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def ringfilter(motif, bond, pivot1, pivot2): """ For a given linear sequence of atoms it tests whether they for a ring, i.e., whether atoms pivot1 and pivot 2 are connected. """ if bond[motif[pivot1]][motif[pivot2]] > 0: return 1 else: return 0
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import os def read_data(): """ Function: read_data\n Parameters: None\n Functionality: Read the data and convert it to a meaning ful form\n """ parent_dir = os.getcwd() dir_name = 'analysis_output_files' file_name = 'scenario_analysis.log' file_path = os.path.join(parent_dir, dir_n...
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def FindNonTrivialOrbit(generators): """ Given a generating set <generators> (a Python list containing permutations), this function returns an element <el> with a nontrivial orbit in the group generated by <generators>, or <None> if no such element exists. (Useful for order computation / membership ...
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def city_functions(city, country, population=''): """Generate a neatly formatted city.""" if population: return (city.title() + ', ' + country.title() + ' - population ' + str(population) + '.') return city.title() + ', ' + country.title() + '.'
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def create_pivot_df(df_snp): """constructs pivot DataFrame grouping data by the duplex variant """ context_data = df_snp.groupby('ref_duplex').sum() context_data.drop(['start_pos', 'stop_pos'], inplace=True, axis=1) return context_data
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def key_(arg): """ get an argument's destiation key """ _, kwargs = arg return kwargs['dest']
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import torch def smooth_dice_loss(pred: torch.Tensor, target: torch.Tensor, smooth: float=1., eps: float=1e-6) -> torch.Tensor: """ Smoothed dice loss. :param pred: (torch.Tensor) predictions, logits :param target: (torch.Tensor) target, logits or binrary :param smooth: (floa...
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import argparse def parse_args(): """Use argparse to get command line arguments.""" ''' task: segmentation gt: path to ground truth result: path to results to be evaluated num_classes: dataset classes. #e.g. 19 for cityscapes ignore_label: label to be ignored when to do evalution. #e.g. 25...
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def climbing_stairs_three_recur(steps: int) -> int: """Staircase by top-down recursion. Time complexity: O(3^n). Space complexity: O(n). """ if steps < 0: return 0 if steps == 0: return 1 return (climbing_stairs_three_recur(steps - 1) + climbing_stairs_three_r...
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def get_seat_id(ticket: str) -> int: """Get seat id based on boarding ticket (ie. 'BBFFBBFRLL')""" rows = range(128) cols = range(8) for letter in ticket: if letter in "FB": midpoint = len(rows) // 2 rows = rows[:midpoint] if letter == "F" else rows[midpoint:] e...
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def _create_object_from_type_and_dict(cls, obj_dict): """Creates an object, bypassing the constructor. Creates an object of type `cls`, whose `__dict__` is updated to contain `obj_dict`. Args: cls: The type of the new object. obj_dict: A `Mapping` that should be used to initialize the new object's ...
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import copy def populate_target_env_cfg(target_cfg, target_env): """ Read out context from target config then merge it with global magic context All keys in target config that starts with `_` is considered magic context and will be merged into each target_env config. """ # we need to do deepc...
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import re def valid_email(email): """Verifica la validità sintattia di una mail Args: email (str): email da validare Returns: bool: restituisce True se la mail è valida """ EMAIL_REGEX = r"[a-z0-9!#$%&'*+/=?^_`{|}~-]+(?:\.[a-z0-9!#$%&'*+/=?^_`{|}~-]+)*@(?:[a-z0-9](?:[a-z0-9-]*[a...
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from typing import Union from typing import Callable import importlib def validate_task(task: Union[str, Callable]) -> str: """ Helper function for dealing with task inputs which may either be a callable, or a path to a callable as a string In case of a string being provided, this function checks whether...
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def SetSingleTrack(center_row, height): """ This function will set the single track parameters. The parameters are validated in the following order: centre row and then track height. Parameters: int center_row: centre row of track int height: height of trac...
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def check_msg_size(msg): """Check if the commit message is too long. Parameters ---------- msg : str Returns ------- bool """ if len(msg) > 72: print( "ERROR: Commit message is too long. It should be 72 characters or" " less." ) retur...
