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def get_object(node): """ Parse rebaron AtomTrailers node into Python object (taken from ongoing conversion object) Works for object and local scope """ if len(node) > 1 and (node[0].value == 'self' or node[0].value == 'self_next'): var_t = super_getattr(convert_obj, str(node)) else: #...
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def read_label_from_txt(label_path): """Read label from txt file.""" text = np.fromfile(label_path) bounding_box = [] with open(label_path, "r") as f: labels = f.read().split("\n") for label in labels: if not label: continue label = label.split(" "...
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from typing import Union def _load_recipe(module, baked: bool = False) -> Union[BakedRecipe, Recipe]: # load entry-point DAG """Load Queenbee plugin from Python package. Usually you should not be using this function directly. Use ``load`` function instead. args: module: Python module obj...
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def compute_coeffs(shape, Aref, alfa): """Computes the lift and drag coefficients of the given shape at the given angle of attack using the given reference area""" alfa_vect = np.array([-np.sin(alfa),0,-np.cos(alfa)]) Fvect = np.array([0,0,0]) #Force coefficient vector for panel in shape: p...
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def draw_pitch(axis, rotate=False): """ Plots the lines of a soccer pitch using matplotlib. Arguments --------- axis : matplotlib.axes._subplots.AxesSubplot - matplotlib axis object on which to plot shot freeze frame rotate : bool - if set to True, pitch is horizontal, d...
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import click def file(filename, searchspec=None, searchtype=None, list_images=False, sort_by=None, fields=None): """Examine images from a local file.""" if not list_images: if searchtype is None or searchspec is None: raise click.BadParameter( 'SEARCHTYPE and SEARC...
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def clip_to_norm(array, clip): """Clips the examples of a 2-dimensional array to a given maximum norm. Parameters ---------- array : np.ndarray Array to be clipped. After clipping, all examples have a 2-norm of at most `clip`. clip : float Norm at which to clip each example R...
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def getlineno(frame): """Get the line number from a frame object, allowing for optimization.""" # FrameType.f_lineno is now a descriptor that grovels co_lnotab return frame.f_lineno
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def _batch_sum(F, loss, batch_axis): """Return sum on the specified batch axis, not keeping the axis""" if is_np_array(): axes = list(range(loss.ndim)) del axes[batch_axis] return F.np.sum(loss, axis=axes) else: return F.sum(loss, axis=batch_axis, exclude=True)
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def tree_cons(a, tree: Pytree) -> Pytree: """ Prepend ``a`` in all tuples of the given tree. """ return jax.tree_map( lambda x: _OpaqueSequence((a,) + tuple(x)), tree, is_leaf=lambda x: isinstance(x, tuple), )
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from datetime import datetime def add(moment: datetime) -> datetime: """Add one gigasecond to a given date and time.""" return moment + GIGASECOND
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def convert_to_short_log(log_level, message): """Convert a log message to its shorter format. :param log_level: enum - 'LogLevel.<level>' e.g. 'LogLevel.Error' :param message: str - log message :return: enum - 'LogLevelInt.<value>` e.g. 'LogLevelInt.5' """ return f'{LogLevelInt[log_level.na...
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import zipfile import io import pathlib import warnings def load_map(path, callback=None, meta_override=None): """Load a set of zipped csv AFM workshop data If you are recording quantitative force-maps (i.e. multiple curves on an x-y-grid) with AFM workshop setups, then you might have realized that y...
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def format_len(x): """ >>> format_len('abc') 3 >>> format_len(('(', ('(', 'def', ')'), 'yz', ')')) 11 """ if not isinstance(x, (list, tuple)): return len(x) if len(x) > 3: sep_len = 2 * (len(x) - 3) else: sep_len = 0 return sum(map(format_len, x)) + sep_len
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def set_doi_ark(page_number, records_per_page, sort_on, doi_ark_value): """ Retrieve all metadata records for admin view. Retrieval is done via POST because we must pass a session id so that the user is authenticated. Access control is done here. A user can modify only their own records because...
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def empiriline(x,p,L): """ Use the line L (which is an EmissionLine object) as a template. The line is shifted, then interpolated, then rescaled, and allowed to float. """ xnew = x - p[1] yout = sp.zeros(len(xnew)) m = (xnew >= L.wv.min())*(xnew <= L.wv.max() ) ynew,znew = L.interp(x...
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def _get_z_slice_fn(z, data_dir): """Get array slice map to be applied to z dimension Args: z: String or 1-based index selector for z indexes constructed as any of the following: - "best": Indicates that z slices should be inferred based on focal quality - "all": Indicates that ...
