content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
from typing import Dict
def render_into_template(
screenshots: Dict[str, Image.Image],
template: Image.Image,
) -> Image.Image:
"""Place all the screenshots, into the correct place."""
# Place all the screenshots
for device, screenshot in screenshots.items():
template.paste(screenshot, SCR... | 67313b0005bb2c1dee9650a555731de0b4b6f569 | 3,613,811 |
import unicodedata
import re
from bs4 import BeautifulSoup
def _process_text(text):
"""
Pre-process Text
"""
text = unicodedata.normalize("NFKD", text) # Normalize
text = '\n'.join(text.splitlines()) # Let python take care of unicode break lines
# Take care of breaklines & whitespaces c... | e593a8450d92d8c59c8ae20c6889b678c78b886d | 3,613,812 |
def get_model_effectors(file_path, sheet_name):
"""
Gets the effectors and respective references for each reaction on the kinetics1 sheet and returns a dictionary
{rxn_id : ([effector_list], [effector_references])}. Entry i in effector_references contains all references as a
string for effector i in... | b0f49bf8ae7e5339653440ab6ea036914762cff0 | 3,613,813 |
def account(request, user_id):
"""
:param request:
:return:
"""
if not request.user.is_superuser:
return HttpResponseRedirect(reverse('index'))
error_messages = []
user = User.objects.get(id=user_id)
user_insts = UserInstance.objects.filter(user_id=user_id)
instances = Inst... | 7390b1f326123f9c05b7f4b83fa4fe2e491466de | 3,613,814 |
import hashlib
def create_hash_key(index: str, params: str) -> str:
"""
:param index: индекс в elasticsearch
:param params: параметры запроса
:return: хешированый ключ в md5
"""
hash_key = hashlib.md5(params.encode()).hexdigest()
return f"{index}:{hash_key}" | 1762d3d089cd26c6c7e9423fd37e782b61be1235 | 3,613,815 |
def _estimate_mmd2_linear_time(latent, i1, i2, sigma=None):
"""From Gretton et. al. 2012"""
if sigma is None:
sigma = estimate_median_sigma(latent)
A = -0.5 / sigma
n = min(len(i1), len(i2))
m = n // 2
assert m > 0
k = lambda x,y: np.exp(A * np.sum(np.power(x-y,2)))
h = lambda x1,y1,x2,y2: k(x1,x2)+k(y1,y2)-k... | f8ded845b3d2b14faa814ade8a14c13252cd1630 | 3,613,816 |
def CreateVotes(blockable, count, **kwargs):
"""Creates multiple Vote entites for the given Blockable.
Args:
blockable: The Blockable to create Votes for.
count: int, The number of Votes to create.
**kwargs: dict, Any Vote properties to customize.
Returns:
The newly-created Vote entities.
"""
... | e925da1638779d61b0b2745b9ad9f22e837fe1d1 | 3,613,817 |
def compute_codes_requiring_type(handle_data, types_to_codes, registry=None):
"""Compute a DictOfStringSets of return codes to a set of input types able
to provide the ability to generate that code.
handle_data is a HandleData instance.
d is a dictionary of input types to associated return codes(same f... | e10cff2df26baef6f68b52ec0de9987c8f938ec3 | 3,613,819 |
def delta_disk_neighbors(
poses: np.ndarray,
agent: int,
delta: float) -> np.ndarray:
"""Return the agents within the 2-norm of the supplied agent.
NOTE: The does not including the agent itself!
Parameters
----------
poses : np.ndarray
A `3xN` numpy array representi... | 69735dbac90547d89eebb65ef524e570872c30f1 | 3,613,820 |
def categorize_answers(df, question, answer_column):
""" Extract a question answered and count different answers.
Parameters
----------
df : Pandas Dataframe
Dataframe containing questionnaire data
question : str
question id
answer_column : str
column containing the an... | 66af22d0e0a3af854f3e083186cff094e8420f1c | 3,613,821 |
async def async_setup_entry(opp: OpenPeerPower, entry: ConfigEntry) -> bool:
"""Set up Verisure from a config entry."""
coordinator = VerisureDataUpdateCoordinator(opp, entry=entry)
if not await coordinator.async_login():
raise ConfigEntryAuthFailed
entry.async_on_unload(
opp.bus.async... | 81f5edeaaeec7cb03496e3bd9fcde130f23c8ff1 | 3,613,822 |
def get_spreadsheet(user, spreadsheet_id):
"""
Get spreadsheet
:type user: django.contrib.auth.models.User
:param user: User of spreadsheet
:type spreadsheet_id: str
:param spreadsheet_id: Spreadsheet ID of spreadsheet to get
:rtype: Google `Spreadsheet` resource, int
:return: Spread sh... | 8d3ef4ac7bb31761e40e4f5d1d721acee5407dd4 | 3,613,824 |
import base64
def GetFileSha1(file_path):
"""Returns the SHA1 checksum of the file given (base64 encoded)."""
return base64.b64encode(GetFileHashes(file_path, do_sha1=True)['sha1']) | 5c6fd72de791f835731a966df419bbfb11b7214a | 3,613,825 |
def quarterly_visits(customer_logins):
"""
Small subroutine to return quarterly visits from an amount of
customer login data.
