Rewrite EJML module by dropping ejml-simple abstraction level; multiple build script changes

.github/workflows/pages.yml

@@ -30,9 +30,7 @@ jobs:
           restore-keys: |
             ${{ runner.os }}-gradle-
       - name: Build
-        run: |
+        run: ./gradlew dokkaHtmlMultiModule --no-daemon --no-parallel --stacktrace
-          ./gradlew dokkaHtmlMultiModule --no-daemon --no-parallel --stacktrace
-          mv build/dokka/htmlMultiModule/-modules.html build/dokka/htmlMultiModule/index.html
       - name: Deploy to GitHub Pages
         uses: JamesIves/github-pages-deploy-action@4.1.0
         with:

CHANGELOG.md

@@ -10,7 +10,7 @@
 - Blocking chains and Statistics
 - Multiplatform integration
 - Integration for any Field element
-- Extendend operations for ND4J fields
+- Extended operations for ND4J fields
 
 ### Changed
 - Exponential operations merged with hyperbolic functions
@@ -24,6 +24,7 @@
 - Redesign MST. Remove MSTExpression.
 - Move MST to core
 - Separated benchmarks and examples
+- Rewritten EJML module without ejml-simple
 
 ### Deprecated
 

benchmarks/build.gradle.kts

@@ -9,14 +9,10 @@ sourceSets.register("benchmarks")
 
 repositories {
     mavenCentral()
-    jcenter()
     maven("https://repo.kotlin.link")
     maven("https://clojars.org/repo")
-    maven("https://dl.bintray.com/egor-bogomolov/astminer/")
-    maven("https://dl.bintray.com/hotkeytlt/maven")
     maven("https://jitpack.io")
-    maven {
+    maven("http://logicrunch.research.it.uu.se/maven") {
-        setUrl("http://logicrunch.research.it.uu.se/maven/")
         isAllowInsecureProtocol = true
     }
 }

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

@@ -10,7 +10,7 @@ import kotlinx.benchmark.Blackhole
 import kotlinx.benchmark.Scope
 import kotlinx.benchmark.State
 import space.kscience.kmath.commons.linear.CMLinearSpace
-import space.kscience.kmath.ejml.EjmlLinearSpace
+import space.kscience.kmath.ejml.EjmlLinearSpaceDDRM
 import space.kscience.kmath.linear.LinearSpace
 import space.kscience.kmath.linear.invoke
 import space.kscience.kmath.operations.DoubleField
@@ -29,8 +29,8 @@ internal class DotBenchmark {
         val cmMatrix1 = CMLinearSpace { matrix1.toCM() }
         val cmMatrix2 = CMLinearSpace { matrix2.toCM() }
 
-        val ejmlMatrix1 = EjmlLinearSpace { matrix1.toEjml() }
+        val ejmlMatrix1 = EjmlLinearSpaceDDRM { matrix1.toEjml() }
-        val ejmlMatrix2 = EjmlLinearSpace { matrix2.toEjml() }
+        val ejmlMatrix2 = EjmlLinearSpaceDDRM { matrix2.toEjml() }
     }
 
     @Benchmark
@@ -42,14 +42,14 @@ internal class DotBenchmark {
 
     @Benchmark
     fun ejmlDot(blackhole: Blackhole) {
-        EjmlLinearSpace {
+        EjmlLinearSpaceDDRM {
             blackhole.consume(ejmlMatrix1 dot ejmlMatrix2)
         }
     }
 
     @Benchmark
     fun ejmlDotWithConversion(blackhole: Blackhole) {
-        EjmlLinearSpace {
+        EjmlLinearSpaceDDRM {
             blackhole.consume(matrix1 dot matrix2)
         }
     }

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

@@ -11,25 +11,26 @@ import kotlinx.benchmark.Scope
 import kotlinx.benchmark.State
 import space.kscience.kmath.commons.linear.CMLinearSpace
 import space.kscience.kmath.commons.linear.inverse
-import space.kscience.kmath.ejml.EjmlLinearSpace
+import space.kscience.kmath.ejml.EjmlLinearSpaceDDRM
-import space.kscience.kmath.ejml.inverse
+import space.kscience.kmath.linear.InverseMatrixFeature
 import space.kscience.kmath.linear.LinearSpace
 import space.kscience.kmath.linear.inverseWithLup
 import space.kscience.kmath.linear.invoke
+import space.kscience.kmath.nd.getFeature
 import kotlin.random.Random
 
 @State(Scope.Benchmark)
 internal class MatrixInverseBenchmark {
-    companion object {
+    private companion object {
-        val random = Random(1224)
+        private val random = Random(1224)
-        const val dim = 100
+        private const val dim = 100
 
         private val space = LinearSpace.real
 
         //creating invertible matrix
-        val u = space.buildMatrix(dim, dim) { i, j -> if (i <= j) random.nextDouble() else 0.0 }
+        private val u = space.buildMatrix(dim, dim) { i, j -> if (i <= j) random.nextDouble() else 0.0 }
-        val l = space.buildMatrix(dim, dim) { i, j -> if (i >= j) random.nextDouble() else 0.0 }
+        private val l = space.buildMatrix(dim, dim) { i, j -> if (i >= j) random.nextDouble() else 0.0 }
-        val matrix = space { l dot u }
+        private val matrix = space { l dot u }
     }
 
     @Benchmark
@@ -46,8 +47,8 @@ internal class MatrixInverseBenchmark {
 
     @Benchmark
     fun ejmlInverse(blackhole: Blackhole) {
-        with(EjmlLinearSpace) {
+        with(EjmlLinearSpaceDDRM) {
-            blackhole.consume(inverse(matrix))
+            blackhole.consume(matrix.getFeature<InverseMatrixFeature<Double>>()?.inverse)
         }
     }
 }

build.gradle.kts

@@ -4,14 +4,12 @@ plugins {
 
 allprojects {
     repositories {
-        jcenter()
         maven("https://clojars.org/repo")
-        maven("https://dl.bintray.com/egor-bogomolov/astminer/")
-        maven("https://dl.bintray.com/hotkeytlt/maven")
         maven("https://jitpack.io")
-        maven("http://logicrunch.research.it.uu.se/maven/") {
+        maven("http://logicrunch.research.it.uu.se/maven") {
             isAllowInsecureProtocol = true
         }
+        maven("https://maven.pkg.jetbrains.space/public/p/kotlinx-html/maven")
         mavenCentral()
     }
 