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def bar_data_wrapper(func): """Standardizes column names for any bar data""" def wrapper(*args, **kwargs): assert Ticker(args[0]) res: pd.DataFrame = func(*args, **kwargs) return res.rename(columns=COL_NAMES).iterrows() return wrapper
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import torch def rgb_to_grayscale( image: Tensor, rgb_weights: list[float] = [0.299, 0.587, 0.114] ) -> Tensor: """Convert an RGB image to grayscale version of image. Image data is assumed to be in the range of [0.0, 1.0]. Args: image (Tensor[B, 3, H, W]): RGB image to be converte...
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def _aware_to_agnostic(fr: NDFrame) -> NDFrame: """Recalculate values in tz-aware series or dataframe, to get a tz-agnostic one. (i.e., A to B).""" if not fr.index.tz: raise ValueError("``fr`` must be tz-aware.") idx_out = _idx_after_conversion(fr, None) # Convert daily or longer. if s...
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import math def cumulative_prob_to_value(prob, hp): """Convert a value from [0, 1] to a hyperparameter value.""" if isinstance(hp, Fixed): return hp.value elif isinstance(hp, Boolean): return bool(prob >= 0.5) elif isinstance(hp, Choice): ele_prob = 1 / len(hp.values) i...
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import podpac import podpac.datalib # May not be imported by default import inspect def get_ui_node_spec(module=None, category="default"): """ Returns a dictionary describing the specifications for each Node in a module. Parameters ----------- module: module The Python module for which t...
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def parse_branch_name(branch_name): """Split up a branch name of the form 'ocm-X.Y[-mce-M.N]. :param branch_name: A branch name. If of the form [remote/]ocm-X.Y[-mce-M.N] we will parse it as noted below; otherwise the first return will be False. :return parsed (bool): True if the branch_name was pa...
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import itertools def symmetric_padding( arr, width): """ Pad an array using symmetric values. This is equivalent to `np.pad(mode='symmetric')`, but should be faster. Also, the `width` parameter is interpreted in a more general way. Args: arr (np.ndarray): The input array....
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def _uid_or_str(node_or_entity): """ Helper function to support the transition from `Entitie`s to `Node`s. """ return ( node_or_entity.uid if hasattr(node_or_entity, "uid") else str(node_or_entity) )
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def power(maf=0.5,beta=0.1, N=100, cutoff=5e-8): """ estimate power for a given allele frequency, effect size beta and sample size N Assumption: z-score = beta_ML distributed as p(0) = N(0,1.0(maf*(1-maf)*N))) under the null hypothesis the actual beta_ML is distributed as p(alt) = N( beta , 1.0/(maf*(1-maf)N) )...
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def get_rotation_matrix(angle: float, direction: np.ndarray, point: np.ndarray = None) -> np.ndarray: """Compute rotation matrix relative to point and direction Args: angle (float): angle of rotation in radian direction (np.ndarray): axis of rotation point (np.ndarray, optional): center...
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def answer(panel_array): """ Returns the maximum product of positive and (odd) negative numbers.""" print("panel_array=", panel_array) # Edge case I: no panels :] if (len(panel_array) == 0): return str(0) # Get zero panels. zero_panels = list(filter(lambda x: x == 0 , panel_arra...
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def load_fromh5(filepath, dir_structure, slice_num, strt_frm=0): """ load_fromh5 will extract the sinogram from the h5 file Output: the sinogram filepath: where the file is located in the system dir_structure: the h5 file directory structure slice_num: the slice where the singoram will be ext...
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def lqr_6_2(time_limit=_DEFAULT_TIME_LIMIT, random=None, environment_kwargs=None): """Returns an LQR environment with 6 bodies of which first 2 are actuated.""" return _make_lqr( n_bodies=6, n_actuators=2, control_cost_coef=_CONTROL_COST_COEF, time_limit=time_limit, rando...
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def machine_stop(request, tenant, machine): """ Stop (power off) the specified machine. """ with request.auth.scoped_session(tenant) as session: serializer = serializers.MachineSerializer( session.stop_machine(machine), context = { "request": request, "tenant": tenant } ...
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from typing import Tuple from typing import Dict from typing import Any def _get_input_value(arg: Tuple[str, GraphQLArgument]) -> Dict[str, Any]: """Compute data for the InputValue fragment of the introspection query for a particular arg.""" return { "name": __InputValue.fields["name"].resolve(arg, No...
