content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
import itertools
def decaying(start, decay):
"""Return an iterator of exponentially decaying values.
The first value is ``start``. Every further value is obtained by multiplying
the last one by a factor of ``decay``.
Examples
--------
>>> from climin.schedule import decaying
>>> s = dec... | ee88365b3a8e768952fc66d02047b60e3e1a34c1 | 3,613,133 |
from pytz import timezone
from datetime import datetime
def chime_local_datetime(*args):
"""Create a :class:`datetime.datetime` object in Canada/Pacific timezone.
Parameters
----------
*args
Any valid arguments to the constructor of :class:`datetime.datetime`
except *tzinfo*. Local da... | 70c0f8bbe53051514ae48e554924e73c5d2f6327 | 3,613,134 |
def build_calling_regions(contigs, regions_to_include, regions_to_exclude):
"""Builds a RangeSet containing the regions we should call variants in.
This function intersects the Ranges spanning all of the contigs with those
from regions_to_include, if not empty, and removes all of the regions in
regions_to_excl... | 13d59aedb55c3728559d5434f366448f9df642f7 | 3,613,135 |
import inspect
def _is_bound_method(the_function: object) -> bool:
"""
Returns True if fn is a bound method, regardless of whether
fn was implemented in Python or in C.
"""
if inspect.ismethod(the_function):
return True
if inspect.isbuiltin(the_function):
self = getattr(the_fun... | a0d3121c6c4e1c26b2000af73e25a3d772ef2ad3 | 3,613,136 |
import urllib
import hmac
def _is_valid_output_hash(outputs):
"""Test if a set of outputs have valid hashes on the staging channel.
Parameters
----------
outputs : dict
A dictionary mapping each output to its md5 hash. The keys should be the
full names with the platform directory, ver... | 5c750cc9344e12d44c324a0e057d945fe0adcf97 | 3,613,137 |
def rm_clusters(name):
"""
Requires the following pillar to be set:
- ceph-salt:execution:fsid
"""
ret = {'name': name, 'changes': {}, 'comment': '', 'result': False}
fsid = __salt__['pillar.get']('ceph-salt:execution:fsid')
__salt__['ceph_salt.begin_stage']("Remove cluster {}".format(fsid... | 08d4cb05ef1d681891b525196a1fe98e05a5a5ac | 3,613,140 |
def micro_averaged_auprc(df_dict, return_df=False):
"""
Compute micro-averaged area under the precision-recall curve (AUPRC)
from a dictionary of class-wise DataFrames obtained via `evaluate`.
"""
# List all unique values of thresholds across coarse categories.
thresholds = np.unique(
np... | b6d53dc94c25d8bf1c66cfa550cacfd90ccca357 | 3,613,141 |
def d2vardx2(var, lon, lat, xdim, ydim, cyclic=True, sphere=True):
"""
calculate second center finite difference along x or longitude.
https://bitbucket.org/tmiyachi/pymet/src/8df8e3ff2f899d625939448d7e96755dfa535357/pymet/grid.py
:param var: ndarray, grid values.
:param lon: array_like, longitude
... | d7ea5abbfca0ff702b42601724d57f414ec52df7 | 3,613,142 |
import json
def get_chain() -> str:
"""
Endpoint to query all of the data to display
"""
chain_data = []
for block in blockchain.chain:
chain_data.append(block.__dict__)
return json.dumps({"length": len(chain_data), "chain": chain_data}) | 6a3e0cde6a737e8d706f632556efaafed847de5b | 3,613,143 |
def read_terrace_csv(DataDirectory,fname_prefix):
"""
This function reads in the csv file with the extension "_terrace_info.csv"
and returns it as a pandas dataframe
Args:
DataDirectory (str): the data directory
fname_prefix (str): the name of the DEM
Returns:
pandas datafr... | 7005b47553f8b9d2b6852a58efa751b65d737ba9 | 3,613,144 |
import tqdm
import torch
def eval_net(net, loader, device, n_val):
"""Evaluation without the densecrf with the dice coefficient"""
net.eval()
tot = 0
with tqdm(total=n_val, desc='Validation round', unit='img', leave=False) as pbar:
for batch in loader:
imgs = batch['image']
... | d3c9d9ce57e51d39c83c894d36817362c8980560 | 3,613,145 |
def load_image(file_path, average=True):
"""
Load data from an image.
Parameters
----------
file_path : str
Path to a file.
average : bool, optional
Average a multi-channel image if True.
