content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def get_transceiver_sensor_sub_id(ifindex, sensor):
"""
Returns sub OID for transceiver sensor. Sub OID is calculated as folows:
sub OID = transceiver_oid + XCVR_SENSOR_PART_ID_MAP[sensor]
:param ifindex: interface index
:param sensor: sensor key
:return: sub OID = {{index}} * 1000 + {{lane}} * ... | 4c718feb45384ab6bef11e1f3c42ab4cd8d0ae2c | 21,500 |
def patch_twitter_get_following_users(value):
"""Return a function decorator which patches the TwitterClient.get_following_user_ids method."""
return patch_twitter_client_method("get_following_user_ids", value) | 296d20a3dbce3684cb2af2568c64fac25ab345c9 | 21,501 |
def conv1x1_1d(inplanes: int,
outplanes: int,
stride: int = 1) -> nn.Conv1d:
"""1x1一维卷积，用于短接时降采样"""
return nn.Conv1d(
inplanes,
outplanes,
kernel_size=(1,),
stride=(stride,),
padding=0,
bias=False
) | 481dc7b71b31ae6199bcafd1112bf1541d7a5d25 | 21,502 |
import hashlib
import os
def load_cifar10(channels_last=True, x_shape=None, x_dtype=np.float32,
y_dtype=np.int32, normalize_x=False):
"""
Load the CIFAR-10 dataset as NumPy arrays.
Args:
channels_last (bool): Whether or not to place the channels axis
at the last?
... | d730abf0de556a8990289e92359c5d31df6c0e9c | 21,503 |
import struct
def unpack_mmap_block(mm, n):
"""Decode the nth 4-byte long byte string from mapped memory."""
return struct.unpack("<L", mm[n*DATA_BLOCK_SIZE:(n+1)*DATA_BLOCK_SIZE])[0] | a75ac48e188e03e1ec7d3c289ffdd8e12173bc6f | 21,504 |
def tobs():
"""Return a list of temperatures for prior year"""
# * Query for the dates and temperature observations from the last year.
# * Convert the query results to a Dictionary using `date` as the key and `tobs` as the value.
# * Return the json representation of your dictionary.
las... | c7411130bb5c8d956d10a2ba3ce535f41ca04474 | 21,505 |
def reactToAMQPMessage(message, send_back):
"""
React to given (AMQP) message. `message` is expected to be
:py:func:`collections.namedtuple` structure from :mod:`.structures` filled
with all necessary data.
Args:
message (object): One of the request objects defined in
... | fd34510d58e6b164f37f93c0b17f2b2a1c8d32d2 | 21,506 |
def recE(siEnergy, layer):
""" Reconstructed energy from sim energy """
return ( (siEnergy/mipSiEnergy) * layerWeights[layer-1] + siEnergy)*\
secondOrderEnergyCorrection | 9efde4432f3a81ff06505c6fbb529be7404027d4 | 21,507 |
def get_account_id():
"""
Retrieve the AWS account ID
"""
client = boto3.client("sts")
account_id = client.get_caller_identity()["Account"]
return account_id | 579bdc686a0ceb5d71e180bf8ce7a17243cff849 | 21,508 |
def process_tag(item, profile, level=0):
"""
Processes element with <code>tag</code> type
@type item: ZenNode
@type profile: dict
@type level: int
"""
if not item.name:
# looks like it's root element
return item
attrs = make_attributes_string(item, profile)
cursor = profile['place_cursor'] and zen_codin... | 7d06160cadb0d828799713d888327a41e7ab0b80 | 21,509 |
from typing import Optional
import google
def read_secret(project_id: str, secret_name: str) -> Optional[str]:
"""Reads the latest version of a GCP Secret Manager secret.
Returns None if the secret doesn't exist."""
secret_manager = secretmanager.SecretManagerServiceClient()
secret_path = secret_man... | 388fa51983452f0852646d1ed1ab183da706c0ab | 21,510 |
import xml
def find_in_xml(data, search_params):
"""Try to find an element in an xml
Take an xml from string or as xml.etree.ElementTree
and an iterable of strings (and/or tuples in case of findall) to search.
The tuple should contain the string to search for and a true value.
