content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def report_cursor() -> tuple[int, int] | None:
"""Get position of cursor"""
print("\x1b[6n")
chars = getch()
posy, posx = chars[2:-1].split(";")
if not posx.isdigit() or not posy.isdigit():
return None
return int(posx), int(posy) | daf44e19af3c3644ed8d3f38f719a2123523025e | 66,213 |
import builtins
def iscallable(t):
"""True if type ``t`` is a code object that can be called"""
return builtins.callable(t) and hasattr(t, '__call__') | 9dc806eff1ebce90d9df8a3f3c53256ef73f0f66 | 66,216 |
def extract_body_schema(schema):
"""Return the body parameter schema from an operation schema."""
matching_body_schemas = filter_params_by_type(schema, 'body')
# There can be only one body param
return matching_body_schemas[0] if matching_body_schemas else None | 1e9f3cc3d6b951148e25f7b48510a3597d5c08bf | 66,217 |
def as_token(ctx: ParserRuleContext) -> str:
""" Extract the token for an identifier from the context. Tokens can be:
* ID - The name of a JSG definition
* idref -- A reference to an existing JSG definition
* LEXER_ID - The name of a match pattern definition
* LEXER_ID_REF - A reference to an existi... | 0ffa87ee71019f1f9e5b3774c1bfe94168d4c8a5 | 66,218 |
def calculate_cost(problem: np.ndarray, solution: np.ndarray, k: int) -> float:
"""
Calculates the overall cost as the L2 norm of the cost vector.
:param problem: The problem matrix.
:param solution: The solution vector.
:param k: The number of folds.
:return: The scalar cost.
"""
retur... | 652130c94a48f0c99df6e2567f529ecc654970a1 | 66,219 |
import ast
def matheval(expr, numtype=float):
"""
>>> matheval('2^6')
4
>>> matheval('2**6')
64
>>> matheval('1 + 2*3**(4^5) / (6 + -7)')
-5.0
"""
return eval_(ast.parse(expr, mode='eval').body, numtype) | 26469e8f92f67f5a83645be4f06c550c50265264 | 66,220 |
def normalize(value, minimum, maximum):
"""min-max normalization"""
if value < minimum:
value = minimum
if value > maximum:
value = maximum
return (value - minimum)/(maximum - minimum) | 0c1318d71db43eeb27ff59ac743f8909279451b5 | 66,221 |
def _normalise_X(X):
"""Helper function to normalise X using the z-score standardisation"""
# get the number of attributes and instances
num_atts = X.shape[1]
num_insts = X.shape[0]
df = pd.DataFrame()
for x in X.columns:
col = X[x]
data = []
for y in range(num_insts):
... | 86ae2fef7558db4cdc22da62bce706cd9fce585d | 66,222 |
def recursive_parse_xml_to_dict(xml):
"""Recursively parses XML contents to python dict.
We assume that `object` tags are the only ones that can appear
multiple times at the same level of a tree.
Args:
xml: xml tree obtained by parsing XML file contents using lxml.etree
Returns:
Python dictionary h... | f9f48396d1de1e21e0122261caff238a6ba82e32 | 66,223 |
import platform
def _PathForExecutable(executable_name):
"""Fetches the executable from cloud storage, and returns its path."""
arch_name = platform.GetHostPlatform().GetArchName()
return binary_manager.FetchPath(executable_name, arch_name, 'mac') | ec440a58e44231632c5a96d4ad9836385c0c5d29 | 66,224 |
def get_baseurl_from_request(request):
"""Use the request object to build a base url"""
assert isinstance(request, HttpRequest),\
"request must be a django.http.HttpRequest object"""
urlParts = urlparse(request.build_absolute_uri())
return '%s://%s' % (urlParts.scheme, urlParts.netloc) | a4e89c4694d3651968fccb3a57cf646a0151dfe0 | 66,225 |
def us30History(
token="", version="stable", filter="", format="json", **timeseries_kwargs
):
"""Economic data
https://iexcloud.io/docs/api/#economic-data
Args:
token (str): Access token
version (str): API version
filter (str): filters: https://iexcloud.io/docs/api/#filter-resu... | 82338c790ce6416355dea0a3f67c38384b0b844e | 66,227 |
from typing import Dict
from typing import Any
def new_from_at_rest(transaction_type_data: Dict[str, Any]) -> "TransactionTypeModel":
"""
Construct a transaction type model from at rest (cached storage)
"""
if transaction_type_data.get("version") == "1":
# V1 custom indexes are not supported, ... | 67068417bb683cfc4d20cdfcf0345f6ac7d8ac28 | 66,228 |
def load_object(module: str, name: str, *, raise_ex: bool = True) -> tp.Any:
"""Loads the specified object from the specified `module`.
