content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
from typing import Dict
from typing import Any
import toml
from pathlib import Path
import textwrap
def load_configuration() -> Dict[str, Any]:
"""
Return dict from TOML formatted string or file.
Returns:
The dict configuration.
"""
default_config = """
[key_bindings]
... | a7a53382dd43023b74fbb88b9c2540499c9beb4f | 8,900 |
def type_weapon(stage, bin, data=None):
"""Weapon"""
if data == None:
return 1
if stage == 1:
return (str(data),'')
try:
v = int(data)
if 0 > v or v > 255:
raise
except:
raise PyMSError('Parameter',"Invalid Weapon value '%s', it must be 1 for ground attack or not 1 for air attack." % data)
return v | 51ad1c627b05b57ad67f5558bb76de3fe6e48f27 | 8,901 |
def to_square_feet(square_metres):
"""Convert metres^2 to ft^2"""
return square_metres * 10.7639 | 50510aad230efcb47662936237a232662fef5596 | 8,902 |
def middle_name_handler(update: Update, context: CallbackContext) -> str:
"""Get and save patronymic of user. Send hello with full name."""
u = User.get_user(update, context)
name = (f'{context.user_data[LAST_NAME]} {context.user_data[FIRST_NAME]} '
f'{context.user_data[MIDDLE_NAME]}')
cont... | dab2144282aeb63c2a3c4218236d04c3bb940ac8 | 8,903 |
def submit_barcodes(barcodes):
"""
Submits a set of {release1: barcode1, release2:barcode2}
Must call auth(user, pass) first
"""
query = mbxml.make_barcode_request(barcodes)
return _do_mb_post("release", query) | 6e975e791196ed31ef6f52cdd0ca04d71a8d19eb | 8,904 |
from typing import Counter
def get_idf_dict(arr, tokenizer, nthreads=4):
"""
Returns mapping from word piece index to its inverse document frequency.
Args:
- :param: `arr` (list of str) : sentences to process.
- :param: `tokenizer` : a BERT tokenizer corresponds to `model`.
- :pa... | e98a9578695781e4965b36d713c4c0a4351e53da | 8,905 |
import json
def load_id_json_file(json_path):
"""
load the JSON file and get the data inside
all this function does is to call json.load(f)
inside a with statement
Args:
json_path (str): where the target JSON file is
Return:
ID list (list): all the d... | fd0f7fb73636cdf407b4de3e1aa3ae66dcc8f964 | 8,906 |
def check_github_scopes(exc: ResponseError) -> str:
"""
Parse github3 ResponseError headers for the correct scopes and return a
warning if the user is missing.
@param exc: The exception to process
@returns: The formatted exception string
"""
user_warning = ""
has_wrong_status_code = e... | ebb3fffcaddc792dac7c321d9029b5042a42be86 | 8,907 |
def user_login():
"""
# 显示页面的设置
:return: 接收前端的session信息来显示不同的页面
"""
# 获取参数
name = session.get("name")
if name is not None:
return jsonify(errno=RET.OK, errmsg="True", data={"name": name})
else:
return jsonify(errno=RET.SESSIONERR, errmsg="用户未登入") | 213ad2338260364186c0539a9e995b84ee889b42 | 8,908 |
def sample_conditional(node: gtsam.GaussianConditional, N: int, parents: list = [], sample: dict = {}):
"""Sample from conditional """
# every node ~ exp(0.5*|R x + S p - d|^2)
# calculate mean as inv(R)*(d - S p)
d = node.d()
n = len(d)
rhs = d.reshape(n, 1)
if len(parents) > 0:
rhs... | b9ab05ea50eea05a779c6d601db4643a86b343d5 | 8,909 |
def _liftover_data_path(data_type: str, version: str) -> str:
"""
Paths to liftover gnomAD Table.
:param data_type: One of `exomes` or `genomes`
:param version: One of the release versions of gnomAD on GRCh37
:return: Path to chosen Table
"""
return f"gs://gnomad-public-requester-pays/relea... | 8da0f93c86568d56b3211bcb9e226b9cb495c8e2 | 8,910 |
def valueinfo_to_tensor(vi):
"""Creates an all-zeroes numpy tensor from a ValueInfoProto."""
dims = [x.dim_value for x in vi.type.tensor_type.shape.dim]
return np.zeros(
dims, dtype=onnx.mapping.TENSOR_TYPE_TO_NP_TYPE[vi.type.tensor_type.elem_type]
) | b814373e7c9d4f1e43f9d1af0c6e48b82989602e | 8,911 |
def signup_email():
"""Create a new account using data encoded in the POST body.
