# # Copyright 2019 Gianluca Frison, Dimitris Kouzoupis, Robin Verschueren, # Andrea Zanelli, Niels van Duijkeren, Jonathan Frey, Tommaso Sartor, # Branimir Novoselnik, Rien Quirynen, Rezart Qelibari, Dang Doan, # Jonas Koenemann, Yutao Chen, Tobias Schöls, Jonas Schlagenhauf, Moritz Diehl # # This file is part of acados. # # The 2-Clause BSD License # # Redistribution and use in source and binary forms, with or without # modification, are permitted provided that the following conditions are met: # # 1. Redistributions of source code must retain the above copyright notice, # this list of conditions and the following disclaimer. # # 2. Redistributions in binary form must reproduce the above copyright notice, # this list of conditions and the following disclaimer in the documentation # and/or other materials provided with the distribution. # # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" # AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE # IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE # ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE # LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR # CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF # SUBSTITUTE GOODS OR SERVICES LOSS OF USE, DATA, OR PROFITS OR BUSINESS # INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN # CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) # ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE # POSSIBILITY OF SUCH DAMAGE. # import os from casadi import * from .utils import ALLOWED_CASADI_VERSIONS, casadi_length, casadi_version_warning def generate_c_code_discrete_dynamics( model, opts ): casadi_version = CasadiMeta.version() casadi_opts = dict(mex=False, casadi_int='int', casadi_real='double') if casadi_version not in (ALLOWED_CASADI_VERSIONS): casadi_version_warning(casadi_version) # load model x = model.x u = model.u p = model.p phi = model.disc_dyn_expr model_name = model.name nx = x.size()[0] if isinstance(phi, casadi.MX): symbol = MX.sym elif isinstance(phi, casadi.SX): symbol = SX.sym else: Exception("generate_c_code_disc_dyn: disc_dyn_expr must be a CasADi expression, you have type: {}".format(type(phi))) # assume nx1 = nx !!! lam = symbol('lam', nx, 1) # generate jacobians ux = vertcat(u,x) jac_ux = jacobian(phi, ux) # generate adjoint adj_ux = jtimes(phi, ux, lam, True) # generate hessian hess_ux = jacobian(adj_ux, ux) ## change directory code_export_dir = opts["code_export_directory"] if not os.path.exists(code_export_dir): os.makedirs(code_export_dir) cwd = os.getcwd() os.chdir(code_export_dir) model_dir = model_name + '_model' if not os.path.exists(model_dir): os.mkdir(model_dir) model_dir_location = os.path.join('.', model_dir) os.chdir(model_dir_location) # set up & generate Functions fun_name = model_name + '_dyn_disc_phi_fun' phi_fun = Function(fun_name, [x, u, p], [phi]) phi_fun.generate(fun_name, casadi_opts) fun_name = model_name + '_dyn_disc_phi_fun_jac' phi_fun_jac_ut_xt = Function(fun_name, [x, u, p], [phi, jac_ux.T]) phi_fun_jac_ut_xt.generate(fun_name, casadi_opts) fun_name = model_name + '_dyn_disc_phi_fun_jac_hess' phi_fun_jac_ut_xt_hess = Function(fun_name, [x, u, lam, p], [phi, jac_ux.T, hess_ux]) phi_fun_jac_ut_xt_hess.generate(fun_name, casadi_opts) os.chdir(cwd)