content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
from typing import Optional
def add_vqsr_eval_jobs(
b: hb.Batch,
dataproc_cluster: dataproc.DataprocCluster,
combined_mt_path: str,
rf_annotations_ht_path: str,
info_split_ht_path: str,
final_gathered_vcf_path: str,
rf_result_ht_path: Optional[str],
fam_stats_ht_path: Optional[str],
... | 16baacc4bdb0fa5aab5c0413dcc4734ea79f6238 | 3,632,195 |
def interpolate(r, g, b):
""" Interpolate missing values in the bayer pattern
by using bilinear interpolation
Args:
red, green, blue color channels as numpy array (H,W)
Returns:
Interpolated image as numpy array (H,W,3)
"""
#
# You code here
#
'''
rb各四分之一
... | cab347871f4b0ebc71f82cb6776976f9e0756aee | 3,632,197 |
def heatmap(pois, sample_size=-1, kwd=None, tiles='OpenStreetMap', width='100%', height='100%', radius=10):
"""Generates a heatmap of the input POIs.
Args:
pois (GeoDataFrame): A POIs GeoDataFrame.
sample_size (int): Sample size (default: -1; show all).
kwd (string): A keyword to filter... | f099aeb54a0b3bc300a8c335c9663da63e6b53b7 | 3,632,198 |
from typing import Tuple
def _color_int_to_rgb(integer: int) -> Tuple[int, int, int]:
"""Convert an 24 bit integer into a RGB color tuple with the value range (0-255).
Parameters
----------
integer : int
The value that should be converted
Returns
-------
Tuple[int, int, int]:
... | df3eb5ad92d9383b0e6fe5c1603e0caec0df5c45 | 3,632,199 |
def read_fchk(in_name):
"""
Read a Gaussian .fchk.
Returns the total energy, gradients and ground state energy.
Parameters
----------
in_name : str
Name of the file to read
Returns
-------
energy : float
Gaussian total calculated energy in Hartree
grad : list of... | c2686ca723dc2e874355879a84ec4b57157a70cf | 3,632,201 |
def miles(kilometers=0, meters=0, feet=0, nautical=0):
"""
Convert distance to miles.
"""
ret = 0.
if nautical:
kilometers += nautical / nm(1.)
if feet:
kilometers += feet / ft(1.)
if meters:
kilometers += meters / 1000.
ret += kilometers / 1.609344
return ret | 6ffd67913280a7148a84463b9679a17e004176d6 | 3,632,202 |
def LookupScope(scope):
"""Helper to produce a more readable scope line.
Args:
scope: String url that reflects the authorized scope of access.
Returns:
Line of text with more readable explanation of the scope with the scope.
"""
readable_scope = _SCOPE_MAP.get(scope.rstrip('/'))
if readable_scope:... | de7d24b6769830d55e6260d5ee2ac5b4846e854c | 3,632,203 |
def label2binary(y, label):
"""
Map label val to +1 and the other labels to -1.
Paramters:
----------
y : `numpy.ndarray`
(nData,) The labels of two classes.
val : `int`
The label to map to +1.
Returns:
--------
y : `numpy.ndarray`
(nData,) Maps ... | 5bce8491e9eef3a8c36b784ee0e252c641b24fdf | 3,632,204 |
from typing import Tuple
def detect_corners(R: np.array, threshold: float = 0.1) -> Tuple[np.array, np.array]:
"""Computes key-points from a Harris response image.
Key points are all points where the harris response is significant and greater than its neighbors.
Args:
R: A float image with the h... | b8cb5ae857a8255b263af2034703a0cf08ce66ca | 3,632,205 |
from typing import Union
from typing import Iterable
def add_file_replica_records(
files: Union[Iterable[File], QuerySet],
compute_resource: Union[str, ComputeResource],
set_as_default=False,
) -> int:
"""
Adds a new laxy+sftp:// file location to every files in a job, given
a ComputeResource. ... | 0a703205bd0e972b8c1e829bd850946cc1fe855a | 3,632,207 |
def in_suit3(list, list0):
"""
test 2 suits of street numbers if they have crossed numbers
For example: "22-27" in "21-24"retruns True
:param a: Int of number
:param b: String List of number
:return: boolean
"""
text = list.replace("-", "")
text0 = list0.replace("-", "")
if (... | 57409220b93c66ab4b957a05713e5e89b380253a | 3,632,210 |
def mp_wfs_110_nometadata(monkeypatch):
"""Monkeypatch the call to the remote GetCapabilities request of WFS
version 1.1.0, not containing MetadataURLs.
Parameters
----------
monkeypatch : pytest.fixture
PyTest monkeypatch fixture.
