content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def compute_lab_volume(image):
"""
Compute the perceivable color volume in LAB space as a measure for the used colors (or color flatness)
Parameters
----------
image: the image to compute the LAB space volume for
Returns
-------
LABvolume = std(L)*std(a)*std(b)
"""
lab = rgb2la... | 303d378a7ecbbe75bb6b285462d3a39484d46517 | 3,598,832 |
import yaml
def get_project_id(dataset: str) -> str:
"""Returns the GCP project ID associated with the given dataset."""
with open(f'../stack/Pulumi.{dataset}.yaml', encoding='utf-8') as f:
return yaml.safe_load(f)['config']['gcp:project'] | d951e8d2a6c96df9aa2dc15499c36f93123f8038 | 3,598,833 |
def dense_nn(x):
"""
Network used to classify MNIST digits.
:param x: tensor with shape [batch_size, 784], input to the dense fully connected layer.
:return: [batch_size, 10], logits of dense fully connected.
"""
dense_1 = tf.nn.dropout(tf.nn.relu(dense(x, input_dim, n_l1, 'dense_1')), keep_prob... | 696eabfd1b93a269c8b63465653ab3fc18bc3b02 | 3,598,834 |
def score_state(num_answer, ans_one):
"""Takes in the player's answer, and ans_one
(explained in question);
checks if the player's choice is correct
"""
#assert num_answer in [1, 2]
if num_answer == 1:
if ans_one == True:
correct = True
else:
correct = Fa... | 123a0c5f40930fe5a6dc65220c39097a55120c19 | 3,598,838 |
from typing import List
from typing import Callable
def make_transformer(
nlp: Language,
name: str,
model: Model[List[Doc], FullTransformerBatch],
set_extra_annotations: Callable[[List[Doc], FullTransformerBatch], None],
max_batch_items: int,
):
"""Construct a Transformer component, which lets... | 978e31bb0cf672b4012e5dba03b67a03190747e2 | 3,598,839 |
def generate_AA_random_walks(APP_start, apk2idx, idx2apk, apk2node, node2apk, A, BP, p, q, length):
"""
Given a starting node, generate AA random walks that have max length of 'length'
"""
APP1 = apk2node[APP_start]
APP_idx = apk2idx[APP_start]
ser = pd.Series(A[APP_idx].toarray()[0])
API1 =... | a1e100e5f167fac3e1b9decfb130fe94e557b1cc | 3,598,840 |
def req_add_from_template(req_id):
"""
Add a Request from a Template
"""
fieldnames = ["type",
"priority",
"site_id",
"purpose",
"requester_id",
"comments",
]
db = current.db
s3db = c... | 3786f41d789c72cf61cf4a971850ea225ab08dc2 | 3,598,841 |
def law_of_orbits_perihelion(a: radius, e: eccentricity) -> radius:
"""Calculate aphelion from Kepler's Law or Orbits.
Where:
R = Displacement from major body to perihelion
a = Semimajor axis
e = eccentricity
"""
logger.trace(f"BASE FUNCTION: \"law_of_orbits_perihelion\" invoked.")
R: r... | 5c1278e6fc19214f844997439dbf0a56a62e056e | 3,598,842 |
def is_anagram_v3(s, t):
"""
NOTE: THIS SOLUTION DOES NOT WORK FOR ALL CASES
e.g: s = 'ac', t = 'bb', or aa vs bb
"""
val = 0
for i in range(len(s)):
val ^= ord(s[i])
print(f"val: {val}")
val ^= ord(s[i])
print(f"val: {val}")
return val == 0 | 121c4fd1841d6372fd5a03af3ae6f74e3dfb7b25 | 3,598,843 |
def register():
"""
{"username" : "user1", "password": "123qwe", "type"=0}
"""
data = request.json
username = data["username"]
password = data["password"]
type = int(data["type"])
user = User(username=username, password=password,type=type)
db.session.add(user)
try:
db.ses... | 3a50ecdae06a7ff02c706a33737b44ffd55a1a32 | 3,598,844 |
import hmac
def verify_hmac_sha1(request):
"""Verify a HMAC-SHA1 signature."""
base_string = generate_signature_base_string(request)
sig = hmac_sha1_signature(
base_string, request.client_secret, request.token_secret)
return hmac.compare_digest(sig, request.signature) | 31b8c5843b4587d078d512e4f821e093e1b80543 | 3,598,846 |
from typing import Any
import sympy
import numpy
def vyxalify(value: Any) -> Any:
"""Takes a value and returns it as one of the four types we use here."""
