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def clear_tables(data): """ Function clears table if rows are not valid (dasen't hold jumper data). :param data: raw data from the pdf tables :return: cleared raw data """ table_raw_content_list = [] # clean rows for pdfs with tables data_to_skip = ['Jury', 'RACE', 'Club', 'Rank', 'Name', 'Fini', 'not ', 'Disq', 'Code', 'PRAG', 'NOC ', 'Not ', 'TIME', 'WIND', 'Fina', 'GATE', 'No. D', 'Comp', 'Worl', 'FIS ', 'Hill'] data_to_skip = list(x.lower() for x in data_to_skip) for lines in data: for line in lines: for row in line: if row[0] is None: continue if row[0][0:4].lower() in data_to_skip: continue if row[0] in ['Weather Information', 'Statistics', '1st Round', 'Did Not Start', 'Qualification']: break if row[0][0:18] == 'Technical Delegate': break if row[0][0:4] in ['Note', 'NOTE']: break # DSQ row if row[0] == '1st Round': continue if row[0] == '' or row[0].split()[0] in ['DNS', 'DSQ']: continue if 'SCE' in row or 'ICR' in row[2] or 'SCE' in row[2]: continue table_raw_content_list.append(row) return table_raw_content_list
def get_total_price_of_items(pizzas, kebabs, drinks): """Calculates and returns the total price of items provided. arguments: pizzas - list of pizzas kebabs - list of kebabs drinks - list of drinks """ total = 0.0 for p in pizzas: total += float(p.price_without_dollar_sign()) for k in kebabs: total += float(k.price_without_dollar_sign()) for d in drinks: total += float(d.price_without_dollar_sign()) return total
def format_status(items, symbol_success='success', symbol_failed='failed'): """Format the status field of pipeline jobs.""" result = {} for name, content in items.items(): result[name] = content if content['status'] == 'success': result[name]['status'] = symbol_success if content['status'] == 'failed': result[name]['status'] = symbol_failed return result
def e_s(msg): """Return a string, with reserved characters escaped""" msg = msg.replace(".", "\\.") msg = msg.replace("=", "\\=") msg = msg.replace("-", "\\-") msg = msg.replace("(", "\\(") msg = msg.replace(")", "\\)") msg = msg.replace("]", "\\]") msg = msg.replace("!", "\\!") return msg
def curies_runtime(base): """ base is .e.g https://api.blackfynn.io/datasets/{dataset_id}/ """ return { 'local': base, 'contributor': base + 'contributors/', 'subject': base + 'subjects/', 'sample': base + 'samples/', }
def mean(data): """Compute the mean of the provided data.""" n = len(data) try: return [float(sum(l))/len(l) for l in zip(*data)] except TypeError: return sum(data)/n
def get_link_type(link: str) -> str: """ Analyzes the given link and returns the type of download type required. (track for individual song, album for an album URL and playlist if given a the Spotify link of a playlist). """ # a spotify link is in the form of: open.spotify.com/<type>/<id> # we only need the type part link_type = link.split("/") return link_type[len(link_type) - 2]
def discrete_uniform_expval(lower, upper): """ Expected value of discrete_uniform distribution. """ return (upper - lower) / 2.
def is_set(object): """Check the given object is a set""" return isinstance(object, set)
def clean_exchanges(data): """Make sure all exchange inputs are tuples, not lists.""" def tupleize(value): for exc in value.get("exchanges", []): exc["input"] = tuple(exc["input"]) return value return {key: tupleize(value) for key, value in data.items()}
def text_to_title(value): """when a title is required, generate one from the value""" title = None if not value: return title words = value.split(" ") keep_words = [] for word in words: if word.endswith(".") or word.endswith(":"): keep_words.append(word) if len(word) > 1 and "<italic>" not in word and "<i>" not in word: break else: keep_words.append(word) if len(keep_words) > 0: title = " ".join(keep_words) if title.split(" ")[-1] != "spp.": title = title.rstrip(" .:") return title
def billions(x, pos): """The two args are the value and tick position.""" return '${:1.0f}B'.format(x*1e-9)
def get_identifier(recipe): """Return identifier from recipe dict. Tries the Identifier top-level key and falls back to the legacy key location.""" try: return recipe["Identifier"] except (KeyError, AttributeError): try: return recipe["Input"]["IDENTIFIER"] except (KeyError, AttributeError): return None except TypeError: return None
def to_solution(parameters, columns): """Convert a solution given as a list pairs of column indices and values to a solution given as a list of pairs of columns and values.""" return [(parameters.columns[column_id], value) for column_id, value in columns]
def map_schema(line, schema): """ cleans the message msg, leaving only the fields given by schema, and casts the appropriate types returns None if unable to parse :type line : str message to parse :type schema: dict schema that contains the fields to filter :rtype : dict message in the format {"field": value} """ try: msg = line.split(schema["DELIMITER"]) msg = {key:eval("%s(\"%s\")" % (schema["FIELDS"][key]["type"], msg[schema["FIELDS"][key]["index"]])) for key in schema["FIELDS"].keys()} except: return return msg
