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def sum_node_list(node_list): """Custom sum func to avoid creating redundant nodes in Python sum func.""" node_list = [n for n in node_list if n is not None] if node_list == []: return None from operator import add from functools import reduce return reduce(add, node_list)
def extract_major_version(scala_version): """Return major Scala version given a full version, e.g. "2.11.11" -> "2.11" """ return scala_version[:scala_version.find(".", 2)]
def serialize_beneficiarios_programa(beneficiario): """ # $ref: '#/components/schemas/beneficiariosPrograma' """ if beneficiario: if beneficiario.codigo == 'DC': return { "clave": beneficiario.codigo, "valor": beneficiario.tipo_relacion } else: return {"clave": "OTRO", "valor":"Otro"} else: return {"clave": "OTRO", "valor":"Otro"}
def get_chebi_synonyms(chebi_ent): """ Get synonyms from ChEBI entity :param chebi_ent: :return: """ if hasattr(chebi_ent, 'Synonyms'): return [entry.data for entry in chebi_ent.Synonyms] else: return []
def find_keywords_sentences(keywords, cleaned_lines): """ Find the occurrences of the keywords in the text. :param keywords: The keywords to be searched in the lines :param cleaned_lines: The lines of the document :return: The lines with the given keywords """ accepted_lines = list() for cleaned_line in cleaned_lines: for keyword in keywords: if keyword.lower() in cleaned_line.lower(): accepted_lines.append(cleaned_line) return list(set(accepted_lines))
def flatten_cond_gen_values(gen_eval: dict): """ Converts the coherence evaluation results into a flattened dict """ flattened_dict = {} for j, l_key in enumerate(sorted(gen_eval['cond'].keys())): for k, s_key in enumerate(gen_eval['cond'][l_key].keys()): for g_key in gen_eval['cond'][l_key][s_key]: key = l_key + '_' + s_key + '__' + g_key flattened_dict[key] = gen_eval['cond'][l_key][s_key][g_key] return flattened_dict
def to_sbp_file_name(identifier): """ Creates file name from sbp message identifier. """ prefix = 'swiftnav.sbp.' if identifier.startswith(prefix): return identifier[len(prefix):] else: return identifier
def info_from_header(header): """Returns mb, ms, sequence extracted from header in logfile.""" from numpy import nan # If present in header information, extract mb, ms, and sequence mb = nan ms = nan sequence = '' header = str(header).replace(' ','') # remove spaces before splitting if 'mb=' in header: mb = float(header.split('mb=')[1].split(',')[0]) if 'ms=' in header: ms = float(header.split('ms=')[1].split(',')[0]) if 'sequence=' in header: sequence = header.split('sequence=')[1].split(',')[0] return mb,ms,sequence
def build_description(summary, description): """ Return a description string from a summary and description """ summary = (summary or '').strip() description = (description or '').strip() if not description: description = summary else: if summary and summary not in description: description = '\n'.join([summary , description]) return description
def try_parse_float(text): """ Try to parse a string to a float. """ try: return float(text) except ValueError: return None
def single_timeseries_to_json(value=None, unit="", label="", asset_type=""): """format the information about a single timeseries in a specific JSON""" if value is None: value = [] return {"value": value, "unit": unit, "label": label, "asset_type": asset_type}
def _GenerateEstimatorConstructor(estimator_class_name, variable_types, variable_names, extension_class_name): """ Generates the consructor for the estimator class. """ code = ["\n\npublic {0}(IHostEnvironment env".format(estimator_class_name)] # Generate the Constructor parameters for variable_type, variable_name in zip(variable_types, variable_names): code.append(", {0}.TransformParameter<{1}> {2}".format(extension_class_name, variable_type, variable_name)) code.extend( [ ", string outputColumn", ")\n{" ] ) # Generate assigning the values in the constructor for variable_name in variable_names: code.append("\n_{0} = {0};".format(variable_name)) # Add assignments that are always required code.extend( [ "\n_outputColumn = outputColumn;", "\n_host = env.Register(nameof({0}));".format(estimator_class_name), "\n}" ] ) return "".join(code)
def compute_poi_email_ratio(poi_messages, all_messages): """ FEATURE given a number messages to/from POI (numerator) and number of all messages to/from a person (denominator), return the ratio of messages to/from that person that are from/to a POI """ ratio = 0. if type(poi_messages) is int and type(all_messages) is int and poi_messages > 0 and all_messages > 0: ratio = float(poi_messages) / float(all_messages) return ratio
def selu_initialization_std(shape): """ initialization meant to be used in conjunction with selu non-linearity. sqrt(1/fan_in) """ std = (1.0/shape[0]) ** .5 print("selu init std", shape, std) return std
def HelperParseOutput(lst): """Self defined parameter function for 'object_pairs_hook' of json.loads(). Purpose: This function helps to parse json text with duplicate keys, for instance: json text: {"key":1, "key":2, "key2":3, "key2":4} With this function, we will have the following dict: {"key":[1, 2], "key2":[3, 4] } Args: lst: A list of tuples contains the output of benchmark tests. Returns: A dict contains the output of benchmark tests. """ result = {} for key, val in lst: if key in result: if isinstance(result[key], list): result[key].append(val) else: result[key] = [result[key], val] else: result[key] = val return result
