content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
import hashlib
import six
def make_hashkey(seed):
"""
Generate a string key by hashing
"""
h = hashlib.md5()
h.update(six.b(str(seed)))
return h.hexdigest() | 38d088005cb93fc0865933bbb706be171e72503a | 3,638,454 |
import asyncio
async def report(database, year, month, limit):
"""Get a report."""
matches_query = """
select count(*) as count
from matches
where extract(year from played)=:year and extract(month from played)=:month
"""
players_query = """
select count(distinct players... | 91059c5a8bd44536f24a7edbb88ff27b9036b83a | 3,638,455 |
def dy3(vector, g, m1, m2, L1, L2):
"""
Abbreviations
M = m0 + m1
S = sin(y1 - y2)
C = cos(y1 - y2)
s1 = sin(y1)
s2 = sin(y2)
Equation
y3' = g*[m2 * C * s2 - M * s1] - S*m2*[L1 * y3^2 * C + L2*y4^2]
-------------------------------------------------------------
... | b93086cfcbb9d5f32143279ad01972d3f8719a78 | 3,638,457 |
from typing import Any
def getType(resp: falcon.Response, class_type: str, method: str) -> Any:
"""Return the @type of object allowed for POST/PUT."""
for supportedOp in get_doc(resp).parsed_classes[class_type]["class"].supportedOperation:
if supportedOp.method == method:
return supportedO... | d20b77b4f40d266e685ce87f67d8f2fcbcfbe3eb | 3,638,458 |
def full_data_numeric():
"""DataFrame with numeric data
"""
data_dict = {'a': [2, 2, 2, 3, 4, 4, 7, 8, 8, 8],
'c': [1, 2, 3, 4, 4, 4, 7, 9, 9, 9],
'e': [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
}
df = pd.DataFrame(data_dict)
return df | ebd105f2648475dc7dcd40f51482d18e29486254 | 3,638,459 |
def fix(x):
"""
Replaces spaces with tabs, removes spurious newlines, and lstrip()s each
line. Makes it really easy to create BED files on the fly for testing and
checking.
"""
s = ""
for i in x.splitlines():
i = i.lstrip()
if i.endswith('\t'):
add_tab = '\t'
... | ecd3a4d7f470feae1b697025c8fbf264d5c6b149 | 3,638,460 |
def get_collect_method(collect_method_name):
"""Return the collect method."""
try:
collect_method = CollectMethod.get(name=collect_method_name)
except ValueError:
raise RuntimeError(f'Collect Method {collect_method_name} not found!')
return collect_method | b80fcb916d461deea1784386062017291292f218 | 3,638,461 |
def TriangleBackwardSub(U,b):
"""C = TriangleBackwardSub(U,b)
Solve linear system UC = b
"""
C = solve(U,b)
return C | 95c7fb76ad02a5546a79b95f18b51fe385307329 | 3,638,462 |
from unittest.mock import patch
def test_binance_query_balances_unknown_asset(function_scope_binance):
"""Test that if a binance balance query returns unknown asset no exception
is raised and a warning is generated. Same for unsupported asset."""
binance = function_scope_binance
def mock_unknown_asse... | 7521fd3039398c3eedccb16e16202687b4c28b2d | 3,638,463 |
def petsc_to_stencil(x, Xh):
""" converts a numpy array to StencilVector or BlockVector format"""
x = x.array
u = array_to_stencil(x, Xh)
return u | 6df02bbbfb9e9e386ca03510f2e4d563a6fed1aa | 3,638,464 |
from typing import Optional
import contextlib
def index_internal_txs_task(self) -> Optional[int]:
"""
Find and process internal txs for monitored addresses
:return: Number of addresses processed
"""
with contextlib.suppress(LockError):
with only_one_running_task(self):
logger.... | b1a40ec713ff8d302f5c47b2c5d41300c699f3b4 | 3,638,465 |
import math
def make_lagrangian(func, equality_constraints):
"""Make a Lagrangian function from an objective function `func` and `equality_constraints`
Args:
func (callable): Unary callable with signature `f(x, *args, **kwargs)`
equality_constraints (callable): Unary callable with signature `... | c5795cded21e9cc4a7092eee63b88a4fac3b346a | 3,638,466 |
def ungroup(expr):
"""Helper to undo pyparsing's default grouping of And expressions,
even if all but one are non-empty.
