content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def filter_endpoints(end_points):
"""
Keep only conv layers and reshape into
[Nl x Ml] matrixes
"""
d = {}
for k, v in end_points.items():
if 'conv' in k:
el = tf.squeeze(v)
n_f = el.shape[-1]
el = tf.reshape(el, (-1, n_f))
el = tf.transp... | 1e0088d489dfebfb2d0b60f6324954017d1a2771 | 3,598,246 |
def validate(X, Y):
"""
校验X和Y的格式是否正常，如果不正常，返回False；否则返回True
:param X:
:param Y:
:return:
"""
m1, n1 = np.shape(X)
m2, n2 = np.shape(Y)
if m1 != m2:
return False
else:
if n2 != 1:
return False
else:
return True | 44de6cb937b6e0db810fb569b654b91dcea7a361 | 3,598,248 |
def quote_aware_split(string, delim=',', quote='"'):
""" Split outside of quotes (i.e. ignore delimiters within quotes."""
out = []
s = ''
open_quote=False
for c in string:
if c == quote:
open_quote = not open_quote
if c == delim and not open_quote:
out += [s... | 0ef5f7040eee2a041fa1b6e6d8bf3a773a80f5f9 | 3,598,249 |
def NormalizarSerie(SR):
"""
Descripción:
-----------
Normaliza una serie basandose en maximo y minimo
Haciendo que la misma se encuentre entre 0 y 1
Un ejemplo de uso seria normalizar el DPO y operar
en 0.2 para la compra y 0.5 para la venta (estrategia comprado)
Parametros
... | 6e7a9f0b2dd9be0fd82712ab5c9176e245e34549 | 3,598,250 |
def is_const(array, *, is_const=_speedups and _speedups.is_const):
"""Returns if the given array is constant"""
if is_const:
res = is_const(array)
if res is not None:
return res
if array.size == 0:
return True
else:
return (array == array[0]).all() | d5a5ceb519b3f0a7433ea6ff7860a9650a4b6d8f | 3,598,251 |
def entropy(x):
"""
calculate shanno ent of x
"""
x_value_list = set([x[i] for i in range(x.shape[0])])
ent = 0.0
for x_value in x_value_list:
p = float(x[x == x_value].shape[0]) / x.shape[0]
logp = np.log2(p)
ent -= p * logp
return ent | 86e3e999501a38e3143c244c736a51855dfcc431 | 3,598,252 |
def MinMaxScaler(x, min_value=0, max_value=1):
"""
:brief: Normalizes data using the min max scaling.
:param x: are the data
:param min_value: is the minimum value
:param max_value: is the maximum value
:return: scaled data
"""
data_size = len(x)
dimensions = len(x[0]... | 88e11f79cb84800cef56950f8e120eaa6de6ee3f | 3,598,253 |
def _define_rt_plan(ds: Dataset) -> Dataset:
"""Return an RT PLAN directory record from `ds`."""
_check_dataset(ds, ["InstanceNumber", "RTPlanLabel"])
record = Dataset()
record.InstanceNumber = ds.InstanceNumber
record.RTPlanLabel = ds.RTPlanLabel
record.RTPlanDate = ds.get("RTPlanDate")
re... | aad48d9b4317151fd973b41f0a2331377d42adaa | 3,598,254 |
def NcbiTaxonomyFromFiles(nodes_file, names_file, strict=False):
"""Returns new NcbiTaxonomy fron nodes and names files."""
taxa = NcbiTaxonLookup(NcbiTaxonParser(nodes_file))
names = NcbiNameLookup(NcbiNameParser(names_file))
return NcbiTaxonomy(taxa, names, strict) | a4ff1dc311b9c3aa0505304585bdc2e3354da591 | 3,598,256 |
def minutes_for_days_in_range(start, end, days_in_range_hook,
minutes_for_day_hook):
"""
Get all execution minutes for the days between start and end,
inclusive.
"""
start_date = normalize_date(start)
end_date = normalize_date(end)
all_minutes = []
for day ... | 514c7a1dfc28579cbb0c4203599eb80d7480df61 | 3,598,257 |
def new_action(parent, text, slot=None, shortcut=None, icon=None, tip=None, enabled=True):
"""actionの設定と取得"""
# アクション取得
a = QAction(text, parent)
# icon設定 iconsフォルダから取得
if icon is not None:
a.setIcon(QIcon('icons/'+icon))
# ショートカット作成
if shortcut is not None:
if isinstance(sho... | a02051154fec7d69ddca8a01073e9367e3e695ba | 3,598,258 |
def _millis(when):
"""Convert a zone-aware datetime to integer milliseconds.
