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from datetime import datetime def build_data_table(row, fields_to_try): """ Create HTML table for one row of data If no fields are valid, returns empty string """ th_class = 'attribute_heading' td_class = 'attribute_value' field_names = pd.read_csv('data/fiel...
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def time_entry_reader(date, configuration): """Read the entries and return a list of entries that are apart of the date provided.""" parser = YAML(typ='rt') date = date.date() try: with open(configuration['filename'], 'r') as data_file: time_entries = parser.load(data_file).get('rec...
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import asyncio async def test_send_write(event_loop): """Check feed-receive scenarios used in the library.""" STREAM_ID = 'whatever' DATA = b'data' def make_writer(): queue = asyncio.Queue() async def writer(id, data): assert id == STREAM_ID await queue.put(da...
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def width_series(value_series, outer_average_width=5, max_value=None, method='linear'): """ :param value_series: the pd.Series that contain the values :param outer_average_width: the average width of the width series to return :param max_value: value to use as the maximum when normalizing the series (to...
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def unroll_upper_triangular(matrix): """Converts square matrix to vector by unrolling upper triangle.""" rows, cols = matrix.shape assert rows == cols, "Not a square matrix." row_idx, col_idx = np.triu_indices(rows, 1) unrolled = [] for i, j in zip(row_idx, col_idx): unrolled.append(mat...
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from typing import Sequence from typing import Any from typing import Optional from typing import Tuple def fill_tuples( tuples: Sequence[Any], length: Optional[int] = None, repeat: bool = False, fill_method: str = 'bfill', ) -> Sequence[Tuple]: """Fill tuples so they are all the same length. ...
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def intersect(connection, items, ttl=30, execute=True): """并集计算""" return _set_common(connection, 'sinterstore', items, ttl, execute)
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def batch_decode(raw_logits, use_random, decode_times): """ tbd """ size = (raw_logits.shape[1] + 7) // 8 logit_lists = [] for i in range(0, raw_logits.shape[1], size): if i + size < raw_logits.shape[1]: logit_lists.append(raw_logits[:, i: i + size, :]) else: ...
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import pathlib import pkg_resources import yaml def _load_schemata(obj_type: str) -> dict: """Load the schemata from the package, returning merged results of other schema files if referenced in the file loaded. :raises: FileNotFoundError """ schema_path = pathlib.Path(pkg_resources.resource_file...
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def waitfor(msg, status = '', spinner = None, log_level = log_levels.INFO): """waitfor(msg, status = '', spinner = None) -> waiter Starts a new progress indicator which includes a spinner if :data:`pwnlib.term.term_mode` is enabled. By default it outputs to loglevel :data:`pwnlib.log_levels.INFO`. ...
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def f(i): """Add 2 to a value Args: i ([int]): integer value Returns: [int]: integer value """ return i + 2
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def show_forecast(cmp_df, num_predictions, num_values, title): """Visualize the forecast.""" def create_go(name, column, num, **kwargs): points = cmp_df.tail(num) args = dict(name=name, x=points.index, y=points[column], mode='lines') args.update(kwargs) return go.Scatter(**a...
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import os import warnings def build_jobs_dict(path): """Build a dictionary of "job_name" : [recipe list] from a directory full of job files.""" jobfiles = nested_glob(path, '.ajp') jobs = {} for jobfile in jobfiles: job_name = os.path.basename(jobfile).strip('.ajp') try: ...
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def get_concepts_from_kmeans(tfidf, kmeans): """Get kmeans cluster centers in term space. Parameters ---------- tfidf : TfidfVectorizer Fitted vectorizer with learned term vocabulary. kmeans : KMeans KMeans fitted to document-term matrix returned by tfidf. Returns -...
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def streams_to_dataframe(streams, imcs=None, imts=None, event=None): """Extract peak ground motions from list of processed StationStream objects. Note: The PGM columns underneath each channel will be variable depending on the units of the Stream being passed in (velocity sensors can only generate PGV) ...
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def timestamp_diff(time_point_unit: TimePointUnit, time_point1, time_point2) -> Expression: """ Returns the (signed) number of :class:`~pyflink.table.expression.TimePointUnit` between time_point1 and time_point2. For example, `timestamp_diff(TimePointUnit.DAY, lit("2016-06-15").to_date, lit("2016-0...
