Uses of Interface
org.episteme.core.mathematics.linearalgebra.Matrix
Packages that use Matrix
Package
Description
Provides classes for social geography, human settlements, and mapping.
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Uses of Matrix in org.episteme.benchmarks.benchmark.benchmarks
Methods in org.episteme.benchmarks.benchmark.benchmarks that return Matrix -
Uses of Matrix in org.episteme.client.client.mathematics.linearalgebra.backends
Methods in org.episteme.client.client.mathematics.linearalgebra.backends that return MatrixModifier and TypeMethodDescriptionMethods in org.episteme.client.client.mathematics.linearalgebra.backends with parameters of type MatrixModifier and TypeMethodDescriptionGRPCLinearAlgebraBackend.bicgstab(Matrix<E> a, Vector<E> b, Vector<E> x0, E tolerance, int maxIterations) GRPCLinearAlgebraBackend.conjugateGradient(Matrix<E> a, Vector<E> b, Vector<E> x0, E tolerance, int maxIterations) GRPCLinearAlgebraBackend.determinant(Matrix<E> a) GRPCLinearAlgebraBackend.gmres(Matrix<E> a, Vector<E> b, Vector<E> x0, E tolerance, int maxIterations, int restart) GRPCLinearAlgebraBackend.solveTriangular(Matrix<E> A, Vector<E> b, boolean upper, boolean transpose, boolean conjugate, boolean unit) -
Uses of Matrix in org.episteme.core.io.interop
Methods in org.episteme.core.io.interop with parameters of type MatrixModifier and TypeMethodDescriptionstatic ByteBufferArrowAdapter.toArrowBuffer(Matrix<Real> matrix) Converts a Matrix to an Arrow-compatible ByteBuffer (Float64 array). -
Uses of Matrix in org.episteme.core.mathematics.algebra.algebras
Classes in org.episteme.core.mathematics.algebra.algebras that implement interfaces with type arguments of type MatrixModifier and TypeClassDescriptionclassA concrete Lie Algebra where elements are square matrices and the bracket is the commutator [A, B] = AB - BA.Methods in org.episteme.core.mathematics.algebra.algebras that return MatrixMethods in org.episteme.core.mathematics.algebra.algebras with parameters of type MatrixModifier and TypeMethodDescriptionboolean -
Uses of Matrix in org.episteme.core.mathematics.algebra.categories
Classes in org.episteme.core.mathematics.algebra.categories that implement interfaces with type arguments of type MatrixModifier and TypeClassDescriptionclassRepresents the Category of Hilbert Spaces (Hilb).Methods in org.episteme.core.mathematics.algebra.categories that return MatrixModifier and TypeMethodDescriptionMatrix<?> Matrix<?> HilbertSpacesCategory.identity(HilbertSpace<?, ?> object) Methods in org.episteme.core.mathematics.algebra.categories that return types with arguments of type MatrixModifier and TypeMethodDescriptionHilbertSpacesCategory.hom(HilbertSpace<?, ?> source, HilbertSpace<?, ?> target) Methods in org.episteme.core.mathematics.algebra.categories with parameters of type Matrix -
Uses of Matrix in org.episteme.core.mathematics.algebra.groups
Classes in org.episteme.core.mathematics.algebra.groups that implement interfaces with type arguments of type MatrixModifier and TypeClassDescriptionclassA Lie group is a group that is also a differentiable manifold.classThe group of all linear transformations of Minkowski space that preserve the spacetime interval ds²=-c²dt²+dx²+dy²+dz².classThe group of 2x2 unitary matrices with determinant 1.classThe group of 3x3 unitary matrices with determinant 1.Methods in org.episteme.core.mathematics.algebra.groups that return MatrixModifier and TypeMethodDescriptionSO3_1Group.boostX(double beta) Creates a boost matrix in the x-direction.LieGroup.getElement(Vector<Real> v) Generates a group element near the identity using the exponential map approximation.LieGroup.identity()SO3_1Group.identity()SU2Group.identity()SU3Group.identity()Methods in org.episteme.core.mathematics.algebra.groups with parameters of type MatrixModifier and TypeMethodDescriptionbooleanbooleanbooleanbooleanConstructors in org.episteme.core.mathematics.algebra.groups with parameters of type Matrix -
Uses of Matrix in org.episteme.core.mathematics.analysis
Methods in org.episteme.core.mathematics.analysis that return Matrix -
Uses of Matrix in org.episteme.core.mathematics.analysis.fem
Methods in org.episteme.core.mathematics.analysis.fem that return MatrixModifier and TypeMethodDescriptionElement.computeJacobian(Vector<Real> localCoords) Computes the Jacobian matrix at the given local coordinates.LinearElement1D.computeJacobian(Vector<Real> localCoords) TetrahedralElement3D.computeJacobian(Vector<Real> localCoords) TriangularElement2D.computeJacobian(Vector<Real> localCoords) -
