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# Conflicts:
#	CHANGELOG.md
#	kmath-core/api/kmath-core.api
#	kmath-core/src/commonMain/kotlin/space/kscience/kmath/domains/HyperSquareDomain.kt
#	kmath-histograms/src/commonMain/kotlin/space/kscience/kmath/histogram/RealHistogram.kt
#	kmath-histograms/src/commonTest/kotlin/scietifik/kmath/histogram/MultivariateHistogramTest.kt
#	kmath-histograms/src/jsMain/kotlin/space/kscience/kmath/histogram/Counters.kt
#	kmath-histograms/src/jvmMain/kotlin/space/kscience/kmath/histogram/Counters.kt
#	kmath-histograms/src/jvmMain/kotlin/space/kscience/kmath/histogram/UnivariateHistogram.kt
#	kmath-histograms/src/jvmMain/kotlin/space/kscience/kmath/histogram/UnivariateHistogramSpace.kt
This commit is contained in:
Alexander Nozik 2021-02-19 09:46:25 +03:00
commit c6ea423bd6
18 changed files with 1899 additions and 1793 deletions
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1
CHANGELOG.md
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@ -42,6 +42,7 @@
- `Complex` and related features moved to a separate module `kmath-complex` - `Complex` and related features moved to a separate module `kmath-complex`
- Refactor AlgebraElement - Refactor AlgebraElement
- `symbol` method in `Algebra` renamed to `bindSymbol` to avoid ambiguity - `symbol` method in `Algebra` renamed to `bindSymbol` to avoid ambiguity
- Add `out` projection to `Buffer` generic
### Deprecated ### Deprecated

13
kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/MstExpression.kt
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@ -21,8 +21,17 @@ public class MstExpression<T, out A : Algebra<T>>(public val algebra: A, public
null null
} ?: arguments.getValue(StringSymbol(value)) } ?: arguments.getValue(StringSymbol(value))
override fun unaryOperationFunction(operation: String): (arg: T) -> T = algebra.unaryOperationFunction(operation) override fun unaryOperation(operation: String, arg: T): T =
override fun binaryOperationFunction(operation: String): (left: T, right: T) -> T = algebra.binaryOperationFunction(operation) algebra.unaryOperation(operation, arg)
override fun binaryOperation(operation: String, left: T, right: T): T =
algebra.binaryOperation(operation, left, right)
override fun unaryOperationFunction(operation: String): (arg: T) -> T =
algebra.unaryOperationFunction(operation)
override fun binaryOperationFunction(operation: String): (left: T, right: T) -> T =
algebra.binaryOperationFunction(operation)
@Suppress("UNCHECKED_CAST") @Suppress("UNCHECKED_CAST")
override fun number(value: Number): T = if (algebra is NumericAlgebra<*>) override fun number(value: Number): T = if (algebra is NumericAlgebra<*>)

2747
kmath-core/api/kmath-core.api
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19
kmath-core/src/commonMain/kotlin/space/kscience/kmath/domains/HyperSquareDomain.kt
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@ -13,11 +13,12 @@
* See the License for the specific language governing permissions and * See the License for the specific language governing permissions and
* limitations under the License. * limitations under the License.
*/ */
package space.kscience.kmath.domains package kscience.kmath.domains
import space.kscience.kmath.linear.Point import kscience.kmath.linear.Point
import space.kscience.kmath.structures.RealBuffer import kscience.kmath.structures.Buffer
import space.kscience.kmath.structures.indices import kscience.kmath.structures.RealBuffer
import kscience.kmath.structures.indices
/** /**
* *
@ -25,20 +26,20 @@ import space.kscience.kmath.structures.indices
* *
* @author Alexander Nozik * @author Alexander Nozik
*/ */
public class HyperSquareDomain(private val lower: RealBuffer, private val upper: RealBuffer) : RealDomain { public class HyperSquareDomain(private val lower: Buffer<Double>, private val upper: Buffer<Double>) : RealDomain {
public override val dimension: Int get() = lower.size public override val dimension: Int get() = lower.size
public override operator fun contains(point: Point<Double>): Boolean = point.indices.all { i -> public override operator fun contains(point: Point<Double>): Boolean = point.indices.all { i ->
point[i] in lower[i]..upper[i] point[i] in lower[i]..upper[i]
} }
public override fun getLowerBound(num: Int, point: Point<Double>): Double? = lower[num] public override fun getLowerBound(num: Int, point: Point<Double>): Double = lower[num]
public override fun getLowerBound(num: Int): Double? = lower[num] public override fun getLowerBound(num: Int): Double = lower[num]
public override fun getUpperBound(num: Int, point: Point<Double>): Double? = upper[num] public override fun getUpperBound(num: Int, point: Point<Double>): Double = upper[num]
public override fun getUpperBound(num: Int): Double? = upper[num] public override fun getUpperBound(num: Int): Double = upper[num]
public override fun nearestInDomain(point: Point<Double>): Point<Double> { public override fun nearestInDomain(point: Point<Double>): Point<Double> {
val res = DoubleArray(point.size) { i -> val res = DoubleArray(point.size) { i ->

