content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
from datetime import datetime
def index(request):
"""Magicaltastic front page.
Plugins can register a hook called 'frontpage_updates_<type>' to add
updates to the front page. `<type>` is an arbitrary string indicating
the sort of update the plugin knows how to handle; for example,
spline-forum h... | 14e4200c2277e48792fd4d02f0126293a82a9ba8 | 16,200 |
def fd_d1_o4_smoothend(var,grid,mat=False):
"""Centered finite difference, first derivative, 4th order using extrapolation to get boundary points
var: quantity to be differentiated.
grid: grid for var
mat: matrix for the finite-differencing operator. if mat=False then it is created"""
dx = grid[1]... | e1b57204e6fd9fe2839e4fb2e7230dd0f8854841 | 16,201 |
def find_node_pair_solutions(node_pairs, graph):
""" Return path and cost for all node pairs in the path sets. """
node_pair_solutions = {}
counter = 0
for node_pair in node_pairs:
if node_pair not in node_pair_solutions:
cost, path = dijkstra.find_cost(node_pair, graph)
... | f2f742cc1e969b4b60394148508cbb9cacaa3cfc | 16,202 |
import math
def get_step(a, b, marks=1):
"""Return a coordinate set between ``a`` and ``b``.
This function returns a coordinate point between the two provided
coordinates. It does this by determining the angle of the path
between the two points and getting the sine and cosine from that
angle. The... | e242823df263f1cee28409ef3f984f9b3066dad5 | 16,203 |
import torch
def get_model_mask_neurons(model, layers):
"""
Defines a dictionary of type {layer: tensor} containing for each layer of a model, the binary mask representing
which neurons have a value of zero (all of its parameters are zero).
:param model: PyTorch model.
:param layers: Tuple of laye... | 2e24af14d05802bac69b65a225ce284b5a7785e7 | 16,204 |
def connection():
"""Open a new connection or return the cached existing one"""
try:
existing_connection = GLOBAL_CACHE[CACHE_KEY_CONNECTION]
except KeyError:
new_connection = win32com.client.Dispatch(ADO_CONNECTION)
new_connection.Provider = CONNECTION_PROVIDER
new_connectio... | f2c09fac89e0b0c9f9894869bb559ce61bca942a | 16,205 |
import subprocess
def getRigidAtoms():
"""Returns atoms in rigid bodies in PDB"""
atoms = []
fileName = pdbs[0]
subprocess.call(["kgs_prepare.py", fileName])
f = open(fileName[:-4] + ".kgs.pdb", "r")
lineList = f.readlines()
f.close()
if connectivity and not "CONECT" in lineList[-1]:
... | 63a903a7a7a7f99c2d6bcd36329a07845dd327d5 | 16,206 |
def precision(theta,X,Y):
"""
accuracy function
computes the accuracy of the logistic model theta on X with true target variable Y
"""
m = np.shape(X)[0]
H = sigmoid(np.dot(X,theta))
H[H >= 0.5] = 1
H[H < 0.5] = 0
return np.sum(H == Y)/m | e3b2c1c613f5ae2f20b2b9a8e6e343348be845df | 16,207 |
def get_converter(obj, coords=None, dims=None, chains=None):
"""Get the converter to transform a supported object to an xarray dataset.
This function sends `obj` to the right conversion function. It is idempotent,
in that it will return xarray.Datasets unchanged.
Parameters
----------
obj : A ... | ee293672d74de5f0e1de0ff25c806fa10327c71c | 16,208 |
import pytz
def timezone_by_tzvar(tzvar):
"""Convert a WWTS tzvar to a tzdata timezone"""
return pytz.timezone(city_by_tzvar(tzvar)) | 0bc4d634ca5fcc55ceed062ae06fbe2eefb6c11a | 16,209 |
import json
def group_recommend(request):
"""
Get or post file/directory discussions to a group.
"""
content_type = 'application/json; charset=utf-8'
result = {}
if request.method == 'POST':
form = GroupRecommendForm(request.POST)
if form.is_valid():
repo_id = form... | 1821eba9f2144ac5e9b6b9a4c5c8d935b3dd5e08 | 16,210 |
def easy_map(parser, token):
"""
The syntax:
{% easy_map <address> [<width> <height>] [<zoom>] [using <template_name>] %}
The "address" parameter can be an Address instance or a string describing it.
If an address is not found a new entry is created in the database.