Uses of Matrix in org.episteme.core.mathematics.analysis.transform
Methods in org.episteme.core.mathematics.analysis.transform that return Matrix -
Uses of Matrix in org.episteme.core.mathematics.linearalgebra
Subinterfaces with type arguments of type Matrix in org.episteme.core.mathematics.linearalgebraModifier and TypeInterfaceDescriptioninterfaceMatrix<E>Represents a matrix of scalar elements.interfaceMatrix<E>Represents a matrix of scalar elements.Methods in org.episteme.core.mathematics.linearalgebra that return MatrixModifier and TypeMethodDescriptionReturns the sum of this matrix and another.LinearAlgebraProvider.conjugateTranspose(Matrix<E> a) Computes the matrix exponential e^A.Converts a dense matrix to its sparse representation.Matrix.getSubMatrix(int rowStart, int rowEnd, int colStart, int colEnd) Returns a submatrix of this matrix.Matrix.identity()static <E> Matrix<E> Creates an identity matrix.Matrix.inverse()Returns the multiplicative inverse of this matrix.Applies a mapping function to each element of this matrix.Returns the product of this matrix and another.Matrix.negate()Returns the negation of this matrix (-this).static <E> Matrix<E> Creates a matrix from a 2D array.static <E> Matrix<E> Creates a matrix from a 2D list.Convenience scalar multiplication (scalar × this).Returns the difference of this matrix and another.Converts a sparse matrix to its dense representation.Vector.toMatrix()Converts this vector to a column matrix (Nx1).Matrix.transpose()Returns the transpose of this matrix.static <E> Matrix<E> Matrix.triangular(List<List<E>> data, Ring<E> ring) Creates a triangular matrix from a 2D list.static <E> Matrix<E> Matrix.tridiagonal(List<List<E>> data, Ring<E> ring) Creates a tridiagonal matrix from a 2D list.Matrix.zero()Returns the zero matrix of the same dimensions.static <E> Matrix<E> Creates a matrix of zeros.Methods in org.episteme.core.mathematics.linearalgebra with parameters of type MatrixModifier and TypeMethodDescriptionReturns the sum of this matrix and another.static <E> Vector<E> Solves Ax = b using BiCGSTAB.SparseLinearAlgebraProvider.bicgstab(Matrix<E> a, Vector<E> b, Vector<E> x0, E tolerance, int maxIterations) Solves Ax = b using BiCGSTAB (BiConjugate Gradient Stabilized) method.static <E> CholeskyResult<E> Computes the Cholesky decomposition of the specified matrix.default CholeskyResult<E> Computes the Cholesky decomposition of the specified matrix.default ELinearAlgebraProvider.conditionNumber(Matrix<E> a) Returns the condition number of the matrix (L2 norm).default ESparseLinearAlgebraProvider.conditionNumber(Matrix<E> a) static <E> Vector<E> Decomposition.conjugateGradient(Matrix<E> a, Vector<E> b, Vector<E> x0, E tolerance, int maxIterations) Solves Ax = b using Conjugate Gradient.SparseLinearAlgebraProvider.conjugateGradient(Matrix<E> a, Vector<E> b, Vector<E> x0, E tolerance, int maxIterations) Solves Ax = b using Conjugate Gradient method.LinearAlgebraProvider.conjugateTranspose(Matrix<E> a) default ELinearAlgebraProvider.determinant(Matrix<E> a) static <E> EigenResult<E> Computes the eigenvalue decomposition of the specified matrix.default EigenResult<E> Computes the eigenvalue decomposition of the specified matrix.Computes the matrix exponential e^A.Converts a dense matrix to its sparse representation.static <E> Vector<E> Decomposition.gmres(Matrix<E> a, Vector<E> b, Vector<E> x0, E tolerance, int maxIterations, int restarts) Solves Ax = b using GMRES.SparseLinearAlgebraProvider.gmres(Matrix<E> a, Vector<E> b, Vector<E> x0, E tolerance, int maxIterations, int restarts) Solves Ax = b using GMRES (Generalized Minimal Residual) method.static <E> LUResult<E> Computes the LU decomposition of the specified matrix.Computes the LU decomposition of the specified matrix.Returns the product of this matrix and another.static <E> QRResult<E> Computes the QR decomposition of the specified matrix.Computes the QR decomposition of the specified matrix.default intReturns the rank of the matrix.default intstatic <E> Vector<E> Solves Ax = b using the most appropriate decomposition.LinearAlgebraProvider.solveTriangular(Matrix<E> A, Vector<E> b, boolean upper, boolean transpose, boolean conjugate, boolean unit) Solves the triangular system Ax = b.Returns the difference of this matrix and another.static <E> SVDResult<E> Computes the Singular Value Decomposition (SVD) of the specified matrix.Computes the Singular Value Decomposition (SVD) of the specified matrix.Converts a sparse matrix to its dense representation.default E -
