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def AllenAtlas(res_um=25, par=None): """ Instantiates an atlas.BrainAtlas corresponding to the Allen CCF at the given resolution using the IBL Bregma and coordinate system :param res_um: 25 or 50 um :return: atlas.BrainAtlas """ if par is None: # Bregma indices for the 10um Allen Bra...
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def mplot3d(f, var1, var2, show=True): """ Plot a 3d function using matplotlib/Tk. """ import warnings warnings.filterwarnings("ignore", "Could not match \S") p = import_module('pylab') # Try newer version first p3 = import_module('mpl_toolkits.mplot3d', __import__kwargs={'from...
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def nsd_delete1(ctx, name, force): """deletes a NSD/NSpkg NAME: name or ID of the NSD/NSpkg to be deleted """ nsd_delete(ctx, name, force)
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def get_devices_properties(device_expr,properties,hosts=[],port=10000): """ Usage: get_devices_properties('*alarms*',props, hosts=[get_bl_host(i) for i in bls]) props must be an string as passed to Database.get_device_property(); regexp are not enabled! get_matching_device_prop...
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def benchmark_classifier(cls, y_test, labels, scoring): """ Use 10-fold cross validation to benchmark the performance of the provided classifier. Parameters ---------- cls : estimator object implementing `fit` y_test : array labels : list (of strings) List containing the labels tha...
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def atexit_shutdown_grace_period(grace_period=-1.0): """Return and optionally set the default worker cache shutdown grace period. This only affects the `atexit` behavior of the default context corresponding to :func:`trio_parallel.run_sync`. Existing and future `WorkerContext` instances are unaffected....
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def combine_files(root, pattern=None): """Combine all files in root path directory Parameters: root (str) : file path to directory of files pattern (str) : optional file pattern to search for in directory Returns: combined files """ if pattern is not None: files = [...
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def get_point(points, cmp, axis): """ Get a point based on values of either x or y axys. :cmp: Integer less than or greater than 0, representing respectively < and > singhs. :returns: the index of the point matching the constraints """ index = 0 for i in range(len(points)): if cmp <...
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def benchmark_parser_header_16(nb_headers, nb_fields, do_checksum=False): """ This method generate the P4 program to benchmark the P4 parser :param nb_headers: the number of generic headers included in the program :type nb_headers: int :param nb_fields: the number of fields (16 bits) in each header...
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def check_result(reference, result_list, enable_assertion): """Checks result, warns when latency is abnormal. Args: reference: { environment : reference_time}, environment is a string tuple while reference_time is a float number. result_list: a list of tuple. enable_assertion: bool, throw asserti...
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def create_jobs_list(chunks, outdir, *filters): # TO DO # Figure out the packing/unpacking """ Create a list of dictionaries that hold information for the given chunks Arguments: chunks: list: A list of lists. Each nested list contains the filepaths to be processed outdir: Pat...
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def per_symbol_to_per_seq_probs(per_symbol_probs, tgt_out_idx): """ Gather per-symbol probabilities into per-seq probabilities """ # per_symbol_probs shape: batch_size, seq_len, candidate_size # tgt_out_idx shape: batch_size, seq_len # output shape: batch_size, 1 return torch.prod( torch.gat...
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def append_open_buildinfo(buildinfo_path, files=open_buildinfo_files): """Append BUILD-INFO.txt with open section for open_buildinfo_files""" if os.path.exists(os.path.join(buildinfo_path, BUILDINFO)): try: bifile = open(os.path.join(buildinfo_path, BUILDINFO), "a") try: ...
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def solve_game(payoffs): """ given payoff matrix for a zero-sum normal-form game, return first mixed equilibrium (may be multiple) returns a tuple of numpy arrays """ # .vertex_enumeration() # .lemke_howson(initial_dropped_label=0) - does not return *all* equilibrium game = nash.Game(payoffs) ...
