Uses of Class mikera.matrixx.AMatrix (Vectorz 0.62.0 API)

Packages that use AMatrix
Package	Description
mikera.arrayz
mikera.arrayz.impl
mikera.matrixx
mikera.matrixx.algo
mikera.matrixx.decompose
mikera.matrixx.decompose.impl.bidiagonal
mikera.matrixx.decompose.impl.chol
mikera.matrixx.decompose.impl.eigen
mikera.matrixx.decompose.impl.hessenberg
mikera.matrixx.decompose.impl.lu
mikera.matrixx.decompose.impl.qr
mikera.matrixx.decompose.impl.svd
mikera.matrixx.impl
mikera.matrixx.solve
mikera.matrixx.solve.impl
mikera.matrixx.solve.impl.lu
mikera.matrixx.solve.impl.qr
mikera.transformz
mikera.transformz.impl
mikera.vectorz
mikera.vectorz.impl
mikera.vectorz.ops
mikera.vectorz.util

Uses of AMatrix in mikera.arrayz

Methods in mikera.arrayz that return AMatrix
Modifier and Type	Method and Description
`AMatrix`	INDArray.`broadcastLike(AMatrix target)` Broadcasts an array to match the shape of the target matrix

Methods in mikera.arrayz with parameters of type AMatrix
Modifier and Type	Method and Description
`AMatrix`	INDArray.`broadcastLike(AMatrix target)` Broadcasts an array to match the shape of the target matrix

Uses of AMatrix in mikera.arrayz.impl

Methods in mikera.arrayz.impl that return AMatrix
Modifier and Type	Method and Description
`AMatrix`	AbstractArray.`broadcastLike(AMatrix target)`

Methods in mikera.arrayz.impl with parameters of type AMatrix
Modifier and Type	Method and Description
`void`	AbstractArray.`addInnerProduct(AMatrix a, INDArray b)` Adds the inner product of a matrix and an array to this array
`AMatrix`	AbstractArray.`broadcastLike(AMatrix target)`

Uses of AMatrix in mikera.matrixx

Subclasses of AMatrix in mikera.matrixx
Modifier and Type	Class and Description
`class`	`Matrix` Standard MxN matrix class backed by a densely packed double[] array This is the most efficient Vectorz type for dense 2D matrices.
`class`	`Matrix11` Optimised 1x1 matrix implementation
`class`	`Matrix22` Specialised 2*2 Matrix for Vector2 maths, using primitive matrix elements
`class`	`Matrix33` Specialised 3*3 Matrix for Vector3 maths, using primitive matrix elements

Methods in mikera.matrixx that return AMatrix
Modifier and Type	Method and Description
`AMatrix`	IMatrix.`addCopy(AMatrix a)` Adds another matrix to this matrix, returning a new matrix
`AMatrix`	AMatrix.`addCopy(AMatrix a)`
`AMatrix`	IMatrix.`addCopy(AVector v)` Adds a vector to every row of this matrix, returning a new matrix
`AMatrix`	AMatrix.`addCopy(AVector v)`
`AMatrix`	AMatrix.`addCopy(double d)`
`AMatrix`	AMatrix.`applyOpCopy(Op op)`
`AMatrix`	AMatrix.`broadcastLike(AMatrix target)`
`AMatrix`	AMatrix.`clone()`
`AMatrix`	AMatrix.`copy()`
`static AMatrix`	Matrixx.`create(IMatrix m)` Creates a mutable copy of a matrix
`static AMatrix`	Matrixx.`create(Object... vs)` Creates a matrix using the given objects to generate individual rows
`static AMatrix`	Matrixx.`createFromVectors(INDArray... data)` Create a matrix using as array of vectors which represent the data for each row
`static AMatrix`	Matrixx.`createFromVectors(List<INDArray> data)` Create a matrix using a list of vectors as the data for each row
`static AMatrix`	Matrixx.`createIdentityMatrix(int dimensions)` Creates an identity matrix
`AMatrix`	Matrixx.`createInverse(AMatrix m)` Computes the inverse of a matrix.
`static AMatrix`	Matrixx.`createMutableIdentityMatrix(int dimensions)` Creates a fully mutable identity matrix
`static AMatrix`	Matrixx.`createRandomMatrix(int rows, int columns)` Creates a mutable matrix containing random double values in the range [0.0 , 1.0)
`static AMatrix`	Matrixx.`createRandomMatrix(int rows, int columns, Random rand)` Creates a mutable matrix containing random double values in the range [0.0 , 1.0)
`static AMatrix`	Matrixx.`createSparse(AMatrix m)` Creates a sparse matrix from the given matrix, ignoring zeros
`static AMatrix`	Matrixx.`createSparse(int columnCount, Index[] indexes, AVector[] weights)` Create a sparse array, given an Index of column positions and AVector of corresponding values for each row in the sparse array Performs a defensive copy of underlying data.
`static AMatrix`	Matrixx.`createSparse(Iterable<INDArray> slices)` Creates a sparse matrix using the given arrays as slices
`static AMatrix`	Matrixx.`createSparse(Object... slices)` Creates a sparse matrix using the given objects as slices
`static AMatrix`	Matrixx.`createSparseRows(AMatrix m)` Creates a SparseRowMatrix matrix from the given matrix, ignoring zeros
`AMatrix`	AMatrix.`dense()`
`AMatrix`	AMatrix.`ensureMutable()`
`AMatrix`	Matrix11.`exactClone()`
`abstract AMatrix`	AMatrix.`exactClone()`
`static AMatrix`	Matrixx.`extractLowerTriangular(AMatrix a)` Extracts a lower triangular matrix from a matrix
`static AMatrix`	Matrixx.`extractUpperTriangular(AMatrix a)` Extracts an upper triangular matrix from a matrix
`AMatrix`	IMatrix.`getTranspose()` Returns the transpose of this matrix.
`AMatrix`	AMatrix.`getTranspose()`
`AMatrix`	AMatrix.`getTransposeCopy()` Gets a mutable transposed clone of the matrix
`AMatrix`	IMatrix.`getTransposeView()` Returns a transposed view of this matrix.
`AMatrix`	AMatrix.`getTransposeView()`
`AMatrix`	Matrix33.`innerProduct(AMatrix a)`
`AMatrix`	Matrix22.`innerProduct(AMatrix a)`
`AMatrix`	IMatrix.`innerProduct(AMatrix a)` Computes the inner product of this matrix with another.
`AMatrix`	AMatrix.`innerProduct(AMatrix a)`
`AMatrix`	AMatrix.`innerProduct(AScalar s)`
`AMatrix`	AMatrix.`innerProduct(double d)`
`AMatrix`	IMatrix.`inverse()` Computes the inverse of this matrix.
`AMatrix`	AMatrix.`inverse()` Computes the inverse of a matrix.
`AMatrix`	AMatrix.`multiplyCopy(double factor)`
`AMatrix`	AMatrix.`mutable()`
`static AMatrix`	Matrixx.`newMatrix(int rows, int columns)` Creates an empty (zero-filled) mutable matrix of the specified size.
`static AMatrix`	Matrixx.`parse(String ednString)` Parse a matrix in edn format
`AMatrix`	AMatrix.`reorder(int[] order)`
`AMatrix`	AMatrix.`reorder(int dim, int[] order)`
`AMatrix`	AMatrix.`sparse()`
`AMatrix`	AMatrix.`sparseClone()`
`AMatrix`	AMatrix.`subArray(int[] offsets, int[] shape)`
`AMatrix`	IMatrix.`subMatrix(int rowStart, int rows, int colStart, int cols)` Gets a rectangular submatrix view of part of a matrix
`AMatrix`	AMatrix.`subMatrix(int rowStart, int rows, int colStart, int cols)`
`static AMatrix`	Matrixx.`toMatrix(Object o)` Coerce an object to a matrix format, on a best effort basis.
`AMatrix`	AMatrix.`toMutableMatrix()` Creates a fully mutable deep copy of this matrix
`AMatrix`	AMatrix.`transposeInnerProduct(AMatrix s)`
`AMatrix`	AMatrix.`transposeInnerProduct(Matrix s)`