if isinstance(value, sympy.core.numbers.Integer):
return int(value)
elif is_sympy(value):
return sympy.nsimplify(value.as_real_imag()[... | 86db306af2eeec8b49cff82af878240f156a0bb2 | 3,598,847 |
def low_frequency_turn_over_power_law(v, vc, a, c, beta, v0):
"""power law with low-frequency turn-over:
.. math::
S_v = c \\left( \\frac{v}{v0} \\right)^{a} \\exp\\left [ \\frac{a}{\\beta} \\left( \\frac{v}{vc} \\right)^{-\\beta} \\right ]
Parameters
----------
v : `list`
Frequenc... | d97e218f5ddfebac21dfe6eba73686aadda6457a | 3,598,848 |
import six
def OverrideProjectIdToProjectNumber(request):
"""Returns an updated `request` with the Cloud project number."""
resource, resource_name = GetResourceInfo(request)
project_id = DeriveProjectFromResource(resource)
project_number = ProjectIdToProjectNumber(project_id)
setattr(request, resource_name... | 595407ca014ad2152729bfb07aa27cc2f249dcaf | 3,598,849 |
def arg_name2cli_name(arg_name: str) -> str:
"""
Convert a snake_case argument into a --kabob-case argument.
"""
return "--" + arg_name.lower().replace("_", "-") | 541601ae07b09acdd2d33487517159cd3cbd6125 | 3,598,850 |
from typing import Tuple
from typing import Any
def _basic_computation_tracincp_fast(
influence_instance: TracInCPFast,
inputs: Tuple[Any, ...],
targets: Tensor,
):
"""
For instances of TracInCPFast and children classes, computation of influence scores
or self influence scores repeatedly calls... | 4bf9df9d035b9d901a17a505399d3101c29d50ac | 3,598,852 |
def get_split_counts(df: pd.DataFrame):
"""Returns number of rows for each data split type given dataframe."""
assert constants.SPLIT_KEY in df.columns
return df[constants.SPLIT_KEY].value_counts().to_dict() | 470ca5cd0cbe247e0abc32ad4a002b9538520eae | 3,598,853 |
import requests
from datetime import datetime
def erc20_address_call(address):
"""API call to etherscan for an ethereum wallet
and returns the total positive count of remaining erc-20 coins
in the wallet"""
address = str(address)
url = "http://api.etherscan.io/api?module=account&action=t... | 0bebb4c96cd49b54c70b3f54605f230a97254647 | 3,598,854 |
def get_num_lines(input_src):
"""Count number of lines in file.
Args:
input_src: input file
Returns: number of lines
"""
# get number of lines
num_lines = 0
with open(input_src, "r", encoding="utf-8") as in_file:
try:
for line in in_file:
num_lin... | 4c1e9fdc1e67bb6e26a6c342d6c1a8ff077a26c4 | 3,598,855 |
def _label_check(label_string: str, search_label: str):
""" Mask labels with Booleans that appear in row """
for label in label_string.split(' '):
if search_label == label:
return True
return False | 084d23321133dfcd9d8f819e8209165d1cac2c15 | 3,598,857 |
def lp(m, n):
""" Create a linear program with random equality constraints and
non-negative inequality constraints """
_x = np.maximum(0.0, np.random.randn(n))
# inequality constriants
A1 = -np.eye(n)
b1 = np.zeros(n)
# equality constraints
A2 = np.random.randn(m, n)
b2 = A2.dot(... | 892cd6abccfe70b58d274bd2fb0f74ac3e62f495 | 3,598,858 |
def get_strategies_properties():
"""
A function that returns a data frame with the strategies of the Axelrod
library and for each strategy it's property.
"""
axl_strategies = pd.DataFrame(
columns=[
"Name",
"Stochastic",
"Memory_depth",
"Make... | ab2f2a5d8c8f2c59e211d7a6bd8550fc80215ecf | 3,598,859 |
from scipy.optimize import minimize
from scipy.spatial.distance import pdist, squareform
def spring_layout(p, c0=0.2, c1=1.0):
"""Calculate points positions for Pharmacophore depiction using spring
layout.
Args:
p (Pharmacophore): model to depict
c0, c1 (float, optional): coefficients for s... | a3fc0bfd1451d63b28af0c2161a853469b471584 | 3,598,860 |
def flat_concat(xs):
""" From SpinningUp: Merges list of tensors into one (X,) tensor. """
return tf.concat([tf.reshape(x, (-1,)) for x in xs], axis=0) | 049756c1f929ab72264097c382b750602b1a61f1 | 3,598,861 |
import time
import PIL
def upscale_image(model, img):
"""Predict the result based on input image and restore the image as RGB."""
ycbcr = img.convert("YCbCr")
y, cb, cr = ycbcr.split()
y = img_to_array(y)
y = y.astype("float32") / 255.0
input = np.expand_dims(y, axis=0)
start = time.time... | f7be50cb2eff48e9727baa641d3b170ed69f4c1f | 3,598,863 |
def _create_instantiation_proposal(tran_prop_req, chain):
"""Create a chaincode instantiation proposal
This involves assembling the proposal with the data (chaincodeID,
chaincode invocation spec, etc.) and signing it using the private key
corresponding to the ECert to sign.