"""
if isinstan... | 1cb4685a042349231cd946116a4894ca5b9d68d5 | 21,511 |
def conditional_expect(
X,
func,
reg,
method=None,
quantile_method=None,
n_integration_samples=10,
quad_dict=None,
random_state=None,
include_x=False,
include_idx=False,
vector_func=False,
):
"""Calculates the conditional expectation, i.e. E[func(Y)|X=x_eval], where
Y... | fb89adedeada5e100f2483d927d945ffe2d99034 | 21,512 |
def getSumOfSquaresPixel16_Image16(Image):
"""getSumOfSquaresPixel16_Image16(Image) -> unsigned __int16"""
return _ImageFunctions.getSumOfSquaresPixel16_Image16(Image) | 9ba21171e26fc32d938a3f377684830df5f03b8f | 21,513 |
def parse_statement(parsed, output):
"""Parses a tokenized sql_parse token and returns an encoded table."""
# Get the name of the table being created
table_name = next(token.value for token in parsed.tokens if isinstance(token, Identifier))
# Add the table metadata to the cached tables to access later.
... | a81791deac59e496145993bba0547294d5d5a7fa | 21,514 |
def create_hue_success_response(entity_number, attr, value):
"""Create a success response for an attribute set on a light."""
success_key = f"/lights/{entity_number}/state/{attr}"
return {"success": {success_key: value}} | c8570ca95ada89bd26d93f659261c91032c915c7 | 21,515 |
import warnings
def get_deaths():
"""***DEPRECATED - Use get_data_jhu instead.***
Get most recent fatality counts from JHU."""
# Deprecated warning
url = "https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/"
warnings.warn("This function is... | c747d27b10d0845520f4dbbfbb5efcf23c655b7e | 21,516 |
def transform_sentence(text, model):
"""
Mean embedding vector
"""
def preprocess_text(raw_text, model=model):
"""
Excluding unknown words and get corresponding token
"""
raw_text = raw_text.split()
return list(filter(lambda x: x in model.vocab, raw_text))
... | 57f9002e4f7fccefa824f1691324b4593b11fbe0 | 21,517 |
from typing import Sequence
from typing import List
import inspect
def model_primary_key_columns_and_names(Model: DeclarativeMeta) -> (Sequence[Column], List[str]):
""" Get the list of primary columns and their names as two separate tuples
Example:
pk_columns, pk_names = model_primary_key_columns_an... | 9466524452a77459042081e7becf968302b3dd3b | 21,518 |
def biweekly_test_data():
""" Provides test data for the full system test when using "biweekly" time_scale."""
time_scale = "biweekly"
time_per_task = {
"Free" : 480 * 9 * 2,
"Work" : 480 * 5 * 2,
"Sleep" : 480 * 7 * 2
}
min_task_time = 60
preferences = {
"Free" :... | b5f354a17819133c3c29e7652f6b1132599e89b6 | 21,519 |
def plot_bar_whiskers_jitter_significance(data, comparison_columns,
significant_comparison_columns,
heights, ylabel,
xlabels=None,
ax_handle=None,
... | dfdaf95034d3d53fac7c79eb4c7b387f9ac18f5b | 21,520 |
def _is_trans_valid(seed, mutate_sample):
"""
Check a mutated sample is valid. If the number of changed pixels in
a seed is less than pixels_change_rate*size(seed), this mutate is valid.
Else check the infinite norm of seed changes, if the value of the
infinite norm less than pixel_value_change_rate... | 118dc0e566fc4f5c481d21f8c8aec7fe4f1ece29 | 21,521 |
def split_axis(x, indices_or_sections, axis):
"""Splits given variables along an axis.
Args:
x (tuple of Variables): Variables to be split.
indices_or_sections (int or 1-D array): If this argument is an integer,
N, the array will be divided into N equal arrays along axis.
... | 245841aaef14ea130b20254775152a9199d63c41 | 21,522 |
def status(**kwargs):
"""Execute \"git status\" on the repository."""
status = check_output(["git", "status"]).decode("utf-8")
repo_clean = True
for keyword in ["ahead", "modified", "untracked"]:
if keyword in status:
repo_clean = False
return {"clean": repo_clean, "status": st... | 8e81264579628407e8560a6d89be884179636ea9 | 21,523 |
import os
import tqdm
def preprocessing_raw_csv(PATH=".//tcdata//hy_round2_train_20200225//",
local_file_name="train.pkl"):
"""Loading and processing all train csv data."""
if PATH is None:
raise ValueError("Invalid PATH !")
file_names = sorted(os.listdir(PATH), key=lambd... | 774e3865bac16458439fe597d4a5a5a745957a9c | 21,524 |
from typing import Counter
def find_listener_frequent_words(df, num):
"""
Given a conversation dataframe from a certain subreddit, find the top frequent words spoken by listeners.
