content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def append_unique(func):
"""
This decorator will append each result - regardless of type - into a
list.
"""
def inner(*args, **kwargs):
return list(
set(
_results(
args[0],
func.__name__,
*args,
... | ed656c500f95b03e8036605e9af5cc739830ff7b | 3,657,687 |
def _get_unique_figs(tree):
"""
Extract duplicate figures from the tree
"""
return _find_unique_figures_wrap(list(map(_get_fig_values(tree),
tree)), []) | ba8a40766981bca9ca23fd3ec681f1a8d52ad85b | 3,657,688 |
def read_fssp(fssp_handle):
"""Process a FSSP file and creates the classes containing its parts.
Returns:
:header: Contains the file header and its properties.
:sum_dict: Contains the summary section.
:align_dict: Contains the alignments.
"""
header = FSSPHeader()
sum_dict ... | 4ac2c61ed40f14102d0ae1a8a3b6fa8e69252f27 | 3,657,689 |
import json
def LoadJSON(json_string):
"""Loads json object from string, or None.
Args:
json_string: A string to get object from.
Returns:
JSON object if the string represents a JSON object, None otherwise.
"""
try:
data = json.loads(json_string)
except ValueError:
data = None
return ... | 598c9b4d5e358a7a4672b25541c9db7743fcd587 | 3,657,690 |
import inspect
import re
def _dimensions_matrix(channels, n_cols=None, top_left_attribute=None):
"""
time,x0 y0,x0 x1,x0 y1,x0
x0,y0 time,y0 x1,y0 y1,y0
x0,x1 y0,x1 time,x1 y1,x1
x0,y1 y0,y1 x1,y1 time,y1
"""
# Generate the dimensions matrix from the docstring.
ds = i... | 2c119c74e7e37827d6813437d9e0d8bbd97cbbc7 | 3,657,691 |
def is_monotonic_increasing(x):
"""
Helper function to determine if a list is monotonically increasing.
"""
dx = np.diff(x)
return np.all(dx >= 0) | 6d0afe3a6a70d57ec4ae09e20164c34c0739855f | 3,657,692 |
import copy
def cluster_size_threshold(data, thresh=None, min_size=20, save=False):
""" Removes clusters smaller than a prespecified number in a stat-file.
Parameters
----------
data : numpy-array or str
3D Numpy-array with statistic-value or a string to a path pointing to
a nifti-fil... | 3b946a639e2dae1c47fb78ad30dded32b0dd5f06 | 3,657,693 |
def convert_df(df):
"""Makes a Pandas DataFrame more memory-efficient through intelligent use of Pandas data types:
specifically, by storing columns with repetitive Python strings not with the object dtype for unique values
(entirely stored in memory) but as categoricals, which are represented by repeated... | 7f6f2c20762963dceb0f52d36b7b724c5a89d8d4 | 3,657,694 |
def run_add(request):
"""Add a run."""
if request.method == "POST":
form = forms.AddRunForm(request.POST, user=request.user)
run = form.save_if_valid()
if run is not None:
messages.success(
request, u"Run '{0}' added.".format(
run.name)
... | c1eca5702e93e3a0751b2b22de18aa1aa4c88db7 | 3,657,695 |
def map_aemo_facility_status(facility_status: str) -> str:
"""
Maps an AEMO facility status to an Opennem facility status
"""
unit_status = facility_status.lower().strip()
if unit_status.startswith("in service"):
return "operating"
if unit_status.startswith("in commissioning"):
... | 43e1d5e5ea984d36260604cf25f4c7b90d5e56f1 | 3,657,696 |
def demand_monthly_ba(tfr_dfs):
"""A stub transform function."""
return tfr_dfs | 74bbb3d732b64a30f0529f76deedd646cc7d4171 | 3,657,697 |
def render_page(page, title="My Page", context=None):
"""
A simple helper to render the md_page.html template with [context] vars, and
the additional contents of `page/[page].md` in the `md_page` variable.
It automagically adds the global template vars defined above, too.
It returns a string, usuall... | fd2e427f096324b2e9a17587f498626a2ebfb47e | 3,657,698 |
def _SortableApprovalStatusValues(art, fd_list):
"""Return a list of approval statuses relevant to one UI table column."""
sortable_value_list = []
for fd in fd_list:
for av in art.approval_values:
if av.approval_id == fd.field_id:
# Order approval statuses by life cycle.
# NOT_SET == 8 ... | 15ce3c6191495957674ab38c2f990d34f10ecdf6 | 3,657,699 |
import re
from typing import Sequence
def resolve_pointer(document, pointer: str):
"""
Resolve a JSON pointer ``pointer`` within the referenced ``document``.
