code stringlengths 4 4.48k | docstring stringlengths 1 6.45k | _id stringlengths 24 24 |
|---|---|---|
def approximate_spd( panel_properties: Dict[str, Any], des_distance: float, des_intensity: float, des_spectrum: Dict[str, float], ) -> Tuple[Dict, Dict, float]: <NEW_LINE> <INDENT> desired_spd_dict = calculate_spd_dict(des_intensity, des_spectrum) <NEW_LINE> desired_spd_vector = accessors.vectorize_dict(desired_spd_dic... | Approximates spectral power distribution. | 625941b85fcc89381b1e150f |
def process_links(txt, prefix): <NEW_LINE> <INDENT> txt = re.sub(r'[^\[][0,2](attachment:.*)[^\]][0,2]', '[[' + "\\1" + ']]', txt) <NEW_LINE> txt = re.sub(r'\[\[(.*?)\]\]', lambda matchobj: '[[' + convert_link(matchobj, prefix) + ']]', txt) <NEW_LINE> if prefix: <NEW_LINE> <INDENT> wikiword_re = re.compile(r'(\s)([A-Z]... | convert links to moin syntax | 625941b8498bea3a759b98fc |
def step(self, step=None): <NEW_LINE> <INDENT> activearrays = self.pre_step(step) <NEW_LINE> h0 = red2comp( activearrays["hessian"], self.im.dbeads.nbeads, self.im.dbeads.natoms, self.im.coef, ) <NEW_LINE> h1 = np.add(self.im.h, h0) <NEW_LINE> d, w = clean_hessian( h1, self.im.dbeads.q, self.im.dbeads.natoms, self.im.d... | Does one simulation time step. | 625941b867a9b606de4a7d08 |
@utils.arg('--limit', metavar='<NUMBER>', default=20, help='Page limit') <NEW_LINE> @utils.arg('--offset', metavar='<OFFSET>', help='Page offset') <NEW_LINE> @utils.arg('--order-by', metavar='<ORDER_BY>', help='Name of fields order by') <NEW_LINE> @utils.arg('--order', metavar='<ORDER>', choices=['desc', 'asc'], help='... | List all RegionQuota | 625941b8a17c0f6771cbde9f |
def do_fit( self, fit_function=None, x_data=None, y_data=None, channel_index=0, pixel_fit=False): <NEW_LINE> <INDENT> self.coord = None <NEW_LINE> if pixel_fit and np.count_nonzero(self.sweep_images) != 0: <NEW_LINE> <INDENT> frames = self.sweep_images / self.elapsed_sweeps <NEW_LINE> frames[:] = [cv2.flip(frame, 0) fo... | Execute the currently configured fit on the measurement data. Optionally on passed data | 625941b8dc8b845886cb5380 |
def get_bin_seeds(X, bin_size, min_bin_freq=1): <NEW_LINE> <INDENT> bin_sizes = defaultdict(int) <NEW_LINE> for point in X: <NEW_LINE> <INDENT> binned_point = np.round(point / bin_size) <NEW_LINE> bin_sizes[tuple(binned_point)] += 1 <NEW_LINE> <DEDENT> bin_seeds = np.array([point for point, freq in six.iteritems(bin_si... | Finds seeds for mean_shift.
Finds seeds by first binning data onto a grid whose lines are
spaced bin_size apart, and then choosing those bins with at least
min_bin_freq points.
Parameters
----------
X : array-like, shape=[n_samples, n_features]
Input points, the same points that will be used in mean_shift.
bin_... | 625941b87047854f462a1258 |
def __len__(self): <NEW_LINE> <INDENT> return self.n | Return the number of nodes in the trie. | 625941b8adb09d7d5db6c5de |
def alias(self): <NEW_LINE> <INDENT> return _spacegrant_swig.hdlc_framer_sptr_alias(self) | alias(hdlc_framer_sptr self) -> std::string | 625941b899fddb7c1c9de1de |
def test_login(self): <NEW_LINE> <INDENT> authenticator = Authenticator({'test': HiveUser('test', 'test')}) <NEW_LINE> Session.authenticator = authenticator <NEW_LINE> sessions = {} <NEW_LINE> users = {'test': HiveUser('test', 'test')} <NEW_LINE> cap = http.http(sessions, {'enabled': 'True', 'port': 0}, users, self.wor... | Tries to login using the username/password as test/test.
| 625941b899fddb7c1c9de1df |
def set_stance(self, stance: Stance): <NEW_LINE> <INDENT> if isinstance(self.__toy, (R2D2, R2Q5)): <NEW_LINE> <INDENT> if stance == Stance.Bipod: <NEW_LINE> <INDENT> ToyUtil.perform_leg_action(self.__toy, R2LegActions.TWO_LEGS) <NEW_LINE> <DEDENT> elif stance == Stance.Tripod: <NEW_LINE> <INDENT> ToyUtil.perform_leg_ac... | Changes the stance between bipod and tripod. Set to bipod using ``set_stance(Stance.Bipod)`` and
to tripod using ``set_stance(Stance.Tripod)``. Tripod is required for rolling. | 625941b863b5f9789fde6f31 |
def recompute_grad(fn): <NEW_LINE> <INDENT> @functools.wraps(fn) <NEW_LINE> def wrapped(*args): <NEW_LINE> <INDENT> return _recompute_grad(fn, args) <NEW_LINE> <DEDENT> return wrapped | Decorator that recomputes the function on the backwards pass.
Args:
fn: a function that takes Tensors (all as positional arguments) and returns
a tuple of Tensors.
