Merge branch 'dev' into kotlin/1.9.20

# Conflicts:
#	build.gradle.kts

CHANGELOG.md

@@ -3,14 +3,21 @@
 ## Unreleased
 
 ### Added
+- Integer division algebras
+- Float32 geometries
 
 ### Changed
+- Default naming for algebra and buffers now uses IntXX/FloatXX notation instead of Java types.
+- Remove unnecessary inlines in basic algebras.
+- QuaternionField -> QuaternionAlgebra and does not implement `Field` anymore since it is non-commutative
+- kmath-geometry is split into `euclidean2d` and `euclidean3d`
 
 ### Deprecated
 
 ### Removed
 
 ### Fixed
+- Median statistics
 
 ### Security
 

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

@@ -11,7 +11,7 @@ import kotlinx.benchmark.Scope
 import kotlinx.benchmark.State
 import space.kscience.kmath.UnstableKMathAPI
 import space.kscience.kmath.expressions.*
-import space.kscience.kmath.operations.DoubleField
+import space.kscience.kmath.operations.Float64Field
 import space.kscience.kmath.operations.bindSymbol
 import space.kscience.kmath.operations.invoke
 import kotlin.math.sin
@@ -84,7 +84,7 @@ class ExpressionsInterpretersBenchmark {
         private val x by symbol
         private const val times = 1_000_000
 
-        private val functional = DoubleField.expression {
+        private val functional = Float64Field.expression {
             val x = bindSymbol(Symbol.x)
             x * number(2.0) + 2.0 / x - 16.0 / sin(x)
         }
@@ -93,10 +93,10 @@ class ExpressionsInterpretersBenchmark {
             x * 2.0 + number(2.0) / x - number(16.0) / sin(x)
         }
 
-        private val mst = node.toExpression(DoubleField)
+        private val mst = node.toExpression(Float64Field)
         @OptIn(UnstableKMathAPI::class)
-        private val wasm = node.wasmCompileToExpression(DoubleField)
-        private val estree = node.estreeCompileToExpression(DoubleField)
+        private val wasm = node.wasmCompileToExpression(Float64Field)
+        private val estree = node.estreeCompileToExpression(Float64Field)
 
         private val raw = Expression<Double> { args ->
             val x = args[x]!!

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)

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

@@ -13,7 +13,7 @@ import space.kscience.kmath.commons.linear.CMLinearSpace
 import space.kscience.kmath.ejml.EjmlLinearSpaceDDRM
 import space.kscience.kmath.linear.invoke
 import space.kscience.kmath.linear.linearSpace
-import space.kscience.kmath.operations.DoubleField
+import space.kscience.kmath.operations.Float64Field
 import space.kscience.kmath.operations.invoke
 import space.kscience.kmath.tensorflow.produceWithTF
 import space.kscience.kmath.tensors.core.DoubleTensorAlgebra
@@ -27,10 +27,10 @@ internal class DotBenchmark {
         const val dim = 1000
 
         //creating invertible matrix
-        val matrix1 = DoubleField.linearSpace.buildMatrix(dim, dim) { _, _ ->
+        val matrix1 = Float64Field.linearSpace.buildMatrix(dim, dim) { _, _ ->
             random.nextDouble()
         }
-        val matrix2 = DoubleField.linearSpace.buildMatrix(dim, dim) { _, _ ->
+        val matrix2 = Float64Field.linearSpace.buildMatrix(dim, dim) { _, _ ->
             random.nextDouble()
         }
 
@@ -45,7 +45,7 @@ internal class DotBenchmark {
     @Benchmark
     fun tfDot(blackhole: Blackhole) {
         blackhole.consume(
-            DoubleField.produceWithTF {
+            Float64Field.produceWithTF {
                 matrix1 dot matrix1
             }
         )
@@ -72,7 +72,7 @@ internal class DotBenchmark {
     }
 
     @Benchmark
-    fun tensorDot(blackhole: Blackhole) = with(DoubleField.tensorAlgebra) {
+    fun tensorDot(blackhole: Blackhole) = with(Float64Field.tensorAlgebra) {
         blackhole.consume(matrix1 dot matrix2)
     }
 
@@ -82,12 +82,12 @@ internal class DotBenchmark {
     }
 
     @Benchmark
-    fun bufferedDot(blackhole: Blackhole) = with(DoubleField.linearSpace) {
+    fun bufferedDot(blackhole: Blackhole) = with(Float64Field.linearSpace) {
         blackhole.consume(matrix1 dot matrix2)
     }
 
     @Benchmark
-    fun doubleDot(blackhole: Blackhole) = with(DoubleField.linearSpace) {
+    fun doubleDot(blackhole: Blackhole) = with(Float64Field.linearSpace) {
         blackhole.consume(matrix1 dot matrix2)
     }
 

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

@@ -12,7 +12,7 @@ import kotlinx.benchmark.State
 import space.kscience.kmath.asm.compileToExpression
 import space.kscience.kmath.expressions.*
 import space.kscience.kmath.operations.Algebra
-import space.kscience.kmath.operations.DoubleField
+import space.kscience.kmath.operations.Float64Field
 import space.kscience.kmath.operations.bindSymbol
 import space.kscience.kmath.operations.invoke
 import kotlin.math.sin
@@ -100,7 +100,7 @@ internal class ExpressionsInterpretersBenchmark {
         private val x by symbol
         private const val times = 1_000_000
 
-        private val functional = DoubleField.expression {
+        private val functional = Float64Field.expression {
             val x = bindSymbol(Symbol.x)
             x * number(2.0) + 2.0 / x - 16.0 / sin(x)
         }
@@ -109,12 +109,12 @@ internal class ExpressionsInterpretersBenchmark {
             x * 2.0 + number(2.0) / x - number(16.0) / sin(x)
         }
 
-        private val mst = node.toExpression(DoubleField)
+        private val mst = node.toExpression(Float64Field)
 
-        private val asmPrimitive = node.compileToExpression(DoubleField)
+        private val asmPrimitive = node.compileToExpression(Float64Field)
         private val xIdx = asmPrimitive.indexer.indexOf(x)
 
-        private val asmGeneric = node.compileToExpression(DoubleField as Algebra<Double>)
+        private val asmGeneric = node.compileToExpression(Float64Field as Algebra<Double>)
 
         private val raw = Expression<Double> { args ->
             val x = args[x]!!

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

@@ -11,7 +11,7 @@ import org.openjdk.jmh.annotations.Scope
 import org.openjdk.jmh.annotations.State
 import space.kscience.kmath.jafama.JafamaDoubleField
 import space.kscience.kmath.jafama.StrictJafamaDoubleField
-import space.kscience.kmath.operations.DoubleField
+import space.kscience.kmath.operations.Float64Field
 import space.kscience.kmath.operations.invoke
 import kotlin.contracts.InvocationKind
 import kotlin.contracts.contract
@@ -26,7 +26,7 @@ internal class JafamaBenchmark {
 
     @Benchmark
     fun core(blackhole: Blackhole) = invokeBenchmarks(blackhole) { x ->
-        DoubleField { x * power(x, 4) * exp(x) / cos(x) + sin(x) }
+        Float64Field { x * power(x, 4) * exp(x) / cos(x) + sin(x) }
     }
 
     @Benchmark

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

@@ -16,7 +16,7 @@ import org.jetbrains.kotlinx.multik.ndarray.data.DataType
 import space.kscience.kmath.UnsafeKMathAPI
 import space.kscience.kmath.nd.*
 import space.kscience.kmath.nd4j.nd4j
-import space.kscience.kmath.operations.DoubleField
+import space.kscience.kmath.operations.Float64Field
 import space.kscience.kmath.tensors.core.DoubleTensor
 import space.kscience.kmath.tensors.core.one
 import space.kscience.kmath.tensors.core.tensorAlgebra
@@ -86,9 +86,9 @@ internal class NDFieldBenchmark {
         private const val dim = 1000
         private const val n = 100
         private val shape = ShapeND(dim, dim)
-        private val specializedField = DoubleField.ndAlgebra
-        private val genericField = BufferedFieldOpsND(DoubleField)
-        private val nd4jField = DoubleField.nd4j
-        private val viktorField = DoubleField.viktorAlgebra
+        private val specializedField = Float64Field.ndAlgebra
+        private val genericField = BufferedFieldOpsND(Float64Field)
+        private val nd4jField = Float64Field.nd4j
+        private val viktorField = Float64Field.viktorAlgebra
     }
 }

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

@@ -12,7 +12,7 @@ import kotlinx.benchmark.State
 import space.kscience.kmath.linear.linearSpace
 import space.kscience.kmath.linear.matrix
 import space.kscience.kmath.linear.symmetric
-import space.kscience.kmath.operations.DoubleField
+import space.kscience.kmath.operations.Float64Field
 import space.kscience.kmath.tensors.core.symEigJacobi
 import space.kscience.kmath.tensors.core.symEigSvd
 import space.kscience.kmath.tensors.core.tensorAlgebra
@@ -24,7 +24,7 @@ internal class TensorAlgebraBenchmark {
         private val random = Random(12224)
         private const val dim = 30
 
-        private val matrix = DoubleField.linearSpace.matrix(dim, dim).symmetric { _, _ -> random.nextDouble() }
+        private val matrix = Float64Field.linearSpace.matrix(dim, dim).symmetric { _, _ -> random.nextDouble() }
     }
 
     @Benchmark

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

@@ -14,7 +14,7 @@ import space.kscience.kmath.nd.ShapeND
 import space.kscience.kmath.nd.StructureND
 import space.kscience.kmath.nd.ndAlgebra
 import space.kscience.kmath.nd.one
-import space.kscience.kmath.operations.DoubleField
+import space.kscience.kmath.operations.Float64Field
 import space.kscience.kmath.viktor.ViktorFieldND
 
 @State(Scope.Benchmark)
@@ -52,7 +52,7 @@ internal class ViktorBenchmark {
         private val shape = ShapeND(dim, dim)
 
         // automatically build context most suited for given type.
-        private val doubleField = DoubleField.ndAlgebra
+        private val doubleField = Float64Field.ndAlgebra
         private val viktorField = ViktorFieldND(dim, dim)
     }
 }

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

@@ -13,7 +13,7 @@ import org.jetbrains.bio.viktor.F64Array
 import space.kscience.kmath.nd.ShapeND
 import space.kscience.kmath.nd.ndAlgebra
 import space.kscience.kmath.nd.one
-import space.kscience.kmath.operations.DoubleField
+import space.kscience.kmath.operations.Float64Field
 import space.kscience.kmath.viktor.ViktorFieldND
 
 @State(Scope.Benchmark)
@@ -52,7 +52,7 @@ internal class ViktorLogBenchmark {
         private val shape = ShapeND(dim, dim)
 
         // automatically build context most suited for given type.
-        private val doubleField = DoubleField.ndAlgebra
+        private val doubleField = Float64Field.ndAlgebra
         private val viktorField = ViktorFieldND(dim, dim)
     }
 }

build.gradle.kts

@@ -1,3 +1,4 @@
+import space.kscience.gradle.isInDevelopment
 import space.kscience.gradle.useApache2Licence
 import space.kscience.gradle.useSPCTeam
 
@@ -14,7 +15,7 @@ allprojects {
     }
 
     group = "space.kscience"
-    version = "0.3.2-dev-1"
+    version = "0.4.0-dev-2"
 }
 
 subprojects {
@@ -63,10 +64,17 @@ ksciencePublish {
         useApache2Licence()
         useSPCTeam()
     }
-    repository("spc","https://maven.sciprog.center/kscience")
+    github("kmath", "SciProgCentre")
+    space(
+        if (isInDevelopment) {
+            "https://maven.pkg.jetbrains.space/spc/p/sci/dev"
+        } else {
+            "https://maven.pkg.jetbrains.space/spc/p/sci/maven"
+        }
+    )
     sonatype("https://oss.sonatype.org")
 }
 
 apiValidation.nonPublicMarkers.add("space.kscience.kmath.UnstableKMathAPI")
 
-val multikVersion by extra("0.2.2")
+val multikVersion by extra("0.2.0")

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("Float", "FloatField", "FMatrix", "FMatrixRMaj", "FMatrixRMaj", "FDRM", "FDRM", true)
+        it.appendEjmlLinearSpace("Double", "Float64Field", "DMatrix", "DMatrixRMaj", "DMatrixRMaj", "DDRM", "DDRM", 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/ast/expressions.kt

@@ -8,13 +8,13 @@ package space.kscience.kmath.ast
 import space.kscience.kmath.asm.compileToExpression
 import space.kscience.kmath.expressions.MstExtendedField
 import space.kscience.kmath.expressions.Symbol.Companion.x
-import space.kscience.kmath.operations.DoubleField
+import space.kscience.kmath.operations.Float64Field
 import space.kscience.kmath.operations.invoke
 
 fun main() {
     val expr = MstExtendedField {
         x * 2.0 + number(2.0) / x - number(16.0) + asinh(x) / sin(x)
-    }.compileToExpression(DoubleField)
+    }.compileToExpression(Float64Field)
 
     val m = DoubleArray(expr.indexer.symbols.size)
     val xIdx = expr.indexer.indexOf(x)

examples/src/main/kotlin/space/kscience/kmath/ast/kotlingradSupport.kt

@@ -5,12 +5,12 @@
 
 package space.kscience.kmath.ast
 
+import space.kscience.kmath.expressions.Symbol.Companion.x
 import space.kscience.kmath.expressions.derivative
 import space.kscience.kmath.expressions.invoke
-import space.kscience.kmath.expressions.Symbol.Companion.x
 import space.kscience.kmath.expressions.toExpression
 import space.kscience.kmath.kotlingrad.toKotlingradExpression
-import space.kscience.kmath.operations.DoubleField
+import space.kscience.kmath.operations.Float64Field
 
 /**
  * In this example, *x<sup>2</sup> &minus; 4 x &minus; 44* function is differentiated with Kotlin∇, and the
@@ -19,9 +19,9 @@ import space.kscience.kmath.operations.DoubleField
 fun main() {
     val actualDerivative = "x^2-4*x-44"
         .parseMath()
-        .toKotlingradExpression(DoubleField)
+        .toKotlingradExpression(Float64Field)
         .derivative(x)
 
-    val expectedDerivative = "2*x-4".parseMath().toExpression(DoubleField)
+    val expectedDerivative = "2*x-4".parseMath().toExpression(Float64Field)
     check(actualDerivative(x to 123.0) == expectedDerivative(x to 123.0))
 }

examples/src/main/kotlin/space/kscience/kmath/ast/symjaSupport.kt

@@ -9,7 +9,7 @@ import space.kscience.kmath.expressions.Symbol.Companion.x
 import space.kscience.kmath.expressions.derivative
 import space.kscience.kmath.expressions.invoke
 import space.kscience.kmath.expressions.toExpression
-import space.kscience.kmath.operations.DoubleField
+import space.kscience.kmath.operations.Float64Field
 import space.kscience.kmath.symja.toSymjaExpression
 
 /**
@@ -19,9 +19,9 @@ import space.kscience.kmath.symja.toSymjaExpression
 fun main() {
     val actualDerivative = "x^2-4*x-44"
         .parseMath()
-        .toSymjaExpression(DoubleField)
+        .toSymjaExpression(Float64Field)
         .derivative(x)
 
-    val expectedDerivative = "2*x-4".parseMath().toExpression(DoubleField)
+    val expectedDerivative = "2*x-4".parseMath().toExpression(Float64Field)
     check(actualDerivative(x to 123.0) == expectedDerivative(x to 123.0))
 }

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

@@ -13,7 +13,7 @@ import space.kscience.kmath.complex.algebra
 import space.kscience.kmath.integration.gaussIntegrator
 import space.kscience.kmath.integration.integrate
 import space.kscience.kmath.integration.value
-import space.kscience.kmath.operations.DoubleField
+import space.kscience.kmath.operations.Float64Field
 import kotlin.math.pow
 
 fun main() {
@@ -21,7 +21,7 @@ fun main() {
     val function: Function1D<Double> = { x -> 3 * x.pow(2) + 2 * x + 1 }
 
     //get the result of the integration
-    val result = DoubleField.gaussIntegrator.integrate(0.0..10.0, function = function)
+    val result = Float64Field.gaussIntegrator.integrate(0.0..10.0, function = function)
 
     //the value is nullable because in some cases the integration could not succeed
     println(result.value)

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

@@ -7,8 +7,8 @@ package space.kscience.kmath.functions
 
 import space.kscience.kmath.interpolation.SplineInterpolator
 import space.kscience.kmath.interpolation.interpolatePolynomials
-import space.kscience.kmath.operations.DoubleField
-import space.kscience.kmath.structures.DoubleBuffer
+import space.kscience.kmath.operations.Float64Field
+import space.kscience.kmath.structures.Float64Buffer
 import space.kscience.plotly.Plotly
 import space.kscience.plotly.UnstablePlotlyAPI
 import space.kscience.plotly.makeFile
@@ -25,10 +25,10 @@ fun main() {
     }
 
     val polynomial: PiecewisePolynomial<Double> = SplineInterpolator(
-        DoubleField, ::DoubleBuffer
+        Float64Field, ::Float64Buffer
     ).interpolatePolynomials(data)
 
-    val function = polynomial.asFunction(DoubleField, 0.0)
+    val function = polynomial.asFunction(Float64Field, 0.0)
 
     val cmInterpolate = org.apache.commons.math3.analysis.interpolation.SplineInterpolator().interpolate(
         data.map { it.first }.toDoubleArray(),

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

@@ -7,7 +7,7 @@ package space.kscience.kmath.functions
 
 import space.kscience.kmath.interpolation.interpolatePolynomials
 import space.kscience.kmath.interpolation.splineInterpolator
-import space.kscience.kmath.operations.DoubleField
+import space.kscience.kmath.operations.Float64Field
 import space.kscience.kmath.real.map
 import space.kscience.kmath.real.step
 import space.kscience.plotly.Plotly
@@ -28,9 +28,9 @@ fun main() {
     val xs = 0.0..100.0 step 0.5
     val ys = xs.map(function)
 
-    val polynomial: PiecewisePolynomial<Double> = DoubleField.splineInterpolator.interpolatePolynomials(xs, ys)
+    val polynomial: PiecewisePolynomial<Double> = Float64Field.splineInterpolator.interpolatePolynomials(xs, ys)
 
-    val polyFunction = polynomial.asFunction(DoubleField, 0.0)
+    val polyFunction = polynomial.asFunction(Float64Field, 0.0)
 
     Plotly.plot {
         scatter {

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
@@ -15,13 +15,13 @@ import space.kscience.kmath.viktor.ViktorStructureND
 import space.kscience.kmath.viktor.viktorAlgebra
 
 fun main() {
-    val viktorStructure: ViktorStructureND = DoubleField.viktorAlgebra.structureND(ShapeND(2, 2)) { (i, j) ->
+    val viktorStructure: ViktorStructureND = Float64Field.viktorAlgebra.structureND(ShapeND(2, 2)) { (i, j) ->
         if (i == j) 2.0 else 0.0
     }
 
     val cmMatrix: Structure2D<Double> = CMLinearSpace.matrix(2, 2)(0.0, 1.0, 0.0, 3.0)
 
-    val res: DoubleBufferND = DoubleField.ndAlgebra {
+    val res: Float64BufferND = Float64Field.ndAlgebra {
         exp(viktorStructure) + 2.0 * cmMatrix
     }
 

