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def bivariate_histogram(xsample, ysample, reference_value_mean=None,\ reference_value_covariance=None, bins=None, matplotlib_function='imshow',\ xlabel='', ylabel='', title='', fontsize=28, ax=None, show=False,\ contour_confidence_levels=0.95, reference_color='r', reference_alpha=1,\ minima=None, maxima...
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def arrayToVec(array, arrType=carmcmcLib.vecD): """ Convert the input numpy array to a python wrapper of a C++ std::vector<double> object. """ vec = arrType() vec.extend(array) return vec
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import six def moma(model, reference=None, cache=None, reactions=None, *args, **kwargs): """ Minimization of Metabolic Adjustment[1] Parameters ---------- model: cobra.Model reference: FluxDistributionResult, dict cache: ProblemCache reactions: list Returns ------- FluxDi...
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def api_v2_url(path_str, params=None, base_route=settings.API_BASE_URL, **kwargs): """ Convenience function for APIv2 usage: Concatenates parts of the absolute API url based on arguments provided For example: given path_str = '/nodes/abcd3/contributors/' and par...
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import json def serialize_timingsession(session_pk, pk_offset=0): """Serialize all data associated with a timing session into JSON.""" session = TimingSession.objects.get(pk=session_pk) data_to_dump = [ [session], [session.coach], [session.coach.user], Split.objects.filter(...
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def send_via_mail_to(request): """ send email to list of freinds :param request: in the square represented by : west < longitude < east north < latitude < south """ idAlert = int(request.POST['id']) emails = request.POST['list'] text = request.POST['text'] lis...
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import glob import os import time def getdata(): """Returns a numpy array containing the most recently written EDA spectrum. Return None,None if the most recent file is older than MAXAGE seconds. NOTE - this will only work when run on 'bigdas', where live spectrum data is written to /tmp every seco...
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def get_tables_from_url(url, url_to_html='requests'): """Get's a list of pandas dataframes from tables scraped from a url. Note that this will only work with static pages. If the html needs to be rendered dynamically, you'll have to get your needed html otherwise (like with selenium). >>> url = 'https:...
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import random import math import tqdm import time def matrix_split(interaction_dataset, user_test_ratio=0.2, item_test_ratio=0.2, min_user_interactions=0, seed=0, max_concurrent_threads=4, **kwds): """Dataset split method that uses a matrix split strategy. More specifically, item_test_ratio items...
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import copy def Loadexc(casefile_dyn): """ Loads exciter data. @param casefile_dyn: m-file or struct with dynamic data @return: exciter parameter matrix @see: U{http://www.esat.kuleuven.be/electa/teaching/matdyn/} """ # Load data if isinstance(casefile_dyn, dict): exc = casefile_...
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def _num_requests_needed(num_repos, factor=2, wiggle_room=100): """ Helper function to estimate the minimum number of API requests needed """ return num_repos * factor + wiggle_room
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import re def linebreakshtml(value, autoescape=True): """ Replaces double line breaks in HTML to a paragraph break (``</p>``). This tag ignores single line breaks. """ autoescape = autoescape and not isinstance(value, SafeData) value = normalize_newlines(force_text(value)) if autoescape: ...
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def season(date, hemisphere, isleapyear): """ date is a datetime object hemisphere is either 'north' or 'south', dependent on long/lat. https://stackoverflow.com/questions/16139306/determine-season-given-timestamp-in-python-using-datetime """ if isleapyear: dd = date.day + 1 ...
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from typing import Generator def find_files(base_path: str, annotation_path: str or None = None) -> Generator[str, Annotation, None]: """Get each file and its proper annotation object. Parameters ---------- base_path : srt Base path of input files. annotation_path : str or None Pa...
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def request_course_creator(request): """ User has requested course creation access. """ user_requested_access(request.user) return render(request)
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def _generate_monthly_price_materialized_view_sql(): """ Generate the SQL used to generate the materialized view used by the last point view :return: """ return """ CREATE MATERIALIZED VIEW instancedata_monthly_price_mv ENGINE = SummingMergeTree PARTITION BY crawlMonth ...
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def number_constructors(): """A decorator for parametrized tests that test particular number operations. """ return pytest.mark.parametrize( "newobj", [ lambda: weakget(0), lambda: pep505(0), lambda: _weakget__nothing, # a singleton ], ids...