Returns:
A wrapped fn that is identical to fn when called, but its activations will
be discarded and recomputed on the backwards pass (i.e. on a... | 625941b8097d151d1a222ca7 |
def conv_block(input_tensor, kernel_size, filters, stage, block, strides=(2, 2)): <NEW_LINE> <INDENT> nb_filter1, nb_filter2, nb_filter3 = filters <NEW_LINE> conv_name_base = 'res' + str(stage) + block + '_branch' <NEW_LINE> bn_name_base = 'bn' + str(stage) + block + '_branch' <NEW_LINE> x = Convolution2D(nb_filter1, 1... | conv_block is the block that has a conv layer at shortcut
# Arguments
input_tensor: input tensor
kernel_size: defualt 3, the kernel size of middle conv layer at main path
filters: list of integers, the nb_filters of 3 conv layer at main path
stage: integer, current stage label, used for generating layer... | 625941b8004d5f362079a182 |
def random_seeds(size, entropy=None): <NEW_LINE> <INDENT> return np.random.SeedSequence(entropy).generate_state(size) | Generates a sequence of most likely independent seeds. | 625941b8e5267d203edcdaec |
def _testLoadPinout(): <NEW_LINE> <INDENT> print(icGenerator.loadPinout("pinoutTest.ods")) | test for loadPinout function | 625941b8925a0f43d2549cbf |
def began_convergence_lossfun(y_true, y_pred, gamma): <NEW_LINE> <INDENT> x_hat = y_pred[..., 0] <NEW_LINE> x_hat_reconstructed = y_pred[..., 1] <NEW_LINE> x_real = y_true[..., 0] <NEW_LINE> x_real_reconstructed = y_pred[..., 2] <NEW_LINE> fake_ae_loss = K.mean(K.abs(x_hat - x_hat_reconstructed)) <NEW_LINE> real_ae_los... | y_pred[:,0]: (Gx(z))
y_pred[:,1]: D(Gx(z))
y_pred[:,2]: D(x)
y_true: x | 625941b8d18da76e2353231d |
def add_handler(self, name: str): <NEW_LINE> <INDENT> if name in self.handlers: <NEW_LINE> <INDENT> return self.handlers[name] <NEW_LINE> <DEDENT> self.handlers[name] = handler = Handler(name) <NEW_LINE> self.add_function(name, lambda nme, inp: Handler._recursive_handle(handler, nme, inp)) <NEW_LINE> return handler | If a handler hasn't been added, a new handler is created. A function is also
added in order to mimic a recursive call to handle.
If a handler has previously been addend, that instance is returned.
:param name: The name for the handler
:return: A handler | 625941b85166f23b2e1a4fa4 |
def nvidia_model_small(): <NEW_LINE> <INDENT> model = Sequential() <NEW_LINE> model.add(Conv2D(8, (5, 5), strides=(2, 2), activation="relu", input_shape=(67, 320, 1))) <NEW_LINE> model.add(Conv2D(12, (5, 5), strides=(2, 2), activation="relu")) <NEW_LINE> model.add(Conv2D(16, (5, 5), strides=(2, 2), activation="relu")) ... | Designed for single layer grayscale input. | 625941b8ad47b63b2c509dd5 |
def setmem(vm_, memory, config=False, **kwargs): <NEW_LINE> <INDENT> conn = __get_conn(**kwargs) <NEW_LINE> dom = _get_domain(conn, vm_) <NEW_LINE> if VIRT_STATE_NAME_MAP.get(dom.info()[0], "unknown") != "shutdown": <NEW_LINE> <INDENT> return False <NEW_LINE> <DEDENT> flags = libvirt.VIR_DOMAIN_MEM_MAXIMUM <NEW_LINE> i... | Changes the amount of memory allocated to VM. The VM must be shutdown
for this to work.
:param vm_: name of the domain
:param memory: memory amount to set in MB
:param config: if True then libvirt will be asked to modify the config as well
:param connection: libvirt connection URI, overriding defaults
.. versiona... | 625941b8009cb60464c63208 |
def pmf(self, k): <NEW_LINE> <INDENT> if (k > self.m) | (k != int(k)): <NEW_LINE> <INDENT> raise ValueError("k must be an integer between 0 and m, inclusive") <NEW_LINE> <DEDENT> if self.p == 1: <NEW_LINE> <INDENT> p_k = 1 if k == self.m else 0 <NEW_LINE> <DEDENT> elif self.p == 0: <NEW_LINE> <INDENT> p_k = 1 if k == 0... | Probability mass function. Uses exponents and logs to avoid overflow.
Arguments: self, ConwayMaxwellBinomial object,
k, int, must be an integer in the interval [0, m]
Returns: P(k) | 625941b8046cf37aa974cb96 |
@task <NEW_LINE> def seed_kafka(kafka_hosts="streamparse-box:9092", topic_name="pixels", num_pixels=100000): <NEW_LINE> <INDENT> kafka = KafkaClient(kafka_hosts) <NEW_LINE> producer = SimpleProducer(kafka) <NEW_LINE> puts("Seeding Kafka ({}) topic '{}' with {:,} fake pixels..." .format(kafka_hosts, topic_name, num_pixe... | Seed the local Kafka cluster's "pixels" topic with sample pixel data. | 625941b876d4e153a657e97c |
def p_c_p(t): <NEW_LINE> <INDENT> t[0] = ExpresionBinaria(t[2], t[3], OPERACION_RELACIONAL.IGUAL) <NEW_LINE> global gramatical <NEW_LINE> gramatical.append( " expresion.val := expresion.val == expresion.val") | c_p : IGUALQUE e c_p | 625941b8b7558d58953c4d67 |
def compare_timestamps(ts1: str, ts2: str) -> bool: <NEW_LINE> <INDENT> ts1_head, ts1_pred = ts1.split("_") <NEW_LINE> ts2_head, ts2_pred = ts2.split("_") <NEW_LINE> return int(ts1_head) > int(ts2_head) or int(ts1_pred) > int(ts2_pred) | Compares the timestamp of two combined timestamp strings and determines if
the first one is newer than the second one.
Args:
ts1: the first combined timestamp string
ts2: the second combined timestamp string
Returns: True if ``ts1`` is newer than ``ts2`` | 625941b87b180e01f3dc4651 |
def runBlocking(self,selector=selectors.DefaultSelector): <NEW_LINE> <INDENT> if self._is_started: <NEW_LINE> <INDENT> return <NEW_LINE> <DEDENT> self.initialize() <NEW_LINE> self.connect() <NEW_LINE> with self._selector_lock: <NEW_LINE> <INDENT> if self._is_started: <NEW_LINE> <INDENT> return <NEW_LINE> <DEDENT> self.... | Runs the client main loop in a blocking manner.
``selector`` may be changed to override the selector used for smart waiting.
