Object

org.apache.spark.mllib.linalg

Matrices

Related Doc: package linalg

Permalink

object Matrices

Factory methods for org.apache.spark.mllib.linalg.Matrix.

Annotations
@Since( "1.0.0" )
Source
Matrices.scala
Linear Supertypes
AnyRef, Any
Ordering
  1. Alphabetic
  2. By Inheritance
Inherited
  1. Matrices
  2. AnyRef
  3. Any
  1. Hide All
  2. Show All
Visibility
  1. Public
  2. All

Value Members

  1. final def !=(arg0: Any): Boolean

    Permalink
    Definition Classes
    AnyRef → Any
  2. final def ##(): Int

    Permalink
    Definition Classes
    AnyRef → Any
  3. final def ==(arg0: Any): Boolean

    Permalink
    Definition Classes
    AnyRef → Any
  4. final def asInstanceOf[T0]: T0

    Permalink
    Definition Classes
    Any
  5. def clone(): AnyRef

    Permalink
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  6. def dense(numRows: Int, numCols: Int, values: Array[Double]): Matrix

    Permalink

    Creates a column-major dense matrix.

    Creates a column-major dense matrix.

    numRows

    number of rows

    numCols

    number of columns

    values

    matrix entries in column major

    Annotations
    @Since( "1.0.0" )
  7. def diag(vector: Vector): Matrix

    Permalink

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

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

    vector

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

    returns

    Square Matrix with size values.length x values.length and values on the diagonal

    Annotations
    @Since( "1.2.0" )
  8. final def eq(arg0: AnyRef): Boolean

    Permalink
    Definition Classes
    AnyRef
  9. def equals(arg0: Any): Boolean

    Permalink
    Definition Classes
    AnyRef → Any
  10. def eye(n: Int): Matrix

    Permalink

    Generate a dense Identity Matrix in Matrix format.

    Generate a dense Identity Matrix in Matrix format.

    n

    number of rows and columns of the matrix

    returns

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

    Annotations
    @Since( "1.2.0" )
  11. def finalize(): Unit

    Permalink
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  12. final def getClass(): Class[_]

    Permalink
    Definition Classes
    AnyRef → Any
  13. def hashCode(): Int

    Permalink
    Definition Classes
    AnyRef → Any
  14. def horzcat(matrices: Array[Matrix]): Matrix

    Permalink

    Horizontally concatenate a sequence of matrices.

    Horizontally concatenate a sequence of matrices. The returned matrix will be in the format the matrices are supplied in. Supplying a mix of dense and sparse matrices will result in a sparse matrix. If the Array is empty, an empty DenseMatrix will be returned.

    matrices

    array of matrices

    returns

    a single Matrix composed of the matrices that were horizontally concatenated

    Annotations
    @Since( "1.3.0" )
  15. final def isInstanceOf[T0]: Boolean

    Permalink
    Definition Classes
    Any
  16. final def ne(arg0: AnyRef): Boolean

    Permalink
    Definition Classes
    AnyRef
  17. final def notify(): Unit

    Permalink
    Definition Classes
    AnyRef
  18. final def notifyAll(): Unit

    Permalink
    Definition Classes
    AnyRef
  19. def ones(numRows: Int, numCols: Int): Matrix

    Permalink

    Generate a DenseMatrix consisting of ones.

    Generate a DenseMatrix consisting of ones.

    numRows

    number of rows of the matrix

    numCols

    number of columns of the matrix

    returns

    Matrix with size numRows x numCols and values of ones

    Annotations
    @Since( "1.2.0" )
  20. def rand(numRows: Int, numCols: Int, rng: Random): Matrix

    Permalink

    Generate a DenseMatrix consisting of i.i.d. uniform random numbers.

    Generate a DenseMatrix consisting of i.i.d. uniform random numbers.

    numRows

    number of rows of the matrix

    numCols

    number of columns of the matrix

    rng

    a random number generator

    returns

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

    Annotations
    @Since( "1.2.0" )
  21. def randn(numRows: Int, numCols: Int, rng: Random): Matrix

    Permalink

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

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

    numRows

    number of rows of the matrix

    numCols

    number of columns of the matrix

    rng

    a random number generator

    returns

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

    Annotations
    @Since( "1.2.0" )
  22. def sparse(numRows: Int, numCols: Int, colPtrs: Array[Int], rowIndices: Array[Int], values: Array[Double]): Matrix

    Permalink

    Creates a column-major sparse matrix in Compressed Sparse Column (CSC) format.

    Creates a column-major sparse matrix in Compressed Sparse Column (CSC) format.

    numRows

    number of rows

    numCols

    number of columns

    colPtrs

    the index corresponding to the start of a new column

    rowIndices

    the row index of the entry

    values

    non-zero matrix entries in column major

    Annotations
    @Since( "1.2.0" )
  23. def speye(n: Int): Matrix

    Permalink

    Generate a sparse Identity Matrix in Matrix format.

    Generate a sparse Identity Matrix in Matrix format.

    n

    number of rows and columns of the matrix

    returns

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

    Annotations
    @Since( "1.3.0" )
  24. def sprand(numRows: Int, numCols: Int, density: Double, rng: Random): Matrix

    Permalink

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

    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

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

    Annotations
    @Since( "1.3.0" )
  25. def sprandn(numRows: Int, numCols: Int, density: Double, rng: Random): Matrix

    Permalink

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

    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

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

    Annotations
    @Since( "1.3.0" )
  26. final def synchronized[T0](arg0: ⇒ T0): T0

    Permalink
    Definition Classes
    AnyRef
  27. def toString(): String

    Permalink
    Definition Classes
    AnyRef → Any
  28. def vertcat(matrices: Array[Matrix]): Matrix

    Permalink

    Vertically concatenate a sequence of matrices.

    Vertically concatenate a sequence of matrices. The returned matrix will be in the format the matrices are supplied in. Supplying a mix of dense and sparse matrices will result in a sparse matrix. If the Array is empty, an empty DenseMatrix will be returned.

    matrices

    array of matrices

    returns

    a single Matrix composed of the matrices that were vertically concatenated

    Annotations
    @Since( "1.3.0" )
  29. final def wait(): Unit

    Permalink
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  30. final def wait(arg0: Long, arg1: Int): Unit

    Permalink
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  31. final def wait(arg0: Long): Unit

    Permalink
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  32. def zeros(numRows: Int, numCols: Int): Matrix

    Permalink

    Generate a Matrix consisting of zeros.

    Generate a Matrix consisting of zeros.

    numRows

    number of rows of the matrix

    numCols

    number of columns of the matrix

    returns

    Matrix with size numRows x numCols and values of zeros

    Annotations
    @Since( "1.2.0" )

Inherited from AnyRef

Inherited from Any

Ungrouped