code stringlengths 4 4.48k | docstring stringlengths 1 6.45k | _id stringlengths 24 24 |
|---|---|---|
def parse_file(filename): <NEW_LINE> <INDENT> with open(filename, "r") as f: <NEW_LINE> <INDENT> data = [[float(y) for y in x.strip().split(" ")] for x in f] <NEW_LINE> data[0] = [int(x) for x in data[0]] <NEW_LINE> return data | This function is provided to you as an example of the preprocessing we do
prior to calling run_train_test | 625941cd99fddb7c1c9de4ad |
def dialog_info(self, title, message): <NEW_LINE> <INDENT> box = QMessageBox() <NEW_LINE> box.setWindowTitle(title) <NEW_LINE> box.setText(message) <NEW_LINE> box.exec_() | Generic Qt Message box
Arg 1: the window title <string>
Arg 2: the message <string> | 625941cd10dbd63aa1bd2cc0 |
def drop_question(self, name): <NEW_LINE> <INDENT> if name in self.keys(): <NEW_LINE> <INDENT> del self[name] <NEW_LINE> self.columns = list(self.keys()) <NEW_LINE> self._update_log(command='remove question', column=name) | Removes a dictionary entry for the specified column.
Parameters
----------
name: str
The name of the dictionary column to be returned | 625941cdd18da76e235325f3 |
def enhance_projs_aps_1id(imgstack, median_ks=5, ncore=None): <NEW_LINE> <INDENT> ncore = mproc.mp.cpu_count()-1 if ncore is None else ncore <NEW_LINE> tmp = [] <NEW_LINE> with cf.ProcessPoolExecutor(ncore) as e: <NEW_LINE> <INDENT> for n_img in range(imgstack.shape[0]): <NEW_LINE> <INDENT> tmp.append(e.submit(_enhance... | Enhance the projection images with weak contrast collected at APS 1ID
This filter uses a median fileter (will be switched to enhanced recursive
median fileter, ERMF, in the future) for denoising, and a histogram
equalization for dynamic range adjustment to bring out the details.
Parameters
----------
imgstack : np.... | 625941cda8ecb033257d31ea |
def call(self, inputs, reset_mask, initial_state=None): <NEW_LINE> <INDENT> if initial_state is None and self.dtype is None: <NEW_LINE> <INDENT> raise ValueError("Must provide either dtype or initial_state") <NEW_LINE> <DEDENT> inputs = tf.nest.map_structure(common.transpose_batch_time, inputs) <NEW_LINE> inputs_flat =... | Perform the computation.
Args:
inputs: A tuple containing tensors in batch-major format,
each shaped `[batch_size, n, ...]`.
reset_mask: A `bool` matrix shaped `[batch_size, n]`, describing the
locations for which the state will be reset to zeros. Typically this is
the value `time_steps.is_first()` wh... | 625941cd3617ad0b5ed68014 |
def columns(self) -> [str]: <NEW_LINE> <INDENT> return () | Return list of columns required/defined by this statement. | 625941cdb5575c28eb68e11d |
def test_merge(): <NEW_LINE> <INDENT> list1 = [13, 11, 9, 7, 5, 3, 1] <NEW_LINE> list2 = [14, 12, 10, 8, 6, 4, 2] <NEW_LINE> result = list(util.merge([list1, list2])) <NEW_LINE> assert result[::-1] == sorted(result) | This should return a sorted (from greatest to least) merged list
from list1 and list2. | 625941cdbde94217f3682f0e |
def get_build_source_upload_url( self, resource_group_name, registry_name, custom_headers=None, raw=False, **operation_config): <NEW_LINE> <INDENT> api_version = "2018-02-01-preview" <NEW_LINE> url = self.get_build_source_upload_url.metadata['url'] <NEW_LINE> path_format_arguments = { 'subscriptionId': self._serialize.... | Get the upload location for the user to be able to upload the source.
:param resource_group_name: The name of the resource group to which
the container registry belongs.
:type resource_group_name: str
:param registry_name: The name of the container registry.
:type registry_name: str
:param dict custom_headers: header... | 625941cd97e22403b379d0b6 |
@blueprint.route('/delete/<use_cace_id>', methods=['GET', 'POST']) <NEW_LINE> def delete(use_cace_id): <NEW_LINE> <INDENT> if not ObjectId.is_valid(use_cace_id): <NEW_LINE> <INDENT> return init_return({}, sucess=False, error="用例id参数错误", errorCode=1001) <NEW_LINE> <DEDENT> result = UseCase.objects(id=ObjectId(use_cace_i... | 5 根据用例id
:param: use_cace_id
:return: | 625941cdfb3f5b602dac37b0 |
def test_video_task_chain(mocker): <NEW_LINE> <INDENT> def ctx(): <NEW_LINE> <INDENT> return celery.app.task.Context( { "lang": "py", "task": "cloudsync.tasks.stream_to_s3", "id": "1853b857-84d8-4af4-8b19-1c307c1e07d5", "chain": [ { "task": "cloudsync.tasks.transcode_from_s3", "args": [351], "kwargs": {}, "options": {"... | Test that video task get_task_id method returns the correct id from the chain. | 625941cd32920d7e50b282ed |
def main(thread, email, pwd, links, names, file, save_path, count_total, counts): <NEW_LINE> <INDENT> print("\033[H\033[J") <NEW_LINE> one_thread = detect_one_thread(counts, links, 0) <NEW_LINE> start = FileJoker(email, pwd, links, names, file, save_path, thread, count_total, one_thread) <NEW_LINE> with futures.ThreadP... | for e, url in zip(counts, links):
FileJoker(email, pwd, url, names, file, save_path, thread, count_total, e) | 625941cd0a366e3fb873e937 |
def draw_node(draw, tree, x, y): <NEW_LINE> <INDENT> if tree.results is None: <NEW_LINE> <INDENT> w1 = get_width(tree.tb) * 100 <NEW_LINE> w2 = get_width(tree.fb) * 100 <NEW_LINE> left = x - (w1 + w2) / 2 <NEW_LINE> right = x + (w1 + w2) / 2 <NEW_LINE> draw.text((x - 20, y - 10), ('feature' + str(tree.col) + ':' + str(... | 实际绘制决策树的节点，递归工作
:param draw:
:param tree:
:param x:
:param y:
:return: | 625941cd5510c4643540f501 |
def do_zpj_distributions(root_dir, dir_append=""): <NEW_LINE> <INDENT> dir_names = ["ZPlusJets_Presel_q", "ZPlusJets_Presel_g", "ZPlusJets_Presel_unknown"][:2] <NEW_LINE> dir_names = [d+dir_append for d in dir_names] <NEW_LINE> root_file = cu.open_root_file(os.path.join(root_dir, qgc.DY_FILENAME)) <NEW_LINE> directorie... | Do plots comparing different jet flavs in z+jets region | 625941cdadb09d7d5db6c8ac |
def purchase_pr_with_haircut(self, haircut_perc=None): <NEW_LINE> <INDENT> if not haircut_perc: <NEW_LINE> <INDENT> return self.start_payment() <NEW_LINE> <DEDENT> return self.start_payment() * (1.0 - haircut_perc * 0.01) | Calculate repo start payment with haircut.
