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from datetime import datetime def count_time(time_logon,time_logoff): """count the logoning time Arg: time_longon: for example, 07:20:00 time_logoff: for example, 15:20:00 return: last_time: float, the number of hours of online. """ time_logon=datetime.strptime(time_logon,'%H:%M:%...
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from contextlib import suppress def _purge_headers_cb(headers): """ Remove headers from the response. Args: headers (list): headers to remove from the response Returns: callable: for been used in before_record_response VCR constructor. """ header_list = [] for item in he...
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import shlex def tokenize(string): """ # parse the command # 比如,'ls -l /home/shiyanlou' 划分之后就是 # ['ls', '-l', '/home/shiyanlou'] :param string: :return: """ return shlex.split(string)
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import re def get_label_and_caption(lines, i): """Capture any label and caption immediately after a code environment's end Use regex on the two lines after a code environment's end (e.g. !ec) to extract any label or caption. NB! This method might modify the two lines after the code environment by rem...
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def post_compute(e, q, d): """ Get single result, like a sum or count, from mongodb query """ field = e.dshape[0].names[0] result = q.coll.aggregate(list(q.query))['result'] return result[0][field]
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def compute_yield(x): """ Compute yield as measured with UMIs for a droplet x. """ return x["az_total"]*x["nb_hp"]*10.0/x["hp_total"]
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def compute_multiples(origin_shape, broadcast_shape): """Compute multiples between origin shape with broadcast shape.""" len_gap = len(broadcast_shape) - len(origin_shape) return broadcast_shape[0:len_gap] + tuple(map(lambda x, y: x // y, broadcast_shape[len_gap:], origin_shape))
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def area_is_at_diagonal(i, j): """ Find whether extracted area is from the diagonal. Parameters: i -- First interval index. j -- Second interval index. Output: Whether an area is at the diagonal. """ return(i == j)
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import pkgutil import encodings def encoding_exists(encoding): """Check if an encoding is available in Python""" false_positives = set(["aliases"]) found = set(name for imp, name, ispkg in pkgutil.iter_modules(encodings.__path__) if not ispkg) found.difference_update(false_positives) if encoding: ...
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def assign_worksessions(df, threshold=1, milliseconds=True): """Assign work sessions to events, in a column called workSessionId. """ delimit_hours = threshold * 3600 if milliseconds: delimit_hours = delimit_hours * 1000 df['newSession'] = df['time'].diff() > delimit_hours # diff > thre...
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import pickle def deserialize(src): """ The default deserialization method, can automatically read the version number, so no need to specify Parameters ---------- src Returns ------- """ return pickle.loads(src)
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def get_descriptions(nzo, match, name): """If present, get a description from the nzb name. A description has to be after the matched item, separated either like ' - Description' or '_-_Description' """ if nzo: ep_name = nzo.nzo_info.get("episodename") else: ep_name = "" if n...
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def terminate(library, session, degree, job_id): """Request a VISA session to terminate normal execution of an operation. Corresponds to viTerminate function of the VISA library. Parameters ---------- library : ctypes.WinDLL or ctypes.CDLL ctypes wrapped library. session : VISASession ...
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import time def select_timestamp(entry): """ Returns the date and time `entry` was updated, published or created (respectively) as a time-tuple. """ for attr in ('updated', 'published', 'created'): try: return entry['%s_parsed'] % attr except KeyError: pass ...
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import datetime def create_table_schema(df, table_name): """Generates a SQL create table statement based off the columns (and their dtypes) in a Pandas dataframe""" sql_obj_mapping={'string':'VARCHAR (255)', 'integer':'INT', 'float':'FLOAT', 'date...
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def calculate_dynamic_pressure(rho, TAS): """Calculates the dynamic pressure. Parameters ---------- rho : float Air density (kg/m³). TAS : float True Air Speed (m/s). Returns ------- q_inf : float Dynamic pressure. (Pa) Notes ----- $$ q_{inf} = 1/2 ...
