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def columns_not_changed(df, col_to_keep): """ insert the clean columns as features without changing the columns :param df: dataframe :param col_to_keep: columns that are clean and should not be changed :return unchanged columns plus SK_ID_CURR """ df = df.loc[:, ['SK_ID_CURR'] + col_to_ke...
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def removeRestaurantFromList(update: Update, context: CallbackContext) -> int: """Removes the current restaurant from the current preferred list.""" query = update.callback_query query.answer() # Removing the restaurant from the list in the database removeRestaurantFromListDb( context.chat_...
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def _process_null(_): """ Placeholder for an efficient replacement for when no columns of a `WaveformReducer` are activated. """ return dict()
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def GenerateRst(proto_file): """Generate a RST representation from a FileDescriptor proto.""" source_code_info = SourceCodeInfo(proto_file.name, proto_file.source_code_info) # Find the earliest detached comment, attribute it to file level. # Also extract file level titles if any. header, comment = FormatHeade...
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def make_padded_batch(items): """ Pads sequences in a batch, so they are all the same length as the longest. """ max_len = max(len(d["input_ids"]) for d in items) if max_len == 0: return {k: torch.zeros((0, 0), dtype=torch.long) for k in items[0]} return { k: pad_sequence([d[k] f...
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def hlmlEventSetCreate() -> hlml_t.HLML_EVENT_SET.TYPE: """ Create an empty set of events Parameters: None. Returns: st (HLML_EVENT_SET) - An empty set of events. """ global _hlmlOBJ st = hlml_t.HLML_EVENT_SET.TYPE fn = _hlmlOBJ.get_func_ptr("hlml_event_set_create") ...
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def is_ip_addr(value): """ Check that the supplied value is an Internet Protocol address, v.4, represented by a dotted-quad string, i.e. '1.2.3.4'. >>> vtor.check('ip_addr', '1 ') '1' >>> vtor.check('ip_addr', ' 1.2') '1.2' >>> vtor.check('ip_addr', ' 1.2.3 ') '1.2.3' >>> vt...
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async def do_work(number): """ # 此方法在调用时不会立即被执行,而是返回一个协程对象 :param number: :return: """ print('Number:', number)
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def batchEuclid (features, patterns, knowledge): """ Classifies whole dataset via euclidean distance. Returns score. """ dists = euclidean_distances (knowledge, features) preds = np.array (dists).argmin (axis = 0) truthVector = (preds.T.astype (float) == patterns) pos = truthVector.sum () ...
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def upload_plans_for_template(request): """ Allow user to upload a csv file to create plans based on a previously selected template """ ctxd = {} context = RequestContext(request, ctxd) return render_to_response("rundb/plan/modal_batch_planning_upload.html", context_instance=context)
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def calculate_total_correlativity(coefficient_array): """ Returns the total correlativity of the coefficient_array. The total correlativity is the sum of the absolute values and a measure of how correlated to timeseries are. The greater the value the more correlated.""" return sum(map(abs, coefficient...
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def merge_by_name(out_file_name, in_file_names): """ Merge name-sorted bam files into bam file sorted by name""" args = ['samtools', 'merge', '-n', out_file_name] args.extend(in_file_names) log_subprocess.check_call(args)
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def test_execute_command(): """ Execute "SELECT 1;" Assert: A result of 1 is returned """ cur = create_connection(host=host, port=port, user=usr, password=paswd, db=db) assert type(cur) == pymysql.cursors.Cursor stmt = "SELECT 1" result = execute_command(cur, stmt) assert r...
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def mosmix_example(): """Retrieve Mosmix mosmix data by DWD.""" # A. MOSMIX-L -- Specific stations_result - each station with own file Settings.tidy = True Settings.humanize = True request = DwdMosmixRequest( parameter=["DD", "ww"], start_issue=DwdForecastDate.LATEST, # automatical...
