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java.lang.Objectorg.ojalgo.matrix.decomposition.LUDecomposition<N>
public abstract class LUDecomposition<N extends Number>
| Nested Class Summary | |
|---|---|
static class |
LUDecomposition.Pivot
|
| Field Summary | |
|---|---|
static boolean |
DEBUG
|
| Method Summary | |
|---|---|
boolean |
compute(MatrixStore<N> aStore)
|
boolean |
computeWithoutPivoting(MatrixStore<N> aStore)
The normal MatrixDecomposition.compute(MatrixStore) method must handle cases
where pivoting is required. |
boolean |
equals(MatrixDecomposition<N> aDecomp,
NumberContext aCntxt)
|
boolean |
equals(MatrixStore<N> aStore,
NumberContext aCntxt)
|
boolean |
equals(Object someObj)
|
N |
getDeterminant()
|
MatrixStore<N> |
getInverse()
The output must be a "right inverse" and a "generalised inverse". |
MatrixStore<N> |
getL()
|
int[] |
getPivotOrder()
This can be used to create a [P] matrix using IdentityStore in combination with SelectedRowsStore or SelectedColumnsStore. |
int |
getRank()
|
MatrixStore<N> |
getU()
http://en.wikipedia.org/wiki/Row_echelon_form This is the same as [D][U]. |
MatrixStore<N> |
invert(MatrixStore<N> aStore)
A convenience method that produces exactly the same result as if you first call MatrixDecomposition.compute(MatrixStore) and then MatrixDecomposition.getInverse(). |
boolean |
isAspectRatioNormal()
|
boolean |
isComputed()
|
boolean |
isFullSize()
|
boolean |
isSolvable()
|
boolean |
isSquareAndNotSingular()
|
static LU<BigDecimal> |
makeBig()
|
static LU<ComplexNumber> |
makeComplex()
|
static LU<Double> |
makeJama()
|
static LU<Double> |
makePrimitive()
|
MatrixStore<N> |
reconstruct()
|
void |
reset()
Delete computed results, and resets attributes to default values |
MatrixStore<N> |
solve(MatrixStore<N> aRHS)
Solves [this][X] = [aRHS] by first solving |
Future<DecomposeAndSolve<N>> |
solve(MatrixStore<N> aBody,
MatrixStore<N> aRHS)
Will solve [aBody][X]=[aRHS] concurrently by first calling MatrixDecomposition.compute(MatrixStore) using [aBody], and then MatrixDecomposition.solve(MatrixStore) using [aRHS]. |
| Methods inherited from class java.lang.Object |
|---|
getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
| Methods inherited from interface org.ojalgo.matrix.decomposition.MatrixDecomposition |
|---|
equals, invert, isComputed, solve |
| Field Detail |
|---|
public static boolean DEBUG
| Method Detail |
|---|
public static final LU<BigDecimal> makeBig()
public static final LU<ComplexNumber> makeComplex()
public static final LU<Double> makeJama()
public static final LU<Double> makePrimitive()
public boolean compute(MatrixStore<N> aStore)
compute in interface MatrixDecomposition<N extends Number>aStore - A matrix to decompose
public boolean computeWithoutPivoting(MatrixStore<N> aStore)
LUMatrixDecomposition.compute(MatrixStore) method must handle cases
where pivoting is required. If you know that pivoting is not needed
you may call this method instead - it's faster.
computeWithoutPivoting in interface LU<N extends Number>
public boolean equals(MatrixStore<N> aStore,
NumberContext aCntxt)
equals in interface MatrixDecomposition<N extends Number>public N getDeterminant()
getDeterminant in interface LU<N extends Number>public MatrixStore<N> getInverse()
MatrixDecomposition
getInverse in interface MatrixDecomposition<N extends Number>BasicMatrix.invert()public MatrixStore<N> getL()
getL in interface LU<N extends Number>public int[] getPivotOrder()
LU
getPivotOrder in interface LU<N extends Number>public int getRank()
getRank in interface LU<N extends Number>public MatrixStore<N> getU()
LU
getU in interface LU<N extends Number>LU.getPivotOrder(),
LU.getL()public final boolean isFullSize()
isFullSize in interface MatrixDecomposition<N extends Number>public boolean isSolvable()
isSolvable in interface MatrixDecomposition<N extends Number>MatrixDecomposition.solve(MatrixStore),
MatrixDecomposition.isComputed()public final boolean isSquareAndNotSingular()
isSquareAndNotSingular in interface LU<N extends Number>public MatrixStore<N> reconstruct()
reconstruct in interface MatrixDecomposition<N extends Number>public void reset()
MatrixDecomposition
reset in interface MatrixDecomposition<N extends Number>public MatrixStore<N> solve(MatrixStore<N> aRHS)
[L][Y] = [aRHS]and then
[U][X] = [Y].
solve in interface MatrixDecomposition<N extends Number>aRHS - The right hand side
public final boolean equals(MatrixDecomposition<N> aDecomp,
NumberContext aCntxt)
equals in interface MatrixDecomposition<N extends Number>public boolean equals(Object someObj)
equals in class Objectpublic final MatrixStore<N> invert(MatrixStore<N> aStore)
MatrixDecomposition
invert in interface MatrixDecomposition<N extends Number>public final boolean isAspectRatioNormal()
public final boolean isComputed()
isComputed in interface MatrixDecomposition<N extends Number>MatrixDecomposition.compute(MatrixStore),
MatrixDecomposition.isSolvable()
public Future<DecomposeAndSolve<N>> solve(MatrixStore<N> aBody,
MatrixStore<N> aRHS)
MatrixDecomposition
solve in interface MatrixDecomposition<N extends Number>aBody - The equation system bodyaRHS - The equation system right hand side
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