content stringlengths 22 815k | id int64 0 4.91M |
|---|---|
def load_indice_file(file, net_config):
"""Take the idlfile, data mean and net configuration and create a generator
that outputs a jittered version of a random image from the annolist
that is mean corrected."""
indice_list = []
with open(file, 'r') as f:
while True:
line = f.read... | 5,342,500 |
def test_valid_args(voltage, expected_byte):
"""
Test if the return value of voltage_to_byte() is correct when passing
a valid voltage.
"""
byte = voltage_to_byte(voltage)
assert type(byte) is int
assert byte == expected_byte | 5,342,501 |
def context_list_entities(context):
"""
Returns list of entities to be displayed in list view
"""
# log.info(context['List_rows'])
if 'List_rows' in context:
return context['List_rows']['field_value']
elif 'entities' in context:
return context['entities']
log.warning("No enti... | 5,342,502 |
def run(arg):
"""Entry point"""
error_map = {}
validate_path(arg, None, error_map)
if len(error_map) > 0:
error_count = 0
for file, errors in error_map.items():
print(f"Error in {file}:")
for error in errors:
print(f" {error}")
e... | 5,342,503 |
def test_retrieve_events_where_is_admin_only_includes_events_where_is_admin(
user, member_of_organizer, organizer_type, membership_type, expected_events_amount
):
"""When retrieving events where is admin, only events where is admin should be returned"""
hs = GroupFactory(type=GroupType.BOARD, name=AdminGro... | 5,342,504 |
def _bitcode_symbols_partial_impl(
*,
actions,
binary_artifact,
bitcode_symbol_maps,
dependency_targets,
label_name,
output_discriminator,
package_bitcode,
platform_prerequisites):
"""Implementation for the bitcode symbols processing partial.""... | 5,342,505 |
def _str_trim_left(x):
"""
Remove leading whitespace.
"""
return x.str.replace(r"^\s*", "") | 5,342,506 |
def fabric_host(docker_client):
"""Keep this session scoped to save time"""
container = docker_client.containers.run(
"efagerberg/pytest-fabric-sshd:latest",
name="pytest-fabric-test-container",
ports={'22': '2222'},
detach=True,
)
env.disable_known_hosts = True
env.p... | 5,342,507 |
def zipcompress(items_list, flags_list):
"""
SeeAlso:
vt.zipcompress
"""
return [compress(list_, flags) for list_, flags in zip(items_list, flags_list)] | 5,342,508 |
def test_config_file_fails_missing_value(monkeypatch, presence, config):
"""Check if test fails with missing value in database configuration."""
def mock_file_config(self):
return {'database': {}}
monkeypatch.setattr(presence.builder, "fetch_file_config", mock_file_config)
status, msg = presen... | 5,342,509 |
def construct_run_config(iterations_per_loop):
"""Construct the run config."""
# Parse hparams
hparams = ssd_model.default_hparams()
hparams.parse(FLAGS.hparams)
return dict(
hparams.values(),
num_shards=FLAGS.num_shards,
num_examples_per_epoch=FLAGS.num_examples_per_epoch,
resnet_ch... | 5,342,510 |
def bezier_curve(points, nTimes=1000):
"""
Given a set of control points, return the
bezier curve defined by the control points.
Control points should be a list of lists, or list of tuples
such as [ [1,1],
[2,3],
[4,5], ..[Xn, Yn] ]
nTimes is ... | 5,342,511 |
def _compact_temporaries(exprs):
"""
Drop temporaries consisting of isolated symbols.
"""
# First of all, convert to SSA
exprs = makeit_ssa(exprs)
# What's gonna be dropped
mapper = {e.lhs: e.rhs for e in exprs
if e.lhs.is_Symbol and (q_leaf(e.rhs) or e.rhs.is_Function)}
... | 5,342,512 |
def print_formula(elements):
"""
The input dictionary, atoms and their amount, is processed to produce
the chemical formula as a string
Parameters
----------
elements : dict
The elements that form the metabolite and their corresponding amount
Returns
-------
formula : str
... | 5,342,513 |
def try_get_code(url):
"""Returns code of URL if exists in database, else None"""
command = """SELECT short FROM urls WHERE full=?;"""
result = __execute_command(command, (url,))
if result is None:
return None
return result[0] | 5,342,514 |
def is_chinese_char(cc):
"""
Check if the character is Chinese
args:
cc: char
output:
boolean
"""
return unicodedata.category(cc) == 'Lo' | 5,342,515 |
def _get_ec2_on_demand_prices(region_name: str) -> pd.DataFrame:
"""
Returns a dataframe with columns instance_type, memory_gb, logical_cpu, and price
where price is the on-demand price
"""
# All comments about the pricing API are based on
# https://www.sentiatechblog.com/using-the-ec2-price-li... | 5,342,516 |
def resize_image(image, min_dim=None, max_dim=None, padding=False):
"""
Resizes an image keeping the aspect ratio.