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import threading def approve_paper(request): """API approve_paper""" if not request.user.is_authenticated: return JsonResponse({'status': 'false'}, status=401) if request.method == 'POST': id = request.POST['id'] comment = request.POST['comment'] paper = get_object_or_404(...
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def dopamine_eval(runner, patient0, seed=100): """Evaluate an agent.""" base_env = runner._environment.environment # pylint: disable=protected-access initial_health_state = np.zeros_like( base_env.initial_params.initial_health_state) initial_health_state[patient0] = 1 base_env.set_initial_health_state...
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import torch def pad_data(data_list, fill=0): """ Pad tensors with fill-value such that list of variable shaped tensors can be stacked """ n_samples = len(data_list) #first determine longest time series: lengths = [x.shape[0] for x in data_list] max_len = max(lengths) output = fil...
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import json def market(request): """ Consulta a API procurando por informações sobre o mercado """ conn.request("GET", "/market/v2/get-summary?region=BR", headers=headers) res = conn.getresponse() data = res.read() summary = json.loads(data.decode("utf-8"))['marketSummaryAndSparkResponse'] ret...
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def setup_invalid_yaml(tmpdir): """Returns a list containing three Vector instances""" test_config_data = """ test: 1 test2: 1 """ default_dict = {'test': 'testing', 'test2': 'still testing'} test_cfg = tmpdir.mkdir("sub").join('test_config.yml') test_cfg.write(test_config_data) ...
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import torch def fuse_features(features1, features2, frame_batch_size=64, device='cuda'): """feature fusion""" video_length = features1.shape[0] frame_start = 0 frame_end = frame_start + frame_batch_size features = np.empty(shape=[0, 4096], dtype=np.float32) if video_length <= frame_batch_siz...
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def raHMS2deg(angle): """ EXAMPLE: Angle("10:42:44",unit=u.hourangle).deg """ return astropy.coordinates.Angle(angle,unit=u.hourangle).deg
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import os import uuid import json def generate(images, captions=dict(), outputdir='.', no_cache=False, stage_width=1080, stage_height=680, width=1200, height=800, thumbheight=50, disable_keyboard_nav=0, image_margin=0, toggleinfo=True, thumbnails=True, ...
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import os def rel(*x): """"Simple path helper""" abspath = os.path.abspath(main_file_location) BASE_DIR = os.path.dirname(abspath) return os.path.join(BASE_DIR, *x)
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def same_padding_for_kernel(shape, corr, strides_up=None): """Determine correct amount of padding for `same` convolution. To implement `'same'` convolutions, we first pad the image, and then perform a `'valid'` convolution or correlation. Given the kernel shape, this function determines the correct amount of p...
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import re def dedeidentify(text): """ MIMIC-specific :param text: The text to de-de-identify :return: """ return re.sub(r"\[\*\*.*\*\*\]", xxxx, text).lower()
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def embed_net_siam1(): """ This is a siamese type network to compare two patches. """ data1 = mx.sym.Variable("data1") data2 = mx.sym.Variable("data2") conv_weight = [] conv_bias = [] for i in range(3): conv_weight.append(mx.sym.Variable('conv' + str(i) + '_weight')) conv...
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import os def traced_graphql_wrapped( func, args, kwargs, span_kwargs=None, span_callback=None, ignore_exceptions=(), ): """ Wrapper for graphql.graphql function. """ # allow schemas their own tracer with fall-back to the global schema = args[0] tracer = getattr(schema,...
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def get_time_ms(frame, position): """Get time in ms and string based on the finishing position :param frame: A frame from AsyncVideoCapture / cv2.VideoCapture :type frame: numpy.ndarray :param position: Position 1-4 :type position: int :return: Time in milliseconds, time as string :rtype: (...
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def _extract_license_outliers(license_service_output): """Extract license outliers. This helper function extracts license outliers from the given output of license analysis REST service. :param license_service_output: output of license analysis REST service :return: list of license outlier package...
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def maxout(x, pool_size, axis=1): """Maxout activation function. It accepts an input tensor ``x``, reshapes the ``axis`` dimension (say the size being ``M * pool_size``) into two dimensions ``(M, pool_size)``, and takes maximum along the ``axis`` dimension. Args: x (:class:`~chainer.Variab...
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from tests.fpga_drivers import FpgaDriverBase from ctypes import c_uint32 def test_fpga_drivers_base(): """ Test accelize_drm.fpga_drivers.FpgaDriverBase. """ library = 'fpga_library.so' fpga_slot_id = 5 base_address = 0x10 fpga_image = 'fpga_image' class Fpga: """Fake FPGA""...
