content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
import time
def confirm_channel(bitcoind, n1, n2):
"""
Confirm that a channel is open between two nodes
"""
assert n1.id() in [p.pub_key for p in n2.list_peers()]
assert n2.id() in [p.pub_key for p in n1.list_peers()]
for i in range(10):
time.sleep(0.5)
if n1.check_channel(n2) ... | bcbf895b286b446f7bb0ad2d7890a0fa902cdbd1 | 4,655 |
def has_permissions(**perms):
"""A :func:`check` that is added that checks if the member has any of
the permissions necessary.
The permissions passed in must be exactly like the properties shown under
:class:`discord.Permissions`.
Parameters
------------
perms
An argument list of p... | bf9432f136db8cd2643fe7d64807194c0479d3cd | 4,656 |
def extend_params(params, more_params):
"""Extends dictionary with new values.
Args:
params: A dictionary
more_params: A dictionary
Returns:
A dictionary which combines keys from both dictionaries.
Raises:
ValueError: if dicts have the same key.
"""
for yak in more_params:
if yak in p... | 626db0ae8d8a249b8c0b1721b7a2e0f1d4c084b8 | 4,657 |
import logging
def __compute_libdeps(node):
"""
Computes the direct library dependencies for a given SCons library node.
the attribute that it uses is populated by the Libdeps.py script
"""
if getattr(node.attributes, 'libdeps_exploring', False):
raise DependencyCycleError(node)
env ... | 93e44b55bb187ae6123e22845bd4da69b260b107 | 4,658 |
def _AccumulatorResultToDict(partition, feature, grads, hessians):
"""Converts the inputs to a dictionary since the ordering changes."""
return {(partition[i], feature[i, 0], feature[i, 1]): (grads[i], hessians[i])
for i in range(len(partition))} | 20cc895cf936749a35c42a1158c9ea6645019e7d | 4,659 |
async def create(payload: ProductIn):
"""Create new product from sent data."""
product_id = await db.add_product(payload)
apm.capture_message(param_message={'message': 'Product with %s id created.', 'params': product_id})
return ProductOut(**payload.dict(), product_id=product_id) | 77f9ef1699cba57aa8e0cfd5a09550f6d03b8f72 | 4,661 |
def get_glove_info(glove_file_name):
"""Return the number of vectors and dimensions in a file in GloVe format."""
with smart_open(glove_file_name) as f:
num_lines = sum(1 for line in f)
with smart_open(glove_file_name) as f:
num_dims = len(f.readline().split()) - 1
return num_lines, num_... | 4fde6a034197e51e3901b22c46d946330e2e213e | 4,662 |
from typing import Dict
from typing import List
def retrieve_database_inputs(db_session: Session) -> (
Dict[str, List[RevenueRate]], Dict[str, MergeAddress], List[Driver]):
"""
Retrieve the static inputs of the model from the database
:param db_session: SQLAlchemy Database connection session
:... | f5242680576d7e07b87fb8fd31e26efc1b0c30f0 | 4,663 |
def _evolve_cx(base_pauli, qctrl, qtrgt):
"""Update P -> CX.P.CX"""
base_pauli._x[:, qtrgt] ^= base_pauli._x[:, qctrl]
base_pauli._z[:, qctrl] ^= base_pauli._z[:, qtrgt]
return base_pauli | 5d0529bc4bfe74a122c24069eccb20fa2b69f153 | 4,664 |
def tp_pixel_num_cal(im, gt):
""" im is the prediction result;
gt is the ground truth labelled by biologists;"""
tp = np.logical_and(im, gt)
tp_pixel_num = tp.sum()
return tp_pixel_num | 197c1f64df3430cfbb6f45413b83360a1b9c44bf | 4,665 |
import time
def xsg_data(year=None, month=None,
retry_count=3, pause=0.001):
"""
获取限售股解禁数据
Parameters
--------
year:年份,默认为当前年
month:解禁月份，默认为当前月
retry_count : int, 默认 3
如遇网络等问题重复执行的次数
pause : int, 默认 0
重复请求数据过程中暂停的秒数，防止请求间隔时间太短出现的问题
... | 0ca7070a63ec9ee58bb590b82d9bcdb8e4801d33 | 4,666 |
def crm_ybquery_v2():
"""
crm根据用户手机号查询subId
:return:
"""
resp = getJsonResponse()
try:
jsonStr = request.data
# 调用业务逻辑
resp = {"message":"","status":200,"timestamp":1534844188679,"body":{"password":"21232f297a57a5a743894a0e4a801fc3","username":"admin"},"result":{"id"... | 02b7ff4e1f44643537b4549376aa637dcdbf5261 | 4,667 |
from typing import Dict
from typing import List
from typing import Union
from pathlib import Path
from typing import Iterable
from typing import Tuple
import tqdm
import logging
def get_split_file_ids_and_pieces(
data_dfs: Dict[str, pd.DataFrame] = None,
xml_and_csv_paths: Dict[str, List[Union[str, Path]]] = ... | d01768fddcef9428e5dd3a22592dca8dd083fc9c | 4,668 |
def calc_full_dist(row, vert, hor, N, site_collection_SM):
"""
Calculates full distance matrix. Called once per row.
