content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
import shutil
def cmd_exists(cmd):
"""Returns True if a binary exists on
the system path"""
return shutil.which(cmd) is not None | 0d43181532b9b71cb06b6a5d1f207bbb19899129 | 3,604,531 |
def read_viewpoint_quats(f):
"""Reads viewpoint qauternion from file
Args:
f (string): Path to the .mat file
Returns:
dict: A dictionary of viewpoint quaternions, indexed by the class id number.
"""
vp_data = loadmat(f)
vpq = vp_data['viewpoints']['quaternion'][0][0]
quat_di... | c9e8607f98ad36c3e5290b96f8a3bad6f774e6a3 | 3,604,532 |
import requests
def get_swapi_resource(url, params=None):
"""This function initiates an HTTP GET request to the SWAPI service in order to return a
representation of a resource. The function defines two parameters, the resource url (str) and
an optional params (dict) query string of key:value pairs may be ... | 3a5de57fc498da1e25de4f2b3e61cae8508ad7c7 | 3,604,533 |
def svm_accuracy_in_euc_space_params(X, labels, params, folds=3):
"""SVM classifier accuracy in an Euclidean Space.
Args:
X (np.ndarray): The data array.
labels (list, np.ndarray): The data labels.
params (dict): Dictionary of parameters and its values.
folds (int): Amount of fo... | f5ae96a642b3025168e8eaad7cb522a784d323f5 | 3,604,534 |
def get_user_categories(user: User):
"""
Retrieves a User's Categories.
:param user: A User
:return: A list of a User's Categories
"""
return Category.categories.filter(user_storage__id=user.id).order_by('name') | 253f53b3788133d49e80fe58ca725d5ab97c9249 | 3,604,535 |
def _normalize_results(inputs, outputs, results, return_rank1=False):
"""normalize_results() does standard return value handling for
a given set of ufunc actual parameters and results. Ufunc inputs
are assumed to be arrays or scalars, ufunc outputs can be arrays
or unspecified, and ufunc "preliminary r... | aa187e4e294afb847261e968e02910e9aa60a3f5 | 3,604,536 |
def assertify(text):
"""Wraps text in the (assert )."""
return '(assert ' + text + ')' | da7af0fe5d27759d8cef4589843796bee8e74383 | 3,604,537 |
def remove_nodata_records(df_records, nodata_value=-999):
"""
Read a numpy record array and remove nodata records.
Parameters
----------
df_records: pandas dataframe
A pandas dataframe type containing values extracted from env variables.
nodata_value : int, float, np.nan
A int, ... | 5523bad6bde93ef2b425110b37696d07e43ad6de | 3,604,538 |
def get_config(config_file_path):
"""
:param config_file_path:
:return:
"""
return parse_config_utils.Config(config_path=config_file_path) | 8f4f717c14d44de586dd567564e2379d8e10ffa7 | 3,604,539 |
def create_uniform_layer(
num_components, component_fn, combiner_fn, router_fn):
"""Creates a layer of components with the same architecture and router.
Args:
num_components: (int) number of components.
component_fn: function that creates a new component.
combiner_fn: function that creates a combin... | 780dbe32b404c7dd45192439a96b91a48bf67929 | 3,604,540 |
import time
def wait_for_services(cloud_name, host=None, service=None, admin_up_only=True, retries=18, timeout=10, **kwargs):
"""Ensure the service is up and running on specified host.
:param host: name of a host where service is running
:param admin_up_only: do not check status for admin disa... | 9f831e12f54522e328a5b184620380e356dd7558 | 3,604,541 |
import PIL
def resize_image(img:PIL.Image, size:int)->PIL.Image:
""" resize PIL-image """
w, h = img.size
if w == size and h == size: return img
else: return img.resize((size, size), PIL.Image.BICUBIC) | d9548e12730b0972803ed7a0e485a65b1cc07db2 | 3,604,543 |
def find_resp_subject(subj, RESP):
"""Find if there is one matching subject in RESPECT database based on
the channel names"""
matching_subj = []
sessions = [x for x in subj.list_sessions() if x.name == 'IEMU']
for sess in sessions:
for chan in sess.list_channels():
matched = find... | 897d72c16d87a7b44c5a03673725de0a4c91ea57 | 3,604,545 |
def mjed_from_tdb(tdb):
"""Modified Julian Ephemeris Date from TDB seconds."""
