content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def build_tree(train, max_depth, min_size, n_features):
"""build_tree(创建一个决策树)
Args:
train 训练数据集
max_depth 决策树深度不能太深，不然容易导致过拟合
min_size 叶子节点的大小
n_features 选取的特征的个数
Returns:
root 返回决策树
"""
# 返回最优列和相关的信息
root = get_sp... | 5afd343436f14d9ab704636eb480d92a31d59f04 | 5,000 |
import pprint
def delete_bucket(bucket_name: str, location: str, verbose: bool) -> bool:
"""Delete the specified S3 bucket
Args:
bucket_name (str): name of the S3 bucket
location (str): the location (region) the S3 bucket resides in
verbose (bool): enable verbose output
Returns:
... | 79c225c9f8caa0d8c3431709d3f08ccaefe3fc1c | 5,001 |
import re
def generate_ordered_match_str_from_subseqs(r1,
subseqs_to_track,
rc_component_dict,
allow_overlaps=False):
"""Generates an ordered subsequences match string for the input se... | 202f228b40b73518342b1cc2419ca466626fc166 | 5,002 |
def combination(n: int, r: int) -> int:
""":return nCr = nPr / r!"""
return permutation(n, r) // factorial(r) | 6cf58428cacd0e09cc1095fb120208aaeee7cb7c | 5,003 |
def _extract_operator_data(fwd, inv_prep, labels, method='dSPM'):
"""Function for extracting forward and inverse operator matrices from
the MNE-Python forward and inverse data structures, and assembling the
source identity map.
Input arguments:
================
fwd : ForwardOperator
... | 6daded6f6df4abbd3dea105927ca39e02e64b970 | 5,004 |
def create_new_containers(module, intended, facts):
"""
Create missing container to CVP Topology.
Parameters
----------
module : AnsibleModule
Object representing Ansible module structure with a CvpClient connection
intended : list
List of expected containers based on following ... | d173c49a40e6a7a71588618e18378260c05018c6 | 5,005 |
from prompt_toolkit.interface import CommandLineInterface
from .containers import Window
from .controls import BufferControl
def find_window_for_buffer_name(cli, buffer_name):
"""
Look for a :class:`~prompt_toolkit.layout.containers.Window` in the Layout
that contains the :class:`~prompt_toolkit.layout.co... | 7912cc96365744c3a4daa44a72f272b083121e3c | 5,006 |
def create_pilot(username='kimpilot', first_name='Kim', last_name='Pilot', email='kim@example.com', password='secret'):
"""Returns a new Pilot (User) with the given properties."""
pilot_group, _ = Group.objects.get_or_create(name='Pilots')
pilot = User.objects.create_user(username, email, password, first_na... | 6c173a94a97d64182dcb28b0cef510c0838a545f | 5,007 |
def dict_to_datasets(data_list, components):
"""add models and backgrounds to datasets
Parameters
----------
datasets : `~gammapy.modeling.Datasets`
Datasets
components : dict
dict describing model components
"""
models = dict_to_models(components)
datasets = []
for... | e021317aae6420833d46782b3a611d17fb7156dc | 5,008 |
def of(*args: _TSource) -> Seq[_TSource]:
"""Create sequence from iterable.
Enables fluent dot chaining on the created sequence object.
"""
return Seq(args) | eb8ea24c057939cf82f445099c953a84a4b51895 | 5,009 |
def find_anagrams(word_list: list) -> dict:
"""Finds all anagrams in a word list and returns it in a dictionary
with the letters as a key.
"""
d = dict()
for word in word_list:
unique_key = single(word)
if unique_key in d:
d[unique_key].append(word... | 5e3514344d396d11e8a540b5faa0c31ae3ee6dab | 5,010 |
import itertools
def resolver(state_sets, event_map):
"""Given a set of state return the resolved state.
Args:
state_sets(list[dict[tuple[str, str], str]]): A list of dicts from
type/state_key tuples to event_id
event_map(dict[str, FrozenEvent]): Map from event_id to event
Re... | 90b8f78e46e13904a9c898cda417378964667ff8 | 5,011 |
def parse_study(study):
"""Parse study
Args:
study (object): object from DICOMDIR level 1 object (children of patient_record)
Returns:
children_object
appending_keys
"""
#study_id = study.StudyID
study_date = study.StudyDate
study_time = study.StudyTime
... | d0e85d991e4f2f13e6f2bd87c0823858ea9c83bc | 5,012 |
def list_organizational_units_for_parent_single_page(self, **kwargs):
"""
This will continue to call list_organizational_units_for_parent until there are no more pages left to retrieve.
