Uses of Class org.ejml.data.FMatrixD1

Packages that use FMatrixD1

Package

Description

org.ejml.data

org.ejml.dense.row

org.ejml.dense.row.misc

org.ejml.dense.row.mult

org.ejml.masks

Uses of FMatrixD1 in org.ejml.data

Subclasses of FMatrixD1 in org.ejml.data

Modifier and Type

Class

Description

class

FMatrix1Row

Interface for a row-major matrix that uses a single array internally.

class

FMatrixRBlock

A row-major block matrix declared on to one continuous array.

class

FMatrixRMaj

FMatrixRMaj is a row matrix with real elements that are 32-bit floats.

Methods in org.ejml.data with parameters of type FMatrixD1

Modifier and Type

Method

Description

void

FMatrixD1.setTo(FMatrixD1 b)

Sets the value of this matrix to be the same as the value of the provided matrix.

Constructors in org.ejml.data with parameters of type FMatrixD1

Modifier

Constructor

Description

FMatrixIterator(FMatrixD1 a, boolean rowMajor, int minRow, int minCol, int maxRow, int maxCol)

Creates a new iterator for traversing through a submatrix inside this matrix.

FSubmatrixD1(FMatrixD1 original)

FSubmatrixD1(FMatrixD1 original, int row0, int row1, int col0, int col1)
Uses of FMatrixD1 in org.ejml.dense.row

Methods in org.ejml.dense.row with type parameters of type FMatrixD1

Modifier and Type

Method

Description

static <T extends FMatrixD1> T

CommonOps_FDRM.add(float alpha, T a, float beta, T b, T output)

Performs the following operation:

c = α * a + β * b
c_ij = α * a_ij + β * b_ij

static <T extends FMatrixD1> T

CommonOps_FDRM.add(float alpha, T a, T b, T output)

Performs the following operation:

c = α * a + b
c_ij = α * a_ij + b_ij

static <T extends FMatrixD1> T

CommonOps_FDRM.add(T a, float val, T output)

Performs scalar addition:

c = a + val
c_ij = a_ij + val

static <T extends FMatrixD1> T

CommonOps_FDRM.add(T a, float beta, T b, T output)

Performs the following operation:

c = a + β * b
c_ij = a_ij + β * b_ij

static <T extends FMatrixD1> T

CommonOps_FDRM.add(T a, T b, T output)

Performs the following operation:

c = a + b
c_ij = a_ij + b_ij

static <T extends FMatrixD1> T

CommonOps_FDRM.changeSign(T input, T output)

Changes the sign of every element in the matrix.

output_ij = -input_ij

static <T extends FMatrixD1> T

CommonOps_FDRM.divide(float alpha, T input, T output)

Performs an element by element scalar division with the scalar on top.

b_ij = α/a_ij

static <T extends FMatrixD1> T

CommonOps_FDRM.divide(T input, float alpha, T output)

Performs an element by element scalar division with the scalar on botton.

b_ij = a_ij /α

static <T extends FMatrixD1> T

CommonOps_FDRM.elementDiv(T A, T B, T output)

Performs the an element by element division operation:

c_ij = a_ij / b_ij

static <T extends FMatrixD1> T

CommonOps_FDRM.elementExp(T A, T output)

Element-wise exp operation
c_ij = (float)Math.exp(a_ij)

static <T extends FMatrixD1> T

CommonOps_FDRM.elementLog(T A, T output)

Element-wise log operation
c_ij = (float)Math.log(a_ij)

static <T extends FMatrixD1> T

CommonOps_FDRM.elementMult(T A, T B, T output)

Performs the an element by element multiplication operation:

c_ij = a_ij * b_ij

static <T extends FMatrixD1> T

CommonOps_FDRM.elementPower(float a, T B, T output)

Element-wise power operation
c_ij = a ^ b_ij

static <T extends FMatrixD1> T

CommonOps_FDRM.elementPower(T A, float b, T output)

