code stringlengths 4 4.48k | docstring stringlengths 1 6.45k | _id stringlengths 24 24 |
|---|---|---|
def calcula_stop_loss(preco_actual, preco_inicial): <NEW_LINE> <INDENT> tmp_stop_loss = float((preco_actual*4.0)/100) <NEW_LINE> stop_loss = float(preco_actual - tmp_stop_loss) <NEW_LINE> return stop_loss | Calcula o valor de um stop loss
Sempre que o preco actual for superior em 3% ao preco anterior
é colocado um stop-loss | 625941c41f037a2d8b9461f2 |
def delete_user(self, id, realm): <NEW_LINE> <INDENT> path = "/{realm}/users/{id}".format( id=id, realm=realm ) <NEW_LINE> params = { } <NEW_LINE> headers = { } <NEW_LINE> return self.session.request( method="DELETE", endpoint=self.session._admurl(path), params=params, ) | Delete the user (Users)
Parameters
----------
id : string
(Required, Path) User id
realm : string
(Required, Path) realm name (not id!) | 625941c4dd821e528d63b19e |
def diagonalize(self, H_NN, eps_n): <NEW_LINE> <INDENT> nbands = self.bd.nbands <NEW_LINE> mynbands = self.bd.mynbands <NEW_LINE> eps_N = np.empty(nbands) <NEW_LINE> self.timer.start('Diagonalize') <NEW_LINE> self.block_comm.broadcast(H_NN, 0) <NEW_LINE> self._diagonalize(H_NN, eps_N) <NEW_LINE> self.timer.stop('Diagon... | Serial diagonalizer must handle two cases:
1. Parallelization over domains only.
2. Simultaneous parallelization over domains and bands. | 625941c4cdde0d52a9e53025 |
def is_str_type(val): <NEW_LINE> <INDENT> return isinstance(val, (bytes, unicode, np.string_, np.bytes_, np.unicode)) | Return True if val is a string type | 625941c4d53ae8145f87a266 |
def dequeue(self): <NEW_LINE> <INDENT> if self.is_empty(): <NEW_LINE> <INDENT> raise PrioQueueError('in dequeue') <NEW_LINE> <DEDENT> elems = self._elems <NEW_LINE> e0 = elems[0] <NEW_LINE> e = elems.pop() <NEW_LINE> return e0 | 出队操作 | 625941c4a05bb46b383ec817 |
def main(): <NEW_LINE> <INDENT> x = 0.07*2*math.pi <NEW_LINE> vaspy.MakeInputs.all('.', kp_rx=0.18, kp_soc=0.15) | alt parameter | 625941c4bf627c535bc131c2 |
@then("click '{ng_if_locator}' button element") <NEW_LINE> def step(context, ng_if_locator): <NEW_LINE> <INDENT> context.clickActions = ClickActions(context) <NEW_LINE> context.clickActions.click_ng_if_xpath(ng_if_locator) | Then click '{ng_if_locator}' button element | 625941c4ff9c53063f47c1e8 |
def __eq__(self, other): <NEW_LINE> <INDENT> if not isinstance(other, JsonChangeAssetTypeRequest): <NEW_LINE> <INDENT> return False <NEW_LINE> <DEDENT> return self.__dict__ == other.__dict__ | Returns true if both objects are equal | 625941c4d6c5a1020814403d |
def testSupportQ(self): <NEW_LINE> <INDENT> source = dict(q=Q(a=1) | Q(b=2) & Q(c=3)) <NEW_LINE> content_type, encoding, result = serialization.dumps(source, 'x-rpc-json') <NEW_LINE> restored = serialization.loads(result, content_type, encoding) <NEW_LINE> expected = jsonpickle.encode(source) <NEW_LINE> result = jsonpi... | Encoder/Decoder support Django Q-object
| 625941c4be383301e01b547c |
def __init__(self, cv, x, pps, colors, pos, speed, timer, angle=0.25): <NEW_LINE> <INDENT> super().__init__(cv) <NEW_LINE> self.y = 500 <NEW_LINE> if isinstance(x, list) and len(x) > 1: <NEW_LINE> <INDENT> self.x = x[0] <NEW_LINE> self.y = x[1] <NEW_LINE> <DEDENT> else: <NEW_LINE> <INDENT> self.x = x <NEW_LINE> <DEDENT... | Shoots a rocket into the sky which then explodes.
Arguments:
cv {idontknow} -- the canvas upon which this wonderful display
is painted
x {int} -- the position of the rocketrocket
pps {int} -- pixels per second (the speed of the particles)
colors {str} -- the color of the particles
pos {int}... | 625941c4fb3f5b602dac3685 |
def fix_updr(self, updr:int, delta:int) -> int: <NEW_LINE> <INDENT> while delta != 0: <NEW_LINE> <INDENT> if delta < 0: <NEW_LINE> <INDENT> new_updr = max(0,updr+delta) <NEW_LINE> <DEDENT> else: <NEW_LINE> <INDENT> new_updr = min(self.num_updr-1,updr+delta) <NEW_LINE> <DEDENT> if (self.avail_updr & (1<<new_updr)) != 0 ... | Move given up datarate by delta notches. Delta > 0 towards faster datarates.
Used in ADR decisions in network server. | 625941c4187af65679ca5112 |
def delete(self, keypress=None): <NEW_LINE> <INDENT> if len(self.values) < 1: <NEW_LINE> <INDENT> return False <NEW_LINE> <DEDENT> entry = self.values[self.cursor_line] <NEW_LINE> really = npyscreen.notify_yes_no( 'Really delete the entry "{}"?'.format(entry['name']), form_color='CRITICAL' ) <NEW_LINE> if really: <NEW_... | Ask and delete entry. | 625941c45f7d997b87174a8a |
def add_cloudstack(self, url, api_key, secret_key): <NEW_LINE> <INDENT> parsed_url = urlparse(url) <NEW_LINE> hostname = parsed_url.hostname <NEW_LINE> deviceRoot = self._dmd.getDmdRoot("Devices") <NEW_LINE> device = deviceRoot.findDeviceByIdExact(hostname) <NEW_LINE> if device: <NEW_LINE> <INDENT> return False, _t("A ... | Handles adding a new CloudStack cloud to the system. | 625941c401c39578d7e74e2f |
def get_paginated_response(self, data): <NEW_LINE> <INDENT> return Response(OrderedDict([ ("page", self.page.number), ("num_pages", self.page.paginator.num_pages), ("count", self.page.paginator.count), ("next", self.get_next_link()), ("next_page_number", self.page.next_page_number() if self.page.has_next() else None), ... | Return response with some additional fields.
