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def transformation(job_title): """ Transform a job title in a unisex job title Here are examples of main transformations : - Chauffeur / Chauffeuse de machines agricoles --->>> Chauffeur de machines agricoles - Débardeur / Débardeuse --->>> Débardeur - Arboriste grimpeur / grimpeuse --->>> Arbor...
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from typing import Optional from typing import Any def _handle_tileset(tileset: Optional[tcod.tileset.Tileset]) -> Any: """Get the TCOD_Tileset pointer from a Tileset or return a NULL pointer.""" return tileset._tileset_p if tileset else ffi.NULL
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import gzip import bz2 def open_zipped(infile, mode='r'): """ Return file handle of file regardless of zipped or not Text mode enforced for compatibility with python2 """ mode = mode[0] + 't' p2mode = mode if hasattr(infile, 'write'): return infile if isinstance(infile, str): ...
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from typing import Dict def user_kid_injection(jwt_json: Dict, injection: str) -> str: """ Print for kid injection method. Parameters ---------- jwt_json: Dict your jwt json (use encode_to_json.Check Doc). injection: str your injection Returns ---------- str ...
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def render_text_block(el, ns=None): """ Created for EcoSpold2. Take all the children of an objectified element and render them as a text block. Implement variable substitution (!!!) :param el: Element with tags including 'text' and 'variable' :param ns: [None] namespace :return: """ vs ...
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import time import requests import json def macro_china_cpi_monthly(): """ 中国月度CPI数据, 数据区间从19960201-至今 https://datacenter.jin10.com/reportType/dc_chinese_cpi_mom :return: pandas.Series """ t = time.time() res = requests.get( JS_CHINA_CPI_MONTHLY_URL.format( str(int(roun...
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def get_integer(prompt): """Gets an integer from the user.""" myInteger = input(prompt) while not is_integer(myInteger): print("Integers only please.") myInteger = input(prompt) myInteger = int(myInteger) return myInteger
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def all_pairwise_distances(x, y=None, squared=False, approx=False): """ Fast pairwise L2 squared distances between two sets of d-dimensional vectors Args: x (Tensor): an Nxd matrix y (Tensor, default=None): an optional Mxd matirx squared (bool, default=False): if True returns square...
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def _random_zoom(x, scale=0.1, imshape=(256,256), **kwargs): """ Randomly zoom in on the image- augmented image will be between [scale] and 100% of original area. Based on the random crop function in the SimCLR repo: https://github.com/google-research/simclr/blob/7fd0c80092a650c5318ce08fd3...
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def common_keys(dictionary_list): """ Identify keys common to a set of dictionaries. Arguments: dictionary_list (list of dict): dictionaries to analyze Returns: (list): sorted list of common keys """ # find intersection of key sets common_key_set = None for current_diction...
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def gaus(x, a, x0, sigma, c): """ Gaussian function. :param x: :param a: constant :param x0: constant :param sigma: RMS width :param c: gaussian function offset :return: """ return a * np.exp(-(x - x0) ** 2 / (2 * sigma ** 2)) + c
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import random def coin_flip(): """Randomly return 'heads' or 'tails'.""" if random.randint(0,1) == 0: return "heads" else: return "tails"
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def part_one(data): """Part one""" nodes = read_nodes(data) for name, _, _ in nodes: count = data.count(name) if count == 1: return name return None
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from typing import Type def get_tree_model() -> Type['TreeBase']: """Returns the Tree model, set for the project.""" return get_model_class('MODEL_TREE')
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def wigner_d_parallel(m1,m2,theta,l,ncpu=None,l_use_bessel=1.e4): """ Compute wigner matrix in parallel. """ if ncpu is None: ncpu=cpu_count() p=Pool(ncpu) d_mat=np.array(p.map(partial(wigner_d,m1,m2,theta,l_use_bessel=l_use_bessel),l)) p.close() p.join() return d_mat[:,:,0]....
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def check_rule_permission(rule_id, permission): """ Check the respective rule breaking the respective permission. Args: rule_id (str): ruleNumber which should match 1 of the rules present in rule_ids for auto-remediation. permission (list): The permis...
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import os def readESO6Trajectory(trajectoryFile): ### DONE """ Reading trajectory eS06 file trajectory [list] initTime [s] endTime [s] """ trajectory=[] for line in open(trajectoryFile): trajectory.append(line.split()) firstLine=os.popen('head -1 '+trajectoryFile).read().split() endLine=os.popen('tail -1 ...