Returns
-------
array_like
"""
if "\\" in file_path:
raise Val... | a879f89c9d015181ce43f627f94992796fa0a284 | 3,613,146 |
def interp(frame, idx, **args):
""" Get interpolated values at indices """
unique_idx = [i for i in idx if i not in frame.index]
aug_frame = frame.append(pd.DataFrame(index=unique_idx), sort=True)
in_frame = aug_frame.sort_index().interpolate('index', **args)
return in_frame.loc[idx, frame.columns] | 9a10c48e2998dca2128d46d9fac9f7f70f2d2874 | 3,613,147 |
def calcStateTransitionMatrix(orbit, dt, mu=0.0002959122082855911, max_iter=100, tol=1e-15):
"""
Calculate the state transition matrix for a given change in epoch. The state transition matrix
maps deviations from a state at an epoch t0 to a different epoch t1 (dt = t1 - t0).
Parameters
----------
... | 3f107a34c0ef11d755065e11766c25e22656322f | 3,613,148 |
def macro_calc(item):
"""
Calculate PPV_Macro and TPR_Macro.
:param item: PPV or TPR
:type item:dict
:return: PPV_Macro or TPR_Macro as float
"""
try:
item_sum = sum(item.values())
item_len = len(item.values())
return item_sum / item_len
except Exception:
... | ec74fe80a4f52d7676beeca1f9abd701043c77af | 3,613,149 |
def convert_from_pj_fat_food(pj_fat_food):
""" Convert the given PyJSON Fat-Food to a Natural
:param pj_fat_food: The PyJSON Fat-Food being converted
:type pj_fat_food: PJ_FatFood
:return: The resulting Natural
:rtype: Natural
"""
if not is_pj_fat_food(pj_fat_food):
raise ValueError(... | a4e6b635e9406f0bada11f131e09e12e047f299b | 3,613,150 |
def raw_to_multiindex(raw_df, name):
"""
Takes a raw dataframe (vertically oriented) and transforms it in a multiindexed one.
The indices are (date, feature).
"""
iterables = [raw_df.index, raw_df.columns]
index = pd.MultiIndex.from_product(iterables, names=[DATE_COL, FEATURE_COL])
data_df =... | 5a02c1a7faf12293a92d4f239cab69351784bf42 | 3,613,151 |
def sizeof_fmt(num, suffix='B'):
"""Size to human readable format.
From stack overflow.
"""
for unit in ['', 'Ki', 'Mi', 'Gi', 'Ti', 'Pi', 'Ei', 'Zi']:
if abs(num) < 1024.0:
return "%3.1f%s%s" % (num, unit, suffix)
num /= 1024.0
return "%.1f%s%s" % (num, 'Yi', suffix) | f4b568f35e152519a12d7a154e93fa71828d5976 | 3,613,152 |
from typing import Optional
def op_register(tag: str, selector: str, info: str, min_version: Optional[str] = None):
"""
Decorator used for registering operational-data items with the op catalog.
The class being decorated needs to be a subclass of OperationalItem.
@param tag: Tag string associated with... | d1271251789a6dfbf3fc29a9dcdeae506f6c02bc | 3,613,153 |
def macdext(candles: np.ndarray, fast_period: int = 12, fast_matype: int = 0, slow_period: int = 26,
slow_matype: int = 0, signal_period: int = 9, signal_matype: int = 0, source_type: str = "close",
sequential: bool = False) -> MACDEXT:
"""
MACDEXT - MACD with controllable MA type
:... | 9cf3db38be7f705a7a3b2c6bf48b4ac601109735 | 3,613,154 |
def user_info():
"""
个人中心
:return:
"""
user = g.user
if not user:
return credits("/")
data = {
"user_info":user.to_dict()
}
return render_template("/news/user.html", data=data) | 12b527595323d043ae2a6aef13401ca4c1dd6a20 | 3,613,155 |
def height_implied_by_aspect_ratio(W, X, Y):
"""
Utility function for calculating height (in pixels)
which is implied by a width, x-range, and y-range.
Simple ratios are used to maintain aspect ratio.
Parameters
----------
W: int
width in pixel
X: tuple(xmin, xmax)
x-range i... | 8c3225a27f0284acb708434238d4861bb49b0899 | 3,613,156 |
def convert_to_valid(seq, correction_dictionary=None, alignment=False):
"""
Function that converts non-standard amino acid residues to standard ones.