:param data: data queryset.
:type data: django.db.models.query.QuerySet.
:return: extended django rest framework response.
:rtype: rest_framework.response.Response. | 625941c43eb6a72ae02ec4cd |
def HuffEncode(freq_dict): <NEW_LINE> <INDENT> heap = [[wt, [sym, ""]] for sym, wt in freq_dict.items()] <NEW_LINE> heapify(heap) <NEW_LINE> while len(heap) > 1: <NEW_LINE> <INDENT> lo = heappop(heap) <NEW_LINE> hi = heappop(heap) <NEW_LINE> for pair in lo[1:]: <NEW_LINE> <INDENT> pair[1] = '0' + pair[1] <NEW_LINE> <DE... | Return a dictionary which maps keys from the input dictionary freq_dict
to bitstrings using a Huffman code based on the frequencies of each key | 625941c41d351010ab855b10 |
def register_errorhandlers(app): <NEW_LINE> <INDENT> def render_error(error): <NEW_LINE> <INDENT> error_code = getattr(error, 'code', 500) <NEW_LINE> return render_template("{0}.html".format(error_code)), error_code <NEW_LINE> <DEDENT> for errcode in [401, 403, 404, 500]: <NEW_LINE> <INDENT> app.errorhandler(errcode)(r... | Add errorhandlers to the app. | 625941c4236d856c2ad447cc |
@app.route('/count/movies', defaults={'go': Movie}) <NEW_LINE> @app.route('/count/people', defaults={'go': Person}) <NEW_LINE> def count_objects(go): <NEW_LINE> <INDENT> return jsonify({ 'primary_label': go.__primarylabel__, 'total': go.count_nodes(ogm.graph) }) | Count the total number of nodes of this type | 625941c4d10714528d5ffcd5 |
def test_file_positive() -> None: <NEW_LINE> <INDENT> collection = RulesCollection() <NEW_LINE> collection.register(BecomeUserWithoutBecomeRule()) <NEW_LINE> success = "examples/playbooks/become-user-without-become-success.yml" <NEW_LINE> good_runner = Runner(success, rules=collection) <NEW_LINE> assert [] == good_runn... | Positive test for partial-become. | 625941c460cbc95b062c6537 |
def test_e_edit_inside_apply(self): <NEW_LINE> <INDENT> start_time = "2017-10-10" <NEW_LINE> eamount = "80000" <NEW_LINE> year_sales = "90" <NEW_LINE> lianbao_daikuan_yue = "0" <NEW_LINE> jiufen = "否" <NEW_LINE> inside.inside_apply(self.webdriver, self.loanno, self.fullname, self.loan_type, self.marry_status, self.bank... | 编辑内部审批 | 625941c4f9cc0f698b1405f1 |
def __init__(self, version, sid): <NEW_LINE> <INDENT> super(AssistantContext, self).__init__(version) <NEW_LINE> self._solution = {'sid': sid, } <NEW_LINE> self._uri = '/Assistants/{sid}'.format(**self._solution) <NEW_LINE> self._field_types = None <NEW_LINE> self._tasks = None <NEW_LINE> self._model_builds = None <NEW... | Initialize the AssistantContext
:param Version version: Version that contains the resource
:param sid: A 34-character string that uniquely identifies this resource.
:returns: twilio.rest.autopilot.v1.assistant.AssistantContext
:rtype: twilio.rest.autopilot.v1.assistant.AssistantContext | 625941c438b623060ff0ade2 |
def request_hints(): <NEW_LINE> <INDENT> result = {} <NEW_LINE> for var in [ "SERVER_ADDR", "LOCAL_ADDR" ]: <NEW_LINE> <INDENT> value = request.environ.get(var, None) <NEW_LINE> if value is not None: <NEW_LINE> <INDENT> result["server"] = value <NEW_LINE> break <NEW_LINE> <DEDENT> <DEDENT> try: <NEW_LINE> <INDENT> requ... | Return tuple of (hints, response). If hints is None, response is a
response for the caller to return to the requester. | 625941c430c21e258bdfa490 |
def __init__(self): <NEW_LINE> <INDENT> MaximaFunction.__init__(self, name) | Constructs an object that wraps a Maxima function.
TESTS::
sage: spherical_hankel2(2,x)
(-I*x^2 - 3*x + 3*I)*e^(-I*x)/x^3 | 625941c40c0af96317bb81dc |
def _decrypt_data(self, session_data): <NEW_LINE> <INDENT> if self.encrypt_key: <NEW_LINE> <INDENT> try: <NEW_LINE> <INDENT> __, nonce_b64len = self.encrypt_nonce_size <NEW_LINE> nonce = session_data[:nonce_b64len] <NEW_LINE> encrypt_key = crypto.generateCryptoKeys(self.encrypt_key, self.validate_key + nonce, 1) <NEW_L... | Bas64, decipher, then un-serialize the data for the session
dict | 625941c44f6381625f114a30 |
def get_raw(self, use_cache=None): <NEW_LINE> <INDENT> params = {} <NEW_LINE> if use_cache is not None: <NEW_LINE> <INDENT> params["useCache"] = use_cache <NEW_LINE> <DEDENT> response = self.connection.api_call( "GET", ["deliveries", self.dataset_id, self.id, "raw"], params=params ) <NEW_LINE> resource_list = response.... | Get the raw delivery data
Args:
use_cache (bool): Preference to set cached response
Returns:
list (:obj:`crux.models.Resource`): List of resources. | 625941c46fb2d068a760f08f |
def test_without_strip_whitespace(self): <NEW_LINE> <INDENT> strip = Strip(strip_whitespace=False) <NEW_LINE> result = strip(["a", "", " ", "b"]) <NEW_LINE> self.assertListEqual(result, ["a", " ", "b"]) | Only empty items must be removed. | 625941c4ab23a570cc250175 |
def testCreateGroups(self): <NEW_LINE> <INDENT> with sudo.SudoKeepAlive(): <NEW_LINE> <INDENT> with cgroups.SimpleContainChildren('example', sigterm_timeout=5): <NEW_LINE> <INDENT> parallel.RunTasksInProcessPool(self._CrosSdk, [[]] * 20, 10) | Run many cros_sdk processes in parallel to test for race conditions. | 625941c4004d5f362079a328 |
def __init__(self, images, *, custom_classes=None, images_processed=None, warnings=None): <NEW_LINE> <INDENT> self.custom_classes = custom_classes <NEW_LINE> self.images_processed = images_processed <NEW_LINE> self.images = images <NEW_LINE> self.warnings = warnings | Initialize a ClassifiedImages object.
