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def check_status(self, agent_positions): <NEW_LINE> <INDENT> if not self.dead and (self.sugar <= 0 or self.spice <= 0 or self.age == self.dying_age): <NEW_LINE> <INDENT> self.die(agent_positions) <NEW_LINE> <DEDENT> self.age += 1
Check whether I'm still healthy and stuff
625941c7d99f1b3c44c675d5
def split(s): <NEW_LINE> <INDENT> s = tuple(s) <NEW_LINE> size = len(s) <NEW_LINE> return s[:size//2], s[size//2:]
Split s into two roughly equal parts
625941c75fdd1c0f98dc0278
def _cpshnext(self, args=None): <NEW_LINE> <INDENT> self.cpinfo['shtime'] = args['time'] <NEW_LINE> self.savestate()
handle cpshnext
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def _add_self_references(namespace, autograph_module): <NEW_LINE> <INDENT> global ag_internal <NEW_LINE> if ag_internal is None: <NEW_LINE> <INDENT> ag_internal = imp.new_module('autograph') <NEW_LINE> ag_internal.__dict__.update(autograph_module.__dict__) <NEW_LINE> ag_internal.ConversionOptions = converter.Conversion...
Adds namespace references to the module that exposes the api itself.
625941c7187af65679ca5163
def set_sticker_position_in_set(self, sticker, position): <NEW_LINE> <INDENT> return apihelper.set_sticker_position_in_set(self.token, sticker, position)
Use this method to move a sticker in a set created by the bot to a specific position . Returns True on success. :param sticker: :param position: :return:
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def __init__(self, width=640, height=400, fps=30): <NEW_LINE> <INDENT> pygame.init() <NEW_LINE> pygame.display.set_caption("Press ESC to quit") <NEW_LINE> self.width = width <NEW_LINE> self.height = height <NEW_LINE> self.screen = pygame.display.set_mode((self.width, self.height), pygame.DOUBLEBUF) <NEW_LINE> self.back...
Initialize pygame, window, background, font,... default arguments
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@docfiller <NEW_LINE> def gaussian_filter1d(input, sigma, axis=-1, order=0, output=None, mode="reflect", cval=0.0, truncate=4.0): <NEW_LINE> <INDENT> if order not in range(4): <NEW_LINE> <INDENT> raise ValueError('Order outside 0..3 not implemented') <NEW_LINE> <DEDENT> sd = float(sigma) <NEW_LINE> lw = int(truncate * ...
One-dimensional Gaussian filter. Parameters ---------- %(input)s sigma : scalar standard deviation for Gaussian kernel %(axis)s order : {0, 1, 2, 3}, optional An order of 0 corresponds to convolution with a Gaussian kernel. An order of 1, 2, or 3 corresponds to convolution with the first, second or thi...
625941c7e8904600ed9f1f70
def get_rcmd_users(user): <NEW_LINE> <INDENT> sex = user.profile.dating_sex <NEW_LINE> location = user.profile.location <NEW_LINE> min_age = user.profile.min_dating_age <NEW_LINE> max_age = user.profile.max_dating_age <NEW_LINE> current_year = datetime.date.today().year <NEW_LINE> min_year = current_year - min_age <NEW...
获取用户列表 :param user: :return: max_year min_year current_year ----|-----------------|----------------|--------------|--------> 2018 2019
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def play_theme(self): <NEW_LINE> <INDENT> songs = ['james_bond','glad_you_came'] <NEW_LINE> try: <NEW_LINE> <INDENT> pg.mixer.music.stop() <NEW_LINE> play_theme_song(songs[random.randint(0,1)],1) <NEW_LINE> <DEDENT> except Exception: <NEW_LINE> <INDENT> play_theme_song(songs[random.randint(0,1)],1)
Selects a random theme for the game
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def test_iter(self): <NEW_LINE> <INDENT> self.__add_movies() <NEW_LINE> imdbList = list(self.movie_data) <NEW_LINE> self.assertListEqual( imdbList, ['tt0110912', 'tt0090605', 'tt0268978'], )
Load movies and make sure the iterator returns the movies in the correct order
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def getModel(self, model, data, stringresponse=False): <NEW_LINE> <INDENT> apiurl = urljoin(self.api.scheme + '://', COGNIOUS_API_BASEURL, 'v1.0', model) <NEW_LINE> headers = self.api.headers <NEW_LINE> res = requests.post(apiurl, headers=headers, data=data) <NEW_LINE> if res.status_code == 200: <NEW_LINE> <INDENT> sel...
**DEPRICATED** scheme = 'https' if parsed.scheme == '' else parsed.scheme base_url = parsed.path if not parsed.netloc else parsed.netloc self.base_url = base_url self.scheme = scheme
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def _log_info(self, message, level=0, offset=0): <NEW_LINE> <INDENT> if level == 0 or (self._debug and self._debug_level >= level): <NEW_LINE> <INDENT> tf.logging.info("[LMS][{}] ".format(level) + ' '*offset + "{}".format(message))
Log debug information. Args: message: a formatted string. level: an `integer`.
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def test_user_cannot_retrieve_unregistered_person(self): <NEW_LINE> <INDENT> logger = logging.getLogger('django.request') <NEW_LINE> previous_level = logger.getEffectiveLevel() <NEW_LINE> logger.setLevel(logging.ERROR) <NEW_LINE> url = reverse( 'person-detail', kwargs={'person_guid': self.unregistered_driller.person_gu...
unauthorized request to person detail view. Note: now always returns 401 if not staff.
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def __len__(self): <NEW_LINE> <INDENT> return len(self.Serialize())
Return a length of serialized packet .
