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import pickle def read_img_pkl(path): """Real image from a pkl file. :param path: the file path :type path: str :return: the image :rtype: tuple """ with open(path, "rb") as file: return pickle.load(file)
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from datetime import datetime def create_new_session(connection_handler, session_tablename="session"): """ Creates a new session record into the session datatable :param connection_handler: the connection handler :param session_tablename: the session tablename (default: session) ...
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def splitData(y, tx, ratios=[0.4, 0.1]): """ Split the dataset into train, test and validation sets """ indices = np.arange(len(y)) np.random.shuffle(indices) splits = (np.array(ratios) * len(y)).astype(int).cumsum() training_indices, validation_indices, test_indices = np.split(indices, splits) ...
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def conv_compare(node1, node2): """Compares two conv_general_dialted nodes.""" assert node1["op"] == node2["op"] == "conv_general_dilated" params1, params2 = node1["eqn"].params, node2["eqn"].params for k in ("window_strides", "padding", "lhs_dilation", "rhs_dilation", "lhs_shape", "rhs_shape"): ...
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import json def render_zones(zones: dict): """Render the zones based on accept header""" requested_types = bottle.request.headers.get("Accept") if "application/json" in requested_types: output = json.dumps(zones) content_type = "application/json" elif "text/html" in requested_types: ...
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from typing import Union import numbers def less(left: Tensor, right: Union[Tensor, np.ndarray,numbers.Number],dtype=Dtype.float32,name='less'): """Elementwise 'less' comparison of two tensors. Result is 1 if left < right else 0. Args: left: left side tensor right: right side tensor d...
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def load_sample_image(image_name): """Load the numpy array of a single sample image Read more in the :ref:`User Guide <sample_images>`. Parameters ---------- image_name : {`china.jpg`, `flower.jpg`} The name of the sample image loaded Returns ------- img : 3D array The...
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from datetime import datetime def read_date_from_GPM(infile, radar_lat, radar_lon): """ Extract datetime from TRMM HDF files. Parameters: =========== infile: str Satellite data filename. radar_lat: float Latitude of ground radar radar_lon: float Longitude of ground...
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from typing import Optional def build_cluster_endpoint( domain_key: DomainKey, custom_endpoint: Optional[CustomEndpoint] = None, engine_type: EngineType = EngineType.OpenSearch, preferred_port: Optional[int] = None, ) -> str: """ Builds the cluster endpoint from and optional custom_endpoint an...
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import requests import re def get_community_pools(): """Get community pool coins Returns: List[dict]: A list of dicts which consists of following keys: denom, amount """ url = f"{BLUZELLE_PRIVATE_TESTNET_URL}:{BLUZELLE_API_PORT}/cosmos/distribution/v1beta1/community_pool" res...
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def rgb2bgr(x): """ given an array representation of an RGB image, change the image into an BGR representtaion of the image """ return(bgr2rgb(x))
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from datetime import datetime def draw_des1_plot(date, plot_A, plot_B): """ This function is to draw the plot of DES 1. """ #make up some data for the plot df = pd.DataFrame({'date': np.array([datetime.datetime(2020, 1, i+1) for i in range(12)]), ...
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def kolmogorov_smirnov_rank_test(gene_set, gene_list, adj_corr, plot=False): """ Rank test used in GSEA method. It measures dispersion of genes from gene_set over a gene_list. Every gene from gene_list has its weight specified by adj_corr, where adj_corr are gene weights (correlation with fenotype)...
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import re async def segment_url(request: schemas.UrlSegmentationRequest) -> schemas.SegmentationResponse: """ This endpoint accept the URL of an image, and returns a SegmentationResponse. The endpoint will try to download the image at the given URL. Note: not all servers allow for non-browser user...
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def generate_answers(session, model, word2id, qn_uuid_data, context_token_data, qn_token_data): """ Given a model, and a set of (context, question) pairs, each with a unique ID, use the model to generate an answer for each pair, and return a dictionary mapping each unique ID to the generated answer. ...
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import cmath def _add_agline_to_dict(geo, line, d={}, idx=0, mesh_size=1e-2, n_elements=0, bc=None): """Draw a new Air Gap line and add it to GMSH dictionary if it does not exist Parameters ---------- geo : Model GMSH Model objet line : Object Line Object d : Dictionary ...
