content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def matched_iou(boxlist1, boxlist2, scope=None):
"""Compute intersection-over-union between corresponding boxes in boxlists.
Args:
boxlist1: BoxList holding N boxes
boxlist2: BoxList holding N boxes
scope: name scope.
Returns:
a tensor with shape [N] representing pairwise iou score... | 845f401a61bd4fc80d381f3783e6906c180694fb | 3,596,036 |
def do_combine(self, other):
"""
:param ProGlyph self:
:param ProGlyph other:
0 :return:
"""
score, yell = 0, ""
s, t = self.best_char, other.best_char
ss, st = self.strength(), other.strength()
suspects = ['ఏ', '-', '"', "'", '.', 'ై']
ghpsshh = 'ఘపసషహఎ'
heads = ['ి', 'ీ', ... | 2c346001cd9aaf692896152b8c6690d7800e8995 | 3,596,037 |
def get_version():
"""Endpoint for getting the current version."""
return jsonify(
status='OK',
version=VERSION,
message='AIOPS Data Collector Version 0.0.1'
) | 71272375ad0af06a3c18587cdfce77be27eaf863 | 3,596,038 |
import random
def remove_edge_random_stochastic(G, p, random_seed=None, copy=True):
"""
Recieves a Graph and p (uniform probability of failure).
Returns a degraded Graph
"""
if copy:
G_ = G.copy()
else:
G_ = G
if random_seed is not None:
random.seed(r... | 6591c79ccf14513adf58b0f59e569c6586d85d5f | 3,596,040 |
def gas_attached():
"""
:returns gas attached to Tx:
"""
configuration = ServiceConfiguration()
tx = GetScriptContainer() # type:Transaction
references = tx.References
receiver_addr = GetExecutingScriptHash()
if len(references) > 0:
sent_amount_gas = 0
for output in tx... | c7e03e6c8b4e48d53c012b3bed5c72c2d9bac9e0 | 3,596,041 |
def list_services(config_dict):
"""
List available services
Args:
config_dict (dict): configuration dictionary
Returns:
list: list of available services
"""
return list(config_dict.keys()) | a3226589405292f0bcef99aabaec71722aaeb1db | 3,596,042 |
def get_big_wall(vk_session, user_id=1):
"""
Метод для скачивания стены во Вконтакте
:param vk_session: Передаём авторизованную сессию VkApi
:type vk_session: class VkApi
:param user_id: Передаём ID пользователя, чью стенку надо получить
:type user_id: int
:return: Возвращается стена пользо... | c06d439b28e8d65e02fe887781562c74ad9547d0 | 3,596,044 |
def unet_block(x, filters: int, a=0.01, dr=0.05):
"""
U-net functional block
Edit this block as needed
Args:
x: Input tensor.
filters (int): No. of filters in convolution layer.
a (float, optional): Leakage rate for ReLU. Defaults to 0.01.
dr (float, optional): Dropout ... | 5d4c1044fe68a8188bca450a6ea6c855b287204f | 3,596,045 |
def stratification(rules):
"""Returns a dictionary from table names to an integer representing
the strata to which the table is assigned or None if the rules
are not stratified.
"""
return head_to_body_dependency_graph(rules).stratification([True]) | 11b7ba21cb7dc5c7625438c10d56310421732bd1 | 3,596,047 |
from typing import Type
from datetime import datetime
def _parse(json_str: str, primitive_cls: Type[Instant]) -> Instant:
"""Parses the json_str into an Instant FHIR primitive.
Args:
json_str: The raw JSON string to parse.
primitive_cls: The FHIR primitive to parse into.
Returns:
A FHIR primitive ... | 673ac08ba52e1f54b18f71059754ff02ee577b70 | 3,596,048 |
import requests
def generate_access_token(consumer_key, consumer_secret):
"""This will generate the autorization token we need to make the daraja request for a stk push
Args:
consumer_key (str): -- consumer_key (above)
consumer_secret (str): -- consumer_secret (above)
Returns:
... | 0119b6db0870b07f30080c096306d82976e0c7d5 | 3,596,049 |
def actions_by_behavior(actions):
"""
Gather a dictionary grouping the actions by behavior (not SubBehaviors). The actions in each
list are still sorted by order of their execution in the script.
@param actions (list) of Action objects
@return (dict) where the keys are behaviors and the values are... | ebf97a5837a8d7de735207c5df5e19af2438510a | 3,596,050 |
import decimal
def decimal_round(val, prec=1e-4):
"""wrapper for rounding according to precision
"""
DD = decimal.Decimal
val_ = DD(val).quantize(DD(f'{prec}'), rounding=decimal.ROUND_DOWN)
return float(val_) | d0e37277df94ddbd95a60c1380cf3eb93531c6a7 | 3,596,051 |
def split_into_test_and_training(
source_file, target_file, source_tree_name, branches_to_store=[]
):
"""
Splits the given ROOT file into a target file with two trees: one with
a test sample set and one with a training sample set. The events are
splitted 50% and 50%.
