Finish naming change

CHANGELOG.md

@@ -3,14 +3,18 @@
 ## Unreleased
 
 ### Added
+- Integer divistion algebras
 
 ### Changed
+- Default naming for algebra and buffers now uses IntXX/FloatXX notation instead of Java types.
+- Remove unnecessary inlines in basic algebras.
 
 ### Deprecated
 
 ### Removed
 
 ### Fixed
+- Median statistics
 
 ### Security
 

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

@@ -14,7 +14,7 @@ import space.kscience.kmath.complex.ComplexField
 import space.kscience.kmath.complex.complex
 import space.kscience.kmath.operations.invoke
 import space.kscience.kmath.structures.Buffer
-import space.kscience.kmath.structures.DoubleBuffer
+import space.kscience.kmath.structures.Float64Buffer
 import space.kscience.kmath.structures.getDouble
 import space.kscience.kmath.structures.permute
 
@@ -33,7 +33,7 @@ internal class BufferBenchmark {
 
     @Benchmark
     fun doubleBufferReadWrite(blackhole: Blackhole) {
-        val buffer = DoubleBuffer(size) { it.toDouble() }
+        val buffer = Float64Buffer(size) { it.toDouble() }
         var res = 0.0
         (0 until size).forEach {
             res += buffer[it]
@@ -43,7 +43,7 @@ internal class BufferBenchmark {
 
     @Benchmark
     fun bufferViewReadWrite(blackhole: Blackhole) {
-        val buffer = DoubleBuffer(size) { it.toDouble() }.permute(reversedIndices)
+        val buffer = Float64Buffer(size) { it.toDouble() }.permute(reversedIndices)
         var res = 0.0
         (0 until size).forEach {
             res += buffer[it]
@@ -53,7 +53,7 @@ internal class BufferBenchmark {
 
     @Benchmark
     fun bufferViewReadWriteSpecialized(blackhole: Blackhole) {
-        val buffer = DoubleBuffer(size) { it.toDouble() }.permute(reversedIndices)
+        val buffer = Float64Buffer(size) { it.toDouble() }.permute(reversedIndices)
         var res = 0.0
         (0 until size).forEach {
             res += buffer.getDouble(it)

build.gradle.kts

@@ -15,7 +15,7 @@ allprojects {
     }
 
     group = "space.kscience"
-    version = "0.3.2-dev-1"
+    version = "0.4.0-dev-2"
 }
 
 subprojects {

buildSrc/src/main/kotlin/space/kscience/kmath/ejml/codegen/ejmlCodegen.kt

@@ -387,9 +387,15 @@ import space.kscience.kmath.linear.*
 import space.kscience.kmath.linear.Matrix
 import space.kscience.kmath.UnstableKMathAPI
 import space.kscience.kmath.nd.StructureFeature
+import space.kscience.kmath.structures.Float64
+import space.kscience.kmath.structures.Float32
+import space.kscience.kmath.operations.Float64Field
+import space.kscience.kmath.operations.Float32Field
 import space.kscience.kmath.operations.DoubleField
 import space.kscience.kmath.operations.FloatField
 import space.kscience.kmath.operations.invoke
+import space.kscience.kmath.structures.Float64Buffer
+import space.kscience.kmath.structures.Float32Buffer
 import space.kscience.kmath.structures.DoubleBuffer
 import space.kscience.kmath.structures.FloatBuffer
 import kotlin.reflect.KClass
@@ -399,12 +405,12 @@ import kotlin.reflect.cast""")
         it.appendEjmlVector("Float", "FMatrix")
         it.appendEjmlMatrix("Double", "DMatrix")
         it.appendEjmlMatrix("Float", "FMatrix")
-        it.appendEjmlLinearSpace("Double", "DoubleField", "DMatrix", "DMatrixRMaj", "DMatrixRMaj", "DDRM", "DDRM", true)
+        it.appendEjmlLinearSpace("Double", "Float64Field", "DMatrix", "DMatrixRMaj", "DMatrixRMaj", "DDRM", "DDRM", true)
-        it.appendEjmlLinearSpace("Float", "FloatField", "FMatrix", "FMatrixRMaj", "FMatrixRMaj", "FDRM", "FDRM", true)
+        it.appendEjmlLinearSpace("Float", "Float32Field", "FMatrix", "FMatrixRMaj", "FMatrixRMaj", "FDRM", "FDRM", true)
 
         it.appendEjmlLinearSpace(
             type = "Double",
-            kmathAlgebra = "DoubleField",
+            kmathAlgebra = "Float64Field",
             ejmlMatrixParentTypeMatrix = "DMatrix",
             ejmlMatrixType = "DMatrixSparseCSC",
             ejmlMatrixDenseType = "DMatrixRMaj",
@@ -415,7 +421,7 @@ import kotlin.reflect.cast""")
 
         it.appendEjmlLinearSpace(
             type = "Float",
-            kmathAlgebra = "FloatField",
+            kmathAlgebra = "Float32Field",
             ejmlMatrixParentTypeMatrix = "FMatrix",
             ejmlMatrixType = "FMatrixSparseCSC",
             ejmlMatrixDenseType = "FMatrixRMaj",

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

@@ -8,7 +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.DoubleBuffer
+import space.kscience.kmath.structures.Float64Buffer
 import space.kscience.plotly.Plotly
 import space.kscience.plotly.UnstablePlotlyAPI
 import space.kscience.plotly.makeFile
@@ -25,7 +25,7 @@ fun main() {
     }
 
     val polynomial: PiecewisePolynomial<Double> = SplineInterpolator(
-        Float64Field, ::DoubleBuffer
+        Float64Field, ::Float64Buffer
     ).interpolatePolynomials(data)
 
     val function = polynomial.asFunction(Float64Field, 0.0)

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

@@ -6,7 +6,7 @@
 package space.kscience.kmath.linear
 
 import space.kscience.kmath.real.*
-import space.kscience.kmath.structures.DoubleBuffer
+import space.kscience.kmath.structures.Float64Buffer
 
 fun main() {
     val x0 = DoubleVector(0.0, 0.0, 0.0)
@@ -19,9 +19,9 @@ fun main() {
 
     fun ((Point<Double>) -> Double).grad(x: Point<Double>): Point<Double> {
         require(x.size == x0.size)
-        return DoubleBuffer(x.size) { i ->
+        return Float64Buffer(x.size) { i ->
             val h = sigma[i] / 5
-            val dVector = DoubleBuffer(x.size) { if (it == i) h else 0.0 }
+            val dVector = Float64Buffer(x.size) { if (it == i) h else 0.0 }
             val f1 = this(x + dVector / 2)
             val f0 = this(x - dVector / 2)
             (f1 - f0) / h

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

@@ -7,7 +7,7 @@ package space.kscience.kmath.operations
 
 import space.kscience.kmath.commons.linear.CMLinearSpace
 import space.kscience.kmath.linear.matrix
-import space.kscience.kmath.nd.DoubleBufferND
+import space.kscience.kmath.nd.Float64BufferND
 import space.kscience.kmath.nd.ShapeND
 import space.kscience.kmath.nd.Structure2D
 import space.kscience.kmath.nd.ndAlgebra
@@ -21,7 +21,7 @@ fun main() {
 
     val cmMatrix: Structure2D<Double> = CMLinearSpace.matrix(2, 2)(0.0, 1.0, 0.0, 3.0)
 
-    val res: DoubleBufferND = Float64Field.ndAlgebra {
+    val res: Float64BufferND = Float64Field.ndAlgebra {
         exp(viktorStructure) + 2.0 * cmMatrix
     }
 

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

@@ -32,15 +32,15 @@ class StreamDoubleFieldND(override val shape: ShapeND) : FieldND<Double, Float64
     }
 
     @OptIn(PerformancePitfall::class)
-    private val StructureND<Double>.buffer: DoubleBuffer
+    private val StructureND<Double>.buffer: Float64Buffer
         get() = when {
             !shape.contentEquals(this@StreamDoubleFieldND.shape) -> throw ShapeMismatchException(
                 this@StreamDoubleFieldND.shape,
                 shape
             )
 
-            this is BufferND && indices == this@StreamDoubleFieldND.strides -> this.buffer as DoubleBuffer
+            this is BufferND && indices == this@StreamDoubleFieldND.strides -> this.buffer as Float64Buffer
-            else -> DoubleBuffer(strides.linearSize) { offset -> get(strides.index(offset)) }
+            else -> Float64Buffer(strides.linearSize) { offset -> get(strides.index(offset)) }
         }
 
     override fun structureND(shape: ShapeND, initializer: Float64Field.(IntArray) -> Double): BufferND<Double> {

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

@@ -16,7 +16,7 @@ import kotlin.system.measureTimeMillis
 fun main() {
     val n = 6000
     val array = DoubleArray(n * n) { 1.0 }
-    val buffer = DoubleBuffer(array)
+    val buffer = Float64Buffer(array)
     val strides = ColumnStrides(ShapeND(n, n))
     val structure = BufferND(strides, buffer)
 

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

@@ -32,10 +32,10 @@ fun main() {
 
     println("Array mapping finished in $time2 millis")
 
-    val buffer = DoubleBuffer(DoubleArray(n * n) { 1.0 })
+    val buffer = Float64Buffer(DoubleArray(n * n) { 1.0 })
 
     val time3 = measureTimeMillis {
-        val target = DoubleBuffer(DoubleArray(n * n))
+        val target = Float64Buffer(DoubleArray(n * n))
         val res = array.forEachIndexed { index, value ->
             target[index] = value + 1
         }

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

@@ -5,9 +5,9 @@
 
 package space.kscience.kmath.ast
 
-import space.kscience.kmath.operations.ByteRing
 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 kotlin.test.Test
 import kotlin.test.assertEquals
@@ -47,6 +47,6 @@ internal class TestFolding {
     @Test
     fun foldNumeric() = assertEquals(
         42.toByte(),
-        ("42".parseMath().evaluateConstants(ByteRing) as? TypedMst.Constant<Byte> ?: fail()).value,
+        ("42".parseMath().evaluateConstants(Int8Ring) as? TypedMst.Constant<Byte> ?: fail()).value,
     )
 }

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

@@ -11,7 +11,7 @@ import space.kscience.kmath.linear.*
 import space.kscience.kmath.nd.StructureFeature
 import space.kscience.kmath.operations.Float64Field
 import space.kscience.kmath.structures.Buffer
-import space.kscience.kmath.structures.DoubleBuffer
+import space.kscience.kmath.structures.Float64Buffer
 import kotlin.reflect.KClass
 import kotlin.reflect.cast
 
@@ -136,7 +136,7 @@ public object CMLinearSpace : LinearSpace<Double, Float64Field> {
                 override val u: Matrix<Double> by lazy { CMMatrix(sv.u) }
                 override val s: Matrix<Double> by lazy { CMMatrix(sv.s) }
                 override val v: Matrix<Double> by lazy { CMMatrix(sv.v) }
-                override val singularValues: Point<Double> by lazy { DoubleBuffer(sv.singularValues) }
+                override val singularValues: Point<Double> by lazy { Float64Buffer(sv.singularValues) }
             }
             else -> null
         }?.let(type::cast)

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

@@ -47,7 +47,7 @@ public object Transformations {
     public fun sine(
         normalization: DstNormalization = DstNormalization.STANDARD_DST_I,
         direction: TransformType = TransformType.FORWARD,
-    ): BufferTransform<Double, Double> = DoubleBufferTransform {
+    ): BufferTransform<Double, Double> = Float64BufferTransform {
         FastSineTransformer(normalization).transform(it.array, direction).asBuffer()
     }
 
@@ -60,7 +60,7 @@ public object Transformations {
 
     public fun hadamard(
         direction: TransformType = TransformType.FORWARD,
-    ): BufferTransform<Double, Double> = DoubleBufferTransform {
+    ): BufferTransform<Double, Double> = Float64BufferTransform {
         FastHadamardTransformer().transform(it.array, direction).asBuffer()
     }
 }

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

@@ -13,12 +13,12 @@ import space.kscience.kmath.expressions.Symbol.Companion.x
 import space.kscience.kmath.expressions.Symbol.Companion.y
 import space.kscience.kmath.expressions.autodiff
 import space.kscience.kmath.expressions.symbol
-import space.kscience.kmath.operations.DoubleBufferOps.Companion.map
+import space.kscience.kmath.operations.Float64BufferOps.Companion.map
 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.DoubleBuffer
+import space.kscience.kmath.structures.Float64Buffer
 import space.kscience.kmath.structures.asBuffer
 import kotlin.test.Test
 
@@ -61,7 +61,7 @@ internal class OptimizeTest {
             it.pow(2) + it + 1 + chain.next()
         }
 
-        val yErr = DoubleBuffer(x.size) { sigma }
+        val yErr = Float64Buffer(x.size) { sigma }
 
         val chi2 = Double.autodiff.chiSquaredExpression(
             x, y, yErr

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

@@ -23,7 +23,7 @@ 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), DoubleDomain {
+) : Domain1D<Double>(doubleRange), Float64Domain {
     override fun getLowerBound(num: Int): Double {
         require(num == 0)
         return range.start

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

@@ -12,7 +12,7 @@ import space.kscience.kmath.UnstableKMathAPI
  * @author Alexander Nozik
  */
 @UnstableKMathAPI
-public interface DoubleDomain : Domain<Double> {
+public interface Float64Domain : Domain<Double> {
     /**
      * Global lower edge
      * @param num axis number

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

@@ -7,7 +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.DoubleBuffer
+import space.kscience.kmath.structures.Float64Buffer
 import space.kscience.kmath.structures.indices
 
 /**
@@ -15,7 +15,7 @@ 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>) : DoubleDomain {
+public class HyperSquareDomain(public val lower: Buffer<Double>, public val upper: Buffer<Double>) : Float64Domain {
     init {
         require(lower.size == upper.size) {
             "Domain borders size mismatch. Lower borders size is ${lower.size}, but upper borders size is ${upper.size}."
@@ -27,7 +27,7 @@ public class HyperSquareDomain(public val lower: Buffer<Double>, public val uppe
 
     override val dimension: Int get() = lower.size
 
-    public val center: DoubleBuffer get() = DoubleBuffer(dimension) { (lower[it] + upper[it]) / 2.0 }
+    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 ->
         point[i] in lower[i]..upper[i]

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

@@ -8,7 +8,7 @@ import space.kscience.kmath.UnstableKMathAPI
 import space.kscience.kmath.linear.Point
 
 @UnstableKMathAPI
-public class UnconstrainedDomain(override val dimension: Int) : DoubleDomain {
+public class UnconstrainedDomain(override val dimension: Int) : Float64Domain {
     override operator fun contains(point: Point<Double>): Boolean = true
 
     override fun getLowerBound(num: Int): Double = Double.NEGATIVE_INFINITY

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

@@ -9,7 +9,7 @@ import space.kscience.kmath.UnstableKMathAPI
 import space.kscience.kmath.linear.Point
 import space.kscience.kmath.nd.Structure2D
 import space.kscience.kmath.structures.BufferFactory
-import space.kscience.kmath.structures.DoubleBuffer
+import space.kscience.kmath.structures.Float64Buffer
 import kotlin.contracts.InvocationKind
 import kotlin.contracts.contract
 import kotlin.jvm.JvmInline
@@ -62,8 +62,8 @@ public interface SymbolIndexer {
     public fun <T> Map<Symbol, T>.toPoint(bufferFactory: BufferFactory<T>): Point<T> =
         bufferFactory(symbols.size) { getValue(symbols[it]) }
 
-    public fun Map<Symbol, Double>.toPoint(): DoubleBuffer =
+    public fun Map<Symbol, Double>.toPoint(): Float64Buffer =
-        DoubleBuffer(symbols.size) { getValue(symbols[it]) }
+        Float64Buffer(symbols.size) { getValue(symbols[it]) }
 
 
     public fun Map<Symbol, Double>.toDoubleArray(): DoubleArray = DoubleArray(symbols.size) { getValue(symbols[it]) }

kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/Float64LinearSpace.kt

@@ -7,13 +7,13 @@ package space.kscience.kmath.linear
 
 import space.kscience.kmath.PerformancePitfall
 import space.kscience.kmath.nd.*
-import space.kscience.kmath.operations.DoubleBufferOps
+import space.kscience.kmath.operations.Float64BufferOps
 import space.kscience.kmath.operations.Float64Field
 import space.kscience.kmath.operations.invoke
 import space.kscience.kmath.structures.Buffer
-import space.kscience.kmath.structures.DoubleBuffer
+import space.kscience.kmath.structures.Float64Buffer
 
-public object DoubleLinearSpace : LinearSpace<Double, Float64Field> {
+public object Float64LinearSpace : LinearSpace<Double, Float64Field> {
 
     override val elementAlgebra: Float64Field get() = Float64Field
 
@@ -21,29 +21,29 @@ public object DoubleLinearSpace : LinearSpace<Double, Float64Field> {
         rows: Int,
         columns: Int,
         initializer: Float64Field.(i: Int, j: Int) -> Double
-    ): Matrix<Double> = DoubleFieldOpsND.structureND(ShapeND(rows, columns)) { (i, j) ->
+    ): Matrix<Double> = Floa64FieldOpsND.structureND(ShapeND(rows, columns)) { (i, j) ->
         Float64Field.initializer(i, j)
     }.as2D()
 
-    override fun buildVector(size: Int, initializer: Float64Field.(Int) -> Double): DoubleBuffer =
+    override fun buildVector(size: Int, initializer: Float64Field.(Int) -> Double): Float64Buffer =
-        DoubleBuffer(size) { Float64Field.initializer(it) }
+        Float64Buffer(size) { Float64Field.initializer(it) }
 
-    override fun Matrix<Double>.unaryMinus(): Matrix<Double> = DoubleFieldOpsND {
+    override fun Matrix<Double>.unaryMinus(): Matrix<Double> = Floa64FieldOpsND {
         asND().map { -it }.as2D()
     }
 
-    override fun Matrix<Double>.plus(other: Matrix<Double>): Matrix<Double> = DoubleFieldOpsND {
+    override fun Matrix<Double>.plus(other: Matrix<Double>): Matrix<Double> = Floa64FieldOpsND {
         require(shape.contentEquals(other.shape)) { "Shape mismatch on Matrix::plus. Expected $shape but found ${other.shape}" }
         asND().plus(other.asND()).as2D()
     }
 
-    override fun Matrix<Double>.minus(other: Matrix<Double>): Matrix<Double> = DoubleFieldOpsND {
+    override fun Matrix<Double>.minus(other: Matrix<Double>): Matrix<Double> = Floa64FieldOpsND {
         require(shape.contentEquals(other.shape)) { "Shape mismatch on Matrix::minus. Expected $shape but found ${other.shape}" }
         asND().minus(other.asND()).as2D()
     }
 
     // Create a continuous in-memory representation of this vector for better memory layout handling
-    private fun Buffer<Double>.linearize() = if (this is DoubleBuffer) {
+    private fun Buffer<Double>.linearize() = if (this is Float64Buffer) {
         this.array
     } else {
         DoubleArray(size) { get(it) }
@@ -66,10 +66,10 @@ public object DoubleLinearSpace : LinearSpace<Double, Float64Field> {
     }
 
     @OptIn(PerformancePitfall::class)
-    override fun Matrix<Double>.dot(vector: Point<Double>): DoubleBuffer {
+    override fun Matrix<Double>.dot(vector: Point<Double>): Float64Buffer {
         require(colNum == vector.size) { "Matrix dot vector operation dimension mismatch: ($rowNum, $colNum) x (${vector.size})" }
         val rows = this@dot.rows.map { it.linearize() }
-        return DoubleBuffer(rowNum) { i ->
+        return Float64Buffer(rowNum) { i ->
             val r = rows[i]
             var res = 0.0
             for (j in r.indices) {
@@ -80,29 +80,29 @@ public object DoubleLinearSpace : LinearSpace<Double, Float64Field> {
 
     }
 
-    override fun Matrix<Double>.times(value: Double): Matrix<Double> = DoubleFieldOpsND {
+    override fun Matrix<Double>.times(value: Double): Matrix<Double> = Floa64FieldOpsND {
         asND().map { it * value }.as2D()
     }
 
-    public override fun Point<Double>.plus(other: Point<Double>): DoubleBuffer = DoubleBufferOps.run {
+    public override fun Point<Double>.plus(other: Point<Double>): Float64Buffer = Float64BufferOps.run {
         this@plus + other
     }
 
-    public override fun Point<Double>.minus(other: Point<Double>): DoubleBuffer = DoubleBufferOps.run {
+    public override fun Point<Double>.minus(other: Point<Double>): Float64Buffer = Float64BufferOps.run {
         this@minus - other
     }
 
-    public override fun Point<Double>.times(value: Double): DoubleBuffer = DoubleBufferOps.run {
+    public override fun Point<Double>.times(value: Double): Float64Buffer = Float64BufferOps.run {
         scale(this@times, value)
     }
 
-    public operator fun Point<Double>.div(value: Double): DoubleBuffer = DoubleBufferOps.run {
+    public operator fun Point<Double>.div(value: Double): Float64Buffer = Float64BufferOps.run {
         scale(this@div, 1.0 / value)
     }
 
-    public override fun Double.times(v: Point<Double>): DoubleBuffer = v * this
+    public override fun Double.times(v: Point<Double>): Float64Buffer = v * this
 