@@ -23,22 +21,16 @@ subprojects {
     if (name.startsWith("kmath")) apply<MavenPublishPlugin>()
 
     afterEvaluate {
-        tasks.withType<org.jetbrains.dokka.gradle.DokkaTask> {
+        tasks.withType<org.jetbrains.dokka.gradle.DokkaTaskPartial> {
-            dokkaSourceSets.all {
+            dependsOn(tasks.getByName("assemble"))
-                val readmeFile = File(this@subprojects.projectDir, "./README.md")
-                if (readmeFile.exists())
-                    includes.setFrom(includes + readmeFile.absolutePath)
 
-                arrayOf(
+            dokkaSourceSets.all {
-                    "http://ejml.org/javadoc/",
+                val readmeFile = File(this@subprojects.projectDir, "README.md")
-                    "https://commons.apache.org/proper/commons-math/javadocs/api-3.6.1/",
+                if (readmeFile.exists()) includes.setFrom(includes + readmeFile.absolutePath)
-                    "https://deeplearning4j.org/api/latest/"
+                externalDocumentationLink("http://ejml.org/javadoc/")
-                ).map { java.net.URL("${it}package-list") to java.net.URL(it) }.forEach { (a, b) ->
+                externalDocumentationLink("https://commons.apache.org/proper/commons-math/javadocs/api-3.6.1/")
-                    externalDocumentationLink {
+                externalDocumentationLink("https://deeplearning4j.org/api/latest/")
-                        packageListUrl.set(a)
+                externalDocumentationLink("https://kotlin.github.io/kotlinx.coroutines/kotlinx-coroutines-core/")
-                        url.set(b)
-                    }
-                }
             }
         }
     }

docs/templates/ARTIFACT-TEMPLATE.md

@@ -6,8 +6,7 @@ The Maven coordinates of this project are `${group}:${name}:${version}`.
 ```gradle
 repositories {
     maven { url 'https://repo.kotlin.link' }
-    maven { url 'https://dl.bintray.com/hotkeytlt/maven' }
+    mavenCentral()
-    maven { url "https://dl.bintray.com/kotlin/kotlin-eap" } // include for builds based on kotlin-eap
 }
 
 dependencies {
@@ -18,8 +17,7 @@ dependencies {
 ```kotlin
 repositories {
     maven("https://repo.kotlin.link")
-    maven("https://dl.bintray.com/kotlin/kotlin-eap") // include for builds based on kotlin-eap
+    mavenCentral()
-    maven("https://dl.bintray.com/hotkeytlt/maven") // required for a
 }
 
 dependencies {

examples/build.gradle.kts

@@ -4,14 +4,11 @@ plugins {
 
 repositories {
     mavenCentral()
-    jcenter()
     maven("https://repo.kotlin.link")
     maven("https://clojars.org/repo")
-    maven("https://dl.bintray.com/egor-bogomolov/astminer/")
-    maven("https://dl.bintray.com/hotkeytlt/maven")
     maven("https://jitpack.io")
-    maven{
+    maven("https://maven.pkg.jetbrains.space/kotlin/p/kotlin/kotlin-js-wrappers")
-        setUrl("http://logicrunch.research.it.uu.se/maven/")
+    maven("http://logicrunch.research.it.uu.se/maven") {
         isAllowInsecureProtocol = true
     }
 }

kmath-ast/README.md

@@ -16,8 +16,7 @@ The Maven coordinates of this project are `space.kscience:kmath-ast:0.3.0-dev-7`
 ```gradle
 repositories {
     maven { url 'https://repo.kotlin.link' }
-    maven { url 'https://dl.bintray.com/hotkeytlt/maven' }
+    mavenCentral()
-    maven { url "https://dl.bintray.com/kotlin/kotlin-eap" } // include for builds based on kotlin-eap
 }
 
 dependencies {
@@ -28,8 +27,7 @@ dependencies {
 ```kotlin
 repositories {
     maven("https://repo.kotlin.link")
-    maven("https://dl.bintray.com/kotlin/kotlin-eap") // include for builds based on kotlin-eap
+    mavenCentral()
-    maven("https://dl.bintray.com/hotkeytlt/maven") // required for a
 }
 
 dependencies {

kmath-complex/README.md

@@ -14,8 +14,7 @@ The Maven coordinates of this project are `space.kscience:kmath-complex:0.3.0-de
 ```gradle
 repositories {
     maven { url 'https://repo.kotlin.link' }
-    maven { url 'https://dl.bintray.com/hotkeytlt/maven' }
+    mavenCentral()
-    maven { url "https://dl.bintray.com/kotlin/kotlin-eap" } // include for builds based on kotlin-eap
 }
 
 dependencies {
@@ -26,8 +25,7 @@ dependencies {
 ```kotlin
 repositories {
     maven("https://repo.kotlin.link")
-    maven("https://dl.bintray.com/kotlin/kotlin-eap") // include for builds based on kotlin-eap
+    mavenCentral()
-    maven("https://dl.bintray.com/hotkeytlt/maven") // required for a
 }
 
 dependencies {

kmath-core/README.md

@@ -21,8 +21,7 @@ The Maven coordinates of this project are `space.kscience:kmath-core:0.3.0-dev-7
 ```gradle
 repositories {
     maven { url 'https://repo.kotlin.link' }
-    maven { url 'https://dl.bintray.com/hotkeytlt/maven' }
+    mavenCentral()
-    maven { url "https://dl.bintray.com/kotlin/kotlin-eap" } // include for builds based on kotlin-eap
 }
 
 dependencies {
@@ -33,8 +32,7 @@ dependencies {
 ```kotlin
 repositories {
     maven("https://repo.kotlin.link")
-    maven("https://dl.bintray.com/kotlin/kotlin-eap") // include for builds based on kotlin-eap
+    mavenCentral()
-    maven("https://dl.bintray.com/hotkeytlt/maven") // required for a
 }
 
 dependencies {

kmath-ejml/README.md

@@ -2,9 +2,9 @@
 
 EJML based linear algebra implementation.
 
