Automated commit of generated code

Author: github-actions[bot]

core/generated-sources/src/main/kotlin/org/jetbrains/kotlinx/dataframe/impl/aggregation/aggregators/inputHandlers/NumberInputHandler.kt

@@ -1,6 +1,5 @@
 package org.jetbrains.kotlinx.dataframe.impl.aggregation.aggregators.inputHandlers
 
-import io.github.oshai.kotlinlogging.KotlinLogging
 import org.jetbrains.kotlinx.dataframe.documentation.UnifyingNumbers
 import org.jetbrains.kotlinx.dataframe.impl.UnifiedNumberTypeOptions
 import org.jetbrains.kotlinx.dataframe.impl.aggregation.aggregators.Aggregator
@@ -22,8 +21,6 @@ import kotlin.reflect.full.isSubtypeOf
 import kotlin.reflect.full.withNullability
 import kotlin.reflect.typeOf
 
-private val logger = KotlinLogging.logger { }
-
 /**
  * Input handler for aggregators that can handle any (mixed) primitive [Number] type of input.
  *
@@ -107,14 +104,6 @@ internal class NumberInputHandler<out Return : Any?> : AggregatorInputHandler<Nu
     override fun calculateValueType(valueTypes: Set<KType>): ValueType {
         val unifiedType = valueTypes.unifiedNumberTypeOrNull(UnifiedNumberTypeOptions.PRIMITIVES_ONLY)
             ?: typeOf<Number>().withNullability(valueTypes.any { it.isMarkedNullable })
-
-        if (unifiedType.isSubtypeOf(typeOf<Double?>()) &&
-            (typeOf<ULong>() in valueTypes || typeOf<Long>() in valueTypes)
-        ) {
-            logger.warn {
-                "Number unification of Long -> Double happened during ${aggregator!!.name} aggregation. Loss of precision may have occurred."
-            }
-        }
         if (!unifiedType.isPrimitiveOrMixedNumber() && !unifiedType.isNothing) {
             throw IllegalArgumentException(
                 "Cannot calculate ${aggregator!!.name} of ${

core/generated-sources/src/main/kotlin/org/jetbrains/kotlinx/dataframe/math/mean.kt

@@ -1,6 +1,5 @@
 package org.jetbrains.kotlinx.dataframe.math
 
-import io.github.oshai.kotlinlogging.KotlinLogging
 import org.jetbrains.kotlinx.dataframe.api.skipNaNDefault
 import org.jetbrains.kotlinx.dataframe.impl.aggregation.aggregators.CalculateReturnType
 import org.jetbrains.kotlinx.dataframe.impl.nothingType
@@ -10,8 +9,6 @@ import java.math.BigInteger
 import kotlin.reflect.KType
 import kotlin.reflect.typeOf
 
-private val logger = KotlinLogging.logger { }
-
 @Suppress("UNCHECKED_CAST")
 internal fun <T : Number> Sequence<T>.mean(type: KType, skipNaN: Boolean): Double {
     if (type.isMarkedNullable) {
@@ -29,7 +26,6 @@ internal fun <T : Number> Sequence<T>.mean(type: KType, skipNaN: Boolean): Doubl
         typeOf<Byte>() -> (this as Sequence<Byte>).map { it.toDouble() }.mean(false)
 
         typeOf<Long>() -> {
-            logger.warn { "Converting Longs to Doubles to calculate the mean, loss of precision may occur." }
             (this as Sequence<Long>).map { it.toDouble() }.mean(false)
         }
 

core/generated-sources/src/main/kotlin/org/jetbrains/kotlinx/dataframe/math/median.kt

@@ -1,6 +1,5 @@
 package org.jetbrains.kotlinx.dataframe.math
 
-import io.github.oshai.kotlinlogging.KotlinLogging
 import org.jetbrains.kotlinx.dataframe.api.isNaN
 import org.jetbrains.kotlinx.dataframe.impl.aggregation.aggregators.CalculateReturnType
 import org.jetbrains.kotlinx.dataframe.impl.canBeNaN
@@ -15,8 +14,6 @@ import kotlin.reflect.KType
 import kotlin.reflect.full.withNullability
 import kotlin.reflect.typeOf
 
-private val logger = KotlinLogging.logger { }
-
 /**
  * Returns the median of the comparable input:
  * - `null` if empty
@@ -48,8 +45,7 @@ internal fun <T : Comparable<T>> Sequence<T>.medianOrNull(type: KType, skipNaN:
                 "Cannot calculate the median for big numbers in DataFrame. Only primitive numbers are supported.",
             )
 
