content stringlengths 22 815k | id int64 0 4.91M |
|---|---|
def cheat_interest_points(eval_file, scale_factor):
"""
This function is provided for development and debugging but cannot be used in
the final handin. It 'cheats' by generating interest points from known
correspondences. It will only work for the 3 image pairs with known
correspondences.
Args:... | 60,400 |
def get_person_speech_pair(file_name):
"""
XML parser to get the person_ids from given XML file
Args:
file_name(str): file name
Returns:
person_id_speech_pair(dict): Dict[person_id(int) -> speech(str)]
"""
person_id_speech_dict = dict()
with open(file_name, encoding='utf-8') ... | 60,401 |
def decode_jpeg(image_string: tf.Tensor, channels: int = 0) -> tf.Tensor:
"""Decodes JPEG raw bytes string into a RGB uint8 Tensor.
Args:
image_string: A `tf.Tensor` of type strings with the raw JPEG bytes where
the first dimension is timesteps.
channels: Number of channels of the JPEG image. Allowed... | 60,402 |
def get_df(a: int) -> pandas.DataFrame:
"""
Generate a sample dataframe
"""
return pandas.DataFrame(data={"col1": [a, 2], "col2": [a, 4]}) | 60,403 |
def log_softmax(x):
"""Perform log softmax activation on the data
Parameters
----------
data : tvm.te.Tensor
2-D input data
Returns
-------
output : tvm.te.Tensor
2-D output with same shape
"""
assert len(x.shape) == 2, "only support 2-dim log softmax"
m, n = x... | 60,404 |
def hours(datetime: dt.datetime) -> int:
"""
Returns the hours component for the given datetime value, in local time.
"""
return datetime.hour | 60,405 |
def Call_setattr(t, x):
"""Translate ``setattr(foo, bar, value)`` to ``foo[bar] = value``."""
if (isinstance(x.func, ast.Name) and x.func.id == 'setattr') and \
len(x.args) == 3:
return JSExpressionStatement(
JSAssignmentExpression(
JSSubscript(x.args[0], x.args[1]),
... | 60,406 |
def skip_check():
""" Check if an environment variable was used to skip this actor """
if os.getenv('LEAPP_SKIP_CHECK_OS_RELEASE'):
reporting.create_report([
reporting.Title('Skipped OS release check'),
reporting.Summary('Source RHEL release check skipped via LEAPP_SKIP_CHECK_OS_... | 60,407 |
def get_excessive_pdf():
"""
this function is a generator to be used by 'remove_excessive_pdf()'
"""
categories = ['battery', 'catalysis', 'cells', 'city', 'dssc', 'light', 'nano', 'neel', 'solar', 'super alloy']
for category in categories:
path_xml = r'/Users/miao/Desktop/PDFDataExt... | 60,408 |
def triagToNormal(triag, M):
"""Convert triangular matrix to a regular matrix"""
ar = np.arange(M)
mask = ar[:, None] <= ar[None, :]
x, y = np.nonzero(mask)
new = np.zeros((M, M), dtype=triag.dtype)
new[x, y] = triag
return new + new.T | 60,409 |
def search_users_by_id(dataset_path: str, users: list):
"""
Searches the number of movies and genres that a given user or a group of users watched.
The number of movies watched are calculated by counting the number of movies that the user rated.
The number of genres watched are calculated by counting a... | 60,410 |
def bosch_shc_mock_async_zeroconf(mock_async_zeroconf):
"""Auto mock zeroconf.""" | 60,411 |
def get_fsl_metrics(datadir, subject_list):
"""
Calculates both dice similarity coefficients between FNIRT masks and
ground truth lesionmasks as well as SSIM between FNIRT and FLIRT images.
Input: data directory, subjects to calculate DSC and SSIM
Output: list of DSCs and SSIM for each slice of eac... | 60,412 |
def execute_parallel_functions_in_threads(tasks_groups: Deque[List[ThreadedFunctionData]], max_workers, timeout=None)\
-> List[Tuple[Future, str, str]]:
"""
This function takes a Queue (tasks_groups: Deque[List[ThreadedFunctionData]])
of lists, when each queued item represents a list of functions th... | 60,413 |
def plot_entropy(probabilities, models_entropy):
"""
Replicates figure 3 from A Tutorial for Information Theory in Neuroscience.