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import tqdm def plot_solar_twins_results(star_postfix=''): """Plot results for 17 pairs with q-coefficients for solar twins""" def format_pair_label(pair_label): """Format a pair label for printing with MNRAS ion format. Parameters ---------- pair_label : str A p...
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def equalize(pil_img: Image.Image, level: float): """Equalize an image. .. seealso:: :func:`PIL.ImageOps.equalize`. Args: pil_img (Image.Image): The image. level (float): The intensity. """ del level # unused return ImageOps.equalize(pil_img)
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def lightfm_trainer( train: np.ndarray, loss: str, n_components: int, lam: float ) -> None: """Train lightfm models.""" # detect and init the TPU tpu = tf.distribute.cluster_resolver.TPUClusterResolver.connect() # instantiate a distribution strategy tpu_strategy = tf.distribute.experimental.TPU...
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def get_wspd_ts(path, storm, res, shpmask): """ Extracts the U and V component and returns the wind speed timeseries of storm_dict Arguments: path (str): Path containing data to load storm (str): Name of storm res (str): Resolution of data Returns: Pandas dataframe with...
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def _read_output_file(path): """Read Stan csv file to ndarray.""" comments = [] data = [] columns = None with open(path, "rb") as f_obj: # read header for line in f_obj: if line.startswith(b"#"): comments.append(line.strip().decode("utf-8")) ...
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def _transform_data(raw_df, cols_config): """ Applies required transformations to the raw dataframe :returns : Trasformed dataframe ready to be exported/loaded """ # Perform column and dtype checks if check_columns(raw_df, cols_config): df = raw_df else: logger.warning("Inco...
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import os def dcmToSimpleITK(dcmDirectory): """Return a simple ITK image from a pile of dcm files. The returned sITK image has been rescaled based on the value of the rescale slope on the dicom tag. Array-like data of the 3D image can be obtained with the GetArrayFromImage() method""" list_dcmFiles = ...
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import math def mean_and_std(values): """Compute mean standard deviation""" size = len(values) mean = sum(values)/size s = 0.0 for v in values: s += (v - mean)**2 std = math.sqrt((1.0/(size-1)) * s) return mean, std
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from typing import Union from typing import List def blacken( color: Color, amount: FloatOrFloatIterable ) -> Union[Color, List[Color]]: """ Return a color or colors amount fraction or fractions of the way from `color` to `black`. :param color: The existing color. :param amount: The propo...
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def llf_gradient_sigma_neq_gamma(history, sum_less_equal=True): """ Calculate the gradient of the log-likelihood function symbolically. Parameters ---------- sum_less_equal : bool, default: True This arg is passed to :meth:`self.llf_sigma_eq_gamma`. Returns ------- gradient : s...
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def selection_support_df(df, combinations, min_support): """ selection combinations with support Parameters ---------- df : pandas.DataFrame data to be selected. for example : = | banana | mango | apple | | 1 | 1 | 1 | ...
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from trie import TrieTree def empty_trie_tree(): """Empty trie tree fixture.""" return TrieTree()
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def bind_context_to_node(context, node): """Give a context a boundnode to retrieve the correct function name or attribute value with from further inference. Do not use an existing context since the boundnode could then be incorrectly propagated higher up in the call stack. :param context: Cont...
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def get_weight_matrix(file_handle): """ Read each line in file_handle and return the weight matrix as a dict, in which each key is the original node name, and each value is a nested dict, whose keys are gene systematic names, and values are weights. """ weight_matrix = dict() for line_num, ...
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def get_uptime(): """ Get uptime """ try: with open('/proc/uptime', 'r') as f: uptime_seconds = float(f.readline().split()[0]) uptime_time = str(timedelta(seconds=uptime_seconds)) data = uptime_time.split('.', 1)[0] except Exception as err: data =...
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import json def measure_list_for_upcoming_elections_retrieve_api_view(request): # measureListForUpcomingElectionsRetrieve """ Ask for all measures for the elections in google_civic_election_id_list :param request: :return: """ status = "" google_civic_election_id_list = request.GET.getlis...
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import argparse def check_template_path(path): """ Argument checker, check if template exists and get the content """ try: with open(path) as template: tmp = template.read() return tmp except: raise argparse.ArgumentTypeError("Invalid template path!")
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from fedelemflowlist.globals import flow_list_fields def get_required_flowlist_fields(): """ Gets required field names for Flow List. :return:list of required fields """ required_fields = [] for k, v in flow_list_fields.items(): if v[1]['required']: required_fields.append(...
