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import requests def make_new_paste(devkey, paste_text, user_key=None, paste_title=None, paste_format=None, paste_type=None, paste_expiry: int=None): """This function creates a new paste on pastebin with the given arguments.""" data = {'api_dev_key': devkey, 'api_option': 'paste', 'api_paste_code': paste_...
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def not_none(value): """ This function ensures that passed value is not None: >>> schema = Schema(not_none) >>> assert 1 == schema(1) >>> try: ... schema(None) ... assert False, "an exception should've been raised" ... except MultipleInvalid: ... pass """ if val...
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def j1c_dblprime(amplitudes): """Calculate j''1c angular observable""" [_, _, _, _, a_0_l, a_0_r, a_00_l, a_00_r] = amplitudes return (2 / tf.sqrt(3.0)) * ( tf.math.real(a_00_l * tf.math.conj(a_0_l) * bw_k700_k892) + tf.math.real(a_00_r * tf.math.conj(a_0_r) * bw_k700_k892) )
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def preprocess(img): """Changes RGB [0,1] valued image to BGR [0,255] with mean subtracted.""" mean_bgr = load_mean_bgr() print 'mean blue', np.mean(mean_bgr[:, :, 0]) print 'mean green', np.mean(mean_bgr[:, :, 1]) print 'mean red', np.mean(mean_bgr[:, :, 2]) out = np.copy(img) * 255.0 out =...
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def profile_detail(request, username, template_name='userena/profile_detail.html', extra_context=None, **kwargs): """ Detailed view of an user. :param username: String of the username of which the profile should be viewed. :param template_name: String representing the template name tha...
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def prepare_ternary(figsize, scale): """Help function to ternary plot""" fig, ax = plt.subplots(figsize=figsize) tax = ternary.TernaryAxesSubplot(ax=ax, scale=scale) ax.axis('off') gm = 0.1 * scale blw = 1 tlw = 1 # Draw Boundary and Gridlines tax.boundary(linewidth=blw) tax.grid...
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from typing import Dict def parse_spreadsheet(hca_spreadsheet: Workbook, entity_dictionary: Dict): """ Parse the spreadsheet and fill the metadata with accessions. :param hca_spreadsheet: Workbook object of the spreadsheet :param entity_dictionary: Dictionary mapping by entity UUID to the proper arch...
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def decode(data): """Decode JSON serialized string, with possible embedded Python objects. """ return _decoder.decode(data)
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def p_correction(p_values): """ Corrects p_values for multiple testing. :param p_values: Dictionary storing p_values with corresponding feature names as keys. :return: DataFrame which shows the results of the analysis; p-value, corrected p-value and boolean indicating \ significance. """ p...
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def GetFlippedPoints3(paths, array): """same as first version, but doesnt flip locations: just sets to -1 used for random walks with self intersections - err type 6""" # this may not work for double ups? for i in paths: for j in i: # for the rest of the steps... array[j[0]][j[1]][j[...
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from typing import Callable async def _silent_except(f: Callable, *args, **kwargs): """ Helper Function that calls a function or coroutine and returns its result excepting all errors """ try: called = f(*args, **kwargs) except: return if isawaitable(called): try: ...
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def get_concat_h(im1, im2): """Concatenate two images horizontally.""" dst = Image.new("RGB", (im1.width + im2.width, im1.height)) dst.paste(im1, (0, 0)) dst.paste(im2, (im1.width, 0)) return dst
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def get_taxname(taxid): """Return scientific name for NCBI Taxonomy ID.""" if get_taxname.id_name_map is None: get_taxname.id_name_map = load_taxid_name_map('data/taxnames.tsv') if get_taxname.id_name_map is None: # assume fail, fallback get_taxname.id_name_map = TAXID_NAME_MAP ...
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import os def _get_movies(dir): """Gets the movies from the specified directory""" movieList = [] directories = os.listdir(dir) for d in directories: # We need to skip past directories without instruction sets if '__' not in d: continue files = os.listdir("{root}/{...
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def lrfn(epoch): """ lrfn(epoch) This function creates a custom piecewise linear-exponential learning rate function for a custom learning rate scheduler. It is linear to a max, then exponentially decays * INPUTS: current `epoch` number * OPTIONAL INPUTS: None * GLOBAL INPUTS:`START_LR`, `MIN_LR...