Expects the following form data:
first_name: E.g. 'Taylor'
last_name: E.g. 'Swift'
email: E.g. 'tswift@gmail.com'
password: E.g. 'iknewyouweretrouble'
Responds with the session cookie via the `... | e3ecca4bd244d1d20ad166a153a6c3f5c80f4876 | 8,912 |
def calculate_multi_rmse(regressor, n_task):
"""
Method which calculate root mean squared error value for trained model
Using regressor attributes
Return RMSE metrics as dict for train and test datasets
:param regressor: trained regression model object
:param n_task:
:type regressor: Traine... | 53daee6abb97a96af44831df59767a447fd2786e | 8,913 |
import torch
from re import T
def detr_predict(model, image, thresh=0.95):
"""
Function used to preprocess the image, feed it into the detr model, and prepare the output draw bounding boxes.
Outputs are thresholded.
Related functions: detr_load, draw_boxes in coco.py
Args:
model -- the... | 394824358138eb66b69569963b21ccc2d0f5a4d3 | 8,914 |
def comp_fill_factor(self):
"""Compute the fill factor of the winding"""
if self.winding is None:
return 0
else:
(Nrad, Ntan) = self.winding.get_dim_wind()
S_slot_wind = self.slot.comp_surface_wind()
S_wind_act = (
self.winding.conductor.comp_surface_active()
... | 55be8ac7aa2961ad970cd16de961fdcf857016fd | 8,915 |
def idewpt(vp):
"""
Calculate the dew point given the vapor pressure
Args:
vp - array of vapor pressure values in [Pa]
Returns:
dewpt - array same size as vp of the calculated
dew point temperature [C] (see Dingman 2002).
"""
# ensure that vp is a numpy array
... | 68b58d7702a50472a4851e1a7ecdd6ba13fe540a | 8,916 |
def _hexify(num):
"""
Converts and formats to hexadecimal
"""
num = "%x" % num
if len(num) % 2:
num = '0'+num
return num.decode('hex') | 71fabff1191f670ec503c76a3be916636e8045ce | 8,917 |
def syn_ucbpe(num_workers, gp, acq_optimiser, anc_data):
""" Returns a recommendation via UCB-PE in the synchronous setting. """
# Define some internal functions.
beta_th = _get_ucb_beta_th(gp.input_dim, anc_data.t)
# 1. An LCB for the function
def _ucbpe_lcb(x):
""" An LCB for GP-UCB-PE. """
mu, sigm... | 2c12a608c87d61f64b219aaf301189b6c8ee73a2 | 8,918 |
def get_reward(intervention, state, time):
"""Compute the reward based on the observed state and choosen intervention."""
A_1, A_2, A_3 = 60, 500, 60
C_1, C_2, C_3, C_4 = 25, 20, 30, 40
discount = 4.0 / 365
cost = (
A_1 * state.asymptomatic_humans
+ A_2 * state.symptomatic_humans
... | 72803b1a5f09d0856d29601bc766b6787a8255e7 | 8,919 |
def array_of_floats(f):
"""Read an entire file of text as a list of floating-point numbers."""
words = f.read().split()
return [builtin_float(x) for x in words] | 8b357afb3f977761118f7df2632a4f1c198d721a | 8,920 |
def change_currency():
""" Change user's currency """
form = CurrencyForm()
if form.validate_on_submit():
currency = form.rate.data
redirected = redirect(url_for('cashtrack.overview'))
redirected.set_cookie('filter', currency)
symbol = rates[currency]['symbol']
flash(... | 08a23e47a603ee5d5e49cff0259a83f4a2ffc3e0 | 8,921 |
import subprocess
def get_host_checks():
"""
Returns lxc configuration checks.
"""
out = subprocess.check_output('lxc-checkconfig', shell=True)
response = []
if out:
for line in out.splitlines():
response.append(line.decode('utf-8'))
info = {
'checks': respo... | d94b3b94ec6f32e2706eaf7b67f570de2fc34f14 | 8,922 |
def q2_1(df: pd.DataFrame) -> int:
"""
Finds # of entries in df
"""
return df.size[0] | d98a3d5592994e7dd3758dfab683cb96b532ce6d | 8,923 |
def is_shell(command: str) -> bool:
"""Check if command is shell."""
return command.startswith(get_shell()) | 0cc1497dc17e1535fdfb23c1b160bfcd63141eb1 | 8,924 |
import argparse
def parse_args():
"""set and check parameters."""