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def sparse_table_function(*, index, data) -> callable: """ The very simplest Python-ish "sparse matrix", and plenty fast on modern hardware, for the size of tables this module will probably ever see, is an ordinary Python dictionary from <row,column> tuples to significant table entries. There are better ways if you...
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import asyncio async def _get_db_connection() -> asyncpg.Connection: """ Initialise database connection. On failure, retry multiple times. When the DB starts in parallel with the app (with Compose), it may not yet be ready to take connections. """ log.info("Creating DB connection") n_atte...
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def get_view_content(view): """ Returns view content as string. """ return utils.execute_in_sublime_main_thread(lambda: view.substr(sublime.Region(0, view.size())))
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def signed_byte8(x: IntVar) -> Int8: """Implementation for `SBYTE8`.""" return signed_byte_n(x, 8)
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import numpy import itertools def join(zma1, zma2, join_key_mat, join_name_mat, join_val_dct): """ join two z-matrices together """ syms1 = symbols(zma1) syms2 = symbols(zma2) natms1 = count(zma1) natms2 = count(zma2) key_mat1 = numpy.array(key_matrix(zma1)) key_mat2 = numpy.array(key_...
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def multi_to_weighted(G: nx.MultiDiGraph): """ Converts a multidigraph into a weighted digraph. """ nG = nx.DiGraph(G) # nG.add_nodes_from(G.nodes) nG.name = G.name + "_weighted_nomulti" edge_weights = {(u, v): 0 for u, v, k in G.edges} for u, v, key in G.edges: edge_weights[(u, ...
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def RetentionInDaysMatch(days): """Test whether the string matches retention in days pattern. Args: days: string to match for retention specified in days format. Returns: Returns a match object if the string matches the retention in days pattern. The match object will contain a 'number' group for th...
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from typing import Tuple import re def _extract_result_details(pipx_output: str) -> Tuple[str, str, str]: """ Extracts name and version from pipx's stdout """ match = re.search(r'installed package(.*),(.*)\n.*\n.*?-(.*)', pipx_output) if match: package, python_version, plugin_name = map(str.strip,...
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def get_pwr_SXT(sxt_los, plasma, emiss, num_pts=100, labels=labels_full): """ """ pwr_int = {} for ll in labels: # Get the appropriate database label filt = ll.split()[1] pix_los = sxt_los[ll] # Get the spatial points along the line of sight num_pixels = ...
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import requests import json def get_mstp_port(auth): """ Function to get list of mstp port status :param auth: AOSSAuth class object returned by pyarubaoss.auth :return list of mstp port status :rtype dict """ url_mstp_port = "http://" + auth.ipaddr + "/rest/"+auth.version+"/mstp/port" ...
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from typing import OrderedDict def _process_tree(tree, nstag): """Process XML tree for a record and return a dictionary for our standard """ rec = OrderedDict() for key, tag_, getall, trans1_, transall_ in [ ('author', 'creatorName', True, None, None), ('name', "title[@titleType='Alter...
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def prepare_all_predictions( data, uid_map, iid_map, interactions, model, num_threads, user_features=None, item_features=None, ): """Function to prepare all predictions for evaluation. Args: data (pandas df): dataframe of all users, items and ratings as loaded ui...
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from typing import Union from typing import Callable def touch(v: Union[Callable, str], default=None): """ Touch a function or an expression `v`, see if it causes exception. If not, output the result, otherwise, output `default`. Note: Use `default = pycamia.functions.identity_function`...
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def q_mult(q1, q2): """Quaternion multiplication""" w1, x1, y1, z1 = q1 w2, x2, y2, z2 = q2 w = w1 * w2 - x1 * x2 - y1 * y2 - z1 * z2 x = w1 * x2 + x1 * w2 + y1 * z2 - z1 * y2 y = w1 * y2 + y1 * w2 + z1 * x2 - x1 * z2 z = w1 * z2 + z1 * w2 + x1 * y2 - y1 * x2 return w, x, y, z
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import math def round_repeats(repeats, global_params): """Calculate module's repeat number of a block based on depth multiplier. Use depth_coefficient of global_params. Args: repeats (int): num_repeat to be calculated. global_params (namedtuple): Global params of the model. Returns:...
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def estimate_label_width(labels): """ Given a list of labels, estimate the width in pixels and return in a format accepted by CSS. Necessarily an approximation, since the font is unknown and is usually proportionally spaced. """ max_length = max([len(l) for l in labels]) return "{0}px".f...