- - [ejml-vector](src/main/kotlin/space/kscience/kmath/ejml/EjmlVector.kt) : The Point implementation using SimpleMatrix.
+ - [ejml-vector](src/main/kotlin/space/kscience/kmath/ejml/EjmlVector.kt) : Point implementations.
- - [ejml-matrix](src/main/kotlin/space/kscience/kmath/ejml/EjmlMatrix.kt) : The Matrix implementation using SimpleMatrix.
+ - [ejml-matrix](src/main/kotlin/space/kscience/kmath/ejml/EjmlMatrix.kt) : Matrix implementation.
- - [ejml-linear-space](src/main/kotlin/space/kscience/kmath/ejml/EjmlLinearSpace.kt) : The LinearSpace implementation using SimpleMatrix.
+ - [ejml-linear-space](src/main/kotlin/space/kscience/kmath/ejml/EjmlLinearSpace.kt) : LinearSpace implementations.
 
 
 ## Artifact:
@@ -15,8 +15,7 @@ The Maven coordinates of this project are `space.kscience:kmath-ejml:0.3.0-dev-7
 ```gradle
 repositories {
     maven { url 'https://repo.kotlin.link' }
-    maven { url 'https://dl.bintray.com/hotkeytlt/maven' }
+    mavenCentral()
-    maven { url "https://dl.bintray.com/kotlin/kotlin-eap" } // include for builds based on kotlin-eap
 }
 
 dependencies {
@@ -27,8 +26,7 @@ dependencies {
 ```kotlin
 repositories {
     maven("https://repo.kotlin.link")
-    maven("https://dl.bintray.com/kotlin/kotlin-eap") // include for builds based on kotlin-eap
+    mavenCentral()
-    maven("https://dl.bintray.com/hotkeytlt/maven") // required for a
 }
 
 dependencies {

kmath-ejml/build.gradle.kts

@@ -4,7 +4,7 @@ plugins {
 }
 
 dependencies {
-    api("org.ejml:ejml-simple:0.40")
+    api("org.ejml:ejml-ddense:0.40")
     api(project(":kmath-core"))
 }
 
@@ -14,19 +14,19 @@ readme {
 
     feature(
         id = "ejml-vector",
-        description = "The Point implementation using SimpleMatrix.",
+        description = "Point implementations.",
         ref = "src/main/kotlin/space/kscience/kmath/ejml/EjmlVector.kt"
     )
 
     feature(
         id = "ejml-matrix",
-        description = "The Matrix implementation using SimpleMatrix.",
+        description = "Matrix implementation.",
         ref = "src/main/kotlin/space/kscience/kmath/ejml/EjmlMatrix.kt"
     )
 
     feature(
         id = "ejml-linear-space",
-        description = "The LinearSpace implementation using SimpleMatrix.",
+        description = "LinearSpace implementations.",
         ref = "src/main/kotlin/space/kscience/kmath/ejml/EjmlLinearSpace.kt"
     )
 }

kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/EjmlLinearSpace.kt

@@ -5,45 +5,71 @@
 
 package space.kscience.kmath.ejml
 
+import org.ejml.data.DMatrix
+import org.ejml.data.DMatrixD1
+import org.ejml.data.DMatrixRMaj
+import org.ejml.dense.row.CommonOps_DDRM
 import org.ejml.dense.row.factory.DecompositionFactory_DDRM
-import org.ejml.simple.SimpleMatrix
 import space.kscience.kmath.linear.*
 import space.kscience.kmath.misc.UnstableKMathAPI
 import space.kscience.kmath.nd.StructureFeature
-import space.kscience.kmath.nd.getFeature
 import space.kscience.kmath.operations.DoubleField
+import space.kscience.kmath.operations.Ring
 import space.kscience.kmath.structures.DoubleBuffer
 import kotlin.reflect.KClass
 import kotlin.reflect.cast
 
 /**
- * Represents context of basic operations operating with [EjmlMatrix].
+ * [LinearSpace] implementation specialized for a certain EJML type.
+ *
+ * @param T the type of items in the matrices.
+ * @param A the element context type.
+ * @param M the EJML matrix type.
+ * @author Iaroslav Postovalov
+ */
+public abstract class EjmlLinearSpace<T : Any, out A : Ring<T>, M : org.ejml.data.Matrix> : LinearSpace<T, A> {
+    /**
+     * Converts this matrix to EJML one.
+     */
+    public abstract fun Matrix<T>.toEjml(): EjmlMatrix<T, M>
+
+    /**
+     * Converts this vector to EJML one.
+     */
+    public abstract fun Point<T>.toEjml(): EjmlVector<T, M>
+
+    public abstract override fun buildMatrix(
+        rows: Int,
+        columns: Int,
+        initializer: A.(i: Int, j: Int) -> T,
+    ): EjmlMatrix<T, M>
+
+    public abstract override fun buildVector(size: Int, initializer: A.(Int) -> T): EjmlVector<T, M>
+}
+
+/**
+ * [EjmlLinearSpace] implementation based on [CommonOps_DDRM], [DecompositionFactory_DDRM] operations and
+ * [DMatrixRMaj] matrices.
  *
  * @author Iaroslav Postovalov
- * @author Alexander Nozik
  */
-public object EjmlLinearSpace : LinearSpace<Double, DoubleField> {
+public object EjmlLinearSpaceDDRM : EjmlLinearSpace<Double, DoubleField, DMatrixRMaj>() {
     /**
      * The [DoubleField] reference.
      */
     public override val elementAlgebra: DoubleField get() = DoubleField
 
