content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
import torch
def create_mock_target(number_of_nodes, number_of_classes):
"""
Creating a mock target vector.
"""
return torch.LongTensor(
[np.random.randint(0, number_of_classes - 1) for node in range(number_of_nodes)]
) | 0892fcea085dab7df3633720c69466ac958f3e3d | 55,668 |
def string_of_error(return_code: int) -> str:
"""Decode the TREXIO exit code.
Argument is an integer return code that correspond to one of the TREXIO errors.
Returns string that contains description of TREXIO ~return_code~.
"""
try:
error_str = pytr.trexio_string_of_error(return_code)
... | ec6a391cdb1051080ebe93dfb07e5d59f5a9f996 | 55,669 |
from typing import Optional
def get_float(message: str = "Choose a number", title: str = "Title", default_value: float = 0.0,
min_: float = -10000, max_: float = 10000, decimals: int = 3) -> Optional[float]:
"""
Simple dialog to ask a user to select a floating point number
within a certain r... | 809fb85f96eed285c4a301a9a263866aa3fed697 | 55,670 |
def score_filter(predictions, min_score):
"""Remove prediction bounding boxes with probability under a threshold
Parameters
----------
predictions : dict
all predictions
min_score : int
threshold score
Returns
-------
dict
filtered predictions
"""
new_p... | 28f8c0604f3dabc76ffbda911357d0bdd5bd5331 | 55,672 |
import math
def plot_connectivity(
epoch,
fig=None,
locations=None,
calc_type="correlation",
pair_list=[],
threshold=0,
show_sphere=True,
readjust_sphere="auto",
colormap="RdBu_r",
vmin=None,
vmax=None,
line_width=None,
title=None,
colorbar=True,
caption=Non... | 450362f28beb17dd36b066f786a8023abb8e939e | 55,673 |
def consolidate(*levels):
"""
Arranges list of object dictionaries levels into a
hierarchical data structure, based upon the attribute
"parent"
Must pass arguments in ascending order (e.g. children,
parents, grandparents)
"""
# consolidated = list(levels) # modify copy
consolidate... | 7cb064d3651767732c979ba34952a0a8c8962eb0 | 55,674 |
def verbose_name_plural(obj):
"""Return model verbose name in plural mode."""
if isinstance(obj, models.Model):
type(obj)._meta.verbose_name_plural
return obj._meta.verbose_name_plural | df05ace5cd8927ba5549cf601148554bc69f34b0 | 55,675 |
import struct
def decode_option(packet, offset):
"""Decode a navdata option."""
id_nr, size = struct.unpack_from("HH", packet, offset)
end_offset = offset + size
data = packet[offset + struct.calcsize("HH"):end_offset]
return id_nr, data, end_offset | c0ada56ba1f227a9db74b6d090496b3cfdbb1041 | 55,676 |
def split_range_into_groups(
n,
group_size,
which_group_complete="last"):
"""Partitions `n` elements into adjacent groups,
each with `group_size` elements
Group number starts from 0 and increments upward
Can be used to generate groups for sliding window aggregation.
... | aba2d19fa52f44dc0817290efb9fcea9a9209845 | 55,677 |
import math
def getsteps(tspan, h):
"""
Given a timespan and a timestep h, return the number of steps.
"""
t1, t2 = tspan
return int(math.floor((t2-t1)/h)) | a10e0a4302352be6eafb9fad8e00005b9c79dd27 | 55,678 |
def mds(data, variables=None):
"""
Python implementation of the MDS coordinates calculated by the CCG program corrmat when set to
'ordination' mode.
MDS coordinates are calculate from the correlation matrix
.. seealso::
1. Deutsch, M. V, & Deutsch, C. V. (2013). A Program to Calculate and... | 5cbe72605825bc49fd41addf3c13cdb143279808 | 55,679 |
from typing import Union
def boolean(value: Union[bool, str, float] = False) -> bool:
"""
Return boolean from string.