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def flags_to_faces(flags, vert_tags): """ flags is a dict where the key face tag + vert tag value (face tag, vert tag, tag of next CCW vert in the face) vert_tags key vert tag value index of vert returns a list of faces, where each face is given as a list of vert indices in CCW...
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def generate_cell_type_cell_sets(df, cl_obo_file): """ Generate a tree of cell sets for hierarchical cell type annotations. """ tree = init_cell_sets_tree() # Load the cell ontology DAG graph, id_to_name, name_to_id = load_cl_obo_graph(cl_obo_file) ancestors_and_sets = [] for cell...
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import os import json def paginate(entries_to_post): """ This expects a list of dicts, and returns a list of lists of dicts, where the maximum length of each list of dicts, under JSONification, is less than max_chars """ max_chars = int(os.environ.get("PAGE_MAX_CHARS")) if os.environ.get("PA...
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def selectPersonsWhoAreRadiologists(): """ Helper method to select all persons who are radiologists. :return: A list of persons who are radiologists. """ return db.session.query(models.Person).join(models.User).filter(models.User.user_class == 'r').all()
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def init_flat_save_grid( dataset, grid_shape, times, time_units, projection, x_min, x_max, y_min, y_max, units, ): """ Prepare a netCDF4 dataset for saving a concentration grid. This preparation involves creating the appropriate dimensions, variables, and attribut...
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import os def load_training_df(dataset_path: str) -> pd.DataFrame: """ Load data from training set in Deep Fashion 2 into DataFrame """ #training_dir = os.path.join(dataset_path, 'train') training_dir = dataset_path images_dir = os.path.join(training_dir, 'image') images_df = _load_images_df(image...
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import argparse def get_args(): """Parse sys.argv""" parser = argparse.ArgumentParser() parser.add_argument('-i','--input-dir', required=True, help='The input directory containing the phylip files.') args = parser.parse_args() return args
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import uuid def Upload( id="dash-uploader", text="Drag and Drop Here to upload!", text_completed="Uploaded: ", cancel_button=True, pause_button=False, filetypes=None, max_file_size=1024, chunk_size=1, default_style=None, upload_id=None, max_files=1, ): """ du.Upload...
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from re import T def adagrad(loss, all_params, learning_rate=1.0, epsilon=1e-6): """ epsilon is not included in the typical formula, See "Notes on AdaGrad" by Chris Dyer for more info. """ all_grads = theano.grad(loss, all_params) all_accumulators = [theano.shared(np.zeros(param.get_value().sh...
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def _get_or_build_subword_text_encoder(tmp_dir, vocab_filepath, target_size): """Builds a SubwordTextEncoder based on the corpus. Args: tmp_dir: directory containing dataset. vocab_filepath: path to store (or load) vocab. target_size: an optional integer. Returns: a SubwordTextEncoder. """ i...
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import ast def _ast_tree_to_dict(tree, only_self_params=False, lineno=False): """Parses ast trees to dict. :param tree: ast.Tree :param only_self_params: get only self params from class __init__ function :param lineno: add params line number (needed for update) :return: """ result = {} ...
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import logging import argparse import bisect def main(): """Finds the commit SHA where an error was initally introduced.""" logging.getLogger().setLevel(logging.INFO) utils.chdir_to_root() parser = argparse.ArgumentParser( description='git bisection for finding introduction of bugs') parser.add_argum...
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def create_apps( blockchain_services, endpoint_discovery_services, raiden_udp_ports, transport_class, verbosity, reveal_timeout, settle_timeout, database_paths, retry_interval, retries_before_backoff, throttle_capacity, thro...
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def sqnxt23_w3d2(**kwargs): """ 0.75-SqNxt-23 model from 'SqueezeNext: Hardware-Aware Neural Network Design,' https://arxiv.org/abs/1803.10615. Parameters: ---------- pretrained : bool, default False Whether to load the pretrained weights for model. root : str, default '~/.torch/models'...
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import requests def spotlight(text): """To implement the DBpedia Spotlight API: """ headers = { 'Accept': 'application/json', } #e.g. text = "What is a car?" "enitenziagite" #"President Obama" data = { "text":text , 'confidence': '0.35' } response = requests.post('http:...
