content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def compare_lr_test(model_result, restricted_result):
"""
Likelihood ratio test to test whether restricted model is correct
Parameters
----------
model_result : Result instance
restricted : Result instance
The restricted model is assumed to be nested in the current model.
The r... | 3169cc7c8d1f18176a2ed744409649ec0a14a045 | 3,602,563 |
def vgg13_bn(num_classes=1000, pretrained='imagenet'):
"""VGG 13-layer model (configuration "B") with batch normalization
"""
model = models.vgg13_bn(pretrained=False)
if pretrained is not None:
settings = pretrained_settings['vgg13_bn'][pretrained]
model = load_pretrained(model, num_cla... | 935ff120fbee9319840f270412ae262266bb2aec | 3,602,564 |
def absolute(operand: ValueOrExpression) -> Expression:
"""
Constructs an absolute value expression.
"""
return ArithmeticUnary(operators.ArithmeticUnaryOperator.ABS, ensure_expr(operand)) | 39888a9108d1cabbe45cad58c11c1ba39912ba8a | 3,602,565 |
def covariance_matrix(X):
"""
Args:
X (ndarray) (m, n)
Return:
cov_mat (ndarray) (n, n):
covariance matrix of X
"""
m = X.shape[0]
return (X.T @ X) / m | 128d9bfe12169cb344c150bf9f8f05565b5a8831 | 3,602,566 |
import operator
def filter(array, *args, foos_filtering=[operator.gt, operator.lt], **kwargs):
"""general filter function for escape arrays. checking for 1D arrays, applies
arbitrary number of
filter functions that take one argument as input and"""
if not np.prod(np.asarray(array.shape)) == array.shap... | 825290fa49ae66455e6b8c5edd840c3d6d51d996 | 3,602,567 |
def sigmoid_deriv(x):
"""
Calculates the sigmoid derivative for the given value.
:param x: Values whose derivatives should be calculated
:return: Derivatives for given values
"""
return x * (1. - x) | 8a7a1005fafb1b34c17c6ce4a8a04f80334e396a | 3,602,568 |
from typing import Mapping
def UpdateDict( target, override ):
"""Apply the updates in |override| to the dict |target|. This is like
dict.update, but recursive. i.e. if the existing element is a dict, then
override elements of the sub-dict rather than wholesale replacing.
e.g.
UpdateDict(
{
'outer... | a07a3d7989e227ff1759271248777e167b7e5467 | 3,602,569 |
def calculate_propensity(kinetic_rates, lattice_state):
""" Calculate the propensity for each event type
Parameters
----------
kinetic_rates : list
kinetic rates as defined in sim_parameters.py
lattice : numpy.ndarray
current lattice state
Returns
------
event_propensit... | d689a5cd09930eaa881ce11d37c3ec006a20b37d | 3,602,570 |
def fib(n):
"""calculate fibonanchi"""
if mem[n] != 0:
return mem[n]
if (n <= 1):
return n
mem[n] = (fib(n - 1) + fib(n - 2))
return mem[n] | c9b5976411143f4e5be93cf3849c651b521ba6d9 | 3,602,572 |
def calc_sharp_v_scan(t, v, res_points=10):
"""Calculate the discontinuous rate of change of v with respect to t
Args:
t (np.array): the data of the independent variable, typically time
v (np.array): the data of the dependent variable
res_points (int): the resolution in data points, i.e... | cac85ac0a6a1ad9fcd13e83569b21dcfb01370d0 | 3,602,574 |
def traer_mayor_24_doge():
""" This function returns the highest price of the last 24 hours """
newxd = MySQLdb.connect(host=MY_H, user=MY_U, passwd=MY_P, db=MY_D)
consulta = newxd.cursor()
consulta.execute("SELECT price FROM history_coin WHERE name='DOGE' ORDER BY price DESC LIMIT 1;")
resultado =... | ae093cf25290aee5eedaf14bdb18431b57910efb | 3,602,575 |
def run_adaptive_grid(gdf, rtree, G, params, types, topk_regions, start_time, updates):
"""Executes the AdaptiveGrid algorithm. Employs a top-tier grid to identify promising cells and then applies ExpandBest over seeds that may be chosen using Bayesian optimization within those cells.
Args:
gdf: A... | ccf7d65302f9b59d14ef1dd65c896092c3a25b2c | 3,602,578 |
from pathlib import Path
import uuid
def get_filename(filename):
"""CKEditor - Filename Generator"""
extension = Path(filename).suffix
return '{0}{1}'.format(uuid.uuid4(), extension) | 50988191c0145e686b38306a6f1bfd686d4dff25 | 3,602,579 |
def NewtonRaphson(funcion, tolerancia, maxIteraciones, semilla):
"""
La tolerancia y numero de iteraciones tienen que ser positivos.