"""
if isinstance(value, bool):
return value
elif isinstance(value, str):
value = value.lower().strip()[0]
if value in ["y", "t"]:
return True
... | 4f1db3e1224e0633c5d663e6ae85a8ae19c51624 | 55,680 |
from typing import List
def solve(
context: mgp.ProcCtx, points: List[mgp.Vertex], method: str = DEFAULT_SOLVING_METHOD
) -> mgp.Record(sources=List[mgp.Vertex], destinations=List[mgp.Vertex]):
"""
The tsp_module solver returns 2 fields whose elements at indexes are correlated
* `sources` - element... | 6662f6e353441dbfb360684829a30fd4c542f616 | 55,681 |
def convert_dataset_to_samples(dataset, max_span_length, ner_label2id=None, context_window=0, split=0):
"""
Extract sentences and gold entities from a dataset
"""
# split: split the data into train and dev (for ACE04)
# split == 0: don't split
# split == 1: return first 90% (train)
# split =... | c060cccfbf6892999cf9ccd0ee2f72f0e2e9a6f8 | 55,683 |
def build_bin_mask(n,chrs,zoom_dict,chr_dict,chr_bin_range,bin_positions,axis=None):
"""build a 1D mask (x or y axis) based upon user chr/coor selection
"""
bin_mask=np.zeros(n,dtype=bool)
# build bin mask based on user chr/zoom selection
for c in chrs:
c_ind=chr_dict[c]
r=c... | bd651489e524c89826f8d59b4acab0dad66b3da0 | 55,685 |
def fill_nnz(
mat: "sp.csr_matrix", all_nnz: "np.ndarray[int]", fill_value: float = 1e-9
) -> sp.csr_matrix:
"""
Given an input sparse matrix and a superset of nonzero coordinates, fill the
matrix to ensure all values in the set are stored explicitely with the
value of fill_value.
Parameters
... | 08fa0f5de958adf0608a69937839e131ceaaba85 | 55,686 |
def maxima(array):
""" get the index of the maximum value in a 2D array"""
return np.unravel_index(array.argmax(), array.shape) | a64de68bbdda70a9dd789769f6c7334d23f9eb6a | 55,687 |
def strip_noise_from_key_signature(key):
"""Removes any unneccessary characters (7,9,11,m,M etc...)"""
#Change this to a map or something
key = key.replace('9', '')
key = key.replace('7', '')
key = key.replace('5', '')
key = key.replace('m', '')
key = key.replace('M', '')
return key | 5aa910f96dce275f9e4b6af7926179e73a2c313d | 55,688 |
def validate_digits(digits):
"""Validate digits parameter."""
if digits is None:
return None
try:
digits = int(digits)
except ValueError as e:
raise ValidationError("Digits must be a valid integer value") from e
if digits < 6 or digits > 8:
raise ValidationError("Digi... | 0b1ef0f6b71efeb7b08379ff3d899f5aaa6c7a46 | 55,689 |
def inet_aton(ipaddress):
"""
Convert an IP address in presentation format to its integer octet format
"""
return struct_unpack("<I", struct_pack("<B<B<B<B", \
*map(int, ipaddress.split("."))))[0] | 12d97f46bc57d353c23124d2936d951475a6981a | 55,690 |
def create_cdr(src_cdr, dst_visit):
""" Create cdr """
dst_cdr, _ = dst.Cdr.get_or_create(
cdr_id=src_cdr.cdr_id,
subject_visit_id=dst_visit.subject_visit_id,
memory=src_cdr.memory,
orientation=src_cdr.orientation,
judge_prob_solving=src_cdr.judge_prob_solving,
c... | 1f8d5431c6010a207efe5e305e60a3e0089a941a | 55,692 |
def derived_something():
"""
A docstring template to describe the function.
This function is part of the unit test template
Returns
-------
An string with the word output
"""
print("This message shows that you have successfully imported \
the derived_something() function from the ... | 97586600645d87c557a1ebeb83e0f9e3a5c1381f | 55,693 |
def calculate_percent(x, y):
"""
计算百分比
:param x: 分子
:param y: 分母
:return: 百分比
"""
x = float(x)
y = float(y)
return safe_div(x, y) * 100 | d63e33462995573f4bab1e8bdc35c6d3eea98f9d | 55,694 |
def plot_histogram(filename, mydata, bins = 10, title = None, xlabel = None, ylabel = None, dpi = 150, figsize = (10,10), tfont = 17, lfont = 14):
"""
Plots a histogram for scalar timeseries.