"""
width, height, z... | b2968f6ff3cde324711f84a5b449fbab92cc22fa | 16,211 |
import six
def pack_feed_dict(name_prefixs, origin_datas, paddings, input_fields):
"""
Args:
name_prefixs: A prefix string of a list of strings.
origin_datas: Data list or a list of data lists.
paddings: A padding id or a list of padding ids.
input_fields: A list of input fiel... | 2946a8869cac26737f6c5b6234ce0320cfdf5bcf | 16,212 |
def get_session_maker():
"""
Return an sqlalchemy sessionmaker object using an engine from get_engine().
"""
return sessionmaker(bind=get_engine()) | 2f1a500cf799910f98e7821582cb78d063eeb273 | 16,213 |
def rescale_intensity(arr, in_range, out_range):
""" Return arr after stretching or shrinking its intensity levels.
Parameters
----------
arr: array
input array.
in_range, out_range: 2-tuple
min and max intensity values of input and output arr.
Returns
-------
out: arra... | 580c789a6eb2ad03bcbdefd8e5f27b0c6a239f32 | 16,214 |
import traceback
import sys
def get_error_info():
"""Return info about last error."""
msg = "{0}\n{1}".format(str(traceback.format_exc()), str(sys.exc_info()))
return msg | 539a26f0a6bd6b733aa6e6ff1325faac6a32be12 | 16,215 |
import requests
def call_oai_api(resumption_token):
"""
Request page of data from the Argitrop OAI API
Parameters
----------
resumption_token : object (first page) or string or xml.etree.ElementTree.Element
token returned by previous request.
Returns
-------
response_xml : st... | e69ec11f75676a94134f4541b421391367ab1e3c | 16,216 |
import yaml
def save_pano_config(p):
"""
saves a panorama config file to the local disk from the session vars.
:return:
"""
filename = get_filename(p)
with open(filename, 'w') as yml_fh:
yml_fh.write(yaml.dump(session[p + '_config'], default_flow_style=False))
return redirect("/... | 6a2575af4fe54caed7ce812d3fc2a876424912f7 | 16,217 |
import os
def append_source_filess(index_filename, source_files, driver):
"""This appends the paths to different source files to the temporary index file
For example
SRCSRV: source files ---------------------------------------
c:\php-sdk\phpdev\vc15\x86\php-7.2.14-src\ext\pdo_sqlsrv\pdo_dbh.cpp*pdo_... | e26252740c2c64b581d4be56e25086216bc36e1b | 16,218 |
def is_transport(name):
"""Test if all parts of a name are transport coefficients
For example, efe_GB, chie_GB_div_efi_GB are all composed of transport
coefficients, but gam_GB and chiee_GB_plus_gam_GB are not.
"""
transport = True
try:
for part_name in extract_part_names(split_parts(na... | 1aea3915680b3c74422cbd7648fd920719dd3cc8 | 16,219 |
def detect_moved_files(file_manifest, diff):
""" Detect files that have been moved """
previous_hashes = defaultdict(set)
for item in file_manifest['files']: previous_hashes[item['hash']].add(item['path'])
diff_dict = make_dict(diff)
# files with duplicate hashes are assumed to have the same conten... | db97dfb88d4fa253351e149dacf68a9fa3043072 | 16,220 |
def decodecaps(blob):
"""decode a bundle2 caps bytes blob into a dictionary
The blob is a list of capabilities (one per line)
Capabilities may have values using a line of the form::
capability=value1,value2,value3
The values are always a list."""
caps = {}
for line in blob.splitlines(... | 3c18bbe6b4b6a0562719d4992d6937d60f6bc114 | 16,221 |
from typing import Tuple
import os
def create_feature_columns() -> Tuple[list, list, list, list, list]:
"""
Returns:
dense_feature_columns (list): 连续特征的feature_columns
category_feature_columns (list): 类别特征的feature_columns
target_feedid_feature_columns (list): 目标feed的feature_columns
... | 292497e6228e858e98b69350fb6507a0346efd16 | 16,222 |
def an(pos=5):
"""
Alineamiento del texto.
@pos:
1: Abajo izquierda
2: Abajo centro
3: Abajo derecha
4: Mitad derecha
5: Mitad centro
6: Mitad derecha
7: Arriba izquierda
8: Arriba centro
9: Arriba derecha
"""
apos = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
if pos not... | fbe1e89282ebdf7b4977bee295e2cac7735bd652 | 16,223 |
def arista_output(accesslist):
"""Helper function to generate accesslist ouput appropriate for an
Arista switch/router. This will eventually get rolled up into
a output module or class."""
