Fix Median statistics. Update algebra naming. Add integer fields

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 wasm = node.wasmCompileToExpression(Float64Field)
-        private val estree = node.estreeCompileToExpression(DoubleField)
+        private val estree = node.estreeCompileToExpression(Float64Field)
 
         private val raw = Expression<Double> { args ->
             val x = args[x]!!

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 specializedField = Float64Field.ndAlgebra
-        private val genericField = BufferedFieldOpsND(DoubleField)
+        private val genericField = BufferedFieldOpsND(Float64Field)
-        private val nd4jField = DoubleField.nd4j
+        private val nd4jField = Float64Field.nd4j
-        private val viktorField = DoubleField.viktorAlgebra
+        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)
     }
 }

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

@@ -7,7 +7,7 @@ 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.operations.Float64Field
 import space.kscience.kmath.structures.DoubleBuffer
 import space.kscience.plotly.Plotly
 import space.kscience.plotly.UnstablePlotlyAPI
@@ -25,10 +25,10 @@ fun main() {
     }
 
     val polynomial: PiecewisePolynomial<Double> = SplineInterpolator(
-        DoubleField, ::DoubleBuffer
+        Float64Field, ::DoubleBuffer
     ).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/operations/mixedNDOperations.kt

@@ -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: DoubleBufferND = 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 } }
 
@@ -43,10 +43,10 @@ class StreamDoubleFieldND(override val shape: ShapeND) : FieldND<Double, DoubleF
             else -> DoubleBuffer(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/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))
     }
 }

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.Float64Field
-import space.kscience.kmath.operations.IntRing
+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.interpret(Int32Ring, x to 3),
-            mst.compile(IntRing, 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.interpret(Float64Field, x to 2.0),
-            mst.compile(DoubleField, 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.Float64Field
-import space.kscience.kmath.operations.IntRing
+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

@@ -6,8 +6,8 @@
 package space.kscience.kmath.ast
 
 import space.kscience.kmath.operations.ByteRing
-import space.kscience.kmath.operations.DoubleField
+import space.kscience.kmath.operations.Float64Field
-import space.kscience.kmath.operations.IntRing
+import space.kscience.kmath.operations.Int32Ring
 import space.kscience.kmath.operations.pi
 import kotlin.test.Test
 import kotlin.test.assertEquals
@@ -17,31 +17,31 @@ 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,
+        Float64Field.pi,
-        ("pi".parseMath().evaluateConstants(DoubleField) as? TypedMst.Constant<Double> ?: fail()).value,
+        ("pi".parseMath().evaluateConstants(Float64Field) as? TypedMst.Constant<Double> ?: fail()).value,
     )
 
     @Test

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.Float64Field
-import space.kscience.kmath.operations.IntRing
+import space.kscience.kmath.operations.Int32Ring
 
 internal interface CompilerTestContext {
-    fun MST.compileToExpression(algebra: IntRing): Expression<Int>
+    fun MST.compileToExpression(algebra: Int32Ring): Expression<Int>
-    fun MST.compile(algebra: IntRing, arguments: Map<Symbol, Int>): Int
+    fun MST.compile(algebra: Int32Ring, arguments: Map<Symbol, Int>): Int
-    fun MST.compile(algebra: IntRing, vararg arguments: Pair<Symbol, Int>): Int = compile(algebra, mapOf(*arguments))
+    fun MST.compile(algebra: Int32Ring, vararg arguments: Pair<Symbol, Int>): Int = compile(algebra, mapOf(*arguments))
-    fun MST.compileToExpression(algebra: DoubleField): Expression<Double>
+    fun MST.compileToExpression(algebra: Float64Field): Expression<Double>
-    fun MST.compile(algebra: DoubleField, arguments: Map<Symbol, Double>): 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.Float64Field
-import space.kscience.kmath.operations.IntRing
+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.Float64Field
-import space.kscience.kmath.operations.IntRing
+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.compileToExpression(algebra: Int32Ring): Expression<Int> = wasmCompileToExpression(algebra)
-    override fun MST.compile(algebra: IntRing, arguments: Map<Symbol, Int>): Int = wasmCompile(algebra, arguments)
+    override fun MST.compile(algebra: Int32Ring, arguments: Map<Symbol, Int>): Int = wasmCompile(algebra, arguments)
-    override fun MST.compileToExpression(algebra: DoubleField): Expression<Double> = wasmCompileToExpression(algebra)
+    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.compileToExpression(algebra: Int32Ring): Expression<Int> = estreeCompileToExpression(algebra)
-    override fun MST.compile(algebra: IntRing, arguments: Map<Symbol, Int>): Int = estreeCompile(algebra, arguments)
+    override fun MST.compile(algebra: Int32Ring, arguments: Map<Symbol, Int>): Int = estreeCompile(algebra, arguments)
-    override fun MST.compileToExpression(algebra: DoubleField): Expression<Double> = estreeCompileToExpression(algebra)
+    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.Float64Field
-import space.kscience.kmath.operations.IntRing
+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.Float64Field
-import space.kscience.kmath.operations.IntRing
+import space.kscience.kmath.operations.Int32Ring
-import space.kscience.kmath.operations.LongRing
+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.Float64Field
-import space.kscience.kmath.operations.IntRing
+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.compileToExpression(algebra: Int32Ring): Expression<Int> = asmCompileToExpression(algebra)
-    override fun MST.compile(algebra: IntRing, arguments: Map<Symbol, Int>): Int = asmCompile(algebra, arguments)
+    override fun MST.compile(algebra: Int32Ring, arguments: Map<Symbol, Int>): Int = asmCompile(algebra, arguments)
-    override fun MST.compileToExpression(algebra: DoubleField): Expression<Double> = asmCompileToExpression(algebra)
+    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

@@ -9,7 +9,7 @@ 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 kotlin.reflect.KClass
@@ -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> {
+public object CMLinearSpace : 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,
+        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> =
+    override fun buildVector(size: Int, initializer: Float64Field.(Int) -> Double): Point<Double> =
-        ArrayRealVector(DoubleArray(size) { DoubleField.initializer(it) }).wrap()
+        ArrayRealVector(DoubleArray(size) { Float64Field.initializer(it) }).wrap()
 
     override fun Matrix<Double>.plus(other: Matrix<Double>): CMMatrix =
         toCM().origin.add(other.toCM().origin).wrap()

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

@@ -14,7 +14,7 @@ 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.Float64Field
 import space.kscience.kmath.optimization.*
 import space.kscience.kmath.random.RandomGenerator
 import space.kscience.kmath.stat.chiSquaredExpression
@@ -24,7 +24,7 @@ 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)
     }
 

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(
+public inline fun Float64Field.expression(
-    block: FunctionalExpressionExtendedField<Double, DoubleField>.() -> Expression<Double>,
+    block: FunctionalExpressionExtendedField<Double, Float64Field>.() -> Expression<Double>,
 ): Expression<Double> = FunctionalExpressionExtendedField(this).block()

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

@@ -8,25 +8,25 @@ 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.Float64Field
 import space.kscience.kmath.operations.invoke
 import space.kscience.kmath.structures.Buffer
 import space.kscience.kmath.structures.DoubleBuffer
 
-public object DoubleLinearSpace : LinearSpace<Double, DoubleField> {
+public object DoubleLinearSpace : 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
+        initializer: Float64Field.(i: Int, j: Int) -> Double
     ): Matrix<Double> = DoubleFieldOpsND.structureND(ShapeND(rows, columns)) { (i, j) ->
-        DoubleField.initializer(i, j)
+        Float64Field.initializer(i, j)
     }.as2D()
 
-    override fun buildVector(size: Int, initializer: DoubleField.(Int) -> Double): DoubleBuffer =
+    override fun buildVector(size: Int, initializer: Float64Field.(Int) -> Double): DoubleBuffer =
-        DoubleBuffer(size) { DoubleField.initializer(it) }
+        DoubleBuffer(size) { Float64Field.initializer(it) }
 
     override fun Matrix<Double>.unaryMinus(): Matrix<Double> = DoubleFieldOpsND {
         asND().map { -it }.as2D()
@@ -105,4 +105,4 @@ public object DoubleLinearSpace : LinearSpace<Double, DoubleField> {
 
 }
 
-public val DoubleField.linearSpace: DoubleLinearSpace get() = DoubleLinearSpace
+public val Float64Field.linearSpace: DoubleLinearSpace get() = DoubleLinearSpace

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

@@ -155,7 +155,7 @@ 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> =
@@ -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> =
+public fun LinearSpace<Double, Float64Field>.lupSolver(singularityThreshold: Double = 1e-11): LinearSolver<Double> =
     lupSolver(::DoubleBuffer) { 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/DoubleFieldND.kt

@@ -29,7 +29,7 @@ public class DoubleBufferND(
 }
 
 
-public sealed class DoubleFieldOpsND : BufferedFieldOpsND<Double, DoubleField>(DoubleField.bufferAlgebra),
+public sealed class DoubleFieldOpsND : BufferedFieldOpsND<Double, Float64Field>(Float64Field.bufferAlgebra),
     ScaleOperations<StructureND<Double>>, ExtendedFieldOps<StructureND<Double>> {
 
     @OptIn(PerformancePitfall::class)
@@ -63,18 +63,18 @@ public sealed class DoubleFieldOpsND : BufferedFieldOpsND<Double, DoubleField>(D
     }
 
     @OptIn(PerformancePitfall::class)
-    override fun StructureND<Double>.map(transform: DoubleField.(Double) -> Double): BufferND<Double> =
+    override fun StructureND<Double>.map(transform: Float64Field.(Double) -> Double): BufferND<Double> =
-        mapInline(toBufferND()) { DoubleField.transform(it) }
+        mapInline(toBufferND()) { Float64Field.transform(it) }
 
 
     @OptIn(PerformancePitfall::class)
     override fun zip(
         left: StructureND<Double>,
         right: StructureND<Double>,
-        transform: DoubleField.(Double, Double) -> Double,
+        transform: Float64Field.(Double, Double) -> Double,
-    ): BufferND<Double> = zipInline(left.toBufferND(), right.toBufferND()) { l, r -> DoubleField.transform(l, r) }
+    ): 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): DoubleBufferND {
         val indexer = indexerBuilder(shape)
         return DoubleBufferND(
             indexer,
@@ -190,7 +190,7 @@ public sealed class DoubleFieldOpsND : BufferedFieldOpsND<Double, DoubleField>(D
 
 @OptIn(UnstableKMathAPI::class)
 public class DoubleFieldND(override val shape: ShapeND) :
-    DoubleFieldOpsND(), FieldND<Double, DoubleField>, NumbersAddOps<StructureND<Double>>,
+    DoubleFieldOpsND(), FieldND<Double, Float64Field>, NumbersAddOps<StructureND<Double>>,
     ExtendedField<StructureND<Double>> {
 
     override fun power(arg: StructureND<Double>, pow: UInt): DoubleBufferND = mapInline(arg.toBufferND()) {
@@ -229,16 +229,16 @@ public class DoubleFieldND(override val shape: ShapeND) :
     }
 }
 
-public val DoubleField.ndAlgebra: DoubleFieldOpsND get() = DoubleFieldOpsND
+public val Float64Field.ndAlgebra: DoubleFieldOpsND get() = DoubleFieldOpsND
 