Args:
df: A specified dataframe from a subreddit.
num: A ranking number used for finding the top frequent wor... | 80bc4b95e5713429751ff1725afce4ac02f0bddd | 21,525 |
def is_rescue_entry(boot_entry):
"""
Determines whether the given boot entry is rescue.
:param BootEntry boot_entry: Boot entry to assess
:return: True is the entry is rescue
:rtype: bool
"""
return 'rescue' in boot_entry.kernel_image.lower() | ba456c2724c3ad4e35bef110ed8c4cc08147b42c | 21,526 |
import base64
def estimate_cost(features, ssd):
"""Generate a TensorFlow subgraph to estimate the cost of an architecture.
Args:
features: A 1D float tensor containing features for a single network
architecture.
ssd: The name of the search space definition to use for the cost model.
Returns:
... | 2c85cc5d320cd214dae260793a1c779d8019177c | 21,527 |
def short_bubble(l, debug=True):
"""
what if the whole list is already in ascending order, the bubble would then still go through the entire outer loops
actually, if there is no swap happens in a certain iteration ( the inner loop), the next loop should stop
:param l:
:param debug:
:return:
... | d79ec7311e8a08267ddcbe82d08a85b35b9d4a6f | 21,528 |
import yaml
def IsResourceLike(item):
"""Return True if item is a dict like object or list of dict like objects."""
return yaml.dict_like(item) or (yaml.list_like(item) and
all(yaml.dict_like(x) for x in item)) | bc6ae6c4d84949511c679116454343731e8d8bd2 | 21,529 |
import math
def rad_to_gon(angle: float) -> float:
"""Converts from radiant to gon (grad).
Args:
angle: Angle in rad.
Returns:
Converted angle in gon.
"""
return angle * 200 / math.pi | cbf7070a9c3a9796dfe4bffe39fdf2421f7279ed | 21,530 |
def check_interface_status(conn_obj, interface, state, device="dut"):
"""
API to check the interface state
Author: Chaitanya Vella (chaitanya-vella.kumar@broadcom.com)
:param conn_obj:
:param interface:
:param state:
:param device:
:return:
"""
interface_state = get_interface_sta... | 484c1a8dcf96a3160791a63979d47096e5e51fbc | 21,531 |
def hungarian_match(self, y_true, y_pred):
"""Matches predicted labels to original using hungarian algorithm."""
y_true = self.adjust_range(y_true)
y_pred = self.adjust_range(y_pred)
D = max(y_pred.max(), y_true.max()) + 1
w = np.zeros((D, D), dtype=np.int64)
# Confusion matrix.
fo... | 29a9976edcfa4a935d451f6471641b3836343d83 | 21,532 |
import torch
def orthantree(scaled, capacity=8):
"""Constructs a :ref:`tree <presolve>` for the given :func:`~pybbfmm.scale`'d problem.
This is a bit of a mess of a function, but long story short it starts with all the sources allocated to the root
and repeatedly subdivides overfull boxes, constructing t... | 9813697be3b19a2d7e3b71f28b1212c91a590fd3 | 21,533 |
def make_sparse(
docs_to_fit, min_df=50, stop_words=None,
docs_to_transform=None, ngram_range=None,
):
"""
Take a pre-tokenized document and turn into a sparse matrix.
:param docs_to_fit: A list of lists of tokenized words to build the vocabulary from.
:param min_df: Number of records th... | 467d04f465ed4c19b4e20aa69c05508f6faafdc6 | 21,534 |
import random
def weightedPriorityReliabilityScore(service_instances, last_records):
"""
Algorithm to find highest priority of the service based on
reliability score achieved in past discovery results
"""
priority_list = []
for i in range(0, len(service_instances)):
sin... | e215ae3e4009de7e8e6e8a8a0b66a66238e30f16 | 21,535 |
def calculate_output(param_dict, select_device, input_example):
"""Calculate the output of the imported graph given the input.
Load the graph def from graph file on selected device, then get the tensors based on the input and output name from the graph,
then feed the input_example to the graph and retrieve... | e98bf63743d7f940170ca7ab4dcd97b751be178f | 21,536 |
def is_instance_failed_alarm(alarms, instance, guest_hb=False):
"""
Check if an instance failed alarm has been raised
"""
expected_alarm = {'alarm_id': fm_constants.FM_ALARM_ID_VM_FAILED,
'severity': fm_constants.FM_ALARM_SEVERITY_CRITICAL}
return _instance_alarm_raised(alarms... | 5c886bea0b72d52392ed38217af20b7ebc87bd91 | 21,537 |
from modules.plumedwrapper import io as plumedio
import os
def load_metad_fes(fes_dir_path):
"""Load all the PLUMED free energy profiles saved by sumhills."""