"""
return TokenConverter(expr).addParseAction(lambda t: t[0]) | c007a51e5073d8a3cbcbe52ca32ad84d58f4100a | 3,638,468 |
def test_qnn_legalize():
"""Test directly replacing an operator with a new one"""
def before():
x = relay.var("x", shape=(1, 64, 56, 56), dtype='int8')
y = relay.qnn.op.requantize(x,
input_scale=1,
input_zero_point=0,
... | b6f4a930e5c7156e60a5b26583b6e8fc48a6f441 | 3,638,471 |
import yaml
def load(data, schema, yamlLoader=yaml.UnsafeLoader):
"""
Loads the given data and validates it according to the schema provided.
Data must be either JSON or YAML, it must be a dictionary, a path, or a string of JSON.
Schema must be JSON, it must be a dictionary, a path, or a string of JSO... | e7f29e1b61e60ce1cac5b1b1217f1df645691c17 | 3,638,472 |
from typing import List
def calculate_slice_rotations(im_stack: np.ndarray, max_rotation:float = 45) -> List[float]:
"""Calculate the rotation angle to align each slice so the
objects long axis is aligned with the horizontal axis.
Parameters
----------
im_stack : np.ndarray
A stack of ima... | 42c0fdbdf02e937f449cb3ca137588003c715651 | 3,638,473 |
def calc_rest_interval(data):
"""
SubTool for Investigate: after median_deviation filters through all the
points run entropy on the remaining non_rest points. This will filter the
close but could still be rest points.
"""
lst, rest = median_deviation(data)
average = median(data)
st_entr... | 7710e0784a5a025d99c8ead9799b1062942e3cdc | 3,638,474 |
def get_objanno(fin_anno, godag, namespace='all'):
"""Get annotation object"""
fin_full = get_anno_fullname(fin_anno)
return get_objanno_factory(fin_full, godag=godag, namespace=namespace) | 5e071190596ab37943d4001b4f03cf20d6395e06 | 3,638,475 |
def create_table_descriptives(datasets):
"""Merge dataset descriptives."""
df = pd.concat(
[pd.read_json(ds, orient="index") for ds in datasets],
axis=0
)
df.index.name = "dataset_name"
return df | 7c4554381ffb14572d949c27035411567d69e25d | 3,638,476 |
def get_ngram_universe(sequence, n):
"""
Computes the universe of possible ngrams given a sequence. Where n is equal to the length of the sequence, the resulting number represents the sequence universe.
Example
--------
>>> sequence = [2,1,1,4,2,2,3,4,2,1,1]
>>> ps.get_ngram_universe(sequence, 3)
64
"""
# if... | 3dbfe1822fdefb3e683b3f2b36926b4bb066468f | 3,638,477 |
from typing import Union
from typing import Iterable
def as_nested_dict(
obj: Union[DictLike, Iterable[DictLike]], dct_class: type = DotDict
) -> Union[DictLike, Iterable[DictLike]]:
"""
Given a obj formatted as a dictionary, transforms it (and any nested dictionaries)
into the provided dct_class
... | a89261253174ce5b75d61343f0b45d3fe65e12f9 | 3,638,478 |
def twoindices_positive_up_to(n, m):
"""
build 2D integer indices up to n (each scanned from 0 to n)
"""
if not isinstance(n, int) or n <= 0:
raise ValueError("%s is not a positive integer" % str(n))
nbpos_n = n + 1
nbpos_m = m + 1
gripos = np.mgrid[: n : nbpos_n * 1j, : m : nbpo... | 63f850703f7598f1a4611c13700aa1921d77dd1a | 3,638,479 |
def ban_user(request, user):
"""Bans a given user."""
user = User.query.filter_by(username=user).first()
if user is None:
raise NotFound()
next = request.next_url or url_for('admin.bans')
if user.is_banned:
request.flash(_(u'The user is already banned.'))