INPUTS:
:param vert:
integer, number of included rows
:param hor:
integer, number of columns within radius
:param N:
integer, number of points in row
... | e332b3b51cf4dadb764865f7c75eb361aa0cc100 | 4,669 |
def background_upload_do():
"""Handle the upload of a file."""
form = request.form
# Is the upload using Ajax, or a direct POST by the form?
is_ajax = False
if form.get("__ajax", None) == "true":
is_ajax = True
print form.items()
# Target folder for these uploads.
# target = o... | 267608fa9c93a75ca260eb742fed9023ec350b65 | 4,670 |
def load_dict_data(selected_entities=None, path_to_data_folder=None):
"""Loads up data from .pickle file for the selected entities.
Based on the selected entities, loads data from storage,
into memory, if respective files exists.
Args:
selected_entities: A list of string entity names to be loa... | 0236d69d6ed6c663c3bba5edabd59ced9755c546 | 4,673 |
def cart_del(request, pk):
""" remove an experiment from the analysis cart and return"""
pk=int(pk) # make integer for lookup within template
analyze_list = request.session.get('analyze_list', [])
if pk in analyze_list:
analyze_list.remove(pk)
request.session['analyze_list'] = analyze_list
... | 210a0fd58d9470aa365906420f3769b57815839a | 4,674 |
def get_block_devices(bdms=None):
"""
@type bdms: list
"""
ret = ""
if bdms:
for bdm in bdms:
ret += "{0}\n".format(bdm.get('DeviceName', '-'))
ebs = bdm.get('Ebs')
if ebs:
ret += " Status: {0}\n".format(ebs.get('Status', '-'))
... | bd375f988b13d8fe5949ebdc994210136acc3405 | 4,675 |
from scipy import stats # lazy import
from pandas import DataFrame
def outlier_test(model_results, method='bonf', alpha=.05, labels=None,
order=False, cutoff=None):
"""
Outlier Tests for RegressionResults instances.
Parameters
----------
model_results : RegressionResults instance... | 39219cf5ad86f91cf6da15ea66dc2d18f0a371af | 4,676 |
def move(request, content_type_id, obj_id, rank):
"""View to be used in the django admin for changing a :class:`RankedModel`
object's rank. See :func:`admin_link_move_up` and
:func:`admin_link_move_down` for helper functions to incoroprate in your
admin models.
Upon completion this view sends the ... | 0a8e73d83d7d7c575a8ed5abe43524b22d701a38 | 4,677 |
def test_second_playback_enforcement(mocker, tmp_path):
"""
Given:
- A mockable test
When:
- The mockable test fails on the second playback
Then:
- Ensure that it exists in the failed_playbooks set
- Ensure that it does not exists in the succeeded_playbooks list
"""
... | 314cbfb4f659b34adfdafb6b1c1153c8560249b0 | 4,678 |
import re
def decode_textfield_ncr(content):
"""
Decodes the contents for CIF textfield from Numeric Character Reference.
:param content: a string with contents
:return: decoded string
"""
def match2str(m):
return chr(int(m.group(1)))
return re.sub('&#(\d+);', match2str, content... | 28bf8017869d1ad47dce4362ec2b57131f587bba | 4,679 |
def reflect_or_create_tables(options):
"""
returns a dict of classes
make 'em if they don't exist
"tables" is {'wfdisc': mapped table class, ...}
"""
tables = {}
# this list should mirror the command line table options
for table in list(mapfns.keys()) + ['lastid']:
# if option... | 8974f6e6299240c69cf9deffdb3efb7ba9dc771f | 4,680 |
def config_section_data():
"""Produce the default configuration section for app.config,
when called by `resilient-circuits config [-c|-u]`
"""
config_data = u"""[fn_grpc_interface]
interface_dir=<<path to the parent directory of your Protocol Buffer (pb2) files>>
#<<package_name>>=<<communication_ty... | cb26012ff6ad1a2dbccbbcc5ef81c7a91def7906 | 4,681 |
def color_print(path: str, color = "white", attrs = []) -> None:
"""Prints colorized text on terminal"""
colored_text = colored(
text = read_warfle_text(path),
color = color,
attrs = attrs
)
print(colored_text)
return None | c3f587d929f350c86d166e809c9a63995063cf95 | 4,683 |
def create_cluster_spec(parameters_server: str, workers: str) -> tf.train.ClusterSpec:
"""
Creates a ClusterSpec object representing the cluster.