Methods in mikera.matrixx with parameters of type AMatrix
Modifier and Type	Method and Description
`void`	Matrix22.`add(AMatrix a)`
`void`	Matrix.`add(AMatrix m)`
`void`	AMatrix.`add(AMatrix m)` Adds another matrix to this matrix.
`void`	Matrix.`add2(AMatrix a, AMatrix b)`
`void`	IMatrix.`add2(AMatrix a, AMatrix b)` Adds two matrices to this matrix.
`void`	AMatrix.`add2(AMatrix a, AMatrix b)`
`AMatrix`	IMatrix.`addCopy(AMatrix a)` Adds another matrix to this matrix, returning a new matrix
`AMatrix`	AMatrix.`addCopy(AMatrix a)`
`void`	AMatrix.`addInnerProduct(AMatrix a, AMatrix b)` Adds the inner product (matrix multiply) of two matrices to this matrix
`void`	AMatrix.`addInnerProduct(AMatrix a, INDArray b)`
`void`	Matrix.`addMultiple(AMatrix m, double factor)`
`void`	AMatrix.`addMultiple(AMatrix m, double factor)` Adds a scalar multiple of another matrix to this matrix
`void`	AMatrix.`applyOp(Op2 op, AMatrix b)`
`AMatrix`	AMatrix.`broadcastLike(AMatrix target)`
`protected void`	AMatrix.`checkSameShape(AMatrix m)` Checks if this matrix has the same shape as another matrix.
`void`	AMatrix.`composeWith(AMatrix a)`
`static Matrix`	Matrixx.`create(AMatrix m)` Creates a mutable deep copy of a matrix
`static Matrix`	Matrix.`create(AMatrix m)` Creates a new mutable dense matrix containing a copy of another matroix
`AMatrix`	Matrixx.`createInverse(AMatrix m)` Computes the inverse of a matrix.
`static AMatrix`	Matrixx.`createSparse(AMatrix m)` Creates a sparse matrix from the given matrix, ignoring zeros
`static SparseColumnMatrix`	Matrixx.`createSparseColumns(AMatrix m)` Creates a SparseColumnMatrix from the given matrix, ignoring zeros
`static AMatrix`	Matrixx.`createSparseRows(AMatrix m)` Creates a SparseRowMatrix matrix from the given matrix, ignoring zeros
`void`	AMatrix.`divide(AMatrix m)` Divides this matrix in-place by another in an entrywise manner.
`boolean`	AMatrix.`epsilonEquals(AMatrix a)` Returns true if this matrix is approximately equal to a second matrix, up to a default tolerance level
`boolean`	AMatrix.`epsilonEquals(AMatrix a, double epsilon)`
`boolean`	AMatrix.`equals(AMatrix a)` Returns true if this matrix is exactly equal to another matrix
`protected boolean`	AMatrix.`equalsByRows(AMatrix m)` Internal method to test for equality in a row-wise basis.
`boolean`	AMatrix.`equalsTranspose(AMatrix a)` Tests if this matrix is exactly equal to the transpose of another matrix
`static AMatrix`	Matrixx.`extractLowerTriangular(AMatrix a)` Extracts a lower triangular matrix from a matrix
`static AMatrix`	Matrixx.`extractUpperTriangular(AMatrix a)` Extracts an upper triangular matrix from a matrix
`static void`	Matrixx.`fillRandomValues(AMatrix m)` Fills a matrix with uniform random numbers
`static void`	Matrixx.`fillRandomValues(AMatrix m, Random rand)` Fills a matrix with uniform random numbers, using the specified Random instance
`AMatrix`	Matrix33.`innerProduct(AMatrix a)`
`AMatrix`	Matrix22.`innerProduct(AMatrix a)`
`Matrix`	Matrix.`innerProduct(AMatrix a)`
`AMatrix`	IMatrix.`innerProduct(AMatrix a)` Computes the inner product of this matrix with another.
`AMatrix`	AMatrix.`innerProduct(AMatrix a)`
`boolean`	AMatrix.`isSameShape(AMatrix a)` Returns true iff this matrix is exactly the same shape as another matrix
`void`	AMatrix.`mul(AMatrix a)` "Multiplies" this matrix by another, composing the transformation
`void`	AMatrix.`multiply(AMatrix m)` Multiplies this matrix in-place by another in an entrywise manner (Hadamard product).
`void`	Matrix22.`set(AMatrix m)`
`void`	Matrix.`set(AMatrix a)`
`void`	AMatrix.`set(AMatrix a)` Sets this matrix with the element values from another matrix.
`void`	AMatrix.`sub(AMatrix m)` Subtracts another matrix from this one
`AMatrix`	AMatrix.`transposeInnerProduct(AMatrix s)`
`void`	Matrix22.`unsafeSet(AMatrix m)`

Constructors in mikera.matrixx with parameters of type AMatrix
Constructor and Description
`Matrix(AMatrix m)` Creates a new Matrix with a copy of all data from the source matrix
`Matrix11(AMatrix m)`
`Matrix22(AMatrix m)`
`Matrix33(AMatrix m)`

Uses of AMatrix in mikera.matrixx.algo

Methods in mikera.matrixx.algo that return AMatrix
Modifier and Type	Method and Description
`static AMatrix`	Inverse.`calculate(AMatrix a)` Computes the inverse of an arbitrary square Matrix.
`static AMatrix`	Inverse.`calculateSymmetric(AMatrix a)` Computes the inverse of a symmetric matrix
`static AMatrix`	Multiplications.`naiveMultiply(AMatrix a, AMatrix b)`