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def slot_style(self, style): <NEW_LINE> <INDENT> selection = self.editor.selection <NEW_LINE> if selection.isSelection(): <NEW_LINE> <INDENT> sm1, sm2 = selection.order() <NEW_LINE> tl = sm1[0].tline <NEW_LINE> self.rsubject.restyle(tl, sm2[0].tline.para, style) <NEW_LINE> selection.markSelection() <NEW_LINE> <DEDENT> ...
Handler for 'style' action - change style: u"n"/normal, u"l"/special, u"r"/special/right-aligned
625941c7c432627299f04c8a
def check_solution(self, potential_solution): <NEW_LINE> <INDENT> old_k = self.K <NEW_LINE> new_k = potential_solution.set_K(self.len_connections) <NEW_LINE> delta = new_k - old_k <NEW_LINE> if delta >= 0: <NEW_LINE> <INDENT> probability = 1 <NEW_LINE> <DEDENT> probability = np.exp(delta / self.T) <NEW_LINE> if random....
Calculates new and old K. Checks and accepts better solutions than the current solution. Also sometimes accepts solutions that are worse, depending on the current temperature.
625941c776d4e153a657eb76
def load_repos_info(channel_lookup): <NEW_LINE> <INDENT> with open(os.path.join(SCRIPT_DIR, "repos_info.json"), "r", encoding="utf-8") as f: <NEW_LINE> <INDENT> repos_info = json.load(f) <NEW_LINE> <DEDENT> infos = [ RepoInfo( name=repo_info["name"], repo_url=repo_info["repo_url"], ci_hash_url=( repo_info["ci_hash_url"...
Load repo information from JSON and looks up channel ids for each repo Args: channel_lookup (dict): Map of channel names to channel ids Returns: list of RepoInfo: Information about the repositories
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def remove(self, child): <NEW_LINE> <INDENT> if isinstance(child, JSONableDict): <NEW_LINE> <INDENT> try: <NEW_LINE> <INDENT> del(self[child.name]) <NEW_LINE> <DEDENT> except KeyError: <NEW_LINE> <INDENT> warnings.warn('{0} not found in dict when attempting removal'.format(child.name)) <NEW_LINE> <DEDENT> <DEDENT> else...
Remove a child node Args: child: An instance of JSONableDict Raises: AddRemoveError: :exc:`cfn_pyplates.exceptions.AddRemoveError`
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def insert_object(self, index, obj): <NEW_LINE> <INDENT> self.__objects.insert(index, obj)
Insert an item before specific position. :param index: The position. :param obj: The object.
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def test_register(self): <NEW_LINE> <INDENT> def test_converter(session, value): <NEW_LINE> <INDENT> pass <NEW_LINE> <DEDENT> self.translator.register('convert', test_converter) <NEW_LINE> assert_true(self.translator.converters.has_key('convert')) <NEW_LINE> assert_equals(len(self.translator.converters.keys()), 2) <NEW...
Test that the register method works as expected (i.e., registers the specified converter) .. versionadded:: v00_03_00
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def _train_controller(self): <NEW_LINE> <INDENT> self._search_space.eval() <NEW_LINE> self._controller.train() <NEW_LINE> for _ in range(self._controller_max_steps): <NEW_LINE> <INDENT> dag, log_prob = self._controller() <NEW_LINE> self._search_space.dag = dag <NEW_LINE> batch = self._valid_iter.next() <NEW_LINE> input...
Training the controller parameters Fix omega and update the policy parameters theta the gradient is computed using REINFORCE, with a moving average baseline to reduce variance.
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def minimum_x(x): <NEW_LINE> <INDENT> def decorator(fun): <NEW_LINE> <INDENT> def wrapper(y): <NEW_LINE> <INDENT> if y >= x: <NEW_LINE> <INDENT> fun(y) <NEW_LINE> <DEDENT> else: <NEW_LINE> <INDENT> raise ValueError <NEW_LINE> <DEDENT> <DEDENT> return wrapper <NEW_LINE> <DEDENT> return decorator
Write a function decorator that takes an argument, and returns a decorator that can be used to decorate a function, which verifies that the first argument to a decorated function is at least the given value, raising a ValueError on failure. >>> @minimum_x(6) ... def test(arg): ... print arg ... >>> test(6) 6 >>> tes...
625941c75fc7496912cc39c3
def plusOne(self, digits): <NEW_LINE> <INDENT> for i in range(len(digits) - 1, -1, -1): <NEW_LINE> <INDENT> digits[i] += 1 <NEW_LINE> if digits[i] >= 10: <NEW_LINE> <INDENT> digits[i] = 0 <NEW_LINE> <DEDENT> else: <NEW_LINE> <INDENT> return digits <NEW_LINE> <DEDENT> <DEDENT> digits.insert(0, 1) <NEW_LINE> return digit...
:type digits: List[int] :rtype: List[int]
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def same(self): <NEW_LINE> <INDENT> return self.current_dict == self.past_dict
True if the two dicts are the same.
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def highlight_span(start=None, end=None, color='g', alpha=0.5, grapher=None): <NEW_LINE> <INDENT> if start is None and end is None: <NEW_LINE> <INDENT> raise Exception("strat and end cannot both be None") <NEW_LINE> <DEDENT> if grapher is None: <NEW_LINE> <INDENT> fig = charting.gcf() <NEW_LINE> grapher = fig.grapher <...
A quick shortcut way to highlight regions of a chart. Uses the Grapher.df.index to translate non int-position arguments to int locations.
625941c726068e7796caed23
def test_sensor_source(self): <NEW_LINE> <INDENT> assert setup_component( self.hass, "sensor", { "sensor": { "platform": "statistics", "name": "test", "entity_id": "sensor.test_monitored", } }, ) <NEW_LINE> self.hass.block_till_done() <NEW_LINE> self.hass.start() <NEW_LINE> self.hass.block_till_done() <NEW_LINE> for va...
Test if source is a sensor.
