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def create_app(): """Create and configure an instance of the Flask application.""" app = Flask(__name__) # vvvvv use sqlite database vvvvv app.config['SQLALCHEMY_DATABASE_URI'] = 'sqlite:///db.sqlite3' # vvvvv have DB initialize the app DB.init_app(app) @app.route('/') def root(): ...
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from mpi4py import MPI def MPITest(commsize): """ A decorator that repeatedly calls the wrapped function, with communicators of varying sizes. This converts the test to a generator test; therefore the underlyig test shall not be a generator test. Parameters ---------- commsize: scala...
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def getClassicalPitchNames(pitches): """ takes a list of pitches and returns a list of classical pitch class names """ return getPitchNames([normalizePitch(x,12) for x in pitches],getClassicalPitchNameCandidates)
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import pymel.core.uitypes def toPyUIList(res): # type: (str) -> List[pymel.core.uitypes.PyUI] """ returns a list of PyUI objects Parameters ---------- res : str Returns ------- List[pymel.core.uitypes.PyUI] """ if res is None: return [] return [pymel.core.uity...
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def best_B(Ag): """ Given an antigenic determinant Ag this function returns the binding value of the best possible binder. """ top = 0 for i in range(len(Ag)): etop = np.min(cf.TD20[int(Ag[i]) - 1]) top += etop return top
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def forward_gradients_v2(ys, xs, grad_xs=None, gate_gradients=False): """Forward-mode pushforward analogous to the pullback defined by tf.gradients. With tf.gradients, grad_ys is the vector being pulled back, and here d_xs is the vector being pushed forward.""" if type(ys) == list: v = [tf.ones_...
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import resource def __limit_less(lim1, lim2): """Helper function for comparing two rlimit values, handling "unlimited" correctly. Params: lim1 (integer): first rlimit lim2 (integer): second rlimit Returns: true if lim1 <= lim2 """ if lim2 == resource.RLIM_INFINITY: ...
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from typing import List def getswarmlocations() -> List[str]: """ checks if the provided location is a location where a swarm can happen. :param location: the provided location :return: boolean if location is in the list of locations where swarms can happen, """ swarmlocationlist = open("comma...
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from typing import Any from typing import Optional def Request( default: Any = Undefined, *, default_factory: Optional[NoArgAnyCallable] = None, alias: Optional[str] = None, ) -> Any: """ Used to provide extra information about a field. :param default: since this is replacing the field’s ...
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import sys from django.conf import settings import os def get_jobs(when=None, only_scheduled=False): """ Returns a dictionary mapping of job names together with their respective application class. """ # FIXME: HACK: make sure the project dir is on the path when executed as ./manage.py try: ...
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import os import json import logging def get_project_id(): """ Gets the project ID. It defaults to the project declared in the enviorment variable PROJECT but if it can't find it there it will try looking for a service account and take the project ID from there Args: Returns: """ service_acc_address = os....
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def val_err_str(val: float, err: float) -> str: """ Get a float representation of a value/error pair and create a string representation 12.345 +/- 1.23 --> 12.3(12) 12.345 +/- 0.012 -> 12.345(12 12345 +/- 654 ---> 12340(650) :param val: float representing the value :param err: float represe...
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import os def discrete_distribution(probabilities, path='', fig_name='distribution_events_states.pdf', v_labels=None, h_labels=None, title=None, color_map=None, figsize=(12, 6), size_labels=16, size_values=14, bottom=None, top=None, left=None, right=None, savefig=Fa...
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import re def find_map(address): """ Look up a specified address in the /proc/PID/maps for a process. Returns: A string representing the map in question, or None if no match. """ maps = fetch_maps() for m in re.finditer(begin_pattern, maps): begin = int(m.group("begin"), 16) e...
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import regex def _format_css_declarations(content: list, indent_level: int) -> str: """ Helper function for CSS formatting that formats a list of CSS properties, like `margin: 1em;`. INPUTS content: A list of component values generated by the tinycss2 library OUTPUTS A string of formatted CSS """ output = ...
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def rosen_hess(x): """ The Hessian matrix of the Rosenbrock function. Parameters ---------- x : array_like 1-D array of points at which the Hessian matrix is to be computed. Returns ------- rosen_hess : ndarray The Hessian matrix of the Rosenbrock function at `x`. ...