"""
fig = plt.figure(figsize = figsize)
plt.hist(mydata, bins = bins)
if title:
plt.title(title,... | 06cd0b9a88fb4dbab67061a6cc188ba8bde50c3a | 55,695 |
def _darknet_body(x, for_small=False):
"""Darknent body having 52 Convolution2D layers"""
x = _darknet_conv_bn_act(32, (3, 3), "block1_conv1")(x)
x = _darknet_resblocks(x, 64, 1, block_index=2, downsampling=not for_small)
x = _darknet_resblocks(x, 128, 2, block_index=3)
x = _darknet_resblocks(x, 256... | 8fbfc4475c05c57c5c5119e601e3cdcf082b1280 | 55,696 |
from typing import List
import random
import string
def get_addresses(n=50) -> List[dict]:
"""
Generate random addresses
"""
def _get_address() -> dict:
return {
"name": "John Doe",
"companyName": "Test Co",
"streetAddress": "{} Test St".format(random.randi... | e125abb419cfeb9e06c2c0930f5e3082baa01b72 | 55,697 |
def share_post_friends(request, author_id, post_id):
"""
**[Internal]** <br>
## Description
POST to the endpoint to reshare a post. the server will create a new, reshared post,
and forward it to the corresponding followers' inboxes.
## Request
nothing, but requires to be authenticated as t... | 54964d3179c25b3f8e2c4d317f69ad81996bf0b2 | 55,698 |
def equal_weighting(X, types):
"""
Calculate criteria weights using objective Equal weighting method
Parameters
----------
X : ndarray
Decision matrix with performance values of m alternatives and n criteria
types : ndarray
Returns
-------
ndarray
... | a769da203c9c10a488d650c11272bb544b523133 | 55,699 |
def prelu(features, initializer=None, scope=None):
"""
Implementation of [Parametric ReLU](https://arxiv.org/abs/1502.01852) borrowed from Keras.
"""
with tf.variable_scope(scope, 'PReLU', initializer=initializer):
alpha = tf.get_variable('alpha', features.get_shape().as_list()[1:])
pos ... | f0d4e9f32f314bdc541085e18e76c24cb7bb536a | 55,700 |
def create(hilbert, site):
"""
Builds the boson creation operator acting on the `site`-th of the
Hilbert space `hilbert`.
If `hilbert` is a non-Bosonic space of local dimension M, it is considered
as a bosonic space of local dimension M.
:param hilbert: The hilbert space
:param site: the ... | b775520a9b366e097cbfbedfd6b229580dfc52c3 | 55,701 |
async def list_items():
"""
Get all items
"""
items = await get_all_objects('items')
return items | e38e3f8f12928c10ce9b627f6ef5da7a2ce67c61 | 55,702 |
import re
def url_matches(pattern):
"""An expectation for checking the current url.
pattern is the expected pattern, which must be an exact match
returns True if the url matches, false otherwise."""
def _predicate(driver):
return bool(re.search(pattern, driver.current_url))
return _predic... | c7a613efff1828c5cf79471e3bc534f78fade3fc | 55,703 |
def create() -> MailboxID:
"""
Create a new mailbox.
:returns: The mailbox unique identifier
"""
mid = str(uuid4())
mailbox_registry = context_mailbox_registry.get()
mailbox_registry[mid] = trio.open_memory_channel(0)
return mid | dbb02fd1dcfd731f614b8ad6267eb31661f6ea1a | 55,704 |
import math
def layout_roboport_row(bus, width):
"""Return layout for a row of roboports covering an x region out to width,
including the bus lines needed.
"""
layout = Layout("roboports")
# Underpasses. Note these are shorter underpasses, without pumps.
for bus_pos, line in enumerate(bus):
bus_x = BUS_STAR... | d9d933fea140fc9e83cff893d38561533f18fbb5 | 55,705 |
def open_threads_window(*args):
"""
open_threads_window() -> TWidget *
Open the threads window ( 'ui_open_builtin' ).
@return: pointer to resulting window
"""
return _ida_kernwin.open_threads_window(*args) | 838986349ea25321c3d36a6996d56a80f4d76ca3 | 55,706 |
def delete(ground_station_id):
"""JRPC method: configuration.gs.delete
Deletes the ground station identified by the given 'ground_station_id'. It
also deletes all channels associated to this ground station.
:param ground_station_id: Identifier of the Ground Station
"""
segment_models.GroundStat... | 763f13b68857113cb52c0d30c5e4f6efa44c6454 | 55,707 |
from sage.misc.superseded import deprecation
def standard_form(sp):
"""
Deprecated in :trac:`14140`. Use :meth:`SetPartition.standard_form()`
instead.
EXAMPLES::
sage: map(sage.combinat.set_partition.standard_form, SetPartitions(4, [2,2]))
doctest:1: DeprecationWarning: standard_form... | c6efcae436f517497e24cd0602e112da927426dd | 55,708 |
def article(text, accesskey:str ="", class_: str ="", contenteditable: str ="",
data_key: str="", data_value: str="", dir_: str="", draggable: str="",
hidden: str="", id_: str="", lang: str="", spellcheck: str="",
style: str="", tabindex: str="", title: str="", transla... | 6eafaedf9d53ca0269162093688b301b8ed77d53 | 55,709 |
def question_reply_committees():
"""
A list of those committees that have received questions and replies.