:param list[ClassifiedImage] images: Classified images.
:param int custom_classes: (optional) Number of custom classes identified
in the images.
:param int images_processed: (optional) Number of images processed for the
API call.
:param list[WarningInfo] warnings: (o... | 625941c4be383301e01b547d |
def test_set_is_poa(self): <NEW_LINE> <INDENT> article_xml_file = "pb369-jats.xml" <NEW_LINE> file_path = TEST_DATA_PATH + article_xml_file <NEW_LINE> config_section = "pb" <NEW_LINE> articles = generate.build_articles_for_pubmed( article_xmls=[file_path], config_section=config_section ) <NEW_LINE> articles[0].is_poa =... | test a method to make a non-eLife article aheadofprint by setting is_poa | 625941c45fcc89381b1e16b2 |
def find_best_split(data): <NEW_LINE> <INDENT> best_gain = 0 <NEW_LINE> best_question = None <NEW_LINE> current_uncertainty = gini_impurity(data['label']) <NEW_LINE> n_features = list(data.columns) <NEW_LINE> n_features.remove('label') <NEW_LINE> for col in n_features: <NEW_LINE> <INDENT> values = list(data[col].value_... | Find the best question to ask by iterating over every feature / value
and calculating the information gain. | 625941c4046cf37aa974cd3d |
def removeFirst(e, L): <NEW_LINE> <INDENT> if L == []: <NEW_LINE> <INDENT> return [] <NEW_LINE> <DEDENT> elif L == '': <NEW_LINE> <INDENT> return '' <NEW_LINE> <DEDENT> elif L[0] == e: <NEW_LINE> <INDENT> return L[1:] <NEW_LINE> <DEDENT> elif isinstance(L, list) == True: <NEW_LINE> <INDENT> return [L[0]] + removeFirst(... | Returns a list identical to list L
without the first top-level instance of e.
input e: an element
input L: a list | 625941c431939e2706e4ce60 |
def set_html_resources_prefix(self, prefix): <NEW_LINE> <INDENT> self.html_resources_prefix = prefix + '-' | Sets the prefix for the resources filename.
example: set_resources_prefix('jbds') | 625941c47c178a314d6ef451 |
def shear(value: float = 0.0, mirror: bool = False, proportional: int = 'DISABLED', proportional_edit_falloff: int = 'SMOOTH', proportional_size: float = 1.0, snap: bool = False, snap_target: int = 'CLOSEST', snap_point: float = (0.0, 0.0, 0.0), snap_align: bool = False, snap_normal: float = (0.0, 0.0, 0.0), gpencil_st... | Shear selected items along the horizontal screen axis
:param value: Offset
:type value: float
:param mirror: Mirror Editing
:type mirror: bool
:param proportional: Proportional EditingDISABLED Disable, Proportional Editing disabled.ENABLED Enable, Proportional Editing enabled.PROJECTED Projected (2D), Proportional ... | 625941c58c3a8732951583ad |
@fixture <NEW_LINE> def post(request, entity): <NEW_LINE> <INDENT> schema = 'https://tent.io/types/post/status/v0.1.0' <NEW_LINE> post = Post(entity=entity, schema=schema) <NEW_LINE> post.new_version( content={ 'text': "Hello world", 'coordinates': [0, 0], }, mention=[]) <NEW_LINE> post.new_version( content={ 'text': "... | A post with multiple versions | 625941c4379a373c97cfab38 |
def match_dict_regexp(d, r): <NEW_LINE> <INDENT> for pattern, elem in d.items(): <NEW_LINE> <INDENT> result = re.match(pattern, r) <NEW_LINE> if result: <NEW_LINE> <INDENT> return elem, result <NEW_LINE> <DEDENT> <DEDENT> return None, None | The same as d[r] but uses regex match.
Return (d[r] and match_result)
Return None in case no match found. | 625941c5b830903b967e9901 |
def circle_shift(data, random_state=None): <NEW_LINE> <INDENT> random_state = check_random_state(random_state) <NEW_LINE> data = np.array(data) <NEW_LINE> if len(data.shape) == 1: <NEW_LINE> <INDENT> shift = random_state.choice(np.arange(len(data)), replace=False) <NEW_LINE> shifted = np.concatenate((data[-shift:], dat... | Circle shift data for each feature
Args:
data: time series (1D or 2D). If 2D, then must be observations by features
random_state: (int, None, or np.random.RandomState) Initial random seed (default: None)
Returns:
shifted data | 625941c5097d151d1a222e4f |
def get_price(self): <NEW_LINE> <INDENT> return self.unit_price | Returns the price for this item (provided for extensibility). | 625941c59f2886367277a883 |
def base_context(request): <NEW_LINE> <INDENT> return { 'SITE_NAME': settings.SITE_NAME, 'SITE_SUB_NAME': settings.SITE_SUB_NAME, } | Base Settings to Context | 625941c571ff763f4b54967d |
def createUniqueFragmentsTable(self,color=None,unique_fragments=None,average_unique=None): <NEW_LINE> <INDENT> vTableHtml = [] <NEW_LINE> self.tableDefinition(vectorHtml=vTableHtml,color=color) <NEW_LINE> vTableHtml.append(" <TR>\n") <NEW_LINE> vTableHtml.append(" <TH scope=\"col\">Concept</TH> <TH scope=\"col\">V... | Create Unique and Fragments Statistics Table
color - Table color, could be green or blue
unique_fragments - Fragments that were considere as unique
average_unique - Average unique fragments
returns vector of HTML tags | 625941c556ac1b37e62641c7 |
def p_boolean_bracket(p): <NEW_LINE> <INDENT> p[0] = "(" + str(p[2]) + ")" | boolean : LPAREN boolean RPAREN | 625941c58da39b475bd64f66 |
def masked_max_pooling(data_tensor, mask, dim): <NEW_LINE> <INDENT> if dim < 0: <NEW_LINE> <INDENT> dim = len(data_tensor.shape) + dim <NEW_LINE> <DEDENT> mask = mask.view(list(mask.shape) + [1] * (len(data_tensor.shape) - len(mask.shape))) <NEW_LINE> data_tensor = data_tensor.masked_fill(mask == 0, -1e9) <NEW_LINE> ma... | Performs masked max-pooling across the specified dimension of a Tensor.
