content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def _jsonify(vals):
"""문서 출력을 위해 파이썬 값을 JSON 형태로."""
_vals = []
for val in vals:
if type(val) is bool:
_vals.append(str(val).lower())
else:
_vals.append(val)
return _vals | d9240bc43f1ca9a31152b12a94fc1ba1980e2b82 | 3,597,323 |
def order_matrix(original, sortd, sigma=0.1):
"""Apply a simple RBF kernel to the difference between original and sortd,
with the kernel width set by sigma. Normalise each row to sum to 1.0."""
diff = (tf.reshape(original, (-1, 1)) - tf.reshape(sortd, (1, -1))) ** 2
rbf = tf.exp(-(diff) / (2 * sigma ** ... | 4deac4093f6d3440e094a0a4dfcc83aef08cae0e | 3,597,324 |
def load_ref_schema(ref_schema_uri):
"""
loads a referenced schema
"""
sub_schema = generate_schema_name_from_uri(ref_schema_uri)
return import_schema_to_json(sub_schema) | 3f888f40fc96d4bae0cc8b0a8982213973069c97 | 3,597,326 |
def by_tid(
move_data, tid_=None, label_tid=TID, filter_out=False, inplace=False
):
"""
Filters trajectories points according to a specified trajectory tid.
Parameters
----------
move_data : dataframe
The input trajectory data
tid_ : String
Specifies the number of the tid u... | 2400df83ac905be3f05080c5cf948c80d2ee8f34 | 3,597,327 |
def sph_dot(theta1, theta2, delta_phi):
"""
Compute the dot product of two unit vectors in spherical coordinates
"""
return np.sin(theta1) * np.cos(delta_phi) * np.sin(theta2) + np.cos(theta1) * np.cos(theta2) | 8e28f015a0ff82b3f5be2d8d9d6e87016e411e63 | 3,597,328 |
def TTF_WasInit():
"""Checks if the TTF engine is initialized.
This function can be used before calling :func:`TTF_Init` to avoid
initializing twice in a row, or to determine if need to call
:func:`TTF_Quit`.
Returns:
int: The number of times :func:`TTF_Init` has been called without ... | b30b1ab7b9c5946dae61d09f26246b7c5134d9f0 | 3,597,329 |
def poly_from_expr(expr, *gens, **args):
"""Construct a polynomial from an expression. """
opt = options.build_options(gens, args)
return _poly_from_expr(expr, opt) | 8cca85d539104a34e16bf7fc89ac311b3c4220e6 | 3,597,330 |
from typing import Dict
from typing import Any
def get_metrics(database: Database):
"""Get all metrics."""
metrics: Dict[str, Any] = {}
reports = get_reports(database)
for report in reports["reports"]:
for subject in report["subjects"].values():
metrics.update(subject["metrics"])
... | 2716d2716e194e457e3d548ed752dcde00197b78 | 3,597,331 |
def move_axes_to_end(mx_orig,axes):
""" Moves the listed axes to the end.
"""
mx = mx_orig
mx_axes = list(range(mx.ndim))
for i in range(len(axes)):
# Finding the axis
ind = mx_axes.index(axes[i])
# Move from to the end
mx = np.moveaxis(mx,ind,-1)
# Following ... | 6a100f58a20abe440a7c2bb1ab2243d1a4f4fd74 | 3,597,332 |
def split(data, num_or_size_splits, split_axis=0, num=None):
"""
Splits a tensor into sub tensors.
Args:
data: Tensor.
num_or_size_splits: Integer or list. Used to split data.
split_axis: Integer. The dimension along which to split.
Returns:
Tuple of tensor, counts of w... | 0d198ae44edafc6cadcbf949401329804483ea21 | 3,597,333 |
def _read_hc(directory):
"""Read the hc file to get the HPI info and to prepare for coord trans."""
fname = _make_ctf_name(directory, 'hc', raise_error=False)
if fname is None:
logger.info(' hc data not present')
return None
s = list()
with open(fname, 'rb') as fid:
while(... | 4768754342e9537db44239f5d6c1fc270690da48 | 3,597,335 |
def find_prev_bn(bn_module, relu_attached, graph, bottoms, bot):
"""
Find the batchnorm layers for calculation of expectation or min/max value of input activation.
And find branching type(one, add, or cat).
"""
bot_tmp = list(zip(bot, [str(x) for x in range(len(bot))]))
type_tmp = {}
targ_wi... | 3c47d83329bf8334f56d02aaa9928befac4408a7 | 3,597,336 |
def get_boundary_locations(size, sector_size, stride):
"""Get a list of 1D sector boundary positions.