This method blocks until :py:meth:`stop()` is called. | 625941b823849d37ff7b2edd |
def multi_lasso_plot(X,CO_response,ethylene_response,supress=False): <NEW_LINE> <INDENT> from sklearn import linear_model <NEW_LINE> y=[] <NEW_LINE> for i in range(0,395): <NEW_LINE> <INDENT> y.append([CO_response[i],ethylene_response[i]]) <NEW_LINE> <DEDENT> model2 = linear_model.MultiTaskLasso(alpha=1200) <NEW_LINE> ... | Multi Task Lasso
# X is the (m x n) feature vector. This can be an array or a pandas data frame.
# CO_response is the m dimensional vector with the true CO values
# ethylene_response is the m dimensional vector with the true ethylene values
#If suppress is true, the plots are supressed. | 625941b85166f23b2e1a4fa5 |
def __init__(self, explicit=False, is_run_shell=True): <NEW_LINE> <INDENT> self.platform_id = 2 <NEW_LINE> if sys.platform == 'win32': <NEW_LINE> <INDENT> self.platform_id = 0 <NEW_LINE> <DEDENT> if sys.platform == 'darwin': <NEW_LINE> <INDENT> self.platform_id = 1 <NEW_LINE> <DEDENT> info = publishinfo() <NEW_LINE> na... | 编码默认为utf8
info: 由pushlishinfo获取的元组
explicit: 弹出页面是否使用显式调用
is_run_shell: bool 是否跑生成后的start | 625941b80a50d4780f666cdb |
def _cartesian_to_llh(x, y, z, model): <NEW_LINE> <INDENT> a, _, _, e2 = ELLIPSOID_MODELS[model] <NEW_LINE> p = math.sqrt(x*x+y*y) <NEW_LINE> lam = math.atan2(y, x) <NEW_LINE> phi = math.atan2(z, p*(1-e2)) <NEW_LINE> while True: <NEW_LINE> <INDENT> sp = math.sin(phi) <NEW_LINE> nu = a / math.sqrt(1 - e2*sp*sp) <NEW_LIN... | Approximate conversion from plane to spherical coordinates.
Used as part of the Helmert transformation used outside the OSTN02
area.
>>> _cartesian_to_llh(3841039.2016489909, -201300.3346975291, 5070178.453880735, 'OSGB36')
(53.0, -3.0, 10.0) | 625941b85fdd1c0f98dc007d |
def get_Description(self): <NEW_LINE> <INDENT> return super(IServerObjectConfiguration, self).get_Description() | Method IServerObjectConfiguration.get_Description
OUTPUT
desc : BSTR* | 625941b891af0d3eaac9b860 |
def say_hi(name, age): <NEW_LINE> <INDENT> print("Hello " + name + "! you are " + age + " years old.") | name = input("Enter Name: ") | 625941b80a366e3fb873e663 |
def _select_last_modified_file(self): <NEW_LINE> <INDENT> role = self.model.DateModifiedRole <NEW_LINE> view = self.widgets["list"] <NEW_LINE> model = view.model() <NEW_LINE> highest_index = None <NEW_LINE> highest = 0 <NEW_LINE> for row in range(model.rowCount()): <NEW_LINE> <INDENT> index = model.index(row, 0, parent... | Utility function to select the file with latest date modified | 625941b855399d3f055884ff |
def test_set_new_password_for_own_user(self): <NEW_LINE> <INDENT> self.send_request('GET', 'users', username=self.testuser['username'], password=self.testuser['password']) <NEW_LINE> initial_pass = self.testuser['password'] <NEW_LINE> self.testuser['password'] = 'new_pass' <NEW_LINE> self.send_request('PUT', 'users', u... | Try to refresh the password of the current testuser. | 625941b894891a1f4081b8f4 |
def __init__(self, **kwargs) : <NEW_LINE> <INDENT> self.alphabet = None <NEW_LINE> self.creator_text = release_description <NEW_LINE> self.logo_title = "" <NEW_LINE> self.logo_label = "" <NEW_LINE> self.stacks_per_line = 40 <NEW_LINE> self.unit_name = "bits" <NEW_LINE> self.show_yaxis = True <NEW_LINE> self.yaxis_label... | Create a new LogoOptions instance.
>>> L = LogoOptions(logo_title = "Some Title String")
>>> L.show_yaxis = False
>>> repr(L) | 625941b897e22403b379cde5 |
def main(): <NEW_LINE> <INDENT> os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'orgbranchs.settings') <NEW_LINE> try: <NEW_LINE> <INDENT> from django.core.management import execute_from_command_line <NEW_LINE> <DEDENT> except ImportError as exc: <NEW_LINE> <INDENT> raise ImportError( "Couldn't import Django. Are you s... | Run administrative tasks. | 625941b8656771135c3eb6bf |
def create_thumbnail(fname, size=(100, 100), aspect_ratio=False): <NEW_LINE> <INDENT> im = Image.open(fname) <NEW_LINE> width, height = im.size <NEW_LINE> if width > height: <NEW_LINE> <INDENT> delta = width - height <NEW_LINE> left = int(delta / 2) <NEW_LINE> upper = 0 <NEW_LINE> right = height + left <NEW_LINE> lower... | @type fname: C{string}
@param: Full path to image file
@type size: C{tuple}
@param: Width and height of the thumbnail
@rtype: C{Image}
@return: Returns PIL Image object | 625941b8fb3f5b602dac34db |
def test_query_sum(self): <NEW_LINE> <INDENT> start_date = datetime(2015, 1, 1) <NEW_LINE> end_date = datetime(2016, 1, 1) <NEW_LINE> result = data_query.query_sum(self.db, ["tot_1"], start_date, end_date, 1) <NEW_LINE> self.assertEqual(result["total"], 10) <NEW_LINE> result = data_query.query_sum(self.db, ["tot_1"], s... | Test basic query_sum functionality | 625941b823e79379d52ee3b4 |
def extract_maf_wrapper(target, args): <NEW_LINE> <INDENT> accelerated_genomes = set(args.accelerated_genomes + [args.ref_genome]) <NEW_LINE> outgroup_genomes = set(args.target_genomes) - accelerated_genomes <NEW_LINE> bed_recs = [x.split() for x in open(args.conserved_bed)] <NEW_LINE> result_dir = target.getGlobalTemp... | Main pipeline wrapper. Calls out to hal2maf once for each region in args.conserved_bed | 625941b8d58c6744b4257aad |
def write(self, **kwargs): <NEW_LINE> <INDENT> return self.stub.write(**kwargs) | insert a level1 record into database
:param kwargs: Parameter dictionary, key items support:
level0_id: [str]
data_type : [str]
prc_params : [str]
filename : [str]
file_path : [str]
prc_status : [int]
prc_time : [str]
pipeline_id : [str]
refs: [dict]
:returns: csst_dfs_... | 625941b82c8b7c6e89b35610 |
def run_editor_on_exception(root_path=None, usercode_traceback=True, usercode_frame=True): <NEW_LINE> <INDENT> sys.excepthook = _get_debug_except_hook(root_path=root_path, usercode_traceback=usercode_traceback, usercode_frame=usercode_frame) | Run the editor when an unhandled exception (a fatal error) happens.
