content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def get_provider_info(provider_name):
"""Get provider info matching given provider name"""
return PROVIDERS_INFO.get(provider_name) | 6f95c632ad8842777390751a1bc5f7cf5a62b4e0 | 37,362 |
def close_ticket(session, ticket_id, return_type=None, **kwargs):
"""
Closes a support ticket for the VPSA.
:type session: zadarapy.session.Session
:param session: A valid zadarapy.session.Session object. Required.
:type ticket_id: int
:param ticket_id: The support ticket 'id' value as return... | 79f5f2dba8ab993ddfa3fecb110a205cb3ded066 | 37,364 |
import re
def verify_mpls_ping(
device, address=None, mask=None, expected_max_success_rate=100,
expected_min_success_rate=0,count=None, source=None, vc_id=None,
tunnel_id=None, vrf=None, max_time=60, check_interval=10,):
"""Verify ping
Args:
device ('obj'): Device object
... | 3efc533d5c97caf577c32efd5cc784816a1b9949 | 37,365 |
def cryoscope_v2_processing(
time_ns: np.array,
osc_data: np.array,
pnts_per_fit_first_pass: int = 4,
pnts_per_fit_second_pass: int = 3,
init_guess_first_pass: dict = {},
fixed_params_first_pass: dict = {},
init_guess_second_pass: dict = {},
max_params: dict = {},
min_params: dict = ... | 8540da6a1458c84a88bbde6a58aceaaea883444e | 37,367 |
def getCurrentSettingsAsDict():
"""
Returns the current babylon parameters saved in the root node as a dict
\nout:
dictionary key: pymxs user property string
value: var
"""
sceneRoot = sceneUtils.getSceneRootNode()
newDict = dict()
for val in BabylonPYMXS.babylonParame... | aeb36e9a4cc456c5ff46eb0503db14de423ddf49 | 37,369 |
def isjsonclass(class_: type) -> bool:
"""Check if a class is jsonclass.
Args:
class_ (type): The class to check.
Returns:
bool: True if it's a jsonclass, otherwise False.
"""
return hasattr(class_, '__is_jsonclass__') | 3234cf62beb03aa968888dd8ec3b65f4c5f4cab3 | 37,370 |
import math
def mu_from_pdiv(pdiv, nobj=3):
"""
Get population count based on divisions per objective for NSGA-III
"""
h = int(math.factorial(nobj + pdiv - 1) / (math.factorial(pdiv) * math.factorial(nobj - 1)))
mu = int(h + (4 - h % 4))
return mu | b4087bcab34a0fe03c6a1d5c9e2d9fb1f47d79f0 | 37,371 |
def on_reload_plugins(branch='master'):
"""
`[branch]` - reload plugins in debot
"""
resp = []
try:
git_plugins_manager = current_app.extensions['git_plugins_manager']
except KeyError:
pass
else:
resp.append(git_plugins_manager.reload(branch))
dispatcher = current... | 17b521b3812a3c5130e7595df63389d4abac9fdb | 37,372 |
import copy
def _get_model_cfg(fname):
"""Grab configs necessary to create a model.
These are deep copied to allow for safe modification of parameters without
influencing other tests.
"""
config = _get_config_module(fname)
model = copy.deepcopy(config.model)
return model | 9f64d51e20a60c61388b2488dbfa9c640c103d84 | 37,373 |
def make_inference_request(serving_name, data, verb=":predict"):
"""
Submit an inference request
Example use-case:
>>> from hops import serving
>>> serving.make_inference_request("irisFlowerClassifier", [[1,2,3,4]], ":predict")
Args:
:serving_name: name of the model being served
... | ee59fb0949390c91ee53200447b290f87fa0742a | 37,374 |
import tqdm
def online_variance(paths):
"""
Calculate mean and variance in an online way (Welford's algorithm)
:param paths:
:return:
"""
mean = np.zeros((conf.img_h, conf.img_w, conf.dest_channels))
M2 = np.zeros((conf.img_h, conf.img_w, conf.dest_channels))
i = 0
for i, path in ... | 67b09232c0518ea60b6f2fbfe439f2bd607b9c02 | 37,375 |
def check_requires(request):
"""
This call checks whether a certain value requires another input to be filled.
"""
values = map(int, request.POST.getlist('value[]'))
model = apps.get_model(request.POST.get('app'), request.POST.get('model'))
required_values = model.objects.filter(**{
requ... | cca52b6d7b02d9deb05e3f72aa5dd3186e404f5d | 37,376 |
def start(name):
"""
Start running a recipe.
