DenseMatrix

Dense Matrix Documentation

Description

A Dense Matrix class that internally represents values as a contiguous array.

When a method fails, it will return null.

Methods

Method	Description
Static Methods
static DenseMatrix from_packed_array(from, rows, columns)	From is a PackedFloat64Array containing the data in row-major order. Rows and columns specify the dimensions of the matrix to be created.
static DenseMatrix identity(size)	Creates a square identity matrix of the given size.
static DenseMatrix zero(size)	Creates a square zero matrix of the given size.
Data Manipulation
void set_dimensions(rows, columns)	Enlarges or shrinks the matrix to the dimensions. This method will truncate or zero pad if there is existing data.
Vector2i get_dimensions()	Returns a Vector2i(), with x = rows, y = columns of the matrix
void set_element(row, column, value)	Sets the cell in the matrix to the specified value.
float get_element(row, column)	Returns the value of the cell.
DenseMatrix tranposed()	Returns a transposed version of the matrix.
DenseMatrix clone()	Returns an identical copy of the matrix.
PackedFloat64Array to_packed_array()	Returns the matrix elements as a packed array, in row-major order.
SparseMatrix to_sparse(zero_threshold)	Returns a SparseMatrix with equivalent non-zeros. Any value less than or equal to zero_threshold are treated as zeros of the SparseMatrix.
Algebra Methods
DenseMatrix multiply_dense(other)	Multiplies the two dense matrices together, returning the result, with other on the RHS of the multiplication.
DenseMatrix multiply_sparse(other)	Multiplies the dense matrix with a sparse matrix, returning a dense result.
VectorN multiply_vector(vector)	Does a vector multiplication, with the vector treated as a column vector on the RHS.
DenseMatrix add_dense(other)	Adds two DenseMatrix's, and returns the result.
DenseMatrix subtract_dense(other)	Subtracts two DenseMatrix's, and returns the result.
DenseMatrix add_sparse(other)	Adds the DenseMatrix to the SparseMatrix other, and returns a DenseMatrix.
DenseMatrix subtract_sparse(other)	Subtracts the SparseMatrix from the DenseMatrix, returning a DenseMatrix.
void multiply_scalar_in_place(scalar)	Multiplies all values of the matrix by the scalar. This updates the DenseMatrix in-place.
void add_sparse_in_place(other)	Add the SparseMatrix (other) to the DenseMatrix, in place.
void subtract_sparse_in_place(other)	Subtracts the SparseMatrix (other) from the DenseMatrix, in place.
void add_dense_in_place(other)	Add the DenseMatrix (other) to the DenseMatrix, in place.
void subtract_dense_in_place(other)	Subtracts the DenseMatrix (other) from the DenseMatrix, in place.
DenseMatrix solve(B)	If "A" is the matrix object, then this method solves the matrix equation Ax=B, where 'B' is the parameter, and 'x' is the return value. This is solved using Gaussian Elimination. To solve for a vector instead of a matrix, do solve(vector.column_vector()), to convert the vector to the appropriate column matrix.
VectorN solve_iterative_cg(B, initial_guess, max_iterations)	This performs an iterative solve using the Conjugate Gradient Method, starting from the initial_guess. This method is guaranteed to converge on Positive-Definite matrices, but may converge otherwise as well. If initial_guess is null, a zero vector is chosen by default. If max_iterations is negative, then it will be ignored.
DenseMatrix inverse()	Performs an inverse, and returns it. This is equivalent to matrix.solve(DenseMatrix.identity(matrix.get_dimensions().x)).
double norm_squared()	Returns the Frobenius norm squared (equal to summing all values squared).
double norm()	Returns the Frobenius norm (equal to the square root of summing all values squared).