content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def _plot_enn_samples_2d(sample_df: pd.DataFrame,
train_df: pd.DataFrame) -> gg.ggplot:
"""Plot realizations of enn samples."""
p = (gg.ggplot(sample_df)
+ gg.aes(x='x0', y='x1', fill='y')
+ gg.geom_tile()
+ gg.geom_point(data=train_df, size=3, stroke=1.5)
+ gg.s... | 975dd8d3ee0a6ce7f13c351915a15a4d95a2722b | 52,751 |
def square2vec(rdm):
"""map 2D distance matrix to [n,1] vector of unique distances. Returns distances in
same order as scipy.spatial.distance.squareform."""
return rdm[np.triu_indices_from(rdm, k=1)][:, None] | 830a91f5890017f035383d1c728be3048deed44a | 52,752 |
from datetime import datetime
import pytz
def parse_date_string(dt_string, alexa=False):
"""Parse the date string from the database into a `datetime` object.
:param date_string: the raw date string to parse
:returns: the `datetime` version of the given date string
"""
if(alexa):
return da... | 3deb8558d84cd28e2eca5b575587fe8315f6de0c | 52,753 |
from typing import Union
from typing import ContextManager
from pathlib import Path
def _get_filepath(
dataset_name: str, dir_path: Union[None, str], filename: str
) -> Union[str, ContextManager[Path]]:
"""
Returns the path to a decay dataset file (located either within a sub-package of
``radioactived... | a4e7d480bf0abf209f3fc094452d6e38d4334741 | 52,754 |
import json
def get_frequent_queries(**kwargs):
"""
Gets the most frequent queries
Kwargs:
db: global database instance
redis: global redis instance
"""
db = kwargs["db"]
with db.scoped_session() as session:
q = sqlalchemy.text(
"SELECT query, calls FROM pg... | 2b0a58aeb4ef228bcf230030d1d2b5f02e49452e | 52,755 |
def Bellman_exp_inplace_prt(Qsa, S, action, action_list, ff=0.9, N_A=9, N_Symbols=3, disp_flag=False):
"""Evaluate q(s,a) using ``S`` and ``action``.
Returns q(s,a).
Parameters
----------
S : numpy.ndarray, shape=(N_A,)
State matrix <--> state index, ``S_Idx``
action : int
... | 77c371749d5cbc0c7162ecf2a4916d34143ce7fd | 52,756 |
def beh_idx_to_2p_idx(beh_indices, cam_line, frame_counter):
"""
This functions converts behaviour frame numbers into the corresponding
2p frame numbers.
Parameters
----------
beh_indices : numpy array
Indices of the behaviour frames to be converted.
cam_line : numpy array
P... | 1521f29eaf0fed628dd8dedd3cc0ce5f8223c7ca | 52,757 |
def num2julian(num):
"""
Convert a Julian days to a matplotlib date.
Parameters
----------
num : numpy.ndarray : int32
Number of days since 0001-01-01 00:00:00 UTC *plus* *one*.
Returns
-------
jd : numpy.ndarray : int32
Julian days.
"""
return num + 1721424.5 | c3d4815ef316062065109ebb7c52290ca13c01fe | 52,758 |
import logging
def get_logger(module_name: str) -> logging.Logger:
"""
Gets a namespaced logger based on the project name and module name
"""
if "" == LOGGING_PROJECT_NAME:
return get_fqn_logger(module_name)
return get_fqn_logger("{}.{}".format(
LOGGING_PROJECT_NAME,
modul... | 4543e7fafb5788607664de0749dff5456dc63c6f | 52,759 |
def crop_and_resize_instance_masks(masks, boxes, mask_size):
"""Crop and resize each mask according to the given boxes.
Args:
masks: A [N, H, W] float tensor.
boxes: A [N, 4] float tensor of normalized boxes.
mask_size: int, the size of the output masks.
Returns:
masks: A [N, mask_size, mask_siz... | 81f06b34499ec8c51c5635e4c79a5943179b3108 | 52,760 |
def compute_source_flags(tod=None, P=None, mask=None, wrap=None,
center_on=None, res=None):
"""Process masking instructions and create RangesMatrix that flags
samples in the TOD that are within the masked region. This
masking makes use of a map with the footprint encoded in P, so
... | 857eb7db8bd8490695a8198714d3675c2ea5940d | 52,761 |
def _split(df, keepvars, force_numeric=False):
"""
Splits a dataframe into a list of arrays based on a key variable. Pass keepvars
to keep variables other than the key variable
"""
# df = df.sort_values('__key_var__') #now done outside of function
small_df = df[['__key_var__'] + keepvars]
ar... | 0a93671b0348a3e8d288485733bba1befa93445a | 52,762 |
import functools
def pmg_serialize(method):
"""
Decorator for methods that add MSON serializations keys
to the dictionary. See documentation of MSON for more details
"""
@functools.wraps(method)
def wrapper(*args, **kwargs):
self = args[0]
d = method(*args, **kwargs)
#... | bbe2ed20bf563d97c5cfc920e9ad226e096f5cba | 52,763 |
def normalize_dataframes(grouped_df, year):
""" Takes a dataframe which has been grouped by phrase and aggregated, and normalizes the
total_occurrences and total_docs columns by dividing them by the total no. of phrases or total no. of
docs in the relevant year and multiplying by 100 to create percentages.