:param name:
The recipe name. Must be one of the items returned by /list
:return:
object
response
One of:
ok
error
message
Only present if response is "error" and there is a ... | 34615ec7e2b8832f2458275116c423adf5b344ad | 37,379 |
def ate_exploitability(dist, payoff_tensor, p=1, aggregate=np.mean):
"""Compute Tsallis regularized exploitability of dist for non-symmetric game.
Args:
dist: list of 1-d np.arrays, current estimate of nash distribution
payoff_tensor: (n x A1 x ... x An) np.array, payoffs for each joint action
assume... | a7b119c3f38c3bcacc075abbc1457a6cb57058eb | 37,381 |
def angular_cl_cov_SSC(cosmo, cltracer1, cltracer2, ell, tkka,
sigma2_B=None, fsky=1.,
cltracer3=None, cltracer4=None, ell2=None,
integration_method='qag_quad'):
"""Calculate the super-sample contribution to the connected
non-Gaussian covarian... | 1abac47d2414ba7fd297fc829285285749e811e4 | 37,382 |
def locals_in_putty():
"""Hard-coded information regarding local variables
"""
locals_d = {
# k: index
# v: dict of local properties
0x14007DA84: {
6: {'name': 'v6', 'size': 8, 'type_name': '__int64'},
7: {'name': 'v7', 'size': 8, 'type_name': '__int64'},
... | 52398e84aa324f8f751e2ca50bee9ad33be6eeb5 | 37,383 |
def _post_apply_columns(
pydf: "PyDataFrame",
columns: ColumnsType,
) -> "PyDataFrame":
"""
Apply 'columns' param _after_ PyDataFrame creation (if no alternative).
"""
pydf_columns, pydf_dtypes = pydf.columns(), pydf.dtypes()
columns, dtypes = _unpack_columns(columns or pydf_columns)
if ... | 7373b774b5e76da1b8820feff4ccc7d37e6a572f | 37,384 |
import torch
def join_blocks(splitted, final_shape):
"""Join blocks to reobtain a splitted image
Attribute:
splitted (tensor) = image splitted in blocks, size = (N_blocks, Channels, Height, Width)
final_shape (tuple) = size of the final image reconstructed (Height, Width)
Return:
... | e6cf7382011e7f1ce0463f949e227e677cd0e8f2 | 37,385 |
def log_agg_function_alpha(alpha, cent1, cent2):
""" Allows additional scaling of log_agg_function with a parameter alpha
to roughly get retain factors for BA use
retain factor 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9
alpha 1.7, 1.0, 0.7, 0.5, 0.4, 0.26, 0.2, 0.1, 0.015 """
return np.cli... | e488468838987bc95ea12789e6abd4b7fe499843 | 37,386 |
from typing import Type
from re import T
def from_yaml(c: Type[T], s: str, de=YamlDeserializer, **opts) -> T:
"""
Take yaml string and return deserialized object..
>>> from dataclasses import dataclass
>>> from serde import deserialize
>>>
>>> @deserialize
... @dataclass
... class Set... | 5eb24a55ec63dbe01e4efa8c536c84e120b875f2 | 37,387 |
from ..interfaces.nibabel import Binarize
def init_n4_only_wf(
atropos_model=None,
atropos_refine=True,
atropos_use_random_seed=True,
bids_suffix="T1w",
mem_gb=3.0,
name="n4_only_wf",
omp_nthreads=None,
):
"""
Build a workflow to sidetrack brain extraction on skull-stripped dataset... | d8708f3d1d4c93dafd901bbf89704c6677473657 | 37,388 |
def dvi( redchan, nirchan ):
"""
DVI: Difference Vegetation Index
dvi( redchan, nirchan )
"""
redchan = 1.0*redchan
nirchan = 1.0*nirchan
result = ( nirchan - redchan )
return result | afa5ffffccc3053598cd3597de1efd3dcfc4cd8f | 37,389 |
def needs_min_max_values(mode, buckets):
"""
Returns True, if an encoding mode needs minimum and maximum column values, otherwise False
"""
return not buckets and mode in ['one-hot',
'one-hot-gaussian',
'one-hot-gaussian-fluent',
... | 50ae2b899e5957347061dd59905290506c460093 | 37,390 |
def _rolling_player_f(player, gfcf, **kwargs):
"""
Creates a graph with CF% or GF% (on plus off). Use gfcf to indicate which one.