15
kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/NDStructure.kt
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@ -78,8 +78,7 @@ public interface NDStructure<T> {
strides: Strides, strides: Strides,
bufferFactory: BufferFactory<T> = Buffer.Companion::boxing, bufferFactory: BufferFactory<T> = Buffer.Companion::boxing,
initializer: (IntArray) -> T, initializer: (IntArray) -> T,
): NDBuffer<T> = ): NDBuffer<T> = NDBuffer(strides, bufferFactory(strides.linearSize) { i -> initializer(strides.index(i)) })
NDBuffer(strides, bufferFactory(strides.linearSize) { i -> initializer(strides.index(i)) })
/** /**
* Inline create NDStructure with non-boxing buffer implementation if it is possible * Inline create NDStructure with non-boxing buffer implementation if it is possible
@ -87,15 +86,13 @@ public interface NDStructure<T> {
public inline fun <reified T : Any> auto( public inline fun <reified T : Any> auto(
strides: Strides, strides: Strides,
crossinline initializer: (IntArray) -> T, crossinline initializer: (IntArray) -> T,
): NDBuffer<T> = ): NDBuffer<T> = NDBuffer(strides, Buffer.auto(strides.linearSize) { i -> initializer(strides.index(i)) })
NDBuffer(strides, Buffer.auto(strides.linearSize) { i -> initializer(strides.index(i)) })
public inline fun <T : Any> auto( public inline fun <T : Any> auto(
type: KClass<T>, type: KClass<T>,
strides: Strides, strides: Strides,
crossinline initializer: (IntArray) -> T, crossinline initializer: (IntArray) -> T,
): NDBuffer<T> = ): NDBuffer<T> = NDBuffer(strides, Buffer.auto(type, strides.linearSize) { i -> initializer(strides.index(i)) })
NDBuffer(strides, Buffer.auto(type, strides.linearSize) { i -> initializer(strides.index(i)) })
public fun <T> build( public fun <T> build(
shape: IntArray, shape: IntArray,
@ -106,8 +103,7 @@ public interface NDStructure<T> {
public inline fun <reified T : Any> auto( public inline fun <reified T : Any> auto(
shape: IntArray, shape: IntArray,
crossinline initializer: (IntArray) -> T, crossinline initializer: (IntArray) -> T,
): NDBuffer<T> = ): NDBuffer<T> = auto(DefaultStrides(shape), initializer)
auto(DefaultStrides(shape), initializer)
@JvmName("autoVarArg") @JvmName("autoVarArg")
public inline fun <reified T : Any> auto( public inline fun <reified T : Any> auto(
@ -120,8 +116,7 @@ public interface NDStructure<T> {
type: KClass<T>, type: KClass<T>,
vararg shape: Int, vararg shape: Int,
crossinline initializer: (IntArray) -> T, crossinline initializer: (IntArray) -> T,
): NDBuffer<T> = ): NDBuffer<T> = auto(type, DefaultStrides(shape), initializer)
auto(type, DefaultStrides(shape), initializer)
} }
} }

2
kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/Buffer.kt
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@ -21,7 +21,7 @@ public typealias MutableBufferFactory<T> = (Int, (Int) -> T) -> MutableBuffer<T>
* *
* @param T the type of elements contained in the buffer. * @param T the type of elements contained in the buffer.
*/ */
public interface Buffer<T> { public interface Buffer<out T> {
/** /**
* The size of this buffer. * The size of this buffer.
*/ */

12
kmath-histograms/build.gradle.kts
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@ -1,4 +1,10 @@
plugins { id("ru.mipt.npm.mpp") } plugins {
id("ru.mipt.npm.mpp")
}
kscience {
useAtomic()
}
kotlin.sourceSets { kotlin.sourceSets {
commonMain { commonMain {
@ -6,8 +12,8 @@ kotlin.sourceSets {
api(project(":kmath-core")) api(project(":kmath-core"))
} }
} }
commonTest{ commonTest {
dependencies{ dependencies {
implementation(project(":kmath-for-real")) implementation(project(":kmath-for-real"))
} }
} }

76
kmath-histograms/src/commonMain/kotlin/kscience/kmath/histogram/IndexedHistogramSpace.kt Normal file
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@ -0,0 +1,76 @@
package kscience.kmath.histogram
import kscience.kmath.domains.Domain
import kscience.kmath.linear.Point
import kscience.kmath.misc.UnstableKMathAPI
import kscience.kmath.nd.NDSpace
import kscience.kmath.nd.NDStructure
import kscience.kmath.nd.Strides
import kscience.kmath.operations.Space
import kscience.kmath.operations.SpaceElement
import kscience.kmath.operations.invoke
/**
* A simple histogram bin based on domain
*/
public data class DomainBin<T : Comparable<T>>(
public val domain: Domain<T>,
public override val value: Number,
) : Bin<T>, Domain<T> by domain
@OptIn(UnstableKMathAPI::class)
public class IndexedHistogram<T : Comparable<T>, V : Any>(
override val context: IndexedHistogramSpace<T, V>,
public val values: NDStructure<V>,
) : Histogram<T, Bin<T>>, SpaceElement<IndexedHistogram<T, V>, IndexedHistogramSpace<T, V>> {
override fun get(point: Point<T>): Bin<T>? {
val index = context.getIndex(point) ?: return null
return context.produceBin(index, values[index])
}
override val dimension: Int get() = context.strides.shape.size
override val bins: Iterable<Bin<T>>
get() = context.strides.indices().map {
context.produceBin(it, values[it])
}.asIterable()
}
/**
* A space for producing histograms with values in a NDStructure
*/
public interface IndexedHistogramSpace<T : Comparable<T>, V : Any> : Space<IndexedHistogram<T, V>> {
//public val valueSpace: Space<V>
public val strides: Strides
public val histogramValueSpace: NDSpace<V, *> //= NDAlgebra.space(valueSpace, Buffer.Companion::boxing, *shape),
/**
* Resolve index of the bin including given [point]
*/
public fun getIndex(point: Point<T>): IntArray?
/**
* Get a bin domain represented by given index
*/
public fun getDomain(index: IntArray): Domain<T>?
public fun produceBin(index: IntArray, value: V): Bin<T>
public fun produce(builder: HistogramBuilder<T>.() -> Unit): IndexedHistogram<T, V>
override fun add(a: IndexedHistogram<T, V>, b: IndexedHistogram<T, V>): IndexedHistogram<T, V> {
require(a.context == this) { "Can't operate on a histogram produced by external space" }
require(b.context == this) { "Can't operate on a histogram produced by external space" }
return IndexedHistogram(this, histogramValueSpace.invoke { a.values + b.values })
}
override fun multiply(a: IndexedHistogram<T, V>, k: Number): IndexedHistogram<T, V> {
require(a.context == this) { "Can't operate on a histogram produced by external space" }
return IndexedHistogram(this, histogramValueSpace.invoke { a.values * k })
}
override val zero: IndexedHistogram<T, V> get() = produce { }
}

