content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def int_not_in_range(bounds, inclusive=False):
"""Creates property that must be an int outside bounds[0] and bounds[1].
Parameters:
bounds: Subscriptable with len()==2, where bounds[0] is the lower
bound and bounds[1] is the upper bound.
Requires bounds[1] > bounds[0].
... | 6890cd827fb741329c958a001e48013466414d11 | 3,640,600 |
from typing import Dict
from typing import List
def plot_concordance_pr(
pr_df: pd.DataFrame,
snv: bool,
colors: Dict[str, str] = None,
size_prop: str = None,
bins_to_label: List[int] = None,
) -> Column:
"""
Generates plots showing Precision/Recall curves for truth samples:
Two tabs:
... | 8ad9541605c8f9f274faba03de7e19766341a562 | 3,640,601 |
from enum import Enum
def typehint_metavar(typehint):
"""Generates a metavar for some types."""
metavar = None
if typehint == bool:
metavar = '{true,false}'
elif is_optional(typehint, bool):
metavar = '{true,false,null}'
elif _issubclass(typehint, Enum):
enum = typehint
... | 31b42c29dd970d561917420e789eea6a7bd84cfa | 3,640,602 |
from datetime import datetime
def generate_signed_url(filename):
"""
Generate a signed url to access publicly
"""
found_blob = find(filename)
expiration = datetime.now() + timedelta(hours=1)
return found_blob.generate_signed_url(expiration) | 917f78cfa12496baf655a8ea707143b4922f99c0 | 3,640,603 |
def delete_old_layer_versions(client, table, region, package, prefix):
"""
Loops through all layer versions found in DynamoDB and deletes layer version if it's <maximum_days_older> than
latest layer version.
The latest layer version is always kept
Because lambda functions are created at a maximum... | 291afac422a37cad59a8c2128776567b24c5a0c1 | 3,640,604 |
def _run_simulation(sim_desc):
"""Since _run_simulation() is always run in a separate process, its input
and output params must be pickle-friendly. Keep that in mind when
making changes.
This is what each worker executes.
Given a SimulationDescription object, calls the sequence & binning
code,... | 16cacdb3eaf1fadff8769ab6316eb06e89c226eb | 3,640,605 |
def view_filestorage_file(self, request):
""" Renders the given filestorage file in the browser. """
return getattr(request.app, self.storage).getsyspath(self.path) | ad65b83b9462c8b8efec7626d4751685df3aba8b | 3,640,606 |
def enum_choice_list(data):
""" Creates the argparse choices and type kwargs for a supplied enum type or list of strings """
# transform enum types, otherwise assume list of string choices
if not data:
return {}
try:
choices = [x.value for x in data]
except AttributeError:
c... | 4f91c76569a4b42e655ed198a5c4ec2e48d9e839 | 3,640,607 |
def chartset(request):
""" Conjunto de caracteres que determian la pagina
request: respuesta de la url"""
print "--------------- Obteniendo charset -------------------"
try:
charset = request.encoding
except AttributeError as error_atributo:
charset = "NA"
print "charset: " +... | 072ec863bd555706a64bab48d147afb24142fae4 | 3,640,608 |
import uuid
def generate_UUID():
"""
Generate a UUID and return it
"""
return str(uuid.uuid4()) | feab11861e366ddf60cdc74c12f77f6a6ece2fa3 | 3,640,609 |
def streaming_recall_at_thresholds(predictions, labels, thresholds,
ignore_mask=None, metrics_collections=None,
updates_collections=None, name=None):
"""Computes various recall values for different `thresholds` on `predictions`.
The `streaming_r... | 6cdaa7cf3b0d1c35204764fb78c4f9cefb09b577 | 3,640,610 |
def fib(n):
"""Returns the nth Fibonacci number."""
if n == 0:
return 1
elif n == 1:
return 1
else:
return fib(n - 1) + fib(n - 2) | 397d5714f45491dde68c13379fe2a6acafe55002 | 3,640,611 |
import os
def load_saved_users(args) -> list:
"""
:param args:
:return: list
"""
data_frame = pd.read_csv(os.path.join(args.data_dir,
args.users_tweets_dir,
args.users_file),
header=No... | efb4f9bbd055f39c30693fbea23d7e9254760e27 | 3,640,612 |
import logging
def remove_artifacts_from_biom_table(table_filename,
fasta_filename,
ref_fp,
biom_table_dir,
ref_db_fp,
threads=1,
... | 89f8be391587598db8fec97c3d6f9a46b4fdff54 | 3,640,613 |
def template_review(context, mapping):
""":phabreview: Object describing the review for this changeset.