-public fun DoubleField.ndAlgebra(vararg shape: Int): DoubleFieldND = DoubleFieldND(ShapeND(shape))
+public fun Float64Field.ndAlgebra(vararg shape: Int): DoubleFieldND = DoubleFieldND(ShapeND(shape))
-public fun DoubleField.ndAlgebra(shape: ShapeND): DoubleFieldND = DoubleFieldND(shape)
+public fun Float64Field.ndAlgebra(shape: ShapeND): DoubleFieldND = DoubleFieldND(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: DoubleFieldND.() -> R): R {
     contract { callsInPlace(action, InvocationKind.EXACTLY_ONCE) }
     return DoubleFieldND(ShapeND(shape)).run(action)
 }

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

@@ -6,7 +6,7 @@
 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
@@ -18,9 +18,9 @@ public class IntBufferND(
     override val buffer: IntBuffer,
 ) : 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,
@@ -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/nd/ShortRingND.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 sealed class ShortRingOpsND : BufferedRingOpsND<Short, Int16Ring>(Int16Ring.bufferAlgebra) {
     public companion object : ShortRingOpsND()
 }
 
 @OptIn(UnstableKMathAPI::class)
 public class ShortRingND(
     override val shape: ShapeND
-) : ShortRingOpsND(), RingND<Short, ShortRing>, NumbersAddOps<StructureND<Short>> {
+) : ShortRingOpsND(), 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: ShortRingND.() -> R): R {
     contract { callsInPlace(action, InvocationKind.EXACTLY_ONCE) }
     return ShortRingND(ShapeND(shape)).run(action)
 }

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>
+public val Int32Ring.bufferAlgebra: BufferRingOps<Int, Int32Ring>
-    get() = BufferRingOps(IntRing)
+    get() = BufferRingOps(Int32Ring)
 
-public val ShortRing.bufferAlgebra: BufferRingOps<Short, ShortRing>
+public val Int16Ring.bufferAlgebra: BufferRingOps<Short, Int16Ring>
-    get() = BufferRingOps(ShortRing)
+    get() = BufferRingOps(Int16Ring)
 
 public open class BufferFieldOps<T, A : Field<T>>(
     elementAlgebra: A,

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

@@ -14,32 +14,32 @@ import kotlin.math.sqrt
 /**
  * [ExtendedFieldOps] over [DoubleBuffer].
  */
-public abstract class DoubleBufferOps : BufferAlgebra<Double, DoubleField>, ExtendedFieldOps<Buffer<Double>>,
+public abstract class DoubleBufferOps : 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 =
+    final override inline fun Buffer<Double>.map(block: Float64Field.(Double) -> Double): DoubleBuffer =
-        DoubleArray(size) { DoubleField.block(getDouble(it)) }.asBuffer()
+        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 =
+    final override inline fun Buffer<Double>.mapIndexed(block: Float64Field.(index: Int, arg: Double) -> Double): DoubleBuffer =
-        DoubleBuffer(size) { DoubleField.block(it, getDouble(it)) }
+        DoubleBuffer(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,
+        block: Float64Field.(left: Double, right: Double) -> Double,
     ): DoubleBuffer {
         require(size == other.size) { "Incompatible buffer sizes. left: ${size}, right: ${other.size}" }
-        return DoubleBuffer(size) { DoubleField.block(getDouble(it), other.getDouble(it)) }
+        return DoubleBuffer(size) { Float64Field.block(getDouble(it), other.getDouble(it)) }
     }
 
     override fun unaryOperationFunction(operation: String): (arg: Buffer<Double>) -> Buffer<Double> =

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(::ShortBuffer)
+    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(::IntBuffer)
+    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(::LongBuffer)
+    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.*
@@ -67,7 +66,7 @@ public interface ExtendedField<T> : ExtendedFieldOps<T>, Field<T>, NumericAlgebr
  * A field for [Double] without boxing. Does not produce appropriate field element.
  */
 @Suppress("EXTENSION_SHADOWED_BY_MEMBER", "OVERRIDE_BY_INLINE")
-public object DoubleField : ExtendedField<Double>, Norm<Double, Double>, ScaleOperations<Double> {
+public object Float64Field : ExtendedField<Double>, Norm<Double, Double>, ScaleOperations<Double> {
     override val bufferFactory: MutableBufferFactory<Double> = MutableBufferFactory(::DoubleBuffer)
 
     override inline val zero: Double get() = 0.0
@@ -121,13 +120,15 @@ public object DoubleField : ExtendedField<Double>, Norm<Double, Double>, ScaleOp
     override inline 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.
  */
 @Suppress("EXTENSION_SHADOWED_BY_MEMBER", "OVERRIDE_BY_INLINE")
-public object FloatField : ExtendedField<Float>, Norm<Float, Float> {
+public object Float32Field : ExtendedField<Float>, Norm<Float, Float> {
     override val bufferFactory: MutableBufferFactory<Float> = MutableBufferFactory(::FloatBuffer)
 
     override inline val zero: Float get() = 0.0f
@@ -177,13 +178,15 @@ public object FloatField : ExtendedField<Float>, Norm<Float, Float> {
     override inline 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.
  */
 @Suppress("EXTENSION_SHADOWED_BY_MEMBER", "OVERRIDE_BY_INLINE")
-public object IntRing : Ring<Int>, Norm<Int, Int>, NumericAlgebra<Int> {
+public object Int32Ring : Ring<Int>, Norm<Int, Int>, NumericAlgebra<Int> {
     override val bufferFactory: MutableBufferFactory<Int> = MutableBufferFactory(::IntBuffer)
 
     override inline val zero: Int get() = 0
@@ -200,13 +203,15 @@ public object IntRing : Ring<Int>, Norm<Int, Int>, NumericAlgebra<Int> {
     override inline 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.
  */
 @Suppress("EXTENSION_SHADOWED_BY_MEMBER", "OVERRIDE_BY_INLINE")
-public object ShortRing : Ring<Short>, Norm<Short, Short>, NumericAlgebra<Short> {
+public object Int16Ring : Ring<Short>, Norm<Short, Short>, NumericAlgebra<Short> {
     override val bufferFactory: MutableBufferFactory<Short> = MutableBufferFactory(::ShortBuffer)
 
     override inline val zero: Short get() = 0
@@ -223,7 +228,9 @@ public object ShortRing : Ring<Short>, Norm<Short, Short>, NumericAlgebra<Short>
     override inline 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.
@@ -249,10 +256,10 @@ public object ByteRing : Ring<Byte>, Norm<Byte, Byte>, NumericAlgebra<Byte> {
 public val Byte.Companion.algebra: ByteRing get() = ByteRing
 
 /**
- * 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> {
+public object Int64Ring : Ring<Long>, Norm<Long, Long>, NumericAlgebra<Long> {
     override val bufferFactory: MutableBufferFactory<Long> = MutableBufferFactory(::LongBuffer)
 
     override inline val zero: Long get() = 0L
@@ -269,4 +276,6 @@ public object LongRing : Ring<Long>, Norm<Long, Long>, NumericAlgebra<Long> {
     override inline 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/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/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>,
+        body: SimpleAutoDiffField<Double, Float64Field>.(x: AutoDiffValue<Double>) -> AutoDiffValue<Double>,
-    ): DerivationResult<Double> = DoubleField.simpleAutoDiff(xBinding) { body(bindSymbol(xBinding.first)) }
+    ): 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>,
+        body: SimpleAutoDiffField<Double, Float64Field>.(x: AutoDiffValue<Double>, y: AutoDiffValue<Double>) -> AutoDiffValue<Double>,
-    ): DerivationResult<Double> = DoubleField.simpleAutoDiff(xBinding, yBinding) {
+    ): DerivationResult<Double> = Float64Field.simpleAutoDiff(xBinding, yBinding) {
         body(bindSymbol(xBinding.first), bindSymbol(yBinding.first))
     }
 
-    fun diff(block: SimpleAutoDiffField<Double, DoubleField>.() -> AutoDiffValue<Double>): SimpleAutoDiffExpression<Double, DoubleField> {
+    fun diff(block: SimpleAutoDiffField<Double, Float64Field>.() -> AutoDiffValue<Double>): SimpleAutoDiffExpression<Double, Float64Field> {
-        return SimpleAutoDiffExpression(DoubleField, block)
+        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/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-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

@@ -19,12 +19,12 @@ 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.operations.DoubleField
+import space.kscience.kmath.operations.Float32Field
-import space.kscience.kmath.operations.FloatField
+import space.kscience.kmath.operations.Float64Field
 import space.kscience.kmath.operations.invoke
 import space.kscience.kmath.structures.DoubleBuffer
 import space.kscience.kmath.structures.FloatBuffer
@@ -71,11 +71,11 @@ 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 +94,7 @@ 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 +103,7 @@ 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 +307,11 @@ 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 +330,7 @@ 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 +339,7 @@ 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 +543,11 @@ 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 +566,7 @@ 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 +575,7 @@ 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 +774,11 @@ 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 +797,7 @@ 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 +806,7 @@ 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/RealMatrix.kt

@@ -11,7 +11,7 @@ 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
@@ -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 {

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

@@ -6,14 +6,14 @@
 package space.kscience.kmath.real
 
 import space.kscience.kmath.nd.BufferND
-import space.kscience.kmath.operations.DoubleField
+import space.kscience.kmath.operations.Float64Field
 import space.kscience.kmath.structures.DoubleBuffer
 
 /**
  * Map one [BufferND] using function without indices.
  */
-public inline fun BufferND<Double>.mapInline(crossinline transform: DoubleField.(Double) -> Double): BufferND<Double> {
+public inline fun BufferND<Double>.mapInline(crossinline transform: Float64Field.(Double) -> Double): BufferND<Double> {
-    val array = DoubleArray(indices.linearSize) { offset -> DoubleField.transform(buffer[offset]) }
+    val array = DoubleArray(indices.linearSize) { offset -> Float64Field.transform(buffer[offset]) }
     return BufferND(indices, DoubleBuffer(array))
 }
 

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

@@ -6,8 +6,8 @@
 package space.kscience.kmath.integration
 
 import space.kscience.kmath.UnstableKMathAPI
-import space.kscience.kmath.operations.DoubleField
 import space.kscience.kmath.operations.Field
+import space.kscience.kmath.operations.Float64Field
 import space.kscience.kmath.operations.invoke
 import space.kscience.kmath.operations.sum
 
@@ -105,4 +105,4 @@ public object DoubleSimpsonIntegrator : UnivariateIntegrator<Double> {
     }
 }
 
-public val DoubleField.simpsonIntegrator: DoubleSimpsonIntegrator get() = DoubleSimpsonIntegrator
+public val Float64Field.simpsonIntegrator: DoubleSimpsonIntegrator get() = DoubleSimpsonIntegrator

