Spark 3.5.1 ScalaDoc - org.apache.spark.ml.linalg.Matrices

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

Creates a column-major dense matrix.

numRows: number of rows
numCols: number of columns
values: matrix entries in column major

Annotations: @Since( "2.0.0" )

def diag(vector: Vector): Matrix

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( "2.0.0" )

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def eye(n: Int): Matrix

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( "2.0.0" )

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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

Annotations: @Since( "2.0.0" )

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

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" )

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

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" )

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

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" )

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.

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( "2.0.0" )

def speye(n: Int): Matrix

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" )

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

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" )

def sprandn(numRows: Int, numCols: Int, density: Double, rng: Random): Matrix

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( "2.0.0" )

final def synchronized[T0](arg0: ⇒ T0): T0

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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

Annotations: @Since( "2.0.0" )

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

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( "2.0.0" )

Packages

Matrices

object Matrices

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