content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def triplet_margin_loss(
anchor,
positive,
negative,
margin=0.1,
p=2,
use_cosine=False,
swap=False,
eps=1e-6,
scope='',
reduction=tf.losses.Reduction.SUM
):
"""
Computes the triplet margin loss
Args:
anchor: The tensor containing the anchor embeddings
... | 55e85a9ae98ab57458ae1a61a1dbd445deddd7cb | 13,900 |
def f_raw(x, a, b):
"""
The raw function call, performs no checks on valid parameters..
:return:
"""
return a * x + b | 89bbe9e7a08e3bf4bf37c3efa695ed20fdca95c5 | 13,901 |
from pyapprox.cython.barycentric_interpolation import \
def compute_barycentric_weights_1d(samples, interval_length=None,
return_sequence=False,
normalize_weights=False):
"""
Return barycentric weights for a sequence of samples. e.g. of seq... | 1711328af31b756c040455e0b03363def08e6504 | 13,902 |
import collections
def _generate_conversions():
"""
Generate conversions for unit systems.
"""
# conversions to inches
to_inch = {'microinches': 1.0 / 1000.0,
'mils': 1.0 / 1000.0,
'inches': 1.00,
'feet': 12.0,
'yards': 36.0,
... | 8fa4f625e693fe352b2bba0082d0b18c46f5bec1 | 13,903 |
def _ifail(repo, mynode, orig, fcd, fco, fca, toolconf):
"""
Rather than attempting to merge files that were modified on both
branches, it marks them as unresolved. The resolve command must be
used to resolve these conflicts."""
return 1 | 278bb52f96e1a82ce9966626be08bc6fdd0df65d | 13,904 |
from typing import Pattern
from typing import Optional
from typing import Callable
from typing import Union
import logging
def parser(
text: str,
*,
field: str,
pattern: Pattern[str],
type_converter: Optional[Callable] = None,
clean_up: Optional[Callable] = None,
limit_size: Optional[int] ... | 0b44fecf252399b3109efedffe0f561809982ea6 | 13,905 |
import os
def checkpoint_metrics_path(checkpoint_path, eval_name, file_name=None):
"""Gets a path to the JSON of eval metrics for checkpoint in eval_name."""
checkpoint_dir = os.path.dirname(checkpoint_path)
checkpoint_name = os.path.basename(checkpoint_path)
if eval_name:
# This bit of magic is defined b... | e176b873d13ae28f6a53100adba6ca437c4ce805 | 13,906 |
def colorize(text='', opts=(), **kwargs):
"""
Return your text, enclosed in ANSI graphics codes.
Depends on the keyword arguments 'fg' and 'bg', and the contents of
the opts tuple/list.
Return the RESET code if no parameters are given.
Valid colors:
'black', 'red', 'green', 'yellow', ... | 02ad24710413770cebdaa4265a1d40c69212ecc8 | 13,907 |
from re import T
def get_prediction(img_path, threshold):
"""
get_prediction
parameters:
- img_path - path of the input image
- threshold - threshold value for prediction score
method:
- Image is obtained from the image path
- the image is converted to image tensor ... | d6df91fb464b072b06ef759ad53aa00fb7d624ec | 13,908 |
def make_fixed_size(protein, shape_schema, msa_cluster_size, extra_msa_size,
num_res, num_templates=0):
"""Guess at the MSA and sequence dimensions to make fixed size."""
pad_size_map = {
NUM_RES: num_res,
NUM_MSA_SEQ: msa_cluster_size,
NUM_EXTRA_SEQ: extra_msa_size,... | f74306815dd7cd5291305c7b5c67cae4625c4d38 | 13,909 |
def plot_skymap_tract(skyMap, tract=0, title=None, ax=None):
"""
Plot a tract from a skyMap.
Parameters
----------
skyMap: lsst.skyMap.SkyMap
The SkyMap object containing the tract and patch information.
tract: int [0]
The tract id of the desired tract to plot.
title: st... | a8f1b25d8afedfbb0ed643b7954e615932031419 | 13,910 |
import json
def label(vertex):
""" Graph vertex label in dot format """
label = f"{vertex.name} {vertex.state or ''}\n{vertex.traceback or ''}"
label = json.dumps(label).replace("\\n", r"\l")
return f"[label={label}]" | a8604cfd837afbdba8b8ee7666d81df4b015ad2a | 13,911 |
import six
import hashlib
def compute_hashes_from_fileobj(fileobj, chunk_size=1024 * 1024):
"""Compute the linear and tree hash from a fileobj.
This function will compute the linear/tree hash of a fileobj
in a single pass through the fileobj.
:param fileobj: A file like object.
