How to do X * diag(Y) in Scala Breeze? - scala

Question

How to do X * diag(Y) in Scala Breeze? X could be for example a CSCMatrix and Y could be a DenseVector?
In MATLAB syntax, this would be:
X * spdiags(0, Y, N, N )
Or:
X .* repmat( Y', K, 0 )
In SciPy syntax, this would be a 'broadcast multiply':
Y * X
How to do X * diag(Y) in Scala Breeze?

Answer 1

I wrote my own sparse diagonal method, and dense / sparse multiplication method in the end.
Use like this:
val N = 100000
val K = 100
val A = DenseMatrix.rand(N,K)
val b = DenseVector.rand(N)
val c = MatrixHelper.spdiag(b)
val d = MatrixHelper.mul( A.t, c )
Here are the implementations of spdiag and mul:
// Copyright Hugh Perkins 2012
// You can use this under the terms of the Apache Public License 2.0
// http://www.apache.org/licenses/LICENSE-2.0
package root
import breeze.linalg._
object MatrixHelper {
// it's only efficient to put the sparse matrix on the right hand side, since
// it is a column-sparse matrix
def mul( A: DenseMatrix[Double], B: CSCMatrix[Double] ) : DenseMatrix[Double] = {
val resultRows = A.rows
val resultCols = B.cols
var row = 0
val result = DenseMatrix.zeros[Double](resultRows, resultCols )
while( row < resultRows ) {
var col = 0
while( col < resultCols ) {
val rightRowStartIndex = B.colPtrs(col)
val rightRowEndIndex = B.colPtrs(col + 1) - 1
val numRightRows = rightRowEndIndex - rightRowStartIndex + 1
var ri = 0
var sum = 0.
while( ri < numRightRows ) {
val inner = B.rowIndices(rightRowStartIndex + ri)
val rightValue = B.data(rightRowStartIndex + ri)
sum += A(row,inner) * rightValue
ri += 1
}
result(row,col) = sum
col += 1
}
row += 1
}
result
}
def spdiag( a: Tensor[Int,Double] ) : CSCMatrix[Double] = {
val size = a.size
val result = CSCMatrix.zeros[Double](size,size)
result.reserve(a.size)
var i = 0
while( i < size ) {
result.rowIndices(i) = i
result.colPtrs(i) = i
result.data(i) = i
//result(i,i) = a(i)
i += 1
}
//result.activeSize = size
result.colPtrs(i) = i
result
}
}