"""
visits = np.zeros(4)
customer_visits = len(customer_logins.index)
# 6 is the size of a part of day, integer division gives a
# number between 0 and 3
vi... | afcad1111a6b98134d9aaed56e9570581053b478 | 3,613,826 |
def connect_UDP(host, port, waitTimeout=None):
"""
Connect RPC server via UDP. Returns C{t.i.d.Deferred} that will
callback with C{protocol.MsgpackDatagramProtocol} object.
@param host: IP address of host.
@type host: C{str}
@param port: port number.
@type port: C{int}
@param waitTimeou... | 68c6d35f6970d7b4cf3cef5ab651e3f7c809d84d | 3,613,827 |
def get_root_url():
"""Return the root URL for this resource."""
# path = request.path
# path = path[1:].split('/')
# path = '/'.join(path[:2])
# return request.url_root + path
return request.url_root | 136e37f2768f7c6dd2bb1e95940d2768a68e970b | 3,613,828 |
def welcome():
"""List all available api routes."""
return (
f"Available Routes:<br/>"
f"/api/v1.0/precipitation<br/>"
f"/api/v1.0/stations<br/>"
f"/api/v1.0/tobs<br/>"
f"/api/v1.0/2017-07-01<br/>"
f"/api/v1.0/2017-07-01/2017-07-10<br/>"
) | b1ee7659f4eb778559cdaa9a2afbbb4e36563ed1 | 3,613,829 |
import hashlib
def HashFileContents(filename):
"""Return the hash (sha1) of tthe contents of a file.
Args:
filename: Filename to read.
Returns:
The sha1 of a file.
"""
hasher = hashlib.sha1()
fh = open(filename, 'rb')
try:
while True:
data = fh.read(4096)
if not data:
br... | 930ecd76dac76c09a17cddeeb52229189098553a | 3,613,830 |
import pprint
def hello_airflow(execution_date: dt.datetime, argument=None, **kwargs):
"""
Print the execution date (and other variables passed from airflow).
Args:
execution_date (dt.datetime): the time of the dag's execution (passed by airflow)
argument: an example argument
**kw... | 8c34d614f7ce476d65dc66f6d17a1536620670a4 | 3,613,831 |
def get_moyenne(points_3D, indice):
"""Calcul la moyenne d'une coordonnée des points,
la profondeur est le 3 ème = z, le y est la verticale
indice = 0 pour x, 1 pour y, 2 pour z
"""
somme = 0
n = 0
for i in range(17):
if points_3D[i]:
n += 1
somme += points_3... | 739548f93b2361e5f7e442dd0504e6b619ded1f9 | 3,613,832 |
def simplify_list_item_mathematical(list_item_mathematical: list) -> Real:
"""
Apply mathematical operations on the operands and reduce to 1 value
Not Used
:param list_item_mathematical: list of mathematical items
:return: value
"""
# Current value
value = None
# Current Operator... | c28fd34970eeb3f97da101483843071f2429d299 | 3,613,833 |
from typing import cast
def ca_authorize_key(h_session, h_object, auth_data):
"""
User authorizes key within session or access for use
:param h_session: session handle
:param object: key handle to authorize
:param auth_data: authorization byte list, e.g. [11, 12, 13, ..]
:return: Ret code
... | c84ca52e080c4b9a15505e89d9e8cc89a163c31b | 3,613,834 |
def code_to_md(source, metadata, language):
"""
Represent a code cell with given source and metadata as a md cell
:param source:
:param metadata:
:param language:
:return:
"""
options = []
if language:
options.append(language)
if 'name' in metadata:
options.append... | aa51b274d4aacd1bc5dce5bf9ee638429f0f9370 | 3,613,835 |
def get_schema(is_ipv6, octet):
"""Get the template with word slots"""
new_line = '\n'
period = '.'
space = ' '
non_words = [new_line, period, space]
if is_ipv6:
schema = [octet, octet, 'and', octet, octet, new_line, octet, octet,
octet, octet, octet, octet, octet, peri... | 039e8a623be8e37acea7f2a4373a3b5f9bdaf53c | 3,613,836 |
def zone_from_longitude(phi):
"""Return the difference between UT and local mean time at longitude
'phi' as a fraction of a day."""
return phi / deg(360) | 690b965b13d1dad9d86fb0f6f41b55f32e3ed20d | 3,613,837 |
def get_version(arg):
""" Get version.