Parameters
----------
root_path : str, optional
Defaults to None (the directory of the main script).
usercode_traceback : bool, optional
Whether or not to show only the part of the traceback (error log) which corresponds to the user code.
... | 625941b83539df3088e2e197 |
def test_one_task(): <NEW_LINE> <INDENT> f = Flow(name="test") <NEW_LINE> f.add_task(get_task("x1")) <NEW_LINE> steps = f.generate_local_task_ids(_debug_steps=True) <NEW_LINE> assert count_unique_ids(steps[1]) == 1 <NEW_LINE> assert steps[1] == steps[2] == steps[3] == steps[4] == steps[5] | x1
A single task | 625941b84e4d5625662d4229 |
def allocate_structure(self,device=-1): <NEW_LINE> <INDENT> self.E = nn.Embedding( self.ref_set.lex_vocab.size(),self.embedding_size) <NEW_LINE> self.lstm = nn.LSTM(self.embedding_size, self.rnn_memory,num_layers=1,bidirectional=False) <NEW_LINE> self.W_struct_label = nn.Linear(self.rnn_memory... | This allocates the model parameters on the machine.
Args:
action_size (int): the number of action types
lex_size (int): the size of the lexicon vocabulary
struct_size (int): the size of the non terminal vocabulary
rnn_memory (int): the size of the rnn hidden memory
embedding_size(int): the e... | 625941b83346ee7daa2b2bb5 |
def onConnectionPrompt(prompt, state, logger): <NEW_LINE> <INDENT> prompt = prompt.lower() <NEW_LINE> state.setdefault('triedPassword', 0) <NEW_LINE> state.setdefault('triedKeys', {}) <NEW_LINE> if 'enter passphrase for key' in prompt: <NEW_LINE> <INDENT> key = re.findall( r'key \'(.+)\':\s*$', prompt, flags = re.IGNOR... | :type prompt: str
:type state: dict[str, object]
:type logger: logging.Logger
:rtype: str|None | 625941b8090684286d50eb2c |
@patchmethod(tf.Tensor, tf.Variable) <NEW_LINE> def padaxis(t, paddings, axis, mode='CONSTANT', name=None): <NEW_LINE> <INDENT> if isinstance(axis, int): <NEW_LINE> <INDENT> axis = (axis,) <NEW_LINE> if len(paddings) == 2: <NEW_LINE> <INDENT> paddings = [paddings] <NEW_LINE> <DEDENT> assert len(axis) == len(paddings) <... | t.pad((1,1), axis=0) # padleft, padright
t.pad([(1,1), (1,1)], axis=[0,1]) # padleft, right, top, bottom
:param t:
:param paddings:
:param axis:
:param mode:
:return: | 625941b8dd821e528d63aff7 |
def test_role_edit_audit_errors(self): <NEW_LINE> <INDENT> admin_session = self.get_session('admin') <NEW_LINE> admin_session.edit('matholymprole', '1', {'room_types': ['Single room'], 'default_room_type': 'Shared room'}, error='Default room type not in permitted ' 'room types') | Test errors from role edit auditor. | 625941b823849d37ff7b2ede |
def move_const_torque(self, torque, **kwargs): <NEW_LINE> <INDENT> assert self._current_pos_enc is not None, ( "Home the actuator before attempting to move") <NEW_LINE> self.set_max_torque(torque, chain=True) <NEW_LINE> self.torque_mode(chain=True) <NEW_LINE> self.go(**kwargs) | Make the actuator maintain a constant torque output, units match
read_torque return value. | 625941b87d847024c06be10c |
def guest_live_upload(self, guestaddr, file_to_upload, destination, timeout=10): <NEW_LINE> <INDENT> self.guest_execute_command(guestaddr, "mkdir -p " + os.path.dirname(destination), timeout) <NEW_LINE> return oz.ozutil.subprocess_check_output(["scp", "-i", self.sshprivkey, "-F", "/dev/null", "-o", "ServerAliveInterval... | Method to copy a file to the live guest. | 625941b8c4546d3d9de7287c |
def parse_ini( source: typing.Union[str, Path, typing.TextIO], intent_filter: typing.Optional[typing.Callable[[str], bool]] = None, sentence_transform: typing.Callable[[str], str] = None, file_name: typing.Optional[str] = None, ) -> IntentsType: <NEW_LINE> <INDENT> intent_filter = intent_filter or (lambda x: True) <NEW... | Parse multiple JSGF grammars from an ini file. | 625941b8287bf620b61d38bb |
def kraken_results_df_creator(kraken_hits, rds_or_cntgs): <NEW_LINE> <INDENT> dict_hits = {} <NEW_LINE> k = 1 <NEW_LINE> for i in range(0, len(kraken_hits)): <NEW_LINE> <INDENT> dict_hits['sp_krkn'+str(k)+'_'+rds_or_cntgs] = kraken_hits[i][5].lstrip() <NEW_LINE> dict_hits['sp_krkn'+str(k)+'_'+rds_or_cn... | Take the 2D array from a kraken search and return result as a dictionary. | 625941b876e4537e8c3514c4 |
def likelihood(data, theta): <NEW_LINE> <INDENT> mu = theta['mu'] <NEW_LINE> tau = theta['tau'] <NEW_LINE> p = theta['p'] <NEW_LINE> lam = theta['lam'] <NEW_LINE> n_cts = len(mu) <NEW_LINE> n_bin = len(p) <NEW_LINE> n_ord = len(lam) <NEW_LINE> product = 1 <NEW_LINE> if isinstance(data, pd.DataFrame): <NEW_LINE> <INDENT... | Calculates likelihood
:param data: the data
:type data: pd.DataFrame or pd.Series
:param parameters theta: parameters of the distributions
:return: P(data|theta)
:rtype: 0<=float<=1 | 625941b832920d7e50b28018 |
def __init__(self, flask_app, url, server_token): <NEW_LINE> <INDENT> self.server_token = server_token <NEW_LINE> self.error_reply = nothing_reply <NEW_LINE> self.text_match_registry = {} <NEW_LINE> self.text_re_match_registry = [] <NEW_LINE> self.msg_registry = {} <NEW_LINE> self.event_registry = {} <NEW_LINE> flask_a... | A wechat server.