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

@@ -13,7 +13,7 @@ import space.kscience.kmath.nd.StructureND
 import space.kscience.kmath.nd.as2D
 import space.kscience.kmath.nd.ndAlgebra
 import space.kscience.kmath.nd.structureND
-import space.kscience.kmath.operations.DoubleField
+import space.kscience.kmath.operations.Float64Field
 import space.kscience.kmath.operations.invoke
 import kotlin.system.measureTimeMillis
 
@@ -21,7 +21,7 @@ fun main() {
     val dim = 1000
     val n = 1000
 
-    val realField = DoubleField.ndAlgebra(dim, dim)
+    val realField = Float64Field.ndAlgebra(dim, dim)
     val complexField: ComplexFieldND = ComplexField.ndAlgebra(dim, dim)
 
     val realTime = measureTimeMillis {

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

@@ -10,7 +10,7 @@ import kotlinx.coroutines.GlobalScope
 import org.nd4j.linalg.factory.Nd4j
 import space.kscience.kmath.nd.*
 import space.kscience.kmath.nd4j.nd4j
-import space.kscience.kmath.operations.DoubleField
+import space.kscience.kmath.operations.Float64Field
 import space.kscience.kmath.operations.invoke
 import space.kscience.kmath.viktor.ViktorFieldND
 import kotlin.contracts.InvocationKind
@@ -33,15 +33,15 @@ fun main() {
 
 
     // specialized nd-field for Double. It works as generic Double field as well.
-    val doubleField = DoubleField.ndAlgebra
+    val doubleField = Float64Field.ndAlgebra
     //A generic field. It should be used for objects, not primitives.
-    val genericField = BufferedFieldOpsND(DoubleField)
+    val genericField = BufferedFieldOpsND(Float64Field)
     // Nd4j specialized field.
-    val nd4jField = DoubleField.nd4j
+    val nd4jField = Float64Field.nd4j
     //viktor field
     val viktorField = ViktorFieldND(dim, dim)
     //parallel processing based on Java Streams
-    val parallelField = DoubleField.ndStreaming(dim, dim)
+    val parallelField = Float64Field.ndStreaming(dim, dim)
 
     measureAndPrint("Boxing addition") {
         genericField {

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

@@ -7,8 +7,8 @@ package space.kscience.kmath.structures
 
 import space.kscience.kmath.PerformancePitfall
 import space.kscience.kmath.nd.*
-import space.kscience.kmath.operations.DoubleField
 import space.kscience.kmath.operations.ExtendedField
+import space.kscience.kmath.operations.Float64Field
 import space.kscience.kmath.operations.NumbersAddOps
 import java.util.*
 import java.util.stream.IntStream
@@ -17,12 +17,12 @@ import java.util.stream.IntStream
  * A demonstration implementation of NDField over Real using Java [java.util.stream.DoubleStream] for parallel
  * execution.
  */
-class StreamDoubleFieldND(override val shape: ShapeND) : FieldND<Double, DoubleField>,
+class StreamDoubleFieldND(override val shape: ShapeND) : FieldND<Double, Float64Field>,
     NumbersAddOps<StructureND<Double>>,
     ExtendedField<StructureND<Double>> {
 
     private val strides = ColumnStrides(shape)
-    override val elementAlgebra: DoubleField get() = DoubleField
+    override val elementAlgebra: Float64Field get() = Float64Field
     override val zero: BufferND<Double> by lazy { structureND(shape) { zero } }
     override val one: BufferND<Double> by lazy { structureND(shape) { one } }
 
@@ -32,21 +32,21 @@ class StreamDoubleFieldND(override val shape: ShapeND) : FieldND<Double, DoubleF
     }
 
     @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
-            else -> DoubleBuffer(strides.linearSize) { offset -> get(strides.index(offset)) }
+            this is BufferND && indices == this@StreamDoubleFieldND.strides -> this.buffer as Float64Buffer
+            else -> Float64Buffer(strides.linearSize) { offset -> get(strides.index(offset)) }
         }
 
-    override fun structureND(shape: ShapeND, initializer: DoubleField.(IntArray) -> Double): BufferND<Double> {
+    override fun structureND(shape: ShapeND, initializer: Float64Field.(IntArray) -> Double): BufferND<Double> {
         val array = IntStream.range(0, strides.linearSize).parallel().mapToDouble { offset ->
             val index = strides.index(offset)
-            DoubleField.initializer(index)
+            Float64Field.initializer(index)
         }.toArray()
 
         return BufferND(strides, array.asBuffer())
@@ -54,18 +54,18 @@ class StreamDoubleFieldND(override val shape: ShapeND) : FieldND<Double, DoubleF
 
     @OptIn(PerformancePitfall::class)
     override fun StructureND<Double>.map(
-        transform: DoubleField.(Double) -> Double,
+        transform: Float64Field.(Double) -> Double,
     ): BufferND<Double> {
-        val array = Arrays.stream(buffer.array).parallel().map { DoubleField.transform(it) }.toArray()
+        val array = Arrays.stream(buffer.array).parallel().map { Float64Field.transform(it) }.toArray()
         return BufferND(strides, array.asBuffer())
     }
 
     @OptIn(PerformancePitfall::class)
     override fun StructureND<Double>.mapIndexed(
-        transform: DoubleField.(index: IntArray, Double) -> Double,
+        transform: Float64Field.(index: IntArray, Double) -> Double,
     ): BufferND<Double> {
         val array = IntStream.range(0, strides.linearSize).parallel().mapToDouble { offset ->
-            DoubleField.transform(
+            Float64Field.transform(
                 strides.index(offset),
                 buffer.array[offset]
             )
@@ -78,10 +78,10 @@ class StreamDoubleFieldND(override val shape: ShapeND) : FieldND<Double, DoubleF
     override fun zip(
         left: StructureND<Double>,
         right: StructureND<Double>,
-        transform: DoubleField.(Double, Double) -> Double,
+        transform: Float64Field.(Double, Double) -> Double,
     ): BufferND<Double> {
         val array = IntStream.range(0, strides.linearSize).parallel().mapToDouble { offset ->
-            DoubleField.transform(left.buffer.array[offset], right.buffer.array[offset])
+            Float64Field.transform(left.buffer.array[offset], right.buffer.array[offset])
         }.toArray()
         return BufferND(strides, array.asBuffer())
     }
@@ -111,4 +111,4 @@ class StreamDoubleFieldND(override val shape: ShapeND) : FieldND<Double, DoubleF
     override fun atanh(arg: StructureND<Double>): BufferND<Double> = arg.map { atanh(it) }
 }
 
-fun DoubleField.ndStreaming(vararg shape: Int): StreamDoubleFieldND = StreamDoubleFieldND(ShapeND(shape))
+fun Float64Field.ndStreaming(vararg shape: Int): StreamDoubleFieldND = StreamDoubleFieldND(ShapeND(shape))

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
         }

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

@@ -5,7 +5,7 @@
 
 package space.kscience.kmath.structures
 
-import space.kscience.kmath.operations.DoubleField
+import space.kscience.kmath.operations.Float64Field
 import space.kscience.kmath.operations.buffer
 import space.kscience.kmath.operations.bufferAlgebra
 import space.kscience.kmath.operations.withSize
@@ -17,7 +17,7 @@ inline fun <reified R : Any> MutableBuffer.Companion.same(
 
 
 fun main() {
-    with(DoubleField.bufferAlgebra.withSize(5)) {
+    with(Float64Field.bufferAlgebra.withSize(5)) {
         println(number(2.0) + buffer(1, 2, 3, 4, 5))
     }
 }

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

@@ -0,0 +1,90 @@
+/*
+ * Copyright 2018-2023 KMath contributors.
+ * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
+ */
+
+package space.kscience.kmath.tensors.LevenbergMarquardt.StaticLm
+
+import space.kscience.kmath.nd.ShapeND
+import space.kscience.kmath.nd.as2D
+import space.kscience.kmath.nd.component1
+import space.kscience.kmath.tensors.LevenbergMarquardt.funcDifficultForLm
+import space.kscience.kmath.tensors.core.BroadcastDoubleTensorAlgebra
+import space.kscience.kmath.tensors.core.BroadcastDoubleTensorAlgebra.div
+import space.kscience.kmath.tensors.core.DoubleTensorAlgebra
+import space.kscience.kmath.tensors.core.LMInput
+import space.kscience.kmath.tensors.core.levenbergMarquardt
+import kotlin.math.roundToInt
+
+fun main() {
+    val NData = 200
+    var t_example = DoubleTensorAlgebra.ones(ShapeND(intArrayOf(NData, 1))).as2D()
+    for (i in 0 until NData) {
+        t_example[i, 0] = t_example[i, 0] * (i + 1) - 104
+    }
+
+    val Nparams = 15
+    var p_example = DoubleTensorAlgebra.ones(ShapeND(intArrayOf(Nparams, 1))).as2D()
+    for (i in 0 until Nparams) {
+        p_example[i, 0] = p_example[i, 0] + i - 25
+    }
+
+    val exampleNumber = 1
+
+    var y_hat =  funcDifficultForLm(t_example, p_example, exampleNumber)
+
+    var p_init = DoubleTensorAlgebra.zeros(ShapeND(intArrayOf(Nparams, 1))).as2D()
+    for (i in 0 until Nparams) {
+        p_init[i, 0] = (p_example[i, 0] + 0.9)
+    }
+
+    var t = t_example
+    val y_dat = y_hat
+    val weight = 1.0 / Nparams * 1.0 - 0.085
+    val dp = BroadcastDoubleTensorAlgebra.fromArray(
+        ShapeND(intArrayOf(1, 1)), DoubleArray(1) { -0.01 }
+    ).as2D()
+    var p_min = DoubleTensorAlgebra.ones(ShapeND(intArrayOf(Nparams, 1)))
+    p_min = p_min.div(1.0 / -50.0)
+    val p_max = DoubleTensorAlgebra.ones(ShapeND(intArrayOf(Nparams, 1)))
+    p_min = p_min.div(1.0 / 50.0)
+    val opts = doubleArrayOf(3.0, 10000.0, 1e-6, 1e-6, 1e-6, 1e-6, 1e-2, 11.0, 9.0, 1.0)
+//    val opts = doubleArrayOf(3.0, 10000.0, 1e-6, 1e-6, 1e-6, 1e-6, 1e-3, 11.0, 9.0, 1.0)
+
+    val inputData = LMInput(::funcDifficultForLm,
+        p_init.as2D(),
+        t,
+        y_dat,
+        weight,
+        dp,
+        p_min.as2D(),
+        p_max.as2D(),
+        opts[1].toInt(),
+        doubleArrayOf(opts[2], opts[3], opts[4], opts[5]),
+        doubleArrayOf(opts[6], opts[7], opts[8]),
+        opts[9].toInt(),
+        10,
+        1)
+
+    val result = DoubleTensorAlgebra.levenbergMarquardt(inputData)
+
+    println("Parameters:")
+    for (i in 0 until result.resultParameters.shape.component1()) {
+        val x = (result.resultParameters[i, 0] * 10000).roundToInt() / 10000.0
+        print("$x ")
+    }
+    println()
+
+    println("Y true and y received:")
+    var y_hat_after =  funcDifficultForLm(t_example, result.resultParameters, exampleNumber)
+    for (i in 0 until y_hat.shape.component1()) {
+        val x = (y_hat[i, 0] * 10000).roundToInt() / 10000.0
+        val y = (y_hat_after[i, 0] * 10000).roundToInt() / 10000.0
+        println("$x $y")
+    }
+
+    println("Сhi_sq:")
+    println(result.resultChiSq)
+    println("Number of iterations:")
+    println(result.iterations)
+}

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

@@ -0,0 +1,57 @@
+/*
+ * Copyright 2018-2023 KMath contributors.
+ * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
+ */
+
+package space.kscience.kmath.tensors.LevenbergMarquardt.StaticLm
+
+import space.kscience.kmath.nd.ShapeND
+import space.kscience.kmath.nd.as2D
+import space.kscience.kmath.nd.component1
+import space.kscience.kmath.tensors.LevenbergMarquardt.funcDifficultForLm
+import space.kscience.kmath.tensors.LevenbergMarquardt.funcEasyForLm
+import space.kscience.kmath.tensors.LevenbergMarquardt.getStartDataForFuncEasy
+import space.kscience.kmath.tensors.core.DoubleTensorAlgebra
+import space.kscience.kmath.tensors.core.LMInput
+import space.kscience.kmath.tensors.core.levenbergMarquardt
+import kotlin.math.roundToInt
+
+fun main() {
+    val startedData = getStartDataForFuncEasy()
+    val inputData = LMInput(::funcEasyForLm,
+        DoubleTensorAlgebra.ones(ShapeND(intArrayOf(4, 1))).as2D(),
+        startedData.t,
+        startedData.y_dat,
+        startedData.weight,
+        startedData.dp,
+        startedData.p_min,
+        startedData.p_max,
+        startedData.opts[1].toInt(),
+        doubleArrayOf(startedData.opts[2], startedData.opts[3], startedData.opts[4], startedData.opts[5]),
+        doubleArrayOf(startedData.opts[6], startedData.opts[7], startedData.opts[8]),
+        startedData.opts[9].toInt(),
+        10,
+        startedData.example_number)
+
+    val result = DoubleTensorAlgebra.levenbergMarquardt(inputData)
+
+    println("Parameters:")
+    for (i in 0 until result.resultParameters.shape.component1()) {
+        val x = (result.resultParameters[i, 0] * 10000).roundToInt() / 10000.0
+        print("$x ")
+    }
+    println()
+
+    println("Y true and y received:")
+    var y_hat_after =  funcDifficultForLm(startedData.t, result.resultParameters, startedData.example_number)
+    for (i in 0 until startedData.y_dat.shape.component1()) {
+        val x = (startedData.y_dat[i, 0] * 10000).roundToInt() / 10000.0
+        val y = (y_hat_after[i, 0] * 10000).roundToInt() / 10000.0
+        println("$x $y")
+    }
+
+    println("Сhi_sq:")
+    println(result.resultChiSq)
+    println("Number of iterations:")
+    println(result.iterations)
+}

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

@@ -0,0 +1,88 @@
+/*
+ * Copyright 2018-2023 KMath contributors.
+ * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
+ */
+
+package space.kscience.kmath.tensors.LevenbergMarquardt.StaticLm
+
+import space.kscience.kmath.nd.ShapeND
+import space.kscience.kmath.nd.as2D
+import space.kscience.kmath.nd.component1
+import space.kscience.kmath.tensors.LevenbergMarquardt.funcMiddleForLm
+import space.kscience.kmath.tensors.core.BroadcastDoubleTensorAlgebra
+import space.kscience.kmath.tensors.core.BroadcastDoubleTensorAlgebra.div
+import space.kscience.kmath.tensors.core.DoubleTensorAlgebra
+import space.kscience.kmath.tensors.core.LMInput
+import space.kscience.kmath.tensors.core.levenbergMarquardt
+import kotlin.math.roundToInt
+fun main() {
+    val NData = 100
+    var t_example = DoubleTensorAlgebra.ones(ShapeND(intArrayOf(NData, 1))).as2D()
+    for (i in 0 until NData) {
+        t_example[i, 0] = t_example[i, 0] * (i + 1)
+    }
+
+    val Nparams = 20
+    var p_example = DoubleTensorAlgebra.ones(ShapeND(intArrayOf(Nparams, 1))).as2D()
+    for (i in 0 until Nparams) {
+        p_example[i, 0] = p_example[i, 0] + i - 25
+    }
+
+    val exampleNumber = 1
+
+    var y_hat =  funcMiddleForLm(t_example, p_example, exampleNumber)
+
+    var p_init = DoubleTensorAlgebra.zeros(ShapeND(intArrayOf(Nparams, 1))).as2D()
+    for (i in 0 until Nparams) {
+        p_init[i, 0] = (p_example[i, 0] + 0.9)
+    }
+
+    var t = t_example
+    val y_dat = y_hat
+    val weight = 1.0
+    val dp = BroadcastDoubleTensorAlgebra.fromArray(
+        ShapeND(intArrayOf(1, 1)), DoubleArray(1) { -0.01 }
+    ).as2D()
+    var p_min = DoubleTensorAlgebra.ones(ShapeND(intArrayOf(Nparams, 1)))
+    p_min = p_min.div(1.0 / -50.0)
+    val p_max = DoubleTensorAlgebra.ones(ShapeND(intArrayOf(Nparams, 1)))
+    p_min = p_min.div(1.0 / 50.0)
+    val opts = doubleArrayOf(3.0, 7000.0, 1e-5, 1e-5, 1e-5, 1e-5, 1e-5, 11.0, 9.0, 1.0)
+
+    val inputData = LMInput(::funcMiddleForLm,
+        p_init.as2D(),
+        t,
+        y_dat,
+        weight,
+        dp,
+        p_min.as2D(),
+        p_max.as2D(),
+        opts[1].toInt(),
+        doubleArrayOf(opts[2], opts[3], opts[4], opts[5]),
+        doubleArrayOf(opts[6], opts[7], opts[8]),
+        opts[9].toInt(),
+        10,
+        1)
+
+    val result = DoubleTensorAlgebra.levenbergMarquardt(inputData)
+
+    println("Parameters:")
+    for (i in 0 until result.resultParameters.shape.component1()) {
+        val x = (result.resultParameters[i, 0] * 10000).roundToInt() / 10000.0
+        print("$x ")
+    }
+    println()
+
+
+    var y_hat_after =  funcMiddleForLm(t_example, result.resultParameters, exampleNumber)
+    for (i in 0 until y_hat.shape.component1()) {
+        val x = (y_hat[i, 0] * 10000).roundToInt() / 10000.0
+        val y = (y_hat_after[i, 0] * 10000).roundToInt() / 10000.0
+        println("$x $y")
+    }
+
+    println("Сhi_sq:")
+    println(result.resultChiSq)
+    println("Number of iterations:")
+    println(result.iterations)
+}

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

@@ -0,0 +1,68 @@
+/*
+ * Copyright 2018-2023 KMath contributors.
+ * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
+ */
+
+package space.kscience.kmath.tensors.LevenbergMarquardt.StreamingLm
+
+import kotlinx.coroutines.delay
+import kotlinx.coroutines.flow.*
+import space.kscience.kmath.nd.*
+import space.kscience.kmath.tensors.LevenbergMarquardt.StartDataLm
+import space.kscience.kmath.tensors.core.BroadcastDoubleTensorAlgebra.zeros
+import space.kscience.kmath.tensors.core.DoubleTensorAlgebra
+import space.kscience.kmath.tensors.core.LMInput
+import space.kscience.kmath.tensors.core.levenbergMarquardt
+import kotlin.random.Random
+import kotlin.reflect.KFunction3
+
+fun streamLm(lm_func: (MutableStructure2D<Double>, MutableStructure2D<Double>, Int) -> (MutableStructure2D<Double>),
+             startData: StartDataLm, launchFrequencyInMs: Long, numberOfLaunches: Int): Flow<MutableStructure2D<Double>> = flow{
+
+    var example_number = startData.example_number
+    var p_init = startData.p_init
+    var t = startData.t
+    var y_dat = startData.y_dat
+    val weight = startData.weight
+    val dp = startData.dp
+    val p_min = startData.p_min
+    val p_max = startData.p_max
+    val opts = startData.opts
+
+    var steps = numberOfLaunches
+    val isEndless = (steps <= 0)
+
+    val inputData = LMInput(lm_func,
+        p_init,
+        t,
+        y_dat,
+        weight,
+        dp,
+        p_min,
+        p_max,
+        opts[1].toInt(),
+        doubleArrayOf(opts[2], opts[3], opts[4], opts[5]),
+        doubleArrayOf(opts[6], opts[7], opts[8]),
+        opts[9].toInt(),
+        10,
+        example_number)
+
+    while (isEndless || steps > 0) {
+        val result = DoubleTensorAlgebra.levenbergMarquardt(inputData)
+        emit(result.resultParameters)
+        delay(launchFrequencyInMs)
+        inputData.realValues = generateNewYDat(y_dat, 0.1)
+        inputData.startParameters = result.resultParameters
+        if (!isEndless) steps -= 1
+    }
+}
+
+fun generateNewYDat(y_dat: MutableStructure2D<Double>, delta: Double): MutableStructure2D<Double>{
+    val n = y_dat.shape.component1()
+    val y_dat_new = zeros(ShapeND(intArrayOf(n, 1))).as2D()
+    for (i in 0 until n) {
+        val randomEps = Random.nextDouble(delta + delta) - delta
+        y_dat_new[i, 0] = y_dat[i, 0] + randomEps
+    }
+    return y_dat_new
+}

