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def Rotation_EQJ_GAL(): """Calculates a rotation matrix from equatorial J2000 (EQJ) to galactic (GAL). This is one of the family of functions that returns a rotation matrix for converting from one orientation to another. Source: EQJ = equatorial system, using the equator at the J2000 epoch. Target:...
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from pathlib import Path import tqdm def query_copernicus_hub(aoi, username, password, hub, **kwargs): """Query Copernicus Open access Hub. :param aoi: (str) Geojson Area of interest url :param username: (str) Username to use for API connection :param password: (str) Password to use for API connectio...
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from saq.database import get_db_connection def delete_password(key): """Deletes the given password from the database. Returns True if the password was deleted.""" with get_db_connection() as db: c = db.cursor() c.execute("DELETE FROM `encrypted_passwords` WHERE `key` = %s", (key,)) db....
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def StandardMols(mols, n_jobs=1): """ """ mols = mols if type(mols) is not Chem.rdchem.Mol else [mols] n_jobs = n_jobs if n_jobs>=1 else None pool = Pool(n_jobs) sm = pool.map_async(StandardMol, mols).get() pool.close() pool.join() return sm
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def af_to_maf(af): """ Converts an allele frequency to a minor allele frequency Args: af (float or str) Returns: float """ # Sometimes AF == ".", in these cases, set to 0 try: af = float(af) except ValueError: af = 0.0 if af <= 0.5: return af ...
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from lasagne import layers from nolearn.lasagne import NeuralNet from .shape import ReshapeLayer import logging def generate_nnet(feats): """Generate a neural network. Parameters ---------- feats : list with at least one feature vector Returns ------- Neural network object """ # ...
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import sys def sleep(retcode=0, time=SLEEP_TIME): """ Sleep for {time} seconds & return code {retcode} """ return [ sys.executable, '-c', 'import sys, time; time.sleep({}); sys.exit({})'.format(time, retcode) ]
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def validate_auth(config: ConfigType) -> ConfigType: """Validate presence of CONF_ACCESS_TOKEN when CONF_DEVICE_CLASS=tv.""" token = config.get(CONF_ACCESS_TOKEN) if config[CONF_DEVICE_CLASS] == "tv" and not token: raise vol.Invalid( f"When '{CONF_DEVICE_CLASS}' is 'tv' then '{CONF_ACCES...
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def GetBuildShortBaseName(target_platform): """Returns the build base directory. Args: target_platform: Target platform. Returns: Build base directory. Raises: RuntimeError: if target_platform is not supported. """ platform_dict = { 'Windows': 'out_win', 'Mac': 'out_mac', 'Li...
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def build_B_from_A(A, nodes=None): """ Create the numpy adjacency tensor of a networkX graph. Parameters ---------- A : list List of MultiDiGraph NetworkX objects. nodes : list List of nodes IDs. Returns ------- B : ndarra...
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def get_sort_order(ds_spec): """ Find how quickly the spectroscopic values are changing in each row and the order of rows from fastest changing to slowest. Parameters ---------- ds_spec : 2D HDF5 dataset or numpy array Rows of indices to be sorted from fastest changing to slowest R...
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import traceback import calendar import time def generate_error(request, cls, e, tb, include_traceback=False): """ Builds an L{ErrorMessage<pyamf.flex.messaging.ErrorMessage>} based on the last traceback and the request that was sent. """ if hasattr(cls, '_amf_code'): code = cls._amf_code...
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def reads(text, ext, format_name=None, rst2md=False, as_version=4, **kwargs): """Read a notebook from a string""" if ext == '.ipynb': return nbformat.reads(text, as_version, **kwargs) format_name = read_format_from_metadata(text, ext) or format_name if not format_name: format...
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def make_wildcard(title, *exts): """Create wildcard string from a single wildcard tuple.""" return "{0} ({1})|{1}".format(title, ";".join(exts))
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def _getFields(qset=None, model=None): """ returns a list of fields for specified QuerySet or Model """ if hasattr(qset, '_meta') and getattr(qset, '_meta') != None: fields = qset._meta.fields elif hasattr(qset, 'model') and getattr(qset, 'model') != None: fields = qset.model._meta.f...
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from pathlib import Path def dir_files(path, pattern="*"): """ Returns all files in a directory """ if not isinstance(path, Path): raise TypeError("path must be an instance of pathlib.Path") return [f for f in path.glob(pattern) if f.is_file()]
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def fix_while_loop(x): """Change Javascript for loop to Python for loop for(var i = 0fi < x.length;i++){" --> "for i in range(0,len(x),1): Args: x (str): A string with Javascript syntax. Returns: [str]: Python string Examples: >>> from ee_extra import fix_for_loop ...