625941c73317a56b86939ca0
def get_calendar_service(): <NEW_LINE> <INDENT> creds = None <NEW_LINE> if os.path.exists('token.pickle'): <NEW_LINE> <INDENT> with open('token.pickle', 'rb') as token: <NEW_LINE> <INDENT> creds = pickle.load(token) <NEW_LINE> <DEDENT> <DEDENT> if not creds or not creds.valid: <NEW_LINE> <INDENT> if creds and creds.exp...
Authenticates user with google, thene exports calendar service
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def test_multpack4(self): <NEW_LINE> <INDENT> csv_file_as_str = ",123456,,123456,,123456\n" <NEW_LINE> pack_size = 8 <NEW_LINE> self.assertEqual(field_width.calculate_field_widths(csv_file_as_str, pack_size), [0, 6, 0, 6, 0, 6])
Test with multi-pack aligned on pack boundaries.
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def backupHotpatch(): <NEW_LINE> <INDENT> if os.path.samefile(g_gausshome, g_opts.newClusterAppPath): <NEW_LINE> <INDENT> g_logger.debug("Has switched to new version, no need to backup again.") <NEW_LINE> return <NEW_LINE> <DEDENT> for dbInstance in g_dbNode.cmservers: <NEW_LINE> <INDENT> backupInstanceHotpatchConfig(d...
function: if the upgrade process failed in check cluster status, user can reenter upgrade process
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def solve_manual(totals, ks_constants, params, log_kt_constants, ptargets=None): <NEW_LINE> <INDENT> if ptargets is None: <NEW_LINE> <INDENT> ptargets = stoichiometric.create_ptargets(totals, ks_constants) <NEW_LINE> <DEDENT> optresult_thermodynamic = thermodynamic.solve( totals, ks_constants, params, log_kt_constants,...
Solve for thermodynamic equilibrium to return solute molalities and stoichiometric equilibrium constants, having manually evaluated the relevant constants.
625941c76e29344779a62658
@_send <NEW_LINE> def update_farmware(package): <NEW_LINE> <INDENT> kind = 'update_farmware' <NEW_LINE> return _assemble(kind, {'package': package})
Send command: update_farmware. Args: package (str): Name of the Farmware to update.
625941c76aa9bd52df036de9
def __init__(self): <NEW_LINE> <INDENT> self.message = 'Invalid Task Parameters.' <NEW_LINE> self.code = 't-1' <NEW_LINE> self.status_code = 400
Initial values.
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def train_distributed(self, num_gpus) -> None: <NEW_LINE> <INDENT> logger.warning("train_distributed() not implemented in the base Trainer.")
Executes the training of the model in a distributed fashion. :param num_gpus: The number of gpus to use for training. :return: None
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def _get_mediatypes_from_qsa(self): <NEW_LINE> <INDENT> qsa_mediatypes = self.request.query_params.get('_format', self.request.query_params.get('_mediatype', None)) <NEW_LINE> if qsa_mediatypes is not None: <NEW_LINE> <INDENT> qsa_mediatypes = str(qsa_mediatypes).replace(' ', '+').split(',') <NEW_LINE> if qsa_mediatype...
Returns a list of Media Types from QSA :return: list
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def default_classification_model(num_classes, num_anchors, pyramid_feature_size=256, prior_probability=0.01, classification_feature_size=256, name='classification_submodel'): <NEW_LINE> <INDENT> options = { 'kernel_size': 3, 'strides': 1, 'padding': 'same', } <NEW_LINE> inputs = keras.layers.Input(shape=(None, None, py...
Creates the default classification submodel. Args num_classes: Number of classes to predict a score for at each feature level. num_anchors: Number of anchors to predict classification scores for at each feature level. pyramid_feature_size: The number of filters to expect from the fe...
625941c77d43ff24873a2ce6
def isPalindrome(self, s): <NEW_LINE> <INDENT> list1 = [] <NEW_LINE> for a in s: <NEW_LINE> <INDENT> if (a.isalnum()) == True: <NEW_LINE> <INDENT> list1.append(a.lower()) <NEW_LINE> <DEDENT> <DEDENT> list2 = list(reversed(list1)) <NEW_LINE> if list1 == list2: <NEW_LINE> <INDENT> return True <NEW_LINE> <DEDENT> else: <N...
:type s: str :rtype: bool
625941c7fbf16365ca6f6208
def saveVariantsLayer(self, origin, fileName=None): <NEW_LINE> <INDENT> fileName = self.getFileDialog( fileName, options=False, fileType="USD (*.usd *.usda)") <NEW_LINE> if not fileName: <NEW_LINE> <INDENT> return <NEW_LINE> <DEDENT> return pm.walterStandin(saveVariantsLayer=(origin, fileName))
Save the shader assignment to external file.
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def from_object(self, obj): <NEW_LINE> <INDENT> for key in dir(obj): <NEW_LINE> <INDENT> if key.isupper(): <NEW_LINE> <INDENT> val = getattr(obj, key) <NEW_LINE> setattr(self, key, val) <NEW_LINE> <DEDENT> <DEDENT> return self
Copy uppercase attributes from another object to this one
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def Run(self, args): <NEW_LINE> <INDENT> holder = base_classes.ComputeApiHolder(self.ReleaseTrack()) <NEW_LINE> client = holder.client <NEW_LINE> peer_network_ref = resources.REGISTRY.Parse( args.peer_network, params={ 'project': args.peer_project or properties.VALUES.core.project.GetOrFail }, collection='compute.netwo...
Issues the request necessary for adding the peering.
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def Clean_0_Jet(Train, Val, Test): <NEW_LINE> <INDENT> sets = [Train, Val, Test] <NEW_LINE> for df in sets: <NEW_LINE> <INDENT> df.drop('PRI_jet_leading_pt', axis=1, inplace=True) <NEW_LINE> df.drop('PRI_jet_leading_eta', axis=1, inplace=True) <NEW_LINE> df.drop('PRI_jet_leading_phi', axis=1, inplace=True) <NEW_LINE> d...