 
 }
 
-public val Float64Field.linearSpace: DoubleLinearSpace get() = DoubleLinearSpace
+public val Float64Field.linearSpace: Float64LinearSpace get() = Float64LinearSpace

kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/LupDecomposition.kt

@@ -8,7 +8,7 @@ package space.kscience.kmath.linear
 import space.kscience.kmath.UnstableKMathAPI
 import space.kscience.kmath.operations.*
 import space.kscience.kmath.structures.BufferAccessor2D
-import space.kscience.kmath.structures.DoubleBuffer
+import space.kscience.kmath.structures.Float64Buffer
 import space.kscience.kmath.structures.MutableBuffer
 import space.kscience.kmath.structures.MutableBufferFactory
 
@@ -159,7 +159,7 @@ public fun LinearSpace<Double, Float64Field>.lup(
     matrix: Matrix<Double>,
     singularityThreshold: Double = 1e-11,
 ): LupDecomposition<Double> =
-    lup(::DoubleBuffer, matrix) { it < singularityThreshold }
+    lup(::Float64Buffer, matrix) { it < singularityThreshold }
 
 internal fun <T : Any> LupDecomposition<T>.solve(
     factory: MutableBufferFactory<T>,
@@ -227,4 +227,4 @@ public fun <T : Comparable<T>, F : Field<T>> LinearSpace<T, F>.lupSolver(
 }
 
 public fun LinearSpace<Double, Float64Field>.lupSolver(singularityThreshold: Double = 1e-11): LinearSolver<Double> =
-    lupSolver(::DoubleBuffer) { it < singularityThreshold }
+    lupSolver(::Float64Buffer) { it < singularityThreshold }

kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/Float64FieldND.kt

@@ -8,7 +8,7 @@ package space.kscience.kmath.nd
 import space.kscience.kmath.PerformancePitfall
 import space.kscience.kmath.UnstableKMathAPI
 import space.kscience.kmath.operations.*
-import space.kscience.kmath.structures.DoubleBuffer
+import space.kscience.kmath.structures.Float64Buffer
 import kotlin.contracts.InvocationKind
 import kotlin.contracts.contract
 import kotlin.math.pow
@@ -17,9 +17,9 @@ import kotlin.math.pow as kpow
 /**
  * A simple mutable [StructureND] of doubles
  */
-public class DoubleBufferND(
+public class Float64BufferND(
     indexes: ShapeIndexer,
-    override val buffer: DoubleBuffer,
+    override val buffer: Float64Buffer,
 ) : MutableBufferND<Double>(indexes, buffer), MutableStructureNDOfDouble{
     override fun getDouble(index: IntArray): Double = buffer[indices.offset(index)]
 
@@ -29,37 +29,37 @@ public class DoubleBufferND(
 }
 
 
-public sealed class DoubleFieldOpsND : BufferedFieldOpsND<Double, Float64Field>(Float64Field.bufferAlgebra),
+public sealed class Floa64FieldOpsND : BufferedFieldOpsND<Double, Float64Field>(Float64Field.bufferAlgebra),
     ScaleOperations<StructureND<Double>>, ExtendedFieldOps<StructureND<Double>> {
 
     @OptIn(PerformancePitfall::class)
-    override fun StructureND<Double>.toBufferND(): DoubleBufferND = when (this) {
+    override fun StructureND<Double>.toBufferND(): Float64BufferND = when (this) {
-        is DoubleBufferND -> this
+        is Float64BufferND -> this
         else -> {
             val indexer = indexerBuilder(shape)
-            DoubleBufferND(indexer, DoubleBuffer(indexer.linearSize) { offset -> get(indexer.index(offset)) })
+            Float64BufferND(indexer, Float64Buffer(indexer.linearSize) { offset -> get(indexer.index(offset)) })
         }
     }
 
     protected inline fun mapInline(
-        arg: DoubleBufferND,
+        arg: Float64BufferND,
         transform: (Double) -> Double,
-    ): DoubleBufferND {
+    ): Float64BufferND {
         val indexes = arg.indices
         val array = arg.buffer.array
-        return DoubleBufferND(indexes, DoubleBuffer(indexes.linearSize) { transform(array[it]) })
+        return Float64BufferND(indexes, Float64Buffer(indexes.linearSize) { transform(array[it]) })
     }
 
     private inline fun zipInline(
-        l: DoubleBufferND,
+        l: Float64BufferND,
-        r: DoubleBufferND,
+        r: Float64BufferND,
         block: (l: Double, r: Double) -> Double,
-    ): DoubleBufferND {
+    ): Float64BufferND {
         require(l.indices == r.indices) { "Zip requires the same shapes, but found ${l.shape} on the left and ${r.shape} on the right" }
         val indexes = l.indices
         val lArray = l.buffer.array
         val rArray = r.buffer.array
-        return DoubleBufferND(indexes, DoubleBuffer(indexes.linearSize) { block(lArray[it], rArray[it]) })
+        return Float64BufferND(indexes, Float64Buffer(indexes.linearSize) { block(lArray[it], rArray[it]) })
     }
 
     @OptIn(PerformancePitfall::class)
@@ -74,56 +74,56 @@ public sealed class DoubleFieldOpsND : BufferedFieldOpsND<Double, Float64Field>(
         transform: Float64Field.(Double, Double) -> Double,
     ): BufferND<Double> = zipInline(left.toBufferND(), right.toBufferND()) { l, r -> Float64Field.transform(l, r) }
 
-    override fun structureND(shape: ShapeND, initializer: Float64Field.(IntArray) -> Double): DoubleBufferND {
+    override fun structureND(shape: ShapeND, initializer: Float64Field.(IntArray) -> Double): Float64BufferND {
         val indexer = indexerBuilder(shape)
-        return DoubleBufferND(
+        return Float64BufferND(
             indexer,
-            DoubleBuffer(indexer.linearSize) { offset ->
+            Float64Buffer(indexer.linearSize) { offset ->
                 elementAlgebra.initializer(indexer.index(offset))
             }
         )
     }
 
-    override fun add(left: StructureND<Double>, right: StructureND<Double>): DoubleBufferND =
+    override fun add(left: StructureND<Double>, right: StructureND<Double>): Float64BufferND =
         zipInline(left.toBufferND(), right.toBufferND()) { l, r -> l + r }
 
-    override fun multiply(left: StructureND<Double>, right: StructureND<Double>): DoubleBufferND =
+    override fun multiply(left: StructureND<Double>, right: StructureND<Double>): Float64BufferND =
         zipInline(left.toBufferND(), right.toBufferND()) { l, r -> l * r }
 
-    override fun StructureND<Double>.unaryMinus(): DoubleBufferND = mapInline(toBufferND()) { -it }
+    override fun StructureND<Double>.unaryMinus(): Float64BufferND = mapInline(toBufferND()) { -it }
 
-    override fun StructureND<Double>.div(arg: StructureND<Double>): DoubleBufferND =
+    override fun StructureND<Double>.div(arg: StructureND<Double>): Float64BufferND =
         zipInline(toBufferND(), arg.toBufferND()) { l, r -> l / r }
 
-    override fun divide(left: StructureND<Double>, right: StructureND<Double>): DoubleBufferND =
+    override fun divide(left: StructureND<Double>, right: StructureND<Double>): Float64BufferND =
         zipInline(left.toBufferND(), right.toBufferND()) { l: Double, r: Double -> l / r }
 
-    override fun StructureND<Double>.div(arg: Double): DoubleBufferND =
+    override fun StructureND<Double>.div(arg: Double): Float64BufferND =
         mapInline(toBufferND()) { it / arg }
 
-    override fun Double.div(arg: StructureND<Double>): DoubleBufferND =
+    override fun Double.div(arg: StructureND<Double>): Float64BufferND =
         mapInline(arg.toBufferND()) { this / it }
 
-    override fun StructureND<Double>.unaryPlus(): DoubleBufferND = toBufferND()
+    override fun StructureND<Double>.unaryPlus(): Float64BufferND = toBufferND()
 
-    override fun StructureND<Double>.plus(arg: StructureND<Double>): DoubleBufferND =
+    override fun StructureND<Double>.plus(arg: StructureND<Double>): Float64BufferND =
         zipInline(toBufferND(), arg.toBufferND()) { l: Double, r: Double -> l + r }
 
-    override fun StructureND<Double>.minus(arg: StructureND<Double>): DoubleBufferND =
+    override fun StructureND<Double>.minus(arg: StructureND<Double>): Float64BufferND =
         zipInline(toBufferND(), arg.toBufferND()) { l: Double, r: Double -> l - r }
 
-    override fun StructureND<Double>.times(arg: StructureND<Double>): DoubleBufferND =
+    override fun StructureND<Double>.times(arg: StructureND<Double>): Float64BufferND =
         zipInline(toBufferND(), arg.toBufferND()) { l: Double, r: Double -> l * r }
 
-    override fun StructureND<Double>.times(k: Number): DoubleBufferND =
+    override fun StructureND<Double>.times(k: Number): Float64BufferND =
         mapInline(toBufferND()) { it * k.toDouble() }
 
-    override fun StructureND<Double>.div(k: Number): DoubleBufferND =
+    override fun StructureND<Double>.div(k: Number): Float64BufferND =
         mapInline(toBufferND()) { it / k.toDouble() }
 
-    override fun Number.times(arg: StructureND<Double>): DoubleBufferND = arg * this
+    override fun Number.times(arg: StructureND<Double>): Float64BufferND = arg * this
 
-    override fun StructureND<Double>.plus(arg: Double): DoubleBufferND = mapInline(toBufferND()) { it + arg }
+    override fun StructureND<Double>.plus(arg: Double): Float64BufferND = mapInline(toBufferND()) { it + arg }
 
     override fun StructureND<Double>.minus(arg: Double): StructureND<Double> = mapInline(toBufferND()) { it - arg }
 
@@ -131,49 +131,49 @@ public sealed class DoubleFieldOpsND : BufferedFieldOpsND<Double, Float64Field>(
 
     override fun Double.minus(arg: StructureND<Double>): StructureND<Double> = mapInline(arg.toBufferND()) { this - it }
 
-    override fun scale(a: StructureND<Double>, value: Double): DoubleBufferND =
+    override fun scale(a: StructureND<Double>, value: Double): Float64BufferND =
         mapInline(a.toBufferND()) { it * value }
 
-    override fun exp(arg: StructureND<Double>): DoubleBufferND =
+    override fun exp(arg: StructureND<Double>): Float64BufferND =
         mapInline(arg.toBufferND()) { kotlin.math.exp(it) }
 
-    override fun ln(arg: StructureND<Double>): DoubleBufferND =
+    override fun ln(arg: StructureND<Double>): Float64BufferND =
         mapInline(arg.toBufferND()) { kotlin.math.ln(it) }
 
-    override fun sin(arg: StructureND<Double>): DoubleBufferND =
+    override fun sin(arg: StructureND<Double>): Float64BufferND =
         mapInline(arg.toBufferND()) { kotlin.math.sin(it) }
 
-    override fun cos(arg: StructureND<Double>): DoubleBufferND =
+    override fun cos(arg: StructureND<Double>): Float64BufferND =
         mapInline(arg.toBufferND()) { kotlin.math.cos(it) }
 
-    override fun tan(arg: StructureND<Double>): DoubleBufferND =
+    override fun tan(arg: StructureND<Double>): Float64BufferND =
         mapInline(arg.toBufferND()) { kotlin.math.tan(it) }
 
-    override fun asin(arg: StructureND<Double>): DoubleBufferND =
+    override fun asin(arg: StructureND<Double>): Float64BufferND =
         mapInline(arg.toBufferND()) { kotlin.math.asin(it) }
 
-    override fun acos(arg: StructureND<Double>): DoubleBufferND =
+    override fun acos(arg: StructureND<Double>): Float64BufferND =
         mapInline(arg.toBufferND()) { kotlin.math.acos(it) }
 
-    override fun atan(arg: StructureND<Double>): DoubleBufferND =
+    override fun atan(arg: StructureND<Double>): Float64BufferND =
         mapInline(arg.toBufferND()) { kotlin.math.atan(it) }
 
-    override fun sinh(arg: StructureND<Double>): DoubleBufferND =
+    override fun sinh(arg: StructureND<Double>): Float64BufferND =
         mapInline(arg.toBufferND()) { kotlin.math.sinh(it) }
 
-    override fun cosh(arg: StructureND<Double>): DoubleBufferND =
+    override fun cosh(arg: StructureND<Double>): Float64BufferND =
         mapInline(arg.toBufferND()) { kotlin.math.cosh(it) }
 
-    override fun tanh(arg: StructureND<Double>): DoubleBufferND =
+    override fun tanh(arg: StructureND<Double>): Float64BufferND =
         mapInline(arg.toBufferND()) { kotlin.math.tanh(it) }
 
-    override fun asinh(arg: StructureND<Double>): DoubleBufferND =
+    override fun asinh(arg: StructureND<Double>): Float64BufferND =
         mapInline(arg.toBufferND()) { kotlin.math.asinh(it) }
 
-    override fun acosh(arg: StructureND<Double>): DoubleBufferND =
+    override fun acosh(arg: StructureND<Double>): Float64BufferND =
         mapInline(arg.toBufferND()) { kotlin.math.acosh(it) }
 
-    override fun atanh(arg: StructureND<Double>): DoubleBufferND =
+    override fun atanh(arg: StructureND<Double>): Float64BufferND =
         mapInline(arg.toBufferND()) { kotlin.math.atanh(it) }
 
     override fun power(
@@ -185,23 +185,23 @@ public sealed class DoubleFieldOpsND : BufferedFieldOpsND<Double, Float64Field>(
         mapInline(arg.toBufferND()) { it.pow(pow.toDouble()) }
     }
 
-    public companion object : DoubleFieldOpsND()
+    public companion object : Floa64FieldOpsND()
 }
 
 @OptIn(UnstableKMathAPI::class)
-public class DoubleFieldND(override val shape: ShapeND) :
+public class Float64FieldND(override val shape: ShapeND) :
-    DoubleFieldOpsND(), FieldND<Double, Float64Field>, NumbersAddOps<StructureND<Double>>,
+    Floa64FieldOpsND(), FieldND<Double, Float64Field>, NumbersAddOps<StructureND<Double>>,
     ExtendedField<StructureND<Double>> {
 
-    override fun power(arg: StructureND<Double>, pow: UInt): DoubleBufferND = mapInline(arg.toBufferND()) {
+    override fun power(arg: StructureND<Double>, pow: UInt): Float64BufferND = mapInline(arg.toBufferND()) {
         it.kpow(pow.toInt())
     }
 
-    override fun power(arg: StructureND<Double>, pow: Int): DoubleBufferND = mapInline(arg.toBufferND()) {
+    override fun power(arg: StructureND<Double>, pow: Int): Float64BufferND = mapInline(arg.toBufferND()) {
         it.kpow(pow)
     }
 
-    override fun power(arg: StructureND<Double>, pow: Number): DoubleBufferND = if (pow.isInteger()) {
+    override fun power(arg: StructureND<Double>, pow: Number): Float64BufferND = if (pow.isInteger()) {
         power(arg, pow.toInt())
     } else {
         val dpow = pow.toDouble()
@@ -211,34 +211,34 @@ public class DoubleFieldND(override val shape: ShapeND) :
         }
     }
 
-    override fun sinh(arg: StructureND<Double>): DoubleBufferND = super<DoubleFieldOpsND>.sinh(arg)
+    override fun sinh(arg: StructureND<Double>): Float64BufferND = super<Floa64FieldOpsND>.sinh(arg)
 
-    override fun cosh(arg: StructureND<Double>): DoubleBufferND = super<DoubleFieldOpsND>.cosh(arg)
+    override fun cosh(arg: StructureND<Double>): Float64BufferND = super<Floa64FieldOpsND>.cosh(arg)
 
-    override fun tanh(arg: StructureND<Double>): DoubleBufferND = super<DoubleFieldOpsND>.tan(arg)
+    override fun tanh(arg: StructureND<Double>): Float64BufferND = super<Floa64FieldOpsND>.tan(arg)
 
-    override fun asinh(arg: StructureND<Double>): DoubleBufferND = super<DoubleFieldOpsND>.asinh(arg)
+    override fun asinh(arg: StructureND<Double>): Float64BufferND = super<Floa64FieldOpsND>.asinh(arg)
 
-    override fun acosh(arg: StructureND<Double>): DoubleBufferND = super<DoubleFieldOpsND>.acosh(arg)
+    override fun acosh(arg: StructureND<Double>): Float64BufferND = super<Floa64FieldOpsND>.acosh(arg)
 
-    override fun atanh(arg: StructureND<Double>): DoubleBufferND = super<DoubleFieldOpsND>.atanh(arg)
+    override fun atanh(arg: StructureND<Double>): Float64BufferND = super<Floa64FieldOpsND>.atanh(arg)
 
-    override fun number(value: Number): DoubleBufferND {
+    override fun number(value: Number): Float64BufferND {
         val d = value.toDouble() // minimize conversions
         return structureND(shape) { d }
     }
 }
 
-public val Float64Field.ndAlgebra: DoubleFieldOpsND get() = DoubleFieldOpsND
+public val Float64Field.ndAlgebra: Floa64FieldOpsND get() = Floa64FieldOpsND
 
-public fun Float64Field.ndAlgebra(vararg shape: Int): DoubleFieldND = DoubleFieldND(ShapeND(shape))
+public fun Float64Field.ndAlgebra(vararg shape: Int): Float64FieldND = Float64FieldND(ShapeND(shape))
-public fun Float64Field.ndAlgebra(shape: ShapeND): DoubleFieldND = DoubleFieldND(shape)
+public fun Float64Field.ndAlgebra(shape: ShapeND): Float64FieldND = Float64FieldND(shape)
 
 /**
  * Produce a context for n-dimensional operations inside this real field
  */
 @UnstableKMathAPI
-public inline fun <R> Float64Field.withNdAlgebra(vararg shape: Int, action: DoubleFieldND.() -> R): R {
+public inline fun <R> Float64Field.withNdAlgebra(vararg shape: Int, action: Float64FieldND.() -> R): R {
     contract { callsInPlace(action, InvocationKind.EXACTLY_ONCE) }
-    return DoubleFieldND(ShapeND(shape)).run(action)
+    return Float64FieldND(ShapeND(shape)).run(action)
 }

kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/Int16RingND.kt

@@ -12,14 +12,14 @@ import space.kscience.kmath.operations.bufferAlgebra
 import kotlin.contracts.InvocationKind
 import kotlin.contracts.contract
 
-public sealed class ShortRingOpsND : BufferedRingOpsND<Short, Int16Ring>(Int16Ring.bufferAlgebra) {
+public sealed class Int16RingOpsND : BufferedRingOpsND<Short, Int16Ring>(Int16Ring.bufferAlgebra) {
-    public companion object : ShortRingOpsND()
+    public companion object : Int16RingOpsND()
 }
 
 @OptIn(UnstableKMathAPI::class)
-public class ShortRingND(
+public class Int16RingND(
     override val shape: ShapeND
-) : ShortRingOpsND(), RingND<Short, Int16Ring>, NumbersAddOps<StructureND<Short>> {
+) : Int16RingOpsND(), RingND<Short, Int16Ring>, NumbersAddOps<StructureND<Short>> {
 
     override fun number(value: Number): BufferND<Short> {
         val short
@@ -28,7 +28,7 @@ public class ShortRingND(
     }
 }
 
-public inline fun <R> Int16Ring.withNdAlgebra(vararg shape: Int, action: ShortRingND.() -> R): R {
+public inline fun <R> Int16Ring.withNdAlgebra(vararg shape: Int, action: Int16RingND.() -> R): R {
     contract { callsInPlace(action, InvocationKind.EXACTLY_ONCE) }
-    return ShortRingND(ShapeND(shape)).run(action)
+    return Int16RingND(ShapeND(shape)).run(action)
 }

kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/IntRingND.kt

@@ -9,13 +9,13 @@ import space.kscience.kmath.UnstableKMathAPI
 import space.kscience.kmath.operations.Int32Ring
 import space.kscience.kmath.operations.NumbersAddOps
 import space.kscience.kmath.operations.bufferAlgebra
-import space.kscience.kmath.structures.IntBuffer
+import space.kscience.kmath.structures.Int32Buffer
 import kotlin.contracts.InvocationKind
 import kotlin.contracts.contract
 
 public class IntBufferND(
     indexes: ShapeIndexer,
-    override val buffer: IntBuffer,
+    override val buffer: Int32Buffer,
 ) : MutableBufferND<Int>(indexes, buffer)
 
 public sealed class IntRingOpsND : BufferedRingOpsND<Int, Int32Ring>(Int32Ring.bufferAlgebra) {
@@ -24,7 +24,7 @@ public sealed class IntRingOpsND : BufferedRingOpsND<Int, Int32Ring>(Int32Ring.b
         val indexer = indexerBuilder(shape)
         return IntBufferND(
             indexer,
-            IntBuffer(indexer.linearSize) { offset ->
+            Int32Buffer(indexer.linearSize) { offset ->
                 elementAlgebra.initializer(indexer.index(offset))
             }
         )

