def log_setup(self) -> None: """ Create the folders to store data. """ run_name = self.__run_name if run_name is None: run_name = "c1_" + self.fid_func.__name__ + "_" + self.algorithm.__name__ self.logdir = log_setup(self.__dir_path, run_name) self.logname = "open_loop.c3log" if isinstance(self.exp.created_by, str): shutil.copy2(self.exp.created_by, self.logdir) if isinstance(self.created_by, str): shutil.copy2(self.created_by, self.logdir)
def log_setup(self, dir_path, run_name): """ Create the folders to store data. Parameters ---------- dir_path : str Filepath run_name : str User specified name for the run """ self.dir_path = os.path.abspath(dir_path) if run_name is None: run_name = self.eval_func.__name__ + self.algorithm.__name__ self.logdir = log_setup(self.dir_path, run_name) self.logname = 'calibration.log'
def log_setup(self, dir_path, run_name): """ Create the folders to store data. Parameters ---------- dir_path : str Filepath run_name : str User specified name for the run """ self.dir_path = os.path.abspath(dir_path) if run_name is None: run_name = ('c1_' + self.fid_func.__name__ + '_' + self.algorithm.__name__) self.logdir = log_setup(self.dir_path, run_name) self.logname = 'open_loop.log'
def log_setup(self) -> None: """ Create the folders to store data. Parameters ---------- dir_path : str Filepath run_name : str User specified name for the run """ run_name = self.__run_name if run_name is None: run_name = "-".join([ self.algorithm.__name__, self.sampling.__name__, self.fom.__name__ ]) self.logdir = log_setup(self.__dir_path, run_name)
def log_setup(self, dir_path, run_name): """ Create the folders to store data. Parameters ---------- dir_path : str Filepath run_name : str User specified name for the run """ self.dir_path = os.path.abspath(dir_path) if run_name is None: run_name = self.algorithm.__name__ + '-' \ + self.sampling.__name__ + '-' \ + self.fom.__name__ self.logdir = log_setup(self.dir_path, run_name) self.logname = 'model_learn.log'
def log_setup(self) -> None: """ Create the folders to store data. Parameters ---------- dir_path : str Filepath run_name : str User specified name for the run """ dir_path = os.path.abspath(self.__dir_path) run_name = self.__run_name if run_name is None: run_name = self.eval_func.__name__ + self.algorithm.__name__ self.logdir = log_setup(dir_path, run_name) self.logname = "calibration.log" shutil.copy2(self.eval_func, self.logdir) real_log = os.path.join(self.logdir, "real_model.hjson") self.exp_right.pmap.model.write_config(real_log)
def log_setup(self): """ Create the folders to store data. Parameters ---------- dir_path : str Filepath run_name : str User specified name for the run """ dir_path = os.path.abspath(self.__dir_path) run_name = self.__run_name if run_name is None: run_name = "-".join([ self.algorithm.__name__, self.sampling.__name__, self.fom.__name__ ]) self.logdir = log_setup(dir_path, run_name) self.logname = "model_learn.log" shutil.copy2(self.__real_model_folder, self.logdir)
def log_setup(self) -> None: """ Create the folders to store data. Parameters ---------- dir_path : str Filepath run_name : str User specified name for the run """ dir_path = os.path.abspath(self.__dir_path) run_name = self.__run_name if run_name is None: run_name = "c1_" + self.fid_func.__name__ + "_" + self.algorithm.__name__ self.logdir = log_setup(dir_path, run_name) self.logname = "open_loop.log" if isinstance(self.exp.created_by, str): shutil.copy2(self.exp.created_by, self.logdir) if isinstance(self.created_by, str): shutil.copy2(self.created_by, self.logdir)
def log_setup(self) -> None: """ Create the folders to store data. Parameters ---------- dir_path : str Filepath run_name : str User specified name for the run """ run_name = self.__run_name if run_name is None: run_name = self.eval_func.__name__ + self.algorithm.__name__ self.logdir = log_setup(self.__dir_path, run_name) self.logname = "calibration.log" # We create a copy of the source code of the evaluation function in the log with open(os.path.join(self.logdir, "eval_func.py"), "w") as eval_source: eval_source.write(inspect.getsource(self.eval_func))