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

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

matchers.kt

Source:matchers.kt Github

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...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}369fun <T : Number> haveVariance(expectedValue: BigDecimal, precision: Int) = object : Matcher<Collection<T>> {370 override fun test(value: Collection<T>): MatcherResult = testVariance(value, expectedValue, precision)371}372fun <T : Number> haveVariance(expectedValue: Double, precision: Int) = object : Matcher<Collection<T>> {373 override fun test(value: Collection<T>): MatcherResult = testVariance(value, expectedValue.toBigDecimal(), precision)374}375fun <T : Number> haveStandardDeviation(expectedValue: BigDecimal, precision: Int) = object : Matcher<Collection<T>> {376 override fun test(value: Collection<T>): MatcherResult = testStandardDeviation(value, expectedValue, precision)377}378fun <T : Number> haveStandardDeviation(expectedValue: Double, precision: Int) = object : Matcher<Collection<T>> {379 override fun test(value: Collection<T>): MatcherResult = testStandardDeviation(value, expectedValue.toBigDecimal(), precision)380}...

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testMean

Using AI Code Generation

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1 import io.kotest.matchers.shouldBe2 import io.kotest.matchers.shouldNotBe3 import io.kotest.matchers.shouldNotThrow4 import io.kotest.matchers.shouldThrow5 import io.kotest.matchers.should6 import io.kotest.matchers.shouldNot7 import io.kotest.matchers.doubles.beGreaterThan8 import io.kotest.matchers.doubles.beGreaterThanOrEqualTo9 import io.kotest.matchers.doubles.beLessThan10 import io.kotest.matchers.doubles.beLessThanOrEqualTo11 import io.kotest.matchers.doubles.beBetween12 import io.kotest.matchers.doubles.beZero13 import io.kotest.matchers.doubles.beNegative14 import io.kotest.matchers.doubles.bePositive15 import io.kotest.matchers.doubles.beNaN16 import io.kotest.matchers.doubles.beInfinite17 import io.kotest.matchers.doubles.beFinite18 import io.kotest.matchers.doubles.beCloseTo19 import io.kotest.matchers.doubles.beExactly20 import io.kotest.matchers.doubles.beExactlyOne21 import io.kotest.matchers.doubles.beOne22 import io.kotest.matchers.doubles.beExactlyZero23 import io.kotest.matchers.doubles.beZero24 import io.kotest.matchers.doubles.bePositiveInfinity25 import io.kotest.matchers.doubles.beNegativeInfinity26 import io.kotest.matchers.doubles.beNegativeOrZero27 import io.kotest.matchers.doubles.bePositiveOrZero28 import io.kotest.matchers.doubles.beNonNegative29 import io.kotest.matchers.doubles.beNonPositive30 import io.kotest.matchers.doubles.beWithin31 import io.kotest.matchers.doubles.beWithinPercent32 import io.kotest.matchers.doubles.beWithinTolerance33 import io.kotest.matchers.doubles.shouldBeGreaterThan34 import io.kotest.matchers.doubles.shouldBeGreaterThanOrEqualTo35 import io.kotest.matchers.doubles.shouldBeLessThan36 import io.kotest.matchers.doubles.shouldBeLessThanOrEqualTo37 import io.kotest.matchers.doubles.shouldBeBetween38 import

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testMean

Using AI Code Generation

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1testMean ( 1 , 2 , 3 , 4 ) shouldBe 2.52testMedian ( 1 , 2 , 3 , 4 ) shouldBe 2.53testMode ( 1 , 2 , 3 , 4 ) shouldBe 14testRange ( 1 , 2 , 3 , 4 ) shouldBe 1..45testVariance ( 1 , 2 , 3 , 4 ) shouldBe 1.256testStandardDeviation ( 1 , 2 , 3 , 4 ) shouldBe 1.1180339887498957testRange ( 1 , 2 , 3 , 4 ) shouldBe 1..48testQuartiles ( 1 , 2 , 3 , 4 ) shouldBe 1.25..3.759testInterquartileRange ( 1 , 2 , 3 , 4 ) shouldBe 2.510testMeanDeviation ( 1 , 2 , 3 , 4 ) shouldBe 0.7511testSkewness ( 1 , 2 , 3 , 4 ) shouldBe 0.012testKurtosis ( 1 , 2 , 3 , 4 ) shouldBe -1.2

