# Copyright (c) 2023, The University of Texas at Austin
# & Georgia Institute of Technology
#
# All Rights reserved.
# See file COPYRIGHT for details.
#
# This file is part of the SOUPy package. For more information see
# https://github.com/hippylib/soupy/
#
# SOUPy is free software; you can redistribute it and/or modify it under the
# terms of the GNU General Public License (as published by the Free
# Software Foundation) version 3.0 dated June 2007.
from mpi4py import MPI
from ..modeling import STATE, PARAMETER, ADJOINT, CONTROL
from ..collectives import get_global, set_local_from_global
[docs]
class ScipyCostWrapper:
"""
Class to interface the :py:class:`soupy.ControlCostFunctional` with a \
scipy optimizer. Converts inputs to functions taking \
and returning :code:`numpy` arrays
"""
def __init__(self, cost_functional, verbose=False):
"""
Constructor
:param cost_functional: The cost functional to wrap
:type cost_functional: :py:class:`ControlCostFunctional`
"""
self.cost_functional = cost_functional
self.z_help = self.cost_functional.generate_vector(CONTROL)
self.z_hat_help = self.cost_functional.generate_vector(CONTROL)
self.z_out_help = self.cost_functional.generate_vector(CONTROL)
self.verbose = verbose
self.n_func = 0
self.n_grad = 0
self.n_hess = 0
[docs]
def cost(self, z_np):
"""
Evaluates the cost functional at given control
:param z_np: The control as a numpy array
:type z_np: :py:class:`numpy.ndarray`
:returns: The value of the cost functional
:return type: float
"""
# self.z_help.set_local(z_np)
# self.z_help.apply("")
set_local_from_global(self.z_help, z_np)
cost_value = self.cost_functional.cost(self.z_help, order=0)
self.n_func += 1
if self.verbose and MPI.COMM_WORLD.Get_rank() == 0:
print("Cost: ", cost_value)
return cost_value
[docs]
def grad(self, z_np):
"""
Evaluates the gradient of the cost functional at given control
:param z_np: The control as a numpy array
:type z_np: :py:class:`numpy.ndarray`
:returns: The gradient
:return type: :py:class:`numpy.ndarray`
"""
# self.z_help.set_local(z_np)
# self.z_help.apply("")
set_local_from_global(self.z_help, z_np)
self.cost_functional.cost(self.z_help, order=1)
self.cost_functional.grad(self.z_out_help)
if self.verbose and MPI.COMM_WORLD.Get_rank() == 0:
print("Gradient evaluation")
self.n_grad += 1
return get_global(self.z_out_help)
[docs]
def hessian(self, z_np, zhat_np):
# self.z_help.set_local(z_np)
# self.z_help.apply("")
set_local_from_global(self.z_help, z_np)
# self.z_hat_help.set_local(zhat_np)
# self.z_hat_help.apply("")
set_local_from_global(self.z_hat_help, zhat_np)
self.cost_functional.cost(self.z_help, order=2)
self.cost_functional.hessian(self.z_hat_help, self.z_out_help)
if self.verbose and MPI.COMM_WORLD.Get_rank() == 0:
print("Hessian action evaluation")
self.n_hess += 1
return get_global(self.z_out_help)
[docs]
def function(self):
"""
:returns: A function that evaluates the cost functional at a given control
"""
return lambda x : self.cost(x)
[docs]
def jac(self):
"""
:returns: A function that evaluates the gradient of the \
cost functional at a given control
"""
return lambda x : self.grad(x)
[docs]
def hessp(self):
"""
:returns: A function that evaluates the Hessian of the \
cost functional at a given control :code:`x`: applied in a direction :code:`p`
"""
return lambda x, p : self.hessian(x,p)