... | 4a4ca38c13b8a18b0b72f86ae9610882314bac74 | 52,764 |
async def setup_file(config_file, cmd_args):
"""Set up control center from config file and command line args.
Parameters
----------
config_file : str
The path to the configuration YAML file.
cmd_args : dict
The dict with the command line arguments.
Returns
-------
Cente... | 912b8c044fdfce07f0d2fdad141feb548ea8c5fb | 52,765 |
def egd_get_user_lang(user=None) -> str:
"""If user logged use gessed language on session beginning or resumption"""
if is_app_for_actual_site():
return frappe.local.lang
else:
return frappe_get_user_lang(user) | 2fe52f7259dc2cb5fa33dd883e475960ef7040a3 | 52,766 |
def oldest_youngest():
"""Get JSON Data.
Compile a dictionary of all billionaires' names and ages.
Find the oldest billionaire under 80, and youngest living billionaire."""
data = get_json()
age_dict = {}
for item in data['billionaires']:
if item['age'] >= 80 or item['age'] < 0:
... | 25e04edac9fb7ba7f4fa7b399dd28403c1ffffe0 | 52,767 |
import pickle
def read_narr_mask(pickle_file_name):
"""Reads NARR mask from Pickle file.
:param pickle_file_name: Path to input file.
:return: mask_matrix: See doc for `check_narr_mask`.
"""
pickle_file_handle = open(pickle_file_name, 'rb')
mask_matrix = pickle.load(pickle_file_handle)
p... | ad78202ef4cf136647ad51d4e558fe3de58ef9d0 | 52,768 |
from typing import Dict
from typing import Optional
def get_imported(context: dict) -> Dict[str, Optional[version_types]]:
"""Create list of imported modules in given context.
Only outputs modules from given context that have
conventional version attributes.
Context is typically globals() or locals()... | 1a1e2a84db5de4490f2adbe677fc08315a99de2f | 52,769 |
from typing import Callable
def mpi_reduce(x: np.ndarray, op: Callable) -> np.ndarray:
"""Apply reduce operation over MPI processes."""
buffer = np.zeros_like(x)
MPI.COMM_WORLD.Allreduce(x, buffer, op=op)
return buffer | 7c048c5f3fdcd19b436e45cdbab17ad02255bdbf | 52,770 |
def get_det_bbox_with_cls_of_img(all_boxes, img_idx):
"""get_det_bbox_with_cls_of_img
:param all_boxes: det result
:param img_idx: img idx in imageset.txt
:return bboxes: N*6-dim matrix, N is number of bbox, 6 is [x1,y1,x2,y2,score,cls], the cls is the addtion information we get from this function
... | b4c2023c385712675b99b944a179614dbac9e1f5 | 52,772 |
def _multiply_calculate(a, b): # pragma: no cover
"""
a in GF(2^m), can be represented as a degree m-1 polynomial in GF(2)[x]
b in GF(2^m), can be represented as a degree m-1 polynomial in GF(2)[x]
p(x) in GF(2)[x] with degree m is the primitive polynomial of GF(2^m)
a * b = c
= (a(x) * ... | 7cb631ceed1c635eca26c105f82c43301bc158b0 | 52,773 |
def hugoniot_rho(p, rho0, c0, s, min_strain=0.01):
"""
calculate density in g/cm^3 from a hugoniot curve
:param p: pressure in GPa
:param rho0: density at 1 bar in g/cm^3
:param c0: velocity at 1 bar in km/s
:param s: slope of the velocity change
:param min_strain: defining minimum v/v0 val... | c8afd51030c9b7c8c1353bab0ac7199b349aa77d | 52,774 |
def name( path ):
"""Extracts the resource name."""