Uses of Matrix in org.episteme.core.mathematics.linearalgebra.algorithms
Methods in org.episteme.core.mathematics.linearalgebra.algorithms that return MatrixModifier and TypeMethodDescriptionstatic <E> Matrix<E> static <E> Matrix<E> RealCARMAAlgorithm.multiply(Matrix<E> A, Matrix<E> B, LinearAlgebraProvider<E> leafProvider) static <E> Matrix<E> RealStrassenAlgorithm.multiply(Matrix<E> A, Matrix<E> B, LinearAlgebraProvider<E> leafProvider) Methods in org.episteme.core.mathematics.linearalgebra.algorithms with parameters of type MatrixModifier and TypeMethodDescriptionstatic voidDistributedCannonAlgorithm.multiply(Matrix<Real> A, Matrix<Real> B, Matrix<Real> C, DistributedContext ctx) Multiplies two matrices distributed across a 2D processor grid.static <E> Matrix<E> static <E> Matrix<E> RealCARMAAlgorithm.multiply(Matrix<E> A, Matrix<E> B, LinearAlgebraProvider<E> leafProvider) static <E> Matrix<E> RealStrassenAlgorithm.multiply(Matrix<E> A, Matrix<E> B, LinearAlgebraProvider<E> leafProvider) -
Uses of Matrix in org.episteme.core.mathematics.linearalgebra.backends
Methods in org.episteme.core.mathematics.linearalgebra.backends that return MatrixModifier and TypeMethodDescriptionMethods in org.episteme.core.mathematics.linearalgebra.backends with parameters of type MatrixModifier and TypeMethodDescriptionEpistemeLinearAlgebraBackend.bicgstab(Matrix<E> a, Vector<E> b, Vector<E> x0, E tolerance, int maxIterations) EpistemeLinearAlgebraBackend.conjugateGradient(Matrix<E> a, Vector<E> b, Vector<E> x0, E tolerance, int maxIterations) ColtBackend.determinant(Matrix<E> a) CommonsMathBackend.determinant(Matrix<E> a) EJMLBackend.determinant(Matrix<E> a) EpistemeLinearAlgebraBackend.determinant(Matrix<E> a) JBlasBackend.determinant(Matrix<E> a) EpistemeLinearAlgebraBackend.gmres(Matrix<E> a, Vector<E> b, Vector<E> x0, E tolerance, int maxIterations, int restarts) EJMLBackend.solveTriangular(Matrix<E> A, Vector<E> b, boolean upper, boolean transpose, boolean conjugate, boolean unit) EpistemeLinearAlgebraBackend.solveTriangular(Matrix<E> a, Vector<E> b, boolean upper, boolean transpose, boolean conjugate, boolean unit) JBlasBackend.solveTriangular(Matrix<E> A, Vector<E> b, boolean upper, boolean transpose, boolean conjugate, boolean unit) -
Uses of Matrix in org.episteme.core.mathematics.linearalgebra.matrices
Classes in org.episteme.core.mathematics.linearalgebra.matrices that implement MatrixModifier and TypeClassDescriptionclassDenseMatrix<E>A dense matrix implementation.classA generic matrix implementation with smart storage and provider selection.classMemory-Mapped Matrix implementation for Out-of-Core processing.classA specialized Matrix implementation for Doubles with SIMD and Native optimization.classSIMD-accelerated Matrix implementation using JDK Vector API.classSIMD-accelerated Matrix implementation using JDK Vector API for Float (Single) precision.classSparseMatrix<E>A sparse matrix implementation.classTiledMatrix<E>A matrix decomposed into smaller tiles (blocks).Methods in org.episteme.core.mathematics.linearalgebra.matrices that return MatrixModifier and TypeMethodDescriptionSIMDRealDoubleMatrix.abs()SIMDRealFloatMatrix.abs()SIMDRealDoubleMatrix.acos()SIMDRealFloatMatrix.acos()SIMDRealDoubleMatrix.acosh()SIMDRealFloatMatrix.acosh()SIMDRealDoubleMatrix.asin()SIMDRealFloatMatrix.asin()SIMDRealDoubleMatrix.asinh()SIMDRealFloatMatrix.asinh()SIMDRealDoubleMatrix.atan()SIMDRealFloatMatrix.atan()SIMDRealDoubleMatrix.atanh()SIMDRealFloatMatrix.atanh()SIMDRealDoubleMatrix.cbrt()SIMDRealFloatMatrix.cbrt()SIMDRealDoubleMatrix.cos()SIMDRealFloatMatrix.cos()SIMDRealDoubleMatrix.cosh()SIMDRealFloatMatrix.cosh()SIMDRealDoubleMatrix.exp()SIMDRealFloatMatrix.exp()GenericMatrix.getSubMatrix(int rowStart, int rowEnd, int colStart, int colEnd) MMapMatrix.getSubMatrix(int rs, int re, int cs, int ce) SIMDRealDoubleMatrix.getSubMatrix(int rs, int re, int cs, int ce) TiledMatrix.getTile(int i, int j) GenericMatrix.inverse()MMapMatrix.inverse()SIMDRealDoubleMatrix.inverse()SIMDRealDoubleMatrix.log()SIMDRealFloatMatrix.log()SIMDRealDoubleMatrix.log10()SIMDRealFloatMatrix.log10()static <E> Matrix<E> DistributedMatrixMultiply.multiply(TiledMatrix<E> A, TiledMatrix<E> B) Multiplies two matrices using a tiled algorithm distributed across the current