La semilla debe de estar cerca del intervalo, caso contrario no va a converger.
"""
historia = np.zeros((maxIteraciones, 3))
if tolerancia < 0 or maxIteraciones < ... | 1bb85b2663d732cb094e90645ed27252fb53fdcb | 3,602,580 |
def IntToStr(input_bvv):
"""
Returns the string representation of the integer expressed in the BitVector
:param input_bvv: the integer expressed as a BitVector we want to convert as a string
:return: the string representation of the integer
"""
return StringV(str(input_bvv.value)) | e92961fa876fd5047dc0715db40de13e2d5f89c5 | 3,602,581 |
def tee(cmd, cwd=None):
"""
executes a command, echoing output and buffering it
for later use by the program. returns (exit_code, output)
"""
pipe = subprocess.Popen(cmd, stdout=subprocess.PIPE, stderr=subprocess.STDOUT, cwd=cwd, shell=True)
output = []
while True:
if pipe.poll() i... | 8be56162728cda2711803251e441f35c8a993e6d | 3,602,582 |
def dss_target(request):
"""
This is a parameterized fixture. Its value will be set with the different DSS target (DSS7, DSS8 ...) that are specified in the configuration file.
It returns the value of the considered DSS target for the test. Here it is only used by other fixtures, but one could use it
a... | 0aa9f85160280032dfdea872b7c9a147a5717523 | 3,602,583 |
from typing import Tuple
def get_contours_iou(contour1, contour2, image_size: Tuple = None, plot=False):
"""
计算两个轮廓(多边形)交并比(Intersection-over-Union,IoU)
:param contour1: 多边形1 (num_points,2),由num_points个点构成的封闭多边形
:param contour2: 多边形2 (num_points,2),由num_points个点构成的封闭多边形
:param image_size: (W,H) im... | 11b307f984b467eaacfe11042b4e5056d1eca0cc | 3,602,584 |
from typing import Dict
import uuid
def cancel_run(
config: Dict,
celery_app: Celery,
run_id: str,
*args,
**kwargs
) -> Dict:
"""Cancels running workflow."""
collection_runs = get_conf(config, 'database', 'collections', 'runs')
document = collection_runs.find_one(
filter={'run_... | bb112b763c47328c247102a9485d20b4982b76c6 | 3,602,586 |
import re
def _clean_name(name):
"""
This function sets the name of a recipe to the standard naming
convention specified
"""
name = re.sub(r'\s', "_", name)
return name.lower() | 940792220aa6eabfcf067c6450f30bca66d1b214 | 3,602,587 |
def get_base_dict():
"""Get basic dictionary containing special tokens."""
return {
TOKEN_PAD: 0,
TOKEN_UNK: 1,
TOKEN_CLS: 2,
TOKEN_SEP: 3,
TOKEN_MASK: 4,
} | 166f420317455c14045911d84acf18cbac3d9070 | 3,602,588 |
def label_data(dictionary, images):
"""
Labels the data depending on patient's diagnosis
Parameters
----------
dictionary: Dict with patient information
images: Names of images to label
Returns
-------
Labeled data
"""
data = []
last_patient = ''
aux = []
for img... | 01eb965d4cff7a8d4242eeb57e43fe3d72ee74f9 | 3,602,589 |
from pathlib import Path
import csv
def save_csv(csvpath, data, header):
"""Save data & header as a csv output file in the path provided.
Args:
csvpath (Path): The csv file-path where the output data will be saved
data (list of list): list of list with the same number of elements that can be ... | d9e592842a7c428f1165e290e51b17d959a76bd9 | 3,602,590 |
def gym_size(gym):
"""Returns the size of the gym."""
return len(gym) | b31a46a7b56e973da8dfa0cac9950fad14b48622 | 3,602,591 |
def is_houdini_paste_event(uievent: KeyboardEvent) -> bool:
"""Check whether or not the event is an item paste event.
:param uievent: The occurring keyboard event.
:return: Whether or not the event is a paste event (h.paste).
"""
return setKeyPrompt(uievent.editor, uievent.key, "h.paste", uievent.... | 84c2c60369b790546755f2d31a39950ad6f68ac0 | 3,602,592 |
import json
def get_outputs(file_name, pretty_quotes=False):
"""Read outputs from notebook."""
with open(file_name) as file:
saved_cell_outputs = defaultdict(lambda: None)
nb_cells = json.load(file)["cells"]
for cell_index, cell in enumerate(nb_cells):
if "outputs" not in cell:
continue
... | 69c116b1f63890f476a835a2d0682ac65af71735 | 3,602,593 |
def dump(obj, file=None, file_format=None, **kwargs):
"""Dump data to json/yaml/pickle strings or files.