return redirect(next... | dd8c2a43a3843a6055e9e690d8cffee8cfac2b0e | 3,638,481 |
def lastDate():
"""[summary]
lastDate() function: return the total revenue of the nearest day
Returns:
[type]: [description]
"""
lastDate = totalDate().tail(1)
last_date = lastDate.iloc[0]['total'].round(2)
return last_date | 93130bf39dc2a82fa2cae11a6ea11468211f61b6 | 3,638,482 |
import json
def multitask_result(request):
"""多任务结果"""
task_id = request.GET.get('task_id')
task_obj = models.Task.objects.get(id=task_id)
results = list(task_obj.tasklog_set.values('id','status',
'host_user_bind__host__hostname',
'host... | c9c37fe4852a8c04662a5061445c1565400e94a1 | 3,638,484 |
from typing import Dict
def process_xpath_list(node, property_manifest: Dict):
"""
Return a list of values as a result of running a list of XPath
expressions against an input node
:param node: Input node
:param property_manifest: Manifest snippet of the property
:return: List of values
"""... | e52ef3a7ff6b2f74554a69a5fec53125c077f6e5 | 3,638,485 |
def collect_username_and_password(db: Session) -> UserCreate:
"""Collect username and password information and validate"""
username = get_username("Enter your username: ")
password = get_password("Enter your password: ")
verify_pass = get_password("Enter your password again: ")
if password != verif... | be1557a4aa24cfb653c5e03f7f3cb340be1a6c1b | 3,638,486 |
def replace_header(input_df):
"""replace headers of the dataframe with first row of sheet"""
new_header = input_df.iloc[0]
input_df = input_df[1:]
input_df.columns=new_header
return input_df | c8946fc269dd313b80df421af8d0b3fc6c47aed7 | 3,638,487 |
def cartToRadiusSq(cartX, cartY):
"""Convert Cartesian coordinates into their corresponding radius squared."""
return cartX**2 + cartY**2 | 3fb79d2c056f06c2fbf3efc14e08a36421782dbd | 3,638,488 |
def unique_entity_id(entity):
"""
:param entity: django model
:return: unique token combining the model type and id for use in HTML
"""
return "%s-%s" % (type(entity).__name__, entity.id) | c58daf9a115c9840707ff5e807efadad36a86ce8 | 3,638,489 |
def normalize_tuple(value, n, name):
"""Transforms a single int or iterable of ints into an int tuple.
# Arguments
value: The value to validate and convert. Could be an int, or any iterable
of ints.
n: The size of the tuple to be returned.
name: The name of the argument being ... | cf396bac48b720686bb65ae7ab91b2e4cb22ac0e | 3,638,490 |
def load_user(user_id):
"""
@login_manager.user_loader Passes in a user_id to this function and in return the
function queries the database and gets a user's id as a response...
"""
return User.query.get(int(user_id)) | 2c2a2e7f6f9a5bc7392056bfd16402c9d2e96c22 | 3,638,491 |
def replaceall(table, a, b):
"""
Convenience function to replace all instances of `a` with `b` under all
fields. See also :func:`convertall`.
.. versionadded:: 0.5
"""
return convertall(table, {a: b}) | 19d6c0fb60c71994de02deafb5ec9c2995aba622 | 3,638,492 |
def get_job_metadata(ibs, jobid):
"""
Web call that returns the metadata of a job
CommandLine:
# Run Everything together
python -m wbia.web.job_engine --exec-get_job_metadata
# Start job queue in its own process
python -m wbia.web.job_engine job_engine_tester --bg
#... | 24ba96d6a71f105057a9fc9012de9edb187787d5 | 3,638,493 |
import math
def create_learning_rate_scheduler(max_learn_rate, end_learn_rate, warmup_proportion, n_epochs):
"""Learning rate scheduler, that increases linearly within warmup epochs
then exponentially decreases to end_learn_rate.
Args:
max_learn_rate: Float. Maximum learning rate.
end_lea... | 5c5649e429ad5f138894d30064c24bf23e547f85 | 3,638,494 |
def matchyness(section, option):
"""Assign numerical 'matchyness' value between target and value
Parameters:
section -- target value
option -- proposed match
"""
if section != option:
return _hc.NEQ
if isinstance(section, rt.flask_placeholder):
if isinstance(option, rt.flask_placeholder):
return _hc.PP ... | c8e3773a8afe190181fd7552460852a27b2534d3 | 3,638,495 |
def log_sum_exp_elem(*a):
"""
:param a: elements
:return: (a[0].exp() + a[1].exp() + ...).log()
"""
bias = max(a).detach()
ans = bias + sum([(ai-bias).exp() for ai in a]).log()
return ans | a87871a7c8af9d2c6c8db683ba63124319d09a0d | 3,638,496 |
def car_portrayal(agent):
"""Visualises the cars for the Mesa webserver
:return: Dictionary containing the settings of an agent"""
if agent is None:
return
portrayal = {}
# update portrayal characteristics for each CarAgent object
if isinstance(agent, CarAgent):
if agent.is_fro... | 68c0bffb02299f2b03abf6ee2dc590375ad8e2a5 | 3,638,497 |
import re
from typing import OrderedDict
def _load_spc_format_type_a(filepath: str):
"""load A(w,k) in the spc format type a
Args:
filepath (str): output filename
Returns:
np.ndarray, np.ndarray, np.ndarray, np.ndarray, np.ndarray: kcrt, Awk, kdist, energy, kpath
"""
with open(fi... | 0a5c3f316875495e37502dd426e6eee7dd76ee53 | 3,638,498 |
def variable_to_json(var):
"""Converts a Variable object to dict/json struct"""
o = {}
o['x'] = var.x
o['y'] = var.y
o['name'] = var.name
return o | 86497a7915e4825e6e2cbcfb110c9bc4c229efed | 3,638,499 |
import math
def getDewPoint(temp, humidity):
"""
A utility function to get the temperature to which an amount of air must be
cooled in order for water vapor to condense into water. This is only valid
for: 1) temperatures between 0C and 60C, 2) relative humidity between 1%
and 100%, and 3) dew poin... | 0e67eef5a90d9e55f85906d57e6c2eb347044897 | 3,638,502 |
import json
def get_result_handler(rc_value, sa_file=None):
"""Returns dict of result handler config. Backwards compatible for JSON input.