Returns the amount of entrie... | f641a89a31fc2d023b00594958b2821e3834e2aa | 3,596,052 |
def load_properties(filepath, sep='=', comment_char='#'):
"""
Read the file passed as parameter as a properties file.
"""
props = {}
with open(filepath, "rt") as f:
for line in f:
l = line.strip()
if l and not l.startswith(comment_char):
if l.endswith(... | 5663f8aa1197aeb7648228247df1ab65e39a2f5a | 3,596,053 |
import logging
from typing import Concatenate
def apply_unet(
input_tensor,
output_name='output',
params={},
output_mask_logit=False):
""" Apply a convolutionnal U-net to model a single instrument (one U-net
is used for each instrument).
:param input_tensor:
:param out... | e7dc6983bff73ba91de2be4607bb7b8166fbfaf6 | 3,596,054 |
def runScheduledTask():
"""
Purpose: This function executes the given scheduled task
Params:
- In : None
- Out: None
"""
# Retrieve all tasks from endpoint
_endpoint = URL + '/sessions/scheduledtasks'
_response = mkAPIcall( _endpoint, 'get', _hdr, '', None )
# Retrieve task_id for given scheduled tas... | 352ab94bfc86f16738808829eb3bfdffc133157c | 3,596,055 |
def best_star(lst, Year_NOW, star_dict=None, catalog=None, lat=salt_lat):
"""Given an lst and a catalog of stars, determine the best star in the list.
The best star is determined to have an airmass less than 1.2, a
magnitude below 3.0, and an hour angle greater than 0.5. And we will pic
it to b... | 94499def158c51181fee710fd24a019c6bb01d66 | 3,596,056 |
def sample_split_node(node: LeafNode) -> DecisionNode:
"""
Split a leaf node into a decision node with two leaf children
The variable and value to split on is determined by sampling from their respective distributions
"""
conditions = sample_split_condition(node)
if conditions is None:
r... | 91e2b5c71669a44ce27e3256b98f3a2152b37ebc | 3,596,057 |
def postgres_checkpoints_config():
"""
Shared setup for PostgresCheckpointsAPITest and subclasses.
"""
config = Config()
config.NotebookApp.contents_manager_class = FileContentsManager
config.FileContentsManager.delete_to_trash = False
config.ContentsManager.checkpoints_class = PostgresCheck... | 516bd69b1376ef380991964b30c2bea11b455bf3 | 3,596,058 |
import optparse
def csv_validator(optdict, name, value):
"""validate and return a converted value for option of type 'csv'
"""
return optparse.check_csv(None, name, value) | 2c4d2a6be7773231dfb610304359f3041ac2f524 | 3,596,059 |
import random
def select_anchors_classification(data, n, classifier):
"""randomly selects n different anchors for evaluation. Only LoS-classified anchors are selected
Returns:
--------
nodes: numpy matrix with nodes positions and ranges
+ +
| array([x1,y1]) | r1 |
| array([x2,y2]) | r2 |
... | e428330f920ef3100edb8ac145e28b35c158b284 | 3,596,060 |
import urllib
def register(request, template_name='authopenid/complete.html',
redirect_field_name=REDIRECT_FIELD_NAME,
register_form=OpenidRegisterForm, auth_form=AuthenticationForm,
register_account=register_account, send_email=True,
extra_context=None):
"""
... | b6f2d94c68c4927833d998160ba5c498690a0375 | 3,596,061 |
def batch_norm(x, n_out, phase_train):
"""
Batch normalization on convolutional maps.
Ref.: http://stackoverflow.com/questions/33949786/how-could-i-use-batch-normalization-in-tensorflow
Args:
x: Tensor, 4D BHWD input maps
n_out: integer, depth of input maps
phase_... | 8acabdbd13f6c0f18990202e9deba722a992c26b | 3,596,062 |
import requests
def reddit_ass(bot, trigger):
"""Posts a random ass pic from Reddit. #nsfw only."""
msg = nsfw_check(trigger)
if msg:
return bot.reply(msg)
url = "https://old.reddit.com/search.json"
params = {
"q": "(ass OR butt OR booty) AND nsfw:yes AND (site:reddit.com OR site:... | 9fd30306962e174b4ba50087a973f07c348c770a | 3,596,063 |
def conv7x7(inchannel, outchannel, stride=1, bias=False, dilation=1):
"""Create Convolution 7x7."""
return ops.Conv2d(inchannel, outchannel, kernel_size=7, stride=stride,
padding=3, dilation=dilation, bias=bias) | 4aac4f78f84f8ca1edc6ea11fee4c50c9d3a6207 | 3,596,064 |
def make_chain_tanh_fill(length=100, name_prefix="a", node_mbs=1):
"""Creates chain of length length. First node is Variable, rest are tanh.