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def hide_topic(topic_id: TopicID, moderator_id: UserID) -> BoardTopicHidden: """Hide the topic.""" topic = _get_topic(topic_id) moderator = _get_user(moderator_id) now = datetime.utcnow() topic.hidden = True topic.hidden_at = now topic.hidden_by_id = moderator.id db.session.commit() ...
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def shell(): """ Starts an interactive shell with app object imported. """ # Local vars defined/imported will be available in shells global scope import IPython from app.main import app IPython.embed()
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def argmax(a, axis=None, out=None): """ Returns the indices of the maximum values along an axis. Parameters ---------- a: array_like axis: int, optional By default, the index is into the flattened array, otherwise along the specified axis. out: ...
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def FlowBalance_rule(model, node): """Ensures that flows into and out of a node are equal """ return model.Supply[node] \ + sum(model.Flow[i, node] for i in model.NodesIn[node]) \ - model.Demand[node] \ - sum(model.Flow[node, j] for j in model.NodesOut[node]) \ == 0
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def evaluate_perfs(num_images, duration): """ Calculate and print the inference duration. """ #fps = float(num_images / duration) #print("Throughput=%.2f fps, total frames = %.0f , time=%.4f seconds" %(fps, num_images, duration)) print("Duration = %.2f ms" %(duration * 1000))
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def test_config_merging_missing(): """ If we have set a boolean value in the TOML file, but not on the CLI, we want the TOML value to be taken. """ toml = StringIO( dedent( """\ [tool.vulture] verbose = true ignore_names = ["name1"] """ ) ...
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def abcd(actual, predicted, distribution, as_percent=True): """ Confusion Matrix: |`````````````|`````````````| | TN[0][0] | FP[0][1] | | | | |`````````````|`````````````| | FN[1][0] | TP[1][1] | | | | ````````````````````...
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def get_gene_name(protein_id, web_fallback=True): """Return the gene name for the given UniProt ID. This is an alternative to get_hgnc_name and is useful when HGNC name is not availabe (for instance, when the organism is not homo sapiens). Parameters ---------- protein_id : str Uni...
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def AddEventTypePositionalArg(parser): """Adds event type positional arg.""" parser.add_argument( 'event_type', help='Type of event (e.g. com.google.gc.object.finalize).')
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def summarize(): """ Returns summary of articles """ if request.method == 'POST': url = request.form['pageurl'] parser = HtmlParser.from_url(url, Tokenizer(LANGUAGE)) stemmer = Stemmer(LANGUAGE) summarizer = Summarizer(stemmer) summarizer.stop_words = get_stop_words(LANG...
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def _env_constructor(loader, node): """ Replaces environment variables in YAML file """ value = loader.construct_scalar(node) for group in env_pattern.findall(value): try: value = value.replace(f"${{{group}}}", os.environ.get(group)) except TypeError as error: ...
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def version(include_copyright=False): """Get the version number of ``ssocr``. Equivalent of running: ``ssocr --version`` Parameters ---------- include_copyright : :class:`bool`, optional Whether to include the copyright information. Returns ------- :class:`str` The ver...
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def intersection(n: np.ndarray, d: float, A: np.ndarray, b: np.ndarray) -> List[np.ndarray]: """Return the intersection of the plane and convex ployhedron. Returns a list of points which define the intersection between the plane nx = d and the convex ployh...
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def create_session(checkpoint_path, target_device): """Create ONNX runtime session""" if target_device == 'GPU': providers = ['CUDAExecutionProvider'] elif target_device == 'CPU': providers = ['CPUExecutionProvider'] else: raise ValueError( f'Unsupported target device...
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def V_eN_int(cgf_1, cgf_2, mol): """ Compute electron-nuclear integral between two contracted gaussian functions. """ v = 0 for i, _ in enumerate(cgf_1.alpha): for j, _ in enumerate(cgf_2.alpha): for k in range(mol.num_atoms): v += cgf_1.co[i] * cgf_2.co[j] * pote...
