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from typing import Union from typing import Tuple from typing import Dict from typing import Any import io def format_result(result: Union[Pose, PackedPose]) -> Tuple[str, Dict[Any, Any]]: """ :param: result: Pose or PackedPose object. :return: tuple of (pdb_string, metadata) Given a `Pose` or `Packed...
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def str_array( listString): """ Becase the way tha Python prints an array is different from CPLEX, this function goes the proper CPLEX writing of Arrays :param listString: A list of values :type listString: List[] :returns: The String printing of the array, in CPLEX format :rtype: String """ ...
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def read_gene_annos(phenoFile): """Read in gene-based metadata from an HDF5 file Args: phenoFile (str): filename for the relevant HDF5 file Returns: dictionary with feature annotations """ fpheno = h5py.File(phenoFile,'r') # Feature annotations: geneAnn = {} for key...
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from typing import Optional import binascii def hex_xformat_decode(s: str) -> Optional[bytes]: """ Reverse :func:`hex_xformat_encode`. The parameter is a hex-encoded BLOB like .. code-block:: none "X'CDE7A24B1A9DBA3148BCB7A0B9DA5BB6A424486C'" Original purpose and notes: - SPECIAL ...
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def threshold(data, direction): """ Find a suitable threshold value which maximizes explained variance of the data projected onto direction. NOTE: the chosen hyperplane would be described mathematically as $ x \dot direction = threshold $. """ projected_data = np.inner(data, direction) sorted_x ...
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def StrType_any(*x): """ Ignores all parameters to return a StrType """ return StrType()
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def height(tree): """Return the height of tree.""" if tree.is_empty(): return 0 else: return 1+ max(height(tree.left_child()),\ height(tree.right_child()))
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def applyTelluric(model, tell_alpha=1.0, airmass=1.5, pwv=0.5): """ Apply the telluric model on the science model. Parameters ---------- model : model object BT Settl model alpha : float telluric scaling factor (the power on the flux) Returns ------- model : model object BT Settl model times...
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def max_power_rule(mod, g, tmp): """ **Constraint Name**: DAC_Max_Power_Constraint **Enforced Over**: DAC_OPR_TMPS Power consumption cannot exceed capacity. """ return ( mod.DAC_Consume_Power_MW[g, tmp] <= mod.Capacity_MW[g, mod.period[tmp]] * mod.Availability_Derate[g, tmp] ...
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def check_archs( copied_libs, # type: Mapping[Text, Mapping[Text, Text]] require_archs=(), # type: Union[Text, Iterable[Text]] stop_fast=False, # type: bool ): # type: (...) -> Set[Union[Tuple[Text, FrozenSet[Text]], Tuple[Text, Text, FrozenSet[Text]]]] # noqa: E501 """Check compatibility of ar...
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def create_data_table(headers, columns, match_tol=20) -> pd.DataFrame: """Based on headers and column data, create the data table.""" # Store the bottom y values of all of the row headers header_tops = np.array([h.top for h in headers]) # Set up the grid: nrows by ncols nrows = len(headers) nc...
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def interp2d_vis(model, model_lsts, model_freqs, data_lsts, data_freqs, flags=None, kind='cubic', flag_extrapolate=True, medfilt_flagged=True, medfilt_window=(3, 7), fill_value=None): """ Interpolate complex visibility model onto the time & frequency basis of a data visibil...
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def eps_divide(n, d, eps=K.epsilon()): """ perform division using eps """ return (n + eps) / (d + eps)
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import requests def get_mc_uuid(username): """Gets the Minecraft UUID for a username""" url = f"https://api.mojang.com/users/profiles/minecraft/{username}" res = requests.get(url) if res.status_code == 204: raise ValueError("Users must have a valid MC username") else: return res.js...
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def api(default=None, api=None, **kwargs): """Returns the api instance in which this API function is being ran""" return api or default
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def parse_json(data): """Parses the PupleAir JSON file, returning a Sensors protobuf.""" channel_a = [] channel_b = {} for result in data["results"]: if "ParentID" in result: channel_b[result["ParentID"]] = result else: channel_a.append(result) sensors = list(...
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import logging import traceback def asynchronize_tornado_handler(handler_class): """ A helper function to turn a blocking handler into an async call :param handler_class: a tornado RequestHandler which should be made asynchronus :return: a class which does the same work on a threadpool """ cl...
