content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
import json
def handle_response(command, frame, args, quiet=False):
"""
Handle a response frame from the device.
Return a dictionary of interesting information.
"""
ret_dict = {}
resp_command = frame.get_frame()[0]
if resp_command & protocol.CMD_RESPONSE:
resp_command ^= protocol.C... | 47b8eb435db997ec57581f100e9f72bc2bb8591c | 3,617,000 |
def trace(f):
"""
helps debug recursive calls
"""
indent = ' '
def _f(*args):
signature = '%s(%s)' % (f.__name__, ', '.join(map(repr, args)))
print '%s--> %s' % (trace.level * indent, signature)
trace.level += 1
try:
result = f(*args)
print ... | 718a70489887e47e0c3708b840dfffde7d0193fb | 3,617,001 |
import sqlite3
from typing import Any
def generate_table(rows: list[sqlite3.Row],
target: tuple[int, Any] = None) -> list[str]:
"""Generate a Markdown-like table out of the given rows.
The optional `target` parameter expects a tuple of the form
``(col#, value)``. If the given column nu... | 650e31efe92774749c306cf94dfeb91ad68ad502 | 3,617,002 |
def getPrivateKeyObject(filename = None, data = '', passphrase = ''):
"""
Return a C{Crypto.PublicKey.pubkey.pubkey} object corresponding to the
private key file/data. If the private key is encrypted, passphrase B{must}
be specified, other wise a L{BadKeyError} will be raised.
@type filename: ... | 07a5c5b302726b2db4eab3e451765ebbe592e374 | 3,617,003 |
import statistics
def get_two_movies_average_rating(movie1_id, movie2_id, threshold=50):
"""return the average rating for two movies, based on the users who have watched both of the movies"""
users = get_user_watched_two_movies(movie1_id, movie2_id)
if users and len(users) > threshold:
ratings1 = ... | 8a2080624357cd112d8789317984d0e01d1cf2da | 3,617,004 |
import torch
def test_extraction():
"""End-to-end test of a model extraction attack"""
# Create a query function for a target PyTorch Lightning model
model = train_four_layer_mnist_victim(gpus=torch.cuda.device_count())
def query_mnist(input_data):
# PrivacyRaven provides built-in query func... | 72ce6c053a9bca2cfaf965193b9cf5aa9f889df6 | 3,617,005 |
def read_parquet(filename, column, **kwargs):
"""read_parquet"""
memory = kwargs.get("memory", "")
start = kwargs.get("start", 0)
stop = kwargs.get("stop", None)
if stop is None and column.shape[0] is not None:
stop = column.shape[0] - start
if stop is None:
stop = -1
return parquet_ops.io_read_pa... | 785f0a6f16679b0f60ee37bcdadc9fba409b8099 | 3,617,006 |
from pathlib import Path
import os
import subprocess
def decompress(full_bzip_filename: Path, temp_pth: Path) -> str:
"""
Decompresses .bz2 file and returns the non-compressed filename
Args:
full_bzip_filename: Full compressed filename
temp_pth: Temporary path to save the native file
... | 4fdacd7340a75de056f08557c87509b0b899b1a8 | 3,617,007 |
def to_int(value):
"""Converts the given string value into an integer. Returns 0 if the
conversion fails."""
try:
return int(value)
except (TypeError, ValueError):
return 0 | f219844de96d1d2236e94c4427c0ad27cc4b587b | 3,617,008 |
def create_two_transforms_curve(transform1, transform2, name = ''):
"""
Create a curve between two transforms.
"""
if not name:
name = '%s_to_%s_curve' % (transform1, transform2)
pos1 = cmds.xform(transform1, q = True, ws = True, t = True)
pos2 = cmds.xform(transform2, q = True, ws ... | e894c77d647afdbe7676360ed73640193f03fe2e | 3,617,009 |
def vms_ajax_assign_disk(request, vm_id, template_name='vms/ajax/assign_disk.html', form_class=AssignDiskForm):
"""
Ajax view for assigning Disk to a virtual machine.