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from datetime import datetime def update_user(user_id): """ :Route: PUT /<user_id>?active=false&admin=true&password=str&first_name=Katrina&last_name=Wijaya&email=mappeningdevx@gmail.com :Description: Updates user with id `user_id`. Updates any optional fields that are set as query parameters. :param...
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import glob import os def install_package(pkg, directory, python_version, pip_args): """Downloads wheel for a package. Assumes python binary provided has pip and wheel package installed. :param pkg: package name :param directory: destination directory to download the wheel file in :param python: ...
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import six def ssh_encrypt_text(ssh_public_key, text): """Encrypt text with an ssh public key. If text is a Unicode string, encode it to UTF-8. """ if isinstance(text, six.text_type): text = text.encode('utf-8') try: pub_bytes = ssh_public_key.encode('utf-8') pub_key = ser...
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from typing import List import os def add_missing_init_files_from_path( paths: List[str], folders_to_ignore: List[str], source_extensions: List[str], folder_trees_to_ignore: List[str], recursive: bool, ) -> bool: """ Add missing __init__.py files to the specified root directories and subdi...
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def naildown_entity(entity_class, entity_dict, entity, state, module, check_missing=None): """ Ensure that a given entity has a certain state """ changed, changed_entity = False, entity if state == 'present_with_defaults': if entity is None: changed, changed_entity = create_entity(entity...
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def get_all_admins(): """ Returns a queryset of all active admin users. """ current_admins = User.objects.filter(is_admin=True, is_active=True) return current_admins
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def htx_numpy(h, x): """ Convolution of reversed h with each line of u. Numpy implementation. Parameters ---------- h : array, shape (n_time_hrf), HRF x : array, shape (n_samples, n_time), neural activity signals Return ------ h_conv_x : array, shape (n_samples, n_time_valid), convolve...
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import torch def get_mask_results(probs, boxes, im_w, im_h, pixil_score_th=0.25): """ Args: probs (Tensor) boxes (ImageContainer) Returns: rles (list[string]) mask_pixel_scores (Tensor) """ device = probs.device N, _, H, W = probs.shape num_chunks = N if d...
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from typing import Dict from typing import Any def openapi() -> Dict[str, Any]: """ >>> client = app.test_client() >>> response = client.get("/openapi.json") >>> response.get_json()['openapi'] '3.0.0' >>> response.get_json()['info']['title'] 'Chapter 13. Example 2' """ # See domino...
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def koliko_izdelkov_v_skladiscu(): """ Vrne stevilo razlicnih izdelkov v skladiscu. >>> koliko_izdelkov_v_skladiscu() 18 """ poizvedba = """ SELECT COUNT(*) FROM izdelki WHERE kolicina IS NOT null """ st, = conn.execute(poizvedba).fetchone() return st
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import math import random def create_spline(curve_data, s_type='NURBS', len_nodes=100, spline_id=0, splines_count=1, bud_position=None): """ Create a spline of given type with n nodes to form a path made of sin and cos """ spline = curve_data.splines.new(type=s_type) # Regular spline points n...
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from os.path import join as opj import os def getImgN(path): """ 入力されたフォルダにある画像を全て読み込む [in] path: [out] 読みこんだ画像リスト """ if not os.path.isdir(path): print('path not found:', path) exit(1) return np.array([cv2.imread(opj(path, f), IMG.getCh(0)) for f in ...
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def get_composed_jumps(jumps, levels, win, verbose=0): """ Take the output of get_jumps (from landmarks) Compose the jumps, return them as an array of array. If intermediate=True, we return the jumps for intermediary levels, not just the requested one. We use a temporary sqlite3 connection to wo...
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import itertools def calculate_agreement_stv(agreement_dictionary, turker_accuracies): """ Inter agreement with most accurate chair vote Args: agreement_dictionary: holding sentence annotation records - 9 from non-experts and 1 expert sentence -> list of annotations (size settings.RESPON...
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def count_num_peps(filename): """ Count the number of peptide sequences in FASTA file. """ with open(filename) as f: counter = 0 for line in f: if line.startswith(">"): counter += 1 return counter
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import re def get_variables(examples): """Convert a code string to a list of variables. We assume a variable is a 'word' with only alphanumeric characters in it.""" variables = [" ".join(re.split(r"\W+", text)) for text in examples["text"]] return {"variables": variables}
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def _stored_data_paths(wf, name, serializer): """Return list of paths created when storing data""" metadata = wf.datafile(".{}.alfred-workflow".format(name)) datapath = wf.datafile(name + "." + serializer) return [metadata, datapath]
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def ascii_to_walls(char_matrix): """ A parser to build a gridworld from a text file. Each grid has ONE start and goal location. A reward of +1 is positioned at the goal location. :param char_matrix: Matrix of characters. :param p_success: Probability that the action is successful. :param see...