:param player: str or int, player to generate for
:param gfcf: str. Use 'G' for GF% and GF% Off and 'C' for CF% and CF% Off
:param kwargs: other filters. See scrapenhl2.... | 6d3ef2716f5d72c7599c6fd68fdb0d09ce7a148f | 37,391 |
def param(myval=None):
"""Parameterised decorator example"""
if myval:
print(f"Param: {myval}")
def decorator(func): # real decorator
decorated["param"].append(func)
name = func.__name__
@wraps(func)
def wrapparam(*argv): # inner to return
arg_str = ",... | 9b709bb0fca9d8efbbcd489161c39dcfc9c84dbc | 37,392 |
def listed_list(list_list):
"""Return presentable string from given list
"""
return '{} and {}'.format(', '.join(list_list[:-1]), list_list[-1]) if (
len(list_list) > 1) else list_list[0] | da35296196fff56816fe7b0427985ee278238dab | 37,394 |
import re
def remove_plus_signs(_s: str) -> str:
"""Removes plus signs from string"""
return re.sub(pattern=r'\+', repl=r'', string=_s) | 53cf3117221ce82578a20d75e7eb807c2d41b8fc | 37,395 |
def has_more_than_two_occurence(x):
"""creating a function for finding words with more than 2 occurences"""
if(x[1]>1):
return(x) | 6e39c6cf4b473480786add14e76112c122ce439f | 37,396 |
def compute_gas_flux(gas_coords, star_data, times, params, bins, fig_name,
plot_flag=True):
"""Calculate the flux contribution from each point particle.
Assumptions: light travel time from stars to gas plus the
recombination time is shorter than the time it takes the
stars to move ... | 1f643946723f60b366795c44242796aeceeb984b | 37,397 |
def evaluate(predictions, answerss):
"""
Returns a tuple of (F1 score, EM score, sentence score)
The sentence score is our evaluation method for determining the
effectiveness of finding the correct sentence within the context
paragraph that may contain the answer. This metric is much softer
than the F1 or... | f5edd23faf0a46cfd1407285b8d7d38d8b2b955c | 37,398 |
from typing import Any
from typing import Union
from typing import List
def style(
text: Any,
*,
fg: Union[str, fg] = '',
bg: Union[str, bg] = '',
bold: bool = False,
dim: bool = False,
underline: bool = False
) -> str:
"""
Apply ANSI colors and/or styles to a string and return it.... | bf1ad5b0d88f74a2496d4ad7e4951e4b89414916 | 37,399 |
def get_shape_tags(tags, font_info=(cv2.FONT_HERSHEY_COMPLEX_SMALL, 0.75, (255,255,255), 1)):
"""Get information about how much the list of tags will occupy (width and height)
with the current configuration.
Arguments:
tags -- list of strings/tags you want to check shape.
Keyword arguments:
fo... | a95d546432adb1e0d1656a8420ba63c29e4d23bd | 37,400 |
def Intersection(S1x, S1y, D1x, D1y, S2x, S2y, D2x, D2y):
"""
Find intersection of 2 line segments
:param S1x: x coordinate of segment 1's start point
:param S1y: y coordinate of segment 1's start point
:param D1x: x coordinate of segment 1's end point
:param D1y: y coordinate of segment 1's end... | 2dba8839ebf24b55fe3c1b7797e53c7e0c3ed72a | 37,401 |
def optimization_writer():
""" Writes an input file for a geometry optimization.
"""
return opt_string | b3cc7ba7d96c0f2ee584a09e0dadc8db2b8e3eb4 | 37,402 |
def _offset(ax, x, y):
"""Provide offset in pixels
Parameters
----------
x : int
Offset in pixels for x
y : int
Offset in pixels for y
Idea borrowed from
http://www.scipy.org/Cookbook/Matplotlib/Transformations
but then heavily extended to be compatible with many
reinc... | e8051a75f5cdcb5de0f36d354ee10bd72398045c | 37,403 |
def augment(input_img, input_angle):
"""
Increase the training data set.
"""
output_images, output_angles = [],[]
"""
Fun fact: I had this condition around the data flipping code
but these function calls somehow SIGNIFICANTLY slowed down
the training process!!!
if ((abs(in... | 56b5e06a71631264a897f4b6a7fd78f93410c304 | 37,404 |
def check_host(hwaddr, ipaddr, config, args, timestr):
"""
check host infos against the config
returns changes, updated_config
"""
changes = []
# get hostname
hostname = get_hostname(ipaddr)
if hwaddr in config:
# shortcut
c = config[hwaddr]
# check statu... | 6d20938332dec55acb480abcde32e53cb30c7084 | 37,405 |
def Update(dEntities):
"""This will initiate all of the different updates that need done for
the Chunk Manager Entity."""