"""
def read(*args, **kwargs):
with open('... | 1c3f83f9ae7665a3cf77e5e2fa6217f72b7dc4ea | 3,632,211 |
def extract_power(eeg, D=3, dt=0.2, start=0):
""" extract power vaules for image
Parameters
----------
seizure : EEG | dict
eeg data
D : int, optional
epoch duration, by default 3
dt : float, optional
time step (seconds), by default 0.2
start : int, optional
... | 04c3fed38fa2a2d46ba7edee4bb3f04011d9d2a7 | 3,632,212 |
import time
import tqdm
def extract_HOG(generator, category='species', image_size=256, train=True, verbose=True):
"""
Extract HOG features for specified dataset (train/test).
Args:
generator (Generator class object): Generator class object.
train (bool): Am I working with train or test da... | 76cd3a6ed206bbbe258ade6433708dd8df20f990 | 3,632,213 |
def maybe_convert_platform(values):
""" try to do platform conversion, allow ndarray or list here """
if isinstance(values, (list, tuple, range)):
values = construct_1d_object_array_from_listlike(values)
if getattr(values, "dtype", None) == np.object_:
if hasattr(values, "_values"):
... | 79790a639ee5946f81c033584904491bfcd9be8b | 3,632,214 |
def build_training_response(mongodb_result, hug_timer, remaining_count):
"""
For reducing the duplicate lines in the 'get_single_training_movie' function.
"""
return {'movie_result': list(mongodb_result)[0],
'remaining': remaining_count,
'success': True,
'valid_key': True,
'took': float(hug_timer)} | 77d541957ff9abaa51bd3eb7fd06b550f41291e2 | 3,632,215 |
def calc_fm_perp_for_fm_loc(k_loc_i, fm_loc):
"""Calculate perpendicular component of fm to scattering vector."""
k_1, k_2, k_3 = k_loc_i[0], k_loc_i[1], k_loc_i[2]
mag_1, mag_2, mag_3 = fm_loc[0], fm_loc[1], fm_loc[2]
mag_p_1 = (k_3*mag_1 - k_1*mag_3)*k_3 - (k_1*mag_2 - k_2*mag_1)*k_2
mag_p_2 = (k_... | 00ba68c74d781748f39d2a577f227316dc523f0f | 3,632,216 |
def generate(
song_name,
raw_data_name,
base_path=utils.BASE_PATH,
chunk_size=100,
context_size=7,
drop_diffs=[],
log=False):
"""
Generate an SMDataset from SM/wav files.
Only creates datasets with no step predictions.
"""
sm = SMData.SMFile(s... | b61a20cfe1080139d80b3a1ee4ad8e9a7a7c0928 | 3,632,217 |
from functools import reduce
def cmap_map(function, cmap):
""" from scipy cookbook
Applies function (which should operate on vectors of shape 3: [r, g, b], on colormap cmap.
This routine will break any discontinuous points in a colormap.
"""
cdict = cmap._segmentdata
step_dict = {}
# Firt ... | 874618f4a685ae46edf896d759beafdd222dedf5 | 3,632,218 |
from datetime import datetime
from typing import Dict
from typing import Any
def get_legislation_passed_legislature_within_time_frame(
begin_date: datetime, end_date: datetime
) -> Dict[str, Any]:
"""See: http://wslwebservices.leg.wa.gov/legislationservice.asmx?op=GetLegislationPassedLegislatureWithinTimeFram... | ed851675da641b33665a814f8d50ee936c97af7d | 3,632,219 |
def trim_mismatches(gRNA):
"""
trim off 3' mismatches
1. first trim to prevent long alignments past end of normal expressed gRNAs
2. second trim to mismatches close to end of gRNA
"""
pairing = gRNA['pairing']
# 1. index of right-most mismatch before index -40
# if no MM is... | ab0bed78d29d64e9218201a561bb857fd80ed885 | 3,632,221 |
def validateRequest(endpoint, params):
"""Validate that a valid argument with the correct number of parameters has been supplied."""
if endpoint not in endpoints:
helpInfo = ", ".join(endpoints.keys())
print(f"Invalid endpoint. Please use one of the following: {helpInfo}")
return False
... | b2037f9ea1706f39c406e3708b445c0fb3474c01 | 3,632,222 |
import random
def augment_sequence(seq):
""" Flip / rotate a sequence with some random variations"""
imw, imh = 1024, 570
if random.random()>0.5:
for frame in range(len(seq)):
for m in [0, 1]:
seq[frame][m][0] = imw-seq[frame][m][0] # X flip
if random.random()>0.5:
... | 1f95c7e183cd696c985f30da335bcbc9337b5255 | 3,632,223 |
from mapalign import embed
from sklearn import metrics
from sklearn.utils.extmath import _deterministic_vector_sign_flip
def dme(network, threshold=90, n_components=10, return_result=False, **kwargs):
"""
Threshold, cosine similarity, and diffusion map embed `network`
Parameters
----------
networ... | 97a5014fc0cf174ea10dca171fdaea96509ac3ef | 3,632,224 |
def constant_substitution(text, constants_dict=None):
"""
Substitute some constant in the text.
