content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
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)
) | 82f5747e8c73e1c167d351e1926239f17ea37b98 | 3,645,800 |
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) )... | 1806718cd0af5deb38a25a90864bb14f40e2c57a | 3,645,801 |
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... | fd7c8d22368b51310a85453f6a9732f56a443803 | 3,645,802 |
import logging
import sys
import traceback
import inspect
def assert_check(args: dict = None, log_level: str = LOG_LEVEL) -> bool:
""" assert caller function args """
if args is None:
logger.critical("Arguments dict is empty or does not exist!")
return False
else:
logging.debug("A... | a61d33f78f99cf91bcde7d5920ba20d6ac3e6816 | 3,645,803 |
from typing import Any
import os
def establish_github_connection(store: dict[str, Any]) -> ValidationStepResult:
"""
Establishes the connection to GitHub.
If the name of the environment variable storing the GitHub PAT is not given,
then it will default to searching for one named "GH_TOKEN". If provid... | 8aab64c1d042639096b307f11dc469525095cfcf | 3,645,804 |
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... | 7169fba8dcf6c0932722dcbc606d6d60fdaf3ed1 | 3,645,805 |
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... | 90aa278a7429cc832071a374df9de2d8dd2abb88 | 3,645,806 |
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... | b27a4fd55d67cfcbb9a651b7915fd2e3b4460af9 | 3,645,807 |
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 }
... | b91a375c1aa8b62a6ed665d0045ff4b9eeae6a18 | 3,645,808 |
import subprocess
def exec_command_rc(*cmdargs, **kwargs):
"""
Return the exit code of the command specified by the passed positional arguments, optionally configured by the
passed keyword arguments.
Parameters
----------
cmdargs : list
Variadic list whose:
1. Mandatory first ... | bfe4f5bbdcbed6cfc3c8f52abffe2be7107fd091 | 3,645,809 |
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... | 7e82936b07b01531b0716c6904709c37e807d868 | 3,645,810 |
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] ... | f5e093590897c363bbab2360a14d7c3a82fd6bcd | 3,645,811 |
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
... | 4c43832560126c19b8b9ebc01daf3920603b5f17 | 3,645,812 |
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:]]) | 0cf1a9d07b4b3fe1836ce5c8a308ff67b5fe4c70 | 3,645,813 |
import os
def fetch_hillstrom(target_col='visit', data_home=None, dest_subdir=None, download_if_missing=True,
return_X_y_t=False, as_frame=True):
"""Load and return Kevin Hillstrom Dataset MineThatData (classification or regression).
This dataset contains 64,000 customers who last purchas... | a400779d477f413e88c252d2f47b6318385f8ab1 | 3,645,814 |
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... | d6668b89854e4aa6c248041a97a55c95cd568e9e | 3,645,815 |
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... | 077eeed2f8f0f2e91aa482c93f36825bdbcef17a | 3,645,816 |
def pixels():
"""
Raspberry Pi pixels
"""
return render_template("pixels.html") | d3af0be80b09096e05a29ef3e9209cef2dba8431 | 3,645,817 |
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) | 2185c62db03bba3019d9d010fc5603c432a0048f | 3,645,818 |
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 | 642398d72abe89aa63b7537372499655af5a5ded | 3,645,819 |
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... | 4d3e4f0da5ca61789171db5d8d16a5fa06e975cc | 3,645,820 |
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(... | 14aad1709b5efa46edc5d7ac8659fe1de0615a57 | 3,645,821 |
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... | 0b43452f00378ddc1345b85ca72b37ff1edfae05 | 3,645,822 |
import os
def get_environ_list(name, default=None):
"""Return the split colon-delimited list from an environment variable.
Returns an empty list if the variable didn't exist.