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

@@ -0,0 +1,32 @@
+/*
+ * Copyright 2018-2023 KMath contributors.
+ * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
+ */
+
+package space.kscience.kmath.tensors.LevenbergMarquardt.StreamingLm
+
+import space.kscience.kmath.nd.*
+import space.kscience.kmath.tensors.LevenbergMarquardt.*
+import kotlin.math.roundToInt
+
+suspend fun main(){
+    val startData = getStartDataForFuncDifficult()
+    // Создание потока:
+    val lmFlow = streamLm(::funcDifficultForLm, startData, 0,  100)
+    var initialTime = System.currentTimeMillis()
+    var lastTime: Long
+    val launches = mutableListOf<Long>()
+    // Запуск потока
+    lmFlow.collect { parameters ->
+        lastTime = System.currentTimeMillis()
+        launches.add(lastTime - initialTime)
+        initialTime = lastTime
+        for (i in 0 until parameters.shape.component1()) {
+            val x = (parameters[i, 0] * 10000).roundToInt() / 10000.0
+            print("$x ")
+            if (i == parameters.shape.component1() - 1) println()
+        }
+    }
+
+    println("Average without first is: ${launches.subList(1, launches.size - 1).average()}")
+}

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

@@ -0,0 +1,222 @@
+/*
+ * Copyright 2018-2023 KMath contributors.
+ * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
+ */
+
+package space.kscience.kmath.tensors.LevenbergMarquardt
+
+import space.kscience.kmath.nd.MutableStructure2D
+import space.kscience.kmath.nd.ShapeND
+import space.kscience.kmath.nd.as2D
+import space.kscience.kmath.nd.component1
+import space.kscience.kmath.tensors.core.BroadcastDoubleTensorAlgebra
+import space.kscience.kmath.tensors.core.BroadcastDoubleTensorAlgebra.div
+import space.kscience.kmath.tensors.core.DoubleTensorAlgebra
+import space.kscience.kmath.tensors.core.DoubleTensorAlgebra.Companion.max
+import space.kscience.kmath.tensors.core.DoubleTensorAlgebra.Companion.plus
+import space.kscience.kmath.tensors.core.DoubleTensorAlgebra.Companion.pow
+import space.kscience.kmath.tensors.core.DoubleTensorAlgebra.Companion.times
+import space.kscience.kmath.tensors.core.asDoubleTensor
+
+public data class StartDataLm (
+    var lm_matx_y_dat: MutableStructure2D<Double>,
+    var example_number: Int,
+    var p_init: MutableStructure2D<Double>,
+    var t: MutableStructure2D<Double>,
+    var y_dat: MutableStructure2D<Double>,
+    var weight: Double,
+    var dp: MutableStructure2D<Double>,
+    var p_min: MutableStructure2D<Double>,
+    var p_max: MutableStructure2D<Double>,
+    var consts: MutableStructure2D<Double>,
+    var opts: DoubleArray
+)
+
+fun funcEasyForLm(t: MutableStructure2D<Double>, p: MutableStructure2D<Double>, exampleNumber: Int): MutableStructure2D<Double> {
+    val m = t.shape.component1()
+    var y_hat = DoubleTensorAlgebra.zeros(ShapeND(intArrayOf(m, 1)))
+
+    if (exampleNumber == 1) {
+        y_hat = DoubleTensorAlgebra.exp((t.times(-1.0 / p[1, 0]))).times(p[0, 0]) + t.times(p[2, 0]).times(
+            DoubleTensorAlgebra.exp((t.times(-1.0 / p[3, 0])))
+        )
+    }
+    else if (exampleNumber == 2) {
+        val mt = t.max()
+        y_hat = (t.times(1.0 / mt)).times(p[0, 0]) +
+                (t.times(1.0 / mt)).pow(2).times(p[1, 0]) +
+                (t.times(1.0 / mt)).pow(3).times(p[2, 0]) +
+                (t.times(1.0 / mt)).pow(4).times(p[3, 0])
+    }
+    else if (exampleNumber == 3) {
+        y_hat = DoubleTensorAlgebra.exp((t.times(-1.0 / p[1, 0])))
+            .times(p[0, 0]) + DoubleTensorAlgebra.sin((t.times(1.0 / p[3, 0]))).times(p[2, 0])
+    }
+
+    return y_hat.as2D()
+}
+
+fun funcMiddleForLm(t: MutableStructure2D<Double>, p: MutableStructure2D<Double>, exampleNumber: Int): MutableStructure2D<Double> {
+    val m = t.shape.component1()
+    var y_hat = DoubleTensorAlgebra.zeros(ShapeND(intArrayOf (m, 1)))
+
+    val mt = t.max()
+    for(i in 0 until p.shape.component1()){
+        y_hat += (t.times(1.0 / mt)).times(p[i, 0])
+    }
+
+    for(i in 0 until 5){
+        y_hat = funcEasyForLm(y_hat.as2D(), p, exampleNumber).asDoubleTensor()
+    }
+
+    return y_hat.as2D()
+}
+
+fun funcDifficultForLm(t: MutableStructure2D<Double>, p: MutableStructure2D<Double>, exampleNumber: Int): MutableStructure2D<Double> {
+    val m = t.shape.component1()
+    var y_hat = DoubleTensorAlgebra.zeros(ShapeND(intArrayOf (m, 1)))
+
+    val mt = t.max()
+    for(i in 0 until p.shape.component1()){
+        y_hat = y_hat.plus( (t.times(1.0 / mt)).times(p[i, 0]) )
+    }
+
+    for(i in 0 until 4){
+        y_hat = funcEasyForLm((y_hat.as2D() + t).as2D(), p, exampleNumber).asDoubleTensor()
+    }
+
+    return y_hat.as2D()
+}
+
+
+fun getStartDataForFuncDifficult(): StartDataLm  {
+    val NData = 200
+    var t_example = DoubleTensorAlgebra.ones(ShapeND(intArrayOf(NData, 1))).as2D()
+    for (i in 0 until NData) {
+        t_example[i, 0] = t_example[i, 0] * (i + 1) - 104
+    }
+
+    val Nparams = 15
+    var p_example = DoubleTensorAlgebra.ones(ShapeND(intArrayOf(Nparams, 1))).as2D()
+    for (i in 0 until Nparams) {
+        p_example[i, 0] = p_example[i, 0] + i - 25
+    }
+
+    val exampleNumber = 1
+
+    var y_hat =  funcDifficultForLm(t_example, p_example, exampleNumber)
+
+    var p_init = DoubleTensorAlgebra.zeros(ShapeND(intArrayOf(Nparams, 1))).as2D()
+    for (i in 0 until Nparams) {
+        p_init[i, 0] = (p_example[i, 0] + 0.9)
+    }
+
+    var t = t_example
+    val y_dat = y_hat
+    val weight = 1.0 / Nparams * 1.0 - 0.085
+    val dp = BroadcastDoubleTensorAlgebra.fromArray(
+        ShapeND(intArrayOf(1, 1)), DoubleArray(1) { -0.01 }
+    ).as2D()
+    var p_min = DoubleTensorAlgebra.ones(ShapeND(intArrayOf(Nparams, 1)))
+    p_min = p_min.div(1.0 / -50.0)
+    val p_max = DoubleTensorAlgebra.ones(ShapeND(intArrayOf(Nparams, 1)))
+    p_min = p_min.div(1.0 / 50.0)
+    val consts = BroadcastDoubleTensorAlgebra.fromArray(
+        ShapeND(intArrayOf(1, 1)), doubleArrayOf(0.0)
+    ).as2D()
+    val opts = doubleArrayOf(3.0, 10000.0, 1e-2, 1e-3, 1e-2, 1e-2, 1e-2, 11.0, 9.0, 1.0)
+
+    return StartDataLm(y_dat, 1, p_init, t, y_dat, weight, dp, p_min.as2D(), p_max.as2D(), consts, opts)
+}
+
+fun getStartDataForFuncMiddle(): StartDataLm  {
+    val NData = 100
+    var t_example = DoubleTensorAlgebra.ones(ShapeND(intArrayOf(NData, 1))).as2D()
+    for (i in 0 until NData) {
+        t_example[i, 0] = t_example[i, 0] * (i + 1)
+    }
+
+    val Nparams = 20
+    var p_example = DoubleTensorAlgebra.ones(ShapeND(intArrayOf(Nparams, 1))).as2D()
+    for (i in 0 until Nparams) {
+        p_example[i, 0] = p_example[i, 0] + i - 25
+    }
+
+    val exampleNumber = 1
+
+    var y_hat =  funcMiddleForLm(t_example, p_example, exampleNumber)
+
+    var p_init = DoubleTensorAlgebra.zeros(ShapeND(intArrayOf(Nparams, 1))).as2D()
+    for (i in 0 until Nparams) {
+        p_init[i, 0] = (p_example[i, 0] + 10.0)
+    }
+    var t = t_example
+    val y_dat = y_hat
+    val weight = 1.0
+    val dp = BroadcastDoubleTensorAlgebra.fromArray(
+        ShapeND(intArrayOf(1, 1)), DoubleArray(1) { -0.01 }
+    ).as2D()
+    var p_min = DoubleTensorAlgebra.ones(ShapeND(intArrayOf(Nparams, 1)))
+    p_min = p_min.div(1.0 / -50.0)
+    val p_max = DoubleTensorAlgebra.ones(ShapeND(intArrayOf(Nparams, 1)))
+    p_min = p_min.div(1.0 / 50.0)
+    val consts = BroadcastDoubleTensorAlgebra.fromArray(
+        ShapeND(intArrayOf(1, 1)), doubleArrayOf(0.0)
+    ).as2D()
+    val opts = doubleArrayOf(3.0, 10000.0, 1e-5, 1e-5, 1e-5, 1e-5, 1e-5, 11.0, 9.0, 1.0)
+
+    var example_number = 1
+
+    return StartDataLm(y_dat, example_number, p_init, t, y_dat, weight, dp, p_min.as2D(), p_max.as2D(), consts, opts)
+}
+
+fun getStartDataForFuncEasy(): StartDataLm {
+    val lm_matx_y_dat = doubleArrayOf(
+        19.6594, 18.6096, 17.6792, 17.2747, 16.3065, 17.1458, 16.0467, 16.7023, 15.7809, 15.9807,
+        14.7620, 15.1128, 16.0973, 15.1934, 15.8636, 15.4763, 15.6860, 15.1895, 15.3495, 16.6054,
+        16.2247, 15.9854, 16.1421, 17.0960, 16.7769, 17.1997, 17.2767, 17.5882, 17.5378, 16.7894,
+        17.7648, 18.2512, 18.1581, 16.7037, 17.8475, 17.9081, 18.3067, 17.9632, 18.2817, 19.1427,
+        18.8130, 18.5658, 18.0056, 18.4607, 18.5918, 18.2544, 18.3731, 18.7511, 19.3181, 17.3066,
+        17.9632, 19.0513, 18.7528, 18.2928, 18.5967, 17.8567, 17.7859, 18.4016, 18.9423, 18.4959,
+        17.8000, 18.4251, 17.7829, 17.4645, 17.5221, 17.3517, 17.4637, 17.7563, 16.8471, 17.4558,
+        17.7447, 17.1487, 17.3183, 16.8312, 17.7551, 17.0942, 15.6093, 16.4163, 15.3755, 16.6725,
+        16.2332, 16.2316, 16.2236, 16.5361, 15.3721, 15.3347, 15.5815, 15.6319, 14.4538, 14.6044,
+        14.7665, 13.3718, 15.0587, 13.8320, 14.7873, 13.6824, 14.2579, 14.2154, 13.5818, 13.8157
+    )
+
+    var example_number = 1
+    val p_init = BroadcastDoubleTensorAlgebra.fromArray(
+        ShapeND(intArrayOf(4, 1)), doubleArrayOf(5.0, 2.0, 0.2, 10.0)
+    ).as2D()
+
+    var t = DoubleTensorAlgebra.ones(ShapeND(intArrayOf(100, 1))).as2D()
+    for (i in 0 until 100) {
+        t[i, 0] = t[i, 0] * (i + 1)
+    }
+
+    val y_dat = BroadcastDoubleTensorAlgebra.fromArray(
+        ShapeND(intArrayOf(100, 1)), lm_matx_y_dat
+    ).as2D()
+
+    val weight = 4.0
+
+    val dp = BroadcastDoubleTensorAlgebra.fromArray(
+        ShapeND(intArrayOf(1, 1)), DoubleArray(1) { -0.01 }
+    ).as2D()
+
+    val p_min = BroadcastDoubleTensorAlgebra.fromArray(
+        ShapeND(intArrayOf(4, 1)), doubleArrayOf(-50.0, -20.0, -2.0, -100.0)
+    ).as2D()
+
+    val p_max = BroadcastDoubleTensorAlgebra.fromArray(
+        ShapeND(intArrayOf(4, 1)), doubleArrayOf(50.0, 20.0, 2.0, 100.0)
+    ).as2D()
+
+    val consts = BroadcastDoubleTensorAlgebra.fromArray(
+        ShapeND(intArrayOf(1, 1)), doubleArrayOf(0.0)
+    ).as2D()
+
+    val opts = doubleArrayOf(3.0, 100.0, 1e-3, 1e-3, 1e-1, 1e-1, 1e-2, 11.0, 9.0, 1.0)
+
+    return StartDataLm(y_dat, example_number, p_init, t, y_dat, weight, dp, p_min, p_max, consts, opts)
+}

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

@@ -9,8 +9,8 @@ import space.kscience.kmath.expressions.MstField
 import space.kscience.kmath.expressions.MstRing
 import space.kscience.kmath.expressions.Symbol.Companion.x
 import space.kscience.kmath.expressions.interpret
-import space.kscience.kmath.operations.DoubleField
-import space.kscience.kmath.operations.IntRing
+import space.kscience.kmath.operations.Float64Field
+import space.kscience.kmath.operations.Int32Ring
 import space.kscience.kmath.operations.invoke
 import kotlin.test.Test
 import kotlin.test.assertEquals
@@ -32,8 +32,8 @@ internal class TestCompilerConsistencyWithInterpreter {
         }
 
         assertEquals(
-            mst.interpret(IntRing, x to 3),
-            mst.compile(IntRing, x to 3),
+            mst.interpret(Int32Ring, x to 3),
+            mst.compile(Int32Ring, x to 3),
         )
     }
 
@@ -48,8 +48,8 @@ internal class TestCompilerConsistencyWithInterpreter {
         }
 
         assertEquals(
-            mst.interpret(DoubleField, x to 2.0),
-            mst.compile(DoubleField, x to 2.0),
+            mst.interpret(Float64Field, x to 2.0),
+            mst.compile(Float64Field, x to 2.0),
         )
     }
 }

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

@@ -8,7 +8,7 @@ package space.kscience.kmath.ast
 import space.kscience.kmath.expressions.MstExtendedField
 import space.kscience.kmath.expressions.Symbol.Companion.x
 import space.kscience.kmath.expressions.invoke
-import space.kscience.kmath.operations.DoubleField
+import space.kscience.kmath.operations.Float64Field
 import space.kscience.kmath.operations.invoke
 import kotlin.test.Test
 import kotlin.test.assertEquals
@@ -16,73 +16,73 @@ import kotlin.test.assertEquals
 internal class TestCompilerOperations {
     @Test
     fun testUnaryPlus() = runCompilerTest {
-        val expr = MstExtendedField { +x }.compileToExpression(DoubleField)
+        val expr = MstExtendedField { +x }.compileToExpression(Float64Field)
         assertEquals(2.0, expr(x to 2.0))
     }
 
     @Test
     fun testUnaryMinus() = runCompilerTest {
-        val expr = MstExtendedField { -x }.compileToExpression(DoubleField)
+        val expr = MstExtendedField { -x }.compileToExpression(Float64Field)
         assertEquals(-2.0, expr(x to 2.0))
     }
 
     @Test
     fun testAdd() = runCompilerTest {
-        val expr = MstExtendedField { x + x }.compileToExpression(DoubleField)
+        val expr = MstExtendedField { x + x }.compileToExpression(Float64Field)
         assertEquals(4.0, expr(x to 2.0))
     }
 
     @Test
     fun testSine() = runCompilerTest {
-        val expr = MstExtendedField { sin(x) }.compileToExpression(DoubleField)
+        val expr = MstExtendedField { sin(x) }.compileToExpression(Float64Field)
         assertEquals(0.0, expr(x to 0.0))
     }
 
     @Test
     fun testCosine() = runCompilerTest {
-        val expr = MstExtendedField { cos(x) }.compileToExpression(DoubleField)
+        val expr = MstExtendedField { cos(x) }.compileToExpression(Float64Field)
         assertEquals(1.0, expr(x to 0.0))
     }
 
     @Test
     fun testTangent() = runCompilerTest {
-        val expr = MstExtendedField { tan(x) }.compileToExpression(DoubleField)
+        val expr = MstExtendedField { tan(x) }.compileToExpression(Float64Field)
         assertEquals(0.0, expr(x to 0.0))
     }
 
     @Test
     fun testArcSine() = runCompilerTest {
-        val expr = MstExtendedField { asin(x) }.compileToExpression(DoubleField)
+        val expr = MstExtendedField { asin(x) }.compileToExpression(Float64Field)
         assertEquals(0.0, expr(x to 0.0))
     }
 
     @Test
     fun testArcCosine() = runCompilerTest {
-        val expr = MstExtendedField { acos(x) }.compileToExpression(DoubleField)
+        val expr = MstExtendedField { acos(x) }.compileToExpression(Float64Field)
         assertEquals(0.0, expr(x to 1.0))
     }
 
     @Test
     fun testAreaHyperbolicSine() = runCompilerTest {
-        val expr = MstExtendedField { asinh(x) }.compileToExpression(DoubleField)
+        val expr = MstExtendedField { asinh(x) }.compileToExpression(Float64Field)
         assertEquals(0.0, expr(x to 0.0))
     }
 
     @Test
     fun testSubtract() = runCompilerTest {
-        val expr = MstExtendedField { x - x }.compileToExpression(DoubleField)
+        val expr = MstExtendedField { x - x }.compileToExpression(Float64Field)
         assertEquals(0.0, expr(x to 2.0))
     }
 
