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331 lines
12 KiB
331 lines
12 KiB
# -*- coding: future_fstrings -*-
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#
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# Copyright 2019 Gianluca Frison, Dimitris Kouzoupis, Robin Verschueren,
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# Andrea Zanelli, Niels van Duijkeren, Jonathan Frey, Tommaso Sartor,
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# Branimir Novoselnik, Rien Quirynen, Rezart Qelibari, Dang Doan,
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# Jonas Koenemann, Yutao Chen, Tobias Schöls, Jonas Schlagenhauf, Moritz Diehl
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#
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# This file is part of acados.
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#
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# The 2-Clause BSD License
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#
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# Redistribution and use in source and binary forms, with or without
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# modification, are permitted provided that the following conditions are met:
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#
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# 1. Redistributions of source code must retain the above copyright notice,
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# this list of conditions and the following disclaimer.
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#
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# 2. Redistributions in binary form must reproduce the above copyright notice,
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# this list of conditions and the following disclaimer in the documentation
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# and/or other materials provided with the distribution.
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#
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# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
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# ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
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# LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
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# CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
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# SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
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# INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
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# CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
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# ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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# POSSIBILITY OF SUCH DAMAGE.;
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#
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import numpy as np
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import casadi as ca
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import os
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from .acados_model import AcadosModel
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from .utils import get_acados_path
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class AcadosSimDims:
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"""
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Class containing the dimensions of the model to be simulated.
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"""
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def __init__(self):
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self.__nx = None
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self.__nu = None
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self.__nz = 0
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self.__np = 0
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@property
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def nx(self):
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""":math:`n_x` - number of states. Type: int > 0"""
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return self.__nx
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@property
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def nz(self):
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""":math:`n_z` - number of algebraic variables. Type: int >= 0"""
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return self.__nz
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@property
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def nu(self):
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""":math:`n_u` - number of inputs. Type: int >= 0"""
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return self.__nu
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@property
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def np(self):
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""":math:`n_p` - number of parameters. Type: int >= 0"""
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return self.__np
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@nx.setter
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def nx(self, nx):
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if isinstance(nx, int) and nx > 0:
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self.__nx = nx
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else:
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raise Exception('Invalid nx value, expected positive integer. Exiting.')
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@nz.setter
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def nz(self, nz):
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if isinstance(nz, int) and nz > -1:
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self.__nz = nz
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else:
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raise Exception('Invalid nz value, expected nonnegative integer. Exiting.')
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@nu.setter
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def nu(self, nu):
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if isinstance(nu, int) and nu > -1:
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self.__nu = nu
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else:
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raise Exception('Invalid nu value, expected nonnegative integer. Exiting.')
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@np.setter
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def np(self, np):
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if isinstance(np, int) and np > -1:
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self.__np = np
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else:
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raise Exception('Invalid np value, expected nonnegative integer. Exiting.')
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def set(self, attr, value):
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setattr(self, attr, value)
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class AcadosSimOpts:
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"""
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class containing the solver options
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"""
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def __init__(self):
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self.__integrator_type = 'ERK'
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self.__collocation_type = 'GAUSS_LEGENDRE'
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self.__Tsim = None
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# ints
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self.__sim_method_num_stages = 1
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self.__sim_method_num_steps = 1
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self.__sim_method_newton_iter = 3
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# bools
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self.__sens_forw = True
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self.__sens_adj = False
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self.__sens_algebraic = False
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self.__sens_hess = False
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self.__output_z = False
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self.__sim_method_jac_reuse = 0
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@property
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def integrator_type(self):
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"""Integrator type. Default: 'ERK'."""
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return self.__integrator_type
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@property
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def num_stages(self):
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"""Number of stages in the integrator. Default: 1"""
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return self.__sim_method_num_stages
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@property
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def num_steps(self):
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"""Number of steps in the integrator. Default: 1"""
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return self.__sim_method_num_steps
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@property
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def newton_iter(self):
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"""Number of Newton iterations in simulation method. Default: 3"""
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return self.__sim_method_newton_iter
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@property
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def sens_forw(self):
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"""Boolean determining if forward sensitivities are computed. Default: True"""
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return self.__sens_forw
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@property
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def sens_adj(self):
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"""Boolean determining if adjoint sensitivities are computed. Default: False"""
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return self.__sens_adj
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@property
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def sens_algebraic(self):
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"""Boolean determining if sensitivities wrt algebraic variables are computed. Default: False"""
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return self.__sens_algebraic
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@property
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def sens_hess(self):
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"""Boolean determining if hessians are computed. Default: False"""
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return self.__sens_hess
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@property
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def output_z(self):
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"""Boolean determining if values for algebraic variables (corresponding to start of simulation interval) are computed. Default: False"""
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return self.__output_z
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@property
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def sim_method_jac_reuse(self):
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"""Integer determining if jacobians are reused (0 or 1). Default: 0"""
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return self.__sim_method_jac_reuse
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@property
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def T(self):
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"""Time horizon"""
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return self.__Tsim
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@property
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def collocation_type(self):
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"""Collocation type: relevant for implicit integrators
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-- string in {GAUSS_RADAU_IIA, GAUSS_LEGENDRE}
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Default: GAUSS_LEGENDRE
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"""
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return self.__collocation_type
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@integrator_type.setter
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def integrator_type(self, integrator_type):
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integrator_types = ('ERK', 'IRK', 'GNSF')
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if integrator_type in integrator_types:
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self.__integrator_type = integrator_type
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else:
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raise Exception('Invalid integrator_type value. Possible values are:\n\n' \
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+ ',\n'.join(integrator_types) + '.\n\nYou have: ' + integrator_type + '.\n\nExiting.')