Parameters
----------
haircut_perc: float, optional
A float which specifies the haircut (in percent) of purchase price.
Default is None.
Returns
-------
float
The purchase price of repo.
Examples
--------
>>> repo_test = Repo(settlement=date(2020,7,15), maturit... | 625941cd63d6d428bbe4460c |
def write_data(uuid, data): <NEW_LINE> <INDENT> try: <NEW_LINE> <INDENT> CACHE.set( "{}{}".format(Keys.complete.value, uuid), codecs.decode( base64.b64encode(compress(codecs.encode( ujson.dumps(data), "utf-8", ))), "utf-8", ), timeout=EXPIRY, ) <NEW_LINE> <DEDENT> except Exception as error: <NEW_LINE> <INDENT> LOG.warn... | Try to store the data, log errors. | 625941cd8a43f66fc4b54182 |
def _generate_level(self): <NEW_LINE> <INDENT> level = 0 <NEW_LINE> while True: <NEW_LINE> <INDENT> if random.random() <= 0.5: <NEW_LINE> <INDENT> break <NEW_LINE> <DEDENT> level += 1 <NEW_LINE> <DEDENT> return level | Private help method for insert. It generates the the level for an
element to be inserted by randomness. The probability of level x is
(1/2)^x. | 625941cda79ad161976cc263 |
def generate_emeny(self, position=None): <NEW_LINE> <INDENT> if position is None: <NEW_LINE> <INDENT> position = self.field.get_random_empty_cell() <NEW_LINE> self.enemy = position <NEW_LINE> <DEDENT> self.field[position] = CellType.SNAKE_BODY <NEW_LINE> if np.random.random() > 0.2: <NEW_LINE> <INDENT> if (self.field[p... | Generate a new fruit at a random unoccupied cell. | 625941cd44b2445a339321b3 |
def GetAttributes(self, pane): <NEW_LINE> <INDENT> attrs = [] <NEW_LINE> attrs.extend([pane.window, pane.frame, pane.state, pane.dock_direction, pane.dock_layer, pane.dock_pos, pane.dock_row, pane.dock_proportion, pane.floating_pos, pane.floating_size, pane.best_size, pane.min_size, pane.max_size, pane.caption, pane.na... | Returns all the attributes of a L{AuiPaneInfo}.
:param `pane`: a L{AuiPaneInfo} instance. | 625941cda4f1c619b28b0156 |
def strictly_increasing(L): <NEW_LINE> <INDENT> return all(x<y for x, y in zip(L, L[1:])) | Check for strictly increasing monotonously in L | 625941cdd4950a0f3b08c46c |
def class_prior(Y): <NEW_LINE> <INDENT> arr = [0] * 2 <NEW_LINE> for ele in Y: <NEW_LINE> <INDENT> if ele != 0: <NEW_LINE> <INDENT> arr[1] += 1 <NEW_LINE> <DEDENT> else: <NEW_LINE> <INDENT> arr[0] += 1 <NEW_LINE> <DEDENT> <DEDENT> nparr = np.array(arr) <NEW_LINE> PY = nparr/float(len(Y)) <NEW_LINE> return PY | Estimate the prior probability of Class labels: P(Class=y).
Here we assume this is binary classification problem.
Input:
Y : the labels of training instances, an integer numpy vector of length n.
Here n is the number of training instances. Each Y[i] = 0 or 1.