"""
packed = os.environ.get(name)
if packed is not None:
return packed.split(':')
elif default is not None:
... | 3e59962558b127790e456a79edf6175d1c3f7bbe | 3,645,823 |
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:
... | 081bf9e8b1e0dcc847fdd0bc78167819506e3f1c | 3,645,824 |
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": ... | d28e520a9159cb4812079b4a7a5f2f6eb5723403 | 3,645,825 |
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... | b941f110ee8efbdfb9e4d2a6b5ba0a5b3e5881ed | 3,645,826 |
def convert_to_mp3(path, start=None, end=None, cleanup_after_done=True):
"""Covert to mp3 using the python ffmpeg module."""
new_name = path + '_new.mp3'
params = {
"loglevel": "panic",
"ar": 44100,
"ac": 2,
"ab": '{}k'.format(defaults.DEFAULT.SONG_QUALITY),
"f": "mp3... | 9d30c593e761103e6b434b530290637e8a4c345c | 3,645,827 |
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) | 7741248a5af70e33abe803469c8a20eb2f4bcdb1 | 3,645,828 |
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... | e44beaaf7657848fa377700021671d6c27317696 | 3,645,829 |
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') | d0999c488ea1af1d0117eb53a6e67d5ce876a142 | 3,645,830 |
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
... | f84ac88bb3f3474fe5611486031e746e4dc9954d | 3,645,831 |
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... | 3275fdf70d088df2f00bfe9e0148026caca16fcc | 3,645,832 |
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 ... | 8ea31bcbbc1d6393e2d60d9ef6a1052b3b5347c5 | 3,645,833 |
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... | d169e9e247d8b969f6adf5161f0f7399a7b69da6 | 3,645,834 |
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... | 4d3a039f60f8976893e5ad3775f61fbfa2656acc | 3,645,835 |
def add(x, y):
"""Add two numbers"""
return x+y | 7f18ee62d6cd75e44a9401d000d9bcada63f2c24 | 3,645,836 |
import os
def generateCSR(host_id, key):
"""Generate a Certificate Signing Request"""
pod_name = os.environ['MY_POD_NAME']
namespace = os.environ['TEST_APP_NAMESPACE']
SANURI = f'spiffe://cluster.local/namespace/{namespace}/podname/{pod_name}'
req = crypto.X509Req()
req.get_subject().CN = ho... | 761cfe7b2627c38dcddce68be99f7ead4965369c | 3,645,837 |
import logging
def sdecorator(decoratorHandleDelete: bool = False, expectedProperties: list = None, genUUID: bool = True,
enforceUseOfClass: bool = False, hideResourceDeleteFailure: bool = False,
redactConfig: RedactionConfig = None, timeoutFunction: bool = True):
"""Decorate a funct... | f06647b034c2c5fa10a84afed83673f3a8be15f7 | 3,645,838 |
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... | 1cceb2af22d2f5bbf223a0eb381b4c6643d76f0e | 3,645,839 |
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
---... | 7f0d7447ed475292f221e1dc6e4944f5cb2e8bd4 | 3,645,840 |
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) | bf443aad3ca38eb35b647d26b38b1404cf82f387 | 3,645,841 |
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 | 9726cc24f6d79214e652d42ff1b872f60b5a4594 | 3,645,842 |
import time
def kalman_smoother(Z, M_inv, plotting=False):
"""
X: state
U: control
Z: observation (position and forces)
F: state transition model
B: control input model
Q: process variance
R: observation variance
"""
t_steps = Z.shape[0]
x0 = np.r_[Z[0,0:6],
... | 927062585686897462ca866819ecdff22aed245c | 3,645,843 |
def get_convex_hull(coords, dim = 2, needs_at_least_n_points = 6): #FIXME restrict only for 2D?
"""
For fitting an ellipse, at least 6 points are needed
Parameters
----------
coords : 2D np.array of points
dim : dimensions to keep when calculating convex hull
Returns
---------
coo... | 6939db4475b9e11c8d0e53a5d820773bb899f15a | 3,645,844 |
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... | c4b0fee2df964e65ee0aec12c84b0b1d7985a254 | 3,645,845 |
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:
... | 1fb38af2c3aa3bdf092196e8e12539e0a2cf9e58 | 3,645,846 |
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... | c89fd14fae7099b43f639bf0825600e26b60e417 | 3,645,847 |
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_... | e5a48cdf2c93b037c4f983a56467e839920fa06c | 3,645,848 |
from pathlib import Path
import subprocess
def git_patch_tracked(path: Path) -> str:
""" Generate a patchfile of the diff for all tracked files in the repo
This function catches all exceptions to make it safe to call at the end of
dataset creation or model training
Args:
path (Path): pat... | 374d80f8d1f74de76ab1dc1305f0772fde85d4f5 | 3,645,849 |
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... | 09407d39e624f9a863a7633627d042b17b7a6158 | 3,645,850 |
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_ ... | 328eeb88e37a2d78a6c0f0f9b3b81459230d87d5 | 3,645,851 |
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.... | db2fcd7a2d9ed0073741d02a0bcafef37f714299 | 3,645,852 |
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... | d07f6c6915967a1e61bc8f9bd1b72adb24207684 | 3,645,853 |
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
... | 3649942de13f698a92703747d8ea73be7ece4ddb | 3,645,854 |
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... | ce1bdb00a5fb6958c51422543e62f289de5e96cb | 3,645,855 |
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[... | a215440e630aeb79758e8b0d324ae52ea87eba52 | 3,645,856 |
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)} | 7baabd98042ab59feb5d8527c18fe9fa4b6a50af | 3,645,857 |
def choose(db_issue: Issue, db_user: User, pgroup_ids: [int], history: str, path: str) -> dict:
"""
Initialize the choose step for more than one premise in a discussion. Creates helper and returns a dictionary
containing several feedback options regarding this argument.