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def wrapper(X_mixture,X_component): """ Takes in 2 arrays containing the mixture and component data as numpy arrays, and prints the estimate of kappastars using the two gradient thresholds as detailed in the paper as KM1 and KM2""" N=X_mixture.shape[0] ...
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import torch def iou( outputs: torch.Tensor, targets: torch.Tensor, eps: float = 1e-7, threshold: float = 0.5, activation: str = "sigmoid" ): """ Args: outputs (torch.Tensor): A list of predicted elements targets (torch.Tensor): A list of elements that are to be predicted ...
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def readCoords(f): """Read XYZ file and return as MRChem JSON friendly string.""" with open(f) as file: return '\n'.join([line.strip() for line in file.readlines()[2:]])
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def api_update_note(note_id: int): """Update a note""" db = get_db() title = request.form["title"] if "title" in request.form.keys() else None content = request.form["content"] if "content" in request.form.keys() else None note = db.update_note(note_id, title, content) return jsonify(note.__dict...
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def padding_oracle(decrypt, cipher, *, bs, unknown=b"\x00", iv=None): """Padding Oracle Attack Given a ciphersystem such that: - The padding follows the format of PKCS7 - The mode of the block cipher is CBC - We can check if the padding of a given cipher is correct - We can try to decrypt ciphe...
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def pixels(): """ Raspberry Pi pixels """ return render_template("pixels.html")
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async def get_song_info(id: str): """ 获取歌曲详情 """ params = {'ids': id} return get_json(base_url + '/song/detail', params=params)
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def _find_odf_idx(map, position): """Find odf_idx in the map from the position (col or row). """ odf_idx = bisect_left(map, position) if odf_idx < len(map): return odf_idx return None
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def get_or_create(session, model, **kwargs): """ Creates and returns an instance of the model with given kwargs, if it does not yet exist. Otherwise, get instance and return. Parameters: session: Current database session model: The Class of the database model **kw...
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def pack_asn1(tag_class, constructed, tag_number, b_data): """Pack the value into an ASN.1 data structure. The structure for an ASN.1 element is | Identifier Octet(s) | Length Octet(s) | Data Octet(s) | """ b_asn1_data = bytearray() if tag_class < 0 or tag_class > 3: raise ValueError(...
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from typing import Dict def choose(text: str, prompt: str, options: Dict[str, str], suggestion: str, none_allowed: bool): """ Helper function to ask user to select from a list of options (with optional description). Suggestion can be given. 'None' can be allowed as a valid input value. """ p = Col...
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def util_color( graph: list[list[int]], max_color: int, colored_vertices: list[int], index: int ) -> bool: """ alur : 1. Periksa apakah pewarnaan selesai 1.1 Jika pengembalian lengkap True (artinya kita berhasil mewarnai grafik) Langkah Rekursif: 2. Iterasi atas setiap warna: ...
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def reverse_complement(sequence): """ Return reverse complement of a sequence. """ complement_bases = { 'g':'c', 'c':'g', 'a':'t', 't':'a', 'n':'n', 'G':'C', 'C':'G', 'A':'T', 'T':'A', 'N':'N', "-":"-", "R":"Y", "Y":"R", "S":"W", "W":"S", "K":"M", "M":"K", "B":"V", "V":"B", "D": ...
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def get_variable_ddi( name, shape, value, init, initializer=None, dtype=tf.float32, regularizer=None, trainable=True): """Wrapper for data-dependent initialization.""" kwargs = {"trainable": trainable} if initializer: kwargs["initializer"] = initializer if regularizer: kwargs["regularizer"] = re...
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def conv3x3(in_planes, out_planes, Conv=nn.Conv2d, stride=1, groups=1, dilation=1): """3x3 convolution with padding""" return Conv(in_planes, out_planes, kernel_size=3, stride=stride, padding=dilation, groups=groups, bias=False, dilation=dilation)
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async def async_setup(hass, config): """Set up the AirVisual component.""" hass.data[DOMAIN] = {} hass.data[DOMAIN][DATA_CLIENT] = {} hass.data[DOMAIN][DATA_LISTENER] = {} if DOMAIN not in config: return True conf = config[DOMAIN] hass.async_create_task( hass.config_entrie...
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def hasConnection(document): """ Check whether document has a child of :class:`Sea.adapter.connection.Connection`. :param document: a :class:`FreeCAD.Document` instance """ return _hasObject(document, 'Connection')
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from typing import List def trsfrm_aggregeate_mulindex(df:pd.DataFrame, grouped_cols:List[str], agg_col:str, operation:str, k:int=5): """transform aggregate statistics for multiindex ...