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def emit_settings_changed_event(user, db_table, changed_fields: Dict[str, Tuple[Any, Any]]): """Emits an event for a change in a setting. Args: user (User): the user that this setting is associated with. db_table (str): the name of the table that we're modifying. changed_fields: all cha...
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def zone_features(df, zfeatures, aufeatures): """Create zone features from the data Args: df (DataFrame): Input dataframe zfeatures (list): List of zone median features aufeatures (list): List of zone autocorr features Return: 2 dataframes """ # Medians from the last 1,...
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def get_active_validator_indices(validators: [ValidatorRecord]) -> List[int]: """ Gets indices of active validators from ``validators``. """ return [i for i, v in enumerate(validators) if is_active_validator(v)]
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def test_tag_links_render_on_bookmarks_list(client, db_setup): """When a user views their bookmark list - links to the tags should be incldued in the respose, but it should NOT include links to tags associated with other user's bookmarks. """ user = db_setup.get("homer") login = client.login(...
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def parse_decodes(sentences, predictions, lengths, label_vocab): """Parse the padding result Args: sentences (list): the tagging sentences. predictions (list): the prediction tags. lengths (list): the valid length of each sentence. label_vocab (dict): the label vocab. Retur...
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def get_weekday(start_date, end_date, weekday_nums, repeat=None): """ 获取一段时间范围内每个周天对应的日期 :param start_date: :param end_date: :param weekday_nums: list, 星期对应数字 0 ~ 6 :param repeat: :return: """ sdate = datetime.datetime.strptime(start_date, date_pattern1) edate = datetime.datetim...
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def context_processor(target): """ Decorator that allows context processors with parameters to be assigned (and executed properly) in a RequestContext Example:: return render_to_response( template_name, context_instance=RequestContext( request, processors=[ ...
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def write_checkgroups(groups, path): """ Write the current checkgroups file. Arguments: groups (a dictionary representing a checkgroups) path (path of the checkgroups file) No return value """ keys = groups.keys() keys.sort() checkgroups_file = file(path, 'wb') ...
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def test_put_object_from_filelike(repository, generate_directory): """Test the ``Repository.put_object_from_filelike`` method.""" directory = generate_directory({'file_a': None, 'relative': {'file_b': None}}) with open(directory / 'file_a', 'rb') as handle: repository.put_object_from_filelike(handl...
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def data_context_path_computation_context_path_comp_serviceuuid_end_pointlocal_id_capacity_bandwidth_profile_committed_burst_size_delete(uuid, local_id): # noqa: E501 """data_context_path_computation_context_path_comp_serviceuuid_end_pointlocal_id_capacity_bandwidth_profile_committed_burst_size_delete removes...
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def BuildWagonCommand(state): """Build wagon command to build MCEP model for the given state. Example command - $ESTDIR/bin/wagon -track_feats 1-50 -vertex_output mean -desc festival/clunits/mcep.desc -data 'festival/feats/w_3.feats' -test 'festival/feats/w_3.feats' -balance 0 -track 'festival/dist...
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def decode_messages(fit_bytes: bytes) -> typing.List[typing.Dict]: """Decode serialized messages. Arguments: fit_bytes: Encoded messages Returns: Decoded messages """ messages = [] for line in fit_bytes.splitlines(): payload = json.loads(line) messages.append(s...
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def main() : """ Main Function: to compute performance of Two Models with different non-linear functions for different losses Namely, this will generate 4 graphs, for losses MSE and MAE, for each non-linear type Relu and Tanh :return: nothing but four graphs and write the number of errors in the terminal """ ###...
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def test_parse_no_pint_objects_in_df(): """Test that there are no Pint quantities in dataframes created by parser.""" input_file = get_test_data('metar_20190701_1200.txt', mode='rt') metar_str = ('KSLK 011151Z AUTO 21005KT 1/4SM FG VV002 14/13 A1013 RMK AO2 SLP151 70043 ' 'T01390133 10139 2...
