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import six def compact(seq): """ Removes ``None`` values from various sequence-based data structures. dict: Removes keys with a corresponding ``None`` value. list: Removes ``None`` values. >>> compact({'foo': 'bar', 'baz': None}) {'foo': 'bar'} >>> compact([1, None, 2])...
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def remove(bowl_a, bowl_b): """Return bowl b without the "ingredients" of bowl_a.""" for ingredient in bowl_a: # If an ingredient is also in bowl_a and bowl_b - remove it. if ingredient in bowl_b: bowl_b.remove(ingredient) return bowl_b
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from typing import Optional from pathlib import Path from typing import Tuple def _load_root_datadir( datadir_txt: Optional[Path], ) -> Tuple[Optional[Path], Optional[Path]]: """ Locate the root and datadir, returning Paths if possible. Uses the location of the datadir.txt file to define the data dir...
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def halfstring(inputstr): """Return the first half of a string.""" strlen = len(inputstr) return inputstr[:strlen / 2]
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def check_suffix_exists(obj_name, suffix): """ Checks whether given suffix in given Maya node or not :param obj_name: str, name of the object to check suffix of :param suffix: str, suffix to check :return: bool, Whether given suffix already exists in given node or not """ base_name_split = ...
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def remove_nulls(dictionary, deep=True): """ Removes all null values from a dictionary. """ return { k: remove_nulls(v, deep) if deep and type(v) is dict else v for k, v in dictionary.items() if v is not None }
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def to_dict_query(self) -> list: """Returns all SQLAlchemy records in a query as dictionaries.""" return [row.to_dict() for row in self.all()]
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import json def read_config(config_path): """Reads config :param config_path: path to configuration file :returns: dict with configuration data """ with open(config_path, "r") as fo: config = json.loads(fo.read()) return config
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def positive_index(index, size): """ Return a positive index from any index. If the index is positive, it is returned. If negative, size+index will be returned. Parameters ---------- index : int The input index. size : int The size of the indexed dimension. Returns ...
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def _has_valid_syntax(row): """ Check whether a given row in the CSV file has the required syntax, i.e. - lemma is an existing string object - example sentence is a string and contains at least one pair of lemma markers in the right order - score is one of the following strings: '0', '1', '2', '3', ...
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from pathlib import Path def test_images_dir() -> Path: """ Returns the filesystem path corresponding to the location of test VASP images. DiSPy-API (root) -> tests -> test_images """ return Path(__file__).parent.parent.parent / "tests/test_images"
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def get_report_png_by_id(triage_instance, report_id): """Fetch and return the PNG file associated with the specified report_id""" return triage_instance.request( f"reports/{report_id}.png", raw_response=True ).content
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def _startswith_and_remainder(string, prefix): """Returns if the string starts with the prefix and the string without the prefix.""" if string.startswith(prefix): return True, string[len(prefix):] else: return False, ''
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import torch def softmax_sample(x): """Sample the categorical distribution from logits and sample it.""" dist = torch.distributions.OneHotCategorical(logits=x) return dist.sample()
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import unittest def build_suite(classes): """Creates a TestSuite for all unit test classes in the list. Assumes that each of the classes in the list has unit test methods which begin with 'test'. Calls unittest.makeSuite. Returns: A new unittest.TestSuite containing a test suite for all classes. ...
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def normalize_connector_config(config): """Normalize connector config This is porting of TD CLI's ConnectorConfigNormalizer#normalized_config. see also: https://github.com/treasure-data/td/blob/15495f12d8645a7b3f6804098f8f8aca72de90b9/lib/td/connector_config_normalizer.rb#L7-L30 Args: config (...
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def partition(arr, start, end, pivot_index): """ Partitions the array such that all elements before pivot_index are <= pivot element, and all the elements after are >= pivot element. The pivot element will come at its rightful position at the end. Returns the rightful index of the pivot. """ ...
