OpenPisco.Optim.Algorithms.OptimAlgoNullSpace module#

OpenPisco.Optim.Algorithms.OptimAlgoNullSpace.CheckIntegrity(GUI=False)[source]#

OpenPisco.Optim.Algorithms.OptimAlgoNullSpace.CheckIntegrity2D(GUI=False)[source]#

OpenPisco.Optim.Algorithms.OptimAlgoNullSpace.CheckIntegrityTopo(GUI=False)[source]#

OpenPisco.Optim.Algorithms.OptimAlgoNullSpace.CreateOptimAlgoNullSpace(ops)[source]#

class OpenPisco.Optim.Algorithms.OptimAlgoNullSpace.OptimAlgoNullSpace[source]#

Bases: OptimAlgoBase

numberOfIterationsMax#

Number of trials in between time steps until the merit function decreases (default 20)

Type: int

numberOfDesignStepsMax#

Maximal number of design steps (steps) (default : 200)

Type: int

alphaJ#

Scaling coefficient for the null space direction (default 1)

Type: float

alphaC#

Scaling coefficient for the Gauss Newton direction (default 1)

Type: float

alphas#

Vector of dimension problem.nconstraints+problem.nineqconstraints of proportionality coefficients for the tuning how the Gauss Newton direction accounts for each of the constraints (not yet implemented)

Type: array_like

dt#

The normalisation of the descent step (default 1) is such that ||dxiJ|| = alphaJ * dt ||dxiC|| = alphaC * dt

Type: float

K#

Tunes the distance at which inactive inequality constraints are felt. Constraints are felt from a distance K*dt.

Type: float

tol_merit#

Tolerance for acceptance step with the merit function method

Type: float

ComputeEps(Dh)[source]#

ComputeMeritFunction(J, C)[source]#

ComputeNorm(data)[source]#

ComputeTildeIds(h, eps=None)[source]#

DoOneStep()[source]#

Finalize()[source]#

SolveDualProblem(DJ, DC, DCExtT, tildeEpsIds)[source]#

Start()[source]#

StatusFromResult(resultVal)[source]#

TryToAdvance()[source]#