content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
from operator import add
def set(isamAppliance, name, properties, attributes=None, description=None, type="JavaScript", new_name=None,
check_mode=False, force=False):
"""
Creating or Modifying a JavaScript PIP
"""
ret_obj = search(isamAppliance, name=name)
id = ret_obj['data']
if id =... | 6c7f097eb22a1f3033dce2cdf3264bff5f7c9acb | 29,708 |
import logging
def init_model(model, opt, argv):
"""select the network initialization method"""
if hasattr(opt, 'weight_init') and opt.weight_init == 'xavier':
network_weight_xavier_init(model)
elif hasattr(opt, 'weight_init') and opt.weight_init == 'MSRAPrelu':
network_weight_MSRAPrelu_in... | 5c53efd15af6403a6323d25dc877dc652e4a49b1 | 29,709 |
import math
def shoulders_up(x, y, max_angle=10):
"""
1:"Neck",
2:"RShoulder",
5:"LShoulder".
looks at line from left shoulder to neck, and
line from right shoulder to neck
if either are not straight returns 1
if both are flat (slope of 0 or close to 0) returns 1
"""
left_degre... | 2a6adce5dad431c91cac77bd79e4011964f76341 | 29,711 |
def str(x: i32) -> str:
"""
Return the string representation of an integer `x`.
"""
if x == 0:
return '0'
result: str
result = ''
if x < 0:
result += '-'
x = -x
rev_result: str
rev_result = ''
rev_result_len: i32
rev_result_len = 0
pos_to_str: list... | 6af580da343eb6adab58021eb489cf837b50571c | 29,712 |
def grad_spsp_mult_entries_x_reverse(b_out, entries_a, indices_a, entries_x, indices_x, N):
""" Now we wish to do the gradient with respect to the X matrix in AX=B
Instead of doing it all out again, we just use the previous grad function on the transpose equation X^T A^T = B^T
"""
# get the transp... | 64e5fbf5ca12fb9516c7aab2a357823c201d3d5a | 29,713 |
def execute_until_false(method, interval_s):
"""Executes a method forever until the method returns a false value.
Args:
method: The callable to execute.
interval_s: The number of seconds to start the execution after each method
finishes.
Returns:
An Interval object.
"""
interval = Interval... | eee730604ea98080e669d02f18a6ca55c4a4fe97 | 29,715 |
def vecnorm(a):
"""Return a/|a|"""
return a / mdamath.norm(a) | 425de4c8ddae138e1528ada448f86781b4c5130e | 29,716 |
def count_qubits(operator):
"""Compute the minimum number of qubits on which operator acts.
Args:
operator: FermionOperator, QubitOperator, DiagonalCoulombHamiltonian,
or PolynomialTensor.
Returns:
num_qubits (int): The minimum number of qubits on which operator acts.
Rais... | 9963c7b8202a825725ca3906b95f16d0243f81ed | 29,717 |
def datenum_to_date(date_num):
"""Transform date_num to datetime object.
Returns pd.NaT on invalid input"""
try:
total_seconds = round(dt.timedelta(days=date_num - 366).total_seconds())
return dt.datetime(1, 1, 1) + dt.timedelta(seconds=total_seconds) - dt.timedelta(days=1)
except Overf... | f2a523f0e1c1af15835ae042fdeac8ebcf0a5717 | 29,718 |
def save_ground_truth_part(name, tuple_path, mean, sem, std, sestd):
"""Saves a ground truth part to strings.
This is meant to be called with outputs of
`nest.flatten_with_tuple_paths(ground_truth_mean)`.
Args:
name: Python `str`. Name of the sample transformation.
tuple_path: Tuple path of the part o... | a4b769383dd0b250375205efeed363161b28ed0a | 29,719 |
def parse_cpe(cpe):
"""
Split the given CPE name into its components.
:param cpe: CPE name.
:type cpe: str
:returns: CPE components.
:rtype: list(str)
"""
ver = get_cpe_version(cpe)
if ver == "2.2":
parsed = [cpe22_unquote(x.strip()) for x in cpe[5:].split(":")]
if ... | 4dfbac57d3719a1c6ed00b5884be1321800827f5 | 29,720 |
def draw_points(xs, ys, covs, M):
"""
Resample a set of points M times, adding noise according to their covariance matrices.
Returns
-------
x_samples, y_samples : np.array
Every column j, is x[j] redrawn M times.
Has M rows, and every row is a realization of xs or ys.