Args:
probabilities (list): Probabilities for each model.
models_entropy (list): Entropy for each model.
"""
states_vector = range(1, probabilities[0].sha... | 60,414 |
def _download(pep_number):
"""
Fetches PEP files as HTML from python.org.
"""
# PEP URLs look like https://www.python.org/dev/peps/pep-0123/
url = f'https://www.python.org/dev/peps/pep-{_format_pep_number(pep_number)}/'
response = requests.get(url)
if response.status_code == 200:
re... | 60,415 |
def kwargs_function(**kwargs):
"""test with kwargs
:param kwargs: default para eg. x=1 ; kwargs is dictionary
:return: none
"""
for i in kwargs:
print(kwargs[i]) | 60,416 |
def stretched_flow_para_function(
x, beta, relaxation_rate, alpha, flow_velocity, baseline=1
):
"""
flow_velocity: q.v (q vector dot v vector = q*v*cos(angle) )
"""
Diff_part = np.exp(-2 * (relaxation_rate * x) ** alpha)
Flow_part = (
np.pi ** 2
/ (16 * x * flow_velocity)
... | 60,417 |
def svn_path_is_url(path):
"""svn_path_is_url(char const * path) -> svn_boolean_t"""
return _core.svn_path_is_url(path) | 60,418 |
def random_key_generator(key_length):
"""
Creates a random key with key_length written
in hexadecimal as string
Paramaters
----------
key_length : int
Key length in bits
Returns
-------
key : string
Key in hexadecimal as string
"""
return bytes.hex(os.uran... | 60,419 |
def process_error(err):
"""Special handling for consent_required"""
body = err.body.decode('utf8')
if "consent_required" in body:
consent_scopes = ' '.join(DsConfig.permission_scopes())
consent_url = f"{DsConfig.auth_server()}/oauth/auth?response_type=code&scope={consent_scopes}&client_id={D... | 60,420 |
def get_sheet(sheet_id, gid=None, use_cache=True):
"""Returns a list of rows from a sheet."""
query_dict = get_query_dict()
force_cache = RELOAD_ACL_QUERY_PARAM in query_dict
cache_key = 'google_sheet:{}:{}'.format(sheet_id, gid)
logging.info('Loading Google Sheet -> {}'.format(cache_key))
resul... | 60,421 |
def _make_geometry_1_file(filename):
"""See n.comment for details."""
n = netCDF4.Dataset(filename, "w", format="NETCDF3_CLASSIC")
n.Conventions = "CF-" + VN
n.featureType = "timeSeries"
n.comment = (
"Make a netCDF file with 2 node coordinates variables, each of "
"which has a corr... | 60,422 |
def bootstrap_classify(sample_list, fout, header=False, metrics=None,
cutoff_t=0.07, cutoff_min=4, mad=7):
"""
Get cluster_distance, cluster_cutoff, and global_coverage for a sample
"""
# Skip header
if header:
sample_list.next()
# header_fmt = "%s\t" * 4 + "%s\n... | 60,423 |
def conv_forward_im2col(x, w, b, conv_param):
"""
A fast implementation of the forward pass for a convolutional layer
based on im2col and col2im.
"""
N, C, H, W = x.shape
num_filters, _, filter_height, filter_width = w.shape
stride, pad = conv_param["stride"], conv_param["pad"]
# Check ... | 60,424 |
def get_model(pretrained=True):
"""Function to obtain a pytorch resnet50 model with modified final layer
Args:
pretrained (bool): whether to use pretrained weights of the resnet50 model
Returns:
model (pytorch model): a pytorch model with resnet50 architecture with ... | 60,425 |
def dilation_dependent(input_tensor: torch.Tensor,
structuring_element: torch.Tensor,
origin: Optional[Union[tuple, List[int]]] = None,
border_value: Union[int, float, str] = 'geodesic'):
""" This type of dilation is needed when you want a structu... | 60,426 |
def audio_process(songname: str) -> pd.DataFrame:
"""
:rtype: DataFrame of all the features
"""
y, sr = librosa.load(songname, mono=True, duration=30)
rmse = librosa.feature.rms(y=y)
chroma_stft = librosa.feature.chroma_stft(y=y, sr=sr)
spec_cent = librosa.feature.spectral_centroid(y=y, s... | 60,427 |
def estimate_fundamental_matrix(points_a, points_b):
"""
Calculates the fundamental matrix. Try to implement this function as
efficiently as possible. It will be called repeatedly in part 3.
