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def poly_lines_to_lines(polyline_list): """Convert a set of polylines to a simple lines (start and end points) Arguments: polyline_list {list} -- Set of polylines Returns: list -- Set of lines """ line_list = [] for polyline in polyline_list: prev_pt = None for the_pt in polyline: if prev_pt is not None: line_list.append([prev_pt, the_pt]) prev_pt = the_pt return line_list
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import re def wikify(value): """Converts value to wikipedia "style" of URLS, removes non-word characters and converts spaces to hyphens and leaves case of value. """ value = re.sub(r'[^\w\s-]', '', value).strip() return re.sub(r'[-\s]+', '_', value)
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def check_type(obj, accept_types): """Verify the type of an object is an anticipated type or is contained within a list of accepted types. Args: obj (type ambiguous): The object whose type will be assessed. accept_types (list): A list of types to check the passed object against. Raises: TypeError: If the object type is not in the list of accepted (anticipated) types. Returns: obj_type (type): The type of the object. """ obj_type = type(obj) if obj_type not in accept_types: raise TypeError('Invalid object type. Received ' 'type {0} but expected one of the following ' 'types: {1}'.format(obj_type, accept_types)) return obj_type
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def hex_to_rgb(value): """Convert a hex-formatted color to rgb, ignoring alpha values.""" value = value.lstrip("#") return [int(value[i:i + 2], 16) for i in range(0, 6, 2)]
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def unique(S, start, stop): """Return True if there are no duplicate elements in slice S[start: stop]""" print("start = {}, stop = {}".format(start, stop)) if stop - start <= 1: # at most 1 item return True elif not unique(S, start, stop-1): # first part has duplicate print("checking uniqueness in (S, {}, {})".format(start, stop-1)) return False elif not unique(S, start+1, stop): # second part has duplicate print("checking uniqueness in (S, {}, {})".format(start+1, stop)) return False else: print("Check uniqueness of 1st and last element for start = {} and stop = {}" .format(start, stop)) # do first and last differ return S[start] != S[stop] # do first and last differ
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from typing import Union def duplicate(nested_list: Union[list, int]) -> list: """Return a new nested list with all numbers in <nested_list> duplicated. Each integer in <nested_list> should appear twice *consecutively* in the output nested list. The nesting structure is the same as the input, only with some new numbers added. See doctest examples for details. If <nested_list> is an int, return a list containing two copies of it. >>> duplicate(1) [1, 1] >>> duplicate([]) [] >>> duplicate([1, 2]) [1, 1, 2, 2] >>> duplicate([1, [2, 3]]) # NOT [1, 1, [2, 2, 3, 3], [2, 2, 3, 3]] [1, 1, [2, 2, 3, 3]] """ new_list = [] # base case: if isinstance(nested_list, int): new_list.extend([nested_list, nested_list]) else: # nested_list is a list. for item in nested_list: # item is either an int or a list. if isinstance(item, int): new_list.extend(duplicate(item)) else: # item is another list. new_list.append(duplicate(item)) return new_list # try it with listcomp and ternary operators.. challenging!
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def key_prefix_replace(d, prefix, new_prefix=""): """ replaces the list of prefix in keys of a flattened dict :param d: the flattened dict :param prefix: a list of prefixes that are replaced with a new prefix. Typically this will be "" :type prefix: list of str :param new_prefix: The new prefix. By default it is set to "" :return: the dict with the keys replaced as specified """ items = [] for k, v in d.items(): new_key = k for p in prefix: new_key = new_key.replace(p, new_prefix, 1) items.append((new_key, v)) return dict(items)
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def find_all_indexes(text, pattern): """Return a list of starting indexes of all occurrences of pattern in text, or an empty list if not found.""" ''' worksheet: String Algorithms, pt. 2 let p = len(pattern) let t = len(text) p * t = checking every letter in text against every letter in pattern p(p-1) = p(p^2 - 1) = # REVIEW N/A VALUES IN WORKSHEET Best time complexity -- O(___), Worst time complexity -- O( p*t - p^2 + p ) = O( p*t + 1) - p^2 ) = O( p*t - p^2 ) remove constant since it doesn't have that much of an effect if p < t, then O(p * t) ''' if pattern == '': return list(range(0, len(text))) index = 0 t_index = 0 # first letter of pattern matching_indexes_list = [] while index <= len(text) - len(pattern): if text[index + t_index] == pattern[t_index]: # if t_index is the last index in pattern if t_index == len(pattern) - 1: matching_indexes_list.append(index) t_index = 0 index += 1 else: t_index += 1 else: t_index = 0 # reset index += 1 return matching_indexes_list
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def get_ccd_geometry(header): """Get basic geometry of CCD. Args: header (:class:`astropy.io.fits.header`): FITS header. Returns: tuple: A tuple of **(x1, x2, xbin, ybin)**, where **(0, x1)** is the columns of the prescan region, **(x1, x2)** is the columns of the science region, **(x2, )** is the columns of the overscan region, and **(xbin, ybin)** are the CCD binning along X and Y axes. """ cdelt1 = int(round(header['CDELT1'])) cdelt2 = int(round(header['CDELT2'])) # check nx if header['ESO DET CHIP1 NX'] == header['ESO DET OUT1 NX']: nx = header['ESO DET OUT1 NX'] else: raise ValueError # check ny if header['ESO DET CHIP1 NY'] == header['ESO DET OUT1 NY']: ny = header['ESO DET OUT1 NY'] else: raise ValueError prex = header['HIERARCH ESO DET OUT1 PRSCX'] prey = header['HIERARCH ESO DET OUT1 PRSCY'] ovrx = header['HIERARCH ESO DET OUT1 OVSCX'] ovry = header['HIERARCH ESO DET OUT1 OVSCY'] if prey != 0 or ovry != 0: raise ValueError if prex + nx + ovrx != header['NAXIS1']: raise ValueError if prey + ny + ovry != header['NAXIS2']: raise ValueError if cdelt1*nx != 2048: raise ValueError if cdelt2*ny != 4096: raise ValueError x1 = prex x2 = prex + nx binx = cdelt1 biny = cdelt2 return x1, x2, binx, biny