context.GenericMatrix.negate()MMapMatrix.negate()SIMDRealDoubleMatrix.negate()SIMDRealFloatMatrix.negate()static <E> Matrix<E> Creates a DenseMatrix with automatic storage optimization.static <E> Matrix<E> Creates a DenseMatrix with automatic storage optimization.GenericMatrix.one()MMapMatrix.one()SIMDRealDoubleMatrix.one()SIMDRealFloatMatrix.one()SIMDRealDoubleMatrix.powScalar(double exponent) SIMDRealFloatMatrix.powScalar(float exponent) SIMDRealDoubleMatrix.scale(double scalar) SIMDRealFloatMatrix.scale(float scalar) SIMDRealDoubleMatrix.sin()SIMDRealFloatMatrix.sin()SIMDRealDoubleMatrix.sinh()SIMDRealFloatMatrix.sinh()SIMDRealDoubleMatrix.sqrt()SIMDRealFloatMatrix.sqrt()SIMDRealDoubleMatrix.tan()SIMDRealFloatMatrix.tan()SIMDRealDoubleMatrix.tanh()SIMDRealFloatMatrix.tanh()GenericMatrix.transpose()MMapMatrix.transpose()SIMDRealDoubleMatrix.transpose()SIMDRealFloatMatrix.transpose()GenericMatrix.zero()MMapMatrix.zero()SIMDRealDoubleMatrix.zero()SIMDRealFloatMatrix.zero()Methods in org.episteme.core.mathematics.linearalgebra.matrices with parameters of type MatrixModifier and TypeMethodDescriptionbooleanbooleanbooleanstatic SIMDRealDoubleMatrixstatic SIMDRealFloatMatrixvoidvoidTiledMatrix.updateTile(int i, int j, Matrix<E> delta) Thread-safe update of a tile (adds delta to current tile).Constructors in org.episteme.core.mathematics.linearalgebra.matrices with parameters of type MatrixModifierConstructorDescriptionTiledMatrix(Matrix<E> original, int tileRows, int tileCols) Creates a TiledMatrix from an existing matrix. -
Uses of Matrix in org.episteme.core.mathematics.linearalgebra.matrices.solvers
Methods in org.episteme.core.mathematics.linearalgebra.matrices.solvers that return MatrixModifier and TypeMethodDescriptionEigenResult.getEigenvectors()CholeskyResult.getL()LUResult.getL()LUResult.getOriginalA()Reconstructs the original matrix A (un-permuted).QRResult.getQ()QRResult.getR()LUResult.getU()SVDResult.getU()EigenResult.getV()SVDResult.getV()static <E> Matrix<E> GenericLU.inverse(Matrix<E> a, Field<E> field, LinearAlgebraProvider<E> provider) CholeskyResult.L()Returns the value of theLrecord component.LUResult.L()Returns the value of theLrecord component.QRResult.Q()Returns the value of theQrecord component.QRResult.R()Returns the value of theRrecord component.LUResult.reconstruct()Reconstructs the matrix A (as permuted by P).LUResult.U()Returns the value of theUrecord component.SVDResult.U()Returns the value of theUrecord component.EigenResult.V()Returns the value of theVrecord component.SVDResult.V()Returns the value of theVrecord component.Methods in org.episteme.core.mathematics.linearalgebra.matrices.solvers with parameters of type MatrixModifier and TypeMethodDescriptionstatic CholeskyResult<Real> Computes Cholesky decomposition using the best available LinearAlgebraProvider.static EigenResult<Real> Computes Eigenvalue decomposition using the best available LinearAlgebraProvider.static <E> CholeskyResult<E> GenericCholesky.decompose(Matrix<E> matrix, Field<E> field, LinearAlgebraProvider<E> provider) static <E> EigenResult<E> GenericEigen.decompose(Matrix<E> matrix, Field<E> field, LinearAlgebraProvider<E> provider) static <E> LUResult<E> GenericLU.decompose(Matrix<E> matrix, Field<E> field, LinearAlgebraProvider<E> provider) static <E> QRResult<E> GenericQR.decompose(Matrix<E> matrix, Field<E> field, LinearAlgebraProvider<E> provider) static <E> SVDResult<E> GenericSVD.decompose(Matrix<E> matrix, Field<E> field, LinearAlgebraProvider<E> provider) Computes LU decomposition using the best available LinearAlgebraProvider.Computes QR decomposition using the best available LinearAlgebraProvider.Computes SVD decomposition using the best available LinearAlgebraProvider.static <E> EGenericLU.determinant(Matrix<E> a, Field<E> field, LinearAlgebraProvider<E> provider) static <E> Matrix<E> GenericLU.inverse(Matrix<E> a, Field<E> field, LinearAlgebraProvider<E> provider) static booleanMatrixSolver.isSymmetric(Matrix<Real> A) static MatrixSolver.StrategyRecommends the best solver strategy for the given matrix.static <E> Vector<E> GenericLU.solve(Matrix<E> a, Vector<E> b, Field<E> field, LinearAlgebraProvider<E> provider) static Real[]Solves Ax = b with automatic algorithm selection.static Real[]MatrixSolver.solve(Matrix<Real> A, Real[] b, MatrixSolver.Strategy strategy) Solves Ax = b with explicit algorithm selection.Constructors in org.episteme.core.mathematics.linearalgebra.matrices.solvers with parameters of type MatrixModifierConstructorDescriptionCholeskyResult(Matrix<E> L) Creates an instance of aCholeskyResultrecord class.EigenResult(Matrix<E> V, Vector<E> D) Creates an instance of aEigenResultrecord class.Creates an instance of aLUResultrecord class.Creates an instance of aQRResultrecord class.Creates an instance of aSVDResultrecord class. -
