def solveInverse(self, zeta0, u_obs, zeta_inv):
r"""Executes the inversion algorithm.
:param zeta0: The best `a-priori` guess for the value of the parameterized design variable value :math:`\zeta`.
Ignored by siple gradient algorithms in deference to `zeta_inv`.
:param u_obs: :cpp:class:`IceModelVec2V` of observed surface velocities.
:param zeta_inv: :cpp:class:`zeta_inv` starting value of :math:`\zeta` for iterative minimization.
:returns: A :cpp:class:`TerminationReason`.
"""
try:
vecs = self.ssarun.modeldata.vecs
if vecs.has('zeta_fixed_mask'):
self.ssarun.ssa.set_tauc_fixed_locations(vecs.zeta_fixed_mask)
(self.zeta_i,
self.u_i) = self.siple_solver.solve(zeta_inv, u_obs,
self.target_misfit)
except Exception:
import traceback
exc_type, exc_value, exc_traceback = sys.exc_info()
description = ""
for l in traceback.format_exception(exc_type, exc_value,
exc_traceback):
description += l
# It would be nice to make siple so that if the inverse solve fails
# you can still keep the most recent iteration.
self.u_i = None
self.zeta_i = None
return PISM.GenericTerminationReason(-1, description)
return PISM.GenericTerminationReason(1, "Morozov Discrepancy Met")