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import os def config(key): """ reads key-value pairs from a .env file. """ return os.environ.get(key)
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def get_option_value(option): """ An option in a Checkboxes or CheckboxTree question is a dict, but we need to treat their contents in consistent ways, e.g. when getting the value to be persisted in the API. :param option: dict from a Question's list of options :return: string value to be persisted ...
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def bytes2str(data): """ Convert bytes to string >>> bytes2str(b'Pwning') 'Pwning' >>> """ data = "".join(map(chr, data)) return data
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from io import StringIO def svg(plot, close=True): """ Creates SVG code and closes plot. Args: plot: matplotlib.pyplot Plot from which the SVG should be made. Returns: str SVG code. """ # make SVG svg_file = StringIO() plot.savefig...
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def docselect(posts, category): """ Receives the category of devices and returns the relevant documents """ search_filter = {'Ancestors': {"$in": [category]}, "$where": 'this.Toolbox.length>0'} postsample = posts.find(search_filter, no_cursor_timeout=True) print('{} document are selected'.format...
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def mocked_events_ics(source: str = "uqcs") -> bytes: """ Returns a locally stored .ics file that imitates the UQCS Calendar on Google Calendar. """ with open("test/test_events_events.ics", "rb") as events_file: return events_file.read()
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def extract_elements_from_nested_list(nested_list): """Extract elements from nested list.""" new_list = [] # For item in nested list for item in nested_list: # Detangle if type(item) != str: new_item = extract_elements_from_nested_list(item) ...
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import re def split_psalm(reference): """splits pslams when multiple are included together""" # Example input: 'Ps. 33,108:1-6,7-13' # Example input: 'Ps. 63:1-8,9-11,Ps. 98' if len(re.findall(r'Ps\.', reference)) > 1: psalms = reference.split(',Ps. ') psalms[0] = re.sub(r'Ps\. ', '', ...
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def remove_upper_channel(lo, hi): """ take difference between two channels: # rule: lo ) 0 0 1 1 up ) 0 1 0 1 -> 0 0 1 0 """ lo = lo.astype(bool) hi = hi.astype(bool) return (lo ^ (lo & hi).astype(bool)).astype(bool)
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def _dictify(value): """ Converts non-dictionary value to a dictionary with a single empty-string key mapping to the given value. Or returns the value itself if it's already a dictionary. This is useful to map values to row's columns. """ return value if isinstance(value, dict) else {'': value}
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def find_opposite_neighbor(node, element, elements): """ This function returns the neighbor of 'element' that doesn't contain the node 'node'. NOTE: Valid only for triangular elements. """ neighbors = elements[element.neighbors - 1] for neighbor in neighbors: if node not in neigh...
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import random def random_row(categories=None): """ Make a random row Returns rows like (category, a, b): - category is a categorical variable, - a is a randomly selected cluster value (with two clusters) - b is a uniform integer on 0, 1 Returns: (category, a, b) - the r...
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import re def _generate_remote_name(remote_url: str) -> str: """Generate a kind-of human readable name based on a url.""" filtered = ( re.sub(r"[./\\@:\^]", "-", remote_url).replace("https", "").replace("http", "") ) return re.sub(r"[-]{2,}", "-", filtered).strip("-")
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def connect_device_success(self, *args, **kwargs): """Return `self`, which will result in the ADB connection being interpreted as available.""" return self
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import logging def prepare_data(df): """it is used to separate the dependent variables and independent features Args: df (pd.DataFrame): its the pandas DataFrame to Returns: tuple: it returns the tuples of dependent variables and independent variables """ logging.info("Preparing th...
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def count_vowels(sentence:str) -> dict: """ find vowel count in a sentence We are not initializing a vowels_count with each vowel set to 0 """ vowels = ['a', 'e', 'i', 'o', 'u'] vowel_cnt = {} for char in sentence: if char in vowels: vowel_cnt.setdefault(char, 0) ...
