http://git-wip-us.apache.org/repos/asf/spark/blob/ff1cfce1/mllib/src/test/scala/org/apache/spark/ml/classification/LogisticRegressionSuite.scala ---------------------------------------------------------------------- diff --git a/mllib/src/test/scala/org/apache/spark/ml/classification/LogisticRegressionSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/classification/LogisticRegressionSuite.scala index 69650eb..a1b4853 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/classification/LogisticRegressionSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/classification/LogisticRegressionSuite.scala @@ -17,18 +17,19 @@ package org.apache.spark.ml.classification +import scala.collection.JavaConverters._ import scala.language.existentials import scala.util.Random +import scala.util.control.Breaks._ import org.apache.spark.SparkFunSuite -import org.apache.spark.ml.feature.Instance +import org.apache.spark.ml.classification.LogisticRegressionSuite._ +import org.apache.spark.ml.feature.{Instance, LabeledPoint} +import org.apache.spark.ml.linalg.{Vector, Vectors} import org.apache.spark.ml.param.ParamsSuite import org.apache.spark.ml.util.{DefaultReadWriteTest, MLTestingUtils} -import org.apache.spark.mllib.classification.LogisticRegressionSuite._ -import org.apache.spark.mllib.linalg.{Vector, Vectors} -import org.apache.spark.mllib.regression.LabeledPoint +import org.apache.spark.ml.util.TestingUtils._ import org.apache.spark.mllib.util.MLlibTestSparkContext -import org.apache.spark.mllib.util.TestingUtils._ import org.apache.spark.sql.{DataFrame, Dataset, Row} import org.apache.spark.sql.functions.lit @@ -967,4 +968,122 @@ object LogisticRegressionSuite { "standardization" -> false, "threshold" -> 0.6 ) + + def generateLogisticInputAsList( + offset: Double, + scale: Double, + nPoints: Int, + seed: Int): java.util.List[LabeledPoint] = { + generateLogisticInput(offset, scale, nPoints, seed).asJava + } + + // Generate input of the form Y = logistic(offset + scale*X) + def generateLogisticInput( + offset: Double, + scale: Double, + nPoints: Int, + seed: Int): Seq[LabeledPoint] = { + val rnd = new Random(seed) + val x1 = Array.fill[Double](nPoints)(rnd.nextGaussian()) + + val y = (0 until nPoints).map { i => + val p = 1.0 / (1.0 + math.exp(-(offset + scale * x1(i)))) + if (rnd.nextDouble() < p) 1.0 else 0.0 + } + + val testData = (0 until nPoints).map(i => LabeledPoint(y(i), Vectors.dense(Array(x1(i))))) + testData + } + + /** + * Generates `k` classes multinomial synthetic logistic input in `n` dimensional space given the + * model weights and mean/variance of the features. The synthetic data will be drawn from + * the probability distribution constructed by weights using the following formula. + * + * P(y = 0 | x) = 1 / norm + * P(y = 1 | x) = exp(x * w_1) / norm + * P(y = 2 | x) = exp(x * w_2) / norm + * ... + * P(y = k-1 | x) = exp(x * w_{k-1}) / norm + * where norm = 1 + exp(x * w_1) + exp(x * w_2) + ... + exp(x * w_{k-1}) + * + * @param weights matrix is flatten into a vector; as a result, the dimension of weights vector + * will be (k - 1) * (n + 1) if `addIntercept == true`, and + * if `addIntercept != true`, the dimension will be (k - 1) * n. + * @param xMean the mean of the generated features. Lots of time, if the features are not properly + * standardized, the algorithm with poor implementation will have difficulty + * to converge. + * @param xVariance the variance of the generated features. + * @param addIntercept whether to add intercept. + * @param nPoints the number of instance of generated data. + * @param seed the seed for random generator. For consistent testing result, it will be fixed. + */ + def generateMultinomialLogisticInput( + weights: Array[Double], + xMean: Array[Double], + xVariance: Array[Double], + addIntercept: Boolean, + nPoints: Int, + seed: Int): Seq[LabeledPoint] = { + val rnd = new Random(seed) + + val xDim = xMean.length + val xWithInterceptsDim = if (addIntercept) xDim + 1 else xDim + val nClasses = weights.length / xWithInterceptsDim + 1 + + val x = Array.fill[Vector](nPoints)(Vectors.dense(Array.fill[Double](xDim)(rnd.nextGaussian()))) + + x.foreach { vector => + // This doesn't work if `vector` is a sparse vector. + val vectorArray = vector.toArray + var i = 0 + val len = vectorArray.length + while (i < len) { + vectorArray(i) = vectorArray(i) * math.sqrt(xVariance(i)) + xMean(i) + i += 1 + } + } + + val y = (0 until nPoints).map { idx => + val xArray = x(idx).toArray + val margins = Array.ofDim[Double](nClasses) + val probs = Array.ofDim[Double](nClasses) + + for (i <- 0 until nClasses - 1) { + for (j <- 0 until xDim) margins(i + 1) += weights(i * xWithInterceptsDim + j) * xArray(j) + if (addIntercept) margins(i + 1) += weights((i + 1) * xWithInterceptsDim - 1) + } + // Preventing the overflow when we compute the probability + val maxMargin = margins.max + if (maxMargin > 0) for (i <- 0 until nClasses) margins(i) -= maxMargin + + // Computing the probabilities for each class from the margins. + val norm = { + var temp = 0.0 + for (i <- 0 until nClasses) { + probs(i) = math.exp(margins(i)) + temp += probs(i) + } + temp + } + for (i <- 0 until nClasses) probs(i) /= norm + + // Compute the cumulative probability so we can generate a random number and assign a label. + for (i <- 1 until nClasses) probs(i) += probs(i - 1) + val p = rnd.nextDouble() + var y = 0 + breakable { + for (i <- 0 until nClasses) { + if (p < probs(i)) { + y = i + break + } + } + } + y + } + + val testData = (0 until nPoints).map(i => LabeledPoint(y(i), x(i))) + testData + } }
http://git-wip-us.apache.org/repos/asf/spark/blob/ff1cfce1/mllib/src/test/scala/org/apache/spark/ml/classification/MultilayerPerceptronClassifierSuite.scala ---------------------------------------------------------------------- diff --git a/mllib/src/test/scala/org/apache/spark/ml/classification/MultilayerPerceptronClassifierSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/classification/MultilayerPerceptronClassifierSuite.scala index d5282e0..85f325f 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/classification/MultilayerPerceptronClassifierSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/classification/MultilayerPerceptronClassifierSuite.scala @@ -18,14 +18,16 @@ package org.apache.spark.ml.classification import org.apache.spark.SparkFunSuite +import org.apache.spark.ml.classification.LogisticRegressionSuite._ +import org.apache.spark.ml.linalg.{Vector, Vectors} import org.apache.spark.ml.util.DefaultReadWriteTest import org.apache.spark.ml.util.MLTestingUtils -import org.apache.spark.mllib.classification.LogisticRegressionSuite._ +import org.apache.spark.ml.util.TestingUtils._ import org.apache.spark.mllib.classification.LogisticRegressionWithLBFGS import org.apache.spark.mllib.evaluation.MulticlassMetrics -import org.apache.spark.mllib.linalg.{Vector, Vectors} +import org.apache.spark.mllib.linalg.{Vectors => OldVectors} +import org.apache.spark.mllib.regression.{LabeledPoint => OldLabeledPoint} import org.apache.spark.mllib.util.MLlibTestSparkContext -import org.apache.spark.mllib.util.TestingUtils._ import org.apache.spark.sql.{Dataset, Row} class MultilayerPerceptronClassifierSuite @@ -134,12 +136,13 @@ class MultilayerPerceptronClassifierSuite .setNumClasses(numClasses) lr.optimizer.setRegParam(0.0) .setNumIterations(numIterations) - val lrModel = lr.run(rdd) - val lrPredictionAndLabels = lrModel.predict(rdd.map(_.features)).zip(rdd.map(_.label)) + val lrModel = lr.run(rdd.map(OldLabeledPoint.fromML)) + val lrPredictionAndLabels = + lrModel.predict(rdd.map(p => OldVectors.fromML(p.features))).zip(rdd.map(_.label)) // MLP's predictions should not differ a lot from LR's. val lrMetrics = new MulticlassMetrics(lrPredictionAndLabels) val mlpMetrics = new MulticlassMetrics(mlpPredictionAndLabels) - assert(mlpMetrics.confusionMatrix ~== lrMetrics.confusionMatrix absTol 100) + assert(mlpMetrics.confusionMatrix.asML ~== lrMetrics.confusionMatrix.asML absTol 100) } test("read/write: MultilayerPerceptronClassifier") { http://git-wip-us.apache.org/repos/asf/spark/blob/ff1cfce1/mllib/src/test/scala/org/apache/spark/ml/classification/NaiveBayesSuite.scala ---------------------------------------------------------------------- diff --git a/mllib/src/test/scala/org/apache/spark/ml/classification/NaiveBayesSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/classification/NaiveBayesSuite.scala index 2a05c44..ff52115 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/classification/NaiveBayesSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/classification/NaiveBayesSuite.scala @@ -17,16 +17,20 @@ package org.apache.spark.ml.classification -import breeze.linalg.{Vector => BV} +import scala.util.Random + +import breeze.linalg.{DenseVector => BDV, Vector => BV} +import breeze.stats.distributions.{Multinomial => BrzMultinomial} import org.apache.spark.SparkFunSuite +import org.apache.spark.ml.classification.NaiveBayesSuite._ +import org.apache.spark.ml.feature.LabeledPoint +import org.apache.spark.ml.linalg._ import org.apache.spark.ml.param.ParamsSuite import org.apache.spark.ml.util.{DefaultReadWriteTest, MLTestingUtils} +import org.apache.spark.ml.util.TestingUtils._ import org.apache.spark.mllib.classification.NaiveBayes.{Bernoulli, Multinomial} -import org.apache.spark.mllib.classification.NaiveBayesSuite._ -import org.apache.spark.mllib.linalg._ import org.apache.spark.mllib.util.MLlibTestSparkContext -import org.apache.spark.mllib.util.TestingUtils._ import org.apache.spark.sql.