# I have studied the sacred texts from the merciless Trigger Dojo
# TODO: this should be refactored, i... | 7bebd68d76aa51c5965f5850731c47b220871a0b | 16,224 |
def main(iterator):
"""
Given a line iterator of the bash file, returns a dictionary of
keys to values
"""
values = {}
for line in iterator:
if not line.startswith('#') and len(line.strip()) > 0:
match_obj = line_regex.search(line)
if match_obj is not None:
key, value = match_obj.gr... | 16cc188b367200c317119348d9440d57faa322a9 | 16,225 |
def is_any(typeref: irast.TypeRef) -> bool:
"""Return True if *typeref* describes the ``anytype`` generic type."""
return isinstance(typeref, irast.AnyTypeRef) | 75ca055529fea35dfeb2519c3de61bf3739ce1f7 | 16,226 |
from typing import Union
def repeat_1d(inputs: tf.Tensor, count: Union[tf.Tensor, int], name="repeat_1d"):
"""Repeats each element of `inputs` `count` times in a row.
'''python
repeat_1d(tf.range(4), 2) -> 0, 0, 1, 1, 2, 2, 3, 3
'''
Parameters:
inputs: A 1D tensor wit... | 44a8bb29dcd2ba0e2e5970aff1eab94b85a34c13 | 16,227 |
import logging
def create_logger(logfile=r"/tmp/tomoproc.log"):
"""Default logger for exception tracking"""
logger = logging.getLogger("tomoproc_logger")
logger.setLevel(logging.INFO)
# create the logging file handler
fh = logging.FileHandler(logfile)
fh.setFormatter(
logging.Formatt... | a0c005c39af9d24d7198790cf0cfe31a1b6395a0 | 16,228 |
async def async_setup(opp: OpenPeerPower, config: ConfigType) -> bool:
"""Set up the Twente Milieu components."""
async def update(call) -> None:
"""Service call to manually update the data."""
unique_id = call.data.get(CONF_ID)
await _update_twentemilieu(opp, unique_id)
opp.servic... | f2c0dd14e9193b9fa3ae3ea87689e90d9eb2c1bc | 16,229 |
import re
def parsePDCfile(fpath='data/CPTAC2_Breast_Prospective_Collection_BI_Proteome.tmt10.tsv'):
"""
Takes a PDC file ending in .tmt10.tsv or .itraq.tsv and creates
tidied data frame with Gene, Patient, logratio and diffFromMean values
Parameters
----------
fpath : chr, optional
... | 48b421d965e9b7f337a1f58c3665643eba514a7c | 16,230 |
def ave(x):
"""
Returns the average value of a list.
:param x: a given list
:return: the average of param x
"""
return np.mean(x) | ad7737321d9f0fc8461129b0153f40da2d75dc70 | 16,231 |
def information_gain(f1, f2):
"""
This function calculates the information gain, where ig(f1,f2) = H(f1) - H(f1|f2)
Input
-----
f1: {numpy array}, shape (n_samples,)
f2: {numpy array}, shape (n_samples,)
Output
------
ig: {float}
"""
ig = entropyd(f1) - conditional_entropy... | 39c60bf6a9fbf18f4d5ba3af609fed53771bd817 | 16,232 |
import os
def output_if_exists(filename):
"""Returns file name if the file exists
Parameters
----------
filename : str
File in question.
Returns
-------
str
Filename.
"""
if os.path.exists(filename):
return filename
return None | 7589e8c5f2a42013cb391cf2d10ad3a9f9cb46ed | 16,233 |
def subsequent_chunk_mask(
size: int,
chunk_size: int,
num_left_chunks: int=-1, ) -> paddle.Tensor:
"""Create mask for subsequent steps (size, size) with chunk size,
this is for streaming encoder
Args:
size (int): size of mask
chunk_size (int): size of chunk
... | 512def08ef2fe35cdd80ba7eb92f30b73aef1782 | 16,234 |
def top_tags(request):
"""
Shows a list of the most-used Tags.
Context::
object_list
The list of Tags
Template::
cab/top_tags.html
"""
return render_to_response('cab/top_tags.html',
{ 'object_list': Snippet.objects.top_item... | 07cf792fb3bd0ed5a1185986fb3154cb645b2a75 | 16,235 |
def check_integer_sign(value):
"""
:param value:
:return:
"""
return value >= 0 | 0ab012b62bf7b12ecabea8d1a4538bb30e197e07 | 16,236 |
import torch
def masks_empty(sample, mask_names):
""" Tests whether a sample has any non-masked values """
return any(not torch.any(sample[name] != 0) for name in mask_names) | 4c13b123fe6f5a17c3cd2ee673c54de331af7b23 | 16,237 |
def quantize_factor(factor_data, quantiles=5, bins=None, by_group=False):
"""
Computes period wise factor quantiles.