Args:
size: length of the full domain.
sector_size: length of the sector.
stride: how far each sector moves to the right
Returns:
boundaries: a list of 1D sector boundary pos... | ae6a2b6461f2c823f0129e7f691d63830834cbe7 | 3,597,337 |
def estimate_closest_point(dataset, lons, lats):
"""Estimate the closest grid point to an array of lat/lons
using a index file created by make_mapping_file above
:param xarray dataset: dataset
:param numpy array or list: lons
:param numpy array or list: lats
return: numpy array of indexes: i... | a3687348489adad8e8e5894409a44581172479f3 | 3,597,338 |
def index(request):
"""Displaying the index page"""
post_list = Post.objects.order_by('-pub_date').all()
paginator = Paginator(post_list, 6)
page_number = request.GET.get('page')
page = paginator.get_page(page_number)
return render(
request,
'index.html',
{'page': page, '... | dd1f9e1dad5cd22eafb93fc964864ff6c164ae15 | 3,597,339 |
def get_paging_start_end(page, numberMatches):
"""Get tuple (iStart, iEnd)"""
iStart = (page-1)*numberMatches
iEnd = iStart+numberMatches
fields = (iStart, iEnd)
return fields | bb2b89fd2f9b6c18f134cfabc5e56da682688b55 | 3,597,340 |
def create_kcg(documents, big_graph, dataset_name=None):
"""
:param documents: list of documents, each document is taken as a string
:return: nodes (a list of nodes including{'keyword', 'feature'});
node['feature'] is the average of its sentences' SBERT embeddings,
and adjacency ... | bf0a5b775d1b81133a3c400ab4c76e76fa289762 | 3,597,341 |
from typing import Union
from typing import Optional
from typing import Sequence
def subset_gridpoint(
da: Union[xarray.DataArray, xarray.Dataset],
lon: Optional[Union[float, Sequence[float], xarray.DataArray]] = None,
lat: Optional[Union[float, Sequence[float], xarray.DataArray]] = None,
start_date: ... | 174f1f3a46d0058b6dd53f73c2b0d500660ed28f | 3,597,343 |
def random_shear(image, max_lambda, bbox=None, prob=0.5):
"""Applies random shear in either the x or y direction"""
shear_lambda = tf.random.uniform([], minval=-max_lambda, maxval=max_lambda, dtype=tf.float32)
image_shape = tf.cast(tf.shape(image), tf.float32)
image_height, image_width = image_shape[0],... | 59f1a8b6290237beb5eb7f96b0c0b8a8544092a9 | 3,597,345 |
import random
def random_strategy(D):
"""
Retourne un nombre entre 1 et D correspondant à une stratégie aléatoire utilisée comme baseline
----------------------------------------------------
Args:
- D : nombre maximum de dés
"""
return random.randint(1,D) | 280f3deff20e0f4e96f7cbd8f3ea4d4ae671aba8 | 3,597,346 |
def next_setting(hass, entity_id=None):
""" Returns the datetime object representing the next sun setting. """
entity_id = entity_id or ENTITY_ID
state = hass.states.get(ENTITY_ID)
try:
return str_to_datetime(state.attributes[STATE_ATTR_NEXT_SETTING])
except (AttributeError, KeyError):
... | e40f4a3ab1e2673dc57a745d1474791bca52df4d | 3,597,347 |
def _get_rate_via_base(rates, target):
"""
:param: rates: A set/tuple of two base Rate instances
:param: target: A string instance of the currency to convert to
Both target and source are not a base currency - actual rate could be calculated via their rates to base currency.
For example:
7.84 ... | 705ae5339cbb62da315898ae4e481f8c25edc2f3 | 3,597,348 |
def read_our_csv(startOfPath, netVers):
""" Read in the edge list of a graph.
In our case we created the graphs in R and output the edgelists in a certain manner
with file names following a certain convention.
This function simply reads in csvs formatted in that specific way,
with the file paths f... | bcea9c8b622066f5d64ed46db5fce66a76edb05c | 3,597,349 |
from typing import Any
def coro_as_method_coro(coro: CoroutineFunction) -> CoroutineMethod:
"""Wrapper function to coro"""
@wraps(coro)
async def method(*args, **kwargs) -> Any:
return await coro(*args, **kwargs)
return method | 38cebe8b7ef7e60f619d8157de8db5b4dd94a3cd | 3,597,350 |
def fix_coordinate_system(value: float, min_value: float = 0.0, max_value: float = 1.0):
"""
In case of Out-Of-Range values: fix the rounding error
"""
value = min(value, max_value)
value = max(value, min_value)
return value | f692d6e94ed61be5bd25207bf787267e921a2f08 | 3,597,351 |
def solution_decomposition(xx, obj, success):
"""
Decomposition of objective functions
:param xx: Solution
:param obj: Objective value
:param success: Success or not
:return:
"""
T = 24
ng = 54
result = {}
result["success"] = success
result["obj"] = obj
if success:
... | c786a2a610d2bbe39a81bc23417f7e4494370086 | 3,597,352 |
def setup(app):
"""Sets the extension up"""
from docutils.parsers.rst import roles # pylint: disable=wrong-import-order
roles.register_local_role("template-fields", partial(template_field_role, app))
return {"version": "builtin", "parallel_read_safe": True, "parallel_write_safe": True} | f83c702744b257d4726dd74f1ce15b3e1ca1b088 | 3,597,353 |
from typing import List
def setup(client: Client) -> List[BasePlugin]:
"""Creates an instance of the ChallstrHandler plugin and returns it.