We might want to generalise this at some point
"""
items = Committee.for_related(QuestionReply).all()
return send_api_response(serializers.queryset_to_json(items, count=len(items))) | 137b8b4abb3ae92d7b2344e43c00618f095f7a1e | 55,710 |
def select_cross_event(slclist, event_date, num_igrams=None):
"""Choose a list of independent igrams spanning `event_date`"""
insert_idx = np.searchsorted(slclist, event_date)
num_igrams = num_igrams or len(slclist) - insert_idx
# Since `event_date` will fit in the sorted array at `insert_idx`, then
... | c8b2c74115edf14e66b1c72a3798931d7a6a8300 | 55,712 |
def host_list_route():
"""list hosts"""
return render_template('storage/host/list.html') | 22ad2c63f93b478280887c80b901d495533b56ee | 55,713 |
import re
def _prepare_date(from_date):
"""
Private function to prepare from_date by converting
it to YYYY-MM-DD format.
"""
# check if from_date was provided and if it was provided in the right
# format
from_date_str = None
if from_date is not None:
if not isinstance(from_date... | 2766138027a1a2cc89e66370d792e2a317f6aa21 | 55,714 |
def ssa_full(time_series, embedding_dim=20, reconstruct_components=np.arange(10)):
"""
combine SSA decomposition and reconstruction together
"""
pc, s, v = ssa_decompose(time_series, embedding_dim)
time_series_reconstructed = ssa_reconstruct(pc, v, reconstruct_components)
return time_series_re... | 6ad6c0b02af9b0513dbdeb94d647c64481b7c31f | 55,715 |
def create_corpus_dir(corpus):
"""Create the directory to hold the various forms of the corpus written to disk.
:param corpus: a corpus model object.
:returns: an absolute path to the directory for the corpus.
"""
corpus_dir_path = get_corpus_dir_path(corpus)
h.make_directory_safely(corpus... | 0b206cd7f3451806538971f6722f6dbd1cc6d742 | 55,717 |
from datetime import datetime
def fixtures(request, week):
"""
render the fixtures full page
"""
#get closest week from today's date
today = datetime.datetime.now().strftime(settings.DATE_FORMAT)
if week:
if not isWeekValid(week):
raise Http404
else:
we... | cf001f0409d017eb749d8e67c3e4075f737f58c4 | 55,718 |
import copy
import torch
def get_loss(cfg_loss):
"""
Build the loss with the proper parameters and return it.
Parameters
----------
cfg_loss : dict
Dictionary containing the name of the loss to use and it's specific configs.
Returns
-------
loss_function : function
Th... | 88bacc521eee93c2a8c8d73a829a57f5d02bfdbd | 55,719 |
def coplanar_points(points: ty.Union[ty.List['Point'], np.ndarray],
tol: ty.Optional[float] = None) -> bool:
"""Returns True if the poins are coplanar
Parameters
----------
points : List[Point], np.ndarray
The list of points or MxN array of point coords
tol : float, None... | d0920136020b1e9424053be13a296d5c764f5aac | 55,720 |
from datetime import datetime
def dev_offline(file):
"""
do online prediction. each time make prediction for one instance.
you can change to a batch if you want.
:param line: a list. element is: [dummy_label,text_a,text_b]
:return:
"""
def convert(line, bmeo_label, attr_label):
fe... | 1e9ee43d5399bcec423506987e8a0048078acfe9 | 55,721 |
def select(data: xarray.DataArray, max_seen_frac) -> xarray.DataArray:
"""
Removes stationary stations from data, based on histogram of SSID.