:param document: the referent document
:param str pointer: a json pointer URI fragment to resolve within it
"""
root = document
# D... | c37323b19547f4cb8e20eb8c391d606e77c68b66 | 3,657,700 |
def load_config_file(config_file):
""" Loads the given file into a list of lines
:param config_file: file name of the config file
:type config_file: str
:return: config file as a list (one item per line) as returned by open().readlines()
"""
with open(config_file, 'r') as f:
config_doc... | 6a6e0199566e9ea27db309b2164f323cd5f57fdc | 3,657,701 |
def retrieve_analysis_report(accession, fields=None, file=None):
"""Retrieve analysis report from ENA
:param accession: accession id
:param fields: comma-separated list of fields to have in the report (accessible with get_returnable_fields with result=analysis)
:param file: filepath to save the content... | 4adde7fea75c26f809d5efc1b5ff04b31ff9fa87 | 3,657,702 |
import copy
def visualize_cluster_entropy(
doc2vec, eval_kmeans, om_df, data_cols, ks, cmap_name="brg"
):
"""Visualize entropy of embedding space parition. Currently only supports doc2vec embedding.
Parameters
----------
doc2vec : Doc2Vec model instance
Instance of gensim.models.doc2vec.... | 5e91167fa23c09ada2f81d5e388e5d95a84fe283 | 3,657,704 |
def delete_student_meal_plan(
person_id: str = None,
academic_term_id: str = None):
"""
Removes a meal plan from a student.
:param person_id: The numeric ID of the person.
:param academic_term_id: The numeric ID of the academic term you're interested in.
:returns: String containing ... | 75cd875b751b5af0ccbf71c090712f73b866f29b | 3,657,705 |
import torch
def colorize(x):
"""Converts a one-channel grayscale image to a color heatmap image. """
if x.dim() == 2:
torch.unsqueeze(x, 0, out=x)
return
if x.dim() == 3:
cl = torch.zeros([3, x.size(1), x.size(2)])
cl[0] = gauss(x, .5, .6, .2) + gauss(x, 1, .8, .3)
... | 0b5c95bc296fcdc3ed352d656984a3f46fa66fad | 3,657,706 |
from typing import Counter
def local_role_density(
annotated_hypergraph, include_focus=False, absolute_values=False, as_array=False
):
"""
Calculates the density of each role within a 1-step neighbourhood
of a node, for all nodes.
Input:
annotated_hypergraph [AnnotatedHypergraph]: An anno... | 75ccc0e51ad627f3bd6f2f664bfaa93fd9e532d8 | 3,657,707 |
import re
import requests
def get(url: str) -> dict:
"""
author、audioName、audios
"""
data = {}
headers = {
"Accept": "application/json, text/plain, */*",
"Accept-Encoding": "gzip, deflate",
"Accept-Language": "zh-CN,zh;q=0.9",
"Connection": "keep-alive",
"Ho... | 5dd97f4974b1fdc0a89ad36bbb14ad5c26e1582d | 3,657,708 |
import glob
def get_subject_mask(subject, run=1, rois=[1030,2030], path=DATADIR,
space=MRISPACE,
parcellation=PARCELLATION):
"""
Get subject mask by run and ROI key to apply to a dataset
(rois are in DATADIR/PARCELLATION.tsv)
inputs:
subject - sid00... | 2838c8067dff1878af2b7f874cffa3cd4fc5adf1 | 3,657,709 |
def social_auth(user):
"""
Return True if specified user has logged in with local account, False if user
uses 3rd party account for sign-in.
"""
return True if user.password is not settings.SOCIAL_AUTH_USER_PASSWORD else False | 197fccbe875de1e4ea08a28a2f7927160d9dae6e | 3,657,710 |
def update_post(post_id):
"""
The route used to update a post. It displays the create_post.html page with the original posts contents filled in,
and allows the user to change anything about the post. When the post has been successfully updated it redirects to
the post route.
"""
post = Post.que... | 2761f2fdc9ad50f96c36e8ee13f87f67275b360e | 3,657,711 |
def lrelu(x, leak=0.2, scope="lrelu"):
"""
leaky relu
if x > 0: return x
else: return leak * x
:param x: tensor
:param leak: float, leak factor alpha >= 0
:param scope: str, name of the operation
:return: tensor, leaky relu operation
"""
with tf.variable_scope(scope):
... | 25757c70ae7d37b568b16ea9d489a5d15b68042f | 3,657,712 |
from typing import Callable
from typing import Optional
def enable_async(func: Callable) -> Callable:
"""
Overview:
Empower the function with async ability.
Arguments:
- func (:obj:`Callable`): The original function.