:param tran_prop_req: se... | f4ef3cbd057c58a0fdb5ca0adf08d22f151b3709 | 3,598,864 |
def flip_nested_dict(nested_dict):
"""Flip nested dictionary inside out."""
flipped = dict()
for key, subdict in nested_dict.items():
for k, v in subdict.items():
flipped[k] = flipped.get(k, dict())
flipped[k][key] = v
return flipped | c1ddbe48a158ed4a96db3b33deb2f423afd304fe | 3,598,865 |
def atr(df, window, high_col="High", low_col="Low", price_col="adj_close"):
"""Average True Range, measuring price volatility.
Parameters:
-----------
df : DataFrame
Input dataframe.
window : int
Length of rolling window for calculation of the ATR.
high_col : str
Column ... | afb6338e33a5c1ab4d4200f43429c3ff0cb9a7cc | 3,598,866 |
def queryConferences(self, request):
"""Query for conferences."""
conferences = Conference.query()
# return individual ConferenceForm object per Conference
return ConferenceForms(
items=[self._copyConferenceToForm(conf, "") \
for conf in conferences]
) | 933e601a8df63564228a015412169cb214bcd65d | 3,598,867 |
def get_users(client):
"""Return the db containing users metadata.
Parameters
----------
client --> pymongo.mongo_client.MongoClient class, MongoDB client
Returns
-------
metadatafs['fs'] --> pymongo.collection.Collection, reference to collection users
"""
#get the MongoDb ... | bd2f0b60781e27a23f015f7a7573821a0e2b8ef0 | 3,598,868 |
def read_raw_values(datasize, datastore, test):
"""read the raw data for a given test"""
in_file_name = str(datasize) + '/' + datastore + '_' + test + '.csv'
return [int(line.strip()) for line in open(in_file_name)] | 1d724b873ee0ccf50d2027df79a2d32472e7942a | 3,598,869 |
def nwi_add_color(fc):
"""Converts NWI vector dataset to image and add color to it.
Args:
fc (object): ee.FeatureCollection
Returns:
object: ee.Image
"""
emergent = ee.FeatureCollection(
fc.filter(ee.Filter.eq('WETLAND_TY', 'Freshwater Emergent Wetland')))
emergent = em... | 9e01958cb02c48b9bb45bb9d4b084dde443ab1ea | 3,598,870 |
from datetime import datetime
async def calculate_maintenance_times():
"""
calculate_maintenance_times: Calculates the proper times for maintenance and
:return: - If there's maintenance, a list of the times as tuples as follows:
[
(JST_START_TIME, JST_END_TIME),
... | fec5e1f8746dc7e3c70cb057d9f7d211732a27ca | 3,598,872 |
def TrimMu(Stot, oldmu, thresh, norm=True):
""" Remove mu measurements below the threshold and adjust mu measurements
above the threshold to unity if we seek P(mu > thresh). """
trim = oldmu > thresh
if norm:
oldmu[:] = 0
oldmu[trim] = 1
else:
oldmu = oldmu[trim]
St... | 2a986599a6116b104b839d8b664f0caff57b1aee | 3,598,873 |
def getMultiData(channel, startTime, endTime):
""" getting multiple values - in progress, testing mode"""
channels = ["25m:guider:probe:exposureID", "25m:guider:probe:probeID",
"25m:guider:probe:flags"]
archiver.scan_archives()
data0, data1, data2 = archiver.get(channels, startTime, end... | 636388fa4341ee66b72f9da3b41ab5a32a21e8ab | 3,598,874 |
async def async_setup(hass: HomeAssistant, yaml_config: ConfigType) -> bool:
"""Activate the emulated_hue component."""
local_ip = await async_get_source_ip(hass)
config = Config(hass, yaml_config.get(DOMAIN, {}), local_ip)
await config.async_setup()
app = web.Application()
app["hass"] = hass
... | 6b0d929b201ede8527f3f4a56b1e93a2c7220599 | 3,598,875 |
def phase(x,period):
"""phase(x,period) returns the phase of location x with respect to the module with spacing period. The phase is between 0 and 1."""
return np.mod(x/float(period),1) | 2b0929d892abd0444a31274adb0f574e34e46014 | 3,598,876 |
def geo_rect(pnt1, pnt2):
"""Generate geo string (Rectangle) for mysql"""
_p1 = range(0, 2)
_p2 = range(0, 2)
_p1[0] = min(pnt1[0], pnt2[0])
_p1[1] = min(pnt1[1], pnt2[1])
_p2[0] = max(pnt1[0], pnt2[0])
_p2[1] = max(pnt1[1], pnt2[1])
return ' GeomFromText(\'Polygon(({0} {1}, {0} {3}, {2... | d47873a7dd1de36b229fb4e26c64a6647b2589b6 | 3,598,877 |
import numpy
def eval_h(x, lagrange, obj_factor, out):
"""Hessian of the Lagrangian
L = obj_factor * f + <lagrange, g>,
where <.,.> denotes the inner product.