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def convert_single_example(ex_index, example: InputExample, tokenizer, label_map, dict_builder=None): """Converts a single `InputExample` into a single `InputFeatures`.""" # label_map = {"B": 0, "M": 1, "E": 2, "S": 3} # tokens_raw = tokenizer.tokenize(example.text) tokens_ra...
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async def converter_self_interaction_target(client, interaction_event): """ Internal converter for returning the received interaction event's target. Applicable for context application commands. This function is a coroutine. Parameters ---------- client : ``Client`` The cli...
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from typing import List def publication_pages(publication_index_page) -> List[PublicationPage]: """Fixture providing 10 PublicationPage objects attached to publication_index_page""" rv = [] for _ in range(0, 10): p = _create_publication_page( f"Test Publication Page {_}", publication_i...
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from typing import List def rp_completion( rp2_metnet, sink, rp2paths_compounds, rp2paths_pathways, cache: rrCache = None, upper_flux_bound: float = default_upper_flux_bound, lower_flux_bound: float = default_lower_flux_bound, max_subpaths_filter: int = default_max_subpaths_filter, ...
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import torch def wrap(func, *args, unsqueeze=False): """ Wrap a torch function so it can be called with NumPy arrays. Input and return types are seamlessly converted. """ args = list(args) for i, arg in enumerate(args): if type(arg) == np.ndarray: args[i] = torch.from_nump...
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def STOCHF(data, fastk_period=5, fastd_period=3, fastd_ma_type=0): """ Stochastic %F :param pd.DataFrame data: pandas DataFrame with open, high, low, close data :param int fastk_period: period used for K fast indicator calculation :param int fastd_period: period used for D fast indicator calculatio...
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def playerid_reverse_lookup(player_ids, key_type=None): """Retrieve a table of player information given a list of player ids :param player_ids: list of player ids :type player_ids: list :param key_type: name of the key type being looked up (one of "mlbam", "retro", "bbref", or "fangraphs") :type ke...
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def get_delta_z(z, rest_ghz, ghz=None): """ Take a measured GHz value, and calculates the restframe GHz value based on the given z of the matched galaxy :param z: :param ghz: :return: """ # First step is to convert to nm rom rest frame GHz set_zs = [] for key, values in transitions....
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def hist_orientation(qval, dt): """ provided with quats, and time spent* in the direction defined by quat produces grouped by ra, dec and roll quaternions and corresponding time, spent in quats params: qval a set of quats stored in scipy.spatial.transfrom.Rotation class params: dt corresponding to...
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def proclamadelcaucacom_story(soup): """ Function to pull the information we want from Proclamadelcauca.com stories :param soup: BeautifulSoup object, ready to parse """ hold_dict = {} #text try: article_body = soup.find('div', attrs={"class": "single-entradaContent"}) mainte...
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def asarray_fft(x, inverse): """Recursive implementation of the 1D Cooley-Tukey FFT using np asarray to prevent copying. Parameters: x (array): the discrete amplitudes to transform. inverse (bool): perform the inverse fft if true. Returns: x (array): the amplitudes of the origin...
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import jinja2 def wrap_locale_context(func): """Wraps the func with the current locale.""" @jinja2.contextfilter def _locale_filter(ctx, value, *args, **kwargs): doc = ctx['doc'] if not kwargs.get('locale', None): kwargs['locale'] = str(doc.locale) return func(value, *...
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from numpy import loadtxt from scipy.interpolate import UnivariateSpline def mu_Xe(keV=12): """Returns inverse 1/e penetration depth [mm-1 atm-1] of Xe given the x-ray energy in keV. The transmission through a 3-mm thick slab of Xe at 6.17 atm (76 psi) was calculated every 100 eV over an energy range ...
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import hashlib def file_md5(input_file): """ :param input_file: Path to input file. :type input_file: str :return: Returns the encoded data in the inputted file in hexadecimal format. """ with open(input_file, 'rb') as f: data = f.read() return hashlib.md5(data).hexdigest()
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from typing import Dict def message_args() -> Dict[str, str]: """A formatted message.""" return {"subject": "Test message", "message": "This is a test message"}
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def to_drive_type(value): """Convert value to DriveType enum.""" if isinstance(value, DriveType): return value.value sanitized = str(value).upper().strip().replace(" ", "_") try: return DriveType[sanitized].value except KeyError as err: raise ValueError(f"Unknown drive type:...