Returns:
- runtime_handler (:obj:`Callable`): The wrap functi... | 82b44b7e3bc3b59e6d0a12aca7983f3c2b0f6468 | 3,657,713 |
from io import StringIO
def get_past_data_from_bucket_as_dataframe():
"""Read a blob"""
bucket_name = "deep_learning_model_bucket"
blob_name = "past_data.csv"
storage_client = storage.Client()
bucket = storage_client.bucket(bucket_name)
blob = bucket.blob(blob_name)
return_data = bl... | 74ca2fddbd94efc51652974cc2e62a699e92ea80 | 3,657,714 |
def align_junction_LeftRight(viral_seq, bp_pos, ri_pos, align_to="L"):
"""If align_to="L", put all the ambiguous nucleotides in the
'body' part of the junction defined by bp_pos and ri_pos,
that is the junction point is moved as close to the 5'
end (of viral_seq) as possible. If align_to="R", do the op... | 92634e4ff6ca6600fb91046202c240d87aac1135 | 3,657,715 |
def poisson2vpvs(poisson_ratio):
"""
Convert Poisson's ratio to Vp/Vs ratio.
Parameters
----------
poisson_ratio : float
Poisson's ratio.
Returns
-------
vpvs_ratio : float
Vp/Vs ratio.
"""
return sqrt(2 * (poisson_ratio - 1) / (2 * poisson_ratio - 1)) | 9f0f41ec3dd5be539dca341ed2ec4b091aeee730 | 3,657,717 |
def vs30_to_z1pt0_cy14(vs30, japan=False):
"""
Returns the estimate depth to the 1.0 km/s velocity layer based on Vs30
from Chiou & Youngs (2014) California model
:param numpy.ndarray vs30:
Input Vs30 values in m/s
:param bool japan:
If true returns the Japan model, otherwise the Ca... | f4f985c2e0aa533cac8afd8533bfad126edbaf01 | 3,657,718 |
def empowerment(iface, priority=0):
"""
Class decorator for indicating a powerup's powerup interfaces.
The class will also be declared as implementing the interface.
@type iface: L{zope.interface.Interface}
@param iface: The powerup interface.
@type priority: int
@param priority: The prio... | 2f63892e539928951ca462239cfd014bdd8b0409 | 3,657,719 |
def multigauss_and_bgd_jacobian(x, *params):
"""Jacobien of the multiple Gaussian profile plus a polynomial background to data.
The degree of the polynomial background is fixed by parameters.CALIB_BGD_NPARAMS.
The order of the parameters is a first block CALIB_BGD_NPARAMS parameters (from low to high Legend... | e4347f50da3bd94ec4aac49c5af3ead4e08fed3b | 3,657,720 |
def get_empty_config():
"""
Return an empty Config object with no options set.
"""
empty_color_config = get_empty_color_config()
result = Config(
examples_dir=None,
custom_dir=None,
color_config=empty_color_config,
use_color=None,
pager_cmd=None,
edito... | f744d770822bd6d58777d346674ea6c16b665701 | 3,657,721 |
def parse(sql_string):
"""Given a string containing SQL, parse it and return the normalized result."""
parsed = select_stmt.parseString(sql_string)
parsed.from_clause = _normalize_from_clause(parsed.from_clause)
parsed.where_clause = _normalize_where_clause(parsed.where_clause)
return parsed | 96a369262bfd852ab7da484c86a2cd06b121d4be | 3,657,722 |
from pathlib import Path
def check_overwrite(path: str, overwrite: bool = False) -> str:
"""
Check if a path exists, if so raising a RuntimeError if overwriting is disabled.
:param path: Path
:param overwrite: Whether to overwrite
:return: Path
"""
if Path(path).is_file() and not overwrit... | 961affdcc87b055cdd5acb9a28547ef87ae426b9 | 3,657,723 |
import struct
def bytes_to_text(input):
"""Converts given bytes (latin-1 char + padding)*length to text"""
content = struct.unpack((int(len(input)/2))*"sx", input)
return "".join([x.decode("latin-1") for x in content]).rstrip("\x00") | f058847886fc3a488c54b8e01c3d7506f6d76510 | 3,657,724 |
def flatten_conv_capsule(inputs):
"""
:param inputs is output from a convolutional capsule layer
inputs.shape = [N,OH,OW,C,PH] C is channel number, PH is vector length
:return shape = [N,OH*OW*C,PH]
"""
inputs_shape = inputs.shape
l=[]
for i1 in range(inputs_shape[1]):
for i... | 8be5319c85311122ef728af5266dd9aecf549be0 | 3,657,725 |
def LookupValue(values, name, scope, kind):
"""Like LookupKind, but for constant values."""