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def read_DELETE(msg, hosts): """Parse the DELETE request and send data to the response generator function Args: msg (String): The request message to parse hosts (List): The array of hosts Returns: List: An array of information about the request, including status code, ...
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def iresnet101(pretrained=False, progress=True, **kwargs): """ Constructs the IResNet-101 model trained on Glint360K(https://github.com/deepinsight/insightface/tree/master/recognition/partial_fc#4-download). .. note:: The required input size of the model is 112x112. Args: pretrained (b...
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def get_full_jwt(user: User) -> Dict: """ Get a full jwt response from the username and uid token. """ return { 'access_token': create_access_token(identity=user, fresh=True), 'refresh_token': create_refresh_token(identity=user) }
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def delete(): """ (Local command) Deletes the current note. """ path = vim.current.buffer.name if exists(path): confirm = vim.eval('input("really delete? (y/n): ")') if confirm in ("y", "Y"): remove(path) vim.command("bd!") vim.command("redraw!")
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def GridSearch_Prophet(prophet_grid, metric='mape'): """ GridSearch tool to determine the optimal parameters for prophet Args: - prophet_grid: List of parameters. Enter it as list(ParameterGrid(prophet_grid) - metric: String. Not used yet. May be used to change the metric used to sort ...
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def test_reference_links_548(): """ Test case 548: Unicode case fold is used: """ # Arrange source_markdown = """[ẞ] [SS]: /url""" expected_tokens = [ "[para(1,1):]", "[link(1,1):shortcut:/url:::::ẞ:::::]", "[text(1,2):ẞ:]", "[end-link::]", "[end-para::...
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def _check_max_features(importances, max_features): """Interpret the max_features value""" n_features = len(importances) if max_features is None: max_features = n_features elif isinstance(max_features, int): max_features = min(n_features, max_features) elif isinstance(max_feature...
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def map_blocks(func, data): """Curried version of Dask's map_blocks Args: func: the function to map data: a Dask array Returns: a new Dask array >>> f = map_blocks(lambda x: x + 1) >>> f(da.arange(4, chunks=(2,))) dask.array<lambda, shape=(4,), dtype=int64, chunksize=(2,)> ...
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def download_and_extract( package: str, directory: Path, version: Optional[str] = None, remove_after: bool = False ) -> Path: """Modified to allow avoiding removing files after. Parameters ---------- package directory version remove_after Returns ---...
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def test_case_3_b(setup_leveldb, setup_sqlite): """ Test case 3.b: 3. Incoming record contains 2+ OCNs that resolve to two Concordance Table primary record b. Record OCNs + OCLC OCNs match one CID Test datasets: Zephir cluster: one match CID: 008648991 OCNs: 4912741,...
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def dump_config(exp_dir: str, config: Union[ConfigDict, FrozenConfigDict]) -> None: """Dump a config to disk. Args: exp_dir (str): Path to the experiment directory. config (Union[ConfigDict, FrozenConfigDict]): The config to dump. """ if not os.path.exists(exp_dir): os.makedirs(...
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def premises_to_syllogism(premises): """ >>> premises_to_syllogism(["Aab", "Ebc"]) 'AE1' """ figure = {"abbc": "1", "bacb": "2", "abcb": "3", "babc": "4"}[premises[0][1:] + premises[1][1:]] return premises[0][0] + premises[1][0] + figure
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def fix_fits_keywords(header): """ Update header keyword to change '-' by '_' as columns with '-' are not allowed on SQL """ new_header = {} for key in header.keys(): new_key = key.replace('-', '_') new_header[new_key] = header[key] # Temporary fix - needs to be removed ...
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def request_password(email: str, mailer: Mailer, _tn: Translator): """ Create new hashed password and send mail.. :param email: Mail-address which should be queried :param mailer: pyramid Mailer :param _tn: Translator :return: dict with info about mailing """ db_user = DBDiscussionSessi...