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def upload_authorized_key(host, port, filepath): """UPLOAD (key) upload_authorized_key""" params = {'method': 'upload_authorized_key'} files = [('key', filepath, file_get_contents(filepath))] return _check(https.client.https_post(host, port, '/', params, files=files))
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def thermalize_cutoff(localEnergies, smoothing_window, tol): """Return position where system is thermalized according to some tolerance tol, based on the derivative of the smoothed local energies """ mean = np.mean(localEnergies) smoothLocalEnergies = smoothing(localEnergies, smoothing_window) ...
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def annualize_metric(metric: float, holding_periods: int = 1) -> float: """ Annualize metric of arbitrary periodicity :param metric: Metric to analyze :param holding_periods: :return: Annualized metric """ days_per_year = 365 trans_ratio = days_per_year / holding_periods return (1...
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def get_latest_tag(): """ Find the value of the latest tag for the Adafruit CircuitPython library bundle. :return: The most recent tag value for the project. """ global LATEST_BUNDLE_VERSION # pylint: disable=global-statement if LATEST_BUNDLE_VERSION == "": LATEST_BUNDLE_VERSION = g...
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def read_gold_conll2003(gold_file): """ Reads in the gold annotation from a file in CoNLL 2003 format. Returns: - gold: a String list containing one sequence tag per token. E.g. [B-Kochschritt, L-Kochschritt, U-Zutat, O] - lines: a list list containing the original line spli...
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import functools def translate_nova_exception(method): """Transforms a cinder exception but keeps its traceback intact.""" @functools.wraps(method) def wrapper(self, ctx, *args, **kwargs): try: res = method(self, ctx, *args, **kwargs) except (nova_exceptions.ConnectionRefused, ...
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def _update_form(form): """ """ if not form.text(): return form.setStyleSheet(error_css) return form.setStyleSheet(success_css)
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import torch from torch_adapter import TorchAdapter from openvino.inference_engine import IEPlugin from openvino_adapter import OpenvinoAdapter from torch_adapter import TorchAdapter import importlib def create_adapter(openvino, cpu_only, force_torch, use_myriad): """Create the best adapter based on constraints p...
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def _make_ecg(inst, start, stop, reject_by_annotation=False, verbose=None): """Create ECG signal from cross channel average.""" if not any(c in inst for c in ['mag', 'grad']): raise ValueError('Unable to generate artificial ECG channel') for ch in ['mag', 'grad']: if ch in inst: ...
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def lorentzian(freq, freq0, area, hwhm, phase, offset, drift): """ Lorentzian line-shape function Parameters ---------- freq : float or float array The frequencies for which the function is evaluated freq0 : float The center frequency of the function area : float hwhm: float ...
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def findTilt(root): """ :type root: TreeNode :rtype: int """ if root is None: return 0 return findTilt_helper(root)[1]
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def generate_report(): """ Get pylint analization report and write it to file """ files = get_files_to_check() dir_path = create_report_dir() file_path = create_report_file(dir_path) config_opts = get_config_opts() pylint_opts = '--load-plugins pylint_flask' + config_opts pylint_stdo...
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def make_trampoline(func_name): """ Create a main function that calls another function """ mod = ir.Module('main') main = ir.Procedure('main') mod.add_function(main) entry = ir.Block('entry') main.add_block(entry) main.entry = entry entry.add_instruction(ir.ProcedureCall(func_name, [])) ...
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def model_fields(dbo, baseuri=None): """Extract known fields from a BQ object, while removing any known from C{excluded_fields} @rtype: dict @return fields to be rendered in XML """ attrs = {} try: dbo_fields = dbo.xmlfields except AttributeError: # This occurs when the ...
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def get_bsj(seq, bsj): """Return transformed sequence of given BSJ""" return seq[bsj:] + seq[:bsj]
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from typing import Dict import warnings import math def sample(problem: Dict, N: int, calc_second_order: bool = True, skip_values: int = 0): """Generates model inputs using Saltelli's extension of the Sobol' sequence. Returns a NumPy matrix containing the model inputs using Saltelli's sampling ...