Has attributes `url` and `id`.
"""
ctx = context.resource(mapping, b'ctx')
m = _differentialrevisiondescre.search(ctx.description())
if m:
return templateutil.hybriddict({
... | f475cf717026329ecc3c1ed1ccaff89089423e50 | 3,640,614 |
def addRandomEdges(graph: nx.Graph, nEdges: int) -> tuple:
""" Adds random edges to a given graph """
nodes = list(graph.nodes)
n = len(nodes)
edges = []
for i in range(nEdges):
newEdge = False
while not newEdge:
i_u, i_v = np.random.randint(0, n-1), np.random.randint(0, ... | 004723ac17a431a266bae27c91316a66ced507f9 | 3,640,615 |
def get_s3_buckets_for_account(account, region='us-east-1'):
""" Get S3 buckets for a specific account.
:param account: AWS account
:param region: AWS region
"""
session = boto3.session.Session() # create session for Thread Safety
assume = rolesession.assume_crossact_audit_role(
session... | bc2a334bb6c358c43fb97336d3092c27372bd2d0 | 3,640,616 |
import os
def create_uid_email(username=None, hostname=None):
"""Create an email address suitable for a UID on a GnuPG key.
:param str username: The username portion of an email address. If None,
defaults to the username of the running Python
process.
:... | ca8ad0204e188d850f93f94d559a5a2e04a9170c | 3,640,617 |
def get_users():
""" Alle Benutzer aus der Datenbank laden. """
session = get_cassandra_session()
future = session.execute_async("SELECT user_id, username, email FROM users")
try:
rows = future.result()
except Exception:
log.exeception()
users = []
for row in rows:
... | c6f7b49447dd187e188e9094af3443fe3e4ed218 | 3,640,618 |
import signal
def fastcorrelate(
input1, input2, usefft=True, zeropadding=0, weighting="None", displayplots=False, debug=False,
):
"""Perform a fast correlation between two arrays.
Parameters
----------
input1
input2
usefft
zeropadding
weighting
displayplots
debug
Ret... | 2cb18d598f6071806cd5cd9c6260fa5a58764cd7 | 3,640,619 |
def vgconv(xinput,yinput,fwhm, ppr=None):
"""convolution with a Gaussian in log lambda scale
for a constant resolving power
Parameters
----------
xinput: numpy float array
wavelengths
yinput: numpy array of floats
fluxes
fwhm: float
FWHM of the Gaussian (km/s)
ppr: float, optional
... | d4722c87881eca27bac45cd47f84269249591cd0 | 3,640,620 |
def attach_component_to_entity(entity_id, component_name):
# type: (azlmbr.entity.EntityId, str) -> azlmbr.entity.EntityComponentIdPair
"""
Adds the component if not added already.
:param entity_id: EntityId of the entity to attach the component to
:param component_name: name of the component
:r... | f2c29f18ede8eef7accaf19970d18b0a432801ed | 3,640,621 |
def get_raw_samples(sampling_strategy: sample_entry.Strategy, step: int) -> np.ndarray:
"""
Collects raw samples from database associated with sampling strategy. If the raw samples do not exists in
the database new ones will be created by calling the Sobol function
"""
sampling_strategy.reload()
... | d0b2b4d643767eb1afc65611a78888d2c5b57824 | 3,640,622 |
import yaml
from io import StringIO
def mix_to_dat(probspec,isStringIO=True):
"""
Reads a YAML mix file and generates all of the GMPL dat components associated with
the mix inputs.
Inputs:
ttspec - the tour type spec object created from the mix file
param_name - string name of paramte... | 972c1118c8d7af6dc8f9ff87908b1ca7184c880e | 3,640,623 |
from typing import Any
def get_setting(setting_name: str, default: Any=None) -> Any:
"""
Convenience wrapper to get the value of a setting.