"""
rest_data = prep_data({'disks': 'user/storage_image/get_list/',
'disk_controllers': 'user/storage_image/ge... | c0fd472d9a9fbbd8a1e27a1b5bb86c313776cbdf | 3,617,010 |
def _default_function(l, default, i):
"""
EXAMPLES::
sage: from sage.combinat.integer_vector import _default_function
sage: import functools
sage: f = functools.partial(_default_function, [1,2,3], 99)
sage: f(-1)
99
sage: f(0)
1
sage: f(1)
... | 05da74d0c4ecee914928e8760d75730efc3434e5 | 3,617,011 |
import base64
import json
def parse_id_token(token: str) -> GoogleUserInfo:
"""Parse the base64 encoded id token."""
parts = token.split(".")
if len(parts) != 3:
raise RuntimeError("Received Invalid ID Token")
payload = parts[1]
padded = payload + ("=" * (4 - len(payload) % 4))
decode... | 8a7ea6c8d959c35df8f623f892b4df7e4b8af3b0 | 3,617,012 |
def _parse_apple(data):
"""Parse an AppleSingle or AppleDouble file."""
header = _APPLE_HEADER.from_bytes(data)
if header.magic == _APPLESINGLE_MAGIC:
container = 'AppleSingle'
elif header.magic == _APPLEDOUBLE_MAGIC:
container = 'AppleDouble'
else:
raise ValueError('Not an A... | 8cade17b36fcafdfde6ebd81a9918d77e114586c | 3,617,013 |
def convert_headers_str(_str):
"""
convert headers str to dict
"""
_list = [i.strip() for i in _str.split('\n')]
headers_dict = dict()
for i in _list:
k, v = i.split(':', 1)
headers_dict[k.strip()] = v.strip()
return headers_dict | cc80c1c2f5fc128243e59529808685335f7cead4 | 3,617,014 |
def make_expand_dims_tests(options):
"""Make a set of tests to do expand_dims."""
test_parameters = [{
"input_type": [tf.float32, tf.int32],
"input_shape": [[5, 4], [1, 5, 4]],
"axis_value": [0, 1, 2, -1, -2, -3],
"constant_axis": [True, False],
"fully_quantize": [False],
}, {
... | 238d4a6ba427357c4e02223c01d5245610016492 | 3,617,015 |
def eliminate_from_neighbors(csp, var) :
"""Eliminates incompatible values from var's neighbors' domains, modifying
the original csp. Returns an alphabetically sorted list of the neighboring
variables whose domains were reduced, with each variable appearing at most
once. If no domains were reduced, re... | 66062fce99f7f596239c27b27265bdec20cd55ae | 3,617,016 |
def cross(a, b):
"""Cross Product function
Given vectors a and b, calculate the cross product.
Parameters
----------
a : list
First 3D vector.
b : list
Second 3D vector.
Returns
-------
c : list
The cross product of vector a and vector b.
... | d71244391e28af7b42eff45af62cc936b8651cd2 | 3,617,017 |
from operator import add
def add_multiply(x, y, z):
"""Add two numbers and multiply it with a third."""
addition = add(x, y)
product = multiply(addition, z)
return product | 430e5c17106faab4a123123c42c10064727e654c | 3,617,018 |
async def async_setup(hass: HomeAssistant, config: dict):
"""Set up the media_source component."""
hass.data[DOMAIN] = {}
hass.components.websocket_api.async_register_command(websocket_browse_media)
hass.components.websocket_api.async_register_command(websocket_resolve_media)
hass.components.fronten... | 4de2588406b96b0a9eb8f9ad6ac959c79ad601ee | 3,617,019 |
import random
def rand_sampling(ratio, stop, start=1) :
"""
random sampling from close interval [start, stop]
Args :
ratio (float): percentage of sampling
stop (int): upper bound of sampling interval
start (int): lower bound of sampling interval
Returns :
A random... | 9b54c6b364e71a97d7cd9fa392790c4afde2bae0 | 3,617,020 |
import urllib
def open_webpage(url):
"""some webpages block the user agent 'python'"""
hdr = {'User-Agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.11 (KHTML, like Gecko) Chrome/23.0.1271.64 Safari/537.11'}
req = urllib.request.Request(url, headers=hdr)
return urllib.request.urlopen(req) | 1b7fd7d6edd652818f6c454e9e27a4c5bd11c298 | 3,617,021 |
def compare_from_file(filename, disable_tokenizers=None, verbose=True,
additional_tokenizers=None):
"""
Method to compare the tokenizers from an input text.
This function outputs information about the execution environment
and data and comparison results.
Parameters
-----... | 77863249c1ee2940bb5c3fa770ae3bd2ec934858 | 3,617,022 |
def humanbool(name, value):
"""
Determine human boolean value
:Parameters:
`name` : ``str``
The config key (used for error message)
`value` : ``str``
The config value
:Return: The boolean value
:Rtype: ``bool``
:Exceptions:
- `ValueError` : The value could n... | 422d45167c26f422e1f0a2fc5aa1c5e2eb752276 | 3,617,023 |
import os
def xlsx_to_array(url, sheetname='Data', skiprows=1, **kwds):
"""
Convert xlsx to numpy 2D array of objects
Parameters
---------
url: string or io
Can either be a path or and io object
sheetname: str
The sheet name for the sheet in the xlsx file wanted
Defa... | eab8e50b2970efc6b9d785022c175d68ef4e5ee0 | 3,617,024 |
async def filter_record(record_a, record_b, filter_fields=None):
"""
Filters a record for unique information.
