def cs_hdmr_modeler(inputs, outputs, ord_cap=3, deg_cap=3, independent=False):
d = inputs.shape[1]
syms = [sympy.Symbol('x' + str(i+1)) for i in range(d)]
if independent:
def get_range(i):
in_i = np.array([x[i] for x in inputs])
center = np.sum(in_i) / len(in_i)
var = np.var(in_i)
d = np.sqrt(12*var)
s = 2*center
b = (s + d) / 2
a = s - b
return [a, b]
ranges = [get_range(i) for i in range(d)]
basis_dict = sym_poly_utils.uniform_honb(
ranges, inputs, syms, ord_cap=ord_cap, deg_cap=deg_cap
)
else:
basis_dict = sym_poly_utils.sample_honb(
inputs, syms, ord_cap=ord_cap, deg_cap=deg_cap
)
expansion = cs_hdmr_expansion(inputs, outputs, basis_dict)
return expansion
def _test_sample_basis_hon(self, row_generator):
syms = [sympy.Symbol('x' + str(i + 1)) for i in range(self.d)]
sample = np.array([row_generator() for i in range(self.N)])
basis = sym_poly_utils.sample_honb(sample, syms)
self._validate_basis(sample, basis)
def _test_sample_basis_hon(self, row_generator):
syms = [sympy.Symbol('x' + str(i+1)) for i in range(self.d)]
sample = np.array(
[row_generator() for i in range(self.N)]
)
basis = sym_poly_utils.sample_honb(sample, syms)
self._validate_basis(sample, basis)