"""
configuration = get_configuration()
if not configuration: # pragma: no cover
raise Exception('get_setting() called before configuration was initi... | 774ee06824a227ed66357cb46a5277c24ba11f09 | 3,640,624 |
def deceptivemultimodal(x: np.ndarray) -> float:
"""Infinitely many local optima, as we get closer to the optimum."""
assert len(x) >= 2
distance = np.sqrt(x[0]**2 + x[1]**2)
if distance == 0.:
return 0.
angle = np.arctan(x[0] / x[1]) if x[1] != 0. else np.pi / 2.
invdistance = int(1. / ... | c08ab425bbc9803fcea9695c46acee71c2455873 | 3,640,625 |
import os
def get_basins_scores(memory_array, binarized_cluster_dict, basinscore_method="default"):
"""
Args:
- memory_array: i.e. xi matrix, will be N x K (one memory from each cluster)
- binarized_cluster_dict: {k: N x M array for k in 0 ... K-1 (i.e. cluster index)}
- basinscore_met... | 9b4bf91ed760767444a595fb575c81593189e486 | 3,640,626 |
from aiida.orm import Dict
from aiida_quantumespresso.utils.resources import get_default_options
def generate_inputs_ph(fixture_sandbox, fixture_localhost, fixture_code, generate_remote_data, generate_kpoints_mesh):
"""Generate default inputs for a `PhCalculation."""
def _generate_inputs_ph():
"""Gen... | 4ab1f46ff08094fccd4197a19ab56c31dc1ac93c | 3,640,627 |
from urllib.parse import quote
def escape_url(raw):
"""
Escape urls to prevent code injection craziness. (Hopefully.)
"""
return quote(raw, safe="/#:") | 4eee23f244998d2d2f4abd892a867f2e27f502a2 | 3,640,628 |
def split_sample(labels):
"""
Split the 'Sample' column of a DataFrame into a list.
Parameters
----------
labels: DataFrame
The Dataframe should contain a 'Sample' column for splitting.
Returns
-------
DataFrame
Updated DataFrame has 'Sample' column with a list of strin... | 483f1b78e07a2156aa3e48ae6c1f5ce41f5e60fe | 3,640,629 |
def pmi_odds(pnx, pn, nnx, nn):
"""
Computes the PMI with odds
Args:
pnx (int): number of POSITIVE news with the term x
pn (int): number of POSITIVE news
nnx (int): number of NEGATIVE news with the term x
nn (int): number of NEGATIVE news
Ret... | 5d4786f477fb12051a5a56887a7a7573aeab0802 | 3,640,630 |
def berDecodeLength(m, offset=0):
"""
Return a tuple of (length, lengthLength).
m must be atleast one byte long.
"""
l = ber2int(m[offset + 0:offset + 1])
ll = 1
if l & 0x80:
ll = 1 + (l & 0x7F)
need(m, offset + ll)
l = ber2int(m[offset + 1:offset + ll], signed=0)
... | e93252966e370088274f62bd512d59062e7431b2 | 3,640,631 |
def hasAspect(obj1, obj2, aspList):
""" Returns if there is an aspect between objects
considering a list of possible aspect types.
"""
aspType = aspectType(obj1, obj2, aspList)
return aspType != const.NO_ASPECT | 71907043900d080f2254557fe0bd2420b9bf9ac3 | 3,640,632 |
def gen_decomposition(denovo_name, basis_names, weights, output_path, project, \
mtype, denovo_plots_dict, basis_plots_dict, reconstruction_plot_dict, \
reconstruction=False, statistics=None, sig_version=None, custom_text=None):
"""
Generate the correct plot based on mtype.
Parameters:
----------
denovo_name: ... | 9bb65728017a3f9f2a64ae94cb1ae7e15268c93b | 3,640,633 |
from unittest.mock import Mock
def org(gh):
"""Creates an Org instance and adds an spy attribute to check for calls"""
ret = Organization(gh, name=ORG_NAME)
ret._gh = Mock(wraps=ret._gh)
ret.spy = ret._gh
return ret | 017d044015ff60c91742ea2eb12e2cd7720328c6 | 3,640,634 |
def merge_regions(
out_path: str, sample1_id: int, regions1_file: File, sample2_id: int, regions2_file: File
) -> File:
"""
Merge two sorted region files into one.
"""
def iter_points(regions):
for start, end, depth in regions:
yield (start, "start", depth)
yield (en... | eeb4b8bf73df45ae9d6af39d0d8c9db04251da41 | 3,640,635 |
import hashlib
def get_text_hexdigest(data):
"""returns md5 hexadecimal checksum of string/unicode data
NOTE
----
The md5 sum of get_text_hexdigest can differ from get_file_hexdigest.
This will occur if the line ending character differs from being read in
'rb' versus 'r' modes.