It will return the aggregated response in the same structure as list_organizational_units_for_parent does.
:param sel... | 73e942d59026830aac528b9dd358f08ebe8a66b3 | 5,013 |
def daemon(target, name=None, args=None, kwargs=None, after=None):
"""
Create and start a daemon thread.
It is same as `start()` except that it sets argument `daemon=True`.
"""
return start(target, name=name, args=args, kwargs=kwargs,
daemon=True, after=after) | 27d608c9cc5be1ab45abe9666e52bbbf89a1f066 | 5,014 |
import threading
def add_image_to_obj(obj, img, *args, **kwargs):
"""
"""
# skip everything if there is no image
if img == None:
return None
# find out of the object is an artist or an album
# then add the artist or the album to the objects
objs = {}
if isinstance(obj, Artist)... | 60b2f9eb871e5b4943b4ab68c817afdd8cf47cab | 5,015 |
from datetime import datetime
def rr_category_ad(context, ad_zone, ad_category, index=0):
"""
Returns a rr advert from the specified category based on index.
Usage:
{% load adzone_tags %}
{% rr_category_ad 'zone_slug' 'my_category_slug' 1 %}
"""
to_return = {'random_int': randint(1000000... | db78853ebdf64267e2cca217589ac309706333a1 | 5,016 |
def decoderCNN(x, layers):
""" Construct the Decoder
x : input to decoder
layers : the number of filters per layer (in encoder)
"""
# Feature unpooling by 2H x 2W
for _ in range(len(layers) - 1, 0, -1):
n_filters = layers[_]
x = Conv2DTranspose(n_filters, (3, 3), strides... | 9c48c5242b0793c71385f9137729393d17d2db06 | 5,017 |
import torch
def binary_dice_iou_score(
y_pred: torch.Tensor,
y_true: torch.Tensor,
mode="dice",
threshold=None,
nan_score_on_empty=False,
eps=1e-7,
ignore_index=None,
) -> float:
"""
Compute IoU score between two image tensors
:param y_pred: Input image tensor of any shape
... | 9d4b751dbdd9c3b7e5f2490c7f7cd8ac08868233 | 5,018 |
def get_uname_arch():
"""
Returns arch of the current host as the kernel would interpret it
"""
global _uname_arch # pylint: disable=global-statement
if not _uname_arch:
_uname_arch = detect_uname_arch()
return _uname_arch | b30946675f6cad155eab3f81b711618551b49f44 | 5,019 |
from typing import Tuple
def _getSTSToken() -> Tuple[str, BosClient, str]:
"""
Get the token to upload the file
:return:
"""
if not Define.hubToken:
raise Error.ArgumentError('Please provide a valid token', ModuleErrorCode, FileErrorCode, 4)
config = _invokeBackend("circuit/genSTS",... | 553844ce8530911bab70fc823bdec65b058b70a4 | 5,020 |
import os
async def get_thumb_file(mass: MusicAssistant, url, size: int = 150):
"""Get path to (resized) thumbnail image for given image url."""
assert url
cache_folder = os.path.join(mass.config.data_path, ".thumbs")
cache_id = await mass.database.get_thumbnail_id(url, size)
cache_file = os.path.... | fe9a10e6460453b44e8509f2b2b42b30639be48b | 5,021 |
import pickle
def load_pickle(filename):
"""Load Pickfle file"""
filehandler = open(filename, 'rb')
return pickle.load(filehandler) | f93b13616f94c31bc2673232de14b834a8163c5f | 5,022 |
import json
def columnize(s, header=None, width=40):
"""Dump an object and make each line the given width
The input data will run though `json.loads` in case it is a JSON object
Args:
s (str): Data to format
header (optional[str]): Header to prepend to formatted results
width (op... | 36343f682677f04d0b3670882539e58b48146c46 | 5,023 |
def create_eeg_epochs(config):
"""Create the data with each subject data in a dictionary.
Parameter
----------
subject : string of subject ID e.g. 7707
trial : HighFine, HighGross, LowFine, LowGross
Returns
----------
eeg_epoch_dataset : dataset of all the subjects with different con... | a33abcb056b9e94a637e58a42936b886e90a94f2 | 5,024 |
def to_newick(phylo):
"""
Returns a string representing the simplified Newick code of the input.
:param: `PhyloTree` instance.
:return: `str` instance.