:type when: :class:`datetime.datetime`
:param when: the datetime to convert
:rtype: int
:returns: milliseconds since epoch for ``when``
"""
micros = _microseconds_from_datetime(when)
return micros // 1000 | 4eed9d17bf127d9b0794a539e58f4118dca415bd | 3,598,259 |
import re
import code
def clean_python_code(python_code, isort=True, black=True, autoflake=True):
"""Clean Python code."""
# Temporarily comment out IPython %magic to avoid Black errors.
python_code = re.sub("^%", "##%##", python_code, flags=re.M)
# Run source code string through autoflake, isort, an... | 5c9e875c5de8b688331467392c8011633d69adee | 3,598,260 |
from re import T
def check_opt_isinstance(item: T, classinfo: _ClassInfo) -> T:
"""
Checks something is ether None or an instance of a given class.
Raises a TypeError otherwise
"""
if item and not isinstance(item, classinfo):
raise TypeError(
"Expected instance of type {!r} bu... | d6d4a439ded2aedd3a243e48b8c2e101be18f5bd | 3,598,261 |
def getcwd():
"""Return a string representing the current working directory.
:rtype: string
"""
return '' | 31ba3c781dad707ef5feaa15a841d8d528ded3e3 | 3,598,262 |
def getRenamingCommands():
"""
Get all available L{renamer.irenamer.IRenamingCommand}s.
"""
return getPlugins(IRenamingCommand, plugins) | 60b9a11d04ccab30d2dbadeb6103932115950b64 | 3,598,263 |
def _tess_ffi_file(file_name):
""" TESS FFI File """
# tess2018229142941-s0001-4-3-0120-s_ffic.fits
# yyyyddd sssss ccc
# s0001/2018/229/4-3
# 18-23 4-8 8-11 24-27
sector = file_name[18:23]
year = file_name[4:8]
day_number = file_name[8:11]
camera_chip = file_name[24:27]
... | 8a0381c1c6566ecd518e8e7c0033453a1a9e66fe | 3,598,264 |
def pairwise_distance(feature, squared=False):
"""Computes the pairwise distance matrix with numerical stability.
output[i, j] = || feature[i, :] - feature[j, :] ||_2
Args:
feature: 2-D Tensor of size [number of data, feature dimension].
squared: Boolean, whether or not to square the pairwise ... | eb53830e8e11309c17ea2b3e5e0bae5d87aeafee | 3,598,266 |
def path_specific_constraints(prefix, constraints, var_mapping):
"""Creates duplicate constraints with all variables replaced with path
specific copies"""
new_constraints = []
for cs in constraints:
new_cs = [path_specific_expr(prefix, c, var_mapping) for c in cs]
new_constraints.append... | 0a0344f7e811dd1bdfa04fe251359bea23b74472 | 3,598,267 |
import torch
def get_style_grams(style_im, cfg):
"""
Computes the style grams for the vgg activations of the given style image.
Args:
--style_im: <tensor> The pre-processed style image. Should have shape
(ch, h, w)
--cfg: <dict> The training config dictionary
Returns:
<list> The ... | c2f9e30cd42d99b548875860fb6ff6c3373c81bc | 3,598,268 |
import torch
def fft_shift(input: torch.Tensor) -> torch.Tensor:
"""
PyTorch version of np.fftshift
Args
- input: (Bx)CxHxWx2
Return
- ret: (Bx)CxHxWx2
"""
dims = [i for i in range(1 if input.dim() == 4 else 2, input.dim() - 1)] # H, W
shift = [input.size(dim) // 2 for dim in dim... | 9a08c3e33516378b80a7a53cf17915d9baa5d290 | 3,598,269 |
from typing import Callable
def fcn_from_str(name: str) -> Callable:
"""
Get the matching function. This method is a workaround / utility tool to intended to work with optuna. Since we can
not pass functions directly, we pass a sting.
:param name: name of the function
:return: the function
""... | abcf93d1c13e484d375d55550e3e0e599cdbdeba | 3,598,270 |
from typing import Mapping
from typing import Any
import json
def get_config(config_path: str = "secrets/config_oauth.json") -> Mapping[str, Any]:
"""
Get the config from /test_input
"""
with open(config_path, "r") as f:
return json.loads(f.read()) | 9ad1726bc5b1017f47872ce422d1c7a6fbf5d59c | 3,598,271 |
def flop(x):
"""
Flops each 1/2 byte with the adjacent 1/2 byte.
Flop is its own inverse.