:param parameters_server: comma-separated list of hostname:port pairs to which the parameter servers are assigned
:param workers: comma-separated list of host... | 2b4555b68821327451c48220e64bc92ecd5f3acc | 4,684 |
def bq_client(context):
"""
Initialize and return BigQueryClient()
"""
return BigQueryClient(
context.resource_config["dataset"],
) | 839a72d82b29e0e57f5973aee418360ef6b3e2fc | 4,685 |
def longascnode(x, y, z, u, v, w):
"""Compute value of longitude of ascending node, computed as
the angle between x-axis and the vector n = (-hy,hx,0), where hx, hy, are
respectively, the x and y components of specific angular momentum vector, h.
Args:
x (float): x-component of position
... | d108847fa6835bc5e3ff70eb9673f6650ddf795a | 4,686 |
def convert_to_distance(primer_df, tm_opt, gc_opt, gc_clamp_opt=2):
"""
Convert tm, gc%, and gc_clamp to an absolute distance
(tm_dist, gc_dist, gc_clamp_dist)
away from optimum range. This makes it so that all features will need
to be minimized.
"""
primer_df['tm_dist'] = get_distance(
... | 4d556fd79c2c21877b3cb59712a923d5645b5eba | 4,689 |
import copy
def _tmap_error_detect(tmap: TensorMap) -> TensorMap:
"""Modifies tm so it returns it's mean unless previous tensor from file fails"""
new_tm = copy.deepcopy(tmap)
new_tm.shape = (1,)
new_tm.interpretation = Interpretation.CONTINUOUS
new_tm.channel_map = None
def tff(_: TensorMap,... | 263a16a5cb92e0a9c3d42357280eeb6d15a59773 | 4,690 |
def generate_dataset(config, ahead=1, data_path=None):
"""
Generates the dataset for training, test and validation
:param ahead: number of steps ahead for prediction
:return:
"""
dataset = config['dataset']
datanames = config['datanames']
datasize = config['datasize']
testsize = co... | 89136efffbbd6e115b1d0b887fe7a3c904405bda | 4,691 |
def search(isamAppliance, name, check_mode=False, force=False):
"""
Search UUID for named Web Service connection
"""
ret_obj = get_all(isamAppliance)
return_obj = isamAppliance.create_return_object()
return_obj["warnings"] = ret_obj["warnings"]
for obj in ret_obj['data']:
if obj['na... | f642e9e62203b490a347c21899d45968f6258eba | 4,692 |
def flask_app(initialize_configuration) -> Flask:
"""
Fixture for making a Flask instance, to be able to access application context manager.
This is not possible with a FlaskClient, and we need the context manager for creating
JWT tokens when is required.
@return: A Flask instance.
"""
fla... | 265c912833025d13d06c2470443e68110ce4f60f | 4,693 |
import requests
def http_request(method, url_suffix, params=None, data=None, headers=HEADERS, safe=False):
"""
A wrapper for requests lib to send our requests and handle requests and responses better.
:type method: ``str``
:param method: HTTP method for the request.
:type url_suf... | 9fbd5123e4f1a39f5fa10fbc6a8f41db7ed1775b | 4,694 |
def FP(target, prediction):
"""
False positives.
:param target: target value
:param prediction: prediction value
:return:
"""
return ((target == 0).float() * prediction.float().round()).sum() | 9c8b21ecbc4f48b737c92fbaf73ef820fe035218 | 4,696 |
import math
def get_angle(A, B, C):
"""
Return the angle at C (in radians) for the triangle formed by A, B, C
a, b, c are lengths
C
/ \
b / \a
/ \
A-------B
c
"""
(col_A, row_A) = A
(col_B, row_B) = B
(col_C, row_C) = C
a = pixel_distance(C, ... | 30e1681bf2c065c4094b2dd909322158a9968c3c | 4,697 |
def single_labels(interesting_class_id):
"""
:param interesting_class_id: integer in range [0,2] to specify class
:return: number of labels for the "interesting_class"
"""
def s_l(y_true, y_pred):
class_id_true = K.argmax(y_true, axis=-1)
accuracy_mask = K.cast(K.equal(class_id_true,... | d137bbd4bba4bcb19e9bc296e4cecdbd7d8effe6 | 4,698 |
def get_rdf_lables(obj_list):
"""Get rdf:labels from a given list of objects."""
rdf_labels = []
for obj in obj_list:
rdf_labels.append(obj['rdf:label'])
return rdf_labels | 2bcf6a6e8922e622de602f5956747955ea39eeda | 4,700 |
import json
def _create_model_fn(pipeline_proto, is_chief=True):
"""Creates a callable that build the model.