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def flow_corr(): """ Symmetric cumulants SC(m, n) at the MAP point compared to experiment. """ fig, axes = plt.subplots( figsize=figsize(0.5, 1.2), sharex=True, nrows=2, gridspec_kw=dict(height_ratios=[4, 5]) ) observables = ['sc', 'sc_normed'] ylims = [(-2.5e-6, 2.5e-6), (...
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def dodecagon(samples=128, radius=1): """Create a dodecagon mask. Parameters ---------- samples : `int`, optional number of samples in the square output array radius : `float`, optional radius of the shape in the square output array. radius=1 will fill the x Returns ...
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def port_name(name, nr=0): """Map node output number to name.""" return name + ":" + str(nr)
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import os import urllib def url(ticker, start_date, end_date): """Format the correct URL from the params""" base_url = ''.join([API_BASE_PATH, ticker, '.csv']) params = {'start_date': start_date, 'end_date': end_date} if API_KEY_ENV in os.environ: params['api_key'] = os.environ[API_KEY_ENV] ...
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def AC3(csp, queue=None, removals=None, arc_heuristic=csp.dom_j_up): """[Figure 6.3]""" if queue is None: queue = {(Xi, Xk) for Xi in csp.variables for Xk in csp.neighbors[Xi]} csp.support_pruning() queue = arc_heuristic(csp, queue) checks = 0 while queue: (Xi, Xj) = queue.pop() ...
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from typing import Optional from typing import List from typing import Union import pandas def load( name: str, ids: Optional[List[Union[str, int]]] = None, limit: Optional[int] = None, ) -> pandas.DataFrame: """Load dataset data to a pandas DataFrame. Args: name: The dataset ...
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def _stringify(values): """internal method: used to convert values to a string suitable for an xml attribute""" if type(values) == list or type(values) == tuple: return " ".join([str(x) for x in values]) elif type(values) == type(True): return "1" if values else "0" else: return ...
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def xml_safe(s): """Returns the XML-safe version of a given string. """ new_string = s.replace("&", "&amp;").replace("<", "&lt;") new_string = new_string.replace("\r", "").replace("\n", "<br/>") return new_string
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import re def range_values(ent): """Extract values from the range and cached label.""" data = {} range_ = [e for e in ent.ents if e._.cached_label.split('.')[0] == 'range'][0] values = re.findall(FLOAT_RE, range_.text) if not all([re.search(INT_TOKEN_RE, v) for v in values]): raise Rejec...
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import os def plot_mw_nii_bars(ax, snr_min = None, shaded_kwargs = {}, **kwargs): """ Plots vertical lines and bars on bpt Diagram for Tilted Disk where only NII/HA line is detected Parameters ---------- ax 'matplotlib.pyplot.figure.axes' axes to plot lines on snr_min: 'number', ...
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def get_weights(connections): """Returns the weights of the connections :param connections: :return: Numpy array of weights """ return np.array(nest.GetStatus(connections, keys="weight"))
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def w2v_matrix_vocab_generator(w2v_pickle): """ Creates the w2v dict mapping word to index and a numpy matrix of (num words, size of embedding), words will be mapped to their index, such that row ith will be the embedding of the word mapped to the i index. :param w2v_pickle: Dataframe containing token ...
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def concat( dfs, axis=0, join="outer", uniform=False, filter_warning=True, ignore_index=False ): """Concatenate, handling some edge cases: - Unions categoricals between partitions - Ignores empty partitions Parameters ---------- dfs : list of DataFrame, Series, or Index axis : int or s...
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def resize(dataset: xr.Dataset, invalid_value: float = 0) -> xr.Dataset: """ Pixels whose aggregation window exceeds the reference image are truncated in the output products. This function returns the output products with the size of the input images : add rows and columns that have been truncated. Thes...
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import requests def score(graphs, schema, url, port): """ graphs is expected to be a list of dictionaries, where each entry in the list represents a graph with * key idx -> index value * key nodes -> list of ints representing vertices of the graph * key edges -> list of list of ints represen...
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from typing import List from typing import Dict def group_by_author(commits: List[dict]) -> Dict[str, List[dict]]: """Group GitHub commit objects by their author.""" grouped: Dict[str, List[dict]] = {} for commit in commits: name = commit["author"]["login"] if name not in grouped: ...
