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def rhand (x,y,z,iopt,parmod,exname,inname): """ Calculates the components of the right hand side vector in the geomagnetic field line equation (a subsidiary subroutine for the subroutine step) :param x,y,z: :param iopt: :param parmod: :param exname: name of the subroutine for the external...
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def unique_slug_generator_by_email(instance, new_slug=None): """ This is for a Django project and it assumes your instance has a model with a slug field and a title character (char) field. """ slug = new_slug if new_slug is not None else slugify(instance.email) Klass = instance.__class__ qs_...
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import logging def register_provider(price_core_min=1): """Register Provider""" mine(1) web3.eth.defaultAccount = accounts[0] prices = [price_core_min, price_data_transfer, price_storage, price_cache] tx = config.ebb.registerProvider( GPG_FINGERPRINT, provider_email, federa...
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from typing import Callable def get_signature_and_params(func: Callable): """Get the parameters and signature from a coroutine. func: Callable The coroutine from whom the information should be extracted. Returns ------- Tuple[List[Union[:class:`str`, :class:`inspect.Parameter`]]] ...
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def quadratic_formula(polynomial): """ input is single-variable polynomial of degree 2 returns zeros """ if len(polynomial.term_matrix) == 3: if polynomial.term_matrix[2][1] == 1: a, b = polynomial.term_matrix[1][0], polynomial.term_matrix[2][0] return 0, -b/a ...
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def handle_domain_deletion_commands(client: Client, demisto_args: dict) -> str: """ Removes domains from the inbound blacklisted list. :type client: ``Client`` :param client: Client to use. :type demisto_args: ``dict`` :param demisto_args: The demisto arguments. :...
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def create_l2_lag_interface(name, phys_ports, lacp_mode="passive", mc_lag=False, fallback_enabled=False, vlan_ids_list=[], desc=None, admin_state="up", **kwargs): """ Perform a POST call to create a Port table entry for L2 LAG interface. :param name: Alphanumeric name of LAG Por...
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import argparse def main_args_parser() -> argparse.Namespace: """ Implements an easy user-friendly command-line interface. It creates three main subparser (classify, train, eval) and add the appropriated arguments for each subparser. Returns ------- args: argparse.Namespace input argum...
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def get_train_image_matrices(folder_name, num_images=4): """Gets image matrices for training images. :param folder_name: String with name of training image folder in input_data/train_images directory path. :param num_images: Integer with number of images. :return: Matrices from training images....
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import torch def to_chainer_device(device): """Create a chainer device from a given torch device. Args: device (torch.device): Device to be converted. Returns: A ``chainer.device`` object corresponding to the given input. """ if not isinstance(device, torch.device): raise...
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def decode_region(code): """ Returns the region name for the given region code. For example: decode_region("be") => "Belgium". """ for tag, (language, region, iso639, iso3166) in LANGUAGE_REGION.iteritems(): if iso3166 == code.upper(): return region
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import zipfile import os def unzip_whatsapp_file(whatsapp_file): """ unzips a whatsapp .zip file and returns the path of the _chat.txt file that was extracted from the zip Parameters ---------- whatsapp_file: str path to a .zip file with the exported data from Whatsapp. Returns -...
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def neighbourhood_peaks(signal, n=10): """Computes the number of peaks from a defined neighbourhood of the signal. Reference: Christ, M., Braun, N., Neuffer, J. and Kempa-Liehr A.W. (2018). Time Series FeatuRe Extraction on basis of Scalable Hypothesis tests (tsfresh -- A Python package). Neurocomputing 3...
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def check_success(env, policy, act_noise_pct, render=False): """Tests whether a given policy solves an environment Args: env (metaworld.envs.MujocoEnv): Environment to test policy (metaworld.policies.policies.Policy): Policy that's supposed to succeed in env act_noise_pct (fl...
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import glob def import_data(file_regex, index_col_val=None, parse_dates=None, date_format=None): """ takes in a regular expression describing the filepath to the data files and returns a pandas dataFrame Usage1: var_name = import_data.import_data("./hackat...
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def shift_num_right_by(num: int, digits: int) -> int: """Shift a number to the right by discarding some digits We actually use string conversion here since division can provide wrong results due to precision errors for very big numbers. e.g.: 6150000000000000000000000000000000000000000000000 // 1e27 ...