:param chunk_siz... | 8c6aed21ae59ecb3e5449ee0856be1d032108aa6 | 13,912 |
def imshow(axim, img, amp_range=None, extent=None,\
interpolation='nearest', aspect='auto', origin='upper',\
orientation='horizontal', cmap='jet') :
"""
extent - list of four image physical limits for labeling,
cmap: 'gray_r'
#axim.cla()
"""
imsh = axim.imshow(img, interpol... | 3483690b01c5d182877c3bf944fa5409d4cb9e69 | 13,913 |
def get_total():
"""
Return the rounded total as properly rounded string.
Credits:
https://github.com/dbrgn/coverage-badge
"""
cov = coverage.Coverage()
cov.load()
total = cov.report(file=Devnull())
class Precision(coverage.results.Numbers):
"""
A class for usin... | 9df511f0d895721061642c2fb88268490e27cc0b | 13,914 |
def _infer_subscript_list(context, index):
"""
Handles slices in subscript nodes.
"""
if index == ':':
# Like array[:]
return ValueSet([iterable.Slice(context, None, None, None)])
elif index.type == 'subscript' and not index.children[0] == '.':
# subscript basically implies ... | bde1de5e7604d51e6c85e429ceb2102d79e91ca6 | 13,915 |
def count_by_guess(dictionary, correctly=False):
"""
Count the number of correctly/incorrectly guessed images for a dataset
:param dictionary:
:param correctly:
:return:
"""
guessed = 0
for response in dictionary:
guessed = guessed + count_by_guess_user(response, correctly)
... | d1328a63d3029707131f1932be1535dabb62ab66 | 13,916 |
def get_game_by_index(statscursor, table, index):
""" Holds get_game_by_index db related data """
query = "SELECT * FROM " + table + " WHERE num=:num"
statscursor.execute(query, {'num': index})
return statscursor.fetchone() | 754a83f2281ad095ffc32eb8a03c95490bd5f815 | 13,917 |
def create_queue():
"""Creates the SQS queue and returns the queue url and metadata"""
conn = boto3.client('sqs', region_name=CONFIG['region'])
queue_metadata = conn.create_queue(QueueName=QUEUE_NAME, Attributes={'VisibilityTimeout':'3600'})
if 'queue_tags' in CONFIG:
conn.tag_queue(QueueUrl=qu... | ae61c542182bc1238b76bf94991e50809bace595 | 13,918 |
def db_describe(table, **args):
"""Return the list of columns for a database table
(interface to `db.describe -c`). Example:
>>> run_command('g.copy', vector='firestations,myfirestations')
0
>>> db_describe('myfirestations') # doctest: +ELLIPSIS
{'nrows': 71, 'cols': [['cat', 'INTEGER', '20'], ... | 6265a2f6dcc26fcd1fcebb5ead23abfb37cfa179 | 13,919 |
def objective_func(x, cs_objects, cs_data):
"""
Define the objective function
:param x: 1D array containing the voltages to be set
:param args: tuple containing all extra parameters needed
:return: average count rate for 100 shots
"""
x = np.around(x,2)
try:
flag_range = 0
... | 677b6455b0db177a3a4f716ced3dd309c711cf74 | 13,920 |
def getHPELTraceLogAttribute(nodename, servername, attributename):
""" This function returns an attribute of the HPEL Trace Log for the specified server.
Function parameters:
nodename - the name of the node on which the server to be configured resides.
servername - the name of the server w... | 8003066ec41ee07dab311690d0687d7f79e6952a | 13,921 |
def dispersionTable(adata):
"""
Parameters
----------
adata
Returns
-------
"""
if adata.uns["ispFitInfo"]["blind"] is None:
raise ("Error: no dispersion model found. Please call estimateDispersions() before calling this function")
disp_df = pd.DataFrame({"gene_id": adata... | 7f7b4c122ffc42402248ec55155c774c77fbad51 | 13,922 |
def L10_indicator(row):
"""
Determine the Indicator of L10 as one of five indicators
"""
if row < 40:
return "Excellent"
elif row < 50:
return "Good"
elif row < 61:
return "Fair"
elif row <= 85:
return "Poor"
else:
return "Hazard" | 10656a76e72f99f542fd3a4bc2481f0ef7041fa9 | 13,923 |
def create_ip_record(
heartbeat_df: pd.DataFrame, az_net_df: pd.DataFrame = None
) -> IpAddress:
"""
Generate ip_entity record for provided IP value.
Parameters
----------
heartbeat_df : pd.DataFrame
A dataframe of heartbeat data for the host
az_net_df : pd.DataFrame
Option ... | 63deb15081f933b0a445d22eed25646782af4221 | 13,924 |
import re
def extract_version(version_file_name):
"""Extracts the version from a python file.