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from pathlib import Path def test_directory(): """Return the path to the top-level directory containing the tests.""" return Path(__file__).parent
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def reindex_elements_in_tree(result): """ Change the level numbers from parent to chil Before it was from children to parent :param result: dict format of element specification :return: result_list reindexed """ result_list = [values for index, values in result.items()] # pp(result_list...
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def parse_hostnames_from_ingresses(ingress_list): """ This function parses a list of Ingress objects into a map of hostname=>address """ hostnames = {} for ingress in ingress_list: rules = ingress.spec.rules if ingress.status.load_balancer.ingress is None: continue ...
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from pathlib import Path import re def get_min_ver(dependency: str) -> str: """Retrieve version of `dependency` from setup.py, raise if not found.""" setup_py = Path(__file__).parent.joinpath("../../../setup.py") with open(setup_py, "r") as setup_file: for line in setup_file.readlines(): ...
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def init(module, weight_init, bias_init, gain=1): """ Parameters ---------- module : nn.Module nn.Module to initialize. weight_init : func Function to initialize module weights. bias_init : func Function to initialize module biases. Returns ------- module : nn...
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def convert_ftp_url(url): """Convert FTP to HTTPS URLs.""" return url.replace('ftp://', 'https://', 1)
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import warnings def _fix_auth(auth, username=None, password=None, verify=None, cert=None): """Updates auth from deprecated parameters username, password, verify and cert.""" if any(p is not None for p in (username, password, verify, cert)): message = 'The use of "username", "password", "verify", and "...
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import torch import random def addGaussianNoise2Image(images, labels, std=0.1, shuffle=True, device=None): """ 给图片添加高斯噪声 原图片的标签为1:正样本 添加了噪声的图片的标签为0:负样本 """ images = images.float().to(device) labels = labels.float().to(device) batch_size = labels.size(0) labels = torch.unsqueeze(lab...
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def postproc(maps): """Generate PD, R1, R2* (and MTsat) volumes from log-parameters Parameters ---------- maps : ParameterMaps Returns ------- pd : ParameterMap r1 : ParameterMap r2s : ParameterMap mt : ParameterMap, optional """ maps.r1.volume = maps.r1.fdata().exp_()...
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def join_dict(keys, values): """ Create a dictionary from a list of keys and values having equal lengths """ if len(keys) == len(values): adict = dict(zip(keys, values)) return adict else: print('Error: Attempting to create a dictionary from ' 'a key and val...
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from typing import List def get_whitespace_operations(from_sequence: str, to_sequence: str) -> List[int]: """ Get the repair sequence that turns from_sequence into to_sequence (after applying the repair_whitespace function) :param from_sequence: sequence that the returned repair tokens should be applied...
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import json def read_values(file): """ The function deserialize the JSON string from a file using json.load method. """ try: with open(file) as f: data = json.load(f) return data except IOError: print('An IOError has occured!')
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def ticker_price_history(data, ticker): """filter time history of the specifed ticker, history of ticker close price """ tts_sub = data[[("Close", ticker)]] # ticker time series tts_sub = tts_sub.reset_index() tts_sub.columns = tts_sub.columns.droplevel() tts_sub.columns = ["time_ts", "close_price"...
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def batch_norm(inputs, activation_fn=None, normalizer_fn=None, normalizer_params=None): """Batch normalization layer compatible with the classic conv. API. Simpler to use with arg. scopes. """ outputs = inputs # BN... if normalizer_fn is not None: ...
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import torch def squash(input_tensors, dim=2): """ Squashing function Parameters ---------- input_tensors : a tensor dim: dimensions along which to apply squashing Returns ------- squashed : torch.FloatTensor A tensor of shape ``(batch_size, num_tokens, input_dim)`` . ...
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def sanitize(address): """ Sanitize the location field if needed. :param str address: address to sanitize """ # Remove 'block of ' from the address. addr = address.lower() addr = addr.replace('block of ', '') addr = addr.replace('block ', '') return addr
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import sys import io def capture_output(func): """Decorate a function with @capture_output to define a CapturedFunction() wrapper around it. Doesn't currently capture non-python output but could with dup2. Decorate any function to wrap it in a CapturedFunction() wrapper: >>> @capture_output ...
