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def σ(input, axis=1): """Softmax on an axis Softmax on an axis Arguments: input {Tensor} -- input Tensor Keyword Arguments: axis {number} -- axis on which to take softmax on (default: {1}) Returns: Tensor -- Softmax output Tensor """ input_size = input.size() ...
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def get_xps_list(xps_dict): """Convert XPs from internal format to API format""" xps_list = [] for (filetype, xp) in xps_dict.items(): item = dict(language=get_language_name(filetype), xp=xp) xps_list.append(item) return xps_list
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import numpy def gesvdj(a, full_matrices=True, compute_uv=True, overwrite_a=False): """Singular value decomposition using cusolverDn<t>gesvdj(). Factorizes the matrix ``a`` into two unitary matrices ``u`` and ``v`` and a singular values vector ``s`` such that ``a == u @ diag(s) @ v*``. Args: ...
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def decide_collocational(accum): """ accum is the n-grams sized windows of list of tokens to be analysed. N-grams size are given in function `decide` Decide whether there is a collocational evidence against an intervening sentence boundary """ global CONTEXT_SIZE, collocations center = CONT...
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import os def create_data_set(data_dir, csv_name, valid_size_frac): """ # Import image folder and csv file to create dataset. :param data_dir: directory of data. :param csv_name: Image file and the corresponding steering angle. :param valid_size_frac: Ratio of dividing the data set into validatio...
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import torch from typing import Tuple from typing import List from pathlib import Path def cluster_generated_images( images: torch.Tensor, activations: torch.Tensor, selected_neuron_idx: int, num_clusters: int = 8, show: bool = False, ) -> Tuple[List[torch.Tensor], List[torch.Tensor]]: """Clus...
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def get_list_of_all_forks(): """gets the list of all the forked repos""" url = "https://api.github.com/orgs/mlh-fellowship/repos?type=forks" all_repos = [] for i in range(1, 6): each_url = url + '&page=' + str(i) result = github_api(each_url) for repo in result.json(): ...
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from numpy import interp def linear(x, y, xref): """ Linear interpolation. :param x: :param y: :param xref: :return: """ return interp(xref, x, y, left=None, right=None, period=None)
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from datetime import datetime import pytz import traceback import json def getMappedObjectsJson(request, object_name, filter=None, range=0, isLive=False, force=False): """ Get the object json information to show in table or map views. """ try: try: THE_OBJECT = LazyGetModelByName(getat...
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def generate_grid_ds( ds, axes_dims_dict, axes_coords_dict=None, position=None, boundary_discontinuity=None, pad="auto", new_name=None, ): """ Add c-grid dimensions and coordinates (optional) to observational Dataset Parameters ---------- ds : xarray.Dataset Dataset...
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def slugify(value): """Coerce a value to a slug.""" if value is None: raise vol.Invalid("Slug should not be None") slg = utility_slugify(str(value)) if len(slg) > 0: return slg raise vol.Invalid("Unable to slugify {}".format(value))
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def is_td3_policy(policy): """Check whether a policy is for designed to support TD3.""" return policy in [ TD3FeedForwardPolicy, TD3GoalConditionedPolicy, TD3MultiFeedForwardPolicy, ]
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def get_generator(): """ construct and return generator """ g_net = gluon.nn.Sequential() with g_net.name_scope(): g_net.add(gluon.nn.Conv2DTranspose( channels=512, kernel_size=4, strides=1, padding=0, use_bias=False)) g_net.add(gluon.nn.BatchNorm()) g_net.add(gluon.nn.L...
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from typing import Type def is_wrapped(env: Type[gym.Env], wrapper_class: Type[gym.Wrapper]) -> bool: """ Check if a given environment has been wrapped with a given wrapper. :param env: Environment to check :param wrapper_class: Wrapper class to look for :return: True if environment has been wrap...
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def get_appliance_nat_maps( self, ne_id: str, cached: bool, ) -> dict: """Get Edge Connect appliance NAT maps configuration .. list-table:: :header-rows: 1 * - Swagger Section - Method - Endpoint * - nat - GET - /nat/{neId}/maps?cache...
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def status() -> str: """Returns the status battery ('Full', 'Charging' or 'Discharging')""" return _get_value("status")
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def half_gauss_density(data, sd): """ Takes a sequence of spike times and produces a non-normalised density estimate by summing Half-gaussian (asymetric) defined by sd at each spike time. The range of the output is guessed from the extent of the data (which need not be ordered), the resolution is autom...