return path[1+path.rfind('/'):] | 7e8448e5b1c62c30e7ae28c80580731aa9f6f9fb | 52,777 |
def report_dfa(q_0, dfa, g):
"""
Give a complete description of the DFA as a string
"""
output = ""
output += "----------- DFA ----------- " + "Goal: " + g + " ----------- \n"
transitions = [(i,dfa[(i,sigma)],sigma) for i,sigma in dfa]
transitions.sort()
for i,j,sigma in transitions:
output += (f"delta({i},{s... | 99d86557b9e1aede93f46e1ef78ecb1fe6cdbf30 | 52,778 |
def get_page_response(query, page, per_page, itemskey, return_method=None,
replaceobj=None, replaceobj_key_only=False, **kwargs):
""" 获取一个多页响应对象
:param query: 查询对象，或者直接返回的对象
:param page: 当前页
:param per_page: 每页项目数
:param itemskey: 对应 items 的键名
:param return_method: 若值不为 Non... | fb15af91981ff057ed75a633a9012ab68d5653e3 | 52,779 |
def decrypted(data, password=None, is_user=True):
"""Decrypt to any Python object
:param data: a byte string previously encrypted using :func:`encrypted`
:param passowrd: the optional password originally used to encrypt
:param is_user: optionally indicate whether user or machine
:returns: a Python ... | d3924de10aaa4b0918205373cf2e4f7744a0bc7c | 52,780 |
def on_pad_pressed(pad_n=None, pad_ij=None):
"""Shortcut for registering handlers for ACTION_PAD_PRESSED events.
Optional "pad_n" or "pad_ij" arguments are to link the handler to a specific pad.
Functions decorated with this decorator will be called with the following positional
arguments:
* Pus... | 458be38bacca5347370bb9526a7603d0d6455f85 | 52,781 |
def score(n):
"""根据成绩，计算成绩的级别，级别有：A、B、C、D
成绩>=90 ——A
成绩>=80 ——B
成绩>=70 ——C
成绩>=60 ——D
参数：
- n-：成绩
返回值：返回‘A’或‘B’或者'C'或者'D'
"""
if n >= 90:
return 'A'
if n >= 80:
return 'B'
if n >= 70:
return 'C'
if n >= 60:
return 'D' | fb854dbdb77e31b75a70eddf6d001814100c44d3 | 52,782 |
def get_linked_clusters():
"""
Get linked clusters.
:returns: list of linked clusters
:rtype: [LinkedCluster]
"""
current_cluster = get_attached_cluster()
if not current_cluster:
return []
links = get_cluster_links(current_cluster.get_url()).get('links')
linked_clusters = ... | 524d231676d1db77cf1804d626f7aeb2ff69a228 | 52,785 |
from unittest.mock import Mock
def cube_mesh():
""" cube mesh """
mesh = Mock()
mesh.vertices = cube_vertices()
mesh.loop_triangles = [
triangle(0, 2, 1),
triangle(0, 3, 2),
triangle(2, 3, 4),
triangle(2, 4, 5),
triangle(1, 2, 5),
triangle(1, 5, 6),
... | 3a572fd73fe5a2aca2f59517ba19f8b7d6b214f9 | 52,786 |
def algo_options():
"""
Return the list of default options for supported algorithms.
"""
return {"grid": "",
"hubbard": "",
"medial": "-merge -burst -expand",
"octree": "",
"spawn": ""} | f52c12efe477bd50a49e7053cca97fc9e4072433 | 52,787 |
def fill_matrix(X: np.ndarray, mixture: GaussianMixture) -> np.ndarray:
"""Fills an incomplete matrix according to a mixture model
Args:
X: (n, d) array of incomplete data (incomplete entries =0)
mixture: a mixture of gaussians
Returns
np.ndarray: a (n, d) array with completed data... | c7001e668a04a3221f9db48038815abfcdbb1575 | 52,789 |
def detect(agent, fill_none=False):
"""
fill_none: if name/version is not detected respective key is still added to the result with value None
"""
result = dict(platform=dict(name=None, version=None))
_suggested_detectors = []
for info_type in detectorshub:
detectors = _suggested_detect... | bef47ccbff4bbf09d0195a6f9e71f8ed675f04ef | 52,790 |
def shutting_down(globals=globals):
"""
Whether the interpreter is currently shutting down.
For use in finalizers, __del__ methods, and similar; it is advised
to early bind this function rather than look it up when calling it,
since at shutdown module globals may be cleared.
"""
# At shutdow... | 01f601b989611b06a438a3be3e15937eff389038 | 52,791 |
def _err(msg=None):
"""To return a string to signal "error" in output table"""
if msg is None:
msg = 'error'
return '!' + msg | 029fae3786df61160867696fb71cc94b2edf0506 | 52,792 |
from datetime import datetime
import pickle
def run_qpe(
unitary,
precision_qubits,
query_qubits,
query_circuit,
device,
items_to_keep=1,
shots=1000,
save_to_pck=False,
):
"""
Function to run QPE algorithm end-to-end and return measurement counts.
