content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
from datetime import datetime
def parse_last_timestamp(df):
"""
Parse last timestamp from dataframe.
Add one minute forward to prevent the script from fetching the same value.
The last timestamp already in database, so we need to fetch the weather data
one minute forward.
"""
if df.empty:... | 2fe7430344229e89aab33ef47af944735b79c169 | 31,225 |
def NextLexem_OperatorPredicate(op_value):
""" construct a predicate: lexem_list -> boolean
which checks if the next lexem is an operator whose value macthes
@p op_value (do not consume it) """
def predicate(lexem_list):
if len(lexem_list) == 0:
return False
head_lexe... | caf2866e85a42bee2e7eab0355cad4568bde46de | 31,227 |
import torch
def optim_inits(objective, x_opt, inference_samples, partition_samples, edge_mat_samples, n_vertices,
acquisition_func=expected_improvement, reference=None):
"""
:param x_opt: 1D Tensor
:param inference_samples:
:param partition_samples:
:param edge_mat_samples:
:p... | f048fc3290d890bc687f3176f66e5ad86dfa5141 | 31,228 |
def _pushb2phases(pushop, bundler):
"""handle phase push through bundle2"""
if 'phases' in pushop.stepsdone:
return
b2caps = bundle2.bundle2caps(pushop.remote)
if not 'pushkey' in b2caps:
return
pushop.stepsdone.add('phases')
part2node = []
enc = pushkey.encode
for newrem... | ff8f5c839919c6593e2d7d5cb98c477f8b2bc735 | 31,231 |
def predict_all(model, all_data):
"""
Predict odor probabilities for all trials.
:param model: (keras) decoding model
:param all_data: (4d numpy array) data of format [trial, window, neuron, time]
:return: (3d numpy array) prediction of format [trial, time, odor]
"""
test = stack_data(all_d... | 5bc748f6eddc4e6791601b87ff73a000a72efa4c | 31,232 |
def normalize(X):
"""Normalize the given dataset X
Args:
X: ndarray, dataset
Returns:
(Xbar, mean, std): tuple of ndarray, Xbar is the normalized dataset
with mean 0 and standard deviation 1; mean and std are the
mean and standard deviation respectively.
Note:
... | 5db71253b148387663b8575cf4df086cd182fbff | 31,233 |
def get_lat_lon(exif_data):
"""Returns the latitude and longitude, if available, from the provided exif_data (obtained through get_exif_data above)"""
lat = None
lon = None
if "GPSInfo" in exif_data:
gps_info = exif_data["GPSInfo"]
gps_latitude = _get_if_exist(gps_info, "GP... | d653dd84cd47efb2063db724cf7a88fa3f2a7490 | 31,234 |
def reduce_dimensions(df, reduce_cols=None, n_components=2):
"""
given a dataframe, columns to reduce and number of components for dimensionality reduction algorithm
returns a dictionary of reduction algorithm to it's name and reduced df.
dimensionality reduction or dimension reduction is the process o... | 39c5bf6257da93f449dc4081fde98ecd18465a0f | 31,237 |
import numpy
import math
def _dct_or_dst_type3(
x, n=None, axis=-1, norm=None, forward=True, dst=False, overwrite_x=False
):
"""Forward DCT/DST-III (or inverse DCT/DST-II) along a single axis.
Parameters
----------
x : cupy.ndarray
The data to transform.
n : int
The size of th... | 7e617e478c38ea47767a259df74581c960bfcaff | 31,238 |
def indi_events(person, tags=None):
"""Returns all events for a given individual.
Parameters
----------
person : `ged4py.model.Individual`
GEDCOM INDI record.
tags : `list` [ `str` ], optional
Set of tags to return, default is all event tags.
Returns
-------
events : `l... | 632a532ddcf6d187d1a9f8a5cf7b4451b3d73f37 | 31,239 |
def encrypt(key, plaintext):
"""Encrypt the string and return the ciphertext"""
return ''.join(key[l] for l in plaintext) | 0dc693fe1357756fdfee21cbc847fc6929dab2d1 | 31,240 |
from re import T
def rename_keys(
mapping: T.Dict[str, T.Any],
*,
prefix: T.Optional[str] = None,
suffix: T.Optional[str] = None
) -> T.Dict[str, T.Any]:
"""Renames every key in `mapping` with a `prefix` and/or `suffix`.
