Merge remote-tracking branch 'origin/dev' into dev
# 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:
commit
c6ea423bd6
@ -42,6 +42,7 @@
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- `Complex` and related features moved to a separate module `kmath-complex`
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- Refactor AlgebraElement
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- `symbol` method in `Algebra` renamed to `bindSymbol` to avoid ambiguity
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- Add `out` projection to `Buffer` generic
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### Deprecated
|
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|
||||
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||||
@ -21,8 +21,17 @@ public class MstExpression<T, out A : Algebra<T>>(public val algebra: A, public
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null
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} ?: arguments.getValue(StringSymbol(value))
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override fun unaryOperationFunction(operation: String): (arg: T) -> T = algebra.unaryOperationFunction(operation)
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override fun binaryOperationFunction(operation: String): (left: T, right: T) -> T = algebra.binaryOperationFunction(operation)
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override fun unaryOperation(operation: String, arg: T): T =
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algebra.unaryOperation(operation, arg)
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override fun binaryOperation(operation: String, left: T, right: T): T =
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algebra.binaryOperation(operation, left, right)
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override fun unaryOperationFunction(operation: String): (arg: T) -> T =
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algebra.unaryOperationFunction(operation)
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override fun binaryOperationFunction(operation: String): (left: T, right: T) -> T =
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algebra.binaryOperationFunction(operation)
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@Suppress("UNCHECKED_CAST")
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override fun number(value: Number): T = if (algebra is NumericAlgebra<*>)
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File diff suppressed because it is too large
Load Diff
@ -13,11 +13,12 @@
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* See the License for the specific language governing permissions and
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||||
* limitations under the License.
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||||
*/
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package space.kscience.kmath.domains
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package kscience.kmath.domains
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import space.kscience.kmath.linear.Point
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import space.kscience.kmath.structures.RealBuffer
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import space.kscience.kmath.structures.indices
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import kscience.kmath.linear.Point
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import kscience.kmath.structures.Buffer
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import kscience.kmath.structures.RealBuffer
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import kscience.kmath.structures.indices
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/**
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*
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@ -25,20 +26,20 @@ import space.kscience.kmath.structures.indices
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*
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* @author Alexander Nozik
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*/
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public class HyperSquareDomain(private val lower: RealBuffer, private val upper: RealBuffer) : RealDomain {
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public class HyperSquareDomain(private val lower: Buffer<Double>, private val upper: Buffer<Double>) : RealDomain {
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public override val dimension: Int get() = lower.size
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public override operator fun contains(point: Point<Double>): Boolean = point.indices.all { i ->
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point[i] in lower[i]..upper[i]
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}
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||||
|
||||
public override fun getLowerBound(num: Int, point: Point<Double>): Double? = lower[num]
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public override fun getLowerBound(num: Int, point: Point<Double>): Double = lower[num]