"""
#... | 5609efcf6ba42fc2a059d308e8391b6057de3a16 | 29,721 |
def k_folds_split(raw_indexes, n_splits, labels=default_pars.validation_pars_labels,
shuffle=default_pars.validation_pars_shuffle, random_state=default_pars.random_state,
return_original_indexes=default_pars.validation_pars_return_original_indexes):
"""Splits a raw set of indexes... | 77394ca5d345d97423abaa0fe421e50cb0017762 | 29,722 |
def element_wise_entropy(px):
"""
Returns a numpy array with element wise entropy calculated as -p_i*log_2(p_i).
Params
------
px (np.array)
Array of individual probabilities, i.e. a probability vector or distribution.
Returns
-------
entropy (np.array)
Array of element... | 7637cac96e51ce6b89a395c306a6104e77bcef0d | 29,723 |
def score_page(preds, truth):
"""
Scores a single page.
Args:
preds: prediction string of labels and center points.
truth: ground truth string of labels and bounding boxes.
Returns:
True/false positive and false negative counts for the page
"""
tp = 0
fp = 0
fn = ... | 25b3d4280db734ded586eb627fe98d417164601d | 29,724 |
import re
def _validate_eida_token(token):
"""
Just a basic check if the string contains something that looks like a PGP
message
"""
if re.search(pattern='BEGIN PGP MESSAGE', string=token,
flags=re.IGNORECASE):
return True
return False | 746fbd011b38abab43be983a1a054505526dcf78 | 29,725 |
def dn_histogram_mode_5(y, y_min, y_max):
"""
Mode of z-scored distribution (5-bin histogram)
"""
return histogram_mode(y, y_min, y_max, 5) | 0dc10f46136e60e2523f4ca79449f18aaedd4854 | 29,726 |
def _make_element(spec, parent, attributes=None):
"""Helper function to generate the right kind of Element given a spec."""
if (spec.name == constants.WORLDBODY
or (spec.name == constants.SITE
and (parent.tag == constants.BODY
or parent.tag == constants.WORLDBODY))):
return _Attac... | 7635e8380e8238541544495f250e78a5da3ad441 | 29,727 |
def nlf_css(parser, token):
"""Newsletter friendly CSS"""
args = token.split_contents()
css = {}
css_order = []
for item in args[1:]:
tag, value = item.split("=")
tag, value = tag.strip('"'), value.strip('"')
css[tag] = value
css_order.append(tag)
nodelist = parse... | eadf74cdd6e58fb4e1551f1b951ad74226e175c2 | 29,730 |
def data_context_connectivity_context_connectivity_serviceuuid_requested_capacity_bandwidth_profile_peak_information_rate_put(uuid, tapi_common_capacity_value=None): # noqa: E501
"""data_context_connectivity_context_connectivity_serviceuuid_requested_capacity_bandwidth_profile_peak_information_rate_put
create... | c9ee5c8751e8424732f066598525a44d1c66d1c5 | 29,731 |
import logging
def _get_default_dataset_statistics(
statistics: statistics_pb2.DatasetFeatureStatisticsList
) -> statistics_pb2.DatasetFeatureStatistics:
"""Gets the DatasetFeatureStatistics to use for validation.
If there is a single DatasetFeatureStatistics, this function returns that. If
there are multi... | 8466e67c9ea5d795ea9b6c16c637b9a55048056c | 29,732 |
from typing import Callable
from re import A
def foldr(_folder: Callable[[A, B], B], _init: B, _linked_list: LinkedList[A]) -> B:
""" foldr """
if _linked_list.content is None:
return _init
else:
head = _linked_list.content[0]
tail = _linked_list.content[1]
return _folder(h... | 93aa3749442d8028dd115619e358e8fcf40ada46 | 29,733 |
def get_per_lane_sample_dist_plot(sample_data: pd.DataFrame) -> dict:
"""
A function for returing sample distribution plots
:params sample_data: A Pandas DataFrame containing sample data
:returns: A dictionary containing sample distribution plots
"""
try:
lane_plots = dict()
for... | 143094fc909ac9044c5986c958cff79e9e218414 | 29,734 |
def mark_volatile(obj):
"""DEPRECATED(Jiayuan Mao): mark_volatile has been deprecated and will be removed by 10/23/2018; please use torch.no_grad instead."""
return stmap(_mark_volatile, obj) | 2e299889fe7982069fb5987f6af0e56ae365a9ee | 29,735 |
def list_keys(bucket):
"""
Lists all the keys in a bucket.
:param bucket: (string) A bucket name.
:return: (string list) Keys in the bucket.