return tdb/86400. + MJED_OF_J2000 | 95c20b0838fd0e9a89f44581c215cc8cb0f6a89c | 3,604,547 |
def deseasonalize(ts):
""" removing monthly mean climatology """
dt_year = (ts.time[12]-ts.time[0]).values #
ts_ds = ts.copy()
yrly = ts.groupby_bins('time', np.arange(0,len(ts.time)+1,12)/12*dt_year, right=False).mean(dim='time').rename({'time_bins':'time'})
for j in range(12):
m = ts.isel... | b97ac236ebafb21544b9e5ff620af4403e38e1a2 | 3,604,548 |
def load_variable(checkpoint_dir, name):
"""See `tf.contrib.framework.load_variable`."""
return checkpoint_utils.load_variable(checkpoint_dir, name) | cf0ad703242287f85cd3399beb167bfc6dc4305f | 3,604,549 |
from typing import Optional
def parse_json_and_match_value(line: str, value: str) -> Optional[LogType]:
"""Parse a line as JSON log and check if it a valid log."""
log = parse_json(line)
if log:
key = "logbook_type"
if key not in log or log[key] != value:
log = None
return ... | 5468995f710aa5691a45a49fcfbd0c58db53df87 | 3,604,550 |
def get_images_from_multi_tiff(path, nb_img=False):
"""
Import .tif file from a given path and convert it to a 3d np.array where
the first dimension represent the image index.
Parameters
----------
path : str
.tif file path.
the tif file must carry only 2d arrays of the same dim... | d5b28dfbe1816098eb538d42c5847edc6f44c87a | 3,604,551 |
def test_print_validate_tuple():
"""
Feature: JIT Fallback
Description: Support print.
Expectation: No exception.
"""
@ms_function
def print_func():
x = Tensor(np.array([1, 2, 3, 4, 5]))
y = Tensor(np.array([1, 2, 3, 4, 5]))
tensor_sum = x + y
print("tensor_su... | f4100d80ff6526cd4848f47ba571ab103ff23410 | 3,604,552 |
def about_time(all_df):
"""
elapsed time
remaining time
Note: remaining time not collected anymore!
"""
# time_list = [all_df['elapsed'].iloc[-1], all_df['remaining_time'].iloc[-1]]
time_list = [all_df['elapsed'].iloc[-1], None]
if len(time_list) != 2:
print("***len(time_list): ... | 780a426c05ed8484796d718ca1aabaec1b648d03 | 3,604,553 |
def remove_repository(s3_client, bucket, prefix):
"""Remove a P2 repository from a prefix on an S3 bucket
:param s3_client Boto s3_client object to apply
:param bucket: Bucket to remove from
:param prefix: Prefix at which to remove the repository
:return: True if repository was removed, else False
... | d23a54195751a4ccfbe77a7fb099a8d4743bb83a | 3,604,554 |
import typing
def func_pq_annotate(*, p: "3" = "p", q="q") -> typing.Tuple:
"""func.
Parameters
----------
p, q: str, optional
Returns
-------
p, q: str
"""
return None, None, None, None, None, p, q, None | c65555a391e05248aecec5abcce6b6d0c60ef3ec | 3,604,555 |
def multi_row_selector(table, keyword, value_list,
row_selector=None, **kwargs):
"""Returns lists of indices into a table, one list per value of `keyword`
Parameters
----------
table : `~astropy.table.Table`
Usually a `ccdproc.ImageFileCollection.summary`, hence the use
... | d5de585afe3f97355dded18a59d3ec60576b55ee | 3,604,556 |
import requests
from bs4 import BeautifulSoup
def commitstrip_scraper():
"""
Filenames are in an javascript object on the mainpage.
"""
try:
except ModuleNotFoundError:
raise CartoonError("Packages for scraping not installed. Install requests and beautifulsoup4. "
... | 815d7684f9bec00a5d3bc376bc69f9eca3a38320 | 3,604,557 |
def invert_instruction(f, args):
"""
Transform a parsed instruction into its inverse
"""
if f in (swap_position, swap_char, move):
args.reverse()
elif f == rotate:
args[0] = -args[0]
elif f == rotate_position:
f = rotate_position_inverse
return f, args | 132ce0996daa26f0e69eccc1f86e1e3ac92ae800 | 3,604,558 |
def new_fountain():
"""
Drinking from the fountain makes the player stronger.
"""
fountain = Composite()
set_dungeon_feature_components(fountain)
fountain.set_child(Description("Fountain",
("A Fountain full of clean water",
"... | 6640ce957517c425961581a22617a6f4b13ac505 | 3,604,560 |
def _chunk_outline(chunk: ChunkData) -> np.ndarray:
"""Return the line verts that outline this single chunk.
Parameters
----------
chunk : ChunkData
Create outline of this chunk.
Return
------
np.ndarray
The chunk verts for a line drawn with the 'segments' mode.