The statement setting the __version__ variable must not be indented. Comments after that
statement are allowed.
"""
regex = re.compile(r"^__version__\s*=\s*['\"]([^'\"]*)['\"]\s*(#.*)?$")
with open(v... | 1cc70ba4bf69656bb8d210a49c236e38eba59513 | 13,925 |
def powerlaw_loglike(data, theta):
"""Return the natural logarithm of the likelihood P(data | theta) for our
model of the ice flow.
data is expected to be a tuple of numpy arrays = (x, y, sigma)
theta is expected to be an array of parameters = (intercept, slope)
"""
x, y, sigma = data
n = ... | 98650e66d2a16762b2534be9083b6b92e0d9e9fd | 13,926 |
def get_conv(dim=3):
"""Chooses an implementation for a convolution layer."""
if dim == 3:
return nn.Conv3d
elif dim == 2:
return nn.Conv2d
else:
raise ValueError('dim has to be 2 or 3') | 4152984ecf7220dc4693013ee567822a2487e225 | 13,927 |
import os
import errno
def resolve_path(path, parent=None):
"""Resolves the absolute path of the specified file.
Args:
path (str): Path to resolve.
parent (str): The directory containing ``path`` if ``path`` is relative.
Returns:
The absolute path.
Raises:
... | c8088bc2dcee62b0ed12e8b0902a35e2e291313c | 13,928 |
import ipykernel
from notebook.notebookapp import list_running_servers
import re
import requests
def notebook_metadata():
"""Attempts to query jupyter for the path and name of the notebook file"""
error_message = "Failed to query for notebook name, you can set it manually with the WANDB_NOTEBOOK_NAME environm... | 47cd98371605240ae52ca90fda23c46b9bde52d0 | 13,929 |
async def create_mute_role(bot, ctx):
"""Create the mute role for a guild"""
perms = discord.Permissions(
send_messages=False, read_messages=True)
mute_role = await ctx.guild.create_role(
name='Muted', permissions=perms,
reason='Could not find a muted role in the process of muting or... | 9128de3a7f4f841e47531699a878a1c18d8be9d5 | 13,930 |
import json
import uuid
def build_request_data(useralias,
req_node):
"""build_request_data
:param useralias: user alias for directory name
:param req_node: simulated request node
"""
if "file" not in req_node:
return None
use_uniques = req_node["unique_names"]... | 938c79c290e1e4c086e6d48f71cbd0b965d36b36 | 13,931 |
def _get_stmt_lists(self):
"""
Returns a tuple of the statement lists contained in this `ast.stmt`
node. This method should only be called by an `ast.stmt` node.
"""
if self.is_simple():
return ()
elif self.is_body():
return (self.body,)
elif self.is_body_orelse():
r... | 0ec85481bc4261ae77ced0ae32c72081ef80c651 | 13,932 |
def get_article(name):
"""a general function to get an article, returns None if doesn't exist
"""
article = None
if name is not None:
try:
article = Article.objects.get(name=name)
except Article.DoesNotExist:
pass
return article | d69e801a1d18ccf81753cc35ce2afa645b304fba | 13,933 |
import tempfile
import os
import shutil
def _CreateNginxConfigMapDir():
"""Returns a TemporaryDirectory containing files in the Nginx ConfigMap."""
if FLAGS.nginx_conf:
nginx_conf_filename = FLAGS.nginx_conf
else:
nginx_conf_filename = (
data.ResourcePath('container/kubernetes_nginx/http.conf'))... | 9f9cde4e270e60ae03e65af61017ead886e89d18 | 13,934 |
def abbreviateLab(lab):
"""Lab names are very long and sometimes differ by punctuation or typos. Abbreviate for easier comparison."""
labAbbrev = apostropheSRe.sub('', lab)
labAbbrev = firstLetterRe.sub(r'\1', labAbbrev, count=0)
labAbbrev = spacePunctRe.sub('', labAbbrev, count=0)
return labAbbrev | dce4a1d0f6302a2968fe701d067b209fb61b8930 | 13,935 |
def backproject(depth, intrinsics, instance_mask):
""" Back-projection, use opencv camera coordinate frame.
"""
cam_fx = intrinsics[0, 0]
cam_fy = intrinsics[1, 1]
cam_cx = intrinsics[0, 2]
cam_cy = intrinsics[1, 2]
non_zero_mask = (depth > 0)
final_instance_mask = np.logical_and(insta... | 9828197b646342ec76cc21b1083540d0fe62978f | 13,936 |
def if_any(
_data,
*args,
_names=None,
_context=None,
**kwargs,
):
"""Apply the same predicate function to a selection of columns and combine
the results True if any element is True.