Methods in mikera.matrixx.algo with parameters of type AMatrix
Modifier and Type	Method and Description
`static Matrix`	Multiplications.`blockedMultiply(Matrix a, AMatrix b)` Performs fast matrix multiplication using temporary working storage for the second matrix
`static AMatrix`	Inverse.`calculate(AMatrix a)` Computes the inverse of an arbitrary square Matrix.
`static double`	Determinant.`calculate(AMatrix m)` Calculate the determinant of an AMatrix.
`static AMatrix`	Inverse.`calculateSymmetric(AMatrix a)` Computes the inverse of a symmetric matrix
`static int`	Rank.`compute(AMatrix A)` Returns the rank of a matrix.
`static int`	Rank.`compute(AMatrix A, double threshold)` Returns the rank of a matrix.
`static Matrix`	Multiplications.`directMultiply(Matrix a, AMatrix b)`
`static Matrix`	Multiplications.`doubleBlockedMultiply(AMatrix a, AMatrix b)` Performs fast matrix multiplication using temporary working storage for both matrices
`static boolean`	Definite.`isPositiveDefinite(AMatrix a)` Tests whether a symmetric matrix is positive definite Results are undefined if the matrix is not symmetric
`static boolean`	Definite.`isPositiveSemiDefinite(AMatrix a)` Tests whether a symmetric matrix is positive semi-definite Results are undefined if the matrix is not symmetric
`static Matrix`	Multiplications.`multiply(AMatrix a, AMatrix b)` General purpose matrix multiplication, with smart selection of algorithm based on matrix size and type.
`static Matrix`	Multiplications.`multiply(Matrix a, AMatrix b)`
`static AMatrix`	Multiplications.`naiveMultiply(AMatrix a, AMatrix b)`

Uses of AMatrix in mikera.matrixx.decompose

Methods in mikera.matrixx.decompose that return AMatrix
Modifier and Type	Method and Description
`AMatrix`	IBidiagonalResult.`getB()` Returns the bidiagonal matrix.
`AMatrix`	IHessenbergResult.`getH()` An upper Hessenberg matrix from the decompostion.
`AMatrix`	ILUResult.`getL()` Returns the L matrix from the decomposition.
`AMatrix`	ICholeskyResult.`getL()` Returns the lower triangular matrix from the decomposition.
`AMatrix`	IQRResult.`getQ()` Returns the Q matrix from the decomposition.
`AMatrix`	IHessenbergResult.`getQ()` An orthogonal matrix that has the following property: H = Q^TAQ
`AMatrix`	IQRResult.`getR()` Returns the R matrix from the decomposition.
`AMatrix`	ISVDResult.`getS()` Returns a diagonal matrix with the singular values.
`AMatrix`	ISVDResult.`getU()` Returns the orthogonal 'U' matrix.
`AMatrix`	ILUResult.`getU()` Returns the U matrix from the decomposition.
`AMatrix`	ICholeskyResult.`getU()` Returns the upper triangular matrix from the decomposition.
`AMatrix`	IBidiagonalResult.`getU()` Returns the orthogonal U matrix.
`AMatrix`	ISVDResult.`getV()` Returns the orthogonal 'V' matrix.
`AMatrix`	IBidiagonalResult.`getV()` Returns the orthogonal V matrix.

Methods in mikera.matrixx.decompose with parameters of type AMatrix
Modifier and Type	Method and Description
`static ISVDResult`	SVD.`decompose(AMatrix A)` Computes the Singular Value Decomposition of a matrix, which is the decomposition of the given matrix A as: A = USV, where U and V are orthogonal and S is a diagonal matrix containing singular values along its diagonal.
`static IQRResult`	QR.`decompose(AMatrix matrix)` Computes the QR factorisation of a matrix A such that: A = Q.R Where: Q is an orthogonal matrix R is an upper triangular matrix If A is rectangular (m x n where m>n) then Q will also be (m x n)
`static ILUPResult`	LUP.`decompose(AMatrix A)` This performs LU decomposition on the given matrix and returns the result as a ILUPResult object
`static IHessenbergResult`	Hessenberg.`decompose(AMatrix A)` Finds the decomposition of a matrix in the form of: A = QHQ^T where A is an m by m matrix, Q is an orthogonal matrix, and H is an upper Hessenberg matrix.
`static IEigenResult`	Eigen.`decompose(AMatrix A)` Computes the eigenvalues and eigenvectors of a matrix.
`static ICholeskyResult`	Cholesky.`decompose(AMatrix a)` Decompose a Matrix according the the Cholesky decomposition A = L.L*
`static IBidiagonalResult`	Bidiagonal.`decompose(AMatrix A)`
`static ISVDResult`	SVD.`decompose(AMatrix A, boolean compact)` Computes the Singular Value Decomposition of a matrix, which is the decomposition of the given matrix A as: A = USV, where U and V are orthogonal and S is a diagonal matrix containing singular values along its diagonal.
`static IQRResult`	QR.`decompose(AMatrix matrix, boolean compact)` Computes the QR factorisation of a matrix A such that: A = Q.R Where: Q is an orthogonal matrix R is an upper triangular matrix If A is rectangular (m x n where m>n) then Q will also be (m x n)
`static IEigenResult`	Eigen.`decompose(AMatrix A, boolean computeVectors)` Computes the eigenvalues and eigenvectors of a matrix.
`static IBidiagonalResult`	Bidiagonal.`decompose(AMatrix A, boolean compact)`
`static ISVDResult`	SVD.`decomposeCompact(AMatrix A)` Computes the Singular Value Decomposition of a matrix, which is the decomposition of the given matrix A as: A = USV, where U and V are orthogonal and S is a diagonal matrix containing singular values along its diagonal.
`static IQRResult`	QR.`decomposeCompact(AMatrix matrix)` Computes the QR factorisation of a matrix A such that: A = Q.R Where: Q is an orthogonal matrix R is an upper triangular matrix If A is rectangular (m x n where m>n) then Q will also be (m x n)
`static IBidiagonalResult`	Bidiagonal.`decomposeCompact(AMatrix A)`
`static IEigenResult`	Eigen.`decomposeSymmetric(AMatrix A)` Computes the eigenvalues and eigenvectors of a real symmetric matrix.
`static IEigenResult`	Eigen.`decomposeSymmetric(AMatrix A, boolean computeVectors)` Computes the eigenvalues and eigenvectors of a real symmetric matrix.

Uses of AMatrix in mikera.matrixx.decompose.impl.bidiagonal

Methods in mikera.matrixx.decompose.impl.bidiagonal that return AMatrix
Modifier and Type	Method and Description
`AMatrix`	BidiagonalRowResult.`getB()`
`AMatrix`	BidiagonalRowResult.`getU()`
`AMatrix`	BidiagonalRowResult.`getV()`

Methods in mikera.matrixx.decompose.impl.bidiagonal with parameters of type AMatrix
Modifier and Type	Method and Description
`static IBidiagonalResult`	BidiagonalRow.`decompose(AMatrix A)` Computes the decomposition of the provided matrix.
`static IBidiagonalResult`	BidiagonalRow.`decompose(AMatrix A, boolean compact)` Computes the decomposition of the provided matrix.

Constructors in mikera.matrixx.decompose.impl.bidiagonal with parameters of type AMatrix
Constructor and Description
`BidiagonalRowResult(AMatrix U, AMatrix B, AMatrix V)`

Uses of AMatrix in mikera.matrixx.decompose.impl.chol

Methods in mikera.matrixx.decompose.impl.chol that return AMatrix
Modifier and Type	Method and Description
`AMatrix`	CholeskyResult.`getL()` Returns the lower triangular matrix from the decomposition.
`AMatrix`	CholeskyHelper.`getL()` Returns L matrix from the decomposition. L*L^T=A
`AMatrix`	CholeskyResult.`getU()` Returns the upper triangular matrix from the decomposition.