{DataFrame, Dataset, Row} class NaiveBayesSuite extends SparkFunSuite with MLlibTestSparkContext with DefaultReadWriteTest { @@ -206,4 +210,48 @@ object NaiveBayesSuite { "predictionCol" -> "myPrediction", "smoothing" -> 0.1 ) + + private def calcLabel(p: Double, pi: Array[Double]): Int = { + var sum = 0.0 + for (j <- 0 until pi.length) { + sum += pi(j) + if (p < sum) return j + } + -1 + } + + // Generate input of the form Y = (theta * x).argmax() + def generateNaiveBayesInput( + pi: Array[Double], // 1XC + theta: Array[Array[Double]], // CXD + nPoints: Int, + seed: Int, + modelType: String = Multinomial, + sample: Int = 10): Seq[LabeledPoint] = { + val D = theta(0).length + val rnd = new Random(seed) + val _pi = pi.map(math.pow(math.E, _)) + val _theta = theta.map(row => row.map(math.pow(math.E, _))) + + for (i <- 0 until nPoints) yield { + val y = calcLabel(rnd.nextDouble(), _pi) + val xi = modelType match { + case Bernoulli => Array.tabulate[Double] (D) { j => + if (rnd.nextDouble () < _theta(y)(j) ) 1 else 0 + } + case Multinomial => + val mult = BrzMultinomial(BDV(_theta(y))) + val emptyMap = (0 until D).map(x => (x, 0.0)).toMap + val counts = emptyMap ++ mult.sample(sample).groupBy(x => x).map { + case (index, reps) => (index, reps.size.toDouble) + } + counts.toArray.sortBy(_._1).map(_._2) + case _ => + // This should never happen. + throw new UnknownError(s"Invalid modelType: $modelType.") + } + + LabeledPoint(y, Vectors.dense(xi)) + } + } } http://git-wip-us.apache.org/repos/asf/spark/blob/ff1cfce1/mllib/src/test/scala/org/apache/spark/ml/classification/OneVsRestSuite.scala ---------------------------------------------------------------------- diff --git a/mllib/src/test/scala/org/apache/spark/ml/classification/OneVsRestSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/classification/OneVsRestSuite.scala index 5044d40..361dd74 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/classification/OneVsRestSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/classification/OneVsRestSuite.scala @@ -19,14 +19,16 @@ package org.apache.spark.ml.classification import org.apache.spark.SparkFunSuite import org.apache.spark.ml.attribute.NominalAttribute +import org.apache.spark.ml.classification.LogisticRegressionSuite._ +import org.apache.spark.ml.feature.LabeledPoint import org.apache.spark.ml.feature.StringIndexer +import org.apache.spark.ml.linalg.Vectors import org.apache.spark.ml.param.{ParamMap, ParamsSuite} import org.apache.spark.ml.util.{DefaultReadWriteTest, MetadataUtils, MLTestingUtils} -import org.apache.spark.mllib.classification.LogisticRegressionSuite._ import org.apache.spark.mllib.classification.LogisticRegressionWithLBFGS import org.apache.spark.mllib.evaluation.MulticlassMetrics -import org.apache.spark.mllib.linalg.Vectors -import org.apache.spark.mllib.regression.LabeledPoint +import org.apache.spark.mllib.linalg.{Vectors => OldVectors} +import org.apache.spark.mllib.regression.{LabeledPoint => OldLabeledPoint} import org.apache.spark.mllib.util.MLlibTestSparkContext import org.apache.spark.mllib.util.TestingUtils._ import org.apache.spark.rdd.RDD @@ -88,8 +90,8 @@ class OneVsRestSuite extends SparkFunSuite with MLlibTestSparkContext with Defau val lr = new LogisticRegressionWithLBFGS().setIntercept(true).setNumClasses(numClasses) lr.optimizer.setRegParam(0.1).setNumIterations(100) - val model = lr.run(rdd) - val results = model.predict(rdd.map(_.features)).zip(rdd.map(_.label)) + val model = lr.run(rdd.map(OldLabeledPoint.fromML)) + val results = model.predict(rdd.map(p => OldVectors.fromML(p.features))).zip(rdd.map(_.label)) // determine the #confusion matrix in each class. // bound how much error we allow compared to multinomial logistic regression. val expectedMetrics = new MulticlassMetrics(results) http://git-wip-us.apache.org/repos/asf/spark/blob/ff1cfce1/mllib/src/test/scala/org/apache/spark/ml/classification/ProbabilisticClassifierSuite.scala ---------------------------------------------------------------------- diff --git a/mllib/src/test/scala/org/apache/spark/ml/classification/ProbabilisticClassifierSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/classification/ProbabilisticClassifierSuite.scala index cfa75ec..b3bd2b3 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/classification/ProbabilisticClassifierSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/classification/ProbabilisticClassifierSuite.scala @@ -18,7 +18,7 @@ package org.apache.spark.ml.classification import org.apache.spark.SparkFunSuite -import org.apache.spark.mllib.linalg.{Vector, Vectors} +import org.apache.spark.ml.linalg.{Vector, Vectors} final class TestProbabilisticClassificationModel( override val uid: String, http://git-wip-us.apache.org/repos/asf/spark/blob/ff1cfce1/mllib/src/test/scala/org/apache/spark/ml/classification/RandomForestClassifierSuite.scala ---------------------------------------------------------------------- diff --git a/mllib/src/test/scala/org/apache/spark/ml/classification/RandomForestClassifierSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/classification/RandomForestClassifierSuite.scala index 8002a2f..2e99ee1 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/classification/RandomForestClassifierSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/classification/RandomForestClassifierSuite.scala @@ -18,12 +18,13 @@ package org.apache.spark.ml.classification import org.apache.spark.SparkFunSuite +import org.apache.spark.ml.feature.LabeledPoint +import org.apache.spark.ml.linalg.{Vector, Vectors} import org.apache.spark.ml.param.ParamsSuite import org.apache.spark.ml.tree.LeafNode import org.apache.spark.ml.tree.impl.TreeTests import org.apache.spark.ml.util.{DefaultReadWriteTest, MLTestingUtils} -import org.apache.spark.mllib.linalg.{Vector, Vectors} -import org.apache.spark.mllib.regression.LabeledPoint +import org.apache.spark.mllib.regression.{LabeledPoint => OldLabeledPoint} import org.apache.spark.mllib.tree.{EnsembleTestHelper, RandomForest => OldRandomForest} import org.apache.spark.mllib.tree.configuration.{Algo => OldAlgo} import org.apache.spark.mllib.util.MLlibTestSparkContext @@ -46,8 +47,10 @@ class RandomForestClassifierSuite super.beforeAll() orderedLabeledPoints50_1000 = sc.parallelize(EnsembleTestHelper.generateOrderedLabeledPoints(numFeatures = 50, 1000)) + .map(_.asML) orderedLabeledPoints5_20 = sc.parallelize(EnsembleTestHelper.generateOrderedLabeledPoints(numFeatures = 5, 20)) + .map(_.asML) } ///////////////////////////////////////////////////////////////////////////// @@ -233,7 +236,8 @@ private object RandomForestClassifierSuite extends SparkFunSuite { val oldStrategy = rf.getOldStrategy(categoricalFeatures, numClasses, OldAlgo.Classification, rf.getOldImpurity) val oldModel = OldRandomForest.trainClassifier( - data, oldStrategy, rf.getNumTrees, rf.getFeatureSubsetStrategy, rf.getSeed.toInt) + data.map(OldLabeledPoint.fromML), oldStrategy, rf.getNumTrees, rf.getFeatureSubsetStrategy, + rf.getSeed.toInt) val newData: DataFrame = TreeTests.setMetadata(data, categoricalFeatures, numClasses) val newModel = rf.fit(newData) // Use parent from newTree since this is not checked anyways. http://git-wip-us.apache.org/repos/asf/spark/blob/ff1cfce1/mllib/src/test/scala/org/apache/spark/ml/clustering/KMeansSuite.scala ---------------------------------------------------------------------- diff --git a/mllib/src/test/scala/org/apache/spark/ml/clustering/KMeansSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/clustering/KMeansSuite.scala index 2832db2..88f31a1 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/clustering/KMeansSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/clustering/KMeansSuite.scala @@ -18,9 +18,9 @@ package org.apache.spark.ml.clustering import org.apache.spark.SparkFunSuite +import org.apache.spark.ml.linalg.{Vector, Vectors} import org.apache.spark.ml.util.DefaultReadWriteTest import org.apache.spark.mllib.clustering.{KMeans => MLlibKMeans} -import org.apache.spark.mllib.linalg.{Vector, Vectors} import org.apache.spark.mllib.util.MLlibTestSparkContext import org.apache.spark.sql.{DataFrame, Dataset, SparkSession} http://git-wip-us.apache.org/repos/asf/spark/blob/ff1cfce1/mllib/src/test/scala/org/apache/spark/ml/clustering/LDASuite.scala ---------------------------------------------------------------------- diff --git a/mllib/src/test/scala/org/apache/spark/ml/clustering/LDASuite.scala b/mllib/src/test/scala/org/apache/spark/ml/clustering/LDASuite.scala index 34e8964..ddfa875 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/clustering/LDASuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/clustering/LDASuite.scala @@ -20,10 +20,10 @@ package org.apache.spark.ml.clustering import org.apache.hadoop.fs.Path import org.apache.spark.SparkFunSuite +import org.apache.spark.ml.linalg.{Vector, Vectors} import org.apache.spark.ml.util.{DefaultReadWriteTest, MLTestingUtils} -import org.apache.spark.mllib.linalg.{Vector, Vectors} +import org.apache.spark.ml.util.TestingUtils._ import org.apache.spark.mllib.util.MLlibTestSparkContext -import org.apache.spark.mllib.util.TestingUtils._ import org.apache.spark.sql._ http://git-wip-us.apache.org/repos/asf/spark/blob/ff1cfce1/mllib/src/test/scala/org/apache/spark/ml/evaluation/BinaryClassificationEvaluatorSuite.scala ---------------------------------------------------------------------- diff --git a/mllib/src/test/scala/org/apache/spark/ml/evaluation/BinaryClassificationEvaluatorSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/evaluation/BinaryClassificationEvaluatorSuite.scala index a8766f9..9ee3df5 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/evaluation/BinaryClassificationEvaluatorSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/evaluation/BinaryClassificationEvaluatorSuite.scala @@ -18,9 +18,9 @@ package org.apache.spark.ml.evaluation import org.apache.spark.SparkFunSuite +import org.apache.spark.ml.linalg.Vectors import org.apache.spark.ml.param.ParamsSuite import org.apache.spark.ml.util.{DefaultReadWriteTest, MLTestingUtils} -import org.apache.spark.mllib.linalg.Vectors import org.apache.spark.mllib.util.MLlibTestSparkContext class BinaryClassificationEvaluatorSuite http://git-wip-us.apache.org/repos/asf/spark/blob/ff1cfce1/mllib/src/test/scala/org/apache/spark/ml/evaluation/RegressionEvaluatorSuite.scala ---------------------------------------------------------------------- diff --git a/mllib/src/test/scala/org/apache/spark/ml/evaluation/RegressionEvaluatorSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/evaluation/RegressionEvaluatorSuite.scala index dcc0043..42ff8ad 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/evaluation/RegressionEvaluatorSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/evaluation/RegressionEvaluatorSuite.scala @@ -44,7 +44,7 @@ class RegressionEvaluatorSuite */ val dataset = spark.createDataFrame( sc.parallelize(LinearDataGenerator.generateLinearInput( - 6.3, Array(4.7, 7.2), Array(0.9, -1.3), Array(0.7, 1.2), 100, 42, 0.1), 2)) + 6.3, Array(4.7, 7.2), Array(0.9, -1.3), Array(0.7, 1.2), 100, 42, 0.1), 2).map(_.asML)) /** * Using the following R code to load the data, train the model and evaluate metrics. http://git-wip-us.apache.org/repos/asf/spark/blob/ff1cfce1/mllib/src/test/scala/org/apache/spark/ml/feature/BinarizerSuite.scala ---------------------------------------------------------------------- diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/BinarizerSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/BinarizerSuite.scala index e91f758..9cb84a6 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/feature/BinarizerSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/feature/BinarizerSuite.scala @@ -18,9 +18,9 @@ package org.apache.spark.ml.feature import org.apache.spark.SparkFunSuite +import org.apache.spark.ml.linalg.