Github user jkbradley commented on a diff in the pull request:

    https://github.com/apache/spark/pull/2451#discussion_r17802293
  
    --- Diff: mllib/src/main/scala/org/apache/spark/mllib/linalg/Matrices.scala 
---
    @@ -57,13 +250,709 @@ trait Matrix extends Serializable {
      * @param numCols number of columns
      * @param values matrix entries in column major
      */
    -class DenseMatrix(val numRows: Int, val numCols: Int, val values: 
Array[Double]) extends Matrix {
    +class DenseMatrix(val numRows: Int, val numCols: Int, val values: 
Array[Double]) extends Matrix with Serializable {
     
    -  require(values.length == numRows * numCols)
    +  require(values.length == numRows * numCols, "The number of values 
supplied doesn't match the " +
    +    s"size of the matrix! values.length: ${values.length}, numRows * 
numCols: ${numRows * numCols}")
     
       override def toArray: Array[Double] = values
     
    -  private[mllib] override def toBreeze: BM[Double] = new 
BDM[Double](numRows, numCols, values)
    +  private[mllib] def toBreeze: BM[Double] = new BDM[Double](numRows, 
numCols, values)
    +
    +  private[mllib] def apply(i: Int): Double = values(i)
    +
    +  private[mllib] def apply(i: Int, j: Int): Double = values(index(i, j))
    +
    +  private[mllib] def index(i: Int, j: Int): Int = i + numRows * j
    +
    +  private[mllib] def update(i: Int, j: Int, v: Double): Unit = {
    +    values(index(i, j)) = v
    +  }
    +
    +  override def copy = new DenseMatrix(numRows, numCols, values.clone())
    +
    +  private[mllib] def elementWiseOperateOnColumnsInPlace(
    +      f: (Double, Double) => Double,
    +      y: Matrix): DenseMatrix = {
    +    val y_vals = y.toArray
    +    val len = y_vals.length
    +    require(y_vals.length == numRows)
    +    var j = 0
    +    while (j < numCols){
    +      var i = 0
    +      while (i < len){
    +        val idx = index(i, j)
    +        values(idx) = f(values(idx), y_vals(i))
    +        i += 1
    +      }
    +      j += 1
    +    }
    +    this
    +  }
    +
    +  private[mllib] def elementWiseOperateOnRowsInPlace(
    +     f: (Double, Double) => Double,
    +     y: Matrix): DenseMatrix = {
    +    val y_vals = y.toArray
    +    require(y_vals.length == numCols)
    +    var j = 0
    +    while (j < numCols){
    +      var i = 0
    +      while (i < numRows){
    +        val idx = index(i, j)
    +        values(idx) = f(values(idx), y_vals(j))
    +        i += 1
    +      }
    +      j += 1
    +    }
    +    this
    +  }
    +
    +  private[mllib] def elementWiseOperateInPlace(f: (Double, Double) => 
Double, y: Matrix): DenseMatrix =  {
    +    val y_val = y.toArray
    +    val len = values.length
    +    require(y_val.length == values.length)
    +    var j = 0
    +    while (j < len){
    +      values(j) = f(values(j), y_val(j))
    +      j += 1
    +    }
    +    this
    +  }
    +
    +  private[mllib] def elementWiseOperateScalarInPlace(f: (Double, Double) 
=> Double, y: Double): DenseMatrix =  {
    +    var j = 0
    +    val len = values.length
    +    while (j < len){
    +      values(j) = f(values(j), y)
    +      j += 1
    +    }
    +    this
    +  }
    +
    +  private[mllib] def operateInPlace(f: (Double, Double) => Double, y: 
Matrix): DenseMatrix = {
    +    if (y.numCols==1 || y.numRows == 1){
    +      require(numCols != numRows, "Operation is ambiguous. Please use 
elementWiseOperateOnRows " +
    +        "or elementWiseOperateOnColumns instead")
    +    }
    +    if (y.numCols == 1 && y.numRows == 1){
    +      elementWiseOperateScalarInPlace(f, y.toArray(0))
    +    } else {
    +      if (y.numCols==1) {
    +        elementWiseOperateOnColumnsInPlace(f, y)
    +      }else if (y.numRows==1){
    --- End diff --
    
    style: Maybe search for "}else" too.


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