Args:
mapping (T.Dict): Mapping.
prefix (str, optional):... | fdfc335354e0ccf36c5416159927b7ffe8e5aec9 | 31,241 |
def any_root_path(path):
"""Rendering the React template."""
return render_template('index.html') | ba1069e4e52f2388b7a68129fa6ee7a4701ce31b | 31,242 |
def getChartdata():
"""
获取图表数据
params: request
return: response
"""
data = {'staff': {}}
data['staff']['is_worker'] = Staff.query.filter(Staff.is_leave==True).count()
data['staff']['not_worker'] = Staff.query.filter(Staff.is_leave==False).count()
data['staff']['total_worker'] = data[... | 70dcee23ca8e55ab8500e6ca56d44216aea69f95 | 31,243 |
def md_to_html(content):
""" Converts markdown content to HTML """
html = markdown.markdown(content)
return html | 16c67405d35b1119e2f52708aed26ad2f3f23244 | 31,244 |
import logging
def userdata_loader(s3_training_bucket='', trainer_script_name='trainer-script.sh'):
"""
Given the filepath for the trainer-script, load and return its contents as a str.
:param s3_training_bucket:
:param trainer_script_name:
:return:
"""
try:
# If the user didn't p... | 9ed6bf1c4cb252c855acf4ed943f3c8ce2a07952 | 31,245 |
def timer(string,i,f):
"""
Takes in:
i = starting time;
f = finishing time.
Returns: Time taken in full minutes and seconds.
"""
sec = f - i # Total time to run.
mins, sec= divmod(sec, 60.0)
time = string+' time: '+str(int(mins))+'min '+str(int(sec))+'s'
print(time)
... | cbb3c857160a4cbade7a02311455737b1e6e89ef | 31,246 |
def format_server_wrs(world_records, server_id):
"""Format the world records on the server browser to a table
world_records format: {server_id: [list of records]}
where every record is a tuple like {map_name, mode, date, time, player_name, steam_id, rank} accessible like sqlalchemy result"""
if ... | eef6be19b13694e8e7c7bf33d833c2f74960ad95 | 31,247 |
from pathlib import Path
def clean_file(path=Path('data') / 'Fangraphs Leaderboard.csv',
level='MLB', league='', season='', position=''):
"""Update names for querying and provide additional context.
Args:
level (str): the minor/major leave level selected. Default MLB.
league (s... | 4b01de07630f694c4b5a8010036b6394bed414ec | 31,248 |
def TextRangeCommandStart(builder):
"""This method is deprecated. Please switch to Start."""
return Start(builder) | dacf2fdb830f0fdfc5951288730963e3deb77741 | 31,249 |
import random
def ai_derp(gstate: TicTacToe, *args):
"""AI that randomly picks the next move"""
return random.choice(list(gstate.next_moves.keys())) | bfa1521c4bc2d4dad79a9f91b6bfed14b872f918 | 31,250 |
def get_logits_img(features, n_classes, mode, params):
"""Computes logits for provided features.
Args:
features: A dictionary of tensors that are the features
and whose first dimension is batch (as returned by input_fn).
n_classes: Number of classes from which to predict (i.e. the number
... | e4170d31949c531c54021b6a17c9cbd6306175eb | 31,251 |
def ccnv(pad=0):
"""Current canvas"""
global _cnvs
if pad == 0:
return _cnvs[-1]
_cnvs[-1].cd(pad)
return _cnvs[0].GetPad(pad) | 121f61661ea2a7d9ae941503c3bc2caa29f86dbd | 31,252 |
import functools
import unittest
def NetworkTest(reason='Skipping network test'):
"""Decorator for unit tests. Skip the test if --network is not specified."""
def Decorator(test_item):
@functools.wraps(test_item)
def NetworkWrapper(*args, **kwargs):
if GlobalTestConfig.NETWORK_TESTS_DISABLED:
... | f694902249d38be4d897ac20d47a23eb9ce10223 | 31,253 |
from typing import Dict
from typing import Any
def azure_firewall_network_rule_collection_update_command(client: AzureFirewallClient,
args: Dict[str, Any]) -> CommandResults:
"""
Update network rule collection in firewall or policy.
Args:
c... | 4d3d5ac09d345d661b2ef258ba2d6311c0f5b764 | 31,254 |
from typing import Optional
def get_stream(id: Optional[str] = None,
ledger_name: Optional[str] = None,
opts: Optional[pulumi.InvokeOptions] = None) -> AwaitableGetStreamResult:
"""
Resource schema for AWS::QLDB::Stream.