:param text:
:param constants_dict:
:return:
"""
if not constants_dict:
# No constants, so return the same text
return text
template = Template(text)
return template.safe_... | ea5b6e49818064fc6051740d85b9661ca431d3f7 | 3,632,225 |
def zticks(model_name, dat, let):
"""
Read model name and return the corresponding
array of z-coordinates of front side of cells.
"""
delzarr = delz(model_name, dat, let)
arr = np.array([np.sum(delzarr[:i]) for i in range(delzarr.size+1)])
return arr | 12c48e5d73c364436aadaaa6a1d468d2e319c75c | 3,632,226 |
import copy
def reformat_args(args):
"""
reformat_args(args)
Returns reformatted args for analyses, specifically
- Sets stimulus parameters to "none" if they are irrelevant to the
stimtype
- Changes stimulus parameters from "both" to actual values
- Changes grps string... | 305999d1e1c252660314d837b7bbce8a8d5e7cc8 | 3,632,227 |
def load_xlsx_to_plan_list(
filename, sort_by=["sample_num"], rev=[False], retract_when_done=False
):
"""
run all sample dictionaries stored in the list bar
@param bar: a list of sample dictionaries
@param sort_by: list of strings determining the sorting of scans
strings include ... | dc106e243cf5174c263954a33a968a0ac2a83af1 | 3,632,228 |
def WTERMSIG(status):
"""Return the signal which caused the process to exit."""
return 0 | d4f45d41de95308c4a16f374e58c16b4384f8fc0 | 3,632,229 |
import io
def create_toplevel_function_string(args_out, args_in, pm_or_pf):
"""
Create a string for a function of the form:
def hl_func(x_0, x_1, x_2, ...):
outputs = (...) = calc_func(...)
header = [...]
return DataFrame(data, columns=header)
Parameters
-... | 44d78a9d0a3146b4008868073e5828422b819cc8 | 3,632,230 |
def remove_duplicates(df: pd.DataFrame, **kwargs: dict) -> pd.DataFrame:
"""
Remove duplicates entries
Args:
df (pd.DataFrame): DataFrame to check
Returns:
pd.DataFrame: DataFrame with duplicates removed
"""
return df[~(df.duplicated(**kwargs))] | 5d4f290acfda2f51334fc58bad71dd79f7b1a185 | 3,632,231 |
from npc_engine.exporters.base_exporter import Exporter
import click
def test_model(models_path: str, model_id: str):
"""Send test request to the model and print reply."""
if not validate_local_model(models_path, model_id):
click.echo(
click.style(f"{(model_id)} is not a valid npc-engine ... | bf05a6147ceb8769c4cbe5bac25ceab906b4fa92 | 3,632,233 |
def create_x11_client_listener(loop, display, auth_path):
"""Create a listener to accept X11 connections forwarded over SSH"""
host, dpynum, _ = _parse_display(display)
auth_proto, auth_data = yield from lookup_xauth(loop, auth_path,
host, dpynum)
r... | 806230b424f3ce2efa0197d50762b5e7ee497521 | 3,632,234 |
def expand_tile(expand_info):
"""Tile expander"""
# get op info.
input_desc = expand_info['input_desc'][0]
attrs = expand_info['attr']
multiples = None
for item in attrs:
if 'multiples' in item:
multiples = item['multiples']
output_shape, _, _, shape_compatible = _get_ti... | b4550770d82387d7245b142975b1e6d347a5b630 | 3,632,235 |
def compare_system_and_attributes_csv(self, file_number):
"""compare systems and associated attributes"""
# get objects
analysisstatus_1 = Analysisstatus.objects.get(
analysisstatus_name='analysisstatus_1'
)
systemstatus_1 = Systemstatus.objects.get(systemstatus_name='systemstatus_1')
... | d438b767af16deaa4d8d435a6ba7d4c6a943d026 | 3,632,236 |
def is_live_request(request):
"""
Helper to differentiate between live requests and scripts.
Requires :func:`~.request_is_live_tween_factory`.
"""
return request.environ.get("LIVE_REQUEST", False) | 1e5e64901715131f363d6d343acbd4d631cf6b6f | 3,632,237 |
import requests
from bs4 import BeautifulSoup
def get_videos(episode):
"""
Get the list of videos.
