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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

...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}...

testMean

Using AI Code Generation

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

testMean

Using AI Code Generation

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

testMean

Using AI Code Generation

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

testMean

Using AI Code Generation

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)

testMean

Using AI Code Generation

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}

testMean

Using AI Code Generation

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)

testMean

Using AI Code Generation

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,

testMean

Using AI Code Generation

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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