Update_Load_List({"LoadList":dEntities["ChunkMan"].get_component("LIST:LoadList"), \
"ChunkDataDir":dEntities["ChunkMan"].get_component("MISC:C... | 18518cdb7718718599c7943db86e0adfe4e93945 | 37,406 |
import sqlite3
def getIdForTable(table):
"""resolve a table name to an ID"""
with sqlite3.connect(DB_PATH) as conn:
db = conn.cursor()
db.execute('SELECT table_id FROM tables WHERE table_name=?', [table])
return db.fetchone()[0] | 8b11309b50d4bc7fef35a3096f5bf8f42e36b0a2 | 37,407 |
def blasi(wood, gas, tar, char, T, dt, s=1):
"""
Primary and secondary kinetic reactions from Table 1 in Blasi 1993 paper.
Note that primary reaction parameters in table are not cited correctly from
the Thurner and Mann 1981 paper, this function uses the correct parameters.
Parameters
---------... | 813f532b5750ec6c7e1a402a980ac2041b0bdebf | 37,408 |
def davis_southern_women_graph() -> nx.Graph:
"""Returns Davis Southern women social network.
This is a bipartite graph.
References
----------
.. [1] A. Davis, Gardner, B. B., Gardner, M. R., 1941. Deep South.
University of Chicago Press, Chicago, IL.
"""
G = nx.Graph()
# Top n... | af8d628cb03db7a64609b36af59c93b24299f2cc | 37,410 |
def is_extension_enabled(extension_name, service):
"""A function that will check the list of enabled extensions from config
"""
config_dict = {
'compute': CONF.compute_feature_enabled.api_extensions,
'volume': CONF.volume_feature_enabled.api_extensions,
'network': CONF.network_featu... | 524fc5abb3826058ab16cb3ee4b516d6eb3e2a01 | 37,411 |
import requests
def existing_droplets(token):
"""infos about existing Marian droplets."""
params = {
'tag_name': 'marian'
}
url = 'https://api.digitalocean.com/v2/droplets'
request = requests.get(url, headers=headers(token), params=params)
return request.json()['droplets'] | 824a955d4c928004c265991b7268061f24c1cd27 | 37,412 |
import io
import numpy
def overlayLabel(dataSource, labelSource, sink = None, alpha = False, labelColorMap = 'jet', x = all, y = all, z = all):
"""Overlay a gray scale image with colored labeled image
Arguments:
dataSouce (str or array): volumetric image data
labelSource (str or array): ... | 7f84924fac34a0aea0fefc088b45eee32ac24f8d | 37,413 |
def constrain_sum(a, b, result):
"""Constrain a + b == result. Note that overflows are forbidden,
even if the result is never used."""
# This is a ripple-carry adder.
c = False # carry bit
# Optimization: stop at the the necessary number of bits.
max_bit = max([i+1 for i in BITS if a.bits[i].i... | 09371cbae682bfdef52b5db95b5dc904b7eb2ca2 | 37,414 |
def min_pos_root(a, b, c):
"""Returns the minimum positive root for the function ax²+bx+c = 0. If no positive roots exist, returns None"""
roots = all_pos_roots(a, b, c)
if not roots or len(roots) == 0:
return None
return roots[0] | afd619261002d8f65b982f74858b198d848eb572 | 37,415 |
from typing import Iterable
def patch_module(module):
"""
Extends all iterables in the module
with ``asq.queryables.Queryable`` methods.
Applies the same as ``patch_type`` to every appropriate member of
the module.
Args:
module: Module object or its __dict__.