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def io_connection_pattern(inputs, outputs): """Return the connection pattern of a subgraph defined by given inputs and outputs.""" inner_nodes = io_toposort(inputs, outputs) # Initialize 'connect_pattern_by_var' by establishing each input as # connected only to itself connect_pattern_by_var = {} ...
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import argparse import sys def parse_args(args=None): """Parse arguments from sys.argv""" parser = argparse.ArgumentParser() parser.add_argument( '-w', '--window', default="pyqt5", choices=find_window_classes(), help='Name for the window type to use', ) parser.add_...
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def pool_forward(A_prev, hparameters, mode = "max"): """ Implements the forward pass of the pooling layer. Parameters: ----------- A_prev: tensor of shape (m, n_H_prev, n_W_prev, n_C_prev) Input data. hparameters: dictionary Contains "f" and "stride". ...
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def myDownsample(y, N) : """ yds = myDownsample(y,N) yds is y sampled at every Nth index, starting with yds[0]=y[0] with y[range(0,len(y),N)]. Implementing Matlab's downsample. Ted Golfinopoulos, 7 June 2012 """ return y[range(0,len(y),N)]
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def _norm_args(norm): """ Returns the proper normalization parameter values. Possible `norm` values are "backward" (alias of None), "ortho", "forward". This function is used by both the builders and the interfaces. """ if norm == "ortho": ortho = True normalise_idft = Fals...
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import yaml import os def LoadConfigDict(config_paths, model_params): """Loads config dictionary from specified yaml files or command line yaml.""" # Ensure that no duplicate keys can be loaded (causing pain). yaml.add_constructor(yaml.resolver.BaseResolver.DEFAULT_MAPPING_TAG, NoDuplica...
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def get_next_point_in_trace(trace: LineString, point: Point) -> Point: """ Determine next coordinate point towards middle of LineString from point. """ coord_points = get_trace_coord_points(trace) assert point in coord_points if point == coord_points[-1]: return coord_points[-2] if p...
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def reduced_quantity(a_quantity, b_quantity): """ Returns the reduced mass of two particles. Examples: ``` >>> reduced_quantity(1*u.kg, 1*u.kg) <Quantity(0.5, 'kilogram')> >>> reduced_quantity(1*u.kg, 20*u.kg).m 0.9523809523809523 >>> reduced_quantity(1, 200)...
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def expected_value(values, state, action, discount=0.9): """Calculate expected value for a given action :param state: state which value is updated :type state: tuple :param action: action taken in this state :type action: int :param discount: discount :type discount: float :return: new ...
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def tf(*args, **kwargs): """ Create a transfer function model of a system. :param args: pass in num :type args: TransferFunction | List[numbers.Real] | numbers.Real :return: the transfer function of the system :rtype: TransferFunction :Example: >>> from tcontrol imp...
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import torch def all_pair_iou(boxes_a, boxes_b): """ Compute the IoU of all pairs. :param boxes_a: (n, 4) minmax form boxes :param boxes_b: (m, 4) minmax form boxes :return: (n, m) iou of all pairs of two set """ N = boxes_a.size(0) M = boxes_b.size(0) max_xy = torch.min(boxes_a[:...
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def get_matching_list_from_graph(graph): """ :param graph: nx.Graph(); each edge should have an attribute "color" :return: List of matching; each matching is an nx.Graph() representing a sub-graph of "graph" """ degree = get_graph_degree(graph) colors = [i for i in range(degree + 1)] ...
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def remove_zeros(res_array): """ Erase all zeros in res_array and return (reduced) array without zeros. Parameters ---------- res_array : np.array Numpy results array Returns ------- res_no_zeros : np.array Numpy results array without zeros (shorter than res_array, if z...
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def butter_lowpass(cutoff, fs, order=5): """ This is based on butter_bandpass """ nyq = 0.5 * fs normal_cutoff = cutoff / nyq b, a = ssig.butter(order, normal_cutoff, btype="low", analog=False) return b, a
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import warnings def instantaneous_phase_shift(analytic_sig, time_vect, carrier_frequency): """ For a signal $x(ray) = A * exp(i (2 pi f_0 ray + phi(ray)))$, returns phi(ray) in [-pi, pi[. Parameters ---------- analytic_sig: ndarray time_vect: ndarray carrier_frequency: float Returns ...