Parameters
----------
module : str
The (full) name of the module to load the object from.
name : str
The name of the object to load from the given ... | a8ca051299a7368a7fb1a854e7e5539a63c8b74a | 66,229 |
def validate_tokens_input(func):
"""check provide key and refresh token from the request and make sure they are all provide and valid"""
def dec(request):
try:
key = request.data['key']
refresh_token = request.headers['Authorization']
if refresh_token == '':
... | 57c89efc5c87684be175f0dc4aeec0362250e233 | 66,230 |
def sbar(Ss):
"""
calculate average s,sigma from list of "s"s.
"""
if type(Ss) == list:
Ss = np.array(Ss)
npts = Ss.shape[0]
Ss = Ss.transpose()
avd, avs = [], []
# D=np.array([Ss[0],Ss[1],Ss[2],Ss[3]+0.5*(Ss[0]+Ss[1]),Ss[4]+0.5*(Ss[1]+Ss[2]),Ss[5]+0.5*(Ss[0]+Ss[2])]).transpose(... | cb31f9703126eef4daa569281efad32a9e2542de | 66,232 |
def resize(img, size, interpolation=cv2.INTER_LINEAR):
""" resize """
if isinstance(size, int):
h, w = img.shape[:2] # hwc
min_hw = min(h, w)
if size == min_hw:
return img
percent = float(size) / min_hw
rw = int(round(w * percent))
rh = int(round(h ... | e6d0734808f051dea641438c112724420998bb2d | 66,233 |
def _get_version(name):
"""Get a dataset version."""
if not has_dataset(name):
return None
return _data_path(name=name, return_version=True)[1] | 088232676b1e5d5754b06d48ce3828b82599c430 | 66,234 |
def jobscript_get_exec_prefix(jg : JobGeneration):
"""
Prefix before executable
Returns
-------
string
multiline text for scripts
"""
content = ""
content += jg.runtime.get_jobscript_plan_exec_prefix(jg.compile, jg.runtime)
return content | 58f7ffede5369ea150e0f882b871bfba22683261 | 66,238 |
def get_log_dirs(parent_path,prog_name):
"""get logs paths"""
### high priority at the begin of the list
### low priority at the end of the list
pathnames_list=[]
pathnames_list.append( pathnames.get_log_dir(prog_name,PROG_PUBLISHER) )
pathnames_list.append( pathnames.join_pathname(parent_path,LOGS_DIRECTORY) )
... | 21501cd871d88811ae77f668385fe693ce4e2655 | 66,241 |
def get_valid_values(value, min_value, max_value):
"""Assumes value a string, min_value and max_value integers.
If value is in the range returns True.
Otherwise returns False."""
valid_values = [i for i in range(min_value, max_value + 1)]
try:
value = int(value)
except ValueError:
... | 4385f8328cfbe6497f7a723be37e54f0a86f9fbf | 66,242 |
import torch
def _spherical_harmonics_l0(xyz):
"""Compute the l=0 Spherical Harmonics
Args:
xyz : array (Nbatch,Nelec,Nrbf,Ndim) x,y,z, of (Point - Center)
Returns
Y00 = 1/2 \sqrt(1 / \pi)
"""
return 0.2820948 * torch.ones_like(xyz[..., 0]) | 83831d0a140d85dc356ae04bcbaeeda74c5a9fee | 66,243 |
def sanitizeString(string: str) -> str:
""" Sanitize a string to be safe for filenames
Args:
string: String to sanitize for filenames
Returns:
Version of input string safe for filenames
"""
return string.replace("|", "-").\
replace("/","-").\
replace("\\","-").\
... | c0aefd6c7af0aca9c1bdd4071b9e76041731c183 | 66,244 |
def upload_lu(v_uuid, lu, io_handle, f_size, sha_chksum=None,
upload_type=UploadType.IO_STREAM):
"""Uploads a data stream to an existing SSP Logical Unit.
:param v_uuid: The UUID of the Virtual I/O Server through which to perform
the upload.
:param lu: LU Wrapper representi... | c240697565cf975a3542d493f91a9537753188e0 | 66,245 |
def top_1_acc(output, target):
"""
Computes the top 1 accuracy
"""
return top_k_acc(output, target, k=1) | 3ae7d2faf996144ed112a8a752df94494777b7df | 66,246 |
def add_DenseNet_convX_body(model, block_counts, dim_in, dim_inner, group_rate):
"""Add a DenseNet body from input data up through the res5 (aka conv5) stage.