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def is_sum_lucky(x, y): """This returns a string describing whether or not the sum of input is lucky This function first makes sure the inputs are valid and then calculates the sum. Then, it will determine a message to return based on whether or not that sum should be considered "lucky" """ if x...
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def unsync_function(func, *args, **kwargs): """Runs an async function in a standard blocking way and returns output""" return asyncio.run(func(*args, **kwargs))
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def zip_results(name: str, recipes: Iterable[Recipe], cache=CacheType.Auto) \ -> Recipe[Union[List[Tuple[Any, ...]], Dict[Any, Tuple[Any, ...]]]]: """ Create a Recipe that zips the outputs from a number of recipes into elements, similar to Python's built-in zip(). Notably, dictionaries are handled a...
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def get_muscle_reference_dictionary(): """ The @article{bashkatov2011optical, title={Optical properties of skin, subcutaneous, and muscle tissues: a review}, author={Bashkatov, Alexey N and Genina, Elina A and Tuchin, Valery V}, journal={Journal of Innovative Op...
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def flake8_entrypoint(physical_line: str) -> Optional[Tuple[int, str]]: """Flake8 plugin entrypoint that operates on physical lines.""" match = RX_TODO_OR_ELSE.search(physical_line) if match: by = match.group(2) pact = match.group(3).strip() try: TodoOrElse().by(pact, by=...
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def test_to_config_dict_given_non_configurable() -> None: """ Test that ``to_config_dict`` errors when passed an instance that does not descend from configurable. """ class SomeOtherClassType (object): pass inst = SomeOtherClassType() with pytest.raises(ValueError, ...
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def smartquotes(text): """ Runs text through pandoc for smartquote correction. This script accepts a paragraph of input and outputs typographically correct text using pandoc. Note line breaks are not retained. """ command = shlex.split('pandoc --smart -t plain') com = Popen(command, shell=...
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def get_nearest_stations_xy(x, y, variable, n=1, stations=None, ignore=None): """find the KNMI stations that measure 'variable' closest to the x, y coordinates Parameters ---------- x : int or float x coordinate in RD y : int or float x coordinate in RD variable : str ...
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def parseStdInput(): """Obtain a graph by parsing the standard input as per the format specified in the PACE Challange. """ edges = [(1,2),(2,3),(3,4),(4,1)] G = nx.Graph() G.add_edges_from(edges) return G
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def train_worker(dpw, reverb_client, config): """Train worker loop. Collects rollouts and writes sampled discounted state visitation to reverb indefinitely (xmanager should kill this job when the learner job ends). Args: dpw: The discretized puddle world to use. rever...
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def strfdelta(tdelta, fmt): """ Get a string from a timedelta. """ f, d = Formatter(), {} l = {"D": 86400, "H": 3600, "M": 60, "S": 1} k = list(map(lambda x: x[1], list(f.parse(fmt)))) rem = int(tdelta.total_seconds()) for i in ("D", "H", "M", "S"): if i in k and i in l.keys(): ...
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def get_file_list_from_dir(parent_dir: Path, file_mask: str = "*") -> list: """ Recursively gets a list of files in a Path directory with the specified name mask and return absolute string paths for files """ get_logger(__name__).debug("Iterating for files in '{}'".format(parent_dir.absolute())) ...
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def imputation_Y(X, model): """Perform imputation. Don't normalize for depth. Args: X: feature matrix from h5. model: a trained scBasset model. Returns: array: a peak*cell imputed accessibility matrix. Sequencing depth isn't corr...
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def format_percent(x, _pos=None): """ plt.gca().yaxis.set_major_formatter(format_percent) """ x = 100 * x if abs(x - round(x)) > 0.05: return r"${:.1f}\%$".format(x) else: return r"${:.0f}\%$".format(x)
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def is_row_and_col_balanced(T1, T2): """ Partial latin squares T1 and T2 are balanced if the symbols appearing in row r of T1 are the same as the symbols appearing in row r of T2, for each r, and if the same condition holds on columns. EXAMPLES:: sage: from sage.combinat.matrices.latin...
