content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def get_default_interpreter():
"""Returns an instance of the default interpreter class."""
return __default_interpreter.get() | 8807e2480787d26e81ab1be3377f8e3a11daa1de | 3,655,221 |
def fx_ugoira_frames():
"""frames data."""
return {
'000000.jpg': 1000,
'000001.jpg': 2000,
'000002.jpg': 3000,
} | e3517b37bb4c9cd1dfb70b13128d16ef80a9801a | 3,655,222 |
import array
def coherent_tmm(pol, n_list, d_list, th_0, lam_vac):
"""
This is my slightly modified version of byrnes's "coh_tmm"
I've rearranged the calculations in a way that is more intuitive to me
Example inputs:
For angle dependence, be careful to include air first, otherwise the angle ... | 3e10041325ee211d684c9ad960b445df8e6de2db | 3,655,223 |
def base_info():
"""
基本资料的展示和修改
1、尝试获取用户信息
2、如果是get请求，返回用户信息给模板
如果是post请求：
1、获取参数，nick_name,signature,gender[MAN,WOMAN]
2、检查参数的完整性
3、检查gender性别必须在范围内
4、保存用户信息
5、提交数据
6、修改redis缓存中的nick_name
注册：session['nick_name'] = mobile
登录：session['nick_name'] = user.nick_name
修... | 87d5595171e2cecc469ea933b210783e15c477d2 | 3,655,224 |
def to_list(obj):
""" """
if isinstance(obj, np.ndarray):
return obj.tolist()
raise TypeError('Not serializable') | 92e4851bb117ab908dc256f8b42ef03c85d70e28 | 3,655,225 |
from sage.symbolic.expression import Expression
from sage.symbolic.ring import SR
from inspect import signature, Parameter
def symbolic_expression(x):
"""
Create a symbolic expression or vector of symbolic expressions from x.
INPUT:
- ``x`` - an object
OUTPUT:
- a symbolic expression.
... | 648c85a8fd3f4ffefec44e5720f8c9ac68c10388 | 3,655,226 |
def seq_hyphentation(words):
"""
Converts words in a list of strings into lists of syllables
:param words: a list of words (strings)
:return: a list of lists containing word syllables
"""
return [hyphenation(w) for w in words] | dd1ab65f64926e724718edac316a98bac99991da | 3,655,227 |
def angle(A, B, dim=1):
"""
Computes the angle in radians between the inputs along the specified dimension
Parameters
----------
A : Tensor
first input tensor
B : Tensor
second input tensor
dim : int (optional)
dimension along the angle is computed (default is 1)
... | f64950b8004a32e2ab274efee3a9bedf6441439a | 3,655,228 |
import functools
def _run_lint_helper(
*, fail_on_missing_sub_src, exclude_lint, warn_lint, site_name=None):
"""Helper for executing lint on specific site or all sites in repo."""
if site_name:
func = functools.partial(engine.lint.site, site_name=site_name)
else:
func = engine.lint... | a73e2e9a4bb968376622308cf7af2f97f6533595 | 3,655,229 |
def simulate_from_orders_nb(target_shape: tp.Shape,
group_lens: tp.Array1d,
init_cash: tp.Array1d,
call_seq: tp.Array2d,
size: tp.ArrayLike = np.asarray(np.inf),
price: tp.ArrayLik... | 32898fa1a1aadf50d6d07553da8e7bed94f3de0e | 3,655,230 |
def exp_map_individual(network, variable, max_degree):
"""Summary measure calculate for the non-parametric mapping approach described in Sofrygin & van der Laan (2017).
This approach works best for networks with uniform degree distributions. This summary measure generates a number
of columns (a total of ``m... | cb4424ad10dae3df4a3d60ec5d7b143b2130a9bb | 3,655,232 |
def bridge_meshes(Xs, Ys, Zs, Cs):
"""
Concatenate multiple meshes, with hidden transparent bridges, to a single mesh, so that plt.plot_surface
uses correct drawing order between meshes (as it really should)
:param list Xs: list of x-coordinates for each mesh
:param list Ys: list of y-coordinates fo... | 389948e3d357cb7a87e844eee8417f2466c41cab | 3,655,233 |
def get_groups():
"""
Get the list of label groups.
@return: the list of label groups.