Parameters
----------
factor_data : pd.DataFrame - MultiIndex
A MultiIndex DataFrame indexed by date (level 0) and asset (level 1),
containing the values for a single... | 1b51b84e9f22a1b0e0c2bb578a2011c1b8f725e2 | 16,238 |
import os
def load_all_dbs(database_dir):
"""Load and return a ShowDB and TrackerDB.
Returns:
showdb: ShowDatabse instance
tracker: TrackerDatabase instance
"""
showdb = load_database(os.path.join(database_dir, '.showdb.json'))
tracker = load_database(os.path.join(database_dir, '... | 65fa856c2561cf54a4cc10dbf380f3c2fc5b97d3 | 16,239 |
def listSplit(aList, n):
"""将一个列表以n个元素为一个单元进行均分，返回嵌套列表"""
return [aList[i:i+n] for i in range(0,len(aList),n)] | 936d4ff5b3bbbc39c57c01dc6a12e42b7dc6e0de | 16,240 |
import json
def refs(request):
""" Настройка назначения анализов вместе """
if request.method == "GET":
rows = []
fraction = directory.Fractions.objects.get(pk=int(request.GET["pk"]))
for r in directory.References.objects.filter(fraction=fraction).order_by("pk"):
rows.appen... | 7635525efbdab8e22c21019f8de9cc74a83c9c2a | 16,241 |
def transform(data):
"""replace the data value in the sheet if it is zero
:param data: data set
:return: data set without zero
"""
data_transformed = data.applymap(zero2minimum)
return data_transformed | b717c6f42c8f0ae0c68c97647a33e77aec2f1508 | 16,242 |
def findChildren(node, name):
"""Returns all the children of input node, with a matching name.
Arguments:
node (dagNode): The input node to search
name (str): The name to search
Returns:
dagNode list: The children dagNodes
"""
return __findChildren(node, name, False) | 9258dac1261e24d3cc5e58030147ce693fbd0356 | 16,243 |
def get_process_rss(force_update=False, pid=None):
"""
<Purpose>
Returns the Resident Set Size of a process. By default, this will
return the information cached by the last call to _get_proc_info_by_pid.
This call is used in get_process_cpu_time.
<Arguments>
force_update:
Allows the caller ... | 99c1c3fd35db4bb22c2c37aba48ddb7049ec26fa | 16,244 |
from typing import Dict
def doc_to_dict(doc) -> Dict:
"""Takes whatever the mongo doc is and turns into json serializable dict"""
ret = {k: stringify_mongovalues(v) for k, v in doc.items() if k != "_id"}
ret["_id"] = str(doc["_id"])
return ret | 9e3f72568cf25ac864c1add2989c8e1cb064661d | 16,245 |
def add_srv_2cluster(cluster_name, srvjson):
"""
添加服务到数据库
:param cluster_name:
:param srvjson:
:return:
"""
status = ''
message = ''
resp = {"status": status, "message": message}
host_name = srvjson.get('host_name')
service_name = srvjson.get('service_name')
sfo_clu_node ... | 2e3c6ec6a312016785affbc71c5c2f178a0ecd84 | 16,246 |
def _add_left_zeros(number, iteration_digits):
"""Add zeros to the left side of the experiment run number.
Zeros will be added according to missing spaces until iterations_digits are
reached.
"""
number = str(number)
return f'{"0" * (iteration_digits - len(number))}{number}' | e3f86a7e7f276ceff4eb662a3f5bc364b4d10ea3 | 16,247 |
def sharpdiff(y_true, y_pred):
"""
@param y_true: tensor of shape (batch_size, height, width, channels)
@param y_pred: tensor of shape (batch_size, height, width, channels)
@return: the sharpness difference as a scalar
"""
def log10(tensor):
numerator = tf.math.log(tensor);
... | 0c08541fd5c551c5a2ca1afb598adfc627c06286 | 16,248 |
import logging
def admin_setfriend():
""" Set the friend state of a user """
uid = request.args.get("uid", "")
state = request.args.get("state", "1") # Default: set as friend
try:
state = bool(int(state))
except Exception:
return (
"<html><body><p>Invalid state string:... | f4b3a04b18735320968513666ad5901a68e5a492 | 16,249 |
def LF_CG_BICLUSTER_BINDS(c):
"""
This label function uses the bicluster data located in the
A global network of biomedical relationships
"""
sen_pos = c.get_parent().position
pubmed_id = c.get_parent().document.name
query = bicluster_dep_df.query("pubmed_id==@pubmed_id&sentence_num==@sen_p... | 29aeb5af69257a9c762bccc45c09e68d0799174c | 16,250 |
import argparse
def setup_argparse(parser: argparse.ArgumentParser) -> None:
"""Setup argument parser for ``cubi-tk org-raw check``."""
return OrganizeCommand.setup_argparse(parser) | fefbb3fd16905f353f9d6f98c3631024ca3e4e78 | 16,251 |
from typing import List
import random
def single_point_crossover(parents: List[Chromosome], probability: float = 0.7) -> List[Chromosome]:
""" Make the crossover of two parents to generate two child.
