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def connect_registry_client(): """ connect the module client for the Registry implementation we're using return the client object """ client = adapters.RegistryClient() client.connect(environment.service_connection_string) return client
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def get_group_average_score(gid=None, name=None): """ Get the average score of teams in a group. Args: gid: The group id name: The group name Returns: The total score of the group """ group_scores = get_group_scores(gid=gid, name=name) total_score = sum([entry['scor...
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def solve_with_cdd_for_II(A, verbose=False): """This method finds II's minmax strategy for zero-sum game A""" m = A.shape[0] # number of rows n = A.shape[1] # number of columns A = np.column_stack([[0]*m,-A,[1]*m]) I = np.eye(n) nn = np.column_stack([[0]*n,I,[0]*n]) # non-negativity cons...
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def build_none() -> KeySetNone: """Returns NONE.""" return KeySetNone()
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import csv import numpy def load_csv(file, shape=None, normalize=False): """ Load CSV file. :param file: CSV file. :type file: file like object :param shape : data array is reshape to this shape. :type shape: tuple of int :return: numpy array """ value_list = [] for row in cs...
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from typing import Tuple def flip_around_axis( coords: np.ndarray, axis: Tuple[float, float, float] = (0.2, 0.2, 0.2) ) -> np.ndarray: """Flips coordinates randomly w.r.t. each axis with its associated probability.""" for col in range(3): if np.random.binomial(1, axis[col]): ...
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import math def get_tc(name): """Determine the amount of tile columns to use.""" args = ["ffprobe", "-hide_banner", "-select_streams", "v", "-show_streams", name] proc = sp.run(args, text=True, stdout=sp.PIPE, stderr=sp.DEVNULL) lines = proc.stdout.splitlines() d = {} for ln in lines[1:-1]: ...
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def cmap_hex_color(cmap, i): """ Convert a Colormap to hex color. Parameters ---------- cmap : matplotlib.colors.ListedColormap Represents the Colormap. i : int List color index. Returns ------- String Represents corresponding hex string. """ return ...
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def train_folds(X, y, fold_count, batch_size, get_model_func): """ K-Fold Cross-Validation for Keras Models Inspired by PavelOstyakov https://github.com/PavelOstyakov/toxic/blob/master/toxic/train_utils.py """ fold_size = len(X[0]) // fold_count models = [] for fold_id in range(0, fold_co...
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async def cancel(command: HALCommandType, script: str): """Cancels the execution of a script.""" try: await command.actor.helpers.scripts.cancel(script) except Exception as err: command.warning(text=f"Error found while trying to cancel {script}.") return command.fail(error=err) ...
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def get_nodes_by_betweenness_centrality(query_id, node_number): """Get a list of nodes with the top betweenness-centrality. --- tags: - query parameters: - name: query_id in: path description: The database query identifier required: true type: integer ...
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import sympy def preprocess(function): """ Converts a given function from type str to a Sympy object. Keyword arguments: function -- a string type representation of the user's math function """ expr = function while True: if '^' in expr: expr = expr[:expr.index('...
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import re def tot_changes(changes: str) -> int: """Add deletions and insertions.""" insertions_pat = re.compile(r"(\d+) insertion") deletions_pat = re.compile(r"(\d+) deletion") insertions = insertions_pat.search(changes) insertions = int(insertions.group(1)) if insertions else 0 deletions =...
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def update_from_mcd(full_table, update_table): # type: (pd.DataFrame, pd.DataFrame) -> pd.DataFrame """ Update the full table (aka the PDG extended-style table) with the up-to-date information from the PDG .mcd file. Example ------- >>> new_table = update_from_mcd('mass_width_2008.fwf', 'ma...
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import socket def resolve_hostname(host): """Get IP address of hostname or URL.""" try: parsed = urlparse.urlparse(host) except AttributeError as err: error = "Hostname `%s`is unparseable. Error: %s" % (host, err) LOG.exception(error) raise errors.SatoriInvalidNetloc(error)...
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import pandas as pd import numpy as np from .data_utils import keep_common_genes from .data_utils import df_normalization def DeconRNASeq_main(rna_df, sig_df, patient_IDs='ALL', args={}): """ This function does the following: - parses the dictionary 'args' for the arguments to pass on to the DeconRNAS...
