[ILkotlin/jvm/functions/Function1;)Lspace/kscience/kmath/nd/PermutedMutableStructureND;
-	public static synthetic fun permute-_A0By-k$default (Lspace/kscience/kmath/nd/MutableStructureND;[ILkotlin/jvm/functions/Function1;ILjava/lang/Object;)Lspace/kscience/kmath/nd/PermutedMutableStructureND;
+	public static synthetic fun permute$default (Lspace/kscience/kmath/nd/MutableStructureND;Lspace/kscience/kmath/nd/ShapeND;Lkotlin/jvm/functions/Function1;ILjava/lang/Object;)Lspace/kscience/kmath/nd/PermutedMutableStructureND;
 }
 
 public final class space/kscience/kmath/nd/PrimitiveStructureNDKt {
@@ -1349,10 +1346,10 @@ public final class space/kscience/kmath/nd/RingOpsND$Companion {
 
 public final class space/kscience/kmath/nd/RowStrides : space/kscience/kmath/nd/Strides {
 	public static final field Companion Lspace/kscience/kmath/nd/RowStrides$Companion;
-	public synthetic fun <init> ([ILkotlin/jvm/internal/DefaultConstructorMarker;)V
+	public fun <init> (Lspace/kscience/kmath/nd/ShapeND;)V
 	public fun equals (Ljava/lang/Object;)Z
 	public fun getLinearSize ()I
-	public fun getShape-IIYLAfE ()[I
+	public fun getShape ()Lspace/kscience/kmath/nd/ShapeND;
 	public fun hashCode ()I
 	public fun index (I)[I
 }
@@ -1364,7 +1361,7 @@ public abstract interface class space/kscience/kmath/nd/ShapeIndexer : java/lang
 	public abstract fun asSequence ()Lkotlin/sequences/Sequence;
 	public abstract fun equals (Ljava/lang/Object;)Z
 	public abstract fun getLinearSize ()I
-	public abstract fun getShape-IIYLAfE ()[I
+	public abstract fun getShape ()Lspace/kscience/kmath/nd/ShapeND;
 	public abstract fun hashCode ()I
 	public abstract fun index (I)[I
 	public fun iterator ()Ljava/util/Iterator;
@@ -1372,54 +1369,49 @@ public abstract interface class space/kscience/kmath/nd/ShapeIndexer : java/lang
 }
 
 public final class space/kscience/kmath/nd/ShapeIndicesKt {
-	public static final fun Strides-dNlrn20 ([I)Lspace/kscience/kmath/nd/Strides;
+	public static final fun Strides (Lspace/kscience/kmath/nd/ShapeND;)Lspace/kscience/kmath/nd/Strides;
 }
 
 public final class space/kscience/kmath/nd/ShapeMismatchException : java/lang/RuntimeException {
-	public synthetic fun <init> ([I[ILkotlin/jvm/internal/DefaultConstructorMarker;)V
-	public final fun getActual-IIYLAfE ()[I
-	public final fun getExpected-IIYLAfE ()[I
+	public fun <init> (Lspace/kscience/kmath/nd/ShapeND;Lspace/kscience/kmath/nd/ShapeND;)V
+	public final fun getActual ()Lspace/kscience/kmath/nd/ShapeND;
+	public final fun getExpected ()Lspace/kscience/kmath/nd/ShapeND;
 }
 
 public final class space/kscience/kmath/nd/ShapeND {
-	public static final synthetic fun box-impl ([I)Lspace/kscience/kmath/nd/ShapeND;
-	public static fun constructor-impl ([I)[I
+	public fun <init> ([I)V
 	public fun equals (Ljava/lang/Object;)Z
-	public static fun equals-impl ([ILjava/lang/Object;)Z
-	public static final fun equals-impl0 ([I[I)Z
-	public static final fun get-impl ([II)I
-	public static final fun getSize-impl ([I)I
+	public final fun get (I)I
+	public final fun getArray ()[I
+	public final fun getSize ()I
 	public fun hashCode ()I
-	public static fun hashCode-impl ([I)I
 	public fun toString ()Ljava/lang/String;
-	public static fun toString-impl ([I)Ljava/lang/String;
-	public final synthetic fun unbox-impl ()[I
 }
 