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||||
|
||||
public override fun getLowerBound(num: Int): Double? = lower[num]
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public override fun getLowerBound(num: Int): Double = lower[num]
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|
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public override fun getUpperBound(num: Int, point: Point<Double>): Double? = upper[num]
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public override fun getUpperBound(num: Int, point: Point<Double>): Double = upper[num]
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|
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public override fun getUpperBound(num: Int): Double? = upper[num]
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public override fun getUpperBound(num: Int): Double = upper[num]
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||||
|
||||
public override fun nearestInDomain(point: Point<Double>): Point<Double> {
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val res = DoubleArray(point.size) { i ->
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|
||||
@ -78,8 +78,7 @@ public interface NDStructure<T> {
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strides: Strides,
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bufferFactory: BufferFactory<T> = Buffer.Companion::boxing,
|
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initializer: (IntArray) -> T,
|
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): NDBuffer<T> =
|
||||
NDBuffer(strides, bufferFactory(strides.linearSize) { i -> initializer(strides.index(i)) })
|
||||
): NDBuffer<T> = NDBuffer(strides, bufferFactory(strides.linearSize) { i -> initializer(strides.index(i)) })
|
||||
|
||||
/**
|
||||
* 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(
|
||||
strides: Strides,
|
||||
crossinline initializer: (IntArray) -> T,
|
||||
): NDBuffer<T> =
|
||||
NDBuffer(strides, Buffer.auto(strides.linearSize) { i -> initializer(strides.index(i)) })
|
||||
): NDBuffer<T> = NDBuffer(strides, Buffer.auto(strides.linearSize) { i -> initializer(strides.index(i)) })
|
||||
|
||||
public inline fun <T : Any> auto(
|
||||
type: KClass<T>,
|
||||
strides: Strides,
|
||||
crossinline initializer: (IntArray) -> T,
|
||||
): NDBuffer<T> =
|
||||
NDBuffer(strides, Buffer.auto(type, strides.linearSize) { i -> initializer(strides.index(i)) })
|
||||
): NDBuffer<T> = NDBuffer(strides, Buffer.auto(type, strides.linearSize) { i -> initializer(strides.index(i)) })
|
||||
|
||||
public fun <T> build(
|
||||
shape: IntArray,
|
||||
@ -106,8 +103,7 @@ public interface NDStructure<T> {
|
||||
public inline fun <reified T : Any> auto(
|
||||
shape: IntArray,
|
||||
crossinline initializer: (IntArray) -> T,
|
||||
): NDBuffer<T> =
|
||||
auto(DefaultStrides(shape), initializer)
|
||||
): NDBuffer<T> = auto(DefaultStrides(shape), initializer)
|
||||
|
||||
@JvmName("autoVarArg")
|
||||
public inline fun <reified T : Any> auto(
|
||||
@ -120,8 +116,7 @@ public interface NDStructure<T> {
|
||||
type: KClass<T>,
|
||||
vararg shape: Int,
|
||||
crossinline initializer: (IntArray) -> T,
|
||||
): NDBuffer<T> =
|
||||
auto(type, DefaultStrides(shape), initializer)
|
||||
): NDBuffer<T> = auto(type, DefaultStrides(shape), initializer)
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
@ -21,7 +21,7 @@ public typealias MutableBufferFactory<T> = (Int, (Int) -> T) -> MutableBuffer<T>
|
||||
*
|
||||
* @param T the type of elements contained in the buffer.
|
||||
*/
|
||||
public interface Buffer<T> {
|
||||
public interface Buffer<out T> {
|
||||
/**
|
||||
* The size of this buffer.
|
||||
*/
|
||||
|
||||
@ -1,4 +1,10 @@
|
||||
plugins { id("ru.mipt.npm.mpp") }
|
||||
plugins {
|
||||
id("ru.mipt.npm.mpp")
|
||||
}
|
||||
|
||||
kscience {
|
||||
useAtomic()
|
||||
}
|
||||
|
||||
kotlin.sourceSets {
|
||||
commonMain {
|
||||
|
||||
@ -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 { }
|
||||
}
|
||||
|
||||
@ -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()
|
||||
)
|
||||
}
|
||||
}
|
||||
@ -1,20 +1,49 @@
|
||||
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
|
||||
* TODO replace with atomics
|
||||
*/
|
||||
|
||||
public expect class LongCounter() {
|
||||
public fun decrement()
|
||||
public fun increment()
|
||||
public fun reset()
|
||||
public fun sum(): Long
|
||||
public fun add(l: Long)
|
||||
public interface Counter<T : Any> {
|
||||
public fun add(delta: T)
|
||||
public val value: T
|
||||
public companion object{
|
||||
public fun real(): ObjectCounter<Double> = ObjectCounter(RealField)
|
||||
}
|
||||
}
|
||||
|
||||
public expect class DoubleCounter() {
|
||||
public fun reset()
|
||||
public fun sum(): Double
|
||||
public fun add(d: Double)
|
||||
public class IntCounter : Counter<Int> {
|
||||
private val innerValue = atomic(0)
|
||||
|
||||
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
|
||||
}
|
||||
|
||||
|
||||
|
||||
@ -6,18 +6,16 @@ import space.kscience.kmath.structures.ArrayBuffer
|
||||
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> {
|
||||
/**
|
||||
* The value of this bin.