"""
out[-1] = 0.0
out[:-2:2] = obj_factor * (2.0 + 400.0 * (3.0 * x[:-1] * x[:-1] - x[1:]))
out[:-4:2] -= lagrange * (2.0 + x[:-2])... | 5864ec66b160a98a75c62cdafc859a87e7e7795f | 3,598,878 |
def translate(speech):
"""
Translate the given speech
:param speech: the string text being given
:return: the returned string changed based on the language
"""
translator = Translator()
word = translator.translate(speech, dest='zh-cn')
print(word.text)
return word.text | 420356ce971807937fed7c9223ec0ef699c4ad6e | 3,598,879 |
def preprocess(dataframe):
"""Converts categorical features to numeric. Removes unused columns.
Args:
dataframe: Pandas dataframe with raw data
Returns:
Dataframe with preprocessed data
"""
dataframe = dataframe.drop(columns=UNUSED_COLUMNS)
# Convert integer valued (numeric) colum... | 7aaf7065d5486e995701513705bb80d463e6b5e0 | 3,598,880 |
def get_training_roidb(imdb):
"""Returns a roidb (Region of Interest database) for use in training."""
# if cfg.TRAIN.USE_FLIPPED:
# print 'Appending horizontally-flipped training examples...'
# imdb.append_flipped_images()
# print 'done'
print 'Preparing training data...'
if cf... | 6fdeb92c4f968155ecb0a3b26ee501103b9503c7 | 3,598,881 |
import collections
def mkparts(sequence, indices=None):
"""
Make some parts from sequence by indices
:param sequence: indexable object
:param indices: index list
:return: [seq_part1, seq_part2, ...]
"""
indices = indices or [1]
result_list = collections.deque()
start = 0
seq_le... | 710841ca3861a33382b6243579eec07f866eb965 | 3,598,882 |
def log_minor_tick_formatter(y: int, pos: float) -> str:
""" Provide reasonable minor tick formatting for a log y axis.
Provides ticks on the 2, 3, and 5 for every decade.
Args:
y: Tick value.
pos: Tick position.
Returns:
Formatted label.
"""
ret_val = ""
# The posi... | a378bd94ceab8698a45403544a728c6c29b402c9 | 3,598,883 |
def s_and_were_or_just_was(parameter):
"""a utility function for grammatical correctness [and DRY, i.e. Don`t Repeat Yourself]"""
return ("s were" if parameter != 1 else " was") | e4d1c03565e89b9b8ecba0137e1b0b9e3bcafa40 | 3,598,884 |
from typing import Union
from pathlib import Path
from typing import Any
from typing import TextIO
def fopen(filepath: Union[str, Path], *args: Any, **kwargs: Any) -> TextIO:
"""Open file.
Args:
filepath (Union[str, Path]): filepath
Returns:
TextIOWrapper: buffer text stream.
"""
... | fcf4ccf53c99a390ceaa9b27f86a7e3f4cff3af1 | 3,598,885 |
import html
def common_null_warning_html(text, alignment="center", top_margin=50):
"""
Get a null warning html block which can be used across all apps. Useful for
when no text is entered into a box, etc.
Args:
text (str): The null warning text.
alignment (str): Either "center" or "lef... | cf9d15b453778d9615da60a5f208c1fbc2a20f57 | 3,598,886 |
def calc_base_rate(data, training=True):
"""Calculates the base-rate for intelligent parameter initialization from the training data."""
suffix = 'train' if training else 'test'
in_key = suffix + '_time_in_seq'
out_key = suffix + '_time_out_seq'
valid_key = suffix + '_event_in_seq'
dts = (data[... | 372680ce7b66a1d370531ab8c3f9ee71f9a48cd9 | 3,598,888 |
def train_model(train_vectors, train_target, model_name):
"""
To train model based on passed data and model name
:param train_vectors: A vector of training data after applying operation of preprocess.py
:param train_target: Corresponding target variable for training data
:param model_name: name of m... | 341e8b08695110f8f6eab6d872e708a7dde6599d | 3,598,889 |
def sql_update(sql):
""" Updates data in table """
string = ''
try:
conn = None
rows = 0
try:
# connect to the PostgreSQL database and create cursor
conn, cur = sql_login()
# execute the UPDATE statement
cur.execute(sql)
#... | 998d7e49d909251593071d1f2790affcfc77b80c | 3,598,891 |
def sample_conditional(category):
"""Samples a drawing for the given category."""