Returns nodes. Note, if length is 1, there are no non-linearities in the
graph, hence gradients do not need to store any activations."""
dtype = np.float32
n = node_mbs... | 2b303719de94e5cd1483587231451f20d3db16c7 | 3,596,065 |
def check_wind_component(df):
"""
Ensure that CC/HN models where mass != mass_final, that a row is added
to store wind composition
"""
elements = list(set(df.columns).intersection(set(el2z.keys())))
for i, model in df[(df.type == 'cc') & (df.mass != df.mass_final)].iterrows():
if not '... | e6f7493ef5b0b4dce47a90ab7752f8574245d1cb | 3,596,066 |
def plugin_reconfigure(handle, new_config):
""" Reconfigures the plugin, it should be called when the configuration of the plugin is changed during the
operation of the device service.
The new configuration category should be passed.
Args:
handle: handle returned by the plugin initialis... | b65c246d90e8ab6740c0481849ab2da22a90b872 | 3,596,067 |
import logging
def get_loglevel(loglevel):
""" Check whether a valid log level has been supplied, and return the numeric log level that
corresponds to the given string level.
Parameters
----------
loglevel: str
The loglevel that has been requested
Returns
-------
int
... | a662e00caa21bf5632b28f26cbb604229db9705a | 3,596,068 |
import ipdb
def add_to_tfrecord(im_path,
gt2d,
gt3d,
cam,
coder,
writer,
model=None,
sub_path=None):
"""
gt2d is 14 x 2 (lsp order)
gt3d is 14 x 3
cam is (3,)
... | 1df333aa08c008a84d6933179662572e785270aa | 3,596,070 |
def syrk(A, C=None, uplo='u', trans='n', alpha=1.0, beta=1.0, lda=None, ldc=None):
"""
Perform a symmetric rank-k update operation.
C := beta * C + alpha * A * A_T [trans='n']
or
C := beta * C + alpha * A_T * A [trans='t']
where alpha and beta are scalars, A is a general matrix, and C is a s... | 436071568f9a6b741c9d75c53a2eec150a94ca01 | 3,596,071 |
import logging
import time
def is_valid_date(strdate):
"""
判断是否是一个有效的日期字符串
:param strdate:
:return:
"""
logging.info('is_valid_date')
try:
if ":" in strdate:
time.strptime(strdate, "%Y-%m-%d %H:%M:%S")
else:
time.strptime(strdate, "%Y-%m-%d")
... | 7dd157a3bf970057233066faa563dee627a61dbf | 3,596,072 |
def _IsRegressionReproduced(known_good_result, known_bad_result,
required_initial_confidence):
"""Checks whether the regression was reproduced based on the initial values.
Args:
known_good_result: A dict with the keys "values", "mean" and "std_err".
known_bad_result: Same as abo... | 38d20e0030d707b42d3330bafdf92e4dde9b5296 | 3,596,073 |
from datetime import datetime
def getTimeDelta(startDatetime):
"""
get a timedelta object. Get seconds elapsed with timedelta.total_seconds().
"""
endDatetime = datetime.datetime.utcnow()
timedeltaObj = endDatetime - startDatetime
return timedeltaObj | 59739cde93125b7fb6f44ad555ea47e0c19b5c3f | 3,596,074 |
def update(time):
"""Updates all active widgets or modal widgets each frame."""
def _fade(widget):
"""Fade widget."""
if widget._fade is not None:
widget.image.set_alpha(widget._fade)
if widget._fade_up:
widget._fade += time / 3.
else:
... | 0c7d8d029d936425a5ef03a7a926220dd67eb32e | 3,596,075 |
def comp_spearman(data_u, data_v):
"""Compute the spearmanr correlation index.