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def parseExitStatus(exitStatus): """Parse exit status of command line commands""" # 0 means executed correctly return not bool(exitStatus)
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import re def delete_links(string): """Delete links from input string Args: string (str): string to delete links Returns: str: string without links """ return re.sub(r'http\S+', '', string)
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def validate_entrypoints(entrypoints): """Check that the loaded entrypoints are valid. Expects a dict of dicts, e.g.:: {'console_scripts': {'flit': 'flit:main'}} """ def _is_identifier_attr(s): return all(n.isidentifier() for n in s.split('.')) problems = [] for groupname, gr...
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import six def prepare_call(parameters): """Dispatches messages to a different pipeline. Sends the message through another pipeline. Any changes to the message will be visible in the remainder of this pipeline. Note that there is a hardcoded limit of 10 pipeline changes per message (includes jumps ...
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import random def random_pick(i_list: list,n)-> list: """ Select n numbers from the source list :param i_list: The source list :param n: The number of element to pick :return: The output list """ _list_copy = i_list.copy() _shallow_list = [] assert(n <= len(i_list)) iter_idx = ...
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def parse_ffmpeg(input_dir, input_file_name, video_scale_bitrates, video_keyint): """parse ffmpeg command""" ffmpeg_cmd = [] ffmpeg_files = [] # 音频处理 audio_file = input_dir + '\\' + 'video_audio.mp4' # audio_cmd = 'ffmpeg' + ' ' + '-i ' + input_file_name + ' ' + '-c:a copy -vn' + ' ' + audio_f...
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def strip_uri(repo): """ Remove the trailing slash from the URI in a repo definition """ splits = repo.split() for idx, val in enumerate(splits): if any(val.startswith(x) for x in ("http://", "https://", "ftp://")): splits[idx] = val.rstrip("/") return " ".join(splits)
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def aoi_status(objects,status): """ Returns the status of the aoi """ return objects.filter(status=status)
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import logging import sys def parser_cvs(filename, fields_jsons): """esta funcion lista con un diccionario con la configuracion""" try: with open(filename, "r") as conf_file: readfilecsv = conf_file.readlines() info_load_config = "Cargado archivo: {}" logging.info(info_loa...
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def one_text_header(response, header_name): """ Retrieve one text header from the given HTTP response. """ return response.headers.getRawHeaders(header_name)[0].decode("utf-8")
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import numpy as np def vectorised_exceed_ns_icpm(cln_min, cln_max, cls_min, cls_max, dep_n, dep_s): """Vectorised version of exceed_ns_icpm(). Calculates exceedances based on the methodology outlined by Max Posch in the ICP Mapping manual (section VII.4): https://www.umweltbundesamt.de/si...
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from typing import Optional from typing import Dict from typing import List from typing import Tuple import base64 def as_metadata( credentials: Optional[Dict[str, str]] = None, requires_leader: Optional[bool] = None ) -> Optional[List[Optional[Tuple[str, str]]]]: """Returns a valid grpc "metadata" object."""...
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def node_tuple(): """ :returns: The tuple that defines a node :rtype: :class:`tuple_(dict, dict)` """ return {}, {}
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def split_string(string: str, indices: list) -> list: """Splits string between indices. Notes: It is possible to skip characters from the beginning and end of the string but not from the middle. Examples: >>> s = 'abcde' >>> indices = [1, 2, 4] >>> split_string(s, i...
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import subprocess def check_vault_connection(): """docstring for check_vault_connection""" try: out = subprocess.check_output(['vault', 'read', '--format', 'json', '/auth/token/lookup-self']) == 0 except subprocess.CalledProcessError as e: return False else: return True
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def preproc(line): """ 一行の命令を命令名と引数の列に分解する。 引数はカンマ区切りで分割され、前から順番にargsに入る。 d(Rb)の形式のものは、d,Rbの順でargsに入る。 """ head, tail = "", "" for i in range(len(line)): if line[i] == " ": tail = line[i + 1 :] break head += line[i] cmd = head.upper() tmp...
