content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def _reorder_for_qbb_experiment(df: pd.DataFrame) -> pd.DataFrame:
"""By default the entries are ordered alphabetically. We want SPOTA, EPOpt, PPO"""
print("Changed the order")
return df.iloc[[2, 0, 1]] | beccd22a765eb526ed855fd34dde4a05e2b394f2 | 3,657,098 |
def get_field(self, *args, is_squeeze=False, node=None, is_rthetaz=False):
"""Get the value of variables stored in Solution.
Parameters
----------
self : SolutionData
an SolutionData object
*args: list of strings
List of axes requested by the user, their units and values (optional)
... | e93455cbc4b306762336fd13603342e9d92badd1 | 3,657,099 |
def handle_session_event(event: EventData) -> core_pb2.SessionEvent:
"""
Handle session event when there is a session event
:param event: event data
:return: session event
"""
event_time = event.time
if event_time is not None:
event_time = float(event_time)
return core_pb2.Sessi... | ddaa78a889c23326f52595d4a7fb71c1813eb971 | 3,657,101 |
def bump_patch(version):
"""Raise the patch part of the version
:param: version string
:return: the raised version string
:rtype: str
"""
verinfo = parse(version)
return format_version(verinfo['major'], verinfo['minor'],
verinfo['patch'] + 1) | 350e53788b0851138eb0d0248250bebd7e357e10 | 3,657,103 |
def _extract_bike_location(bike, lon_abbrev='lon'):
"""
Standardize the bike location data from GBFS. Some have extra fields,
and some are missing fields.
Arguments:
bike (dict[str, str]): A GBFS bike object as it appears in free_bike_status.json
lon_abbrev (str): The abbreviation used for `longitude`
... | a20929a85c993a59b82b552fcfee81b1f818648d | 3,657,104 |
def clean_word(word):
"""Return word in lowercase stripped of whitespace"""
return word.strip().lower() | ce57fa95ec111ee18c8a00c2076c686bc0abfe5c | 3,657,105 |
def get_batch_size(tracks):
"""
If tracks is a track-major list of possibly None tracks, get the batch size
"""
return get_shape(tracks)[0] | 677f26a0f42d4e745d77ff6abc1867ce857ea208 | 3,657,106 |
def find_edges_from_wires(body: TopoDS_Shape) -> set[TopoDS_Edge]:
"""Return set of edges from Wires."""
edge_set = set()
for wire in TopologyExplorer(body, ignore_orientation=False).wires():
for edge in WireExplorer(wire).ordered_edges():
edge_set.add(edge)
return edge_set | 89d8d848d98c32e925f955da623a3e1018245f75 | 3,657,107 |
def getSentB(text2: str, offsetB: int, nextPoint: int, sentLength: int):
"""
alignSentences auxiliar function to get the sentences of the original text.
"""
posB = text2[offsetB+sentLength:].find('.')
sentLength += posB+1
sentB = text2[offsetB:offsetB+sentLength]
nextPoint = offsetB + sentLe... | 54914a3c1d85464c0e5a4267538a73693e3df238 | 3,657,109 |
def get_mapping_fcost_local(interface, bus_def):
"""
coarse cost function to cheaply estimate local (subset of ports)
interface match to bus_def
"""
cost = _get_mapping_fcost_base(interface, bus_def, penalize_umap=False)
name_cost = _get_name_fcost2(interface, bus_def)
cost.nc = name_cost
... | c945e89174fea0c131f35ad4688c5539a55c3eda | 3,657,110 |
import base64
def base64_image(image: bytes, mime_type: str) -> str:
"""Encode the image for an URL using base64
Args:
image: the image
mime_type: the mime type
Returns:
A string starting with "data:{mime_type};base64,"
"""
base64_data = base64.b64encode(image)
image_... | 3079c73137959fea1d16ceb64251870500ae30a5 | 3,657,111 |
import math
import six
import numpy
def multi_box_head(inputs,
image,
base_size,
num_classes,
aspect_ratios,
min_ratio=None,
max_ratio=None,
min_sizes=None,
max_sizes... | e3fabec0dd64fec9caea929e0bf4c04848d22df6 | 3,657,112 |
from operator import invert
import numpy
def expandMask(img, shrink = False, step = 1):
"""Grow or shrink a mask by a pixel."""
