@Deprecated public abstract class LUDecomposition<N extends java.lang.Number> extends java.lang.Object implements LU<N>
InverterTask.Factory<N extends java.lang.Number>
SolverTask.Factory<N extends java.lang.Number>
DeterminantTask.Factory<N extends java.lang.Number>
BIG, COMPLEX, PRIMITIVE
BIG, COMPLEX, PRIMITIVE
BIG, COMPLEX, PRIMITIVE
Modifier and Type | Method and Description |
---|---|
boolean |
compute(Access2D<?> aStore)
Deprecated.
|
boolean |
computeWithoutPivoting(MatrixStore<?> matrix)
Deprecated.
The normal
MatrixDecomposition.compute(Access2D) method must handle cases where pivoting is required. |
boolean |
equals(MatrixStore<N> aStore,
NumberContext context)
Deprecated.
|
boolean |
equals(java.lang.Object someObj) |
N |
getDeterminant()
Deprecated.
|
MatrixStore<N> |
getInverse()
The output must be a "right inverse" and a "generalised inverse".
|
MatrixStore<N> |
getInverse(DecompositionStore<N> preallocated)
Deprecated.
Implementiong this method is optional.
|
MatrixStore<N> |
getL()
Deprecated.
|
int[] |
getPivotOrder()
Deprecated.
This can be used to create a [P] matrix using IdentityStore in combination with
RowsStore or ColumnsStore.
|
int |
getRank()
Deprecated.
|
int[] |
getReducedPivots()
Deprecated.
|
MatrixStore<N> |
getU()
Deprecated.
http://en.wikipedia.org/wiki/Row_echelon_form
This is the same as [D][U]. |
MatrixStore<N> |
invert(MatrixStore<N> original)
The output must be a "right inverse" and a "generalised inverse".
|
MatrixStore<N> |
invert(MatrixStore<N> original,
DecompositionStore<N> preallocated)
Implementiong this method is optional.
|
boolean |
isComputed() |
boolean |
isFullSize()
Deprecated.
|
boolean |
isSolvable()
Deprecated.
|
boolean |
isSquareAndNotSingular()
Deprecated.
|
static <N extends java.lang.Number> |
make(Access2D<N> aTypical)
Deprecated.
v38 Use
LU.make(Access2D) instead |
static LU<java.math.BigDecimal> |
makeBig()
Deprecated.
v38 Use
LU.makeBig() instead |
static LU<ComplexNumber> |
makeComplex()
Deprecated.
v38 Use
LU.makeComplex() instead |
static LU<java.lang.Double> |
makeJama()
Deprecated.
v38 Use
LU.makePrimitive() instead |
static LU<java.lang.Double> |
makePrimitive()
Deprecated.
v38 Use
LU.makePrimitive() instead |
DecompositionStore<N> |
preallocate(Access2D<N> template)
Implementiong this method is optional.
|
DecompositionStore<N> |
preallocate(Access2D<N> templateBody,
Access2D<N> templateRHS)
Implementiong this method is optional.
|
void |
reset()
Deprecated.
Delete computed results, and resets attributes to default values
|
MatrixStore<N> |
solve(Access2D<N> rhs)
[A][X]=[B] or [this][return]=[rhs]
|
MatrixStore<N> |
solve(Access2D<N> body,
Access2D<N> rhs)
[A][X]=[B] or [body][return]=[rhs]
|
MatrixStore<N> |
solve(Access2D<N> body,
Access2D<N> rhs,
DecompositionStore<N> preallocated)
Implementiong this method is optional.
|
MatrixStore<N> |
solve(Access2D<N> rhs,
DecompositionStore<N> preallocated)
Deprecated.
Solves [this][X] = [rhs] by first solving
|
getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
reconstruct
calculateDeterminant
equals, getInverse, isComputed, solve
invert, invert, preallocate
preallocate, solve, solve
@Deprecated public static final <N extends java.lang.Number> LU<N> make(Access2D<N> aTypical)
LU.make(Access2D)
instead@Deprecated public static final LU<java.math.BigDecimal> makeBig()
LU.makeBig()
instead@Deprecated public static final LU<ComplexNumber> makeComplex()
LU.makeComplex()
insteadmakeComplex
in interface LU<N extends java.lang.Number>
@Deprecated public static final LU<java.lang.Double> makeJama()
LU.makePrimitive()
instead@Deprecated public static final LU<java.lang.Double> makePrimitive()
LU.makePrimitive()
insteadmakePrimitive
in interface LU<N extends java.lang.Number>
public boolean compute(Access2D<?> aStore)
compute
in interface MatrixDecomposition<N extends java.lang.Number>
aStore
- A matrix to decomposepublic boolean computeWithoutPivoting(MatrixStore<?> matrix)
LU
MatrixDecomposition.compute(Access2D)
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 java.lang.Number>
public boolean equals(MatrixStore<N> aStore, NumberContext context)
equals
in interface MatrixDecomposition<N extends java.lang.Number>
public N getDeterminant()
getDeterminant
in interface LDU<N extends java.lang.Number>
public MatrixStore<N> getInverse(DecompositionStore<N> preallocated)
MatrixDecomposition
Implementiong this method is optional.