See Also:
[`across()`](datar.dplyr.across.across)
"""
if not args:
args = (None,... | 41bf4a14cc8b16845f7d0dd8138871a7ccfad66f | 13,937 |
def get_inpgen_para_from_xml(inpxmlfile, inpgen_ready=True):
"""
This routine returns an python dictionary produced from the inp.xml
file, which can be used as a calc_parameters node by inpgen.
Be aware that inpgen does not take all information that is contained in an inp.xml file
:param inpxmlfile... | e0454061da7c817b4dfe3f1eb0257493dc92437b | 13,938 |
import os
def confirm_revocation(cert):
"""Confirm revocation screen.
:param cert: certificate object
:type cert: :class:
:returns: True if user would like to revoke, False otherwise
:rtype: bool
"""
return util(interfaces.IDisplay).yesno(
"Are you sure you would like to revoke ... | d64c64a6426e521fa8d9edc817b44a50fdd75894 | 13,939 |
def Gaussian(y, model, yerr):
"""Returns the loglikelihood for a Gaussian distribution.
In this calculation, it is assumed that the parameters
are true, and the loglikelihood that the data is drawn from
the distribution established by the parameters is calculated
Parameters
----------
model... | d9eaa41b95006a9d17907582b804a4921f672141 | 13,940 |
def clean_us_demographics(us_demographics_spark, spark_session):
"""
Clean data from us_demographics
Args:
us_demographics (object): Pyspark dataframe object
spark_session (object): Pyspark session
Returns:
(object): Pyspark dataframe with cleaned data
"""
s... | dcf812bf64a2f6c3b908d895488e1a57e1729301 | 13,941 |
from datetime import datetime
def parse_date(date=None):
"""
Parse a string in YYYY-MM-DD format into a datetime.date object.
Throws ValueError if input is invalid
:param date: string in YYYY-MM-DD format giving a date
:return: a datetime.date object corresponding to the date given
"""
if... | a4c6cef85dabd445dd308fdd5f2c20a38accd6de | 13,942 |
def status():
""" Incoming status handler: forwarded by ForwardServerProvider """
req = jsonex_loads(request.get_data())
status = g.provider._receive_status(req['status'])
return {'status': status} | 3a50ff8d829a7bf37b84871897335345496dbc49 | 13,943 |
def get_feature_extractor_info():
"""Return tuple of pretrained feature extractor and its best-input image size for the extractor"""
return get_pretrained_feature_extractor(), K_MODEL_IMAGE_SIZE | bdec6d5a2d402f659b9a001f4082f6b5e33ca3cc | 13,944 |
import networkx
def nx_find_connected_limited(graph, start_set, end_set, max_depth=3):
"""Return the neurons in end_set reachable from start_set with limited depth."""
reverse_graph = graph.reverse()
reachable = []
for e in end_set:
preorder_nodes = list(
(
network... | 4322f4231be73b575d05442f09608c71c3b9f605 | 13,945 |
def hexbyte_2integer_normalizer(first_int_byte, second_int_btye):
"""Function to normalize integer bytes to a single byte
Transform two integer bytes to their hex byte values and normalize
their values to a single integer
Parameters
__________
first_int_byte, second_int_byte : int
inte... | a3bbe75014b6e08607314b615440039bab245f04 | 13,946 |
def wrapAngle(angle):
""" Ensures angle is between -360 and 360
arguments:
angle - float angle that you want to be between -360 and 360
returns:
float - angle between -360 and 360
"""
printDebug("In wrapAngle, angle is " + str(angle), DEBUG_INFO)
if angle >... | 4ec1ee51b895075053468dfa5d09f988d15413d1 | 13,947 |
import os
def _save_first_checkpoint(keras_model, custom_objects, config):
"""Save first checkpoint for the keras Estimator.
Args:
keras_model: an instance of compiled keras model.
custom_objects: Dictionary for custom objects.
config: Estimator config.
Returns:
The path where keras model chec... | 790cc96785c6a2a66d19af886c82e0dc354704c9 | 13,948 |
import logging
import os
def build_reference_spectrum_list_from_config_file(config):
"""
Read reference spectrum file glob(s) from configuration file to create
and return a list of ReferenceSpectrum instances.
:param config: configparser instance
:return: list of ReferenceSpectrum instances
"... | 31d4f54e786846122845b7eb6d73dfa1353ef7d6 | 13,949 |
def make_window(signal, sample_spacing, which=None, alpha=4):
"""Generate a window function to be used in PSD analysis.
