- All Superinterfaces:
DeterminantTask<N>,MatrixDecomposition<N>,MatrixDecomposition.Determinant<N>,MatrixDecomposition.Hermitian<N>,MatrixDecomposition.Ordered<N>,MatrixDecomposition.Values<N>,MatrixTask<N>,Provider2D,Provider2D.Determinant<N>,Provider2D.Eigenpairs,Structure1D,Structure2D
- All Known Subinterfaces:
Eigenvalue.Generalised<N>,Eigenvalue.Spectral<N>
- All Known Implementing Classes:
DenseEigenvalue,DynamicEvD,DynamicEvD.R064,GeneralEvD,GeneralEvD.R064,GeneralisedEvD,HermitianEvD,HermitianEvD.C128,HermitianEvD.H256,HermitianEvD.Q128,HermitianEvD.R064,HermitianEvD.R128,RawEigenvalue,RawEigenvalue.Dynamic,RawEigenvalue.General,RawEigenvalue.Symmetric
- [A] = any square matrix.
- [V] = contains the eigenvectors as columns.
- [D] = a diagonal matrix with the eigenvalues on the diagonal (possibly in blocks).
[A] is normal if [A][A]H = [A]H[A], and [A] is normal if and only if there exists a unitary matrix [Q] such that [A] = [Q][D][Q]H. Hermitian matrices are normal.
[V] and [D] can always be calculated in the sense that they will satisfy [A][V] = [V][D], but it is not always possible to calculate [V]-1. (Check the rank and/or the condition number of [V] to determine the validity of [V][D][V]-1.)
The eigenvalues (and their corresponding eigenvectors) of a non-symmetric matrix could be complex.
-
Nested Class Summary
Nested ClassesModifier and TypeInterfaceDescriptionstatic classstatic interfaceEigenvalue.Factory<N extends Comparable<N>>static enumstatic interfaceEigenvalue.Generalised<N extends Comparable<N>>static interfaceEigenvalue.Spectral<N extends Comparable<N>>“Spectral decomposition” refers specifically to the orthogonal/unitary eigen-decomposition of a normal matrix (most commonly Hermitian / symmetric).Nested classes/interfaces inherited from interface org.ojalgo.matrix.decomposition.MatrixDecomposition
MatrixDecomposition.Determinant<N extends Comparable<N>>, MatrixDecomposition.EconomySize<N extends Comparable<N>>, MatrixDecomposition.Hermitian<N extends Comparable<N>>, MatrixDecomposition.Ordered<N extends Comparable<N>>, MatrixDecomposition.Pivoting<N extends Comparable<N>>, MatrixDecomposition.RankRevealing<N extends Comparable<N>>, MatrixDecomposition.Solver<N extends Comparable<N>>, MatrixDecomposition.Updatable<N extends Comparable<N>>, MatrixDecomposition.Values<N extends Comparable<N>>Nested classes/interfaces inherited from interface org.ojalgo.matrix.Provider2D
Provider2D.Condition, Provider2D.Determinant<N extends Comparable<N>>, Provider2D.Eigenpairs, Provider2D.Hermitian, Provider2D.Inverse<M>, Provider2D.Rank, Provider2D.Solution<M>, Provider2D.Symmetric, Provider2D.Trace<N extends Comparable<N>>Nested classes/interfaces inherited from interface org.ojalgo.structure.Structure1D
Structure1D.BasicMapper<T>, Structure1D.IndexMapper<T>, Structure1D.IntIndex, Structure1D.LongIndex, Structure1D.LoopCallbackNested classes/interfaces inherited from interface org.ojalgo.structure.Structure2D
Structure2D.IntRowColumn, Structure2D.Logical<S extends Structure2D,B extends Structure2D.Logical<S, B>>, Structure2D.LongRowColumn, Structure2D.ReducibleTo1D<R extends Structure1D>, Structure2D.Reshapable, Structure2D.RowColumnKey<R, C>, Structure2D.RowColumnMapper<R, C> -
Field Summary
FieldsModifier and TypeFieldDescriptionstatic final Eigenvalue.Factory<ComplexNumber> static final Comparator<ComplexNumber> Sorts on the norm in descending order.static final Eigenvalue.Factory<Quaternion> static final Eigenvalue.Factory<RationalNumber> static final Eigenvalue.Factory<Double> static final Eigenvalue.Factory<Quadruple> Fields inherited from interface org.ojalgo.matrix.decomposition.MatrixDecomposition
TYPICAL -
Method Summary
Modifier and TypeMethodDescriptionprivate voidcopyEigenvector(int index, Array1D<ComplexNumber> destination) static <N extends Comparable<N>>