def text_to_sentences(text, terminators = (".", "?", "!", '."', '?"', '!"'), exclude = ("Mr.", "Ms.", "Mrs.", "Dr.", "e.g.", "i.e.")): """ Break text into a list of sentences. This is a highly imperfect function that takes a passage of text and breaks it into a list of sentences. The main stumbling block for the function is that there are numerous words that could indicate either the end of a sentence or the end of an abbreviation. I do not know of an effective solution to this problem. NB: The assumption is made that line breaks always denote the end of a sentence, regardless of the preceding character. Parameters: text: the passage to break into sentences. Keyword Parameters: terminators: strings that denote the end of a sentence. exclude: exceptions to the terminators. Returns: sentences: a list of sentences in text. """ sentences = [] text_as_paragraphs = text.split("\n") paragraphs_as_words = [] for paragraph in text_as_paragraphs: paragraph = paragraph.strip() if not paragraph: # This is a blank line. paragraphs_as_words.append([]) # Go to the next paragraph: continue words = paragraph.split(" ") paragraphs_as_words.append(words) for paragraph in paragraphs_as_words: if not paragraph: # This is a blank line. sentences.append("") continue sentence = "" for word in paragraph: # Add word to sentence, along with a leading space if necessary: if sentence: sentence = sentence+" "+word else: sentence = word # Check whether word ends with a terminator: try: ends_with_terminator = word.endswith(terminators) except TypeError: # terminators is probably a list rather than a tuple. # str.endswith() requires a tuple. terminators = tuple(terminators) ends_with_terminator = word.endswith(terminators) if ends_with_terminator and word not in exclude: # This ends the sentence. sentences.append(sentence) sentence = "" # Check for a dangling sentence: if sentence: sentences.append(sentence) return sentences
def div(numer, denom): """PFA division behavior: inf and -inf for a finite number divided by zero and nan for 0/0. Also ensures that return type of any two numbers (including integers) is floating point. :type numer: number :param numer: the numerator :type denom: number :param denom: the denominator :rtype: float :return: fraction, including non-numeric possibilities """ try: return numer / float(denom) except ZeroDivisionError: if numer > 0.0: return float("inf") elif numer < 0.0: return float("-inf") else: return float("nan")
def min_max_indexes(seq): """ Uses enumerate, max, and min to return the indices of the values in a list with the maximum and minimum value: """ l = sorted(enumerate(seq), key=lambda s: s[1]) return l[0][0], l[-1][0]
def _build_pure_transition_impl(settings, attr): """ Transition that enables pure, static build of Go binaries. """ return { "@io_bazel_rules_go//go/config:pure": True, "@io_bazel_rules_go//go/config:static": True, }
def av_good_mock(url, request): """ Mock for availability, best case. """ return {'status_code': 301, 'text': 'Light side'}
def upsample_kernel_size_solver( in_size, out_size, stride=1, padding=0, output_padding=0, dilation=1, ): """ Returns kernel size needed to upsample a tensor of some input size to a desired output size. The implementation solves for kernel size in the equation described the the "Shape" section of the pytorch docs: https://pytorch.org/docs/stable/generated/torch.nn.ConvTranspose1d.html """ x = out_size - 1 - output_padding - (in_size - 1) * stride + 2 * padding x = int(x / dilation + 1) return (x, )
def addr_to_text(mac_addr, big_endian=False, sep=""): """Convert a mac_addr in bytes to text.""" return sep.join(["{:02x}".format(b) for b in (mac_addr if big_endian else reversed(mac_addr))])
def get_core_identifier(cpu_identifier, sensor_identifier): """ a cpu has many sensors. some of them for cores. cores themselves don't have identifiers. thus, we use the identifier of the sensor to infer to which core it belongs. :param cpu_identifier: e.g. /intelcpu/0 :param sensor_identifier: e.g. /intelcpu/0/load/1 - i.e. the load sensor for core #1 of CPU #0. :return: a core identifier e.g. /intelcpu/0/1 """ core_number = sensor_identifier.split('/')[-1] return cpu_identifier + "/" + core_number
def parse_bool(value): """Attempt to parse a boolean value.""" if value in ("true", "True", "yes", "1", "on"): return True if value in ("false", "False", "None", "no", "0", "off"): return False return bool(int(value))
def convert_values_to_string(variables): """ Converts the values in the dictionary to the string type. :param variables: the variables dictionary :rtype: dict[str, object] :return: the variables dictionary with string values :rtype: dict[str, str] """ if not variables: return {} return dict((k, str(v)) for k, v in variables.items())
def chunk(arr:list, size:int=1) -> list: """ This function takes a list and divides it into sublists of size equal to size. Args: arr ( list ) : list to split size ( int, optional ) : chunk size. Defaults to 1 Return: list : A new list containing the chunks of the original Examples: >>> chunk([1, 2, 3, 4]) [[1], [2], [3], [4]] >>> chunk([1, 2, 3, 4], 2) [[1, 2], [3, 4]] >>> chunk([1, 2, 3, 4, 5, 6], 3) [[1, 2, 3], [4, 5, 6]] """ _arr = [] for i in range(0, len(arr), size): _arr.append(arr[i : i + size]) return _arr