# Read the FES in time.
fes_file_prefix_path = os.path.join(fes_dir_path, 'fes_')
fes_time = plumedio.read_table(fes_file_prefix_path + 'time.... | 29e341193670e1ff82e33d1ab818f7df8a4d9042 | 21,538 |
def detected(numbers, mode):
"""
Returns a Boolean result indicating whether the last member in a numeric array is the max or
min, depending on the setting.
Arguments
- numbers: an array of numbers
- mode: 'max' or 'min'
"""
call_dict = {'min': min, 'max': max}
if mode not in ca... | b0a5b19e7d97db99769f28c4b8ce998dbe318c5b | 21,539 |
import math
def calculate_compass_bearing(point_a, point_b):
"""
Calculates the bearing between two points.
The formulae used is the following:
θ = atan2(sin(Δlong).cos(lat2),
cos(lat1).sin(lat2) − sin(lat1).cos(lat2).cos(Δlong))
:Parameters:
- `pointA: The tuple repres... | 535fc0cfc086974b1e329df297bdbea4aab1f127 | 21,540 |
import re
def parse_instructions(instruction_list):
"""
Parses the instruction strings into a dictionary
"""
instruction_dict = []
for instruction in instruction_list:
regex_match = re.match(r"(?P<direction>\w)(?P<value>\d*)",instruction)
if regex_match:
instruction_dic... | 67b773bae0cb2cc0509503f2ea27f3312ce9d41c | 21,541 |
def calc_elapsed_sleep(in_num, hyp_file, fpath, savedir, export=True):
"""
Calculate minutes of elapsed sleep from a hypnogram file & concatenate stage 2 sleep files
Parameters
----------
in_num: str
patient identifier
hyp_file: str (format: *.txt)
file with hypnogram at 30-sec... | 61390b205c7dcbd65884e8f073f1b1395f1d1ca2 | 21,542 |
def valid_pairs(pairs, chain):
"""
Determine if the chain contains any invalid pairs (e.g. ETH_XMR)
"""
for primary, secondary in zip(chain[:-1], chain[1:]):
if not (primary, secondary) in pairs and \
not (secondary, primary) in pairs:
return False
return True | c9e36d0490893e1b1a6cd8c3fb0b14b382d69515 | 21,543 |
import os
import json
def setup(sub_args, ifiles, repo_path, output_path):
"""Setup the pipeline for execution and creates config file from templates
@param sub_args <parser.parse_args() object>:
Parsed arguments for run sub-command
@param repo_path <str>:
Path to installation or source co... | 30a45285d09ba2d7e919c918fa2e67f67c3b57e6 | 21,544 |
from typing import Any
def fqname_for(obj: Any) -> str:
"""
Returns the fully qualified name of ``obj``.
Parameters
----------
obj
The class we are interested in.
Returns
-------
str
The fully qualified name of ``obj``.
"""
if "<locals>" in obj.__qualname__:
... | 6d4e5db255715c999d1bb40533f3dbe03b948b07 | 21,545 |
import time
import io
import zipfile
import os
def analyzer_zipfile(platform, monitor):
"""Creates the Zip file that is sent to the Guest."""
t = time.time()
zip_data = io.BytesIO()
zip_file = zipfile.ZipFile(zip_data, "w", zipfile.ZIP_STORED)
# Select the proper analyzer's folder according to t... | 4c302ce81f1a3a18bfda9681e1761e246a6de42a | 21,546 |
def symbol_size(values):
""" Rescale given values to reasonable symbol sizes in the plot. """
max_size = 50.0
min_size = 5.0
# Rescale max.
slope = (max_size - min_size)/(values.max() - values.min())
return slope*(values - values.max()) + max_size | a33f77ee8eeff8d0e63035c5c408a0788b661886 | 21,547 |
from datetime import datetime
def delete(id):
"""Soft delete a patient."""
check_patient_permission(id)
patient = Patient.query.get(id)
patient.deleted = datetime.datetime.now()
patient.deleted_by = current_user
db.session.commit()
return redirect(url_for('screener.index')) | 0e9c984bb8bf8429c662f1af14945089789b8bc8 | 21,548 |
import os
import tempfile
def system_temp_dir():
"""
Return the global temp directory for the current user.