:return: list
"""
videos = []
html = requests.get(episode).text
mlink = SoupStrainer('p', {'class':'vidLinksContent'})
soup = BeautifulSoup(html, parseOnlyThese=mlink)
items = soup.fi... | 34f13b9ace698738c62be6ac3794c9937844ab03 | 3,632,238 |
from typing import List
import logging
def validate_documentation_files(documentation_dir: str,
files_to_validate: List[str] = None):
"""Validate documentation files in a directory."""
file_paths = list(filesystem_utils.recursive_list_dir(documentation_dir))
do_smoke_test = bool... | 80a4b4b5f3ca42234cf3d2db86669f71c245e313 | 3,632,239 |
def _add_reference_resources(data):
"""Add genome reference information to the item to process.
"""
aligner = data["config"]["algorithm"].get("aligner", None)
align_ref, sam_ref = genome.get_refs(data["genome_build"], aligner, data["dirs"]["galaxy"])
data["align_ref"] = align_ref
data["sam_ref"]... | 63b4d7f70e6074341f84429d4d4e90cfa56d8fab | 3,632,240 |
def parse_solid_selection(pipeline_def, solid_selection):
"""Take pipeline definition and a list of solid selection queries (inlcuding names of solid
invocations. See syntax examples below) and return a set of the qualified solid names.
It currently only supports top-level solids.
Query syntax exa... | 6a69d79f0bdcf459c213262f05c06f9c0b256854 | 3,632,241 |
def _equal(v1, v2):
"""Same type as well."""
if isinstance(v2, float) and np.isinf(v2):
return True
if isinstance(v2, str):
v2 = th.string(v2)
return v1 == v2 | 0e5803da376019b93b6f3084cfb10fc0c36d873a | 3,632,242 |
def dec_prefix(value, restricted=True):
"""Get an appropriate decimal prefix for a number.
:param value: the number
:type value: int or float
:param bool restricted: if ``True`` only integer powers of 1000 are used,
i.e. *hecto, deca, deci, centi* are skipped
:return: de... | ecd78692a2638aa06b44292219f35488eb294667 | 3,632,243 |
from datetime import datetime
def _download_coaching(
loc_id: str,
start_date: datetime.datetime,
end_date: datetime.datetime = None,
collection: str = "CoachingActionEntries",
base = "prod",
pipeline_name = "sleep_quality"):
"""Queries the database for given location id, source id and i... | 8247446d6358a09b752c45d83d20bda59d3dc296 | 3,632,244 |
import random
def Make_Random(sents):
"""
Make random parses (from LG-parser "any"), to use as baseline
"""
any_dict = Dictionary('any') # Opens dictionary only once
po = ParseOptions(min_null_count=0, max_null_count=999)
po.linkage_limit = 100
options = 0x00000000 | BIT_STRIP #| BIT_U... | d32d0b17935c7c5951e817f156de6223ee7f0d1d | 3,632,245 |
def get_published_online_date(crossref_data):
"""
This function pulls the published online date out of the crossref data and returns it as an arrow date object
:param doi: the DOI of interest that you want the published online date for
:returns: arrow date object for published online date if it exists
... | 5d2f506f34ff956b344d1663b78ef1fb72dc3d04 | 3,632,246 |
from typing import OrderedDict
def pyvcf_calls_to_sample_info_list(calls):
"""
Given pyvcf.model._Call instances, return a dict mapping each sample
name to its per-sample info:
sample name -> field -> value
"""
return OrderedDict(
(call.sample, call.data._asdict()) for call in call... | 937a748b3a0ff26a28ff4a4db5e1505dbb927ff9 | 3,632,248 |
def DesignPatch(Er, h, Freq):
"""
Returns the patch_config parameters for standard lambda/2 rectangular microstrip patch. Patch length L and width W are calculated and returned together with supplied parameters Er and h.
Returned values are in the same format as the global patchr_config variable, so can be... | 90b35a7c46f96c977ccd5ce4fed987d0c1beccd6 | 3,632,249 |
from typing import Optional
def injection_file_name(
science_case: str, num_injs_per_redshift_bin: int, task_id: Optional[int] = None
) -> str:
"""Returns the file name for the raw injection data without path.
Args:
science_case: Science case.
num_injs_per_redshift_bin: Number of injectio... | 57b034b6a60c317f0c071c1313d0d99f2802db30 | 3,632,250 |
def focal_general_triplet_loss(embs, labels, minibatch_size, alpha=0.2):
"""
NOTE: In order for this loss to work properly, it is prefered that
labels contains several repetitions. In other word:
len(np.unique(labels))!=len(labels)
"""
classes = tf.one_hot(labels,depth=minibatch_size)
# Cla... | 2dc3d531051a61217d1429c1c10c44f9422cec29 | 3,632,251 |
def angle_between(v1, v2):
""" Returns the angle in degrees between vectors 'v1' and 'v2'."""