"""
labels_dict = load_yaml_from_file("labels")
groups = []
for group_info in labels_dict["groups"]:
group = Group(**group_info)
label_names = group_info.pop("labels", [])
groups.a... | 03822287ab1a2525560f6fdf2a55a3c2461c6bea | 3,655,234 |
def diffractometer_rotation(phi=0, chi=0, eta=0, mu=0):
"""
Generate the 6-axis diffracometer rotation matrix
R = M * E * X * P
Also called Z in H. You, J. Appl. Cryst 32 (1999), 614-623
:param phi: float angle in degrees
:param chi: float angle in degrees
:param eta: float angle in degree... | 7f56caf6585f74406b8f681614c6a6f32592ad91 | 3,655,235 |
def supports_build_in_container(config):
"""
Given a workflow config, this method provides a boolean on whether the workflow can run within a container or not.
Parameters
----------
config namedtuple(Capability)
Config specifying the particular build workflow
Returns
-------
tu... | 278bde73252d13784298d01d954a56fcecd986dc | 3,655,236 |
def get_img_array_mhd(img_file):
"""Image array in zyx convention with dtype = int16."""
itk_img = sitk.ReadImage(img_file)
img_array_zyx = sitk.GetArrayFromImage(itk_img) # indices are z, y, x
origin = itk_img.GetOrigin() # x, y, z world coordinates (mm)
origin_zyx = [origin[2], origin[1], origin... | 6c6bafedf34aaf0c03367c9058b29401bf133fd0 | 3,655,237 |
def registration(request):
"""Render the registration page."""
if request.user.is_authenticated:
return redirect(reverse('index'))
if request.method == 'POST':
registration_form = UserRegistrationForm(request.POST)
if registration_form.is_valid():
r... | dae59392e290291d9d81ca427ee35b07c6ed554b | 3,655,238 |
def _get_arc2height(arcs):
"""
Parameters
----------
arcs: list[(int, int)]
Returns
-------
dict[(int, int), int]
"""
# arc2height = {(b,e): np.abs(b - e) for b, e in arcs}
n_arcs = len(arcs)
arcs_sorted = sorted(arcs, key=lambda x: np.abs(x[0] - x[1]))
arc2height = {ar... | feb929e9f2e23e1c154423930ae33944b95af699 | 3,655,239 |
from shutil import copyfile
def init_ycm(path):
"""
Generate a ycm_extra_conf.py file in the given path dir to specify
compilation flags for a project. This is necessary to get
semantic analysis for c-family languages.
Check ycmd docs for more details.
"""
conf = join(path, '.ycm_extra_... | 361d744982c2a8c4fd1e787408150381a3b111d3 | 3,655,240 |
def get_aggregate_stats_flows_single_appliance(
self,
ne_pk: str,
start_time: int,
end_time: int,
granularity: str,
traffic_class: int = None,
flow: str = None,
ip: str = None,
data_format: str = None
) -> dict:
"""Get aggregate flow stats data for a single appliance filter by
... | 5ca6e2b5ce1b176aea603a254b0ca655e0f43c0c | 3,655,241 |
def load_user(userid):
"""Callback to load user from db, called by Flask-Login"""
db = get_db()
user = db.execute("SELECT id FROM users WHERE id = ?", [userid]).fetchone()
if user is not None:
return User(user[0])
return None | 0dd9516af3670794c107bd6633c74a033f0a4983 | 3,655,242 |
import torch
def get_partial_outputs_with_prophecies(prophecies, loader, model, my_device,
corpus, seq2seq):
"""
Parameters
----------
prophecies : dict
Dictionary mapping from sequence index to a list of prophecies, one
for each prefix in... | cae0ed8643f677a5d2a2f3e75858b68f473acc50 | 3,655,243 |
from typing import Tuple
from typing import Optional
from typing import List
import io
import textwrap
from re import I
def _generate_deserialize_impl(
symbol_table: intermediate.SymbolTable,
spec_impls: specific_implementations.SpecificImplementations,
) -> Tuple[Optional[Stripped], Optional[List[Error]]]:
... | 3e2e3c78709b75a8b650d775d4b0f8b6c8287ca0 | 3,655,244 |
def timestep_to_transition_idx(snapshot_years, transitions, timestep):
"""Convert timestep to transition index.
Args:
snapshot_years (list): a list of years corresponding to the provided
rasters
transitions (int): the number of transitions in the scenario
timestep (int): the... | 96bcda2493fcd51f9c7b335ea75fd612384207e3 | 3,655,245 |
def resolve_checks(names, all_checks):
"""Returns a set of resolved check names.
Resolving a check name expands tag references (e.g., "@tag") to all the
checks that contain the given tag. OpenShiftCheckException is raised if
names contains an unknown check or tag name.
names should be a sequence o... | d86dcd9a5539aeaa31fb3c86304c62f8d86bbb11 | 3,655,247 |
from typing import Optional
def swish(
data: NodeInput,
beta: Optional[NodeInput] = None,
name: Optional[str] = None,
) -> Node:
"""Return a node which performing Swish activation function Swish(x, beta=1.0) = x * sigmoid(x * beta)).