parser = argparse.ArgumentParser(description="bert process")
parser.add_argument("--pipeline_path", type=str, default="./config/fat_deepffm.pipeline", help="SDK infer pipeline")
parser.add_argument("--data_dir", type=str, default="../da... | d93eca1a5c36d73944762967bf6557ee5e15d346 | 8,925 |
def board_init():
"""
Initializes board with all available values 1-9 for each cell
"""
board = [[[i for i in range(1,n+1)] for j in range(n)] for k in range(n)]
return board | e4b7192c02e298de915eb3024f32f194942a061b | 8,926 |
def gen_int_lists(num):
"""
Generate num list strategies of integers
"""
return [
s.lists(s.integers(), max_size=100)
for _ in range(num)
] | f1bd151a09f78b1eee9803ce2a077a4f01d34aaa | 8,927 |
def is_blob(bucket: str, file:str):
""" checking if it's a blob """
client = storage.Client()
blob = client.get_bucket(bucket).get_blob(file)
return hasattr(blob, 'exists') and callable(getattr(blob, 'exists')) | ba9bb07f1f15175a28027907634c37b402c6b292 | 8,928 |
def rotate(q, p):
"""
Rotation of vectors in p by quaternions in q
Format: The last dimension contains the quaternion components which
are ordered as (i,j,k,w), i.e. real component last.
The other dimensions follow the default broadcasting rules.
"""
iw = 3
ii = 0
i... | da8c715276d5bef0340ad3378aa127c9ddb75f96 | 8,929 |
from typing import Union
def _is_whitelisted(name: str, doc_obj: Union['Module', 'Class']):
"""
Returns `True` if `name` (relative or absolute refname) is
contained in some module's __pdoc__ with a truish value.
"""
refname = doc_obj.refname + '.' + name
module = doc_obj.module
while modul... | c54c69ae0180c1764c8885d00e96640f1bfff0f8 | 8,930 |
import copy
def permute_bond_indices(atomtype_vector):
"""
Permutes the set of bond indices of a molecule according to the complete set of valid molecular permutation cycles
atomtype_vector: array-like
A vector of the number of each atoms, the length is the total number of atoms.
An A3B8C ... | ebf398e55d8a80a2e4ce2cef4f48d957e47d68a3 | 8,931 |
def get_cell_integer_param(device_resources,
cell_data,
name,
force_format=None):
"""
Retrieves definition and decodes value of an integer cell parameter. The
function can optionally force a specific encoding format if needed.
... | 6ab281004f324e8c40e176d5676cd7e42f50eaa9 | 8,932 |
import hashlib
def get_md5(filename):
""" Calculates the MD5 sum of the passed file
Args:
filename (str): File to hash
Returns:
str: MD5 hash of file
"""
# Size of buffer in bytes
BUF_SIZE = 65536
md5 = hashlib.md5()
# Read the file in 64 kB blocks
... | c43538aee954f670c671c2e26e18f4a17e298455 | 8,933 |
import os
def get_py_path(pem_path):
"""Returns the .py filepath used to generate the given .pem path, which may
or may not exist.
Some test files (notably those in verify_certificate_chain_unittest/ have a
"generate-XXX.py" script that builds the "XXX.pem" file. Build the path to
the corresponding "genera... | 0bc97d23138c44e051282fdfa22517f1289ab65a | 8,934 |
def is_recurrent(sequence):
"""
Returns true if the given sequence is recurrent (elements can exist more than once), otherwise returns false.
Example
---------
>>> sequence = [1,2,3,4,5]
>>> ps.is_recurrent(sequence)
False
>>> sequence = [1,1,2,2,3]
>>> ps.is_recurrent(sequence)
True
"""
element_counts... | e123ddd960b262651b20e54ccbd3d5b11fe3695e | 8,935 |
import torch
def flex_stack(items, dim=0):
"""
"""
if len(items) < 1:
raise ValueError("items is empty")
if len(set([type(item) for item in items])) != 1:
raise TypeError("items are not of the same type")
if isinstance(items[0], list):
return items
elif isinstance(it... | 47ca0e47647ce86619f1cdc86eef560fbbb9304e | 8,936 |
from pathlib import Path
def download_image_data(gpx_file,
padding,
square,
min_lat,
min_long,
max_lat,
max_long,
cache_di... | 4ceef45da21622ab716031e8f68ed4724e168062 | 8,937 |
def find_nearest_values(array, value):
"""Find indexes of the two nearest values of an array to a given value
Parameters
----------
array (numpy.ndarray) : array
value (float) : value
Returns
-------
idx1 (int) : index of nearest value in the array
idx2 (int) : index of s... | 9c873692878ef3e4de8762bb89306e7ef907f90a | 8,938 |
def channel_info(channel_id):
"""
Get Slack channel info
"""
channel_info = slack_client.api_call("channels.info", channel=channel_id)
if channel_info:
return channel_info['channel']
return None | 260eeaa2849350e2ede331ddecd68aead798f76c | 8,939 |
from typing import Callable
from typing import Any
import logging
def log(message: str) -> Callable:
"""Returns a decorator to log info a message before function call.
