content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def get_module(obs_space: Space, action_space: Space, config: dict) -> nn.Module:
"""Retrieve and construct module of given name.
Args:
obs_space: Observation space
action_space: Action space
config: Configurations for module construction and initialization
"""
type_ = config.po... | 1554ef3641a1b10468df770c4a0407800ff8547c | 36,532 |
def _replace_event_values_arr(
timearr: NDArray[float], old_value: int, new_value: int
) -> NDArray[int]:
"""Replace the values 'old_value' with 'new_value' for the array."""
timearr[np.where(timearr == old_value)] = new_value
return timearr | 28a23d989798fa6b8dde55c64c0d52df1812f727 | 36,534 |
def validate_api_host_url(url):
"""
Validate SolveBio API host url.
Valid urls must not be empty and
must contain either HTTP or HTTPS scheme.
"""
if not url:
raise SolveError('No SolveBio API host is set')
# Default to https if no scheme is set
if '://' not in url:
url... | 92f8bf36c8b39805c6cc76608f49c9a85efb2b6d | 36,535 |
def search_permission_filter():
"""Filter list of results."""
# Send empty query for admins
if Permission(superuser_access).allows(g.identity):
return Q()
provides = get_user_provides()
# Filter for public records
public = Q('missing', field='_access.read')
# Filter for restricted ... | 9f7219b0cacbb3d27bffcd61e76f1e487f359692 | 36,536 |
def check_depth_submission(path):
"""Checks if all files required for the submission exist and are in the right format."""
ready_for_submission = True
ready_for_submission = ready_for_submission and _check_frames(_get_test_frame_paths('depth', path, '.pfm'))
return ready_for_submission | 80e46c17d531f60976573db775a3cde70a3d01df | 36,537 |
def qual2fastq(quals):
"""
Convert a list of quality scores to a single fastq line
:param quals: A list of quality scores
:type quals: list
:return: A fastq quality string
:rtype: str
"""
quality = [chr(q + 33) for q in quals]
return "".join(quality) | e32f52da5a9ada3fdf8b1789c6e3982044f775f7 | 36,538 |
def generate_honeycomb_coordinates(n_x, n_y, scaling=1.0):
"""
Generate coordinates from a honeycomb mesh which can be used to set up a
cell population.
Parameters
----------
n_x: int
number of columns
n_y: int
number of rows
scaling: float
distance between the c... | 0207826e53714bcd780c28799d0879d53b5b0607 | 36,539 |
import pathlib
def exists(path: str) -> bool:
"""Checks if path exists
e.g
j.sals.fs.exists("/home/rafy/testing_make_dir/test1") -> True
j.sals.fs.exists("/home/rafy/testing_make_dir/fasdljd") -> False
Args:
path (str): path to check for existence
Returns:
bool: Tru... | a3b3717c947656042d3ddcf9e1107d3f6ec9c06d | 36,540 |
def load_token(token):
"""
decrypt token and load User
"""
max_age = app.config['REMEMBER_COOKIE_DURATION'].total_seconds()
data = login_serializer.loads(token, max_age=max_age)
u = model.Users.query.filter_by(email=data[0]).first()
if u and data[1] == u.password:
return u
retu... | afb1d1471c1d3d28e18fef575194fba6b4ede974 | 36,541 |
import this
def heSHjuBBFVLp():
"""Let notation."""
return Injector.let(bar=(this << 2).foo) | 3ada0c74b4c3aa360ebaa15f00457abc4ed89e64 | 36,542 |
def _create_cql_update_query(key_space: str, table_name: str,
set_columns_value_dict: dict,
primary_key_values: dict) -> str:
""" This function will create an update CQL query"""
cql_update = "UPDATE " + key_space + "." + table_name + " SET "
for key... | b133feef14daefe7f5cc82936c2399bad3139672 | 36,543 |
def apply_psd(signal_t, psd, sampling_rate=4096, apply_butter=True):
"""
Take a signal in the time domain, and a precalculated Power Spectral
Density, and color the signal according to the given PSD.
Args:
signal_t: A signal in time domain (i.e. a 1D numpy array)
psd: A Power Spectral D... | 7289ff3135b94197dd9a97cfc44c07700eb553a4 | 36,544 |
def do_zoom_image_job(port_input_name: str,
zoom_factor: float,
do_interpolation: bool = True, port_output_name: str = None,
level: PYRAMID_LEVEL = PYRAMID_LEVEL.LEVEL_0, wave_offset: int = 0, is_rgb: bool = False) -> str:
"""
Function for zoomin... | 67d5475268a494459d4317799b07a5d969491eee | 36,545 |
def update_raid_group_resync_speed(session, raid_id, minimum, maximum,
return_type=None, **kwargs):
"""
Updates the speed at which a RAID group will rebuild using the minimum and
maximum arguments.