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

@@ -85,7 +85,7 @@ public class SplineIntegrator<T : Comparable<T>>(
 public object DoubleSplineIntegrator : UnivariateIntegrator<Double> {
     override fun process(integrand: UnivariateIntegrand<Double>): UnivariateIntegrand<Double> {
         val range = integrand.getFeature<IntegrationRange>()?.range ?: 0.0..1.0
-        val interpolator: PolynomialInterpolator<Double> = SplineInterpolator(DoubleField, ::DoubleBuffer)
+        val interpolator: PolynomialInterpolator<Double> = SplineInterpolator(Float64Field, ::DoubleBuffer)
 
         val nodes: Buffer<Double> = integrand.getFeature<UnivariateIntegrationNodes>()?.nodes ?: run {
             val numPoints = integrand.getFeature<IntegrandMaxCalls>()?.maxCalls ?: 100
@@ -95,12 +95,12 @@ public object DoubleSplineIntegrator : UnivariateIntegrator<Double> {
 
         val values = nodes.mapToBuffer(::DoubleBuffer) { integrand.function(it) }
         val polynomials = interpolator.interpolatePolynomials(nodes, values)
-        val res = polynomials.integrate(DoubleField, range)
+        val res = polynomials.integrate(Float64Field, range)
         return integrand + IntegrandValue(res) + IntegrandCallsPerformed(integrand.calls + nodes.size)
     }
 }
 
 @Suppress("unused")
 @UnstableKMathAPI
-public inline val DoubleField.splineIntegrator: UnivariateIntegrator<Double>
+public inline val Float64Field.splineIntegrator: UnivariateIntegrator<Double>
     get() = DoubleSplineIntegrator

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

@@ -9,8 +9,8 @@ import space.kscience.kmath.UnstableKMathAPI
 import space.kscience.kmath.data.XYColumnarData
 import space.kscience.kmath.functions.PiecewisePolynomial
 import space.kscience.kmath.functions.Polynomial
-import space.kscience.kmath.operations.DoubleField
 import space.kscience.kmath.operations.Field
+import space.kscience.kmath.operations.Float64Field
 import space.kscience.kmath.operations.invoke
 import space.kscience.kmath.structures.DoubleBuffer
 import space.kscience.kmath.structures.MutableBufferFactory
@@ -79,5 +79,5 @@ public fun <T : Comparable<T>> Field<T>.splineInterpolator(
     bufferFactory: MutableBufferFactory<T>,
 ): SplineInterpolator<T> = SplineInterpolator(this, bufferFactory)
 
-public val DoubleField.splineInterpolator: SplineInterpolator<Double>
+public val Float64Field.splineInterpolator: SplineInterpolator<Double>
     get() = SplineInterpolator(this, ::DoubleBuffer)

kmath-functions/src/commonTest/kotlin/space/kscience/kmath/integration/GaussIntegralTest.kt

@@ -6,7 +6,7 @@
 package space.kscience.kmath.integration
 
 import space.kscience.kmath.UnstableKMathAPI
-import space.kscience.kmath.operations.DoubleField
+import space.kscience.kmath.operations.Float64Field
 import kotlin.math.PI
 import kotlin.math.sin
 import kotlin.test.Test
@@ -16,7 +16,7 @@ import kotlin.test.assertEquals
 class GaussIntegralTest {
     @Test
     fun gaussSin() {
-        val res = DoubleField.gaussIntegrator.integrate(0.0..2 * PI) { x ->
+        val res = Float64Field.gaussIntegrator.integrate(0.0..2 * PI) { x ->
             sin(x)
         }
         assertEquals(0.0, res.value, 1e-2)
@@ -24,7 +24,7 @@ class GaussIntegralTest {
 
     @Test
     fun gaussUniform() {
-        val res = DoubleField.gaussIntegrator.integrate(35.0..100.0) { x ->
+        val res = Float64Field.gaussIntegrator.integrate(35.0..100.0) { x ->
             if(x in 30.0..50.0){
                 1.0
             } else {

kmath-functions/src/commonTest/kotlin/space/kscience/kmath/integration/SimpsonIntegralTest.kt

@@ -6,7 +6,7 @@
 package space.kscience.kmath.integration
 
 import space.kscience.kmath.UnstableKMathAPI
-import space.kscience.kmath.operations.DoubleField
+import space.kscience.kmath.operations.Float64Field
 import kotlin.math.PI
 import kotlin.math.sin
 import kotlin.test.Test
@@ -16,7 +16,7 @@ import kotlin.test.assertEquals
 class SimpsonIntegralTest {
     @Test
     fun gaussSin() {
-        val res = DoubleField.simpsonIntegrator.integrate(0.0..2 * PI, IntegrandMaxCalls(5)) { x ->
+        val res = Float64Field.simpsonIntegrator.integrate(0.0..2 * PI, IntegrandMaxCalls(5)) { x ->
             sin(x)
         }
         assertEquals(0.0, res.value, 1e-2)
@@ -24,7 +24,7 @@ class SimpsonIntegralTest {
 
     @Test
     fun gaussUniform() {
-        val res = DoubleField.simpsonIntegrator.integrate(35.0..100.0, IntegrandMaxCalls(20)) { x ->
+        val res = Float64Field.simpsonIntegrator.integrate(35.0..100.0, IntegrandMaxCalls(20)) { x ->
             if (x in 30.0..50.0) {
                 1.0
             } else {

kmath-functions/src/commonTest/kotlin/space/kscience/kmath/integration/SplineIntegralTest.kt

@@ -8,7 +8,7 @@ package space.kscience.kmath.integration
 import space.kscience.kmath.UnstableKMathAPI
 import space.kscience.kmath.functions.Polynomial
 import space.kscience.kmath.functions.integrate
-import space.kscience.kmath.operations.DoubleField
+import space.kscience.kmath.operations.Float64Field
 import kotlin.math.PI
 import kotlin.math.sin
 import kotlin.test.Test
@@ -20,13 +20,13 @@ class SplineIntegralTest {
     @Test
     fun integratePolynomial(){
         val polynomial = Polynomial(1.0, 2.0, 3.0)
-        val integral = polynomial.integrate(DoubleField,1.0..2.0)
+        val integral = polynomial.integrate(Float64Field,1.0..2.0)
         assertEquals(11.0, integral, 0.001)
     }
 
     @Test
     fun gaussSin() {
-        val res = DoubleField.splineIntegrator.integrate(0.0..2 * PI, IntegrandMaxCalls(5)) { x ->
+        val res = Float64Field.splineIntegrator.integrate(0.0..2 * PI, IntegrandMaxCalls(5)) { x ->
             sin(x)
         }
         assertEquals(0.0, res.value, 1e-2)
@@ -34,7 +34,7 @@ class SplineIntegralTest {
 
     @Test
     fun gaussUniform() {
-        val res = DoubleField.splineIntegrator.integrate(35.0..100.0, IntegrandMaxCalls(20)) { x ->
+        val res = Float64Field.splineIntegrator.integrate(35.0..100.0, IntegrandMaxCalls(20)) { x ->
             if(x in 30.0..50.0){
                 1.0
             } else {

kmath-functions/src/commonTest/kotlin/space/kscience/kmath/interpolation/LinearInterpolatorTest.kt

@@ -5,7 +5,7 @@
 
 package space.kscience.kmath.interpolation
 
-import space.kscience.kmath.operations.DoubleField
+import space.kscience.kmath.operations.Float64Field
 import kotlin.test.Test
 import kotlin.test.assertEquals
 
@@ -20,7 +20,7 @@ internal class LinearInterpolatorTest {
         )
 
         //val polynomial: PiecewisePolynomial<Double> = DoubleField.linearInterpolator.interpolatePolynomials(data)
-        val function = DoubleField.linearInterpolator.interpolate(data)
+        val function = Float64Field.linearInterpolator.interpolate(data)
         assertEquals(null, function(-1.0))
         assertEquals(0.5, function(0.5))
         assertEquals(2.0, function(1.5))

kmath-functions/src/commonTest/kotlin/space/kscience/kmath/interpolation/SplineInterpolatorTest.kt

@@ -5,7 +5,7 @@
 
 package space.kscience.kmath.interpolation
 
-import space.kscience.kmath.operations.DoubleField
+import space.kscience.kmath.operations.Float64Field
 import kotlin.math.PI
 import kotlin.math.sin
 import kotlin.test.Test
@@ -21,7 +21,7 @@ internal class SplineInterpolatorTest {
 
         //val polynomial: PiecewisePolynomial<Double> = DoubleField.splineInterpolator.interpolatePolynomials(data)
 
-        val function = DoubleField.splineInterpolator.interpolate(data, Double.NaN)
+        val function = Float64Field.splineInterpolator.interpolate(data, Double.NaN)
 
         assertEquals(Double.NaN, function(-1.0))
         assertEquals(sin(0.5), function(0.5), 0.1)

kmath-geometry/src/commonMain/kotlin/space/kscience/kmath/geometry/rotations3D.kt

@@ -14,7 +14,7 @@ import space.kscience.kmath.linear.LinearSpace
 import space.kscience.kmath.linear.Matrix
 import space.kscience.kmath.linear.linearSpace
 import space.kscience.kmath.linear.matrix
-import space.kscience.kmath.operations.DoubleField
+import space.kscience.kmath.operations.Float64Field
 import kotlin.math.pow
 import kotlin.math.sqrt
 
@@ -66,7 +66,7 @@ public fun Euclidean3DSpace.rotate(vector: DoubleVector3D, composition: Quaterni
 
 public fun Euclidean3DSpace.rotate(vector: DoubleVector3D, matrix: Matrix<Double>): DoubleVector3D {
     require(matrix.colNum == 3 && matrix.rowNum == 3) { "Square 3x3 rotation matrix is required" }
-    return with(DoubleField.linearSpace) { matrix.dot(vector).asVector3D() }
+    return with(Float64Field.linearSpace) { matrix.dot(vector).asVector3D() }
 }
 
 /**
@@ -74,7 +74,7 @@ public fun Euclidean3DSpace.rotate(vector: DoubleVector3D, matrix: Matrix<Double
  */
 @OptIn(UnstableKMathAPI::class)
 public fun Quaternion.toRotationMatrix(
-    linearSpace: LinearSpace<Double, *> = DoubleField.linearSpace,
+    linearSpace: LinearSpace<Double, *> = Float64Field.linearSpace,
 ): Matrix<Double> {
     val s = QuaternionField.norm(this).pow(-2)
     return linearSpace.matrix(3, 3)(

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

@@ -7,7 +7,7 @@ package space.kscience.kmath.histogram
 
 import kotlinx.atomicfu.atomic
 import kotlinx.atomicfu.getAndUpdate
-import space.kscience.kmath.operations.DoubleField
+import space.kscience.kmath.operations.Float64Field
 import space.kscience.kmath.operations.Group
 
 /**
@@ -18,7 +18,7 @@ public interface Counter<T : Any> {
     public val value: T
 
     public companion object {
-        public fun ofDouble(): ObjectCounter<Double> = ObjectCounter(DoubleField)
+        public fun ofDouble(): ObjectCounter<Double> = ObjectCounter(Float64Field)
         public fun <T: Any> of(group: Group<T>): ObjectCounter<T> = ObjectCounter(group)
     }
 }

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

@@ -128,7 +128,7 @@ public fun <V : Any, A : Field<V>> Histogram.Companion.uniformNDFromRanges(
 
 public fun Histogram.Companion.uniformDoubleNDFromRanges(
     vararg ranges: ClosedFloatingPointRange<Double>,
-): UniformHistogramGroupND<Double, DoubleField> =
+): UniformHistogramGroupND<Double, Float64Field> =
     uniformNDFromRanges(DoubleFieldOpsND, *ranges, bufferFactory = ::DoubleBuffer)
 
