Fix #135

plot-builder-portable/src/commonMain/kotlin/jetbrains/datalore/plot/builder/data/DataProcessing.kt

@@ -12,13 +12,15 @@ import jetbrains.datalore.base.gcommon.collect.Iterables
 import jetbrains.datalore.base.gcommon.collect.Ordering.Companion.natural
 import jetbrains.datalore.plot.base.*
 import jetbrains.datalore.plot.base.DataFrame.Builder
+import jetbrains.datalore.plot.base.DataFrame.Builder.Companion.emptyFrame
 import jetbrains.datalore.plot.base.DataFrame.Variable
 import jetbrains.datalore.plot.base.data.DataFrameUtil
 import jetbrains.datalore.plot.base.scale.ScaleUtil
 import jetbrains.datalore.plot.base.stat.Stats
 import jetbrains.datalore.plot.builder.VarBinding
+import jetbrains.datalore.plot.builder.data.GroupUtil.indicesByGroup
 import jetbrains.datalore.plot.common.data.SeriesUtil
-import jetbrains.datalore.plot.common.data.SeriesUtil.allFinineAreEqual
+import jetbrains.datalore.plot.common.data.SeriesUtil.pickAtIndices
 
 object DataProcessing {
 
@@ -46,10 +48,7 @@ object DataProcessing {
  facetXVar: String?, facetYVar: String?, statCtx: StatContext, messageConsumer: Consumer<String>
  ): DataAndGroupingContext {
  if (stat === Stats.IDENTITY) {
- return DataAndGroupingContext(
- Builder.emptyFrame(),
- groupingContext
- )
+ return DataAndGroupingContext(emptyFrame(), groupingContext)
  }
 
  val groups = groupingContext.groupMapper
@@ -59,15 +58,7 @@ object DataProcessing {
 
  // if only one group no need to modify
  if (groups === GroupUtil.SINGLE_GROUP) {
- val sd = applyStat(
- data,
- stat,
- bindings,
- facetXVar,
- facetYVar,
- statCtx,
- messageConsumer
- )
+ val sd = applyStat(data, stat, bindings, facetXVar, facetYVar, statCtx, messageConsumer)
  groupSizeListAfterStat.add(sd.rowCount())
  for (variable in sd.variables()) {
  @Suppress("UNCHECKED_CAST")
@@ -77,15 +68,7 @@ object DataProcessing {
  } else { // add offset to each group
  var lastStatGroupEnd = -1
  for (d in splitByGroup(data, groups)) {
- var sd = applyStat(
- d,
- stat,
- bindings,
- facetXVar,
- facetYVar,
- statCtx,
- messageConsumer
- )
+ var sd = applyStat(d, stat, bindings, facetXVar, facetYVar, statCtx, messageConsumer)
  if (sd.isEmpty) {
  continue
  }
@@ -110,7 +93,7 @@ object DataProcessing {
  } else { // if stat has ..group.. then groupingVar won't be checked, so no need to update
  val groupingVar = groupingContext.optionalGroupingVar
  if (groupingVar != null) {
- val size = sd[sd.variables().iterator().next()].size
+ val size = sd[sd.variables().first()].size
  val v = d[groupingVar][0]
  sd = sd.builder().put(groupingVar, List(size) { v }).build()
  }
@@ -153,23 +136,14 @@ object DataProcessing {
  }
 
  private fun splitByGroup(data: DataFrame, groups: (Int) -> Int): List<DataFrame> {
- val dataSize = data.rowCount()
-
- val result = ArrayList<DataFrame>()
- val indicesByGroup = GroupUtil.indicesByGroup(dataSize, groups)
- for (group in indicesByGroup.keys) {
- val indices = indicesByGroup[group]!!
- val b = Builder()
-
- for (`var` in data.variables()) {
- val serie = data[`var`]
- b.put(`var`, SeriesUtil.pickAtIndices(serie, indices))
+ return indicesByGroup(data.rowCount(), groups).values.map { indices ->
+ data.variables().fold(Builder()) { b, variable ->
+ when (data.isNumeric(variable)) {
+ true -> b.putNumeric(variable, pickAtIndices(data.getNumeric(variable), indices))
+ false -> b.putDiscrete(variable, pickAtIndices(data[variable], indices))
+ }
  }
-
- result.add(b.build())
- }
-
- return result
+ }.map(Builder::build)
  }
 
  /**
@@ -246,22 +220,10 @@ object DataProcessing {
  } else {
  // Do not override series obtained via 'default stat var'
  if (!newInputSeries.containsKey(variable)) {
- val value =
- if (data.isNumeric(variable)) {
- val values = data.getNumeric(variable)
- if (allFinineAreEqual(values)) {
- // ToDo: This is a patch for "is_discrete: a rounding error. #135"
- // (https://github.com/JetBrains/lets-plot/issues/135)
- // Expectations: data.isNumeric(variable) should return False.
- // But it returns True and as a result we get a rounding error
- // when computing `mean` value.
- SeriesUtil.firstFinine(values, 0.0)
- } else {
- SeriesUtil.mean(values, null)
- }
- } else {
- SeriesUtil.firstNotNull(data[variable], null)
- }
+ val value = when (data.isNumeric(variable)) {
+ true -> SeriesUtil.mean(data.getNumeric(variable), defaultValue = null)
+ false -> SeriesUtil.firstNotNull(data[variable], defaultValue = null)
+ }
  val newInputSerie = List(statDataSize) { value }
  newInputSeries[variable] = newInputSerie
  }

plot-common-portable/src/commonMain/kotlin/jetbrains/datalore/plot/common/data/SeriesUtil.kt

@@ -231,29 +231,6 @@ object SeriesUtil {
  return defaultValue
  }
 
- fun firstFinine(list: List<Double?>, defaultValue: Double): Double {
- for (v in list) {
- if (isFinite(v)) {
- return v!!
- }
- }
- return defaultValue
- }
-
- fun allFinineAreEqual(list: List<Double?>): Boolean {
- var firstFinite = Double.NaN
- for (v in list) {
- if (isFinite(v)) {
- if (firstFinite.isNaN()) {
- firstFinite = v!!
- } else if (v != firstFinite) {
- return false
- }
- }
- }
- return !firstFinite.isNaN()
- }
-
  fun mean(values: List<Double?>, defaultValue: Double?): Double? {
  var result = 0.0
  var i = -1.0