optimization
- optimization.find_nominal_inputs(b, p)
Function
find_nominal_inputs()- Parameters:
b – Design variable bounds struct
p – Parameter struct
- Returns:
F_max_nom
- optimization.gradient_optim(x0_input, p, b, which_objs, plotfn, disp_on)
Function
gradient_optim()- Parameters:
x0_input – x0_input
p – Parameter struct
b – Design variable bounds struct
which_objs – which_objs
plotfn – plotfn
disp_on – disp_on
- Returns:
Xs_opt
- Returns:
objs_opt
- Returns:
Optimization output flags
- Returns:
probs
- Returns:
lambdas
- Returns:
grads
- Returns:
hesses
- Returns:
vals
- optimization.run_solver(prob, obj, x0, opts, idxs, filename_uuid)
Function
run_solver()- Parameters:
prob – prob
obj – Objective function value
x0 – Initial design variable vector
opts – opts
idxs – idxs
filename_uuid – filename_uuid
- Returns:
Optimal design variables
- Returns:
obj_opt
- Returns:
Optimization output flag
- Returns:
output
- Returns:
$\lambda$
- Returns:
grad
- Returns:
hess
- Returns:
problem
- optimization.max_avg_power(p, b, x0_vec)
Function
max_avg_power()- Parameters:
p – Parameter struct
b – Design variable bounds struct
x0_vec – x0_vec
- Returns:
X_opt_2
- Returns:
val_2
- Returns:
flag_2
- Returns:
P_elec_2
- optimization.compare_run(p, b)
Function
compare_run()- Parameters:
p – Parameter struct
b – Design variable bounds struct
- Returns:
Design variable vector
- Returns:
vals
Modules