121
kmath-histograms/src/commonMain/kotlin/kscience/kmath/histogram/RealHistogramSpace.kt Normal file
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@ -0,0 +1,121 @@
package kscience.kmath.histogram
import kscience.kmath.domains.Domain
import kscience.kmath.domains.HyperSquareDomain
import kscience.kmath.nd.*
import kscience.kmath.structures.*
import kotlin.math.floor
public class RealHistogramSpace(
private val lower: Buffer<Double>,
private val upper: Buffer<Double>,
private val binNums: IntArray = IntArray(lower.size) { 20 },
) : IndexedHistogramSpace<Double, Double> {
init {
// argument checks
require(lower.size == upper.size) { "Dimension mismatch in histogram lower and upper limits." }
require(lower.size == binNums.size) { "Dimension mismatch in bin count." }
require(!lower.indices.any { upper[it] - lower[it] < 0 }) { "Range for one of axis is not strictly positive" }
}
public val dimension: Int get() = lower.size
private val shape = IntArray(binNums.size) { binNums[it] + 2 }
override val histogramValueSpace: RealNDField = NDAlgebra.real(*shape)
override val strides: Strides get() = histogramValueSpace.strides
private val binSize = RealBuffer(dimension) { (upper[it] - lower[it]) / binNums[it] }
/**
* Get internal [NDStructure] bin index for given axis
*/
private fun getIndex(axis: Int, value: Double): Int = when {
value >= upper[axis] -> binNums[axis] + 1 // overflow
value < lower[axis] -> 0 // underflow
else -> floor((value - lower[axis]) / binSize[axis]).toInt()
}
override fun getIndex(point: Buffer<Double>): IntArray = IntArray(dimension) {
getIndex(it, point[it])
}
override fun getDomain(index: IntArray): Domain<Double> {
val lowerBoundary = index.mapIndexed { axis, i ->
when (i) {
0 -> Double.NEGATIVE_INFINITY
strides.shape[axis] - 1 -> upper[axis]
else -> lower[axis] + (i.toDouble()) * binSize[axis]
}
}.asBuffer()
val upperBoundary = index.mapIndexed { axis, i ->
when (i) {
0 -> lower[axis]
strides.shape[axis] - 1 -> Double.POSITIVE_INFINITY
else -> lower[axis] + (i.toDouble() + 1) * binSize[axis]
}
}.asBuffer()
return HyperSquareDomain(lowerBoundary, upperBoundary)
}
override fun produceBin(index: IntArray, value: Double): Bin<Double> {
val domain = getDomain(index)
return DomainBin(domain, value)
}
override fun produce(builder: HistogramBuilder<Double>.() -> Unit): IndexedHistogram<Double, Double> {
val ndCounter = NDStructure.auto(strides) { Counter.real() }
val hBuilder = HistogramBuilder<Double> { point, value ->
val index = getIndex(point)
ndCounter[index].add(1.0)
}
hBuilder.apply(builder)
val values: NDBuffer<Double> = ndCounter.mapToBuffer { it.value }
return IndexedHistogram(this, values)
}
public companion object {
/**
* Use it like
* ```
*FastHistogram.fromRanges(
* (-1.0..1.0),
* (-1.0..1.0)
*)
*```
*/
public fun fromRanges(vararg ranges: ClosedFloatingPointRange<Double>): RealHistogramSpace = RealHistogramSpace(
ranges.map(ClosedFloatingPointRange<Double>::start).asBuffer(),
ranges.map(ClosedFloatingPointRange<Double>::endInclusive).asBuffer()
)
/**
* Use it like
* ```
*FastHistogram.fromRanges(
* (-1.0..1.0) to 50,
* (-1.0..1.0) to 32
*)
*```
*/
public fun fromRanges(vararg ranges: Pair<ClosedFloatingPointRange<Double>, Int>): RealHistogramSpace =
RealHistogramSpace(
ListBuffer(
ranges
.map(Pair<ClosedFloatingPointRange<Double>, Int>::first)
.map(ClosedFloatingPointRange<Double>::start)
),
ListBuffer(
ranges
.map(Pair<ClosedFloatingPointRange<Double>, Int>::first)
.map(ClosedFloatingPointRange<Double>::endInclusive)
),
ranges.map(Pair<ClosedFloatingPointRange<Double>, Int>::second).toIntArray()
)
}
}

55
kmath-histograms/src/commonMain/kotlin/space/kscience/kmath/histogram/Counters.kt
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@ -1,20 +1,49 @@
package space.kscience.kmath.histogram package space.kscience.kmath.histogram
/* import kotlinx.atomicfu.atomic
import kotlinx.atomicfu.getAndUpdate
import kscience.kmath.operations.RealField
import kscience.kmath.operations.Space
/**
* Common representation for atomic counters * Common representation for atomic counters
* TODO replace with atomics
*/ */
public interface Counter<T : Any> {
public expect class LongCounter() { public fun add(delta: T)
public fun decrement() public val value: T
public fun increment() public companion object{
public fun reset() public fun real(): ObjectCounter<Double> = ObjectCounter(RealField)
public fun sum(): Long }
public fun add(l: Long)
} }
public expect class DoubleCounter() { public class IntCounter : Counter<Int> {
public fun reset() private val innerValue = atomic(0)
public fun sum(): Double
public fun add(d: Double) override fun add(delta: Int) {
innerValue += delta
}
override val value: Int get() = innerValue.value
} }
public class LongCounter : Counter<Long> {
private val innerValue = atomic(0L)
override fun add(delta: Long) {
innerValue += delta
}
override val value: Long get() = innerValue.value
}
public class ObjectCounter<T : Any>(public val space: Space<T>) : Counter<T> {
private val innerValue = atomic(space.zero)
override fun add(delta: T) {
innerValue.getAndUpdate { space.run { it + delta } }
}
override val value: T get() = innerValue.value
}