Specifically:
B -> N
U -> C
X -> G
Z -> Q
' ' -> <empty string> (i.e. an empty space)
* -> <empty string>
- -> <empty string> (ON... | 1fe1f934a6c4ba92be988bb310600aee3356b95c | 3,613,157 |
def CTPixel8_getPixelName():
"""CTPixel8_getPixelName() -> char const *"""
return _VPLPython.CTPixel8_getPixelName() | 01cb3ae9fe00370806f42c15373dca5f856219c1 | 3,613,158 |
from datetime import datetime
def create_access_token(identity: str) -> bytes:
"""Create a jwt based on identity."""
payload = {
"identity": identity,
"exp": datetime.utcnow() + timedelta(seconds=JWT_EXP_DELTA_SECONDS),
}
jwt_token = jwt.encode(payload, JWT_SECRET, JWT_ALGORITHM) # ty... | bb257506df76d004466be210bd374a9363b54909 | 3,613,160 |
import site
def apply_vs30_mod_non_parametric(
im_values: pd.DataFrame, site_info: site.SiteInfo, im: IM
) -> pd.Series:
"""Applies the user vs30 modification for non-parametric data"""
assert "PGA" in im_values.columns
pga = im_values["PGA"].copy()
return im_values[str(im)] * __get_site_amp_rati... | c8006ce81dff810f2505af7f30225b4ad713d175 | 3,613,161 |
def calc_earfcn(low_freq_hz: int, high_freq_hz: int) -> int:
"""
Calculate EARFCN in mhz for CBRS
Args:
low_freq_hz: int, Low frequency limit taken from available channel
high_freq_hz: int, High frequency limit taken from available channel
Returns:
EARFCN in mhz
"""
mid... | f757f94d65af96289fd5fe360fceb7a055788c44 | 3,613,162 |
def sortino_ratio(returns, required_return=0, period=DAILY):
"""
Determines the Sortino ratio of a strategy.
Parameters
----------
returns : pd.Series or pd.DataFrame
Daily returns of the strategy, noncumulative.
- See full explanation in tears.create_full_tear_sheet.
returns_s... | fffc6552f23f676d9a460e23383300dbc897218a | 3,613,163 |
def confusion_matrix(
prediction_detections: ndarray,
truth_detections: ndarray,
threshold: float = DEFAULT_NEG_THRESHOLD,
num_foreground_classes: int = 3,
) -> np.ndarray:
""" Compute confusion matrix to evaluate the accuracy of a classification.
By definition a confusion matrix :math:`C` is s... | 2c12478668e5ea421e98b9dfaaf75638d8c35bb7 | 3,613,164 |
def subsol_vector(str1, str2, in11, str3, str4):
"""subsol_vector(ConstSpiceChar * str1, ConstSpiceChar * str2, ConstSpiceDouble * in11, ConstSpiceChar * str3, ConstSpiceChar * str4)"""
return _cspyce0.subsol_vector(str1, str2, in11, str3, str4) | 30b59f04243c9b299848408a66eb05eb2f45305f | 3,613,165 |
def compute_per_char(ground_truth, predictions):
"""
compute per char accuracy
:param ground_truth:
:param predictions:
:return:
"""
accuracy = []
for index, label in enumerate(ground_truth):
prediction = predictions[index]
total_count = len(label)
correct_count =... | dc33b3cf7890755d9c9ef5901b4201e572323a4a | 3,613,166 |
def getBinaryFormat(name: str) -> type[BinaryFormat]:
"""
Looks up a binary format by its name attribute.
Returns the binary format with the given value for its name attribute.
Raises KeyError if there is no match.
"""
return _formatsByName[name] | 41461d9426bac31b934490aacf7b9c1b2d0ba2c4 | 3,613,167 |
import scipy
import time
import numpy
import multiprocessing
def cholesky_method(
A,
B=None,
gram=False,
exponent=1,
invert_cholesky=True,
cholmod=None):
"""
Computes trace of inverse of matrix using Cholesky factorization by
.. math::
\\mathrm{tra... | a502e29684e0f348b44e6a4897a0904aea503224 | 3,613,168 |
def extractNextlevelforthePLOT(item):
"""
'Next level for the PLOT'
"""
vol, chp, frag, postfix = extractVolChapterFragmentPostfix(item['title'])
if not (chp is not None or vol is not None or frag is not None) or 'preview' in item['title'].lower():
return None
if 'scan-trad' in item['tags']:
return None
... | 983a0c1a9605922d15ee47be934cdd82bce58517 | 3,613,169 |
def kitti_squeezeSeg16_config():
"""Specify the parameters to tune below."""
mc = base_model_config('KITTI')
mc.CLASSES = ['unknown', 'car', 'pedestrian', 'cyclist']
mc.NUM_CLASS = len(mc.CLASSES)
mc.CLS_2_ID = dict(zip(mc.CLASSES, range(len(mc.CLASSES))))
mc... | 7ed52b9b20f5f1cc04220df137470fd0050fe2a0 | 3,613,170 |
def filter_modules(command_loader, help_file_entries, modules=None, include_whl_extensions=False):
""" Modify the command table and help entries to only include certain modules/extensions.
: param command_loader: The CLICommandsLoader containing the command table to filter.