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from typing import Set def GetNumDistinctChromeVersions(db, build_config, start_date, end_date): """Get the number of distinct chrome versions. This represents the number of successful chrome uprevs. Args: db: cidb.CIDBConnection object. build_config: Name of build config of master builder. start_...
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def install_pip(): """ Install pip using apt-get install. """ #we need to upgrade pip package using pip itself return apt_get_install("python-pip") + pip_install("pip")
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import subprocess def runProcess(exe, working_dir): """ Function that opens a command line and runs a command. Captures the output and returns. Input: - exe: str, string of the command to be run. ! REMEMBER TO ESCAPE CHARS! - working_dir: str, directory where the cmd sh...
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import sys def get_os(): """ Determines the type of operating system being used. Needed for when we are loading & saving local files later Parameters ------------ none Returns ------------ os_type : str Type of OS the script is running on Ex: 'linux' is the scrip...
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def center(map, object): """ Center an ee.Image or ee.Feature on the map. Args: map: The map to center the object on. object: The ee.Image or ee.Feature to center. Returns: The provided map. """ coordinates = object.geometry().bounds().coordinates().getInfo()[0] ...
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from datetime import datetime def login_user(): """ Login user in api :return: token """ print('Login') auth = request.authorization # print(request.authorization) if not auth or not auth.username or not auth.password: return make_response('could not verify', 401, {'WWW.Authent...
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import warnings def normalized_diff(b1, b2): """Take two numpy arrays and calculate the normalized difference. Math will be calculated (b1-b2) / (b1+b2). Parameters ---------- b1, b2 : arrays with the same shape Math will be calculated (b1-b2) / (b1+b2). Returns ---------- n_...
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from sys import path def read_expected_result(test_name): """ :param test_name: :return: """ data_file_path = path.join( get_test_data_prefix(test_name), "Result.xlsx" ) return pd.read_excel( data_file_path, sheet_name=None )
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import tkinter as tk from tkinter import filedialog def get_json_file_path(): """Opens dialog box for user to choose where to save the measurements. Uses default directory in case of failure. Requires very hacky work-around of installing tk and tcl in NX directories""" try: root = tk.Tk(...
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import shlex def parse_config_string(config_string, issue_warnings=True): """ Parses a config string (comma-separated key=value components) into a dict. """ config_dict = {} my_splitter = shlex.shlex(config_string, posix=True) my_splitter.whitespace = "," my_splitter.whitespace_split = Tru...
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import os def dump_sections(path, bank_size=0x4000, initial_bank=0, last_bank=None, separator="\n\n"): """ Returns a str of assembly source code. The source code delineates each SECTION and includes bytes from the file specified by baserom. """ if not last_bank: last_bank = calculate_bank_...
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def load_data_clf(ds_name): """ Load the data for classification by the specified dataset name. Parameters ---------- ds_name : str Returns ------- data : DataFrame """ ds_load_func = None if ds_name in DS_LOAD_FUNC_CLF.keys(): ds_load_func = DS_LOAD_FUNC_CLF[ds_na...
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def parse_file_name(file_name): """ <Purpose> Parses a file name to identify its module and its descriptor <Arguments> file_name: the name of the test file <Exceptions> InvalidTestFileError: if you provide a test file which does not follow the naming convention of 'ut_<module>_<descriptor>...
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def _proto_builder_test_impl(ctx): """The implementation of the 'proto_builder_test' rule. Tests the files generated by the 'proto_builder' rule. The test performs a textual comparison of the generated source and header with the expected source and header respectively. Args: ctx: The current...
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def _make_nxm_w (*args, **kw): """ Make a simple wildcarded NXM entry class """ t = _fix_types(kw.pop('type', _nxm_maskable_numeric_entry)) ok = False for tt in t: if _issubclass(tt, _nxm_maskable): ok = True break if not ok: t.insert(0, _nxm_maskable) return _make_nxm(*args, type=t...
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def process_datasets(dataset_class, dataset_args, unc_model, device, test_fn=test_unc_model, N=1000, **forward_kwargs): """ calls test_fn(unc_model, dataset) for every dataset in datasets """ results = {} for name in dataset_args: print("Testing", name) print(N) dataset = dat...