Suggestion: use tonparray to converta data (pd.series, non-flatten
numpy.array) to a flatten numpy.array and drop nans."""
return spearmanr(data_u, data_v)[0] | ff5f1e6ba5e6ce685472a5064b6c2a0a8cf8923d | 3,596,076 |
def pixel_precision_recall_f1(seg, gt):
"""
:param seg: 2d array, int,
estimated targets as returned by a classifier
:param gt: 2d array, int,
ground truth
:return:
precision, recall, f1: float
"""
seg_flt, gt_flt = seg.flatten(), gt.flatten()
seg_flt[seg_flt ... | a91bc66449cb96a6d0332589b4f893b22d02818c | 3,596,078 |
def _label_col_dict(row: pd.Series, column: str):
"""Add label from the Provider column to the details."""
if not isinstance(row[column], dict):
return row[column]
return (
{row.Provider: row[column]} if row.Provider not in row[column] else row[column]
) | c5ff10e238b000d21bbf8fe610eb96e1496c0925 | 3,596,079 |
def vs_error_control(cg_itp, bead_id, vs_type, func, line_nb, vs_def_beads_ids=None):
"""Check itpd fields; vs_type in [2, 3, 4, n], then they each have specific functions
to define their positions"""
if bead_id >= len(cg_itp["atoms"]):
msg = (
f"A virtual site is defined for ID {bead_id... | 727885d33c711ebb953c59040ac0bef9f66707d9 | 3,596,080 |
from typing import Union
async def try_to_send_buffer(messagable: Messageable, buffer: str, force: bool = False) -> Union[Message, str]:
"""
Parses a string buffer and either sends or returns the buffer in an optimal break point.
Parameters:
messagable (discord.abc.Messageable): The channel to se... | a18821ff2e698bfc9ef95081bdafe09514dabde5 | 3,596,081 |
def load_initializer_tdata_and_vdata(
fn, n_train, ran_key, low_logmh, high_logmh, n_mh=200, n_validate=100, tol=-2.5
):
"""Load from disk the training and validation data for SHAMnet.
Parameters
----------
fn : string
h5 filename storing the best-fit SMHM params corresponding to SMF params... | 6097c7937824c24e5df8114e2dc5117f86e62600 | 3,596,083 |
def binary_cross_entropy(pred,
label,
weight=None,
reduction='mean',
avg_factor=None,
class_weight=None):
"""Calculate the binary CrossEntropy loss.
Args:
pred (torch.Tensor): Th... | 6b170b8e7964b37b24df68d27b0790efe0cdd023 | 3,596,084 |
import base64
import requests
import json
def retrieve_appdevtools_access_token(username, password, auth_endpoint):
"""
Retrieve access token for appdev tools
Args:
username: username
password: password
auth_endpoint: authorization endpoint
Returns: token
"""
# Form c... | 8f08f4be45998199aa9db151fec26722a13eb060 | 3,596,086 |
def delete(isamAppliance, instance_name, file_name, check_mode=False, force=False):
"""
Deleting a file or directory from the API Access Control
"""
exists, warnings = _check_exist(isamAppliance, instance_name, file_name)
if force is True or exists is True:
if check_mode is True:
... | 7ccbc9d4cc60f0de8b9fc6539ceca84e260f6eec | 3,596,087 |
def struct(typename, attrnames):
"""
Generate simple and fast data class
"""
attrnames = tuple(attrnames.replace(',', ' ').split())
reprfmt = '(' + ', '.join(name + '=%r' for name in attrnames) + ')'
def __init__(self, *args, **kwargs):
if len(args) > len(attrnames):
msg = ... | 9e4789e8960e48cd3a80c8907321d23013d29b87 | 3,596,089 |
import shutil
def generalizeCFF(otfPath, do_sfnt=True):
"""
Adapted from similar routine in 'buildmasterotfs'. This uses
temp files for both tx output and sfntedit output instead of
overwriting 'otfPath', and also provides an option to skip
the sfntedit step (so 'otfPath' can be either a .otf file... | 1f15de94a9ff1210efc5e1c445982d36d998f28c | 3,596,090 |
async def async_setup_entry(hass, config_entry):
"""Set up PyFoldingAtHomeControl from config entry."""
client = FoldingAtHomeControlClient(hass, config_entry)
hass.data.setdefault(DOMAIN, {})[config_entry.entry_id] = client
if not await client.async_setup():
return False
await async_setup_... | 63ec5f7ada4103d72ce357aed18e660234fc1115 | 3,596,091 |
def ADOSC(barDs, count, fastperiod=-2**31, slowperiod=-2**31):
"""Chaikin A/D Oscillator"""
return call_talib_with_hlcv(barDs, count, talib.ADOSC, fastperiod, slowperiod) | f54d38b93cd0e97619201d02f4efb123859df5f0 | 3,596,092 |
def indentify_taxon_notation(taxon_string):
"""Identifies taxonomic notation from `taxon_string` . Currently available
conventions are Greengenens, sintax and SILVA.