{Vector, Vectors} import org.apache.spark.ml.param.ParamsSuite import org.apache.spark.ml.util.DefaultReadWriteTest -import org.apache.spark.mllib.linalg.{Vector, Vectors} import org.apache.spark.mllib.util.MLlibTestSparkContext import org.apache.spark.sql.{DataFrame, Row} http://git-wip-us.apache.org/repos/asf/spark/blob/ff1cfce1/mllib/src/test/scala/org/apache/spark/ml/feature/BucketizerSuite.scala ---------------------------------------------------------------------- diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/BucketizerSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/BucketizerSuite.scala index 98b2316..cd10c78 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/feature/BucketizerSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/feature/BucketizerSuite.scala @@ -20,11 +20,11 @@ package org.apache.spark.ml.feature import scala.util.Random import org.apache.spark.{SparkException, SparkFunSuite} +import org.apache.spark.ml.linalg.Vectors import org.apache.spark.ml.param.ParamsSuite import org.apache.spark.ml.util.{DefaultReadWriteTest, MLTestingUtils} -import org.apache.spark.mllib.linalg.Vectors +import org.apache.spark.ml.util.TestingUtils._ import org.apache.spark.mllib.util.MLlibTestSparkContext -import org.apache.spark.mllib.util.TestingUtils._ import org.apache.spark.sql.{DataFrame, Row} class BucketizerSuite extends SparkFunSuite with MLlibTestSparkContext with DefaultReadWriteTest { http://git-wip-us.apache.org/repos/asf/spark/blob/ff1cfce1/mllib/src/test/scala/org/apache/spark/ml/feature/ChiSqSelectorSuite.scala ---------------------------------------------------------------------- diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/ChiSqSelectorSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/ChiSqSelectorSuite.scala index 4fcc974..40d5b48 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/feature/ChiSqSelectorSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/feature/ChiSqSelectorSuite.scala @@ -18,12 +18,11 @@ package org.apache.spark.ml.feature import org.apache.spark.SparkFunSuite +import org.apache.spark.ml.linalg.{Vector, Vectors} import org.apache.spark.ml.util.{DefaultReadWriteTest, MLTestingUtils} +import org.apache.spark.ml.util.TestingUtils._ import org.apache.spark.mllib.feature -import org.apache.spark.mllib.linalg.{Vector, Vectors} -import org.apache.spark.mllib.regression.LabeledPoint import org.apache.spark.mllib.util.MLlibTestSparkContext -import org.apache.spark.mllib.util.TestingUtils._ import org.apache.spark.sql.{Row, SparkSession} class ChiSqSelectorSuite extends SparkFunSuite with MLlibTestSparkContext http://git-wip-us.apache.org/repos/asf/spark/blob/ff1cfce1/mllib/src/test/scala/org/apache/spark/ml/feature/CountVectorizerSuite.scala ---------------------------------------------------------------------- diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/CountVectorizerSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/CountVectorizerSuite.scala index b82e3e9..a59203c 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/feature/CountVectorizerSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/feature/CountVectorizerSuite.scala @@ -17,11 +17,11 @@ package org.apache.spark.ml.feature import org.apache.spark.SparkFunSuite +import org.apache.spark.ml.linalg.{Vector, Vectors} import org.apache.spark.ml.param.ParamsSuite import org.apache.spark.ml.util.DefaultReadWriteTest -import org.apache.spark.mllib.linalg.{Vector, Vectors} +import org.apache.spark.ml.util.TestingUtils._ import org.apache.spark.mllib.util.MLlibTestSparkContext -import org.apache.spark.mllib.util.TestingUtils._ import org.apache.spark.sql.Row class CountVectorizerSuite extends SparkFunSuite with MLlibTestSparkContext http://git-wip-us.apache.org/repos/asf/spark/blob/ff1cfce1/mllib/src/test/scala/org/apache/spark/ml/feature/DCTSuite.scala ---------------------------------------------------------------------- diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/DCTSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/DCTSuite.scala index dbd5ae8..c02e961 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/feature/DCTSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/feature/DCTSuite.scala @@ -22,8 +22,8 @@ import scala.beans.BeanInfo import edu.emory.mathcs.jtransforms.dct.DoubleDCT_1D import org.apache.spark.SparkFunSuite +import org.apache.spark.ml.linalg.{Vector, Vectors} import org.apache.spark.ml.util.DefaultReadWriteTest -import org.apache.spark.mllib.linalg.{Vector, Vectors} import org.apache.spark.mllib.util.MLlibTestSparkContext import org.apache.spark.sql.Row http://git-wip-us.apache.org/repos/asf/spark/blob/ff1cfce1/mllib/src/test/scala/org/apache/spark/ml/feature/ElementwiseProductSuite.scala ---------------------------------------------------------------------- diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/ElementwiseProductSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/ElementwiseProductSuite.scala index fc1c05d..a4cca27 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/feature/ElementwiseProductSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/feature/ElementwiseProductSuite.scala @@ -18,8 +18,8 @@ package org.apache.spark.ml.feature import org.apache.spark.SparkFunSuite +import org.apache.spark.ml.linalg.Vectors import org.apache.spark.ml.util.DefaultReadWriteTest -import org.apache.spark.mllib.linalg.Vectors import org.apache.spark.mllib.util.MLlibTestSparkContext class ElementwiseProductSuite http://git-wip-us.apache.org/repos/asf/spark/blob/ff1cfce1/mllib/src/test/scala/org/apache/spark/ml/feature/HashingTFSuite.scala ---------------------------------------------------------------------- diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/HashingTFSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/HashingTFSuite.scala index 89d67d8..99b8007 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/feature/HashingTFSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/feature/HashingTFSuite.scala @@ -19,12 +19,12 @@ package org.apache.spark.ml.feature import org.apache.spark.SparkFunSuite import org.apache.spark.ml.attribute.AttributeGroup +import org.apache.spark.ml.linalg.{Vector, Vectors} import org.apache.spark.ml.param.ParamsSuite import org.apache.spark.ml.util.DefaultReadWriteTest +import org.apache.spark.ml.util.TestingUtils._ import org.apache.spark.mllib.feature.{HashingTF => MLlibHashingTF} -import org.apache.spark.mllib.linalg.{Vector, Vectors} import org.apache.spark.mllib.util.MLlibTestSparkContext -import org.apache.spark.mllib.util.TestingUtils._ import org.apache.spark.util.Utils class HashingTFSuite extends SparkFunSuite with MLlibTestSparkContext with DefaultReadWriteTest { http://git-wip-us.apache.org/repos/asf/spark/blob/ff1cfce1/mllib/src/test/scala/org/apache/spark/ml/feature/IDFSuite.scala ---------------------------------------------------------------------- diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/IDFSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/IDFSuite.scala index 208ea84..09dc8b9 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/feature/IDFSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/feature/IDFSuite.scala @@ -18,12 +18,13 @@ package org.apache.spark.ml.feature import org.apache.spark.SparkFunSuite +import org.apache.spark.ml.linalg.{DenseVector, SparseVector, Vector, Vectors} import org.apache.spark.ml.param.ParamsSuite import org.apache.spark.ml.util.DefaultReadWriteTest +import org.apache.spark.ml.util.TestingUtils._ import org.apache.spark.mllib.feature.{IDFModel => OldIDFModel} -import org.apache.spark.mllib.linalg.{DenseVector, SparseVector, Vector, Vectors} +import org.apache.spark.mllib.linalg.VectorImplicits._ import org.apache.spark.mllib.util.MLlibTestSparkContext -import org.apache.spark.mllib.util.TestingUtils._ import org.apache.spark.sql.Row class IDFSuite extends SparkFunSuite with MLlibTestSparkContext with DefaultReadWriteTest { http://git-wip-us.apache.org/repos/asf/spark/blob/ff1cfce1/mllib/src/test/scala/org/apache/spark/ml/feature/InteractionSuite.scala ---------------------------------------------------------------------- diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/InteractionSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/InteractionSuite.scala index 3409928..3429172 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/feature/InteractionSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/feature/InteractionSuite.scala @@ -21,9 +21,9 @@ import scala.collection.mutable.ArrayBuilder import org.apache.spark.{SparkException, SparkFunSuite} import org.apache.spark.ml.attribute._ +import org.apache.spark.ml.linalg.{Vector, Vectors} import org.apache.spark.ml.param.ParamsSuite import org.apache.spark.ml.util.DefaultReadWriteTest -import org.apache.spark.mllib.linalg.{Vector, Vectors} import org.apache.spark.mllib.util.MLlibTestSparkContext import org.apache.spark.sql.functions.col http://git-wip-us.apache.org/repos/asf/spark/blob/ff1cfce1/mllib/src/test/scala/org/apache/spark/ml/feature/MaxAbsScalerSuite.scala ---------------------------------------------------------------------- diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/MaxAbsScalerSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/MaxAbsScalerSuite.scala index 73d69eb..d6400ee 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/feature/MaxAbsScalerSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/feature/MaxAbsScalerSuite.scala @@ -17,8 +17,8 @@ package org.apache.spark.ml.feature import org.apache.spark.SparkFunSuite +import org.apache.spark.ml.linalg.{Vector, Vectors} import org.apache.spark.ml.util.{DefaultReadWriteTest, MLTestingUtils} -import org.apache.spark.mllib.linalg.