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def get_objective_by_task(target, task): """Returns an objective and a set of metrics for a specific task.""" if task == 'classification': if target.nunique() == 2: objective = 'binary' else: objective = 'multi' elif task == 'regression': objective = 'regressi...
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def pileupGenes(GenePositions,filename,pad=500000,doBalance=False, TPM=0,CTCFWapldKO=False,TPMlargerthan=True, minlength=0,maxlength=5000000,OE=None, useTTS=False): """ This function piles up Hi-C contact maps around genes, centered on TSSs or TTSs. Inputs ------ Gene...
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def model_cnn_2layer(in_ch, in_dim, width, linear_size=128): """ CNN, small 2-layer (default kernel size is 4 by 4) Parameter: in_ch: input image channel, 1 for MNIST and 3 for CIFAR in_dim: input dimension, 28 for MNIST and 32 for CIFAR width: width multiplier """ model = nn...
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def reserve_api(): """Helper function for making API requests to the /reserve API endpoints :returns: a function that can be called to make a request to /reserve """ def execute_reserve_api_request(method, endpoint, **kwargs): master_api_client = master_api() return master_api_client(me...
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import re def extract_user_id(source_open_url): """ extract the user id from given user's id :param source_open_url: "sslocal://profile?refer=video&uid=6115075278" example :return: """ if source_open_url[10:17] != 'profile': return None try: res = re.search("\d+$", source_...
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def prolog_rule(line): """Specify prolog equivalent""" def specify(rule): """Apply restrictions to rule""" rule.prolog.insert(0, line) return rule return specify
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def load_GloVe_model(path): """ It is a function to load GloVe model :param path: model path :return: model array """ print("Load GloVe Model.") with open(path, 'r') as f: content = f.readlines() model = {} for line in content: splitLine = line.split() word = ...
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import numpy def quadratic_program() -> MPQP_Program: """a simple mplp to test the dimensional correctness of its functions""" A = numpy.array( [[1, 1, 0, 0], [0, 0, 1, 1], [-1, 0, -1, 0], [0, -1, 0, -1], [-1, 0, 0, 0], [0, -1, 0, 0], [0, 0, -1, 0], [0, 0, 0, -1]]) b = numpy.array([350, 6...
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def snr(flux, axis=0): """ Calculates the S/N ratio of a spectra. Translated from the IDL routine der_snr.pro """ signal = np.nanmedian(flux, axis=axis) noise = 1.482602 / np.sqrt(6.) * np.nanmedian(np.abs(2.*flux - \ np.roll(flux, 2, axis=axis) - np.roll(flux, -2, axis=axis)), \ ...
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def subtract_images(img_input, img_output, img_height, img_width): """Subtract input and output image and compute difference image and ela image""" input_data = img_input.T output_data = img_output.T if len(input_data) != len(output_data): raise Exception("Input and Output image have different s...
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import ctypes def k4a_playback_get_track_name(playback_handle, track_index, track_name, track_name_size): """ K4ARECORD_EXPORT k4a_buffer_result_t k4a_playback_get_track_name(k4a_playback_t playback_handle, size_t track_index, char *track_name, size_t *track_name_si...
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def recommend_lowercase_d(data: pd.Series, **kwargs) -> int: """Returns the recommended value of differencing order 'd' to use Parameters ---------- data : pd.Series The data for which the differencing order needs to be calculated *kwargs: Keyword arguments that can be passed to the differ...
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from typing import Dict import json def get_player_current_games_to_move(username: str) -> Dict: """Public method that returns an array of Daily Chess games where it is the player's turn to act Parameters: username -- username of the player """ r = _internal.do_get_request(f"/player/{use...
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def get_rb_data_attribute(xmldict, attr): """Get Attribute `attr` from dict `xmldict` Parameters ---------- xmldict : dict Blob Description Dictionary attr : str Attribute key Returns ------- sattr : int Attribute Values """ try: sattr = int(xml...
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def tls_params(mqtt_config): """Return the TLS configuration parameters from a :class:`.MQTTConfig` object. Args: mqtt_config (:class:`.MQTTConfig`): The MQTT connection settings. Returns: dict: A dict {'ca_certs': ca_certs, 'certfile': certfile, 'keyfile': keyfile} with the TL...
