.. _modify_gpr:
=========================
Modifying surrogate model
=========================
This tutorial extends the previous one for
:ref:`Cu15 clusters `. It is
therefore recomended that you do that one before the present one.
In the avove mentioned tutorial GOFEE was initialized with the following
arguments::
from gofee import GOFEE
search = GOFEE(calc=calc,
startgenerator=sg,
candidate_generator=candidate_generator,
max_steps=60,
population_size=5)
however GOFEE takes a number of other arguments, including a
Gaussian Process regression (GPR) model, which is actively learned
during the search and used for cheap optimization of new candidates.
One can for example apply a GPR model with another degree of regularization
in the search. This is controlled by the ``noise`` parameter of the ``kernel``,
passed to the GPR model. The modification can be achieved by::
from gofee.surrogate import GPR
from gofee.surrogate.kernel import DoubleGaussKernel
kernel = DoubleGaussKernel(noise=1e-6)
gpr = GPR(kernel=kernel)
search = GOFEE(calc=calc,
gpr=gpr,
startgenerator=sg,
candidate_generator=candidate_generator,
max_steps=60,
population_size=5)