     @Test
     fun testDivide() = runCompilerTest {
-        val expr = MstExtendedField { x / x }.compileToExpression(DoubleField)
+        val expr = MstExtendedField { x / x }.compileToExpression(Float64Field)
         assertEquals(1.0, expr(x to 2.0))
     }
 
     @Test
     fun testPower() = runCompilerTest {
-        val expr = MstExtendedField { x pow 2 }.compileToExpression(DoubleField)
+        val expr = MstExtendedField { x pow 2 }.compileToExpression(Float64Field)
         assertEquals(4.0, expr(x to 2.0))
     }
 }

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

@@ -9,8 +9,8 @@ import space.kscience.kmath.expressions.MstRing
 import space.kscience.kmath.expressions.Symbol.Companion.x
 import space.kscience.kmath.expressions.Symbol.Companion.y
 import space.kscience.kmath.expressions.invoke
-import space.kscience.kmath.operations.DoubleField
-import space.kscience.kmath.operations.IntRing
+import space.kscience.kmath.operations.Float64Field
+import space.kscience.kmath.operations.Int32Ring
 import space.kscience.kmath.operations.invoke
 import kotlin.test.Test
 import kotlin.test.assertEquals
@@ -19,25 +19,25 @@ import kotlin.test.assertFailsWith
 internal class TestCompilerVariables {
     @Test
     fun testNoVariables() = runCompilerTest {
-        val expr = "0".parseMath().compileToExpression(DoubleField)
+        val expr = "0".parseMath().compileToExpression(Float64Field)
         assertEquals(0.0, expr(), 0.0001)
     }
 
     @Test
     fun testOneVariable() = runCompilerTest {
-        val expr = MstRing { x }.compileToExpression(IntRing)
+        val expr = MstRing { x }.compileToExpression(Int32Ring)
         assertEquals(1, expr(x to 1))
     }
 
     @Test
     fun testTwoVariables() = runCompilerTest {
-        val expr = "y+x/y+x".parseMath().compileToExpression(DoubleField)
+        val expr = "y+x/y+x".parseMath().compileToExpression(Float64Field)
         assertEquals(8.0, expr(x to 4.0, y to 2.0))
     }
 
     @Test
     fun testUndefinedVariableFails() = runCompilerTest {
-        val expr = MstRing { x }.compileToExpression(IntRing)
+        val expr = MstRing { x }.compileToExpression(Int32Ring)
         assertFailsWith<NoSuchElementException> { expr() }
     }
 }

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.DoubleField
-import space.kscience.kmath.operations.IntRing
+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
@@ -17,36 +17,36 @@ internal class TestFolding {
     @Test
     fun foldUnary() = assertEquals(
         -1,
-        ("-(1)".parseMath().evaluateConstants(IntRing) as? TypedMst.Constant<Int> ?: fail()).value,
+        ("-(1)".parseMath().evaluateConstants(Int32Ring) as? TypedMst.Constant<Int> ?: fail()).value,
     )
 
     @Test
     fun foldDeepUnary() = assertEquals(
         1,
-        ("-(-(1))".parseMath().evaluateConstants(IntRing) as? TypedMst.Constant<Int> ?: fail()).value,
+        ("-(-(1))".parseMath().evaluateConstants(Int32Ring) as? TypedMst.Constant<Int> ?: fail()).value,
     )
 
     @Test
     fun foldBinary() = assertEquals(
         2,
-        ("1*2".parseMath().evaluateConstants(IntRing) as? TypedMst.Constant<Int> ?: fail()).value,
+        ("1*2".parseMath().evaluateConstants(Int32Ring) as? TypedMst.Constant<Int> ?: fail()).value,
     )
 
     @Test
     fun foldDeepBinary() = assertEquals(
         10,
-        ("1*2*5".parseMath().evaluateConstants(IntRing) as? TypedMst.Constant<Int> ?: fail()).value,
+        ("1*2*5".parseMath().evaluateConstants(Int32Ring) as? TypedMst.Constant<Int> ?: fail()).value,
     )
 
     @Test
     fun foldSymbol() = assertEquals(
-        DoubleField.pi,
-        ("pi".parseMath().evaluateConstants(DoubleField) as? TypedMst.Constant<Double> ?: fail()).value,
+        Float64Field.pi,
+        ("pi".parseMath().evaluateConstants(Float64Field) as? TypedMst.Constant<Double> ?: fail()).value,
     )
 
     @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-ast/src/commonTest/kotlin/space/kscience/kmath/ast/TestParser.kt

@@ -9,7 +9,7 @@ import space.kscience.kmath.complex.Complex
 import space.kscience.kmath.complex.ComplexField
 import space.kscience.kmath.expressions.interpret
 import space.kscience.kmath.operations.Algebra
-import space.kscience.kmath.operations.DoubleField
+import space.kscience.kmath.operations.Float64Field
 import kotlin.test.Test
 import kotlin.test.assertEquals
 
@@ -32,7 +32,7 @@ internal class TestParser {
     @Test
     fun evaluateMstUnary() {
         val mst = "sin(0)".parseMath()
-        val res = mst.interpret(DoubleField)
+        val res = mst.interpret(Float64Field)
         assertEquals(0.0, res)
     }
 

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

@@ -6,7 +6,7 @@
 package space.kscience.kmath.ast
 
 import space.kscience.kmath.expressions.interpret
-import space.kscience.kmath.operations.DoubleField
+import space.kscience.kmath.operations.Float64Field
 import kotlin.test.Test
 import kotlin.test.assertEquals
 
@@ -36,6 +36,6 @@ internal class TestParserPrecedence {
     fun test8(): Unit = assertEquals(18.0, "2*2^3+2".parseMath().interpret(f))
 
     private companion object {
-        private val f = DoubleField
+        private val f = Float64Field
     }
 }

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

@@ -8,17 +8,17 @@ package space.kscience.kmath.ast
 import space.kscience.kmath.expressions.Expression
 import space.kscience.kmath.expressions.MST
 import space.kscience.kmath.expressions.Symbol
-import space.kscience.kmath.operations.DoubleField
-import space.kscience.kmath.operations.IntRing
+import space.kscience.kmath.operations.Float64Field
+import space.kscience.kmath.operations.Int32Ring
 
 internal interface CompilerTestContext {
-    fun MST.compileToExpression(algebra: IntRing): Expression<Int>
-    fun MST.compile(algebra: IntRing, arguments: Map<Symbol, Int>): Int
-    fun MST.compile(algebra: IntRing, vararg arguments: Pair<Symbol, Int>): Int = compile(algebra, mapOf(*arguments))
-    fun MST.compileToExpression(algebra: DoubleField): Expression<Double>
-    fun MST.compile(algebra: DoubleField, arguments: Map<Symbol, Double>): Double
+    fun MST.compileToExpression(algebra: Int32Ring): Expression<Int>
+    fun MST.compile(algebra: Int32Ring, arguments: Map<Symbol, Int>): Int
+    fun MST.compile(algebra: Int32Ring, vararg arguments: Pair<Symbol, Int>): Int = compile(algebra, mapOf(*arguments))
+    fun MST.compileToExpression(algebra: Float64Field): Expression<Double>
+    fun MST.compile(algebra: Float64Field, arguments: Map<Symbol, Double>): Double
 
-    fun MST.compile(algebra: DoubleField, vararg arguments: Pair<Symbol, Double>): Double =
+    fun MST.compile(algebra: Float64Field, vararg arguments: Pair<Symbol, Double>): Double =
         compile(algebra, mapOf(*arguments))
 }
 

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

@@ -86,7 +86,7 @@ internal sealed class WasmBuilder<T : Number, out E : Expression<T>>(
 
 @UnstableKMathAPI
 internal class DoubleWasmBuilder(target: TypedMst<Double>) :
-    WasmBuilder<Double, DoubleExpression>(f64, DoubleField, target) {
+    WasmBuilder<Double, DoubleExpression>(f64, Float64Field, target) {
     override val instance by lazy {
         object : DoubleExpression {
             override val indexer = SimpleSymbolIndexer(keys)
@@ -131,7 +131,7 @@ internal class DoubleWasmBuilder(target: TypedMst<Double>) :
 }
 
 @UnstableKMathAPI
-internal class IntWasmBuilder(target: TypedMst<Int>) : WasmBuilder<Int, IntExpression>(i32, IntRing, target) {
+internal class IntWasmBuilder(target: TypedMst<Int>) : WasmBuilder<Int, IntExpression>(i32, Int32Ring, target) {
     override val instance by lazy {
         object : IntExpression {
             override val indexer = SimpleSymbolIndexer(keys)

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

@@ -11,8 +11,8 @@ import space.kscience.kmath.UnstableKMathAPI
 import space.kscience.kmath.ast.TypedMst
 import space.kscience.kmath.ast.evaluateConstants
 import space.kscience.kmath.expressions.*
-import space.kscience.kmath.operations.DoubleField
-import space.kscience.kmath.operations.IntRing
+import space.kscience.kmath.operations.Float64Field
+import space.kscience.kmath.operations.Int32Ring
 import space.kscience.kmath.wasm.internal.DoubleWasmBuilder
 import space.kscience.kmath.wasm.internal.IntWasmBuilder
 
@@ -22,7 +22,7 @@ import space.kscience.kmath.wasm.internal.IntWasmBuilder
  * @author Iaroslav Postovalov
  */
 @UnstableKMathAPI
-public fun MST.compileToExpression(algebra: IntRing): IntExpression {
+public fun MST.compileToExpression(algebra: Int32Ring): IntExpression {
     val typed = evaluateConstants(algebra)
 
     return if (typed is TypedMst.Constant) object : IntExpression {
@@ -39,7 +39,7 @@ public fun MST.compileToExpression(algebra: IntRing): IntExpression {
  * @author Iaroslav Postovalov
  */
 @UnstableKMathAPI
-public fun MST.compile(algebra: IntRing, arguments: Map<Symbol, Int>): Int =
+public fun MST.compile(algebra: Int32Ring, arguments: Map<Symbol, Int>): Int =
     compileToExpression(algebra)(arguments)
 
 
@@ -49,7 +49,7 @@ public fun MST.compile(algebra: IntRing, arguments: Map<Symbol, Int>): Int =
  * @author Iaroslav Postovalov
  */
 @UnstableKMathAPI
-public fun MST.compile(algebra: IntRing, vararg arguments: Pair<Symbol, Int>): Int =
+public fun MST.compile(algebra: Int32Ring, vararg arguments: Pair<Symbol, Int>): Int =
     compileToExpression(algebra)(*arguments)
 
 /**
@@ -58,7 +58,7 @@ public fun MST.compile(algebra: IntRing, vararg arguments: Pair<Symbol, Int>): I
  * @author Iaroslav Postovalov
  */
 @UnstableKMathAPI
-public fun MST.compileToExpression(algebra: DoubleField): Expression<Double> {
+public fun MST.compileToExpression(algebra: Float64Field): Expression<Double> {
     val typed = evaluateConstants(algebra)
 
     return if (typed is TypedMst.Constant) object : DoubleExpression {
@@ -76,7 +76,7 @@ public fun MST.compileToExpression(algebra: DoubleField): Expression<Double> {
  * @author Iaroslav Postovalov
  */
 @UnstableKMathAPI
-public fun MST.compile(algebra: DoubleField, arguments: Map<Symbol, Double>): Double =
+public fun MST.compile(algebra: Float64Field, arguments: Map<Symbol, Double>): Double =
     compileToExpression(algebra)(arguments)
 
 
@@ -86,5 +86,5 @@ public fun MST.compile(algebra: DoubleField, arguments: Map<Symbol, Double>): Do
  * @author Iaroslav Postovalov
  */
 @UnstableKMathAPI
-public fun MST.compile(algebra: DoubleField, vararg arguments: Pair<Symbol, Double>): Double =
+public fun MST.compile(algebra: Float64Field, vararg arguments: Pair<Symbol, Double>): Double =
     compileToExpression(algebra)(*arguments)

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

@@ -11,8 +11,8 @@ import space.kscience.kmath.UnstableKMathAPI
 import space.kscience.kmath.expressions.Expression
 import space.kscience.kmath.expressions.MST
 import space.kscience.kmath.expressions.Symbol
-import space.kscience.kmath.operations.DoubleField
-import space.kscience.kmath.operations.IntRing
+import space.kscience.kmath.operations.Float64Field
+import space.kscience.kmath.operations.Int32Ring
 import kotlin.contracts.InvocationKind
 import kotlin.contracts.contract
 import space.kscience.kmath.estree.compile as estreeCompile
@@ -21,20 +21,20 @@ import space.kscience.kmath.wasm.compile as wasmCompile
 import space.kscience.kmath.wasm.compileToExpression as wasmCompileToExpression
 
 private object WasmCompilerTestContext : CompilerTestContext {
-    override fun MST.compileToExpression(algebra: IntRing): Expression<Int> = wasmCompileToExpression(algebra)
-    override fun MST.compile(algebra: IntRing, arguments: Map<Symbol, Int>): Int = wasmCompile(algebra, arguments)
-    override fun MST.compileToExpression(algebra: DoubleField): Expression<Double> = wasmCompileToExpression(algebra)
+    override fun MST.compileToExpression(algebra: Int32Ring): Expression<Int> = wasmCompileToExpression(algebra)
+    override fun MST.compile(algebra: Int32Ring, arguments: Map<Symbol, Int>): Int = wasmCompile(algebra, arguments)
+    override fun MST.compileToExpression(algebra: Float64Field): Expression<Double> = wasmCompileToExpression(algebra)
 
-    override fun MST.compile(algebra: DoubleField, arguments: Map<Symbol, Double>): Double =
+    override fun MST.compile(algebra: Float64Field, arguments: Map<Symbol, Double>): Double =
         wasmCompile(algebra, arguments)
 }
 
 private object ESTreeCompilerTestContext : CompilerTestContext {
-    override fun MST.compileToExpression(algebra: IntRing): Expression<Int> = estreeCompileToExpression(algebra)
-    override fun MST.compile(algebra: IntRing, arguments: Map<Symbol, Int>): Int = estreeCompile(algebra, arguments)
-    override fun MST.compileToExpression(algebra: DoubleField): Expression<Double> = estreeCompileToExpression(algebra)
+    override fun MST.compileToExpression(algebra: Int32Ring): Expression<Int> = estreeCompileToExpression(algebra)
+    override fun MST.compile(algebra: Int32Ring, arguments: Map<Symbol, Int>): Int = estreeCompile(algebra, arguments)
+    override fun MST.compileToExpression(algebra: Float64Field): Expression<Double> = estreeCompileToExpression(algebra)
 
-    override fun MST.compile(algebra: DoubleField, arguments: Map<Symbol, Double>): Double =
+    override fun MST.compile(algebra: Float64Field, arguments: Map<Symbol, Double>): Double =
         estreeCompile(algebra, arguments)
 }
 

kmath-ast/src/jsTest/kotlin/space/kscience/kmath/wasm/TestWasmSpecific.kt

@@ -10,8 +10,8 @@ import space.kscience.kmath.expressions.MstExtendedField
 import space.kscience.kmath.expressions.MstRing
 import space.kscience.kmath.expressions.invoke
 import space.kscience.kmath.expressions.symbol
-import space.kscience.kmath.operations.DoubleField
-import space.kscience.kmath.operations.IntRing
+import space.kscience.kmath.operations.Float64Field
+import space.kscience.kmath.operations.Int32Ring
 import space.kscience.kmath.operations.invoke
 import kotlin.test.Test
 import kotlin.test.assertEquals
@@ -20,20 +20,20 @@ import kotlin.test.assertEquals
 internal class TestWasmSpecific {
     @Test
     fun int() {
-        val res = MstRing { number(100000000) + number(10000000) }.compile(IntRing)
+        val res = MstRing { number(100000000) + number(10000000) }.compile(Int32Ring)
         assertEquals(110000000, res)
     }
 
     @Test
     fun real() {
-        val res = MstExtendedField { number(100000000) + number(2).pow(10) }.compile(DoubleField)
+        val res = MstExtendedField { number(100000000) + number(2).pow(10) }.compile(Float64Field)
         assertEquals(100001024.0, res)
     }
 
     @Test
     fun argsPassing() {
         val res = MstExtendedField { y + x.pow(10) }.compile(
-            DoubleField,
+            Float64Field,
             x to 2.0,
             y to 100000000.0,
         )
@@ -43,7 +43,7 @@ internal class TestWasmSpecific {
 
     @Test
     fun powFunction() {
-        val expr = MstExtendedField { x.pow(1.0 / 6.0) }.compileToExpression(DoubleField)
+        val expr = MstExtendedField { x.pow(1.0 / 6.0) }.compileToExpression(Float64Field)
         assertEquals(0.9730585187140817, expr(x to 0.8488554755054833))
     }
 

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

@@ -13,9 +13,9 @@ import space.kscience.kmath.ast.TypedMst
 import space.kscience.kmath.ast.evaluateConstants
 import space.kscience.kmath.expressions.*
 import space.kscience.kmath.operations.Algebra
-import space.kscience.kmath.operations.DoubleField
-import space.kscience.kmath.operations.IntRing
-import space.kscience.kmath.operations.LongRing
+import space.kscience.kmath.operations.Float64Field
+import space.kscience.kmath.operations.Int32Ring
+import space.kscience.kmath.operations.Int64Ring
 
 /**
  * Compiles given MST to an Expression using AST compiler.
@@ -91,7 +91,7 @@ public inline fun <reified T : Any> MST.compile(algebra: Algebra<T>, vararg argu
  * @author Iaroslav Postovalov
  */
 @UnstableKMathAPI
-public fun MST.compileToExpression(algebra: IntRing): IntExpression  {
+public fun MST.compileToExpression(algebra: Int32Ring): IntExpression  {
     val typed = evaluateConstants(algebra)
 
     return if (typed is TypedMst.Constant) object : IntExpression {
@@ -108,7 +108,7 @@ public fun MST.compileToExpression(algebra: IntRing): IntExpression  {
  * @author Iaroslav Postovalov
  */
 @UnstableKMathAPI
-public fun MST.compile(algebra: IntRing, arguments: Map<Symbol, Int>): Int =
+public fun MST.compile(algebra: Int32Ring, arguments: Map<Symbol, Int>): Int =
     compileToExpression(algebra)(arguments)
 
 /**
@@ -117,7 +117,7 @@ public fun MST.compile(algebra: IntRing, arguments: Map<Symbol, Int>): Int =
  * @author Iaroslav Postovalov
  */
 @UnstableKMathAPI
-public fun MST.compile(algebra: IntRing, vararg arguments: Pair<Symbol, Int>): Int =
+public fun MST.compile(algebra: Int32Ring, vararg arguments: Pair<Symbol, Int>): Int =
     compileToExpression(algebra)(*arguments)
 
 
@@ -127,7 +127,7 @@ public fun MST.compile(algebra: IntRing, vararg arguments: Pair<Symbol, Int>): I
  * @author Iaroslav Postovalov
  */
 @UnstableKMathAPI
-public fun MST.compileToExpression(algebra: LongRing): LongExpression {
+public fun MST.compileToExpression(algebra: Int64Ring): LongExpression {
     val typed = evaluateConstants(algebra)
 
     return if (typed is TypedMst.Constant<Long>) object : LongExpression {
@@ -144,7 +144,7 @@ public fun MST.compileToExpression(algebra: LongRing): LongExpression {
  * @author Iaroslav Postovalov
  */
 @UnstableKMathAPI
-public fun MST.compile(algebra: LongRing, arguments: Map<Symbol, Long>): Long =
+public fun MST.compile(algebra: Int64Ring, arguments: Map<Symbol, Long>): Long =
     compileToExpression(algebra)(arguments)
 
