Packages

object SparseMatrix extends Serializable

Annotations
@Since( "2.0.0" )
Source
Matrices.scala
Linear Supertypes
Serializable, Serializable, AnyRef, Any
Ordering
  1. Alphabetic
  2. By Inheritance
Inherited
  1. SparseMatrix
  2. Serializable
  3. Serializable
  4. AnyRef
  5. Any
  1. Hide All
  2. Show All
Visibility
  1. Public
  2. All

Value Members

  1. def fromCOO(numRows: Int, numCols: Int, entries: Iterable[(Int, Int, Double)]): SparseMatrix

    Generate a SparseMatrix from Coordinate List (COO) format.

    Generate a SparseMatrix from Coordinate List (COO) format. Input must be an array of (i, j, value) tuples. Entries that have duplicate values of i and j are added together. Tuples where value is equal to zero will be omitted.

    numRows

    number of rows of the matrix

    numCols

    number of columns of the matrix

    entries

    Array of (i, j, value) tuples

    returns

    The corresponding SparseMatrix

    Annotations
    @Since( "2.0.0" )
  2. def spdiag(vector: Vector): SparseMatrix

    Generate a diagonal matrix in SparseMatrix format from the supplied values.

    Generate a diagonal matrix in SparseMatrix format from the supplied values.

    vector

    a Vector that will form the values on the diagonal of the matrix

    returns

    Square SparseMatrix with size values.length x values.length and non-zero values on the diagonal

    Annotations
    @Since( "2.0.0" )
  3. def speye(n: Int): SparseMatrix

    Generate an Identity Matrix in SparseMatrix format.

    Generate an Identity Matrix in SparseMatrix format.

    n

    number of rows and columns of the matrix

    returns

    SparseMatrix with size n x n and values of ones on the diagonal

    Annotations
    @Since( "2.0.0" )
  4. def sprand(numRows: Int, numCols: Int, density: Double, rng: Random): SparseMatrix

    Generate a SparseMatrix consisting of i.i.d.

    Generate a SparseMatrix consisting of i.i.d. uniform random numbers. The number of non-zero elements equal the ceiling of numRows x numCols x density

    numRows

    number of rows of the matrix

    numCols

    number of columns of the matrix

    density

    the desired density for the matrix

    rng

    a random number generator

    returns

    SparseMatrix with size numRows x numCols and values in U(0, 1)

    Annotations
    @Since( "2.0.0" )
  5. def sprandn(numRows: Int, numCols: Int, density: Double, rng: Random): SparseMatrix

    Generate a SparseMatrix consisting of i.i.d.

    Generate a SparseMatrix consisting of i.i.d. gaussian random numbers.

    numRows

    number of rows of the matrix

    numCols

    number of columns of the matrix

    density

    the desired density for the matrix

    rng

    a random number generator

    returns

    SparseMatrix with size numRows x numCols and values in N(0, 1)

    Annotations
    @Since( "2.0.0" )