"""
__args__ = dict()
__args__['id'] = id
_... | 244721f3424c8de4c923b8eb57c96429c028280d | 31,255 |
def _is_course_or_run_deleted(title):
"""
Returns True if '[delete]', 'delete ' (note the ending space character)
exists in a course's title or if the course title equals 'delete' for the
purpose of skipping the course
Args:
title (str): The course.title of the course
Returns:
... | c32c69e15fafbc899048b89ab8199f653d59e7a8 | 31,256 |
def copy_installer_dict(installer_dict, default_installer):
"""Copy installer dict.
The installer rules themselves are not deep-copied.
'default_installer' installer names are replaced according to
``default_installer``.
:param str default_installer: name of the default installer
"""
resu... | 1bae37f603b0ac36b80e433b44722245f5df0090 | 31,257 |
import numpy
def pbg_dispersion_1d_imre(
results,
wave="p",
size=(6,4), xlim=(-1, 1), ylim=(0, 1)
):
"""
Plots the photonic dispersion (Bloch wavevector) of a photonic crystal structure,
computed for a range of frequencies (wavelengths) and one angle of incidence.
... | d1c8605e1255669b31f9caf530f3c8669a2e03a6 | 31,258 |
from typing import OrderedDict
def map_constructor(loader, node):
"""
Constructs a map using OrderedDict.
:param loader: YAML loader
:param node: YAML node
:return: OrderedDictionary data
"""
loader.flatten_mapping(node)
return OrderedDict(loader.construct_pairs(node)) | 21bf92d0c3975758ae434026fae3f54736b7f21d | 31,259 |
def index():
"""首页"""
return redirect(url_for('site.hot')) | 816585c515c254929fdbd0f8e2c0af99c73f9f9d | 31,260 |
def tpr(df, label_column):
"""Measure the true positive rate."""
fp = sum((df['predictions'] >= 0.0) & (df[label_column] > 0.5))
ln = sum(df[label_column] > 0.5)
return float(fp) / float(ln) | 62cd3908f5e8490c507b2b320a8a453aa861f77d | 31,261 |
from typing import Optional
def get_pathway_names(
database: str,
pathway_df: pd.DataFrame,
kegg_manager: Optional[bio2bel_kegg.Manager] = None,
reactome_manager: Optional[bio2bel_reactome.Manager] = None,
wikipathways_manager: Optional[bio2bel_wikipathways.Manager] = None
):
... | 40397aa26fc90b06f21fe30605ef654b14a98662 | 31,262 |
from pathlib import Path
def gather_rgi_results(rgi_sample_list: [RGIResult], outdir: Path) -> tuple:
"""
Symlinks RGI result files to a single destination folder -- required for rgi heatmap command
:param rgi_sample_list: List containing RGIResult object instances
:param outdir: Destination directory... | 664172d0d6de5619c7f92ba74a5f3673726aedf9 | 31,263 |
from connio.rest.api.v3.account.propertyy import PropertyInstance
def retention(retention):
"""
Serialize a retention object to retention JSON
:param retention: PropertyInstance.Retention
:return: jsonified string represenation of obj
"""
if retention is values.unset or retention is None... | 38762297e80c434ce3e561731850b40137a16fdb | 31,264 |
def get_tool_path(loader, node):
""" yaml tag handler to access tools dict at load time """
py_str = loader.construct_python_str(node)
return py_str.format(**tools) | 22e2d82e428e376b31082b213a50d7ed33a5045f | 31,265 |
def _get_oath2_access_token(client_key, client_secret):
"""
Query the vistara API and get an access_token
"""
if not client_key and not client_secret:
log.error(
"client_key and client_secret have not been specified "
"and are required parameters."
)
retu... | 2be67e8305aac64f3cf39517e64efa7659100bf5 | 31,266 |
def sanity_check_dp(A_org, XW, U, L, delta_l, delta_g, check_symmetry=True, \
activation='linear'):
"""
Sanity approach for solving min_{A_G^{1+2+3}} F_c(A) + np.sum(A.*L)
param:
A_org: original adjacency matrix
XW: X... | 21f51523b21c2ca94feddf4724d7848317054279 | 31,267 |
def quadratic_bezier(t, p0, p1, p2):
"""
:return: Quadratic bezier formular according to https://en.wikipedia.org/wiki/B%C3%A9zier_curve#Quadratic_B%C3%A9zier_curves
"""
return (1 - t) * ((1 - t) * p0 + t * p1) + t * ((1 - t) * p1 + t * p2) | ac9319683afb5b156ac40ba24865d9bc04531917 | 31,268 |
def add_musician_genres(musician, genre_list):
"""Add genres to a musician's profile"""
musician_genres = []
found_genres = Genre.query.filter(Genre.genre_name.in_(genre_list)).all()
for genre in found_genres:
musician_genre = MusicianGenre(genre_id=genre.genre_id,
... | 2557498853b8ecb634c282db5c27d0772ae066a1 | 31,269 |
def test_eat_exceptions_normal_case():
"""
If no exceptions, this wrapper should do nothing.