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def index_handler(request): """ List latest 6 articles, or post a new article. """ if request.method == 'GET': return get_article_list(request) elif request.method == 'POST': return post_article(request)
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def getRawOutput(seqs, tmpfile, command, func): """ Returns output from a given subprocess command that is run iteratively on a given sequence list. It writes to a temporary file on the disk that should be specified. Also, a text processing function can be passed that takes the command line program'...
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import sys def is_windows() -> bool: """ Returns True if the current system is Windows. Returns False otherwise. """ return sys.platform == "win32"
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import os import multiprocessing def hillis_steeles_scan_inclusive_parallel(inp_list): """ Takes in a list, performs hillis-steeles inclusive scan parallelly, returns a shared memory array with the results input: inp_list, 1D list of n elements. returns: 1D Array, newArr of n elements. """ numProcessors = os.cp...
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import math import os def confusion_matrices(prediction, matrix=False, save=False, OutputPath=None, name=None): """ This function plot the confusion matrix at every level of the classification tree. """ cnf_matrix_level_1 = confusion_matrix(prediction['label_level_1'].values,prediction['...
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import numpy def back_propogation(weights, aa, zz, y1hot, lam=0.0): """Perform a back propogation step Args: weights (``list`` of numpy.ndarray): weights between each layer aa (``list`` of numpy.ndarray): activation of nodes for each layer. The last item in the list is the hypothesis. ...
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async def get_reverse_objects_topranked_for_lst(entities): """ get pairs that point to the given entity as the primary property primary properties are those with the highest rank per property see https://www.wikidata.org/wiki/Help:Ranking """ # some lookups just take too long, so we remove them...
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import stat def compute_confidence_interval(data,confidence=0.95): """ Function to determine the confidence interval :param data: input data :param confidence: confidence level :return: confidence interval """ a = 1.0 * np.array(data) n = len(a) se = stat.sem(a...
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def adjacent_powerset(iterable): """ Returns every combination of elements in an iterable where elements remain ordered and adjacent. For example, adjacent_powerset('ABCD') returns ['A', 'AB', 'ABC', 'ABCD', 'B', 'BC', 'BCD', 'C', 'CD', 'D'] Args: iterable: an iterable Returns: a li...
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from typing import Iterator from typing import Counter import tqdm def export_ngrams( docs: Iterator[str], nlp: spacy.language.Language, n: str, patterns=False ) -> Counter: """ Extracts n-gram frequencies of a series of documents Parameters ---------- docs : Iterator[str] An iterator...
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import argparse def getArguments(): """ Gets the name of the gameFile. :return: The arguments provided by the user """ parser = argparse.ArgumentParser() parser.add_argument('gameFile', help='The ini formatted file with the game configuration') return parser.parse_args()
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import torch def solve2D_system( pde_system, conditions, xy_min=None, xy_max=None, single_net=None, nets=None, train_generator=None, shuffle=True, valid_generator=None, optimizer=None, criterion=None, additional_loss_term=None, batch_size=16, max_epochs=1000, monitor=None, retu...
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def model_criterion(preds, labels): """ Function: Model criterion to train the model """ loss = nn.CrossEntropyLoss() return loss(preds, labels)
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def get_dbmapping(syn: Synapse, project_id: str) -> dict: """Gets database mapping information Args: syn: Synapse connection project_id: Project id where new data lives Returns: {'synid': database mapping syn id, 'df': database mapping pd.DataFrame} """ project_ent =...
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def end_position(variant_obj): """Calculate end position for a variant.""" alt_bases = len(variant_obj['alternative']) num_bases = max(len(variant_obj['reference']), alt_bases) return variant_obj['position'] + (num_bases - 1)
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def cast_to_server(server_params, topic, msg): """ Invoke a remote method that does not return anything """ return _get_impl().cast_to_server(cfg.CONF, server_params, topic, msg)
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def get_classification_systems(): """Retrieve all classification systems available in service.""" system = db.session.query(LucClassificationSystem).all() return ClassificationSystemSchema().dump(system, many=True)
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def read_annotations(filename, tagset, labeled): """ Read tsv data and return sentences and [word, tag, sentenceID, filename] list """ with open(filename, encoding="utf-8") as f: sentence = [] sentence.append(["[CLS]", -100, -1, -1, None]) sentences = [] sentenceID=0 for line in f: if len(line) > 0: ...