"""
... | fb8db1c4c1bb2cc95a9701e48733cb4b6c3abb2a | 3,604,561 |
def shuffle(batches):
"""Shuffle the data.
This method groups the batches together in pairs and within each pair shuffles
the data between the two members.
Args:
batches (List[Tuple[ObjectID, ObjectID]]): This is a list of tuples, where
each tuple consists of two object IDs. The first component is a... | 8180bf3f972f9206d7fa0b0e2deb1ffe175df98d | 3,604,562 |
import logging
def create_network(batch_size, update_freq):
"""Create a linear regression network for performing SVRG optimization.
:return: an instance of mx.io.NDArrayIter
:return: an instance of mx.mod.svrgmodule for performing SVRG optimization
"""
head = '%(asctime)-15s %(message)s'
loggi... | fb878f4f796a195b4e1c258f5742d034b7c272c2 | 3,604,563 |
def bubble_sort(items):
"""Sort given items by swapping adjacent items that are out of order, and
repeating until all items are in sorted order.
Running time: O(n**2) because it passes through n/2 (on average) elements
n-1 times, which simplifies to n elements n times, n**2
Memory usage: O(1), a... | 88748e0d552f0d08e228049f12268e34aed4907b | 3,604,564 |
import numbers
def is_special_slice(key) -> bool:
"""Does the key contain a list, ndarray, or logical ndarray?
"""
# Slices and int-like numbers are fine.
for elem in to_tuple(key):
if not (isinstance(elem, (numbers.Number, slice)) or np.isscalar(elem)):
return True
return Fal... | e7d5888002048472688f0f491b684d68fbd5014d | 3,604,565 |
def human_list(_list) -> str:
"""Convert a list of items into 'a, b or c'"""
last_item = _list.pop()
result = ", ".join(_list)
return "%s or %s" % (result, last_item) | 04ee703d1878ac7602ba33aaf1831ccc188ee9e2 | 3,604,566 |
import base64
import io
def preprocess(data):
"""
This method decodes base64 encoded image, resizes it to 299 x 299 shape,
and turns it into tensor digestable by the model
"""
decoded_image = base64.b64decode(data);
image = Image.open(io.BytesIO(decoded_image));
resized_image = image.res... | ecfc2efa8f68a1263e94f7457e2ced9289b10774 | 3,604,568 |
import logging
def recluster(particles, Rjet,jetdef_tree):
"""Recluster the jet constituents"""
# Recluster the jet constituents and access the clustering history
#set up our jet definition and a jet selector
if jetdef_tree=='antikt':
tree_jet_def = fj.JetDefinition(fj.antikt_algorithm, Rjet)
... | 85196c3c477328570c06f61bfb8d7f8fc3b33efd | 3,604,569 |
def netcsf2sql(file_name: str, rootgrp: Dataset, xr_file, force_save_db):
"""_summary_
Args:
file_name (str): _description_
rootgrp (Dataset): _description_
Returns:
bool: _description_
"""
error = False
for name in settings.vars:
try:
tempc = rootgr... | 391a779526be9b70f9222aa1fb69bf4a40869032 | 3,604,570 |
def segment_mean(x, segment_ids):
"""
Computes the mean along segments of a tensor.
Parameters
----------
x : tensor
The tensor to segment_mean. Should have real numeric type.
segment_ids : tensor
A 1-D tensor whose size is equal to the size of data's first dimension. Values sho... | 232800aad718554162a48d4b5d418d5b4e18879a | 3,604,571 |
def compute_distances_squared(xi1, xi2):
"""
Return matrix of squared Euclidian distance between all pairs of points in d-dimensions.
Args:
xi1 (ndarray): Sample locations in d-dimensions, shape `(n1, d)`.
xi2 (ndarray): Sample locations in d-dimensions, shape `(n2, d)`.
Return:
out (ndarray): Shape `(n1... | 7177e0a08bf09257b1e8402040c8a8d7e6e2884e | 3,604,572 |
def is_unique_chars_v2(str):
"""
Let N be the string length
Dictionary construction: O(N); d[k] = v is O(1), done N times
Containment check: O(N)
=> O(N) time
=> O(N) space
"""
chars_map = defaultdict(int)
for char in str:
chars_map[char] += 1
return 2 not in chars_map.va... | 256bab14de37f9a1a86e6f2354085d4936382fff | 3,604,573 |
def get_session_detail_list_for_recover(session_list):
"""
根据集群名称列表，查询补全详细的信息("cluster_group", "cluster_label", "cluster_name", "version")
:param session_list: 集群名称列表
:return:
"""
session_detail_list = []
for cluster_name in session_list:
res = ResourceCenterHelper.get_cluster_info(
... | 5566892541d4214e7321aaaf120b9b5e5f810ec2 | 3,604,574 |
def mixup(
alpha,
beta,
sample_1,
label_1,
*,
sample_2=None,
label_2=None,
repeat=1,
shuffle=True
):
""" The interface of mixup functions.