"""
_check_bucket(bucket)
bucket_path = _bucket_path(bucket)
keys = []
for key_path in bucket_path.iterdir():
keys.append(key_path.name... | 0a84c72165cf76970221974196911853d0db027a | 29,736 |
def h6(content, accesskey:str ="", class_: str ="", contenteditable: str ="",
data_key: str="", data_value: str="", dir_: str="", draggable: str="",
hidden: str="", id_: str="", lang: str="", spellcheck: str="",
style: str="", tabindex: str="", title: str="", translate... | c68a5ba229643571ce49e535b32e99580443e56c | 29,737 |
def extractUniversesWithMeaning(item):
"""
"""
vol, chp, frag, postfix = extractVolChapterFragmentPostfix(item['title'])
if not (chp or vol) or 'preview' in item['title'].lower():
return None
if 'Angel of Death' in item['title']:
return buildReleaseMessageWithType(item, 'Angel of Death', vol, chp, frag=frag, ... | 0a00cc344bdb1d5a2498252f529536b2c58f2825 | 29,738 |
def get_provenance(message):
"""Given a message with results, find the source of the edges"""
prov = defaultdict(lambda: defaultdict(int)) # {qedge->{source->count}}
results = message['message']['results']
kg = message['message']['knowledge_graph']['edges']
edge_bindings = [ r['edge_bindings'] for r... | 1f6dfe9e48da49b72cb55f3f949146db3db164f2 | 29,739 |
def bricklinkColorToLEGO(colornum):
"""
Get the LEGO equivalent to a bricklink color number if it exists
:param colornum:
:return:
"""
default = {"name": "Unknown", "Lego": colornum, "BrickLink": colornum}
if colornum < 0:
return default
for color in color_data:
if colo... | 9ed77c271168025c5864a28624470c26ae3a0a9e | 29,740 |
def bounds(gdf):
"""Calculates the bounding coordinates (left, bottom, right, top) in the given GeoDataFrame.
Args:
gdf: A GeoDataFrame containing the input points.
Returns:
An array [minx, miny, maxx, maxy] denoting the spatial extent.
"""
bounds = gdf.to... | 48242e870edd1db9b1191518c4b9ba7433420610 | 29,741 |
def powerport_get_row_boot_strap (port_id, raw = False):
""" Get boot strapping setting
"""
result = powerport_get_port_status (port_id + 24, "pdu", raw)
state = result.pop ("Port State", None)
if (state):
result["Boot Strap"] = "Normal" if (state == "Off") else "Network"
... | 00d41e0a505c6d88ce44c4a701865556ccff0f89 | 29,743 |
def inv_ltri(ltri, det):
"""Lower triangular inverse"""
inv_ltri = np.array((ltri[2], -ltri[1], ltri[0]), dtype=ltri.dtype) / det
return inv_ltri | 539bbcec02286f991d5cc426ebe631d1cbe0b890 | 29,744 |
def create_dummy_review(user, title='Review 1'):
"""Simple function for creating reviews of a user"""
review = Review.objects.create(
reviewer=user,
title=title,
rating=5,
summary='This is my first review!!!',
ip='190.190.190.1',
... | ffa9ad526072fa48eff513f9b6d10628e700a266 | 29,745 |
def check_user(update):
"""verify that a user has signed up"""
user = update.message.from_user
if db.tel_get_user(user.id) is not None:
return True
else:
return False | 6654ba29d15158b63f78cea16d796f26f9199b07 | 29,747 |
def acmg():
"""Calculate an ACMG classification from submitted criteria."""
criteria = request.args.getlist("criterion")
classification = get_acmg(criteria)
return jsonify(dict(classification=classification)) | 83e70afcd986ca8b7fe0e442130615cff2e84a1b | 29,748 |
def import_bin(filename, **kwargs):
"""
Read a .bin file generated by the IRIS Instruments Syscal Pro System and
return a curated dataframe for further processing. This dataframe contains
only information currently deemed important. Use the function
reda.importers.iris_syscal_pro_binary._import_bin... | 2ec4d3febad7eae08db4b2df5b4552459b627dd9 | 29,749 |
def get_messages(receive_address, send_address, offset, count):
""" return most recent messages from offset to count from both communicators """
conn = connect_db()
cur = conn.cursor()
cur.execute(
"(SELECT * FROM message WHERE (recvAddress=%s AND sendAddress=%s) ORDER by id DESC LIMIT %s OFFSET... | 13e46a46a4bc15931de77374249ae701f5b65c1a | 29,750 |
def get_test_node(context, **kw):
"""Return a Node object with appropriate attributes.
NOTE: The object leaves the attributes marked as changed, such
that a create() could be used to commit it to the DB.