rc_value (str): Result config argument specified.
sa_file (str): SA path argument specified.
"""
try:
result_handler = json.loads(rc_value)
except... | 83c6aa6e0cacdc64422553050072af5d8ea46bf6 | 3,638,503 |
def speedup_experiment_ts(args, model_iter_fn, model, example_inputs):
"""
Measure baseline performance (without using TorchDynamo) of TorchScript and optimize_for_inference.
Writes to ./baseline_ts.csv
"""
return baselines(
[
("eager", model),
("ts", try_script(mode... | 0936d5e24759ae5e04027f8e68e467caa24d5ccb | 3,638,504 |
from typing import Tuple
def my_polyhedron_to_label(
rays: Rays_Base, dists: ArrayLike, points: ArrayLike, shape: Tuple[int, ...]
) -> npt.NDArray[np.int_]:
"""Convenience funtion to pass 1-d arrays to polyhedron_to_label."""
return polyhedron_to_label( # type: ignore [no-any-return]
np.expand_di... | f967a963fcb47c964895da182a48568a2a8a8ee2 | 3,638,505 |
from typing import Optional
def get_incident_comment(incident_comment_id: Optional[str] = None,
incident_id: Optional[str] = None,
operational_insights_resource_provider: Optional[str] = None,
resource_group_name: Optional[str] = None,
... | c0fa6ec1bb7bcccc379455454296bc6a5814946f | 3,638,507 |
def getOrElseUpdate(dictionary, key, opr):
"""If given key is already in the dictionary, returns associated value.
Otherwise compute the value with opr, update the dictionary and return it.
None dictionary are ignored.
>>> d = dict()
>>> getOrElseUpdate(d, 1, lambda _: _ + 1)
2
>>> print(d)
{... | 95454d7ca34d6ae243fda4e70338cf3d7584b827 | 3,638,508 |
from operator import add
from operator import mul
def gs_norm(f, g, q):
"""
Compute the squared Gram-Schmidt norm of the NTRU matrix generated by f, g.
This matrix is [[g, - f], [G, - F]].
This algorithm is equivalent to line 9 of algorithm 5 (NTRUGen).
"""
sqnorm_fg = sqnorm([f, g])
ffgg ... | da30e1bac41cba3a6c051ba0159234aac5e6e3cc | 3,638,509 |
from phaser import substructure
def find_anomalous_scatterers(*args, **kwds):
"""
Wrapper for corresponding method in phaser.substructure, if phaser is
available and configured.
"""
if (not libtbx.env.has_module("phaser")):
if "log" in kwds:
print("Phaser not available", file=kwds["log"])
retu... | 0c88f0df336802fa798ac26966485b28105a6238 | 3,638,510 |
def OpChr(ea, n):
"""
@param ea: linear address
@param n: number of operand
- 0 - the first operand
- 1 - the second, third and all other operands
- -1 - all operands
"""
return idaapi.op_chr(ea, n) | 39c2716ed7344fccd85edda2d27b7a7f305cb14b | 3,638,511 |
def check_access(func):
"""
Check whether user is in policy owners group
"""
def inner(*args, **kwargs):
keycloak = get_keycloak()
if 'policy_id' in kwargs:
current_user = kwargs['user']
group_name = f'policy-{kwargs["policy_id"]}-owners'
group_list = ... | 6655af97f11ae04587904f1aaf2a2225ace5b64d | 3,638,512 |
def score_ranking(score_dict):
"""
用pandas实现分组排序
:param score_dict: dict {'591_sum_test_0601': 13.1, '591_b_tpg7': 13.1, '591_tdw_ltpg6': 14.14}
:return: DataFrame
pd.DataFrame([['591_sum_test_0601', 13.10, 2.0, 0.6667],
['591_b_tpg7', 13.10, 2.0, 0.6667],
['591_tdw_ltpg6', 14.14, 3.0, 1.0]]... | d799576afe382c13124c703351b69b8bcb7393b2 | 3,638,513 |
def dock_widget(widget, label="DockWindow", area="right", floating=False):
"""Dock the given widget properly for both M2016 and 2017+."""