:type session: zadarapy.session.Session
:param session: A valid za... | e40d387378e4a0499b2180980ff679b0df82dd46 | 36,546 |
def extract_file_number(file_name):
""" Extract the file number from a file name """
file_name = str(file_name)
dot_contents = file_name.split('.')
hyp_contents = dot_contents[0].split('-')
base_name = hyp_contents[len(hyp_contents) - 1]
return int(base_name[:-1]) | 0b29ba7e75ddfcdc31832641d51f5f0a507021b0 | 36,549 |
from re import S
def solve_rational_inequalities(eqs):
"""
Solve a system of rational inequalities with rational coefficients.
Examples
========
>>> solve_rational_inequalities([[((Poly(-x + 1), Poly(1, x)), '>='),
... ((Poly(-x + 1), Poly(1, x)), '<=')]])
{... | 5e471fc24fc272e33b7ba777694eae038c7874df | 36,550 |
import torch
def BHV_diffeo( ind_current_topo, dictionnary_topology_comparison,
mask_topo_comparison, mask_topo, mask_segments,
singular_template, singular_connections, n_leaves,
template, template_connections,
target, target_connections,
... | 9f13b5a8405895ab66450989f2762029d050323b | 36,551 |
def add_address(x, y):
"""Returns a string representation of the sum of the two parameters.
x is a hex string address that can be converted to an int.
y is an int.
"""
return "{0:08X}".format(int(x, 16) + y) | 3e6fef3d5de0216c68c980b24d9f1ab05bc0a043 | 36,552 |
def inv_linear_DisPrinc_sparse(
Tn=None,
TTn=None,
Tyn=None,
R=None,
yn=None,
sol0=None,
nchan=None,
mu0=None,
precond=None,
verb=None,
verb2head=None,
# specific
chi2n_tol=None,
chi2n_obj=None,
maxiter=None,
tol=None,
**kwdargs,
):
"""
Discrep... | 64be8690491f89c43c945ec8963ef529371065b8 | 36,553 |
import re
def replaceRoadWithRd(a_string):
"""assumes a_string is a string
returns a string, with "Rd." where a_string has "Road" """
pattern = "[Rr]oad"
replacement = "Rd."
result = re.sub(pattern, replacement, a_string)
return result | 08cafdc84c61fc4131f923bf65f271b1d08be0c9 | 36,555 |
def get(columns=None):
"""Get or create MetaData singleton."""
if columns is None:
columns = _DEFAULT_COLUMNS
global _METADATA
if not _METADATA:
_METADATA = MetaData(columns)
return _METADATA | ef37b70a7f870543b5e19ed290e2fe3cbb26b015 | 36,556 |
def read_data(report_name: str):
"""Читает исходные данные по стоимости портфеля из файла"""
data = pd.read_excel(REPORTS_DATA_PATH / f'{report_name}.xlsx',
sheet_name=SHEET_NAME,
header=0,
index_col=0,
converter... | 714513b7c9538cbf7823fb1099420320dcd884a3 | 36,557 |
def extract_fcp_data(raw_data, status):
"""
extract data from smcli System_WWPN_Query output.
Input:
raw data returned from smcli
Output:
data extracted would be like:
'status:Free \n
fcp_dev_no:1D2F\n
physical_wwpn:C05076E9928051D1\n
channel_path_id:8B\n
npiv_wwp... | bbe9de1f075fa68a4130c44afea9d388b1a678d5 | 36,558 |
def prepare_design_symmetry(D: np.ndarray) -> np.ndarray:
"""Add to the design matrix strip simmetric to the one in the input
Args
----
D: np.ndarray
The design matrix as it comes from build_Design_Matrix
Returns
-------
New design matrix with appended the simmetric angles
... | 2e5f1d9c01cf847f19985d51f04d0bf9e84821f7 | 36,559 |
def generate_output_html(htmlfile):
"""Load HTML template and add current date, return result"""
try:
with open(htmlfile) as f:
html = f.read().format(date_string)
return html
except Exception as ex:
logger.error('Exception occured while loading template {}. Details: ... | e7794d1d132858b45fba326d983b31d0e7c366e9 | 36,560 |
from typing import Union
from typing import Dict
def check_existence_and_date_s3(query_hash: Union[int, str]) -> Dict[str, str]:
"""Check if a query hash has corresponding result and query json on S3
Parameters
----------
query_hash :
The query hash to check
Returns
-------
:
... | 1d25d4869aa874b85a85dd376f8ff59e07712375 | 36,561 |
def verifying_key_from_hex(key: bytes):
"""Load the VerifyingKey from a compressed or uncompressed hex public key.