min_dim: if provided, resizes the image such that it's smaller
dimension == min_dim
max_dim: if provided, ensures that the image longest side doesn't
exceed this value.
... | 5,342,517 |
def _handle_add_fifo(pool, to_add: transaction.Transaction):
"""
FIFO is defined by putting the BUY transactions at the end.
For split coins, they need to be sold first.
"""
if to_add.operation == transaction.Operation.SPLIT:
pool.insert(0, to_add)
else:
assert to_add.operation i... | 5,342,518 |
def save_gradients_images(gradients, file_name):
"""
Exports the original gradients image
Args:
gradients (np arr): Numpy array of the gradients with shape (3, 224, 224)
file_name (str): File name to be exported
"""
if not os.path.exists('results'):
os.makedirs('results')... | 5,342,519 |
def _set_no_data(gdal_ds, no_data):
""" Set no data value into gdal dataset
Description
-----------
Parameters
----------
gdal_ds: gdal.Dataset
gdal dataset
no_data: list or tuple
list of no data values corresponding to each raster band
"""
for band in range(gdal_d... | 5,342,520 |
def idwt(approx, wavelets, h=np.array([1.0 / np.sqrt(2), -1.0 / np.sqrt(2)]),
g=np.array([1.0 / np.sqrt(2), 1.0 / np.sqrt(2)])):
"""
Simple inverse discrete wavelet transform.
for good reference: http://www.mathworks.com/help/wavelet/ref/dwt.html
@param approx: approximation of signal at low re... | 5,342,521 |
def app_durations():
"""Generate JavaScript for appDurations."""
return 'appDurations = ' + json.dumps(supported_durations) | 5,342,522 |
def generic_cc(mag=10,dmag=8,band='K'):
"""Returns a generic contrast curve.
Keyword arguments:
mag -- magnitude of target star in passband
dmag -- can currently be either 8 or 4.5 (two example generic cc's being used)
band -- passband of observation.
"""
if dmag==8:
return fpp.Con... | 5,342,523 |
def read_routes(*, db: Session = Depends(deps.get_db),data_in: schemas.DictDataCreate,current_user: models.User = Depends(deps.get_current_active_user)) -> Any:
"""
Retrieve Mock Data.
"""
db.add(models.Dict_Data(**jsonable_encoder(data_in)))
return {
"code": 20000,
"data": "",
... | 5,342,524 |
def plotTruePreds(tr_gamma, pred_gamma, tr_ele, pred_ele, tr_pi0, pred_pi0, tr_chPi, pred_chPi):
"""
Plots 4 True X Pred energy plots, one for each kind of particle
:parameter tr_gamma: array containing the true values of the energy for photons.
:parameter pred_gamma: array containing the predicted ener... | 5,342,525 |
def get_companies_pagination_from_lagou(city_id=0, finance_stage_id=0, industry_id=0, page_no=1):
"""
爬取拉勾公司分页数据
:param city_id: 城市 id
:param finance_stage_id: 融资阶段 id
:param industry_id: 行业 id
:param page_no: 页码
:return: 拉勾公司分页数据
:rtype: utils.pagination.Pagination
"""
url = co... | 5,342,526 |
def test_d3_3_10v01_d3_3_10v01i(mode, save_output, output_format):
"""
A day is a calendar (or "local time") day in each timezone, including
the timezones outside of +12:00 through -11:59 inclusive.