"""
return phylo_to_newick_node(phylo).newick | 814610413223e37a6417ff8525262f0beb2e8091 | 5,025 |
import functools
def pipe(*functions):
"""
pipes functions one by one in the provided order
i.e. applies arg1, then arg2, then arg3, and so on
if any arg is None, just skips it
"""
return functools.reduce(
lambda f, g: lambda x: f(g(x)) if g else f(x),
functions[::-1],
... | f58afedd5c7fe83edd605b12ca0e468657a78b56 | 5,026 |
import logging
def remove_news_update(removed_update_name: str, expired: bool) -> None:
"""Removes any expired news articles or any articles that have been
manuallyremoved by the user.
If an update has expired, a loop is used to find the update and remove it
from the global list of updates. Otherwise... | a8a01af22ef2377265f49f35f288f6eebabef3f0 | 5,027 |
import torch
def initialize_graph_batch(batch_size):
""" Initialize a batch of empty graphs to begin the generation process.
Args:
batch_size (int) : Batch size.
Returns:
generated_nodes (torch.Tensor) : Empty node features tensor (batch).
generated_edges (torch.Tensor) : Empty edge fe... | f7ae56b3a0d728dd0fd4b40a3e45e960f65bcf31 | 5,028 |
def TimestampFromTicks(ticks):
"""Construct an object holding a timestamp value from the given ticks value
(number of seconds since the epoch).
This function is part of the `DBAPI 2.0 specification
<http://www.python.org/dev/peps/pep-0249/>`_.
:rtype: :class:`datetime.datetime`
"""
return ... | ccb377b793d600d1a98363e35fc6cd041517b50a | 5,029 |
from typing import Counter
def extract_object_token(data, num_tokens, obj_list=[], verbose=True):
""" Builds a set that contains the object names. Filters infrequent tokens. """
token_counter = Counter()
for img in data:
for region in img['objects']:
for name in region['names']:
... | c35ea7a9eaa2f259c9b38b47e3c982b9ee11682b | 5,030 |
def test_lambda_expressions():
"""Lambda 表达式"""
# 这个函数返回两个参数的和:lambda a, b: a+b
# 与嵌套函数定义一样，lambda函数可以引用包含范围内的变量。
def make_increment_function(delta):
"""本例使用 lambda 表达式返回函数"""
return lambda number: number + delta
increment_function = make_increment_function(42)
assert increm... | e727df25b2165bb0cd7c9cce47700e86d37a2a1a | 5,031 |
def _generate_with_relative_time(initial_state, condition, iterate, time_mapper) -> Observable:
"""Generates an observable sequence by iterating a state from an
initial state until the condition fails.
Example:
res = source.generate_with_relative_time(0, lambda x: True, lambda x: x + 1, lambda x: 0... | d3f5549f94125065b387515299014b5701411be8 | 5,032 |
def is_prime(num):
"""判断一个数是不是素数"""
for factor in range(2, int(num ** 0.5) + 1):
if num % factor == 0:
return False
return True if num != 1 else False | c0e8435b046a87dd15278149f5e1af7258634a01 | 5,033 |
def ptcorr(y1, y2, dim=-1, eps=1e-8, **kwargs):
"""
Compute the correlation between two PyTorch tensors along the specified dimension(s).
Args:
y1: first PyTorch tensor
y2: second PyTorch tensor
dim: dimension(s) along which the correlation is computed. Any valid PyTor... | 140cad4de4452edeb5ea0fb3e50267c66df948c1 | 5,034 |
import typing
def discretize_time_difference(
times, initial_time, frequency, integer_timestamps=False
) -> typing.Sequence[int]:
"""method that discretizes sequence of datetimes (for prediction slices)
Arguments:
times {Sequence[datetime] or Sequence[float]} -- sequence of datetime ... | 871726102dbdedfbc92570bff4f73faf1054e986 | 5,035 |
def pathlines(u_netcdf_filename,v_netcdf_filename,w_netcdf_filename,
startx,starty,startz,startt,
t,
grid_object,
t_max,delta_t,
u_netcdf_variable='UVEL',
v_netcdf_variable='VVEL',
w_netcdf_variable='WVEL',
u_gri... | 2c7da1a6de8157c690fb6ea57e30906108728711 | 5,036 |
def firing_rate(x, theta=0.5, alpha=0.12):
""" Sigmoidal firing rate function
Parameters
----------
x : float
Mean membrane potential.
theta : float
Inflection point (mean firing activity) of sigmoidal curve (default
value 0.12)
alpha : float
Steepness of si... | ddb4ce078f8613a088971d4ed0a4a71d746772b5 | 5,037 |
def map_points(pois, sample_size=-1, kwd=None, show_bbox=False, tiles='OpenStreetMap', width='100%', height='100%'):
"""Returns a Folium Map displaying the provided points. Map center and zoom level are set automatically.