Parameters
----------
message : str
message to log before function call
"""
def decorator(function: Callable) -> Cal... | c8ed8f8119be8d6e80935d73034f752ad2cb1dd9 | 8,940 |
def client(identity: PrivateIdentity) -> Client:
"""Client for easy access to iov42 platform."""
return Client(PLATFORM_URL, identity) | a0ad172765b50a76485bd3ec630a2c3ffeae85ef | 8,941 |
def init_weights(module, init='orthogonal'):
"""Initialize all the weights and biases of a model.
:param module: any nn.Module or nn.Sequential
:param init: type of initialize, see dict below.
:returns: same module with initialized weights
:rtype: type(module)
"""
if init is None: # Base ... | e8cd95743b8a36dffdb53c7f7b9723e896d2071d | 8,942 |
def getsoundchanges(reflex, root): # requires two ipastrings as input
"""
Takes a modern-day L1 word and its reconstructed form and returns \
a table of sound changes.
:param reflex: a modern-day L1-word
:type reflex: str
:param root: a reconstructed proto-L1 word
:type root: str
:re... | 8230e836e109ed8453c6fdbc72e6a4f77833f69b | 8,943 |
def compute_normals(filename, datatype='cell'):
"""
Given a file, this method computes the surface normals of the mesh stored
in the file. It allows to compute the normals of the cells or of the points.
The normal computed in a point is the interpolation of the cell normals of
the cells adiacent to ... | e0cfc90a299f6db52d9cec2f39eebfc96158265c | 8,944 |
from typing import List
from typing import Optional
def build_layers_url(
layers: List[str], *, size: Optional[LayerImageSize] = None
) -> str:
"""Convenience method to make the server-side-rendering URL of the provided layer URLs.
Parameters
-----------
layers: List[:class:`str`]
The ima... | 2cc7ab58af2744a4c898903d9a035c77accbae2e | 8,945 |
def SyncBatchNorm(*args, **kwargs):
"""In cpu environment nn.SyncBatchNorm does not have kernel so use nn.BatchNorm2D instead"""
if paddle.get_device() == 'cpu':
return nn.BatchNorm2D(*args, **kwargs)
else:
return nn.SyncBatchNorm(*args, **kwargs) | f08a7141700b36286893bbbc82b28686d1ca88a9 | 8,946 |
def data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_capacity_bandwidth_profile_peak_burst_size_get(uuid, local_id): # noqa: E501
"""data_context_connectivity_context_connectivity_serviceuuid_end_pointlocal_id_capacity_bandwidth_profile_peak_burst_size_get
returns tapi.common.Capac... | 340189bc76bdbbc14666fe542aa05d467c7d4898 | 8,947 |
import re
def parse_path_length(path):
"""
parse path length
"""
matched_tmp = re.findall(r"(S\d+)", path)
return len(matched_tmp) | 762e2b86fe59689800ed33aba0419f83b261305b | 8,948 |
def check_permisions(request, allowed_groups):
""" Return permissions."""
try:
profile = request.user.id
print('User', profile, allowed_groups)
is_allowed = True
except Exception:
return False
else:
return is_allowed | 4bdb54bd1edafd7a0cf6f50196d470e0d3425c66 | 8,949 |
def kanji2digit(s):
"""
1から99までの漢数字をアラビア数字に変換する
"""
k2d = lambda m, i: _kanjitable[m.group(i)]
s = _re_kanjijiu1.sub(lambda m: k2d(m,1) + k2d(m,2), s)
s = _re_kanjijiu2.sub(lambda m: u'1' + k2d(m,1), s)
s = _re_kanji.sub(lambda m: k2d(m,1), s)
s = s.replace(u'十', u'10')
return s | 27589cee8a9b4f14ad7120061f05077b736b8632 | 8,950 |
def calc_rdm_segment(t, c, segment_id_beg, segment_id_end, segment_id, ph_index_beg, segment_ph_cnt, debug=0):
"""
Function to calculate radiometry (rdm)
Input:
t - time or delta_time of ATL03, for a given gt num
c - classification of ATL03 for a given gt num
ensure that no nan... | 47ac61f816a5f8e9c3f86c5b1e8ad2f9f660f8a2 | 8,951 |
def load_featurizer(pretrained_local_path):
"""Load pretrained model."""
