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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- 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("1.0.0")
- 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 sizevalues.length
xvalues.length
andvalues
on the diagonal
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- @Since("1.2.0")
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- 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 sizen
xn
and values of ones on the diagonal
- Annotations
- @Since("1.2.0")
- def fromML(m: ml.linalg.Matrix): Matrix
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")
- final def getClass(): Class[_ <: AnyRef]
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- def hashCode(): Int
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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
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- @Since("1.3.0")
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- 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 sizenumRows
xnumCols
and values of ones
- Annotations
- @Since("1.2.0")
- def rand(numRows: Int, numCols: Int, rng: Random): Matrix
Generate a
DenseMatrix
consisting ofi.i.d.
uniform random numbers.Generate a
DenseMatrix
consisting ofi.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 sizenumRows
xnumCols
and values in U(0, 1)
- Annotations
- @Since("1.2.0")
- def randn(numRows: Int, numCols: Int, rng: Random): Matrix
Generate a
DenseMatrix
consisting ofi.i.d.
gaussian random numbers.Generate a
DenseMatrix
consisting ofi.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 sizenumRows
xnumCols
and values in N(0, 1)
- Annotations
- @Since("1.2.0")
- 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.
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("1.2.0")
- 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 sizen
xn
and values of ones on the diagonal
- Annotations
- @Since("1.3.0")
- def sprand(numRows: Int, numCols: Int, density: Double, rng: Random): Matrix
Generate a
SparseMatrix
consisting ofi.i.d.
uniform random numbers.Generate a
SparseMatrix
consisting ofi.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 sizenumRows
xnumCols
and values in U(0, 1)
- Annotations
- @Since("1.3.0")
- def sprandn(numRows: Int, numCols: Int, density: Double, rng: Random): Matrix
Generate a
SparseMatrix
consisting ofi.i.d.
gaussian random numbers.Generate a
SparseMatrix
consisting ofi.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 sizenumRows
xnumCols
and values in N(0, 1)
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- @Since("1.3.0")
- 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
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- @Since("1.3.0")
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- 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 sizenumRows
xnumCols
and values of zeros
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- @Since("1.2.0")
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- Deprecated
(Since version 9)