def fuzzy_not(arg): """ Not in fuzzy logic Will return Not if arg is a boolean value, and None if argument is None. Examples: >>> from sympy.logic.boolalg import fuzzy_not >>> fuzzy_not(True) False >>> fuzzy_not(None) >>> fuzzy_not(False) True """ if arg is None: return return not arg
def write_key(key, value): """Write a `key = value` line in an LTA file. Parameters ---------- key : str value : int or float or str Returns ------- str """ if isinstance(value, (str, int, float)): return f'{key} = {value}' else: return f'{key} = ' + ' '.join([str(v) for v in value])
def enumerate(lst): """ >>> enumerate(["a", "b", "c"]) [(0, 'a'), (1, 'b'), (2, 'c')] >>> for index, value in enumerate(["a", "b", "c"]): ... print index, value 0 a 1 b 2 c """ return [(i, lst[i]) for i in range(len(lst))]
def get_user_plist_path(): """ Helper function returning the path to the user account property list. """ user_plist_path = "/private/var/db/dslocal/nodes/Default/users/" return user_plist_path
def argif(cond,if_true_value,else_value): """ If cond is true, returns the if_true_value, otherwise else_value. Roughly equilvanet to a lisp (if cond true false) """ if(cond): return if_true_value else: return else_value
def splitext(fname): """Splits filename and extension (.gz safe) >>> splitext('some/file.nii.gz') ('file', '.nii.gz') >>> splitext('some/other/file.nii') ('file', '.nii') >>> splitext('otherext.tar.gz') ('otherext', '.tar.gz') >>> splitext('text.txt') ('text', '.txt') Source: niworkflows """ from pathlib import Path basename = str(Path(fname).name) stem = Path(basename.rstrip(".gz")).stem return stem, basename[len(stem) :]
def get_AC(GT): """ Convert GT to AC for a single sample """ if GT == 'None/None': AC = 'NA' else: AC = sum([int(a) for a in GT.split('/')]) return str(AC)
def unhappy_f_point_lin(list, index, other_index): """ Checks if a new point will be unhappy. Returns False if will be happy. """ if list[other_index] == 1: list[other_index] = 0 else: list[other_index] = 1 if index == 0: if list[index] != list[index + 1]: if list[other_index] == 1: list[other_index] = 0 else: list[other_index] = 1 return False if index == len(list)-1: if list[index] != list[index - 1]: if list[other_index] == 1: list[other_index] = 0 else: list[other_index] = 1 return False else: if list[index] != list[index - 1] or list[index] != list[(index + 1) % len(list)]: if list[other_index] == 1: list[other_index] = 0 else: list[other_index] = 1 return False if list[other_index] == 1: list[other_index] = 0 else: list[other_index] = 1 return True
def left_join(phrases): """ Join strings and replace "right" to "left" """ # l = list(phrases) return ','.join([x.replace('right', 'left') for x in phrases])
def remove_optimized_key_from_ai_list(key_list: list, optimized_dict: dict): """ :param key_list: :param optimized_dict: :return: """ for key, value in optimized_dict.items(): if value in key_list: ind = key_list.index(value) key_list.pop(ind) return key_list
def find_number(value): """Convert value to a number, if posible, and indicate success or failure Parameters: value: The variable to convert (could be _anything_) Return values: First the converted number, as float or int; then a boolean that shows whether the conversion succeeded (true) or failed (false) """ number = 0 #Default value valid = True #Also a default (one of these will usually change) try: number = float(value) except (ValueError, TypeError): valid = False if not valid: try: number = int(value, 16) # Catch hexadecimals valid = True except (ValueError, TypeError): valid = False return number, valid
def cat_matrices2D(mat1, mat2, axis=0): """Concatenates two matrices along a specific axis""" ans = [] if axis == 0 and len(mat1[0]) == len(mat2[0]): return mat1 + mat2 elif axis == 1 and len(mat1) == len(mat2): for i in range(len(mat1)): ans.append(mat1[i] + mat2[i]) return ans return None
def _tupleindex(index): """Convert 'line.column' to (line, column).""" line, column = index.split('.') return (int(line), int(column))
def read_leaf_header(leaf): """ Parse the leaf header """ header = {} header["version"] = int(leaf[0]) header["merkle_leaf_type"] = int(leaf[1]) header["timestamp"] = int.from_bytes(leaf[2:10], "big") header["LogEntryType"] = int.from_bytes(leaf[10:12], "big") header["Entry"] = leaf[12:] return header
def advance_version(v, bumprule): """ Advance the version based on a version bump rule """ vercomps = v.replace('v', '').split('.') majv = int(vercomps[0]) minv = int(vercomps[1]) patchv = int(vercomps[2]) if bumprule == "major": majv += 1 minv = 0 patchv = 0 if bumprule == "minor": minv += 1 patchv = 0 if bumprule == "patch": patchv += 1 return "{}.{}.{}".format(majv, minv, patchv)