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def standardize(table, option): """ standardize Z = (X - mean) / (standard deviation) """ if option == 'table': mean = np.mean(table) std = np.std(table) t = [] for row in table: t_row = [] if option != 'table': mean = np.mean(row) std ...
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def raw_input_nonblock(): """ return result of raw_input if has keyboard input, otherwise return None """ if _IS_OS_WIN32: return _raw_input_nonblock_win32() else: raise NotImplementedError('Unsupported os.')
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def get_batch_hard(draw_batch_size,hard_batchs_size,semihard_batchs_size,easy_batchs_size,norm_batchs_size,network,dataset,nb_classes, margin): """ Create batch of APN "hard" triplets Arguments: draw_batch_size -- integer : number of initial randomly taken samples hard_batchs_size -- interger : sel...
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import math def sine( start, end, freq, amp: Numeric = 1, n_periods: Numeric = 1 ) -> TimeSerie: """ Generate a sine TimeSerie. """ index = pd.date_range(start=start, end=end, freq=freq) return TimeSerie( index=index, y_values=np.sin( np.linspace(0, 2 * math.pi * n_...
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def get_from_address(sending_profile, template_from_address): """Get campaign from address.""" # Get template display name if "<" in template_from_address: template_display = template_from_address.split("<")[0].strip() else: template_display = None # Get template sender template...
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import ctypes def is_dwm_compositing_enabled(): """Is Desktop Window Manager compositing (Aero) enabled. """ enabled = ctypes.c_bool() try: DwmIsCompositionEnabled = ctypes.windll.dwmapi.DwmIsCompositionEnabled except (AttributeError, WindowsError): # dwmapi or DwmIsCompositionEna...
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def fgsm(x, y_true, y_hat, epsilon=0.075): """Calculates the fast gradient sign method adversarial attack Following the FGSM algorithm, determines the gradient of the cost function wrt the input, then perturbs all the input in the direction that will cause the greatest error, with small magnitude. ...
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def tour_delete(request,id): """ delete tour depending on id """ success_message, error_message = None, None form = TourForm() tour = get_object_or_404(Tour, id=id) tours = Tour.objects.all() if request.method=="POST": tour.delete() success_message = "deleted tour" ...
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import random def d3(): """Simulate the roll of a 3 sided die""" return random.randint(1, 3)
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def _search_qr(model, identifier, session): """Search the database using a Query/Retrieve *Identifier* query. Parameters ---------- model : pydicom.uid.UID Either *Patient Root Query Retrieve Information Model* or *Study Root Query Retrieve Information Model* for C-FIND, C-GET or C-MOVE...
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def find_max_value(binary_tree): """This function takes a binary tree and returns the largest value of all the nodes in that tree with O(N) space and O(1) time using breadth first traversal while keeping track of the largest value thus far in the traversal """ root_node = [] rootnode.push(binar...
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def failed_jobs(username, root_wf_id, wf_id): """ Get a list of all failed jobs of the latest instance for a given workflow. """ dashboard = Dashboard(g.master_db_url, root_wf_id, wf_id) args = __get_datatables_args() total_count, filtered_count, failed_jobs_list = dashboard.get_failed_jobs( ...
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def get_vm_types(resources): """ Get all vm_types for a list of heat resources, do note that some of the values retrieved may be invalid """ vm_types = [] for v in resources.values(): vm_types.extend(list(get_vm_types_for_resource(v))) return set(vm_types)
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def interface_names(obj): """ Return: a list of interface names to which `obj' is conformant. The list begins with `obj' itself if it is an interface. Names are returned in depth-first order, left to right. """ return [o.__name__ for o in interfaces(obj)]
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import six def add_basic(token): """For use with Authorization headers, add "Basic ".""" if token: return (u"Basic " if isinstance(token, six.text_type) else b"Basic ") + token else: return token
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import json import requests def updateUser(token, leaderboard=None, showUsername=None, username=None): """ Update user account information. Parameters- token: Authentication token. leaderboard: True to show user's profit on leaderboard. showUsername: True to show the username on LN Marktes pu...
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def init_validator(required, cls, *additional_validators): """ Create an attrs validator based on the cls provided and required setting. :param bool required: whether the field is required in a given model. :param cls: the expected class type of object value. :return: attrs validator chained correct...