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def is_admin(): """Check if current user is an admin.""" try: return flask.g.admin except AttributeError: return False
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def statistic(): """ RESTful CRUD Controller """ return crud_controller()
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def segment_range_to_fragment_range(segment_start, segment_end, segment_size, fragment_size): """ Takes a byterange spanning some segments and converts that into a byterange spanning the corresponding fragments within their fragment archives. Handles prefix, suff...
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import collections def update_dict(d, u): """ Recursively update dict d with values from dict u. Args: d: Dict to be updated u: Dict with values to use for update Returns: Updated dict """ for k, v in u.items(): if isinstance(v, collections.Mapping): default ...
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def get_dataset(args, tokenizer, evaluate=False): """Convert the text file into the GPT-2 TextDataset format. Args: tokenizer: The GPT-2 tokenizer object. evaluate: Whether to evalute on the dataset. """ file_path = args.eval_data_file if evaluate else args.train_data_file if args.l...
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def test_function_decorators(): """Function Decorators.""" # Function decorators are simply wrappers to existing functions. Putting the ideas mentioned # above together, we can build a decorator. In this example let's consider a function that # wraps the string output of another function by p tags. ...
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def make_loci_field( loci ): """ make string representation of contig loci """ codes = [L.code for L in loci] return c_delim2.join( codes )
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import tqdm def compute_wilderness_impact1(ground_truth_all, prediction_all, video_list, known_classes, tiou_thresholds=np.linspace(0.5, 0.95, 10)): """ Compute wilderness impact for each video (WI=Po/Pc < 1) """ wi = np.zeros((len(tiou_thresholds), len(known_classes))) # # Initialize true positive a...
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def require_client(func): """ Decorator for class methods that require a client either through keyword argument, or through the object's client attribute. Returns: A wrapped version of the function. The object client attrobute will be passed in as the client keyword if None is provided....
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import base64 def format_template(string, tokens=None, encode=None): """Create an encoding from given string template.""" if tokens is None: tokens = {} format_values = {"config": config, "tokens": tokens} result = string.format(**format_values) if encode == "base64":...
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import six def make_datastore_api(client): """Create an instance of the GAPIC Datastore API. :type client: :class:`~google.cloud.datastore.client.Client` :param client: The client that holds configuration details. :rtype: :class:`.datastore.v1.datastore_client.DatastoreClient` :returns: A datast...
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def _mul_certain(left, right): """Multiplies two values, where one is certain and the other is uncertain, and returns the result.""" if _is_number(left): return Uncertain( value=right.value * left, delta=right.delta, ) return Uncertain( value=lef...
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def felica_RequestSystemCode(): # -> (int, List[int]): """ Sends FeliCa Request System Code command :returns: (status, systemCodeList) status 1: Success, < 0: error systemCodeList System Code list (Array length should longer than 16) """ cmd = bytearra...
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from typing import Optional from typing import Callable import types def get_regularizer( regularizer_type: str, l_reg_factor_weight: float ) -> Optional[Callable[[tf.Tensor], Optional[tf.Tensor]]]: """Gets a regularizer of a given type and scale. Args: regularizer_type: One of types.RegularizationType ...
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def metadata(): """Returns shared metadata instance with naming convention.""" naming_convention = { 'ix': 'ix_%(column_0_label)s', 'uq': 'uq_%(table_name)s_%(column_0_name)s', 'ck': 'ck_%(table_name)s_%(constraint_name)s', 'fk': 'fk_%(table_name)s_%(column_0_name)s_%(referred_ta...
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import time def date_rss(dte=None): """Dtate au format RSS """ ctime = time if dte is None else time.mktime(dte.timetuple()) return ctime.strftime('%a, %d %b %Y %H:%M:%S %z')
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def generate_parallelogrammatic_board(width=5, height=5): """ Creates a board with a shape of a parallelogram. Width and height specify the size (in fields) of the board. """ return [[1] * height for _ in range(width)]
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def function_is_even(latex_dict: dict) -> str: """ colloquially, sympy.cos(x)==sympy.cos(-x) sympy.cos(x) - sympy.cos(-x) == 0 >>> latex_dict = {} >>> latex_dict['input'] = [{'LHS': parse_latex(''), 'RHS': parse_latex('')}] >>> latex_dict['feed'] = [parse_latex('')] >>> latex_dict['out...