"""
assert_bindings(
schema="ibmData/valid/D3_3_10/d3_3_10v01.xsd",
instance="ibmData... | 5,342,527 |
def _onTextReceive(iface, asDict):
"""Special text auto parsing for received messages"""
# We don't throw if the utf8 is invalid in the text message. Instead we just don't populate
# the decoded.data.text and we log an error message. This at least allows some delivery to
# the app and the app can deal... | 5,342,528 |
def is_quant_contam(contam_model):
"""Get the flag for quantitative contamination"""
# the list of quantitative models
quant_models = ['GAUSS', 'FLUXCUBE']
# set the default value
isquantcont = True
# check whether the contamination is not quantitative
if not contam_model.upper() in quant_... | 5,342,529 |
def nms_wrapper(scores, boxes, threshold = 0.7, class_sets = None):
"""
post-process the results of im_detect
:param scores: N * K numpy
:param boxes: N * (K * 4) numpy
:param class_sets: e.g. CLASSES = ('__background__','person','bike','motorbike','car','bus')
:return: a list of K-1 dicts, no b... | 5,342,530 |
def Rbf(
gamma: float = 1.0) -> InternalLayer:
"""Dual activation function for normalized RBF or squared exponential kernel.
Dual activation function is `f(x) = sqrt(2)*sin(sqrt(2*gamma) x + pi/4)`.
NNGP kernel transformation correspond to (with input dimension `d`)
`k = exp(- gamma / d * ||x - x'||^2) = e... | 5,342,531 |
def upgrade_state_dict_with_xlm_weights(
state_dict: Dict[str, Any], pretrained_xlm_checkpoint: str,
) -> Dict[str, Any]:
"""
Load XLM weights into a Transformer encoder or decoder model.
Args:
state_dict: state dict for either TransformerEncoder or
TransformerDecoder
pretr... | 5,342,532 |
def test_get_current(client):
"""Assert that the business info for regular (not xpro) business is correct to spec."""
rv = client.get('/api/v1/businesses/CP0001965/directors')
assert 200 == rv.status_code
is_valid, errors = validate(rv.json, 'directors', validate_schema=True)
if errors:
for... | 5,342,533 |
def create_returns_tear_sheet(returns, positions=None,
transactions=None,
live_start_date=None,
cone_std=(1.0, 1.5, 2.0),
benchmark_rets=None,
bootstrap=False,
... | 5,342,534 |
def vectorize_text(text_col: pd.Series,
vec_type: str = 'count',
**kwargs):
"""
Vectorizes pre-processed text. Instantiates the vectorizer and
fit_transform it to the data provided.
:param text_col: Pandas series, containing preprocessed text.
:param vec_type: ... | 5,342,535 |
def creation_LS(X,y,N):
"""Generates a random learning set of size N from the data in X
(containing the input samples) and in y (containing the corresponding
output values).
Parameters
----------
X: array containing the input samples
y: arr... | 5,342,536 |
def init_logger():
"""将日志信息输出到控制台
Params:
asctime: 打印日志的时间
levelname: 打印日志级别
name: 打印日志名字
message: 打印日志信息
"""
logging.basicConfig(
format='%(asctime)s - %(levelname)s - %(name)s - %(message)s',
datefmt='%m/%d/%Y %H:%M:%S',
level=logging.INFO
) | 5,342,537 |
def print_summary(show="all",
blocks=False, cid=True, blobs=True, size=True,
typ=False, ch=False, ch_online=True,
name=True, title=False, path=False,
sanitize=False,
start=1, end=0, channel=None, invalid=False,
r... | 5,342,538 |
def nice_number_en(number, speech, denominators=range(1, 21)):
""" English helper for nice_number
This function formats a float to human understandable functions. Like
4.5 becomes "4 and a half" for speech and "4 1/2" for text
Args:
number (int or float): the float to format
speech (bo... | 5,342,539 |
def test_unexpected_response(requests_mock_get, invalid_response):
"""
Check that the corresponding exception is raised if the response body is unexpected
"""
_, response = requests_mock_get
response.status_code = 200
response.json = lambda: invalid_response
with raises(TemperatureSourceExc... | 5,342,540 |
def read_dataframe_by_substring(directory, substring, index_col=None, parse_dates=False, **kwargs):
"""Return a dataframe for the file containing substring.
Parameters
----------
directory : str
substring : str
identifier for output file, must be unique in directory
index_col : str | in... | 5,342,541 |
def load_embeddings(path):
"""
Load embeddings from file and put into dict.