-        type == typeOf<Long>() ->
-            logger.warn { "Converting Longs to Doubles to calculate the median, loss of precision may occur." }
+        // TODO kdocs: note about loss of precision for Long
     }
 
     val p = 0.5

core/generated-sources/src/main/kotlin/org/jetbrains/kotlinx/dataframe/math/percentile.kt

@@ -1,6 +1,5 @@
 package org.jetbrains.kotlinx.dataframe.math
 
-import io.github.oshai.kotlinlogging.KotlinLogging
 import org.jetbrains.kotlinx.dataframe.api.isNaN
 import org.jetbrains.kotlinx.dataframe.impl.aggregation.aggregators.CalculateReturnType
 import org.jetbrains.kotlinx.dataframe.impl.isIntraComparable
@@ -14,8 +13,6 @@ import kotlin.reflect.KType
 import kotlin.reflect.full.withNullability
 import kotlin.reflect.typeOf
 
-private val logger = KotlinLogging.logger { }
-
 /**
  * Uses [QuantileEstimationMethod.R8] for primitive numbers, else [QuantileEstimationMethod.R3]
  */
@@ -41,8 +38,7 @@ internal fun <T : Comparable<T>> Sequence<T>.percentileOrNull(percentile: Double
                 "Cannot calculate the percentile for big numbers in DataFrame. Only primitive numbers are supported.",
             )
 
-        type == typeOf<Long>() ->
-            logger.warn { "Converting Longs to Doubles to calculate the percentile, loss of precision may occur." }
+        // TODO kdocs: note about loss of precision for Long
     }
 
     // percentile of 25.0 means the 25th 100-quantile, so 25 / 100 = 0.25

core/generated-sources/src/main/kotlin/org/jetbrains/kotlinx/dataframe/math/quantile.kt

@@ -1,6 +1,5 @@
 package org.jetbrains.kotlinx.dataframe.math
 
-import io.github.oshai.kotlinlogging.KotlinLogging
 import org.jetbrains.kotlinx.dataframe.api.isNaN
 import org.jetbrains.kotlinx.dataframe.impl.canBeNaN
 import org.jetbrains.kotlinx.dataframe.impl.isIntraComparable
@@ -16,8 +15,6 @@ import kotlin.reflect.KType
 import kotlin.reflect.full.withNullability
 import kotlin.reflect.typeOf
 
-private val logger = KotlinLogging.logger { }
-
 /**
  * Returns the p-quantile: the k'th q-quantile, where p = k/q.
  *
@@ -60,9 +57,6 @@ internal fun <T : Comparable<T>> Sequence<Any>.quantileOrNull(
             throw IllegalArgumentException(
                 "Cannot calculate the $name for big numbers in DataFrame. Only primitive numbers are supported.",
             )
-
-        type == typeOf<Long>() ->
-            logger.warn { "Converting Longs to Doubles to calculate the $name, loss of precision may occur." }
     }
 
     // propagate NaN to return if they are not to be skipped

core/generated-sources/src/main/kotlin/org/jetbrains/kotlinx/dataframe/math/std.kt

@@ -1,6 +1,5 @@
 package org.jetbrains.kotlinx.dataframe.math
 
-import io.github.oshai.kotlinlogging.KotlinLogging
 import org.jetbrains.kotlinx.dataframe.api.ddofDefault
 import org.jetbrains.kotlinx.dataframe.api.skipNaNDefault
 import org.jetbrains.kotlinx.dataframe.impl.aggregation.aggregators.CalculateReturnType
@@ -12,8 +11,6 @@ import kotlin.math.sqrt
 import kotlin.reflect.KType
 import kotlin.reflect.typeOf
 
-private val logger = KotlinLogging.logger { }
-
 /**
  * Calculates the standard deviation from [this] with optional delta degrees of freedom.
  *
@@ -39,7 +36,6 @@ internal fun <T : Number> Sequence<T?>.std(type: KType, skipNaN: Boolean, ddof:
         typeOf<Byte>() -> (this as Sequence<Byte>).map { it.toDouble() }.std(false, ddof)
 
         typeOf<Long>() -> {
-            logger.warn { "Converting Longs to Doubles to calculate the std, loss of precision may occur." }
             (this as Sequence<Long>).map { it.toDouble() }.std(false, ddof)
         }