Args:
pipeline_proto: an instance of pipeline_pb2.Pipeline.
Returns:
model_fn: a callable that takes [features, labels, mode, params] as inputs.
"""
if not isinstance(pipeline_proto, pipeli... | f29e86a0bc1355a7cf509e57ad0262bc5a9ca1e5 | 4,701 |
def boolean_automatic(meshes, operation, **kwargs):
"""
Automatically pick an engine for booleans based on availability.
Parameters
--------------
meshes : list of Trimesh
Meshes to be booleaned
operation : str
Type of boolean, i.e. 'union', 'intersection', 'difference'
Returns... | 7e5b1a483862bb05bb4cd78d21ec22c835f218e6 | 4,702 |
from .workflow import WorkSpec
def get_context(work=None):
"""Get a concrete Context object.
Args:
work (gmx.workflow.WorkSpec): runnable work as a valid gmx.workflow.WorkSpec object
Returns:
An object implementing the :py:class:`gmx.context.Context` interface, if possible.
Raises:
... | 838de2ce25dbe44c058f5360a59e48a68fa7dc2a | 4,703 |
def test_data():
"""Get the `CIFAR-10` test data."""
global _MEAN # pylint: disable=global-statement
_np.random.seed(1)
view = _skdc10.view.OfficialImageClassificationTask()
permutation = _np.random.permutation(range(10000))
if _MEAN is None:
_MEAN = view.train.x.reshape((50000 * 32 * 3... | e20acfc0e46dba2441b03d0d1443fc193c500e62 | 4,704 |
def normalize_key_combo(key_combo):
"""Normalize key combination to make it easily comparable.
All aliases are converted and modifier orders are fixed to:
Control, Alt, Shift, Meta
Letters will always be read as upper-case.
Due to the native implementation of the key system, Shift pressed in
c... | e242c6d9177d31c60a534e9734917c6fdf2de9f7 | 4,705 |
def shape_to_np(shape, dtype="int"):
"""
Used to convert from a shape object returned by dlib to an np array
"""
return np.array([[shape.part(i).x, shape.part(i).y] for i in range(68)], dtype=dtype) | 6d3d0205a8ac90dc8fb17b844fd5e150e25bdde1 | 4,706 |
def inet_pton(space, address):
""" Converts a human readable IP
address to its packed in_addr representation"""
n = rsocket.inet_pton(rsocket.AF_INET, address)
return space.newstr(n) | d015f76ab252e8f1f9f8f764bb7a2131f9ca9b92 | 4,707 |
def delete_routing_segmentation_maps_from_source_segment(
self,
segment_id: int,
) -> bool:
"""Delete D-NAT policies for specific source segment
.. list-table::
:header-rows: 1
* - Swagger Section
- Method
- Endpoint
* - vrf
- DELETE
- /v... | 32064ca159928ccc0802791e161a614f3303555f | 4,708 |
def _identifier(name):
"""
:param name: string
:return: name in lower case and with '_' instead of '-'
:rtype: string
"""
if name.isidentifier():
return name
return name.lower().lstrip('0123456789. ').replace('-', '_') | fbbbc9dd3f2bc5b6e43520c0685f63a10ee95f0a | 4,710 |
def roots(p):
"""
Return the roots of a polynomial with coefficients given in p.
The values in the rank-1 array `p` are coefficients of a polynomial.
If the length of `p` is n+1 then the polynomial is described by
p[0] * x**n + p[1] * x**(n-1) + ... + p[n-1]*x + p[n]
Parameters
----------
... | 02e3f37a81c84aac9ac949662ec64b85e24432c9 | 4,711 |
from typing import List
def calculate_trade_from_swaps(
swaps: List[AMMSwap],
trade_index: int = 0,
) -> AMMTrade:
"""Given a list of 1 or more AMMSwap (swap) return an AMMTrade (trade).
The trade is calculated using the first swap token (QUOTE) and last swap
token (BASE). Be aware that an... | 55071041fd0cab3fd2c0cb89f24cd9267a4e164a | 4,712 |
def tokenize(s):
"""
Tokenize a string.
Args:
s: String to be tokenized.
Returns:
A list of words as the result of tokenization.