def moving_average(lst, size): """ calculate simple moving average values """ if not isinstance(size, int): raise TypeError('size must be integer. {} given'.format(size)) if not size > 0: raise ValueError('size must be greater than zero. {} given'.format(size)) if len(lst) < size: raise ValueError(('length of list must be greater than size.' ' list: {} size: {}'.format(lst, size))) summ = sum(lst[:size]) nlst = [summ / size] for end in range(size, len(lst)): summ += lst[end] - lst[end - size] nlst.append(summ / size) return nlst
def flatten_research(research): """Flatten research data.""" flat = [] for pid, techs in research.items(): for tid, values in techs.items(): flat.append(dict(values, player_number=pid, technology_id=tid)) return flat
def check_password(option, opt, value): """check a password value (can't be empty) """ # no actual checking, monkey patch if you want more return value
def getFIndex(field_names, field_name): """Will get the index for a arcpy da.cursor based on a list of field names as an input. Assumes string will match if all the field names are made lower case.""" try: return [str(i).lower() for i in field_names].index(str(field_name).lower()) # Make iter items lower case to get right time field index. except: print("Couldn't retrieve index for {0}, check arguments.".format(str(field_name))) return None
def priviledged_instructions(instr, bv, isa_specific_data): """ """ if not isa_specific_data: return False if isa_specific_data and isa_specific_data.get('privileged_instructions'): if instr[0][0].text in isa_specific_data['privileged_instructions']: return True return False
def sort_list(data_list, index, reverse): """ index: int number, according to it to sort data_list""" if index is None: sorted_data_list = sorted(data_list, key=lambda x: x, reverse=reverse) else: sorted_data_list = sorted(data_list, key=lambda x: x[index], reverse=reverse) return sorted_data_list
def extend(value, tupleo): """ extend(...) method of tupleo.tuple instance T.extend(iterable, tupleo) -> None -- extend tuple, tupleo by appending elements from the iterable """ if type(tupleo) != tuple: raise TypeError("{} is not tuple".format(tupleo)) if type(value) !=tuple: raise TypeError("{} is not tuple".format(value)) convertlist = list(tupleo) convertlist.extend(list(value)) return convertlist
def var_name(var): """ Return the name of a variable """ for name,value in globals().items() : if value is var : return name return None
def decrement_items(inventory, items): """ :param inventory: dict - inventory dictionary. :param items: list - list of items to decrement from the inventory. :return: dict - updated inventory dictionary with items decremented. """ for item in items: inventory[item] = max(0, inventory[item] - 1) return inventory
def count_same(sequence1, sequence2): """ What comes in: -- two sequences that have the same length What goes out: Returns the number of indices at which the two given sequences have the same item at that index. Side effects: None. Examples: If the sequences are: (11, 33, 83, 18, 30, 55) (99, 33, 83, 19, 30, 44) then this function returns 3 since the two sequences have the same item at: -- index 1 (both are 33) -- index 2 (both are 83) -- index 4 (both are 30) Another example: if the sequences are: 'how are you today?' 'HOW? r ex u tiday?' then this function returns 8 since the sequences are the same at indices 5 (both are 'r'), 10 (both are 'u'), 11 (both are ' '), 12 (both are 't'), 14 (both are 'd'), 15 (both are 'a'), 16 (both are 'y') and 17 (both are '?') -- 8 indices. Type hints: type: sequence1: tuple or list or string type: sequence2: tuple or list or string """ # ------------------------------------------------------------------------- # DONE: 6. Implement and test this function. # The testing code is already written for you (above). # ------------------------------------------------------------------------- count = 0 for k in range(len(sequence1)): if sequence1[k] == sequence2[k]: count = count + 1 return count
def _convert_german_time_to_iso(date_string: str): """Convert a german date input as a string to ISO format (DD.MM.YYYY -> YYYY-MM-DD). ONLY DD.MM.YYYY FORMAT.""" return date_string[-4:] + '-' + date_string[3:5] + '-' + date_string[:2]
def set_optional_arguments(options, option_values, command_line_options): """ Validate and set optional command cline arguments. """ option_value_keys = option_values.keys() for option in options: if option[0] == '<': non_required_option = option[1:len(option) - 1] if non_required_option in option_value_keys: command_line_options[non_required_option] = option_values[non_required_option] elif non_required_option[0] in option_value_keys: command_line_options[non_required_option] = option_values[non_required_option[0]] else: if option in option_value_keys: command_line_options[option] = option_values[option] elif option[0] in option_value_keys: command_line_options[option] = option_values[option[0]] else: return (True, f'Missing required option: {option}') return None
def ATGC_content(dna_sequence): """Returns ATGC contents in the form of a dict.""" ATGCDict = {'A': 0, 'T': 0, 'G': 0, 'C': 0} for nucleotide in dna_sequence: try: ATGCDict[nucleotide] += 1 except KeyError: pass return ATGCDict
def numberIn(s): """Return a Decimal from a string that might have unicode pound symbols and commas""" number = str() for c in s: if c in '0123456789.': number = number + c if len(number) > 0: from decimal import Decimal return Decimal(number) else: return None
