code string | signature string | docstring string | loss_without_docstring float64 | loss_with_docstring float64 | factor float64 |
|---|---|---|---|---|---|
system = self.system
pos = []
names = []
pairs = ''
size = jac.size
diag = jac[0:size[0] ** 2:size[0] + 1]
for idx in range(size[0]):
if abs(diag[idx]) <= 1e-8:
pos.append(idx)
for idx in pos:
names.append(system.varname.__dict__[name][idx])
if len(names) > 0:
for i, j in zip(pos, names):
pairs += '{0}: {1}\n'.format(i, j)
logger.debug('Jacobian diagonal check:')
logger.debug(pairs) | def check_diag(self, jac, name) | Check matrix ``jac`` for diagonal elements that equals 0 | 3.840814 | 3.618305 | 1.061495 |
_, _, tb = sys.exc_info()
while tb.tb_next:
tb = tb.tb_next
f = tb.tb_frame
lineno = tb.tb_lineno
co = f.f_code
filefullpath = co.co_filename
filename = os.path.basename(filefullpath)
name = co.co_name
linecache.checkcache(filefullpath)
line = linecache.getline(filefullpath, lineno, f.f_globals)
if line:
line = line.strip()
else:
line = None
return filefullpath, filename, lineno, name, line | def get_exception_source() | Returns full file path, file name, line number, function name, and line contents
causing the last exception. | 1.798808 | 1.702239 | 1.05673 |
# Function taken from Python 3.6 QueueHandler
# The format operation gets traceback text into record.exc_text
# (if there's exception data), and also puts the message into
# record.message. We can then use this to replace the original
# msg + args, as these might be unpickleable. We also zap the
# exc_info attribute, as it's no longer needed and, if not None,
# will typically not be pickleable.
self.format(record)
record.msg = record.message
record.args = None
record.exc_info = None
return record | def prepare(self, record) | Prepares a record for queuing. The object returned by this method is
enqueued.
The base implementation formats the record to merge the message
and arguments, and removes unpickleable items from the record
in-place.
You might want to override this method if you want to convert
the record to a dict or JSON string, or send a modified copy
of the record while leaving the original intact. | 3.805721 | 4.265472 | 0.892216 |
try:
self._callback(self.prepare(record))
except Exception:
self.handleError(record) | def emit(self, record) | Send a LogRecord to the callback function, after preparing it
for serialization. | 4.681175 | 4.057303 | 1.153765 |
if status_code is not None:
self._service_status = status_code
self._utilization.update_status(status_code)
# Check whether IDLE status should be delayed
if self._service_status == CommonService.SERVICE_STATUS_IDLE:
if self._status_idle_since is None:
self._status_idle_since = time.time()
return
elif self._status_idle_since + 0.5 > time.time():
return
else:
self._status_idle_since = None
new_status = self._service_status != self._service_status_announced
if (
(
new_status
or self._status_last_broadcast + self._status_interval <= time.time()
)
and self._transport
and self._transport.is_connected()
):
self._service_status_announced = self._service_status
self._transport.broadcast_status(self.get_status())
self._status_last_broadcast = time.time() | def update_status(self, status_code=None) | Update the service status kept inside the frontend (_service_status).
The status is broadcast over the network immediately. If the status
changes to IDLE then this message is delayed. The IDLE status is only
broadcast if it is held for over 0.5 seconds.
When the status does not change it is still broadcast every
_status_interval seconds.
:param status_code: Either an integer describing the service status
(see workflows.services.common_service), or None
if the status is unchanged. | 3.103184 | 2.600452 | 1.193325 |
self.log.debug("Entered main loop")
while not self.shutdown:
# If no service is running slow down the main loop
if not self._pipe_service:
time.sleep(0.3)
self.update_status()
# While a service is running, check for incoming messages from that service
if self._pipe_service and self._pipe_service.poll(1):
try:
message = self._pipe_service.recv()
if isinstance(message, dict) and "band" in message:
# only dictionaries with 'band' entry are valid messages
try:
handler = getattr(self, "parse_band_" + message["band"])
except AttributeError:
handler = None
self.log.warning("Unknown band %s", str(message["band"]))
if handler:
# try:
handler(message)
# except Exception:
# print('Uh oh. What to do.')
else:
self.log.warning("Invalid message received %s", str(message))
except EOFError:
# Service has gone away
error_message = False
if self._service_status == CommonService.SERVICE_STATUS_END:
self.log.info("Service terminated")
elif self._service_status == CommonService.SERVICE_STATUS_ERROR:
error_message = "Service terminated with error code"
elif self._service_status in (
CommonService.SERVICE_STATUS_NONE,
CommonService.SERVICE_STATUS_NEW,
CommonService.SERVICE_STATUS_STARTING,
):
error_message = (
"Service may have died unexpectedly in "
+ "initialization (last known status: %s)"
% CommonService.human_readable_state.get(
self._service_status, self._service_status
)
)
else:
error_message = (
"Service may have died unexpectedly"
" (last known status: %s)"
% CommonService.human_readable_state.get(
self._service_status, self._service_status
)
)
if error_message:
self.log.error(error_message)
self._terminate_service()
if self.restart_service:
self.exponential_backoff()
else:
self.shutdown = True
if error_message:
raise workflows.Error(error_message)
with self.__lock:
if (
self._service is None
and self.restart_service
and self._service_factory
):
self.update_status(status_code=CommonService.SERVICE_STATUS_NEW)
self.switch_service()
# Check that the transport is alive
if not self._transport.is_connected():
self._terminate_service()
raise workflows.Error("Lost transport layer connection")
self.log.debug("Left main loop")
self.update_status(status_code=CommonService.SERVICE_STATUS_TEARDOWN)
self._terminate_service()
self.log.debug("Terminating.") | def run(self) | The main loop of the frontend. Here incoming messages from the service
are processed and forwarded to the corresponding callback methods. | 3.421334 | 3.318307 | 1.031048 |
if self._pipe_commands:
self._pipe_commands.send(command)
else:
if self.shutdown:
# Stop delivering messages in shutdown.
self.log.info(
"During shutdown no command queue pipe found for command\n%s",
str(command),
)
else:
self.log.error(
"No command queue pipe found for command\n%s", str(command)
) | def send_command(self, command) | Send command to service via the command queue. | 5.774755 | 5.108583 | 1.130402 |
if not isinstance(message, dict):
return
relevant = False
if "host" in message: # Filter by host
if message["host"] != self.__hostid:
return
relevant = True
if "service" in message: # Filter by service
if message["service"] != self._service_class_name:
return
relevant = True
if not relevant: # Ignore message unless at least one filter matches
return
if message.get("command"):
self.log.info(
"Received command '%s' via transport layer", message["command"]
)
if message["command"] == "shutdown":
self.shutdown = True
else:
self.log.warning("Received invalid transport command message") | def process_transport_command(self, header, message) | Parse a command coming in through the transport command subscription | 3.682559 | 3.569442 | 1.03169 |
if "payload" in message and hasattr(message["payload"], "name"):
record = message["payload"]
for k in dir(record):
if k.startswith("workflows_exc_"):
setattr(record, k[14:], getattr(record, k))
delattr(record, k)
for k, v in self.get_status().items():
setattr(record, "workflows_" + k, v)
logging.getLogger(record.name).handle(record)
else:
self.log.warning(
"Received broken record on log band\n" + "Message: %s\nRecord: %s",
str(message),
str(
hasattr(message.get("payload"), "__dict__")
and message["payload"].__dict__
),
) | def parse_band_log(self, message) | Process incoming logging messages from the service. | 3.953272 | 3.730031 | 1.05985 |
self.log.debug("Service requests termination")
self._terminate_service()
if not self.restart_service:
self.shutdown = True | def parse_band_request_termination(self, message) | Service declares it should be terminated. | 9.052119 | 6.887255 | 1.314329 |
if message.get("name"):
self._service_name = message["name"]
else:
self.log.warning(
"Received broken record on set_name band\nMessage: %s", str(message)
) | def parse_band_set_name(self, message) | Process incoming message indicating service name change. | 8.013097 | 6.413738 | 1.249364 |
self.log.debug("Status update: " + str(message))
self.update_status(status_code=message["statuscode"]) | def parse_band_status_update(self, message) | Process incoming status updates from the service. | 5.797485 | 5.016924 | 1.155585 |
return {
"host": self.__hostid,
"status": self._service_status_announced,
"statustext": CommonService.human_readable_state.get(
self._service_status_announced
),
"service": self._service_name,
"serviceclass": self._service_class_name,
"utilization": self._utilization.report(),
"workflows": workflows.version(),
} | def get_status(self) | Returns a dictionary containing all relevant status information to be
broadcast across the network. | 7.544106 | 6.873206 | 1.097611 |
last_service_switch = self._service_starttime
if not last_service_switch:
return
time_since_last_switch = time.time() - last_service_switch
if not self._service_rapidstarts:
self._service_rapidstarts = 0
minimum_wait = 0.1 * (2 ** self._service_rapidstarts)
minimum_wait = min(5, minimum_wait)
if time_since_last_switch > 10:
self._service_rapidstarts = 0
return
self._service_rapidstarts += 1
self.log.debug("Slowing down service starts (%.1f seconds)", minimum_wait)
time.sleep(minimum_wait) | def exponential_backoff(self) | A function that keeps waiting longer and longer the more rapidly it is called.
It can be used to increasingly slow down service starts when they keep failing. | 3.793165 | 3.375204 | 1.123833 |
if new_service:
self._service_factory = new_service
with self.__lock:
# Terminate existing service if necessary
if self._service is not None:
self._terminate_service()
# Find service class if necessary
if isinstance(self._service_factory, basestring):
self._service_factory = workflows.services.lookup(self._service_factory)
if not self._service_factory:
return False
# Set up new service object
service_instance = self._service_factory(
environment=self._service_environment
)
# Set up pipes and connect service object
svc_commands, self._pipe_commands = multiprocessing.Pipe(False)
self._pipe_service, svc_tofrontend = multiprocessing.Pipe(False)
service_instance.connect(commands=svc_commands, frontend=svc_tofrontend)
# Set up transport layer for new service
service_instance.transport = self._transport_factory()
# Start new service in a separate process
self._service = multiprocessing.Process(
target=service_instance.start,
args=(),
kwargs={"verbose_log": self._verbose_service},
)
self._service_name = service_instance.get_name()
self._service_class_name = service_instance.__class__.__name__
self._service.daemon = True
self._service.name = "workflows-service"
self._service.start()
self._service_starttime = time.time()
# Starting the process copies all file descriptors.
# At this point (and no sooner!) the passed pipe objects must be closed
# in this process here.
svc_commands.close()
svc_tofrontend.close()
self.log.info("Started service: %s", self._service_name)
return True | def switch_service(self, new_service=None) | Start a new service in a subprocess.