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from typing import Optional def get_hub_virtual_network_connection(connection_name: Optional[str] = None, resource_group_name: Optional[str] = None, virtual_hub_name: Optional[str] = None, opts: Option...
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def newcombe_binomial_ratio_err(k1,n1, k2,n2, z=1.0): """ Newcombe-Brice-Bonnett ratio confidence interval of two binomial proportions. """ RR = (k1/n1) / (k2/n2) # mean logRR = np.log(RR) seLogRR = np.sqrt(1/k1 + 1/k2 - 1/n1 - 1/n2) ash = 2 * np.arcsinh(z/2 * seLogRR) lower ...
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from typing import Any from typing import Optional import json def parse_metrics(rpcs: Any, detokenizer: Optional[detokenize.Detokenizer], timeout_s: Optional[float]): """Detokenizes metric names and retrieves their values.""" # Creates a defaultdict that can infinitely have other defaultdic...
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def cigarlist_to_cigarstring(cigar_list): """ Convert a list of tuples into a cigar string. Example:: [ (0, 10), (1, 1), (0, 75), (2, 2), (0, 20) ] => 10M 1I 75M 2D 20M => 10M1I75M2D20M :param cigar_list: a list of tuples (code, l...
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def add(x, y): """Add two numbers""" return x+y
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def clean_acl(name, value): """ Returns a cleaned ACL header value, validating that it meets the formatting requirements for standard Swift ACL strings. The ACL format is:: [item[,item...]] Each item can be a group name to give access to or a referrer designation to grant or deny base...
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def test(X, Y, perms=10000, method="pearson", tail="two-tail", ignore_nans=False): """ Takes two distance matrices (either redundant matrices or condensed vectors) and performs a Mantel test. The Mantel test is a significance test of the correlation between two distance matrices. Parameters ---...
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def get_format_datestr(date_str, to_format='%Y-%m-%d'): """ Args: date_str (str): '' to_format (str): '%Y-%m-%d' Returns: date string (str) """ date_obj = parser.parse(date_str).date() return date_obj.strftime(to_format)
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def lor(*goalconsts): """ Logical or for goal constructors >>> from logpy.arith import lor, eq, gt >>> gte = lor(eq, gt) # greater than or equal to is `eq or gt` """ def goal(*args): return lany(*[gc(*args) for gc in goalconsts]) return goal
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import logging from operator import gt def score(input, index, output=None, scoring="+U,+u,-s,-t,+1,-i,-a", filter=None, # "1,2,25" quality=None, compress=False, threads=1, raw=False, remove_existing=False): """Score the in...
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def keyword_search(queryset: QuerySet, keywords: str) -> QuerySet: """ Performs a keyword search over a QuerySet Uses PostgreSQL's full text search features Args: queryset (QuerySet): A QuerySet to be searched keywords (str): A string of keywords to search the QuerySet Returns: ...
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def classification_loss(hidden, labels, n_class, initializer, name, reuse=None, return_logits=False): """ Different classification tasks should use different scope names to ensure different dense layers (parameters) are used to produce the logits. An exception will be in tr...
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def do_pdfimages(pdf_file, state, page_number=None, use_tmp_identifier=True): """Convert a PDF file to images in the TIFF format. :param pdf_file: The input file. :type pdf_file: jfscripts._utils.FilePath :param state: The state object. :type state: jfscripts.pdf_compress.State :param int page_...
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def connect(transport=None, host='localhost', username='admin', password='', port=None, key_file=None, cert_file=None, ca_file=None, timeout=60, return_node=False, **kwargs): """ Creates a connection using the supplied settings This function will create a connection to an Arista EOS nod...
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def cov_hc2(results): """ See statsmodels.RegressionResults """ # probably could be optimized h = np.diag(np.dot(results.model.exog, np.dot(results.normalized_cov_params, results.model.exog.T))) het_scale = results.resid**2/(1-h) cov_hc2_ ...
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def add_people(): """ Show add form """ if request.method == 'POST': #save data to database db_conn = get_connection() cur = db_conn.cursor() print ('>'*10, request.form) firstname = request.form['first-name'] lastname = request.form['last-name'] address = request.form['address'] country = request....