 
@@ -163,5 +163,5 @@ public fun <V : Any, A : Field<V>> Histogram.Companion.uniformNDFromRanges(
 
 public fun Histogram.Companion.uniformDoubleNDFromRanges(
     vararg ranges: Pair<ClosedFloatingPointRange<Double>, Int>,
-): UniformHistogramGroupND<Double, DoubleField> =
+): UniformHistogramGroupND<Double, Float64Field> =
     uniformNDFromRanges(DoubleFieldOpsND, *ranges, bufferFactory = ::DoubleBuffer)

kmath-histograms/src/commonTest/kotlin/space/kscience/kmath/histogram/UniformHistogram1DTest.kt

@@ -9,7 +9,7 @@ import kotlinx.coroutines.ExperimentalCoroutinesApi
 import kotlinx.coroutines.test.runTest
 import space.kscience.kmath.UnstableKMathAPI
 import space.kscience.kmath.distributions.NormalDistribution
-import space.kscience.kmath.operations.DoubleField
+import space.kscience.kmath.operations.Float64Field
 import space.kscience.kmath.random.RandomGenerator
 import space.kscience.kmath.stat.nextBuffer
 import kotlin.native.concurrent.ThreadLocal
@@ -22,7 +22,7 @@ internal class UniformHistogram1DTest {
     @Test
     fun normal() = runTest {
         val distribution = NormalDistribution(0.0, 1.0)
-        with(Histogram.uniform1D(DoubleField, 0.1)) {
+        with(Histogram.uniform1D(Float64Field, 0.1)) {
             val h1 = produce(distribution.nextBuffer(generator, 10000))
 
             val h2 = produce(distribution.nextBuffer(generator, 50000))
@@ -35,16 +35,16 @@ internal class UniformHistogram1DTest {
 
     @Test
     fun rebinDown() = runTest {
-        val h1 = Histogram.uniform1D(DoubleField, 0.01).produce(generator.nextDoubleBuffer(10000))
+        val h1 = Histogram.uniform1D(Float64Field, 0.01).produce(generator.nextDoubleBuffer(10000))
-        val h2 = Histogram.uniform1D(DoubleField, 0.03).produceFrom(h1)
+        val h2 = Histogram.uniform1D(Float64Field, 0.03).produceFrom(h1)
 
         assertEquals(10000, h2.bins.sumOf { it.binValue }.toInt())
     }
 
     @Test
     fun rebinUp() = runTest {
-        val h1 = Histogram.uniform1D(DoubleField, 0.03).produce(generator.nextDoubleBuffer(10000))
+        val h1 = Histogram.uniform1D(Float64Field, 0.03).produce(generator.nextDoubleBuffer(10000))
-        val h2 = Histogram.uniform1D(DoubleField, 0.01).produceFrom(h1)
+        val h2 = Histogram.uniform1D(Float64Field, 0.01).produceFrom(h1)
 
         assertEquals(10000, h2.bins.sumOf { it.binValue }.toInt())
     }

kmath-histograms/src/jvmTest/kotlin/space/kscience/kmath/histogram/TreeHistogramTest.kt

@@ -7,7 +7,7 @@ package space.kscience.kmath.histogram
 
 import org.junit.jupiter.api.Test
 import space.kscience.kmath.UnstableKMathAPI
-import space.kscience.kmath.operations.DoubleField
+import space.kscience.kmath.operations.Float64Field
 import space.kscience.kmath.real.step
 import kotlin.random.Random
 import kotlin.test.assertEquals
@@ -19,7 +19,7 @@ class TreeHistogramTest {
     @Test
     fun normalFill() {
         val random  = Random(123)
-        val histogram = Histogram.custom1D(DoubleField, 0.0..1.0 step 0.1).produce {
+        val histogram = Histogram.custom1D(Float64Field, 0.0..1.0 step 0.1).produce {
             repeat(100_000) {
                 putValue(random.nextDouble())
             }

kmath-kotlingrad/src/test/kotlin/space/kscience/kmath/kotlingrad/AdaptingTests.kt

@@ -12,7 +12,7 @@ import space.kscience.kmath.ast.parseMath
 import space.kscience.kmath.expressions.MstNumericAlgebra
 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 kotlin.test.Test
 import kotlin.test.assertEquals
 import kotlin.test.assertTrue
@@ -22,8 +22,8 @@ import kotlin.test.fail
 internal class AdaptingTests {
     @Test
     fun symbol() {
-        assertEquals(x.identity, x.toSVar<KMathNumber<Double, DoubleField>>().name)
+        assertEquals(x.identity, x.toSVar<KMathNumber<Double, Float64Field>>().name)
-        val c2 = "kitten".parseMath().toSFun<KMathNumber<Double, DoubleField>>()
+        val c2 = "kitten".parseMath().toSFun<KMathNumber<Double, Float64Field>>()
         if (c2 is SVar<*>) assertTrue(c2.name == "kitten") else fail()
     }
 
@@ -31,15 +31,15 @@ internal class AdaptingTests {
     fun number() {
         val c1 = MstNumericAlgebra.number(12354324)
         assertTrue(c1.toSConst<DReal>().doubleValue == 12354324.0)
-        val c2 = "0.234".parseMath().toSFun<KMathNumber<Double, DoubleField>>()
+        val c2 = "0.234".parseMath().toSFun<KMathNumber<Double, Float64Field>>()
         if (c2 is SConst<*>) assertTrue(c2.doubleValue == 0.234) else fail()
-        val c3 = "1e-3".parseMath().toSFun<KMathNumber<Double, DoubleField>>()
+        val c3 = "1e-3".parseMath().toSFun<KMathNumber<Double, Float64Field>>()
         if (c3 is SConst<*>) assertEquals(0.001, c3.value) else fail()
     }
 
     @Test
     fun simpleFunctionShape() {
-        val linear = "2*x+16".parseMath().toSFun<KMathNumber<Double, DoubleField>>()
+        val linear = "2*x+16".parseMath().toSFun<KMathNumber<Double, Float64Field>>()
         if (linear !is Sum<*>) fail()
         if (linear.left !is Prod<*>) fail()
         if (linear.right !is SConst<*>) fail()
@@ -47,22 +47,22 @@ internal class AdaptingTests {
 
     @Test
     fun simpleFunctionDerivative() {
-        val xSVar = x.toSVar<KMathNumber<Double, DoubleField>>()
+        val xSVar = x.toSVar<KMathNumber<Double, Float64Field>>()
-        val quadratic = "x^2-4*x-44".parseMath().toSFun<KMathNumber<Double, DoubleField>>()
+        val quadratic = "x^2-4*x-44".parseMath().toSFun<KMathNumber<Double, Float64Field>>()
-        val actualDerivative = quadratic.d(xSVar).toMst().compileToExpression(DoubleField)
+        val actualDerivative = quadratic.d(xSVar).toMst().compileToExpression(Float64Field)
-        val expectedDerivative = "2*x-4".parseMath().compileToExpression(DoubleField)
+        val expectedDerivative = "2*x-4".parseMath().compileToExpression(Float64Field)
         assertEquals(actualDerivative(x to 123.0), expectedDerivative(x to 123.0))
     }
 
     @Test
     fun moreComplexDerivative() {
-        val xSVar = x.toSVar<KMathNumber<Double, DoubleField>>()
+        val xSVar = x.toSVar<KMathNumber<Double, Float64Field>>()
-        val composition = "-sqrt(sin(x^2)-cos(x)^2-16*x)".parseMath().toSFun<KMathNumber<Double, DoubleField>>()
+        val composition = "-sqrt(sin(x^2)-cos(x)^2-16*x)".parseMath().toSFun<KMathNumber<Double, Float64Field>>()
-        val actualDerivative = composition.d(xSVar).toMst().compileToExpression(DoubleField)
+        val actualDerivative = composition.d(xSVar).toMst().compileToExpression(Float64Field)
 
         val expectedDerivative = "-(2*x*cos(x^2)+2*sin(x)*cos(x)-16)/(2*sqrt(sin(x^2)-16*x-cos(x)^2))"
             .parseMath()
-            .compileToExpression(DoubleField)
+            .compileToExpression(Float64Field)
 
         assertEquals(actualDerivative(x to -0.1), expectedDerivative(x to -0.1))
     }

kmath-multik/src/commonMain/kotlin/space/kscience/kmath/multik/MultikDoubleAlgebra.kt

@@ -11,15 +11,15 @@ import org.jetbrains.kotlinx.multik.api.ndarrayOf
 import org.jetbrains.kotlinx.multik.ndarray.data.DataType
 import space.kscience.kmath.PerformancePitfall
 import space.kscience.kmath.nd.StructureND
-import space.kscience.kmath.operations.DoubleField
 import space.kscience.kmath.operations.ExponentialOperations
+import space.kscience.kmath.operations.Float64Field
 import space.kscience.kmath.operations.TrigonometricOperations
 
 public class MultikDoubleAlgebra(
     multikEngine: Engine
-) : MultikDivisionTensorAlgebra<Double, DoubleField>(multikEngine),
+) : MultikDivisionTensorAlgebra<Double, Float64Field>(multikEngine),
     TrigonometricOperations<StructureND<Double>>, ExponentialOperations<StructureND<Double>> {
-    override val elementAlgebra: DoubleField get() = DoubleField
+    override val elementAlgebra: Float64Field get() = Float64Field
     override val type: DataType get() = DataType.DoubleDataType
 
     override fun sin(arg: StructureND<Double>): MultikTensor<Double> = multikMath.mathEx.sin(arg.asMultik().array).wrap()

kmath-multik/src/commonMain/kotlin/space/kscience/kmath/multik/MultikFloatAlgebra.kt

@@ -9,12 +9,12 @@ import org.jetbrains.kotlinx.multik.api.Engine
 import org.jetbrains.kotlinx.multik.api.Multik
 import org.jetbrains.kotlinx.multik.api.ndarrayOf
 import org.jetbrains.kotlinx.multik.ndarray.data.DataType
-import space.kscience.kmath.operations.FloatField
+import space.kscience.kmath.operations.Float32Field
 
 public class MultikFloatAlgebra(
     multikEngine: Engine
-) : MultikDivisionTensorAlgebra<Float, FloatField>(multikEngine) {
+) : MultikDivisionTensorAlgebra<Float, Float32Field>(multikEngine) {
-    override val elementAlgebra: FloatField get() = FloatField
+    override val elementAlgebra: Float32Field get() = Float32Field
     override val type: DataType get() = DataType.FloatDataType
 
     override fun scalar(value: Float): MultikTensor<Float> = Multik.ndarrayOf(value).wrap()

kmath-multik/src/commonMain/kotlin/space/kscience/kmath/multik/MultikIntAlgebra.kt