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def create_subword_vocab(input_data, subword_size): """create subword vocab from input data""" def generate_subword(word, subword_size): """generate subword for word""" subwords = [] chars = list(word) char_length = len(chars) ...
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def main() -> None: """Create a map of nodes with available SSH connection.""" map_ssh = folium.Map(location=[45.523, -122.675], zoom_start=2) with open("lib/base_data.txt") as tsv: for row in csv.reader(tsv, delimiter="\t"): name = row[0] try: x = float(row[...
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def request_json(input_data): """Request JSON data from full node, given request data input. More info: http://docs.python-requests.org/en/master/""" requested_data = None # Prevent no state if all servers fail! for full_node_url in full_node_list_http: try: requested_data = requests.get(full_node_url, dat...
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def rrange(x, y = 0): """ Creates a reversed range (from x - 1 down to y). Example: >>> rrange(10, 0) # => [9, 8, 7, 6, 5, 4, 3, 2, 1, 0] """ return range(x - 1, y - 1, -1)
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def registry_auth_gcloud(deployment, project, service_key): """ Setup GCR authentication with a service_key This changes *global machine state* on where docker can push to! """ encrypted_service_key_path = os.path.join( 'deployments', deployment, 'secrets', service_key ) with decryp...
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def einsum_outshape(subscripts, *operants): """Compute the shape of output from `numpy.einsum`. Does not support ellipses. """ if "." in subscripts: raise ValueError(f"Ellipses are not supported: {subscripts}") insubs, outsubs = subscripts.replace(",", "").split("->") if outsubs == ""...
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def random_points(region, color="00FFFF", points=100, seed=0): """Generates a specified number of random points inside a given area. Args: region(feature): region to generate points color(color code): default is red, I think points(numeric): how many points do you want? Default is 100 ...
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def test_init_smart_sleep_mode(): """Test that the new state array is populated correctly.""" const = get_const("1.4") sensor_id = 1 sensor = Sensor(sensor_id) sensor.add_child_sensor(0, const.Presentation.S_LIGHT_LEVEL) sensor.add_child_sensor(1, const.Presentation.S_LIGHT_LEVEL) assert n...
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def GridSearch(X_train_df, Y_train_df, hps_NaN_dict, features_l, hps_models_dict, cv=5, n_jobs=-1, randomise=True): """Launch a grid search over different value of the hps.""" # Compute all the possible combinations of hps tuples_hp = BuildHpTuples(X_train_df, hps_NaN_dict, ...
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def atm(): """Fixture to compute atmospheric properties just once before tests. Returns: Atmosphere object """ return Atmosphere(h_geom_truth_arr)
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def toPaf(inputFile, fileformat): """ This function converts the file (input) into a Preference-based Argumentation Framework. Here the PAF is represented by one set and 3 dictionnaries: - the set contains the arguments - the first dictionnary contains the attacks from an argument a to anoth...
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def get_key(my_dict: dict, val): """Get key value form dictionary using key value. Args: collection_name: dict: collection in dictionary format val: Value in dictionary Returns: Key from dictionary. """ for key, value in my_dict.items(): if val == value: ret...
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def test_get_mesh_grid_as_point_cloud_downsample(): """ Sample a regular grid and return the (x,y) coordinates of the sampled points. """ min_x = -3 # integer, minimum x-coordinate of 2D grid max_x = 0 # integer, maximum x-coordinate of 2D grid min_y = 2 # integer, minimum y-coordinate o...
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def closest(point, points): """works, but @@DEPRECATED!! return index into points of closest-to-point """ da = dist_array(point, points) return N.argmin(da)
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def generate_provenance_json(script="unknown", params={}): """Generate the provenance in a format which can later be output as valid json. Inputs: string: The name of the script used to trigger the data generation/deidentification/synthesis process dict: The parameters used to tune the data gen...