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def summarize_curriculum( curriculum: AbstractCurriculum, ) -> str: """ Generate a detailed string summarizing the contents of the curriculum. :return: A string that would print as a formatted outline of this curriculum's contents. """ def maybe_plural(num: int, label: str): return f"{...
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def get_solarsample(): """ NAME: get_solarsample PURPOSE: get the RC sample at solar abundances INPUT: None so far OUTPUT: sample HISTORY: 2015-03-18 - Started - Bovy (IAS) """ # Get the full sample first data= get_rcsample() # Now cut it lo...
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from typing import List def perform_context_selection( estimation_tasks: List[EstimationTask], ) -> List[EstimationTask]: """Changes the circuits in estimation tasks to involve context selection. Args: estimation_tasks: list of estimation tasks """ output_estimation_tasks = [] for est...
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import torch def where(condition, x, y): """Wrapper of `torch.where`. Parameters ---------- condition : DTensor of bool Where True, yield x, otherwise yield y. x : DTensor The first tensor. y : DTensor The second tensor. """ return torch.where(condition, x, y)
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def ukhls_wave_prefix(columns, year): """ Determine wave prefix for ukhls wave data. Parameters ---------- columns : list A list of column names to add wave prefixes to. year : int Which wave year is being processed. Returns ------- columns : list Column names w...
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from typing import Iterable from typing import Optional from typing import List from typing import cast def sort_converters(converters: Iterable[Optional[GenericConverter]]) -> List[GenericConverter]: """ Sort a list of converters according to their priority. """ converters = cast(Iterable[GenericConv...
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def createPolygon(fire): """ create a Polygon object from list of points """ points = [] for coordinate in fire["geometry"]["coordinates"][0]: points.append(tuple(coordinate)) polygon = Polygon(points) return polygon
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def change_anim_nodes(node_object="", in_tangent='linear', out_tangent='linear'): """ Changes the setting on all anim nodes. :param node_object: :param in_tangent: :param out_tangent: :return: <bool> True for success. <bool> False for failure. """ anim_nodes = object_utils.get_connected_...
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def is_x_degenerated(x, codon, table): """Determine if codon is x-fold degenerated. @param codon the codon @param table code table id @param true if x <= the degeneration of the codon """ return (x <= len(altcodons(codon, table)))
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import torch def get_long_tensor(tokens_list, batch_size, pad_id=constant.PAD_ID): """ Convert (list of )+ tokens to a padded LongTensor. """ sizes = [] x = tokens_list while isinstance(x[0], list): sizes.append(max(len(y) for y in x)) x = [z for y in x for z in y] tokens = torch.L...
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def business(): """ show business posts """ business = Post.query.filter_by(category="Business").all() return render_template('business.html', post=business)
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def tile_image(x_gen, tiles=()): """Tiled image representations. Args: x_gen: 4D array of images (n x w x h x 3) tiles (int pair, optional): number of rows and columns Returns: Array of tiled images (1 x W x H x 3) """ n_images = x_gen.shape[0] if not tiles: for i in range(int(np.sqrt(n_im...
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def note_updated_data(note, role): """Return the data for updated date :param note: the note that holds the data :type note: :class:`jukeboxcore.djadapter.models.Note` :param role: item data role :type role: QtCore.Qt.ItemDataRole :returns: data for the updated date :rtype: depending on rol...
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def _xyz_atom_coords(atom_group): """Use this method if you need to identify if CB is present in atom_group and if not return CA""" tmp_dict = {} for atom in atom_group.atoms(): if atom.name.strip() in {"CA", "CB"}: tmp_dict[atom.name.strip()] = atom.xyz if 'CB' in tmp_dict: ...
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import pathlib def InitBareRepository(path): """Returns the Repo object""" assert isinstance(path, str) pathlib.Path(path).parent.mkdir(parents=True,exist_ok=True) return git.Repo.init(path,bare=True)
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def get_http_exception(code): """Return an exception class based on its code""" try: return http_exceptions[int(code)] except: return None
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from typing import Union def _gradients_input(model: Union[tf.keras.models.Model, 'keras.models.Model'], x: tf.Tensor, target: Union[None, tf.Tensor]) -> tf.Tensor: """ Calculates the gradients of the target class output (or the output if the output dimension is equal...