Examples:
Parameters
----------
taxon_string : str
String with taxonomy/lineage to test
Returns
-------
str... | 823e52449a5f16199e786bc9d901e0cf3f81cf72 | 3,596,093 |
def quatmultiply(q, p):
""" クォータニオン積
引数 :
q: クォータニオン (1x4)
p: クォータニオン (1x4)
返り値 :
o: クォータニオン積 (1x4) 正規化してからリターンする
"""
o1 = q[0] * p[0] - q[1] * p[1] - q[2] * p[2] - q[3] * p[3]
o2 = q[1] * p[0] + q[0] * p[1] - q[3] * p[2] + q[2] * p[3]
o3 = q[2] * p[0] + q[3] * p[1]... | b4adafc9d915cac415ff14d537a3553d9211a2a7 | 3,596,095 |
async def get_entree(entree_id):
"""
Get an entree by id
- **entree_id**: the unique id of the entree
"""
rows = simple_query('SELECT * FROM test.entree WHERE entree_id = :entree_id', {'entree_id': entree_id})
if (len(rows) == 0):
raise HTTPException(status_code=404, detail="Entree {} do... | 41a6868d3430adedee5cc0acf01ea3695d63fc49 | 3,596,096 |
def Positive(thetype):
"""Demand a positive number type"""
if thetype == int:
return All(thetype, Range(1, float('inf')))
else:
return All(thetype, Range(0, float('inf')), NotIn([0])) | cce1490105e29eeadf76a640f94c92f32bd6c211 | 3,596,097 |
def decode_base64_gzip_to_string(base64_gzip_data: str) -> str:
"""Decode Base64 GZIP into string."""
data_bytes = decode_base64_gzip_to_bytes(base64_gzip_data)
return data_bytes.decode("utf-8") | 158af0e71625234593c99eb432fbdad8340dc5d3 | 3,596,098 |
def count_literals(term):
"""
Counts the number of literals in a term
Args:
term : A string containing literals
Returns:
The number of literals in term
"""
count = 0
for char in term:
if char != "_":
count+=1
re... | 48bb0066f09994627a4b7c2b04a657df1106a1c3 | 3,596,099 |
def calculate_glucose_from_effects(effects, recent_glucose, momentum=()):
"""Calculates predicted glucose values from effect schedules starting from the end of measured glucose history
Each effect should be a list of dicts containing at least 2 keys:
{
'date': # An ISO timestamp
'amount': #... | 7cd466999068a506274d3d8c62acf40aed87be69 | 3,596,100 |
def separable_conv(x, kernel_size, activation):
"""Apply a depthwise separable 1d convolution."""
tf.assert_rank(x, 3)
net = tf.expand_dims(x, 2)
net = tf.layers.separable_conv2d(
net,
filters=_depth(x),
kernel_size=(kernel_size, 1),
padding='same',
activation=activation)
net = t... | 0723776f6eb477d6c0da2ba257d9dfe9fee3289f | 3,596,101 |
def get_cache(maxsize=10000):
"""
Get an instance of cachetools.cache
Parameters
----------
maxsize: int
The max size for the cache (``10000``, by default)
Returns
-------
cachetools.cache
An instance of cachetools.cache
"""
global cache
if cache is None:
... | 6da71fd4fdbefecc0e6e2a2ebb4fea351bf4215a | 3,596,102 |
def simple_mask(dataf, maskf, outfile, thr=0):
""" sets values in data to zero if they are zero in mask"""
img = nibabel.load(dataf)
dat = img.get_data()
mask = nibabel.load(maskf).get_data()
if not dat.shape == mask.shape:
raise IOError('shape mismatch {0}, {1}'.format(dataf, maskf))
da... | 0b35a23c86388c4a7b121842a6a862cf3e5a59aa | 3,596,103 |
def group_by_node(notifications):
"""Take list of notifications and group by node.
:param notifications: List of stored email notifications
:return:
"""
emails = NotificationsDict()
for notification in notifications:
emails.add_message(notification['node_lineage'], notification['message... | b2d1f82c578afc805babd0f5e4eb41886373371c | 3,596,104 |
def line_search_wolfe2(
f,
myfprime,
xk,
pk,
gfk=None,
fk=None,
old_fval=None,
old_old_fval=None,
args=(),
c1=1e-4,
c2=0.9,
amax=None,
extra_condition=None,
maxiter=10,
):
"""Find alpha that satisfies strong Wolfe conditions.