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import numbers def get_balances(): """ Get the balances of the configured validator (if possible) """ balances = account.get_balance_on_all_shards(validator_config['validator-addr'], endpoint=node_config['endpoint']) for bal in balances: bal['balance'] = float(numbers.convert_atto_to_one(b...
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import collections def _make_ordered_node_map( pipeline: pipeline_pb2.Pipeline ) -> 'collections.OrderedDict[str, pipeline_pb2.PipelineNode]': """Prepares the Pipeline proto for DAG traversal. Args: pipeline: The input Pipeline proto, which must already be topologically sorted. Returns: An O...
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def energy(_x, _params): """Kinetic and Potential Energy of point mass pendulum. _x is an array/list in the following order: q1: Angle of first pendulum link relative to vertical (0 downwards) u1: A[1] measure number of the inertial angular velocity of the first link. _params is an array...
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import math def gelu(input_tensor): """Gaussian Error Linear Unit. This is a smoother version of the RELU. Original paper: https://arxiv.org/abs/1606.08415 Args: input_tensor: float Tensor to perform activation. Returns: `input_tensor` with the GELU activation applied. """ #...
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import torch def KPConv_ops(query_points, support_points, neighbors_indices, features, K_points, K_values, KP_extent, KP_influence, aggregation_mode): """ This function creates a graph of op...
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def kerneleval(X_test, X_train, kernel): """ This function computes the pariwise distances between each row in X_test and X_train using the kernel specified in 'kernel' X_test, X_train: 2d np.arrays kernel: kernel parameters """ if kernel is None: return X_train fn = kernel...
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def aks_show_snapshot_table_format(result): """Format a snapshot as summary results for display with "-o table".""" return [_aks_snapshot_table_format(result)]
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from typing import List from typing import Dict from typing import Any import subprocess def get_all_monitors() -> List[Dict[str, Any]]: """ :return: all monitors array list sorted from left to right. i.e: [ {'hr': 1366, 'vr': 768, 'ho': 0, 'vo': 914, 'name': 'eDP-1-1'}, {'hr': 2560, 'vr':...
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def poly_prem(f, g, *symbols): """Returns polynomial pseudo-remainder. """ return poly_pdiv(f, g, *symbols)[1]
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def gen_input_code(question, id): """ Returns the html code for rendering the appropriate input field for the given question. Each question is identified by name=id """ qtype = question['type'] if qtype == 'text': return """<input type="text" class="ui text" name="{0}" ...
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def orbit_position(data, body='sun'): """calculate orbit position of sun or moon for instrument position at each time in 'data' using :class:`ephem` Args: data: :class:`xarray.Dataset`, commonly Measurement.data body (optional): name of astronomical body to calculate orbit from ('sun' or 'moon'...
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def list_inventory (inventory): """ :param inventory: dict - an inventory dictionary. :return: list of tuples - list of key, value pairs from the inventory dictionary. """ result = [] for element, quantity in inventory.items(): if quantity > 0: result.append ((element, qua...
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def wsd_is_duplicated_msg(msg_id): """ Check for a duplicated message. Implements SOAP-over-UDP Appendix II Item 2 """ if msg_id in wsd_known_messages: return True wsd_known_messages.append(msg_id) if len(wsd_known_messages) > WSD_MAX_KNOWN_MESSAGES: wsd_known_messages.popl...
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import matplotlib.pyplot as plt def match_diagnostic_plot(V1, V2, pair_ix, tf=None, new_figure=False): """ Show the results of the pair matching from `match_catalog_quads`. """ if new_figure: fig = plt.figure(figsize=[4,4]) ax = fig.add_subplot(111) else: ax = plt.gca(...
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import json def sliding_tile_state(): """ Return the current state of the puzzle :return: JSON object representing the state of the maze puzzle """ json_state = {'sliding_tile': sliding_tile.array(), 'solver': sliding_tile_str_solver, 'steps': sliding_tile_steps, 'search_steps': ...
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import json def _json_to_numpy(string_like, dtype=None): # type: (str) -> np.array """Convert a JSON object to a numpy array. Args: string_like (str): JSON string. dtype (dtype, optional): Data type of the resulting array. If None, the dtypes will be determined by the ...
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import json import time def connect(**kwargs): """ A strategy to connect a bot. :param kwargs: strategy, listener, and orders_queue :return: the input strategy with a report """ strategy = kwargs['strategy'] listener = kwargs['listener'] orders_queue = kwargs['orders_queue'] asset...