The crossover has a probability to be made.
The crossover point is random.
:param parents: selected p... | 4e8dd96fc42a8a1a1feb7c1c3dad42892e060425 | 16,252 |
def get_node_count(network=None, base_url=DEFAULT_BASE_URL):
"""Reports the number of nodes in the network.
Args:
network (SUID or str or None): Name or SUID of a network or view. Default is the
"current" network active in Cytoscape.
base_url (str): Ignore unless you need to specify... | c80e34443c4e39a96496eca5867333800b0208c5 | 16,253 |
from typing import Dict
from typing import Any
from typing import Tuple
from typing import Optional
import re
def process_sample(
sample: Dict[str, Any],
relation_vocab: Dict[str, int],
spacy_model: Any,
tokenizer: Any,
) -> Tuple[Optional[Dict[str, Any]], Dict[str, int]]:
"""Processes WebRED sample... | 74a80fb69fdebb35c86830f54344fc770ad91cd4 | 16,254 |
import tempfile
def transform_s3(key, bucket="songsbuckettest"):
"""
REMEBER TO DO DEFENSIVE PROGRAMMING, WRAP IN TRY/CATCH
"""
s3 = boto3.client('s3')
# print("connection to s3 -- Test")
with tempfile.NamedTemporaryFile(mode='wb') as tmp:
s3.download_fileobj(bucket, key, tmp)
... | 3e7419185ab3c3581ea24227c204fd207b113b1e | 16,255 |
def get_active_users(URM, popular_threshold=100):
"""
Get the users with activity above a certain threshold
:param URM: URM on which users will be extracted
:param popular_threshold: popularty threshold
:return:
"""
return _get_popular(URM, popular_threshold, axis=1) | 6b05e1a4288e00903ce9b396407c4e3547402710 | 16,256 |
def default_data_to_device(
input, target=None, device: str = "cuda", non_blocking: bool = True
):
"""Sends data output from a PyTorch Dataloader to the device."""
input = input.to(device=device, non_blocking=non_blocking)
if target is not None:
target = target.to(device=device, non_blocking=n... | 8dafddbd52b54a576ddc67d7d79af4372fbd57dc | 16,257 |
def _get_diff2_data(request, ps_left_id, ps_right_id, patch_id, context,
column_width, tab_spaces, patch_filename=None):
"""Helper function that returns objects for diff2 views"""
ps_left = models.PatchSet.get_by_id(int(ps_left_id), parent=request.issue.key)
if ps_left is None:
return Http... | 47aef66544acec7d57125f3c7c0f8edb385ba150 | 16,258 |
def vec_add(iter_a, iter_b):
"""element wise addition"""
if len(iter_a) != len(iter_b):
raise ValueError
return (a + b for a, b in zip(iter_a, iter_b)) | f3e5bf50d61cfe518ee8b0eb838503a7f054baa8 | 16,259 |
def run():
""" Read inputs into a dictionary for recursive searching """
for line in inputs:
# Strip the trailing "." and split
container, rest = line[:-1].split(" contain ")
# Strip the trailing " bags"
container = container[:-5]
contained = []
for bag in rest.sp... | c3b565efbb923562c13955d808cf6ac2f09b616b | 16,260 |
def _get_prolongation_coordinates(grid, d1, d2):
"""Calculate required coordinates of finer grid for prolongation."""
D2, D1 = np.broadcast_arrays(
getattr(grid, 'vectorN'+d2), getattr(grid, 'vectorN'+d1)[:, None])
return np.r_[D1.ravel('F'), D2.ravel('F')].reshape(-1, 2, order='F') | 6534c456413cd062f9c35c14f5d9b57b1aba6c12 | 16,261 |
import os
from functools import cmp_to_key
def get_sorted_filediffs(filediffs, key=None):
"""Sorts a list of filediffs.
The list of filediffs will be sorted first by their base paths in
ascending order.
Within a base path, they'll be sorted by base name (minus the extension)
in ascending order.