:param flask_app:
:param url: register url to handle.
:param server_token: wechat's server token.
:return: | 625941b8e8904600ed9f1d75 |
def __train_tree(self): <NEW_LINE> <INDENT> train_on = 15 <NEW_LINE> if len(self.history) > train_on: <NEW_LINE> <INDENT> f = -train_on <NEW_LINE> <DEDENT> else: <NEW_LINE> <INDENT> f = 0 <NEW_LINE> <DEDENT> for cont in self.history[f:]: <NEW_LINE> <INDENT> if not cont.result: <NEW_LINE> <INDENT> continue <NEW_LINE> <D... | L.__train_tree() -> None -- update short & long memory and build new tree and test old and new | 625941b838b623060ff0ac3b |
def sendGetMessage(url, cookiename, callback): <NEW_LINE> <INDENT> request = {"action": "getCookie", "url": url, "cookieName": cookiename} <NEW_LINE> chrome.runtime.sendMessage(request, callback) | broadcast a cookie get request. | 625941b8f9cc0f698b140452 |
def test_no_displacement(self): <NEW_LINE> <INDENT> self.logTestName() <NEW_LINE> mag_alpha = 0. <NEW_LINE> for phase_alpha in phase_alphas: <NEW_LINE> <INDENT> alpha = mag_alpha * np.exp(1j * phase_alpha) <NEW_LINE> self.circuit.reset(pure=self.kwargs['pure']) <NEW_LINE> self.circuit.displacement(alpha, 0) <NEW_LINE> ... | Tests displacement operation in some limiting cases where the result should be a vacuum state. | 625941b856b00c62f0f144aa |
def put(self,key,value,ex=60 * 60 * 24 * 5): <NEW_LINE> <INDENT> self.redis.set(key, value,ex=ex) | ex:默认过期时间为5天，如果一个task 5天都没有跑完，直接丢弃记录 | 625941b87cff6e4e811177d3 |
def normalise(self): <NEW_LINE> <INDENT> _, θ = self.polar() <NEW_LINE> return Vector.from_polar(1, θ) | return a normalised unit vector | 625941b866673b3332b91ee4 |
def handle_getperms(bot, ievent): <NEW_LINE> <INDENT> try: name = ievent.args[0] <NEW_LINE> except IndexError: <NEW_LINE> <INDENT> ievent.missing('<name>') <NEW_LINE> return <NEW_LINE> <DEDENT> name = name.lower() <NEW_LINE> if not bot.users.exist(name): <NEW_LINE> <INDENT> ievent.reply("can't find user %s" % name) <NE... | arguments: <name> - get permissions of name. | 625941b830bbd722463cbc0f |
def draw_network(graph, filename = 'network.pdf', show = False, verbose = 2 ): <NEW_LINE> <INDENT> if verbose >=2: <NEW_LINE> <INDENT> print(".. Saving the network down as an image") <NEW_LINE> <DEDENT> if verbose >=3 : <NEW_LINE> <INDENT> print("... Coverting to dot") <NEW_LINE> <DEDENT> dot = to_pydot(graph) <NEW_LIN... | This is a simple wrapper to the networkx_draw.
Args:
graph: Supply a networkx graph object. NNs are all DiGraphs.
filename: what file to save down as. Will add '.png' to the end.
verbose: Do I even have to talk about this ?
Notes:
Takes any format that networkx plotter takes. This is not ready to be u... | 625941b8460517430c393fdb |
def invokeFactory(self, type_name, id, RESPONSE=None, *args, **kw): <NEW_LINE> <INDENT> constrains = IConstrainTypes(self, None) <NEW_LINE> if constrains: <NEW_LINE> <INDENT> allowed_ids = [ fti.getId() for fti in constrains.allowedContentTypes() ] <NEW_LINE> if type_name not in allowed_ids: <NEW_LINE> <INDENT> raise V... | Invokes the portal_types tool
| 625941b80383005118ecf431 |
def get_all_balances_paged(self, limit=None, page=None): <NEW_LINE> <INDENT> data = {} <NEW_LINE> if limit: <NEW_LINE> <INDENT> data['limit'] = limit <NEW_LINE> <DEDENT> if page: <NEW_LINE> <INDENT> data['page'] = page <NEW_LINE> <DEDENT> return self._get('account/balances', True, data=data) | Get all coin balances with paging if that's what you want
https://kucoinapidocs.docs.apiary.io/#reference/0/assets-operation/get-all-balance
:param limit: optional - Number of balances default 12, max 20
:type limit: int
:param page: optional - Page to fetch
:type page: int
.. code:: python
# get the default re... | 625941b84a966d76dd550e59 |
def run(self, force=False): <NEW_LINE> <INDENT> if self.solution['results'] is not None and not force: <NEW_LINE> <INDENT> return <NEW_LINE> <DEDENT> master_results = np.zeros_like(np.arange(self._starts[0], self._stops[0], self._skip), dtype=np.float32) <NEW_LINE> counter = np.zeros_like(master_results, dtype=np.float... | Run all the required passes
Parameters:
-----------
force : bool, optional
Will overwrite previous results if they exist | 625941b89b70327d1c4e0c20 |
def fix_on_leg(self, fix, leg): <NEW_LINE> <INDENT> larger_than_minimum = not self.fix_before_leg(fix, leg) <NEW_LINE> smaller_than_maximum = not self.fix_after_leg(fix, leg) <NEW_LINE> return larger_than_minimum and smaller_than_maximum | Return whether fix takes place within certain leg, excluding the boundaries
:param fix:
:param leg:
:return: | 625941b8cc40096d615957a0 |
def test_topology_normalization(topology_with_dupl_links, normalized_topology_example): <NEW_LINE> <INDENT> top_with_data = task_25_1c.Topology(topology_with_dupl_links) <NEW_LINE> assert len(top_with_data.topology) == len(normalized_topology_example) | Проверка удаления дублей в топологии | 625941b8377c676e91271ff7 |
def wait(self, expect=0): <NEW_LINE> <INDENT> if expect > 0: <NEW_LINE> <INDENT> raise AssertionError('expect <= 0') <NEW_LINE> <DEDENT> if expect == 0 and len(self.buffer) > 0: <NEW_LINE> <INDENT> return self.pop() <NEW_LINE> <DEDENT> while True: <NEW_LINE> <INDENT> s = self.ch_in.readline() <NEW_LINE> self.logger.inf... | Blocking function. Use with care!