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import re from typing import OrderedDict def parse_c_interface(c_interface_file): """ @brief Parses a c-interface file and generates a dictionary of function names to parameter lists. Exported functions are expected to be preceded by 'DLL_EXPORT'. Python keywords should not be used as variable names f...
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def con_minimize(fun, bounds, constr=(), x0=None, args=(), callback=None, options={}, workers=None): """Constrained minimization of `fun` using Genetic Algorithm. This function is a wrapper over modetga.minimize(). The constraints are defined as a tuple of functions (`fcon1(x, *args)`, `...
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def unique_v2(lst): """ Returns a list of all unique elements in the input list "lst." This algorithm runs in o(n), as it only passes through the list "lst" twice """ dd = defaultdict(int) # avoids blank dictionary problem (KeyError when accessing nonexistent entries) unique_list = [] for va...
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import ipaddress def is_ip_network(network, strict=False): """Returns True/False if a string is a valid network.""" network = str(network) try: ipaddress.ip_network(network, strict) return True except ValueError: return False
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def assign_point_of_contact(point_of_contact): """ Assign a user to be the point of contact in emails/letters :param point_of_contact: A string containing the user_guid if point of contact has been set for a request :return: A User object to be designated as the point of contact for a request """ ...
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def response_with_pagination(guests, previous, nex, count): """ Make a http response for GuestList get requests. :param count: Pagination Total :param nex: Next page Url if it exists :param previous: Previous page Url if it exists :param guests: Guest :return: Http Json response """ ...
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def put_object(request, old_pid): """MNStorage.update(session, pid, object, newPid, sysmeta) → Identifier.""" if django.conf.settings.REQUIRE_WHITELIST_FOR_UPDATE: d1_gmn.app.auth.assert_create_update_delete_permission(request) d1_gmn.app.util.coerce_put_post(request) d1_gmn.app.views.assert_db....
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def _match_gelu_pattern(gf, entry_node): """ Return the nodes that form the subgraph of a GELU layer """ try: if not len(entry_node.outputs) == 3: return None pow_1, add_2, mul_3 = [gf[x] for x in entry_node.outputs] if not (pow_1.op == 'Pow' and add_2.op == 'Add' and mul...
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def assign_obs_error(param, truth_mag, band, run): """ Assign errors to Object catalog quantities Returns ------- obs_err : float or np.array The error values in units defined in get_astrometric_error(), get_photometric_error err_type : str Type of observational error ...
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from typing import List from typing import Tuple import tokenize def dir_frequency(dirname: str, amount=50) -> List[Tuple[str, int]]: """Pipeline of word_frequency from a directory of raw input file.""" md_list = md.collect_md_text(dirname) return compute_frequency(tokenize(normalize(" ".join(md_list))), ...
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def test_solver1(N, version='scalar'): """ Very simple test case. Store the solution at every N time level. """ def I(x): return sin(2*x*pi/L) def f(x,t): return 0 solutions = [] # Need time_level_counter as global variable since # it is assigned in the action function (that makes ...
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import requests def get_auth_data(): """ Create auth data. Returns: return: access token and token expiring time. """ payload = { 'client_id': CLIENT_ID, 'client_secret': CLIENT_SECRET, 'grant_type': 'client_credentials', } api_url = '{0}/oauth/access_toke...
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def datatable(module, tag): """Mapping for DataTable.""" if tag == "DataTable": return module, tag
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def remove_prepending(seq): """ Method to remove prepending ASs from AS path. """ last_add = None new_seq = [] for x in seq: if last_add != x: last_add = x new_seq.append(x) is_loopy = False if len(set(seq)) != len(new_seq): is_loopy = True ...
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def github_handle_error(e): """ Handles an error from the Github API an error example: Error in API call [401] - Unauthorized {"message": "Bad credentials", "documentation_url": "https://docs.github.com/rest"} The error might contain error_code, error_reason and error_message The error_reason an...
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def netmask_to_bits(net_mask): """ Convert netmask to bits Args: net_mask ('str'): Net mask IP address ex.) net_mask = '255.255.255.255' Raise: None Returns: Net mask bits """ return IPAddress(net_mask).netmask_bits()
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def register_corrector(cls=None, *, name=None): """A decorator for registering corrector classes.""" def _register(cls): if name is None: local_name = cls.__name__ else: local_name = name if local_name in _CORRECTORS: raise ValueError(f'Already registered model with name: {local_name}...
