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Random numbers

Data2viz offers several random numbers generators you can access using the RandomDistribution.* factories.
To use these random numbers distributions, import the io.data2viz.random dependency and use the io.data2viz.random.* import.

Factory
RandomDistribution.*
Distribution of random numbers
uniform(min, max)Continuous uniform distribution
normal(mu, sigma)Normal (gaussian) distribution
logNormal(mu, sigma)Log-normal distribution
exponential(lambda)Exponential distribution
irwinHall(n)Irwin–Hall distribution
bates(n)Bates distribution

RandomDistribution.uniform is the "standard" number generator.

Standard (uniform)

The RandomDistribution.uniform(min, max) generates random numbers using an uniform distribution.

Numbers generated are greater or equals to min and less than max.
Default min is 0.0, default max is 1.0, so default range is [0, 1[

import io.data2viz.color.* import io.data2viz.geom.* import io.data2viz.math.* import io.data2viz.viz.* import io.data2viz.random.* fun main() { viz { size = size(620, 100) (0..600 step 50).forEach { text { x = 10.0 + it y = 94.0 textContent = "$it" fill = Colors.Web.black textAlign = textAlign(TextHAlign.MIDDLE, TextVAlign.MIDDLE) } } //sampleStart val generator = RandomDistribution.uniform(max = 600.0) val groupCount = (0..30000).map { generator().toInt() } .groupingBy { it } .eachCount() groupCount.forEach { valueCount -> rect { y = 85.0 - valueCount.value x = 10.0 + valueCount.key size = size(1, valueCount.value) fill = Colors.Web.crimson } } //sampleEnd }.bindRendererOnNewCanvas() }

Other distributions

Normal

The RandomDistribution.normal(mu, sigma) generates random numbers using a normal (Gaussian) distribution.

The expected value of the generated numbers is mu (default 0.0), with the given standard deviation sigma (default 1.0).

import io.data2viz.color.* import io.data2viz.geom.* import io.data2viz.math.* import io.data2viz.viz.* import io.data2viz.random.* fun main() { viz { size = size(620, 100) (0..600 step 50).forEach { text { x = 10.0 + it y = 94.0 textContent = "$it" fill = Colors.Web.black textAlign = textAlign(TextHAlign.MIDDLE, TextVAlign.MIDDLE) } } //sampleStart val generator = RandomDistribution.normal(300.0, 50.0) val groupCount = (0..8000).map { generator().toInt() } .groupingBy { it } .eachCount() groupCount.forEach { valueCount -> rect { y = 85.0 - valueCount.value x = 10.0 + valueCount.key size = size(1, valueCount.value) fill = Colors.Web.crimson } } //sampleEnd }.bindRendererOnNewCanvas() }

Log-Normal

The RandomDistribution.logNormal(mu, sigma) generates random numbers using a log-normal distribution.

The expected value of the random variable’s natural logarithm is mu (defaults to 0.0), with the given standard deviation sigma (defaults to 1.0)

import io.data2viz.color.* import io.data2viz.geom.* import io.data2viz.math.* import io.data2viz.viz.* import io.data2viz.random.* fun main() { viz { size = size(620, 100) (0..600 step 60).forEach { text { x = 10.0 + it y = 94.0 textContent = "${(it / 3.0).toInt() / 100.0}" fill = Colors.Web.black textAlign = textAlign(TextHAlign.MIDDLE, TextVAlign.MIDDLE) } } //sampleStart val generator = RandomDistribution.logNormal(sigma = 0.25) val groupCount = (0..8000).map { generator() } .groupingBy { (it * 300).toInt() } .eachCount() groupCount.forEach { valueCount -> rect { y = 85.0 - valueCount.value x = 10.0 + valueCount.key size = size(1, valueCount.value) fill = Colors.Web.crimson } } //sampleEnd }.bindRendererOnNewCanvas() }

Exponential

The RandomDistribution.exponential(lambda) generates random numbers using an exponential distribution.

This generates random numbers with an exponential distribution with the rate lambda (defaults to 1.0) equivalent to time between events in a Poisson process with a mean of 1 / lambda.

import io.data2viz.color.* import io.data2viz.geom.* import io.data2viz.math.* import io.data2viz.viz.* import io.data2viz.random.* fun main() { viz { size = size(620, 100) (0..600 step 60).forEach { text { x = 10.0 + it y = 94.0 textContent = "${(it / 60.0).toInt()}" fill = Colors.Web.black textAlign = textAlign(TextHAlign.MIDDLE, TextVAlign.MIDDLE) } } //sampleStart val generator = RandomDistribution.exponential() val groupCount = (0..4000).map { generator() } .groupingBy { (it * 60).toInt() } .eachCount() groupCount.forEach { valueCount -> rect { y = 85.0 - valueCount.value x = 10.0 + valueCount.key size = size(1, valueCount.value) fill = Colors.Web.crimson } } //sampleEnd }.bindRendererOnNewCanvas() }

Irwin-Hall

The RandomDistribution.irwinHall(n) generates random numbers using an Irwin-Hall distribution with n independent variables.

import io.data2viz.color.* import io.data2viz.geom.* import io.data2viz.math.* import io.data2viz.viz.* import io.data2viz.random.* fun main() { viz { size = size(620, 100) (0..600 step 60).forEach { text { x = 10.0 + it y = 94.0 textContent = "${(it / 60.0).toInt()}" fill = Colors.Web.black textAlign = textAlign(TextHAlign.MIDDLE, TextVAlign.MIDDLE) } } //sampleStart val generator = RandomDistribution.irwinHall(8.0) val groupCount = (0..8000).map { generator() } .groupingBy { (it * 60).toInt() } .eachCount() groupCount.forEach { valueCount -> rect { y = 85.0 - valueCount.value x = 10.0 + valueCount.key size = size(1, valueCount.value) fill = Colors.Web.crimson } } //sampleEnd }.bindRendererOnNewCanvas() }

Bates

The RandomDistribution.bates(n) generates random numbers using a Bates distribution with n independent variables (1.0 by default).

import io.data2viz.color.* import io.data2viz.geom.* import io.data2viz.math.* import io.data2viz.viz.* import io.data2viz.random.* fun main() { viz { size = size(620, 100) (0..600 step 60).forEach { text { x = 10.0 + it y = 94.0 textContent = "${(it / 6.0).toInt() / 100.0}" fill = Colors.Web.black textAlign = textAlign(TextHAlign.MIDDLE, TextVAlign.MIDDLE) } } //sampleStart val generator = RandomDistribution.bates(10.0) val groupCount = (0..8000).map { generator() } .groupingBy { (it * 600).toInt() } .eachCount() groupCount.forEach { valueCount -> rect { y = 85.0 - valueCount.value x = 10.0 + valueCount.key size = size(1, valueCount.value) fill = Colors.Web.crimson } } //sampleEnd }.bindRendererOnNewCanvas() }