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

@@ -1,43 +0,0 @@
-/*
- * Copyright 2018-2022 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.operations
-
-import space.kscience.kmath.structures.Buffer
-import space.kscience.kmath.structures.DoubleBuffer
-
-/**
- * [ExtendedField] over [DoubleBuffer].
- *
- * @property size the size of buffers to operate on.
- */
-public class DoubleBufferField(public val size: Int) : ExtendedField<Buffer<Double>>, DoubleBufferOps() {
-    override val zero: Buffer<Double> by lazy { DoubleBuffer(size) { 0.0 } }
-    override val one: Buffer<Double> by lazy { DoubleBuffer(size) { 1.0 } }
-
-    override fun sinh(arg: Buffer<Double>): DoubleBuffer = super<DoubleBufferOps>.sinh(arg)
-
-    override fun cosh(arg: Buffer<Double>): DoubleBuffer = super<DoubleBufferOps>.cosh(arg)
-
-    override fun tanh(arg: Buffer<Double>): DoubleBuffer = super<DoubleBufferOps>.tanh(arg)
-
-    override fun asinh(arg: Buffer<Double>): DoubleBuffer = super<DoubleBufferOps>.asinh(arg)
-
-    override fun acosh(arg: Buffer<Double>): DoubleBuffer = super<DoubleBufferOps>.acosh(arg)
-
-    override fun atanh(arg: Buffer<Double>): DoubleBuffer = super<DoubleBufferOps>.atanh(arg)
-
-    override fun power(arg: Buffer<Double>, pow: Number): DoubleBuffer = if (pow.isInteger()) {
-        arg.map { it.pow(pow.toInt()) }
-    } else {
-        arg.map {
-            if(it<0) throw IllegalArgumentException("Negative argument $it could not be raised to the fractional power")
-            it.pow(pow.toDouble())
-        }
-    }
-
-    override fun unaryOperationFunction(operation: String): (arg: Buffer<Double>) -> Buffer<Double> =
-        super<ExtendedField>.unaryOperationFunction(operation)
-}

kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/Float64BufferField.kt

@@ -0,0 +1,43 @@
+/*
+ * Copyright 2018-2022 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.operations
+
+import space.kscience.kmath.structures.Buffer
+import space.kscience.kmath.structures.Float64Buffer
+
+/**
+ * [ExtendedField] over [Float64Buffer].
+ *
+ * @property size the size of buffers to operate on.
+ */
+public class Float64BufferField(public val size: Int) : ExtendedField<Buffer<Double>>, Float64BufferOps() {
+    override val zero: Buffer<Double> by lazy { Float64Buffer(size) { 0.0 } }
+    override val one: Buffer<Double> by lazy { Float64Buffer(size) { 1.0 } }
+
+    override fun sinh(arg: Buffer<Double>): Float64Buffer = super<Float64BufferOps>.sinh(arg)
+
+    override fun cosh(arg: Buffer<Double>): Float64Buffer = super<Float64BufferOps>.cosh(arg)
+
+    override fun tanh(arg: Buffer<Double>): Float64Buffer = super<Float64BufferOps>.tanh(arg)
+
+    override fun asinh(arg: Buffer<Double>): Float64Buffer = super<Float64BufferOps>.asinh(arg)
+
+    override fun acosh(arg: Buffer<Double>): Float64Buffer = super<Float64BufferOps>.acosh(arg)
+
+    override fun atanh(arg: Buffer<Double>): Float64Buffer = super<Float64BufferOps>.atanh(arg)
+
+    override fun power(arg: Buffer<Double>, pow: Number): Float64Buffer = if (pow.isInteger()) {
+        arg.map { it.pow(pow.toInt()) }
+    } else {
+        arg.map {
+            if(it<0) throw IllegalArgumentException("Negative argument $it could not be raised to the fractional power")
+            it.pow(pow.toDouble())
+        }
+    }
+
+    override fun unaryOperationFunction(operation: String): (arg: Buffer<Double>) -> Buffer<Double> =
+        super<ExtendedField>.unaryOperationFunction(operation)
+}

kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/Float64BufferOps.kt

@@ -12,9 +12,9 @@ import kotlin.math.pow
 import kotlin.math.sqrt
 
 /**
- * [ExtendedFieldOps] over [DoubleBuffer].
+ * [ExtendedFieldOps] over [Float64Buffer].
  */
-public abstract class DoubleBufferOps : BufferAlgebra<Double, Float64Field>, ExtendedFieldOps<Buffer<Double>>,
+public abstract class Float64BufferOps : BufferAlgebra<Double, Float64Field>, ExtendedFieldOps<Buffer<Double>>,
     Norm<Buffer<Double>, Double> {
 
     override val elementAlgebra: Float64Field get() = Float64Field
@@ -23,23 +23,23 @@ public abstract class DoubleBufferOps : BufferAlgebra<Double, Float64Field>, Ext
 
     @Suppress("OVERRIDE_BY_INLINE")
     @OptIn(UnstableKMathAPI::class)
-    final override inline fun Buffer<Double>.map(block: Float64Field.(Double) -> Double): DoubleBuffer =
+    final override inline fun Buffer<Double>.map(block: Float64Field.(Double) -> Double): Float64Buffer =
         DoubleArray(size) { Float64Field.block(getDouble(it)) }.asBuffer()
 
 
     @OptIn(UnstableKMathAPI::class)
     @Suppress("OVERRIDE_BY_INLINE")
-    final override inline fun Buffer<Double>.mapIndexed(block: Float64Field.(index: Int, arg: Double) -> Double): DoubleBuffer =
+    final override inline fun Buffer<Double>.mapIndexed(block: Float64Field.(index: Int, arg: Double) -> Double): Float64Buffer =
-        DoubleBuffer(size) { Float64Field.block(it, getDouble(it)) }
+        Float64Buffer(size) { Float64Field.block(it, getDouble(it)) }
 
     @OptIn(UnstableKMathAPI::class)
     @Suppress("OVERRIDE_BY_INLINE")
     final override inline fun Buffer<Double>.zip(
         other: Buffer<Double>,
         block: Float64Field.(left: Double, right: Double) -> Double,
-    ): DoubleBuffer {
+    ): Float64Buffer {
         require(size == other.size) { "Incompatible buffer sizes. left: ${size}, right: ${other.size}" }
-        return DoubleBuffer(size) { Float64Field.block(getDouble(it), other.getDouble(it)) }
+        return Float64Buffer(size) { Float64Field.block(getDouble(it), other.getDouble(it)) }
     }
 
     override fun unaryOperationFunction(operation: String): (arg: Buffer<Double>) -> Buffer<Double> =
@@ -48,32 +48,32 @@ public abstract class DoubleBufferOps : BufferAlgebra<Double, Float64Field>, Ext
     override fun binaryOperationFunction(operation: String): (left: Buffer<Double>, right: Buffer<Double>) -> Buffer<Double> =
         super<ExtendedFieldOps>.binaryOperationFunction(operation)
 
-    override fun Buffer<Double>.unaryMinus(): DoubleBuffer = map { -it }
+    override fun Buffer<Double>.unaryMinus(): Float64Buffer = map { -it }
 
-    override fun add(left: Buffer<Double>, right: Buffer<Double>): DoubleBuffer {
+    override fun add(left: Buffer<Double>, right: Buffer<Double>): Float64Buffer {
         require(right.size == left.size) {
             "The size of the first buffer ${left.size} should be the same as for second one: ${right.size} "
         }
 
-        return if (left is DoubleBuffer && right is DoubleBuffer) {
+        return if (left is Float64Buffer && right is Float64Buffer) {
             val aArray = left.array
             val bArray = right.array
-            DoubleBuffer(DoubleArray(left.size) { aArray[it] + bArray[it] })
+            Float64Buffer(DoubleArray(left.size) { aArray[it] + bArray[it] })
-        } else DoubleBuffer(DoubleArray(left.size) { left[it] + right[it] })
+        } else Float64Buffer(DoubleArray(left.size) { left[it] + right[it] })
     }
 
-    override fun Buffer<Double>.plus(arg: Buffer<Double>): DoubleBuffer = add(this, arg)
+    override fun Buffer<Double>.plus(arg: Buffer<Double>): Float64Buffer = add(this, arg)
 
-    override fun Buffer<Double>.minus(arg: Buffer<Double>): DoubleBuffer {
+    override fun Buffer<Double>.minus(arg: Buffer<Double>): Float64Buffer {
         require(arg.size == this.size) {
             "The size of the first buffer ${this.size} should be the same as for second one: ${arg.size} "
         }
 
-        return if (this is DoubleBuffer && arg is DoubleBuffer) {
+        return if (this is Float64Buffer && arg is Float64Buffer) {
             val aArray = this.array
             val bArray = arg.array
-            DoubleBuffer(DoubleArray(this.size) { aArray[it] - bArray[it] })
+            Float64Buffer(DoubleArray(this.size) { aArray[it] - bArray[it] })
-        } else DoubleBuffer(DoubleArray(this.size) { this[it] - arg[it] })
+        } else Float64Buffer(DoubleArray(this.size) { this[it] - arg[it] })
     }
 
     //
@@ -96,61 +96,61 @@ public abstract class DoubleBufferOps : BufferAlgebra<Double, Float64Field>, Ext
 //    }
 
     @UnstableKMathAPI
-    override fun multiply(left: Buffer<Double>, right: Buffer<Double>): DoubleBuffer {
+    override fun multiply(left: Buffer<Double>, right: Buffer<Double>): Float64Buffer {
         require(right.size == left.size) {
             "The size of the first buffer ${left.size} should be the same as for second one: ${right.size} "
         }
 
-        return if (left is DoubleBuffer && right is DoubleBuffer) {
+        return if (left is Float64Buffer && right is Float64Buffer) {
             val aArray = left.array
             val bArray = right.array
-            DoubleBuffer(DoubleArray(left.size) { aArray[it] * bArray[it] })
+            Float64Buffer(DoubleArray(left.size) { aArray[it] * bArray[it] })
-        } else DoubleBuffer(DoubleArray(left.size) { left[it] * right[it] })
+        } else Float64Buffer(DoubleArray(left.size) { left[it] * right[it] })
     }
 
-    override fun divide(left: Buffer<Double>, right: Buffer<Double>): DoubleBuffer {
+    override fun divide(left: Buffer<Double>, right: Buffer<Double>): Float64Buffer {
         require(right.size == left.size) {
             "The size of the first buffer ${left.size} should be the same as for second one: ${right.size} "
         }
 
-        return if (left is DoubleBuffer && right is DoubleBuffer) {
+        return if (left is Float64Buffer && right is Float64Buffer) {
             val aArray = left.array
             val bArray = right.array
-            DoubleBuffer(DoubleArray(left.size) { aArray[it] / bArray[it] })
+            Float64Buffer(DoubleArray(left.size) { aArray[it] / bArray[it] })
-        } else DoubleBuffer(DoubleArray(left.size) { left[it] / right[it] })
+        } else Float64Buffer(DoubleArray(left.size) { left[it] / right[it] })
     }
 
-    override fun sin(arg: Buffer<Double>): DoubleBuffer = arg.map { sin(it) }
+    override fun sin(arg: Buffer<Double>): Float64Buffer = arg.map { sin(it) }
 
-    override fun cos(arg: Buffer<Double>): DoubleBuffer = arg.map { cos(it) }
+    override fun cos(arg: Buffer<Double>): Float64Buffer = arg.map { cos(it) }
 
-    override fun tan(arg: Buffer<Double>): DoubleBuffer = arg.map { tan(it) }
+    override fun tan(arg: Buffer<Double>): Float64Buffer = arg.map { tan(it) }
 
-    override fun asin(arg: Buffer<Double>): DoubleBuffer = arg.map { asin(it) }
+    override fun asin(arg: Buffer<Double>): Float64Buffer = arg.map { asin(it) }
 
-    override fun acos(arg: Buffer<Double>): DoubleBuffer = arg.map { acos(it) }
+    override fun acos(arg: Buffer<Double>): Float64Buffer = arg.map { acos(it) }
 
-    override fun atan(arg: Buffer<Double>): DoubleBuffer = arg.map { atan(it) }
+    override fun atan(arg: Buffer<Double>): Float64Buffer = arg.map { atan(it) }
 
-    override fun sinh(arg: Buffer<Double>): DoubleBuffer = arg.map { sinh(it) }
+    override fun sinh(arg: Buffer<Double>): Float64Buffer = arg.map { sinh(it) }
 
-    override fun cosh(arg: Buffer<Double>): DoubleBuffer = arg.map { cosh(it) }
+    override fun cosh(arg: Buffer<Double>): Float64Buffer = arg.map { cosh(it) }
 
-    override fun tanh(arg: Buffer<Double>): DoubleBuffer = arg.map { tanh(it) }
+    override fun tanh(arg: Buffer<Double>): Float64Buffer = arg.map { tanh(it) }
 
-    override fun asinh(arg: Buffer<Double>): DoubleBuffer = arg.map { asinh(it) }
+    override fun asinh(arg: Buffer<Double>): Float64Buffer = arg.map { asinh(it) }
 
-    override fun acosh(arg: Buffer<Double>): DoubleBuffer = arg.map { acosh(it) }
+    override fun acosh(arg: Buffer<Double>): Float64Buffer = arg.map { acosh(it) }
 
-    override fun atanh(arg: Buffer<Double>): DoubleBuffer = arg.map { atanh(it) }
+    override fun atanh(arg: Buffer<Double>): Float64Buffer = arg.map { atanh(it) }
 
-    override fun exp(arg: Buffer<Double>): DoubleBuffer = arg.map { exp(it) }
+    override fun exp(arg: Buffer<Double>): Float64Buffer = arg.map { exp(it) }
 
-    override fun ln(arg: Buffer<Double>): DoubleBuffer = arg.map { ln(it) }
+    override fun ln(arg: Buffer<Double>): Float64Buffer = arg.map { ln(it) }
 
-    override fun norm(arg: Buffer<Double>): Double = DoubleL2Norm.norm(arg)
+    override fun norm(arg: Buffer<Double>): Double = Float64L2Norm.norm(arg)
 
-    override fun scale(a: Buffer<Double>, value: Double): DoubleBuffer = a.map { it * value }
+    override fun scale(a: Buffer<Double>, value: Double): Float64Buffer = a.map { it * value }
 
     override fun power(arg: Buffer<Double>, pow: Number): Buffer<Double> = if (pow is Int) {
         arg.map { it.pow(pow) }
@@ -158,37 +158,37 @@ public abstract class DoubleBufferOps : BufferAlgebra<Double, Float64Field>, Ext
         arg.map { it.pow(pow.toDouble()) }
     }
 
-    public companion object : DoubleBufferOps()
+    public companion object : Float64BufferOps()
 }
 
-public object DoubleL2Norm : Norm<Point<Double>, Double> {
+public object Float64L2Norm : Norm<Point<Double>, Double> {
     override fun norm(arg: Point<Double>): Double = sqrt(arg.fold(0.0) { acc: Double, d: Double -> acc + d.pow(2) })
 }
 
-public fun DoubleBufferOps.sum(buffer: Buffer<Double>): Double = buffer.reduce(Double::plus)
+public fun Float64BufferOps.sum(buffer: Buffer<Double>): Double = buffer.reduce(Double::plus)
 
 /**
  * Sum of elements using given [conversion]
  */
-public inline fun <T> DoubleBufferOps.sumOf(buffer: Buffer<T>, conversion: (T) -> Double): Double =
+public inline fun <T> Float64BufferOps.sumOf(buffer: Buffer<T>, conversion: (T) -> Double): Double =
     buffer.fold(0.0) { acc, value -> acc + conversion(value) }
 
-public fun DoubleBufferOps.average(buffer: Buffer<Double>): Double = sum(buffer) / buffer.size
+public fun Float64BufferOps.average(buffer: Buffer<Double>): Double = sum(buffer) / buffer.size
 
 /**
  * Average of elements using given [conversion]
  */
-public inline fun <T> DoubleBufferOps.averageOf(buffer: Buffer<T>, conversion: (T) -> Double): Double =
+public inline fun <T> Float64BufferOps.averageOf(buffer: Buffer<T>, conversion: (T) -> Double): Double =
     sumOf(buffer, conversion) / buffer.size
 
-public fun DoubleBufferOps.dispersion(buffer: Buffer<Double>): Double {
+public fun Float64BufferOps.dispersion(buffer: Buffer<Double>): Double {
     val av = average(buffer)
     return buffer.fold(0.0) { acc, value -> acc + (value - av).pow(2) } / buffer.size
 }
 
-public fun DoubleBufferOps.std(buffer: Buffer<Double>): Double = sqrt(dispersion(buffer))
+public fun Float64BufferOps.std(buffer: Buffer<Double>): Double = sqrt(dispersion(buffer))
 
-public fun DoubleBufferOps.covariance(x: Buffer<Double>, y: Buffer<Double>): Double {
+public fun Float64BufferOps.covariance(x: Buffer<Double>, y: Buffer<Double>): Double {
     require(x.size == y.size) { "Expected buffers of the same size, but x.size == ${x.size} and y.size == ${y.size}" }
     val xMean = average(x)
     val yMean = average(y)

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

@@ -22,7 +22,7 @@ import kotlin.math.roundToLong
  */
 @Suppress("EXTENSION_SHADOWED_BY_MEMBER")
 public object Int16Field : Field<Int16>, Norm<Int16, Int16>, NumericAlgebra<Int16> {
-    override val bufferFactory: MutableBufferFactory<Int16> = MutableBufferFactory(::ShortBuffer)
+    override val bufferFactory: MutableBufferFactory<Int16> = MutableBufferFactory(::Int16Buffer)
     override val zero: Int16 get() = 0
     override val one: Int16 get() = 1
 
@@ -45,7 +45,7 @@ public object Int16Field : Field<Int16>, Norm<Int16, Int16>, NumericAlgebra<Int1
  */
 @Suppress("EXTENSION_SHADOWED_BY_MEMBER")
 public object Int32Field : Field<Int32>, Norm<Int32, Int32>, NumericAlgebra<Int32> {
-    override val bufferFactory: MutableBufferFactory<Int> = MutableBufferFactory(::IntBuffer)
+    override val bufferFactory: MutableBufferFactory<Int> = MutableBufferFactory(::Int32Buffer)
     override val zero: Int get() = 0
     override val one: Int get() = 1
 
@@ -68,7 +68,7 @@ public object Int32Field : Field<Int32>, Norm<Int32, Int32>, NumericAlgebra<Int3
  */
 @Suppress("EXTENSION_SHADOWED_BY_MEMBER")
 public object Int64Field : Field<Int64>, Norm<Int64, Int64>, NumericAlgebra<Int64> {
-    override val bufferFactory: MutableBufferFactory<Int64> = MutableBufferFactory(::LongBuffer)
+    override val bufferFactory: MutableBufferFactory<Int64> = MutableBufferFactory(::Int64Buffer)
     override val zero: Int64 get() = 0L
     override val one: Int64 get() = 1L
 

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

@@ -63,16 +63,16 @@ public interface ExtendedField<T> : ExtendedFieldOps<T>, Field<T>, NumericAlgebr
 }
 
 /**
- * A field for [Double] without boxing. Does not produce appropriate field element.
+ * A field for [Double] without boxing. Does not produce an appropriate field element.
  */
-@Suppress("EXTENSION_SHADOWED_BY_MEMBER", "OVERRIDE_BY_INLINE")
+@Suppress("EXTENSION_SHADOWED_BY_MEMBER")
 public object Float64Field : ExtendedField<Double>, Norm<Double, Double>, ScaleOperations<Double> {
-    override val bufferFactory: MutableBufferFactory<Double> = MutableBufferFactory(::DoubleBuffer)
+    override val bufferFactory: MutableBufferFactory<Double> = MutableBufferFactory(::Float64Buffer)
 
-    override inline val zero: Double get() = 0.0
+    override val zero: Double get() = 0.0
-    override inline val one: Double get() = 1.0
+    override val one: Double get() = 1.0
 
-    override inline fun number(value: Number): Double = value.toDouble()
+    override fun number(value: Number): Double = value.toDouble()
 
     override fun binaryOperationFunction(operation: String): (left: Double, right: Double) -> Double =
         when (operation) {
@@ -80,26 +80,26 @@ public object Float64Field : ExtendedField<Double>, Norm<Double, Double>, ScaleO
             else -> super<ExtendedField>.binaryOperationFunction(operation)
         }
 
-    override inline fun add(left: Double, right: Double): Double = left + right
+    override fun add(left: Double, right: Double): Double = left + right
 
-    override inline fun multiply(left: Double, right: Double): Double = left * right
+    override fun multiply(left: Double, right: Double): Double = left * right
-    override inline fun divide(left: Double, right: Double): Double = left / right
+    override fun divide(left: Double, right: Double): Double = left / right
 
-    override inline fun scale(a: Double, value: Double): Double = a * value
+    override fun scale(a: Double, value: Double): Double = a * value
 
-    override inline fun sin(arg: Double): Double = kotlin.math.sin(arg)
+    override fun sin(arg: Double): Double = kotlin.math.sin(arg)
-    override inline fun cos(arg: Double): Double = kotlin.math.cos(arg)
+    override fun cos(arg: Double): Double = kotlin.math.cos(arg)
-    override inline fun tan(arg: Double): Double = kotlin.math.tan(arg)
+    override fun tan(arg: Double): Double = kotlin.math.tan(arg)
-    override inline fun acos(arg: Double): Double = kotlin.math.acos(arg)
+    override fun acos(arg: Double): Double = kotlin.math.acos(arg)
-    override inline fun asin(arg: Double): Double = kotlin.math.asin(arg)
+    override fun asin(arg: Double): Double = kotlin.math.asin(arg)
-    override inline fun atan(arg: Double): Double = kotlin.math.atan(arg)
+    override fun atan(arg: Double): Double = kotlin.math.atan(arg)
 
