content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def state(state_vec):
""" Qiskit wrapper of qobj
"""
return gen_operator.state(state_vec) | 74094c7c6e3c33cff28777f54d8852245c31f276 | 10,149 |
def get_games_for_platform(platform_id):
"""Return the list of all the games for a given platform"""
controller = GameController
return controller.get_list_by_platform(MySQLFactory.get(), platform_id) | 83855b6cdb4d39442e255d14d2f94d76a702a0ea | 10,151 |
def validate_dataset(elem: object) -> Dataset:
"""Check that `elem` is a :class:`~pydicom.dataset.Dataset` instance."""
if not isinstance(elem, Dataset):
raise TypeError('Sequence contents must be Dataset instances.')
return elem | d4744b06f0ccdc8dca0deab57585706c1ee91db9 | 10,152 |
def conv3x3(in_channels, out_channels, stride=1):
"""3x3 convolution """
weight_shape = (out_channels, in_channels, 3, 3)
weight = Tensor(np.ones(weight_shape).astype(np.float32))
conv = Conv2d(in_channels, out_channels,
kernel_size=3, stride=stride, padding=0, weight_init=weight, has_... | 011a3f74e8665669f9ecf5d4b9e8abf14f52e053 | 10,154 |
def _workflow_complete(workflow_stage_dict: dict):
"""Check if the workflow is complete.
This function checks if the entire workflow is complete.
This function is used by `execute_processing_block`.
Args:
workflow_stage_dict (dict): Workflow metadata dictionary.
Returns:
bool, Tr... | 4e5be4c4768d82e8b1e76d1964c3effb2e604dd2 | 10,155 |
def get_name(f, opera_format=True):
"""Load dataset and extract radar name from it"""
ds = xr.open_dataset(f)
if hasattr(ds, 'source'):
radar = ds.source
else:
filename = osp.splitext(osp.basename(f))[0]
radar = filename.split('_')[-1]
if opera_format:
if '/' in rad... | 8c50bebfde1300aa6de55981537cbc23171e6ee8 | 10,157 |
import six
def range_join(numbers, to_str=False, sep=",", range_sep=":"):
"""
Takes a sequence of positive integer numbers given either as integer or string types, and
returns a sequence 1- and 2-tuples, denoting either single numbers or inclusive start and stop
values of possible ranges. When *to_str... | c1b2d10ec1b47fa5c917fccead2ef8d5fc506370 | 10,158 |
def power_spectrum(x, fs, N=None):
"""
Power spectrum of instantaneous signal :math:`x(t)`.
:param x: Instantaneous signal :math:`x(t)`.
:param fs: Sample frequency :math:`f_s`.
:param N: Amount of FFT bins.
The power spectrum, or single-sided autospectrum, contains the squared RMS amplitudes ... | f665c529541420ada0ae4819e53de1e73035d83f | 10,159 |
def CreateInstanceTemplate(task, task_dir):
"""Create the Compute Engine instance template that will be used to create the
instances.
"""
backend_params = task.BackendParams()
instance_count = backend_params.get('instance_count', 0)
if instance_count <= 0:
clovis_logger.info('No template required.')
... | 558e4ed3152bb87a51bd2bb7dd107af5dd76bcd1 | 10,160 |
def get_config_string(info_type, board_num, dev_num, config_item, max_config_len):
"""Returns configuration or device information as a null-terminated string.
Parameters
----------
info_type : InfoType
The configuration information for each board is grouped into different categories. This
... | 72a35d984cb35e38a5e0742c7d790dc72ccbc928 | 10,161 |
import inspect
def _get_kwargs(func, locals_dict, default=None):
"""
Convert a function's args to a kwargs dict containing entries that are not identically default.
Parameters
----------
func : function
The function whose args we want to convert to kwargs.
locals_dict : dict
T... | ae0a06cb4e17b5512a03e89d7ca2119c58ea762b | 10,162 |
from datetime import datetime
def iso_to_date(iso_str: str):
"""Convert a date string with iso formating to a datetime date object"""
if not iso_str:
return None
return datetime.date(*map(int, iso_str.split('-'))) | a0d0541298ed538d7df9940ceef7b2bac121af27 | 10,163 |
def call_with_error(error_type):
"""Collects a bunch of errors and returns them all once.
Decorator that collects the errors in the decorated function so that the
user can see everything they need to fix at once. All errors are thrown
with the same error type.