Output:
PY: the prior probability of each ... | 625941cdec188e330fd5a8bc |
def redo(self): <NEW_LINE> <INDENT> if not self.can_redo(): <NEW_LINE> <INDENT> LOGGER.info("Can't redo turn: stack is empty") <NEW_LINE> return <NEW_LINE> <DEDENT> assert self._start_time is not None <NEW_LINE> LOGGER.info('Redo turn') <NEW_LINE> with utils.at_exit(self._end_change): <NEW_LINE> <INDENT> prev = self._s... | Повтор хода | 625941cde5267d203edcddba |
def recommended_move(self, depth=2): <NEW_LINE> <INDENT> score, moves = ai.minimax.alphabeta(self, self.current_player, 0, depth, -float('inf'), float('inf')) <NEW_LINE> return random.choice(moves) | Use minimax ai to determine a move
:param depth: Depth to search in minimax tree
:return: Move | 625941cd5166f23b2e1a5276 |
def checkout(self, identifier=None): <NEW_LINE> <INDENT> super().checkout() <NEW_LINE> if not identifier: <NEW_LINE> <INDENT> identifier = self.default_branch or self.fallback_branch <NEW_LINE> <DEDENT> identifier = self.find_ref(identifier) <NEW_LINE> code, out, err = self.checkout_revision(identifier) <NEW_LINE> self... | Checkout to identifier or latest. | 625941cd796e427e537b06e3 |
def get_position(self): <NEW_LINE> <INDENT> return list(self.position) | Get the position of the object | 625941cd91f36d47f21ac610 |
def test_globWin32(self): <NEW_LINE> <INDENT> self.assertGlob( ['a', 'a[b]c'], ['[ab]', 'a[b]c'], platform='win32') | On Windows globbing will only occur if the glob argument is not the
name of an existing file, in which case the existing file name will be
the only result of globbing that argument. | 625941cd6fece00bbac2d85c |
@with_setup_args(setup) <NEW_LINE> def three_particle_integral_light_test(params): <NEW_LINE> <INDENT> photon = Particle(**SMP.photon) <NEW_LINE> neutrino_e = Particle(**SMP.leptons.neutrino_e) <NEW_LINE> sterile = Particle(**NuP.dirac_sterile_neutrino(mass=100 * UNITS.MeV)) <NEW_LINE> neutral_pion = Particle(**SMP.had... | If M_N < M_pi, there should be integrals for the reactions:
N + anti-nu_e <--> pion
nu_e + anti-N <--> pion
pi^0 <--> anti-nu_e + N
pi^0 <--> nu_e + anti-N | 625941cdadb09d7d5db6c8ad |
@check_path <NEW_LINE> def config(path): <NEW_LINE> <INDENT> fname = os.path.join(path, BASE_GRM_DIR, CONFIG_FILE) <NEW_LINE> open_file(os.path.abspath(fname)) | Edit the config. | 625941cd1f037a2d8b94631b |
def ev(self, x): <NEW_LINE> <INDENT> answer = 0 <NEW_LINE> for i in range(len(self.coefficients) - 1, -1, -1): <NEW_LINE> <INDENT> answer *= x <NEW_LINE> answer += self.coefficients[i] <NEW_LINE> <DEDENT> return answer | Returns a(x) | 625941cdf548e778e58cd69b |
@channels_endpoint.route('/resume/<int:channel_id>', methods = ['POST']) <NEW_LINE> @login_required <NEW_LINE> def resume(channel_id): <NEW_LINE> <INDENT> channel = get_channel(channel_id, must_owner = True) <NEW_LINE> if not (channel.is_published or channel.is_calculating): <NEW_LINE> <INDENT> raise BadRequest('cannot... | 恢复频道状态, 避免因客户端网络原因造成的断流而错误的将频道终结.
:param channel_id: 要恢复状态的频道id
:return: | 625941cd627d3e7fe0d68f6d |
def analyze(self, text): <NEW_LINE> <INDENT> tokenizer = nltk.tokenize.TweetTokenizer() <NEW_LINE> tokens = tokenizer.tokenize(text) <NEW_LINE> score = 0 <NEW_LINE> for word in tokens: <NEW_LINE> <INDENT> word.lower() <NEW_LINE> word = word + '\n' <NEW_LINE> if word in self.positives: <NEW_LINE> <INDENT> score +=1 <NEW... | Analyze text for sentiment, returning its score. | 625941cd4e4d5625662d44f5 |
def test_get(self): <NEW_LINE> <INDENT> self.assertEqual(200, self.response_get.status_code) | Check response of get scheduling is 200 ok | 625941cd442bda511e8be536 |
def neighbors(graph,v): <NEW_LINE> <INDENT> return sorted(graph.neighbors(v)) | Return the ordered list of neighbors ov a vertex
Parameters
----------
graph : input graph
v : vertex | 625941cd596a897236089bde |
def gradient_memory_mbs(): <NEW_LINE> <INDENT> start_time0 = time.perf_counter() <NEW_LINE> start_time = start_time0 <NEW_LINE> tf.reset_default_graph() <NEW_LINE> tf.set_random_seed(1) <NEW_LINE> train_op, loss = create_train_op_and_loss() <NEW_LINE> print("Graph construction: %.2f ms" %(1000*(time.perf_counter()-star... | Evaluates gradient, prints peak memory. | 625941cd0a366e3fb873e938 |
def _new_spline_to_blender_curve(self, curve_object_data, is_cyclic): <NEW_LINE> <INDENT> style = self._calculate_style_in_context() <NEW_LINE> if style["fill"] != "none": <NEW_LINE> <INDENT> is_cyclic = True <NEW_LINE> <DEDENT> curve_object_data.splines.new("BEZIER") <NEW_LINE> spline = curve_object_data.splines[-1] <... | Adds a new spline to an existing Blender curve object and returns
a reference to the spline. | 625941cd60cbc95b062c6661 |
def readNCNRSensitivity(inputfile): <NEW_LINE> <INDENT> f = open(inputfile, 'rb') <NEW_LINE> data = f.read() <NEW_LINE> f.close() <NEW_LINE> dataformatstring = '<65600s' <NEW_LINE> (rawdatastring,) = struct.unpack_from(dataformatstring, data, offset=516) <NEW_LINE> detdata = np.empty(16384) <NEW_LINE> a = 0 <NEW_LINE> ... | Read VAX format SANS sensitivity file. | 625941cd23849d37ff7b31ad |
def connect(self): <NEW_LINE> <INDENT> self.client = Client( access_token=self.settings["access_token"], environment="production" ) <NEW_LINE> self.orders_api = self.client.orders <NEW_LINE> self.locations_api = self.client.locations | Create the client and necessary mini-apis if access_token is set. | 625941cd26068e7796caedfd |
def delete(self, table, dump): <NEW_LINE> <INDENT> dumpname = listkey(dump) <NEW_LINE> sql = 'delete from ' + table + ' where ' + dumpname + '=?' <NEW_LINE> return self.cs.execute(sql, [dump[dumpname]]) | Delete
table str, dump dict | 625941cd4428ac0f6e5ba910 |
def pca(data, numcomp = .99): <NEW_LINE> <INDENT> from sklearn.decomposition import PCA <NEW_LINE> pca = PCA(n_components=numcomp, random_state = 52594) <NEW_LINE> pca.fit(data) <NEW_LINE> print("the explained variance ratio is ", pca.explained_variance_ratio_.sum()) <NEW_LINE> reduct = pca.transform(data) <NEW_LINE> p... | Performs PCA on the given data.
:param data: DataFrame. The data to perform PCA on.
:Param numcomp: Variable. As an int, the number of components to use when performing PCA. As a 2 decimal float < 1, the percentage of explained variance required when PCA is complete. | 625941cd94891a1f4081bbc7 |
def valid_end_date(self, target_date): <NEW_LINE> <INDENT> return target_date | Returns a date that is valid for the end of the report.