-    /**
+    @Suppress("UNCHECKED_CAST")
-     * Converts this matrix to EJML one.
+    public override fun Matrix<Double>.toEjml(): EjmlDoubleMatrix<DMatrixRMaj> = when {
-     */
+        this is EjmlDoubleMatrix<*> && origin is DMatrixRMaj -> this as EjmlDoubleMatrix<DMatrixRMaj>
-    @OptIn(UnstableKMathAPI::class)
-    public fun Matrix<Double>.toEjml(): EjmlMatrix = when (val matrix = origin) {
-        is EjmlMatrix -> matrix
         else -> buildMatrix(rowNum, colNum) { i, j -> get(i, j) }
     }
 
-    /**
+    @Suppress("UNCHECKED_CAST")
-     * Converts this vector to EJML one.
+    public override fun Point<Double>.toEjml(): EjmlDoubleVector<DMatrixRMaj> = when {
-     */
+        this is EjmlDoubleVector<*> && origin is DMatrixRMaj -> this as EjmlDoubleVector<DMatrixRMaj>
-    public fun Point<Double>.toEjml(): EjmlVector = when (this) {
+        else -> EjmlDoubleVector(DMatrixRMaj(size, 1).also {
-        is EjmlVector -> this
+            (0 until it.numRows).forEach { row -> it[row, 0] = get(row) }
-        else -> EjmlVector(SimpleMatrix(size, 1).also {
-            (0 until it.numRows()).forEach { row -> it[row, 0] = get(row) }
         })
     }
 
@@ -51,159 +77,178 @@ public object EjmlLinearSpace : LinearSpace<Double, DoubleField> {
         rows: Int,
         columns: Int,
         initializer: DoubleField.(i: Int, j: Int) -> Double,
-    ): EjmlMatrix = EjmlMatrix(SimpleMatrix(rows, columns).also {
+    ): EjmlDoubleMatrix<DMatrixRMaj> = EjmlDoubleMatrix(DMatrixRMaj(rows, columns).also {
         (0 until rows).forEach { row ->
-            (0 until columns).forEach { col -> it[row, col] = DoubleField.initializer(row, col) }
+            (0 until columns).forEach { col -> it[row, col] = elementAlgebra.initializer(row, col) }
         }
     })
 
-    public override fun buildVector(size: Int, initializer: DoubleField.(Int) -> Double): Point<Double> =
+    public override fun buildVector(
-        EjmlVector(SimpleMatrix(size, 1).also {
+        size: Int,
-            (0 until it.numRows()).forEach { row -> it[row, 0] = DoubleField.initializer(row) }
+        initializer: DoubleField.(Int) -> Double,
+    ): EjmlDoubleVector<DMatrixRMaj> = EjmlDoubleVector(DMatrixRMaj(size, 1).also {
+        (0 until it.numRows).forEach { row -> it[row, 0] = elementAlgebra.initializer(row) }
     })
 
-    private fun SimpleMatrix.wrapMatrix() = EjmlMatrix(this)
+    private fun <T : DMatrix> T.wrapMatrix() = EjmlDoubleMatrix(this)
-    private fun SimpleMatrix.wrapVector() = EjmlVector(this)
+    private fun <T : DMatrixD1> T.wrapVector() = EjmlDoubleVector(this)
 
     public override fun Matrix<Double>.unaryMinus(): Matrix<Double> = this * (-1.0)
 
-    public override fun Matrix<Double>.dot(other: Matrix<Double>): EjmlMatrix =
+    public override fun Matrix<Double>.dot(other: Matrix<Double>): EjmlDoubleMatrix<DMatrixRMaj> {
-        EjmlMatrix(toEjml().origin.mult(other.toEjml().origin))
+        val out = DMatrixRMaj(1, 1)
+        CommonOps_DDRM.mult(toEjml().origin, other.toEjml().origin, out)
+        return out.wrapMatrix()
+    }
 
-    public override fun Matrix<Double>.dot(vector: Point<Double>): EjmlVector =
+    public override fun Matrix<Double>.dot(vector: Point<Double>): EjmlDoubleVector<DMatrixRMaj> {
-        EjmlVector(toEjml().origin.mult(vector.toEjml().origin))
+        val out = DMatrixRMaj(1, 1)
+        CommonOps_DDRM.mult(toEjml().origin, vector.toEjml().origin, out)
+        return out.wrapVector()
+    }
 
-    public override operator fun Matrix<Double>.minus(other: Matrix<Double>): EjmlMatrix =
+    public override operator fun Matrix<Double>.minus(other: Matrix<Double>): EjmlDoubleMatrix<DMatrixRMaj> {
-        (toEjml().origin - other.toEjml().origin).wrapMatrix()
+        val out = DMatrixRMaj(1, 1)
+        CommonOps_DDRM.subtract(toEjml().origin, other.toEjml().origin, out)
+        return out.wrapMatrix()
+    }
 
-    public override operator fun Matrix<Double>.times(value: Double): EjmlMatrix =
+    public override operator fun Matrix<Double>.times(value: Double): EjmlDoubleMatrix<DMatrixRMaj> {
-        toEjml().origin.scale(value).wrapMatrix()
+        val res = this.toEjml().origin.copy()
+        CommonOps_DDRM.scale(value, res)
+        return res.wrapMatrix()
+    }
 
-    public override fun Point<Double>.unaryMinus(): EjmlVector =
+    public override fun Point<Double>.unaryMinus(): EjmlDoubleVector<DMatrixRMaj> {
-        toEjml().origin.negative().wrapVector()
+        val out = toEjml().origin.copy()
+        CommonOps_DDRM.changeSign(out)
+        return out.wrapVector()
+    }
 