"""
id_byte = key[0]
if not isinstance(id_byte, int):
id_byte = ord(id_byte)
if id_byte == 4:
# Uncompressed public point
# 1B ID + 32B x coord + 32B y coord = 6... | c87efcee39bd92a0988aeb85b3b055d8d6a951c7 | 36,562 |
def get_graph():
"""Creates dictionary {node: {child1, child2, ..},..} for current
TensorFlow graph. Result is compatible with networkx/toposort"""
ops = tf.get_default_graph().get_operations()
return {op: children(op) for op in ops} | a0b912395a550bf2f2b2bf929f7ab90b97a3ba98 | 36,563 |
def find_coord(find_coords, search_coords, tol=1.e-6):
""" {TEST}
Find the index for the coordinate in search_coords that matches
the coordinate find_coords.
:param find_coords: Coordinates for the point to find
:type find_coords: tuple[ float ]
:param search_coords: Coordinate lists ... | 94fe9cee4ac639337f0a9b4649ac5893133b06f9 | 36,564 |
def nonOverlappingMinima(minDists, m, fromSeq=None):
"""
Returns the indices i such that (minDist[i] <= minDists[j] or
fromSeq[i] != fromSeq[j]) for all j in [i, i + m - 1]. If fromSeq
is not provided, the latter test always fails (i.e., both dists are
assumed to be from the same sequence, and thus able to overlap... | 5362dbdfa42b8d0aedb7b780720f793baae7ab4c | 36,565 |
def draw_contour_(contour_img,
contour,
color,
gradient_colors=("red", "blue"),
min_size=10,
filled=True,
compute_mask=False):
""" Draw a contour as optionally fill it with color.
Differs from draw_contour() i... | 73f4bc88699d9d090972a474f8826eb47e5a9cc8 | 36,566 |
def list_to_include_array(data_list):
"""Convert python list to ble_gattc_include_array."""
data_array = _populate_array(data_list, driver.ble_gattc_include_array)
return data_array | f84aea79d33d9de01047841891a67570ed161da7 | 36,568 |
def check_for_valid_numerical_encoding_of_labels(labels):
"""
Checks whether the labels are numerical labels satisfying the following
requirements:
1. each label is an integer greater or equal to zero
2. the smallest label is zero
The labels encoded by applying "sklearn.preprocessing.La... | a4e356b3d8680b330f6c6b9aff1082e95b39ec72 | 36,569 |
import torch
def video_pack_sequences(in_batch):
"""
Pad the variable-length input sequences to fixed length
:param in_batch: the original input batch of sequences generated by pytorch DataLoader
:return:
out_batch (list): the padded batch of sequences
"""
# Get the number of return va... | 983b86cfb867268ca0759b4cdf29052153d97785 | 36,570 |
from operator import sub
def generate_nologin_hash(public_string):
"""Generate hash for users who are not logged in"""
hex_hash = sha256(settings.EMAIL_SECRET_KEY + public_string).hexdigest()
# Decode the hex hash into base64, reducing the length of the code
b64_hash = hex_hash.decode('hex').encode("... | 7781848e151d1054d8338bef1728863c02a53b3c | 36,571 |
def compute_v_dot_upper_bound(dV, mean, variance=None, beta=2.):
"""
Compute the safe set
Parameters
----------
dV: np.array
The derivatives of the Lyapunov function at grid points
mean: np.array
mean of the dynamics (including prior dynamics as mean)
variance: np.array
... | 927cec0dda57b55da9e30a1cd21e1c5ef8f7fa84 | 36,572 |
import json
def decode_resource_id_options(request):
""" Extract resource ID options from a HTTP request, making sure the keys have the same names as the
ResourceIdentifier object's fields. """
return {
# Resource ID
'resource_id': request['id'],
'target_platforms': json.dumps(requ... | 97f61b5c1ffb82cb9f29caebb9a85d42348fbfa7 | 36,576 |
import json
def load_data(data):
""" Wrapper to load json data, to be compatible with Python3.