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def ShiftRight(x, **unused_kwargs): """Layer to shift the tensor to the right by padding on axis 1.""" if not isinstance(x, (list, tuple)): # non-chunked inputs pad_widths = [(0, 0)] * len(x.shape) pad_widths[1] = (1, 0) # Padding on axis=1 padded = np.pad(x, pad_widths, mode='constant') return pa...
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def empty_record(): """Create an empty record.""" record = dump_empty(Marc21RecordSchema) record["metadata"] = "<record> <leader>00000nam a2200000zca4500</leader></record>" record["is_published"] = False record["files"] = {"enabled": True} return record
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def illuminanceToPhotonPixelRate(illuminance, objective_numerical_aperture=1.0, illumination_wavelength=0.55e-6, camera_pixel_size=6.5e-6, objective_magnification=1, ...
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def stop_tuning(step): """ stop tuning the current step method """ if hasattr(step, 'tune'): step.tune = False elif hasattr(step, 'methods'): step.methods = [stop_tuning(s) for s in step.methods] return step
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import json def assemble_english(): """Assemble each statement into """ if request.method == 'OPTIONS': return {} response = request.body.read().decode('utf-8') body = json.loads(response) stmts_json = body.get('statements') stmts = stmts_from_json(stmts_json) sentences = {} fo...
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def schema_class(classname, schema, schemarepr=None, basename='SchemaBase'): """Generate code for a schema class Parameters ---------- classname : string The name of the class to generate schema : dict The dictionary defining the schema class basename : string (default: "SchemaB...
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import requests def orthology_events(ids='R-HSA-6799198,R-HSA-168256,R-HSA-168249', species='49633'): """ Reactome uses the set of manually curated human reactions to computationally infer reactions in twenty evolutionarily divergent eukaryotic species for which high-quality whole-genome sequence data...
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def judge(name): """ Return some sort of score for automatically ranking names based on all the features we can extract so far. I guess we'll just add the scores * weights up for now. """ score = 0 for scoreID, scorer, weight in weights: subscore = scorer(name) score += subs...
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import re def parse_year(inp, option='raise'): """ Attempt to parse a year out of a string. Parameters ---------- inp : str String from which year is to be parsed option : str Return option: - "bool" will return True if year is found, else False. - Return yea...
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def retry_import(e, **kwargs): """ When an exception occurs during channel/content import, if * there is an Internet connection error or timeout error, or HTTPError where the error code is one of the RETRY_STATUS_CODE, return return True to retry the file transfer * the file ...
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def cvCloneMat(*args): """cvCloneMat(CvMat mat) -> CvMat""" return _cv.cvCloneMat(*args)
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from typing import Callable import time def run_episode(kwargs) -> [Trajectory]: """ Runs a single episode and collects the trajectories of each agent """ total_controller_time = 0 env_dict: Callable = kwargs.get("env_dict") obs_builder = kwargs.get("obs_builder") controller_creator: Calla...
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def get_data(request: Request): """ Get the data page. Parameters ---------- request : Request The request object. Returns ------- HTMLResponse The data page. """ return templates.TemplateResponse("data.html", {"request": request})
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def remove_last_measurements(dag_circuit, perform_remove=True): """Removes all measurements that occur as the last operation on a given qubit for a DAG circuit. Measurements that are followed by additional gates are untouched. This operation is done in-place on the input DAG circuit if perform_pop=Tru...
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def J(*args, **kwargs): """Wrapper around jsonify that sets the Content-Type of the response to application/vnd.api+json. """ response = jsonify(*args, **kwargs) response.mimetype = "application/vnd.api+json" return response
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def is_gzipped(filename): """ Returns True if the target filename looks like a GZIP'd file. """ with open(filename, 'rb') as fh: return fh.read(2) == b'\x1f\x8b'
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def tag_helper(tag, items, locked=True, remove=False): """ Simple tag helper for editing a object. """ if not isinstance(items, list): items = [items] data = {} if not remove: for i, item in enumerate(items): tagname = '%s[%s].tag.tag' % (tag, i) data[tagname] = i...