Parameters
----------
signal : `numpy.ndarray`
signal or phase data
sample_spacing : `float`
spacing of samples in the input data
which : `str,` {'welch', 'han... | 5ef18c990225b6610ee10c848ab4ee0b2ce0fc9b | 13,950 |
from typing import Dict
from typing import Union
def set_units(
df: pd.DataFrame, units: Dict[str, Union[pint.Unit, str]]
) -> pd.DataFrame:
"""Make dataframe unit-aware. If dataframe is already unit-aware, convert to specified
units. If not, assume values are in specified unit.
Parameters
------... | 8a0cf821e3e0d1ba7b1b8c3dbdddb5f517ea0acb | 13,951 |
def address_repr(buf, reverse: bool = True, delimit: str = "") -> str:
"""Convert a buffer into a hexlified string."""
order = range(len(buf) - 1, -1, -1) if reverse else range(len(buf))
return delimit.join(["%02X" % buf[byte] for byte in order]) | 6b4b8921d6280cd688c3bfcfca82b2b5546001e7 | 13,952 |
import re
def _highlight(line1, line2):
"""Returns the sections that should be bolded in the given lines.
Returns:
two tuples. Each tuple indicates the start and end of the section
of the line that should be bolded for line1 and line2 respectively.
"""
start1 = start2 = 0
match = re.search(r'\S', ... | d9bf7667e24d21e6f91b656af0697765c2b74f55 | 13,953 |
import subprocess
def get_comrec_build(pkg_dir, build_cmd=build_py):
""" Return extended build command class for recording commit
The extended command tries to run git to find the current commit, getting
the empty string if it fails. It then writes the commit hash into a file
in the `pkg_dir` path, ... | f704fecc1c0001c3feeb66ccc4e251c019694c1b | 13,954 |
def get_detected_objects_new(df, siglim=5, Terr_lim=3, Toffset=2000):
"""
Get a dataframe with only the detected objects.
:param df: A DataFrame such as one output by get_ccf_summary with N > 1
:param siglim: The minimum significance to count as detected
:param Terr_lim: The maximum number of standa... | 7662086053c093b9eb19ffe7c56f5cf7914b1ab8 | 13,955 |
def cmp(a, b):
"""
Python 3 does not have a cmp function, this will do the cmp.
:param a: first object to check
:param b: second object to check
:return:
"""
# convert to lower case for string comparison.
if a is None:
return -1
if type(a) is str and type(b) is str:
a... | c82837a0d8887f55fdd1175b5d828742529b3e37 | 13,956 |
def pe(cmd, shell=True):
"""
Print and execute command on system
"""
ret = []
for line in execute(cmd, shell=shell):
ret.append(line)
print(line, end="")
return ret | 0a238be68a7c383153834d45fbf3193f9b8c9a72 | 13,957 |
import os
def create_photo(user_id, text: str, greencolor: bool): # color: tuple(R,G,B)
"""
:param user_id: int or str
:param text: str
:param greencolor: bool
True = зеленый (204, 255, 204)
False = серый (240, 238, 237)
"""
color = (204, 255, 204)
if n... | c06c15f450d614febfc52d3f274e80b6d79d6688 | 13,958 |
def crop(image):
"""
Method to crop out the uncessary white parts of the image.
Inputs:
image (numpy array): Numpy array of the image label.
Outputs:
image (numpy array): Numpy array of the image label, cropped.
"""
image = ImageOps.invert(image)
imageBox = image.getbbox()
imag... | 37a12733bcda66a9da16d72ff3fae749784481a0 | 13,959 |
def all_pairs_normalized_distances(X):
"""
We can't really compute distances over incomplete data since
rows are missing different numbers of entries.
The next best thing is the mean squared difference between two vectors
(a normalized distance), which gets computed only over the columns that
tw... | c744c6ac87cbd3760d6512178747ac60794d616a | 13,960 |
import torch
def forward_pass(model, target_angle, mixed_data, conditioning_label, args):
"""
Runs the network on the mixed_data
with the candidate region given by voice
"""
target_pos = np.array([
FAR_FIELD_RADIUS * np.cos(target_angle),
FAR_FIELD_RADIUS * np.sin(target_angle)
... | e9644b01ea04b08ae92d50d3c7944e0d72213b2b | 13,961 |
import select
from typing import Optional
from datetime import datetime
import pytz
async def get_event_by_code(code: str, db: AsyncSession) -> Event:
"""
Get an event by its code
"""
statement = select(Event).where(Event.code == code)
result = await db.execute(statement)
event: Optional[Event... | 592cd6b5aad7b12a98889bf82ea7e32a55b8832e | 13,962 |
def get(name):
"""Returns an OpDef for a given `name` or None if the lookup fails."""