# If the type is an enum, the value can be specified as a qualified name, in
# which case the form EnumName.ENUM_VALUE must be used. We use the presence
# of a '.' in the requested name to identify this. Otherwise, we pr... | 211a4b161c74971d59d256db28935e33005f1782 | 3,657,726 |
def SI1452(key,
Aleph=u'\u05d0', Tav=u'\u05ea'):
"""
Minimalist caps action
Make sure latin capital letters are produced in keys carrying them
(additionally, make Hebrew-letter keys go to level 2)
"""
if Aleph<=key.level_chars[1]<=Tav or u'A' <=key.level_chars[2]<=u'Z':
return... | 51c14d32d090d25e5625582e32d8bbd45d9a819b | 3,657,727 |
def new_topic(request):
"""添加新主题"""
if request.method != 'POST':
form = TopicForm() # 如果不是POST请求, 表示首次请求, 返回空表单
else:
# POST提交了数据, 对数据进行处理
form = TopicForm(request.POST) # 根据请求传入的数据创建一个表单对象
# is_valid()函数核实用户填写了所有必不可少的字段(表单字段默认都是必不可少的),
# 且输入的数据与要求的字段类型一致
i... | b4e6524f0c8d4fdc6d88bd879f61c7430112ae9f | 3,657,728 |
from pathlib import Path
async def get_xdg_data_dir(app=None):
"""Return a data directory for this app.
Create the directory if it does not exist.
"""
if app is None:
app = await get_package_name()
data_home = Path(await get_xdg_home('XDG_DATA_HOME'))
data_dir = data_home / app
i... | fe73abc5e91bf2c3c4a1dfd745981b1e0733aa5a | 3,657,730 |
def patch_subscription(subscription, data):
""" Patches the given subscription with the data provided
"""
return stage_based_messaging_client.update_subscription(
subscription["id"], data) | 68575f24a0e0a881b8c3a9572a496b2ba6293be2 | 3,657,731 |
def update_game(game_obj, size, center1, center2):
"""
Update game state
"""
new_game_obj = game_obj.copy()
if center1 is not None:
new_game_obj['rudder1_pos'] = center1
if center2 is not None:
new_game_obj['rudder2_pos'] = center2
# Check if hitting corner
init_vel = n... | 33646593e6743d11174f72be6f4b825633fe8782 | 3,657,732 |
import requests
def download_thumb(se: requests.Session, proxy: dict, addr: str) -> str:
"""下载缩略图
Args:
se: 会话对象
proxy: 代理字典
addr: 缩略图地址
Returns:
成功时返回缩略图的本地绝对路径，失败时返回空字符串
"""
header = {'User-Agent': USER_AGENT}
try:
with se.get(addr,
... | 06971178c80376bb9c7bf30ca6cc8ad8c2a4b6b9 | 3,657,734 |
def iter_dir_completions(arg):
"""Generate an iterator that iterates through directory name completions.
:param arg: The directory name fragment to match
:type arg: str
"""
return iter_file_completions(arg, True) | e29544ea7886b08c03d6ba79374d0576b5af701e | 3,657,735 |
def climate_eurotronic_spirit_z_fixture(client, climate_eurotronic_spirit_z_state):
"""Mock a climate radio danfoss LC-13 node."""
node = Node(client, climate_eurotronic_spirit_z_state)
client.driver.controller.nodes[node.node_id] = node
return node | 7d24ada11d4ed30dd62d7bf160757f8909f7d4c8 | 3,657,736 |
def xi_eta_to_ab(ξ, η):
""" function to transform xi, eta coords to a, b
see Hesthaven function 'rstoab'
@param xi, eta vectors of xi, eta pts
"""
a, b = np.zeros_like(ξ), np.zeros_like(η)
singular = np.isclose(η, 1.0)
nonsingular = np.logical_not(singular)
a[nonsingular] = 2*(1. + ξ[non... | 3664e90754ab9ebb86cc76f585e8383d76d6d75d | 3,657,737 |
def mulaw_to_value(mudata):
"""Convert a mu-law encoded value to linear."""
position = ((mudata & 0xF0) >> 4) + 5
return ((1 << position) | ((mudata & 0xF) << (position - 4)) | (1 << (position - 5))) - 33 | 2ccca7f13861c7a212ac3a1dd2afc439839b19a7 | 3,657,739 |
from typing import Iterable
from typing import Set
import re
import click
def init_exclusion_regexes(paths_ignore: Iterable[str]) -> Set[re.Pattern]:
"""
filter_set creates a set of paths of the ignored
entries from 3 sources:
.gitguardian.yaml
files in .git
files ignore in .gitignore
"""
... | 54c7dd9b064fd2582545b82b2f8df324448e49f3 | 3,657,740 |
def validate_watch(value):
"""Validate "watch" parameter."""