# convert widget to Qt if needed
if not issubclass(widget.__class__, QObject):
widget = utils.to_qwidget(widget)
# make sure our widget has a name
name =... | 80ef6bde493585e0010a497dfb179600aae04e9e | 3,638,514 |
def compute_benjamin_feir_index(bandwidth, steepness, water_depth, peak_wavenumber):
"""Compute Benjamin-Feir index (BFI) from bandwidth and steepness estimates.
Reference:
Serio, Marina, et al. “On the Computation of the Benjamin-Feir Index.”
Nuovo Cimento Della Societa Italiana Di Fisica C, ... | 2b3ef715a85a6dab837a36f86c3eeeaed05f8345 | 3,638,515 |
def plaintext_property_map(name: str) -> Mapper:
"""
Arguments
---------
name : str
Name of the property.
Returns
-------
Mapper
Property map.
See Also
--------
property_map
"""
return property_map(
name,
python_to_api=plaintext_to_noti... | 9b909de0eba2d8f55375896bb2acbbb53c6d759f | 3,638,517 |
def pooling_layer(net_input, ksize=(1, 2, 2, 1), strides=(1, 2, 2, 1)):
"""
TensorFlow pooling layer
:param net_input: Input tensor
:param ksize: kernel size of pooling
:param strides: stride of pooling
:return: Tensor after pooling
"""
return tf.nn.max_pool(net_input, ksize=ksize, strid... | 4de6b7bdb5860cfa235975f799204522e77b9299 | 3,638,518 |
from typing import OrderedDict
def set_standard_attrs(da):
""" Add standard attributed to xarray DataArray"""
da.coords["lat"].attrs = OrderedDict(
[
("standard_name", "latitude"),
("units", "degrees_north"),
("axis", "Y"),
("long_name", "latitude"),
... | 21f83552466127928c9a30e9354e91c3031225aa | 3,638,519 |
def isnotebook():
"""
Utility function to detect if the code being run is within a jupyter
notebook. Useful to change progress indicators for example.
Returns
-------
isnotebook : bool
True if the function is being called inside a notebook, False otherwise.
"""
try:
shel... | 71e0a77c4bbf3afe16723b01ee5a8d08cf3b98a3 | 3,638,521 |
from typing import Optional
from typing import Tuple
from typing import List
from typing import Dict
def get_poagraph(dagmaf: DAGMaf.DAGMaf,
fasta_provider: missings.FastaProvider,
metadata: Optional[msa.MetadataCSV]) -> \
Tuple[List[graph.Node], Dict[msa.SequenceID, graph.Se... | cdc62d444cd22a8ff4c1b99382ffcc35a0ab33a6 | 3,638,522 |
def const_bool(value):
"""Create an expression representing the given boolean value.
If value is not a boolean, it is converted to a boolean. So, for
instance, const_bool(1) is equivalent to const_bool(True).
"""
return ['constant', 'bool', ['{0}'.format(1 if value else 0)]] | d11d01f94b8ad20d393a39a28dbfd18cc8fa217e | 3,638,523 |
import struct
def long_to_bytes(n, blocksize=0):
"""Convert an integer to a byte string.
In Python 3.2+, use the native method instead::
>>> n.to_bytes(blocksize, 'big')
For instance::
>>> n = 80
>>> n.to_bytes(2, 'big')
b'\x00P'
If the optional :data:`blocksize` i... | 1157a466ce9754c12e01f7512e879cc28a2a4b23 | 3,638,524 |
def peek(library, session, address, width):
"""Read an 8, 16 or 32-bit value from the specified address.
:param library: the visa library wrapped by ctypes.
:param session: Unique logical identifier to a session.
:param address: Source address to read the value.
:param width: Number of bits to read... | 6203a516f5a67daa67ec0f37c0e3a8818515f2de | 3,638,526 |
def mtf_from_psf(psf, dx=None):
"""Compute the MTF from a given PSF.