Arguments:
target_date (datetime): The date you'd like examined
Returns:
datetime: A datetime made valid for the report based on the target_date argument. | 625941cdd164cc6175782e6b |
@rpc4django.rpcmethod( name='scheduling.sc.operational', signature=['String'], login_required=satnet_settings.JRPC_LOGIN_REQUIRED ) <NEW_LINE> def get_operational_slots(spacecraft_id): <NEW_LINE> <INDENT> return scheduling_serializers.serialize_sc_operational_slots( spacecraft_id ) | JRPC method that permits obtaining all the OperationalSlots for all the
channels that belong to the Spacecraft with the given identifier.
:param spacecraft_id: Identifier of the spacecraft.
:return: JSON-like structure with the data serialized. | 625941cd30c21e258bdfa5bb |
def analyze_parameters(args, parser): <NEW_LINE> <INDENT> payload = {} <NEW_LINE> payload['VmmControlType'] = args.Type <NEW_LINE> if args.Type == "Connect": <NEW_LINE> <INDENT> if args.Image is None: <NEW_LINE> <INDENT> parser.error('the following arguments are required: -i') <NEW_LINE> <DEDENT> else: <NEW_LINE> <INDE... | #====================================================================================
# @Method: Encapsulate the request body.
# @Param:args,payload
# @Return:
# @date: 2017.8.1 11:09
#==================================================================================== | 625941cdeab8aa0e5d26dc76 |
def gethtml(self, url): <NEW_LINE> <INDENT> ob_openurl = OpenUrl(url) <NEW_LINE> code, html = ob_openurl.run() <NEW_LINE> if code == 200: <NEW_LINE> <INDENT> return html <NEW_LINE> <DEDENT> else: <NEW_LINE> <INDENT> print('open [{}] failed..'.format(url)) <NEW_LINE> return None | 获取html文件
返回url的列表 | 625941cd6e29344779a62730 |
def next(self): <NEW_LINE> <INDENT> node = self._node <NEW_LINE> while node: <NEW_LINE> <INDENT> self._stack.append(node) <NEW_LINE> node = node.left <NEW_LINE> <DEDENT> node = self._stack.pop() <NEW_LINE> self._node = node.right <NEW_LINE> return node.val | :rtype: int | 625941cd8c3a8732951584d9 |
def soft_reset(event): <NEW_LINE> <INDENT> NETWORK.controller.soft_reset() | Soft reset the controller. | 625941cd5166f23b2e1a5277 |
def ffl_path(self, site, frametype): <NEW_LINE> <INDENT> try: <NEW_LINE> <INDENT> return self.paths[(site, frametype)] <NEW_LINE> <DEDENT> except KeyError: <NEW_LINE> <INDENT> self._find_paths() <NEW_LINE> return self.paths[(site, frametype)] | Returns the path of the FFL file for the given site and frametype
Examples
--------
>>> from gwpy.io.datafind import FflConnection
>>> conn = FflConnection()
>>> print(conn.ffl_path('V', 'V1Online'))
/virgoData/ffl/V1Online.ffl | 625941cd50812a4eaa59c440 |
def train_test(config, obj_classifier=None, teacher=None, model_params={}): <NEW_LINE> <INDENT> net = RelDN(config) <NEW_LINE> train_tester = TrainTester( net, config, {'images'}, obj_classifier, teacher ) <NEW_LINE> train_tester.train_test() | Train and test a net. | 625941cdd486a94d0b98e264 |
def get_repeat_state(self): <NEW_LINE> <INDENT> try: <NEW_LINE> <INDENT> return self.sp.current_playback()['repeat_state'] <NEW_LINE> <DEDENT> except TypeError: <NEW_LINE> <INDENT> raise ConnectionError('User is not connected to Spotify.') | Gets repeat state.
:return: Repeat state, which can be 'track', 'context' or 'off'.
:raises ConnectionError: User is not connected to Spotify. | 625941cd498bea3a759b9bcd |
def _handle_twilio_voice_end(self, request_context, chat, path, params): <NEW_LINE> <INDENT> context = {} <NEW_LINE> result = END_TEMPLATE.substitute(context) <NEW_LINE> return str(result) | Handle a request.
Args:
request_context: RequestContext object
chat: Chat object
path: http request path
params: dict of http request params
Returns:
Twilio TwiML response
Raises:
TwilioHandlerException if the message is invalid
and should be propagated. | 625941cde8904600ed9f204b |
def drpc(): <NEW_LINE> <INDENT> cppaths = [CLUSTER_CONF_DIR] <NEW_LINE> jvmopts = parse_args(confvalue("drpc.childopts", cppaths)) + [ "-Dlogfile.name=drpc.log", "-Dlog4j.configurationFile=" + os.path.join(get_log4j_conf_dir(), "cluster.xml") ] <NEW_LINE> exec_storm_class( "backtype.storm.daemon.drpc", jvmtype="-server... | Syntax: [storm drpc]
Launches a DRPC daemon. This command should be run under supervision
with a tool like daemontools or monit.
See Distributed RPC for more information.
(http://storm.incubator.apache.org/documentation/Distributed-RPC) | 625941cd5fdd1c0f98dc0351 |
@pytest.fixture(scope='module') <NEW_LINE> def contained_evaluator() -> BooleanExpressionEvaluator: <NEW_LINE> <INDENT> token_evaluator = TokenContainedEvaluator(TOKENS_THAT_ARE_TRUE) <NEW_LINE> evaluator = BooleanExpressionEvaluator(token_evaluator, TOKEN_FORMAT) <NEW_LINE> return evaluator | Boolean expression evaluator using the TokenContainedEvaluator.