Methods in mikera.matrixx.decompose.impl.chol with parameters of type AMatrix
Modifier and Type	Method and Description
`protected ICholeskyResult`	CholeskyCommon.`_decompose(AMatrix mat)` Performs Choleksy decomposition on the provided matrix.
`protected ICholeskyResult`	Cholesky.`_decompose(AMatrix mat)` Performs Choleksy decomposition on the provided matrix.
`static ICholeskyResult`	SimpleCholesky.`decompose(AMatrix a)` Decompose a matrix according the the Cholesky decomposition A = L.L*
`static ICholeskyLDUResult`	CholeskyLDU.`decompose(AMatrix mat)`
`static ICholeskyResult`	CholeskyInner.`decompose(AMatrix mat)` Computes the Cholesky LDU Decomposition (A = LDU) of a matrix.
`static ICholeskyResult`	Cholesky.`decompose(AMatrix mat)` Computes the Cholesky Decomposition (A = LU) of a matrix, taking default block width = 60.
`static ICholeskyResult`	Cholesky.`decompose(AMatrix mat, int blockWidth)` Computes the Cholesky LDU Decomposition (A = LDU) of a matrix.
`boolean`	CholeskyHelper.`decompose(AMatrix mat, int indexStart, int n)` Decomposes a submatrix.

Constructors in mikera.matrixx.decompose.impl.chol with parameters of type AMatrix
Constructor and Description
`CholeskyResult(AMatrix L)`
`CholeskyResult(AMatrix L, ADiagonalMatrix D, AMatrix U)`

Uses of AMatrix in mikera.matrixx.decompose.impl.eigen

Methods in mikera.matrixx.decompose.impl.eigen with parameters of type AMatrix
Modifier and Type	Method and Description
`EigenResult`	SymmetricQRAlgorithmDecomposition.`decompose(AMatrix orig)` Decomposes the matrix using the QR algorithm.

Uses of AMatrix in mikera.matrixx.decompose.impl.hessenberg

Methods in mikera.matrixx.decompose.impl.hessenberg that return AMatrix
Modifier and Type	Method and Description
`AMatrix`	HessenbergResult.`getH()`
`AMatrix`	HessenbergResult.`getQ()`
`AMatrix`	TridiagonalDecompositionHouseholder.`getQ(boolean transposed)` An orthogonal matrix that has the following property: T = Q^TAQ
`AMatrix`	HessenbergSimilarDecomposition.`getQH()` The raw QH matrix that is stored internally.
`AMatrix`	TridiagonalDecompositionHouseholder.`getQT()` Returns the internal matrix where the decomposed results are stored.
`AMatrix`	TridiagonalDecompositionHouseholder.`getT()` Extracts the tridiagonal matrix found in the decomposition.

Methods in mikera.matrixx.decompose.impl.hessenberg with parameters of type AMatrix
Modifier and Type	Method and Description
`boolean`	TridiagonalDecompositionHouseholder.`decompose(AMatrix A)` Decomposes the provided symmetric matrix.
`static HessenbergResult`	HessenbergSimilarDecomposition.`decompose(AMatrix A)` Computes the decomposition of the provided matrix.
`void`	TridiagonalDecompositionHouseholder.`init(AMatrix A)` If needed declares and sets up internal data structures.

Constructors in mikera.matrixx.decompose.impl.hessenberg with parameters of type AMatrix
Constructor and Description
`HessenbergResult(AMatrix H, AMatrix Q)`

Uses of AMatrix in mikera.matrixx.decompose.impl.lu

Methods in mikera.matrixx.decompose.impl.lu that return AMatrix
Modifier and Type	Method and Description
`AMatrix`	LUPResult.`getL()`
`AMatrix`	AltLU.`getLU()`
`AMatrix`	LUPResult.`getU()`

Methods in mikera.matrixx.decompose.impl.lu with parameters of type AMatrix
Modifier and Type	Method and Description
`LUPResult`	AltLU.`_decompose(AMatrix a)` This is a modified version of what was found in the JAMA package.
`static Matrix`	DecomposeLUP.`createLUPInverse(AMatrix m)`
`static ILUPResult`	SimpleLUP.`decompose(AMatrix matrix)`
`static LUPResult`	AltLU.`decompose(AMatrix A)`

Constructors in mikera.matrixx.decompose.impl.lu with parameters of type AMatrix
Constructor and Description
`LUPResult(AMatrix l, AMatrix u)`
`LUPResult(AMatrix l, AMatrix u, PermutationMatrix p)`

Uses of AMatrix in mikera.matrixx.decompose.impl.qr

Methods in mikera.matrixx.decompose.impl.qr that return AMatrix
Modifier and Type	Method and Description
`protected AMatrix`	HouseholderQR.`computeQ()` Computes the Q matrix from the information stored in the QR matrix.
`protected AMatrix`	HouseholderColQR.`computeQ()` Computes Q.
`protected AMatrix`	HouseholderQR.`computeR()` Returns an upper triangular matrix which is the R in the QR decomposition.
`protected AMatrix`	HouseholderColQR.`computeR()` Computes R.
`AMatrix`	QRResult.`getQ()`
`AMatrix`	HouseholderQR.`getQ()`
`AMatrix`	HouseholderColQR.`getQ()`
`AMatrix`	HouseholderQR.`getQR()` Returns a single matrix which contains the combined values of Q and R.
`AMatrix`	QRResult.`getR()`
`AMatrix`	HouseholderQR.`getR()`
`AMatrix`	HouseholderColQR.`getR()`

Methods in mikera.matrixx.decompose.impl.qr with parameters of type AMatrix
Modifier and Type	Method and Description
`protected void`	HouseholderColQR.`convertToColumnMajor(AMatrix A)` Converts the standard row-major matrix into a column-major vector that is advantageous for this problem.
`IQRResult`	QRDecomposition.`decompose(AMatrix A)`
`QRResult`	HouseholderQR.`decompose(AMatrix A)` In order to decompose the matrix 'A' it must have full rank.
`QRResult`	HouseholderColQR.`decompose(AMatrix A)` To decompose the matrix 'A' it must have full rank.

Constructors in mikera.matrixx.decompose.impl.qr with parameters of type AMatrix
Constructor and Description
`QRResult(AMatrix Q, AMatrix R)`

Uses of AMatrix in mikera.matrixx.decompose.impl.svd

Methods in mikera.matrixx.decompose.impl.svd that return AMatrix
Modifier and Type	Method and Description
`AMatrix`	SVDResult.`getS()` Returns a diagonal matrix with the singular values.
`AMatrix`	SvdImplicitQr.`getS()`
`AMatrix`	SVDResult.`getU()` Returns the orthogonal 'U' matrix.
`AMatrix`	SvdImplicitQr.`getU()`
`AMatrix`	SvdImplicitQrAlgorithm.`getUt()`
`AMatrix`	SVDResult.`getV()` Returns the orthogonal 'V' matrix.
`AMatrix`	SvdImplicitQr.`getV()`
`AMatrix`	SvdImplicitQrAlgorithm.`getVt()`