:param new_service: Either a service name or a service class. If not set,
start up a new instance of the previous class
:return: True on success, False on failure. | 3.968127 | 3.952949 | 1.00384 |
with self.__lock:
if self._service:
self._service.terminate()
if self._pipe_commands:
self._pipe_commands.close()
if self._pipe_service:
self._pipe_service.close()
self._pipe_commands = None
self._pipe_service = None
self._service_class_name = None
self._service_name = None
if self._service_status != CommonService.SERVICE_STATUS_TEARDOWN:
self.update_status(status_code=CommonService.SERVICE_STATUS_END)
if self._service:
self._service.join() # must wait for process to be actually destroyed
self._service = None | def _terminate_service(self) | Force termination of running service.
Disconnect queues, end queue feeder threads.
Wait for service process to clear, drop all references. | 3.714316 | 3.462612 | 1.072692 |
if self.sparselib == 'umfpack':
return umfpack.symbolic(A)
elif self.sparselib == 'klu':
return klu.symbolic(A) | def symbolic(self, A) | Return the symbolic factorization of sparse matrix ``A``
Parameters
----------
sparselib
Library name in ``umfpack`` and ``klu``
A
Sparse matrix
Returns
symbolic factorization
------- | 4.01716 | 2.44325 | 1.644187 |
if self.sparselib == 'umfpack':
return umfpack.numeric(A, F)
elif self.sparselib == 'klu':
return klu.numeric(A, F) | def numeric(self, A, F) | Return the numeric factorization of sparse matrix ``A`` using symbolic factorization ``F``
Parameters
----------
A
Sparse matrix
F
Symbolic factorization
Returns
-------
N
Numeric factorization of ``A`` | 4.109475 | 4.670392 | 0.879899 |
if self.sparselib == 'umfpack':
umfpack.solve(A, N, b)
elif self.sparselib == 'klu':
klu.solve(A, F, N, b) | def solve(self, A, F, N, b) | Solve linear system ``Ax = b`` using numeric factorization ``N`` and symbolic factorization ``F``.
Store the solution in ``b``.
Parameters
----------
A
Sparse matrix
F
Symbolic factorization
N
Numeric factorization
b
RHS of the equation
Returns
-------
None | 4.652089 | 4.839779 | 0.961219 |
if self.sparselib == 'umfpack':
return umfpack.linsolve(A, b)
elif self.sparselib == 'klu':
return klu.linsolve(A, b) | def linsolve(self, A, b) | Solve linear equation set ``Ax = b`` and store the solutions in ``b``.
Parameters
----------
A
Sparse matrix
b
RHS of the equation
Returns
-------
None | 3.531707 | 4.383871 | 0.805614 |
# Bus Pi
if not self.n:
return
m = self.system.dae.m
xy_idx = range(m, self.n + m)
self.system.varname.append(
listname='unamey',
xy_idx=xy_idx,
var_name='P',
element_name=self.name)
self.system.varname.append(
listname='fnamey',
xy_idx=xy_idx,
var_name='P',
element_name=self.name)
# Bus Qi
xy_idx = range(m + self.n, m + 2 * self.n)
self.system.varname.append(
listname='unamey',
xy_idx=xy_idx,
var_name='Q',
element_name=self.name)
self.system.varname.append(
listname='fnamey',
xy_idx=xy_idx,
var_name='Q',
element_name=self.name) | def _varname_inj(self) | Customize varname for bus injections | 2.769399 | 2.610382 | 1.060917 |
if not self.system.pflow.config.flatstart:
dae.y[self.a] = self.angle + 1e-10 * uniform(self.n)
dae.y[self.v] = self.voltage
else:
dae.y[self.a] = matrix(0.0,
(self.n, 1), 'd') + 1e-10 * uniform(self.n)
dae.y[self.v] = matrix(1.0, (self.n, 1), 'd') | def init0(self, dae) | Set bus Va and Vm initial values | 3.822448 | 3.505894 | 1.090292 |
if (not self.islanded_buses) and (not self.island_sets):
return
a, v = list(), list()
# for islanded areas without a slack bus
# TODO: fix for islanded sets without sw
# for island in self.island_sets:
# nosw = 1
# for item in self.system.SW.bus:
# if self.uid[item] in island:
# nosw = 0
# break
# if nosw:
# self.islanded_buses += island
# self.island_sets.remove(island)
a = self.islanded_buses
v = [self.n + item for item in a]
dae.g[a] = 0
dae.g[v] = 0 | def gisland(self, dae) | Reset g(x) for islanded buses and areas | 5.491147 | 4.363315 | 1.258481 |
if self.system.Bus.islanded_buses:
a = self.system.Bus.islanded_buses
v = [self.system.Bus.n + item for item in a]
dae.set_jac(Gy, 1e-6, a, a)
dae.set_jac(Gy, 1e-6, v, v) | def gyisland(self, dae) | Reset gy(x) for islanded buses and areas | 5.918261 | 4.416303 | 1.340094 |
if not (self.islanded_buses and self.island_sets):
return
a, v = list(), list()
# for islanded areas without a slack bus
for island in self.island_sets:
nosw = 1
for item in self.system.SW.bus:
if self.uid[item] in island:
nosw = 0
break
if nosw:
self.islanded_buses += island
self.island_sets.remove(island)
a = self.islanded_buses
v = [self.n + item for item in a]
dae.g[a] = 0
dae.g[v] = 0 | def gisland(self, dae) | Reset g(x) for islanded buses and areas | 6.00981 | 4.653182 | 1.291548 |
if not hasattr(get_known_transports, "cache"):
setattr(
get_known_transports,
"cache",
{
e.name: e.load()
for e in pkg_resources.iter_entry_points("workflows.transport")
},
)
return get_known_transports.cache.copy() | def get_known_transports() | Return a dictionary of all known transport mechanisms. | 3.032811 | 2.752984 | 1.101645 |
ws = [0] * self.n
for i in range(self.n):
q = ceil(t / self.dt[i])
q_prev = 0 if q == 0 else q - 1
r = t % self.dt[i]
r = 0 if abs(r) < 1e-6 else r
if r == 0:
ws[i] = self.speed[i][q]
else:
t1 = self.time[i][q_prev]
s1 = self.speed[i][q_prev]
s2 = self.speed[i][q]
ws[i] = s1 + (t - t1) * (s2 - s1) / self.dt[i]
return matrix(ws) | def windspeed(self, t) | Return the wind speed list at time `t` | 2.754999 | 2.677233 | 1.029047 |
self.vf0 = vf
self.system.dae.y[self.vf] = matrix(vf) | def set_vf0(self, vf) | set value for self.vf0 and dae.y[self.vf] | 12.209021 | 4.794827 | 2.54629 |
self.devman.sort_device()
self.call.setup()
self.model_setup()
self.xy_addr0()
self.dae.setup()
self.to_sysbase()
return self | def setup(self) | Set up the power system object by executing the following workflow:
* Sort the loaded models to meet the initialization sequence
* Create call strings for routines
* Call the ``setup`` function of the loaded models
* Assign addresses for the loaded models
* Call ``dae.setup`` to assign memory for the numerical dae structure
* Convert model parameters to the system base
Returns
-------
PowerSystem
The instance of the PowerSystem | 26.870178 | 12.049016 | 2.230072 |
if self.config.base:
for item in self.devman.devices:
self.__dict__[item].data_to_sys_base() | def to_sysbase(self) | Convert model parameters to system base. This function calls the
``data_to_sys_base`` function of the loaded models.
Returns
-------
None | 14.215375 | 13.433491 | 1.058204 |
if self.config.base:
for item in self.devman.devices:
self.__dict__[item].data_to_elem_base() | def to_elembase(self) | Convert parameters back to element base. This function calls the
```data_to_elem_base``` function.
Returns
-------
None | 16.015846 | 12.715166 | 1.259586 |
if not hasattr(self, name):
self.__dict__[name] = Group(self, name)
self.loaded_groups.append(name) | def group_add(self, name='Ungrouped') | Dynamically add a group instance to the system if not exist.
Parameters
----------
name : str, optional ('Ungrouped' as default)
Name of the group
Returns
-------
None | 3.788669 | 4.381001 | 0.864795 |
# non-JIT models
for file, pair in non_jits.items():
for cls, name in pair.items():
themodel = importlib.import_module('andes.models.' + file)
theclass = getattr(themodel, cls)
self.__dict__[name] = theclass(self, name)
group = self.__dict__[name]._group
self.group_add(group)
self.__dict__[group].register_model(name)
self.devman.register_device(name)
# import JIT models
for file, pair in jits.items():
for cls, name in pair.items():
self.__dict__[name] = JIT(self, file, cls, name) | def model_import(self) | Import and instantiate the non-JIT models and the JIT models.
Models defined in ``jits`` and ``non_jits`` in ``models/__init__.py``
will be imported and instantiated accordingly.
Returns
-------
None | 4.556047 | 4.114913 | 1.107204 |
for r in routines.__all__:
file = importlib.import_module('.' + r.lower(), 'andes.routines')
self.__dict__[r.lower()] = getattr(file, r)(self) | def routine_import(self) | Dynamically import routines as defined in ``routines/__init__.py``.
The command-line argument ``--routine`` is defined in ``__cli__`` in
each routine file. A routine instance will be stored in the system
instance with the name being all lower case.
For example, a routine for power flow study should be defined in
``routines/pflow.py`` where ``__cli__ = 'pflow'``. The class name
for the routine should be ``Pflow``. The routine instance will be
saved to ``PowerSystem.pflow``.
Returns
-------
None | 5.07816 | 5.432455 | 0.934782 |
for device in self.devman.devices:
if self.__dict__[device].n:
try:
self.__dict__[device].setup()
except Exception as e:
raise e | def model_setup(self) | Call the ``setup`` function of the loaded models. This function is
to be called after parsing all the data files during the system set up.