 public final class space/kscience/kmath/nd/ShapeNDKt {
-	public static final fun ShapeND (I[I)[I
-	public static final fun asArray-dNlrn20 ([I)[I
-	public static final fun asList-dNlrn20 ([I)Ljava/util/List;
-	public static final fun component1-dNlrn20 ([I)I
-	public static final fun component2-dNlrn20 ([I)I
-	public static final fun component3-dNlrn20 ([I)I
-	public static final fun contentEquals-9Nqdy04 ([I[I)Z
-	public static final fun contentHashCode-dNlrn20 ([I)I
-	public static final fun first-dNlrn20 ([I)I
-	public static final fun first-qL90JFI ([II)[I
-	public static final fun forEach-qL90JFI ([ILkotlin/jvm/functions/Function1;)V
-	public static final fun forEachIndexed-qL90JFI ([ILkotlin/jvm/functions/Function2;)V
-	public static final fun getIndices-dNlrn20 ([I)Lkotlin/ranges/IntRange;
-	public static final fun getLinearSize-dNlrn20 ([I)I
-	public static final fun isEmpty-dNlrn20 ([I)Z
-	public static final fun isNotEmpty-dNlrn20 ([I)Z
-	public static final fun last-dNlrn20 ([I)I
-	public static final fun last-qL90JFI ([II)[I
-	public static final fun plus-9Nqdy04 ([I[I)[I
-	public static final fun plus-qL90JFI ([I[I)[I
-	public static final fun slice-qL90JFI ([ILkotlin/ranges/IntRange;)[I
-	public static final fun toArray-dNlrn20 ([I)[I
-	public static final fun transposed-bYNkpeI ([III)[I
+	public static final fun ShapeND (I[I)Lspace/kscience/kmath/nd/ShapeND;
+	public static final fun asArray (Lspace/kscience/kmath/nd/ShapeND;)[I
+	public static final fun asList (Lspace/kscience/kmath/nd/ShapeND;)Ljava/util/List;
+	public static final fun component1 (Lspace/kscience/kmath/nd/ShapeND;)I
+	public static final fun component2 (Lspace/kscience/kmath/nd/ShapeND;)I
+	public static final fun component3 (Lspace/kscience/kmath/nd/ShapeND;)I
+	public static final fun contentEquals (Lspace/kscience/kmath/nd/ShapeND;Lspace/kscience/kmath/nd/ShapeND;)Z
+	public static final fun contentHashCode (Lspace/kscience/kmath/nd/ShapeND;)I
+	public static final fun first (Lspace/kscience/kmath/nd/ShapeND;)I
+	public static final fun first (Lspace/kscience/kmath/nd/ShapeND;I)Lspace/kscience/kmath/nd/ShapeND;
+	public static final fun forEach (Lspace/kscience/kmath/nd/ShapeND;Lkotlin/jvm/functions/Function1;)V
+	public static final fun forEachIndexed (Lspace/kscience/kmath/nd/ShapeND;Lkotlin/jvm/functions/Function2;)V
+	public static final fun getIndices (Lspace/kscience/kmath/nd/ShapeND;)Lkotlin/ranges/IntRange;
+	public static final fun getLinearSize (Lspace/kscience/kmath/nd/ShapeND;)I
+	public static final fun isEmpty (Lspace/kscience/kmath/nd/ShapeND;)Z
+	public static final fun isNotEmpty (Lspace/kscience/kmath/nd/ShapeND;)Z
+	public static final fun last (Lspace/kscience/kmath/nd/ShapeND;)I
+	public static final fun last (Lspace/kscience/kmath/nd/ShapeND;I)Lspace/kscience/kmath/nd/ShapeND;
+	public static final fun plus (Lspace/kscience/kmath/nd/ShapeND;Lspace/kscience/kmath/nd/ShapeND;)Lspace/kscience/kmath/nd/ShapeND;
+	public static final fun plus (Lspace/kscience/kmath/nd/ShapeND;[I)Lspace/kscience/kmath/nd/ShapeND;
+	public static final fun slice (Lspace/kscience/kmath/nd/ShapeND;Lkotlin/ranges/IntRange;)Lspace/kscience/kmath/nd/ShapeND;
+	public static final fun toArray (Lspace/kscience/kmath/nd/ShapeND;)[I
+	public static final fun transposed (Lspace/kscience/kmath/nd/ShapeND;II)Lspace/kscience/kmath/nd/ShapeND;
 }
 