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def find_rmse(data_1, data_2, ax=0): """ Finds RMSE between data_1 and data_2 Inputs ------ data_1 (np.array) data_2 (np.array) ax (int) The axis (or axes) to mean over Outpts ------ (int) RMSE between data_1 and data_2 """ return np.sqrt(...
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def validate_tag_update(update): """ Property: ResourceUpdateConstraint.TagUpdateOnProvisionedProduct """ valid_tag_update_values = [ "ALLOWED", "NOT_ALLOWED", ] if update not in valid_tag_update_values: raise ValueError("{} is not a valid tag update value".format(update)...
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def bollinger_band(df: pd.DataFrame, window: int = 20, window_dev: int = 2) -> pd.DataFrame: """Implementation of bollinger band.""" df_with_signals = df.copy() typical_price = (df["close"] + df["low"] + df["high"]) / 3 df_with_signals["typical_price"] = typical_price std_dev = df_with_signals["typi...
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def close_corner_contour(contour: np.ndarray, shape: tuple) -> np.ndarray: """Check if contours are in the corner, and close them if needed. Contours which cover a corner cannot be closed by joining the first and last element, because some of the area is missed. This algorithm adds the corner point to ...
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import os import argparse def writable_prefix(prefix): """ Checks if this prefix is writable and exists. :param prefix: str - prefix to check :return: str - prefix """ directory = os.path.dirname(prefix) if not os.path.exists(directory): error = "Output directory %s does not exist ...
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def simulate_spatial_ratiometric_reading( do, temperature, sealed_patch_do=0, sealed_patch_kwargs={}, unsealed_patch_kwargs={} ): """ Simulate a "spatial ratiometric" reading using a sealed DO patch as the ratiometric reference Args: do: Dissolved Oxygen partial pressure in mmHg in the unsealed pat...
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import json async def create_pool(uri, **kwargs) -> asyncpg.pool.Pool: """Creates a connection pool to the specified PostgreSQL server""" def _encode_jsonb(value): return b'\x01' + json.dumps(value).encode('utf-8') def _decode_jsonb(value): return json.loads(value[1:].decode('utf-8')) ...
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from .interactive._iplot_state import iplot_state from ._state_visualization import plot_state as plot from .interactive._iplot_state import iplot_state from ._state_visualization import plot_state as plot def plot_state(rho, method='city', filename=None, options=None, mode=None, show=False): """Pl...
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from datetime import datetime def tick_format(ticktime): """ Format the tick date/time """ datetime_object = datetime.strptime(ticktime, '%Y-%m-%dT%H:%M:%S.%fZ') return datetime_object.strftime("%H:%M:%S UTC %A %d %B")
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def add_finite_filter_to_scorer(score_func): """Takes a scorer and returns a scorer that ignores NA / infinite elements in y_true. sklearn scorers (and others) don't handle arrays with 0 length. In that case, return None :param score_func: function that maps two arrays to a number. E.g. (y_true, y_pred) -...
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import gc def lsst_fit(lc, grp): """Take full mock LC and SDSS cadence to find best_fit params. Args: lc: Kali LC object, full mock LC. grp: HDF5 group storing the MCMC chains. """ best_param = [] # store best-fit params ref_ls = [] task = kali.carma.CARMATask(1, 0, nste...
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def getStudioModeStatus(): """ Indicates if Studio Mode is currently enabled. """ return __createJSON("GetStudioModeStatus", {})
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from typing import Tuple def calc_long_short_prec( pred: pd.Series, label: pd.Series, date_col="datetime", quantile: float = 0.2, dropna=False, is_alpha=False ) -> Tuple[pd.Series, pd.Series]: """ calculate the precision for long and short operation :param pred/label: index is **pd.MultiIndex**, ind...
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def prepare_tuple_argument(arg, n, arg_name, validate_args=False): """Helper which processes `Tensor`s to tuples in standard form.""" arg_size = ps.size(arg) arg_size_ = tf.get_static_value(arg_size) assertions = [] if arg_size_ is not None: if arg_size_ not in (1, n): raise ValueError('The size of ...
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import zipfile def isValidLibreOfficeFile(file_path): """ Return true if given file is valid LibreOffice ods file containing manifest.xml, false otherwise. """ try: with zipfile.ZipFile(file_path, 'a') as open_document: open_document.open(DOCUMENT_MANIFEST_PATH) return ...