"""
if sample_2 is None:
return _mixup_samples(
alpha, beta, sample_1, label_1, sample_1, label_1, repeat, shuffl... | 3a704fe0ca3bc054accafc5f544c9146bf9d2df4 | 3,604,575 |
def operate(id, event, qstate, qdata):
"""
Perform action on pending query. Accepts a new query, or work on pending
query.
You have to set qstate.ext_state on exit. The state informs unbound about
result and controls the following states.
Parameters:
id - module identifier (integer)
... | 368687808b53c92e6346af26ebbf457815676f87 | 3,604,576 |
def readOpenMMReporterFile(reporter_file):
"""
Creates a dictionary containing all the entries in the reported data reporter_file
Parameters
----------
reporter_file : str
Path to the reporter output file
"""
with open(reporter_file, 'r') as ef:
lines = ef.readlines()
... | 9f7d3c958ef82994764f276bdd854868099c7960 | 3,604,577 |
def run_parallel(workflow, n_threads):
"""Run a workflow in parallel threads.
:param workflow: Workflow or PromisedObject to evaluate.
:param n_threads: number of threads to use (in addition to the scheduler).
:returns: evaluated workflow.
"""
scheduler = Scheduler()
threaded_worker = Queue... | 0aa3674a3a964a130c21d64a08cd21592eda3492 | 3,604,578 |
def parse_chain(chain_desc):
"""Parse user input chain
assign id to each nf and group nf by location
assgin offloadability to each nf
"""
global nf_offlodability
nf_id = 0
cur_location = None
cur_group = None
nf_groups = {}
for nf in chain_desc:
# assign id first
... | 925463a29789ce2fee118ba4a90691604cc3223c | 3,604,579 |
def sobel_fg_alpha(idepth, beta=5.0):
"""Computes foreground alpha with sobel edges.
Alphas will be low when there are strong sobel edges.
Args:
idepth: [B, H, W, 1] inverse depth tensor.
beta: (float) Higher the beta, higher the sensitivity to the idepth edges.
Returns:
alpha: [B, H, W, 1] alpha... | 4eab004f66d301f778cf453b7d939dcd8c8aa3b1 | 3,604,580 |
def hat_3d(xi):
"""
Converts a 3D twist to its corresponding 4x4 matrix representation
Args:
xi - (6,) ndarray: the 3D twist
Returns:
xi_hat - (4,4) ndarray: the corresponding 4x4 matrix
"""
if not xi.shape == (6,):
raise TypeError('xi must be a 6-vector')
xi_hat =... | 932074306716e933cd557f57a6f9809c34332abb | 3,604,581 |
def colourise(value, colour, condition=None):
"""Colour a piece of text. If a condition callback is passed in, the text will only be
coloured if the condition is met.
"""
if condition is not None:
if not condition(value):
return str(value)
return f"{colour}{value}{Fore.RESET}" | e70af19a68a049ff4a4b680c1547417dc89ff4a2 | 3,604,582 |
def get_cohort_by_name(course_key, name):
"""
Return the CourseUserGroup object for the given cohort. Raises DoesNotExist
it isn't present.
"""
return CourseUserGroup.objects.get(
course_id=course_key,
group_type=CourseUserGroup.COHORT,
name=name
) | d29170ec078a58e56d77b2daee76c7be03a35bf5 | 3,604,583 |
from typing import List
from typing import Optional
from typing import Dict
def merge_records_gnss(
records_gnss_list: List[Optional[kapture.RecordsGnss]],
sensor_mappings: List[Dict[str, str]]) -> kapture.RecordsGnss:
"""
Merge several gnss records list into one list with new identifiers for ... | 1bc128662172691c44c48bec90a639f51900c496 | 3,604,584 |
import math
def attention(query, key, value, mask=None, dropout=None):
"""Compute 'Scaled Dot Product Attention.