return CNN_tf("vgg", pretrained_local_path) | 1f39acdae01e484302d8f8051c2f55a178aa2301 | 8,952 |
import os
import zipfile
def create_zipfile(dir_to_zip, savepath=''):
"""Create a zip file from all the files under 'dir_to_zip'.
The output zip file will be saved to savepath.
If savepath ends with '.zip', then the output zip file will be
saved AS 'savepath'. Necessary tree subdirectories are create... | dd18a1272a25c3fb272345fc8b71a303c6cc4053 | 8,953 |
from templateflow.conf import setup_home
def make_cmdclass(basecmd):
"""Decorate setuptools commands."""
base_run = basecmd.run
def new_run(self):
setup_home()
base_run(self)
basecmd.run = new_run
return basecmd | dc66370f19e2d1b3dbc2da3942f8923a07d8d9a6 | 8,954 |
def rmse(predictions, targets):
"""Compute root mean squared error"""
rmse = np.sqrt(((predictions - targets) ** 2).mean())
return rmse | 1a5fe824c5ef768f3df34463724fdd057d37901a | 8,955 |
import math
def format_timedelta(value, time_format=None):
""" formats a datetime.timedelta with the given format.
Code copied from Django as explained in
http://stackoverflow.com/a/30339105/932593
"""
if time_format is None:
time_format = "{days} days, {hours2}:{minutes2}:{seconds2}... | 0ee6a48e0eee5e553e665d44173f0a4843b4007f | 8,956 |
def categorical_log_likelihood(probs: chex.Array, labels: chex.Array):
"""Computes joint log likelihood based on probs and labels."""
num_data, unused_num_classes = probs.shape
assert len(labels) == num_data
assigned_probs = probs[jnp.arange(num_data), jnp.squeeze(labels)]
return jnp.sum(jnp.log(ass... | 6209fc59dc6a76f8afc49788b9e5c5a11f58354f | 8,957 |
def ask_name(question: str = "What is your name?") -> str:
"""Ask for the users name."""
return input(question) | 1cc9ec4d3bc48d7ae4be1b2cf8eb64a0b4f94b23 | 8,958 |
from typing import Sequence
def _maxcut(g: Graph, values: Sequence[int]) -> float:
"""
cut by given values $$\pm 1$$ on each vertex as a list
:param g:
:param values:
:return:
"""
cost = 0
for e in g.edges:
cost += g[e[0]][e[1]].get("weight", 1.0) / 2 * (1 - values[e[0]] * val... | 1ca8d2cfce6a741fb4eab55f7fcd9d9db5e3578f | 8,959 |
def cp_als(X, rank, random_state=None, init='randn', **options):
"""Fits CP Decomposition using Alternating Least Squares (ALS).
Parameters
----------
X : (I_1, ..., I_N) array_like
A tensor with ``X.ndim >= 3``.
rank : integer
The `rank` sets the number of components to be compute... | b6402f03ba4e8be7d0abb2b13232d88b07a73be9 | 8,960 |
import os
def load_station_enu(
station_name,
start_date=None,
end_date=None,
download_if_missing=True,
force_download=False,
zero_by="mean",
to_cm=True,
):
"""Loads one gps station's ENU data since start_date until end_date as a dataframe
Args:
station_name (str): 4 Lette... | 208b6b6776ad3eb0ef765a5b56d287e7ed06e63f | 8,961 |
def decode_hint(hint: int) -> str:
"""Decodes integer hint as a string.
The format is:
⬜ (GRAY) -> .
🟨 (YELLOW) -> ?
🟩 (GREEN) -> *
Args:
hint: An integer representing the hint.
Returns:
A string representing the hint.
