def __init__(self,
worker_id,
data,
response_surface,
maxeval,
nsamples,
exp_design=None,
sampling_method=None,
extra=None):
"""Initialize the optimization strategy.
:param worker_id: Start ID in a multistart setting
:param data: Problem parameter data structure
:param response_surface: Surrogate model object
:param maxeval: Function evaluation budget
:param nsamples: Number of simultaneous fevals allowed
:param exp_design: Experimental design
:param search_procedure: Search procedure for finding
points to evaluate
:param extra: Points to be added to the experimental design
"""
self.worker_id = worker_id
self.data = data
self.fhat = response_surface
if self.fhat is None:
self.fhat = RBFInterpolant(surftype=CubicRBFSurface, maxp=maxeval)
self.maxeval = maxeval
self.nsamples = nsamples
self.extra = extra
# Default to generate sampling points using Symmetric Latin Hypercube
self.design = exp_design
if self.design is None:
if self.data.dim > 50:
self.design = LatinHypercube(data.dim, data.dim + 1)
else:
self.design = SymmetricLatinHypercube(data.dim,
2 * (data.dim + 1))
self.xrange = np.asarray(data.xup - data.xlow)
# algorithm parameters
self.sigma_min = 0.005
self.sigma_max = 0.2
self.sigma_init = 0.2
self.failtol = max(5, data.dim)
self.succtol = 3
self.numeval = 0
self.status = 0
self.sigma = 0
self.resubmitter = RetryStrategy()
self.xbest = None
self.fbest = np.inf
self.fbest_old = None
# Set up search procedures and initialize
self.sampling = sampling_method
if self.sampling is None:
self.sampling = CandidateDYCORS(data)
self.check_input()
# Start with first experimental design
self.sample_initial()
if __name__ == "__main__":
# Test DYCORS
dim = 10
maxeval = 100
initeval = 80
from test_problems import Ackley
from experimental_design import LatinHypercube
from rbf_interpolant import RBFInterpolant
from rbf_surfaces import CubicRBFSurface
xbest = np.ones(dim)
data = Ackley(dim)
cand = CandidateDYCORS(data, 100 * dim)
exp_des = LatinHypercube(dim, npts=initeval)
initpoints = exp_des.generate_points()
rbf = RBFInterpolant(surftype=CubicRBFSurface)
for i in range(initeval):
rbf.add_point(initpoints[i, :], data.objfunction(initpoints[i, :]))
cand.init(initpoints, maxeval, True, None)
def evals(x, scaling):
return rbf.evals(x)
cand.make_points(xbest, 0.02, evals, maxeval)
import matplotlib.pyplot as plt
plt.plot(cand.xcand[:, 0], cand.xcand[:, 1], 'ro')
plt.ylabel('Dimension 1')
plt.xlabel('Dimension 2')
plt.show()