def encode(session, eval_model, input_strokes, length):
strokes = to_big_strokes(input_strokes, length).tolist()
strokes.insert(0, [0, 0, 1, 0, 0])
seq_len = [len(input_strokes)]
return session.run(... | a069819ad248fd27a387a05b681be44de7ef98f7 | 3,598,893 |
def wikify(value):
"""Makes WikiWords"""
return replace_wikiwords(value) | a6f07a01eaf39cc0240f5bddde76f4e7d1153540 | 3,598,894 |
def d_dz_mid(quantity):
"""Derivative applied to quantity at mid level"""
return_value = np.zeros(
[quantity.shape[0], quantity.shape[1]+1], dtype=quantity.dtype)
return_value[1:-1] = quantity[:, 1:] - quantity[:, :-1]
# in CLUBB it is assumed quantities are linear outside of their range at
... | 878482e4d704c97f27f9c0bb067f79f3ae186b3f | 3,598,896 |
def merge(line):
"""
Helper function that merges a single row or column in 2048
line: list like [8, 0, 16, 0, 16, 8]
returns: merged list [8, 32, 8, 0]
loop cur pos and index in list:
if two equal numbers seperated by 0s, double the previous index and replace number at current position with ... | ad43cd74f991490a2fd1ce18a68ae360534c9fd7 | 3,598,897 |
import signal
def signal_number_to_name(signum):
"""
Given an OS signal number, returns a signal name. If the signal
number is unknown, returns ``'UNKNOWN'``.
"""
# Since these numbers and names are platform specific, we use the
# builtin signal module and build a reverse mapping.
signal... | cc17db79f6e47b25e9ec5b9c33fb8d7bf7c0ad26 | 3,598,899 |
def gen_seq_obj_lst(file_contents):
"""
Takes the individual lines from a clustal .aln file
Remove the first few lines.
Make a sequence object list from the remaining.
Sequence object will contain the sequence name (header), sequence and length
"""
sequence_list = []
for line in file_co... | 6925b4c30d5c61aec9582a56894458ebf353eb27 | 3,598,900 |
import socket
def sendethframe(src, dst, eth_type, payload, interface = "eth0"):
"""Send RAW Ethernet Frame."""
assert(len(src) == len(dst) == 6) # 48-bit ethernet addresses
assert(len(eth_type) == 2) # 16-bit ethernet type
s = socket(AF_PACKET, SOCK_RAW)
s.bind((interface, 0))
return s.send(dst + src ... | fec62a08cbf3fc1ce1a18098ede63db9bfd43c12 | 3,598,901 |
from dynamix.correlator.event import EventCorrelator
import time
def gpu_ecorr_q(events, times, offsets, shape, nframes, dtype, qqmask, max_nnz):
""" Calculation of the event correlation function using GPU
:param events: 1D array of events values
:param times: 1D array of times
:param offsets: 1D arr... | 0ac53f30f9a74e9f852620ef6025057f8f289e91 | 3,598,902 |
def label_contiguous_1d(X):
"""
WARNING: API for this function is not liable to change!!!
By example:
X = [F T T F F T F F F T T T]
result = [0 1 1 0 0 2 0 0 0 3 3 3]
Or:
X = [0 3 3 0 0 5 5 5 1 1 0 2]
result = [0 1 1 0 0 2 2 2 3 3 0 4]
The ``0`` or ``Fal... | 202e252e701d560cad3d4c86c15c48dd04bd0e7a | 3,598,903 |
def merge_tables(tables_dict1: SINGLE_REPORT_TABLES, tables_dict2: SINGLE_REPORT_TABLES) -> MERGED_REPORT_TABLES:
"""Combine 2-column tables from single reports, to 3-column tables, with columns corresponding to each report."""
new_table_dict = defaultdict(list)
for tab_name, tab_metrics1 in tables_dict1.... | 9b4514fd0b9266425f8bbd59a1427193e073c464 | 3,598,904 |
def pton_unpack6(address):
"""
Converts IPv6 address to int.
Requires a string, returns a 128 bit int.