"""
hint_str = []
for _ ... | 4180b847cd252a1e3c762431327b1b6d359dac3d | 8,962 |
import os
import tempfile
import subprocess
def validate_notebook(nb_path, timeout=60):
""" Executes the notebook via nbconvert and collects the output
Args:
nb_path (string): path to the notebook of interest
timeout (int): max allowed time (in seconds)
Returns:
(parsed nbformat.... | 475a11036a5330df8f82d9876731d3d688749aa8 | 8,963 |
def is_symmetric(arr, i_sym=True, j_sym=True):
"""
Takes in an array of shape (n, m) and check if it is symmetric
Parameters
----------
arr : 1D or 2D array
i_sym : array
symmetric with respect to the 1st axis
j_sym : array
symmetric with respect to the 2nd axis
Returns... | 488744d34d851b690eb6114b06d754e46b04e36f | 8,964 |
def linear_powspec(k, a):
"""linear power spectrum P(k) - linear_powspec(k in h/Mpc, scale factor)"""
return _cosmocalc.linear_powspec(k, a) | 9abe99ef5251b4b8ef04e7113a30dd26ed86d14a | 8,965 |
def light_eff(Pmax, Iz, I0, Ik):
"""
Photosynthetic efficiency based on the light conditions. By definition, the
efficiency has a value between 0 and 1.
Parameters
----------
Pmax : numeric
Maximum photosynthetic rate [-].
Iz : numeric
Coral biomass-averaged light-intensity ... | a2e0de2cb0791d3afea15f4c78b7d673200504b3 | 8,966 |
import array
import time
def radial_kernel_evaluate(rmax, kernel, pos, wts, log=null_log, sort_data=False,
many_ngb_approx=None):
"""
Perform evaluation of radial kernel over neighbours.
Note you must set-up the linear-interpolation kernel before calling this
function.
... | 41c4600be3a5684c97d69acb4ebe15846dcc4b0d | 8,967 |
def get_referents(source, exclude=None):
"""
:return: dict storing lists of objects referring to source keyed by type.
"""
res = {}
for obj_cls, ref_cls in [
(models.Language, models.LanguageSource),
(models.ValueSet, models.ValueSetReference),
(models.Sentence, models.Senten... | 2aeccbbe61cdcb2b3183682a5cce8ed959fc14c9 | 8,968 |
import array
def asarray(buffer=None, itemsize=None, shape=None, byteoffset=0,
bytestride=None, padc=" ", kind=CharArray):
"""massages a sequence into a chararray.
If buffer is *already* a chararray of the appropriate kind, it is
returned unaltered.
"""
if isinstance(buffer, kind) and... | 346eaaa9ece9671f5b2fa0633552f72e40300adc | 8,969 |
import zipfile
import os
import sys
def _extract_symlink(zipinfo: zipfile.ZipInfo,
pathto: str,
zipfile: zipfile.ZipFile,
nofixlinks: bool=False) -> str:
"""
Extract: read the link path string, and make a new symlink.
'zipinfo' is the link fi... | da3e470cb78474bf56b82f9deb2e1febdd53f668 | 8,970 |
import os
def read_file(fname, ObsClass, verbose=False):
"""This method is used to read the file.
"""
if verbose:
print('reading menyanthes file {}'.format(fname))
if ObsClass == observation.GroundwaterObs:
_rename_dic = {'xcoord': 'x',
'ycoord': 'y',
... | c35b31048cd823fa1f0157cedd6ce88331be5bf0 | 8,971 |
def cumulative_gain_curve(df: pd.DataFrame,
treatment: str,
outcome: str,
prediction: str,
min_rows: int = 30,
steps: int = 100,
effect_fn: EffectFnType = linear_ef... | ca493a85d1aa7d74335b1ddb65f2f2a94fcaa152 | 8,972 |
def last(*args):
"""Return last value from any object type - list,tuple,int,string"""
if len(args) == 1:
return int(''.join(map(str,args))) if isinstance(args[0],int) else args[0][-1]
return args[-1] | ad8d836597dd6a5dfe059756b7d8d728f6ea35fc | 8,973 |
from matplotlib.patheffects import withStroke
def load_ann_kwargs():
"""emboss text"""
myeffect = withStroke(foreground="w", linewidth=3)
ann_kwargs = dict(path_effects=[myeffect])
return ann_kwargs | a4ff019fe234b44da20e3b8f686f852554018546 | 8,974 |
import sys
def color_conversion(img_name, color_type="bgr2rgb"):
"""
色空間の変換
Parameters
----------
img_name : numpy.ndarray
入力画像
color_type : str
変換のタイプ
bgr2rgb, bgr2hsv, bgr2gray, rgb2bgr,
rgb2hsv, rgb2gray, hsv2bgr, hsv2rgb
Return
-------
conversi... | 66abc2c44721e262a948b86221063fb57bf1e148 | 8,975 |
def predict(self, celldata):
"""
This is the method that's to perform prediction based on a model
For now it just returns dummy data
:return:
"""
ai_model = load_model_parameter()
ret = predict_unseen_data(ai_model, celldata)
print("celldata: ", celldata)
print("Classification: ", re... | 435be195c765aa3823a710982bdc6f7954a24178 | 8,976 |
from typing import List
def statements_to_str(statements: List[ASTNode], indent: int) -> str:
"""Takes a list of statements and returns a string with their C representation"""
stmt_str_list = list()
for stmt in statements:
stmt_str = stmt.to_str(indent + 1)
if not is_compound_statement(stm... | 01bd0546be8b7a212dbb73fae3c505bbe0086b48 | 8,977 |
def _make_filter(class_name: str, title: str):
"""https://docs.microsoft.com/en-us/windows/win32/api/winuser/nf-winuser-enumwindows"""
def enum_windows(handle: int, h_list: list):
if not (class_name or title):
h_list.append(handle)
if class_name and class_name not in win32gui.GetCla... | 3b9d5f3fe4afd666cfa7ed43f8abe103b9575249 | 8,978 |
def is_float(s):
"""
Detertmine if a string can be converted to a floating point number.