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@collocation_type.setter
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def collocation_type(self, collocation_type):
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collocation_types = ('GAUSS_RADAU_IIA', 'GAUSS_LEGENDRE')
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if collocation_type in collocation_types:
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self.__collocation_type = collocation_type
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else:
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raise Exception('Invalid collocation_type value. Possible values are:\n\n' \
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+ ',\n'.join(collocation_types) + '.\n\nYou have: ' + collocation_type + '.\n\nExiting.')
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@T.setter
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def T(self, T):
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self.__Tsim = T
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@num_stages.setter
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def num_stages(self, num_stages):
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if isinstance(num_stages, int):
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self.__sim_method_num_stages = num_stages
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else:
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raise Exception('Invalid num_stages value. num_stages must be an integer.')
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@num_steps.setter
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def num_steps(self, num_steps):
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if isinstance(num_steps, int):
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self.__sim_method_num_steps = num_steps
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else:
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raise Exception('Invalid num_steps value. num_steps must be an integer.')
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@newton_iter.setter
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def newton_iter(self, newton_iter):
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if isinstance(newton_iter, int):
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self.__sim_method_newton_iter = newton_iter
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else:
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raise Exception('Invalid newton_iter value. newton_iter must be an integer.')
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@sens_forw.setter
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def sens_forw(self, sens_forw):
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if sens_forw in (True, False):
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self.__sens_forw = sens_forw
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else:
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raise Exception('Invalid sens_forw value. sens_forw must be a Boolean.')
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@sens_adj.setter
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def sens_adj(self, sens_adj):
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if sens_adj in (True, False):
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self.__sens_adj = sens_adj
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else:
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raise Exception('Invalid sens_adj value. sens_adj must be a Boolean.')
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@sens_hess.setter
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def sens_hess(self, sens_hess):
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if sens_hess in (True, False):
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self.__sens_hess = sens_hess
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else:
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raise Exception('Invalid sens_hess value. sens_hess must be a Boolean.')
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@sens_algebraic.setter
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def sens_algebraic(self, sens_algebraic):
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if sens_algebraic in (True, False):
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self.__sens_algebraic = sens_algebraic
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else:
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raise Exception('Invalid sens_algebraic value. sens_algebraic must be a Boolean.')
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@output_z.setter
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def output_z(self, output_z):
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if output_z in (True, False):
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self.__output_z = output_z
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else:
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raise Exception('Invalid output_z value. output_z must be a Boolean.')
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@sim_method_jac_reuse.setter
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def sim_method_jac_reuse(self, sim_method_jac_reuse):
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if sim_method_jac_reuse in (0, 1):
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self.__sim_method_jac_reuse = sim_method_jac_reuse
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else:
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raise Exception('Invalid sim_method_jac_reuse value. sim_method_jac_reuse must be 0 or 1.')
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class AcadosSim:
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"""
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The class has the following properties that can be modified to formulate a specific simulation problem, see below:
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:param acados_path: string with the path to acados. It is used to generate the include and lib paths.
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- :py:attr:`dims` of type :py:class:`acados_template.acados_ocp.AcadosSimDims` - are automatically detected from model
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- :py:attr:`model` of type :py:class:`acados_template.acados_model.AcadosModel`
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- :py:attr:`solver_options` of type :py:class:`acados_template.acados_sim.AcadosSimOpts`
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- :py:attr:`acados_include_path` (set automatically)
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- :py:attr:`acados_lib_path` (set automatically)
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- :py:attr:`parameter_values` - used to initialize the parameters (can be changed)
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"""
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def __init__(self, acados_path=''):
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if acados_path == '':
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acados_path = get_acados_path()
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self.dims = AcadosSimDims()
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"""Dimension definitions, automatically detected from :py:attr:`model`. Type :py:class:`acados_template.acados_sim.AcadosSimDims`"""
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self.model = AcadosModel()
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"""Model definitions, type :py:class:`acados_template.acados_model.AcadosModel`"""
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self.solver_options = AcadosSimOpts()
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"""Solver Options, type :py:class:`acados_template.acados_sim.AcadosSimOpts`"""
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self.acados_include_path = os.path.join(acados_path, 'include').replace(os.sep, '/') # the replace part is important on Windows for CMake
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"""Path to acados include directory (set automatically), type: `string`"""
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self.acados_lib_path = os.path.join(acados_path, 'lib').replace(os.sep, '/') # the replace part is important on Windows for CMake
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"""Path to where acados library is located (set automatically), type: `string`"""
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self.code_export_directory = 'c_generated_code'
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"""Path to where code will be exported. Default: `c_generated_code`."""
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self.cython_include_dirs = ''
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self.__parameter_values = np.array([])
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@property
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def parameter_values(self):
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""":math:`p` - initial values for parameter - can be updated"""
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return self.__parameter_values
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@parameter_values.setter
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def parameter_values(self, parameter_values):
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if isinstance(parameter_values, np.ndarray):
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self.__parameter_values = parameter_values
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else:
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raise Exception('Invalid parameter_values value. ' +
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f'Expected numpy array, got {type(parameter_values)}.')
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def set(self, attr, value):
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# tokenize string
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tokens = attr.split('_', 1)
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if len(tokens) > 1:
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setter_to_call = getattr(getattr(self, tokens[0]), 'set')
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else:
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setter_to_call = getattr(self, 'set')
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setter_to_call(tokens[1], value)
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return
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