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def bool_to_str(val): """ bool类似转化为是或否,为空则保留 """ return val if not isinstance(val, bool) else val and '是' or '否'
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def paint(width, height, performance): """Calculates how many paint does one need for given area @param width: area's width @param height: area's height @param performance: paint performance/m^2""" area = width * height return area / performance
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import torch def decode(box_p, priors): """ Decode predicted bbox coordinates using the same scheme employed by Yolov2: https://arxiv.org/pdf/1612.08242.pdf b_x = (sigmoid(pred_x) - .5) / conv_w + prior_x b_y = (sigmoid(pred_y) - .5) / conv_h + prior_y b_w = prior_w * exp(loc_w) ...
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import pandas def flatten_results_dataset(dataset, row_levels=frozenset({'output'})): """Given an xarray.Dataset with results, flatten it into a pandas.DataFrame. This function individually unstacks arrays, which results in a much more compact DataFrame than calling `dataset.to_dataframe()`. Args: datas...
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from functools import reduce def test_reduce(): """ Test reduce 当需要对一个列表进行一些计算并返回结果时,Reduce 是个非常有用的函数。 """ product = reduce((lambda x, y: x * y), [1, 2, 3, 4]) return product
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def cross(environment, book, row, sheet_source, column_source, column_key): """ Returns a single value from a column from a different dataset, matching by the key. """ a = book.sheets[sheet_source] return environment.copy(a.get(**{column_key: row[column_key]})[column_source])
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from typing import Dict from typing import Iterable def build_pattern_registrar(d: Dict): """ :param d: a dictionary-like object that patterns will be registered to :return: a function that """ def registrar(pattern: int, first_nibbles: Iterable) -> None: """ :param pattern: a c...
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def example_smiles_n_features(): """ Sample data for testing Returns ------- dictionary format {'smiles':required feature vector : List} """ feature_vector_C = [[ 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,...
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from typing import Dict from pathlib import Path def _certificate_check(path) -> Dict[str, Path]: """ Check if the right certificates are at the given path. """ certi_path = { "ca": "ca.crt", "crt": "client.crt", "key": "client.key", } r_paths: Dict[str, Path] = {} ...
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def map_unconstrained_range( x: float, in_min: float, in_max: float, out_min: float, out_max: float ) -> float: """ Maps a number from one range to another. Somewhat similar to the Arduino :attr:`map()` function, but returns a floating point result, and does not constrain the output value to be betw...
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def get_add_dict(add_default_dict, request): """ 组合新增字典 :param add_default_dict: :param request: :return: """ add_dict = {} if add_default_dict: for k, v in add_default_dict.items(): add_dict[k] = v(request) return add_dict
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def flatten_series(): """ By default, MIPPY will pass the image datasets as a 2D list, divided by series. If you want only a single, flat list from all your series, return True. """ return True
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def find_unique_value_error(exc_detail): """Find unique value error in exception details.""" for field, errors in exc_detail.items(): # noqa: B007 for error in errors: if error.code == 'unique': return error return None
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def split_and_strip(string, delimiter): """ Return a list of stripped strings after splitting `string` by `delimiter`. Parameters ---------- string : str The string to split and strip. delimiter : str The string to split by. Returns ------- list[str] The lis...
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import requests def get_word_count(title, base_url="https://klexikon.zum.de/api.php") -> int: """ Return the word count of an Klexikon article. :param title: :param base_url :return: """ params = { "action": "query", "format": "json", "list": "search", "srli...
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import math def f0(system): """Return the natural frequency of the system.""" c1,c2,r1,r2 = system fn = 1 / (2 * math.pi * math.sqrt(r1 * c1 * r2 * c2)) return fn
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def component(): """ Returns a test component. """ return { "name": "foo", "display_name": "Foo", "attributes": [] }
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import os def reduce_2_basename(files): """ Converts full file paths to file base names. Parameters ---------- files : list of str list of filepaths Returns ------- filenames : list of str List of base file names. """ return [os.path.basename(f) for f in files...