v1_u = unit_vector(v1)
v2_u = unit_vector(v2)
return np.degrees(np.arccos(np.clip(np.dot(v1_u, v2_u), -1.0, 1.0))) | 01ccbdd26398b1dbb14e08766c6fee4ec9d8006e | 3,632,252 |
def SUM(A: pd.DataFrame, n) -> pd.DataFrame:
"""Sum (Time Series)
Args:
A (pd.DataFrame): factor data with multi-index
n: days
Returns:
pd.DataFrame: sum data with multi-index
"""
At = pivot_table(A)
res = At.rolling(n, min_periods=int(n/2)).sum()
res = stack_table(re... | a761d854b516be3dd3d52bcc0060d87e074c9bf9 | 3,632,253 |
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):
key_value = l.... | 05769171ffe2e57e1022ff40b9c3ed2b82bb31bc | 3,632,254 |
def query_add(session, *objs):
"""Add `objs` to `session`."""
for obj in objs:
session.add(obj)
session.commit()
return objs | 95ffa9e0f5a4a9255f8b0b063c5bd092f0f66039 | 3,632,256 |
from re import T
from typing import Iterator
def scale_streams(s: Stream[T], factor: T) -> Stream[T]:
"""
scale streams
"""
def scale_generator(g: Iterator[T]) -> Iterator[T]:
"""
scale generator
"""
yield next(iter(g)) * factor
yield from scale_generator(g)
... | d6ddfc6c031c4e74ae284e9b92325bd86f6bcead | 3,632,257 |
def sd_title(bs4_object, target=None):
"""
:param bs4_object: An object of class BeautifulSoup
:param target: Target HTML tag. Defaults to class:title-text, a dict.
:return: Returns paper title from Science Direct
"""
if target is None:
target = {"class": "title-text"}
return bs4_o... | 8429fe680fafb86c773a0cd2b3280e893b95fc9a | 3,632,258 |
def generate_word_feat(sentence,
word_vocab_index,
word_max_size,
word_pad):
"""process words for sentence"""
sentence_words = tf.string_split([sentence], delimiter=' ').values
sentence_words = tf.concat([sentence_words[:word_max_size],
... | 433dc0c79998828a95d87f8dce16f4209a017229 | 3,632,259 |
def split_formula(formula, net_names_list):
"""
Splits the formula into two parts - the structured and unstructured part.
Parameters
----------
formula : string
The formula to be split, e.g. '~ 1 + bs(x1, df=9) + dm1(x2, df=9)'.
net_names_list : list of strings
A... | 1fce8617cbdaf767c1aebb6d0d685ca63975c820 | 3,632,260 |
from math import ceil
from struct import pack
def message(
command=0,
payload_size=0,
data_type=0,
data_count=0,
parameter1=0,
parameter2=0,
payload=b"",
):
"""Assemble a Channel Access message datagram for network transmission"""
if type(command) == str:
command = commands... | babbc4830a147f47819733095e0afe45b77c1b33 | 3,632,262 |
def polynomial(x, degree=1, add_bias_coefs=False):
"""used to calculate the polynomial coefficients of a given array.
Args:
x (array): the input array to be calculated.
degree (int, optional): polynominal degree. Defaults to 1.
add_bias_coefs (bool, optional): set True if you wan to add... | fdfc6e8c7e00e56636f07cc115a57f997630b5e2 | 3,632,263 |
def plot_energy_group_comparison(df: pd.DataFrame, reverse_axes: bool = False, size: float = 5.0) -> \
sns.axisgrid.FacetGrid:
"""
Plot energy level recovery for a group of conformation sets.
:param df: DataFrame where the columns are Energy, Method, and Discovery. Energy is the energy level (kcal/m... | fbde0758fcb060c419bc1f55f07dcba6b1667111 | 3,632,264 |
def get_summary_mapping(inputs_df, oed_hierarchy, is_fm_summary=False):
"""
Create a DataFrame with linking information between Ktools `OasisFiles`
And the Exposure data
:param inputs_df: datafame from gul_inputs.get_gul_input_items(..) / il_inputs.get_il_input_items(..)
:type inputs_df: pandas.Da... | 2000cad2e91009807d9907ae671f97e5038456c1 | 3,632,265 |
def run_tests():
"""Run test suite.
"""
with virtualenv("benlew.is"):
with cd('~/repos/me'):
return run("nosetests") | ab56bb53e43f7f204782191130436f944d2dcdcf | 3,632,267 |
from typing import Dict
import requests
def ls( # pylint: disable=invalid-name
url: str, resource_type: str, headers: Dict[str, str]
) -> requests.Response:
"""
Get a list of all of the resources of a certain type.