The final res5/conv5 stage may be optionally excluded (hence convX, where
X = 4 or 5)."""
freeze_at = cfg.TRAIN.FREEZE_AT
assert freeze_at in... | 9deb1898d37a77beffd47d3237954157af4b1faf | 66,247 |
def index_all(elm, lst):
"""return list[int] all positions where elm appears in lst. Empty list if not found"""
if type(list)!=list:
lst=list(lst)
return [i for i,e in enumerate(lst) if e==elm] | 0db325714d6c8de5b1a1fbb516287c56931cf0a9 | 66,248 |
def ValueIteration(gamma=0.95, th=0.01):
"""
value iterationで全状態の価値評価する.
はじめ,すべての状態は価値0とする.
以下の価値更処理をすべての状態に行う.何度も繰り返し,更新幅がth未満になったら終了.
・終了状態に遷移できたら,その状態の価値を1とする.
・遷移可能な状態のうち最大価値に割引率gammaをかけたものをその状態の価値とする.
繰り返しごとに終了状態に近いものから順に価値が伝搬していくイメージ.
return:状態価値テーブルV
"""
actions = list(ran... | 9422371711fdb01a26f1219870751edb63d8d4de | 66,251 |
def _get_effective_credentials(cli_ctx, existing_credentials, account_name):
"""Returns AzureStorageCredentialInfo for the account
:param models.AzureStorageCredentialsInfo existing_credentials: known credentials
:param str account_name: storage account name
:return models.AzureStorageCredentialsInfo: ... | dddcfcc98400ef30884320768e29f72d3623dba5 | 66,253 |
import logging
def add_phab_project(project_information, project_columns):
"""Add a project on Phabricator.
Parameters
----------
project_information : dict
project_columns: dict
"""
logging.info("Adding Phabricator project.")
name = project_information[project_columns["english_name"]... | 9d21d281e110d41606461bc799a6071b2e47f1b7 | 66,254 |
def mixture_mse(params, targets, **kwargs):
"""Given log-unnormalized mixture weights for equi-spaced truncated
Gaussians on the unit interval, return the likelihoods for targets.
(Currently unused.)
Args:
params: N x d x 3*ncomp tensor of parameters of mixture model.
targets: N x d x 1 ... | f6c908c8d518f1b35941915b58ff316f034c40c2 | 66,255 |
def socfaker_timestamp_current():
"""
The current timestamp
Returns:
str: Returns the current timestamp in ISO 8601 format
"""
if validate_request(request):
return { 'value': socfaker.timestamp.current } | 833ab3b23194ef033065f340826dc21d4098ba4c | 66,256 |
def get_lines(file_path):
"""
get all lines in file
"""
with open(file_path, encoding='utf-8') as data_file:
lines = map(lambda line: line.strip(), data_file.readlines())
return lines | caf42286bc985c609076cb31432242552483a661 | 66,257 |
def str_of_max_length(length):
"""Validate that the value is a string with a max length."""
def validator(instance, attribute, value):
instance_of(str)(instance, attribute, value)
if len(value) > length:
raise ValueError(
'{0.name} must be at most {1} chars, '
... | 2b2dc062026b1c81f6b984669f169cd96bda57da | 66,258 |
def version(server, component=None):
"""
Returns the version of the specified component. If *component* is None, then a list of all of the components
available will be returned.
:param CasparServer server: The :py:class:`~caspartalk.CasparServer` that the *amcp_command* will be sent to.
:param str ... | 642d80ede6afee88484095f631b1b194e32fac4b | 66,259 |
from typing import Dict
from typing import Any
from typing import Optional
from typing import List
import logging
def gather_gene_dict_from_contig(
contig: str,
variant_source: cyvcf2.VCFReader,
config: Dict[str, Any],
panelapp_data: PanelAppDict,
singletons: bool,
blacklist: Optional[List[str... | 25219bc32531602c44db202bde350be9402c5b18 | 66,260 |
import socket
def translate_addrmask(af, addr):
"""Validate IP address"""
addr_mask = addr.split("/")
try:
socket.inet_pton(af, addr_mask[0])
except socket.error:
raise BadRequestError("Invalid IP address")
# Test v4 or v6 mask
max_cidr_prefix = 32 if af == socket.AF_INET else... | bc2a20c5f7ee803cf908e8f710ce62bc3b5e1dea | 66,263 |
import asyncio
async def network_list(cluster_id: str):
"""Get All Virtual Network from cluster"""
try:
session = create_session(
_id=cluster_id, get_xen_clusters=Settings.get_xen_clusters()
)
networks = Network.get_all(session=session)
__santilized_networks = awa... | 85f4aa966ecb4e09221b48ce91d0cb03f4e73312 | 66,264 |
def train_dgcnn(graphs, graph_labels, n_epochs=50):
""" Build and train DGCNN model """
generator = PaddedGraphGenerator(graphs=graphs)
k = graphs[0].number_of_nodes() # the number of rows for the output tensor, no truncation
# done here because all graphs have same number of nod... | 3af30a8189f905a5c7b898b9013721d687cc5549 | 66,265 |
def modelSimilarity(ex_submodel, ex_ts, valid_new_submodel, new_ts, submod_type):
"""
This function calcualtes the evaluation measure for the run.