-    override inline fun sinh(arg: Double): Double = kotlin.math.sinh(arg)
+    override fun sinh(arg: Double): Double = kotlin.math.sinh(arg)
-    override inline fun cosh(arg: Double): Double = kotlin.math.cosh(arg)
+    override fun cosh(arg: Double): Double = kotlin.math.cosh(arg)
-    override inline fun tanh(arg: Double): Double = kotlin.math.tanh(arg)
+    override fun tanh(arg: Double): Double = kotlin.math.tanh(arg)
-    override inline fun asinh(arg: Double): Double = kotlin.math.asinh(arg)
+    override fun asinh(arg: Double): Double = kotlin.math.asinh(arg)
-    override inline fun acosh(arg: Double): Double = kotlin.math.acosh(arg)
+    override fun acosh(arg: Double): Double = kotlin.math.acosh(arg)
-    override inline fun atanh(arg: Double): Double = kotlin.math.atanh(arg)
+    override fun atanh(arg: Double): Double = kotlin.math.atanh(arg)
 
     override fun sqrt(arg: Double): Double = kotlin.math.sqrt(arg)
     override fun power(arg: Double, pow: Number): Double = when {
@@ -108,16 +108,16 @@ public object Float64Field : ExtendedField<Double>, Norm<Double, Double>, ScaleO
         else -> arg.kpow(pow.toDouble())
     }
 
-    override inline fun exp(arg: Double): Double = kotlin.math.exp(arg)
+    override fun exp(arg: Double): Double = kotlin.math.exp(arg)
-    override inline fun ln(arg: Double): Double = kotlin.math.ln(arg)
+    override fun ln(arg: Double): Double = kotlin.math.ln(arg)
 
-    override inline fun norm(arg: Double): Double = abs(arg)
+    override fun norm(arg: Double): Double = abs(arg)
 
-    override inline fun Double.unaryMinus(): Double = -this
+    override fun Double.unaryMinus(): Double = -this
-    override inline fun Double.plus(arg: Double): Double = this + arg
+    override fun Double.plus(arg: Double): Double = this + arg
-    override inline fun Double.minus(arg: Double): Double = this - arg
+    override fun Double.minus(arg: Double): Double = this - arg
-    override inline fun Double.times(arg: Double): Double = this * arg
+    override fun Double.times(arg: Double): Double = this * arg
-    override inline fun Double.div(arg: Double): Double = this / arg
+    override fun Double.div(arg: Double): Double = this / arg
 }
 
 public typealias DoubleField = Float64Field
@@ -125,14 +125,14 @@ public typealias DoubleField = Float64Field
 public val Double.Companion.algebra: Float64Field get() = Float64Field
 
 /**
- * A field for [Float] without boxing. Does not produce appropriate field element.
+ * A field for [Float] without boxing. Does not produce an appropriate field element.
  */
-@Suppress("EXTENSION_SHADOWED_BY_MEMBER", "OVERRIDE_BY_INLINE")
+@Suppress("EXTENSION_SHADOWED_BY_MEMBER")
 public object Float32Field : ExtendedField<Float>, Norm<Float, Float> {
-    override val bufferFactory: MutableBufferFactory<Float> = MutableBufferFactory(::FloatBuffer)
+    override val bufferFactory: MutableBufferFactory<Float> = MutableBufferFactory(::Float32Buffer)
 
-    override inline val zero: Float get() = 0.0f
+    override val zero: Float get() = 0.0f
-    override inline val one: Float get() = 1.0f
+    override val one: Float get() = 1.0f
 
     override fun number(value: Number): Float = value.toFloat()
 
@@ -142,40 +142,40 @@ public object Float32Field : ExtendedField<Float>, Norm<Float, Float> {
             else -> super.binaryOperationFunction(operation)
         }
 
-    override inline fun add(left: Float, right: Float): Float = left + right
+    override fun add(left: Float, right: Float): Float = left + right
     override fun scale(a: Float, value: Double): Float = a * value.toFloat()
 
-    override inline fun multiply(left: Float, right: Float): Float = left * right
+    override fun multiply(left: Float, right: Float): Float = left * right
 
-    override inline fun divide(left: Float, right: Float): Float = left / right
+    override fun divide(left: Float, right: Float): Float = left / right
 
-    override inline fun sin(arg: Float): Float = kotlin.math.sin(arg)
+    override fun sin(arg: Float): Float = kotlin.math.sin(arg)
-    override inline fun cos(arg: Float): Float = kotlin.math.cos(arg)
+    override fun cos(arg: Float): Float = kotlin.math.cos(arg)
-    override inline fun tan(arg: Float): Float = kotlin.math.tan(arg)
+    override fun tan(arg: Float): Float = kotlin.math.tan(arg)
-    override inline fun acos(arg: Float): Float = kotlin.math.acos(arg)
+    override fun acos(arg: Float): Float = kotlin.math.acos(arg)
-    override inline fun asin(arg: Float): Float = kotlin.math.asin(arg)
+    override fun asin(arg: Float): Float = kotlin.math.asin(arg)
-    override inline fun atan(arg: Float): Float = kotlin.math.atan(arg)
+    override fun atan(arg: Float): Float = kotlin.math.atan(arg)
 
-    override inline fun sinh(arg: Float): Float = kotlin.math.sinh(arg)
+    override fun sinh(arg: Float): Float = kotlin.math.sinh(arg)
-    override inline fun cosh(arg: Float): Float = kotlin.math.cosh(arg)
+    override fun cosh(arg: Float): Float = kotlin.math.cosh(arg)
-    override inline fun tanh(arg: Float): Float = kotlin.math.tanh(arg)
+    override fun tanh(arg: Float): Float = kotlin.math.tanh(arg)
-    override inline fun asinh(arg: Float): Float = kotlin.math.asinh(arg)
+    override fun asinh(arg: Float): Float = kotlin.math.asinh(arg)
-    override inline fun acosh(arg: Float): Float = kotlin.math.acosh(arg)
+    override fun acosh(arg: Float): Float = kotlin.math.acosh(arg)
-    override inline fun atanh(arg: Float): Float = kotlin.math.atanh(arg)
+    override fun atanh(arg: Float): Float = kotlin.math.atanh(arg)
 
-    override inline fun sqrt(arg: Float): Float = kotlin.math.sqrt(arg)
+    override fun sqrt(arg: Float): Float = kotlin.math.sqrt(arg)
-    override inline fun power(arg: Float, pow: Number): Float = arg.kpow(pow.toFloat())
+    override fun power(arg: Float, pow: Number): Float = arg.kpow(pow.toFloat())
 
-    override inline fun exp(arg: Float): Float = kotlin.math.exp(arg)
+    override fun exp(arg: Float): Float = kotlin.math.exp(arg)
-    override inline fun ln(arg: Float): Float = kotlin.math.ln(arg)
+    override fun ln(arg: Float): Float = kotlin.math.ln(arg)
 
-    override inline fun norm(arg: Float): Float = abs(arg)
+    override fun norm(arg: Float): Float = abs(arg)
 
-    override inline fun Float.unaryMinus(): Float = -this
+    override fun Float.unaryMinus(): Float = -this
-    override inline fun Float.plus(arg: Float): Float = this + arg
+    override fun Float.plus(arg: Float): Float = this + arg
-    override inline fun Float.minus(arg: Float): Float = this - arg
+    override fun Float.minus(arg: Float): Float = this - arg
-    override inline fun Float.times(arg: Float): Float = this * arg
+    override fun Float.times(arg: Float): Float = this * arg
-    override inline fun Float.div(arg: Float): Float = this / arg
+    override fun Float.div(arg: Float): Float = this / arg
 }
 
 public typealias FloatField = Float32Field
@@ -183,24 +183,24 @@ public typealias FloatField = Float32Field
 public val Float.Companion.algebra: Float32Field get() = Float32Field
 
 /**
- * A field for [Int] without boxing. Does not produce corresponding ring element.
+ * A field for [Int] without boxing. Does not produce a corresponding ring element.
  */
-@Suppress("EXTENSION_SHADOWED_BY_MEMBER", "OVERRIDE_BY_INLINE")
+@Suppress("EXTENSION_SHADOWED_BY_MEMBER")
 public object Int32Ring : Ring<Int>, Norm<Int, Int>, NumericAlgebra<Int> {
-    override val bufferFactory: MutableBufferFactory<Int> = MutableBufferFactory(::IntBuffer)
+    override val bufferFactory: MutableBufferFactory<Int> = MutableBufferFactory(::Int32Buffer)
 
-    override inline val zero: Int get() = 0
+    override val zero: Int get() = 0
-    override inline val one: Int get() = 1
+    override val one: Int get() = 1
 
     override fun number(value: Number): Int = value.toInt()
-    override inline fun add(left: Int, right: Int): Int = left + right
+    override fun add(left: Int, right: Int): Int = left + right
-    override inline fun multiply(left: Int, right: Int): Int = left * right
+    override fun multiply(left: Int, right: Int): Int = left * right
-    override inline fun norm(arg: Int): Int = abs(arg)
+    override fun norm(arg: Int): Int = abs(arg)
 
-    override inline fun Int.unaryMinus(): Int = -this
+    override fun Int.unaryMinus(): Int = -this
-    override inline fun Int.plus(arg: Int): Int = this + arg
+    override fun Int.plus(arg: Int): Int = this + arg
-    override inline fun Int.minus(arg: Int): Int = this - arg
+    override fun Int.minus(arg: Int): Int = this - arg
-    override inline fun Int.times(arg: Int): Int = this * arg
+    override fun Int.times(arg: Int): Int = this * arg
 }
 
 public typealias IntRing = Int32Ring
@@ -208,24 +208,24 @@ public typealias IntRing = Int32Ring
 public val Int.Companion.algebra: Int32Ring get() = Int32Ring
 
 /**
- * A field for [Short] without boxing. Does not produce appropriate ring element.
+ * A field for [Short] without boxing. Does not produce an appropriate ring element.
  */
-@Suppress("EXTENSION_SHADOWED_BY_MEMBER", "OVERRIDE_BY_INLINE")
+@Suppress("EXTENSION_SHADOWED_BY_MEMBER")
 public object Int16Ring : Ring<Short>, Norm<Short, Short>, NumericAlgebra<Short> {
-    override val bufferFactory: MutableBufferFactory<Short> = MutableBufferFactory(::ShortBuffer)
+    override val bufferFactory: MutableBufferFactory<Short> = MutableBufferFactory(::Int16Buffer)
 
-    override inline val zero: Short get() = 0
+    override val zero: Short get() = 0
-    override inline val one: Short get() = 1
+    override val one: Short get() = 1
 
     override fun number(value: Number): Short = value.toShort()
-    override inline fun add(left: Short, right: Short): Short = (left + right).toShort()
+    override fun add(left: Short, right: Short): Short = (left + right).toShort()
-    override inline fun multiply(left: Short, right: Short): Short = (left * right).toShort()
+    override fun multiply(left: Short, right: Short): Short = (left * right).toShort()
     override fun norm(arg: Short): Short = if (arg > 0) arg else (-arg).toShort()
 
-    override inline fun Short.unaryMinus(): Short = (-this).toShort()
+    override fun Short.unaryMinus(): Short = (-this).toShort()
-    override inline fun Short.plus(arg: Short): Short = (this + arg).toShort()
+    override fun Short.plus(arg: Short): Short = (this + arg).toShort()
-    override inline fun Short.minus(arg: Short): Short = (this - arg).toShort()
+    override fun Short.minus(arg: Short): Short = (this - arg).toShort()
-    override inline fun Short.times(arg: Short): Short = (this * arg).toShort()
+    override fun Short.times(arg: Short): Short = (this * arg).toShort()
 }
 
 public typealias ShortRing = Int16Ring
@@ -235,45 +235,47 @@ public val Short.Companion.algebra: Int16Ring get() = Int16Ring
 /**
  * A field for [Byte] without boxing. Does not produce appropriate ring element.
  */
-@Suppress("EXTENSION_SHADOWED_BY_MEMBER", "OVERRIDE_BY_INLINE")
+@Suppress("EXTENSION_SHADOWED_BY_MEMBER")
-public object ByteRing : Ring<Byte>, Norm<Byte, Byte>, NumericAlgebra<Byte> {
+public object Int8Ring : Ring<Byte>, Norm<Byte, Byte>, NumericAlgebra<Byte> {
-    override val bufferFactory: MutableBufferFactory<Byte> = MutableBufferFactory(::ByteBuffer)
+    override val bufferFactory: MutableBufferFactory<Byte> = MutableBufferFactory(::Int8Buffer)
 
-    override inline val zero: Byte get() = 0
+    override val zero: Byte get() = 0
-    override inline val one: Byte get() = 1
+    override val one: Byte get() = 1
 
     override fun number(value: Number): Byte = value.toByte()
-    override inline fun add(left: Byte, right: Byte): Byte = (left + right).toByte()
+    override fun add(left: Byte, right: Byte): Byte = (left + right).toByte()
-    override inline fun multiply(left: Byte, right: Byte): Byte = (left * right).toByte()
+    override fun multiply(left: Byte, right: Byte): Byte = (left * right).toByte()
     override fun norm(arg: Byte): Byte = if (arg > 0) arg else (-arg).toByte()
 
-    override inline fun Byte.unaryMinus(): Byte = (-this).toByte()
+    override fun Byte.unaryMinus(): Byte = (-this).toByte()
-    override inline fun Byte.plus(arg: Byte): Byte = (this + arg).toByte()
+    override fun Byte.plus(arg: Byte): Byte = (this + arg).toByte()
-    override inline fun Byte.minus(arg: Byte): Byte = (this - arg).toByte()
+    override fun Byte.minus(arg: Byte): Byte = (this - arg).toByte()
-    override inline fun Byte.times(arg: Byte): Byte = (this * arg).toByte()
+    override fun Byte.times(arg: Byte): Byte = (this * arg).toByte()
 }
 
-public val Byte.Companion.algebra: ByteRing get() = ByteRing
+public typealias ByteRing = Int8Ring
+
+public val Byte.Companion.algebra: Int8Ring get() = Int8Ring
 
 /**
  * A field for [Double] without boxing. Does not produce an appropriate ring element.
  */
-@Suppress("EXTENSION_SHADOWED_BY_MEMBER", "OVERRIDE_BY_INLINE")
+@Suppress("EXTENSION_SHADOWED_BY_MEMBER")
 public object Int64Ring : Ring<Long>, Norm<Long, Long>, NumericAlgebra<Long> {
-    override val bufferFactory: MutableBufferFactory<Long> = MutableBufferFactory(::LongBuffer)
+    override val bufferFactory: MutableBufferFactory<Long> = MutableBufferFactory(::Int64Buffer)
 
-    override inline val zero: Long get() = 0L
+    override val zero: Long get() = 0L
-    override inline val one: Long get() = 1L
+    override val one: Long get() = 1L
 
     override fun number(value: Number): Long = value.toLong()
-    override inline fun add(left: Long, right: Long): Long = left + right
+    override fun add(left: Long, right: Long): Long = left + right
-    override inline fun multiply(left: Long, right: Long): Long = left * right
+    override fun multiply(left: Long, right: Long): Long = left * right
     override fun norm(arg: Long): Long = abs(arg)
 
-    override inline fun Long.unaryMinus(): Long = (-this)
+    override fun Long.unaryMinus(): Long = (-this)
-    override inline fun Long.plus(arg: Long): Long = (this + arg)
+    override fun Long.plus(arg: Long): Long = (this + arg)
-    override inline fun Long.minus(arg: Long): Long = (this - arg)
+    override fun Long.minus(arg: Long): Long = (this - arg)
-    override inline fun Long.times(arg: Long): Long = (this * arg)
+    override fun Long.times(arg: Long): Long = (this * arg)
 }
 
 public typealias LongRing = Int64Ring

kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/Buffer.kt

@@ -93,8 +93,8 @@ public interface Buffer<out T> : WithSize {
             List(size, initializer).asBuffer()
 
         /**
-         * Creates a [Buffer] of given [type]. If the type is primitive, specialized buffers are used ([IntBuffer],
+         * Creates a [Buffer] of given [type]. If the type is primitive, specialized buffers are used ([Int32Buffer],
-         * [DoubleBuffer], etc.), [ListBuffer] is returned otherwise.
+         * [Float64Buffer], etc.), [ListBuffer] is returned otherwise.
          *
          * The [size] is specified, and each element is calculated by calling the specified [initializer] function.
          */
@@ -110,8 +110,8 @@ public interface Buffer<out T> : WithSize {
             }
 
         /**
-         * Creates a [Buffer] of given type [T]. If the type is primitive, specialized buffers are used ([IntBuffer],
+         * Creates a [Buffer] of given type [T]. If the type is primitive, specialized buffers are used ([Int32Buffer],
-         * [DoubleBuffer], etc.), [ListBuffer] is returned otherwise.
+         * [Float64Buffer], etc.), [ListBuffer] is returned otherwise.
          *
          * The [size] is specified, and each element is calculated by calling the specified [initializer] function.
          */

kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/Float32Buffer.kt

@@ -14,7 +14,7 @@ import kotlin.jvm.JvmInline
  * @author Iaroslav Postovalov
  */
 @JvmInline
-public value class FloatBuffer(public val array: FloatArray) : PrimitiveBuffer<Float> {
+public value class Float32Buffer(public val array: FloatArray) : PrimitiveBuffer<Float> {
     override val size: Int get() = array.size
 
     override operator fun get(index: Int): Float = array[index]
@@ -26,35 +26,37 @@ public value class FloatBuffer(public val array: FloatArray) : PrimitiveBuffer<F
     override operator fun iterator(): FloatIterator = array.iterator()
 
     override fun copy(): MutableBuffer<Float> =
-        FloatBuffer(array.copyOf())
+        Float32Buffer(array.copyOf())
 }
 
+public typealias FloatBuffer = Float32Buffer
+
 /**
- * Creates a new [FloatBuffer] with the specified [size], where each element is calculated by calling the specified
+ * Creates a new [Float32Buffer] with the specified [size], where each element is calculated by calling the specified
  * [init] function.
  *
  * The function [init] is called for each array element sequentially starting from the first one.
  * It should return the value for a buffer element given its index.
  */
-public inline fun FloatBuffer(size: Int, init: (Int) -> Float): FloatBuffer = FloatBuffer(FloatArray(size) { init(it) })
+public inline fun Float32Buffer(size: Int, init: (Int) -> Float): Float32Buffer = Float32Buffer(FloatArray(size) { init(it) })
 
 /**
- * Returns a new [FloatBuffer] of given elements.
+ * Returns a new [Float32Buffer] of given elements.
  */
-public fun FloatBuffer(vararg floats: Float): FloatBuffer = FloatBuffer(floats)
+public fun Float32Buffer(vararg floats: Float): Float32Buffer = Float32Buffer(floats)
 
 /**
  * Returns a new [FloatArray] containing all the elements of this [Buffer].
  */
 public fun Buffer<Float>.toFloatArray(): FloatArray = when (this) {
-    is FloatBuffer -> array.copyOf()
+    is Float32Buffer -> array.copyOf()
     else -> FloatArray(size, ::get)
 }
 
 /**
- * Returns [FloatBuffer] over this array.
+ * Returns [Float32Buffer] over this array.
  *
  * @receiver the array.
  * @return the new buffer.
  */
-public fun FloatArray.asBuffer(): FloatBuffer = FloatBuffer(this)
+public fun FloatArray.asBuffer(): Float32Buffer = Float32Buffer(this)

kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/Float64Buffer.kt

@@ -14,7 +14,7 @@ import kotlin.jvm.JvmInline
  * @property array the underlying array.
  */
 @JvmInline
-public value class DoubleBuffer(public val array: DoubleArray) : PrimitiveBuffer<Double> {
+public value class Float64Buffer(public val array: DoubleArray) : PrimitiveBuffer<Double> {
     override val size: Int get() = array.size
 
     override operator fun get(index: Int): Double = array[index]
@@ -25,57 +25,59 @@ public value class DoubleBuffer(public val array: DoubleArray) : PrimitiveBuffer
 
     override operator fun iterator(): DoubleIterator = array.iterator()
 
-    override fun copy(): DoubleBuffer = DoubleBuffer(array.copyOf())
+    override fun copy(): Float64Buffer = Float64Buffer(array.copyOf())
 
     override fun toString(): String = Buffer.toString(this)
 
     public companion object {
-        public fun zero(size: Int): DoubleBuffer = DoubleArray(size).asBuffer()
+        public fun zero(size: Int): Float64Buffer = DoubleArray(size).asBuffer()
     }
 }
 
+public typealias DoubleBuffer = Float64Buffer
+
 /**
- * Creates a new [DoubleBuffer] with the specified [size], where each element is calculated by calling the specified
+ * Creates a new [Float64Buffer] with the specified [size], where each element is calculated by calling the specified
  * [init] function.
  *
  * The function [init] is called for each array element sequentially starting from the first one.
  * It should return the value for a buffer element given its index.
  */
-public inline fun DoubleBuffer(size: Int, init: (Int) -> Double): DoubleBuffer =
+public inline fun Float64Buffer(size: Int, init: (Int) -> Double): Float64Buffer =
-    DoubleBuffer(DoubleArray(size) { init(it) })
+    Float64Buffer(DoubleArray(size) { init(it) })
 