"""
left = x & FLOP_MASK
right = x & ~FLOP_MASK
return ((right << 4) | (left >> 4)) & ID_MASK | 8b0208c11cbab8a92671de2ccdc94f7c030bce9a | 3,598,272 |
def get_view_proxy_registration_name(proxy):
"""Assuming the given proxy is registered in the group 'views',
lookup the proxy's registration name with the servermanager"""
return servermanager.ProxyManager().GetProxyName("views", proxy) | a85cd2dfbc83e2d94a14413a9174ce0f288e7529 | 3,598,273 |
def LMpM_total_size(ell_min, ell_max):
"""Total array size of Wigner D matrix
Assuming an array (e.g., Wigner D matrices) in the order
[[ell,mp,m] for ell in range(ell_min, ell_max+1)
for mp in range(-ell,ell+1)
for m in range(-ell,ell+1)]
this function returns the tot... | 7a6175640236ec3bc905d3b458f99eedbc792e09 | 3,598,274 |
def get_signature_locals(f, loc):
"""Filters locals to only include keys in original method signature"""
return {k: v for k, v in loc.items() if k in signature(f).parameters} | d157623fc0af02e2de6518697b2f2c8a59a72f96 | 3,598,275 |
def filter_factory(global_conf, **local_conf):
"""
paste.deploy app factory for creating WSGI proxy apps.
"""
conf = global_conf.copy()
conf.update(local_conf)
if config_true_value(conf.get('read_only')):
register_swift_info('read_only')
def read_only_filter(app):
return Re... | d6ea8e82d61b38f37f8400f0534a063452bc28fc | 3,598,276 |
def map_obs_subfields(epochs_selec, obs_fieldID, obs_subfield, mapdic):
"""Return boolean array corresponding to observed subfields.
Parameters
----------
epochs_selec : numpy.array(bool)
Actual observations selection.
obs_fieldID : bool
Id of pre selected observed fields.
obs_s... | a27b1c37ec827b4a2f1dee0a6cc930c253676739 | 3,598,277 |
def value_at_depht_in_BT(tree, depth):
"""
O(n) time
O(n) space
"""
if depth == 0:
return [tree.value]
if tree.left and tree.right:
return []+value_at_depht_in_BT(tree.left, depth-1)+value_at_depht_in_BT(tree.right, depth-1)
if tree.left:
return []+value_at_depht_in_BT(tree.left, depth-1)
if tree.right:... | dc4bcc8398fe1357d0fb8a903b26828cd20c093d | 3,598,278 |
def load_base_library():
"""Load style library defined in this package."""
library = read_style_directory(BASE_LIBRARY_PATH)
return library | b027dfcbc8a622a37689470ecb3a1d3a83edffd7 | 3,598,279 |
def hdbx_keymap():
"""
HDBX配列 デフォルトレイヤーをこの配列にしたい場合は、AdjustレイヤーでK (Lower + Raise + K)
,----------------------------------. ,----------------------------------.
| Q | W | E | , | . | | Y | D | P | F | : |
|------+------+------+------+------| ... | 3cd38fc34ffc4a76398d04163478a8db4791f873 | 3,598,280 |
def get_fcurve_data_path_property(fcurve):
""" Gets fcurve's data path property
Example fcurve's data_path: 'sequence_editor.sequences_all["Transform"].scale_start_x'
For that example path this function will return 'scale_start_x'
:param fcurve: Fcurve instance to get data path from
:return: The la... | 0a7ce5fecdaa5cb1fe0024a18f6b6f057b5fe6cb | 3,598,281 |
import torch
import tqdm
def train(config_path, model_path, model_type, src_filename, trg_filename):
"""
flags:
saveto: str
reload: store_true
config_path: str
pretrain_path: str, default=""
model_name: str
log_path: str
"""
# ==========================... | c1d085c9cd458543c6978bb919c806ccc816560e | 3,598,282 |
import ctypes
import numpy
def ctypes2numpy(cptr, length, dtype):
"""convert a ctypes pointer array to numpy array """
assert isinstance(cptr, ctypes.POINTER(ctypes.c_float))
res = numpy.zeros(length, dtype=dtype)
assert ctypes.memmove(res.ctypes.data, cptr, length * res.strides[0])
return res | d4f85de74946e5477f2f29bfa5cce119d3fe66a3 | 3,598,284 |
def align(offset, alignment):
"""
Return the offset aligned to the nearest greater given alignment
Arguments:
- `offset`: An integer
- `alignment`: An integer
"""
if offset % alignment == 0:
return offset
return offset + (alignment - (offset % alignment)) | 1f9d8fd4d4ac7798e14ee92d83510bb4b0ba09aa | 3,598,285 |
def update_path(alpha, beta, gradE, delta, T=100, k=5):
"""
Update the path along the direction -gradE
:param alpha: numpy ndarray of shape (2,M) of M samples
:param beta: numpy ndarray of shape (2,M) of M samples
:param gradE: numpy ndarray of shape (2,M) of M samples
:param delta: gradient pa... | b570d447dbc1eabc5b58e3be8fe68577b0c572fb | 3,598,286 |
def convert_str_length_to_int(length):
""" Convert a position in char to integer """
if type(length) is int:
return length
if length in "0123456789":
return int(length)
elif length <= "Z" and length >= "A":
return ord(length) - ord("A") + 10
elif length == "z":
return... | d89a56bbf542f8c76cee219b1759a054c6894119 | 3,598,287 |
from typing import Tuple
def angles(a: float, e: float, r: float) -> Tuple[float, float]:
"""
theta = arccos((a * (1 - e * e) - r) / (e * r))
:param a: semi-major axis
:type a: float
:param e: eccentricity
:type e: float
:param r: radius vector
:type r: float
:return: the two thet... | 8a6796dbcef6f9044d4f51811462087ad0b59e76 | 3,598,288 |
def parse_property_string(prop_str):
"""
Generate valid property string for extended xyz files.