The decorated must have an `error` ke... | 9a64fb630b0a491bc9e01d77ebe35199df47ab55 | 10,164 |
def _get_metadata_and_fingerprint(instance_name, project, zone):
"""Return the metadata values and fingerprint for the given instance."""
instance_info = _get_instance_info(instance_name, project, zone)
if not instance_info:
logs.log_error('Failed to fetch instance metadata')
return None, None
fingerpr... | 7049805d538c7942dc8249e91c27faa2c1867936 | 10,165 |
def solve_token_pair_and_fee_token_economic_viable(
token_pair, accounts, b_orders, s_orders, f_orders, fee,
xrate=None
):
"""Match orders between token pair and the fee token, taking into
account all side constraints, including economic viability.
If xrate is given, then it will be used instead of... | f6fcf5bccdf498f29852614751cf120a8e2addd4 | 10,166 |
def two_categorical(df, x, y, plot_type="Cross tab"):
"""
['Cross tab', "Stacked bone_numeric_one_categorical"]
"""
if plot_type is None:
plot_type = 'Cross tab'
if plot_type == 'Stacked bar': # 20
df_cross = pd.crosstab(df[x], df[y])
data = []
for x in df_cross.... | 5c0908055848d9de02920f8e2718de0918f4b460 | 10,167 |
def yices_bvconst_one(n):
"""Set low-order bit to 1, all the other bits to 0.
Error report:
if n = 0
code = POS_INT_REQUIRED
badval = n
if n > YICES_MAX_BVSIZE
code = MAX_BVSIZE_EXCEEDED
badval = n.
"""
# let yices deal with int32_t excesses
if n > MAX_INT... | 6a70c4773a6558e068d2bbafb908657d5b5b4d1d | 10,168 |
def showItem(category_id):
"""Show all Items"""
category = session.query(Category).filter_by(id=category_id).one()
items = session.query(Item).filter_by(
category_id=category_id).all()
return render_template('item.html', items=items, category=category) | 230cc9b7e8043b0bb3e78866b2a27a0aec287828 | 10,169 |
def get_standard_t_d(l, b, d):
"""
Use NE2001 to estimate scintillation time at 1 GHz and 1 km/s transverse velocity.
Parameters
----------
l : float
Galactic longitude
b : float
Galactic latitude
d : float
Distance in kpc
Returns
-------
t_d... | e1743ae75a6893376c5e13126deda6f0eb41d38f | 10,170 |
def match(pattern: str, text: str) -> bool:
"""
匹配同样长度的字符串
"""
if pattern:
return True
elif pattern == "$" and text == "":
return True
elif pattern[1] == "?":
return _match_question(pattern, text)
elif pattern[1] == "*":
return _match_star(pattern, text)
e... | 0dc71f00323502de7c1a2e00c502c99d75f56fc1 | 10,172 |
def config_func(tools, index, device_id, config_old: {}, config_new: {}):
"""
CANedge configuration update function
:param tools: A collection of tools used for device configuration
:param index: Consecutive device index (from 0)
:param device_id: Device ID
:param config_old: The current device ... | c0585c3a268fb40e3e00a2613e03001bc561566a | 10,173 |
def load_figure(file_path: str) -> matplotlib.figure.Figure:
"""Fully loads the saved figure to be able to be modified.
It can be easily showed by:
fig_object.show()
Args:
file_path: String file path without file extension.
Returns:
Figure object.
Raises:
None.
... | 76dcc0a27a3ae04e574a3d69fb431eedbc0c618a | 10,174 |
def cluster_vectors(vectors, k=500, n_init=100, **kwargs):
"""Build NearestNeighbors tree."""
kwargs.pop('n_clusters', None)
kwargs.pop('init', None)
kwargs.pop('n_init', None)
return KMeans(n_clusters=k, init='k-means++', n_init=n_init,
**kwargs).fit(vectors) | 28984811ea58a2a2c123d36cdb5e56c1d5b8d0db | 10,175 |
import torch
import math
def positional_encoding(d_model, length):
"""
:param d_model: dimension of the model
:param length: length of positions
:return: length*d_model position matrix
"""
if d_model % 2 != 0:
raise ValueError("Cannot use sin/cos positional encoding with "
... | de41f0c99b46f16dbe300d59527e11b98a0b1f14 | 10,176 |
def invert_hilbert_QQ(n=40, system='sage'):
"""
Runs the benchmark for calculating the inverse of the hilbert
matrix over rationals of dimension n.
INPUT:
- ``n`` - matrix dimension (default: ``300``)
- ``system`` - either 'sage' or 'magma' (default: 'sage')
EXAMPLES::
sage: impo... | 153e7400467a57cf07f839042d31d4800fe161bd | 10,179 |
def getModelListForEnumProperty(self, context):
"""Returns a list of (str, str, str) elements which contains the models
contained in the currently selected model category.
If there are no model categories (i.e. '-') return ('-', '-', '-').