:param data: Tensor with input data floating point type.
:r... | d17562d0e63aa1610d9bc641faabec27264a2919 | 3,655,248 |
from datetime import datetime
def cut_out_interval(data, interval, with_gaps=False):
"""
Cuts out data from input array.
Interval is the start-stop time pair.
If with_gaps flag is True, then one NaN value will be added
between the remaining two pieces of data.
Returns modified data array.
... | 753be7e45102a7e0adc1b19365d10e009c8f6b89 | 3,655,249 |
import re
def _abbreviations_to_word(text: str):
"""
对句子中的压缩次进行扩展成单词
:param text: 单个句子文本
:return: 转换后的句子文本
"""
abbreviations = [
(re.compile('\\b%s\\.' % x[0], re.IGNORECASE), x[1]) for x in [
('mrs', 'misess'),
('mr', 'mister'),
('dr', 'doctor'),
... | 576eb1588c40ab4b9ffa7d368249e520ecf887ba | 3,655,250 |
def resnet56(num_classes=100):
"""Constructs a ResNet-56 model for CIFAR-10 (by default)
Args:
num_classes (uint): number of classes
"""
model = CifarResNet(ResNetBasicblock, 56, num_classes)
return model | 98070a6a1b6f69b2d253537b604c616ae52de9b2 | 3,655,251 |
def pad_set_room(request):
"""
pad修改关联会议室
:param request:
:return:
"""
dbs = request.dbsession
user_id = request.POST.get('user_id', '')
room_id = request.POST.get('room_id', '')
pad_code = request.POST.get('pad_code', '')
if not user_id:
error_msg = '用户ID不能为空！'
elif ... | 1646204a666e68021c649b6d322b74cbcd515fd2 | 3,655,253 |
def airffromrh_wmo(rh_wmo,temp,pres,asat=None,dhsat=None,chkvals=False,
chktol=_CHKTOL,asat0=None,dhsat0=None,chkbnd=False,mathargs=None):
"""Calculate dry fraction from WMO RH.
Calculate the dry air mass fraction from the relative humidity. The
relative humidity used here is defined by the WMO as:... | 1e4418591087a4bd26b48c470239df58087cdb6e | 3,655,254 |
import base64
import zlib
def inflate(data: str) -> str:
"""
reverses the compression used by draw.io
see: https://drawio-app.com/extracting-the-xml-from-mxfiles/
see: https://stackoverflow.com/questions/1089662/python-inflate-and-deflate-implementations
:param data: base64 encoded string
:r... | e4456c7482591611436a92a71464754871461fd5 | 3,655,256 |
import operator
def get_tree(data_path,sep,root,cutoff,layer_max,up=True):
"""
This function takes the path of a data file of edge list with numeric
weights and returns a tree (DiGraph object). The parameters include:
data_path: The path of a data file of edge list with numeric weights.
sep: The ... | 6f2d151aac39786311c61da4f38140e6c0159562 | 3,655,257 |
def delete_functions(lambda_client, function_list) -> list:
"""Deletes all instances in the instances parameter.
Args:
lambda_client: A lambda boto3 client
function_list: A list of instances you want deleted.
Returns:
A count of deleted instances
"""
terminated_functions = ... | f0ca59647f6813d04bf2bbd6ec33ed7744acdd04 | 3,655,258 |
def make_random_shares(seed, minimum, n_shares, share_strength=256):
"""
Generates a random shamir pool for a given seed phrase.
Returns share points as seeds phrases (word list).
"""
if minimum > n_shares:
raise ValueError(
"More shares needed (%d) to recover the seed phrase tha... | a8496909cc06f3663d07036e54af744ac7e26b18 | 3,655,259 |
from typing import Optional
from typing import Sequence
def confusion_matrix(
probs: Optional[Sequence[Sequence]] = None,
y_true: Optional[Sequence] = None,
preds: Optional[Sequence] = None,
class_names: Optional[Sequence[str]] = None,
title: Optional[str] = None,
):
"""
Computes a multi-r... | c2b63ccf7e3f226b6bfbea4656bc816eaa6e336a | 3,655,260 |
import html
def get_monitor_details():
"""Render the index page."""
monitor_id = paranoid_clean(request.args.get('id'))
monitors = mongo.db[app.config['MONITORS_COLLECTION']]
monitor = monitors.find_one({'hashed': monitor_id}, {'_id': 0})
if not monitor:
return jsonify({'success': False, '... | 6a45ed67ff79216c9048ce9e3ed80be4e43b9bd9 | 3,655,261 |
def _simplify(obj: object) -> object:
"""
This function takes an object as input and returns a simple
Python object which is supported by the chosen serialization
method (such as JSON or msgpack). The reason we have this function
is that some objects are either NOT supported by high level (fast)
... | fc17b64e3701faa70ea5bfb36a8e2b9195dcbab1 | 3,655,262 |
import copy
def match_v2v3(aperture_1, aperture_2, verbose=False):
"""Use the V2V3 from aperture_1 in aperture_2 modifying X[Y]DetRef,X[Y]SciRef to match.