Methods in mikera.matrixx.decompose.impl.svd with parameters of type AMatrix
Modifier and Type	Method and Description
`SVDResult`	SvdImplicitQr.`_decompose(AMatrix _orig)`
`static ISVDResult`	ThinSVD.`decompose(AMatrix a)`
`static SVDResult`	SvdImplicitQr.`decompose(AMatrix A, boolean compact)`
`void`	SvdImplicitQrAlgorithm.`setUt(AMatrix ut)`
`void`	SvdImplicitQrAlgorithm.`setVt(AMatrix vt)`

Constructors in mikera.matrixx.decompose.impl.svd with parameters of type AMatrix
Constructor and Description
`SVDResult(AMatrix U, AMatrix S, AMatrix V, AVector singularValues)`

Uses of AMatrix in mikera.matrixx.impl

Subclasses of AMatrix in mikera.matrixx.impl
Modifier and Type	Class and Description
`class`	`AArrayMatrix` Abstract class for a Matrix backed with a single double[] data array Dimensions are fixed, but leaves open the possibility of arbitrary indexing
`class`	`ABandedMatrix` Abstract base class for banded matrices Banded matrix implementations are assumed to store their data efficiently in diagonal bands, so functions on banded matrices can be designed to exploit this fact.
`class`	`ABlockMatrix` Abstract base class for a large matrix constructed out of regular subMatrix blocks
`class`	`ABooleanMatrix` Abstract base class for matrices limited to boolean 0/1 values Such matrices allow for various efficient representations
`class`	`ADenseArrayMatrix` Abstract base class for matrices wrapping a dense (rows*cols) subset of a double[] array
`class`	`ADiagonalMatrix` Abstract base class for square diagonal matrices
`class`	`APrimitiveMatrix` Abstract base class for the small square primitive backed matrices
`class`	`ARectangularMatrix` Abstract class for regular rectangular matrices that maintain a final fixed row and column count.
`class`	`ASingleBandMatrix` Abstract base class to represent sparse matrices with a single non-zero band Unlike ADiagonalMatrix, this matrix need not be square, and may have non-zero values on an arbitrary diagonal.
`class`	`ASparseRCMatrix` Abstract base class for matrices that store sparse rows or columns.
`class`	`AStridedMatrix` Abstract base class for arbitrary strided matrices
`class`	`ATriangularMatrix` Abstract base class for densely packed triangular matrices (upper and lower)
`class`	`AVectorMatrix<T extends AVector>` Abstract base class for matrices that use a collection of Vectors as storage for the matrix rows.
`class`	`BandedMatrix` Sparse banded matrix implementation.
`class`	`BaseStridedMatrix`
`class`	`BlockDiagonalMatrix` Class representing a square, block diagonal matrix.
`class`	`BroadcastVectorMatrix` Specialised class representing the broadcasting of a vector to a matrix shape.
`class`	`BufferMatrix` A matrix class implemented using a java.nio.DoubleBuffer Intended for use with native libraries that require interop with buffer memory
`class`	`ColumnMatrix` Matrix class that wraps a vector as a single-column matrix
`class`	`DenseColumnMatrix` A densely packed matrix organised in column-major format.
`class`	`DiagonalMatrix` Specialised diagonal matrix class, with dense double[] array storage for the leading diagonal only.
`class`	`IdentityMatrix` Specialised identity matrix class.
`class`	`ImmutableMatrix` Immutable dense matrix class This is the immutable equivalent of mikera.matrixx.Matrix
`class`	`LowerTriangularMatrix` Class for a lower triangular matrix packed densely by rows.
`class`	`PermutationMatrix` Class representing a square permutation matrix i.e.
`class`	`PermutedMatrix` Matrix class representing a permuted view of a matrix
`class`	`QuadtreeMatrix` A matrix implemented as a quadtree of submatrices.
`class`	`RowMatrix` Matrix class that wraps a vector as a single-row matrix
`class`	`ScalarMatrix` Immutable scalar matrix class - a diagonal matrix with an identical value along the leading diagonal.
`class`	`SparseColumnMatrix` Matrix stored as a collection of normally sparse column vectors This format is especially efficient for: - transposeInnerProduct() with another matrix - access via getColumn() operation - transpose into SparseRowMatrix
`class`	`SparseRowMatrix` Matrix stored as a collection of normally sparse row vectors.
`class`	`StridedMatrix` A general purpose strided matrix implementation
`class`	`StridedRowMatrix` A strided matrix implementation with a column stride of 1 Provides a fast, mutable subMatrix view for the dense Matrix class
`class`	`SubMatrixView` Matrix class that wraps a SubMatrix of another matrix
`class`	`TransposedMatrix` Class representing a transposed view of another matrix The transposed matrix is a reference to the underlying matrix data
`class`	`UpperTriangularMatrix` Class for an upper triangular matrix packed densely by columns.
`class`	`VectorMatrixM3` Specialised N*3 Matrix with Vector3 row components
`class`	`VectorMatrixMN` A matrix implemented as a composition of M length N vectors
`class`	`ZeroMatrix` Lightweight immutable zero matrix class.