: help_file_entries: The dict of... | 2f0ec2164a67abc9c691e66a0470977a06d51b97 | 3,613,171 |
from texar.agents.agent_utils import Space
def convert_gym_space(spc):
"""Converts a :gym:`gym.Space <#spaces>` instance to a
:class:`~texar.agents.Space` instance.
Args:
spc: An instance of `gym.Space` or
:class:`~texar.agents.Space`.
"""
if isinstance(spc, Space):
re... | d9362e00a95a76a60d9aaf6b6935dc9ec5bb92d6 | 3,613,173 |
from typing import List
def save_inventory(
session: SessionABC, inventory: List[InventoryType], merge_samples: bool = False
) -> List[InventoryType]:
"""Saves a list of inventory items to the server.
:param session: the AqSession instance
:param inventory: list of inventory items
:param merge_sa... | d01956ba2334a3ab824845a4db3261fbdec25a94 | 3,613,174 |
def positional_encoding(max_position, d_model):
"""Return the tensor encoding the position of elements in a sequence
Compute the positional encoding with a combination of sinusoidal functions
as suggested in (Vaswani at al., "Attention is all you need", 2017)
Note:
When we add the positional e... | 7ecc8ba093ab9be744ba945975fdb57570fc09be | 3,613,175 |
import re
def get_namespace(element):
"""Extract the namespace using a regular expression."""
match = re.match(r"\{.*\}", element.tag)
return match.group(0) if match else "" | 9380e104d05ae6b56463b96bf87d9c0fcd8202cf | 3,613,176 |
import numpy
def create_LOFAR_configuration(antfile: str, meta: dict = None,
params={}):
""" Define from the LOFAR configuration file
:param antfile:
:type str:
:param name:
:type str:
:param meta:
:type dict:
:param params: Dictionary containing paramet... | affed3d6e7c7fa24d434fb51af5f15648a7e202e | 3,613,178 |
import random
def get_fittest_solution(solutions):
"""Return the fittest of the passed solutions, using tie-breaking criteria if there are ties and only using random tie-breaking as a last resort"""
# ensure that there are solutions
if not solutions:
return None
# a single solution is the ... | 9bdf8274e9f8be491da2de14b76114e95c4f0584 | 3,613,179 |
import itertools
def sphere_plane(map, mapi) -> plt.Figure:
"""
Plots map from (3d) sphere to (2d) plane and its inverse.
:param map: Map from sphere to plane.
:param mapi: Map from plane to sphere.
:return: Figure.
"""
# Init plot object:
fig = plt.figure()
ax = np.array([[fig.ad... | a07d747fd0e1a12629591a3fdd8db2a71b6ba8e2 | 3,613,181 |
import json
import hashlib
def hash_config(configuration: dict) -> str:
"""Computes a SHA256 hash from a dictionnary.
Args:
configuration (dict): The configuration to hash
Returns:
str: _description_
"""
stringified = json.dumps(configuration, sort_keys=True)
return hashlib.s... | ccf30915fc736ce4724eb0ceceab59220e94efd0 | 3,613,182 |
def get_bag_of_communities(network, partition):
"""
:param network: dictionary containing for each key (each node/page) a dictionary containing the page categories.
:param partition: list of the community assignment
:return: list of dictionaries, one dictionary per community. Each dictionary contains th... | 615e88393b30b1989d98eeea1ac7123588a51ea9 | 3,613,183 |
import asyncio
def connect( stream_generator, user=None, database=None, password=None, loop=None, **kwargs):
"""Creates a connection to a PostgreSQL database.
This function is part of the `DBAPI 2.0 specification
<http://www.python.org/dev/peps/pep-0249/>`_; however, the arguments of the
function are... | 954e5a0b3bdb2718910f6f50df7064966fdc806f | 3,613,184 |
def add_neighbor_count_features(edge_df, X_df, structures_df):
"""
edge_df must be symmetric.
"""
cnt_df = edge_df.groupby(
['molecule_name', 'atom_index_0']).size().to_frame('EF_neighbor_count')
cnt_df.reset_index(inplace=True)
cnt_df.rename({'atom_index_0': 'atom_index_zero'}, inplace=... | 688e04893035f1340c7a14a0173f7059604665cb | 3,613,185 |
def _to_pascal_case(value: str) -> str:
"""Converts a snake_case string into a PascalCase one."""
value = value.replace("-", "_")
if value.find("_") == -1:
return value[0].upper() + value[1:]
return "".join([v.capitalize() for v in value.split("_")]) | d41985f1d182b723c9861473e4f9eca8c7a7977e | 3,613,186 |
import yaml
def load(modelSpecFilename):
"""
Need the following items in the model spec file:
costFn
decisionFn
stages
specs
:param modelSpecFilename:
:return:
"""
with open(modelSpecFilename) as f:
modelDict = yaml.load(f)
for stageDict in modelDict['specs']:
... | 5033aec67b5f0a19651cdffe96b5ce5e704aa816 | 3,613,187 |
from typing import Any
from typing import Union
from typing import Set
import re
def _replace_prefixed(text: Any, prefix: Union[str, Set[str]], value: str) -> Any:
"""
Replace all substrings starting with the prefix(es) with the value.