def parseVectors(nodes): """ Parses a list of nodes (inputs, outputs, regs, wires, etc.) and encodes them based on whether they are a bus like [127:0]sk, or a single bit value like [1234] or 'a'. Args: nodes (list(string)): list of nodes to parse Returns: dict(string : int): dictionary encoding the inputted nodes """ visited = [] vectors = dict() for node in nodes: vec = node.split('~') if len(vec) == 1: visited.append(vec[0]) vectors[vec[0]] = 0 else: vName, vIdx, _ = vec if vName not in visited: visited.append(vName) vectors[vName] = int(vIdx) elif int(vIdx) > vectors[vName]: vectors[vName] = int(vIdx) return vectors
def score(word): """ Calculate score for a word """ result = 0 for char in word.upper(): if char in "AEIOULNRST": result += 1 elif char in "DG": result += 2 elif char in "BCMP": result += 3 elif char in "FHVWY": result += 4 elif char == "K": result += 5 elif char in "JX": result += 8 else: result += 10 return result
def get_symmetric_key(): """Returns symmetric key bytes 16 bytes that were randomly generated. Form a 128 bit key. """ symmetric_key = ( b'\x92\xcf\x1e\xd9\x54\xea\x30\x70\xd8\xc2\x48\xae\xc1\xc8\x72\xa3') return symmetric_key
def is_remove(list, object): """remove objects from a list using is equivalence instead of comparison equivalence""" result = [] for e in list: if object is not e: result.append(e) return result
def overlap(range1, range2): """ Checks whether two ranges (f.e. character offsets overlap) This snippet by Steven D'Aprano is from the forum of www.thescripts.com. Keyword arguments: range1 -- a tuple where range1[0] <= range1[1] range1 -- a tuple where range2[0] <= range2[1] Returns: True (ranges overlap) or False (no overlap) """ assert(range1[0] <= range1[1]), (range1, range2) assert(range2[0] <= range2[1]), (range1, range2) # Fully overlapping cases: # x1 <= y1 <= y2 <= x2 # y1 <= x1 <= x2 <= y2 # Partially overlapping cases: # x1 <= y1 <= x2 <= y2 # y1 <= x1 <= y2 <= x2 # Non-overlapping cases: # x1 <= x2 < y1 <= y2 # y1 <= y2 < x1 <= x2 return not (range1[1] <= range2[0] or range2[1] <= range1[0])
def build_history_object(metrics): """ Builds history object """ history = {"batchwise": {}, "epochwise": {}} for matrix in metrics: history["batchwise"][f"training_{matrix}"] = [] history["batchwise"][f"validation_{matrix}"] = [] history["epochwise"][f"training_{matrix}"] = [] history["epochwise"][f"validation_{matrix}"] = [] return history
def has_straight(h): """ Straight: All cards are consecutive values. return: (hand value, remaining cards) or None """ values = {value for value, _ in h} if len(values) == 5 and max(values) - min(values) == 4: return max(values), [] else: return None
def float_fraction(trainpct): """ Float bounded between 0.0 and 1.0 """ try: f = float(trainpct) except ValueError: raise Exception("Fraction must be a float") if f < 0.0 or f > 1.0: raise Exception("Argument should be a fraction! Must be <= 1.0 and >= 0.0") return f
def color_negative_red(val): """ Takes a scalar and returns a string with the css property `'color: red'` for negative strings, black otherwise. """ color = 'red' return 'color: %s' % color
def mapset(mapping, oldset): """ Applies a mapping to a set. Args: mapping: oldset (set): Returns: """ newset = set() for e in oldset: newset.add(mapping[e]) return newset
def _estimate_correlation_length(bins, averages): """Estimate the correlation length of a spatial velocity correlation function. The correlation length is typically defined as the radial distance at which the correlation first becomes zero. """ n_point = len(bins) for i in range(0, n_point-1): bottom = averages[i] top = averages[i+1] if bottom > 0.0 and top < 0.0: return (bins[i]+bins[i+1])/2.0 return None
def bound_ros_command(bounds, ros_pos, fail_out_of_range_goal, clip_ros_tolerance=1e-3): """Clip the command with clip_ros_tolerance, instead of invalidating it, if it is close enough to the valid ranges. """ if ros_pos < bounds[0]: if fail_out_of_range_goal: return bounds[0] if (bounds[0] - ros_pos) < clip_ros_tolerance else None else: return bounds[0] if ros_pos > bounds[1]: if fail_out_of_range_goal: return bounds[1] if (ros_pos - bounds[1]) < clip_ros_tolerance else None else: return bounds[1] return ros_pos
def percents_to_pixels(image_width, image_height, row_percent, col_percent, width_percent, height_percent): """ Convert from percents of image to pixel values Args: image_width: image_height: row_percent: col_percent: width_percent: height_percent: Returns: (int, int, int, int): row, col, height width in pixels. """ row = int(image_height * row_percent) col = int(image_width * col_percent) width = int(image_width * width_percent) height = int(image_height * height_percent) return row, col, height, width
def strip_position(pos): """ Stripes position from +- and blankspaces. """ pos = str(pos) return pos.strip(' +-').replace(' ', '')
def get_texture_declaration(texture): """Return the GLSL texture declaration.""" declaration = "uniform sampler%dD %s;\n" % (texture["ndim"], texture["name"]) return declaration
def add_trailing_slash(directory_path): """ Add trailing slash if one is not already present. Argument: directory_path -- path to which trailing slash should be confirmed. """ # Add trailing slash. if directory_path[-1] != '/': directory_path=str().join([directory_path, '/']) # Return directory_path with trailing slash. return directory_path