Args:
pois (GeoDataFrame): A GeoDataFrame containing the POIs to be displayed.
... | cb8e2a32b62ca364e54c90b94d2d4c3da74fc12a | 5,038 |
def read_data_file():
"""
Reads Data file from datafilename given name
"""
datafile = open(datafilename, 'r')
old = datafile.read()
datafile.close()
return old | 5aa6aa7cbf0305ca51c026f17e29188e472e61f3 | 5,039 |
def squared_loss(y_hat, y):
"""均方损失。"""
return (y_hat - y.reshape(y_hat.shape))**2 / 2 | 4f796ed753de6ed77de50578271a4eca04fc1ffb | 5,040 |
import re
def normalize_string(string, lowercase=True, convert_arabic_numerals=True):
"""
Normalize the given string for matching.
Example::
>>> normalize_string("tétéà 14ème-XIV, foobar")
'tetea XIVeme xiv, foobar'
>>> normalize_string("tétéà 14ème-XIV, foobar", False)
... | b6772b47f4cc049e09d37c97710a4f37e5a50a7c | 5,041 |
from typing import Sequence
def find_sub_expression(
expression: Sequence[SnailfishElement],
) -> Sequence[SnailfishElement]:
"""Finds the outermost closed sub-expression in a subsequence."""
num_open_braces = 1
pos = 0
while num_open_braces > 0:
pos += 1
if expression[pos] == "[":... | 11d91c38c66fc8c9ce1e58297fcfbb290c18b968 | 5,042 |
import tempfile
import os
import logging
import subprocess
def run_tha_test(manifest, cache_dir, remote, max_cache_size, min_free_space):
"""Downloads the dependencies in the cache, hardlinks them into a temporary
directory and runs the executable.
"""
cache = Cache(cache_dir, remote, max_cache_size, min_free... | 340bbc2daf4f28b1574ca0729575d5abdb5848d4 | 5,043 |
import importlib
def get_rec_attr(obj, attrstr):
"""Get attributes and do so recursively if needed"""
if attrstr is None:
return None
if "." in attrstr:
attrs = attrstr.split('.', maxsplit=1)
if hasattr(obj, attrs[0]):
obj = get_rec_attr(getattr(obj, attrs[0]), attrs[1]... | a6831d48c79b8c58542032385a5c56373fd45321 | 5,044 |
def _get_message_mapping(types: dict) -> dict:
"""
Return a mapping with the type as key, and the index number.
:param types: a dictionary of types with the type name, and the message type
:type types: dict
:return: message mapping
:rtype: dict
"""
message_mapping = {}
entry_index = ... | a098e0386aa92c41d4d404154b0b2a87ce9365ce | 5,045 |
import sys
import os
def _get_default_config_files_location():
"""Get the locations of the standard configuration files. These are
Unix/Linux:
1. `/etc/pywps.cfg`
2. `$HOME/.pywps.cfg`
Windows:
1. `pywps\\etc\\default.cfg`
Both:
1. `$PYWPS_CFG environment variable`
... | a359c0ac95092200cf346768e6db8ea7e2753416 | 5,046 |
def cd(path):
"""
Change location to the provided path.
:param path: wlst directory to which to change location
:return: cmo object reference of the new location
:raises: PyWLSTException: if a WLST error occurs
"""
_method_name = 'cd'
_logger.finest('WLSDPLY-00001', path, class_name=_c... | fbb8d9ac0a9a4c393d06d0c15bfd15154b0a5c0a | 5,047 |
def plt_roc_curve(y_true, y_pred, classes, writer, total_iters):
"""
:param y_true:[[1,0,0,0,0], [0,1,0,0], [1,0,0,0,0],...]
:param y_pred: [0.34,0.2,0.1] , 0.2,...]
:param classes:5
:return:
"""
fpr = {}
tpr = {}
roc_auc = {}
roc_auc_res = []
n_classes = len(classes)
fo... | 5e02d83f5a7cd4e8c8abbc3afe89c25271e3944e | 5,048 |
def get_deps(sentence_idx: int, graph: DependencyGraph):
"""Get the indices of the dependants of the word at index sentence_idx
from the provided DependencyGraph"""
return list(chain(*graph.nodes[sentence_idx]['deps'].values())) | 9eb00fc5719cc1fddb22ea457cc6b49a385eb51d | 5,049 |
import functools
def incr(func):
"""
Increment counter
"""
@functools.wraps(func)
def wrapper(self):
# Strip off the "test_" from the function name
name = func.__name__[5:]
def _incr(counter, num):
salt.utils.process.appendproctitle("test_{}".format(name))
... | 036ae9eac9d223a34871737a7294fad027c2d3c9 | 5,050 |
import operator
def index(a: protocols.SupportsIndex) -> int:
"""
Return _a_ converted to an integer. Equivalent to a.__index__().