"""
@utils.eat_exceptions
def test_function(x):
return x
assert test_function(1) == 1 | ce16fff9511ac52b1e2ffb08305c839a1bb36b57 | 31,270 |
def delete_system_interface(api_client, interface_id, **kwargs): # noqa: E501
"""delete_system_interface # noqa: E501
Delete System Interface # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> response = awa... | a6c4db5d1c5ea1674146a7d723b8cea5725dcd51 | 31,271 |
def IsPlacementGroupCompatible(machine_type):
"""Returns True if VMs of 'machine_type' can be put in a placement group."""
prefix = machine_type.split('.')[0]
return prefix not in NON_PLACEMENT_GROUP_PREFIXES | 4c5cd10e2f2024d93b676df87a6e531fb866c228 | 31,272 |
import binascii
def create_public_key_from_b64(b64Key: bytes) -> X25519PublicKey:
"""Derive X25519 Private key from b64 ascii string"""
public_bytes = binascii.a2b_base64(b64Key)
loaded_private_key = X25519PublicKey.from_public_bytes(public_bytes)
return loaded_private_key | 8cdac21431ed278fb82cfc4c76379baec401e518 | 31,274 |
from re import T
def im_detect_bbox(model, images, target_scale, target_max_size, device,
captions=None,
positive_map_label_to_token=None
):
"""
Performs bbox detection on the original image.
"""
if cfg.INPUT.FORMAT is not '':
input_form... | a20c4eb8fb8b5cf37bc5ee59901504e3a03a1307 | 31,275 |
import warnings
def jmap(g, H, ae0, be0, af0, bf0, max_iter=1000, tol=1e-4, rcond=None, observer=None):
"""Maximum a posteriori estimator for g = H @ f + e
p(g | f) = normal(H f, ve I)
p(ve) = inverse_gauss(ae0, be0)
p(f | vf) = normal(0, vf I)
p(vf) = inverse_gauss(af0, bf0)
JMAP: maximizes... | 82b1199dfbaf1ecc9811b0d3127d976304df576f | 31,276 |
def get_chats(im):
"""This function gets the chatting messages.
Arguments:
im (PIL.Image.Image): Image object
Return:
Image object list (PIL.Image.Image).
[0]: The most latest chatting message. e.g, The most below messages.
"""
return get_chat_msg(im) | b3d30ee36025866020e8b8ce4c1b1477c2950fa3 | 31,277 |
def state_field(value):
"""Fetch the pagination state field from flask.request.args.
:returns: list of the state(s)
"""
states = istate.States.all()
value = value.split(',')
invalid_states = [state for state in value if state not in states]
assert not invalid_states, \
_('State(s) "... | c7e3d31780994c46fc1e43fc3f4398a4e93e77f6 | 31,278 |
import torch
def cal_smoothness_orig(var1_orig, var2_orig, var3_orig, io, args):
"""
Input:
var1_orig, var2_orig, var3_orig: scalar tensors, original variances on the 3 principal orientations
Return: smoothness_orig: scalar, original smoothness of this region (linearity/planarity/scattering,
... | 4713aede2109c17deb917fb2f86f73142185a258 | 31,279 |
def format_size(size):
"""Format provided size in bytes in a human-friendly format
:param int size: size to format in bytes
:return: formatted size with an SI prefix ('k', 'M', 'G', 'T') and unit
('B')
:rtype: str
"""
if abs(size) < 1000:
return str(size) + 'B'
for unit in ... | 04d9099a99e7c4863ada898096829aed9f6d7fc1 | 31,280 |
def get_acl_permission(acl, complete_acl_list):
"""
This uses numpy's vectorized operations to quickly match the acl returned from the API, to
the complete list of acls to get the description.
"""
index = -1
where_arrays = np.where(acl == complete_acl_list[:,0])
try:
index = wher... | 55dc256c75be9dfcf897fffc6a5842cc19dbf1d8 | 31,281 |
import torch
def interface_script(mod_interface, nn_module):
"""
Makes a ScriptModule from an nn.Module, using the interface methods rule for
determining which methods to compile.
Args:
mod_interface: the interface type that the module have
nn_module: The original Python nn.Module th... | dcfe3b7710a353da53c3e3b3ee2d360a943b77dd | 31,282 |
def create_call_error(message: str) -> str:
"""Create CallError serialized representation based on serialize Call.