This method provides a unified api for dumping data as strings or to files,
and also supports custom arguments for each file format.
Args:
obj (any): The python object to be dumped.
... | 16068381f3f1fa1a80b2f8c8b31702dbdbfcb08a | 3,602,595 |
def is_call_id_in_video_state(log, ad, call_id, video_state):
"""Return is the call_id is in expected video_state
Args:
log: logger object
ad: android_device object
call_id: call id
video_state: valid VIDEO_STATE
Returns:
True is call_id in expected video_state; Fal... | d0da323a21a23d461fc2aec06ac5d0bebac7cbef | 3,602,596 |
def call_torch(func, arg, *args, dtype=None, device=None, batch_size=64):
"""Call a torch function with numpy arguments and numpy results."""
args = (arg, *args)
index, values = flatten_with_index(args)
result_batches = []
for start in it.count(0, batch_size):
end = start + batch_size
... | 75f3b6d62b374e3c3fff1e3f5db1d60faf05b7d5 | 3,602,597 |
import time
def gstat_elapsed(metric):
"""
decorator that logs the elapsed time spent in the decorated method
"""
def wrap(f):
def wrapped_f(*args, **kwargs):
start_time = time.time()
ret = f(*args, **kwargs)
gstat(metric, time.time() - start_time)
... | b1ad90f1004f66d5f3a6694104d2b62eb6550eb8 | 3,602,598 |
def interpolate_points(
line: "shapely.geometry.linestring.LineString",
num_pts=5) -> list:
"""
Create a list of multipoints for the interpolated points along each linestring
Arguments:
-----------
line: "shapely.geometry.linestring.LineString"
shapely.geometry.linestring.Lin... | 4f5142d325b228602654806ed8aef8f54ffd15a6 | 3,602,599 |
def pressure_to_eta(del_p, wavenumber, device_d, water_d):
"""Convert the non-hydrostatic pressure to height above device_d=0."""
return del_p / _coefficient(wavenumber, device_d, water_d) | 26718e66164d236ae8d8f7b5bd1618b4a36ccefd | 3,602,600 |
def init_net(net, init_type='normal', init_gain=0.02, gpu_ids=[],init_weight=True):
"""Initialize a network: 1. register CPU/GPU device (with multi-GPU support); 2. initialize the network weights
Parameters:
net (network) -- the network to be initialized
init_type (str) -- the name of an... | b8d5e6185b247cc96b2774479aa065c7a5211b70 | 3,602,601 |
def confirm_pw(username, pw, pw_hash):
"""Verify a password for a given user."""
salt = pw_hash.split(',')[0]
return make_pw_hash(username, pw, salt) == pw_hash | a479b45499701ccdd82d596eef99cb6f0c063bc2 | 3,602,602 |
def run_bandit(params, means, variances, experiment):
"""
Performs the bandit->environment->attacker interaction for a number of trials.
Arguments:
params (Python dict): holds parameter values of interest (see main.py)
means (np.ndarray (n_arms,)): mean of the reward distribution assoc... | 293dae01227319f7924b21bd837bd10708cff85b | 3,602,604 |
def predicted_effects_for_variant(
variant,
transcript_id_whitelist=None,
only_coding_transcripts=False,
only_coding_effects=False,
require_mutant_protein_sequence=False):
"""
For a given variant, return its set of predicted effects. Optionally
filter to transcripts w... | 69ea8e1b078d0e0bac9759d744f64b823009f26a | 3,602,605 |
from typing import Tuple
def __coord_on_finish(
piece_number: int, player_number: int, piece_progress=0
) -> Tuple[int, int]:
"""Piece number is irrelevant
>>> __coord_on_finish(1, 0, 57)
(9, 3)
>>> __coord_on_finish(1, 0, 61)
(9, 7)
>>> __coord_on_finish(1, 1, 57)
(3, 9)
>>> _... | 41dac0a68d63fe738726c2a97bddaa236a536766 | 3,602,606 |
def _extract_spots_outside_foci(cell_cyt_mask, spots_out_foci):
"""
Extract spots detected outside foci, in a specific cell.