:param db_issue:
:param db_u... | 0404e955a7872086d45ccf4018bc8a9977c2df21 | 3,645,858 |
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... | 82201310483b72c525d1488b5229e628d44a65ca | 3,645,859 |
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... | f8f9bf6fadbae962206255ab3de57edbab9d935e | 3,645,860 |
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.
"""
... | 32c1cce310c06f81036ee79d70a8d4bbe28c8417 | 3,645,861 |
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 | b9bb0e498a768eb6b7875018c78ca23e54353620 | 3,645,862 |
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... | a0e4cabb613ac77659fda2d31867a7e9df32f288 | 3,645,863 |
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 | 48e76a5c1ed42aed696d441c71799b47f9193b29 | 3,645,864 |
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... | a7c2f0f7405eea96c1ebb4a7e103cf28a95b6f5a | 3,645,865 |
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... | c8e91ac49305e3aa7aa33961939c3add23fc5327 | 3,645,866 |
def roundtrip(sender, receiver):
"""
Send datagrams from `sender` to `receiver` and back.
"""
return transfer(sender, receiver), transfer(receiver, sender) | 939d9fd861b89037322fcc7c851d291ab073b520 | 3,645,867 |
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:
... | de8af6d5e5562869c992e08343aadb77c48933b0 | 3,645,868 |
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... | 141b170e0d4c6447750e2ece967afec7a92a37ea | 3,645,869 |
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.... | 59db7122f9139f7fda744284e83045533d6361fb | 3,645,870 |
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... | b342fa322cb26571b5df7e5e8f117ce016a7febf | 3,645,871 |
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... | 3aeb44ca1974b63f63b9ef97526aef20d2d92ddb | 3,645,872 |
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 = ""... | ea175812465fa30866fe90c6461f416c4af1d6b2 | 3,645,873 |
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... | 37c27cced9cc77f3a3aefef32d56f92f0ceb292f | 3,645,874 |
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 "" | b7b8faf55095288e5c2d693aeed85f6412449c08 | 3,645,875 |
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) | 44b7fb501a10551167ad37ffdafaef42c6c849b9 | 3,645,876 |
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... | 99b89d4fd9f35deab141e178aaa107dabf35ccfe | 3,645,877 |
def tph_chart_view(request, template_name="monitor/chart.html", **kwargs):
"""Create example view.
that inserts content into the dash context passed to the dash application.
"""
logger.debug('start')
context = {
'site_title': 'TPH monitor',
'title': 'TPH chart via Plotly Dash for D... | 135adb437fb3c27327ea8c6a83e33dfadec1f3ce | 3,645,878 |
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... | 701097aaebbe15306818593daf501b0f7d622f49 | 3,645,879 |
import re
def ExtractCalledByNatives(contents):
"""Parses all methods annotated with @CalledByNative.
Args:
contents: the contents of the java file.
Returns:
A list of dict with information about the annotated methods.
TODO(bulach): return a CalledByNative object.
Raises:
ParseError: if una... | bbf8c80cc7ac323469de7bf8a2fdf0da84b834e1 | 3,645,880 |
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... | 8deaec88369d2d0cb42ebdd3961caf891357335b | 3,645,881 |
from datetime import datetime
import re
def charReplace(contentData, modificationFlag):
"""
Attempts to convert PowerShell char data types using Hex and Int values into ASCII.