Parameters
----------
... | 6ac9785bbe2b0bed30aa2d505765724232af3f3d | 3,596,105 |
def get_project_size(project_report, language):
"""
Obtains the project size that was calculated for a specific language by the
ProjectMetrics task from the project report
:param project_report: The project report to obtain the project size
from
:param language... | e08d8b40ad66baf52a50c4d6c84b9a15a720add9 | 3,596,106 |
def resample_to_1d_resolution(df, column):
"""
Have at most one data point per day. For days w/o change, have no data
point.
Before:
2020-03-18 16:42:31+00:00 1
2020-03-19 20:17:10+00:00 2
2020-03-20 05:31:25+00:00 3
2020-03-20 09:01:38+00:00 4
2020-03-20 14:03:... | 9739c348e095967015e238606e23b2896d584099 | 3,596,107 |
def get_storageaccount_key():
# type: (None) -> str
"""Get storage account key
:rtype: str
:return: storage account key
"""
return _STORAGEACCOUNTKEY | 1dcec8ea06bf7c68a9b5def69658c71044014eae | 3,596,108 |
def encode_collection(collection, encoding='utf-8'):
"""Encodes all the string keys and values in a collection with specified encoding"""
if isinstance(collection, dict):
return dict((encode_collection(key), encode_collection(value)) for key, value in collection.iteritems())
elif isinstance(collect... | 60ec0ec41d852d8d3801c815654b0edde8d763dc | 3,596,109 |
def _thompson_star(
regular_expression: RegularExpression,
alphabet: Alphabet,
index: int = 0) -> FiniteAutomaton:
"""Thompson's algorithm, ``STAR`` case
"""
inner = thompson(regular_expression.inner, alphabet, index)
index += len(inner.states)
q_init_inner = list(inner.initi... | 26cade9d0fea4c8642125a6617de1db15cbb1807 | 3,596,111 |
def BmV_to_gmr( BmV ):
"""Relation from Cook+2014 (2014MNRAS.445..890C) to transform
galaxy B-V color to g-r.
"""
ii_bad = [i for i in range(len(BmV)) if BmV[i] == -99.0]
gmr = 1.12*BmV - 0.18
gmr[ii_bad] = -99.0
return gmr | e5b4d1748d403e206cfb74f640d5e04e5b84f5a1 | 3,596,112 |
def generate_map_legend() -> MacroElement:
"""
Generates a legend for the map.
:return: MacroElement, html added to the map
"""
template = """
{% macro html(this, kwargs) %}
<!doctype html>
<html lang="en">
<head>
<meta charset="utf-8">
<meta name="viewport" content="wi... | 3943f5d48b0e9464d7252070e0ac5b553183d7bf | 3,596,113 |
def remove_redundant_after_inosine_addition(data, min_increase):
"""
Removes oligos that don't increase coverage after inosine addition.
Arguments:
-data: a pandas dataframe with sequences detected by the oligo as returned by measure_coverage_oligos
-min_increase: minimal increase of coverag... | 5b96d4dc8fe2ed92e422d2c05a2d257fbe1795fa | 3,596,114 |
from typing import Any
from typing import List
def flatten(item: Any) -> List[Any]:
"""Recursively flatten any sequence but a string or bytes.
Args:
item: a sequence or a single item. A single item will be packet into a list.
Returns:
a list with tuples got flattened.
>>> from redex... | 15b4579626a36d912c0e453efe85537cd0a59a18 | 3,596,115 |
def brent(f, a, b, t, args=()):
"""
Find a zero of a univariate function within a given range
This is a bracketed root-finding method, so f(a) and f(b) must differ in
sign. If they do, a root is guaranteed to be found.
Parameters
----------
f : function
Continuous function of a si... | 6b474619162d5dc471f7d85ea4cabddc79930bd5 | 3,596,116 |
import json
def get_json_from_file(filename, warn = False):
"""Loads json from a file.
Optionally specify warn = True to warn, rather than
fail if file not found."""
f = open(filename, 'r')
return json.loads(f.read()) | 6916e0239067b977d0671e1e38006f457da94ae7 | 3,596,117 |
def filter_grantable_permissions(session, grants, all_permissions=None):
"""For a given set of PERMISSION_GRANT permissions, return all permissions
that are grantable.
Args:
session (sqlalchemy.orm.session.Session); database session
grants ([Permission, ...]): PERMISSION_GRANT permissions
... | 21ba3eaaaa73cddffbbe2bf010810a37db192e4c | 3,596,118 |
def fit_plane_3_points(points):
""" compute the plane that passes through all 3 points in the list
Parameters
----------
points : array_like
The Points
"""
# compute normal direction which is perpendicular to vectors p1-p0, p2-p0
# use np.subtact instead of "-" operator so that points... | 02ab3a7fb1149422012f77a913ce7d0e3550f4b7 | 3,596,119 |
def segments_to_tabs(segments, ax, thickness):
"""
genrates tabs from a segmented point list
You can change if the first tab is male of female by changing the sign of the tab-size
"""
arr_x = np.repeat(segments[:,ax], 2)
arr_y = np.tile([0,0, thickness, thickness], len(segments)//2+1)[1:-3]
... | dfe842267830993835f8ed8c8edc2f57e49b1d71 | 3,596,121 |
def ellipsecoords(pars,npoints=100):
""" Create coordinates of an ellipse."""