 
@@ -154,7 +154,7 @@ public fun MST.compile(algebra: LongRing, arguments: Map<Symbol, Long>): Long =
  * @author Iaroslav Postovalov
  */
 @UnstableKMathAPI
-public fun MST.compile(algebra: LongRing, vararg arguments: Pair<Symbol, Long>): Long =
+public fun MST.compile(algebra: Int64Ring, vararg arguments: Pair<Symbol, Long>): Long =
     compileToExpression(algebra)(*arguments)
 
 
@@ -164,7 +164,7 @@ public fun MST.compile(algebra: LongRing, vararg arguments: Pair<Symbol, Long>):
  * @author Iaroslav Postovalov
  */
 @UnstableKMathAPI
-public fun MST.compileToExpression(algebra: DoubleField): DoubleExpression {
+public fun MST.compileToExpression(algebra: Float64Field): DoubleExpression {
     val typed = evaluateConstants(algebra)
 
     return if (typed is TypedMst.Constant) object : DoubleExpression {
@@ -182,7 +182,7 @@ public fun MST.compileToExpression(algebra: DoubleField): DoubleExpression {
  * @author Iaroslav Postovalov
  */
 @UnstableKMathAPI
-public fun MST.compile(algebra: DoubleField, arguments: Map<Symbol, Double>): Double =
+public fun MST.compile(algebra: Float64Field, arguments: Map<Symbol, Double>): Double =
     compileToExpression(algebra)(arguments)
 
 /**
@@ -191,5 +191,5 @@ public fun MST.compile(algebra: DoubleField, arguments: Map<Symbol, Double>): Do
  * @author Iaroslav Postovalov
  */
 @UnstableKMathAPI
-public fun MST.compile(algebra: DoubleField, vararg arguments: Pair<Symbol, Double>): Double =
+public fun MST.compile(algebra: Float64Field, vararg arguments: Pair<Symbol, Double>): Double =
     compileToExpression(algebra)(*arguments)

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

@@ -382,7 +382,7 @@ internal sealed class PrimitiveAsmBuilder<T : Number, out E : Expression<T>>(
 
 @UnstableKMathAPI
 internal class DoubleAsmBuilder(target: TypedMst<Double>) : PrimitiveAsmBuilder<Double, DoubleExpression>(
-    DoubleField,
+    Float64Field,
     java.lang.Double::class.java,
     java.lang.Double.TYPE,
     DoubleExpression::class.java,
@@ -457,7 +457,7 @@ internal class DoubleAsmBuilder(target: TypedMst<Double>) : PrimitiveAsmBuilder<
 @UnstableKMathAPI
 internal class IntAsmBuilder(target: TypedMst<Int>) :
     PrimitiveAsmBuilder<Int, IntExpression>(
-        IntRing,
+        Int32Ring,
         Integer::class.java,
         Integer.TYPE,
         IntExpression::class.java,
@@ -487,7 +487,7 @@ internal class IntAsmBuilder(target: TypedMst<Int>) :
 
 @UnstableKMathAPI
 internal class LongAsmBuilder(target: TypedMst<Long>) : PrimitiveAsmBuilder<Long, LongExpression>(
-    LongRing,
+    Int64Ring,
     java.lang.Long::class.java,
     java.lang.Long.TYPE,
     LongExpression::class.java,

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

@@ -10,34 +10,34 @@ import space.kscience.kmath.expressions.Expression
 import space.kscience.kmath.expressions.MST
 import space.kscience.kmath.expressions.Symbol
 import space.kscience.kmath.operations.Algebra
-import space.kscience.kmath.operations.DoubleField
-import space.kscience.kmath.operations.IntRing
+import space.kscience.kmath.operations.Float64Field
+import space.kscience.kmath.operations.Int32Ring
 import kotlin.contracts.InvocationKind
 import kotlin.contracts.contract
 import space.kscience.kmath.asm.compile as asmCompile
 import space.kscience.kmath.asm.compileToExpression as asmCompileToExpression
 
 private object GenericAsmCompilerTestContext : CompilerTestContext {
-    override fun MST.compileToExpression(algebra: IntRing): Expression<Int> =
+    override fun MST.compileToExpression(algebra: Int32Ring): Expression<Int> =
         asmCompileToExpression(algebra as Algebra<Int>)
 
-    override fun MST.compile(algebra: IntRing, arguments: Map<Symbol, Int>): Int =
+    override fun MST.compile(algebra: Int32Ring, arguments: Map<Symbol, Int>): Int =
         asmCompile(algebra as Algebra<Int>, arguments)
 
-    override fun MST.compileToExpression(algebra: DoubleField): Expression<Double> =
+    override fun MST.compileToExpression(algebra: Float64Field): Expression<Double> =
         asmCompileToExpression(algebra as Algebra<Double>)
 
-    override fun MST.compile(algebra: DoubleField, arguments: Map<Symbol, Double>): Double =
+    override fun MST.compile(algebra: Float64Field, arguments: Map<Symbol, Double>): Double =
         asmCompile(algebra as Algebra<Double>, arguments)
 }
 
 @OptIn(UnstableKMathAPI::class)
 private object PrimitiveAsmCompilerTestContext : CompilerTestContext {
-    override fun MST.compileToExpression(algebra: IntRing): Expression<Int> = asmCompileToExpression(algebra)
-    override fun MST.compile(algebra: IntRing, arguments: Map<Symbol, Int>): Int = asmCompile(algebra, arguments)
-    override fun MST.compileToExpression(algebra: DoubleField): Expression<Double> = asmCompileToExpression(algebra)
+    override fun MST.compileToExpression(algebra: Int32Ring): Expression<Int> = asmCompileToExpression(algebra)
+    override fun MST.compile(algebra: Int32Ring, arguments: Map<Symbol, Int>): Int = asmCompile(algebra, arguments)
+    override fun MST.compileToExpression(algebra: Float64Field): Expression<Double> = asmCompileToExpression(algebra)
 
-    override fun MST.compile(algebra: DoubleField, arguments: Map<Symbol, Double>): Double =
+    override fun MST.compile(algebra: Float64Field, arguments: Map<Symbol, Double>): Double =
         asmCompile(algebra, arguments)
 }
 

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

@@ -9,9 +9,9 @@ import org.apache.commons.math3.linear.*
 import space.kscience.kmath.UnstableKMathAPI
 import space.kscience.kmath.linear.*
 import space.kscience.kmath.nd.StructureFeature
-import space.kscience.kmath.operations.DoubleField
+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
 
@@ -35,15 +35,15 @@ public value class CMVector(public val origin: RealVector) : Point<Double> {
 
 public fun RealVector.toPoint(): CMVector = CMVector(this)
 
-public object CMLinearSpace : LinearSpace<Double, DoubleField> {
-    override val elementAlgebra: DoubleField get() = DoubleField
+public object CMLinearSpace : LinearSpace<Double, Float64Field> {
+    override val elementAlgebra: Float64Field get() = Float64Field
 
     override fun buildMatrix(
         rows: Int,
         columns: Int,
-        initializer: DoubleField.(i: Int, j: Int) -> Double,
+        initializer: Float64Field.(i: Int, j: Int) -> Double,
     ): CMMatrix {
-        val array = Array(rows) { i -> DoubleArray(columns) { j -> DoubleField.initializer(i, j) } }
+        val array = Array(rows) { i -> DoubleArray(columns) { j -> Float64Field.initializer(i, j) } }
         return CMMatrix(Array2DRowRealMatrix(array))
     }
 
@@ -65,8 +65,8 @@ public object CMLinearSpace : LinearSpace<Double, DoubleField> {
     internal fun RealMatrix.wrap(): CMMatrix = CMMatrix(this)
     internal fun RealVector.wrap(): CMVector = CMVector(this)
 
-    override fun buildVector(size: Int, initializer: DoubleField.(Int) -> Double): Point<Double> =
-        ArrayRealVector(DoubleArray(size) { DoubleField.initializer(it) }).wrap()
+    override fun buildVector(size: Int, initializer: Float64Field.(Int) -> Double): Point<Double> =
+        ArrayRealVector(DoubleArray(size) { Float64Field.initializer(it) }).wrap()
 
     override fun Matrix<Double>.plus(other: Matrix<Double>): CMMatrix =
         toCM().origin.add(other.toCM().origin).wrap()
@@ -136,7 +136,7 @@ public object CMLinearSpace : LinearSpace<Double, DoubleField> {
                 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/integration/IntegrationTest.kt

@@ -9,7 +9,7 @@ import org.junit.jupiter.api.Test
 import space.kscience.kmath.UnstableKMathAPI
 import space.kscience.kmath.integration.integrate
 import space.kscience.kmath.integration.value
-import space.kscience.kmath.operations.DoubleField.sin
+import space.kscience.kmath.operations.Float64Field.sin
 import kotlin.math.PI
 import kotlin.math.abs
 import kotlin.test.assertTrue

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

@@ -13,18 +13,18 @@ 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.DoubleField
+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
 
 @OptIn(UnstableKMathAPI::class)
 internal class OptimizeTest {
-    val normal = DSFieldExpression(DoubleField) {
+    val normal = DSFieldExpression(Float64Field) {
         exp(-bindSymbol(x).pow(2) / 2) + exp(-bindSymbol(y).pow(2) / 2)
     }
 
@@ -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-complex/src/commonMain/kotlin/space/kscience/kmath/complex/Quaternion.kt

@@ -122,16 +122,17 @@ public val Quaternion.reciprocal: Quaternion
 /**
  * Produce a normalized version of this quaternion
  */
-public fun Quaternion.normalized(): Quaternion = with(QuaternionField){ this@normalized / norm(this@normalized) }
+public fun Quaternion.normalized(): Quaternion = with(QuaternionAlgebra){ this@normalized / norm(this@normalized) }
 
 /**
  * A field of [Quaternion].
  */
 @OptIn(UnstableKMathAPI::class)
-public object QuaternionField : Field<Quaternion>, Norm<Quaternion, Double>, PowerOperations<Quaternion>,
+public object QuaternionAlgebra : Group<Quaternion>, Norm<Quaternion, Double>, PowerOperations<Quaternion>,
     ExponentialOperations<Quaternion>, NumbersAddOps<Quaternion>, ScaleOperations<Quaternion> {
+
     override val zero: Quaternion = Quaternion(0.0)
-    override val one: Quaternion = Quaternion(1.0)
+    public val one: Quaternion = Quaternion(1.0)
 
     /**
      * The `i` quaternion unit.
@@ -154,14 +155,16 @@ public object QuaternionField : Field<Quaternion>, Norm<Quaternion, Double>, Pow
     override fun scale(a: Quaternion, value: Double): Quaternion =
         Quaternion(a.w * value, a.x * value, a.y * value, a.z * value)
 
-    override fun multiply(left: Quaternion, right: Quaternion): Quaternion = Quaternion(
+    public fun multiply(left: Quaternion, right: Quaternion): Quaternion = Quaternion(
         left.w * right.w - left.x * right.x - left.y * right.y - left.z * right.z,
         left.w * right.x + left.x * right.w + left.y * right.z - left.z * right.y,
         left.w * right.y - left.x * right.z + left.y * right.w + left.z * right.x,
         left.w * right.z + left.x * right.y - left.y * right.x + left.z * right.w,
     )
 
-    override fun divide(left: Quaternion, right: Quaternion): Quaternion {
+    public operator fun Quaternion.times(other: Quaternion): Quaternion = multiply(this, other)
+
+    public fun divide(left: Quaternion, right: Quaternion): Quaternion {
         val s = right.w * right.w + right.x * right.x + right.y * right.y + right.z * right.z
 
         return Quaternion(
@@ -172,14 +175,17 @@ public object QuaternionField : Field<Quaternion>, Norm<Quaternion, Double>, Pow
         )
     }
 
+    public operator fun Quaternion.div(other: Quaternion): Quaternion = divide(this, other)
+
+
     override fun power(arg: Quaternion, pow: Number): Quaternion {
-        if (pow is Int) return pwr(arg, pow)
-        if (floor(pow.toDouble()) == pow.toDouble()) return pwr(arg, pow.toInt())
+        if (pow is Int) return power(arg, pow)
+        if (floor(pow.toDouble()) == pow.toDouble()) return power(arg, pow.toInt())
         return exp(pow * ln(arg))
     }
 
-    private fun pwr(x: Quaternion, a: Int): Quaternion = when {
-        a < 0 -> -(pwr(x, -a))
+    private fun power(x: Quaternion, a: Int): Quaternion = when {
+        a < 0 -> -(power(x, -a))
         a == 0 -> one
         a == 1 -> x
         a == 2 -> pwr2(x)
@@ -243,14 +249,15 @@ public object QuaternionField : Field<Quaternion>, Norm<Quaternion, Double>, Pow
         return Quaternion(ln(n), th * arg.x, th * arg.y, th * arg.z)
     }
 
-    override operator fun Number.plus(other: Quaternion): Quaternion =
+    public override operator fun Number.plus(other: Quaternion): Quaternion =
         Quaternion(toDouble() + other.w, other.x, other.y, other.z)
 
-    override operator fun Number.minus(other: Quaternion): Quaternion =
+    public override operator fun Number.minus(other: Quaternion): Quaternion =
         Quaternion(toDouble() - other.w, -other.x, -other.y, -other.z)
 
-    override operator fun Quaternion.plus(other: Number): Quaternion = Quaternion(w + other.toDouble(), x, y, z)
-    override operator fun Quaternion.minus(other: Number): Quaternion = Quaternion(w - other.toDouble(), x, y, z)
+    public override operator fun Quaternion.plus(other: Number): Quaternion = Quaternion(w + other.toDouble(), x, y, z)
+
+    public override operator fun Quaternion.minus(other: Number): Quaternion = Quaternion(w - other.toDouble(), x, y, z)
 
     override operator fun Number.times(arg: Quaternion): Quaternion =
         Quaternion(toDouble() * arg.w, toDouble() * arg.x, toDouble() * arg.y, toDouble() * arg.z)
@@ -275,7 +282,7 @@ public object QuaternionField : Field<Quaternion>, Norm<Quaternion, Double>, Pow
     override fun sinh(arg: Quaternion): Quaternion = (exp(arg) - exp(-arg)) / 2.0
     override fun cosh(arg: Quaternion): Quaternion = (exp(arg) + exp(-arg)) / 2.0
     override fun tanh(arg: Quaternion): Quaternion = (exp(arg) - exp(-arg)) / (exp(-arg) + exp(arg))
-    override fun asinh(arg: Quaternion): Quaternion = ln(sqrt(arg * arg + one) + arg)
+    override fun asinh(arg: Quaternion): Quaternion = ln(sqrt(pwr2(arg) + one) + arg)
     override fun acosh(arg: Quaternion): Quaternion = ln(arg + sqrt((arg - one) * (arg + one)))
     override fun atanh(arg: Quaternion): Quaternion = (ln(arg + one) - ln(one - arg)) / 2.0
 }

kmath-complex/src/commonTest/kotlin/space/kscience/kmath/complex/QuaternionTest.kt

@@ -14,20 +14,20 @@ internal class QuaternionTest {
 
     @Test
     fun testNorm() {
-        assertEquals(2.0, QuaternionField.norm(Quaternion(1.0, 1.0, 1.0, 1.0)))
+        assertEquals(2.0, QuaternionAlgebra.norm(Quaternion(1.0, 1.0, 1.0, 1.0)))
     }
 
     @Test
-    fun testInverse() = QuaternionField {
+    fun testInverse() = QuaternionAlgebra {
         val q = Quaternion(1.0, 2.0, -3.0, 4.0)
         assertBufferEquals(one, q * q.reciprocal, 1e-4)
     }
 
     @Test
     fun testAddition() {
-        assertEquals(Quaternion(42, 42), QuaternionField { Quaternion(16, 16) + Quaternion(26, 26) })
-        assertEquals(Quaternion(42, 16), QuaternionField { Quaternion(16, 16) + 26 })
-        assertEquals(Quaternion(42, 16), QuaternionField { 26 + Quaternion(16, 16) })
+        assertEquals(Quaternion(42, 42), QuaternionAlgebra { Quaternion(16, 16) + Quaternion(26, 26) })
+        assertEquals(Quaternion(42, 16), QuaternionAlgebra { Quaternion(16, 16) + 26 })
+        assertEquals(Quaternion(42, 16), QuaternionAlgebra { 26 + Quaternion(16, 16) })
     }
 
 //    @Test
@@ -39,9 +39,9 @@ internal class QuaternionTest {
 
     @Test
     fun testMultiplication() {
-        assertEquals(Quaternion(42, 42), QuaternionField { Quaternion(4.2, 0) * Quaternion(10, 10) })
-        assertEquals(Quaternion(42, 21), QuaternionField { Quaternion(4.2, 2.1) * 10 })
-        assertEquals(Quaternion(42, 21), QuaternionField { 10 * Quaternion(4.2, 2.1) })
+        assertEquals(Quaternion(42, 42), QuaternionAlgebra { Quaternion(4.2, 0) * Quaternion(10, 10) })
+        assertEquals(Quaternion(42, 21), QuaternionAlgebra { Quaternion(4.2, 2.1) * 10 })
+        assertEquals(Quaternion(42, 21), QuaternionAlgebra { 10 * Quaternion(4.2, 2.1) })
     }
 
 //    @Test
@@ -53,11 +53,11 @@ internal class QuaternionTest {
 
     @Test
     fun testPower() {
-        assertEquals(QuaternionField.zero, QuaternionField { zero pow 2 })
-        assertEquals(QuaternionField.zero, QuaternionField { zero pow 2 })
+        assertEquals(QuaternionAlgebra.zero, QuaternionAlgebra { zero pow 2 })
+        assertEquals(QuaternionAlgebra.zero, QuaternionAlgebra { zero pow 2 })
 
         assertEquals(
-            QuaternionField { i * 8 }.let { it.x.toInt() to it.w.toInt() },
-            QuaternionField { Quaternion(2, 2) pow 2 }.let { it.x.toInt() to it.w.toInt() })
+            QuaternionAlgebra { i * 8 }.let { it.x.toInt() to it.w.toInt() },
+            QuaternionAlgebra { Quaternion(2, 2) pow 2 }.let { it.x.toInt() to it.w.toInt() })
     }
 }

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/DSAlgebra.kt

@@ -464,4 +464,4 @@ public class DSFieldProcessor<T, A : ExtendedField<T>>(
 }
 
 @UnstableKMathAPI
-public val Double.Companion.autodiff: DSFieldProcessor<Double, DoubleField> get() = DSFieldProcessor(DoubleField)
+public val Double.Companion.autodiff: DSFieldProcessor<Double, Float64Field> get() = DSFieldProcessor(Float64Field)

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

@@ -191,6 +191,6 @@ public inline fun <T, A : ExtendedField<T>> A.expressionInExtendedField(
     block: FunctionalExpressionExtendedField<T, A>.() -> Expression<T>,
 ): Expression<T> = FunctionalExpressionExtendedField(this).block()
 