Args:
precision_q... | 04e6cecd3a28c50f635a0a42f1ee24f6ac8c0b70 | 52,793 |
def LNETF(N,loc_rad,taper='GC',infl=1.0,Rs=1.0,rot=False,**kwargs):
"""
The Nonlinear-Ensemble-Transform-Filter (localized).
Ref: Julian Tödter and Bodo Ahrens (2014):
"A Second-Order Exact Ensemble Square Root Filter for Nonlinear Data Assimilation"
It is (supposedly) a deterministic upgrade of the NLEAF ... | e1f3beb387371d3178598b724cc08c0a0e3f53b8 | 52,794 |
def alert_unmanaged_error(request_id, error, sys_exc_info):
"""Compose error on unmanaged error."""
return UNMANAGED_TEXT_MESSAGE.format(
date=get_date(),
request_id=request_id,
error=error,
traceback=format_traceback(sys_exc_info),
locals=format_locals(sys_exc_info)
... | 53c504a2bef9f7c7593988b63238a95c753fbbde | 52,795 |
def load_transcript(transcript_path):
""""
Load transcript from *.srt file
"""
transcript = []
subs = pysrt.open(transcript_path)
for sub in subs:
transcript.append((sub.text, time2second(tuple(sub.start)[:4]), time2second(tuple(sub.end)[:4])))
return transcript | ff4725e0f2ec68b16bd750b28066a4446280c866 | 52,796 |
async def get_attachment_obj(ctx: commands.Context):
"""Gets the attachment object from a message"""
# switch to the replied message if it's there
if ctx.message.attachments:
msg = ctx.message
elif ctx.message.reference:
msg = ctx.message.reference.resolved
else:
return False... | 176a7e2c9dcc27dff9586440c23486dc7d273301 | 52,797 |
def day_wind_chart(qs_list, unit, plot_func, width, height, colors):
"""
Returns a URL which produces one line for each queryset.
"""
data_list = [] # list of value lists
for date_qs in qs_list:
if date_qs: # only work on this if the queryset is not empty
data_list.append(conv... | eda14897fec89f14b340c7dc5234b7a91f4ca59d | 52,798 |
from operator import eq
def conso(h, t, l):
""" Logical cons -- l[0], l[1:] == h, t """
if isinstance(l, (tuple, list)):
if len(l) == 0:
return fail
else:
return (conde, [(eq, h, l[0]), (eq, t, l[1:])])
elif isinstance(t, (tuple, list)):
return eq((h, ) + tu... | cb576eeeb8de5a2a71a8843a4d81b3933af6d64a | 52,799 |
def select_text(table, col_names, version):
"""Generate a select statement for new or old values of this table."""
slt = "SELECT {tuple_str} FROM {table} WHERE rowid={version}.rowid".format(
tuple_str=sqlite_list_text([col_pair_text(c, version)
for c in col_names]),
... | 28f22ad8478cd87d1d56c7a1a6b86d0b81e1d457 | 52,800 |
def predict(Theta1, Theta2, X):
""" outputs the predicted label of X given the
trained weights of a neural network (Theta1, Theta2)
"""
if X.ndim == 1:
X = X.reshape(1, -1)
# Useful values
m = len(X)
# ====================== YOUR CODE HERE ======================
# Instructions:... | ba3df784fdd2a76fc59f0f010a9a4eb4c5be035f | 52,801 |
def aml_token(chain, team_multisig, token_name, token_symbol, initial_supply) -> Contract:
"""Create the token contract."""
args = [token_name, token_symbol, initial_supply, 0, True] # Owner set
tx = {
"from": team_multisig
}
contract, hash = chain.provider.deploy_contract('AMLToken', de... | b114cfc3abeeea9c600dccbc1bed78de60a7576f | 52,802 |
def invr():
"""
For taking space seperated integer variable inputs.
"""
return(list(map(int, input().split()))) | 9794b5c44a817cbd48709de99f16515c8684712b | 52,803 |
def _path_residuals(X, y, train, test, path, path_params, alphas=None,
l1_ratio=1, X_order=None, dtype=None):
"""Returns the MSE for the models computed by 'path'
Parameters
----------
X : {array-like, sparse matrix}, shape (n_samples, n_features)
Training data.
y : arr... | 0bfb35f3de8f5c8ba136a9cf29650667c110a039 | 52,804 |
def is_an_exact_imagined_object(predicate, imagined_object):
"""
Returns whether the imagined object matches exactly what the predicate
describes.
Inputs:
predicate: WordPredicate instance
imagined_object: RecognizedObject instance
"""
target = possible_reco... | 06aef2d1fb87d02cf60baceff81d8b153d487967 | 52,805 |
def read_field__list(infile, varname, lon, lat):
"""Read point list and initialize field."""