"""
da... | 762115178406c0b49080b3076859a3d1c13ad356 | 3,640,636 |
import json
def recipe(recipe_id):
"""
Display the recipe on-page for each recipe id that was requested
"""
# Update the rating if it's an AJAX call
if request.method == "POST":
# check if user is login in order to proceed with rating
if not session:
return json.dumps({... | 60db178d071d1880410e4e752ec484c4b59b0f96 | 3,640,637 |
def api_program_ordering(request, program):
"""Returns program-wide RF-aware ordering (used after indicator deletion on program page)"""
try:
data = ProgramPageIndicatorUpdateSerializer.load_for_pk(program).data
except Program.DoesNotExist:
logger.warning('attempt to access program page orde... | d4966689b0ea65885456ad7b52cf5dfd845ac822 | 3,640,638 |
def isinteger(x):
"""
determine if a string can be converted to an integer
"""
try:
a = int(x)
except ValueError:
return False
else:
return True | 180cea2f61733ada26b20ff046ae26deffa5d396 | 3,640,639 |
from typing import Tuple
from typing import List
def unmarshal_tools_pcr_values(
buf: bytes, selections: TPML_PCR_SELECTION
) -> Tuple[int, List[bytes]]:
"""Unmarshal PCR digests from tpm2_quote using the values format.
Args:
buf (bytes): content of tpm2_quote PCR output.
selections (TPML... | 3a5b9dd36ca787026bb9bade4b5e5cc175add9e9 | 3,640,640 |
def new_topic(request):
"""添加新主题"""
if request.method != 'POST':
#未提交数据，创建一个新表单
form = TopicForm()
else:
#POST提交的数据，对数据进行处理
form = TopicForm(request.POST)
if form.is_valid():
new_topic = form.save(commit = False)
new_topic.owner = request.user
new_topic.save()
form.save()
return HttpResponse... | 8d41cb1926d809742e89ec7e79ef7bd1ed14443c | 3,640,641 |
from typing import Union
from typing import List
from typing import Any
from typing import Optional
def address(lst: Union[List[Any], str], dim: Optional[int] = None) -> Address:
"""
Similar to :meth:`Address.fromList`, except the name is shorter, and
the dimension is inferred if possible. Otherwise, an e... | ef9e21bb3ef98b12c8ad02c75ccf2cbf6552fd44 | 3,640,642 |
from .views.entrance_exam import remove_entrance_exam_milestone_reference
from .views.entrance_exam import add_entrance_exam_milestone
from sys import path
import base64
import os
import shutil
import tarfile
def import_olx(self, user_id, course_key_string, archive_path, archive_name, language):
"""
Import a ... | 39a83c292e82e5b9c86f793195f140f6249dc57e | 3,640,643 |
import io
def create_scenario_dataframes_geco(scenario):
"""
Reads GECO dataset and creates a dataframe of the given scenario
"""
df_sc = pd.read_csv(io["scenario_geco_path"])
df_sc_europe = df_sc.loc[df_sc["Country"] == "EU28"]
df_scenario = df_sc_europe.loc[df_sc_europe["Scenario"] == scenar... | 8a17d452feeb506bc2c2bf61a91e8473f2097649 | 3,640,644 |
def escape_env_var(varname):
"""
Convert a string to a form suitable for use as an environment variable.
The result will be all uppercase, and will have all invalid characters
replaced by an underscore.
The result will match the following regex: [a-zA-Z_][a-zA-Z0-9_]*
Example:
"my.pri... | c1e57ff3b9648e93a540202f00d0325f91bccde1 | 3,640,645 |
def rms(signal):
"""
rms(signal)
Measures root mean square of a signal
Parameters
----------
signal : 1D numpy array
"""
return np.sqrt(np.mean(np.square(signal))) | 6643ad464b4048ad71c7fb115e97b42d58a84a9c | 3,640,646 |
import os
def get_template_page(page):
"""method used to get the a page based on the theme
it will check the options.theme defined theme for the page first and if it isnt found
it will fallback to options.theme_dir/cling for the template page
"""
templates = ['%s.html' % os.path.join(options.them... | b8e642f9513300f984b5e701b1d18d07d1ab6554 | 3,640,647 |
def get_config(
config_path, trained: bool = False, runner="d2go.runner.GeneralizedRCNNRunner"
):
"""
Returns a config object for a model in model zoo.
Args:
config_path (str): config file name relative to d2go's "configs/"
directory, e.g., "COCO-InstanceSegmentation/mask_rcnn_R_50_F... | e6d2b57bcadd833d625bd0a291fbb8de9d333624 | 3,640,648 |
from typing import Optional
def make_game(
width: int = defaults.WIDTH,
height: int = defaults.HEIGHT,
max_rooms: int = defaults.MAX_ROOMS,
seed: Optional[int] = defaults.SEED,
slippery_coefficient: float = defaults.SLIPPERY_COEFFICIENT,
default_reward: float = defaults.DEFAULT_REWARD,
goa... | 908c772cdc3af5a891bce8c169d744e335da6e61 | 3,640,649 |
def weighted_var(x, weights=None):
"""Unbiased weighted variance (sample variance) for the components of x.