"""
if isinstance(arg, pymongo.MongoClient):
return arg.server_info()['version']
elif isinstance(arg, str) or isinstance(arg, unicode):
host, port = parse_hostportstr(arg)
with pymongo.MongoClient(host, port, connect=True, serverSelectionTim... | c208fcfb93d8bda61e7bdcd3aee55bf84b4b51bd | 3,613,838 |
def impute_features(feature_df):
"""Imputes data using the following methods:
- `smoothed_ssn`: forward fill
- `solar_wind`: interpolation
"""
# forward fill sunspot data for the rest of the month
feature_df.smoothed_ssn = feature_df.smoothed_ssn.fillna(method="ffill")
# interpolate between ... | 3b61e29b30a011f86a8f18f649b77e72f3f87878 | 3,613,839 |
def module_fixture():
"""Mock a module."""
return MockModule("test") | ec32830f43cbeb3330ffc4d95be115a403aab521 | 3,613,840 |
def update_user(username):
""" Update attributes for a single user. Only users with 'role' admin
can update users.
Args:
password(str): user's password
role(int): user's role
Returns:
success(bool): successfully updated
"""
if not g.user.is_authe... | a1005d0eebe6263fc437edfd5791b404846094f8 | 3,613,842 |
import torch
def loss_calc_pose(out, label, gpu0):
"""
This function returns loss for the pose auxilary task
"""
# out shape batch_size x channels x h x w -> batch_size x channels x h x w
# label shape h x w x 1 x batch_size -> batch_size x 1 x h x w
label = torch.from_numpy(label).long()
... | 77f5a8b15307eeb729599f75843bdb4ab45ae8dd | 3,613,843 |
def retrieve_text_document(image, default_lang=ALL_LANGUAGE) -> TextDocument:
"""
Retrieves text with all possible languages, detects the exact language and retrieves the
text again, but with the correct language.
Should only be used for medium or large images
"""
text = pytesseract.image_to_s... | 6ebc5359f46df4a88be98b800e6a9c441a520d23 | 3,613,845 |
def login_view(request):
"""Provide the login view and functionality."""
if request.user.is_authenticated():
return redirect(reverse('index'))
form = UserLoginForm(request.POST or None, request=request)
next_page = request.GET.get('next', reverse('index'))
if form.is_valid():
if re... | b4e18a81dda4d11b1840ed3ce129f79a39d5f549 | 3,613,847 |
import time
def chi2_bin(df: pd.DataFrame, x: str, y: str, bins=5, init_bins=100, init_method='qcut', init_precision=3,
print_process=True):
"""
卡方分箱
:param df: 数据集
:param x: 待分箱特征名称
:param y: 目标变量的名称
:param bins: 最终的分箱数量
:param init_bins: 初始化分箱的数量，若为空则钚进行初始化的分箱
:param in... | 9ae231a8bdacc262fef9b18540bb3e3e2e08e339 | 3,613,848 |
def cache_control_expires(num_hours):
"""
Set the appropriate Cache-Control and Expires headers for the given
number of hours.
"""
num_seconds = int(num_hours * 60 * 60)
def decorator(func):
@wraps(func)
def inner(request, *args, **kwargs):
response = func(request, *... | b6f726e84b9d9e43775e130effeb023ccd86c7af | 3,613,849 |
def get_widget_at_mouse():
"""
Get the widget under the mouse
:return: variant, QWidget || None
"""
current_pos = QtGui.QCursor().pos()
widget = QApplication.widgetAt(current_pos)
return widget | 52e11f16d34723170cbeb76e8f3c36c1ba5a022a | 3,613,850 |
from typing import Dict
from typing import List
from typing import Union
from typing import Iterable
from datetime import datetime
def build_can_scraper_dataframe(
data_by_variable: Dict[ccd_helpers.ScraperVariable, List[float]],
location=DEFAULT_LOCATION,
location_type=DEFAULT_LOCATION_TYPE,
location... | 80c4f3c4f3a8b443f4291c89f9e08afe07926e68 | 3,613,851 |
import re
def process_text():
"""Remove emoticons, numbers etc. and returns list of cleaned tweets."""
data = pull_tweets()
regex_remove = "(@[A-Za-z0-9]+)|([^0-9A-Za-z \t])|(\w+:\/\/\S+)|^RT|http.+?"
stripped_text = [
re.sub(regex_remove, '',
tweets).strip() for tweets in data
... | 667ed53c3f23c4d280c389692feea12e3b309e91 | 3,613,853 |
import copy
def concat(input_op_nodes: list, output_name: str, column_names: [list, None] = None):
"""
Define Concat operation.