Args:
client (Client): A reference to the client.
Returns:
List[BasePlugin]: A list containing the ChallstrHandler plugin.
"""
return [Chall... | c3453897d48ade1144b12bb92f2db792ec620a9c | 3,597,354 |
def from_dero(value_in_dero):
"""Convert number in dero to smallest unit"""
return int(value_in_dero*10**12) | 6a27469721cbd9851312f73a971caf279c95ffa8 | 3,597,355 |
def plainFlag_Task(values,*args):
"""
This method is identical to plainFlag but for the task decorator.
"""
flag = plainFlag(values,*args)
return flag | ba36bff70a19bf0818ce9daeb773530500e0a05e | 3,597,356 |
def tasks_widget(doc, notifier, cmap):
"""Defines the tab for the task plot"""
task_plot = TasksPlot(doc, cmap=cmap)
notifier.subscribe(task_plot.set_collection)
return task_plot.layout() | 7948e553093965017a831d8d9228610d8eca67c3 | 3,597,357 |
def _subproc(cmd):
"""
call subprocess `cmd` and get its output
>>> _subproc(['echo', 'foo'])
'foo'
"""
try:
p = subprocess.Popen(
cmd,
stderr=subprocess.STDOUT,
stdout=subprocess.PIPE,
env={"PATH": PATH})
ret, _dummy = p.communicat... | 4dbfbb353f64b9091d19a83b179ce57b7a3a7930 | 3,597,358 |
def extract_gates_T1_from_result_GST(result, gate_operation_time):
"""Calculates the T1 from the extracted diagonal decay out of the result of GST analysis.
Which is given as a number e.g. 0.001, from which T1 can be calculated.
Which is done by: (1-decayrate)**N=e**(N*ln(1-decayrate)), where N is the
n... | 4b8be32b7d7c950578e6d719b7355b60fe089ce4 | 3,597,359 |
def rospack_depends(pkg):
"""
@param pkg: package name
@type pkg: str
@return: A list of the names of the packages which pkg depends on
@rtype: list
"""
return rospackexec(['deps', pkg]).split() | 084a6ccced5ecd7b6e03c298249a18de77174b3d | 3,597,360 |
def check_duplicates(df, column):
"""
Function to check no.of values that occur more than once.
Parameter
---------
df : DataFrame to be processed.
column : column in df for which we want to find duplicate values.
"""
assert_cols_in_df(df, columns_provided=[column], columns_df=df.co... | ef9a86d196122f6be1adec6aa3654d23da0baede | 3,597,361 |
def get_batch_topk(candidate_starts, candidate_ends, candidate_scores, topk_ratio, text_len,
max_sentence_length, sort_spans=False, enforce_non_crossing=True):
"""
Args:
candidate_starts: [num_sentences, max_num_candidates]
candidate_mask: [num_sentences, max_num_candidates]
topk_rati... | 66957cfb06499588d6c9b7e31bb4e6fc4743edf0 | 3,597,362 |
def t1t2shuffle_ex(angle_ex_rad, angles_rad, TE, TRs, M0, T1, T2, B1=1.):
"""Same as t1t2shuffle, with arbitrary RF excitation flip angle"""
T = angles_rad.size
URs = TRs - (T+1)*TE # T + 1 to account for fast recovery
fi = epg.FSE_signal_ex(angle_ex_rad, angles_rad, TE, T1, T2, B1)
Ej = T1_recov... | 66c2078ba9c93bc997f7ade85ca087275e95b84a | 3,597,363 |
def dump_glyphs(font):
"""Dump info for each glyph in a font
Parameters
----------
font: DFont
Returns
-------
DFontTableIMG
Each row in the table is represented as a dict.
