content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
from typing import Optional
def build_cluster_endpoint(
domain_key: DomainKey,
custom_endpoint: Optional[CustomEndpoint] = None,
engine_type: EngineType = EngineType.OpenSearch,
preferred_port: Optional[int] = None,
) -> str:
"""
Builds the cluster endpoint from and optional custom_endpoint an... | 82136d78ea6edf68fc5c8bf92653be033649bdfd | 3,636,808 |
import requests
import re
def get_community_pools():
"""Get community pool coins
Returns:
List[dict]: A list of dicts which consists of following keys:
denom, amount
"""
url = f"{BLUZELLE_PRIVATE_TESTNET_URL}:{BLUZELLE_API_PORT}/cosmos/distribution/v1beta1/community_pool"
res... | c4a78e0a953933f453f7684e66aff2b39572f593 | 3,636,809 |
def rgb2bgr(x):
"""
given an array representation of an RGB image, change the image
into an BGR representtaion of the image
"""
return(bgr2rgb(x)) | c9412018e6595513c29da54f8179ff2a7c953d07 | 3,636,810 |
from datetime import datetime
def draw_des1_plot(date, plot_A, plot_B):
"""
This function is to draw the plot of DES 1.
"""
#make up some data for the plot
df = pd.DataFrame({'date': np.array([datetime.datetime(2020, 1, i+1)
for i in range(12)]),
... | 811f4d844bafe3d35287b774f61c9337a3163d47 | 3,636,811 |
def kolmogorov_smirnov_rank_test(gene_set, gene_list, adj_corr, plot=False):
"""
Rank test used in GSEA method. It measures dispersion of genes from
gene_set over a gene_list. Every gene from gene_list has its weight
specified by adj_corr, where adj_corr are gene weights (correlation
with fenotype)... | 6c38a40d18465729e544694bd4c61547b98076ea | 3,636,812 |
import re
async def segment_url(request: schemas.UrlSegmentationRequest) -> schemas.SegmentationResponse:
""" This endpoint accept the URL of an image, and returns a SegmentationResponse.
The endpoint will try to download the image at the given URL.
Note: not all servers allow for non-browser user... | 9cdec9a06946629d35a0dc882e27a9a218075d32 | 3,636,813 |
def generate_answers(session, model, word2id, qn_uuid_data, context_token_data, qn_token_data):
"""
Given a model, and a set of (context, question) pairs, each with a unique ID,
use the model to generate an answer for each pair, and return a dictionary mapping
each unique ID to the generated answer.
... | 253e2ef5a4d03d6eccf418aae23373cd17e0c143 | 3,636,814 |
import cmath
def _add_agline_to_dict(geo, line, d={}, idx=0, mesh_size=1e-2, n_elements=0, bc=None):
"""Draw a new Air Gap line and add it to GMSH dictionary if it does not exist
Parameters
----------
geo : Model
GMSH Model objet
line : Object
Line Object
d : Dictionary
... | 07f14b04cfb9f72d8150cfd39332ba2979cd3ae4 | 3,636,815 |
def mat_toeplitz_2d(h, x):
"""
Constructs a Toeplitz matrix for 2D convolutions
Parameters
----------
h: list[list]
A matrix of scalar values representing the filter
x: list[list]
A matrix of scalar values representing the signal
Returns
-------
list[list]
A... | 10ca8c25eb421aa34c0caf67a63b621a93de6d32 | 3,636,817 |
import unicodedata
def fix_text_segment(
text,
*,
fix_entities='auto',
remove_terminal_escapes=True,
fix_encoding=True,
fix_latin_ligatures=True,
fix_character_width=True,
uncurl_quotes=True,
fix_line_breaks=True,
fix_surrogates=True,
remove_control_chars=True,
remove_b... | 645bbbfb2f1da94b941e51c50ef7fd682ac6e823 | 3,636,818 |
import random
def SSValues(MPKa,Rfa,r):
"""
Steady-State Values (Numerical solutions Linear)
Input: Annual MPK and Rf Rates, r (repetition index)
Output: Annual MPK and Rf Rates (Input), mu, gamma, SS Capital, SS Wage, SS Investment, Value function
"""
#Compute Parameters
MPK =... | 31e693da8878d84f6b619f0052a140bbf5307695 | 3,636,819 |
def simplify_junctures(graph, epsilon=5):
"""Simplifies clumps by replacing them with a single juncture node. For
each clump, any nodes within epsilon of the clump are deleted. Remaining
nodes are connected back to the simplified junctures appropriately."""