Inputs:
- query: [batch_size, num_heads, num_objects, feat_dim]
- key: [batch_size, num_heads, num_objects, feat_dim]
- value: [batch_size, num_heads, num_objects, feat_dim]
- m... | 9718f8f75629cb46072df1f721e8ce32c561531e | 3,604,585 |
def make_random_walks(dataset, k, L):
"""Computes random walks."""
cfg = {
'walker-name': 'uniform',
'args': {'walk_length': L, 'num_walks': k}
}
graph = to_undirected(dataset['graph'])
walker = ng_walkers.make_walker(cfg)
rws = ng_rw_util.precompute_rws_par(
g=graph,
... | e7c3928c539beb298bec0f2eb67ab610935f0a17 | 3,604,587 |
import inspect
def full_class_name(cls):
"""Returns the full qualified name of given class."""
assert isinstance(cls, type)
return inspect.getmodule(cls).__name__ + '.' + cls.__name__ | 876ced2ab0aa95af6d1a71f37c7c70da5ac8d5bf | 3,604,588 |
def form_node_label_prediction_matrix(y_pred, y_test):
"""
Given the discriminator distances, this function forms the node-label prediction matrix.
It is assumed that the number of true labels is known.
Inputs: - y_pred: A NumPy array that contains the distance from the discriminator for each label f... | ccfe961dbc744dc85c5ea9e586e825383b1e48b4 | 3,604,589 |
from typing import List
def check_pool_exist(pool: str, region: str) -> bool:
""" Check that we have slaves in the provided pool and region
"""
system_paasta_config = load_system_paasta_config()
expected_slave_attributes = system_paasta_config.get_expected_slave_attributes()
if expected_slave_attr... | 1f159ada404dd67aa00a7dcf419571249c030036 | 3,604,590 |
from typing import Optional
def get_databases(opts: Optional[pulumi.InvokeOptions] = None) -> AwaitableGetDatabasesResult:
"""
## Example Usage
```python
import pulumi
import pulumi_snowflake as snowflake
this = snowflake.get_databases()
```
"""
__args__ = dict()
if opts is N... | 0aef42b26a6b25d1b63edc1fab98613f3c3387e2 | 3,604,591 |
from typing import Callable
from typing import Optional
import pathlib
from typing import Sequence
import logging
import torch
import pprint
def maybe_launch(
main: Callable,
*,
exp_root: Optional[pathlib.Path],
overrides: Sequence[str],
cfg: pathlib.Path,
mode: util.ModeType,
adhoc: bool ... | e985a3088e63974fc0326b3def7a39f30aed45d0 | 3,604,593 |
from typing import Optional
def estimate_high_probability_upper_bound_bias(
reward: np.ndarray,
iw: np.ndarray,
iw_hat: np.ndarray,
q_hat: Optional[np.ndarray] = None,
delta: float = 0.05,
) -> float:
"""Helper to estimate a high probability upper bound of bias in OPE.
Parameters
----... | b5639db126029f0f24c641c39b443cd64e3aed99 | 3,604,594 |
def error_handler(error):
"""
Logs errors and renders specific, if available, or generic error page
"""
# For 4XX and 5XX level HTTP errors, save specific info
if isinstance(error, HTTPException):
code = error.code
description = error.get_description(request.environ)
name = ... | 16ba9672058555602e8b1eba4d5c08f31a704066 | 3,604,595 |
def compute_lr(
cv_in_2d_front: np.ndarray,
lr_2d_previous: np.ndarray,
disp: int,
p1_in_1d: np.ndarray,
p2_in_1d: np.ndarray,
current_segm_1d: np.ndarray,
previous_segm_1d: np.ndarray,
):
"""
Compute Lr of current plane, at a given disparity
:param cv_in_2d_front: cost volume
... | a78f5c14a8a77dead230aa7f75b53c4b06789e98 | 3,604,596 |
import typing
def ssub(s1: SliceRangeT, *rest: typing.Iterable[SliceRangeT]) -> SliceRangeSeqT:
"""Subtracts n >= 1 ranges"""
res = (s1,)
for i, el2 in enumerate(rest):
res1 = ()
for el1 in res:
res1 += ssub2(el1, el2)
res = res1
return res | eb1ea275e7cd58172ad3ee3a60605cda211e6d82 | 3,604,597 |
def logout(request, next_page=None,
template_name='myregistration/logged_out.html',
redirect_field_name=REDIRECT_FIELD_NAME,
current_app=None, extra_context=None):
"""
Logs out the user and displays 'You are logged out' message.
"""
auth_logout(request)
if next_page... | 4b2b4cf98a3c1fc8ccc658ea7ee33290622dc942 | 3,604,598 |
def make_response_409() -> jsonify(): # Conflict
"""This method is used to return request params related errors. Missing params or misspelling error handled"""
response_msg: dict = {
"Server Message": "The request could not be completed due to a conflict with the current state of the resource."