"""
temp_dir = os.getenv('SCANCODE_TMP')
if not temp_dir:
sc = text.python_safe_name('scancode_' + system.username)
temp_dir = os.path.join(tempfile.gettempdir(), sc)
cre... | 14c82a59d049068042d10845f63c61f53879259b | 21,549 |
from typing import List
from typing import Callable
from typing import Union
import os
import click
def _pipeline_network_multiple_database(database: List[str], kernel_method: Callable,
filter_network_omic: Union[List, str]) -> Union[Matrix, str]:
"""Process network for a m... | 60f454aee74f5d2779d3a54fdcfb119637c73919 | 21,550 |
import torch
import tensorflow as tf
def _to_tensor(args, data):
"""Change data to tensor."""
if vega.is_torch_backend():
data = torch.tensor(data)
if args.device == "GPU":
return data.cuda()
else:
return data
elif vega.is_tf_backend():
data = tf.con... | 77d87982c81232bac4581eb5269629c268a7fe16 | 21,551 |
def materialize_jupyter_deployment(
config: ClusterConfig,
uuid: str,
definition: DeploymentDefinition) -> JupyterDeploymentImpl: # noqa
"""Materializes the Jupyter deployment definition.
:param config: Cluster to materialize the Jupyter deployment with.
:param uuid: Unique... | d4a12efd7d4f55d5261734cf3eb0dd3b230c363d | 21,552 |
def _CreateLSTMPruneVariables(lstm_obj, input_depth, h_depth):
"""Function to create additional variables for pruning."""
mask = lstm_obj.add_variable(
name="mask",
shape=[input_depth + h_depth, 4 * h_depth],
initializer=tf.ones_initializer(),
trainable=False,
dtype=lstm_obj.dtype)
... | 398dd89a9b8251f11aef3ba19523e26861ff5874 | 21,553 |
def get_index_fredkin_gate(N, padding = 0):
"""Get paramaters for log2(N) Fredkin gates
Args:
- N (int): dimensional of states
- padding (int, optional): Defaults to 0.
Returns:
- list of int: params for the second and third Frekin gates
"""
indices = []
for i in range(... | d7ab1f4bc414ad741533d5fabfb0f7c8b4fe0959 | 21,554 |
def import_by_name(name):
"""
动态导入
"""
tmp = name.split(".")
module_name = ".".join(tmp[0:-1])
obj_name = tmp[-1]
module = __import__(module_name, globals(), locals(), [obj_name])
return getattr(module, obj_name) | 714ca90704d99a8eafc8db08a5f3df8e17bc6da4 | 21,555 |
def f1_score(y_true, y_pred):
"""F-measure."""
p = precision(y_true, y_pred)
r = true_positive_rate(y_true, y_pred)
return 2 * (p * r) / (p + r) | e5f79def2db902bb0aa1efd9ea1ccef52b62072a | 21,556 |
def hexColorToInt(rgb):
"""Convert rgb color string to STK integer color code."""
r = int(rgb[0:2],16)
g = int(rgb[2:4],16)
b = int(rgb[4:6],16)
color = format(b, '02X') + format(g, '02X') + format(r, '02X')
return int(color,16) | 59b8815d647b9ca3e90092bb6ee7a0ca19dd46c2 | 21,557 |
import torch
def test(model, X, model_type, test_type, counter=False):
"""Test functions."""
if model_type == 'notear-mlp':
X = np.vstack(X)
y = model(torch.from_numpy(X))
y = y.cpu().detach().numpy()
mse = mean_squared_loss(y.shape[0], y[:, 0], X[:, 0])
elif model_type == 'notear-castle':
... | cb98e2096052270e786bbb81fafc328076b1aa40 | 21,558 |
def scale():
"""
Returns class instance of `Scale`.
For more details, please have a look at the implementations inside `Scale`.
Returns
-------
Scale :
Class instance implementing all 'scale' processes.
"""
return Scale() | f5fb9daf9baaf86674be110aae78b1bf91f09371 | 21,559 |
def imread_rgb(filename):
"""Read image file from filename and return rgb numpy array"""
bgr = cv2.imread(filename)
rgb = cv2.cvtColor(bgr, cv2.COLOR_BGR2RGB)
return rgb | 6fcef3f9f5d8b02c28c596f706f3e1fcf685dd24 | 21,560 |
def insert_at_index(rootllist, newllist, index):
""" Insert newllist in the llist following rootllist such that newllist is at the provided index in the resulting llist"""
# At start
if index == 0:
newllist.child = rootllist
return newllist
# Walk through the list
curllist = rootllist
for i in ran... | 767cde29fbc711373c37dd3674655fb1bdf3fedf | 21,561 |
def kpi_value(request, body):
"""kpi值接口 根据 indicator 传入参数不同请求不同的 handler"""
params = {
"indicator": body.indicator
}
handler = KpiFactory().create_handler(params["indicator"])
result = handler(params=params)
return DashboardResult(content=result) | 5f242028d7f95b1ffa81690c3ed1b1d7006cf97c | 21,562 |
def safeReplaceOrder( references ):
"""
When inlining a variable, if multiple instances occur on the line, then the
last reference must be replaced first. Otherwise the remaining intra-line
references will be incorrect.