 public abstract class space/kscience/kmath/nd/Strides : space/kscience/kmath/nd/ShapeIndexer {
@@ -1453,7 +1445,7 @@ public abstract interface class space/kscience/kmath/nd/Structure2D : space/ksci
 	public fun getColumns ()Ljava/util/List;
 	public abstract fun getRowNum ()I
 	public fun getRows ()Ljava/util/List;
-	public fun getShape-IIYLAfE ()[I
+	public fun getShape ()Lspace/kscience/kmath/nd/ShapeND;
 }
 
 public final class space/kscience/kmath/nd/Structure2D$Companion {
@@ -1473,7 +1465,7 @@ public abstract interface class space/kscience/kmath/nd/StructureND : space/ksci
 	public abstract fun get ([I)Ljava/lang/Object;
 	public fun getAttributes ()Lspace/kscience/attributes/Attributes;
 	public fun getDimension ()I
-	public abstract fun getShape-IIYLAfE ()[I
+	public abstract fun getShape ()Lspace/kscience/kmath/nd/ShapeND;
 }
 
 public final class space/kscience/kmath/nd/StructureND$Companion {
@@ -1484,9 +1476,9 @@ public final class space/kscience/kmath/nd/StructureND$Companion {
 }
 
 public final class space/kscience/kmath/nd/StructureNDKt {
+	public static final fun BufferND--rwW0uw (Lkotlin/reflect/KType;Lspace/kscience/kmath/nd/ShapeND;Lkotlin/jvm/functions/Function1;)Lspace/kscience/kmath/nd/BufferND;
 	public static final fun BufferND--rwW0uw (Lkotlin/reflect/KType;Lspace/kscience/kmath/nd/Strides;Lkotlin/jvm/functions/Function1;)Lspace/kscience/kmath/nd/BufferND;
 	public static final fun BufferND--rwW0uw (Lkotlin/reflect/KType;[ILkotlin/jvm/functions/Function1;)Lspace/kscience/kmath/nd/BufferND;
-	public static final fun BufferND-vHyE91E (Lkotlin/reflect/KType;[ILkotlin/jvm/functions/Function1;)Lspace/kscience/kmath/nd/BufferND;
 	public static final fun contentEquals (Lspace/kscience/kmath/linear/LinearSpace;Lspace/kscience/kmath/nd/StructureND;Lspace/kscience/kmath/nd/StructureND;)Z
 	public static final fun contentEquals (Lspace/kscience/kmath/linear/LinearSpace;Lspace/kscience/kmath/nd/StructureND;Lspace/kscience/kmath/nd/StructureND;Ljava/lang/Comparable;)Z
 	public static final fun contentEquals (Lspace/kscience/kmath/nd/AlgebraND;Lspace/kscience/kmath/nd/StructureND;Lspace/kscience/kmath/nd/StructureND;)Z
@@ -1506,15 +1498,15 @@ public abstract interface class space/kscience/kmath/nd/StructureNDOfInt : space
 }
 