"""
if pd.isna(text):
return text
text = str(text)
... | cc034958d2e175e93ef9fdb252e7e0e66e2442f2 | 3,613,188 |
def perma(mat,m):
"""
Permanent of the matrix
"""
if not mat.isSquare:
return None
if mat.isIdentity:
return 1
if mat.dim[0]==2:
return m[0][0]*m[1][1] + m[1][0]*m[0][1]
if mat.dim[0]==3:
return (m[0][0]*m[1][1]*m[2][2] +
m[0][1... | 71e2408c79e09b4fa5eb328130d2b5b7e7efdf41 | 3,613,189 |
def realtime_to_gametime(secs=0, mins=0, hrs=0, days=1, weeks=1, months=1, yrs=0, format=False):
"""
This method calculates how much in-game time a real-world time
interval would correspond to. This is usually a lot less
interesting than the other way around.
Keyword Args:
times (int): The ... | 3fa4c85f4f5a71357c64d4aab53248b348736a10 | 3,613,190 |
def char_class_abbrev(cc_abbrev: str, **config):
"""
Constructs a char_class spec
:param cc_abbrev: alternative type abbreviation i.e. ascii, cc-ascii, visible, cc-visible
:param config: in **kwargs format
:return: the char_class spec
"""
spec = {
"type": 'char_class_abbrev'
} ... | da14e16657cf5666bde881c0a27d995327878ecb | 3,613,191 |
def trial_division(n):
"""Return a list of the prime factors for a natural number."""
if n < 2:
return []
prime_factors_list = []
temp = primeGenerate(int(n**0.5) + 1)
for p in temp:
if p*p > n:
break
while n % p == 0:
prime_factors_list.append(p)
... | 1c5dc9beb3ca237e2a7f663cb7e864bfb42c3141 | 3,613,193 |
def occlusion(net: Module, input_image: Tensor, n_top_classes: int = 3) -> Tensor:
"""Creates a attribution heatmap by occluding parts of the input image.
Args:
net: the network to visualize attribution for
input_image: image tensor of dimensions (c, h, w) or (1, c, h, w)
n_top_classes:... | e40c1ecf7293fe5b0d51de999b5f4cad3d3d2dd1 | 3,613,194 |
def log_pos(x):
"""Computes log with the assumption that x values are positive.
"""
return jnp.log(jnp.maximum(x, jnp.finfo(float).eps)) | f963ed2a38b9d81ed05e698da66a0c4e3c96a47e | 3,613,195 |
from typing import List
import json
def import_tree_to_json_str(imports=List[Import]) -> str:
"""
Print the imported modules tree in json format.
"""
exclude_root = imports[0]["nested_imports"]
return json.dumps(exclude_root, indent=2) | 8796c1099fb39d8cac72a50e83da23ca25e1f821 | 3,613,197 |
from typing import Tuple
def place_targets_with_goal_distance_ratio(
object_bounding_boxes: np.ndarray,
table_dimensions: Tuple[np.ndarray, np.ndarray, float],
placement_area: PlacementArea,
object_placements: np.ndarray,
goal_distance_ratio: float,
goal_distance_min: float,
max_placement_... | 26962960db0d6a4c4681890d553cafe0d78150f7 | 3,613,198 |
import torch
import tqdm
def predict(model, test_batch_generator, num_batches, device, label_map, class_weight):
"""
Main evaluation routine
"""
epoch_loss = 0
epoch_acc = 0
epoch_results = {}
epoch_results_by_tag = {}
epoch_CR = ""
output_t_pred = None
model.eval()
with ... | 0ec7d472a4cc2b17ecd5e6a033243300e1184f60 | 3,613,199 |
def using_cumisc(handle=None):
"""Temporarily set chainer's CUBLAS handle to scikit-cuda.
The usage is similar to :func:`using_device`.
Args:
handle: CUBLAS handle. If ``None`` is specified, it uses CUBLAS handle
for the current device.
