def _set_points_and_weights(self):
"""
Private function that sets the quadrature points.
:param Poly self:
An instance of the Poly object.
"""
self.quadrature = Quadrature(parameters=self.parameters, basis=self.basis, \
points=self.inputs, mesh=self.mesh)
quadrature_points, quadrature_weights = self.quadrature.get_points_and_weights(
)
if self.subsampling_algorithm_name is not None:
P = self.get_poly(quadrature_points)
W = np.mat(np.diag(np.sqrt(quadrature_weights)))
A = W * P.T
self.A = A
mm, nn = A.shape
m_refined = int(np.round(self.sampling_ratio * nn))
z = self.subsampling_algorithm_function(A, m_refined)
self._quadrature_points = quadrature_points[z, :]
self._quadrature_weights = quadrature_weights[z] / np.sum(
quadrature_weights[z])
else:
self._quadrature_points = quadrature_points
self._quadrature_weights = quadrature_weights
P = self.get_poly(quadrature_points)
W = np.mat(np.diag(np.sqrt(quadrature_weights)))
A = W * P.T
self.A = A
def _set_statistics(self):
"""
Private method that is used within the statistics routines.
"""
if self.statistics_object is None:
if hasattr(self, 'inv_R_Psi'):
# quad_pts, quad_wts = self.quadrature.get_points_and_weights()
N_quad = 20000
quad_pts = self.corr.get_correlated_samples(N=N_quad)
quad_wts = 1.0 / N_quad * np.ones(N_quad)
poly_vandermonde_matrix = self.get_poly(quad_pts)
elif self.method != 'numerical-integration' and self.dimensions <= 6 and self.highest_order <= MAXIMUM_ORDER_FOR_STATS:
quad = Quadrature(parameters=self.parameters, basis=Basis('tensor-grid', orders= np.array(self.parameters_order) + 1), \
mesh='tensor-grid', points=None)
quad_pts, quad_wts = quad.get_points_and_weights()
poly_vandermonde_matrix = self.get_poly(quad_pts)
elif self.mesh == 'monte-carlo':
quad = Quadrature(parameters=self.parameters,
basis=self.basis,
mesh=self.mesh,
points=None,
oversampling=10.0)
quad_pts, quad_wts = quad.get_points_and_weights()
N_quad = len(quad_wts)
quad_wts = 1.0 / N_quad * np.ones(N_quad)
poly_vandermonde_matrix = self.get_poly(quad_pts)
else:
poly_vandermonde_matrix = self.get_poly(
self._quadrature_points)
quad_pts, quad_wts = self.get_points_and_weights()
if self.highest_order <= MAXIMUM_ORDER_FOR_STATS and (
self.basis.basis_type.lower() == 'total-order'
or self.basis.basis_type.lower() == 'hyperbolic-basis'):
self.statistics_object = Statistics(self.parameters, self.basis, self.coefficients, quad_pts, \
quad_wts, poly_vandermonde_matrix, max_sobol_order=self.highest_order)
else:
self.statistics_object = Statistics(self.parameters, self.basis, self.coefficients, quad_pts, \
quad_wts, poly_vandermonde_matrix, max_sobol_order=MAXIMUM_ORDER_FOR_STATS)
def _set_statistics(self):
"""
Private method that is used withn the statistics routines.
"""
if self.statistics_object is None:
if self.method != 'numerical-integration' and self.dimensions <= 6 and self.highest_order <= MAXIMUM_ORDER_FOR_STATS:
quad = Quadrature(parameters=self.parameters, basis=Basis('tensor-grid', orders= np.array(self.parameters_order) + 1), \
mesh='tensor-grid', points=None)
quad_pts, quad_wts = quad.get_points_and_weights()
poly_vandermonde_matrix = self.get_poly(quad_pts)
else:
poly_vandermonde_matrix = self.get_poly(self._quadrature_points)
quad_pts, quad_wts = self.get_points_and_weights()
if self.highest_order <= MAXIMUM_ORDER_FOR_STATS:
self.statistics_object = Statistics(self.parameters, self.basis, self.coefficients, quad_pts, \
quad_wts, poly_vandermonde_matrix, max_sobol_order=self.highest_order)
else:
self.statistics_object = Statistics(self.parameters, self.basis, self.coefficients, quad_pts, \
quad_wts, poly_vandermonde_matrix, max_sobol_order=MAXIMUM_ORDER_FOR_STATS)