Update interpolation API to agree with other conventions.

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Alexander Nozik 2022-03-07 10:39:59 +03:00
parent c80f70fe0f
commit 4575ab2b79
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10 changed files with 87 additions and 18 deletions

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@ -15,8 +15,10 @@ import space.kscience.kmath.linear.invoke
import space.kscience.kmath.linear.linearSpace import space.kscience.kmath.linear.linearSpace
import space.kscience.kmath.multik.multikAlgebra import space.kscience.kmath.multik.multikAlgebra
import space.kscience.kmath.operations.DoubleField import space.kscience.kmath.operations.DoubleField
import space.kscience.kmath.operations.invoke
import space.kscience.kmath.structures.Buffer import space.kscience.kmath.structures.Buffer
import space.kscience.kmath.tensorflow.produceWithTF import space.kscience.kmath.tensorflow.produceWithTF
import space.kscience.kmath.tensors.core.DoubleTensorAlgebra
import space.kscience.kmath.tensors.core.tensorAlgebra import space.kscience.kmath.tensors.core.tensorAlgebra
import kotlin.random.Random import kotlin.random.Random
@ -90,4 +92,9 @@ internal class DotBenchmark {
fun doubleDot(blackhole: Blackhole) = with(DoubleField.linearSpace) { fun doubleDot(blackhole: Blackhole) = with(DoubleField.linearSpace) {
blackhole.consume(matrix1 dot matrix2) blackhole.consume(matrix1 dot matrix2)
} }
@Benchmark
fun doubleTensorDot(blackhole: Blackhole) = DoubleTensorAlgebra.invoke {
blackhole.consume(matrix1 dot matrix2)
}
} }

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@ -5,8 +5,8 @@
package space.kscience.kmath.functions package space.kscience.kmath.functions
import space.kscience.kmath.interpolation.SplineInterpolator
import space.kscience.kmath.interpolation.interpolatePolynomials import space.kscience.kmath.interpolation.interpolatePolynomials
import space.kscience.kmath.interpolation.splineInterpolator
import space.kscience.kmath.operations.DoubleField import space.kscience.kmath.operations.DoubleField
import space.kscience.kmath.real.map import space.kscience.kmath.real.map
import space.kscience.kmath.real.step import space.kscience.kmath.real.step
@ -28,7 +28,7 @@ fun main() {
val xs = 0.0..100.0 step 0.5 val xs = 0.0..100.0 step 0.5
val ys = xs.map(function) val ys = xs.map(function)
val polynomial: PiecewisePolynomial<Double> = SplineInterpolator.double.interpolatePolynomials(xs, ys) val polynomial: PiecewisePolynomial<Double> = DoubleField.splineInterpolator.interpolatePolynomials(xs, ys)
val polyFunction = polynomial.asFunction(DoubleField, 0.0) val polyFunction = polynomial.asFunction(DoubleField, 0.0)

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@ -28,6 +28,8 @@ public fun <T : Comparable<T>> PiecewisePolynomial<T>.integrate(algebra: Field<T
/** /**
* Compute definite integral of given [PiecewisePolynomial] piece by piece in a given [range] * Compute definite integral of given [PiecewisePolynomial] piece by piece in a given [range]
* Requires [UnivariateIntegrationNodes] or [IntegrationRange] and [IntegrandMaxCalls] * Requires [UnivariateIntegrationNodes] or [IntegrationRange] and [IntegrandMaxCalls]
*
* TODO use context receiver for algebra
*/ */
@UnstableKMathAPI @UnstableKMathAPI
public fun <T : Comparable<T>> PiecewisePolynomial<T>.integrate( public fun <T : Comparable<T>> PiecewisePolynomial<T>.integrate(
@ -98,6 +100,7 @@ public object DoubleSplineIntegrator : UnivariateIntegrator<Double> {
} }
} }
@Suppress("unused")
@UnstableKMathAPI @UnstableKMathAPI
public inline val DoubleField.splineIntegrator: UnivariateIntegrator<Double> public inline val DoubleField.splineIntegrator: UnivariateIntegrator<Double>
get() = DoubleSplineIntegrator get() = DoubleSplineIntegrator