"""
def safeReplaceOrderCmp(self, other):
return -cmp(self.colno, o... | dae29bf1c8da84c77c64210c4d897ac4a9d0c098 | 21,563 |
from typing import Union
from typing import Iterable
import time
from typing import List
from typing import Any
import requests
def broken_link_finder(urls: Union[str, list, tuple, set],
print_to_console: bool = False,
file_out = None,
viewer = DEFA... | 2cbbe3c40d2d78e68144c03dcb93f2f2ac6feb83 | 21,564 |
def clean_value(value: str) -> t.Union[int, float, str]:
"""Return the given value as an int or float if possible, otherwise as the original string."""
try:
return int(value)
except ValueError:
pass
try:
return float(value)
except ValueError:
pass
return value | 52c09e2aaf77cb22e62f47e11226350112390eb2 | 21,565 |
import types
def sumstat(*L):
"""
Sums a list or a tuple L
Modified from pg 80 of Web Programming in Python
"""
if len(L) == 1 and \
( isinstance(L[0],types.ListType) or \
isinstance (L[0], types.TupleType) ) :
L = L[0]
s = 0.0
for k in L:
s = s + k
... | c37aa0aa0b7dbf6adbe77d82b27b25e469891795 | 21,566 |
def halref_to_data_url(halref: str) -> str:
"""
Given a HAL or HAL-data document URIRef, returns the corresponding HAL-data URL
halref: str
HAL document URL
(Most important!) https://hal.archives-ouvertes.fr/hal-02371715v2 -> https://data.archives-ouvertes.fr/document/hal-02371715v... | 48ef6629fc3198af2c8004a3dbcbbde6e700cb12 | 21,567 |
def find_best_rate():
"""
Input: Annual salary, semi-annual raise, cost of home
Assumes: a time frame of three years (36 months), a down payment of 25% of the total cost,
current savings starting from 0 and annual return of 4%
Returns the best savings rate within (plus/minus) $100 of the downpayme... | 451fc72c006182b63233376a701b4cbb855ad39a | 21,568 |
def q_inv(a):
"""Return the inverse of a quaternion."""
return [a[0], -a[1], -a[2], -a[3]] | e8d06e7db6d5b23efab10c07f4b9c6088190fa07 | 21,569 |
def divide_hex_grid_flower(points, hex_radius=None):
"""Partitions a hexagonal grid into a flower pattern (this is what I used for the final product. Returns a list of partition indices for each point."""
if hex_radius is None: # copied from build_mirror_array()
mini_hex_radius = (10 * 2.5 / 2) + 1
... | 9f77e85d4bbfd00ea5eff6905209aad84e3a9191 | 21,570 |
def fis_gauss2mf(x:float, s1:float, c1:float, s2:float, c2:float):
"""Split Gaussian Member Function"""
t1 = 1.0
t2 = 1.0
if x < c1:
t1 = fis_gaussmf(x, s1, c1)
if x > c2:
t2 = fis_gaussmf(x, s2, c2)
return (t1 * t2) | 443e02dff7ab3827ac0006443964f45a6f9f4ce2 | 21,571 |
def _is_trigonal_prism(vectors, dev_cutoff=15):
"""
Triangular prisms are defined by 3 vertices in a triangular pattern on two
aligned planes. Unfortunately, the angles are dependent on the length and
width of the prism. Need more examples to come up with a better way of
detecting this shape.
For now, this... | 2b3ffb318b3201923828eea8f4769a6ce854dd58 | 21,572 |
import os
def get_sza(times, rad, mask=None):
"""
Fetch sza at all range cell in radar FoV
rad: Radar code
mask: mask metrix
"""
fname = "data/sim/{rad}.geolocate.data.nc.gz".format(rad=rad)
os.system("gzip -d " + fname)
fname = fname.replace(".gz","")
data = Dataset(fname)
lat... | 2b3ecd5c07ba00cbaae3274ade46925a5ad377dc | 21,573 |
def load_results(path):
"""
return a dictionary of columns
can't use genfromtex because of weird format for arrays that I used
:param path:
:return:
"""
data = defaultdict(list)
column_casts = {
"epoch": float,
"env_name": str,
"game_counter": int,
"game... | a4015d37d41353d41c5044d84249ad2e0700d7dc | 21,574 |
def priority(n=0):
"""
Sets the priority of the plugin.