Exactly how a specific implementation makes use of preallocated
is not specified by this
interface. It must be documented for each implementation.
Should produce the same results as calling MatrixDecomposition.getInverse()
.
getInverse
in interface MatrixDecomposition<N extends java.lang.Number>
preallocated
- Preallocated memory for the results, possibly some intermediate results. You must
assume this is modified, but you cannot assume it will contain the full/final/correct solution.public MatrixStore<N> getL()
public int[] getPivotOrder()
LU
getPivotOrder
in interface LU<N extends java.lang.Number>
public int getRank()
public int[] getReducedPivots()
public MatrixStore<N> getU()
LU
getU
in interface LU<N extends java.lang.Number>
LU.getPivotOrder()
,
LU.getL()
public final boolean isFullSize()
isFullSize
in interface MatrixDecomposition<N extends java.lang.Number>
public boolean isSolvable()
isSolvable
in interface MatrixDecomposition<N extends java.lang.Number>
MatrixDecomposition.solve(Access2D)
,
MatrixDecomposition.isComputed()
public final boolean isSquareAndNotSingular()
isSquareAndNotSingular
in interface LU<N extends java.lang.Number>
public void reset()
MatrixDecomposition
reset
in interface MatrixDecomposition<N extends java.lang.Number>
public MatrixStore<N> solve(Access2D<N> rhs, DecompositionStore<N> preallocated)
[L][Y] = [rhs]and then
[U][X] = [Y]
solve
in interface MatrixDecomposition<N extends java.lang.Number>
rhs
- The right hand sidepreallocated
- Preallocated memory for the results, possibly some intermediate results. You must
assume this is modified, but you cannot assume it will contain the full/final/correct solution.MatrixDecomposition.solve(Access2D,
org.ojalgo.matrix.decomposition.DecompositionStore)
public final MatrixStore<N> getInverse()
MatrixDecomposition
BasicMatrix.invert()
public final MatrixStore<N> solve(Access2D<N> rhs)
MatrixDecomposition
public boolean equals(java.lang.Object someObj)
equals
in class java.lang.Object
public final MatrixStore<N> invert(MatrixStore<N> original)
InverterTask
BasicMatrix.invert()
public final MatrixStore<N> invert(MatrixStore<N> original, DecompositionStore<N> preallocated)
InverterTask
Implementiong this method is optional.
Exactly how a specific implementation makes use of preallocated
is not specified by this
interface. It must be documented for each implementation.
Should produce the same results as calling InverterTask.invert(MatrixStore)
.
preallocated
- Preallocated memory for the results, possibly some intermediate results. You must
assume this is modified, but you cannot assume it will contain the full/final/correct solution.public final MatrixStore<N> solve(Access2D<N> body, Access2D<N> rhs)
SolverTask
public final MatrixStore<N> solve(Access2D<N> body, Access2D<N> rhs, DecompositionStore<N> preallocated)
SolverTask
Implementiong this method is optional.
Exactly how a specific implementation makes use of preallocated
is not specified by this
interface. It must be documented for each implementation.
Should produce the same results as calling SolverTask.solve(Access2D, Access2D)
.
rhs
- The Right Hand Side, wont be modfiedpreallocated
- Preallocated memory for the results, possibly some intermediate results. You must
assume this is modified, but you cannot assume it will contain the full/final/correct solution.public final DecompositionStore<N> preallocate(Access2D<N> template)
InverterTask
Implementiong this method is optional.
Will create a DecompositionStore instance suitable for use withInverterTask.invert(MatrixStore, DecompositionStore)
. When solving an equation system [A][X]=[B]
([mxn][nxb]=[mxb]) the preallocated memory/matrix will typically be either mxb or nxb (if A is square
then there is no doubt).preallocate
in interface InverterTask<N extends java.lang.Number>
public final DecompositionStore<N> preallocate(Access2D<N> templateBody, Access2D<N> templateRHS)
SolverTask
Implementiong this method is optional.
Will create a DecompositionStore instance suitable for use withSolverTask.solve(Access2D, Access2D, DecompositionStore)
. When solving an equation system [A][X]=[B]
([mxn][nxb]=[mxb]) the preallocated memory/matrix will typically be either mxb or nxb (if A is square
then there is no doubt).preallocate
in interface SolverTask<N extends java.lang.Number>
public final boolean isComputed()
isComputed
in interface MatrixDecomposition<N extends java.lang.Number>
MatrixDecomposition.compute(Access2D)
,
MatrixDecomposition.isSolvable()