You must normalize your coordinates through linear transformations as
described on the project webpage befor... | 60,428 |
def insert_to_weekday_table(dbName: str, df: pd.DataFrame, table_name: str) -> None:
"""
Parameters
----------
dbName :
str:
df :
pd.DataFrame:
table_name :
str:
dbName :
str:
df :
pd.DataFrame:
table_name :
str:
dbName:str :
... | 60,429 |
def main(video_dir, elan_dir, output_dir,
padding_format=0.1, num_jobs=1,
tmp_dir='/tmp/video_trim', check=False):
"""
The main function for cropping videos in a folder
"""
# Sanity check (if we have all files / folders)
files = check_folders(video_dir, elan_dir, tmp_dir, output_d... | 60,430 |
def maincgi():
"""SWRC Fit to run as CGI"""
import cgi
from io import TextIOWrapper
import unsatfit
f = unsatfit.Fit()
if DEBUG:
import cgitb
cgitb.enable()
# Change encoding of stdout to utf-8
# It is required becaue CGI script runs as another user and may not
# pr... | 60,431 |
def qg8_chunk_get_type(chunk: qg8_chunk):
"""
Return the chunk type as an integer
"""
if not isinstance(chunk, qg8_chunk):
raise TypeError("Argument is not a qg8_chunk")
return chunk.type | 60,432 |
def agg_func(data:pd.DataFrame, object_column:str, agg_list=['nunique', 'count'])->pd.DataFrame:
"""
Parameters
----------
data:pd.DataFrame :
object_column:str :
agg_list :
(Default value = ['nunique', 'count'] :
Returns
-------
A dataframe with... | 60,433 |
def update_top_config_in(top_config_in):
""" Extra updates for build/Config.in """
contents = []
patten = re.compile(r".*(NULL|Null).*")
with open (top_config_in, "r") as cf:
for line in cf.readlines():
match = patten.match(line)
if match:
continue
... | 60,434 |
def _process_triggers(buffers, out_file, draw_png, json_dict):
"""Save the buffers if necessary and report their averages."""
if out_file:
csv_file = _replace_file_suffix(out_file, '.csv')
if json_dict:
json_dict['CSV_FILE'] = csv_file
with open(csv_file, "w", newline='') as ... | 60,435 |
async def test_kubernetes_score_failing_metrics_provider(
aiohttp_server, config, db, loop
):
"""Test the error handling of the Scheduler in the case of fetching the value of a
metric (referenced by a Cluster) from its provider, but the connection has an issue.
"""
routes = web.RouteTableDef()
... | 60,436 |
def get_audits():
"""Get OS hardening login.defs audits.
:returns: dictionary of audits
"""
audits = [TemplatedFile('/etc/login.defs', LoginContext(),
template_dir=TEMPLATES_DIR,
user='root', group='root', mode=0o0444)]
return audits | 60,437 |
def test_init_default_values():
"""Attrs get set to their default values"""
c = CountStore()
s = SendTimeData(c)
assert s._countstore is c
assert s._flushwait == 2
assert s._channel is stat.timedata | 60,438 |
def do_load_list(cc, args):
"""List all loads."""
loads = cc.load.list()
field_labels = ['id', 'state', 'software_version']
fields = ['id', 'state', 'software_version']
utils.print_list(loads, fields, field_labels, sortby=0) | 60,439 |
def draw_component_loss_barchart_s3(ctype_resp_sorted,
scenario_tag,
hazard_type,
output_path,
fig_name):
""" Plots bar charts of direct economic losses for components type... | 60,440 |
def test_xpub_and_subaccount_search(mock_bitcoincore):
"""Test that the options --ga-xpub and --search-subaccounts are mutually exlcusive"""
mock_bitcoincore.return_value = AuthServiceProxy('testnet_txs')
estimate = {'blocks': 3, 'feerate': 1, }
mock_bitcoincore.return_value.estimatesmartfee.return_valu... | 60,441 |
def train():
"""
train model, then construct post-processing network
"""
# load mnist data
transform = Compose([Normalize(mean=[127.5], std=[127.5], data_format='CHW')])
train_dataset = paddle.vision.datasets.MNIST(mode='train', transform=transform)
test_dataset = paddle.vision.datasets.MNI... | 60,442 |
def username_exists(username):
""" Checks if a username aldready exists
:param username: username to be checked
:return: Boolean indicating whether the username exists or not
:rtype: boolean
"""
return not User.query.filter_by(
username=username).first() is None | 60,443 |
def import_series_from_dump(
sources, rectype, loader_class=CDSSeriesDumpLoader
):
"""Load serial records from given sources."""