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import re def convert(name): """ CamelCase to under_score :param name: :return: """ s1 = re.sub('(.)([A-Z][a-z]+)', r'\1_\2', name) return re.sub('([a-z0-9])([A-Z])', r'\1_\2', s1).lower()
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def plot(graph, particles=None, polyline=None, particles_alpha=None, label_start_end=True, bgcolor='white', node_color='grey', node_size=0, edge_color='lightgrey', edge_linewidth=3, **kwargs): """ Plots particle approximation of trajectory :param graph: NetworkX MultiDiGraph UTM projection ...
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def non_empty_string(value): """Must be a non-empty non-blank string""" return bool(value) and bool(value.strip())
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def metadataAbstractElementRequiredChildElementTest6(): """ Optional child elements, child elements required. >>> doctestMetadataAbstractElementFunction( ... testMetadataAbstractElementKnownChildElements, ... metadataAbstractElementRequiredChildElementTest6(), ... requiredChildEleme...
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def index(): """ List containers """ containers = g.api.get_containers() clonable_containers = [] for container in containers: if container['state'] == 'STOPPED': clonable_containers.append(container['name']) context = { 'containers': containers, 'clonable...
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import torch def spatial_discounting_mask(): """ Input: config: Config should have configuration including HEIGHT, WIDTH, DISCOUNTED_MASK. Output: tf.Tensor: spatial discounting mask Description: Generate spatial discounting mask constant. Spatial discounting ma...
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from pathlib import Path import os def does_file_exist(filepath:Path)-> bool: """ Checks if file path exists. """ if os.path.exists(filepath): LOG.info("Data path detected:\n{}\.".format(filepath)) return True else: LOG.info("Data path\n{}\nnot detected. Downloading now.....
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def pca_results(scaled, pca): """ Plot the explained variance of the DataSet as a barchart, and return a DataFrame with the explained variance for each feature, for each dimension of the PCA. ----------------------------------------------------------- # Parameters: # scaled (pd.DataFrame): The DataFrame in wh...
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import pwd def get_uid_from_user(user): """Return UID from user name Looks up UID matching the supplied user name; returns None if no matching name can be found. NB returned UID will be an integer. """ try: return pwd.getpwnam(str(user)).pw_uid except KeyError: return No...
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def get_approval_distance(election_1: ApprovalElection, election_2: ApprovalElection, distance_id: str = None) -> float or (float, list): """ Return: distance between approval elections, (if applicable) optimal matching """ inner_distance, main_distance = extract_distance_id(distance_...
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from pathlib import Path def get_base_folder(): """Return the base folder of ProfileQC.""" return Path(__file__).parent
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def u16le_list_to_byte_list(data): """! @brief Convert a halfword array into a byte array""" byteData = [] for h in data: byteData.extend([h & 0xff, (h >> 8) & 0xff]) return byteData
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def process_IBM_strings(string): """ Format all the IBM string in the same way, creating a single string of lowercase characters :param string: :return: """ parts = string.split() result = str(parts[0].lower()) for part in parts[1:]: result += " " + str(part.lower()) return r...
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def get_sample_size(number_of_clones, fold_difference, error_envelope_x_vals, error_envelope_y_vals, number_of_error_bars): """ This returns the number of cells in a sample that produce the an error bar of max_error_bar for a given number_of_clones in the parent population. This is the inverse ...
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def get_r2(y,yhat): """ Calcualte the coef. of determination (R^2) """ ybar = np.mean(y) return 1 - (np.sum((y-yhat)**2))/(np.sum((y-ybar)**2))
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from typing import Dict from typing import Any def get_context() -> Dict[str, Any]: """ Retrieve the current Server Context. Returns: - Dict[str, Any]: the current context """ ctx = _context.get() # type: ignore if ctx is not None: assert isinstance(ctx, dict) return ...
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import pandas as pd def kiinteisto_alueiksi(kiinteisto): """ kiinteist: kiinteisto/property register An artificial property / constituency division will be made for the regionalization of postal codes. A brute-force distribution is used, where the relative number of residential properties i...
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def G1DListCrossoverSinglePoint(genome, **args): """ The crossover of G1DList, Single Point .. warning:: You can't use this crossover method for lists with just one element. """ sister = None brother = None gMom = args["mom"] gDad = args["dad"] if len(gMom) == 1: utils.raise...