"""
db_node = db_utils.get_test_node(**kw)
# Let DB generate ID if it isn't specified expli... | 6ce089c0d6643f2c58633ce846a4a46d2c9e5732 | 29,751 |
from typing import OrderedDict
def GlobalAttributes(ds, var):
"""
Creates the global attributes for the netcdf file that is being written
these attributes come from :
https://www.unidata.ucar.edu/software/thredds/current/netcdf-java/metadata/DataDiscoveryAttConvention.html
args:
runinfo Table containing all t... | b5fcf1627f8c23964a1ec2fe4fa657a60cb8efa3 | 29,752 |
from typing import List
from typing import Tuple
def extend_path(path: List[Tuple[MerkleTree, hash.HashTriple]],
tree: MerkleTree,
) -> List[List[Tuple[MerkleTree, hash.HashTriple]]]:
"""Extend path if possible."""
paths = []
for t in (tree.left, tree.right):
if t i... | 294ea5b1e2b844065a2fd962768f1b6501b4513f | 29,753 |
def load_dictionary(loc):
"""
Load a dictionary
"""
with open(loc, 'r') as f:
worddict = pkl.load(f)
return worddict | f659ebb94410e02bbeab51b04b60e727cc749641 | 29,756 |
import json
def get_specific_post(post_id):
"""Get specific post"""
value = posts.get(post_id)
if not value:
return json.dumps({"error": "Post Not Found"}), 404
return json.dumps(value), 200 | 86ca2ee5847c3e7043dbd52f1a713477ea6191c5 | 29,757 |
def first_half(dayinput):
"""
first half solver:
"""
houses = { (0,0): 1 }
coords = [0, 0]
for h in dayinput:
coords = change_coords(h, coords)
home = (coords[0], coords[1])
if houses.get(home, None):
houses[home] += 1
else:
houses[home] = ... | c0ed5c66c3f259257e14c2c6bc4daec406028135 | 29,758 |
def compute_cluster_metrics(neighbor_mat, max_k=10, included_fovs=None,
fov_col='SampleID'):
"""Produce k-means clustering metrics to help identify optimal number of clusters
Args:
neighbor_mat (pandas.DataFrame):
a neighborhood matrix, created from create_neighb... | bc13b2eb1b4bd9824e4134395ed5d31a9cfa7cb0 | 29,759 |
def map_flat_line(x, y, data, linestyles='--', colors='k', ax=None, **kwargs):
"""Plot a flat line across every axis in a FacetGrid.
For use with seaborn's map_dataframe, this will plot a horizontal or
vertical line across all axes in a FacetGrid.
Parameters
----------
x, y : str, float, or li... | dd46189458ee0da79785d2c9119a41969dc1357e | 29,760 |
def build_dictionary(sentences, size):
"""
Create dictionary containing most frequent words in the sentences
:param sentences: sequence of sentence that contains words
Caution: the sequence might be exhausted after calling this function!
:param size: size of dictionary you want
:return: dict... | 24a998d9df539b44c2dad1ffabb2737a189e7a3e | 29,762 |
import re
def simplestr(text):
"""convert a string into a scrubbed lower snakecase. Intended use is converting
human typed field names deterministically into a string that can be used for a
key lookup.
:param text: type str text to be converted
"""
text = text.strip()
text = text.replace(... | b030c50cd300dd97d69a9d2b8421892bb1f0c23a | 29,763 |
def lti_launch(request):
"""
This method is here to build the LTI_LAUNCH dictionary containing all
the LTI parameters and place it into the session. This is nessesary as we
need to access these parameters throughout the application and they are only
available the first time the application loads.
... | a65d4395095e36f4e27ae802ae7c2635f211521e | 29,764 |
def cartesian_to_altaz(x):
""" Converts local Cartesian coordinates to Alt-az,
inverting altaz_to_cartesian
"""
x, y, z = x
return np.arcsin(z), np.arctan2(-y, x) | e585fb57a9509fab277e15f08e76e1367c8334d4 | 29,766 |
def discount_opex(opex, global_parameters, country_parameters):
"""
Discount opex based on return period.
Parameters
----------
cost : float
Financial cost.
global_parameters : dict
All global model parameters.
country_parameters : dict
All country specific parameter... | 6e079ffc9accc7679bada3b31d07748c93d4b18c | 29,768 |
import torch
def permute(x, perm):
"""Permutes the last three dimensions of the input Tensor or Array.
Args:
x (Tensor or Array): Input to be permuted.
perm (tuple or list): Permutation.