Returns:
CumiscUser: Misc user objec... | 8cb4bd00f63e8a856ea315eec9452b17f6ece08d | 3,613,201 |
def remove_list_duplicates(my_list: list) -> list:
""" Removes any duplicated values from a list. """
return list(dict.fromkeys(my_list)) | e3dd86733117fce7bad2860d860b98b349efcfb5 | 3,613,202 |
from typing import Union
from typing import Iterable
def sql_from_binary_tree(X: Union[list, np.ndarray],
children_left: Union[list, np.ndarray],
children_right: Union[list, np.ndarray],
feature: Union[list, np.ndarray],
... | 177b6172846a8187fd398b2d098c46f522633eec | 3,613,203 |
from typing import Callable
import click
def target_id_option(command: Callable[..., None]) -> Callable[..., None]:
"""
An option decorator for choosing a target ID.
"""
click_option_function: Callable[
[Callable[..., None]],
Callable[..., None],
] = click.option(
'--target... | 1fe67f22e00b4d4930af347c482d28e30032508d | 3,613,204 |
def tdnsresp(**kwargs) -> dns.Message:
"""
Returns:
mitmproxy.dns.Message
"""
default = dict(
timestamp=946681201,
id=42,
query=False,
op_code=dns.op_codes.QUERY,
authoritative_answer=False,
truncation=False,
recursion_desired=True,
... | ae4f0080b37fc7fd9f2efa6ec1daf85e990c130b | 3,613,205 |
def __fetch_query_from_uuid(uuid: str) -> bigquery.BigQueryResult:
""" Fetches a cached BigQuery result from its UUID.
Args:
uuid (str): The UUID of the query to be retrieved.
Returns:
(BigQueryResult): The corresponding BigQuery result object.
"""
# Fetch cached qu... | c7f0c5bb1ac94dea6c251a8ecf0c52cdad1fd6c7 | 3,613,207 |
def _get_keys(response):
"""
return lists of strings that are the keys from a client.list_objects() response
"""
keys = []
if 'Contents' in response:
objects_list = response['Contents']
keys = [obj['Key'] for obj in objects_list]
return keys | dfa1f066ac19138920509935b1dbbdde52591f18 | 3,613,208 |
def round_updown_to_x(num_in, x, direction="up"):
"""
Rounds a given value (num_in) to the nearest multiple of x, in a given
direction (up or down)
:param num_in: Input value
:param x: Value to round to a multiple of
:param direction: Round up or down. Default: 'up'
:return: Rounded number
... | 206b582843eea234b5b655dddd54eea6e32eec42 | 3,613,209 |
async def player_stop():
"""
Full route: /music/player/resume
Request (JSON): None
Stop (unload) the current song.
"""
# no json expected
was_playing = await player.player_stop()
if was_playing:
return with_status(None, 200, StatusType.OK)
else:
return with_status... | 320c71a1ca669b6a2b386f8b3ab500b78a1b70b4 | 3,613,210 |
async def revocation_registries_created(request: web.BaseRequest):
"""
Request handler to get revocation registries that current agent created.
Args:
request: aiohttp request object
Returns:
List of identifiers of matching revocation registries.
"""
context = request.app["requ... | 0adc59382ffc991fb7d5c7e191aa960b0db2d516 | 3,613,211 |
def vwap(bars):
"""
calculate vwap of entire time series
(input can be pandas series or numpy array)
bars are usually mid [ (h+l)/2 ] or typical [ (h+l+c)/3 ]
"""
typical = ((bars['high'] + bars['low'] + bars['close']) / 3).values
volume = bars['volume'].values
return pd.Series(index=ba... | 06d6554b301c229f8679f5a987f651ac09956b4e | 3,613,212 |
import jqmobile
from xml.dom import minidom
import re
def get_svn_revision(path=None):
"""
Returns the SVN revision in the form SVN-XXXX,
where XXXX is the revision number.
Returns SVN-unknown if anything goes wrong, such as an unexpected
format of internal SVN files.
If path is provided, it... | 20db6d1b3e4d9190d736ac43b93626eacb652a6d | 3,613,213 |
def checkFrameRateChange_Lenient(op, graph, frm, to):
"""
Confirm frame rate has not changed.
:param op:
:param graph:
:param frm:
:param to:
:return:
"""
if _checkFrameRateChange(op, graph, frm, to):
return (Severity.WARNING, 'Frame Rate Changed between nodes') | f8e5a32906e2b1d231b20796ea8fb3481b6ee6d1 | 3,613,214 |
def img2port(img_url):
"""
mimvp.com的端口号用图片来显示, 本函数将图片url转为端口, 目前的临时性方法并不准确
"""
code = img_url.split("=")[-1]
if code.find("AO0OO0O")>0:
return 80
else:
return None | 60768ee0723808ef7d1f3e74287b7a6e576f94c5 | 3,613,215 |
def coverage(tiles):
"""Sum of length of all tiles.