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def NullBBox(): """ Returns a BBox object with all NaN entries. This represents a Null BB box; BB merged with it will return BB. Nothing is inside it. """ arr = np.array(((np.nan, np.nan), (np.nan, np.nan)), np.float64) return np.ndarray.__new__(BBox, shape=arr.shape, dtype=arr.dtype,...
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def fallback_to_gcc(args): """Check whether if we should fall back to GCC.""" if not invoked_as_gcc(): return False return any(arg in GCC_ONLY_ARGS for arg in args[1:])
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def wms_in_extent(vector, extent_geom, buffer=0.1): """ checks if vector layer within extent """ bounds = wms_bbox(vector) bbox_vector = (bounds[0], bounds[2], bounds[1], bounds[3]) extent_buff = extent_geom.Buffer(buffer) bbox_extent = extent_buff.GetEnvelope() return bbox1_in_bbox2(bbox_vector...
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def nans(axes=None, dims=None, shape=None): """ Initialize an empty array filled with NaNs. See empty for doc. >>> nans(dims=('time','items'), shape=(2, 3)) dimarray: 0 non-null elements (6 null) 0 / time (2): 0 to 1 1 / items (3): 0 to 2 array([[nan, nan, nan], [nan, nan, nan]]) ...
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def maximize( criterion, params, algorithm, criterion_kwargs=None, constraints=None, general_options=None, algo_options=None, gradient_options=None, logging=DEFAULT_DATABASE_NAME, log_options=None, dashboard=False, db_options=None, ): """Maximize *criterion* using *al...
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def hog_feature(image, multichannel=True): """ Extract HOG feature descriptors from the image. Args: image (numpy array): Array of image pixels. multichannel (bool): True for RGB image, else False. Returns: (numpy array): Feature descriptors. """ hog_feature_var = hog(ima...
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import io def return_object(): """ Retrieve object data from the Fink database """ if 'output-format' in request.json: output_format = request.json['output-format'] else: output_format = 'json' # Check all required args are here required_args = [i['name'] for i in args_objects...
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def detect_anomalies_cons(residuals, threshold, summary=True): """ Compares residuals to a constant threshold to identify anomalies. Can use set threshold level or threshold determined by set_cons_threshold function. Arguments: residuals: series of model residuals. threshold: constant th...
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import redis def connect_redis(dsn): """ Return the redis connection :param dsn: The dsn url :return: Redis """ return redis.StrictRedis.from_url(url=dsn)
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def _instance_to_allocations_dict(instance): """Given an `objects.Instance` object, return a dict, keyed by resource class of the amount used by the instance. :param instance: `objects.Instance` object to translate """ # NOTE(danms): Boot-from-volume instances consume no local disk is_bfv = com...
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def _tag_depth(path, depth=None): """Add depth tag to path.""" # All paths must start at the root if not path or path[0] != '/': raise ValueError("Path must start with /!") if depth is None: depth = path.count('/') return "{}{}".format(depth, path).encode('utf-8')
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def init_effects(context): """ Initialise common effects :returns: effect configuration """ surface_manager = context.surface_manager config = [] config.append(('cure minor wounds', {'type': Heal, 'duration': 20, 'frequency': 5, ...
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from typing import Dict from typing import Any async def provider() -> Dict[str, Any]: """Define a basic example data provider function.""" async with Browser() as browser: await browser.goto("https://httpbin.org/html") content = await browser.content() # response = await client.get("h...
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def get_runtime_map(runtimes, module, tags=()): """Return a mapping of module and its derivatives that satisfy a specified set of runtimes""" result = {} modruntimes = get_compatible_runtimes(module, tags=tags, include_ancestors=True) runtimes_full = [] ...
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def calc_sl_price(contract_price, sl_percent): """Returns price that is sl_percent below the contract price""" return round(contract_price * (1 - sl_percent), 2)
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def Vortex(df, n): """ Vortex Indicator """ i = 0 TR = [0] while i < len(df) - 1: # df.index[-1]: Range = max(df.get_value(i + 1, 'High'), df.get_value(i, 'Close')) - min(df.get_value(i + 1, 'Low'), df.get_value(i, 'Close')) TR.append(Range) i = i + 1 i = 0 VM = ...
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def qutip_gate(gate_name: str): """Generates the Pauli gate from a name Parameters: ----------- gate_name: string representing the gate, e.g. 'X' for sigmax() etc. """ if gate_name == 'X': return sigmax() elif gate_name == 'Y': return sigmay() elif gate_name == 'Z': ...