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def create_env(env, render=False, shared=False, maddpg=False, evaluate=False): """Return, and potentially create, the environment. Parameters ---------- env : str or gym.Env the environment, or the name of a registered environment. render : bool whether to render the environment ...
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def measure_approximate_cost(structure): """ Various bits estimate the size of the structures they return. This makes that consistent. """ if isinstance(structure, (list, tuple)): return 1 + sum(map(measure_approximate_cost, structure)) elif isinstance(structure, dict): return len(structure) + sum(map(measure_approx...
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def make3DArray(dim1, dim2, dim3, initValue): """ Return a list of lists of lists representing a 3D array with dimensions dim1, dim2, and dim3 filled with initialValue """ result = [] for i in range(dim1): result = result + [make2DArray(dim2, dim3, initValue)] return result
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import math def generate_boxes(bounds=(-1, -1, 1, 1), method='size', size=math.inf): """ Generate a stream of random bounding boxes Has two methods for generating random boxes: - *size* - generates a random central point (x0, y0) within the bounding box, and then draws widths and heig...
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def create_assets(asset_ids, asset_type, mk_parents): """Creates the specified assets if they do not exist. This is a fork of the original function in 'ee.data' module with the difference that - If the asset already exists but the type is different that the one we want, raise an error - Start...
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def decoration(markdown: str, separate: int = 0) -> str: """見出しが使われているマークダウンをDiscordで有効なものに変換します。 ただたんに`# ...`を`**#** ...`に変換して渡された数だけ後ろに改行を付け足すだけです。 Parameters ---------- markdown : str 変換するマークダウンです。 separate : int, default 1 見出しを`**`で囲んだ際に後ろに何個改行を含めるかです。""" new = "" ...
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import hashlib def get_fingerprint(file_path: str) -> str: """ Calculate a fingerprint for a given file. :param file_path: path to the file that should be fingerprinted :return: the file fingerprint, or an empty string """ try: block_size = 65536 hash_method = hashlib.md5() ...
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def set_publish_cluster_args(args): """Set args to publish cluster """ public_cluster = {} if args.public_cluster: public_cluster = {"private": False} if args.model_price: public_cluster.update(price=args.model_price) if args.cpp: public_cluster.update(cr...
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import os def create_session(): """creates database session""" db_engine = sa.create_engine(os.environ.get('DATABASE_URL'), echo=True) return sessionmaker(bind=db_engine)
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def _get_iforest_anomaly_score_per_node(children_left, children_right, n_node_samples): """ Get anomaly score per node in isolation forest, which is node depth + _average_path_length(n_node_samples). Will be used to replace "value" in each tree. Args: children_left: left children childr...
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def get_invalid_value_message(value_name: str, value: str, line_no: int, uid: str, expected_vals: "list[str]") -> str: """ Returns the formatted message template for invalid value while parsing students data! """ msg = f"Invalid {value_name} <span class=\"font-weight-bold\">{value}</span>\ o...
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def compute_score_for_coagulation(platelets_count: int) -> int: """ Computes score based on platelets count (unit is number per microliter). """ if platelets_count < 20_000: return 4 if platelets_count < 50_000: return 3 if platelets_count < 100_000: return 2 if plate...
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def check_horizontal_visibility(board: list): """ Check row-wise visibility (left-right and vice versa) Return True if all horizontal hints are satisfiable, i.e., for line 412453* , hint is 4, and 1245 are the four buildings that could be observed from the hint looking to the right. >>> che...
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import requests def _get_soup(header, url): """This functions simply gets the header and url, creates a session and generates the "soup" to pass to the other functions. Args: header (dict): The header parameters to be used in the session. url (string): The url address to create the ses...
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import sys def test_model(model, name_model, X_train, y_train, X_test, y_test, details=False, normalize=False, weights=None, return_model=False, lib='scikit-learn', fit_params=None): """ Function that does a detailed investigation of a given model. Confusion matrices are generated and vario...
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import json def get_text_block(dunning_type, language, doc): """ This allows the rendering of parsed fields in the jinja template """ if isinstance(doc, string_types): doc = json.loads(doc) text_block = frappe.db.get_value('Dunning Type Text Block', {'parent': dunning_type, 'language': language}, ['...
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import os def load(test=False, cols=None): """Loads data from FTEST if *test* is True, otherwise from FTRAIN. Pass a list of *cols* if you're only interested in a subset of the target columns. """ fname = FTEST if test else FTRAIN df = pd.read_csv(os.path.expanduser(fname)) # load pandas data...