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import time def wait_for_translation(client, id): """Wait for a translation to finish""" while True: res = client.get_translation_status(id) res_data = res.json() state = res_data['requestState'] if state == 'ACTIVE': time.sleep(2) continue else:...
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from math import log, sqrt def calculate_d1(underlying, strike, domestic_short_rate, foreign_short_rate, sigma, days_to_maturity): """ d1 = (ln(i_F/i_S) + ((r_d - r_f) + 1/2 * sigma^2) * T) / (sigma * sqrt(T)) :param domestic_short_rate: :param foreign_short_rate: :param underlying: :param strike:...
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def get_last_data_idx(productions): """ Find index of the last production :param productions: list of 24 production dict objects :return: (int) index of the newest data or -1 if no data (empty day) """ for i in range(len(productions)): if productions[i]['total'] < 1000: retur...
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import re def split_keyword(keyword): """Split a keyword in multiple ones on any non-alphanumeric character :param string keyword: keyword :return: keywords :rtype: set """ split = set(re.findall(r'\w+', keyword)) return split
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import subprocess import sys import re def get_sub_track_id(file, num): """Returns wanted sub track id and type of subs""" # could also use ffprobe to json as it turns out try: raw_info = subprocess.check_output(["mkvmerge", "-i", file], stderr=subprocess...
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def valid_history(history, expected_count, expected_messages=None): """Checks if history is valid""" expected_messages = expected_messages or [] if len(history) != expected_count: return False for i, value in enumerate(expected_messages): if history[i]["type"] != value: retur...
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import math def select_dim_over_m(maxM, maxN, coef_nm, coef_n, coef_m, tot, rest=0): """ solves the problem, max n*m such that n <= maxN, m <= maxM and coef_nm*nm + coef_n*n + coef_m*m <= tot """ tot = tot - rest # We consider x = m = n and solve the quadratic equation b = coef_n + coef_m ...
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def _get_main_opset_version(model): """ Returns the main opset version. """ for op in model.opset_import: if op.domain == '' or op.domain == 'ai.onnx': return op.version return None
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def compute_ref_area(body_chord, body_span, tran_chord, tran_span, wing_chord, wing_span, wing_tip_chord): """ Simple sum of 3 trapezoids. """ body_area = 0.5*(body_chord+tran_chord)*body_span tran_area = 0.5*(tran_chord+wing_chord)*tran_span wing_area = 0.5*(wing_chord+wing...
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import os def getAndAppend(name, append): """Retrieves the given environment variable and appends the given string to its value and returns the new value. The environment variable is not modified. Returns an empty string if the environment variable does not exist.""" if name in os.environ: ...
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import pandas def load_csv_as_dataframe_from_web(url, dtype=None): """Loads csv data from the provided url to a DataFrame. Expects the data to be in csv format, with the first row as the column names. url: url to download the csv file from""" return pandas.read_csv(url, dtype=dtype)
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def get_package_data(): """ Returns the packages with static files of Wapyce. :return: The packages with static files of Wapyce. :rtype: dict(str, list(str)) """ package_data = {'': ['requirements.txt']} return package_data
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def introduction(): """Handle a request for the "Introduction" page. This function really doesn't do much, but it returns the data contained at views/introduction.tpl which contains some detail on the project and useful links to other information. Returns: (string) A web page (via the @vie...
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def create_parser(subparsers): """Parse the arguments for the train command. Returns ------- parser : ArgumentParser """ train_parser = subparsers.add_parser('train', help='Train MARL policies ') train_parser.add_argument( 'configuration', type=str, help='Path to python config f...
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import math def _tree_depth(num_leaves: int, arity: int): """Returns the depth of the tree given the number of leaf nodes and arity.""" return math.ceil(math.log(num_leaves) / math.log(arity)) + 1
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from typing import Any def _rebase_entity_dict( entity_dict: str, group: dict[str, Any], base_channel_no: int ) -> dict[int, Any]: """Rebase entity_dict with base_channel_no.""" new_fields = {} if fields := group.get(entity_dict): for channel_no, field in fields.items(): new_fields...