ex_submodel = (DataFrame) either existing/expert demand_summary or hourly_profiles submodel
valid_new_submodel = (DataFrame) output from dataIntegrity f... | cf1bb5076d52eec159100527718171f75582574f | 66,266 |
def _GKEConnectNamespace(kube_client, project_id):
"""Returns the namespaces into which to install or update the connect agent.
Connect namespaces are identified by the presence of the hub.gke.io/project
label. If there are existing namespaces with this label in the cluster,
then a list of all those namespaces... | d8d1e666fb28e4c44fd9880b7234dc5cd9cec637 | 66,267 |
import torch
def lm_forward_step(data, model, args, timers, mems, eval_metric=None):
"""Forward step."""
# Get the batch.
if timers is not None:
timers('batch generator').start()
if 'mask' in data:
data['attention_mask'] = data.pop('mask')
tokens, labels, loss_mask, attention_mask... | 0db8ea0f3e7ebca0287e0fd0f1c68bd3fa848147 | 66,268 |
def load_vars(basepath, results, vault_password=None):
"""
Load variables from any potential yaml filename combinations of basepath,
returning result.
"""
paths_to_check = [ "".join([basepath, ext])
for ext in C.YAML_FILENAME_EXTENSIONS ]
found_paths = []
for path i... | 721391474076e92e6b1ffd260d7630716e45d881 | 66,269 |
def print_pred(query, corpus, model):
"""Prints details about input query relative to a corpus and model:
- The cleaned query text
- The bag of words
- Query topic predictions
- Topics for individual words from the query."""
def word_topics(word_id):
return(model.get_term_topics(wor... | 90cf10e19a91ad7ceb545f47e74b2e50db2def7f | 66,270 |
async def url_callback_func(fetcher, range_stream, url):
"""
Async function which puts the URL onto the storage class's list of values
"""
return CallbackMutatedClass.values.append(url) | 0de9f98378ad3a18e4c4d7b0bc836b900938f6ca | 66,271 |
import struct
def short_string(value):
""" Encode a string.
:param value: Value to encode
:type value: bytes or str or unicode
:rtype: bytes
:raises: TypeError
"""
if PYTHON3 and not isinstance(value, (bytes, str)):
raise TypeError('bytes or str required')
elif not PYTHON3 an... | 95de1b4aa1e92a8a265913a9fc7b88940cb8e23f | 66,272 |
def example_check_main_engine(app_configs=None, **kwargs):
"""
Check for existence of the "Main engine" component in the database
"""
# your check logic here
errors = []
logger.info("Our check has been called :]")
if not Component.objects.filter(title="Main engine").exists():
errors... | b65f2001a12e50da72ace09eff5e7ea71df0fcff | 66,273 |
def shift_objects(data,
solar_za,
solar_az,
sensor_za,
sensor_az,
h,
num_workers):
"""
Shifts objects along x and y dimensions
Args:
data (DataArray): The data to shift.
solar_za (Da... | 59aca73ebf57f2911ab2d3a8a39643b8d570c690 | 66,274 |
def build_A_analytical(material_property_library, mesh, materials):
""" While not intended for long term use,
this function demonstrates that our steady state model matches
the analytical solution.
inputs:
material_property_library contains relevant material data
mesh contains the radial positions of ... | d3f9b0d46852b1664018b0a941b84c07818fd2e1 | 66,275 |
def earthsun_distance(unixtime, delta_t, numthreads=1):
"""
Calculates the distance from the earth to the sun using the
NREL SPA algorithm described in [1].
Parameters
----------
unixtime : numpy array
Array of unix/epoch timestamps to calculate solar position for.
