content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def delete_partitions(rt_info, partitions):
"""
删除指定分区
:param rt_info: rt的字段和配置信息
:param partitions: 分区值集合
:return: 执行结果
"""
params = construct_connect_config(rt_info)
params[DELETE_PARTITION] = partitions
rsp = DataHubApi.iceberg_delete_partitions.create(params)
if not rsp.is_s... | 91c827f9b3e45fcc6bba3c9a17253283aefdee2c | 71,900 |
def jucesp_simple_driver():
"""
# Fazendo DEFIS
# Driver que armazena perfil e recebi caminho para download
:return: o driver.
"""
# __padrao = profile_path
# o try já tá dentro de replace
chrome_options = Options()
# chrome_options.add_argument("--headless")
chrome_options.a... | 77160587e1821b5a4db73cadf689e82f293df892 | 71,901 |
def generate_uncrypted_record(timestamp, input_template_text, key):
"""Generates formatted individual record and returns the iv and the record as a tuple.
Keyword arguments:
timestamp -- the timestamp for the record
input_template_text -- the input template text
key -- the key for the id
plaint... | 98cc6afebc732045078e2bae461e29b9016c6cf6 | 71,902 |
import os
def main():
"""Script entry point."""
stop_at = 80 * 1000 * 1000
prefix = 'simple'
# noinspection PyUnusedLocal
experiments_very_sparse = [
Experiment('doom_curious_vs_vanilla/doom_maze_very_sparse/doom_maze_very_sparse_pre_0.0', 'A2C (no curiosity)'),
Experiment('doom_s... | 6e5a3f0332ae0fe059469bc5d94a487c53ed6557 | 71,903 |
def kelvin_to_fahrenheit(kelvintemp):
"""
Converts a numeric temperature from Kelvin degrees to Fahrenheit degrees
:param kelvintemp: the Kelvin temperature
:type kelvintemp: int/long/float
:returns: the float Fahrenheit temperature
:raises: *TypeError* when bad argument types are provided
... | 20b26915c9e32a52dad04704937e685b068bd081 | 71,904 |
import requests
def _post_request(url, params, headers):
"""
Utilizes requests module to formulate
HTTP POST request over the network
:param url: String representing base URL of request
:param params: String or Dictionary containing parameters
:param headers: Dictionary containing headers
... | a429defc62199b3783b73d237ac7923dde78145a | 71,905 |
import os
def get_image_list(path):
"""
Get list of image files in given directory
:param path: path of image directory
:type path: str
:return: list of image files
:rtype: list[str]
"""
return sorted([f for f in os.listdir(path)
if os.path.splitext(f)[1] in setting.IMAGE_... | 5ee38bd2545e555fe6f6f12a3b05fbd73cc0f1a3 | 71,906 |
from typing import OrderedDict
import os
def _read_config(fname, arg):
"""Simple parser to read configuration files. """
data = OrderedDict()
sec = None
line_num = 0
with open(fname, 'r') as fhandle:
for line in fhandle:
line_num += 1
if line[0] == '[':
... | c2b4f3a5452e7f4d3a3dac55b56fbea768504751 | 71,907 |
def delete_parameter_group(name, region=None, key=None, keyid=None, profile=None):
"""
Delete an RDS parameter group.
CLI Example:
.. code-block:: bash
salt myminion boto_rds.delete_parameter_group my-param-group \
region=us-east-1
"""
try:
conn = _get_conn(reg... | 94c49786d10c2f2eee3fd5d77d040f89166f87b2 | 71,908 |
def Start():
""" Renders the Home Page """
return render_template('Start.html') | a4bb3c7f16d89afaf701a9601fe80c163d77ce6c | 71,909 |
import random
def get_fast_smallworld_graph(N, k_over_2, beta, verbose=False):
"""
Loop over all possibler short-range edges and add
each with probability :math:`p_S`.
Sample :math:`m_L` from a binomial distribution
:math:`\mathcal B(N(N-1-k)/2, p_L`. For each edge
m with :math:`0\leq m\leq m... | 8fe43e228ec3e7ab88667e14c73c5932e4cb00bd | 71,910 |
def derive_ionmode(spectrum_in: SpectrumType) -> SpectrumType:
"""Derive missing ionmode based on adduct.