-    public override fun Matrix<Double>.plus(other: Matrix<Double>): EjmlMatrix =
+    public override fun Matrix<Double>.plus(other: Matrix<Double>): EjmlDoubleMatrix<DMatrixRMaj> {
-        (toEjml().origin + other.toEjml().origin).wrapMatrix()
+        val out = DMatrixRMaj(1, 1)
+        CommonOps_DDRM.add(toEjml().origin, other.toEjml().origin, out)
+        return out.wrapMatrix()
+    }
 
-    public override fun Point<Double>.plus(other: Point<Double>): EjmlVector =
+    public override fun Point<Double>.plus(other: Point<Double>): EjmlDoubleVector<DMatrixRMaj> {
-        (toEjml().origin + other.toEjml().origin).wrapVector()
+        val out = DMatrixRMaj(1, 1)
+        CommonOps_DDRM.add(toEjml().origin, other.toEjml().origin, out)
+        return out.wrapVector()
+    }
 
-    public override fun Point<Double>.minus(other: Point<Double>): EjmlVector =
+    public override fun Point<Double>.minus(other: Point<Double>): EjmlDoubleVector<DMatrixRMaj> {
-        (toEjml().origin - other.toEjml().origin).wrapVector()
+        val out = DMatrixRMaj(1, 1)
+        CommonOps_DDRM.subtract(toEjml().origin, other.toEjml().origin, out)
+        return out.wrapVector()
+    }
 
-    public override fun Double.times(m: Matrix<Double>): EjmlMatrix =
+    public override fun Double.times(m: Matrix<Double>): EjmlDoubleMatrix<DMatrixRMaj> = m * this
-        m.toEjml().origin.scale(this).wrapMatrix()
 
-    public override fun Point<Double>.times(value: Double): EjmlVector =
+    public override fun Point<Double>.times(value: Double): EjmlDoubleVector<DMatrixRMaj> {
-        toEjml().origin.scale(value).wrapVector()
+        val res = this.toEjml().origin.copy()
+        CommonOps_DDRM.scale(value, res)
+        return res.wrapVector()
+    }
 
-    public override fun Double.times(v: Point<Double>): EjmlVector =
+    public override fun Double.times(v: Point<Double>): EjmlDoubleVector<DMatrixRMaj> = v * this
-        v.toEjml().origin.scale(this).wrapVector()
 
     @UnstableKMathAPI
     public override fun <F : StructureFeature> getFeature(structure: Matrix<Double>, type: KClass<out F>): F? {
-        //Return the feature if it is intrinsic to the structure
+        // Return the feature if it is intrinsic to the structure
         structure.getFeature(type)?.let { return it }
 
         val origin = structure.toEjml().origin
 
         return when (type) {
             InverseMatrixFeature::class -> object : InverseMatrixFeature<Double> {
-                override val inverse: Matrix<Double> by lazy { EjmlMatrix(origin.invert()) }
+                override val inverse: Matrix<Double> by lazy {
+                    val res = origin.copy()
+                    CommonOps_DDRM.invert(res)
+                    EjmlDoubleMatrix(res)
+                }
             }
 
             DeterminantFeature::class -> object : DeterminantFeature<Double> {
-                override val determinant: Double by lazy(origin::determinant)
+                override val determinant: Double by lazy { CommonOps_DDRM.det(DMatrixRMaj(origin)) }
             }
 
             SingularValueDecompositionFeature::class -> object : SingularValueDecompositionFeature<Double> {
                 private val svd by lazy {
-                    DecompositionFactory_DDRM.svd(origin.numRows(), origin.numCols(), true, true, false)
+                    DecompositionFactory_DDRM.svd(origin.numRows, origin.numCols, true, true, false)
-                        .apply { decompose(origin.ddrm.copy()) }
+                        .apply { decompose(origin.copy()) }
                 }
 
-                override val u: Matrix<Double> by lazy { EjmlMatrix(SimpleMatrix(svd.getU(null, false))) }
+                override val u: Matrix<Double> by lazy { EjmlDoubleMatrix(svd.getU(null, false)) }
-                override val s: Matrix<Double> by lazy { EjmlMatrix(SimpleMatrix(svd.getW(null))) }
+                override val s: Matrix<Double> by lazy { EjmlDoubleMatrix(svd.getW(null)) }
-                override val v: Matrix<Double> by lazy { EjmlMatrix(SimpleMatrix(svd.getV(null, false))) }
+                override val v: Matrix<Double> by lazy { EjmlDoubleMatrix(svd.getV(null, false)) }
                 override val singularValues: Point<Double> by lazy { DoubleBuffer(svd.singularValues) }
             }
 
             QRDecompositionFeature::class -> object : QRDecompositionFeature<Double> {
                 private val qr by lazy {
-                    DecompositionFactory_DDRM.qr().apply { decompose(origin.ddrm.copy()) }
+                    DecompositionFactory_DDRM.qr().apply { decompose(origin.copy()) }
                 }
 
                 override val q: Matrix<Double> by lazy {
-                    EjmlMatrix(SimpleMatrix(qr.getQ(null, false))) + OrthogonalFeature
+                    EjmlDoubleMatrix(qr.getQ(null, false)) + OrthogonalFeature
                 }
 
-                override val r: Matrix<Double> by lazy { EjmlMatrix(SimpleMatrix(qr.getR(null, false))) + UFeature }
+                override val r: Matrix<Double> by lazy { EjmlDoubleMatrix(qr.getR(null, false)) + UFeature }
             }
 
             CholeskyDecompositionFeature::class -> object : CholeskyDecompositionFeature<Double> {
                 override val l: Matrix<Double> by lazy {
                     val cholesky =
-                        DecompositionFactory_DDRM.chol(structure.rowNum, true).apply { decompose(origin.ddrm.copy()) }
+                        DecompositionFactory_DDRM.chol(structure.rowNum, true).apply { decompose(origin.copy()) }
 
-                    EjmlMatrix(SimpleMatrix(cholesky.getT(null))) + LFeature
+                    EjmlDoubleMatrix(cholesky.getT(null)) + LFeature
                 }
             }
 