Raises ValueError if message is not type Call. CallResult and CallError
don't require response.
"""
call: Call = unpack(message)
if isinstance(call, Call):
call_error: Call... | c30a5c50c8d43805b554e4b2002bdc73be568918 | 31,283 |
def filter_boxes(min_score, boxes, scores, classes):
"""Return boxes with a confidence >= `min_score`"""
n = len(classes)
idxs = []
for i in range(n):
if scores[i] >= min_score:
idxs.append(i)
filtered_boxes = boxes[idxs, ...]
filtered_scores = scores[idxs, ...]
filtered_... | 596c9ecab145df0d6a3a7f1da44898da27566b72 | 31,284 |
def recenter_image(im):
"""
"""
n_height, n_width = im.shape
com = nd.center_of_mass(im)
if any(np.isnan(com)):
return im
im_center = im[(com[0]-n_height/2):(com[0]+n_height/2)]
offset = [(n_height-im_center.shape[0]),(n_width-im_center.shape[1])]
if offset[0]%2 > 0:
h_odd = 1
else:
h_odd = 0
if offse... | 64a180c8ea67a8105a08e7c326cc92c6cf281803 | 31,285 |
from typing import Counter
def cal_participate_num(course: Course) -> Counter:
"""
计算该课程对应组织所有成员的参与次数
return {Naturalperson.id:参与次数}
前端使用的时候直接读取字典的值就好了
"""
org = course.organization
activities = Activity.objects.activated().filter(
organization_id=org,
status=Activity.Statu... | c2dff0f9b956c819170070116f4fda858f616546 | 31,286 |
def plot(
self,
fig=None,
ax=None,
is_lam_only=False,
sym=1,
alpha=0,
delta=0,
is_edge_only=False,
edgecolor=None,
is_add_arrow=False,
is_display=True,
is_show_fig=True,
):
"""Plot the Lamination with empty Slots in a matplotlib fig
Parameters
----------
... | b317fe6518b20cd266f035bbb6a6ff3e4de94e10 | 31,287 |
def usage_percentage(usage, limit):
"""Usage percentage."""
if limit == 0:
return ""
return "({:.0%})".format(usage / limit) | 7caf98ddb37036c79c0e323fc854cbc550eaaa60 | 31,288 |
def all(numbered=False):
"""
Get all included stanzas.
Takes optional argument numbered.
Returns a dict if numbered=True, else returns a list.
"""
return dict(zip(range(1, 165 + 1), stanzas)) if numbered else stanzas | af61087223411f3d57ec2e35f048da9da41bf469 | 31,289 |
from tensorflow.python.ops import math_ops
from tensorflow.python.framework import ops
def cosine_decay(learning_rate, global_step, maximum_steps,
name=None):
"""
"""
if global_step is None:
raise ValueError("global_step is required for cosine_decay.")
with ops.name_scope(name, "CosineDe... | 6f4395bf5ca38beb483f142acec91455e2a77ced | 31,290 |
def parse_file_header_64(bytes):
"""Parse the ELF file header."""
e_ident = {}
e_ident['EI_CLASS'] = get_bytes(bytes, 4)
e_ident['EI_DATA'] = get_bytes(bytes, 5)
endian = get_byte_order(e_ident['EI_DATA'])
e_ident['EI_VERSION'] = get_bytes(bytes, 6)
e_ident['EI_OSABI'] = get_bytes(bytes, 7)
... | 1b4a5cbd8f9dad58dc8d8ad6bd6a87f65d7bad07 | 31,291 |
def _or (*args):
"""Helper function to return its parameters or-ed
together and bracketed, ready for a SQL statement.
eg,
_or ("x=1", _and ("a=2", "b=3")) => "(x=1 OR (a=2 AND b=3))"
"""
return " OR ".join (args) | 1162600b49acb57e3348e6281767ce2fb0118984 | 31,292 |
from typing import Dict
def strip_empty_values(values: Dict) -> Dict:
"""Remove any dict items with empty or ``None`` values."""
return {k: v for k, v in values.items() if v or v in [False, 0, 0.0]} | 982814edbd73961d9afa2e2389cbd970b2bc231e | 31,293 |
import torch
def dispnet(path=None, batch_norm=True):
"""dispNet model architecture.