Methods in mikera.matrixx.impl that return AMatrix
Modifier and Type	Method and Description
`AMatrix`	ABooleanMatrix.`absCopy()`
`AMatrix`	ZeroMatrix.`addCopy(AMatrix a)`
`AMatrix`	SparseColumnMatrix.`addCopy(AMatrix m)`
`AMatrix`	IdentityMatrix.`addCopy(AMatrix m)`
`AMatrix`	ADiagonalMatrix.`addCopy(AMatrix a)`
`AMatrix`	ZeroMatrix.`clone()`
`AMatrix`	SparseRowMatrix.`clone()`
`AMatrix`	SparseColumnMatrix.`clone()`
`AMatrix`	DiagonalMatrix.`clone()`
`AMatrix`	AVectorMatrix.`clone()`
`AMatrix`	ADiagonalMatrix.`clone()`
`AMatrix`	APrimitiveMatrix.`copy()`
`static AMatrix`	BufferMatrix.`create(AMatrix m)`
`AMatrix`	UpperTriangularMatrix.`exactClone()`
`AMatrix`	SubMatrixView.`exactClone()`
`AMatrix`	StridedRowMatrix.`exactClone()`
`AMatrix`	StridedMatrix.`exactClone()`
`AMatrix`	QuadtreeMatrix.`exactClone()`
`AMatrix`	LowerTriangularMatrix.`exactClone()`
`AMatrix`	ImmutableMatrix.`exactClone()`
`AMatrix`	BroadcastVectorMatrix.`exactClone()`
`AMatrix`	BlockDiagonalMatrix.`exactClone()`
`AMatrix`	QuadtreeMatrix.`getBlock(int rowBlock, int colBlock)`
`AMatrix`	BlockDiagonalMatrix.`getBlock(int rowBlock, int colBlock)`
`abstract AMatrix`	ABlockMatrix.`getBlock(int rowBlock, int colBlock)`
`AMatrix`	ABlockMatrix.`getComponent(int k)`
`AMatrix`	TransposedMatrix.`getTranspose()`
`AMatrix`	TransposedMatrix.`getTransposeCopy()`
`AMatrix`	TransposedMatrix.`getTransposeView()`
`AMatrix`	IdentityMatrix.`innerProduct(ADiagonalMatrix a)`
`AMatrix`	DiagonalMatrix.`innerProduct(ADiagonalMatrix a)`
`AMatrix`	ADiagonalMatrix.`innerProduct(ADiagonalMatrix a)` Computes the inner product of this matrix with another diagonal matrix of the same shape.
`AMatrix`	ZeroMatrix.`innerProduct(AMatrix m)`
`AMatrix`	TransposedMatrix.`innerProduct(AMatrix s)`
`AMatrix`	SparseRowMatrix.`innerProduct(AMatrix a)`
`AMatrix`	SparseColumnMatrix.`innerProduct(AMatrix a)`
`AMatrix`	ScalarMatrix.`innerProduct(AMatrix m)`
`AMatrix`	IdentityMatrix.`innerProduct(AMatrix a)`
`AMatrix`	DiagonalMatrix.`innerProduct(AMatrix a)`
`AMatrix`	ADiagonalMatrix.`innerProduct(AMatrix a)`
`AMatrix`	IdentityMatrix.`inverse()`
`AMatrix`	SparseRowMatrix.`multiplyCopy(double a)`
`AMatrix`	SparseColumnMatrix.`multiplyCopy(double a)`
`AMatrix`	ScalarMatrix.`multiplyCopy(double d)`
`AMatrix`	ABooleanMatrix.`signumCopy()`
`AMatrix`	SparseRowMatrix.`sparse()`
`AMatrix`	SparseColumnMatrix.`sparse()`
`AMatrix`	ASparseRCMatrix.`sparse()`
`AMatrix`	ZeroMatrix.`sparseClone()`
`AMatrix`	TransposedMatrix.`sparseClone()`
`AMatrix`	ABooleanMatrix.`squareCopy()`
`AMatrix`	ZeroMatrix.`subMatrix(int rowStart, int rows, int colStart, int cols)`
`AMatrix`	BroadcastVectorMatrix.`subMatrix(int rowStart, int rows, int colStart, int cols)`
`AMatrix`	AVectorMatrix.`subMatrix(int rowStart, int rows, int colStart, int cols)`
`AMatrix`	ASingleBandMatrix.`subMatrix(int rowStart, int rows, int colStart, int cols)`
`AMatrix`	TransposedMatrix.`transposeInnerProduct(AMatrix s)`
`AMatrix`	SparseColumnMatrix.`transposeInnerProduct(AMatrix a)`
`AMatrix`	ADiagonalMatrix.`transposeInnerProduct(AMatrix s)`
`AMatrix`	TransposedMatrix.`transposeInnerProduct(Matrix s)`
`static AMatrix`	TransposedMatrix.`wrap(AMatrix m)`

Methods in mikera.matrixx.impl with parameters of type AMatrix
Modifier and Type	Method and Description
`void`	SparseRowMatrix.`add(AMatrix a)`
`void`	SparseColumnMatrix.`add(AMatrix a)`
`void`	AStridedMatrix.`add(AMatrix m)`
`void`	ADenseArrayMatrix.`add(AMatrix a)`
`AMatrix`	ZeroMatrix.`addCopy(AMatrix a)`
`AMatrix`	SparseColumnMatrix.`addCopy(AMatrix m)`
`AMatrix`	IdentityMatrix.`addCopy(AMatrix m)`
`AMatrix`	ADiagonalMatrix.`addCopy(AMatrix a)`
`void`	SparseColumnMatrix.`addMultiple(AMatrix a, double factor)`
`void`	DenseColumnMatrix.`addMultiple(AMatrix m, double factor)`
`void`	SparseColumnMatrix.`applyOp(Op2 op, AMatrix b)`
`protected void`	ARectangularMatrix.`checkSameShape(AMatrix m)`
`protected void`	ADiagonalMatrix.`checkSameShape(AMatrix m)`
`static BlockDiagonalMatrix`	BlockDiagonalMatrix.`create(AMatrix... blocks)`
`static VectorMatrixMN`	VectorMatrixMN.`create(AMatrix source)`
`static StridedMatrix`	StridedMatrix.`create(AMatrix m)`
`static SparseRowMatrix`	SparseRowMatrix.`create(AMatrix source)`
`static SparseColumnMatrix`	SparseColumnMatrix.`create(AMatrix source)`
`static ImmutableMatrix`	ImmutableMatrix.`create(AMatrix a)`
`static DiagonalMatrix`	DiagonalMatrix.`create(AMatrix m)`
`static DenseColumnMatrix`	DenseColumnMatrix.`create(AMatrix m)`
`static AMatrix`	BufferMatrix.`create(AMatrix m)`
`static BandedMatrix`	BandedMatrix.`create(AMatrix m)`
`static QuadtreeMatrix`	QuadtreeMatrix.`create(AMatrix c00, AMatrix c01, AMatrix c10, AMatrix c11)`
`static AVector`	MatrixBandView.`create(AMatrix source, int band)`
`static UpperTriangularMatrix`	UpperTriangularMatrix.`createFrom(AMatrix m)`
`static LowerTriangularMatrix`	LowerTriangularMatrix.`createFrom(AMatrix m)`
`boolean`	SparseColumnMatrix.`epsilonEquals(AMatrix a, double epsilon)`
`boolean`	ZeroMatrix.`equals(AMatrix m)`
`boolean`	UpperTriangularMatrix.`equals(AMatrix a)`
`boolean`	TransposedMatrix.`equals(AMatrix m)`
`boolean`	StridedRowMatrix.`equals(AMatrix a)`
`boolean`	StridedMatrix.`equals(AMatrix a)`
`boolean`	SparseRowMatrix.`equals(AMatrix m)`
`boolean`	SparseColumnMatrix.`equals(AMatrix m)`
`boolean`	ImmutableMatrix.`equals(AMatrix a)`
`boolean`	AVectorMatrix.`equals(AMatrix m)`
`boolean`	ADenseArrayMatrix.`equals(AMatrix a)`
`boolean`	TransposedMatrix.`equalsTranspose(AMatrix a)`
`boolean`	ADiagonalMatrix.`equalsTranspose(AMatrix m)`
`AMatrix`	ZeroMatrix.`innerProduct(AMatrix m)`
`AMatrix`	TransposedMatrix.`innerProduct(AMatrix s)`
`AMatrix`	SparseRowMatrix.`innerProduct(AMatrix a)`
`AMatrix`	SparseColumnMatrix.`innerProduct(AMatrix a)`
`AMatrix`	ScalarMatrix.`innerProduct(AMatrix m)`
`Matrix`	PermutationMatrix.`innerProduct(AMatrix a)`
`Matrix`	ImmutableMatrix.`innerProduct(AMatrix a)`
`AMatrix`	IdentityMatrix.`innerProduct(AMatrix a)`
`AMatrix`	DiagonalMatrix.`innerProduct(AMatrix a)`
`AMatrix`	ADiagonalMatrix.`innerProduct(AMatrix a)`
`boolean`	ARectangularMatrix.`isSameShape(AMatrix m)`
`boolean`	ADiagonalMatrix.`isSameShape(AMatrix m)`
`void`	ZeroMatrix.`multiply(AMatrix m)`
`void`	SparseRowMatrix.`set(AMatrix a)`
`void`	SparseColumnMatrix.`set(AMatrix a)`
`void`	DenseColumnMatrix.`set(AMatrix m)`
`void`	ADenseArrayMatrix.`set(AMatrix m)`
`protected static int`	ABlockMatrix.`sumColumnCounts(AMatrix... mats)`
`protected static int`	ABlockMatrix.`sumRowCounts(AMatrix... mats)`
`AMatrix`	TransposedMatrix.`transposeInnerProduct(AMatrix s)`
`AMatrix`	SparseColumnMatrix.`transposeInnerProduct(AMatrix a)`
`AMatrix`	ADiagonalMatrix.`transposeInnerProduct(AMatrix s)`
`static VectorMatrixMN`	VectorMatrixMN.`wrap(AMatrix source)`
`static AMatrix`	TransposedMatrix.`wrap(AMatrix m)`
`static QuadtreeMatrix`	QuadtreeMatrix.`wrap(AMatrix c00, AMatrix c01, AMatrix c10, AMatrix c11)`