`expect` should either be 0 or a negative number. If `expect == 0`, any positive
indexed object is returned. Otherwise, it will queue any positive objects until the
first negative object is received. If the received negative object does not match
`expect`, then a ValueError is raised. | 625941b838b623060ff0ac3c |
def __init__(self, name=None, value=None): <NEW_LINE> <INDENT> self._name = None <NEW_LINE> self._value = None <NEW_LINE> self.discriminator = None <NEW_LINE> if name is not None: <NEW_LINE> <INDENT> self.name = name <NEW_LINE> <DEDENT> if value is not None: <NEW_LINE> <INDENT> self.value = value | ScreenRecordingFilterPageViewReferrerParam - a model defined in Swagger | 625941b8099cdd3c635f0aa9 |
def add_nzb(self, filename, content=None, category=None, priority=PRIORITY.NORMAL): <NEW_LINE> <INDENT> if not self.api_connect(): <NEW_LINE> <INDENT> return None <NEW_LINE> <DEDENT> add_to_top = False <NEW_LINE> add_paused = False <NEW_LINE> dup_key = '' <NEW_LINE> dup_score = 0 <NEW_LINE> dup_mode = NZBGetDuplicateMo... | Simply add's an NZB file to NZBGet (via the API)
| 625941b857b8e32f524832ed |
def leafSimilar(self, root1, root2): <NEW_LINE> <INDENT> def dfs(node, lst): <NEW_LINE> <INDENT> if not node.left and not node.right: <NEW_LINE> <INDENT> lst.append(node.val) <NEW_LINE> return <NEW_LINE> <DEDENT> if node.left: <NEW_LINE> <INDENT> dfs(node.left, lst) <NEW_LINE> <DEDENT> if node.right: <NEW_LINE> <INDENT... | :type root1: TreeNode
:type root2: TreeNode
:rtype: bool | 625941b8d99f1b3c44c673e4 |
def check_for_password_before_cmdlist_func_call(*args, **kwargs): <NEW_LINE> <INDENT> util.log_info("... cmdlist_func = %s %s" % (archive_cmdlist_func, '')) <NEW_LINE> util.log_info("... kwargs=%s args=%s" % (kwargs, args)) <NEW_LINE> if 'password' in kwargs and kwargs['password'] is None: <NEW_LINE> <INDENT> kwargs.po... | If password is None, or not set, run command as usual.
If password is set, but can't be accepted raise appropriate
message. | 625941b8fbf16365ca6f6009 |
@pytest.fixture(scope="module") <NEW_LINE> def inertialbase_objects_rt(dcm, mem): <NEW_LINE> <INDENT> dico = {} <NEW_LINE> coord = ["X", "Y", "Z"] <NEW_LINE> for each in coord: <NEW_LINE> <INDENT> dico["Acc" + each] = InertialSensorBase( dcm, mem, "Accelerometer" + each) <NEW_LINE> dico["Angle" + each] = InertialSensor... | Return a dictionary with several objects for
each sensor value of the inertial base | 625941b810dbd63aa1bd29fc |
def create_deck(self, user_id, deck_name): <NEW_LINE> <INDENT> url = f'http://127.0.0.1:5000//Server/create_deck/{user_id}' <NEW_LINE> data = {deck_name: ''} <NEW_LINE> response = requests.post(url, json=data) <NEW_LINE> print(response.json()) | Создание колоды | 625941b8d7e4931a7ee9dd68 |
@deprecated( "2016-11-30", "Please switch to tf.summary.image. Note that " "tf.summary.image uses the node name instead of the tag. " "This means that TensorFlow will automatically de-duplicate summary " "names based on the scope they are created in. Also, the max_images " "argument was renamed to max_outputs.") <NEW_L... | Outputs a `Summary` protocol buffer with images.
For an explanation of why this op was deprecated, and information on how to
migrate, look ['here'](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/contrib/deprecated/__init__.py)
The summary has up to `max_images` summary values containing images. The
i... | 625941b8090684286d50eb2d |
def show_conv_to_rve(self): <NEW_LINE> <INDENT> self.convert_to_rve_widget = ConvertSegForRVEWidget() <NEW_LINE> self.convert_to_rve_widget.show() | show window to convert segmentations
to RhizoVision Explorer compatible format | 625941b850485f2cf553cbe6 |
def pthread_self(): <NEW_LINE> <INDENT> f = gdb.newest_frame() <NEW_LINE> while f.name() != 'start_thread': <NEW_LINE> <INDENT> f = f.older() <NEW_LINE> if f is None: <NEW_LINE> <INDENT> return get_fs_base() <NEW_LINE> <DEDENT> <DEDENT> try: <NEW_LINE> <INDENT> return f.read_var("arg") <NEW_LINE> <DEDENT> except ValueE... | Fetch pthread_self() from the glibc start_thread function. | 625941b8ab23a570cc24ffcd |
def GetTitleString(self): <NEW_LINE> <INDENT> fname = self.GetFileName() <NEW_LINE> title = os.path.split(fname)[-1] <NEW_LINE> if not len(title): <NEW_LINE> <INDENT> title = fname = self.GetTabLabel() <NEW_LINE> <DEDENT> if self.GetModify() and not title.startswith(u'*'): <NEW_LINE> <INDENT> title = u"*" + title <NEW_... | Get the title string to display in the MainWindows title bar
@return: (unicode) string | 625941b8fff4ab517eb2f286 |
def commit_counts(self, session): <NEW_LINE> <INDENT> limit = 1 <NEW_LINE> if self.cpt >= limit: <NEW_LINE> <INDENT> session.commit() <NEW_LINE> self.cpt = 0 | Commits data to db if enough data has to be updated
FIXME: By not commiting every time, we might have duplicates
if the same guy tweets several times with the same flag | 625941b8498bea3a759b98fe |
def get_version(request): <NEW_LINE> <INDENT> if 'jsonrpc' in request: <NEW_LINE> <INDENT> return 2.0 <NEW_LINE> <DEDENT> elif 'id' in request: <NEW_LINE> <INDENT> return 1.0 <NEW_LINE> <DEDENT> return None | Computes the JSON-RPC version
:param request: A request dictionary
:return: The JSON-RPC version or None | 625941b85e10d32532c5ed7c |
def __iter__(self): <NEW_LINE> <INDENT> return iter(self._item) | 调用迭代环境时返回迭代器 | 625941b86fece00bbac2d588 |
def get_default_params(type='BSPLINE'): <NEW_LINE> <INDENT> p = Parameters() <NEW_LINE> type = type.upper() <NEW_LINE> p.Metric = 'AdvancedMattesMutualInformation' <NEW_LINE> p.NumberOfHistogramBins = 32 <NEW_LINE> p.ImageSampler = 'RandomCoordinate' <NEW_LINE> p.NumberOfSpatialSamples = 2048 <NEW_LINE> p.NewSamplesEve... | get_default_params(type='BSPLINE')
Get `Parameters` struct with parameters that users may want to tweak.