[
{'glyph': A, 'area': 1000, string': 'A',
'description': "A | ()", 'features': ... | d16109600a60e9cd105ff1844095833b86a5a8a3 | 3,597,364 |
from typing import List
def _hash_layer(layer: List[HashedEntry], last_index: int) -> List[HashedEntry]:
""" Takes a layer as a list of hashed entries and the last index as an int and returns a new layer. """
new_len = (len(layer) + 1) // 2
new_layer: List[HashedEntry] = []
for i in range(new_len):
... | 1ce5b76928313420b8b8f0b6c1f7e9fd0358b0a2 | 3,597,365 |
def pixel_to_sky_position(position_px: npt.NDArray[np.float_], wcs: WCS) -> SkyCoord:
"""Convert pixel coordinates to the corresponding sky position.
Parameters
----------
position_px: `~numpy.ndarray` of `float`
Pixel coordinates.
wcs: `~astropy.wcs.WCS`
WCS object.
Returns
... | 2f514e17626b9b7ab24401a61860e912fe700624 | 3,597,366 |
def JMatrixEpoch12Epoch2(Jepoch1, Jepoch2):
#----------------------------------------------------------------------
"""
Precession from one epoch to another in the fk5 system.
It uses :func:`Lieskeprecangles` to calculate the
precession angles.
:param Jepoch1:
Julian start epoch
:type Jepoch1:
Floating point... | 2822e297cdd667d3fa83518c651658a25cbfcb04 | 3,597,367 |
def bech32_encode(hrp, data):
"""Compute a Bech32 string given HRP and data values."""
combined = data + bech32_create_checksum(hrp, data)
return hrp + '1' + ''.join([CHARSET[d] for d in combined]) | 626ddcf23cd3d75e8092cf5c3f257f3d46268f8b | 3,597,368 |
import socket
import struct
def open_channel(client, channel_name, media_type):
"""func"""
try:
message_name = pb._OPENCHANNELREQUEST.full_name
message_name_size = len(pb._OPENCHANNELREQUEST.full_name)
image_data = protobuf_open_channel(channel_name, media_type)
image_data_size... | be353095b091f5878317d007e1a1aa810079d9c5 | 3,597,369 |
from typing import Any
def update_membership(
*,
db: Session = Depends(deps.get_db),
id: int,
membership_in: schemas.membership.MembershipUpdate,
current_user: models.User = Depends(deps.get_current_active_user),
) -> Any:
"""
Update an membership.
"""
membership = crud.membership.... | 9f99c5b8feddd25388900560c586850098bf02e5 | 3,597,370 |
def j2s(*args):
"""
.. function:: j2s(jpack) -> space separated string
Converts multiple input jpacks to a space separated string. Newlines are converted to spaces.
Examples:
>>> sql("select j2s('[1,2,3]')") # doctest: +NORMALIZE_WHITESPACE
j2s('[1,2,3]')
--------------
1 2 3
>>... | 79e0fe02bcb7a06b3e2f21e5a42ffdfa0d16f8f0 | 3,597,371 |
import scipy.special
def detectThresholdToNoiseSignalToNoisepD(SignalToNoise, pD):
""" Solve for the threshold to noise ratio, given the signal to noise ratio and
probability of detection.
References:
"Electro-optics handbook," Tech. Rep. EOH-11, RCA, 1974. RCA Technical Series Publication.
R. ... | 7e26c555631efcb4a4a165a71e539a24134f0eb7 | 3,597,372 |
def lemmatize(sentence):
"""
pass in a sentence as a string, return just core text that has been "lematised"
stop words are removed - could effect ability to detect if this is a question or answer
- depends on import lemma = nltk.wordnet.WordNetLemmatizer() and from nltk.corpus import stopwords
... | 7ae73e43f092246e2ba3a5060c11f870499aabd9 | 3,597,375 |
from operator import or_
def getProjectList(customer_id):
""" Returns a list of projects. If a customer id is provided, the list will contain
only contain projects to the given customer id """
if request.method == 'GET':
search = request.args.get("search")
status = request.args.get('status... | aa738c77441fb98d72797ab10a2861d4acb86701 | 3,597,376 |
def find_top_features_in_multiple_runs(x, y, importance_func, n_runs=100):
""" Calculating MDI value over multiple random forest
classifiers with different random seeds.
Parameters:
x - features vectors dataframe
y - true labels dataframe
importance_func - importance function
n_runs - ... | 16f87981db45bf9ad8fc52bbc07b3afdcd3c0d69 | 3,597,377 |
def rotm_to_quat(rotm):
"""
calculate the rotation matrix of a given quaternion (frames assumed to be consistant
with the UKF state quaternion). First element of quat is the scalar.