{Vector, Vectors} import org.apache.spark.mllib.util.MLlibTestSparkContext import org.apache.spark.sql.Row http://git-wip-us.apache.org/repos/asf/spark/blob/ff1cfce1/mllib/src/test/scala/org/apache/spark/ml/feature/MinMaxScalerSuite.scala ---------------------------------------------------------------------- diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/MinMaxScalerSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/MinMaxScalerSuite.scala index e495c8e..5da8471 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/feature/MinMaxScalerSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/feature/MinMaxScalerSuite.scala @@ -18,8 +18,8 @@ package org.apache.spark.ml.feature import org.apache.spark.SparkFunSuite +import org.apache.spark.ml.linalg.{Vector, Vectors} import org.apache.spark.ml.util.{DefaultReadWriteTest, MLTestingUtils} -import org.apache.spark.mllib.linalg.{Vector, Vectors} import org.apache.spark.mllib.util.MLlibTestSparkContext import org.apache.spark.sql.Row http://git-wip-us.apache.org/repos/asf/spark/blob/ff1cfce1/mllib/src/test/scala/org/apache/spark/ml/feature/NormalizerSuite.scala ---------------------------------------------------------------------- diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/NormalizerSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/NormalizerSuite.scala index 241a1e9..b692831 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/feature/NormalizerSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/feature/NormalizerSuite.scala @@ -18,10 +18,10 @@ package org.apache.spark.ml.feature import org.apache.spark.SparkFunSuite +import org.apache.spark.ml.linalg.{DenseVector, SparseVector, Vector, Vectors} import org.apache.spark.ml.util.DefaultReadWriteTest -import org.apache.spark.mllib.linalg.{DenseVector, SparseVector, Vector, Vectors} +import org.apache.spark.ml.util.TestingUtils._ import org.apache.spark.mllib.util.MLlibTestSparkContext -import org.apache.spark.mllib.util.TestingUtils._ import org.apache.spark.sql.{DataFrame, Row} http://git-wip-us.apache.org/repos/asf/spark/blob/ff1cfce1/mllib/src/test/scala/org/apache/spark/ml/feature/OneHotEncoderSuite.scala ---------------------------------------------------------------------- diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/OneHotEncoderSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/OneHotEncoderSuite.scala index 06ffbc3..7841b4f 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/feature/OneHotEncoderSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/feature/OneHotEncoderSuite.scala @@ -19,9 +19,9 @@ package org.apache.spark.ml.feature import org.apache.spark.SparkFunSuite import org.apache.spark.ml.attribute.{AttributeGroup, BinaryAttribute, NominalAttribute} +import org.apache.spark.ml.linalg.Vector import org.apache.spark.ml.param.ParamsSuite import org.apache.spark.ml.util.DefaultReadWriteTest -import org.apache.spark.mllib.linalg.Vector import org.apache.spark.mllib.util.MLlibTestSparkContext import org.apache.spark.sql.DataFrame import org.apache.spark.sql.functions.col http://git-wip-us.apache.org/repos/asf/spark/blob/ff1cfce1/mllib/src/test/scala/org/apache/spark/ml/feature/PCASuite.scala ---------------------------------------------------------------------- diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/PCASuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/PCASuite.scala index 4befa84..ddb51fb 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/feature/PCASuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/feature/PCASuite.scala @@ -18,12 +18,13 @@ package org.apache.spark.ml.feature import org.apache.spark.SparkFunSuite +import org.apache.spark.ml.linalg._ import org.apache.spark.ml.param.ParamsSuite import org.apache.spark.ml.util.{DefaultReadWriteTest, MLTestingUtils} -import org.apache.spark.mllib.linalg._ +import org.apache.spark.ml.util.TestingUtils._ +import org.apache.spark.mllib.linalg.{Vectors => OldVectors} import org.apache.spark.mllib.linalg.distributed.RowMatrix import org.apache.spark.mllib.util.MLlibTestSparkContext -import org.apache.spark.mllib.util.TestingUtils._ import org.apache.spark.sql.Row class PCASuite extends SparkFunSuite with MLlibTestSparkContext with DefaultReadWriteTest { @@ -45,9 +46,9 @@ class PCASuite extends SparkFunSuite with MLlibTestSparkContext with DefaultRead val dataRDD = sc.parallelize(data, 2) - val mat = new RowMatrix(dataRDD) + val mat = new RowMatrix(dataRDD.map(OldVectors.fromML)) val pc = mat.computePrincipalComponents(3) - val expected = mat.multiply(pc).rows + val expected = mat.multiply(pc).rows.map(_.asML) val df = spark.createDataFrame(dataRDD.zip(expected)).toDF("features", "expected") http://git-wip-us.apache.org/repos/asf/spark/blob/ff1cfce1/mllib/src/test/scala/org/apache/spark/ml/feature/PolynomialExpansionSuite.scala ---------------------------------------------------------------------- diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/PolynomialExpansionSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/PolynomialExpansionSuite.scala index e3adbba..8e1f9dd 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/feature/PolynomialExpansionSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/feature/PolynomialExpansionSuite.scala @@ -20,11 +20,11 @@ package org.apache.spark.ml.feature import org.scalatest.exceptions.TestFailedException import org.apache.spark.SparkFunSuite +import org.apache.spark.ml.linalg.{DenseVector, SparseVector, Vector, Vectors} import org.apache.spark.ml.param.ParamsSuite import org.apache.spark.ml.util.DefaultReadWriteTest -import org.apache.spark.mllib.linalg.{DenseVector, SparseVector, Vector, Vectors} +import org.apache.spark.ml.util.TestingUtils._ import org.apache.spark.mllib.util.MLlibTestSparkContext -import org.apache.spark.mllib.util.TestingUtils._ import org.apache.spark.sql.Row class PolynomialExpansionSuite http://git-wip-us.apache.org/repos/asf/spark/blob/ff1cfce1/mllib/src/test/scala/org/apache/spark/ml/feature/RFormulaSuite.scala ---------------------------------------------------------------------- diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/RFormulaSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/RFormulaSuite.scala index c623a62..c12ab8f 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/feature/RFormulaSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/feature/RFormulaSuite.scala @@ -19,9 +19,9 @@ package org.apache.spark.ml.feature import org.apache.spark.SparkFunSuite import org.apache.spark.ml.attribute._ +import org.apache.spark.ml.linalg.Vectors import org.apache.spark.ml.param.ParamsSuite import org.apache.spark.ml.util.{DefaultReadWriteTest, MLTestingUtils} -import org.apache.spark.mllib.linalg.Vectors import org.apache.spark.mllib.util.MLlibTestSparkContext import org.apache.spark.sql.types.DoubleType http://git-wip-us.apache.org/repos/asf/spark/blob/ff1cfce1/mllib/src/test/scala/org/apache/spark/ml/feature/StandardScalerSuite.scala ---------------------------------------------------------------------- diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/StandardScalerSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/StandardScalerSuite.scala index d62301b..2243a0f 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/feature/StandardScalerSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/feature/StandardScalerSuite.scala @@ -18,11 +18,11 @@ package org.apache.spark.ml.feature import org.apache.spark.SparkFunSuite +import org.apache.spark.ml.linalg.{Vector, Vectors} import org.apache.spark.ml.param.ParamsSuite import org.apache.spark.ml.util.DefaultReadWriteTest -import org.apache.spark.mllib.linalg.{Vector, Vectors} +import org.apache.spark.ml.util.TestingUtils._ import org.apache.spark.mllib.util.MLlibTestSparkContext -import org.apache.spark.mllib.util.TestingUtils._ import org.apache.spark.sql.{DataFrame, Row} class StandardScalerSuite extends SparkFunSuite with MLlibTestSparkContext http://git-wip-us.apache.org/repos/asf/spark/blob/ff1cfce1/mllib/src/test/scala/org/apache/spark/ml/feature/VectorAssemblerSuite.scala ---------------------------------------------------------------------- diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/VectorAssemblerSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/VectorAssemblerSuite.scala index 250011c..14973e7 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/feature/VectorAssemblerSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/feature/VectorAssemblerSuite.scala @@ -19,9 +19,9 @@ package org.apache.spark.ml.feature import org.apache.spark.{SparkException, SparkFunSuite} import org.apache.spark.ml.attribute.{AttributeGroup, NominalAttribute, NumericAttribute} +import org.apache.spark.ml.linalg.{DenseVector, SparseVector, Vector, Vectors} import org.apache.spark.ml.param.ParamsSuite import org.apache.spark.ml.util.DefaultReadWriteTest -import org.apache.spark.mllib.linalg.{DenseVector, SparseVector, Vector, Vectors} import org.apache.spark.mllib.util.MLlibTestSparkContext import org.apache.spark.sql.Row import org.apache.spark.sql.functions.col http://git-wip-us.apache.org/repos/asf/spark/blob/ff1cfce1/mllib/src/test/scala/org/apache/spark/ml/feature/VectorIndexerSuite.scala ---------------------------------------------------------------------- diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/VectorIndexerSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/VectorIndexerSuite.scala index d1c0270..7071423 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/feature/VectorIndexerSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/feature/VectorIndexerSuite.scala @@ -22,9 +22,9 @@ import scala.beans.{BeanInfo, BeanProperty} import org.apache.spark.{SparkException, SparkFunSuite} import org.apache.spark.internal.Logging import org.apache.spark.ml.attribute._ +import org.apache.spark.ml.linalg.{SparseVector, Vector, Vectors} import org.apache.spark.ml.param.ParamsSuite import org.apache.spark.ml.util.{DefaultReadWriteTest, MLTestingUtils} -import org.apache.spark.mllib.linalg.{SparseVector, Vector, Vectors} import org.apache.spark.mllib.util.MLlibTestSparkContext import org.apache.spark.rdd.RDD import org.apache.spark.sql.DataFrame http://git-wip-us.apache.org/repos/asf/spark/blob/ff1cfce1/mllib/src/test/scala/org/apache/spark/ml/feature/VectorSlicerSuite.scala ---------------------------------------------------------------------- diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/VectorSlicerSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/VectorSlicerSuite.scala index 88a077f..1746ce5 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/feature/VectorSlicerSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/feature/VectorSlicerSuite.scala @@ -19,9 +19,9 @@ package org.apache.spark.ml.feature import org.apache.spark.SparkFunSuite import org.apache.spark.ml.attribute.