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def dwa_control(x, config, goal, ob): """ Dynamic Window Approach control """ dw = calc_dynamic_window(x, config) u, trajectory = calc_final_input(x, dw, config, goal, ob) return u, trajectory
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def decompress_bytes(inp_bytes: bytes, verbose=False) -> bytearray: """ Main function to decompress input bytes by extracting the Huffman map and using the map to replace the encoded sequences with the original characters. :param inp_bytes: Input data to be compressed :param verbose: set to Tru...
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def filter_nans(data, threshold = 3, threshold_type = "data"): """ ================================================================================================= filter_nans(data, threshold, threshold_type) This function is meant to filter out the nan values from...
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def edit_seq2seq_config(config, frameworks=FULL_FRAMEWORKS, no_attn=False): """Rotate frameworks and optionally remove attention.""" configs = [] for fw in frameworks: c = deepcopy(config) c['backend'] = fw configs.append(c) if not no_attn: new_configs = [] # Run ...
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from typing import Optional def get_bioportal_prefix(prefix: str) -> Optional[str]: """Get the Bioportal prefix if available.""" return _get_mapped_prefix(prefix, "bioportal")
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def _obtain_rapt(request, access_token, requested_scopes): """Given an http request method and reauth access token, get rapt token. Args: request (google.auth.transport.Request): A callable used to make HTTP requests. access_token (str): reauth access token requested_scopes ...
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def argunique(items, key=None): """ Returns indices corresponding to the first instance of each unique item. Args: items (Sequence[VT]): indexable collection of items key (Callable[[VT], Any], default=None): custom normalization function. If specified returns items where ``key(...
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def promote_cvals(*vals): """ Promote Python values into the most general dshape containing all of them. Only defined over simple CType instances. >>> promote_vals(1,2.) dshape("float64") >>> promote_vals(1,2,3j) dshape("complex128") """ promoted = np.result_type(*vals) datasha...
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def load_directory_metadata(directory_path, return_copy=True): """ Get stored metadata for files in path. This currently only stores bookmarks. If no metadata is available, return an empty dictionary. This is a hidden file in the directory which stores metadata for all files in the directory, as w...
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def _traverse_tree_and_group_all_objects_by_oclass(root_obj, result=None): """Traverses the tree once and groups all objects by oclass :param root_obj: The root object where to start the traversion :type root_obj: CUDS :param result: The current results of the recursion, defaults to None :type resu...
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def check_measurement(m_info, filters): """ Determine whether a given measurement should be included based on the filters. Inputs: m_info - A dictionary containing the configuration parameters for an individual measurement. filters - A dictionary containing a set of configur...
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def audiosegment2wav(data: AudioSegment): """ pydub.AudioSegment格式转为音频信号wav。 :param data: :return: """ wav = np.array(data.get_array_of_samples()) / _int16_max return wav
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def embargo(cand_times, test_times, embargo_table): """ "Embargo" observations from the training set. Args: cand_times(Series): times of candidates to be the "embargoed set" index: t0(start time) value: t1(end time) test_times(Series): times of the test set ...
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async def async_setup_entry(hass, entry, async_add_entities): """Set up the WiZ Light platform from config_flow.""" # Assign configuration variables. wiz_data = hass.data[DOMAIN][entry.entry_id] wizbulb = WizBulbEntity(wiz_data.bulb, entry.data.get(CONF_NAME), wiz_data.scenes) # Add devices with def...
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async def check_account(): """ A check that checks if the user has an account and if not creates one for them. """ async def check(ctx) -> bool: conn = get_db() cur = conn.cursor() cur.execute("SELECT * FROM economy WHERE user_id = ?", (ctx.author.id,)) if cur.fetchone() ...
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def mtf_image_transformer_base_cifar(): """Data parallel CIFAR parameters.""" hparams = mtf_image_transformer_base() hparams.mesh_shape = "batch:8" hparams.layout = "batch:batch" hparams.learning_rate_decay_steps = 13600 # one epoch hparams.batch_size = 32 hparams.num_heads = 4 hparams.num_decoder_laye...
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def init_group_prams(net): """Initialize group_prams.""" decayed_params = [] no_decayed_params = [] for param in net.trainable_params(): if 'beta' not in param.name and 'gamma' not in param.name and 'bias' not in param.name: decayed_params.append(param) else: no_d...
