[LINALG] Adds Matrix and Vector operations and constructors

emmalanguage · Apr 29, 2016 · b8ef32b · b8ef32b
1 parent f475c92
commit b8ef32b
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diff --git a/emma-common/src/main/scala/eu/stratosphere/emma/api/lara/DenseMatrix.scala b/emma-common/src/main/scala/eu/stratosphere/emma/api/lara/DenseMatrix.scala
@@ -92,6 +92,15 @@ private[emma] class DenseMatrix[A: Numeric : ClassTag](
     new DenseMatrix[A](numRows, that.numCols, values)
   }
 
+  override
+  def %*%(that: Vector[A]): Vector[A] = {
+    val values: Array[A] = new Array[A](numRows)
+    for (i <- rRange) {
+      values(i) = row(i) dot that
+    }
+    new DenseVector[A](numRows, values)
+  }
+
   //////////////////////////////////////////
   // M operation
   //////////////////////////////////////////

diff --git a/emma-common/src/main/scala/eu/stratosphere/emma/api/lara/Matrix.scala b/emma-common/src/main/scala/eu/stratosphere/emma/api/lara/Matrix.scala
@@ -3,6 +3,7 @@ package eu.stratosphere.emma.api.lara
 import spire.math.Numeric
 
 import scala.reflect.ClassTag
+import scala.util.Random
 
 trait Matrix[A] {
 
@@ -52,8 +53,14 @@ trait Matrix[A] {
 
   def /(that: Matrix[A]): Matrix[A]
 
+  //////////////////////////////////////////
+  // M x M -> M and  M x V -> V
+  //////////////////////////////////////////
+
   def %*%(that: Matrix[A]): Matrix[A]
 
+  def %*%(that: Vector[A]): Vector[A]
+
   //////////////////////////////////////////
   // M operation
   //////////////////////////////////////////
@@ -125,4 +132,8 @@ object Matrix {
   def eye[A: Numeric : ClassTag](rows: Int): Matrix[A] = {
     Matrix.fill(rows, rows)((i, j) => if (i == j) implicitly[Numeric[A]].one else implicitly[Numeric[A]].zero)
   }
+
+  def rand[A: Numeric : ClassTag](rows: Int, cols: Int): Matrix[A] = {
+    Matrix.fill(rows, cols)((i, j) => implicitly[Numeric[A]].fromDouble(Random.nextDouble()))
+  }
 }
diff --git a/emma-common/src/main/scala/eu/stratosphere/emma/api/lara/Vector.scala b/emma-common/src/main/scala/eu/stratosphere/emma/api/lara/Vector.scala
@@ -2,7 +2,9 @@ package eu.stratosphere.emma.api.lara
 
 import spire.math.Numeric
 
+import scala.collection.immutable.NumericRange
 import scala.reflect.ClassTag
+import scala.util.Random
 
 trait Vector[A] {
 
@@ -105,6 +107,18 @@ object Vector {
     new DenseVector[A](values.length, values, rowVector = isRowVector)
   }
 
+  def apply[A: Numeric : ClassTag](range: NumericRange[A]): Vector[A] = {
+    new DenseVector[A](range.length, range.toArray)
+  }
+
+  def apply[_ <: Int](range: Range): Vector[Int] = {
+    new DenseVector[Int](range.length, range.toArray)
+  }
+
+  def apply[A: Numeric : ClassTag](range: Range.Partial[Double, NumericRange[A]]): Vector[A] = {
+    apply[A](range.by(1.0))
+  }
+
   //////////////////////////////////////////
   // Generators
   // TODO: THIS SHOULD BE REPLACED BY CTORS USING EITHER DENSE OR SPARSE IMPLEMENTATION
@@ -122,7 +136,28 @@ object Vector {
     new DenseVector[A](size, Array.fill(size)(implicitly[Numeric[A]].zero), rowVector = isRowVector)
   }
 
+  def zerosLike[A: Numeric: ClassTag](that: Vector[A]): Vector[A] = {
+    Vector.zeros[A](that.length)
+  }
+
   def ones[A: Numeric : ClassTag](size: Int, isRowVector: Boolean = false): Vector[A] = {
     new DenseVector[A](size, Array.fill(size)(implicitly[Numeric[A]].one), rowVector = isRowVector)
   }
+
+  def rand[A: Numeric:ClassTag](size: Int, isRowVector: Boolean = false): Vector[A] = {
+    val rng = new Random()
+    new DenseVector[A](
+      size,
+      Array.fill(size)(implicitly[Numeric[A]].fromDouble(rng.nextDouble())),
+      rowVector = isRowVector
+    )
+  }
+
+  def rand[A: Numeric: ClassTag](size: Int, isRowVector: Boolean, seed: Long): Vector[A] = {
+    val rng = new Random(seed)
+    new DenseVector[A](size,
+      Array.fill(size)(implicitly[Numeric[A]].fromDouble(rng.nextDouble())),
+      rowVector = isRowVector
+    )
+  }
 }