Args:
record_a (``dictionary``): New airtable record.
record_b (``dictionary``): Old airtable record (This will be dictate the ``id``)
Kwargs:
filter_fields (``list``, o... | 79e42ff50bf8e43fb7c4df218b0de58f61ea778d | 3,617,025 |
def mask_tokens_evenly(tokens, gap, min_token_lengths, mask_token, gap_mask=1):
"""Produce several maskings for the given tokens where each masking is created by masking every
"gap" tokens, as long as the token is large enough according to min_token_lengths.
Args:
tokens (List[str]): a sequence of ... | 76cb6d402b73a5d5af0e1e87835485962e9b2353 | 3,617,026 |
async def async_setup(hass, config):
"""Set up the Polar component."""
conf = config.get(DOMAIN)
hass.data[DOMAIN] = conf or {}
if conf is not None:
_LOGGER.debug('Setting up Polar config flow from configuration data')
hass.async_create_task(
hass.config_entries.flow.async... | 699136d6751311b25c433e5944e8a8f0363637ab | 3,617,027 |
from .hosts import Host
def valid_host(host: Host) -> Host:
""" Validation test for valid Host class
Parameters:
host (Host): Host class object
Returns:
Host: Valid Host object
"""
if not isinstance(host, Host):
raise ex.InvalidHostError(
f'Must be Host class ... | bc8b25f3be0df5ed82b15d9e59f0453f70848be5 | 3,617,028 |
def build_graph(input_file):
"""Build the graph data structure from the input csv file."""
# Open the csv as dict iterator
input_file = open(input_file, 'rU')
reader = csv.DictReader(input_file)
# Create all nodes
nodes = {}
for row in reader:
name = row['NODE']
nodes[name] ... | aea8f7ccbadad85495c9d621de78ce31e03df4cb | 3,617,029 |
def build_rnn_dataset(sst_home, reader, class_func=ternary_class_func):
"""Given an SST reader, return the `class_func` version of the
dataset as (X, y) training pair.
Parameters
----------
sst_home : str
Full path to the 'trees' directory for SST.
reader : train_reader or dev_reader
... | 52526a5d778c17d229ac48beb7b70dcfd1ad83a0 | 3,617,030 |
from datetime import datetime
def iso_dt_to_datetime(t: str) -> str:
""" """
return default_datetime_repr(datetime.datetime.fromisoformat(t[:-1])) | 7b6fbb00188572aeac5629423ef739a5adc01861 | 3,617,031 |
def index():
"""
后台管理首页
"""
user = g.user
return render_template("admin/index.html", user=user.to_dict()) | 4d1b2fc5af8e5f0774e482a5201b4fc1ac73a839 | 3,617,032 |
def test_distance(markers, verbose=True,threshold=200,size=None):
"""detect if to center is too near than seuil delet the smaller
markers : image input
verbose : if you want display process
threshold : the sqaure distance into center
size : the minimum size of area of the retai... | d1c4cefcfb19a75493a5ca1b14a543711ef3eeab | 3,617,033 |
def cs(dataset, pts=0.0, neg=False, **kwargs):
"""
Circular shift.
For multidimensional NDDataset,
the shift is by default performed on the last dimension.
Parameters
----------
dataset : nddataset
nddataset to be shifted
pts : int
Number of points toshift.
neg : bo... | 051b56afa521f8c545cba27bef6648c1e21f9edc | 3,617,034 |
def _result_value_flat_to_batchable(result_value_flat, result_flat_signature):
"""Converts result_value_flat -> result_value_batchable."""
result_value_batchable = []
for (r_value, r_spec) in zip(result_value_flat, result_flat_signature):
if isinstance(r_spec, tensor_spec.TensorSpec):
result_value_batch... | bc63f3fa692912622bfa1ce84373c94f3f9ec5e3 | 3,617,035 |
def sample_action(Q, state, num_actions, epsilon):
"""
Epsilon greedy action selection.
Parameters
----------
Q : numpy array of shape (N, 1)
Q function for the environment where N is the total number of states.
state : int
The current state.
num_actions : int
The ... | 8034037fbdb4bb0538f786b262930c64c4615412 | 3,617,036 |
def get_socket_from_cluster_id(cluster_id):
"""
Returns the socket and token/queue dict for the specified cluster id
:param cluster_id: The if of the cluster to check
:return: The websocket and dict if found or None
"""
# Iterate over the connections
for sock in CONNECTION_MAP:
# Ch... | 07ffe7a17e093d7bd8f1087501019f7527681535 | 3,617,037 |
from typing import Tuple
from typing import Dict
def save_user_giphy(user: "Users", giphy: "str") -> "Tuple[Response, int]":
""" Saves giphy to user account
Params:
user (Users): User model provided by token_required
giphy (str): Giphy ID provided by GIPHY
Returns Tuple[Response, int]
... | 2d0ffaa40841cef373cea600c968bea6a9dd9682 | 3,617,038 |
def contain_same_digit(a, b):
"""
This function tests whether or not numbers a and b contains the same digits.