{Attribute, AttributeGroup, NumericAttribute} +import org.apache.spark.ml.linalg.{Vector, Vectors, VectorUDT} import org.apache.spark.ml.param.ParamsSuite import org.apache.spark.ml.util.DefaultReadWriteTest -import org.apache.spark.mllib.linalg.{Vector, Vectors, VectorUDT} import org.apache.spark.mllib.util.MLlibTestSparkContext import org.apache.spark.sql.{DataFrame, Row} import org.apache.spark.sql.types.{StructField, StructType} http://git-wip-us.apache.org/repos/asf/spark/blob/ff1cfce1/mllib/src/test/scala/org/apache/spark/ml/feature/Word2VecSuite.scala ---------------------------------------------------------------------- diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/Word2VecSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/Word2VecSuite.scala index 8cbe0f3..280a36f 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/feature/Word2VecSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/feature/Word2VecSuite.scala @@ -18,12 +18,12 @@ package org.apache.spark.ml.feature import org.apache.spark.SparkFunSuite +import org.apache.spark.ml.linalg.{Vector, Vectors} import org.apache.spark.ml.param.ParamsSuite import org.apache.spark.ml.util.{DefaultReadWriteTest, MLTestingUtils} +import org.apache.spark.ml.util.TestingUtils._ import org.apache.spark.mllib.feature.{Word2VecModel => OldWord2VecModel} -import org.apache.spark.mllib.linalg.{Vector, Vectors} import org.apache.spark.mllib.util.MLlibTestSparkContext -import org.apache.spark.mllib.util.TestingUtils._ import org.apache.spark.sql.Row class Word2VecSuite extends SparkFunSuite with MLlibTestSparkContext with DefaultReadWriteTest { http://git-wip-us.apache.org/repos/asf/spark/blob/ff1cfce1/mllib/src/test/scala/org/apache/spark/ml/linalg/VectorUDTSuite.scala ---------------------------------------------------------------------- diff --git a/mllib/src/test/scala/org/apache/spark/ml/linalg/VectorUDTSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/linalg/VectorUDTSuite.scala index 7b50876..6ddb12c 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/linalg/VectorUDTSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/linalg/VectorUDTSuite.scala @@ -17,19 +17,11 @@ package org.apache.spark.ml.linalg -import scala.beans.BeanInfo - import org.apache.spark.SparkFunSuite +import org.apache.spark.ml.feature.LabeledPoint import org.apache.spark.sql.catalyst.JavaTypeInference import org.apache.spark.sql.types._ -@BeanInfo -case class LabeledPoint(label: Double, features: Vector) { - override def toString: String = { - s"($label,$features)" - } -} - class VectorUDTSuite extends SparkFunSuite { test("preloaded VectorUDT") { http://git-wip-us.apache.org/repos/asf/spark/blob/ff1cfce1/mllib/src/test/scala/org/apache/spark/ml/optim/IterativelyReweightedLeastSquaresSuite.scala ---------------------------------------------------------------------- diff --git a/mllib/src/test/scala/org/apache/spark/ml/optim/IterativelyReweightedLeastSquaresSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/optim/IterativelyReweightedLeastSquaresSuite.scala index 6040212..b30d995 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/optim/IterativelyReweightedLeastSquaresSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/optim/IterativelyReweightedLeastSquaresSuite.scala @@ -19,9 +19,9 @@ package org.apache.spark.ml.optim import org.apache.spark.SparkFunSuite import org.apache.spark.ml.feature.Instance -import org.apache.spark.mllib.linalg.Vectors +import org.apache.spark.ml.linalg.Vectors +import org.apache.spark.ml.util.TestingUtils._ import org.apache.spark.mllib.util.MLlibTestSparkContext -import org.apache.spark.mllib.util.TestingUtils._ import org.apache.spark.rdd.RDD class IterativelyReweightedLeastSquaresSuite extends SparkFunSuite with MLlibTestSparkContext { http://git-wip-us.apache.org/repos/asf/spark/blob/ff1cfce1/mllib/src/test/scala/org/apache/spark/ml/optim/WeightedLeastSquaresSuite.scala ---------------------------------------------------------------------- diff --git a/mllib/src/test/scala/org/apache/spark/ml/optim/WeightedLeastSquaresSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/optim/WeightedLeastSquaresSuite.scala index 0b58a98..c8de796 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/optim/WeightedLeastSquaresSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/optim/WeightedLeastSquaresSuite.scala @@ -19,9 +19,9 @@ package org.apache.spark.ml.optim import org.apache.spark.SparkFunSuite import org.apache.spark.ml.feature.Instance -import org.apache.spark.mllib.linalg.Vectors +import org.apache.spark.ml.linalg.Vectors +import org.apache.spark.ml.util.TestingUtils._ import org.apache.spark.mllib.util.MLlibTestSparkContext -import org.apache.spark.mllib.util.TestingUtils._ import org.apache.spark.rdd.RDD class WeightedLeastSquaresSuite extends SparkFunSuite with MLlibTestSparkContext { http://git-wip-us.apache.org/repos/asf/spark/blob/ff1cfce1/mllib/src/test/scala/org/apache/spark/ml/param/ParamsSuite.scala ---------------------------------------------------------------------- diff --git a/mllib/src/test/scala/org/apache/spark/ml/param/ParamsSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/param/ParamsSuite.scala index a3366c0..aa9c53c 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/param/ParamsSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/param/ParamsSuite.scala @@ -17,11 +17,11 @@ package org.apache.spark.ml.param -import java.io.{ByteArrayOutputStream, NotSerializableException, ObjectOutputStream} +import java.io.{ByteArrayOutputStream, ObjectOutputStream} import org.apache.spark.SparkFunSuite +import org.apache.spark.ml.linalg.{Vector, Vectors} import org.apache.spark.ml.util.MyParams -import org.apache.spark.mllib.linalg.{Vector, Vectors} class ParamsSuite extends SparkFunSuite { http://git-wip-us.apache.org/repos/asf/spark/blob/ff1cfce1/mllib/src/test/scala/org/apache/spark/ml/recommendation/ALSSuite.scala ---------------------------------------------------------------------- diff --git a/mllib/src/test/scala/org/apache/spark/ml/recommendation/ALSSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/recommendation/ALSSuite.scala index 9da0c32..bbfc415 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/recommendation/ALSSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/recommendation/ALSSuite.scala @@ -31,11 +31,11 @@ import org.apache.commons.io.filefilter.TrueFileFilter import org.apache.spark._ import org.apache.spark.internal.Logging +import org.apache.spark.ml.linalg.Vectors import org.apache.spark.ml.recommendation.ALS._ import org.apache.spark.ml.util.{DefaultReadWriteTest, MLTestingUtils} -import org.apache.spark.mllib.linalg.Vectors +import org.apache.spark.ml.util.TestingUtils._ import org.apache.spark.mllib.util.MLlibTestSparkContext -import org.apache.spark.mllib.util.TestingUtils._ import org.apache.spark.rdd.RDD import org.apache.spark.scheduler.{SparkListener, SparkListenerStageCompleted} import org.apache.spark.sql.{DataFrame, Row, SparkSession} http://git-wip-us.apache.org/repos/asf/spark/blob/ff1cfce1/mllib/src/test/scala/org/apache/spark/ml/regression/AFTSurvivalRegressionSuite.scala ---------------------------------------------------------------------- diff --git a/mllib/src/test/scala/org/apache/spark/ml/regression/AFTSurvivalRegressionSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/regression/AFTSurvivalRegressionSuite.scala index e4772df..05aae80 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/regression/AFTSurvivalRegressionSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/regression/AFTSurvivalRegressionSuite.scala @@ -20,12 +20,12 @@ package org.apache.spark.ml.regression import scala.util.Random import org.apache.spark.SparkFunSuite +import org.apache.spark.ml.linalg.{Vector, Vectors} import org.apache.spark.ml.param.ParamsSuite import org.apache.spark.ml.util.{DefaultReadWriteTest, MLTestingUtils} -import org.apache.spark.mllib.linalg.{Vector, Vectors} +import org.apache.spark.ml.util.TestingUtils._ import org.apache.spark.mllib.random.{ExponentialGenerator, WeibullGenerator} import org.apache.spark.mllib.util.MLlibTestSparkContext -import org.apache.spark.mllib.util.TestingUtils._ import org.apache.spark.sql.{DataFrame, Row} class AFTSurvivalRegressionSuite http://git-wip-us.apache.org/repos/asf/spark/blob/ff1cfce1/mllib/src/test/scala/org/apache/spark/ml/regression/DecisionTreeRegressorSuite.scala ---------------------------------------------------------------------- diff --git a/mllib/src/test/scala/org/apache/spark/ml/regression/DecisionTreeRegressorSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/regression/DecisionTreeRegressorSuite.scala index 2d30cbf..9afb742 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/regression/DecisionTreeRegressorSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/regression/DecisionTreeRegressorSuite.scala @@ -18,10 +18,11 @@ package org.apache.spark.ml.regression import org.apache.spark.SparkFunSuite +import org.apache.spark.ml.feature.LabeledPoint +import org.apache.spark.ml.linalg.Vector import org.apache.spark.ml.tree.impl.TreeTests import org.apache.spark.ml.util.{DefaultReadWriteTest, MLTestingUtils} -import org.apache.spark.mllib.linalg.Vector -import org.apache.spark.mllib.regression.LabeledPoint +import org.apache.spark.mllib.regression.{LabeledPoint => OldLabeledPoint} import org.apache.spark.mllib.tree.