SparseMatrix

Instance Constructors

new SparseMatrix(numRows: Int, numCols: Int, colPtrs: Array[Int], rowIndices: Array[Int], values: Array[Double])

Column-major sparse matrix.
Column-major sparse matrix. The entry values are stored in Compressed Sparse Column (CSC) format. For example, the following matrix
```
1.0 0.0 4.0
0.0 3.0 5.0
2.0 0.0 6.0
```
is stored as values: [1.0, 2.0, 3.0, 4.0, 5.0, 6.0], rowIndices=[0, 2, 1, 0, 1, 2], colPointers=[0, 2, 3, 6].
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. They must be in strictly increasing order for each column
values
non-zero matrix entries in column major

Annotations
@Since( "1.2.0" )
new SparseMatrix(numRows: Int, numCols: Int, colPtrs: Array[Int], rowIndices: Array[Int], values: Array[Double], isTransposed: Boolean)

numRows
number of rows
numCols
number of columns
colPtrs
the index corresponding to the start of a new column (if not transposed)
rowIndices
the row index of the entry (if not transposed). They must be in strictly increasing order for each column
values
nonzero matrix entries in column major (if not transposed)
isTransposed
whether the matrix is transposed. If true, the matrix can be considered Compressed Sparse Row (CSR) format, where colPtrs behaves as rowPtrs, and rowIndices behave as colIndices, and values are stored in row major.

Annotations
@Since( "1.3.0" )

Value Members

final def !=(arg0: Any): Boolean

Definition Classes
AnyRef → Any
final def ##(): Int

Definition Classes
AnyRef → Any
final def ==(arg0: Any): Boolean

Definition Classes
AnyRef → Any
def apply(i: Int, j: Int): Double

Gets the (i, j)-th element.
Gets the (i, j)-th element.

Definition Classes
SparseMatrix → Matrix
Annotations
@Since( "1.3.0" )
final def asInstanceOf[T0]: T0

Definition Classes
Any
def asML: ml.linalg.SparseMatrix

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

Definition Classes
SparseMatrix → Matrix
Annotations
@Since( "2.0.0" )
def clone(): AnyRef

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( ... )
def colIter: Iterator[Vector]

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

Definition Classes
SparseMatrix → Matrix
Annotations
@Since( "2.0.0" )
val colPtrs: Array[Int]

the index corresponding to the start of a new column (if not transposed)
the index corresponding to the start of a new column (if not transposed)

Annotations
@Since( "1.2.0" )
def copy: SparseMatrix

Get a deep copy of the matrix.
Get a deep copy of the matrix.

Definition Classes
SparseMatrix → Matrix
Annotations
@Since( "1.4.0" )
final def eq(arg0: AnyRef): Boolean

Definition Classes
AnyRef
def equals(o: Any): Boolean

Definition Classes
SparseMatrix → AnyRef → Any
def finalize(): Unit

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( classOf[java.lang.Throwable] )
final def getClass(): Class[_]

Definition Classes
AnyRef → Any
def hashCode(): Int

Definition Classes
SparseMatrix → AnyRef → Any
final def isInstanceOf[T0]: Boolean

Definition Classes
Any
val isTransposed: Boolean

whether the matrix is transposed.
whether the matrix is transposed. If true, the matrix can be considered Compressed Sparse Row (CSR) format, where colPtrs behaves as rowPtrs, and rowIndices behave as colIndices, and values are stored in row major.

Definition Classes
SparseMatrix → Matrix
Annotations
@Since( "1.3.0" )
def multiply(y: Vector): DenseVector

Convenience method for Matrix-Vector multiplication.
Convenience method for Matrix-Vector multiplication.

Definition Classes
Matrix
Annotations
@Since( "1.4.0" )
def multiply(y: DenseVector): DenseVector

Convenience method for Matrix-DenseVector multiplication.
Convenience method for Matrix-DenseVector multiplication. For binary compatibility.

Definition Classes
Matrix
Annotations
@Since( "1.2.0" )
def multiply(y: DenseMatrix): DenseMatrix

Convenience method for Matrix-DenseMatrix multiplication.
Convenience method for Matrix-DenseMatrix multiplication.