"""
try:
float(s)
except:
return False
return True | 2df52b4f8e0835d9f169404a6cb4f003ca661fff | 8,979 |
def build_lm_model(config):
"""
"""
if config["model"] == "transformer":
model = build_transformer_lm_model(config)
elif config["model"] == "rnn":
model = build_rnn_lm_model(config)
else:
raise ValueError("model not correct!")
return model | 03a84f28ec4f4a7cd847575fcbcf278943b72b8a | 8,980 |
def __virtual__():
"""
Only load if boto3 libraries exist.
"""
has_boto_reqs = salt.utils.versions.check_boto_reqs()
if has_boto_reqs is True:
__utils__["boto3.assign_funcs"](__name__, "cloudfront")
return has_boto_reqs | 63d2f1102713b8da66e75b28c4c642427fe69e8a | 8,981 |
import glob
import os
def extract_binaries(pbitmap, psamples):
"""
Extract sample binaries from subdirectories according to dataset defined in bitmap.
"""
bins = glob.glob(psamples+'/**/*.bin', recursive=True)
bitmap = pd.read_csv(pbitmap) if '.tsv' not in pbitmap else pd.read_csv(pbitmap, sep='\t... | e3086e1ec5dcda0b89f34fb917eb422c8cde285b | 8,982 |
def search_range(nums, target):
"""
Find first and last position of target in given array by binary search
:param nums: given array
:type nums : list[int]
:param target: target number
:type target: int
:return: first and last position of target
:rtype: list[int]
"""
result = [-1... | 8165e3a2f33741c15494d5d98a82a85c2fb610ff | 8,983 |
def process_mean_results(data, capacity, constellation, scenario, parameters):
"""
Process results.
"""
output = []
adoption_rate = scenario[1]
overbooking_factor = parameters[constellation.lower()]['overbooking_factor']
constellation_capacity = capacity[constellation]
max_capacity = ... | 0619c397a21d27440988c4b23284e44700ba69eb | 8,984 |
def identify_ossim_kwl(ossim_kwl_file):
"""
parse geom file to identify if it is an ossim model
:param ossim_kwl_file : ossim keyword list file
:type ossim_kwl_file : str
:return ossim kwl info : ossimmodel or None if not an ossim kwl file
:rtype str
"""
try:
with open(ossim_kwl_... | 9a63a8b5e7ece79b11336e71a8afa5a703e3acbc | 8,985 |
def conv_cond_concat(x, y):
""" Concatenate conditioning vector on feature map axis.
# Arguments
x: 4D-Tensor
y: 4D-Tensor
# Return
4D-Tensor
"""
x_shapes = x.get_shape()
y_shapes = y.get_shape()
return tf.concat(3, [x, y * tf.ones([x_shapes[0], x_shapes[1], x_shape... | c30a4328d3a6e8cf2b1e38cf012edca045e9de69 | 8,986 |
def get(args, syn):
"""TODO_Sphinx."""
