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))