25
kmath-histograms/src/commonMain/kotlin/space/kscience/kmath/histogram/Histogram.kt
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@ -6,18 +6,16 @@ import space.kscience.kmath.structures.ArrayBuffer
import space.kscience.kmath.structures.RealBuffer import space.kscience.kmath.structures.RealBuffer
/** /**
* The bin in the histogram. The histogram is by definition always done in the real space * The binned data element. Could be a histogram bin with a number of counts or an artificial construct
*/ */
public interface Bin<T : Any> : Domain<T> { public interface Bin<T : Any> : Domain<T> {
/** /**
* The value of this bin. * The value of this bin.
*/ */
public val value: Number public val value: Number
public val center: Point<T>
} }
public interface Histogram<T : Any, out B : Bin<T>> : Iterable<B> { public interface Histogram<T : Any, out B : Bin<T>> {
/** /**
* Find existing bin, corresponding to given coordinates * Find existing bin, corresponding to given coordinates
*/ */
@ -27,28 +25,31 @@ public interface Histogram<T : Any, out B : Bin<T>> : Iterable<B> {
* Dimension of the histogram * Dimension of the histogram
*/ */
public val dimension: Int public val dimension: Int
public val bins: Iterable<B>
} }
public interface MutableHistogram<T : Any, out B : Bin<T>> : Histogram<T, B> { public fun interface HistogramBuilder<T : Any> {
/** /**
* Increment appropriate bin * Increment appropriate bin
*/ */
public fun putWithWeight(point: Point<out T>, weight: Double) public fun putValue(point: Point<out T>, value: Number)
public fun put(point: Point<out T>): Unit = putWithWeight(point, 1.0)
} }
public fun <T : Any> MutableHistogram<T, *>.put(vararg point: T): Unit = put(ArrayBuffer(point)) public fun <T : Any, B : Bin<T>> HistogramBuilder<T>.put(point: Point<out T>): Unit = putValue(point, 1.0)
public fun MutableHistogram<Double, *>.put(vararg point: Number): Unit = public fun <T : Any> HistogramBuilder<T>.put(vararg point: T): Unit = put(ArrayBuffer(point))
public fun HistogramBuilder<Double>.put(vararg point: Number): Unit =
put(RealBuffer(point.map { it.toDouble() }.toDoubleArray())) put(RealBuffer(point.map { it.toDouble() }.toDoubleArray()))
public fun MutableHistogram<Double, *>.put(vararg point: Double): Unit = put(RealBuffer(point)) public fun HistogramBuilder<Double>.put(vararg point: Double): Unit = put(RealBuffer(point))
public fun <T : Any> MutableHistogram<T, *>.fill(sequence: Iterable<Point<T>>): Unit = sequence.forEach { put(it) } public fun <T : Any> HistogramBuilder<T>.fill(sequence: Iterable<Point<T>>): Unit = sequence.forEach { put(it) }
/** /**
* Pass a sequence builder into histogram * Pass a sequence builder into histogram
*/ */
public fun <T : Any> MutableHistogram<T, *>.fill(block: suspend SequenceScope<Point<T>>.() -> Unit): Unit = public fun <T : Any> HistogramBuilder<T>.fill(block: suspend SequenceScope<Point<T>>.() -> Unit): Unit =
fill(sequence(block).asIterable()) fill(sequence(block).asIterable())