Removes variable columns that are meaningless for events with 0 jets. Parameters ---------- Train : pandas.dataframe dataset with also meaningless variables. Val : pandas.dataframe dataset with also meaningless variables. Test : pandas.dataframe dataset with also meaningless variables. Returns ------- Tra...
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def test_past_questions(self): <NEW_LINE> <INDENT> past_question = create_question(question_text='Past Question.', days=-5) <NEW_LINE> url = reverse('polls:detail', args=(past_question.id,)) <NEW_LINE> response = self.client.get(url) <NEW_LINE> self.assertContains(response, past_question.question_text)
The detail view of a question with a pub_date in the past displays the question's text.
625941c78da39b475bd64fb8
def get_cltk_text_dir(lang, corpus='perseus'): <NEW_LINE> <INDENT> cltk_home = os.path.expanduser('~/cltk_data') <NEW_LINE> text_dir = os.path.join(cltk_home, lang.casefold(), 'text', lang.casefold() + '_text_' + corpus, 'json') <NEW_LINE> return text_dir
Take relative filepath, return absolute
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def _generate_outside_terrain(self, empty_outside_terrain_grid, number_of_generations): <NEW_LINE> <INDENT> grid = empty_outside_terrain_grid <NEW_LINE> number_of_generations = number_of_generations <NEW_LINE> for x in range(number_of_generations): <NEW_LINE> <INDENT> next_grid = [] <NEW_LINE> for column_index, column ...
creates a bubble effect with cellular automaton
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def make_encoder(activation, latent_size, base_depth): <NEW_LINE> <INDENT> conv = functools.partial( tf.keras.layers.Conv2D, padding="SAME", activation=activation) <NEW_LINE> encoder_net = tf.keras.Sequential([ conv(base_depth, 5, 1), conv(base_depth, 5, 2), conv(2 * base_depth, 5, 1), conv(2 * base_depth, 5, 2), conv(...
Creates the encoder function. Args: activation: Activation function in hidden layers. latent_size: The dimensionality of the encoding. base_depth: The lowest depth for a layer. Returns: encoder: A `callable` mapping a `Tensor` of images to a `tf.distributions.Distribution` instance over encodings.
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def getyieldy(self, key): <NEW_LINE> <INDENT> if key in self.propmap: <NEW_LINE> <INDENT> funcval = self.propmap[key] <NEW_LINE> if isinstance(funcval, ScriptCallable): <NEW_LINE> <INDENT> if not funcval.yieldy: <NEW_LINE> <INDENT> return (funcval.func(), False) <NEW_LINE> <DEDENT> else: <NEW_LINE> <INDENT> return (fun...
Get an entry which may be an asychronous operation. (This is terrible, but better than handling every single nmsp.attr as a coroutine call? I think?) Anyhow, you call this with the idiom: (res, yieldy) = nmsp.getyieldy(key) if yieldy: res = yield res()
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def write(self, data): <NEW_LINE> <INDENT> self._processor.process(data)
Write directly to the C{MessageProcessor}.
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def create_alien(ai_settings,screen,aliens,alien_number,row_number): <NEW_LINE> <INDENT> alien = Alien(ai_settings, screen) <NEW_LINE> alien_width=alien.rect.width <NEW_LINE> alien.x=alien_width+2*alien_width*alien_number <NEW_LINE> alien.rect.x=alien.x <NEW_LINE> alien.rect.y=alien.rect.height+2*alien.rect.height*row_...
创建一个外星人并将其放入当前行
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def getLastUV( self ): <NEW_LINE> <INDENT> result = self.sendMessage( 'D3' ) <NEW_LINE> return result.split(',')
Fetches (from the device) the last CIE 1976 u,v coords :returns: list: status, units, Photometric brightness, u, v :see also: :func:`~PR655.measure` automatically populates pr655.lastUV with [u,v]
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def test_bytes(self): <NEW_LINE> <INDENT> self.check_hosts((['host'], [], [], [], [], [], []), ([0], [], [], [], [], [], []), from_bytes=True)
Test match against byte string
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def get_seed(self, rating, me=None): <NEW_LINE> <INDENT> seed = self.seed[rating] <NEW_LINE> if me: <NEW_LINE> <INDENT> seed -= self.elo_win_prob[rating - me.rating] <NEW_LINE> <DEDENT> return seed
Get seed given a rating and user.
625941c73617ad0b5ed67f3e
def __add__(self, other): <NEW_LINE> <INDENT> v = self.data + other.data <NEW_LINE> return MyNumber(v)
此方法来用制定self + other的规则
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def set_weights(self, new_weights): <NEW_LINE> <INDENT> self._check_sess() <NEW_LINE> self.sess.run(self.assignment_nodes, feed_dict={self.placeholders[name]: value for (name, value) in new_weights.items() if name in self.placeholders})
Sets the weights to new_weights.
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def phi(dvw, width): <NEW_LINE> <INDENT> z = dvw/width <NEW_LINE> val = np.exp(-1.0*(z*z)/2.0) <NEW_LINE> return val
Given the sigma in velocity units, this routine computes the relative Gaussian value of the instrumental profile Called by routine instrument iteratively
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def install(cwd=None): <NEW_LINE> <INDENT> directory = cwd <NEW_LINE> chromedriver_filepath = download_chromedriver(directory) <NEW_LINE> if not chromedriver_filepath: <NEW_LINE> <INDENT> logging.debug('Can not download chromedriver.') <NEW_LINE> return <NEW_LINE> <DEDENT> chromedriver_dir = os.path.dirname(chromedrive...