 /**
- * Returns a new [DoubleBuffer] of given elements.
+ * Returns a new [Float64Buffer] of given elements.
  */
-public fun DoubleBuffer(vararg doubles: Double): DoubleBuffer = DoubleBuffer(doubles)
+public fun Float64Buffer(vararg doubles: Double): Float64Buffer = Float64Buffer(doubles)
 
 /**
  * Returns a new [DoubleArray] containing all the elements of this [Buffer].
  */
 public fun Buffer<Double>.toDoubleArray(): DoubleArray = when (this) {
-    is DoubleBuffer -> array
+    is Float64Buffer -> array
     else -> DoubleArray(size, ::get)
 }
 
 /**
- * Represent this buffer as [DoubleBuffer]. Does not guarantee that changes in the original buffer are reflected on this buffer.
+ * Represent this buffer as [Float64Buffer]. Does not guarantee that changes in the original buffer are reflected on this buffer.
  */
-public fun Buffer<Double>.toDoubleBuffer(): DoubleBuffer = when (this) {
+public fun Buffer<Double>.toFloat64Buffer(): Float64Buffer = when (this) {
-    is DoubleBuffer -> this
+    is Float64Buffer -> this
     else -> DoubleArray(size, ::get).asBuffer()
 }
 
 /**
- * Returns [DoubleBuffer] over this array.
+ * Returns [Float64Buffer] over this array.
  *
  * @receiver the array.
  * @return the new buffer.
  */
-public fun DoubleArray.asBuffer(): DoubleBuffer = DoubleBuffer(this)
+public fun DoubleArray.asBuffer(): Float64Buffer = Float64Buffer(this)
 
 
-public fun interface DoubleBufferTransform : BufferTransform<Double, Double> {
+public fun interface Float64BufferTransform : BufferTransform<Double, Double> {
-    public fun transform(arg: DoubleBuffer): DoubleBuffer
+    public fun transform(arg: Float64Buffer): Float64Buffer
 
-    override fun transform(arg: Buffer<Double>): DoubleBuffer = arg.toDoubleBuffer()
+    override fun transform(arg: Buffer<Double>): Float64Buffer = arg.toFloat64Buffer()
 }

kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/Int16Buffer.kt

@@ -13,7 +13,7 @@ import kotlin.jvm.JvmInline
  * @property array the underlying array.
  */
 @JvmInline
-public value class ShortBuffer(public val array: ShortArray) : MutableBuffer<Short> {
+public value class Int16Buffer(public val array: ShortArray) : MutableBuffer<Short> {
     override val size: Int get() = array.size
 
     override operator fun get(index: Int): Short = array[index]
@@ -23,35 +23,37 @@ public value class ShortBuffer(public val array: ShortArray) : MutableBuffer<Sho
     }
 
     override operator fun iterator(): ShortIterator = array.iterator()
-    override fun copy(): MutableBuffer<Short> = ShortBuffer(array.copyOf())
+    override fun copy(): MutableBuffer<Short> = Int16Buffer(array.copyOf())
 }
 
+public typealias ShortBuffer = Int16Buffer
+
 /**
- * Creates a new [ShortBuffer] with the specified [size], where each element is calculated by calling the specified
+ * Creates a new [Int16Buffer] with the specified [size], where each element is calculated by calling the specified
  * [init] function.
  *
  * The function [init] is called for each array element sequentially starting from the first one.
  * It should return the value for a buffer element given its index.
  */
-public inline fun ShortBuffer(size: Int, init: (Int) -> Short): ShortBuffer = ShortBuffer(ShortArray(size) { init(it) })
+public inline fun Int16Buffer(size: Int, init: (Int) -> Short): Int16Buffer = Int16Buffer(ShortArray(size) { init(it) })
 
 /**
- * Returns a new [ShortBuffer] of given elements.
+ * Returns a new [Int16Buffer] of given elements.
  */
-public fun ShortBuffer(vararg shorts: Short): ShortBuffer = ShortBuffer(shorts)
+public fun Int16Buffer(vararg shorts: Short): Int16Buffer = Int16Buffer(shorts)
 
 /**
  * Returns a new [ShortArray] containing all the elements of this [Buffer].
  */
 public fun Buffer<Short>.toShortArray(): ShortArray = when (this) {
-    is ShortBuffer -> array.copyOf()
+    is Int16Buffer -> array.copyOf()
     else -> ShortArray(size, ::get)
 }
 
 /**
- * Returns [ShortBuffer] over this array.
+ * Returns [Int16Buffer] over this array.
  *
  * @receiver the array.
  * @return the new buffer.
  */
-public fun ShortArray.asBuffer(): ShortBuffer = ShortBuffer(this)
+public fun ShortArray.asBuffer(): Int16Buffer = Int16Buffer(this)

kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/Int32Buffer.kt

@@ -13,7 +13,7 @@ import kotlin.jvm.JvmInline
  * @property array the underlying array.
  */
 @JvmInline
-public value class IntBuffer(public val array: IntArray) : PrimitiveBuffer<Int> {
+public value class Int32Buffer(public val array: IntArray) : PrimitiveBuffer<Int> {
     override val size: Int get() = array.size
 
     override operator fun get(index: Int): Int = array[index]
@@ -24,35 +24,37 @@ public value class IntBuffer(public val array: IntArray) : PrimitiveBuffer<Int>
 
     override operator fun iterator(): IntIterator = array.iterator()
 
-    override fun copy(): IntBuffer = IntBuffer(array.copyOf())
+    override fun copy(): Int32Buffer = Int32Buffer(array.copyOf())
 }
 
+public typealias IntBuffer = Int32Buffer
+
 /**
- * Creates a new [IntBuffer] with the specified [size], where each element is calculated by calling the specified
+ * Creates a new [Int32Buffer] with the specified [size], where each element is calculated by calling the specified
  * [init] function.
  *
  * The function [init] is called for each array element sequentially starting from the first one.
  * It should return the value for a buffer element given its index.
  */
-public inline fun IntBuffer(size: Int, init: (Int) -> Int): IntBuffer = IntBuffer(IntArray(size) { init(it) })
+public inline fun Int32Buffer(size: Int, init: (Int) -> Int): Int32Buffer = Int32Buffer(IntArray(size) { init(it) })
 
 /**
- * Returns a new [IntBuffer] of given elements.
+ * Returns a new [Int32Buffer] of given elements.
  */
-public fun IntBuffer(vararg ints: Int): IntBuffer = IntBuffer(ints)
+public fun Int32Buffer(vararg ints: Int): Int32Buffer = Int32Buffer(ints)
 
 /**
  * Returns a new [IntArray] containing all the elements of this [Buffer].
  */
 public fun Buffer<Int>.toIntArray(): IntArray = when (this) {
-    is IntBuffer -> array.copyOf()
+    is Int32Buffer -> array.copyOf()
     else -> IntArray(size, ::get)
 }
 
 /**
- * Returns [IntBuffer] over this array.
+ * Returns [Int32Buffer] over this array.
  *
  * @receiver the array.
  * @return the new buffer.
  */
-public fun IntArray.asBuffer(): IntBuffer = IntBuffer(this)
+public fun IntArray.asBuffer(): Int32Buffer = Int32Buffer(this)

kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/Int64Buffer.kt

@@ -13,7 +13,7 @@ import kotlin.jvm.JvmInline
  * @property array the underlying array.
  */
 @JvmInline
-public value class LongBuffer(public val array: LongArray) : PrimitiveBuffer<Long> {
+public value class Int64Buffer(public val array: LongArray) : PrimitiveBuffer<Long> {
     override val size: Int get() = array.size
 
     override operator fun get(index: Int): Long = array[index]
@@ -25,35 +25,37 @@ public value class LongBuffer(public val array: LongArray) : PrimitiveBuffer<Lon
     override operator fun iterator(): LongIterator = array.iterator()
 
     override fun copy(): MutableBuffer<Long> =
-        LongBuffer(array.copyOf())
+        Int64Buffer(array.copyOf())
 }
 
+public typealias LongBuffer = Int64Buffer
+
 /**
- * Creates a new [LongBuffer] with the specified [size], where each element is calculated by calling the specified
+ * Creates a new [Int64Buffer] with the specified [size], where each element is calculated by calling the specified
  * [init] function.
  *
  * The function [init] is called for each array element sequentially starting from the first one.
  * It should return the value for a buffer element given its index.
  */
-public inline fun LongBuffer(size: Int, init: (Int) -> Long): LongBuffer = LongBuffer(LongArray(size) { init(it) })
+public inline fun Int64Buffer(size: Int, init: (Int) -> Long): Int64Buffer = Int64Buffer(LongArray(size) { init(it) })
 
 /**
- * Returns a new [LongBuffer] of given elements.
+ * Returns a new [Int64Buffer] of given elements.
  */
-public fun LongBuffer(vararg longs: Long): LongBuffer = LongBuffer(longs)
+public fun Int64Buffer(vararg longs: Long): Int64Buffer = Int64Buffer(longs)
 
 /**
  * Returns a new [LongArray] containing all the elements of this [Buffer].
  */
 public fun Buffer<Long>.toLongArray(): LongArray = when (this) {
-    is LongBuffer -> array.copyOf()
+    is Int64Buffer -> array.copyOf()
     else -> LongArray(size, ::get)
 }
 
 /**
- * Returns [LongBuffer] over this array.
+ * Returns [Int64Buffer] over this array.
  *
  * @receiver the array.
  * @return the new buffer.
  */
-public fun LongArray.asBuffer(): LongBuffer = LongBuffer(this)
+public fun LongArray.asBuffer(): Int64Buffer = Int64Buffer(this)

kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/Int8Buffer.kt

@@ -13,7 +13,7 @@ import kotlin.jvm.JvmInline
  * @property array the underlying array.
  */
 @JvmInline
-public value class ByteBuffer(public val array: ByteArray) : MutableBuffer<Byte> {
+public value class Int8Buffer(public val array: ByteArray) : MutableBuffer<Byte> {
     override val size: Int get() = array.size
 
     override operator fun get(index: Int): Byte = array[index]
@@ -23,35 +23,35 @@ public value class ByteBuffer(public val array: ByteArray) : MutableBuffer<Byte>
     }
 
     override operator fun iterator(): ByteIterator = array.iterator()
-    override fun copy(): MutableBuffer<Byte> = ByteBuffer(array.copyOf())
+    override fun copy(): MutableBuffer<Byte> = Int8Buffer(array.copyOf())
 }
 
 /**
- * Creates a new [ByteBuffer] with the specified [size], where each element is calculated by calling the specified
+ * Creates a new [Int8Buffer] with the specified [size], where each element is calculated by calling the specified
  * [init] function.
  *
  * The function [init] is called for each array element sequentially starting from the first one.
  * It should return the value for a buffer element given its index.
  */
-public inline fun ByteBuffer(size: Int, init: (Int) -> Byte): ByteBuffer = ByteBuffer(ByteArray(size) { init(it) })
+public inline fun Int8Buffer(size: Int, init: (Int) -> Byte): Int8Buffer = Int8Buffer(ByteArray(size) { init(it) })
 
 /**
- * Returns a new [ByteBuffer] of given elements.
+ * Returns a new [Int8Buffer] of given elements.
  */
-public fun ByteBuffer(vararg bytes: Byte): ByteBuffer = ByteBuffer(bytes)
+public fun Int8Buffer(vararg bytes: Byte): Int8Buffer = Int8Buffer(bytes)
 
 /**
  * Returns a new [ByteArray] containing all the elements of this [Buffer].
  */
 public fun Buffer<Byte>.toByteArray(): ByteArray = when (this) {
-    is ByteBuffer -> array.copyOf()
+    is Int8Buffer -> array.copyOf()
     else -> ByteArray(size, ::get)
 }
 
 /**
- * Returns [ByteBuffer] over this array.
+ * Returns [Int8Buffer] over this array.
  *
  * @receiver the array.
  * @return the new buffer.
  */
-public fun ByteArray.asBuffer(): ByteBuffer = ByteBuffer(this)
+public fun ByteArray.asBuffer(): Int8Buffer = Int8Buffer(this)

kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/MutableBuffer.kt

@@ -25,40 +25,40 @@ public interface MutableBuffer<T> : Buffer<T> {
 
     public companion object {
         /**
-         * Creates a [DoubleBuffer] with the specified [size], where each element is calculated by calling the specified
+         * Creates a [Float64Buffer] with the specified [size], where each element is calculated by calling the specified
          * [initializer] function.
          */
-        public inline fun double(size: Int, initializer: (Int) -> Double): DoubleBuffer =
+        public inline fun double(size: Int, initializer: (Int) -> Double): Float64Buffer =
-            DoubleBuffer(size, initializer)
+            Float64Buffer(size, initializer)
 
         /**
-         * Creates a [ShortBuffer] with the specified [size], where each element is calculated by calling the specified
+         * Creates a [Int16Buffer] with the specified [size], where each element is calculated by calling the specified
          * [initializer] function.
          */
-        public inline fun short(size: Int, initializer: (Int) -> Short): ShortBuffer =
+        public inline fun short(size: Int, initializer: (Int) -> Short): Int16Buffer =
-            ShortBuffer(size, initializer)
+            Int16Buffer(size, initializer)
 
         /**
-         * Creates a [IntBuffer] with the specified [size], where each element is calculated by calling the specified
+         * Creates a [Int32Buffer] with the specified [size], where each element is calculated by calling the specified
          * [initializer] function.
          */
-        public inline fun int(size: Int, initializer: (Int) -> Int): IntBuffer =
+        public inline fun int(size: Int, initializer: (Int) -> Int): Int32Buffer =
-            IntBuffer(size, initializer)
+            Int32Buffer(size, initializer)
 
         /**
-         * Creates a [LongBuffer] with the specified [size], where each element is calculated by calling the specified
+         * Creates a [Int64Buffer] with the specified [size], where each element is calculated by calling the specified
          * [initializer] function.
          */
-        public inline fun long(size: Int, initializer: (Int) -> Long): LongBuffer =
+        public inline fun long(size: Int, initializer: (Int) -> Long): Int64Buffer =
-            LongBuffer(size, initializer)
+            Int64Buffer(size, initializer)
 
 
         /**
-         * Creates a [FloatBuffer] with the specified [size], where each element is calculated by calling the specified
+         * Creates a [Float32Buffer] with the specified [size], where each element is calculated by calling the specified
          * [initializer] function.
          */
-        public inline fun float(size: Int, initializer: (Int) -> Float): FloatBuffer =
+        public inline fun float(size: Int, initializer: (Int) -> Float): Float32Buffer =
-            FloatBuffer(size, initializer)
+            Float32Buffer(size, initializer)
 
 
         /**
@@ -69,7 +69,7 @@ public interface MutableBuffer<T> : Buffer<T> {
 
         /**
          * Creates a [MutableBuffer] of given [type]. If the type is primitive, specialized buffers are used
-         * ([IntBuffer], [DoubleBuffer], etc.), [ListBuffer] is returned otherwise.
+         * ([Int32Buffer], [Float64Buffer], etc.), [ListBuffer] is returned otherwise.
          *
          * The [size] is specified, and each element is calculated by calling the specified [initializer] function.
          */
@@ -86,7 +86,7 @@ public interface MutableBuffer<T> : Buffer<T> {
 
         /**
          * Creates a [MutableBuffer] of given type [T]. If the type is primitive, specialized buffers are used
-         * ([IntBuffer], [DoubleBuffer], etc.), [ListBuffer] is returned otherwise.
+         * ([Int32Buffer], [Float64Buffer], etc.), [ListBuffer] is returned otherwise.
          *
          * The [size] is specified, and each element is calculated by calling the specified [initializer] function.
          */

kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/bufferPrimitiveAccess.kt

@@ -13,7 +13,7 @@ public fun Buffer<Double>.getDouble(index: Int): Double = if (this is BufferView
     } else {
         get(index)
     }
-} else if (this is DoubleBuffer) {
+} else if (this is Float64Buffer) {
     array[index]
 } else {
     get(index)
@@ -30,7 +30,7 @@ public fun Buffer<Int>.getInt(index: Int): Int = if (this is BufferView) {
     } else {
         get(index)
     }
-} else if (this is IntBuffer) {
+} else if (this is Int32Buffer) {
     array[index]
 } else {
     get(index)

kmath-core/src/commonTest/kotlin/space/kscience/kmath/misc/PermSortTest.kt

@@ -7,7 +7,7 @@ package space.kscience.kmath.misc
 
 import space.kscience.kmath.UnstableKMathAPI
 import space.kscience.kmath.misc.PermSortTest.Platform.*
-import space.kscience.kmath.structures.IntBuffer
+import space.kscience.kmath.structures.Int32Buffer
 import space.kscience.kmath.structures.asBuffer
 import kotlin.random.Random
 import kotlin.test.Test
@@ -29,7 +29,7 @@ class PermSortTest {
      */
     @Test
     fun testOnEmptyBuffer() {
-        val emptyBuffer = IntBuffer(0) {it}
+        val emptyBuffer = Int32Buffer(0) {it}
         var permutations = emptyBuffer.indicesSorted()
         assertTrue(permutations.isEmpty(), "permutation on an empty buffer should return an empty result")
         permutations = emptyBuffer.indicesSortedDescending()
@@ -100,5 +100,5 @@ class PermSortTest {
         }
     }
 
-    private fun Random.buffer(size : Int) = IntBuffer(size) { nextInt() }
+    private fun Random.buffer(size : Int) = Int32Buffer(size) { nextInt() }
 }

kmath-coroutines/src/commonMain/kotlin/space/kscience/kmath/chains/BlockingDoubleChain.kt

@@ -5,7 +5,7 @@
 
 package space.kscience.kmath.chains
 
-import space.kscience.kmath.structures.DoubleBuffer
+import space.kscience.kmath.structures.Float64Buffer
 
 /**
  * Chunked, specialized chain for double values, which supports blocking [nextBlocking] operation
@@ -15,7 +15,7 @@ public interface BlockingDoubleChain : BlockingBufferChain<Double> {
     /**
      * Returns an [DoubleArray] chunk of [size] values of [next].
      */
-    override fun nextBufferBlocking(size: Int): DoubleBuffer
+    override fun nextBufferBlocking(size: Int): Float64Buffer
 
     override suspend fun fork(): BlockingDoubleChain
 
@@ -23,9 +23,9 @@ public interface BlockingDoubleChain : BlockingBufferChain<Double> {
 }
 
 public fun BlockingDoubleChain.map(transform: (Double) -> Double): BlockingDoubleChain = object : BlockingDoubleChain {
-    override fun nextBufferBlocking(size: Int): DoubleBuffer {
+    override fun nextBufferBlocking(size: Int): Float64Buffer {
         val block = this@map.nextBufferBlocking(size)
-        return DoubleBuffer(size) { transform(block[it]) }
+        return Float64Buffer(size) { transform(block[it]) }
     }
 
     override suspend fun fork(): BlockingDoubleChain = this@map.fork().map(transform)

kmath-coroutines/src/commonMain/kotlin/space/kscience/kmath/chains/BlockingIntChain.kt

@@ -5,13 +5,13 @@
 
 package space.kscience.kmath.chains
 
-import space.kscience.kmath.structures.IntBuffer
+import space.kscience.kmath.structures.Int32Buffer
 
 /**
  * Performance optimized chain for integer values
  */
 public interface BlockingIntChain : BlockingBufferChain<Int> {
-    override fun nextBufferBlocking(size: Int): IntBuffer
+    override fun nextBufferBlocking(size: Int): Int32Buffer
 
     override suspend fun fork(): BlockingIntChain
 }

kmath-coroutines/src/commonMain/kotlin/space/kscience/kmath/streaming/BufferFlow.kt

@@ -16,7 +16,7 @@ import kotlinx.coroutines.flow.flow
 import space.kscience.kmath.chains.BlockingDoubleChain
 import space.kscience.kmath.structures.Buffer
 import space.kscience.kmath.structures.BufferFactory
-import space.kscience.kmath.structures.DoubleBuffer
+import space.kscience.kmath.structures.Float64Buffer
 
 /**
  * Create a [Flow] from buffer
@@ -55,7 +55,7 @@ public fun <T> Flow<T>.chunked(bufferSize: Int, bufferFactory: BufferFactory<T>)
 /**
  * Specialized flow chunker for real buffer
  */
-public fun Flow<Double>.chunked(bufferSize: Int): Flow<DoubleBuffer> = flow {
+public fun Flow<Double>.chunked(bufferSize: Int): Flow<Float64Buffer> = flow {
     require(bufferSize > 0) { "Resulting chunk size must be more than zero" }
 
     if (this@chunked is BlockingDoubleChain) {
@@ -70,13 +70,13 @@ public fun Flow<Double>.chunked(bufferSize: Int): Flow<DoubleBuffer> = flow {
             counter++
 
             if (counter == bufferSize) {
-                val buffer = DoubleBuffer(array)
+                val buffer = Float64Buffer(array)
                 emit(buffer)
                 counter = 0
             }
         }
 