:param path: path to embeddings file
:return: a map word->embedding
"""
logging.info('Loading embeddings...')
embeddings = dict()
with open(path, 'r') as f:
for line in f:
line = line.split('... | 5,342,542 |
def helm_preserve(preserve):
"""Convert secret data to a "--set" string for Helm deployments.
Args:
preserve (Iterable): Set of secrets we wish to get data from to assign to the Helm Chart.
Returns:
str: String containing variables to be set with Helm release.
"""
env_vars = []
... | 5,342,543 |
def format_component_descriptor(name, version):
"""
Return a properly formatted component 'descriptor' in the format
<name>-<version>
"""
return '{0}-{1}'.format(name, version) | 5,342,544 |
def dbconn():
"""
Initializing db connection
"""
sqlite_db_file = '/tmp/test_qbo.db'
return sqlite3.connect(sqlite_db_file, detect_types=sqlite3.PARSE_DECLTYPES|sqlite3.PARSE_COLNAMES) | 5,342,545 |
def md5(fname):
"""
Compute the md5 of a file in chunks.
Avoid running out of memory when hashing large files.
"""
hash_md5 = hashlib.md5()
with open(fname, "rb") as f:
for chunk in iter(lambda: f.read(4096), b""):
hash_md5.update(chunk)
return hash_md5.hexdigest() | 5,342,546 |
def _create_comments_revisions(connection, obj_type):
"""Creates delete revisions for comments.
Args:
connection: An instance of SQLAlchemy connection.
obj_type: String representation of object type.
"""
result = _get_comments_ids_by_obj_type(connection, obj_type)
if result:
result = [row[0] for... | 5,342,547 |
def get_r(x, y, x1, y1):
"""
Get r vector following Xu et al. (2006) Eq. 4.2
x, y = arrays; x1, y1 = single points; or vice-versa
"""
return ((x-x1)**2 + (y-y1)**2)**0.5 | 5,342,548 |
def test_pylintrc_file_toml(testdir):
"""Verify that pyproject.toml can be used as a pylint rc file."""
rcfile = testdir.makefile(
'.toml',
pylint="""
[tool.pylint.FORMAT]
max-line-length = "3"
"""
)
testdir.makepyfile('import sys')
result = testdir.runpytest(... | 5,342,549 |
def replace_empty_bracket(tokens):
"""
Remove empty bracket
:param tokens: List of tokens
:return: Fixed sequence
"""
merged = "".join(tokens)
find = re.search(r"\{\}", merged)
while find:
merged = re.sub(r"\{\}", "", merged)
find = re.search(r"\{\}", merged)
return l... | 5,342,550 |
def presentation():
"""
This route is the final project and will be test
of all previously learned skills.
"""
return render_template("") | 5,342,551 |
def extra_credit(grades,students,bonus):
"""
Returns a copy of grades with extra credit assigned
The dictionary returned adds a bonus to the grade of
every student whose netid is in the list students.
Parameter grades: The dictionary of student grades
Precondition: grades has netids as keys, i... | 5,342,552 |
def get_geo_signal_combos(data_source):
"""
Get list of geo type-signal type combinations that we expect to see.
Cross references based on combinations reported available by COVIDcast metadata.
"""
meta = covidcast.metadata()
source_meta = meta[meta['data_source'] == data_source]
# Need to ... | 5,342,553 |
def absolute_(x, track_types = True, **kwargs):
"""Compute the absolute value of x.
Parameters
----------
x : :obj:`xarray.DataArray`
Data cube containing the values to apply the operator to.
track_types : :obj:`bool`
Should the operator promote the value type of the output object, based
... | 5,342,554 |
def upconv(path):
"""Check a 24bit FLAC file for upconversion"""
if os.path.isfile(path):
_upconvert_check_handler(path)
elif os.path.isdir(path):
for root, _, figles in os.walk(path):
for f in figles:
if f.lower().endswith(".flac"):
filepath =... | 5,342,555 |
def any_input(sys_, t, input_signal=0, init_cond=None, *, plot=True):
"""
Accept any input signal, then calculate the response of the system.