Higher values indicate a higher priority.
This should be used as a decorator.
Returns a decorator function.
:param n: priority (higher values = higher priority)
:type n: int
:rtype: function
"""
def wrapper(cls):
cls... | 58ab19fd88e9e293676943857a0fa04bf16f0e93 | 21,575 |
import math
def vecangle(u,v):
"""
Calculate as accurately as possible the angle between two 3-component vectors u and v.
This formula comes from W. Kahan's advice in his paper "How Futile are Mindless Assessments
of Roundoff in Floating-Point Computation?" (https://www.cs.berkeley.edu/~wkahan/Mindles... | dde6ebed830130f122b0582d4c19963a061a3d31 | 21,576 |
def sanitize_option(option):
"""
Format the given string by stripping the trailing parentheses
eg. Auckland City (123) -> Auckland City
:param option: String to be formatted
:return: Substring without the trailing parentheses
"""
return ' '.join(option.split(' ')[:-1]).strip() | ece0a78599e428ae8826b82d7d00ffc39495d27f | 21,577 |
def node_values_for_tests():
"""Creates a list of possible node values for parameters
Returns:
List[Any]: possible node values
"""
return [1, 3, 5, 7, "hello"] | b919efc5e59a5827b3b27e4f0a4cd070ceb9a5a4 | 21,578 |
import torch
def computeGramMatrix(A, B):
"""
Constructs a linear kernel matrix between A and B.
We assume that each row in A and B represents a d-dimensional feature vector.
Parameters:
A: a (n_batch, n, d) Tensor.
B: a (n_batch, m, d) Tensor.
Returns: a (n_batch, n, m) Tensor.... | c9b221b3d6a8c7a16337178a1f148873b27ec04a | 21,579 |
def parse_config(config):
"""Backwards compatible parsing.
:param config: ConfigParser object initilized with nvp.ini.
:returns: A tuple consisting of a control cluster object and a
plugin_config variable.
raises: In general, system exceptions are not caught but are propagated
up to the... | 74689d11c1d610a9211dc5895ff42a8b8e2389ae | 21,580 |
def deletable_proxy_user(request, onefs_client):
"""Get the name of an existing proxy user that it is ok to delete."""
return _deletable_proxy_user(request, onefs_client) | c7440099fe4435cf9b5b557253f7fb9563dc600c | 21,581 |
import six
def get_from_module(identifier, module_params, module_name,
instantiate=False, kwargs=None):
"""The function is stolen from keras.utils.generic_utils.
"""
if isinstance(identifier, six.string_types):
res = module_params.get(identifier)
if not res:
... | 406a1da5843feb8556bbd1802426b57e7a33b20d | 21,582 |
def color_lerp(c1, c2, a):
"""Return the linear interpolation between two colors.
``a`` is the interpolation value, with 0 returing ``c1``,
1 returning ``c2``, and 0.5 returing a color halfway between both.
Args:
c1 (Union[Tuple[int, int, int], Sequence[int]]):
The first color. At... | 96c950c447994a729c9eb4c18bdcc60976dbb675 | 21,583 |
def get_equations(points):
""" Calculate affine equations of inputted points
Input : 1
points : list of list
ex : [[[x1, y1], [x2, y2]], [[xx1, yy1], [xx2, yy2]]] for 2 identified
elements
Contains coordinates of separation lines i.e.
[[[start poin... | 4eea43aee8b5f9c63793daae0b28e3c8b4ce0929 | 21,584 |
def Temple_Loc(player, num):
"""temple location function"""
player.coins -= num
player.score += num
player.donation += num
# player = temple_bonus_check(player) for acheivements
return (player) | dced7b9f23f63c0c51787291ab12701bd7021152 | 21,585 |
def indexGenomeFile(input, output):
"""Index STAR genome index file
`input`: Input probes fasta file
`output`: SAindex file to check the completion of STAR genome index
"""
#print input
#print output
base = splitext(input)[0]
base = base + ".gtf"
#print base
gtfFile = base
o... | 2ebd981ebad97f68adb1043e9c06fd01dc270c10 | 21,586 |
import math
def performance(origin_labels, predict_labels, deci_value, bi_or_multi=False, res=False):
"""evaluations used to evaluate the performance of the model.