             LupDecompositionFeature::class -> object : LupDecompositionFeature<Double> {
                 private val lup by lazy {
-                    DecompositionFactory_DDRM.lu(origin.numRows(), origin.numCols())
+                    DecompositionFactory_DDRM.lu(origin.numRows, origin.numCols).apply { decompose(origin.copy()) }
-                        .apply { decompose(origin.ddrm.copy()) }
                 }
 
                 override val l: Matrix<Double> by lazy {
-                    EjmlMatrix(SimpleMatrix(lup.getLower(null))) + LFeature
+                    EjmlDoubleMatrix(lup.getLower(null)) + LFeature
                 }
 
                 override val u: Matrix<Double> by lazy {
-                    EjmlMatrix(SimpleMatrix(lup.getUpper(null))) + UFeature
+                    EjmlDoubleMatrix(lup.getUpper(null)) + UFeature
                 }
 
-                override val p: Matrix<Double> by lazy { EjmlMatrix(SimpleMatrix(lup.getRowPivot(null))) }
+                override val p: Matrix<Double> by lazy { EjmlDoubleMatrix(lup.getRowPivot(null)) }
             }
 
             else -> null
         }?.let(type::cast)
     }
-}
 
-/**
+    /**
      * Solves for *x* in the following equation: *x = [a] <sup>-1</sup> &middot; [b]*.
      *
      * @param a the base matrix.
      * @param b n by p matrix.
      * @return the solution for 'x' that is n by p.
- * @author Iaroslav Postovalov
      */
-public fun EjmlLinearSpace.solve(a: Matrix<Double>, b: Matrix<Double>): EjmlMatrix =
+    public fun solve(a: Matrix<Double>, b: Matrix<Double>): EjmlDoubleMatrix<DMatrixRMaj> {
-    EjmlMatrix(a.toEjml().origin.solve(b.toEjml().origin))
+        val res = DMatrixRMaj(1, 1)
+        CommonOps_DDRM.solve(DMatrixRMaj(a.toEjml().origin), DMatrixRMaj(b.toEjml().origin), res)
+        return EjmlDoubleMatrix(res)
+    }
 
-/**
+    /**
      * Solves for *x* in the following equation: *x = [a] <sup>-1</sup> &middot; [b]*.
      *
      * @param a the base matrix.
      * @param b n by p vector.
      * @return the solution for 'x' that is n by p.
- * @author Iaroslav Postovalov
      */
-public fun EjmlLinearSpace.solve(a: Matrix<Double>, b: Point<Double>): EjmlVector =
+    public fun solve(a: Matrix<Double>, b: Point<Double>): EjmlDoubleVector<DMatrixRMaj> {
-    EjmlVector(a.toEjml().origin.solve(b.toEjml().origin))
+        val res = DMatrixRMaj(1, 1)
-
+        CommonOps_DDRM.solve(DMatrixRMaj(a.toEjml().origin), DMatrixRMaj(b.toEjml().origin), res)
-/**
+        return EjmlDoubleVector(res)
- * Inverts this matrix.
+    }
- *
+}
- * @author Alexander Nozik
- */
-@OptIn(UnstableKMathAPI::class)
-public fun EjmlMatrix.inverted(): EjmlMatrix = getFeature<InverseMatrixFeature<Double>>()!!.inverse as EjmlMatrix
-
-/**
- * Inverts the given matrix.
- *
- * @author Alexander Nozik
- */
-public fun EjmlLinearSpace.inverse(matrix: Matrix<Double>): Matrix<Double> = matrix.toEjml().inverted()

kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/EjmlMatrix.kt

@@ -5,18 +5,28 @@
 
 package space.kscience.kmath.ejml
 
-import org.ejml.simple.SimpleMatrix
+import org.ejml.data.DMatrix
-import space.kscience.kmath.linear.Matrix
+import org.ejml.data.Matrix
+import space.kscience.kmath.nd.Structure2D
 
 /**
- * The matrix implementation over EJML [SimpleMatrix].
+ * [space.kscience.kmath.linear.Matrix] implementation based on EJML [Matrix].
  *
- * @property origin the underlying [SimpleMatrix].
+ * @param T the type of elements contained in the buffer.
+ * @param M the type of EJML matrix.
+ * @property origin The underlying EJML matrix.
  * @author Iaroslav Postovalov
  */
-public class EjmlMatrix(public val origin: SimpleMatrix) : Matrix<Double> {
+public abstract class EjmlMatrix<T, out M : Matrix>(public open val origin: M) : Structure2D<T> {
-    public override val rowNum: Int get() = origin.numRows()
+    public override val rowNum: Int get() = origin.numRows
-    public override val colNum: Int get() = origin.numCols()
+    public override val colNum: Int get() = origin.numCols
+}
 
+/**
+ * [EjmlMatrix] specialization for [Double].
+ *
+ * @author Iaroslav Postovalov
+ */
+public class EjmlDoubleMatrix<out M : DMatrix>(public override val origin: M) : EjmlMatrix<Double, M>(origin) {
     public override operator fun get(i: Int, j: Int): Double = origin[i, j]
 }

kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/EjmlVector.kt

@@ -5,35 +5,41 @@
 
 package space.kscience.kmath.ejml
 
-import org.ejml.simple.SimpleMatrix
+import org.ejml.data.DMatrixD1
+import org.ejml.data.Matrix
 import space.kscience.kmath.linear.Point
 
 /**
- * Represents point over EJML [SimpleMatrix].
+ * [Point] implementation based on EJML [Matrix].
  *
- * @property origin the underlying [SimpleMatrix].
+ * @param T the type of elements contained in the buffer.
+ * @param M the type of EJML matrix.
+ * @property origin The underlying matrix.
  * @author Iaroslav Postovalov
  */
-public class EjmlVector internal constructor(public val origin: SimpleMatrix) : Point<Double> {
+public abstract class EjmlVector<out T, out M : Matrix>(public open val origin: M) : Point<T> {
     public override val size: Int
-        get() = origin.numRows()
+        get() = origin.numRows
 
