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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.evaluation

import org.apache.spark.annotation.{Experimental, Since}
import org.apache.spark.ml.param.{Param, ParamMap, ParamValidators}
import org.apache.spark.ml.param.shared.{HasLabelCol, HasPredictionCol}
import org.apache.spark.ml.util.{DefaultParamsReadable, DefaultParamsWritable, Identifiable, SchemaUtils}
import org.apache.spark.mllib.evaluation.RegressionMetrics
import org.apache.spark.sql.{DataFrame, Row}
import org.apache.spark.sql.functions._
import org.apache.spark.sql.types.{DoubleType, FloatType}

/**
 * :: Experimental ::
 * Evaluator for regression, which expects two input columns: prediction and label.
 */
@Since("1.4.0")
@Experimental
final class RegressionEvaluator @Since("1.4.0") (@Since("1.4.0") override val uid: String)
  extends Evaluator with HasPredictionCol with HasLabelCol with DefaultParamsWritable {

  @Since("1.4.0")
  def this() = this(Identifiable.randomUID("regEval"))

  /**
   * param for metric name in evaluation (supports `"rmse"` (default), `"mse"`, `"r2"`, and `"mae"`)
   *
   * Because we will maximize evaluation value (ref: `CrossValidator`),
   * when we evaluate a metric that is needed to minimize (e.g., `"rmse"`, `"mse"`, `"mae"`),
   * we take and output the negative of this metric.
   * @group param
   */
  @Since("1.4.0")
  val metricName: Param[String] = {
    val allowedParams = ParamValidators.inArray(Array("mse", "rmse", "r2", "mae"))
    new Param(this, "metricName", "metric name in evaluation (mse|rmse|r2|mae)", allowedParams)
  }

  /** @group getParam */
  @Since("1.4.0")
  def getMetricName: String = $(metricName)

  /** @group setParam */
  @Since("1.4.0")
  def setMetricName(value: String): this.type = set(metricName, value)

  /** @group setParam */
  @Since("1.4.0")
  def setPredictionCol(value: String): this.type = set(predictionCol, value)

  /** @group setParam */
  @Since("1.4.0")
  def setLabelCol(value: String): this.type = set(labelCol, value)

  setDefault(metricName -> "rmse")

  @Since("1.4.0")
  override def evaluate(dataset: DataFrame): Double = {
    val schema = dataset.schema
    val predictionColName = $(predictionCol)
    val predictionType = schema($(predictionCol)).dataType
    require(predictionType == FloatType || predictionType == DoubleType,
      s"Prediction column $predictionColName must be of type float or double, " +
        s" but not $predictionType")
    val labelColName = $(labelCol)
    val labelType = schema($(labelCol)).dataType
    require(labelType == FloatType || labelType == DoubleType,
      s"Label column $labelColName must be of type float or double, but not $labelType")

    val predictionAndLabels = dataset
      .select(col($(predictionCol)).cast(DoubleType), col($(labelCol)).cast(DoubleType))
      .map { case Row(prediction: Double, label: Double) =>
        (prediction, label)
      }
    val metrics = new RegressionMetrics(predictionAndLabels)
    val metric = $(metricName) match {
      case "rmse" => metrics.rootMeanSquaredError
      case "mse" => metrics.meanSquaredError
      case "r2" => metrics.r2
      case "mae" => metrics.meanAbsoluteError
    }
    metric
  }

  @Since("1.4.0")
  override def isLargerBetter: Boolean = $(metricName) match {
    case "rmse" => false
    case "mse" => false
    case "r2" => true
    case "mae" => false
  }

  @Since("1.5.0")
  override def copy(extra: ParamMap): RegressionEvaluator = defaultCopy(extra)
}

@Since("1.6.0")
object RegressionEvaluator extends DefaultParamsReadable[RegressionEvaluator] {

  @Since("1.6.0")
  override def load(path: String): RegressionEvaluator = super.load(path)
}