}
... | d548cccfb1aef3c0f4e1de45b98f05e7f8b4eb8c | 3,604,599 |
import logging
from datetime import datetime
def check_date(schedule, msg):
"""
Check with a regex the data as user input, can accept several formats
"""
match = REGEX_DATE.match(msg.content)
if not match:
schedule.custom_response = "Votre format de date est invalide."
logging.info... | f7d9a31f063525d2a0c66c87fdcfccc53d21f28a | 3,604,600 |
def choose_word(file_path, index):
"""
:param file_path:
:param index:
:return: tuple (num of words without duplicates, the word of the given index in the file
"""
file_input = open(file_path, "r")
count_of_words = len(set(file_input.read().split(" ")))
file_input.seek(0)
lines = fil... | 9c038574509918a4e91c316cde749dda322ef0e1 | 3,604,601 |
def getCommentsByThread(dbSession, tid):
"""gets all comments associated with a thread, ordered by time"""
comments = dbSession.query(Comment).filter(Comment.thread_id == tid).order_by(Comment.time_created.desc())
if comments:
return comments.all()
return None | 6a9c7e4f708cb68da0922c29154b0869cedff257 | 3,604,602 |
import json
def get_l2_t_from_file(diffusion_file):
"""
:param diffusion_file: json file with diffusion results
:return: The function takes from the file the experimental values of D and lifetime, It returns a list
with values of time from 0 to lifetime. With D computes the respective values of l².
... | c284e39af1e15bd6adf236a52455da45aae22382 | 3,604,603 |
def generate_false_pertinents_replace(text, present, m, neighbors, n_best_co_occurrence, proba_change=0.5,
forbidden=[], forbidden_tags=['PRP$'],
forbidden_words=['be'], top_n=50, temperature=.4,
pos=['NOUN', 'VERB', 'ADJ', 'ADV', 'ADP', 'DET'], use_proba=T... | 3104877924b4dbbd8108b9ed64cc3feae398858c | 3,604,604 |
def eigenfaces(X: ndarray, n_comp):
"""
Performs PCA to project faces in a reduced space.
Parameters
----------
X: ndarray
faces to project (shape: (n_samples, w*h))
n_comp: int
number of principal components
Returns
-------
tuple
proj_faces: the projected f... | 0d5f76c1848c91128a5ae7d2d8357c756e313062 | 3,604,607 |
def assignment(G, weight="weight", resolution=1):
""" Assign community partition to the graph by Louvain method"""
if G.number_of_edges():
part = community.best_partition(
G, weight=weight, resolution=resolution)
modu = community.modularity(part, G)
else:
part = {n: n for... | f9b24cbf2ea1b1c1c512781a44a2204b0354d6f8 | 3,604,608 |
import select
async def create_code(session: AsyncSession, longUrl: str):
"""Encodes a URL to a shortened URL.
"""
code = await generate_code()
generate_count = 0
while generate_count < 10 and (await session.execute(select(models.LongToCode).where(models.LongToCode.code == code))).first():
... | 4476ab4e75767cb4c65ecd0cc953c49f99c39cf8 | 3,604,609 |
def load_train_data():
"""
Loading the train data from data set
:return: Training components
"""
# Data preparation for train and test
raw_data_set = data_controller.load_data_file(FLAGS.positive_train_data_path,
FLAGS.negative_train_data_path,
... | 6696209e7ffdae8951c14462cd2345460506857e | 3,604,610 |
def collect_trainable_variables(modules):
"""Collects all trainable variables of modules.
Trainable variables included in multiple modules occur only once in the
returned list.
Args:
modules: A (list of) instance of the subclasses of
:class:`~texar.modules.ModuleBase`.
Returns... | e478563a59cfd940138f2344747037280c1c7447 | 3,604,611 |
def _get_split_cnn_model(img_dim, n_channels, num_partitions,
blocks_per_partition):
"""Creates a test model that is split into `num_partitions` smaller models."""
models = [tf.keras.Sequential() for _ in range(num_partitions)]
models[0].add(layers.Input(shape=(img_dim, img_dim, n_channel... | f626bc31bd0392aa888ce99067611a5642207d14 | 3,604,612 |
def ccall_except_check(x):
"""
>>> ccall_except_check(41)
42
>>> ccall_except_check(-2)
-1
>>> ccall_except_check(0)
Traceback (most recent call last):
ValueError
"""
if x == 0:
raise ValueError
return x+1 | f4a877f63a189b39fea477af218438de2e6c2a78 | 3,604,613 |
from pathlib import Path
import tokenize
def convert_to_tracer(file, placeholder):
""" Eats a filename of a text file.
Normalizes and tokenizes the text.
Converts it to tsv in the TRACER input format.
Writes the tsv file.