Appends the directory of the chromedriver binary file to PATH. :param cwd: Flag indicating whether to download to current working directory :return: The file path of chromedriver
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@logic.validate(logic.schema.default_activity_list_schema) <NEW_LINE> def organization_activity_list(context, data_dict): <NEW_LINE> <INDENT> data_dict['include_data'] = False <NEW_LINE> include_hidden_activity = data_dict.get('include_hidden_activity', False) <NEW_LINE> _check_access('organization_activity_list', cont...
Return a organization's activity stream. :param id: the id or name of the organization :type id: string :param offset: where to start getting activity items from (optional, default: ``0``) :type offset: int :param limit: the maximum number of activities to return (optional, default: ``31`` unless set in site's...
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def get(self, a, b, limit): <NEW_LINE> <INDENT> try: <NEW_LINE> <INDENT> return self._get((a, b, limit)) <NEW_LINE> <DEDENT> except KeyError: <NEW_LINE> <INDENT> pass <NEW_LINE> <DEDENT> return self._get((b, a, limit))
Return cost or raise KeyError
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def print_server_info(ip, user, password): <NEW_LINE> <INDENT> try: <NEW_LINE> <INDENT> r = requests.get(f'https://{ip}:8443/api/v2/server', auth=(user, password), verify=False) <NEW_LINE> if r.status_code != 200: <NEW_LINE> <INDENT> raise Exception(f"Invalid response from plesk api. Response code: {r.status_code}") <N...
Fetch and print servers info @params: ip - Required : the ip of the server (Str) user - Required : the administrator username (Str) password - Required : The administrator password (Str)
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def create_column(conn, schema, table, column_name, data_type): <NEW_LINE> <INDENT> full_table_name = create_full_table_name(schema, table) <NEW_LINE> query = "ALTER TABLE {0} ADD COLUMN \"{1}\" {2};".format( full_table_name, column_name, data_type) <NEW_LINE> with closing(conn.cursor()) as cursor: <NEW_LINE> <INDENT> ...
Create a new column with matching datatype for the specified trend.
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def test_xor(self): <NEW_LINE> <INDENT> def ggen(n): <NEW_LINE> <INDENT> i=0 <NEW_LINE> while i<n: <NEW_LINE> <INDENT> r1=random.normalvariate(0,0.01) <NEW_LINE> r2=random.normalvariate(0,0.01) <NEW_LINE> if i%4==0: <NEW_LINE> <INDENT> yield np.array([0,1]),[r1,r2] <NEW_LINE> <DEDENT> elif i%4==1: <NEW_LINE> <INDENT> y...
A test to verify training for XOR
625941c7009cb60464c633f9
def counter_subtract_demo(self, now_iterable='abcdab', other_iterable='chci'): <NEW_LINE> <INDENT> now_counter_result = collections.Counter(now_iterable) <NEW_LINE> print(now_counter_result) <NEW_LINE> other_counter_result = collections.Counter(other_iterable) <NEW_LINE> print(other_counter_result) <NEW_LINE> now_count...
求 now_iterable 与 other_iterable的差
625941c74e4d5625662d4420
def get_course_lang(course_url): <NEW_LINE> <INDENT> return constant.CRSLANG_EN if "cycle" in course_url else constant.CRSLANG_IT
Getter function to get a course's language without directly analyzing the URL
625941c7bf627c535bc13215
def _ChangedIndexRows(composite_indexes, old_entity, new_entity): <NEW_LINE> <INDENT> unique_old_properties = collections.defaultdict(set) <NEW_LINE> unique_new_properties = collections.defaultdict(set) <NEW_LINE> if old_entity is not None: <NEW_LINE> <INDENT> for old_prop in old_entity.property_list(): <NEW_LINE> <IND...
Determine the number of index rows that need to change. We assume that old_entity represents the current state of the Datastore. Args: composite_indexes: The composite_indexes for the kind of the entities. old_entity: Entity representing the current state in the Datastore. new_entity: Entity representing the de...
625941c771ff763f4b5496d0
def _sim_one_sig(self, sig_param): <NEW_LINE> <INDENT> f0 = self._system_parameters['f0'] <NEW_LINE> incF = self._system_parameters['delta_f'] <NEW_LINE> Tm = self._system_parameters['Tm'] <NEW_LINE> fs = self._system_parameters['fs'] <NEW_LINE> N = self._system_parameters['length'] <NEW_LINE> delay = si...
Simulate one harmonic beat signal. Parameters ------------- * sig_param: dict dictionary of signal parameters, whcih include (a,delay,delta_delat,phi0,callback). Returns ------------ * sig: 1d ndarray (complex), simulated signal. Notes --------- * Parameters f0, Delta_f, fs and N are system paramet...
625941c7f7d966606f6aa04a
def testGetWithInvalidOperation(self): <NEW_LINE> <INDENT> user = createUser(u'name', u'password', u'Name', u'name@example.com') <NEW_LINE> namespace = createNamespace(user, u'name') <NEW_LINE> permission = createNamespacePermission(namespace) <NEW_LINE> self.assertRaises(RuntimeError, permission.get, Operation.WRITE_T...
L{NamespacePermission.get} raises a C{RuntimeError} if an invalid L{Operation} is provided.
625941c7adb09d7d5db6c7d7
def __init__(self, first_name, last_name, username, email, location): <NEW_LINE> <INDENT> super().__init__(first_name, last_name, username, email, location) <NEW_LINE> self.privileges = []
Initializes Admin
625941c75fdd1c0f98dc0279
def get_auxSignal(self): <NEW_LINE> <INDENT> if self._cacheExpiration <= YAPI.GetTickCount(): <NEW_LINE> <INDENT> if self.load(YAPI._yapiContext.GetCacheValidity()) != YAPI.SUCCESS: <NEW_LINE> <INDENT> return YStepperMotor.AUXSIGNAL_INVALID <NEW_LINE> <DEDENT> <DEDENT> res = self._auxSignal <NEW_LINE> return res
Returns the current value of the signal generated on the auxiliary output. @return an integer corresponding to the current value of the signal generated on the auxiliary output On failure, throws an exception or returns YStepperMotor.AUXSIGNAL_INVALID.