All the tokens in TOKENS_THAT_ARE_TRUE will be evaluated to True and
any other token to False. | 625941ced18da76e235325f4 |
def is_empty(self): <NEW_LINE> <INDENT> return len(self.codelets()) == 0 | Return True if the coderack is empty. | 625941cd851cf427c661a62d |
def parse_rec(filename, muscima, rescale_factor=1): <NEW_LINE> <INDENT> if not muscima: <NEW_LINE> <INDENT> tree = ET.parse(filename) <NEW_LINE> for size in tree.findall('size'): <NEW_LINE> <INDENT> width = int(round(float(size[0].text) * rescale_factor)) <NEW_LINE> height = int(round(float(size[1].text) * rescale_fact... | Parse a PASCAL VOC xml file | 625941ce7cff6e4e81117aa4 |
@receiver(signals.post_save, sender=User) <NEW_LINE> def save_profile(sender, instance, **kwargs): <NEW_LINE> <INDENT> instance.userprofile.save() | the method responsible for saving each of the user profile | 625941ce283ffb24f3c55a1f |
def editListValues(self): <NEW_LINE> <INDENT> dialog = QListEditDialog(self._alias, self.controller, None) <NEW_LINE> if dialog.exec_() == QtGui.QDialog.Accepted: <NEW_LINE> <INDENT> values = dialog.getList() <NEW_LINE> self._alias.component.valueList = copy.copy(values) <NEW_LINE> self._str_values = [str(v) for v in v... | editListValues() -> None
Show a dialog for editing the values | 625941ce32920d7e50b282ee |
def __init__(self, testcase, driver, logger): <NEW_LINE> <INDENT> super(FeiFanMembershipPage, self).__init__(testcase, driver, logger) | Constructor | 625941ce5fcc89381b1e17dd |
def __init__(self, name=None, parent=None): <NEW_LINE> <INDENT> super().__init__(name, parent) | Parameters
---------- | 625941ce627d3e7fe0d68f6e |
def zero_normalize(image): <NEW_LINE> <INDENT> return (image - np.mean(image)) / np.std(image) | Zero-center and standardize image pixel values.
:param image: (array) either one slice, met, or stack
:return: (array) zero-centered and standardized image | 625941ce7047854f462a1528 |
def deQueue(self): <NEW_LINE> <INDENT> if self.isEmpty(): <NEW_LINE> <INDENT> print("deQueue: ",self.queue, self.head, self.tail) <NEW_LINE> return False <NEW_LINE> <DEDENT> if self.tail==self.head: <NEW_LINE> <INDENT> self.tail=-1 <NEW_LINE> self.head=-1 <NEW_LINE> print("deQueue: ",self.queue, self.head, self.tail) <... | Delete an element from the circular queue. Return true if the operation is successful.
:rtype: bool | 625941ceb545ff76a8913f34 |
def get_groups(self): <NEW_LINE> <INDENT> from search.models import GroupMember <NEW_LINE> gm_objects = GroupMember.objects.filter(user=self.user) <NEW_LINE> groups = [] <NEW_LINE> for g in gm_objects: <NEW_LINE> <INDENT> groups.append(g.group) <NEW_LINE> <DEDENT> return groups | return list of groups that a user is in. Also can be used to see if a
user is any group. | 625941ceff9c53063f47c312 |
def main(): <NEW_LINE> <INDENT> args = create_parser().parse_args() <NEW_LINE> args = optionst.defaults(args) <NEW_LINE> try: <NEW_LINE> <INDENT> properties = propertyt.do_make_property(args.viewer_property, args.cbmc_property, args.srcdir) <NEW_LINE> print(properties) <NEW_LINE> <DEDENT> except UserWarning as error: <... | Properties checked by CBMC during property checking. | 625941ced4950a0f3b08c46d |
def parse(self, start_year=None, end_year=None, replace_missing_data=True): <NEW_LINE> <INDENT> if (end_year and start_year) and (end_year < start_year): <NEW_LINE> <INDENT> raise ValueError('end_year {} cannot be less than start_year {}'.format(end_year, start_year)) <NEW_LINE> <DEDENT> dly_delimiter = [11,4,2,4] + [5... | Parse the .dly file and store the resulting numpy array internally.
Parameters
----------
start_year : int, optional
Slice the initial data so only rows after start_year are stored
end_year : int, optional
Slice the initial data so only rows before end_year are stored
replace_missing_data: bool, optional
... | 625941ce711fe17d8254248a |
def dcm_to_npy(dcm, norm=False): <NEW_LINE> <INDENT> def _dcm_to_npy(dcm, norm): <NEW_LINE> <INDENT> dcm_dtype = dcm.BitsAllocated <NEW_LINE> pixel = dcm.pixel_array.astype("float32") <NEW_LINE> if dcm.RescaleSlope != 1: <NEW_LINE> <INDENT> pixel *= dcm.RescaleSlope <NEW_LINE> <DEDENT> pixel += dcm.RescaleIntercept + 1... | Parameters
----------
dcm : Single Dicom object(2D), List Dicom object(3D)
norm : If False :[0 4095]:, True :[0 1]:, default False
Return
------
2D or 3D CT Image(ndarray float32)
Examples
--------
>>> dcm = pydicom.dcmread("ex.dcm")
>>> npy = dcm_to_npy(dcm, norm=True)
>>> npy.min(), npy.max()
>>> 0.0 1.0 | 625941ce656771135c3eb98d |
def prop(attr): <NEW_LINE> <INDENT> class Inner: <NEW_LINE> <INDENT> def __init__(self): <NEW_LINE> <INDENT> self.attr = attr <NEW_LINE> self.set_attr = None <NEW_LINE> self.delete_attr = None <NEW_LINE> <DEDENT> def __get__(self, instance, owner): <NEW_LINE> <INDENT> return self.attr(instance) <NEW_LINE> <DEDENT> def ... | This is the decorator version of the descriptor property. It decorates some attribute attr of the owner class. | 625941ce460517430c3942a3 |
def helper(self, nums, start, paths, path, target): <NEW_LINE> <INDENT> if target < 0: <NEW_LINE> <INDENT> return <NEW_LINE> <DEDENT> if target == 0: <NEW_LINE> <INDENT> paths.append(path[:]) <NEW_LINE> return <NEW_LINE> <DEDENT> for i in range(start, len(nums)): <NEW_LINE> <INDENT> path.append(nums[i]) <NEW_LINE> self... | 以当前path为起点, 找到所有能够得到target的路径. | 625941ce16aa5153ce362596 |
def hash_directory(directory): <NEW_LINE> <INDENT> assert os.path.isdir(directory), '"directory" must be a directory!' <NEW_LINE> md5_hash = hashlib.md5() <NEW_LINE> for root, dirs, files in os.walk(directory): <NEW_LINE> <INDENT> for name in sorted(files): <NEW_LINE> <INDENT> filename = os.path.join(root, name) <NEW_L... | Hashes recursively the content of a directory.