(ref. https://libatoms.github.io/QUIP/io.html#extendedxyz)
Args:
prop_str (str): Valid property string, or appendix of property string
Returns:
valid property string
"""
if prop_... | 24a865dcf2cba5b5f840e3e682fd58486b658355 | 3,598,289 |
def getPacketKey(opCode):
"""
Gets the packet key for a given instruction
Input:
- opCode: The opcode of instruction for which the packet key has to be generated
Output:
- The packet keys initialized in packetDict function for the given opcode
"""
if opCode in ["00000", "00001", "0001... | c7730a444a4e8dacc20ae83038ddfc04ca5ba721 | 3,598,290 |
import torch
def stack_sample(sample):
"""Stack a sample from multiple sensors"""
# If there is only one sensor don't do anything
if len(sample) == 1:
return sample[0]
# Otherwise, stack sample
stacked_sample = {}
for key in sample[0]:
# Global keys (do not stack)
if k... | 1b17f43b048a86759409ee5b6cdbc506c36a588b | 3,598,291 |
def map_to_legacy_object_map(m):
"""Converts a Soy map to a Soy legacy_object_map.
legacy_object_maps must have string keys, but maps do not have this
restriction.
Args:
m: Map to convert.
Returns:
An equivalent legacy_object_map, with keys coerced to strings.
"""
return {str(key): m[key] for k... | 17423488a85011c7be5429af58a5baf26ab8e30a | 3,598,292 |
def getLastRecords(desde, hasta):
"""
Esta tabla retorna una lista de tuplas de la forma (id_segment, data, timestamp)
con los ultimos registros agregados a la tabla "historical"
"""
# realizando una consulta
# desde = datetime.datetime.strptime(desde, '%Y-%m-%dT%H:%M:%S-03:00')
# hasta = da... | eaa41ea6ba981701dfe21c3108723b2240e940bf | 3,598,293 |
def Terrahawk(): # A.K.A. the Dillon Mayhew Matroid
"""
Return the Terrahawk matroid.
The Terrahawk is a binary matroid that is a sporadic exception in a chain
theorem for internally 4-connected binary matroids. See [CMO2011]_.
EXAMPLES::
sage: M = matroids.named_matroids.Terrahawk()
... | c48dfda7e7ac4132aa274f2e83f61a9ccf83baca | 3,598,294 |
def session_mm_secondary_master_tcp_master_publish_pull():
"""
Returns an unused localhost port
"""
return get_unused_localhost_port() | a01d291f9ba18cd87e7d2a6ffc292bc004386b16 | 3,598,295 |
def MikotaPair(n):
"""Build a pair of full diagonal matrices for the generalized eigenvalue
problem. The Mikota pair acts as a nice test since the eigenvalues are the
squares of the integers n, n=1,2,...
"""
x = np.arange(1, n+1)
B = diag(1./x)
y = np.arange(n-1, 0, -1)
z = np.arange(2*n... | 3091f54c44a910a787748d204bb692d425f62a6c | 3,598,296 |
def as_composite(identifier: str) -> str:
"""
Translate the identifier of a mapry composite to a composite name in C++.
:param identifier: mapry identifier of a composite
:return: translated to a C++ identifier of a composite
>>> as_composite(identifier='Some_URL_class')
'SomeURLClass'
""... | 9a702dbd2f9b4dfb65102a18f4924be432a85282 | 3,598,297 |
def create_rsa_public_and_private_from_pem(pem, passphrase=None):
"""
<Purpose>
Generate public and private RSA keys from an optionally encrypted PEM. The
public and private keys returned conform to
'securesystemslib.formats.PEMRSA_SCHEMA' and have the form:
'-----BEGIN RSA PUBLIC KEY----- ... ---... | 1c11fa3d8e761992fdc4212e90f373465a103907 | 3,598,298 |
def notas(*n, sit=False):
"""
-> Função para avaliar a situação de varios alunos
:param n: uma ou mais notas dos aluno
:param sit: valor opcional, indica se deve ou não colocar a sitação
:return: dicionário com várias informaçoes sobre a sitação da turma
"""
bib = dict()
soma = 0
bib... | d10baf761af8ece8eaa1a7e2afce2299643e474f | 3,598,300 |
def get_user_from_token(token):
"""
Return user from authorization token.