Note:
If the input has fewer than three dimensions a copy is returned.
"""
if is_tens... | 513164bfc6d25a82f2bfeba05427bd69c8df181c | 29,770 |
def is_hr_between(time: int, time_range: tuple) -> bool:
"""
Calculate if hour is within a range of hours
Example: is_hr_between(4, (24, 5)) will match hours from 24:00:00 to 04:59:59
"""
if time_range[1] < time_range[0]:
return time >= time_range[0] or time <= time_range[1]
return time_... | 70d874f0a5dee344d7638559101fc6be2bcca875 | 29,771 |
def calc_Topt(sur,obs,Tvals,objfunc='nse'):
"""
Function to calibrate the T parameter using a brute-force method
Args: sur (pandas.Series): pandas series of the surface soil moisture
obs (pandas.Series): pandas series of the soil moisture at layer x to calibrate
Tvals (list,tuple,set... | 39df23619ea364cbf477f02665a86e72cef86e11 | 29,772 |
def share_file(service, file_id):
"""Make files public
For a given file-id, sets role 'reader' to 'anyone'. Returns public
link to file.
:param: file_id (string)
:return: (string) url to shared file
"""
permission = {
'type': "anyone",
'role': "reader",
... | 70a1132667663fa85cf7f00fd3ced2fb81b03cc4 | 29,773 |
import data
def convert_image_for_visualization(image_data, mean_subtracted=True):
"""
Convert image data from tensorflow to displayable format
"""
image = image_data
if mean_subtracted:
image = image + np.asarray(data.IMAGE_BGR_MEAN, np.float32)
if FLAGS.image_channel_order == 'BGR':
image = ima... | 9fe138051f7886d3c3e8e70e75f23b636a1ccd02 | 29,775 |
def mld(returns_array, scale=252):
"""
Maximum Loss Duration
Maximum number of time steps when the returns were below 0
:param returns_array: array of investment returns
:param scale: number of days required for normalization. By default in a year there are 252 trading days.
:return: MLD
"""... | 2d78d76c1456ebb4df606a9450f45e47b5e49808 | 29,776 |
from typing import Union
from typing import List
from typing import Dict
from typing import Any
def json2geodf(
content: Union[List[Dict[str, Any]], Dict[str, Any]],
in_crs: str = DEF_CRS,
crs: str = DEF_CRS,
) -> gpd.GeoDataFrame:
"""Create GeoDataFrame from (Geo)JSON.
Parameters
----------
... | de9e956a79821611d6f209e9b206d3c15e24708e | 29,777 |
from typing import Optional
from typing import List
from typing import Tuple
from typing import Any
import logging
def build_block_specs(
block_specs: Optional[List[Tuple[Any, ...]]] = None) -> List[BlockSpec]:
"""Builds the list of BlockSpec objects for SpineNet."""
if not block_specs:
block_specs = SPIN... | 6046b2ee33d15254ff6db989b63be4276d0bad19 | 29,778 |
def est_agb(dbh_mat, sp_list):
"""
Estimate above ground biomass using the allometric equation in Ishihara et al. 2015.
"""
# wood density
wd_list = [
dict_sp[sp]["wood_density"]
if sp in dict_sp and dict_sp[sp]["wood_density"]
else None
for sp in sp_list
]
#... | ab0d80408bc9d216e387565cde3d6e758f738252 | 29,779 |
from typing import Optional
def parse_json_and_match_key(line: str) -> Optional[LogType]:
"""Parse a line as JSON string and check if it a valid log."""
log = parse_json(line)
if log:
key = "logbook_type"
if key not in log or log[key] != "config":
log = None
return log | c4efa103730ac63d2ee6c28bba2de99a450f6b8d | 29,780 |
def nearDistance(img, centers):
"""
Get the blob nearest to the image center, which is probably the blob for cells, using euclidian distance.
Parameters: img, image with labels defined;
centers, list of label' centers of mass.
Returns: nearestLabel, label nearest to the image center.
... | 6414d30cb1d591b5bf6f8101c084823f92605f1e | 29,781 |
from flask_swagger import swagger
import json
def create_app(config_object=ProdConfig):
"""This function is an application factory.
As explained here: http://flask.pocoo.org/docs/patterns/appfactories/.
:param config_object: The configuration object to use.
