Github user chiwanpark commented on a diff in the pull request:
https://github.com/apache/flink/pull/861#discussion_r37137811
--- Diff:
flink-staging/flink-ml/src/main/scala/org/apache/flink/ml/statistics/FieldStats.scala
---
@@ -0,0 +1,119 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.flink.ml.statistics
+
+import org.apache.flink.ml.statistics.FieldType._
+
+import scala.collection.mutable
+
+/** Class to represent Field statistics.
+ *
+ * =Parameters=
+ * -[[fieldType]]:
+ * Type of this field, [[DISCRETE]] or [[CONTINUOUS]]
+ *
+ * For [[DISCRETE]] fields, [[entropy]], [[gini]] and [[categoryCounts]]
are provided.
+ * For [[CONTINUOUS]] fields, [[min]], [[max]], [[mean]] and [[variance]]
are provided.
+ *
+ */
+class FieldStats(val fieldType: FieldType) extends Serializable {
+ // field parameters
+ private [statistics] var _min: Double = _
+ private [statistics] var _max: Double = _
+ private [statistics] var _mean: Double = _
+ private [statistics] var _variance: Double = _
+ private [statistics] var _counts: mutable.HashMap[Double,Int] = _
+
+ //-------------------- Access methods ----------------------------//
+ def min: Double = {
+ exception(DISCRETE)
+ _min
+ }
+
+ def max: Double = {
+ exception(DISCRETE)
+ _max
+ }
+
+ def mean: Double = {
+ exception(DISCRETE)
+ _mean
+ }
+
+ def variance: Double = {
+ exception(DISCRETE)
+ _variance
+ }
+
+ def categoryCounts: mutable.HashMap[Double,Int] = {
+ exception(CONTINUOUS)
+ _counts
+ }
+
+ /**
+ * Returns the entropy value for this [[DISCRETE]] field.
+ */
+ def entropy: Double = {
+ exception(CONTINUOUS)
+ val total: Double = _counts.valuesIterator.sum
+ 3.322 * _counts.iterator.map(x => - (x._2 / total) * Math.log10(x._2 /
total)).sum
+ }
+
+ /**
+ * Returns the Gini impurity for this [[DISCRETE]] field.
+ */
+ def gini: Double = {
+ exception(CONTINUOUS)
+ val total: Double = _counts.valuesIterator.sum
+ 1 - _counts.iterator.map(x => (x._2 * x._2)).sum / (total * total)
+ }
+
+ //------------------ Setter methods ------------------//
+ private [statistics] def setContinuousParameters(
+ min: Double,
+ max: Double,
+ mean: Double,
+ variance: Double)
+ : Unit = {
+ exception(DISCRETE)
+ _min = min
+ _max = max
+ _mean = mean
+ _variance = variance
+ }
+
+ private [statistics] def setDiscreteParameters(counts:
mutable.HashMap[Double,Int]): Unit = {
+ exception(CONTINUOUS)
+ _counts = counts
+ }
+
+ private def exception(checkFor: FieldType) = {
+ if(fieldType == checkFor){
+ throw new RuntimeException("Invalid access of data. Check field
types.")
+ }
+ }
--- End diff --
Maybe If we check `FieldType` in each method (`min`, `max`, `mean`, ...,
`gini`) with `Predef.assume` method, the user can understand what is the
problem more properly. For example, when the user call `gini` method for
continuous histogram, we can throw exception with detailed message such as
"Gini impurity for continuous histogram is not supported.".
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