1. get a list of all the BSSIDs seen across time
2. get SSIDs that are not seen persistently vs. time
The code below is not necessarily the most efficient ... | a232217f02345943bea2b365ffd70d9f54085730 | 55,722 |
def _fix_params(params):
"""For v1 api -- True is True but False is a string"""
for key, val in params.items():
if val is False or str(val).lower() == 'false':
params[key] = 'False'
elif str(val).lower() == 'true':
params[key] = True
return params | 1629cf618153c10169e2b963c99f06ef2e453075 | 55,725 |
def printDihedral(dihedral):
"""Generate dihedral line
Parameters
----------
dihedral : dihedral Object
dihedral Object
Returns
-------
dihedralLine : str
dihedral line data
"""
V1 = dihedral.V1*0.5*kcalToKj
V2 = dihedral.V2*0.5*kcalToKj
V3 = dihedral.V3*0.... | 4d8ff81a6361e86d6ab8f7fc865aa8ea36a3aad1 | 55,726 |
def getNDEllipse(u, v, pt):
"""
Get an N-dimensional ellipse point cloud
Parameters
----------
u: ndarray(1, N)
First axis
v: ndarray(1, N)
Second axis
pt: ndarray(M)
Parameterization in the interval [0, 1]
"""
t = 2*np.pi*pt
t = t[:, None]
return np.c... | ef95d9eef5dba75a8eec46db3c07e6e1cf25b2c2 | 55,728 |
import csv
def difference(old_file, new_file):
"""
Make a difference between an old csv file and a new one; get the full row if it's different
:return:
"""
old_results = list(csv.reader(open(old_file, 'r'), delimiter=';'))
new_results = list(csv.reader(open(new_file, 'r'), delimiter=';'))
... | dc5f346a17d96cf8c10b71135d8ed0d133d1089b | 55,729 |
def bte_float_input(than, text='', error_text="Enter number between ", error_text_format_bool=True,
error_text_format="Enter number great and less or equal than {}", pause=True, pause_text_bool=True,
pause_text='Press Enter...', clear=True, error_text_input="Enter float number!",... | b7ae0e2846d998f5b928dfa791a557eb915cb01c | 55,730 |
def get_public_key_bytes_compressed(public_key: ec.EllipticCurvePublicKey) -> bytes:
"""Return the bytes of a pubkey in the compressed format."""
return public_key.public_bytes(Encoding.X962, PublicFormat.CompressedPoint) | 7661f0e28e3aec45508a1ba2dc3e5ce7501eae72 | 55,731 |
def __generate_adaptive_random_samples(input_points, aspect_ratio_scaling, centralized,
num_samples=8182, bandwidth=0.2):
""" Generates samples for Lloyd relaxation, following the density distribution of the input
data.
Args:
input_points (List[float]): 1D-Arr... | 0e9654e5773871e005d266e9ade2d9e44a1b4498 | 55,732 |
def split_nav_dataframe(nav_table, split_date):
"""
Split NAV pandas DataFrame into
a training and a testing DataFrame according to a split_date,
such that split_date becomes the last date of the
training DataFrame.
Args:
- split_date (datetime.datetime)
Returns:
- train: th... | 78c6ae901641b3508d2a9f9c790be6d576cf8458 | 55,733 |
def get_episodes_count(episode_list, max_val):
"""
This method is used to count the count of episode_list value which is bigger than 30
:param episode_list:
:return:
"""
return len([x for x in episode_list if x > max_val]) | fc49154c644c1807e818e0b598c680878e342767 | 55,734 |
def find_groups_in_cluster(clustervs, elementgroupList):
"""
A utility function to find vertices with the same cluster
memberships.
:param igraph.vertex clustervs: an igraph vertex instance
:param list elementgroupList: a list containing the vertices to group
:returns:
a list-of-list... | 7cc941d086d7be7c7395e21f6bde1cd4e5611851 | 55,735 |
def calculate_CE_per_group(samples, test_contribs, group_names, all_groups_toks, n_words_per_contrib):
"""
Calculates the Cross-Entropy between each combination of groups.
:param samples: contributions for training snapshot models.
:param test_contribs: contributions for comparing to snapshots.
:pa... | 8ae9ba2baffcdaae4d5b63ec2440bc30bbccfc50 | 55,736 |
def svn_io_file_checksum2(*args):
"""svn_io_file_checksum2(char const * file, svn_checksum_kind_t kind, apr_pool_t pool) -> svn_error_t"""
return _core.svn_io_file_checksum2(*args) | 35cd0c60bc9da84d401842d455e0079a9e69aac1 | 55,738 |
from datetime import datetime
import logging
def parse_date_arg(arg_str, oldest_allowed_date=None, max_days_since_now=None):
"""Parse request arg as date with limits on oldest allowed date or max days since now.
Accepts date format %Y-%m-%d.