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from typing import OrderedDict def get_databases(): """Return an ordered dict of (dbname: database). The order is according to search preference, the first DB to contain a document should be assumed to be the authoritative one.""" sql_dbs = [ _SQLDb( XFormInstanceSQL._meta.db_table...
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def list_examples(): """List all examples""" examples = ExampleModel.query() form = ExampleForm() if form.validate_on_submit(): example = ExampleModel( example_name=form.example_name.data, example_description=form.example_description.data, added_by=users.get_c...
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import re def parse_direct_mention(message_text): """ Finds a direct mention (a mention that is at the beginning) in message text and returns the user ID which was mentioned. If there is no direct mention, returns None """ matches = re.search(_MENTION_REGEX, message_text) # the first g...
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import types def prepare_deep(schema: types.Schema, schemas: types.Schemas): """ Resolve $ref and merge allOf including for object properties and items. Assume the schema is a valid JSONSchema. Args: schema: The schema to prepare. schemas: The schemas from which to resolve any $ref. ...
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def _resize_and_center_fundus(image, diameter): """ Helper function for scale normalizing image. """ copy = image.copy() # Find largest contour in image. contours = _find_contours(image) # Return unless we have gotten some result contours. if contours is None: return None ...
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def _pad_X_delta(X, delta, indices, padded_group_size): """Currently Unused.""" X_group = onp.take(X, indices, axis=0) X_group = onp.pad(X_group, [(0, padded_group_size - X_group.shape[0]), (0, 0)]) delta_group = onp.take(delta, indices, axis=0) delta_group = onp.pad(delta_group...
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def union(x, y=None): """Get sorted list of elements combined for two iterables.""" x, y = de_list_pair(x, y) return sorted(list(set(x) | set(y)))
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from typing import get_origin from typing import Tuple def is_tuple(typ) -> bool: """ Test if the type is `typing.Tuple`. """ try: return issubclass(get_origin(typ), tuple) except TypeError: return typ in (Tuple, tuple)
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import functools import unittest def _skip_if(cond, reason): """Skip test if cond(self) is True""" def decorator(impl): @functools.wraps(impl) def wrapper(self, *args, **kwargs): if cond(self): raise unittest.SkipTest(reason) else: impl(s...
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def permute_columns(df, column_to_order: str, ind_permute: bool = False, columns_to_permute: list = []): """ Author: Allison Wu Description: This function permutes the columns specified in columns_to_permute :param df: :param column_to_orde...
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def reset_dismissed(institute_id, case_name): """Reset all dismissed variants for a case""" institute_obj, case_obj = institute_and_case(store, institute_id, case_name) controllers.reset_all_dimissed(store, institute_obj, case_obj) return redirect(request.referrer)
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def texts_from_array(x_train, y_train, x_test=None, y_test=None, class_names = [], max_features=MAX_FEATURES, maxlen=MAXLEN, val_pct=0.1, ngram_range=1, preprocess_mode='standard', verbose=1): """ Loads and preprocesses text data from arrays. Args: ...
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def display2(depts, level=0): """ [[a, 1], [b, 2], [c, 3], [d, 3], [a, 1]] :param depts: :return: """ lists = [] for d in depts: lists.append([d, level]) children = Department.objects.filter(parent_id=d.id) if children: lists.extend(display2(children, leve...
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def _get_target_id_to_skill_opportunity_dict(suggestions): """Returns a dict of target_id to skill opportunity summary dict. Args: suggestions: list(BaseSuggestion). A list of suggestions to retrieve opportunity dicts. Returns: dict. Dict mapping target_id to corresponding skil...
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def default_loc_scale_fn( is_singular=False, loc_initializer=tf.random_normal_initializer(stddev=0.1), untransformed_scale_initializer=tf.random_normal_initializer( mean=-3., stddev=0.1), loc_regularizer=None, untransformed_scale_regularizer=None, loc_constraint=None, untransformed_s...
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from skimage.morphology import disk from cv2 import dilate def db_eval_boundary(args): """ Compute mean,recall and decay from per-frame evaluation. Calculates precision/recall for boundaries between foreground_mask and gt_mask using morphological operators to speed it up. Arguments: f...