Returns:
A ... | d5f0f7e7def1ca0938e0a52930eb3f746996e403 | 37,416 |
def trace_func(resource):
"""Trace calls to function using provided resource name"""
@wrapt.function_wrapper
def _trace_func(wrapped, instance, args, kwargs):
pin = Pin.get_from(molten)
if not pin or not pin.enabled():
return wrapped(*args, **kwargs)
with pin.tracer.tr... | 968fc735e755d8960d5d457f3ae2923a655a087e | 37,417 |
def search_for_item(project):
"""Generate a string search key for a project"""
elements = []
elements.append(project['attributes']['title'])
return u' '.join(elements) | 3ca0850b0c7b01900609aedfa41fd3fb8b86abac | 37,418 |
def sort_by_status(ori_list):
"""
sort feature progress
:param ori_list:
:return:
"""
for i in range(len(ori_list) - 1):
for j in range(len(ori_list) - 1 - i):
if compare_two_features(ori_list[j], ori_list[j + 1]):
ori_list[j], ori_list[j + 1] = ori_list[j + 1... | 389add5b03278b7cee490b507fcc0b9261a2dd4c | 37,419 |
def perturb_word(word: str, skip_stopwords=True, skip_punctuation=True):
"""
:param skip_stopwords:
:param word:
:return: pertubed word, None if no perturbation is available
"""
if skip_stopwords and word.lower() in stopwords.words('english') \
or skip_punctuation and not word.lowe... | 6334896e3f489ed1cc0baa7cfe785179579c77c5 | 37,420 |
def boxzoom(viewer, event):
"""Enable box zoom."""
def _get_shape():
if "Control" in event.modifiers:
return Shape.VERTICAL
elif "Shift" in event.modifiers:
return Shape.HORIZONTAL
return Shape.BOX
# make sure box is visible
if not viewer.drag_tool.tool.... | 49716b217b04a78c4dada95a60c9aa6c4f8e2f4c | 37,421 |
def gen_coeffs(num_dim):
"""
Helper function for generating a linear simulation.
:param num_dim: number of dimensions for the simulation
:return: a vector of coefficients
"""
coeff_vec = np.array([1 / (x+1) for x in range(num_dim)])
return coeff_vec.reshape(-1, 1) | 87fe28331ec0be2d4eef59ca68fbd2055d49304f | 37,422 |
def read_passwords(addr):
""" read passwords as list from a file """
with open(addr) as f:
lines = f.readlines()
pwlist = [clean_word(line) for line in lines]
pwlist = [x for x in pwlist if x != ""]
return pwlist | e2190dee8fe0b5afbc3f0b7e23d7267e837be975 | 37,423 |
def get_model(name, version, project_name=None):
"""
Get a specific model version given a model name and a version.
For example if you run this:
>>> from hops import model
>>> model.get_model('mnist', 1)
You will get version 1 of the model 'mnist'
Args:
:name: name of the model
... | 2e82f7b6703df0313abc29cbadbe6e140a01aeb2 | 37,424 |
def index():
"""Return the home page."""
return render_template('index.html') | 193f867973725dc89f5b213217cb15bc6980a66a | 37,425 |
def generate_scope_name(data_loader):
"""
Generate scope name according to computation graph.
Args:
data_loader (OnnxDataLoader): Data loader instance.
Returns:
list[str], generated scope name.
"""
init_dag = _build_connection(data_loader)
try:
if USER_DEFINED_PATTE... | d57495866f8c100271b2327669b6245409052060 | 37,426 |
def get_active_questions(netid, course_id):
"""Gets all questions that are not yet being helped
Returns a list of questions with their question text, id, enqueue_time, and the asking student's name
or None if the requester is not a TA
"""
if not verify_is_ta(netid, course_id):
return None
... | 95d670927231e20cbbc9f468dace1ebe6c760eef | 37,428 |
def hamiltonian(edges, directed=False, time_limit=5, concorde=False, precision=0):
"""
Calculates shortest path that traverses each node exactly once. Convert
Hamiltonian path problem to TSP by adding one dummy point that has a distance
of zero to all your other points. Solve the TSP and get rid of the ... | 24a857d2184c20ef00b46fb06aa2a1c87a21299c | 37,429 |
def analytic_kernel(k):
"""Calculate the X4 kernel from the X2 kernel (for proof see appendix in paper)"""
k_size = k.shape[0]
# Calculate the big kernels size
big_k = np.zeros((3 * k_size - 2, 3 * k_size - 2))
# Loop over the small kernel to fill the big one
for r in range(k_size):
for ... | 385ccd1e2ae4906780df909aa2e7830208466e48 | 37,430 |
def simple_3dof_arm(seg1_len, seg2_len, seg3_len, q0, base=None):
"""Creates a simple human-like robotic arm with 7 links and 2 segments
with the desired lengths and starting joint configuration
:param seg1_len: The length of the first segment of the arm
:type seg1_len: int
:param seg2_len: The le... | 8a0c211cf72c764dc8b973c04ce8a045397660c8 | 37,431 |
def collect_nodes(points, highlighted_nodes=[], color='#79FF06', highlighted_color='blue', width=200, highlighted_width=400):
"""
Собирает необходимые нам вершины в нужный формат
Parameters
----------
points : [str, str, ...]