Args:
directory (path): path to a directory to be hashed
Returns:
hash of the directory content | 625941ce8c0ade5d55d3ead9 |
def popular_sites(self, repeat=7): <NEW_LINE> <INDENT> random_repeat = random.randint(3, repeat) <NEW_LINE> for i in range(random_repeat): <NEW_LINE> <INDENT> self.browsing(random.choice(self.urls), i) <NEW_LINE> time.sleep(5) <NEW_LINE> self.limit_repeat = 0 <NEW_LINE> self.browse_populate_site() <NEW_LINE> <DEDENT> w... | Visit popular sites
:return: | 625941cea8ecb033257d31eb |
def add(self, satp, boot=None, claimoption=None, description=None, device=None, driver=None, force=None, model=None, option=None, psp=None, pspoption=None, transport=None, type=None, vendor=None): <NEW_LINE> <INDENT> return execute_soap(self._client, self._host, self.moid, 'vim.EsxCLI.storage.nmp.satp.rule.Add', boot=b... | Add a rule to the list of claim rules for the given SATP.
:param boot: boolean, This is a system default rule added at boot time. Do not modify esx.conf or add to host profile.
:param claimoption: string, Set the claim option string when adding a SATP claim rule.
:param description: string, Set the claim rule descripti... | 625941ce2eb69b55b151c9ce |
def pop_lowest_polygone(self): <NEW_LINE> <INDENT> if len(self.collection) == 0: <NEW_LINE> <INDENT> logging.info("There is no polygone in the collection") <NEW_LINE> return <NEW_LINE> <DEDENT> polygone_min = list(self.collection)[0] <NEW_LINE> min_y = self.collection[polygone_min][0][0][0][1] <NEW_LINE> for vertex in ... | Delete the polygone with the lowest y-axis in the collection
and returns it.
Returns
-------
lowest_polygone : array of tuple of float | 625941cead47b63b2c50a09e |
def test__parse_binary_time(self): <NEW_LINE> <INDENT> cases = [ (datetime.timedelta(0, 44130), '\x08\x00\x00\x00\x00\x00\x0c\x0f\x1e'), (datetime.timedelta(14, 15330), '\x08\x00\x0e\x00\x00\x00\x04\x0f\x1e'), (datetime.timedelta(-14, 15330), '\x08\x01\x0e\x00\x00\x00\x04\x0f\x1e'), (datetime.timedelta(10, 58530, 23000... | Parse a time value from a binary packet | 625941ced7e4931a7ee9e03c |
def getInletXNew(linelons, linelats, lon, lat, lon0, lat0, anchorind=0): <NEW_LINE> <INDENT> xx = (linelons - lon0)*np.cos(lat0 * np.pi / 180.) * 60. * 1.85 <NEW_LINE> yy = (linelats - lat0)*60.*1.85 <NEW_LINE> distline = np.cumsum(np.sqrt(np.diff(xx)**2 + np.diff(yy)**2)) <NEW_LINE> distline = np.append([0.], distline... | get potison along an inlet line Anchor Ind should be S4 | 625941ce76e4537e8c351791 |
def statLinkedFiles(self): <NEW_LINE> <INDENT> files = [] <NEW_LINE> for lf in self.document.getLinkedFiles(): <NEW_LINE> <INDENT> filename = lf.filename <NEW_LINE> try: <NEW_LINE> <INDENT> s = os.stat(filename) <NEW_LINE> files.append( (filename, s.st_mtime, s.st_size) ) <NEW_LINE> <DEDENT> except OSError: <NEW_LINE> ... | Stat linked files.
Returns a list of (filename, mtime, size) | 625941ce15fb5d323cde0c2e |
def get_user_id_for_username(user_name, allow_none=False): <NEW_LINE> <INDENT> try: <NEW_LINE> <INDENT> if c.userobj and c.userobj.name == user_name: <NEW_LINE> <INDENT> return c.userobj.id <NEW_LINE> <DEDENT> <DEDENT> except TypeError: <NEW_LINE> <INDENT> pass <NEW_LINE> <DEDENT> user = model.User.get(user_name) <NEW_... | Helper function to get user id | 625941ce94891a1f4081bbc8 |
def open_logfile_allconn(self, log_file_conn): <NEW_LINE> <INDENT> self.log_file_open = 1 <NEW_LINE> self.log_file_conn = log_file_conn | Run on all connections to signal log file is open | 625941cebe383301e01b55a4 |
def test_touch_with_extra_parameter(self): <NEW_LINE> <INDENT> key = ('test', 'demo', 1) <NEW_LINE> policy = {'timeout': 1000} <NEW_LINE> with pytest.raises(TypeError) as typeError: <NEW_LINE> <INDENT> TestTouch.client.touch(key, 120, {}, policy, "") <NEW_LINE> <DEDENT> assert "touch() takes at most 4 arguments (5 give... | Invoke touch() with extra parameter. | 625941cebd1bec0571d9074e |
def read_file_header(self): <NEW_LINE> <INDENT> hdict = {} <NEW_LINE> hdr_dtype = MDTYPES[self.byte_order]['dtypes']['file_header'] <NEW_LINE> hdr = read_dtype(self.mat_stream, hdr_dtype) <NEW_LINE> hdict['__header__'] = hdr['description'].item().strip(b' \t\n\000') <NEW_LINE> v_major = hdr['version'] >> 8 <NEW_LINE> v... | Read in mat 5 file header | 625941ced99f1b3c44c676ac |
def get_xray_scan_schema(self, img: str) -> dict: <NEW_LINE> <INDENT> xray_scan = { "version": "1.0.0", "producerID": self.producer_id, "createdTS": self.scheduler.now_as_str(), "imageID": img, "imagePath": self.path_images } <NEW_LINE> return xray_scan | Returns an empty x_ray_scan schema.