Returns
-------
None | 6.645863 | 7.352543 | 0.903886 |
for device, pflow in zip(self.devman.devices, self.call.pflow):
if pflow:
self.__dict__[device]._addr()
self.__dict__[device]._intf_network()
self.__dict__[device]._intf_ctrl()
self.varname.resize()
for device, pflow in zip(self.devman.devices, self.call.pflow):
if pflow:
self.__dict__[device]._varname() | def xy_addr0(self) | Assign indicies and variable names for variables used in power flow
For each loaded model with the ``pflow`` flag as ``True``, the following
functions are called sequentially:
* ``_addr()``
* ``_intf_network()``
* ``_intf_ctrl()``
After resizing the ``varname`` instance, variable names from models
are stored by calling ``_varname()``
Returns
-------
None | 5.765868 | 3.191754 | 1.806489 |
stagens = []
for device, stagen in zip(self.devman.devices, self.call.stagen):
if stagen:
stagens.append(device)
for gen in idx:
for stagen in stagens:
if gen in self.__dict__[stagen].uid.keys():
self.__dict__[stagen].disable_gen(gen) | def rmgen(self, idx) | Remove the static generators if their dynamic models exist
Parameters
----------
idx : list
A list of static generator idx
Returns
-------
None | 6.252291 | 6.254881 | 0.999586 |
ret = []
for model in self.__dict__['Event'].all_models:
if self.__dict__[model].is_time(sim_time):
ret.append(model)
if self.Breaker.is_time(sim_time):
ret.append('Breaker')
return ret | def check_event(self, sim_time) | Check for event occurrance for``Event`` group models at ``sim_time``
Parameters
----------
sim_time : float
The current simulation time
Returns
-------
list
A list of model names who report (an) event(s) at ``sim_time`` | 5.194508 | 4.49989 | 1.154363 |
times = []
times.extend(self.Breaker.get_times())
for model in self.__dict__['Event'].all_models:
times.extend(self.__dict__[model].get_times())
if times:
times = sorted(list(set(times)))
return times | def get_event_times(self) | Return event times of Fault, Breaker and other timed events
Returns
-------
list
A sorted list of event times | 5.840324 | 5.747899 | 1.01608 |
if conf_path is None:
return
conf = configparser.ConfigParser()
conf.read(conf_path)
self.config.load_config(conf)
for r in routines.__all__:
self.__dict__[r.lower()].config.load_config(conf)
logger.debug('Loaded config file from {}.'.format(conf_path)) | def load_config(self, conf_path) | Load config from an ``andes.conf`` file.
This function creates a ``configparser.ConfigParser`` object to read
the specified conf file and calls the ``load_config`` function of the
config instances of the system and the routines.
Parameters
----------
conf_path : None or str
Path to the Andes config file. If ``None``, the function body
will not run.
Returns
-------
None | 4.210881 | 3.538634 | 1.189974 |
if os.path.isfile(file_path):
logger.debug('File {} alreay exist. Overwrite? [y/N]'.format(file_path))
choice = input('File {} alreay exist. Overwrite? [y/N]'.format(file_path)).lower()
if len(choice) == 0 or choice[0] != 'y':
logger.info('File not overwritten.')
return
conf = self.config.dump_conf()
for r in routines.__all__:
conf = self.__dict__[r.lower()].config.dump_conf(conf)
with open(file_path, 'w') as f:
conf.write(f)
logger.info('Config written to {}'.format(file_path)) | def dump_config(self, file_path) | Dump system and routine configurations to an rc-formatted file.
Parameters
----------
file_path : str
path to the configuration file. The user will be prompted if the
file already exists.
Returns
-------
None | 3.102417 | 3.195565 | 0.970851 |
if not hasattr(self, 'Line'):
logger.error('<Line> device not found.')
return
self.Line.connectivity(self.Bus)
if show_info is True:
if len(self.Bus.islanded_buses) == 0 and len(
self.Bus.island_sets) == 0:
logger.debug('System is interconnected.')
else:
logger.info(
'System contains {:d} islands and {:d} islanded buses.'.
format(
len(self.Bus.island_sets),
len(self.Bus.islanded_buses)))
nosw_island = [] # no slack bus island
msw_island = [] # multiple slack bus island
for idx, island in enumerate(self.Bus.island_sets):
nosw = 1
for item in self.SW.bus:
if self.Bus.uid[item] in island:
nosw -= 1
if nosw == 1:
nosw_island.append(idx)
elif nosw < 0:
msw_island.append(idx)
if nosw_island:
logger.warning(
'Slack bus is not defined for {:g} island(s).'.format(
len(nosw_island)))
if msw_island:
logger.warning(
'Multiple slack buses are defined for {:g} island(s).'.
format(len(nosw_island)))
if (not nosw_island) and (not msw_island):
logger.debug(
'Each island has a slack bus correctly defined.') | def check_islands(self, show_info=False) | Check the connectivity for the ac system
Parameters
----------
show_info : bool
Show information when the system has islands. To be used when
initializing power flow.
Returns
-------
None | 3.203117 | 3.055882 | 1.048181 |
if self.pflow.solved is False:
logger.error('Power flow not solved when getting bus data.')
return tuple([False] * 8)
idx = self.Bus.idx
names = self.Bus.name
Vm = [self.dae.y[x] for x in self.Bus.v]
if self.pflow.config.usedegree:
Va = [self.dae.y[x] * rad2deg for x in self.Bus.a]
else:
Va = [self.dae.y[x] for x in self.Bus.a]
Pg = [self.Bus.Pg[x] for x in range(self.Bus.n)]
Qg = [self.Bus.Qg[x] for x in range(self.Bus.n)]
Pl = [self.Bus.Pl[x] for x in range(self.Bus.n)]
Ql = [self.Bus.Ql[x] for x in range(self.Bus.n)]
if sort_names:
ret = (list(x) for x in zip(*sorted(
zip(idx, names, Vm, Va, Pg, Qg, Pl, Ql), key=itemgetter(0))))
else:
ret = idx, names, Vm, Va, Pg, Qg, Pl, Ql
return ret | def get_busdata(self, sort_names=False) | get ac bus data from solved power flow | 2.576409 | 2.402849 | 1.072231 |
if not self.Node.n:
return
if not self.pflow.solved:
logger.error('Power flow not solved when getting bus data.')
return tuple([False] * 7)
idx = self.Node.idx
names = self.Node.name
V = [self.dae.y[x] for x in self.Node.v]
if sort_names:
ret = (list(x)
for x in zip(*sorted(zip(idx, names, V), key=itemgetter(0))))
else:
ret = idx, names, V
return ret | def get_nodedata(self, sort_names=False) | get dc node data from solved power flow | 5.939427 | 4.916299 | 1.208109 |
if not self.pflow.solved:
logger.error('Power flow not solved when getting line data.')
return tuple([False] * 7)
idx = self.Line.idx
fr = self.Line.bus1
to = self.Line.bus2
Sloss = self.Line.S1 + self.Line.S2
Pfr = list(self.Line.S1.real())
Qfr = list(self.Line.S1.imag())
Pto = list(self.Line.S2.real())
Qto = list(self.Line.S2.imag())
Ploss = list(Sloss.real())
Qloss = list(Sloss.imag())
if sort_names:
ret = (list(x) for x in zip(*sorted(
zip(idx, fr, to, Pfr, Qfr, Pto, Qto, Ploss, Qloss),
key=itemgetter(0))))
else:
ret = idx, fr, to, Pfr, Qfr, Pto, Qto, Ploss, Qloss
return ret | def get_linedata(self, sort_names=False) | get line data from solved power flow | 2.961116 | 2.690799 | 1.10046 |
assert isinstance(model, str)
if model not in self.all_models:
self.all_models.append(model) | def register_model(self, model) | Register ``model`` to this group
:param model: model name
:return: None | 3.642045 | 3.442065 | 1.058099 |
if idx is None:
idx = model + '_' + str(len(self._idx_model))
self._idx_model[idx] = model
self._idx.append(idx)
return idx | def register_element(self, model, idx) | Register element with index ``idx`` to ``model``
:param model: model name
:param idx: element idx
:return: final element idx | 4.149626 | 4.24026 | 0.978625 |
ret = []
scalar = False
# TODO: ensure idx is unique in this Group
if isinstance(idx, (int, float, str)):
scalar = True
idx = [idx]
models = [self._idx_model[i] for i in idx]
for i, m in zip(idx, models):
ret.append(self.system.__dict__[m].get_field(field, idx=i))
if scalar is True:
return ret[0]
else:
return ret | def get_field(self, field, idx) | Return the field ``field`` of elements ``idx`` in the group
:param field: field name
:param idx: element idx
:return: values of the requested field | 4.674031 | 4.724199 | 0.989381 |
if isinstance(idx, (int, float, str)):
idx = [idx]
if isinstance(value, (int, float)):
value = [value]
models = [self._idx_model[i] for i in idx]
for i, m, v in zip(idx, models, value):
assert hasattr(self.system.__dict__[m], field)
uid = self.system.__dict__[m].get_uid(idx)
self.system.__dict__[m].__dict__[field][uid] = v | def set_field(self, field, idx, value) | Set the field ``field`` of elements ``idx`` to ``value``.
This function does not if the field is valid for all models.
:param field: field name
:param idx: element idx
:param value: value of fields to set
:return: None | 3.495697 | 3.293758 | 1.06131 |
# Enumerate all known services
known_services = workflows.services.get_known_services()
# Set up parser
parser = OptionParser(
usage=program_name + " [options]" if program_name else None, version=version
)
parser.add_option("-?", action="help", help=SUPPRESS_HELP)
parser.add_option(
"-s",
"--service",
dest="service",
metavar="SVC",
default=None,
help="Name of the service to start. Known services: "
+ ", ".join(known_services),
)
parser.add_option(
"-t",
"--transport",
dest="transport",
metavar="TRN",
default="StompTransport",
help="Transport mechanism. Known mechanisms: "
+ ", ".join(workflows.transport.get_known_transports())
+ " (default: %default)",
)
workflows.transport.add_command_line_options(parser)
# Call on_parser_preparation hook
parser = self.on_parser_preparation(parser) or parser
# Parse command line options
(options, args) = parser.parse_args(cmdline_args)
# Call on_parsing hook
(options, args) = self.on_parsing(options, args) or (options, args)
# Create Transport factory
transport_factory = workflows.transport.lookup(options.transport)
# Call on_transport_factory_preparation hook
transport_factory = (
self.on_transport_factory_preparation(transport_factory)
or transport_factory
)
# Set up on_transport_preparation hook to affect newly created transport objects
true_transport_factory_call = transport_factory.__call__
def on_transport_preparation_hook():
transport_object = true_transport_factory_call()
return self.on_transport_preparation(transport_object) or transport_object
transport_factory.__call__ = on_transport_preparation_hook
# When service name is specified, check if service exists or can be derived
if options.service and options.service not in known_services:
matching = [s for s in known_services if s.startswith(options.service)]
if not matching:
matching = [
s
for s in known_services
if s.lower().startswith(options.service.lower())
]
if matching and len(matching) == 1:
options.service = matching[0]
kwargs.update({"service": options.service, "transport": transport_factory})
# Call before_frontend_construction hook
kwargs = self.before_frontend_construction(kwargs) or kwargs
# Create Frontend object
frontend = workflows.frontend.Frontend(**kwargs)
# Call on_frontend_preparation hook
frontend = self.on_frontend_preparation(frontend) or frontend
# Start Frontend
try:
frontend.run()
except KeyboardInterrupt:
print("\nShutdown via Ctrl+C") | def run(
self,
cmdline_args=None,
program_name="start_service",
version=workflows.version(),
**kwargs
) | Example command line interface to start services.