{DecisionTree => OldDecisionTree, DecisionTreeSuite => OldDecisionTreeSuite} import org.apache.spark.mllib.util.MLlibTestSparkContext @@ -38,7 +39,7 @@ class DecisionTreeRegressorSuite override def beforeAll() { super.beforeAll() categoricalDataPointsRDD = - sc.parallelize(OldDecisionTreeSuite.generateCategoricalDataPoints()) + sc.parallelize(OldDecisionTreeSuite.generateCategoricalDataPoints().map(_.asML)) } ///////////////////////////////////////////////////////////////////////////// @@ -170,7 +171,7 @@ private[ml] object DecisionTreeRegressorSuite extends SparkFunSuite { categoricalFeatures: Map[Int, Int]): Unit = { val numFeatures = data.first().features.size val oldStrategy = dt.getOldStrategy(categoricalFeatures) - val oldTree = OldDecisionTree.train(data, oldStrategy) + val oldTree = OldDecisionTree.train(data.map(OldLabeledPoint.fromML), oldStrategy) val newData: DataFrame = TreeTests.setMetadata(data, categoricalFeatures, numClasses = 0) val newTree = dt.fit(newData) // Use parent from newTree since this is not checked anyways. http://git-wip-us.apache.org/repos/asf/spark/blob/ff1cfce1/mllib/src/test/scala/org/apache/spark/ml/regression/GBTRegressorSuite.scala ---------------------------------------------------------------------- diff --git a/mllib/src/test/scala/org/apache/spark/ml/regression/GBTRegressorSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/regression/GBTRegressorSuite.scala index ac833b8..7b5df8f 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/regression/GBTRegressorSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/regression/GBTRegressorSuite.scala @@ -18,10 +18,11 @@ package org.apache.spark.ml.regression import org.apache.spark.SparkFunSuite +import org.apache.spark.ml.feature.LabeledPoint +import org.apache.spark.ml.linalg.Vectors import org.apache.spark.ml.tree.impl.TreeTests import org.apache.spark.ml.util.{DefaultReadWriteTest, MLTestingUtils} -import org.apache.spark.mllib.linalg.Vectors -import org.apache.spark.mllib.regression.LabeledPoint +import org.apache.spark.mllib.regression.{LabeledPoint => OldLabeledPoint} import org.apache.spark.mllib.tree.{EnsembleTestHelper, GradientBoostedTrees => OldGBT} import org.apache.spark.mllib.tree.configuration.{Algo => OldAlgo} import org.apache.spark.mllib.util.MLlibTestSparkContext @@ -48,10 +49,13 @@ class GBTRegressorSuite extends SparkFunSuite with MLlibTestSparkContext override def beforeAll() { super.beforeAll() data = sc.parallelize(EnsembleTestHelper.generateOrderedLabeledPoints(numFeatures = 10, 100), 2) + .map(_.asML) trainData = sc.parallelize(EnsembleTestHelper.generateOrderedLabeledPoints(numFeatures = 20, 120), 2) + .map(_.asML) validationData = sc.parallelize(EnsembleTestHelper.generateOrderedLabeledPoints(numFeatures = 20, 80), 2) + .map(_.asML) } test("Regression with continuous features") { @@ -197,7 +201,7 @@ private object GBTRegressorSuite extends SparkFunSuite { val numFeatures = data.first().features.size val oldBoostingStrategy = gbt.getOldBoostingStrategy(categoricalFeatures, OldAlgo.Regression) val oldGBT = new OldGBT(oldBoostingStrategy, gbt.getSeed.toInt) - val oldModel = oldGBT.run(data) + val oldModel = oldGBT.run(data.map(OldLabeledPoint.fromML)) val newData: DataFrame = TreeTests.setMetadata(data, categoricalFeatures, numClasses = 0) val newModel = gbt.fit(newData) // Use parent from newTree since this is not checked anyways. http://git-wip-us.apache.org/repos/asf/spark/blob/ff1cfce1/mllib/src/test/scala/org/apache/spark/ml/regression/GeneralizedLinearRegressionSuite.scala ---------------------------------------------------------------------- diff --git a/mllib/src/test/scala/org/apache/spark/ml/regression/GeneralizedLinearRegressionSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/regression/GeneralizedLinearRegressionSuite.scala index 3d9aeb8..a4568e83 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/regression/GeneralizedLinearRegressionSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/regression/GeneralizedLinearRegressionSuite.scala @@ -20,15 +20,15 @@ package org.apache.spark.ml.regression import scala.util.Random import org.apache.spark.SparkFunSuite +import org.apache.spark.ml.classification.LogisticRegressionSuite._ import org.apache.spark.ml.feature.Instance +import org.apache.spark.ml.feature.LabeledPoint +import org.apache.spark.ml.linalg.{BLAS, DenseVector, Vector, Vectors} import org.apache.spark.ml.param.ParamsSuite import org.apache.spark.ml.util.{DefaultReadWriteTest, MLTestingUtils} -import org.apache.spark.mllib.classification.LogisticRegressionSuite._ -import org.apache.spark.mllib.linalg.{BLAS, DenseVector, Vector, Vectors} +import org.apache.spark.ml.util.TestingUtils._ import org.apache.spark.mllib.random._ -import org.apache.spark.mllib.regression.LabeledPoint import org.apache.spark.mllib.util.MLlibTestSparkContext -import org.apache.spark.mllib.util.TestingUtils._ import org.apache.spark.sql.{DataFrame, Row} import org.apache.spark.sql.functions._ http://git-wip-us.apache.org/repos/asf/spark/blob/ff1cfce1/mllib/src/test/scala/org/apache/spark/ml/regression/IsotonicRegressionSuite.scala ---------------------------------------------------------------------- diff --git a/mllib/src/test/scala/org/apache/spark/ml/regression/IsotonicRegressionSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/regression/IsotonicRegressionSuite.scala index bed4978..14d8a4e 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/regression/IsotonicRegressionSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/regression/IsotonicRegressionSuite.scala @@ -18,9 +18,9 @@ package org.apache.spark.ml.regression import org.apache.spark.SparkFunSuite +import org.apache.spark.ml.linalg.Vectors import org.apache.spark.ml.param.ParamsSuite import org.apache.spark.ml.util.{DefaultReadWriteTest, MLTestingUtils} -import org.apache.spark.mllib.linalg.Vectors import org.apache.spark.mllib.util.MLlibTestSparkContext import org.apache.spark.sql.{DataFrame, Row} http://git-wip-us.apache.org/repos/asf/spark/blob/ff1cfce1/mllib/src/test/scala/org/apache/spark/ml/regression/LinearRegressionSuite.scala ---------------------------------------------------------------------- diff --git a/mllib/src/test/scala/org/apache/spark/ml/regression/LinearRegressionSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/regression/LinearRegressionSuite.scala index a98227d..332d331 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/regression/LinearRegressionSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/regression/LinearRegressionSuite.scala @@ -21,12 +21,12 @@ import scala.util.Random import org.apache.spark.SparkFunSuite import org.apache.spark.ml.feature.Instance +import org.apache.spark.ml.feature.LabeledPoint +import org.apache.spark.ml.linalg.{DenseVector, Vector, Vectors} import org.apache.spark.ml.param.ParamsSuite import org.apache.spark.ml.util.{DefaultReadWriteTest, MLTestingUtils} -import org.apache.spark.mllib.linalg.{DenseVector, Vector, Vectors} -import org.apache.spark.mllib.regression.LabeledPoint +import org.apache.spark.ml.util.TestingUtils._ import org.apache.spark.mllib.util.{LinearDataGenerator, MLlibTestSparkContext} -import org.apache.spark.mllib.util.TestingUtils._ import org.apache.spark.sql.{DataFrame, Row} class LinearRegressionSuite @@ -45,7 +45,7 @@ class LinearRegressionSuite datasetWithDenseFeature = spark.createDataFrame( sc.parallelize(LinearDataGenerator.generateLinearInput( intercept = 6.3, weights = Array(4.7, 7.2), xMean = Array(0.9, -1.3), - xVariance = Array(0.7, 1.2), nPoints = 10000, seed, eps = 0.1), 2)) + xVariance = Array(0.7, 1.2), nPoints = 10000, seed, eps = 0.1), 2).map(_.asML)) /* datasetWithDenseFeatureWithoutIntercept is not needed for correctness testing but is useful for illustrating training model without intercept @@ -53,7 +53,7 @@ class LinearRegressionSuite datasetWithDenseFeatureWithoutIntercept = spark.createDataFrame( sc.parallelize(LinearDataGenerator.generateLinearInput( intercept = 0.0, weights = Array(4.7, 7.2), xMean = Array(0.9, -1.3), - xVariance = Array(0.7, 1.2), nPoints = 10000, seed, eps = 0.1), 2)) + xVariance = Array(0.7, 1.2), nPoints = 10000, seed, eps = 0.1), 2).map(_.asML)) val r = new Random(seed) // When feature size is larger than 4096, normal optimizer is choosed @@ -64,7 +64,7 @@ class LinearRegressionSuite intercept = 0.0, weights = Seq.fill(featureSize)(r.nextDouble()).toArray, xMean = Seq.fill(featureSize)(r.nextDouble()).toArray, xVariance = Seq.fill(featureSize)(r.nextDouble()).toArray, nPoints = 200, - seed, eps = 0.1, sparsity = 0.7), 2)) + seed, eps = 0.1, sparsity = 0.7), 2).map(_.asML)) /* R code: @@ -795,7 +795,7 @@ class LinearRegressionSuite Seq("auto", "l-bfgs", "normal").foreach { solver => val (data, weightedData) = { val activeData = LinearDataGenerator.generateLinearInput( - 6.3, Array(4.7, 7.2), Array(0.9, -1.3), Array(0.7, 1.2), 500, 1, 0.1) + 6.3, Array(4.7, 7.2), Array(0.9, -1.3), Array(0.7, 1.2), 500, 1, 0.1).map(_.asML) val rnd = new Random(8392) val signedData = activeData.map { case p: LabeledPoint => @@ -822,7 +822,7 @@ class LinearRegressionSuite } val noiseData = LinearDataGenerator.generateLinearInput( - 2, Array(1, 3), Array(0.9, -1.3), Array(0.7, 1.2), 500, 1, 0.1) + 2, Array(1, 3), Array(0.9, -1.3), Array(0.7, 1.2), 500, 1, 0.1).map(_.asML) val weightedNoiseData = noiseData.map { case LabeledPoint(label, features) => Instance(label, weight = 0, features) } http://git-wip-us.apache.org/repos/asf/spark/blob/ff1cfce1/mllib/src/test/scala/org/apache/spark/ml/regression/RandomForestRegressorSuite.scala ---------------------------------------------------------------------- diff --git a/mllib/src/test/scala/org/apache/spark/ml/regression/RandomForestRegressorSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/regression/RandomForestRegressorSuite.scala index 7a3a369..c08335f 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/regression/RandomForestRegressorSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/regression/RandomForestRegressorSuite.scala @@ -18,9 +18,10 @@ package org.apache.spark.ml.regression import org.apache.spark.SparkFunSuite +import org.apache.spark.ml.feature.LabeledPoint import org.apache.spark.ml.tree.impl.TreeTests import org.apache.spark.ml.util.{DefaultReadWriteTest, MLTestingUtils} -import org.apache.spark.mllib.regression.LabeledPoint +import org.apache.spark.mllib.regression.{LabeledPoint => OldLabeledPoint} import org.apache.spark.mllib.tree.{EnsembleTestHelper, RandomForest => OldRandomForest} import org.apache.spark.mllib.tree.configuration.