Uses of Matrix in org.episteme.core.mathematics.linearalgebra.matrices.solvers.sparse
Methods in org.episteme.core.mathematics.linearalgebra.matrices.solvers.sparse with parameters of type MatrixModifier and TypeMethodDescriptionstatic <E> Vector<E> GenericSparseSolvers.bicgstab(SparseLinearAlgebraProvider<E> provider, Matrix<E> A, Vector<E> b, Vector<E> x0, E tolerance, int maxIterations, Field<E> f) static <E> Vector<E> GenericSparseSolvers.conjugateGradient(SparseLinearAlgebraProvider<E> provider, Matrix<E> A, Vector<E> b, Vector<E> x0, E tolerance, int maxIterations, Field<E> f) static <E> Vector<E> GenericSparseSolvers.gmres(SparseLinearAlgebraProvider<E> provider, Matrix<E> A, Vector<E> b, Vector<E> x0, E tolerance, int maxIterations, int restarts, Field<E> f) static Real[]Solves Ax = b using BiCGSTAB.static Real[]Solves Ax = b using Conjugate Gradient.static Real[]Solves Ax = b using GMRES with restarts. -
Uses of Matrix in org.episteme.core.mathematics.linearalgebra.matrices.storage
Methods in org.episteme.core.mathematics.linearalgebra.matrices.storage that return MatrixModifier and TypeMethodDescriptionTiledMatrixStorage.getTile(int tileRow, int tileCol) Gets a tile at the specified position.Methods in org.episteme.core.mathematics.linearalgebra.matrices.storage with parameters of type MatrixModifier and TypeMethodDescriptionvoidSets a tile at the specified position.Constructors in org.episteme.core.mathematics.linearalgebra.matrices.storage with parameters of type MatrixModifierConstructorDescriptionTiledMatrixStorage(Matrix<E>[][] tiles, int rows, int cols, int tileRows, int tileCols) Creates a tiled matrix storage. -
Uses of Matrix in org.episteme.core.mathematics.linearalgebra.providers
Methods in org.episteme.core.mathematics.linearalgebra.providers that return MatrixModifier and TypeMethodDescriptionstatic <E> Matrix<E> CPUDenseLinearAlgebraProvider.standardMultiply(Matrix<E> a, Matrix<E> b, Field<E> field, LinearAlgebraProvider<E> provider) Methods in org.episteme.core.mathematics.linearalgebra.providers with parameters of type MatrixModifier and TypeMethodDescriptionCPUSparseLinearAlgebraProvider.bicgstab(Matrix<E> a, Vector<E> b, Vector<E> x0, E tolerance, int maxIterations) DistributedLinearAlgebraProvider.bicgstab(Matrix<E> a, Vector<E> b, Vector<E> x0, E tolerance, int maxIterations) CPUSparseLinearAlgebraProvider.conjugateGradient(Matrix<E> a, Vector<E> b, Vector<E> x0, E tolerance, int maxIterations) DistributedLinearAlgebraProvider.conjugateGradient(Matrix<E> a, Vector<E> b, Vector<E> x0, E tolerance, int maxIterations) CPUDenseLinearAlgebraProvider.determinant(Matrix<E> a) CPUSparseLinearAlgebraProvider.determinant(Matrix<E> a) DistributedLinearAlgebraProvider.determinant(Matrix<E> a) StrassenLinearAlgebraProvider.determinant(Matrix<E> a) CPUSparseLinearAlgebraProvider.gmres(Matrix<E> a, Vector<E> b, Vector<E> x0, E tolerance, int maxIterations, int restarts) DistributedLinearAlgebraProvider.gmres(Matrix<E> a, Vector<E> b, Vector<E> x0, E tolerance, int maxIterations, int restarts) CPUDenseLinearAlgebraProvider.solveTriangular(Matrix<E> A, Vector<E> b, boolean upper, boolean transpose, boolean conjugate, boolean unit) CPUSparseLinearAlgebraProvider.solveTriangular(Matrix<E> A, Vector<E> b, boolean upper, boolean transpose, boolean conjugate, boolean unit) DistributedLinearAlgebraProvider.solveTriangular(Matrix<E> A, Vector<E> b, boolean upper, boolean transpose, boolean conjugate, boolean unit) static <E> Matrix<E> CPUDenseLinearAlgebraProvider.standardMultiply(Matrix<E> a, Matrix<E> b, Field<E> field, LinearAlgebraProvider<E> provider) -
Uses of Matrix in org.episteme.core.mathematics.linearalgebra.vectors
Methods in org.episteme.core.mathematics.linearalgebra.vectors that return Matrix -
Uses of Matrix in org.episteme.core.mathematics.ml
Methods in org.episteme.core.mathematics.ml that return Matrix -
Uses of Matrix in org.episteme.core.mathematics.sets
Classes in org.episteme.core.mathematics.sets that implement interfaces with type arguments of type MatrixModifier and TypeClassDescriptionfinal classThe structure of n×n square matrices over a field, forming a ring.Methods in org.episteme.core.mathematics.sets that return MatrixMethods in org.episteme.core.mathematics.sets with parameters of type MatrixModifier and TypeMethodDescriptionboolean -