The given `type` specifies the type of allowed transform, and can
be 'RIGID', 'AFFINE', 'BSPLINE'.
For detail on what parameters are available and how they should be used,
we refer to the Elastix documentation. He... | 625941b885dfad0860c3aca6 |
def matches(self, jira_connection: 'JiraConnection', find: str) -> bool: <NEW_LINE> <INDENT> if self.jira_connection_name == jira_connection.connection_name: <NEW_LINE> <INDENT> if find in self.issue_key: <NEW_LINE> <INDENT> return True <NEW_LINE> <DEDENT> for value in list(self.values()): <NEW_LINE> <INDENT> if find i... | Tests all values in the ticket to see if they match the input string.
Requires input of the JiraConnection you want to compare against to protect against
duplicate project names across different JIRA instances. | 625941b8b545ff76a8913c6c |
def die(msg, *args): <NEW_LINE> <INDENT> error(msg, *args) <NEW_LINE> sys.exit(1) | Print as error message to stderr and exit the program. | 625941b831939e2706e4ccbd |
def delete(self, item_id, comment_id): <NEW_LINE> <INDENT> auth, retval = __check_auth__(self.auth_dict) <NEW_LINE> if auth: <NEW_LINE> <INDENT> return retval <NEW_LINE> <DEDENT> query = ItemComment.query.filter(ItemComment.id == comment_id) <NEW_LINE> query = query.filter(ItemComment.user_id == current_user.id).delete... | .. http:delete:: /api/1/items/<int:item_id>/comment/<int:comment_id>
Deletes an item comment.
**Example Request**:
.. sourcecode:: http
DELETE /api/1/items/1234/comment/7718 HTTP/1.1
Host: example.com
Accept: application/json
{
}
**Example Response**:
.. sourcecode:: http
HTTP/1.1 202 OK... | 625941b826068e7796caeb25 |
def _after_init(self, _): <NEW_LINE> <INDENT> username = password = None <NEW_LINE> if creds is not None: <NEW_LINE> <INDENT> username, password = creds.username, creds.password <NEW_LINE> <DEDENT> if username is None: <NEW_LINE> <INDENT> pass <NEW_LINE> <DEDENT> if username is not None: <NEW_LINE> <INDENT> callback = ... | Get password | 625941b8dc8b845886cb5381 |
def borrow_book(self, book, patron): <NEW_LINE> <INDENT> patron.add_borrowed_book(book.lower()) <NEW_LINE> self.db.update_patron(patron) | Borrows a book for a Patron.
:param book: the title of the book
:param patron: the Patron object | 625941b88c0ade5d55d3e80c |
def OnInit(self): <NEW_LINE> <INDENT> self.SetAppName('CEBL') <NEW_LINE> main = CEBLMain() <NEW_LINE> return True | Create a new CEBLMain frame.
| 625941b8d164cc6175782b9b |
def test_nets(self): <NEW_LINE> <INDENT> good_nets = self.good.nets[:] <NEW_LINE> self.assertEqual(len(good_nets), 5) <NEW_LINE> for net in self.actual.nets: <NEW_LINE> <INDENT> for goodnet in good_nets: <NEW_LINE> <INDENT> if set(net.points) == set(goodnet.points): <NEW_LINE> <INDENT> good_nets.remove(goodnet) <NEW_LI... | Test that all the right nets are present with
the right points. | 625941b81d351010ab85596b |
def get_stdev(nums): <NEW_LINE> <INDENT> pass | Helper function for calculating the standard deviation of a list of numbers.
:param nums: list of numbers
:return: standard deviation of list | 625941b8d268445f265b4cc2 |
def schedule_teleport(self, position, map_id=None, *map_args): <NEW_LINE> <INDENT> if map_id is not None: <NEW_LINE> <INDENT> self.world.schedule_teleport(position, map_id, *map_args) <NEW_LINE> self.controller.stop() <NEW_LINE> <DEDENT> else: <NEW_LINE> <INDENT> self.teleport_object(self.party_avatar, position) | After the current iteration of the WorldMap's context stack, the
party will be teleported to the WorldMap represented by *map_id*
at *position*.