... | dfd7fe9436bc59f5949dca838f82af01d14bfe83 | 16,262 |
def get_info(obj):
"""
get info from account obj
:type obj: account object
:param obj: the object of account
:return: dict of account info
"""
if obj:
return dict(db_instance_id=obj.dbinstance_id,
account_name=obj.account_name,
account_status=o... | c654ab1bdb4b4bf20223172dae450e1e7e6a52b9 | 16,263 |
def vlookup(x0, vals, ind, approx=True):
"""
Equivalent to the spreadsheet VLOOKUP function
:param vals: array_like
2d array of values - first column is searched for index
:param x0:
:param ind:
:param approx:
:return:
"""
if isinstance(vals[0][0], str):
x0 = str(x0)... | 59ee6ecd7c001bf6cf3f03ad678d93eda33f5e21 | 16,264 |
def matmul(a00, a10, a01, a11, b00, b10, b01, b11):
"""
Compute 2x2 matrix mutiplication in vector way
C = A*B
C = [a00 a01] * [b00 b01] = [c00 c01]
[a10 a11] [b10 b11] [c10 c11]
"""
c00 = a00*b00 + a01*b10
c10 = a10*b00 + a11*b10
c01 = a00*b01 + a01*... | d34506cc8099cbbf8b7a9e1eb9d4d068d768ebac | 16,265 |
import collections
import random
def random_sample_with_weight_and_cost(population, weights, costs, cost_limit):
"""
Like random_sample_with_weight but with the addition of a cost and limit.
While performing random samples (with priority for higher weight) we'll keep track of cost
If cost exceeds the ... | 637afd1c0e83bbda879f41bd15feb0f65b238fb3 | 16,266 |
def hardnet68ds(pretrained=False, **kwargs):
""" # This docstring shows up in hub.help()
Harmonic DenseNet 68ds (Depthwise Separable) model
pretrained (bool): kwargs, load pretrained weights into the model
"""
# Call the model, load pretrained weights
model = hardnet.HarDNet(depth_wise=True, arc... | 5167b79f8effdb9a4b94e9d0a7902f35468a1d8b | 16,267 |
def get_config():
"""Base config for training models."""
config = ml_collections.ConfigDict()
# How often to save the model checkpoint.
config.save_checkpoints_steps: int = 1000
# Frequency fo eval during training, e.g. every 1000 steps.
config.eval_frequency: int = 1000
# Total batch size for training.... | 67dfe8aff3f1a3e660d9debccc181690ea561ae2 | 16,268 |
def slave_addresses(dns):
"""List of slave IP addresses
@returns: str Comma delimited list of slave IP addresses
"""
return ', '.join(['{}:53'.format(s['address'])
for s in dns.pool_config]) | e293442272496f02a58055dd778ecfe875124ccd | 16,269 |
def processAndLabelStates(role, states, reason, positiveStates=None, negativeStates=None, positiveStateLabelDict={}, negativeStateLabelDict={}):
"""Processes the states for an object and returns the appropriate state labels for both positive and negative states.
@param role: The role of the object to process states f... | 23be0c7d943961f756a02abea98c51500f92b00f | 16,270 |
def shape_for_stateful_rnn(data, batch_size, seq_length, seq_step):
"""
Reformat our data vector into input and target sequences to feed into our
RNN. Tricky with stateful RNNs.
"""
# Our target sequences are simply one timestep ahead of our input sequences.
# e.g. with an input vector "wherefor... | 431eb54acc9bfe2281a3a863335eb135f050f47e | 16,271 |
import time
import tqdm
def setup_features(dataRaw, label='flux', notFeatures=[], pipeline=None, verbose=False, resample=False, returnAll=None):
"""Example function with types documented in the docstring.
For production level usage: All scaling and transformations must be done
with resp... | 7c1fb86dc66d97610bd1d22ef65ccb88e105dd92 | 16,272 |
from typing import List
from typing import Any
def plot_marginal_effects(model: ModelBridge, metric: str) -> AxPlotConfig:
"""
Calculates and plots the marginal effects -- the effect of changing one
factor away from the randomized distribution of the experiment and fixing it
at a particular level.
... | f68c72d54e4e8ff1011ae6daec8a00ab30069d78 | 16,273 |
def _client_row_class(client: dict) -> str:
"""
Set the row class depending on what's in the client record.