:param img: ID of the scanned image
:return: filled xray_scan schema represented by a dictionary | 625941cea79ad161976cc264 |
def __init__(self, condition_value_t=1000, eigenvals_t=1e-10): <NEW_LINE> <INDENT> self._condition_value_t = condition_value_t <NEW_LINE> self._eigenvals_t = eigenvals_t | Initializes a 'StatsLinear' instance.
Args:
condition_value_t (int): The condition value threshold (for
multicollinearity). Usually, values higher
than 1000 indicate strong
multicollinearity or other numerical
... | 625941ce507cdc57c6306dfa |
def list( self, resource_group_name, virtual_network_name, **kwargs ): <NEW_LINE> <INDENT> cls = kwargs.pop('cls', None) <NEW_LINE> error_map = { 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError } <NEW_LINE> error_map.update(kwargs.pop('error_map', {})) <NEW_LINE> api_version = "2018... | Gets all subnets in a virtual network.
:param resource_group_name: The name of the resource group.
:type resource_group_name: str
:param virtual_network_name: The name of the virtual network.
:type virtual_network_name: str
:keyword callable cls: A custom type or function that will be passed the direct response
:retur... | 625941ce046cf37aa974ce66 |
def beale_func(x): <NEW_LINE> <INDENT> if not x.shape[1] == 2: <NEW_LINE> <INDENT> raise IndexError("Beale function only takes two-dimensional input.") <NEW_LINE> <DEDENT> if not np.logical_and(x >= -4.5, x <= 4.5).all(): <NEW_LINE> <INDENT> raise ValueError( "Input for Beale function must be within " "[-4.5, 4.5]." ) ... | Beale objective function.
Only takes two dimensions and has a global minimum of `0` at
:code:`f([3,0.5])` Its domain is bounded between :code:`[-4.5, 4.5]`
Parameters
----------
x : numpy.ndarray
set of inputs of shape :code:`(n_particles, dimensions)`
Returns
-------
numpy.ndarray
computed cost of size :cod... | 625941ce097d151d1a222f78 |
def test_profile_exists(self): <NEW_LINE> <INDENT> self.new_profile.save_profile() <NEW_LINE> test_profile = Passwords("Gmail", "ilovemygirlfriend", "17") <NEW_LINE> test_profile.save_profile() <NEW_LINE> test_exists = Passwords.profile_exists("Gmail") <NEW_LINE> self.assertTrue(test_exists) | Test to check if we can return a boolean if we cannot find a profile | 625941ce99fddb7c1c9de4af |
def buildSubtrees(self, child): <NEW_LINE> <INDENT> if child.isLeaf(): <NEW_LINE> <INDENT> return child.symbol() <NEW_LINE> <DEDENT> if (child.child1() is not None) and (child.child2() is not None): <NEW_LINE> <INDENT> subtree1 = self.buildSubtrees(child.child1()) <NEW_LINE> subtree2 = self.buildSubtrees(child.child2()... | child is a Label | 625941ce66656f66f7cbc2c9 |
def nbgrader_format_db_url(course_id: str) -> str: <NEW_LINE> <INDENT> course_id = LTIUtils().normalize_string(course_id) <NEW_LINE> database_name = f"{org_name}_{course_id}" <NEW_LINE> return f"postgresql://{nbgrader_db_user}:{nbgrader_db_password}@{nbgrader_db_host}:{nbgrader_db_port}/{database_name}" | Returns the nbgrader database url with the format: <org_name>_<course-id>
Args:
course_id: the course id (usually associated with the course label) from which the launch was initiated. | 625941ce99fddb7c1c9de4b0 |
def configuration_candidate_properties_values_all(self, id, **kwargs): <NEW_LINE> <INDENT> kwargs['_return_http_data_only'] = True <NEW_LINE> if kwargs.get('callback'): <NEW_LINE> <INDENT> return self.configuration_candidate_properties_values_all_with_http_info(id, **kwargs) <NEW_LINE> <DEDENT> else: <NEW_LINE> <INDENT... | Get Candidate Property values
Lists all available values for given candidate property id. This endpoint is available only for SINGLE_SELECT candidate property type.
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when recei... | 625941ce07f4c71912b115a1 |
def is_opposition(body, date): <NEW_LINE> <INDENT> time1 = ephem.Date(date) <NEW_LINE> time2 = ephem.Date(time1 + 1) <NEW_LINE> body.compute(time1) <NEW_LINE> elong1 = body.elong.norm <NEW_LINE> body.compute(time2) <NEW_LINE> elong2 = body.elong.norm <NEW_LINE> return ((elong1 <= ephem.pi) and (elong2 >= ephem.pi)) or ... | Returns True if the body is at opposition (i.e. its elongation from the
Sun passes 180 degrees, placing it behind the Earth).
Keyword arguments:
body -- a PyEphem Body object (typically a planet).