def h3(text): """Heading 3. Args: text (str): text to make heading 3. Returns: str: heading 3 text. """ return '### ' + text + '\r\n'
def change_key_in_dict(d, old_key, new_key): """Change the key of the entry in `d` with key `old_key` to `new_key`. If there is an existing entry Returns: The modified dict `d`. Raises: KeyError : If `old_key` is not in `d`. """ d[new_key] = d.pop(old_key) return d
def get_min_rooms(lectures): """ Given an array of start and end times for lectures, find the minimum number of classrooms necessary. """ starts = sorted(start for start, _ in lectures) ends = sorted(end for _, end in lectures) num_rooms = 0 current_overlap = 0 start_idx, end_idx = 0, 0 while start_idx < len(starts) and end_idx < len(ends): if starts[start_idx] < ends[end_idx]: current_overlap += 1 num_rooms = max(num_rooms, current_overlap) start_idx += 1 else: current_overlap -= 1 end_idx += 1 return num_rooms
def find_active_firmware(sector): """Returns a tuple of the active firmware's configuration""" for i in range(8): app_entry = sector[i * 32 : i * 32 + 32] config_flags = int.from_bytes(app_entry[0:4], "big") active = config_flags & 0b1 == 0b1 if not active: continue app_address = int.from_bytes(app_entry[4 : 4 + 4], "big") app_size = int.from_bytes(app_entry[8 : 8 + 4], "big") return app_address, app_size, i return None, None, None
def f_exists(fname): """ checks if a file exists :param fname: :return: """ try: with open(fname) as f: return True except IOError: return False
def shorten_name(name, max_length = 10): """ Makes a string shorter, leaving only certain quantity of the last characters, preceded by '...'. @param name: The string to shorten. @param max_length: Maximum length of the resulting string. @return: A string with max_lenght characters plus '...' """ if len(name) > max_length: return "..."+name[-max_length:] else: return name
def perlin_noise_1d(count, seed, octaves, bias): """ Return a noise 1d array """ perlin_noise = [0.0] * count for x in range(count): noise = 0.0 scale = 1.0 scale_accumulate = 0.0 for o in range(octaves): n_pitch = count >> o if n_pitch == 0: continue n_sample1 = (x / n_pitch) * n_pitch # this helps with tessellation n_sample2 = (n_sample1 + n_pitch) % count # return value between 0 and 1 blend = float(x - n_sample1) / float(n_pitch) sample = (1.0 - blend) * seed[ n_sample1] + blend * seed[n_sample2] noise += sample * scale # half the scale so the noise is less strong scale_accumulate += scale scale /= bias perlin_noise[x] = noise / scale_accumulate return perlin_noise
def multi_gpu_load_single_gpu_model(checkpoint): """ Use the single gpu trained model in multi gpus. """ new_state_dict = {} for k, v in checkpoint.items(): # remove prefix 'module'. name = 'module.' + k new_state_dict[name] = v # Use 'load_state_dict' to load parameters. return new_state_dict
def add_sequences(seq1: list, seq2: list): """ A function to add two sequences and return the result seq1: A list of integers seq2: A list of integers returns: seq1 + seq2 as a list """ if len(seq1) == len(seq2): return [x + y for x, y in zip(seq1, seq2)] elif len(seq1) == 0 or len(seq2) == 0: return [] else: smaller_length = len(seq1) if len(seq1) < len(seq2) else len(seq2) seq1 = seq1[0:smaller_length] seq2 = seq2[0:smaller_length] return [x + y for x, y in zip(seq1, seq2)]
def wrappable_range_overlaps(start, end, test, wrap_after=59, wrap_to=0, overlap=False ): """Figure out whether a range of numbers (specified by 'start' and 'end') has any overlap with the set of numbers in the set 'test'. The numbers in the range may wrap (e.g., the 60th minute wraps to the 0th or the 12th month wraps to the 1st); where the wrap occurs is governed by 'wrap_after' (default 59) and where it wraps is governed by 'wrap_to' (default 0). If 'overlap' is true, the start and end must simply overlap with the test set, otherwise it must be completely contained within it. """ if not isinstance(test, set): raise ValueError("Type of 'test' must be 'set'") if wrap_to >= wrap_after: raise ValueError("Unusuable wrap values.") if not ( (wrap_to <= start <= wrap_after) and (wrap_to <= end <= wrap_after) ): raise ValueError("Start and end must be in [%d..%d]" \ % (wrap_to, wrap_after)) ranges = [] if end >= start: ranges.extend(list(range(start, end+1))) else: ranges.extend(list(range(start, wrap_after+1))) ranges.extend(list(range(0, wrap_to+1))) ranges = set(ranges) return bool(test.intersection(ranges)) if overlap \ else ranges.issubset(test)
def check_lammps_sim(out_file, verbose=True): """ Check if LAMMPS simulation is finished. """ FINISHED = False try: with open(out_file, 'r') as f: lines = f.readlines() if 'Total wall time' in lines[-1]: FINISHED = True except Exception as e: if verbose: print(e) # print(lines[-1]) return FINISHED
def _tf(word_occured_in_doc: int, total_words_in_doc: int) -> float: """Term frequency of a word in certain document. See: https://bit.ly/3zEDkMn """ assert word_occured_in_doc <= total_words_in_doc return word_occured_in_doc / total_words_in_doc
def getid(obj): """Extracts object ID. Abstracts the common pattern of allowing both an object or an object's ID (UUID) as a parameter when dealing with relationships. """ try: return obj.id except AttributeError: return obj