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import numpy def _sample_perc_from_list(lst, perc=100, algorithm="cum_rand", random_state=None): """ Sample randomly a certain percentage of items from the given list. The original order of the items is kept. :param lst: list, shape = (n,), input items :param perc: scalar, percentage to sample ...
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def irods_setacls(path, acl_list, verbose=False): """ This function will add the ACLs listed in 'acl_list' to the collection or data object at 'path'. 'acl_list' is a list where each element itself is a list consisting of the username in name#zone format, and the access level ('read', 'write', ...
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from datetime import datetime def add_years(date_to_change, years): """ Return a date that's `years` years after the date (or datetime) object `date_to_change`. Return the same calendar date (month and day) in the destination year, if it exists, otherwise use the following day (thus changing Febru...
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def concurrency_update_done(client, function_name, qualifier): """wait fn for ProvisionedConcurrencyConfig 'Status'""" def _concurrency_update_done(): status = client.get_provisioned_concurrency_config( FunctionName=function_name, Qualifier=qualifier )["Status"] if status ==...
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def googleapis_email(url, params): """Loads user data from googleapis service, only email so far as it's described in http://sites.google.com/site/oauthgoog/Home/emaildisplayscope Parameters must be passed in queryset and Authorization header as described on Google OAuth documentation at: http://gr...
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def max_pool_2x2(input_): """ Perform max pool with 2x2 kelner""" return tf.nn.max_pool(input_, ksize=[1, 2, 2, 1], strides=[1, 2, 2, 1], padding='SAME')
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import tqdm def remove_numerals(df, remove_mixed_strings=True): """Removes rows from an ngram table with words that are numerals. This does not include 4-digit numbers which are interpreted as years. Arguments: df {Pandas dataframe} -- A dataframe of with columns 'word', 'count'. Keyword ...
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def b32_ntop(*args): """LDNS buffer.""" return _ldns.b32_ntop(*args)
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from typing import Callable from typing import Dict import torch def infer_feature_extraction_pytorch( model: PreTrainedModel, run_on_cuda: bool ) -> Callable[[Dict[str, torch.Tensor]], torch.Tensor]: """ Perform Pytorch inference for feature extraction task :param model: Pytorch model (sentence-trans...
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def editRole(userSource, oldName, newName): """Renames a role in the specified user source. When altering the Gateway System User Source, the Allow User Admin setting must be enabled. Args: userSource (str): The user source in which the role is found. Blank will use the default use...
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def beam_hardening_correction(mat, q, n, opt=True): """ Correct the grayscale values of a normalized image using a non-linear function. Parameters ---------- mat : array_like Normalized projection image or sinogram image. q : float Positive number. Recommended range [0.005, ...
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def cargar_recursos_vectores_transpuestos(): """ Se carga la informacion para poder calcular los vectores transpuestos """ # Se crea el df filename = 'csv/' + conf.data['env']['path'] + '/vectores_transpuestos.csv' recursos_v_transpuestos = pd.read_csv(filename) # Se cambia el nombre de los ...
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def read_pdb(file_name, exclude=('SOL',), ignh=False, modelidx=1): """ Parse a PDB file to create a molecule. Parameters ---------- filename: str The file to read. exclude: collections.abc.Container[str] Atoms that have one of these residue names will not be included. ignh: ...
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def sao_isomorficas(texto1: str, texto2: str) -> bool: """ >>> sao_isomorficas('egg', 'add') True >>> sao_isomorficas('foo', 'bar') False >>> sao_isomorficas('eggs', 'add') False """ # Algoritmo O(n) em tempo e memória letras_encontradas = {} if len(texto1) != len(texto2): ...
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def _is_no_args(fn): """Check if function has no arguments. """ return getargspec(fn).args == []
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def failure(parsed_args): """ :param :py:class:`argparse.Namespace` parsed_args: :return: Nowcast system message type :rtype: str """ logger.critical( f"{parsed_args.model_config} {parsed_args.run_type} FVCOM VH-FR run for " f'{parsed_args.run_date.format("YYYY-MM-DD")} ' ...