"""
list_a = list(str(a))
list_b = list(str(b))
if len(list_a) == len(list_b):
for elt in list_a:
if elt not in list_b:
return False
return T... | a09feb891e5413593531e56871a92c335e585d7b | 3,617,039 |
def get_names_of_packages(packages_info, without_rpmem):
"""
Returns names of packages, that should be built.
"""
packages = []
types = ['-', '-debug-', '-devel-', '-debuginfo-', '-debug-debuginfo-']
for elem in packages_info:
# checks if rpmem and rpmemd packages should be built
... | 8116824b61bc4d2528458304408c8eb8b3d8fc21 | 3,617,040 |
from typing import Union
def has_nonnegative_entries(input_matrix: Union[sparse.csr_matrix, np.ndarray]) -> bool:
"""True if the array has non negative entries."""
if type(input_matrix) == sparse.csr_matrix:
return np.all(input_matrix.data >= 0)
else:
return np.all(input_matrix >= 0) | 882bb05a6ef60835145dafdbe1f7a1a5b855fe84 | 3,617,041 |
def get_worker():
"""
Creates a redis queue worker with a retry exception handler.
To run the worker:
>> worker = get_worker()
>> worker.work(with_scheduler=True)
"""
settings = get_config()
queue = redis_queue(settings)
return Worker(
queues=[queue], connection=queue.connec... | 2397098513afb9fad917b2d1e1ea2cf5cb800077 | 3,617,042 |
def setup_platform(hass, config, add_devices, discovery_info=None):
"""Setup the Command Sensor."""
if config.get('command') is None:
_LOGGER.error('Missing required variable: "command"')
return False
data = CommandSensorData(config.get('command'))
add_devices([CommandBinarySensor(
... | 784a790b375ab25d4c6bbb4c42f131c08f270c1a | 3,617,043 |
def error_data(code):
"""Constructs a dictionary with status and message for returning in an
error response"""
error = {
'status': code,
'message': http_status_message(code),
}
return error | 6e4a01e5b32a74701605dba62b88738f9e852073 | 3,617,044 |
from typing import NamedTuple
import logging
def get_logger(config: NamedTuple) -> logging.Logger:
"""
Create instance of a logger and configure it using the variables from yaml config variables
:return:
"""
try:
# create logger with app name
logger: logging.Logger = logging.getLog... | 53c1de3180b467eec0ba937565eec524c945259e | 3,617,045 |
def test_Mesh_NO6_transfinite():
"""Unittests for the mesh."""
if rAnk == mAster_rank:
print(">>> {test_Mesh_NO6_transfinite} ...... ", flush=True)
def u(t, x, y, z): return np.cos(np.pi*x) + np.sin(np.pi*y) * np.sin(np.pi*z-0.125)**2 + t/2
def v(t, x, y, z): return np.sin(np.pi*x) + np.sin(np.... | aada50c384ffff0477962158f2e3902e8c9f471f | 3,617,046 |
def range_correction(series, range=None, value=np.nan):
"""Corrects issues with ranges.
Some values collected are not within the ranges. They could
also be removed using the IQR rule, but if we know the limits
we can filter them as errors instead of outliers.
.. todo: Warn if replace value is outs... | 452472772d955597f3a1495a38cd0a42c7b2accf | 3,617,047 |
def isPILAllowed():
"""Return true iff PIL should be used by the caller."""
global _pil_allowed
if _pil_allowed is None:
app = grailutil.get_grailapp()
_pil_allowed = (app.prefs.GetBoolean("browser", "enable-pil")
and pil_installed())
return _pil_allowed | 34a33d0789cca703c8dc36103b652c307bb51820 | 3,617,048 |
import yaml
def read_yaml(config_path):
"""Load config files."""
with open(config_path) as file:
data = yaml.load(file, Loader=yaml.FullLoader)
return data | b46882ad841228edb3398a5742fa4dea6c4e9495 | 3,617,049 |
def read_jsonlines(filepath: str) -> pd.DataFrame:
"""Function that reads a jsonlines file as a pandas dataframe"""
with open(filepath) as f:
lines = f.read().splitlines()
dicts = [eval(line) for line in lines]
return pd.DataFrame(dicts) | 01c77934df604de88d747d032045f886ffe33bdf | 3,617,050 |
from typing import Tuple
def read_data_attention(strategy: tf.distribute.TPUStrategy,
max_len: int,
) -> Tuple[np.array, np.array, np.array, np.array, tf.data.Dataset, tf.data.Dataset, tf.data.Dataset, int]:
"""
read data from attention models
"""
logger... | fa3943c787f203a6e57a59da7c93baa090223360 | 3,617,051 |
def cosine_sim(text1, text2):
"""
Calcuates the cosine distance between the skills
and the course description.