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import shutil from pathlib import Path def locate_program(name): """Locates program path by name. Args: name (str): Name of executable Returns: pathlib.Path: Pathlike Object to Program NoneType: If no suitable path is found """ prog_path = shutil.which(name) if not prog_path: return None return Path(prog_path)
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def get_key(dict, value): """ Get the first key of the given value in the given dictionary :param dict:dict :param value:str :return:str """ for item in dict.items(): if item[1] == value: return item[0]
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import math def tile_resolution(zoom, latitude): """Compute resolution for a given position Notes: https://wiki.openstreetmap.org/wiki/Slippy_map_tilenames Args: zoom (int): zoom level latitude (float): latitude in degrees Returns: (float): [m.pix-1] number of meters per pixel in the tile """ return 156543.034 * math.cos(math.radians(latitude)) / (2 ** zoom)
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def count_steps(splitting="OVRVO"): """Computes the number of O, R, V steps in the splitting string""" n_O = sum([step == "O" for step in splitting]) n_R = sum([step == "R" for step in splitting]) n_V = sum([step == "V" for step in splitting]) return n_O, n_R, n_V
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def get_region(chrom, start, end, region_trees): """Check if a position overlapps any regions Arguments: chrom (str): The chromosome start (int): The start position for the feature end (int): The stop position for the feature region_trees (dict): A dictionary with chromosomes as keys and interval trees as values Returns: regions (set): The regions that the variant ovelapps """ regions = set() if chrom in region_trees: tree = region_trees[chrom] result = tree[start:end] for interval in result: regions.add(interval.data) return regions
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import textwrap def shorten(text, width=70, placeholder='...'): """Shortens text to a max length. Shortens text to a max length using some optional placeholder with textwrap (if Python > 3.3) or a custom method. :param text: The text to shorten :type text: str :param width: The max width, defaults to 70 :type width: number, optional :param placeholder: The placeholder to truncate with, defaults to '...' :type placeholder: str, optional :returns: The shortened text with placeholder :rtype: {str} """ try: textwrap.indent except AttributeError: # function wasn't added until Python 3.3 return (text if len(text) <= width else text[:width - len(placeholder)] + placeholder) else: return textwrap.shorten(text, width=width, placeholder=placeholder)
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def get_value(kwargs, key_str, default_val=None): """ Returns kwargs[key_str] if there is one. Else it returns default_val if there is one. Else aborts. Parameters ---------- kwargs : dict[str, float] key_str : str default_val : float Returns ------- float """ if key_str in kwargs: return kwargs[key_str] elif default_val: return default_val else: assert False, "must pass-in keyword " + key_str +\ ' in ' + str(kwargs)
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def pop_target(unpopped_data): """ Removed target column from the data frame. Args: unpopped_data: Data frame with target column. Returns: data: Data frame without target column. target: Target column. """ data = unpopped_data.copy() target = data.pop('CONTROL_STATUS') return data, target
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def build_get_meta_side_effects(metas): """Returns a mock side effects method to be used as a side effect for the purpose of unit testing. This method replaces doctype metas for user defined ones. The returned method should be passed to a unittest.mock.MagicMock instance via patch or mock. This prevents database calls and enforces unit test isolation. Params: metas: list -> A list of Meta instances created with mock_meta() Example: @patch('frappe.get_doc') @patch('frappe.get_meta') def test_fetch_quotation(self, get_meta, get_doc): # Mock Quotation get_doc.side_effect = [Document({ "doctype": "Quotation", "name": "test-quotation", "customer_name": "test-customer" })] # Mock Quotation Metadata. Notice the limited set of fields. get_meta.side_effect = build_get_meta_side_effects( mock_meta("Quotation", fields=[ { "fieldname": "name", "fieldtype": "Data" }, { "fieldname": "customer_name", "fieldtype": "Link", "options": "Customer" } ]) ) # Fetches the mocked quotation doc = frappe.get_doc("Quotation", "test-quotation") # Then perform your tests get_doc.assert_called() get_meta.assert_called() self.assertTrue(doc.customer == "test-customer") """ def side_effect(doctype, cached=False): for meta in metas: if meta.name == doctype: return meta raise Exception("Unexpected get_meta doctype: {}".format(doctype)) return side_effect
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import math def to_pi_mpi_range(angle): """ Puts an angle in the -pi, pi range """ if angle > math.pi: return angle - math.pi elif angle < - math.pi: return math.pi + angle else: return angle
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import re def has_2x_in_row(chars): """ It contains at least one letter that appears twice in a row, like xx, abcdde (dd), or aabbccdd (aa, bb, cc, or dd). """ if re.search(r'(\w)\1+', chars): return True return False
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def autolabel(dropdown): """Automatically set Dropdown label on_click""" def callback(event): for label, _value in dropdown.menu: if event.item == _value: dropdown.label = label dropdown.on_click(callback) return callback
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def Convert(string): """converts string to list""" li = list(string.split(" ")) return li
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import torch def rot_z(gamma): """ Rotation around Z axis """ if not torch.is_tensor(gamma): gamma = torch.tensor(gamma, dtype=torch.get_default_dtype()) return gamma.new_tensor([ [gamma.cos(), -gamma.sin(), 0], [gamma.sin(), gamma.cos(), 0], [0, 0, 1] ])