Also shift the polynomial coefficients to reflect the new reference point origin
and for NIRCam recalculate angles.
Parameters
----------
... | 295eb72c43f073f71b1cedaf8a94d6b1cc61dbf7 | 3,655,263 |
import time
def get_offset(sample_time):
"""
Find simple offsett values.
During the sample time of this function
the BBB with the magnetometer on should be rotated
along all axis.
sample_time is in seconds
"""
start = time.clock()
mag_samples = []
mag_max = [0,0,0]
mag_mi... | 712fe82dbdc50e198baf93b752f572331ce33f63 | 3,655,265 |
def get_multimode_2d_dist(num_modes: int = 1, scale: float = 1.0):
"""Get a multimodal distribution of Gaussians."""
angles = jnp.linspace(0, jnp.pi * 2, num_modes + 1)
angles = angles[:-1]
x, y = jnp.cos(angles) * scale / 2., jnp.sin(angles) * scale / 2.
loc = jnp.array([x, y]).T
scale = jnp.ones((num_mode... | dab5400e545feb7cde2804af151f3c20c600b0ce | 3,655,267 |
def residual_squared_error(data_1, data_2):
"""
Calculation the residual squared error between two arrays.
Parameters
----------
data: numpy array
Data
calc: numpy array
Calculated values
Return
------
rse: float
residual squared error
"""
RSS = np.... | 771c365fc38d6eda07989a1a6eb34c0f96347c3c | 3,655,268 |
def by_index(pot):
""" Build a new potential where the keys of the potential dictionary
correspond to the indices along values of n-dimensional grids,
rather than, possibly, the coordinate values of the grids themselves.
Key Transformation:
((grid_val_i, grid_val_j, ...)_i,) -> ((i,... | 7235322f606cf972c8bf4ad46a614001f235b3e9 | 3,655,269 |
def current_user():
"""Получить текущего пользователя или отредактировать профиль"""
user = get_user_from_request()
if request.method == "POST":
json = request.get_json()
user.email = json.get("email", user.email)
user.name = json.get("name", user.name)
user.about = sanitiz... | e7e3db1744e21c64732217e1609a113b938c677c | 3,655,270 |
from datetime import datetime
async def async_union_polygons(bal_name, geom_list):
"""union a set of polygons & return the resulting multipolygon"""
start_time = datetime.now()
big_poly = unary_union(geom_list)
print(f"\t - {bal_name} : set of polygons unioned: {datetime.now() - start_time}")
r... | 2432818d6bb38232e08a4439e7a69007a7c24334 | 3,655,271 |
def _error_text(because: str, text: str, backend: usertypes.Backend) -> str:
"""Get an error text for the given information."""
other_backend, other_setting = _other_backend(backend)
if other_backend == usertypes.Backend.QtWebKit:
warning = ("<i>Note that QtWebKit hasn't been updated since "
... | cb4fda8ab6c06d01ae01e6226d435d30cd0bd971 | 3,655,272 |
def COUNT(condition: pd.DataFrame, n: int):
"""the number of days fits the 'condition' in the past n days
Args:
condition (pd.DataFrame): dataframe index by date time(level 0) and asset(level 1), containing bool values
n (int): the number of past days
"""
return condition.rolling(n, ce... | ed380061249803e9c378950a88dc5162543cfee0 | 3,655,273 |
def Mat33_nrow():
"""Mat33_nrow() -> int"""
return _simbody.Mat33_nrow() | 7f22177bcf150458e6545ed204e47b3326ce6193 | 3,655,274 |
def isstruct(ob):
""" isstruct(ob)
Returns whether the given object is an SSDF struct.
"""
if hasattr(ob, '__is_ssdf_struct__'):
return bool(ob.__is_ssdf_struct__)
else:
return False | 465196af79c9de1f7685e0004e92b68a7f524149 | 3,655,275 |
def where_between(field_name, start_date, end_date):
"""
Return the bit of query for the dates interval.