"""
#return s.split(" ")
return nltk.word_tokenize(s) | 8dcc01364b3442539dbcc979d3238492bb7904d1 | 4,713 |
from datetime import datetime
def evaluate(request):
"""Eval view that shows how many times each entry was tracked"""
# default filter
end_date = datetime.date.today()
start_date = datetime.date(year=end_date.year, month=end_date.month - 1, day=end_date.day)
num_entries = 5
# get custom filte... | 44708b65846fd9e21ebc7baf1fe0377054ae2221 | 4,714 |
def significant_pc_test(adata, p_cutoff=0.1, update=True, obsm='X_pca', downsample=50000):
"""
Parameters
----------
adata
p_cutoff
update
obsm
downsample
Returns
-------
"""
pcs = adata.obsm[obsm]
if pcs.shape[0] > downsample:
print(f'Downsample PC matrix ... | c8e367c53330bcb959fb7baba9649d090de91389 | 4,716 |
def unique_hurricanes(hurdat):
"""
Returns header info for each unique hurricanes in HURDAT2-formatted text
file hurdat.
"""
#split on returns if hurdat is not a list
if not isinstance(hurdat, list):
hurdat = hurdat.split('\n')
header_rows = [parse_header(
line, line_num
... | c87561b80f6c8b70c33d64834c4d289508a2c120 | 4,718 |
def delete_models_shares_groups(id, group_id, client=None):
"""Revoke the permissions a group has on this object
Use this function on both training and scoring jobs.
Parameters
----------
id : integer
The ID of the resource that is shared.
group_id : integer
The ID of the group... | 59f3391e6e92fe0bf2f4c204a9da7c55a8ac8c6c | 4,720 |
def step1ddiffusionanalytical(q, dt, alpha, beta, prng=np.random, **kwargs):
"""Analytical time stepping as proposed in Jenkins, Spano arXiv:1506.06998
Uses the asymptotic normality of the death process for small times
(see Griffiths, J. Math. Bio, 1984)
"""
theta = alpha+beta
beta_ =... | ae1034488250a7a0afc184878496cd656b239016 | 4,721 |
def no_vtk():
""" Checks if VTK is installed and the python wrapper is functional """
global _vtk_version
return _vtk_version is None | 654dfd0f10a36bbfd3e46c5a93f84a9234e8c0ca | 4,722 |
def get_request_list(flow_list: list) -> list:
"""
将flow list转换为request list。在mitmproxy中，flow是对request和response的总称，这个功能只获取request。
:param flow_list: flow的列表
:return: request的列表
"""
req_list = []
for flow in flow_list:
request = flow.get("request")
req_list.append(request)
... | a70e0120ef2be88bd0644b82317a2a0748352c6c | 4,723 |
from typing import Tuple
import logging
def query_total_production(start_date, end_date) -> Tuple[int]:
"""Total count of semi production on the given time interval"""
semi_count = None
fg_count = None
try:
with stSession() as s:
semi_count = (
s.query(ProductionSc... | 4ecf7b2e70feaa75456550deca6a5b8a326adc11 | 4,724 |
import pytz
def add_fields(_, level, event_dict):
""" Add custom fields to each record. """
now = dt.datetime.now()
event_dict['timestamp'] = TZ.localize(now, True).astimezone(pytz.utc).isoformat()
event_dict['level'] = level
if session:
event_dict['session_id'] = session.get('session_id'... | 3efbffc2808a048fde80a3655e28417c39f2ad04 | 4,725 |
def Smith_set(A,P,params,election_ID,printing_wanted=False):
"""
Compute and return a list of the candidates in the Smith set.
This is the smallest set of candidates such that every candidate in the
Smith set beats every candidate not in the Smith set in one-on-one contests.
In this implementation, ... | eb71ee5ae402d732a3bea804aad5b39fe3bd92a2 | 4,726 |
from typing import Callable
from typing import Coroutine
from typing import Any
def run_async_from_thread(func: Callable[..., Coroutine[Any, Any, T_Retval]], *args) -> T_Retval:
"""
Call a coroutine function from a worker thread.
:param func: a coroutine function
:param args: positional arguments for... | 829a9008e8aa058b66cb637db71f8f8eb8499374 | 4,727 |
def check_tensor_shape(tensor_tf, target_shape):
""" Return a Tensorflow boolean graph that indicates whether
sample[features_key] has the specified target shape. Only check
not None entries of target_shape.
:param tensor_tf: Tensor to check shape for.