Constructors in mikera.matrixx.impl with parameters of type AMatrix
Constructor and Description
`ImmutableMatrix(AMatrix m)`
`MatrixColumnList(AMatrix m)`
`MatrixColumnView(AMatrix aMatrix, int column)`
`MatrixElementIterator(AMatrix source)`
`MatrixRowIterator(AMatrix source)`
`MatrixRowList(AMatrix m)`
`MatrixRowView(AMatrix aMatrix, int row)`
`PermutedMatrix(AMatrix source, Index rowPermutations)`
`PermutedMatrix(AMatrix source, Index rowPermutations, Index columnPermutations)`
`SubMatrixView(AMatrix source, int rowStart, int colStart, int rows, int cols)`

Uses of AMatrix in mikera.matrixx.solve

Methods in mikera.matrixx.solve that return AMatrix
Modifier and Type	Method and Description
`static AMatrix`	Linear.`solve(AMatrix A, AMatrix B)` A general linear system solver, For a matrix A, returns a matrix whose each column is the solution to the equation A.x = b, where b is the corresponding column of B.
`static AMatrix`	Linear.`solveLeastSquares(AMatrix A, AMatrix B)` Returns the least squares solution to the equation A.X = B Use this in the case of over-determined (more equations than unknowns) or under-determined (more unknowns than equations)

Methods in mikera.matrixx.solve with parameters of type AMatrix
Modifier and Type	Method and Description
`static AMatrix`	Linear.`solve(AMatrix A, AMatrix B)` A general linear system solver, For a matrix A, returns a matrix whose each column is the solution to the equation A.x = b, where b is the corresponding column of B.
`static AVector`	Linear.`solve(AMatrix A, AVector b)` A general linear system solver, Returns the solution to the equation A.x = b, returns null if A is square and has no unique solution.
`static AMatrix`	Linear.`solveLeastSquares(AMatrix A, AMatrix B)` Returns the least squares solution to the equation A.X = B Use this in the case of over-determined (more equations than unknowns) or under-determined (more unknowns than equations)
`static AVector`	Linear.`solveLeastSquares(AMatrix A, AVector b)` Returns the least squares solution to the equation A.x = b Use this in the case of over-determined (more equations than unknowns) or under-determined (more unknowns than equations)

Uses of AMatrix in mikera.matrixx.solve.impl

Methods in mikera.matrixx.solve.impl that return AMatrix
Modifier and Type	Method and Description
`AMatrix`	CholeskySolver.`invert()` Sets the matrix 'inv' equal to the inverse of the matrix that was decomposed.
`AMatrix`	CholeskyLDUSolver.`invert()` returns the matrix 'inv' equal to the inverse of the matrix that was decomposed.
`AMatrix`	CholeskySolver.`solve(AMatrix B)` Using the decomposition, finds the value of 'X' in the linear equation below: A*x = b where A has dimension of n by n, x and b are n by m dimension.
`AMatrix`	CholeskyLDUSolver.`solve(AMatrix B)` Using the decomposition, finds the value of 'X' in the linear equation below: A*x = b where A has dimension of n by n, x and b are n by m dimension.

Methods in mikera.matrixx.solve.impl with parameters of type AMatrix
Modifier and Type	Method and Description
`boolean`	CholeskySolver.`setA(AMatrix _A)`
`boolean`	CholeskyLDUSolver.`setA(AMatrix _A)`
`AMatrix`	CholeskySolver.`solve(AMatrix B)` Using the decomposition, finds the value of 'X' in the linear equation below: A*x = b where A has dimension of n by n, x and b are n by m dimension.
`AMatrix`	CholeskyLDUSolver.`solve(AMatrix B)` Using the decomposition, finds the value of 'X' in the linear equation below: A*x = b where A has dimension of n by n, x and b are n by m dimension.

Uses of AMatrix in mikera.matrixx.solve.impl.lu

Fields in mikera.matrixx.solve.impl.lu declared as AMatrix
Modifier and Type	Field and Description
`protected AMatrix`	LUSolver.`A`

Methods in mikera.matrixx.solve.impl.lu that return AMatrix
Modifier and Type	Method and Description
`AMatrix`	LUSolver.`getA()`
`AMatrix`	LUSolver.`invert()`

Methods in mikera.matrixx.solve.impl.lu with parameters of type AMatrix
Modifier and Type	Method and Description
`void`	LUSolver.`improveSol(AMatrix b, AMatrix x)` This attempts to improve upon the solution generated by account for numerical imprecisions.
`LUPResult`	LUSolver.`setA(AMatrix A)`
`ADenseArrayMatrix`	LUSolver.`solve(AMatrix b)`

Uses of AMatrix in mikera.matrixx.solve.impl.qr

Fields in mikera.matrixx.solve.impl.qr declared as AMatrix
Modifier and Type	Field and Description
`protected AMatrix`	QRHouseColSolver.`A`

Methods in mikera.matrixx.solve.impl.qr that return AMatrix
Modifier and Type	Method and Description
`AMatrix`	QRHouseColSolver.`getA()`
`AMatrix`	QRHouseColSolver.`solve(AMatrix B)` Solves for X using the QR decomposition.

Methods in mikera.matrixx.solve.impl.qr with parameters of type AMatrix
Modifier and Type	Method and Description
`protected void`	QRHouseColSolver.`_setA(AMatrix A)`
`static double`	QRHouseColSolver.`qualityTriangular(boolean upper, AMatrix T)` Computes the quality of a triangular matrix.
`boolean`	QRHouseColSolver.`setA(AMatrix A)` Performs QR decomposition on A
`AMatrix`	QRHouseColSolver.`solve(AMatrix B)` Solves for X using the QR decomposition.