graph = graph.copy()
max_quadrance = epsil... | b88e63d0ac5242e93d1d061c3eeed773d9a7c6bc | 3,636,820 |
def sample_truncated_norm(clip_low, clip_high, mean, std):
"""
Given a range (a,b), returns the truncated norm
"""
a, b = (clip_low - mean) / std, (clip_high - mean) / std
return int(truncnorm.rvs(a, b, mean, std)) | de722881ce95b83239af74ba081539dfedca3363 | 3,636,821 |
def f(x):
""" Approximated funhction."""
return x.mm(w_target)+b_target[0] | 8a76358acd7d56aeb18c104198e253fda582652f | 3,636,822 |
import requests
from bs4 import BeautifulSoup
def get_urls():
""" get all sci-hub-torrent url
"""
source_url = 'http://gen.lib.rus.ec/scimag/repository_torrent/'
urls_list = []
try:
req = requests.get(source_url)
soups = BeautifulSoup(req.text, 'lxml').find_all('a')
for sou... | e14f15ebc7e39393bd614183e1eccb8fc1933359 | 3,636,823 |
def getVariablesForCookie(request=None):
""" returns dict with variables for cookie
"""
cookie_path = '/'
portalurl = absoluteURL(getSite(), request)
cookie_name = "%s%s"%('__zojax_comment_author_', md5(portalurl).hexdigest())
return dict(name=cookie_name, path=cookie_path) | ba6578036d69ceef45be1b583d8b52b699519823 | 3,636,824 |
import torch
def logsumexp(x, dim):
""" sums up log-scale values """
offset, _ = torch.max(x, dim=dim)
offset_broadcasted = offset.unsqueeze(dim)
safe_log_sum_exp = torch.log(torch.exp(x-offset_broadcasted).sum(dim=dim))
return safe_log_sum_exp + offset | 53a12a2c91c6a0cae3fcae46a860801f05480abe | 3,636,825 |
import requests
def make_request(session, verb, endpoint, data={},
timeoutInSeconds=REQUEST_TIMEOUT_IN_SECONDS,
max_retries=MAX_RETRIES):
""" Make a REST request """
try:
if verb is RequestVerb.post:
r = session.post(url=endpoint, json=data, timeout=timeou... | 5a0637a130a5f2c1c834ddfb61cccaceeeb5c3c9 | 3,636,826 |
def certificate_managed(
name, days_remaining=90, append_certs=None, managed_private_key=None, **kwargs
):
"""
Manage a Certificate
name
Path to the certificate
days_remaining : 90
Recreate the certificate if the number of days remaining on it
are less than this number. The... | 0d98b58b26bb8266bbd7817b3b8533940b7b5f33 | 3,636,827 |
from typing import Iterable
from typing import Dict
from typing import List
def _unique_field_to_col_matching(
rules: Iterable[Rule], field_to_matching_cols: Dict[str, List[int]]
) -> Dict[str, int]:
"""
Given a potential field to column matching this functions tries to determine a unique 1-to-1
matc... | b0f8f63eb86701605bc67140b91e2e67f368082a | 3,636,828 |
import yaml
import textwrap
def minimal_config():
"""Return YAML parsing result for (somatic) configuration"""
return yaml.round_trip_load(
textwrap.dedent(
r"""
static_data_config:
reference:
path: /path/to/ref.fa
dbsnp:
path: /path/to/d... | 806da8976dea510997b6fea8d264ac2e7d619e75 | 3,636,829 |
def walk(n=1000, mu=0, sigma=1, alpha=0.01, s0=NaN):
"""
Mean reverting random walk.
Returns an array of n-1 steps in the following process::
s[i] = s[i-1] + alpha*(mu-s[i-1]) + e[i]
with e ~ N(0,sigma).
