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def find_largest_keys(root, k): """ Question 15.4: Find k largest keys in bst """ largest = [] stack = [] done = False while not done and len(largest) < k: if root: stack.append(root) root = root.right else: if len(stack): root = stack.pop() largest.insert(0, root.val) root = root.left else: done = True return largest
def GetFullPartitionSize(partition, metadata): """Get the size of the partition including metadata/reserved space in bytes. The partition only has to be bigger for raw NAND devices. Formula: - Add UBI per-block metadata (2 pages) if partition is UBI - Round up to erase block size - Add UBI per-partition metadata (4 blocks) if partition is UBI - Add reserved erase blocks """ erase_block_size = metadata.get('erase_block_size', 0) size = partition['bytes'] if erase_block_size == 0: return size # See "Flash space overhead" in # http://www.linux-mtd.infradead.org/doc/ubi.html # for overhead calculations. is_ubi = partition.get('format') == 'ubi' reserved_erase_blocks = partition.get('reserved_erase_blocks', 0) page_size = metadata.get('page_size', 0) if is_ubi: ubi_block_size = erase_block_size - 2 * page_size erase_blocks = (size + ubi_block_size - 1) // ubi_block_size size += erase_blocks * 2 * page_size erase_blocks = (size + erase_block_size - 1) // erase_block_size size = erase_blocks * erase_block_size if is_ubi: size += erase_block_size * 4 size += reserved_erase_blocks * erase_block_size return size
def calculate_iteration_count(total_recs, max_rec): """ Given the total number of records and the maximum records allowed in a granule, calculates the number of iterations required to traverse the entire array in chunks of size max_rec @param total_recs The total number of records @param max_rec The maximum number of records allowed in a granule """ cnt = total_recs / max_rec if total_recs % max_rec > 0: cnt += 1 return cnt
def check_name_in_string(name, string): """ Check whether the name string is a substring of another string (i.e. wikipedia title) """ return int(name.lower() in string)
def trapezoid_area(base_minor, base_major, height): """Returns the area of a trapezoid""" # You have to code here # REMEMBER: Tests first!!! return ((base_major+base_minor) / 2 ) * height
def calculate_receptive_field(kernel_size, n_layers, stride, dilations=[]): """ Given model parameters, calcualte the receptive field. Args: model (obj): model object. """ if len(dilations) == 0: dilations = [1 for n in range(n_layers)] receptive_field = kernel_size for n in range(n_layers): receptive_field += ((kernel_size-1)*stride)*dilations[n] return receptive_field
def _nullable_list_intersection(list_1, list_2): """ Returns the intersection of 2 nullable lists. Parameters ---------- list_1 : `None` or `list` of ``DiscordEntity`` First list. list_2 : `None` or `list` of ``DiscordEntity`` First list. Returns ------- intersection : `None` or `list` of ``DiscordEntity`` A list with the two list's intersection. """ if list_1 is None: return None if list_2 is None: return None intersection = set(list_1) & set(list_2) if not intersection: return None return list(intersection)
def insert_underscores(num: str) -> str: """Given a number, insert underscore every 3 digit after decimal dot """ # add underscore before . if "." in num: idx = num.index(".")-3 else: idx = len(num) - 3 while idx > 0: num = num[:idx] + "_" +num[idx:] idx -= 3 # add underscores after . if not "." in num: return num idx = num.index('.') + 4 if "e" in num: e_idx = len(num) - num.index('e') else: e_idx = 0 while idx < len(num) - e_idx: num = num[:idx] + "_" +num[idx:] idx += 3+1 return num
def label2string(labels): """ List of labels to a comma-saperated string. """ if labels is not None: for _i in labels: if "," in _i: raise ValueError( "The labels must not contain a comma as it is used " "as the separator for the different values.") labels = u",".join([_i.strip() for _i in labels]) return labels
def sanity_check(vars, cons): """ Check all variables participate in some constraint """ v_con = [] for c in cons: for x in cons[c]['scope']: if x not in v_con: v_con.append(x) for v in vars: if v not in v_con: return False return True
def find_first_slice_value(slices, key): """For a list of slices, get the first value for a certain key.""" for s in slices: if key in s and s[key] is not None: return s[key] return None
def onBoard(top, left=0): """Simplifies a lot of logic to tell if the coords are within the board""" return 0 <= top <= 9 and 0 <= left <= 9