-    init {
+    public override operator fun iterator(): Iterator<T> = object : Iterator<T> {
-        require(origin.numCols() == 1) { "Only single column matrices are allowed" }
-    }
-
-    public override operator fun get(index: Int): Double = origin[index]
-
-    public override operator fun iterator(): Iterator<Double> = object : Iterator<Double> {
         private var cursor: Int = 0
 
-        override fun next(): Double {
+        override fun next(): T {
             cursor += 1
-            return origin[cursor - 1]
+            return this@EjmlVector[cursor - 1]
         }
 
-        override fun hasNext(): Boolean = cursor < origin.numCols() * origin.numRows()
+        override fun hasNext(): Boolean = cursor < origin.numCols * origin.numRows
     }
 
     public override fun toString(): String = "EjmlVector(origin=$origin)"
 }
+
+/**
+ * [EjmlVector] specialization for [Double].
+ *
+ * @author Iaroslav Postovalov
+ */
+public class EjmlDoubleVector<out M : DMatrixD1>(public override val origin: M) : EjmlVector<Double, M>(origin) {
+    public override operator fun get(index: Int): Double = origin[index]
+}

kmath-ejml/src/test/kotlin/space/kscience/kmath/ejml/EjmlMatrixTest.kt

@@ -5,12 +5,15 @@
 
 package space.kscience.kmath.ejml
 
+import org.ejml.data.DMatrixRMaj
+import org.ejml.dense.row.CommonOps_DDRM
+import org.ejml.dense.row.RandomMatrices_DDRM
 import org.ejml.dense.row.factory.DecompositionFactory_DDRM
-import org.ejml.simple.SimpleMatrix
+import space.kscience.kmath.linear.DeterminantFeature
-import space.kscience.kmath.linear.*
+import space.kscience.kmath.linear.LupDecompositionFeature
+import space.kscience.kmath.linear.getFeature
 import space.kscience.kmath.misc.UnstableKMathAPI
 import space.kscience.kmath.nd.StructureND
-import space.kscience.kmath.nd.getFeature
 import kotlin.random.Random
 import kotlin.random.asJavaRandom
 import kotlin.test.*
@@ -22,65 +25,59 @@ fun <T : Any> assertMatrixEquals(expected: StructureND<T>, actual: StructureND<T
 internal class EjmlMatrixTest {
     private val random = Random(0)
 
-    private val randomMatrix: SimpleMatrix
+    private val randomMatrix: DMatrixRMaj
         get() {
             val s = random.nextInt(2, 100)
-            return SimpleMatrix.random_DDRM(s, s, 0.0, 10.0, random.asJavaRandom())
+            val d = DMatrixRMaj(s, s)
+            RandomMatrices_DDRM.fillUniform(d, random.asJavaRandom())
+            return d
         }
 
     @Test
     fun rowNum() {
         val m = randomMatrix
-        assertEquals(m.numRows(), EjmlMatrix(m).rowNum)
+        assertEquals(m.numRows, EjmlDoubleMatrix(m).rowNum)
     }
 
     @Test
     fun colNum() {
         val m = randomMatrix
-        assertEquals(m.numCols(), EjmlMatrix(m).rowNum)
+        assertEquals(m.numCols, EjmlDoubleMatrix(m).rowNum)
     }
 
     @Test
     fun shape() {
         val m = randomMatrix
-        val w = EjmlMatrix(m)
+        val w = EjmlDoubleMatrix(m)
-        assertEquals(listOf(m.numRows(), m.numCols()), w.shape.toList())
+        assertContentEquals(intArrayOf(m.numRows, m.numCols), w.shape)
     }
 
     @OptIn(UnstableKMathAPI::class)
     @Test
     fun features() {
         val m = randomMatrix
-        val w = EjmlMatrix(m)
+        val w = EjmlDoubleMatrix(m)
-        val det: DeterminantFeature<Double> = EjmlLinearSpace.getFeature(w) ?: fail()
+        val det: DeterminantFeature<Double> = EjmlLinearSpaceDDRM.getFeature(w) ?: fail()
-        assertEquals(m.determinant(), det.determinant)
+        assertEquals(CommonOps_DDRM.det(m), det.determinant)
-        val lup: LupDecompositionFeature<Double> = EjmlLinearSpace.getFeature(w) ?: fail()
+        val lup: LupDecompositionFeature<Double> = EjmlLinearSpaceDDRM.getFeature(w) ?: fail()
 
-        val ludecompositionF64 = DecompositionFactory_DDRM.lu(m.numRows(), m.numCols())
+        val ludecompositionF64 = DecompositionFactory_DDRM.lu(m.numRows, m.numCols)
-            .also { it.decompose(m.ddrm.copy()) }
+            .also { it.decompose(m.copy()) }
 
-        assertMatrixEquals(EjmlMatrix(SimpleMatrix(ludecompositionF64.getLower(null))), lup.l)
+        assertMatrixEquals(EjmlDoubleMatrix(ludecompositionF64.getLower(null)), lup.l)
-        assertMatrixEquals(EjmlMatrix(SimpleMatrix(ludecompositionF64.getUpper(null))), lup.u)
+        assertMatrixEquals(EjmlDoubleMatrix(ludecompositionF64.getUpper(null)), lup.u)
-        assertMatrixEquals(EjmlMatrix(SimpleMatrix(ludecompositionF64.getRowPivot(null))), lup.p)
+        assertMatrixEquals(EjmlDoubleMatrix(ludecompositionF64.getRowPivot(null)), lup.p)
-    }
-
-    private object SomeFeature : MatrixFeature {}
-
-    @OptIn(UnstableKMathAPI::class)
-    @Test
-    fun suggestFeature() {
-        assertNotNull((EjmlMatrix(randomMatrix) + SomeFeature).getFeature<SomeFeature>())
     }
 