-public inline fun DoubleField.expression(
-    block: FunctionalExpressionExtendedField<Double, DoubleField>.() -> Expression<Double>,
+public inline fun Float64Field.expression(
+    block: FunctionalExpressionExtendedField<Double, Float64Field>.() -> Expression<Double>,
 ): Expression<Double> = FunctionalExpressionExtendedField(this).block()

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 =
-        DoubleBuffer(symbols.size) { getValue(symbols[it]) }
+    public fun Map<Symbol, Double>.toPoint(): Float64Buffer =
+        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

@@ -7,43 +7,43 @@ 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.DoubleField
+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, DoubleField> {
+public object Float64LinearSpace : LinearSpace<Double, Float64Field> {
 
-    override val elementAlgebra: DoubleField get() = DoubleField
+    override val elementAlgebra: Float64Field get() = Float64Field
 
     override fun buildMatrix(
         rows: Int,
         columns: Int,
-        initializer: DoubleField.(i: Int, j: Int) -> Double
-    ): Matrix<Double> = DoubleFieldOpsND.structureND(ShapeND(rows, columns)) { (i, j) ->
-        DoubleField.initializer(i, j)
+        initializer: Float64Field.(i: Int, j: Int) -> Double
+    ): Matrix<Double> = Floa64FieldOpsND.structureND(ShapeND(rows, columns)) { (i, j) ->
+        Float64Field.initializer(i, j)
     }.as2D()
 
-    override fun buildVector(size: Int, initializer: DoubleField.(Int) -> Double): DoubleBuffer =
-        DoubleBuffer(size) { DoubleField.initializer(it) }
+    override fun buildVector(size: Int, initializer: Float64Field.(Int) -> Double): Float64Buffer =
+        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, DoubleField> {
     }
 
     @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, DoubleField> {
 
     }
 
-    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 DoubleField.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
 
@@ -155,11 +155,11 @@ public inline fun <reified T : Comparable<T>> LinearSpace<T, Field<T>>.lup(
     noinline checkSingular: (T) -> Boolean,
 ): LupDecomposition<T> = lup(MutableBuffer.Companion::auto, matrix, checkSingular)
 
-public fun LinearSpace<Double, DoubleField>.lup(
+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>,
@@ -226,5 +226,5 @@ public fun <T : Comparable<T>, F : Field<T>> LinearSpace<T, F>.lupSolver(
     override fun inverse(matrix: Matrix<T>): Matrix<T> = solve(matrix, one(matrix.rowNum, matrix.colNum))
 }
 
-public fun LinearSpace<Double, DoubleField>.lupSolver(singularityThreshold: Double = 1e-11): LinearSolver<Double> =
-    lupSolver(::DoubleBuffer) { it < singularityThreshold }
+public fun LinearSpace<Double, Float64Field>.lupSolver(singularityThreshold: Double = 1e-11): LinearSolver<Double> =
+    lupSolver(::Float64Buffer) { it < singularityThreshold }

kmath-core/src/commonMain/kotlin/space/kscience/kmath/misc/sorting.kt

@@ -65,6 +65,15 @@ public fun <V, C : Comparable<C>> Buffer<V>.sortedByDescending(selector: (V) ->
 public fun <V> Buffer<V>.indicesSortedWith(comparator: Comparator<V>): IntArray =
     permSortIndicesWith { i1, i2 -> comparator.compare(get(i1), get(i2)) }
 
+/**
+ * Create virtual zero-copy buffer with elements sorted by [comparator]
+ */
+@OptIn(UnstableKMathAPI::class)
+public fun <V> Buffer<V>.sortedWith(comparator: Comparator<V>): Buffer<V> {
+    val permutations = indicesSortedWith(comparator)
+    return VirtualBuffer(size) { this[permutations[it]] }
+}
+
 private fun <V> Buffer<V>.permSortIndicesWith(comparator: Comparator<Int>): IntArray {
     if (size < 2) return IntArray(size) { 0 }
 

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)]
 
@@ -29,101 +29,101 @@ public class DoubleBufferND(
 }
 
 
-public sealed class DoubleFieldOpsND : BufferedFieldOpsND<Double, DoubleField>(DoubleField.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) {
-        is DoubleBufferND -> this
+    override fun StructureND<Double>.toBufferND(): Float64BufferND = when (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,
-        r: DoubleBufferND,
+        l: Float64BufferND,
+        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)
-    override fun StructureND<Double>.map(transform: DoubleField.(Double) -> Double): BufferND<Double> =
-        mapInline(toBufferND()) { DoubleField.transform(it) }
+    override fun StructureND<Double>.map(transform: Float64Field.(Double) -> Double): BufferND<Double> =
+        mapInline(toBufferND()) { Float64Field.transform(it) }
 
 
     @OptIn(PerformancePitfall::class)
     override fun zip(
         left: StructureND<Double>,
         right: StructureND<Double>,
-        transform: DoubleField.(Double, Double) -> Double,
-    ): BufferND<Double> = zipInline(left.toBufferND(), right.toBufferND()) { l, r -> DoubleField.transform(l, r) }
+        transform: Float64Field.(Double, Double) -> Double,
+    ): BufferND<Double> = zipInline(left.toBufferND(), right.toBufferND()) { l, r -> Float64Field.transform(l, r) }
 
-    override fun structureND(shape: ShapeND, initializer: DoubleField.(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, DoubleField>(D
 
     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, DoubleField>(D
         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) :
-    DoubleFieldOpsND(), FieldND<Double, DoubleField>, NumbersAddOps<StructureND<Double>>,
+public class Float64FieldND(override val shape: ShapeND) :
+    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 DoubleField.ndAlgebra: DoubleFieldOpsND get() = DoubleFieldOpsND
+public val Float64Field.ndAlgebra: Floa64FieldOpsND get() = Floa64FieldOpsND
 
-public fun DoubleField.ndAlgebra(vararg shape: Int): DoubleFieldND = DoubleFieldND(ShapeND(shape))
-public fun DoubleField.ndAlgebra(shape: ShapeND): DoubleFieldND = DoubleFieldND(shape)
+public fun Float64Field.ndAlgebra(vararg shape: Int): Float64FieldND = Float64FieldND(ShapeND(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> DoubleField.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

@@ -6,20 +6,20 @@
 package space.kscience.kmath.nd
 
 import space.kscience.kmath.UnstableKMathAPI
+import space.kscience.kmath.operations.Int16Ring
 import space.kscience.kmath.operations.NumbersAddOps
-import space.kscience.kmath.operations.ShortRing
 import space.kscience.kmath.operations.bufferAlgebra
 import kotlin.contracts.InvocationKind
 import kotlin.contracts.contract
 
-public sealed class ShortRingOpsND : BufferedRingOpsND<Short, ShortRing>(ShortRing.bufferAlgebra) {
-    public companion object : ShortRingOpsND()
+public sealed class Int16RingOpsND : BufferedRingOpsND<Short, Int16Ring>(Int16Ring.bufferAlgebra) {
+    public companion object : Int16RingOpsND()
 }
 
 @OptIn(UnstableKMathAPI::class)
-public class ShortRingND(
+public class Int16RingND(
     override val shape: ShapeND
-) : ShortRingOpsND(), RingND<Short, ShortRing>, 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> ShortRing.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

@@ -6,25 +6,25 @@
 package space.kscience.kmath.nd
 
 import space.kscience.kmath.UnstableKMathAPI
-import space.kscience.kmath.operations.IntRing
+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, IntRing>(IntRing.bufferAlgebra) {
+public sealed class IntRingOpsND : BufferedRingOpsND<Int, Int32Ring>(Int32Ring.bufferAlgebra) {
 
-    override fun structureND(shape: ShapeND, initializer: IntRing.(IntArray) -> Int): IntBufferND {
+    override fun structureND(shape: ShapeND, initializer: Int32Ring.(IntArray) -> Int): IntBufferND {
         val indexer = indexerBuilder(shape)
         return IntBufferND(
             indexer,
-            IntBuffer(indexer.linearSize) { offset ->
+            Int32Buffer(indexer.linearSize) { offset ->
                 elementAlgebra.initializer(indexer.index(offset))
             }
         )
@@ -36,7 +36,7 @@ public sealed class IntRingOpsND : BufferedRingOpsND<Int, IntRing>(IntRing.buffe
 @OptIn(UnstableKMathAPI::class)
 public class IntRingND(
     override val shape: ShapeND
-) : IntRingOpsND(), RingND<Int, IntRing>, NumbersAddOps<StructureND<Int>> {
+) : IntRingOpsND(), RingND<Int, Int32Ring>, NumbersAddOps<StructureND<Int>> {
 
     override fun number(value: Number): BufferND<Int> {
         val int = value.toInt() // minimize conversions
@@ -44,7 +44,7 @@ public class IntRingND(
     }
 }
 
-public inline fun <R> IntRing.withNdAlgebra(vararg shape: Int, action: IntRingND.() -> R): R {
+public inline fun <R> Int32Ring.withNdAlgebra(vararg shape: Int, action: IntRingND.() -> R): R {
     contract { callsInPlace(action, InvocationKind.EXACTLY_ONCE) }
     return IntRingND(ShapeND(shape)).run(action)
 }

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

@@ -300,7 +300,7 @@ public interface Ring<T> : Group<T>, RingOps<T> {
  * commutative operations [add] and [multiply]; binary operation [divide] as multiplication of left operand by
  * reciprocal of right one.
  *
- * @param T the type of element of this semifield.
+ * @param T the type of the semifield element.
  */
 public interface FieldOps<T> : RingOps<T> {
     /**
@@ -336,10 +336,12 @@ public interface FieldOps<T> : RingOps<T> {
 
 /**
  * Represents field i.e., algebraic structure with three operations: associative, commutative addition and
- * multiplication, and division. **This interface differs from the eponymous mathematical definition: fields in KMath
+ * multiplication, and division.
+ *
+ * **This interface differs from the eponymous mathematical definition: fields in KMath
  * also support associative multiplication by scalar.**
  *
- * @param T the type of element of this field.
+ * @param T the type of the field element.
  */
 public interface Field<T> : Ring<T>, FieldOps<T>, ScaleOperations<T>, NumericAlgebra<T> {
     override fun number(value: Number): T = scale(one, value.toDouble())

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

@@ -142,11 +142,11 @@ public open class BufferRingOps<T, A : Ring<T>>(
         super<BufferAlgebra>.binaryOperationFunction(operation)
 }
 
-public val IntRing.bufferAlgebra: BufferRingOps<Int, IntRing>
-    get() = BufferRingOps(IntRing)
+public val Int32Ring.bufferAlgebra: BufferRingOps<Int, Int32Ring>
+    get() = BufferRingOps(Int32Ring)
 
-public val ShortRing.bufferAlgebra: BufferRingOps<Short, ShortRing>
-    get() = BufferRingOps(ShortRing)
+public val Int16Ring.bufferAlgebra: BufferRingOps<Short, Int16Ring>
+    get() = BufferRingOps(Int16Ring)
 
 public open class BufferFieldOps<T, A : Field<T>>(
     elementAlgebra: A,

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

@@ -12,34 +12,34 @@ import kotlin.math.pow
 import kotlin.math.sqrt
 
 /**
- * [ExtendedFieldOps] over [DoubleBuffer].
+ * [ExtendedFieldOps] over [Float64Buffer].
  */
-public abstract class DoubleBufferOps : BufferAlgebra<Double, DoubleField>, ExtendedFieldOps<Buffer<Double>>,
+public abstract class Float64BufferOps : BufferAlgebra<Double, Float64Field>, ExtendedFieldOps<Buffer<Double>>,
     Norm<Buffer<Double>, Double> {
 
-    override val elementAlgebra: DoubleField get() = DoubleField
+    override val elementAlgebra: Float64Field get() = Float64Field
 
     override val elementBufferFactory: MutableBufferFactory<Double> get() = elementAlgebra.bufferFactory
 
     @Suppress("OVERRIDE_BY_INLINE")
     @OptIn(UnstableKMathAPI::class)
-    final override inline fun Buffer<Double>.map(block: DoubleField.(Double) -> Double): DoubleBuffer =
-        DoubleArray(size) { DoubleField.block(getDouble(it)) }.asBuffer()
+    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: DoubleField.(index: Int, arg: Double) -> Double): DoubleBuffer =
-        DoubleBuffer(size) { DoubleField.block(it, getDouble(it)) }
+    final override inline fun Buffer<Double>.mapIndexed(block: Float64Field.(index: Int, arg: Double) -> Double): Float64Buffer =
+        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: DoubleField.(left: Double, right: Double) -> Double,
-    ): DoubleBuffer {
+        block: Float64Field.(left: Double, right: Double) -> Double,
+    ): Float64Buffer {
         require(size == other.size) { "Incompatible buffer sizes. left: ${size}, right: ${other.size}" }
-        return DoubleBuffer(size) { DoubleField.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, DoubleField>, Exte
     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] })
-        } else DoubleBuffer(DoubleArray(left.size) { left[it] + right[it] })
+            Float64Buffer(DoubleArray(left.size) { aArray[it] + bArray[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] })
-        } else DoubleBuffer(DoubleArray(this.size) { this[it] - arg[it] })
+            Float64Buffer(DoubleArray(this.size) { aArray[it] - bArray[it] })
+        } else Float64Buffer(DoubleArray(this.size) { this[it] - arg[it] })
     }
 
     //
@@ -96,61 +96,61 @@ public abstract class DoubleBufferOps : BufferAlgebra<Double, DoubleField>, Exte
 //    }
 
     @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] })
-        } else DoubleBuffer(DoubleArray(left.size) { left[it] * right[it] })
+            Float64Buffer(DoubleArray(left.size) { aArray[it] * bArray[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] })
-        } else DoubleBuffer(DoubleArray(left.size) { left[it] / right[it] })
+            Float64Buffer(DoubleArray(left.size) { aArray[it] / bArray[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, DoubleField>, Exte
         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/NumericAlgebra.kt

@@ -150,7 +150,7 @@ public interface ScaleOperations<T> : Algebra<T> {
  * TODO to be removed and replaced by extensions after multiple receivers are there
  */
 @UnstableKMathAPI
-public interface NumbersAddOps<T> : RingOps<T>, NumericAlgebra<T> {
+public interface NumbersAddOps<T> : GroupOps<T>, NumericAlgebra<T> {
     /**
      * Addition of element and scalar.
      *
@@ -177,7 +177,7 @@ public interface NumbersAddOps<T> : RingOps<T>, NumericAlgebra<T> {
     public operator fun T.minus(other: Number): T = this - number(other)
 
     /**
-     * Subtraction of number from element.
+     * Subtraction of number from the element.
      *
      * @receiver the minuend.
      * @param other the subtrahend.

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

@@ -82,9 +82,9 @@ public expect fun Number.isInteger(): Boolean
 /**
  * A context extension to include power operations based on exponentiation.
  *
- * @param T the type of element of this structure.
+ * @param T the type of this structure element
  */
-public interface PowerOperations<T> : FieldOps<T> {
+public interface PowerOperations<T>: Algebra<T> {
 
     /**
      * Raises [arg] to a power if possible (negative number could not be raised to a fractional power).

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

@@ -0,0 +1,85 @@
+/*
+ * Copyright 2018-2023 KMath contributors.
+ * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
+ */
+
+package space.kscience.kmath.operations
+
+import space.kscience.kmath.operations.Int16Field.div
+import space.kscience.kmath.operations.Int32Field.div
+import space.kscience.kmath.operations.Int64Field.div
+import space.kscience.kmath.structures.*
+import kotlin.math.roundToInt
+import kotlin.math.roundToLong
+
+
+/**
+ * A [Int16] field with integer division and scale. The division operation is done according to [Short.div] rules.
+ *
+ * Scaling is done according to [Double.roundToInt] rules.
+ *
+ * All results are converted to Int16.
+ */
+@Suppress("EXTENSION_SHADOWED_BY_MEMBER")
+public object Int16Field : Field<Int16>, Norm<Int16, Int16>, NumericAlgebra<Int16> {
+    override val bufferFactory: MutableBufferFactory<Int16> = MutableBufferFactory(::Int16Buffer)
+    override val zero: Int16 get() = 0
+    override val one: Int16 get() = 1
+
+    override fun number(value: Number): Int16 = value.toShort()
+    override fun add(left: Int16, right: Int16): Int16 = (left + right).toShort()
+    override fun multiply(left: Int16, right: Int16): Int16 = (left * right).toShort()
+    override fun norm(arg: Int16): Int16 = abs(arg)
+
+    override fun scale(a: Int16, value: Double): Int16 = (a*value).roundToInt().toShort()
+
+    override fun divide(left: Int16, right: Int16): Int16 = (left / right).toShort()
+
+    override fun Int16.unaryMinus(): Int16 = (-this).toShort()
+}
+
+/**
+ * A [Int32] field with integer division and scale. The division operation is done according to [Int.div] rules.
+ *
+ * Scaling is done according to [Double.roundToInt] rules.
+ */
+@Suppress("EXTENSION_SHADOWED_BY_MEMBER")
+public object Int32Field : Field<Int32>, Norm<Int32, Int32>, NumericAlgebra<Int32> {
+    override val bufferFactory: MutableBufferFactory<Int> = MutableBufferFactory(::Int32Buffer)
+    override val zero: Int get() = 0
+    override val one: Int get() = 1
+
+    override fun number(value: Number): Int = value.toInt()
+    override fun add(left: Int, right: Int): Int = left + right
+    override fun multiply(left: Int, right: Int): Int = left * right
+    override fun norm(arg: Int): Int = abs(arg)
+
+    override fun scale(a: Int, value: Double): Int = (a*value).roundToInt()
+
+    override fun divide(left: Int, right: Int): Int = left / right
+
+    override fun Int.unaryMinus(): Int = -this
+}
+
+/**
+ * A [Int64] field with integer division and scale. The division operation is done according to [Long.div] rules.
+ *
+ * Scaling is done according to [Double.roundToLong] rules.
+ */
+@Suppress("EXTENSION_SHADOWED_BY_MEMBER")
+public object Int64Field : Field<Int64>, Norm<Int64, Int64>, NumericAlgebra<Int64> {
+    override val bufferFactory: MutableBufferFactory<Int64> = MutableBufferFactory(::Int64Buffer)
+    override val zero: Int64 get() = 0L
+    override val one: Int64 get() = 1L
+
+    override fun number(value: Number): Int64 = value.toLong()
+    override fun add(left: Int64, right: Int64): Int64 = left + right
+    override fun multiply(left: Int64, right: Int64): Int64 = left * right
+    override fun norm(arg: Int64): Int64 = abs(arg)
+
+    override fun scale(a: Int64, value: Double): Int64 = (a*value).roundToLong()
+
+    override fun divide(left: Int64, right: Int64): Int64 = left / right
+
+    override fun Int64.unaryMinus(): Int64 = -this
+}

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

@@ -2,7 +2,6 @@
  * 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.
  */
-@file:Suppress("NOTHING_TO_INLINE")
 package space.kscience.kmath.operations
 
 import space.kscience.kmath.structures.*
@@ -64,16 +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")
-public object DoubleField : ExtendedField<Double>, Norm<Double, Double>, ScaleOperations<Double> {
-    override val bufferFactory: MutableBufferFactory<Double> = MutableBufferFactory(::DoubleBuffer)
+@Suppress("EXTENSION_SHADOWED_BY_MEMBER")
+public object Float64Field : ExtendedField<Double>, Norm<Double, Double>, ScaleOperations<Double> {
+    override val bufferFactory: MutableBufferFactory<Double> = MutableBufferFactory(::Float64Buffer)
 