Depends on normalize(), save_abbreviations() and tokenize(... | 90a4dc0acd9a051a77935a0907da07b4a6178f01 | 3,604,614 |
def loadSVMLightData(filename):
"""
Load a file containing train/test data following the svmlight input format.
:param filename: The input data file
:return: The tuple (ITEMS, COMMENTS), where ITEMS is a list of tuples (TARGET, [(FEATURE,VALUE)], INFO)
and COMMENTS is a list of comment line... | 21ead993836806e27bee6846f23643051b2c3230 | 3,604,615 |
import scipy
def get_rotation_matrix(a,b,c,Order):
"""
[R, Q] = GetRotationMatrix(a,b,c,Order)
Computes a rotation matrix R between the coefficients of Spherical
Harmonic sound field descriptions before and after rotation. Note that R
is block diagonal, since rotations only involve coefficien... | 8b360a0fd19e90e6babe247665950b3731a01865 | 3,604,618 |
def packet_write(dxl_id, reg0, *register_values):
"""Create an instruction packet to write data in the DXL control table.
Args:
dxl_id: An integer representing the DXL ID number
reg0: An integer representing the register index in the control table
*register_values: A list containing inte... | 991fe6a983858bb2febc9b8f1d8008e50f2560f2 | 3,604,620 |
def WbDiscover( network, forTime = 5 ):
"""
This function looks for webbricks on the provided network.
The network parameter is in the form nn.nn.nn.nn/bits and identifies
a subnet accessible to the current computer.
The result is a list of dictionaries where there is a dictionary entry for each ... | 64df27860a70e36c52f262ade1256c9723324804 | 3,604,621 |
def num_fragmentations(df, obj_frequencies):
"""Total number of switches from tracked to not tracked."""
fra = 0
for o in obj_frequencies.index:
# Find first and last time object was not missed (track span). Then count
# the number switches from NOT MISS to MISS state.
dfo = df[df.OI... | 5d7bcebfeb486499eb8c102789db6cf9141f9247 | 3,604,622 |
def canon_did(uri: str) -> str:
"""
Convert a URI into a DID if need be, left-stripping 'did:mydata:' if present.
Args:
uri: input URI or DID
Raises:
ValueError: for invalid input.
"""
if ok_did(uri):
return uri
if uri.startswith("did:mydata:"):
mydata_di... | 62a5363759c88efeba5283bcce13710e1b2b23a8 | 3,604,623 |
def sort_tss_tts_files(tss, tts, genome_size):
"""
Sort the tss and tts files and combine them into a TS file
# IDEA: create a function where you sort only
and another one to merge and clean the TS file.
"""
# combine the two file to keep the lines consistents/together
ts = pd.me... | d76c19e3fdb449f5892c8ba502ea8c054ac83181 | 3,604,624 |
def input_prompt(prompt):
"""
Get user input
:param prompt: the prompt to display to the user
"""
return input(prompt) | b780278c37f048d1ea61f36af0947b683c5f9b9c | 3,604,625 |
def retail_score(flu_space, access_variables):
"""
Scores/weights for retail development.
"""
# access columns
prox_pers = 'persons_to_within15_OpAuto'
prox_jobs = 'sb_jobs_to_within15_OpAuto'
prox_retail_jobs = 'sb_jobs_in_retl_to_within15_OpAuto'
prox_retail_space = 'job_spaces_in_ret... | 95e47991d5cbeaaf4db0e2b99e95a146813a17e1 | 3,604,626 |
from peachpy.x86_64.registers import Register, MaskedRegister
from peachpy.x86_64.pseudo import Label
from peachpy.x86_64.function import LocalVariable
from peachpy.literal import Constant
from peachpy import Argument
from peachpy.util import is_int, is_int64
from copy import copy, deepcopy
from copy import copy, deepc... | 7c727f0965caad6c37df68d90e2e0d618374be5f | 3,604,627 |
def virtualaddress(target, **kwds):
"""Returns a pointer to /target/ where value is a va"""
kwds.setdefault('__name__', 'virtualaddress')
if 'type' in kwds:
return dyn.opointer(target, CalculateRelativeAddress, kwds.pop('type'), **kwds)
return dyn.opointer(target, CalculateRelativeAddress, **kwd... | d1c6082e897bf8737aae58cf473e4ae73da93e88 | 3,604,628 |
def safeintorbignumber(value):
"""safely converts value to integer or 10M"""
try:
return int(value)
except ValueError:
return 10000000 | de665dc11ba27c6846412b706cf833e46dc26758 | 3,604,629 |
import numpy
import math
def sigmamix(pfile, j, a, b, r1 , r2 = None):
"""returns sigma corresponding to r1 and r2 radius for mixed window.