@@ -9,12 +9,12 @@ import org.jetbrains.kotlinx.multik.api.Engine
 import org.jetbrains.kotlinx.multik.api.Multik
 import org.jetbrains.kotlinx.multik.api.ndarrayOf
 import org.jetbrains.kotlinx.multik.ndarray.data.DataType
-import space.kscience.kmath.operations.IntRing
+import space.kscience.kmath.operations.Int32Ring
 
 public class MultikIntAlgebra(
     multikEngine: Engine
-) : MultikTensorAlgebra<Int, IntRing>(multikEngine) {
+) : MultikTensorAlgebra<Int, Int32Ring>(multikEngine) {
-    override val elementAlgebra: IntRing get() = IntRing
+    override val elementAlgebra: Int32Ring get() = Int32Ring
     override val type: DataType get() = DataType.IntDataType
     override fun scalar(value: Int): MultikTensor<Int>  = Multik.ndarrayOf(value).wrap()
 }

kmath-multik/src/commonMain/kotlin/space/kscience/kmath/multik/MultikLongAlgebra.kt

@@ -9,12 +9,12 @@ import org.jetbrains.kotlinx.multik.api.Engine
 import org.jetbrains.kotlinx.multik.api.Multik
 import org.jetbrains.kotlinx.multik.api.ndarrayOf
 import org.jetbrains.kotlinx.multik.ndarray.data.DataType
-import space.kscience.kmath.operations.LongRing
+import space.kscience.kmath.operations.Int64Ring
 
 public class MultikLongAlgebra(
     multikEngine: Engine
-) : MultikTensorAlgebra<Long, LongRing>(multikEngine) {
+) : MultikTensorAlgebra<Long, Int64Ring>(multikEngine) {
-    override val elementAlgebra: LongRing get() = LongRing
+    override val elementAlgebra: Int64Ring get() = Int64Ring
     override val type: DataType get() = DataType.LongDataType
 
     override fun scalar(value: Long): MultikTensor<Long>  = Multik.ndarrayOf(value).wrap()

kmath-multik/src/commonMain/kotlin/space/kscience/kmath/multik/MultikShortAlgebra.kt

@@ -9,12 +9,12 @@ import org.jetbrains.kotlinx.multik.api.Engine
 import org.jetbrains.kotlinx.multik.api.Multik
 import org.jetbrains.kotlinx.multik.api.ndarrayOf
 import org.jetbrains.kotlinx.multik.ndarray.data.DataType
-import space.kscience.kmath.operations.ShortRing
+import space.kscience.kmath.operations.Int16Ring
 
 public class MultikShortAlgebra(
     multikEngine: Engine
-) : MultikTensorAlgebra<Short, ShortRing>(multikEngine) {
+) : MultikTensorAlgebra<Short, Int16Ring>(multikEngine) {
-    override val elementAlgebra: ShortRing get() = ShortRing
+    override val elementAlgebra: Int16Ring get() = Int16Ring
     override val type: DataType get() = DataType.ShortDataType
     override fun scalar(value: Short): MultikTensor<Short>  = Multik.ndarrayOf(value).wrap()
 }

kmath-multik/src/commonTest/kotlin/space/kscience/kmath/multik/MultikNDTest.kt

@@ -10,7 +10,7 @@ import space.kscience.kmath.PerformancePitfall
 import space.kscience.kmath.nd.ShapeND
 import space.kscience.kmath.nd.StructureND
 import space.kscience.kmath.nd.one
-import space.kscience.kmath.operations.DoubleField
+import space.kscience.kmath.operations.Float64Field
 import space.kscience.kmath.tensors.core.DoubleTensorAlgebra
 import space.kscience.kmath.tensors.core.randomNormal
 import space.kscience.kmath.tensors.core.tensorAlgebra
@@ -37,7 +37,7 @@ internal class MultikNDTest {
             tensor1 dot tensor2
         }
 
-        val defaultResult = with(DoubleField.tensorAlgebra) {
+        val defaultResult = with(Float64Field.tensorAlgebra) {
             tensor1 dot tensor2
         }
 

kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jArrayAlgebra.kt

@@ -124,7 +124,7 @@ public sealed interface Nd4jArrayRingOps<T, out R : Ring<T>> : RingOpsND<T, R>,
          */
         @Suppress("UNCHECKED_CAST")
         public inline fun <reified T : Number> auto(): Nd4jArrayRingOps<T, Ring<T>> = when {
-            T::class == Int::class -> IntRing.nd4j as Nd4jArrayRingOps<T, Ring<T>>
+            T::class == Int::class -> Int32Ring.nd4j as Nd4jArrayRingOps<T, Ring<T>>
             else -> throw UnsupportedOperationException("This factory method only supports Long type.")
         }
     }
@@ -149,8 +149,8 @@ public sealed interface Nd4jArrayField<T, out F : Field<T>> : FieldOpsND<T, F>,
          */
         @Suppress("UNCHECKED_CAST")
         public inline fun <reified T : Any> auto(): Nd4jArrayField<T, Field<T>> = when {
-            T::class == Float::class -> FloatField.nd4j as Nd4jArrayField<T, Field<T>>
+            T::class == Float::class -> Float32Field.nd4j as Nd4jArrayField<T, Field<T>>
-            T::class == Double::class -> DoubleField.nd4j as Nd4jArrayField<T, Field<T>>
+            T::class == Double::class -> Float64Field.nd4j as Nd4jArrayField<T, Field<T>>
             else -> throw UnsupportedOperationException("This factory method only supports Float and Double types.")
         }
     }
@@ -190,8 +190,8 @@ public sealed interface Nd4jArrayExtendedFieldOps<T, out F : ExtendedField<T>> :
 /**
  * Represents [FieldND] over [Nd4jArrayDoubleStructure].
  */
-public open class DoubleNd4jArrayFieldOps : Nd4jArrayExtendedFieldOps<Double, DoubleField> {
+public open class DoubleNd4jArrayFieldOps : Nd4jArrayExtendedFieldOps<Double, Float64Field> {
-    override val elementAlgebra: DoubleField get() = DoubleField
+    override val elementAlgebra: Float64Field get() = Float64Field
 
     override fun INDArray.wrap(): Nd4jArrayStructure<Double> = asDoubleStructure()
 
@@ -223,19 +223,19 @@ public open class DoubleNd4jArrayFieldOps : Nd4jArrayExtendedFieldOps<Double, Do
     public companion object : DoubleNd4jArrayFieldOps()
 }
 
-public val DoubleField.nd4j: DoubleNd4jArrayFieldOps get() = DoubleNd4jArrayFieldOps
+public val Float64Field.nd4j: DoubleNd4jArrayFieldOps get() = DoubleNd4jArrayFieldOps
 
-public class DoubleNd4jArrayField(override val shape: ShapeND) : DoubleNd4jArrayFieldOps(), FieldND<Double, DoubleField>
+public class DoubleNd4jArrayField(override val shape: ShapeND) : DoubleNd4jArrayFieldOps(), FieldND<Double, Float64Field>
 
-public fun DoubleField.nd4j(shapeFirst: Int, vararg shapeRest: Int): DoubleNd4jArrayField =
+public fun Float64Field.nd4j(shapeFirst: Int, vararg shapeRest: Int): DoubleNd4jArrayField =
     DoubleNd4jArrayField(ShapeND(shapeFirst, * shapeRest))
 
 
 /**
  * Represents [FieldND] over [Nd4jArrayStructure] of [Float].
  */
-public open class FloatNd4jArrayFieldOps : Nd4jArrayExtendedFieldOps<Float, FloatField> {
+public open class FloatNd4jArrayFieldOps : Nd4jArrayExtendedFieldOps<Float, Float32Field> {
-    override val elementAlgebra: FloatField get() = FloatField
+    override val elementAlgebra: Float32Field get() = Float32Field
 
     override fun INDArray.wrap(): Nd4jArrayStructure<Float> = asFloatStructure()
 
@@ -272,18 +272,18 @@ public open class FloatNd4jArrayFieldOps : Nd4jArrayExtendedFieldOps<Float, Floa
     public companion object : FloatNd4jArrayFieldOps()
 }
 
-public class FloatNd4jArrayField(override val shape: ShapeND) : FloatNd4jArrayFieldOps(), RingND<Float, FloatField>
+public class FloatNd4jArrayField(override val shape: ShapeND) : FloatNd4jArrayFieldOps(), RingND<Float, Float32Field>
 
-public val FloatField.nd4j: FloatNd4jArrayFieldOps get() = FloatNd4jArrayFieldOps
+public val Float32Field.nd4j: FloatNd4jArrayFieldOps get() = FloatNd4jArrayFieldOps
 
-public fun FloatField.nd4j(shapeFirst: Int, vararg shapeRest: Int): FloatNd4jArrayField =
+public fun Float32Field.nd4j(shapeFirst: Int, vararg shapeRest: Int): FloatNd4jArrayField =
     FloatNd4jArrayField(ShapeND(shapeFirst, * shapeRest))
 
 /**
  * Represents [RingND] over [Nd4jArrayIntStructure].
  */
-public open class IntNd4jArrayRingOps : Nd4jArrayRingOps<Int, IntRing> {
+public open class IntNd4jArrayRingOps : Nd4jArrayRingOps<Int, Int32Ring> {
-    override val elementAlgebra: IntRing get() = IntRing
+    override val elementAlgebra: Int32Ring get() = Int32Ring
 
     override fun INDArray.wrap(): Nd4jArrayStructure<Int> = asIntStructure()
 
@@ -311,9 +311,9 @@ public open class IntNd4jArrayRingOps : Nd4jArrayRingOps<Int, IntRing> {
     public companion object : IntNd4jArrayRingOps()
 }
 
-public val IntRing.nd4j: IntNd4jArrayRingOps get() = IntNd4jArrayRingOps
+public val Int32Ring.nd4j: IntNd4jArrayRingOps get() = IntNd4jArrayRingOps
 
-public class IntNd4jArrayRing(override val shape: ShapeND) : IntNd4jArrayRingOps(), RingND<Int, IntRing>
+public class IntNd4jArrayRing(override val shape: ShapeND) : IntNd4jArrayRingOps(), RingND<Int, Int32Ring>
 
-public fun IntRing.nd4j(shapeFirst: Int, vararg shapeRest: Int): IntNd4jArrayRing =
+public fun Int32Ring.nd4j(shapeFirst: Int, vararg shapeRest: Int): IntNd4jArrayRing =
     IntNd4jArrayRing(ShapeND(shapeFirst, * shapeRest))

kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jTensorAlgebra.kt

@@ -15,8 +15,8 @@ import org.nd4j.linalg.ops.transforms.Transforms
 import space.kscience.kmath.PerformancePitfall
 import space.kscience.kmath.UnsafeKMathAPI
 import space.kscience.kmath.nd.*
-import space.kscience.kmath.operations.DoubleField
 import space.kscience.kmath.operations.Field
+import space.kscience.kmath.operations.Float64Field
 import space.kscience.kmath.tensors.api.AnalyticTensorAlgebra
 import space.kscience.kmath.tensors.api.Tensor
 import space.kscience.kmath.tensors.api.TensorAlgebra
@@ -171,14 +171,14 @@ public sealed interface Nd4jTensorAlgebra<T : Number, A : Field<T>> : AnalyticTe
 /**
  * [Double] specialization of [Nd4jTensorAlgebra].
  */
-public object DoubleNd4jTensorAlgebra : Nd4jTensorAlgebra<Double, DoubleField> {
+public object DoubleNd4jTensorAlgebra : Nd4jTensorAlgebra<Double, Float64Field> {
 