:param cmdline_args: List of command line arguments to pass to parser
:param program_name: Name of the command line tool to display in help
:param version: Version number to print when run with '--version' | 2.494121 | 2.510787 | 0.993362 |
sort_direction = request.GET.get("dir")
field_name = (request.GET.get("sort") or "") if sort_direction else ""
sort_sign = "-" if sort_direction == "desc" else ""
result_field = "{sign}{field}".format(sign=sort_sign, field=field_name)
return result_field | def get_sort_field(request) | Retrieve field used for sorting a queryset
:param request: HTTP request
:return: the sorted field name, prefixed with "-" if ordering is descending | 3.294733 | 3.169323 | 1.03957 |
bits = [b for b in token.split_contents()]
if len(bits) < 2:
raise template.TemplateSyntaxError("anchor tag takes at least 1 argument.")
title_is_var = False
try:
title = bits[2]
if title[0] in ('"', "'"):
if title[0] == title[-1]:
title = title[1:-1]
else:
raise template.TemplateSyntaxError(
'anchor tag title must be a "string", _("trans string"), or variable'
)
elif title.startswith('_("') or title.startswith("_('"):
title = _(title[3:-2])
else:
title_is_var = True
except IndexError:
title = bits[1].capitalize()
return SortAnchorNode(bits[1].strip(), title.strip(), title_is_var) | def anchor(parser, token) | Parses a tag that's supposed to be in this format '{% anchor field title %}'
Title may be a "string", _("trans string"), or variable | 3.488387 | 2.746691 | 1.270033 |
params['format'] = 'json'
if sys.version_info[0] == 3:
fixed = urllib.urlencode(tuple(params.items()))
# urllib.urlencode (in Python 2) expects str objects, not unicode
elif sys.version_info[0] == 2:
fixed = urllib.urlencode(
tuple((to_bytes(k), to_bytes(v)) for k, v in
params.items())).encode('utf-8')
if force_get:
request = urllib2.Request(url + '?' + fixed)
else:
if sys.version_info[0] == 3:
fixed = bytearray(fixed, 'utf-8')
request = urllib2.Request(url, fixed)
if self._http_user is not None:
auth_str = '%s:%s' % (self._http_user, self._http_password)
if sys.version_info[0] == 3:
auth_str = bytearray(auth_str, 'utf-8')
base64string = base64.encodestring(auth_str).replace('\n', '')
request.add_header("Authorization", "Basic %s" % base64string)
request.add_header('Accept-encoding', 'gzip')
response = self._opener.open(request)
if isinstance(self._cj, cookielib.FileCookieJar):
self._cj.save()
if response.headers.get('Content-Encoding') == 'gzip':
compressed = StringIO(response.read())
gzipper = gzip.GzipFile(fileobj=compressed)
data = gzipper.read()
else:
data = response.read()
if sys.version_info[0] == 3:
encoding = response.info().get_content_charset() or "utf-8"
data = data.decode(encoding)
return data | def _fetch_http(self, url, params, force_get=False) | Standard HTTP request handler for this class with gzip and cookie
support. This was separated out of :py:func:`MediaWiki.call` to make
:py:func:`MediaWiki.normalize_api_url` useful.
.. note::
This function should not be used. Use :py:func:`MediaWiki.call`
instead.
:param url: URL to send POST request to
:param params: dictionary of query string parameters
:param force_get: force a GET request instead of POST | 2.075505 | 2.095695 | 0.990366 |
return json.loads(self._fetch_http(self._api_url, params)) | def call(self, params) | Make an API call to the wiki. *params* is a dictionary of query string
arguments. For example, to get basic information about the wiki, run:
>>> wiki.call({'action': 'query', 'meta': 'siteinfo'})
which would make a call to
``http://domain/w/api.php?action=query&meta=siteinfo&format=json``
(except the query string would be sent in POST).
:param params: dictionary of query string parameters
:returns: dictionary containing API response | 9.788351 | 12.694012 | 0.7711 |
def tester(self, api_url):
data = self._fetch_http(api_url, {'action': 'query',
'meta': 'siteinfo'})
try:
data_json = json.loads(data)
return (data, data_json)
except ValueError:
return (data, None)
data, data_json = tester(self, self._api_url)
if data_json:
return self._api_url
else:
# if there's an index.php in the URL, we might find the API
if 'index.php' in self._api_url:
test_api_url = self._api_url.split('index.php')[0] + 'api.php'
test_data, test_data_json = tester(self, test_api_url)
if test_data_json:
self._api_url = test_api_url
return self._api_url
return None | def normalize_api_url(self) | Checks that the API URL used to initialize this object actually returns
JSON. If it doesn't, make some educated guesses and try to find the
correct URL.
:returns: a valid API URL or ``None`` | 2.724831 | 2.658645 | 1.024895 |
def do_login(self, user, passwd, token=None):
data = {'action': 'login',
'lgname': user,
'lgpassword': passwd}
if token:
data['lgtoken'] = token
result = self.call(data)
if result['login']['result'] == 'Success':
self._high_limits = None
return True
elif result['login']['result'] == 'NeedToken' and not token:
return do_login(self, user, passwd, result['login']['token'])
else:
return False
return do_login(self, user, passwd) | def login(self, user, passwd) | Logs into the wiki with username *user* and password *passwd*. Returns
``True`` on successful login.
:param user: username
:param passwd: password
:returns: ``True`` on successful login, otherwise ``False`` | 3.435565 | 2.975946 | 1.154445 |
if self._high_limits is None:
result = self.call({'action': 'query',
'meta': 'userinfo',
'uiprop': 'rights'})
self._high_limits = 'apihighlimits' in \
result['query']['userinfo']['rights']
if self._high_limits:
return high
else:
return low | def limits(self, low, high) | Convenience function for determining appropriate limits in the API. If
the (usually logged-in) client has the ``apihighlimits`` right, it will
return *high*; otherwise it will return *low*.
It's generally a good idea to use the highest limit possible; this
reduces the amount of HTTP requests and therefore overhead. Read the
API documentation for details on the limits for the function you are
using.
:param low: value to return if client does not have ``apihighlimits``
:param high: value to return if client has ``apihighlimits``
:returns: *low* or *high* | 5.216236 | 3.690267 | 1.413512 |
if self._namespaces is None:
result = self.call({'action': 'query',
'meta': 'siteinfo',
'siprop': 'namespaces'})
self._namespaces = {}
self._psuedo_namespaces = {}
for nsid in result['query']['namespaces']:
if int(nsid) >= 0:
self._namespaces[int(nsid)] = \
result['query']['namespaces'][nsid]['*']
else:
self._psuedo_namespaces[int(nsid)] = \
result['query']['namespaces'][nsid]['*']
if psuedo:
retval = {}
retval.update(self._namespaces)
retval.update(self._psuedo_namespaces)
return retval
else:
return self._namespaces | def namespaces(self, psuedo=True) | Fetches a list of namespaces for this wiki and returns them as a
dictionary of namespace IDs corresponding to namespace names. If
*psuedo* is ``True``, the dictionary will also list psuedo-namespaces,
which are the "Special:" and "Media:" namespaces (special because they
have no content associated with them and their IDs are negative).
:param psuedo: boolean to determine inclusion of psuedo-namespaces
:returns: dictionary of namespace IDs and names | 2.066674 | 1.895953 | 1.090045 |
if self._strictAxisNames and not self.documentObject.axes:
raise DesignSpaceDocumentError("No axes defined")
loc = {}
for dimensionElement in locationElement.findall(".dimension"):
dimName = dimensionElement.attrib.get("name")
if self._strictAxisNames and dimName not in self.axisDefaults:
# In case the document contains no axis definitions,
self.log.warning("Location with undefined axis: \"%s\".", dimName)
continue
xValue = yValue = None
try:
xValue = dimensionElement.attrib.get('xvalue')
xValue = float(xValue)
except ValueError:
self.log.warning("KeyError in readLocation xValue %3.3f", xValue)
try:
yValue = dimensionElement.attrib.get('yvalue')
if yValue is not None:
yValue = float(yValue)
except ValueError:
pass
if yValue is not None:
loc[dimName] = (xValue, yValue)
else:
loc[dimName] = xValue
return loc | def readLocationElement(self, locationElement) | Format 0 location reader | 3.903938 | 3.885111 | 1.004846 |
import os, glob
if os.path.isdir(documentPath):
# process all *.designspace documents in this folder
todo = glob.glob(os.path.join(documentPath, "*.designspace"))
else:
# process the
todo = [documentPath]
results = []
for path in todo:
document = DesignSpaceProcessor(ufoVersion=outputUFOFormatVersion)
document.useVarlib = useVarlib
document.roundGeometry = roundGeometry
document.read(path)
try:
r = document.generateUFO(processRules=processRules)
results.append(r)
except:
if logger:
logger.exception("ufoProcessor error")
#results += document.generateUFO(processRules=processRules)
reader = None
return results | def build(
documentPath,
outputUFOFormatVersion=3,
roundGeometry=True,
verbose=True, # not supported
logPath=None, # not supported
progressFunc=None, # not supported
processRules=True,
logger=None,
useVarlib=False,
) | Simple builder for UFO designspaces. | 3.66211 | 3.676933 | 0.995969 |
if self._infoMutator:
return self._infoMutator
infoItems = []
for sourceDescriptor in self.sources:
if sourceDescriptor.layerName is not None:
continue
loc = Location(sourceDescriptor.location)
sourceFont = self.fonts[sourceDescriptor.name]
if sourceFont is None:
continue
if hasattr(sourceFont.info, "toMathInfo"):
infoItems.append((loc, sourceFont.info.toMathInfo()))
else:
infoItems.append((loc, self.mathInfoClass(sourceFont.info)))
bias, self._infoMutator = self.getVariationModel(infoItems, axes=self.serializedAxes, bias=self.newDefaultLocation())
return self._infoMutator | def getInfoMutator(self) | Returns a info mutator | 5.428369 | 5.360778 | 1.012608 |
if self._kerningMutator and pairs == self._kerningMutatorPairs:
return self._kerningMutator
kerningItems = []
if pairs is None:
for sourceDescriptor in self.sources:
if sourceDescriptor.layerName is not None:
continue
if not sourceDescriptor.muteKerning:
loc = Location(sourceDescriptor.location)
sourceFont = self.fonts[sourceDescriptor.name]
if sourceFont is None: continue
# this makes assumptions about the groups of all sources being the same.
kerningItems.append((loc, self.mathKerningClass(sourceFont.kerning, sourceFont.groups)))
else:
self._kerningMutatorPairs = pairs
for sourceDescriptor in self.sources:
# XXX check sourceDescriptor layerName, only foreground should contribute
if sourceDescriptor.layerName is not None:
continue
if not os.path.exists(sourceDescriptor.path):
continue
if not sourceDescriptor.muteKerning:
sourceFont = self.fonts[sourceDescriptor.name]
if sourceFont is None:
continue
loc = Location(sourceDescriptor.location)
# XXX can we get the kern value from the fontparts kerning object?
kerningItem = self.mathKerningClass(sourceFont.kerning, sourceFont.groups)
sparseKerning = {}
for pair in pairs:
v = kerningItem.get(pair)
if v is not None:
sparseKerning[pair] = v
kerningItems.append((loc, self.mathKerningClass(sparseKerning)))
bias, self._kerningMutator = self.getVariationModel(kerningItems, axes=self.serializedAxes, bias=self.newDefaultLocation())
return self._kerningMutator | def getKerningMutator(self, pairs=None) | Return a kerning mutator, collect the sources, build mathGlyphs.