:param data_tensor: ND Tensor.
:param mask: Tensor containing a binary mask that can be broad-casted to the shape of data_tensor.
:param dim: Int that corresponds to the dimension.
:return: (N-1)D Tensor containing the result of the max-pooling op... | 625941c585dfad0860c3ae4f |
@rule(Regex(r'[a-zA-Z_][a-zA-Z0-9_]*')) <NEW_LINE> def identifier(value): <NEW_LINE> <INDENT> return value | An identifier. | 625941c563f4b57ef0001112 |
def remove_strand_ambiguous_snp(a1, a2, strand_ambiguous_alleles): <NEW_LINE> <INDENT> a1a2 = a1 + a2 <NEW_LINE> if strand_ambiguous_alleles[a1a2]: <NEW_LINE> <INDENT> return(False) <NEW_LINE> <DEDENT> else: <NEW_LINE> <INDENT> return(True) | remove snps where strand cannot be determined | 625941c50a50d4780f666e86 |
def _linear(args, output_size, bias, bias_start=0.0, scope=None): <NEW_LINE> <INDENT> if args is None or (nest.is_sequence(args) and not args): <NEW_LINE> <INDENT> raise ValueError("`args` must be specified") <NEW_LINE> <DEDENT> if not nest.is_sequence(args): <NEW_LINE> <INDENT> args = [args] <NEW_LINE> <DEDENT> total_... | Linear map: sum_i(args[i] * W[i]), where W[i] is a variable.
Args:
args: a 2D Tensor or a list of 2D, batch x n, Tensors.
output_size: int, second dimension of W[i].
bias: boolean, whether to add a bias term or not.
bias_start: starting value to initialize the bias; 0 by default.
scope: VariableSco... | 625941c563b5f9789fde70da |
def lambda_handler(event, context): <NEW_LINE> <INDENT> print('-------------------------') <NEW_LINE> bucketing_decision = None <NEW_LINE> querystring_params = event["queryStringParameters"] or {} <NEW_LINE> user_ip_address = event['requestContext']['identity']['sourceIp'] <NEW_LINE> user_id = querystring... | Demonstrates a simple HTTP endpoint using API Gateway. You have full
access to the request and response payload, including headers and
status code. | 625941c5c432627299f04c39 |
def _get(self): <NEW_LINE> <INDENT> character = self.look_ahead <NEW_LINE> self.look_ahead = None <NEW_LINE> if character == None: <NEW_LINE> <INDENT> character = self.input_file.read(1) <NEW_LINE> <DEDENT> if character >= " " or character == "\n": <NEW_LINE> <INDENT> return character <NEW_LINE> <DEDENT> if character =... | return the next character from stdin. Watch out for lookahead. If
the character is a control character, translate it to a space or
linefeed. | 625941c55510c4643540f3dd |
def shoot(self, beam_x, beam_y, charged=False): <NEW_LINE> <INDENT> if not charged: <NEW_LINE> <INDENT> b = PlayerWeapon(beam_x, beam_y) <NEW_LINE> <DEDENT> else: <NEW_LINE> <INDENT> b = PlayerWeaponCharged(beam_x, beam_y) <NEW_LINE> b.charging = True <NEW_LINE> self.charged_beam = b <NEW_LINE> <DEDENT> return b | Arguments:
beam_x (int): x coordinate of where beam will be drawn
beam_y (int): y coordinate of where beam will be drawn
charged (bool): True/False depending on whether it is a charged beam or not
Returns:
A newly created beam object | 625941c5ab23a570cc250176 |
def print_node_edge(graph, graph_name): <NEW_LINE> <INDENT> print("{0} number_of_nodes : {1}".format(graph_name, graph.number_of_nodes())) <NEW_LINE> print("{0} number_of_edges : {1}".format(graph_name, graph.number_of_edges())) | Graph의 node와 edge를 보여준다 | 625941c58da39b475bd64f67 |
def psimso_cv_reference_index(self, psimso_id): <NEW_LINE> <INDENT> if not hasattr(self, 'psimso_index_dict'): <NEW_LINE> <INDENT> self.psimso_index_dict = dict([(ref[2], i) for (i, ref) in enumerate(self.all_cv_references()) if ref[1] == 'MS']) <NEW_LINE> <DEDENT> return self.psimso_index_dict[psimso_id] | Takes in a Proteomics Standards Initiative Mass Spectrometry Ontology
identifier (psimso_id) and returns the HDF5 CV reference index for that
identifier. | 625941c59c8ee82313fbb769 |
def get_vms(self, root=None): <NEW_LINE> <INDENT> raw_vms = self._get_all_objs([vim.VirtualMachine], root) <NEW_LINE> return sorted(raw_vms, key=lambda vm: vm.summary.config.name) | Returns all vms | 625941c5796e427e537b05b9 |
def generate_java(src, out, jpackage_name=None): <NEW_LINE> <INDENT> package = compile(src) <NEW_LINE> java.generate(package, out, jpackage_name=jpackage_name) | Generates java files. | 625941c5e1aae11d1e749caa |
def g_connect(versions): <NEW_LINE> <INDENT> def decorator(method): <NEW_LINE> <INDENT> def wrapped(self, *args, **kwargs): <NEW_LINE> <INDENT> if not self._available_api_versions: <NEW_LINE> <INDENT> display.vvvv("Initial connection to galaxy_server: %s" % self.api_server) <NEW_LINE> n_url = self.api_server <NEW_LINE>... | Wrapper to lazily initialize connection info to Galaxy and verify the API versions required are available on the
endpoint.