Unixtime is t... | 8d06d5e61de386d987bec07af351420db87b2c10 | 66,276 |
def backward_prop(data, labels, params,lamb=0.0):
"""
return gradient of parameters
"""
W1 = params['W1']
b1 = params['b1']
W2 = params['W2']
b2 = params['b2']
### YOUR CODE HERE
h, y, cost = forward_prop(data,labels,params)
y = y-labels
gradW2 = h.T.dot(y)
gradb2 = np.s... | 578ddeea44398cfc1565195b1880728c0b3575e4 | 66,277 |
def list_available_networks(caller_id):
"""
@cmview_admin_cm
@response{list(dict)} AvailableNetwork.dict property for each requested AvailableNetwork
"""
response = []
for network in AvailableNetwork.objects.all():
response.append(network.dict)
return response | b8bcf54acbe85bed1e36968fed1c1cac4a122854 | 66,280 |
import logging
def blocking_prob(n_servers,
n_sources,
total_traffic,
alg=Algorithm.NEWTON,
max_n_iters=1024,
tol=pow(2, -24),
**kwargs):
"""Blocking probability in the Engset model.
Parameters
---... | 36ce12e60589519270fffe2960f794835774b662 | 66,281 |
def update():
"""
Update me
"""
req_data = request.get_json()
data = personal_schema.load(req_data, partial=True)
if error:
return custom_response(error, 400)
user = personalModel.get_one_student(g.user.get('id'))
user.update(data)
ser_user = personal_schema.dump(user)
return custom_response(se... | 049966c6877ef59f3bcd651736f4e69a8c466361 | 66,282 |
import select
def win32select(r, w, e, timeout=None):
"""Win32 select wrapper."""
if not (r or w):
# windows select() exits immediately when no sockets
if timeout is None:
timeout = 0.01
else:
timeout = min(timeout, 0.001)
sleep(timeout)
return [... | d909eefa6576b41373869a3f5fa4c02245bfde7b | 66,283 |
def rbf_svm_classify_roc(X_train, X_test, Y_train, Y_test):
"""
Parameters
----------
X_train : numpy.ndarray
training feature vectors
X_test : numpy.ndarray
testing feature vectors
Y_train : numpy.ndarray
training set labels
Y_test : numpy.ndarray
test se... | a9da4c635f27d8ef7a324ecfa26e343db3fda6b5 | 66,284 |
def _sbprofile_colors():
"""Return an iterator of colors good for the surface brightness profile plots.
https://seaborn.pydata.org/generated/seaborn.color_palette.html#seaborn.color_palette
"""
_colors = sns.color_palette('Set1', n_colors=11, desat=0.75)
colors = iter([ _colors[1], _colors[2], _col... | dd0d0f5fef44032d3fbcecaa35a267fddfa3e896 | 66,285 |
def dice_loss(y_true, y_pred, smooth=1e-6):
""" Loss function base on dice coefficient.
Parameters
----------
y_true : keras tensor
tensor containing target mask.
y_pred : keras tensor
tensor containing predicted mask.
smooth : float
small real value used for avoiding di... | 8f2011e60308a57d6abba71c4fce0cb042db1d24 | 66,287 |
def render_form(parser, token):
"""
render_form takes one argument in one of the following formats:
{% render_build_form form_instance %}
"""
try:
_, arg = token.split_contents()
arg = "form=" + arg
name, value = arg.split("=", 1)
except ValueError:
raise templa... | c32b91299700283a6ab5a5269f2f39a4856d5b44 | 66,288 |
def produce_phrases(file):
"""
Function, which implements all the
magic with Markov's chains. As you
can see, looks pretty easy:)
@param file: input file, consisted of text
to be converted into sensible phrases
@return: "sensible phrases of MIPT teachers"
"""
with open(file, "r", enc... | e7ab6e22ce1fa5b8a01995b67159499fdbcdc280 | 66,289 |
from pathlib import Path
import json
def load_processing_unit(unit_path):
"""Load a :class:`ProcessingUnit` from a persisted processing unit
directory"""
unit_path = Path(unit_path)
with (unit_path / "metadata.json").open(encoding="utf8") as f:
metadata = json.load(f)
unit = _get_unit_type... | 15650de7c6724287d0e4ee0f204852e70da21320 | 66,290 |
def get_meraki_device_clients(org_name, device_name):
"""Query Meraki for Clients."""
dashboard = meraki.DashboardAPI(suppress_logging=True)
return dashboard.devices.getDeviceClients(_name_to_serial(org_name, device_name)) | 9682132355feb59b943edf856fb0d5ff59bd5a97 | 66,291 |
def rec_to_bintable(arr, name=None):
"""
Construct an `astropy.io.fits.BinTableHDU` from a record array.