"""
return np.roll(R.from_dcm(rotm).as_quat(),1) | 3caef8738a7496a84e72ab1bb1ab1a02a3e3c566 | 3,597,378 |
def get_constant_scheduler_with_warmup(optim: Optimizer, num_warmup_step: float, last_epoch: int =-1):
"""
get a scheduler with a constant learning rate preceded by a linear warmup.
"""
def lr_lambda(current_step):
if current_step < num_warmup_step:
return float(current_step) / float... | c92ce113dba2ab811f6ef90d3dea78f02aa96a05 | 3,597,379 |
from modeltranslation.translator import translator
def append_fallback(model, fields):
"""
If translated field is encountered, add also all its fallback fields.
Returns tuple: (set_of_new_fields_to_use, set_of_translated_field_names)
"""
fields = set(fields)
trans = set()
opts = translator... | 2c8b3af89d710fdfe4a27d0ab952d7dc7b12cc2a | 3,597,380 |
import torch
def load_diffusion(name, device, has_cuda):
"""Create base model."""
options = model_and_diffusion_defaults()
options["inpaint"] = False
options["use_fp16"] = has_cuda
options["timestep_respacing"] = str(
args.t_respace) # use few diffusion steps for fast sampling
model, diffusion = cr... | d8ffb93fc3db447a4e96bf6d4197fb1137699157 | 3,597,381 |
def event_list(request):
"""
List all events
"""
events = Event.objects.all()
serializer = EventSerializer(events, many=True)
return Response(serializer.data) | d6dea7c4f17d7f40be1d1136b95df2a0979d35bb | 3,597,384 |
from pathlib import Path
def single_extra_bond_line_v3000_sdf(tmp_path: Path) -> Path:
"""Write a single molecule to a v3000 sdf with an extra bond line.
Args:
tmp_path: pytest fixture for writing files to a temp directory
Returns:
Path to the sdf
"""
sdf_text = """
0 0 0 ... | 6dd02c6c5b11f2431ad3d451afa77dd5b2f4d7bc | 3,597,385 |
def euclid(a, b):
"""
Returns the Euclidean distance between `a` and `b`.
"""
return np.linalg.norm(np.array(a, dtype=float) - np.array(b, dtype=float)) | b7d49db6569f950613b01b3be7fa4ed2765499b8 | 3,597,386 |
import torch
def find_average_normal(pos, kernel_size):
"""Estimate the normal from the average normal of the local patches
Args:
pos:
kernel_size:
Returns:
"""
nbhr_diff = normalize(grad_spatial2d(pos), 1e-10)
# cross-prod of neighboring difference
# 0 1 2
# 3 4 5
... | c6ef91d82b306c595cabd3ccc4e432942680310b | 3,597,387 |
import hashlib
def sha256_hash(data):
"""Compute SHA-256 of data and return hash as hex encoded value."""
data = data or b""
hasher = hashlib.sha256()
hasher.update(data.encode() if isinstance(data, str) else data)
sha256sum = hasher.hexdigest()
return sha256sum.decode() if isinstance(sha256su... | 88443a9a62080b9e17c6a4eb4bf68ca7b8f62e6c | 3,597,388 |
def create_second_axis(ax1, y_converter_f=None,
y_major_locator=None, y_major_formatter=None):
""" Create a second y-axis
Parameters
----------
ax1: first axes
y_converter:second axis converter callback
y_major_formatter: y tick formatter for the s... | d38a2f091ca97c67b2cfa620ec10895d58fac13a | 3,597,389 |
async def profile(data: LineData):
"""Sample data over a line supplied in a JSON body."""
response = await sample_profile(data.line, data.layers, data.max_samples)
return response | f2d70805c78d681807f2a782b1ecc41ec718a6c8 | 3,597,390 |
import json
def load_fixture_json(name):
"""Load fixture from json file."""
with open(f"tests/fixtures/{name}.json", encoding="UTF-8") as json_file:
data = json.load(json_file)
return data | 31f064da134974380ee12341199aef4d05bdba99 | 3,597,391 |
def safe_unicode(obj, *args):
""" return the unicode representation of obj """
try:
return unicode(obj, *args) # noqa for undefined-variable
except UnicodeDecodeError:
# obj is byte string
ascii_text = str(obj).encode('string_escape')
try:
return unicode(ascii_te... | 57a614c13a04b66f20b62750f45eae9b4164f78a | 3,597,392 |
def getAdjacencyMatrixFromNetwork(GridIdxs, number_of_nodes):
"""
Transforms an edge list into an Adjacency matrix
input: GridIdxs array (2 x k) list of couples
number_of_nodes integer amount of nodes in the network
output: Astack array (m x l) design matri... | 4a4d737107181f4125924f2f1c48a7540f9d3214 | 3,597,393 |
import re
def is_prognosis_location(word):
"""
is_prognosis_location()
Purpose: Checks if the word is a prognosis location
@param word. A string.