The parameters are::
*n* walk length
*s0* starting value, defaults ... | c87e06b2fc046ece6acbffaf982b9258272f81a6 | 3,636,830 |
def GetCLIInfoMgr():
""" Get the vmomi type manager """
return _gCLIInfoMgr | 4adf784890a6c72cacd951f675350dd40d68c0d5 | 3,636,831 |
from datetime import datetime
def pretty_date(time=False):
"""
Get a datetime object or a int() Epoch timestamp and return a
pretty string like 'an hour ago', 'Yesterday', '3 months ago',
'just now', etc
"""
now = datetime.now()
if type(time) is int:
diff = now - datetime.fromtimes... | 28be383e0064640f3781c781db06eb3a914205dd | 3,636,832 |
def per_cpu_times():
"""Return system CPU times as a named tuple"""
ret = []
for cpu_t in cext.per_cpu_times():
user, nice, system, idle = cpu_t
item = scputimes(user, nice, system, idle)
ret.append(item)
return ret | b43152c58323fc0d74ec8297e419622485bd7505 | 3,636,833 |
def cooldown(rate, per, type=commands.BucketType.default):
"""See `commands.cooldown` docs"""
def decorator(func):
if isinstance(func, Command):
func._buckets = CooldownMapping(Cooldown(rate, per, type))
else:
func.__commands_cooldown__ = Cooldown(rate, per, type)
... | c15bc00a7b71c95086088f5d42c09de350c148d5 | 3,636,834 |
def construct_psi_k2(theta, y, X, kappa = 30):
"""
Kappa-based filter for time-varying autoregressive component, based on
Platteau (2021)
"""
#get parameter vector
T = len(y)
omega = theta[0]
alpha = theta[1]
beta = theta[2]
#Filter Volatility
psi = np.zeros(T)
#i... | e020f7f437dbba96aac15a51491496f701995693 | 3,636,835 |
def calHoahaoSancai(tian_ge, ren_ge, di_ge):
"""
三才五行吉凶计算
:return:
:param tian_ge: 天格
:param ren_ge: 人格
:param di_ge: 地格
:return:
"""
sancai = getSancaiWuxing(tian_ge) + getSancaiWuxing(ren_ge) + getSancaiWuxing(di_ge)
if sancai in g_sancai_wuxing_dict:
data = g_sancai... | ea75055c3b2c749af9b97b8271aea2242de3c85f | 3,636,836 |
def load_coeff_swarm_mio_internal(path):
""" Load internal model coefficients and other parameters
from a Swarm MIO_SHA_2* product file.
"""
with open(path, encoding="ascii") as file_in:
data = parse_swarm_mio_file(file_in)
return SparseSHCoefficientsMIO(
data["nm"], data["gh"],
... | cbc2eac4a293ecf432c2520aef741c7499a9be70 | 3,636,837 |
def plot_trajectory_from_data(X : np.array, y : np.array, sample_n = 0, excludeY=True, ylabel=None, xlabel=None):
"""
Plots trajectory from data
sample_n: sample index
"""
fig, ax = plt.subplots()
dim = X.shape[2]
for d in range(dim):
trajectory = list(X[sample_n,:,d... | 7bff6c0da9342501e0b230e423ca5a2201757f40 | 3,636,839 |
async def get_prices(database, match_id):
"""Get market prices."""
query = """
select
timestamp::interval(0), extract(epoch from timestamp)::integer as timestamp_secs,
round((food + (food * .3)) * 100) as buy_food, round((wood + (wood * .3)) * 100) as buy_wood, round((stone + (st... | 3571006c37319135a3202622b73e7e2379ca93ee | 3,636,841 |
def isChinese():
"""
Determine whether the current system language is Chinese
确定当前系统语言是否为 中文
"""
return SYSTEM_LANGUAGE == 'zh_CN' | 8de1502c153189bc66774569fc00b2408d4ed694 | 3,636,844 |
def load_db(db):
"""
Load database as a dataframe. Extracts the zip files if necessary. The database is indexed by the user, session.
"""
if DEV_GENUINE == db or DEV_IMPOSTOR == db:
extract_dev_db()
if GENUINE == db or UNKNOWN == db:
extract_test_db()
return pd.read_csv(db, ind... | 9ebab9118d7572575fc3b82bbb02bdf1de68e6f5 | 3,636,845 |
def _pool_tags(hash, name):
"""Return a dict with "hidden" tags to add to the given cluster."""
return dict(__mrjob_pool_hash=hash, __mrjob_pool_name=name) | de9a9e7faa4d4f9dd3bfe05cb26790ff8ae66397 | 3,636,848 |
from pathlib import Path
def clusters_dictionary():
"""
Read the column 'label' from final_dataframe.tsv' and return the clusters as a dictionary.
If the column 'label' is not in final_dataframe.tsv', call k_means_clustering and perform
the clustering.