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def cspline(r,L,extra=False): """ CSPLINE Compactly supported spline function and derivatives. f = cspline(R,L) is the compactly supported spline function with length scale parameter L evaluated at R. The length scale L is defined here as L = sqrt(-1/f''(0)). f,df,ddf = cspline(R,L...
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import logging def _publish_project_details(project, config, batch_id, published_projects): """Publish project data to pubsub topic. Args: project: obj, projects_lib._Project object. config: obj, config_utils._Config object. batch_id: random number. published_projects: set, to...
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def complete_key(ctx, param, incomplete): """ Autocompletion for keys. """ database = ctx.parent.params.get("database") if database: data = load_database(database) else: data = [] data = bib_entries(data) return [x["key"] for x in data if x["key"].startswith(incomplete.lo...
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import argparse def get_args(): """ Command line arguments parser. """ ap = argparse.ArgumentParser( prog='preprocess_treegrafter.py', description="TreeGrafter data preprocessor", formatter_class=argparse.ArgumentDefaultsHelpFormatter) ap.add_argument( '-d', '--data', req...
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import requests import json import time def get_report(scan_id, headers): """ Will get all vulnerabilities for the scan """ url = f"https://cloud.tenable.com/was/v2/scans/{scan_id}/report" headers["Content-Type"] = "application/json" response = requests.request("GET", url, headers=heade...
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def softmax(input, use_cudnn=False, name=None, axis=-1): """ This operator implements the softmax layer. The calculation process is as follows: 1. The dimension :attr:`axis` of the ``input`` will be permuted to the last. 2. Then the input tensor will be logically flattened to a 2-D matrix. The matrix's...
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def binaryStat(augboost_m, X_test, y_test, y_pred): """ calculate stats for binary classification :param augboost_m: AugBoost classifier :param X_test: test data :param y_test: test classification :param y_pred: predicted classification using augboost_m :return: accuracy, TPR, FPR, precision...
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def get_loaders( train_batch_size, val_batch_size, train_set, val_set, num_stages=1, num_workers=8, train_shuffle=True, val_shuffle=False, train_pin_memory=False, val_pin_memory=False, train_drop_last=False, val_drop_last=False, ): """Create train and val loaders""" ...
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def mysigmoid(mylist:list)->list: """ This function converted each element of the input list to its sigmoid form # Input: mylist: list, This is the input list where sigmoid operation is performed # Returns: list: It returns the transformed list # Functionality: The input ...
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def _loadmat_internal(fn): """ Helper function to load matlab data Parameters ---------- fn: basestring Filename of Matlab .mat file Returns ------- mat: dict Data in fn Notes ----- Data is loaded with mat_dtype=True so that e.g. data stored in float (i...
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import json def get_snapshot_time_points_table(results: PyDssResults, job_info: JobInfo): """Return the snapshot time points determined by each job.""" snapshot_time_points_table = [] data = json.loads(results.read_file(f"Exports/snapshot_time_points.json")) row = {"name": job_info.name} for time_...
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import hashlib def verifyhash_password_hashlib(password: str, hash: str) -> bool: """check if password is correct using hashlib Args: password (str): user password hash (str): user password encrypted Returns: bool: True if correct password else False """ return hashlib.md...
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import random def uniform_coords(lim): """ Generates uniformly distributed random coordinates in the 2D square, (0,lim)^2. Parameters ---------- lim : int, float Upper bound of coordinate value in both the x and y directions. Returns ------- tuple 2D coordinates. ...
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def docalculations(set1, set2, tempdir, pairwisecorr, activeds): """compute canonical correlations and return results dictionary tempdir is where to write the temporary sav files printcorr is whether or not to print correlations activeds is the name of the active dataset""" # In order to c...
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def get_utility_command_kill_signal(name): """ Return the proper kill signal used to stop the utility command. :param name: name of utility command (string). :return: kill signal """ # note that the NetworkMonitor does not require killing (to be confirmed) sig = SIGUSR1 if name == 'MemoryM...
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def get_files_recursive_by_id(root_entry): """ Walk the tree starting from a specified root node, collecting all of the files that hang from those entries. """ results = {'.': root_entry} # Get the files for file1 in get_all_files(root_entry['id']): results[file1['title']] = file1 ...