"""
app = Flask(__name__.split('.')[0]... | b9214ee822c8012a5273cf72daa04f33b9b99539 | 29,782 |
def get_f1_dist1(y_true, y_pred, smooth=default_smooth):
"""Helper to turn the F1 score into a loss"""
return 1 - get_f1_score1(y_true, y_pred, smooth) | c200bbe75f7013a75b2801fbb7de4cbf588bb873 | 29,783 |
def get_date_info_for_pids_tables(project_id, client):
"""
Loop through tables within all datasets and determine if the table has an end_date date or a date field. Filtering
out the person table and keeping only tables with PID and an upload or start/end date associated.
:param project_id: bq name of p... | e75dd8176583673e8ee6e89a8c75312fe06216bc | 29,784 |
def preprocess_sent(sentence):
"""input: a string containing multiple sentences;
output: a list of tokenized sentences"""
sentence = fill_whitespace_in_quote(sentence)
output = tokenizer0(sentence)
# tokens = [token.text for token in tokenizer.tokenize(sentence)]
tokens = list(map(lambda x: x.te... | eddaa08e3b0a8ad43f410541793f873449101904 | 29,785 |
def average_slope_intercept(image, lines):
"""
This function combines line segments into one or two lane lines
"""
left_fit = [] # contains the coordinate of on the line in the left
right_fit = []
if lines is None:
return None
# now loop through very line we did previously
f... | b6dbd56555d5c9d71905b808db20e4f8be6de15f | 29,787 |
def build_upper_limb_roll_jnts(main_net, roll_jnt_count=3):
"""Add roll jnts, count must be at least 1"""
increment = 1.0/float(roll_jnt_count)
def create_joints(jnt_a, jnt_b, net, lower_limb=False, up_axis='-Z'):
"""
:param jnt_a: Start Joint
:param jnt_b: End Joint
:param... | 0985a33a9fac3b218042cac4d1213df13f606464 | 29,788 |
def create_one(**kwargs):
""" Create a Prediction object with the given fields.
Args:
Named arguments.
date: Date object. Date of the predicted changes.
profitable_change: Decimal. Predicted profitable change in pips.
instrument: Instrument object... | d71d14445c5e53c032b529652f3ed5fb12df6544 | 29,790 |
import math
def get_distance_wgs84(lon1, lat1, lon2, lat2):
"""
根据https://github.com/googollee/eviltransform，里面的算法：WGS - 84
:param lon1: 经度1
:param lat1: 纬度1
:param lon2: 经度2
:param lat2: 纬度2
:return: 距离，单位为 米
"""
earthR = 6378137.0
pi180 = math.pi / 180
arcLatA = lat1 * p... | 8da67a3a690ff0cb548dc31fb65f3b2133fa3e3f | 29,792 |
def make_uuid(ftype, size=6):
"""
Unique id for a type.
"""
uuid = str(uuid4())[:size]
return f'{ftype}-{uuid}' | 3cb779431e5cb452f63f8bab639e9a437d7aa0f9 | 29,793 |
def region_of_interest(img, vertices):
"""
Applies an image mask.
Only keeps the region of the image defined by the polygon
formed from `vertices`. The rest of the image is set to black.
`vertices` should be a numpy array of integer points.
Args:
img (image): Mas... | bd22cd8b6642dd820e786f88d54c63f4811c5221 | 29,794 |
import pytz
def _adjust_utc_datetime_to_phone_datetime(value, phone_tz):
"""
adjust a UTC datetime so that it's comparable with a phone datetime
(like timeEnd, modified_on, etc.)
returns a timezone-aware date
"""
phone_tz = _soft_assert_tz_not_string(phone_tz)
assert value.tzinfo is None... | 48a875af1082d1538c6bf09905afacc411e1408c | 29,795 |
def cache_function(length=CACHE_TIMEOUT):
"""
A variant of the snippet posted by Jeff Wheeler at
http://www.djangosnippets.org/snippets/109/
Caches a function, using the function and its arguments as the key, and the return
value as the value saved. It passes all arguments on to the function, as
... | 81c2574621e81c485712e456f9b34c638f47cdf8 | 29,796 |
def plot_contour_1d(X_grid, Y_grid, data,
xlabel, ylabel, xticks, yticks,
metric_bars, fillblack=True):
"""Create contour plots and return the figure and the axes."""
n = len(metric_bars)
assert data.shape == (*X_grid.shape, n), (
"data shape must be (X, Y, ... | 2eb534ebe841a96386976fa477ec357b5ea07ea7 | 29,798 |
def dataset_to_rasa(dataset: JsonDict) -> JsonDict:
"""Convert dataset to RASA format, ignoring entities
See: "https://rasa.com/docs/nlu/dataformat/"
"""
return {
"rasa_nlu_data": {
"common_examples": [
{"text": text, "intent": intent, "entities": []}
... | 64a9b6291b0a2d2af297e3fb0ca214b8d65792f4 | 29,799 |
import math
import tqdm
def SurfacePlot(Fields,save_plot,as_video=False, Freq=None, W=None, L=None, h=None, Er=None):
"""Plots 3D surface plot over given theta/phi range in Fields by calculating cartesian coordinate equivalent of spherical form."""
print("Processing SurfacePlot...")
fig = plt.figure()
... | 23b0c3f8f569d480f3818ed970ea41adce51dacc | 29,800 |
def resource_method_wrapper(method):
"""
Wrap a 0-ary resource method as a generic renderer backend.