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import io def read_placeholder(file_desc: io.BufferedReader, size=3) -> bytes: """ Read size bytes from file :param file_desc:file descriptor :param size:number of reading bytes :return: bytes """ return file_desc.read(size)
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from typing import Dict def in_obiectum_planum( rem: Dict, pydictsep: str = '.', pylistsep: str = ' ') -> dict: """in_obiectum_planum Flatten a nested python object Trivia: - obiectum, https://en.wiktionary.org/wiki/obiectum#Latin - recursiōnem, https://en.wiktionary.org/w...
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def find_delimiter_loc(delimiter, str): """Return a list of delimiter locations in the str""" out = [] pos = 0 while pos < len(str): if str[pos] == "%": out.append(pos) pos += 1 return out
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def convertCountry(zippedList,name): """Converts a country name to the corresponding country code""" #e.g. Russia --> RU codeIndex = [i[1] for i in zippedList].index(name) print(zippedList[codeIndex][0]) return zippedList[codeIndex][0]
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def read_file(path): """read files from path Args: path (str): full path of the file Returns: list(str): list of lines """ with open(path, "r", encoding="utf8") as f: lines = f.readlines() f.close() return lines
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def select_login_fields(fields): """ Select field having highest probability for class ``field``. :param dict fields: Nested dictionary containing label probabilities for each form element. :returns: (username field, password field, captcha field) :rtype: tuple """ username_field = ...
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import torch as th def _topk_torch(keys, k, descending, x): """Internal function to take graph-wise top-k node/edge features according to the rank given by keys, this function is PyTorch only. Parameters ---------- keys : Tensor The key for ranking. k : int The :math:`k` in "t...
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import re def ConvertStringToFilename(name): """Converts an unicode string to a filesystem safe filename. For maximum compatibility we escape all chars which are not alphanumeric (in the unicode sense). Args: name: a unicode string that is part of a subject. Returns: A safe filename with escaped s...
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import json def json_to_dict(json_str): """Convert a JSON string to a dictionary if not already a dictionary. :param json_str: JSON string to convert. :type json_str: str :return: JSON string as a dictionary. :rtype: dict or None """ if json_str: if isinstance(json_str, dict): ...
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import hashlib import base64 def get_sha256_checksum(byte_string): """ :param byte_string: byte-string to create checksum from :return: b32-encoded sh256-checksum as string """ sha256 = hashlib.sha256(byte_string) return base64.b32encode(sha256.hexdigest().encode("utf8")).decode("utf8").strip(...
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def escape_quotes(string): """Escape double quotes in string.""" return string.replace('"', '\\"')
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def index_of_first_zero_bit_moving_right_to_left(ii): """ Return the first the index of the first zero bit of the integer ii when moving right to left. Returns index in [0,...,nbits(ii)-1] # x >> y Returns x with the bits shifted to the right by y places. # This is the same as //'ing x by 2**y. ...
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def get_act_sent_len(head_indexes_2d): """ Get actual sentence length (counting only head indexes) """ sent_len_list = [0] * len(head_indexes_2d) for idx, head_list in enumerate(head_indexes_2d): sent_len = 0 for item in head_list: if item != 0: sent_len += ...
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def is_versioned(obj): """ Returns whether or not given object is versioned. :param obj: SQLAlchemy declarative model object. """ return ( hasattr(obj, '__versioned__') and ( ( 'versioning' in obj.__versioned__ and obj.__versioned__['versi...
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def key2mongo(tup): """Return a string given an (int, string) plate-well key. Parameters ---------- tup : (int, string) tuple A (plate, well) identifier. Returns ------- mongo_id : string A string, suitable for representing a mongodb _id field. Examples -------- ...
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def parse_console_interface(console_interface): """ parse console interface Foramt: line_number.baud.flow_control_option Example: 27.9600.0 """ fields = console_interface.split('.') return fields[0], fields[1], fields[2]
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import torch def tensor_encode_id(img_id): """ Encodes a FathomNet image id like '00a6db92-5277-4772-b019-5b89c6af57c3' as a tensor of shape torch.Size([4]) of four integers in the range [0, 2^32-1]. """ hex_str = img_id.replace('-', '') length = len(hex_str) // 4 img_id_enc = tuple(int(he...