"""
str = """ {0} between date_format('{1}', '%%Y-%%c-%%d %%H:%%i:%%S')
and date_format('{2}', '%%Y-%%c-%%d 23:%%i:%%S')
""" .format( field_name,
... | 4801d01ac8743f138e7c558da40518b75ca6daed | 3,655,276 |
def to_console_formatted_string(data: dict) -> str:
"""..."""
def make_line(key: str) -> str:
if key.startswith('__cauldron_'):
return ''
data_class = getattr(data[key], '__class__', data[key])
data_type = getattr(data_class, '__name__', type(data[key]))
value = '{... | 05cec50b3eee8199b19024aae32dda2a8ba33115 | 3,655,277 |
def cluster_instance_get_info_ajax(request, c_id):
"""
get cluster instance status
"""
dic = {"res": True, "info":None, "err":None}
instance_id = request.GET.get("instance_id")
require_vnc = request.GET.get("require_vnc")
if require_vnc == "true":
require_vnc = True
else:
require_vnc = False
if instance_id... | 1c000a659893b375a2e89faadedccde7ca8dcab6 | 3,655,278 |
import time
def timeit(verbose=False):
"""
Time functions via decoration. Optionally output time to stdout.
Parameters:
-----------
verbose : bool
Example Usage:
>>> @timeit(verbose=True)
>>> def foo(*args, **kwargs): pass
"""
def _timeit(f):
@wraps(f)
def wra... | 5e8e0441914b5d26db99fc378374bebde2d39376 | 3,655,279 |
def signal_period(peaks, sampling_rate=1000, desired_length=None,
interpolation_order="cubic"):
"""Calculate signal period from a series of peaks.
Parameters
----------
peaks : list, array, DataFrame, Series or dict
The samples at which the peaks occur. If an array is passed i... | dae9a7af6d23fdaa1f742cbc3b18649a525c4041 | 3,655,280 |
import google.cloud.dataflow as df
from google.cloud.dataflow.utils.options import PipelineOptions
def model_co_group_by_key_tuple(email_list, phone_list, output_path):
"""Applying a CoGroupByKey Transform to a tuple.
URL: https://cloud.google.com/dataflow/model/group-by-key
"""
p = df.Pipeline(options=Pipel... | 7256b9dac30fe731011729ea463e37b39d8c4dde | 3,655,281 |
def get_recommendation(anime_name, cosine_sim, clean_anime, anime_index):
"""
Getting pairwise similarity scores for all anime in the data frame.
The function returns the top 10 most similar anime to the given query.
"""
idx = anime_index[anime_name]
sim_scores = list(enumerate(cosine_sim[idx]))... | 93bc3e53071200810b34e31674fcaa0a98cdaebb | 3,655,282 |
def get_nwb_metadata(experiment_id):
"""
Collects metadata based on the experiment id and converts the weight to a float.
This is needed for further export to nwb_converter.
This function also validates, that all metadata is nwb compatible.
:param experiment_id: The experiment id given by the us... | 9882e71cb869e1ebf762fd851074d316b9fda462 | 3,655,283 |
from typing import Tuple
from typing import Union
def string_to_value_error_mark(string: str) -> Tuple[float, Union[float, None], str]:
"""
Convert string to float and error.
Parameters
----------
string : str
DESCRIPTION.
Returns
-------
value : float
Value.
erro... | c2c69c419d44e8342376ee24f6a4ced6ee2090e7 | 3,655,284 |
import itertools
def _children_with_tags(element, tags):
"""Returns child elements of the given element whose tag is in a given list.
Args:
element: an ElementTree.Element.
tags: a list of strings that are the tags to look for in child elements.
Returns:
an iterable of ElementTree.Element instance... | 522151e7e9ad355e5c6850cef62093e1bd4ed0a0 | 3,655,285 |
def align_with_known_width(val, width: int, lowerBitCntToAlign: int):
"""
Does same as :func:`~.align` just with the known width of val
"""
return val & (mask(width - lowerBitCntToAlign) << lowerBitCntToAlign) | 8c9b7ffd8fced07f2ca78db7665ea5425417e45a | 3,655,287 |
def get_email_from_request(request):
"""Use cpg-utils to extract user from already-authenticated request headers."""
user = get_user_from_headers(request.headers)
if not user:
raise web.HTTPForbidden(reason='Invalid authorization header')
return user | 60872f86bb69de6b1b339f715a2561dafd231489 | 3,655,288 |
from typing import List
from typing import Tuple
def get_kernels(params: List[Tuple[str, int, int, int, int]]) -> List[np.ndarray]:
"""
Create list of kernels
:param params: list of tuples with following format ("kernel name", angle, multiplier, rotation angle)
:return: list of kernels
"""
ker... | b39fd152fe94f4c52398ae4984414d2cefbf401f | 3,655,289 |
def forward_propagation(propagation_start_node, func, x):
"""A forward propagation starting at the `propagation_start_node` and
wrapping the all the composition operations along the way.