Args:
token: authorization token instance.
Returns:
user instance or AnonymousUser.
"""
if token:
backend_path = token.backend
if backend_path in django_settings.AUTHENTICATION_BACKENDS and... | c6aeb7ef73d45eec447fa28eeb1e47e249243e30 | 3,598,302 |
from typing import List
def _format_plugin_names_and_versions(plugininfo) -> List[str]:
"""Format name and version of loaded plugins."""
values: List[str] = []
for _, dist in plugininfo:
# Gets us name and version!
name = f"{dist.project_name}-{dist.version}"
# Questionable conveni... | 2313f2f60e71be2209ebb201297d44e8dcad513a | 3,598,303 |
def ix_neighbors(site, dims=None, radius=1):
""" use np.ix_ instead of np.meshgrid -- requires less memory """
index = np.unravel_index(site, dims=dims)
id_range = [np.arange(idx-radius, idx+radius+1)
for idx in index]
neighs = np.ravel_multi_index(np.ix_(*id_range),
... | 896c126d7afbf36c76d81ad0b4c614ef6e262dbc | 3,598,304 |
from typing import Dict
from typing import Callable
from typing import Set
def state_enumeration(init_dist: Dict[State, int], rule: Callable[[State, State], Output]) -> Set[State]:
"""Finds all reachable states by breadth-first search.
Args:
init_dist: dictionary mapping states to counts
... | 39c73e4536d6e614c8b7d73d527ac2bcf7d36127 | 3,598,305 |
def make_datagrid(x):
"""returns a MyDataGrid object"""
return MyDataGrid(x) | e6292d5c7f564a12acc7c071ea22b0685686b1d9 | 3,598,306 |
def dist_string(dist):
"""Formats a distance (a float) as a colorized similarity percentage
string.
"""
out = u'%.1f%%' % ((1 - dist) * 100)
if dist <= config['match']['strong_rec_thresh'].as_number():
out = ui.colorize('text_success', out)
elif dist <= config['match']['medium_rec_thresh... | 1a316130d3fe71e41fae077b9ae06014e96aeb9b | 3,598,307 |
def do_category_choice(available_categories, dice):
"""
Ask the player to interactively choose a scoring category, on the command-line.
:param available_categories: the categories available for the player to choose from
:param dice: the dice the player previously rolled
:return: the category chosen... | f401a772636f0b5699e5b076b689cc46a4f9cc53 | 3,598,308 |
def star_sub_sections(body:str):
"""
Change
\subsection
\subsubsection
To:
\subsection*
\subsubsection*
"""
body = body.replace(r'\subsection',r'\subsection*')
body = body.replace(r'\subsubsection',r'\subsubsection*')
return body | 06583d16c76393edb614955c4e3786b292c5fa51 | 3,598,311 |
def clean_temerature_usa_data(temperature_usa_df: psd.DataFrame, spark: pss.SparkSession) -> psd.DataFrame:
"""[This cleans temperature data in USA. It casts date, city, average recorded temperature, and port entry.]
Args:
temperature_usa_df (psd.DataFrame): [spark dataframe that describes average temp... | 4d3880609cc1465db108f451ea132814aa160536 | 3,598,313 |
def rjd_to_mjd(rjd):
"""
RJD (Reduced Julian Date)
days elapsed since 1858-11-16T12Z (JD 2400000.0)
MJD (Modified Julian Date)
days elapsed since 1858-11-17T00Z (JD 2400000.5)
This function transforms RJD in MJD
"""
return rjd - 0.5 | 2b1f4d830670f754fbbc2259face4d261877d335 | 3,598,314 |
from typing import List
from typing import Dict
from typing import Optional
from typing import Tuple
from typing import Iterable
async def apply(
last_message: Message, recent_messages: List[Message], config: Dict[str, int]
) -> Optional[Tuple[str, Iterable[Member], Iterable[Message]]]:
"""Detects total attac... | 3f5d2f9022ae2eab8ebcc4215248749eafe686ab | 3,598,315 |
def combine_last_two_dimensions(x):
"""Reshape x so that the last two dimension become one.