:return: a dictionary, where the key is the c... | 6d47865a98a4b2136fd2ec9baf346a880ee8acfb | 3,636,850 |
def apply_wet_day_frequency_correction(ds, process):
"""
Parameters
----------
ds : xr.Dataset
process : {"pre", "post"}
Returns
-------
xr.Dataset
Notes
-------
[1] A.J. Cannon, S.R. Sobie, & T.Q. Murdock, "Bias correction of GCM precipitation by quantile mapping: How wel... | e974a19d537888b866cf3117524815559c28108a | 3,636,852 |
def get_nb_build_nodes_and_entities(city, print_out=False):
"""
Returns number of building nodes and building entities in city
Parameters
----------
city : object
City object of pycity_calc
print_out : bool, optional
Print out results (default: False)
Returns
-------
... | ff3b36dcd2ca7cd0be316b573f20a6dd16bd1c1d | 3,636,853 |
def generate_pairs(agoals, props):
"""Forms all the pairs that are applicable to the current goals"""
all_pairs = []
for i in range(0, len(agoals)):
for j in range(i, len(agoals)):
goal1, goal2 = agoals[i], agoals[j]
all_pairs.extend(list(form_pairs(goal1, goal2, props)))
... | d0c7881682f057207db22cf5fb612f1a42d10c6d | 3,636,854 |
def construct_aircraft_data(args):
"""
create the set of aircraft data
:param args: parser argument class
:return: aircraft_name(string), aircraft_data(list)
"""
aircraft_name = args.aircraft_name
aircraft_data = [args.passenger_number,
args.overall_length,
... | da77ae883d67879b9c51a511f46173eb5366aead | 3,636,855 |
def Oplus_simple(ne):
"""
"""
return ne | 7476203cb99ee93dddcf9fda249f5532e908e40f | 3,636,856 |
def lin_exploit(version):
"""
The title says it all :)
"""
kernel = version
startno = 119
exploits_2_0 = {
'Segment Limit Privilege Escalation': {'min': '2.0.37', 'max': '2.0.38', 'cve': ' CVE-1999-1166', 'src': 'https://www.exploit-db.com/exploits/19419/'}
}
exploits_2_2 = {
... | 499e21091fb508b26564d06ad119d8b8ea783443 | 3,636,857 |
async def get_device(
hass: HomeAssistant,
config_entry_id: str,
device_category: str,
device_type: str,
vin: str,
):
"""Get a tesla Device for a Config Entry ID."""
entry_data = hass.data[TESLA_DOMAIN][config_entry_id]
devices = entry_data["devices"].get(device_category, [])
for d... | 8a3be6e7d1a5f69790b98d07433af1b6e6fe1b16 | 3,636,858 |
def cartesian2complex(real, imag):
"""
Calculate the complex number from the cartesian form: z = z' + i * z".
Args:
real (float|np.ndarray): The real part z' of the complex number.
imag (float|np.ndarray): The imaginary part z" of the complex number.
Returns:
z (complex|np.ndar... | 1fd44bc0accff8c9f26edfa84f4fcfafb2323728 | 3,636,859 |
def compare_maps(ra_id, method_id, type_id, method_comp=None, type_comp=None):
"""Function to compare maps / or just print off a given map"""
# Get the map
map_one = GPVal.objects.filter(my_anal_id=ra_id,
type_id=type_id,
method_id=method_id)
if meth... | 57008a0ad144974a06ae0a12de8a8133924c50e9 | 3,636,860 |
def _row_reduce_list(mat, rows, cols, one, iszerofunc, simpfunc,
normalize_last=True, normalize=True, zero_above=True,
dotprodsimp=None):
"""Row reduce a flat list representation of a matrix and return a tuple
(rref_matrix, pivot_cols, swaps) where ``rref_matrix`` is a flat list,... | a3791c303b483b158f766bacac73fd0ba63f5f18 | 3,636,861 |
import importlib
def get_action_class(class_str):
"""Imports the action class.
Args:
class_str (str): A string action class.
Returns:
Action: A child class of Action.
Raises:
ActionImportError: If the class doesn't exist.
"""
(module_name, class_name) = class_str.rsplit('.... | fdbf6f793d8a864b82f491a15c2a0268b14715b6 | 3,636,862 |
def rate_comments(request):
""" Render a bloom page where respondents can rate comments by others. """
return render(request, 'rate-comments.html') | f87777be409d79abc6c9649ec6dbe6df8cdb2ab4 | 3,636,863 |
def gaussian2d(size=(32, 32), sigma=0.5):
"""
Generate a Gaussian kernel (not normalized).