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import json def json_loader(file) -> dict: """ Returns json data given a valid filepath. Returns {} if error occurs """ try: with open(file) as my_file: data = my_file.read() return json.loads(data) except Exception as e: capture_message(str(e), level="error") return error_msg("T...
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def get_user_by_email(db_session: Session, email: str) -> Users: """Get the User from its email.""" return db_session.query(Users).filter_by(email=email).first()
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def merge_unique(list1, list2): """ Merge two list and keep unique values """ for item in list2: if item not in list1: list1.append(item) return list1
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def increment(number: int) -> int: """Increment a number. Args: number (int): The number to increment. Returns: int: The incremented number. """ return number + 1
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def mi(T, Y, num_classes=10): """ Computes the mutual information I(T; Y) between predicted T and true labels Y as I(T;Y) = H(Y) - H(Y|T) = H_Y - H_cond_YgT @param T: vector with dimensionality (num_instances,) @param Y: vector with dimensionality (num_instances,) @param num_classes: number of c...
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import xml def render(canvas, fobj=None, animation=False): """Render the SVG representation of a canvas. Parameters ---------- canvas: :class:`toyplot.canvas.Canvas` The canvas to be rendered. fobj: file-like object or string, optional The file to write. Use a string filepath to wri...
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def by_dist_time_speed( move_data, label_id=TRAJ_ID, max_dist_between_adj_points=3000, max_time_between_adj_points=7200, max_speed_between_adj_points=50.0, drop_single_points=True, label_new_tid=TID_PART, inplace=True, ): """ Splits the trajectories into segments based on distanc...
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import tqdm def timelockanalysis(data, trials=None): """Prototype function for averaging :class:`~syncopy.AnalogData` across trials Parameters ---------- data : Syncopy :class:`~syncopy.AnalogData` object Syncopy :class:`~syncopy.AnalogData` object to be averaged across trials trials ...
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def generate_navigator_js(os=None, navigator=None, platform=None, device_type=None): """ Generates web navigator's config with keys corresponding to keys of `windows.navigator` JavaScript object. :param os: limit list of oses for generation :type os: string or list/tuple o...
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def stillinger_weber_neighborlist(displacement, box_size=None, A=7.049556277, B=0.6022245584, p=4, lam=21.0, epsilon...
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def sentences(s): """Split the string s into a list of sentences.""" try: s + "" except TypeError: print "s must be a string" pos = 0 sentence_list = [] l = len(s) while pos < l: try: p = s.index('.', pos) except: p = l + 1 try:...
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import functools def skip_if_import_exception(function): """Assist in skipping tests failing because of missing dependencies.""" @functools.wraps(function) def wrapper(*args, **kwargs): try: return function(*args, **kwargs) except ImportError as err: pytest.skip(str...
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def closest_pair(points): """ input: a list of points represented by tuples (x_coordinate, y_coordinate) output: a tuple(the closest distance, the closest pair) runtime: O(nlog(n)) """ # sort only once, keep the sorted copy points_x = sorted(points, key=lambda p: p[0]) # sort by x_coordinat...
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def CPP(record): """ "Channel Process if Passive": a CP input link will be treated as a channel access link and if the linking record is passive, the linking passive record will be processed any time the linked record is updated. Example (Python source) ----------------------- `my_record.IN...
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def get_mcc_lite_v3(df_c, df_mc, base_call_cutoff): """ """ # get mcc matrix with kept bins and nan values for low coverage sites df_c_nan = df_c.copy() df_c_nan[df_c < base_call_cutoff] = np.nan df_mcc = df_mc/df_c_nan return df_mcc
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from typing import Optional from typing import Sequence from typing import get_args def main(args: Optional[Sequence[str]] = None) -> int: """Main entrypoint.""" parsed_args, remainder_args = get_args(args=args) # Detect which CI environment, if any, we are in ci_env = detect_ci_platform(parsed_args,...
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def hist(x, bins=500, title=None, show=0, stats=0, ax=None, fig=None, w=1, h=1, xlims=None, ylims=None, xlabel=None, ylabel=None): """Histogram. `stats=True` to print mean, std, min, max of `x`.""" def _fmt(*nums): return [(("%.3e" % n) if (abs(n) > 1e3 or abs(n) < 1e-3) else (...
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def GetJValuesDataset( FileStr='GEOSChem.JValues.*', wd=None ): """ Wrapper to get NetCDF photolysis rates (Jvalues) output as a Dataset Parameters ---------- wd (str): Specify the wd to get the results from a run. FileStr (str): a str for file format with wildcards (?, *) Returns -----...