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import os def flow_read(src_file): """Read optical flow stored in a .flo, .pfm, or .png file Args: src_file: Path to flow file Returns: flow: optical flow in [h, w, 2] format Refs: - Interpret bytes as packed binary data Per https://docs.python.org/3/library/struct.html...
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def group_create_factory(context, request): """Return a GroupCreateService instance for the passed context and request.""" user_service = request.find_service(name="user") return GroupCreateService( session=request.db, user_fetcher=user_service.fetch, publish=partial(_publish, reques...
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def verify(params, vk, m, sig): """ verify a signature on a clear message """ (G, o, g1, hs, g2, e) = params (g2, X, Y) = vk sig1 , sig2 = sig return not sig1.isinf() and e(sig1, X + m * Y) == e(sig2, g2)
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import os def prepend_items(): """ Return a function than prepend any item from "paths" list with "prefix" """ def prepend_func(prefix, paths): return [os.path.join(prefix, item) for item in paths] return prepend_func
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def generate_data(n): """ 生成训练数据 """ X, y = make_classification(n_samples=n, n_features=4) data = pd.DataFrame(X, columns=["x1", "x2", "x3", "x4"]) data["y"] = y return data
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def blsimpv(p, s, k, rf, t, div=0, cp=1): """ Computes implied Black vol from given price, forward, strike and time. """ f = lambda x: blsprice(s, k, rf, t, x, div, cp) - p result = brentq(f, 1e-9, 1e+9) return result
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def container_describe(object_id, input_params={}, always_retry=True, **kwargs): """ Invokes the /container-xxxx/describe API method. For more info, see: https://wiki.dnanexus.com/API-Specification-v1.0.0/Containers-for-Execution#API-method%3A-%2Fcontainer-xxxx%2Fdescribe """ return DXHTTPRequest('...
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from typing import Union from typing import Dict def nested(fields: Union[Dict[str, Dict], DataSpec], **config) -> dict: """ Constructs a nested Field Spec Args: fields: sub field specifications config: in kwargs format Returns: the nested spec """ spec = { "...
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from matplotlib.colors import ListedColormap def make_cluster_cmap(labels, grey_pos='start'): """ Creates an appropriate colormap for a vector of cluster labels. Parameters ---------- labels : array_like The labels of multiple clustered points grey_pos: str Where to put th...
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from typing import List def objects_from_array( objects_arr: np.ndarray, default_keys=constants.DEFAULT_OBJECT_KEYS ) -> List[btypes.PyTrackObject]: """Construct PyTrackObjects from a numpy array.""" assert objects_arr.ndim == 2 n_features = objects_arr.shape[1] assert n_features >= 3 n_obje...
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def run_policy(env, policy, scaler, logger, episodes): """ Run policy and collect data for a minimum of min_steps and min_episodes Args: env: ai gym environment policy: policy object with sample() method scaler: scaler object, used to scale/offset each observation dimension ...
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def load_data(): """Load database""" db = TinyDB(DATABASE_PATH) data = db.all() return pd.DataFrame(data)
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def plotcmaponaxis(ax, surf, title, point_sets=None): """Plot a Surface as 2D heatmap on a given matplotlib Axis""" surface = ax.pcolormesh(surf.X, surf.Y, surf.Z, cmap=cm.viridis) if point_sets: for x_y, z, style in point_sets: ax.scatter(x_y[:, 0], x_y[:, 1], **style) ax.set_xlabe...
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def get_log_storage() -> TaskLogStorage: """Get current TaskLogStorage instance associated with the current application.""" return current_app.config.get("LOG_STORAGE")
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def test_optional_posonly_args1(a, b=10, /, c=100): """ >>> test_optional_posonly_args1(1, 2, 3) 6 >>> test_optional_posonly_args1(1, 2, c=3) 6 >>> test_optional_posonly_args1(1, b=2, c=3) # doctest: +ELLIPSIS Traceback (most recent call last): TypeError: test_optional_posonly_args1() g...
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def _build_schema_resource(fields): """Generate a resource fragment for a schema. Args: fields (Sequence[google.cloud.bigquery.schema.SchemaField): schema to be dumped. Returns: Sequence[Dict]: Mappings describing the schema of the supplied fields. """ return [field.to_api_repr() f...
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def flatten_swtn(x): """ Flatten list an array. Parameters ---------- x: list of dict or ndarray the input data Returns ------- y: ndarray 1D the flatten input list of array. shape: list of dict the input list of array structure. """ # Check input if...