Args:
context:
Returns:
"""
category = con... | 46f642933dd220b0f71431ff4a9cb7410858fbf0 | 10,180 |
import logging
def run_wcs(*args, **kwargs):
"""
Set up the environment and run the bundled wcs.exe (from the Talon distribution)
using the supplied command line arguments
"""
# Pull out keyword args that we are interested in
write_stdout_to_console = kwargs.get("write_stdout_to_console",... | 51461fcbc4ed5a08063d630aea926d312b9da825 | 10,182 |
def store_exposure_fp(fp, exposure_type):
"""
Preserve original exposure file extention if its in a pandas supported
compressed format
compression : {‘infer’, ‘gzip’, ‘bz2’, ‘zip’, ‘xz’, None}, default ‘infer’
For on-the-fly decompression of on-disk data. If ‘infer’ and
... | c187e79d4cce7ea79b66671a2e7378a35de4841f | 10,184 |
def velocity_genes(data, vkey='velocity', min_r2=0.01, highly_variable=None, copy=False):
"""Estimates velocities in a gene-specific manner
Arguments
---------
data: :class:`~anndata.AnnData`
Annotated data matrix.
vkey: `str` (default: `'velocity'`)
Name under which to refer to the... | 7d2a0b86d2fb4402cdef9ab56fe2638f89d09fac | 10,185 |
def update_graphics_labels_from_node_data(node, n_id_map, add_new_props):
"""Updates the graphics labels so they match the node-data"""
try:
gfx = select_child(node, n_id_map, 'nodegraphics').getchildren()[0].getchildren()
except:
return None
node_label = select_child(node, n_id_map, 'l... | c2d3104dbc3a20ff6c34de754ff681b176091787 | 10,186 |
def ProcuraPalavra(dicionário, palavra):
"""
Procura as possíveis palavras para substituir
a palavra passada, e as devolve numa lista
"""
#Antes de mais nada tornamos a palavra maiuscula
#para realizar as comparações
palavra = palavra.upper()
#Primeiro olhamos para o caso de haver u... | 1a283aec6670c0e2fe6ca6f4366ef43c6ba97e9f | 10,189 |
import json
import six
def _build_auth_record(response):
"""Build an AuthenticationRecord from the result of an MSAL ClientApplication token request"""
try:
id_token = response["id_token_claims"]
if "client_info" in response:
client_info = json.loads(_decode_client_info(response[... | 96aed71945c354e41cafd89bf5d7a7d62c31a40a | 10,191 |
def loc_data_idx(loc_idx):
"""
Return tuple of slices containing the unflipped idx corresponding to loc_idx.
By 'unflipped' we mean that if a slice has a negative step, we wish to retrieve
the corresponding indices but not in reverse order.
Examples
--------
>>> loc_data_idx(slice(11, None,... | d30b1b27957e24ff30caf19588487645ac198dc8 | 10,192 |
def eat_descriptor(descr):
"""
Read head of a field/method descriptor. Returns a pair of strings, where
the first one is a human-readable string representation of the first found
type, and the second one is the tail of the parameter.
"""
array_dim = 0
while descr[0] == '[':
array_di... | 411ce48ce250fe15438cd89f43b91ee9b87908a6 | 10,193 |
def legendre(a, p):
"""Legendre symbol"""
tmp = pow(a, (p-1)//2, p)
return -1 if tmp == p-1 else tmp | 66b86dce23ae10ba226ffb19942b98550bb7c218 | 10,194 |
def precheck_arguments(args):
""" Make sure the argument choices are valid """
any_filelist = (len(args.filelist_name[0]) > 0 or len(args.output_dir[0]) > 0 or args.num_genomes[0] > 0)
if len(args.filelist_name[0]) > 0 and len(args.output_dir[0]) == 0:
print("Error: Need to specify output directory with -O if... | 984865d214cca63eae8bacf5bc7be238e7209ddb | 10,196 |
def get_image_blob(im):
"""Converts an image into a network input.
Arguments:
im (ndarray): a color image
Returns:
blob (ndarray): a data blob holding an image pyramid
im_scale_factors (list): list of image scales (relative to im) used
in the image pyramid
"""
im_... | 6d72ea1ffcdf20bbf05f75f6084a9027e771196a | 10,197 |
def get_expr_fields(self):
"""
get the Fields referenced by switch or list expression
"""
def get_expr_field_names(expr):
if expr.op is None:
if expr.lenfield_name is not None:
return [expr.lenfield_name]
else:
# constant value expr
... | 103aa0ac54be37b23d9695dddfda9972a9f0d7f0 | 10,198 |
import math
def add_bias_towards_void(transformer_class_logits, void_prior_prob=0.9):
"""Adds init bias towards the void (no object) class to the class logits.
We initialize the void class with a large probability, similar to Section 3.3
of the Focal Loss paper.