Returns: JSON data
Keyword arguments:
data: might be bytes or str
"""
if type(data) == bytes:
return json.loads(data.decode("utf-8"))
else:
return json.loads(data) | c33c661c2a42d162d06c3e17487e072908fd0bf4 | 36,578 |
import itertools
def Pauli_strings(num_qubits):
"""Returns the matrix representation of Pauli strings of size=num_qubits. e.g., for num_qubits=2, it returns
the matrix representations of ['II','IX','IY','IZ,'XI','YI',...]"""
pauli_labels = ['I', 'X', 'Y', 'Z']
Pauli_strings_matrices = [Pauli(''.join(p... | 256fa607695c067c4d4c13543a5c7010e2c0b212 | 36,579 |
def factor_rank_autocorrelation(factor_data, period=1):
"""
Computes autocorrelation of mean factor ranks in specified time spans.
We must compare period to period factor ranks rather than factor values
to account for systematic shifts in the factor values of all names or names
within a group. This ... | d1a527313aa44f0fbd0b9abe23581934c163cd1f | 36,580 |
def indices_for(df, nprocs):
"""
group rows in dataframe and assign each group to each process
Args:
df: Pandas dataframe object
nprocs: number of processes used
Returns:
indeces grouped to each process
"""
N = df.shape[0]
L = int(N / nprocs)
indices... | c68408e6fcf70b885ca86fb80f8c31b0bd07e334 | 36,581 |
def _dynamic_range(fig, range_padding=0.05, range_padding_units='percent'):
"""Automatically rescales figure axes range when source data changes."""
fig.x_range.range_padding = range_padding
fig.x_range.range_padding_units = range_padding_units
fig.y_range.range_padding = range_padding
fig.y_range.r... | e3c82605ab20ad6ab3c6f2a6e6d32479a9012ed2 | 36,582 |
def norm(x):
"""
This function takes an array and makes it strictly superior to zero.
This is NOT a normalizing function, as it doesn't scale each value relatively to the others.
:param x: Array to make superior to zero.
:return: Resulting array.
"""
return np.log(np.exp(x + 1)) | 630c77de869d36d02b987fa6d3c755501d162cd5 | 36,583 |
def _match_expr(parent, expr):
"""Match expressions to rewrite `A.select(A < 5)` into select expression
The argument must match the parent, so this _won't_ be rewritten: `A.select(B < 5)`
"""
args = expr.args
op = expr.op
if (
expr.method_name == "apply"
and len(args) == 2
... | 8eaaff2b5edf7c36ea500479bee70c7d67cff412 | 36,584 |
def generate_new_api_key(user_id):
"""
Generate a new API key for the user.
:param user_id: User ID for which to generate a new API key
:return: User object for that user ID with a modified API key
:raises UserDoesNotExistException: If no user exists with the given user_id
"""
user = get_us... | e374fbc5f7da258e67ec2101741230e34b6b3eb9 | 36,585 |
def account_reset():
"""Handler for account reset."""
return account_handler("account_reset") | c395bd8fa18080ddc4d9aaf8183d899aee6dfbd3 | 36,586 |
def _get_validated_config_mapping(name, config_schema, config_fn):
"""Config mapping must set composite config_schema and config_fn or neither."""
if config_fn is None and config_schema is None:
return None
elif config_fn is not None and config_schema is not None:
return ConfigMapping(confi... | cddab5a70c64d1985ce65e56887138cf9a9a0aef | 36,587 |
def find_ops(optype):
"""Find ops of a given type in graphdef or a graph.
Args:
optype: operation type (e.g. Conv2D)
Returns:
List of operations.
"""
gd = tf.get_default_graph()
return [var for var in gd.get_operations() if var.type == optype] | 03d1902adc0872170b618257da488c4ec05d276d | 36,588 |
def continuous_ob(orderbooks):
"""
Creates a continuous orderbook timeseries data, for all orderbooks included as input. i.e. all timestamps
that one orderbook has and the other dont, in the latter repeates the information of the former, with
this, the output will deliver two historical orderbooks with ... | 03a5124a58f51625b1a63535f8b7ca3d06058aa7 | 36,590 |
from util import PriorityQueue # i use PriorityQueue to store the frontier
def aStarSearch(problem, heuristic=nullHeuristic):
"""Search the node that has the lowest combined cost and heuristic first."""