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@ -9,6 +9,7 @@ package space.kscience.kmath.interpolation
import space.kscience.kmath.data.XYColumnarData import space.kscience.kmath.data.XYColumnarData
import space.kscience.kmath.functions.PiecewisePolynomial import space.kscience.kmath.functions.PiecewisePolynomial
import space.kscience.kmath.functions.asFunction
import space.kscience.kmath.functions.value import space.kscience.kmath.functions.value
import space.kscience.kmath.misc.UnstableKMathAPI import space.kscience.kmath.misc.UnstableKMathAPI
import space.kscience.kmath.operations.Ring import space.kscience.kmath.operations.Ring
@ -59,3 +60,33 @@ public fun <T : Comparable<T>> PolynomialInterpolator<T>.interpolatePolynomials(
val pointSet = XYColumnarData.of(data.map { it.first }.asBuffer(), data.map { it.second }.asBuffer()) val pointSet = XYColumnarData.of(data.map { it.first }.asBuffer(), data.map { it.second }.asBuffer())
return interpolatePolynomials(pointSet) return interpolatePolynomials(pointSet)
} }
public fun <T : Comparable<T>> PolynomialInterpolator<T>.interpolate(
x: Buffer<T>,
y: Buffer<T>,
): (T) -> T? = interpolatePolynomials(x, y).asFunction(algebra)
public fun <T : Comparable<T>> PolynomialInterpolator<T>.interpolate(
data: Map<T, T>,
): (T) -> T? = interpolatePolynomials(data).asFunction(algebra)
public fun <T : Comparable<T>> PolynomialInterpolator<T>.interpolate(
data: List<Pair<T, T>>,
): (T) -> T? = interpolatePolynomials(data).asFunction(algebra)
public fun <T : Comparable<T>> PolynomialInterpolator<T>.interpolate(
x: Buffer<T>,
y: Buffer<T>,
defaultValue: T,
): (T) -> T = interpolatePolynomials(x, y).asFunction(algebra, defaultValue)
public fun <T : Comparable<T>> PolynomialInterpolator<T>.interpolate(
data: Map<T, T>,
defaultValue: T,
): (T) -> T = interpolatePolynomials(data).asFunction(algebra, defaultValue)
public fun <T : Comparable<T>> PolynomialInterpolator<T>.interpolate(
data: List<Pair<T, T>>,
defaultValue: T,
): (T) -> T = interpolatePolynomials(data).asFunction(algebra, defaultValue)

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@ -22,6 +22,7 @@ internal fun <T : Comparable<T>> insureSorted(points: XYColumnarData<*, T, *>) {
* Reference JVM implementation: https://github.com/apache/commons-math/blob/master/src/main/java/org/apache/commons/math4/analysis/interpolation/LinearInterpolator.java * Reference JVM implementation: https://github.com/apache/commons-math/blob/master/src/main/java/org/apache/commons/math4/analysis/interpolation/LinearInterpolator.java
*/ */
public class LinearInterpolator<T : Comparable<T>>(override val algebra: Field<T>) : PolynomialInterpolator<T> { public class LinearInterpolator<T : Comparable<T>>(override val algebra: Field<T>) : PolynomialInterpolator<T> {
@OptIn(UnstableKMathAPI::class) @OptIn(UnstableKMathAPI::class)
override fun interpolatePolynomials(points: XYColumnarData<T, T, T>): PiecewisePolynomial<T> = algebra { override fun interpolatePolynomials(points: XYColumnarData<T, T, T>): PiecewisePolynomial<T> = algebra {
require(points.size > 0) { "Point array should not be empty" } require(points.size > 0) { "Point array should not be empty" }
@ -37,3 +38,6 @@ public class LinearInterpolator<T : Comparable<T>>(override val algebra: Field<T
} }
} }
} }
public val <T : Comparable<T>> Field<T>.linearInterpolator: LinearInterpolator<T>
get() = LinearInterpolator(this)

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@ -63,8 +63,8 @@ public class SplineInterpolator<T : Comparable<T>>(
//Shift coefficients to represent absolute polynomial instead of one with an offset //Shift coefficients to represent absolute polynomial instead of one with an offset
val polynomial = Polynomial( val polynomial = Polynomial(
a - b * x0 + c * x02 - d * x03, a - b * x0 + c * x02 - d * x03,
b - 2*c*x0 + 3*d*x02, b - 2 * c * x0 + 3 * d * x02,
c - 3*d*x0, c - 3 * d * x0,
d d
) )
cOld = c cOld = c
@ -72,8 +72,12 @@ public class SplineInterpolator<T : Comparable<T>>(
} }
} }
} }
public companion object {
public val double: SplineInterpolator<Double> = SplineInterpolator(DoubleField, ::DoubleBuffer)
}
} }
public fun <T : Comparable<T>> Field<T>.splineInterpolator(
bufferFactory: MutableBufferFactory<T>,
): SplineInterpolator<T> = SplineInterpolator(this, bufferFactory)
public val DoubleField.splineInterpolator: SplineInterpolator<Double>
get() = SplineInterpolator(this, ::DoubleBuffer)