Element-wise power operation
c_ij = a_ij ^ b

static <T extends FMatrixD1> T

CommonOps_FDRM.elementPower(T A, T B, T output)

Element-wise power operation
c_ij = a_ij ^ b_ij

static <T extends FMatrixD1> T

CommonOps_FDRM.subtract(float val, T a, T output)

Performs matrix scalar subtraction:

c = val - a
c_ij = val - a_ij

static <T extends FMatrixD1> T

CommonOps_FDRM.subtract(T a, float val, T output)

Performs matrix scalar subtraction:

c = a - val
c_ij = a_ij - val

static <T extends FMatrixD1> T

CommonOps_FDRM.subtract(T a, T b, T output)

Performs the following subtraction operation:

c = a - b
c_ij = a_ij - b_ij

Methods in org.ejml.dense.row with parameters of type FMatrixD1

Modifier and Type

Method

Description

static void

CommonOps_FDRM.abs(FMatrixD1 a)

Performs absolute value of a matrix:

a = abs(a)
a_ij = abs(a_ij)

static void

CommonOps_FDRM.abs(FMatrixD1 a, FMatrixD1 c)

Performs absolute value of a matrix:

c = abs(a)
c_ij = abs(a_ij)

static void

CommonOps_FDRM.add(FMatrixD1 a, float val)

Performs an in-place scalar addition:

a = a + val
a_ij = a_ij + val

static void

CommonOps_FDRM.addEquals(FMatrixD1 a, float beta, FMatrixD1 b)

Performs the following operation:

a = a + β * b
a_ij = a_ij + β * b_ij

static void

CommonOps_FDRM.addEquals(FMatrixD1 a, FMatrixD1 b)

Performs the following operation:

a = a + b
a_ij = a_ij + b_ij

static void

CommonOps_FDRM.changeSign(FMatrixD1 a)

Changes the sign of every element in the matrix.

a_ij = -a_ij

static void

CommonOps_CDRM.convert(FMatrixD1 input, CMatrixD1 output)

Converts the real matrix into a complex matrix.

static float

SpecializedOps_FDRM.diffNormF(FMatrixD1 a, FMatrixD1 b)

Computes the F norm of the difference between the two Matrices:

Sqrt{∑_i=1:m ∑_j=1:n ( a_ij - b_ij)²}

static float

SpecializedOps_FDRM.diffNormF_fast(FMatrixD1 a, FMatrixD1 b)

static float

SpecializedOps_FDRM.diffNormP1(FMatrixD1 a, FMatrixD1 b)

Computes the p=1 p-norm of the difference between the two Matrices:

∑_i=1:m ∑_j=1:n | a_ij - b_ij|

where |x| is the absolute value of x.

static void

CommonOps_FDRM.divide(float alpha, FMatrixD1 a)

Performs an in-place element by element scalar division with the scalar on top.

a_ij = α/a_ij

static void

CommonOps_FDRM.divide(FMatrixD1 a, float alpha)

Performs an in-place element by element scalar division with the scalar on bottom.

a_ij = a_ij/α

static float

CommonOps_FDRM.dot(FMatrixD1 a, FMatrixD1 b)

Computes the dot product or inner product between two vectors.

static float

SpecializedOps_FDRM.elementDiagonalMaxAbs(FMatrixD1 a)

Returns the absolute value of the digonal element in the matrix that has the largest absolute value.

Max{ |a_ij| } for all i and j

static void

CommonOps_FDRM.elementDiv(FMatrixD1 A, FMatrixD1 B)

Performs the an element by element division operation:

a_ij = a_ij / b_ij

static float

CommonOps_FDRM.elementMax(FMatrixD1 a)

Returns the value of the element in the matrix that has the largest value.

Max{ a_ij } for all i and j

static float

CommonOps_FDRM.elementMax(FMatrixD1 a, ElementLocation loc)

Returns the value of the element in the matrix that has the largest value.