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from sys import path def checkpoint(cache, **csv_args): """ Return a decorator which automatically caches the result of a function which returns a pandas.DataFrame. Parameters ---------- cache : str or path object The path to the file which contains the results of `func`. **csv_ar...
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def crossing(series, value, **options): """Find where a function crosses a value. series: Series value: number options: passed to interp1d (default is linear interp) returns: number """ interp = interp1d(series.values, series.index, **options) return interp(value)
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import math def equilSoundSpeeds(gas, rtol=1.0e-6, maxiter=5000): """ Returns a tuple containing the equilibrium and frozen sound speeds for a gas with an equilibrium composition. The gas is first set to an equilibrium state at the temperature and pressure of the gas, since otherwise the equilibr...
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import time import click def benchmark(partitioner_list: list, item_list: list, bucket_list: list, iterations: int = 1, begin_range: int = 1, end_range: int = 10, specified_items_sizes: list = None, verbose: bool = False)\ -> pd.DataFrame: """ Args: Returns: Raises: """ ...
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def adj_by_strand(genes): """ liste: list of hmm gene with homogenous strand Check if the gene is in tandem with another and if so store the gene inside a set obj.TA_gene.linked In parallel it clean up the list obj.TA_gene.genes by removing the genes that forme a tandem. Then TA_gene.genes has only ...
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def register_user(): """ register a user and take to profile page """ form = RegisterForm() if form.validate_on_submit(): username = form.username.data password = form.password.data email = form.email.data first_name = form.first_name.data last_name = form.last...
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def stack_init_image(init_image, num_images): """Create a list from a single image. Args: init_image: a single image to be copied and stacked num_images: number of copies to be included Returns: A list of copies of the original image (numpy ndarrays) """ init_images = [] ...
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import os def process_problem(_path, _lang=EN): """ Обработка задачи """ path = os.path.join(_path, 'problem.xml') with open(path, 'r', encoding='utf-8') as file: root = ET.parse(file).getroot() titles = root.find('names').findall('name') title = titles[0].attrib['value'] for t in titl...
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import sys def input_to_text(s): """Convert the given byte string or text type to text using the file system encoding of the current system. :param basestring s: String or text type to convert :return: The string as text :rtype: unicode """ return avalon.compat.to_text(s, sys.getfilesyste...
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def f5(x, eps=0.0): """The function f(x)=tanh(4x)+noise""" return np.tanh(4*x) + eps * np.random.normal(size=x.shape)
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def get_next_event(game, players): """ return None if a player has to move before the next event otherwise return the corresponding Event enum entry """ active_player = get_active_player(players, game.finish_time) if active_player is None: return None planet_rotation_event = ( ...
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import six import json def _convert_requirements(requirements): """Convert the requirements to an array of strings. ["key op value", "key op value", ...] """ # TODO(frossigneux) Support the "or" operator # Convert text to json if isinstance(requirements, six.string_types): try: ...
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def max_width(string, cols, separator='\n'): """Returns a freshly formatted :param string: string to be formatted :type string: basestring or clint.textui.colorred.ColoredString :param cols: max width the text to be formatted :type cols: int :param separator: separator to break rows :type se...
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import base64 def aes_encrypt(text, sec_key): """ AES encrypt method. :param text: :param sec_key: :return: """ pad = 16 - len(text) % 16 if isinstance(text, bytes): text = text.decode('utf-8') text += pad * chr(pad) encryptor = AES.new(sec_key, 2, '0102030405060708') ...
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def get_value_at_coords(matrix, x, y): """Returns the value of the matrix at given integer coordinates. Arguments: matrix {ndarray} -- Square matrix. x {int} -- x-coordinate. y {int} -- y-coordinate. Returns: int -- Value of the matrix. """ offset = matrix_offset(m...
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def rms(vector): """ Parameters ---------- vector Returns ------- """ return np.sqrt(np.mean(np.square(vector)))
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def parse(text): """Parse a tag-expression as text and return the expression tree. .. code-block:: python tags = ["foo", "bar"] tag_expression = parse("foo and bar or not baz") assert tag_expression.evaluate(tags) == True :param text: Tag expression as text to parse. :param...
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import itertools def average_distance(points, distance_func): """ Given a set of points and their pairwise distances, it calculates the average distances between a pair of points, averaged over all C(num_points, 2) pairs. """ for p0, p1 in itertools.combinations(points, 2): # assert symmetry...