-    override val elementAlgebra: DoubleField get() = DoubleField
+    override val elementAlgebra: Float64Field get() = Float64Field
 
     override fun INDArray.wrap(): Nd4jArrayStructure<Double> = asDoubleStructure()
 
     @OptIn(UnsafeKMathAPI::class)
-    override fun structureND(shape: ShapeND, initializer: DoubleField.(IntArray) -> Double): Nd4jArrayStructure<Double> {
+    override fun structureND(shape: ShapeND, initializer: Float64Field.(IntArray) -> Double): Nd4jArrayStructure<Double> {
         val array: INDArray = Nd4j.zeros(*shape.asArray())
         val indices = ColumnStrides(shape)
         indices.asSequence().forEach { index ->

kmath-nd4j/src/test/kotlin/space/kscience/kmath/nd4j/Nd4jArrayAlgebraTest.kt

@@ -10,8 +10,8 @@ import space.kscience.kmath.PerformancePitfall
 import space.kscience.kmath.nd.StructureND
 import space.kscience.kmath.nd.one
 import space.kscience.kmath.nd.structureND
-import space.kscience.kmath.operations.DoubleField
+import space.kscience.kmath.operations.Float64Field
-import space.kscience.kmath.operations.IntRing
+import space.kscience.kmath.operations.Int32Ring
 import space.kscience.kmath.operations.invoke
 import kotlin.math.PI
 import kotlin.test.Test
@@ -23,7 +23,7 @@ import kotlin.test.fail
 internal class Nd4jArrayAlgebraTest {
     @Test
     fun testProduce() {
-        val res = DoubleField.nd4j.structureND(2, 2) { it.sum().toDouble() }
+        val res = Float64Field.nd4j.structureND(2, 2) { it.sum().toDouble() }
         val expected = (Nd4j.create(2, 2) ?: fail()).asDoubleStructure()
         expected[intArrayOf(0, 0)] = 0.0
         expected[intArrayOf(0, 1)] = 1.0
@@ -34,7 +34,7 @@ internal class Nd4jArrayAlgebraTest {
 
     @Test
     fun testMap() {
-        val res = IntRing.nd4j {
+        val res = Int32Ring.nd4j {
             one(2, 2).map { it + it * 2 }
         }
         val expected = (Nd4j.create(2, 2) ?: fail()).asIntStructure()
@@ -47,7 +47,7 @@ internal class Nd4jArrayAlgebraTest {
 
     @Test
     fun testAdd() {
-        val res = IntRing.nd4j { one(2, 2) + 25 }
+        val res = Int32Ring.nd4j { one(2, 2) + 25 }
         val expected = (Nd4j.create(2, 2) ?: fail()).asIntStructure()
         expected[intArrayOf(0, 0)] = 26
         expected[intArrayOf(0, 1)] = 26
@@ -57,7 +57,7 @@ internal class Nd4jArrayAlgebraTest {
     }
 
     @Test
-    fun testSin() = DoubleField.nd4j{
+    fun testSin() = Float64Field.nd4j{
         val initial = structureND(2, 2) { (i, j) -> if (i == j) PI / 2 else 0.0 }
         val transformed = sin(initial)
         val expected = structureND(2, 2) { (i, j) -> if (i == j) 1.0 else 0.0 }

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

@@ -9,8 +9,8 @@ import space.kscience.kmath.UnstableKMathAPI
 import space.kscience.kmath.expressions.*
 import space.kscience.kmath.linear.*
 import space.kscience.kmath.misc.log
-import space.kscience.kmath.operations.DoubleField
 import space.kscience.kmath.operations.DoubleL2Norm
+import space.kscience.kmath.operations.Float64Field
 import space.kscience.kmath.operations.algebra
 import space.kscience.kmath.structures.DoubleBuffer
 import kotlin.math.abs
@@ -32,7 +32,7 @@ public class QowRuns(public val runs: Int) : OptimizationFeature {
 @UnstableKMathAPI
 public object QowOptimizer : Optimizer<Double, XYFit> {
 
-    private val linearSpace: LinearSpace<Double, DoubleField> = Double.algebra.linearSpace
+    private val linearSpace: LinearSpace<Double, Float64Field> = Double.algebra.linearSpace
     private val solver: LinearSolver<Double> = linearSpace.lupSolver()
 
     @OptIn(UnstableKMathAPI::class)

kmath-stat/src/commonMain/kotlin/space/kscience/kmath/distributions/NormalDistribution.kt

@@ -6,7 +6,7 @@
 package space.kscience.kmath.distributions
 
 import space.kscience.kmath.chains.Chain
-import space.kscience.kmath.operations.DoubleField.pow
+import space.kscience.kmath.operations.Float64Field.pow
 import space.kscience.kmath.random.RandomGenerator
 import space.kscience.kmath.samplers.GaussianSampler
 import space.kscience.kmath.samplers.InternalErf

kmath-stat/src/commonMain/kotlin/space/kscience/kmath/series/VarianceRatioTest.kt

@@ -6,7 +6,7 @@
 package space.kscience.kmath.series
 
 import space.kscience.kmath.distributions.NormalDistribution
-import space.kscience.kmath.operations.DoubleField.pow
+import space.kscience.kmath.operations.Float64Field.pow
 import space.kscience.kmath.operations.fold
 import kotlin.math.absoluteValue
 

kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/Mean.kt

@@ -13,21 +13,20 @@ import space.kscience.kmath.structures.indices
  * Arithmetic mean
  */
 public class Mean<T>(
-    private val group: Ring<T>,
+    private val field: Field<T>
-    private val division: (sum: T, count: Int) -> T,
 ) : ComposableStatistic<T, Pair<T, Int>, T>, BlockingStatistic<T, T> {
 
-    override fun evaluateBlocking(data: Buffer<T>): T = group {
+    override fun evaluateBlocking(data: Buffer<T>): T = with(field) {
         var res = zero
         for (i in data.indices) {
             res += data[i]
         }
-        division(res, data.size)
+        res / data.size
     }
 
     override suspend fun evaluate(data: Buffer<T>): T = super<ComposableStatistic>.evaluate(data)
 
-    override suspend fun computeIntermediate(data: Buffer<T>): Pair<T, Int> = group {
+    override suspend fun computeIntermediate(data: Buffer<T>): Pair<T, Int> = with(field) {
         var res = zero
         for (i in data.indices) {
             res += data[i]
@@ -36,32 +35,23 @@ public class Mean<T>(
     }
 
     override suspend fun composeIntermediate(first: Pair<T, Int>, second: Pair<T, Int>): Pair<T, Int> =
-        group { first.first + second.first } to (first.second + second.second)
+        with(field) { first.first + second.first } to (first.second + second.second)
 
-    override suspend fun toResult(intermediate: Pair<T, Int>): T = group {
+    override suspend fun toResult(intermediate: Pair<T, Int>): T = with(field) {
-        division(intermediate.first, intermediate.second)
+        intermediate.first/ intermediate.second
     }
 
     public companion object {
-        @Deprecated("Use Double.mean instead")
+        public fun evaluate(buffer: Buffer<Double>): Double = Float64Field.mean.evaluateBlocking(buffer)
-        public val double: Mean<Double> = Mean(DoubleField) { sum, count -> sum / count }
+        public fun evaluate(buffer: Buffer<Int>): Int = Int32Ring.mean.evaluateBlocking(buffer)
-
+        public fun evaluate(buffer: Buffer<Long>): Long = Int64Ring.mean.evaluateBlocking(buffer)
-        @Deprecated("Use Int.mean instead")
-        public val int: Mean<Int> = Mean(IntRing) { sum, count -> sum / count }
-
-        @Deprecated("Use Long.mean instead")
-        public val long: Mean<Long> = Mean(LongRing) { sum, count -> sum / count }
-
-        public fun evaluate(buffer: Buffer<Double>): Double = DoubleField.mean.evaluateBlocking(buffer)
-        public fun evaluate(buffer: Buffer<Int>): Int = IntRing.mean.evaluateBlocking(buffer)
-        public fun evaluate(buffer: Buffer<Long>): Long = LongRing.mean.evaluateBlocking(buffer)
     }
 }
 
 
 //TODO replace with optimized version which respects overflow
-public val DoubleField.mean: Mean<Double> get() = Mean(DoubleField) { sum, count -> sum / count }
+public val Float64Field.mean: Mean<Double> get() = Mean(Float64Field)
-public val IntRing.mean: Mean<Int> get() = Mean(IntRing) { sum, count -> sum / count }
+public val Int32Ring.mean: Mean<Int> get() = Mean(Int32Field)
-public val LongRing.mean: Mean<Long> get() = Mean(LongRing) { sum, count -> sum / count }
+public val Int64Ring.mean: Mean<Long> get() = Mean(Int64Field)
 
 

kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/Median.kt

@@ -5,17 +5,34 @@
 
 package space.kscience.kmath.stat
 
-import space.kscience.kmath.operations.asSequence
+import space.kscience.kmath.misc.sortedWith
+import space.kscience.kmath.operations.*
 import space.kscience.kmath.structures.Buffer
 
 /**
  * Non-composable median
  */
-public class Median<T>(private val comparator: Comparator<T>) : BlockingStatistic<T, T> {
+public class Median<T>(private val field: Field<T>, private val comparator: Comparator<T>) : BlockingStatistic<T, T> {
-    override fun evaluateBlocking(data: Buffer<T>): T =
+
-        data.asSequence().sortedWith(comparator).toList()[data.size / 2] //TODO check if this is correct
+    override fun evaluateBlocking(data: Buffer<T>): T = when {
+        data.size == 0 -> error("Can't compute median of an empty buffer")
+        data.size == 1 -> data[0]
+        data.size % 2 == 0 -> with(field) {
+            val sorted = data.sortedWith(comparator)
+            (sorted[data.size / 2 - 1] + sorted[data.size / 2]) / 2
+        }
+
+        else -> data.sortedWith(comparator)[(data.size - 1) / 2]
+    }
 
     public companion object {
-        public val real: Median<Double> = Median { a: Double, b: Double -> a.compareTo(b) }
+
+        public fun evaluate(buffer: Buffer<Double>): Double = Float64Field.mean.evaluateBlocking(buffer)
+        public fun evaluate(buffer: Buffer<Int>): Int = Int32Ring.mean.evaluateBlocking(buffer)
+        public fun evaluate(buffer: Buffer<Long>): Long = Int64Ring.mean.evaluateBlocking(buffer)
     }
-}
+}
+
+public val Float64Field.median: Median<Double> get() = Median(Float64Field) { a, b -> a.compareTo(b) }
+public val Int32Ring.median: Median<Int> get() = Median(Int32Field) { a, b -> a.compareTo(b) }
+public val Int64Ring.median: Median<Long> get() = Median(Int64Field) { a, b -> a.compareTo(b) }

kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/Statistic.kt

@@ -15,7 +15,7 @@ import space.kscience.kmath.coroutines.mapParallel
 import space.kscience.kmath.structures.Buffer
 