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def _h1_pdf_convex_decreasing_ ( h1 , degree , *args , **kwargs ) : """Parameterize/fit histogram with convex decreasing polynomial >>> h1 = ... >>> results = h1.pdf_convex_decreasing ( 3 ,) >>> results = h1.pdf_convex_decreasing ( 3 , draw = True , silent = True ) >>> print results[ 0] ## fit r...
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def create_read_supported_services_cmd() -> list: """Create TaiSEIA device services request protocol data.""" return SAInfoRequestPacket.create( sa_info_type=SARegisterServiceIDEnum.READ_SUPPORTED_SERVICES ).to_pdu()
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import re def normalize_name(name: str) -> str: """Replace hyphen (-) and slash (/) with underscore (_) to generate valid C++ and Python symbols. """ name = name.replace('+', '_PLUS_') return re.sub('[^a-zA-Z0-9_]', '_', name)
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def cross_validation(*, task, pipeline, X, y, cv_method, metrics, inverse=None): """ Performs cross validation. ------------------------- Parameters ...
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def generate_host_key(args): """Generate SSH host keys with ssh-keygen.""" key_paths = [ args.output_dir / ssh_host_key_filename(algorithm) for algorithm, _ in HOST_KEYS ] okay = True for key_path in key_paths: if key_path.exists(): LOG.error('attempt to overwrit...
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from typing import Optional def get_replication_configuration(registry_id: Optional[str] = None, opts: Optional[pulumi.InvokeOptions] = None) -> AwaitableGetReplicationConfigurationResult: """ The AWS::ECR::ReplicationConfiguration resource configures the replication destinat...
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import json def _GetTokenScopes(access_token): """Return the list of valid scopes for the given token as a list.""" url = _OAUTH2_TOKENINFO_TEMPLATE.format(access_token=access_token) response = apitools_base.MakeRequest( apitools_base.GetHttp(), apitools_base.Request(url)) if response.status_c...
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def sample(f1, f2, f3, f4): """ @see: field 1 @note : is it a field? has space before colon @param f1: field 3 with an arg @type f1: integer @param f2 : is it a field? has space before colon @return: some value @param f3: another one """ return 1
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def read_tree(attributes, data): """ Read the attibutes and create the pickle and tree files """ att_trees = [] index = 0 for attribute in attributes: if attributes[attribute].get('qi', False): if attributes[attribute].get('category', False): categories = get_...
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def cexpr_operands(self): """ return a dictionary with the operands of a cexpr_t. """ if self.op >= cot_comma and self.op <= cot_asgumod or \ self.op >= cot_lor and self.op <= cot_fdiv or \ self.op == cot_idx: return {'x': self.x, 'y': self.y} elif self.op == cot_tern: ...
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def live_ticket(db, live_taxpayer): """Return an authentication ticket usable with AFIP's test servers. AFIP doesn't allow requesting tickets too often, so we after a few runs of the test suite, we can't generate tickets any more and have to wait. This helper generates a ticket, and saves it to disk i...
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def define_model(): """ This model is a little less accurate than the best one I found. But it also has onlya quarter the paramenters so its a lot smaller. """ model = k.Sequential() model.add(k.layers.Conv2D(filters=15, kernel_size=(3,3), strides=(1, 1), padding="valid", input_shape=(40, 24, 1)...
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def volume_opt(src, dest, require=True): """Return a volume's argument for docker run Don't use volume_opt with hard-coded linux paths, it will make Windows try and mkdir in C:\\WINDOWS\\system32 and fail. volume_opt can handle C:\\... syntax correctly. Instead, just use '-v /linux/path:/mount/point an...
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import math def _project_rf(input, output, offset_x=0, offset_y=0, return_pos=False): """Project one-hot output gradient, using back-propagation, and return its bounding box at the input.""" # create one-hot output gradient tensor, with 1 in the center (spatially) pos = [0] * len(output.shape) # index 0th bat...
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def fill_ts_missing_entries(start, end, timeseries, interpolation_method, timestep): """ :param start: "YYYY-MM-DD HH:MM:SS" the starting timestamp of the timeseries index :param end: "YYYY-MM-DD HH:MM:SS" the last timestamp of the timeseries index :param timeseries: list of [time, value] lists :pa...
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def play_game(iterations, initialize_game): """ Simulate gameplay and record number of rounds and trains used each time """ winners = [] records = {} for i in range(iterations): record = {} game, players = initialize_game() record["deck"] = game.cards record["des...