if rectype == "serial":
dojson_model = serial_marc21
elif rectype == "multipart":
dojson_model = multipart_marc21
else:
dojson_model = journal_marc... | 60,444 |
def group_difference(shap_values, group_mask, feature_names=None, xlabel=None, xmin=None, xmax=None,
max_display=None, sort=True, show=True):
""" This plots the difference in mean SHAP values between two groups.
It is useful to decompose many group level metrics about the model output... | 60,445 |
def buy_ticket(email,price,name,quantity):
"""
Update user balance
:param email: email of user
:param price: price of ticket
:param name: name of ticket
:param quantity: quantity to buy
"""
user=User.query.filter_by(email=email).first()
user.balance=int(float(user.balance)-float(pric... | 60,446 |
def test_validators():
"""Tests of validatorfuncs.py that aren't covered elsewhere"""
# PercentageString
with raises(Invalid, match="Not a valid percentage string"):
validatorfuncs.PercentageString("mess%")
# ListOfType
testfunc = validatorfuncs.ListOfType(int)
assert testfunc([1, 2, 3]... | 60,447 |
def rand_precision_mat(lat_row, lat_col, max_neighbors=8, rho=1):
"""Generate a random spatial precision matrix.
The spatial precision matrix is generated using a rectengular lattice
of dimensions `lat_row` x `lat_col`, and thus the row and colum size of
the matrix is (`lat_row` x `lat_col`).
Para... | 60,448 |
def generate_df(cols_to_keep: List[str]) -> pd.DataFrame:
"""Generates the cleaned dataframe."""
df = pd.read_csv(CSV_URL)
for col in INTEGRAL_COLS:
df[col] = df[col].astype('Int64')
if col.endswith('_flag'):
assert get_unique_values(df[col]) == [0, 1, pd.NA]
df = pd.merge(d... | 60,449 |
def scrape_attackdex(
save_csv: bool = True,
file_path: str = 'data/attackdex.csv'
) -> pd.DataFrame:
"""Return dataframe of scraped attack data from serebii.net"""
gen_dict = {
1: '-rby',
2: '-gs',
3: '',
4: '-dp',
5: '-bw',
6: '-xy',
7: '... | 60,450 |
def get_ppm_df():
"""Get a pandas dataframe containing all PPM data.
Returns:
pd.DataFrame: PPM Pandas dataframe
"""
if app.mongo is None:
return None
docs = app.mongo.get("PPM")
if docs is None:
return None
ppm_dict = {
"date": [],
"total": [],
... | 60,451 |
def utc2local(utc_dtm):
"""
UTC 时间转本地时间（ +8:00 ）
:param utc_dtm:
:return:
"""
local_tm = datetime.fromtimestamp(0)
utc_tm = datetime.utcfromtimestamp(0)
offset = local_tm - utc_tm
return utc_dtm + offset | 60,452 |
def add_base_args(parser: argparse.PARSER, exp='sandbox', dataset='shapes'):
"""base experiments arguments use across all exps"""
parser.add_argument('--dataset', default=dataset,
help='dataset [shapes | binmnist | omniglot | fashion | gmm-toy | gaussian-toy]')
parser.add_argument('-... | 60,453 |
def make_serviceitem_servicedll(servicedll, condition='contains', negate=False, preserve_case=False):
"""
Create a node for ServiceItem/serviceDLL
:return: A IndicatorItem represented as an Element node
"""
document = 'ServiceItem'
search = 'ServiceItem/serviceDLL'
content_type = 'strin... | 60,454 |
def func6():
"""
Get an item and predict with upload
""" | 60,455 |
def main() -> None:
"""
Calculate and output the solutions based on the real puzzle input.