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def submit(ds, entry_name, molecule, index): """ Submit an optimization job to a QCArchive server. Parameters ---------- ds : qcportal.collections.OptimizationDataset The QCArchive OptimizationDataset object that this calculation belongs to entry_name : str The base entr...
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def db(): """Database queries (including initialization)."""
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def list_isos(apiclient, **kwargs): """Lists all available ISO files.""" cmd = listIsos.listIsosCmd() [setattr(cmd, k, v) for k, v in kwargs.items()] return(apiclient.listIsos(cmd))
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async def edit_message_live_location( token: str = TOKEN_VALIDATION, latitude: float = Query(..., description='Latitude of new location'), longitude: float = Query(..., description='Longitude of new location'), chat_id: Optional[Union[int, str]] = Query(None, description='Required if inline_message_id i...
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def process_rollout(rollout, gamma, lambda_=1.0): """ given a rollout, compute its returns and the advantage """ batch_si = np.asarray(rollout.states) batch_a = np.asarray(rollout.actions) rewards = np.asarray(rollout.rewards) action_reward = np.concatenate((batch_a,rewards[:,np.newaxis]), a...
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async def async_setup_entry(hass, config_entry, async_add_entities): """Add sensors for passed config_entry in HA.""" coordinator: IotawattUpdater = hass.data[DOMAIN][config_entry.entry_id] created = set() @callback def _create_entity(key: str) -> IotaWattSensor: """Create a sensor entity."...
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def calculate_cost(cost, working_days_flag, month, nr_of_passes): """Calculate the monthly tolls cost""" if working_days_flag: passes = working_days(month) * nr_of_passes else: now = datetime.datetime.now() passes = calendar.monthrange(now.year, month)[1] * nr_of_passes total_cos...
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def e_dl() -> str: """Fetch size of archives to be downloaded for next system update.""" size = 'Calculating...' with open(file=TMERGE_LOGFILE, mode='r', encoding='utf-8') as log_file: for line in list(log_file)[::-1]: reqex = search(r'(Size of downloads:.)([0-9,]*\s[KMG]iB)', line) ...
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def get_model_fn(): """Returns the model definition.""" def model_fn(features, labels, mode, params): """Returns the model function.""" feature = features['feature'] print(feature) labels = labels['label'] one_hot_labels = model_utils.get_label( labels, params, FLAGS.src...
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def build_node(idx, node_type): """ Build node list :idx: a value to id mapping dict :node_type: a string describe the node type :returns: a list of records of the nodes extracted from the mapping """ return rekey(idx, 'value', 'id:ID', {':LABEL': node_type})
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def _getTypeFromExtension(path, mode='write'): """ Parameters ---------- path : str path from with to pull the extension from - note that it may NOT be ONLY the extension - ie, "obj" and ".obj", will not work, but "foo.obj" will mode : {'write', 'read'} the type is ba...
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def residual_block(filters, repetitions,kernel_size=(3,3),strides=(2,2), is_first_layer=False): """Builds a residual block with repeating bottleneck blocks. """ def f(input): for i in range(repetitions): init_strides = (1, 1) if i == 0 and not is_first_layer: ...
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def vpg_omega(X,Y,Gamma=1, sigma=1, polarIn=False): """ Vorticity distribution for 2D Gaussian vortex patch """ if polarIn: r = X else: r = np.sqrt(X ** 2 + Y ** 2) omega_z = Gamma/(np.pi*sigma) * (np.exp(- r**2/sigma**2)) return omega_z
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async def _run_filter_tests(hass, tests, process_queue, mock_batch): """Run a series of filter tests on azure event hub.""" for test in tests: hass.states.async_set(test.id, STATE_ON) await hass.async_block_till_done() await process_queue(None) if test.should_pass: m...