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def nni_differences_parameters(nni=None, rpeaks=None): """Computes basic statistical parameters from a series of successive NN interval differences (mean, min, max, standard deviation). Parameters ---------- nni : array NN intervals in [ms] or [s]. rpeaks : array R-peak times in [ms] or [s]. Returns (biospp...
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def contextualize_model(model, cell_line, genes): """Contextualize model at the level of a PySB model.""" # Here we just make a PysbAssembler to be able # to apply set_context on the model being passed in model.name = cell_line cell_line_ccle = cell_line + '_SKIN' pa = PysbAssembler() pa.mod...
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def _quaternionInverse(quat): """ Inverses a list of quaternions """ quat_ = np.empty((quat.shape[0],4)) # For every quaternion for i in range(quat.shape[0]): mag = quat[i,0]**2 + quat[i,1]**2 + quat[i,2]**2 + quat[i,3]**2 quat_[i,0] = -quat[i,0]/mag quat_[i,1] = -quat[i,1]...
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from typing import Union def load_dataset(files: list[str]) -> Union[list[int], list[list[list[int]]]]: """load the images and labels of the test dataset Args: files (list[str]): list of files path for images and label dataset Returns: Union[list[int], list[list[list[int]]]]: list of labels and li...
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def get_minion_node_ips(boot_conf, hb_conf): """ Returns a list of IPs for all master nodes :param boot_conf: the snaps-boot configuration dict :param hb_conf: the adrenaline configuration dict :return: a list of IP addresses """ return __get_node_ips(boot_conf, hb_conf, 'minions')
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def _normalize_sql(sql, maxlen=150): """Collapse whitespace and middle-truncate if needed.""" out = ' '.join(sql.split()) if len(out) > maxlen: i = int(maxlen / 2 - 4) out = (out[0:i] + ' . . . ' + out[-i:None]) return out
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from typing import Dict def utt_non_punct_dialog(dialog: Dict): """ Used by: book_skill """ dialog = utils.get_last_n_turns(dialog) dialog = utils.remove_clarification_turns_from_dialog(dialog) return [{"dialogs": [dialog]}]
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def griddata_easy(xx, yy, data, xi=None, yi=None, dx=None, dy=None, nx=10, ny=10, method='nearest', fill_value=None): """ Generate a girdded data from scattered data z=f(x, y) ... Wrapper of scipy.interplate.riddata Parameters ---------- xx: nd array-like x-coordinate of scattered data ...
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def emit_cover(ctx, go_toolchain, source = None, mode = None, importpath = ""): """See go/toolchains.rst#cover for full documentation.""" if source == None: fail("source is a required parameter") if mode == None: fail("mode is a required parameter") if not importpat...
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def shortdate(date=None): """turn (timestamp, tzoff) tuple into iso 8631 date.""" return datestr(date, format='%Y-%m-%d')
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from datetime import datetime import time import numpy def default_fram( object_to_serialize): """ Python json api custom serializer function for FRAM Warehouse API per:'Specializing JSON object encoding', https://simplejson.readthedocs.org >>> import simplejson as json >>> json.dumps({'With...
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import timeit def _benchmark_grep(filename, pattern): """Benchmarks grep. Args: - filename: The name of the file to be searched. - pattern: The pattern we are searching for in the file. """ time_taken = timeit(setup=BENCHMARK_SETUP, number=SINGLE_STRING_TESTS, stmt='subprocess.cal...
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import pathlib def inotify_test( test_paths: dict[str, pathlib.Path], tmp_path: pathlib.Path ) -> InotifyTest: """Generate a pre-configured test instance of `inotify_simple.INotify`. Parameters ---------- test_paths: dict[str, pathlib.Path] The test fixture that generates test files based...
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def set_system_bios( context, settings, system_id = None ): """ Finds a system matching the given ID and sets the BIOS settings Args: context: The Redfish client object with an open session settings: The settings to apply to the system system_id: The system to locate; if None, perfo...
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def create() -> UserSecurityModel: """ Creates a new instance of the USM """ return UserSecurityModel()
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def clDice(v_p, v_l): """[this function computes the cldice metric] Args: v_p ([bool]): [predicted image] v_l ([bool]): [ground truth image] Returns: [float]: [cldice metric] """ if len(v_p.shape)==2: tprec = cl_score(v_p,skeletonize(v_l)) tsens = cl_score(v...