Parameters
----------
cell_cyt_mask : np.ndarray, bool
Binary mask of the cell with shape (y, x).
spots_out_foci : np.ndarray, np.int64
Coordinate of the ... | d4e06d9ad14ced3b8984b71c32d9d3b1e0cebaae | 3,602,607 |
def augment(im, augment_str):
"""Augments image (used for training)."""
if augment_str:
im = Image.fromarray((im * 255).astype(np.uint8))
im = make_augment(augment_str)(im)
im = np.asarray(im).astype(np.float32) / 255
return im | c35d72fc97a56ac11f31862fc7bb16bebb3a9b9e | 3,602,608 |
def aoc_string(data):
"""Read AOC string."""
length = unpack('<h', data)
return data.read(length) | a765759b94cb5cf693956d95abc07c70c839e077 | 3,602,609 |
import dateutil
def parse_date(date_string):
"""Parse a timestamp
If it doesn't have a timezone, assume utc
Returned datetime object will always be timezone-aware
"""
dt = dateutil.parser.parse(date_string)
if not dt.tzinfo:
# assume naive timestamps are UTC
dt = dt.replace(t... | fe858fef9e454afa3352849733e9282e14be18b6 | 3,602,611 |
from re import T
def nzseel2():
"""
RESTful CRUD controller
"""
tablename = "%s_%s" % (module, resourcename)
table = db[tablename]
# Pre-populate Inspector ID
table.person_id.default = s3_logged_in_person()
# Subheadings in forms:
s3db.configure(tablename,
deletable... | e67223a2216d47b28f3175339a9ec160cf836e80 | 3,602,612 |
def End_Net(input_x, phase_depth, keep_prob):
"""
Define Aggregation Network
"""
weights, summaries = End_Net_weights_init()
layer8 = conv2d_batchnorm_init(input_x, weights[0], name="conv_9", phase= phase_depth, stride=[1,2,2,1])
layer9 = conv2d_batchnorm_init(layer8, weights[1], name="conv_1... | 06036b2d05a841e43a9970be7033ee1537671606 | 3,602,613 |
import base64
def decrypt(cipher_text, working_key):
"""
Method decrypt cc-avenue response.
:param cipher_text: encrypted data
:param working_key: working data
:return: list
"""
cipher_text = base64.b64decode(cipher_text)
iv = cipher_text[:AES.block_size]
cipher = AES.new(bytes(wo... | 8786af7539378c069690513fc665bb5d84b830ef | 3,602,614 |
from datetime import datetime
def get_start():
"""
Helper function to retrieve the start of the time period from which to gather stock data
"""
weekdays = ['Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday', 'Saturday', 'Sunday']
day = weekdays[datetime.today().weekday()]
now = datetime.today()
if day in... | d79886240011a0e7c56cf9c11c93fb8569ef57a1 | 3,602,615 |
import io
def get_custom_stopwords(stop_words_file):
"""
创建停用词list，
:param stop_words_file: 停用词文件
:return:
"""
with io.open(stop_words_file, encoding='utf-8')as f:
stopwords = f.read()
stopwords_list = stopwords.split('\n')
custom_stopwords_list = [i for i in stopwords_list]
... | d2e25e44815b6769688493a96852cc537d1127bf | 3,602,616 |
from typing import Union
def _hex(v: Union[LayerFieldsContainer, LayerField]) -> int:
"""parse the layer field as a hex string"""
# split v into octets and reverse the order
assert not isinstance(v, LayerFieldsContainer) or len(v.fields) == 1
return int(v.get_default_value(), 16) | 00e1dd102085866a44ed092fadf59e03d10eb0ba | 3,602,617 |
def read_bytes(vw, va):
"""
read up to MAX_BYTES_FEATURE_SIZE from the given address.
raises:
envi.SegmentationViolation: if the given address is not valid.
"""
segm = vw.getSegment(va)
if not segm:
raise envi.SegmentationViolation()
segm_end = segm[0] + segm[1]
try:
... | e2a94adff54cd97c7d36f661a3cd14bd18182ccb | 3,602,618 |
def extract_image_number(filename: str, from_file: bool) -> int:
"""
finds the number of the image from the original images of LITIV 2014 dataset.
:param filename: name of the image file.
:param from_file: filename is read from a ground-truth file or not.
:return: number.
"""
number = filena... | e55431beffb02959907106a01596310812ba7363 | 3,602,619 |
def subarraySum(nums, k):
"""
Given an array of integers and an integer k, you need to find the total number of continuous subarrays whose sum equals to k.
"""
count = 0
s = 0
for i in range(len(nums)):
s += nums[i]
if s % k == 0:
count += 1
return count | 6bbad5ec5511f8563fc951aa916f76a6297946ba | 3,602,620 |
def traffic_sign_detection_noisy(img_in):
"""Finds all traffic signs in a synthetic noisy image.