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def get_p0_gaussian(x, y): """Estimate (x0, dV, Tb) for the spectrum.""" if x.size != y.size: raise ValueError("Mismatch in array shapes.") Tb = np.max(y) x0 = x[y.argmax()] dV = np.trapz(y, x) / Tb / np.sqrt(2. * np.pi) return x0, dV, Tb
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def list_mendeley_accounts_user(auth): """ Returns the list of all of the current user's authorized Mendeley accounts """ provider = MendeleyCitationsProvider() return provider.user_accounts(auth.user)
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import os def find_source_files(input_path, export_packages): """ Get a recursive list of filenames for all Java source files within the given directory. Only include files in packages that are exported """ java_files = [] input_path = os.path.normpath(os.path.abspath(input_path)) exclude_...
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import ipaddress def _verify_address(addr): """Function verifies that address is valid IPv4 address Args: addr : address of machine Return: boolean value defining validity of address """ try: ipaddress.ip_address(unicode(addr)) return True except ValueError: ...
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import subprocess import sys def make_repo_ref_from_cur_dir(): """Gets the prefix string for a git clone command dependening on the current directories git setup. i.e. if it is https, then use https. """ try: git_output = subprocess.check_output(['git', 'config', '--get', 'remote.origin.url']) excep...
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def output_reduce_list(path_list, force=False): """Generates structure file with protons from a list of structure files.""" output_paths = [] for path in path_list: output_path = output_reduce(path, force=force) if output_path: output_paths.append(output_path) return output_p...
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def asStructuredText(I, munge=0): """ Output structured text format. Note, this will whack any existing 'structured' format of the text. """ r = [I.getName()] outp = r.append level = 1 if I.getDoc(): outp(_justify_and_indent(_trim_doc_string(I.getDoc()), level)) bases = [base ...
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def current_distribution_by_website(site): """ Reads the checker framework version from the checker framework website and returns the version of the current release """ print 'Looking up checker-framework-version from %s\n' % site ver_re = re.compile(r"<!-- checker-framework-version -->(.*),") ...
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import statistics def build_card_objects(media_list: list = None) -> list: """ Creates DB objects from S3 objects list """ logger.info("Crafting list of DB objects...") logger.debug( f"Context Parameters: {build_card_objects.__name__} => {build_card_objects.__code__.co_varnames}" ) medias...
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def make_hyperspherical_classification_loss(prototypes): """ Args: prototypes: (num_classes, embed_dim) """ def _get_prototypes(labels): return tf.tensordot(labels, prototypes, [[1], [0]]) def loss(preds, labels): """ Args: preds: (Batch, embed_d...
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def nz_MgCLN_Gayer( lam: float, T: float, ax: str=None, ): """ Refractive index for MgCLN, based on Gayer et al, APB 2008 Parameters ---------- lam: wavelength (lambda) [um] T: Temperature [Celsius Degrees] ax: polarization Returns ------- nz: Refractive...
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from pathlib import Path import logging def export_corpora( corpus_ids, granularity, corpora_folder, filename, no_download=False ): """ Generates a single JSON file with the chosen granularity for all of the selected corpora :param corpus_ids: IDs of the corpora that will be exported :par...
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from typing import Iterable from re import T from typing import Callable from typing import Tuple from typing import Iterator import itertools from typing import cast def all_pairs_iterator(values: Iterable[T], with_replacement: bool = True, where: Callable[[Tuple[T, T]],...
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def syllable_tokenize(text): """ :param str text: input string to be tokenized :return: returns list of strings of syllables """ syllables = [] if text: words = word_tokenize(text) trie = create_custom_dict_trie(custom_dict_source=syllable_dict()) for word in words: ...
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from src import bcrypt def create_sponsor(loggedin_user): """ Creates a new Sponsor manually and bypasses email verification. --- tags: - admin summary: Create Sponsor requestBody: content: application/json: schema: $ref: '#/compo...
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def get_empty_theme(): """Create object that contains empty theme.""" return { 'theme': {}, 'background': bytearray() }
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def random_nat(n: int) -> int: """ Generate a random natural number L{n} bytes long. """ return utils.int_from_bytes(random_bytes(n), 'big', signed=False)
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import base64 def getNumAtoms(ctab): """ Counts number of atoms of given compounds. CTAB is urlsafe_base64 encoded string containing single molfile or concatenation of multiple molfiles. cURL examples: curl -X GET ${BEAKER_ROOT_URL}getNumAtoms/$(cat aspirin.mol | base64 -w 0 | tr "+/" "-_") """ dat...