def call_req(obj_name, method, params): """Construct message used when sending API calls to CtrlServer. :param obj_name: Name of API-exported system that owns the given method. :type obj_name: string :param method: API-exported method to call on the given object. :type method: string :param params: Params to pass to the given method. :type params: dict :returns: Constructed call_req dict, ready to be sent over the wire. """ return { "type": "call_req", "obj_name": obj_name, "method": method, "params": params }
def subtract(v1, v2): """ Subtracts v2 from v1. """ return [v1[0] - v2[0], v1[1] - v2[1], v1[2] - v2[2]]
def divide(intf, ints): """ overpython.divide(intf, ints) Divide intf by ints. Raises ValueError if intf/ints is a string. """ try: return float(intf) / float(ints) except ValueError: raise ValueError("%s/%s is not a number" % (intf, ints))
def parse_keqv_list(l): """Parse list of key=value strings where keys are not duplicated.""" parsed = {} for elt in l: k, v = elt.split('=', 1) if v[0] == '"' and v[-1] == '"': v = v[1:-1] parsed[k] = v return parsed
def dico_add(*dicos): """ dictionnaries addition, with (shallow) copy """ if len(dicos) == 0: return {} res = dicos[0].__class__() for dico in dicos: res.update(dico) return res
def hr_range_formatter(start, end, step): """Format a range (sequence) in a simple and human-readable format by specifying the range's starting number, ending number (inclusive), and step size. Parameters ---------- start, end, step : numeric Notes ----- If `start` and `end` are integers and `step` is 1, step size is omitted. The format does NOT follow Python's slicing syntax, in part because the interpretation is meant to differ; e.g., '0-10:2' includes both 0 and 10 with step size of 2 whereas 0:10:2 (slicing syntax) excludes 10 Numbers are converted to integers if they are equivalent for more compact display. Examples -------- >>> hr_range_formatter(start=0, end=10, step=1) '0-10' >>> hr_range_formatter(start=0, end=10, step=2) '0-10:2' >>> hr_range_formatter(start=0, end=3, step=8) '0-3:8' >>> hr_range_formatter(start=0.1, end=3.1, step=1.0) '0.1-3.1:1' """ if int(start) == start: start = int(start) if int(end) == end: end = int(end) if int(step) == step: step = int(step) if int(start) == start and int(end) == end and step == 1: return '{}-{}'.format(start, end) return '{}-{}:{}'.format(start, end, step)
def get_insert_many_query(table_name: str) -> str: """Build a SQL query to insert several RDF triples into a PostgreSQL table. Argument: Name of the SQL table in which the triples will be inserted. Returns: A prepared SQL query that can be executed with a list of tuples (subject, predicate, object). """ return f"INSERT INTO {table_name} (subject,predicate,object) VALUES %s"
def to_bytes(something, encoding='utf8'): """ cast string to bytes() like object, but for python2 support it's bytearray copy """ if isinstance(something, bytes): return something if isinstance(something, str): return something.encode(encoding) elif isinstance(something, bytearray): return bytes(something) else: raise TypeError("Not a string or bytes like object")
def frequencies(seq): """ Find number of occurrences of each value in seq >>> frequencies(['cat', 'cat', 'ox', 'pig', 'pig', 'cat']) #doctest: +SKIP {'cat': 3, 'ox': 1, 'pig': 2} See Also: countby groupby """ d = dict() for item in seq: try: d[item] += 1 except KeyError: d[item] = 1 return d
def cage_correlations_summing(target_species_hit, transcript_id, target_cages, tf_cages, cage_correlations_dict, cage_corr_weights_dict): """ Extract correlation values between CAGEs associated with a predicted TFBS protein, and CAGEs associated with the current gene. """ corr_weights_ls = [] corr_weight_sum = 0 # cages for all transcripts of the predicted TFBS's proteins tf_name = target_species_hit[0] for target_cage in target_cages: if target_cage in cage_correlations_dict: for tf_cage in tf_cages: if tf_cage in cage_correlations_dict[target_cage]: cage_correlation = cage_correlations_dict[target_cage][tf_cage] cage_corr_weight = cage_corr_weights_dict[abs(cage_correlation)] corr_weights_ls.append(cage_corr_weight) # take strongest correlation weight score if len(corr_weights_ls) > 0: corr_weights_ls.sort() corr_weight_sum = corr_weights_ls[-1] return corr_weight_sum
def func_extract_all_project_ids(project_version_mapping): """ :param project_version_mapping: :return: project id list """ ids = [] for _ in project_version_mapping.keys(): ids.append(_.id) return ids
def uniq_arr(arr): """Remove repeated values from an array and return new array.""" ret = [] for i in arr: if i not in ret: ret.append(i) return ret
def line_intersect(pt1, pt2, ptA, ptB): """ Taken from https://www.cs.hmc.edu/ACM/lectures/intersections.html Returns the intersection of Line(pt1,pt2) and Line(ptA,ptB). """ import math DET_TOLERANCE = 0.00000001 # the first line is pt1 + r*(pt2-pt1) # in component form: x1, y1 = pt1 x2, y2 = pt2 dx1 = x2 - x1 dy1 = y2 - y1 # the second line is ptA + s*(ptB-ptA) x, y = ptA xB, yB = ptB dx = xB - x dy = yB - y DET = -dx1 * dy + dy1 * dx if math.fabs(DET) < DET_TOLERANCE: return None # now, the determinant should be OK DETinv = 1.0 / DET # find the scalar amount along the "self" segment r = DETinv * (-dy * (x - x1) + dx * (y - y1)) # find the scalar amount along the input line s = DETinv * (-dy1 * (x - x1) + dx1 * (y - y1)) # return the average of the two descriptions xi = (x1 + r * dx1 + x + s * dx) / 2.0 yi = (y1 + r * dy1 + y + s * dy) / 2.0 if r >= 0 and 0 <= s <= 1: return xi, yi else: return None