"""
accu = 0
for tile in tiles:
accu = accu + tile[2]
return accu | b2cbb6b926e070d9fc457523bb60169ef9b70821 | 3,613,216 |
import pytz
from datetime import datetime
async def stations(id: int, date_from: str = None, date_to: str = None, param: str = 'pm25'):
"""
Get pollution data for a specific station and a date range
:return: json of format {"data": [{date, time, value}, ...]
"""
if not date_from or not date_to:
... | 4971e81dc696c32f072f38b2da40f7a2a710bc7e | 3,613,217 |
def update(head: str, td: Tag) -> Attr:
"""
Update a developing part dictionary based on a cell from the product table
:param head: The head string from the <th>
:param td: The <td> from the product table
:return The applicable CSS class, and the dictionary with kvs to update.
"""
cl... | 7f3ba66b1158f08f9e2f7f13afd7908a1c0ba6a9 | 3,613,218 |
import errno
def load_doc(name, doctype = None, project = None):
"""Load document
Args:
name: Name of document (file must exist in :/username/project/docs.zip: file).
doctype: Type of document. 'pdf', 'docx', etc.
project: reference to ArthurProject object.
Returns:
list:... | 31245e378be54c8933dfe1e38644c32f22bce110 | 3,613,219 |
def lognormalize_chroma(C):
"""Log-normalizes chroma such that each vector is between -80 to 0."""
C += np.abs(C.min()) + 0.1
C = C / C.max(axis=0)
C = 80 * np.log10(C) # Normalize from -80 to 0
return C | 977f8fac9b16bfd32c331d6ee713864a61f930d0 | 3,613,220 |
def kei_zeros(nt):
"""Compute nt zeros of the Kelvin function kei x
"""
if not isscalar(nt) or (floor(nt) != nt) or (nt <= 0):
raise ValueError("nt must be positive integer scalar.")
return specfun.klvnzo(nt,4) | 0a92514543ee9ff0bacdd18a1eb9136be366f6f6 | 3,613,221 |
def _reflect_particle_diffusive(arr, **kwargs):
""" Reflect particles given in a diffusive manner.
Args:
arr (np.ndarray): 2D-ndarray of shape *number of particles x 5*. Each particle is describes by : [x, y, vx, vy, vz]
Returns:
[np.ndarray]: returns the modified array by default (in most... | 0b2fd08c2c6b367275ad139b0915432653fb164c | 3,613,222 |
def get_int() -> int:
"""
Gets a lone integer from the console (the integer is on its own line)
:return: The int value that was read in from the console
"""
line = input().strip()
return int(line) | 1bffcb1c5c1e7910a11358d4616a747b38ba3d73 | 3,613,224 |
import tqdm
def plot_tract_profiles(
X,
groups,
group_names,
group_by=None,
group_by_name=None,
bins=None,
quantiles=None,
palette="colorblind",
ci=95.0,
subplot_positions=None,
nrows=None,
ncols=None,
):
"""Plot profiles for each bundle and each metric.
Parame... | 9a174dadabc0463b7072ad451b8a03d8c0610ed9 | 3,613,225 |
def regex_search_matches_output(get_output, search):
"""
Applies a regex search func to the current output
"""
return search(get_output()) | 6f054990d3454a447656567b3ceb12a38c2809a5 | 3,613,226 |
def crop(img, start_y, start_x, h, w):
"""
Crop an image given the top left corner.
:param img: The image
:param start_y: The top left corner y coord
:param start_x: The top left corner x coord
:param h: The result height
:param w: The result width
:return: The cropped image.
"""
... | cb3a05989f1538bcec34102c33291d500a21c59d | 3,613,227 |
def validate_existing_delivery(start, end, queryset):
"""Validate if exists a deliver at that time by date"""
delivery_exist = False
msg = ""
if len(queryset):
for deliver in queryset:
deliver_start = format_date(deliver.start)
deliver_end = format_date(deliver.end)
... | 5f8a612ed84e47f73fd084d2319e3f0c2b446204 | 3,613,230 |
def separate_by_class(train):
""" For each dependent variable (last column of DF) value, map to
corresponding rows of the DF
"""
classifications = set(train[:, -1])
return {c: train[train[:, -1] == c] for c in classifications} | 1ed0fd5c077a0d7391955687ec190ded873a9bee | 3,613,231 |
def plot_profile(datasets,
fields=None,
times=None,
timerange=None,
fig=None,ax=None,
fieldlimits=None,
heightlimits=None,
fieldlabels={},
cmap=None,
stack_by_datasets... | 996d267a8bd21e24d26aad56e38e6d67fdec3997 | 3,613,232 |
def abs(v):
"""Create abs in the sense of distance instead of just vanishing the sign.
Create abs in the sense of distance instead of vanishing the sign. Used
to calculate the length of coordinates, or anything that can be interpreted
as coordinate.