:param versions: A list of API versions that the function supports. | 625941c5d10714528d5ffcd6 |
def index_impl(self): <NEW_LINE> <INDENT> runs = self._multiplexer.Runs() <NEW_LINE> result = {run: {} for run in runs} <NEW_LINE> mapping = self._multiplexer.PluginRunToTagToContent(metadata.PLUGIN_NAME) <NEW_LINE> for (run, tag_to_content) in six.iteritems(mapping): <NEW_LINE> <INDENT> for (tag, content) in six.iteri... | Return {runName: {tagName: {displayName: ..., description: ...}}}. | 625941c567a9b606de4a7eb0 |
def remove(self, grid): <NEW_LINE> <INDENT> if self._action == INSERT: <NEW_LINE> <INDENT> grid.remove_row(self.row) <NEW_LINE> <DEDENT> else: <NEW_LINE> <INDENT> grid.insert_row(self.row) | Revert the action. | 625941c5046cf37aa974cd3e |
def floating_ip_added_dist(self, fip, fip_cidr): <NEW_LINE> <INDENT> if fip.get(lib_constants.DVR_SNAT_BOUND): <NEW_LINE> <INDENT> return self.add_centralized_floatingip(fip, fip_cidr) <NEW_LINE> <DEDENT> if not self._check_if_floatingip_bound_to_host(fip): <NEW_LINE> <INDENT> return <NEW_LINE> <DEDENT> if (self.agent_... | Add floating IP to respective namespace based on agent mode. | 625941c507d97122c417887d |
def p_square_block(p): <NEW_LINE> <INDENT> child1 = create_leaf('SQUARE_BEGIN', p[1]) <NEW_LINE> child2 = create_leaf('SQUARE_END', p[3]) <NEW_LINE> p[0] = Node('square_block', [child1, p[2],child2], p[2].type, None,None,None,None) | square_block : SQUARE_BEGIN type SQUARE_END | 625941c57b180e01f3dc47f5 |
def lambda_handler(event, context): <NEW_LINE> <INDENT> raw_kpl_records = event['records'] <NEW_LINE> output = [process_kpl_record(kpl_record) for kpl_record in raw_kpl_records] <NEW_LINE> success_count = sum(1 for record in output if record['result'] == 'Ok') <NEW_LINE> failure_count = sum(1 for record in output if re... | A Python AWS Lambda function to process aggregated records sent to KinesisAnalytics. | 625941c5627d3e7fe0d68e44 |
def balanced_accuracy_multiclass(y_true, y_pred): <NEW_LINE> <INDENT> perclass_balanced_accuracy = np.zeros(np.unique(y_true).shape[0]) <NEW_LINE> for i, class_ in enumerate(np.unique(y_true)): <NEW_LINE> <INDENT> y_true_class = (y_true == class_).astype(int) <NEW_LINE> y_pred_class = (y_pred == class_).astype(int) <NE... | Return a balanced accuracy, supporting also multiclass learning.
This is computed averaging the balanced accuracy for each class.
Here
https://github.com/scikit-learn/scikit-learn/issues/6747
there is an issue on how to implement this in sklearn. | 625941c58e71fb1e9831d79f |
def test_get_index_sort_disk_format_asc(self): <NEW_LINE> <INDENT> UUID3 = _gen_uuid() <NEW_LINE> extra_fixture = {'id': UUID3, 'status': 'active', 'is_public': True, 'disk_format': 'ami', 'container_format': 'ami', 'name': 'asdf', 'size': 19, 'checksum': None} <NEW_LINE> db_api.image_create(self.context, extra_fixture... | Tests that the /images registry API returns list of
public images sorted alphabetically by disk_format in
ascending order. | 625941c5a79ad161976cc13a |
def _flush_buffer(self, post_ws_control=Token.WS_NONE): <NEW_LINE> <INDENT> text = "" <NEW_LINE> if self._buffer: <NEW_LINE> <INDENT> text = "".join(self._buffer) <NEW_LINE> if self._autostrip == self.AUTOSTRIP_STRIP: <NEW_LINE> <INDENT> text = text.strip() <NEW_LINE> <DEDENT> elif self._autostrip == self.AUTOSTRIP_TRI... | Flush the buffer to output. | 625941c53346ee7daa2b2d60 |
def add_blackhole_interfaces(offset, total_interfaces, interface_list): <NEW_LINE> <INDENT> if total_interfaces == len(interface_list): <NEW_LINE> <INDENT> return interface_list <NEW_LINE> <DEDENT> updated_interface_list = [] <NEW_LINE> for i in range(offset, total_interfaces + offset): <NEW_LINE> <INDENT> for interfac... | Adds blackhole interfaces to host data by inserting a
dict of blackhole config in the correct interface index position.
:param offset: Interface numbering offset.
:param total_interfaces: Total number of interfaces.
:param interface_list: List of interface dicts to update.
:return: New list of interface dicts. | 625941c5fff4ab517eb2f430 |
def test_template(self): <NEW_LINE> <INDENT> self.assertTemplateUsed(self.response, 'index.html') | Should get index.html template | 625941c5656771135c3eb862 |
def __init__(self, secret, path, plotall=True): <NEW_LINE> <INDENT> self.gc = pygsheets.authorize(outh_file=secret, outh_nonlocal=True, no_cache=True) <NEW_LINE> self.path = os.path.dirname(path) <NEW_LINE> self.plotall = plotall | Configure object.
Args:
secret (str): path to secret file
path (str): folder where plot are saved. Name of plot is same as name of datafile.
plotall (bool): If True, filename given when calling object is interpreted as prefix.
Otherwise it is exact name of file and only this plot ... | 625941c5c432627299f04c3a |
def get_tags(self): <NEW_LINE> <INDENT> return self.__tags | Returns the list of tags. | 625941c50383005118ecf5d9 |
def act(self, state): <NEW_LINE> <INDENT> if self.MODE == 'test': <NEW_LINE> <INDENT> return self.sess.run(self.actions, {self.states: state[np.newaxis, :]})[0] <NEW_LINE> <DEDENT> elif self.MODE == 'train': <NEW_LINE> <INDENT> if self.config['COUNTER'] < self.config['MEMORY_CAPACITY']: <NEW_LINE> <INDENT> if self.conf... | When the current state is inputted to this function, the current state is fed into the rl agent andthe action is outputted.