Example:
>>> class Index:
... def __index__(self) -> int:
... return 0
>>> [1][Index()]
1
Args:
a:
"""
... | 52f2fbdb8d65b12cb53761647b2c13d3cb368272 | 5,051 |
def col_to_num(col_str):
""" Convert base26 column string to number. """
expn = 0
col_num = 0
for char in reversed(col_str):
col_num += (ord(char) - ord('A') + 1) * (26 ** expn)
expn += 1
return col_num | d6bb00d3ef77c48338df635a254cf3ca5503bb73 | 5,052 |
def process_chunk(chunk, verbose=False):
"""Return a tuple of chunk kind, task-create links, task-create times, task-leave times and the chunk's graph"""
# Make function for looking up event attributes
get_attr = attr_getter(chunk.attr)
# Unpack events from chunk
(_, (first_event, *events, last_ev... | f2430377bc592b2a317b6db627cc39c185f64177 | 5,053 |
def delazi_wgs84(lat1, lon1, lat2, lon2):
"""delazi_wgs84(double lat1, double lon1, double lat2, double lon2)"""
return _Math.delazi_wgs84(lat1, lon1, lat2, lon2) | 3ced7e7dc3fd8dd7ced621a536c43bfb9062d89d | 5,054 |
def clipped_zoom(x: np.ndarray, zoom_factor: float) -> np.ndarray:
"""
Helper function for zoom blur.
Parameters
----------
x
Instance to be perturbed.
zoom_factor
Zoom strength.
Returns
-------
Cropped and zoomed instance.
"""
h = x.shape[0]
ch = int(np... | befbe10493bd4acc63c609432c1c00ac3eeab652 | 5,055 |
def NextFchunk(ea):
"""
Get next function chunk
@param ea: any address
@return: the starting address of the next function chunk or BADADDR
@note: This function enumerates all chunks of all functions in the database
"""
func = idaapi.get_next_fchunk(ea)
if func:
return func.s... | b70136da02d6b689fdc3ce7e946aeff87841cb46 | 5,056 |
def share_to_group(request, repo, group, permission):
"""Share repo to group with given permission.
"""
repo_id = repo.id
group_id = group.id
from_user = request.user.username
if is_org_context(request):
org_id = request.user.org.org_id
group_repo_ids = seafile_api.get_org_group... | 20cdd294692a71e44a635f5fb9dd8ab3a77f95c4 | 5,057 |
def change_config(python, backend, cheatsheet, asciiart):
"""
Show/update configuration (Python, Backend, Cheatsheet, ASCIIART).
"""
asciiart_file = "suppress_asciiart"
cheatsheet_file = "suppress_cheatsheet"
python_file = 'PYTHON_MAJOR_MINOR_VERSION'
backend_file = 'BACKEND'
if asciiart... | b76f40546981c66f8b068c12fa1c1701b532ee7f | 5,058 |
def get_memcached_usage(socket=None):
"""
Returns memcached statistics.
:param socket: Path to memcached's socket file.
"""
cmd = 'echo \'stats\' | nc -U {0}'.format(socket)
output = getoutput(cmd)
curr_items = None
bytes_ = None
rows = output.split('\n')[:-1]
for row in rows:... | fcabd77bbf0186498753a4630c50ed7fd900cf96 | 5,059 |
def dataset_config():
"""Return a DatasetConfig for testing."""
return hubs.DatasetConfig(factory=Dataset, flag=True) | 15d8c33e5706c07c03589adb945bdaee3b1dd18a | 5,060 |
import itertools
def combinations():
"""Produce all the combinations for different items."""
combined = itertools.combinations('ABC', r=2)
combined = [''.join(possibility) for possibility in combined]
return combined | 501060cf9c7de9b4b4453940e017ad30cec2f84f | 5,061 |
from evohomeclient2 import EvohomeClient
import logging
def setup(hass, config):
"""Create a Honeywell (EMEA/EU) evohome CH/DHW system.
One controller with 0+ heating zones (e.g. TRVs, relays) and, optionally, a
DHW controller. Does not work for US-based systems.