Args:
arg_str: str request arg to parse.
oldes... | 108e1c95968f50845156c9ae6a76373e661f1cd4 | 55,740 |
import csv
def readbalfour(fname):
"""returns list of lists representing balfour csv"""
with open(fname, "r") as f:
reader = csv.reader(f, delimiter="\t", quotechar="\"")
return list(reader) | d48071ff01bee67c13c38a6ca0ed22064b6bdca6 | 55,741 |
def computeCycleConsistencyLoss(x, x2, y, y2):
"""
This function is used to compute the cycle consistency loss
The equation is Equation(6) in Chp6
:param x:
:param x2:
:param y:
:param y2:
:return:
"""
# MSE Loss and Optimizer
criterion = nn.MSELoss()
c_loss = criterion(x... | e8ccfdf19970034073ce94630caa3b7a2c13da6c | 55,742 |
def post_kwargs(body: BodyModel, query: QueryModel):
"""
Basic example with both query and body parameters, response object serialization.
This time using the decorated function kwargs `body` and `query` type hinting
"""
# save model to DB
id_ = 3
return ResponseModel(id=id_, age=query.age,... | d7aac311a54bbfdd69af878c0af71318a0d9cda8 | 55,744 |
def getMeanDouble_Image8(Image):
"""getMeanDouble_Image8(Image) -> double"""
return _ImageFunctions.getMeanDouble_Image8(Image) | d79ecce92a26af4e601e131d83fc5be2567a4eb2 | 55,745 |
def vbObjectInitialize(size=None, objtype=None, preserve=None):
"""Return a new object with the given size and type"""
if size is None:
size = [0]
#
# Create the object
def getObj():
if len(size) == 1:
return objtype()
else:
return vbObjectInitialize(... | aa68220018cf7982787c2e67598f89fe1383c4c4 | 55,746 |
def sam_to_sortbam_cl(data, tx_out_file, name_sort=False):
"""Convert to sorted BAM output.
Set name_sort to True to sort reads by queryname
"""
samtools = config_utils.get_program("samtools", data["config"])
cores, mem = _get_cores_memory(data, downscale=2)
tmp_file = "%s-sorttmp" % utils.spli... | 3e3cbc5ed3c3b852c3846cc9a9b95c3144db96a3 | 55,747 |
import html
from typing import Container
def page():
"""Creates a page for demands"""
team_id, set_team_id = use_state("")
epic_id, set_epic_id = use_state("")
year_month, set_year_month = use_state("")
days, set_days = use_state("")
is_event, set_is_event = use_state(False)
return html.di... | 9788087f99d60ba0dcb1c6fc948f237be128432b | 55,749 |
import torch
def create_mock_data(num_nodes, num_features, num_classes=3, eta=0.1, p=0.2):
"""
Creating a mock feature matrix, edge index and edge weight.
"""
(A_p_scipy, A_n_scipy), labels = SSBM(num_nodes, num_classes, p, eta)
X = torch.FloatTensor(np.random.uniform(-1, 1, (num_nodes, num_featur... | 9ee11920e99f5ef3a857a72370a1e4de1d0fcb16 | 55,750 |
def loss_v0(args, pred, target, conf, cost):
"""loss version 0
Arguments are
* args: command line arguments entered by user.
* pred: prediction result of each exit point.
* target: target prediction values.
* conf: confidence value of each exit point.
* cost: cost rate of ... | d9a6be3b321fe279e7e05cd28158bc202e4657c1 | 55,751 |
def rmsd(V, W):
"""
Calculate Root-mean-square deviation from two sets of vectors V and W.
Parameters
----------
V : np.array
(N,D) matrix, where N is points and D is dimension.
W : np.array
(N,D) matrix, where N is points and D is dimension.
Returns
-------
fit : f... | bab88a8e149f0f20c5c8aca4153b0da880517628 | 55,752 |
import json
def sync_ckan_allowed_users_by_resource(*args, **kwargs):
"""Synchroniser `ckan-restricted` pour le cas particuliers
des autorisations par organisation.
"""
def get_all_users_for_organisations(organisation__in):
filter = {'organisation__in': organisation__in,
'or... | 1398ef166793223980489aa73b60c0afe3c1b12b | 55,753 |
import base64
def numpy_to_b64str(img, format="JPG"):
"""
Converts a numpy array into a base 64 string
Args:
img (np.array): the image represented as an Numpy Array
format: The format of the image to be converted into
Returns:
str: base 64 representation of the numpy array/im... | f58f7e95d09fdca6e5d968dde368b7f01adc7081 | 55,754 |
def resource_schedule(
tag_value: celtypes.Value,
) -> celtypes.Value:
"""
Reach into C7N and use the the :py:class:`c7n.filters.offhours.ScheduleParser` class
to examine the tag's value, the current time, and return a True/False.