Args:
arr (`numpy.recarray`):
The data array to write to a binary table.
name (:obj:`str`, optional):
The name for the binary table extension.
Returns:
... | fd1aeda99cf3bb45a24b646afbf263610a19175d | 66,292 |
import http
def node_identifiers_post(auth, node, **kwargs):
"""Create identifier pair for a node. Node must be a public registration.
"""
if not node.is_public or node.is_retracted:
raise HTTPError(http.BAD_REQUEST)
if node.get_identifier('doi') or node.get_identifier('ark'):
raise HT... | ab0d799b40925333476fd331a09b9a4b36143e0b | 66,294 |
def getPluginsDisabled():
""" Return the names of plugin that were disabled.
"""
if not options:
return ()
return tuple(set(options.plugins_disabled)) | 0feb34a7d4a840f3828a8f6939944d29de23b915 | 66,295 |
def match(pattern, text):
"""Match pattern against start of text; return longest match found or None."""
remainders = matchset(pattern, text)
if remainders:
shortest = min(remainders, key=len)
return text[: len(text) - len(shortest)] | 4bbe38e1f459a9e57cf13f3afb77edbdf110df7b | 66,296 |
def getClasspathOptions():
"""gets the classpath of the vmx86 distributions"""
return mx.get_runtime_jvm_args(['VM', 'VMX86_LAUNCHER', 'CORE', 'POSIX']) | b53420a14a0fb6192a83e11fe7927b5a0fb6ef32 | 66,299 |
import socket
def get_local_usable_addr():
"""Get local usable IP and port
Returns
-------
str
IP address, e.g., '192.168.8.12:50051'
"""
sock = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
try:
# doesn't even have to be reachable
sock.connect(('10.255.255.255'... | d7dfb57a755c5f96ae2e1e5864d5e6b66d45e2cd | 66,300 |
def create_example_randomizer_cata() -> DomainRandomizer:
"""
Create the randomizer for the `CatapultSim` used for the 'illustrative example' in F. Muratore et al, 2019, TAMPI.
:return: randomizer based on the nominal domain parameter values
"""
return DomainRandomizer(
BernoulliDomainParam... | 6909e7b28454a3343d92ac5a6ce3af680216a85b | 66,301 |
def boost_with_rotation_to_lab(four_vecs, rot, inv_rot):
"""rotated back, boost the 4 vecs, rotate again
very ugly..
"""
arr = []
for fv, rotation, inv_rotation in zip(four_vecs, rot, inv_rot):
e = fv.item(0)
p = fv[:, [1, 2, 3]]
p = inv_rotation * p.T
fv = np.mat... | 496748f52cc4689020e48d83ce9cde3426aea043 | 66,302 |
import itertools
def powerset(iterable):
"""All *nonempty* subsets of an iterable.
From itertools docs.
powerset([1,2,3]) --> (1,) (2,) (3,) (1,2) (1,3) (2,3) (1,2,3)
"""
s = list(iterable)
return itertools.chain.from_iterable(itertools.combinations(s, r) for r in range(1, len(s)+1)) | 875e4cacc9f1abf92604e89c7a6211e571150b69 | 66,303 |
import base64
def __decode(encoded, n):
"""
decode the string
"""
token = encoded.split(":")[0]
for _ in range(0, n):
token = base64.b64decode(token)
return token | 9ac3ba6da27ae255117b25c5f1c61f35d06c2c2e | 66,304 |
def _exact_instance_filter(query, filters, legal_keys):
"""Applies exact match filtering to an Instance query.
Returns the updated query. Modifies filters argument to remove
filters consumed.
:param query: query to apply filters to
:param filters: dictionary of filters; values that are lists,
... | ffa8e827903e3400f1c0aa0273bb0714827891e0 | 66,305 |
import numpy
def smooth_waterfall(arr,fwhm=4.0,unsharp=False):
"""
Smooth a waterfall plot.