"*** YOUR CODE HERE ***"
frontier = PriorityQueue() # initialize frontier
explored = s... | 99ff121f4415f7e730963b73ee5269f310f8ce4d | 36,591 |
def split_irregular_date_list(date_list):
"""
Takes a list of dates and groups it into blocks of continuous dates.
It returns the begin and end of those blocks
eg. A list with continuous dates from januari to march and september to october will be split into two lists
Parameters
----------
... | d246e25dacb4d1c7e60f40cbafb653a90d4556d3 | 36,593 |
import tqdm
import torch
def validate(args, fid_stat, gen_net: nn.Module, writer_dict=None):
"""
Compute both IS and FID (torch).
:param args:
:param fid_stat:
:param gen_net:
:param writer_dict:
:return:
"""
# eval mode
gen_net = gen_net.eval()
eval_iter = args.num_eval_i... | ceadaca144a937eadf7b47fd69ae9b1e65700c14 | 36,594 |
def transform_observation(attribute, data):
""" place to hook any transforms on te data """
output = data
if (attribute == 'observation_time'):
output = data[16:]
return output | 875d35a6c66cf57fe7ac4995f913b8dbe70e63f3 | 36,595 |
import json
def batch_handler(repo, request):
"""Handle batch requests."""
req = {}
try:
req = json.loads(request)
except json.JSONDecodeError:
return create_response(status_code=400)
operation = req['operation']
objects = req['objects']
res_objects = []
for obj in ob... | 5a159645edcda539f3a56f53ffb5f3273b7cea49 | 36,596 |
def cos_angular_separation_tf(y_true, y_pred):
"""
Compute the angular separation in radians
between two pointing direction given with lat-long
Parameters
----------
lat1: 1d `numpy.ndarray` , latitude of the first pointing direction
long1: 1d `numpy.ndarray` longitude of the first pointing ... | 2ff53483b94f07d7c34e096bf5c2757813aa152a | 36,597 |
def all_stocks():
"""
#查询当前所有正常上市交易的股票列表
:return:
"""
data = pro.stock_basic(exchange='', list_status='L', fields='ts_code,symbol,name,area,industry,list_date')
# d = data["symbol"].values
# random.shuffle(d)
return data["symbol"].values | 0f8ef4b09ea908b0012b6605feaf9c97287e069c | 36,598 |
def get_dependent_databases(demand_dict):
"""Demand can be activitiy ids or tuple keys."""
db_labels = [
x[0] if isinstance(x, tuple) else get_activity(x)["database"]
for x in demand_dict
]
return set.union(*[Database(label).find_graph_dependents() for label in db_labels]) | 37edfaa699bc2d1deefd93dc90961ac76b0470d5 | 36,599 |
from typing import Sequence
def build_action_observations(
observations: Sequence[data.Observation]
) -> Sequence[data.ActionObservation]:
"""Given observations, creates the actions associated with them.
Args:
observations: a sequence of Observation objects capturing a PanoContext, a
heading, and t... | cec2c5007c7192e778ecf3c6edd5ef2aef781850 | 36,600 |
def handle_write_config_request(config_request):
"""Set piaware-config setting
Expected config_request format:
{
"request": piaware_config_write
"request_payload" : {"rtlsdr-gain": 20, "wireless-network": "no"}
}
request_payload must be a dictionary of key/v... | 8e91fdafac073813e4365eb1f535375bfdb4bf8a | 36,601 |
import numpy
def nanallclose(x, y, rtol=1.0e-5, atol=1.0e-8):
"""Numpy allclose function which allows NaN
Args:
* x, y: Either scalars or numpy arrays
Returns:
* True or False
Note:
Returns True if all non-nan elements pass.