This parser is the `parser` value of the :py:class:`c7n.filters.o... | 162fa3cdd0d5ec6dbf8203acdbf6bd44e6744c22 | 55,755 |
import json
def parse_history_event(directive_result):
"""Based on the type of event, parse the JSON.serializable portion of the event."""
event_type = directive_result.event_type
if event_type is None:
raise ValueError("EventType is not found in task object")
if event_type == HistoryEventTyp... | fba04a9d2c1ddf8dbaad0b9c92a04847cb65ed87 | 55,756 |
def get_private_key(cert_arn):
"""
Checks if an ACM certificate has an associated private key
stored in an SSM parameters, and returns the value.
"""
param_name = get_ssm_param_name(cert_arn)
try:
response = ssm.get_parameter(
Name=param_name,
WithDecryption=Tr... | 1f392fb24ee912bc10b27ed4324657d5f69a633b | 55,758 |
def unparse_vs(tup):
"""version list to string"""
return '.'.join(map(str, tup)) | 4c4f4d8fb02bffd676b2a4d87118eaf55cb0afe8 | 55,761 |
import base64
def encryptstring(text, password):
"""
Encrypt a string according to a specific password.
:type text: string
:param text: The text to encrypt.
:type pass: string
:param pass: The password to encrypt the text with.
"""
enc = []
for i in enumerate(text):
key_... | 46142bc54828058bf131834fa13276da78e90842 | 55,762 |
from typing import Tuple
def ts2xy(data_frame: pd.DataFrame, x_axis: str) -> Tuple[np.ndarray, np.ndarray]:
"""
Decompose a data frame variable to x ans ys
:param data_frame: the input data
:param x_axis: the axis for the x and y output
(can be X_TIMESTEPS='timesteps', X_EPISODES='episodes' or... | 444286f2391be76944d059cda4e0954b2f7d05c7 | 55,763 |
import fractions
def strategy_for_grain_attribute(attr, grain_type=None):
"""Returns a default strategy for generating data compatible with a particular attribute of a particular grain_type
:param attr: a string, the name of an attribute of one of the GRAIN subclasses
:param grain_type: some grains types... | 487ca42bcdcef1bc8beeccbdec623387ae522fc4 | 55,764 |
def ldns_dnssec_zone_sign_nsec3_flg_mkmap(*args):
"""LDNS buffer."""
return _ldns.ldns_dnssec_zone_sign_nsec3_flg_mkmap(*args) | aec6df122fd6eed61e21b39011f46091dcd8129d | 55,766 |
import torch
def DSConv(in_channels: int, out_channels: int, stride: int = 1, **kwargs):
"""Depth-wise separable convolution followed by a 2D convolution
each followed by a batch normalization and ReLU activation.
"""
return torch.nn.Sequential(
torch.nn.Conv2d(
in_channels, in_cha... | 89df37f79ff9bd6c6fe31c3001bb6d725fac8a2a | 55,767 |
def hist_from_samples(x, num_bins=100):
"""Returns a histogram with the specified number of bins from the array of
samples, x"""
x_density = np.histogram(x.ravel(), bins=num_bins)[0] + 1
return x_density / np.sum(x_density) | 086921df1def87718732523e4f54202c59a22a54 | 55,768 |
import torch
def compute_cer(predictionBatch, targetBatch, predictionLenBatch, targetLenBatch):
"""
Function to compute the Character Error Rate using the Predicted character indices and the Target character
indices over a batch.
CER is computed by dividing the total number of character edits (comput... | 696b64308eb2786d013f210cae0557087392c4ba | 55,769 |
import torch
def top_pool(x): # from right to left
"""
:param x:feature map x, a Tensor
:return: feature map with the same size as x
"""
x_p = torch.zeros_like(x)
x_p[:, :, :, -1] = x[:, :, :, -1]
_, _, h, w = x.size()
for col in range(w - 1, -1, -1):
x_p[:, :, :, col] = x[:, ... | 7222d018a59270daf4041109e7979718ff4c68a6 | 55,770 |
def test_learning_four_mode_Interferometer():
"""Finding the optimal Interferometer to make a NOON state with N=2"""
np.random.seed(11)
ops = [
Sgate(
r=np.random.uniform(size=4),
phi=np.random.normal(size=4),
r_trainable=True,
phi_trainable=True,
... | 900fd7daa53197b92e2e248ea8c4420a064a53e0 | 55,771 |
def slug(name):
"""
Slugifies a division name.