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def mean_absolute_percentage_error(y_true, y_pred, zeros_strategy='mae'): """ Similar to sklearn https://scikit-learn.org/stable/modules/generated/sklearn.metrics.mean_absolute_error.html with options for behaviour for around zeros :param y_true: :param y_pred: :param zeros_strategy: :return...
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import json def __get_pretty_body__(headers, body): """ Return a pretty printed body using the Content-Type header information :param headers: Headers for the request/response (dict) :param body: Body to pretty print (string) :return: Body pretty printed (string) """ if HEADER_CONTENT_TYP...
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def bell_sigmoid(ds, a=None, bc=None, d=None, inplace=True): """ Apply a fuzzy membership function to data using bell-shaped sigmoidal function. Requires a low left inflection (a), a mid-point (bc), and a low right inflection (d) point to set the bounds in which to rescale all values to. Value...
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import os import logging def post_binary(binary, byte_start, byte_data): """Accept a binary file or packet. binary = binary to get the file to write to from byte_start = offset from beginning of file to begin writing byte_data = an iterable that contains data """ result = True ...
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def get_composite(name, error=DontCatchError, error_message=None, identifier=None, component_category='unknown'): """ Gets a Composite Singleton :param: - `name`: name to register singleton (clients that want same singleton, use same name) - `error`: exception to catch (``DontC...
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def is_list_of_float(value): """ Check if an object is a liat of floats :param value: :return: """ return bool(value) and isinstance(value, list) and all(isinstance(elem, float) for elem in value)
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def get_example_params(example_index): """ Gets used variables for almost all visualizations, like the image, model etc. Args: example_index (int): Image id to use from examples returns: original_image (numpy arr): Original image read from the file prep_img (numpy_arr): Proce...
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from geometrylab.geometry import Polyline def bezier_curve(points, nTimes=500, is_poly=False, is_crv=False): """ Given a set of control points, return the bezier curve defined by the control points. points should be a list of lists, or list of tuples such as [ [1,1], ...
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import functools def decorator_with_keywords(func=None, **dkws): # NOTE: ONLY ACCEPTS KW ARGS """ A decorator that can handle optional keyword arguments. When the decorator is called with no optional arguments like this: @decorator def function ... The function is passed as the first a...
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from datetime import datetime def parse_line(line): """ Extract all the data we want from each line. :param line: A line from our log files. :return: The data we have extracted. """ time = line.split()[0].strip() response = line.split(' :') message = response[len(response) - 1].strip...
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def semi_lagrangian(field: GridType, velocity: Field, dt: float, integrator=euler) -> GridType: """ Semi-Lagrangian advection with simple backward lookup. This method samples the `velocity` at the grid points of `field` to determine the lo...
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def pptx_to_bbox(left, top, width, height): """ Convert matplotlib bounding box format to pptx format Parameters ---------- left : float top : float width : float height : float Returns ------- bottom, left, width, height """ return top-height, left, width, height
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from typing import Counter def reindex(labels): """ Given a list of labels, reindex them as integers from 1 to n_labels Also orders them in nonincreasing order of prevalence """ old2new = {} j = 1 for i, _ in Counter(labels).most_common(): old2new[i] = j j += 1 old2newf...
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def _validate_vg(module, vg): """ Check the current state of volume group. :param module: Ansible module argument spec. :param vg: Volume Group name. :return: True (VG in varyon state) or False (VG in varyoff state) or None (VG does not exist), message. """ lsvg_cmd = module.ge...
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from typing import List def news_items(news_index_page) -> List[News]: """Fixture providing 10 News objects attached to news_index_page """ rv = [] for _ in range(0, 10): p = _create_news_page(f"Test News Page {_}", news_index_page) rv.append(p) return rv
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def is_annotated(procedure): """Return True if procedure is annotated.""" procedure = annotatable(procedure) try: ann = procedure.func_annotations return ann.are_for(procedure) and bool(ann) except AttributeError: return False
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import io import os def read_matrix(name): """\ Helper function to read a matrix from /ref_matrix. The file extension .txt is added automatically. :return: A tuple of bytearrays """ matrix = [] with io.open(os.path.join(os.path.dirname(__file__), 'ref_matrix/{0}.txt'.format(name)), 'rt') ...
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def _enable_disable_pim_config(tgen, topo, input_dict, router, build=False): """ Helper API to enable or disable pim on interfaces Parameters ---------- * `tgen` : Topogen object * `topo` : json file data * `input_dict` : Input dict data, required when configuring from testcase * `route...