Some input formates (e.g. MGF files) do not always provide a correct ionmode.
This function reads the adduct from the metadata and uses this to fill in the
correct ionmode where missing.
Param... | 12e7d98bc2b9e35df67ccccc955e545c96f9b597 | 71,911 |
def channel_type(info, idx):
"""Get channel type
Parameters
----------
info : dict
Measurement info
idx : int
Index of channel
Returns
-------
type : 'grad' | 'mag' | 'eeg' | 'stim' | 'eog' | 'emg' | 'ecg'
Type of channel
"""
kind = info['chs'][idx]['ki... | 37cd3ee91e09d0c183c472ca81c8e0e703268a4c | 71,912 |
from re import T
def init_weights__(l):
"""
source: https://github.com/Xingyu-Lin/mbpo_pytorch/blob/main/model.py#L64
"""
def truncated_normal_(w, mean=0.0, std=1.0):
nn.init.normal_(w, mean=mean, std=std)
while True:
i = T.logical_or(w < mean - 2*std, w > mean + 2*std)
... | b3a452150010343609a73a2bd254789355adb77a | 71,913 |
def calc_box(box,x_gap,y_gap,rotate_angle,center):
"""
calculate the size of the required surrounding environment for doorway segmentation
box: four corners' coordinates of doorway
x_gap: remained space in the vertical way
y_gap: remained space in the horizontal way
"""
door_box = np.array([... | 2265f83dd70f9a1ae08843dc66dc0b5a8df557a6 | 71,914 |
def get_dummy_img_point(contour, principal_point=None, offset=-7):
"""
Return an estimated position of the dummy from
its contour if principal point is provided.
"""
M = cv.moments(contour)
centroid = np.array([
M['m10']/M['m00'],
M['m01']/M['m00']
])
if principal_poi... | 91bcfd4a8e7d8d658c344545228700a1c872ce1f | 71,915 |
import os
def docker_compose_files(in_docker_compose, pytestconfig):
"""
This fixture provides support for `cloudbuild`.
By passing the command line argument `--in-docker-compose=cloudbuild`,
uses `docker-compose.cloudbuild.yml`.
"""
dc_type = f".{in_docker_compose}" if in_docker_compose else ... | 22aec9c7953955febc6ea52c5fec450b36a1d144 | 71,916 |
from typing import Callable
from typing import Tuple
def compute_pairwise_distances(
charge: int, n_spectra: int, mz_splits: np.ndarray,
process_spectrum: Callable, vectorize: Callable,
precursor_tol_mass: float, precursor_tol_mode: str, n_neighbors: int,
n_neighbors_ann: int, batch_si... | d6923d6e898f13ca91b432f811026abb8525ae5b | 71,917 |
def jensen_shannon(vec1, vec2, num_features=None):
"""Calculate Jensen-Shannon distance between two probability distributions using `scipy.stats.entropy`.
Parameters
----------
vec1 : {scipy.sparse, numpy.ndarray, list of (int, float)}
Distribution vector.
vec2 : {scipy.sparse, numpy.ndarra... | 721c1ca1218ca5aa201af1d4e8d131424cd5d8bf | 71,918 |
from joblib import load as joblib_load
def load_extractor(extractor: str) -> BaseEstimator:
"""loads a custom feature extractor"""
return joblib_load(f"msvc/src/features/feature_extractors/{extractor}.joblib") | 1e20fad04b38eadb6874c38aca940a5fa255de99 | 71,919 |
def conv2d(x, W,strides=[1, 1, 1, 1],dilations=[1,1,1,1],padding='SAME'):
"""conv2d returns a 2d convolution layer with full stride."""
return tf.nn.conv2d(x, W, strides=strides,padding=padding) | f0919e14c948185d390eaa152a3bdce27e9f53ba | 71,920 |
def infer_keypoint_left_right_type(left_right_types, indices):
"""Infers keypoint left/right type.