"""
required_cols = ['trust_balance', 'refresh_trigger']
for col in required_cols:
if col not in client:
return 'dark'
try:
if client['trust_balance'] > clien... | cd5ebd8fd64c7d994d6803df473cd317af65e9ac | 16,274 |
def num2ord(place):
"""Return ordinal for the given place."""
omap = { u'1' : u'st',
u'2' : u'nd',
u'3' : u'rd',
u'11' : u'th',
u'12' : u'th',
u'13' : u'th' }
if place in omap:
return place + omap[place]
elif place.isdigit():
... | 3552257bba134ac00ed8c68d72bf5c947424b2e7 | 16,275 |
from typing import Type
def _get_dist_class(
policy: Policy, config: AlgorithmConfigDict, action_space: gym.spaces.Space
) -> Type[TFActionDistribution]:
"""Helper function to return a dist class based on config and action space.
Args:
policy: The policy for which to return the action
... | 08c09b876d5c2797d517a87957049c34939aee3a | 16,276 |
def expectation_values(times, states, operator):
"""expectation values of operator at times wrt states"""
def exp_value(state, operator, time):
if len(state.shape) == 2: #DensityMatrix
return np.trace(np.dot(state, operator(time)))
else: #Stat... | 4c18fa3b2ad7bec01f8f833ade59fe90315724ec | 16,277 |
def compute_f_all(F1,fft_size,windowing,dtype_complex,F_frac=[],F_fs=[],F_refs=[],freq_channel=0,\
F_first_sample=[],F_rates=[],F_pcal_fix=[],F_side=[],F_ind=[],F_lti=[]):
"""
Compute FFTs for all stations (all-baselines-per-task mode), and correct for fractional sample correction (linear ... | d9a4838347e498472228992dc77d08d44ed01c6e | 16,278 |
import http
def bookmark(request):
"""
Add or remove a bookmark based on POST data.
"""
if request.method == 'POST':
# getting handler
model_name = request.POST.get('model', u'')
model = django_apps.get_model(*model_name.split('.'))
if model is None:
# inva... | 32743894345e170d6d0efc427f3be0fb8d24b044 | 16,279 |
def start_nodenetrunner(nodenet_uid):
"""Starts a thread that regularly advances the given nodenet by one step."""
nodenets[nodenet_uid].is_active = True
if runner['runner'].paused:
runner['runner'].resume()
return True | 7511f217beb64936d403a5f5472036206f446c90 | 16,280 |
def transform_coordinates_3d(coordinates, RT):
"""
Input:
coordinates: [3, N]
RT: [4, 4]
Return
new_coordinates: [3, N]
"""
if coordinates.shape[0] != 3 and coordinates.shape[1]==3:
coordinates = coordinates.transpose()
coordinates = np.vstack([coordinates, np.on... | 8a31f97bddd1c84a21d4b396e877c2b327e6890b | 16,281 |
def _get_misclass_auroc(preds, targets, criterion, topk=1, expected_data_uncertainty_array=None):
"""
Get AUROC for Misclassification detection
:param preds: Prediction probabilities as numpy array
:param targets: Targets as numpy array
:param criterion: Criterion to use for scoring on misclassifica... | 282ef66926092e99a62003152daccf733913b6c2 | 16,282 |
from typing import Iterable
from typing import List
def flatten(l: Iterable) -> List:
"""Return a list of all non-list items in l
:param l: list to be flattened
:return:
"""
rval = []
for e in l:
if not isinstance(e, str) and isinstance(e, Iterable):
if len(list(e)):
... | 2d2202c21e6da7064491d55d5519c259d10f42c0 | 16,283 |
def create_note(dataset_id, fhir_store_id, note_id): # noqa: E501
"""Create a note
Create a note # noqa: E501
:param dataset_id: The ID of the dataset
:type dataset_id: str
:param fhir_store_id: The ID of the FHIR store
:type fhir_store_id: str
:param note_id: The ID of the note that is b... | 396f81b4a6035a9f295faebdd1aa313131d0da2b | 16,284 |
def load_credential_from_args(args):
"""load credential from command
Args:
args(str): str join `,`
Returns:
list of credential content
"""
if ',' not in args:
raise
file_path_list = args.split(',')
if len(file_path_list) != 2:
raise
if not file_path_list... | 4f2e0b1e57ee3baaeb1bab3dc0e7e3874aaeec7c | 16,285 |
def encode(string: str, key: str) -> str:
"""
Encode string using the Caesar cipher with the given key
:param string: string to be encoded
:param key: letter to be used as given shift
:return: encoded string
:raises: ValueError if key len is invalid
"""
if len(key) > 1:
raise Val... | ddba41c5efc01df06290cd6496ef8eb54dbb28be | 16,286 |
def compile_binary(binary, compiler, override_operator=None, **kw):
"""
If there are more than 10 elements in the `IN` set, inline them to avoid hitting the limit of \
the number of query arguments in Postgres (1<<15).