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def create_game(gm): """ Configure and create a game. Creates a game with base settings equivalent to one of the default presets. Allows user to customize the settings before starting the game. Parameters ---------- gm : int Game type to replicate: 0: Normal mode. ...
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def mat_toeplitz_2d(h, x): """ Constructs a Toeplitz matrix for 2D convolutions Parameters ---------- h: list[list] A matrix of scalar values representing the filter x: list[list] A matrix of scalar values representing the signal Returns ------- list[list] A...
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import unicodedata def fix_text_segment( text, *, fix_entities='auto', remove_terminal_escapes=True, fix_encoding=True, fix_latin_ligatures=True, fix_character_width=True, uncurl_quotes=True, fix_line_breaks=True, fix_surrogates=True, remove_control_chars=True, remove_b...
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import random def SSValues(MPKa,Rfa,r): """ Steady-State Values (Numerical solutions Linear) Input: Annual MPK and Rf Rates, r (repetition index) Output: Annual MPK and Rf Rates (Input), mu, gamma, SS Capital, SS Wage, SS Investment, Value function """ #Compute Parameters MPK =...
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def simplify_junctures(graph, epsilon=5): """Simplifies clumps by replacing them with a single juncture node. For each clump, any nodes within epsilon of the clump are deleted. Remaining nodes are connected back to the simplified junctures appropriately.""" graph = graph.copy() max_quadrance = epsil...
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def sample_truncated_norm(clip_low, clip_high, mean, std): """ Given a range (a,b), returns the truncated norm """ a, b = (clip_low - mean) / std, (clip_high - mean) / std return int(truncnorm.rvs(a, b, mean, std))
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def f(x): """ Approximated funhction.""" return x.mm(w_target)+b_target[0]
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import requests from bs4 import BeautifulSoup def get_urls(): """ get all sci-hub-torrent url """ source_url = 'http://gen.lib.rus.ec/scimag/repository_torrent/' urls_list = [] try: req = requests.get(source_url) soups = BeautifulSoup(req.text, 'lxml').find_all('a') for sou...
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def getVariablesForCookie(request=None): """ returns dict with variables for cookie """ cookie_path = '/' portalurl = absoluteURL(getSite(), request) cookie_name = "%s%s"%('__zojax_comment_author_', md5(portalurl).hexdigest()) return dict(name=cookie_name, path=cookie_path)
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import torch def logsumexp(x, dim): """ sums up log-scale values """ offset, _ = torch.max(x, dim=dim) offset_broadcasted = offset.unsqueeze(dim) safe_log_sum_exp = torch.log(torch.exp(x-offset_broadcasted).sum(dim=dim)) return safe_log_sum_exp + offset
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import requests def make_request(session, verb, endpoint, data={}, timeoutInSeconds=REQUEST_TIMEOUT_IN_SECONDS, max_retries=MAX_RETRIES): """ Make a REST request """ try: if verb is RequestVerb.post: r = session.post(url=endpoint, json=data, timeout=timeou...
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def certificate_managed( name, days_remaining=90, append_certs=None, managed_private_key=None, **kwargs ): """ Manage a Certificate name Path to the certificate days_remaining : 90 Recreate the certificate if the number of days remaining on it are less than this number. The...
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from typing import Iterable from typing import Dict from typing import List def _unique_field_to_col_matching( rules: Iterable[Rule], field_to_matching_cols: Dict[str, List[int]] ) -> Dict[str, int]: """ Given a potential field to column matching this functions tries to determine a unique 1-to-1 matc...
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import yaml import textwrap def minimal_config(): """Return YAML parsing result for (somatic) configuration""" return yaml.round_trip_load( textwrap.dedent( r""" static_data_config: reference: path: /path/to/ref.fa dbsnp: path: /path/to/d...
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def walk(n=1000, mu=0, sigma=1, alpha=0.01, s0=NaN): """ Mean reverting random walk. Returns an array of n-1 steps in the following process:: s[i] = s[i-1] + alpha*(mu-s[i-1]) + e[i] with e ~ N(0,sigma). The parameters are:: *n* walk length *s0* starting value, defaults ...
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def GetCLIInfoMgr(): """ Get the vmomi type manager """ return _gCLIInfoMgr
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from datetime import datetime def pretty_date(time=False): """ Get a datetime object or a int() Epoch timestamp and return a pretty string like 'an hour ago', 'Yesterday', '3 months ago', 'just now', etc """ now = datetime.now() if type(time) is int: diff = now - datetime.fromtimes...