The inferred left/right type is decided as follows:
1. If either type is UNKNOWN, returns UNKNOWN.
2. If both types are the same, returns this type.
3. If one type is CENTRAL, and the other type is LEFT or RIGH... | d0895036a088c20bbe4f88fb3af098a03922dcca | 71,921 |
def get_length(vector):
""" calculate the lengt of a 3d vector
@type vector: tuple(float) | list(float)
@value vector: the given 3d vector
@rtype: float
@return: the length of a vector is the square root of the dot product
of the vector with itself
"""
return sqrt(get_dot_product(ve... | be3d779e9cdd8164ac4808d155702615e98d0704 | 71,922 |
from typing import Mapping
def normalize_and_encode(
charset: Mapping[str, bytes], value: str, field_name=None
) -> bytes:
"""
unicode normalize value and translate it into the datanorm charset
:param charset: A mapping from string to bytes
:param value: A unicode string to be translated.
:pa... | a42af498157c0df5f52e4927a5ed98b02f2e192b | 71,923 |
from typing import Optional
def sqlupload_start(
request: HttpRequest,
pk: int,
workflow: Optional[Workflow] = None,
) -> HttpResponse:
"""Load a data frame using a SQL connection.
The four step process will populate the following dictionary with name
upload_data (divided by steps in which th... | 6713e6bd486fe0369e57ea0942e41ffdb3ed6b3e | 71,924 |
def evaluate_hist_x_multi_y(x, row, bins, vals):
"""
Evaluate a set of values from histograms
Parameters
----------
x : array_like (n)
X values to interpolate at
row : array_like (n)
Which rows to interpolate at
bins : array_like (N)
X-values used for the interpolati... | 93e9623e2a8eb5f106efbd0054c26dc4f2079314 | 71,925 |
def bg_trim(im):
"""
Function to programmatically crop card to edge.
`im` is a PIL Image Object.
"""
# This initial crop is hacky and stupid (should just be able to set device
# options) but scanner isn't 'hearing' those settings.
# w,h = im.size
im = im.crop((443, 0, 1242, 1200))
# ... | b5b59059aa9823cd2be385ead5cc21b135a4e24b | 71,926 |
import torch
def datasets_fn(num_features: int):
"""
Docs.
"""
X = torch.rand(int(1e4), num_features)
y = torch.rand(X.shape[0])
dataset = TensorDataset(X, y)
return {"train": dataset, "valid": dataset} | 0b812c29928f62a7e9d431376138f337572e6af9 | 71,927 |
def handle_tags(text, keeptags, tags, filetype, previewing=False):
"""
Handles tags that are found in the text. Useless tags (header tags) are deleted and
depending on the specifications chosen by the user, words between meaninful tags (corr, foreign)
are either kept or deleted.
Args:
text:... | 00ecd330ae86aee576301a8cb8c90e199f54a021 | 71,928 |
import csv
def lastMonthsRetun(fileName):
"""Function taking the formatter data array and then converting it to dataFrame, with aim to find returns data we are interested in
Args:
fileName (String): File we want to have the data from
Returns:
Float : Returns sum devided by 5
"""
... | a24d5ce7704a4751f93c4b6404a42d772360d80f | 71,929 |
import importlib
import pkgutil
def get_indexes(package_name):
"""
Gets a sorted list of migrations in a package
"""
package = importlib.import_module(package_name)
indexes = []
for (loader, name, ispkg) in pkgutil.iter_modules(package.__path__):
try:
insort(indexes, int(na... | d820c910add680a625a483b20a6c21aded630aba | 71,930 |
def get_filtered_query(must_list=None, must_not_list=None):
"""Get the correct query string for a boolean filter. Accept must and
must_not lists. Use MatchList for generating the appropriate lists.
"""
bool_filter = {}
if must_list:
bool_filter['must'] = must_list
if must_not_list:
... | 2190456ad7e91239bb623f7ec3d2c460e521e36f | 71,931 |
def _mask_tissue(image, kernel_size=(7, 7), gray_threshold=220):
"""Masks tissue in image. Uses gray-scaled image, as well as
dilation kernels and 'gap filling'
"""
# Define elliptic kernel
kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, kernel_size)
# Convert rgb to gray scale for easier ... | 7f901a0625efd0e7e7fa7cd3ebcf8c77e362b761 | 71,932 |
def stack2designs(old_X, new_X, old_contrasts={}, new_contrasts={}):
"""
Add some columns to a design matrix that has contrasts matrices
already specified, adding some possibly new contrasts as well.