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def mock_sd(nresp=1): """Fake Stackdriver Monitoring API response for the ListTimeSeries endpoint. Args: nresp (int): Number of responses to add to response. Returns: ChannelStub: Mocked gRPC channel stub. """ timeserie = load_fixture('time_series_proto.json') response = {'next...
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def cohesion_separation(chroms, doc): """Measure balancing both cohesion and separation of clusters.""" coh = cohesion(chroms, doc) sep = separation(chroms, doc) return (1 + sigmoid(coh)) ** sep
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import locale import shlex import sys import subprocess def shellCall(shellCmd, stdin='', stderr=False, env=None, encoding=None): """Call a single system command with arguments, return its stdout. Returns stdout, stderr if stderr is True. Handles simple pipes, passing stdin to shellCmd (pipes are untested...
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import re def get_number_location( input : str, ): # endregion get_number_location header # region get_number_location docs """ get the string indices of all numbers that occur on the string format example: [ ( 0, 1 ), ( 4, 6 ), ( 9, 9 ) ] both begin and end are inclusive, in contrast with t...
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def update_object(obj, new_values): """update an object attributes from a supplied dictionary""" # avoiding obj.__dict__.update(new_values) as it will set a new attribute if it doesn't exist for k, v in new_values.items(): if hasattr(obj, k): try: setattr(obj, k, v) ...
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def subpathNeedsRefresh(modTimes, ufoPath, *subPath): """ Determine if a file needs to be refreshed. Returns True if the file's latest modification time is different from its previous modification time. """ previous = modTimes.get(subPath[-1]) if previous is None: return True lat...
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def resxy_(x: float, y: float, /) -> Resolution: """Construct resolution from X,Y order.""" return Resolution(x=x, y=y)
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def group_toggle_modules(request, group): """Enable or disable modules. """ if request.method != 'POST': raise Http404 referer = request.META.get('HTTP_REFERER', None) next = SITE_ROOT if referer is None else referer username = request.user.username group_wiki = request.POST.ge...
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def bilinear_sampler(imgs, coords): """ Construct a new image by bilinear sampling from the input image. Args: imgs: source image to be sampled from [batch, height_s, width_s, channels] coords: coordinates of source pixels to sample from [batch, height_t, Returns: A new sampled im...
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import types def wrap_array(typingctx, data_ptr, shape_tup): """create an array from data_ptr with shape_tup as shape """ assert isinstance(data_ptr, types.CPointer), "invalid data pointer" assert (isinstance(shape_tup, types.UniTuple) and shape_tup.dtype == np.intp), "invalid shape tuple"...
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import subprocess def change(port, password, limit): """修改用户""" port, password, limit = str(port), str(password), str(limit) ret = subprocess.check_output([SS_ADMIN, 'change', port, password, limit], stderr=subprocess.STDOUT) return ret
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from typing import Union from typing import Optional from typing import Dict from typing import Any import tempfile import os def reshape_resting_ecg_to_tidy( sample_id: Union[int, str], folder: Optional[str] = None, tmap: TensorMap = DEFAULT_RESTING_ECG_SIGNAL_TMAP, ) -> pd.DataFrame: """Wrangle resting ECG da...
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from geometric.internal import Angle, Dihedral, Distance, OutOfPlane from geometric.internal import PrimitiveInternalCoordinates as GeometricPRIC from geometric.internal import ( RotationA, RotationB, RotationC, TranslationX, TranslationY, TranslationZ, ) from geometr...
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def api_get_script(request): """POST - Frida Get Script.""" if not request.POST.getlist('scripts[]'): return make_api_response( {'error': 'Missing Parameters'}, 422) resp = tests_frida.get_script(request, True) if resp['status'] == 'ok': return make_api_response(resp, 200) ...