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def count_consonants(string): """ Function which returns the count of all consonants in the string \"string\" """ consonants = "bcdfghjklmnpqrstvwxz" counter = 0 if string: for ch in string.lower(): if ch in consonants: counter += 1 return counter
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def remove_trailing_whitespace(line): """Removes trailing whitespace, but preserves the newline if present. """ if line.endswith("\n"): return "{}\n".format(remove_trailing_whitespace(line[:-1])) return line.rstrip()
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def set_view_timeout(config): """Set timeout duration for generating static images.""" return config["settings"].get("view_timeout", 60)
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def handle_tensorboard_timeout(e): """Handle exception: TensorBoard does not respond.""" return "Tensorboard does not respond. Sorry.", 503
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def dimensions(rotor_lst): """ Get the dimensions of each of the rotors """ return tuple(len(rotor) for rotor in rotor_lst)
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def _process_field_value(field): """Used in the csv writing task to return an appropriate representation """ if field.value == "": return "[Empty]" if field.type == "boolean": return "True" if field.value else "False" return field.value
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from functools import reduce import operator def calculate_nmea_checksum(nmea_line): """ Given the complete nmea line (including starting '$' and ending checksum '*##') calculate the checksum from the body of the line. NOTE: this does not check for structural correctness, so you should check that '$' and '*##' checksum are present and that the checksum matches before calling this function. """ # # xor all characters in the message to get a one byte checksum. # don't include starting '$' or trailing checksum '*##' # return reduce(operator.xor, map(ord, nmea_line[1:-3]), 0)
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import re def has_problem_form(word): """ has_problem_form() Purpose: Checks if the word has problem form. @param word. A string @return the matched object if it has problem form, otheriwse None. >>> has_problem_form('prognosis') is not None True >>> has_problem_form('diagnosis') is not None True >>> has_problem_form('diagnostic') is not None True >>> has_problem_form('arachnophobic') is not None True >>> has_problem_form('test') is not None False >>> has_problem_form('ice') is not None False """ regex = r".*(ic|is)$" return re.search(regex, word)
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def __require_tab_separator(section): """ Given a section name, returns True iff in that section of the project config only tab separators should be permitted. This exception initially introduced to allow slighlty different syntax for the [labels] section than others. """ return section == "labels"
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def _store_chunks_in_order(seen: str, unseen: str, seen_first: bool) -> list: """ Save two strings (a 'seen' and an 'unseen' string) in an array where the 'seen' string is the first element if the seen_first parameter is True. @param seen: The 'seen' string @param unseen: The 'unseen' string @return: An array where either the seen or unseen strings are the first/second element depending on the value of the seen_first parameter. """ if seen_first: return [seen, unseen] else: return [unseen, seen]
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import calendar def dt2ts(dt): """Converts a datetime object to UTC timestamp naive datetime will be considered UTC. """ return calendar.timegm(dt.utctimetuple())
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import re def file_is_of_type(file_name, extension): """ Return whether a file is of a certain type. Args: file_name the name of the file to test. extension the part of the name after the . which will be checked with a regular expression. Returns: True if file_name ends with extension. """ type_re = re.compile(r'\.%s' % extension) return type_re.search(file_name) != None
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def jaccard_similarity(b1, b2): """Jaccard similarity between two set b1 and b2 :param b1: set of index if there is a rate for business b1 :param b2: set of index if there is a rate for business b2 :return: jaccard similarity of two sets """ return len(b1.intersection(b2))/len(b1.union(b2))
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from typing import Tuple import re def get_line_property_key_value(text: str, reversed_key: bool) -> Tuple[str, str]: """Returns the unformatted key and formatted value for a given line. Examples: reversed_key = False key= value 123 -> key, value reversed_key = True value 123= key asdf -> key, value Args: text (str): Text from where to extract key and value. reversed_key (bool): Whether the key comes before or after the value. Returns: Tuple[str, str]: Unformatted key and formatted value. """ key_idx, value_idx = (-1, 0) if reversed_key else (0, -1) text_parts = re.split(":|=", text.strip()) key_part = "" if len(text_parts) > 1: # Only consider a value if there is more than one field. key_part = text_parts[key_idx].strip() value_part = text_parts[value_idx].strip() if value_part: # If there was a value in the first field, clean it. return key_part, re.split(" ", value_part)[0].strip() return key_part, ""
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import hashlib def calculate_digest(body): """Calculate the sha256 sum for some body (bytes)""" hasher = hashlib.sha256() hasher.update(body) return hasher.hexdigest()
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def has_params(data, *args): """ Validates required parameters against an object. :param data: :param args: required parameters :return: """ if not data: return False for a in args: if not a in data: return False v = data[a] if not v or v.isspace(): return False return True