if shrink:
img = invert(img)
img = jitterSum(img.data, step) > 0
img = Image(data = img.astype(numpy.uint8)*255)
if shrink:
img = invert(img)
return i... | 4853a0c42856cc34a5b9b58533d335c0ac858345 | 3,657,113 |
def isHeader(line):
"""
tests to see if 'line' is in the event file
header
"""
if containsAny(line, 'EVF Filename:', 'Generation Time:', 'Start_time:',
'End_time:', 'events in list)', '#', 'Include:',
'Init_value:'):
return True
elif len(line... | 548d0273b174c16e7ab874fe8a94d4ec7e87703b | 3,657,114 |
import requests
def redirect_page(source_url, destination_url):
"""returns False is current page is not 200"""
def _check_redirect(full_url):
print('Getting ' + full_url)
response = requests.get(full_url, allow_redirects=False)
if response.status_code == 200:
print("Was 20... | 8caa9db41948f44cc015ca51f179ff318eb22ada | 3,657,115 |
def WrapWithQuotes(text, quote='"'):
""" Wrap the supplied text with quotes
Args:
text: Input text to wrap
quote: Quote character to use for wrapping (default = "")
Returns:
Supplied text wrapped in quote char
"""
if not text.startswith(quote):
text = quote + text
... | f4f7b83d60e3ea928e3502b9d19ca4c8d52914b9 | 3,657,117 |
def login_aws_via_idp(session, username, password, entity_id):
""" Get a SAML assertion and set of AWS roles which can be assumed with the SAML assertion. """
logger.info("Looking up your IdP")
idp_url, idp_form = get_idp_login_form(
session, username, password, entity_id)
logger.info("Logging ... | 586250b66771275b5282ae0e22d40298550164e2 | 3,657,119 |
def fit_linreg(x, y, intercept=True):
"""Simple linear regression: y = kx + b.
Arguments
---------
x: :class:`~numpy.ndarray`
A vector of independent variables.
y: :class:`~numpy.ndarray`
A vector of dependent variables.
intercept: bool
If using steady state assumption f... | 18248eb0ece96dfda5fbc2d94a591f98570feddd | 3,657,120 |
import torch
def entropy(x, input_as_probabilities):
"""
Helper function to compute the entropy over the batch
input: batch w/ shape [b, num_classes]
output: entropy value [is ideally -log(num_classes)]
"""
if input_as_probabilities:
x_ = torch.clamp(x, min = 1e-8)
b = x_ ... | 9cf9f5ecd59ffe068bbf8f25da62ac3c5c2eedb6 | 3,657,121 |
from typing import Callable
def find_function_in_object(o: object, function_name: str) -> Callable:
"""Finds a callable object matching given function name in given object.
Args:
o: Any object.
function_name: Name of attribute within o.
Returns:
Callable object with name <functio... | c3b6ad12f42d005f643bc8a657f728613bd0e93c | 3,657,122 |
async def refresh(db: AsyncSession, schema: RefreshToken):
"""
Refresh token
:param db: DB
:type db: AsyncSession
:param schema: Refresh token
:type schema: RefreshToken
:return: Access token
:rtype: dict
:raise HTTPException 400: User not found
""... | f20cde1c44ef515c18318c45af9df4bb360c85e6 | 3,657,123 |
def gumbel_softmax(logits, temperature, hard=False):
"""Sample from the Gumbel-Softmax distribution and optionally discretize.
Args:
logits: [batch_size, n_class] unnormalized log-probs
temperature: non-negative scalar
hard: if True, take argmax, but differentiate w.r.t. soft sample y
Returns:
[... | 7612ef322acf77f8c2fdf1963b6d15934f84b416 | 3,657,124 |
def build_custom_Theta(
data,
data_description=[],
add_constant_term=True,
):
"""
builds a matrix Theta(U) from a predefined set of terms
This is used when we subsample and take all the derivatives point by point or if there is an
extra input to put in.
input:
data: column 0 is... | 451c306124e94d5f04d436c98ede6af232a6458e | 3,657,126 |
import pathlib
from typing import Optional
import importlib
def load(plugin: pathlib.Path) -> Optional[ModuleType]:
"""Load a specific cemu plugin
Args:
plugin (pathlib.Path): the path of the plugin to load
Returns:
Optional[ModuleType]: the loaded plugin module on success, None if there... | eac265743ba9a58842cf7e97a1b961234ea3b17b | 3,657,127 |
import traceback
def getDatabaseConnection(databaseString):
"""Attempt connection to the database"""
sqlsession = None
try:
sqlengine = sqlalchemy.create_engine(databaseString)
SQLSession = sessionmaker(bind=sqlengine)
sqlsession = SQLSession()
print("Connection to " + databaseString + " successfull")
... | 8199838e24c6828977d5fe6a7f2af20f755f25f6 | 3,657,129 |
def prepare_multiple_configs(conf):
""" This function uses workload_1 as a base, and then duplicates its configuration for all
other workloads 2,3... while leaving properties already defined in subsequent workloads (2,3..)
unchanged.