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def test_example_file_passing_using_fixture(fs_reload_example): """Test passes if using a fixture that reloads the module containing EXAMPLE_FILE""" fs_reload_example.create_file(example.EXAMPLE_FILE, contents='stuff here') check_that_example_file_is_in_fake_fs()
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def autoload(): """ Attempts to load (import) notification handlers from modules defined in ``PYNOTIFY_AUTOLOAD_MODULES`` """ modules = settings.AUTOLOAD_MODULES if modules: for module in modules: try: import_module(module) except ImportError: ...
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def get_outgroup(tree: CassiopeiaTree, triplet: Tuple[str, str, str]) -> str: """Infers the outgroup of a triplet from a CassioepiaTree. Finds the outgroup based on the depth of the latest-common-ancestors of each pair of items. The pair with the deepest LCA is the ingroup and the remaining leaf is th...
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def delete_host(resource_root, host_id): """ Delete a host by id @param resource_root: The root Resource object. @param host_id: Host id @return: The deleted ApiHost object """ return call(resource_root.delete, "%s/%s" % (HOSTS_PATH, host_id), ApiHost)
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def get_preds(model: nn.Module, image: Union[np.array, str], **kwargs) -> Tuple[List]: """ Generated predictions for the given `image` using `model`. """ logger = _get_logger(name=__name__) # load in the image if string is give if isinstance(image, str): image = Image.open(image).conver...
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def get_csv_data(filepath, source='DoQ'): """ Yield a large csv row by row to avoid memory overload """ if source =='DoQ': with open(filepath, "rt") as csvfile: datareader = csv.reader(csvfile, delimiter='\t') for row in datareader: if row[2] == 'LENGTH' o...
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async def unblock_func(func_name:object, func_args, logger=None, default_res=None, is_new_loop=False,): """ 异步函数非阻塞 :param func_name: def 函数对象名 :param func_args: 请求参数可迭代对象(必须遵循元素入参顺序!) :param logger: :par...
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def replace_if_has_wiki_link(line: str, folder_dict: Dict) -> Tuple[str, int]: """ ^title :return: (string with all wikis replaced, replacement count) """ embed_rule = re.compile(re_md_reference) wiki_partial_rule = re.compile(re_md_wiki_partial) wiki_rule = re.compile(re_md_wiki) ne...
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def init_w(w, n): """ :purpose: Initialize a weight array consistent of 1s if none is given This is called at the start of each function containing a w param :params: w : a weight vector, if one was given to the initial function, else None NOTE: w MUST be an array of np.float6...
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def parallelise_edges(xy, edges, targets, i_nbrs, ij_e, fixed=None, kmax=100, lmin=None, lmax=None, callback=None): """Parallelise the edges of a mesh to given target vectors. Parameters ---------- xy : list The XY coordinates of the vertices of the edges. edges : list The edges as ...
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def _ensure_min_resources(progs, cores, memory, min_memory): """Ensure setting match minimum resources required for used programs. """ for p in progs: if p in min_memory: if not memory or cores * memory < min_memory[p]: memory = float(min_memory[p]) / cores return cor...
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def ctypes_pointer(name): """Create a ctypes type representing a C pointer to a custom data type ``name``.""" return type("c_%s_p" % name, (ctypes.c_void_p,), {})
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def generate_linear_data(n, betas, sigma): """Generate pandas df with x and y variables related by a linear equation. Export data as csv. :param n: Number of observations. :param betas: beta parameters. :param sigma: standard deviation :return: None """ x = np.linspace(start=0.0, stop=1....
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def entry( text, *, foreground: str = "", background: str = "", sgr: str = "", jump_line: str = "\n> ", ) -> str: """ This function is derived from the input, but with the option of coloring it and some different formatting. Note: If you use Windows, the coloring opti...
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def vrotate_3D(vec: np.ndarray, ref: np.ndarray) -> np.ndarray: """Rotates a vector in a 3D space. Returns the rotation matrix for `vec` to match the orientation of a reference vector `ref`. https://math.stackexchange.com/questions/180418/calculate-rotation-matrix-to-align-vector-a-to-...