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def attributes(attrs): """Returns an attribute list, constructed from the dictionary attrs. """ attrs = attrs or {} ident = attrs.get("id","") classes = attrs.get("classes",[]) keyvals = [[x,attrs[x]] for x in attrs if (x != "classes" and x != "id")] return [ident, classes, keyvals]
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def fact_iter(n): """ 1. number of times around loop is n 2. number of operations inside loop is a constant 3. overall just O(n) >>> fact_iter(5) 120 >>> fact_iter(12) 479001600 >>> fact_iter(10) 3628800 >>> fact_iter(16) 20922789888000 >>> fact_iter(4) 24 ""...
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def char_sum(word: str) -> int: """Sum letter indices of uppercase word.""" total = 0 for letter in word: total += ord(letter) - 65 return total
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def _new_base(dests: str) -> str: """ Create New Base State :param dests: Dests :return: New Base """ bat, run1, run2, run3 = int(dests[:1]), int(dests[1:2]), int(dests[2:3]), int(dests[3:4]) nrunner1, nrunner2, nrunner3 = '0', '0', '0' if run1 == 1 or bat == 1: nrunner1 = '1' ...
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def execute(command, document): """Call obj as an command recursively while callable.""" while callable(command): command = command(document) return command
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def r(a, b, C): """ Defines the compatibility coefficients """ return C[a, b]
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def _model_field_values(model_instance) -> dict: """Return model fields values (with the proper type) as a dictionary.""" return model_instance.schema().dump(model_instance)
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import re def is_in_file(path, search_string): """ Determine whether a string is contained in a file. Like ``grep``. Parameters ---------- path : str The path to a file. search_string : str The string to be located in the file. """ with open(path, 'r') as filep: ...
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def rc_one_hot_encoding(encoded_seq): """Reverse complements one hot encoding for one sequence.""" return(encoded_seq[::-1, ::-1])
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def safe_get(obj, key, def_val=None): """ try to return the key'd value from either a class or a dict (or return the raw value if we were handed a native type) """ ret_val = def_val try: ret_val = getattr(obj, key) except: try: ret_val = obj[key] except: ...
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def _genotypes_str(sample_genotypes, genotypes_str_cache): """ Returns - string representations of sample genotypes, - string representations of various marginal probabilities in form (0??, 1??, ..., ?0?, ...). """ n_copies = len(sample_genotypes[0]) sample_cn = sum(sample_genotypes[...
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import uuid def format_jsonrpc_msg(method, params=None, *, notification=False): """ Returns dictionary that contains JSON RPC message. Parameters ---------- method: str Method name params: dict or list, optional List of args or dictionary of kwargs. notification: boolean ...
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def day2yr(day): """day -> yr""" return day/365
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import os def generate_indexed_filename(name_format, idx_start=0, folder=""): """ Generate an unused indexed filename in `folder`. The name has `name_format` (using standard Python :func:`format()` rules), with index starting with `idx_start`. """ while True: name=name_format.format(i...
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import gzip import base64 def decompress(data): """ Decodes a Base64 bytes (or string) input and decompresses it using Gzip :param data: Base64 (bytes) data to be decoded :return: Decompressed and decoded bytes """ if isinstance(data, bytes): source = data elif isinstance(data, st...
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from typing import Dict def largest_valued_key(dic: Dict[str, set]) -> str: """Find the key with the largest value.""" biggest_size = -1 biggest_key = None for key, value in dic.items(): length = len(value) if length > biggest_size: biggest_size = length biggest...
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def validate_entangler_map(entangler_map, num_qubits, allow_double_entanglement=False): """Validate a user supplied entangler map and converts entries to ints. Args: entangler_map (list[list]) : An entangler map, keys are source qubit index (int), value is array ...
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def keyName(*args): """Sort values in order and separate by hyphen - used as a unique key.""" a = [int(i) for i in [*args]] # make sure all ints a = [str(i) for i in sorted(a)] # sort ints and then return strings return '-'.join(a)
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def get_declarative_base(model): """ Returns the declarative base for given model class. :param model: SQLAlchemy declarative model """ for parent in model.__bases__: try: parent.metadata return get_declarative_base(parent) except AttributeError: ...