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def dot(v, w): """v_1 * w_1 + ... + v_n * w_n""" return sum(v_i * w_i for v_i, w_i in zip(v, w))
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def get_users(): """Query for user accounts.""" return JsonResponse(queryFor(UserAccount))
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def test_create_project_pi_too_short(client): """Create a project with too short PI.""" create_unit_admins(num_admins=2) current_unit_admins = models.UnitUser.query.filter_by(unit_id=1, is_admin=True).count() assert current_unit_admins == 3 proj_data_short_pi = proj_data.copy() proj_data_short...
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def get_added_and_removed_pitches( chord_root_tpc: int, chord_type: ChordType, changes: str, key_tonic_tpc: int, key_mode: KeyMode, ) -> Dict[str, str]: """ Get a mapping of pitch alterations from the given chord. Pitches are given and returned with PitchType TPC because accidental-speci...
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def get_n_random_points_in_region(region_mesh, N, s=None): """ Gets N random points inside (or on the surface) of a mes """ region_bounds = region_mesh.bounds() if s is None: s = int(N * 2) X = np.random.randint(region_bounds[0], region_bounds[1], size=s) Y = np.random.randint(regio...
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def test_get_issues_for_org_merges_issues_pull_requests(github, requests_mock): """ The '_get_issues_for_org' helper should merge both issues with pull requests and treat them both as issues """ repo1 = fixtures.repository( issues=[fixtures.issue(), fixtures.issue(), fixtures.issue()], ...
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def create_computer_query(tx, computer, query, value, rel): """Creates the queries for a computer. Arguments: tx {neo4j.Session} -- Neo4j session computer {dict} -- Single computer object. query {str} -- Query to use. value {[type]} -- Value to read from: LocalAdmins, DcomUsers ...
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def make_octad_tables(basis): """Return tables for encoding an decoding octads. Octads are numbered in the lexicographical order as given by the numbers of the corresponding Golay codewords in 'gcode' representation. The function returns a triple (oct_enc_table, oct_dec_table, oct_enc_...
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def fetch_profile(request): """ attaches the user.profile object into the request object""" context = {} if request.user.is_authenticated(): profile_module_name = get_my_profile_module_name() profile = getattr(request, profile_module_name, None) if profile != None: conte...
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def storeLabledImagesInFile(): """Consolidates the images in the emotion directories and stores them in data.npy and lables.npy file. Does virtual sampling for classes which do not have sufficient samples""" data = [] labels = [] if os.path.exists(OUTPUT_DIRECTORY): images = [] n...
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def test_device_put_method_empty_model_name(flask_app, db): # pylint: disable=unused-argument """ To verify that registration device method is working properly and response is correct""" registration = create_registration(REG_REQ_DATA, uuid.uuid4()) registration.update_status('Pending Review') ...
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def to_local_op(input): """Returns the local tensor of a consistent tensor. Args: input (Tensor): the input tensor. For example: .. code-block:: python >>> import oneflow as flow >>> import numpy as np >>> np_arr = np.array([0.5, 0.6, 0.7]).astype(np.float32) ...
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def col_round(x): """ As Python 3 rounds 0.5 fraction to closest even, floor and cell round methods used here to round 0.5 up to next digit and 0.4 down back to previos. """ frac = x - math.floor(x) if frac < 0.5: return math.floor(x) return math.ceil(x)
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def _create_notebook(client, headers: dict[str, str]) -> str: """Create a notebook. :param client: Test API client. :param headers: Headers with the access token. :return: Notebook ID. """ n = {"name": "Test Notebook"} r = client.post("/notebooks/notebook", headers=headers, json=n) ret...
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def iterate_steps(n): """Calculate derivatives for different parameter classes, and plot""" for vary in ['bary', 'halo', 'progenitor']: print(n, vary) step_convergence(n, Nstep=10, vary=vary) choose_step(n, Nstep=10, vary=vary)
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def createTables(): """ Populate the array with names of sql DDL files """ for sqlFileName in ["Address.sql", "Electricity.sql", "CodeViolationsReport.sql", "FireRescueEMSResponse.sql", "NaturalGasReport.sql", "WaterReport.sql"]: try: runSqlFil...