def rax_clb_node_to_dict(obj): """Function to convert a CLB Node object to a dict""" if not obj: return {} node = obj.to_dict() node['id'] = obj.id node['weight'] = obj.weight return node
def make_airline_link(carrier_names): """Creates a string for an airline's website. >>> carrier_names = [] >>> make_airline_link(carrier_names) [] >>> carrier_names = [[u'Alaska', u'Airlines', u'Inc.'], [u'United', u'Airlines', u'', u'Inc.']] >>> make_airline_link(carrier_names) [u'alaskaairlines.com', u'unitedairlines.com'] >>> carrier_names = [[u'Alaska', u'Airlines', u'Inc.'], [u'Alaska', u'Airlines', u'Inc.'], [u'United', u'Airlines', u'', u'Inc.']] >>> make_airline_link(carrier_names) [u'alaskaairlines.com', u'alaskaairlines.com', u'unitedairlines.com'] """ airlines = [] for carrier_name in carrier_names: carrier_name = carrier_name[:2] airline_link = "" for word in carrier_name: airline_link = airline_link + word airlines.append(airline_link) airline_links = [] for airline in airlines: airline_link = (airline+".com").lower() airline_links.append(airline_link) return airline_links
def flatten(l): """Flattens list l. :type l: list :arg l: list to flatten :rtype: list :return: flattened list """ return [item for sublist in l for item in sublist]
def polarity(num): """ Returns the polarity of the given number. """ if num > 0: return 1 if num < 0: return -1 return 0
def seconds_to_datetime(seconds): """ Updates the information from seconds to 00:00:00 time :param seconds: :return: """ m, s = divmod(seconds, 60) h, m = divmod(m, 60) h, m, s = int(h), int(m), int(s) if h < 0: h = m = s = 0 if h < 10: h = "0" + str(h) else: h = str(h) if m < 10: m = "0" + str(m) else: m = str(m) if s < 10: s = "0" + str(s) else: s = str(s) return h, m, s
def get_localized_name(name): """Returns the localizedName from the name object""" locale = "{}_{}".format( name["preferredLocale"]["language"], name["preferredLocale"]["country"] ) return name['localized'].get(locale, '')
def l1_distance(x1, y1, x2, y2): """ Returns l1 (manhattan) distance.""" return abs(x1-x2) + abs(y1-y2)
def sign(x): """ Devuelve el signo de x (0 se interpreta con signo positivo) x>=0 --> +1 x <0 --> -1 """ if x<0: return -1 elif x>=0: return +1
def parse_unknown_options(args): """ Args: args: """ warning_message = 'Please provide args with a proper ' \ 'identifier as the key and the following structure: ' \ '--custom_argument="value"' assert all(a.startswith('--') for a in args), warning_message assert all(len(a.split('=')) == 2 for a in args), warning_message p_args = [a.lstrip('--').split('=') for a in args] assert all(k.isidentifier() for k, _ in p_args), warning_message r_args = {k: v for k, v in p_args} assert len(p_args) == len(r_args), 'Replicated arguments!' return r_args
def removeInvertedPaths(mpDict): """ Find the number of paths of this type joining the nodes in the sample :param mpDict: dict {str: [int, bool]}, key, str - name of the metapath value, [int, bool] - which matrix file to use, and whether to use the transpose (inverse path) :return: mpList, str list, ordered names of paths available, less paths that are mirror-images of another """ # The item to return mpList = list() # Check the keys in the dict for key in mpDict.keys(): # If the boolean is True, then the path is an # inverse of another; only append if false if mpDict[key][1] == False: mpList.append(key) # end loop mpList.sort() return mpList
def compose_remove_description(document: dict) -> str: """ Compose a change description for removing an OTU. :param document: the OTU document that is being removed :return: a change description """ name = document["name"] abbreviation = document.get("abbreviation") description = f"Removed {name}" if abbreviation: return f"{description} ({abbreviation})" return description
def is_valid_method_param(met): """ Checks if method is compatible with GROMACS """ methods = ['linkage', 'jarvis-patrick', 'monte-carlo', 'diagonalization', 'gromos'] return met in methods
def get_size_and_path(line): """From a 'ls -l' line, return columns 4 (size) and 8 (path).""" cols = line.split() size, path = (int(cols[4]), cols[8]) return size, path
def parse_coordinate(coordinate): """ Args: coordinate (str): Example: >>> parse_coordinate('chr1:153500000-153501000, chr1:153540000-153542000') ['chr1', 153500000, 153501000, 153540000, 153542000] Return: A list [chromosome] + [coordinate of four corners] """ try: pos1, pos2 = [elm.strip() for elm in coordinate.split(',')] pos1 = pos1.replace(':', '-') c1, p11, p12 = [elm.strip() for elm in pos1.split('-')] pos2 = pos2.replace(':', '-') c2, p21, p22 = [elm.strip() for elm in pos2.split('-')] p11, p12, p21, p22 = int(p11), int(p12), int(p21), int(p22) except: raise ValueError('Invalid coordinate string!') if c1 != c2: raise ValueError('Intrachromosomal contacts only!') if p22 - p11 > 200000: raise ValueError('Short-distance contacts (within 200 kb) only!') return [c1, p11, p12, p21, p22]