The image may contain at least one of the following:
- traffic_light
- no_entry
- stop
- warning
- yield
- construction
Use these names for your output.
See the instructions docume... | 50a5430fbe793a6bc863c92378c44522822ce7a3 | 3,602,621 |
def get_planet_variables(mc, theta, verbose=False):
"""
Derived parameters from the Common Models are listed
:param mc:
:return:
"""
try:
n_samplings, n_pams = np.shape(theta)
except:
n_samplings = 1
stellar_values = get_stellar_parameters(mc, theta)
planet_variabl... | 573a84f22734508d22d9887155fc28604fe2079a | 3,602,623 |
def get_container_by_container_id(container_id):
"""
lookup task id based on matching container id
:param container_id: str. container_id is a unique string generated by the docker daemon
for each instance of a container
:return: str. task id
"""
if len(container_id) <= 12:
query = '... | 8e53a998e917ed6929bcee7116ebdc0f3297bddd | 3,602,625 |
def calculate_arc_length(x1, x2, origin):
"""
Calculate the arc length between points x1 and x2.
:param x1, x2: points coordinates.
:return: arc length
"""
r1 = vector.addVectors([x1, origin], [1, -1])
r2 = vector.addVectors([x2, origin], [1, -1])
radius = vector.magnitude(r1)
angle ... | cef209b2b1556700416131e56230bd37196ac956 | 3,602,626 |
def find(data,fwhm=4,thresh=4000) :
""" Star finding using DAOStarfinder
"""
daofind = DAOStarFinder(fwhm=fwhm,threshold=thresh)
sources=daofind(data)
sources.rename_column['xcentroid','x']
sources.rename_column['ycentroid','y']
return sources | befde70505c3567e86d1b33cdb22bacfab19129b | 3,602,627 |
import functools
from datetime import datetime
def cache(ttl=CACHE_DEFAULT_TTL):
""" TTL Cache Decorator
Parameters
----------
ttl: datetime.timedelta
Time-To-Live
Returns
-------
function
Wrapped Function
"""
def wrap(func):
cached = {}
@functool... | f2fbbeb4368ee629b4be4383d7ad80a49c03577f | 3,602,628 |
def make_ro_state(f):
"""
Build a read-only State instance and pass to `f` as the `state` kwarg if the `state` kwarg is None.
Function `f` should have have at least two kwargs, `user` and `state`.
"""
@wraps(f)
def state_check(self, *args, **kwargs):
state = kwargs.pop('state', None)
... | 4df20a8c81eed81b47fd10c92379ec8d58d0ec8a | 3,602,629 |
def get_changes_by_project(changes):
"""
Break changes into a dict of dicts keyed by project
"""
changes_by_project = defaultdict(dict)
for change in changes:
changes_by_project[change.project][change.long_id] = change
return changes_by_project | 76923ce721df8d68fc96ff63cf49a9aac3b0dce4 | 3,602,630 |
from typing import Any
from typing import Callable
from io import StringIO
def yaml_dumps(value: Any, get_yaml_obj: Callable[[], YAML] = get_yaml) -> str:
"""Converts the object to yaml.
:param value: the object to convert.
:param get_yaml_obj: A function such as :func:`get_yaml` that will be called
... | b12390989fc4c64722c38c8931f90906c8261991 | 3,602,631 |
def aaa_check_compute_auth_token(cookie, in_token, in_user):
""" Auto-generated UCS XML API Method. """
method = ExternalMethod("AaaCheckComputeAuthToken")
method.cookie = cookie
method.in_token = in_token
method.in_user = in_user
xml_request = method.to_xml(option=WriteXmlOption.DIRTY)
re... | 8e837e873ef4ca76f53f91e7ce92de79be568b3f | 3,602,632 |
def page_size(request, page_size):
""" Changes page size in user preferences"""
try:
u, created = User.objects.get_or_create(user=request.user.id)
u.pagesize = page_size
u.save()
return HttpResponse('saved pagesize %s' % page_size)
except Exception, inst:
return H... | 0e5bf12142d678481829ea3136d20a559db7c366 | 3,602,633 |
def fail_on_npm_install():
"""
Used to simulate an error when executing "npm install"
"""
return 1 | ea0b2b14487acf8b9833e84374de469a1b22b61a | 3,602,634 |
def calculateNetIncome(gross, state):
"""
Calculate the net income after federal and state tax
:param gross: Gross Income
:param state: State Name
:return: Net Income
"""
state_tax = {'LA': 10, 'SA': 0, 'NY': 9}
# Calculate net income after federal tax
net = gross - (gross * .10)
... | 915528d8bfd15c18003eaeb8f6b3f1e8ad5565a0 | 3,602,635 |
def calc_se3_torch_batch(poses_src, poses_tgt):
"""Bx3x4."""