"""
evo_data = hass.data[DATA_EV... | 2baf2286e4f08ac0ffb452c8d089951fcede8688 | 5,062 |
def geo_exps_MD(n_nodes, radius, l_0, l_1, K=40, thinRatio=1,
gammas=10, max_iter=100, nSamp=50, Niid=1, seed=0):
"""Solves the Connected Subgraph Detection problem and calculates AUC using
Mirror Descent Optimisation for a random geometric graph.
Parameters
----------
n_nodes... | 9e3831975915b6dffecbb1142dbd01cd26a255ca | 5,063 |
from typing import Tuple
def validate_sig_integrity(signer_info: cms.SignedData,
cert: x509.Certificate,
expected_content_type: str,
actual_digest: bytes) -> Tuple[bool, bool]:
"""
Validate the integrity of a signature for a part... | 36e64173d8612c9ca3e95cb0566222140c56c17d | 5,064 |
def linemod_dpt(path):
"""
read a depth image
@return uint16 image of distance in [mm]"""
dpt = open(path, "rb")
rows = np.frombuffer(dpt.read(4), dtype=np.int32)[0]
cols = np.frombuffer(dpt.read(4), dtype=np.int32)[0]
return (np.fromfile(dpt, dtype=np.uint16).reshape((rows, cols)) / 1000.... | e2538520ba3bd82ada339b816c4d1a067bbd4000 | 5,065 |
from typing import Iterable
from typing import Optional
def findNode(nodes: Iterable[AstNode], name: str) -> Optional[SExpr]:
"""
Finds a node with given name in a list of nodes
"""
for node in nodes:
if isinstance(node, Atom):
continue
if len(node.items) == 0:
... | 5b3f53e98269e6d00cb2dc11dd75d81dfed98f30 | 5,066 |
def search(keywords=None, servicetype=None, waveband=None):
"""
execute a simple query to the RegTAP registry.
Parameters
----------
keywords : list of str
keyword terms to match to registry records.
Use this parameter to find resources related to a
particular topic.
ser... | 855e00f2a001995de40beddb6334bdd8ddb8be77 | 5,067 |
import os
def _get_credentials(vcap_services, service_name=None):
"""Retrieves the credentials of the VCAP Service of the specified `service_name`. If
`service_name` is not specified, it takes the information from STREAMING_ANALYTICS_SERVICE_NAME environment
variable.
Args:
vcap_services (di... | a72f3e7b6be56ab6c66252cd8063fd0207aac02b | 5,068 |
def all_are_independent_from_all(program, xs, ys):
"""
Returns true iff all xs are statistially independent from all ys, where the xs are from the current iteration
and the ys are from the previous iteration.
"""
for x in xs:
if not is_independent_from_all(program, x, ys):
return... | 50f091530e322b741465b222da70080463e4f142 | 5,069 |
import sys
import traceback
import string
def get_exc_short():
"""Print only error type and error value.
"""
exType, exValue, exTb = sys.exc_info()
resL1 = traceback.format_exception_only(exType, exValue)
return string.join(resL1, "") | 5dc21b813fd3317544f06512e8c1160599aa6955 | 5,070 |
def is_str_str_dict(x):
"""Tests if something is a str:str dictionary"""
return isinstance(x, dict) and all(
isinstance(k, str) and isinstance(v, str) for k, v in x.items()
) | ce6230714c0526764f2cc67e4dedf598acd28169 | 5,071 |
def _ensureListLike(item):
"""
Return the item if it is a list or tuple, otherwise add it to a list and
return that.
"""
return item if (isinstance(item, list) or isinstance(item, tuple)) \
else [item] | 1c602a1fcf8dd6a5b4583264e63e38747f5b0d50 | 5,072 |
import io
def get_file_from_gitlab(gitpkg, path, ref="master"):
"""Retrieves a file from a Gitlab repository, returns a (StringIO) file."""
return io.StringIO(gitpkg.files.get(file_path=path, ref=ref).decode()) | 7eccad01a538bdd99651b0792aff150f73e82cdd | 5,073 |
def tsne(x, no_dims=2, initial_dims=50, perplexity=30.0, max_iter=1000):
"""Runs t-SNE on the dataset in the NxD array x
to reduce its dimensionality to no_dims dimensions.
The syntaxis of the function is Y = tsne.tsne(x, no_dims, perplexity),
where x is an NxD NumPy array.