def compute_peg(profit, infos_boursiere): """ Returns an approximation of the PEG """ if not 'PER' in infos_boursiere: return 0 if profit is None: return None per = float(infos_boursiere['PER'].split()[0]) if profit <= 0: return 0 return round(per/profit, 1)
def count_ways(target, max_integer=None, cache=None): """ Count the number of ways of making target from sum of at least 1 integers with max_integer as the largest integer in the sum. If max_integer is not provided, count all possible ways from sum of at least 2 integers. """ # Special cases: because we use this recursively, we'll special-case the 1 or 2 targets # and the 1 max_integer if max_integer == 1: return 1 if target == 1: return 1 elif target == 2 and max_integer == 2: return 2 if not max_integer: max_integer = target - 1 if max_integer > target: max_integer = target if not cache: # Create a cache for storing results for all combinations of (target, max_integer) cache = [[None] * target for i in range(target + 1)] elif cache[target][max_integer] is not None: return cache[target][max_integer] remainder = target ways = 0 # How many ways are there to make target using max_integer at least once? while remainder > max_integer: remainder -= max_integer ways += count_ways(remainder, max_integer - 1, cache=cache) # Special case: we have just 1 way to make this last case! if remainder == max_integer: ways += 1 # Now recurse with the next smaller max_integer if max_integer > 0: ways += count_ways(target, max_integer - 1, cache=cache) cache[target][max_integer] = ways return ways
def baby_names_list_from_table_rows(a_table_rows): """ a_table_rows is a list of dictionaries return list of lists, discarding gender information contained in a_table_rows element [name, rank] list is sorted by name """ print('baby_names_list_from_table_rows') baby_names_list = [] for row in a_table_rows: baby_names_list.append([row['name_boy'], row['rank']]) baby_names_list.append([row['name_girl'], row['rank']]) def sort_key_from_array(an_array): """ return key for sorted() """ return an_array[0] baby_names_list = sorted(baby_names_list, key=sort_key_from_array) #print(baby_names_list) return baby_names_list
def build_bankruptcy_definition(years): """Build a bankruptcy definition Notes: This function is set according to a line of best fit from Year 0 at -10% ROI to 10% ROI by Year 7. Args: years (int): No. of years for analysis Returns: Bankruptcy definition (list): A timeseries of the bankruptcy threshold graph TO DO: Allow flexibility of bankruptcy definition by allowing input of two data points rather than assuming (-10%, 0) and (10%, 7) """ bankruptcy_definition =[] for y in range(years+1): # Threshold for bankruptcy if y <= 7: bankruptcy_definition.append(y*2.8571 - 10) # Year 0 - below 10% ROI, Year 7 - 10% ROI elif y > 7: bankruptcy_definition.append(10) balance_threshold = 0 return bankruptcy_definition, balance_threshold return bankruptcy_definition
def get_iou(bb1, bb2): """ Determine Intersection over Union for two bounding boxes """ # Determine the coordinates of the intersection rectangle xmin = max(bb1[0], bb2[0]) ymin = max(bb1[1], bb2[1]) xmax = min(bb1[2], bb2[2]) ymax = min(bb1[3], bb2[3]) if xmax < xmin or ymax < ymin: return 0.0 # Determine intersection area intersection_area = (xmax - xmin) * (ymax - ymin) # Compute area of bounding boxes bb1_area = (bb1[2] - bb1[0]) * (bb1[3] - bb1[1]) bb2_area = (bb2[2] - bb2[0]) * (bb2[3] - bb2[1]) # compute the intersection over union iou = intersection_area / float(bb1_area + bb2_area - intersection_area) return iou
def get_varinfo_from_table(discipline,parmcat,parmnum): """ Return the GRIB2 variable information given values of `discipline`, `parmcat`, and `parmnum`. NOTE: This functions allows for all arguments to be converted to a string type if arguments are integer. Parameters ---------- **`discipline`**: `int` or `str` of Discipline code value of a GRIB2 message. **`parmcat`**: `int` or `str` of Parameter Category value of a GRIB2 message. **`parmnum`**: `int` or `str` of Parameter Number value of a GRIB2 message. Returns ------- **`list`**: containing variable information. "Unknown" is given for item of information if variable is not found. - list[0] = full name - list[1] = units - list[2] = short name (abbreviated name) """ if isinstance(discipline,int): discipline = str(discipline) if isinstance(parmcat,int): parmcat = str(parmcat) if isinstance(parmnum,int): parmnum = str(parmnum) try: tblname = 'table_4_2_'+discipline+'_'+parmcat modname = '.section4_discipline'+discipline exec('from '+modname+' import *') return locals()[tblname][parmnum] except(ImportError,KeyError): return ['Unknown','Unknown','Unknown']
def matrix_from_vectors(op, v): """ Given vector v, build matrix [[op(v1, v1), ..., op(v1, vn)], ... [op(v2, v1), ..., op(vn, vn)]]. Note that if op is commutative, this is redundant: the matrix will be equal to its transpose. The matrix is represented as a list of lists. """ return [[op(vi, vj) for vj in v] for vi in v]
