aquakin.OptimizeResult#

class aquakin.OptimizeResult(input_names, x, objective, constraint_values, feasible, success, message, n_iter, n_starts)[source]#

Bases: object

Result of optimize_design().

Variables:

  • input_names (list[str]) – Names of the design variables (order of x).

  • x (np.ndarray) – The optimal design vector.

  • objective (float) – Objective value at x (in the original sense – already un-negated for a maximize run).

  • constraint_values (dict) – name -> fn(x) for every constraint at the optimum.

  • feasible (bool) – Whether every constraint is satisfied at x (within constraint_tol).

  • success (bool) – The optimizer reported convergence for the chosen start.

  • message (str) – Optimizer status message.

  • n_starts (n_iter,) – Iterations of the winning run; number of multistart runs.

Parameters:

  • input_names (list[str])

  • x (ndarray)

  • objective (float)

  • constraint_values (dict)

  • feasible (bool)

  • success (bool)

  • message (str)

  • n_iter (int)

  • n_starts (int)

__init__(input_names, x, objective, constraint_values, feasible, success, message, n_iter, n_starts)#
Parameters:

  • input_names (list[str])

  • x (ndarray)

  • objective (float)

  • constraint_values (dict)

  • feasible (bool)

  • success (bool)

  • message (str)

  • n_iter (int)

  • n_starts (int)

Return type:

None

Methods

__init__(input_names, x, objective, ...)

report()

Attributes

x_named

The optimal design as a name -> value dict.

input_names

x

objective

constraint_values

feasible

success

message

n_iter

n_starts

property x_named: dict#

The optimal design as a name -> value dict.