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from typing import Union def linear_interpolation_formula( left: Union[float, np.array], right: Union[float, np.array], gamma: Union[float, np.array], ) -> Union[float, np.array]: """ Compute the linear interpolation weighted by gamma on each point of two same shape array. """ return gamma...
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def estimate_visib_mask_est(d_test, d_est, visib_gt, delta, visib_mode='bop19'): """Estimates a mask of the visible object surface in the estimated pose. For an explanation of why the visibility mask is calculated differently for the estimated and the ground-truth pose, see equation (14) and related text in Ho...
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import itertools def combine_assertions(input_filename, output_filename): """ Take in a tab-separated, sorted "CSV" files, indicated by `input_filename`, that should be grouped together into assertions. Output a msgpack stream of assertions the file indicated by `output_filename`. The input f...
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import os def find_testclass(package, program, testclass, file_required=False): """Find the relative path of the test-class file""" name = f'{program.lower()}.clas.testclasses.abap' for root, _, files in os.walk('.'): if name in files: return os.path.join(root, name)[2:] if file_...
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def sanitize_mobile_number(number): """Add country code and strip leading zeroes from the phone number.""" return "254" + str(number).lstrip("0")
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def fakebaraxis(ticks, painter=fakebarpainter(),*args, **kwargs): """Return a PyX linear axis that can be used to make fake bar plots. Use "keyticks" to create the ticks expected by this function.""" return axis.linear( min=-0.75, max=len(ticks)-0.25, parter=None, manualtick...
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import csv def get_score_sent_pairs_from_tsv(tsv_filepath, encoding="ISO-8859-1"): """expects tokenized sentences in tsv file!""" with open(tsv_filepath, encoding=encoding) as tsvfile: reader = csv.reader(tsvfile, delimiter='\t') score_sent_pairs = [[float(row[0]), row[1]] for row in reader] return scor...
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def test_timings_trie(port, individual_test_timings): """Breaks a test name into chunks by directory and puts the test time as a value in the lowest part, e.g. foo/bar/baz.html: 1ms foo/bar/baz1.html: 3ms becomes foo: { bar: { baz.html: 1, baz1.html: 3 } ...
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def prop_end(wf, **kwargs): """Set variables needed to properly conclude a propagation run. Parameters ---------- wf : obj The current WaveFront class object Returns ------- wf.wfarr : numpy ndarray Wavefront array sampling : float Sampling in meters Oth...
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def add_others_ta(df, close, fillna=False): """Add others analysis features to dataframe. Args: df (pandas.core.frame.DataFrame): Dataframe base. close (str): Name of 'close' column. fillna(bool): if True, fill nan values. Returns: pandas.core.frame.DataFrame: Dataframe wit...
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def _fixture_union(caller_module, name, fixtures, idstyle, scope="function", ids=fixture_alternative_to_str, unpack_into=None, autouse=False, **kwargs): """ Internal implementation for fixture_union :param caller_module: :param name: :param fixtures: :param idstyle: :para...
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def service_class(cls): """ A class decorator enabling the instances of the class to be used as a ``services``-provider in `JSONRpc Objects`_ and `BSONRpc Objects`_. Use decorators ``request``, ``notification``, ``rpc_request`` and ``rpc_notification`` to expose methods for the RPC peer node. ...
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def lightcurveplain(request, tcs_transient_objects_id): """lightcurveplain. Args: request: tcs_transient_objects_id: """ transient = get_object_or_404(TcsTransientObjects, pk=tcs_transient_objects_id) mjdLimit = 55347.0 # Hard wired to 31st May 2010 # 2012-07-18 KWS Changed this...
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def locate_address(ip_list, ip_attack): """ for each line in the file pointer define the ip ranges and country codes if the attacking ip is in between the range then return country code :param ip_list - list of ip address ranges and country code: :param ip_attack - attacking ip as an int...
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import scipy def invertnd(f, x, *other_vars, kind='linear', vectorized=False): """ Invert a multivariate function numerically Args: f: Function to invert x: Domain to invert the function on (range of inverted function) *other_vars: Domain to invert the function on (parameters of in...
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def most_mentioned(msgs, limit=20): """Top mentions by '@' references """ mentions = {} for m in msgs: for at in preproc.extract_ats_from_text(m['text']): mentions[at] = mentions[at] + 1 if at in mentions else 1 return sorted(mentions.items(), key=lambda x: x[1]...