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import unittest def check_tf_min_version(min_required_version, message=""): """ Skip if tf_version < min_required_version """ config = get_test_config() reason = _append_message("conversion requires tf >= {}".format(min_required_version), message) return unittest.skipIf(config.tf_version < LooseVersio...
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from typing import Union def filt2( kernel: np.ndarray, im1: np.ndarray, reflect_style: Union[str, int, float] = "odd", ) -> np.ndarray: """ Improved version of filter2 in MATLAB, which includes reflection. Default style is 'odd'. Also can be 'even', or 'wrap'. Args: kernel: Kerne...
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def getAccountASABalance(account: Addr, assetId: Int) -> TealType.uint64: """ This subroutine returns the amount of ASA held by a certain account. Note that the asset id must also be passed in the ``foreignAssets`` field in the outer transaction (otherwise you will get a reference error) :param Add...
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import re def get_package_version(): """get version from top-level package init""" version_file = read('pywcmp/__init__.py') version_match = re.search(r"^__version__ = ['\"]([^'\"]*)['\"]", version_file, re.M) if version_match: return version_match.group(1) ra...
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def copyFilesToEOS(directory, destination, filenames): """ Copy the given filenames to EOS. Files which failed are returned so that these files can be saved and the admin can be alerted to take additional actions. Args: directory (str): Path to the directory where the files are stored locally....
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from datetime import datetime def random_date_strf() -> str: """Generate a random date.""" year = random_year() day_of_year = random_day_of_year(year=year) return datetime.strptime(f"{year}-{day_of_year}", "%Y-%j").strftime("%Y-%m-%d")
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def __sample(data, labels, sampling_rate): """subsample data""" indices = [] for i in set(labels): idxs = [x for x in range(len(labels)) if labels[x] == i] n = len(idxs) s = int(np.ceil(len(idxs) * sampling_rate)) aux = np.random.permutation(n)[0:s] indices += [idxs[x...
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def format_span_json(span): """Helper to format a Span in JSON format. :type span: :class:`~opencensus.trace.span.Span` :param span: A Span to be transferred to JSON format. :rtype: dict :returns: Formatted Span. """ span_json = { 'displayName': _get_truncatable_str(span.name), ...
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import json async def main(req: func.HttpRequest, starter: str) -> func.HttpResponse: """This function starts up the orchestrator from an HTTP endpoint. It retrieves the user requested entity state and returns it back as a HTTP response. Args: req (func.HttpRequest): An HTTP Request object, it ca...
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import math import PIL def slide_to_img(slide, new_mpp=0.5, return_np=True, return_sizes=False): """ Scale slide image based on desired microns per pixel """ old_mpp_x = np.float(slide.properties['openslide.mpp-x']) old_mpp_y = np.float(slide.properties['openslide.mpp-y']) new_mpp = np.fl...
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def get_table2(res): """ Puts columns for table 2 together in a Dataframe and adds labels Args: res(list): list of arrays containing the subject specific paramater estimates Returns: table2(Pd.DataFrame): Dataframe containing table 2 """ rownames = [ "mean...
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def decode_dist_anchor(det_residual, det_angle_cls, det_angle_res, batch_anchors_3d, is_training): """ Decode bin loss anchors: Args: det_residual: [bs, points_num, 6] det_angle_cls: [bs, points_num, -1] det_angle_res: [bs, points_num, -1] batch_anchors_3d: [bs, points_num, 7...
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def refund_query(): """ swagger-doc: 'do refund query' required: [] req: page_limit: description: 'records in one page 分页中每页条数' type: 'integer' page_no: description: 'page no, start from 1 分页中页序号' type: 'integer' order_id: description: '订单编号' ...
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from distutils.version import LooseVersion from PyQt5.QtCore import QT_VERSION_STR def qt_551_plus(): """ Return True if Qt version is 5.5.1+ """ return LooseVersion(QT_VERSION_STR) >= LooseVersion("5.5.1")
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def dist_to_pixel(val_dist, mode, d_max=D_MAX, d_min=D_MIN): """ Returns pixel value from distance measurment Args: val_dist: distance value (m) mode: 'inverse' vs 'standard' d_max: maximum distance to consider d_min: minimum distance to consider Returns: ...
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import argparse def parse_args(): """Parse command line arguements. Parameters: Nothing Returns: arguments: argparse.Namespace object An object containing all of the added arguments. Outputs: Nothing """ input_help = 'Images to tweak back to flts. Defaul...
