org.apache.spark.mllib.linalg

Class DenseMatrix

Object

org.apache.spark.mllib.linalg.DenseMatrix

All Implemented Interfaces:

java.io.Serializable, Matrix

public class DenseMatrix
extends Object
implements Matrix

Column-major dense matrix. The entry values are stored in a single array of doubles with columns listed in sequence. For example, the following matrix

   1.0 2.0
   3.0 4.0
   5.0 6.0
 

is stored as [1.0, 3.0, 5.0, 2.0, 4.0, 6.0].

param: numRows number of rows param: numCols number of columns param: values matrix entries in column major if not transposed or in row major otherwise param: isTransposed whether the matrix is transposed. If true, values stores the matrix in row major.

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
DenseMatrix(int numRows, int numCols, double[] values) Column-major dense matrix.
DenseMatrix(int numRows, int numCols, double[] values, boolean isTransposed)

Method Summary

Methods

Modifier and Type	Method and Description
double	apply(int i, int j) Gets the (i, j)-th element.
DenseMatrix	asML() Convert this matrix to the new mllib-local representation.
scala.collection.Iterator<Vector>	colIter() Returns an iterator of column vectors.
DenseMatrix	copy() Get a deep copy of the matrix.
static DenseMatrix	diag(Vector vector) Generate a diagonal matrix in DenseMatrix format from the supplied values.
boolean	equals(Object o)
static DenseMatrix	eye(int n) Generate an Identity Matrix in DenseMatrix format.
static DenseMatrix	fromML(DenseMatrix m) Convert new linalg type to spark.mllib type.
int	hashCode()
boolean	isTransposed() Flag that keeps track whether the matrix is transposed or not.
static DenseMatrix	multiply(DenseMatrix y)
static DenseVector	multiply(DenseVector y)
static DenseVector	multiply(Vector y)
int	numActives() Find the number of values stored explicitly.
int	numCols() Number of columns.
int	numNonzeros() Find the number of non-zero active values.
int	numRows() Number of rows.
static DenseMatrix	ones(int numRows, int numCols) Generate a DenseMatrix consisting of ones.
static DenseMatrix	rand(int numRows, int numCols, java.util.Random rng) Generate a DenseMatrix consisting of i.i.d. uniform random numbers.
static DenseMatrix	randn(int numRows, int numCols, java.util.Random rng) Generate a DenseMatrix consisting of i.i.d. gaussian random numbers.
static scala.collection.Iterator<Vector>	rowIter()
static double[]	toArray()
SparseMatrix	toSparse() Generate a SparseMatrix from the given DenseMatrix.
static String	toString()
static String	toString(int maxLines, int maxLineWidth)
DenseMatrix	transpose() Transpose the Matrix.
double[]	values()
static DenseMatrix	zeros(int numRows, int numCols) Generate a DenseMatrix consisting of zeros.

Methods inherited from class Object

getClass, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface org.apache.spark.mllib.linalg.Matrix

multiply, multiply, multiply, rowIter, toArray, toString, toString

Constructor Detail

DenseMatrix

public DenseMatrix(int numRows,
           int numCols,
           double[] values,
           boolean isTransposed)

DenseMatrix

public DenseMatrix(int numRows,
           int numCols,
           double[] values)

Column-major dense matrix. The entry values are stored in a single array of doubles with columns listed in sequence. For example, the following matrix

   1.0 2.0
   3.0 4.0
   5.0 6.0
 

is stored as [1.0, 3.0, 5.0, 2.0, 4.0, 6.0].

Parameters:

numRows - number of rows

numCols - number of columns

values - matrix entries in column major

Method Detail

zeros

public static DenseMatrix zeros(int numRows,
                int numCols)

Generate a DenseMatrix consisting of zeros.

Parameters:

numRows - number of rows of the matrix

numCols - number of columns of the matrix

Returns:

DenseMatrix with size numRows x numCols and values of zeros

ones

public static DenseMatrix ones(int numRows,
               int numCols)

Generate a DenseMatrix consisting of ones.

Parameters:

numRows - number of rows of the matrix

numCols - number of columns of the matrix

Returns:

DenseMatrix with size numRows x numCols and values of ones

eye

public static DenseMatrix eye(int n)

Generate an Identity Matrix in DenseMatrix format.

Parameters:

n - number of rows and columns of the matrix

Returns:

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

rand

public static DenseMatrix rand(int numRows,
               int numCols,
               java.util.Random rng)

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

Parameters:

numRows - number of rows of the matrix

numCols - number of columns of the matrix

rng - a random number generator

Returns:

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

randn

public static DenseMatrix randn(int numRows,
                int numCols,
                java.util.Random rng)

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

Parameters:

numRows - number of rows of the matrix

numCols - number of columns of the matrix

rng - a random number generator

Returns:

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

diag

public static DenseMatrix diag(Vector vector)

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

Parameters:

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

Returns:

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

fromML

public static DenseMatrix fromML(DenseMatrix m)

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

Parameters:

m - (undocumented)

Returns:

(undocumented)

toArray

public static double[] toArray()

rowIter

public static scala.collection.Iterator<Vector> rowIter()

multiply

public static DenseMatrix multiply(DenseMatrix y)

multiply

public static DenseVector multiply(DenseVector y)

multiply

public static DenseVector multiply(Vector y)

toString

public static String toString()

toString

public static String toString(int maxLines,
              int maxLineWidth)

numRows

public int numRows()

Description copied from interface: Matrix

Number of rows.

Specified by:

numRows in interface Matrix

numCols

public int numCols()

Description copied from interface: Matrix

Number of columns.

Specified by:

numCols in interface Matrix

values

public double[] values()

isTransposed

public boolean isTransposed()

Description copied from interface: Matrix

Flag that keeps track whether the matrix is transposed or not. False by default.

Specified by:

isTransposed in interface Matrix

equals

public boolean equals(Object o)

Overrides:

equals in class Object

hashCode

public int hashCode()

Overrides:

hashCode in class Object

apply

public double apply(int i,
           int j)

Description copied from interface: Matrix

Gets the (i, j)-th element.

Specified by:

apply in interface Matrix

copy

public DenseMatrix copy()

Description copied from interface: Matrix

Get a deep copy of the matrix.

Specified by:

copy in interface Matrix

transpose

public DenseMatrix transpose()

Description copied from interface: Matrix

Transpose the Matrix. Returns a new `Matrix` instance sharing the same underlying data.

Specified by:

transpose in interface Matrix

numNonzeros

public int numNonzeros()

Description copied from interface: Matrix

Find the number of non-zero active values.

Specified by:

numNonzeros in interface Matrix

Returns:

(undocumented)

numActives

public int numActives()

Description copied from interface: Matrix

Find the number of values stored explicitly. These values can be zero as well.

Specified by:

numActives in interface Matrix

Returns:

(undocumented)

toSparse

public SparseMatrix toSparse()

Generate a SparseMatrix from the given DenseMatrix. The new matrix will have isTransposed set to false.

Returns:

(undocumented)

colIter

public scala.collection.Iterator<Vector> colIter()

Description copied from interface: Matrix

Returns an iterator of column vectors. This operation could be expensive, depending on the underlying storage.

Specified by:

colIter in interface Matrix

Returns:

(undocumented)

asML

public DenseMatrix asML()

Description copied from interface: Matrix

Convert this matrix to the new mllib-local representation. This does NOT copy the data; it copies references.

Specified by:

asML in interface Matrix

Returns:

(undocumented)