Source code for gemseo.core.analytic_discipline

# -*- coding: utf-8 -*-
# Copyright 2021 IRT Saint Exupéry,
# 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
# 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
Analytic MDODiscipline based on symbolic expressions
from __future__ import absolute_import, division, print_function, unicode_literals

from future import standard_library
from numpy import array, float64, zeros
from six import string_types
from sympy.parsing.sympy_parser import parse_expr

from gemseo.core.discipline import MDODiscipline


from gemseo import LOGGER

[docs]class AnalyticDiscipline(MDODiscipline): """Discipline based on analytic expressions list, using the symbolic calculation sympy engine. Automatically differentiates the expressions to obtain the Jacobian matrices. See also -------- gemseo.core.discipline.MDODiscipline : abstract class defining the key concept of discipline """ def __init__(self, name=None, expressions_dict=None): """ Constructor :param name: name of the discipline. :param expressions_dict: dictionary of outputs and their expressions for instance : { 'y_1':'2*x**2', 'y_2':'4*x**2+5+z**3'} will create a discipline with outputs y_1, y_2 and inputs x, and z. """ super(AnalyticDiscipline, self).__init__(name) if not expressions_dict: raise ValueError("expressions_dict is a mandatory argument") self.expressions_dict = expressions_dict self.expr_symbols_dict = {} self.input_names = [] self._sympy_exprs = {} self._sympy_jac_exprs = {} self._init_expressions() self._init_grammars() self._init_default_inputs() self.re_exec_policy = self.RE_EXECUTE_DONE_POLICY def _init_grammars(self): """Initializes the |g| grammars from the expressions dict""" zero = zeros(2) in_dict = {k: zero for k in self.input_names} self.input_grammar.initialize_from_base_dict(in_dict) out_dict = {k: zero for k in self.expressions_dict} self.output_grammar.initialize_from_base_dict(out_dict) def _init_expressions(self): """Parses the expressions and get sympy exprs idem for jacobians """ input_symbols = [] for out_var, expr in self.expressions_dict.items(): if not isinstance(expr, string_types): raise TypeError("Expressions must be an iterable of strings") parsed = parse_expr(expr) args = list(parsed.free_symbols) self._sympy_exprs[out_var] = parsed input_symbols += args args_names = [ for arg in args] self.expr_symbols_dict[out_var] = args_names self._sympy_jac_exprs[out_var] = {} for arg in args_names: jac_expr = parsed.diff(arg) self._sympy_jac_exprs[out_var][arg] = jac_expr self.input_names = [ for symb in set(input_symbols)] def _init_default_inputs(self): """Initalizes the default inputs of the discipline with zeros """ zeros_array = zeros(1) self.default_inputs = {k: zeros_array for k in self.input_names} def _run(self): """ Runs the discipline """ outputs = {} # Do not pass useless tokens to the expr, this may # fail when tokens contains dots, or slow down the process filtered_inputs = {key: float(val.real) for key, val in self.local_data.items()} for out_var, expr in self._sympy_exprs.items(): try: out_val = expr.evalf(subs=filtered_inputs) outputs[out_var] = array([out_val], dtype=float64) except TypeError: LOGGER.error("Failed to evaluate expression : %s", str(expr)) LOGGER.error("With inputs : %s", str(self.local_data)) raise self.store_local_data(**outputs) def _compute_jacobian(self, inputs=None, outputs=None): """ Computes the jacobian :param inputs: Default value = None) :param outputs: Default value = None) """ # otherwise there may be missing terms # if some formula have no dependency self._init_jacobian(inputs, outputs, with_zeros=True) filtered_inputs = {key: float(val.real) for key, val in self.local_data.items()} for out_var, expr in self._sympy_exprs.items(): for arg in expr.free_symbols: j_expr = self._sympy_jac_exprs[out_var][] jac_val = j_expr.evalf(subs=filtered_inputs) self.jac[out_var][] = array([[jac_val]], dtype=float64)