625941c77b25080760e394a0
def test_small_pos(self): <NEW_LINE> <INDENT> d = 1 <NEW_LINE> arr = [1,3,5,7] <NEW_LINE> result = hackerrank_DS_4.rotateLeft(d, arr) <NEW_LINE> self.assertEqual(result, [3, 5, 7, 1])
test to rotate a small array by only 1 position :return: 3,5,7,1
625941c7ab23a570cc2501c8
def _uninstall(self): <NEW_LINE> <INDENT> return None
This method is called by *uninstall()* and should remove all data or configuration generated by the plugin. **Subclass:** * You may completly override this method.
625941c730bbd722463cbe0c
def create_child_with_parents(node, address, privkeys, parents_tx, values, locking_scripts, fee=DEFAULT_FEE): <NEW_LINE> <INDENT> num_parents = len(parents_tx) <NEW_LINE> total_value = sum(values) <NEW_LINE> inputs = [{"txid": tx.rehash(), "vout": 0} for tx in parents_tx] <NEW_LINE> outputs = {address : total_value - f...
Creates a transaction that spends the first output of each parent in parents_tx.
625941c730bbd722463cbe0b
def query_from_elem(elem): <NEW_LINE> <INDENT> if elem is None: <NEW_LINE> <INDENT> return None <NEW_LINE> <DEDENT> output = [] <NEW_LINE> for subelem in elem: <NEW_LINE> <INDENT> if subelem.tag == "constant": <NEW_LINE> <INDENT> name = subelem.attrib['name'] <NEW_LINE> value = subelem.text.strip() <NEW_LINE> try: <NEW...
Creates a Query object from the specified xml element
625941c7507cdc57c6306d1f
def draw_emoji(self, frame, emoji_bbs): <NEW_LINE> <INDENT> if emoji_bbs is None or len(emoji_bbs) == 0: <NEW_LINE> <INDENT> return frame <NEW_LINE> <DEDENT> frameDC = copy.deepcopy(frame) <NEW_LINE> frame_h, frame_w = frameDC.shape[:2] <NEW_LINE> for emoji_name, bb in emoji_bbs: <NEW_LINE> <INDENT> l,t,r,b = bb <NEW_L...
Draw emoji is non-trivial omg. Params ------- emoji_bbs : list of tuples Each tuple consist of (emoji_name, bb) pairs Returns ------- Drawn frame ndarray
625941c7046cf37aa974cd8f
def get_url(endpoint): <NEW_LINE> <INDENT> if not isinstance(endpoint, str): <NEW_LINE> <INDENT> raise Exception('endpoint has to be a string') <NEW_LINE> <DEDENT> return base_url + endpoint
This utility function will return a url to be used in a request :param endpoint: :return:
625941c79f2886367277a8d5
def cast(*args): <NEW_LINE> <INDENT> return _itkFlipImageFilterPython.itkFlipImageFilterIUL2_cast(*args)
cast(itkLightObject obj) -> itkFlipImageFilterIUL2
625941c750485f2cf553cde0
def retry_erroneous(self, name, properties_update=None): <NEW_LINE> <INDENT> with self.__instances_lock: <NEW_LINE> <INDENT> try: <NEW_LINE> <INDENT> stored_instance = self.__instances[name] <NEW_LINE> <DEDENT> except KeyError: <NEW_LINE> <INDENT> raise ValueError( "Unknown component instance '{0}'".format(name)) <NEW_...
Removes the ERRONEOUS state of the given component, and retries a validation :param name: Name of the component to retry :param properties_update: A dictionary to update component properties :return: The new state of the component :raise ValueError: Invalid component name
625941c7a79ad161976cc18c
def check_pages(language): <NEW_LINE> <INDENT> yaml_pat = re.compile(r'\A---\n.+\n---\n.+', flags=re.DOTALL + re.MULTILINE) <NEW_LINE> links_pat = re.compile(r'{%\s+include\s+links.md\s+%}\s*\Z', flags=re.DOTALL + re.MULTILINE) <NEW_LINE> content = get_all_docs(language) <NEW_LINE> result = set() <NEW_LINE> for (slug, ...
Check that Markdown pages are properly structured.
625941c7462c4b4f79d1d717
def __init__(self, _conf_): <NEW_LINE> <INDENT> self.conf_ = _conf_ <NEW_LINE> self.PATH_LOG = set_.APPS[self.conf_]['PATH_LOG'] <NEW_LINE> self.log = set_.log_init('covid-l_pro.log', self.conf_) <NEW_LINE> self.PATH_DATA = set_.DATA[self.conf_]['PATH'] <NEW_LINE> self.DB_ = set_.MYSQL[self.conf_]['DB'] <NEW_LINE> pass
Is base of the root.
625941c75fdd1c0f98dc027a
def getData(self, label): <NEW_LINE> <INDENT> data = self._ensemble.getData(label) <NEW_LINE> if data is not None: <NEW_LINE> <INDENT> data = data[self._index] <NEW_LINE> <DEDENT> return data
Returns a copy of the data array associated with *label*, or **None** if such data is not present.
625941c7b7558d58953c4f5d
def depthFirstSearch(problem): <NEW_LINE> <INDENT> currState = problem.getStartState() <NEW_LINE> visited = set() <NEW_LINE> visited.add(currState) <NEW_LINE> currPath = [] <NEW_LINE> result = dfsHelper(problem, visited, currPath, currState) <NEW_LINE> return result
Search the deepest nodes in the search tree first. Your search algorithm needs to return a list of actions that reaches the goal. Make sure to implement a graph search algorithm. To get started, you might want to try some of these simple commands to understand the search problem that is being passed in: print "Start...