Reference:
Focal Loss for Dense Object De... | f5b3439fc7fbc987bbcbc3b64fd689208db7c5e6 | 10,199 |
def trajnet_batch_multi_eval(preds, gt, seq_start_end):
"""Calculate Top-k ADE, Top-k FDE for batch of samples.
pred = Num_modes x Num_ped x Num_timesteps x 2
gt = Num_ped x Num_timesteps x 2
seq_start_end (batch delimiter) = Num_batches x 2
"""
s_topk_ade = 0
s_topk_fde = 0
for (start,... | ff93309e61d871a2d337810cc1836950f883c184 | 10,200 |
def disemvowel(sentence):
"""Disemvowel:
Given a sentence, return the sentence with all vowels removed.
>>> disemvowel('the quick brown fox jumps over the lazy dog')
'th qck brwn fx jmps vr th lzy dg'
"""
vowels = ('a','e','i','o','u')
for x in sentence:
if x in vowels:
... | d9b6d873c29e82cb65e43f71e2b6298af18b25fd | 10,201 |
def runPolyReg(xValueList, yValueList, degrees):
"""
Preforms *Polynomial Regression* based on the arguments provided.
Note that we split the data by the *First* 80 percent of the data and then the *Last* 20 percent of the data, rather than randomly splitting the data by 80/20 for the Train/Test split.
... | 25d4699f720d943dc49264edc12f2246df51f053 | 10,202 |
def unfold_phi_vulpiani(phidp, kdp):
"""Alternative phase unfolding which completely relies on :math:`K_{DP}`.
This unfolding should be used in oder to iteratively reconstruct
:math:`Phi_{DP}` and :math:`K_{DP}` (see :cite:`Vulpiani2012`).
Parameters
----------
phidp : :class:`numpy:numpy.ndar... | 72386a05500c4ba11385e3b57288655e0a207352 | 10,203 |
def get_result_df(session):
"""
query the match table and put results into pandas dataframe,
to train the team-level model.
"""
df_past = pd.DataFrame(
np.array(
[
[s.fixture.date, s.fixture.home_team, s.fixture.away_team, s.home_score, s.away_score]
... | 364d9e7f9ef1a97018402fa964f246954f51f945 | 10,204 |
def permute1d(preserve_symmetry = True):
"""Choose order to rearrange rows or columns of puzzle."""
bp = block_permutation(preserve_symmetry)
ip = [block_permutation(False),block_permutation(preserve_symmetry)]
if preserve_symmetry:
ip.append([2-ip[0][2],2-ip[0][1],2-ip[0][0]])
else:
... | a9ccd2cb486e0ee3d50840c6ab41871396f3ca93 | 10,205 |
from typing import Iterable
from typing import List
def take(n: int, iterable: Iterable[T_]) -> List[T_]:
"""Return first n items of the iterable as a list"""
return list(islice(iterable, n)) | 491cdaaa20ad67b480ea92acaeb53e4edf2b4d56 | 10,208 |
def abs(rv):
"""
Returns the absolute value of a random variable
"""
return rv.abs() | 6bf2f8420f8a5e883dfddfc9a93106662a8f1a74 | 10,209 |
def compute_ssm(X, metric="cosine"):
"""Computes the self-similarity matrix of X."""
D = distance.pdist(X, metric=metric)
D = distance.squareform(D)
for i in range(D.shape[0]):
for j in range(D.shape[1]):
if np.isnan(D[i, j]):
D[i, j] = 0
D /= D.max()
return 1... | 646d9af2134db13b69391817ddfeace0fef1217d | 10,210 |
def escape(instruction):
"""
Escape used dot graph characters in given instruction so they will be
displayed correctly.
"""
instruction = instruction.replace('<', r'\<')
instruction = instruction.replace('>', r'\>')
instruction = instruction.replace('|', r'\|')
instruction = instruction.... | 936ed1d6c55650bf5f9ce52af8f113a9d466a534 | 10,211 |
def _json_object_hook(d):
"""
JSON to object helper
:param d: data
:return: namedtuple
"""
keys = []
for k in d.keys():
if k[0].isdigit():
k = 'd_{}'.format(k)
keys.append(k)
return namedtuple('X', keys)(*d.values()) | a4a534a975d6faff440f66065d4954e2a5a91ff2 | 10,212 |
def _fourier_interpolate(x, y):
""" Simple linear interpolation for FFTs"""
xs = np.linspace(x[0], x[-1], len(x))
intp = interp1d(x, y, kind="linear", fill_value="extrapolate")
ys = intp(xs)
return xs, ys | cfe663b9e261bbaea2ab6fe58366f4ec3726468c | 10,213 |
import hashlib
def compute_hash_json_digest(*args, **kwargs):
"""compute json hash of given args and kwargs and return md5 hex digest"""
as_json = compute_hash_json(*args, **kwargs)
return hashlib.md5(as_json).hexdigest() | 98dfedb000e2780dba5007d9fe6abd7a74a43a31 | 10,214 |
def hello_world():
"""Print welcome message as the response body."""