Args:
path : where to load pretrained network. will create a new one if not set
"""
model = DispNet(batch_norm=batch_norm)
if path is not None:
data = torch.load(path)
if 'state_dict' in d... | 8229c4616148c771686edbb7d99217404c48e3f9 | 31,294 |
def apigw_required(view_func):
"""apigw装饰器
"""
@wraps(view_func, assigned=available_attrs(view_func))
def _wrapped_view(request, *args, **kwargs):
request.jwt = JWTClient(request)
if not request.jwt.is_valid:
return jwt_invalid_view(request)
return view_func(request,... | c0bd9105df47297ae0f7db418ac3260c93272488 | 31,296 |
def text_analysis(string: str, *, nlp) -> str:
"""Return a text analysed string.
post-analysis sentences are separated by <sent> tags
e.g., 'a sentence<sent>a second sentence<sent>a third.
see https://spacy.io/usage/rule-based-matching#adding-patterns-attributes
"""
sents = []
doc = nlp(s... | 6bd16be281237bd2f2001755ce06d056a2cd8fda | 31,297 |
def wtr_tens(P, T):
"""Function to Calculate Gas-Water Interfacial Tension in dynes/cm"""
#P pressure, psia
#T temperature, °F
s74 = 75 - 1.108 * P ** 0.349
s280 = 53 - 0.1048 * P ** 0.637
if (T <= 74):
sw = s74
elif(T >= 280):
sw = s280
else:
sw... | acbf649a8dfe1302350b35f141afc09198470d8d | 31,298 |
from typing import List
def _decompose_move(event: MoveElements) -> List[MoveElements]:
"""
Decompose an event moving elements into a list of MoveElements events representing the
same action.
:param event: event to decompose
:return: list of events representing the same action
"""
return ... | c3572a2b183219280b4f352a8ddc98cbdfb7aa43 | 31,299 |
import math
def get_line_equation(segment_point0, segment_point1):
"""
Ax + By + C = 0
:param segment_point0: Point
:param segment_point1:
:return: A, B, C
"""
x0, y0 = segment_point0.px, segment_point0.py
x1, y1 = segment_point1.px, segment_point1.py
a, b, c = y1 - y0, x0 - x1, x... | 9e0b35f2cac4c7a5835755878fd8aa5d32735699 | 31,301 |
def keep_lesser_x0_y0_zbt0_pair_in_dict(p, p1, p2):
"""Defines x0, y0, and zbt0 based on the group associated with the
lowest x0. Thus the new constants represent the point at the left-most
end of the combined plot.
:param p: plot to combine p1 and p2 into
:param p1: 1st plot to combine
:param p... | 4dc7c008e86606b4257980f59b12fc6a183e060f | 31,302 |
from typing import List
from typing import Dict
from typing import Optional
def build_csv_from_cellset_dict(
row_dimensions: List[str],
column_dimensions: List[str],
raw_cellset_as_dict: Dict,
top: Optional[int] = None,
line_separator: str = "\r\n",
value_separator: str... | b6f40a97f14da3c37d63b6bfd545dc95fa61240e | 31,303 |
def get_stages_from_api(**kwargs):
"""
This is the API method, called by the appConfig.instantiate method
"""
resp = utils.request(utils.RETRIEVE, 'stages', kwargs)
return utils.parse(resp) | 03e6ae52b0e3e18bd107b5bf0069ccaa6c01b322 | 31,304 |
import numpy
import numba
def fill_str_array(data, size, push_back=True):
"""
Fill StringArrayType array with given values to reach the size
"""
string_array_size = len(data)
nan_array_size = size - string_array_size
num_chars = sdc.str_arr_ext.num_total_chars(data)
result_data = sdc.str... | 5dc586a7334bdae73145574fa9afb2f939f1808e | 31,305 |
def _visible_fields(user_profile, user, configuration=None):
"""
Return what fields should be visible based on user's preferences
:param user_profile: User profile object
:param user: User object
:param configuration: A visibility configuration dictionary.
:return: whitelist List of fields to b... | 43e9b0f03ebee891681a6c3cf7892c5dab36e5f0 | 31,306 |
def open_dataframe():
"""
Function to open the dataframe if it exists, or create a new one if it does not
:return: Dataframe
"""
print("Checking for presence of data file......")
try:
datafile = './data/data.csv'
dataframe = pd.read_csv(datafile)
print("File found.... loa... | 8f6bbed1e57df7a1567863c4ecd3bc4656901727 | 31,307 |
import fnmatch
def zipglob(sfiles, namelist, path):
"""Returns a subset of filtered namelist"""
files = []
# cycle the sfiles
for sfile in sfiles:
# we will create a list of existing files in the zip filtering them
# by the sfile filename
sfile.zfiles = fnmatch.filter(namelist,... | 818e9a7598ba0827616061bbfed80e345d1e22a5 | 31,309 |
def to_string(result: ValidationResult, name_col_width: int) -> str:
"""Format a validation result for printing."""
name = state_name(result.state)
if result.failed:
msg = ", ".join(result.error_details.strip().split("\n"))
return f"❌ {name} {msg}"
elif result.state.reward is None:
... | 263e327e053e6aee06a936b24eaabc2dd9ef028a | 31,310 |
def two_sum_v1(array, target):
"""
For each element, find the complementary value and check if this second value is in the list.