"""
keys_starting_with_workload = []
for k, _ in conf.iterite... | 760adf50bbca9dd160375ed8d506a33618d39a94 | 3,657,130 |
def undo_coefficient_scaling(clf = None, coefficients = None, intercept = 0.0, scaler = None):
"""
given coefficients and data for scaled data, returns coefficients and intercept for unnormalized data
w = w_scaled / sigma
b = b_scaled - (w_scaled / sigma).dot(mu) = b_scaled - w.dot(mu)
:param skle... | cee60338386bdc87cb50e4b54af43517135fba46 | 3,657,131 |
import copy
def reduce(snail_nr):
"""Returns a fully reduced version of the given snail number."""
new_snail_nr = copy.deepcopy(snail_nr)
# print("Start:")
# print(snail_nr)
while True:
# print("\nNew reduction phase...")
if explode_in_place(new_snail_nr):
# print("Exp... | 1facd7a7bbc73794ff2519ef0894ec9536c18690 | 3,657,132 |
def load_image_embedding_model(input_repr, content_type, embedding_size):
"""
Returns a model with the given characteristics. Loads the model
if the model has not been loaded yet.
Parameters
----------
input_repr : "linear", "mel128", or "mel256"
Spectrogram representation used for audi... | f78d458e2cd000206d3fcc35c166ede43e84e8fd | 3,657,133 |
def prepare_alm(alm=None, ainfo=None, lmax=None, pre=(), dtype=np.float64):
"""Set up alm and ainfo based on which ones of them are available."""
if alm is None:
if ainfo is None:
if lmax is None:
raise ValueError("prepare_alm needs either alm, ainfo or lmax to be specified")
ainfo = sharp.alm_info(lmax)
... | 21406a6b3df7e63eeb05998c8940e525021b62ce | 3,657,134 |
from typing import Any
def increment_occurance_dict(d: dict, k: Any) -> None:
"""
Increment occurance dict, updates in-place so nothing is returned.
"""
try:
d[k] += 1
except KeyError:
d[k] = 1
return None | 725b437494f4c647848c54a3d13b4e974fa7f0e8 | 3,657,135 |
import scipy
def closest_line(query_lines, metric='cosine'):
"""Compute the distance to, and parameters for, the closest line to each
line in query_lines.
Args:
- query_lines: Array of lines to compute closest matches for, shape
(n_lines, width, height, 1)
- metric: String to ... | 187cb6f8266ddf7bd0347fb233fb02a7ea4cbad3 | 3,657,137 |
def deref_vtk(obj):
"""Dereferences the VTK object from the object if possible."""
if isinstance(obj, TVTKBase):
return obj._vtk_obj
else:
return obj | 1ba46f83a389983df3c35f011c94836f12fdd905 | 3,657,138 |
def order_assignee_factory(team):
"""
Creates a :class:`datahub.omis.order.models.OrderAssignee` instance related to ``team``
"""
adviser = Advisor.objects.create(
first_name='John',
last_name='Doe',
email=f'{uuid4()}@example.com',
)
order_assignee = OrderAssignee.objects... | fe39d16a105ff01be63614e76dcf001b5ca4171f | 3,657,139 |
def is_bool(space, w_obj):
""" Finds out whether a variable is a boolean"""
return space.wrap(w_obj.tp == space.tp_bool) | 39b62ec08ebbdd4d7505e558ad4901ca67afc12d | 3,657,140 |
def air_density(t_f, elevation):
"""Eq 20, page 25"""
return (1.293 - 1.525e-4 * elevation + 6.379e-9 * elevation ** 2) / (
1 + 0.00367 * t_f
) | d5677c755fc52e1ae8cc5293d4ed5c9a4debb71d | 3,657,143 |
def _strip_after_new_lines(s):
"""Removes leading and trailing whitespaces in all but first line."""
lines = s.splitlines()
if len(lines) > 1:
lines = [lines[0]] + [l.lstrip() for l in lines[1:]]
return '\n'.join(lines) | 247cee0f34ab1e742069e05c8c00095cd24d80bc | 3,657,144 |
def make_connection(request):
"""
Create a StreamSplitRoutine from a MockConnection and a container, return topics 'A' and 'B' as well as the routine
"""
def generate(*, max_items_send: int):
return MockConnection(max_items_send=max_items_send)
yield generate | a0a4adbdf6fb7487d27f9e81c8f4bb5af49fae58 | 3,657,145 |
import copy
def my_browse(*args, **kwargs):
""" Creates and starts an ObjectBrowser with modified summary column.