This function takes into consideration the concept of exploration and exploitation.
Args:
state (arr): the state parameter defined in the Simulator class.
Returns:
Either a randomly... | 625941c599cbb53fe6792bdc |
def _getFilePathFromId(self, jobStoreFileID): <NEW_LINE> <INDENT> absPath = os.path.join(self.jobStoreDir, jobStoreFileID) <NEW_LINE> return absPath | :param str jobStoreFileID: The ID of a file
:rtype : string, string is the absolute path that that file should
appear at on disk, under either self.jobsDir if it is to be
cleaned up with a job, or self.filesDir otherwise. | 625941c53d592f4c4ed1d067 |
def initGui(self): <NEW_LINE> <INDENT> icon_path = ':/plugins/VectorDistributionExtractionPerFile/icon.png' <NEW_LINE> self.add_action( icon_path, text=self.tr(u'Write the distribution of one or several vector layers/files in each feature of an area vector layer/file'), callback=self.run, parent=self.iface.mainWindow()... | Create the menu entries and toolbar icons inside the QGIS GUI. | 625941c53317a56b86939c51 |
def reshape_to_long_for_output(df): <NEW_LINE> <INDENT> del df['file_name'] <NEW_LINE> del df['link'] <NEW_LINE> del df['source'] <NEW_LINE> del df['version'] <NEW_LINE> del df['description'] <NEW_LINE> df = df.set_index(['year', 'code', 'ressources', 'institution', 'file_title']) <NEW_LINE> df = df.unstack(level = 'ye... | Unmelts the data, using the years as variables (columns).
Parameters
----------
df : DataFrame
DataFrame generated by get_comptes_nationaux_data(year) and/or look_many(df, my_selection)
Example
--------
>>> from ipp_macro_series_parser.comptes_nationaux.cn_parser_main import get_comptes_nationaux_data
>>> from ip... | 625941c5cc40096d61595946 |
def shbkDiff(self): <NEW_LINE> <INDENT> return currencyDiff(self.data, lexiconList()[7]) | 生活百科类接口
:return: | 625941c550812a4eaa59c318 |
def serialize_numpy(self, buff, numpy): <NEW_LINE> <INDENT> try: <NEW_LINE> <INDENT> _x = self <NEW_LINE> buff.write(_get_struct_3I().pack(_x.header.seq, _x.header.stamp.secs, _x.header.stamp.nsecs)) <NEW_LINE> _x = self.header.frame_id <NEW_LINE> length = len(_x) <NEW_LINE> if python3 or type(_x) == unicode: <NEW_LINE... | serialize message with numpy array types into buffer
:param buff: buffer, ``StringIO``
:param numpy: numpy python module | 625941c53eb6a72ae02ec4ce |
def ExportSetPlane(self,pPlane): <NEW_LINE> <INDENT> pass | ExportSetPlane(self: DelegateFake,pPlane: dotPlane_t) -> (int,dotPlane_t) | 625941c5004d5f362079a329 |
def perm_test(labels, response_vars, stat_func, n): <NEW_LINE> <INDENT> unique_label_counts = labels.value_counts() <NEW_LINE> label_0 = unique_label_counts.index[0] <NEW_LINE> label_1 = unique_label_counts.index[1] <NEW_LINE> label_0_count = unique_label_counts[0] <NEW_LINE> label_1_count = unique_label_counts[1] <NEW... | Labels: Series with two labels, Response_vars series in same order as labels
stat_func is a function that takes in two series and returns a statistic, n is permutation numnber | 625941c5dc8b845886cb5529 |
def write2grp(genomeSizeDict, fwd=None, rev=None, prefix=None, toInteger=True): <NEW_LINE> <INDENT> if (fwd and (not rev)) or (rev and (not fwd)): <NEW_LINE> <INDENT> if fwd: <NEW_LINE> <INDENT> header = "# BASE fwd_grp\n# colour 0:255:0\n" <NEW_LINE> wig = fwd <NEW_LINE> <DEDENT> else: <NEW_LINE> <INDENT> header = "# ... | convert wig to grp file
| 625941c5f8510a7c17cf96f1 |
def emit(self, record): <NEW_LINE> <INDENT> write_api = self.client.write_api(write_options=SYNCHRONOUS) <NEW_LINE> data = self.get_point(record) <NEW_LINE> write_api.write(self.bucket, self.org, data) | Emit a record.
Send the record to the Web server as line protocol | 625941c5adb09d7d5db6c786 |
def search_advanced(self): <NEW_LINE> <INDENT> self.form = my_forms.AdvancedSearchForm(self.request.GET) <NEW_LINE> if self.form.is_valid(): <NEW_LINE> <INDENT> and_list = [] <NEW_LINE> if 'search_name' in self.request.GET: <NEW_LINE> <INDENT> name = self.request.GET['search_name'].strip() <NEW_LINE> if len(name) > 0: ... | Constructs a raw PyMongo query dictionary from the get data, joining the filters
for each feild together with an $and operator. Sets self.search_list to the
models.Experiments queried by this dictionary
:return: | 625941c5a219f33f34628961 |
def _swipe_right(board, tile=0): <NEW_LINE> <INDENT> return _reverse(_swipe_left(_reverse(board), tile)) | Perform what happens at board level when you swipe right
Based on _swipe_left | 625941c5d7e4931a7ee9df12 |
def list_by_resource_group( self, resource_group_name, custom_headers=None, raw=False, **operation_config): <NEW_LINE> <INDENT> def internal_paging(next_link=None, raw=False): <NEW_LINE> <INDENT> if not next_link: <NEW_LINE> <INDENT> url = '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Mi... | Returns all the resources of a particular type belonging to a resource
group.
:param resource_group_name: The name of the resource group within the
user's subscription.