return '{"info": "Refer to internal http://metadata-db for more information"}' | ecb2208053e4ff530bcc0dcc117172449a51afbd | 10,215 |
import google
from datetime import datetime
def build_timestamp(timestamp=None) -> google.protobuf.timestamp_pb2.Timestamp:
"""Convert Python datetime to Protobuf Timestamp"""
# https://github.com/protocolbuffers/protobuf/issues/3986
proto_timestamp = google.protobuf.timestamp_pb2.Timestamp()
return p... | ae2278b66c200f007240ca5f683a60ebc1ebddf2 | 10,217 |
def read_blosum():
"""Read blosum dict and delete some keys and values."""
with open('./psiblast/blosum62.pkl', 'rb') as f:
blosum_dict = cPickle.load(f)
temp = blosum_dict.pop('*')
temp = blosum_dict.pop('B')
temp = blosum_dict.pop('Z')
temp = blosum_dict.pop('X')
temp = blosum_dic... | ddbf71c03e05bd156ad688a9fe9692da1d0a3dc4 | 10,219 |
from typing import List
from typing import Tuple
def parse_spans_bio_with_errors(seq: List[str]) -> Tuple[List[Span], List[Error]]:
"""Parse a sequence of BIO labels into a list of spans but return any violations of the encoding scheme.
Note:
In the case where labels violate the span encoded scheme, ... | 6cea777cfb8bf96325f2695af2c48cc22c4884cf | 10,220 |
from typing import Sequence
from typing import Tuple
def find_best_similar_match(i1: int, i2: int, j1: int, j2: int, a: Sequence, b: Sequence, sm: SequenceMatcher = None) \
-> Tuple[int, int, float]:
"""
Finds most similar pair of elements in sequences bounded by indexes a[i1:i2], b[j1: j2].
:par... | ca6e73c2315e2d2419b631cb505131f3daabea4b | 10,221 |
def ConvUpscaleBlock(inputs, n_filters, kernel_size=[3, 3], scale=2):
"""
Basic conv transpose block for Encoder-Decoder upsampling
Apply successivly Transposed Convolution, BatchNormalization, ReLU nonlinearity
"""
net = slim.conv2d_transpose(inputs, n_filters, kernel_size=[3, 3], stride=[2, 2], ac... | 787104a3015bd901105383b203551573f9f07fcb | 10,222 |
def make_random_password(self, length = 10, allowed_chars = 'abcdefghjkmnpqrstuvwxyzABCDEFGHJKLMNPQRSTUVWXYZ23456789'):
"""
Generate a random password with the given length and given
allowed_chars. The default value of allowed_chars does not have "I" or
"O" or letters and digits that look similar -- just to avoid c... | be155b2537b062a396ed1d5aed6367857b21d49e | 10,224 |
def autocov_vector(x, nlags=None):
"""
This method computes the following function
.. math::
R_{xx}(k) = E{ x(t)x^{*}(t-k) } = E{ x(t+k)x^{*}(k) }
k \in {0, 1, ..., nlags-1}
(* := conjugate transpose)
Note: this is related to
the other commonly used definition for vector autocovarian... | 8725b2695b51c014e8234605bc5e64ad1ca0c26b | 10,225 |
def sequence_masking(x, mask, mode=0, axis=None, heads=1):
"""为序列条件mask的函数
mask: 形如(batch_size, sequence)的0-1矩阵；
mode: 如果是0，则直接乘以mask；
如果是1，则在padding部分减去一个大正数。
axis: 序列所在轴，默认为1；
heads: 相当于batch这一维要被重复的次数。
"""
if mask is None or mode not in [0, 1]:
return x
else:
... | ac7e0da24eca87ab3510c1c274f0caeb2d527816 | 10,226 |
def __long_description() -> str:
"""Returns project long description."""
return f"{__readme()}\n\n{__changelog()}" | 53260637e4e4f1e59e6a67238577fb6969e7769c | 10,228 |
def captains_draft(path=None, config=None):
"""Similar to captains mode with a 27 heroes, only 3 bans per teams"""
game = _default_game(path, config=config)
game.options.game_mode = int(DOTA_GameMode.DOTA_GAMEMODE_CD)
return game | 05af49626cff0827ff1b78ffb1da082bba160d29 | 10,229 |
def create(width, height, pattern=None):
"""Create an image optionally filled with the given pattern.