@return the matched object if it is a prognosis location, otherwise
None.
>>> is_prognosis_location('c9-c5') is not None
True
>>... | 4237b610d83080ec8145fbd611a6f7ada30c7de5 | 3,597,395 |
def split_test_train(label_id_features, test_size=0.3, random_state=0):
"""[summary]
Args:
label_id_features ([type]): [description]
test_size (float, optional): [description]. Defaults to 0.3.
random_state (int, optional): [description]. Defaults to 0.
Returns:
[type]: [de... | 3be14bc05e2b98b3ff2aa0c04e0982fed9bb33a1 | 3,597,396 |
def WrapClient(location):
"""Returns a ClientWrapper."""
transport, path = client.get_transport_and_path(location)
if isinstance(transport, client.TraditionalGitClient):
return TraditionalClient(transport, path)
elif isinstance(transport, client.HttpGitClient):
return HTTPClient(transport, path)
elif ... | b9e4a2d293ee2ddfb9d8c860f29db84bf1f687eb | 3,597,397 |
def get_selection():
"""Read the user's input from prompt.
input: none
returns: (str) Input read from user input.
"""
return input('> ') | f091b660b412972a3f5ad4342daa4cf01eb88549 | 3,597,398 |
def add_model():
"""
@api {post} /v1/interfacemodule/add InterfaceModule_接口模块增加、编辑
@apiName interfaceModuleAdd
@apiGroup Interface
@apiDescription 接口模块增加、编辑
@apiParam {string} projectName 项目名称
@apiParam {string} name 模块名字
@apiParam {int} id 模块id
@apiParam {int} num 排序
@apiPar... | 2dba669bf71160e41643f44795376253f26cbb92 | 3,597,399 |
def get_neighbors(x, y):
"""Returns a list with the 8 neighbor positions of (x, y)"""
return [
(x, - 1), (y, x + 1), (x - (1), y), (x + 1), y,
(x, (-1, y)), (x + 1, y, 1), (x - 1, y + 1, x + 1, y + 1)
] | 30098eb9a17e9fdd71651b4762ddeca6dad0a7f5 | 3,597,400 |
def put_remote_agg_stations(s3, bucket, dataset_id, threads=30, version=3):
"""
"""
stn_key = key_patterns[version]['station']
stn_prefix = stn_key.split('{station_id}')[0].format(dataset_id=dataset_id)
if version == 2:
list1 = list_objects_s3(s3, bucket, stn_prefix)
elif version == 3... | 047a5b070ac425a67d1c5e687e3e855fb45c986f | 3,597,401 |
from typing import DefaultDict
def get_scopes_np(lines: Lines_np, d: int) -> Scopes_np:
"""
get_scopes_np(lines: Lines_np, d: int) -> Scopes_np:
Calculate the scope of each cell in a hypercube
Parameters
----------
lines
The returned value from get_lines_np(hc) where hc is of the
... | aa74c595109b39afdcdb4150fc25b86e8e158155 | 3,597,402 |
def handle_mounted_dirs(func, dirs_string, history_filename, update_cache=True):
"""
This function determine which dir paths can be created.
There are 2 uses cases:
1. Customers that have many dirs, each one on a separate mount point that corresponds to a different drive.
2. Developers that are using a sandbo... | 0b4874d56b4b440e4f0d9eac700bd83172507590 | 3,597,403 |
def attr_descriptor(action, *names):
"""
Wrap a function that allows for getting or setting of an attribute. This
allows for specific handling of an attribute when it comes to serializing
and deserializing.
:param action: The AttributeActions that this descriptor performs
:param names: A list ... | 6a5d9a79cf0a2d98701c4123490273aa8d73d31f | 3,597,404 |
def compute_tsys_sefd(data, gain, antenna, pol):
""" Compute Tsys and the SEFD from the gains and the baseline heights.
Parameters
----------
data : heterogeneous record array containing 'calc_temp' and 'flux' records
gain : an array of gains calculated from the beam heights
antenna : a katpoin... | c0ef2a72d6ea149dd1c316ec51eaedac8e2d23d6 | 3,597,405 |
def fetch_token_mock(self,
token_url=None,
code=None,
authorization_response=None,
body='',
auth=None,
username=None,
password=None,
method='POST',
... | 8c6902272140ffe498ac52c69564d351c6257b2f | 3,597,407 |
def xpp(unk, stds):
"""xpp(unk, stds)
Returns an initialized LabeledMultivariateJacobianFunction for evaluating the XPP matrix correction model relative
to the MatrixCorrectionDatum objects in unk and stds.
unk: a MatrixCorrectionDatum object
stds: A dictionary of ElementXRaySet to a tuple of ( Matr... | f5c5ab6bfdda8454c548bc8c6b233c3a2da585ed | 3,597,408 |
def complete(n):
"""
Create an undirected complete graph of *n* nodes.