if not value:
return None
if isinstance(value, str):
value = [_ for _ in value.split("\n") if _]
return value | 203b77f376a747cbd10f0c674897f912bb75618f | 3,657,741 |
def diatomic_unitary(a, b, c):
"""
Unitary decomposed as a diatomic gate of the form
Ztheta + X90 + Ztheta + X90 + Ztheta
"""
X90 = expm(-0.25j*np.pi*pX)
return expm(-0.5j*a*pZ)@X90@expm(-0.5j*b*pZ)@X90@expm(-0.5j*c*pZ) | 38bbd194f2179aff1874190dbbb95546790f9d91 | 3,657,742 |
def is_x_y_in_hidden_zone_all_targets(room_representation, camera_id, x, y):
"""
:description
Extend the function is_x_y_in_hidden_zone_one_target,
1.for every target in the room
:param
1. (RoomRepresentation) -- room description of the target... | a682a2ac99798c3c8d7ad23881f965ffa33071bf | 3,657,743 |
def _create_pure_mcts_player(
game: polygames.Game, mcts_option: mcts.MctsOption, num_actor: int
) -> mcts.MctsPlayer:
"""a player that uses only mcts + random rollout, no neural net"""
player = mcts.MctsPlayer(mcts_option)
for _ in range(num_actor):
actor = polygames.Actor(
None, ga... | 8faf70a43e0734362dfd3aba0c0575758945eb09 | 3,657,744 |
def get_fans_users():
"""
获取用户的粉丝
:return:
"""
user_id = request.argget.all("user_id")
page = str_to_num(request.argget.all("page", 1))
pre = str_to_num(request.argget.all("pre", 20))
s, r = arg_verify(reqargs=[("user id", user_id)], required=True)
if not s:
return r
data... | 0af36e4f2b3051975f834df554ff09e9d539ec82 | 3,657,745 |
import re
def test_invalid_patterns(list, pattern):
"""
Function to facilitate the tests in MyRegExTest class
:param list: list with strings of invalid cases
:param pattern: a regular expression
:return: list with the result of all matches which should be a list of None
"""
newList = []
... | 94a8232d66ff4c705e7a587aedc9d1cbe0b4f072 | 3,657,746 |
def remove_constant_features(sfm):
"""
Remove features that are constant across all samples
"""
# boolean matrix of whether x == first column (feature)
x_not_equal_to_1st_row = sfm._x != sfm._x[0]
non_const_f_bool_ind = x_not_equal_to_1st_row.sum(axis=0) >= 1
return sfm.ind_x(selected_f_inds... | ae8c6e1d14b7260c8d2491b2f8a00ba352d7375a | 3,657,748 |
def flatten(x):
""" Flatten list an array.
Parameters
----------
x: list of ndarray or ndarray
the input dataset.
Returns
-------
y: ndarray 1D
the flatten input list of array.
shape: list of uplet
the input list of array structure.
"""
# Check input
... | 4efb7c740cb197bf9e8e094a9e6b6e38badb5a25 | 3,657,749 |
def sample_automaton():
"""
Creates a sample automaton and returns it.
"""
# The states are a python Set. Name them whatever you want.
states = {"0","1","2"}
# Choose one of the states to be the initial state. You need to give this a Set, but that Set usually only contains one state.
init_state = {"0"}
... | f0b7da88825c88841e55dd1ebaf46d5979eaa0fb | 3,657,750 |
def mae(data, data_truth):
"""Computes mean absolute error (MAE)
:param data: Predicted time series values (n_timesteps, n_timeseries)
:type data: numpy array
:param data_truth: Ground truth time series values
:type data_truth: numpy array
"""
return np.mean(np.abs(data - data_truth)) | 76fce7e40adbfbf28f3d08df4117502baa01cbed | 3,657,751 |
def _find_ntc_family(guide_id):
"""Return a String of the NTC family
"""
guide_id_list = guide_id.split('_')
return '_'.join(guide_id_list[0:2]) | 2b340694c2379682b232e49c9b0f1f0a91c778cf | 3,657,752 |
def CreateFilletCurves(curve0, point0, curve1, point1, radius, join, trim, arcExtension, tolerance, angleTolerance, multiple=False):
"""
Creates a tangent arc between two curves and trims or extends the curves to the arc.
Args:
curve0 (Curve): The first curve to fillet.
point0 (Point3d): A ... | fee4c009db83ff77d6369e8e88d2bd3bc1d64390 | 3,657,753 |
from typing import List
from typing import Tuple
import json
from typing import Dict
def select_ads() -> jsonify:
"""
select ads
"""
try:
if INSERTED_FILES_NUM == 0 or INSERTED_FILES_NUM != PROCESSED_FILES_NUM:
raise Exception('server is not ready')
weights: List[Tuple[str... | 7e65b21792c6b80e90dcb16bab644a329e8f7eb5 | 3,657,754 |
from typing import Dict
from typing import List
from typing import Any
def _xpath_find(data: Dict, xparts: List, create_if_missing: bool = False) -> Any:
"""
Descend into a data dictionary.
:arg data:
The dictionary where to look for `xparts`.