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import re def validate_regex(regex_str): """ Checks if a given string is valid regex :param str regex_str: a suspicios string that may or may not be valid regex :rtype: bool :return: True if valid regex was give, False in case of TypeError or re.error """ # another of those super basic fu...
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import json def load_stats_from_file(date): """ Load stats data from a stat file. Params: date -- a `datetime` instance. """ file_path = _build_stats_file_path(date) if not isfile(file_path): raise IOError # This will be FileNotFoundError in Python3. with open(file_path, 'r...
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def null_gt_null(left, right): """:yaql:operator > Returns false. This function is called when left and right are null. :signature: left > right :arg left: left operand :argType left: null :arg right: right operand :argType right: null :returnType: boolean .. code: yaql> ...
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def read_header(file): """ Read the information in an OpenFOAM file header. Parameters ---------- file : str Name (path) of OpenFOAM file. Returns ------- info : dictionary The information in the file header. """ with open(file, 'r') as f: content = f.read()...
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def point_from_b58(b): """Return b58 decoded P.""" x, y = [int_from_b58(t) for t in b.split(",")] return ECC.EccPoint(x=x, y=y, curve=CURVE)
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def _cp_embeds_into(cp1, cp2): """Check that any state in ComplexPattern2 is matched in ComplexPattern1. """ # Check that any state in cp2 is matched in cp1 # If the thing we're matching to is just a monomer pattern, that makes # things easier--we just need to find the corresponding monomer pattern ...
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def get_tags_for_message(khoros_object, msg_id): """This function retrieves the tags for a given message. .. versionadded:: 2.8.0 :param khoros_object: The core :py:class:`khoros.Khoros` object :type khoros_object: class[khoros.Khoros] :param msg_id: The Message ID for the message from which to re...
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def _build_hierarchical_histogram_computation( lower_bound: float, upper_bound: float, num_bins: int, aggregation_factory: factory.UnweightedAggregationFactory): """Utility function creating tff computation given the parameters and factory. Args: lower_bound: A `float` specifying the lower bound of the...
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import inspect def check_endpoint(func): """Check available endpoint.""" @wraps(func) def wrapper(*args, **kwargs): sig = inspect.signature(func) args_value = sig.bind(*args, **kwargs) endpoint = args_value.arguments["endpoint"] if endpoint not in AVAILABLE_ENDPOINTS: ...
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def read_sql_one(id): """ This function responds to a request for api/reviews/{id} with one matching review from reviews :param id: id of the review :return: review matching the id """ response = Response.query.filter_by(id=id).one_or_none() if response is not None: # serial...
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from typing import Tuple def ds_to_numpy(ds: Dataset) -> Tuple[np.ndarray, np.ndarray]: """Transform torch dataset to numpy arrays Parameters ---------- ds : Dataset COVID dataset Returns ------- Tuple[np.ndarray, np.ndarray] Flattened images + labels """ imgs = ...
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import base64 def _b64(b): """Helper function base64 encode for jose spec.""" return base64.urlsafe_b64encode(b).decode('utf8').replace("=", "")
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def load_from_arff(filename, label_count, label_location="end", input_feature_type='float', encode_nominal=True, load_sparse=False, return_attribute_definitions=False): """Method for loading ARFF files as numpy array Parameters ---------- filename : str path...
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def gapfill_to_ensemble(model, iterations=1, universal=None, lower_bound=0.05, penalties=None, exchange_reactions=False, demand_reactions=False, integer_threshold=1e-6): """ Performs gapfilling on model, pulling reactions from universal. Any existing constraints on base_mod...
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import torch def reparameterize(mu, logvar, n_samples=1): """Reparameterization trick. Args: mu (torch.Tensor): Mean. logvar (torch.Tensor): Logarithm of variation. n_samples (int): The number of samples. Returns: torch.Tensor: Samples drawn from the given Gaussian distri...
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def rotationMatrixFromNormals(v0,v1,tol=1e-20): """ Performs the minimum number of rotations to define a rotation from the direction indicated by the vector n0 to the direction indicated by n1. The axis of rotation is n0 x n1 https://en.wikipedia.org/wiki/Rodrigues%27_rotation_formula ...
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def P_to_array(P: NestedDicts) -> np.array: """ Converts a transition matrix in nested dictionary format to a numpy array. P is usually given as starting state -> action -> ending state w/ data, we reorder this to action -> starting state -> ending state -> transition probability. """ # Action, Sta...