This basically performs an np.hstack of old_X, new_X
and makes sure the contrast matrices are dealt... | 55a11a02c09bdbbd685a0e7e88f665945e28621f | 71,933 |
import os
import shutil
def prepare_ta_directory_tree(src, dest, logger, envs):
"""
If dest doesn't exist, then generate a new TA directory tree.
If dest exists, then merge with the new one
"""
output_dir = dest
if not output_dir:
# if not output, then all content will be print to scr... | 860f44797b59caf2a2c1c838877ffd6c13353f16 | 71,934 |
def duplicate_event_files(event):
"""Get list of event files that have equivalent deferred events.
:param event: Event to compare
:type event: ServiceEvent
:returns: List of event files
:rtype: List[str]
"""
duplicates = []
for event_file, existing_event in deferred_events():
if... | 76d59e96d71da34d7a596f99ac170adbafecb83e | 71,935 |
def cluster_input(prosumer, emissions, load, PV, k, hours):
""" Clustering of hourly input data into representative time periods using
k-means clustering algorithm
Keyword arguments:
prosumer ... list of prosumer names
emissions ... marginal emissions (pandas.DataFrame(index=time_steps... | 32cf73f7175a140fbc08ce800deb66a028c377ef | 71,936 |
def handle_array_input(args):
"""
Format any command argument that is supposed to be an array from a string to a list.
parameter: (dict) args
The command arguments dictionary
returns:
The arguments dict with field values transformed from strings to lists where necessary
"""
arr... | f072412936e16425d1217423c01689d8c32e3f2e | 71,937 |
def parse_source(source):
"""Parse a source in the format <region>:<db-identifier>
Args:
source (str): The source string
Returns:
:class:`Source`: A Source namedtuple.
"""
try:
region, _id = source.split(":", 1)
except ValueError:
raise ValueError(
"... | a799392e353dedc6e34d2242143ae3212923cae0 | 71,938 |
def mat_load(path, m_dict=None):
"""
Load mat files.
:param path:
:return:
"""
if m_dict is None:
data = sio.loadmat(path)
else:
data = sio.loadmat(path, m_dict)
return data | ebab6c377c0d7d2fc544d5f94b4f002021454677 | 71,939 |
def internal_redirect(url, default_path):
"""
Redirect to the specified URL after checking that
host is in the allowed hosts list
:param url: URL to redirect to
:param default_path: Default path to redirect to if url is unsafe
"""
if not is_safe_url(url, settings.ALLOWED_HOSTS):
retu... | 5ee3e46e46ed9a28e46ae3e741a9ffa255ec3a7d | 71,940 |
def convert_to_letter(grade):
"""Convert a decimal number to letter grade"""
grade = round(grade, 1)
if grade >= 82.5:
return 'A'
elif grade >= 65:
return 'B'
elif grade >= 55:
return 'C'
elif grade >= 50:
return 'D'
else:
return 'F' | 13ce25275750e7a27e0699078a15ba551674a941 | 71,941 |
import numpy
def _reorient_4d(image):
"""
Reorganize the data for a 4d nifti
"""
# print 'converting 4d image'
# Create empty array where x,y,z correspond to LR (sagittal), PA (coronal), IS (axial) directions and the size
# of the array in each direction is the same with the corresponding dire... | 9159e75daef5bc65dab9a7d8c6ff0cfa35fae96c | 71,942 |
def mask_sequence(aln, rstart, rend):
"""Masks quality according to changed softclips in cigarstring
Args:
aln (pysam.AlignedSegment): aligned read
rstart (int): start of non-primer sequence
rend (int): end of non-primer sequence
Returns:
aln (pysam.AlignedSegment): aligned... | ba351335136411e4c0dd1c55a800c9990fe3f217 | 71,943 |
import base64
def get_encid(decid):
"""
Generate an encrypted ID from a decrypted ID
:param decid: Decrypted ID, type int
:return: Encrypted ID, type str
"""
try:
int(decid)
except:
raise InvalidIDException('Decrypted ID must be int-castable')
# Slashes are not URL-fr... | 9fd425bc8f09ade997b12d533386ef2be7c6eaa8 | 71,944 |
import os
import matplotlib
import matplotlib.cm as cm
from mpl_toolkits.axes_grid1 import ImageGrid
from mpl_toolkits.axes_grid import ImageGrid
import matplotlib.pyplot as plt
import nibabel as nb
import numpy as np
from CPAC.qc.utils import determine_start_and_end, get_spacing
def make_montage_axial(overlay, under... | 8d4d4d53cbda192df8691fb95df87c0013b57aea | 71,945 |
def time_coord(cube):
"""
Return the variable attached to time axis.