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def create_labels(dcr_root): """ Returns activity name event label mapping function :param dcr_root: The Etree root element of a dcr graph :return: Dictionary of all labels and names """ mappings = [] for mapping in dcr_root.iter('labelMapping'): mappings.append(mapping.get('labelId')) return mappings
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def calc_angle(main_vector, second_vector): """ Calculate angle between two vectors :param main_vector: DB.XYZ :param second_vector: DB.XYZ :return: Angle with sign :rtype: float """ angle = main_vector.AngleTo(second_vector) sign = 1 if main_vector.CrossProduct(second_vector).Z >= 0 else -1 return sign * angle
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def IntegrateLambdaOrRho(terms): """ IntegrateLambdaOrRho(terms): terms: A hash table containing lambda or rho coefficients. For example, if lambda(x) = .4 x^2 + .6 x^3, then the input would be {2:.4, 3:.6}. Returns The integral of the argument from 0 to 1. """ sum = 0 total = 0 for i in terms.keys(): sum = sum + terms[i] total = total + terms[i]/float(i) assert(abs(sum-1.0) < .0001) return total
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def get_issue_assigned_names(repo_issues) -> list: """Get the list of issues from the no-verified-domain-email-repo and create a list of the names of the assignees Args: repo_issues([type]): The list of repo issues in the no-verified-domain-email-repo Returns: list: The list of user usernames assigned to the issues in the repo """ issue_assigned_names_list = [] for issue in repo_issues: if issue["assignees"]["edges"]: if issue["state"] == "OPEN": issue_assigned_names_list.append( issue["assignees"]["edges"][0]["node"]["login"] ) return issue_assigned_names_list
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import re def picard_friendly(umi): """ Converts a UMI string into a format that Picard Tools can understand >>> picard_friendly("ACGT+ACGT") 'ACGT-ACGT' >>> picard_friendly("ACGT_ACGT") 'ACGT-ACGT' >>> picard_friendly("TTTAA") 'TTTAA' """ return re.sub("[^actgnACTGN]", "-", umi)
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def is_js_file(filename): """ Return true if the filename ends in .js and is not a packed or minified file (no '.pack' or '.min' in the filename) >>> is_js_file('jquery.min.js') False >>> is_js_file('foo.json') False >>> is_js_file('ui.combobox.js') True """ return filename.endswith('.js') \ and not '.pack' in filename \ and not '.min' in filename
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from pathlib import Path def is_file(file_obj): """Check a file exists on the system. Examples -------- :: >>> from pyutil.sys_checks import is_file >>> if is_file('path/to/file'): >>> pass """ p = Path(file_obj) return p.is_file()
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def pascal_to_torr(pascal): """Convert Pascal to Torr.""" return pascal / 101325.0 * 760.0
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def mutate_DataFrame(df, **kwargs): """Verb: add columns to a DataFrame defined by kwargs: Parameters ---------- kwargs : scalar, pd.Series, callable, dict * scalar, pd.Series -> assign column * callable - call callable(df) and assign result * dict (None: column) - result of itergroups on non-grouped DF to have parity with mutate_DataFrameGroupBy Examples -------- add a rank for one column:: dp(mtcars).mutate(hp_rank = X.hp.rank) rank all columns:: # dict comprehension for illustrative purposes dp(mtcars).mutate(**{f"{column}_rank": X[column].rank() for column in X.columns}).pd # more efficient dp(mtcars).rank().pd() one rank per group using callback:: dp(mtcars).group_by('cyl').mutate(rank = lambda X: X['hp'].rank()).pd add_count variant 1 (see :func:`dppd.single_verbs.add_count`):: dp(mtcars).group_by('cyl').mutate(count=lambda x: len(x)).pd add_count variant 2:: dp(mtcars).group_by('cyl').mutate(count={grp: len(sub_df) for (grp, sub_df) in X.itergroups()}).pd """ for k, v in kwargs.items(): if isinstance(v, dict): if len(v) != 1: raise KeyError("Expected dict with single key: None") kwargs[k] = v[None] to_assign = kwargs return df.assign(**to_assign)
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import base64 def b2s(bs: bytes) -> str: """Bytes to b64 string.""" return base64.b64encode(bs).decode('utf-8')
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def user_upload_directory(instance, filename): """Return the upload directory for a given File (should have an owner).""" return 'user_{0}/{1}'.format(instance.owner.id, filename)
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from typing import Dict from typing import List import pkg_resources import json def load_weat() -> Dict[str, List[str]]: """Load the word sets used in the paper *Semantics Derived Automatically* *From Language Corpora Contain Human-Like Biases*. It includes gender (male, female), ethnicity (black, white) and pleasant, unpleasant word sets, among others. References ---------- Semantics derived automatically from language corpora contain human-like biases. Caliskan, A., Bryson, J. J., & Narayanan, A. (2017). Science, 356(6334), 183-186. Returns ------- word_sets_dict : dict A dictionary with the word sets. """ resource_package = __name__ resource_path = "/".join(("data", "WEAT.json")) weat_data = pkg_resources.resource_string(resource_package, resource_path) data = json.loads(weat_data.decode()) return data
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from typing import List def get_nodes_for_homek8s_group(inventory, group_name) -> List[str]: """Return the nodes' names of the given group from the inventory as a list.""" hosts_dict = inventory['all']['children']['homek8s']['children'][group_name]['hosts'] if hosts_dict: return list(hosts_dict.keys()) else: return []
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def key_generator(value): """Simple key generator that maps all values to lower case.""" return value.lower()
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import string def remove_stop_words(words): """ Remove stop words and single letter words from WORDS """ with open('../stop_words.txt') as stop_words_file: stop_words = stop_words_file.read().split(',') # single-letter words are also stop_words stop_words.extend(list(string.ascii_lowercase)) indexes = [] for i, word in enumerate(words): if word in stop_words: indexes.append(i) for i in reversed(indexes): words.pop(i) return words