:param input_op_nodes: List of parent nodes for the node returned by this method.
:param output_name: Name of returned Concat node.
:param column_names: List of output r... | 03da1af22d5edc44e5a4de2be167f474d603bfdf | 3,613,854 |
def ca_set_container_policy(h_session, h_containerber, policy_id, policy_val):
"""Sets a policy on the container.
NOTE: With per partition SO this method should generally not be used. Instead
ca_set_partition_policies should be used
:param int h_session: Session handle
:param h_containerber: The c... | d697965035ce173f9c119498d2923c0f81187894 | 3,613,856 |
def crop_xyz_grid_by_extents(xyzgrid,extents):
""" crop grid in xy plane
xyzgrid: Dataframe with x,y,z columns or ARRAY with first 3 columns being x,y,z coordinates
extents: (xmin,ymin,xmax,ymax)
returns: cropped Dataframe
"""
if type(xyzgrid) == np.array:
xyzgridnew = pd.DataFrame(xyzgrid,columns=... | 52e456f2d63b87727a6871a2d9404558edbd8da1 | 3,613,857 |
def _bytes_through_tmp_image(arr):
"""Retrieve binary blob for a numpy array image"""
mimetype = 'tiff'
arr_min = numpy.min(arr)
arr_max = numpy.max(arr)
# if (arr_max > 1) & (arr_max <= 255):
# arr = arr / 255 # numpy.uint8(arr)
print "MIN:"
print numpy.min(arr)
print "MAX:"
... | fb4a704ae331a5f2e807d1d6ad65df52c420fed2 | 3,613,858 |
def _create_machine_onapp(conn, public_key,
machine_name, image, size_ram,
size_cpu, size_disk_primary, size_disk_swap,
boot, build, cpu_priority, cpu_sockets,
cpu_threads, port_speed,
locat... | 3385f16f2548412f28b15f67809bdac1e1205a64 | 3,613,859 |
import random
def rand_5() -> int:
"""
Generates a single, randomly generated 5-digit number.
Returns:
The generated 5-digit number.
"""
return random.randrange(100000) | b6abb4ecbd4397548e35c386a4e653df205282ea | 3,613,860 |
def GVizGetLayoutStr(*args):
"""
GVizGetLayoutStr(TGVizLayout const & Layout) -> TStr
Parameters:
Layout: TGVizLayout const &
"""
return _snap.GVizGetLayoutStr(*args) | e0c40ff6d0f74c9d4c423abd5c41b2507481242c | 3,613,861 |
def discard_and_merge_types_select_most_common_n(dataset: pd.DataFrame, most_common_n: int = 20) -> pd.DataFrame:
"""
It is possible that the negative example creation suffers due to a
long tail distribution of types.
- Can we merge some of the types?
- Using name based matching? Eg.
... | 7bf7c4b14ae8ceadb40c8fe92adb06b8fd4837b6 | 3,613,862 |
def iou(box_group1, box_group2):
""" Calculates the intersection over union (aka. Jaccard Index) between two boxes.
Boxes are assumed to be in corners format (xmin, ymin, xmax, ymax)
Args:
- box_group1: boxes in group 1
- box_group2: boxes in group 2
Returns:
- A numpy array of shape (len(... | 4a547c0b623cac4b58eb90ec71a58c18ad6c0a4a | 3,613,863 |
import random
def perform_DQN(agent, episodes, iterations, path, batch_size=4, C=30, randomize_theta=False):
"""
:param agent: the RL agent
:param batch_size: size of minibatch sampled from replay buffer
:param C: network update frequency
:return: agent, and other information about DQN
"""
... | 7c1404d2266472300127d54212e09220b8d119cc | 3,613,864 |
from typing import Mapping
from typing import Sequence
def freeze(data):
"""
:param data: Anything serializable as JSON
:return: An immutable and hashable version of `data`. Mappings are
replaced by `frozendict` instances, sequences are replaced by tuples,
and everything else is returned uncha... | d69bbd43c466ec50d3f915cb9d97b4eeb0de1d21 | 3,613,866 |
def getattribute(value, arg):
"""Gets an attribute of an object dynamically from a string name"""
assert hasattr(value, str(arg)), "Invalid %s in %s" % (arg, value)
return getattr(value, str(arg)) | e7cac978986448784f4b9f841e7126eca78236fa | 3,613,867 |
def task_project():
""" RESTful CRUD controller for options.s3json lookups """
if auth.permission.format != "s3json":
return ""
# Pre-process
def prep(r):
if r.method != "options":
return False
return True
s3.prep = prep
return s3_rest_controller() | 7afffb382e7ecf1bc1f5f398a94227a8722c7c90 | 3,613,868 |
import re
import click
def validate_memory(_ctx, _param, value):
"""Validate memory string."""