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def plot_range_range_rate(x_sat_orbdyn_stm:np.ndarray, x_obs_multiple:np.ndarray, t_sec: np.array): """ Plots range and range relative to the station Args: x_sat_orbdyn_stm (np.ndarray): satellite trajectory array. x_obs_multiple (np.ndarray): observer positions. t_sec (np.ndarray): arr...
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def parse_autostep(rule): """ Parse the autostep line """ parser = argparse.ArgumentParser() rules = shlex.split(rule) rules.pop(0) parser.add_argument("--autoscreenshot", dest="autoscreenshot", action="store") args = clean_args(vars(parser.parse_args(rules))) parser = None retu...
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def AUTO_TECHSUPPORT_GLOBAL_state(db, state): """ Knob to make techsupport invocation event-driven based on core-dump generation """ table = "AUTO_TECHSUPPORT" key = "GLOBAL" data = { "state": state, } try: update_entry_validated(db.cfgdb, table, key, data, create_if_not_exists=...
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def _make_tag(tagname: str, content: str = "", **attrs) -> str: """Creates a tag.""" tag = f"<{tagname} " for key, value in attrs.items(): if key == "raw": tag += " " + value continue if key == "cls": key = "class" if isinstance(value, float): ...
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def download(url: str, dest: Optional[str] = None, extract: bool=True, ignore_if_exists: bool = False, compression: Optional[str] = None): """ Download a file from the internet. Args: url: the url to download dest: destination file if extract=False, or destionation dir if extra...
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def action_functions(action_id: str): """Determines which function needs to be run.""" action_mappings = { NewIncidentSubmission.form_slack_view: [report_incident_from_submitted_form], UpdateParticipantCallbacks.submit_form: [update_participant_from_submitted_form], UpdateParticipantCall...
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def get_default_sender(): """ Determines the sender / to address for outgoing emails. """ try: return os.environ["EMAIL"] except KeyError: pass else: # Guess. # Not sure if euid is the right one to use here. user = pwd.getpwuid(os.geteuid()).pw_name ...
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def setup_function(function): """ Make sure there are no adapters defined before start of test """ clear_adapters() # Setup a basic int adapter for all tests @adapter((str, float, int), (int, str)) def to_int(obj, to_cls): return to_cls(obj)
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def get_best_response_actions_as_string(best_response_actions): """Turns a dict<bytes, int> into a bytestring compatible with C++. i.e. the bytestring can be copy-pasted as the brace initialization for a {std::unordered_,std::,absl::flat_hash_}map<std::string, int>. Args: best_response_actions: A dict map...
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def rank_velocity_genes(adata, vkey="velocity_S", prefix_store="rank", **kwargs): """Rank genes based on their raw and absolute velocities for each cell group. Parameters ---------- adata: :class:`~anndata.AnnData` AnnData object that contains the gene-wise velocities. vkey: str...
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def build_genome(tree, genome): """ Goes through a tree and builds a genome from all codons in the subtree. :param tree: An individual's derivation tree. :param genome: The list of all codons in a subtree. :return: The fully built genome of a subtree. """ if tree.codon: # If th...
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def fixture_yaml_formatting_fixtures(fixture_filename: str) -> Tuple[str, str, str]: """Get the contents for the formatting fixture files. To regenerate these fixtures, please run ``test/fixtures/test_regenerate_formatting_fixtures.py``. Ideally, prettier should not have to change any ``formatting-after``...
