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object Matrices

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

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@Since( "2.0.0" )
Source
Matrices.scala
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  1. final def !=(arg0: Any): Boolean
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  2. final def ##(): Int
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  6. def dense(numRows: Int, numCols: Int, values: Array[Double]): Matrix

    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( "2.0.0" )
  7. def diag(vector: Vector): Matrix

    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( "2.0.0" )
  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

    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( "2.0.0" )
  11. final def getClass(): Class[_]
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  12. def hashCode(): Int
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  13. def horzcat(matrices: Array[Matrix]): Matrix

    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( "2.0.0" )
  14. final def isInstanceOf[T0]: Boolean
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  17. final def notifyAll(): Unit
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  18. def ones(numRows: Int, numCols: Int): Matrix

    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( "2.0.0" )
  19. def rand(numRows: Int, numCols: Int, rng: Random): Matrix

    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( "2.0.0" )
  20. def randn(numRows: Int, numCols: Int, rng: Random): Matrix

    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( "2.0.0" )
  21. def sparse(numRows: Int, numCols: Int, colPtrs: Array[Int], rowIndices: Array[Int], values: Array[Double]): Matrix

    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

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    @Since( "2.0.0" )
  22. def speye(n: Int): Matrix

    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( "2.0.0" )
  23. def sprand(numRows: Int, numCols: Int, density: Double, rng: Random): Matrix

    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( "2.0.0" )
  24. def sprandn(numRows: Int, numCols: Int, density: Double, rng: Random): Matrix

    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( "2.0.0" )
  25. final def synchronized[T0](arg0: ⇒ T0): T0
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  26. def toString(): String
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  27. def vertcat(matrices: Array[Matrix]): Matrix

    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( "2.0.0" )
  28. final def wait(arg0: Long, arg1: Int): Unit
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  30. final def wait(): Unit
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  31. def zeros(numRows: Int, numCols: Int): Matrix

    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

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    @Since( "2.0.0" )

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