|
||||
*/
|
||||
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
|
||||
*/
|
||||
@ -27,28 +25,31 @@ public interface Histogram<T : Any, out B : Bin<T>> : Iterable<B> {
|
||||
* Dimension of the histogram
|
||||
*/
|
||||
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
|
||||
*/
|
||||
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()))
|
||||
|
||||
public fun MutableHistogram<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 HistogramBuilder<Double>.put(vararg point: Double): Unit = put(RealBuffer(point))
|
||||
public fun <T : Any> HistogramBuilder<T>.fill(sequence: Iterable<Point<T>>): Unit = sequence.forEach { put(it) }
|
||||
|
||||
/**
|
||||
* 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())
|
||||
|
||||
@ -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()
|
||||
)
|
||||
}
|
||||
}
|
||||
@ -1,22 +1,24 @@
|
||||
package scietifik.kmath.histogram
|
||||
|
||||
import space.kscience.kmath.histogram.RealHistogram
|
||||
import space.kscience.kmath.histogram.fill
|
||||
import space.kscience.kmath.histogram.put
|
||||
import space.kscience.kmath.real.RealVector
|
||||
import space.kscience.kmath.real.invoke
|
||||
import kscience.kmath.histogram.RealHistogramSpace
|
||||
import kscience.kmath.histogram.put
|
||||
import kscience.kmath.operations.invoke
|
||||
import kscience.kmath.real.RealVector
|
||||
import kscience.kmath.real.invoke
|
||||
import kotlin.random.Random
|
||||
import kotlin.test.*
|
||||
|
||||
internal class MultivariateHistogramTest {
|
||||
@Test
|
||||
fun testSinglePutHistogram() {
|
||||
val histogram = RealHistogram.fromRanges(
|
||||
val hSpace = RealHistogramSpace.fromRanges(
|
||||
(-1.0..1.0),
|
||||
(-1.0..1.0)
|
||||
)
|
||||
histogram.put(0.55, 0.55)
|
||||
val bin = histogram.find { it.value.toInt() > 0 } ?: fail()
|
||||
val histogram = hSpace.produce {
|
||||
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(0.6, 0.5)) }
|
||||
assertFalse { bin.contains(RealVector(-0.55, 0.55)) }
|
||||
@ -24,7 +26,7 @@ internal class MultivariateHistogramTest {
|
||||
|
||||
@Test
|
||||
fun testSequentialPut() {
|
||||
val histogram = RealHistogram.fromRanges(
|
||||
val hSpace = RealHistogramSpace.fromRanges(
|
||||
(-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)
|
||||
|
||||
val n = 10000
|
||||
|
||||
histogram.fill {
|
||||
val histogram = hSpace.produce {
|
||||
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() })
|
||||
}
|
||||
}
|
||||
}
|
||||
@ -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
|
||||
}
|
||||
}
|
||||
@ -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)
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
@ -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
|
||||
@ -1,76 +1,38 @@
|
||||
package space.kscience.kmath.histogram
|
||||
package kscience.kmath.histogram
|
||||
|
||||
import space.kscience.kmath.linear.Point
|
||||
import space.kscience.kmath.misc.UnstableKMathAPI
|
||||
import space.kscience.kmath.operations.SpaceElement
|
||||
import space.kscience.kmath.structures.Buffer
|
||||
import space.kscience.kmath.structures.asBuffer
|
||||
import space.kscience.kmath.structures.asSequence
|
||||
import java.util.*
|
||||
import kotlin.math.floor
|
||||
import kscience.kmath.domains.UnivariateDomain
|
||||
import kscience.kmath.misc.UnstableKMathAPI
|
||||
import kscience.kmath.operations.Space
|
||||
import kscience.kmath.operations.SpaceElement
|
||||
import kscience.kmath.structures.Buffer
|
||||
import kscience.kmath.structures.asSequence
|
||||
|
||||
//TODO move to common
|
||||
|
||||
public val UnivariateDomain.center: Double get() = (range.endInclusive - range.start) / 2
|
||||
|
||||
/**
|