:arg xparts:
Elements of an Xpath split w... | 24bd5e04c5ba8bd7dc4950c3f655241d4d4e8d65 | 3,657,755 |
def r_mediate(y, t, m, x, interaction=False):
"""
This function calls the R function mediate from the package mediation
(https://cran.r-project.org/package=mediation)
y array-like, shape (n_samples)
outcome value for each unit, continuous
t array-like, shape (n_samples)
... | c07afc4c2569566d67e652e8de4a5ee770a49218 | 3,657,756 |
def default_props(reset=False, **kwargs):
"""Return current default properties
Parameters
----------
reset : bool
if True, reset properties and return
default: False
"""
global _DEFAULT_PROPS
if _DEFAULT_PROPS is None or reset:
reset_default_props(**kwargs)
... | 43a7015bd8089082d17ca7625748a8789b3eb52a | 3,657,757 |
def ReadFlatFileNGA(xlsfile):
"""
Generate NGA flatfile dictionary for generate usage
"""
# read in excel flatfile
book = xlrd.open_workbook(xlsfile)
sh = book.sheet_by_index(0) # 'Flatfile' sheet name
keys = sh.row_values(0)
for itmp in range( len(keys) ):
keys[itmp] = keys[i... | 8ed4c66a541cb5fcebce6965c1f9b9a514bea1ae | 3,657,758 |
def _chr_ord(x):
"""
This is a private utility function for getBytesIOString to return
chr(ord(x))
"""
return chr(ord(x)) | 8529686bf3a40cd1f2c32f458ebdba17a9b35a05 | 3,657,759 |
def vkToWchar (m):
""" Mapping from virtual key to character """
ret = []
retTbl = ['/* table of virtual key to wchar mapping tables */',
'static VK_TO_WCHAR_TABLE aVkToWcharTable[] = {']
def generate (n, g, defPrefix=''):
defname = f'aVkToWch{defPrefix}{n}'
ret.extend ([f'... | b0b938720c13ed45c32dcd402f43e93f24aaa111 | 3,657,760 |
def load_glove_vectors(glove_file="/home/yaguang/pretrained_models/glove.6B.50d.txt"):
"""Load the glove word vectors"""
word_vectors = {}
with open(glove_file) as f:
for line in f:
split = line.split()
word_vectors[split[0]] = [float(x) for x in split[1:]]
return word_ve... | a7bb1650885e12f436273b012d0c1c381e1be311 | 3,657,761 |
def _ParseFileVersion(file_version):
"""Convert the string file_version in event.proto into a float.
Args:
file_version: String file_version from event.proto
Returns:
Version number as a float.
"""
tokens = file_version.split("brain.Event:")
try:
return float(tokens[-1])
... | 43e4cfdc116ae5e687e4c0f6ed55bc8b7518f6b1 | 3,657,762 |
import gzip
def get_file_format(input_files):
"""
Takes all input files and checks their first character to assess
the file format. Returns one of the following strings; fasta, fastq,
other or mixed. fasta and fastq indicates that all input files are
of the same format, either fasta or fastq. othe... | 901ed1ca81563321eb9a16e6a36fbebb12f3b2ea | 3,657,763 |
def get_nominal_hour(train_num):
"""Get the nominal hour for a train num (most frequent)"""
res = database.get().query("""
SELECT count(*) as count, substr(date, 12, 5) as hour
FROM results WHERE num = '%s'
GROUP BY hour ORDER BY count DESC LIMIT 1;
""" % train_num)
return next(r... | c51fba63b03e2aa930399077143ff77e1fe5f485 | 3,657,764 |
def compute_cgan_metrics(img_y, img_g, i = 0):
"""
Computes accuracy, precision, recall, f1, iou_score for passed image, return None in case of div 0
img_y: ground truth building footprint semantic map
img_g: generated image
i: 0 for entire image, 1 for inner (excluding border)
N... | be900b303d333ec1c7233d59779c8006333fba36 | 3,657,766 |
def learning(spiking_neurons, spike_times, taup, taum, Ap, Am, wmax, w_init):
"""
Takes a spiking group of neurons, connects the neurons sparsely with each other, and learns the weight 'pattern' via STDP:
exponential STDP: f(s) = A_p * exp(-s/tau_p) (if s > 0), where s=tpost_{spike}-tpre_{spike}
:param ... | 7324a2290e7ec14146be28d2b5a14e10b6ec44e4 | 3,657,767 |
import optparse
def build_arg_parser2():
"""
Build an argument parser using optparse. Use it when python version is 2.5 or 2.6.