The weights are assumed to be non random (reliability weights).
Parameters
----------
x : np.ndarray
1d or 2d with observations in rows
weights : np.ndarray or None
1d ar... | 2166b214351da22117bf395fda950f1c79ccf0d1 | 3,640,650 |
def start_detailed_result_worker_route():
"""
Add detailed result worker if not exist
:return: JSON
"""
# check if worker already exist
if check_worker_result(RABBITMQ_DETAILED_RESULT_QUEUE_NAME) == env.HTML_STATUS.OK.value:
return jsonify(status=env.HTML_STATUS.OK.value)
if 'db_nam... | 567595574a09ce99f3feb11988bed0ba403b04cd | 3,640,651 |
def _find_next_pickup_item(not_visited_neighbors, array_of_edges_from_node):
"""
Args:
not_visited_neighbors:
array_of_edges_from_node:
Returns:
"""
# last node in visited_nodes is where the traveling salesman is.
cheapest_path = np.argmin(
array_of_edges_from_node[not... | 06dc80e09d5b87cbc94558bee53677c887844b4b | 3,640,652 |
def deformable_conv(input,
offset,
mask,
num_filters,
filter_size,
stride=1,
padding=0,
dilation=1,
groups=None,
deformable_groups=None,
... | 0dce5c2333a0a3dcaa568a85f3a6dec1536d2cfb | 3,640,653 |
def ieee():
"""IEEE fixture."""
return t.EUI64.deserialize(b"ieeeaddr")[0] | b00b13bb16c74bc96e52ad067dc0c523f5b5a249 | 3,640,654 |
def is_in(a_list):
"""Returns a *function* that checks if its argument is in list.
Avoids recalculation of list at every comparison."""
def check(arg): return arg in a_list
return check | 34afbc269c164f0e095b1cbbf4e9576bafc7a9e1 | 3,640,655 |
def get_log_record_extra_fields(record):
"""Taken from `common` repo logging module"""
# The list contains all the attributes listed in
# http://docs.python.org/library/logging.html#logrecord-attributes
skip_list = (
'args', 'asctime', 'created', 'exc_info', 'exc_text', 'filename',
'func... | 95fe6a74cd169c14ac32728f0bb1d16a2aa9e874 | 3,640,656 |
def ldap_is_intromember(member):
"""
:param member: A CSHMember instance
"""
return _ldap_is_member_of_group(member, 'intromembers') | d858afac4870cacc18be79a0b2d6d7d51dd33e07 | 3,640,657 |
def details(request, slug):
"""
Show product set
"""
productset = get_object_or_404(models.ProductSet, slug=slug)
context = {}
response = []
variant_instances = productset.variant_instances()
signals.product_view.send(
sender=type(productset), instances=variant_instances,... | 9ac9b3f975a6501cfb94dd5d545c29c63a47a125 | 3,640,658 |
def applies(platform_string, to='current'):
""" Returns True if the given platform string applies to the platform
specified by 'to'."""
def _parse_component(component):
component = component.strip()
parts = component.split("-")
if len(parts) == 1:
if parts[0] in VALID_PL... | 4692fb0d302948e07a1b2586f614dfcfa5618503 | 3,640,659 |
import threading
def _GetClassLock(cls):
"""Returns the lock associated with the class."""
with _CLASS_LOCKS_LOCK:
if cls not in _CLASS_LOCKS:
_CLASS_LOCKS[cls] = threading.Lock()
return _CLASS_LOCKS[cls] | 98b034a0984431a752801407bfbc5e5694ad44ae | 3,640,660 |
from apysc._expression import event_handler_scope
def _get_expression_table_name() -> TableName:
"""
Get a expression table name. This value will be switched whether
current scope is event handler's one or not.
Returns
-------
table_name : str
Target expression table name.