Вершины графа.
highlighted_nodes : [str, str, ...], optional
... | a3a218b5f8c8c25a0f13a4154f12779a84726f9d | 37,432 |
def conv3x3(in_planes, out_planes, stride=1):
"""3x3 convolution with padding"""
conv3x3 = nn.Sequential(
nn.Conv2d(in_planes, out_planes, kernel_size=3, stride=stride,
padding=1, bias=False),
nn.BatchNorm2d(out_planes),
nn.ReLU(inplace=True),
)
return conv3x3 | f1c658e9115a741b34ebb9e6c89965d97d18cbf9 | 37,433 |
def get_ransac_pipeline():
""" Function return pipeline with lagged transformation in it """
node_ransac = PrimaryNode('ransac_lin_reg')
node_final = SecondaryNode('linear', nodes_from=[node_ransac])
pipeline = Pipeline(node_final)
return pipeline | 4a6e0b21fe35691753885cd509c5344b96f4da67 | 37,436 |
def feature_names_from_extractor_list(feature_extractors):
"""
get a list of feature names from a list of feature extractors
:param feature_extractors: a list of feature extractors
:return: a list of the feature names for each extractor (think first row of .csv file)
"""
feature_names = [feature... | 2f23aa860137e70270e9c7d564df5dacfa1d22a2 | 37,437 |
def blank_publish_view(request):
"""Save posts into db w/o publishing."""
return poster(lambda: tasks.fetch_and_publish(force=True, blank=True)) | 6883c038bdfbee7d975134152fd83f61f830b22f | 37,439 |
import io
def read_txt(filename, encoding='utf-8'):
"""Text file reader."""
with io.open(filename, 'r', encoding=encoding) as f:
return f.read() | 2ca0d80bddc49b793e8cbc63c513410154b4d460 | 37,440 |
def level_detect(x, fs, attack_ms=0.1, release_ms=100, mode='peak'):
"""Performs level detection on an input signal
Parameters
----------
x : ndarray
Input vector
fs : float
Sample rate [Hz]
attack_ms : float, optional
Time constant for attack [ms]
release_ms : float... | dacde4e210f2d9d821c26cfc7a2965dbc3bcebe4 | 37,441 |
import copy
def get_doc_permissions(doc, verbose=False, user=None, ptype=None):
"""Returns a dict of evaluated permissions for given `doc` like `{"read":1, "write":1}`"""
if not user: user = frappe.session.user
if frappe.is_table(doc.doctype): return {"read": 1, "write": 1}
meta = frappe.get_meta(doc.doctype)
... | 06698057696dbb6385de951668baddd535ae7b5c | 37,442 |
def get_job_type(name):
"""Returns job type based on its name."""
if 'phase1' in name:
return 'phase1'
elif 'phase2' in name:
return 'phase2'
elif 'dfg' in name:
return 'dfg'
else:
return 'other' | 50db4a7833028b0a0944a4b915d82a8cabf91595 | 37,443 |
def ames_score(emb):
"""
Measure the ames positive probability of molecule,
more close to 1, more "toxic"
Parameters
----------
emb : numpy.ndarray, size (x,512)
the cddd descriptor of molecule
Returns
-------
ames : float
ames score
"""
ames = ames_model.p... | 5dc55dd36c8627ea97314227e9f72e168b488da8 | 37,444 |
def quadrature(func,a,b,args=(),tol=1.49e-8,maxiter=50, reference=False):
"""Compute a definite integral using fixed-tolerance Gaussian quadrature.
Description:
Integrate func from a to b using Gaussian quadrature
with absolute tolerance tol.
Inputs:
func -- a Python function or method to integr... | dc3188ced57ae6d138410bcbd34595f4142f078c | 37,445 |
def read_sensor():
"""Returns the orientation in quaternion form"""
quat = sensor.quaternion
return quat | f8dfc128987f03de35ef9ed7e1bd184919411989 | 37,447 |
def is_resnet(name):
"""
Simply checks if name represents a resnet, by convention, all resnet names start with 'resnet'
:param name:
:return:
"""
name = name.lower()
return name.startswith('resnet') | 6310d849b76a1006c7c2e97405aa9f0ebc53a78b | 37,448 |
from typing import Optional
def _get_object_system_id(obj) -> Optional[str]:
"""Finds the System id (as a string) for the supplied object"""
system_id = None
if isinstance(obj, System):
system_id = obj.id
elif isinstance(obj, BrewtilsSystem):
system_id = ObjectId(obj.id)
elif type... | 40545e2a572954a8ed1e2e81de17e47a7941616c | 37,449 |
def _regress_1d(design_matrix, boot_mean, boot_var, Nc_list, treatment_idx, **kwargs):
"""
Performs hypothesis testing for a single gene for many bootstrap iterations.