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import math def normal_probability_plot(data): """Plot the distribution of normal probabilities of errors.""" norm = distributions.normal_distribution() n = len(data["delta_hl"]) if n <= 10: a = 3 / 8 else: a = 0.5 y = flex.sorted(flex.double(data["delta_hl"])) x = [norm....
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import time def save_data_with_time_stamp(signal): """ Save signal in time-stamped file. Creates a filename using the current time. Args: signal: array of ellipsometer readings Returns: filename of the file created """ t = time.localtime() time_stamp_name = time.strft...
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import math def calc_vega( asset_price, asset_volatility, strike_price, time_to_expiration, risk_free_rate ): """The first-order partial-derivative with respect to the underlying asset volatility of the Black-Scholes equation is known as vega. Vega refers to how the option value changes when there is ...
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import urllib import requests def get_short_doi(doi, cache={}, verbose=False): """ Get the shortDOI for a DOI. Providing a cache dictionary will prevent multiple API requests for the same DOI. """ if doi in cache: return cache[doi] quoted_doi = urllib.request.quote(doi) url = 'http...
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def calculate_payments(yearly_payments_percentage, cost_reductions, days_with_payments, days_for_discount_rate): """ Calculates payments for a participant/investor """ return [period_payment(yearly_payments_percentage, ccr, days_with_payments[i], days_for_disco...
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def draw_random(G, **kwargs): """Draw networkx graph with random layout. Parameters ---------- G : graph A networkx graph kwargs : optional keywords See hvplot.networkx.draw() for a description of optional keywords, with the exception of the pos parameter which is not us...
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def test_preprocessor_visit_one_children(patch, magic, preprocessor): """ Check that a single inline_expression is found """ tree = magic() c1 = magic() replace = magic() c1.children = [magic()] tree.children = [c1] def is_inline(n): return n == c1 preprocessor.visit(tre...
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def connect_to_contract(address): """Helper function for connecting to a contract at an address""" url = "https://mainnet.infura.io/v3/1a09c4705f114af2997548dd901d655b" endpt = RPCEndpoint(network=network, provider=provider, url=url) endpt.connect() c = Contract(node=endpt, address=address, abi=tel...
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import json import select def get_user(): """Retreives a single user from a Database, and render it using a HTML template""" try: data = json.loads(request.data) except ValueError: return '', 400 else: email = data['customer']['email'] # For more complex queries, consider ...
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def sniff( resource: bytes, mime_type_string: str = "unknown/unknown", no_sniff: bool = False, check_for_apache_bug: bool = False) -> str: """ Implementation of algorithm in: https://mimesniff.spec.whatwg.org/#determining-the-computed-mime-type-of-a-resource The main met...
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import base64 def decrypt(key, enc, use_base64=True): """Optionally base64-decode and decrypt.""" decoded = enc if use_base64: decoded = base64.b64decode(enc) raw = _cipher(key).decrypt(decoded) return _unpad(raw).decode("utf-8")
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def create_rng(random_state): """ Creates a random state object Parameters ---------- random_state : int or NoneType or np.random.RandomState Input to create RNG Returns ------- rng : np.random.RandomState Pseudo-random number generator """ if random_state is N...
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def read_header(file_handle): """Reads a CPHD header from a file. Parameters ---------- file_handle Readable File object, i.e., ``file_handle = open(filename, 'rb')``. Handle of the CPHD file that is to be read Returns ------- Dict Dictionary containing CPHD header val...
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async def validate_input(hass: core.HomeAssistant, conf): """Validate the user input allows us to connect.""" try: info = await async_get_discovery_info( hass, conf[CONF_HOST], conf[CONF_PORT], conf.get(CONF_SECURE, False), conf[CONF_ACCESS_TOK...
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def read(): """Return the contents of the Windows Common Setup as a string""" setup_in = open(PATH) try: return setup_in.read() finally: setup_in.close()
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from typing import List def longest_subarray(numbers: List[int], limit: int) -> int: """https://leetcode.com/problems/longest-continuous-subarray-with-absolute-diff-less-than-or-equal-to-limit/""" # monotone increasing queue with indices that could become the sliding window minimum min_queue = deque() ...
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def ris_defaultValue_get(fieldsTuple): """ params: fieldsTuple, () return: fieldVaule_dict, {} """ # ris_element = fieldsTuple[0] if len(fieldsTuple[1]) != 0: default_value = fieldsTuple[1][0] else: default_value = [] fieldValue_dict = {} fieldValue_dict[ris_eleme...