Args:
x: a Tensor with shape [..., a, b]
Returns:
a Tensor with shape [..., ab]
"""
old_shape = x.get_shape().dims
a, b = old_shape[-2:]
new_shape = old_shape[:-2] + [a * b if a and b else Non... | c059f577848f0d83c7c7b8536678151c4cbf1029 | 3,598,316 |
def discretizer(df_list, names, config):
"""
concat the df_list as one pd.DataFrame then using sklean.KBinsDiscretizer depart it,
Parameters
----------
df_list: object
a collection of one or more pd.DataFrame. they must have one column named 'id' for indexing.
names : list
a lis... | 946549faafaa79cf5a2e3c50244be7381dcea64b | 3,598,317 |
import torch
def MixtureDensityLSTMLoss(trueLatents, predMu, predSigma, predMDLogProbs):
"""Computes the loss for a MixtureDensityLSTM model
Loss per sample is defined as the negative of the log probability, which is then reduced across the batch
Args:
trueLatents: Actual latents observed (th... | 52e680ce0dca62952ea1e4c870463b9893e2aa72 | 3,598,318 |
def post_key(name="default"):
"""It builds a new Key object from posts."""
return db.Key.from_path("posts", name) | 09d080f5ca2810b45bb408428240b89e98c8a379 | 3,598,319 |
def arg_xor_dict(args_array, opt_xor_dict):
"""Function: arg_xor_dict
Description: Does a Xor check between a key in opt_xor_dict and its values
using args_array for the check. Therefore, the key can be in
args_array or one or more of its values can be in arg_array, but both
can not... | 08001050d5e542bcd09343920c49e8bb59c9c7a6 | 3,598,321 |
from typing import List
def process_ancrubadan_data(ac_file: str) -> List[str]:
"""Processes An Crubadan file into list of strings for normalization.
An Crubadan data format is the word, followed by a space, followed by
the total count of that word in the corpora that were crawled. For example:
... | 84714cabc078f08cc95c4ee255431e506df74c5c | 3,598,322 |
def cbin(n):
"""Return `n` as a clean 32-bit binary number, without a leading '0b'."""
if n < 0:
n = UMAX + n
return '{0:0>32}'.format(bin(n)[2:]) | d54e270fa3844c84096c7fd40ce832d97bd96646 | 3,598,323 |
def import_module_by_path(mod_path, mod_name, sys_add=True, sys_use=True):
"""Import a module by module file path.
@param mod_path: module file path.
@param mod_name: module name to be imported as.
@param sys_use: see func |import_module_by_code|'s same name arg.
@param sys_add: see func |import... | 5e8c8e3cf59121a5f3e8add8ad5590d98ea5fa50 | 3,598,325 |
def example_function(a: int) -> int:
"""Takes an integer as input and return it's square
Parameters
----------
a : int
input number
Returns
-------
int
square of a
"""
return a ** 2 | fd519e72ec385aa905868facee198b3eaf57f778 | 3,598,326 |
import random
def sample_params(params):
"""Randomly sample hyper-parameters stored in a dictionary on a predefined range and scale.
Useful for hyper-parameter random search.
Args:
params (dict): hyper-parameters to sample. Dictionary value-type parsing:
- :python:`[1e3, 1e... | 516aadec130a8f83ccd920c06ca4317736ddfa75 | 3,598,327 |
def _richardson_lucy(img, psf, otf, iterations=10, accelerate=True, **kwargs):
"""Perform actual RL deconvolution.
assumes that img, psf, and otf have been prepared.
Typically, you would call richardson_lucy (see docstring there)
"""
eps = finfo(img.dtype).eps
t = img
tm1 = zeros_like(t)
... | a1d302437e5980043e7e6cdf24bef19bfc533691 | 3,598,328 |
def wrapTo180(lon):
"""Wrap longitude to 180 deg """
q = (lon < -180.0) | (180.0 < lon)
lon[q] = wrapTo360(lon[q] + 180.0) - 180.0
return lon | 601700dae1cd76524e6f2ab4161727445ae82db5 | 3,598,329 |
def free_color(wks_id,index):
"""
Removes a color entry from a workstation.
Ngl.free_color(workstation, color_index)
workstation -- An identifier returned from calling Ngl.open_wks.
color_index -- An integer scalar specifying a color index.