with _sync_lock:
return _registered_ops.get(name) | 75e3ba3601f1ad8f67e77046a9b286bee8e60be6 | 13,963 |
def angle_detect_dnn(img, adjust=True):
"""
文字方向检测
"""
h, w = img.shape[:2]
ROTATE = [0, 90, 180, 270]
if adjust:
thesh = 0.05
xmin, ymin, xmax, ymax = int(thesh * w), int(thesh * h), w - int(thesh * w), h - int(thesh * h)
img = img[ymin:ymax, xmin:xmax] ##剪切图片边缘
in... | a3fc8513afce26e96a315a606acfd9be9feaa376 | 13,964 |
def get_correct_line(df_decisions):
"""
The passed df has repeated lines for the same file (same chemin_source).
We take the most recent one.
:param df_decisions: Dataframe of decisions
:return: Dataframe without repeated lines (according to the chemin_source column)
"""
return df_decisions.... | 989f1aba1c5e0c61f8b7ca1c883baf4dd181ebbc | 13,965 |
def fix_1(lst1, lst2):
"""
Divide all of the elements in `lst1` by each element in `lst2`
and return the values in a list.
>>> fix_1([1, 2, 3], [0, 1])
[1.0, 2.0, 3.0]
>>> fix_1([], [])
[]
>>> fix_1([10, 20, 30], [0, 10, 10, 0])
[1.0, 2.0, 3.0, 1.0, 2.0, 3.0]
"""
out = []
... | 7929cfc19952a829c66c18af967668d1015f8477 | 13,966 |
def user_wants_upload():
"""
Determines whether or not the user wants to upload the extension
:return: boolean
"""
choice = input("Do you want to upload your extension right now? :")
if "y" in choice or "Y" in choice:
return True
else:
return False | 67643d1ccf8d1ffe23ddc503cd8e9f4dc4e98707 | 13,967 |
def has_genus_flag(df, genus_col="mhm_Genus", bit_col="mhm_HasGenus", inplace=False):
"""
Creates a bit flag: `mhm_HasGenus` where 1 denotes a recorded Genus and 0 denotes the contrary.
Parameters
----------
df : pd.DataFrame
A mosquito habitat mapper DataFrame
genus_col : str, default=... | 7e178f7570f8de436521047e012518e6f5ee6a72 | 13,968 |
from typing import Tuple
def compass(
size: Tuple[float, float] = (4.0, 2.0),
layer: Layer = gf.LAYER.WG,
port_type: str = "electrical",
) -> Component:
"""Rectangular contact pad with centered ports on rectangle edges
(north, south, east, and west)
Args:
size: rectangle size
... | fefa0842958fb91b870eb78e2170a81d7c8daaa9 | 13,969 |
def get_service(vm, port):
"""Return the service for a given port."""
for service in vm.get('suppliedServices', []):
if service['portRange'] == port:
return service | d617771c25c69ee874b0bc64adcc735aa876f929 | 13,970 |
async def async_setup_entry(hass, config_entry):
"""Set up AirVisual as config entry."""
entry_updates = {}
if not config_entry.unique_id:
# If the config entry doesn't already have a unique ID, set one:
entry_updates["unique_id"] = config_entry.data[CONF_API_KEY]
if not config_entry.opt... | e09b0c8e499a055123a88503cac4d1d1492a3d53 | 13,971 |
def rotation_point_cloud(pc):
"""
Randomly rotate the point clouds to augment the dataset
rotation is per shape based along up direction
:param pc: B X N X 3 array, original batch of point clouds
:return: BxNx3 array, rotated batch of point clouds
"""
# rotated_data = np.zeros(pc.shape, dtyp... | f1f84b9dad06bea6c377559d8b4a64be88031847 | 13,972 |
import time
def alliance_system_oneday(mongohandle, alliance_id, system):
"""find by corp and system - one day"""
allkills = mongohandle.allkills
system = int(system)
timeframe = 24 * 60 * 60
gmtminus = time.mktime(time.gmtime()) - timeframe
cursor = allkills.find({"alliance_id": alliance_id,
... | b951f11f606352dc6614e1ff1c587c3a64ed1ea8 | 13,973 |
def slit_select(ra, dec, length, width, center_ra=0, center_dec=0, angle=0):
"""
:param ra: angular coordinate of photon/ray
:param dec: angular coordinate of photon/ray
:param length: length of slit
:param width: width of slit
:param center_ra: center of slit
:param center_dec: center of s... | a3047a59bbc8566d261f1d52f92b437ad2b26d52 | 13,974 |
def login():
""" Logs in user """
req = flask.request.get_json(force=True)
username = req.get('username', None)
password = req.get('password', None)
user = guard.authenticate(username, password)
ret = {'access_token': guard.encode_jwt_token(user)}
return ret, 200 | b577c7982bf65d3a24cfd3f116f5cb128079cd1f | 13,975 |
def statuses_filter(auth, **params):
"""
Collect tweets from the twitter statuses_filter api.