Examples
--------
>>> import iris
>>> url = ('http://omgsrv1.meas.ncsu.edu:8080/thredds/dodsC/'
... 'fmrc/us_east/US_East_Forecast_Model_Run_Collection_best.ncd')
>>> cube = iris.load_cube(url, 'sea_water_potent... | 12a706f956846e8471d0d7f044367c77210c4486 | 71,946 |
def filter_lowpass(trace: Trace, sampling_frequency: int, cutoff: int) -> Trace:
"""
Apply a lowpass digital filter (Butterworth) to `trace`, given `sampling_frequency` and `cutoff` frequency.
:param trace:
:param sampling_frequency:
:param cutoff:
:return:
"""
return _filter_any(trace,... | 47dc83a5a53f97af562eba45289b9bf52bcfbc9b | 71,947 |
import multiprocessing
def _valid_general_args(cfg, logger):
"""
Validates the "general" parameters of a json configuration file used for inference.
:param cfg: EasyDict, json configuration file imported as dictionary
:param logger: logger instance
:return: EasyDict, dictionary compos... | 0f78e2b905a15289730ed4252d3c7e6568d1b5fb | 71,948 |
import re
def oneliner(s) -> str:
"""Collapse any whitespace in stringified `s` into a single space. """
return re.sub(r"[\n ]+", " ", str(s).strip()) | ed1d419b4fab8cb2deccdbc2944996ef7be28cc5 | 71,949 |
def _get_nominal_integer_dict(nominal_vals):
"""Convert nominal values in integers, starting at 0.
Parameters:
nominal_vals (pd.Series): A series.
Returns:
d (dict): An dictionary with numeric values.
"""
d = {}
for val in nominal_vals:
if val not in d:
curre... | 1005c00ea5d7033368b589d4954934e85b0e1d6e | 71,950 |
import cgi
def xml_escape(input):
"""Replace special characters "&", "<" and ">" to
HTML-safe sequences.
"""
return cgi.escape(input) | 87f60cdf680372761da23e64c2880ad649d5b0a6 | 71,951 |
from typing import Counter
def diff_counts(values : list[int]) -> dict[int, int]:
"""Count the gaps between ordered elements in a list, by size."""
ordered = [0] + sorted(values) + [max(values) + 3]
return Counter(j - i for i, j in zip(ordered, ordered[1:])) | 897cb7fdfed85b37bd8bd7031290e34199c57574 | 71,952 |
def plot_visibility(snnames, obs_windows, dark_time, priorities=None, labeltype='index', figsize=None):
"""Function for plotting visibility of targets as previously determined in
ztfcosmology_visibility.ipynb
"""
if priorities is None:
priorities = np.zeros(len(snnames), dtype=int)
... | 2f396fb45cc3c9526cb74e5824aca5acbce10c07 | 71,953 |
import re
def find_autoxc_code_skeleton(lines,subr_lines):
"""
Assuming that the subroutine is of the autoxc code skeleton type find all
the if-branches and return a list of all the (start,end) tuples.
"""
(lineno_start,lineno_end) = subr_lines
ifbranches = []
line = lineno_start
ifstart = -1
... | 122e5e082929451019d1689eed9f182085593daa | 71,954 |
def get_one_prior_probability(state, segment_df, total_positions):
"""
Returns the number of genomics positions that are of the state
"""
state_df = segment_df[segment_df[3] == state]
num_pos_this_state = float(sum(state_df['num_occ']))
return num_pos_this_state / float(total_positions) | 157666f84d9ba6b7d236bb0f10e331e9315d9efa | 71,955 |
def ticket_details():
"""
Upon request, generate a TicketDetails object for the user's session if it does not
exist, fetch the details of the requested ticket as well as its associated users by
the given ticket URL using the TicketDetails get_ticket() method. Render the pop-up
modal HTML with the ti... | 2276f2a5b9d57667433c75bec35d1320c6a7cca9 | 71,956 |
from typing import Callable
def stochastic_policy(
fun: Callable[[FloatLike], FloatLike],
fun_params0: randvars.RandomVariable,
rng: np.random.Generator,
) -> float:
"""Policy returning a random action.