def _expand_prefix(all_names, prefix): """Expand the given prefix into real entity names. Args: all_names: A list of all entity names. prefix: A prefix string. Returns: A list of entity names that the pattern expands to. """ return [name for name in all_names if name.startswith(prefix)]
def miller_rabin(n): """ primality Test if n < 3,825,123,056,546,413,051, it is enough to test a = 2, 3, 5, 7, 11, 13, 17, 19, and 23. Complexity: O(log^3 n) """ if n == 2: return True if n <= 1 or not n&1: return False primes = [2, 3, 5, 7, 11, 13, 17, 19, 23] d = n - 1 s = 0 while not d&1: d >>= 1 s += 1 for prime in primes: if prime >= n: continue x = pow(prime, d, n) if x == 1: break for r in range(s): if x == n - 1: break if r + 1 == s: return False x = x * x % n return True
def parse_batch_parse_statement_forwarder_id_url(json): """ Extract the statement forwarder ids from a batch of statement forwarders. :param json: JSON text to parse. :type json: list(dict(str, dict(str, str))) :return: List of ids from statement forwarders. :rtype: list(dict(str, str)) """ forwarder_list = [] for forwarder in json: forwarder_list.append({ 'url': forwarder['configuration']['url'], 'id': forwarder['_id'] }) return forwarder_list
def checkPatch_index_inImages_naive(Index_check_patch,Num_patches_perImage,num_col,num_row): """check the index of patches and the size of images""" aaa = int(Index_check_patch/Num_patches_perImage) nn = Index_check_patch%Num_patches_perImage bbb = int(nn/num_col) ccc = nn%num_col # aaa = np.where(reshaped_Index_Array==Index_check_patch) return aaa,bbb,ccc #this part cost too much time, it should be somehow changed to save more time
def searching(value, liste): """ filter the items that math the search term """ list1 = [] for item in liste: if value.lower() in item.lower(): list1.append(item) return list1
def str_int_dpid(str_dpid): """Return stringified int version, of int or hex DPID from YAML.""" str_dpid = str(str_dpid) if str_dpid.startswith('0x'): return str(int(str_dpid, 16)) else: return str(int(str_dpid))
def underscore_join( strlis ): """Uses an underscore to join a list of strings into a long string.""" return '_'.join( [s for s in strlis if s is not None and len(s)>0] )
def return_calibration_type(model_name): """ Returns metadata for the calibration dataset for specified model Parameters ---------- model: string String of model name. Returns ------- dict Metadata on the dataset. A dict is returned with parameters CO2, H2O, or mixed set to True or False. True indicates that experiments where performed using that fluid type. For example, a model may be able to calculate mixed H2O-CO2 solubilities, but it's dataset may be made up only of pure-CO2 and pure-H2O data. In this case, a model's metadata would be {'CO2': True, 'H2O': True, 'Mixed': False}. This value expresses whether experiments used to parameterized models are pure-CO2, pure-H2O, or mixed H2O-CO2 experiments. In many cases, pure-CO2 experiments cannot be distinguished from mixed H2O-CO2 experiments, in which case the experiments are classified as 'Mixed'. """ if model_name == 'AllisonCarbon': return {'CO2': False, 'H2O': False, 'Mixed': True} if model_name == 'Dixon': return {'CO2': True, 'H2O': True, 'Mixed': False} if model_name == 'DixonCarbon': return {'CO2': True, 'H2O': False, 'Mixed': False} if model_name == 'DixonWater': return {'CO2': False, 'H2O': True, 'Mixed': False} if model_name == 'IaconoMarziano': return {'CO2': False, 'H2O': True, 'Mixed': True} if model_name == 'IaconoMarzianoCarbon': return {'CO2': False, 'H2O': False, 'Mixed': True} if model_name == 'IaconoMarzianoWater': return {'CO2': False, 'H2O': True, 'Mixed': False} if model_name == 'Liu': return {'CO2': False, 'H2O': True, 'Mixed': True} if model_name == 'LiuCarbon': return {'CO2': False, 'H2O': False, 'Mixed': True} if model_name == 'LiuWater': return {'CO2': False, 'H2O': True, 'Mixed': False} if model_name == 'MagmaSat': return{'CO2': True, 'H2O': True, 'Mixed': True} if model_name == 'MooreWater': return {'CO2': False, 'H2O': False, 'Mixed': True} if model_name == 'Shishkina': return {'CO2': False, 'H2O': True, 'Mixed': True} if model_name == 'ShishkinaCarbon': return {'CO2': False, 'H2O': False, 'Mixed': True} if model_name == 'ShishkinaWater': return {'CO2': False, 'H2O': True, 'Mixed': False}
