def apply(self, x, mode):
self._check_mode(mode=mode)
if mode == self.TIMES:
x_tau_beta = x.val['tau_beta']
# (delta_{zz'} beta.del_B_inv_z.beta + smoothing_beta)
field_for_diagonal = nifty5.Field.from_local_data(
domain=self.p_space,
arr=np.array([
self.beta.vdot(del_B_inv.times(self.beta))
for del_B_inv in self.del_B_inv_list
]))
delta_beta_del_B_inv_beta = nifty5.DiagonalOperator(
domain=self.p_space, diagonal=field_for_diagonal)
term_tau_beta_1 = delta_beta_del_B_inv_beta.times(x_tau_beta)
term_tau_beta_2 = self.smoothness_operator_beta.times(x_tau_beta)
result_fields = {
'beta': nifty5.Field.zeros(domain=self.s_space),
'tau_beta': term_tau_beta_1 + term_tau_beta_2,
}
result = global_newton.MultiField(domain=x.domain,
val=result_fields)
return result
def apply(self, x, mode):
self._check_mode(mode=mode)
if mode == self.TIMES:
x_tau_beta = x.val['tau_beta']
# -beta.del_B_inv applied to tau_beta
term_beta = nifty5.Field.from_global_data(
domain=self.s_space,
arr=np.array([
nifty5.Field.from_global_data(
domain=self.p_space,
arr=np.array([
B_inv.adjoint_times(self.beta).val[i]
for B_inv in self.del_B_inv_list
])).vdot(x_tau_beta)
for i in range(self.s_space.shape[0])
]))
result_fields = {
'beta': term_beta,
'tau_beta': nifty5.Field.zeros(domain=self.p_space)
}
result = global_newton.MultiField(domain=x.domain,
val=result_fields)
return result
def gradient(self):
if self.mode == 'multifield':
gradient_beta = sum(self.get_gradient_beta_terms())
gradient_tau_beta = sum(self.get_gradient_tau_beta_terms())
gradients = {
'beta': gradient_beta,
'tau_beta': gradient_tau_beta,
}
gradient = global_newton.MultiField(
self.position.domain, val=gradients)
elif self.mode == 'beta':
gradient = sum(self.get_gradient_beta_terms())
elif self.mode == 'tau_beta':
gradient = sum(self.get_gradient_tau_beta_terms())
else:
print('invalid mode')
return gradient
def apply(self, x, mode):
self._check_mode(mode=mode)
if mode == self.TIMES:
x_beta = x.val['beta']
# application of operator to beta field
term_beta_1 = self.B_inv.times(x_beta)
rho_exp_beta = np.zeros(self.len_s_space)
for i, pos in enumerate(self.grid):
rho_exp_beta[pos] = (self.rho * np.exp(self.beta.val[pos]))
rho_exp_beta_field = nifty5.Field.from_global_data(
domain=self.s_space, arr=rho_exp_beta)
term_beta_2 = rho_exp_beta_field * x_beta
result_fields = {
'beta': term_beta_1 + term_beta_2,
'tau_beta': nifty5.Field.zeros(domain=self.p_space),
}
result = global_newton.MultiField(domain=x.domain,
val=result_fields)
return result