"""
data = aocd.get_data(year=2016, day=12)
print(f'Part 1: {run_program(data).get("a")}')
print(f'Part 2: {run_program(data, 1).get("a")}') | 60,456 |
def load_dataset_with_augmentation(source_dir, augmentation=None, min_count=None):
"""
Wczytanie sampli z opcjonalną augmentacją. Użyć parametru augmentation albo min_count, nie obu na raz.
:param source_dir: katalog źródłowy z plikami PNG.
:param augmentation: krotność augmentacji.
:param min_coun... | 60,457 |
def test_list_unsigned_int_min_length_nistxml_sv_iv_list_unsigned_int_min_length_1_5(mode, save_output, output_format):
"""
Type list/unsignedInt is restricted by facet minLength with value 5.
"""
assert_bindings(
schema="nistData/list/unsignedInt/Schema+Instance/NISTSchema-SV-IV-list-unsignedIn... | 60,458 |
def get_mse(prices, predictions):
"""Get the mean squared error of a network by analysing actual price and the network's corresponding predictions.
:rtype: float64
:param prices: the prices that the predictions aim to mimic
:param predictions: the predictions
:return: the mean-squared error of ... | 60,459 |
def test_read_predictions(
test_app, user_auth_headers, multiple_new_predictions
):
"""Test getting all predictions from predictions table."""
# Verify input with authentication returns all predictions in predictions
# table
endpoint = "/api/v1/topics/read_predictions"
r = test_app.get(endpoint,... | 60,460 |
def test_action_create_post_multipart_form_zero_files_fails(
app: Flask,
indieauthfix: IndieAuthActions,
client: FlaskClient,
testconstsfix: TestConsts,
):
"""Zero files should fail"""
with app.app_context():
z2btd = indieauthfix.zero_to_bearer_with_test_data()
headers = Headers(... | 60,461 |
def find_k_neighbors():
"""Receiving input and returning closest neighbors"""
input_dict = json.loads(request.get_json())
# print(pd.json_normalize(input_dict).info())
result = KNN.kneighbors(
TRANSFORMER.transform(pd.json_normalize(input_dict)),
return_distance=False)
return jsoni... | 60,462 |
def get_databases(task=None):
"""Get list of databases
Parameters
----------
task : str, optional
Only returns databases providing protocols for this task.
Defaults to returning every database.
Returns
-------
databases : list
List of database, sorted in alphabetica... | 60,463 |
def dimensions(image: np.ndarray, kernel: np.ndarray, padding:int, strides:int) -> np.ndarray:
"""
See https://medium.com/analytics-vidhya/2d-convolution-using-python-numpy-43442ff5f381
:param image:
:param kernel:
:param padding:
:param strides:
:return:
"""
x_kern_shape = kernel.sh... | 60,464 |
def intcode_comp(puzzle_input, phase_setting, input_signal):
"""Compute based on the intcode instructions below
# position mode:
# 1: positional add
# 2: positional multiply
# 3: get input and save it at location of parameter
# 4: output value located at parameter
# immediat... | 60,465 |
def watch_insert_queue(queue, queue_name, counter_name, engine, stop_event, sleep_time=5):
"""
A worker process to be launched in a thread that will asynchronously insert or update
objects in the Session using dicts pulled from a redis queue. Using this queuing approach
many cluster jobs are able to pu... | 60,466 |
def copy(cell: SpiceCell) -> SpiceCell:
"""
Copy the contents of a SpiceCell of any data type to another
cell of the same type.
https://naif.jpl.nasa.gov/pub/naif/toolkit_docs/C/cspice/copy_c.html
:param cell: Cell to be copied.
:return: New cell
"""
assert isinstance(cell, stypes.Spic... | 60,467 |
def get_list_of_audios(folder_path, audio_extension = 'wav',
confirm_with_transcript = True,
verbose = False):
"""
Confirm_with_transcript requires: file path in first column
To-do: check if in csv file the header_none will throw count the header as the first ro... | 60,468 |
def get_hash_hex(raw_hash):
"""Creates a nice hex representation of a raw req"""
return raw_hash.encode('iso-8859-1').encode('hex') | 60,469 |
def new_document(source_path: str, settings: Any = None) -> nodes.document:
"""Return a new empty document object. This is an alternative of docutils'.