Uses of Matrix in org.episteme.core.mathematics.util
Methods in org.episteme.core.mathematics.util that return MatrixModifier and TypeMethodDescriptionArrayConverters.toMatrix(double[][] arr) Converts a 2D primitive double array to Matrix. Methods in org.episteme.core.mathematics.util with parameters of type MatrixModifier and TypeMethodDescriptionstatic double[][]ArrayConverters.toDoubleMatrix(Matrix<Real> m) Converts a Matrixto 2D primitive double array. -
Uses of Matrix in org.episteme.nativ.mathematics.linearalgebra.backends
Methods in org.episteme.nativ.mathematics.linearalgebra.backends that return MatrixModifier and TypeMethodDescriptionNativeMPFRDenseLinearAlgebraBackend.applyTranscendental(Matrix<E> a, String op, Object... args) NativeMPFRSparseLinearAlgebraBackend.applyTranscendental(Matrix<E> a, String op, Object... args) AbstractNativeFFMBLASBackend.conjugateTranspose(Matrix<E> m) NativeCUDADenseLinearAlgebraDoubleBackend.conjugateTranspose(Matrix<E> a) NativeCUDADenseLinearAlgebraFloatBackend.conjugateTranspose(Matrix<E> a) NativeCUDASparseLinearAlgebraDoubleBackend.conjugateTranspose(Matrix<E> a) NativeCUDASparseLinearAlgebraFloatBackend.conjugateTranspose(Matrix<E> a) NativeMPFRDenseLinearAlgebraBackend.conjugateTranspose(Matrix<E> a) NativeOpenCLDenseLinearAlgebraDoubleBackend.conjugateTranspose(Matrix<E> a) NativeOpenCLDenseLinearAlgebraFloatBackend.conjugateTranspose(Matrix<E> a) NativeOpenCLSparseLinearAlgebraDoubleBackend.conjugateTranspose(Matrix<E> a) NativeOpenCLSparseLinearAlgebraFloatBackend.conjugateTranspose(Matrix<E> a) Methods in org.episteme.nativ.mathematics.linearalgebra.backends with parameters of type MatrixModifier and TypeMethodDescriptionNativeMPFRDenseLinearAlgebraBackend.applyTranscendental(Matrix<E> a, String op, Object... args) NativeMPFRSparseLinearAlgebraBackend.applyTranscendental(Matrix<E> a, String op, Object... args) NativeCUDASparseLinearAlgebraDoubleBackend.bicgstab(Matrix<E> a, Vector<E> b, Vector<E> x0, E tolerance, int maxIterations) NativeCUDASparseLinearAlgebraFloatBackend.bicgstab(Matrix<E> a, Vector<E> b, Vector<E> x0, E tolerance, int maxIterations) NativeMPFRSparseLinearAlgebraBackend.bicgstab(Matrix<E> a, Vector<E> b, Vector<E> x0, E tolerance, int maxIterations) NativeOpenCLSparseLinearAlgebraDoubleBackend.bicgstab(Matrix<E> a, Vector<E> b, Vector<E> x0, E tolerance, int maxIterations) NativeOpenCLSparseLinearAlgebraFloatBackend.bicgstab(Matrix<E> a, Vector<E> b, Vector<E> x0, E tolerance, int maxIterations) AbstractNativeFFMBLASBackend.conditionNumber(Matrix<E> a) NativeCUDASparseLinearAlgebraDoubleBackend.conjugateGradient(Matrix<E> a, Vector<E> b, Vector<E> x0, E tolerance, int maxIterations) NativeCUDASparseLinearAlgebraFloatBackend.conjugateGradient(Matrix<E> a, Vector<E> b, Vector<E> x0, E tolerance, int maxIterations) NativeMPFRSparseLinearAlgebraBackend.conjugateGradient(Matrix<E> a, Vector<E> b, Vector<E> x0, E tolerance, int maxIterations) NativeOpenCLSparseLinearAlgebraDoubleBackend.conjugateGradient(Matrix<E> a, Vector<E> b, Vector<E> x0, E tolerance, int maxIterations) NativeOpenCLSparseLinearAlgebraFloatBackend.conjugateGradient(Matrix<E> a, Vector<E> b, Vector<E> x0, E tolerance, int maxIterations) AbstractNativeFFMBLASBackend.conjugateTranspose(Matrix<E> m) NativeCUDADenseLinearAlgebraDoubleBackend.conjugateTranspose(Matrix<E> a) NativeCUDADenseLinearAlgebraFloatBackend.conjugateTranspose(Matrix<E> a) NativeCUDASparseLinearAlgebraDoubleBackend.conjugateTranspose(Matrix<E> a) NativeCUDASparseLinearAlgebraFloatBackend.conjugateTranspose(Matrix<E> a) NativeMPFRDenseLinearAlgebraBackend.conjugateTranspose(Matrix<E> a) NativeOpenCLDenseLinearAlgebraDoubleBackend.conjugateTranspose(Matrix<E> a) NativeOpenCLDenseLinearAlgebraFloatBackend.conjugateTranspose(Matrix<E> a) NativeOpenCLSparseLinearAlgebraDoubleBackend.conjugateTranspose(Matrix<E> a) NativeOpenCLSparseLinearAlgebraFloatBackend.conjugateTranspose(Matrix<E> a) AbstractNativeCPULinearAlgebraBackend.determinant(Matrix<E> a) AbstractNativeFFMBLASBackend.determinant(Matrix<E> A) AbstractNativeSIMDLinearAlgebraBackend.determinant(Matrix<E> a) NativeCUDADenseLinearAlgebraDoubleBackend.determinant(Matrix<E> a) NativeCUDADenseLinearAlgebraFloatBackend.determinant(Matrix<E> a) NativeMPFRDenseLinearAlgebraBackend.determinant(Matrix<E> a) NativeMPFRSparseLinearAlgebraBackend.determinant(Matrix<E> a) NativeND4JLinearAlgebraBackend.determinant(Matrix<Real> a) Determinant