"""
attribute_columns = copy.deepcopy(DEFAULT_ATTR_COLS)
summary_column = [col for col in attribute_columns if col.name == 'summary'][0]
summary_column.data_fn = my_summary
return ... | 3f5e681112bf5dd7a56a3259e188a1c5773f2cf5 | 3,657,146 |
import psutil
def cpu_min_frequency():
"""
Returns the processor minimum frequency, in Mhz (> int)
"""
return psutil.cpu_freq().min | de4312ccd95e46d6d157bdb1a08d48fe5924942f | 3,657,147 |
def log_error(message: str) -> str:
"""error log"""
return message | dbd86c39bc504dbac8d308e124c73310df21f372 | 3,657,148 |
from datetime import datetime
from operator import or_
from operator import and_
def exclude_preservation_pending(q):
"""
Transform query to exclude MuseumObject entries which are pending
preservation
"""
now = datetime.datetime.now(datetime.timezone.utc)
preservation_boundary = now - PRESERVA... | a43eefeaaac16ac872ae02bd522873966e5f21e2 | 3,657,149 |
from datetime import datetime
def naturalday(value, format=None):
"""
For date values that are tomorrow, today or yesterday compared to
present day returns representing string. Otherwise, returns a string
formatted according to settings.DATE_FORMAT.
"""
value = localtime(value)
try:
... | fbc1fe32f5735f57c989488989aabd427a59c160 | 3,657,150 |
import tensorflow as tf
from torch.utils.data import DataLoader
def test_adaptors(adaptor: str, shuffle_buffer_size: int):
"""
Test if framework-specific generator adpators yield batches.
"""
idx = np.arange(0, 10)
def map_fn(x_, obs_):
"""
Note: Need to convert to numpy in output... | 088bd70f50b63a07f7392f1712de0d6aab9515a2 | 3,657,151 |
def qg8_graph_write(filename: str, graph: qg8_graph):
"""
Wrapper function which prepares a collection of chunks (graph) and writes it to a file
"""
if not isinstance(graph, qg8_graph):
raise TypeError("Second argument is not a qg8_graph")
try:
qg8f = qg8_file_open(filename, QG8_MOD... | a26891c86df5541cb1ffa3d3eb463bea5472d3d7 | 3,657,152 |
def valid_post_author(user, post):
"""This function checks whether the post was created by the user"""
if str(user.key().id()) == str(post.user.key().id()):
return True | 94ca2f23aa66f79be997080c61fc2f265e868e5f | 3,657,153 |
import json
import time
import collections
from datetime import datetime
def listing(request, **kwargs):
"""view for processing and applying listings"""
context = {
'view': 'listing',
'all_channels': CHANNELS,
'all_towns': TOWNS,
'method': request.method,
'actions': ['l... | c4938dc4db4526ca93558305ea702660956e77fa | 3,657,154 |
def get_rise_or_fall(U, V, Im, demo=0):
"""
Get increase or decrease of intensity in flow direction: This finds us
the front and the wake regions of each wave.
"""
rr, cc = np.shape(Im)
ax_x, ax_y = np.linspace(1, cc, cc), np.linspace(1, rr, rr)
XX, YY = np.meshgrid(ax_x, ax_y)
Velo_mag ... | a2d86bd986f576054ccd2686af7d9da4ffd3a1f0 | 3,657,155 |
import functools
def has_vanity_name(func):
"""Decorator checking whether a command has been provided a vanity_name value"""
@functools.wraps(func)
async def wrapper(*args, **kwargs):
vanity_name = args[1]
if vanity_name is None:
ctx = args[0]
await ctx.send("Please... | 5da3cc410822f0e112a2be1b3cdfc66fb4d79b0c | 3,657,156 |
from typing import List
import logging
def get_data_providers(
data_providers_configs: List[dict], data_providers_input: List[str]
) -> List[data.DataProvider]:
"""
Determines which data provider and in which order should be used.
:param data_providers_configs: A list of data provider configurations
... | 076659d2bf619808f5cb0ac124839e569af0c74a | 3,657,157 |
def _PredatorForFracas(config=None):
"""A helper to pass in the standard pipeline class."""
return PredatorForFracas(MOCK_GET_REPOSITORY, config or {}) | c7e1e3c771a8b8afa921a291198adc084f75d186 | 3,657,158 |
def py_SurfStatSmooth(Y, surf, FWHM):
"""Smooths surface data by repeatedly averaging over edges.
Parameters
----------
Y : numpy array of shape (n,v) or (n,v,k)
surface data, v=#vertices, n=#observations, k=#variates.
surf : a dictionary with key 'tri' or 'lat', or a BSPolyData object.
