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How to use calculateStandardDeviation method of io.kotest.matchers.stats.matchers class

Best Kotest code snippet using io.kotest.matchers.stats.matchers.calculateStandardDeviation

matchers.kt

Source:matchers.kt

...307      sumOfSquaredDifferences += (BigDecimal(elem.toString()) - mean).pow(2)308   }309   return sumOfSquaredDifferences.divide(BigDecimal(collection.size), defaultMathContext)310}311private fun <T : Number> calculateStandardDeviation(collection: Collection<T>): BigDecimal {312   val variance = calculateVariance(collection)313   val two = BigDecimal(2)314   var x0 = BigDecimal.ZERO315   var x1 = BigDecimal(sqrt(variance.toDouble()))316   while (x0 != x1) {317      x0 = x1318      x1 = variance.divide(x0, defaultMathContext)319      x1 = x1.add(x0)320      x1 = x1.divide(two, defaultMathContext)321   }322   return x1323}324private fun <T : Number> testMean(collection: Collection<T>, expectedValue: BigDecimal, precision: Int): MatcherResult {325   val expected = expectedValue.stripTrailingZeros()326   val actual = if (collection.isEmpty()) BigDecimal.ZERO else calculateMean(collection).round(precision)327   return MatcherResult(328      expected.compareTo(actual) == 0,329      { "Collection should have mean $expected but was $actual" },330      {331         "Collection should not have mean $expected but was $actual"332      })333}334private fun <T : Number> testVariance(335   collection: Collection<T>,336   expectedValue: BigDecimal,337   precision: Int338): MatcherResult {339   val expected = expectedValue.stripTrailingZeros()340   val actual = if (collection.isEmpty()) BigDecimal.ZERO else calculateVariance(collection).round(precision)341   return MatcherResult(342      expected.compareTo(actual) == 0,343      { "Collection should have variance $expected but was $actual" },344      {345         "Collection should not have variance $expected but was $actual"346      })347}348private fun <T : Number> testStandardDeviation(349   collection: Collection<T>,350   expectedValue: BigDecimal,351   precision: Int352): MatcherResult {353   val expected = expectedValue.stripTrailingZeros()354   val actual = if (collection.isEmpty()) BigDecimal.ZERO else calculateStandardDeviation(collection).round(precision)355   return MatcherResult(356      expected.compareTo(actual) == 0,357      { "Collection should have standard deviation $expected but was $actual" },358      {359         "Collection should not have standard deviation $expected but was $actual"360      })361}362fun <T : Number> haveMean(expectedValue: BigDecimal, precision: Int = 4) = object :363   Matcher<Collection<T>> {364   override fun test(value: Collection<T>): MatcherResult = testMean(value, expectedValue, precision)365}366fun <T : Number> haveMean(expectedValue: Double, precision: Int = 4) = object : Matcher<Collection<T>> {367   override fun test(value: Collection<T>): MatcherResult = testMean(value, expectedValue.toBigDecimal(), precision)368}...

calculateStandardDeviation

Using AI Code Generation

1val  list  =  listOf ( 1 ,  2 ,  3 ,  4 ,  5 ,  6 ,  7 ,  8 ,  9 ,  10 )2list . should ( haveStandardDeviation ( 2.8722813232690143 ))3list . should ( haveStandardDeviation ( 3.0276503540974917 ,  0.0000001 ))4val  list  =  listOf ( 1 ,  2 ,  3 ,  4 ,  5 ,  6 ,  7 ,  8 ,  9 ,  10 )5list . should ( haveVariance ( 8.25 ))6list . should ( haveVariance ( 9.166666666666666 ,  0.0000001 ))7val  list  =  listOf ( 1 ,  2 ,  3 ,  4 ,  5 ,  6 ,  7 ,  8 ,  9 ,  10 )8list . should ( haveZScore ( 0.0 ,  0.0 ))9list . should ( haveZScore ( 0.0 ,  0.0 ,  0.0000001 ))10val  list  =  listOf ( 1 ,  2 ,  3 ,  4 ,  5 ,  6 ,  7 ,  8 ,  9 ,  10 )11list . should ( haveZScore ( 0.0 ,  0.0 ))12list . should ( haveZScore ( 0.0 ,  0.0 ,  0.0000001 ))13val  list  =  listOf ( 1 ,  2 ,  3 ,  4 ,  5 ,  6 ,  7 ,  8 ,  9 ,  10 )14list . should ( haveZScore

calculateStandardDeviation

Using AI Code Generation

1val data = listOf(1, 2, 3, 4, 5, 6, 7, 8, 9)2data.calculateStandardDeviation() shouldBe 2.5819888974716113val data = listOf(1, 2, 3, 4, 5, 6, 7, 8, 9)4data.calculateStandardDeviation() shouldBe 2.5819888974716115val data = listOf(1, 2, 3, 4, 5, 6, 7, 8, 9)6data.calculateStandardDeviation() shouldBe 2.5819888974716117val data = listOf(1, 2, 3, 4, 5, 6, 7, 8, 9)8data.calculateStandardDeviation() shouldBe 2.5819888974716119val data = listOf(1, 2, 3, 4, 5, 6, 7, 8, 9)10data.calculateStandardDeviation() shouldBe 2.58198889747161111val data = listOf(1, 2, 3, 4, 5, 6, 7, 8, 9)12data.calculateStandardDeviation() shouldBe 2.58198889747161113val data = listOf(1, 2, 3, 4, 5, 6, 7, 8, 9)14data.calculateStandardDeviation() shouldBe 2.58198889747161115val data = listOf(1, 2, 3, 4, 5, 6,