:param text1: Phrase 1
:param text2: Phrase 2
:return: returns the probabilistic measure of similarity.
"""
vectorizer = TfidfVectorizer(tokenizer=normalize, stop_words='english... | abef404514d9db40ca79c04f3663f1ea062e5b12 | 3,617,052 |
def distinct(key_mapper=None):
"""Returns an observable sequence that contains only distinct
elements according to the key_mapper. Usage of
this operator should be considered carefully due to the maintenance
of an internal lookup structure which can grow large.
The source must be a MuxObservable.
... | 80f40e88ecfff69a954c82fd15f8fafe797b13f4 | 3,617,053 |
def svn_client_commit3(*args):
"""
svn_client_commit3(svn_commit_info_t commit_info_p, apr_array_header_t targets,
svn_boolean_t recurse, svn_boolean_t keep_locks,
svn_client_ctx_t ctx, apr_pool_t pool) -> svn_error_t
"""
return apply(_client.svn_client_commit3, args) | d69ebad3d11e194a7b4bd25935e57f7b8b17362f | 3,617,054 |
def parse_range(string):
"""
Parses IP range for args parser
:param string: formatted string X.X.X.X-Y.Y.Y.Y
:return: tuple of range
"""
ip_rng = string.split("-")
return [(ip_rng[0], ip_rng[1])] | 6f38e105284d58af2cef94275c25e02ad76acb80 | 3,617,055 |
from typing import Optional
from typing import Union
from typing import Sequence
from typing import Literal
def panas(
data: pd.DataFrame,
columns: Optional[Union[Sequence[str], pd.Index]] = None,
language: Optional[Literal["english", "german"]] = None,
) -> pd.DataFrame:
"""Compute the **Positive and... | 90933eab4a82f64c37cfee455d756218151d4e46 | 3,617,056 |
def notes(l, b, i):
"""!parent-command
!c new
!d Create a new note (use \n for newline)
!a <title> <message...>
!r user
!c list
!d List all notes available
!r user
!c append
!d Append a line of text to a note
!a <title> <message...>
!r user... | c2594c2d4fb21bf5d8d1f28d7077f8a5ebd60e49 | 3,617,057 |
def measure_circuits_nondeterministic(allow_sampling=True):
""""Measure test circuits with non-deterministic count output."""
circuits = []
qr = QuantumRegister(2)
cr = ClassicalRegister(2)
# Measure |++> state (sampled)
circuit = QuantumCircuit(qr, cr)
circuit.h(qr)
circuit.barrier(qr... | b7e5424c2340753d374ecc1f14fe6f65034e9661 | 3,617,058 |
def process_stanford_sentiment_corpus(train_path, dev_path, test_path,
pkl_path,
unk_threshold,
unk_token= '<UNK>',
pad_token= '<PADDING>'):
"""
Input three... | fd341b283801fee3face62117e1a5845e10892b6 | 3,617,059 |
from io import StringIO
import gzip
def _get_data(url):
"""Helper function to get data over http or from a local file"""
if url.startswith('http://'):
resp = urllib2.urlopen(url)
encoding = resp.headers.dict.get('content-encoding', 'plain')
data = resp.read()
if encoding == 'pl... | 6b7b1a803dd03d6fce25a0e679abf6110cef423a | 3,617,060 |
import inspect
def lineno(): # pragma: no cover
"""
Returns the current line number in our script
:return:
"""
return str(' - line number: ' + str(inspect.currentframe().f_back.f_lineno)) | ca40ae90ea44883ac40bd5524fee04c3957b2021 | 3,617,061 |
def _require_response_200_ok(response):
"""
Accept a requests.response object.
Raise ResponseNotOK if status code is not 200.