 /**
- * A function, that transforms a buffer of random quantities to some resulting value
+ * A function that transforms a buffer of random quantities to some resulting value
  */
 public fun interface Statistic<in T, out R> {
     public suspend fun evaluate(data: Buffer<T>): R
@@ -67,7 +67,7 @@ private fun <T, I, R> ComposableStatistic<T, I, R>.flowIntermediate(
 
 
 /**
- * Perform a streaming statistical analysis on a chunked data. The computation of inner representation is done in parallel
+ * Perform a streaming statistical analysis on chunked data. The computation of inner representation is done in parallel
  * if [dispatcher] allows it.
  *
  * The resulting flow contains values that include the whole previous statistics, not only the last chunk.

kmath-stat/src/commonTest/kotlin/space/kscience/kmath/stat/TestBasicStatistics.kt

@@ -0,0 +1,31 @@
+/*
+ * 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.stat
+
+import space.kscience.kmath.UnstableKMathAPI
+import space.kscience.kmath.operations.Float64Field
+import space.kscience.kmath.random.RandomGenerator
+import space.kscience.kmath.structures.slice
+import kotlin.test.Test
+import kotlin.test.assertEquals
+
+@OptIn(UnstableKMathAPI::class)
+class TestBasicStatistics {
+    companion object {
+        val float64Sample = RandomGenerator.default(123).nextDoubleBuffer(100)
+    }
+
+    @Test
+    fun medianFloat64() {
+        assertEquals(0.508, Float64Field.median(float64Sample), 0.0005)
+        assertEquals(0.5055, Float64Field.median(float64Sample.slice { 0..<last }), 0.0005)
+    }
+
+    @Test
+    fun meanFloat64() {
+        assertEquals(0.488, Float64Field.mean(float64Sample), 0.0002)
+    }
+}

kmath-stat/src/jvmTest/kotlin/space/kscience/kmath/stat/StatisticTest.kt

@@ -9,7 +9,7 @@ import kotlinx.coroutines.flow.first
 import kotlinx.coroutines.flow.last
 import kotlinx.coroutines.flow.take
 import kotlinx.coroutines.runBlocking
-import space.kscience.kmath.operations.DoubleField
+import space.kscience.kmath.operations.Float64Field
 import space.kscience.kmath.random.RandomGenerator
 import space.kscience.kmath.random.chain
 import space.kscience.kmath.streaming.chunked
@@ -29,20 +29,20 @@ internal class StatisticTest {
     @Test
     fun singleBlockingMean() {
         val first = runBlocking { chunked.first() }
-        val res = DoubleField.mean(first)
+        val res = Float64Field.mean(first)
         assertEquals(0.5, res, 1e-1)
     }
 
     @Test
     fun singleSuspendMean() = runBlocking {
         val first = runBlocking { chunked.first() }
-        val res = DoubleField.mean(first)
+        val res = Float64Field.mean(first)
         assertEquals(0.5, res, 1e-1)
     }
 
     @Test
     fun parallelMean() = runBlocking {
-        val average = DoubleField.mean
+        val average = Float64Field.mean
             .flow(chunked) //create a flow from evaluated results
             .take(100) // Take 100 data chunks from the source and accumulate them
             .last() //get 1e5 data samples average

kmath-tensorflow/src/main/kotlin/space/kscience/kmath/tensorflow/DoubleTensorFlowAlgebra.kt

@@ -16,7 +16,7 @@ import space.kscience.kmath.expressions.Symbol
 import space.kscience.kmath.nd.ColumnStrides
 import space.kscience.kmath.nd.ShapeND
 import space.kscience.kmath.nd.StructureND
-import space.kscience.kmath.operations.DoubleField
+import space.kscience.kmath.operations.Float64Field
 import space.kscience.kmath.operations.PowerOperations
 
 public class DoubleTensorFlowOutput(
@@ -32,13 +32,13 @@ internal fun ShapeND.toLongArray(): LongArray = LongArray(size) { get(it).toLong
 
 public class DoubleTensorFlowAlgebra internal constructor(
     graph: Graph,
-) : TensorFlowAlgebra<Double, TFloat64, DoubleField>(graph), PowerOperations<StructureND<Double>> {
+) : TensorFlowAlgebra<Double, TFloat64, Float64Field>(graph), PowerOperations<StructureND<Double>> {
 
-    override val elementAlgebra: DoubleField get() = DoubleField
+    override val elementAlgebra: Float64Field get() = Float64Field
 
     override fun structureND(
         shape: ShapeND,
-        initializer: DoubleField.(IntArray) -> Double,
+        initializer: Float64Field.(IntArray) -> Double,
     ): StructureND<Double> {
         val res = TFloat64.tensorOf(org.tensorflow.ndarray.Shape.of(*shape.toLongArray())) { array ->
             ColumnStrides(shape).forEach { index ->
@@ -83,7 +83,7 @@ public class DoubleTensorFlowAlgebra internal constructor(
  * The resulting tensor is available outside of scope
  */
 @UnstableKMathAPI
-public fun DoubleField.produceWithTF(
+public fun Float64Field.produceWithTF(
     block: DoubleTensorFlowAlgebra.() -> StructureND<Double>,
 ): StructureND<Double> = Graph().use { graph ->
     val scope = DoubleTensorFlowAlgebra(graph)
@@ -96,7 +96,7 @@ public fun DoubleField.produceWithTF(
  * The resulting tensors are available outside of scope
  */
 @OptIn(UnstableKMathAPI::class)
-public fun DoubleField.produceMapWithTF(
+public fun Float64Field.produceMapWithTF(
     block: DoubleTensorFlowAlgebra.() -> Map<Symbol, StructureND<Double>>,
 ): Map<Symbol, StructureND<Double>> = Graph().use { graph ->
     val scope = DoubleTensorFlowAlgebra(graph)

kmath-tensorflow/src/test/kotlin/space/kscience/kmath/tensorflow/DoubleTensorFlowOps.kt

@@ -10,7 +10,7 @@ import space.kscience.kmath.UnstableKMathAPI
 import space.kscience.kmath.nd.ShapeND
 import space.kscience.kmath.nd.get
 import space.kscience.kmath.nd.structureND
-import space.kscience.kmath.operations.DoubleField
+import space.kscience.kmath.operations.Float64Field
 import space.kscience.kmath.tensors.core.DoubleTensorAlgebra
 import space.kscience.kmath.tensors.core.DoubleTensorAlgebra.Companion.sum
 import space.kscience.kmath.tensors.core.randomNormal
@@ -20,7 +20,7 @@ import kotlin.test.assertEquals
 class DoubleTensorFlowOps {
     @Test
     fun basicOps() {
-        val res = DoubleField.produceWithTF {
+        val res = Float64Field.produceWithTF {
             val initial = structureND(2, 2) { 1.0 }
 
             initial + (initial * 2.0)
@@ -36,14 +36,14 @@ class DoubleTensorFlowOps {
         val tensor1 = DoubleTensorAlgebra.randomNormal(shape = ShapeND(dim, dim), 12224)
         val tensor2 = DoubleTensorAlgebra.randomNormal(shape = ShapeND(dim, dim), 12225)
 
-        DoubleField.produceWithTF {
+        Float64Field.produceWithTF {
             tensor1 dot tensor2
         }.sum()
     }
 
     @Test
     fun extensionOps(){
-        val res = DoubleField.produceWithTF {
+        val res = Float64Field.produceWithTF {
             val i = structureND(2, 2) { 0.5 }
 
             sin(i).pow(2) + cos(i).pow(2)

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

@@ -11,25 +11,28 @@ package space.kscience.kmath.tensors.core
 import space.kscience.kmath.PerformancePitfall
 import space.kscience.kmath.nd.*
 import space.kscience.kmath.operations.DoubleBufferOps
-import space.kscience.kmath.operations.DoubleField
+import space.kscience.kmath.operations.Float64Field
 import space.kscience.kmath.structures.*
 import space.kscience.kmath.tensors.api.AnalyticTensorAlgebra
 import space.kscience.kmath.tensors.api.LinearOpsTensorAlgebra
 import space.kscience.kmath.tensors.api.Tensor
 import space.kscience.kmath.tensors.core.internal.*
-import kotlin.math.*
+import kotlin.math.abs
+import kotlin.math.ceil
+import kotlin.math.floor
+import kotlin.math.sqrt
 
 /**
  * Implementation of basic operations over double tensors and basic algebra operations on them.
  */
 @OptIn(PerformancePitfall::class)
 public open class DoubleTensorAlgebra :
-    AnalyticTensorAlgebra<Double, DoubleField>,
+    AnalyticTensorAlgebra<Double, Float64Field>,
-    LinearOpsTensorAlgebra<Double, DoubleField> {
+    LinearOpsTensorAlgebra<Double, Float64Field> {
 
     public companion object : DoubleTensorAlgebra()
 
-    override val elementAlgebra: DoubleField get() = DoubleField
+    override val elementAlgebra: Float64Field get() = Float64Field
 
     public val bufferAlgebra: DoubleBufferOps get() = DoubleBufferOps
 
@@ -41,10 +44,10 @@ public open class DoubleTensorAlgebra :
      * @return the resulting tensor after applying the function.
      */
     @Suppress("OVERRIDE_BY_INLINE")
-    final override inline fun StructureND<Double>.map(transform: DoubleField.(Double) -> Double): DoubleTensor {
+    final override inline fun StructureND<Double>.map(transform: Float64Field.(Double) -> Double): DoubleTensor {
         val tensor = asDoubleTensor()
         //TODO remove additional copy
-        val array = DoubleBuffer(tensor.source.size) { DoubleField.transform(tensor.source[it]) }
+        val array = DoubleBuffer(tensor.source.size) { Float64Field.transform(tensor.source[it]) }
         return DoubleTensor(
             tensor.shape,
             array,
@@ -59,12 +62,12 @@ public open class DoubleTensorAlgebra :
         }
     }
 
-    public inline fun Tensor<Double>.mapIndexedInPlace(operation: DoubleField.(IntArray, Double) -> Double) {
+    public inline fun Tensor<Double>.mapIndexedInPlace(operation: Float64Field.(IntArray, Double) -> Double) {
-        indices.forEach { set(it, DoubleField.operation(it, get(it))) }
+        indices.forEach { set(it, Float64Field.operation(it, get(it))) }
     }
 
     @Suppress("OVERRIDE_BY_INLINE")
-    final override inline fun StructureND<Double>.mapIndexed(transform: DoubleField.(index: IntArray, Double) -> Double): DoubleTensor {
+    final override inline fun StructureND<Double>.mapIndexed(transform: Float64Field.(index: IntArray, Double) -> Double): DoubleTensor {
         return copyToTensor().apply { mapIndexedInPlace(transform) }
     }
 