     @Test
     fun get() {
         val m = randomMatrix
-        assertEquals(m[0, 0], EjmlMatrix(m)[0, 0])
+        assertEquals(m[0, 0], EjmlDoubleMatrix(m)[0, 0])
     }
 
     @Test
     fun origin() {
         val m = randomMatrix
-        assertSame(m, EjmlMatrix(m).origin)
+        assertSame(m, EjmlDoubleMatrix(m).origin)
     }
 }

kmath-ejml/src/test/kotlin/space/kscience/kmath/ejml/EjmlVectorTest.kt

@@ -5,7 +5,8 @@
 
 package space.kscience.kmath.ejml
 
-import org.ejml.simple.SimpleMatrix
+import org.ejml.data.DMatrixRMaj
+import org.ejml.dense.row.RandomMatrices_DDRM
 import kotlin.random.Random
 import kotlin.random.asJavaRandom
 import kotlin.test.Test
@@ -15,30 +16,34 @@ import kotlin.test.assertSame
 internal class EjmlVectorTest {
     private val random = Random(0)
 
-    private val randomMatrix: SimpleMatrix
+    private val randomMatrix: DMatrixRMaj
-        get() = SimpleMatrix.random_DDRM(random.nextInt(2, 100), 1, 0.0, 10.0, random.asJavaRandom())
+        get() {
+            val d = DMatrixRMaj(random.nextInt(2, 100), 1)
+            RandomMatrices_DDRM.fillUniform(d, random.asJavaRandom())
+            return d
+        }
 
     @Test
     fun size() {
         val m = randomMatrix
-        val w = EjmlVector(m)
+        val w = EjmlDoubleVector(m)
-        assertEquals(m.numRows(), w.size)
+        assertEquals(m.numRows, w.size)
     }
 
     @Test
     fun get() {
         val m = randomMatrix
-        val w = EjmlVector(m)
+        val w = EjmlDoubleVector(m)
         assertEquals(m[0, 0], w[0])
     }
 
     @Test
     fun iterator() {
         val m = randomMatrix
-        val w = EjmlVector(m)
+        val w = EjmlDoubleVector(m)
 
         assertEquals(
-            m.iterator(true, 0, 0, m.numRows() - 1, 0).asSequence().toList(),
+            m.iterator(true, 0, 0, m.numRows - 1, 0).asSequence().toList(),
             w.iterator().asSequence().toList()
         )
     }
@@ -46,7 +51,7 @@ internal class EjmlVectorTest {
     @Test
     fun origin() {
         val m = randomMatrix
-        val w = EjmlVector(m)
+        val w = EjmlDoubleVector(m)
         assertSame(m, w.origin)
     }
 }

kmath-for-real/README.md

@@ -15,7 +15,6 @@ The Maven coordinates of this project are `space.kscience:kmath-for-real:0.3.0-d
 ```gradle
 repositories {
     maven { url 'https://repo.kotlin.link' }
-    maven { url 'https://dl.bintray.com/hotkeytlt/maven' }
     maven { url "https://dl.bintray.com/kotlin/kotlin-eap" } // include for builds based on kotlin-eap
 }
 
@@ -28,7 +27,6 @@ dependencies {
 repositories {
     maven("https://repo.kotlin.link")
     maven("https://dl.bintray.com/kotlin/kotlin-eap") // include for builds based on kotlin-eap
-    maven("https://dl.bintray.com/hotkeytlt/maven") // required for a
 }
 
 dependencies {

kmath-functions/README.md

@@ -17,7 +17,6 @@ The Maven coordinates of this project are `space.kscience:kmath-functions:0.3.0-
 ```gradle
 repositories {
     maven { url 'https://repo.kotlin.link' }
-    maven { url 'https://dl.bintray.com/hotkeytlt/maven' }
     maven { url "https://dl.bintray.com/kotlin/kotlin-eap" } // include for builds based on kotlin-eap
 }
 
@@ -30,7 +29,6 @@ dependencies {
 repositories {
     maven("https://repo.kotlin.link")
     maven("https://dl.bintray.com/kotlin/kotlin-eap") // include for builds based on kotlin-eap
-    maven("https://dl.bintray.com/hotkeytlt/maven") // required for a
 }
 
 dependencies {

kmath-kotlingrad/build.gradle.kts

@@ -4,8 +4,8 @@ plugins {
 }
 
 dependencies {
-    implementation("com.github.breandan:kaliningraph:0.1.4")
+    api("com.github.breandan:kaliningraph:0.1.4")
-    implementation("com.github.breandan:kotlingrad:0.4.0")
+    api("com.github.breandan:kotlingrad:0.4.5")
     api(project(":kmath-ast"))
 }
 

kmath-nd4j/README.md

@@ -15,8 +15,7 @@ The Maven coordinates of this project are `space.kscience:kmath-nd4j:0.3.0-dev-7
 ```gradle
 repositories {
     maven { url 'https://repo.kotlin.link' }
-    maven { url 'https://dl.bintray.com/hotkeytlt/maven' }
+    mavenCentral()
-    maven { url "https://dl.bintray.com/kotlin/kotlin-eap" } // include for builds based on kotlin-eap
 }
 
 dependencies {
@@ -27,8 +26,7 @@ dependencies {
 ```kotlin
 repositories {
     maven("https://repo.kotlin.link")
-    maven("https://dl.bintray.com/kotlin/kotlin-eap") // include for builds based on kotlin-eap
+    mavenCentral()
-    maven("https://dl.bintray.com/hotkeytlt/maven") // required for a
 }
 
 dependencies {

kmath-viktor/build.gradle.kts

@@ -7,7 +7,7 @@ description = "Binding for https://github.com/JetBrains-Research/viktor"
 
 dependencies {
     api(project(":kmath-core"))
-    api("org.jetbrains.bio:viktor:1.0.1")
+    api("org.jetbrains.bio:viktor:1.1.0")
 }
 
 readme {