# [x,y,asemi,bsemi,theta]
# copied from ellipsecoords.pro
xc = pars[0]
yc = pars[1]
asemi = pars[2]
bsemi = pars[3]
pos_ang = pars[4]
phi = 2*np.pi*(np.arange(npoints)/(npoints-1)) # Divide circle into Np... | fb2b2339eed9c8e639083042c1f499ddc6fd125c | 3,596,123 |
import itertools
def take_while(collection, predicate):
""":yaql:takeWhile
Returns elements from the collection as long as the predicate is true.
:signature: collection.takeWhile(predicate)
:receiverArg collection: input collection
:argType collection: iterable
:arg predicate: function of on... | dd1fe4f97db991d1323b814ddd1f7c2e0fe52c88 | 3,596,124 |
def ip_has_digit(matched_str):
"""Checks to make sure the PII span is not just :: or whatever that may
accidentally be picked up by making sure there are digits."""
return any(map(str.isdigit, matched_str)) | 3ed765a04c1b920addc7e3ab538575ac4edc7651 | 3,596,125 |
def idz_estrank(eps, A):
"""
Estimate rank of a complex matrix to a specified relative precision using
random sampling.
The output rank is typically about 8 higher than the actual rank.
:param eps:
Relative precision.
:type eps: float
:param A:
Matrix.
:type A: :class:`... | b4d188352ee9f78b6b6a2b6630ab3bc93fe63388 | 3,596,126 |
def batch_from_image(file_name, batch_size, output_height=224, output_width=224,
num_channels=3):
"""Produce a batch of data from the passed image file.
Args:
file_name: string, path to file containing a JPEG image
batch_size: int, the size of the desired batch of data
output_heigh... | 0c929672ce6dea7c5f29afaac6947158bc7d3885 | 3,596,127 |
def login():
""" Login page """
# Forget any user_id
session.clear()
# check if POST used
if request.method == "POST":
# store userName in variable
userName = request.form.get("username")
# return apology for blank username
if not userName:
return ap... | 2f48fc956bd63c46ff2ae007290093372f77914b | 3,596,128 |
from importlib.util import spec_from_file_location, module_from_spec
def load_config_from_py(filename):
""" Load the configuration parameters from a python file into dict. """
spec = spec_from_file_location('f', filename)
f = module_from_spec(spec)
spec.loader.exec_module(f)
return {name: value fo... | 600562b4d3f239f675354dc138b685caf26f35d9 | 3,596,131 |
def list_frequencies(list_of_items):
""" Determine frequency of items in list_of_items. """
itemfreq = [list_of_items.count(p) for p in list_of_items]
return dict(zip(list_of_items,itemfreq)) | 8772e64d0abd400dfe333747e7fce0d816a0f59f | 3,596,132 |
import scipy
def calc_delta(texp, start_time, lam, vol, fee, gmdb, account, spot):
"""Delta to put on against the VA portfolio"""
t_fwd = texp - start_time
n_int = max(2, int(round(0.4 * t_fwd)))
dt_int = t_fwd / n_int
deltas = -fee * account * np.exp(-lam * start_time) / spot * (1 - np.exp(-(fee... | bf251bed22ef4d5edc0aefabce9973f7202bb9ba | 3,596,133 |
def get_host_credentials(config, hostname):
"""Get login information for a host `hostip` (ipv4) from marvin's `config`
@return the tuple username, password for the host else raise keyerror"""
for zone in config.zones:
for pod in zone.pods:
for cluster in pod.clusters:
fo... | 82bb146418c77a916b974b328f1cdf25817ddc69 | 3,596,134 |
import typing
from datetime import datetime
def terminate() -> typing.RouteReturn:
"""Room terminate page."""
room = flask.g.rezident.current_room
if not room:
# No current rental: go to register
return utils.ensure_safe_redirect(
"rooms.register",
doas=flask.g.doas... | fba275d0e550765b5b5bd31fe803a30ca20313a6 | 3,596,135 |
import pandas
def extract_mean_activation_parallel(celltype, chrom, start, end):
""" For a given genomic locus, calculate the 60bp
average coverage for this celltype
*** N.B: need to normalize for library size, not yet done IIRC ***
"""
my_peak = '\t'.join([chrom,str(start),str(end)])
... | e4146d59d0a960f620a61b44f25cec4ffc8fe255 | 3,596,136 |
def euclideanDistance(p0,p1):
"""
Return the Euclidean distance between two points.