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def angle_trunc(a): """ helper function to map all angles onto [-pi, pi] """ while a < 0.0: a += pi * 2 return ((a + pi) % (pi * 2)) - pi
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from typing import Optional def get_tag_or_default( alignment: pysam.AlignedSegment, tag_key: str, default: Optional[str] = None ) -> Optional[str]: """Extracts the value associated to `tag_key` from `alignment`, and returns a default value if the tag is not present.""" try: return alignment.g...
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def vtln_warp_mel_freq(vtln_low_cutoff, vtln_high_cutoff, low_freq, high_freq, vtln_warp_factor, mel_freq): """ Inputs: vtln_low_cutoff (float): lower frequency cutoffs for VTLN vtln_high_cutoff (float): upper frequency cutoffs for VTLN low_freq (float): lower freq...
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def _squared_loss_and_spatial_grad_derivative(X, y, w, mask, grad_weight): """ Computes the derivative of _squared_loss_and_spatial_grad. Parameters ---------- X : ndarray, shape (n_samples, n_features) Design matrix. y : ndarray, shape (n_samples,) Target / response vector. ...
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import ctypes def destructor(cfunc): """ Make a C function a destructor. Destructors accept pointers to void pointers as argument. They are also wrapped as a staticmethod for usage in classes. :param cfunc: The C function as imported by ctypes. :return: The configured destructor. """ ...
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def invalid_auth_header(jwt): """Produce invalid JWT tokens for use in tests.""" return {'Authorization': 'Bearer ' + jwt.create_jwt(claims=TestJwtClaims.invalid, header=JWT_HEADER)}
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def update_file_info_in_job(job, file_infos): """ Update the 'setup.package.fileInformations' data in the JSON to append new file information. """ for file_info in file_infos: try: job['setup']['package']['fileInformations'].append(file_info) except (KeyError, TypeError, Attr...
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def _FirstStatementsInScriptElements(contents): """Returns a list of first statements found in each <script> element.""" soup = parse_html.BeautifulSoup(contents) script_elements = soup.find_all('script', src=None) return [_FirstStatement(e.get_text()) for e in script_elements]
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def load_image(input_file_path): """ Load the 'input_file_path' and return a 2D numpy array of the image it contains. """ image_array = np.array(pil_img.open(input_file_path).convert('L')) return image_array
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def ask_the_user(runner: Runner) -> Direction: """Ask the user what to do (in absolute UP, DOWN, etc.)""" return runner.ask_absolute()
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def optimize_spot_bid(ctx, instance_type, spot_bid): """ Check whether the bid is sane and makes an effort to place the instance in a sensible zone. """ spot_history = _get_spot_history(ctx, instance_type) if spot_history: _check_spot_bid(spot_bid, spot_history) zones = ctx.ec2.get_all_z...
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def new_hassle_participants(): """Select participants for the room helpers.""" # Get a list of all current members. members = helpers.get_all_members() return flask.render_template('hassle_new_participants.html', members=members)
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import json def data_store_remove_folder(request): """ remove a sub-folder/sub-collection in hydroshareZone or any federated zone used for HydroShare resource backend store. It is invoked by an AJAX call and returns json object that include a status of 'success' if succeeds, and HttpResponse of status...
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import math def distance(x1: float, y1: float, x2: float, y2: float) -> float: """ Finds distance between two given points Parameters: x1, y1 : The x and y coordinates of first point x2, y2 : The x and y coordinates of second point Returns: ...
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def load_target_class(input_dir): """Loads target classes.""" df = pd.read_csv(join(input_dir, "target_class.csv"), header=None, index_col=0, names=["Target"]) return df
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def fix_labels(ply_gt, ply_seg): """ Remove extra vertices from the ground truth """ size = len(ply_gt.elements[0]["x"]) gt_x = np.array(ply_gt.elements[0]["x"]) seg_x = np.array(ply_seg.elements[0]["x"]) new_gt_label = np.zeros_like(seg_x) gt_label = np.array(ply_gt.elements[0]["labe...
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import requests def get_coin_price(api_url: str, currency: str) -> float: """ Get the USD price of a coin from Gemini Args: api_url: The API URL for Gemini currency: The cryptocurrency the bot is monitoring Returns: coin_price: The price the coin currently holds in USD """ # Inst...