""" # noqa: D200
operator = override_operator or binary.operator
if operato... | 1798ded35c12d6a3bf2e5edc34dcf11ff70ce697 | 16,287 |
from typing import Callable
from typing import Iterable
from typing import Iterator
import itertools
def flat_map(
fn: Callable[[_T], Iterable[_S]], collection: Iterable[_T]
) -> Iterator[_S]:
"""Map a function over a collection and flatten the result by one-level"""
return itertools.chain.from_iterable(m... | a1a09611f920078cb25a23279004acd00ac23142 | 16,288 |
def create_vector_clock(node_id, timeout):
"""This method builds the initial vector clock for a new key.
Parameters
----------
node_id : int
the id of one node in the cluster
timeout : int
the expire timeout of the key
Returns
-------
dict
the vector clock as di... | ed6df0e7e493d448f52e5fe47b55df8a1de94543 | 16,289 |
def ParseStateFoldersFromFiles(state_files):
"""Returns list of StateFolder objects parsed from state_files.
Args:
state_files: list of absolute paths to state files.
"""
def CreateStateFolder(folderpath, parent_namespace):
del parent_namespace # Unused by StateFolder.
return state_lib.StateFolde... | c70421da1f193ca2dc86f12e7cffd84a1011af22 | 16,290 |
def spectral_norm(inputs, epsilon=1e-12, singular_value="left"):
"""Performs Spectral Normalization on a weight tensor.
Details of why this is helpful for GAN's can be found in "Spectral
Normalization for Generative Adversarial Networks", Miyato T. et al., 2018.
[https://arxiv.org/abs/1802.05957].
Args:
... | eb6961e984fbb8eb5c3d807faa7fa6d016c011b5 | 16,291 |
def rs_for_staff(user_id):
"""Returns simple JSON for research studies in staff user's domain
---
tags:
- User
- ResearchStudy
operationId: research_studies_for_staff
parameters:
- name: user_id
in: path
description: TrueNTH user ID, typically subject or staff
... | 9d36a02cc4909e336730fb27b3bcfe284bcd5d82 | 16,292 |
from typing import Mapping
from typing import Any
import tqdm
def from_hetionet_json(
hetionet_dict: Mapping[str, Any],
use_tqdm: bool = True,
) -> BELGraph:
"""Convert a Hetionet dictionary to a BEL graph."""
graph = BELGraph( # FIXME what metadata is appropriate?
name='Hetionet',
ve... | 34db6048369945964c61aa4297164458f576a786 | 16,293 |
import re
import click
def validate_memory(_ctx, _param, value):
"""Validate memory string."""
if value is None:
return None
if not re.search(r'\d+[KkMmGg]$', value):
raise click.BadParameter('Memory format: nnn[K|M|G].')
return value | c050863a974c08ccc18fdaa2f03388c8f6674835 | 16,294 |
def BlockAvg3D( data , blocksize , mask ):
"""
3-D version of block averaging. Mainly applicable to making superpixel averages of datfile traces.
Not sure non-averaging calcs makes sense?
mask is a currently built for a 2d boolean array of same size as (data[0], data[1]) where pixels to be averaged a... | 4c0c9cb60c80f47289e7bff3e50ae3e39dd31c63 | 16,295 |
def build(buildconfig: BuildConfig, merge_train_and_test_data: bool = False):
"""Build regressor or classifier model and return it."""
estimator = buildconfig.algorithm.estimator()
if merge_train_and_test_data:
train_smiles, train_y = buildconfig.data.get_merged_sets()
else:
train_smile... | 9a98f15ae9b966e42cda848169b38a651e727205 | 16,296 |
import databrowse.support.dummy_web_support as db_web_support_module
import databrowse.support.handler_support as handler_support_module
import os
def GetXML(filename, output=OUTPUT_ELEMENT, **params):
"""
Get the XML representation of a file, as produced by the Databrowse library
Arguments:
filena... | 369a14f950371711c032805b74b8b640f1b4af66 | 16,297 |
def stellar_radius(M, logg):
"""Calculate stellar radius given mass and logg"""
if not isinstance(M, (int, float)):
raise TypeError('Mass must be int or float. {} type given'.format(type(M)))
if not isinstance(logg, (int, float)):
raise TypeError('logg must be int or float. {} type given'.fo... | 2afbd991c7461d7861370f18d90df840569da857 | 16,298 |
def set_plus_row(sets, row):
"""Update each set in list with values in row."""
for i in range(len(sets)):
sets[i].add(row[i])
return sets | 87f448dc3199c8d3137d5811dd184b3d2bd7cbe3 | 16,299 |
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