:note: You can make no assumptions about the return type; usually it will
be ImageData or CompressedImageData, but patterns are free to return
any subclass of AbstractImage.
:Parameters:
... | dcd287353c84924afcdd0a56e9b51f00cde7bb85 | 10,230 |
import logging
def compute_conformer(smile: str, max_iter: int = -1) -> np.ndarray:
"""Computes conformer.
Args:
smile: Smile string.
max_iter: Maximum number of iterations to perform when optimising MMFF force
field. If set to <= 0, energy optimisation is not performed.
Returns:
A tuple con... | 0b923d7616741312d8ac129d7c7c99081a2c3f97 | 10,231 |
def get_api_key():
"""Load API key."""
api_key_file = open('mailgun_api_key.txt', 'r')
api_key = api_key_file.read()
api_key_file.close()
return api_key.strip() | 55c87d15d616f0f6dfbc727253c2222128b63560 | 10,232 |
def bitserial_conv2d_strategy_hls(attrs, inputs, out_type, target):
"""bitserial_conv2d hls strategy"""
strategy = _op.OpStrategy()
layout = attrs.data_layout
if layout == "NCHW":
strategy.add_implementation(
wrap_compute_bitserial_conv2d(topi.nn.bitserial_conv2d_nchw),
w... | f009b1f7ac073573877b1ddab616868cdf1d42c7 | 10,233 |
def get_fpga_bypass_mode(serverid):
""" Read back FPGA bypass mode setting
"""
try:
interface = get_ipmi_interface(serverid, ["ocsoem", "fpgaread", "mode"])
return parse_get_fpga_bypass_mode(interface, "mode")
except Exception, e:
return set_failure_dict("get_fpga_bypass_mo... | b572a372c6c73bb0f65686b3235e3362d31e8655 | 10,235 |
def lookup_complement(binding):
"""
Extracts a complement link from the scope of the given binding.
Returns an instance of :class:`htsql.core.tr.binding.Recipe`
or ``None`` if a complement link is not found.
`binding` (:class:`htsql.core.tr.binding.Binding`)
A binding node.
"""
pro... | 104f7b0139a8ca6390cb90dc10529d3be9a723ea | 10,236 |
import itertools
def flatten(colours):
"""Flatten the cubular array into one long list."""
return list(itertools.chain.from_iterable(itertools.chain.from_iterable(colours))) | 41576ef947354c30d1995fefdd30ad86bddbfe6f | 10,237 |
import numpy
def create_word_search_board(number: int):
"""
This function creates a numpy array of zeros, with dimensions of
number x number, which is set by the user. The array is then
iterated through, and zeros are replaced with -1's to avoid
confusion with the alphabet (A) beginning at 0.
... | 31f22d56c947f61840ba87d028eb7de275d33cc9 | 10,239 |
def get_parent_choices(menu, menu_item=None):
"""
Returns flat list of tuples (possible_parent.pk, possible_parent.caption_with_spacer).
If 'menu_item' is not given or None, returns every item of the menu. If given, intentionally omit it and its descendant in the list.
"""
def get_flat_tuples(menu_i... | c88ca93f7e8a7907425a51323ba53bb75bdf29c2 | 10,240 |
def _update_jacobian(state, jac):
"""
we update the jacobian using J(t_{n+1}, y^0_{n+1})
following the scipy bdf implementation rather than J(t_n, y_n) as per [1]
"""
J = jac(state.y0, state.t + state.h)
n_jacobian_evals = state.n_jacobian_evals + 1
LU = jax.scipy.linalg.lu_factor(state.M - ... | 31570ad29dca3ee01281819865e6efe1aec4050d | 10,241 |
from typing import Tuple
from typing import List
def reduce_pad(sess: tf.Session, op_tensor_tuple: Tuple[Op, List[tf.Tensor]], _) -> (str, tf.Operation, tf.Operation):
"""
Pad module reducer
:param sess: current tf session
:param op_tensor_tuple: tuple containing the op to reduce, and a list of input ... | 29d7e8daf85a9fe8fee118fd5ec5dc00018120a9 | 10,242 |
def parse_fastq(fh):
""" Parse reads from a FASTQ filehandle. For each read, we
return a name, nucleotide-string, quality-string triple. """
reads = []
while True:
first_line = fh.readline()
if len(first_line) == 0:
break # end of file
name = first_line[1:].rstr... | d33d3efebdd1c5f61e25397328c6b0412f1911dd | 10,243 |
def minhash_256(features):
# type: (List[int]) -> bytes
"""
Create 256-bit minimum hash digest.