"""
NhlFreeColor(_int_id(wks_id),index)
return None | 366b48b738f9513eb092abe87a667300052b5f3e | 3,598,330 |
def prepare_pre_actual_for_prestg(unnested_df):
"""
preparing preprocessed data to be pushed into prestg table
"""
pre_actual_old_columns=['nodeid','section','module','ts','nodename']+[f"preprocessed_output_{i}" for i in range(0,5)]
pre_actual_df=unnested_df.cols.select(pre_actual_old_columns)
... | 10ff80f213df117b14ab8fb25dc2067bfcd83d72 | 3,598,331 |
def run(audit_files=None,
tags='*',
labels=None,
verbose=None,
show_compliance=None):
"""
:param audit_files:
Profile to execute. Can have one or more files
(python list or comma separated) (default: {None})
:param tags:
Can be used to target a subset ... | e09bde6b91fa2e379f933e60c9070872e0be6d14 | 3,598,332 |
def get_file_mode(fd):
"""
Returns access mode with which file was opened.
:Arguments:
fd - file descriptor got from open_file
:Return:
mode
"""
mode = ""
try:
mode = fd.mode
except ValueError:
print_error("file is already closed...")
except Exception ... | 2c6ff465c680aec845d1b6761298a60c7cea7c69 | 3,598,333 |
import random
def normal12(startt,endt,money,first,second,third,forth,fifth,sixth,seventh,ff1,ff2,mm1,mm2):
"""
for source and destination id generation
"""
"""
for type of banking work,label of fraud and type of fraud
"""
idvariz=random.choice(ff1)
idgirande=... | c13d1a535d061e9631337bba1d1d57ff841e6a05 | 3,598,334 |
def read_xml(path_to_file):
"""XML read
:param path_to_file: path to yaml file
:type path_to_file: str
:return: XML datastructure
:rtype: dict
"""
return xmltodict.parse(read_plain_text(path_to_file)) | 3b9153cb837ec9c0dddc4ae572869738e8ceffa6 | 3,598,335 |
def distance_matrix(points):
"""return NxN point to point distance matrix
this works but is not needed for USR
"""
points = N.array(points)
num, dim = points.shape
delta = N.zeros((num, num), "d")
for d in range(dim):
data = points[:, d]
delta += (data - data[:, N.NewAxis]) *... | 5e1a1c1922fb0a6d027665341e91e62aa469cf8e | 3,598,336 |
def merge_dicts(*args):
"""
Creates a new dictionary that merges those passed as arguments.
"""
if not args:
return {}
d = args[0].copy()
for extra in args[1:]:
d.update(extra)
return d | f23aeac179bd3ae16c0b1c141f8c918d87075396 | 3,598,337 |
def register_get():
"""
If a user is logged in redirect to the home page.
Otherwise displays a registration page.
"""
if 'logged_in' in session:
return redirect('/', code=303)
else:
# templates are stored in the templates folder
return render_template('register.html', mes... | 2de743ce92b561ed2d18ac1ab2b1280d7fed7b83 | 3,598,338 |
from pathlib import Path
def job_output():
"""Return job_output protobuf message"""
job_output_correct_answer = pb.JobOutput()
with open(
Path(__file__).parent / "answers" / "cisno_casci_result.pbmsg", "rb"
) as f:
job_output_correct_answer.ParseFromString(f.read())
return job_outp... | 90deb64b0249d66d7127199e0e8f633bc19c9a58 | 3,598,339 |
import doctest
def _quiet_testmod(module):
"""
Run all of a modules doctests, not producing any output to stdout.
Return a tuple with the number of failures and the number of tries.
"""
finder = doctest.DocTestFinder(exclude_empty=False)
runner = doctest.DocTestRunner(verbose=False)
for te... | 2c788dd128214e7c230124636aad3b0630060dd1 | 3,598,340 |
def ionizing_luminosity_fraction(temp, cutoff=13.6):
"""Calculate the total ionizing luminosity given a temp/cutoff energey."""
nulow = cutoff * eV / h
nuhi = 100 * nulow
value = (2.0 * h / cc ** 2) * quad(
lambda nu: nu ** 3 / (np.expm1(
h * nu / (kb * temp))), nulow, nuhi)[0] / (
... | dc0a28baa4348ab10c36d0125053f4d8c7922e6b | 3,598,343 |
def _pango_attr_list_types(attributes):
"""Returns the types of all attributes in the given Pango.AttrList."""
# Pango.AttrList does not appear to have any normal ways to access its
# contents, so this is a bit of a hack.
types = []
attributes.filter(lambda attribute: types.append(attribute.klass.ty... | d14a28fd88eb60cbe8190efaf09e1b5081c437c5 | 3,598,344 |
def transform_to_recurrent(arr,sequence_length,num_features):
"""
@param arr: The 2D numpy array to be transformed to a 3D array of size
(arr.shape[0],sequence_length,num_features). This format is amenable
for use with a recurrent network architecture.