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def rotate(list, places): """Shift the elements in a list. A positive place will move the list to the left, a negative place to the right.""" return list[places:] + list[:places]
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import json def search(es_object, index, search_params): """ Search the Elasticsearch index. """ json_search = json.dumps(search_params) result = es_object.search(index=index, body=json_search) return result
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from typing import Any def smallid(n: Any, seglen: int = 3, sep: str = "...") -> str: """Reduce a String into the first and last `seglen` characters, on either side of `sep`. smallid(1234567890, 3, "...") -> "123...890" """ ns = str(n) return f"{ns[:seglen]}{sep}{ns[-seglen:]}"
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def get_workdir_data(project_doc, asset_doc, task_name, host_name): """Prepare data for workdir template filling from entered information. Args: project_doc (dict): Mongo document of project from MongoDB. asset_doc (dict): Mongo document of asset from MongoDB. task_name (str): Task name...
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def excel_column(column: int) -> str: """Convert column position (indexed from 0) to Excel column name. Args: column (int): Column index (position from 0). Returns: str: Definition of column in Excel. """ letter_list = 'ABCDEFGHIJKLMNOPQRSTUVWXYZ' result = [] column += 1 ...
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import csv def get_csv_collection(filename, **kwargs): """ Loads a record collection from a CSV file. The CSV file MUST include columns for Artist, Title, and Year Arguments: filename (str) - CSV filename **kwargs (dict) - Optional kwargs: skip=0, don't load the first <skip> rows Returns...
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from pathlib import Path def get_ref_file() -> str: """Read the ref file, cached to reduce amount of times we need to read the file into memory Returns: str: ref file contents """ ref_file_path = Path.cwd() / '.palm/model_template/ref_files/ref_file.sql' if not ref_file_path.exists(): ...
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def sum_of_lists(lists): """Aggregates list of numeric lists by summing.""" if len(lists) == 1: return lists[0] # Preserve datatype size = len(lists[0]) init_val = type(lists[0][0])(0.0) total = [init_val] * size for ll in lists: for i in range(size): total[i] +=...
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def get_digits(n, reverse=False): """Returns the digits of n as a list, from the lowest power of 10 to the highest. If `reverse` is `True`, returns them in from the highest to the lowest""" digits = [] while n != 0: digits.append(n % 10) n //= 10 if reverse: digits.reverse...
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def includes_subpaths(path) : """Checks if a given path includes subpaths or not. It includes them if it ends in a '+' symbol. """ return path[-1] == '+'
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def response(speech_message): """ create a simple json response """ return { 'version': '1.0', 'response': speech_message }
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def str_to_int_array(string, base=16): """ Converts a string to an array of integer values according to the base specified (int numbers must be whitespace delimited).\n Example: "13 a3 3c" => [0x13, 0xa3, 0x3c] :return: [int] """ int_strings = string.split() return [int(int_str, base) ...
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import difflib def _diff(a, b): """ diff of strings; returns a generator, 3 lines of context by default, - or + for changes """ return difflib.unified_diff(a, b)
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from typing import List import plistlib def load_plist(plist_path: str) -> List[dict]: """ Open a plist file. :param plist_path: The path to plist file. :return: The plist dictionary. In our particular case is a list of dicts. """ with open(plist_path, 'rb') as fp: plist = plistlib.lo...
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def rescaleInput(input): """ scales input's elements down to range 0.1 to 1.0. """ return (0.99 * input / 255.0) + .1
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def snakecase_to_camelcase(value): """Convert a snakecase string to a camelcase string. Args: value: The input snakecase string (e.g. 'grasp_env'). Returns: The converted camelcase string (e.g. 'GraspEnv'). """ words = value.split('_') return ''.join(word.title() for word in wo...