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def optional_observation_map(env, inner_obs): """ If the env implements the `observation` function (i.e. if one of the wrappers is an ObservationWrapper), call that `observation` transformation on the observation produced by the inner environment """ if hasattr(env, 'observation'): retur...
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def RunMetadataLabels(run_metadata): """Returns all labels in run_metadata.""" labels = [] for dev_stats in run_metadata.step_stats.dev_stats: for node_stats in dev_stats.node_stats: labels.append(node_stats.timeline_label) return labels
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import sys import re def ShouldPackageFile(filename, target): """Returns true if the file should be a part of the resulting archive.""" if chromium_utils.IsMac(): file_filter = r'^.+\.(a|dSYM)$' elif chromium_utils.IsLinux(): file_filter = r'^.+\.(o|a|d)$' else: raise NotImplementedError('%s is no...
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def is_entity_extractor_present(interpreter: Interpreter) -> bool: """Checks whether entity extractor is present.""" extractors = get_entity_extractors(interpreter) return extractors != []
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def get_workflow(name, namespace): """Get a workflow.""" api_group = "argoproj.io" api_version = "v1alpha1" co_name = "workflows" co_client = _get_k8s_custom_objects_client() return co_client.get_namespaced_custom_object(api_group, api_version, n...
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import torch def step(x, b): """ The step function for ideal quantization function in test stage. """ y = torch.zeros_like(x) mask = torch.gt(x - b, 0.0) y[mask] = 1.0 return y
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from typing import Union def encode_intended_validator( validator_address: Union[Address, str], primitive: bytes = None, *, hexstr: str = None, text: str = None) -> SignableMessage: """ Encode a message using the "intended validator" approach (ie~ version 0) defined...
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def _ip_desc_from_proto(proto): """ Convert protobuf to an IP descriptor. Args: proto (protos.keyval_pb2.IPDesc): protobuf of an IP descriptor Returns: desc (magma.mobilityd.IPDesc): IP descriptor from :proto: """ ip = ip_address(proto.ip.address) ip_block_addr = ip_address(...
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import inspect def inheritdocstrings(cls): """A class decorator for inheriting method docstrings. >>> class A(object): ... class_attr = True ... def method(self): ... '''Method docstring.''' >>> @inheritdocstrings ... class B(A): ... def method(self): ... pass ...
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def get_totd_text(): """ Get the text for the Top of the Day post. :return: The body for the post. """ sections = [] # Most Upvoted Posts top_submissions = sorted([submission for submission in get_reddit().subreddit("all").top("day", limit=5)], key=lambda x: x.score, reverse=True) items...
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import os def check_checkpoints(store_path): """ Inputs 1) store_path: The path where the checkpoint file will be searched at Outputs 1) checkpoint_file: The checkpoint file if it exists 2) flag: The flag will be set to True if the directory exists at the path Function: This function takes in the store_pa...
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import pickle import time def dump_ensure_space(file, value, fun_err=None): """ Only dump value if space enough in disk. If is not enough space, then it retry until have space Note: this method is less efficient and slowly than simple dump >>> with open("test_ensure_space.tmp", "wb") as f: .....
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import torch def store_images(input, predicts, target, dataset='promise12'): """ store the test or valid image in tensorboardX images container :param input: NxCxHxW :param predicts: NxCxHxW :param target: NxHxW :return: """ N = input.shape[0] grid_image_list = [] for i...
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from typing import Optional from typing import List from typing import Dict import csv def snmptable(ipaddress: str, oid: str, community: str = 'public', port: OneOf[str, int] = 161, timeout: int = 3, sortkey: Optional[str] = None ) -> OneOf[List[Dict[str, str]], Dict[str, Di...
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def GetFile(message=None, title=None, directory=None, fileName=None, allowsMultipleSelection=False, fileTypes=None): """Ask the user to select a file. Some of these arguments are not supported: title, directory, fileName, allowsMultipleSelection and fileTypes are here for compatibility reasons. """ default_f...
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def lda_recommend(context_list): """ With multiprocessing using Dask""" print("Recommending") topn = 500 sleep(0.2) vec_bow = id2word_dictionary.doc2bow(context_list) # This line takes a LONG time: it has to map to each of the 300 topics vec_ldamallet = ldamallet[vec_bow] # Convert the q...