# Read field ...
if infile.endswith(".npz"):
# ... from numpy archive
with np.load(infile) as fi:
pts_lon, pts_lat, pts_fld = fi["lon"], fi["lat"], fi[varname]
fld = point_list_t... | 1e1baafdab9fac5a43bb95d28fb8d7d0c9d8ba31 | 52,806 |
def CircuitHeaderStartConfigurationVector(builder, numElems):
"""This method is deprecated. Please switch to Start."""
return StartConfigurationVector(builder, numElems) | 9ad0c7dd86a9f0cb90f573720802658616f81bff | 52,807 |
def get_processed_masks_and_boundaries(mask_path: str, boundary_path: str) -> tuple[ndarray, ndarray]:
"""Utility function for loading and applying preprocessing to mask and boundary image array
:param paths:
:return: tuple[ndarray, ndarray]
"""
masks = np.array(
cv2.imread(
mask... | 26def41a1e8dfe33d2d35b155164412374dfa30f | 52,808 |
import warnings
def nx_to_gdf(net, points=True, lines=True, spatial_weights=False, nodeID="nodeID"):
"""
Convert ``networkx.Graph`` to LineString GeoDataFrame and Point GeoDataFrame
Parameters
----------
net : networkx.Graph
``networkx.Graph``
points : bool
export point-based ... | 1821d06896eb9b7bfafa81aa748521ff2153bd0f | 52,809 |
def p2pkh(pubkey) -> Script:
"""Return Pay-To-Pubkey-Hash ScriptPubkey"""
return Script(b'\x76\xa9\x14'+hashes.hash160(pubkey.sec())+b'\x88\xac') | 2728805a090ddcd070b7454549018d538d71ee73 | 52,810 |
def _extract_center_face(image_shape, detected_faces):
"""Extracts the face that's the closest to the center of a image.
### Parameters
image: image with the faces.
detected_faces: list of resulting bounding boxes and keypoints from\
MTCNN().detect_faces().
### Returns
(bounding_b... | cbfb3bc4c90a62cb75eaa40854fe8829d76a18eb | 52,811 |
from typing import Optional
from typing import Union
def get_county_polygons(county_ids: Optional[intseq], state_ids: Union[int, intseq]):
"""Get a dataframe with the polygons or multipolygons representing county borders
The returned dataframe will have the county polygons for each county listed. `county_ids... | ad8a71ab0fc38658c4eff0f86030e3b14ac64a28 | 52,812 |
def add_xls_tag(file_name):
"""
Check the file_name to ensure it has ".xlsx" extension, if not add it
"""
if file_name[:-5] != ".xlsx":
return file_name + ".xlsx"
else:
return file_name | e053d9f7dad8e638122e93d05e49c5a06de3e664 | 52,813 |
def order_queryset_by_z_coord_desc(queryset, geometry_field="location"):
"""Order an queryset based on point geometry's z coordinate"""
return queryset.annotate(
z_coord=models.ExpressionWrapper(
models.Func(geometry_field, function="ST_Z"),
output_field=models.FloatField(),
... | bd9e4d9b09b2676727dc2f83452e93b50eda3716 | 52,814 |
def err_number(error) :
""" Return a error number """
result = errOk
if isinstance(error, int) :
result = error
elif isinstance(error, Error) :
result = error.error_code
if result < 0 :
result = (result - ErrorBaseNumber) * -1
return result | 8c6912a8c8466ecf4ce486a43001748d4237a217 | 52,815 |
def value_iteration(env):
"""
Performs Value Iteration to find the most optimal policy for the
Tax-v3 environment
Args:
env: Taxiv3 Gym environment
Returns:
policy: the most optimum policy
"""
V = dict()
gamma = 0.9
state_size = env.observation_space.n
action_si... | 461b65bf8de4cf30f018aad24f8452ed6b7ec247 | 52,816 |
def keypoint_3d_pck(pred, gt, mask, alignment='none', threshold=150.):
"""Calculate the Percentage of Correct Keypoints (3DPCK) w. or w/o rigid
alignment.
Paper ref: `Monocular 3D Human Pose Estimation In The Wild Using Improved
CNN Supervision' 3DV'2017. <https://arxiv.org/pdf/1611.09813>`__ .
Note... | 704cf2cc4b00ad232689d76e65d2a7241eda8fec | 52,817 |
from bioservices import biomart
from io import StringIO
def mitochondrial_genes(host, org):
"""Mitochondrial gene symbols for specific organism through BioMart.