If unsharp set, remove the smoothed component
Input array should have dimensions [timelen, nbolos]
"""
timelen,nbolos = arr.shape
kernel = numpy.exp(-numpy.linspace(-timelen/2,timelen/2,timelen)*... | 849b144a63b1209523e588724531e5cd24269e76 | 66,306 |
def load_graph_from_ckpt_file(weights_path):
"""
:param weights_path:
:return:
"""
# construct compute graph
input_tensor = tf.placeholder(dtype=tf.float32, shape=[1, 512, 512, 3], name='input_tensor')
net = resnet_fcn.ResNetFCN(phase='test', cfg=CFG)
prediction = net.inference(
... | 91dfc03a5cf62b0624b97660b5daa6532beefeb0 | 66,307 |
from typing import Dict
async def get_backend_auth_headers(session: ClientSession) -> Dict[str, str]:
"""
Authenticates with the OC Backend server
:return: Authorization header containing the returned JWT
"""
async with session.post(
f"{BACKEND_URL}/auth/login/",
json={"email": B... | 72e6d9bb9c8467f7e5cd1379b5ae3ad8b7aab64e | 66,308 |
from typing import Tuple
from typing import List
def _get_package_names_for_distribution(
distribution_path: str,
) -> Tuple[List[str], str]:
"""Get the top-level import names and project name for a given distribution file path
Args:
distribution_path: Path to the .whl, .tar.gz, or .zip file cont... | 866046a8f23d5c80534cbb500fb875efd42c2fa7 | 66,309 |
def find_geom(geom, geoms):
"""
Returns the index of a geometry in a list of geometries avoiding
expensive equality checks of `in` operator.
"""
for i, g in enumerate(geoms):
if g is geom:
return i | 2c2c9c2230ae745b6a781337192c694ba4ba4c59 | 66,310 |
def calculate_saliency_map(model: Model, data: np.ndarray, c: int, dependencies=None, normalise=True) -> np.ndarray:
"""
https://arxiv.org/abs/1312.6034 - saliency maps
https://arxiv.org/abs/1706.03825 - smoothed version
Calculates saliency map / vanilla gradient for feedforward neural network. Calculat... | 0e0f841995236ce0e2adf36960dc4232a0fd0333 | 66,311 |
from typing import List
from typing import Tuple
def cluster_state(m: int, n: int, inputs: List[Tuple[int,int]]=[]) -> BaseGraph:
"""Build a cluster state m qubits tall and n qubits wide. Optionally, give a list of grid positions
which serve as inputs."""
g = Graph()
vs = [[g.add_vertex(VertexType.Z, ... | 09e338650bcc040f02db7b9d7ee6fc171137ed43 | 66,312 |
def add_two_numbers(value1: int, value2: int) -> int:
"""Method to add two add_two_numbers
ARGUMENTS:
Value1: first value
Value2: second value
"""
try:
return value1 + value2
except TypeError as error:
print('Error at add_two_numbers()', error)
exce... | de4c3b1bd5ebd69fd2ff1dbc63a411f875841d8e | 66,313 |
def summary_table(params, proteins):
"""
Returns a string representing a simple summary table of
protein classifcations.
"""
out = ""
counts = {}
for seqid in proteins:
category = proteins[seqid]['category']
if category not in counts:
counts[category] = 1
... | 1fa3f16f799964bf9f1c0f1c593020902ab2219f | 66,314 |
def add_leading_zeroes( number, digits ):
"""
adds leading zeroes to fill up the digits.
"""
number = int( number )
string = str(number)
i = 1
while i < digits:
if number < 10 ** i:
string = '0' + string
i += 1
return string | 4437a3f930f5947ae749f34a07edd1a68fc6e077 | 66,315 |
def instance_has_unpaused(instance, log_files, alarms, event_logs, alarm_history,
start_datetime, end_datetime, action=False,
guest_hb=False):
"""
Returns true if the instance has unpaused
"""
success, reason = instance_is_running(instance)
if not ... | e8afd87130bad0a2a923c6c1555bab82694d85d2 | 66,316 |
def foreign_key(other_table, nullable=False):
"""
Declare a foreign key property, which will also create a foreign key column in the table with
the name of the property. By convention the property name should end in "_fk".
You are required to explicitly create foreign keys in order to allow for one-to-... | ff837bf20ab423772dce93dec88a9b83857cacb5 | 66,317 |
def propertize(fieldKeyName):
"""Transforms a string into an Python parameter name
"""
return stringcase.snakecase(fieldKeyName) | 4b8b463953500ce0a3848e70709bbbda7817f4fd | 66,318 |
from datetime import datetime
def get_default_datetime():
"""
A hook to help with mock data testing - put the default datetime
right in the middle of the "current" term.
"""
if is_using_file_dao():
term = get_current_term()
first_day = term.first_day_quarter
default_date = ... | 7b97bebb400653f91139ace6b5cdda1961a7f38f | 66,319 |
def get_map(nmers, vocabulary, vectors=None, mapping='random'):
"""
Prep and get a map.