This is a simple wrapper for ``docutils.utils.new_document()``. It
caches the result of docutils' and use it on second call for instanciation.
This m... | 60,470 |
def to(config, restart):
"""
Switch to specified configuration file
"""
userSystem = platform.system()
if vlc_running(userSystem):
click.echo('VLC is running, stopping it')
if userSystem == 'Windows':
subprocess.call('taskkill /F /IM vlc.exe', shell=True)
elif userSystem =... | 60,471 |
def guild_only() -> AC:
"""A :func:`.check` that indicates this command must only be used in a
guild context only. Basically, no private messages are allowed when
using the command.
This check raises a special exception, :exc:`.ApplicationNoPrivateMessage`
that is inherited from :exc:`.ApplicationC... | 60,472 |
def importable_name(cls):
"""
>>> class Example(object):
... pass
>>> ex = Example()
>>> importable_name(ex.__class__)
'jsonpickle.util.Example'
>>> importable_name(type(25))
'__builtin__.int'
>>> importable_name(None.__class__)
'__builtin__.NoneType'
>>> importable_n... | 60,473 |
def loadDictDDIs(path_file:str):
"""
load the ddi source if the pickle file already existe
:param path_file: path of the picke file
:type path_file: str
:return: dictionary with the ddis sources ids
:rtype: dict[(domain_id_a, domain_id_b)] : id sources
"""
dict_ddis_source_data = {}... | 60,474 |
def print_and_log(msg, log_file, write_mode='a'):
"""
print `msg` (string) on stdout and also append ('a') or write ('w') (default 'a') it to `log_file`
"""
print(msg)
with open(log_file, write_mode) as f:
f.write(msg + '\n') | 60,475 |
def gen_client(api_id: str, api_hash: str) -> Client:
"""Generates Client instance, nothing special
Args:
api_id (str): Telegram App API ID
api_hash (str): Telegram App API Hash key
Returns:
Pyrogram::Client
"""
return Client(
"tgresender",
api_id=api_id,
... | 60,476 |
def encode_argument_text_from_spans(arguments: Iterable[Argument], tokens: List[str]) -> str:
""" Return a string for the CSV field 'answer' """
return SPAN_SEPARATOR.join([span_to_text(span, tokens) for span in arguments]) | 60,477 |
def get_folder_size_human(path, container: DockerContainer):
"""disk usage in human readable format (e.g. '2,1GB')"""
cmd_folder_size = "du -sh {}".format(path)
result = DockerUtils.run_cmd(cmd=cmd_folder_size, container=container)
return result.split()[0].decode('utf-8') | 60,478 |
def is_input_type(graphql_type: "GraphQLType") -> bool:
"""
Determines whether or not the "GraphQLType" is an input type.
:param graphql_type: schema type to test
:type graphql_type: GraphQLType
:return: whether or not the "GraphQLType" is an input type.
:rtype: bool
"""
return isinstanc... | 60,479 |
def which_package(path):
"""
given the path (of a (presumably) conda installed file) iterate over
the conda packages the file came from. Usually the iteration yields
only one package.
"""
path = abspath(path)
prefix = which_prefix(path)
if prefix is None:
from ..exceptions impor... | 60,480 |
def update_counter(new_d_counter, new_a_counter):
"""
This function saves the counters of the amount of payload (data and audio) received in a file
Args:
new_d_counter (integer): The new data counter
new_a_counter (integer): The new audio counter
Returns:
No returns
"""
... | 60,481 |
def shuffle(x):
"""
Modify a sequence in-place by shuffling its contents.
This function only shuffles the array along the first axis of a
multi-dimensional array. The order of sub-arrays is changed but
their contents remain the same.