Here, :X_center:, :X_center_Sq:, :boot_var:, :boot_mean: should have the same number of rows
"""
num_boot = boot_mean.shape[1]
nonneg = Fal... | 042f3ea973db7602c7b3e3e712715c39788e1ca4 | 37,451 |
def handle_pmid_25502872(filename):
"""Bergseng, ..., Sollid. Immunogenetics 2015 [PMID 25502872]"""
return None | 25a11d19293c59e4ae636b0b26389dbfd6b74955 | 37,453 |
def expand_schema_for_inheritance(schema):
"""
Allows the schema to support inheritance.
The schema supports configs that (optionally) point to zero or more parent YAML configs
(using a path) that will be taken as base configurations to be overwritten.
"""
return merge({'inherit': stlistorstring... | 045505ea4634aef392196c1c174fefd8c1b541e6 | 37,454 |
def option_two(choice_two):
"""Functions to for different methods to search the database"""
if choice_two == 1:
query_sub = search_record.search_date()
elif choice_two == 2:
query_sub = search_record.search_time()
elif choice_two == 3:
query_sub = search_record.search_string()
... | 6b1b20f452cfa24eed6c67346215da204a5d3012 | 37,455 |
import re
def parse_fmt(fmt: str) -> (int, int):
"""Parse Q<m>.<n> string
Parameters
----------
fmt
Format string in the form 'Qm.n', where
m is the number of integer bits
n is the number of fractional bits
Returns
-------
n, m
Number o... | f72133fdef9bbf40eb89d977d217376df8f2a3bd | 37,456 |
from typing import Dict
def invert_dictionary(mapping: Dict) -> Dict:
"""Invert the keys and values of a dictionary."""
remap = {v: k for k, v in mapping.items()}
if len(remap) != len(mapping):
raise ValueError("Dictionary cannot be inverted; some values were not unique")
return remap | 911aee48eff3bf0d980e5ad054c77c8a3081e232 | 37,457 |
def store_file(file):
"""Stores the file to specified destination"""
destination = "/".join(["api/test_docs", file.name])
file.save(destination)
return destination | 1118415a1c1b7c2a33ecc539df7bf27dfd783d16 | 37,458 |
def getNumberedTypedString(items, maxLen=5000, numPrefix=''):
"""get a string that has each item of the list on its own line,
and each item is numbered on the left from zero"""
digits = 0
n = len(items)
while n > 0:
digits += 1
n //= 10
digits = digits
format = numPrefix + '%... | 4fa1f93c420c555093f1fc3b3ba3e43a4ce839f0 | 37,460 |
def mpl_dict(params):
""""Convert _ to . for easier mpl rcparams grid definition"""
return {k.replace('_', '.'): v for k, v in params.items()} | a8c4ae683205a1412a73f00e6965cb345ec63a3e | 37,461 |
def data_source_get(context, data_source):
"""Return the Data Source or None if it does not exist."""
return IMPL.data_source_get(context, data_source) | 5da4900f1e1099830253293ddf7391279d75c38e | 37,463 |
def add_pseudo_counts(ccm,ad=None,num=None):
"""Add a small number of fake mutations or 'pseudo counts' to the co-clustering and ancestor-descendant matrices for
subchallenges 2 and 3, each in their own, new cluster. This ensures that there are not cases where
either of these matrices has a variance of zero... | f239f26ac0349bb3011b74f8a8d040fb34adb8a9 | 37,464 |
def compute_coefficients(xyz):
"""Fit a plane to the first three dimensions of a matrix
Parameters
----------
xyz : array-like
The matrix of data to fit the plane to.