"""
usage_str = "Smatch table calculator -- arguments"
parser = optparse.OptionParser(usage=usage_str)
parser.add_option("--fl", dest="fl", type="string", help='AMR ... | 7118b337bda7b9b170bf3eedf230a5fcd323a17b | 3,657,768 |
def _write_log(path, lines):
"""
:param path: log file path
:param lines: content
:return status:Bool
"""
try:
with open(path, 'w') as file:
logi('open file {log_path} for writting'.format(log_path=path))
file.writelines(lines)
except Exception as e:
l... | f98d87939a23549a82370ce81e7bf28b1ac52b10 | 3,657,769 |
def update_meal_plan(plan_id: str, meal_plan: MealPlan):
""" Updates a meal plan based off ID """
meal_plan.process_meals()
meal_plan.update(plan_id)
# try:
# meal_plan.process_meals()
# meal_plan.update(plan_id)
# except:
# raise HTTPException(
# status_code=404,... | cf201280d6f89aac5d412af3344e4ba89b29d1ed | 3,657,770 |
def clean_data(df):
"""
INPUT:
df - Panda DataFrame - A data frame that contains the data
OUTPUT:
df - Panda DataFrame - A Cleaned Panda Data frame
"""
#split categories into a data frame and take the first row
cat = df.categories.str.split(';', expand=True)
row = cat.iloc[... | 7d19cf395094fe780da6204f10f80528526083d0 | 3,657,771 |
def vec2transform(v):
"""Convert a pose from 7D vector format ( x y z qx qy qz qw) to transformation matrix form
Args: v pose in 7D vector format
Returns:
T 4x4 transformation matrix
$ rosrun tf tf_echo base os_lidar
- Translation: [-0.084, -0.025, 0.050]
- Rotation: in Quaternion [... | e3a6023fe2b6bedc7b023d08bb22abd406bb9612 | 3,657,772 |
import re
def cleanup_name_customregex(cname, customregex=None, returnmatches=False):
"""Cleanup the input name given a custom dictionary of regular expressions (format of customregex: a dict like {'regex-pattern': 'replacement'}"""
if customregex is None:
customregex = {'_': ' ',
... | 15cbaf0cb439ba8aa3a550cc7713e19e34d714d4 | 3,657,773 |
import math
def compute_recommended_batch_size_for_trustworthy_experiments(C: int, H: int, W: int, safety_val: float) -> int:
"""
Based on inequality with safety_val=s:
N' >= s*D'
the recommended batch size is, assuming N'=B*H*W and D'=C (so considering neurons as filter, patches as data):
... | 80f11adb87b252a31aba590c38e60350535025ae | 3,657,774 |
def filter_gradient(t, h_, n_std=3):
"""Filter outliers by evaluating the derivative.
Take derivative and evaluate outliers in derivative.
"""
h = h_.copy()
# NOTE: This must be a separate step
# dh/dt = 0 -> invalid
dhdt = np.gradient(h)
invalid = np.round(dhdt, 6) == 0.0
dhdt[inv... | 4e4547f38c2886f33c3b42442ff37b9100dda9c7 | 3,657,775 |
def generate_valve_from_great_vessel(
label_great_vessel,
label_ventricle,
valve_thickness_mm=8,
):
"""
Generates a geometrically-defined valve.
This function is suitable for the pulmonic and aortic valves.
Args:
label_great_vessel (SimpleITK.Image): The binary mask for the great ve... | 4a40ab9513e6093486a914099316e80a8a24f58e | 3,657,777 |
def current_decay(dataframe,two_components=False):
"""
Fits 95% peak to:
A(t) = A*exp(-t/Taufast) + B*exp(-t/Tauslow) +Iss
Parameters
----------
dataframe : A pandas dataframe
Should be baselined
two_components : True/False
When False, a single exponential component ... | 048e001b23344b2ac72f6683b0ca1ca66af8dcbd | 3,657,778 |
import ctypes
def get_n_mode_follow(p_state, idx_image=-1, idx_chain=-1):
"""Returns the index of the mode which to follow."""
return int(_MMF_Get_N_Mode_Follow(p_state, ctypes.c_int(idx_image), ctypes.c_int(idx_chain))) | 30a548369b4fd708b3c8c73549b79951c9435667 | 3,657,779 |
def divide(lhs, rhs):
"""Division with auto-broadcasting
Parameters
----------
lhs : tvm.Tensor or Expr
The left operand
rhs : tvm.Tensor or Expr
The right operand
Returns
-------
ret : tvm.Tensor or Expr
Returns Expr if both operands are Expr.