def get_filter_constant(interval_distance, track_size): """Given a track size and distance, determine the minimum allowable split duration. """ # Determine constant of impossible time for 400m off of distance. if interval_distance <= 200: constant = 20 elif interval_distance > 200 and interval_distance <= 300: constant = 30 elif interval_distance > 300 and interval_distance <= 400: constant = 50 elif interval_distance > 400 and interval_distance <= 800: constant = 52 elif interval_distance > 800 and interval_distance <= 1200: constant = 55 elif interval_distance > 1200 and interval_distance <= 1600: constant = 58 else: constant = 59 # Modify constant if on different sized track like 300m or 200m. # (Don't modify if 200s on 200m track.) if interval_distance > 200: constant = constant * (track_size/400.0) return constant
def IsValidTimezone(timezone): """ Checks the validity of a timezone string value: - checks whether the timezone is in the pytz common_timezones list - assumes the timezone to be valid if the pytz module is not available """ try: import pytz return timezone in pytz.common_timezones except ImportError: # no pytz print("Timezone not checked " "(install pytz package for timezone validation)") return True
def type_error_message(func_name: str, expected: str, got: str) -> str: """Return an error message for function func_name returning type got, where the correct return type is expected.""" return ('{0} should return a {1}, but returned {2}' + '.').format(func_name, expected, got)
def excstr(e): """Return a string for the exception. The string will be in the format that Python normally outputs in interactive shells and such: <ExceptionName>: <message> AttributeError: 'object' object has no attribute 'bar' Neither str(e) nor repr(e) do that. """ if e is None: return None return '%s: %s' % (e.__class__.__name__, e)
def _check_geo_type_suffix(x): """ Checks if `geo_type` suffix contains an `int` """ try: return int(x) except: raise ValueError(f"`geo_type` suffix: '{x}' cannot be parsed as `int`.")
def build_jrn(**kwargs): """ Composes a journal file of journal blocks. :param kwargs: journal blocks :return: """ jrn_text = "\n".join(kwargs.values()) return jrn_text
def point_in_rectangle(point, rect_top_left, rect_sides): """ Checks if point is in rectangle Parameters ---------- point : (float, float) (x,y) coordinates of point rect_top_left : (float, float) (x,y) coordinates of rectangle top left corner rect_sides : (float, float) (x,y) lengths of rectangle sides Returns ------- bool True if point is in rectangle, otherwise False. """ return rect_top_left[0] < point[0] < rect_top_left[0] + rect_sides[0] and \ rect_top_left[1] < point[1] < rect_top_left[1] + rect_sides[1]
def f(x): """ Function x^3 - x -2 Example function. """ return x**3. - x - 2
def add(vec_1, vec_2): """ This function performs vector addition. This is a good place to play around with different collection types (list, tuple, set...), :param vec_1: a subscriptable collection of length 3 :param vec_2: a subscriptable collection of length 3 :return vec_3: a subscriptable collection of length 3 """ # add two vectors vec_3 = [float(vec_1[0]) + float(vec_2[0]), float(vec_1[1]) + float(vec_2[1]), float(vec_1[2]) + float(vec_2[2])] return vec_3
def _format_result(result): """Format result into string for templating.""" # do not include decimal if it's 100 if result == 100: return "100" return "{:.1f}".format(result)
def convert(list): """ Converts list to categories. """ categories = dict() for dict_row in list: try: categories[tuple(dict_row[0][0])][dict_row[1]].append(dict_row[2][0]) except KeyError: try: categories[tuple(dict_row[0][0])][dict_row[1]] = [dict_row[2][0]] except: categories[tuple(dict_row[0][0])] = {dict_row[1]: [dict_row[2][0]]} return categories
def fibonacci_comprehension(limit): """fibonacci sequence using a list comprehension.""" sequence = [0, 1] [sequence.append(sequence[i] + sequence[i-1]) for i in range(1, limit)] return sequence[-1]
def constant_increment_growth_rule(increment, level): """ The number of samples in the 1D quadrature rule where number of of points grow by a fixed constant at each level. Parameters ---------- level : integer The level of the quadrature rule Return ------ num_samples_1d : integer The number of samples in the quadrature rule """ if level == 1: return 3 return increment*level+1
def unwrap_hash( signals ): """ unwrap all signals in a hash array and return a copy """ # make a copy list_of_unwrapped_signals = signals.copy() # create a new list of signals for key, signal in list_of_unwrapped_signals.items(): list_of_unwrapped_signals[key] = signal.unwrap return list_of_unwrapped_signals