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def good_AP_finder(time,voltage): """ This function takes the following input: time - vector where each element is a time in seconds voltage - vector where each element is a voltage at a different time We are assuming that the two vectors are in correspondance (meaning t...
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from typing import Dict from typing import Any import tqdm def parse(excel_sheets: Dict[Any, pd.DataFrame], dictionary: Dict[str, Any], verbose: bool = False) -> pd.DataFrame: """Parse sheets of an excel file according to instructions in `dictionary`. """ redux_dict = recursive_traver...
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def build_LAMP(prob,T,shrink,untied): """ Builds a LAMP network to infer x from prob.y_ = matmul(prob.A,x) + AWGN return a list of layer info (name,xhat_,newvars) name : description, e.g. 'LISTA T=1' xhat_ : that which approximates x_ at some point in the algorithm newvars : a tuple of layer-...
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def coeffVar(X, precision=3): """ Coefficient of variation of the given data (population) Argument: X: data points, a list of int, do not mix negative and positive numbers precision (optional): digits precision after the comma, default=3 Returns: float, the cv (measure of dispers...
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def tostring(node): """ Generates a string representation of the tree, in a format determined by the user. @ In, node, InputNode or InputTree, item to turn into a string @ Out, tostring, string, full tree in string form """ if isinstance(node,InputNode) or isinstance(node,InputTree): return node.p...
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from typing import Dict import random def pick_char_from_dict(char: str, dictionary: Dict[str, str]) -> str: """ Picks a random format for the givin letter in the dictionary """ return random.choice(dictionary[char])
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from typing import List def bmeow_to_bilou(tags: List[str]) -> List[str]: """Convert BMEOW tags to the BILOU format. Args: tags: The BMEOW tags we are converting Raises: ValueError: If there were errors in the BMEOW formatting of the input. Returns: Tags that produce the sam...
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def site_sold_per_category(items): """For every category, a (site, count) pair with the number of items sold by the site in that category. """ return [(site, [(cat, total_sold(cat_items)) for cat, cat_items in categories]) for site, categories in categ...
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from typing import List import ctypes def swig_py_object_2_list_int(object, size : int) -> List[int]: """ Converts SwigPyObject to List[float] """ y = (ctypes.c_float * size).from_address(int(object)) new_object = [] for i in range(size): new_object += [int(y[i])] return new_ob...
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from typing import Tuple from typing import Union async def reactionFromRaw(payload: RawReactionActionEvent) -> Tuple[Message, Union[User, Member], emojis.BasedEmoji]: """Retrieve complete Reaction and user info from a RawReactionActionEvent payload. :param RawReactionActionEvent payload: Payload describing ...
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import array def poisson2d(N,dtype='d',format=None): """ Return a sparse matrix for the 2d poisson problem with standard 5-point finite difference stencil on a square N-by-N grid. """ if N == 1: diags = asarray( [[4]],dtype=dtype) return dia_matrix((diags,[0]), shape=(1,1)).a...
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import random def get_factory(): """随机获取一个工厂类""" return random.choice([BasicCourseFactory, ProjectCourseFactory])()
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def delay_class_factory(motor_class): """ Create a subclass of DelayBase that controls a motor of class motor_class. Used in delay_instace_factory (DelayMotor), may be useful for one-line declarations inside ophyd Devices. """ try: cls = delay_classes[motor_class] except KeyError: ...
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def lonlat2px_gt(img, lon, lat, lon_min, lat_min, lon_max, lat_max): """ Converts a pair of lon and lat to its corresponding pixel value in an geotiff image file. Parameters ---------- img : Image File, e.g. PNG, TIFF Input image file lon : float Longitude lat : float ...
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import scipy def array_wishart_rvs(df, scale, **kwargs): """ Wrapper around scipy.stats.wishart to always return a np.array """ if np.size(scale) == 1: return np.array([[ scipy.stats.wishart(df=df, scale=scale, **kwargs).rvs() ]]) else: return scipy.stats.wishart(df...
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async def async_setup_entry(hass, entry): """Set up Jenkins from a config entry.""" hass.async_create_task( hass.config_entries.async_forward_entry_setup(entry, "sensor") ) return True
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import math def signal_to_dataset(raw, fsamp, intvs, labels): """Segmentize raw data into list of epochs. returns dataset and label_array : a list of data, each block is 1 second, with fixed size. width is number of channels in certain standard order. Args: raw: EEG signals. Shap...
