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org.apache.spark.mllib.linalg

Matrices

Related Doc: package linalg

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object Matrices

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

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@Since( "1.0.0" )
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Matrices.scala
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  1. final def !=(arg0: Any): Boolean

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  2. final def ##(): Int

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  3. final def ==(arg0: Any): Boolean

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  4. final def asInstanceOf[T0]: T0

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  5. def clone(): AnyRef

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  6. def dense(numRows: Int, numCols: Int, values: Array[Double]): Matrix

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    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

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

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    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

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

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  9. def equals(arg0: Any): Boolean

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  10. def eye(n: Int): Matrix

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    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

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

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  12. def fromML(m: ml.linalg.Matrix): Matrix

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    Convert new linalg type to spark.mllib type.

    Convert new linalg type to spark.mllib type. Light copy; only copies references

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    @Since( "2.0.0" )
  13. final def getClass(): Class[_]

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  14. def hashCode(): Int

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  15. def horzcat(matrices: Array[Matrix]): Matrix

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    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

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

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  17. final def ne(arg0: AnyRef): Boolean

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  18. final def notify(): Unit

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  19. final def notifyAll(): Unit

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  20. def ones(numRows: Int, numCols: Int): Matrix

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    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" )
  21. def rand(numRows: Int, numCols: Int, rng: Random): Matrix

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    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" )
  22. def randn(numRows: Int, numCols: Int, rng: Random): Matrix

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    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)

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

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    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" )
  24. def speye(n: Int): Matrix

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    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" )
  25. def sprand(numRows: Int, numCols: Int, density: Double, rng: Random): Matrix

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

    Generate a SparseMatrix consisting of i.i.d. uniform 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" )
  26. def sprandn(numRows: Int, numCols: Int, density: Double, rng: Random): Matrix

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    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)

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

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  28. def toString(): String

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  29. def vertcat(matrices: Array[Matrix]): Matrix

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    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

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

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  31. final def wait(arg0: Long, arg1: Int): Unit

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  32. final def wait(arg0: Long): Unit

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  33. def zeros(numRows: Int, numCols: Int): Matrix

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    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" )

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