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def per_cpu_times(): """Return system CPU times as a named tuple""" ret = [] for cpu_t in cext.per_cpu_times(): user, nice, system, idle = cpu_t item = scputimes(user, nice, system, idle) ret.append(item) return ret
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def cooldown(rate, per, type=commands.BucketType.default): """See `commands.cooldown` docs""" def decorator(func): if isinstance(func, Command): func._buckets = CooldownMapping(Cooldown(rate, per, type)) else: func.__commands_cooldown__ = Cooldown(rate, per, type) ...
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def construct_psi_k2(theta, y, X, kappa = 30): """ Kappa-based filter for time-varying autoregressive component, based on Platteau (2021) """ #get parameter vector T = len(y) omega = theta[0] alpha = theta[1] beta = theta[2] #Filter Volatility psi = np.zeros(T) #i...
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def calHoahaoSancai(tian_ge, ren_ge, di_ge): """ 三才五行吉凶计算 :return: :param tian_ge: 天格 :param ren_ge: 人格 :param di_ge: 地格 :return: """ sancai = getSancaiWuxing(tian_ge) + getSancaiWuxing(ren_ge) + getSancaiWuxing(di_ge) if sancai in g_sancai_wuxing_dict: data = g_sancai...
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def load_coeff_swarm_mio_internal(path): """ Load internal model coefficients and other parameters from a Swarm MIO_SHA_2* product file. """ with open(path, encoding="ascii") as file_in: data = parse_swarm_mio_file(file_in) return SparseSHCoefficientsMIO( data["nm"], data["gh"], ...
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import os def verify_variable_with_environment(var, var_name, env_name): """ Helper function that assigns a variable based on the inputs and gives relevant outputs to understand what is being done. If the variable is defined, it will make sure that the environment variable (used by some lower-level code) ...
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def plot_trajectory_from_data(X : np.array, y : np.array, sample_n = 0, excludeY=True, ylabel=None, xlabel=None): """ Plots trajectory from data sample_n: sample index """ fig, ax = plt.subplots() dim = X.shape[2] for d in range(dim): trajectory = list(X[sample_n,:,d...
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import os def ls(directory, create=False): """ List the contents of a directory, optionally creating it first. If create is falsy and the directory does not exist, then an exception is raised. """ if create and not os.path.exists(directory): os.mkdir(directory) onlyfiles = [f ...
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async def get_prices(database, match_id): """Get market prices.""" query = """ select timestamp::interval(0), extract(epoch from timestamp)::integer as timestamp_secs, round((food + (food * .3)) * 100) as buy_food, round((wood + (wood * .3)) * 100) as buy_wood, round((stone + (st...
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import os def ete_database_data(): """ Return path to ete3 database json """ user = os.environ.get('HOME', '/') fp = os.path.join(user, ".mtsv/ete_databases.json") if not os.path.isfile(fp): with open(fp, 'w') as outfile: outfile.write("{}") return fp
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import os def link(srcPath, destPath): """create a hard link from srcPath to destPath""" return os.link(srcPath, destPath)
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def isChinese(): """ Determine whether the current system language is Chinese 确定当前系统语言是否为 中文 """ return SYSTEM_LANGUAGE == 'zh_CN'
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def load_db(db): """ Load database as a dataframe. Extracts the zip files if necessary. The database is indexed by the user, session. """ if DEV_GENUINE == db or DEV_IMPOSTOR == db: extract_dev_db() if GENUINE == db or UNKNOWN == db: extract_test_db() return pd.read_csv(db, ind...
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from astropy.io import fits import os def fetch_rrlyrae_mags(data_home=None, download_if_missing=True): """Loader for RR-Lyrae data Parameters ---------- data_home : optional, default=None Specify another download and cache folder for the datasets. By default all astroML data is store...
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import inspect import sys def is_implemented_in_notebook(cls): """Check if the remote class is implemented in the environments like notebook(e.g., ipython, notebook). Args: cls: class """ assert inspect.isclass(cls) if hasattr(cls, '__module__'): cls_module = sys.modules.get(cls....