@@ -73,14 +76,14 @@ public open class DoubleTensorAlgebra :
     final override inline fun zip(
         left: StructureND<Double>,
         right: StructureND<Double>,
-        transform: DoubleField.(Double, Double) -> Double,
+        transform: Float64Field.(Double, Double) -> Double,
     ): DoubleTensor {
         checkShapesCompatible(left, right)
 
         val leftTensor = left.asDoubleTensor()
         val rightTensor = right.asDoubleTensor()
         val buffer = DoubleBuffer(leftTensor.source.size) {
-            DoubleField.transform(leftTensor.source[it], rightTensor.source[it])
+            Float64Field.transform(leftTensor.source[it], rightTensor.source[it])
         }
         return DoubleTensor(leftTensor.shape, buffer)
     }
@@ -124,9 +127,9 @@ public open class DoubleTensorAlgebra :
      * @param initializer mapping tensor indices to values.
      * @return tensor with the [shape] shape and data generated by the [initializer].
      */
-    override fun structureND(shape: ShapeND, initializer: DoubleField.(IntArray) -> Double): DoubleTensor = fromArray(
+    override fun structureND(shape: ShapeND, initializer: Float64Field.(IntArray) -> Double): DoubleTensor = fromArray(
         shape,
-        RowStrides(shape).asSequence().map { DoubleField.initializer(it) }.toMutableList().toDoubleArray()
+        RowStrides(shape).asSequence().map { Float64Field.initializer(it) }.toMutableList().toDoubleArray()
     )
 
     override fun Tensor<Double>.getTensor(i: Int): DoubleTensor {
@@ -717,4 +720,4 @@ public open class DoubleTensorAlgebra :
 }
 
 public val Double.Companion.tensorAlgebra: DoubleTensorAlgebra get() = DoubleTensorAlgebra
-public val DoubleField.tensorAlgebra: DoubleTensorAlgebra get() = DoubleTensorAlgebra
+public val Float64Field.tensorAlgebra: DoubleTensorAlgebra get() = DoubleTensorAlgebra

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

@@ -10,7 +10,7 @@ package space.kscience.kmath.tensors.core
 
 import space.kscience.kmath.PerformancePitfall
 import space.kscience.kmath.nd.*
-import space.kscience.kmath.operations.IntRing
+import space.kscience.kmath.operations.Int32Ring
 import space.kscience.kmath.structures.*
 import space.kscience.kmath.tensors.api.*
 import space.kscience.kmath.tensors.core.internal.*
@@ -19,12 +19,12 @@ import kotlin.math.*
 /**
  * Implementation of basic operations over double tensors and basic algebra operations on them.
  */
-public open class IntTensorAlgebra : TensorAlgebra<Int, IntRing> {
+public open class IntTensorAlgebra : TensorAlgebra<Int, Int32Ring> {
 
     public companion object : IntTensorAlgebra()
 
 
-    override val elementAlgebra: IntRing get() = IntRing
+    override val elementAlgebra: Int32Ring get() = Int32Ring
 
 
     /**
@@ -34,10 +34,10 @@ public open class IntTensorAlgebra : TensorAlgebra<Int, IntRing> {
      * @return the resulting tensor after applying the function.
      */
     @Suppress("OVERRIDE_BY_INLINE")
-    final override inline fun StructureND<Int>.map(transform: IntRing.(Int) -> Int): IntTensor {
+    final override inline fun StructureND<Int>.map(transform: Int32Ring.(Int) -> Int): IntTensor {
         val tensor = this.asIntTensor()
         //TODO remove additional copy
-        val array = IntBuffer(tensor.source.size) { IntRing.transform(tensor.source[it]) }
+        val array = IntBuffer(tensor.source.size) { Int32Ring.transform(tensor.source[it]) }
         return IntTensor(
             tensor.shape,
             array,
@@ -57,11 +57,11 @@ public open class IntTensorAlgebra : TensorAlgebra<Int, IntRing> {
     }
 
     @Suppress("OVERRIDE_BY_INLINE")
-    final override inline fun StructureND<Int>.mapIndexed(transform: IntRing.(index: IntArray, Int) -> Int): IntTensor {
+    final override inline fun StructureND<Int>.mapIndexed(transform: Int32Ring.(index: IntArray, Int) -> Int): IntTensor {
         val tensor = this.asIntTensor()
         //TODO remove additional copy
         val buffer = IntBuffer(tensor.source.size) {
-            IntRing.transform(tensor.indices.index(it), tensor.source[it])
+            Int32Ring.transform(tensor.indices.index(it), tensor.source[it])
         }
         return IntTensor(tensor.shape, buffer)
     }
@@ -70,14 +70,14 @@ public open class IntTensorAlgebra : TensorAlgebra<Int, IntRing> {
     final override inline fun zip(
         left: StructureND<Int>,
         right: StructureND<Int>,
-        transform: IntRing.(Int, Int) -> Int,
+        transform: Int32Ring.(Int, Int) -> Int,
     ): IntTensor {
         checkShapesCompatible(left, right)
 
         val leftTensor = left.asIntTensor()
         val rightTensor = right.asIntTensor()
         val buffer = IntBuffer(leftTensor.source.size) {
-            IntRing.transform(leftTensor.source[it], rightTensor.source[it])
+            Int32Ring.transform(leftTensor.source[it], rightTensor.source[it])
         }
         return IntTensor(leftTensor.shape, buffer)
     }
@@ -118,9 +118,9 @@ public open class IntTensorAlgebra : TensorAlgebra<Int, IntRing> {
      * @param initializer mapping tensor indices to values.
      * @return tensor with the [shape] shape and data generated by the [initializer].
      */
-    override fun structureND(shape: ShapeND, initializer: IntRing.(IntArray) -> Int): IntTensor = fromArray(
+    override fun structureND(shape: ShapeND, initializer: Int32Ring.(IntArray) -> Int): IntTensor = fromArray(
         shape,
-        RowStrides(shape).asSequence().map { IntRing.initializer(it) }.toMutableList().toIntArray()
+        RowStrides(shape).asSequence().map { Int32Ring.initializer(it) }.toMutableList().toIntArray()
     )
 
     override fun Tensor<Int>.getTensor(i: Int): IntTensor {
@@ -462,6 +462,6 @@ public open class IntTensorAlgebra : TensorAlgebra<Int, IntRing> {
 }
 
 public val Int.Companion.tensorAlgebra: IntTensorAlgebra get() = IntTensorAlgebra
-public val IntRing.tensorAlgebra: IntTensorAlgebra get() = IntTensorAlgebra
+public val Int32Ring.tensorAlgebra: IntTensorAlgebra get() = IntTensorAlgebra
 
 

kmath-viktor/src/main/kotlin/space/kscience/kmath/viktor/ViktorFieldOpsND.kt

@@ -12,15 +12,15 @@ import space.kscience.kmath.PerformancePitfall
 import space.kscience.kmath.UnsafeKMathAPI
 import space.kscience.kmath.UnstableKMathAPI
 import space.kscience.kmath.nd.*
-import space.kscience.kmath.operations.DoubleField
 import space.kscience.kmath.operations.ExtendedFieldOps
+import space.kscience.kmath.operations.Float64Field
 import space.kscience.kmath.operations.NumbersAddOps
 import space.kscience.kmath.operations.PowerOperations
 
 @OptIn(UnstableKMathAPI::class, PerformancePitfall::class)
 @Suppress("OVERRIDE_BY_INLINE", "NOTHING_TO_INLINE")
 public open class ViktorFieldOpsND :
-    FieldOpsND<Double, DoubleField>,
+    FieldOpsND<Double, Float64Field>,
     ExtendedFieldOps<StructureND<Double>>,
     PowerOperations<StructureND<Double>> {
 
@@ -30,13 +30,13 @@ public open class ViktorFieldOpsND :
             else -> structureND(shape) { this@f64Buffer[it] }.f64Buffer
         }
 
-    override val elementAlgebra: DoubleField get() = DoubleField
+    override val elementAlgebra: Float64Field get() = Float64Field
 
     @OptIn(UnsafeKMathAPI::class)
-    override fun structureND(shape: ShapeND, initializer: DoubleField.(IntArray) -> Double): ViktorStructureND =
+    override fun structureND(shape: ShapeND, initializer: Float64Field.(IntArray) -> Double): ViktorStructureND =
         F64Array(*shape.asArray()).apply {
             ColumnStrides(shape).asSequence().forEach { index ->
-                set(value = DoubleField.initializer(index), indices = index)
+                set(value = Float64Field.initializer(index), indices = index)
             }
         }.asStructure()
 
@@ -44,20 +44,20 @@ public open class ViktorFieldOpsND :
 
     @OptIn(UnsafeKMathAPI::class)
     @PerformancePitfall
-    override fun StructureND<Double>.map(transform: DoubleField.(Double) -> Double): ViktorStructureND =
+    override fun StructureND<Double>.map(transform: Float64Field.(Double) -> Double): ViktorStructureND =
         F64Array(*shape.asArray()).apply {
             ColumnStrides(ShapeND(shape)).asSequence().forEach { index ->
-                set(value = DoubleField.transform(this@map[index]), indices = index)
+                set(value = Float64Field.transform(this@map[index]), indices = index)
             }
         }.asStructure()
 
     @OptIn(UnsafeKMathAPI::class)
     @PerformancePitfall
     override fun StructureND<Double>.mapIndexed(
-        transform: DoubleField.(index: IntArray, Double) -> Double,
+        transform: Float64Field.(index: IntArray, Double) -> Double,
     ): ViktorStructureND = F64Array(*shape.asArray()).apply {
         ColumnStrides(ShapeND(shape)).asSequence().forEach { index ->
-            set(value = DoubleField.transform(index, this@mapIndexed[index]), indices = index)
+            set(value = Float64Field.transform(index, this@mapIndexed[index]), indices = index)
         }
     }.asStructure()
 
@@ -66,12 +66,12 @@ public open class ViktorFieldOpsND :
     override fun zip(
         left: StructureND<Double>,
         right: StructureND<Double>,
-        transform: DoubleField.(Double, Double) -> Double,
+        transform: Float64Field.(Double, Double) -> Double,
     ): ViktorStructureND {
         require(left.shape.contentEquals(right.shape))
         return F64Array(*left.shape.asArray()).apply {
             ColumnStrides(left.shape).asSequence().forEach { index ->
-                set(value = DoubleField.transform(left[index], right[index]), indices = index)
+                set(value = Float64Field.transform(left[index], right[index]), indices = index)
             }
         }.asStructure()
     }
@@ -120,12 +120,12 @@ public open class ViktorFieldOpsND :
     public companion object : ViktorFieldOpsND()
 }
 
-public val DoubleField.viktorAlgebra: ViktorFieldOpsND get() = ViktorFieldOpsND
+public val Float64Field.viktorAlgebra: ViktorFieldOpsND get() = ViktorFieldOpsND
 
 @OptIn(UnstableKMathAPI::class)
 public open class ViktorFieldND(
     private val shapeAsArray: IntArray,
-) : ViktorFieldOpsND(), FieldND<Double, DoubleField>, NumbersAddOps<StructureND<Double>> {
+) : ViktorFieldOpsND(), FieldND<Double, Float64Field>, NumbersAddOps<StructureND<Double>> {
 
     override val shape: ShapeND = ShapeND(shapeAsArray)
 
@@ -137,6 +137,6 @@ public open class ViktorFieldND(
         F64Array.full(init = value.toDouble(), shape = shapeAsArray).asStructure()
 }
 
-public fun DoubleField.viktorAlgebra(vararg shape: Int): ViktorFieldND = ViktorFieldND(shape)
+public fun Float64Field.viktorAlgebra(vararg shape: Int): ViktorFieldND = ViktorFieldND(shape)
 
 public fun ViktorFieldND(vararg shape: Int): ViktorFieldND = ViktorFieldND(shape)