165
kmath-histograms/src/commonMain/kotlin/space/kscience/kmath/histogram/RealHistogram.kt
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@ -1,165 +0,0 @@
package space.kscience.kmath.histogram
import space.kscience.kmath.linear.Point
import space.kscience.kmath.nd.DefaultStrides
import space.kscience.kmath.nd.NDStructure
import space.kscience.kmath.operations.SpaceOperations
import space.kscience.kmath.operations.invoke
import space.kscience.kmath.structures.*
import kotlin.math.floor
public data class MultivariateBinDefinition<T : Comparable<T>>(
public val space: SpaceOperations<Point<T>>,
public val center: Point<T>,
public val sizes: Point<T>,
) {
public fun contains(vector: Point<out T>): Boolean {
require(vector.size == center.size) { "Dimension mismatch for input vector. Expected ${center.size}, but found ${vector.size}" }
val upper = space { center + sizes / 2.0 }
val lower = space { center - sizes / 2.0 }
return vector.asSequence().mapIndexed { i, value -> value in lower[i]..upper[i] }.all { it }
}
}
public class MultivariateBin<T : Comparable<T>>(
public val definition: MultivariateBinDefinition<T>,
public val count: Long,
public override val value: Double,
) : Bin<T> {
public override val dimension: Int
get() = definition.center.size
public override val center: Point<T>
get() = definition.center
public override operator fun contains(point: Point<T>): Boolean = definition.contains(point)
}
/**
* Uniform multivariate histogram with fixed borders. Based on NDStructure implementation with complexity of m for bin search, where m is the number of dimensions.
*/
public class RealHistogram(
private val lower: Buffer<Double>,
private val upper: Buffer<Double>,
private val binNums: IntArray = IntArray(lower.size) { 20 },
) : MutableHistogram<Double, MultivariateBin<Double>> {
private val strides = DefaultStrides(IntArray(binNums.size) { binNums[it] + 2 })
private val counts: NDStructure<LongCounter> = NDStructure.auto(strides) { LongCounter() }
private val values: NDStructure<DoubleCounter> = NDStructure.auto(strides) { DoubleCounter() }
public override val dimension: Int get() = lower.size
private val binSize = RealBuffer(dimension) { (upper[it] - lower[it]) / binNums[it] }
init {
// argument checks
require(lower.size == upper.size) { "Dimension mismatch in histogram lower and upper limits." }
require(lower.size == binNums.size) { "Dimension mismatch in bin count." }
require(!(0 until dimension).any { upper[it] - lower[it] < 0 }) { "Range for one of axis is not strictly positive" }
}
/**
* Get internal [NDStructure] bin index for given axis
*/
private fun getIndex(axis: Int, value: Double): Int = when {
value >= upper[axis] -> binNums[axis] + 1 // overflow
value < lower[axis] -> 0 // underflow
else -> floor((value - lower[axis]) / binSize[axis]).toInt() + 1
}
private fun getIndex(point: Buffer<out Double>): IntArray = IntArray(dimension) { getIndex(it, point[it]) }
private fun getCount(index: IntArray): Long = counts[index].sum()
public fun getCount(point: Buffer<out Double>): Long = getCount(getIndex(point))
private fun getValue(index: IntArray): Double = values[index].sum()
public fun getValue(point: Buffer<out Double>): Double = getValue(getIndex(point))
private fun getBinDefinition(index: IntArray): MultivariateBinDefinition<Double> {
val center = index.mapIndexed { axis, i ->
when (i) {
0 -> Double.NEGATIVE_INFINITY
strides.shape[axis] - 1 -> Double.POSITIVE_INFINITY
else -> lower[axis] + (i.toDouble() - 0.5) * binSize[axis]
}
}.asBuffer()
return MultivariateBinDefinition(RealBufferFieldOperations, center, binSize)
}
public fun getBinDefinition(point: Buffer<out Double>): MultivariateBinDefinition<Double> = getBinDefinition(getIndex(point))
public override operator fun get(point: Buffer<out Double>): MultivariateBin<Double>? {
val index = getIndex(point)
return MultivariateBin(getBinDefinition(index), getCount(index),getValue(index))
}
// fun put(point: Point<out Double>){
// val index = getIndex(point)
// values[index].increment()
// }
public override fun putWithWeight(point: Buffer<out Double>, weight: Double) {
val index = getIndex(point)
counts[index].increment()
values[index].add(weight)
}
public override operator fun iterator(): Iterator<MultivariateBin<Double>> =
strides.indices().map { index->
MultivariateBin(getBinDefinition(index), counts[index].sum(), values[index].sum())
}.iterator()
/**
* NDStructure containing number of events in bins without weights
*/
public fun counts(): NDStructure<Long> = NDStructure.auto(counts.shape) { counts[it].sum() }
/**
* NDStructure containing values of bins including weights
*/
public fun values(): NDStructure<Double> = NDStructure.auto(values.shape) { values[it].sum() }
public companion object {
/**
* Use it like
* ```
*FastHistogram.fromRanges(
* (-1.0..1.0),
* (-1.0..1.0)
*)
*```
*/
public fun fromRanges(vararg ranges: ClosedFloatingPointRange<Double>): RealHistogram = RealHistogram(
ranges.map(ClosedFloatingPointRange<Double>::start).asBuffer(),
ranges.map(ClosedFloatingPointRange<Double>::endInclusive).asBuffer()
)
/**
* Use it like
* ```
*FastHistogram.fromRanges(
* (-1.0..1.0) to 50,
* (-1.0..1.0) to 32
*)
*```
*/
public fun fromRanges(vararg ranges: Pair<ClosedFloatingPointRange<Double>, Int>): RealHistogram =
RealHistogram(
ListBuffer(
ranges
.map(Pair<ClosedFloatingPointRange<Double>, Int>::first)
.map(ClosedFloatingPointRange<Double>::start)
),
ListBuffer(
ranges
.map(Pair<ClosedFloatingPointRange<Double>, Int>::first)
.map(ClosedFloatingPointRange<Double>::endInclusive)
),
ranges.map(Pair<ClosedFloatingPointRange<Double>, Int>::second).toIntArray()
)
}
}

61
kmath-histograms/src/commonTest/kotlin/scietifik/kmath/histogram/MultivariateHistogramTest.kt
View File