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def get_keys_from_file(csv): """Extract the credentials from a csv file.""" lines = tuple(open(csv, 'r')) creds = lines[1] access = creds.split(',')[2] secret = creds.split(',')[3] return access, secret
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import pkg_resources import json def fix_model(project, models, invert=False): """Fix model name where file attribute is different from values accepted by facets >>> fix_model('CMIP5', ['CESM1(BGC)', 'CESM1-BGC']) ['CESM1(BGC)', 'CESM1(BGC)'] >>> fix_model('CMIP5', ['CESM1(BGC)', 'CESM1-BGC'], inver...
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from typing import Union from typing import List from typing import Tuple def _get_choices(choices: Union[str, List]) -> List[Tuple[str, str]]: """Returns list of choices, used for the ChoiceFields""" result = [('', '')] if isinstance(choices, str): result.append((choices, choices)) else: ...
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def invalid_file(): """Create an invalid filename string.""" return "/tmp/INVALID.FILE"
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def get_model(app_label, model_name): """ Fetches a Django model using the app registery. All other methods to acces models might raise an exception about registery not being ready yet. This doesn't require that an app with the given app label exists, which makes it safe to call when the regis...
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def affaires_view(request): """ Return all affaires """ # Check connected if not check_connected(request): raise exc.HTTPForbidden() query = request.dbsession.query(VAffaire).order_by(VAffaire.id.desc()).all() return Utils.serialize_many(query)
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from typing import Union def metric_try_to_float(s: str) -> Union[float, str]: """ Try to convert input string to float value. Return float value on success or input value on failure. """ v = s try: if "%" in v: v = v[:-1] return float(v) except ValueError: ...
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def _table_difference(left: TableExpr, right: TableExpr): """ Form the table set difference of two table expressions having identical schemas. A set difference returns only the rows present in the left table that are not present in the right table Parameters ---------- left : TableExpr ...
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def parse_args(): """ It parses the command-line arguments. Parameters ---------- args : list[str] List of command-line arguments to parse Returns ------- parsed_args : argparse.Namespace It contains the command-line arguments that are supplied by the user """ par...
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def parse_row(row, entity_dict, span_capture_list, previous_entity): """ updates the entity dict and span capture list based on row contents """ bio_tag, entity = parse_tag(row.tag) if bio_tag == 'B': # update with previous entity, if applicable entity_dict, span_capture_list, pre...
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def _is_fn_init( tokens: list[Token] | Token, errors_handler: ErrorsHandler, path: str, namehandler: NameHandler, i: int = 0 ): """ "fn" <fn-name> "("<arg>*")" (":" <returned-type>)? <code-body>""" tokens = extract_tokens_with_code_body(tokens, i) if tokens is None ...
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import asyncio from typing import cast async def http_connect(address: str, port: int) -> HttpConnection: """Open connection to a remote host.""" loop = asyncio.get_event_loop() _, connection = await loop.create_connection(HttpConnection, address, port) return cast(HttpConnection, connection)
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def make_parallel_transformer_config() -> t5_architecture.EncoderDecoder: """Returns an EncoderDecoder with parallel=True.""" dtype = jnp.bfloat16 num_attn_heads = 8 make_dropout = lambda: nn.Dropout(rate=0.1, broadcast_dims=(-2,)) make_layer_norm = layer_norm.T5LayerNorm def _make_encoder_layer(shared_rel...
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def get_device_mapping(embedding_sizes, num_gpus, data_parallel_bottom_mlp, experimental_columnwise_split, num_numerical_features): """Get device mappings for hybrid parallelism Bottom MLP running on device 0. Embeddings will be distributed across among all the devices. Optimal solu...
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def _generate_relative_positions_embeddings(length, depth, max_relative_position, name): """Generates tensor of size [length, length, depth].""" with tf.variable_scope(name): relative_positions_matrix = _generate_relative_positions_matrix( length, max_relative...
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def continTapDetector( fs: int, x=[], y=[], z=[], side='right', ): """ Detect the moments of finger-raising and -lowering during a fingertapping task. Function detects the axis with most variation and then first detects several large/small pos/neg peaks, then the function determines sample-w...
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def parallelize(df, func): """ Split data into max core partitions and execute func in parallel. https://www.machinelearningplus.com/python/parallel-processing-python/ Parameters ---------- df : pandas Dataframe func : any functions Returns ------- data : pandas Dataframe R...
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