"""
try:
pton = inet_pton(AF_INET6, address)
except sockerror:
return None
unpacked = unpack("!QQ", pton)
return (unpacked[0] << 64) | unpacked[1] | dbc0103d6a51f2cfa6b2cd4491e01280368d7a90 | 3,598,905 |
def _toledo8217StatusParse(status):
""" Parse a scale's status, returning a `(weight, weight_info)` pair. """
weight, weight_info = None, None
stat = status[status.index(b'?') + 1]
if stat == 0:
weight_info = 'ok'
else:
weight_info = []
if stat & 1 :
weight_info.a... | 83d8132398e740c71bdf3ac6f65f323f8c8ad65b | 3,598,906 |
def pipe_map(n_caps, n_refs, differential=False):
"""
Creates the code->reference map for pipeline operation. Each column in this
map contains the reference index to be used for the feedfoward capacitors.
:param n_caps: Number of feedfoward capacitors with references,
usually the number of stag... | 93ae2866125cab889d4d3827b7b7b52341a984b6 | 3,598,907 |
import requests
import dateutil
def get_ninja_info(guid, customer_id, site_name):
"""
Pull the needed Student information from the dojo. This can be expanded
but right now we are just getting the most current drop in program
"""
detail = requests.get(
GENERAL_STUDENT_DETAIL.format(
... | aa21fb00628a357dd7015fc0e8f50ed8aa532094 | 3,598,908 |
def num_instances ( diff, flag=False ):
"""Counts the number of palindromic ages.
Returns the number of times the mother and daughter have
palindromic ages in their lives, given the difference in age.
diff: int difference in ages
flag: bool, if True, prints the details
"""
daughter = 0
... | 921953465596f9a9d5201cc62a2391880af4588e | 3,598,910 |
def del_tx_sheet(request, sheet_id):
"""Deletes a treatment sheet."""
tx_sheet = get_object_or_404(TxSheet, id=sheet_id)
if request.user == tx_sheet.owner:
tx_sheet.delete()
return redirect('/tx_sheet/')
else:
raise PermissionDenied | ea90ec12224f2b3e8cb3b38d872b5c1e6a834f80 | 3,598,912 |
import time
def remove_unnecessary_edges(modifiedEdgeListUpdated, origin, destination):
"""
Function to remove any node, which is only connected to one other node and thus is unncessary. This is the case,
because we have only postive edge weights. And thus, visiting the node to then just go back the node ... | 1817c3a9c844f8d9753c6e086632dedc2c4829fc | 3,598,913 |
def validateTelescopeModelName(name):
"""
Validate a telescope model name.
Raises
------
ValueError
If name is not valid.
Parameters
----------
name: str
Returns
-------
str
Validated name.
"""
telClass, telType = splitTelescopeModelName(name)
t... | f696e9cacf45e94b376fa92b19c22483c0b9fa16 | 3,598,914 |
def seasonal_test(x_old, period = 12, alpha = 0.05):
"""
This function checks the Seasonal Mann-Kendall (MK) test (Hirsch, R. M., Slack, J. R. 1984).
Input:
x: a vector of data
period: seasonal cycle. For monthly data it is 12, weekly data it is 52 (12 is the default)
alpha: signi... | 3f2a37e0e0bc062ad0a425afb68dd2e39a576025 | 3,598,915 |
def callform(request):
"""Render call form"""
return render(request, 'helpline/callform.html') | e45309b30704480a79f739c82aba476d40615894 | 3,598,916 |
def model_flow_node_model_flow_id_node_id_component_put(model_flow_id, node_id): # noqa: E501
"""update a node's components information in a model flow chart
update a node's information in a model flow chart # noqa: E501
:param model_flow_id: model flow chart id
:type model_flow_id: str
... | 584a493efb379fecc8b7bcacfab607e2320f4f58 | 3,598,917 |
def draw_all_at_index(index):
"""
Draw all lotteries in the specific index
Args:
index(int): zero-based index that indicates the time of lottery
Return:
winners([[User]]): The list of list of users who won
"""
lotteries = Lottery.query.filter_by(index=index)
... | 62816ae24ab901828c22468ee36066ef86a4beaf | 3,598,918 |
import webbrowser
def CreateOauthToken(expiration="30days", scope='read,write', key=None, secret=None, name='trellodump', output=True):
"""
Script to obtain an OAuth token from Trello. More info on token scope here:
https://trello.com/docs/gettingstarted/#getting-a-token-from-a-user
"""
# Ste... | c83b85b68f2fe3f85f1455557a7a96df62a2d692 | 3,598,919 |
def mscorr(X, ref='mean'):
"""MSC base line correction for spectral data.
Args:
X (np.ndarray): The data set to correct.
ref (list, np.ndarray): The reference spectrum.
Returns:
The data set corrected via MSC.
Notes:
* Implementation partially taken from: By Cleiton A.... | 9ed502ef9e7e10f791112da8f608a14c1f9ff88a | 3,598,920 |
def gsl_blas_sdsdot(*args, **kwargs):
"""gsl_blas_sdsdot(float alpha, gsl_vector_float const * X, gsl_vector_float const * Y, float * result) -> int"""
return _gslwrap.gsl_blas_sdsdot(*args, **kwargs) | 4f81c22174d937ba7eb9bd7073759dda38df25e9 | 3,598,921 |
def generate_bm(df, experiment_keys):
""" Given the flatten DataFrame, containing all the experiment
here we extract the experiments correspondent to the dictionary experiment_keys.