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import pkg_resources def get_requirement_version(package_name, dependency_name): """Get assigned version to a dependency in package requirements.""" package_name = package_name.replace('pollination.', 'pollination_') package_name = name_to_pollination(package_name) dependency_name = dependency_name.re...
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from typing import Counter import math def cosine(s1, s2): """ Retuns the cosine value between two strings >>> cosine("This is a sentence", "This is a sentence") 1.0 """ vec1 = Counter(s1.split()) vec2 = Counter(s2.split()) intersection = set(vec1.keys()) & set(vec2.keys()) nume...
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from pathlib import Path import typing def generate_multiple_simulations(path_sumo_cfg: Path, flow_configs: typing.Dict[str, typing.Dict], n_simulation: int) -> typing.List[Path]: """Generate "n_simulation" configuration files while updating valu...
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def get_all_types(inactive=0): """Get all non-deleted instance_types. Pass true as argument if you want deleted instance types returned also. """ return db.instance_type_get_all(context.get_admin_context(), inactive)
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from typing import List def merge_split_assoc_words(assoc_words: List[AssocWord]) -> List[AssocWord]: """ This function merges all groups of AssocWords, apart from when an AssocWord with a `form' appears on the right side in which case a new group is started again. Conversely, if an AssocWord has...
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def get_predicates(rules, roles): """Extract predicate information from the rules""" preds = set() pred_names = set() predTypes = {} # maps places to the equivalence class they're in ec = TypedEquivalenceClass() for r in rules: goal_place_types = {} if r.get_head().get_relation() == 'goal': score = r.get...
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def comment_dicts_to_entities(comment_dicts): """Converts the list of comment dicts to the list of comment entities.""" return [comment_dict_to_entity(comment_dict) for comment_dict in comment_dicts]
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def get_comment(id, check_author=True): """Get a comment and its post and its author by id. Checks that the id exists and optionally that the current user is the author of its post. :param id: id of comment to get :param check_author: require the current user to be the author :return: the comm...
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import string def letter_extractor(raws): """letter_ Frequencies of 26 English letters in a given text, case insensitive. Known differences with Writeprints Static feature "letter frequency": None. Args: raws: List of documents. Returns: Frequencies of English letters in the do...
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def crop_frames(frames, speaker): """ frames: (b h w c) """ if speaker == "chem" or speaker == "hs": return frames elif speaker == "chess": return frames[:, 270:460, 770:1130] elif speaker == "dl" or speaker == "eh": return frames[:, int(frames.shape[1] * 3 / 4) :, int(fr...
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def request_unaffiliated_research_access(request): """ Submit request for unaffiliated research access """ name = "%s %s" % (request.user.first_name, request.user.last_name) form = form_for_request(request, UnaffiliatedResearchRequestForm, initial={'name': name, 'email': request.user.email}) if request...
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def builddict(fin): """ Build a dictionary mapping from username to country for all classes. Takes as input an open csv.reader on the edX supplied file that lists classname, country, and username and returns a dictionary that maps from username to country """ retdict = {} for cours...
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from datetime import datetime def get_timeseries(length, delta=datetime.timedelta(hours=1)): """Generate timeseries data""" start = datetime.datetime.now() timeseries = [start] for i in range(length - 1): timeseries.append(timeseries[i] + delta) return timeseries
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def add_static_values(caomlist, statics, data_type, header_type): """ Add entries from the statics dictionary to the caomlist by looking at properties of data_type and header_type. The add_value_caomxml module is used to actually create the CAOMxml objects and add them to the caomlist. """ caomlis...
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def dict_to_stix2(stix_dict, allow_custom=False, version=None): """convert dictionary to full python-stix2 object Args: stix_dict (dict): a python dictionary of a STIX object that (presumably) is semantically correct to be parsed into a full python-stix2 obj allow_custom...
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from typing import Callable from typing import Type def connector(schema: str) -> Callable[[Type[Connector]], Type[Connector]]: """ The @connector class decorator used to register the connector to the global registry. Parameters ---------- schema The schema for the connector, for exam...