def prep_msg(msg): """ Prepare a string to be sent as a message """ msg += '\0' return msg.encode('utf-8')
def binarySearch(arr, val): """ array values must be sorted """ left = 0 right = len(arr) - 1 half = (left + right) // 2 while arr[half] != val: if val < arr[half]: right = half - 1 else: left = half + 1 half = (left + right) // 2 if arr[half] == val: return half return -1
def cles(lessers, greaters): """ # code from https://github.com/ajschumacher/cles # explanation from https://janhove.github.io/reporting/2016/11/16/common-language-effect-sizes the probability that a score sampled at random from one distribution will be greater than a score sampled from some other distribution. Common-Language Effect Size Probability that a random draw from `greater` is in fact greater than a random draw from `lesser`. Args: lesser, greater: Iterables of comparables. """ if len(lessers) == 0 and len(greaters) == 0: raise ValueError('At least one argument must be non-empty') # These values are a bit arbitrary, but make some sense. # (It might be appropriate to warn for these cases.) if len(lessers) == 0: return 1 if len(greaters) == 0: return 0 numerator = 0 # lessers, greaters = sorted(lessers), sorted(greaters) lesser_index = 0 for greater in greaters: while lesser_index < len(lessers) and lessers[lesser_index] < greater: lesser_index += 1 numerator += lesser_index # the count less than the greater denominator = len(lessers) * len(greaters) return float(numerator) / denominator
def length(tree): """ Count the total number of the tree nodes. :param tree: a tree node :return: the total of nodes in the subtree """ if tree: n_nodes = length(tree.left) n_nodes += length(tree.right) n_nodes += 1 return n_nodes return 0
def usi32_to_si32(val): """ Quick hack to read the signed val of an unsigned int (Image loads all ints from bytes as unsigned ints) :param val: :return: """ bits = 32 if (val & (1 << (bits - 1))) != 0: # if sign bit is set e.g., 8bit: 128-255 val = val - (1 << bits) # compute negative value return val # return positive value as is
def boundary_check(string, start_idx, end_idx): """ Check that given character indexes into given string align with token boundaries. """ start_clause = ( (start_idx == 0) or string[start_idx-1] in (" ", ",") ) end_clause = ( (end_idx == len(string)) or string[end_idx] in (" ", ",", ".") ) return (start_clause and end_clause)
def triangular2(cycle): """ triangular2 for cyclic LR. https://arxiv.org/abs/1506.01186 """ return 1.0 / (2.**(cycle - 1))
def build_search_query(query, page, per_page) -> dict: """ Build the multi-search query for Elasticsearch. :param str query: :param int page: :param int per_page: """ search_query = { "query": {"multi_match": {"query": query, "fields": ["*"]}}, "from": (page - 1) * per_page, "size": per_page, } return search_query
def encoding_description(encoding): """ Function to create a meaningful description that will be added as variable attribute into the netcdf file. Input: ------ encoding: dict Dictionary with the encoding specifications for each variable. """ labels = { 32001: "BLOSC", 32013: "ZFP", 32017: "SZ", } descriptions = {} for variable, var_encoding in encoding.items(): try: filter_id = var_encoding["compression"] filter_name = labels[filter_id] if filter_name == "BLOSC": compression_type = "Lossless" else: compression_type = "Lossy" description = "Compressed using %s (id:%i) - %s" % (filter_name, filter_id, compression_type) descriptions[variable] = description except KeyError: description = "Non compressed" descriptions[variable] = description return descriptions
def split_first_level(dependency): """ Internal function to split nested dependencies. :param dependency: :return: """ dependencies = [] beginning = 0 level = 0 for i in range(len(dependency)): if dependency[i] == ',' and level == 0: dependencies.append(dependency[beginning:i].strip()) beginning = i + 1 elif dependency[i] == '{': level += 1 elif dependency[i] == '}': level -= 1 dependencies.append(dependency[beginning:].strip()) return dependencies
def handle_status_update(loan_id, new_status): """Handles a status update for an order.""" # lookup order in your system using loan_id # set order status to new_status return ''