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def project_dynamic_property_graph(graph, v_prop, e_prop, v_prop_type, e_prop_type): """Create project graph operation for nx graph. Args: graph (:class:`nx.Graph`): A nx graph. v_prop (str): The node attribute key to project. e_prop (str): The edge attribute key to project. v_p...
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def eqfm_(a, b): """Helper for comparing floats AND style names.""" n1, v1 = a n2, v2 = b if type(v1) is not float: return eq_(a, b) eqf_(v1, v2) eq_(n1, n2)
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def flatten_comment(seq): """Flatten a sequence of comment tokens to a human-readable string.""" # "[CommentToken(value='# Extra settings placed in ``[app:main]`` section in generated production.ini.\\n'), CommentToken(value='# Example:\\n'), CommentToken(value='#\\n'), CommentToken(value='# extra_ini_settings...
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def get_community(community_id): """ Verify that a community with a given id exists. :param community_id: id of test community :return: Community instance :return: 404 error if doesn't exist """ try: return Community.objects.get(pk=community_id) except Community.DoesNotExist: ...
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import csv import pprint def load_labeled_info(csv4megan_excell, audio_dataset, ignore_files=None): """Read labeled info from spreat sheet and remove samples with no audio file, also files given in ignore_files """ if ignore_files is None: ignore_files = set() with open(csv4megan_excel...
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def de_dupe_list(input): """de-dupe a list, preserving order. """ sam_fh = [] for x in input: if x not in sam_fh: sam_fh.append(x) return sam_fh
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def donwload_l10ns(): """Download all l10ns in zip archive.""" url = API_PREFIX + 'download/' + FILENAME + KEY_SUFFIX l10ns_file = urllib2.urlopen(url) with open('all.zip','wb') as f: f.write(l10ns_file.read()) return True
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def _constant_velocity_heading_from_kinematics(kinematics_data: KinematicsData, sec_from_now: float, sampled_at: int) -> np.ndarray: """ Computes a constant velocity baseline for given kinematics data, time window ...
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def arg_int(name, default=None): """ Fetch a query argument, as an integer. """ try: v = request.args.get(name) return int(v) except (ValueError, TypeError): return default
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def adapter_rest(request, api_module_rest, api_client_rest): """Pass.""" return { "adapter": request.param, "api_module": api_module_rest, "api_client": api_client_rest, }
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def remove_quotes(string): """Function to remove quotation marks surrounding a string""" string = string.strip() while len(string) >= 3 and string.startswith('\'') and string.endswith('\''): string = string[1:-1] string = quick_clean(string) string = quick_clean(string) return string
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def compute_list_featuretypes( data, list_featuretypes, fourier_n_largest_frequencies, wavelet_depth, mother_wavelet, ): """ This function lets the user choose which combination of features they want to have computed. list_featuretypes: "Basic" - min, max, mean, kurt ,skew, ...
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def select(locator): """ Returns an :class:`Expression` for finding selects matching the given locator. The query will match selects that meet at least one of the following criteria: * the element ``id`` exactly matches the locator * the element ``name`` exactly matches the locator * the elemen...
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def send_image(filename): """Route to uploaded-by-client images Returns ------- file Image file on the server (see Flask documentation) """ return send_from_directory(app.config['UPLOAD_FOLDER'], filename)
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def swissPairings(): """Returns a list of pairs of players for the next round of a match. Assuming that there are an even number of players registered, each player appears exactly once in the pairings. Each player is paired with another player with an equal or nearly-equal win record, that is, a playe...
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import torch def split(data, batch): """ PyG util code to create graph batches """ node_slice = torch.cumsum(torch.from_numpy(np.bincount(batch)), 0) node_slice = torch.cat([torch.tensor([0]), node_slice]) row, _ = data.edge_index edge_slice = torch.cumsum(torch.from_numpy(np.bincount(batch[row])), 0) edge_...
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def _get_shadowprice_data(scenario_id): """Gets data necessary for plotting shadow price :param str/int scenario_id: scenario id :return: (*tuple*) -- interconnect as a str, bus data as a data frame, lmp data as a data frame, branch data as a data frame and congestion data as a data frame ...