:param sys_: the system
:type sys_: TransferFunction | StateSpace
:param t: time
:type t: array_like
:param input_signal: input signal accepted by th... | 5,342,556 |
def get_combinations(suite_dir, fields, subset,
limit, filter_in, filter_out,
include_facet):
"""
Describes the combinations of a suite, optionally limiting
or filtering output based on the given parameters. Includes
columns for the subsuite and facets when incl... | 5,342,557 |
def cli(ctx, dry_run, stack_resources, stack_exports):
"""Print stack status and resources.
Also includes parameters, resources, outputs & exports."""
# shortcut if we only print stack key (and names)
if dry_run:
for context in ctx.obj.runner.contexts:
ctx.obj.ppt.secho(context.sta... | 5,342,558 |
def search(api: ApiClient, context: UserContext, search_string, as_csv):
"""
Search for a user
"""
if as_csv:
fieldnames = ['id', 'title_before', 'first_name', 'last_name', 'title_after', 'avatar_url']
csv_writer = csv.DictWriter(sys.stdout, fieldnames=fieldnames)
csv_writer.wri... | 5,342,559 |
def mnext_mbv2_cfg(pretrained=False,in_chans=3,drop_rate=0.2,drop_connect_rate=0.5,bn_tf=False,bn_momentum=0.9,bn_eps=0.001, global_pool=False, **kwargs):
"""Creates a MNeXt Large model. Tensorflow compatible variant
"""
from .mnext import mnext
model = mnext(**kwargs)
return model | 5,342,560 |
def _embeddings_from_arguments(column,
args,
weight_collections,
trainable,
output_rank=2):
"""Returns embeddings for a column based on the computed arguments.
Args:
column: the co... | 5,342,561 |
def stuw_laagstedoorstroombreedte(damo_gdf=None, obj=None, damo_doorstroombreedte="DOORSTROOMBREEDTE",
damo_kruinvorm="WS_KRUINVORM"):
"""
als LAAGSTEDOORSTROOMHOOGTE is NULL en WS_KRUINVORM =3 (rechthoek) dan LAAGSTEDOORSTROOMBREEDTE = DOORSTROOMBREEDTE
"""
return damo... | 5,342,562 |
def manage_categories():
"""
Display all categories to manage categories page (admin only)
"""
# Denied user access to manage_categories page
if session["user"] != "admin":
return redirect(url_for('error', code=403))
# query for all categories from categories collection
manage_categ... | 5,342,563 |
def callback(id):
"""
获取指定记录
"""
# 检查用户权限
_common_logic.check_user_power()
_positions_logic = positions_logic.PositionsLogic()
# 读取记录
result = _positions_logic.get_model_for_cache(id)
if result:
# 直接输出json
return web_helper.return_msg(0, '成功', result)
else:
... | 5,342,564 |
def setup_exps_rllib(flow_params,
n_cpus,
n_rollouts):
"""Return the relevant components of an RLlib experiment.
Parameters
----------
flow_params : dict
flow-specific parameters (see flow/utils/registry.py)
n_cpus : int
number of CPUs to ru... | 5,342,565 |
def sort_cluster(x: list, t: np.ndarray) -> list:
"""
sort x according to t
:param x:
:param t:
:return:
"""
return [x[i] for i in np.argsort(t)] | 5,342,566 |
def virtualenv(ctx: DoctorContext):
"""Check that we're in the correct virtualenv."""
try:
venv_path = pathlib.Path(os.environ['VIRTUAL_ENV']).resolve()
except KeyError:
ctx.error('VIRTUAL_ENV not set')
return
# When running in LUCI we might not have gone through the normal envi... | 5,342,567 |
def gettof(*args):
"""gettof(flags_t F) -> ushort"""
return _idaapi.gettof(*args) | 5,342,568 |
def test_parse_new_order():
"""Test parsing raw new order data."""
args = {
"limit_price": 1,
"max_quantity": 2,
"client_id": 3,
"side": Side.Sell,
"order_type": OrderType.PostOnly,
}
expected = bytes.fromhex(
"000100000001000000010000000000000002000000000... | 5,342,569 |
def generate(temp):
"""
Wrapper that checks generated names against the base street names to avoid a direct
regurgitation of input data.