"""
resource_url = generate_resource_url(url, resource_type)
return requests.g... | f028a26eb4dc14f70811f175f159b45579869869 | 3,632,268 |
def uniform(iterable):
"""
Returns a random variable that takes each value in `iterable` with equal
probability.
"""
iterable = tuple(iterable)
return RandomVariable({val: 1 for val in iterable}) | 80046c04ba91a4a09287241c9821a192b2f6dfe2 | 3,632,269 |
def remove_id3v2_footer( data ):
"""Remove ID3v2 footer tag if present"""
pos = len( data ) - 10
while pos > 0:
if data[pos:pos+3] == b'ID3' and data[pos+4] == 0:
if data[pos+3] == 2 or data[pos+3] == 3:
return data[:pos] + data[pos+decode_synchsafe_int( data[6:10] )+10:]
elif data[pos+3] == 4:
if da... | ab4014d7b14ac2027ed994cfbaefe7b4e46c2a5b | 3,632,270 |
def get_ilorest_client(oneview_client, server_hardware):
"""Generate an instance of the iLORest library client.
:param oneview_client: an instance of a python-hpOneView
:param: server_hardware: a server hardware uuid or uri
:returns: an instance of the iLORest client
:raises: InvalidParameterValue ... | c1de72a30d3814f7b869d905d9cf2c2584a425b3 | 3,632,271 |
def get_metric(metric):
"""获取使用的评估函数实例.
Arguments:
metric: str or classicML.metrics.Metric 实例,
评估函数.
Raises:
AttributeError: 模型编译的参数输入错误.
"""
if isinstance(metric, str):
if metric == 'binary_accuracy':
return metrics.BinaryAccuracy()
elif met... | 34eed6adabe622a975e14936b0b85f86b30cd28f | 3,632,272 |
import numpy
def compute_ld(chromosome, position, genotype_name, N=20):
"""
Returns ordered list of the N neighboring SNPs positions in high LD
---
parameters:
- name: snp_pk
description: pk of the SNP of interest
required: true
type: string
paramType: p... | 1b4c0449941876cbc8481d894d03a7178624ceee | 3,632,273 |
def load_user(userid):
"""
Flask-Login user_loader callback.
The user_loader function asks this function to get a User Object or return
None based on the userid.
The userid was stored in the session environment by Flask-Login.
user_loader stores the returned User object in current_user during ev... | 0059c0dd65790dee0bca52acd6f9657de8113e96 | 3,632,274 |
def flow_read(input_file, format=None):
"""
Reads optical flow from file
Parameters
----------
output_file: {str, pathlib.Path, file}
Path of the file to read or file object.
format: str, optional
Specify in what format the flow is raed, accepted formats: "png" or "flo"
... | 590cc6bf5a041a569a3f2b202435940ce3936d57 | 3,632,275 |
from itertools import combinations
from typing import List
from functools import reduce
from operator import mul
def max_triple_product_bare_bones(nums: List[int]) -> int:
"""
A bare-bones O(n3) method to determine the largest product of three numbers in a list
:param nums: the list of numbers
:retur... | 8053bc6e35120f6ee8eca2b24e81cbaa7713dfb3 | 3,632,276 |
def is_number(s: str):
"""
Args:
s: (str) string to test if it can be converted into float
Returns:
True or False
"""
try:
# Try the conversion, if it is not possible, error will be raised
float(s)
return True
except ValueError:
return False | 08b0572e66fafdcd239e9f419fa41b31620de2c5 | 3,632,277 |
def getProxyVirtualHostConfig( nodename, proxyname,):
"""Gets or creates a ProxyVirtualHostConfig object."""
m = "getProxyVirtualHostConfig:"
sop(m,"Entry. nodename=%s proxyname=%s" % ( nodename, proxyname, ))
proxy_id = AdminConfig.getid( '/Node:%s/Server:%s' % ( nodename, proxyname ) )
sop(m,"pro... | e115985ebbcb6db88814dc49783e3d1b54ef7a43 | 3,632,278 |
def relu6(name=None, collect=False):
"""Computes Rectified Linear 6: `min(max(features, 0), 6)`.
Args:
name: operation name.
collect: whether to collect this metric under the metric collection.
"""
return built_activation(tf.nn.relu6, name, collect) | b649a5fd646815053f956bc8d1d838330935666a | 3,632,279 |
def announcements(soup):
"""
** Announcements Tab**
"""
try:
_div = soup.find('div', {'class':'ex1'})
z= _div.find_all('a')
return True,collection(z)
except Exception as e:
return False,[str(e)] | 2c4013e954903f7e275a32e37f70293a086a1201 | 3,632,280 |
import requests
def analyze_comments_page(username, repo, per_page, page, print_comments, print_stage_results):
"""
Analyzes one page of GitHub comments. Helping function.
