# -*- coding: future_fstrings -*- # # 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.; # # cython: language_level=3 # cython: profile=False # distutils: language=c cimport cython from libc cimport string cimport acados_solver_common cimport acados_solver cimport numpy as cnp import os import numpy as np cdef class AcadosOcpSolverFast: """ Class to interact with the acados ocp solver C object. :param acados_ocp: type AcadosOcp - description of the OCP for acados :param json_file: name for the json file used to render the templated code - default: acados_ocp_nlp.json :param simulink_opts: Options to configure Simulink S-function blocks, mainly to activate possible Inputs and Outputs """ cdef acados_solver.nlp_solver_capsule *capsule cdef void *nlp_opts cdef acados_solver_common.ocp_nlp_dims *nlp_dims cdef acados_solver_common.ocp_nlp_config *nlp_config cdef acados_solver_common.ocp_nlp_out *nlp_out cdef acados_solver_common.ocp_nlp_in *nlp_in cdef acados_solver_common.ocp_nlp_solver *nlp_solver cdef str model_name cdef int N cdef bint solver_created def __cinit__(self, str model_name, int N, str code_export_dir): self.model_name = model_name self.N = N self.solver_created = False # create capsule self.capsule = acados_solver.acados_create_capsule() # create solver assert acados_solver.acados_create(self.capsule) == 0 self.solver_created = True # get pointers solver self.nlp_opts = acados_solver.acados_get_nlp_opts(self.capsule) self.nlp_dims = acados_solver.acados_get_nlp_dims(self.capsule) self.nlp_config = acados_solver.acados_get_nlp_config(self.capsule) self.nlp_out = acados_solver.acados_get_nlp_out(self.capsule) self.nlp_in = acados_solver.acados_get_nlp_in(self.capsule) self.nlp_solver = acados_solver.acados_get_nlp_solver(self.capsule) def solve(self): """ Solve the ocp with current input. """ return acados_solver.acados_solve(self.capsule) def set_new_time_steps(self, new_time_steps): """ Set new time steps before solving. Only reload library without code generation but with new time steps. :param new_time_steps: vector of new time steps for the solver .. note:: This allows for different use-cases: either set a new size of time-steps or a new distribution of the shooting nodes without changing the number, e.g., to reach a different final time. Both cases do not require a new code export and compilation. """ raise NotImplementedError() def get(self, int stage, str field_): """ Get the last solution of the solver: :param stage: integer corresponding to shooting node :param field: string in ['x', 'u', 'z', 'pi', 'lam', 't', 'sl', 'su',] .. note:: regarding lam, t: \n the inequalities are internally organized in the following order: \n [ lbu lbx lg lh lphi ubu ubx ug uh uphi; \n lsbu lsbx lsg lsh lsphi usbu usbx usg ush usphi] .. note:: pi: multipliers for dynamics equality constraints \n lam: multipliers for inequalities \n t: slack variables corresponding to evaluation of all inequalities (at the solution) \n sl: slack variables of soft lower inequality constraints \n su: slack variables of soft upper inequality constraints \n """ out_fields = ['x', 'u', 'z', 'pi', 'lam', 't', 'sl', 'su'] field = field_.encode('utf-8') if field_ not in out_fields: raise Exception('AcadosOcpSolver.get(): {} is an invalid argument.\ \n Possible values are {}. Exiting.'.format(field_, out_fields)) if stage < 0 or stage > self.N: raise Exception('AcadosOcpSolver.get(): stage index must be in [0, N], got: {}.'.format(self.N)) if stage == self.N and field_ == 'pi': raise Exception('AcadosOcpSolver.get(): field {} does not exist at final stage {}.'\ .format(field_, stage)) cdef int dims = acados_solver_common.ocp_nlp_dims_get_from_attr(self.nlp_config, self.nlp_dims, self.nlp_out, stage, field) cdef cnp.ndarray[cnp.float64_t, ndim=1] out = np.zeros((dims,)) acados_solver_common.ocp_nlp_out_get(self.nlp_config, \ self.nlp_dims, self.nlp_out, stage, field, out.data) return out def print_statistics(self): """ prints statistics of previous solver run as a table: - iter: iteration number - res_stat: stationarity residual - res_eq: residual wrt equality constraints (dynamics) - res_ineq: residual wrt inequality constraints (constraints) - res_comp: residual wrt complementarity conditions - qp_stat: status of QP solver - qp_iter: number of QP iterations - qp_res_stat: stationarity residual of the last QP solution - qp_res_eq: residual wrt equality constraints (dynamics) of the last QP solution - qp_res_ineq: residual wrt inequality constraints (constraints) of the last QP solution - qp_res_comp: residual wrt complementarity conditions of the last QP solution """ raise NotImplementedError() def store_iterate(self, filename='', overwrite=False): """ Stores the current iterate of the ocp solver in a json file. :param filename: if not set, use model_name + timestamp + '.json' :param overwrite: if false and filename exists add timestamp to filename """ raise NotImplementedError() def load_iterate(self, filename): """ Loads the iterate stored in json file with filename into the ocp solver. """ raise NotImplementedError() def get_stats(self, field_): """ Get the information of the last solver call. :param field: string in ['statistics', 'time_tot', 'time_lin', 'time_sim', 'time_sim_ad', 'time_sim_la', 'time_qp', 'time_qp_solver_call', 'time_reg', 'sqp_iter'] """ raise NotImplementedError() def get_cost(self): """ Returns the cost value of the current solution. """ # compute cost internally acados_solver_common.ocp_nlp_eval_cost(self.nlp_solver, self.nlp_in, self.nlp_out) # create output cdef double out # call getter acados_solver_common.ocp_nlp_get(self.nlp_config, self.nlp_solver, "cost_value", &out) return out def get_residuals(self): """ Returns an array of the form [res_stat, res_eq, res_ineq, res_comp]. """ raise NotImplementedError() # Note: this function should not be used anymore, better use cost_set, constraints_set def set(self, int stage, str field_, value_): """ Set numerical data inside the solver. :param stage: integer corresponding to shooting node :param field: string in ['x', 'u', 'pi', 'lam', 't', 'p'] .. note:: regarding lam, t: \n the inequalities are internally organized in the following order: \n [ lbu lbx lg lh lphi ubu ubx ug uh uphi; \n lsbu lsbx lsg lsh lsphi usbu usbx usg ush usphi] .. note:: pi: multipliers for dynamics equality constraints \n lam: multipliers for inequalities \n t: slack variables corresponding to evaluation of all inequalities (at the solution) \n sl: slack variables of soft lower inequality constraints \n su: slack variables of soft upper inequality constraints \n """ cost_fields = ['y_ref', 'yref'] constraints_fields = ['lbx', 'ubx', 'lbu', 'ubu'] out_fields = ['x', 'u', 'pi', 'lam', 't', 'z', 'sl', 'su'] field = field_.encode('utf-8') cdef double[::1] value # treat parameters separately if field_ == 'p': value = np.ascontiguousarray(value_, dtype=np.double) assert acados_solver.acados_update_params(self.capsule, stage, &value[0], value.shape[0]) == 0 else: if field_ not in constraints_fields + cost_fields + out_fields: raise Exception("AcadosOcpSolver.set(): {} is not a valid argument.\ \nPossible values are {}. Exiting.".format(field, \ constraints_fields + cost_fields + out_fields + ['p'])) dims = acados_solver_common.ocp_nlp_dims_get_from_attr(self.nlp_config, self.nlp_dims, self.nlp_out, stage, field) if value_.shape[0] != dims: msg = 'AcadosOcpSolver.set(): mismatching dimension for field "{}" '.format(field_) msg += 'with dimension {} (you have {})'.format(dims, value_.shape[0]) raise Exception(msg) value = np.ascontiguousarray(value_, dtype=np.double) if field_ in constraints_fields: acados_solver_common.ocp_nlp_constraints_model_set(self.nlp_config, self.nlp_dims, self.nlp_in, stage, field, &value[0]) elif field_ in cost_fields: acados_solver_common.ocp_nlp_cost_model_set(self.nlp_config, self.nlp_dims, self.nlp_in, stage, field, &value[0]) elif field_ in out_fields: acados_solver_common.ocp_nlp_out_set(self.nlp_config, self.nlp_dims, self.nlp_out, stage, field, &value[0]) def cost_set(self, int stage, str field_, value_): """ Set numerical data in the cost module of the solver. :param stage: integer corresponding to shooting node :param field: string, e.g. 