Args:
contentData: [char]101
modificationFlag: Boolean
Returns:
contentData: "e"
modificatio... | ca321869608e7524c260a8feeea6f2cf8bd6fd49 | 3,645,882 |
import six
import os
def _prepare_config(separate, resources, flavor_ref,
git_command, zip_patch,
directory, image_ref, architecture, use_arestor):
"""Prepare the Argus config file."""
conf = six.moves.configparser.SafeConfigParser()
conf.add_section("argus")
c... | b2f1528ea0d8426316b7b5a1f6b40f5cc723f5d5 | 3,645,883 |
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... | 32674a4528b69b756b3fc5f161dcbfd3ceaba01f | 3,645,884 |
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}'"... | 6aa90764c167be9a1d980dea0e54243a9467c276 | 3,645,885 |
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... | e19d1a5cf567f72ae261cc0fef69b03e2d8a9696 | 3,645,886 |
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... | 3fbcd1477fc90553cdc5371440083c9737b4bf5b | 3,645,887 |
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 *)
... | 32d827fe0c0d152af98e6bed5baa7a24d372c4f8 | 3,645,888 |
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... | 120e1ee364bf64b00b504fcdc8d0769a6d02db7b | 3,645,889 |
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... | c5c28b7779e9cab2488696435832f9f7cbd03e57 | 3,645,890 |
def GetExperimentStatus(experiment, knobs, exp_data, track='stable'):
"""Determine the status and source of a given experiment.
Take into account all ways that a given experiment may be enabled and allow
the client to determine why a given experiment has a particular status.
Experiments at 100% are always on.... | 9deef37c2e517987bd49cf91892149f202b43993 | 3,645,891 |
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'... | 90488103d929929615dc1e5de1531102a9f7b96a | 3,645,892 |
import re
import tempfile
from pathlib import Path
async def submit_changesheet(
uploaded_file: UploadFile = File(...),
mdb: MongoDatabase = Depends(get_mongo_db),
user: User = Depends(get_current_active_user),
):
"""
Example changesheet [here](https://github.com/microbiomedata/nmdc-runtime/blob/... | ebe9306aba0fef88c906c3c584f87e7c783fe9d8 | 3,645,893 |
import json
def get_notes(request, course, page=DEFAULT_PAGE, page_size=DEFAULT_PAGE_SIZE, text=None):
"""
Returns paginated list of notes for the user.
Arguments:
request: HTTP request object
course: Course descriptor
page: requested or default page number
page_size: requ... | 3256cacd845cf2fd07027cf6b3f2547a59cefd0f | 3,645,894 |
import numpy
def convert_hdf_to_gaintable(f):
""" Convert HDF root to a GainTable
:param f:
:return:
"""
assert f.attrs['ARL_data_model'] == "GainTable", "Not a GainTable"
receptor_frame = ReceptorFrame(f.attrs['receptor_frame'])
frequency = numpy.array(f.attrs['frequency'])
data = nu... | dd816eb0730b0f9993efe07c2b28db692ac6a06e | 3,645,895 |
import pathlib
def list_files(directory):
"""Returns all files in a given directory
"""
return [f for f in pathlib.Path(directory).iterdir() if f.is_file() and not f.name.startswith('.')] | a8c5fea794198c17c2aff41a1a07009984a8e61f | 3,645,896 |
def condition_conjunction(conditions):
"""Do conjuction of conditions if there are more than one, otherwise just
return the single condition."""
if not conditions:
return None
elif len(conditions) == 1:
return conditions[0]
else:
return sql.expression.and_(*conditions) | acf26bd9b8e47d27ad83815be70216db0e4ad091 | 3,645,897 |
def get_claimed_referrals(char):
""" Return how many claimed referrals this character has. """
return db((db.referral.referrer==char) & (db.referral.claimed==True)).count() | 5820cdd21cbb77f6a43537ae18dc227ad4fec1b8 | 3,645,898 |
def groupsplit(X, y, valsplit):
"""
Used to split the dataset by datapoint_id into train and test sets.
The data is split to ensure all datapoints for each datapoint_id occurs completely in the respective dataset split.
Note that where there is validation set, data is split with 80% for training and 2... | e8ba393270a32e2464c30409a13b2c5e9528afdd | 3,645,899 |
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