"""
... | 61d3207d51264e876a472cbd2eea43de730508ac | 3,640,661 |
def measure_option(mode,
number=1,
repeat=1,
timeout=60,
parallel_num=1,
pack_size=1,
check_correctness=False,
build_option=None,
replay_db=None,
sav... | dc3ce9bed84c90d62773e118470943a24896390e | 3,640,662 |
import gc
import time
import joblib
def make_inference(input_data, model):
"""
input_data is assumed to be a pandas dataframe, and model uses standard sklearn API with .predict
"""
input_data['NIR_V'] = m.calc_NIR_V(input_data)
input_data = input_data.replace([np.nan, np.inf, -np.inf, None], np.na... | 472c6eaadf0f9dd705e8600ccb4939d67f387a0e | 3,640,663 |
def property_elements(rconn, redisserver, name, device):
"""Returns a list of dictionaries of element attributes for the given property and device
each dictionary will be set in the list in order of label
:param rconn: A redis connection
:type rconn: redis.client.Redis
:param redisserver: The redis... | 70ee3de0a18a84e9f21df341c685c1380a4ab164 | 3,640,664 |
def _dtype(a, b=None):
"""Utility for getting a dtype"""
return getattr(a, 'dtype', getattr(b, 'dtype', None)) | c553851231f0c4be544e5f93738b43fa98e65176 | 3,640,665 |
def parse_garmin_tcx(filename):
""" Parses tcx activity file from Garmin Connect to Pandas DataFrame object
Args: filename (str) - tcx file
Returns: a tuple of id(str) and data(DataFrame)
DF columns=['time'(datetime.time), 'distance, m'(float), 'HR'(int),
'cadence'(int), 'speed, m/s'(int)]
"""... | bc8052850b9aa9fdab82de2814d38ae62aa298c6 | 3,640,666 |
def get_decay_fn(initial_val, final_val, start, stop):
"""
Returns function handle to use in torch.optim.lr_scheduler.LambdaLR.
The returned function supplies the multiplier to decay a value linearly.
"""
assert stop > start
def decay_fn(counter):
if counter <= start:
return... | d84c0f0305d239834429d83ba4bd5c6d6e945b69 | 3,640,667 |
from typing import Optional
async def is_logged(jwt_cookie: Optional[str] = Cookie(None, alias=config.login.jwt_cookie_name)):
"""
Check if user is logged
"""
result = False
if jwt_cookie:
try:
token = jwt.decode(
jwt_cookie,
smart_text(orjson.du... | e6e3ed4003dc6b60f3b118a98b0fbfb3bcb3b60a | 3,640,668 |
from typing import List
def cached_query_molecules(
client_address: str, molecule_ids: List[str]
) -> List[QCMolecule]:
"""A cached version of ``FractalClient.query_molecules``.
Args:
client_address: The address of the running QCFractal instance to query.
molecule_ids: The ids of the mole... | 33d8c336daba7a79ba66d8823ba93f35fa37c351 | 3,640,669 |
def _domain_to_json(domain):
"""Translates a Domain object into a JSON dict."""
result = {}
# Domain names and bounds are not populated yet
if isinstance(domain, sch.IntDomain):
result['ints'] = {
'min': str(domain.min_value),
'max': str(domain.max_value),
'isCategorical': domain.is_... | c1d9d860ea1735feacfb7349f4516634e217ea5b | 3,640,670 |
def draw_point(state, x, y, col=COLORS["WHITE"], symb="▓"):
"""returns a state with a placed point"""
state[y][x] = renderObject(symb, col)
return state | 64b500fdacda30b0506397d554e8ce6d3b7b4a66 | 3,640,671 |
def _vars_to_add(new_query_variables, current_query_variables):
"""
Return list of dicts representing Query Variables not yet persisted
Keyword Parameters:
new_query_variables -- Dict, representing a new inventory of Query
Variables, to be associated with a DWSupport Query
current_query_vari... | fd5ea2209b374ab9987a05c139ba1f28805f3eff | 3,640,672 |
def Ak(Y2d, H, k):
"""
Calculate Ak for Sk(x)
Parameters
----------
Y2d : list
list of y values with the second derived
H : list
list of h values from spline
k : int
index from Y2d and H
Returns
-------
float
A... | baea453b9c7b023b78c1827dc23bacbd8fd6b057 | 3,640,673 |
def cycle_list_next(vlist, current_val):
"""Return the next element of *current_val* from *vlist*, if
approaching the list boundary, starts from begining.
"""
return vlist[(vlist.index(current_val) + 1) % len(vlist)] | 48e2ac31178f51f981eb6a27ecf2b35d44b893b4 | 3,640,674 |
def _cal_hap_stats(gt, hap, pos, src_variants, src_hom_variants, src_het_variants, sample_size):
"""
Description:
Helper function for calculating statistics for a haplotype.