def sort_and_cut_by_cluster(row, N, fractions): """Pick the top N items from a cluster. This function returns the top N * fractions[cluster] items Args: row (rdd object): row has the form ((user, cluster), iterator_over((user, cluster, item, rating))) N (int): number of items desired in to be recommended in total fractions (dict): map of cluster to fraction of the total dataset that is represented by that cluster. Returns: list of tuples: The tuples have the form (user, rating, item) """ cluster = row[0][1] to_take = round(N * fractions[cluster]) content = ((user, rating, item) for (user, _, item, rating) in row[1]) output = [] i = 0 for tup in sorted(content, reverse=True): if i == to_take: return output output.append(tup) i += 1 return output
def add_auth_response(appreq=None, auth_obj=None): """Called after init_actingweb() if add_response was set to False, and now responses should be added.""" if not appreq or not auth_obj: return False appreq.response.set_status(auth_obj.response['code'], auth_obj.response['text']) if auth_obj.response['code'] == 302: appreq.redirect(auth_obj.redirect) elif auth_obj.response['code'] == 401: appreq.response.out.write("Authentication required") for h in auth_obj.response['headers']: appreq.response.headers[h["header"]] = h["value"] return True
def FWHMeff2FWHMgeom(FWHMeff): """ Convert FWHMeff to FWHMgeom. This conversion was calculated by Bo Xin and Zeljko Ivezic (and will be in an update on the LSE-40 and overview papers). Parameters ---------- FWHMeff: float the single-gaussian equivalent FWHM value, appropriate for calcNeff, in arcseconds Returns ------- float FWHM geom, the geometric FWHM value as measured from a typical PSF profile in arcseconds. """ FWHMgeom = 0.822*FWHMeff + 0.052 return FWHMgeom
def is_truthy(data): """ Returns True if the data is a truthy value, False otherwise. """ string = str(data).lower() return string in ['true', '1', 'f']
def n_tasks(dec_num): """ Takes a decimal number as input and returns the number of ones in the binary representation. This translates to the number of tasks being done by an organism with a phenotype represented as a decimal number. """ bitstring = "" try: bitstring = dec_num[2:] except: bitstring = bin(int(dec_num))[2:] # cut off 0b # print bin(int(dec_num)), bitstring return bitstring.count("1")
def check_if_elements_is_empty(json_object): """ Checks to see that there are elements in the json object :param json_object: :return: bool false if not empty, true if empty """ try: if len(json_object) > 0: is_empty = len(json_object['elements']) == 0 else: is_empty = True except KeyError: print("TypeError [" + str(TypeError) + " ]") return True return is_empty
def _configure_title_plotly(title, font_size, color="black"): """Helper function for plot_surf with plotly engine. This function configures the title if provided. """ if title is None: return dict() return {"text": title, "font": {"size": font_size, "color": color, }, "y": 0.96, "x": 0.5, "xanchor": "center", "yanchor": "top"}
def choices_to_list(choices): """Transforms choices dict to an ordered string list. Arguments: choices -- the dict containing available choices """ return list(map(str, sorted(choices.keys(), key=lambda v: v if type(v) == int else -1)))
def allocz(size): """Alloc zeros with range""" return [0 for _ in range(size)]
def _build_underline(data: str, md: bool = False, emoji: bool = False) -> str: """An internal function to return a rough estimate of an underline""" text_len = len(data) add = 3 if md and not emoji: add = 0 elif emoji and not md: add = 7 elif emoji and md: add = 1 return "\n" + "-" * (len(data) + add)
def complexns_core(strin): """ Improved conversion of string representation of complex numbers to float """ try: return complex(strin) except ValueError: pass # Do the simple fixes tmp = strin.replace(' ', '').replace('*','') tmp = tmp.lower().replace('i','j') try: return complex(strin) except ValueError: pass # Try to move 'j' to end loc = tmp.find('j') if loc: #tmp[1] = tmp[1][1:-1] + tmp[1][0] tmp = tmp[:loc] + tmp[(loc+1):] + 'j' return complex(tmp)
def gray_code(n): """Finds Gray Code of n!""" return n ^ (n >> 1)
def update_fluent_cached_urls(item, dry_run=False): """ Regenerate the cached URLs for an item's translations. This is a fiddly business: we use "hidden" methods instead of the public ones to avoid unnecessary and unwanted slug changes to ensure uniqueness, the logic for which doesn't work with our publishing. """ change_report = [] if hasattr(item, 'translations'): for translation in item.translations.all(): old_url = translation._cached_url item._update_cached_url(translation) change_report.append( (translation, '_cached_url', old_url, translation._cached_url)) if not dry_run: translation.save() if not dry_run: item._expire_url_caches() # Also process all the item's children, in case changes to this item # affect the URL that should be cached for the children. We process # only draft-or-published children, according to the item's status. if item.is_draft: children = [child for child in item.children.all() if child.is_draft] else: children = [child for child in item.get_draft().children.all() if child.is_published] for child in children: update_fluent_cached_urls(child, dry_run=dry_run) return change_report