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from pathlib import Path import subprocess def current_git_hash() -> str: """ Retrieve the current git hash number of the git repo (first 6 digit). """ repo_dir = Path(__file__).parent git_show = subprocess.Popen( 'git rev-parse --short=6 HEAD', stdout=subprocess.PIPE, stderr=subpr...
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import io def _text_reader(text_file): """Returns list of lines from the text file. Performs lowercasing and white-space tokenization on each line before returning. Slightly different than the one in totto_parent_eval.py. Args: text_file: String filename. """ texts = [] with io.open(text_file, enc...
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def obtainDifferences(redundantDict, transformationContext): """ analize what is different between similar rules (same rc, rate and actions) throw unions and intersections of their context """ redundantListDict = {} for center in redundantDict: for rate in redundantDict[center]...
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import copy def flatten_dict(dictionary, flatten_key_method='tuple'): """ This function recursively flattens an arbitrarily nested dictionary. The keys into the flattened dictionary are tuples of the form (key0, key1, key2..) """ dictionary = copy.deepcopy(dictionary) to_flatten = {} ...
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def __top_frond_right(dfs_data): """Returns the frond at the top of the RF stack.""" return dfs_data['RF'][-1]
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def evaluate_sampler( sampler_fn, obs, action ): """ :param sampler_fn: fn(o,k) Function returning sample value [p1,p2..] List of values per-arm p1 Scalar value for all arms :param obs: :param action: :return: """ if callable(sampler_fn): sampl...
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def yx_to_xy(yx_grid): """Turns a y/x grid (row, column) into an x/y grid. Iterates through the yx grid keeping track of the current location, and maps that value to the corresponding position within the xy grid :param map: int[][], a typical ingested y/x grid :return: int[][], a RHR cartesian x,y g...
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def hash_2(): """ Test hash 2 """ return "9afab28587926ce230e2e4430becc599"
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import copy def unwind(data, max_depth = 1000, stop_term = ''): """ Unwind nested dictionaries by repeating higher level fields. Args: max_depth: (int), maximum depth to unwind. stop_term: (str), stop unwinding once this term appears as a key in dict. Returns: ...
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def generate_header_file_main_type_recursive(parent, command, h): """ Generates a struct with callbacks, one callback for each subcommand. These callbacks are called when user issues a subcommand. """ if parent is None: h += "struct CliParamsAll {\n" command_name = command.get("name", N...
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def fetch_data_fake(): """ Creating fake function to deliver the result """ print("fetching fake data") return { "name": "Valee", "age": 40 }
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import math def delta_angle_degrees(from_angle_degrees, to_angle_degrees): """Calculates the shortest signed delta angle.""" delta = to_angle_degrees - from_angle_degrees return delta - 360.0 * math.floor((delta + 180.0) / 360.0)
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def slowComplete(prefix, list_of_words, top): """ For a given prefix, provide top suggestions from this list of words. Parameters ---------- prefix: Signal word used here list_of_words: a file that has the example format top: top many suggestions as output Return ------ the top k recommendations with given ...
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def train_step(loss): """ Defines the ops to conduct an optimization step. You can set a learning rate scheduler or pick your favorite optimizer here. This set of operations should be applicable to both ConvNet() and Siamese() objects. Args: loss: scalar float Tensor, full loss = cross_entropy ...
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def get_folder_items(bucket_items, folder_prefix): """ Returns items in bucket which belong to a folder :param bucket_items: items in the bucket :param folder_prefix: prefix containing the folder name :return: list of items in the folder without the folder prefix """ return [ item['...
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def list_books(args): """List books in this room.""" print('List books of type %s' % args.type) return 0
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def to_palindrome(seq): """ Generates two possible palindromic sequence from the input sequence """ init_type = type(seq) if not (init_type is str or init_type is int): raise TypeError("Input a string or integer only") if init_type == int: seq = str(seq) forward = seq + seq[...
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from typing import Tuple def bbox_center(p: Tuple[float, float], q: Tuple[float, float]) -> Tuple[float, float]: """ Return middle point between two points p and q. """ (min_lon, min_lat), (max_lon, max_lat) = p, q center = min_lon + (max_lon - min_lon) / 2, min_lat + \ (ma...