>>> @resource_method_wrapper
... def func(resource):
... print repr(resource)
>>> action = "abc"
>>> resource = "def"
>>> func(action, resource)
'd... | e07bd139586a7b80d48c246ea831b39c3183224e | 29,801 |
def rotation_matrix(axis_vector, angle, degrees = True):
"""
Return the rotation matrix corresponding to a rotation axis and angle
For more information, see:
https://en.wikipedia.org/wiki/Rotation_matrix#Rotation_matrix_from_axis_and_angle
Parameters
----------
axis_vector : 3 x 1 numpy ar... | c48711d2b4d2bb8ca5ac01ee2c51778f4a9525fd | 29,802 |
def select_int(sql, *args):
"""
执行一个sql, 返回一个数值
:param sql:
:param args:
:return:
"""
d = _select(sql, True, *args)
if d == None:
raise StandardError('Result is None')
if len(d) != 1:
raise MultiColumnsError('Expect only one column.')
return d.values()[0] | 72826727a45cfa902e710371c8bf4bc9fcd07528 | 29,803 |
import logging
import torch
def compute_nas_score(any_plain_net, random_structure_str, gpu, args):
""" compute net score
:param any_plain_net: model class
:param random_structure_str (str): model string
:param gpu (int): gpu index
:param args (list): sys.argv
:return score... | 6188c88151ca501c22a85cccd65bbc01d99c721f | 29,805 |
def _dict_values_match(*args, **kwargs):
"""
Matcher that matches a dict where each of they keys match the matcher
passed in. Similar to ``MatchesStructure``, but for dictionaries rather
than python objects.
"""
matchers = dict(*args, **kwargs)
def extract_val(key):
def extract_val... | b463eb1f24117fb1c37793656632931af05f3a7c | 29,806 |
def fib_lista(n):
"""
Função que retorna uma lista contendo os números da sequência de Fibonacci
até o número n.
"""
lista = []
i, j = 0, 1
while i < n:
lista.append(i)
i, j = j, i + j
return lista | ec307ce80ae70e5fba81d2e26b140f1b86c95619 | 29,807 |
def make_item_accessor(idx):
"""
Returns a property that mirrors access to the idx-th value of an object.
"""
@property
def attr(self):
return self[idx]
@attr.setter
def attr(self, value):
self[idx] = value
return attr | 7cd1248b3f9402fc9be10d277dee849dc47840c0 | 29,810 |
def calc_correlation(data, data2):
"""
Calculate the correlations between 2 DataFrames().
Parameters:
- data: The first dataframe.
- data2: The second dataframe.
Returns:
A Series() object.
"""
return (
data.corrwith(data2).
loc[lambda x: x.notnull()]
... | 7f47592a4525efa9db2fba317d095448d5288399 | 29,811 |
def boschloo_swap(c1r1: int, c2r1: int, c1r2: int, c2r2: int) -> (int, int, int, int):
"""
Four contingency tables always give the same pvalue: ['abcd', 'badc', 'cdab', 'dcba']
Compute and save only one version.
"""
if c1r1 + c1r2 > c2r1 + c2r2: # left > right
c1r1, c1r2, c2r1, c2r2 = c2r1... | 4da7cccd892dcf03412509c4df79132f8ebd5ad1 | 29,812 |
def get_unit_scale(scale60, val30=1):
"""
Returns a function to be used in the UNIT_SCALE of a descriptor that
will change the scale depending on if the 60fps flag is set or not.
"""
assert 0 not in (val30, scale60), ("60fps scale and default 30fps " +
"value m... | 36463d8e7d0cf46bce527cf9cefccdcf730b4414 | 29,813 |
def sample_ingredient(user,name = 'cinnoan'):
"""create and return a sample ingredient"""
return Ingredient.objects.create(user=user,name=name) | 3ccf096e68ed25dc4c35cf2abf68e9139c34b82c | 29,814 |
import six
def before(action):
"""Decorator to execute the given action function *before* the responder.