entity = syn.get(args.id)
## TODO: Is this part even necessary?
## (Other than the print statements)
if 'files' in entity:
for file in entity['files']:
src = os.path.join(entity['cacheDir'], file)
dst = os.path.join('.'... | 61bb507faaa2821619e77972dc23158fdc3228ba | 8,987 |
def swath_pyresample_gdaltrans(file: str, var: str, subarea: dict, epsilon: float, src_tif: str, dst_tif: str):
"""Reprojects swath data using pyresample and translates the image to EE ready tif using gdal
Parameters
----------
file: str
file to be resampled and uploaded to GC -> EE
var: st... | b716a6b45cf48457d0c6ca5849997b7c37c6c795 | 8,988 |
def run_drc(cell_name, gds_name, sp_name=None, extract=True, final_verification=False):
"""Run DRC check on a cell which is implemented in gds_name."""
global num_drc_runs
num_drc_runs += 1
write_drc_script(cell_name, gds_name, extract, final_verification, OPTS.openram_temp, sp_name=sp_name)
(out... | ac44030fc343b50d1035f5b584fc4f64f319aa27 | 8,989 |
def getKeyPairPrivateKey(keyPair):
"""Extracts the private key from a key pair.
@type keyPair: string
@param keyPair: public/private key pair
@rtype: base string
@return private key PEM text
"""
return crypto.dump_privatekey(crypto.FILETYPE_PEM, keyPair) | 0decc2dbb77343a7a200ace2af9277ee7e5717a5 | 8,990 |
def playbook_input(request, playbook_id, config_file=None, template=None):
"""Playbook input view."""
# Get playbook
playbook = Playbook.objects.get(pk=playbook_id)
# Get username
user = str(request.user)
# Check user permissions
if user not in playbook.permissions.users:
return playbooks(request)
... | 4b01e08414f38bdaad45245043ec30adb876e40e | 8,991 |
def _filter_gtf_df(GTF_df, col, selection, keep_columns, silent=False):
"""
Filter a GTF on a specific feature type (e.g., genes)
Parameters:
-----------
GTF_df
pandas DataFrame of a GTF
type: pd.DataFrame
col
colname on which df.loc will be performed
type: str... | 5f41141d69c0c837e396ec95127500a826013500 | 8,992 |
def validation_generator_for_dir(data_dir, model_dict):
"""Create a Keras generator suitable for validation
No data augmentation is performed.
:param data_dir: folder with subfolders for the classes and images therein
:param model_dict: dict as returned by `create_custom_model`
:returns: a generato... | 57b0a83e98438b8e397377a5626094f69ea21083 | 8,993 |
def convert_cbaois_to_kpsois(cbaois):
"""Convert coordinate-based augmentables to KeypointsOnImage instances.
Parameters
----------
cbaois : list of imgaug.augmentables.bbs.BoundingBoxesOnImage or list of imgaug.augmentables.bbs.PolygonsOnImage or list of imgaug.augmentables.bbs.LineStringsOnImage or i... | 6eee2715de3bfc76fac9bd3c246b0d2352101be1 | 8,994 |
import zipfile
import os
import io
import pickle
def gen_stream_from_zip(zip_path, file_extension='wav', label_files=None, label_names=None, utt2spk=None,
corpus_name=None, is_speech_corpus=True, is_rir=False, get_duration=False):
""" Generate speech stream from zip file and utt2spk... | 93a81a8d102c0b76593bcd44b64675c1c1e1fce7 | 8,995 |
def get_query_dsl(
query_string, global_filters=None, facets_query_size=20, default_operator='and'):
"""
returns an elasticsearch query dsl for a query string
param: query_string : an expression of the form
type: person title:foo AND description:bar
where type corresponds to an elastic sea... | 9f6c1371e0de1f28737415c0454f645748af054f | 8,996 |
def prune_visualization_dict(visualization_dict):
"""
Get rid of empty entries in visualization dict
:param visualization_dict:
:return:
"""
new_visualization_dict = {}
# when the form is left blank the entries of visualization_dict have
# COLUMN_NAME key that points to an empty list
... | fae81eb69fc25d61282eb151d931d740c51b8bae | 8,997 |
def _LocationListToGoTo( request_data, positions ):
"""Convert a LSP list of locations to a ycmd GoTo response."""
try:
if len( positions ) > 1:
return [
responses.BuildGoToResponseFromLocation(
*_PositionToLocationAndDescription( request_data, position ) )
for position in positi... | 2ee39fdadd721920a3737561979308223a64b57a | 8,998 |
def calculate_average_grades_and_deviation(course):
"""Determines the final average grade and deviation for a course."""
avg_generic_likert = []
avg_contribution_likert = []
dev_generic_likert = []
dev_contribution_likert = []
avg_generic_grade = []
avg_contribution_grade = []
dev_generi... | 95b26efedba076e0b9b54c565fe2e0787d5fbb0e | 8,999 |
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