def flatten(iterable, n=1): """ remove n levels of list nesting for a list of lists assumes uniform nesting :param iterable: nested list of lists to be flattened :param n: how many levels of nesting to remove :return: flattened list """ tmp = iterable for _ in range(n): tmp = [item for sublist in tmp for item in sublist] return tmp
def find_identical_rects(frames): """Unify ChangedRects with identical key()s.""" rawRectCount = 0 cache = {} for frame in frames: content = frame.content() rawRectCount += len(content) uniqueContent = [] for r in content: key = r.key() r = cache.get(key, r) r.addOccurrence(frame) cache[key] = r uniqueContent.append(r) content[:] = uniqueContent return rawRectCount, len(cache)
def request_id(request, flavor_id): """Flavor id to use on the url call.""" return request.param if hasattr(request, 'param') else flavor_id
def ref_seq_output(in_seq_name, in_ref_name, ext): """ Generate output file name :param in_seq_name: treatment name (str) :param in_ref_name: reference name (str)nt) :param ext: extension (ie. csv or pdf) :return: output filename (str) """ return "{0}_{1}.{2}".format(in_ref_name, in_seq_name, ext)
def unknown_id_to_symbol(unknown_id, header="X"): """Get the symbol of unknown whose id is |unknown_id|. :type unknown_id: int :type header: str :param unknown_id: The ID of the unknown. :param header: The symbol header. :rtype : str :return: A string that contains the symbol. """ # If the |unknown_id| is zero, just returns |PROTECT_HEADER|a. if unknown_id == 0: return header + "a" # Initialize alphabet table. ch_table = "abcdefghijklmnopqrstuvwxyz" ch_table_len = len(ch_table) # Convert decimal to 26 ary. cur_id = unknown_id r = "" while cur_id != 0: r = ch_table[cur_id % ch_table_len] + r cur_id = int(cur_id / ch_table_len) # Return the converted symbol. return header + r
def make_config( image_h, image_w, image_d, train_split=0.8, batch_size=128, cache_images=True, crop_top=0, crop_bot=0, data_path=None, max_thr=0.5 ): """ Make a DonkeyCar config-like object if there is no config file available. Entries needed for: gather_records -> gather_tubs -> gather_tub_paths cfg.DATA_PATH if tub_names is None collate_records cfg.MODEL_CATEGORICAL_MAX_THROTTLE_RANGE, if opts['categorical'] cfg.TRAIN_TEST_SPLIT vae_generator cfg.BATCH_SIZE cfg.CACHE_IMAGES (bool) cfg.IMAGE_H cfg.IMAGE_W cfg.IMAGE_DEPTH -> load_scaled_image_arr cfg.IMAGE_H cfg.IMAGE_W cfg.IMAGE_DEPTH -> normalize_and_crop cfg.ROI_CROP_TOP cfg.ROI_CROP_BOTTOM """ from collections import namedtuple CFG = namedtuple('Config', ['DATA_PATH', 'MODEL_CATEGORICAL_MAX_THROTTLE_RANGE', 'TRAIN_TEST_SPLIT', 'BATCH_SIZE', 'CACHE_IMAGES', 'IMAGE_H', 'IMAGE_W', 'IMAGE_DEPTH', 'ROI_CROP_TOP', 'ROI_CROP_BOTTOM']) cfg = CFG(DATA_PATH=data_path, MODEL_CATEGORICAL_MAX_THROTTLE_RANGE=max_thr, TRAIN_TEST_SPLIT=train_split, BATCH_SIZE=batch_size, CACHE_IMAGES=cache_images, IMAGE_H=image_h, IMAGE_W=image_w, IMAGE_DEPTH=image_d, ROI_CROP_TOP=crop_top, ROI_CROP_BOTTOM=crop_bot) return cfg
def extract_row(key: str, clientresult) -> dict: """ Extract one row from the client result, and return result as dict """ data = clientresult[key] return dict(data)
def trimArray(array): """ >>> trimArray([0 for _ in range(10)]) == [0] True >>> trimArray([1, 0, 0, 0, 0, 0, 0, 0]) [1] """ for i in range(len(array) - 1, -1, -1): if array[i] != 0: return array[:i + 1] return [0]
def RPL_YOURESERVICE(sender, receipient, message): """ Reply Code 383 """ return "<" + sender + ">: " + message
def _texture(number): """Generates ARB assembly for a texture.""" return 'texture[{}]'.format(number)
def solution(value: int) -> str: """ Complete the solution so that it returns a formatted string. The return value should equal "Value is VALUE" where value is a 5 digit padded number. :param value: :return: """ result = str(value) while len(result) != 5: result = '0' + result return 'Value is {}'.format(result)
def _get_axis_num(nrow, row, col): """ computes axis number Parameters ---------- nrow : int number of rows row : int row number col : int column number """ return (nrow * row + col) + 1
def _list_clean(tweet): """Splits the tweet into words based on spaces and returns this list along with a concatenated string without spaces. Args: tweet (str): Tweet text Returns: tuple """ # Tweet split into a list of words tweet_word_list = tweet.split(" ") # Tweet rejoined into string thus removing all spaces tweet_clean = "".join(tweet_word_list) return tweet_word_list, tweet_clean
def plist_set_version(plist_data, version_str): """ <key>CFBundleShortVersionString</key> <string>0.1</string> <key>CFBundleVersion</key> <string>0.1</string> """ plist_lines = plist_data.split("\n") plist_num_lines = len(plist_lines) out_lines = [] line_idx = 0 while line_idx < plist_num_lines: l = plist_lines[line_idx] line_idx += 1 out_lines.append(l) if -1 != l.find("CFBundleShortVersionString") or \ -1 != l.find("CFBundleVersion"): out_lines.append(" <string>%s</string>" % version_str) line_idx += 1 return "\n".join(out_lines)