def factorial(n): """ factorial: calculate factorial n! :param n: input number :return: n! """ fact=1 for i in range(1,n+1): fact*=i return fact
def split(formula): """ >>> split('CNNCB') ('CNN', 'NCB') >>> split('NNCB') ('NNC', 'CB') >>> split('NCB') ('NC', 'CB') """ left = formula[:len(formula) // 2 + 1] right = formula[len(left) - 1:] return left, right
def load_mapeval_runtimes(map_times_path): """ read the runtimes out of map_times.txt, assuming first line is a header """ try: map_times_dict = {} with open(map_times_path) as map_times_file: lines = [line for line in map_times_file] for line in lines[1:]: toks = line.split('\t') map_times_dict[toks[0]] = toks[1] return map_times_dict except: pass return None
def delimiter_check(line): """ Determines what delimiter is used in given text file. Parameters: -line: str line from text file Returns: -delim: str delimiter used in text file Notes: Recognizes only ",", "\t", and ":" delimiters. """ if ',' in line: delim = ',' elif '\t' in line: delim = '\t' elif ':' in line: delim = ':' else: raise ValueError('Unrecognized delimiter, use ",", "\t", or ":" instead.') return delim
def closestMatch(value, _set): """Returns an element of the set that is closest to the supplied value""" a = 0 element = _set[0] while(a<len(_set)): if((_set[a]-value)*(_set[a]-value)<(element-value)*(element-value)): element=_set[a] a = a + 1 return element
def p_value(y, l2): """ returns p-value for each response based on l2 :param y: The value for which the p-value is to be computed :param l2: The list of values on which the p-value calculation is based :return: The calculated p-value """ return (len([x for x in l2 if x >= y]) + 1) / (len(l2) + 1)
def draw_progressbar(value, total, width=40): """Visualize progess with a progress bar. :param value: The current progress as a fraction of total. :type value: int :param total: The maximum value that 'value' may obtain. :type total: int :param width: The character width of the drawn progress bar. :type width: int """ "Helper function for the visualization of progress." assert value >= 0 and total > 0 n = int(value / total * width) return '|' + ''.join(['#'] * n) + ''.join(['-'] * (width - n)) + '|'
def safe_compare(val1, val2): """ Compares two strings to each other. The time taken is independent of the number of characters that match. :param val1: First string for comparison. :type val1: :class:`str` :param val2: Second string for comparison. :type val2: :class:`str` :returns: :class:`bool` -- True if the two strings are equal, False otherwise. """ if len(val1) != len(val2): return False result = 0 for c1, c2 in zip(val1, val2): result |= ord(c1) ^ ord(c2) return result == 0
def color_match_threshold(pxl, ink, thresh): """ Returns True if both colors match, within threshhold """ diff = [0, 0, 0] diff[0] = abs(pxl[0] - ink[0]) diff[1] = abs(pxl[1] - ink[1]) diff[2] = abs(pxl[2] - ink[2]) #print diff if(diff[0]+diff[1]+diff[2]) <= thresh: return True return False
def stringListToFloat(stringList): """Converts a list with strings into a list with floats.""" return [float(singleFloatResult) for singleFloatResult in stringList]
def parse_struct_stat(stats): """Parse the structure of stats values in influencer data in order to return a pandas-compatible object. """ data = dict() for stat in stats: for item in stats[stat]: for metric in item['counts']: data.setdefault(metric, dict()) data[metric].update({ (stat, item['term']): item['counts'][metric] }) return data
def get_probes(probes): """Returns a list of probes""" probe_list = ['a', 'b', 'c', 'd', 'e'] thprobe_list = ['tha', 'thb', 'thc', 'thd', 'the'] ans_list = [] if not isinstance(probes, (list, tuple)): probes = [probes] for p in probes: p = p.lower() if p == '*': ans_list = thprobe_list break if p in probe_list: ans_list.append('th' + p) elif p in thprobe_list: ans_list.append(p) return ans_list
def lib_ext(shared): """Returns the appropriate library extension based on the shared flag""" return '.a' if not shared else '.so'
def observation(s, breaks, matrix, memo): """ Returns an observation using memoization, based on the parameter s. """ b = len(breaks) if b == 0 or s <= breaks[0]: return s * matrix[0] for i in range(1, b + 1): if i == b or s <= breaks[i]: j = (i - 1) * 2 return memo[j] + s * matrix[i] - memo[j + 1]