"""
N = len(nmers)
W = len(vocabulary)
if W < N:
print 'ERROR: Not enough words.'
return False
if W > N:
print 'There are', W, 'elements in the vocabulary and only', N,
pri... | c6de0401bb1030fc4135c79c24ebbc894b7e1156 | 66,320 |
def diapreresnet110_cifar10(classes=10, **kwargs):
"""
DIA-PreResNet-110 model for CIFAR-10 from 'DIANet: Dense-and-Implicit Attention Network,'
https://arxiv.org/abs/1905.10671.
Parameters:
----------
classes : int, default 10
Number of classification classes.
pretrained : bool, de... | baf61449f48a25c85e98dcdeef6107652d676e7a | 66,321 |
from typing import Sequence
def pad_image_to_shape(img: npt.ArrayLike, new_shape: Sequence, mode: str = "constant"):
"""Pad all image axis up to specified shape."""
for i, dim in enumerate(img.shape):
if dim < new_shape[i]:
pad_size = (new_shape[i] - dim) // 2
img = pad_image(i... | 87652efad525263b428be4347cab18c76cae30e0 | 66,322 |
import PIL
def is_corrupt(jpegfile):
"""Returns None if the file is okay, returns an error string if the file is corrupt."""
# http://stackoverflow.com/questions/1401527/how-do-i-programmatically-check-whether-an-image-png-jpeg-or-gif-is-corrupted/1401565#1401565
try:
im = PIL.Image.open(jpegfile)... | bf0b284e2df49c079f1cc260d492aca963fba6a5 | 66,324 |
from apex import amp
def train(args, train_dataset, model: PreTrainedModel, tokenizer: PreTrainedTokenizer) -> Tuple[int, float]:
""" Train the model """
if args.local_rank in [-1, 0]:
tb_writer = SummaryWriter()
args.train_batch_size = args.per_gpu_train_batch_size * max(1, args.n_gpu)
def ... | 89e16027e0eeef4d69323354977357b705375137 | 66,325 |
import math
def is_valid_sample_rate(rate):
# type: (Any) -> bool
"""
Checks the given sample rate to make sure it is valid type and value (a
boolean or a number between 0 and 1, inclusive).
"""
# both booleans and NaN are instances of Real, so a) checking for Real
# checks for the possib... | 77542d10f7c379d565dcf3e66bc2cd5e22322d3f | 66,326 |
import random
def random_password():
"""
随机生成一个8位的数字的字符串
:return:
"""
password = ""
for i in range(8):
password += str(random.randint(0, 9))
return password | d7f83d4e01c79166d6b116c40622c82148252c30 | 66,327 |
import functools
import time
def log_service_time(func):
"""Loga o tempo para o serviço da requisição. Nenhuma exceção relacionada
a medição deve causar erro no serviço da requisição.
"""
@functools.wraps(func)
def wrapper(req):
start_time = time.time()
result = func(req)
e... | 588ce561ce7c47eb72fe207f116698b014c4bf0c | 66,328 |
def partition_to_lists(items, predicate=bool):
"""
Partitions an iterable into two different lists - the first does not match the given condition, and the second
does match the given condition.
Args:
items (iterable): An iterable of items to partition
predicate (function): A function th... | 1c2fe99b8ae7972738ca9028b65135bbfd1dab83 | 66,329 |
def on_board(i, j):
"""Return True if the location is on board
>>> on_board(0,0)
True
>>> on_board(-1,17)
False
"""
return 0 <= i < 8 and 0 <= j < 8 | 107f9e614c965b29c0c872738fd4ea5407971a29 | 66,330 |
def multiplicative_inverse(e, phi):
"""
Euclid's extended algorithm for finding the multiplicative inverse of two numbers
"""
d, next_d, temp_phi = 0, 1, phi
while e > 0:
quotient = temp_phi // e
d, next_d = next_d, d - quotient * next_d
temp_phi, e = e, temp_phi - quotient *... | 9934f6e2f86ff0ef4165728d59f11ba0d1cad928 | 66,331 |
def check_contradiction(statement1, statement2):
"""
Check if two statements are contradictory ignoring the time dimension.
:param statement1: the first statement
:param statement2: the second statement
:return:
"""
if not (statement1.arguments[0][0].startswith("e")
and statement... | fa0a485d68ece3a6ead3c41a017b58926273f42d | 66,332 |
def sort_models_by_encoding(models_list: list) -> list:
"""
Sort models by the encoding that will be used
:param models_list: unsorted list of models
:return: list of models sorted by encoding
"""
encodings = [get_mapping_name_to_class()[model_name].standard_encoding for model_name in models_l... | a45fea6ce8aa9f166340a0c1d181a1d06db1a7d9 | 66,333 |
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