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import inspect def api_to_schema(api: "lightbus.Api") -> dict: """Produce a lightbus schema for the given API""" schema = {"rpcs": {}, "events": {}} if isinstance(api, type): raise InvalidApiForSchemaCreation( "An attempt was made to derive an API schema from a type/class, rather than...
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def sum2(u : SignalUserTemplate, initial_state=0): """Accumulative sum Parameters ---------- u : SignalUserTemplate the input signal initial_state : float, SignalUserTemplate the initial state Returns ------- SignalUserTemplate the output signal of the filter ...
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def approve_report(id): """ Function to approve a report """ # Approve the vulnerability_document record resource = s3db.resource("vulnerability_document", id=id, unapproved=True) resource.approve() # Read the record details vdoc_table = db.vulnerability_document record = db(vdo...
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def sparse_column_multiply(E, a): """ Multiply each columns of the sparse matrix E by a scalar a Parameters ---------- E: `np.array` or `sp.spmatrix` a: `np.array` A scalar vector. Returns ------- Rescaled sparse matrix """ ncol = E.shape[1] if ncol != a.shape[...
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def soup_extract_enzymelinks(tabletag): """Extract all URLs for enzyme families from first table.""" return {link.string: link['href'] for link in tabletag.find_all("a", href=True)}
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def loops_NumbaJit_parallelFast(csm, r0, rm, kj): """ This method implements the prange over the Gridpoints, which is a direct implementation of the currently used c++ methods created with scipy.wave. Very strange: Just like with Cython, this implementation (prange over Gridpoints) produces wrong r...
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import numpy import scipy def sobel_vertical_gradient(image: numpy.ndarray) -> numpy.ndarray: """ Computes the Sobel gradient in the vertical direction. Args: image: A two dimensional array, representing the image from which the vertical gradient will be calculated. Returns: A two di...
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def custom_field_sum(issues, custom_field): """Sums custom field values together. Args: issues: List The issue list from the JQL query custom_field: String The custom field to sum. Returns: Integer of the sum of all the found values of the custom_field. """ ...
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def routingAreaUpdateReject(): """ROUTING AREA UPDATE REJECT Section 9.4.17""" a = TpPd(pd=0x3) b = MessageType(mesType=0xb) # 00001011 c = GmmCause() d = ForceToStandbyAndSpareHalfOctets() packet = a / b / c / d return packet
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def doRipsFiltration(X, maxHomDim, thresh = -1, coeff = 2, getCocycles = False): """ Run ripser assuming Euclidean distance of a point cloud X :param X: An N x d dimensional point cloud :param maxHomDim: The dimension up to which to compute persistent homology :param thresh: Threshold up to which to...
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def build_target_areas(entry): """Cleanup the raw target areas description string""" target_areas = [] areas = str(entry['cap:areaDesc']).split(';') for area in areas: target_areas.append(area.strip()) return target_areas
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def convert_to_celcius(scale, temp): """Convert the specified temperature to Celcius scale. :param int scale: The scale to convert to Celcius. :param float temp: The temperature value to convert. :returns: The temperature in degrees Celcius. :rtype: float """ if scale == temp_scale.FARENHEI...
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def config_file_settings(request): """ Update file metadata settings """ if request.user.username != 'admin': return redirect('project-admin:home') if request.method == 'POST': update_file_metadata(request.POST) return redirect('project-admin:home') files = FileMetaData...
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def roundtrip(sender, receiver): """ Send datagrams from `sender` to `receiver` and back. """ return transfer(sender, receiver), transfer(receiver, sender)
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import json def loadHashDictionaries(): """ Load dictionaries containing id -> hash and hash -> id mappings These dictionaries are essential due to some restrictive properties of the anserini repository Return both dictionaries """ with open(PATH + PATH_ID_TO_HASH, "r") as f: ...
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def preprocess(tensor_dict, preprocess_options, func_arg_map=None): """Preprocess images and bounding boxes. Various types of preprocessing (to be implemented) based on the preprocess_options dictionary e.g. "crop image" (affects image and possibly boxes), "white balance image" (affects only image), etc. If se...
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def update_comment(id): """修改单条评论""" comment = Comment.query.get_or_404(id) if g.current_user != comment.author and not g.current_user.can(Permission.COMMENT): return error_response(403) data = request.get_json() if not data: return bad_request('You must put JSON data.') comment....
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def resnet18(num_classes, pretrained=False, **kwargs): """Constructs a ResNet-18 model. Args: pretrained (bool): If True, returns a model pre-trained on ImageNet """ encoder = ResNetEncoder(BasicBlock, [2, 2, 2, 2]) if pretrained: encoder.load_state_dict(model_zoo.load_url(model_urls...