def rgb_to_hex(r: float, g: float, b: float) -> int: """Convert the color from RGB coordinates to hexadecimal.""" return int(r * 255) << 16 | int(g * 255) << 8 | int(b * 255)
def power_law_vband_norm(x, slope): """Power law normalised at 0.55 microns (V band).""" return (x / 0.55) ** slope
def format_float(value: float, precision: int = 4) -> str: """ Formats a float value to a specific precision. :param value: The float value to format. :param precision: The number of decimal places to use. :return: A string containing the formatted float. """ return f'{value:.{precision}f}'
def conv_if_neg(x): """returns abs of an angle if it's negative""" #sin(-x) = -sin(x) if x<0: return abs(x), True return x,False
def assemble_pair(label, value): """Assemble a 'pair' Celery Script node (for use as a body item).""" return { 'kind': 'pair', 'args': {'label': label, 'value': value}}
def remove_unused_samples(music): """ Remove samples that are never used Depends: to_mod_format """ # Get a list of samples actually referenced (each entry is unique) referenced_samples = [] for chan in music['mod']['channels']: for sample_idx in chan: if sample_idx not in referenced_samples: referenced_samples.append(sample_idx) # Remove samples not in the list for sample_idx in range(len(music['mod']['samples']) - 1, -1, -1): if sample_idx not in referenced_samples: # Actually remove from the samples list del music['mod']['samples'][sample_idx] # Update references to samples with a higher idx for chan in music['mod']['channels']: for chan_sample_num in range(len(chan)): assert chan[chan_sample_num] != sample_idx, 'found use of an unused sample' if chan[chan_sample_num] > sample_idx: chan[chan_sample_num] -= 1 # Note: no need to update referenced_samples as we iterate samples # in reverse we don't care about it referencing bad higher indexes pass return music
def list_results(query_results): """ keys :: [key] = all possible keys. (Not all results will contain all keys). results :: [dict] = list of results """ keys = query_results['head']['vars'] results = query_results['results']['bindings'] return keys, results
def get_qualified_name(names): """ ``get_qualified_name`` gets a qualified name for the provided name list. :param names: name list to qualify :type names: list(str) :return: a qualified name :rtype: str :Example: >>> type, name = demangle_ms(Architecture["x86_64"], "?testf@Foobar@@SA?AW4foo@1@W421@@Z") >>> get_qualified_name(name) 'Foobar::testf' >>> """ return "::".join(names)
def levenshtein_distance(s1, s2): """ The minimum amount of edits needed to make s2 into s1. Args: s1: string s2: string Returns: int """ if len(s1) > len(s2): s1, s2 = s2, s1 distances = range(len(s1) + 1) for index2, char2 in enumerate(s2): new_distances = [index2+1] for index1, char1 in enumerate(s1): if char1 == char2: new_distances.append(distances[index1]) else: new_distances.append( 1 + min( ( distances[index1], distances[index1+1], new_distances[-1] ) ) ) distances = new_distances distance = distances[-1] return distance
def filter_credit_score(credit_score, bank_list): """Filters the bank list by the mininim allowed credit score set by the bank. Args: credit_score (int): The applicant's credit score. bank_list (list of lists): The available bank loans. Returns: A list of qualifying bank loans. """ credit_score_approval_list = [] for bank in bank_list: if credit_score >= int(bank[4]): credit_score_approval_list.append(bank) return credit_score_approval_list
def deserialize_datetime(string): """Deserializes string to datetime. The string should be in iso8601 datetime format. :param string: str. :type string: str :return: datetime. :rtype: datetime """ try: from dateutil.parser import parse return parse(string) except ImportError: return string
def format_vault_encrypted_secret(vault_encrypted_secret): """ returns a prettier vault secret """ # Clean up spacing on the ansible vault line vault_encrypted_secret = vault_encrypted_secret.replace(" $ANSIBLE_VAULT", " $ANSIBLE_VAULT") return vault_encrypted_secret
def char_collect_all(s, c): """ Find all appearances of char in string :param s: haystack :param c: needle :return: list of indices """ start = 0 res = [] clen = len(c) while True: start = s.find(c, start) if start == -1: break res.append(start) start += clen return res
def task9(a: int) -> int: """ Function that computes the value of a+aa+aaa+aaaa with a given digit as the value of a Input: digit as integer Output: number as integer """ pierwsza = a druga = int(str(a)*2) trzecia = int(str(a) * 3) czwarta = int(str(a) * 4) wynik = pierwsza + druga + trzecia + czwarta return wynik