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def accuracy_metric(actual, predicted, correct=0) -> float: """calculate accuracy of the dataset comparing the actual test label vs the predicted label""" for i in range(len(actual)): if actual[i] == predicted[i]: correct += 1 return correct / len(actual) * 100.0
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from typing import Any import copy def get_test_case( data: pd.DataFrame, model: Any, key: str, add: ARITHEMETIC_OPERATIONS = None, multiply: ARITHEMETIC_OPERATIONS = None, ) -> SCORES: """ Helper method to create the different test cases that alter the keys in a dictionary """ ...
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def realign_mol(mol,conf,coord_Map, alg_Map, mol_template, maxsteps): # RAUL: This function requires a clear separation between minimization and alignment. """ Minimizes and aligns the molecule provided freezing the atoms that match the mol_template. Parameters ---------- mol : rdkit.Chem.Mol...
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def measure_shadow_work(simulation, n_steps): """Run the simulation for n_steps and return a vector of the shadow work accumulated during integration. * Check whether simulation.integrator has bookkeeping variables W_shad and/or heat. * If only W_shad is available, measure shadow work as W_shad * I...
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def cumulative_cross_corr(I1, I2): """ doing normalized cross correlation on distance imagery :param I1: NP.ARRAY (_,_) binary array :param I2: NP.ARRAY (_,_) binary array :return result: NP.ARRAY (_,_) similarity surface ...
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def getGbdbTables(database, tableset): """ Remove tables that aren't pointers to Gbdb files.""" sep = "','" tablestr = sep.join(tableset) tablestr = "'" + tablestr + "'" hgsqlOut = qaUtils.callHgsql(database, "select table_name from information_schema.columns where\ ...
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def four_bar_plane_truss(num_samples: int = 100, distribution: str = "lhs") -> list: """Four bar plane truss problem. As found in Multiobjective structural optimization using a microgenetic algorithm. Parameters ---------- x : list or ndarray Should have 4 elements Returns ------- ...
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def parseFile (pomFile): """ Parses a pom.xml file and returns a Maven object or None """ with open (pomFile, 'rb') as f: return parseString (f.read()) return None
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def register_error_handlers(a=app): """Register error handlers.""" # @see https://blog.miguelgrinberg.com/post/the-flask-mega-tutorial-part-vii-error-handling @a.errorhandler(500) def handle_internal(error): db.session.rollback() flash(_('Error: %s') % error, 'error') return rend...
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def evaluations_to_columns(evaluation): """Convert the results of :meth:`metrics.ScoringMixIn.evaluate` to a pandas DataFrame-ready format Parameters ---------- evaluation: dict of OrderedDicts The result of consecutive calls to :meth:`metrics.ScoringMixIn.evaluate` for all given dataset types ...
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import abc import functools def get_metric(name: str, **kwargs) -> abc.Callable: """Returns metric function for given metric name Parameters ---------- name : str Metric name kwargs : any Additional keyword-arguments for metric Returns ------- metric : callable ...
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def resource_exists(env, resource): """Checks for resource existence without actually instantiating a model. :return: `True` if the resource exists, `False` if it doesn't and `None` in case no conclusion could be made (i.e. when `IResourceManager.resource_exists` is not ...
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def run_dqmc(p, unequal_time=True, callback=None, progress=False, *args, **kwargs): """Runs a DQMC simulation. Parameters ---------- p : Parameters The input parameters of the DQMC simulation. unequal_time : bool If `True`, unequal-time measurements will be performed. callback :...
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def merge(left: list, right: list) -> list: """Merges 2 sorted lists (left and right) in 1 single list, which is returned at the end. Time complexity: O(m), where m = len(left) + len(right).""" mid = [] i = 0 # Used to index the left list. j = 0 # Used to index the right list. while i < ...
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def replace(i_list: list, target: int,new_value: int)-> list: """ Replace all the target value with a new value :param i_list: the list to be analyzed :param value: the value to replace :param target: the value to be replaced :return: the new list """ return list(map(lambda value: new_va...
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def single(request, id, template_name="microblogging/single.html"): """ A single tweet. """ tweet = get_object_or_404(Tweet, id=id) return render_to_response(template_name, { "tweet": tweet, }, context_instance=RequestContext(request))
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def generate_responses(prompt, pipeline, seed=None, debug=False, **kwargs): """Generate responses using a text generation pipeline.""" if seed is not None: set_seed(seed) outputs = pipeline(prompt, **kwargs) responses = list(map(lambda x: clean_text(x['generated_text'][len(prompt):]), outputs))...