:param deci_value: decision values used for ROC and AUC.
:param bi_or_multi: binary or multiple classification
:param origin_labels: true ... | aac87e0bdc02b61ccb5136e04e1ac8b09e01ce65 | 21,587 |
def rotkehlchen_instance(
uninitialized_rotkehlchen,
database,
blockchain,
accountant,
start_with_logged_in_user,
start_with_valid_premium,
function_scope_messages_aggregator,
db_password,
rotki_premium_credentials,
accounting_data_dir,
... | 144585d62c04f97aa7bcb7a355bd90f8ff001022 | 21,588 |
def store_inspection_outputs_df(backend, annotation_iterators, code_reference, return_value, operator_context):
"""
Stores the inspection annotations for the rows in the dataframe and the
inspection annotations for the DAG operators in a map
"""
dag_node_identifier = DagNodeIdentifier(operator_conte... | 228a24a4d59162382b5a3ae7d8204e396b8c76dd | 21,589 |
def switched (decorator):
"""decorator transform for switched decorations.
adds start_fun and stop_fun methods to class to control fun"""
@simple_decorator
def new_decorator (fun):
event = new_event()
def inner_fun (self, *args):
if args:
event.wait()
if threads_alive():
retu... | 1996274fcaba2095b43f7d0da134abb59b2f7a56 | 21,590 |
def logistic_embedding0(k=1, dataset='epinions'):
"""using random embedding to train logistic
Keyword Arguments:
k {int} -- [folder] (default: {1})
dataset {str} -- [dataset] (default: {'epinions'})
Returns:
[type] -- [pos_ratio, accuracy, f1_score0, f1_score1, f1_score2, auc_score... | 69b198c6a5f8a44681ccfee67b532b3d38d2ee44 | 21,591 |
def process_plus_glosses(word):
"""
Find all glosses with a plus inside. They correspond
to one-phoneme affix sequences that are expressed by
the same letter due to orthographic requirements.
Replace the glosses and the morphemes.
"""
return rxPartsGloss.sub(process_plus_glosses_ana, word) | 0678efc61d1af0ec75b8d0566866b305b6312448 | 21,592 |
from datetime import datetime
def check_in_the_past(value: datetime) -> datetime:
"""
Validate that a timestamp is in the past.
"""
assert value.tzinfo == timezone.utc, "date must be an explicit UTC timestamp"
assert value < datetime.now(timezone.utc), "date must be in the past"
return value | a439295190bfa2b6d2d6de79c7dc074df562e9ed | 21,593 |
import os
def fixture(filename):
"""
Get the handle / path to the test data folder.
"""
return os.path.join(fixtures_dir, filename) | 7a14e173993b3f226ca71ea335ee153512e3df7d | 21,594 |
from typing import Dict
def character_count_helper(results: Dict) -> int:
"""
Helper Function that computes
character count for ocr results on a single image
Parameters
----------
results: Dict
(OCR results from a clapperboard instance)
Returns
-------
Int
Number... | b5bcba9d39b7b09a1a123fec034ab1f27b31d1eb | 21,595 |
import pickle
def from_pickle(input_path):
"""Read from pickle file."""
with open(input_path, 'rb') as f:
unpickler = pickle.Unpickler(f)
return unpickler.load() | 4e537fcde38e612e22004007122130c545246afb | 21,596 |
def PromptForRegion(available_regions=constants.SUPPORTED_REGION):
"""Prompt for region from list of available regions.
This method is referenced by the declaritive iam commands as a fallthrough
for getting the region.
Args:
available_regions: list of the available regions to choose from
Returns:
T... | 2298fde743219f59b5a36844d85e14929d1e2a1e | 21,597 |
def update(x, new_x):
"""Update the value of `x` to `new_x`.
# Arguments
x: A `Variable`.
new_x: A tensor of same shape as `x`.
# Returns
The variable `x` updated.
"""
return tf.assign(x, new_x) | 363cd3232a57d4c2c946813874a5a3c613f9a8c9 | 21,598 |
def r1r2_to_bp(r1,r2,pl=0.01, pu=0.25):
"""
Convert uniform samling of r1 and r2 to impact parameter b and and radius ratio p
following Espinoza 2018, https://iopscience.iop.org/article/10.3847/2515-5172/aaef38/meta
Paramters:
-----------
r1, r2: float;
uniform parameters in from u(... | 0c7f69f3f7960792e8d0ecd75fde028eda9feefa | 21,599 |
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