dev #24

Merged
altavir merged 14 commits from dev into master 2018-12-11 17:42:42 +03:00
3 changed files with 20 additions and 37 deletions
Showing only changes of commit bdd9dccd4f - Show all commits

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@ -8,23 +8,6 @@ private operator fun RealPoint.minus(other: RealPoint) = ListBuffer((0 until siz
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.mapIndexed { i, value -> value in (center[i] - sizes[i] / 2)..(center[i] + sizes[i] / 2) }.all { it }
// }
//
// override val value get() = counter
// internal operator fun inc() = this.also { counter++ }
//
// override val dimension: Int get() = center.size
//}
/**
* Uniform multivariate histogram with fixed borders. Based on NDStructure implementation with complexity of m for bin search, where m is the number of dimensions.
*/
@ -109,18 +92,17 @@ class FastHistogram(
/**
* Convert this histogram into NDStructure containing bin values but not bin descriptions
*/
fun asND(): NDStructure<Number> {
fun asNDStructure(): NDStructure<Number> {
return ndStructure(this.values.shape) { values[it].sum() }
}
// /**
// * 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())
// }
/**
* Create a phantom lightweight immutable copy of this histogram
*/
fun asPhantomHistogram(): PhantomHistogram<Double> {
val binTemplates = values.associate { (index, _) -> getTemplate(index) to index }
return PhantomHistogram(binTemplates, asNDStructure())
}
companion object {
@ -148,8 +130,8 @@ class FastHistogram(
*/
fun fromRanges(vararg ranges: Pair<ClosedFloatingPointRange<Double>, Int>): FastHistogram {
return FastHistogram(
ranges.map { it.first.start }.toVector(),
ranges.map { it.first.endInclusive }.toVector(),
ListBuffer(ranges.map { it.first.start }),
ListBuffer(ranges.map { it.first.endInclusive }),
ranges.map { it.second }.toIntArray()
)
}

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@ -53,6 +53,7 @@ interface MutableHistogram<T: Any, out B : Bin<T>>: Histogram<T,B>{
fun <T: Any> MutableHistogram<T,*>.put(vararg point: T) = put(ArrayBuffer(point))
fun MutableHistogram<Double,*>.put(vararg point: Number) = put(DoubleBuffer(point.map { it.toDouble() }.toDoubleArray()))
fun MutableHistogram<Double,*>.put(vararg point: Double) = put(DoubleBuffer(point))
fun <T: Any> MutableHistogram<T,*>.fill(sequence: Iterable<Point<T>>) = sequence.forEach { put(it) }

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@ -83,15 +83,15 @@ class DefaultStrides(override val shape: IntArray) : Strides {
}
override fun index(offset: Int): IntArray {
return sequence {
val res = IntArray(shape.size)
var current = offset
var strideIndex = strides.size - 2
while (strideIndex >= 0) {
yield(current / strides[strideIndex])
res[ strideIndex] = (current / strides[strideIndex])
current %= strides[strideIndex]
strideIndex--
}
}.toList().reversed().toIntArray()
return res
}
override val linearSize: Int