forked from kscience/kmath
0.4 WIP
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@ -19,13 +19,19 @@ import org.ejml.sparse.csc.factory.DecompositionFactory_DSCC
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import org.ejml.sparse.csc.factory.DecompositionFactory_FSCC
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import org.ejml.sparse.csc.factory.LinearSolverFactory_DSCC
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import org.ejml.sparse.csc.factory.LinearSolverFactory_FSCC
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import space.kscience.kmath.UnstableKMathAPI
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import space.kscience.kmath.linear.*
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import space.kscience.kmath.linear.Matrix
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import space.kscience.kmath.UnstableKMathAPI
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import space.kscience.kmath.nd.StructureFeature
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import space.kscience.kmath.operations.Float32Field
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import space.kscience.kmath.structures.Float64
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import space.kscience.kmath.structures.Float32
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import space.kscience.kmath.operations.Float64Field
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import space.kscience.kmath.operations.Float32Field
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import space.kscience.kmath.operations.DoubleField
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import space.kscience.kmath.operations.FloatField
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import space.kscience.kmath.operations.invoke
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import space.kscience.kmath.structures.Float64Buffer
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import space.kscience.kmath.structures.Float32Buffer
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import space.kscience.kmath.structures.DoubleBuffer
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import space.kscience.kmath.structures.FloatBuffer
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import kotlin.reflect.KClass
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@ -54,7 +54,7 @@ public class GaussIntegrator<T : Any>(
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}
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}
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override fun process(integrand: UnivariateIntegrand<T>): UnivariateIntegrand<T> = with(algebra) {
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override fun integrate(integrand: UnivariateIntegrand<T>): UnivariateIntegrand<T> = with(algebra) {
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val f = integrand.function
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val (points, weights) = buildRule(integrand)
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var res: T = zero
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@ -68,7 +68,7 @@ public class GaussIntegrator<T : Any>(
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res = t
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}
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return integrand.withAttributes {
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value(res)
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IntegrandValue(res)
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IntegrandCallsPerformed(integrand.calls + points.size)
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}
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}
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@ -102,7 +102,7 @@ public inline fun <reified T : Any> GaussIntegrator<T>.integrate(
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val ranges = UnivariateIntegrandRanges(
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(0 until intervals).map { i -> (range.start + rangeSize * i)..(range.start + rangeSize * (i + 1)) to order }
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)
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return process(
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return integrate(
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UnivariateIntegrand<T>(
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attributeBuilder = {
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IntegrationRange(range)
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@ -8,9 +8,9 @@ package space.kscience.kmath.integration
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/**
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* A general interface for all integrators.
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*/
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public interface Integrator<I : Integrand> {
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public interface Integrator<T, I : Integrand<T>> {
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/**
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* Runs one integration pass and return a new [Integrand] with a new set of features.