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def test_partial_trace_4_by_4(): """Test for 4-by-4 matrix.""" test_input_mat = np.arange(1, 17).reshape(4, 4) pt_1 = partial_trace(test_input_mat, [1], [2, 2]) pt_2 = partial_trace(test_input_mat, [2], [2, 2]) expected_pt_1 = np.array([[12, 14], [20, 22]]) bool_mat = np.isclose(expected_pt_1,...
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def get_base_parser(*args, **kwargs): """ Main parser """ parser=argparse.ArgumentParser(*args, **kwargs) # formatter_class=argparse.ArgumentDefaultsHelpFormatter, # ) # parser.add_argument('--help_all', '--help_model', '--help_dataset', '--help_strategy', '--help_task', '--help_ptr...
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def MakeBuildDirectory(context=None): """Prepares the build and work directories.""" if context is None: raise ValueError("context can't be None") build_dir = config.CONFIG.Get("PyInstaller.build_dir", context=context) work_path = config.CONFIG.Get("PyInstaller.workpath_dir", context=context) CleanDirec...
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def conv_bboxinfo_bboxXYHW_to_centerscale(bbox_xyhw, bLooseBox = False): """ from (bbox_xyhw) -> (center, scale) Args: bbox_xyhw: [minX,minY,W,H] bLooseBox: if true, draw less tight box with sufficient margin (SPIN's default setting) Output: center: bbox center scale: sca...
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def add_video(db: Session, video: schemas.Video): """ Adds video to table video_library model used is Video. Attributes: - video_user_id: int, non-nullable, foreign_key - video_link: string, non-nullable, unique - video_name: string, non-nullable, - video_height: int, non...
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def compute_principal_axes(xyz_centered, weights=None, twodim=True): """ :param xyz_centered: [list_of_xs, lst_of_ys, list_of_zs] :param weights: weights of each pixel :param twodim: whether to compute two main axes in xy plane, or three axes in 3D image. :return: ax1, ax2, (ax3 if not twodim else ...
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def stream_http_get(S, dest): """Get contents of http://dest/ via HTTP/1.0 and samclasses.StreamSession S.""" C = S.connect(dest) C.send('GET / HTTP/1.0\r\n\r\n') while True: line = stream_readline(C).strip() if line.find('Content-Length: ') == 0: clen = int(line.split()[1]) if line == ...
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def get_definition(division_id, path=None): """ Returns the expected contents of a definition file. """ config = {} division = Division.get(division_id, from_csv=ocd_division_csv) # Determine slug, domain and authority. name = division.name if not name: print('%-60s unknown nam...
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def api_last_blog_update(request): """Return the date of the last blog update. This is a PRIVATE API. Format: __lastblogupdate.json JSON return: {'lastupdate': '2019-01-31'} or if none available: {'lastupdate': None} """ api_code = enter_api_call('api_last_blog_update', ...
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def main(): """ 测试当前类的方法的主方法入口 :return: """ # DataProcessing("../data_example/test.tsv","../data_example/test.tfrecords").test_txt2tfrecords() # DataProcessing("../data_example/train.tsv","../data_example/train.tfrecords").train_txt2tfrecords() # DataProcessing("../feature_data/tsz_submission_12.tfrecords","../s...
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def pearson(arr1, arr2): """ calculate pearson correlation between two numpy arrays. :param arr1: one array, the feature is a column. the shape is `m * n` :param arr2: the other array, the feature is a column. the shape is `m * k` :return: a pearson score np.array , the shape is `k * n` """ ...
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def check_input(image): """Check that the provided image consists of a single connected domain of pixels. """ # Check that the input image has no floating pixels. labeled_array, num_features = label(image.astype(int)+1) assert num_features==1, "The input image must contain a single solid domain of c...
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def exact_match_filter(query_set, field, values): """Check if a field exactly matches a value.""" return field_filter(lambda x, y: Q(**{x: y}), query_set, field, values)
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def clean_savepoints(using=None): """ Resets the counter used to generate unique savepoint ids in this thread. """ get_connection(using).clean_savepoints()
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def get_move_descriptions(get_moved_ids, initial_state, current_state, obj_stuff, sort_attributes, obj_attributes): """ Get all 'move' descriptions from the current state (if any). Parameters ---------- get_moved_ids: function Function that extracts the id of objects that are being moved. ...