:param target_shape: Target shape to compare t... | 8b9938c67f2e3655f9ff4dac08261fb6e5803af2 | 4,728 |
def LabelAddressPlus(ea, name, force=False, append_once=False, unnamed=False, nousername=False, named=False, throw=False):
"""
Label an address with name (forced) or an alternative_01
:param ea: address
:param name: desired name
:param force: force name (displace existing name)
:param append_onc... | 4772fa25c482eb10abdfea6aa9542f50827c9346 | 4,729 |
def do_match(station1, station2, latitude, elevation, distance):
"""
Perform the match between two stations.
Do initial latitude check to speed up the test
(not longitude as this isn't a constant distance)
Return probabilities for elevation, separation and Jaccard Index
:param Station Class... | 078d04117363087a512449497713c487bc1180e4 | 4,730 |
def rotation_matrix_from_vectors(vec1, vec2):
""" Find the rotation matrix that aligns vec1 to vec2
Args
----
vec1 (numpy.ndarray): A 3d "source" vector
vec2 (numpy.ndarray): A 3d "destination" vector
Returns
-------
numpy.ndarray: A transform matrix (3x3) which when applie... | 9568378e309c5da6e6dffee4788e07eb0c2ea189 | 4,731 |
def audio(src, type="audio/ogg", other_attr={}):
"""
add audio file
args:
src <str> : source file
type <str> : type of audio file
other_attr <dict> : other attributes
"""
return f"""
<audio {_parse_attr(other_attr)}>
<source src="{src}" type="{type}">
</audi... | 3ccd8aea6d7257c46336bb81184cf4b7f379624e | 4,733 |
def test_triangle(dim):
"""
Tests if dimensions can come from a triangle.
dim is a list or tuple of the three dimensions
"""
dim = [int(x) for x in dim]
dim.sort()
if dim[0] + dim[1] > dim[2]:
return True
else:
return False | fc5bc8f7d3830da0ae8692d7cf65a72bcfe2ba7d | 4,734 |
from typing import List
def arg_parser(data: str):
"""parse "x[a1, a2, a3], y[k1=a1, a2, k3=a3], z"
nested [] are ignored.
"""
res: List[NameWithAttrs] = _ARG_WITH_ATTR_PARSER.parse(data)
return res | fa530584a96829944562d2c08bdfed34bfa3eec4 | 4,735 |
def _get_resource(span):
"""Get resource name for span"""
if "http.method" in span.attributes:
route = span.attributes.get("http.route")
return (
span.attributes["http.method"] + " " + route
if route
else span.attributes["http.method"]
)
return sp... | 71b4d2e568350ccfb436bbff6e7a2cff1f3cb251 | 4,736 |
def get_draw_title(kdata):
"""根据typ值，返回相应的标题，如 上证指数（日线）
参数：kdata: KData实例
返回：一个包含stock名称的字符串，可用作绘图时的标题
"""
if not kdata:
return ""
query = kdata.getQuery()
stock = kdata.getStock()
if stock.isNull():
return ""
s1 = ''
if query.kType == KQuery.KType.DAY:
... | 7c661b63cedb477224d7f5ea9d7c182108f801a5 | 4,737 |
def _B(slot):
"""Convert slot to Byte boundary"""
return slot*2 | 97f13e9fd99989a83e32f635193a0058656df68b | 4,738 |
import torch
def nll(perm, true):
"""
perm: (n, n) or (s, n, n)
true: (n)
"""
n = true.size(-1)
# i = torch.arange(n, device=perm.device)
# j = true.to(perm.device)
# print("perm.nll:", perm.size(), true.size())
elements = perm.cpu()[..., torch.arange(n), true]
# elements = per... | a63c95e814529539ecd964f4309ea96f78cfcbb1 | 4,739 |
def _peaks_colors_from_points(points, colors=None, points_per_line=2):
"""
Returns a VTK scalar array containing colors information for each one of
the peaks according to the policy defined by the parameter colors.
Parameters
----------
points : (N, 3) array or ndarray
points coordinate... | 7abc5be4739164dc225081ec321d1cb591f74bae | 4,740 |
def epi_reg(epi, t1, t1brain, out='epi_reg', **kwargs):
"""Wrapper for the ``epi_reg`` command.
:arg epi: Input EPI image
:arg t1: Input wholehead T1 image
:arg t1brain: Input brain extracted T1 image
:arg out: Output name
"""
asrt.assertIsNifti(epi)
asrt.assertIsNi... | 1d19f0efcfb4fcfc7293f294978d11811861a06b | 4,741 |
import pathlib
import json
def load_towns():
"""Sample of Wikipedia dataset that contains informations about Toulouse, Paris, Lyon and
Bordeaux.