# B = poses_src.shape[0]
se3_src2tgt_batch = se3_mul_torch_batch(poses_tgt, se3_inverse_torch_batch(poses_src))
return se3_src2tgt_batch | d5f2ce006ac08e8c92c463c3631a76e7574fd4c0 | 3,602,636 |
from typing import Union
def _rescale_proba(p: Union[float, pd.Series],
min: float,
max: float) -> Union[float, pd.Series]:
"""Performs min-max-scaling on a probability value"""
return np.abs((p - min) / (max - min)) | caacf603c5a02af15fd6bd640c79f3d3379d46b0 | 3,602,637 |
def build_tree(train: list, max_depth: int, min_size: int) -> dict:
"""
Build a decision tree
:param train: dataset used to build the tree
:param max_depth: of the desired tree
:param min_size: of the terminal nodes
:return:
"""
class_values = list(set(row[-1] for row in dataset))
ro... | 0a6170795677d41e0080aaff80c5758049789341 | 3,602,638 |
def field_size(field_label):
"""
Helper function to determine the size of a binary
table field
Parameters
----------
field_label : PVLModule
The field label
Returns
-------
int :
The size of the one entry in bytes
"""
data_sizes = {
'Intege... | afaff70bc18d4d9d023fb7c89d45560f1a691bcf | 3,602,639 |
def definite_range():
"""Create test fixture for Definite Range."""
return DefiniteRange(min=22, max=33) | 0296dd02adc5e890a0d6a020b1772ad0df91c76f | 3,602,640 |
def WaitForOperation(resources, service, operation, collection, resource_ref,
message):
"""Waits for the operation to finish.
Args:
resources: The resource parser.
service: apitools.base.py.base_api.BaseApiService, the service representing
the target of the operation.
operati... | 90de3bc3c6d49be10aee94af6eb55fcb6cc738aa | 3,602,642 |
def ListInstancesDNS(region, instances=None, node_types=[], states=[], names=[]):
"""Return a list of DNS names for instances matching the arguments.
If instance IDs are specified and one or more is not found, an EC2ResponseError exception is thrown.
"""
return [i.public_dns_name for i in ListInstances(region, ... | 20337bcbb97ca1a3602ec34276b1fb96b2e07747 | 3,602,644 |
def _calc_trans_distor(X: np.ndarray, labels: np.ndarray, Y: float) -> float:
""" Calculate transformed distortion function for the jump method """
_, means, _ = calc_stat_per_batch(X, labels)
distor = (((X - means.T[labels,:]) ** 2).sum() / X.shape[0] / X.shape[1])
trans_distor = distor ** (-Y)
re... | bcbc697833eb65c48abf9ba2e324c493a323c17a | 3,602,645 |
def bencode(thing):
"""
bencodes the given object, returning a bytes object
containing the bencoded data.
Allowed object types are:
- list (list)
- dictionary (dict)
- integer (int)
- string (str)
- bytes object (bytes)
Note that all strings will be converted to byte objects du... | e1c08941a37ce19873e50c33c682ecefbd24073c | 3,602,648 |
def slowSort(array):
"""Sort an array the slow (but certain) way"""
cpy = np.copy(array)
ind = np.arange(0, len(array))
for i in xrange(len(cpy)):
for j in xrange(len(cpy)):
if cpy[i] > cpy[j] and i < j:
# Swap the copy array values
tmp = cpy[i]
... | b110f6aa797c5ab64309a1e982de561445377f33 | 3,602,649 |
def GetBankElementSummary(bank_element):
""" Summarizes the bank element
params: bank_element = value of the object of type bank_element_t
returns: String with summary of the type.
"""
format_str = "{0: <#020x} {1: <16s} {2: <16d} {3: <16d}"
if bank_element.be_type == 0:
out_strin... | b14b9a9cb7744bc02958573bc22009fe075e893e | 3,602,650 |
def test_input(ctx):
"""
To get custom user input!
input: Yes/No
If yes
it stores value in user_input of context
"""
if ctx.get("user_input"):
print("We got: ", ctx.get("user_input"))
return
val = input("Say yes: ")
if val == "yes":
ctx["user_input"] = val
return RepeatStatement() | 28250a05ede180b7d8948a50d6ded526270b1b4f | 3,602,651 |
def _reference_before_setitem(self, key, value):
# type: (Object, str, Any) -> Tuple[str, Any]
"""
This hook allows for the use of any arbitrary attribute, as specified in
the `patternProperties` for this object in the OpenAPI schema
"""
if key != "$ref":
_add_property(self, key)
ret... | 38f5ff3bc96cddac89d3dea6008c9df63835d587 | 3,602,652 |
from typing import List
def _input_fn(file_pattern: List[Text],
data_accessor: tfx.components.DataAccessor,
tf_transform_output: tft.TFTransformOutput,
batch_size: int = 200) -> tf.data.Dataset:
"""Generates features and label for tuning/training.