-    override inline val zero: Double get() = 0.0
-    override inline val one: Double get() = 1.0
+    override val zero: Double get() = 0.0
+    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) {
@@ -81,26 +80,26 @@ public object DoubleField : ExtendedField<Double>, Norm<Double, Double>, ScaleOp
             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 inline fun divide(left: Double, right: Double): Double = left / right
+    override fun multiply(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 inline fun cos(arg: Double): Double = kotlin.math.cos(arg)
-    override inline fun tan(arg: Double): Double = kotlin.math.tan(arg)
-    override inline fun acos(arg: Double): Double = kotlin.math.acos(arg)
-    override inline fun asin(arg: Double): Double = kotlin.math.asin(arg)
-    override inline fun atan(arg: Double): Double = kotlin.math.atan(arg)
+    override fun sin(arg: Double): Double = kotlin.math.sin(arg)
+    override fun cos(arg: Double): Double = kotlin.math.cos(arg)
+    override fun tan(arg: Double): Double = kotlin.math.tan(arg)
+    override fun acos(arg: Double): Double = kotlin.math.acos(arg)
+    override fun asin(arg: Double): Double = kotlin.math.asin(arg)
+    override fun atan(arg: Double): Double = kotlin.math.atan(arg)
 
-    override inline fun sinh(arg: Double): Double = kotlin.math.sinh(arg)
-    override inline fun cosh(arg: Double): Double = kotlin.math.cosh(arg)
-    override inline fun tanh(arg: Double): Double = kotlin.math.tanh(arg)
-    override inline fun asinh(arg: Double): Double = kotlin.math.asinh(arg)
-    override inline fun acosh(arg: Double): Double = kotlin.math.acosh(arg)
-    override inline fun atanh(arg: Double): Double = kotlin.math.atanh(arg)
+    override fun sinh(arg: Double): Double = kotlin.math.sinh(arg)
+    override fun cosh(arg: Double): Double = kotlin.math.cosh(arg)
+    override fun tanh(arg: Double): Double = kotlin.math.tanh(arg)
+    override fun asinh(arg: Double): Double = kotlin.math.asinh(arg)
+    override fun acosh(arg: Double): Double = kotlin.math.acosh(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 {
@@ -109,29 +108,31 @@ public object DoubleField : ExtendedField<Double>, Norm<Double, Double>, ScaleOp
         else -> arg.kpow(pow.toDouble())
     }
 
-    override inline fun exp(arg: Double): Double = kotlin.math.exp(arg)
-    override inline fun ln(arg: Double): Double = kotlin.math.ln(arg)
+    override fun exp(arg: Double): Double = kotlin.math.exp(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 inline fun Double.plus(arg: Double): Double = this + arg
-    override inline fun Double.minus(arg: Double): Double = this - arg
-    override inline fun Double.times(arg: Double): Double = this * arg
-    override inline fun Double.div(arg: Double): Double = this / arg
+    override fun Double.unaryMinus(): Double = -this
+    override fun Double.plus(arg: Double): Double = this + arg
+    override fun Double.minus(arg: Double): Double = this - arg
+    override fun Double.times(arg: Double): Double = this * arg
+    override fun Double.div(arg: Double): Double = this / arg
 }
 
-public val Double.Companion.algebra: DoubleField get() = DoubleField
+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")
-public object FloatField : ExtendedField<Float>, Norm<Float, Float> {
-    override val bufferFactory: MutableBufferFactory<Float> = MutableBufferFactory(::FloatBuffer)
+@Suppress("EXTENSION_SHADOWED_BY_MEMBER")
+public object Float32Field : ExtendedField<Float>, Norm<Float, Float> {
+    override val bufferFactory: MutableBufferFactory<Float> = MutableBufferFactory(::Float32Buffer)
 
-    override inline val zero: Float get() = 0.0f
-    override inline val one: Float get() = 1.0f
+    override val zero: Float get() = 0.0f
+    override val one: Float get() = 1.0f
 
     override fun number(value: Number): Float = value.toFloat()
 
@@ -141,132 +142,142 @@ public object FloatField : 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 inline fun cos(arg: Float): Float = kotlin.math.cos(arg)
-    override inline fun tan(arg: Float): Float = kotlin.math.tan(arg)
-    override inline fun acos(arg: Float): Float = kotlin.math.acos(arg)
-    override inline fun asin(arg: Float): Float = kotlin.math.asin(arg)
-    override inline fun atan(arg: Float): Float = kotlin.math.atan(arg)
+    override fun sin(arg: Float): Float = kotlin.math.sin(arg)
+    override fun cos(arg: Float): Float = kotlin.math.cos(arg)
+    override fun tan(arg: Float): Float = kotlin.math.tan(arg)
+    override fun acos(arg: Float): Float = kotlin.math.acos(arg)
+    override fun asin(arg: Float): Float = kotlin.math.asin(arg)
+    override fun atan(arg: Float): Float = kotlin.math.atan(arg)
 
-    override inline fun sinh(arg: Float): Float = kotlin.math.sinh(arg)
-    override inline fun cosh(arg: Float): Float = kotlin.math.cosh(arg)
-    override inline fun tanh(arg: Float): Float = kotlin.math.tanh(arg)
-    override inline fun asinh(arg: Float): Float = kotlin.math.asinh(arg)
-    override inline fun acosh(arg: Float): Float = kotlin.math.acosh(arg)
-    override inline fun atanh(arg: Float): Float = kotlin.math.atanh(arg)
+    override fun sinh(arg: Float): Float = kotlin.math.sinh(arg)
+    override fun cosh(arg: Float): Float = kotlin.math.cosh(arg)
+    override fun tanh(arg: Float): Float = kotlin.math.tanh(arg)
+    override fun asinh(arg: Float): Float = kotlin.math.asinh(arg)
+    override fun acosh(arg: Float): Float = kotlin.math.acosh(arg)
+    override fun atanh(arg: Float): Float = kotlin.math.atanh(arg)
 
-    override inline fun sqrt(arg: Float): Float = kotlin.math.sqrt(arg)
-    override inline fun power(arg: Float, pow: Number): Float = arg.kpow(pow.toFloat())
+    override fun sqrt(arg: Float): Float = kotlin.math.sqrt(arg)
+    override fun power(arg: Float, pow: Number): Float = arg.kpow(pow.toFloat())
 
-    override inline fun exp(arg: Float): Float = kotlin.math.exp(arg)
-    override inline fun ln(arg: Float): Float = kotlin.math.ln(arg)
+    override fun exp(arg: Float): Float = kotlin.math.exp(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 inline fun Float.plus(arg: Float): Float = this + arg
-    override inline fun Float.minus(arg: Float): Float = this - arg
-    override inline fun Float.times(arg: Float): Float = this * arg
-    override inline fun Float.div(arg: Float): Float = this / arg
+    override fun Float.unaryMinus(): Float = -this
+    override fun Float.plus(arg: Float): Float = this + arg
+    override fun Float.minus(arg: Float): Float = this - arg
+    override fun Float.times(arg: Float): Float = this * arg
+    override fun Float.div(arg: Float): Float = this / arg
 }
 
-public val Float.Companion.algebra: FloatField get() = FloatField
+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")
-public object IntRing : Ring<Int>, Norm<Int, Int>, NumericAlgebra<Int> {
-    override val bufferFactory: MutableBufferFactory<Int> = MutableBufferFactory(::IntBuffer)
+@Suppress("EXTENSION_SHADOWED_BY_MEMBER")
+public object Int32Ring : Ring<Int>, Norm<Int, Int>, NumericAlgebra<Int> {
+    override val bufferFactory: MutableBufferFactory<Int> = MutableBufferFactory(::Int32Buffer)
 
-    override inline val zero: Int get() = 0
-    override inline val one: Int get() = 1
+    override val zero: Int get() = 0
+    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 inline fun multiply(left: Int, right: Int): Int = left * right
-    override inline fun norm(arg: Int): Int = abs(arg)
+    override fun add(left: Int, right: Int): Int = left + right
+    override fun multiply(left: Int, right: Int): Int = left * right
+    override fun norm(arg: Int): Int = abs(arg)
 
-    override inline fun Int.unaryMinus(): Int = -this
-    override inline fun Int.plus(arg: Int): Int = this + arg
-    override inline fun Int.minus(arg: Int): Int = this - arg
-    override inline fun Int.times(arg: Int): Int = this * arg
+    override fun Int.unaryMinus(): Int = -this
+    override fun Int.plus(arg: Int): Int = this + arg
+    override fun Int.minus(arg: Int): Int = this - arg
+    override fun Int.times(arg: Int): Int = this * arg
 }
 
-public val Int.Companion.algebra: IntRing get() = IntRing
+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")
-public object ShortRing : Ring<Short>, Norm<Short, Short>, NumericAlgebra<Short> {
-    override val bufferFactory: MutableBufferFactory<Short> = MutableBufferFactory(::ShortBuffer)
+@Suppress("EXTENSION_SHADOWED_BY_MEMBER")
+public object Int16Ring : Ring<Short>, Norm<Short, Short>, NumericAlgebra<Short> {
+    override val bufferFactory: MutableBufferFactory<Short> = MutableBufferFactory(::Int16Buffer)
 
-    override inline val zero: Short get() = 0
-    override inline val one: Short get() = 1
+    override val zero: Short get() = 0
+    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 inline fun multiply(left: Short, right: Short): Short = (left * right).toShort()
+    override fun add(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 inline fun Short.plus(arg: Short): Short = (this + arg).toShort()
-    override inline fun Short.minus(arg: Short): Short = (this - arg).toShort()
-    override inline fun Short.times(arg: Short): Short = (this * arg).toShort()
+    override fun Short.unaryMinus(): Short = (-this).toShort()
+    override fun Short.plus(arg: Short): Short = (this + arg).toShort()
+    override fun Short.minus(arg: Short): Short = (this - arg).toShort()
+    override fun Short.times(arg: Short): Short = (this * arg).toShort()
 }
 
-public val Short.Companion.algebra: ShortRing get() = ShortRing
+public typealias ShortRing = Int16Ring
+
+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")
-public object ByteRing : Ring<Byte>, Norm<Byte, Byte>, NumericAlgebra<Byte> {
-    override val bufferFactory: MutableBufferFactory<Byte> = MutableBufferFactory(::ByteBuffer)
+@Suppress("EXTENSION_SHADOWED_BY_MEMBER")
+public object Int8Ring : Ring<Byte>, Norm<Byte, Byte>, NumericAlgebra<Byte> {
+    override val bufferFactory: MutableBufferFactory<Byte> = MutableBufferFactory(::Int8Buffer)
 
-    override inline val zero: Byte get() = 0
-    override inline val one: Byte get() = 1
+    override val zero: Byte get() = 0
+    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 inline fun multiply(left: Byte, right: Byte): Byte = (left * right).toByte()
+    override fun add(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 inline fun Byte.plus(arg: Byte): Byte = (this + arg).toByte()
-    override inline fun Byte.minus(arg: Byte): Byte = (this - arg).toByte()
-    override inline fun Byte.times(arg: Byte): Byte = (this * arg).toByte()
+    override fun Byte.unaryMinus(): Byte = (-this).toByte()
+    override fun Byte.plus(arg: Byte): Byte = (this + arg).toByte()
+    override fun Byte.minus(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 appropriate ring element.
+ * A field for [Double] without boxing. Does not produce an appropriate ring element.
  */
-@Suppress("EXTENSION_SHADOWED_BY_MEMBER", "OVERRIDE_BY_INLINE")
-public object LongRing : Ring<Long>, Norm<Long, Long>, NumericAlgebra<Long> {
-    override val bufferFactory: MutableBufferFactory<Long> = MutableBufferFactory(::LongBuffer)
+@Suppress("EXTENSION_SHADOWED_BY_MEMBER")
+public object Int64Ring : Ring<Long>, Norm<Long, Long>, NumericAlgebra<Long> {
+    override val bufferFactory: MutableBufferFactory<Long> = MutableBufferFactory(::Int64Buffer)
 
-    override inline val zero: Long get() = 0L
-    override inline val one: Long get() = 1L
+    override val zero: Long get() = 0L
+    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 inline fun multiply(left: Long, right: Long): Long = left * right
+    override fun add(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 inline fun Long.plus(arg: Long): Long = (this + arg)
-    override inline fun Long.minus(arg: Long): Long = (this - arg)
-    override inline fun Long.times(arg: Long): Long = (this * arg)
+    override fun Long.unaryMinus(): Long = (-this)
+    override fun Long.plus(arg: Long): Long = (this + arg)
+    override fun Long.minus(arg: Long): Long = (this - arg)
+    override fun Long.times(arg: Long): Long = (this * arg)
 }
 
-public val Long.Companion.algebra: LongRing get() = LongRing
+public typealias LongRing = Int64Ring
+
+public val Long.Companion.algebra: Int64Ring get() = 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],
-         * [DoubleBuffer], etc.), [ListBuffer] is returned otherwise.
+         * Creates a [Buffer] of given [type]. If the type is primitive, specialized buffers are used ([Int32Buffer],
+         * [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],
-         * [DoubleBuffer], etc.), [ListBuffer] is returned otherwise.
+         * Creates a [Buffer] of given type [T]. If the type is primitive, specialized buffers are used ([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/BufferView.kt

@@ -96,6 +96,12 @@ public fun <T> Buffer<T>.slice(range: IntRange): BufferView<T> = if (this is Buf
     )
 }
 
+/**
+ *  Dynamically create a range from the initial range
+ */
+@UnstableKMathAPI
+public inline fun <T> Buffer<T>.slice(rangeBuilder: IntRange.() -> IntRange): BufferView<T> = slice(rangeBuilder(indices))
+
 /**
  * Resize original buffer to a given range using given [range], filling additional segments with [defaultValue].
  * Range left border could be negative to designate adding new blank segment to the beginning of the buffer

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 =
-    DoubleBuffer(DoubleArray(size) { init(it) })
+public inline fun Float64Buffer(size: Int, init: (Int) -> Double): Float64Buffer =
+    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) {
-    is DoubleBuffer -> this
+public fun Buffer<Double>.toFloat64Buffer(): Float64Buffer = when (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 transform(arg: DoubleBuffer): DoubleBuffer
+public fun interface Float64BufferTransform : BufferTransform<Double, Double> {
+    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 =
-            DoubleBuffer(size, initializer)
+        public inline fun double(size: Int, initializer: (Int) -> Double): Float64Buffer =
+            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 =
-            ShortBuffer(size, initializer)
+        public inline fun short(size: Int, initializer: (Int) -> Short): Int16Buffer =
+            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 =
-            IntBuffer(size, initializer)
+        public inline fun int(size: Int, initializer: (Int) -> Int): Int32Buffer =
+            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 =
-            LongBuffer(size, initializer)
+        public inline fun long(size: Int, initializer: (Int) -> Long): Int64Buffer =
+            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 =
-            FloatBuffer(size, initializer)
+        public inline fun float(size: Int, initializer: (Int) -> Float): Float32Buffer =
+            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/expressions/DSTest.kt

@@ -8,7 +8,7 @@
 package space.kscience.kmath.expressions
 
 import space.kscience.kmath.UnstableKMathAPI
-import space.kscience.kmath.operations.DoubleField
+import space.kscience.kmath.operations.Float64Field
 import kotlin.contracts.InvocationKind
 import kotlin.contracts.contract
 import kotlin.test.Test
@@ -18,10 +18,10 @@ import kotlin.test.assertFails
 internal inline fun diff(
     order: Int,
     vararg parameters: Pair<Symbol, Double>,
-    block: DSField<Double, DoubleField>.() -> Unit,
+    block: DSField<Double, Float64Field>.() -> Unit,
 ) {
     contract { callsInPlace(block, InvocationKind.EXACTLY_ONCE) }
-    DSField(DoubleField, order, mapOf(*parameters)).block()
+    DSField(Float64Field, order, mapOf(*parameters)).block()
 }
 
 internal class DSTest {
@@ -44,7 +44,7 @@ internal class DSTest {
 
     @Test
     fun dsExpressionTest() {
-        val f = DSFieldExpression(DoubleField) {
+        val f = DSFieldExpression(Float64Field) {
             val x by binding
             val y by binding
             x.pow(2) + 2 * x * y + y.pow(2) + 1

kmath-core/src/commonTest/kotlin/space/kscience/kmath/expressions/ExpressionFieldTest.kt

@@ -5,7 +5,7 @@
 
 package space.kscience.kmath.expressions
 
-import space.kscience.kmath.operations.DoubleField
+import space.kscience.kmath.operations.Float64Field
 import kotlin.test.Test
 import kotlin.test.assertEquals
 import kotlin.test.assertFails
@@ -15,7 +15,7 @@ class ExpressionFieldTest {
 
     @Test
     fun testExpression() {
-        val expression = with(FunctionalExpressionField(DoubleField)) {
+        val expression = with(FunctionalExpressionField(Float64Field)) {
             val x by binding
             x * x + 2 * x + one
         }
@@ -31,7 +31,7 @@ class ExpressionFieldTest {
             return x * x + 2 * x + one
         }
 
-        val expression = FunctionalExpressionField(DoubleField).expression()
+        val expression = FunctionalExpressionField(Float64Field).expression()
         assertEquals(expression(x to 1.0), 4.0)
     }
 
@@ -42,7 +42,7 @@ class ExpressionFieldTest {
             x * x + 2 * x + one
         }
 
-        val expression = FunctionalExpressionField(DoubleField).expressionBuilder()
+        val expression = FunctionalExpressionField(Float64Field).expressionBuilder()
         assertEquals(expression(x to 1.0), 4.0)
     }
 }

kmath-core/src/commonTest/kotlin/space/kscience/kmath/expressions/InterpretTest.kt

@@ -8,7 +8,7 @@ package space.kscience.kmath.expressions
 import space.kscience.kmath.UnstableKMathAPI
 import space.kscience.kmath.expressions.Symbol.Companion.x
 import space.kscience.kmath.operations.BooleanAlgebra
-import space.kscience.kmath.operations.DoubleField
+import space.kscience.kmath.operations.Float64Field
 import space.kscience.kmath.operations.invoke
 import kotlin.test.Test
 import kotlin.test.assertEquals
@@ -19,7 +19,7 @@ internal class InterpretTest {
     fun interpretation() {
         val expr = MstField {
             x * 2.0 + number(2.0) / x - 16.0
-        }.toExpression(DoubleField)
+        }.toExpression(Float64Field)
         assertEquals(-10.69, expr(x to 2.2), 0.02)
     }
 

kmath-core/src/commonTest/kotlin/space/kscience/kmath/expressions/SimpleAutoDiffTest.kt