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def grids_skf_lr(data_x, data_y, grid_params, weight_classes=None, scv_folds=5): """ :param data_x: :param data_y: :param grid_params: :param weight_classes: :param scv_folds: :return: """ if weight_classes is None: weight_classes = {0: 1, 1: 1} m_log = LogisticRegressio...
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def zeros(rows, cols, fortran=True): """Return the zero matrix with the given shape.""" order = "F" if fortran else "C" cparr = cp.zeros(shape=(rows, cols), dtype=cp.complex128, order=order) return CuPyDense._raw_cupy_constructor(cparr)
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def compute_trapezoidal_approx(bm, t0, y0, dt, sqrt_dt, dt1_div_dt=10, dt1_min=0.01): """Estimate int_{t0}^{t0+dt} int_{t0}^{s} dW(u) ds with trapezoidal rule. Slower compared to using the Gaussian with analytically derived mean and standard deviation, but ensures true determinism, since this rids the rand...
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def vavrycuk_psencik_hti(vp1, vs1, p1, d1, e1, y1, vp2, vs2, p2, d2, e2, y2, phi, theta1): """ Reflectivity for arbitrarily oriented HTI media, using the formulation derived by Vavrycuk and Psencik [1998], "PP-wave reflection coefficients in weakly aniso...
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def concatenate_time_series(time_series_seq): """Concatenates a sequence of time-series objects in time. The input can be any iterable of time-series objects; metadata, sampling rates and other attributes are kept from the last one in the sequence. This one requires that all the time-series in the lis...
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def deeplink_url_patterns( url_base_pattern=r'^init/%s/$', login_init_func=login_init, ): """ Returns new deeplink URLs based on 'links' from settings.SAML2IDP_REMOTES. Parameters: - url_base_pattern - Specify this if you need non-standard deeplink URLs. NOTE: This will probably clos...
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def read_words(): """ Returns an array of all words in words.txt """ lines = read_file('resources/words.txt') words = [] for line in lines: words.extend(line.split(' ')) return words
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def lynotename(midinote): """Find the LilyPond/Pently name of a MIDI note number. For example, given 60 (which means middle C), return "c'". """ octave, notewithin = midinote // 12, midinote % 12 notename = notenames[notewithin] if octave < 4: return notename + "," * (4 - octave) else: ...
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from datetime import datetime def json_serial(obj): """ Fallback serializier for json. This serializes datetime objects to iso format. :param obj: an object to serialize. :returns: a serialized string. """ if isinstance(obj, (datetime.datetime, datetime.date)): return obj.isoform...
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import logging import glob import os import copy import warnings def get_library_file(instrument, detector, filt, pupil, wfe, wfe_group, library_path, wings=False, segment_id=None): """Given an instrument and filter name along with the path of the PSF library, find the appropriate library...
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def html_mail(sender='me@mail.com', recipients=['them@mail.com'], html_content='<p>Hi</p>', subject='Hello!', mailserver='localhost'): """ html_mail takes input html, sender, recipents and emails it in a mime type that will show as text or html on the recipients mail reader. ...
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def gotu(input_path: str) -> biom.Table: """Generate a gOTU table based on sequence alignments. """ profile = workflow(input_path, None)['none'] return profile_to_biom(profile)
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def read_data_megset(beamf_type): """ Read and prepare data for plotting.""" if beamf_type == 'lcmv': settings = config.lcmv_settings settings_columns = ['reg', 'sensor_type', 'pick_ori', 'inversion', 'weight_norm', 'normalize_fwd', 'use_noise_cov', ...
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import getpass import logging def collect_user_name(): """ Returns the username as provided by the OS. Returns a constant if it fails. """ try: uname = getpass.getuser() except Exception as e: logger = logging.getLogger(__name__) msg = "Failed to collect the user name: erro...
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def get_dataframe() -> pd.DataFrame(): """Dummy DataFrame""" data = [ {"quantity": 1, "price": 2}, {"quantity": 3, "price": 5}, {"quantity": 4, "price": 8}, ] return pd.DataFrame(data)
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def get_node_mirna(mirna_name, taxid, psi_mi_to_sql_object): """ This function sets up a node dict and returns it. If the node is already in the SQLite database it fetches that node from the db, so it won't be inserted multiple times. """ # Testing if the node is already in the database node_dict =...