def merge_dict_recursive(base, other): """Merges the *other* dict into the *base* dict. If any value in other is itself a dict and the base also has a dict for the same key, merge these sub-dicts (and so on, recursively). >>> base = {'a': 1, 'b': {'c': 3}} >>> other = {'x': 4, 'b': {'y': 5}} >>> want = {'a': 1, 'x': 4, 'b': {'c': 3, 'y': 5}} >>> got = merge_dict_recursive(base, other) >>> got == want True >>> base == want True """ for (key, value) in list(other.items()): if (isinstance(value, dict) and (key in base) and (isinstance(base[key], dict))): base[key] = merge_dict_recursive(base[key], value) else: base[key] = value return base
def tickets(people): """ Determines whether Vasya can sell a ticket to all people in the queue. :param people: an array integers ranging from numbers 25, 50, and 100. :return: YES, if Vasya can sell a ticket to every person and give change with the bills he has at hand at that moment. Otherwise return NO. """ a,b = 0, 0 for x in range(len(people)): if people[x] == 25: a += 1 elif people[x] == 50 and a > 0: a -= 1 b += 1 elif people[x] == 100 and a > 0 and b > 0: a -= 1 b -= 1 elif people[x] == 100 and a > 2: a -= 3 else: return "NO" return "YES"
def is_object(x): """Returns True if x has a __dict__ attribute. This function is intended to determine if its argument is an object in the "classic" sense--that is, one belonging to a type created by the "class" construct, and excluding such built-in types as int, str, and list, which are, strictly speaking, also objects in a general sense. This function also returns True if x is a class or module. """ return hasattr(x, "__dict__")
def cleanArrayForKey(lst): """ This method will clean out so that only the kh will contain 0,1,2,3,4,5,6,7 """ array = [] temp = [] for i, x in enumerate(lst): if x[1] == 0: temp = [i, x[1]] array.append(temp) elif x[1] == 1: temp = [i, x[1]] array.append(temp) elif x[1] == 2: temp = [i, x[1]] array.append(temp) elif x[1] == 3: temp = [i, x[1]] array.append(temp) elif x[1] == 4: temp = [i, x[1]] array.append(temp) elif x[1] == 5: temp = [i, x[1]] array.append(temp) elif x[1] == 6: temp = [i, x[1]] array.append(temp) elif x[1] == 7: temp = [i, x[1]] array.append(temp) return array
def _esc_var(name): """Returns a valid and unique Python identifier derived from name. Just returns name with the "_" appended. This is enough to ensure there's no collisions with any keyword or built-in or import. Args: name (string): The name to escape. Returns: string: A name which is a valid and unique Python identifier. """ return name + '_'
def normalise(val, minimum, maximum): """ Normalise a value between two values :param val: value to normalise :param minimum: minimum boundary :param maximum: maximum boundary :return: value between 0 and 1 """ return (val - minimum) / float(maximum - minimum)
def bubblesort(l): """ Runtime: O(n^2) """ last = len(l)-1 for i in range(last): for j in range(i+1, last): if l[i] > l[j]: l[i], l[j] = l[j], l[i] return l
def join_dots(*inputs): """['123', '456', '789'] -> '123.456.789'""" return '.'.join([item for item in inputs])
def wallis_product(n_terms): """Implement the Wallis product to compute an approximation of pi. See: https://en.wikipedia.org/wiki/Wallis_product XXX : write Parameters and Returns sections as above. """ # XXX : The n_terms is an int that corresponds to the number of # terms in the product. For example 10000. pi = 2 if n_terms > 0: for n in range(1, n_terms+1): pi *= (4*n**2)/(4*n**2 - 1) return pi
def format_datetime(datetime_): """Convert datetime object to something JSON-serializable.""" if datetime_ is None: return None return datetime_.strftime('%Y-%m-%dT%H:%M:%SZ')
def disbursal(from_acc, amount, from_pass, bank): """ Withdraws a desired amount of money from a user's account If a user's account is verified, using the account name and password, the desired amount of money is withdrawn from the user's account. :param from_acc: user's account number :param amount: user's desired amount of money :param from_pass: user's account password :param bank: dictionary consisting of all the bank-related data (mainly the clients' data) :return: if the user's account is verified, returns clients' data after the withdrawal has taken place, and otherwise, returns a string value of "Invalid Disbursal" """ clients_data = [] for client in bank["clients"]: clients_data.append(client) balance = client.get("balance") if client.get("account_number") == from_acc and float(balance) > amount and client.get( "password") == from_pass: name = client.get('name') password = client.get("password") acc_num = client.get("account_number") balance = str(float(balance) - amount) updated_cli = {"name": name, "password": password, "account_number": acc_num, "balance": balance} clients_data.remove(client) clients_data.append(updated_cli) return clients_data return "Invalid Disbursal"
def str2bool(x): """ Convert a string to a boolean. """ return x.lower() in ("true", "1")
def fill_space(s, i, j): """ Replace [i to j) slice in a string with empty space " "*len """ return s[:i] + " " * (j - i) + s[j:]
