forked from kscience/kmath
Added phantom histograms
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@ -84,6 +84,21 @@ class FastHistogram(
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override fun iterator(): Iterator<MultivariateBin> = bins.asSequence().map { it.second }.iterator()
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/**
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* Convert this histogram into NDStructure containing bin values but not bin descriptions
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*/
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fun asND(): NDStructure<Number> {
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return ndStructure(this.bins.shape) { bins[it].value }
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}
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/**
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* Create a phantom lightweight immutable copy of this histogram
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*/
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fun asPhantom(): PhantomHistogram<Double> {
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val binTemplates = bins.associate { (index, bin) -> BinTemplate<Double>(bin.center, bin.sizes) to index }
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return PhantomHistogram(binTemplates, asND())
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}
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companion object {
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/**
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@ -4,7 +4,7 @@ import scientifik.kmath.linear.Vector
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import scientifik.kmath.operations.Space
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import scientifik.kmath.structures.NDStructure
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class BinTemplate<T : Comparable<T>>(val center: Vector<T>, val sizes: Vector<T>) {
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data class BinTemplate<T : Comparable<T>>(val center: Vector<T>, val sizes: Vector<T>) {
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fun contains(vector: Point<out T>): Boolean {
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if (vector.size != center.size) error("Dimension mismatch for input vector. Expected ${center.size}, but found ${vector.size}")
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val upper = center + sizes/2.0
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@ -40,10 +40,11 @@ class PhantomBin<T : Comparable<T>>(val template: BinTemplate<T>, override val v
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/**
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* Immutable histogram with explicit structure for content and additional external bin description.
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* Bin search is slow, but full histogram algebra is supported.
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* @param bins map a template into structure index
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*/
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class PhantomHistogram<T : Comparable<T>>(
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val bins: Map<BinTemplate<T>, IntArray>,
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val data: NDStructure<Double>
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val data: NDStructure<Number>
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) : Histogram<T, PhantomBin<T>> {
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override val dimension: Int
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