-        if (counter > 0) emit(DoubleBuffer(counter) { array[it] })
+        if (counter > 0) emit(Float64Buffer(counter) { array[it] })
     }
 }
 

kmath-for-real/src/commonMain/kotlin/space/kscience/kmath/real/DoubleVector.kt

@@ -7,7 +7,7 @@ package space.kscience.kmath.real
 
 import space.kscience.kmath.UnstableKMathAPI
 import space.kscience.kmath.linear.Point
-import space.kscience.kmath.operations.DoubleL2Norm
+import space.kscience.kmath.operations.Float64L2Norm
 import space.kscience.kmath.structures.Buffer
 import space.kscience.kmath.structures.MutableBuffer.Companion.double
 import space.kscience.kmath.structures.asBuffer
@@ -103,4 +103,4 @@ public fun DoubleVector.sum(): Double {
     return res
 }
 
-public val DoubleVector.norm: Double get() = DoubleL2Norm.norm(this)
+public val DoubleVector.norm: Double get() = Float64L2Norm.norm(this)

kmath-for-real/src/commonMain/kotlin/space/kscience/kmath/real/RealMatrix.kt

@@ -15,7 +15,7 @@ import space.kscience.kmath.operations.Float64Field
 import space.kscience.kmath.operations.algebra
 import space.kscience.kmath.operations.asIterable
 import space.kscience.kmath.structures.Buffer
-import space.kscience.kmath.structures.DoubleBuffer
+import space.kscience.kmath.structures.Float64Buffer
 import kotlin.math.pow
 
 /*
@@ -130,19 +130,19 @@ public fun RealMatrix.extractColumns(columnRange: IntRange): RealMatrix =
 public fun RealMatrix.extractColumn(columnIndex: Int): RealMatrix =
     extractColumns(columnIndex..columnIndex)
 
-public fun RealMatrix.sumByColumn(): DoubleBuffer = DoubleBuffer(colNum) { j ->
+public fun RealMatrix.sumByColumn(): Float64Buffer = Float64Buffer(colNum) { j ->
     columns[j].sum()
 }
 
-public fun RealMatrix.minByColumn(): DoubleBuffer = DoubleBuffer(colNum) { j ->
+public fun RealMatrix.minByColumn(): Float64Buffer = Float64Buffer(colNum) { j ->
     columns[j].asIterable().minOrNull() ?: error("Cannot produce min on empty column")
 }
 
-public fun RealMatrix.maxByColumn(): DoubleBuffer = DoubleBuffer(colNum) { j ->
+public fun RealMatrix.maxByColumn(): Float64Buffer = Float64Buffer(colNum) { j ->
     columns[j].asIterable().maxOrNull() ?: error("Cannot produce min on empty column")
 }
 
-public fun RealMatrix.averageByColumn(): DoubleBuffer = DoubleBuffer(colNum) { j ->
+public fun RealMatrix.averageByColumn(): Float64Buffer = Float64Buffer(colNum) { j ->
     columns[j].asIterable().average()
 }
 

kmath-for-real/src/commonMain/kotlin/space/kscience/kmath/real/grids.kt

@@ -7,7 +7,7 @@ package space.kscience.kmath.real
 
 import space.kscience.kmath.UnstableKMathAPI
 import space.kscience.kmath.structures.Buffer
-import space.kscience.kmath.structures.DoubleBuffer
+import space.kscience.kmath.structures.Float64Buffer
 import kotlin.math.floor
 
 public val ClosedFloatingPointRange<Double>.length: Double get() = endInclusive - start
@@ -16,30 +16,30 @@ public val ClosedFloatingPointRange<Double>.length: Double get() = endInclusive
  * Create a Buffer-based grid with equally distributed [numberOfPoints] points. The range could be increasing or  decreasing.
  * If range has a zero size, then the buffer consisting of [numberOfPoints] equal values is returned.
  */
-public fun Buffer.Companion.fromRange(range: ClosedFloatingPointRange<Double>, numberOfPoints: Int): DoubleBuffer {
+public fun Buffer.Companion.fromRange(range: ClosedFloatingPointRange<Double>, numberOfPoints: Int): Float64Buffer {
     require(numberOfPoints >= 2) { "Number of points in grid must be more than 1" }
     val normalizedRange = when {
         range.endInclusive > range.start -> range
         range.endInclusive < range.start -> range.endInclusive..range.start
-        else -> return DoubleBuffer(numberOfPoints) { range.start }
+        else -> return Float64Buffer(numberOfPoints) { range.start }
     }
     val step = normalizedRange.length / (numberOfPoints - 1)
-    return DoubleBuffer(numberOfPoints) { normalizedRange.start + step * it }
+    return Float64Buffer(numberOfPoints) { normalizedRange.start + step * it }
 }
 
 /**
  * Create a Buffer-based grid with equally distributed points with a fixed [step]. The range could be increasing or  decreasing.
  * If the step is larger than the range size, single point is returned.
  */
-public fun Buffer.Companion.withFixedStep(range: ClosedFloatingPointRange<Double>, step: Double): DoubleBuffer {
+public fun Buffer.Companion.withFixedStep(range: ClosedFloatingPointRange<Double>, step: Double): Float64Buffer {
     require(step > 0) { "The grid step must be positive" }
     val normalizedRange = when {
         range.endInclusive > range.start -> range
         range.endInclusive < range.start -> range.endInclusive..range.start
-        else -> return DoubleBuffer(range.start)
+        else -> return Float64Buffer(range.start)
     }
     val numberOfPoints = floor(normalizedRange.length / step).toInt() + 1
-    return DoubleBuffer(numberOfPoints) { normalizedRange.start + step * it  }
+    return Float64Buffer(numberOfPoints) { normalizedRange.start + step * it  }
 }
 
 /**
@@ -51,4 +51,4 @@ public fun Buffer.Companion.withFixedStep(range: ClosedFloatingPointRange<Double
  * If step is negative, the same goes from upper boundary downwards
  */
 @UnstableKMathAPI
-public infix fun ClosedFloatingPointRange<Double>.step(step: Double): DoubleBuffer = Buffer.withFixedStep(this, step)
+public infix fun ClosedFloatingPointRange<Double>.step(step: Double): Float64Buffer = Buffer.withFixedStep(this, step)

kmath-for-real/src/commonMain/kotlin/space/kscience/kmath/real/realND.kt

@@ -7,14 +7,14 @@ package space.kscience.kmath.real
 
 import space.kscience.kmath.nd.BufferND
 import space.kscience.kmath.operations.Float64Field
-import space.kscience.kmath.structures.DoubleBuffer
+import space.kscience.kmath.structures.Float64Buffer
 
 /**
  * Map one [BufferND] using function without indices.
  */
 public inline fun BufferND<Double>.mapInline(crossinline transform: Float64Field.(Double) -> Double): BufferND<Double> {
     val array = DoubleArray(indices.linearSize) { offset -> Float64Field.transform(buffer[offset]) }
-    return BufferND(indices, DoubleBuffer(array))
+    return BufferND(indices, Float64Buffer(array))
 }
 
 /**

kmath-for-real/src/commonTest/kotlin/space/kscience/kmath/real/DoubleVectorTest.kt

@@ -9,30 +9,30 @@ import space.kscience.kmath.linear.asMatrix
 import space.kscience.kmath.linear.linearSpace
 import space.kscience.kmath.linear.transpose
 import space.kscience.kmath.operations.algebra
-import space.kscience.kmath.structures.DoubleBuffer
+import space.kscience.kmath.structures.Float64Buffer
 import kotlin.test.Test
 import kotlin.test.assertEquals
 
 internal class DoubleVectorTest {
     @Test
     fun testSum() {
-        val vector1 = DoubleBuffer(5) { it.toDouble() }
+        val vector1 = Float64Buffer(5) { it.toDouble() }
-        val vector2 = DoubleBuffer(5) { 5 - it.toDouble() }
+        val vector2 = Float64Buffer(5) { 5 - it.toDouble() }
         val sum = vector1 + vector2
         assertEquals(5.0, sum[2])
     }
 
     @Test
     fun testVectorToMatrix() {
-        val vector = DoubleBuffer(5) { it.toDouble() }
+        val vector = Float64Buffer(5) { it.toDouble() }
         val matrix = vector.asMatrix()
         assertEquals(4.0, matrix[4, 0])
     }
 
     @Test
     fun testDot() = Double.algebra.linearSpace.run {
-        val vector1 = DoubleBuffer(5) { it.toDouble() }
+        val vector1 = Float64Buffer(5) { it.toDouble() }
-        val vector2 = DoubleBuffer(5) { 5 - it.toDouble() }
+        val vector2 = Float64Buffer(5) { 5 - it.toDouble() }
         val matrix1 = vector1.asMatrix()
         val matrix2 = vector2.asMatrix().transpose()
         val product = matrix1 dot matrix2

kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/GaussIntegratorRuleFactory.kt

@@ -7,7 +7,7 @@ package space.kscience.kmath.integration
 
 import space.kscience.kmath.operations.mapToBuffer
 import space.kscience.kmath.structures.Buffer
-import space.kscience.kmath.structures.DoubleBuffer
+import space.kscience.kmath.structures.Float64Buffer
 import space.kscience.kmath.structures.asBuffer
 import kotlin.math.ulp
 import kotlin.native.concurrent.ThreadLocal
@@ -32,11 +32,11 @@ public fun GaussIntegratorRuleFactory.build(
     val normalized: Pair<Buffer<Double>, Buffer<Double>> = build(numPoints)
     val length = range.endInclusive - range.start
 
-    val points = normalized.first.mapToBuffer(::DoubleBuffer) {
+    val points = normalized.first.mapToBuffer(::Float64Buffer) {
         range.start + length / 2 + length / 2 * it
     }
 
-    val weights = normalized.second.mapToBuffer(::DoubleBuffer) {
+    val weights = normalized.second.mapToBuffer(::Float64Buffer) {
         it * length / 2
     }
 
@@ -64,8 +64,8 @@ public object GaussLegendreRuleFactory : GaussIntegratorRuleFactory {
         if (numPoints == 1) {
             // Break recursion.
             return Pair(
-                DoubleBuffer(0.0),
+                Float64Buffer(0.0),
-                DoubleBuffer(0.0)
+                Float64Buffer(0.0)
             )
         }
 

kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/SplineIntegrator.kt

@@ -14,7 +14,7 @@ import space.kscience.kmath.interpolation.SplineInterpolator
 import space.kscience.kmath.interpolation.interpolatePolynomials
 import space.kscience.kmath.operations.*
 import space.kscience.kmath.structures.Buffer
-import space.kscience.kmath.structures.DoubleBuffer
+import space.kscience.kmath.structures.Float64Buffer
 import space.kscience.kmath.structures.MutableBufferFactory
 
 /**
@@ -62,7 +62,7 @@ public class SplineIntegrator<T : Comparable<T>>(
         val nodes: Buffer<Double> = integrand.getFeature<UnivariateIntegrationNodes>()?.nodes ?: run {
             val numPoints = integrand.getFeature<IntegrandMaxCalls>()?.maxCalls ?: 100
             val step = (range.endInclusive - range.start) / (numPoints - 1)
-            DoubleBuffer(numPoints) { i -> range.start + i * step }
+            Float64Buffer(numPoints) { i -> range.start + i * step }
         }
 
         val values = nodes.mapToBuffer(bufferFactory) { integrand.function(it) }
@@ -85,15 +85,15 @@ public class SplineIntegrator<T : Comparable<T>>(
 public object DoubleSplineIntegrator : UnivariateIntegrator<Double> {
     override fun process(integrand: UnivariateIntegrand<Double>): UnivariateIntegrand<Double> {
         val range = integrand.getFeature<IntegrationRange>()?.range ?: 0.0..1.0
-        val interpolator: PolynomialInterpolator<Double> = SplineInterpolator(Float64Field, ::DoubleBuffer)
+        val interpolator: PolynomialInterpolator<Double> = SplineInterpolator(Float64Field, ::Float64Buffer)
 
         val nodes: Buffer<Double> = integrand.getFeature<UnivariateIntegrationNodes>()?.nodes ?: run {
             val numPoints = integrand.getFeature<IntegrandMaxCalls>()?.maxCalls ?: 100
             val step = (range.endInclusive - range.start) / (numPoints - 1)
-            DoubleBuffer(numPoints) { i -> range.start + i * step }
+            Float64Buffer(numPoints) { i -> range.start + i * step }
         }
 
-        val values = nodes.mapToBuffer(::DoubleBuffer) { integrand.function(it) }
+        val values = nodes.mapToBuffer(::Float64Buffer) { integrand.function(it) }
         val polynomials = interpolator.interpolatePolynomials(nodes, values)
         val res = polynomials.integrate(Float64Field, range)
         return integrand + IntegrandValue(res) + IntegrandCallsPerformed(integrand.calls + nodes.size)

kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/UnivariateIntegrand.kt

@@ -8,7 +8,7 @@ package space.kscience.kmath.integration
 import space.kscience.kmath.UnstableKMathAPI
 import space.kscience.kmath.misc.FeatureSet
 import space.kscience.kmath.structures.Buffer
-import space.kscience.kmath.structures.DoubleBuffer
+import space.kscience.kmath.structures.Float64Buffer
 
 public class UnivariateIntegrand<T> internal constructor(
     override val features: FeatureSet<IntegrandFeature>,
@@ -46,7 +46,7 @@ public class UnivariateIntegrandRanges(public val ranges: List<Pair<ClosedRange<
 }
 
 public class UnivariateIntegrationNodes(public val nodes: Buffer<Double>) : IntegrandFeature {
-    public constructor(vararg nodes: Double) : this(DoubleBuffer(nodes))
+    public constructor(vararg nodes: Double) : this(Float64Buffer(nodes))
 
     override fun toString(): String = "UnivariateNodes($nodes)"
 }

kmath-functions/src/commonMain/kotlin/space/kscience/kmath/interpolation/SplineInterpolator.kt

@@ -12,7 +12,7 @@ import space.kscience.kmath.functions.Polynomial
 import space.kscience.kmath.operations.Field
 import space.kscience.kmath.operations.Float64Field
 import space.kscience.kmath.operations.invoke
-import space.kscience.kmath.structures.DoubleBuffer
+import space.kscience.kmath.structures.Float64Buffer
 import space.kscience.kmath.structures.MutableBufferFactory
 
 /**
@@ -80,4 +80,4 @@ public fun <T : Comparable<T>> Field<T>.splineInterpolator(
 ): SplineInterpolator<T> = SplineInterpolator(this, bufferFactory)
 
 public val Float64Field.splineInterpolator: SplineInterpolator<Double>
-    get() = SplineInterpolator(this, ::DoubleBuffer)
+    get() = SplineInterpolator(this, ::Float64Buffer)

kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/RotationTest.kt

@@ -7,7 +7,7 @@ package space.kscience.kmath.geometry
 
 import space.kscience.kmath.complex.Quaternion
 import space.kscience.kmath.complex.normalized
-import space.kscience.kmath.structures.DoubleBuffer
+import space.kscience.kmath.structures.Float64Buffer
 import space.kscience.kmath.testutils.assertBufferEquals
 import kotlin.test.Test
 
@@ -38,15 +38,15 @@ class RotationTest {
     fun fromRotation() {
         val q = Quaternion.fromRotation(0.3.radians, Euclidean3DSpace.vector(1.0, 1.0, 1.0))
 
-        assertBufferEquals(DoubleBuffer(0.9887711, 0.0862781, 0.0862781, 0.0862781), q)
+        assertBufferEquals(Float64Buffer(0.9887711, 0.0862781, 0.0862781, 0.0862781), q)
     }
 
     @Test
     fun fromEuler() {
         val q = Quaternion.fromEuler(0.1.radians, 0.2.radians, 0.3.radians, RotationOrder.ZXY)
-        assertBufferEquals(DoubleBuffer(0.9818562, 0.0342708, 0.1060205, 0.1534393), q)
+        assertBufferEquals(Float64Buffer(0.9818562, 0.0342708, 0.1060205, 0.1534393), q)
 
         val q1 = Quaternion.fromEuler(0.1.radians, 0.2.radians, 0.3.radians, RotationOrder.XYZ)
-        assertBufferEquals(DoubleBuffer(0.9818562, 0.0640713, 0.0911575, 0.1534393), q1)
+        assertBufferEquals(Float64Buffer(0.9818562, 0.0640713, 0.0911575, 0.1534393), q1)
     }
 }

kmath-histograms/src/commonMain/kotlin/space/kscience/kmath/histogram/Histogram.kt

@@ -7,7 +7,7 @@ package space.kscience.kmath.histogram
 
 import space.kscience.kmath.domains.Domain
 import space.kscience.kmath.linear.Point
-import space.kscience.kmath.structures.DoubleBuffer
+import space.kscience.kmath.structures.Float64Buffer
 import space.kscience.kmath.structures.asBuffer
 
 /**
@@ -66,9 +66,9 @@ public fun <T : Any> HistogramBuilder<T, *>.put(point: Point<out T>): Unit = put
 public fun <T : Any> HistogramBuilder<T, *>.put(vararg point: T): Unit = put(point.asBuffer())
 
 public fun HistogramBuilder<Double, *>.put(vararg point: Number): Unit =
-    put(DoubleBuffer(point.map { it.toDouble() }.toDoubleArray()))
+    put(Float64Buffer(point.map { it.toDouble() }.toDoubleArray()))
 
-public fun HistogramBuilder<Double, *>.put(vararg point: Double): Unit = put(DoubleBuffer(point))
+public fun HistogramBuilder<Double, *>.put(vararg point: Double): Unit = put(Float64Buffer(point))
 public fun <T : Any> HistogramBuilder<T, *>.fill(sequence: Iterable<Point<T>>): Unit = sequence.forEach { put(it) }
 
 /**

kmath-histograms/src/commonMain/kotlin/space/kscience/kmath/histogram/UniformHistogramGroupND.kt

@@ -41,7 +41,7 @@ public class UniformHistogramGroupND<V : Any, A : Field<V>>(
 
     override val shape: ShapeND = ShapeND(IntArray(binNums.size) { binNums[it] + 2 })
 
-    private val binSize = DoubleBuffer(dimension) { (upper[it] - lower[it]) / binNums[it] }
+    private val binSize = Float64Buffer(dimension) { (upper[it] - lower[it]) / binNums[it] }
 
     /**
      * Get internal [StructureND] bin index for given axis
@@ -129,7 +129,7 @@ public fun <V : Any, A : Field<V>> Histogram.Companion.uniformNDFromRanges(
 public fun Histogram.Companion.uniformDoubleNDFromRanges(
     vararg ranges: ClosedFloatingPointRange<Double>,
 ): UniformHistogramGroupND<Double, Float64Field> =
-    uniformNDFromRanges(DoubleFieldOpsND, *ranges, bufferFactory = ::DoubleBuffer)
+    uniformNDFromRanges(Floa64FieldOpsND, *ranges, bufferFactory = ::Float64Buffer)
 
 
 /**
@@ -164,4 +164,4 @@ public fun <V : Any, A : Field<V>> Histogram.Companion.uniformNDFromRanges(
 public fun Histogram.Companion.uniformDoubleNDFromRanges(
     vararg ranges: Pair<ClosedFloatingPointRange<Double>, Int>,
 ): UniformHistogramGroupND<Double, Float64Field> =
-    uniformNDFromRanges(DoubleFieldOpsND, *ranges, bufferFactory = ::DoubleBuffer)
+    uniformNDFromRanges(Floa64FieldOpsND, *ranges, bufferFactory = ::Float64Buffer)

kmath-optimization/src/commonMain/kotlin/space/kscience/kmath/optimization/QowOptimizer.kt

@@ -9,10 +9,10 @@ import space.kscience.kmath.UnstableKMathAPI
 import space.kscience.kmath.expressions.*
 import space.kscience.kmath.linear.*
 import space.kscience.kmath.misc.log
-import space.kscience.kmath.operations.DoubleL2Norm
 import space.kscience.kmath.operations.Float64Field
+import space.kscience.kmath.operations.Float64L2Norm
 import space.kscience.kmath.operations.algebra
-import space.kscience.kmath.structures.DoubleBuffer
+import space.kscience.kmath.structures.Float64Buffer
 import kotlin.math.abs
 
 
@@ -63,7 +63,7 @@ public object QowOptimizer : Optimizer<Double, XYFit> {
          * Array of dispersions in each point
          */
         val dispersion: Point<Double> by lazy {
-            DoubleBuffer(problem.data.size) { d ->
+            Float64Buffer(problem.data.size) { d ->
                 1.0 / problem.weight(d).invoke(allParameters)
             }
         }
@@ -148,8 +148,8 @@ public object QowOptimizer : Optimizer<Double, XYFit> {
      * Quasi optimal weights equations values
      */
     private fun QoWeight.getEqValues(theta: Map<Symbol, Double>): Point<Double> {
-        val distances = DoubleBuffer(data.size) { d -> distance(d, theta) }
+        val distances = Float64Buffer(data.size) { d -> distance(d, theta) }
-        return DoubleBuffer(size) { s ->
+        return Float64Buffer(size) { s ->
             val base = (0 until data.size).sumOf { d -> distances[d] * derivs[d, s] / dispersion[d] }
             //Prior probability correction
             prior?.let { prior ->
@@ -186,7 +186,7 @@ public object QowOptimizer : Optimizer<Double, XYFit> {
 
         var eqvalues = getEqValues(par) //Values of the weight functions
 
-        dis = DoubleL2Norm.norm(eqvalues) // discrepancy
+        dis = Float64L2Norm.norm(eqvalues) // discrepancy
         logger?.log { "Starting discrepancy is $dis" }
         var i = 0
         var flag = false
@@ -205,7 +205,7 @@ public object QowOptimizer : Optimizer<Double, XYFit> {
             logger?.log { "Parameter values after step are: \n\t$currentSolution" }
 
             eqvalues = getEqValues(currentSolution.freeParameters)
-            val currentDis = DoubleL2Norm.norm(eqvalues)// discrepancy after the step
+            val currentDis = Float64L2Norm.norm(eqvalues)// discrepancy after the step
 
             logger?.log { "The discrepancy after step is: $currentDis." }
 

kmath-stat/src/commonMain/kotlin/space/kscience/kmath/random/RandomChain.kt

@@ -7,7 +7,7 @@ package space.kscience.kmath.random
 
 import space.kscience.kmath.chains.BlockingDoubleChain
 import space.kscience.kmath.chains.Chain
-import space.kscience.kmath.structures.DoubleBuffer
+import space.kscience.kmath.structures.Float64Buffer
 