@ -1,22 +1,24 @@
package scietifik.kmath.histogram package scietifik.kmath.histogram
import space.kscience.kmath.histogram.RealHistogram import kscience.kmath.histogram.RealHistogramSpace
import space.kscience.kmath.histogram.fill import kscience.kmath.histogram.put
import space.kscience.kmath.histogram.put import kscience.kmath.operations.invoke
import space.kscience.kmath.real.RealVector import kscience.kmath.real.RealVector
import space.kscience.kmath.real.invoke import kscience.kmath.real.invoke
import kotlin.random.Random import kotlin.random.Random
import kotlin.test.* import kotlin.test.*
internal class MultivariateHistogramTest { internal class MultivariateHistogramTest {
@Test @Test
fun testSinglePutHistogram() { fun testSinglePutHistogram() {
val histogram = RealHistogram.fromRanges( val hSpace = RealHistogramSpace.fromRanges(
(-1.0..1.0), (-1.0..1.0),
(-1.0..1.0) (-1.0..1.0)
) )
histogram.put(0.55, 0.55) val histogram = hSpace.produce {
val bin = histogram.find { it.value.toInt() > 0 } ?: fail() put(0.55, 0.55)
}
val bin = histogram.bins.find { it.value.toInt() > 0 } ?: fail()
assertTrue { bin.contains(RealVector(0.55, 0.55)) } assertTrue { bin.contains(RealVector(0.55, 0.55)) }
assertTrue { bin.contains(RealVector(0.6, 0.5)) } assertTrue { bin.contains(RealVector(0.6, 0.5)) }
assertFalse { bin.contains(RealVector(-0.55, 0.55)) } assertFalse { bin.contains(RealVector(-0.55, 0.55)) }
@ -24,7 +26,7 @@ internal class MultivariateHistogramTest {
@Test @Test
fun testSequentialPut() { fun testSequentialPut() {
val histogram = RealHistogram.fromRanges( val hSpace = RealHistogramSpace.fromRanges(
(-1.0..1.0), (-1.0..1.0),
(-1.0..1.0), (-1.0..1.0),
(-1.0..1.0) (-1.0..1.0)
@ -34,12 +36,45 @@ internal class MultivariateHistogramTest {
fun nextDouble() = random.nextDouble(-1.0, 1.0) fun nextDouble() = random.nextDouble(-1.0, 1.0)
val n = 10000 val n = 10000
val histogram = hSpace.produce {
histogram.fill {
repeat(n) { repeat(n) {
yield(RealVector(nextDouble(), nextDouble(), nextDouble())) put(nextDouble(), nextDouble(), nextDouble())
} }
} }
assertEquals(n, histogram.sumBy { it.value.toInt() }) assertEquals(n, histogram.bins.sumBy { it.value.toInt() })
}
@Test
fun testHistogramAlgebra() {
val hSpace = RealHistogramSpace.fromRanges(
(-1.0..1.0),
(-1.0..1.0),
(-1.0..1.0)
).invoke {
val random = Random(1234)
fun nextDouble() = random.nextDouble(-1.0, 1.0)
val n = 10000
val histogram1 = produce {
repeat(n) {
put(nextDouble(), nextDouble(), nextDouble())
}
}
val histogram2 = produce {
repeat(n) {
put(nextDouble(), nextDouble(), nextDouble())
}
}
val res = histogram1 - histogram2
assertTrue {
strides.indices().all { index ->
res.values[index] <= histogram1.values[index]
}
}
assertTrue {
res.bins.count() >= histogram1.bins.count()
}
assertEquals(0.0, res.bins.sumByDouble { it.value.toDouble() })
}
} }
} }

37
kmath-histograms/src/jsMain/kotlin/space/kscience/kmath/histogram/Counters.kt
View File

@ -1,37 +0,0 @@
package space.kscience.kmath.histogram
public actual class LongCounter {
private var sum: Long = 0L
public actual fun decrement() {
sum--
}
public actual fun increment() {
sum++
}
public actual fun reset() {
sum = 0
}
public actual fun sum(): Long = sum
public actual fun add(l: Long) {
sum += l
}
}
public actual class DoubleCounter {
private var sum: Double = 0.0
public actual fun reset() {
sum = 0.0
}
public actual fun sum(): Double = sum
public actual fun add(d: Double) {
sum += d
}
}

155
kmath-histograms/src/jvmMain/kotlin/kscience/kmath/histogram/TreeHistogramSpace.kt Normal file
View File

@ -0,0 +1,155 @@
package kscience.kmath.histogram
import kscience.kmath.domains.UnivariateDomain
import kscience.kmath.misc.UnstableKMathAPI
import kscience.kmath.operations.Space
import kscience.kmath.structures.Buffer
import java.util.*
import kotlin.math.abs
import kotlin.math.sqrt
private fun <B : ClosedFloatingPointRange<Double>> TreeMap<Double, B>.getBin(value: Double): B? {