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*/
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public fun process(integrand: I): I
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public fun integrate(integrand: I): I
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}
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@ -44,12 +44,12 @@ public class SimpsonIntegrator<T : Any>(
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return res
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}
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override fun process(integrand: UnivariateIntegrand<T>): UnivariateIntegrand<T> {
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override fun integrate(integrand: UnivariateIntegrand<T>): UnivariateIntegrand<T> {
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val ranges = integrand[UnivariateIntegrandRanges]
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return if (ranges != null) {
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val res = algebra.sum(ranges.ranges.map { integrateRange(integrand, it.first, it.second) })
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integrand.withAttributes {
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value(res)
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IntegrandValue(res)
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IntegrandCallsPerformed(integrand.calls + ranges.ranges.sumOf { it.second })
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}
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} else {
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@ -58,7 +58,7 @@ public class SimpsonIntegrator<T : Any>(
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val range = integrand[IntegrationRange] ?: 0.0..1.0
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val res = integrateRange(integrand, range, numPoints)
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integrand.withAttributes {
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value(res)
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IntegrandValue(res)
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IntegrandCallsPerformed(integrand.calls + numPoints)
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}
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}
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@ -96,12 +96,12 @@ public object DoubleSimpsonIntegrator : UnivariateIntegrator<Double> {
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return res
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}
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override fun process(integrand: UnivariateIntegrand<Double>): UnivariateIntegrand<Double> {
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override fun integrate(integrand: UnivariateIntegrand<Double>): UnivariateIntegrand<Double> {
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val ranges = integrand[UnivariateIntegrandRanges]
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return if (ranges != null) {
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val res = ranges.ranges.sumOf { integrateRange(integrand, it.first, it.second) }
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integrand.withAttributes {
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value(res)
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IntegrandValue(res)
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IntegrandCallsPerformed(integrand.calls + ranges.ranges.sumOf { it.second })
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}
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} else {
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@ -110,7 +110,7 @@ public object DoubleSimpsonIntegrator : UnivariateIntegrator<Double> {
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val range = integrand[IntegrationRange] ?: 0.0..1.0
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val res = integrateRange(integrand, range, numPoints)
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integrand.withAttributes {
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value(res)
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IntegrandValue(res)
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IntegrandCallsPerformed(integrand.calls + numPoints)
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}
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}
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@ -54,7 +54,7 @@ public class SplineIntegrator<T : Comparable<T>>(
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public val algebra: Field<T>,
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public val bufferFactory: MutableBufferFactory<T>,
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) : UnivariateIntegrator<T> {
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override fun process(integrand: UnivariateIntegrand<T>): UnivariateIntegrand<T> = algebra {
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override fun integrate(integrand: UnivariateIntegrand<T>): UnivariateIntegrand<T> = algebra {
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val range = integrand[IntegrationRange] ?: 0.0..1.0
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val interpolator: PolynomialInterpolator<T> = SplineInterpolator(algebra, bufferFactory)
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@ -72,7 +72,7 @@ public class SplineIntegrator<T : Comparable<T>>(
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)
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val res = polynomials.integrate(algebra, number(range.start)..number(range.endInclusive))
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integrand.withAttributes {
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value(res)
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IntegrandValue(res)
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IntegrandCallsPerformed(integrand.calls + nodes.size)
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}
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}
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@ -86,7 +86,7 @@ public class SplineIntegrator<T : Comparable<T>>(
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*/
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@UnstableKMathAPI
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public object DoubleSplineIntegrator : UnivariateIntegrator<Double> {
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override fun process(integrand: UnivariateIntegrand<Double>): UnivariateIntegrand<Double> {
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override fun integrate(integrand: UnivariateIntegrand<Double>): UnivariateIntegrand<Double> {
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val range = integrand[IntegrationRange] ?: 0.0..1.0
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val interpolator: PolynomialInterpolator<Double> = SplineInterpolator(Float64Field, ::Float64Buffer)
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@ -100,7 +100,7 @@ public object DoubleSplineIntegrator : UnivariateIntegrator<Double> {
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val polynomials = interpolator.interpolatePolynomials(nodes, values)
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val res = polynomials.integrate(Float64Field, range)
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return integrand.withAttributes {
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value(res)
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IntegrandValue(res)
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IntegrandCallsPerformed(integrand.calls + nodes.size)
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}
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}
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@ -34,7 +34,7 @@ public inline fun <reified T : Any> UnivariateIntegrand(
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noinline function: (Double) -> T,
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): UnivariateIntegrand<T> = UnivariateIntegrand(safeTypeOf(), Attributes(attributeBuilder), function)
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public typealias UnivariateIntegrator<T> = Integrator<UnivariateIntegrand<T>>
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public typealias UnivariateIntegrator<T> = Integrator<T, UnivariateIntegrand<T>>
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public object IntegrationRange : IntegrandAttribute<ClosedRange<Double>>
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@ -70,7 +70,7 @@ public fun TypedAttributesBuilder<UnivariateIntegrand<*>>.integrationNodes(varar
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public inline fun <reified T : Any> UnivariateIntegrator<T>.integrate(
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attributesBuilder: TypedAttributesBuilder<UnivariateIntegrand<T>>.() -> Unit,
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noinline function: (Double) -> T,
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): UnivariateIntegrand<T> = process(UnivariateIntegrand(attributesBuilder, function))
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): UnivariateIntegrand<T> = integrate(UnivariateIntegrand(attributesBuilder, function))
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/**
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* A shortcut method to integrate a [function] in [range] with additional features.