Parameters
----------
fun :
One-dimensional objective function.
fun_params... | 57524f09045a21b47eafe553b869e5ad98838a29 | 71,957 |
def load_whoop_data(sleep_file) -> pd.DataFrame:
"""
Load a Whoop daily summary CSV file and return a pandas DataFrame version of the file.
Only read in a subset of columns defined by the expected_cols parameter.
Args:
sleep_file: file to be converted to a DataFrame.
Returns: pandas DataFra... | 3e124434c0694c611753136abcee399c93acc94b | 71,958 |
import torch
def conv1x1(in_planes, out_planes, stride=1, num_experts=1, binary=False,
activation=torch.sigmoid, use_se=False):
"""1x1 convolution"""
if num_experts > 1:
return EBConv2d(in_planes, out_planes, kernel_size=1, stride=stride,
bias=False, num_experts=num... | 8461c4e8be1438aeaf383b0804e4aebfa9720298 | 71,959 |
def get_welcome_response():
""" If we wanted to initialize the session to have some attributes we could
add those here
"""
session_attributes = {}
card_title = "Welcome"
speech_output = "Welcome to the UCSC Bus Bot. " \
"Please state the bus stop id or location to get starte... | deed05421cf8d19b88f1c1703f3bab15cf6354a2 | 71,960 |
def parse_request_query(request) -> QueryModel:
"""
Like atoolbox.utils.parse_request_query but simplified and with a more human readable error response.
"""
data = {}
for k in QueryModel.__fields__.keys():
v = request.query.get(k)
if v is not None:
data[k] = v
try:
... | 62c59422610d6080d97a465b159e881746abcbec | 71,961 |
def convert_netdict_to_pydict(dict_in):
"""Convert a net dictionary to a Python dictionary.
Parameters
----------
dict_in : dict
Net dictionary to convert.
Returns
-------
dict
Dictionary converted to Python.
"""
pydict = {}
for key in dict_in.Keys:
pyd... | 6aa9bb5ac00ff92d23ff5a449d096caad0d01c9c | 71,962 |
def sigmoid (x, parameters):
"""Sigmoid function
POI = A2 + (A1 - A2) / (1. + exp((x - x0) / dx))
Parameters
----------
x: float or array of floats
variable
parameters: dict
dictionary containing 'sigmoid_A1','sigmoid_A2','sigmoid_x0',
and 'sigmoid_dx'
R... | bcf77e2e508800f6c4c37ec4c8c79c4bda2a6934 | 71,963 |
def heatmap_chart(df, title=""):
"""Plot custom confusion matrix chart."""
source = df.copy()
source = source.reset_index()
source = pd.melt(source, id_vars="index", value_vars=df.columns)
source.columns = ["m1", "m2", "value"]
base = alt.Chart(source).encode(
alt.X('m1:O', title="New M... | 6e6405afcbffff7159446c96ad1c87757708ac09 | 71,964 |
def server(request):
"""Return the server based upon the server class in the request."""
if 'production' == request.param:
return ReviewBoardServer('https', 'reviews.reviewboard.org')
if 'demonstration' == request.param:
return DemonstrationServer()
raise ValueError("invalid internal tes... | d4a485706258a032e6a069ce9cdad4671f13c141 | 71,965 |
def poolformer_s24(pretrained=False, **kwargs):
""" PoolFormer-S24 model, Params: 21M """
model = _create_poolformer('poolformer_s24', pretrained=pretrained, layers=(4, 4, 12, 4), **kwargs)
return model | 84f255eff21b158e4826830e74e3cb8dcdfe4ae0 | 71,966 |
def laptop_history(request, id):
"""
View a history of password retrievals and rotations for a given laptop
:param id: Primary key of laptop
"""
laptop = get_object_or_404(Laptop, retired=False, pk=id)
password_retrievals = laptop.password_retrievals.all()
password_rotations = laptop.passwo... | 20908500aa5946e3e4dce7004ef57ae15efae753 | 71,967 |
import logging
def make_restore_checkpoint_fn(checkpoint_path, prefix='', skip_regex=None):
"""Returns scaffold function to restore parameters from v1 checkpoint.