Parameters
----------
psf : `prysm.RichData` or `numpy.ndarray`
object with data property having 2D data containing the psf,
or the array itself
dx : `float`
sample spacing of the data
Returns
----... | fb009d3068c67447d2f10c3448e91b258a0d7ca3 | 3,638,528 |
def check_intersection(vertical_line: Line, other_line: Line) -> bool:
"""
Check for intersection between two line segments.
:param vertical_line: The first line segment. Guaranteed to be vertical.
:param other_line: The second line segment.
:return: Whether or not they intersect.
"""
intersection = get... | 7e9279ea5976b99c9edb36ae5c59bcc69d22aa59 | 3,638,529 |
from krun.scheduler import ManifestManager
from krun.platform import detect_platform
def get_session_info(config):
"""Gets information about the session (for --info)
Overwrites any existing manifest file.
Separated from print_session_info for ease of testing"""
platform = detect_platform(None, conf... | 25729c3838fc7b600600dd74da44a3be9fd7b46d | 3,638,530 |
def rotate(x, y, a):
"""Rotate vector (x, y) by an angle a."""
return x * np.cos(a) + y * np.sin(a), -x * np.sin(a) + y * np.cos(a) | 2858539f3de5c15072657af5f39231f8e7867b6b | 3,638,531 |
def filt_all(list_, func):
"""Like filter but reverse arguments and returns list"""
return [i for i in list_ if func(i)] | 72010b483cab3ae95d49b55ca6a70b0838b0a34d | 3,638,532 |
def auth_user_logout(payload,
override_authdb_path=None,
raiseonfail=False,
config=None):
"""Logs out a user.
Deletes the session token from the session store. On the next request
(redirect from POST /auth/logout to GET /), the frontend will is... | 1f468a53f82a58f8c5c3f5397d6f026276a93f05 | 3,638,533 |
def rx_observer(on_next: NextHandler, on_error: ErrorHandler = default_error, on_completed: CompleteHandler = default_on_completed) -> Observer:
"""Return an observer.
The underlying implementation use an named tuple.
Args:
on_next (NextHandler): on_next handler which process items
on_erro... | 2ebfd3c6b4e5ed854fdc89e76ac006fddd20ad0b | 3,638,534 |
def _rav_setval_ ( self , value ) :
"""Assign the valeu for the variable
>>> var = ...
>>> var.value = 10
"""
value = float ( value )
self.setVal ( value )
return self.getVal() | 80ad7ddec68d5c97f72ed63dd6ba4a1101de99cb | 3,638,535 |
import scipy
def import_matrix_as_anndata(matrix_path, barcodes_path, genes_path):
"""Import a matrix as an Anndata object.
:param matrix_path: path to the matrix ec file
:type matrix_path: str
:param barcodes_path: path to the barcodes txt file
:type barcodes_path: str
:param genes_path: pat... | 83f5ccdaa945f26451ab2834c832e0e1ea58ce89 | 3,638,536 |
import torch
import tqdm
def get_representations(dataset, pretrained_model, alphabet, batch_size=128):
"""Returns: N x 1280 numpy array"""
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
pretrained_model = pretrained_model.to(device)
dataloader = DataLoader(
dataset, bat... | 7a199156810b787ae7fb8ea059ebe69b6de70250 | 3,638,537 |
def rem_hap_cands():
"""json endpoint to set a sample or set of
sample's haplotype candidate designation to false"""
form = flask.request.form
samples = form['samples']
return mds.remove_hap_cands(samples) | ca22c2af4b6079f3b03accb3b414d553da75e1e3 | 3,638,538 |
def UndistortImage(image,image_size,\
image_rotation=None,image_center=None,\
out_xs=None,out_ys=None,\
direction='fwd',regenerate_grids=True,\
**kwargs):
"""Remember the recipe for fixin gwyddion image orientation: `image0=image0.T[:,:... | 12cc1e1e428b8a860b0b29a6b81169cb6c1dc73d | 3,638,541 |
def quartic_oscillator(grids, k=1.):
"""Potential of quantum quartic oscillator.
Args:
grids: numpy array of grid points for evaluating 1d potential.
(num_grids,)
k: strength constant for potential.
Returns:
vp: Potential on grid.
(num_grid,)
"""
vp = 0.5 * k * gr... | c4a386816cd85e24080d62365d2bcd25b6735d5f | 3,638,542 |
def compute_row_similarities(A):
"""
Compute pairwise similarities between the rows of a binary sparse matrix.
Parameters
----------
A: scipy csr_matrix, shape (rows, cols)
Binary matrix.