Otherwise, return True
"""
if response.status_code != 200:
raise ResponseNotOK(
status_code=response.status_code, message=response.text
)
... | 4b35584eca30d7b0ac62ef51587f6f7cf03749a3 | 3,617,062 |
import fnmatch
import os
def trial_matrix(root,iwhisker=0,ifeature=3):
""" image plot of a feature for a whisker where each row is a trial
"""
def gen_names(root):
for r,dirnames,filenames in os.walk(root):
for filename in fnmatch.filter(filenames,'*.measurements'):
yield os.path.join(r,file... | 5f9f6779060327bfc9302038176317e7cf6a940b | 3,617,063 |
def pf_index(grid: Grid, grid_params: GridParams) -> PFIndex:
"""Ordered buses and mappings to admittances and slack factors."""
pv_idx = pv_buses(grid, grid_params)
pq_idx = pq_buses(grid, grid_params)
s_idx = slack_factors(grid, grid_params)
y_idx = admittances(grid, grid_params)
ret... | 2b092b71051bb0bdbd97ed9926b310f016f88d50 | 3,617,064 |
import re
def read_rdump(filename: str) -> dict:
"""
Read data formatted using the R dump format.
"""
contents = open(filename).read().strip()
names = [name.strip() for name in re.findall(r'^(\w+) <-', contents,
re.MULTILINE)]
values = [value.strip() for value in re.split(r'\w+ +<... | 3624f56d2872885c50d2d7f521730bb8a8864211 | 3,617,065 |
def selectYear(update: Update, context: CallbackContext):
"""
Select the yaer for which to list expenses
"""
year = update.message.text
context.user_data['inputYear'] = year
text = ("Received '"+year+"' as the selected year"
+"\nSelect from below the month for which you'd like to list exp... | 79c982b1591e15b9014302ca4380ec8900bad17f | 3,617,066 |
def sort_by_field(boxlist, field, order=SortOrder.descend, scope=None):
"""Sort boxes and associated fields according to a scalar field.
A common use case is reordering the boxes according to descending scores.
Args:
boxlist: BoxList holding N boxes.
field: A BoxList field for sorting and reordering the... | a091e699182fe9c1b8a2bca881759004e67fc7d9 | 3,617,067 |
import json
def process_frame(frame_data, d_width, d_height, features_file, images_dir, min_trajectory_len):
"""Save faces + features from a frame, and creating face embeddings.
"""
# Filter to faces with a valid trajectory (len > MIN)
valid_faces = [
face for face in frame_data["faces"]
... | 07be5d8fe578ca89cf56c763c3ad3c9bbe5c5986 | 3,617,068 |
from sympy.polys.polytools import degree
from sympy.polys.domains import FractionField
from sympy.core.basic import preorder_traversal
def minimal_polynomial(ex, x=None, **args):
"""
Computes the minimal polynomial of an algebraic element.
Parameters
==========
ex : algebraic element expression
... | 7f9c74d05a19858607fecf0b4f87798eafbf9534 | 3,617,069 |
import struct
import tqdm
def init_compress_timepix_data(
pos, t, binstep, filename, mask=None, md=None, nobytes=2, with_pickle=True
):
"""YG.Dev@CHX Nov 19, 2017 with optimal algorithm by using complex index techniques
Compress the timepixeldata, in a format of x, y, t
x: pos_x in pixel
y: pos_y... | 6bf01ebc99e0bd2d40dc00152e3329f5fa9427c3 | 3,617,070 |
import torch
def calc_dihedral(v1, v2, v3, v4, x_idx=None, y_idx=None, eps=1e-6):
"""
Calculate the dihedral angle between 4 vectors.
v1, v2, v3, v4: shape (..., 3)
x_idx, y_idx: shape (...), additional information of vectors.
return: (x_idx, y_idy, dihedral)
"""
x = v2 - v1
y = v3 - v... | 4ef064aa607ff23d212b628dd5c465e13fffd9b5 | 3,617,071 |
def set_convert_inputs(flag):
""" This function is a temporary workaround for reducing the overhead of operator
invocations. The function `convert_inputs` is disabled if the global state
`_enable_convert_inputs` is set to `False`, otherwise enabled. This function is for
internal use only, and should be ... | 5bf661d6aeef099b7ecdfd117cf9dfdb4fae1285 | 3,617,072 |
import ctypes
def encode_flush():
"""
Flush the encoding buffers and return final frames (if any).
"""
_lib.lame_encode_flush.argtypes = [
ctypes.c_void_p, ctypes.c_void_p, ctypes.c_int]
_lib.lame_encode_flush.restype = ctypes.c_int
mp3buffer = (ctypes.c_char * 7200)()
mp3buffer_us... | d0f137df60020c55ab27f4b98cb4dba7bc71a60f | 3,617,073 |
import logging
import traceback
from datetime import datetime
async def format_stream(member: discord.Member, osu_score: dict, beatmap: dict):
""" Format the stream url and a VOD button when possible. """
stream_url = None
for activity in member.activities:
if activity and activity.type == discord... | 6814fd8329868e13baf4fd2b3d03888c211e39a5 | 3,617,074 |
def parse_city_state_zip(city_state_zip):
""" Parses city_state_zip into a dict """
city_state_zip = normalize(city_state_zip.replace(",", ", ").replace(".", ". ").strip())
if city_state_zip:
# normalize commas
_m = " ,"
while _m in city_state_zip:
city_state_zip = city_s... | d60cefd3ac24acae08bc2196bf1629fd1fc92e45 | 3,617,075 |
def flows_from_sff(flows):
"""lines is sff file lines.