:param size: k x m size of the returned kernel
:param sigma: standard deviation of the returned Gaussian
:return: A tensor with the Gaussian kernel
"""
x, y = tf.meshgrid(tf.linspace(-1.0, 1.0, size[0... | 4a27fffe68fb031e6f47304bece9e8cfffd7224b | 3,636,864 |
def home():
"""
List all users or add new user
"""
users = User.query.all()
return render_template('home.html', users=users) | 4fb67376f51d677c544ba745680bc9fefed0ced0 | 3,636,865 |
def vgg13_bn(**kwargs):
"""
VGG 13-layer model (configuration "B") with batch normalization
"""
model = VGG(make_layers(cfg['B'], batch_norm=True), **kwargs)
return model | 3d1ac037754384cf37dbb35c1589cbbeebc3d698 | 3,636,866 |
def lr_insight_wr():
"""Return 5-fold cross validation scores r2, mae, rmse"""
steps = [('scaler', t.MyScaler(dont_scale='for_profit')),
('knn', t.KNNKeepDf())]
pipe = Pipeline(steps)
pipe.fit(X_raw)
X = pipe.transform(X_raw)
lr = LinearRegression()
lr.fit(X, y)
cv_results ... | 6d98e5e92ba10e390e96b3494a9dedb2c118df69 | 3,636,867 |
import collections
def complete_list_value(exe_context, return_type, field_asts, info, result):
"""
Complete a list value by completing each item in the list with the inner type
"""
assert isinstance(result, collections.Iterable), \
('User Error: expected iterable, but did not find one ' +
... | bc5af63592ccf6e08bf8f7da14f7852b78ec1ff0 | 3,636,868 |
def projection_ERK(rkm, dt, f, eta, deta, w0, t_final):
"""Explicit Projection Runge-Kutta method."""
rkm = rkm.__num__()
w = np.array(w0) # current value of the unknown function
t = 0 # current time
ww = np.zeros([np.size(w0), 1]) # values at each time step
ww[:,0] = w.copy()
tt = np.zeros... | 137e81c1d4764cde38985d15d04716138b90ccab | 3,636,869 |
def integer(name, value):
"""Validate that the value represents an integer
:param name: Name of the argument
:param value: A value representing an integer
:returns: The value as an int, or None if value is None
:raises: InvalidParameterValue if the value does not represent an integer
"""
if... | bcdb6e02944edc875e42a1e23209ec5002b205f6 | 3,636,870 |
def generate_Euler_Maruyama_propagators():
"""
importer function
function that creates two functions:
1. first function created is a kernel propagator (K)
2. second function returns the kernel ratio calculator
"""
# let's make the kernel propagator first: this is just a batched ULA move
... | d9bc844761e7f0d1689492ebc51159e64d64e4d9 | 3,636,871 |
def get_vtx_neighbor(vtx, faces, n=1, ordinal=False, mask=None):
"""
Get one vertex's n-ring neighbor vertices
Parameters
----------
vtx : integer
a vertex's id
faces : numpy array
the array of shape [n_triangles, 3]
n : integer
specify which ring should be got
o... | 58601345c35a96e4d0e58bfa2821dbc80f911c6c | 3,636,872 |
def tolower(x: StringOrIter) -> StringOrIter:
"""Convert strings to lower case
Args:
x: A string or vector of strings
Returns:
Converted strings
"""
x = as_character(x)
if is_scalar(x):
return x.lower()
return Array([elem.lower() for elem in x]) | 7b35e364aac78ce6e087aeeba9970e9981cdc7f0 | 3,636,875 |
import numpy
import math
def MWA_Tile_analytic(za, az,
freq=100.0e6,
delays=None,
zenithnorm=True,
power=False,
dipheight=config.DIPOLE_HEIGHT,
dip_sep=config.DIPOLE_SEPARATION,
... | 7d1a8a2b8f02c5ae47bcc85302d670a9e3e4d413 | 3,636,876 |
import json
def traindata():
"""Generate Plots in the traindata page.
Args:
None
Returns:
render_template(render_template): Render template for the plots
"""
# read data and create visuals
df_features = read_data_csv("./data/features... | 513312785a8ba7621693c05606e457b535b39c90 | 3,636,877 |
def import_file(file_path, title, source_mime_type, dest_mime_type):
"""Imports a file with conversion to the native Google document format.
Expects the env var GOOGLE_APPLICATION_CREDENTIALS to be set for
credentials.
Args:
path (str): Path to file to import
title(str): The title of th... | 386994c49895accb1433879b43d0e7a9e0b37beb | 3,636,878 |
def test_extract_requested_slot_from_text_with_not_intent():
"""Test extraction of a slot value from text with certain intent
"""
# noinspection PyAbstractClass
class CustomFormAction(FormAction):
def slot_mappings(self):
return {"some_slot": self.from_text(not_intent='some_intent')}... | a96deace8c9d291c3b67a13c250e84a519012fa7 | 3,636,879 |
def create_generic_io_object(ioclass, filename=None, directory=None,
return_path=False, clean=False):
"""
Create an io object in a generic way that can work with both
file-based and directory-based io objects
If filename is None, create a filename.
