Fixed some performance issues with histogram
This commit is contained in:
parent
5e3e0eb09d
commit
15cc4a22e2
@ -1,24 +1,31 @@
|
||||
package scientifik.kmath.histogram
|
||||
|
||||
import scientifik.kmath.linear.RealVector
|
||||
import scientifik.kmath.linear.toVector
|
||||
import scientifik.kmath.structures.Buffer
|
||||
import scientifik.kmath.structures.ListBuffer
|
||||
import scientifik.kmath.structures.NDStructure
|
||||
import scientifik.kmath.structures.ndStructure
|
||||
import kotlin.math.floor
|
||||
|
||||
class MultivariateBin(override val center: RealVector, val sizes: RealVector, val counter: LongCounter = LongCounter()) : Bin<Double> {
|
||||
typealias RealPoint = Point<Double>
|
||||
|
||||
private operator fun RealPoint.minus(other: RealPoint) = ListBuffer((0 until size).map { get(it) - other[it] })
|
||||
|
||||
private inline fun <T> Buffer<out Double>.mapIndexed(crossinline mapper: (Int, Double) -> T): Sequence<T> = (0 until size).asSequence().map { mapper(it, get(it)) }
|
||||
|
||||
|
||||
class MultivariateBin(override val center: RealPoint, val sizes: RealPoint, var counter: Long = 0) : Bin<Double> {
|
||||
init {
|
||||
if (center.size != sizes.size) error("Dimension mismatch in bin creation. Expected ${center.size}, but found ${sizes.size}")
|
||||
}
|
||||
|
||||
override fun contains(vector: Buffer<out Double>): Boolean {
|
||||
if (vector.size != center.size) error("Dimension mismatch for input vector. Expected ${center.size}, but found ${vector.size}")
|
||||
return vector.asSequence().mapIndexed { i, value -> value in (center[i] - sizes[i] / 2)..(center[i] + sizes[i] / 2) }.all { it }
|
||||
return vector.mapIndexed { i, value -> value in (center[i] - sizes[i] / 2)..(center[i] + sizes[i] / 2) }.all { it }
|
||||
}
|
||||
|
||||
override val value get() = counter.sum()
|
||||
internal operator fun inc() = this.also { counter.increment() }
|
||||
override val value get() = counter
|
||||
internal operator fun inc() = this.also { counter++ }
|
||||
|
||||
override val dimension: Int get() = center.size
|
||||
}
|
||||
@ -28,8 +35,8 @@ class MultivariateBin(override val center: RealVector, val sizes: RealVector, va
|
||||
* The histogram is optimized for speed, but have large size in memory
|
||||
*/
|
||||
class FastHistogram(
|
||||
private val lower: RealVector,
|
||||
private val upper: RealVector,
|
||||
private val lower: RealPoint,
|
||||
private val upper: RealPoint,
|
||||
private val binNums: IntArray = IntArray(lower.size) { 20 }
|
||||
) : MutableHistogram<Double, MultivariateBin> {
|
||||
|
||||
@ -37,25 +44,27 @@ class FastHistogram(
|
||||
// argument checks
|
||||
if (lower.size != upper.size) error("Dimension mismatch in histogram lower and upper limits.")
|
||||
if (lower.size != binNums.size) error("Dimension mismatch in bin count.")