"""
xn = numpy.isnan(x)
yn = numpy.is... | 053fdc260d215304f0e913a468775dd4ce86dba9 | 36,602 |
import re
def get_current_data(cfg):
"""Reads the output file to see what are the contents of the arrays and the version control string
Returns a dictionary with:
'etag' -- Etag of the source file used to render the file. As stored in the version control string
'date' -- Date of the source file used to render t... | 7b17b6410b2f38c9fc21cd4904b43673dc227014 | 36,603 |
def vgg13_bn(pretrained=False, requires_grad=False, **kwargs):
"""VGG 13-layer model (configuration "B") with batch normalization
Args:
pretrained (bool): If True, returns a model pre-trained on ImageNet
"""
if pretrained:
kwargs['init_weights'] = False
model = VGG(make_layers(cfg['... | 38f4e2ca715b310c914c7753ac90b66c5c305916 | 36,604 |
def get_shape_label():
"""Get shape of the labels in Thyroid dataset"""
return (None,) | cc7bd48de40de185f39450e360846adc81383aca | 36,605 |
import random
def pick_random_question(df_questions, topic_id):
"""Randomly pick a question for a given topic
Random choice uses 1/box as weight
Parameters
----------
df_questions: DataFrame
DataFrame containing questions
columns = ['ID_question', 'ID_topic', 'label', 'link', 'bo... | 036997a7b80dda05fcb4f1d7a029567b257e35c1 | 36,606 |
def CTDensityPixel_getGray():
"""CTDensityPixel_getGray() -> vpl::img::tDensityPixel"""
return _Core.CTDensityPixel_getGray() | 9b61f68a6231ef2c2685c5755653eeb8b37e65ab | 36,607 |
import math
def bfm2Mesh(bfm_info, image_shape=default_init_image_shape):
"""
generate mesh data from 3DMM (bfm2009) parameters
:param bfm_info:
:param image_shape:
:return: mesh data
"""
[image_h, image_w, channel] = image_shape
pose_para = bfm_info['Pose_Para'].T.astype(np.float32)
... | 2683ec2f532ca8e837797bd09a586e84716b953e | 36,608 |
def _merge_css_item(item):
"""Transform argument into a list with a single string value."""
if isinstance(item, (list, tuple)):
return _merge_css_list(*item)
item = f"{item}" if item else ""
return [item] | dd844fa6ede8b4515e02ab3498242b7a03443af2 | 36,610 |
def get_iscsi_auth_groups(client):
"""Display current authentication group configuration.
Returns:
List of current authentication group configuration.
"""
return client.call('get_iscsi_auth_groups') | 4a31f6c1f1ea4fa543ee731d54e699cdd108e512 | 36,611 |
def _filter_returned_ops(fn):
"""Filtering out any ops returned by function.
Args:
fn: a function
Returns:
A tuple of (
Wrapped function that returns `None` in place of any ops,
dict that maps the index in the flat output structure to the returned op
)
"""
returned_ops = {}
def wr... | b4e3cdb09746dad6ffccd547c3c94ce5b779dbcb | 36,614 |
def subclass_of(*args):
"""
This type validation function can be used in two modes:
* providing two arguments (c, ref_type), it returns `True` if issubclass(c, ref_type) and raises a IsWrongType
error if not. If ref_type is a set of types, any match with one of the included types will do
* provid... | 7f9e8d224756d5da0eb775cb6861788d6c558fc5 | 36,615 |
from typing import Tuple
from typing import List
from typing import Dict
from typing import Any
def info() -> Tuple[List[Dict[str, Any]], List[Dict[str, Any]]]:
"""
Get input and output schemas
:return: OpenAPI specifications. Each specification is assigned as (input / output)
"""
input_sample = ... | 282f60cacac69865736c58712c4bfbdb2f5e2c24 | 36,616 |
def region_growing_lab_hsv(I, max_dist, min_pixels=1, smoothing=0):
"""Performs region growing on an color image in HSV space.
Parameters
----------
I : ndarray of float32
3D array representing the image
max_dist : float
maximum hsv distance to add a neighbou... | f595b92a71ac1f15c0bf5683ed0c49ae3b9b8035 | 36,617 |
def wolf_mass(sigma, Re):
"""
Wolf mass estimator from Wolf+ 2010
Args:
sigma :
1D line of sight velocity dispersion in km/s
Re :
2D radius enclosing half the stellar mass in pc
Returns: estimate of the dynamical mass within the half light radius in Msun
... | 7b5258858e932c0b15eaf45a32d08dcf655f1c24 | 36,618 |
async def delete_pokemon(id: int):
"""
## Deletes a Pokemon by ID.
Path Parameters
---------------
Pokemon ID.