if value is None:
return
if not re.search(r'\d+[KkMmGg]$', value):
raise click.BadParameter('Memory format: nnn[K|M|G].')
return value | 105035f338138ff47b6505868c8bf9d2bf37fa91 | 3,613,869 |
from typing import Dict
from typing import Any
from typing import Optional
from typing import List
import inspect
def get_table_columns(
uri: str,
extra_params: Dict[str, Any],
schema: Optional[str],
table: str,
) -> List[Column]:
"""
Return all columns in a given table.
"""
engine = c... | 1518b79bf248282c2947eb7b748d7c653f313421 | 3,613,871 |
def page (result = ''):
"""Return the main form"""
return CGISH_HTML % {'SHELL_OUTPUT':result} | 72ab545440b2ed2d4151202ad91c58a68f3b582e | 3,613,872 |
def forge_formats( token, verbose ):
"""Retrieve and return the file formats currently
supported by the translation processes."""
headers = {'Authorization': 'Bearer ' + token}
r = requests.get(url_formats, headers=headers)
if verbose:
print '\nForge formats call:'
print ' Status:', r.status_code
... | e2ad74334486c9e4982b5d3e9003aebe6af21f76 | 3,613,873 |
import math
def pad_1dconv_input(input, kernel_size, mode="same"):
"""
This method pads the input for "same" and "full"
convolutions. Currently just Same and full padding modes have been
implemented
:param input: Input Tensor with shape BATCH_SIZE X TIME_STEPS X FEATURES
:param mode:
... | 60baf28bcca653e0df098604ed12013456cf12a2 | 3,613,874 |
def create_dates_list(start_date, end_date):
""" Return list of days in range of start and end date for itinerary."""
delta = end_date - start_date
dates = []
for d in range(delta.days + 1):
dates.append(start_date + timedelta(days = d))
return dates | 9240852b3e0b9f4d54ef547d0c35f63d4d2235ea | 3,613,875 |
def viterbi(observations, states, priors, transitions, emissions,
probabilistic=False):
"""Perform HMM smoothing over observations via Viteri algorithm
:param list(str) observations: List/sequence of activity states
:param numpy.array states: List of unique activity state labels
:param numpy... | 6fd74e9968dc10779bf2ac64595003b66598d5b6 | 3,613,878 |
def build_analysis_data(analyses):
"""
Args:
analyses: (dict) of analysis
Returns:
dict: formatted entry context
"""
entry_context = dict()
entry_context['VMRay.Analysis(val.AnalysisID === obj.AnalysisID)'] = [
{
'AnalysisID': analysis.get('analysis_id'),
... | 6a4d52966ca2cac22e74574110e7da6b5882bb64 | 3,613,879 |
def CurveFilletPoints(curve_id_0, curve_id_1, radius=1.0, base_point_0=None, base_point_1=None, return_points=True):
"""Find points at which to cut a pair of curves so that a fillet of a
specified radius fits. A fillet point is a pair of points (point0, point1)
such that there is a circle of radius tangent ... | f770b62804be7ced30abcbfdee664348c83a9167 | 3,613,880 |
from datetime import datetime
def get_today():
"""
Returns the datetime.date for today. Needed since tests cannot mock a
builtin type: http://stackoverflow.com/a/24005764/4651668
"""
return datetime.date.today() | c03ccfd7ab55036c83d9b2fb2b02386ab61e92b2 | 3,613,881 |
def template_model1():
"""
--------------------------------------------------------------------------
template_model1: Variables / RHS / AUX
--------------------------------------------------------------------------
"""
model_type = 'continuous' # either 'discrete' or 'continuous'
model1 = d... | 3095e6093a04572ebc32a4d35d0579d379ee3464 | 3,613,882 |
def flags(flags):
"""Hard-code KZC flags"""
def f(test, way):
test.way = None
test.args += flags
return f | 4257fd66abc036af0d9ef9f971fcc834c735460a | 3,613,883 |
def indexColumnPivot(Z, minOrMax, tableaux, _colPivot): # seach the value that'll come to base (index column)
"""
[seach the index of pivot column. That is a value that'll come to base]
Arguments:
Z {[list]} -- [list from Z line]
minOrMax {[int]} -- [description]
tableaux {[matr... | b47ac8f8ba3661e193cf9b687d5e0ff6a4bd1d7e | 3,613,884 |
from typing import Callable
def register_model(
name: str, build_function: Callable,
model_type=None, convex=None,
best_value=None, best_dual=None,
opt_value=None,
bigM=None) -> None:
"""
Registers the model in the model library.