... | 6b537e33174459cee6364dbd145181c66156830d | 3,657,159 |
from typing import Tuple
def arm_name_to_sort_key(arm_name: str) -> Tuple[str, int, int]:
"""Parses arm name into tuple suitable for reverse sorting by key
Example:
arm_names = ["0_0", "1_10", "1_2", "10_0", "control"]
sorted(arm_names, key=arm_name_to_sort_key, reverse=True)
["contro... | c29958bb541a9754e7b4defc6ad953030a364d2f | 3,657,160 |
from typing import Optional
from typing import Mapping
from typing import Any
def run_query_row(cur: Cursor, sql: str, params: Optional[Mapping[str, Any]] = None, **kwargs: Any
) -> Optional[skytools.dbdict]:
""" Helper function if everything you need is just paramertisized execute to
fe... | 0ba46ba0666d0cbefeda5b3fe62ac5ed883a190f | 3,657,161 |
def vortex_indicator(high_arr, low_arr, close_arr, n):
"""Calculate the Vortex Indicator for given data.
Vortex Indicator described here:
http://www.vortexindicator.com/VFX_VORTEX.PDF
:param high_arr: high price of the bar, expect series from cudf
:param low_arr: low price of the bar, expect s... | 8b34ca26f7cc52361eb95ff1ad17c010fd270759 | 3,657,162 |
from typing import Dict
def getServiceById(serviceId: str, **kwargs) -> Dict:
"""Retrieve service by its identifier.
Args:
serviceId: Identifier of service to be retrieved.
Returns:
Service object.
"""
db_collection_service = (
current_app.config['FOCA'].db.dbs['serviceSt... | fc568b337495873263f9a7ea85d46ac4bcd55819 | 3,657,163 |
from typing import Dict
from typing import Any
def replace_module_prefix(
state_dict: Dict[str, Any], prefix: str, replace_with: str = "", ignore_prefix: str = ""
):
"""
Remove prefixes in a state_dict needed when loading models that are not VISSL
trained models.
Specify the prefix in the keys th... | b8499c818053e7798e9549fbe546bab7d5fbfa84 | 3,657,164 |
def crop(img, left, top, right, bottom):
"""
Crop rectangle from image.
Inputs:
img - The image to crop.
left - The leftmost index to crop the image.
top - The topmost index.
right - The rightmost index.
bottom - The bottommost index.
Outputs:
img - The c... | 1507a55bba07dc656f51f873d2328b69f70682c9 | 3,657,166 |
import ipaddress
def get_hosts(network):
"""get_hosts() will return all the hosts within a provided network, range"""
network = ipaddress.IPv4Network(network, strict=False)
hosts_obj = network.hosts()
hosts = []
for i in hosts_obj:
hosts.append(str(i))
return hosts | 097fa3abbf1cda1c3c0ddc0c2fec4a06d1d44fa9 | 3,657,168 |
def select_organization(cursor):
"""organization情報取得(全取得)
Args:
cursor (mysql.connector.cursor): カーソル
Returns:
dict: select結果
"""
# select実行
cursor.execute('SELECT * FROM organization ORDER BY organization_id')
rows = cursor.fetchall()
return rows | 6e5c1a2f90d41223ba09fe3278353370515c0430 | 3,657,169 |
def _GetInstDisk(index, cb):
"""Build function for calling another function with an instance Disk.
@type index: int
@param index: Disk index
@type cb: callable
@param cb: Callback
"""
def fn(ctx, inst):
"""Call helper function with instance Disk.
@type ctx: L{InstanceQueryData}
@type inst: ... | 4dc83bb5c7ac3556750f9e3a70f77c9325893fb4 | 3,657,170 |
def Jphii_cal(L, W, q, xi_local):
"""タスク写像のヤコビ行列"""
return np.array([[1, 0, -sin(q[2, 0]) * xi_local[0, 0] - cos(q[2, 0]) * xi_local[1, 0]],
[0, 1, cos(q[2, 0]) * xi_local[0, 0] - sin(q[2, 0]) * xi_local[1, 0]]], dtype = np.float32)
#return np.array([[1, 0, -xi_local[1, 0]],
# ... | 300a3724829d8ce2df15801b6ae02e78e8e2e6b7 | 3,657,171 |
def model_evalution(test_data):
""" function to test the loss and accuracy on validation data """
for X_test, y_test in val_data:
y_pred = model(X_test, training=False)
val_acc_metrics.update_state(y_test, y_pred)
accuracy = val_acc_metrics.result()
return float(accuracy) | d581013f50560082f8f6854f201cfd791be6e876 | 3,657,172 |
import inspect
import numpy
def make_python_script_from_list(list_optical_elements1,script_file=""):
"""
program to build automatically a python script to run shadow3
the system is read from a list of instances of Shadow.Source and Shadow.OE
:argument list of optical_elements A python list with inta... | 85eb57955badaa4a2748be8ca6f2bf0f370b422d | 3,657,173 |
def flax_tag(arr):
"""Wraps a value in a flax module, to inspect intermediate values."""