Parameters
----------
username : str
The GitHub alias of the repository owner
repo : str
The GitHub repo... | e3d153a0319db0bc723df65cb8a92533f9b37b82 | 3,632,281 |
def get_remotes(y, x):
"""
For a given pair of ``y`` (tech) and ``x`` (location), return
``(y_remote, x_remote)``, a tuple giving the corresponding indices
of the remote location a transmission technology is connected to.
Example: for ``(y, x) = ('hvdc:region_2', 'region_1')``,
returns ``('hvdc... | 3c479d818947362349982c77a9bbd87a97a3d4d5 | 3,632,282 |
from typing import List
def ingrid(x: float, y: float, subgrid: List[int]) -> bool:
"""Check if position (x, y) is in a subgrid"""
i0, i1, j0, j1 = subgrid
return (i0 <= x) & (x <= i1 - 1) & (j0 <= y) & (y <= j1 - 1) | d296d8a7abe5eeb3da8d57691755a2bd19dd15b6 | 3,632,283 |
from typing import Union
from pathlib import Path
from typing import Any
import json
def load_jsonl(path: Union[Path, str]) -> list[dict[str, Any]]:
""" Load from jsonl.
Args:
path: path to the jsonl file
"""
path = Path(path)
return [json.loads(line) for line in path.read_text().splitlines()] | a59d2920bfa491b1d4daa693b5e2e1b4846d6fc6 | 3,632,284 |
def getComUser(userId):
"""ユーザー情報を取得を処理するMapperを呼び出す
サービス層のExceptionをキャッチし、処理します。
:param userId: ユーザーデータID
"""
try:
result = __selectUser(userId)
return result
except OperationalError:
abort(500) | 90c656e9ac4646b651c40e7147aead20ebe2fe61 | 3,632,285 |
def to_rgb_array(image):
"""Convert a CARLA raw image to a RGB numpy array."""
array = to_bgra_array(image)
# Convert BGRA to RGB.
#print(array.shape)
array = array[:, :, :3]
array = array[:, :, ::-1]
return array | 2feeef439b25692ecc137d3bc4b1d1385b95ee7c | 3,632,286 |
import typing
def extract_features(data: typing.Union[list, np.ndarray],
attributes: list = None,
nvd_attributes: list = None,
nltk_feed_attributes: list = None,
share_hooks=True,
**kwargs):
"""Extract data by... | 3fd8f3b582dad0375b343b7ba6d1f4de225dc4eb | 3,632,288 |
def wrap(get_io_helper_func):
"""A decorator that takes one argument. The argument should be an instance
of the helper class returned by new_helper(). This decorator wraps a method
so that is may perform asynchronous IO using the helper instance. The
method being wrapped should take a keyword argumen... | f2cdd8009d1722a81d848ab05c3cb6f3acaf5e50 | 3,632,290 |
def loads(fn, sdata=None):
"""
Load compressed pickle
"""
print " loading", fn
fhd = gzip.open(fn, 'rb')
print " loading", fn, 'opened'
data = cPickle.load( fhd )
print " loading", fn, 'loaded'
fhd.close()
#print " loading", fn, 'closed', len(data), data.keys()
if sdata ... | 8d500eebe23a39ceaec90c113175b811f8b6a6c4 | 3,632,291 |
def internal_superset_url():
"""The URL under which the Superset instance can be reached by from mara (usually circumventing SSOs etc.)"""
return 'http://localhost:8088' | 8a66c1d2c0587e9e6a563d08506606d389c2e6be | 3,632,293 |
import tempfile
def temp():
"""
Create a temporary file
Returns
-------
str
Path of temporary file
"""
handle, name = tempfile.mkstemp()
return name | 5955f3ceabd30ba5bb487677d9382253e1fde50a | 3,632,294 |
def ignoreNamePath(path):
"""
For shutil.copytree func
:param path:
:return:
"""
path += ['.idea', '.git', '.pyc']
def ignoref(directory, contents):
ig = [f for f in contents if
(any([f.endswith(elem) for elem in path]))]
return ig
return ignoref | 9d51d53c8dae8fb2322c3f90ea0f451731395816 | 3,632,295 |
def cos_np(data1,data2):
"""numpy implementation of cosine similarity for matrix"""
print("warning: the second matrix will be transposed, so try to put the simpler matrix as the second argument in order to save time.")
dotted = np.dot(data1,np.transpose(data2))
norm1 = np.linalg.norm(data1,axis=1)
n... | 69680cbf1cef58e96ddcd16109dd9408054732e1 | 3,632,296 |
import logging
def log_scale_dataset(df, add_small_value=1, set_NaNs_to=-10):
"""
Takes the log10 of a DF + a small value (to prevent -infs),
and replaces NaN values with a predetermined value.