 public class space/kscience/kmath/nd/VirtualStructureND : space/kscience/kmath/nd/StructureND {
-	public synthetic fun <init> ([ILkotlin/jvm/functions/Function1;Lkotlin/jvm/internal/DefaultConstructorMarker;)V
+	public fun <init> (Lspace/kscience/kmath/nd/ShapeND;Lkotlin/jvm/functions/Function1;)V
 	public fun get ([I)Ljava/lang/Object;
 	public final fun getProducer ()Lkotlin/jvm/functions/Function1;
-	public fun getShape-IIYLAfE ()[I
+	public fun getShape ()Lspace/kscience/kmath/nd/ShapeND;
 }
 
 public abstract interface class space/kscience/kmath/nd/WithShape {
 	public fun getIndices ()Lspace/kscience/kmath/nd/ShapeIndexer;
-	public abstract fun getShape-IIYLAfE ()[I
+	public abstract fun getShape ()Lspace/kscience/kmath/nd/ShapeND;
 }
 
 public abstract interface class space/kscience/kmath/operations/Algebra : space/kscience/attributes/WithType {
@@ -2429,9 +2421,6 @@ public final class space/kscience/kmath/structures/BufferListKt {
 	public static final fun asList (Lspace/kscience/kmath/structures/Buffer;)Ljava/util/List;
 }
 
-public final class space/kscience/kmath/structures/BufferPrimitiveAccessKt {
-}
-
 public final class space/kscience/kmath/structures/BufferSlice : space/kscience/kmath/structures/BufferView {
 	public fun <init> (Lspace/kscience/kmath/structures/Buffer;II)V
 	public synthetic fun <init> (Lspace/kscience/kmath/structures/Buffer;IIILkotlin/jvm/internal/DefaultConstructorMarker;)V

kmath-core/build.gradle.kts

@@ -6,10 +6,10 @@ kscience {
     jvm()
     js()
     native()
-    wasm()
+    wasmJs()
 
     dependencies {
-        api(projects.attributesKt)
+        api(libs.attributes)
     }
 
     testDependencies {
@@ -44,7 +44,12 @@ readme {
     feature(
         id = "linear",
         ref = "src/commonMain/kotlin/space/kscience/kmath/operations/Algebra.kt",
-    ) { "Basic linear algebra operations (sums, products, etc.), backed by the `Space` API. Advanced linear algebra operations like matrix inversion and LU decomposition." }
+    ) {
+        """
+            Basic linear algebra operations (sums, products, etc.), backed by the `Space` API. 
+            Advanced linear algebra operations like matrix inversion and LU decomposition.
+        """.trimIndent()
+    }
 
     feature(
         id = "buffers",
@@ -56,7 +61,7 @@ readme {
         ref = "src/commonMain/kotlin/space/kscience/kmath/expressions"
     ) {
         """
-            By writing a single mathematical expression once, users will be able to apply different types of 
+            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.
         """.trimIndent()

kmath-core/src/commonMain/kotlin/space/kscience/kmath/domains/Domain1D.kt

@@ -7,6 +7,7 @@ package space.kscience.kmath.domains
 
 import space.kscience.kmath.UnstableKMathAPI
 import space.kscience.kmath.linear.Point
+import space.kscience.kmath.structures.Float64
 
 @UnstableKMathAPI
 public abstract class Domain1D<T : Comparable<T>>(public val range: ClosedRange<T>) : Domain<T> {
@@ -22,8 +23,8 @@ public abstract class Domain1D<T : Comparable<T>>(public val range: ClosedRange<
 
 @UnstableKMathAPI
 public class DoubleDomain1D(
-    @Suppress("CanBeParameter") public val doubleRange: ClosedFloatingPointRange<Double>,
-) : Domain1D<Double>(doubleRange), Float64Domain {
+    public val doubleRange: ClosedFloatingPointRange<Float64>,
+) : Domain1D<Float64>(doubleRange), Float64Domain {
     override fun getLowerBound(num: Int): Double {
         require(num == 0)
         return range.start
@@ -55,5 +56,5 @@ public class DoubleDomain1D(
 }
 