If no pairs are given: calculate the whole table.
If pairs are given then query the sources for a value and make a mutator only with those values. | 3.962876 | 3.858355 | 1.02709 |
items = []
empties = []
foundEmpty = False
for sourceDescriptor in self.sources:
if not os.path.exists(sourceDescriptor.path):
#kthxbai
p = "\tMissing UFO at %s" % sourceDescriptor.path
if p not in self.problems:
self.problems.append(p)
continue
if glyphName in sourceDescriptor.mutedGlyphNames:
continue
thisIsDefault = self.default == sourceDescriptor
ignoreMaster, filteredLocation = self.filterThisLocation(sourceDescriptor.location, self.mutedAxisNames)
if ignoreMaster:
continue
f = self.fonts.get(sourceDescriptor.name)
if f is None: continue
loc = Location(sourceDescriptor.location)
sourceLayer = f
if not glyphName in f:
# log this>
continue
layerName = getDefaultLayerName(f)
sourceGlyphObject = None
# handle source layers
if sourceDescriptor.layerName is not None:
# start looking for a layer
# Do not bother for mutatorMath designspaces
layerName = sourceDescriptor.layerName
sourceLayer = getLayer(f, sourceDescriptor.layerName)
if sourceLayer is None:
continue
if glyphName not in sourceLayer:
# start looking for a glyph
# this might be a support in a sparse layer
# so we're skipping!
continue
# still have to check if the sourcelayer glyph is empty
if not glyphName in sourceLayer:
continue
else:
sourceGlyphObject = sourceLayer[glyphName]
if checkGlyphIsEmpty(sourceGlyphObject, allowWhiteSpace=True):
foundEmpty = True
#sourceGlyphObject = None
#continue
if decomposeComponents:
# what about decomposing glyphs in a partial font?
temp = self.glyphClass()
p = temp.getPointPen()
dpp = DecomposePointPen(sourceLayer, p)
sourceGlyphObject.drawPoints(dpp)
temp.width = sourceGlyphObject.width
temp.name = sourceGlyphObject.name
processThis = temp
else:
processThis = sourceGlyphObject
sourceInfo = dict(source=f.path, glyphName=glyphName,
layerName=layerName,
location=filteredLocation, # sourceDescriptor.location,
sourceName=sourceDescriptor.name,
)
if hasattr(processThis, "toMathGlyph"):
processThis = processThis.toMathGlyph()
else:
processThis = self.mathGlyphClass(processThis)
items.append((loc, processThis, sourceInfo))
empties.append((thisIsDefault, foundEmpty))
# check the empties:
# if the default glyph is empty, then all must be empty
# if the default glyph is not empty then none can be empty
checkedItems = []
emptiesAllowed = False
# first check if the default is empty.
# remember that the sources can be in any order
for i, p in enumerate(empties):
isDefault, isEmpty = p
if isDefault and isEmpty:
emptiesAllowed = True
# now we know what to look for
if not emptiesAllowed:
for i, p in enumerate(empties):
isDefault, isEmpty = p
if not isEmpty:
checkedItems.append(items[i])
else:
for i, p in enumerate(empties):
isDefault, isEmpty = p
if isEmpty:
checkedItems.append(items[i])
return checkedItems | def collectMastersForGlyph(self, glyphName, decomposeComponents=False) | Return a glyph mutator.defaultLoc
decomposeComponents = True causes the source glyphs to be decomposed first
before building the mutator. That gives you instances that do not depend
on a complete font. If you're calculating previews for instance.
XXX check glyphs in layers | 4.964937 | 4.8449 | 1.024776 |
try:
return self.fontClass(path,
layerClass=self.layerClass,
libClass=self.libClass,
kerningClass=self.kerningClass,
groupsClass=self.groupsClass,
infoClass=self.infoClass,
featuresClass=self.featuresClass,
glyphClass=self.glyphClass,
glyphContourClass=self.glyphContourClass,
glyphPointClass=self.glyphPointClass,
glyphComponentClass=self.glyphComponentClass,
glyphAnchorClass=self.glyphAnchorClass)
except TypeError:
# if our fontClass doesnt support all the additional classes
return self.fontClass(path) | def _instantiateFont(self, path) | Return a instance of a font object with all the given subclasses | 2.966582 | 2.765291 | 1.072792 |
whiteSpace = [ 0x9, # horizontal tab
0xa, # line feed
0xb, # vertical tab
0xc, # form feed
0xd, # carriage return
0x20, # space
0x85, # next line
0xa0, # nobreak space
0x1680, # ogham space mark
0x180e, # mongolian vowel separator
0x2000, # en quad
0x2001, # em quad
0x2003, # en space
0x2004, # three per em space
0x2005, # four per em space
0x2006, # six per em space
0x2007, # figure space
0x2008, # punctuation space
0x2009, # thin space
0x200a, # hair space
0x2028, # line separator
0x2029, # paragraph separator
0x202f, # narrow no break space
0x205f, # medium mathematical space
0x3000, # ideographic space
]
emptyPen = EmptyPen()
glyph.drawPoints(emptyPen)
if emptyPen.isEmpty():
# we're empty?
if glyph.unicode in whiteSpace and allowWhiteSpace:
# are we allowed to be?
return False
return True
return False | def checkGlyphIsEmpty(glyph, allowWhiteSpace=True) | This will establish if the glyph is completely empty by drawing the glyph with an EmptyPen.
Additionally, the unicode of the glyph is checked against a list of known unicode whitespace
characters. This makes it possible to filter out glyphs that have a valid reason to be empty
and those that can be ignored. | 1.872823 | 1.791643 | 1.04531 |
# Only configure if necessary
if not skip_configuration:
configuration_command = ['python', 'waf', 'configure', '--enable-examples',
'--disable-gtk', '--disable-python']
if optimized:
configuration_command += ['--build-profile=optimized',
'--out=build/optimized']
# Check whether path points to a valid installation
subprocess.call(configuration_command, cwd=self.path,
stdout=subprocess.PIPE, stderr=subprocess.PIPE)
# Build ns-3
build_process = subprocess.Popen(['python', 'waf', 'build'], cwd=self.path,
stdout=subprocess.PIPE,
stderr=subprocess.PIPE)
# Show a progress bar
if show_progress:
line_iterator = self.get_build_output(build_process)
pbar = None
try:
[initial, total] = next(line_iterator)
pbar = tqdm(line_iterator, initial=initial, total=total,
unit='file', desc='Building ns-3', smoothing=0)
for current, total in pbar:
pbar.n = current
except (StopIteration):
if pbar is not None:
pbar.n = pbar.total
else: # Wait for the build to finish anyway
build_process.communicate() | def configure_and_build(self, show_progress=True, optimized=True,
skip_configuration=False) | Configure and build the ns-3 code.
Args:
show_progress (bool): whether or not to display a progress bar
during compilation.
optimized (bool): whether to use an optimized build. If False, use
a standard ./waf configure.
skip_configuration (bool): whether to skip the configuration step,
and only perform compilation. | 3.719076 | 3.673629 | 1.012371 |
while True:
output = process.stdout.readline()
if output == b'' and process.poll() is not None:
if process.returncode > 0:
raise Exception("Compilation ended with an error"
".\nSTDERR\n%s\nSTDOUT\n%s" %
(process.stderr.read(),
process.stdout.read()))
return
if output:
# Parse the output to get current and total tasks
# This assumes the progress displayed by waf is in the form
# [current/total]
matches = re.search(r'\[\s*(\d+?)/(\d+)\].*',
output.strip().decode('utf-8'))
if matches is not None:
yield [int(matches.group(1)), int(matches.group(2))] | def get_build_output(self, process) | Parse the output of the ns-3 build process to extract the information
that is needed to draw the progress bar.
Args:
process: the subprocess instance to listen to. | 3.821849 | 3.651512 | 1.046648 |
# At the moment, we rely on regex to extract the list of available
# parameters. This solution will break if the format of the output
# changes, but this is the best option that is currently available.
result = subprocess.check_output([self.script_executable,
'--PrintHelp'], env=self.environment,
cwd=self.path).decode('utf-8')
# Isolate the list of parameters
options = re.findall('.*Program\s(?:Options|Arguments):'
'(.*)General\sArguments.*',
result, re.DOTALL)
global_options = subprocess.check_output([self.script_executable,
'--PrintGlobals'],
env=self.environment,
cwd=self.path).decode('utf-8')
# Get the single parameter names
args = []
if len(options):
args += re.findall('.*--(.*?)[?::|=].*', options[0], re.MULTILINE)
if len(global_options):
args += [k for k in re.findall('.*--(.*?)[?::|=].*',
global_options, re.MULTILINE) if k
not in ['RngRun', 'RngSeed', 'SchedulerType',
'SimulatorImplementationType', 'ChecksumEnabled']]
return sorted(args) | def get_available_parameters(self) | Return a list of the parameters made available by the script. | 5.68862 | 5.543368 | 1.026203 |
for idx, parameter in enumerate(parameter_list):
current_result = {
'params': {},
'meta': {}
}
current_result['params'].update(parameter)
command = [self.script_executable] + ['--%s=%s' % (param, value)
for param, value in
parameter.items()]
# Run from dedicated temporary folder
current_result['meta']['id'] = str(uuid.uuid4())
temp_dir = os.path.join(data_folder, current_result['meta']['id'])
os.makedirs(temp_dir)
start = time.time() # Time execution
stdout_file_path = os.path.join(temp_dir, 'stdout')
stderr_file_path = os.path.join(temp_dir, 'stderr')
with open(stdout_file_path, 'w') as stdout_file, open(
stderr_file_path, 'w') as stderr_file:
return_code = subprocess.call(command, cwd=temp_dir,
env=self.environment,
stdout=stdout_file,
stderr=stderr_file)
end = time.time() # Time execution
if return_code > 0:
complete_command = [self.script]
complete_command.extend(command[1:])
complete_command = "python waf --run \"%s\"" % (
' '.join(complete_command))
with open(stdout_file_path, 'r') as stdout_file, open(
stderr_file_path, 'r') as stderr_file:
raise Exception(('Simulation exited with an error.\n'
'Params: %s\n'
'\nStderr: %s\n'
'Stdout: %s\n'
'Use this command to reproduce:\n'
'%s'
% (parameter, stderr_file.read(),
stdout_file.read(), complete_command)))
current_result['meta']['elapsed_time'] = end-start
yield current_result | def run_simulations(self, parameter_list, data_folder) | Run several simulations using a certain combination of parameters.