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import hmac import base64 def GenerateAuthToken(key_name, user_id, action_id='', when=None): """Generates a URL-safe token based on XSRFToken but for generla purpose. Args: key_name (str): name of secret key to generate token. user_id (str): the user ID of the authenticated user. action_id (str): a s...
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import torch def get_dataset_psnr(device, model, dataset, source_img_idx_shift=64, batch_size=10, max_num_scenes=None): """Returns PSNR for each scene in a dataset by comparing the view predicted by a model and the ground truth view. Args: device (torch.device): Device to per...
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def smallest_continuous_multiple(max_multiple): """ Function takes an int, and returns the smallest natural number evenly divisible by all numbers less than or equal to the input max_multiple. REQ: max_multiple >= 0 and whole :param max_multiple: {int} :return: smallest natural number evenly d...
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def context_list_entities(context): """ Returns list of entities to be displayed in list view """ # log.info(context['List_rows']) if 'List_rows' in context: return context['List_rows']['field_value'] elif 'entities' in context: return context['entities'] log.warning("No enti...
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def run(arg): """Entry point""" error_map = {} validate_path(arg, None, error_map) if len(error_map) > 0: error_count = 0 for file, errors in error_map.items(): print(f"Error in {file}:") for error in errors: print(f" {error}") e...
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import struct def _bitcode_symbols_partial_impl( *, actions, binary_artifact, bitcode_symbol_maps, dependency_targets, label_name, output_discriminator, package_bitcode, platform_prerequisites): """Implementation for the bitcode symbols proce...
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def _str_trim_left(x): """ Remove leading whitespace. """ return x.str.replace(r"^\s*", "")
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def zipcompress(items_list, flags_list): """ SeeAlso: vt.zipcompress """ return [compress(list_, flags) for list_, flags in zip(items_list, flags_list)]
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def test_config_file_fails_missing_value(monkeypatch, presence, config): """Check if test fails with missing value in database configuration.""" def mock_file_config(self): return {'database': {}} monkeypatch.setattr(presence.builder, "fetch_file_config", mock_file_config) status, msg = presen...
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def construct_run_config(iterations_per_loop): """Construct the run config.""" # Parse hparams hparams = ssd_model.default_hparams() hparams.parse(FLAGS.hparams) return dict( hparams.values(), num_shards=FLAGS.num_shards, num_examples_per_epoch=FLAGS.num_examples_per_epoch, resnet_ch...
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def bezier_curve(points, nTimes=1000): """ Given a set of control points, return the bezier curve defined by the control points. Control points should be a list of lists, or list of tuples such as [ [1,1], [2,3], [4,5], ..[Xn, Yn] ] nTimes is ...
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def _compact_temporaries(exprs): """ Drop temporaries consisting of isolated symbols. """ # First of all, convert to SSA exprs = makeit_ssa(exprs) # What's gonna be dropped mapper = {e.lhs: e.rhs for e in exprs if e.lhs.is_Symbol and (q_leaf(e.rhs) or e.rhs.is_Function)} ...
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def print_formula(elements): """ The input dictionary, atoms and their amount, is processed to produce the chemical formula as a string Parameters ---------- elements : dict The elements that form the metabolite and their corresponding amount Returns ------- formula : str ...
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def try_get_code(url): """Returns code of URL if exists in database, else None""" command = """SELECT short FROM urls WHERE full=?;""" result = __execute_command(command, (url,)) if result is None: return None return result[0]
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import unicodedata def is_chinese_char(cc): """ Check if the character is Chinese args: cc: char output: boolean """ return unicodedata.category(cc) == 'Lo'
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def resize_image(image, min_dim=None, max_dim=None, padding=False): """ Resizes an image keeping the aspect ratio. min_dim: if provided, resizes the image such that it's smaller dimension == min_dim max_dim: if provided, ensures that the image longest side doesn't exceed this value. ...
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def idwt(approx, wavelets, h=np.array([1.0 / np.sqrt(2), -1.0 / np.sqrt(2)]), g=np.array([1.0 / np.sqrt(2), 1.0 / np.sqrt(2)])): """ Simple inverse discrete wavelet transform. for good reference: http://www.mathworks.com/help/wavelet/ref/dwt.html @param approx: approximation of signal at low re...
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