@param... | acdc104996520c6e19d936458aeb8a7da3639e21 | 3,598,345 |
def get_required_setting(setting, value_re, invalid_msg):
"""
Return a constant from ``django.conf.settings``. The `setting`
argument is the constant name, the `value_re` argument is a regular
expression used to validate the setting value and the `invalid_msg`
argument is used as exception message ... | 2219ee5a2c27215857e86c0c4ea24b2c9a90d1f0 | 3,598,346 |
def process_and_mask_ids(
data,
seq_len=256,
padding='left',
keep='start',
start_token=1,
end_token=2
):
"""
Takes data that contains a list of lines in string form, and returns a
numpy array of shape [nb_sentences, seq_len], as well as a mask for the... | 28e457662e1b8f9367e03fdb5a0e8e03f1b8de06 | 3,598,347 |
def randKrausSet_Haar(d,r,rK):
"""!
Generates random set of Kraus operators
Parameters
-------
d : int
Number of gates
r : int
Superoperator dimension of the gates given by the square of the physical dimension
rK : int
Number of Kraus operators per gate ("Kraus rank... | 580e6a59e603b3c22c3f1b63495f895f2a185d95 | 3,598,348 |
def MtriangleConting(graph_dict, mia = 1.0, Sparse = False):
"""
Caculate 3-order triangle motif number.
Input:
graph_dict: (dictionary) the neighbor dictionary of each node in graph
mia: (float) motif information retention ratio (hyperparametric)
Sparse: (bool) need... | c3d59a081bdd6f330b3aa41466ce898243be6bd7 | 3,598,349 |
def is_street_name(elem):
"""This unction will get the elements in the file (i.e. the tag element) and
return the attributes in that element for which their key is equal to 'addr:street'.
"""
return (elem.attrib['k'] == "addr:street") | 72c751c903cf346548be59dc35c4d0b7345aea7e | 3,598,350 |
import colorsys
def hue_sat_to_cmap(hue, sat):
"""Mkae a color map from a hue and saturation value.
"""
# normalize to floats
hue = float(hue) / 360.0
sat = float(sat) / 100.0
res = []
for val in range(256):
hsv_val = float(val) / 255.0
r, g, b = colorsys.hsv_to_rgb(hue, ... | 816cee4bbf69ee466cdade149b4f4b4547e9b29a | 3,598,351 |
def create_particle_velocities(particle_size, v_min=-4, v_max=4):
"""
Create the velocities associated with a particle
:param particle_size:
:param v_min:
:param v_max:
:return:
"""
velocities = v_min + (v_max - v_min) * np.random.uniform(low=0, high=1, size=particle_size)
return vel... | ce7bb37d1b80a57c84143933f395ff9c928d0c09 | 3,598,352 |
def mine(user_address):
"""
Function that mines the block into block-chain.
"""
block = blockchain.mine_block(user_address, node_address)
response = {'status': True, 'message': 'Successfully Mined the new Block', 'block_data': block}
return response | facfc3c86bfe81d3e87e707c6df318f3f212782b | 3,598,353 |
from localtileserver import TileClient
def local_tile_bands(source):
"""Get band names from COG.
Args:
source (str | TileClient): A local COG file path or TileClient
Returns:
list: A list of band names.
"""
check_package("localtileserver", "https://github.com/banesullivan/localti... | 37b9762ca37985f314b813908f0438eeef5ca60f | 3,598,354 |
def wage_hourly_counts(year, num, source_long):
"""This function returns counts for each of the bins of the variable."""
bins = []
bins += [(0, 1), (1, 99), (100, 199), (200, 299), (300, 399), (400, 499), (500, 599)]
bins += [(600, 699), (700, 799), (800, 899), (900, 999), (1000, np.inf)]
counts = ... | d021e89b6103374a6fe3b042abdb209d9e135f95 | 3,598,355 |
def get_data_frame(root,
stn,
level,
columns=slice(None),
years='all'):
"""
Return a pandas data frame and mapping header information (one
entry per year) for all available data for a given *stn* and data
product *level* at repo... | 9d0d284255d2dc8465162388be35c4e0338ed017 | 3,598,358 |
def prepend_error_from_dir(sourcefile, function, errordirlist, destfile=None):
"""
Wrapper around the prepend error pass
"""
# Reject empty error lists
assert errordirlist
# If no destfile is given, just modify the source file
if destfile is None:
destfile = sourcefile
errordir... | 395b1655f98c2518e6ec1106fee7677bfa702e75 | 3,598,361 |
async def get_user(user_id: int):
"""
Get user from database
:param user_id: User id
:return: Ready to use UserClass
"""
cur.execute("SELECT * from users WHERE userId=?", (user_id,))
res = cur.fetchall()
if len(res) > 0:
res = res[0]
return UserClass(int(res['userId']),
... | 229796f091211f36e73f9eecf9a9764b9b85d27d | 3,598,363 |
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