# # 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 SX, MX, Function, transpose, vertcat, horzcat, hessian, CasadiMeta from .utils import ALLOWED_CASADI_VERSIONS, casadi_version_warning def generate_c_code_external_cost(model, stage_type, 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) x = model.x p = model.p if isinstance(x, MX): symbol = MX.sym else: symbol = SX.sym if stage_type == 'terminal': suffix_name = "_cost_ext_cost_e_fun" suffix_name_hess = "_cost_ext_cost_e_fun_jac_hess" suffix_name_jac = "_cost_ext_cost_e_fun_jac" u = symbol("u", 0, 0) ext_cost = model.cost_expr_ext_cost_e custom_hess = model.cost_expr_ext_cost_custom_hess_e elif stage_type == 'path': suffix_name = "_cost_ext_cost_fun" suffix_name_hess = "_cost_ext_cost_fun_jac_hess" suffix_name_jac = "_cost_ext_cost_fun_jac" u = model.u ext_cost = model.cost_expr_ext_cost custom_hess = model.cost_expr_ext_cost_custom_hess elif stage_type == 'initial': suffix_name = "_cost_ext_cost_0_fun" suffix_name_hess = "_cost_ext_cost_0_fun_jac_hess" suffix_name_jac = "_cost_ext_cost_0_fun_jac" u = model.u ext_cost = model.cost_expr_ext_cost_0 custom_hess = model.cost_expr_ext_cost_custom_hess_0 # set up functions to be exported fun_name = model.name + suffix_name fun_name_hess = model.name + suffix_name_hess fun_name_jac = model.name + suffix_name_jac # generate expression for full gradient and Hessian full_hess, grad = hessian(ext_cost, vertcat(u, x)) if custom_hess is not None: full_hess = custom_hess ext_cost_fun = Function(fun_name, [x, u, p], [ext_cost]) ext_cost_fun_jac_hess = Function( fun_name_hess, [x, u, p], [ext_cost, grad, full_hess] ) ext_cost_fun_jac = Function( fun_name_jac, [x, u, p], [ext_cost, grad] ) # generate C code 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) gen_dir = model.name + '_cost' if not os.path.exists(gen_dir): os.mkdir(gen_dir) gen_dir_location = "./" + gen_dir os.chdir(gen_dir_location) ext_cost_fun.generate(fun_name, casadi_opts) ext_cost_fun_jac_hess.generate(fun_name_hess, casadi_opts) ext_cost_fun_jac.generate(fun_name_jac, casadi_opts) os.chdir(cwd) return