"""
# Check inputs
... | 348c83048190830dd10982e9fa1426db06e983fc | 5,074 |
def add_corp():
"""
添加投顾信息页面,可以让用户手动添加投顾
:by zhoushaobo
:return:
"""
if request.method == 'GET':
fof_list = cache.get(str(current_user.id))
return render_template("add_corp.html", fof_list=fof_list)
if request.method == 'POST':
name = request.form['name']
alia... | 9d70ac010bdf5a3102635eaf1acf75f43689f82e | 5,075 |
def nll_loss(output: Tensor, target: Tensor):
"""
Negative log likelihood loss function.
## Parameters
output: `Tensor` - model's prediction
target: `Target` - training sample targets
## Example usage
```python
from beacon.tensor import Tensor
from beacon.functional import functio... | 339ef1300c42ad6923e044e7011615b934923e23 | 5,076 |
from typing import List
from typing import Optional
async def album_upload(sessionid: str = Form(...),
files: List[UploadFile] = File(...),
caption: str = Form(...),
usertags: Optional[List[Usertag]] = Form([]),
location: Opti... | 303aba7ee57e61082197fe18330663c5c0c51c76 | 5,077 |
def mocked_requests_get(*args, **kwargs):
"""Mock requests.get invocations."""
class MockResponse:
"""Class to represent a mocked response."""
def __init__(self, json_data, status_code):
"""Initialize the mock response class."""
self.json_data = json_data
sel... | 41a54452593cd23e8ea86f1fbdc0c5e92845482f | 5,078 |
def count_disordered(arr, size):
"""Counts the number of items that are out of the expected
order (monotonous increase) in the given list."""
counter = 0
state = {
"expected": next(item for item in range(size) if item in arr),
"checked": []
}
def advance_state():
state... | bb708e7d862ea55e81207cd7ee85e634675b3992 | 5,079 |
from typing import Iterable
import collections
from sys import flags
def lookup_flag_values(flag_list: Iterable[str]) -> collections.OrderedDict:
"""Returns a dictionary of (flag_name, flag_value) pairs for an iterable of flag names."""
flag_odict = collections.OrderedDict()
for flag_name in flag_list:
if n... | 591f0e877a71388de8ad0111f624246ea7a2dc5b | 5,080 |
def test_alignment():
"""Ensure A.M. cosine's peaks are aligned across joint slices."""
if skip_all:
return None if run_without_pytest else pytest.skip()
N = 1025
J = 7
Q = 16
Q_fr = 2
F = 4
# generate A.M. cosine ###################################################
f1, f2 = ... | a0f664a153c1af5942d39d54c75bcb8a3b3b660a | 5,081 |
import base64
def request_text(photo_file, max_results=5):
"""
Request the Google service to find text in an image
:param photo_file: The filename (or path) of the image in a local directory
:param max_results: The requested maximum number of results
:return: A list of text entries found in the im... | 3af646e81fb71f89ffab2a9f20f979cdbaaf29a6 | 5,082 |
def config(request):
"""render a ProsperConfig object for testing"""
return p_config.ProsperConfig(request.config.getini('app_cfg')) | 4222d7d2a56020883e0a196f4c531b44d2f50dd5 | 5,083 |
def flatatt(attrs):
"""
Convert a dictionary of attributes to a single string.
The returned string will contain a leading space followed by key="value",
XML-style pairs. It is assumed that the keys do not need
to be XML-escaped.
If the passed dictionary is empty, then return an empty string.
... | 03175fd9b2d0574bd3634d43821e38177924ed0e | 5,084 |
import json
def json_io_dump(filename, data):
""" Dumps the the JSON data and returns it as a dictionary from filename
:arg filename <string> - Filename of json to point to
:arg data - The already formatted data to dump to JSON
"""
with open(filename, encoding='utf-8', mode='w') as json_file:
... | e0ae7187ac29669330109ae39ebcac33c1e30ab6 | 5,085 |
import requests
import json
def get_restaurants(_lat, _lng):
"""緯度: lat 経度: lng"""
response = requests.get(URL.format(API_KEY, _lat, _lng))
result = json.loads(response.text)
lat_lng = []
for restaurant in result['results']['shop']:
lat = float(restaurant['lat'])
lng = float(restau... | 35884258210174cca0ffcf73dc3451dae07d5712 | 5,086 |
def geomfill_GetCircle(*args):
"""
:param TConv:
:type TConv: Convert_ParameterisationType
:param ns1:
:type ns1: gp_Vec
:param ns2:
:type ns2: gp_Vec
:param nplan:
:type nplan: gp_Vec
:param pt1:
:type pt1: gp_Pnt
:param pt2:
:type pt2: gp_Pnt
:param Rayon:
:ty... | f00ade1b203e819c6ae946c31c8c9821f2a79744 | 5,087 |
def dwconv3x3_block(in_channels,
out_channels,
stride,
padding=1,
dilation=1,
bias=False,
activation=(lambda: nn.ReLU(inplace=True)),
activate=True):
"""
3x3 depthwise vers... | eb2330206510369f8d81d0fc58d2578cf212a1df | 5,088 |
import json
def predict() -> str:
"""
Creates route for model prediction for given number of inputs.