Complexity: O(n²)
"""
for indice, value in enumerate(array):
second_value = target - value
# Complexity of in is O(n). https://stackoverflow.com/questions/... | 0dcc3b4a10ac4c04cabd4ab09a9e71f739455f55 | 31,311 |
def worker_numric_avg(fleet, value, env="mpi"):
"""R
"""
return worker_numric_sum(fleet, value, env) / fleet.worker_num() | 9906fb0c35b718a9da6c8d6d0e0a5a85da5cf28d | 31,312 |
from typing import List
from typing import Tuple
from typing import Dict
def build_graph(
nodes: List[Tuple[str, Dict]], edges: List[Tuple[str, str, Dict]]
) -> nx.DiGraph:
"""Builds the graph using networkx
Arguments
---------
nodes : list
A list of node tuples
edges : list
A... | 0d0bbbfa96ddd5c170a2ec7e9fb06b964b997dd3 | 31,313 |
def table_exists_sql(any_schema=False):
"""SQL to check for existence of a table. Note that for temp tables, any_schema should be set to True."""
if not any_schema:
schema_filter_sql = sql.SQL('AND schemaname = current_schema()')
else:
schema_filter_sql = sql.SQL('')
return sql.SQL("""S... | 2ea073d26705f218d2929c7a419ef61a05c4cced | 31,314 |
def _process_json(data):
"""
return a list of GradPetition objects.
"""
requests = []
for item in data:
petition = GradPetition()
petition.description = item.get('description')
petition.submit_date = datetime_from_string(item.get('submitDate'))
if 'decisionDate' in it... | 5d381b896cd237b7780f1c048ef3e8fc6dd8bb9a | 31,315 |
def PaddingMask(pad=0):
"""Returns a layer that maps integer sequences to padding masks.
The layer expects as input a batch of integer sequences. The layer output is
an N-D array that marks for each sequence position whether the integer (e.g.,
a token ID) in that position represents padding -- value ``pad`` --... | 146f4bb6b518b38c007a42ed78c7e0d344070dee | 31,316 |
import yaml
def python_packages():
"""
Reads input.yml and returns a list of python
related packages
"""
with open(r"tests/input.yml") as file:
inputs = yaml.load(file, Loader=yaml.FullLoader)
return inputs["python_packages"] | 91889c21b1553f9b09c451913e658b458c4502d0 | 31,317 |
import asyncio
def create_tcp_visonic_connection(address, port, protocol=VisonicProtocol, command_queue = None, event_callback=None, disconnect_callback=None, loop=None, excludes=None):
"""Create Visonic manager class, returns tcp transport coroutine."""
# use default protocol if not specified
protocol =... | 0db9e05db4035caf828d61c91799d3658c61b6e0 | 31,318 |
def metric_wind_dict_to_beaufort(d):
"""
Converts all the wind values in a dict from meters/sec
to the corresponding Beaufort scale level (which is not an exact number but rather
represents a range of wind speeds - see: https://en.wikipedia.org/wiki/Beaufort_scale).
Conversion table: https://www.win... | b26ddb5e9c0423612a9c7086030fd77bbfa371ad | 31,319 |
def add_favorite_clubs():
"""
POST endpoint that adds favorite club(s) for student user. Ordering is preserved
based on *when* they favorited.
"""
user = get_current_user()
json = g.clean_json
new_fav_clubs_query = NewOfficerUser.objects \
.filter(confirmed=True) \
.filter(... | 1288e3d579dca54d25883fed4241b6fa1206f7f0 | 31,320 |
def death_rate_60():
"""
Real Name: b'death rate 60'
Original Eqn: b'Critical Cases 60*fraction of death 60/duration of treatment 60'
Units: b'person/Day'
Limits: (None, None)
Type: component
b''
"""
return critical_cases_60() * fraction_of_death_60() / duration_of_treatment_60() | 223990d67fcde9731080e58c7f5ca6ee208c17ff | 31,321 |
from datetime import datetime
def cast_vote(uid, target_type, pcid, value):
""" Casts a vote in a post.