:param List[int] features: List of integer features
:return: 256-bit binary from the least significant bits of the minhash values
:rtype: bytes
"""
return compress(minhash(features), 4) | 1dba3d02dd05bfd2358211fa97d99ce136cc198d | 10,244 |
def coalesce(*values):
"""Returns the first not-None arguement or None"""
return next((v for v in values if v is not None), None) | 245177f43962b4c03c2347725a2e87f8eb5dc08a | 10,245 |
from mitsuba.core.xml import load_string
def test06_load_various_features(variant_scalar_rgb, mesh_format, features, face_normals):
"""Tests the OBJ & PLY loaders with combinations of vertex / face normals,
presence and absence of UVs, etc.
"""
def test():
shape = load_string("""
... | a0117fe48b53e448181014e006ce13368c777d90 | 10,246 |
import torch
def euc_reflection(x, a):
"""
Euclidean reflection (also hyperbolic) of x
Along the geodesic that goes through a and the origin
(straight line)
"""
xTa = torch.sum(x * a, dim=-1, keepdim=True)
norm_a_sq = torch.sum(a ** 2, dim=-1, keepdim=True).clamp_min(MIN_NORM)
proj = x... | 83b5a8559e783b24d36a18fb30059dce82bf9cf7 | 10,247 |
def is_online():
"""Check if host is online"""
conn = httplib.HTTPSConnection("www.google.com", timeout=1)
try:
conn.request("HEAD", "/")
return True
except Exception:
return False
finally:
conn.close() | 4dd9d2050c94674ab60e0dfbcfa0c713915aa2f3 | 10,248 |
def text_value(s):
"""Convert a raw Text property value to the string it represents.
Returns an 8-bit string, in the encoding of the original SGF string.
This interprets escape characters, and does whitespace mapping:
- linebreak (LF, CR, LFCR, or CRLF) is converted to \n
- any other whitespace c... | 24d40367dbefcfbdd0420eb466cf6d09657b2768 | 10,249 |
def modifica_immobile_pw():
"""La funzione riceve l' ID immobile da modificare e ne modifica un attibuto scelto dall'utente """
s = input("Vuoi la lista degli immobili per scegliere il ID Immobile da modificare? (S/N)")
if s == "S" or s =="s":
stampa_immobili_pw()
s= input("Dammi ID... | 99905d61d91178092dba8860265b2034b3f8430b | 10,250 |
def hpat_pandas_series_len(self):
"""
Pandas Series operator :func:`len` implementation
.. only:: developer
Test: python -m hpat.runtests hpat.tests.test_series.TestSeries.test_series_len
Parameters
----------
series: :class:`pandas.Series`
Returns
-------
... | 57bdd2a7f7ae54861943fb44f3bc51f1f6544911 | 10,251 |
from typing import List
def arrays_not_same_size(inputs: List[np.ndarray]) -> bool:
"""Validates that all input arrays are the same size.
Args:
inputs (List[np.ndarray]): Input arrays to validate
Returns:
true if the arrays are the same size and false if they are not
"""
shapes = ... | 8b9988f49d766bc7a27b79cf6495182e98a8fe18 | 10,252 |
def GetReaderForFile(filename):
"""
Given a filename return a VTK reader that can read it
"""
r = vtkPNGReader()
if not r.CanReadFile(filename):
r = vtkPNMReader()
if not r.CanReadFile(filename):
r = vtkJPEGReader()
if not r.CanReadFile(filename):
... | f574417df44f8a43277e62967ec6fd4c986fa85a | 10,253 |
def build_figure_nn(df, non_private, semantic):
"""
Dataframe with one semantic and one model
"""
l = df.query("epsilon > 0").sort_values(["train_size", "epsilon"])
naive, low, high = get_plot_bounds(df)
fig = px.line(
l,
x="train_size",
y="accuracy",
range_y=[lo... | 5eab366e20eaec721d7155d82e42d9222cacd3b5 | 10,254 |
def get_incomplete_sample_nrs(df):
""" Returns sample nrs + topologies if at least 1 algorithm result is missing """
topology_incomplete_sample_nr_map = dict()
n_samples = df.loc[df['sample_idx'].idxmax()]['sample_idx'] + 1
for ilp_method in np.unique(df['algorithm_complete']):
dfx = df[df['algo... | 2d816d80bb2f0c2686780ca49d0c01e89c69e7b5 | 10,255 |
from typing import Optional
def _read_pos_at_ref_pos(rec: AlignedSegment,
ref_pos: int,
previous: Optional[bool] = None) -> Optional[int]:
"""
Returns the read or query position at the reference position.