:return: predicted price
"""
try:
input_params = process_input(request.data)
print(input_params)
predictions = regressor.predict(input_params)
return json.dumps({"p... | ee58cbecf6d44a65f94cb3becd4d6cfe2d30ef30 | 5,089 |
def all_h2h_pairs_all_lanes(matches_df, file_name=''):
"""Produces all head to head win rates for all lane matchups -- even across different lanes
(eg. TOP_SOLO Renekton vs MID_SOLO Xerath)."""
df = pd.DataFrame()
lanes = dc.get_lanes_roles()
for lane1 in lanes:
print(lane1)
for lane... | f6ffd40985455515767c1aa6286dc9998b7bdb7d | 5,090 |
import requests
def reload_rules(testcase, rest_url):
"""
:param TestCase self: TestCase object
:param str rest_url: http://host:port
:rtype: dict
"""
resp = requests.get(rest_url + "/rest/reload").json()
print("Reload rules response: {}".format(resp))
testcase.assertEqual(... | e747668ba8ad5f58f0307194b0008469dd3593c1 | 5,091 |
def encryptMessage(key: str, message: str) -> str:
"""Vigenère cipher encryption
Wrapper function that encrypts given message with given key using the Vigenère cipher.
Args:
key: String encryption key to encrypt with Vigenère cipher.
message: Message string to encrypt.
Returns:
... | 428372d8443579ac691d43a5542de850b49966ce | 5,092 |
def rae(label, pred):
"""computes the relative absolute error
(condensed using standard deviation formula)"""
#compute the root of the sum of the squared error
numerator = np.mean(np.abs(label - pred), axis=None)
#numerator = np.sum(np.abs(label - pred), axis = None)
#compute AE if we were to ... | bff280ba243fd494347643233870524c008c7473 | 5,093 |
def subset_sum(arr, target_sum, i, cache):
"""
Returns whether any subset(not contiguous) of the array has sum equal to target sum.
"""
if target_sum == 0:
return True, {}
if i < 0:
return False, {}
if target_sum in cache[i]:
return cache[i][target_sum]
# Either inclu... | aa90d7eb4ffa3a457a5f27733de56a82df450861 | 5,094 |
from typing import Type
import types
from typing import Optional
def set_runtime_parameter_pb(
pb: pipeline_pb2.RuntimeParameter,
name: Text,
ptype: Type[types.Property],
default_value: Optional[types.Property] = None
) -> pipeline_pb2.RuntimeParameter:
"""Helper function to fill a RuntimeParameter ... | 4c6394f60774c42b0a6be8d55b57a67b8fc6b1d5 | 5,095 |
def get_loader(content_type):
"""Returns loader class for specified content type.
:type content_type: constants.ContentType
:param content_type: Content type.
:returns: Loader class for specified content type.
:raise ValueError: If no loader found for specified content type.
"""
for loader_... | 0d7e37ff17a48e8bed3a4abb7ce9734579fe9100 | 5,096 |
from typing import List
from typing import Dict
import torch
def get_basis_script(max_degree: int,
use_pad_trick: bool,
spherical_harmonics: List[Tensor],
clebsch_gordon: List[List[Tensor]],
amp: bool) -> Dict[str, Tensor]:
"""
... | 9afbe8973541b8b1562f2d336d13b19dae9245fc | 5,097 |
def get_iterative_process_for_minimal_sum_example():
"""Returns an iterative process for a sum example.
This iterative process contains the fewest components required to compile to
`forms.MapReduceForm`.
"""
@computations.federated_computation
def init_fn():
"""The `init` function for `tff.templates.I... | 40ea1b07f2eeccaaff3cc0657207ef445985f795 | 5,098 |
def get_r_port_p_d_t(p):
"""玄関ポーチに設置された照明設備の使用時間率
Args:
p(int): 居住人数
Returns:
ndarray: r_port_p_d_t 日付dの時刻tにおける居住人数がp人の場合の玄関ポーチに設置された照明設備の使用時間率
"""
return get_r_i_p_d_t(19, p) | abdc6f9201594ca946ff2deb25cdf8c1e1d98839 | 5,099 |
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