 /**
  * A possibly stateful chain producing random values.
@@ -31,8 +31,8 @@ public fun <R> RandomGenerator.chain(generator: suspend RandomGenerator.() -> R)
  * A type-specific double chunk random chain
  */
 public class UniformDoubleChain(public val generator: RandomGenerator) : BlockingDoubleChain {
-    override fun nextBufferBlocking(size: Int): DoubleBuffer = generator.nextDoubleBuffer(size)
+    override fun nextBufferBlocking(size: Int): Float64Buffer = generator.nextDoubleBuffer(size)
-    override suspend fun nextBuffer(size: Int): DoubleBuffer = nextBufferBlocking(size)
+    override suspend fun nextBuffer(size: Int): Float64Buffer = nextBufferBlocking(size)
 
     override suspend fun fork(): UniformDoubleChain = UniformDoubleChain(generator.fork())
 }

kmath-stat/src/commonMain/kotlin/space/kscience/kmath/random/RandomGenerator.kt

@@ -5,7 +5,7 @@
 
 package space.kscience.kmath.random
 
-import space.kscience.kmath.structures.DoubleBuffer
+import space.kscience.kmath.structures.Float64Buffer
 import kotlin.random.Random
 
 /**
@@ -25,7 +25,7 @@ public interface RandomGenerator {
     /**
      * A chunk of doubles of given [size].
      */
-    public fun nextDoubleBuffer(size: Int): DoubleBuffer = DoubleBuffer(size) { nextDouble() }
+    public fun nextDoubleBuffer(size: Int): Float64Buffer = Float64Buffer(size) { nextDouble() }
 
     /**
      * Gets the next random `Int` from the random number generator.

kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/AhrensDieterExponentialSampler.kt

@@ -8,7 +8,7 @@ package space.kscience.kmath.samplers
 import space.kscience.kmath.chains.BlockingDoubleChain
 import space.kscience.kmath.random.RandomGenerator
 import space.kscience.kmath.stat.Sampler
-import space.kscience.kmath.structures.DoubleBuffer
+import space.kscience.kmath.structures.Float64Buffer
 import kotlin.math.ln
 import kotlin.math.pow
 
@@ -56,7 +56,7 @@ public class AhrensDieterExponentialSampler(public val mean: Double) : Sampler<D
             return mean * (a + umin * EXPONENTIAL_SA_QI[0])
         }
 
-        override fun nextBufferBlocking(size: Int): DoubleBuffer = DoubleBuffer(size) { nextBlocking() }
+        override fun nextBufferBlocking(size: Int): Float64Buffer = Float64Buffer(size) { nextBlocking() }
 
         override suspend fun fork(): BlockingDoubleChain = sample(generator.fork())
     }

kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/BoxMullerSampler.kt

@@ -7,7 +7,7 @@ package space.kscience.kmath.samplers
 
 import space.kscience.kmath.chains.BlockingDoubleChain
 import space.kscience.kmath.random.RandomGenerator
-import space.kscience.kmath.structures.DoubleBuffer
+import space.kscience.kmath.structures.Float64Buffer
 import kotlin.math.*
 
 /**
@@ -22,11 +22,11 @@ public object BoxMullerSampler : NormalizedGaussianSampler {
     override fun sample(generator: RandomGenerator): BlockingDoubleChain = object : BlockingDoubleChain {
         var state = Double.NaN
 
-        override fun nextBufferBlocking(size: Int): DoubleBuffer {
+        override fun nextBufferBlocking(size: Int): Float64Buffer {
             val xs = generator.nextDoubleBuffer(size)
             val ys = generator.nextDoubleBuffer(size)
 
-            return DoubleBuffer(size) { index ->
+            return Float64Buffer(size) { index ->
                 if (state.isNaN()) {
                     // Generate a pair of Gaussian numbers.
                     val x = xs[index]

kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/KempSmallMeanPoissonSampler.kt

@@ -8,7 +8,7 @@ package space.kscience.kmath.samplers
 import space.kscience.kmath.chains.BlockingIntChain
 import space.kscience.kmath.random.RandomGenerator
 import space.kscience.kmath.stat.Sampler
-import space.kscience.kmath.structures.IntBuffer
+import space.kscience.kmath.structures.Int32Buffer
 import kotlin.math.exp
 
 /**
@@ -55,7 +55,7 @@ public class KempSmallMeanPoissonSampler internal constructor(
             return x
         }
 
-        override fun nextBufferBlocking(size: Int): IntBuffer = IntBuffer(size) { nextBlocking() }
+        override fun nextBufferBlocking(size: Int): Int32Buffer = Int32Buffer(size) { nextBlocking() }
 
         override suspend fun fork(): BlockingIntChain = sample(generator.fork())
     }

kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/MarsagliaNormalizedGaussianSampler.kt

@@ -7,7 +7,7 @@ package space.kscience.kmath.samplers
 
 import space.kscience.kmath.chains.BlockingDoubleChain
 import space.kscience.kmath.random.RandomGenerator
-import space.kscience.kmath.structures.DoubleBuffer
+import space.kscience.kmath.structures.Float64Buffer
 import kotlin.math.ln
 import kotlin.math.sqrt
 
@@ -59,7 +59,7 @@ public object MarsagliaNormalizedGaussianSampler : NormalizedGaussianSampler {
             }
         }
 
-        override fun nextBufferBlocking(size: Int): DoubleBuffer = DoubleBuffer(size) { nextBlocking() }
+        override fun nextBufferBlocking(size: Int): Float64Buffer = Float64Buffer(size) { nextBlocking() }
 
         override suspend fun fork(): BlockingDoubleChain = sample(generator.fork())
     }

kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/PoissonSampler.kt

@@ -9,7 +9,7 @@ import space.kscience.kmath.chains.BlockingIntChain
 import space.kscience.kmath.misc.toIntExact
 import space.kscience.kmath.random.RandomGenerator
 import space.kscience.kmath.stat.Sampler
-import space.kscience.kmath.structures.IntBuffer
+import space.kscience.kmath.structures.Int32Buffer
 import kotlin.math.*
 
 
@@ -71,7 +71,7 @@ public class SmallMeanPoissonSampler(public val mean: Double) : Sampler<Int> {
             return n
         }
 
-        override fun nextBufferBlocking(size: Int): IntBuffer = IntBuffer(size) { nextBlocking() }
+        override fun nextBufferBlocking(size: Int): Int32Buffer = Int32Buffer(size) { nextBlocking() }
 
         override suspend fun fork(): BlockingIntChain = sample(generator.fork())
     }
@@ -191,7 +191,7 @@ public class LargeMeanPoissonSampler(public val mean: Double) : Sampler<Int> {
             return min(y2 + y.toLong(), Int.MAX_VALUE.toLong()).toIntExact()
         }
 
-        override fun nextBufferBlocking(size: Int): IntBuffer = IntBuffer(size) { nextBlocking() }
+        override fun nextBufferBlocking(size: Int): Int32Buffer = Int32Buffer(size) { nextBlocking() }
 
         override suspend fun fork(): BlockingIntChain = sample(generator.fork())
     }

kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/Sampler.kt

@@ -12,8 +12,8 @@ import space.kscience.kmath.chains.combine
 import space.kscience.kmath.random.RandomGenerator
 import space.kscience.kmath.structures.Buffer
 import space.kscience.kmath.structures.BufferFactory
-import space.kscience.kmath.structures.DoubleBuffer
+import space.kscience.kmath.structures.Float64Buffer
-import space.kscience.kmath.structures.IntBuffer
+import space.kscience.kmath.structures.Int32Buffer
 import kotlin.jvm.JvmName
 
 /**
@@ -62,14 +62,14 @@ public suspend fun <T : Any> Sampler<T>.next(generator: RandomGenerator): T = sa
  */
 @JvmName("sampleRealBuffer")
 public fun Sampler<Double>.sampleBuffer(generator: RandomGenerator, size: Int): Chain<Buffer<Double>> =
-    sampleBuffer(generator, size, ::DoubleBuffer)
+    sampleBuffer(generator, size, ::Float64Buffer)
 
 /**
  * Generates [size] integer samples and chunks them into some buffers.
  */
 @JvmName("sampleIntBuffer")
 public fun Sampler<Int>.sampleBuffer(generator: RandomGenerator, size: Int): Chain<Buffer<Int>> =
-    sampleBuffer(generator, size, ::IntBuffer)
+    sampleBuffer(generator, size, ::Int32Buffer)
 
 
 /**

kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/ZigguratNormalizedGaussianSampler.kt

@@ -7,7 +7,7 @@ package space.kscience.kmath.samplers
 
 import space.kscience.kmath.chains.BlockingDoubleChain
 import space.kscience.kmath.random.RandomGenerator
-import space.kscience.kmath.structures.DoubleBuffer
+import space.kscience.kmath.structures.Float64Buffer
 import kotlin.math.*
 
 /**
@@ -63,7 +63,7 @@ public object ZigguratNormalizedGaussianSampler : NormalizedGaussianSampler {
     }
 
     override fun sample(generator: RandomGenerator): BlockingDoubleChain = object : BlockingDoubleChain {
-        override fun nextBufferBlocking(size: Int): DoubleBuffer = DoubleBuffer(size) { sampleOne(generator) }
+        override fun nextBufferBlocking(size: Int): Float64Buffer = Float64Buffer(size) { sampleOne(generator) }
 
         override suspend fun fork(): BlockingDoubleChain = sample(generator.fork())
     }

kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/BroadcastDoubleTensorAlgebra.kt

@@ -7,7 +7,7 @@ package space.kscience.kmath.tensors.core
 
 import space.kscience.kmath.UnstableKMathAPI
 import space.kscience.kmath.nd.StructureND
-import space.kscience.kmath.structures.DoubleBuffer
+import space.kscience.kmath.structures.Float64Buffer
 import space.kscience.kmath.tensors.api.Tensor
 import space.kscience.kmath.tensors.core.internal.broadcastTensors
 import space.kscience.kmath.tensors.core.internal.broadcastTo
@@ -22,7 +22,7 @@ public object BroadcastDoubleTensorAlgebra : DoubleTensorAlgebra() {
         val broadcast = broadcastTensors(asDoubleTensor(), arg.asDoubleTensor())
         val newThis = broadcast[0]
         val newOther = broadcast[1]
-        val resBuffer = DoubleBuffer(newThis.indices.linearSize) { i ->
+        val resBuffer = Float64Buffer(newThis.indices.linearSize) { i ->
             newThis.source[i] + newOther.source[i]
         }
         return DoubleTensor(newThis.shape, resBuffer)
@@ -39,7 +39,7 @@ public object BroadcastDoubleTensorAlgebra : DoubleTensorAlgebra() {
         val broadcast = broadcastTensors(asDoubleTensor(), arg.asDoubleTensor())
         val newThis = broadcast[0]
         val newOther = broadcast[1]
-        val resBuffer = DoubleBuffer(newThis.indices.linearSize) { i ->
+        val resBuffer = Float64Buffer(newThis.indices.linearSize) { i ->
             newThis.source[i] - newOther.source[i]
         }
         return DoubleTensor(newThis.shape, resBuffer)
@@ -56,7 +56,7 @@ public object BroadcastDoubleTensorAlgebra : DoubleTensorAlgebra() {
         val broadcast = broadcastTensors(asDoubleTensor(), arg.asDoubleTensor())
         val newThis = broadcast[0]
         val newOther = broadcast[1]
-        val resBuffer = DoubleBuffer(newThis.indices.linearSize) { i ->
+        val resBuffer = Float64Buffer(newThis.indices.linearSize) { i ->
             newThis.source[i] * newOther.source[i]
         }
         return DoubleTensor(newThis.shape, resBuffer)
@@ -73,7 +73,7 @@ public object BroadcastDoubleTensorAlgebra : DoubleTensorAlgebra() {
         val broadcast = broadcastTensors(asDoubleTensor(), arg.asDoubleTensor())
         val newThis = broadcast[0]
         val newOther = broadcast[1]
-        val resBuffer = DoubleBuffer(newThis.indices.linearSize) { i ->
+        val resBuffer = Float64Buffer(newThis.indices.linearSize) { i ->
             newThis.source[i] / newOther.source[i]
         }
         return DoubleTensor(newThis.shape, resBuffer)

kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/DoubleTensor.kt

@@ -13,7 +13,7 @@ import space.kscience.kmath.structures.*
 import space.kscience.kmath.tensors.core.internal.toPrettyString
 
 public class OffsetDoubleBuffer(
-    override val origin: DoubleBuffer,
+    override val origin: Float64Buffer,
     private val offset: Int,
     override val size: Int,
 ) : MutableBuffer<Double>, BufferView<Double> {
@@ -34,7 +34,7 @@ public class OffsetDoubleBuffer(
     /**
      * Copy only a part of buffer that belongs to this [OffsetDoubleBuffer]
      */
-    override fun copy(): DoubleBuffer = origin.array.copyOfRange(offset, offset + size).asBuffer()
+    override fun copy(): Float64Buffer = origin.array.copyOfRange(offset, offset + size).asBuffer()
 
     override fun iterator(): Iterator<Double> = iterator {
         for (i in indices) {
@@ -60,15 +60,15 @@ public fun OffsetDoubleBuffer.slice(range: IntRange): OffsetDoubleBuffer = view(
 /**
  * Map only operable content of the offset buffer
  */
-public inline fun OffsetDoubleBuffer.map(operation: (Double) -> Double): DoubleBuffer =
+public inline fun OffsetDoubleBuffer.map(operation: (Double) -> Double): Float64Buffer =
-    DoubleBuffer(size) { operation(get(it)) }
+    Float64Buffer(size) { operation(get(it)) }
 
 public inline fun OffsetDoubleBuffer.zip(
     other: OffsetDoubleBuffer,
     operation: (l: Double, r: Double) -> Double,
-): DoubleBuffer {
+): Float64Buffer {
     require(size == other.size) { "The sizes of zipped buffers must be the same" }
-    return DoubleBuffer(size) { operation(get(it), other[it]) }
+    return Float64Buffer(size) { operation(get(it), other[it]) }
 }
 
 /**
@@ -92,7 +92,7 @@ public open class DoubleTensor(
         require(linearSize == source.size) { "Source buffer size must be equal tensor size" }
     }
 
-    public constructor(shape: ShapeND, buffer: DoubleBuffer) : this(shape, OffsetDoubleBuffer(buffer, 0, buffer.size))
+    public constructor(shape: ShapeND, buffer: Float64Buffer) : this(shape, OffsetDoubleBuffer(buffer, 0, buffer.size))
 
 
     @OptIn(PerformancePitfall::class)

kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/DoubleTensorAlgebra.kt

@@ -10,7 +10,7 @@ package space.kscience.kmath.tensors.core
 
 import space.kscience.kmath.PerformancePitfall
 import space.kscience.kmath.nd.*
-import space.kscience.kmath.operations.DoubleBufferOps
+import space.kscience.kmath.operations.Float64BufferOps
 import space.kscience.kmath.operations.Float64Field
 import space.kscience.kmath.structures.*
 import space.kscience.kmath.tensors.api.AnalyticTensorAlgebra
@@ -34,7 +34,7 @@ public open class DoubleTensorAlgebra :
 
     override val elementAlgebra: Float64Field get() = Float64Field
 
-    public val bufferAlgebra: DoubleBufferOps get() = DoubleBufferOps
+    public val bufferAlgebra: Float64BufferOps get() = Float64BufferOps
 
 
     /**
@@ -47,7 +47,7 @@ public open class DoubleTensorAlgebra :
     final override inline fun StructureND<Double>.map(transform: Float64Field.(Double) -> Double): DoubleTensor {
         val tensor = asDoubleTensor()
         //TODO remove additional copy
-        val array = DoubleBuffer(tensor.source.size) { Float64Field.transform(tensor.source[it]) }
+        val array = Float64Buffer(tensor.source.size) { Float64Field.transform(tensor.source[it]) }
         return DoubleTensor(
             tensor.shape,
             array,
@@ -82,14 +82,14 @@ public open class DoubleTensorAlgebra :
 
         val leftTensor = left.asDoubleTensor()
         val rightTensor = right.asDoubleTensor()
-        val buffer = DoubleBuffer(leftTensor.source.size) {
+        val buffer = Float64Buffer(leftTensor.source.size) {
             Float64Field.transform(leftTensor.source[it], rightTensor.source[it])
         }
         return DoubleTensor(leftTensor.shape, buffer)
     }
 
 
-    public inline fun StructureND<Double>.reduceElements(transform: (DoubleBuffer) -> Double): Double =
+    public inline fun StructureND<Double>.reduceElements(transform: (Float64Buffer) -> Double): Double =
         transform(asDoubleTensor().source.copy())
     //TODO Add read-only DoubleBuffer wrapper. To avoid protective copy
 
@@ -107,7 +107,7 @@ public open class DoubleTensorAlgebra :
         check(buffer.size == shape.linearSize) {
             "Inconsistent shape $shape for buffer of size ${buffer.size} provided"
         }
-        return DoubleTensor(shape, buffer.toDoubleBuffer())
+        return DoubleTensor(shape, buffer.toFloat64Buffer())
     }
 
 
@@ -151,7 +151,7 @@ public open class DoubleTensorAlgebra :
      */
     public fun full(value: Double, shape: ShapeND): DoubleTensor {
         checkNotEmptyShape(shape)
-        val buffer = DoubleBuffer(shape.linearSize) { value }
+        val buffer = Float64Buffer(shape.linearSize) { value }
         return DoubleTensor(shape, buffer)
     }
 
@@ -163,7 +163,7 @@ public open class DoubleTensorAlgebra :
      */
     public fun fullLike(structureND: StructureND<*>, value: Double): DoubleTensor {
         val shape = structureND.shape
-        val buffer = DoubleBuffer(structureND.indices.linearSize) { value }
+        val buffer = Float64Buffer(structureND.indices.linearSize) { value }
         return DoubleTensor(shape, buffer)
     }
 
@@ -205,7 +205,7 @@ public open class DoubleTensorAlgebra :
      */
     public fun eye(n: Int): DoubleTensor {
         val shape = ShapeND(n, n)
-        val buffer = DoubleBuffer(n * n) { 0.0 }
+        val buffer = Float64Buffer(n * n) { 0.0 }
         val res = DoubleTensor(shape, buffer)
         for (i in 0 until n) {
             res[intArrayOf(i, i)] = 1.0
@@ -353,7 +353,7 @@ public open class DoubleTensorAlgebra :
      */
     public infix fun StructureND<Double>.matmul(other: StructureND<Double>): DoubleTensor {
         if (shape.size == 1 && other.shape.size == 1) {
-            return DoubleTensor(ShapeND(1), DoubleBuffer(times(other).sum()))
+            return DoubleTensor(ShapeND(1), Float64Buffer(times(other).sum()))
         }
 
         var penultimateDim = false
@@ -529,7 +529,7 @@ public open class DoubleTensorAlgebra :
         val init = foldFunction(DoubleArray(1) { 0.0 })
         val resTensor = DoubleTensor(
             resShape,
-            DoubleBuffer(resNumElements) { init }
+            Float64Buffer(resNumElements) { init }
         )
         val dt = asDoubleTensor()
         for (index in resTensor.indices) {
@@ -557,7 +557,7 @@ public open class DoubleTensorAlgebra :
         val init = foldFunction(DoubleArray(1) { 0.0 })
         val resTensor = IntTensor(
             resShape,
-            IntBuffer(resNumElements) { init }
+            Int32Buffer(resNumElements) { init }
         )
         for (index in resTensor.indices) {
             val prefix = index.take(dim).toIntArray()

kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/IntTensor.kt

@@ -13,7 +13,7 @@ import space.kscience.kmath.structures.*
  * Default [BufferedTensor] implementation for [Int] values
  */
 public class OffsetIntBuffer(
-    private val source: IntBuffer,
+    private val source: Int32Buffer,
     private val offset: Int,
     override val size: Int,
 ) : MutableBuffer<Int> {
@@ -34,7 +34,7 @@ public class OffsetIntBuffer(
     /**
      * Copy only a part of buffer that belongs to this tensor
      */
-    override fun copy(): IntBuffer = source.array.copyOfRange(offset, offset + size).asBuffer()
+    override fun copy(): Int32Buffer = source.array.copyOfRange(offset, offset + size).asBuffer()
 
     override fun iterator(): Iterator<Int> = iterator {
         for (i in indices) {
@@ -53,15 +53,15 @@ public fun OffsetIntBuffer.slice(range: IntRange): OffsetIntBuffer = view(range.
 /**
  * Map only operable content of the offset buffer
  */
-public inline fun OffsetIntBuffer.map(operation: (Int) -> Int): IntBuffer =
+public inline fun OffsetIntBuffer.map(operation: (Int) -> Int): Int32Buffer =
-    IntBuffer(size) { operation(get(it)) }
+    Int32Buffer(size) { operation(get(it)) }
 
 public inline fun OffsetIntBuffer.zip(
     other: OffsetIntBuffer,
     operation: (l: Int, r: Int) -> Int,
-): IntBuffer {
+): Int32Buffer {
     require(size == other.size) { "The sizes of zipped buffers must be the same" }
-    return IntBuffer(size) { operation(get(it), other[it]) }
+    return Int32Buffer(size) { operation(get(it), other[it]) }
 }
 