Parameters
----------
name ... | 9c6c5d53b06968712ce648880d7a0ce443b7229e | 3,613,885 |
from re import T
def cim_size(estimated: T.FloatTensor, target: T.FloatTensor) -> float:
"""
Empirically estimated kernel size for CIM taken as the average reconstruction error
based on Eq. 25 in https://lcs.ios.ac.cn/~ydshen/ICDM-12.pdf.
Parameters:
estimated (list): current Q-values
... | 767237a433757943defc4fe74af4a2a7f1812d7d | 3,613,886 |
def send_message(service, message):
"""Send an email message.
Args:
service: Authorized Gmail API service instance.
user_id: User's email address. The special value "me"
can be used to indicate the authenticated user.
message: Message to be sent.
Returns:
Sent Messa... | 18ec4cf6e72800505860b8d202ad7f5ffa46839f | 3,613,889 |
import re
def rgb2hex(rgb_string, drop_alpha=False) -> str:
"""Convert an RGB string to HEX.
Args:
rgb_string (str): This is the RGB or RGBA string to convert.
drop_alpha (bool): ``True`` will **drop the alpha value** from
the HEX string. This is useful for colour maps that
... | ac673d7ea668a516372650677374ccc81b304b60 | 3,613,890 |
import time
import torch
def train_cn_consistency(net, train_loader, optimizer, scheduler):
"""Train for one epoch."""
print('running train_cn_consistency')
batch_time = AverageMeter()
data_time = AverageMeter()
losses = AverageMeter()
s_losses = AverageMeter()
c_losses = AverageMeter()
... | ddcff494475915f0f657c1127e83cf53d96bd875 | 3,613,891 |
def getLink(node, attr, destination=False, source=False):
"""
:param node:
:param attr:
:return: Linked node
:rtype: str/None
"""
# validate plug
plug = getPlug(node, attr)
if not cmds.objExists(plug):
return
# get connections
connections = cmds.listConnections(
... | 65f23c12b10e22b2d81b984521eac2ead6fb291d | 3,613,892 |
def _reset_pk(query, pk = 'id', num = 0):
""" 找出需要重新排列的主键 """
last_diff, changes = 0, []
start, stop = 0, 0
if num > 0:
query = query.filter(Expr(pk)>num)
for row in query.order_by(pk).iter(pk):
id, num = row[pk], num + 1
curr_diff = id - num
if curr_diff == 0:
... | 967da338f9e2da362b452fee70bfac461a5db63d | 3,613,893 |
def batch(data, batch_size, batch_size_fn=None):
"""Yield elements from data in chunks of batch_size."""
if batch_size_fn is None:
def batch_size_fn(new, count, sofar):
return count
minibatch, size_so_far = [], 0
for ex in data:
minibatch.append(ex)
size_so_far = batc... | eab78d22bba1b0575dcb5fedc2820f2115a6a9f5 | 3,613,894 |
def interpolate_lightcurve(lc_table=None, lc_array=None):
"""Returns linear interpolator of epoch lightcurve
"""
if lc_array is None:
if lc_table is None:
raise ValueError('Must provide one of [lc_table, lc_array]')
else:
lc_array = extract_lightcurve_array(lc_table)
... | 3897b8a5cd836d8ecbc540eb841ab33ca0eb8277 | 3,613,895 |
def get_account_user_id(**kwargs):
""" Returns account_user_id from arguments
Keyword arguments:
:param vm_login_id: user's VM login ID like p100
:param email: user's E-Mail address
:returns: account_user_id
:rtype: int
"""
if 'vm_login_id' in kwargs:
users = User.all()
... | 93669b081cd5535be7a805aa6961da59fd9f4127 | 3,613,896 |
def lnZ_PEB(time: np.ndarray, flux: np.ndarray, sigma: float,
P_orb: float, M_s: float, R_s: float, Teff: float,
Z: float, plx: float, contrast_curve_file: str = None,
N: int = 1000000):
"""
Calculates the marginal likelihood of the PEB scenario.