returns list
"""
is_in_dict = True
while is_in_dict:
result = textgen.generate(temperature=temp, return_as_list=True)
str = ' '.jo... | 5,342,570 |
def __create_pyramid_features(backbone_dict,
ndim=2,
feature_size=256,
include_final_layers=True,
lite=False,
upsample_type='upsamplelike',
... | 5,342,571 |
def graphviz(self, filename=None, directory=None, isEdge=False,showLabel=True, **kwargs):
"""Return graphviz source for visualizing the lattice graph."""
return lattice(self, filename, directory, isEdge, showLabel, **kwargs) | 5,342,572 |
def plotDecisionBoundary(theta, X, y, Lambda):
"""
Plots the data points X and y into a new figure with the decision boundary
defined by theta
PLOTDECISIONBOUNDARY(theta, X,y) plots the data points with + for the
positive examples and o for the negative examples. X is assumed to be
a... | 5,342,573 |
def test_get_tot_pop():
"""Testing
"""
scenario_drivers = {'heating': ['population']}
classobject1 = dw_stock.Dwelling(
2015,
{'longitude': 10, 'latitude': 10},
1000,
['heating'],
scenario_drivers,
population=2.2
)
classobject2 = dw_stock.Dwelling... | 5,342,574 |
def get_rectangle(origin, end):
"""Return all points of rectangle contained by origin and end."""
size_x = abs(origin[0]-end[0])+1
size_y = abs(origin[1]-end[1])+1
rectangle = []
for x in range(size_x):
for y in range(size_y):
rectangle.append((origin[0]+x, origin[1]+y))
retu... | 5,342,575 |
def corr_list(df, target, thresh=0.1, sort=True, fill=True):
"""
List Most Correlated Features
Returns a pandas Series with the most correlated features to a certain
target variable. The function will return features with a correlation value
bigger than some threshold, which can be adjusted.
P... | 5,342,576 |
def test_positive_change_license_status(assignment_type, license_handler, assignment_handler,
create_environment_for_assignment_type):
"""Positive test: test all valid status changes (+ if status was set correct)"""
object_type = _ASSIGNMENT_TYPE_TO_OBJECT_TYPE[assignment... | 5,342,577 |
def compute_epsilon(steps):
"""Computes epsilon value for given hyperparameters."""
if FLAGS.noise_multiplier == 0.0:
return float('inf')
orders = [1 + x / 10. for x in range(1, 100)] + list(range(12, 64))
sampling_probability = FLAGS.batch_size / NUM_TRAIN_EXAMPLES
rdp = compute_rdp(q=sampling_probabilit... | 5,342,578 |
def get_native_includes(object):
"""
After method association, check which native types an object uses
and return a corresponding string list of include file
This will also add the include needed for inheritance
"""
includes = set()
for proc in object.procs:
for argname,arg in proc.... | 5,342,579 |
def libraries_data_path():
"""
Path to Packages/User/Deviot/pio/libraries.json
"""
user_data = user_pio_path()
return path.join(user_data, 'libraries.json') | 5,342,580 |
def dice_coeff(input, target):
"""Dice coeff for batches"""
if input.is_cuda:
s = torch.FloatTensor(1).to(device_f).zero_()
else:
s = torch.FloatTensor(1).zero_()
for i, c in enumerate(zip(input, target)):
s = s + DiceCoeff().forward(c[0], c[1])
return s / (i + 1) | 5,342,581 |
def group_error_rates(labels, predictions, groups):
"""Returns a list containing error rates for each protected group."""
errors = []
for jj in range(groups.shape[1]):
if groups[:, jj].sum() == 0: # Group is empty?
errors.append(0.0)
else:
signed_labels_jj = 2 * labels[groups[:, jj] == 1] - 1... | 5,342,582 |
def lnprior(theta):
"""
Parameters
----------
theta : np.ndarray
Array of parameters.
Returns
-------
Value of log-prior.
"""
pass | 5,342,583 |
def get_emails_by_user_names(user_names):
"""Get emails by user names."""
emails_service = emails_digest_service.DailyEmailsService()
emails_service.open_emails_digest()
user_emails_dict = dict.fromkeys(user_names)
for user_name in user_names:
user_emails_dict[user_name] = emails_service.get_email_by_user... | 5,342,584 |
def get_match_results(depc, qaid_list, daid_list, score_list, config):
""" converts table results into format for ipython notebook """
# qaid_list, daid_list = request.get_parent_rowids()
# score_list = request.score_list
# config = request.config
unique_qaids, groupxs = ut.group_indices(qaid_list)... | 5,342,585 |
def inbound_and_outbound_node_sets(C, CT):
"""
Returns the set of nodes that can reach an event and can be reached by an event,
and the difference between those sets (outbound / inbound).