"""
if isinstance(flows, str):
flows = flows.splitlines()
flows, head = parse_sff(flows)
return flows_from_generic(flows) | 2a917c4f6e747b388c561ef933f861eef918552b | 3,617,076 |
def common_lens(cube_list):
"""
Give the common lenses of a list of pySNIFS cubes
@param cube_list: input list of datacubes
@return: inters: list of the lenses common to all the cubes of the list
"""
inters = cube_list[0].no
for i in xrange(1,len(cube_list)):
inters = filter(lambda x... | f8c22e76a92ae187006977e86b5483601088a98d | 3,617,077 |
def protected(Authorize: AuthJWT = Depends()):
"""
We do not need to make any changes to our protected endpoints. They
will all still function the exact same as they do when sending the
JWT in via a headers instead of a cookies
"""
Authorize.jwt_required()
current_user = Authorize.get_jwt_s... | a0232bd11634ccac83086733e5032c5ccca9ff73 | 3,617,078 |
from typing import Optional
import torch
def sin(x: DNDarray, out: Optional[DNDarray] = None) -> DNDarray:
"""
Compute the trigonometric sine, element-wise.
Result is a ``DNDarray`` of the same shape as ``x``.
Negative input elements are returned as ``NaN``. If ``out`` was provided, ``sin`` is a refer... | 74a52f3a72d35eec4bbea94e3ed51abf02bc30ef | 3,617,079 |
from typing import Optional
from typing import List
def list(lst: 'Optional[List_[PythonValue]]' = None) -> PythonValue:
"""Returns a List wrapped into a PythonValue"""
return PythonValue(List(lst=lst)) | 08f607b4befae0393561cf6bd06f43c1029dc724 | 3,617,080 |
async def set_consumer_to_infernal_job(engine, job_id, consumer_ip):
"""
Update the infernal_job table to register the consumer who will run the job
:param engine: params to connect to the db
:param job_id: id of the job
:param consumer_ip: ip address of the consumer
:return: id or none
"""
... | 05627d52809ebf378a030e40473dcee8b9e6ecc2 | 3,617,081 |
def get_recursively(search_dict: dict, field: str) -> list:
"""Take a dict with nested lists and dicts,
and searche all dicts for a key of the field
provided.
https://stackoverflow.com/a/20254842
Args:
search_dict (dict): Dictionary to search
field (str): Field to search for
R... | 5457a41116cfb58eaf6ab57918a5d87eae7196a6 | 3,617,082 |
from pathlib import Path
def askDestination():
"""
prompts user for backup directory and sets it to destination
:returns: new destination
"""
location = filedialog.askdirectory()
# validation
p = Path(location)
if not p.exists() or not p.is_dir() or location == '':
return bm.d... | fe805e9ec3dbe503a2357ac6bcad4c4aa1809be5 | 3,617,083 |
def get_hostip(req=None, log=None):
"""Look up the IP address for a given requested interface name.
If interface is not given, do some magic."""
global _hostip # pylint: disable=W0603
if _hostip:
return _hostip
AF_INET = netifaces.AF_INET
# We cre... | 27d9d024ae1854b1f122232ef2a17deb8d827eb2 | 3,617,084 |
def time_series_sum_of_reoccurring_values(x):
"""
Returns the sum of all values, that are present in the time series
more than once.
:param x: the time series to calculate the feature of
:type x: pandas.Series
:return: the value of this feature
:return type: float
"""
return ts_feat... | 020203facf8765f292cb2f19f68dc603c8254b66 | 3,617,085 |
def promote_numeric_to_real(stage: ImportStage, value: ir.Value) -> ir.Value:
"""Promotes the value to RealType."""
return d.PromoteNumericOp(d.RealType.get(), value).result | d1be8cac377e34687a7b7ab680c507d9166820a7 | 3,617,086 |
import asyncio
async def make_photo():
"""Photo from web camera.