Max{ a_ij } for all i and j

static float

CommonOps_FDRM.elementMaxAbs(FMatrixD1 a)

Returns the absolute value of the element in the matrix that has the largest absolute value.

Max{ |a_ij| } for all i and j

static float

CommonOps_FDRM.elementMaxAbs(FMatrixD1 a, ElementLocation loc)

Returns the absolute value of the element in the matrix that has the largest absolute value.

Max{ |a_ij| } for all i and j

static float

CommonOps_FDRM.elementMin(FMatrixD1 a)

Returns the value of the element in the matrix that has the minimum value.

Min{ a_ij } for all i and j

static float

CommonOps_FDRM.elementMin(FMatrixD1 a, ElementLocation loc)

Returns the value of the element in the matrix that has the minimum value.

Min{ a_ij } for all i and j

static float

CommonOps_FDRM.elementMinAbs(FMatrixD1 a)

Returns the absolute value of the element in the matrix that has the smallest absolute value.

Min{ |a_ij| } for all i and j

static float

CommonOps_FDRM.elementMinAbs(FMatrixD1 a, ElementLocation loc)

Returns the absolute value of the element in the matrix that has the smallest absolute value.

Min{ |a_ij| } for all i and j

static void

CommonOps_FDRM.elementMult(FMatrixD1 A, FMatrixD1 B)

Performs the an element by element multiplication operation:

a_ij = a_ij * b_ij

static float

CommonOps_FDRM.elementSum(FMatrixD1 mat)

Computes the sum of all the elements in the matrix:

sum(i=1:m , j=1:n ; a_ij)

static float

CommonOps_FDRM.elementSumAbs(FMatrixD1 mat)

Computes the sum of the absolute value all the elements in the matrix:

sum(i=1:m , j=1:n ; |a_ij|)

static float

SpecializedOps_FDRM.elementSumSq(FMatrixD1 m)

Sums up the square of each element in the matrix.

static float

NormOps_FDRM.fastElementP(FMatrixD1 A, float p)

Same as NormOps_FDRM.elementP(org.ejml.data.FMatrix1Row, float) but runs faster by not mitigating overflow/underflow related problems.

static float

NormOps_FDRM.fastNormF(FMatrixD1 a)

This implementation of the Frobenius norm is a straight forward implementation and can be susceptible for overflow/underflow issues.

static void

CommonOps_FDRM.fill(FMatrixD1 a, float value)

Sets every element in the matrix to the specified value.

a_ij = value

static void

RandomMatrices_FDRM.fillGaussian(FMatrixD1 mat, float mean, float stdev, Random rand)

Sets each element in the matrix to a value drawn from an Gaussian distribution with the specified mean and standard deviation

static void

RandomMatrices_FDRM.fillUniform(FMatrixD1 mat, float min, float max, Random rand)

Sets each element in the matrix to a value drawn from an uniform distribution from 'min' to 'max' inclusive.

static boolean

MatrixFeatures_FDRM.hasNaN(FMatrixD1 m)

Checks to see if any element in the matrix is NaN.

static boolean

MatrixFeatures_FDRM.hasUncountable(FMatrixD1 m)

Checks to see if any element in the matrix is NaN of Infinite.

static boolean

MatrixFeatures_FDRM.isEquals(FMatrixD1 a, FMatrixD1 b)

Checks to see if each element in the two matrices are equal: a_ij == b_ij

static boolean

MatrixFeatures_FDRM.isEquals(FMatrixD1 a, FMatrixD1 b, float tol)

Checks to see if each element in the two matrices are within tolerance of each other: tol ≥ |a_ij - b_ij|.

static boolean

MatrixFeatures_FDRM.isIdentical(FMatrixD1 a, FMatrixD1 b, float tol)

Checks to see if each corresponding element in the two matrices are within tolerance of each other or have the some symbolic meaning.