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import html def display_page(pathname): """displays dash page""" if pathname == '/': return main.layout elif pathname == '/explore': return explore.layout elif pathname == '/eval': return eval.layout elif pathname == '/train': return train.layout else: r...
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def getFilterDict(args): """ Function: An entire function just to notify the user of the arguments they've passed to the script? Seems reasonable. Called from: main """ ## Set variables for organization; this can be probably be removed later outText = {} outAction = "" userString = ""...
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def pointwise_multiply(A, B): """Pointwise multiply Args: ----------------------------- A: tvm.te.tensor.Tensor shape [...] B: tvm.te.tensor.Tensor shape same as A ----------------------------- Returns: ----------------------------- tvm.te.tensor.Tensor shap...
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import traceback def create_website(self): """ :param self: :return: """ try: query = {} show = {"_id": 0} website_list = yield self.mongodb.website.find(query, show) return website_list except: logger.error(traceback.format_exc()) return ""
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def _get_sparsity(A, tolerance=0.01): """Returns ~% of zeros.""" positives = np.abs(A) > tolerance non_zeros = np.count_nonzero(positives) return (A.size - non_zeros) / float(A.size)
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def findPeaks(hist): """ Take in histogram Go through each bin in the histogram and: Find local maximum and: Fit a parabola around the two neighbor bins and local max bin Calculate the critical point that produces the max of the parabola (critical point represents orientation...
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def gradient_descent(x_0, a, eta, alpha, beta, it_max, *args, **kwargs): """Perform simple gradient descent with back-tracking line search. """ # Get a copy of x_0 so we don't modify it for other project parts. x = x_0.copy() # Get an initial gradient. g = gradient(x, a) # Compute the norm...
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from typing import Counter def knn_python(input_x, dataset, labels, k): """ :param input_x: 待分类的输入向量 :param dataset: 作为参考计算距离的训练样本集 :param labels: 数据样本对应的分类标签 :param k: 选择最近邻样本的数目 """ # 1. 计算待测样本与参考样本之间的欧式距离 dist = np.sum((input_x - dataset) ** 2, axis=1) ** 0.5 # 2. 选取 k 个最近邻样本的标...
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def all_logit_coverage_function(coverage_batches): """Computes coverage based on the sum of the absolute values of the logits. Args: coverage_batches: Numpy arrays containing coverage information pulled from a call to sess.run. In this case, we assume that these correspond to a batc...
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import asyncio async def create_audio(request): """Process the request from the 'asterisk_ws_monitor' and creates the audio file""" try: message = request.rel_url.query["message"] except KeyError: message = None LOGGER.error(f"No 'message' parameter passed on: '{request.rel_url}'"...
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def reinterpret_axis(block, axis, label, scale=None, units=None): """ Manually reinterpret the scale and/or units on an axis """ def header_transform(hdr, axis=axis, label=label, scale=scale, units=units): tensor = hdr['_tensor'] if isinstance(axis, basestring): axis = tensor['labels...
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def duel(board_size, player_map): """ :param board_size: the board size (i.e. a 2-tuple) :param player_map: a dict, where the key is an int, 0 or 1, representing the player, and the value is the policy :return: the resulting game outcomes """ board_state = init_board_state(board_size) result...
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def set_processor_type(*args): """ set_processor_type(procname, level) -> bool Set target processor type. Once a processor module is loaded, it cannot be replaced until we close the idb. @param procname: name of processor type (one of names present in \ph{psnames}) (C++: const char *) ...
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from onnx.helper import make_node from onnx import TensorProto def convert_repeat(node, **kwargs): """Map MXNet's repeat operator attributes to onnx's Tile operator. """ name, input_nodes, attrs = get_inputs(node, kwargs) opset_version = kwargs['opset_version'] if opset_version < 11: rais...
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def my_quote(s, safe = '/'): """quote('abc def') -> 'abc%20def' Each part of a URL, e.g. the path info, the query, etc., has a different set of reserved characters that must be quoted. RFC 2396 Uniform Resource Identifiers (URI): Generic Syntax lists the following reserved characters. reserve...
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from masci_tools.tools.cf_calculation import CFCalculation, plot_crystal_field_calculation def test_plot_crystal_field_calculation(): """ Test of the plot illustrating the potential and charge density going into the calculation """ cf = CFCalculation() cf.readPot('files/cf_calculation/CFdata.hdf'...
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