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def _prefix_with_swift_module(path, resource_info): """Prepends a path with the resource info's Swift module, if set. Args: path: The path to prepend. resource_info: The resource info struct. Returns: The path with the Swift module name prepended if it was set, or just the path itself if there was no module name. """ swift_module = resource_info.swift_module if swift_module: return swift_module + "-" + path return path
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def get_raw_path(request) -> str: """ Returns the raw_path inside the request. The request can either be a Quart Request object (that encodes the raw path in request.scope['raw_path']) or a Werkzeug WSGi request (that encodes the raw path in request.environ['RAW_URI']). :param request: the request object :return: the raw path if any """ if hasattr(request, "environ"): # werkzeug/flask request return request.environ.get("RAW_URI", request.path) if hasattr(request, "scope"): # quart request return request.scope.get("raw_path", request.path) raise ValueError("cannot extract raw path from request object %s" % request)
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def ParseGitInfoOutput(output): """Given a git log, determine the latest corresponding svn revision.""" for line in output.split('\n'): tokens = line.split() if len(tokens) > 0 and tokens[0] == 'git-svn-id:': return tokens[1].split('@')[1] return None
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def import_dotted_name(name): """Get an object by its "dotted name", a string representing its import location. The last dot can also be a colon instead. .. versionadded:: 0.6 """ name = str(name) if ':' in name: module, obj = name.split(':', 1) elif '.' in name: module, obj = name.rsplit('.', 1) else: return __import__(name, level=0) mod = __import__(module, fromlist=[obj], level=0) return getattr(mod, obj)
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def parse_healing_and_source(line, is_lifetap, is_absorb): """Helper method that finds amount of healing and character providing it""" split_line = line.split() source = '' if is_lifetap: num = int(split_line[3]) elif is_absorb: num = int(split_line[5]) else: source = ' '.join(split_line[5:split_line.index('for')]) num = int(split_line[split_line.index('for')+1]) source = source.replace('the ', '') return [num, source]
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import re def make_test_name(description): """ generate a test name from a description :param description: plain english description of a test :type description: string :return: the generated test name :rtype: string """ return 'test_' + re.sub(r'\s+', '_', description.strip().lower())
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def reformat(formula): """Add spaces around each parens and negate and split the formula.""" formula = ''.join(f' {i} ' if i in '~()' else i for i in formula) return formula.split()
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def jac(a, b): """return the Jaccard similarity of two sets""" if type(a) != set: a = set(a) if type(b) != set: b = set(b) n = len(a.intersection(b)) return n / float(len(a) + len(b) - n)
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from pathlib import Path def create_flag_file(filepath: str) -> str: """ Create a flag file in order to avoid concurrent build of same previews :param filepath: file to protect :return: flag file path """ flag_file_path = "{}_flag".format(filepath) Path(flag_file_path).touch() return flag_file_path
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def listlike(var): """ Takes a variable and returns the variable in a list if it is not already a list :param var: variable :return: List """ if isinstance(var, list): return var else: return [var]
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def copy_df(df): """ DESCRIPTION ----------- Deep copy a pandas dataframe. PARAMETERS ---------- df : pd.DataFrame A pandas dataframe instance RETURNS ------- A deep copy of a given pandas dataframe MODIFICATIONS ------------- Created : 4/26/19 """ return df.copy(deep=True)
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def is_user_active(user_obj): """ Helps to find user is active or not. Returns boolean value True or False :param user_obj: user queryset of User model :return: boolean value """ if user_obj.is_active: return True return False
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def _cmp(x, y): """ Replacement for built-in function cmp that was removed in Python 3 Compare the two objects x and y and return an integer according to the outcome. The return value is negative if x < y, zero if x == y and strictly positive if x > y. """ return (x > y) - (x < y)
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def get_agency_url(operator_code): """Get url for operators""" operator_urls = { 'OId_LUL': "https://tfl.gov.uk/maps/track/tube", 'OId_DLR': "https://tfl.gov.uk/modes/dlr/", 'OId_TRS': "https://www.thamesriverservices.co.uk/", 'OId_CCR': "https://www.citycruises.com/", 'OId_CV': "https://www.thamesclippers.com/", 'OId_WFF': "https://tfl.gov.uk/modes/river/woolwich-ferry", 'OId_TCL': "https://tfl.gov.uk/modes/trams/", 'OId_EAL': "https://www.emiratesairline.co.uk/", #'OId_CRC': "https://www.crownrivercruise.co.uk/", } if operator_code in list(operator_urls.keys()): return operator_urls[operator_code] else: return "NA"
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from typing import List def list_truncated_nums(n: int) -> List[int]: """ Returns a list of all left and right truncated numbers of n >>> list_truncated_nums(927628) [927628, 27628, 92762, 7628, 9276, 628, 927, 28, 92, 8, 9] >>> list_truncated_nums(467) [467, 67, 46, 7, 4] >>> list_truncated_nums(58) [58, 8, 5] """ str_num = str(n) list_nums = [n] for i in range(1, len(str_num)): list_nums.append(int(str_num[i:])) list_nums.append(int(str_num[:-i])) return list_nums