static boolean

MatrixFeatures_FDRM.isNegative(FMatrixD1 a, FMatrixD1 b, float tol)

Checks to see if the two matrices are the negative of each other:

a_ij = -b_ij

static boolean

MatrixFeatures_FDRM.isSquare(FMatrixD1 mat)

Checks to see if it is a square matrix.

static boolean

MatrixFeatures_FDRM.isZeros(FMatrixD1 m, float tol)

Checks to see all the elements in the matrix are zeros

static float

NormOps_FDRM.normF(FMatrixD1 a)

Computes the Frobenius matrix norm:

normF = Sqrt{ ∑_i=1:m ∑_j=1:n { a_ij²} }

static float

SpecializedOps_FDRM.qualityTriangular(FMatrixD1 T)

Computes the quality of a triangular matrix, where the quality of a matrix is defined in LinearSolver.quality().

static void

FMatrixComponent.renderMatrix(FMatrixD1 M, BufferedImage image, float maxValue)

static void

CommonOps_FDRM.scale(float alpha, FMatrixD1 a)

Performs an in-place element by element scalar multiplication.

a_ij = α*a_ij

static void

CommonOps_FDRM.scale(float alpha, FMatrixD1 a, FMatrixD1 b)

Performs an element by element scalar multiplication.

b_ij = α*a_ij

void

FMatrixComponent.setMatrix(FMatrixD1 A)

static void

FMatrixVisualization.show(FMatrixD1 A, String title)

Creates a window visually showing the matrix's state.

static void

CommonOps_FDRM.subtractEquals(FMatrixD1 a, FMatrixD1 b)

Performs the following subtraction operation:

a = a - b
a_ij = a_ij - b_ij
Uses of FMatrixD1 in org.ejml.dense.row.misc

Methods in org.ejml.dense.row.misc with type parameters of type FMatrixD1

Modifier and Type

Method

Description

static <T extends FMatrixD1> T

ImplCommonOps_FDRM.elementDiv(T A, T B, T output)

static <T extends FMatrixD1> T

ImplCommonOps_FDRM.elementExp(T A, T output)

static <T extends FMatrixD1> T

ImplCommonOps_FDRM.elementLog(T A, T output)

static <T extends FMatrixD1> T

ImplCommonOps_FDRM.elementMult(T A, T B, T output)

static <T extends FMatrixD1> T

ImplCommonOps_FDRM.elementPower(float a, T B, T output)

static <T extends FMatrixD1> T

ImplCommonOps_FDRM.elementPower(T A, float b, T output)

static <T extends FMatrixD1> T

ImplCommonOps_FDRM.elementPower(T A, T B, T output)

Methods in org.ejml.dense.row.misc with parameters of type FMatrixD1

Modifier and Type

Method

Description

static void

ImplCommonOps_FDRM.elementDiv(FMatrixD1 A, FMatrixD1 B)

static float

ImplCommonOps_FDRM.elementMax(FMatrixD1 a, @Nullable ElementLocation loc)

static float

ImplCommonOps_FDRM.elementMaxAbs(FMatrixD1 a, @Nullable ElementLocation loc)

static float

ImplCommonOps_FDRM.elementMin(FMatrixD1 a, @Nullable ElementLocation loc)

static float

ImplCommonOps_FDRM.elementMinAbs(FMatrixD1 a, @Nullable ElementLocation loc)

static void

ImplCommonOps_FDRM.elementMult(FMatrixD1 A, FMatrixD1 B)

static float

ImplCommonOps_FDRM.elementSum(FMatrixD1 mat)

static float

ImplCommonOps_FDRM.elementSumAbs(FMatrixD1 mat)
Uses of FMatrixD1 in org.ejml.dense.row.mult

Methods in org.ejml.dense.row.mult with parameters of type FMatrixD1

Modifier and Type

Method

Description

static void

VectorVectorMult_FDRM.addOuterProd(float gamma, FMatrixD1 x, FMatrixD1 y, FMatrix1Row A)