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def get_bin_alignment(begin, end, freq): """Generate a few values needed for checking and filling a series if need be.""" start_bin = get_expected_first_bin(begin,freq) end_bin = (end/freq)*freq expected_bins = expected_bin_count(start_bin, end_bin, freq) return start_bin, end_bin, expecte...
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def TagAndFilterWrapper(target, dontRemoveTag=False): """\ Returns a component that wraps a target component, tagging all traffic coming from its outbox; and filtering outany traffic coming into its inbox with the same unique id. """ if dontRemoveTag: Filter = FilterButKeepTag else: ...
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import requests import json def tweets(url): """tweets count""" try: twitter_url = 'http://urls.api.twitter.com/1/urls/count.json?url=' + url r = requests.get(twitter_url, headers=headers) json_data = json.loads(r.text) return json_data['count'] except: return 0
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def CLJPc(S): """Compute a C/F splitting using the parallel CLJP-c algorithm. CLJP-c, or CLJP in color, improves CLJP by perturbing the initial random weights with weights determined by a vertex coloring. Parameters ---------- S : csr_matrix Strength of connection matrix indicating the...
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def displayTwoDimMapPOST(): """Run displayTwoDimMap""" executionStartTime = int(time.time()) # status and message success = True message = "ok" plotUrl = '' dataUrl = '' # get model, var, start time, end time, lon1, lon2, lat1, lat2, months, scale jsonData = request.json model...
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def encrypt(msg, hexPubkey): """Encrypts message with hex public key""" return pyelliptic.ECC(curve='secp256k1').encrypt( msg, hexToPubkey(hexPubkey))
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def indexing(zDatagridLeft,zDatagridRight,zModelgridLeft,zModelgridRight): """ Searches for closest distances between actual and theorectical points. zDatagridLeft = float - tiled matrix (same values column-wise) of z coordintates of droplet on left side, size = [len(z...
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def torch2np(tensor): """ Convert from torch tensor to numpy convention. If 4D -> [b, c, h, w] to [b, h, w, c] If 3D -> [c, h, w] to [h, w, c] :param tensor: Torch tensor :return: Numpy array """ array, d = tensor.detach().cpu().numpy(), tensor.dim() perm = [0, 2, 3, 1] if d == 4 el...
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import glob import os import random def get_filenames(feature_folder, glob_pattern, sample_size=None): """ Finds the all the files in the given feature folder which matches the glob pattern. :param feature_folder: The folder to search for files. :param glob_pattern: The glob pattern to use for finding...
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from typing import Any import array import numpy def message_to_csv(msg: Any, truncate_length: int = None, no_arr: bool = False, no_str: bool = False) -> str: """ Convert a ROS message to string of comma-separated values. :param msg: The ROS message to convert. :param truncate_leng...
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def create_message(username, message): """ Creates a standard message from a given user with the message Replaces newline with html break """ message = message.replace('\n', '<br/>') return '{{"service":1, "data":{{"message":"{mes}", "username":"{user}"}} }}'.format(mes=message, user=username)
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def overlaps(sdf, other): """ Indicates if the intersection of the two geometries has the same shape type as one of the input geometries and is not equivalent to either of the input geometries. ========================= ========================================================= **Argument** ...
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from django.contrib.auth.views import redirect_to_login def render_page(request, page): """Рендер страницы""" if page.registration_required and not request.user.is_authenticated: return redirect_to_login(request.path) # if page.template: # template = loader.get_template(page.template) ...
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def _whctrs(anchor): """ Return width, height, x center, and y center for an anchor (window). """ w = anchor[2] - anchor[0] + 1 h = anchor[3] - anchor[1] + 1 x_ctr = anchor[0] + 0.5 * (w - 1) y_ctr = anchor[1] + 0.5 * (h - 1) # 16,16, 7.5, 7.5 return w, h, x_ctr, y_ctr
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def obtener_atletas_pais(atletas: list, pais_interes: str) -> list: """ Función que genera una lista con la información de los atletas del país dado, sin importar el año en que participaron los atletas. Parámetros: atletas: list de diccionarios con la información de cada atleta. pais_in...
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def kl_div_mixture_app(m1, v1, m2, v2, return_approximations=False, return_upper_bound=False): """Approximate KL divergence between Gaussian and mixture of Gaussians See Durrieu et al, 2012: "Lower and upper bounds for approximation of the Kullback-Leibler dive...
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