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def calculate_total_bill(subtotal): """ (float) -> float subtotal is passed through as an input HST_RATE variable in this function is multiplied by inputted variable Function returns the resulting variable "total", rounded and formatted to 2 decimal points. Variable "total" is then rounded to the nearest 5 cents using the following nickel rounding scheme standard rules in Canada: 0.01 to 0.02 will round down to 0.00. 0. 03 to 0.04 will round up to 0.05. 0.06 to 0.07 will round down to 0.05. 0.08 to 0.09 will round up to 0.10 >>> calculate_total_bill(3.0) 3.40 >>> calculate_total_bill(6.67) 7.55 >>> calculate_total_bill(2.05) 2.30 """ HST_RATE = 1.13 total_bill = subtotal *HST_RATE return format(round(0.05 * round(float(total_bill)/0.05), 2), '.2f')
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def xr_to_np(S): """Convert xarray into numpy array""" if hasattr(S, "values"): S = S.values return S
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import json def parseBQNumeric(s): """ takes a string with response JSON, and returns the BQNumeric resposnes as an array of arrays. Each BQNumeric will have a single response. :param s: the json structure with responses :return: answer string """ answerlist = [] try: RespDict = json.loads(s) for records in RespDict["Response"]: answerlist.append(records["Response"]) except: return None return answerlist
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def _pairs_to_compute(rids, cids): """Determine the pairs of samples to compute distances between Parameters ---------- rids : Iterable The row IDs in the partial pairwise computation. cids : Iterable The column IDs in the partial pairwise computation. Raises ------ ValueError When determining ID pairs for blocks that fall outside of the diagonal of the resulting distance matrix, if a pair corresponds to the lower triangle, complain loudly. Returns ------- list of tuple The ID pairs to compute distances between. """ # if identical, gather the upper triangle if len(rids) == len(cids) and (rids == cids).all(): return [(i, j) for idx, i in enumerate(rids) for j in rids[idx+1:]] # otherwise, grab pairwise combinations disregarding the diagonal else: if set(rids).intersection(set(cids)): raise ValueError("Attempting to compute a lower triangle") return [(i, j) for i in rids for j in cids if i != j]
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def avg(numbers: list) -> float: """Calculate the average of a list of numbers numbers is a list of numbers Returns a float representing the average""" if len(numbers) != 0: # Check if the list is empty count = 0 for number in numbers: count += number return count / len(numbers) return 0
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import torch def deriv_tanh(x): """ derivative of tanh """ y = torch.tanh(x) return 1.0 - y * y
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from typing import Any from typing import MutableSequence def ensure_list(value: Any, convert_csv: bool = False, delimiter: str = ',') -> MutableSequence[Any]: """Convert an object, response, or (optionally) comma-separated string into a list""" if not value: return [] elif isinstance(value, dict) and 'results' in value: value = value['results'] elif convert_csv and isinstance(value, str) and delimiter in value: return [s.strip() for s in value.split(delimiter)] if isinstance(value, MutableSequence): return value elif isinstance(value, (tuple, set)): return list(value) else: return [value]
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def get_imphash(pefile_pe): """ Retrieve the imphash of a PE file. Returns None if imphash could not be extracted. """ imphash = pefile_pe.get_imphash() if imphash == '': return None else: return imphash
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def mu_na(n: float, a: float) -> float: """ mu = n^2 / a^3 :param n: mean motion in degrees :type n: float :param a: semi-major axis :type a: float :return: mu :rtype: float """ return n * n * a * a * a
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import re def unescape(string: str) -> str: """ Unescaping escaped characters typically inside attribute values. Args: string [str] -- string to be unescaped Returns: [str] -- unescaped string """ return re.sub(r"\\(.)", r"\1", string)
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def _to_image(data, width): """Convert data to an image. Parameters ---------- data : array_like Values of the pixels width : int Width of the image in pixels Returns ------- ndarray Data reshaped into an ndarray with width `width` """ return data.reshape(len(data) // width, width)
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def get_rounded_number( number: float, number_of_digits_after_separator: int = 0, ) -> float: """ Return rounded float number. Parameters ---------- number : float Number to be rounded. number_of_digits_after_separator Number of digits after decimal separator in `number`. Returns ------- float Rounded float number. """ if number_of_digits_after_separator < 0: raise ValueError( '`number_of_digits_after_separator` ' 'must to be positive integer number.' ) sign = -1.0 if number < 0 else 1.0 _number = abs(number) _multiplier = int('1' + '0' * number_of_digits_after_separator) _number_without_separator = _number * _multiplier _integer_part = int(_number_without_separator) _first_discarded_digit = int( (_number_without_separator - _integer_part) * 10 ) if _first_discarded_digit >= 5: _integer_part += 1 result = _integer_part / _multiplier * sign return result