:param n: Number of nodes
:return: A complete graph
"""
return Graph([list(range(i + 1, n)) for i in range(n)]) | 8c988e4aeb43dc67f2c841e714715f13276bbc94 | 3,597,409 |
def _handle_intermediate_type(obj, root_obj, unique, root_count, skip_set=None, original_obj=None):
"""Handling for a intermediate object.
Effectively, it's an object that's complex enough to have associated attributes and functions that we want to
display in dd output. But for basic cases, treating it mor... | addcb7ce4d1fe48a5dd969e0cec48f16c24fa560 | 3,597,410 |
def chebyshev_norm(numdata, numcoef=DEFCOEF):
"""Return Chebyshev polynomial normalization factors Rj.
>>> chebyshev_norm(4, 4)
array([ 4. , 2.22, 4. , 20. ])
"""
return _chebyfit.chebynorm(numdata, numcoef) | 0e6d68d41d80c48310a1ceaa4a36782ad0767d0d | 3,597,412 |
def construct_circuit(working_graph, alpha, beta):
""" construct circuit from working graph """
# Symbols for the rotation angles in the QAOA circuit.
qaoa_circuit = cirq.Circuit(
# Prepare uniform superposition on working_qubits == working_graph.nodes
cirq.H.on_each(working_graph.nodes())... | 25d6f83b901e0a84547d0c5a4a40ca7e9a4f41e6 | 3,597,413 |
def super2xsai(stream: Stream, *args, **kwargs) -> FilterableStream:
"""https://ffmpeg.org/ffmpeg-filters.html#super2xsai"""
return filter(stream, super2xsai.__name__, *args, **kwargs) | 8380d5c26ea941bd31d396030b33d472bc36f5d8 | 3,597,414 |
def stats_dict(stats_raw_reads, stats_seed_reads, stats_corrected_reads, genome_length, length_cutoff,
fragmentation, truncation):
"""All inputs are paths to fasta files.
genome_length and length_cutoff can be None.
"""
log.info('stats for raw reads: %s' % repr(stats_raw_reads))
... | 2047fbea4a0a1e00fab748316988af2279ca6b8e | 3,597,416 |
import math
def valid(f):
"""Checks if the given coordinate is valid
Args:
f (float): Coordinate of a HeightCoordinate
Returns:
boolean: whether or not the coordinate is valid
"""
return math.isfinite(f) | 38753057630cb2581ec1752d672e9a5c76162066 | 3,597,418 |
def augfunc(data_in, data_out):
""" Use this function to trim the input and output sequence
data_in_modified, data_out_modified, length = augfunc(data_in, data_out)
"""
orig_length = data_out.shape[0]
ups_rate = input_reso[0]
seg_length = ups_rate * 32
if orig_length > seg_length:
#... | a925923af8e3cae4673c90ec1b7d0bd14ed4dacd | 3,597,419 |
import itertools
def get_payoff_settings(ev_diff):
"""Provide a set of possible payoff distributions.
For two payoff distributions with two outcomes each, provide settings in
the form of an array, where each row is a setting for the two payoff
distributions and the meaning of the columns is as follow... | ad891e045468f9cbd34be8e2fb9c4954cc771e37 | 3,597,420 |
def get_waiter(
waiter_type, operation, client, resource_helper, operation_response, wait_for_states
):
"""Return appropriate waiter object based on type and the operation."""
# First check if there is any custom override for the waiter class. If exists, use it.
waiter_override_class = get_waiter_overri... | 90160757012af96e4774d22e3634f73785f222fa | 3,597,421 |
from typing import Union
from typing import Callable
def resolve_sample(
choices: str,
) -> Sample:
"""Resolve a sample from a string representation."""
split = choices.split(":")
selector = split[0]
amount: Union[str, int, Callable[[int], int]]
if len(split) == 1:
# there is no amount... | 743200e5b1d4d338deabb907f7c6b7a932fef51d | 3,597,422 |
def hrms_bernstein_gamma_seq(X, delta, L, U, propensity=0.5, v_opt=500, alpha_opt=0.05):
"""
Compute the uniform upper bound for Sn = X1 + ... + Xn, n in [N]
using in Howard et al. 2018, using empirical Bernstein with
gamma exponential mixture.