|
||||
if ((upper - lower).any { it <= 0 }) error("Range for one of axis is not strictly positive")
|
||||
if ((upper - lower).asSequence().any { it <= 0 }) error("Range for one of axis is not strictly positive")
|
||||
}
|
||||
|
||||
|
||||
override val dimension: Int get() = lower.size
|
||||
|
||||
//TODO optimize binSize performance if needed
|
||||
private val binSize = (upper - lower).mapIndexed { index, value -> value / binNums[index] }.toVector()
|
||||
private val binSize: RealPoint = ListBuffer((upper - lower).mapIndexed { index, value -> value / binNums[index] }.toList())
|
||||
|
||||
private val bins: NDStructure<MultivariateBin> by lazy {
|
||||
val actualSizes = IntArray(binNums.size) { binNums[it] + 2 }
|
||||
ndStructure(actualSizes) { indexArray ->
|
||||
val center = indexArray.mapIndexed { axis, index ->
|
||||
when (index) {
|
||||
0 -> Double.NEGATIVE_INFINITY
|
||||
actualSizes[axis] - 1 -> Double.POSITIVE_INFINITY
|
||||
else -> lower[axis] + (index.toDouble() - 0.5) * binSize[axis]
|
||||
}
|
||||
}.toVector()
|
||||
val center = ListBuffer(
|
||||
indexArray.mapIndexed { axis, index ->
|
||||
when (index) {
|
||||
0 -> Double.NEGATIVE_INFINITY
|
||||
actualSizes[axis] - 1 -> Double.POSITIVE_INFINITY
|
||||
else -> lower[axis] + (index.toDouble() - 0.5) * binSize[axis]
|
||||
}
|
||||
}
|
||||
)
|
||||
MultivariateBin(center, binSize)
|
||||
}
|
||||
}
|
||||
@ -91,13 +100,14 @@ class FastHistogram(
|
||||
return ndStructure(this.bins.shape) { bins[it].value }
|
||||
}
|
||||
|
||||
/**
|
||||
* Create a phantom lightweight immutable copy of this histogram
|
||||
*/
|
||||
fun asPhantom(): PhantomHistogram<Double> {
|
||||
val binTemplates = bins.associate { (index, bin) -> BinTemplate<Double>(bin.center, bin.sizes) to index }
|
||||
return PhantomHistogram(binTemplates, asND())
|
||||
}
|
||||
// /**
|
||||
// * Create a phantom lightweight immutable copy of this histogram
|
||||
// */
|
||||
// fun asPhantom(): PhantomHistogram<Double> {
|
||||
// val center =
|
||||
// val binTemplates = bins.associate { (index, bin) -> BinTemplate<Double>(bin.center, bin.sizes) to index }
|
||||
// return PhantomHistogram(binTemplates, asND())
|
||||
// }
|
||||
|
||||
companion object {
|
||||
|
||||
|
@ -1,9 +1,7 @@
|
||||
package scientifik.kmath.linear
|
||||
|
||||
import scientifik.kmath.operations.*
|
||||
import scientifik.kmath.structures.ExtendedNDField
|
||||
import scientifik.kmath.structures.GenericNDField
|
||||
import scientifik.kmath.structures.NDField
|
||||
import scientifik.kmath.structures.*
|
||||
|
||||
/**
|
||||
* The space for linear elements. Supports scalar product alongside with standard linear operations.
|
||||
@ -169,3 +167,21 @@ class ArrayMatrixSpace<T : Any, F : Field<T>>(
|
||||
return ArrayMatrixSpace(rows, columns, field, ndFactory)
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Member of [ArrayMatrixSpace] which wraps 2-D array
|
||||
*/
|
||||
class ArrayMatrix<T : Any, F : Field<T>> internal constructor(override val context: ArrayMatrixSpace<T, F>, val element: NDElement<T, F>) : Matrix<T, F> {
|
||||
|
||||
constructor(context: ArrayMatrixSpace<T, F>, initializer: (Int, Int) -> T) : this(context, context.ndField.produce { list -> initializer(list[0], list[1]) })
|
||||
|
||||
override val rows: Int get() = context.rows
|
||||
|
||||
override val columns: Int get() = context.columns
|
||||
|
||||
override fun get(i: Int, j: Int): T {
|
||||
return element[i, j]
|
||||
}
|
||||
|
||||
override val self: ArrayMatrix<T, F> get() = this
|
||||
}
|
||||
