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/*
* Copyright (c) 2021. JetBrains s.r.o.
* Use of this source code is governed by the MIT license that can be found in the LICENSE file.
*/
package org.jetbrains.letsPlot.sampling
import org.jetbrains.letsPlot.intern.SamplingKind
import org.jetbrains.letsPlot.intern.layer.SamplingOptions
val samplingNone = SamplingOptions(SamplingKind.NONE, emptyMap())
/**
* Returns a subset of randomly selected items.
*
* ## Examples
*
* - [sampling_stratified.ipynb](https://nbviewer.org/github/JetBrains/lets-plot-docs/blob/master/source/kotlin_examples/cookbook/sampling_stratified.ipynb)
*
* @param n Number of items to return.
* @param seed Number used to initialize a pseudo random number generator.
*/
fun samplingRandom(n: Int, seed: Int? = null): SamplingOptions {
return SamplingOptions(SamplingKind.RANDOM, n, seed)
}
/**
* Randomly sample from each stratum (subgroup).
*
* ## Examples
*
* - [sampling_stratified.ipynb](https://nbviewer.org/github/JetBrains/lets-plot-docs/blob/master/source/kotlin_examples/cookbook/sampling_stratified.ipynb)
*
* @param n Number of items to return.
* @param seed Number used to initialize a pseudo random number generator.
* @param minSubsample Minimal number of items in sub sample.
*/
fun samplingRandomStratified(
n: Int,
seed: Int? = null,
minSubsample: Int? = null
): SamplingOptions {
return SamplingOptions(SamplingKind.RANDOM_STRATIFIED, n, seed, minSubsample)
}
fun samplingPick(n: Int): SamplingOptions {
return SamplingOptions(SamplingKind.PICK, n)
}
fun samplingSystematic(n: Int): SamplingOptions {
return SamplingOptions(SamplingKind.SYSTEMATIC, n)
}
fun samplingGroupSystematic(n: Int): SamplingOptions {
return SamplingOptions(SamplingKind.GROUP_SYSTEMATIC, n)
}
fun samplingGroupRandom(n: Int, seed: Int? = null): SamplingOptions {
return SamplingOptions(SamplingKind.GROUP_RANDOM, n, seed)
}
fun samplingVertexVW(n: Int): SamplingOptions {
return SamplingOptions(SamplingKind.VERTEX_VW, n)
}
fun samplingVertexDP(n: Int): SamplingOptions {
return SamplingOptions(SamplingKind.VERTEX_DP, n)
}