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from typing import Optional def get_api_release(api_id: Optional[str] = None, release_id: Optional[str] = None, resource_group_name: Optional[str] = None, service_name: Optional[str] = None, opts: Optional[pulumi.InvokeOptions] = None) ->...
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def run(inp, opt, cfg): """ calculate svv from arterial waveform :param art: arterial waveform :return: max, min, upper envelope, lower envelope, respiratory rate, ppv """ data = arr.interp_undefined(inp['art1']['vals']) srate = inp['art1']['srate'] data = arr.resample_hz(data, srate, 1...
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def build_drive_aggregator( rotation: str = "hadamard", concatenate: bool = True, zeroing: bool = True, clipping: bool = True, weighted: bool = True) -> tff.aggregators.AggregationFactory: """Creates an aggregation factory for comparing to DRIVE. Args: rotation: A string to specify what rot...
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def get_node_info(host, port, serviceNodeId): """GET (serviceNodeId) get_node_info""" method = 'get_node_info' params = { 'serviceNodeId' : serviceNodeId } return _check(https.client.jsonrpc_get(host, port, '/', method, params=params))
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def collect_certificate_data_from_file(certname, pem_file): """ Collect certificate data Input: certname, pem_file Returns: (certname, expiration_date, annotation_data, mode_metadata) expiration_date will be None if data missing or error annotation_data will be set to defaults ...
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def sample_evergreen_configuration(): """Return sample evergreen configuration""" return get_sample_yaml("evergreen_config.yml")
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import copy def add_target_info(data, tables, targets): """ >>> d = [{'data': [{'table': 'products'}]}] >>> tables = {'products': {'target': 'products'}} >>> targets = [{ 'name': 'products', 'type': 'foo' }] >>> result = add_target_info(d, tables, targets) >>> result == [{'data': [{'table': '...
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import logging def fetch_json2xx_async(url, content='', method='GET', credentials=None, headers=None, multipart=False, ua='', timeout=50, returnhandler=lambda x: x, caching=None): """Like `fetch_async()` but returnhandler is called with decoded jsondata.""" def decodingreturnhandler(status, rhead...
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def find_outlier_samples(X, toobig1, toobig2=[]): """Find outlier trials using an absolute threshold.""" n_samples, n_chans, n_trials = theshapeof(X) X = unfold(X) # apply absolute threshold weights = np.ones((n_trials * n_samples, n_chans)) if toobig1 is not None: weights[np.where(abs...
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def new_roc_bound_w_pi( # pylint: disable=invalid-name bc2: float, fpr: np.ndarray, pi: float ) -> np.ndarray: """Calculates our new ROC upper bound for parameter pi. Args: bc2: Bhattacharyya coefficient squared. fpr: False positive rates. pi: Prior for H1 (i.e., weight for FNR). ...
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def check_match(filename, contents): """Check if contents contains any matching entries""" ret = False for reg in REGEX_LIST: match = reg.search(contents) if match: suppressed = False for supp in SUPPRESSION_LIST: idx = match.start() supp_match = supp.match(contents[idx:]) if supp_match: s...
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import time import os def plot(graph, legend=True, labels=False, major=True, filename='', save=True): """If major=True, plot the major component, else plot the entire graph""" # print('Start plotting the network ....') tic = time.time() plt.ioff() plt.clf() if major: g...
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import click def check(context: click.Context) -> int: """ Runs a one-time type check of a Python project. """ return _run_check_command(context.obj["arguments"])
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def riscale_coordination(coordinates, x, y, z): """ Robert: I do not understand why you would want this quantity. """ coordinatesCM = [] for i in range(len(coordinates)): coordinatesCM.append( [str(coordinates[i][0]), coordinates[i][1]-x, coordinates[i][2]-y,...
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def get_bonds(input_group): """Utility function to get indices (in pairs) of the bonds.""" out_list = [] for i in range(len(input_group.bond_order_list)): out_list.append((input_group.bond_atom_list[i * 2], input_group.bond_atom_list[i * 2 + 1],)) return out_list
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def create_iterator(pattern, batch_size, sequence_length, vocab_size, repeat=False): """ Parameters ---------- pattern : string glob pattern with files to read batch_size : integer batch size for input sequence_length : integer unroll size for rnn vocab_size : inte...