 @UnstableKMathAPI
-public val Domain1D<Double>.center: Double
+public val Domain1D<Float64>.center: Double
     get() = (range.endInclusive + range.start) / 2

kmath-core/src/commonMain/kotlin/space/kscience/kmath/domains/Float64Domain.kt

@@ -5,6 +5,7 @@
 package space.kscience.kmath.domains
 
 import space.kscience.kmath.UnstableKMathAPI
+import space.kscience.kmath.structures.Float64
 
 /**
  * n-dimensional volume
@@ -12,7 +13,7 @@ import space.kscience.kmath.UnstableKMathAPI
  * @author Alexander Nozik
  */
 @UnstableKMathAPI
-public interface Float64Domain : Domain<Double> {
+public interface Float64Domain : Domain<Float64> {
     /**
      * Global lower edge
      * @param num axis number

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

@@ -7,6 +7,7 @@ package space.kscience.kmath.domains
 import space.kscience.kmath.UnstableKMathAPI
 import space.kscience.kmath.linear.Point
 import space.kscience.kmath.structures.Buffer
+import space.kscience.kmath.structures.Float64
 import space.kscience.kmath.structures.Float64Buffer
 import space.kscience.kmath.structures.indices
 
@@ -15,7 +16,7 @@ import space.kscience.kmath.structures.indices
  * and a [Buffer] of upper boundaries. Upper should be greater or equals than lower.
  */
 @UnstableKMathAPI
-public class HyperSquareDomain(public val lower: Buffer<Double>, public val upper: Buffer<Double>) : Float64Domain {
+public class HyperSquareDomain(public val lower: Buffer<Float64>, public val upper: Buffer<Float64>) : Float64Domain {
     init {
         require(lower.size == upper.size) {
             "Domain borders size mismatch. Lower borders size is ${lower.size}, but upper borders size is ${upper.size}."
@@ -29,7 +30,7 @@ public class HyperSquareDomain(public val lower: Buffer<Double>, public val uppe
 
     public val center: Float64Buffer get() = Float64Buffer(dimension) { (lower[it] + upper[it]) / 2.0 }
 
-    override operator fun contains(point: Point<Double>): Boolean = point.indices.all { i ->
+    override operator fun contains(point: Point<Float64>): Boolean = point.indices.all { i ->
         point[i] in lower[i]..upper[i]
     }
 

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

@@ -6,10 +6,11 @@ package space.kscience.kmath.domains
 
 import space.kscience.kmath.UnstableKMathAPI
 import space.kscience.kmath.linear.Point
+import space.kscience.kmath.structures.Float64
 
 @UnstableKMathAPI
 public class UnconstrainedDomain(override val dimension: Int) : Float64Domain {
-    override operator fun contains(point: Point<Double>): Boolean = true
+    override operator fun contains(point: Point<Float64>): Boolean = true
 
     override fun getLowerBound(num: Int): Double = Double.NEGATIVE_INFINITY
 

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

@@ -126,7 +126,7 @@ public class DSCompiler<T, out A : Algebra<T>> internal constructor(
      * If all orders are set to 0, then the 0<sup>th</sup> order derivative is returned, which is the value of the
      * function.
      *
-     * The indices of derivatives are between 0 and [size] &minus; 1. Their specific order is fixed for a given compiler, but
+     * The indices of derivatives are between 0 and [getSize] &minus; 1. Their specific order is fixed for a given compiler, but
      * otherwise not publicly specified. There are however some simple cases which have guaranteed indices:
      *
      *  * the index of 0<sup>th</sup> order derivative is always 0
@@ -209,12 +209,12 @@ internal fun <T, A> DSCompiler<T, A>.pow(
     n: Int,
     result: MutableBuffer<T>,
     resultOffset: Int,
-) where A : Field<T>, A : PowerOperations<T> = algebra {
+): Unit where A : Field<T>, A : PowerOperations<T> = algebra {
     if (n == 0) {
         // special case, x^0 = 1 for all x
         result[resultOffset] = one
         result.fill(zero, resultOffset + 1, resultOffset + size)
-        return
+        return Unit
     }
 
     // create the power function value and derivatives