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from functools import cmp_to_key def sort(array, comparison=None, key=None, reverse=False): """Sort `array` using optional `comparison`, `key`, and `reverse` options and return sorted `array`. Note: Python 3 removed the option to pass a custom comparison function and instead only allows a key function. Therefore, if a comparison function is passed in, it will be converted to a key function automatically using ``functools.cmp_to_key``. Args: array (list): List to sort. comparison (callable, optional): A custom comparison function used to sort the list. Function should accept two arguments and return a negative, zero, or position number depending on whether the first argument is considered smaller than, equal to, or larger than the second argument. Defaults to ``None``. This argument is mutually exclusive with `key`. key (callback, optional): A function of one argument used to extract a a comparison key from each list element. Defaults to ``None``. This argument is mutually exclusive with `comparison`. reverse (bool, optional): Whether to reverse the sort. Defaults to ``False``. Returns: list: Sorted list. Warning: `array` is modified in place. Example: >>> sort([2, 1, 4, 3]) [1, 2, 3, 4] >>> sort([2, 1, 4, 3], reverse=True) [4, 3, 2, 1] >>> results = sort([{'a': 2, 'b': 1},\ {'a': 3, 'b': 2},\ {'a': 0, 'b': 3}],\ key=lambda item: item['a']) >>> assert results == [{'a': 0, 'b': 3},\ {'a': 2, 'b': 1},\ {'a': 3, 'b': 2}] .. versionadded:: 2.2.0 """ # pylint: disable=redefined-outer-name if comparison and key: raise Exception( 'The "comparison" and "key" arguments are mutually exclusive') if comparison: key = cmp_to_key(comparison) array.sort(key=key, reverse=reverse) return array
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def Chunkify(list, chunk_size): """divides an array into chunks of chunk_size""" return [list[i:i + chunk_size] for i in range(0, len(list), chunk_size)]
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import json import tempfile def _modify_json_with(json_filename, modifier_func): """ Given a modifier_func which modifies the data in the given file, updates the json file and returns a Tempfile holding the new data """ # Update the sidecar data with open(json_filename, 'r+', encoding='utf-8') as file_obj: data = json.load(file_obj) modifier_func(data) # Write it to a tempfile modified_json_tempfile = tempfile.NamedTemporaryFile() # pylint: disable=consider-using-with with open(modified_json_tempfile.name, 'w', encoding='utf-8') as file_obj: json.dump(data, file_obj) return modified_json_tempfile
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from typing import Union import torch def check_data_types(data) -> Union[list, torch.Tensor]: """ Utility function to check if data passed is all on tensor format. Can handle iterables or single structures :param data: Data to be checked :return: list of tensors """ if torch.is_tensor(data): return data else: try: return torch.tensor(data, dtype=torch.float) except ValueError: return [torch.tensor(x, dtype=torch.float) for x in data]
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import torch def max_shape(data): """Gets the maximum length along all dimensions in a list of Tensors""" shapes = torch.Tensor([_.shape for _ in data]) return torch.max(shapes.transpose(0, 1), dim=1)[0].int()
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def get_str_from_list(message_list: list, cc: str = "and", punct: bool = True) -> str: """Returns list as a formatted string for speech. message list: [list] of the components to be joined. cc: [str] coordinating conjunction to place at end of list. punct: bool - indicates if should include punctuation at end of list. """ speech_list = [] if not message_list: return '' elif len(message_list) == 1: message = str(message_list[0]) if punct: message += "." return message for i in range(len(message_list)): if i == len(message_list) - 1: speech_list.append(' and ') speech_list.append( str(message_list[i])) if i != len(message_list) - 1: speech_list.append(', ') if punct: speech_list.append('.') return ''.join(speech_list)
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import torch def get_torch_zeros(shape, device='cuda'): """ Generate zero tensor with given shape :param shape: array shape :param device: sets training device :return: zero tensor with given shape """ return torch.zeros(shape, dtype=torch.float32).to(device)
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def flatten_list(messy_list): """ Flatten an unruly list of lists. Cf. <http://stackoverflow.com/a/952914> """ return [item for sublist in messy_list for item in sublist]
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def Switch(node): """ Root of switch/case branch Args: node (Switch): Current position in node-tree Return: str : Translation of current node. Children: Expression Case+ Otherwise? Expression: Test-expression Case: Case-block Otherwise: Otherwise-block Examples: >>> print(matlab2cpp.qscript("a=1; switch a; case b; c; otherwise; d")) a = 1 ; if (b == a) { c ; } else { d ; } """ if node[0].cls == "Var": out = "" # create switch variable else: node.type = node[0].type out = "%(type)s _var_%(type)s = %(0)s ;\n" return out + "\n".join(map(str, node[1:]))
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def _number_convert(match): """ Convert number with an explicit base to a decimal integer value: - 0x0000 -> hexadecimal - 16'h0000 -> hexadecimal - 0b0000 -> binary - 3'b000 -> binary - otherwise -> decimal """ prefix, base, number = match.groups() if prefix is not None: return str(match.group(0)) if base in "xh": return str(int(number, 16)) if base == "b": return str(int(number, 2)) return str(int(number, 10))
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def parse_utf(s): """ Decode a utf-8 encoded string. """ return s.strip().decode('utf-8') or None
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def get_fix_range_value(tot_elms, index): """Percentage value of the given index in a set of elements. The value returned is in the middle: For example: 0.0 1.0 |-----|-----|-----| ^ ^ ^ Params: tot_elems (int): number of elements in the set index (int): the index of the current element, starting from 1 Return: float: percentage with dot notation, so from 0.0 to 1.0 """ step = (1. / tot_elms) / 2. return float((index / tot_elms) - step)
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def get_total(lines): """ This function takes in a list of lines and returns a single float value that is the total of a particular variable for a given year and tech. Parameters: ----------- lines : list This is a list of datalines that we want to total. Returns: -------- total : float This is the sum total from the data lines. """ total = 0.0 for line in lines: data_sep = line.split() total += float(data_sep[0]) return total
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from pathlib import Path def _check_cache(arg_hash): """ Check whether a cache file exists for the given arg_hash. """ path = Path(f"./{arg_hash}.pt") return path.is_file()