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@ -83,7 +83,7 @@ public inline fun <reified T : Any> UnivariateIntegrator<T>.integrate(
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noinline function: (Double) -> T,
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): UnivariateIntegrand<T> {
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return process(
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return integrate(
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UnivariateIntegrand(
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attributeBuilder = {
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IntegrationRange(range)
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@ -31,24 +31,3 @@ public fun QuaternionAlgebra.angleBetween(q1: Quaternion, q2: Quaternion): Angle
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* Euclidean product of two quaternions
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*/
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public infix fun Quaternion.dot(other: Quaternion): Double = w * other.w + x * other.x + y * other.y + z * other.z
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//
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///**
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// * Convert a quaternion to XYZ Cardan angles assuming it is normalized.
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// */
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//private fun Quaternion.normalizedToEuler(): Float32Vector3D {
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// val roll = atan2(2 * y * w + 2 * x * z, 1 - 2 * y * y - 2 * z * z)
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// val pitch = atan2(2 * x * w - 2 * y * z, 1 - 2 * x * x - 2 * z * z)
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// val yaw = asin(2 * x * y + 2 * z * w)
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//
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// return Float32Vector3D(roll, pitch, yaw)
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//}
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///**
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// * Quaternion to XYZ Cardan angles
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// */
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//public fun Quaternion.toEuler(): Float32Vector3D = if (QuaternionAlgebra.norm(this) == 0.0) {
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// Float32Space3D.zero
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//} else {
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// normalized().normalizedToEuler()
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//}
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@ -310,7 +310,11 @@ internal fun DoubleTensorAlgebra.svdHelper(
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}
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}
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private fun pythag(a: Double, b: Double): Double {
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internal fun MutableStructure2D<Double>.svdGolubKahanHelper(
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u: MutableStructure2D<Double>, w: BufferedTensor<Double>,
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v: MutableStructure2D<Double>, iterations: Int, epsilon: Double,
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) {
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fun pythag(a: Double, b: Double): Double {
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val at: Double = abs(a)
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val bt: Double = abs(b)
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val ct: Double
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@ -323,19 +327,9 @@ private fun pythag(a: Double, b: Double): Double {
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result = bt * sqrt(1.0 + ct * ct)
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} else result = 0.0
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return result
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}
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}
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private fun SIGN(a: Double, b: Double): Double {
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if (b >= 0.0)
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return abs(a)
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else
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return -abs(a)
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}
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internal fun MutableStructure2D<Double>.svdGolubKahanHelper(
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u: MutableStructure2D<Double>, w: BufferedTensor<Double>,
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v: MutableStructure2D<Double>, iterations: Int, epsilon: Double,
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) {
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val shape = this.shape
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val m = shape.component1()
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val n = shape.component2()
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@ -553,7 +547,7 @@ internal fun MutableStructure2D<Double>.svdGolubKahanHelper(
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h = rv1[k]
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f = ((y - z) * (y + z) + (g - h) * (g + h)) / (2.0 * h * y)
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g = pythag(f, 1.0)
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f = ((x - z) * (x + z) + h * ((y / (f + SIGN(g, f))) - h)) / x
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f = ((x - z) * (x + z) + h * ((y / (f + if (f >= 0.0) abs(g) else -abs(g) )) - h)) / x
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c = 1.0
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s = 1.0
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@ -563,7 +557,7 @@ internal fun MutableStructure2D<Double>.svdGolubKahanHelper(
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g = rv1[i]
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y = wBuffer[wStart + i]
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h = s * g
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g = c * g
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g *= c
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z = pythag(f, h)
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rv1[j] = z
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c = f / z
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