Arguments:
gt allel.GenotypeArray: Genotype data for all the haplotypes within the same window of the haplotype to be... | 10c3105fe582078d1f24cd740600ccf3c6863407 | 3,640,675 |
import json
def read_cfg(file):
"""Read configuration file and return list of (start,end) tuples """
result = []
if isfile(file):
with open(file) as f:
cfg = json.load(f)
for entry in cfg:
if "start" in entry:
filter = (entry["start"], entry.get("end... | bb9c20b03e95f45708eab17313bc446cc1540308 | 3,640,676 |
import scipy
def least_l2_affine(
source: np.ndarray, target: np.ndarray, shift: bool = True, scale: bool = True
) -> AffineParameters:
"""Finds the squared-error minimizing affine transform.
Args:
source: a 1D array consisting of the reward to transform.
target: a 1D array consisting of ... | 5a6d6d69400327c30d21ae205cab88fd95d856d6 | 3,640,677 |
def mark_item_as_read(
client: EWSClient, item_ids, operation="read", target_mailbox=None
):
"""
Marks item as read
:param client: EWS Client
:param item_ids: items ids to mark as read
:param (Optional) operation: operation to execute
:param (Optional) target_mailbox: target mailbox
... | 80b3fc0b47a9a0044538a2862433a50d5ad36edb | 3,640,678 |
import math
def AIC_score(y_true, y_pred, model=None, df=None):
""" calculate Akaike Information Criterion (AIC)
Input:
y_true: actual values
y_pred: predicted values
model (optional): predictive model
df (optional): degrees of freedom of model
One of model or df is requr... | 6b59dea007f414b0bdc6b972434cb1c2def40bb2 | 3,640,679 |
def to_rgb(data, output=None, vmin=None, vmax=None, pmin=2, pmax=98,
categorical=False, mask=None, size=None, cmap=None):
"""Turn some data into a numpy array representing an RGB image.
Parameters
----------
data : list of DataArray
output : str
file path
vmin : float or list... | 477241dd890b78d7bbf56d3095b42f106af694a7 | 3,640,680 |
import requests
def id_convert(values, idtype=None):
"""
Get data from the id converter API.
https://www.ncbi.nlm.nih.gov/pmc/tools/id-converter-api/
"""
base = 'http://www.pubmedcentral.nih.gov/utils/idconv/v1.0/'
params = {
'ids': values,
'format': 'json',
}
if idtype... | a60698fb20ba94445bbd06384b8523e92bfb91a3 | 3,640,681 |
import base64
def authenticate_user():
"""Authenticate user"""
username = request.form['username']
password = request.form['password']
user = User.query.filter_by(username=username, password=password).first()
if user is not None:
ma_schema = UserSchema()
user_data = ma_schema.dum... | 8e15a3bddf4700c1b207798e3162e3fcef0e7d79 | 3,640,682 |
import typing
import inspect
import warnings
def map_signature(
r_func: SignatureTranslatedFunction,
is_method: bool = False,
map_default: typing.Optional[
typing.Callable[[rinterface.Sexp], typing.Any]
] = _map_default_value
) -> typing.Tuple[inspect.Signature, typing.Opti... | e0655bab739b59b0fad94772654a70ce4e6f84fd | 3,640,683 |
def get_random(X):
"""Get a random sample from X.
Parameters
----------
X: array-like, shape (n_samples, n_features)
Returns
-------
array-like, shape (1, n_features)
"""
size = len(X)
idx = np.random.choice(range(size))
return X[idx] | e493b68ae5b7263786a1a447a0cff78d1deeba24 | 3,640,684 |
def _save_update(update):
"""Save one update in firestore db."""
location = {k: v for k, v in update.items() if k in _location_keys}
status = {k: v for k, v in update.items() if k in _update_keys}
# Save location in status to enable back referencing location from a status
status["location"] = _locat... | 109ca0add974f1ac4b604ca7923dbb3444cee9b0 | 3,640,685 |
def get_secondary_connections(network, user):
"""
Finds all the secondary connections (i.e. connections of connections)
of a given user.
Arguments:
network: the gamer network data structure.
user: a string containing the name of the user.
Returns:
A list containing the secondary connecti... | 4e53f6e43f2fb132932381370efa4b3a3cd4793c | 3,640,686 |
def get_regression_function(model, model_code):
"""
Method which return prediction function for trained regression model
:param model: trained model object
:return: regression predictor function
"""
return model.predict | fca4a0767b1e741952534baf59ac07cece2c9342 | 3,640,687 |
def beam_motion_banding_filter(img, padding=20):
"""
:param img: numpy.array.