@@ -5,7 +5,7 @@
 
 package space.kscience.kmath.expressions
 
-import space.kscience.kmath.operations.DoubleField
+import space.kscience.kmath.operations.Float64Field
 import space.kscience.kmath.operations.bindSymbol
 import space.kscience.kmath.structures.Buffer
 import space.kscience.kmath.structures.asBuffer
@@ -21,19 +21,19 @@ internal class SimpleAutoDiffTest {
 
     fun dx(
         xBinding: Pair<Symbol, Double>,
-        body: SimpleAutoDiffField<Double, DoubleField>.(x: AutoDiffValue<Double>) -> AutoDiffValue<Double>,
-    ): DerivationResult<Double> = DoubleField.simpleAutoDiff(xBinding) { body(bindSymbol(xBinding.first)) }
+        body: SimpleAutoDiffField<Double, Float64Field>.(x: AutoDiffValue<Double>) -> AutoDiffValue<Double>,
+    ): DerivationResult<Double> = Float64Field.simpleAutoDiff(xBinding) { body(bindSymbol(xBinding.first)) }
 
     fun dxy(
         xBinding: Pair<Symbol, Double>,
         yBinding: Pair<Symbol, Double>,
-        body: SimpleAutoDiffField<Double, DoubleField>.(x: AutoDiffValue<Double>, y: AutoDiffValue<Double>) -> AutoDiffValue<Double>,
-    ): DerivationResult<Double> = DoubleField.simpleAutoDiff(xBinding, yBinding) {
+        body: SimpleAutoDiffField<Double, Float64Field>.(x: AutoDiffValue<Double>, y: AutoDiffValue<Double>) -> AutoDiffValue<Double>,
+    ): DerivationResult<Double> = Float64Field.simpleAutoDiff(xBinding, yBinding) {
         body(bindSymbol(xBinding.first), bindSymbol(yBinding.first))
     }
 
-    fun diff(block: SimpleAutoDiffField<Double, DoubleField>.() -> AutoDiffValue<Double>): SimpleAutoDiffExpression<Double, DoubleField> {
-        return SimpleAutoDiffExpression(DoubleField, block)
+    fun diff(block: SimpleAutoDiffField<Double, Float64Field>.() -> AutoDiffValue<Double>): SimpleAutoDiffExpression<Double, Float64Field> {
+        return SimpleAutoDiffExpression(Float64Field, block)
     }
 
     val x by symbol
@@ -42,7 +42,7 @@ internal class SimpleAutoDiffTest {
 
     @Test
     fun testPlusX2() {
-        val y = DoubleField.simpleAutoDiff(x to 3.0) {
+        val y = Float64Field.simpleAutoDiff(x to 3.0) {
             // diff w.r.t this x at 3
             val x = bindSymbol(x)
             x + x
@@ -65,7 +65,7 @@ internal class SimpleAutoDiffTest {
     @Test
     fun testPlus() {
         // two variables
-        val z = DoubleField.simpleAutoDiff(x to 2.0, y to 3.0) {
+        val z = Float64Field.simpleAutoDiff(x to 2.0, y to 3.0) {
             val x = bindSymbol(x)
             val y = bindSymbol(y)
             x + y
@@ -78,7 +78,7 @@ internal class SimpleAutoDiffTest {
     @Test
     fun testMinus() {
         // two variables
-        val z = DoubleField.simpleAutoDiff(x to 7.0, y to 3.0) {
+        val z = Float64Field.simpleAutoDiff(x to 7.0, y to 3.0) {
             val x = bindSymbol(x)
             val y = bindSymbol(y)
 

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-core/src/commonTest/kotlin/space/kscience/kmath/nd/NdOperationsTest.kt

@@ -5,14 +5,14 @@
 
 package space.kscience.kmath.nd
 
-import space.kscience.kmath.operations.DoubleField
+import space.kscience.kmath.operations.Float64Field
 import kotlin.test.Test
 import kotlin.test.assertEquals
 
 class NdOperationsTest {
     @Test
     fun roll() {
-        val structure = DoubleField.ndAlgebra.structureND(5, 5) { index ->
+        val structure = Float64Field.ndAlgebra.structureND(5, 5) { index ->
             index.sumOf { it.toDouble() }
         }
 

kmath-core/src/commonTest/kotlin/space/kscience/kmath/operations/DoubleFieldTest.kt

@@ -11,16 +11,16 @@ import kotlin.test.assertEquals
 
 internal class DoubleFieldTest {
     @Test
-    fun verify() = FieldVerifier(DoubleField, 42.0, 66.0, 2.0, 5).verify()
+    fun verify() = FieldVerifier(Float64Field, 42.0, 66.0, 2.0, 5).verify()
 
     @Test
     fun testSqrt() {
-        val sqrt = DoubleField { sqrt(25 * one) }
+        val sqrt = Float64Field { sqrt(25 * one) }
         assertEquals(5.0, sqrt)
     }
 
     @Test
-    fun testPow() = DoubleField {
+    fun testPow() = Float64Field {
         val num = 5 * one
         assertEquals(5.0, power(num, 1), 0.01)
         assertEquals(25.0, power(num, 2), 0.01)

kmath-core/src/commonTest/kotlin/space/kscience/kmath/structures/NDFieldTest.kt

@@ -8,7 +8,7 @@ package space.kscience.kmath.structures
 import space.kscience.kmath.nd.get
 import space.kscience.kmath.nd.ndAlgebra
 import space.kscience.kmath.nd.structureND
-import space.kscience.kmath.operations.DoubleField
+import space.kscience.kmath.operations.Float64Field
 import space.kscience.kmath.operations.invoke
 import space.kscience.kmath.testutils.FieldVerifier
 import kotlin.test.Test
@@ -17,12 +17,12 @@ import kotlin.test.assertEquals
 internal class NDFieldTest {
     @Test
     fun verify() {
-        (DoubleField.ndAlgebra(12, 32)) { FieldVerifier(this, one + 3, one - 23, one * 12, 6.66) }
+        (Float64Field.ndAlgebra(12, 32)) { FieldVerifier(this, one + 3, one - 23, one * 12, 6.66) }
     }
 
     @Test
     fun testStrides() {
-        val ndArray = DoubleField.ndAlgebra.structureND(10, 10) { (it[0] + it[1]).toDouble() }
+        val ndArray = Float64Field.ndAlgebra.structureND(10, 10) { (it[0] + it[1]).toDouble() }
         assertEquals(ndArray[5, 5], 10.0)
     }
 }

kmath-core/src/commonTest/kotlin/space/kscience/kmath/structures/NumberNDFieldTest.kt

@@ -11,7 +11,7 @@ import space.kscience.kmath.nd.StructureND
 import space.kscience.kmath.nd.get
 import space.kscience.kmath.nd.ndAlgebra
 import space.kscience.kmath.nd.structureND
-import space.kscience.kmath.operations.DoubleField
+import space.kscience.kmath.operations.Float64Field
 import space.kscience.kmath.operations.Norm
 import space.kscience.kmath.operations.algebra
 import space.kscience.kmath.operations.invoke
@@ -25,7 +25,7 @@ import kotlin.test.assertEquals
 @OptIn(PerformancePitfall::class)
 @Suppress("UNUSED_VARIABLE")
 class NumberNDFieldTest {
-    val algebra = DoubleField.ndAlgebra
+    val algebra = Float64Field.ndAlgebra
     val array1 = algebra.structureND(3, 3) { (i, j) -> (i + j).toDouble() }
     val array2 = algebra.structureND(3, 3) { (i, j) -> (i - j).toDouble() }
 
@@ -94,7 +94,7 @@ class NumberNDFieldTest {
     @Test
     fun testInternalContext() {
         algebra {
-            (DoubleField.ndAlgebra(array1.shape)) { with(L2Norm) { 1 + norm(array1) + exp(array2) } }
+            (Float64Field.ndAlgebra(array1.shape)) { with(L2Norm) { 1 + norm(array1) + exp(array2) } }
         }
     }
 }

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-dimensions/src/commonMain/kotlin/space/kscience/kmath/dimensions/Wrappers.kt

@@ -8,7 +8,7 @@ package space.kscience.kmath.dimensions
 import space.kscience.kmath.linear.*
 import space.kscience.kmath.nd.ShapeND
 import space.kscience.kmath.nd.Structure2D
-import space.kscience.kmath.operations.DoubleField
+import space.kscience.kmath.operations.Float64Field
 import space.kscience.kmath.operations.Ring
 import space.kscience.kmath.operations.algebra
 import kotlin.jvm.JvmInline
@@ -150,7 +150,7 @@ public value class DMatrixContext<T : Any, out A : Ring<T>>(public val context:
         context.run { (this@transpose as Matrix<T>).transpose() }.coerce()
 
     public companion object {
-        public val real: DMatrixContext<Double, DoubleField> = DMatrixContext(Double.algebra.linearSpace)
+        public val real: DMatrixContext<Double, Float64Field> = DMatrixContext(Double.algebra.linearSpace)
     }
 }
 
@@ -158,12 +158,12 @@ public value class DMatrixContext<T : Any, out A : Ring<T>>(public val context:
 /**
  * A square unit matrix
  */
-public inline fun <reified D : Dimension> DMatrixContext<Double, DoubleField>.one(): DMatrix<Double, D, D> =
+public inline fun <reified D : Dimension> DMatrixContext<Double, Float64Field>.one(): DMatrix<Double, D, D> =
     produce { i, j ->
         if (i == j) 1.0 else 0.0
     }
 
-public inline fun <reified R : Dimension, reified C : Dimension> DMatrixContext<Double, DoubleField>.zero(): DMatrix<Double, R, C> =
+public inline fun <reified R : Dimension, reified C : Dimension> DMatrixContext<Double, Float64Field>.zero(): DMatrix<Double, R, C> =
     produce { _, _ ->
         0.0
     }

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

@@ -19,13 +19,19 @@ import org.ejml.sparse.csc.factory.DecompositionFactory_DSCC
 import org.ejml.sparse.csc.factory.DecompositionFactory_FSCC
 import org.ejml.sparse.csc.factory.LinearSolverFactory_DSCC
 import org.ejml.sparse.csc.factory.LinearSolverFactory_FSCC
-import space.kscience.kmath.UnstableKMathAPI
 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
@@ -71,11 +77,11 @@ public class EjmlFloatMatrix<out M : FMatrix>(override val origin: M) : EjmlMatr
  * [EjmlLinearSpace] implementation based on [CommonOps_DDRM], [DecompositionFactory_DDRM] operations and
  * [DMatrixRMaj] matrices.
  */
-public object EjmlLinearSpaceDDRM : EjmlLinearSpace<Double, DoubleField, DMatrixRMaj>() {
+public object EjmlLinearSpaceDDRM : EjmlLinearSpace<Double, Float64Field, DMatrixRMaj>() {
     /**
-     * The [DoubleField] reference.
+     * The [Float64Field] reference.
      */
-    override val elementAlgebra: DoubleField get() = DoubleField
+    override val elementAlgebra: Float64Field get() = Float64Field
 
     @Suppress("UNCHECKED_CAST")
     override fun Matrix<Double>.toEjml(): EjmlDoubleMatrix<DMatrixRMaj> = when {
@@ -94,7 +100,7 @@ public object EjmlLinearSpaceDDRM : EjmlLinearSpace<Double, DoubleField, DMatrix
     override fun buildMatrix(
         rows: Int,
         columns: Int,
-        initializer: DoubleField.(i: Int, j: Int) -> Double,
+        initializer: Float64Field.(i: Int, j: Int) -> Double,
     ): EjmlDoubleMatrix<DMatrixRMaj> = DMatrixRMaj(rows, columns).also {
         (0 until rows).forEach { row ->
             (0 until columns).forEach { col -> it[row, col] = elementAlgebra.initializer(row, col) }
@@ -103,7 +109,7 @@ public object EjmlLinearSpaceDDRM : EjmlLinearSpace<Double, DoubleField, DMatrix
 
     override fun buildVector(
         size: Int,
-        initializer: DoubleField.(Int) -> Double,
+        initializer: Float64Field.(Int) -> Double,
     ): EjmlDoubleVector<DMatrixRMaj> = EjmlDoubleVector(DMatrixRMaj(size, 1).also {
         (0 until it.numRows).forEach { row -> it[row, 0] = elementAlgebra.initializer(row) }
     })
@@ -307,11 +313,11 @@ public object EjmlLinearSpaceDDRM : EjmlLinearSpace<Double, DoubleField, DMatrix
  * [EjmlLinearSpace] implementation based on [CommonOps_FDRM], [DecompositionFactory_FDRM] operations and
  * [FMatrixRMaj] matrices.
  */
-public object EjmlLinearSpaceFDRM : EjmlLinearSpace<Float, FloatField, FMatrixRMaj>() {
+public object EjmlLinearSpaceFDRM : EjmlLinearSpace<Float, Float32Field, FMatrixRMaj>() {
     /**
-     * The [FloatField] reference.
+     * The [Float32Field] reference.
      */
-    override val elementAlgebra: FloatField get() = FloatField
+    override val elementAlgebra: Float32Field get() = Float32Field
 
     @Suppress("UNCHECKED_CAST")
     override fun Matrix<Float>.toEjml(): EjmlFloatMatrix<FMatrixRMaj> = when {
@@ -330,7 +336,7 @@ public object EjmlLinearSpaceFDRM : EjmlLinearSpace<Float, FloatField, FMatrixRM
     override fun buildMatrix(
         rows: Int,
         columns: Int,
-        initializer: FloatField.(i: Int, j: Int) -> Float,
+        initializer: Float32Field.(i: Int, j: Int) -> Float,
     ): EjmlFloatMatrix<FMatrixRMaj> = FMatrixRMaj(rows, columns).also {
         (0 until rows).forEach { row ->
             (0 until columns).forEach { col -> it[row, col] = elementAlgebra.initializer(row, col) }
@@ -339,7 +345,7 @@ public object EjmlLinearSpaceFDRM : EjmlLinearSpace<Float, FloatField, FMatrixRM
 
     override fun buildVector(
         size: Int,
-        initializer: FloatField.(Int) -> Float,
+        initializer: Float32Field.(Int) -> Float,
     ): EjmlFloatVector<FMatrixRMaj> = EjmlFloatVector(FMatrixRMaj(size, 1).also {
         (0 until it.numRows).forEach { row -> it[row, 0] = elementAlgebra.initializer(row) }
     })
@@ -543,11 +549,11 @@ public object EjmlLinearSpaceFDRM : EjmlLinearSpace<Float, FloatField, FMatrixRM
  * [EjmlLinearSpace] implementation based on [CommonOps_DSCC], [DecompositionFactory_DSCC] operations and
  * [DMatrixSparseCSC] matrices.
  */
-public object EjmlLinearSpaceDSCC : EjmlLinearSpace<Double, DoubleField, DMatrixSparseCSC>() {
+public object EjmlLinearSpaceDSCC : EjmlLinearSpace<Double, Float64Field, DMatrixSparseCSC>() {
     /**
-     * The [DoubleField] reference.
+     * The [Float64Field] reference.
      */
-    override val elementAlgebra: DoubleField get() = DoubleField
+    override val elementAlgebra: Float64Field get() = Float64Field
 
     @Suppress("UNCHECKED_CAST")
     override fun Matrix<Double>.toEjml(): EjmlDoubleMatrix<DMatrixSparseCSC> = when {
@@ -566,7 +572,7 @@ public object EjmlLinearSpaceDSCC : EjmlLinearSpace<Double, DoubleField, DMatrix
     override fun buildMatrix(
         rows: Int,
         columns: Int,
-        initializer: DoubleField.(i: Int, j: Int) -> Double,
+        initializer: Float64Field.(i: Int, j: Int) -> Double,
     ): EjmlDoubleMatrix<DMatrixSparseCSC> = DMatrixSparseCSC(rows, columns).also {
         (0 until rows).forEach { row ->
             (0 until columns).forEach { col -> it[row, col] = elementAlgebra.initializer(row, col) }
@@ -575,7 +581,7 @@ public object EjmlLinearSpaceDSCC : EjmlLinearSpace<Double, DoubleField, DMatrix
 
     override fun buildVector(
         size: Int,
-        initializer: DoubleField.(Int) -> Double,
+        initializer: Float64Field.(Int) -> Double,
     ): EjmlDoubleVector<DMatrixSparseCSC> = EjmlDoubleVector(DMatrixSparseCSC(size, 1).also {
         (0 until it.numRows).forEach { row -> it[row, 0] = elementAlgebra.initializer(row) }
     })
@@ -774,11 +780,11 @@ public object EjmlLinearSpaceDSCC : EjmlLinearSpace<Double, DoubleField, DMatrix
  * [EjmlLinearSpace] implementation based on [CommonOps_FSCC], [DecompositionFactory_FSCC] operations and
  * [FMatrixSparseCSC] matrices.
  */
-public object EjmlLinearSpaceFSCC : EjmlLinearSpace<Float, FloatField, FMatrixSparseCSC>() {
+public object EjmlLinearSpaceFSCC : EjmlLinearSpace<Float, Float32Field, FMatrixSparseCSC>() {
     /**
-     * The [FloatField] reference.
+     * The [Float32Field] reference.
      */
-    override val elementAlgebra: FloatField get() = FloatField
+    override val elementAlgebra: Float32Field get() = Float32Field
 
     @Suppress("UNCHECKED_CAST")
     override fun Matrix<Float>.toEjml(): EjmlFloatMatrix<FMatrixSparseCSC> = when {
@@ -797,7 +803,7 @@ public object EjmlLinearSpaceFSCC : EjmlLinearSpace<Float, FloatField, FMatrixSp
     override fun buildMatrix(
         rows: Int,
         columns: Int,
-        initializer: FloatField.(i: Int, j: Int) -> Float,
+        initializer: Float32Field.(i: Int, j: Int) -> Float,
     ): EjmlFloatMatrix<FMatrixSparseCSC> = FMatrixSparseCSC(rows, columns).also {
         (0 until rows).forEach { row ->
             (0 until columns).forEach { col -> it[row, col] = elementAlgebra.initializer(row, col) }
@@ -806,7 +812,7 @@ public object EjmlLinearSpaceFSCC : EjmlLinearSpace<Float, FloatField, FMatrixSp
 
     override fun buildVector(
         size: Int,
-        initializer: FloatField.(Int) -> Float,
+        initializer: Float32Field.(Int) -> Float,
     ): EjmlFloatVector<FMatrixSparseCSC> = EjmlFloatVector(FMatrixSparseCSC(size, 1).also {
         (0 until it.numRows).forEach { row -> it[row, 0] = elementAlgebra.initializer(row) }
     })

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
@@ -16,7 +16,6 @@ import kotlin.math.pow
 
 public typealias DoubleVector = Point<Double>
 
-@Suppress("FunctionName")
 public fun DoubleVector(vararg doubles: Double): DoubleVector = doubles.asBuffer()
 
 /**
@@ -103,4 +102,4 @@ 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

@@ -11,11 +11,11 @@ package space.kscience.kmath.real
 import space.kscience.kmath.PerformancePitfall
 import space.kscience.kmath.UnstableKMathAPI
 import space.kscience.kmath.linear.*
-import space.kscience.kmath.operations.DoubleField
+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
 
 /*
@@ -32,11 +32,11 @@ import kotlin.math.pow
 
 public typealias RealMatrix = Matrix<Double>
 
-public fun realMatrix(rowNum: Int, colNum: Int, initializer: DoubleField.(i: Int, j: Int) -> Double): RealMatrix =
+public fun realMatrix(rowNum: Int, colNum: Int, initializer: Float64Field.(i: Int, j: Int) -> Double): RealMatrix =
     Double.algebra.linearSpace.buildMatrix(rowNum, colNum, initializer)
 
 @OptIn(UnstableKMathAPI::class)
-public fun realMatrix(rowNum: Int, colNum: Int): MatrixBuilder<Double, DoubleField> =
+public fun realMatrix(rowNum: Int, colNum: Int): MatrixBuilder<Double, Float64Field> =
     Double.algebra.linearSpace.matrix(rowNum, colNum)
 
 public fun Array<DoubleArray>.toMatrix(): RealMatrix {
@@ -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()
 }