If return_path is Tr... | 1f10537695f507f9ea0c9eec6834efd7c0d6d6fe | 3,636,881 |
def select_channels(img_RGB):
"""
Returns the R' and V* channels for a skin lesion image.
Args:
img_RGB (np.array): The RGB image of the skin lesion
"""
img_RGB_norm = img_RGB / 255.0
img_r_norm = img_RGB_norm[..., 0] / (
img_RGB_norm[..., 0] + img_RGB_norm[..., 1] + img_RGB_nor... | 7daacf660c30702b8cbbe6da5da97937d11c0c0a | 3,636,882 |
def upper_case(string):
"""
Returns its argument in upper case.
:param string: str
:return: str
"""
return string.upper() | bbf3fc8b856d466ec73229145443566d85a3457a | 3,636,883 |
import json
def repositoryDefinitions():
"""
Load repositoryDefinitions page
"""
i_d = wmc.repository.get_definition_details()
p_d = json.dumps(i_d, indent=4) + " "
msg = Markup(JSONtoHTML(p_d))
return render_template('repositoryDefinitions.html', data=msg) | a4325e962a81421b4a35c4919d1fa637ae267a0a | 3,636,884 |
def available_adapter_names():
"""Return a string list of the available adapters."""
return [str(adp.name) for adp in plugins.ActiveManifest().adapters] | b5674e901de02bc9e2b94cb9fa8b0885b197cb21 | 3,636,885 |
def count_sort(seq):
""" perform count sort and return sorted sequence without
affecting the original
"""
counts = defaultdict(list)
for elem in seq:
counts[elem].append(elem)
result = []
for i in range(min(seq), max(seq)+1):
result.extend(counts[i])
return result | a035592a9a258f138f0064f4f733f405ee2b75d0 | 3,636,888 |
def detect_overrides(cls, obj):
"""
For each active plugin, check if it wield a packet hook. If it does, add
make a not of it. Hand back all hooks for a specific packet type when done.
"""
res = set()
for key, value in cls.__dict__.items():
if isinstance(value, classmethod):
... | 55b7299c6239050dd94e8e4ffc3484f987c60125 | 3,636,889 |
def morningCalls():
"""localhost:8080/morningcalls"""
session = APIRequest.WebServiceSafra()
return session.listMorningCalls() | 181d491ddd9549ff8cb3b15c66201ee6b9a88249 | 3,636,890 |
def resize_image(img, h, w):
""" resize image """
image = cv2.resize(img, (w, h), interpolation=cv2.INTER_NEAREST)
return image | f4e1c8f24abb44714d3894a255b32d50e72e09b5 | 3,636,891 |
from typing import Dict
def _parse_pars(pars) -> Dict:
"""
Takes dictionary of parameters, converting values to required type
and providing defaults for missing values.
Args:
pars: Parameters dictionary.
Returns:
Dictionary of converted (and optionally validated) parameters.
... | cda13c228f7764718ca0becceae3d721ba111eda | 3,636,892 |
def _get_base_class_names_of_parent_and_child_from_edge(schema_graph, current_location):
"""Return the base class names of a location and its parent from last edge information."""
edge_direction, edge_name = _get_last_edge_direction_and_name_to_location(current_location)
edge_element = schema_graph.get_edge... | 7860208cb305745f5c62aec664acd60a57715f48 | 3,636,893 |
from typing import Callable
def projection(
v: GridVariableVector,
solve: Callable = solve_fast_diag,
) -> GridVariableVector:
"""Apply pressure projection to make a velocity field divergence free."""
grid = grids.consistent_grid(*v)
pressure_bc = boundaries.get_pressure_bc_from_velocity(v)
q0 = grid... | e20ff776603be0faef2d63e29c58f99c255ec19d | 3,636,894 |
def a07_curve_function(curve: CustomCurve):
"""Computes the embedding degree (with respect to the generator order) and its complement"""
q = curve.q()
if q.nbits()>300:
return {"embedding_degree_complement":None,"complement_bit_length":None}
l = curve.order()
embedding_degree = curve.embeddi... | 1f06c9c4425e7d24241d425cfbd9a764d6589963 | 3,636,895 |
def _horizontal_metrics_from_coordinates(xcoord,ycoord):
"""Return horizontal scale factors computed from arrays of projection
coordinates.