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def get_available_smc_versions(): """ Return list of available SMC versions. SMC versioning is done by d70/smc:v6.1.2. Version returned is after the colon. """ return [repotag for image in get_images(filter='d70/smc') for repotag in image.get('RepoTags')]
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def boolean_fn2(a, b, c): """ Return the truth value of (a ∧ b) ∨ (-a ∧ -b) """ return a and b or not a and not b
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from utils.ica_base import get_configuration def get_ica_gds_configuration() -> libgds.Configuration: """ Get the configuration object for ica wes :return: """ return get_configuration(libgds.Configuration)
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import torch import time def retry_load_images(image_paths, retry=10, backend="pytorch"): """ This function is to load images with support of retrying for failed load. Args: image_paths (list): paths of images needed to be loaded. retry (int, optional): maximum time of loading retrying. D...
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def b2p(exts): """Convert two points of a polygon into its bounding box. (Rectangular polygon parallel with axes.) """ p0x = exts[0][0] p0y = exts[0][1] p0 = str(p0x) + ' ' + str(p0y) + ' ' + '0.0' p1x = exts[0][2] p1y = exts[0][3] p1 = str(p1x) + ' ' + str(p1y) + ' ' + '0.0' pb...
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import re def read_conf_file_interface(config_name): """ Get interface settings. @param config_name: Name of WG interface @type config_name: str @return: Dictionary with interface settings @rtype: dict """ conf_location = WG_CONF_PATH + "/" + config_name + ".conf" with open(conf_l...
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import re def book_transformer(query_input, book_dict_input): """grabs the book and casts it to a list""" sample_version = versions_dict.versions_dict() query_input[1] = query_input[1].replace('[', '').replace(']', '').lstrip().rstrip().upper() for i in list(book_dict_input.keys()): result = r...
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import json def custom_response(message, status, mimetype): """handle custom errors""" resp = Response(json.dumps({"message": message, "status_code": status}), status=status, mimetype=mimetype) return resp
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def embed_network(input_net, layers, reuse_variables=False): """Convolutional embedding.""" n_layers = int(len(layers)/3) tf.logging.info('Number of layers: %d' % n_layers) # set normalization and activation functions normalizer_fn = None activation_fn = tf.nn.softplus tf.logging.info('Softplus activati...
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def sample_variance(sample1, sample2): """ Calculate sample variance. After learn.co """ n_1, n_2 = len(sample1), len(sample2) var_1, var_2 = variance(sample1), variance(sample2) return (var_1 + var_2)/((n_1 + n_2)-2)
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def calculate_area(geometry): """ Calculate geometry area :param geometry: GeoJSON geometry :return: the geometry area """ coords = get_coords_from_geometry( geometry, ["Polygon", "MultiPolygon"], raise_exception=False ) if get_input_dimensions(coords) >= 4: areas = l...
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from pathlib import Path import re def read_prb(file): """ Read a PRB file and return a ProbeGroup object. Since PRB do not handle contact shape then circle of 5um are put. Same for contact shape a dummy tip is put. PRB format do not contain any information about the channel of the probe Onl...
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def CreateNode(parent, node_type, position, wx_id): """ Create an instance of a node associated with the specified name. :param parent: parent of the node object (usually a wx.Window) :param node_type: type of node from registry - the IDName :param position: default position for the node :param wx_...
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import json def decode_json_content(content): """ Decodes a given string content to a JSON object :param str content: content to be decoded to JSON. :return: A JSON object if the string could be successfully decoded and None otherwise :rtype: json or None """ try: return json.loads...
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def plot_dist(noise_feats, label=None, ymax=1.1, color=None, title=None, save_path=None): """ Kernel density plot of the number of noisy features included in explanations, for a certain number of test samples """ if not any(noise_feats): # handle special case where noise_feats=0 noise_feat...
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import chunk def simple_simulate(choosers, spec, nest_spec, skims=None, locals_d=None, chunk_size=0, custom_chooser=None, log_alt_losers=False, want_logsums=False, estimator=None, trace_label=None, ...