// check ceiling entry and return it if it is what needed
val ceil = ceilingEntry(value)?.value
if (ceil != null && value in ceil) return ceil
//check floor entry
val floor = floorEntry(value)?.value
if (floor != null && value in floor) return floor
//neither is valid, not found
return null
}
@UnstableKMathAPI
public class TreeHistogram(
override val context: TreeHistogramSpace,
private val binMap: TreeMap<Double, out UnivariateBin>,
) : UnivariateHistogram {
override fun get(value: Double): UnivariateBin? = binMap.getBin(value)
override val dimension: Int get() = 1
override val bins: Collection<UnivariateBin> get() = binMap.values
}
/**
* A space for univariate histograms with variable bin borders based on a tree map
*/
@UnstableKMathAPI
public class TreeHistogramSpace(
public val binFactory: (Double) -> UnivariateDomain,
) : Space<UnivariateHistogram> {
private class BinCounter(val domain: UnivariateDomain, val counter: Counter<Double> = Counter.real()) :
ClosedFloatingPointRange<Double> by domain.range
public fun produce(builder: UnivariateHistogramBuilder.() -> Unit): UnivariateHistogram {
val bins: TreeMap<Double, BinCounter> = TreeMap()
val hBuilder = object : UnivariateHistogramBuilder {
fun get(value: Double): BinCounter? = bins.getBin(value)
fun createBin(value: Double): BinCounter {
val binDefinition = binFactory(value)
val newBin = BinCounter(binDefinition)
synchronized(this) { bins[binDefinition.center] = newBin }
return newBin
}
/**
* Thread safe put operation
*/
override fun putValue(at: Double, value: Double) {
(get(at) ?: createBin(at)).apply {
counter.add(value)
}
}
override fun putValue(point: Buffer<Double>, value: Number) {
put(point[0], value.toDouble())
}
}
hBuilder.apply(builder)
val resBins = TreeMap<Double, UnivariateBin>()
bins.forEach { key, binCounter ->
val count = binCounter.counter.value
resBins[key] = UnivariateBin(binCounter.domain, count, sqrt(count))
}
return TreeHistogram(this, resBins)
}
override fun add(
a: UnivariateHistogram,
b: UnivariateHistogram,
): UnivariateHistogram {
require(a.context == this) { "Histogram $a does not belong to this context" }
require(b.context == this) { "Histogram $b does not belong to this context" }
val bins = TreeMap<Double, UnivariateBin>().apply {
(a.bins.map { it.domain } union b.bins.map { it.domain }).forEach { def ->
put(def.center,
UnivariateBin(
def,
value = (a[def.center]?.value ?: 0.0) + (b[def.center]?.value ?: 0.0),
standardDeviation = (a[def.center]?.standardDeviation
?: 0.0) + (b[def.center]?.standardDeviation ?: 0.0)
)
)
}
}
return TreeHistogram(this, bins)
}
override fun multiply(a: UnivariateHistogram, k: Number): UnivariateHistogram {
val bins = TreeMap<Double, UnivariateBin>().apply {
a.bins.forEach { bin ->
put(bin.domain.center,
UnivariateBin(
bin.domain,
value = bin.value * k.toDouble(),
standardDeviation = abs(bin.standardDeviation * k.toDouble())
)
)
}
}
return TreeHistogram(this, bins)
}
override val zero: UnivariateHistogram = produce { }
public companion object {
/**
* Build and fill a [UnivariateHistogram]. Returns a read-only histogram.
*/
public fun uniform(
binSize: Double,
start: Double = 0.0,
): TreeHistogramSpace = TreeHistogramSpace { value ->
val center = start + binSize * Math.floor((value - start) / binSize + 0.5)
UnivariateDomain((center - binSize / 2)..(center + binSize / 2))
}
/**
* Create a histogram with custom cell borders
*/
public fun custom(borders: DoubleArray): TreeHistogramSpace {
val sorted = borders.sortedArray()
return TreeHistogramSpace { value ->
when {
value < sorted.first() -> UnivariateDomain(
Double.NEGATIVE_INFINITY..sorted.first()
)
value > sorted.last() -> UnivariateDomain(
sorted.last()..Double.POSITIVE_INFINITY
)
else -> {
val index = sorted.indices.first { value > sorted[it] }
val left = sorted[index]
val right = sorted[index + 1]
UnivariateDomain(left..right)
}
}
}
}
}
}

