Repository: spark Updated Branches: refs/heads/branch-1.4 6391be872 -> 88399c34b
[SPARK-8053] [MLLIB] renamed scalingVector to scalingVec I searched the Spark codebase for all occurrences of "scalingVector" CC: mengxr Author: Joseph K. Bradley <jos...@databricks.com> Closes #6596 from jkbradley/scalingVec-rename and squashes the following commits: d3812f8 [Joseph K. Bradley] renamed scalingVector to scalingVec (cherry picked from commit 07c16cb5ba9cb0bfe34e8c0efbf06540a22d4e4e) Signed-off-by: Xiangrui Meng <m...@databricks.com> Project: http://git-wip-us.apache.org/repos/asf/spark/repo Commit: http://git-wip-us.apache.org/repos/asf/spark/commit/88399c34 Tree: http://git-wip-us.apache.org/repos/asf/spark/tree/88399c34 Diff: http://git-wip-us.apache.org/repos/asf/spark/diff/88399c34 Branch: refs/heads/branch-1.4 Commit: 88399c34b25dd1fe90daf14cecdbd81058b95f51 Parents: 6391be8 Author: Joseph K. Bradley <jos...@databricks.com> Authored: Tue Jun 2 22:56:56 2015 -0700 Committer: Xiangrui Meng <m...@databricks.com> Committed: Tue Jun 2 22:57:12 2015 -0700 ---------------------------------------------------------------------- .../apache/spark/ml/feature/ElementwiseProduct.scala | 2 +- .../spark/mllib/feature/ElementwiseProduct.scala | 14 +++++++------- 2 files changed, 8 insertions(+), 8 deletions(-) ---------------------------------------------------------------------- http://git-wip-us.apache.org/repos/asf/spark/blob/88399c34/mllib/src/main/scala/org/apache/spark/ml/feature/ElementwiseProduct.scala ---------------------------------------------------------------------- diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/ElementwiseProduct.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/ElementwiseProduct.scala index 3ae1833..1e758cb 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/feature/ElementwiseProduct.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/feature/ElementwiseProduct.scala @@ -41,7 +41,7 @@ class ElementwiseProduct(override val uid: String) * the vector to multiply with input vectors * @group param */ - val scalingVec: Param[Vector] = new Param(this, "scalingVector", "vector for hadamard product") + val scalingVec: Param[Vector] = new Param(this, "scalingVec", "vector for hadamard product") /** @group setParam */ def setScalingVec(value: Vector): this.type = set(scalingVec, value) http://git-wip-us.apache.org/repos/asf/spark/blob/88399c34/mllib/src/main/scala/org/apache/spark/mllib/feature/ElementwiseProduct.scala ---------------------------------------------------------------------- diff --git a/mllib/src/main/scala/org/apache/spark/mllib/feature/ElementwiseProduct.scala b/mllib/src/main/scala/org/apache/spark/mllib/feature/ElementwiseProduct.scala index b0985ba..d67fe6c 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/feature/ElementwiseProduct.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/feature/ElementwiseProduct.scala @@ -25,10 +25,10 @@ import org.apache.spark.mllib.linalg._ * Outputs the Hadamard product (i.e., the element-wise product) of each input vector with a * provided "weight" vector. In other words, it scales each column of the dataset by a scalar * multiplier. - * @param scalingVector The values used to scale the reference vector's individual components. + * @param scalingVec The values used to scale the reference vector's individual components. */ @Experimental -class ElementwiseProduct(val scalingVector: Vector) extends VectorTransformer { +class ElementwiseProduct(val scalingVec: Vector) extends VectorTransformer { /** * Does the hadamard product transformation. @@ -37,15 +37,15 @@ class ElementwiseProduct(val scalingVector: Vector) extends VectorTransformer { * @return transformed vector. */ override def transform(vector: Vector): Vector = { - require(vector.size == scalingVector.size, - s"vector sizes do not match: Expected ${scalingVector.size} but found ${vector.size}") + require(vector.size == scalingVec.size, + s"vector sizes do not match: Expected ${scalingVec.size} but found ${vector.size}") vector match { case dv: DenseVector => val values: Array[Double] = dv.values.clone() - val dim = scalingVector.size + val dim = scalingVec.size var i = 0 while (i < dim) { - values(i) *= scalingVector(i) + values(i) *= scalingVec(i) i += 1 } Vectors.dense(values) @@ -54,7 +54,7 @@ class ElementwiseProduct(val scalingVector: Vector) extends VectorTransformer { val dim = values.length var i = 0 while (i < dim) { - values(i) *= scalingVector(indices(i)) + values(i) *= scalingVec(indices(i)) i += 1 } Vectors.sparse(size, indices, values) --------------------------------------------------------------------- To unsubscribe, e-mail: commits-unsubscr...@spark.apache.org For additional commands, e-mail: commits-h...@spark.apache.org