Args:
time (numpy... | b6c6a0c5f31ee44900280f36c3e91bdbd351e238 | 3,613,897 |
def interval2string_m(i: float) -> str:
"""Convert a time interval to a string or to NA if it is does not have a value
Arguments:
i: is a number of seconds
Returns:
a string of the number of minutes represented or NA if i is not a float
"""
if type(i) == float:
... | e7d710d10fb8a3393ca2fad4d99e7acc5f4b45eb | 3,613,898 |
def ldns_sign_public_buffer(*args):
"""LDNS buffer."""
return _ldns.ldns_sign_public_buffer(*args) | a81f529c8b735403279b49bd5f253411b50c01fa | 3,613,899 |
def download_image(url):
"""Downloads ipg, jpeg fils from given URL"""
response = request.urlopen(url)
return ContentFile(response.read()) | 6a96efe321dcbd84134400dce34de5484d7aa53f | 3,613,900 |
from typing import Tuple
def _evaluate(dataset: tf.data.Dataset, model: tf.keras.Model,
loss_fn: tf.keras.losses.Loss) -> Tuple[float, float]:
"""Evaluates the given model for the whole dataset once."""
loss_sum = 0
correct_item_count = 0
item_count = 0
for (x, y) in dataset:
... | ba950cea2b5bee509d0b4392f762bbb0f9a3ab1f | 3,613,901 |
def tab(column) -> str:
"""Emulates the TAB command in BASIC. Returns a string with ASCII
codes for setting the cursor to the specified column."""
return f"\r\33[{column}C" | d57e0d6840c9f446b2832bbe725bc986aaabf13e | 3,613,902 |
def _make_laplace_numba_2d(grid: CartesianGrid) -> OperatorType:
"""make a 2d laplace operator using numba compilation
Args:
grid (:class:`~pde.grids.cartesian.CartesianGrid`):
The grid for which the operator is created
Returns:
A function that can be applied to an array of val... | 5e34b9fadcd9a8f8304409f00e744e49645cc89a | 3,613,903 |
def preview(slug):
"""Show the preview of a newly created or edited post.
Parameters
----------
slug : str
The slug is the part of the URL which identifies a particular post
on our blog in an easy to read form.
"""
post = session['post']
# When I put the post object for the ... | d2116c426ec7bf657e5fb596cbb257c690f411b4 | 3,613,904 |
def get_longest_streak_of_all_habits(session):
"""
:return: the value of the largest value in the streak column.
"""
try:
longest_streak_for_all_habits = (max(session.query(HabitHistory.streak)
.all()))
except ValueError:
raise NoHabitsInHisto... | 3be2a0b2e458663e90a810c49cd41f3fda6a98ad | 3,613,905 |
import tokenize
def eye(N, chunks="auto", M=None, k=0, dtype=float):
"""
Return a 2-D Array with ones on the diagonal and zeros elsewhere.
Parameters
----------
N : int
Number of rows in the output.
chunks : int, str
How to chunk the array. Must be one of the following forms:
... | 0882c19f3abd5d9c6936fb704664b129c2b16d0e | 3,613,907 |
def calc_num_walls(side_length, room_positions, ap_positions):
"""
Calculate the number of walls between each room to each AP.
This is used to calculated the wall losses as well as the indoor
pathloss.
Parameters
----------
side_length : float
The side length of the square room.
... | cc1fc51189e614b353810b2f76421aa6951fa84e | 3,613,908 |
import binascii
def x(h):
"""Convert a hex string to bytes"""
return binascii.unhexlify(h.encode('utf8')) | 0cbba146b22419f9e67f0a2ea46851a47826d4f8 | 3,613,910 |
def get_new_goal(current_pos, current_dest, home_pos, rally_point, batt_level,
blocking_time=10, speed=5, energy_consumption=1):
"""
Function for deciding the new goal
All the input coordinates are in the format [LAT, LON] (deg).
returns a [int, int] list with [X, Y] coordinates of n... | da8a22da63d518935a1d1cd2b9aa9515abc301e5 | 3,613,911 |
def is_cuda_consistent(*args):
"""
See if the cuda states are consistent among variables (of type either
tensors or torch.autograd.Variable). For example,
import torch
from torch.autograd import Variable
import torch.nn as nn
net = nn.Linear(512, 10)
tensor = torch.... | 6554bd61956ae08080cf3d4564387cddc7ad0cb7 | 3,613,912 |
def create_nginx_config(server, port):
"""Create NGINX config in sites-enabled directory"""
if config_count() >= config_limit:
abort(400)
ip = request.remote_addr
nginx_config = nginx_sites_enabled + '/' + server
temp = sys.stdout
sys.stdout = open(nginx_config, 'w')
print template... | b998c0dcd27f8578da76ba6fa24cd11c4ed76940 | 3,613,914 |
def elbo_batch_loss(model, X, y, inds, samples):
"""Compute an estimate of the negative ELBO loss from a single batch.