7
kmath-histograms/src/jvmMain/kotlin/space/kscience/kmath/histogram/Counters.kt
View File

@ -1,7 +0,0 @@
package space.kscience.kmath.histogram
import java.util.concurrent.atomic.DoubleAdder
import java.util.concurrent.atomic.LongAdder
public actual typealias LongCounter = LongAdder
public actual typealias DoubleCounter = DoubleAdder

156
kmath-histograms/src/jvmMain/kotlin/space/kscience/kmath/histogram/UnivariateHistogram.kt
View File

@ -1,76 +1,38 @@
package space.kscience.kmath.histogram package kscience.kmath.histogram
import space.kscience.kmath.linear.Point import kscience.kmath.domains.UnivariateDomain
import space.kscience.kmath.misc.UnstableKMathAPI import kscience.kmath.misc.UnstableKMathAPI
import space.kscience.kmath.operations.SpaceElement import kscience.kmath.operations.Space
import space.kscience.kmath.structures.Buffer import kscience.kmath.operations.SpaceElement
import space.kscience.kmath.structures.asBuffer import kscience.kmath.structures.Buffer
import space.kscience.kmath.structures.asSequence import kscience.kmath.structures.asSequence
import java.util.*
import kotlin.math.floor
//TODO move to common
public class UnivariateBin( public val UnivariateDomain.center: Double get() = (range.endInclusive - range.start) / 2
public val position: Double,
public val size: Double,
) : Bin<Double> {
//internal mutation operations
internal val counter: LongCounter = LongCounter()
internal val weightCounter: DoubleCounter = DoubleCounter()
/**
* The precise number of events ignoring weighting
*/
public val count: Long get() = counter.sum()
/**
* The value of histogram including weighting
*/
public override val value: Double get() = weightCounter.sum()
public override val center: Point<Double> get() = doubleArrayOf(position).asBuffer()
public override val dimension: Int get() = 1
public operator fun contains(value: Double): Boolean = value in (position - size / 2)..(position + size / 2)
public override fun contains(point: Buffer<Double>): Boolean = contains(point[0])
}
/** /**
* Univariate histogram with log(n) bin search speed * A univariate bin based an a range
* @param value The value of histogram including weighting
* @param standardDeviation Standard deviation of the bin value. Zero or negative if not applicable
*/ */
@OptIn(UnstableKMathAPI::class) public class UnivariateBin(
public abstract class UnivariateHistogram protected constructor( public val domain: UnivariateDomain,
protected val bins: TreeMap<Double, UnivariateBin> = TreeMap(), override val value: Double,
) : Histogram<Double, UnivariateBin>, SpaceElement<UnivariateHistogram, UnivariateHistogramSpace> { public val standardDeviation: Double,
) : Bin<Double>, ClosedFloatingPointRange<Double> by domain.range {
public operator fun get(value: Double): UnivariateBin? {
// check ceiling entry and return it if it is what needed
val ceil = bins.ceilingEntry(value)?.value
if (ceil != null && value in ceil) return ceil
//check floor entry
val floor = bins.floorEntry(value)?.value
if (floor != null && value in floor) return floor
//neither is valid, not found
return null
}
public override operator fun get(point: Buffer<out Double>): UnivariateBin? = get(point[0])
public override val dimension: Int get() = 1 public override val dimension: Int get() = 1
public override operator fun iterator(): Iterator<UnivariateBin> = bins.values.iterator() public override fun contains(point: Buffer<Double>): Boolean = point.size == 1 && contains(point[0])
}
@OptIn(UnstableKMathAPI::class)
public interface UnivariateHistogram : Histogram<Double, UnivariateBin>,
SpaceElement<UnivariateHistogram, Space<UnivariateHistogram>> {
public operator fun get(value: Double): UnivariateBin?
public override operator fun get(point: Buffer<Double>): UnivariateBin? = get(point[0])
public companion object { public companion object {
/**
* Build a histogram with a uniform binning with a start at [start] and a bin size of [binSize]
*/
public fun uniformBuilder(binSize: Double, start: Double = 0.0): UnivariateHistogramBuilder =
UnivariateHistogramSpace { value ->
val center = start + binSize * floor((value - start) / binSize + 0.5)
UnivariateBin(center, binSize)
}.builder()
/** /**
* Build and fill a [UnivariateHistogram]. Returns a read-only histogram. * Build and fill a [UnivariateHistogram]. Returns a read-only histogram.
*/ */
@ -78,35 +40,7 @@ public abstract class UnivariateHistogram protected constructor(
binSize: Double, binSize: Double,
start: Double = 0.0, start: Double = 0.0,
builder: UnivariateHistogramBuilder.() -> Unit, builder: UnivariateHistogramBuilder.() -> Unit,
): UnivariateHistogram = uniformBuilder(binSize, start).apply(builder) ): UnivariateHistogram = TreeHistogramSpace.uniform(binSize, start).produce(builder)
/**
* Create a histogram with custom cell borders
*/
public fun customBuilder(borders: DoubleArray): UnivariateHistogramBuilder {
val sorted = borders.sortedArray()
return UnivariateHistogramSpace { value ->
when {
value < sorted.first() -> UnivariateBin(
Double.NEGATIVE_INFINITY,
Double.MAX_VALUE
)
value > sorted.last() -> UnivariateBin(
Double.POSITIVE_INFINITY,
Double.MAX_VALUE
)
else -> {
val index = sorted.indices.first { value > sorted[it] }
val left = sorted[index]
val right = sorted[index + 1]
UnivariateBin((left + right) / 2, (right - left))
}
}
}.builder()
}
/** /**
* Build and fill a histogram with custom borders. Returns a read-only histogram. * Build and fill a histogram with custom borders. Returns a read-only histogram.
@ -114,48 +48,26 @@ public abstract class UnivariateHistogram protected constructor(
public fun custom( public fun custom(
borders: DoubleArray, borders: DoubleArray,
builder: UnivariateHistogramBuilder.() -> Unit, builder: UnivariateHistogramBuilder.() -> Unit,
): UnivariateHistogram = customBuilder(borders).apply(builder) ): UnivariateHistogram = TreeHistogramSpace.custom(borders).produce(builder)
} }
} }
public class UnivariateHistogramBuilder internal constructor( @UnstableKMathAPI
override val context: UnivariateHistogramSpace, public interface UnivariateHistogramBuilder : HistogramBuilder<Double> {
) : UnivariateHistogram(), MutableHistogram<Double, UnivariateBin> {
private fun createBin(value: Double): UnivariateBin = context.binFactory(value).also {
synchronized(this) { bins[it.position] = it }
}
/** /**
* Thread safe put operation * Thread safe put operation
*/ */
public fun put(value: Double, weight: Double = 1.0) { public fun putValue(at: Double, value: Double = 1.0)
(get(value) ?: createBin(value)).apply {
counter.increment()
weightCounter.add(weight)
}
}
override fun putWithWeight(point: Buffer<out Double>, weight: Double) { override fun putValue(point: Buffer<Double>, value: Number)
put(point[0], weight)
}
/**
* Put several items into a single bin
*/
public fun putMany(value: Double, count: Int, weight: Double = count.toDouble()) {
(get(value) ?: createBin(value)).apply {
counter.add(count.toLong())
weightCounter.add(weight)
}
}
} }
@UnstableKMathAPI @UnstableKMathAPI
public fun UnivariateHistogramBuilder.fill(items: Iterable<Double>): Unit = items.forEach(::put) public fun UnivariateHistogramBuilder.fill(items: Iterable<Double>): Unit = items.forEach(this::putValue)
@UnstableKMathAPI @UnstableKMathAPI
public fun UnivariateHistogramBuilder.fill(array: DoubleArray): Unit = array.forEach(::put) public fun UnivariateHistogramBuilder.fill(array: DoubleArray): Unit = array.forEach(this::putValue)
@UnstableKMathAPI @UnstableKMathAPI
public fun UnivariateHistogramBuilder.fill(buffer: Buffer<Double>): Unit = buffer.asSequence().forEach(::put) public fun UnivariateHistogramBuilder.fill(buffer: Buffer<Double>): Unit = buffer.asSequence().forEach(this::putValue)

25
kmath-histograms/src/jvmMain/kotlin/space/kscience/kmath/histogram/UnivariateHistogramSpace.kt
View File

@ -1,25 +0,0 @@
package space.kscience.kmath.histogram
import space.kscience.kmath.operations.Space
public class UnivariateHistogramSpace(public val binFactory: (Double) -> UnivariateBin) : Space<UnivariateHistogram> {
public fun builder(): UnivariateHistogramBuilder = UnivariateHistogramBuilder(this)
public fun produce(builder: UnivariateHistogramBuilder.() -> Unit): UnivariateHistogram = builder().apply(builder)
override fun add(
a: UnivariateHistogram,
b: UnivariateHistogram,
): UnivariateHistogram {
require(a.context == this){"Histogram $a does not belong to this context"}
require(b.context == this){"Histogram $b does not belong to this context"}
TODO()
}
override fun multiply(a: UnivariateHistogram, k: Number): UnivariateHistogram {
TODO("Not yet implemented")
}
override val zero: UnivariateHistogram = produce { }
}