:type resource_group_name: str
:param dict custom_headers: headers that will be added to the request
:param bool raw: returns the direct response alo... | 625941c54d74a7450ccd41b9 |
def _make_dict_rec(self, name_list, rec): <NEW_LINE> <INDENT> r = {} <NEW_LINE> for i in range(0, len(name_list)): <NEW_LINE> <INDENT> r[name_list[i]] = rec[i] <NEW_LINE> <DEDENT> return r | 辞書型のレコードを作成
@param name_list カラム名一覧
@param rec レコードの配列 | 625941c5cc0a2c11143dce86 |
def _GetCredentials(): <NEW_LINE> <INDENT> return service_account.Credentials.from_service_account_file( KEY_FILE, scopes=_SCOPES) | Steps through Service Account OAuth 2.0 flow to retrieve credentials. | 625941c557b8e32f5248348f |
def OneDScan(init, final, steps): <NEW_LINE> <INDENT> if len(init) != len(final): <NEW_LINE> <INDENT> raise RuntimeError("init and final must have the same length") <NEW_LINE> <DEDENT> Answer = [] <NEW_LINE> for j in range(len(init)): <NEW_LINE> <INDENT> Answer.append(np.linspace(init[j], final[j], steps)) <NEW_LINE> <... | Return a list of N equally spaced values between initial and final.
This method works with lists of numbers
Parameters
----------
init : list
List of numbers to be interpolated
final : np.ndarray or list
List of final numbers, must have same shape as "init"
steps : int
Number of interpolation steps
Return... | 625941c544b2445a3393208c |
def get_archives(self, offset=None, count=None, session_id=None): <NEW_LINE> <INDENT> params = {} <NEW_LINE> if offset is not None: <NEW_LINE> <INDENT> params["offset"] = offset <NEW_LINE> <DEDENT> if count is not None: <NEW_LINE> <INDENT> params["count"] = count <NEW_LINE> <DEDENT> if session_id is not None: <NEW_LINE... | Returns an ArchiveList, which is an array of archives that are completed and in-progress,
for your API key.
:param int: offset Optional. The index offset of the first archive. 0 is offset
of the most recently started archive. 1 is the offset of the archive that started prior to
the most recent archive. If you do n... | 625941c5287bf620b61d3a5a |
def reset(self): <NEW_LINE> <INDENT> self.digital_write(self.reset_pin, GPIO.LOW) <NEW_LINE> self.delay_ms(200) <NEW_LINE> self.digital_write(self.reset_pin, GPIO.HIGH) <NEW_LINE> self.delay_ms(200) | @brief: module reset.
often used to awaken the module in deep sleep, | 625941c550812a4eaa59c319 |
@patch("pyphi.compute.distance._ces_distance_simple") <NEW_LINE> @patch("pyphi.compute.distance._ces_distance_emd") <NEW_LINE> def test_ces_distance_uses_simple_vs_emd(mock_emd_distance, mock_simple_distance, s): <NEW_LINE> <INDENT> mock_emd_distance.return_value = float() <NEW_LINE> mock_simple_distance.return_value =... | Quick check that we use the correct CES distance function.
If the two CESs differ only in that some concepts have
moved to the null concept and all other concepts are the same then
we use the simple CES distance. Otherwise, use the EMD. | 625941c55e10d32532c5ef1c |
def parse_link_descriptor(self, descriptor): <NEW_LINE> <INDENT> optional_attributes = {} <NEW_LINE> link_components = descriptor.split(":{", 1) <NEW_LINE> device = link_components[0] <NEW_LINE> if (len(link_components) == 2 and link_components[1].endswith("}")): <NEW_LINE> <INDENT> some_json = "{" + link_components[1]... | parse e.g. 'udpin:127.0.0.1:9877:{"foo":"bar"}' into
python structure ("udpin:127.0.0.1:9877", {"foo":"bar"}) | 625941c5e8904600ed9f1f20 |
def write_log(r_info, r_settings, f_name): <NEW_LINE> <INDENT> if r_info['code'] == '404': <NEW_LINE> <INDENT> stats['urls checked'] += 1 <NEW_LINE> can_write = True <NEW_LINE> <DEDENT> elif r_info['err'] == '1' and r_settings['report_errors']: <NEW_LINE> <INDENT> stats['errors'] += 1 <NEW_LINE> can_write = True <NEW_L... | Logs selected data to the 404 report | 625941c5711fe17d82542364 |
def remove_duplicates_without_buffer(self, k): <NEW_LINE> <INDENT> current =self.head <NEW_LINE> while current is not None: <NEW_LINE> <INDENT> runner = current <NEW_LINE> while runner.next is not None: <NEW_LINE> <INDENT> if runner.next.data == current.data: <NEW_LINE> <INDENT> runner.next = runner.next.next <NEW_LINE... | O(n^2)
:return: | 625941c591af0d3eaac9ba0d |
def plot_junction(eptm, edge_index, coords=["x", "y"]): <NEW_LINE> <INDENT> v10, v11 = eptm.edge_df.loc[edge_index, ["srce", "trgt"]] <NEW_LINE> fig, ax = plt.subplots() <NEW_LINE> ax.scatter(*eptm.vert_df.loc[[v10, v11], coords].values.T, marker="+", s=300) <NEW_LINE> v10_out = set(eptm.edge_df[eptm.edge_df["srce"] ==... | Plots local graph around a junction, for debugging purposes. | 625941c5498bea3a759b9aa5 |
def makeJPsi2eMu(name, myconfig): <NEW_LINE> <INDENT> JPsi2eMu = CombineParticles( DecayDescriptors = ["[J/psi(1S) -> e+ mu-]cc","[J/psi(1S) -> e+ mu+]cc"], DaughtersCuts = { "mu+" : "(MIPCHI2DV(PRIMARY)> {min_MIPCHI2DV}) & (TRCHI2DOF < {max_TRCHI2DV}) & (TRGHOSTPROB< {max_TRGHOSTPROB})".format(**myconfig) , "e+" : "(... | Please contact Johannes Albrecht if you think of prescaling this line!
