class SparseMatrix extends 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]
.
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- @Since( "1.2.0" ) @SQLUserDefinedType()
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Instance Constructors
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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, androwIndices
behave as colIndices, andvalues
are stored in row major.
- Annotations
- @Since( "1.3.0" )
Value Members
-
final
def
!=(arg0: Any): Boolean
- Definition Classes
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-
final
def
##(): Int
- Definition Classes
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-
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[lang]
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- @throws( ... ) @native()
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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]
- 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[lang]
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- @throws( classOf[java.lang.Throwable] )
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final
def
getClass(): Class[_]
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- @native()
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def
hashCode(): Int
- Definition Classes
- SparseMatrix → AnyRef → Any
-
final
def
isInstanceOf[T0]: Boolean
- Definition Classes
- Any
-
val
isTransposed: Boolean
Flag that keeps track whether the matrix is transposed or not.
Flag that keeps track whether the matrix is transposed or not. False by default.
- Definition Classes
- SparseMatrix → Matrix
- Annotations
- @Since( "1.3.0" )
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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" )
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final
def
ne(arg0: AnyRef): Boolean
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final
def
notify(): Unit
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- @native()
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final
def
notifyAll(): Unit
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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]
- 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 givenSparseMatrix
.Generate a
DenseMatrix
from the givenSparseMatrix
. 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]
- Annotations
- @Since( "1.2.0" )
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final
def
wait(): Unit
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final
def
wait(arg0: Long, arg1: Int): Unit
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final
def
wait(arg0: Long): Unit
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