def make_spec(repos, slack_user_id, author_name): """ Format and return spec specifying what to analyze Convenience method: spec used by several other methods here Args: repos: list of repo names, which should have their logs jumped to json already in logs2hours/logs/git start_date: datetime start end_date: datetime end slack_user_id: id of desired user, not their name - str look in the dumps to find this author_name: git author name Returns: spec """ spec = { 'repos': repos, 'slack_uid': slack_user_id, 'author_name': author_name } return spec
def first_missing_positive_naive(a): """ O(n) time and O(n) space. """ n = len(a) flag = [False]*n for x in a: if x < 1 or x > n: continue flag[x-1] = True for i, f in enumerate(flag): if not f: return i+1
def init_actions_(service, args): """ this needs to returns an array of actions representing the depencies between actions. Looks at ACTION_DEPS in this module for an example of what is expected """ # some default logic for simple actions return { 'firstact': ['install'], 'secondact': ['install'], }
def djfrontend_h5bp_html(lang): """ Returns HTML tag according to chosen language. Included in HTML5 Boilerplate. """ output=[ '<!--[if lt IE 7]> <html class="no-js lt-ie9 lt-ie8 lt-ie7" lang="%s"> <![endif]-->' % lang, '<!--[if IE 7]> <html class="no-js lt-ie9 lt-ie8" lang="%s"> <![endif]-->' % lang, '<!--[if IE 8]> <html class="no-js lt-ie9" lang="%s"> <![endif]-->' % lang, '<!--[if gt IE 8]><!--> <html class="no-js" lang="%s"> <!--<![endif]-->' % lang, ] return '\n'.join(output)
def tslash(apath): """Add a trailing slash to a path if it needs one. Doesn't use os.sep because you end up jiggered on windoze - when you want separators for URLs. """ if (apath and apath != '.' and not apath.endswith('/') and not apath.endswith('\\')): return apath + '/' else: return apath
def escape_markdown(text: str): """ return text escaped given entity types :param text: text to escape :param entity_type: entities to escape :return: """ # de-escape and escape again to avoid double escaping return text.replace('\\*', '*').replace('\\`', '`').replace('\\_', '_')\ .replace('\\~', '~').replace('\\>', '>').replace('\\[', '[')\ .replace('\\]', ']').replace('\\(', '(').replace('\\)', ')')\ .replace('*', '\\*').replace('`', '\\`').replace('_', '\\_')\ .replace('~', '\\~').replace('>', '\\>').replace('[', '\\[')\ .replace(']', '\\]').replace('(', '\\(').replace(')', '\\)')
def guess_index_name(name: str) -> str: """Guess index name for a preferred name. Naive calculation of "Family Name, Given Name" """ return ', '.join(list(reversed(name.split(maxsplit=1))))
def decode_cigar(cigar): """Return a list of 2-tuples, integer count and operator char.""" count = "" answer = [] for letter in cigar: if letter.isdigit(): count += letter # string addition elif letter in "MIDNSHP=X": answer.append((int(count), letter)) count = "" else: raise ValueError("Invalid character %s in CIGAR %s" % (letter, cigar)) return answer
def removePrefix(str, prefix): """Removes prefix of str.""" return str[len(prefix):] if str.startswith(prefix) else str
def naive_2mm(p, t): """Return a naive string match allowing up to 2 mismatches.""" occurrences = [] for i in range(len(t) - len(p) + 1): # loop over alignments match = True mismatch = 0 for j in range(len(p)): # loop over characters if t[i+j] != p[j]: # compare characters mismatch += 1 # increment mismatch if mismatch > 2: # mismatches > 2 makes it a mismatch match = False break if match: occurrences.append(i) # all chars matched; record return occurrences
def basis_function_ders_one(degree, knot_vector, span, knot, order): """ Finds the derivative of one basis functions for a single knot. Implementation of Algorithm A2.5 from The NURBS Book by Piegl & Tiller. :param degree: degree :type degree: int :param knot_vector: knot_vector :type knot_vector: list, tuple :param span: span of the knot :type span: int :param knot: knot :type knot: float :param order: order of the derivative :type order: int :return: basis function derivatives values :rtype: list """ ders = [0.0 for _ in range(0, order + 1)] # Knot is outside of span range if (knot < knot_vector[span]) or (knot >= knot_vector[span + degree + 1]): for k in range(0, order + 1): ders[k] = 0.0 return ders N = [[0.0 for _ in range(0, degree + 1)] for _ in range(0, degree + 1)] # Initializing the zeroth degree basis functions for j in range(0, degree + 1): if knot_vector[span + j] <= knot < knot_vector[span + j + 1]: N[j][0] = 1.0 # Computing all basis functions values for all degrees inside the span for k in range(1, degree + 1): saved = 0.0 # Detecting zeros saves computations if N[0][k - 1] != 0.0: saved = ((knot - knot_vector[span]) * N[0][k - 1]) / (knot_vector[span + k] - knot_vector[span]) for j in range(0, degree - k + 1): Uleft = knot_vector[span + j + 1] Uright = knot_vector[span + j + k + 1] # Zero detection if N[j + 1][k - 1] == 0.0: N[j][k] = saved saved = 0.0 else: temp = N[j + 1][k - 1] / (Uright - Uleft) N[j][k] = saved + (Uright - knot) * temp saved = (knot - Uleft) * temp # The basis function value is the zeroth derivative ders[0] = N[0][degree] # Computing the basis functions derivatives for k in range(1, order + 1): # Buffer for computing the