def safe_import(origin, funk1, funk2): """Safely import a function whose name was changed from a module whose name was not. This function is specially useful if the function name is not known at runtime. Args: origin (str): name of the module where the function to be imported is located funk1 (str): name of the first function name to try to import funk2 (str): name of the second function name to try to import Returns: function: function object imported from `origin` Example: # instead of writting this try: from itertools import filterfalse except ImportError: from itertools import ifilterfalse as filterfalse # write this filterfalse = safe_import('itertools', 'filterfalse', 'ifilterfalse') """ try: hook = __import__(origin, globals(), locals(), [funk1], 0) return getattr(hook, funk1) except: hook = __import__(origin, globals(), locals(), [funk2], 0) return getattr(hook, funk2)
def same_rank(hand, n_of_a_kind): """ Given a hand of cards, return the number of n_of_a_kind combinations of ranks. For example, with n_of_a_kind=2, the function returns the number of pairs in the hand. """ ranks = [card[1:] for card in hand] counter = 0 already_counted = [] for rank in ranks: if rank not in already_counted and \ ranks.count(rank) == n_of_a_kind: counter += 1 already_counted.append(rank) return counter
def filtered_map(method, object_list): """ Performs a map then a filter on the object list. The final filter strips out objects which evaluate to False. """ return [x for x in map(method, object_list) if x]
def get_pairs(word): """Return set of symbol pairs in a word. Word is represented as tuple of symbols (symbols being variable-length strings). """ pairs = set() prev_char = word[0] for char in word[1:]: pairs.add((prev_char, char)) prev_char = char return pairs
def uniquify_tuples(tuples): """ Uniquifies Mimikatz tuples based on the password. cred format- (credType, domain, username, password, hostname, sid) """ seen = set() return [item for item in tuples if "%s%s%s%s"%(item[0],item[1],item[2],item[3]) not in seen and not seen.add("%s%s%s%s"%(item[0],item[1],item[2],item[3]))]
def version_splitter(s): """Splits a version string into a tuple of integers. The following ASCII characters are allowed, and employ the following conversions: a -> -3 b -> -2 c -> -1 (This permits Python-style version strings such as "1.4b3".) """ version = [] accumulator = [] def flush(): if not accumulator: raise ValueError('Malformed version string: ' + repr(s)) version.append(int(''.join(accumulator))) accumulator.clear() for c in s: if c.isdigit(): accumulator.append(c) elif c == '.': flush() elif c in 'abc': flush() version.append('abc'.index(c) - 3) else: raise ValueError('Illegal character ' + repr(c) + ' in version string ' + repr(s)) flush() return tuple(version)
def layer_type(flags): """ Returns the layer type from the feature classification flag 0 = invalid (bad or missing data) 1 = "clear air" 2 = cloud 3 = aerosol 4 = stratospheric feature 5 = surface 6 = subsurface 7 = no signal (totally attenuated) """ # type flag : bits 1 to 3 return flags & 7
def generate(output, aid_to_ans): """ Return the answer given the Answer ID/label :param output: The answer label :param aid_to_ans: :return: """ ans = aid_to_ans[output] return ans
def improve_answer_span(doc_tokens, input_start, input_end, tokenizer, orig_answer_text): """Returns tokenized answer spans that better match the annotated answer. The SQuAD annotations are character based. We first project them to whitespace-tokenized words. But then after WordPiece tokenization, we can often find a "better match". For example: Question: What year was John Smith born? Context: The leader was John Smith (1895-1943). Answer: 1895 The original whitespace-tokenized answer will be "(1895-1943).". However after tokenization, our tokens will be "( 1895 - 1943 ) .". So we can match the exact answer, 1895. However, this is not always possible. Consider the following: Question: What country is the top exporter of electornics? Context: The Japanese electronics industry is the lagest in the world. Answer: Japan In this case, the annotator chose "Japan" as a character sub-span of the word "Japanese". Since our WordPiece tokenizer does not split "Japanese", we just use "Japanese" as the annotation. This is fairly rare in SQuAD, but does happen. Parameters ---------- doc_tokens: list A list of doc tokens input_start: int start position of the answer input_end: int end position of the answer tokenizer: callable function orig_answer_text: str origin answer text. Returns ------- tuple: a tuple of improved start position and end position """ tok_answer_text = ' '.join(tokenizer(orig_answer_text)) for new_start in range(input_start, input_end + 1): for new_end in range(input_end, new_start - 1, -1): text_span = ' '.join(doc_tokens[new_start:(new_end + 1)]) if text_span == tok_answer_text: return (new_start, new_end) return (input_start, input_end)
def cidr_to_common(cidr_mask): """Function that returns a common mask (Ex: 255.255.255.0) for a given input CIDR mask (Ex: 24)""" cidrtocommon = { 1: "128.0.0.0", 2: "192.0.0.0", 3: "224.0.0.0", 4: "240.0.0.0", 5: "248.0.0.0", 6: "252.0.0.0", 7: "254.0.0.0", 8: "255.0.0.0", 9: "255.128.0.0", 10: "255.192.0.0", 11: "255.224.0.0", 12: "255.240.0.0", 13: "255.248.0.0", 14: "255.252.0.0", 15: "255.254.0.0", 16: "255.255.0.0", 17: "255.255.128.0", 18: "255.255.192.0", 19: "255.255.224.0", 20: "255.255.240.0", 21: "255.255.248.0", 22: "255.255.252.0", 23: "255.255.254.0", 24: "255.255.255.0", 25: "255.255.255.128", 26: "255.255.255.192", 27: "255.255.255.224", 28: "255.255.255.240", 29: "255.255.255.248", 30: "255.255.255.252", 31: "255.255.255.254", 32: "255.255.255.255", } if int(cidr_mask) >= 0 and int(cidr_mask) <= 32: return cidrtocommon[int(cidr_mask)] else: raise ValueError("Incorrect CIDR mask entered")