booleanequals(MatrixStore<N> matrix, Eigenvalue<N> decomposition, NumberContext context) getD()The only requirements on [D] are that it should contain the eigenvalues and that [A][V] = [V][D].default Eigenvalue.EigenpairgetEigenpair(int index) default List<Eigenvalue.Eigenpair> This list is always ordered in descending eigenvalue order – that's regardless of ifisOrdered()returns true or false.Even for real matrices the eigenvalues (and eigenvectors) are potentially complex numbers.default voidgetEigenvalues(double[] realParts, Optional<double[]> imaginaryParts) default MatrixStore<ComplexNumber> getTrace()A matrix' trace is the sum of the diagonal elements.getV()The columns of [V] represent the eigenvectors of [A] in the sense that [A][V] = [V][D].booleanIf [A] is hermitian then [V][D][V]-1 becomes [Q][D][Q]H...booleanThe eigenvalues in D (and the eigenvectors in V) are not necessarily ordered.default MatrixStore<N> static <N extends Comparable<N>>
MatrixStore<N> reconstruct(Eigenvalue<N> decomposition) static voidsort(double[] values, ExchangeColumns vectorExchange) Sort eigenvalues and corresponding vectors.Methods inherited from interface org.ojalgo.matrix.task.DeterminantTask
calculateDeterminantMethods inherited from interface org.ojalgo.matrix.decomposition.MatrixDecomposition
decompose, isComputed, resetMethods inherited from interface org.ojalgo.matrix.decomposition.MatrixDecomposition.Determinant
getDeterminant, toDeterminantProviderMethods inherited from interface org.ojalgo.matrix.decomposition.MatrixDecomposition.Hermitian
checkAndDecomposeMethods inherited from interface org.ojalgo.matrix.decomposition.MatrixDecomposition.Values
computeValuesOnlyMethods inherited from interface org.ojalgo.structure.Structure2D
count, countColumns, countRows, firstInColumn, firstInRow, getColDim, getMaxDim, getMinDim, getRowDim, isEmpty, isFat, isScalar, isSquare, isTall, isVector, limitOfColumn, limitOfRow, size
-
Field Details
-
C128
-
DESCENDING_NORM
Sorts on the norm in descending order. If the 2 eigenvalues have equal norm then the usualComplexNumbersort order is used (reversed). -
H256
-
Q128
-
R064
-
R128
-
-
Method Details
-
equals
static <N extends Comparable<N>> boolean equals(MatrixStore<N> matrix, Eigenvalue<N> decomposition, NumberContext context) -
reconstruct
-
sort
Sort eigenvalues and corresponding vectors.- Parameters:
values- The eigenvalues to sortvectorExchange- A function that can exchange the eigenvectors to follow the new order.
-
copyEigenvector
-
getD
MatrixStore<N> getD()The only requirements on [D] are that it should contain the eigenvalues and that [A][V] = [V][D]. The ordering of the eigenvalues is not specified.- If [A] is real and symmetric then [D] is (purely) diagonal with real eigenvalues.
- If [A] is real but not symmetric then [D] is block-diagonal with real eigenvalues in 1-by-1 blocks and complex eigenvalues in 2-by-2 blocks.
- If [A] is complex then [D] is (purely) diagonal with complex eigenvalues.
- Returns:
- The (block) diagonal eigenvalue matrix.
-
getEigenpair
-
getEigenpairs
This list is always ordered in descending eigenvalue order – that's regardless of ifisOrdered()returns true or false.- Specified by:
getEigenpairsin interfaceProvider2D.Eigenpairs- See Also:
-
getEigenvalues
Array1D<ComplexNumber> getEigenvalues()Even for real matrices the eigenvalues (and eigenvectors) are potentially complex numbers. Typically they need to be expressed as complex numbers when [A] is not symmetric.
The values should be in the same order as the matrices "V" and "D", and if they are ordered or not is indicated by the
isOrdered()method.- Returns:
- The eigenvalues.
-
getEigenvalues
- Parameters:
realParts- An array that will receive the real parts of the eigenvaluesimaginaryParts- An optional array that, if present, will receive the imaginary parts of the eigenvalues
-
getEigenvectors
- Returns:
- A complex valued alternative to
getV().
-
getTrace
ComplexNumber getTrace()A matrix' trace is the sum of the diagonal elements. It is also the sum of the eigenvalues. This method should return the sum of the eigenvalues.- Returns:
- The matrix' trace
-
getV
MatrixStore<N> getV()The columns of [V] represent the eigenvectors of [A] in the sense that [A][V] = [V][D].- Returns:
- The eigenvector matrix.
-
isHermitian
boolean isHermitian()If [A] is hermitian then [V][D][V]-1 becomes [Q][D][Q]H... -
isOrdered
boolean isOrdered()The eigenvalues in D (and the eigenvectors in V) are not necessarily ordered. This is a property of the algorithm/implementation, not the data.- Specified by:
isOrderedin interfaceMatrixDecomposition.Ordered<N extends Comparable<N>>- Returns:
- true if they are ordered
-
reconstruct
- Specified by:
reconstructin interfaceMatrixDecomposition<N extends Comparable<N>>
-