||||
* 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
|
||||
*/
|
||||
public class UnivariateBin(
|
||||
public val position: Double,
|
||||
public val size: Double,
|
||||
) : Bin<Double> {
|
||||
//internal mutation operations
|
||||
internal val counter: LongCounter = LongCounter()
|
||||
internal val weightCounter: DoubleCounter = DoubleCounter()
|
||||
public val domain: UnivariateDomain,
|
||||
override val value: Double,
|
||||
public val standardDeviation: Double,
|
||||
) : Bin<Double>, ClosedFloatingPointRange<Double> by domain.range {
|
||||
|
||||
/**
|
||||
* 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])
|
||||
public override fun contains(point: Buffer<Double>): Boolean = point.size == 1 && contains(point[0])
|
||||
}
|
||||
|
||||
/**
|
||||
* Univariate histogram with log(n) bin search speed
|
||||
*/
|
||||
@OptIn(UnstableKMathAPI::class)
|
||||
public abstract class UnivariateHistogram protected constructor(
|
||||
protected val bins: TreeMap<Double, UnivariateBin> = TreeMap(),
|
||||
) : Histogram<Double, UnivariateBin>, SpaceElement<UnivariateHistogram, UnivariateHistogramSpace> {
|
||||
|
||||
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 operator fun iterator(): Iterator<UnivariateBin> = bins.values.iterator()
|
||||
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 {
|
||||
/**
|
||||
* 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.
|
||||
*/
|
||||
@ -78,35 +40,7 @@ public abstract class UnivariateHistogram protected constructor(
|
||||
binSize: Double,
|
||||
start: Double = 0.0,
|
||||
builder: UnivariateHistogramBuilder.() -> Unit,
|
||||
): UnivariateHistogram = uniformBuilder(binSize, start).apply(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()
|
||||
}
|
||||
): UnivariateHistogram = TreeHistogramSpace.uniform(binSize, start).produce(builder)
|
||||
|
||||
/**
|
||||
* 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(
|
||||
borders: DoubleArray,
|
||||
builder: UnivariateHistogramBuilder.() -> Unit,
|
||||
): UnivariateHistogram = customBuilder(borders).apply(builder)
|
||||
): UnivariateHistogram = TreeHistogramSpace.custom(borders).produce(builder)
|
||||
|
||||
}
|
||||
}
|
||||
|
||||
public class UnivariateHistogramBuilder internal constructor(
|
||||
override val context: UnivariateHistogramSpace,
|
||||
) : UnivariateHistogram(), MutableHistogram<Double, UnivariateBin> {
|
||||
|
||||
private fun createBin(value: Double): UnivariateBin = context.binFactory(value).also {
|
||||
synchronized(this) { bins[it.position] = it }
|
||||
}
|
||||
|
||||
@UnstableKMathAPI
|
||||
public interface UnivariateHistogramBuilder : HistogramBuilder<Double> {
|
||||
/**
|
||||
* Thread safe put operation
|
||||
*/
|
||||
public fun put(value: Double, weight: Double = 1.0) {
|
||||
(get(value) ?: createBin(value)).apply {
|
||||
counter.increment()
|
||||
weightCounter.add(weight)
|
||||
}
|
||||
}
|
||||
public fun putValue(at: Double, value: Double = 1.0)
|
||||
|
||||
override fun putWithWeight(point: Buffer<out Double>, weight: Double) {
|
||||
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)
|
||||
}
|
||||
}
|
||||
override fun putValue(point: Buffer<Double>, value: Number)
|
||||
}
|
||||
|
||||
@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
|
||||
public fun UnivariateHistogramBuilder.fill(array: DoubleArray): Unit = array.forEach(::put)
|
||||
public fun UnivariateHistogramBuilder.fill(array: DoubleArray): Unit = array.forEach(this::putValue)
|
||||
|
||||
@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)
|
||||
@ -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 { }
|
||||
}
|
||||
Loading…
Reference in New Issue
Block a user