Adds the new columns to the dataset, and renames the original ones.
"""
number_columns = get_number... | 5dfcefc6e7a3dc5b5d8c7a5a05c8e42fbbf8e2cc | 3,632,297 |
def ul_model_evaluation(classifier, train_set, test_set, attack_set, beta=20):
"""
Evaluates performance of supervised and unsupervised learning algorithms
"""
y_pred_test = classifier.predict(test_set).astype(float)
y_pred_outliers = classifier.predict(attack_set).astype(float)
n_accurate_test... | d83a23fb0a5f7257fa434bb24d49a324e62659ac | 3,632,299 |
def get_one_hot_predictions(tcdcn, x, dim):
"""
This method gets a model (tcdcn), passes x through it
and gets it's prediction, then it gets one_hot
matrix representation of the predictions. depending on whether
tcdcn is RCN or a structured model, x can be an image
(in the former case) and a one... | 27bf3ad70f77e726ba8484dec8770211907dfbd5 | 3,632,301 |
def render_tablet_screen():
"""
Serves the page for the tablet backend.
:return: The tablet html file.
"""
return app.send_static_file('tablet.html') | d82f1bf75438e05c4745a7eb7e25c2223f8e98cc | 3,632,303 |
def add_content(resp, param, value):
"""Adds content/body of the response.
ecocnt_html: html body,
ecocnt_css: css body,
ecocnt_js: js body,
ecocnt_img: img body,
ecocnt_vid: video body,
ecocnt_audio: audio body,
"""
if param == "ecocnt_html":
t = loader.get_template("echo/t... | 07bc2bc61d9901ab09b0badaef643622eb270754 | 3,632,304 |
def intersection_over_union(box1, box2):
"""Returns the IoU critera for pct of overlap area
box = (left, right, bot, top), same as matplotlib `extent` format
>>> box1 = (0, 1, 0, 1)
>>> box2 = (0, 2, 0, 2)
>>> print(intersection_over_union(box1, box2))
0.25
>>> print(intersection_over_union... | 4825de855bd12fcaaebbfa337fc0f6faa9482a74 | 3,632,305 |
def fpsol(nu,u):
"""
reads the vector normal and slip vector returning strike, rake, dip
"""
dip=np.arccos(-1*nu[2])
if nu[0] ==0. and nu[1] == 0.:
str=0.
else:
str=np.arctan2(-1*nu[0],nu[1])
sstr=np.sin(str)
cstr=np.cos(str)
sdip=np.sin(dip)
cdip=... | 735e99dc9b00c1d22c6a6976892ed709840cc007 | 3,632,306 |
def create_short_ticket(access_token, expire_seconds=2592000, scene_id=0):
"""
创建临时二维码
:param access_token: 微信access_token
:param expire_seconds: 二维码过期时间
:param scene_id: 场景值ID
:return:
"""
target_url = 'https://api.weixin.qq.com/cgi-bin/qrcode/create?access_token=%s' % access_token
... | 30dc627d5319d8145854b568ce8b7a8d4e4eba69 | 3,632,307 |
from qtpy.QtWidgets import QDesktopWidget # noqa
def get_screen_size():
"""Get **available** screen size/resolution."""
if mpl.get_backend().startswith('Qt'):
# Inspired by spyder/widgets/shortcutssummary.py
widget = QDesktopWidget()
sg = widget.availableGeometry(widget.primaryScreen(... | 9575fbf1874d6dcf22e0ebb5a771015dfa570847 | 3,632,310 |
def potential_bond_keys(mgrph):
""" neighboring radical sites of a molecular graph
"""
ridxs = radical_sites(mgrph)
return tuple(frozenset([ridx1, ridx2])
for ridx1, ridx2 in combinations(ridxs, 2)
if ridx2 in atom_neighborhood_indices(mgrph, ridx1)) | ccbff81075cab38b3bc96b39885f1873c733bd93 | 3,632,311 |
def convolve(signal,kernel):
"""
This applies a kernel to a signal through convolution and returns the result.
Some magic is done at the edges so the result doesn't apprach zero:
1. extend the signal's edges with len(kernel)/2 duplicated values
2. perform the convolution ('same' mode)
... | 1eb31d9fdf2a6afa6ea08912f8b28f0ae4af64e6 | 3,632,312 |
def makemebv(gmat, meff):
"""Set up family-specific marker effects (GEBV)."""
qqq = np.zeros((gmat.shape))
for i in range(gmat.shape[0]):
for j in range(gmat.shape[1]):
if gmat[i, j] == 2:
qqq[i, j] = meff[j]*-1
elif gmat[i, j] == 1:
qqq[i, j] ... | 44cbcdeadbfee9b7e802e201ad589f9ebdcb11b3 | 3,632,313 |
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