Args:
X ([N, input_dim] numpy array): Train inputs.
y ([N, output_dim] numpy array): Train outputs.
inds ([batch_size] torch tensor): Indices for the batch.
samp... | 8fc4fa1447607ab7d2190d226df606637b6d98e5 | 3,613,915 |
def to_epoch(str_time):
"""Take in string time(yyyy-mm-dd) and convert to epoch time."""
return int(dt.datetime.strptime(str_time, "%Y-%m-%d").timestamp()) | c085f379399ad7257cf2a1d190ff3360bccda821 | 3,613,917 |
def _rpn_loss_regr(y_true, y_pred):
"""
smooth L1 loss
y_ture [1][HXWX10][3] (class,regr)
y_pred [1][HXWX10][2] (reger)
"""
sigma = 9.0
cls = y_true[0, :, 0]
regr = y_true[0, :, 1:3]
regr_keep = tf.where(K.equal(cls, 1))[:, 0]
regr_true = tf.gather(regr, regr_keep)
regr_pr... | 52cdfc439af2a91a3d638bff5ba46925c90c2063 | 3,613,918 |
def create_markdown_file_from_filename(markdown_filename:str) -> SuccessErrors:
"""Creates a markdown file based on incoming filename suggestion
If already exists, returns false,
If other os.file issue, returns false,
If successful, returns true
Args:
markdown_filename (str),
... | c02f1de1d0f749e60268a56537b10ff4e15544ad | 3,613,919 |
def fit_msm(trajectory, prefix=None, save_path=None):
"""Function to fit the msm to a given trajectory and save the vizualization
Args:
trajectory ([type]): Time series to be discretized
prefix ([type], optional): Name to save a file.
save_path ([type], optional): Wheree to save a fil... | 2f7454f597a9cc3b0daa54c71c7a1e0dba455af5 | 3,613,920 |
def dataclass(
_cls = None,
*arg,
init = True,
repr = True,
eq = True,
order = False,
unsafe_hash = False,
):
"""
Modification of dataclasses.dataclass that adds the following methods:
1. dataclass.from_tuple(data_tuple: Tuple[Any])
2. data... | 5c5315d089496d27554e72f87f67bad85ec45ba1 | 3,613,921 |
def get_quiz_info(random_words):
"""
get examples and random answers for each test word in random_words
:param random_words: a list of random test words
:return: a list of quiz information
"""
db_session = DB_Session()
allrows = db_session.query(TestWords)
quiz_info = []
for word in ... | 3a3d994dc7ba77d6a2a1f1ed36ef0c94244f4baa | 3,613,922 |
def parse_dependencies(file_names):
"""Program logic: read files, verify dependencies.
For each input file, read lines and create dependencies. Verify each dependency.
:param file_names: files to read dependencies from.
:return: The list of dependencies, each verified.
"""
# type: (List[Text])... | 2b34060b79e673b84b5c29114407a7d0e876463d | 3,613,923 |
def load_model_from_link(name, **overrides):
"""Load a model from a shortcut link, or directory in spaCy data path."""
path = get_data_path() / name / '__init__.py'
try:
cls = import_file(name, path)
except AttributeError:
raise IOError(Errors.E051.format(name=name))
return cls.load(... | 9b640bcb621874fcc37bf64853d37dd57add4fe0 | 3,613,924 |
import requests
def tencent_resolve(url_like):
"""根据输入的url_like，查询其腾讯安全接口查询结果
:url_like: 可能有几种形式：url: http://www.baidu.com，domain: www.baidu.com，ip: 14.15.15.17，甚至可能是：http://14.15.16.17:80
:returns: {url_like: tencent}
"""
url = TENCENT_URL
payload = {
'dname': url_like
}
hea... | 89f5f4eb20dfa3a503312eace80bd900acff6146 | 3,613,925 |
def host_create(context, values):
"""Create a host.
:param context: context to query under
:param values: dictionary of host attributes to create
:returns: dictionary-like object containing created host
"""
return IMPL.host_create(context, values) | d7285795b42b4eca9c9bc19f72d18cad8e36d464 | 3,613,926 |
def __dispatch_remove_command(arguments: list) -> str:
"""
Dispatches command to remove file/folder
Returns command that was run
"""
command = ""
if arguments["file"]:
command = "remove-file"
library.remove_file(arguments["file"])
elif arguments["folder"]:
command = "... | fd94f3fcd929b9aa220f99684282b439023b728b | 3,613,927 |
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