Returns
-------
sim: numpy array, shape (rows, rows)
Pairwise column similarities.... | 96ab44ec15f94bf666da248100a98f282119caf1 | 3,638,543 |
def sha9(R, S):
"""Shape functions for a 4-noded quad element
Parameters
----------
x : float
x coordinate for a point within the element.
y : float
y coordinate for a point within the element.
Returns
-------
N : Numpy array
Array of interpolation functions.
Exa... | ba34cde6b5673853d34b9e074e2fbc05dc845aa5 | 3,638,544 |
def padding(seq, size, mode):
"""
Parameters
----------
seq: np.array
The sequence to be padded.
mode: str
Select padding mode among {"zero", "repeat"}.
Returns
-------
seq: np.ndarray
"""
if mode == "zero":
seq = np.array(trimmer(seq, size, fille... | 3a0a070f784a355ead8439ff63f09918fa401014 | 3,638,545 |
def get_dense_span_ends_from_starts(dense_span_starts,
dense_span_ends):
"""For every mention start positions finds the corresponding end position."""
seq_len = tf.shape(dense_span_starts)[0]
start_pos = tf.cast(tf.where(tf.equal(dense_span_starts, 1)), tf.int32)
end_pos = tf... | d825ed109b6055ca84adf46f6e5fd91cb5dd513a | 3,638,546 |
def bb_to_plt_plot(x, y, w, h):
""" Converts a bounding box to parameters
for a plt.plot([..], [..])
for actual plotting with pyplot
"""
X = [x, x, x+w, x+w, x]
Y = [y, y+h, y+h, y, y]
return X, Y | 10ea3d381969b7d30defdfdbbac0a8d58d06d4d4 | 3,638,547 |
def handler404(request, *args):
"""
Renders 404 page.
:param request: the request object used
:type request: HttpRequest
"""
return render(request, '404.html', status=404) | 2ae6e036bb56b46ee16a4c0bec4182ba999f14ed | 3,638,548 |
def merge_dimensions(z, axis, sizes):
"""Merge dimensions of a tensor into one dimension. This operation is the opposite
of :func:`split_dimension`.
Args:
z (tensor): Tensor to merge.
axis (int): Axis to merge into.
sizes (iterable[int]): Sizes of dimensions to merge.
Returns:
... | 5ef62cd90ebf5bd9276f334a65a7a9075f5d3710 | 3,638,549 |
import collections
import re
def get_assignment_map_replaced(init_ckpt,
name_replacement_dict={},
list_vars=None):
""" name_replacement_dict = { old_name_str_chunk: new_name_str_chunk }
"""
if list_vars is None:
list_vars = tf.global_... | fd7df6630f84bde9caf747540c05729b8898ffa0 | 3,638,550 |
def RULE110():
"""RULE 110 celular automata node.
.. code::
000 : 0
001 : 1
010 : 1
011 : 1
100 : 0
101 : 1
110 : 1
111 : 0
"""
return BooleanNode.from_output_list(outputs=[0,1,1,1,0,1,1,0], name="RULE 110") | 3c79a7b6c25f031fdeac4a86f2afc770ad71ea23 | 3,638,551 |
def search_cut(sentence):
"""
HMM的切割方式
:param sentence:
:return:
"""
return jieba.lcut_for_search(sentence) | 7ee0f7eb1a16cd24920b98e38387b2c9b576990f | 3,638,552 |
from typing import Counter
def count_items(column_list:list):
"""
Contar os tipos (valores) e a quantidade de items de uma lista informada
args:
column_list (list): Lista de dados de diferentes tipos de valores
return: Retorna dois valores, uma lista de tipos (list) e... | 06cf25aed4d0de17fa8fb11303c9284355669cf5 | 3,638,553 |
import cloudpickle
def py_call(obj, inputs=(), direct_args=()):
"""Create a task that calls Python code
Example:
>>> def hello(x):
return b"Hello " + x.read()
>>> a = tasks.const("Loom")
>>> b = tasks.py_call((a,), hello)
>>> client.submit(b)
b'Hello Loom'
"""
task = ... | f89a5876fcf9b4c192f2b7c6d1362bf5a97e399c | 3,638,554 |
def to_graph(grid):
"""
Build adjacency list representation of graph
Land cells in grid are connected if they are vertically or horizontally adjacent
"""
adj_list = {}
n_rows = len(grid)
n_cols = len(grid[0])
land_val = "1"
for i in range(n_rows):
for j in range(n_cols):
... | ebdd0406b123a636a9d380391ef4c13220e2dabd | 3,638,555 |
def validate_doc(doc):
"""
Check to see if the given document is a valid dictionary, that is, that it
contains a single definition list.