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def state(predicate): """DBC helper for reusable, simple predicates for object-state tests used in both preconditions and postconditions""" @wraps(predicate) def wrapped_predicate(s, *args, **kwargs): return predicate(s) return wrapped_predicate
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import math def dpp(kernel_matrix, max_length, epsilon=1E-10): """ Our proposed fast implementation of the greedy algorithm :param kernel_matrix: 2-d array :param max_length: positive int :param epsilon: small positive scalar :return: list """ item_size = kernel_matrix.shape[0] cis...
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def adjust_image_resolution(data): """Given image data, shrink it to no greater than 1024 for its larger dimension.""" inputbytes = cStringIO.StringIO(data) output = cStringIO.StringIO() try: im = Image.open(inputbytes) im.thumbnail((240, 240), Image.ANTIALIAS) # co...
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from datetime import datetime def parse_date(txt): """ Returns None or parsed date as {h, m, D, M, Y}. """ date = None clock = None for word in txt.split(' '): if date is None: try: date = datetime.strptime(word, "%d-%m-%Y") continue exc...
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def calc_angle(m, n): """ Calculate the cosθ, where θ is the angle between 2 vectors, m and n. """ if inner_p_s(m, n) == -1: print('Error! The 2 vectors should belong on the same space Rn!') elif inner_p_s(m,n) == 0: print('The cosine of the two vectors is 0, so th...
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def Seuil_var(img): """ This fonction compute threshold value. In first the image's histogram is calculated. The threshold value is set to the first indexe of histogram wich respect the following criterion : DH > 0, DH(i)/H(i) > 0.1 , H(i) < 0.01 % of the Norm. In : img : ipl Image : image to treated ...
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def convert_numpy(file_path, dst=None, orient='row', hold=False, axisf=False, *arg): """ Extract an array of data stored in a .npy file or DATABLOCK Parameters --------- file_path : path (str) Full path to the file to be extracted. dst : str Full path to the file wh...
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def index(): """Every time the html page refreshes this function is called. Checks for any activity from the user (setting an alarm, deleting an alarm, or deleting a notification) :return: The html template with alarms and notifications added """ notification_scheduler.run(blocking=False) ...
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import json import time def check_icinga_should_run(state_file: str) -> bool: """Return True if the script should continue to update the state file, False if the state file is fresh enough.""" try: with open(state_file) as f: state = json.load(f) except Exception as e: logger.e...
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def ln_new_model_to_gll(py, new_flag_dir, output_dir): """ make up the new gll directory based on the OUTPUT_MODEL. """ script = f"{py} -m seisflow.scripts.structure_inversion.ln_new_model_to_gll --new_flag_dir {new_flag_dir} --output_dir {output_dir}; \n" return script
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def deserialize_item(item: dict): """Deserialize DynamoDB item to Python types. Args: item: item to deserialize Return: deserialized item """ return {k: DDB_DESERIALIZER.deserialize(v) for k, v in item.items()}
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def good_result(path_value, pred, source=None, target_path=''): """Constructs a JsonFoundValueResult where pred returns value as valid.""" source = path_value.value if source is None else source return jp.PathValueResult(pred=pred, source=source, target_path=target_path, path_value=pat...
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def bot_properties(bot_id): """ Return all available properties for the given bot. The bot id should be available in the `app.config` dictionary. """ bot_config = app.config['BOTS'][bot_id] return [pd[0] for pd in bot_config['properties']]
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def find_path(ph_tok_list, dep_parse, link_anchor, ans_anchor, edge_dict, ph_dict): """ :param dep_parse: dependency graph :param link_anchor: token index of the focus word (0-based) :param ans_anchor: token index of the answer (0-based) :param link_category: the category of the current focus link ...
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import logging def download_video_url( video_url: str, pipeline: PipelineContext, destination="%(title)s.%(ext)s", progress=ProgressMonitor.NULL, ): """Download a single video from the .""" config = pipeline.config logger = logging.getLogger(__name__) logger.info("Starting video downl...
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def get_block_name(source): """Get block name version from source.""" url_parts = urlparse(source) file_name = url_parts.path extension = file_name.split(".")[-1] new_path = file_name.replace("." + extension, "_block." + extension) new_file_name = urlunparse( ( url_parts.s...
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import token def int_to_symbol(i): """ Convert numeric symbol or token to a desriptive name. """ try: return symbol.sym_name[i] except KeyError: return token.tok_name[i]
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def cranimp(i, s, m, N): """ Calculates the result of c_i,s^dag a_s acting on an integer m. Returns the new basis state and the fermionic prefactor. Spin: UP - s=0, DOWN - s=1. """ offi = 2*(N-i)-1-s offimp = 2*(N+1)-1-s m1 = flipBit(m, offimp) if m1<m: m2=flipBit(m1, offi) if m2>m1: prefactor = prefac...