Parameters
----------
host : {{'www.ensembl.org', ...}}
A valid BioMart host URL.
org : {{'hsapiens', 'mmusculus'}}
Orga... | affd7ff1d9014f36238b535732a1cbaac43b1308 | 52,818 |
def Bold(string):
"""Returns string wrapped in escape codes representing bold typeface."""
return '\x02%s\x0F' % string | 4dd1a0d3aecc93873f9763723a3dad76b45e2725 | 52,819 |
from typing import List
import decimal
import json
def from_bbox_array(bbox_array: List[decimal.Decimal]):
"""returns a geojson geometry object from a bounding box array.
Keeping default number of decimal places to 6 for now,
can change depending on data precision requirements."""
if bbox_array:
... | 3bbaf66d6d5d31f45b93e944474cac5f454df313 | 52,821 |
def taiwanLightCompensation(im, theta=0.5, thresh=0.2, B=[10, 30]):
""" Perform light compensation
http://www.csie.ntu.edu.tw/~fuh/personal/LightCompensation.pdf
:param theta: weight of corrected image in final output
:return: light compensated image
"""
def getOptimalB(im, thresh, B):
... | ac7c1fa06bb7cc2f0904b8da1ad360a027d6778f | 52,823 |
def _is_sweep_sequential(radar, sweep_number):
""" Test if a specific sweep is sequentially ordered. """
start = radar.sweep_start_ray_index['data'][sweep_number]
end = radar.sweep_end_ray_index['data'][sweep_number]
if radar.scan_type == 'ppi':
angles = radar.azimuth['data'][start:end+1]
el... | 3bc493b80d245a51295c5e3461f9442baecd15cb | 52,824 |
import random
def random_expand(image, boxes):
"""
Perform a zooming out operation by placing the image.
Helps to learn to detect smaller objects.
Args:
image(numpy.array): image, a array of dimensions (original_h, original_w, 3)
boxes(numpy.array): bounding boxes in boundary coordin... | 79e958a8acdc622e3e2e9270a2a29ededcc110b3 | 52,825 |
def matMULTI(first,second):
"""
Take in two matrix
multiply each element against the other at the same index
return a new matrix
"""
newMAT = []
newCOL = []
for i in range(len(first)):
for j in range(len(first[i])):
newMAT.append(first[i][j]*second[i][j])
#new... | 28b3b5954a483311bca6245c7472a99e8a12395c | 52,827 |
def put_html(html, sanitize=False, scope=Scope.Current, position=OutputPosition.BOTTOM) -> Output:
"""
Output HTML content
:param html: html string
:param bool sanitize: Whether to use `DOMPurify <https://github.com/cure53/DOMPurify>`_ to filter the content to prevent XSS attacks.
:param int scope,... | 60a10c44df3b4ba66f8ac428bfbfeaa60b069ac9 | 52,828 |
def convert_list2dict(word_list):
"""
把列表写成字典
"""
word_dict = defaultdict(int)
for w in word_list:
word_dict[w] = 1
return word_dict | 72bf12e52f8ebd8d9b9ce3626b995d0ababc2ab5 | 52,830 |
def GetAuthorizationCodeViaCommandLine(config):
"""Gets authorization code via command line.
This way is useful anywhere without a browser.
Args:
config: a dictionary of config.
Returns:
authorization code.
"""
body = urlencode({
'scope': config['scope'],
'redirect_uri': config['redir... | 67f7603825fcf30a4fbb957414e90525a88ceae5 | 52,831 |
def pedestal_ids_file(base_test_dir):
"""Mock pedestal ids file for testing."""
pedestal_ids_dir = base_test_dir / "auxiliary/PedestalFinder/20200117"
pedestal_ids_dir.mkdir(parents=True, exist_ok=True)
file = pedestal_ids_dir / "pedestal_ids_Run01808.0000.h5"
file.touch()
return file | edda4c192e577774e0cc4a38aaa7d838127e7dcd | 52,832 |
def get_fa_icon_class(app_config):
"""Return Font Awesome icon class to use for app."""
if hasattr(app_config, "fa_icon_class"):
return app_config.fa_icon_class
else:
return 'fa-circle' | 3766abb1f80b7ccea9e09a5edf011f1586e9b49e | 52,833 |
def linear_activation_forward(a_prev, w, b, activation):
"""
activation step for forward propagation with multiple choices of activation function.
@param a_prev: previous A from last step of forward propagation, numpy arrays
@param w: parameter W in current layer, numpy arrays
@param b: parameter b... | 58a12f753c42201400747e52213b95d372ae6e89 | 52,834 |
import time
def create_token(args):
"""
POST /api/v1/create_token HTTP/1.1
Host: 127.0.0.1:5000
Content-Type: application/json
Content-Length: 74
{
"name":"1234",
"password" :"1234",
"email" : "1234",
"duration":123
}
{"access_token":"ad236cdb-f645-456... | 74012f112c5d22a088e1e58032d35de5b1436028 | 52,836 |
def getDictionary(id_or_identifier):
"""
指定した id または identifier を持つ辞書のメタデータを返します。
id, identifier に一致する辞書が存在しない場合は None を返します。
Parameters
----------
id_or_identifier : str or int
str の場合は辞書 identifier で指定。
int の場合は内部辞書 id で指定。
Returns
-------
Metadata
Metadat... | 7d3f19ee4a9952afb336eb00cbc28a07191d02b2 | 52,837 |
def is_phone_in_call(log, ad):
"""Return True if phone in call.
