public class LinkedSparseMatrix extends AbstractMatrix
n x m
Matrix with z
elements that has a typical
O(z / m)
insertion / lookup cost and an iterator that traverses
columns then rows: a good fit for unstructured sparse matrices. A secondary
link maintains fast transpose iteration.
However, memory requirements (
1 instance (8 bytes), 2 int (16 bytes), 2 ref (16 bytes), 1 double (8 bytes) = 48 bytes
per matrix element, plus 8 x numcol + 8 x numrow bytes
s for the
cache) are slightly higher than structured sparse matrix storage. Note that
on 32 bit JVMs, or on 64 bit JVMs with CompressedOops enabled, references and ints only cost 4 bytes each,
bringing the cost to 28 bytes per element.Matrix.Norm
numColumns, numRows
Constructor and Description |
---|
LinkedSparseMatrix(int numRows,
int numColumns) |
LinkedSparseMatrix(Matrix A) |
LinkedSparseMatrix(MatrixVectorReader r) |
Modifier and Type | Method and Description |
---|---|
Matrix |
copy()
Creates a deep copy of the matrix
|
double |
get(int row,
int column)
Returns
A(row,column) |
Iterator<MatrixEntry> |
iterator() |
Matrix |
multAdd(double alpha,
Matrix B,
Matrix C)
C = alpha*A*B + C |
Vector |
multAdd(double alpha,
Vector x,
Vector y)
y = alpha*A*x + y |
Matrix |
scale(double alpha)
A = alpha*A |
void |
set(int row,
int column,
double value)
A(row,column) = value |
Matrix |
transABmultAdd(double alpha,
Matrix B,
Matrix C)
C = alpha*AT*BT + C |
Matrix |
transAmultAdd(double alpha,
Matrix B,
Matrix C)
C = alpha*AT*B + C |
Matrix |
transBmultAdd(double alpha,
Matrix B,
Matrix C)
C = alpha*A*BT + C |
Vector |
transMultAdd(double alpha,
Vector x,
Vector y)
y = alpha*AT*x + y |
Matrix |
transpose()
Transposes the matrix in-place.
|
Matrix |
zero()
Zeros all the entries in the matrix, while preserving any underlying
structure.
|
add, add, add, check, checkMultAdd, checkMultAdd, checkRank1, checkRank1, checkRank2, checkRank2, checkSize, checkSolve, checkSolve, checkTransABmultAdd, checkTransAmultAdd, checkTransBmultAdd, checkTransMultAdd, checkTranspose, checkTranspose, checkTransRank1, checkTransRank2, isSquare, max, max, mult, mult, mult, mult, multAdd, multAdd, norm, norm1, normF, normInf, numColumns, numRows, rank1, rank1, rank1, rank1, rank1, rank1, rank2, rank2, rank2, rank2, set, set, solve, solve, toString, transABmult, transABmult, transABmultAdd, transAmult, transAmult, transAmultAdd, transBmult, transBmult, transBmultAdd, transMult, transMult, transMultAdd, transpose, transRank1, transRank1, transRank2, transRank2, transSolve, transSolve
clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait
forEach, spliterator
public LinkedSparseMatrix(int numRows, int numColumns)
public LinkedSparseMatrix(Matrix A)
public LinkedSparseMatrix(MatrixVectorReader r) throws IOException
IOException
public Matrix zero()
Matrix
zero
in interface Matrix
zero
in class AbstractMatrix
public double get(int row, int column)
Matrix
A(row,column)
get
in interface Matrix
get
in class AbstractMatrix
public void set(int row, int column, double value)
Matrix
A(row,column) = value
set
in interface Matrix
set
in class AbstractMatrix
public Iterator<MatrixEntry> iterator()
iterator
in interface Iterable<MatrixEntry>
iterator
in class AbstractMatrix
public Matrix scale(double alpha)
Matrix
A = alpha*A
scale
in interface Matrix
scale
in class AbstractMatrix
public Matrix copy()
Matrix
copy
in interface Matrix
copy
in class AbstractMatrix
public Matrix transpose()
Matrix
transpose
in interface Matrix
transpose
in class AbstractMatrix
public Vector multAdd(double alpha, Vector x, Vector y)
Matrix
y = alpha*A*x + y
multAdd
in interface Matrix
multAdd
in class AbstractMatrix
x
- Vector of size A.numColumns()
y
- Vector of size A.numRows()
public Vector transMultAdd(double alpha, Vector x, Vector y)
Matrix
y = alpha*AT*x + y
transMultAdd
in interface Matrix
transMultAdd
in class AbstractMatrix
x
- Vector of size A.numRows()
y
- Vector of size A.numColumns()
public Matrix multAdd(double alpha, Matrix B, Matrix C)
Matrix
C = alpha*A*B + C
multAdd
in interface Matrix
multAdd
in class AbstractMatrix
B
- Matrix such that B.numRows() == A.numColumns()
and B.numColumns() == C.numColumns()
C
- Matrix such that C.numRows() == A.numRows()
and
B.numColumns() == C.numColumns()
public Matrix transBmultAdd(double alpha, Matrix B, Matrix C)
Matrix
C = alpha*A*BT + C
transBmultAdd
in interface Matrix
transBmultAdd
in class AbstractMatrix
B
- Matrix such that B.numRows() == A.numRows()
and
B.numColumns() == C.numColumns()
C
- Matrix such that C.numRows() == A.numColumns()
and B.numColumns() == C.numColumns()
public Matrix transAmultAdd(double alpha, Matrix B, Matrix C)
Matrix
C = alpha*AT*B + C
transAmultAdd
in interface Matrix
transAmultAdd
in class AbstractMatrix
B
- Matrix such that B.numRows() == A.numRows()
and
B.numColumns() == C.numColumns()
C
- Matrix such that C.numRows() == A.numColumns()
and B.numColumns() == C.numColumns()
public Matrix transABmultAdd(double alpha, Matrix B, Matrix C)
Matrix
C = alpha*AT*BT + C
transABmultAdd
in interface Matrix
transABmultAdd
in class AbstractMatrix
B
- Matrix such that B.numColumns() == A.numRows()
and B.numRows() == C.numColumns()
C
- Matrix such that C.numRows() == A.numColumns()
and B.numRows() == C.numColumns()
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