Github user srowen commented on a diff in the pull request:
https://github.com/apache/spark/pull/11858#discussion_r56839971
--- Diff:
mllib/src/test/scala/org/apache/spark/mllib/classification/NaiveBayesSuite.scala
---
@@ -103,17 +104,26 @@ class NaiveBayesSuite extends SparkFunSuite with
MLlibTestSparkContext {
piData: Array[Double],
thetaData: Array[Array[Double]],
model: NaiveBayesModel): Unit = {
- def closeFit(d1: Double, d2: Double, precision: Double): Boolean = {
- (d1 - d2).abs <= precision
- }
- val modelIndex = (0 until piData.length).zip(model.labels.map(_.toInt))
- for (i <- modelIndex) {
- assert(closeFit(math.exp(piData(i._2)), math.exp(model.pi(i._1)),
0.05))
- }
- for (i <- modelIndex) {
- for (j <- 0 until thetaData(i._2).length) {
- assert(closeFit(math.exp(thetaData(i._2)(j)),
math.exp(model.theta(i._1)(j)), 0.05))
+ val modelIndex = piData.indices.zip(model.labels.map(_.toInt))
+ try {
+ for (i <- modelIndex) {
+ assert(math.exp(piData(i._2)) ~== math.exp(model.pi(i._1)) absTol
0.05)
+ }
+ for (i <- modelIndex) {
+ for (j <- thetaData(i._2).indices) {
+ assert(math.exp(thetaData(i._2)(j)) ~==
math.exp(model.theta(i._1)(j)) absTol 0.05)
+ }
}
+ } catch {
+ case e: TestFailedException =>
+ def arr2str(a: Array[Double]): String = a.mkString("[", ", ", "]")
+ val msg = "\nvalidateModelFit:\n" +
--- End diff --
You could also make a function that generates the error message you want,
and pass that as an arg to the asserts. It's more straightforward but not sure
it's simpler, so whatever you like here.
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