Examples
--------
>>> from pprint import pprint as print
>>> from cherche import data
>>> towns = data.load_towns()
>>> print(towns[:3])
... | 72aa393cfc40db5f254059d78679ea5615f494d2 | 4,742 |
def nonce_initialization(params: InitializeNonceParams) -> TransactionInstruction:
"""Generate an instruction to initialize a Nonce account.
Args:
params: The nonce initialization params.
Returns:
The instruction to initialize the nonce account.
"""
return TransactionInstruction.f... | 99fc70fd7965443b508923013a988f96ecf7b222 | 4,743 |
def to_weeknr(date=''):
"""
Transforms a date strings YYYYMMDD to the corresponding week nr (e.g. 20200713 becomes w29)
"""
week_nr = pd.to_datetime(date).to_pydatetime().isocalendar()[1]
return f"w{week_nr}" | f9699e735be8d92e4340a23464ee54247c355ffd | 4,744 |
def build_logisticregression(X_loc, y_loc, args):
"""finds best parameters for logistic regression"""
Printer(colored('(training) ', 'green') +
'searching for best parameters for logistic regression')
# specify parameters and distributions to sample from
param_dist = {"C": np.logspace(-9, 3, 13),
"solver":... | f63f67bc9debd2adccac39910b29ed705498dd4b | 4,745 |
import re
def load_data(experiments,
remove_outlier=True,
peptides=["A5cons",
"A6cons",
"phage_ctl_0",
"phage_ctl_1",
"phage_ctl_2",
"phage_ctl_4",
... | b9d7c7be8e0bbe5f5aee785cc0b525d9a57acc8b | 4,746 |
def get_lines(clearance):
"""
Add lines per reference well interval between the closest points on the
reference well and the offset well and color them according to the
calculated Separation Factor (SF) between the two wells at these points.
Parameters
----------
clearance: welleng.clea... | 2ec0ef039647b9c72219989d00b3e92092a79c16 | 4,747 |
import hashlib
def generate_md5_hash(filepath):
"""Returns md5 hash of file.
Args:
filepath: str. Absolute path to the file.
Returns:
str. Hexadecimal hash of specified file.
"""
m = hashlib.md5()
with python_utils.open_file(filepath, 'rb', encoding=None) as f:
while ... | d615d9ec14b79eac72168db616664f5878ca8e21 | 4,748 |
def status():
"""Return status."""
return jsonify(STATUS) | de396fdf35e42a36ed40b294a26645efba29c27a | 4,749 |
from typing import Optional
def get_entitlement(account_id: Optional[str] = None,
customer_id: Optional[str] = None,
entitlement_id: Optional[str] = None,
opts: Optional[pulumi.InvokeOptions] = None) -> AwaitableGetEntitlementResult:
"""
Returns the ... | 8cc10901b90a05a4bc0089758ce297c54af48569 | 4,750 |
def skip_to_home(fxn):
""" Skips past page straight to home page if logged in
"""
@wraps(fxn)
def skipped_page_fxn(*arg, **kwargs):
if session.get('logged_in'):
return redirect(url_for('home'))
else:
return fxn(*arg, **kwargs)
return skipped_page_fxn | 9edbbc186caa93046d17c179610a9c1309f281db | 4,751 |
from pathlib import Path
def get_all_paths_from_directory(directory: Path, recursive: bool, paths: [str] = [], ) -> [Path]:
"""
Gets a list of file paths for all files in the given directory (and its subdirectories if recursive is true)
:param directory: The starting directory to get file paths from
:... | 95f26d94ff1656fa5e4c656ecf3e424bf29f21b0 | 4,752 |
def check_contigs_for_dupes(matches):
"""check for contigs that match more than 1 UCE locus"""
node_dupes = defaultdict(list)
for node in matches:
node_dupes[node] = len(set(matches[node]))
dupe_set = set([node for node in node_dupes if node_dupes[node] > 1])
return dupe_set | f20ab684388e38b51e193567b14a2a610d87f227 | 4,753 |
def substitute(P, x0, x1, V=0):
"""
Substitute a variable in a polynomial array.
Args:
P (Poly) : Input data.
x0 (Poly, int) : The variable to substitute. Indicated with either unit
variable, e.g. `x`, `y`, `z`, etc. or through an integer
matching the unit va... | dd176877f8663e7efb3ae99babf29726dbda025b | 4,754 |
def munkres(costs):
"""
Entry method to solve the assignment problem.
costs: list of non-infinite values entries of the cost matrix
[(i,j,value)...]