Uses of AMatrix in mikera.transformz

Methods in mikera.transformz that return AMatrix
Modifier and Type	Method and Description
`AMatrix`	AAffineTransform.`copyOfMatrix()` Returns a deep copy of the transformation matrix for this affine transform
`AMatrix`	Translation3.`getMatrix()`
`AMatrix`	Translation.`getMatrix()`
`AMatrix`	MatrixTransform.`getMatrix()`
`AMatrix`	AffineMN.`getMatrix()`
`AMatrix`	Affine34.`getMatrix()`
`AMatrix`	Affine23.`getMatrix()`
`abstract AMatrix`	AAffineTransform.`getMatrix()`
`static AMatrix`	Transformz.`scale(int dimensions, double factor)` Creates an n-dimensional scaling transform
`static AMatrix`	Transformz.`zeroTransform(int inputDimensions, int outputDimensions)` Creates a zero transform (maps every vector to zero)

Methods in mikera.transformz with parameters of type AMatrix
Modifier and Type	Method and Description
`static AAffineTransform`	Transformz.`createAffineTransform(AMatrix m, AVector v)`

Constructors in mikera.transformz with parameters of type AMatrix
Constructor and Description
`Affine23(AMatrix matrix, ATranslation trans)`
`Affine23(AMatrix m, AVector v)`
`Affine34(AMatrix matrix, ATranslation trans)`
`Affine34(AMatrix m, AVector v)`
`AffineMN(AMatrix matrix, ATranslation translation)`
`AffineMN(AMatrix m, AVector v)`
`MatrixTransform(AMatrix matrix)`

Uses of AMatrix in mikera.transformz.impl

Methods in mikera.transformz.impl that return AMatrix
Modifier and Type	Method and Description
`AMatrix`	IdentityTranslation.`getMatrix()`
`AMatrix`	AConstantTransform.`getMatrix()`

Uses of AMatrix in mikera.vectorz

Methods in mikera.vectorz that return AMatrix
Modifier and Type	Method and Description
`AMatrix`	AVector.`broadcastLike(AMatrix target)`
`AMatrix`	AScalar.`broadcastLike(AMatrix v)`
`AMatrix`	AVector.`outerProduct(AVector a)` Computes the outer product of this vector with another vector

Methods in mikera.vectorz with parameters of type AMatrix
Modifier and Type	Method and Description
`void`	AVector.`addInnerProduct(AMatrix a, AVector b)` Adds the inner product of the arguments (matrix a and vector b) to this vector.
`void`	AVector.`addInnerProduct(AVector a, AMatrix b)` Adds the inner product of the arguments (vector a and matrix b) to this vector.
`void`	Op.`applyTo(AMatrix m)` Applies this operator to every element of a target matrix, mutating the matrix
`void`	Op2.`applyTo(AMatrix a, AMatrix b)`
`AMatrix`	AVector.`broadcastLike(AMatrix target)`
`AMatrix`	AScalar.`broadcastLike(AMatrix v)`
`AVector`	AVector.`innerProduct(AMatrix m)` Computes the inner product of this vector with a matrix
`void`	AVector.`setInnerProduct(AMatrix a, AVector b)` Sets this vector to the inner product of the arguments (matrix a and vector b).
`void`	AVector.`setInnerProduct(AVector a, AMatrix b)` Sets this vector to the inner product of the arguments (vector a and matrix b) to this vector.

Uses of AMatrix in mikera.vectorz.impl

Fields in mikera.vectorz.impl declared as AMatrix
Modifier and Type	Field and Description
`protected AMatrix`	AMatrixViewVector.`source`

Methods in mikera.vectorz.impl with parameters of type AMatrix
Modifier and Type	Method and Description
`AStridedMatrix`	AStridedVector.`broadcastLike(AMatrix target)`
`static AVector`	SparseIndexedVector.`createFromRow(AMatrix m, int row)` Creates a SparseIndexedVector from a row of an existing matrix
`static AVector`	SparseImmutableVector.`createFromRow(AMatrix m, int row)` Creates a SparseIndexedVector from a row of an existing matrix
`static AVector`	SparseHashedVector.`createFromRow(AMatrix m, int row)` Creates a SparseIndexedVector from a row of an existing matrix
`AVector`	ZeroVector.`innerProduct(AMatrix m)`
`AVector`	SparseIndexedVector.`innerProduct(AMatrix m)`
`AVector`	SingleElementVector.`innerProduct(AMatrix a)`
`AVector`	RepeatedElementVector.`innerProduct(AMatrix m)`
`AVector`	AxisVector.`innerProduct(AMatrix m)`
`AVector`	ASparseVector.`innerProduct(AMatrix m)`
`AVector`	ASparseIndexedVector.`innerProduct(AMatrix a)`
`static MatrixIndexScalar`	MatrixIndexScalar.`wrap(AMatrix matrix, int row, int col)`

Constructors in mikera.vectorz.impl with parameters of type AMatrix
Constructor and Description
`AMatrixViewVector(AMatrix source, int length)`
`MatrixViewVector(AMatrix a)`
`SubMatrixViewVector(AMatrix source, int rowStart, int colStart, int rows, int cols)`

Uses of AMatrix in mikera.vectorz.ops

Methods in mikera.vectorz.ops with parameters of type AMatrix
Modifier and Type	Method and Description
`void`	Power.`applyTo(AMatrix a)`
`void`	Offset.`applyTo(AMatrix v)`
`void`	Clamp.`applyTo(AMatrix v)`

Uses of AMatrix in mikera.vectorz.util

Subclasses of AMatrix in mikera.vectorz.util
Modifier and Type	Class and Description
`class`	`MatrixBuilder` Utility class for efficiently building matrices by appending vector rows

Methods in mikera.vectorz.util that return AMatrix
Modifier and Type	Method and Description
`AMatrix`	MatrixBuilder.`exactClone()`

Methods in mikera.vectorz.util with parameters of type AMatrix
Modifier and Type	Method and Description
`static String`	ErrorMessages.`invalidBand(AMatrix source, int band)`
`static String`	ErrorMessages.`nonSquareMatrix(AMatrix a)`
`static String`	ErrorMessages.`notFullyMutable(AMatrix m, int row, int column)`
`static String`	ErrorMessages.`squareMatrixRequired(AMatrix m)`

Uses of Classmikera.matrixx.AMatrix

Uses of AMatrix in mikera.arrayz

Uses of AMatrix in mikera.arrayz.impl

Uses of AMatrix in mikera.matrixx

Uses of AMatrix in mikera.matrixx.algo

Uses of AMatrix in mikera.matrixx.decompose

Uses of AMatrix in mikera.matrixx.decompose.impl.bidiagonal

Uses of AMatrix in mikera.matrixx.decompose.impl.chol

Uses of AMatrix in mikera.matrixx.decompose.impl.eigen

Uses of AMatrix in mikera.matrixx.decompose.impl.hessenberg

Uses of AMatrix in mikera.matrixx.decompose.impl.lu

Uses of AMatrix in mikera.matrixx.decompose.impl.qr

Uses of AMatrix in mikera.matrixx.decompose.impl.svd

Uses of AMatrix in mikera.matrixx.impl

Uses of AMatrix in mikera.matrixx.solve

Uses of AMatrix in mikera.matrixx.solve.impl

Uses of AMatrix in mikera.matrixx.solve.impl.lu

Uses of AMatrix in mikera.matrixx.solve.impl.qr

Uses of AMatrix in mikera.transformz

Uses of AMatrix in mikera.transformz.impl

Uses of AMatrix in mikera.vectorz

Uses of AMatrix in mikera.vectorz.impl

Uses of AMatrix in mikera.vectorz.ops

Uses of AMatrix in mikera.vectorz.util

Uses of Class
mikera.matrixx.AMatrix