Parameters
----------
propagation_start_node : Node
The node where the gradient function (or anything si... | 12fbbb53fd329aacdf5f5fffbfa2a81342663fb8 | 3,655,290 |
def read_entities():
"""
find list of entities
:return:
"""
intents = Entity.objects.only('name','id')
return build_response.sent_json(intents.to_json()) | 842ec7506b49abd6557219e2c9682bdd48df86fb | 3,655,292 |
def available(unit, item) -> bool:
"""
If any hook reports false, then it is false
"""
for skill in unit.skills:
for component in skill.components:
if component.defines('available'):
if component.ignore_conditional or condition(skill, unit):
if not... | 7550a197e2d877ef4ff622d08a056be434f1f06e | 3,655,293 |
def cleanArray(arr):
"""Clean an array or list from unsupported objects for plotting.
Objects are replaced by None, which is then converted to NaN.
"""
try:
return np.asarray(arr, float)
except ValueError:
return np.array([x if isinstance(x, number_types) else None
... | 7ab7d645209ad0815a3eb831a1345cdad0ae4aba | 3,655,294 |
def _ensure_args(G, source, method, directed,
return_predecessors, unweighted, overwrite, indices):
"""
Ensures the args passed in are usable for the API api_name and returns the
args with proper defaults if not specified, or raises TypeError or
ValueError if incorrectly specified.
... | 6d9168de0d25f5ee4d720347182763ad744600a6 | 3,655,296 |
def read_siemens_scil_b0():
""" Load Siemens 1.5T b0 image form the scil b0 dataset.
Returns
-------
img : obj,
Nifti1Image
"""
file = pjoin(dipy_home,
'datasets_multi-site_all_companies',
'1.5T',
'Siemens',
'b0.nii.gz'... | edf700fc6e14a35b5741e4419ba96cb753188da8 | 3,655,297 |
def gdpcleaner(gdpdata: pd.DataFrame):
"""
Author: Gabe Fairbrother
Remove spurious columns, Rename relevant columns, Remove NaNs
Parameters
----------
gdpdata: DataFrame
a loaded dataframe based on a downloaded Open Government GDP at basic prices dataset (https://open.canada.ca/en/open... | 4c685a244a746f05fbef5216518e23a956ae8da7 | 3,655,298 |
import re
def sort_with_num(path):
"""Extract leading numbers in a file name for numerical sorting."""
fname = path.name
nums = re.match('^\d+', fname)
if nums:
return int(nums[0])
else:
return 0 | 2209384720c33b8201c06f7a14b431972712814a | 3,655,299 |
import sqlite3
def prob8(cur: sqlite3.Cursor) -> pd.DataFrame:
"""Give a list of the services which connect the stops 'Craiglockhart' and
'Tollcross'.
Parameters
----------
cur (sqlite3.Cursor) : The cursor for the database we're accessing.
Returns
-------
(pd.DataFrame) ... | 14e8bbb04befc1116f969ca977d83bc27890664c | 3,655,300 |
def get_command(name):
""" return command represented by name """
_rc = COMMANDS[name]()
return _rc | 22e64898973d2a2ec1cca2ff72fa86eaed4a3546 | 3,655,301 |
def _str_struct(a):
"""converts the structure to a string for logging purposes."""
shape_dtype = lambda x: (jnp.asarray(x).shape, str(jnp.asarray(x).dtype))
return str(jax.tree_map(shape_dtype, a)) | 96d417c6cd1332d6e71b21472444cf6178cad92a | 3,655,302 |
def delete_interface_address(
api_client, interface_id, address_id, **kwargs
): # noqa: E501
"""delete_interface_address # noqa: E501
Delete interface address details # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_re... | 19d04ef0783988c8eb86983d589d9f07e82ba3b8 | 3,655,304 |
import types
async def set_promo(message: types.Message, state: FSMContext):
"""
Команда /setpromo
"""
arg = message.get_args()
if not arg:
return await message.answer(_("Укажите аргумент: промокод. Например: <pre>/set_promo my-promo-code</pre>"),
parse... | 9a15dd1bea20c3da6dd31eee5e2a723ddd110ba2 | 3,655,305 |
def plot_waterfall(*sigObjs, step=10, xLim:list=None,
Pmin=20, Pmax=None, tmin=0, tmax=None, azim=-72, elev=14,
cmap='jet', winPlot=False, waterfallPlot=True, fill=True,
lines=False, alpha=1, figsize=(20, 8), winAlpha=0,
removeGridLines=False, ... | 85888e49a938a5e4faac90c52b2df7fa7036610c | 3,655,306 |
import csv
import re
def indices(input_file):
"""
Parse the index file or target file and return a list of values.