kth derivative ND = [0.0 for _ in range(0, k + 1)] # Basis functions values used for the derivative for j in range(0, k + 1): ND[j] = N[j][degree - k] # Computing derivatives used for the kth basis function derivative # Derivative order for the k-th basis function derivative for jj in range(1, k + 1): if ND[0] == 0.0: saved = 0.0 else: saved = ND[0] / (knot_vector[span + degree - k + jj] - knot_vector[span]) # Index of the Basis function derivatives for j in range(0, k - jj + 1): Uleft = knot_vector[span + j + 1] # Wrong in The NURBS Book: -k is missing. # The right expression is the same as for saved with the added j offset Uright = knot_vector[span + j + degree - k + jj + 1] if ND[j + 1] == 0.0: ND[j] = (degree - k + jj) * saved saved = 0.0 else: temp = ND[j + 1] / (Uright - Uleft) ND[j] = (degree - k + jj) * (saved - temp) saved = temp ders[k] = ND[0] return ders
def build_completed_questions_feedback(actor_name, quiz_name, course_name, score, feedback): """ Build the feedback when an user has completed the quiz and has failed the quiz. :param actor_name: Name of the user that has completed the quiz. :type actor_name: str :param quiz_name: Name of the quiz. :type quiz_name: str :param course_name: Name of the course. :type course_name: str :param score: Result of the user. :type score: str :param feedback: String with the feedback. :type feedback: str :return: String of the message. :rtype: str """ if feedback == '': return '' message = f'Hi {actor_name},\n You have completed the quiz "{quiz_name}" for the course "{course_name}". ' \ f'You did not answer every question correct. For information about the topics of the questions ' \ f'you answered wrong, please take a look at: {feedback}' return message
def italReplacements(tex): """ Replace the Latex command "\\textit{<argument>}" with just argument """ while (tex.find("\\textit{") != -1): beg = tex.find("\\textit{") sbrace = tex.find("{", beg) ebrace = tex.find("}", sbrace) tex = tex[:beg] + tex[sbrace+1:ebrace] \ + tex[ebrace+1:] return tex
def toFloat (str, default=None): """toFloat(str[, default]) -> float | default Converts the given string to a floating-point value. If the string could not be converted, default (None) is returned. NOTE: This method is *significantly* more effecient than toNumber() as it only attempts to parse floating-point numbers, not integers or hexadecimal numbers. Examples: >>> f = toFloat("4.2") >>> assert type(f) is float and f == 4.2 >>> f = toFloat("UNDEFINED", 999.9) >>> assert type(f) is float and f == 999.9 >>> f = toFloat("Foo") >>> assert f is None """ value = default try: value = float(str) except ValueError: pass return value
def nest_toc_tokens(toc_list): """Given an unsorted list with errors and skips, return a nested one. [{'level': 1}, {'level': 2}] => [{'level': 1, 'children': [{'level': 2, 'children': []}]}] A wrong list is also converted: [{'level': 2}, {'level': 1}] => [{'level': 2, 'children': []}, {'level': 1, 'children': []}] """ ordered_list = [] if len(toc_list): # Initialize everything by processing the first entry last = toc_list.pop(0) last['children'] = [] levels = [last['level']] ordered_list.append(last) parents = [] # Walk the rest nesting the entries properly while toc_list: t = toc_list.pop(0) current_level = t['level'] t['children'] = [] # Reduce depth if current level < last item's level if current_level < levels[-1]: # Pop last level since we know we are less than it levels.pop() # Pop parents and levels we are less than or equal to to_pop = 0 for p in reversed(parents): if current_level <= p['level']: to_pop += 1 else: # pragma: no cover break if to_pop: levels = levels[:-to_pop] parents = parents[:-to_pop] # Note current level as last levels.append(current_level) # Level is the same, so append to # the current parent (if available) if current_level == levels[-1]: (parents[-1]['children'] if parents else ordered_list).append(t) # Current level is > last item's level, # So make last item a parent and append current as child else: last['children'].append(t) parents.append(last) levels.append(current_level) last = t return ordered_list
def ordinal(n): """If n is a cardinal, ordinal function will return it's ordinality""" return "%d%s" % (n,"tsnrhtdd"[(n/10%10!=1)*(n%10<4)*n%10::4])
def argsparselist(txt): """ Validate a list of txt argument. :param txt: argument with comma separated int strings. :return: list of strings. """ txt = txt.split(",") listarg = [i.strip() for i in txt] return listarg
def tn_rate(TN, neg): """ Gets true positive rate. :param: TP: Number of true negatives :type TN: `int` :param: pos: Number of negative labels :type neg: `int` :return: true negative rate :rtype: `float` """ if neg == 0: return 0 else: return TN / neg
def possible_bipartition(dislikes): """ Will return True or False if the given graph can be bipartitioned without neighboring nodes put into the same partition. Time Complexity: O(n^2) Space Complexity: O(n) """ visited = [False] * len(dislikes) color = [-1] * len(dislikes) def dfs(v, c): visited[v] = True color[v] = c for u in dislikes[v]: if not visited[u]: dfs(u, 1 - c) for i in range(len(dislikes)): if not visited[i]: dfs(i, 0) for i in range(len(dislikes)): for j in dislikes[i]: if color[i] == color[j]: return False return True