# Copyright 2021 IRT Saint Exupéry, https://www.irt-saintexupery.com
#
# This program is free software; you can redistribute it and/or
# modify it under the terms of the GNU Lesser General Public
# License version 3 as published by the Free Software Foundation.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
# Lesser General Public License for more details.
#
# You should have received a copy of the GNU Lesser General Public License
# along with this program; if not, write to the Free Software Foundation,
# Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
"""The functional operations."""
from __future__ import annotations
from typing import TYPE_CHECKING
from numpy import delete
from numpy import insert
from gemseo.core.mdofunctions.mdo_function import MDOFunction
from gemseo.utils.string_tools import pretty_str
if TYPE_CHECKING:
from collections.abc import Sequence
from gemseo.typing import RealArray
[docs]
class RestrictedFunction(MDOFunction):
"""Restrict an MDOFunction to a subset of its input vector.
Fixes the rest of the indices.
"""
def __init__(
self,
orig_function: MDOFunction,
restriction_indices: Sequence[int],
restriction_values: RealArray,
) -> None:
"""
Args:
orig_function: The original function to restrict.
restriction_indices: The indices array of the input vector to fix.
restriction_values: The values of the input vector at the indices,
'restriction_indices' are set to 'restriction_values'.
Raises:
ValueError: If the shape of the restriction values is not consistent
with the shape of the restriction indices.
""" # noqa: D205, D212, D415
if restriction_indices.shape != restriction_values.shape:
msg = "Inconsistent shapes for restriction values and indices."
raise ValueError(msg)
self.restriction_values = restriction_values
self._restriction_indices = restriction_indices
self._orig_function = orig_function
super().__init__(
self._func_to_wrap,
f"{orig_function.name}_restr",
jac=self._jac_to_wrap,
f_type=orig_function.f_type,
expr=orig_function.expr,
input_names=orig_function.input_names,
dim=orig_function.dim,
output_names=orig_function.output_names,
original_name=orig_function.original_name,
)
def _func_to_wrap(self, x_vect: RealArray) -> RealArray:
"""Wrap the provided function in order to be given to the optimizer.
Args:
x_vect: The design variables values.
Returns:
The evaluation of the function at x_vect.
"""
x_full = insert(x_vect, self._restriction_indices, self.restriction_values)
return self._orig_function(x_full)
def _jac_to_wrap(self, x_vect: RealArray) -> RealArray:
"""Wrap the provided Jacobian in order to be given to the optimizer.
Args:
x_vect: The design variables values.
Returns:
The evaluation of the Jacobian at x_vect.
"""
x_full = insert(x_vect, self._restriction_indices, self.restriction_values)
jac = self._orig_function.jac(x_full)
return delete(jac, self._restriction_indices, axis=0)
# TODO: API: move to a specific module
[docs]
class LinearComposition(MDOFunction):
r"""Linear composite function.
Given a matrix :math:`A`, a function :math:`f` and an input vector :math:`x`,
the linear composite function outputs :math:`f(Ax)`.
"""
# TODO: API: rename orig_function to function.
# TODO: API: rename interp_operator to matrix.
def __init__(
self,
orig_function: MDOFunction,
interp_operator: RealArray,
) -> None:
r"""
Args:
orig_function: The function :math:`f`.
interp_operator: The matrix :math:`A`.
""" # noqa: D205, D212, D415
self._orig_function = orig_function
self._interp_operator = interp_operator
self._orig_function = orig_function
# TODO: API: Rename function name to "[f o A]"
input_names = orig_function.input_names
if len(input_names) == 1:
x = orig_function.input_names[0]
else:
x = f"({pretty_str(orig_function.input_names)})'"
super().__init__(
self._restricted_function,
str(orig_function.name) + "_comp",
jac=self._restricted_jac,
f_type=orig_function.f_type,
expr=f"{orig_function.name}(A.{x})",
input_names=orig_function.input_names,
dim=orig_function.dim,
output_names=orig_function.output_names,
)
def _restricted_function(self, x_vect: RealArray) -> RealArray:
"""Wrap the provided function in order to be given to the optimizer.
Args:
x_vect: The design variable values.
Returns:
The evaluation of the function at x_vect.
"""
x_full = self._interp_operator.dot(x_vect)
return self._orig_function(x_full)
def _restricted_jac(self, x_vect: RealArray) -> RealArray:
"""Wrap the provided Jacobian in order to be given to the optimizer.
Args:
x_vect: The design variable values.
Returns:
The evaluation of the function at x_vect.
"""
x_full = self._interp_operator.dot(x_vect)
jac = self._orig_function.jac(x_full)
return self._interp_operator.T.dot(jac)