Parameters
----------
xcoord : xarray dataarray
array of x_coordinate used to build the grid metrics.
either plane_x_coord... | a366c37172bed098607e4c5c7194812d3d82141f | 3,636,896 |
def ultosc(
df,
high,
low,
close,
ultosc,
time_period_1=7,
time_period_2=14,
time_period_3=28,
):
"""
The Ultimate Oscillator (ULTOSC) by Larry Williams is a momentum oscillator
that incorporates three different time periods to improve the overbought and
oversold signals.... | d6f69906bb09e3a7075339cd4a6554d5336f6caa | 3,636,897 |
def mating(child_id, parent1, parent2, gt_matrix):
"""
Given the name of a child and two parents + the genotype matrices, mate them
"""
child_gen = phase_parents(parent1, parent2, gt_matrix)
parent1.add_children(child_id)
parent2.add_children(child_id)
child = Person(child_id)
child.se... | 9962eb24ff175b0b2d77a787dbc50a342ed4a202 | 3,636,898 |
def _tmp(
generator_reconstructed_encoded_fake_data,
encoded_random_latent_vectors,
real_data,
encoded_real_data,
generator_reconstructed_encoded_real_data,
alpha=0.7,
scope="anomaly_score",
add_summaries=False):
"""anomaly score.
See https://arx... | 181bd45d23e14585072917d2ad707f13f13b7d4f | 3,636,899 |
def get_key_metrics_fig(confirmed_ser, recovered_ser, deaths_ser, metric_type):
"""
Return key metrics graph object figure
Parameters
----------
confirmed_ser: pandas.Series
Confirmed pandas series objects with index=dates,
values=number of cases
r... | a11130a21d124c2bf44a02d9c3c58bcde5a326cb | 3,636,900 |
from typing import List
def pr_curve(results: List[TrecEvalResults]) -> plt:
"""
Create a precision-recall graph from trec_eval results.
:param results: A list of TrecEvalResults files.
:return: a matplotlib plt object
"""
names = [r.run_id for r in results]
iprec = [[r.results['ipre... | 90f1e3234304fa7966b93ebdc76235e5356002e6 | 3,636,902 |
def plotData(datalist, part = "real", progressive = True, color = None, clip = False, tcutoff = None):
"""Plot real or imaginary parts of a given list of functions.
arguments:
datalist (list of tuples, each tuple of form (xlist,ylist)): data to plot;
xlist should be real numbers, ylist can be comp... | 5e328c19fe63389d7f2d55e5fd5d75d2dd5d7c24 | 3,636,903 |
def train_and_test(model, dataset, robustness_tests=None, base_config_dict=None, save_model=True):
"""
Train a recommendation model and run robustness tests.
Args:
model (str): Name of model to be trained.
dataset (str): Dataset name; must match the dataset's folder name located in 'data_pat... | 3681bc732b2b39837c871267f4659825105d6e2b | 3,636,904 |
def total_cost(content_cost, style_cost, alpha, beta):
"""Return a tensor representing the total cost."""
return alpha * content_cost + beta * style_cost | 98d42bd8d62dc8cd7110b2f5eb9a9a4e4eb6bc65 | 3,636,905 |
def create_command_using_pip_action(
num_bash_entries=10, uninstall_use_creation_time=False, skip=0):
"""Create commands using latest pip action."""
valid_pip_commands = get_valid_pip_history(num_bash_entries)[skip:]
assert valid_pip_commands, 'No undoable pip commands.'
last_valid_pip_command =... | 5ba22f63d33c1ae60ec3a93590965453885e5e29 | 3,636,906 |
def extract_word_pos_sequences(form, unknown_category, morpheme_splitter=None, extract_morphemes=False):
"""Return the unique word-based pos sequences, as well as (possibly) the morphemes, implicit in the form.
:param form: a form model object
:param morpheme_splitter: callable that splits a strings into i... | e08c285910c4da2f827f81ac65abc2ee3d62b1dc | 3,636,907 |
def model_test(Py, Px_y, testDataArr, testLabelArr):
"""
模型测试
@Args:
Py: 先验概率分布
Px_y: 条件概率分布
testDataArr: 测试集数据
testLabelArr: 测试集标签
@Returns:
准确率
@Riase:
"""
# 错误值
errorCnt = 0
# 循环遍历测试集中的每一个样本
for i in range(len(testDataArr... | f1e06725511750c79e34dc528728aab8cebc7c34 | 3,636,908 |
from typing import Optional
import torch
def int2c2e(shortname: str, wrapper: LibcintWrapper,
other: Optional[LibcintWrapper] = None) -> torch.Tensor:
"""
2-centre 2-electron integrals where the `wrapper` and `other1` correspond
to the first electron, and `other2` corresponds to another electr... | 1f5b6c70c8373c885103d6deb7cba77ea8d0aa73 | 3,636,909 |
def send_group_membership_request(request, group_id, template='group_send_request.html'):
"""
Send membership request to the administrator
of a private group.