"""
inbound = defaultdict(set)
for node, event in zip(*np.nonzero(C)):
inbound[event].add(node)
outbound = defaultdic... | 5,342,586 |
def policy(Q):
"""Hard max over prescriptions
Params:
-------
* Q: dictionary of dictionaries
Nested dictionary representing a table
Returns:
-------
* policy: dictonary of states to policies
"""
pol = {}
for s in Q:
pol[s] = max(Q[s].items(), key=lambda... | 5,342,587 |
def test_should_generate(fixture, color, result, expected):
"""Only return True if existing badge needs updating"""
output = os.path.join(FIXTURES, "default-style", fixture)
actual = badge_gen.should_generate_badge(output, color, result)
assert actual is expected | 5,342,588 |
def main(argv=sys.argv) -> None: # pragma: no cover
"""Run type coverage check."""
parser = argparse.ArgumentParser(
usage=("python type_coverage.py coverage=80 file=typecov/linecount.txt \n")
)
parser.add_argument(
"coverage",
type=float,
metavar="<coverage>",
h... | 5,342,589 |
def fft(series):
"""
FFT of a series
Parameters
----------
series
Returns
-------
"""
signal = series.values
time = series.index
dt = np.mean(np.diff(time))
#n = 11*len(time)
n = 50000
frequencies = np.fft.rfftfreq(n=n, d=dt) # [Hz]
dft = np.abs(np.fft.rf... | 5,342,590 |
def local_variance(V, tsize=5):
""" local non-linear variance calculation
Parameters
----------
V : numpy.array, size=(m,n), dtype=float
array with one velocity component, all algorithms are indepent of their
axis.
Parameters
----------
sig_V : numpy.array, size=(m,n), dtyp... | 5,342,591 |
def get_virtual_device_configuration(device):
"""Get the virtual device configuration for a PhysicalDevice.
Returns the list of VirtualDeviceConfiguration objects previously configured
by a call to `tf.config.experimental.set_virtual_device_configuration()`.
For example:
>>> physical_devices = tf.config.ex... | 5,342,592 |
def user_directory_path(instance, filename):
"""Sets path to user uploads to: MEDIA_ROOT/user_<id>/<filename>"""
return f"user_{instance.user.id}/{filename}" | 5,342,593 |
def process_command_line():
"""Process the file on the command line when run as a script or entry point."""
args = parse_command_line()
code_file = args.code_file[0]
processed_code = strip_file_to_string(code_file, args.to_empty, args.strip_nl,
args.no_ast, args.no_colon_move,... | 5,342,594 |
def not_none_to_dict(args_dict, key, value):
"""
Если значение не None, кладем его в словарь.
"""
if not (value is None):
args_dict[key] = value | 5,342,595 |
async def async_setup_entry(
hass: HomeAssistant,
config_entry: ConfigEntry,
async_add_entities: AddEntitiesCallback,
) -> None:
"""Load Tradfri switches based on a config entry."""
gateway_id = config_entry.data[CONF_GATEWAY_ID]
tradfri_data = hass.data[DOMAIN][config_entry.entry_id]
api = ... | 5,342,596 |
def setup(app):
"""Setup the Sphinx extension."""
# Register builder.
app.add_builder(BeamerBuilder)
# Add setting for allowframebreaks.
app.add_config_value("beamer_allowframebreaks", True, "beamer")
# Add setting for Beamer theme.
app.add_config_value("beamer_theme", "Warsaw", "beamer")
... | 5,342,597 |
def select_object_by_name_no_context(name):
""" This is an attempt to deal with an incorrect context error """
obj = bpy.data.objects[name]
for o in bpy.context.view_layer.objects:
if (is_blender_28()):
o.select_set(False)
else:
o.select = False
if (is_blender_28()):... | 5,342,598 |
def EndorseConnections(browser):
"""
Endorse skills for your connections found. This only likes the top three popular
skills the user has endorsed. If people want this feature can be further
expanded just post an enhancement request in the repository.
browser:
"""
print("Gathering your conn... | 5,342,599 |
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