via Gaussian elimination on ND4J arrays.NativeOpenCLDenseLinearAlgebraDoubleBackend.determinant(Matrix<E> a) NativeOpenCLDenseLinearAlgebraFloatBackend.determinant(Matrix<E> a) NativeMPFRSparseLinearAlgebraBackend.gmres(Matrix<E> a, Vector<E> b, Vector<E> x0, E tolerance, int maxIterations, int restarts) NativeOpenCLSparseLinearAlgebraDoubleBackend.gmres(Matrix<E> a, Vector<E> b, Vector<E> x0, E tolerance, int maxIterations, int restarts) LU decomposition via Gaussian elimination on ND4J arrays.QR decomposition via ND4J's 'qr' custom op.intSolve Ax=b via ND4J's LU decomposition.AbstractNativeCPULinearAlgebraBackend.solveTriangular(Matrix<E> A, Vector<E> b, boolean upper, boolean transpose, boolean conjugate, boolean unit) AbstractNativeFFMBLASBackend.solveTriangular(Matrix<E> A, Vector<E> b, boolean upper, boolean transpose, boolean conjugate, boolean unit) AbstractNativeSIMDLinearAlgebraBackend.solveTriangular(Matrix<E> A, Vector<E> b, boolean upper, boolean transpose, boolean conjugate, boolean unit) NativeCUDADenseLinearAlgebraDoubleBackend.solveTriangular(Matrix<E> a, Vector<E> b, boolean upper, boolean transpose, boolean conjugate, boolean unit) NativeCUDADenseLinearAlgebraFloatBackend.solveTriangular(Matrix<E> a, Vector<E> b, boolean upper, boolean transpose, boolean conjugate, boolean unit) NativeMPFRDenseLinearAlgebraBackend.solveTriangular(Matrix<E> A, Vector<E> b, boolean upper, boolean transpose, boolean conjugate, boolean unit) NativeMPFRSparseLinearAlgebraBackend.solveTriangular(Matrix<E> A, Vector<E> b, boolean upper, boolean transpose, boolean conjugate, boolean unit) NativeND4JLinearAlgebraBackend.solveTriangular(Matrix<Real> A, Vector<Real> b, boolean upper, boolean transpose, boolean conjugate, boolean unit) NativeOpenCLDenseLinearAlgebraDoubleBackend.solveTriangular(Matrix<E> a, Vector<E> b, boolean upper, boolean transpose, boolean conjugate, boolean unit) NativeOpenCLDenseLinearAlgebraFloatBackend.solveTriangular(Matrix<E> a, Vector<E> b, boolean upper, boolean transpose, boolean conjugate, boolean unit) SVD using ND4J's built-in Svd custom op. -
Uses of Matrix in org.episteme.nativ.mathematics.linearalgebra.matrices
Classes in org.episteme.nativ.mathematics.linearalgebra.matrices that implement MatrixModifier and TypeClassDescriptionclassHigh-performance Real Double Matrix backed by a persistent native MemorySegment.classHigh-performance Real Float Matrix backed by a persistent native MemorySegment.Methods in org.episteme.nativ.mathematics.linearalgebra.matrices that return MatrixMethods in org.episteme.nativ.mathematics.linearalgebra.matrices with parameters of type MatrixModifier and TypeMethodDescriptionstatic NativeRealDoubleMatrixNativeRealDoubleMatrix.copyOf(Matrix<Real> other, Arena arena, LinearAlgebraProvider<Real> provider) static NativeRealFloatMatrix -
Uses of Matrix in org.episteme.nativ.mathematics.linearalgebra.matrices.storage
Methods in org.episteme.nativ.mathematics.linearalgebra.matrices.storage that return Matrix -
Uses of Matrix in org.episteme.natural.biology.ecology
Methods in org.episteme.natural.biology.ecology with parameters of type Matrix -
Uses of Matrix in org.episteme.natural.chemistry.computational.quantum
Fields in org.episteme.natural.chemistry.computational.quantum declared as MatrixModifier and TypeFieldDescriptionSCFMethod.densityMatrixSCFMethod.fockMatrixSCFMethod.overlapMatrixMethods in org.episteme.natural.chemistry.computational.quantum that return MatrixModifier and TypeMethodDescriptionDIISSubspace.extrapolate()Extrapolates a new Fock matrix using the DIIS equations.OneElectronIntegrals.getCoreHamiltonian()SCFMethod.getDensityMatrix()SCFMethod.getFockMatrix()OneElectronIntegrals.getOverlap()Methods in org.episteme.natural.chemistry.computational.quantum with parameters of type MatrixModifier and TypeMethodDescriptionvoidAdds an iteration to the subspace.Constructors in org.episteme.natural.chemistry.computational.quantum with parameters of type MatrixModifierConstructorDescriptionOneElectronIntegrals(Matrix<Real> coreHamiltonian, Matrix<Real> overlap) -
Uses of Matrix in org.episteme.natural.engineering.robotics