"""
if request.method == 'POST':
form = GroupMembershipRequestForm(request.POST)
if form.is_valid():
group = Grou... | 22324765a915e1677fb6abab41dfa214fcc05d40 | 3,636,910 |
def _dataset_type_dir(signer):
"""Returns the directory name of the corresponding dataset type.
There is a `TFRecord` file written for each of the 25 signers. The `TFRecord` files of the first 17 signers are
assigned to the train dataset, the `TFRecord` files of the next 4 signers are assigned to the valid... | 515fd2e0871cf9549f3f724da0b45bb07f09e24b | 3,636,912 |
def _merge_blanks(src, targ, verbose=False):
"""Read parallel corpus 2 lines at a time.
Merge both sentences if only either source or target has blank 2nd line.
If both have blank 2nd lines, then ignore.
Returns tuple (src_lines, targ_lines), arrays of strings sentences.
"""
merges_done = [] #... | fe5f765022b2b4de5320272701148cc9f8e691b8 | 3,636,913 |
import codecs
def get_line(file_path, line_rule):
"""
搜索指定文件的指定行到指定行的内容
:param file_path: 指定文件
:param line_rule: 指定行规则
:return:
"""
s_line = int(line_rule.split(',')[0])
e_line = int(line_rule.split(',')[1][:-1])
result = []
# with open(file_path) as file:
file = codecs.o... | a6ccda48f8083e5ff6827306f4abd7f19e8d445c | 3,636,914 |
def _generate_odd_sequence(sequence_id: int, start_value: int,
k_factor: int, max_iterations: int):
"""
This method generates a Collatz sequence containing only odd numbers.
:param sequence_id: ID of the sequence.
:param start_value: The integer value to start with. The value... | d886631d153531fafa2cd9b15be621df9746a909 | 3,636,915 |
def _is_unique_rec_name(info_name):
"""
helper method to see if we should use the uniqueness recommendation on the
fact comparison
"""
UNIQUE_INFO_SUFFIXES = [".ipv4_addresses", ".ipv6_addresses", ".mac_address"]
UNIQUE_INFO_PREFIXES = ["fqdn"]
if info_name.startswith("network_interfaces.lo... | cba744e1e5b6a9612363d2ca12d4751e1894c8ad | 3,636,917 |
def initialized():
"""
Connection finished initializing?
"""
return __context__["netmiko_device"].get("initialized", False) | 6ca85744478bdb17ac99ce827825cde1db8bae3a | 3,636,918 |
def n_round(a, b):
"""safe round"""
element_round = np.vectorize(np.round)
return element_round(a, intify(b)) | 2c38e1585b71d5717ea3cc560521b8a006ceeee3 | 3,636,919 |
def _json_view_params(shape, affine, vmin, vmax, cut_slices, black_bg=False,
opacity=1, draw_cross=True, annotate=True, title=None,
colorbar=True, value=True):
""" Create a dictionary with all the brainsprite parameters.
Returns: params
"""
# Set color pa... | 50ea71a5a99facf4c472f0c18984d84e23b8e301 | 3,636,920 |
from typing import List
from datetime import datetime
def get_timestamps_from_df_data(df) -> List[datetime.datetime]:
"""Get a list of timestamp from rows of a DataFrame containing
raw data.
"""
timestamps = []
for index, row in df.iterrows():
year = int(row["dteday"][:4... | 21f985ebf28d6f5819635a13294e8db0544a292b | 3,636,921 |
def select(var_name, attr_name=None):
"""
Return attribute(s) of a variable given the variable name and an optional field name, or list of attribute name(s)
:param var_name: Name of the variable we're interested in.
:param attr_name: A string representing the name of the attribute whose value we want to... | 22b65439ff4dc831c2fb334595b0f0cd2e764b67 | 3,636,923 |
import re
def _parseWinBuildTimings(logfile):
"""Variant of _parseBuildTimings for Windows builds."""
res = {'Compile': re.compile(r'\d+>Time Elapsed (\d+):(\d+):([0-9.]+)'),
'Test running': re.compile(r'.*?\.+.*?([0-9.]+) sec')}
times = dict([(k, 0.0) for k in res])
for line in logfile:
... | 0473c426d29bb7fe44ff3384f81962f121c11afa | 3,636,924 |
def get_malid(anime: AnimeThemeAnime) -> int:
"""
Returns anime theme of resource.
"""
for resource in anime['resources']:
if resource["site"] == "MyAnimeList":
return resource['external_id'] | a745f95e73e8e061d98100e314faf5a662d69693 | 3,636,926 |
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