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@ -5,8 +5,6 @@
package space.kscience.kmath.interpolation package space.kscience.kmath.interpolation
import space.kscience.kmath.functions.PiecewisePolynomial
import space.kscience.kmath.functions.asFunction
import space.kscience.kmath.operations.DoubleField import space.kscience.kmath.operations.DoubleField
import kotlin.test.Test import kotlin.test.Test
import kotlin.test.assertEquals import kotlin.test.assertEquals
@ -21,8 +19,8 @@ internal class LinearInterpolatorTest {
3.0 to 4.0 3.0 to 4.0
) )
val polynomial: PiecewisePolynomial<Double> = LinearInterpolator(DoubleField).interpolatePolynomials(data) //val polynomial: PiecewisePolynomial<Double> = DoubleField.linearInterpolator.interpolatePolynomials(data)
val function = polynomial.asFunction(DoubleField) val function = DoubleField.linearInterpolator.interpolate(data)
assertEquals(null, function(-1.0)) assertEquals(null, function(-1.0))
assertEquals(0.5, function(0.5)) assertEquals(0.5, function(0.5))
assertEquals(2.0, function(1.5)) assertEquals(2.0, function(1.5))

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@ -5,8 +5,6 @@
package space.kscience.kmath.interpolation package space.kscience.kmath.interpolation
import space.kscience.kmath.functions.PiecewisePolynomial
import space.kscience.kmath.functions.asFunction
import space.kscience.kmath.operations.DoubleField import space.kscience.kmath.operations.DoubleField
import kotlin.math.PI import kotlin.math.PI
import kotlin.math.sin import kotlin.math.sin
@ -21,9 +19,10 @@ internal class SplineInterpolatorTest {
x to sin(x) x to sin(x)
} }
val polynomial: PiecewisePolynomial<Double> = SplineInterpolator.double.interpolatePolynomials(data) //val polynomial: PiecewisePolynomial<Double> = DoubleField.splineInterpolator.interpolatePolynomials(data)
val function = DoubleField.splineInterpolator.interpolate(data, Double.NaN)
val function = polynomial.asFunction(DoubleField, Double.NaN)
assertEquals(Double.NaN, function(-1.0)) assertEquals(Double.NaN, function(-1.0))
assertEquals(sin(0.5), function(0.5), 0.1) assertEquals(sin(0.5), function(0.5), 0.1)
assertEquals(sin(1.5), function(1.5), 0.1) assertEquals(sin(1.5), function(1.5), 0.1)

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@ -6,13 +6,38 @@
package space.kscience.kmath.multik package space.kscience.kmath.multik
import org.junit.jupiter.api.Test import org.junit.jupiter.api.Test
import space.kscience.kmath.nd.StructureND
import space.kscience.kmath.nd.one import space.kscience.kmath.nd.one
import space.kscience.kmath.operations.DoubleField import space.kscience.kmath.operations.DoubleField
import space.kscience.kmath.operations.invoke import space.kscience.kmath.operations.invoke
import space.kscience.kmath.tensors.core.DoubleTensorAlgebra
import space.kscience.kmath.tensors.core.tensorAlgebra
import kotlin.test.assertTrue
internal class MultikNDTest { internal class MultikNDTest {
@Test @Test
fun basicAlgebra(): Unit = DoubleField.multikAlgebra{ fun basicAlgebra(): Unit = DoubleField.multikAlgebra{
one(2,2) + 1.0 one(2,2) + 1.0
} }
@Test
fun dotResult(){
val dim = 100
val tensor1 = DoubleTensorAlgebra.randomNormal(shape = intArrayOf(dim, dim), 12224)
val tensor2 = DoubleTensorAlgebra.randomNormal(shape = intArrayOf(dim, dim), 12225)
val multikResult = with(DoubleField.multikAlgebra){
tensor1 dot tensor2
}
val defaultResult = with(DoubleField.tensorAlgebra){
tensor1 dot tensor2
}
assertTrue {
StructureND.contentEquals(multikResult, defaultResult)
}
}
} }

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@ -6,7 +6,6 @@ import space.kscience.kmath.nd.structureND
import space.kscience.kmath.operations.DoubleField import space.kscience.kmath.operations.DoubleField
import space.kscience.kmath.tensors.core.DoubleTensorAlgebra import space.kscience.kmath.tensors.core.DoubleTensorAlgebra
import space.kscience.kmath.tensors.core.DoubleTensorAlgebra.Companion.sum import space.kscience.kmath.tensors.core.DoubleTensorAlgebra.Companion.sum
import kotlin.random.Random
import kotlin.test.assertEquals import kotlin.test.assertEquals
class DoubleTensorFlowOps { class DoubleTensorFlowOps {
@ -23,7 +22,6 @@ class DoubleTensorFlowOps {
@Test @Test
fun dot(){ fun dot(){
val random = Random(12224)
val dim = 1000 val dim = 1000
val tensor1 = DoubleTensorAlgebra.randomNormal(shape = intArrayOf(dim, dim), 12224) val tensor1 = DoubleTensorAlgebra.randomNormal(shape = intArrayOf(dim, dim), 12224)