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testMean

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1testMean ( 1.0 , 2.0 , 3.0 , 4.0 ) shouldBe 2.52testStdDev ( 1.0 , 2.0 , 3.0 , 4.0 ) shouldBe 1.29099444873580563testVariance ( 1.0 , 2.0 , 3.0 , 4.0 ) shouldBe 1.66666666666666674testMedian ( 1.0 , 2.0 , 3.0 , 4.0 ) shouldBe 2.55testMode ( 1.0 , 2.0 , 3.0 , 4.0 ) shouldBe 1.06testRange ( 1.0 , 2.0 , 3.0 , 4.0 ) shouldBe 3.07testInterQuartileRange ( 1.0 , 2.0 , 3.0 , 4.0 ) shouldBe 1.08testQ1 ( 1.0 , 2.0 , 3.0 , 4.0 ) shouldBe 1.759testQ3 ( 1.0 , 2.0 , 3.0 , 4.0 ) shouldBe 3.2510testSkewness ( 1.0 , 2.0 , 3.0 , 4.0 ) shouldBe 0.0

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testMean

Using AI Code Generation

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1testMean(1.0, 2.0, 3.0)2testMean(1.0, 2.0, 3.0)3testMean(1.0, 2.0, 3.0)4testMean(1.0, 2.0, 3.0)5testMean(1.0, 2.0, 3.0)6testMean(1.0, 2.0, 3.0)7testMean(1.0, 2.0, 3.0)8testMean(1.0, 2.0, 3.0)9testMean(1.0, 2.0, 3.0)10testMean(1.0, 2.0, 3.0)11testMean(1.0, 2.0, 3.0)12testMean(1.0, 2.0, 3.0)13testMean(1.0, 2.0, 3.0)14testMean(1.0, 2.0, 3.0)

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testMean

Using AI Code Generation

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1test("testMean") {2}3test("testMedian") {4}5test("testMode") {6}7test("testRange") {8}9test("testVariance") {10}11test("testStandardDeviation") {12}13test("testCorrelation") {14}15test("testCovariance") {16}17test("testPopulationCorrelation") {18}19test("testPopulationCovariance") {20}21test("testSampleCorrelation") {22}23test("testSampleCovariance") {24}25test("testPopulationStandardDeviation") {26}27test("testSampleStandardDeviation") {28}

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testMean

Using AI Code Generation

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1val mean = testMean(1.0, 2.0, 3.0)2val standardDeviation = testStandardDeviation(1.0, 2.0, 3.0)3val variance = testVariance(1.0, 2.0, 3.0)4val median = testMedian(1.0, 2.0, 3.0)5val mode = testMode(1.0, 2.0, 3.0)6val range = testRange(1.0, 2.0, 3.0)7val interquartileRange = testInterquartileRange(1.0, 2.0, 3.0)8val skewness = testSkewness(1.0, 2.0, 3.0)9val kurtosis = testKurtosis(1.0, 2.0, 3.0)

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testMean

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1val data = listOf(1, 2, 3, 4, 5)2data should testMean(mean)3val data = listOf(1, 2, 3, 4, 5)4data should testMedian(median)5val data = listOf(1, 2, 3, 4, 5)6data should testMode(mode)7val data = listOf(1, 2, 3, 4, 5)8data should testVariance(variance)9val data = listOf(1, 2, 3, 4, 5)10data should testStandardDeviation(standardDeviation)11val data = listOf(1, 2, 3, 4, 5)12data should testMeanAbsoluteDeviation(meanAbsoluteDeviation)13val data = listOf(1, 2, 3, 4, 5)14data should testMedianAbsoluteDeviation(medianAbsoluteDeviation)15val data = listOf(1, 2, 3, 4, 5)16data should testVarianceOfPopulation(varianceOfPopulation)17val data = listOf(1, 2, 3, 4,

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testMean

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1val result = listOf(1, 2, 3, 4, 5).testMean(3.0)2println(result)3val result = listOf(1, 2, 3, 4, 5).testMedian(3.0)4println(result)5val result = listOf(1, 2, 3, 4, 5).testMode(3.0)6println(result)7val result = listOf(1, 2, 3, 4, 5).testVariance(2.5)8println(result)9val result = listOf(1, 2, 3, 4, 5).testStandardDeviation(1.5811388300841898)10println(result)11val result = listOf(1, 2, 3, 4, 5).testStandardError(0.8944271909999159)12println(result)13val result = listOf(1, 2, 3, 4, 5).testZScore(3.0, 3.0)14println(result)15val result = listOf(1, 2, 3, 4, 5).testCorrelation(listOf(1, 2, 3, 4, 5), 1.0)16println(result)

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