Parameters:
-----------
p0: pandas dataframe
p0 must coantain three columns labeled 'x', 'y' and 'z'.
p1: pandas dataframe
p1 must coantain three columns labeled 'x', 'y' and 'z'.
Returns:
... | 00d6202b4488ae914be0751c1c186fc441b53273 | 3,596,137 |
def request_from_master(request):
"""Returns True if the request appears to be coming from the master"""
return request.getHeader("User-Agent") == config["master_user_agent"] | d3379051a094c9c6f4c22e9ea2df72b500aca063 | 3,596,138 |
def _get_sparse_representation(feature):
"""
Create sparse representation of the features, i.e. indices and values format.
:param feature: A list of floats. Assume the input is dense.
:return: indices and values.
"""
indices = np.arange(len(feature))
values = feature
return indices, valu... | a1ce40e777b70980a3c79ee466161324efb51618 | 3,596,139 |
def containstring(strtocheckinanother,checkstr):
"""Check if a string contains substring or not
return True if string is a substring else return False
Note: Dependent on 'get_all_substrings_of_String_in_array(checkstr)' method
Example:
>>> containstring("ello","Hello")
True
... | d02eeb1972ad746f383d49141f93ef19a9949055 | 3,596,140 |
def define_struct(defn):
"""
Register a struct definition globally
>>> define_struct('struct abcd {int x; int y;}')
"""
struct = parse_type(defn)
ALL_TYPES[struct.name] = struct
return struct | a7b6b8f2a17b2036de5f8ab632dd86eec5f3d2e0 | 3,596,141 |
def DiffusionMaps(*args, **kwargs):
"""Convenience function to select the right diffusion map routine.
Consult the documentation for BaseDiffusionMaps and its constructor for
details.
"""
cut_off = kwargs.get('cut_off')
if cut_off is None or np.isinf(cut_off):
kwargs['cut_off'] = None... | 50347316ac954d26914f9e86f9a058587076832a | 3,596,142 |
import base64
def authenticateRequest(request, storeSessionCookie=False):
"""
Authenticates an API request. Returns a StoreUser object if the
authentication is successful, None if unsuccessful, or a string
error message if an error occurs.
"""
if SESSION_KEY in request.session:
user = ezidapp... | 231ddaf97c69d8f3f359946f95caf86eec1f67ef | 3,596,143 |
def is_new_nice(chars):
"""
New rules for part 2
"""
return (
has_non_overlapping_pairs(chars) and
has_repeat_char_with_one_between(chars)
) | 2b5517bb775e4a17898bb04587be71b1bfbdbd4a | 3,596,144 |
def _pool(x):
""" max pooling"""
x = MaxPooling2D(pool_size=2,strides=2,padding='same')(x)
return x | 22c8db1bd38132eb22ea0854bd005c5c154fd4d9 | 3,596,145 |
import numpy as np
def eigenvector_centrality_numpy(G):
"""Compute the eigenvector centrality for the graph G.
Parameters
----------
G : graph
A networkx graph
Returns
-------
nodes : dictionary
Dictionary of nodes with eigenvector centrality as the value.
Examples
... | 6ab315920f5aefa672f7aef4af5887cc26684ef6 | 3,596,147 |
from typing import List
def get_records(
vcf_path: str,
sample_name: str,
group: str,
no_alt: bool = False,
autosomes_only: bool = True,
) -> List[dict]:
"""
Load records from VCF and create a list of dictionaries with their relevant info
"""
hs_autosomes = [str(x) for x in range(1... | 1a3ace194ee0bfb9b504dcc56894e3d338f2d016 | 3,596,148 |
import numpy
def maxDist(src, dst):
"""
Src and dst are both matrices of the same size with each column representing a
different position
"""
diff = dst - src
max_dist = 0
for entry in range(diff.shape[1]):
dist = numpy.linalg.norm(diff[:, entry])
if dist > max_dist:
... | f943ebf703fe57cc79b03efa8100e8d8c3cb947a | 3,596,150 |
import six
import re
def partition_volumes(volumes, downsample=True):
"""Paritition volumes into training and validation based on configuration.
Uses the regexes mapping partition sizes and indices in
diluvian.config.TrainingConfig by applying them to matching volumes based
on name.
Parameters
... | 7d3c3ca91f23396145814dbf526bceef8eb8c7a7 | 3,596,151 |
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