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def resource_show(expression): """returns the metadata of a resource""" url = OPENDATA_URL + "resource_show?{expression}".format(expression=expression) return _request_json(url).get("result", dict())
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import numpy as np def n_overlap_1 ( ri, ei, box, r, e ): """Takes in coordinates and orientations of a molecule and counts overlaps. Values of box and partner coordinate array are supplied. Fast or slow algorithm selected. """ # In general, r will be a subset of the complete set of simulation ...
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def HJB_ode(y, time, b, I_func): """ Hamilton-Jacobi-Bellman equation """ u, v, w = y dudt = cost_effort(b(T_max - time)) + b(T_max - time) * \ I_func(T_max - time) * (v - u) - vac(T_max - time) * u dvdt = cost_infection(time) + gamma * (w - v) dwdt = rho * (u - w) return dudt, d...
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from typing import Tuple import re def get_contexts(pp_threshold: float, d_threshold: float, spans: int, use_qa_table_enrichment: bool, doc_and_tables_dfs: Tuple[pd.DataFrame, pd.DataFrame]) -> Tuple[pd.DataFrame, pd.Dat...
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from typing import Union from pathlib import Path def _get_suffix(filepath: Union[str, Path, FSMap]) -> str: """Check if file type is supported.""" # TODO: handle multiple files through the same set of checks for combining files if isinstance(filepath, FSMap): suffix = Path(filepath.root).suffix ...
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def decision_tree_predict(tree, testing_example, max_value_in_target_attribute): """ :param max_value_in_target_attribute: If we are not able to classify due to less data, we return this value when testing :param tree: This is the trained tree which we will use for finding the class of the given instance ...
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def load_data(census_region: int, filepath: str = "nhts_census_updated.mat"): """Load the data at nhts_census.mat. :param int census_region: the census region to load data from. :param str filepath: the path to the matfile. :raises ValueError: if the census division is not between 1 and 9, inclusive. ...
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import win32api def getFileProperties(fname): """ Read all properties of the given file return them as a dictionary. """ propNames = ( "Comments", "InternalName", "ProductName", "CompanyName", "LegalCopyright", "ProductVersion", "FileDescription...
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def setup_scanner(hass, config, see, discovery_info=None): """Set up the Volvo tracker.""" if discovery_info is None: return vin, _ = discovery_info vehicle = hass.data[DATA_KEY].vehicles[vin] def see_vehicle(vehicle): """Handle the reporting of the vehicle position.""" hos...
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def tvdb_get_id(sername, config): """ TVDB: Get SeriesID from SeriesName """ # Query TVDb for SeriesName xresp = getxml(config.tvdb['mirror'] + "/api/GetSeries.php", {'seriesname': sername}) logthis("Got response from TVDb:", suffix=print_r(xresp), loglevel=LL.DEBUG2) snorm = normalize(sern...
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def check_satisfy_program(w, program): """ For each rule in the program, this function checks whether the head exists if all literals(or atoms) in the body exists in each ruler interval of the given Window ``w'' . Args: w (a Window instance): program (a list of rules): Returns: ...
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import pdb def extend(start,end,vector,holevector) : """ Extend the subgrids one point if possible, to avoid edges """ s=np.max([0,start-1]) e=np.min([len(vector),end+1]) hs=np.max([0,np.where(np.isclose(holevector,vector[s]))[0][0]]) he=np.min([len(holevector),np.where(np.isclose(holevector,v...
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def array(obj, row_major=0): """Wrapper around numpy.ndarray. It gives you the option of specifying the order of the contents. """ if not isinstance(obj, np.ndarray): obj = np.array(obj) if row_major == 0: if obj.flags.f_contiguous: return obj else: dim = ...
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def get_reverse_depends(name, capability_instances): """Gets the reverse dependencies of a given Capability :param name: Name of the Capability which the instances might depend on :type name: str :param capability_instances: list of instances to search for having a dependency on the given Capab...
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import random def normal2(startt,endt,money2,first,second,third,forth,fifth,sixth,seventh,zz1,zz2): """ for source and destination id generation """ """ for type of banking work,label of fraud and type of fraud """ idvariz=random.randrange(1, 100001) idgirand...
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import collections def node_degree_counter(g, node, cache=True): """Returns a Counter object with edge_kind tuples as keys and the number of edges with the specified edge_kind incident to the node as counts. """ node_data = g.node[node] if cache and 'degree_counter' in node_data: return no...