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def _pool_tags(hash, name): """Return a dict with "hidden" tags to add to the given cluster.""" return dict(__mrjob_pool_hash=hash, __mrjob_pool_name=name)
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import sys import example def main(): """ Simple test of phylotree functions. """ if len(sys.argv) > 1: phy_fn = sys.argv[1] with open(phy_fn, 'r') as phy_in: phy = Phylotree(phy_in, anon_haps=True) for hap in phy.hap_var: print(hap, ','.join(phy.hap_var...
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from pathlib import Path def clusters_dictionary(): """ Read the column 'label' from final_dataframe.tsv' and return the clusters as a dictionary. If the column 'label' is not in final_dataframe.tsv', call k_means_clustering and perform the clustering. :return: a dictionary, where the key is the c...
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def normalize_medians_for_batch(expression_matrix, meta_data, **kwargs): """ Calculate the median UMI count per cell for each batch. Transform all batches by dividing by a size correction factor, so that all batches have the same median UMI count (which is the median batch median UMI count) :param expre...
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def apply_wet_day_frequency_correction(ds, process): """ Parameters ---------- ds : xr.Dataset process : {"pre", "post"} Returns ------- xr.Dataset Notes ------- [1] A.J. Cannon, S.R. Sobie, & T.Q. Murdock, "Bias correction of GCM precipitation by quantile mapping: How wel...
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def get_nb_build_nodes_and_entities(city, print_out=False): """ Returns number of building nodes and building entities in city Parameters ---------- city : object City object of pycity_calc print_out : bool, optional Print out results (default: False) Returns ------- ...
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def generate_pairs(agoals, props): """Forms all the pairs that are applicable to the current goals""" all_pairs = [] for i in range(0, len(agoals)): for j in range(i, len(agoals)): goal1, goal2 = agoals[i], agoals[j] all_pairs.extend(list(form_pairs(goal1, goal2, props))) ...
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def construct_aircraft_data(args): """ create the set of aircraft data :param args: parser argument class :return: aircraft_name(string), aircraft_data(list) """ aircraft_name = args.aircraft_name aircraft_data = [args.passenger_number, args.overall_length, ...
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def Oplus_simple(ne): """ """ return ne
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def lin_exploit(version): """ The title says it all :) """ kernel = version startno = 119 exploits_2_0 = { 'Segment Limit Privilege Escalation': {'min': '2.0.37', 'max': '2.0.38', 'cve': ' CVE-1999-1166', 'src': 'https://www.exploit-db.com/exploits/19419/'} } exploits_2_2 = { ...
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async def get_device( hass: HomeAssistant, config_entry_id: str, device_category: str, device_type: str, vin: str, ): """Get a tesla Device for a Config Entry ID.""" entry_data = hass.data[TESLA_DOMAIN][config_entry_id] devices = entry_data["devices"].get(device_category, []) for d...
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def cartesian2complex(real, imag): """ Calculate the complex number from the cartesian form: z = z' + i * z". Args: real (float|np.ndarray): The real part z' of the complex number. imag (float|np.ndarray): The imaginary part z" of the complex number. Returns: z (complex|np.ndar...
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def compare_maps(ra_id, method_id, type_id, method_comp=None, type_comp=None): """Function to compare maps / or just print off a given map""" # Get the map map_one = GPVal.objects.filter(my_anal_id=ra_id, type_id=type_id, method_id=method_id) if meth...
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def _row_reduce_list(mat, rows, cols, one, iszerofunc, simpfunc, normalize_last=True, normalize=True, zero_above=True, dotprodsimp=None): """Row reduce a flat list representation of a matrix and return a tuple (rref_matrix, pivot_cols, swaps) where ``rref_matrix`` is a flat list,...
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import importlib def get_action_class(class_str): """Imports the action class. Args: class_str (str): A string action class. Returns: Action: A child class of Action. Raises: ActionImportError: If the class doesn't exist. """ (module_name, class_name) = class_str.rsplit('....
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def rate_comments(request): """ Render a bloom page where respondents can rate comments by others. """ return render(request, 'rate-comments.html')
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def gaussian2d(size=(32, 32), sigma=0.5): """ Generate a Gaussian kernel (not normalized). :param size: k x m size of the returned kernel :param sigma: standard deviation of the returned Gaussian :return: A tensor with the Gaussian kernel """ x, y = tf.meshgrid(tf.linspace(-1.0, 1.0, size[0...