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import json def get_city_reviews(city): """ Given a city name, return the data for all reviews. Returns a pandas DataFrame. """ with open(f"{DATA_DIR}/{city}/review.json", "r") as f: review_list = [] for line in f: review = json.loads(line) review_list.appen...
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def extract_rows_from_table(dataset, col_names, fill_null=False): """ Extract rows from DB table. :param dataset: :param col_names: :return: """ trans_dataset = transpose_list(dataset) rows = [] if type(col_names).__name__ == 'str': col_names = [col_names] for col_name in col...
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def CalculateHydrogenNumber(mol): """ ################################################################# Calculation of Number of Hydrogen in a molecule ---->nhyd Usage: result=CalculateHydrogenNumber(mol) Input: mol is a molecule object. ...
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def check_update (): """Return the following values: (False, errmsg) - online version could not be determined (True, None) - user has newest version (True, (version, url string)) - update available (True, (version, None)) - current version is newer than online version """ version...
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import torch def count_regularization_baos_for_both(z, count_tokens, count_pieces, mask=None): """ Compute regularization loss, based on a given rationale sequence Use Yujia's formulation Inputs: z -- torch variable, "binary" rationale, (batch_size, sequence_length) percentage -- the ...
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def unsqueeze_samples(x, n): """ """ bn, d = x.shape x = x.reshape(bn//n, n, d) return x
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def f_snr(seq): """compute signal to noise rate of a seq Args: seq: input array_like sequence paras: paras array, in this case should be "axis" """ seq = np.array(seq, dtype=np.float64) result = np.mean(seq)/float(np.std(seq)) if np.isinf(result): print "marker" result = 0 return result
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def _lorentzian_pink_beam(p, x): """ @author Saransh Singh, Lawrence Livermore National Lab @date 03/22/2021 SS 1.0 original @details the lorentzian component of the pink beam peak profile obtained by convolution of gaussian with normalized back to back exponentials. more details can be found in...
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def get_q_HPU_ave(Q_HPU): """1時間平均のヒートポンプユニットの平均暖房出力 (7) Args: Q_HPU(ndarray): 1時間当たりのヒートポンプユニットの暖房出力 (MJ/h) Returns: ndarray: 1時間平均のヒートポンプユニットの平均暖房出力 (7) """ return Q_HPU * 10 ** 6 / 3600
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def particles(t1cat): """Return a list of the particles in a T1 catalog DataFrame. Use it to find the individual particles involved in a group of events.""" return particles_fromlist(t1cat.particles.tolist())
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def prime_list(num): """ This function returns a list of prime numbers less than natural number entered. :param num: natural number :return result: List of primes less than natural number entered """ prime_table = [True for _ in range(num+1)] i = 2 while i ** 2 <= num: if prime_...
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import time def check_deadline_exceeded_and_store_partial_minimized_testcase( deadline, testcase_id, job_type, input_directory, file_list, file_to_run_data, main_file_path): """Store the partially minimized test and check the deadline.""" testcase = data_handler.get_testcase_by_id(testcase_id) store_min...
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import ipaddress def _item_to_python_repr(item, definitions): """Converts the given Capirca item into a typed Python object.""" # Capirca comments are just appended to item strings s = item.split("#")[0].strip() # A reference to another network if s in definitions.networks: return s ...
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import numpy def floor_divide(x1, x2, out=None, where=True, **kwargs): """ Return the largest integer smaller or equal to the division of the inputs. It is equivalent to the Python ``//`` operator and pairs with the Python ``%`` (`remainder`), function so that ``a = a % b + b * (a // b)`` up to r...
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from typing import Callable import click def node_args_argument(command: Callable[..., None]) -> Callable[..., None]: """ Decorate a function to allow choosing arguments to run on a node. """ function = click.argument( 'node_args', type=str, nargs=-1, required=True, ...
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import functools import unittest def _tag_error(func): """Decorates a unittest test function to add failure information to the TestCase.""" @functools.wraps(func) def decorator(self, *args, **kwargs): """Add failure information to `self` when `func` raises an exception.""" self.test_faile...
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from datetime import datetime def get_submission_praw(n, sub, n_num): """ Returns a list of results for submission in past: 1st list: current result from n hours ago until now 2nd list: prev result from 2n hours ago until n hours ago """ mid_interval = datetime.today() - timedelta(hours=n) ...
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