Args:
checkpoint_path: path of the checkpoint folder or file.
Example 1: '/path/to/model_dir/'
Example 2: '/path/to/model.ckpt-22500'
... | 3af8013b460cd9e7f3ef0396c144723600943a73 | 71,968 |
from typing import List
def binary_search(input_array: List[int], target: int):
"""
Given a sorted input array of integers, the function looks for a target or returns None
Returns:
Target index or None
"""
if not input_array or not target:
return None
left_pointer = 0
ri... | b9f389d1b31e5b95bb885bd638549f7775db207e | 71,969 |
from datetime import datetime
def _sort_by_date(time_coord):
"""
Private sorting function used by _file
_sort_by_earliest_date() and sort_by_earl
iest_date().
Args:
time_coord: Cube time coordinate for each cube
to be sorted by.
Returns:
time_origin: The time origin t... | 89c52c40dd8dfa03cbe431a4db6f107b42b22e81 | 71,970 |
def preprocess_img(img):
"""
Preprocesses screenshot of AH for OCR.
Removes details which would be needed for image matching.
"""
# grayscale
newimg = get_grayscale(img)
#cv2.imwrite("screenshots/img_9g.png",newimg)
# crop
newimg = newimg[175:660, 0:1920]
# cv2.imwrite("screensh... | ff3348580e84e2d01069c25b46c327dd98177817 | 71,971 |
from typing import Callable
import functools
def aws_provider(api: str = None, name="default", should_load: Callable[[], bool] = None):
"""
Decorator for marking methods that create a Service instance as a ServicePlugin. Methods marked with this
decorator are discoverable as a PluginSpec within the namesp... | 8db109647f82fbf2fe44ccd1f4140e704f1247b6 | 71,972 |
import galsim
def rotate(image, rot_center, interpolate=False, force_interpolate=False):
""" Rotate an image about a point. Defaults to using numpy array operations, which means that
the rotation center is rounded to the nearest half-pixel grid point. Optionally, use GalSim to
rotate about arbitrary pos... | 86bc0e6a651ac997cd044daac07597cc5896c066 | 71,973 |
def _parse_labels_map(labels_path):
"""Loads a labels map via the `label_map_util` from the TF-Models library.
Args:
labels_path: path to a labels map in `.pbtxt` format
Returns:
(category_index, class_labels), where `category_index` is a dict
mapping IDs to names, and `class_l... | d737831d57f27c983ff54bb7154c26136f3f6a24 | 71,974 |
def is_superuser(view):
"""Allow access to the view if the requesting user is a superuser."""
return view.request.user.is_superuser | 5a15433200634ca326c36bdc17acbc1ada4e6426 | 71,975 |
import os
def read_mat(name):
"""
read .mat file
:param name: dataset name
:return: a dict containing adjacency matrix, nx.Graph() and its node labels
"""
result = dict()
PATH = os.path.join('data', '{}.mat'.format(name))
matfile = sio.loadmat(PATH)
result['adjacency'] = matfile['n... | f173c275ca652a85fe2c5f2a7cea24406571ce97 | 71,976 |
def _restrict_asap(func=None, backend=None, issuers=None,
required=True, subject_should_match_issuer=None):
"""Decorator to allow endpoint-specific ASAP authorization, assuming ASAP
authentication has already occurred.
"""
def restrict_asap_decorator(func):
@wraps(func)
... | 6e9496d41a5aab3c0e3aef0662c8eb3e91019a2f | 71,977 |
import os
def meta(file_dir, file_name=None, deep=1):
"""
返回文件的基本信息
:param file_dir: 路径
:param file_name: 文件名称
:param deep: 深度
:return:文件信息
"""
return {
'dir': file_dir,
'name': file_name,
'path': file_dir if file_name is None else os.path.join(file_dir, file_na... | d68002a864e255151fe5176bfa20c01a2f554c78 | 71,978 |
def tag_row(tag):
"""Format a tag table row"""
return [tag.get('id'), tag.get('name'), tag.get('referenceCount', 0)] | 4cd1d0991eae996a52288c6d1d9bb3bd1a368ea6 | 71,979 |
import types
import numpy
import pandas
def hpat_pandas_series_sort_values(self, axis=0, ascending=True, inplace=False, kind='quicksort', na_position='last'):
"""
Intel Scalable Dataframe Compiler User Guide
********************************************
Pandas API: pandas.Series.sort_values
Limit... | 31b0f49f2a8e75b0cec27a33b5969893924c96e7 | 71,980 |
def get_owner_apikey_id():
"""
Get owner api key id from the config file.