date -- a YYYY-MM-DD string. | 625941ce7b25080760e39578 |
def __init__(self, body): <NEW_LINE> <INDENT> super(Body, self).__init__() <NEW_LINE> self.value = body | Create a new <Body> element
:param body: message body | 625941ce4f6381625f114b59 |
def search_for_coords(dir): <NEW_LINE> <INDENT> def checked_before(r): <NEW_LINE> <INDENT> reruns = False <NEW_LINE> equils = False <NEW_LINE> if "rerun" in os.listdir(r.path): <NEW_LINE> <INDENT> reruns = any(f"{r.title}" in f for f in os.listdir(f"{r.path}/rerun")) <NEW_LINE> <DEDENT> if "spec" in os.listdir(r.path):... | Recursively searched log/out files of optimisations for a successful
equilibration- then writes to `equil.xyz`. If unsuccesful, writes to
`rerun/rerun.xyz`, whilst also creating the corresponding input and
job file. | 625941ced8ef3951e324365c |
def is_gte_today(base): <NEW_LINE> <INDENT> return True if base >= datetime.date.today() else False | 判断给定日期是否大于等于当前日期
:param base 基础日期 | 625941ce7c178a314d6ef57f |
def site(request): <NEW_LINE> <INDENT> return {'site': get_current_site(request)} | Returns site settings which can be accessed with 'site' key. | 625941cefb3f5b602dac37b2 |
def merge(self, path, corr = 1, bias = 0): <NEW_LINE> <INDENT> t2 = self.load(path) <NEW_LINE> t1_start_time = self.start_time <NEW_LINE> t1_end_time = self.end_time <NEW_LINE> t2_start_time = t2.start_time <NEW_LINE> t2_end_time = t2.end_time <NEW_LINE> self.start_time = min(t1_start_time, t2_start_time) <NEW_LINE> se... | Method to merge an existing tidal data set instance into the active one
:param path: path to .tid file to merge
:param corr: correction factor to multiply the water levels
:param corr: bias to add to the water levels
:return: | 625941ce4c3428357757c446 |
def get_insult(date): <NEW_LINE> <INDENT> insults = models.Insult.objects <NEW_LINE> insult = insults.exclude( Q(days__date__range=[date - timezone.timedelta(days=365), date + timezone.timedelta(days=365)]) | Q(days__isnull=False)).order_by('?').first() <NEW_LINE> if not insult: <NEW_LINE> <INDENT> insult = insults.ord... | Get an insult from the database | 625941cecdde0d52a9e53152 |
def control(self, num_ctrl_qubits=1, label=None, ctrl_state=None): <NEW_LINE> <INDENT> cmat = _compute_control_matrix(self.to_matrix(), num_ctrl_qubits, ctrl_state=None) <NEW_LINE> iso = isometry.Isometry(cmat, 0, 0) <NEW_LINE> cunitary = ControlledGate('c-unitary', num_qubits=self.num_qubits+num_ctrl_qubits, params=[c... | Return controlled version of gate
Args:
num_ctrl_qubits (int): number of controls to add to gate (default=1)
label (str): optional gate label
ctrl_state (int or str or None): The control state in decimal or as a
bit string (e.g. '1011'). If None, use 2**num_ctrl_qubits-1.
Returns:
UnitaryGate:... | 625941ce26238365f5f0ef8d |
def read_serial_data(self): <NEW_LINE> <INDENT> qdata = list(get_all_from_queue(self.data_q)) <NEW_LINE> if len(qdata) > 0: <NEW_LINE> <INDENT> data = dict(timestamp=qdata[-1][1], temperature=float(qdata[-1][0])) <NEW_LINE> self.livefeed.add_data(data) | Called periodically by the update timer to read data
from the serial port. | 625941cede87d2750b85feb2 |
def simMove(self, pos, cmd): <NEW_LINE> <INDENT> x = pos[0] <NEW_LINE> y = pos[1] <NEW_LINE> a = pos[2] <NEW_LINE> forward = cmd[0] <NEW_LINE> turn = cmd[1] <NEW_LINE> forwardNoise = gauss(0, self.noise[0]) <NEW_LINE> turnNoise = gauss(0, self.noise[1]) <NEW_LINE> a = a + (turn + turnNoise) <NEW_LINE> a = wrapAngle(a) ... | Simulate the robot moving with noise | 625941ce3d592f4c4ed1d18c |
def calcSpeed(self): <NEW_LINE> <INDENT> pass | void KIO.SlaveInterface.calcSpeed() | 625941ceac7a0e7691ed41eb |
def plenty_api_create_attribute_value_name(self, value_id: int, lang: str, name: str) -> dict: <NEW_LINE> <INDENT> if not value_id or not lang or not name: <NEW_LINE> <INDENT> return [{'error': 'missing_parameter'}] <NEW_LINE> <DEDENT> path = str(f"/attribute_values/{value_id}/names") <NEW_LINE> if utils.get_language(l... | Create an attribute value name for a specific attribute.
Parameter:
value_id [str] - Attribute value ID from PlentyMarkets
lang [str] - two letter abbreviation of a language
name [str] - The visible name of the attribute in the
given language
Return... | 625941cef8510a7c17cf981c |
def set_database(self, db): <NEW_LINE> <INDENT> self.currentDB = db <NEW_LINE> self.set_list(u'', aozoraDB.keyYOMIWORKS) | データベースのアタッチ
| 625941cee1aae11d1e749dd6 |
def makeInputAndTarget(): <NEW_LINE> <INDENT> patterns = read_data("digits_train.txt") <NEW_LINE> inputs = np.empty((2500,196)) <NEW_LINE> targets = np.zeros((2500, 10)) <NEW_LINE> for row in range(2500): <NEW_LINE> <INDENT> inputs[row] = patterns[row].getInput() <NEW_LINE> col = row//250 <NEW_LINE> targets[row][col] =... | Makes training inputs and targets from digit_train.txt | 625941ce435de62698dfdd6c |
def _insert_default_stacors(session,network_code,station_code): <NEW_LINE> <INDENT> statement = text("select net, sta, seedchan, location, min(ondate), max(offdate) " "from channel_data where seedchan in ('SNN', 'SNE', 'BNN', 'BNE', " "'ENN', 'ENE', 'HNN', 'HNE', 'EHN', 'EHE', 'BHN', 'BHE', 'HHN', " "'HHE', 'EH1','EH2'... | inserts 0. (ml) and 1. (me) corrections for horizontal channels | 625941ce187af65679ca523e |
@app.route('/') <NEW_LINE> def hello_world(): <NEW_LINE> <INDENT> keyword_query = 'Covid' <NEW_LINE> article_data = get_article_data(keyword_query) <NEW_LINE> return render_template( "index.html", topic=keyword_query, headlines=article_data['headlines'], snippets=article_data['snippets'], dates=article_data['dates'], u... | Returns root endpoint HTML | 625941ce44b2445a339321b5 |
def daemonize(self): <NEW_LINE> <INDENT> try: <NEW_LINE> <INDENT> pid = os.fork() <NEW_LINE> if pid > 0: <NEW_LINE> <INDENT> sys.exit(0) <NEW_LINE> <DEDENT> <DEDENT> except OSError as e: <NEW_LINE> <INDENT> sys.stderr.write("fork #1 failed: %d (%s)\n" % (e.errno, e.strerror)) <NEW_LINE> sys.exit(1) <NEW_LINE> <DEDENT> ... | do the UNIX double-fork magic, see Stevens' "Advanced
Programming in the UNIX Environment" for details (ISBN 0201563177)
http://www.erlenstar.demon.co.uk/unix/faq_2.html#SEC16 | 625941cea17c0f6771cbe16f |
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