return arr | be2fbef6117c859b7fc9dd7274815df4e70df17e | 3,657,174 |
def toEpoch( dateTimeObject = None ):
"""
Get seconds since epoch
"""
if dateTimeObject == None:
dateTimeObject = dateTime()
return nativetime.mktime( dateTimeObject.timetuple() ) | f679f75e9d416c471491b0b933505fc6bbb6eb7d | 3,657,175 |
import requests
import json
def sendNotification(token, title, message, extraData=None, channelID=None):
"""
send Notification to Devices
:param token:
:param title:
:param message:
:return:
"""
url = 'https://exp.host/--/api/v2/push/send'
headers = {
"Content-Type": "app... | 1038dfd3872221a0d447b7708d58d95e931c59e5 | 3,657,176 |
def make_phsfct_kernel(size_px, dpx, g_fac):
"""
Make a kernel for phase function convolution
:param size_px:
:param dpx: [deg/px]
:param g_fac:
:return: ph_ker [deg]
"""
ke = np.mgrid[:size_px, :size_px]
half = (size_px - 1) / 2
ke[0] -= half
ke[1] -= half
dist = np.sqrt... | 0f214d19f7418385f3db9155e8cabb06779fdf83 | 3,657,177 |
def sample_pts_ellipsoid_surface(mu, Q, NB_pts, random=True):
"""
Uniformly samples points on the surface of an ellipsoid, specified as
(xi-mu)^T Q^{-1} (xi-mu) == 1
arguments: mu - mean [dim]
Q - Q [dim x dim]
NB_pts - nb of points
random - True... | 89fa8383d32b74e8c92a52792fe2de4d35816acc | 3,657,178 |
def load_mzml_path():
"""Return the path to the mzML toy file.
Parameters
----------
None
Returns
-------
path_data : str
The path to the mzML data.
Examples
--------
>>> from specio.datasets import load_mzml_path
>>> load_mzml_path() # doctest: +ELLIPSIS
'...s... | b0548589a209b14ef336a28eeca74782f3550186 | 3,657,179 |
def _czce_df_read(url, skip_rows, encoding='utf-8', header=0):
"""
郑州商品交易所的网页数据
:param header:
:type header:
:param url: 网站 string
:param skip_rows: 去掉前几行 int
:param encoding: utf-8 or gbk or gb2312
:return: pd.DataFrame
"""
headers = {
"Accept": "text/html,application/xh... | 1491e312f1548141294d20b6ebe2fb4517cd3e07 | 3,657,180 |
import random
def select(weights):
"""
select a node with probability proportional to its "weight"
"""
r = random.random() * sum(weights)
s = 0.0
for k,w in enumerate(weights):
s += w
if r <= s:
return k
raise RuntimeError("select WTF from %s" % weights) | fed92de65cfae6f3532754215f5b88a564365ac7 | 3,657,181 |
def kexo(spacecraft_id, sensor_id, band_id):
"""Sun exo-atmospheric irridiance [W/m2/sr]
This is used for processing surface reflectance.
Spacecraft_id: Landsat7
Sensor_id: ETM+
band_id: band1, band2, band3, band4, band5, band7, band8
Spacecraft_id: Terra
Sensor_id: Aster
band_id: band1, band2, band3, ban... | 0e11a1b0b6ea8a43bef954273ed3a32a1d39c842 | 3,657,182 |
def gen_profile_id(profile_id):
"""
Generates the Elasticsearch document id for a profile
Args:
profile_id (str): The username of a Profile object
Returns:
str: The Elasticsearch document id for this object
"""
return "u_{}".format(profile_id) | 003586fe87d2936d9054aaa35963ae0241a5e594 | 3,657,183 |
async def get_self_info(credential: Credential):
"""
获取自己的信息
Args:
credential (Credential): Credential
"""
api = API["info"]["my_info"]
credential.raise_for_no_sessdata()
return await request("GET", api["url"], credential=credential) | 74cc7f5e43c555de45c382db27cd314bb2b5794e | 3,657,185 |
def mpl_event_handler(event_type: MplEvent):
"""Marks the decorated method as given matplotlib event handler
.. note::
This decorator should be used only for methods of classes that
inherited from :class:`MplEventDispatcher` class.