"""
solver = Munkres(costs)
return solver.munkres() | 583dfc977c8f97fd5a3c4c82e21ae6626f4a763b | 4,755 |
import torch
def compute_mean_std(dataset):
"""
https://stats.stackexchange.com/questions/25848/how-to-sum-a-standard-deviation
"""
# global_mean = np.zeros((3 * 64), dtype=np.float64)
# global_var = np.zeros((3 * 64), dtype=np.float64)
n_items = 0
s = RunningStatistics()
for image_... | 83f10fc58e83b41a542fbd088895304b0d0521b5 | 4,756 |
def test_clean_connections_p0(monkeypatch):
"""Add a connection, fake a closed thread and make sure it is removed."""
db_disconnect_all()
class mock_connection():
def __init__(self) -> None: self.value = _MOCK_VALUE_1
def close(self): self.value = None
def mock_connect(*args, **kwargs)... | 9c8c7155566170a3598edcb8a9d7441630545522 | 4,757 |
def add(request):
"""
Add contact information.
**Templates:**
* ``rolodex/add.html``
**Template Variables:**
* form
* results: the list of similar names to allow user to check for dupes
* name: the new name that is submitted
"""
results = []
name = None
if request.m... | b0fdb73f2362dc0a82d46529727cfb3b0093b8e0 | 4,758 |
def convert_total (letter1,number1, letter2, number2):
"""
Description
-----------
Converting the letter of a column and the number of a line from an exceldata to a range
Context
----------
is called in wrapp_ProcessUnits and wrapp_SystemData
Parameters
----------
le... | 51cf6480d92fa1d23841dd5605d024548837df5c | 4,759 |
def scale_facet_list(facet_list, scale):
"""
Scale list of facets by the given scaling factor
"""
new_facet_list = []
for facet in facet_list:
new_facet_list.append(scale_facet(facet, scale))
return new_facet_list | 1b1d34803db191b94fc082685718c08895e2ba28 | 4,760 |
def move_lines_to_index(uwline_index_to, lineno, uwlines, lines):
"""Method moves all lines in the list to the proper index of uwlines and
update lineno on these lines. This is useful when you want to change the
order of code lines. But note: it is not updating lineno on other lines
@:returns positi... | e96f3b9da77468a31275e6255cd08ffa9309fc60 | 4,761 |
def birch(V, E0, B0, BP, V0):
"""
From Intermetallic compounds: Principles and Practice, Vol. I: Principles
Chapter 9 pages 195-210 by M. Mehl. B. Klein, D. Papaconstantopoulos paper downloaded from Web
case where n=0
"""
E = (E0
+ 9.0/8.0*B0*V0*((V0/V)**(2.0/3.0) - 1.0)**2
+... | 6515e2b0b78dfcdc1d7743f3d5a7010fce920aea | 4,762 |
from typing import Set
from typing import Tuple
def debloat(edges: set, nodes: int, threshold: tuple = (0.95, 0.95)) -> Set[Tuple[str, str]]:
"""Remove nodes with inflow and/or ourflow > threshold"""
df = pd.DataFrame(list(edges), columns=["source", "target"])
checkpoint_shape = df.shape[0]
df_inflow ... | 5be2dec388086b10409a3de008f357540019c5cf | 4,763 |
def result(jid):
""" Displays a job result.
Args:
jid (str): The job id.
"""
job = q.fetch_job(jid)
statuses = {
'queued': 202,
'started': 202,
'finished': 200,
'failed': 500,
'job not found': 404,
}
if job:
job_status = job.get_statu... | 2919be693949dd4e873834530565fd28aefcf5d5 | 4,764 |
from typing import Callable
def fd_nabla_1(
x: np.ndarray,
fun: Callable,
delta_vec: np.ndarray,
) -> np.ndarray:
"""Calculate FD approximation to 1st order derivative (Jacobian/gradient).
Parameters
----------
x: Parameter vector, shape (n_par,).
fun: Function returning function valu... | 32363e04bbd22627c7e5c21e02b48154dbfc030a | 4,765 |
def get_ref_len_from_bam(bam_path, target_contig):
"""
Fetch the length of a given reference sequence from a :py:class:`pysam.AlignmentFile`.
Parameters
----------
bam_path : str
Path to the BAM alignment
target_contig : str
The name of the contig for which to recover haplotype... | e80cb3c50f4408b2a614621ff3d688852931e75b | 4,766 |
def vstd(df, n=10):
"""
成交量标准差 vstd(10)
VSTD=STD（Volume,N）=[∑（Volume-MA(Volume，N)）^2/N]^0.5
"""
_vstd = pd.DataFrame()
_vstd['date'] = df.date
_vstd['vstd'] = df.volume.rolling(n).std(ddof=1)
return _vstd | 97b448d00bcbe89d17339f9ed1155786d9ccd0ab | 4,767 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.