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def reliability_diagram(labels, probs, class_conditional=False, y_axis='accuracy', img=False): """Reliability Diagram plotting confidence against accuracy. Note that this reliability diagram is created by looking at the...
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def GuessSlugFromPath(path): """Returns the slug.""" if path.endswith('index.md'): # If it ends with index, get the second last path component. return path.split('/')[-2] else: # Otherwise, just get the filename. return path.split('/')[-1].split('.')[0]
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def get_file(fname, origin, cache_subdir='datasets', file_hash=None): """Downloads a file from a URL if not already in the cache. ref: https://github.com/keras-team/keras/blob/7a39b6c62d43c25472b2c2476bd2a8983ae4f682/keras/utils/data_utils.py#L123 By default the file at the url `origin` is downloaded to th...
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def simplified_fit(train_loader, val_loader, model, loss_fn, optimizer, n_epochs, is_cuda_available, metrics=[], start_epoch=0, scheduler = None, log_interval=1): """ TODO """ train_list = [] valid_list = [] log_interval = len(train_loader)//2 if scheduler != None: for epoch ...
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def _onenorm_matrix_power_nnm(A, p): """ Compute the 1-norm of a non-negative integer power of a non-negative matrix. Parameters ---------- A : a square ndarray or matrix or sparse matrix Input matrix with non-negative entries. p : non-negative integer The power to which the mat...
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def _stiff_terms_null(states, *args, **kwargs): """Dummy function""" return states
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def add_dataset(dset_fp, dset_fromroot, list_ids, up3d_fp, # pylint: disable=too-many-locals, too-many-arguments, too-many-statements, too-many-branches train_list_f, val_list_f, train_val_list_f, test_list_f, scale_f, train_spec, val_spec, test_spec, target_person_size,...
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def _compute_non_batch_kl(mu_a, sigma_a, mu_b, sigma_b): """Non-batch KL for N(mu_a, sigma_a), N(mu_b, sigma_b).""" # Check using numpy operations # This mostly repeats the tensorflow code _kl_mvn_mvn(), but in numpy. # So it is important to also check that KL(mvn, mvn) = 0. sigma_b_inv = np.linalg.inv(sigma_...
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def wait_until(fn, timeout, period, message): """ :param fn: callable function :param timeout: :param period: :param message: :return: bool """ mustend = time() + timeout while time() < mustend: if fn(): return True sleep(period) raise TimeoutError(mes...
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def test_atomic_normalized_string_length_nistxml_sv_iv_atomic_normalized_string_length_1_4(mode, save_output, output_format): """ Type atomic/normalizedString is restricted by facet length with value 0. """ assert_bindings( schema="nistData/atomic/normalizedString/Schema+Instance/NISTSchema-...
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def proxy_wasm_cpp_host_fetch_remote_crates(): """This function defines a collection of repos and should be called in a WORKSPACE file""" maybe( http_archive, name = "proxy_wasm_cpp_host__addr2line__0_16_0", url = "https://crates.io/api/v1/crates/addr2line/0.16.0/download", type ...
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def single_test(model, testdata, max_seq_len=20): """Get accuracy for a single model and dataloader. Args: model (nn.Module): MCTN2 Model testdata (torch.utils.data.DataLoader): Test Dataloader max_seq_len (int, optional): Maximum sequence length. Defaults to 20. Returns: _...
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def generate_tiled_html_result(slide_nums, tile_summaries_dict, data_link): """ Generate HTML to view the tiled images. Args: slide_nums: List of slide numbers. tile_summaries_dict: Dictionary of TileSummary objects keyed by slide number. data_link: If True, add link to tile data csv file. """ sl...
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