Yields results as simulations are completed.
Args:
parameter_list (list): list of parameter combinations to simulate.
data_folder (str): folder in which to save subfolders containing
simulation output. | 2.548421 | 2.537476 | 1.004314 |
# Convert non-list values to single-element lists
# This is required to make sure product work.
for key in param_ranges:
if not isinstance(param_ranges[key], list):
param_ranges[key] = [param_ranges[key]]
return [dict(zip(param_ranges, v)) for v in
product(*param_ranges.values())] | def list_param_combinations(param_ranges) | Create a list of all parameter combinations from a dictionary specifying
desired parameter values as lists.
Example:
>>> param_ranges = {'a': [1], 'b': [2, 3]}
>>> list_param_combinations(param_ranges)
[{'a': 1, 'b': 2}, {'a': 1, 'b': 3}]
Additionally, this function is robust in case values are not lists:
>>> param_ranges = {'a': 1, 'b': [2, 3]}
>>> list_param_combinations(param_ranges)
[{'a': 1, 'b': 2}, {'a': 1, 'b': 3}] | 3.370612 | 4.042333 | 0.833828 |
if not debug:
command = "python waf --run \"" + script + " " + " ".join(
['--%s=%s' % (param, value) for param, value in
result['params'].items()]) + "\""
else:
command = "python waf --run " + script + " --command-template=\"" +\
"gdb --args %s " + " ".join(['--%s=%s' % (param, value) for
param, value in
result['params'].items()]) + "\""
return command | def get_command_from_result(script, result, debug=False) | Return the command that is needed to obtain a certain result.
Args:
params (dict): Dictionary containing parameter: value pairs.
debug (bool): Whether the command should include the debugging
template. | 3.62111 | 3.405118 | 1.063431 |
np.seterr(all='raise')
parsed = {}
for filename, contents in result['output'].items():
if dtypes.get(filename) is None:
dtypes[filename] = None
if converters.get(filename) is None:
converters[filename] = None
with warnings.catch_warnings():
warnings.simplefilter("ignore")
parsed[filename] = np.genfromtxt(io.StringIO(contents),
dtype=dtypes[filename],
converters=converters[filename]
).tolist()
return parsed | def automatic_parser(result, dtypes={}, converters={}) | Try and automatically convert strings formatted as tables into nested
list structures.
Under the hood, this function essentially applies the genfromtxt function
to all files in the output, and passes it the additional kwargs.
Args:
result (dict): the result to parse.
dtypes (dict): a dictionary containing the dtype specification to perform
parsing for each available filename. See the numpy genfromtxt
documentation for more details on how to format these. | 2.351082 | 2.523713 | 0.931596 |
# Convert paths to be absolute
ns_path = os.path.abspath(ns_path)
campaign_dir = os.path.abspath(campaign_dir)
# Verify if the specified campaign is already available
if Path(campaign_dir).exists() and not overwrite:
# Try loading
manager = CampaignManager.load(campaign_dir, ns_path,
runner_type=runner_type,
optimized=optimized,
check_repo=check_repo)
if manager.db.get_script() == script:
return manager
else:
del manager
# Initialize runner
runner = CampaignManager.create_runner(ns_path, script,
runner_type=runner_type,
optimized=optimized)
# Get list of parameters to save in the DB
params = runner.get_available_parameters()
# Get current commit
commit = ""
if check_repo:
from git import Repo, exc
commit = Repo(ns_path).head.commit.hexsha
# Create a database manager from the configuration
db = DatabaseManager.new(script=script,
params=params,
commit=commit,
campaign_dir=campaign_dir,
overwrite=overwrite)
return cls(db, runner, check_repo) | def new(cls, ns_path, script, campaign_dir, runner_type='Auto',
overwrite=False, optimized=True, check_repo=True) | Create a new campaign from an ns-3 installation and a campaign
directory.
This method will create a DatabaseManager, which will install a
database in the specified campaign_dir. If a database is already
available at the ns_path described in the specified campaign_dir and
its configuration matches config, this instance is used instead. If the
overwrite argument is set to True instead, the specified directory is
wiped and a new campaign is created in its place.
Furthermore, this method will initialize a SimulationRunner, of type
specified by the runner_type parameter, which will be locked on the
ns-3 installation at ns_path and set up to run the desired script.
Finally, note that creation of a campaign requires a git repository to
be initialized at the specified ns_path. This will allow SEM to save
the commit at which the simulations are run, enforce reproducibility
and avoid mixing results coming from different versions of ns-3 and its
libraries.
Args:
ns_path (str): path to the ns-3 installation to employ in this
campaign.
script (str): ns-3 script that will be executed to run simulations.
campaign_dir (str): path to the directory in which to save the
simulation campaign database.
runner_type (str): implementation of the SimulationRunner to use.
Value can be: SimulationRunner (for running sequential
simulations locally), ParallelRunner (for running parallel
simulations locally), GridRunner (for running simulations using
a DRMAA-compatible parallel task scheduler). Use Auto to
automatically pick the best runner.
overwrite (bool): whether to overwrite already existing
campaign_dir folders. This deletes the directory if and only if
it only contains files that were detected to be created by sem.
optimized (bool): whether to configure the runner to employ an
optimized ns-3 build. | 3.357688 | 3.279117 | 1.023961 |
# Convert paths to be absolute
if ns_path is not None:
ns_path = os.path.abspath(ns_path)
campaign_dir = os.path.abspath(campaign_dir)
# Read the existing configuration into the new DatabaseManager
db = DatabaseManager.load(campaign_dir)
script = db.get_script()
runner = None
if ns_path is not None:
runner = CampaignManager.create_runner(ns_path, script,
runner_type, optimized)
return cls(db, runner, check_repo) | def load(cls, campaign_dir, ns_path=None, runner_type='Auto',
optimized=True, check_repo=True) | Load an existing simulation campaign.
Note that specifying an ns-3 installation is not compulsory when using
this method: existing results will be available, but in order to run
additional simulations it will be necessary to specify a
SimulationRunner object, and assign it to the CampaignManager.
Args:
campaign_dir (str): path to the directory in which to save the
simulation campaign database.
ns_path (str): path to the ns-3 installation to employ in this
campaign.
runner_type (str): implementation of the SimulationRunner to use.
Value can be: SimulationRunner (for running sequential
simulations locally), ParallelRunner (for running parallel
simulations locally), GridRunner (for running simulations using
a DRMAA-compatible parallel task scheduler).
optimized (bool): whether to configure the runner to employ an
optimized ns-3 build. | 3.670508 | 3.481995 | 1.054139 |
# locals() contains a dictionary pairing class names with class
# objects: we can create the object using the desired class starting
# from its name.
if runner_type == 'Auto' and DRMAA_AVAILABLE:
runner_type = 'GridRunner'
elif runner_type == 'Auto':
runner_type = 'ParallelRunner'
return locals().get(runner_type,
globals().get(runner_type))(
ns_path, script, optimized=optimized) | def create_runner(ns_path, script, runner_type='Auto',
optimized=True) | Create a SimulationRunner from a string containing the desired
class implementation, and return it.
Args:
ns_path (str): path to the ns-3 installation to employ in this
SimulationRunner.
script (str): ns-3 script that will be executed to run simulations.
runner_type (str): implementation of the SimulationRunner to use.
Value can be: SimulationRunner (for running sequential
simulations locally), ParallelRunner (for running parallel
simulations locally), GridRunner (for running simulations using
a DRMAA-compatible parallel task scheduler). If Auto,
automatically pick the best available runner (GridRunner if
DRMAA is available, ParallelRunner otherwise).
optimized (bool): whether to configure the runner to employ an
optimized ns-3 build. | 6.390762 | 5.783201 | 1.105056 |
# Make sure we have a runner to run simulations with.
# This can happen in case the simulation campaign is loaded and not
# created from scratch.
if self.runner is None:
raise Exception("No runner was ever specified"
" for this CampaignManager.")
# Return if the list is empty
if param_list == []:
return
# Check all parameter combinations fully specify the desired simulation
desired_params = self.db.get_params()
for p in param_list:
# Besides the parameters that were actually passed, we add the ones
# that are always available in every script
passed = list(p.keys())
available = ['RngRun'] + desired_params
if set(passed) != set(available):
raise ValueError("Specified parameter combination does not "
"match the supported parameters:\n"
"Passed: %s\nSupported: %s" %
(sorted(passed), sorted(available)))
# Check that the current repo commit corresponds to the one specified
# in the campaign
if self.check_repo:
self.check_repo_ok()
# Build ns-3 before running any simulations
# At this point, we can assume the project was already configured
self.runner.configure_and_build(skip_configuration=True)
# Shuffle simulations
# This mixes up long and short simulations, and gives better time
# estimates.
shuffle(param_list)
# Offload simulation execution to self.runner
# Note that this only creates a generator for the results, no
# computation is performed on this line.
results = self.runner.run_simulations(param_list,
self.db.get_data_dir())
# Wrap the result generator in the progress bar generator.
if show_progress:
result_generator = tqdm(results, total=len(param_list),
unit='simulation',
desc='Running simulations')
else:
result_generator = results
# Insert result object in db. Using the generator here ensures we
# save results as they are finalized by the SimulationRunner, and
# that they are kept even if execution is terminated abruptly by
# crashes or by a KeyboardInterrupt.
for result in result_generator:
self.db.insert_result(result) | def run_simulations(self, param_list, show_progress=True) | Run several simulations specified by a list of parameter combinations.