"""
endpoint = "https://stream.twitter.com/1.1/statuses/filter.json"
if "follow" in params and isinstance(params["follow"], (list, tuple)):
params["follow"] = list_to_csv(params["follow"])
if ... | e81f85d5c747a4bcca8fc9b3b82d362905404452 | 13,976 |
def adjust_hue(image, hue_factor):
"""Adjusts hue of an image.
The image hue is adjusted by converting the image to HSV and
cyclically shifting the intensities in the hue channel (H).
The image is then converted back to original image mode.
`hue_factor` is the amount of shift in H channel and must... | 52390b83a60cc8f23632f198a558b518d687f94e | 13,977 |
import json
import requests
import time
def lambda_handler(event, context):
"""Sample pure Lambda function
Parameters
----------
event: dict, required
API Gateway Lambda Proxy Input Format
Event doc: https://docs.aws.amazon.com/apigateway/latest/developerguide/set-up-lambda-proxy-int... | 05b5da6e2c2aff16c43a3822978f0cd800370bed | 13,978 |
def compareDict(a, b):
"""
Compare two definitions removing the unique Ids from the entities
"""
ignore = ['Id']
_a = [hashDict(dict(x), ignore) for x in a]
_b = [hashDict(dict(y), ignore) for y in b]
_a.sort()
_b.sort()
return _a == _b | 19f0340064c95584a4e80ecb4a090c25944f6923 | 13,979 |
import traceback
import time
def create_twitter_auth(cf_t):
"""Function to create a twitter object
Args: cf_t is configuration dictionary.
Returns: Twitter object.
"""
# When using twitter stream you must authorize.
# these tokens are necessary for user authe... | 0eff78ce2dba182d739cc2bb082d5053a6a8847a | 13,980 |
def _project(doc, projection):
"""Return new doc with items filtered according to projection."""
def _include_key(key, projection):
for k, v in projection.items():
if key == k:
if v == 0:
return False
elif v == 1:
return... | 0f2cd190e73b39ceeec0f850054baab1dd357587 | 13,981 |
import random
def random_swap(words, n):
"""
Randomly swap two words in the sentence n times
Args:
words ([type]): [description]
n ([type]): [description]
Returns:
[type]: [description]
"""
def swap_word(new_words):
random_idx_1 = random.randint(0, l... | d6916404c363176f13010d006cd61354dcd4e16e | 13,982 |
def get_dist_for_angles(dict_of_arrays, clusters, roll, pitch, yaw, metric='3d', kind='max'):
"""
Calculate a single distance metric for a combination of angles
"""
if (dict_of_arrays['yaw_corr'] == 0).all():
rot_by_boresight = apply_boresight_same(dict_of_arrays, roll, pitch, yaw)
else:... | 4db8a68cebc845de942817eb9eb28e57d2db5cc4 | 13,983 |
import asyncio
async def stream():
"""Main streaming loop for PHD"""
while True:
if phd_client.is_connected and manager.active_connections:
response = await phd_client.get_responses()
if response is not None:
# Add to the websocket queue
# If it ... | 19e1934e8cb48fa66f8ab3f61ca013fd19b040fc | 13,984 |
def filter_camera_angle(places, angle=1.):
"""Filter pointclound by camera angle"""
bool_in = np.logical_and((places[:, 1] * angle < places[:, 0]),
(-places[:, 1] * angle < places[:, 0]))
return places[bool_in] | 9956c5b001989c5f64d935087a1e13ffbc6469b7 | 13,985 |
def load_nifti(path: str) \
-> tuple[np.ndarray, np.ndarray, nib.nifti1.Nifti1Header]:
"""
This function loads a nifti image using
the nibabel library.
"""
# Extract image
img = nib.load(path)
img_aff = img.affine
img_hdr = img.header
# Extract the actual data in a numpy arra... | 9e76e3f6e6d200b3cd3be34b3780f8fe84cad53e | 13,986 |
def f5_list_policy_hostnames_command(client: Client, policy_md5: str) -> CommandResults:
"""
Get a list of all policy hostnames.
Args:
client (Client): f5 client.
policy_md5 (str): MD5 hash of the policy.