"""
return len(doc.content) == 1 and \
isinstance(doc.content[0], pf.DefinitionList) | c60799ebbdaa7ec2e3a7e6607853ff021a40ed17 | 3,638,556 |
def V_bandpass(V, R_S, C, L, R_L, f):
"""
filter output voltage
input voltage minus the current times the source impedance
"""
# current in circuit
I = V/(R_S + Z_bandpass(C, L, R_L, f))
# voltage across circuit
V_out = V - I*R_S
return V_out | c21c54e7065a32531dca417eb7e50ea63db820d8 | 3,638,559 |
from admiral.celery import celery
def celery():
"""Celery app test fixture."""
return celery | 69f672e1c6a568e14a4ad9f5df723b454a346b03 | 3,638,561 |
def perm_cache(func):
"""
根据用户+请求参数，把权限验证结果结果进行缓存
"""
def _deco(self, request, view):
# 只对查询（GET方法）进行权限缓存
if request.method != "GET":
return func(self, request, view)
user = request.user.username
kwargs = "_".join("{}:{}".format(_k, _w) for _k, _w in list(vi... | 4ca53057b12efb15dddb422b3aaaddd11898f4bd | 3,638,562 |
def ast_walker(handler):
"""
A generic AST walker decorator.
Decorates either a function or a class (if dispatching based on node type is required).
``handler`` will be wrapped in a :py:class:`~peval.Dispatcher` instance;
see :py:class:`~peval.Dispatcher` for the details of the required class struct... | 978e6718d81663914017af89cf41101ca68dd2bb | 3,638,563 |
def html_escape(text):
"""Produce entities within text."""
L=[]
for c in text:
L.append(html_escape_table.get(c,c))
return "".join(L) | de73c127de8b6338c5db5c9ba7d1f5ebbd6d23a9 | 3,638,564 |
def qs_without_parameter(arg1, arg2):
"""
Removes an argument from the get URL.
Use:
{{ request|url_without_parameter:'page' }}
Args:
arg1: request
arg2: parameter to remove
"""
parameters = {}
for key, value in arg1.items():
if parameters.get(key, None) is ... | 649931de5490621c92513877b21cb8cfce8d66ff | 3,638,565 |
def find_power_graph(I, J, w_intersect=10, w_difference=1):
"""takes a graph with edges I,J, and returns a power
graph with routing edges Ir,Jr and power edges Ip,Jp.
Note that this treats the graph as undirected, and will
internally convert edges to be undirected if not already."""
n = int(max(max(... | 9e682eebd9664863d80689f0aa718f30e3ad611a | 3,638,566 |
import string
def getcomments(pyObject):
"""Get lines of comments immediately preceding an object's source code.
Returns None when source can't be found.
"""
try:
lines, lnum = findsource(pyObject)
except (IOError, TypeError):
return None
if ismodule(pyObject):
# Look... | f58421f176b42ecb2e1e883f48deb31025b13559 | 3,638,567 |
import time
import requests
import io
def crack_captcha(headers):
"""
破解验证码,完整的演示流程
:return:
"""
currentTime = str(int(time.time())*1000)
# 向指定的url请求验证码图片
rand_captcha_url = 'http://59.49.77.231:81/getcode.asp?t=' + currentTime
res = requests.get(rand_captcha_url, stream=True,headers=h... | 538843289a64dde1229f7df0a260632fbbd557b6 | 3,638,568 |
from . import sill
from clawpack.pyclaw.util import check_diff
import numpy as np
from clawpack.pyclaw.util import gen_variants
from itertools import chain
def test_2d_sill():
"""test_2d_sill
Tests against expected classic solution of shallow water equations over
a sill."""
def verify_expected(expe... | 5d37c3ad21d842c3f03d1b464609f94ee86e1496 | 3,638,569 |
def draw_box(
canvas,
layout,
box_width=None,
box_alpha=0,
color_map=None,
show_element_id=False,
show_element_type=False,
id_font_size=None,
id_font_path=None,
id_text_color=None,
id_text_background_color=None,
id_text_background_alpha=1,
):
"""Draw the layout region... | 9d8ca19a35e91c6e8670aed05c2e61b2c89958c5 | 3,638,570 |
def login(request):
"""Home view, displays login mechanism"""
return render(request, 'duck/login.html') | 5d4474d4ce7bb8f7327e1a005fe9e485d8784ec7 | 3,638,571 |
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