

def _add_config(self):
    if self._do_single_runs:
        config_name = ('environment.%s.multiproc' % self.name)
        self._traj.f_add_config(Parameter, config_name, self._multiproc, comment='Whether or not to use multiprocessing.').f_lock()
        if self._multiproc:
            config_name = ('environment.%s.use_pool' % self.name)
            self._traj.f_add_config(Parameter, config_name, self._use_pool, comment='Whether to use a pool of processes or spawning individual processes for each run.').f_lock()
            config_name = ('environment.%s.use_scoop' % self.name)
            self._traj.f_add_config(Parameter, config_name, self._use_scoop, comment='Whether to use scoop to launch single runs').f_lock()
            if (self._niceness is not None):
                config_name = ('environment.%s.niceness' % self.name)
                self._traj.f_add_config(Parameter, config_name, self._niceness, comment='Niceness value of child processes.').f_lock()
            if self._use_pool:
                config_name = ('environment.%s.freeze_input' % self.name)
                self._traj.f_add_config(Parameter, config_name, self._freeze_input, comment='If inputs to each run are static and are not mutated during each run, can speed up pool running.').f_lock()
            elif self._use_scoop:
                pass
            else:
                config_name = ('environment.%s.cpu_cap' % self.name)
                self._traj.f_add_config(Parameter, config_name, self._cpu_cap, comment='Maximum cpu usage beyond which no new processes are spawned.').f_lock()
                config_name = ('environment.%s.memory_cap' % self.name)
                self._traj.f_add_config(Parameter, config_name, self._memory_cap, comment='Tuple, first entry: Maximum RAM usage beyond which no new processes are spawned; second entry: Estimated usage per process in MB. 0 if not estimated.').f_lock()
                config_name = ('environment.%s.swap_cap' % self.name)
                self._traj.f_add_config(Parameter, config_name, self._swap_cap, comment='Maximum Swap memory usage beyond which no new processes are spawned').f_lock()
                config_name = ('environment.%s.immediate_postprocessing' % self.name)
                self._traj.f_add_config(Parameter, config_name, self._immediate_postproc, comment='Whether to use immediate postprocessing.').f_lock()
            config_name = ('environment.%s.ncores' % self.name)
            self._traj.f_add_config(Parameter, config_name, self._ncores, comment='Number of processors in case of multiprocessing').f_lock()
            config_name = ('environment.%s.wrap_mode' % self.name)
            self._traj.f_add_config(Parameter, config_name, self._wrap_mode, comment='Multiprocessing mode (if multiproc), i.e. whether to use QUEUE or LOCK or NONE for thread/process safe storing').f_lock()
            if ((self._wrap_mode == pypetconstants.WRAP_MODE_QUEUE) or (self._wrap_mode == pypetconstants.WRAP_MODE_PIPE)):
                config_name = ('environment.%s.queue_maxsize' % self.name)
                self._traj.f_add_config(Parameter, config_name, self._queue_maxsize, comment='Maximum size of Storage Queue/Pipe in case of multiprocessing and QUEUE/PIPE wrapping').f_lock()
            if (self._wrap_mode == pypetconstants.WRAP_MODE_NETLOCK):
                config_name = ('environment.%s.url' % self.name)
                self._traj.f_add_config(Parameter, config_name, self._url, comment='URL of lock distribution server, including protocol and port.').f_lock()
            if ((self._wrap_mode == pypetconstants.WRAP_MODE_NETLOCK) or self._use_scoop):
                config_name = ('environment.%s.timeout' % self.name)
                timeout = self._timeout
                if (timeout is None):
                    timeout = (- 1.0)
                self._traj.f_add_config(Parameter, config_name, timeout, comment='Timout for scoop and NETLOCK, -1.0 means no timeout.').f_lock()
            if (self._gc_interval and ((self._wrap_mode == pypetconstants.WRAP_MODE_LOCAL) or (self._wrap_mode == pypetconstants.WRAP_MODE_QUEUE) or (self._wrap_mode == pypetconstants.WRAP_MODE_PIPE))):
                config_name = ('environment.%s.gc_interval' % self.name)
                self._traj.f_add_config(Parameter, config_name, self._gc_interval, comment='Intervals with which ``gc.collect()`` is called.').f_lock()
        config_name = ('environment.%s.clean_up_runs' % self._name)
        self._traj.f_add_config(Parameter, config_name, self._clean_up_runs, comment='Whether or not results should be removed after the completion of a single run. You are not advised to set this to `False`. Only do it if you know what you are doing.').f_lock()
        config_name = ('environment.%s.resumable' % self._name)
        self._traj.f_add_config(Parameter, config_name, self._resumable, comment='Whether or not resume files should be created. If yes, everything is handled by `dill`.').f_lock()
        config_name = ('environment.%s.graceful_exit' % self._name)
        self._traj.f_add_config(Parameter, config_name, self._graceful_exit, comment='Whether or not to allow graceful handling of `SIGINT` (`CTRL+C`).').f_lock()
    config_name = ('environment.%s.trajectory.name' % self.name)
    self._traj.f_add_config(Parameter, config_name, self.trajectory.v_name, comment='Name of trajectory').f_lock()
    config_name = ('environment.%s.trajectory.timestamp' % self.name)
    self._traj.f_add_config(Parameter, config_name, self.trajectory.v_timestamp, comment='Timestamp of trajectory').f_lock()
    config_name = ('environment.%s.timestamp' % self.name)
    self._traj.f_add_config(Parameter, config_name, self.timestamp, comment='Timestamp of environment creation').f_lock()
    config_name = ('environment.%s.hexsha' % self.name)
    self._traj.f_add_config(Parameter, config_name, self.hexsha, comment='SHA-1 identifier of the environment').f_lock()
    config_name = ('environment.%s.automatic_storing' % self.name)
    if (not self._traj.f_contains(('config.' + config_name))):
        self._traj.f_add_config(Parameter, config_name, self._automatic_storing, comment='If trajectory should be stored automatically in the end.').f_lock()
    try:
        config_name = ('environment.%s.script' % self.name)
        self._traj.f_add_config(Parameter, config_name, main.__file__, comment='Name of the executed main script').f_lock()
    except AttributeError:
        pass
    for (package_name, version) in pypetconstants.VERSIONS_TO_STORE.items():
        config_name = ('environment.%s.versions.%s' % (self.name, package_name))
        self._traj.f_add_config(Parameter, config_name, version, comment='Particular version of a package or distribution used during experiment. N/A if package could not be imported.').f_lock()
    version._traj.config.environment.v_comment = 'Settings for the different environments used to run the experiments'

dataset/ETHPy150Open SmokinCaterpillar/pypet/pypet/environment.py Environment._add_config/VarMisuse@1067/2252 `self`->`version`