Body Parameters
---------------
None
Returns
-------
None
"""
if not await PokemonRepository.exists(id=id):
# Non-existent Pokemon, ... | 5d0917fbae0bcfeb4c567dd0d15979c02637fb38 | 36,619 |
import requests
import itertools
def anagrams_in_list(word, list_of_words):
"""Given a word (str) and list of words (list or tuple, a list is returned
with the valid anagrams of the word in the list of words
Args:
- word (str): The word that you want to test
- list_of_words (list or tuple... | 3b8621c81bae1fb274cd740113c844ecfeaa83ce | 36,620 |
def oavol(x, y, z, v, xx, yy, zz, pmap=None, weight=10, nx=2, ny=2,
verbose=False):
"""
Objective analysis interpolation for 3D fields
Parameters
----------
x: array [2-D]
x-values of source data
y: array [2-D]
y-values of source data
z: array [3-D]
z-value... | a1a8d1e0e474fea0a99bd4173c0ba2aa892a4773 | 36,622 |
from typing import List
from typing import Optional
def create_study(
name: str,
description: str,
run_ids: List[int],
alias: Optional[str],
benchmark_suite: Optional[int],
) -> OpenMLStudy:
"""
Creates an OpenML study (collection of data, tasks, flows, setups and run),
where the runs ... | bfb3f8ca2650b59754dba8f72077543d91167050 | 36,623 |
def nats_to_params(nat1, nat2, nat3, nat4):
"""
natural parameters to distribution parameters
"""
alpha = nat1 + (1./2)
nu = -2 * nat4
mu = nat3 / nu
beta = - nat2 - (nu * (mu**2) / 2)
return alpha, beta, mu, nu | 56fba0a886d35948edf570c6eb379f6e0175b589 | 36,624 |
def depth_type_order(order):
"""Create a function which constrains paragraphs depths to a particular
type sequence. For example, we know a priori what regtext and
interpretation markers' order should be. Adding this constrain speeds up
solution finding."""
order = list(order) # defensive copy
... | ed22f589f05df52c736c29ccbaef22c14eb24b6b | 36,625 |
from typing import Dict
def euclidean(a: Dict, b: Dict)->float:
"""Return the euclidean distance beetween the given dictionaries.
Parameters
----------------------------
a: Dict,
First dictionary to consider.
b: Dict,
Second dictionary to consider.
Returns
---------------... | 88311a84606ede224437b87a128b76d0da458474 | 36,626 |
def get_system_category():
"""获取文档分类"""
systems = ComponentSystem.objects.all()
doc_category = {}
for system in systems:
if not system.has_display_doc:
continue
system_doc_category = system.doc_category
doc_category.setdefault(system_doc_category.id, {
'na... | 712669eaa4b044f9fd62e2589a1462678aabbc2f | 36,627 |
from typing import Iterable
def _serialize_graph(ops):
"""
Serializes a graph and returns the actual protobuf python object (rather than serialized
byte string as done by `serialize_graph`).
"""
assert isinstance(ops, Iterable), "Ops passed into `serialize_graph` must be an iterable"
ops = Op.... | 65458fe18fff382c90aa9a1bb97f3d654ccac766 | 36,628 |
def single_cell_variables(model_name, dat, let):
"""
Single cell variable of model_name.
1: head, 2:temp, 3:conc, 4:kz, 5:lz, 6:por (inside mem)
11: head, 12:temp, 13:conc, 14:kz, 15:lz, 16:por (not inside mem)
"""
output_path = rm.make_output_dirs(model_name, dat, let)[0]
enkf_inpu... | 711389851f58dcce652d1bb891ca8cd48b805a15 | 36,629 |
import sqlite3
def add_signature(db, df):
"""Adds `signature` from database `db` to dataframe `df`."""
events = df["event_no"]
with sqlite3.connect(db) as con:
query = (
"select event_no, pid, interaction_type from truth where event_no in %s"
% str(tuple(events))
)
... | 5ff85591bf03393cbc428abde40242e6ca3c39f0 | 36,630 |
import re
def getLLVMVersion(llvmProgram):
"""executes the program with --version and extracts the LLVM version string"""
versionString = getVersion(llvmProgram)
printLLVMVersion = re.search(r'(clang |LLVM )?(version )?((\d)\.\d)(\.\d)?', versionString, re.IGNORECASE)
if printLLVMVersion is None:
... | 2facaaf70824febdfb6a79956138963d0f61b6ce | 36,631 |
def lambert(disk):
"""Converts coordinates on the disk to spherical coordinates, using
the Lambert azimuthal equal-area projection.
Args:
disk: Array of shape [..., 2] representing points on the disk.
Returns:
phi, theta: Spherical coordinates
>>> phi, theta = lambert(_TEST_DISK_R... | 6e6461e06fe0092ea9806fba1874a5153d3115cb | 36,633 |
def mandel_geom(params, x, etc = []):
"""
This function computes a transit shape using equations provided by Mandel & Agol (2002).