Args:
file_pattern:... | 8afcf39ff01f8b9b3c643b4b4adccaf1c3586f4f | 3,602,653 |
def leading_by(agents, player):
"""Determine difference between player's score and closest opponent."""
scores = [a.score() for a in agents]
player_score = scores[player]
scores.sort()
if player_score == scores[-1]:
return player_score - scores[-2]
else:
return player_score - sco... | e97aa0a1109bb2ba5f276f34030ea1f93022046f | 3,602,654 |
import torch
def smiles2graph(mol):
"""
Converts SMILES string or rdkit's mol object to graph Data object without remove salt
:input: SMILES string (str)
:return: graph object
"""
if isinstance(mol, Chem.rdchem.Mol):
pass
else:
mol = Chem.MolFromSmiles(mol)
# atoms
... | 2547a07ca8f3beec6681b15c87666197fd58181a | 3,602,655 |
def is_valid(t: float):
"""
Returns a `bool` indicating if the given value for a t
parameter is valid.
A t parameter is valid if in the [0, 1] range.
:param t: `float` t parameter value
:return: `bool` is the t value valid?
"""
return False if t < MIN or t > MAX else True | 6e3ee60136ead77a9bc4ff6b84e3986f5b0532b3 | 3,602,657 |
def get_bid2sid(offsets, stc_lens):
"""
:param offsets: list of 1 tensor, offsets by doc
:param stc_lens: list of 1 list, stc length
:return: bid2sid: dict of int, blank id 2 stc id, both start from 0
"""
bid2sid, acc_len = dict(), 0
sid = 0
for bid, offset in enumerate(offsets[0]):
... | a5a96d3ea6c7fcb17a97df706799fe0716ae659b | 3,602,658 |
import random
def generate_easy_alphanumeric_string():
"""
Generates an "easy" alphanumeric (lower case) string of length 8 without the 0 (zero)
character. This is a design decision, because users will have to type in the "easy"
string on mobile devices, so we have made this a string that is easy to t... | 76c1b5e51344f726dffcd2800b31349427268f22 | 3,602,659 |
def create_abbreviations(metagraph):
"""Creates abbreviations for node and edge kinds."""
kind_to_abbrev = find_abbrevs(metagraph.node_dict.keys())
kind_to_abbrev = {kind: abbrev.upper() for kind, abbrev in kind_to_abbrev.items()}
edge_set_to_keys = dict()
for edge in list(metagraph.edge_dict.keys(... | 98eb8c0e158b592990a4850263a93be08d41f3a4 | 3,602,660 |
def mk_seealso(
function_name: str,
role: str = "func",
prefix: str = "\n\n",
module_location: str = ".",
) -> str:
"""
Returns a sphinx `seealso` pointing to a function.
Intended to be used for building custom fitting model docstrings.
.. admonition:: Usage example for a custom fittin... | 0165599829e8edd3f75adcda9402069066a0381a | 3,602,662 |
import torch
def get_accuracy(prototypes, embeddings, targets):
"""Compute the accuracy of the prototypical network on the test/query points.
Parameters
----------
prototypes : `torch.FloatTensor` instance
A tensor containing the prototypes for each class. This tensor has shape
`(met... | f196820e28258a24ed84a10b4829f3be6a0d68d8 | 3,602,663 |
def take_step(obj, step):
""" Takes a step towards a target obj """
temp_obj = getattr_or_get(obj, step)
if 'id' in step:
# if the step is an ID, we need to get the object represented by that id
model_str = step.split('_')[0].lower().capitalize()
if model_str != 'User':
... | 4366977af518df512c433c057bb3d675a3b8d6c9 | 3,602,664 |
def mock_xibo_api(mocker):
"""Return a mock XiboApi."""
return mocker.MagicMock() | 8c2ad1566ad716d9fb4dd680a624e59f89950a0a | 3,602,665 |
def get_corpus_archive_name(cycle: int) -> str:
"""Returns a corpus archive name given a cycle."""