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def get_supported_versions(): """ """ return ['RAS500', 'RAS41']
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def one_quarter_right_rotation_escalators(escalator): """ Return the escalator coordinates rotated by 1/4. This assumes the escalator is defined for a 4×4 board. """ return ((escalator[0][1], 4 - (escalator[0][0] + 1)), (escalator[1][1], 4 - (escalator[1][0] + 1)))
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def run_caffe_net_forward(net, names): """ :return: The network output is a list of predicted bounding boxes """ outs = net.forward(names) return outs
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def _decorate_tree(t, series): """ Attaches some default values on the tree for plotting. Parameters ---------- t: skbio.TreeNode Input tree series: pd.Series Input pandas series """ for i, n in enumerate(t.postorder()): n.size = 30 if n.is_root(): ...
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from functools import reduce def AddRelativeAndCumulativeDistributions( h ): """adds relative and cumulative percents to a histogram. """ if len(h) == []: return [] new_histogram = [] total = float(reduce( lambda x,y: x+y, map( lambda x: x[1], h))) cumul_down = int(total) cumul_up = 0 ...
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import os def rootname(filename): """Return basename root without extensions.""" name = os.path.basename(filename) root, ext = os.path.splitext(name) while ext: root, ext = os.path.splitext(root) return root
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def format_response(resp, body): """Format an http.client.HTTPResponse for logging.""" s = f'{resp.status} {resp.reason}\n' s = s + '\n'.join(f'{name}: {value}' for name, value in resp.getheaders()) s = s + '\n\n' + body return s
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def public(func): """Do not require authentication on given view method.""" msg = "*Does not require authentication*\n" doc = func.__doc__ prefix = doc[:len(doc) - len(doc.lstrip())] func.__doc__ = prefix + msg + doc func.needs_auth = False return func
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import struct def read_entry(f): """ Read a single entry of trace file f. """ kinds={0:'loads', 1:'stores', 2:'atomics'} mark = f.read(1) # kernel start mark if mark == b'\x00': buf = f.read(2) size, = struct.unpack('H', buf) kernelname = f.read(size).decode('utf-8') ...
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def roh_air( dem, tempka): """ calculates the Atmospheric Air Density. This is found in Bastiaanssen (1995). /* Atmospheric Air Density * Requires Air Temperature and DEM*/ """ b = (( tempka - (0.00627 * dem )) / tempka ) result = 349.467 * pow( b , 5.26 ) / tempka if (result > 1.5): result = -999.99 elif ...
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from typing import Tuple def _should_include(key: str, split_range: Tuple[float, float]) -> bool: """ Hashes key to decimal between 0 and 1 and returns whether it falls within the supplied range. """ max_precision_order = 10000 decimal_hash = (hash(key) % max_precision_order) / max_precision_o...
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def extendedEuclideanAlgorimth(a, b): """ Compute the coefficients of the bezout's identity. Bezout's identity: for integer a and b exist integers x and y such that a * x + b * y = d, where d = gcd(a, b). Parameters ---------- a: int One of the numbers used for compute the coef...
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import torch def get_knots(start, end, n_bases=5, spline_order=3): """ Arguments: x; torch.tensor of dim 1 """ x_range = end - start start = start - x_range * 0.001 end = end + x_range * 0.001 # mgcv annotation m = spline_order - 1 nk = n_bases - m # number of interior kno...
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def make_vlan_name(parent, vlan_id): """ Create a VLAN name. Parameters ---------- parent : str The parent interface. vlan_id : The vlan id. Returns ------- str The VLAN name. """ return '{}.{}'.format(parent, vlan_id)
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def index_to_coord(index): """Returns relative chunk coodinates (x,y,z) given a chunk index. Args: index (int): Index of a chunk location. """ y = index // 256 z = (index - y * 256) // 16 x = index - y * 256 - z * 16 return x, y, z
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import math def diagonal(n: int, p: int) -> int: """ We want to calculate the sum of the binomial coefficients on a given diagonal. The sum on diagonal 0 is 8 (we'll write it S(7, 0), 7 is the number of the line where we start, 0 is the number of the diagonal). In the same way S(7, 1) is 28, S(7, ...
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import torch def orthogonal_random_matrix_(rows, columns, device): """Generate a random matrix whose columns are orthogonal to each other (in groups of size `rows`) and their norms is drawn from the chi-square distribution with `rows` degrees of freedom (namely the norm of a `rows`-dimensional vector ...