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import math def generate_timecode(ms: int) -> str: """ Convert a duration in seconds to ISO8601 hh:mm:ss.sss format """ hours = math.floor(ms / (60 * 60 * 1000)) minutes = math.floor(ms / (60 * 1000)) % 60 seconds = math.floor(ms / 1000) % 60 milliseconds = ms % 1000 return ( s...
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def map_args(tree, args): """ Given a tree and a list of arguments, produce the tree with the arguments instead of integers at the leaves of the tree. E.g. for tree = [[1, 2], [3, 4]] and args = [a, b, c, d] we get [[a, b], [c, d]]. """ (s, t, a) = tree if a[0] == 1: return ...
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def _TransformOperationName(resource): """Get operation name without project prefix.""" # operation name is in the format of: # operations/projects/{}/instances/{}/.../locations/{}/operations/{} operation_name = resource.get('name') results = operation_name.split('/') short_name = '/'.join(results[3:]) re...
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def questionnaire_single(): """ What to ask if only one lookup is needed. """ while True: scanos = input("OS (ex. AAD250): ") branch = scanos[:3] floor = scanos[3:6] quants = [len(scanos) == 6, branch.isalpha(), floor.isdigit()] if not all(quants): pri...
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def expected_status(status_csv_path): """Loads pre-rendered, uncolored status table layouts""" def load_expected_status(expected_status_file): with open(status_csv_path(expected_status_file), "r") as es_file: expected_status = es_file.readlines() return ''.join([line for line in...
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def relative_date_to_str(relative_date: int) -> str: """Convert a relative date to a human readable text.""" mapping = { -2: "vorgestern", -1: "gestern", 0: "heute", 1: "morgen", 2: "übermorgen" } return mapping.get(relative_date, f"vor {relative_date} Tagen" if...
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def shorten(name): """ Shortens full name to use to compare and group """ first_last = name.split(" ") short = first_last[0][0] + "." short+="".join(first_last[1:]) return short
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def _get_queue_choices(queues): """Return list of `choices` array for html form for given queues idea is to return only one choice if there is only one queue or add empty choice at the beginning of the list, if there are more queues """ queue_choices = [] if len(queues) > 1: queue_choi...
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import re def find_col_index(header, col_name): """ Extracts the column index of the given variable in the data. Given a list of headers, searches the list for one that first one that contains the col_name. Uses regex match to search through each header. Parameters ---------- header : list o...
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import os def load_image(logo_image): """Load Bank Image""" pyboleto_dir = os.path.dirname(os.path.abspath(__file__)) image_path = os.path.join(pyboleto_dir, 'media', logo_image) return image_path
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import numpy def get_data_tuple(molecules, indices): """ Take list of molecules and indices, return (x, y) for training machine learning models. :param molecules: List of molecules. :param indices: Indices of molecules that should be in (x, y). :return: """ data = [molecules[x] for x ...
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def formatMultiplier(stat : float) -> str: """Format a module effect attribute into a string, including a sign symbol and percentage symbol. :param stat: The statistic to format into a string :type stat: float :return: A sign symbol, followed by stat, followed by a percentage sign. """ return f...
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def camel2snake(text): """Convert camel case to snake case. This assumes the input is valid camel case (if you have some weird hybrid of camel and snake case, for instance, you'd want to do some preprocessing first). Parameters ---------- text: str Camel case string, e.g. vaderSentiment...
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def sensor_cfg(sensor): """ parses sensor configuration file and select right bias for sensor input: sensor: sensor number in string\ returns: sensor_bias for each axis """ sensor_cfg = '/home/james/catkin_ws/src/cp_simulator/cfg/sensor.cfg' f = open(sensor_cfg, 'r') contents = f.read() contents = conten...
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def get_color(color): """ Can convert from integer to (r, g, b) """ if not color: return None if isinstance(color, int): temp = color blue = temp % 256 temp = int(temp / 256) green = temp % 256 temp = int(temp / 256) red = temp % 256 return...
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