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import re def is_valid_slug(slug): """Returns true iff slug is valid.""" VALID_SLUG_RE = re.compile(r"^[a-z0-9\-]+$") return VALID_SLUG_RE.match(slug)
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import time import torch def KMeans_GPU(x, K=10, Niter=10, verbose=True): """Implements Lloyd's algorithm for the Euclidean metric.""" start = time.time() N, D = x.shape # Number of samples, dimension of the ambient space c = x[:K, :].clone() # Simplistic initialization for the centroids x_i ...
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def make_flat_roof(bm, faces, thick, outset, **kwargs): """Create a basic flat roof Args: bm (bmesh.types.BMesh): bmesh from current edit mesh faces (bmesh.types.BMFace): list of user selected faces thick (float): Thickness of the roof outset (float): How mush the roof overhangs...
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def make_comma_separated_list_fiter(filter_name, field_expression): """ Create a filter which uses a comma-separated list of values to filter the queryset. :param str filter_name: the name of the query param to fetch values :param str field_expression: the field expression to filter the queryset, like ...
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def get_dashboard(id_, token_info=None, user=None): """Get a single dashboard by ID :param id: ID of test dashboard :type id: str :rtype: Dashboard """ dashboard = Dashboard.query.get(id_) if not dashboard: return "Dashboard not found", 404 if dashboard and dashboard.project an...
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from pathlib import Path def get_recorder(execution_cmd, ml_names): """ The helper function for generating a recorder object """ if not execution_cmd.record_progress: return DummyRecorder() root_dir_path = Path(__file__).parent.parent log_dir_path = root_dir_path.joinpath( "ga...
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import torch import tqdm from typing import Counter import json import os def eval_epoch(data_iterator, model, optimizer, args, update=False, log_split='', split_name='', n_iter=0, epoch=0, writer=None, sample_pat...
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def get_customer_key(): """ Reutrn the key of the sample customer from file """ customer_file = open("sample_customer", "r") customer_key = customer_file.readline().rstrip("\n") customer_file.close() return customer_key
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def tau_tex(tex, tau0_): """ Eq. (15) Goldsmith et al. (2012) """ g = gu/gl return tau0_*(1. - np.exp(-tstar/tex))/(1. + g*np.exp(-tstar/tex))
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def cached(f): """Decorator to cache result of property.""" @wraps(f) def inner(self): name = '_{}'.format(f.__name__) if getattr(self, name, None) is None: setattr(self, name, f(self)) return getattr(self, name) return inner
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def thesaurus(*args, sort=False) -> dict: """Формирует словарь, в котором ключи — первые буквы слов, а значения — списки, содержащие слова, начинающиеся с соответствующей буквы :param *args: перечень слов :param sort: признак необходимости сортировки словаря по алфавиту (True - сортировать, False - не ...
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def calculate_ranking(imbalanced_results): """Calculate the ranking of oversamplers for any combination of datasets, classifiers and metrics.""" wide_optimal = calculate_wide_optimal(imbalanced_results) ranking_results = wide_optimal.apply( lambda row: _return_row_ranking( row[3:...
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def extract鏡像翻訳(item): """ Parser for '鏡像翻訳' """ if 'anime' in str(item['tags']).lower(): return None vol, chp, frag, postfix = extractVolChapterFragmentPostfix(item['title']) if not (chp or vol) or 'preview' in item['title'].lower(): return None tagmap = [ ('sodachi fiasco', 'Orokamonogatari - ...
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def config(live_server, django_user_model): """Create a user and return an auth_token config matching that user.""" user = django_user_model.objects.create( email='jathan@localhost', is_superuser=True, is_staff=True ) data = { 'email': user.email, 'secret_key': user.secret_key, ...
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from typing import Dict from typing import Union from typing import List from typing import Any from typing import OrderedDict def combine_data_by_key( combined_outputs: Dict[str, Union[List[Any], Any]], output: Dict[str, Union[List[Any], Any]], ) -> Dict[str, Union[List[Any], Any]]: """ Combine lists...
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import os def arango_connection() -> ArangoClient: """Connecting to arango.""" host = os.getenv("ARANGO_HOST") port = os.getenv("ARANGO_PORT") arango_client = ArangoClient(hosts=f"http://{host}:{port}") return arango_client
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import os def in_bazel() -> bool: """Return whether running under bazel.""" return os.environ.get("TEST_WORKSPACE", "") != ""
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def acceptCode(request): """Redeems a code to accept invitation cash""" params = request.get_params(schemas.AcceptCodeSchema()) device = get_device(request) customer = device.customer access_token = get_wc_token(request, customer) postParams = { 'code': params['code'] } response ...
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