Returns
-------
np.array
1-dimensional array with four values, the coefficients `a`, `b`, `c`
and `... | 07fb6af0c63a75f2a4e88e2a01836a212b2a8a57 | 37,465 |
def _build_step(
docker_api, variables, build_config, step_config, from_image, should_ignore_cache,
should_remove_container):
"""
Builds the image for the given step
:param docker_api: The api interface that is to be used to connect to the docker daemon
:param variables: The list of var... | 437a279364bd89e83ffb01d39089bf23f2480994 | 37,466 |
from functools import reduce
def Sum(onnx_node, ng_inputs): # type: (NodeWrapper, List[TensorOp]) -> Op
"""Calculate element-wise sum of the input tensors."""
return reduce(ng.add, ng_inputs) | 7d1080e490a4cf6d7d06d0f95c903013df730525 | 37,467 |
def test_df_keys():
"""List of keys to be used for populating a bucket with DataFrames"""
return {
'avro': ['df.avro'],
'csv': ['df.csv'],
'csv.gz': ['df.csv.gz'],
'csv.zip': ['df.csv.zip'],
'csv.bz2': ['df.csv.bz2'],
'csv.xz': ['df.csv.xz'],
'psv': ['df.p... | 3b008664744fb6abf8960caebe658ecc2f6525af | 37,468 |
def first_existing(d, keys):
"""Returns the value of the first key in keys which exists in d."""
for key in keys:
if key in d:
return d[key]
return None | eb9f34f1f5adb0a8e44127fe777e35ca8d36dc04 | 37,469 |
def _expand_right(a, n):
"""Insert multiple axes of size 1 at right end of tensor's shape.
Equivalent to performing `expand_dims(..., -1)` `n` times.
Args:
a: tensor into which extra axes will be inserted.
n: number of inserted axes.
"""
return tf.reshape(a, tf.concat([
tf.shape(a), tf.ones([... | 69a3acb3aa717070ac3e1410c0f30fa71acbc56b | 37,471 |
def unregister_mod(mod: Mod) -> bool:
"""
unregisters a mod from the global cache `mods`
:param mod: mod to unregister
:return: if it successfully unregistered it
"""
if mod.name_or_class_name() not in mods:
return False
get_event_loop().create_task(mod.unloaded())
del mods[mod.... | 48e018ebb2d56fd2e6713a6df4ae3f59160d78a8 | 37,472 |
def errors(module):
""" dict: {name:Exception or None} for tests in module. """
modname = module.__name__
errors = ((k, do(v)) for k, v in all_tests(module))
errors = ((k, v) for k, v in errors if v is not None)
return {f"{modname}.{name}": err for name, err in errors} | d60e604a821b4e56f1b560425157d11bc21c0be7 | 37,474 |
def add_column(graph, results, selector):
"""Add a column to `graph`, produce a new graph.
Args:
graph (:class:`Graph`): Source ArrowProperty graph.
results (:class:`Context`): Results that generated by previous app querying.
selector (str): Used to select a subrange of data of results,... | 947160324c54d7d0d2fb7841513269be53f41642 | 37,475 |
def list_templates(sitename):
"""return a list of template names for this site"""
path = WEBROOT / sitename / '.templates'
if not path.exists():
return []
return sorted([f.name for f in path.iterdir() if f.suffix == '.tpl']) | 05c6501b17ec1d6466aa82e818b95bede51c4713 | 37,476 |
import collections
def from_pyqtgraph_struct(dct):
"""
Get simple structured dict from pyqtgraph params saveState() export.
:param dct: dct = parameters.saveState()
:return:
"""
output = {}
key = dct["name"]
if "children" in dct.keys():
reconstruction_type = "dict"
if... | 1c8d5b9f5fa10d0feb812e13dc3f7a8435958c61 | 37,478 |
def receive_msg(topic):
"""
Decorator
"""
def inner(func):
@sio.on(topic)
async def handle_request(data):
# call 'func' to return the data
func(data)
# returning inner function
return inner | 5e9ccdf39762777850ba94beb9a46167256ebf3b | 37,479 |
def get_requirements():
"""Return a list of package requirements from the requirements.txt file."""
with open('requirements.txt') as f:
return f.read().split() | 85efbe71d02ced7c5987f08a56a1a966bff2e1ef | 37,480 |
def integer_to_real_mapper(integers):
"""Define Integer Mapping Function Here(If Needed.)"""
real_numbers = []
range_of_integers = 32767 # each value goes from 0-32767(2 ^ length_of_chromosome)
integer_to_real_number_mapper = 1 / range_of_integers # will produce number between 0-1 when multiplied by ... | 18cc9dc1efe2dd8122d4953a4256cedd5fe234c9 | 37,482 |
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