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def parse_pairs(pairs): """Parse lines like X=5,Y=56, and returns a dict.""" # ENST00000002501=0.1028238844578573,ENST00000006053=0.16846186988367085, # the last elem is always "" data = {x.split("=")[0]: x.split("=")[1] for x in pairs.split(",")[:-1]} return data
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def to_snake_case(camel_str): """ From https://stackoverflow.com/questions/1175208/elegant-python-function-to-convert-camelcase-to-snake-case Note that this function doesn't cover all cases in general, but it covers ours. """ return ''.join(['_'+c.lower() if c.isupper() else c for c in camel_str]).l...
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def symbol_constructor(loader, node): """YAML constructor for Ruby symbols. This constructor may be registered with '!ruby/sym' tag in order to support Ruby symbols serialization (you can use :py:meth:`register_constructors` for that), so it just need return the string scalar representation of the ...
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def drop_peaks(dataframe,data,cutoff): """ Filters out the peaks larger than a cut-off value in a dataseries Parameters ---------- dataframe : pd.DataFrame dataframe from which the peaks need to be removed data : str the name of the column to use for the removal of peak values ...
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import argparse def _parser(): """Take care of all the argparse stuff. :returns: the args """ parser = argparse.ArgumentParser(description='Xml generator for tapas submission') parser.add_argument("fname", help='Input file name', type=str) parser.add_argument("-o", "--output_file", help='Outp...
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def decap(df, neck, end_func=None): """ Separate the head from the body of a dataframe """ if end_func is None: end_func = lambda h, b: len(b) - 1 head = df.iloc[:neck] body = df.iloc[neck:] end = end_func(head, body) body = body[:end] return head, body
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import imghdr def what(pic_filename): """ 获得图片的真实类型 :param pic_name: 图片文件名 :return: """ return imghdr.what(pic_filename)
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import os def get_branch(default="master"): """ Derive the selected branch. We first look to the environment variable for INPUT_BRANCH, meaning that the user set the branch variable. If that is unset we parse GITHUB_REF. If both of those are unset, then we default to default (master). Returns...
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def get_maximal_alignment(address): """ Calculate the maximal alignment of the provided memory location. """ alignment = 1 while address % alignment == 0 and alignment < 256: alignment *= 2 return alignment
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import logging def create_logger(log_name, log_file): """ This function is used to generate logger for the whole program :param log_name: The name of the logger :param log_file: The output log file to save logging :return: logger """ logger = logging.getLogger(log_name) logger.setLevel...
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def intersection(iterableA, iterableB, key=lambda x: x): """Return the intersection of two iterables with respect to `key` function. Used to compare to set of strings case insensitively. """ def unify(iterable): d = {} for item in iterable: d.setdefault(key(item), []).append...
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def get_location_from_action_name(action): """Return the location from the name of the action""" if action.startswith('at_'): location_name = action[len('at_'):] elif action.startswith('go_to_'): location_name = action[len('go_to_'):] elif action.startswith('look_at_'): location_...
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import torch def array_to_tensor(array): """ Converts a numpy.ndarray (N x H x W x C) to a torch.FloatTensor of shape (N x C x H x W) OR converts a nump.ndarray (H x W x C) to a torch.FloatTensor of shape (C x H x W) """ if array.ndim == 4: # NHWC tensor = torch.from_numpy(array)....
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import itertools def subsequences(iterable, seq=2): """Return subsequences of an iterable Each element in the generator will be a tuple of `seq` elements that were ordered in the iterable. """ iters = itertools.tee(iterable, seq) for i, itr in enumerate(iters): for _ in range(i): ...
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def sign(x): """ Return 1 if x is positive, -1 if it's negative, and 0 if it's zero. """ if x > 0: return 1 elif x < 0: return -1 else: return 0
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def copy_metadata(nb_data): """Copy metadata of notebook Args: nb_data (JSON): a json data load from jupyter notebook Returns: dict: metadate copied from nb_data """ metadata = dict() metadata["metadata"] = nb_data["metadata"] metadata["nbformat"] = nb_data["nbformat"] ...
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