{Algo => OldAlgo} import org.apache.spark.mllib.util.MLlibTestSparkContext @@ -40,7 +41,8 @@ class RandomForestRegressorSuite extends SparkFunSuite with MLlibTestSparkContex override def beforeAll() { super.beforeAll() orderedLabeledPoints50_1000 = - sc.parallelize(EnsembleTestHelper.generateOrderedLabeledPoints(numFeatures = 50, 1000)) + sc.parallelize(EnsembleTestHelper.generateOrderedLabeledPoints(numFeatures = 50, 1000) + .map(_.asML)) } ///////////////////////////////////////////////////////////////////////////// @@ -139,8 +141,8 @@ private object RandomForestRegressorSuite extends SparkFunSuite { val numFeatures = data.first().features.size val oldStrategy = rf.getOldStrategy(categoricalFeatures, numClasses = 0, OldAlgo.Regression, rf.getOldImpurity) - val oldModel = OldRandomForest.trainRegressor( - data, oldStrategy, rf.getNumTrees, rf.getFeatureSubsetStrategy, rf.getSeed.toInt) + val oldModel = OldRandomForest.trainRegressor(data.map(OldLabeledPoint.fromML), oldStrategy, + rf.getNumTrees, rf.getFeatureSubsetStrategy, rf.getSeed.toInt) val newData: DataFrame = TreeTests.setMetadata(data, categoricalFeatures, numClasses = 0) val newModel = rf.fit(newData) // Use parent from newTree since this is not checked anyways. http://git-wip-us.apache.org/repos/asf/spark/blob/ff1cfce1/mllib/src/test/scala/org/apache/spark/ml/source/libsvm/LibSVMRelationSuite.scala ---------------------------------------------------------------------- diff --git a/mllib/src/test/scala/org/apache/spark/ml/source/libsvm/LibSVMRelationSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/source/libsvm/LibSVMRelationSuite.scala index 7d0e01f..2517de5 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/source/libsvm/LibSVMRelationSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/source/libsvm/LibSVMRelationSuite.scala @@ -23,7 +23,7 @@ import java.nio.charset.StandardCharsets import com.google.common.io.Files import org.apache.spark.{SparkException, SparkFunSuite} -import org.apache.spark.mllib.linalg.{DenseVector, SparseVector, Vector, Vectors} +import org.apache.spark.ml.linalg.{DenseVector, SparseVector, Vector, Vectors} import org.apache.spark.mllib.util.MLlibTestSparkContext import org.apache.spark.sql.{Row, SaveMode} import org.apache.spark.util.Utils http://git-wip-us.apache.org/repos/asf/spark/blob/ff1cfce1/mllib/src/test/scala/org/apache/spark/ml/tree/impl/GradientBoostedTreesSuite.scala ---------------------------------------------------------------------- diff --git a/mllib/src/test/scala/org/apache/spark/ml/tree/impl/GradientBoostedTreesSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/tree/impl/GradientBoostedTreesSuite.scala index de92b51..5c50a88 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/tree/impl/GradientBoostedTreesSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/tree/impl/GradientBoostedTreesSuite.scala @@ -19,7 +19,7 @@ package org.apache.spark.ml.tree.impl import org.apache.spark.SparkFunSuite import org.apache.spark.internal.Logging -import org.apache.spark.mllib.regression.LabeledPoint +import org.apache.spark.ml.feature.LabeledPoint import org.apache.spark.mllib.tree.{GradientBoostedTreesSuite => OldGBTSuite} import org.apache.spark.mllib.tree.configuration.{BoostingStrategy, Strategy} import org.apache.spark.mllib.tree.configuration.Algo._ @@ -35,8 +35,8 @@ class GradientBoostedTreesSuite extends SparkFunSuite with MLlibTestSparkContext test("runWithValidation stops early and performs better on a validation dataset") { // Set numIterations large enough so that it stops early. val numIterations = 20 - val trainRdd = sc.parallelize(OldGBTSuite.trainData, 2) - val validateRdd = sc.parallelize(OldGBTSuite.validateData, 2) + val trainRdd = sc.parallelize(OldGBTSuite.trainData, 2).map(_.asML) + val validateRdd = sc.parallelize(OldGBTSuite.validateData, 2).map(_.asML) val trainDF = spark.createDataFrame(trainRdd) val validateDF = spark.createDataFrame(validateRdd) http://git-wip-us.apache.org/repos/asf/spark/blob/ff1cfce1/mllib/src/test/scala/org/apache/spark/ml/tree/impl/RandomForestSuite.scala ---------------------------------------------------------------------- diff --git a/mllib/src/test/scala/org/apache/spark/ml/tree/impl/RandomForestSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/tree/impl/RandomForestSuite.scala index 9739e6c..dcc2f30 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/tree/impl/RandomForestSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/tree/impl/RandomForestSuite.scala @@ -21,14 +21,14 @@ import scala.collection.mutable import org.apache.spark.SparkFunSuite import org.apache.spark.ml.classification.DecisionTreeClassificationModel +import org.apache.spark.ml.feature.LabeledPoint +import org.apache.spark.ml.linalg.{Vector, Vectors} import org.apache.spark.ml.tree._ -import org.apache.spark.mllib.linalg.{Vector, Vectors} -import org.apache.spark.mllib.regression.LabeledPoint +import org.apache.spark.ml.util.TestingUtils._ import org.apache.spark.mllib.tree.{DecisionTreeSuite => OldDTSuite, EnsembleTestHelper} import org.apache.spark.mllib.tree.configuration.{Algo => OldAlgo, QuantileStrategy, Strategy => OldStrategy} import org.apache.spark.mllib.tree.impurity.{Entropy, Gini, GiniCalculator} import org.apache.spark.mllib.util.MLlibTestSparkContext -import org.apache.spark.mllib.util.TestingUtils._ import org.apache.spark.util.collection.OpenHashMap /** @@ -43,7 +43,7 @@ class RandomForestSuite extends SparkFunSuite with MLlibTestSparkContext { ///////////////////////////////////////////////////////////////////////////// test("Binary classification with continuous features: split calculation") { - val arr = OldDTSuite.generateOrderedLabeledPointsWithLabel1() + val arr = OldDTSuite.generateOrderedLabeledPointsWithLabel1().map(_.asML) assert(arr.length === 1000) val rdd = sc.parallelize(arr) val strategy = new OldStrategy(OldAlgo.Classification, Gini, 3, 2, 100) @@ -55,7 +55,7 @@ class RandomForestSuite extends SparkFunSuite with MLlibTestSparkContext { } test("Binary classification with binary (ordered) categorical features: split calculation") { - val arr = OldDTSuite.generateCategoricalDataPoints() + val arr = OldDTSuite.generateCategoricalDataPoints().map(_.asML) assert(arr.length === 1000) val rdd = sc.parallelize(arr) val strategy = new OldStrategy(OldAlgo.Classification, Gini, maxDepth = 2, numClasses = 2, @@ -72,7 +72,7 @@ class RandomForestSuite extends SparkFunSuite with MLlibTestSparkContext { test("Binary classification with 3-ary (ordered) categorical features," + " with no samples for one category: split calculation") { - val arr = OldDTSuite.generateCategoricalDataPoints() + val arr = OldDTSuite.generateCategoricalDataPoints().map(_.asML) assert(arr.length === 1000) val rdd = sc.parallelize(arr) val strategy = new OldStrategy(OldAlgo.Classification, Gini, maxDepth = 2, numClasses = 2, @@ -148,7 +148,7 @@ class RandomForestSuite extends SparkFunSuite with MLlibTestSparkContext { } test("Multiclass classification with unordered categorical features: split calculations") { - val arr = OldDTSuite.generateCategoricalDataPoints() + val arr = OldDTSuite.generateCategoricalDataPoints().map(_.asML) assert(arr.length === 1000) val rdd = sc.parallelize(arr) val strategy = new OldStrategy( @@ -189,7 +189,7 @@ class RandomForestSuite extends SparkFunSuite with MLlibTestSparkContext { } test("Multiclass classification with ordered categorical features: split calculations") { - val arr = OldDTSuite.generateCategoricalDataPointsForMulticlassForOrderedFeatures() + val arr = OldDTSuite.generateCategoricalDataPointsForMulticlassForOrderedFeatures().map(_.asML) assert(arr.length === 3000) val rdd = sc.parallelize(arr) val strategy = new OldStrategy(OldAlgo.Classification, Gini, maxDepth = 2, numClasses = 100, @@ -334,7 +334,7 @@ class RandomForestSuite extends SparkFunSuite with MLlibTestSparkContext { } test("Second level node building with vs. without groups") { - val arr = OldDTSuite.generateOrderedLabeledPoints() + val arr = OldDTSuite.generateOrderedLabeledPoints().map(_.asML) assert(arr.length === 1000) val rdd = sc.parallelize(arr) // For tree with 1 group @@ -378,7 +378,7 @@ class RandomForestSuite extends SparkFunSuite with MLlibTestSparkContext { def binaryClassificationTestWithContinuousFeaturesAndSubsampledFeatures(strategy: OldStrategy) { val numFeatures = 50 val arr = EnsembleTestHelper.generateOrderedLabeledPoints(numFeatures, 1000) - val rdd = sc.parallelize(arr) + val rdd = sc.parallelize(arr).map(_.asML) // Select feature subset for top nodes. Return true if OK. def checkFeatureSubsetStrategy( http://git-wip-us.apache.org/repos/asf/spark/blob/ff1cfce1/mllib/src/test/scala/org/apache/spark/ml/tree/impl/TreeTests.scala ---------------------------------------------------------------------- diff --git a/mllib/src/test/scala/org/apache/spark/ml/tree/impl/TreeTests.scala b/mllib/src/test/scala/org/apache/spark/ml/tree/impl/TreeTests.scala index 12ade4c..8cbd652 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/tree/impl/TreeTests.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/tree/impl/TreeTests.scala @@ -22,9 +22,9 @@ import scala.collection.JavaConverters._ import org.apache.spark.{SparkContext, SparkFunSuite} import org.apache.spark.api.java.JavaRDD import org.apache.spark.ml.attribute.{AttributeGroup, NominalAttribute, NumericAttribute} +import org.apache.spark.ml.feature.LabeledPoint +import org.apache.spark.ml.linalg.Vectors import org.apache.spark.ml.tree._ -import org.apache.spark.mllib.linalg.Vectors -import org.apache.spark.mllib.regression.LabeledPoint import org.apache.spark.rdd.RDD import org.apache.spark.sql.{DataFrame, SparkSession} http://git-wip-us.apache.org/repos/asf/spark/blob/ff1cfce1/mllib/src/test/scala/org/apache/spark/ml/tuning/CrossValidatorSuite.scala ---------------------------------------------------------------------- diff --git a/mllib/src/test/scala/org/apache/spark/ml/tuning/CrossValidatorSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/tuning/CrossValidatorSuite.scala index 85df6da..30bd390 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/tuning/CrossValidatorSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/tuning/CrossValidatorSuite.scala @@ -20,17 +20,17 @@ package org.apache.spark.ml.tuning import org.apache.spark.SparkFunSuite import org.apache.spark.ml.{Estimator, Model, Pipeline} import org.apache.spark.ml.classification.{LogisticRegression, LogisticRegressionModel} +import org.apache.spark.ml.classification.LogisticRegressionSuite.generateLogisticInput import org.apache.spark.ml.evaluation.{BinaryClassificationEvaluator, Evaluator, RegressionEvaluator} import org.apache.spark.ml.feature.HashingTF +import org.apache.spark.ml.linalg.Vectors import org.apache.spark.ml.param.{ParamMap, ParamPair} import org.apache.spark.ml.param.shared.HasInputCol import org.apache.spark.ml.regression.LinearRegression import org.apache.spark.ml.util.