Adds to A ∈ ℜ ^{m × n} the results of an outer product multiplication of the two vectors.

static void

VectorVectorMult_FDRM.householder(float gamma, FMatrixD1 u, FMatrixD1 x, FMatrixD1 y)

Multiplies a householder reflection against a vector:

y = (I + γ u u^T)x

static float

VectorVectorMult_FDRM.innerProd(FMatrixD1 x, FMatrixD1 y)

Computes the inner product of the two vectors.

static float

VectorVectorMult_FDRM.innerProdA(FMatrixD1 x, FMatrixD1 A, FMatrixD1 y)

return = x^T*A*y

static float

VectorVectorMult_FDRM.innerProdTranA(FMatrixD1 x, FMatrixD1 A, FMatrixD1 y)

x^TA^Ty

static void

MatrixVectorMult_FDRM.mult(FMatrix1Row A, FMatrixD1 B, FMatrixD1 C)

Performs a matrix vector multiply.

c = A * b
and
c = A * b^T

c_i = Sum{ j=1:n, a_ij * b_j}

where A is a matrix, b is a column or transposed row vector, and c is a column vector.

static void

MatrixVectorMult_FDRM.multAdd(FMatrix1Row A, FMatrixD1 B, FMatrixD1 C)

Performs a matrix vector multiply.

C = C + A * B
or
C = C + A * B^T

c_i = Sum{ j=1:n, c_i + a_ij * b_j}

where A is a matrix, B is a column or transposed row vector, and C is a column vector.

static void

MatrixVectorMult_FDRM.multAddTransA_reorder(FMatrix1Row A, FMatrixD1 B, FMatrixD1 C)

An alternative implementation of MatrixVectorMult_FDRM.multAddTransA_small(org.ejml.data.FMatrix1Row, org.ejml.data.FMatrixD1, org.ejml.data.FMatrixD1) that performs well on large matrices.

static void

MatrixVectorMult_FDRM.multAddTransA_small(FMatrix1Row A, FMatrixD1 B, FMatrixD1 C)

Performs a matrix vector multiply.

C = C + A^T * B
or
C = C^T + A^T * B^T

c_i = Sum{ j=1:n, c_i + a_ji * b_j}

where A is a matrix, B is a column or transposed row vector, and C is a column vector.

static void

MatrixVectorMult_FDRM.multTransA_reorder(FMatrix1Row A, FMatrixD1 B, FMatrixD1 C)

An alternative implementation of MatrixVectorMult_FDRM.multTransA_small(org.ejml.data.FMatrix1Row, org.ejml.data.FMatrixD1, org.ejml.data.FMatrixD1) that performs well on large matrices.

static void

MatrixVectorMult_FDRM.multTransA_small(FMatrix1Row A, FMatrixD1 B, FMatrixD1 C)

Performs a matrix vector multiply.

C = A^T * B
where B is a column vector.
or
C = A^T * B^T
where B is a row vector.

static void

VectorVectorMult_FDRM.outerProd(FMatrixD1 x, FMatrixD1 y, FMatrix1Row A)

Sets A ∈ ℜ ^{m × n} equal to an outer product multiplication of the two vectors.
Uses of FMatrixD1 in org.ejml.masks

Methods in org.ejml.masks with parameters of type FMatrixD1

Modifier and Type

Method

Description

static FMaskPrimitive.Builder

FMaskFactory.builder(FMatrixD1 matrix)

Uses of Classorg.ejml.data.FMatrixD1

Uses of FMatrixD1 in org.ejml.data

Uses of FMatrixD1 in org.ejml.dense.row

Uses of FMatrixD1 in org.ejml.dense.row.misc

Uses of FMatrixD1 in org.ejml.dense.row.mult

Uses of FMatrixD1 in org.ejml.masks

Uses of Class
org.ejml.data.FMatrixD1