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def _can_beeify(): """ Determines if the random chance to beeify has occured """ return randint(0, 12) == 0
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def get_object_classes(db): """return a list of all object classes""" list=[] for item in classinfo: list.append(item) return list
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def get_ax(rows=1, cols=1, size=8): """Return a Matplotlib Axes array to be used in all visualizations in the notebook. Provide a central point to control graph sizes. Change the default size attribute to control the size of rendered images """ _, ax = plt.subplots(rows, cols, figsize=(size...
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def spin_coherent(j, theta, phi, type='ket'): """Generates the spin state |j, m>, i.e. the eigenstate of the spin-j Sz operator with eigenvalue m. Parameters ---------- j : float The spin of the state. theta : float Angle from z axis. phi : float Angle from x axis...
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from operator import add def vgg_upsampling(classes, target_shape=None, scale=1, weight_decay=0., block_name='featx'): """A VGG convolutional block with bilinear upsampling for decoding. :param classes: Integer, number of classes :param scale: Float, scale factor to the input feature, varing from 0 to 1 ...
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def compute_metrics(logits, labels, weights): """Compute summary metrics.""" loss, weight_sum = compute_weighted_cross_entropy(logits, labels, weights) acc, _ = compute_weighted_accuracy(logits, labels, weights) metrics = { 'loss': loss, 'accuracy': acc, 'denominator': weight_sum, } return...
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def start_session(web_session=None): """Starts a SQL Editor Session Args: web_session (object): The web_session object this session will belong to Returns: A dict holding the result message """ new_session = SqleditorModuleSession(web_session) result = Response.ok("New SQL Edit...
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async def error_middleware(request: Request, handler: t.Callable[[Request], t.Awaitable[Response]]) -> Response: """logs an exception and returns an error message to the client """ try: return await handler(request) except Exception as e: logger.exception(e) return json_response(...
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def init_mobility_accordion(): """ Initialize the accordion for mobility tab. Args: None Returns: mobility_accordion (object): dash html.Div that contains individual accordions """ accord_1 = init_accordion_element( title="Mobility Index", id='id_mobility_index', ...
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def per_image_whiten(X): """ Subtracts the mean of each image in X and renormalizes them to unit norm. """ num_examples, height, width, depth = X.shape X_flat = X.reshape((num_examples, -1)) X_mean = X_flat.mean(axis=1) X_cent = X_flat - X_mean[:, None] X_norm = np.sqrt( np.sum( X_cent * X...
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def fill_defaults(data, vals) -> dict: """Fill defaults if source is not present""" for val in vals: _name = val['name'] _type = val['type'] if 'type' in val else 'str' _source = val['source'] if 'source' in val else _name if _type == 'str': _default = val['default']...
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def static_shuttle_between(): """ Route endpoint to show real shuttle data within a certain time range at once. Returns: rendered website displaying all points at once. Example: http://127.0.0.1:5000/?start_time=2018-02-14%2015:40:00&end_time=2018-02-14%2016:02:00 """ start_tim...
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def read_data(inargs, infiles, ref_cube=None): """Read data.""" clim_dict = {} trend_dict = {} for filenum, infile in enumerate(infiles): cube = iris.load_cube(infile, gio.check_iris_var(inargs.var)) if ref_cube: branch_time = None if inargs.branch_times[filenum] == 'default...
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import json async def create_account(*, user): """ Open an account for a user Save account details in json file """ with open("mainbank.json", "r") as f: users = json.load(f) if str(user.id) in users: return False else: users[str(user.id)] = {"wallet": 0, "bank": 0}...
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import ntpath import genericpath def commonpath(paths): """Given a sequence of path names, returns the longest common sub-path.""" if not paths: raise ValueError('commonpath() arg is an empty sequence') if isinstance(paths[0], bytes): sep = b'\\' altsep = b'/' curdir = b'...
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from .slicing import sanitize_index from functools import reduce from operator import mul import tokenize from re import M def reshape(x, shape): """ Reshape array to new shape This is a parallelized version of the ``np.reshape`` function with the following limitations: 1. It assumes that the array...
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