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async def get_location_by_id(request: Request, id: int, source: Sources = "jhu", timelines: bool = True): """ Getting specific location by id. """ location = await request.state.source.get(id) return {"location": location.serialize(timelines)}
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from typing import List def bio_tags_to_spans(tag_sequence: List[str], classes_to_ignore: List[str] = None) -> List[TypedStringSpan]: """ Given a sequence corresponding to BIO tags, extracts spans. Spans are inclusive and can be of zero length, representing a single word span. Il...
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from typing import OrderedDict def file_list_table_format(result): """Format file list as a table.""" table = [] for item in result: row = OrderedDict() row['Name'] = item['name'] row['Type'] = item['fileType'] row['Size'] = '' if item['fileType'] == 'directory' else str(it...
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def scsi_out(d, cdb, data): """Send a low-level SCSI packet with outgoing data.""" return d.scsi_out(pad_cdb(cdb), data)
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def read_data(file, delimiter="\n"): """Read the data from a file and return a list""" with open(file, 'rt', encoding="utf-8") as f: data = f.read() return data.split(delimiter)
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import argparse def create_args_parser(): """ process command line arguments and perform sanity checks """ parser = argparse.ArgumentParser(description="Run the same command across a number of " "AWS accounts and/or regions.", ...
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def deubiquitinase(): """Curate deubiquitinases.""" return _render_func( get_dub_statements, title="Deubiquitinase Curator", description=f"""\ The deubiquitinase curator identifies INDRA statements using INDRA CoGEx whose subjects are human deubiquitinase genes an...
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def mark(name=None) -> Node: """ Mark is a pseudonym of identity. The idea is to mark (associate a name) internal placeholders (from the graph point of view). :param name: The identifier of the identity node :return: """ return Identity(name)
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def create_maf_record_from_vcf(sample_id, center_name, sequence_source, vcf_data, is_germline_data, matched_normal_sample_id, tumor_sample_data_col): """ Creates MAF record from VCF data. """ # init maf record maf_data = init_maf_record() # set easy to resolve values maf_data["Tumor_Sam...
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def disable_by_type(token, _type, disable=False, customerid=None): """ Toggle a check so it is enabled or disabled. Accepts an API token, the checkid of the check to be toggled, whether it's enabled/disabled (disable by default), and the customerid if the check is a part of a subaccount :type toke...
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def delete_reports_endpoint(): """A Flask route which accepts a list of report filenames and then deletes them from the reports path. This endpoint should be json and the body should be in the format {"data":"filenames":["file1.xlsx","file2.xlsx", ...]} This is a POST request but is a destructive ac...
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async def deep_into(url, _list, get): """Test for getting references. Used for raw scan.""" try: resp = await get(url) new_resp = resp if "uri" in new_resp: new_resp["uri"] = remove_all_ip_occurs(resp["uri"]) if "id" in new_resp and new_resp["id"] == "/gateway/uuid": ...
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def get_param_server_cache(): """ Get a handle on the client-wide parameter server cache """ global _param_server_cache if _param_server_cache is None: _param_server_cache = ParamServerCache() return _param_server_cache
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def sanitize (s): """ Removes HTML tags, replaces HTML entities and unescapes the text so that only human generated content remains. """ s = preserve_quotes(s) s = preserve_code(s) s = replace_newlines(s) s = remove_meta(s) return unescape(s)
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def get_auth_id_from_user_id(user_id): """Returns the auth ID associated with the given user ID. Args: user_id: str. The auth ID. Returns: str|None. The user ID associated with the given auth ID, or None if no association exists. """ return platform_auth_services.get_auth_i...
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def make_property(name, bit, size=1, type=bool, var="flags"): """Helper function for make_struct which defines properties based on bit fields. This is called automatically for "flags" when passing a list of flags to make_struct, but can also be added to init_exec to handle flags in other variables if n...
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def get_southwest_ray(bitboard: np.uint64, from_square: int) -> np.uint64: """ Returns a bitboard of southwest sliding piece attacked squares on an otherwise empty board :param bitboard: The bitboard representing the southwest ray sliding attacks from `square` :param from_square: The square from a south...
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from .inspection import PACKAGE_NAME import copy def sanitize_deps(deps_dict): """ Helper function that takes the output of `notebook_path_to_dependencies` or `simple_import_search` and turns normalizes the import names to be synonymous with their conda/pip names Parameters ---------- dep...
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def register(): """Register a user: produce form and handle form submission.""" if request.method == "POST": username = request.form.get("username") password = request.form.get("password") user = User.register(username, password) db.session.add(user) db.session.commit() ...
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