'yref', 'W', 'ext_cost_num_hess' :param value: of appropriate size """ field = field_.encode('utf-8') cdef int dims[2] acados_solver_common.ocp_nlp_cost_dims_get_from_attr(self.nlp_config, \ self.nlp_dims, self.nlp_out, stage, field, &dims[0]) cdef double[::1,:] value value_shape = value_.shape if len(value_shape) == 1: value_shape = (value_shape[0], 0) value = np.asfortranarray(value_[None,:]) elif len(value_shape) == 2: # Get elements in column major order value = np.asfortranarray(value_) if value_shape[0] != dims[0] or value_shape[1] != dims[1]: raise Exception('AcadosOcpSolver.cost_set(): mismatching dimension', \ ' for field "{}" with dimension {} (you have {})'.format( \ field_, tuple(dims), value_shape)) acados_solver_common.ocp_nlp_cost_model_set(self.nlp_config, \ self.nlp_dims, self.nlp_in, stage, field, &value[0][0]) def constraints_set(self, int stage, str field_, value_): """ Set numerical data in the constraint module of the solver. :param stage: integer corresponding to shooting node :param field: string in ['lbx', 'ubx', 'lbu', 'ubu', 'lg', 'ug', 'lh', 'uh', 'uphi', 'C', 'D'] :param value: of appropriate size """ field = field_.encode('utf-8') cdef int dims[2] acados_solver_common.ocp_nlp_constraint_dims_get_from_attr(self.nlp_config, \ self.nlp_dims, self.nlp_out, stage, field, &dims[0]) cdef double[::1,:] value value_shape = value_.shape if len(value_shape) == 1: value_shape = (value_shape[0], 0) value = np.asfortranarray(value_[None,:]) elif len(value_shape) == 2: # Get elements in column major order value = np.asfortranarray(value_) if value_shape[0] != dims[0] or value_shape[1] != dims[1]: raise Exception('AcadosOcpSolver.constraints_set(): mismatching dimension' \ ' for field "{}" with dimension {} (you have {})'.format(field_, tuple(dims), value_shape)) acados_solver_common.ocp_nlp_constraints_model_set(self.nlp_config, \ self.nlp_dims, self.nlp_in, stage, field, &value[0][0]) return def dynamics_get(self, int stage, str field_): """ Get numerical data from the dynamics module of the solver: :param stage: integer corresponding to shooting node :param field: string, e.g. 'A' """ field = field_.encode('utf-8') # get dims cdef int[2] dims acados_solver_common.ocp_nlp_dynamics_dims_get_from_attr(self.nlp_config, self.nlp_dims, self.nlp_out, stage, field, &dims[0]) # create output data out = np.zeros((dims[0], dims[1]), order='F', dtype=np.float64) # call getter acados_solver_common.ocp_nlp_get_at_stage(self.nlp_config, self.nlp_dims, self.nlp_solver, stage, field, out.data) return out def options_set(self, str field_, value_): """ Set options of the solver. :param field: string, e.g. 'print_level', 'rti_phase', 'initialize_t_slacks', 'step_length', 'alpha_min', 'alpha_reduction' :param value: of type int, float """ int_fields = ['print_level', 'rti_phase', 'initialize_t_slacks'] double_fields = ['step_length', 'tol_eq', 'tol_stat', 'tol_ineq', 'tol_comp', 'alpha_min', 'alpha_reduction'] string_fields = ['globalization'] # encode field = field_.encode('utf-8') cdef int int_value cdef double double_value cdef unsigned char[::1] string_value # check field availability and type if field_ in int_fields: if not isinstance(value_, int): raise Exception('solver option {} must be of type int. You have {}.'.format(field_, type(value_))) if field_ == 'rti_phase': if value_ < 0 or value_ > 2: raise Exception('AcadosOcpSolver.solve(): argument \'rti_phase\' can ' 'take only values 0, 1, 2 for SQP-RTI-type solvers') if self.acados_ocp.solver_options.nlp_solver_type != 'SQP_RTI' and value_ > 0: raise Exception('AcadosOcpSolver.solve(): argument \'rti_phase\' can ' 'take only value 0 for SQP-type solvers') int_value = value_ acados_solver_common.ocp_nlp_solver_opts_set(self.nlp_config, self.nlp_opts, field, &int_value) elif field_ in double_fields: if not isinstance(value_, float): raise Exception('solver option {} must be of type float. You have {}.'.format(field_, type(value_))) double_value = value_ acados_solver_common.ocp_nlp_solver_opts_set(self.nlp_config, self.nlp_opts, field, &double_value) elif field_ in string_fields: if not isinstance(value_, bytes): raise Exception('solver option {} must be of type str. You have {}.'.format(field_, type(value_))) string_value = value_.encode('utf-8') acados_solver_common.ocp_nlp_solver_opts_set(self.nlp_config, self.nlp_opts, field, &string_value[0]) raise Exception('AcadosOcpSolver.options_set() does not support field {}.'\ '\n Possible values are {}.'.format(field_, ', '.join(int_fields + double_fields + string_fields))) def __del__(self): if self.solver_created: acados_solver.acados_free(self.capsule) acados_solver.acados_free_capsule(self.capsule)