Definition Classes
Matrix
Annotations
@Since( "1.2.0" )
final def ne(arg0: AnyRef): Boolean

Definition Classes
AnyRef
final def notify(): Unit

Definition Classes
AnyRef
final def notifyAll(): Unit

Definition Classes
AnyRef
def numActives: Int

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

Definition Classes
SparseMatrix → Matrix
Annotations
@Since( "1.5.0" )
val numCols: Int

number of columns
number of columns

Definition Classes
SparseMatrix → Matrix
Annotations
@Since( "1.2.0" )
def numNonzeros: Int

Find the number of non-zero active values.
Find the number of non-zero active values.

Definition Classes
SparseMatrix → Matrix
Annotations
@Since( "1.5.0" )
val numRows: Int

number of rows
number of rows

Definition Classes
SparseMatrix → Matrix
Annotations
@Since( "1.2.0" )
val rowIndices: Array[Int]

the row index of the entry (if not transposed).
the row index of the entry (if not transposed). They must be in strictly increasing order for each column

Annotations
@Since( "1.2.0" )
def rowIter: Iterator[Vector]

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

Definition Classes
Matrix
Annotations
@Since( "2.0.0" )
final def synchronized[T0](arg0: ⇒ T0): T0

Definition Classes
AnyRef
def toArray: Array[Double]

Converts to a dense array in column major.
Converts to a dense array in column major.

Definition Classes
Matrix
Annotations
@Since( "1.0.0" )
def toDense: DenseMatrix

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

Annotations
@Since( "1.3.0" )
def toString(maxLines: Int, maxLineWidth: Int): String

A human readable representation of the matrix with maximum lines and width
A human readable representation of the matrix with maximum lines and width

Definition Classes
Matrix
Annotations
@Since( "1.4.0" )
def toString(): String

A human readable representation of the matrix
A human readable representation of the matrix

Definition Classes
Matrix → AnyRef → Any
def transpose: SparseMatrix

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

Definition Classes
SparseMatrix → Matrix
Annotations
@Since( "1.3.0" )
val values: Array[Double]

nonzero matrix entries in column major (if not transposed)
nonzero matrix entries in column major (if not transposed)

Annotations
@Since( "1.2.0" )
final def wait(): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )
final def wait(arg0: Long, arg1: Int): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )
final def wait(arg0: Long): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )

Related Docs: object SparseMatrix | package linalg

class SparseMatrix extends Matrix

Instance Constructors

new SparseMatrix(numRows: Int, numCols: Int, colPtrs: Array[Int], rowIndices: Array[Int], values: Array[Double])

new SparseMatrix(numRows: Int, numCols: Int, colPtrs: Array[Int], rowIndices: Array[Int], values: Array[Double], isTransposed: Boolean)

Value Members

final def !=(arg0: Any): Boolean

final def ##(): Int

final def ==(arg0: Any): Boolean

def apply(i: Int, j: Int): Double

final def asInstanceOf[T0]: T0

def asML: ml.linalg.SparseMatrix

def clone(): AnyRef

def colIter: Iterator[Vector]

val colPtrs: Array[Int]

def copy: SparseMatrix

final def eq(arg0: AnyRef): Boolean

def equals(o: Any): Boolean

def finalize(): Unit

final def getClass(): Class[_]

def hashCode(): Int

final def isInstanceOf[T0]: Boolean

val isTransposed: Boolean

def multiply(y: Vector): DenseVector

def multiply(y: DenseVector): DenseVector

def multiply(y: DenseMatrix): DenseMatrix

final def ne(arg0: AnyRef): Boolean

final def notify(): Unit

final def notifyAll(): Unit

def numActives: Int

val numCols: Int

def numNonzeros: Int

val numRows: Int

val rowIndices: Array[Int]

def rowIter: Iterator[Vector]

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

def toArray: Array[Double]

def toDense: DenseMatrix

def toString(maxLines: Int, maxLineWidth: Int): String

def toString(): String

def transpose: SparseMatrix

val values: Array[Double]

final def wait(): Unit

final def wait(arg0: Long, arg1: Int): Unit

final def wait(arg0: Long): Unit

Inherited from Matrix

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

Ungrouped