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def select_migrations(current, target, migration_ids): """ Select direction and migrations to run, given current and target migrations, from a list of migration ids """ if target > current: return 'forward', [ id_ for id_ in migration_ids if current < id_ <= targe...
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import math def torad(deg): """ convert degrees to radians """ return math.pi/180.0*deg
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from typing import Union def del_dict_keys(data: dict, keys: Union[tuple, list]) -> dict: """Deletes multiple keys from dictionary. Args: data: A dictionary. keys: Keys to be deleted. Returns: Dictionary without the deleted keys. """ temp_dict = data.copy() for key i...
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def is_port(port): """ returns true if the port is within the valid IPv4 range """ if port >= 0 and port <= 65535: return True return False
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import re import html def html_parse(string): """ Simple html parser for MAL""" pattern = '<br[ ]?/?>|\[/?\w\]' string = re.sub(pattern, '', string) return html.unescape(string)
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import sqlite3 def open_sqlite(input_db): """Open a SQLite database Args: input_db: Path to a SQLite database to open Returns: A connection to a SQLite database """ print("Provided Database: {}".format(input_db)) return sqlite3.connect(input_db)
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def confidence_bound(gpmodel, X_full, **kwargs): """ Confidence bound acquisition function (a modification of upper confidence bound) Args: gpmodel (gpim reconstructor object): Surrogate function that allows computing mean and standard deviation X_full (ndarray):...
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def _get_filter_items(filter_previously_rated, previously_liked, filter_items): """Determine which items to filter out.""" if filter_previously_rated: previously_liked = set(previously_liked) if filter_items is not None: filter_items = set(filter_items) previously_liked ...
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def image_displacement_to_defocus(dz, fno, wavelength=None): """Compute the wavefront defocus from image shift, expressed in the same units as the shift. Parameters ---------- dz : `float` or `numpy.ndarray` displacement of the image fno : `float` f/# of the lens or system wavel...
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import zipfile def read_data(filename): """Extract the first file enclosed in a zip file as a list of words""" with zipfile.ZipFile(filename) as f: data = f.read(f.namelist()[0]).split() return data
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def scale_image(image, cube_size): """ Scale the input image to a whole number of cubes with minimal stretch. :param image: PIL Image object. :param cube_size: Cube size from configuration, int. :return: A scaled PIL Image. """ image_w, image_h = image.size scale_h = image_h // cube_siz...
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import copy def cut(motion, frame_start, frame_end): """ Returns motion object with poses from [frame_start, frame_end) only. The operation is not done in-place. Args: motion: Motion sequence to be cut frame_start, frame_end: Frame number range that defines the boundary of ...
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from pathlib import Path def filter_extensions(files, extensions): """Filter files by extensions.""" extensions = {f".{ext}" for ext in extensions} return [x for x in files if Path(x).suffix in extensions]
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def _parse(tag): """ Used by the BeautifulSoup parser to get the wanted tags """ # Return if it's the title of the PLL Alg if tag.has_attr('id'): return '_Permutation' in tag['id'] # Return if it's an actual alg which are a tags with the following classes elif tag.name == 'a' and tag...
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from typing import List import re def extract_product_handles(text: str, limit: int) -> List[str]: """Extract first <limit> product handles Parameters: text (str): Text to search product handles Returns: List[str]: List of found product handles """ pattern = r"\/collections\/all...
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def make_slist(l, t_sizes): """ Create a list of tuples of given sizes from a list Parameters ---------- l : list or ndarray List or array to pack into shaped list. t_sizes : list of ints List of tuple sizes. Returns ------- slist : list of tuples List of tu...
