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/*
* 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.spark.ml.feature
import org.apache.spark.SparkFunSuite
import org.apache.spark.ml.util.MLTestingUtils
import org.apache.spark.mllib.linalg.{Vector, Vectors}
import org.apache.spark.mllib.util.MLlibTestSparkContext
import org.apache.spark.sql.{Row, SQLContext}
class MinMaxScalerSuite extends SparkFunSuite with MLlibTestSparkContext {
test("MinMaxScaler fit basic case") {
val sqlContext = new SQLContext(sc)
val data = Array(
Vectors.dense(1, 0, Long.MinValue),
Vectors.dense(2, 0, 0),
Vectors.sparse(3, Array(0, 2), Array(3, Long.MaxValue)),
Vectors.sparse(3, Array(0), Array(1.5)))
val expected: Array[Vector] = Array(
Vectors.dense(-5, 0, -5),
Vectors.dense(0, 0, 0),
Vectors.sparse(3, Array(0, 2), Array(5, 5)),
Vectors.sparse(3, Array(0), Array(-2.5)))
val df = sqlContext.createDataFrame(data.zip(expected)).toDF("features", "expected")
val scaler = new MinMaxScaler()
.setInputCol("features")
.setOutputCol("scaled")
.setMin(-5)
.setMax(5)
val model = scaler.fit(df)
model.transform(df).select("expected", "scaled").collect()
.foreach { case Row(vector1: Vector, vector2: Vector) =>
assert(vector1.equals(vector2), "Transformed vector is different with expected.")
}
// copied model must have the same parent.
MLTestingUtils.checkCopy(model)
}
test("MinMaxScaler arguments max must be larger than min") {
withClue("arguments max must be larger than min") {
intercept[IllegalArgumentException] {
val scaler = new MinMaxScaler().setMin(10).setMax(0)
scaler.validateParams()
}
intercept[IllegalArgumentException] {
val scaler = new MinMaxScaler().setMin(0).setMax(0)
scaler.validateParams()
}
}
}
}
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