625941c7d486a94d0b98e18c
def check(self, request, mtype=None): <NEW_LINE> <INDENT> if not request: <NEW_LINE> <INDENT> raise LogDBError("Request name is empty") <NEW_LINE> <DEDENT> if mtype and mtype not in LOGDB_MSG_TYPES: <NEW_LINE> <INDENT> raise LogDBError("Unsupported message type: '%s', supported types %s" % (mtype, ...
Check that given request name is valid
625941c707f4c71912b114c8
def build_sampling_funcs(self): <NEW_LINE> <INDENT> x_sym = tensor.matrix('x_sym') <NEW_LINE> y_sym = tensor.matrix('y_sym') <NEW_LINE> cs, nll, kl_q2ps, kl_p2qs = self.run_model_simul(x_sym, y_sym) <NEW_LINE> cs_as_ys = tensor.nnet.sigmoid(tanh_clip(cs, clip_val=15.0)) <NEW_LINE> nll_term = nll.mean() <NEW_LINE> kl_te...
Build functions for visualizing the behavior of this model.
625941c7c4546d3d9de72a7a
def TrainDNN(self,train_DF,test_DF,multi=False,nclass = 4,epochs=200,batch_size=1024,useDropOut = False,class_weights=None,loss=None): <NEW_LINE> <INDENT> NDIM = len(self.var_list) <NEW_LINE> DNN = Sequential() <NEW_LINE> DNN.add(Dense(64, input_dim=NDIM, kernel_initializer='uniform', activation='relu')) <NEW_LINE> if ...
With training and testing DataFrame, and a list of variables with which to train and evaluate, produce the score series for both the training and testing sets
625941c799cbb53fe6792c2d
def get_user(self, request): <NEW_LINE> <INDENT> if hasattr(request, settings.MARKETPLACE_DOMAIN_NAME_KEY): <NEW_LINE> <INDENT> domain = getattr(request, settings.MARKETPLACE_DOMAIN_NAME_KEY) <NEW_LINE> user = get_gaema_user(domain) <NEW_LINE> if user: <NEW_LINE> <INDENT> user['_service'] = domain <NEW_LINE> key_name =...
check for gaema authenticated user and return the user
625941c776e4537e8c3516b8
def layer(self, layer_id): <NEW_LINE> <INDENT> buf = cStringIO.StringIO() <NEW_LINE> f = gzip.GzipFile(mode='wb', compresslevel=self._compresslevel, fileobj=buf) <NEW_LINE> try: <NEW_LINE> <INDENT> f.write(self._content(layer_id + '/layer.tar', memoize=False)) <NEW_LINE> <DEDENT> finally: <NEW_LINE> <INDENT> f.close() ...
Override.
625941c723e79379d52ee5ac
def calc_template_ranges(network): <NEW_LINE> <INDENT> network.update_network() <NEW_LINE> nbase = network.network.network <NEW_LINE> name_fragment = calc_name_fragment(network) <NEW_LINE> if network.ip_type == '4': <NEW_LINE> <INDENT> if network.prefixlen <= 24 and network.prefixlen >= 20: <NEW_LINE> <INDENT> template...
Given a network, return the range information for that network. These ranges will be used by the user to decide where to request an IP address. This function will not actually find that ip address, it will mearly suggest which ranges a user might want to check in. This function should contain allocation policy that ne...
625941c75166f23b2e1a51a0
def d_input(self): <NEW_LINE> <INDENT> input_ = self.get_cache('input') <NEW_LINE> output = self.get_cache('output') <NEW_LINE> error = self.error() <NEW_LINE> result = np.zeros((error.shape[:1] + self.input_shape)) <NEW_LINE> stride_x, stride_y = self.stride <NEW_LINE> for i in range(self.input_shape[0]): <NEW_LINE> <...
Compute the gradient with respect to the inputs (which are also the activations of the preceding layer).
625941c7e8904600ed9f1f73
def apply( self, func: Callable[..., Styler], axis: Axis | None = 0, subset: Subset | None = None, **kwargs, ) -> Styler: <NEW_LINE> <INDENT> self._todo.append( (lambda instance: getattr(instance, "_apply"), (func, axis, subset), kwargs) ) <NEW_LINE> return self
Apply a CSS-styling function column-wise, row-wise, or table-wise. Updates the HTML representation with the result. Parameters ---------- func : function ``func`` should take a Series if ``axis`` in [0,1] and return an object of same length, also with identical index if the object is a Series. ``func`` sh...
625941c7e8904600ed9f1f72
def test_create(self): <NEW_LINE> <INDENT> pass
Test case for create Create a new Participant for the given Study.
625941c785dfad0860c3aea1
def __init__(self, FLAGS, split): <NEW_LINE> <INDENT> self.n_points = FLAGS.n_points <NEW_LINE> self.len = FLAGS.epoch_length <NEW_LINE> self.split = split <NEW_LINE> assert self.split in ["log", "train"]
Create a dataset of graphs. Each graph represents a set of points in 3D space, where each pair of points interacts according to a randomly parameterised potential. The parameter(s) of this potential are stored in the graph as edge information. Node data has shape (num_points, num_channels, data_dimensionality) Edge da...
625941c7851cf427c661a557
def __get_product_seller(self, doc): <NEW_LINE> <INDENT> product_seller = doc.xpath(self.xpath.item_seller) <NEW_LINE> if product_seller: <NEW_LINE> <INDENT> product_seller = product_seller[0] <NEW_LINE> <DEDENT> return product_seller
Uses the lxml doc to fetch product seller
625941c7377c676e912721f0
def test_mkdir_url_with_revprops(self): <NEW_LINE> <INDENT> directory = urljoin(self.repos_uri+b"/", b"some/deep/subdir") <NEW_LINE> commit_info = client.mkdir3((directory,), 1, {b'customprop':b'value'}, self.client_ctx) <NEW_LINE> self.assertEqual(commit_info.revision, 13) <NEW_LINE> self.assertEqual(self.log_message_...