Args:
log: log object.
ad: android device.
"""
return ad.droid.telecomIsInCall() | bf279c1892077de53f13976179ecf762f45f54b6 | 52,839 |
def omicron_model(
xs: np.ndarray,
ts: np.ndarray,
params: dict
) -> np.ndarray:
"""
SL_2I_4R model with dual immunity
:param np.ndarray xs: actual array of states
:param np.ndarray ts: time values
:param dict params: dictionary of parameters
:return np.ndarray
""... | 52ce91a0be8f8f5054c12c08993ed8303ffd87f3 | 52,840 |
def identity(n):
""" Return n """
return n | cc3249a1164e18f47f962e4db56a425876a87b17 | 52,841 |
def look_for_general(
m_str: str,
ref_dict: defaultdict,
base_num: t.Pattern[str],
full_num: t.Pattern[str],
doc_type: str,
) -> defaultdict:
"""
Reference Extraction by Regular Expression: For general use
Args:
m_str: text string to search
ref_dict: dictionary of refere... | 1563e85f9228f9ffb14f14869ecf1f73441ae2e6 | 52,842 |
def losses_and_metrics(num_classes):
"""
Define loss and metrics
Loss: Categorical Crossentropy
Metrics: (Train, Validation) Accuracy, Precision, Recall, F1
Returns:
loss, train loss, train acc, valid loss, valid acc, precision, recall, auc, f1
"""
loss_fn = CategoricalCrossentropy... | d8f571c4e2948007d8b6f880afbbd0e2fcfab00d | 52,843 |
import copy
def get_skill_from_model(skill_model):
"""Returns a skill domain object given a skill model loaded
from the datastore.
Args:
skill_model: SkillModel. The skill model loaded from the
datastore.
Returns:
skill. A Skill domain object corresponding to the given
... | c75ea6c7705d316a5d279da36468dd9278ceae44 | 52,844 |
def delete_tags_for_manifest(manifest):
""" Deletes all tags pointing to the given manifest. Returns the list of tags
deleted.
"""
query = Tag.select().where(Tag.manifest == manifest)
query = filter_to_alive_tags(query)
query = filter_to_visible_tags(query)
tags = list(query)
now_ms = get_epoch_ti... | a78b77ea96a3870b736301443005e45d58f76c42 | 52,846 |
def eeg_epochs_dataset(subject, trial, config, preload=True):
"""Get the epoched eeg data excluding unnessary channels
from fif file and also filter the signal.
Parameter
----------
subject : string of subject ID e.g. 7707
trial : HighFine, HighGross, LowFine, LowGross
Returns
------... | 58e6a1d63d2cc01416761b48a32a5bc9ebeacef9 | 52,847 |
def differences(lis, n=1):
"""
Returns the `n` successive differences of the elements in
`lis`.
EXAMPLES::
sage: differences(prime_range(50))
[1, 2, 2, 4, 2, 4, 2, 4, 6, 2, 6, 4, 2, 4]
sage: differences([i^2 for i in range(1,11)])
[3, 5, 7, 9, 11, 13, 15, 17, 19]
... | 067ee6e5744211f2b41f55f8cd7383431df1e486 | 52,848 |
def get_bounded_progress():
"""
returns progress as a tensor between 0 and 1
"""
assert get_default_counter().expected_count is not None
return get_default_counter()._bounded_progress | 3279ead5729521280bc0fd9295de861944f02b9a | 52,849 |
import six
def _is_start_piece_sp(piece):
"""Check if the current word piece is the starting piece (sentence piece)."""
special_pieces = set(list('!"#$%&\"()*+,-./:;?@[\\]^_`{|}~'))
special_pieces.add(u"€".encode("utf-8"))
special_pieces.add(u"£".encode("utf-8"))
# Note(mingdachen):
# For foreign characte... | 591373699c5e4c41248c81dac2bae5520123b2e7 | 52,851 |
import math
def atrpips(data, length):
"""Average True Range indicator in pips
Arguments:
data {list} -- List of ohlc data [open, high, low, close]
length {int} -- Lookback period for atr indicator
Returns:
list -- ATR (in pips) of given ohlc data
"""
atr_pips = []
av... | b73ab18cd0e1f338cc8136c0ccd82fd056d668a9 | 52,852 |
def start_day(start):
"""Return TMIN, TAVG, TMAX."""