{DefaultReadWriteTest, MLTestingUtils} -import org.apache.spark.mllib.classification.LogisticRegressionSuite.generateLogisticInput -import org.apache.spark.mllib.linalg.Vectors import org.apache.spark.mllib.util.{LinearDataGenerator, MLlibTestSparkContext} -import org.apache.spark.sql.{DataFrame, Dataset} -import org.apache.spark.sql.types.{StructField, StructType} +import org.apache.spark.sql.Dataset +import org.apache.spark.sql.types.StructType class CrossValidatorSuite extends SparkFunSuite with MLlibTestSparkContext with DefaultReadWriteTest { @@ -69,7 +69,7 @@ class CrossValidatorSuite test("cross validation with linear regression") { val dataset = spark.createDataFrame( sc.parallelize(LinearDataGenerator.generateLinearInput( - 6.3, Array(4.7, 7.2), Array(0.9, -1.3), Array(0.7, 1.2), 100, 42, 0.1), 2)) + 6.3, Array(4.7, 7.2), Array(0.9, -1.3), Array(0.7, 1.2), 100, 42, 0.1), 2).map(_.asML)) val trainer = new LinearRegression().setSolver("l-bfgs") val lrParamMaps = new ParamGridBuilder() http://git-wip-us.apache.org/repos/asf/spark/blob/ff1cfce1/mllib/src/test/scala/org/apache/spark/ml/tuning/TrainValidationSplitSuite.scala ---------------------------------------------------------------------- diff --git a/mllib/src/test/scala/org/apache/spark/ml/tuning/TrainValidationSplitSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/tuning/TrainValidationSplitSuite.scala index f8d3de1..c1e9c2f 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/tuning/TrainValidationSplitSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/tuning/TrainValidationSplitSuite.scala @@ -20,15 +20,15 @@ package org.apache.spark.ml.tuning import org.apache.spark.SparkFunSuite import org.apache.spark.ml.{Estimator, Model} import org.apache.spark.ml.classification.{LogisticRegression, LogisticRegressionModel} +import org.apache.spark.ml.classification.LogisticRegressionSuite.generateLogisticInput import org.apache.spark.ml.evaluation.{BinaryClassificationEvaluator, Evaluator, RegressionEvaluator} +import org.apache.spark.ml.linalg.Vectors import org.apache.spark.ml.param.ParamMap import org.apache.spark.ml.param.shared.HasInputCol import org.apache.spark.ml.regression.LinearRegression import org.apache.spark.ml.util.DefaultReadWriteTest -import org.apache.spark.mllib.classification.LogisticRegressionSuite.generateLogisticInput -import org.apache.spark.mllib.linalg.Vectors import org.apache.spark.mllib.util.{LinearDataGenerator, MLlibTestSparkContext} -import org.apache.spark.sql.{DataFrame, Dataset} +import org.apache.spark.sql.Dataset import org.apache.spark.sql.types.StructType class TrainValidationSplitSuite @@ -60,7 +60,7 @@ class TrainValidationSplitSuite test("train validation with linear regression") { val dataset = spark.createDataFrame( sc.parallelize(LinearDataGenerator.generateLinearInput( - 6.3, Array(4.7, 7.2), Array(0.9, -1.3), Array(0.7, 1.2), 100, 42, 0.1), 2)) + 6.3, Array(4.7, 7.2), Array(0.9, -1.3), Array(0.7, 1.2), 100, 42, 0.1), 2).map(_.asML)) val trainer = new LinearRegression().setSolver("l-bfgs") val lrParamMaps = new ParamGridBuilder() http://git-wip-us.apache.org/repos/asf/spark/blob/ff1cfce1/mllib/src/test/scala/org/apache/spark/ml/util/MLTestingUtils.scala ---------------------------------------------------------------------- diff --git a/mllib/src/test/scala/org/apache/spark/ml/util/MLTestingUtils.scala b/mllib/src/test/scala/org/apache/spark/ml/util/MLTestingUtils.scala index ad7d2c9..6aae625 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/util/MLTestingUtils.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/util/MLTestingUtils.scala @@ -20,9 +20,9 @@ package org.apache.spark.ml.util import org.apache.spark.SparkFunSuite import org.apache.spark.ml.{Estimator, Model} import org.apache.spark.ml.evaluation.Evaluator +import org.apache.spark.ml.linalg.Vectors import org.apache.spark.ml.param.ParamMap import org.apache.spark.ml.tree.impl.TreeTests -import org.apache.spark.mllib.linalg.Vectors import org.apache.spark.sql.{DataFrame, SparkSession} import org.apache.spark.sql.functions._ import org.apache.spark.sql.types._ http://git-wip-us.apache.org/repos/asf/spark/blob/ff1cfce1/mllib/src/test/scala/org/apache/spark/mllib/linalg/MatricesSuite.scala ---------------------------------------------------------------------- diff --git a/mllib/src/test/scala/org/apache/spark/mllib/linalg/MatricesSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/linalg/MatricesSuite.scala index b7df02e..8c5b4bd 100644 --- a/mllib/src/test/scala/org/apache/spark/mllib/linalg/MatricesSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/mllib/linalg/MatricesSuite.scala @@ -560,4 +560,55 @@ class MatricesSuite extends SparkFunSuite { compare(oldSM0, newSM0) compare(oldDM0, newDM0) } + + test("implicit conversions between new local linalg and mllib linalg") { + + def mllibMatrixToTriple(m: Matrix): (Array[Double], Int, Int) = + (m.toArray, m.numCols, m.numRows) + + def mllibDenseMatrixToTriple(m: DenseMatrix): (Array[Double], Int, Int) = + (m.toArray, m.numCols, m.numRows) + + def mllibSparseMatrixToTriple(m: SparseMatrix): (Array[Double], Int, Int) = + (m.toArray, m.numCols, m.numRows) + + def mlMatrixToTriple(m: newlinalg.Matrix): (Array[Double], Int, Int) = + (m.toArray, m.numCols, m.numRows) + + def mlDenseMatrixToTriple(m: newlinalg.DenseMatrix): (Array[Double], Int, Int) = + (m.toArray, m.numCols, m.numRows) + + def mlSparseMatrixToTriple(m: newlinalg.SparseMatrix): (Array[Double], Int, Int) = + (m.toArray, m.numCols, m.numRows) + + def compare(m1: (Array[Double], Int, Int), m2: (Array[Double], Int, Int)): Unit = { + assert(m1._1 === m2._1) + assert(m1._2 === m2._2) + assert(m1._3 === m2._3) + } + + val dm: DenseMatrix = new DenseMatrix(3, 2, Array(0.0, 0.0, 1.0, 0.0, 2.0, 3.5)) + val sm: SparseMatrix = dm.toSparse + val sm0: Matrix = sm.asInstanceOf[Matrix] + val dm0: Matrix = dm.asInstanceOf[Matrix] + + val newSM: newlinalg.SparseMatrix = sm.asML + val newDM: newlinalg.DenseMatrix = dm.asML + val newSM0: newlinalg.Matrix = sm0.asML + val newDM0: newlinalg.Matrix = dm0.asML + + import org.apache.spark.mllib.linalg.MatrixImplicits._ + + compare(mllibMatrixToTriple(dm0), mllibMatrixToTriple(newDM0)) + compare(mllibMatrixToTriple(sm0), mllibMatrixToTriple(newSM0)) + + compare(mllibDenseMatrixToTriple(dm), mllibDenseMatrixToTriple(newDM)) + compare(mllibSparseMatrixToTriple(sm), mllibSparseMatrixToTriple(newSM)) + + compare(mlMatrixToTriple(dm0), mlMatrixToTriple(newDM)) + compare(mlMatrixToTriple(sm0), mlMatrixToTriple(newSM0)) + + compare(mlDenseMatrixToTriple(dm), mlDenseMatrixToTriple(newDM)) + compare(mlSparseMatrixToTriple(sm), mlSparseMatrixToTriple(newSM)) + } } http://git-wip-us.apache.org/repos/asf/spark/blob/ff1cfce1/mllib/src/test/scala/org/apache/spark/mllib/linalg/VectorsSuite.scala ---------------------------------------------------------------------- diff --git a/mllib/src/test/scala/org/apache/spark/mllib/linalg/VectorsSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/linalg/VectorsSuite.scala index a7c1a07..2e9c40a 100644 --- a/mllib/src/test/scala/org/apache/spark/mllib/linalg/VectorsSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/mllib/linalg/VectorsSuite.scala @@ -422,4 +422,43 @@ class VectorsSuite extends SparkFunSuite with Logging { assert(oldSV0.toArray === newSV0.toArray) assert(oldDV0.toArray === newDV0.toArray) } + + test("implicit conversions between new local linalg and mllib linalg") { + + def mllibVectorToArray(v: Vector): Array[Double] = v.toArray + + def mllibDenseVectorToArray(v: DenseVector): Array[Double] = v.toArray + + def mllibSparseVectorToArray(v: SparseVector): Array[Double] = v.toArray + + def mlVectorToArray(v: newlinalg.Vector): Array[Double] = v.toArray + + def mlDenseVectorToArray(v: newlinalg.DenseVector): Array[Double] = v.toArray + + def mlSparseVectorToArray(v: newlinalg.SparseVector): Array[Double] = v.toArray + + val dv: DenseVector = new DenseVector(Array(1.0, 2.0, 3.5)) + val sv: SparseVector = new SparseVector(5, Array(1, 2, 4), Array(1.1, 2.2, 4.4)) + val sv0: Vector = sv.asInstanceOf[Vector] + val dv0: Vector = dv.asInstanceOf[Vector] + + val newSV: newlinalg.SparseVector = sv.asML + val newDV: newlinalg.DenseVector = dv.asML + val newSV0: newlinalg.Vector = sv0.asML + val newDV0: newlinalg.Vector = dv0.asML + + import org.apache.spark.mllib.linalg.VectorImplicits._ + + assert(mllibVectorToArray(dv0) === mllibVectorToArray(newDV0)) + assert(mllibVectorToArray(sv0) === mllibVectorToArray(newSV0)) + + assert(mllibDenseVectorToArray(dv) === mllibDenseVectorToArray(newDV)) + assert(mllibSparseVectorToArray(sv) === mllibSparseVectorToArray(newSV)) + + assert(mlVectorToArray(dv0) === mlVectorToArray(newDV0)) + assert(mlVectorToArray(sv0) === mlVectorToArray(newSV0)) + + assert(mlDenseVectorToArray(dv) === mlDenseVectorToArray(newDV)) + assert(mlSparseVectorToArray(sv) === mlSparseVectorToArray(newSV)) + } } http://git-wip-us.apache.org/repos/asf/spark/blob/ff1cfce1/mllib/src/test/scala/org/apache/spark/mllib/regression/LabeledPointSuite.scala ---------------------------------------------------------------------- diff --git a/mllib/src/test/scala/org/apache/spark/mllib/regression/LabeledPointSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/regression/LabeledPointSuite.scala index f8d0af8..252a068 100644 --- a/mllib/src/test/scala/org/apache/spark/mllib/regression/LabeledPointSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/mllib/regression/LabeledPointSuite.scala @@ -18,6 +18,7 @@ package org.apache.spark.mllib.regression import org.apache.spark.SparkFunSuite +import org.apache.spark.ml.feature.{LabeledPoint => NewLabeledPoint} import org.apache.spark.mllib.linalg.Vectors class LabeledPointSuite extends SparkFunSuite { @@ -40,4 +41,16 @@ class LabeledPointSuite extends SparkFunSuite { val point = LabeledPoint.parse("1.0,1.0 0.0 -2.0") assert(point === LabeledPoint(1.0, Vectors.dense(1.0, 0.0, -2.0))) } + + test("conversions between new ml LabeledPoint and mllib LabeledPoint") { + val points: Seq[LabeledPoint] = Seq( + LabeledPoint(1.0, Vectors.dense(1.0, 0.0)), + LabeledPoint(0.0, Vectors.sparse(2, Array(1), Array(-1.0)))) + + val newPoints: Seq[NewLabeledPoint] = points.map(_.asML) + + points.zip(newPoints).foreach { case (p1, p2) => + assert(p1 === LabeledPoint.fromML(p2)) + } + 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