 /**
@@ -83,7 +83,7 @@ public class IntTensor(
         require(linearSize == source.size) { "Source buffer size must be equal tensor size" }
     }
 
-    public constructor(shape: ShapeND, buffer: IntBuffer) : this(shape, OffsetIntBuffer(buffer, 0, buffer.size))
+    public constructor(shape: ShapeND, buffer: Int32Buffer) : this(shape, OffsetIntBuffer(buffer, 0, buffer.size))
 
     @OptIn(PerformancePitfall::class)
     override fun get(index: IntArray): Int = this.source[indices.offset(index)]

kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/IntTensorAlgebra.kt

@@ -37,7 +37,7 @@ public open class IntTensorAlgebra : TensorAlgebra<Int, Int32Ring> {
     final override inline fun StructureND<Int>.map(transform: Int32Ring.(Int) -> Int): IntTensor {
         val tensor = this.asIntTensor()
         //TODO remove additional copy
-        val array = IntBuffer(tensor.source.size) { Int32Ring.transform(tensor.source[it]) }
+        val array = Int32Buffer(tensor.source.size) { Int32Ring.transform(tensor.source[it]) }
         return IntTensor(
             tensor.shape,
             array,
@@ -60,7 +60,7 @@ public open class IntTensorAlgebra : TensorAlgebra<Int, Int32Ring> {
     final override inline fun StructureND<Int>.mapIndexed(transform: Int32Ring.(index: IntArray, Int) -> Int): IntTensor {
         val tensor = this.asIntTensor()
         //TODO remove additional copy
-        val buffer = IntBuffer(tensor.source.size) {
+        val buffer = Int32Buffer(tensor.source.size) {
             Int32Ring.transform(tensor.indices.index(it), tensor.source[it])
         }
         return IntTensor(tensor.shape, buffer)
@@ -76,14 +76,14 @@ public open class IntTensorAlgebra : TensorAlgebra<Int, Int32Ring> {
 
         val leftTensor = left.asIntTensor()
         val rightTensor = right.asIntTensor()
-        val buffer = IntBuffer(leftTensor.source.size) {
+        val buffer = Int32Buffer(leftTensor.source.size) {
             Int32Ring.transform(leftTensor.source[it], rightTensor.source[it])
         }
         return IntTensor(leftTensor.shape, buffer)
     }
 
 
-    public inline fun StructureND<Int>.reduceElements(transform: (IntBuffer) -> Int): Int =
+    public inline fun StructureND<Int>.reduceElements(transform: (Int32Buffer) -> Int): Int =
         transform(asIntTensor().source.copy())
     //TODO do we need protective copy?
 
@@ -139,7 +139,7 @@ public open class IntTensorAlgebra : TensorAlgebra<Int, Int32Ring> {
      */
     public fun full(value: Int, shape: ShapeND): IntTensor {
         checkNotEmptyShape(shape)
-        val buffer = IntBuffer(shape.linearSize) { value }
+        val buffer = Int32Buffer(shape.linearSize) { value }
         return IntTensor(shape, buffer)
     }
 
@@ -151,7 +151,7 @@ public open class IntTensorAlgebra : TensorAlgebra<Int, Int32Ring> {
      */
     public fun fullLike(structureND: StructureND<*>, value: Int): IntTensor {
         val shape = structureND.shape
-        val buffer = IntBuffer(structureND.indices.linearSize) { value }
+        val buffer = Int32Buffer(structureND.indices.linearSize) { value }
         return IntTensor(shape, buffer)
     }
 
@@ -193,7 +193,7 @@ public open class IntTensorAlgebra : TensorAlgebra<Int, Int32Ring> {
      */
     public fun eye(n: Int): IntTensor {
         val shape = ShapeND(n, n)
-        val buffer = IntBuffer(n * n) { 0 }
+        val buffer = Int32Buffer(n * n) { 0 }
         val res = IntTensor(shape, buffer)
         for (i in 0 until n) {
             res[intArrayOf(i, i)] = 1
@@ -420,7 +420,7 @@ public open class IntTensorAlgebra : TensorAlgebra<Int, Int32Ring> {
         val init = foldFunction(IntArray(1) { 0 })
         val resTensor = IntTensor(
             resShape,
-            IntBuffer(resNumElements) { init }
+            Int32Buffer(resNumElements) { init }
         )
         for (index in resTensor.indices) {
             val prefix = index.take(dim).toIntArray()

kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/internal/doubleTensorHelpers.kt

@@ -6,7 +6,7 @@
 package space.kscience.kmath.tensors.core.internal
 
 import space.kscience.kmath.nd.*
-import space.kscience.kmath.structures.DoubleBuffer
+import space.kscience.kmath.structures.Float64Buffer
 import space.kscience.kmath.structures.asBuffer
 import space.kscience.kmath.structures.indices
 import space.kscience.kmath.tensors.core.BroadcastDoubleTensorAlgebra.eye
@@ -22,13 +22,13 @@ import kotlin.math.sqrt
 internal fun MutableStructure2D<Double>.jacobiHelper(
     maxIteration: Int,
     epsilon: Double,
-): Pair<DoubleBuffer, Structure2D<Double>> {
+): Pair<Float64Buffer, Structure2D<Double>> {
     val n = rowNum
     val A_ = copyToTensor()
     val V = eye(n)
-    val D = DoubleBuffer(n) { get(it, it) }
+    val D = Float64Buffer(n) { get(it, it) }
-    val B = DoubleBuffer(n) { get(it, it) }
+    val B = Float64Buffer(n) { get(it, it) }
-    val Z = DoubleBuffer(n) { 0.0 }
+    val Z = Float64Buffer(n) { 0.0 }
 
     // assume that buffered tensor is square matrix
     operator fun DoubleTensor.get(i: Int, j: Int): Double {
@@ -59,8 +59,8 @@ internal fun MutableStructure2D<Double>.jacobiHelper(
     fun jacobiIteration(
         a: DoubleTensor,
         v: DoubleTensor,
-        d: DoubleBuffer,
+        d: Float64Buffer,
-        z: DoubleBuffer,
+        z: Float64Buffer,
     ) {
         for (ip in 0 until n - 1) {
             for (iq in ip + 1 until n) {
@@ -108,9 +108,9 @@ internal fun MutableStructure2D<Double>.jacobiHelper(
     }
 
     fun updateDiagonal(
-        d: DoubleBuffer,
+        d: Float64Buffer,
-        z: DoubleBuffer,
+        z: Float64Buffer,
-        b: DoubleBuffer,
+        b: Float64Buffer,
     ) {
         for (ip in 0 until d.size) {
             b[ip] += z[ip]
@@ -137,7 +137,7 @@ internal fun MutableStructure2D<Double>.jacobiHelper(
 /**
  * Concatenate a list of arrays
  */
-internal fun List<OffsetDoubleBuffer>.concat(): DoubleBuffer {
+internal fun List<OffsetDoubleBuffer>.concat(): Float64Buffer {
     val array = DoubleArray(sumOf { it.size })
     var pointer = 0
     while (pointer < array.size) {

kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/internal/intTensorHelpers.kt

@@ -9,7 +9,7 @@ import space.kscience.kmath.nd.ShapeND
 import space.kscience.kmath.nd.first
 import space.kscience.kmath.nd.last
 import space.kscience.kmath.operations.asSequence
-import space.kscience.kmath.structures.IntBuffer
+import space.kscience.kmath.structures.Int32Buffer
 import space.kscience.kmath.structures.VirtualBuffer
 import space.kscience.kmath.structures.asBuffer
 import space.kscience.kmath.structures.indices
@@ -19,7 +19,7 @@ import space.kscience.kmath.tensors.core.OffsetIntBuffer
 /**
  * Concatenate a list of arrays
  */
-internal fun List<OffsetIntBuffer>.concat(): IntBuffer {
+internal fun List<OffsetIntBuffer>.concat(): Int32Buffer {
     val array = IntArray(sumOf { it.size })
     var pointer = 0
     while (pointer < array.size) {

kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/internal/linUtils.kt

@@ -7,8 +7,8 @@ package space.kscience.kmath.tensors.core.internal
 
 import space.kscience.kmath.nd.*
 import space.kscience.kmath.operations.invoke
-import space.kscience.kmath.structures.DoubleBuffer
+import space.kscience.kmath.structures.Float64Buffer
-import space.kscience.kmath.structures.IntBuffer
+import space.kscience.kmath.structures.Int32Buffer
 import space.kscience.kmath.structures.asBuffer
 import space.kscience.kmath.structures.indices
 import space.kscience.kmath.tensors.core.*
@@ -97,7 +97,7 @@ internal fun <T> StructureND<T>.setUpPivots(): IntTensor {
 
     return IntTensor(
         ShapeND(pivotsShape),
-        IntBuffer(pivotsShape.reduce(Int::times)) { 0 }
+        Int32Buffer(pivotsShape.reduce(Int::times)) { 0 }
     )
 }
 
@@ -241,10 +241,10 @@ internal fun DoubleTensorAlgebra.svd1d(a: DoubleTensor, epsilon: Double = 1e-10)
     val b: DoubleTensor
     if (n > m) {
         b = a.transposed(0, 1).dot(a)
-        v = DoubleTensor(ShapeND(m), DoubleBuffer.randomUnitVector(m, 0))
+        v = DoubleTensor(ShapeND(m), Float64Buffer.randomUnitVector(m, 0))
     } else {
         b = a.dot(a.transposed(0, 1))
-        v = DoubleTensor(ShapeND(n), DoubleBuffer.randomUnitVector(n, 0))
+        v = DoubleTensor(ShapeND(n), Float64Buffer.randomUnitVector(n, 0))
     }
 
     var lastV: DoubleTensor

kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/internal/utils.kt

@@ -8,22 +8,22 @@ package space.kscience.kmath.tensors.core.internal
 import space.kscience.kmath.PerformancePitfall
 import space.kscience.kmath.nd.asList
 import space.kscience.kmath.nd.last
-import space.kscience.kmath.operations.DoubleBufferOps.Companion.map
+import space.kscience.kmath.operations.Float64BufferOps.Companion.map
 import space.kscience.kmath.random.RandomGenerator
 import space.kscience.kmath.samplers.GaussianSampler
-import space.kscience.kmath.structures.DoubleBuffer
+import space.kscience.kmath.structures.Float64Buffer
 import space.kscience.kmath.tensors.core.BufferedTensor
 import space.kscience.kmath.tensors.core.DoubleTensor
 import kotlin.math.*
 
-internal fun DoubleBuffer.Companion.randomNormals(n: Int, seed: Long): DoubleBuffer {
+internal fun Float64Buffer.Companion.randomNormals(n: Int, seed: Long): Float64Buffer {
     val distribution = GaussianSampler(0.0, 1.0)
     val generator = RandomGenerator.default(seed)
     return distribution.sample(generator).nextBufferBlocking(n)
 }
 
-internal fun DoubleBuffer.Companion.randomUnitVector(n: Int, seed: Long): DoubleBuffer {
+internal fun Float64Buffer.Companion.randomUnitVector(n: Int, seed: Long): Float64Buffer {
-    val unnorm: DoubleBuffer = randomNormals(n, seed)
+    val unnorm: Float64Buffer = randomNormals(n, seed)
     val norm = sqrt(unnorm.array.sumOf { it * it })
     return unnorm.map { it / norm }
 }

kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/tensorOps.kt

@@ -8,7 +8,7 @@ package space.kscience.kmath.tensors.core
 import space.kscience.kmath.nd.*
 import space.kscience.kmath.operations.covariance
 import space.kscience.kmath.structures.Buffer
-import space.kscience.kmath.structures.DoubleBuffer
+import space.kscience.kmath.structures.Float64Buffer
 import space.kscience.kmath.tensors.api.Tensor
 import space.kscience.kmath.tensors.core.internal.*
 import kotlin.math.min
@@ -24,7 +24,7 @@ import kotlin.math.sign
  * with `0.0` mean and `1.0` standard deviation.
  */
 public fun DoubleTensorAlgebra.randomNormal(shape: ShapeND, seed: Long = 0): DoubleTensor =
-    fromBuffer(shape, DoubleBuffer.randomNormals(shape.linearSize, seed))
+    fromBuffer(shape, Float64Buffer.randomNormals(shape.linearSize, seed))
 
 /**
  * Returns a tensor with the same shape as `input` of random numbers drawn from normal distributions
@@ -36,7 +36,7 @@ public fun DoubleTensorAlgebra.randomNormal(shape: ShapeND, seed: Long = 0): Dou
  * with `0.0` mean and `1.0` standard deviation.
  */
 public fun DoubleTensorAlgebra.randomNormalLike(structure: WithShape, seed: Long = 0): DoubleTensor =
-    DoubleTensor(structure.shape, DoubleBuffer.randomNormals(structure.shape.linearSize, seed))
+    DoubleTensor(structure.shape, Float64Buffer.randomNormals(structure.shape.linearSize, seed))
 
 /**
  * Concatenates a sequence of tensors with equal shapes along the first dimension.
@@ -336,7 +336,7 @@ public fun DoubleTensorAlgebra.detLU(structureND: StructureND<Double>, epsilon:
         set(n - 2, 1)
     })
 
-    val resBuffer = DoubleBuffer(detTensorShape.linearSize) { 0.0 }
+    val resBuffer = Float64Buffer(detTensorShape.linearSize) { 0.0 }
 
     val detTensor = DoubleTensor(
         detTensorShape,
@@ -389,7 +389,7 @@ public fun DoubleTensorAlgebra.covariance(vectors: List<Buffer<Double>>): Double
     check(vectors.all { it.size == m }) { "Vectors must have same shapes" }
     val resTensor = DoubleTensor(
         ShapeND(n, n),
-        DoubleBuffer(n * n) { 0.0 }
+        Float64Buffer(n * n) { 0.0 }
     )
     for (i in 0 until n) {
         for (j in 0 until n) {

kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/tensorTransform.kt

@@ -6,7 +6,7 @@
 package space.kscience.kmath.tensors.core
 
 import space.kscience.kmath.nd.*
-import space.kscience.kmath.structures.DoubleBuffer
+import space.kscience.kmath.structures.Float64Buffer
 import space.kscience.kmath.structures.asBuffer
 import space.kscience.kmath.tensors.api.Tensor
 
@@ -16,7 +16,7 @@ import space.kscience.kmath.tensors.api.Tensor
  */
 public fun StructureND<Double>.copyToTensor(): DoubleTensor = if (this is DoubleTensor) {
     DoubleTensor(shape, source.copy())
-} else if (this is DoubleBufferND && indices is RowStrides) {
+} else if (this is Float64BufferND && indices is RowStrides) {
     DoubleTensor(shape, buffer.copy())
 } else {
     DoubleTensor(
@@ -29,7 +29,7 @@ public fun StructureND<Int>.toDoubleTensor(): DoubleTensor {
     return if (this is IntTensor) {
         DoubleTensor(
             shape,
-            DoubleBuffer(linearSize) { source[it].toDouble() }
+            Float64Buffer(linearSize) { source[it].toDouble() }
         )
     } else {
         val tensor = DoubleTensorAlgebra.zeroesLike(this)
@@ -45,7 +45,7 @@ public fun StructureND<Int>.toDoubleTensor(): DoubleTensor {
  */
 public fun StructureND<Double>.asDoubleTensor(): DoubleTensor = if (this is DoubleTensor) {
     this
-} else if (this is DoubleBufferND && indices is RowStrides) {
+} else if (this is Float64BufferND && indices is RowStrides) {
     DoubleTensor(shape, buffer)
 } else {
     copyToTensor()

kmath-tensors/src/commonTest/kotlin/space/kscience/kmath/tensors/core/TestDoubleTensor.kt

@@ -8,7 +8,7 @@ package space.kscience.kmath.tensors.core
 import space.kscience.kmath.PerformancePitfall
 import space.kscience.kmath.nd.*
 import space.kscience.kmath.operations.invoke
-import space.kscience.kmath.structures.DoubleBuffer
+import space.kscience.kmath.structures.Float64Buffer
 import space.kscience.kmath.structures.toDoubleArray
 import space.kscience.kmath.tensors.core.internal.matrixSequence
 import space.kscience.kmath.testutils.assertBufferEquals
@@ -65,10 +65,10 @@ internal class TestDoubleTensor {
     fun testNoBufferProtocol() {
 
         // create buffer
-        val doubleArray = DoubleBuffer(1.0, 2.0, 3.0)
+        val doubleArray = Float64Buffer(1.0, 2.0, 3.0)
 
         // create ND buffers, no data is copied
-        val ndArray: MutableBufferND<Double> = DoubleBufferND(ColumnStrides(ShapeND(3)), doubleArray)
+        val ndArray: MutableBufferND<Double> = Float64BufferND(ColumnStrides(ShapeND(3)), doubleArray)
 
         // map to tensors
         val tensorArray = ndArray.asDoubleTensor() // Data is copied because of strides change.
@@ -95,8 +95,8 @@ internal class TestDoubleTensor {
         val tensor: DoubleTensor = structureND(ShapeND(3, 3)) { (i, j) -> (i - j).toDouble() }
         //println(tensor.toPrettyString())
         val tensor2d = tensor.asDoubleTensor2D()
-        assertBufferEquals(DoubleBuffer(1.0, 0.0, -1.0), tensor2d.rows[1])
+        assertBufferEquals(Float64Buffer(1.0, 0.0, -1.0), tensor2d.rows[1])
-        assertBufferEquals(DoubleBuffer(-2.0, -1.0, 0.0), tensor2d.columns[2])
+        assertBufferEquals(Float64Buffer(-2.0, -1.0, 0.0), tensor2d.columns[2])
     }
 
     @Test

kmath-tensors/src/commonTest/kotlin/space/kscience/kmath/tensors/core/offsetBufferEquality.kt

@@ -6,13 +6,13 @@
 package space.kscience.kmath.tensors.core
 
 import space.kscience.kmath.structures.Buffer
-import space.kscience.kmath.structures.DoubleBuffer
+import space.kscience.kmath.structures.Float64Buffer
 import space.kscience.kmath.structures.indices
 import kotlin.jvm.JvmName
 
 
 /**
- * Simplified [DoubleBuffer] to array comparison
+ * Simplified [Float64Buffer] to array comparison
  */
 public fun OffsetDoubleBuffer.contentEquals(vararg doubles: Double): Boolean = indices.all { get(it) == doubles[it] }
 

kmath-tensors/src/jvmTest/kotlin/space/kscience/kmath/tensors/core/TestLmAlgorithm.kt

@@ -8,7 +8,7 @@ package space.kscience.kmath.tensors.core
 import space.kscience.kmath.PerformancePitfall
 import space.kscience.kmath.nd.*
 import space.kscience.kmath.operations.invoke
-import space.kscience.kmath.structures.DoubleBuffer
+import space.kscience.kmath.structures.Float64Buffer
 import kotlin.test.Test
 import kotlin.test.assertEquals
 
@@ -283,7 +283,7 @@ class TestLmAlgorithm {
         assertEquals(4858, result.funcCalls)
         assertEquals(5.14347, result.resultLambda, 1e-5)
         assertEquals(result.typeOfConvergence, TypeOfConvergence.InParameters)
-        val expectedParameters = DoubleBuffer(
+        val expectedParameters = Float64Buffer(
             -23.6412,
             -16.7402,
             -21.5705,

test-utils/src/commonMain/kotlin/bufferEquality.kt

@@ -5,16 +5,16 @@
 
 package space.kscience.kmath.testutils
 
-import space.kscience.kmath.structures.DoubleBuffer
+import space.kscience.kmath.structures.Float64Buffer
 import kotlin.jvm.JvmName
 
 /**
- * Simplified [DoubleBuffer] to array comparison
+ * Simplified [Float64Buffer] to array comparison
  */
-public fun DoubleBuffer.contentEquals(vararg doubles: Double): Boolean = array.contentEquals(doubles)
+public fun Float64Buffer.contentEquals(vararg doubles: Double): Boolean = array.contentEquals(doubles)
 
 @JvmName("contentEqualsArray")
-public infix fun DoubleBuffer.contentEquals(otherArray: DoubleArray): Boolean = array.contentEquals(otherArray)
+public infix fun Float64Buffer.contentEquals(otherArray: DoubleArray): Boolean = array.contentEquals(otherArray)
 
 @JvmName("contentEqualsBuffer")
-public infix fun DoubleBuffer.contentEquals(otherBuffer: DoubleBuffer): Boolean = array.contentEquals(otherBuffer.array)
+public infix fun Float64Buffer.contentEquals(otherBuffer: Float64Buffer): Boolean = array.contentEquals(otherBuffer.array)