Parameters
----------
midpt: Center of eclipse
width: Eclipse duration from contacts 1 to 4
rp_rs: Planet-star radius ratio
b: Impact parameter
flux... | 62c2b41435600381200af66b9465b054c1a1d0f9 | 36,634 |
def from_columns(mapping, fp):
"""
Write columns to the open file opbject ``fp`` in XPT-format.
The mapping should be of column names to equal-length sequences.
Column labels are restricted to 40 characters. The XPT format also
requires a separate column "name" that is restricted to 8
characte... | 55b5436bfbb99ddaa90b413171111748d1a799b6 | 36,636 |
def list_random_circuits_onelen(opLabels, length, count, seed=None):
"""
Create a list of random operation sequences of a given length.
Parameters
----------
opLabels : tuple
tuple of operation labels to include in operation sequences.
length : int
the operation sequence length... | 6f3a849a54d201dcd39c743b997c9409b5c834da | 36,638 |
def get_number_of_pictures(directions,cutOff,referenceAtom):
"""
Finding the amount of copies
of the original SuperCell
.---------------------------.
/ \ \
/ \ \
/ \ ... | e175e12329707312cd3aa78cb027e70b728756fc | 36,640 |
def _create_extension_feed_items(client, customer_id, campaign_resource_name):
"""Helper method that creates extension feed items.
Args:
client: a GoogleAdsClient instance.
customer_id: a str Google Ads customer ID, that the extension feed items
will be created for.
campaign... | 54eb2ff33e8bea07c8dad0a91201d63484bd9924 | 36,641 |
def rgb2hsv(img):
""" Use matplotlib to convert rgb to hsv (TA allowed) """
return (rgb_to_hsv(img.astype(np.float32) / 255.) * 255).astype(np.uint8) | 2afaefd68fbc68c1c36e8a0000fca999d7f30e83 | 36,642 |
def get_territory_options_formatted():
"""
Formats list of territory options per Dash dropdown standards.
Example of returned data structure:
{'country': [{'label': 'Algeria', 'value': 'Algeria'}, {'label': 'Angola', 'value': 'Angola'}], 'state': [{'label': 'Alberta, Canada', 'value': 'Alberta, Canada'}... | 5359d6bb6581772244a66c7a7568275589145f48 | 36,643 |
def _get_resources(rtype='resources'):
""" resource types from state summary include: resources, used_resources
offered_resources, reserved_resources, unreserved_resources
The default is resources.
:param rtype: the type of resources to return
:type rtype: str
:param role: the name of the role... | 04746e33685d503adb9f0a3527a7bc203ab639b3 | 36,644 |
def feature_name_to_placeholder(feature_name, params):
"""
Get a placeholder for the given feature.
Args:
- feature_name: name of the feature (<string>).
Returns:
Return as a tensor tf.placeholder.
"""
feature_type, shape = (
DATASETS_METADATA[feature_name].dtype,
... | b5785a985517b318e919f03e1f11eaef10fa5827 | 36,645 |
from typing import List
import re
def split_words(value: str) -> List[str]:
"""Split a string on words and known delimiters"""
# We can't guess words if there is no capital letter
if any(c.isupper() for c in value):
value = " ".join(re.split("([A-Z]?[a-z]+)", value))
return re.findall(rf"[^{DE... | 690dfb75c5e22c5d2bbd33797aabe2af41b09518 | 36,646 |
from typing import Dict
from typing import Any
def setup(app: sphinx.application.Sphinx) -> Dict[str, Any]:
"""Entry point for sphinx theming."""
app.require_sphinx("3.0")
app.add_config_value(
"pygments_dark_style", default="native", rebuild="env", types=[str]
)
app.add_html_theme("furo... | 2c196ef86fba7e81f540f4feff3f6c5b924d1940 | 36,647 |
def ldns_key_set_pubkey_owner(*args):
"""LDNS buffer."""
return _ldns.ldns_key_set_pubkey_owner(*args) | f13a90fb29b158254f053523aa387ccf68b41128 | 36,648 |
def graph(ich, no_stereo=False):
""" inchi => graph
"""
return automol.convert.inchi.graph(ich, no_stereo=no_stereo) | 6925a830838ced5714155b3274517574e5dcdb88 | 36,649 |
def get_rancher_services_list():
"""
:return: array of all system services
"""
service_list = []
stacks = get_request(
RANCHER_API_URL + RANCHER_API_STACKS_LIST_ENDPOINTS + '?system=false',
True
)
for stack in stacks['data']:
services = get_request(
RANCH... | 4a9d8076539702fdb754c2a75d9684a712e714b5 | 36,650 |
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