Package de.labathome.trustconstr.matrix

Class SparseMatrix

java.lang.Object

de.labathome.trustconstr.matrix.Matrix

de.labathome.trustconstr.matrix.SparseMatrix

public class SparseMatrix
extends Matrix

Sparse matrix backed by a Dictionary-of-Keys (DOK) representation: a HashMap keyed by the encoded (row, col) index. Supports cheap incremental setAsDouble(double, long, long) (the equivalent of scipy's lil_matrix build phase) and converts to CSRMatrix for compute-heavy paths via toCSR().

Compute kernels (mtimes(Matrix), plus(Matrix) etc.) materialise to dense or convert to CSR internally -- no attempt is made to keep results sparse. The trust-constr port only relies on sparsity in a handful of well-known places (Jacobian storage and the AUGMENTED_SYSTEM KKT factorization, both of which already drop into the CSR fast paths).

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
static final class	SparseMatrix.Factory	Static factories that produce SparseMatrix instances.

Constructor Summary

Constructors

Constructor	Description
SparseMatrix(int rows, int cols)	Allocate a fresh empty sparse matrix.

Method Summary

Modifier and Type	Method	Description
Matrix	abs()
Matrix	copy()
Matrix	divide(double alpha)
Matrix	divide(Matrix elementwise)
double	getAsDouble(long row, long col)
long	getColumnCount()
long	getRowCount()
boolean	isSparse()
Matrix	minus(Matrix other)
Matrix	mtimes(Matrix other)
int	nnz()
double	norm2()
double	normInf()
Matrix	plus(Matrix other)
void	setAsDouble(double v, long row, long col)
Matrix	times(double alpha)
Matrix	times(Matrix elementwise)
CSRMatrix	toCSR()	Materialise this sparse matrix to a CSRMatrix (canonical CSR form: column indices sorted within each row, no explicit zeros).
Matrix	transpose()

Methods inherited from class de.labathome.trustconstr.matrix.Matrix

absInPlace, doubleValue, equalsContent, fill, getSize, isColumnVector, isRowVector, mapAdd, minus, normF, plus, rank, selectColumns, solve, subMatrix, toColumnArray, toDoubleArray

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Details

SparseMatrix

public SparseMatrix(int rows,
 int cols)

Allocate a fresh empty sparse matrix.

Parameters:

rows - number of rows

cols - number of columns

Method Details

isSparse

public boolean isSparse()

Overrides:

isSparse in class Matrix

Returns:

true if this is a sparse matrix

getRowCount

public long getRowCount()

Specified by:

getRowCount in class Matrix

Returns:

number of rows

getColumnCount

public long getColumnCount()

Specified by:

getColumnCount in class Matrix

Returns:

number of columns

getAsDouble

public double getAsDouble(long row,
 long col)

Specified by:

getAsDouble in class Matrix

Parameters:

row - 0-based row index

col - 0-based column index

Returns:

entry at (row, col)

setAsDouble

public void setAsDouble(double v,
 long row,
 long col)

Specified by:

setAsDouble in class Matrix

Parameters:

v - value to store

row - 0-based row index

col - 0-based column index

nnz

public int nnz()

Returns:

number of stored (non-zero) entries

toCSR

public CSRMatrix toCSR()

Materialise this sparse matrix to a CSRMatrix (canonical CSR form: column indices sorted within each row, no explicit zeros).

Returns:

a CSR view of the same content

copy

public Matrix copy()

Specified by:

copy in class Matrix

Returns:

a deep copy of this matrix

mtimes

public Matrix mtimes(Matrix other)

Specified by:

mtimes in class Matrix

Parameters:

other - right operand

Returns:

matrix product this * other

plus

public Matrix plus(Matrix other)

Specified by:

plus in class Matrix

Parameters:

other - right operand

Returns:

element-wise sum this + other

minus

public Matrix minus(Matrix other)

Specified by:

minus in class Matrix

Parameters:

other - right operand

Returns:

element-wise difference this - other

times

public Matrix times(double alpha)

Specified by:

times in class Matrix

Parameters:

alpha - scalar

Returns:

alpha * this

times

public Matrix times(Matrix elementwise)

Specified by:

times in class Matrix

Parameters:

elementwise - same-shape factor

Returns:

Hadamard product this .* elementwise

divide

public Matrix divide(double alpha)

Specified by:

divide in class Matrix

Parameters:

alpha - scalar

Returns:

this / alpha

divide

public Matrix divide(Matrix elementwise)

Specified by:

divide in class Matrix

Parameters:

elementwise - same-shape divisor

Returns:

Hadamard division this ./ elementwise

transpose

public Matrix transpose()

Specified by:

transpose in class Matrix

Returns:

the transpose of this matrix

abs

public Matrix abs()

Specified by:

abs in class Matrix

Returns:

element-wise absolute value as a fresh matrix

norm2

public double norm2()

Specified by:

norm2 in class Matrix

Returns:

Frobenius norm

normInf

public double normInf()

Specified by:

normInf in class Matrix

Returns:

infinity-norm (largest absolute entry)