Note: this function does not verify whether we already have the
required simulations in the database - it just runs all the parameter
combinations that are specified in the list.
Args:
param_list (list): list of parameter combinations to execute.
Items of this list are dictionaries, with one key for each
parameter, and a value specifying the parameter value (which
can be either a string or a number).
show_progress (bool): whether or not to show a progress bar with
percentage and expected remaining time. | 7.219229 | 7.1615 | 1.008061 |
params_to_simulate = []
if runs is not None: # Get next available runs from the database
next_runs = self.db.get_next_rngruns()
available_params = [r['params'] for r in self.db.get_results()]
for param_comb in param_list:
# Count how many param combinations we found, and remove them
# from the list of available_params for faster searching in the
# future
needed_runs = runs
for i, p in enumerate(available_params):
if param_comb == {k: p[k] for k in p.keys() if k != "RngRun"}:
needed_runs -= 1
new_param_combs = []
for needed_run in range(needed_runs):
# Here it's important that we make copies of the
# dictionaries, so that if we modify one we don't modify
# the others. This is necessary because after this step,
# typically, we will add the RngRun key which must be
# different for each copy.
new_param = deepcopy(param_comb)
new_param['RngRun'] = next(next_runs)
new_param_combs += [new_param]
params_to_simulate += new_param_combs
else:
for param_comb in param_list:
if not self.db.get_results(param_comb):
params_to_simulate += [param_comb]
return params_to_simulate | def get_missing_simulations(self, param_list, runs=None) | Return a list of the simulations among the required ones that are not
available in the database.
Args:
param_list (list): a list of dictionaries containing all the
parameters combinations.
runs (int): an integer representing how many repetitions are wanted
for each parameter combination, None if the dictionaries in
param_list already feature the desired RngRun value. | 4.215636 | 3.824648 | 1.102228 |
# If we are passed a dictionary, we need to expand this
if isinstance(param_list, dict):
param_list = list_param_combinations(param_list)
# If we are passed a list already, just run the missing simulations
self.run_simulations(
self.get_missing_simulations(param_list, runs)) | def run_missing_simulations(self, param_list, runs=None) | Run the simulations from the parameter list that are not yet available
in the database.
This function also makes sure that we have at least runs replications
for each parameter combination.
Additionally, param_list can either be a list containing the desired
parameter combinations or a dictionary containing multiple values for
each parameter, to be expanded into a list.
Args:
param_list (list, dict): either a list of parameter combinations or
a dictionary to be expanded into a list through the
list_param_combinations function.
runs (int): the number of runs to perform for each parameter
combination. This parameter is only allowed if the param_list
specification doesn't feature an 'RngRun' key already. | 4.640747 | 3.988115 | 1.163644 |
return np.array(self.get_space(self.db.get_complete_results(), {},
parameter_space, runs,
result_parsing_function)) | def get_results_as_numpy_array(self, parameter_space,
result_parsing_function, runs) | Return the results relative to the desired parameter space in the form
of a numpy array.
Args:
parameter_space (dict): dictionary containing
parameter/list-of-values pairs.
result_parsing_function (function): user-defined function, taking a
result dictionary as argument, that can be used to parse the
result files and return a list of values.
runs (int): number of runs to gather for each parameter
combination. | 8.065258 | 11.241019 | 0.717485 |
# Make sure all values are lists
for key in parameter_space:
if not isinstance(parameter_space[key], list):
parameter_space[key] = [parameter_space[key]]
# Add a dimension label for each non-singular dimension
dimension_labels = [{key: str(parameter_space[key])} for key in
parameter_space.keys() if len(parameter_space[key])
> 1] + [{'runs': range(runs)}]
# Create a list of the parameter names
return savemat(
filename,
{'results':
self.get_results_as_numpy_array(parameter_space,
result_parsing_function,
runs=runs),
'dimension_labels': dimension_labels}) | def save_to_mat_file(self, parameter_space,
result_parsing_function,
filename, runs) | Return the results relative to the desired parameter space in the form
of a .mat file.
Args:
parameter_space (dict): dictionary containing
parameter/list-of-values pairs.
result_parsing_function (function): user-defined function, taking a
result dictionary as argument, that can be used to parse the
result files and return a list of values.
filename (path): name of output .mat file.
runs (int): number of runs to gather for each parameter
combination. | 3.640743 | 3.784297 | 0.962066 |
np.save(filename, self.get_results_as_numpy_array(
parameter_space, result_parsing_function, runs=runs)) | def save_to_npy_file(self, parameter_space,
result_parsing_function,
filename, runs) | Save results to a numpy array file format. | 2.791902 | 2.952937 | 0.945466 |
self.space_to_folders(self.db.get_results(), {}, parameter_space, runs,
folder_name) | def save_to_folders(self, parameter_space, folder_name, runs) | Save results to a folder structure. | 10.009119 | 9.943695 | 1.006579 |
# Base case: we iterate over the runs and copy files in the final
# directory.
if not param_space:
for run, r in enumerate(current_result_list[:runs]):
files = self.db.get_result_files(r)
new_dir = os.path.join(current_directory, "run=%s" % run)
os.makedirs(new_dir, exist_ok=True)
for filename, filepath in files.items():
shutil.copyfile(filepath, os.path.join(new_dir, filename))
return
[key, value] = list(param_space.items())[0]
# Iterate over dictionary values
for v in value:
next_query = deepcopy(current_query)
temp_query = deepcopy(current_query)
# For each list, recur 'fixing' that dimension.
next_query[key] = v # Update query
# Create folder
folder_name = ("%s=%s" % (key, v)).replace('/', '_')
new_dir = os.path.join(current_directory, folder_name)
os.makedirs(new_dir, exist_ok=True)
next_param_space = deepcopy(param_space)
del(next_param_space[key])
temp_query[key] = v
temp_result_list = [r for r in current_result_list if
self.satisfies_query(r, temp_query)]
self.space_to_folders(temp_result_list, next_query,
next_param_space, runs, new_dir) | def space_to_folders(self, current_result_list, current_query, param_space,
runs, current_directory) | Convert a parameter space specification to a directory tree with a
nested structure. | 2.878436 | 2.946863 | 0.97678 |
np_array = np.array(
self.get_space(
self.db.get_complete_results(), {},
collections.OrderedDict([(k, v) for k, v in
parameter_space.items()]),
runs, result_parsing_function))
# Create a parameter space only containing the variable parameters
clean_parameter_space = collections.OrderedDict(
[(k, v) for k, v in parameter_space.items()])
clean_parameter_space['runs'] = range(runs)
if isinstance(output_labels, list):
clean_parameter_space['metrics'] = output_labels
xr_array = xr.DataArray(np_array, coords=clean_parameter_space,
dims=list(clean_parameter_space.keys()))
return xr_array | def get_results_as_xarray(self, parameter_space,
result_parsing_function,
output_labels, runs) | Return the results relative to the desired parameter space in the form
of an xarray data structure.
Args:
parameter_space (dict): The space of parameters to export.
result_parsing_function (function): user-defined function, taking a
result dictionary as argument, that can be used to parse the
result files and return a list of values.
output_labels (list): a list of labels to apply to the results
dimensions, output by the result_parsing_function.
runs (int): the number of runs to export for each parameter
combination. | 3.61887 | 3.989249 | 0.907156 |
if result_parsing_function is None:
result_parsing_function = CampaignManager.files_in_dictionary
# Note that this function operates recursively.
# Base case
if not param_space:
results = [r for r in current_result_list if
self.satisfies_query(r, current_query)]
parsed = []
for r in results[:runs]:
parsed.append(result_parsing_function(r))
return parsed
space = []
[key, value] = list(param_space.items())[0]
# Iterate over dictionary values
for v in value:
next_query = deepcopy(current_query)
temp_query = deepcopy(current_query)
# For each list, recur 'fixing' that dimension.
next_query[key] = v
next_param_space = deepcopy(param_space)
del(next_param_space[key])
temp_query[key] = v
temp_result_list = [r for r in current_result_list if
self.satisfies_query(r, temp_query)]
space.append(self.get_space(temp_result_list, next_query,
next_param_space, runs,
result_parsing_function))
return space | def get_space(self, current_result_list, current_query, param_space, runs,
result_parsing_function) | Convert a parameter space specification to a nested array structure
representing the space. In other words, if the parameter space is::
param_space = {
'a': [1, 2],
'b': [3, 4]
}
the function will return a structure like the following::
[
[
{'a': 1, 'b': 3},
{'a': 1, 'b': 4}
],
[
{'a': 2, 'b': 3},
{'a': 2, 'b': 4}
]
]
where the first dimension represents a, and the second dimension
represents b. This nested-array structure can then be easily converted
to a numpy array via np.array().
Args:
current_query (dict): the query to apply to the structure.
param_space (dict): representation of the parameter space.
result_parsing_function (function): user-defined function to call
on results, typically used to parse data and outputting
metrics.
runs (int): the number of runs to query for each parameter
combination. | 3.257262 | 3.384278 | 0.962469 |
from git import Repo, exc
# Check that git is at the expected commit and that the repo is not
# dirty
if self.runner is not None:
path = self.runner.path
try:
repo = Repo(path)
except(exc.InvalidGitRepositoryError):
raise Exception("No git repository detected.\nIn order to "
"use SEM and its reproducibility enforcing "
"features, please create a git repository at "
"the root of your ns-3 project.")
