# -*- coding: utf-8 -*-
# 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: Francois Gallard
# OTHER AUTHORS - MACROSCOPIC CHANGES
"""
SSBJ Disciplines wrappers
*************************
"""
from __future__ import division, unicode_literals
import time
from numbers import Number
from gemseo.core.discipline import MDODiscipline
from gemseo.problems.sobieski.core import SobieskiProblem
DTYPE_COMPLEX = "complex128"
DTYPE_DOUBLE = "float64"
[docs]class SobieskiBaseWrapper(MDODiscipline):
"""Base wrapper for Sobieski problem discipline wrappers and JSON grammars."""
_ATTR_TO_SERIALIZE = MDODiscipline._ATTR_TO_SERIALIZE + ("dtype",)
def __init__(self, dtype=DTYPE_DOUBLE):
"""Constructor.
:param dtype: type of data, either "float64" or "complex128".
:type dtype: str
"""
super(SobieskiBaseWrapper, self).__init__(auto_detect_grammar_files=True)
self.dtype = dtype
self.sobieski_problem = SobieskiProblem(dtype=dtype)
self.default_inputs = self.sobieski_problem.get_default_inputs(
self.get_input_data_names()
)
self.re_exec_policy = self.RE_EXECUTE_DONE_POLICY
def __setstate__(self, d):
"""Used by pickle to define what to deserialize.
:param d : update self dict from d to deserialize
"""
super(SobieskiBaseWrapper, self).__setstate__(d)
self.sobieski_problem = SobieskiProblem(self.dtype)
def _run(self):
"""Run the discipline."""
raise NotImplementedError()
[docs]class SobieskiMission(SobieskiBaseWrapper):
"""Sobieski range wrapper using the Breguet formula."""
_ATTR_TO_SERIALIZE = SobieskiBaseWrapper._ATTR_TO_SERIALIZE + ("enable_delay",)
def __init__(self, dtype=DTYPE_DOUBLE, enable_delay=False):
"""Constructor of wrapper for range computation.
:param dtype: type of data, either "float64" or "complex128".
:type dtype: str
"""
super(SobieskiMission, self).__init__(dtype=dtype)
self.enable_delay = enable_delay
def _run(self):
"""Compute range."""
if self.enable_delay:
if isinstance(self.enable_delay, Number):
time.sleep(self.enable_delay)
else:
time.sleep(1.0)
data_names = ["y_14", "y_24", "y_34", "x_shared"]
y_14, y_24, y_34, x_shared = self.get_inputs_by_name(data_names)
y_4 = self.sobieski_problem.blackbox_mission(x_shared, y_14, y_24, y_34)
self.store_local_data(y_4=y_4)
def _compute_jacobian(self, inputs=None, outputs=None):
"""Compute the partial derivatives of all outputs wrt all inputs.
:param inputs: Default value = None)
:param outputs: Default value = None)
"""
data_names = ["y_14", "y_24", "y_34", "x_shared"]
y_14, y_24, y_34, x_shared = self.get_inputs_by_name(data_names)
self.jac = self.sobieski_problem.derive_blackbox_mission(
x_shared, y_14, y_24, y_34
)
[docs]class SobieskiStructure(SobieskiBaseWrapper):
"""Sobieski mass estimation wrapper."""
def __init__(self, dtype=DTYPE_DOUBLE):
"""Constructor of wrapper for weight computation.
:param dtype: type of data, either "float64" or "complex128".
:type dtype: str
"""
super(SobieskiStructure, self).__init__(dtype=dtype)
def _run(self):
"""Compute weight."""
data_names = ["x_1", "y_21", "y_31", "x_shared"]
x_1, y_21, y_31, x_shared = self.get_inputs_by_name(data_names)
y_1, y_11, y_12, y_14, g_1 = self.sobieski_problem.blackbox_structure(
x_shared, y_21, y_31, x_1
)
self.store_local_data(y_1=y_1, y_11=y_11, y_12=y_12, y_14=y_14, g_1=g_1)
def _compute_jacobian(self, inputs=None, outputs=None):
"""Linearization of weight analysis.
:param inputs: Default value = None)
:param outputs: Default value = None)
"""
data_names = ["x_1", "y_21", "y_31", "x_shared"]
x_1, y_21, y_31, x_shared = self.get_inputs_by_name(data_names)
self.jac = self.sobieski_problem.derive_blackbox_structure(
x_shared, y_21, y_31, x_1
)
[docs]class SobieskiAerodynamics(SobieskiBaseWrapper):
"""Sobieski aerodynamic discipline wrapper."""
def __init__(self, dtype=DTYPE_DOUBLE):
"""Constructor of wrapper for aerodynamic computation.
:param dtype: type of data, "float64" or "complex128".
:type dtype: str
"""
super(SobieskiAerodynamics, self).__init__(dtype=dtype)
def _run(self):
"""Compute aerodynamics."""
data_names = ["x_2", "y_12", "y_32", "x_shared"]
x_2, y_12, y_32, x_shared = self.get_inputs_by_name(data_names)
y_2, y_21, y_23, y_24, g_2 = self.sobieski_problem.blackbox_aerodynamics(
x_shared, y_12, y_32, x_2
)
self.store_local_data(y_2=y_2, y_21=y_21, y_23=y_23, y_24=y_24, g_2=g_2)
def _compute_jacobian(self, inputs=None, outputs=None):
"""Compute the partial derivatives of all outputs wrt all inputs.
:param inputs: Default value = None)
:param outputs: Default value = None)
"""
data_names = ["x_2", "y_12", "y_32", "x_shared"]
x_2, y_12, y_32, x_shared = self.get_inputs_by_name(data_names)
self.jac = self.sobieski_problem.derive_blackbox_aerodynamics(
x_shared, y_12, y_32, x_2
)
[docs]class SobieskiPropulsion(SobieskiBaseWrapper):
"""Sobieski propulsion propulsion wrapper."""
def __init__(self, dtype=DTYPE_DOUBLE):
"""Constructor of wrapper for propulsion computation.
:param dtype: type of data, either "float64" or "complex128"
:type dtype: str
"""
super(SobieskiPropulsion, self).__init__(dtype=dtype)
def _run(self):
"""Compute propulsion."""
data_names = ["x_3", "y_23", "x_shared"]
x_3, y_23, x_shared = self.get_inputs_by_name(data_names)
y_3, y_34, y_31, y_32, g_3 = self.sobieski_problem.blackbox_propulsion(
x_shared, y_23, x_3
)
self.store_local_data(y_3=y_3, y_34=y_34, y_31=y_31, y_32=y_32, g_3=g_3)
def _compute_jacobian(self, inputs=None, outputs=None):
"""Compute the partial derivatives of all outputs wrt all inputs.
:param inputs: Default value = None)
:param outputs: Default value = None)
"""
data_names = ["x_3", "y_23", "x_shared"]
x_3, y_23, x_shared = self.get_inputs_by_name(data_names)
self.jac = self.sobieski_problem.derive_blackbox_propulsion(x_shared, y_23, x_3)