"""
loop = asyncio.get_running_loop()
img, _ = await loop.run_in_executor(app.ps_executor, get_png_photo)
if img:
result = StreamingResponse(
png_img_to_buffer(img), media_type="image/png"
)
else:
... | 5e243950d75a68d245d751fd6636f1416e30a31b | 3,617,087 |
def get_adj_matr(graph):
"""
Function to create an adjacency matrix representation of a graph.
arg:
graph - (dict) of 'nodes' : [], 'edges' : []
returns:
pd.DataFrame with entry i,j representing an edge from node i to node j
"""
n = len(graph['nodes'])
adj_matr = pd.DataFrame... | 81bc0673071c1afe96340039feb94ab1bd3b2393 | 3,617,088 |
import sqlite3
def _test_sqlite3_db(db_path):
"""Very basic test for validity of database."""
# Check for file existance and if it's a sqlite3 db
if isfile(db_path):
try:
conn = sqlite3.connect(db_path)
# TODO: If we really care, do a more thorough check
# If ... | 61b4fd66edbc32e876ac8ddeae166354b18c94ec | 3,617,089 |
import os
def get_resourcesize(path):
"""指定されたリソースの標準サイズを返す。"""
dpath = os.path.basename(os.path.dirname(path))
fpath = os.path.splitext(os.path.basename(path))[0]
key = "%s/%s" % (dpath, fpath)
if key in SIZE_RESOURCES:
return SIZE_RESOURCES[key]
else:
return None | 22b09f497cb2b361d72ec2da3ea43eb98a201519 | 3,617,090 |
import os
def all_files_from(dir, ext=''):
"""Quick function to get all files from directory and all subdirectories
"""
files = []
for root, dirnames, filenames in os.walk(dir):
for filename in filenames:
if filename.endswith(ext) and not filename.startswith('.'):
f... | e6e2fc545ceda51a2b4560829b0e995c164c5d9c | 3,617,091 |
import requests
import re
def get_title(url: str):
""" Get the Title of the web page and generates markdown formated link"""
html_source = requests.get(url).text
title = re.findall('<title>(.*?)</title>', html_source)[0].strip()
return f"[{title}]({url})" | c6b0a559e7e3369d34e6266b7636d5c4a13ed2f0 | 3,617,092 |
def pow_4_of(number):
"""
fourth power of number
helper function from lalsimulation/src/LALSimIMRPhenomD_internals.h
"""
pow2 = pow_2_of(number)
return pow2 * pow2 | 9ae515bd8ca9e8027f6ddecd71b714010668cfa3 | 3,617,093 |
def item_cost_entry() -> float:
"""Return the sum of all user entries."""
print('\nENTER ITEMS (ENTER 0 TO END)')
subtotal: float = 0.0
while True:
cost: float = float(input('Cost of item: '))
if cost == 0:
break
else:
subtotal += cost
return subtotal | d9d5bdc53f2d37f348d477086935cba3ba6a8e7e | 3,617,094 |
def mark_duplicates(job, config, name, input_bam):
"""Run Picard MarkDuplicates
:param config: The configuration dictionary.
:type config: dict.
:param sample: sample name.
:type sample: str.
:param input_bam: The input_bam file name to process.
:type input_bam: str.
:returns: str -- Th... | d7987f74d4c12ee190e895374a062cdc140ec2d6 | 3,617,095 |
def normalize_tokens(tokens):
"""
The OP-1 gets confused with multiple line segments in one command.
This fixes that by splitting multiple segments into separate commands.
Convert from e.g.:
["l", "20", "20", "20", "-20", "10", "10"]
To:
["l", "20", "20", "l", "20", "-20", "l", "10", "10"]
... | 972b7b2d46ac28d5d06c559fed1878355e18774e | 3,617,096 |
import test
def full_train_and_test(filename):
"""
Uses the entire dataset for both training and testing.
Returns the testing accuracy.
"""
table, cumulative, dataset, index_to_name = train(filename)
preds, targets = test(table, cumulative, dataset, index_to_name)
n_correct, n_total = acc... | c27a9dafa27eab2b137a6b84d8e60e34665683ad | 3,617,097 |
def _read_attachment(fp, has_arg=False, debug=False):
""" Reads an ATTACHMENT block.
"""
target, arg, header, data = _read_block(fp, has_arg=False, debug=debug)
d = dict(header=header,
data=data,
threshold=0.0)
lr = [s.strip() for s in RE_ARROW.split(target)]
if len(... | 6c175b8e9b8c4f401ce4bab6960eb61dde5e8b16 | 3,617,098 |
import torch
def mmd2_rbf(X, t, p, sig=0.1):
"""
Computes the l2-RBF maximum mean discrepancy (MMD) for X given t.
http://www.jmlr.org/papers/volume13/gretton12a/gretton12a.pdf -- Eq3
"""
it = np.where(t==1)[0]
ic = np.where(t==0)[0]
Xc = X[ic]
Xt = X[it]
if list(Xc.shape)[0] == ... | 80d61470c84b2ce2c1f06930ae38bd711ff2f0bb | 3,617,099 |
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