"""
result = client.list_policy_hostnames(policy_md5)
table_name = 'f5 da... | 38263c85480ba5d7de8a21509820052444b4cdab | 13,987 |
def predict(m, count, s, A):
"""predict the chain after s
calculate the probability of a m-length chain,
then return chains.
CAUTION the number of chains maybe less then count
args:
m: the length of predict chain
count: the number of predict chain
s: the last element of the... | f45acc67c97204efdabb48f29d73277fb4b75967 | 13,988 |
import mimetypes
import gzip
import os
def read_lengths_from_fastx_file(fastx_file):
"""
@param fastx_file: file path
@type fastx_file: str
@rtype: dict[str, int]
"""
file_type = mimetypes.guess_type(fastx_file)[1]
if file_type == 'gzip':
f = gzip.open(fastx_file, "rt")
elif n... | 6aef86176269674a96a707bc5f7cbb9798237f57 | 13,989 |
def f_multidim(anchors, basis, distance_measurements, coeffs):
"""
:param anchors: anchors dim x N
:param basis: basis vectors K x M
:param distance_measurements: matrix of squared distances M x N
:param coeffs: coefficient matrix dim x K
:return: vector of differences between estimate distanc... | cd9f7fa67e6cbf3cfb5fe14e53b019713c56aa26 | 13,990 |
def getHomography(indict, outdict, outsize=None):
"""Returns a transformation to go from input pts to output pts using a homography.
'indict' and 'outdict' should contain identical keys mapping to 2-tuples.
We create A:
x1 y1 1 0 0 0 -x1*x1' -y1*x1'
0 0 0 x1 y1 1 -x1*y1' -y1*y1'
... | 709fad7ffba7047e8d2c15e79611c3ac897733b7 | 13,991 |
def variables_to_restore(scope=None, strip_scope=False):
"""Returns a list of variables to restore for the specified list of methods.
It is supposed that variable name starts with the method's scope (a prefix
returned by _method_scope function).
Args:
methods_names: a list of names of configurable methods... | bc1f433b6a67898d8c010a56c6c51821f50df81a | 13,992 |
def from_strings(data, gaps="-", length=None, dtype=np.int8):
"""Convert a series of strings to an array of integer encoded alleles.
Parameters
----------
data : array_like, str
Sequence of strings of alleles.
gaps : str, optional
String of symbols to be interpreted as gaps in the s... | 7405e208613aa75b132f686fcf5fe7451a4160cc | 13,993 |
def get_relationship_targets(item_ids, relationships, id2rec):
"""Get item ID set of item IDs in a relationship target set"""
# Requirements to use this function:
# 1) item Terms must have been loaded with 'relationships'
# 2) item IDs in 'item_ids' arguement must be present in id2rec
# ... | 55542448af0eb2b46442bff0e0464361b669241a | 13,994 |
def cli(ctx, newick, analysis_id, name="", xref_db="null", xref_accession="", match_on_name=False, prefix=""):
"""Load a phylogenetic tree (Newick format) into Chado db
Output:
Number of inserted trees
"""
return ctx.gi.phylogeny.load_tree(newick, analysis_id, name=name, xref_db=xref_db, xref_accessio... | 9b68dec5584a692f2fe04746d9bb179c9e002682 | 13,995 |
def roll_neighbors(sites, site, dims=None, radius=1):
""" N-dimensional pixel neighborhood
for periodic images on regular grids """
index = np.unravel_index(site, dims=dims)
neighs = sites.take(nbr_range+index, axis=0, mode='wrap')
return neighs.flatten() | e653604c07f4824ef766c3a7f41a6c6c8a35bad0 | 13,996 |
import os
def extract_node_name(path, ignore_missing_nodes=False):
"""extracts the token after the 'nodes'"""
tokens = path.split(os.sep)
last_nodes_index = -1
for i, token in enumerate(tokens):
if token == "nodes":
last_nodes_index = i
if last_nodes_index == -1:
if ign... | 0d81e46ef2812e5b087fdef5264ad20a3f3bef2d | 13,997 |
import scipy
import os
import tqdm
def run_model(model, raw_cohort, delta_encoder):
"""
Run the given model using the given cohort and experimental settings contained in args.
This function:
(1) balanced the dataset
(2) splits the cohort intro training:development:testing sets at the patient-leve... | 94aec871db5b4e57014444d57fb1ef6844f516a1 | 13,998 |
import requests
import json
def folder0_content(folder0_id, host, token):
"""
Modules
-------
request, json
----------
Parameters
----------
folder0_id : Onedata folder level 0 id containing the data to publish.
host : OneData provider (e.g., ceta-ciemat-02.datahub.egi.eu).
tok... | 8ce6ae617666f936643b9599ae115e140b30bd2b | 13,999 |
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