- class foxes_opt.problems.layout.FarmLayoutOptProblem(foxes_opt.core.FarmOptProblem)[source]
The turbine positioning optimization problem
Public members¶
- var_names_float()[source]
The names of float variables.
- initial_values_float()[source]
The initial values of the float variables.
- min_values_float()[source]
The minimal values of the float variables.
- max_values_float()[source]
The maximal values of the float variables.
- update_problem_individual(vars_int, vars_float)[source]
Update the algo and other data using the latest optimization variables.
- update_problem_population(vars_int, vars_float)[source]
Update the algo and other data using the latest optimization variables.
-
FarmLayoutOptProblem(name, algo, sel_turbines=
None
, ...)[source] Constructor.
- property farm
The wind farm
- property sel_turbines
The selected turbines
- property n_sel_turbines
The numer of selected turbines
- property all_turbines
Flag for all turbines optimization
- property counter
The current value of the application counter
- classmethod parse_tvar(tvr)[source]
Parse foxes variable name and turbine index from turbine variable
-
initialize(verbosity=
1
)[source] Initialize the object.
- apply_individual(vars_int, vars_float)[source]
Apply new variables to the problem.
- apply_population(vars_int, vars_float)[source]
Apply new variables to the problem, for a whole population.
- add_to_layout_figure(ax, **kwargs)[source]
Add to a layout figure
- classmethod new(problem_type, *args, **kwargs)[source]
Run-time farm opt problem factory.
-
INT_INF =
-999999
- var_names_int()
The names of integer variables.
- initial_values_int()
The initial values of the integer variables.
- min_values_int()
The minimal values of the integer variables.
- max_values_int()
The maximal values of the integer variables.
- property n_vars_int
The number of int variables
- property n_vars_float
The number of float variables
-
add_objective(objective, varmap_int=
None
, varmap_float=None
, ...) Add an objective to the problem.
-
add_constraint(constraint, varmap_int=
None
, varmap_float=None
, ...) Add a constraint to the problem.
- property min_values_constraints
Gets the minimal values of constraints
- property max_values_constraints
Gets the maximal values of constraints
- property constraints_tol
Gets the tolerance values of constraints
- property n_objectives
The total number of objectives, i.e., the sum of all components
- property n_constraints
The total number of constraints, i.e., the sum of all components
- calc_gradients(vars_int, vars_float, func, components, ivars, ...)
The actual gradient calculation, not to be called directly (call get_gradients instead).
-
get_gradients(vars_int, vars_float, func=
None
, components=None
, ...) Obtain gradients of a function that is linked to the problem.
- property maximize_objs
Flags for objective maximization
-
evaluate_individual(vars_int, vars_float, ret_prob_res=
False
) Evaluate a single individual of the problem.
-
evaluate_population(vars_int, vars_float, ret_prob_res=
False
) Evaluate all individuals of a population.
-
check_constraints_individual(constraint_values, verbosity=
0
) Check if the constraints are fullfilled for the given individual.
-
check_constraints_population(constraint_values, verbosity=
0
) Check if the constraints are fullfilled for the given population.
-
finalize_individual(vars_int, vars_float, verbosity=
1
) Finalization, given the champion data.
-
finalize_population(vars_int, vars_float, verbosity=
0
) Finalization, given the final population data.
- prob_res_einsum_individual(prob_res_list, coeffs)
Calculate the einsum of problem results
- prob_res_einsum_population(prob_res_list, coeffs)
Calculate the einsum of problem results
- __str__()
Get info string
- property initialized
Flag for finished initialization