w1(a) corresponds to r1, w2(b) corresponds r2"""
k, p = numpy.loadtxt(pfile, unpack = True)
if r2 is None:
r2 = r1
if a == "T":
w1 ... | 103fb8d0102b57f0eebde953fc6db8cc7996d4ed | 3,604,630 |
import requests
import re
import json
def get_figshare_article(article_id):
"""
Given a figshare article id, return a JSON object containing the article metadata
:param article_id:
:return: JSON object containing Figshare metadata
"""
version = re.compile('v[0-9]*')
article_result = reques... | 375bbb36226f002e8a7c85b8e2b1a28f13f52443 | 3,604,631 |
def isNumber(s):
"""
Tests whether an input is a number
Parameters
----------
s : string or a number
Any string or number which needs to be type-checked as a number
Returns
-------
isNum : Bool
Returns True if 's' can be converted to a float
Returns False if con... | bd1bae27814ddca22c39d6411df3581e8116c324 | 3,604,632 |
from typing import Callable
from typing import Optional
def get_authenticated_user_data(
handler: AuthenticationHandler,
username: str,
password: str,
password_checker: Callable[[str, str], bool]
) -> Optional[UserAuthData]:
"""Get user data if the authentication credentials match."""
user_dat... | 279150caea1484b6f84fe71c08ea1e4b0405bdf8 | 3,604,634 |
from typing import List
def get_ss_for_one_toad(name: str, variable: List[str]):
"""Get small series plot for one specific toad.
:param name: The name of the desired toad.
:param variable: Variable of interest.
:return: Two plots, the kinematic and force plate small series.
"""
# Get the proc... | f5f1c7b4a39198e7997d5ce5393a8be02de2735b | 3,604,635 |
def generate_road_map(sample_x, sample_y, rr, obstacle_kd_tree, height=0):
"""
Road map generation of the free workspace. Returned graph is wholly connected.
Inputs:
sample_x: [m] x positions of sampled points
sample_y: [m] y positions of sampled points
rr: Robot Radius[m]
ob... | 61043a2bea05c08d3db72d49c795143e0862a7ae | 3,604,636 |
import cv2
def _process_contours(image, contours, hierarchy, callback, index=0,
size_filter=True):
"""Traverse a hierachy of contours (contours containing contours) and
returns bounding boxes of the smallest possible objects that still remain
of interest.
Parameters
--------... | c4b1b88bfa97caf12fef7229d967a2b0da0eef02 | 3,604,637 |
def svn_fs_set_access(fs, access_ctx):
"""svn_fs_set_access(svn_fs_t * fs, svn_fs_access_t * access_ctx) -> svn_error_t"""
return _fs.svn_fs_set_access(fs, access_ctx) | 8eef1e5a46fbbdcc5ccbbf3140d6b64a86d8a8f1 | 3,604,638 |
def rescore_problem(entry_id, xmodule_instance_args):
"""Rescores a problem in a course, for all students or one specific student.
`entry_id` is the id value of the InstructorTask entry that corresponds to this task.
The entry contains the `course_id` that identifies the course, as well as the
`task_in... | f9c1005793d38a341e87e6d129e28c300b0be498 | 3,604,639 |
def KeplerH(z, m, grav_const=1):
""" with shapes (bs,2nd)"""
bs, D = z.shape # of ODE dims, 2*num_particles*space_dim
q = z[:, : D // 2].reshape(*m.shape, -1)
p = z[:, D // 2 :].reshape(*m.shape, -1)
potential_energy = KeplerV(q, m, grav_const=grav_const)
kinetic_energy = EuclideanK(p, m)
a... | 160e4bcc6be3659265a02af15ac7e2553a771c45 | 3,604,640 |
def dGElnorm(w: Wilson, El):
"""Normalized distribution 1D El"""
return tauBp / Btaul * dGEl(w, El) | df23eeb16f09544e09a9bebdc579afe95d88168d | 3,604,641 |
import re
def convert_to_utc(timestamp, timezone, printtz=None):
"""
Convert to UTC from timezone
:param1 timestamp: timestamp in ISO format or YYYY-MM-DD HH24:MI:SS
:param2: timezone: src timezone,
:param3: printtz: return string with timezone information
return: converted timestamp
"""
... | 4df0661ab8d5b2460a9b55a6aa664fa8592a37a8 | 3,604,642 |
def generate_log_filename():
""" Return a timestamped log filename """
return "LOG_"+strftime("(%Y-%m-%d)_%H-%M-%S", gmtime())+".txt" | 507b8a1ca128fc19566f41d32437bdbeacb30b93 | 3,604,643 |
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