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import urllib import sys def Web(website, system_id, address, page, params = {}): """Routine for connecting to website that is hosting the database""" data = '' params['systemid'] = system_id params = urllib.urlencode(params) headers = {"Content-type": "application/x-www-form-urlencoded", "Accept"...
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def generate_output_file_name(input_file_name): """ Generates an output file name from input file name. :type input_file_name: str """ assert isinstance(input_file_name, str) output_file_name = input_file_name + ".gen.ipynb" return output_file_name
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def prefixed_field_map(name: str) -> Mapper: """ Arguments --------- name : str Name of the property. Returns ------- Mapper Field map. See Also -------- field_map """ return field_map( name, api_to_python=add_signed_prefix_as_needed, ...
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import sys def a_star(grid, start, end): """A-star algorithm implementation""" # open and closed nodes open_nodes = [] closed_nodes = [] # Create a start node and an goal node start_node = Node(start, None) goal_node = Node(end, None) # Add the start node open_nodes.append(start_...
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def is_water(residue): """ Parameters ---------- residue : a residue from a protein structure object made with PDBParser(). Returns ------- Boolean True if residue is water, False otherwise. """ residue_id = residue.get_id() hetfield = residue_id[0] return hetfield[0...
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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. """ cdf = 0.5 * (1.0 + tf.erf(input_tens...
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def index(): """ Route for signing the policy document or REST headers. """ request_payload = request.get_json() if request_payload.get('headers'): response_data = sign_headers(request_payload['headers']) else: credential = [c for c in request_payload['conditions'] if 'x-amz-credential'...
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from sphinx.jinja2glue import BuiltinTemplateLoader def create_template_bridge(self): """Return the template bridge configured.""" if self.config.template_bridge: templates = self.app.import_object( self.config.template_bridge, 'template_bridge setting')() else: templates = Bui...
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def make_answer(rdtype, answers=None, additionals=None, authorities=None): """For mocking an answer. We make an answer without any message (what would normally come over the network, to be parsed. We instead make a blank object for the sake of test complexity, and later attach the appropriate\ rrsets to...
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def consolidate_payoff_results(period, reporter_configuration, simulation_output, score_map, priority_based): """ Gather per-run metrics according to a simulation result. :param resolved_per_reporter: Resolved issues per priority, including a priority detail. :param period: Description of the period. ...
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def single_ray_belief_propagation( S, ray_voxel_indices, ray_to_occupancy_accumulated_pon, ray_to_occupancy_messages_pon, output_size ): """Run the sum product belief propagation for a single ray Arguments --------- S: tensor (M,) dtype=float32 The depth probability distribut...
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def cse_postprocess(cse_output): """ Perform CSE Postprocessing :arg: output from SymPy CSE with tuple format: (list of ordered pairs that contain substituted symbols and their replaced expressions, reduced SymPy expression) :return: output from SymPy CSE where postprocessing...
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def lap(j, s, alpha): """ Laplace coefficient """ def int_func(x): return np.cos(j*x)/(1. - (2.*alpha*np.cos(x)) + alpha**2.)**s integral = integrate.quad(int_func, 0., 2.*np.pi)[0] return 1./np.pi*integral
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import google def calendar_add(): """Adds a calendar to the database according to the infos in POST data.\ Also creates the calendar in google calendar service if no google_calendar_id is present in POST data. """ calendar_name = request.form["calendar_name"] std_email = request.form["std_ema...
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def proportional_allocation_by_location_and_activity(df, sectorcolumn): """ Creates a proportional allocation within each aggregated sector within a location :param df: :param sectorcolumn: :return: """ # tmp replace NoneTypes with empty cells df = replace_NoneType_with_empty_cells(df) ...
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import os def Console(): """ Factory method that returns the Console object most appropriate for the current OS envrionment. """ if os.name == "posix": return POSIXConsole() elif os.name == "nt": return NTConsole() else: raise NotImplementedError("Console support not implement...
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def prepare_target(): """ Creates a example target face :return: list of RFTargetVertex """ # size = 2 # target = [ # rfsm.RFTargetVertex(0, 0, 0, -size, -size), # rfsm.RFTargetVertex(0, 1, 1, -size, size), # rfsm.RFTargetVertex(1, 1, 1, size, size), # rfsm.RFTarg...
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import json def data_fixture(): """Fixture data.""" data = json.loads(load_fixture("data.json", "evil_genius_labs")) return {item["name"]: item for item in data}
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