Use the function expected_minimum as demonstrated in https://github.com/novonordisk-research/ProcessOptimizer/blob/develop/examples/7Dimensional_optimization_and_plotting.ipynb
from ProcessOptimizer import expected_minimum
minimum = expected_minimum(res)
minimum_x = [ '%.2f' % elem for elem in minimum[0] ]
minimum_y = round(minimum[1], 2)
print(f'position of expected minimum is {minimum_x} with a expected function value of {minimum_y}!')
print(f'(A "true" value of the noisy evaluation is {round(func(minimum[0]),2)})')
Linked to BoostV/process-optimizer-frontend#106
Use the function expected_minimum as demonstrated in https://github.com/novonordisk-research/ProcessOptimizer/blob/develop/examples/7Dimensional_optimization_and_plotting.ipynb
Linked to BoostV/process-optimizer-frontend#106