Otherwise... | d4a6f3b28eaa35faa300a64e5a81ac64aa6740cb | 3,657,781 |
import gzip
import pickle
def load(filename):
"""Loads a compressed object from disk
"""
file = gzip.GzipFile(filename, 'rb')
buffer = b''
while True:
data = file.read()
if data == b'':
break
buffer += data
object = pickle.loads(buffer)
file.close()
... | 8a2b9bff8297fdf2824f962df9202b8e08c8d8a1 | 3,657,782 |
from multiprocessing import Queue
from .rabbitmq import Queue
from .beanstalk import Queue
from .redis_queue import Queue
def connect_message_queue(name, url=None, maxsize=0):
"""
create connection to message queue
name:
name of message queue
rabbitmq:
amqp://username:password@host:5... | 4cb3ea808de8ffd5c157c4fbbf95e78d1ad2b075 | 3,657,783 |
def load_document(filepath):
"""
Description:Opens and loads the file specified by filepath as a raw txt string; assumes valid text file format.
Input: String -> filepath of file from current directory
Output: Entire contents of text file as a string
"""
#assert(filepath.endswith(".txt")), "Function: Load ... | b44a3af09ec7c776a1d3bd1a90efe3deb90da821 | 3,657,784 |
def get_user(request, uid):
"""
GET /user/1/
"""
if uid != 1:
return JsonResponse({"code": 10101, "message": "user id null"})
data = {"age": 22, "id": 1, "name": "tom"}
return JsonResponse({"code": 10200, "data": data, "message": "success"}) | 92ef79cf015de5556d1c5715e57cb550a42ef1ca | 3,657,785 |
import collections
import tokenize
def count_ngrams(lines, min_length=1, max_length=3):
"""
Iterate through given lines iterator (file object or list of
lines) and return n-gram frequencies. The return value is a dict
mapping the length of the n-gram to a collections.Counter
object of n-gram tuple... | 514a313b96d139c3483dc07999f60d1abafd0d91 | 3,657,786 |
def notas(*n, sit = False):
"""
-> Função para analisar notas e situação de vários alunos.
:param n: notas (uma ou mais)
:param sit: situação (valor opcional)
:return: dicionário com várias informaçoes sobre o aluno.
"""
r = {}
r['total'] = len(n)
r['maior'] = max(n)
r['menor'] =... | f151c90e22e5eac1c69b59240906e7bf55943321 | 3,657,787 |
import numpy
def accuracy(output, labels_test):
"""How many correct predictions?"""
TP, TN, FP, FN = confusionMatrix(labels_test, numpy.sign(output))
return float(TP + TN) / (TP + TN + FP + FN) | f3801bbe3590e9d271403795d23a737d642fbed8 | 3,657,788 |
def metric_pairs(request):
"""Pairs of (dask-ml, sklearn) accuracy metrics.
* accuracy_score
"""
return (
getattr(dask_ml.metrics, request.param),
getattr(sklearn.metrics, request.param)
) | e82b799c06e41c4fea19cd33e9d836b1b03d02df | 3,657,789 |
import time
from datetime import datetime
def MyDuration(duration, initial_time=None):
"""
Usecase:
a timestamp is provided as when an access token expires,
then add it to the current time, then showing it as a human-readable
future time.
Alternatively specify a *initial_ti... | d81a12295c2715ab9ed93595ccee2af2474c671e | 3,657,790 |
def orthogonal_init(shape, gain=1.0):
"""Generating orthogonal matrix"""
# Check the shape
if len(shape) < 2:
raise ValueError("The tensor to initialize must be "
"at least two-dimensional")
# Flatten the input shape with the last dimension remaining
# its original s... | 4d7b1f81a13228e4185d59e0fd23ba629888a232 | 3,657,791 |
def application(env, start_response):
"""The callable function per the WSGI spec; PEP 333"""
headers = {x[5:].replace('_', '-'):y for x, y in env.items() if x.startswith('HTTP_')}
if env.get('CONTENT_TYPE', None):
headers['Content-Type'] = env['CONTENT_TYPE']
if env.get('CONTENT_LENGTH', None):
... | 1c5cbb62316b4170bbd54ef8fa404eccc32b8441 | 3,657,792 |
def angle_normalize(x):
"""
Normalize angles between 0-2PI
"""
return ((x + np.pi) % (2 * np.pi)) - np.pi | 0c39dcf67a5aae2340a65173e6a866e429b4d176 | 3,657,793 |
import torch
def load_data(BASE_DIR, DATA_DIR):
"""
Loads data necessary for project
Arguments:
BASE_DIR (str) -- path to working dir
DATA_DIR (str) -- path to KEGG data
Returns:
tla_to_mod_to_kos (defaultdict of dicts) -- maps tla to series of dicts, keys are KEGG modules and values are lists of KOs in... | d32a6be8cae02ac6ab5903f055326f27d0a549c5 | 3,657,794 |
def disable_app(app, base_url=DEFAULT_BASE_URL):
"""Disable App.
Disable an app to effectively remove it from your Cytoscape session without having to uninstall it.
Args:
app (str): Name of app
base_url (str): Ignore unless you need to specify a custom domain,
port or version t... | 2a2a00609b0acb6090219d24fcc7d24ed8f7dc7e | 3,657,795 |
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