Test svn_client_mkdir3 on a file:// URL, with added revprops
625941c776e4537e8c3516b9
def test_check_inputs_1(): <NEW_LINE> <INDENT> Z = X.astype('float') <NEW_LINE> Z[0, 0] = np.inf <NEW_LINE> H, _ = np.testing.assert_warns(InputDataWarning, check_inputs, Z, y, 1) <NEW_LINE> assert id(H) == id(Z) <NEW_LINE> np.testing.assert_array_equal(Z, H)
[Utils] check_inputs: warnings level = 1.
625941c750812a4eaa59c36a
def is_remote(path): <NEW_LINE> <INDENT> return issubclass(path.__class__, RemotePath)
Return whether the given protocol path belongs to a remote protocol or not. :param path: protocol path to process. :type path: ProtocolPath :returns: whether the protocol is local (True in this case). :rtype: bool
625941c71d351010ab855b63
def _valid_epoch(self): <NEW_LINE> <INDENT> self.model.eval() <NEW_LINE> total_val_loss = 0 <NEW_LINE> total_val_metrics = np.zeros(len(self.metrics)) <NEW_LINE> with torch.no_grad(): <NEW_LINE> <INDENT> for batch_idx, gt in enumerate(self.data_loader): <NEW_LINE> <INDENT> img, score_map, geo_map, training_mask, transc...
Validate after training an epoch :return: A log that contains information about validation Note: The validation metrics in log must have the key 'val_metrics'.
625941c7d4950a0f3b08c397
def test_user_can_only_list_where_he_has_journal_membership(self): <NEW_LINE> <INDENT> self.client.login(username=self.user.username, password='top_secret') <NEW_LINE> response = self.client.get( reverse('userspace:journal:editor:issues', args=(self.journal.pk, )), user=self.user) <NEW_LINE> journal_ids = [j.id for j i...
Test list of issue submissions Make sure the list contains only issue submission link to a journal with his membership
625941c7e76e3b2f99f3a854
def test_hostgroups_patch_description_204_ok(self): <NEW_LINE> <INDENT> self.assert_patch(f'/hostgroups/{self.hostgroup_one.name}', {'description': 'new d€scription'}) <NEW_LINE> data = self.assert_get('/hostgroups/%s' % self.hostgroup_one.name).json() <NEW_LINE> self.assertEqual(data['description'], 'new d€scription')
Rename a group should return 204 ok
625941c701c39578d7e74e82
def bin_data_log10(datax,datay,numbins,botedge=-99,topedge=-99): <NEW_LINE> <INDENT> tempx = np.log10(datax) <NEW_LINE> if botedge == -99: <NEW_LINE> <INDENT> botedge = np.min(tempx) <NEW_LINE> <DEDENT> else: <NEW_LINE> <INDENT> botedge = np.log10(botedge) <NEW_LINE> <DEDENT> if topedge == -99: <NEW_LINE> <INDENT> tope...
Place data in bins spaced regularly in log10 space. Calculates binned averages and standard deviations for both the abscissa and ordinate data. Returns arrays containing binned averages and standard deviations of both x and y data as well as the number of samples in each bin: binmeanx, binstdx, binmeany, binstdy, ...
625941c707d97122c41788d0
def rebuild(self, id, image, wait=False, poll=5, timeout=300): <NEW_LINE> <INDENT> uri = "%s/%s/actions" % (self.uri, id) <NEW_LINE> try: <NEW_LINE> <INDENT> image = int(image) <NEW_LINE> <DEDENT> except ValueError: <NEW_LINE> <INDENT> pass <NEW_LINE> <DEDENT> attribs = {"type": "rebuild", "image": image} <NEW_LINE> re...
description: Rebuild a Droplet A rebuild action functions just like a new create. in: - id - number - The id of the Droplet - image - string if an image slug. number if an image ID. - An image slug or ID. This represents the image that the Droplet will use as a base. - wait - boolean - Whether to wait...
625941c767a9b606de4a7f02
def _updater_wrapper(updater): <NEW_LINE> <INDENT> def updater_handle(key, lhs_handle, rhs_handle): <NEW_LINE> <INDENT> lhs = NDArray(NDArrayHandle(lhs_handle)) <NEW_LINE> rhs = NDArray(NDArrayHandle(rhs_handle)) <NEW_LINE> updater(key, lhs, rhs) <NEW_LINE> <DEDENT> return updater_handle
a wrapper for the user-defined handle
625941c71f037a2d8b946245
def getDataAge(self, filesByLumi): <NEW_LINE> <INDENT> maxInsertTime = 0 <NEW_LINE> for filesInfos in list(filesByLumi.values()): <NEW_LINE> <INDENT> for fileInfo in filesInfos: <NEW_LINE> <INDENT> if fileInfo['insert_time'] > maxInsertTime: <NEW_LINE> <INDENT> maxInsertTime = fileInfo['insert_time'] <NEW_LINE> <DEDENT...
_getDataAge_ Return age of youngest streamer in filesByLumi
625941c79c8ee82313fbb7bc
def calc_n_coarse_chan(self): <NEW_LINE> <INDENT> coarse_chan_bw = 2.9296875 <NEW_LINE> bandwidth = abs(self.header[b'nchans']*self.header[b'foff']) <NEW_LINE> n_coarse_chan = bandwidth / coarse_chan_bw <NEW_LINE> return n_coarse_chan
This makes an attempt to calculate the number of coarse channels in a given file. It assumes for now that a single coarse channel is 2.9296875 MHz
625941c7be7bc26dc91cd649