This method may also be used to teleport to another place in the
same map, by passing None. If the map id of the current map is
passed, the party will be removed and added to... | 625941b8796e427e537b040f |
def identify(self, authority, **kwds): <NEW_LINE> <INDENT> return authority.onDescriptor(descriptor=self, **kwds) | Let {authority} know I am a descriptor | 625941b80c0af96317bb8036 |
def show_softclip(self): <NEW_LINE> <INDENT> bsoftclip = self.gamma.bsoftclip <NEW_LINE> if isinstance(bsoftclip, dict): <NEW_LINE> <INDENT> paramstr = ', '.join('{!s}={!r}'.format(key, val) for (key, val) in bsoftclip.items()) <NEW_LINE> <DEDENT> else: <NEW_LINE> <INDENT> paramstr = bsoftclip <NEW_LINE> <DEDENT> retur... | Return softclip start value(s) to show in menu | 625941b829b78933be1e5506 |
def get_auto_login_url(self, url, name, token, login_type): <NEW_LINE> <INDENT> login_type = constants.ClassRoomAutoLoginType(login_type) <NEW_LINE> if login_type in ( constants.ClassRoomAutoLoginType.record, constants.ClassRoomAutoLoginType.audience, ): <NEW_LINE> <INDENT> return '{}&autoLogin=true&viewername={}&viewe... | url 为 room_link 中拿到的各个url,
教师端:
https://class.csslcloud.net/index/presenter/?roomid=FC3548C1133061D09C33DC5901307461&userid=E9607DAFB705A798&username=XXX&password=XXX&autoLogin=true
互动者:
https://class.csslcloud.net/index/talker/?roomid=FC3548C1133061D09C33DC5901307461&userid=E9607DAFB705A798&username=XXX&passwo... | 625941b894891a1f4081b8f5 |
def getPercCpuLoad(self): <NEW_LINE> <INDENT> return int(self.getCpuLoad() * 100.0) | Metoda vrací vytížení procesoru v procentech 0 až 100
\param self Ukazatel na objekt
eturn Procento mezi 0 až 100 | 625941b8de87d2750b85fbdb |
def _test_expected_for_job(self, expected_results, job): <NEW_LINE> <INDENT> results = {} <NEW_LINE> with job.make_runner() as runner: <NEW_LINE> <INDENT> runner.run() <NEW_LINE> for line in runner.stream_output(): <NEW_LINE> <INDENT> key, value = job.parse_output_line(line) <NEW_LINE> results[key] = value <NEW_LINE> <... | Simple utility function to test results are as expected | 625941b8cb5e8a47e48b78fd |
def process_mptcp_pkt_from_server(ts_delta, acks, conn_acks, mptcp_connections, tcp, ip, saddr, daddr, sport, dport): <NEW_LINE> <INDENT> dss, dack, dss_is_8_bytes = get_dss_and_data_ack(tcp) <NEW_LINE> conn_id = acks[daddr, dport, saddr, sport][co.CONN_ID] <NEW_LINE> flow_id = acks[daddr, dport, saddr, sport][co.FLOW_... | Process a packet with ACK set from the server for the MPTCP DSS retransmissions | 625941b823e79379d52ee3b5 |
def SetFullyConnected(self, *args): <NEW_LINE> <INDENT> return _itkOpeningByReconstructionImageFilterPython.itkOpeningByReconstructionImageFilterID3ID3SE3_SetFullyConnected(self, *args) | SetFullyConnected(self, bool _arg) | 625941b863f4b57ef0000f70 |
def query_block_height(height, bestblock=False): <NEW_LINE> <INDENT> if height < 0: <NEW_LINE> <INDENT> return <NEW_LINE> <DEDENT> if not bestblock: <NEW_LINE> <INDENT> kwargs = {'method': 'getblockhash', 'params': [height]} <NEW_LINE> <DEDENT> else: <NEW_LINE> <INDENT> kwargs = {'method': 'getbestblockhash'} <NEW_LINE... | Return a block by its height.
:param bool bestblock: if True, will ignore the heigh param
and return the most recent block. | 625941b830bbd722463cbc10 |
def delDoor(self, ctrllerMac, doorId): <NEW_LINE> <INDENT> doorId = str(doorId).encode('utf8') <NEW_LINE> msg = CUD + b'P' + b'D' + b'{"id": ' + doorId + b'}' + END <NEW_LINE> try: <NEW_LINE> <INDENT> self.netMngr.sendToCtrller(msg, ctrllerMac) <NEW_LINE> <DEDENT> except CtrllerDisconnected: <NEW_LINE> <INDENT> self.lo... | Receives the controller MAC and the door ID.
With them it creates the message to send it to controller (to delete).
It gives the created message to the network manager thread. | 625941b8796e427e537b0410 |
def url__cinema_regulate__open_ticket(self, apply_data: dict, remark_info: dict = None) -> bool: <NEW_LINE> <INDENT> uid = self.session.uid <NEW_LINE> flow_id = chv.OPEN_FLOW <NEW_LINE> apply_name = "开业申请" <NEW_LINE> remark_info = self.ckt.deal_remark_info(remark_info) <NEW_LINE> user, cinema_code = self.ckt.get_cinema... | 开业申请 | 625941b8a8ecb033257d2f23 |
def get_estimation_schema(): <NEW_LINE> <INDENT> schema = TASKSCHEMA.clone() <NEW_LINE> schema['lines']['lines'].doctype = "estimation" <NEW_LINE> tmpl = 'autonomie:deform_templates/paymentdetails_item.pt' <NEW_LINE> schema.add_before( 'communication', TaskNotes(title=u"Notes", name="notes"), ) <NEW_LINE> schema.add_be... | Return the schema for estimation add/edit | 625941b8097d151d1a222ca9 |
def purge_csv(self, name='log.csv'): <NEW_LINE> <INDENT> f = open(name,'w') <NEW_LINE> f.close() | Purge the data from the staging csv file
Parameters
----------
name : `string`
The name of the csv file that you want to log | 625941b8b7558d58953c4d69 |
def __init__(self, hass, device_id, friendly_name, unit_of_measurement, state_template): <NEW_LINE> <INDENT> self.hass = hass <NEW_LINE> self.entity_id = generate_entity_id(ENTITY_ID_FORMAT, device_id, hass=hass) <NEW_LINE> self._name = friendly_name <NEW_LINE> self._unit_of_measurement = unit_of_measurement <NEW_LINE>... | Initialize the sensor. | 625941b8f548e778e58cd3c9 |
def __utf_to_caps_func(self, line): <NEW_LINE> <INDENT> utf_text = line[17:-1] <NEW_LINE> if self.__caps_list[-1] == 'true' and self.__convert_caps: <NEW_LINE> <INDENT> utf_text = self.__utf_token_to_caps_func(utf_text) <NEW_LINE> <DEDENT> self.__write_obj.write('tx<ut<__________<%s\n' % utf_text) | Required:
line -- line to parse
returns
nothing
Logic
Get the text, and use another method to convert | 625941b83c8af77a43ae35ec |
def test_successful_modify_percent_snapshot_space(self): <NEW_LINE> <INDENT> data = self.mock_args() <NEW_LINE> data['percent_snapshot_space'] = '90' <NEW_LINE> set_module_args(data) <NEW_LINE> with pytest.raises(AnsibleExitJson) as exc: <NEW_LINE> <INDENT> self.get_volume_mock_object('volume').apply() <NEW_LINE> <DEDE... | Test successful modify percent_snapshot_space | 625941b8d6c5a10208143e95 |
def get_sec_group(name=None, region=None, secgroup_id=None, tenant_id=None): <NEW_LINE> <INDENT> __args__ = dict() <NEW_LINE> __args__['name'] = name <NEW_LINE> __args__['region'] = region <NEW_LINE> __args__['secgroupId'] = secgroup_id <NEW_LINE> __args__['tenantId'] = tenant_id <NEW_LINE> __ret__ = pulumi.runtime.inv... | Use this data source to get the ID of an available OpenStack security group. | 625941b821bff66bcd6847a3 |
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