`uid` is the id of the user casting the vote
`target_type` is either `post` or `comment`
`pcid` is either the pid or cid of the post/comment
`value` is either `up` or `down`
"""
... | 702622b91612c1b9636c16786c76c1c711cf7520 | 31,322 |
def convert_file(ifn: str, ofn: str, opts: Namespace) -> bool:
"""
Convert ifn to ofn
:param ifn: Name of file to convert
:param ofn: Target file to convert to
:param opts: Parameters
:return: True if conversion is successful
"""
if ifn not in opts.converted_files:
out_json = to... | 963a3bdc4b5fa48295230e183ee99fd4b3f79b22 | 31,323 |
def target_validation(target_name, action):
"""
Given a Target name and an action, determine if the target_name is a valid
target in target.json and if the target supports the action.
Parameters
----------
target_name : str
Name of the Target.
action : str
Type of action the... | c2f8015856f154c16fbcae29f3ed931c3a4d8f73 | 31,324 |
def bartletts_formula(acf_array, n):
"""
Computes the Standard Error of an acf with Bartlet's formula
Read more at: https://en.wikipedia.org/wiki/Correlogram
:param acf_array: (array) Containing autocorrelation factors
:param n: (int) Length of original time series sequence.
"""
# The first ... | d207695a59d1b1c968f2e3877edbee3ce97f1604 | 31,326 |
def AddEnum(idx, name, flag):
"""
Add a new enum type
@param idx: serial number of the new enum.
If another enum with the same serial number
exists, then all enums with serial
numbers >= the specified idx get their
serial numbers incremented (in other words,
... | 1b5a713380c1b79e1bc26e1300e36adbcc7ceb8e | 31,327 |
from typing import Optional
from typing import Tuple
from typing import Union
def get_turbine_shadow_polygons(blade_length: float,
blade_angle: Optional[float],
azi_ang: float,
elv_ang: float,
... | c3d568d60325a8309a3305b871943b55f8959f41 | 31,328 |
def str_igrep(S, strs):
"""Returns a list of the indices of the strings wherein the substring S
is found."""
return [i for (i,s) in enumerate(strs) if s.find(S) >= 0]
#return [i for (s,i) in zip(strs,xrange(len(strs))) if s.find(S) >= 0] | bae8afdb7d0da4eb8384c06e9f0c9bc3f6a31242 | 31,329 |
def random_laplace(shape, loc=0.0, scale=1.0, dtype=tf.float32, seed=None):
"""
Helper function to sample from the Laplace distribution, which is not
included in core TensorFlow.
"""
z1 = random_exponential(shape, loc, dtype=dtype, seed=seed)
z2 = random_exponential(shape, scale, dtype=dtype, seed=seed)
r... | 77c2df0bacfcf2ec07f137def93e2a9429d968ca | 31,330 |
import math
def resample_image(img_in, width_in, height_in, width_out, interpolation_method="bilinear"):
"""
Resample (i.e., interpolate) an image to new dimensions
:return resampled image, new height
"""
img_out = []
scale = float(width_out) / float(width_in)
scale_inv = 1.0 / scale
# print "Resampling sca... | 4d9759c02749cab30244326d3da7cf7c6c48fe46 | 31,331 |
def identify_missing(df=None, na_values=['n/a', 'na', '--', '?']):
"""Detect missing values.
Identify the common missing characters such as 'n/a', 'na', '--'
and '?' as missing. User can also customize the characters to be
identified as missing.
Parameters
----------
df : DataFrame
R... | b7b7fe20309463cd6f9044cb85459084910d23a4 | 31,332 |
def _TryJobSvnRepo(builder_type):
"""Returns an SVN repo to use for try jobs based on the builder type."""
if builder_type == fetch_build.PERF_BUILDER:
return PERF_SVN_REPO_URL
if builder_type == fetch_build.FULL_BUILDER:
return FULL_SVN_REPO_URL
if builder_type == fetch_build.ANDROID_CHROME_PERF_BUILDE... | 9d3a71ee10735499a0f677c88f5b2dc2c8e24e5c | 31,334 |
def find_wr5bis_common2(i, n, norm, solution_init, common2b_init):
"""
Find the point when for the scalar product of the solution
equals the scalar product of a guess with 2 consecutive bits in common.
Fct_common2b(w) = fct_solution(w), for which w in [w0_3 , w0_4]
with 0 =< w0_3 < w0_4 < 1 ?
fct_solution(w) =... | 2678f1ad355f1bc96aaf1be96945af2b21727d97 | 31,335 |
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