calculateStandardDeviation

Using AI Code Generation

1calculateStandardDeviation(listOf(1, 2, 3, 4, 5)) shouldBe 1.02calculateStandardDeviation(listOf(1, 2, 3, 4, 5)) shouldBe 1.03calculateStandardDeviation(listOf(1, 2, 3, 4, 5)) shouldBe 1.04calculateStandardDeviation(listOf(1, 2, 3, 4, 5)) shouldBe 1.05calculateStandardDeviation(listOf(1, 2, 3, 4, 5)) shouldBe 1.06calculateStandardDeviation(listOf(1, 2, 3, 4, 5)) shouldBe 1.07calculateStandardDeviation(listOf(1, 2, 3, 4, 5)) shouldBe 1.08calculateStandardDeviation(listOf(1, 2, 3, 4, 5)) shouldBe 1.09calculateStandardDeviation(listOf(1, 2, 3, 4, 5)) shouldBe 1.010calculateStandardDeviation(listOf(1, 2, 3, 4, 5)) shouldBe 1.011calculateStandardDeviation(listOf(1, 2, 3, 4,

calculateStandardDeviation

Using AI Code Generation

1import io.kotest.matchers.shouldBe2import io.kotest.matchers.stats.matchers.*3val numbers = listOf(1, 2, 3, 4, 5)4numbers.calculateStandardDeviation() shouldBe 1.41421356237309515import io.kotest.matchers.shouldBe6import io.kotest.matchers.stats.matchers.*7val numbers = listOf(1, 2, 3, 4, 5)8numbers.calculateVariance() shouldBe 2.09import io.kotest.matchers.shouldBe10import io.kotest.matchers.stats.matchers.*11val numbers = listOf(1, 2, 3, 4, 5)12numbers.calculateZScore(2) shouldBe 0.707106781186547513import io.kotest.matchers.shouldBe14import io.kotest.matchers.stats.matchers.*15val numbers = listOf(1, 2, 3, 4, 5)16numbers.calculateZScore(2, 3) shouldBe 0.577350269189625817import io.kotest.matchers.shouldBe18import io.kotest.matchers.stats.matchers.*19val numbers = listOf(1, 2, 3, 4, 5)20numbers.calculateChiSquare(listOf(1, 2, 3, 4, 5)) shouldBe 0.021import io.kotest.matchers.shouldBe22import io.kotest.matchers.stats.matchers.*23val numbers = listOf(1, 2, 3, 4, 5)24numbers.calculatePercentile(0.5) shouldBe 3.025import io.kotest.matchers.shouldBe26import io.kotest.matchers.stats.matchers.*27val numbers = listOf(1,

calculateStandardDeviation

Using AI Code Generation

1val standardDeviation = calculateStandardDeviation(listOf(1, 2, 3, 4, 5))2standardDeviation.shouldBe(1.4142135623730951)3val standardDeviation = calculateStandardDeviation(listOf(1, 2, 3, 4, 5))4standardDeviation.shouldBe(1.4142135623730951)5val standardDeviation = calculateStandardDeviation(listOf(1, 2, 3, 4, 5))6standardDeviation.shouldBe(1.4142135623730951)7val standardDeviation = calculateStandardDeviation(listOf(1, 2, 3, 4, 5))8standardDeviation.shouldBe(1.4142135623730951)9val standardDeviation = calculateStandardDeviation(listOf(1, 2, 3, 4, 5))10standardDeviation.shouldBe(1.4142135623730951)11val standardDeviation = calculateStandardDeviation(listOf(1, 2, 3, 4, 5))12standardDeviation.shouldBe(1.4142135623730951)13val standardDeviation = calculateStandardDeviation(listOf(1, 2, 3, 4, 5))14standardDeviation.shouldBe(1.4142135623730951)15val standardDeviation = calculateStandardDeviation(listOf(1, 2, 3, 4, 5))16standardDeviation.shouldBe(1.4142135623730951)

calculateStandardDeviation

Using AI Code Generation

1val standardDeviation = calculateStandardDeviation(listOf(1, 2, 3, 4, 5))2assertThat(standardDeviation).isCloseTo(1.58, 0.01)3val standardDeviation = calculateStandardDeviation(listOf(1, 2, 3, 4, 5))4assertThat(standardDeviation).isCloseTo(1.58, 0.01)5val standardDeviation = calculateStandardDeviation(listOf(1, 2, 3, 4, 5))6assertThat(standardDeviation).isCloseTo(1.58, 0.01)7val standardDeviation = calculateStandardDeviation(listOf(1, 2, 3, 4, 5))8assertThat(standardDeviation).isCloseTo(1.58, 0.01)9val standardDeviation = calculateStandardDeviation(listOf(1, 2, 3, 4, 5))10assertThat(standardDeviation).isCloseTo(1.58, 0.01)11val standardDeviation = calculateStandardDeviation(listOf(1, 2, 3, 4, 5))12assertThat(standardDeviation).isCloseTo(1.58, 0.01)13val standardDeviation = calculateStandardDeviation(listOf(1, 2, 3, 4, 5))14assertThat(standardDeviation).isCloseTo(1.58, 0.01)15val standardDeviation = calculateStandardDeviation(listOf(1, 2, 3, 4, 5))16assertThat(

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