Args
----
v: iterable of float, comp... | effdbb763a1b9e1f04137139eef3f94e662e3cc7 | 3,613,233 |
from pathlib import Path
def confirm_index_opts(taxonomy_name, opts):
"""Confirm expected keys are present in opts for indexing."""
file_key = "taxonomy-%s-file" % taxonomy_name
url_key = "taxonomy-%s-url" % taxonomy_name
for key in {"taxonomy-path", file_key}:
if key not in opts:
... | 904412613fabe115d368d3dfa77ac9be3f355f15 | 3,613,234 |
import json
def podcast_spider(site):
"""
更新源内容
"""
resp = get_with_retry(site.rss)
if resp is None:
logger.info(f"RSS 源可能失效了`{site.rss}")
return None
feed_obj = feedparser.parse(BytesIO(resp.content))
for entry in feed_obj.entries:
# 有些是空的
if not entry:
... | 6151350572181b0776b075af1daa80ac0559fcbf | 3,613,235 |
import xml.etree.cElementTree as ET
def getDataSetUuid(xmlfile):
"""
Quickly retrieve the uuid from the root element of a dataset XML file,
using a streaming parser to avoid loading the entire dataset into memory.
Returns None if the parsing fails.
"""
try:
for event, element in ET.ite... | 7386efea461056f8f4b472923b8f4a30d6d80d3b | 3,613,236 |
def train_mnist_single_machine(data_dir, num_epochs, use_fake_data=False):
"""Train a ConvNet on MNIST.
Args:
data_dir: string. Directory to read MNIST examples from.
num_epochs: int. Number of passes to make over the training set.
use_fake_data: bool. If True, generate a synthetic dataset.
Returns:... | ab4485e898d54122730b9cc82f9d8a7cd2c04140 | 3,613,237 |
def pick_word(probabilities, int_to_vocab):
"""
Pick the next word with some randomness
:param probabilities: Probabilites of the next word
:param int_to_vocab: Dictionary of word ids as the keys and words as the values
:return: String of the predicted word
"""
return np.random.choice(list(int_to_vocab.values())... | 84c9c46133d799313a490c7cc7a03b2dcb776415 | 3,613,238 |
def get_max_cost_matrix(a, bottom_right=True, top_left=False):
"""Return matrix with maximum cost for paths from all nodes"""
maxcost = 9 * a.shape[0] * a.shape[1]
cost = np.zeros(a.shape, int) + maxcost
if bottom_right:
cost[-1, -1] = 0
if top_left:
cost[0, 0] = 0
return cost | 156ef55507558d7b194d51f8dd6533bb6b34925e | 3,613,239 |
def get_synthetic_data(data_size: int, features_num: int) -> (Matrix, ColumnVector):
"""
A method which creates a random matrix of ``size data_size x features_num`` and a ``random 1 x data_size``
random vector.
Args:
data_size(int): The number of samples in the data - ``n``.
features_nu... | bddea3bff042d219f8b9992fa17aecadcbe41e0a | 3,613,240 |
from typing import Union
def injection_volume(val: Union[float, str]) -> Union[int, str]:
"""
Handle special case for injection volume of ``-1``, which indicates "As Method".
:param val:
:type val:
:return:
:rtype:
"""
if val in {-1, "-1"}:
return "As Method"
else:
return int(val) | b09240b9c8bd0eebfb7880494f75b105e313b228 | 3,613,241 |
from typing import Optional
def validate_charge_efficiency(charge_efficiency: Optional[float]) -> Optional[float]:
"""
Validates the charge efficiency of an object.
Charge efficiency is always optional.
:param charge_efficiency: The charge efficiency of the object.
:return: The validated charge e... | 46e40fcdc65ffec453f1bac9bd03f6a9297647fd | 3,613,242 |
def get_module_info(*args):
"""
get_module_info(ea, modinfo) -> bool
"""
return _ida_dbg.get_module_info(*args) | 3d93e2552418968fb9ad2f7343e7f826f00fbe7a | 3,613,243 |
def set_graph_attributes(species):
"""
For a molecular species set the π bonds and stereocentres in the molecular
graph.
Arguments:
species (autode.species.Species):
"""
logger.info('Setting the π bonds in a species')
def is_idx_pi_atom(idx):
return is_pi_atom(atom_label=sp... | 1513a26fb657b6b318511156271eb7ad86eda8e5 | 3,613,245 |
def yices_check_context_with_model(ctx, params, mdl, n, t):
"""Check satisfiability modulo a model.
Check whether the assertions stored in ctx conjoined with a model are satisfiable.
- ctx must be a context initialized with support for MCSAT
(see yices_new_context, yices_new_config, yices_set_c... | 50b7204122de1d1eb295a1d04b9a3b1dd5e2b738 | 3,613,246 |
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