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import string def is_valid_matlab_field_label(label): """ Check that passed string is a valid MATLAB field label """ if not label.startswith(tuple(string.ascii_letters)): return False VALID_CHARS = set(string.ascii_letters + string.digits + "_") return set(label).issubset(VALID_CHARS)
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def identity(n, dtype=DEFAULT_FLOAT_DTYPE): """ Returns the identity tensor. Args: n (int): Number of rows and columns in the output, must be larger than 0. dtype (Union[mstype.dtype, str], optional): Designated tensor dtype, can be in format of np.float32, or `float32`. Default...
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def _chain_connectivity(edges, chains): """Returns chain connectivity treated as clustered entities represented by nodes""" chain_connectivity = np.empty((len(edges), 2), dtype=np.int64) starts = defaultdict(list) for section_index, chain in enumerate(chains): starts[chain[0][0]].append(section...
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def reading2celsius(self, reading): """ Converts sensor reading to celsius """ celsius = reading / 50 - 273.15 return celsius
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import sqlite3 def evaluate_csp(website_id, test_weights): """ Checks: no fallback to default: base-uri form-action frame-ancestors report-to/uri sandbox upgrade-insecure-requests ...
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def get_analysis_alias_from_metadata(eload_cfg): """ Returns analysis alias only if we find a metadata spreadsheet and it has exactly one analysis. Otherwise provides an error message and raise an error. """ metadata_spreadsheet = eload_cfg.query('submission', 'metadata_spreadsheet') if metadata...
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from imcsdk.mometa.bios.BiosProfileManagement import BiosProfileManagement from imcsdk.mometa.bios.BiosProfileManagement import \ def bios_profile_backup_running(handle, server_id=1, **kwargs): """ Backups up the running configuration of various bios tokens to create a 'cisco_backup_profile'. Will ove...
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def variantCombinations(items): """ Calculates variant combinations for given list of options. Each item in the items list represents unique value with it's variants. :param list items: list of values to be combined >>> c = variantCombinations([["1.1", "1.2"], ["2.1", "2.2"], ["3.1", "3.2"]]) >>> ...
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import regex def bm_regex(regex_string): """Compile best multiline regex.""" return regex.compile(regex_string, regex.B | regex.M)
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def test_enable_8021q_1(monkeypatch): """Verify that enable_802q_1 function return exception when 802.1q is not supported by current os. """ def mockreturn(command): return CmdStatus("", "", 0) # monkeypatch.setattr(CLISSHNetNS, 'exec_command', mockreturn) lh = GenericLinuxHost(LH_CFG, OPTS...
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def qlearning_dataset(env, dataset=None, terminate_on_end=False, **kwargs): """ Returns datasets formatted for use by standard Q-learning algorithms, with observations, actions, next_observations, rewards, and a terminal flag. Args: env: An OfflineEnv object. dataset: An optional da...
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import torch def build_save_dataset(corpus_type, fields, opt): # corpus_type: train or valid """ Building and saving the dataset """ assert corpus_type in ["train", "valid"] # Judging whether it is train or valid if corpus_type == "train": src_corpus = opt.train_src # 获取...
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def gaussian_filter(image, sigma): """Returns image filtered with a gaussian function of variance sigma**2""" i, j = np.meshgrid(np.arange(image.shape[0]), np.arange(image.shape[1]), indexing='ij') mu = (int(image.shape[0]/2.0), int(image.shape[1]/2....
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def get_lattice_points(strand): """ 格子点の情報を取得 @param ストランドの格子点の対 @return ストランドの格子点の始点と終点 """ strand_list = eval(strand) strand_from = strand_list[0] strand_to = strand_list[1] return strand_from, strand_to
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def while_(condition): """ A while loop that can be used in a workchain outline. Use as:: while_(cls.conditional)( cls.step1, cls.step2 ) Each step can, of course, also be any valid workchain step e.g. conditional. :param condition: The workchain method that will retu...
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def new(init=None): """Return a new Whirlpool object. An optional string argument may be provided; if present, this string will be automatically hashed.""" return Whirlpool(init)
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def extract_bcr(tab, rep_col='CDR3_aa'): """ Extract BCR repertorie for each patient Args: tab: data table from TRUST BCR outputs rep_col: 'CDR3_aa' or 'complete_CDR3_sequences' or a list of keys Output: a Series vector containing lists of BCR CDR3 sequences """ ta...
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