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Dev #280

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altavir merged 99 commits from dev into master 2021-04-16 19:45:55 +03:00
Conversation 0 Commits 99 Files Changed 283 +5 -4
2 changed files with 5 additions and 4 deletions
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3
kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/GaussianSampler.kt
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@ -3,7 +3,6 @@ package space.kscience.kmath.samplers
import space.kscience.kmath.chains.BlockingDoubleChain
import space.kscience.kmath.chains.map
import space.kscience.kmath.stat.RandomGenerator
import space.kscience.kmath.stat.Sampler
/**
* Sampling from a Gaussian distribution with given mean and standard deviation.
@ -18,7 +17,7 @@ public class GaussianSampler(
public val mean: Double,
public val standardDeviation: Double,
private val normalized: NormalizedGaussianSampler = BoxMullerSampler
) : Sampler<Double> {
) : BlockingDoubleSampler {
init {
require(standardDeviation > 0.0) { "standard deviation is not strictly positive: $standardDeviation" }

6
kmath-stat/src/jvmTest/kotlin/space/kscience/kmath/stat/CommonsDistributionsTest.kt
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@ -18,10 +18,12 @@ internal class CommonsDistributionsTest {
}
@Test
fun testNormalDistributionBlocking() = runBlocking {
fun testNormalDistributionBlocking() {
val distribution = GaussianSampler(7.0, 2.0)
val generator = RandomGenerator.default(1)
val sample = distribution.sample(generator).nextBufferBlocking(1000)
Assertions.assertEquals(7.0, Mean.double(sample), 0.2)
runBlocking {
Assertions.assertEquals(7.0, Mean.double(sample), 0.2)
}
}
}