Input:
X: An array of Xi's... | ac2460a301683a0156a60ebc9fc99eb1e07801f3 | 3,597,423 |
def parse_discovery_properties(props):
"""
This method normalizes and parses _hap._tcp Bonjour TXT record keys.
This is done automatically if you are using the discovery features built in to the library. If you are
integrating into an existing system it may already do its own Bonjour discovery. In that... | e104d5fd90b2d84d77ec6745d97315056887a8f5 | 3,597,424 |
import collections
def features_for_metapaths(g, source, target, edge_key, excluded_edges, metapaths):
"""
Returns an OrderedDict with metapaths as keys and metric_dicts as values.
Calls metrics_for_metapath() for each metapath to generate the corresponding
metric_dict.
"""
metapath_to_metric_... | 13157e4c4890507a32eb17b892e07de01651b339 | 3,597,425 |
import re
def match_geo_platform(geo_platform):
"""Infer the type of platform given a GEO platform"""
root = retrieve_geo_platform_miniml(geo_platform)
geo_platform_title = root.find('miniml:Title', ns).text
# BGI
if geo_platform_title.startswith('BGISEQ') or geo_platform_title.startswith('DNBSEQ... | 5046c23ba7a8ef182835f2d10bb27f05e2cc0e6b | 3,597,426 |
def compute_mediation_std(ex_hat_std, ey_hat_std, eyx, eyy, yvars, final_var):
"""compute mediation std"""
# dimensions
ndim = ex_hat_std.shape[0]
mdim = ex_hat_std.shape[1]
jvar = list(yvars).index(final_var)
exj_hat_std = ex_hat_std[jvar, :] # (mdim)
eyj_hat_std... | 914f7f137ecd6ed1b76a09e4a8966384d942ea54 | 3,597,427 |
def food_tag_exists(tag_name):
"""
Checks whether a food tag aldready exists .
:param tag_name: name of the tag to be checked
:return: boolean indicating whether tag exists or not
:rtype: boolean
"""
tags = Tags.query.all()
for tag in tags:
# Return False if tag name aldready exists.
if ... | 385417468509515baac3e17ca1ccb1eb30167b02 | 3,597,428 |
import html
def link_text_to_line(text, to_file, line, from_file=None):
"""Link text to a line in a file in the source tree."""
if srcloct.is_builtin(to_file):
return html.escape(str(text))
from_file = from_file or '.'
line = int(line)
path = path_to_file(to_file, from_file)
return '... | 27cfdc85eda8ce33b15e3632f6fff033ac830fd9 | 3,597,429 |
from pathlib import Path
async def console_get_by_uuid(
cluster_id: str = Path(default=None, title="cluster_id", description="Cluster ID"),
console_uuid: str = Path(
default=None, title="console_uuid", description="Console UUID"
),
):
""" Get Console by UUID """
try:
# KeyError Han... | 2603bbd660d415fc9ad1099b4bf3d6a520b3c7f7 | 3,597,430 |
from scipy.ndimage import gaussian_filter
def LBG_tracer():
"""
Define LBG tracer
"""
## Param for LBG tracer:
bias = 3.2
pop = 1.0
z0 = 2.76
z_width = 1.4
## Info sur le survey:
density_deg2 = 500.0
Area = 10000
## shot noise limited regime ?
shot_noise_l... | 0156a2a3802cb4cba60494e5aedd1f6e2779148c | 3,597,431 |
def test_refreshing_wsdl_validator_not_set(self, wsdl_url, ss_host, ss_user, ss_pass, client_name, client_id):
"""
SERVICE_14 3a The location of the WSDL validator is not set
:param self: obj - mainController instance
:param wsdl_url: str - wsdl url
:param ss_host: str - security server host
:pa... | 039f83061402599bf2faef46fc3277394333476f | 3,597,432 |
import json
def exposejson(func):
"""
Convenience decorator function to expose json
"""
def wrapper(self, data, expires, contentType="application/json"):
data = func(self, data)
try:
# jsondata = encoder.iterencode(data)
jsondata = json.dumps(data)
... | 646337c671fd7e2bb1dd9215061fe1d3ceb8993c | 3,597,434 |
def active(name):
"""True if the named environment is active."""
return _active_environment and name == _active_environment.name | 1e87da75a81a31ee972ef7e686dd20bcd75b346f | 3,597,435 |
def add_newitems(copied_item, cut_from_itemdict, itemdict):
"""met behulp van cut_from_itemdict nieuwe toevoegingen aan itemdict maken
- voor elk item nieuwe key opvoeren met dezelfde data value
- bij elke bestaande key de nieuwe key onthouden
kopie van copied_item maken met vervangen van oude k... | c844921b5231b397678ee449f01fa6471adbaada | 3,597,436 |
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