DenseMatrix (Spark 2.4.1 JavaDoc)

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

All Methods Static Methods Instance Methods Concrete 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
    
    Returns:
    
    (undocumented)
  - 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)

Class DenseMatrix

Constructor Summary

Method Summary

Methods inherited from class Object

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

Constructor Detail

DenseMatrix

DenseMatrix

Method Detail

zeros

ones

eye

rand

randn

diag

fromML

toArray

rowIter

multiply

multiply

multiply

toString

toString

numRows

numCols

values

isTransposed

equals

hashCode

apply

copy

transpose

numNonzeros

numActives

toSparse

colIter

asML