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def stripAndRemoveNewlines(text): """Removes empty newlines, and removes leading whitespace. """ no_empty_newlines = "\n".join([ll.rstrip() for ll in text.splitlines() if ll.strip()]) return no_empty_newlines.strip()
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def unpack_Any(any_msg, msg_class): """Unpacks any_msg into msg_class. Returns None if msg_class is None. """ if msg_class is None: return None msg = msg_class() any_msg.Unpack(msg) return msg
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def is_absolute_http_url(url): # type (str) -> bool """Tell if a string looks like an absolute HTTP URL """ try: return url[0:6] in {'http:/', 'https:'} except (TypeError, IndexError, ValueError): return False
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def is_nova_server(resource): """ checks resource is a nova server """ return ( isinstance(resource, dict) and "type" in resource and "properties" in resource and resource.get("type") == "OS::Nova::Server" )
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def _band_shortname(long_name): """Get short band name, e.g. `Near Infrared (NIR)` becomes `nir` and `Red` becomes `red`. """ if '(' in long_name: start = long_name.find('(') + 1 end = long_name.find(')') short_name = long_name[start:end] else: short_name = long_name....
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import random def random_colors(amount:int) -> list: """ Create an amount of random colors inside a list. """ return ["#"+''.join([random.choice('ABCDEF0123456789') for i in range(6)]) for j in range(amount)]
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def demo_app_link_id(name): """Returns the value of the id of the dcc.Link related to the demo app. """ return 'app-link-id-{}'.format(name.replace("_", "-"))
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from bs4 import BeautifulSoup def parse_html(request_res): """ Parses the HTML of a page """ soup = BeautifulSoup(request_res.text, 'html.parser') return soup
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def conflict_update_condition(columns): """ Create the (condition) portion of the "ON CONFLICT (condition) DO UPDATE (actions)" statement. """ if columns and len(columns) > 0: return f"({columns if isinstance(columns, str) else ', '.join(columns)})" else: raise TypeError("Columns are...
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def RemoveTrailingSlashes(path): """Removes trailing forward slashes from the path. We expect unix style path separators (/). Gyp passes unix style separators even in windows so this is okay. Args: path: The path to strip trailing slashes from. Returns: The path with trailing slashes removed. ""...
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def ftime(time_): """formats a datetime""" return time_.strftime("%m/%d/%y %H:%M")
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def find_dict_with_keyvalue_in_json(json_dict, key_in_subdict, value_to_find): """ Searches a json_dict for the key key_in_subdict that matches value_to_find :param json_dict: dict :param key_in_subdict: str - the name of the key in the subdict to find :param value_to_find: str - the value of the ke...
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def fit_sklearn_model(ts, model, test_size, val_size): """ Parameters: ts (pandas.DataFrame): time series values created by src.time_series_functions.create_windowing model (Sklearn Model): base model to predict ts test_size (int): size of test set val_size (int): si...
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import functools def coroutine(func): """ Co-Routine decorator that wraps a function and starts the co-routine """ def start(*args, **kwargs): target = func(*args, **kwargs) target.send(None) functools.update_wrapper(start, func) return target return start
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def buildBoard(x, y): # function that creates a board with 1 values and returns it """ :param x - horizontal length :param y - vertical length :return: created board """ board = [] for i in range(x): board_row = [] for j in range(y): board_row.append(1) b...
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def get_batch_series(source): """Extracts sim_batch and series values from full source string e.g.: sim10_1 would return (10, 1) """ stripped = source.strip('sim') sim_batch = int(stripped[:2]) series = int(stripped[3:]) return sim_batch, series
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def get_qumodes_operated_upon(op): """ Helper function that returns list of integers, which are the qumode indexes that are operated by op. """ return [reg.ind for reg in op.reg]
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from typing import List def prettify_alignment(a: List, b: List) -> str: """ Makes two alignments prettier to print next to each other :param a: Alignment (Google side) :param b: Alignment (Transcript side) :return: Prettified alignment """ a = ["-" if el is None else el for el in a] ...
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def fact_ad(x, n): """ Returns x(x-1)(x-2)...(x-n+1), the product of n terms, factorial-like operation Parameters: x, n: two scalars Returns: x(x-1)(x-2)...(x-n+1): scalar Example: >>> fact_ad(5,4) 120 """...
