Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/11553#discussion_r57414488
--- Diff:
mllib/src/test/scala/org/apache/spark/ml/feature/QuantileDiscretizerSuite.scala
---
@@ -17,72 +17,25 @@
package org.apache.spark.ml.feature
-import org.apache.spark.{SparkContext, SparkFunSuite}
-import org.apache.spark.ml.attribute.{Attribute, NominalAttribute}
+import org.apache.spark.SparkFunSuite
import org.apache.spark.ml.util.DefaultReadWriteTest
import org.apache.spark.mllib.util.MLlibTestSparkContext
-import org.apache.spark.sql.{Row, SQLContext}
+import org.apache.spark.sql.SQLContext
class QuantileDiscretizerSuite
extends SparkFunSuite with MLlibTestSparkContext with
DefaultReadWriteTest {
- import org.apache.spark.ml.feature.QuantileDiscretizerSuite._
-
- test("Test quantile discretizer") {
- checkDiscretizedData(sc,
- Array[Double](1, 2, 3, 3, 3, 3, 3, 3, 3),
- 10,
- Array[Double](1, 2, 3, 3, 3, 3, 3, 3, 3),
- Array("-Infinity, 1.0", "1.0, 2.0", "2.0, 3.0", "3.0, Infinity"))
-
- checkDiscretizedData(sc,
- Array[Double](1, 2, 3, 3, 3, 3, 3, 3, 3),
- 4,
- Array[Double](1, 2, 3, 3, 3, 3, 3, 3, 3),
- Array("-Infinity, 1.0", "1.0, 2.0", "2.0, 3.0", "3.0, Infinity"))
-
- checkDiscretizedData(sc,
- Array[Double](1, 2, 3, 3, 3, 3, 3, 3, 3),
- 3,
- Array[Double](0, 1, 2, 2, 2, 2, 2, 2, 2),
- Array("-Infinity, 2.0", "2.0, 3.0", "3.0, Infinity"))
-
- checkDiscretizedData(sc,
- Array[Double](1, 2, 3, 3, 3, 3, 3, 3, 3),
- 2,
- Array[Double](0, 1, 1, 1, 1, 1, 1, 1, 1),
- Array("-Infinity, 2.0", "2.0, Infinity"))
-
- }
-
- test("Test getting splits") {
- val splitTestPoints = Array(
- Array[Double]() -> Array(Double.NegativeInfinity, 0,
Double.PositiveInfinity),
- Array(Double.NegativeInfinity) -> Array(Double.NegativeInfinity, 0,
Double.PositiveInfinity),
- Array(Double.PositiveInfinity) -> Array(Double.NegativeInfinity, 0,
Double.PositiveInfinity),
- Array(Double.NegativeInfinity, Double.PositiveInfinity)
- -> Array(Double.NegativeInfinity, 0, Double.PositiveInfinity),
- Array(0.0) -> Array(Double.NegativeInfinity, 0,
Double.PositiveInfinity),
- Array(1.0) -> Array(Double.NegativeInfinity, 1,
Double.PositiveInfinity),
- Array(0.0, 1.0) -> Array(Double.NegativeInfinity, 0, 1,
Double.PositiveInfinity)
- )
- for ((ori, res) <- splitTestPoints) {
- assert(QuantileDiscretizer.getSplits(ori) === res, "Returned splits
are invalid.")
- }
- }
-
- test("Test splits on dataset larger than minSamplesRequired") {
+ test("Test observed number of buckets matches required number of
buckets") {
val sqlCtx = SQLContext.getOrCreate(sc)
import sqlCtx.implicits._
- val datasetSize = QuantileDiscretizer.minSamplesRequired + 1
+ val datasetSize = 100000
val numBuckets = 5
- val df = sc.parallelize((1.0 to datasetSize by
1.0).map(Tuple1.apply)).toDF("input")
+ val df = sc.parallelize(1.0 to datasetSize by
1.0).map(Tuple1.apply).toDF("input")
--- End diff --
minor: `by 1.0` is unnecessary
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