Args:
action: A function with a similar signature to a resource responder
method, taking (req, resp, params), where params includes values for
URI template field names, if any. Hoo... | d385f6b9ab45546cd2c07612528ad487ae5363d9 | 29,815 |
def commandLine(Argv):
"""
Method converting a list of arguments/parameter in a command line format (to include in the execution of a program for exemple).
list --> str
"""
assert type(Argv) is list, "The argument of this method are the arguments to convert in the command line format. (type Lis... | 4b27e73fd43ec914f75c22f2482271aafd0848ac | 29,816 |
def prob(n: int, p: float) -> float:
"""
Parameters:
- n (int): số lần thực hiện phép thử
- p (float): xác suất phép thử thành công
Returns:
- float: xác suất hình học
"""
pr = p * (1 - p) ** (n - 1)
return pr | fca3fab45ec852c8910619889ac19b0753f5b498 | 29,818 |
from typing import Mapping
import pandas
import numpy
def to_overall_gpu_process_df(gpu_stats: Mapping) -> DataFrame:
""" """
resulta = []
columns = []
for k2, v2 in gpu_stats.items():
device_info = v2["devices"]
for device_i in device_info:
processes = device_i["processes"... | 7fd260b1a0d232f42958d3c073300ad6e7098c2c | 29,819 |
from teospy import liq5_f03
def genliq5():
"""Generate liq5_f03 Testers.
"""
funs = liq5_f03.liq_g
args1 = (300.,1e5)
fargs = [(der+args1) for der in _DERS2]
refs = [-5265.05056073,-393.062597709,0.100345554745e-2,-13.9354762020,
0.275754520492e-6,-0.452067557155e-12]
fnames = 'liq... | 4051aaa831bcfb74a5e871e1619b982ad06cc859 | 29,820 |
def tridiagonalize_by_lanczos(P, m, k):
"""
Tridiagonalize matrix by lanczos method
Parameters
----------
P : numpy array
Target matrix
q : numpy array
Initial vector
k : int
Size of the tridiagonal matrix
Returns
-------
T : numpy array
tridiagon... | 0becf3801e7e486fd0a59fac95223e4d9ca68957 | 29,822 |
def Polygon(xpoints, ypoints, name="", visible=True, strfmt="{:.5f}"):
"""
Polygon defined by point verticies.
Returns
---------
:class:`lxml.etree.Element`
"""
polygon = Element("Polygon", name=str(name), visible=str(visible).lower())
polygon.extend(
[
Element("Poin... | f2cd966a0dd536b8134ccaab4a85607e8511c60c | 29,823 |
def fake_index_by_name(name, pattern, timezone='+08:00'):
"""
generate a fake index name for index template matching
ATTENTION:
- rollover postfix is not supported in index template pattern
- timezone is not supported cause tz is not well supported in python 2.x
"""
if patter... | b8754ce0086409c75edba8d6bc14b7ca313d56ae | 29,824 |
def map_code(func):
"""
Map v to an Ontology code
"""
def mapper(v):
if v is None:
return v
else:
return func(str(v))
return mapper | 76eb3c6756c983fd73c180b57c1c998a348d32eb | 29,825 |
def install_dvwa(instance, verbose: bool=True):
""" Install and configure DVWA web server
instance (object): This argmument define the lxc instance.
verbose (bool, optional): This argument define if the function prompt some informations during his execution. Default to True.
"""
if update(instance,... | 299bddddc06364abfe34c482fa12932f893a224c | 29,826 |
def get(role_arn, principal_arn, assertion, duration):
"""Use the assertion to get an AWS STS token using Assume Role with SAML"""
# We must use a session with a govcloud region for govcloud accounts
if role_arn.split(':')[1] == 'aws-us-gov':
session = boto3.session.Session(region_name='us-gov-west-... | f1012c71eff41bffdad6390b9353745b0e07ab0c | 29,828 |
def find_nth(s, x, n):
"""
find the nth occurence in a string
takes string where to search, substring, nth-occurence
"""
i = -1
for _ in range(n):
i = s.find(x, i + len(x))
if i == -1:
break
return i | b54998db817272ec534e022a9f04ec8d350b08fb | 29,830 |
from typing import Union
from typing import Dict
from typing import Any
def parse_buffer(value: Union[Dict[str, Any], str]) -> str:
"""Parse value from a buffer data type."""
if isinstance(value, dict):
return parse_buffer_from_dict(value)
if is_json_string(value):
return parse_buffer_fro... | e98cad3020fffdaef5ad71d1f59b89db83e05d03 | 29,831 |
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