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def home(): """ List all users or add new user """ users = User.query.all() return render_template('home.html', users=users)
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def vgg13_bn(**kwargs): """ VGG 13-layer model (configuration "B") with batch normalization """ model = VGG(make_layers(cfg['B'], batch_norm=True), **kwargs) return model
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def lr_insight_wr(): """Return 5-fold cross validation scores r2, mae, rmse""" steps = [('scaler', t.MyScaler(dont_scale='for_profit')), ('knn', t.KNNKeepDf())] pipe = Pipeline(steps) pipe.fit(X_raw) X = pipe.transform(X_raw) lr = LinearRegression() lr.fit(X, y) cv_results ...
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import collections def complete_list_value(exe_context, return_type, field_asts, info, result): """ Complete a list value by completing each item in the list with the inner type """ assert isinstance(result, collections.Iterable), \ ('User Error: expected iterable, but did not find one ' + ...
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def projection_ERK(rkm, dt, f, eta, deta, w0, t_final): """Explicit Projection Runge-Kutta method.""" rkm = rkm.__num__() w = np.array(w0) # current value of the unknown function t = 0 # current time ww = np.zeros([np.size(w0), 1]) # values at each time step ww[:,0] = w.copy() tt = np.zeros...
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def integer(name, value): """Validate that the value represents an integer :param name: Name of the argument :param value: A value representing an integer :returns: The value as an int, or None if value is None :raises: InvalidParameterValue if the value does not represent an integer """ if...
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def generate_Euler_Maruyama_propagators(): """ importer function function that creates two functions: 1. first function created is a kernel propagator (K) 2. second function returns the kernel ratio calculator """ # let's make the kernel propagator first: this is just a batched ULA move ...
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def get_vtx_neighbor(vtx, faces, n=1, ordinal=False, mask=None): """ Get one vertex's n-ring neighbor vertices Parameters ---------- vtx : integer a vertex's id faces : numpy array the array of shape [n_triangles, 3] n : integer specify which ring should be got o...
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from typing import Tuple from typing import Optional from typing import List import sys def run_from_text(text: str, n_merges: int=sys.maxsize) -> Tuple[str, int, Optional[List[BpePerformanceStatsEntry]]]: """ >>> def run_and_get_merges(text: str): ... return [(m, occ) for m, occ, _ in run_from_text(t...
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import json def load_line_delimited_json(filename): """Load data from the file that is stored as line-delimited JSON. Parameters ---------- filename : str Returns ------- dict """ objects = [] with open(filename) as f_in: for i, line in enumerate(f_in): t...
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def tolower(x: StringOrIter) -> StringOrIter: """Convert strings to lower case Args: x: A string or vector of strings Returns: Converted strings """ x = as_character(x) if is_scalar(x): return x.lower() return Array([elem.lower() for elem in x])
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import numpy import math def MWA_Tile_analytic(za, az, freq=100.0e6, delays=None, zenithnorm=True, power=False, dipheight=config.DIPOLE_HEIGHT, dip_sep=config.DIPOLE_SEPARATION, ...
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import json def traindata(): """Generate Plots in the traindata page. Args: None Returns: render_template(render_template): Render template for the plots """ # read data and create visuals df_features = read_data_csv("./data/features...
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def import_file(file_path, title, source_mime_type, dest_mime_type): """Imports a file with conversion to the native Google document format. Expects the env var GOOGLE_APPLICATION_CREDENTIALS to be set for credentials. Args: path (str): Path to file to import title(str): The title of th...
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def test_extract_requested_slot_from_text_with_not_intent(): """Test extraction of a slot value from text with certain intent """ # noinspection PyAbstractClass class CustomFormAction(FormAction): def slot_mappings(self): return {"some_slot": self.from_text(not_intent='some_intent')}...
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import os def _get_info_file_path(): """Get path to info file for the current process. As with `_get_info_dir`, the info directory will be created if it does not exist. """ return os.path.join(_get_info_dir(), "pid-%d.info" % os.getpid())
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def create_generic_io_object(ioclass, filename=None, directory=None, return_path=False, clean=False): """ Create an io object in a generic way that can work with both file-based and directory-based io objects If filename is None, create a filename. If return_path is Tr...