If the reference position is not within the span o... | 51270a1c1a5f69b179e3623824632443775ec9c7 | 10,256 |
from astropy.io import fits as pf
import numpy as np
import logging
def load_gtis(fits_file, gtistring=None):
"""Load GTI from HDU EVENTS of file fits_file."""
gtistring = _assign_value_if_none(gtistring, 'GTI')
logging.info("Loading GTIS from file %s" % fits_file)
lchdulist = pf.open(fits_file, chec... | c1a8019d052ce437680e6505e65134a5ed66a1a3 | 10,257 |
import requests
def macro_australia_unemployment_rate():
"""
东方财富-经济数据-澳大利亚-失业率
http://data.eastmoney.com/cjsj/foreign_5_2.html
:return: 失业率
:rtype: pandas.DataFrame
"""
url = "http://datainterface.eastmoney.com/EM_DataCenter/JS.aspx"
params = {
"type": "GJZB",
"sty": "... | 260debcfaf342d08acacfe034da51b3d3162393e | 10,258 |
from typing import List
import math
def _convert_flattened_paths(
paths: List,
quantization: float,
scale_x: float,
scale_y: float,
offset_x: float,
offset_y: float,
simplify: bool,
) -> "LineCollection":
"""Convert a list of FlattenedPaths to a :class:`LineCollection`.
Args:
... | 876421cd7f89dc5f3d64357e76f302c633e41ba7 | 10,259 |
def _CustomSetAttr(self, sAttr, oValue):
""" Our setattr replacement for DispatchBaseClass. """
try:
return _g_dCOMForward['setattr'](self, ComifyName(sAttr), oValue)
except AttributeError:
return _g_dCOMForward['setattr'](self, sAttr, oValue) | 8a0fea986531aec66564bafcc679fed3b8631c10 | 10,260 |
def reduce_to_contemporaneous(ts):
"""
Simplify the ts to only the contemporaneous samples, and return the new ts + node map
"""
samples = ts.samples()
contmpr_samples = samples[ts.tables.nodes.time[samples] == 0]
return ts.simplify(
contmpr_samples,
map_nodes=True,
keep_... | 7661a58b6f4b95d5cb4b711db39bb28852151304 | 10,261 |
def get_name(tree, from_='name'):
"""
Get the name (token) of the AST node.
:param tree ast:
:rtype: str|None
"""
# return tree['name']['name']
if 'name' in tree and isinstance(tree['name'], str):
return tree['name']
if 'parts' in tree:
return djoin(tree['parts'])
i... | b5f1e97eb570859b01bf9489c6b9d4874511fdcc | 10,264 |
def pcaTable(labels,vec_mean,vec_std,val_mean,val_std):
"""Make table with PCA formation mean and std"""
header="\\begin{center}\n\\begin{tabular}{| l |"+" c |"*6+"}\\cline{2-7}\n"
header+="\\multicolumn{1}{c|}{} & \\multicolumn{2}{c|}{PC1} & \multicolumn{2}{c|}{PC2} & \multicolumn{2}{c|}{PC3} \\... | 646fc1b5344a716b8f30714f112a477063bf91ce | 10,265 |
def render_reference_page(conn: Connection, reference: str) -> str:
"""Create HTML section that lists all notes that cite the reference."""
sql = """
SELECT note, Bibliography.html,Notes.html FROM Citations
JOIN Notes ON Citations.note = Notes.id
JOIN Bibliography ON Bibliogr... | 6ab73d0d85da28676e7bb3cf42b3304cd0d6ad47 | 10,266 |
import logging
def normalize_bridge_id(bridge_id: str):
"""Normalize a bridge identifier."""
bridge_id = bridge_id.lower()
# zeroconf: properties['id'], field contains semicolons after each 2 char
if len(bridge_id) == 17 and sum(True for c in "aa:bb:cc:dd:ee:ff"
if... | 5370cc49e4c0272da2a471006bbbf3fd5e5521bf | 10,267 |
import imp
def pyc_file_from_path(path):
"""Given a python source path, locate the .pyc.
See http://www.python.org/dev/peps/pep-3147/
#detecting-pep-3147-availability
http://www.python.org/dev/peps/pep-3147/#file-extension-checks
"""
has3147 = hasattr(imp, 'get_tag')
... | 459011ca1f07a023b139695cd2368767d46ca396 | 10,268 |
def get_bytes_per_data_block(header):
"""Calculates the number of bytes in each 128-sample datablock."""
N = 128 # n of amplifier samples
# Each data block contains N amplifier samples.
bytes_per_block = N * 4 # timestamp data
bytes_per_block += N * 2 * header['num_amplifier_channels']
# ... | 524e9015dacaf99042dd1493b24a418fff8c6b04 | 10,269 |
def recovered():
"""
Real Name: b'Recovered'
Original Eqn: b'INTEG ( RR, 0)'
Units: b'Person'
Limits: (None, None)
Type: component
b''
"""
return integ_recovered() | 1a5133a3cc9231e3f7a90b54557ea9e836975eae | 10,270 |
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