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import torch def project_to_2d(X, camera_params): """ Project 3D points to 2D using the Human3.6M camera projection function. This is a differentiable and batched reimplementation of the original MATLAB script. Arguments: X -- 3D points in *camera space* to transform (N, *, 3) camera_para...
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import csv def read_header_keywords_table(filepath): """ Read a table of .fits keywords from a .csv file into a HeaderKeywordList of HeaderKeyword objects. :param filepath: The location of the .csv file containing the header keyword table. :type filepath: str """ # Op...
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def compara(chave, lst): """Compara usuários da lista lst através da chave A comparacão ocorre montando um dicionário de listas de usuário temporáriamente em dic. Uma vez que todo o dicionário está montado os índices do dicionário que contém mais do que um elemento são copiados para o dicionário de...
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from typing import List def exists(bucket: str, key: str) -> bool: """Checks if there is an object in the object store with the given key Args: bucket (dict): Bucket containing data key (str): Prefix for key in object store Returns: bool: True if exists in store """ # Get ...
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def format_element_to_matlab_confusion_matrix(row, col, confusion_matrix): """ Return a string for the element on row, col location for confusion_matrix to either number of observation\npercentage of observations or percentage_correct_classifications\npercentage_incorrect_classifications per cla...
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def add_lazy_nh4_pm25(d, dict_sum): """Calculates sum of particulate NH4. Parameters ---------- d : xarray.Dataset RRFS-CMAQ model data Returns ------- xarray.Dataset RRFS-CMAQ model data including new NH4 calculation """ keys = _get_keys(d) allvars = Series(di...
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def record(episode, episode_reward, worker_idx, global_ep_reward, total_loss, num_steps): """Helper function to store score and print statistics. Arguments: episode: Current episode episode_reward: Reward accumulated over the current episode ...
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from scipy.spatial import cKDTree from scipy.stats import entropy def transform_cav2im3d_entropy(cavity_coords, grid_min, grid_shape, pharmaco): """ Takes coordinates of grid points and outputs an im3d for skimage Uses entropy at 3A of pharmacophores as values to set the "greyscale" """ # First we simply the ph...
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def _normalize_title(key: str) -> str: """MediaWiki treats the first character of article names as upper-case.""" if not key: # Empty string return "" key = _normalize_spaces(key) return key[0].upper() + key[1:]
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def n_coeffs_to_degree(n_coeffs): """what is degree if 2d polynomial has n_coeffs coefficients""" delta_sqrt = int((8 * n_coeffs + 1.)**.5 + 0.5) if delta_sqrt**2 != (8*n_coeffs+1.): raise ValueError('Wrong input in n_coeffs_to_degree(): {:}'.format(n_coeffs)) return int((delta_sqrt - 3.) / 2. +...
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def load(): """Loads settings static configuration. As the configuration is static and immutable, it is loaded only once from the disk. Returns an instance of the `Settings` class. """ global _SETTINGS if _SETTINGS is not None: return _SETTINGS s = _load_yaml(SUBSTRA_TESTS_CONFIG_...
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def modinv(a, b): """ Returns x such that (x * a) (mod b) == 1 reference: https://stackoverflow.com/questions/4798654/modular-multiplicative-inverse-function-in-python """ g, x, _ = egcd(a, b) if g != 1: raise Exception('modular inverse does not exist') else: return x % b
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def keygen(): """ Generate private and public keys for the "greased", bootstrappable encryption scheme. The main idea here is that we want to minimize computation during decryption because it originally contains an expensive modulus operation (c % p) that is too much for our somewhat homomorphic en...
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def process_image(image_path): """ Given a path to a file, pre-process that image in preparation for making a prediction. :param image_path: the path to the image file :return: the image represented by a flattened numpy array """ im_transforms = TRANSFORM_TEST_VALIDATION # Open image im = Image.open(image_path...
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import hashlib def checksum_md5(filename, blocksize=8192): """Calculate md5sum. Parameters ---------- filename : str or pathlib.Path input filename. blocksize : int MD5 has 128-byte digest blocks (default: 8192 is 128x64). Returns ------- md5 : str calculated ...
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from pyunifi.controller import Controller, APIError def setup_platform(hass, config, add_entities, discovery_info=None): """Set up the Unifi Controller.""" host = config.get(CONF_HOST) username = config.get(CONF_USERNAME) password = config.get(CONF_PASSWORD) site_id = config.get(CONF_SITE_ID) ...
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