Arguments:
name : name of the Selection. | 625941c5507cdc57c6306ccd |
def summarise_stat(stat): <NEW_LINE> <INDENT> pet_names = [ "sweet pea", "human", "fellow", "angel", "colleague", "boiii", "friend", "individual", "person", "muffin", "amiga/amigo", "inspiration", "acquaintance", ] <NEW_LINE> ratio = stat["good_days"] / stat["total_days"] <NEW_LINE> return ( f'{stat["name"]} my {random... | Return an English paragraph summarising the monthly stat for a user | 625941c5a05bb46b383ec819 |
def confirm_sell(self, keys, current_time): <NEW_LINE> <INDENT> dialogue = ['Are you sure?'] <NEW_LINE> choices = ['Yes', 'No'] <NEW_LINE> self.dialogue_box = self.make_dialogue_box(dialogue, 0) <NEW_LINE> self.selection_box = self.make_selection_box(choices) <NEW_LINE> self.selection_arrow.rect.topleft = self.two_arro... | Confirm player wants to sell item. | 625941c5d7e4931a7ee9df13 |
def max_filter(img, filter_dim): <NEW_LINE> <INDENT> img_h, img_w=img.shape <NEW_LINE> for i in range(img_h-filter_dim+1): <NEW_LINE> <INDENT> for j in range(img_w-filter_dim+1): <NEW_LINE> <INDENT> max_value=0 <NEW_LINE> for i_i in range(filter_dim): <NEW_LINE> <INDENT> for j_j in range(filter_dim): <NEW_LINE> <INDENT... | this function sets the pixel value as the max value of the pixels around. | 625941c5187af65679ca5114 |
def stationLocation(self, *args): <NEW_LINE> <INDENT> return _Client.Inventory_stationLocation(self, *args) | stationLocation(self, string networkCode, string stationCode, Time arg2) -> StationLocation | 625941c538b623060ff0ade3 |
def get_predictor(self, n): <NEW_LINE> <INDENT> l = len(self.predictors) <NEW_LINE> if n >= l: <NEW_LINE> <INDENT> logger.warn("n > #towers, will assign predictor to GPU by round-robin") <NEW_LINE> <DEDENT> return [self.predictors[k % l] for k in range(n)] | Returns:
PredictorBase: the nth predictor on the nth tower. | 625941c58c0ade5d55d3e9af |
def hangman(secretWord): <NEW_LINE> <INDENT> print('Welcome to the game Hangman!') <NEW_LINE> print('I am thinking of a word that is', len(secretWord), 'letters long') <NEW_LINE> guesses = 8 <NEW_LINE> lettersGuessed = [] <NEW_LINE> win = False <NEW_LINE> while guesses > 0: <NEW_LINE> <INDENT> print('-----------') <NEW... | secretWord: string, the secret word to guess.
Starts up an interactive game of Hangman.
* At the start of the game, let the user know how many
letters the secretWord contains.
* Ask the user to supply one guess (i.e. letter) per round.
* The user should receive feedback immediately after each guess
about whet... | 625941c5d10714528d5ffcd7 |
def train(self, xs, ys): <NEW_LINE> <INDENT> memory, src_masks = self.encode(xs) <NEW_LINE> logits, y = self.decode(ys, memory, src_masks) <NEW_LINE> ce = tf.nn.softmax_cross_entropy_with_logits_v2(logits=logits, labels=y) <NEW_LINE> loss = tf.reduce_mean(ce) <NEW_LINE> global_step = tf.train.get_or_create_global_step(... | Returns
loss: scalar.
train_op: training operation
global_step: scalar.
summaries: training summary node | 625941c5d164cc6175782d43 |
def transaction(self): <NEW_LINE> <INDENT> if dnfpluginsextras.is_erasing(self.base.transaction, "tracer"): <NEW_LINE> <INDENT> return <NEW_LINE> <DEDENT> if self.base.conf.installroot != "/": <NEW_LINE> <INDENT> return <NEW_LINE> <DEDENT> if not len(self.base.transaction): <NEW_LINE> <INDENT> return <NEW_LINE> <DEDENT... | Call after successful transaction
See https://rpm-software-management.github.io/dnf/api_transaction.html | 625941c5956e5f7376d70e64 |
def _cancel_team_workflow(self, team_submission_uuid, comments, requesting_user_id=None): <NEW_LINE> <INDENT> from openassessment.workflow import team_api as team_workflow_api <NEW_LINE> try: <NEW_LINE> <INDENT> if requesting_user_id is None: <NEW_LINE> <INDENT> requesting_user_id = self.get_student_item_dict()["studen... | Internal helper method to cancel a team workflow using the team workflow API.
If requesting_user is not provided, we will use the user to which this xblock is currently bound. | 625941c50a366e3fb873e80f |
def _make_dir(self): <NEW_LINE> <INDENT> hyper_name = self.uid + "_" + self.args.model_name <NEW_LINE> out_dir = "./{}/{}/{}/{}".format( self.args.log_dir, self.args.dataset, self.args.model_name, self.uid ) <NEW_LINE> try: <NEW_LINE> <INDENT> os.makedirs(out_dir) <NEW_LINE> <DEDENT> except OSError as exc: <NEW_LINE> <... | Make out directory for log file and saving models | 625941c5baa26c4b54cb1117 |
def use_template(self, name, values): <NEW_LINE> <INDENT> self._intf._get_entry_point() <NEW_LINE> bundle = self.get_template(name, True) % values <NEW_LINE> _query = query_from_xml(bundle) <NEW_LINE> bundle = build_search_document(_query['row'], _query['columns'], _query['constraints'] ) <NEW_LINE> content = self._int... | Performs a search query using a previously saved template.
Parameters
----------
name: string
Name of the template.
values: dict
Values to put in the template, get the valid keys using
the get_template method.
Examples
--------
>>> interface.manage.search.use_template(name,
{'subject_id':'ID... | 625941c54f88993c3716c05e |
def __eq__(self, other): <NEW_LINE> <INDENT> if not isinstance(other, JDBCAutoDiscoveryMethod): <NEW_LINE> <INDENT> return False <NEW_LINE> <DEDENT> return self.__dict__ == other.__dict__ | Returns true if both objects are equal | 625941c5ab23a570cc250177 |
def StudentIsExist(self, sno): <NEW_LINE> <INDENT> flag = self._DBHelper.fetchone( "select * from main.students where sno=%s" % sno) <NEW_LINE> if flag: <NEW_LINE> <INDENT> return True <NEW_LINE> <DEDENT> else: <NEW_LINE> <INDENT> return False | 查询是否存在当前个人学号信息,存在为True 不存在返回False | 625941c5b830903b967e9902 |
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