return 'corpus-archive-%04d.tar.gz' % cycle | 3068ce88bd85f2c21819da697a2b1147f547c509 | 3,602,666 |
def _fn_tanh_ ( self , b = 1 ) :
""" Hyperbolic tangent function: f = tan(ab)
>>> f =
>>> a = f.tanh ( )
>>> a = f.tanh ( b )
>>> a = tanh ( f )
"""
return _fn_make_fun_ ( self ,
b ,
Ostap.Mor... | d64cab6625f9a50e2e568a5cb275e7b11d4b6b32 | 3,602,667 |
from typing import Iterable
def mpp_transformer(origin, origin_mpp, aim_mpp):
"""transform numbers according to mpp
:param origin: original numbers
:param origin_mpp: original mpp
:param aim_mpp: aim mpp
:return: transed numbers
"""
if isinstance(origin, Iterable):
transed = []
... | 64955bbc22821990e1087622b23ba46e90ab86bd | 3,602,668 |
def solve(input_grid):
"""
Here we have solve function that takes the input grid.
Every even steps we move the cells around to swap the
digits on the currently processed grid
"""
_output_grid = to_output_array(input_grid)
_, n_cols = get_shape_of_array(input_grid)
for i in range(n_cols)... | 65867f0a80314aab328180d7d070f4b0c61a3d3c | 3,602,669 |
def rank_equality(y_true, y_pred, groups):
"""Compute the rank equality error between two rankings.
Parameters
----------
y_true : array-like of shape = (n_samples)
Ground truth (correct) target values.
y_pred : array-like of shape = (n_samples)
Estimated target values.
groups... | a599e82dd1ea795dce6513b36f0fc24d379f1a8a | 3,602,670 |
def distributionCorrection(df, channel):
"""
Resample file pairs in a dataframe.
df: pd.DataFrame
channel: str
Column name of the values for resampling.
Returns:
estimated_true_positives: pd.DataFrame
To Do:
Make a more generic function, or at least pull... | 56488b5d12119c62b6f36e20f7158d57f937fff1 | 3,602,671 |
from typing import Optional
def get_cluster(arn: Optional[str] = None,
opts: Optional[pulumi.InvokeOptions] = None) -> AwaitableGetClusterResult:
"""
Resource Type definition for AWS::MSK::Cluster
"""
__args__ = dict()
__args__['arn'] = arn
if opts is None:
opts = pulum... | 888bac8b40daa72a7b27532bdc94de6f38b156d4 | 3,602,672 |
def one_step(site, DOY, herb_class, available_forage, prop_legume,
supp_available, supp, intake=None, force_supp=None):
"""One step of the forage model, with one herbivore type, if available
forage does not change."""
row = []
herb_class.calc_distance_walked(site.S, herb_class.stocking_den... | f924f6f2cc2c5bd9175254677c7ef973030edbb1 | 3,602,673 |
def array_replace(space, w_arr, args_w):
""" Replaces elements from passed arrays into the first array """
for i, w_arr in enumerate(args_w):
if w_arr.tp != space.tp_array:
space.ec.warn("array_replace_recursive(): Argument #%d "
"should be an array" % (i+1))
... | bab04d17733a12418b248e6f72e9dc053b263ac7 | 3,602,674 |
def upsample(inputs, out_shape, data_format):
"""
Upsamples to `out_shape` using nearest neighbor interpolation.
"""
if data_format == 'channel_first':
inputs = tf.transpose(inputs, [0, 2, 3, 1])
new_height = out_shape[3]
new_width = out_shape[2]
else:
new_height ... | 0916d0e1b2033690c4d38a80842795c3d7ca44b8 | 3,602,675 |
from typing import Iterable
from typing import List
def _setup_config_sources(spec: YapconfSpec, cli_vars: Iterable[str]) -> List[str]:
"""Sets the sources for configuration loading
Args:
spec: Yapconf specification
cli_vars: Command line arguments
Returns:
List of configuration ... | 8f193cc03750707f330b542e3d168399ac75b07d | 3,602,677 |
def get_transform(_split):
"""Frames train(test) transformation."""
if "test" in _split or "val" in _split:
transform_fn = transforms.Compose([
transforms.Resize(cfg.TEST.IM_SIZE, interpolation=BICUBIC),
transforms.CenterCrop(cfg.TRAIN.IM_SIZE),
transforms.Normalize(... | 7433f23a2e6f4cad1be4b89ce61ee7f58e51b508 | 3,602,678 |
def _chase_up(start_time, interval):
"""Utility function to check if there are missed intervals.
:param start_time: A time object representing the starting time.
:param interval: An integer specifying the time interval in seconds.
:returns: Number of seconds to sleep before next round.
"""
end_... | cf04c16e48ba05a6d7d68841298ef1a8e5976fa6 | 3,602,679 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.