Parameters
----------
x: _Symbol
The array o... | 60,482 |
def write_vector_binary(fn, X, dtype="int"):
""" write 1darray to binary file
@param
@return
"""
with open(fn, "wb") as fo:
outdata = ""
if dtype == "int":
fmt = "i"
elif dtype == "short":
fmt = "h"
elif dtype == "float":
fmt = "f"
... | 60,483 |
def cartao_trello(request, pedido=None, desc=None):
"""Responsavel por enviar ao cartao trello."""
cliente = TrelloClient(api_key=API_KEY, api_secret=API_TOKEN)
my_boards = cliente.get_board('kyL57xiF')
lista = my_boards.all_lists()
pedido = json.dumps(pedido, cls=UUIDEncoder)
desc = serializer... | 60,484 |
def modify_submit_scripts(filename, jobid, cores=8):
"""Modify the submission scripts to include the job and simulation type in the header."""
with open("submit.pbs", "r") as f:
lines = f.readlines()
lines[1] = "#PBS -N {}\n".format(jobid)
with open("submit.pbs", "w") as f:
f.writeli... | 60,485 |
def flush_database(redis: Redis) -> None:
"""Flushes our database."""
redis.flushdb()
print("Database flushed!") | 60,486 |
def data_reorg_half_daily(instrument_type) -> pd.DataFrame:
"""
将每一个交易日主次合约合约行情信息进行展示
:param instrument_type:
:return:
"""
# engine = Config.get_db_engine(Config.DB_SCHEMA_PROD)
engine = Config.get_db_engine(Config.DB_SCHEMA_DEFAULT)
sql_str = r"select lower(instrument_id) instrument_i... | 60,487 |
def assign_boxes_to_levels(boxlist,
min_level,
max_level,
canonical_box_size,
canonical_level):
"""
Map each box in `box_lists` to a feature map level index and return
the assignment vector.
Args:... | 60,488 |
def spectral_maxpeaks(sign, FS):
"""Compute number of peaks along the specified axes.
Parameters
----------
sig: ndarray
input from histogram is computed.
fs: int
sampling frequency of the signal
Returns
-------
num_p: float
total number of peaks
"""
f, ... | 60,489 |
def get_calling_module(point=2):
"""
Return a module at a different point in the stack.
:param point: the number of calls backwards in the stack.
:return:
"""
frm = inspect.stack()[point]
function = str(frm[3])
line = str(frm[2])
modulepath = str(frm[1]).split('/')
module = str(... | 60,490 |
def raises_on_dir_fd(dir_fd):
"""
Raise on use of dir_fd
Args:
dir_fd: Checks if None
Raises:
NotImplementedError: dir_fd is not None.
"""
if dir_fd is not None:
raise ObjectNotImplementedError(feature="dir_fd") | 60,491 |
def upgrade(ctx, revision="head", sql=False, tag=None):
"""Upgrade to a later version"""
command.upgrade(ctx.obj["migrations"], revision, sql=sql, tag=tag) | 60,492 |
def _pad_keys_tabular(data, sort):
"""Pad only the key fields in data (i.e. the strs) in a tabular way, such that they
all take the same amount of characters
Args:
data: list of tuples. The first member of the tuple must be str, the rest can be anything.
Returns:
list with the strs padded with space cha... | 60,493 |
def depth_based_median(
X: FDataGrid,
depth_method: Optional[Depth] = None,
) -> FDataGrid:
"""Compute the median based on a depth measure.
The depth based median is the deepest curve given a certain
depth measure.
Args:
X: Object containing different samples of a
functiona... | 60,494 |
def get_read_only_permission_name(model: str) -> str:
"""
Create read only permission human readable name.
:param model: model name
:type model: str
:return: read only permission human readable name
:rtype: str
"""
return f"{settings.READ_ONLY_ADMIN_PERMISSION_NAME_PREFIX.capitalize()}... | 60,495 |
def _determine_colnums_to_yield(colnames, fname, dtype_fname):
"""Return a list of integers storing the column numbers of the ASCII history file
corresponding to the ordered sequence determined by the input ``colnames``.
"""
colnames = np.atleast_1d(colnames)
colnames = [s.lower() for s in colnames]... | 60,496 |
def get_all_countries():
"""Returns all countries"""
url = BASE_URL + "all"
return _get(url=url) | 60,497 |
async def find_channel(ctx, userstr, interactive=False, collection=None, chan_type=None):
"""
Find a guild channel given a partial matching string,
allowing custom channel collections and several behavioural switches.
Parameters
----------
userstr: str
String obtained from a user, expec... | 60,498 |
def df_params_generator(number_of_facilities, number_of_tasks, seed=0):
"""
Generate instance parameters for the df problem set mentioned in [1].
Parameters
----------
number_of_facilities: int
the number of facilities to schedule on
number_of_tasks: int
the number of tasks to a... | 60,499 |
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