def __init__(self, dim=3):
assert dim == 3
centers = numpy.array([
[.1, .8, .3],
])
e_mat = numpy.array([
[5, 5, 5],
])
coefs = numpy.array([-5])
def kernel(x):
r2 = self.dist_sq(x, centers, e_mat)
return numpy.exp(-r2)
super(McCourt14, self).__init__(dim, kernel, e_mat, coefs, centers)
self.min_loc = [.1, .8, .3]
self.fmin = -5
self.fmax = 0.00030641748
self.classifiers = ['boring', 'unimodal']
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