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import requests import json from typing import OrderedDict def get_model(uri): """ Return a capture model as ordered JSON object :param uri: URI for capture model :return: ordered JSON object """ if uri: r = requests.get(uri) if r.status_code == requests.codes.ok: source = r.text model = json.loads(source, object_pairs_hook=OrderedDict) return model else: return None else: return None
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def test_pkgrepo_with_architectures(pkgrepo, grains, sources_list_file, subtests): """ Test managing a repo with architectures specified """ name = "deb {{arch}}http://foo.com/bar/latest {oscodename} main".format( oscodename=grains["oscodename"] ) def _get_arch(arch): return "[arch={}] ".format(arch) if arch else "" def _run(arch=None, test=False): return pkgrepo.managed( name=name.format(arch=_get_arch(arch)), file=sources_list_file, refresh=False, test=test, ) with subtests.test("test=True"): # Run with test=True ret = _run(test=True) assert ret.changes == {"repo": name.format(arch="")} assert "would be" in ret.comment assert ret.result is None with subtests.test("test=False"): # Run for real ret = _run() assert ret.changes == {"repo": name.format(arch="")} assert ret.comment.startswith("Configured") assert ret.result is True with subtests.test("test=True repeat"): # Run again with test=True, should exit with no changes and a True # result. ret = _run(test=True) assert not ret.changes assert "already" in ret.comment assert ret.result is True with subtests.test("test=False repeat"): # Run for real again, results should be the same as above (i.e. we # should never get to the point where we exit with a None result). ret = _run() assert not ret.changes assert "already" in ret.comment assert ret.result is True expected_changes = { "line": { "new": name.format(arch=_get_arch("amd64")), "old": name.format(arch=""), }, "architectures": {"new": ["amd64"], "old": []}, } with subtests.test("test=True arch=amd64"): # Run with test=True and the architecture set. We should get a None # result with some expected changes. ret = _run(arch="amd64", test=True) assert ret.changes == expected_changes assert "would be" in ret.comment assert ret.result is None with subtests.test("test=False arch=amd64"): # Run for real, with the architecture set. We should get a True # result with the same changes. ret = _run(arch="amd64") assert ret.changes == expected_changes assert ret.comment.startswith("Configured") assert ret.result is True with subtests.test("test=True arch=amd64 repeat"): # Run again with test=True, should exit with no changes and a True # result. ret = _run(arch="amd64", test=True) assert not ret.changes assert "already" in ret.comment assert ret.result is True with subtests.test("test=False arch=amd64 repeat"): # Run for real again, results should be the same as above (i.e. we # should never get to the point where we exit with a None result). ret = _run(arch="amd64") assert not ret.changes assert "already" in ret.comment assert ret.result is True expected_changes = { "line": { "new": name.format(arch=""), "old": name.format(arch=_get_arch("amd64")), }, "architectures": {"new": [], "old": ["amd64"]}, } with subtests.test("test=True arch=None"): # Run with test=True and the architecture set back to the original # value. We should get a None result with some expected changes. ret = _run(test=True) assert ret.changes == expected_changes assert "would be" in ret.comment assert ret.result is None with subtests.test("test=False arch=None"): # Run for real, with the architecture set. We should get a True # result with the same changes. ret = _run() assert ret.changes == expected_changes assert ret.comment.startswith("Configured") assert ret.result is True with subtests.test("test=True arch=None repeat"): # Run again with test=True, should exit with no changes and a True # result. ret = _run(test=True) assert not ret.changes assert "already" in ret.comment assert ret.result is True with subtests.test("test=False arch=None repeat"): # Run for real again, results should be the same as above (i.e. we # should never get to the point where we exit with a None result). ret = _run() assert not ret.changes assert "already" in ret.comment assert ret.result is True
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import torch def transform_verts(verts, T): """ Transform vertices using a 4x4 transformation matrix Inputs: - verts: FloatTensor of shape (N, V, 3) giving a batch of vertex positions. - T: FloatTensor of shape (N, 4, 4) giving transformation matrices Outputs: - verts_out: FloatTensor of shape (N, V, 4) giving vertex homogeneous positions (x, y, z, w) where verts_out[i] is the result of transforming verts[i] by T[i]. """ N, V = verts.shape[0], verts.shape[1] dtype, device = verts.dtype, verts.device # Add an extra row of ones to the world-space coordinates of verts before # multiplying by the projection matrix. We could avoid this allocation by # instead multiplying by a 4x3 submatrix of the projectio matrix, then # adding the remaining 4x1 vector. Not sure whether there will be much # performance difference between the two. ones = torch.ones(N, V, 1, dtype=dtype, device=device) verts_hom = torch.cat([verts, ones], dim=2) verts_cam_hom = torch.bmm(verts_hom, T.transpose(1, 2)) return verts_cam_hom
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def to_fahrenheit(temp): """ Converts a temperature in celsius to fahrenheit. """ return (temp * 1.8) + 32
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def cant_adyacentes(life, f, c): """ Calcula la cantidad de células adyacentes a la celda en la fila `f` y la columna `c`. Importante: El "tablero" se considera "infinito": las celdas del borde izquierdo están conectadas a la izquierda con las celdas del borde derecho, y viceversa. Las celdas del borde superior están conectadas hacia arriba con las celdas del borde inferior, y viceversa. """ return sum([1 if ( i % len(life), j % len(life[0])) != (f, c) and life[i % len(life)][j % len(life[0])] else 0 for j in range(c - 1, c + 2) for i in range(f - 1, f + 2)])
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