Uses of Class
jline.io.Ret.pfqnSens

Packages that use Ret.pfqnSens

Package	Description
jline.api.pfqn.sens
jline.solvers	Solver superclasses and related data structures.

Uses of Ret.pfqnSens in jline.api.pfqn.sens

Methods in jline.api.pfqn.sens that return Ret.pfqnSens

Modifier and Type	Method	Description
static Ret.pfqnSens	Pfqn_sens.pfqn_sens(Matrix L, Matrix N, Matrix Z)
static Ret.pfqnSens	Pfqn_sens.pfqn_sens(Matrix L, Matrix N, Matrix Z, Matrix mi)	Exact derivatives of {X, Q, U, R} w.r.t.

Uses of Ret.pfqnSens in jline.solvers

Methods in jline.solvers that return Ret.pfqnSens

Modifier and Type	Method	Description
Ret.pfqnSens	NetworkSensitivityTable.getSens()	Returns the raw differentiated-MVA result behind this table, the second output that MATLAB's getSensitivityTable returns alongside the table.

Methods in jline.solvers that return types with arguments of type Ret.pfqnSens

Modifier and Type	Method	Description
List<Ret.pfqnSens>	LayeredNetworkSensitivityTable.getLayerSens()	Returns the raw differentiated-MVA result of each layer, the counterpart of the cell array that MATLAB returns as the second output alongside the table.

Methods in jline.solvers with parameters of type Ret.pfqnSens

Modifier and Type	Method	Description
void	NetworkSensitivityTable.setSens(Ret.pfqnSens sens)	Sets the raw differentiated-MVA result.

Method parameters in jline.solvers with type arguments of type Ret.pfqnSens

Modifier and Type	Method	Description
void	LayeredNetworkSensitivityTable.setLayerSens(List<Ret.pfqnSens> layerSens)	Sets the raw differentiated-MVA result of each layer.