start_day = session.query(Measurement.date, func.min(Measurement.tobs), func.avg(Measurement.tobs), func.max(Measurement.tobs)).filter(Measurement.date >= start).group_by(Measurement.date).all()
start_day_list = list(start_day)
return jsonify(start_da... | 3c24c3c22dc1444e4bc46baeaa3e527a1e2af75b | 52,853 |
def R123(a,b,c, degrees=False):
"""Returns a rotation matrix based on: Z*Y*X"""
if degrees:
a *= deg2rad
b *= deg2rad
c *= deg2rad
s3 = np.sin(c); c3 = np.cos(c)
s2 = np.sin(b); c2 = np.cos(b)
s1 = np.sin(a); c1 = np.cos(a)
return np.array(
[
[c1*c2,... | 8097514d390d73d1121c9462cada98060681619e | 52,854 |
from datetime import datetime
from typing import Optional
import time
from typing import Union
import calendar
def get_next(
base: datetime,
interval: Interval,
frequency: int,
at_time: Optional[time] = None,
days: Optional[list[int]] = None,
) -> Union[datetime, date]:
"""Get the next due dat... | 678b5c85615e388e2ae221df7ffba7ee38f97584 | 52,855 |
from typing import Union
def guess_font_size(
size: tuple[int, int], font_name: str
) -> tuple[Union[ImageFont, FreeTypeFont], int]:
"""Try and figure out the correct font size for a given height and font.
Args:
``size``: The dimensions of the image in pixels.
``font_name``: The name of t... | 01733050378885184ea5e0dbaba053263cf139bd | 52,856 |
def create_model(
time_set=None,
time_units=pyo.units.s,
nfe=5,
tee=False,
calc_integ=True,
):
"""Create a test model and solver
Args:
time_set (list): The beginning and end point of the time domain
time_units (Pyomo Unit object): Units of time domain
nfe (int): Numb... | 9330c87db97d42de665c8198eaa113045ef92897 | 52,857 |
from pathlib import Path
def read_table(h5file, path, start=None, stop=None, step=None, condition=None) -> Table:
"""Read a table from an HDF5 file
This reads a table written in the ctapipe format table as an `astropy.table.Table`
object, inversing the column transformations units.
This uses the sam... | f3ef6b3ff7afc81e1afd9cca594727b8117471bc | 52,858 |
from typing import Any
def get_valid_ref(ref: Any) -> str:
"""Checks flow reference input for validity
:param ref: Flow reference to be checked
:return: Valid flow reference, either 't' or 's'
"""
if ref is None:
ref = 't'
else:
if not isinstance(ref, str):
raise ... | 16c66dc9e0568bcd33e1cc9956ed31b5ae47595e | 52,859 |
def k_argmin(l, k, func):
"""
Gets the indices and values of the k-smallest function results
from func.
"""
l_map = map(func, l)
return k_min(l_map, k) | 750f408723ad9e024d45796bcc3250a9fcab296a | 52,860 |
from typing import Optional
from typing import Tuple
def add_ports_from_markers_square(
component: Component,
pin_layer: LayerSpec = "DEVREC",
port_layer: Optional[LayerSpec] = None,
orientation: Optional[int] = 90,
min_pin_area_um2: float = 0,
max_pin_area_um2: float = 150 * 150,
pin_extr... | 349893ef57c43dfc634af54086c98720207d2d6c | 52,862 |
def calc_periodicity(peak_info, period_min=5, period_max=15):
"""
calculate the period
:param peak_info:
:param period_min:
:param period_max:
:return:
"""
num_peaks = peak_info.shape[0]
# calculate periodicity
peak_info[:num_peaks-1, 2] = np.diff(peak_info[:, 0])
peak_info =... | ac7ca44153019773741e6e6ca15fd9961bb16089 | 52,863 |
from typing import Type
def create_global_resource(group: str, version: str, kind: str, plural: str, verbs=None) \
-> Type[GenericGlobalResource]:
"""Create a new class representing a global resource with the provided specifications.
**Parameters**
* **group** `str` - API group of the resource. ... | c6cb2e05a048456ed7103c6e1b4c81692b34987a | 52,864 |
from typing import Dict
from typing import Hashable
from typing import Any
def outline_to_implementation(
name: str,
design: str,
outline: fiat.Outline) -> Dict[Hashable, Any]:
"""[summary]
Args:
name (str): [description]
design (str): [description]
outline (fiat.Outline)... | 871c7fd4f950c291832cbd0fc3dce823831c4257 | 52,865 |
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