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def inject_data(image, key=None, net=None, metadata=None, admin_password=None, files=None, partition=None, use_cow=False): """Injects a ssh key and optionally net data into a disk image. it will mount the image as a fully partitioned disk and attempt to inject into the speci...
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def asymptotic_decay(learning_rate, t, max_iter): """Decay function of the learning process. Parameters ---------- learning_rate : float current learning rate. t : int current iteration. max_iter : int maximum number of iterations for the training. """ return le...
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def get_cell_content(browser, author): """ get novel cells return [cell, cell, cell] """ content = list() cells = browser.find_all(class_='t t2') for cell in cells: if cell.find(class_='r_two').b.string != author: continue for cell_content in cell.find(class_=['tp...
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def add_supported_cxxflags(self, cxxflags): """ Check which cxxflags are supported by compiler and add them to env.CXXFLAGS variable """ if len(cxxflags) == 0: return self.start_msg('Checking supported CXXFLAGS') supportedFlags = [] for flags in cxxflags: flags = Utils.to_l...
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def iter_meta_refresh(file): """Iterate through meta refreshes from a file. Args: file: str, path-like, or file-like object """ try: fh = open(file, 'rb') except TypeError: fh = file except FileNotFoundError: fh = None if not fh: return try: ...
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def kmeans(data: cp.ndarray, K: int, centroids: cp.ndarray): """ Clusters points into k clusters using k_means clustering. """ print("Start K-means clustering.") N, D = data.shape new_centroids = cp.full((K, D), 0.0) loop = 1 while loop < 200: # assign each point to near...
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def _init_unique_pool(_ic_profile_dic, _cac_profile_dic, _ic_shape, _cac_shape): """initialize pool, function used to put data into shared memory""" print(f"- Initialize core with illumination correction profiles for {list(_ic_profile_dic.keys())}") init_dic['illumination'] = _ic_profile_dic print(f"- I...
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def do_host_describe(cs, args): """Describe a specific host.""" result = cs.hosts.get(args.host) columns = ["HOST", "PROJECT", "cpu", "memory_mb", "disk_gb"] utils.print_list(result, columns)
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def triangle_area(a, h): """Given length of a side and high return area for a triangle. >>> triangle_area(5, 3) 7.5 """ #[SOLUTION] return a * h / 2.0
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def generate_exclude_file1_file2(HWEresults_file, batches_list, draw_script, all_output, perbatch_output, allbatches_output, FDR_index_remove_variants): """generate exclude file 1: From HWE calculations across the entire collection, remove variants for which HWE fails even if the worst batch removed (i.e. e...
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def create_mongo_handler(config): """ :param config: configuration dictionary :return: [MongoLogHandler, ] if 'mongo_logger' is in options, else [] """ from nicos.core import ConfigurationError if hasattr(config, 'mongo_logger'): url = urllib.parse.urlparse(config.mongo_logger) ...
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def split_and_load(data, ctx_list, batch_axis=0, even_split=True): """Splits an NDArray into `len(ctx_list)` slices along `batch_axis` and loads each slice to one context in `ctx_list`. Parameters ---------- data : NDArray A batch of data. ctx_list : list of Context A list of Co...
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def _get_scoped_outputs(comp, g, explicit_outs): """Return a list of output varnames scoped to the given name.""" cnamedot = comp.name + '.' outputs = set() if explicit_outs is None: explicit_outs = () for u,v in g.list_connections(): if u.startswith(cnamedot): outputs.a...
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def init_ha_active(datanode, cluster): """ Do initial HA setup on the leader. """ local_hostname = hookenv.local_unit().replace('/', '-') hadoop = get_hadoop_base() hdfs = HDFS(hadoop) hdfs.stop_namenode() remove_state('namenode.started') # initial cluster is us (active) plus a stand...
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