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import torch def evaluate_performance_batch(model,batch, criterion, device = 'cuda'): """Evaluate performance for a single batch""" with torch.no_grad(): images, labels = tuple(map(lambda x: x.to(device), batch)) predictions = model.forward(images) _, predict = torch.max(predictions, 1...
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def select_dict(coll, key, value): """ Given an iterable of dictionaries, return the dictionaries where the values at a given key match the given value. If the value is an iterable of objects, the function will consider any to be a match. This is especially useful when calling REST APIs which ...
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def computeSetOfParetoPointsTuplesFromListOfParetoPoints(ListOfParetoPointsAsDicts): """ Given a list of pareto points encoded as a dictionary, we compute a set of the same pareto points (aka remove duplicates) encoded as tuples ordered by the order of the keys (returned by keys() method of first item) . ...
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from typing import Any import requests def request_with_retry( method: str, url: str, **kwargs: Any ) -> requests.models.Response: """ Wrapper function for `requests.request` that retries timeout, connection, and server-side http errors with exponential backoff and jitter. For more info: https...
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def api_repo_url(org_name): """ With the supplied organization name, constructs a GitHub API URL :param org_name: GitHub organization name :return: URL to GitHub API to query org's repos """ return 'https://api.github.com/orgs/{}/repos'.format(org_name)
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import re def normalize(text: str): """ Strips out formatting, line breaks, and repeated spaces to normalize the string for comparison. This ensures minor formatting changes are not tagged as meaningful changes """ s = text.lower() s = s.replace("\n", " ") s = re.sub(r'[`*\'"]', "", s...
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def pipeline_splitting_rule(val_size = 0.2, test_size = 0.2, random_state = 13): """Setup percentage of train, validate, and test of each pipeline's dataset in Pipeline Cluster Traversal Experiments. Parameters ---------- val_size : float, default = None Value within [0~1]. Percentage of va...
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def delistify(some_list): """ Untangle multiple nested one-element lists. Occasionally a problem in Libris, e.g. "[['x']]". Converts it to 'x'. @param some_list: list to convert. @type some_list: list """ while isinstance(some_list, list) and len(some_list) == 1: some_list = so...
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def longest_loc_length(book): """ Return the length of the longest location key string. """ loc_length = 0 for loc_string in book.keys(): if len(loc_string) > loc_length: loc_length = len(loc_string) return loc_length
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def _get_weights_dict(obj, suffix=''): """ Get the dictionary of weights. Parameters ---------- obj : Model or Optimizer The target object that we want to get the weights. Returns ------- dict The weight dictionary. """ weights_dict = {} weight_names = [weig...
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def clamp(x, a, b): """Clamps value x between a and b""" return max(a, min(b, x))
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from typing import Union def is_downstream(pfaf_id_a: Union[int, str], pfaf_id_b: Union[int, str]) -> bool: """Calculate if pfaf_id_b is downstream of pfaf_id_a Implemented as in https://en.wikipedia.org/wiki/Pfafstetter_Coding_System#Properties Works even if pfaf_id_a and pfaf_id_b are at different leve...
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import re def whole_word_pattern(string: str) -> str: """ Transforms the string 'string' so that a regex search only matches the whole word form of 'string', and not as part of any substring. Taken from Felix Kling at https://stackoverflow.com/a/4155064. """ return r"\b" + re.escape(string) ...
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def make_ordinal(num): """ Create an ordinal (1st, 2nd, etc.) from a number. """ base = num % 10 if base in [0,4,5,6,7,8,9] or num in [11,12,13]: ext = "th" elif base == 1: ext = "st" elif base == 2: ext = "nd" else: ext = "rd" return str(num) + ext
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def _rhel_kernel_info(packages, kernel_version, current_version): """ Return kernel to install with associated repository. Args: packages (dict): DNF/YUM list output. kernel_version (str): Kernel version to install. current_version (str): Current kernel version. Returns: ...
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