This decorator can be used for reassignment event handlers... | 7cec2aad7f50daf832657bc01ac710159d1161a0 | 3,657,187 |
def get_date_pairs(in_dates, step):
"""
入场点出场点数据
:param in_dates: 所有入场日期
:param step: 步长
:return:
"""
DatePair = namedtuple('DatePair', ['in_date', 'out_date'])
date_pairs = []
for in_date in in_dates:
out_date = date_utility.date_cal(in_date, step)
date_pairs.append(... | a2da0f3a48296de6c9f70b0e7535c8a2dd8e3d0b | 3,657,188 |
import random
def new_jitters(jitter):
"""
update jitter vector every 100 frames by setting ~half of noise vector units to lower sensitivity
"""
jitters=np.zeros(128)
for j in range(128):
if random.uniform(0,1)<0.5:
jitters[j]=1
else:
jitters[j]=1-jitter ... | cab660f8b8c6cfb21e745479cae95e964dc412b9 | 3,657,189 |
def add_manuscript_urls_to_ci_params(ci_params):
"""
Return and edit in-place the ci_params dictionary to include 'manuscript_url'.
This function assumes Travis CI is used to deploy to GitHub Pages, while
AppVeyor is used for storing manuscript artifacts for pull request builds.
"""
if not ci_pa... | 7d45c4fe8060d387d0238788e4b7566e09abc499 | 3,657,191 |
def count_sites(vcfpath):
"""Extract number of sites in VCF from its tabix index."""
cmd = ["bcftools","index","--nrecords", vcfpath]
so, se, code = slurp_command(cmd)
return int(so) | 4f340827bbfc279e3b2601bd84ef68669ce1d829 | 3,657,192 |
import torch
from typing import Callable
def model_contrast_score(overlays: torch.Tensor, masks: torch.Tensor, object_labels: torch.Tensor,
scene_labels: torch.Tensor, object_model: Callable, scene_model: Callable,
object_method: Callable, scene_method: Callable, devi... | b44b0a958a79a1ad7a84de15817cdbc32160c13b | 3,657,193 |
from typing import Optional
def get_network_insights_access_scope_analysis(network_insights_access_scope_analysis_id: Optional[str] = None,
opts: Optional[pulumi.InvokeOptions] = None) -> AwaitableGetNetworkInsightsAccessScopeAnalysisResult:
"""
Resource schema f... | cbd65230cf553b438f4a78ad34f6faa9eafb119f | 3,657,194 |
def wavenumber(src, rec, depth, res, freq, wavenumber, ab=11, aniso=None,
epermH=None, epermV=None, mpermH=None, mpermV=None, verb=2):
"""Return the electromagnetic wavenumber-domain field.
Calculate the electromagnetic wavenumber-domain field due to infinitesimal
small electric or magnetic ... | c108f3343936a62b0d49a3807d2d25b4f3fc1eda | 3,657,196 |
def gumbel_softmax(logits, temperature, dtype=tf.float32, seed=0):
"""Gumbel Softmax Layer."""
log_alpha = tf.nn.log_softmax(logits)
eps = 1e-7
gumbel = -tf.log(-tf.log(
tf.random_uniform(
tf.shape(logits), minval=0, maxval=1 - eps, dtype=dtype, seed=seed) +
eps))
prob = tf.nn.softmax((log_alpha + gumbe... | 3889105f39e6f81c35e1a3ca94685b6e6d7e3f37 | 3,657,197 |
def divide(num1, num2=1):
"""
除法
:param num1: int
:param num2: int
:return: float
"""
# 增加判断操作，抛出自定义异常
if num2 == 0:
raise InvalidOpreation()
val = num1 / num2
return val | 6bcc9631ebba74a15f16f8da0a9dc7f76e372725 | 3,657,198 |
def convert2int(image):
""" Transfrom from float tensor ([-1.,1.]) to int image ([-1024,6500])
"""
return tf.image.convert_image_dtype((image + 1) * 2036 - 1000, tf.float32) | 1697e6bb6911e936e9ff4bbb0ab37ddfc8115340 | 3,657,199 |
import time
def execution_duration(fun):
"""
Calculates the duration the function 'fun' takes to execute.
execution_duration returns a wrapper function to which you pass your arguments.
Example: execution_duration(my_function)(my_first_param, my_second_param)
The result of the wrapper function w... | b824ce8e1448a65bd932ec8344b1976d2a86dd09 | 3,657,201 |
def return_origin_and_destination():
"""Return origin and destination from session's waypoints key."""
waypoints = session['waypoints']
if len(waypoints) <= 1:
return 'Please enter at least 2 destinations for your trip.'
else:
origin = session['waypoints'][0]
destination = sess... | db8764fc32fe1367f303fa44b9c5c0c113a8c9ee | 3,657,202 |
def attempt_move(piece):
"""
Attempts to make a move if the target coordinate is a legal move.