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import warnings def astropy_tabular_data(*args, **kwargs): """ Build a data set from a table. We restrict ourselves to tables with 1D columns. All arguments are passed to astropy.table.Table.read(...). """ result = Data() with warnings.catch_warnings(): warnings.simplefi...
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def words_cmp(a, b): """ word比较器 :param a: (word, 词频) :param b: (word, 词频) :return: [-1|0|1] """ a_word, a_freq = a b_word, b_freq = b if a_freq != b_freq: return b_freq - a_freq elif a_word != b_word: return -1 if a_word < b_word else 1 else: return 0
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def _load_data(args): """Load data from path.""" if args.data_format == 'CULANE': return vega.dataset("AutoLaneDataset", dataset_format="CULane", data_path=args.data_path, mode="test", batch_size=args.batch_size).loader elif args.data_format == 'COCO': return ...
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def extract_u_nk(xvg, T): """Return reduced potentials `u_nk` from a Hamiltonian differences XVG file. Parameters ---------- xvg : str Path to XVG file to extract data from. T : float Temperature in Kelvin the simulations sampled. Returns ------- u_nk : DataFrame ...
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def group(query, fields=None, step=None): """Group results by `fields` and/or `step`.""" if fields is None: fields = [] if isinstance(fields, string_types): fields = [fields] fields = ['"%s"' % f for f in fields] if step: fields.insert(0, 'time(%s)' % step) return '%s GRO...
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def first_level_directory(path): """Return the first level directory of a path. >>> first_level_directory('home/syt/work') 'home' >>> first_level_directory('/home/syt/work') '/' >>> first_level_directory('work') 'work' >>> :type path: str :param path: the path for which we want...
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def get_plugin_option(name, options): """ Retrieve option name from options dict. :param options: :return: """ for o in options: if o.get('name') == name: return o['value']
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def run_cc(hf): """ Run and return a restricted CCSD calculation on mol, with HF molecular orbital coefficients in the RHF object hf. """ if type(hf) == SCF_TYPES['RHF']: calc_cls = cc.CCSD elif type(hf) == SCF_TYPES['UHF']: calc_cls = cc.UCCSD else: raise NotImplemen...
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def contains( name, value, count_lt=None, count_lte=None, count_eq=None, count_gte=None, count_gt=None, count_ne=None, ): """ Only succeed if the value in the given register location contains the given value USAGE: .. code-block:: yaml foo: check....
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async def top_salty(): """ ### Returns top 10 saltiest user - Takes `/top_salty` ### Response `id` - userid `username` - username `saltiness` - saltiness `salty_description` = salty description """ QUERY = "SELECT * FROM users ORDER BY saltiness limit 10" pg_conn=db_conec...
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from datetime import datetime def thai_strftime( datetime: datetime.datetime, fmt: str, thaidigit: bool = False ) -> str: """ Convert :class:`datetime.datetime` into Thai date and time format. The formatting directives are similar to :func:`datatime.strrftime`. This function uses Thai names and ...
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def dot_product(t1, t2, keep_dims=False, name=None, reduction_dim=None): """Computes the dot product of t1 and t2. Args: t1: A rank 2 tensor. t2: A tensor that is the same size as t1. keep_dims: If true, reduction does not change the rank of the input. name: Optional name for this op. reduction...
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def assert_boolean(raw_val): """ Assert that the value is boolean. :return The value if it is boolean, otherwise raise an exception """ return assert_type(raw_val, bool)
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def classic_vs_bayesian_normal(mu, sigma, num_points, prior): """ Compute both classical and Bayesian inference processes over the range of data sample sizes (num_points) for a normal distribution with parameters mu,sigma for comparison. Args: mu (scalar): the mean parameter of the normal distribution ...
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def get_canonical_synonym(key): """Returns canonical synonym for key, else just key. """ if key == 'SAMPLE': return MELTED_SCHEMA_KEY__ES_LABEL return key
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import torch def get_batch_pipe(data, neox_args): """A modification of get_batch() to work with the latest batch instead of an iterator.""" # Items and their type. keys = ["text"] datatype = torch.int64 tokens, labels, loss_mask, attention_mask, position_ids = _get_batch( neox_args, neox_...
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def compute_precision(output, target, topk=(1,)): """Computes the precision@k for the specified values of k""" maxk = max(topk) batch_size = target.size(0) _, pred = output.topk(k=maxk, dim=1, largest=True, sorted=True) pred = pred.t() correct = pred.eq(target.view(1, -1).expand_as(pred)) ...
