# Source code for gemseo.algos.sequence_transformer.composite.composite

```
# 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.
# Contributors:
# INITIAL AUTHORS - initial API and implementation and/or initial
# documentation
# :author: Sebastien Bocquet, Alexandre Scotto Di Perrotolo
# OTHER AUTHORS - MACROSCOPIC CHANGES
"""A composite of sequence transformers applied sequentially."""
from __future__ import annotations
from typing import TYPE_CHECKING
from gemseo.algos.sequence_transformer.sequence_transformer import SequenceTransformer
if TYPE_CHECKING:
from numpy.typing import NDArray
from typing import ClassVar
from typing import Iterable
[docs]class CompositeSequenceTransformer(SequenceTransformer):
"""A composite of SequenceTransformer."""
_MINIMUM_NUMBER_OF_ITERATES: ClassVar[int] = 0
_MINIMUM_NUMBER_OF_RESIDUALS: ClassVar[int] = 0
_sequence_transformers: Iterable[SequenceTransformer]
"""The sequence transformers that are chained."""
def __init__(self, sequence_transformers: Iterable[SequenceTransformer]) -> None:
"""
Args:
sequence_transformers: The sequence of SequenceTransformers.
""" # noqa:D205 D212 D415
super().__init__()
self._sequence_transformers = sequence_transformers
def _compute_transformed_iterate(self) -> None: # pragma: no cover
pass
[docs] def clear(self) -> None:
"""Clear the iterates in the double-ended queues."""
for transformer in self._sequence_transformers:
transformer.clear()
[docs] def compute_transformed_iterate(
self,
current_iterate: NDArray,
next_iterate: NDArray,
) -> NDArray:
"""Compute the next transformed iterate.
Args:
current_iterate: The current iterate :math:`x_n`.
next_iterate: The new iterate :math:`G(x_n)`.
Returns:
The next transformed iterate :math:`x_{n+1}`.
"""
for transformer in self._sequence_transformers:
next_iterate = transformer.compute_transformed_iterate(
current_iterate, next_iterate
)
return next_iterate
```