:param df: pandas DataFrame containing the flatten df
:param experiment_keys: dictionary with all the keys.
:returns d... | 43f91e734419c76157920fe486db48e1c17ebdc5 | 3,598,923 |
from typing import Optional
from typing import Union
from typing import Iterable
from typing import Dict
def discover_datasets_unchecked(
uuid_prefix: str,
store: StoreInput,
filter_ktk_cube_dataset_ids: Optional[Union[str, Iterable[str]]] = None,
) -> Dict[str, DatasetMetadata]:
"""
Get all known... | cdac0f0fd08801901c67d50bfecff4122ed30b0c | 3,598,924 |
def findNextKeyForTargetEntry(ipAddr):
""" Find the next available TargetEntry key """
key = "None"
index = 1
while 1:
key = "targetEntry{}".format(index)
index += 1
keypath = cc.Path('/restconf/data/ietf-snmp:snmp/target={name}', name=key)
response=aa.get(keypath)
if response.ok():
if... | 4358f88ac4791bb5cf36e9a50db964752501c4c5 | 3,598,925 |
def twitter_reply(reply_id, username, text):
"""
Args:
reply_id: the tweet id that the bot is replying to
username: the username of the account the bot is replying to
text: what test the bot will use in its reply
Returns:
"""
# This is a default if no text is input
if... | 6159aba6ec50eab18b0ccdfce35e16ceab90d425 | 3,598,926 |
def labeledFcn(fcn, paramNames):
"""Wraps a function with its parameter names (in-place).
:type fcn: callable Python object
:param fcn: function to wrap
:type paramNames: list of strings
:param paramNames: parameters to attach to the function
:rtype: callable Python object
:return: the orig... | e8885cf0cf4db4e84069ec4f0164748b0ab52ae3 | 3,598,927 |
def correct_spectra( df, correction ):
"""
Corrects a spectral DataFrame.
:param df: DataFrame of spectra.
:param correction: Series of correction with same index type as df.
:returns: Corrected DataFrame.
"""
_, corr = std.common_reindex( [ df, correction ] ) # match index
cdf = df.mu... | 43c639d19753ba0fb51fba2f950f4024d43c5546 | 3,598,930 |
from traja.trajectory import _get_time_col
def to_trajr(trj):
"""Convert trajectory to R `trajr` object. Default fps is 30.
Args:
trajectory (:class:`~traja.TrajaDataFrame`): trajectory
Returns:
traj (:class:`rpy2.robjects.vectors.DataFrame`): column names are ['x', 'y', 'time', 'displa... | 9365605e5c48c853650a2573be7ff7583ceb13c1 | 3,598,931 |
def get_rfx_object(packetid):
"""Return the RFXObject with the packetid."""
try:
binarypacket = bytearray.fromhex(packetid)
except ValueError:
return None
pkt = rfxtrxmod.lowlevel.parse(binarypacket)
if pkt is None:
return None
if isinstance(pkt, rfxtrxmod.lowlevel.Senso... | c60ffbbc7dee9423ddbec2107d5ae5951e78ae41 | 3,598,932 |
def get_mask(image, mask, class_ids):
"""Apply color overlay.
image: RGB image [height, width, 3]
mask: instance segmentation mask [height, width, instance count]
Returns result image.
"""
overlay = image
pd_mask = np.zeros([overlay.shape[0], overlay.shape[1], 5], dtype=np.uint8) #classchan... | d549e63904e95ac5a1e16a8bd766c15b9e106c8f | 3,598,933 |
def sell_stock(stock, amount, limit_price, index):
"""
卖出股票，并记录订单号，便于查询订单状态
:param stock:
:param amount:
:param limit_price:
:param index:
:return:
"""
try:
sell_order = order(stock, amount, LimitOrderStyle(limit_price))
finally:
g.__manager.work()
if sell_or... | 4c9415199b7a058e3234fe785708c9b3011989b6 | 3,598,934 |
import logging
def FetchArrayByName(init_def, name):
"""fetch array by name"""
for index, op in enumerate(init_def.op):
if op.output[0] != name:
continue
if op.type != "GivenTensorFill":
logging.error("The array {} is not contained"
" by Given... | ef7d7a57ab5e72ae97a53675a0488f23e4d59564 | 3,598,935 |
from typing import Optional
def calc_interpolation(
val_0: pd.Series,
val_1: pd.Series,
wt_0: pd.Series,
wt_1: Optional[pd.Series] = None,
method: str = "linear",
) -> pd.Series:
"""Calculate interpolation between two values.