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import torch def get_landmark_model(output_size) -> torch.nn.Module: """Build the convolutional network model with Keras Functional API. Args: output_size: the number of output node, usually equals to the number of marks times 2 (in 2d space). Returns: a model """ model = torch.n...
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def isPerfectSquare(p: int) -> bool: """Checks if given number is a perfect square. A perfect square is an integer that is a square of another integer. Parameters: p: int number to check Returns: result: bool True if number is a perfect square F...
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def frequencies_for_cutoffs(col, cutoffs): """ Sets cutoffs for the frequencies """ # Sets each frequency to 0 by default freqs = [0] * len(cutoffs) for el in col: for i in range(len(cutoffs)): if el <= cutoffs[i]: freqs[i] += 1 break return freqs
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def find(user_id, session): """ Find all the history. :param user_id: history user_id :param session: session :return: history data. """ result = [] fetch = session.query(KMHistory) for history in fetch.filter_by(user_id=user_id).all(): result.append(history) return resul...
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import socket def fetch(url, data='', agent=None, referrer=None, charset=None, verbose=0, cookiejar={}, type=None, method=None, accept_language=None): """Make an HTTP or HTTPS request. If 'data' is given, do a POST; otherwise do a GET. If 'agent', 'referrer' and/or 'accept_language' are given,...
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import json def emolument_new_view(request): """ Add new emolument """ # Check authorization if not Utils.has_permission(request, request.registry.settings['affaire_facture_edition']): raise exc.HTTPForbidden() params = request.params data = json.loads(params['data']) emolumen...
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def display(auth_context): """ View function for displaying the checkout page. Parameters: auth_context (dict): The authentication context of request. See middlewares/auth.py for more information. Output: Rendered HTML page. """ products = [] # Pre...
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def golden_ratio(n): """returns the Golden Ratio to an accuracy of `n` decimal places Examples -------- >>> print(golden_ratio(20)) 1.61803398874989484820 >>> print(golden_ratio(50)) 1.61803398874989484820458683436563811772030917980576 """ x = _sym.symbols('x') gr = [sol for sol...
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from datetime import datetime import aiohttp import async_timeout async def _is_new_version_available() -> bool: """Return `True` if a newer archive of the repo at http://github.com/zwave-js/node-zwave-js is available.""" file_updated_at = _load_db_from_file().get(UPDATED_AT) if file_updated_at is None: ...
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def totalbp(file): """Count total number of sequenced base pairs""" with open(file, 'r') as Infile: loci = '' Count = 0 Loci_count = 0 start = False for line in Infile: #count first locus if Loci_count == 0: ...
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import mysensors.mysensors as mysensors import socket def setup(hass, config): """Setup the MySensors component.""" version = config[DOMAIN].get(CONF_VERSION) persistence = config[DOMAIN].get(CONF_PERSISTENCE) def setup_gateway(device, persistence_file, baud_rate, tcp_port, in_prefix, ...
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def oppositeFunction(basef): """ the opposite of a function """ if isinstance(basef, FitnessEvaluator): if isinstance(basef, FunctionEnvironment): ''' added by JPQ ''' if isinstance(basef, MultiObjectiveFunction): res = MultiObjectiveFunction() else: ...
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import os def _state(base, kwargs): """Gets version and package_data. Writes MANIFEST.in. Args: base (dict): our base params Returns: dict: base updated """ state = {} sha = '\n' if not 'version' in kwargs: state['version'], s = _version(base) if s: ...
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def cell(n): """Format a cell""" return '{:3} {:5}'.format( n, 'SPACE' if n == 32 else 'DEL' if n == 127 else chr(n) if n >= 33 else 'NA')
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def shape_arrays_for_pcolor_plotting(ps, indexing_list_indep_vars, ordered_params, dep_var_mgf): """ """ X = ps.get_mgf_arr(ordered_params[0].name)[ tuple(indexing_list_indep_vars)] Y = ps.get_mgf_arr(ordered_params[1].name)[ tuple(indexing_list_indep_vars)] Z = None if (np.shape(d...
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def adoytoymd(year, doy, hour=0, min=0, sec=0): """adoytoymd(year, doy, hour, min, sec) -> string Convert an array time with a day-of-year to a year-month-day time string. The hour, minute and second parameters are optional. All input parameters must be of type int.""" # # validate input values # ...
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