:return:
"""
index_list = []
line_num = 0
index_file = list(csv.reader(open(input_file), delimiter='\t'))
for line in index_file:
line_num += 1
col_count ... | ea07d6f2bc8f3d23cf2ae59cb2df6c19158752fc | 3,655,307 |
def has_same_facts(ruler_intervals1, ruler_intervals2, D):
"""
Check whether the two same-pattern ruler lists have the same facts at each corresponding ruler-interval
Args:
ruler_intervals1: a list of ruler-intervals
ruler_intervals2: a list of ruler-intervals
D: contain all relation... | 210540bd2c2062f3150a34c5911017ec49b5603f | 3,655,310 |
def main():
""" """
undet = argument_parse()
print 'Start\t|\tCheck incorrect index'
fq_list = split_fastq(undet)
print 'Process\t|\tAnalysis undetermined data'
combined_df = multi_process(fq_list)
sorted_combined_df = combined_df.sort_values(
by='count',
ascending=F... | e20f65e172f49ce2f184b32344135ccadb550253 | 3,655,311 |
def ruleset_delete(p_engine, p_username, rulesetname, envname):
"""
Delete ruleset from Masking engine
param1: p_engine: engine name from configuration
param2: rulesetname: ruleset name
return 0 if added, non 0 for error
"""
return ruleset_worker(p_engine=p_engine, p_username=p_username, ru... | 470e2d104a6d10737bba975a0cb15a4768238244 | 3,655,312 |
def config_from_file(file_name):
"""Load and return json from file."""
with open(file_name) as config_file:
config = ujson.load(config_file)
return config | 2dd1b57612c528a85dbe04c717800b6908cb9c40 | 3,655,313 |
def build_yaml_object(
dataset_id: str,
table_id: str,
config: dict,
schema: dict,
metadata: dict = dict(),
columns_schema: dict = dict(),
partition_columns: list = list(),
):
"""Build a dataset_config.yaml or table_config.yaml
Args:
dataset_id (str): The dataset id.
... | 8fa7d3acac0e9636fda923d9a38e9a82f904afae | 3,655,314 |
from pathlib import Path
def make_cumulative(frame, filedate, unit):
"""Create a cumulative graph of cases over time"""
gb = frame.groupby("Accurate_Episode_Date").agg(patients=("Row_ID", "count"))
gb = gb.resample("D").last().fillna(0).reset_index()
max_date = gb["Accurate_Episode_Date"].max().strfti... | 44a2a1b3af68c293a86af97b11edf8cca562e6b8 | 3,655,316 |
def most_common(l):
""" Helper function.
:l: List of strings.
:returns: most common string.
"""
# another way to get max of list?
#from collections import Counter
#data = Counter(your_list_in_here)
#data.most_common() # Returns all unique items and their counts
#data.most_... | 5010e4e26b00099c287f8597d8dc5881a67c4034 | 3,655,317 |
def reduce_avg(reduce_target, lengths, dim):
"""
Args:
reduce_target : shape(d_0, d_1,..,d_dim, .., d_k)
lengths : shape(d0, .., d_(dim-1))
dim : which dimension to average, should be a python number
"""
shape_of_lengths = lengths.get_shape()
shape_of_target = reduce_target.g... | 3bba229f448d393019857d89d16820076732e932 | 3,655,318 |
def _near_mod_2pi(e, t, atol=_DEFAULT_ATOL):
"""Returns whether a value, e, translated by t, is equal to 0 mod 2 * pi."""
return _near_mod_n(e, t, n=2 * np.pi, atol=atol) | 465911aca0fe1a7cd397ed2304426da5fdaaccc3 | 3,655,319 |
def create_returns_similarity(strategy: QFSeries, benchmark: QFSeries, mean_normalization: bool = True,
std_normalization: bool = True, frequency: Frequency = None) -> KDEChart:
"""
Creates a new returns similarity chart. The frequency is determined by the specified returns series.... | a83a7d2171ee488c1ac9ede80f39778658a4538f | 3,655,320 |
def _cli():
"""
command line interface
:return:
"""
parser = generate_parser()
args = parser.parse_args()
return interface(args.bids_dir,
args.output_dir,
args.aseg,
args.subject_list,
args.session_list,
... | 0b37b2eab79c5f50d5f18b5d6b435e3b97682a36 | 3,655,322 |
import base64
def urlsafe_b64decode_nopadding(val):
"""Deal with unpadded urlsafe base64."""