def _parse_versions_json_field(line): """Parses a line like '"key": "value",' into a key and value pair.""" if line.endswith(","): line = line[:-1] k, sep, v = line.partition('": "') if not sep or not k.startswith('"') or not v.endswith('"'): return "", "" return k[1:], v[:-1]
def generate_gateway_url(project, gateway): """ Format the resource name as a resource URI. """ return 'projects/{}/global/gateways/{}'.format(project, gateway)
def is_ambiguous_align(tags, multi_align_tag): """Returns whether the read aligns to multiple locations. The multi_align_tag depends on mapper. For bowtie2 it is XS.""" for t in tags: if t[0] == multi_align_tag: return True return False
def normalize_index(i): """Ensure 0 <= i < 2.""" return max(0, min(2, i))
def get_qualified_name(obj): """Retrieve the full module path of an object. Example: .. code-block:: python from watson.http.messages import Request request = Request() name = get_qualified_name(request) # watson.http.messages.Request """ try: name = obj.__qualname__ except AttributeError: try: name = obj.__class__.__name__ except Exception: # pragma: no cover name = obj.__name__ # pragma: no cover try: module = obj.__module__ return '{0}.{1}'.format(module, name) except Exception: # pragma: no cover return name
def response_with_headers(headers, code=200): """ Content-Type: text/html Set-Cookie: user=gua """ header = 'HTTP/1.x {} VERY OK\r\n'.format(code) header += ''.join([ '{}: {}\r\n'.format(k, v) for k, v in headers.items() ]) return header
def parse_int(value, fallback=0): """ Convert a string number to integer """ if value is None: return fallback try: return int(value) except ValueError: return fallback
def adjust_ifs(content): """ Adds ':' after ')' """ for n,line in enumerate(content): count = 0 if line.strip().startswith('IF'): i = line.find('(') if i >= 0: count = 1 for k in range(i,len(line)): #print(k, line[k]) if line[k] == '#': break if line[k] == ')': count = 0 if k==len(line)-1 : content[n] = line[:k+1] + ':' + line[k+1:] elif line[k+1] != ':': content[n] = line[:k+1] + ':\n' + line[k+1:] break else: count = 0 i = line.find('#') if i >= 0: content[n] = line[:i] + ':' + line[i:] else: content[n] = line + ':' else: if count > 0: i = 0 for k in range(i,len(line)): if line[k] == '#': break if line[k] == ')': count = 0 content[n] = line[:k+1] + ':' + line[k+1:] break return content
def attack(p, k, a1, f, x, y): """ Recovers the shared secret if the coefficients are generated deterministically, and a single share is given. :param p: the prime used for Shamir's secret sharing :param k: the amount of shares needed to unlock the secret :param a1: the first coefficient of the polynomial :param f: a function which takes a coefficient and returns the next coefficient in the polynomial :param x: the x coordinate of the given share :param y: the y coordinate of the given share :return: the shared secret """ s = y a = a1 for i in range(1, k): s -= a * x ** i a = f(a) return s % p
def invertIntervalList(inputList, maxValue=None): """ Inverts the segments of a list of intervals e.g. [(0,1), (4,5), (7,10)] -> [(1,4), (5,7)] """ inputList = sorted(inputList) # Special case -- empty lists if len(inputList) == 0 and maxValue is not None: invList = [ (0, maxValue), ] else: # Insert in a garbage head and tail value for the purpose # of inverting, in the range does not start and end at the # smallest and largest values if inputList[0][0] != 0: inputList.insert(0, ["", 0]) if maxValue is not None and inputList[-1][1] < maxValue: inputList.append((maxValue, "")) invList = [ [inputList[i][1], inputList[i + 1][0]] for i in range(0, len(inputList) - 1) ] return invList
def get_labeled_spans(prop): """ :param prop: 1D: n_words; elem=bracket label :return: 1D: n_words; elem=BIO label """ def _concat_c_spans(_spans): labels = [_span[0] for _span in _spans] c_indices = [i for i, _span in enumerate(_spans) if _span[0].startswith('C')] non_ant_c_spans = [] for c_index in c_indices: c_span = _spans[c_index] _label = c_span[0][2:] if _label in labels: _spans[labels.index(_label)].extend(c_span[1:]) else: non_ant_c_spans.append([_label] + c_span[1:]) concated_spans = [span for i, span in enumerate(_spans) if i not in c_indices] _spans = concated_spans + non_ant_c_spans return _spans labeled_spans = [] labeled_span = [] for i, arg in enumerate(prop): if arg.startswith('('): if arg.endswith(')'): label = arg.split("*")[0][1:] labeled_span = [label, i, i] else: label = arg[1:-1] labeled_span = [label, i] elif arg.endswith(')'): labeled_span.append(i) if len(labeled_span) == 3 and labeled_span[0] != "V" and labeled_span[0] != "C-V": labeled_spans.append(labeled_span) labeled_span = [] labeled_spans = _concat_c_spans(labeled_spans) return labeled_spans