|
@ -73,23 +73,7 @@ class ArrayVectorSpace<T : Any, F : Field<T>>(
|
||||
override fun produce(initializer: (Int) -> T): Vector<T, F> = ArrayVector(this, initializer)
|
||||
}
|
||||
|
||||
/**
|
||||
* Member of [ArrayMatrixSpace] which wraps 2-D array
|
||||
*/
|
||||
class ArrayMatrix<T : Any, F : Field<T>> internal constructor(override val context: ArrayMatrixSpace<T, F>, val element: NDElement<T, F>) : Matrix<T, F> {
|
||||
|
||||
constructor(context: ArrayMatrixSpace<T, F>, initializer: (Int, Int) -> T) : this(context, context.ndField.produce { list -> initializer(list[0], list[1]) })
|
||||
|
||||
override val rows: Int get() = context.rows
|
||||
|
||||
override val columns: Int get() = context.columns
|
||||
|
||||
override fun get(i: Int, j: Int): T {
|
||||
return element[i, j]
|
||||
}
|
||||
|
||||
override val self: ArrayMatrix<T, F> get() = this
|
||||
}
|
||||
|
||||
|
||||
class ArrayVector<T : Any, F : Field<T>> internal constructor(override val context: VectorSpace<T, F>, val element: NDElement<T, F>) : Vector<T, F> {
|
||||
|
@ -4,12 +4,16 @@ package scientifik.kmath.structures
|
||||
/**
|
||||
* A generic random access structure for both primitives and objects
|
||||
*/
|
||||
interface Buffer<T> : Iterable<T> {
|
||||
interface Buffer<T> {
|
||||
|
||||
val size: Int
|
||||
|
||||
operator fun get(index: Int): T
|
||||
|
||||
operator fun iterator(): Iterator<T>
|
||||
|
||||
fun asSequence(): Sequence<T> = iterator().asSequence()
|
||||
|
||||
/**
|
||||
* A shallow copy of the buffer
|
||||
*/
|
||||
@ -25,7 +29,20 @@ interface MutableBuffer<T> : Buffer<T> {
|
||||
override fun copy(): MutableBuffer<T>
|
||||
}
|
||||
|
||||
inline class ListBuffer<T>(private val list: MutableList<T>) : MutableBuffer<T> {
|
||||
|
||||
inline class ListBuffer<T>(private val list: List<T>) : Buffer<T> {
|
||||
|
||||
override val size: Int
|
||||
get() = list.size
|
||||
|
||||
override fun get(index: Int): T = list[index]
|
||||
|
||||
override fun iterator(): Iterator<T> = list.iterator()
|
||||
|
||||
override fun copy(): ListBuffer<T> = ListBuffer(ArrayList(list))
|
||||
}
|
||||
|
||||
inline class MutableListBuffer<T>(private val list: MutableList<T>) : MutableBuffer<T> {
|
||||
|
||||
override val size: Int
|
||||
get() = list.size
|
||||
@ -38,7 +55,7 @@ inline class ListBuffer<T>(private val list: MutableList<T>) : MutableBuffer<T>
|
||||
|
||||
override fun iterator(): Iterator<T> = list.iterator()
|
||||
|
||||
override fun copy(): MutableBuffer<T> = ListBuffer(ArrayList(list))
|
||||
override fun copy(): MutableBuffer<T> = MutableListBuffer(ArrayList(list))
|
||||
}
|
||||
|
||||
class ArrayBuffer<T>(private val array: Array<T>) : MutableBuffer<T> {
|
||||
|
@ -76,7 +76,7 @@ class DefaultStrides(override val shape: IntArray) : Strides {
|
||||
override fun offset(index: IntArray): Int {
|
||||
return index.mapIndexed { i, value ->
|
||||
if (value < 0 || value >= shape[i]) {
|
||||
throw RuntimeException("Index $value out of shape bounds: (0,${shape[i]})")
|
||||
throw RuntimeException("Index $value out of shape bounds: (0,${this.shape[i]})")
|
||||
}
|
||||
value * strides[i]
|
||||
}.sum()
|
||||
@ -169,6 +169,6 @@ fun <T> genericNdStructure(shape: IntArray, initializer: (IntArray) -> T): Mutab
|
||||
yield(initializer(it))
|
||||
}
|
||||
}
|
||||
val buffer = ListBuffer<T>(sequence.toMutableList())
|
||||
val buffer = MutableListBuffer<T>(sequence.toMutableList())
|
||||
return MutableBufferNDStructure(strides, buffer)
|
||||
}
|
||||
|
Loading…
Reference in New Issue
Block a user