2d projection image or sinogram. The left and right side of the image should be
empty. So that `padding` on the left and right will be used to create an beam motion
banding image and be ... | 5191c1f3022711459ce81cfbf0c4d6c6fb7dcd41 | 3,640,688 |
def log(session):
"""Clear nicos log handler content"""
handler = session.testhandler
handler.clear()
return handler | 086e362c8195b917c826fc8b20d3095210ac82fd | 3,640,689 |
import os
import gzip
def load_mnist(path, kind='train'):
"""Load MNIST data from `path`"""
labels_path = os.path.join(path, '%s-labels-idx1-ubyte.gz' % kind)
images_path = os.path.join(path, '%s-images-idx3-ubyte.gz' % kind)
with gzip.open(labels_path, 'rb') as lbpath:
lbpath.read(8)
... | 94a123ea29017bd666deebe95f6926e32edf23d8 | 3,640,690 |
def calculate_dvh(dose_grid, label, bins=1001):
"""Calculates a dose-volume histogram
Args:
dose_grid (SimpleITK.Image): The dose grid.
label (SimpleITK.Image): The (binary) label defining a structure.
bins (int | list | np.ndarray, optional): Passed to np.histogram,
can be ... | 007c7eb9c2ddca9809ac2c86f7bf6d34ed14d41b | 3,640,691 |
import torch
def build_target(output, gt_data, H, W):
"""
Build the training target for output tensor
Arguments:
output_data -- tuple (delta_pred_batch, conf_pred_batch, class_pred_batch), output data of the yolo network
gt_data -- tuple (gt_boxes_batch, gt_classes_batch, num_boxes_batch), groun... | 4608acb06f8fb0d682058841a8b8151e73b89e7b | 3,640,692 |
def dataframe_with_new_calendar(df: pd.DataFrame, new_calendar: pd.DatetimeIndex):
"""
Returns a new DataFrame where the row data are based on the new calendar (similar to Excel's VLOOKUP with
approximate match)
:param df: DataFrame
:param new_calendar: DatetimeIndex
:return: DataFrame
"""
... | 4f5b39494080f3eae9083c78d6dd1666c1945e35 | 3,640,693 |
def get_language_titles():
""" Extract language and title from input file. """
language_titles = {}
input_file = open("resources/events/%s.tsv" % args.event).readlines()
for line in sorted(input_file):
try:
language, title = line.split('\t')[0], line.split('\t')[1].strip()
except IndexError:
language, t... | dedfa8720194aef1b27c7762041692625c2955e7 | 3,640,694 |
def _find_additional_age_entities(request, responder):
"""
If the user has a query such as 'list all employees under 30', the notion of age is
implicit rather than explicit in the form of an age entity. Hence, this function is
beneficial in capturing the existence such implicit entities.
Returns a ... | 971bc0805c607134b6947e0d61ebab6f217c6961 | 3,640,695 |
def merge_local_and_remote_resources(resources_local, service_sync_type, service_id, session):
"""
Main function to sync resources with remote server.
"""
if not get_last_sync(service_id, session):
return resources_local
remote_resources = _query_remote_resources_in_database(service_id, sess... | 1809caa17c3a8a32a5a3236b313c575ec939c0d8 | 3,640,696 |
def alertmanager():
"""
to test this:
$ curl -H "Content-Type: application/json" -d '[{"labels":{"alertname":"test-alert"}}]' 172.17.0.2:9093/api/v1/alerts
or
$ curl -H "Content-Type: application/json" -d '{"alerts":[{"labels":{"alertname":"test-alert"}}]}' 127.0.0.1:5000/alertmanager
"""
alert_json=request.get_... | 1e204bd6dce8368c3401cb7e13ea062abebafd71 | 3,640,697 |
import argparse
def parse_args():
"""Process arguments"""
parser = argparse.ArgumentParser(description=__doc__,
formatter_class=argparse.ArgumentDefaultsHelpFormatter)
parser.add_argument('--train', '-t', required=True, type=str, help="Training ProteinNet data")
... | c37d11327cb0d0baf3049943320c5bed6fb18e18 | 3,640,698 |
def RefundablePayrollTaxCredit(was_plus_sey_p, was_plus_sey_s,
RPTC_c, RPTC_rt,
rptc_p, rptc_s, rptc):
"""
Computes refundable payroll tax credit amounts.
"""
rptc_p = min(was_plus_sey_p * RPTC_rt, RPTC_c)
rptc_s = min(was_plus_sey_s * RP... | e282139921045fe8e286abbde6bb4ae44151a50d | 3,640,699 |
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