"""
return unidecode(str(name).lower().translate({
ord(' '): '_',
ord("'"): '_',
ord('-'): '_', # dash
ord('—'): '_', # m-dash
ord('–'): '_', # n-dash
ord('.'): None,
})) | 44683b7cd04182a0d8e7fbc42072f1ecfa3b18fa | 55,772 |
def status(request):
"""API view for status list"""
data = list(Faculty.objects.values_list('status', flat=True).distinct().order_by('status')) # wrap in list(), because QuerySet is not JSON serializable
return JsonResponse(data, safe=False) | 39f419d31f4488e4d2e062d6a42117f9208ea9b4 | 55,773 |
def ns(relative_name):
"""Return a full name from a name relative to the tested module"s name space."""
return NS + "." + relative_name | 3ab9f1213c6f3b139c29d11685d27ecf1b7bf587 | 55,774 |
def listofdict_topn_sorter(raw_listofdict, attr_key, reverse=True):
"""
对 list of dict 数据结构排序
:param raw_listofdict:
:param attr_key: 指定要排序的attr, eg 分数高低，成本高低.
:param reverse: True 倒排从大到小.
:return: 1) raw数据不变 2)排序后返回原始index 3)排序后可获得需求attr.
"""
sorted_res = sorted(enumerate(raw_listofdict... | 8dfb7a60dd7e904d99a3896908cd213d34e1a922 | 55,775 |
from scipy.optimize import linear_sum_assignment as linear_assignment
def eval_acc(y_true, y_pred):
"""
Calculate clustering accuracy. Require scikit-learn installed.
# Arguments
y: true labels, numpy.array with shape `(n_samples,)`
y_pred: predicted labels, numpy.array with shape `(n_samp... | 03935f1916f15627e2bbf4c016af252ba54b7854 | 55,777 |
def read_nii_bysitk(input_fid, peel_info = False):
""" read nii to numpy through simpleitk
peelinfo: taking direction, origin, spacing and metadata out
"""
img_obj = sitk.ReadImage(input_fid)
img_np = sitk.GetArrayFromImage(img_obj)
if peel_info:
info_obj = {
"spacin... | 0a8af67bd348c9170cc0b5abddb691da433e0f5f | 55,778 |
def build_user_secrets(seed: bytes, name: str,
seed_method: SeedMethod = SeedMethod.SEED_METHOD_BIP39,
password: str = '') -> KeyPairSecrets:
"""
Build a valid key pair secrets for User.
:param seed: User key seed
:param name: User key name
:param seed_m... | bc138f2cc803d5029bf1db03d31454a2baf98ed9 | 55,779 |
def _get_answers_on_path(answers, schema, routing_path) -> AnswerStore:
"""
Get any answers that are on the routing path and return an answer store.
"""
answers_to_remove = [answer for answer in answers if not _is_answer_on_path(schema, answer, routing_path)]
answers_on_path = answers.copy()
f... | 57578ff326246f34ab6da605f9b7304552f197ea | 55,780 |
def e_mag2frac(errmag):
"""Convert mag error to fractionary flux error"""
return 10.**(.4 * errmag) - 1. | 470415550968f0db7dc016c41b4c1f0552ba9893 | 55,781 |
def compare_user(passed_user=None, user_list=None):
"""Check if supplied User instance exists in supplied Users list and, if so, return the differences.
args:
passed_user (User): the user instance to check for differences
user_list (Users): the Users instance containing a list of Users instance... | 9f00a7548bc67075b491305f0d43b4f8c859f62f | 55,782 |
def choose_template_by_blasr(fasta_filename, out_filename, nproc=8,
maxScore=-1000, min_number_reads=1):
"""
Choose the best template for gcon reference
Pick the one that has the highest average hit identity to others
Returns: FastaRecord of selected ref
"""
fd = Fa... | 588f503d0cb910c7fc8db92e537e7c77568cdee1 | 55,783 |
def check_padding(query):
"""
Check for missing padding in base64 encoding and fill it up with "=".
:param query:
:return: query
"""
missing_padding = len(query) % 4
if missing_padding:
query += "=" * (4 - missing_padding)
return query | d8ad3c96074d311dbd5ba17bb93d7ca7a8b5ccab | 55,784 |
import inspect
def _get_method_classname(m):
"""Get class name for method, assuming method is bound and class has __dict__."""
for k, v in inspect.getmembers(m):
if k == "__qualname__":
return v
return "<unknown>" | 88edafc4e3319ad32e2a77feed4dfb7e14f1bd4c | 55,785 |
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