def is_pod_type(type_name): """ Those are types for which no class should be generated. """ return type_name in [ "Nil", "void", "bool", "real_t", "float", "double", "int", "int8_t", "uint8_t", "int16_t", "uint16_t", "int32_t", "int64_t", "uint32_t", "uint64_t", ]
def pad(string): """ Decongest statements """ padded = string.replace("\r", "").replace("\t", " ") symbols = ["#", "%", "*", ")", "+", "-", "=", "{", "}", "]", "\"", "'", "<", ">" ] for item in symbols: padded = padded.replace(item, f" {item} ") return padded.replace("(", "( ")
def file_finder(filepath): """ Takes a filepath (str) and exracts: (1) its path, (2) its name, and (3) its extension. This metadata is filtered into a dictionary. For example, the filepath 'folder/directory/repository/file_name.txt' would return: File path: 'folder/directory/repository/' File name: 'file_name' File extention: '.txt' :param: filepath: string of a filepath (from current working directory) :returns: dictionary with orginal filepath as well as sorted metadata """ prefix = "" file_name = "" file_ext = "" furthest_dir_index = 0 extention_index = 0 if "/" in filepath: index_ls = [] for index,char in enumerate(filepath): if char == "/": index_ls.append(index) furthest_dir_index = max(index_ls) path = filepath[:(furthest_dir_index + 1)] if "." in filepath: for i,c in enumerate(filepath): if c == ".": extention_index = i file_ext = filepath[extention_index:] file_name = filepath[(furthest_dir_index + 1):(extention_index)] else: file_name = filepath[furthest_dir_index:] dictionary = {"full_path": filepath, "file_name": file_name, "prefix": prefix, "extention" : file_ext} return(dictionary)
def get_object_type(objects: list, types: list) -> list: """Get the object specified. Args: objects: a list of objects. types: a list of the types. Returns: A list of a certain type. """ return [item for item in objects if item.get('type') in types]
def pipe(arg, *args): """ Pipe """ last_result = arg for combinator in args: last_result = combinator(last_result) if last_result is None: return None return last_result
def format_boolean(value): """Return value as boolean.""" return_value = None if value is not None: return_value = value return return_value
def svm_grid(): """ Return grid for RandomSearchCV for the SVM classifier :return: dictionary """ C = [0.1, 1, 10, 100] kernel = ['linear', 'poly', 'rbf', 'sigmoid'] degree = [2, 3, 4, 5, 6, 7, 8] coef0 = [0.1, 1, 10, 100] gamma = ['scale', 'auto'] shrinking = [True, False] probability = [True, False] grid = {'C': C, 'kernel': kernel, 'degree': degree, 'coef0': coef0, 'gamma': gamma, 'shrinking': shrinking, 'probability': probability} return grid
def recursive_max(items): """O(n).""" if len(items) == 1: return items[0] prev_max = recursive_max(items[1:]) return prev_max if prev_max > items[0] else items[0]
def rotate(string, bits): """ Given that all our words are stored as strings, using slice notation is the easiest way to perform rotations. :param string: :param bits: :return: """ rf = string[0: len(string) - bits] rs = string[len(string) - bits:] return rs + rf
def PlmIndex(l, m): """ Compute the index of a array of Legendre functions corresponding to degree l and angular order m. Usage ----- index = PlmIndex (l, m) Returns ------- index : integer, ndarray Index of an array of associated Legendre functions corresponding to degree l and angular order m. Parameters ---------- l : integer, array_like The spherical harmonic degree. m : integer, array_like The angular order. Notes ----- PlmIndex will calculate the index of an array of associated Legendre functions corresponding to degree l and angular order m. The input arrays are generated by routines such as PlmBar, PlmBar_d1, PlmSchmidt, PlmSchmidt_d1, PlmON, PlmON_d1, PLegendreA, and PLegendreA_d1. The array index in Python is equal to l * (l + 1) / 2 + m. """ return (l * (l + 1)) // 2 + m
def _Join(*args): """Join parts of a gs:// Cloud Storage or local file:// path.""" # URIs always uses '/' as separator, regardless of local platform. return '/'.join([arg.strip('/') for arg in args])
def obj_type(key): """If it is a 'dir' it will end with a slash otherwise it is a 'file' """ if key[-1:] == '/': return 'directory' else: return 'file'
def watch(name, timespec, tag=None, user=None, job=None, unique_tag=False): """ .. versionadded:: 2017.7.0 Add an at job if trigger by watch job : string Command to run. timespec : string The 'timespec' follows the format documented in the at(1) manpage. tag : string Make a tag for the job. user : string The user to run the at job .. versionadded:: 2014.1.4 unique_tag : boolean If set to True job will not be added if a job with the tag exists. .. versionadded:: 2017.7.0 .. code-block:: yaml minion_restart: at.watch: - job: 'salt-call --local service.restart salt-minion' - timespec: 'now +1 min' - tag: minion_restart - unique_tag: trye - watch: - file: /etc/salt/minion """ return {"name": name, "changes": {}, "result": True, "comment": ""}
def get_policy_published(reportee, policy, **kw): """Return "policy_published" part for a passed `reportee` and `policy`. For now we use the hardcoded values for `adkim`, `aspf` and `pct` everywhere. """ return { "domain": reportee, "adkim": "r", "aspf": "r", "p": policy, "sp": policy, "pct": 100 }