Parameters
----------
val_0 : pd.Series
zzz
... | 81a00afbc1c5e60de3b8fd2f3b4dbf26fc20dd7b | 3,598,936 |
def get_min_max(input_list: list) -> tuple:
"""
Return a tuple(min, max) out of list of unsorted integers.
Args:
input_list(list): list of integers containing one or more integers
"""
print("->get_min_max: input_list= " + str(input_list))
if len(input_list) == 0:
return None, No... | 26db872de57ed6c94825e089607a4bb81390b423 | 3,598,939 |
def _code_and_constants(object_):
"""Helper function to get python code and constants"""
return _code_and_constants_attr_getter(object_.__code__) | 0385a73ac2ed70e30cdaf3246ec722e4fe1d97da | 3,598,940 |
from typing import Union
def threshold_events(
data: np.ndarray, threshold: Union[float, int]
) -> np.ndarray:
"""Apply threshold to find start and end of events.
Arguments
---------
data : np.ndarray
Input data to apply thresholding to.
threshold : float | int
Threshold value... | 066f799af2ecd245cd278d73aa1ce534475da571 | 3,598,941 |
import torch
def value_td_residuals(
rewards: torch.Tensor,
values: torch.Tensor,
next_values: torch.Tensor,
discount: float,
) -> torch.Tensor:
"""Compute TD residual of state value function.
All tensors must be one dimensional. This is valid only for one trajectory.
Parameters
----... | 723ed0f0ce651cc7da5ad9c7950972d104198888 | 3,598,942 |
from typing import List
def get_dataset(organisms: List[Organism]):
""" Builds a dataset with the samples associated with the given organisms """
dataset = {}
filter_query = Q()
for organism in organisms:
filter_query = filter_query | Q(organisms=organism)
experiments = Experiment.object... | af4edb3b09b8391c47efe31db83f88c2598650c5 | 3,598,944 |
async def agather(aiter):
"""Gather an async iterator into a list"""
lst = []
async for elem in aiter:
lst.append(elem)
return lst | 0a7f278d38237a722724572b6705deab429c8e70 | 3,598,945 |
import random
def generate_Gnp_with_planted_clique(n, p, clique_size):
"""
Given a number of vertices n, a probability p and a clique size
the method returns a networkx gnp graph with an additional planted clique
i.e. from the Gnp graph we select a random subset of vertices of size clique_size
and... | 7ce98916c3a47e4af578474a3e83621fbf2e3c4d | 3,598,946 |
def default_panels(institute_id, case_name):
"""Update default panels for a case."""
panel_ids = request.form.getlist('panel_ids')
controllers.update_default_panels(store, current_user, institute_id, case_name, panel_ids)
return redirect(request.referrer) | abfcffcf26e41be209eb35bf4230f0055b193ccf | 3,598,948 |
def ParseImportLine(line):
"""Parse a line potentially containing an import.
Note that this function does NOT properly handle:
from foo.bar import FooClass
It's too expensive to code for and against Python style anyway.
Args:
line: string, like "from x import y" or "import x.y"
Returns:
None:... | 2f1d2fe3bd3744e09826bf2625e3bb2c6796494c | 3,598,949 |
def client_inner_dirichlet_partition(targets, num_clients, num_classes, dir_alpha,
client_sample_nums, verbose=True):
"""Non-iid Dirichlet partition.
The method is from The method is from paper `Federated Learning Based on Dynamic Regularization <https://openreview.net/foru... | 90828ef055f520d62aecb1ac92c6622121fba4ad | 3,598,950 |
def filterTCPString(TCPMessage):
""" Remove any unwanted characters from the TCP message string and truncate if necessary """
# sometimes a failed command will return html which end up in (e.g.) pilotErrorDiag, remove it
if TCPMessage.upper().find("<HTML>") >= 0:
# reset here. the error diag will b... | 3f17c7ca4c7bb738e055127b1150bbbcbffd8653 | 3,598,951 |
from datetime import datetime
import pytz
def now():
"""Returns the ISO 8601 formatted time in UTC"""
return datetime.now(pytz.utc).isoformat() | e423e8555315f551f284c92f4fee5b3f92c1f41d | 3,598,952 |
def carmichaellambda(n):
"""carmichaellambda(n) - Computer Carmichael's Lambda function
of n - the smallest exponent e such that b**e = 1 for all b coprime to n.
Otherwise defined as the exponent of the group of integers mod n."""
thefactors = factors(n)
thefactors.sort()
thefactors += [0] # Mark the end of the... | c076deb1a8216c2da32a2f83cc224bf3fe6b5040 | 3,598,953 |
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