Returns:
True if the move is made, False otherwise
"""
x, y = pygame.mouse.get_pos()
x = x // 100
y = y // 100
if (piece is not None) and (x, y) in piece.legal_moves:
piece.move... | 36c2b7764f6bb13765cf2eed7270f90f1cb338d1 | 3,657,203 |
def give(user_id, text, group):
"""construct a message to be sent that mentions a user,
which is surprisingly complicated with GroupMe"""
nickname = group.members().filter(user_id=user_id).first.nickname
mention = attachments.Mentions([user_id], [[0, len(nickname)+1]]).as_dict()
message = '@{}... | f9d36042b3ab5a2681fe065ac935321d8d398085 | 3,657,204 |
def make_annotation_loader_factory():
"""Generate a factory function for constructing annotation loaders.
Invoke the returned factory function by passing the name of the annotation
loader class you want to construct, followed by the parameters for the
constructor as named arguments
(e.g., factory('... | 70e6d9834a903a614a41510b6d97b62c3d1d5b3f | 3,657,206 |
def test_arma():
"""arma, check that rho is correct (appendix 10.A )and reproduce figure 10.2"""
a,b, rho = arma_estimate(marple_data, 20, 20, 40)
psd = arma2psd(A=a,B=b, rho=rho, NFFT=None)
psd = arma2psd(A=a,B=b, rho=rho)
try:
psd = arma2psd(A=None, B=None, rho=rho)
assert False
... | b1db09017fe060746ae1b503315bfaa6f3a44a58 | 3,657,207 |
from typing import Union
def chunks_lists_to_tuples(level: Union[list, int, float]) -> Union[tuple, int, float]:
"""Convert a recursive list of lists of ints into a tuple of tuples of ints. This is
a helper function needed because MongoDB automatically converts tuples to lists, but
the dask constructor wa... | 49cc7923211d50fdf6a386016af12b80a2f821df | 3,657,208 |
def oid_pattern_specificity(pattern):
# type: (str) -> Tuple[int, Tuple[int, ...]]
"""Return a measure of the specificity of an OID pattern.
Suitable for use as a key function when sorting OID patterns.
"""
wildcard_key = -1 # Must be less than all digits, so that e.G. '1.*' is less specific than ... | 7d1b4304791076fca42add7a8b9aeb31f85359f9 | 3,657,209 |
def extract_entities(text, json_={}):
"""
Extract entities from a given text using metamap and
generate a json, preserving infro regarding the sentence
of each entity that was found. For the time being, we preserve
both concepts and the entities related to them
Input:
- text: str,
... | 15f8b88e430c451a517f11b661aa1c57a93288fe | 3,657,210 |
def gaul_as_df(gaul_path):
"""
Load the Gaussian list output by PyBDSF as a pd.DataFrame
Args:
gaul_path (`str`): Path to Gaussian list (.gaul file)
"""
gaul_df = pd.read_csv(
gaul_path, skiprows=6, names=GAUL_COLUMNS, delim_whitespace=True,
)
return gaul_df | 806f8c386344c5380109705b053b89a82db62e66 | 3,657,211 |
def normalize_matrix(mat, dim=3, p=2):
"""Normalize matrix.
Args:
mat: matrix
dim: dimension
p: p value for norm
Returns: normalized matrix
"""
mat_divided = F.normalize(mat, p=p, dim=dim)
return mat_divided | 35ac155a51818d2b93fc12a0c91ce35c0dfd9fe2 | 3,657,212 |
from typing import List
import math
def species_to_parameters(species_ids: List[str],
sbml_model: 'libsbml.Model') -> List[str]:
"""
Turn a SBML species into parameters and replace species references
inside the model instance.
:param species_ids:
List of SBML species... | a7cb9df992bad98584124320bc485aa978495050 | 3,657,213 |
import warnings
def gaussian_filter_cv(array: np.ndarray, sigma) -> np.ndarray:
"""
Apply a Gaussian filter to a raster that may contain NaNs, using OpenCV's implementation.
Arguments are for now hard-coded to be identical to scipy.
N.B: kernel_size is set automatically based on sigma
:param arr... | f39223111ff6624756491b37c32b7162ae8f3e5c | 3,657,214 |
import inspect
import functools
def refresh_cache(f):
"""Decorator to update the instance_info_cache
Requires context and instance as function args
"""
argspec = inspect.getargspec(f)
@functools.wraps(f)
def wrapper(self, context, *args, **kwargs):
res = f(self, context, *args, **kwa... | 6ca9449f1ae222052f89da9a8baa611b42b47fe4 | 3,657,215 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.