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def select_channels(img_RGB): """ Returns the R' and V* channels for a skin lesion image. Args: img_RGB (np.array): The RGB image of the skin lesion """ img_RGB_norm = img_RGB / 255.0 img_r_norm = img_RGB_norm[..., 0] / ( img_RGB_norm[..., 0] + img_RGB_norm[..., 1] + img_RGB_nor...
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def upper_case(string): """ Returns its argument in upper case. :param string: str :return: str """ return string.upper()
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import json def repositoryDefinitions(): """ Load repositoryDefinitions page """ i_d = wmc.repository.get_definition_details() p_d = json.dumps(i_d, indent=4) + " " msg = Markup(JSONtoHTML(p_d)) return render_template('repositoryDefinitions.html', data=msg)
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def available_adapter_names(): """Return a string list of the available adapters.""" return [str(adp.name) for adp in plugins.ActiveManifest().adapters]
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import argparse import os def parse_user_arguments(*args, **kwds): """ Parses the arguments of the program """ parser = argparse.ArgumentParser( description = "Generate the profiles of the input drug", epilog = "@oliva's lab 2017") parser.add_argument('-d','--drug_name',dest=...
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import os def createNewLetterSession(letter): """ # Take letter and create next session folder (session id is current max_id + 1) # Return path to session directory """ # Search for last training folder path = "gestures_database/"+letter+"/" last = -1 for r,d,f in os.walk(path): for folder in d: last ...
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def count_sort(seq): """ perform count sort and return sorted sequence without affecting the original """ counts = defaultdict(list) for elem in seq: counts[elem].append(elem) result = [] for i in range(min(seq), max(seq)+1): result.extend(counts[i]) return result
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def detect_overrides(cls, obj): """ For each active plugin, check if it wield a packet hook. If it does, add make a not of it. Hand back all hooks for a specific packet type when done. """ res = set() for key, value in cls.__dict__.items(): if isinstance(value, classmethod): ...
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def morningCalls(): """localhost:8080/morningcalls""" session = APIRequest.WebServiceSafra() return session.listMorningCalls()
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def resize_image(img, h, w): """ resize image """ image = cv2.resize(img, (w, h), interpolation=cv2.INTER_NEAREST) return image
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from typing import Dict def _parse_pars(pars) -> Dict: """ Takes dictionary of parameters, converting values to required type and providing defaults for missing values. Args: pars: Parameters dictionary. Returns: Dictionary of converted (and optionally validated) parameters. ...
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def _get_base_class_names_of_parent_and_child_from_edge(schema_graph, current_location): """Return the base class names of a location and its parent from last edge information.""" edge_direction, edge_name = _get_last_edge_direction_and_name_to_location(current_location) edge_element = schema_graph.get_edge...
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from typing import Callable def projection( v: GridVariableVector, solve: Callable = solve_fast_diag, ) -> GridVariableVector: """Apply pressure projection to make a velocity field divergence free.""" grid = grids.consistent_grid(*v) pressure_bc = boundaries.get_pressure_bc_from_velocity(v) q0 = grid...
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def a07_curve_function(curve: CustomCurve): """Computes the embedding degree (with respect to the generator order) and its complement""" q = curve.q() if q.nbits()>300: return {"embedding_degree_complement":None,"complement_bit_length":None} l = curve.order() embedding_degree = curve.embeddi...
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def _horizontal_metrics_from_coordinates(xcoord,ycoord): """Return horizontal scale factors computed from arrays of projection coordinates. Parameters ---------- xcoord : xarray dataarray array of x_coordinate used to build the grid metrics. either plane_x_coord...
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def ultosc( df, high, low, close, ultosc, time_period_1=7, time_period_2=14, time_period_3=28, ): """ The Ultimate Oscillator (ULTOSC) by Larry Williams is a momentum oscillator that incorporates three different time periods to improve the overbought and oversold signals....
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def mating(child_id, parent1, parent2, gt_matrix): """ Given the name of a child and two parents + the genotype matrices, mate them """ child_gen = phase_parents(parent1, parent2, gt_matrix) parent1.add_children(child_id) parent2.add_children(child_id) child = Person(child_id) child.se...
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def _tmp( generator_reconstructed_encoded_fake_data, encoded_random_latent_vectors, real_data, encoded_real_data, generator_reconstructed_encoded_real_data, alpha=0.7, scope="anomaly_score", add_summaries=False): """anomaly score. See https://arx...
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