current_commit = repo.head.commit.hexsha
campaign_commit = self.db.get_commit()
if repo.is_dirty(untracked_files=True):
raise Exception("ns-3 repository is not clean")
if current_commit != campaign_commit:
raise Exception("ns-3 repository is on a different commit "
"from the one specified in the campaign") | def check_repo_ok(self) | Make sure that the ns-3 repository's HEAD commit is the same as the one
saved in the campaign database, and that the ns-3 repository is clean
(i.e., no untracked or modified files exist). | 5.342927 | 4.613842 | 1.158021 |
sem.parallelrunner.MAX_PARALLEL_PROCESSES = max_processes
# Create a campaign
campaign = sem.CampaignManager.new(ns_3_path,
script,
results_dir,
overwrite=False,
optimized=not no_optimization)
# Print campaign info
click.echo(campaign)
# Run the simulations
[params, defaults] = zip(*get_params_and_defaults(campaign.db.get_params(),
campaign.db))
# Check whether we need to read parameters from the command line
if not parameters:
# Substitute non-None defaults with their string representation
# This will be then converted back to a Python data structure in
# query_parameters
string_defaults = list()
for idx, d in enumerate(defaults):
if d is not None:
string_defaults.append(str(d))
else:
string_defaults.append(d)
script_params = query_parameters(params, defaults=string_defaults)
else:
script_params = import_parameters_from_file(parameters)
# Finally, run the simulations
campaign.run_missing_simulations(script_params,
runs=click.prompt("Total runs", type=int)) | def run(ns_3_path, results_dir, script, no_optimization, parameters,
max_processes) | Run multiple simulations. | 5.799188 | 5.80454 | 0.999078 |
campaign = sem.CampaignManager.load(results_dir)
# Pick the most appropriate function based on the level of detail we want
if hide_simulation_output:
get_results_function = campaign.db.get_results
else:
get_results_function = campaign.db.get_complete_results
# If a result id was specified, just query for that result
if result_id:
output = '\n\n\n'.join([pprint.pformat(item) for item in
get_results_function(result_id=result_id)])
else:
[params, defaults] = zip(*get_params_and_defaults(
campaign.db.get_params(), campaign.db))
if not parameters:
# Convert to string
string_defaults = list()
for idx, d in enumerate(defaults):
string_defaults.append(str(d))
script_params = query_parameters(params, string_defaults)
else:
script_params = import_parameters_from_file(parameters)
# Perform the search
output = '\n\n\n'.join([pprint.pformat(item) for item in
get_results_function(script_params)])
# Print the results
if no_pager:
click.echo(output)
else:
click.echo_via_pager(output) | def view(results_dir, result_id, hide_simulation_output, parameters, no_pager) | View results of simulations. | 3.709768 | 3.768704 | 0.984362 |
campaign = sem.CampaignManager.load(results_dir)
result = campaign.db.get_results(result_id=result_id)[0]
click.echo("Simulation command:")
click.echo(sem.utils.get_command_from_result(campaign.db.get_script(),
result))
click.echo("Debug command:")
click.echo(sem.utils.get_command_from_result(campaign.db.get_script(),
result,
debug=True)) | def command(results_dir, result_id) | Print the command that needs to be used to reproduce a result. | 4.265355 | 4.029961 | 1.058411 |
# Get the extension
_, extension = os.path.splitext(filename)
campaign = sem.CampaignManager.load(results_dir)
[params, defaults] = zip(*get_params_and_defaults(campaign.db.get_params(),
campaign.db))
if do_not_try_parsing:
parsing_function = None
else:
parsing_function = sem.utils.automatic_parser
if not parameters:
# Convert to string
string_defaults = list()
for idx, d in enumerate(defaults):
string_defaults.append(str(d))
parameter_query = query_parameters(params, string_defaults)
else:
# Import specified parameter file
parameter_query = import_parameters_from_file(parameters)
if extension == ".mat":
campaign.save_to_mat_file(parameter_query, parsing_function, filename,
runs=click.prompt("Runs", type=int))
elif extension == ".npy":
campaign.save_to_npy_file(parameter_query, parsing_function, filename,
runs=click.prompt("Runs", type=int))
elif extension == "":
campaign.save_to_folders(parameter_query, filename,
runs=click.prompt("Runs", type=int))
else: # Unrecognized format
raise ValueError("Format not recognized") | def export(results_dir, filename, do_not_try_parsing, parameters) | Export results to file.
An extension in filename is required to deduce the file type. If no
extension is specified, a directory tree export will be used. Note that
this command automatically tries to parse the simulation output.
Supported extensions:
.mat (Matlab file),
.npy (Numpy file),
no extension (Directory tree) | 3.942804 | 4.050431 | 0.973428 |
# Get paths for all campaign JSONS
jsons = []
for s in sources:
filename = "%s.json" % os.path.split(s)[1]
jsons += [os.path.join(s, filename)]
# Check that the configuration for all campaigns is the same
reference_config = TinyDB(jsons[0]).table('config')
for j in jsons[1:]:
for i, j in zip(reference_config.all(), TinyDB(j).table('config').all()):
assert i == j
# Create folders for new results directory
filename = "%s.json" % os.path.split(output_dir)[1]
output_json = os.path.join(output_dir, filename)
output_data = os.path.join(output_dir, 'data')
os.makedirs(output_data)
# Create new database
db = TinyDB(output_json)
db.table('config').insert_multiple(reference_config.all())
# Import results from all databases to the new JSON file
for s in sources:
filename = "%s.json" % os.path.split(s)[1]
current_db = TinyDB(os.path.join(s, filename))
db.table('results').insert_multiple(current_db.table('results').all())
# Copy or move results to new data folder
for s in sources:
for r in glob.glob(os.path.join(s, 'data/*')):
basename = os.path.basename(r)
if move:
shutil.move(r, os.path.join(output_data, basename))
else:
shutil.copytree(r, os.path.join(output_data, basename))
if move:
for s in sources:
shutil.rmtree(os.path.join(s, 'data/*'))
shutil.rmtree(os.path.join(s, "%s.json" % os.path.split(s)[1]))
shutil.rmtree(s) | def merge(move, output_dir, sources) | Merge multiple results folder into one, by copying the results over to a new folder.
For a faster operation (which on the other hand destroys the campaign data
if interrupted), the move option can be used to directly move results to
the new folder. | 2.408557 | 2.316008 | 1.03996 |
return [[p, d] for p, d in db.get_all_values_of_all_params().items()] | def get_params_and_defaults(param_list, db) | Deduce [parameter, default] pairs from simulations available in the db.
Args:
param_list (list): List of parameters to query for.
db (DatabaseManager): Database where to query for defaults. | 7.938762 | 8.747237 | 0.907574 |
script_params = collections.OrderedDict([k, []] for k in param_list)
for param, default in zip(list(script_params.keys()), defaults):
user_input = click.prompt("%s" % param, default=default)
script_params[param] = ast.literal_eval(user_input)
return script_params | def query_parameters(param_list, defaults=None) | Asks the user for parameters. If available, proposes some defaults.
Args:
param_list (list): List of parameters to ask the user for values.
defaults (list): A list of proposed defaults. It must be a list of the
same length as param_list. A value of None in one element of the
list means that no default will be proposed for the corresponding
parameter. | 3.534588 | 3.75628 | 0.940981 |
params = {}
with open(parameters_file, 'r') as f:
matches = re.findall('(.*): (.*)', f.read())
for m in matches:
params[m[0]] = ast.literal_eval(m[1])
return params | def import_parameters_from_file(parameters_file) | Try importing a parameter dictionary from file.
We expect values in parameters_file to be defined as follows:
param1: value1
param2: [value2, value3] | 2.610924 | 2.919969 | 0.894162 |
self.data_folder = data_folder
with Pool(processes=MAX_PARALLEL_PROCESSES) as pool:
for result in pool.imap_unordered(self.launch_simulation,
parameter_list):
yield result | def run_simulations(self, parameter_list, data_folder) | This function runs multiple simulations in parallel.
Args:
parameter_list (list): list of parameter combinations to simulate.
data_folder (str): folder in which to create output folders. | 3.617771 | 4.108502 | 0.880557 |
return next(SimulationRunner.run_simulations(self, [parameter],
self.data_folder)) | def launch_simulation(self, parameter) | Launch a single simulation, using SimulationRunner's facilities.
This function is used by ParallelRunner's run_simulations to map
simulation running over the parameter list.
Args:
parameter (dict): the parameter combination to simulate. | 15.568825 | 14.573655 | 1.068286 |
return self.helper.string.serialization.json.stringify(
obj=obj,
beautify=beautify,
raise_exception=raise_exception) | def stringify(self, obj, beautify=False, raise_exception=False) | Alias of helper.string.serialization.json.stringify | 5.293786 | 2.308929 | 2.292745 |
return self.helper.string.serialization.json.parse(
text=text,
encoding=encoding,
raise_exception=raise_exception) | def parse(self, text, encoding='utf8', raise_exception=False) | Alias of helper.string.serialization.json.parse | 6.635807 | 2.506233 | 2.647721 |
# We only accept absolute paths
if not Path(campaign_dir).is_absolute():
raise ValueError("Path is not absolute")
# Make sure the directory does not exist already
if Path(campaign_dir).exists() and not overwrite:
raise FileExistsError("The specified directory already exists")
elif Path(campaign_dir).exists() and overwrite:
# Verify we are not deleting files belonging to the user
campaign_dir_name = os.path.basename(campaign_dir)
folder_contents = set(os.listdir(campaign_dir))
allowed_files = set(
['data', '%s.json' % campaign_dir_name] +
# Allow hidden files (like .DS_STORE in macos)
[os.path.basename(os.path.normpath(f)) for f in
glob.glob(os.path.join(campaign_dir, ".*"))])
if(not folder_contents.issubset(allowed_files)):
raise ValueError("The specified directory cannot be overwritten"
" because it contains user files.")
# This operation destroys data.
shutil.rmtree(campaign_dir)
# Create the directory and database file in it
# The indent and separators ensure the database is human readable.
os.makedirs(campaign_dir)
tinydb = TinyDB(os.path.join(campaign_dir, "%s.json" %
os.path.basename(campaign_dir)))
# Save the configuration in the database
config = {
'script': script,
'commit': commit,
'params': sorted(params)
}
tinydb.table('config').insert(config)
return cls(tinydb, campaign_dir) | def new(cls, script, commit, params, campaign_dir, overwrite=False) | Initialize a new class instance with a set configuration and filename.
The created database has the same name of the campaign directory.
Args:
script (str): the ns-3 name of the script that will be used in this
campaign;
commit (str): the commit of the ns-3 installation that is used to
run the simulations.
params (list): a list of the parameters that can be used on the
script.
campaign_dir (str): The path of the file where to save the DB.
overwrite (bool): Whether or not existing directories should be
overwritten. | 3.564069 | 3.508443 | 1.015855 |
# We only accept absolute paths
if not Path(campaign_dir).is_absolute():
raise ValueError("Path is not absolute")
# Verify file exists
if not Path(campaign_dir).exists():
raise ValueError("Directory does not exist")
# Extract filename from campaign dir
filename = "%s.json" % os.path.split(campaign_dir)[1]
filepath = os.path.join(campaign_dir, filename)
try:
# Read TinyDB instance from file
tinydb = TinyDB(filepath)
# Make sure the configuration is a valid dictionary
assert set(
tinydb.table('config').all()[0].keys()) == set(['script',
'params',
'commit'])
except:
# Remove the database instance created by tinydb
os.remove(filepath)
raise ValueError("Specified campaign directory seems corrupt")
return cls(tinydb, campaign_dir) | def load(cls, campaign_dir) | Initialize from an existing database.
It is assumed that the database json file has the same name as its
containing folder.
Args:
campaign_dir (str): The path to the campaign directory. | 4.535041 | 4.586905 | 0.988693 |
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