Generic Problem to Pygmo UserDefinedProblem adapter

Attributes¶

problem: iwopy.Problem

The problem to optimize

n_vars_all: int

The sum of int and float variable counts

n_fitness: int

The sum of objective and constraint counts

c_tol: list of float

Constraint tolerances

values: numpy.ndarray

The function values, shape: (n_fitness,)

pop: bool

Vectorized fitness computation

verbosity: int

The verbosity level, 0 = silent

Public members¶

UDP(problem, pop=False, verbosity=0)[source]

Constructor

fitness(dv)[source]

batch_fitness(dvs)[source]

has_batch_fitness()[source]

get_bounds()[source]

get_nobj()[source]

get_nec()[source]

get_nic()[source]

get_nix()[source]

has_gradient()[source]

gradient(x)[source]

has_gradient_sparsity()[source]

gradient_sparsity()[source]

has_hessians()[source]

has_hessians_sparsity()[source]

has_set_seed()[source]

get_name()[source]

get_extra_info()[source]

finalize(pygmo_pop, verbosity=1)[source]

Finalize the problem.