Methods in org.episteme.natural.engineering.robotics that return MatrixModifier and TypeMethodDescriptionKinematics.dhMatrix(Quantity<Angle> theta, Quantity<Length> d, Quantity<Length> a, Quantity<Angle> alpha) Denavit-Hartenberg transformation matrix.Kinematics.jacobian2Link(Quantity<Length> L1, Quantity<Length> L2, Quantity<Angle> theta1, Quantity<Angle> theta2) Jacobian for 2-link planar arm (velocity kinematics).Methods in org.episteme.natural.engineering.robotics with parameters of type MatrixModifier and TypeMethodDescriptionKinematics.getPosition(Matrix<Real> T) Extracts position vector from a 4x4 transformation matrix. -
Uses of Matrix in org.episteme.natural.physics.classical.mechanics
Methods in org.episteme.natural.physics.classical.mechanics that return MatrixModifier and TypeMethodDescriptionProjectileMotion.getTrajectory(int numPoints) Generates trajectory points as a Matrix. -
Uses of Matrix in org.episteme.natural.physics.classical.mechanics.collision
Methods in org.episteme.natural.physics.classical.mechanics.collision that return MatrixModifier and TypeMethodDescriptionRigidBody.getInertiaTensor()RigidBody.getInverseInertiaTensor()Constructors in org.episteme.natural.physics.classical.mechanics.collision with parameters of type Matrix -
Uses of Matrix in org.episteme.natural.physics.quantum.backends
Methods in org.episteme.natural.physics.quantum.backends that return MatrixModifier and TypeMethodDescriptionAmazonBraketBackend.stateTomography(QuantumBackend.QuantumCircuit c, int s) PythonQuantumBackend.stateTomography(QuantumBackend.QuantumCircuit c, int s) QiskitBackend.stateTomography(QuantumBackend.QuantumCircuit c, int s) Quantum4JBackend.stateTomography(QuantumBackend.QuantumCircuit c, int s) StrangeBackend.stateTomography(QuantumBackend.QuantumCircuit c, int s) Methods in org.episteme.natural.physics.quantum.backends with parameters of type MatrixModifier and TypeMethodDescriptionAmazonBraketBackend.matrixToUnitary(Matrix<Complex> m) PythonQuantumBackend.matrixToUnitary(Matrix<Complex> m) QiskitBackend.matrixToUnitary(Matrix<Complex> m) Quantum4JBackend.matrixToUnitary(Matrix<Complex> m) StrangeBackend.matrixToUnitary(Matrix<Complex> m) doubleAmazonBraketBackend.quantumPhaseEstimation(Matrix<Complex> u, Vector<Complex> e, int p) doublePythonQuantumBackend.quantumPhaseEstimation(Matrix<Complex> u, Vector<Complex> e, int p) doubleQiskitBackend.quantumPhaseEstimation(Matrix<Complex> u, Vector<Complex> e, int p) doubleQuantum4JBackend.quantumPhaseEstimation(Matrix<Complex> u, Vector<Complex> e, int p) doubleStrangeBackend.quantumPhaseEstimation(Matrix<Complex> u, Vector<Complex> e, int p) doubleAmazonBraketBackend.vqe(Matrix<Complex> h, QuantumBackend.QuantumCircuit a, String o) doublePythonQuantumBackend.vqe(Matrix<Complex> hamiltonian, QuantumBackend.QuantumCircuit ansatz, String optimizer) doubleQiskitBackend.vqe(Matrix<Complex> h, QuantumBackend.QuantumCircuit a, String o) doubleQuantum4JBackend.vqe(Matrix<Complex> h, QuantumBackend.QuantumCircuit a, String o) doubleStrangeBackend.vqe(Matrix<Complex> h, QuantumBackend.QuantumCircuit a, String o) -
Uses of Matrix in org.episteme.natural.technical.backend.quantum
Methods in org.episteme.natural.technical.backend.quantum that return MatrixModifier and TypeMethodDescriptionQuantumAlgorithmProvider.stateTomography(QuantumBackend.QuantumCircuit circuit, int shots) Performs quantum state tomography to reconstruct a density matrix.Methods in org.episteme.natural.technical.backend.quantum with parameters of type MatrixModifier and TypeMethodDescriptionQuantumAlgorithmProvider.matrixToUnitary(Matrix<Complex> matrix) Converts a classical matrix to a quantum unitary operator.Performs Quantum Approximate Optimization Algorithm (QAOA).doubleQuantumAlgorithmProvider.quantumPhaseEstimation(Matrix<Complex> unitary, Vector<Complex> eigenstate, int precision) Performs Quantum Phase Estimation (QPE).doubleQuantumAlgorithmProvider.vqe(Matrix<Complex> hamiltonian, QuantumBackend.QuantumCircuit ansatz, String optimizer) Performs Variational Quantum Eigensolver (VQE) to find ground state energy. -
Uses of Matrix in org.episteme.social.economics.models
Methods in org.episteme.social.economics.models with parameters of type MatrixModifier and TypeMethodDescriptionstatic int[]NashEquilibriumSolver.findPureStrategyNE(Matrix<Real> payoffMatrixA, Matrix<Real> payoffMatrixB) Finds a pure strategy Nash Equilibrium in a 2-player normal-form game. -
Uses of Matrix in org.episteme.social.geography
Methods in org.episteme.social.geography that return MatrixMethods in org.episteme.social.geography with parameters of type Matrix