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async def get_account_id(db, name): """Get account id from account name.""" return await db.query_one("SELECT find_account_id( (:name)::VARCHAR, True )", name=name)
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def params_to_payload(params, config): """Converts a set of parameters into a payload for a GET or POST request. """ base_payload = {config['param-api-key']: config['api-key']} return dict(base_payload, **params)
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def colorize_img(value, vmin=None, vmax=None, cmap='jet'): """ A utility function for TensorFlow that maps a grayscale image to a matplotlib colormap for use with TensorBoard image summaries. By default it will normalize the input value to the range 0..1 before mapping to a grayscale colormap. A...
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from typing import Mapping import types def evaluate_models( models: Mapping[K, RewardModel], batch: types.Transitions ) -> Mapping[K, np.ndarray]: """Computes prediction of reward models.""" reward_outputs = {k: m.reward for k, m in models.items()} feed_dict = make_feed_dict(models.values(), batch) ...
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import os def check_clangxx(default="clang++"): """Compile a basic C++11 binary.""" executable = os.getenv("CXX", default) return check_bin(executable, "-x c++ -std=c++11 - -o /dev/null".split(), what="clang++", input="int main() { return 1; }...
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from typing import Any def is_a_string(v: Any) -> bool: """Returns if v is an instance of str. """ return isinstance(v, str)
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def wheel_speed_commands(u_ref, w_ref, d, r): """Converts reference speeds to wheel speed commands""" leftSpeed = float((2 * u_ref - d * w_ref) / (2 * r)) rightSpeed = float((2 * u_ref + d * w_ref) / (2 * r)) leftSpeed = np.sign(leftSpeed) * min(np.abs(leftSpeed), MAX_SPEED) rightSpeed = np.sig...
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def _get_dataset_from_filename(filename_skip_take, do_skip, do_take): """Returns a tf.data.Dataset instance from given (filename, skip, take).""" filename, skip, take = (filename_skip_take['filename'], filename_skip_take['skip'], filename_skip_take['take'],) dat...
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def kde_normalize(arr, mask=None, modality="T1w", norm_value=1): """ Use kernel density estimation to find the peak of the white matter in the histogram of a skull-stripped image. Then normalize intensitites to a normalization value. Parameters ---------- arr: array the input data. ...
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import argparse def _parse_cmd_args(args_to_parse: list[str]) -> HashableDict: """Parse command line arguments for the sound change applier.""" parser = argparse.ArgumentParser( prog="sound-change-applier-v2.0", description="A program that applies phonological rules to words.", epilog=...
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def nfour_connectivity(I): """ Returns an image of four-connectivity for each pixel, where the pixel value is the number of 4-connected neighbors. """ Ir = np.ravel(I) edgeidcs = edge_coords(I.shape, dtype='flat') allpix = set(np.where(Ir==1)[0]) dopix = allpix - edgeidcs...
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def plot_bargraph(count_plot_df, plot_df): """ Plots the bargraph Arguments: count_plot_df - The dataframe that contains lemma counts plot_df - the dataframe that contains the odds ratio and lemmas """ graph = ( p9.ggplot(count_plot_df.astype({"count": int}), p9.aes(x="lemma...
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def flip_labels(Y, p): """Returns binary class labels with proportion p randomly flipped.""" assert set(Y) == {1, 2} Y = np.copy(Y) for i, e in enumerate(Y): if np.random.rand() < p: if e == 1: Y[i] = 2 else: Y[i] = 1 return Y
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def find_key(obj, predicate=None): """This method is like :func:`pydash.arrays.find_index` except that it returns the key of the first element that passes the predicate check, instead of the element itself. Args: obj (list|dict): Object to search. predicate (mixed): Predicate applied pe...
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import os import json import logging def trigger_github_deployment_create(payload): """ Trigger the function that creates the GH deployment with the given payload """ response = lambda_client.invoke( FunctionName="{}-github_deployment_create".format( os.environ['FUNCTION_PREFIX']),...
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def reports_home(request): """Some default page for reports home page.""" try: blank_date = '..' * 23 blank_time = '.' * 20 address = 'P.O Box %s' % ('.' * 30) params, location = {}, '.' * 20 form = CaseLoad(request.user) if request.method == 'POST': d...
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def historical(): """" Retrieve stored data from datastore. """ return { 'page': 'historical', }
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import subprocess def run_tests(code, probid, subid, test_name): """ Run the code on test cases. Assume that the code is already compiled to [probid]-[subid]. Return the error code (no_err, runtime_err, or mismatch_err) and extra info. Note: Does not clean up the files. Need to run cleanup after...
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