# Yes, it accepts extra = characters.
return base64.urlsafe_b64decode(str(val) + '===') | 22ed00b07e16b4b557dc46b5caeb9f7ce9513c0d | 3,655,324 |
def _subimg_bbox(img, subimage, xc, yc):
"""
Find the x/y bounding-box pixel coordinates in ``img`` needed to
add ``subimage``, centered at ``(xc, yc)``, to ``img``. Returns
``None`` if the ``subimage`` would extend past the ``img``
boundary.
"""
ys, xs = subimage.shape
y, x = img.shap... | b299a6b3726ced525b538b4fea45b235fc0bd56e | 3,655,325 |
from datetime import datetime
def _ToDatetimeObject(date_str):
"""Converts a string into datetime object.
Args:
date_str: (str) A date and optional time for the oldest article
allowed. This should be in ISO 8601 format. (yyyy-mm-dd)
Returns:
datetime.datetime Object.
Raises:
... | df675cb5391456122bb350a126e0b4a4ed31fc49 | 3,655,326 |
def select_most_uncertain_patch(x_image_pl, y_label_pl, fb_pred, ed_pred, fb_prob_mean_bald, kernel_window, stride_size,
already_select_image_index, previously_selected_binary_mask, num_most_uncert_patch,
method):
"""This function is used to acquire th... | 21f40e34b1436d91eca041998cb927800cc10f7b | 3,655,327 |
import requests
import json
def submit_extraction(connector, host, key, datasetid, extractorname):
"""Submit dataset for extraction by given extractor.
Keyword arguments:
connector -- connector information, used to get missing parameters and send status updates
host -- the clowder host, including htt... | 449fc6c3c37ef8a5206a7ebe18b367885ae319a8 | 3,655,328 |
import math
def fcmp(x, y, precision):
"""fcmp(x, y, precision) -> -1, 0, or 1"""
if math.fabs(x-y) < precision:
return 0
elif x < y:
return -1
return 1 | 905421b36635ab830e2216ab34fee89f75c7f4c4 | 3,655,329 |
def parse_vcf_line(line):
"""
Args:
line (str): line in VCF file obj.
Returns:
parsed_line_lst (lst): with tuple elem (chr, pos, ref, alt)
Example:
deletion
pos 123456789012
reference ATTAGTAGATGT
deletion ATTA---GATGT
VCF:
... | 705c3bfe2ed3a0d4552dcbd18e8c08b73b84b40b | 3,655,330 |
def fuzzy_lookup_item(name_or_id, lst):
"""Lookup an item by either name or id.
Looking up by id is exact match. Looking up by name is by containment, and
if the term is entirely lowercase then it's also case-insensitive.
Multiple matches will throw an exception, unless one of them was an exact
mat... | 604b3879d0f97822d5a36db6dcf468ef8eefaac9 | 3,655,331 |
def fantasy_pros_ecr_scrape(league_dict=config.sean):
"""Scrape Fantasy Pros ECR given a league scoring format
:param league_dict: league dict in config.py used to determine whether to pull PPR/standard/half-ppr
"""
scoring = league_dict.get('scoring')
if scoring == 'ppr':
url = 'https:... | c20ae9542f9fea096510681bcf3c430b23cbdf29 | 3,655,333 |
def lda(X, y, nr_components=2):
"""
Linear discrimindant analysis
:param X: Input vectors
:param y: Input classes
:param nr_components: Dimension of output co-ordinates
:return: Output co-ordinates
"""
print("Computing Linear Discriminant Analysis projection")
X2 = X.copy()
X2.fl... | c9db65d494304246cf518833c1ae5c6ed22f3fa6 | 3,655,334 |
def _flatten_value_to_list(batch_values):
"""Converts an N-D dense or sparse batch to a 1-D list."""
# Ravel for flattening and tolist so that we go to native Python types
# for more efficient followup processing.
#
batch_value, = batch_values
return batch_value.ravel().tolist() | 77bfd9d32cbbf86a16a8da2701417a9ac9b9cc93 | 3,655,335 |
def sun_position(time):
"""
Computes the sun's position in longitude and colatitude at a given time
(mjd2000).
It is accurate for years 1901 through 2099, to within 0.006 deg.
Input shape is preserved.
Parameters
----------
time : ndarray, shape (...)
Time given as modified Jul... | d5465044fbbe650580f4e9afaa13cf83e2cad758 | 3,655,336 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.