"""
config_key = 'owner_api_key_id'
try:
owner_apikey_id = CONFIG.get(AUTH_SECTION, config_key)
if not validators.uuid(owner_apikey_id):
print_config_error_and_exit(AUTH_SECTION, 'Owner API key ID(... | 9c7cac14a60b38788ef49d2103e6dd331673ef1b | 71,981 |
import math
import time
def parse_cookies(target_cookie):
"""Deserializes single Target cookie into several individual cookies"""
if not target_cookie:
return {}
raw_internal_cookies = get_internal_cookies(target_cookie)
now_in_seconds = math.ceil(time.time())
valid_cookies = [deserialize... | 33591141624a06bf37f1bc879521b5ac45e8692e | 71,982 |
from typing import Any
def get_state_from_observation(observation: Any) -> State:
"""
Function which given an observation returns a state
:param observation:
:return:
"""
return State(
robots_data=list(observation[:len(observation) // 2]),
time=observation[len(observation) // ... | 95e33e884df25a6c4f00ee91dd764d886eafe05e | 71,983 |
from typing import Iterable
import ctypes
def vaddg(v1: Iterable[float], v2: Iterable[float], ndim: int) -> ndarray:
""" Add two n-dimensional vectors
https://naif.jpl.nasa.gov/pub/naif/toolkit_docs/C/cspice/vaddg_c.html
:param v1: First vector to be added.
:param v2: Second vector to be added.
:... | d87c7171e0296587d02d66e04522ff3f1c5d02e7 | 71,984 |
from typing import Any
import torch
import numbers
def python_scalar_to_tensor(data: Any, device: torch.device = torch.device("cpu")) -> Any:
""" Converts a Python scalar number to a torch tensor and places it on the given device. """
if isinstance(data, numbers.Number):
data = torch.tensor([data], de... | 83e4ac093a40225f9c5fe121d9b67424f258e039 | 71,985 |
def allpath(path):
"""
return paths
"""
paths = path.strip("/").split("/")
for i in range(1,len(paths)):
paths[i] = paths[i-1] + "/" + paths[i]
return paths | 8b76f70dbae41a1ae46462d0755dbb5c5c0eb4c1 | 71,986 |
def setup(hass, config):
"""Set up the NZBGet sensors."""
host = config[DOMAIN][CONF_HOST]
port = config[DOMAIN][CONF_PORT]
ssl = "s" if config[DOMAIN][CONF_SSL] else ""
name = config[DOMAIN][CONF_NAME]
username = config[DOMAIN].get(CONF_USERNAME)
password = config[DOMAIN].get(CONF_PASSWORD... | 9a1d9867ff95e724a84a3e5a9843a3a9c216f5a8 | 71,987 |
def globus_callback_authorize(request):
"""
TODO: This logic 'lets the auth token escape'
May need to refactor this...
"""
code = request.GET.get('code')
user_token = globus_validate_code(request)
if not user_token:
# Redirect out of the OAuth loop
return HttpResponseRedirect... | 17fdce6c846d2771d0d0b69aa44d7e1aa0eb1a74 | 71,988 |
def zoom(input, zoom, mode="nearest", blocks=(16, 16, 4), **kwargs):
"""scale array with nearest neighbors or linear interpolation
If a float, `zoom` is the same for each axis. If a sequence,
`zoom` should contain one value for each axis.
"""
if isinstance(zoom, (int, float)):
zoom = tuple(... | 299689876f03776d121f9d36256ba90adf6f404c | 71,989 |
def calculate_null_kl(experimental_condition_list=None, filename=None):
"""
Calculates the smoothed null KL distribution. One of the two parameters must be non-null
:param experimental_condition_list: [list] The list of treatment condition from which the null kl is to be calculated.
:param filename: If ... | 55ff2d73827e2a5b0140a0460ea9a4e1a9c97efe | 71,990 |
def read_tsv(file_path):
"""
General method for converting a tsv into a dictionary of lists, assuming each key has an associated time series
:param file_path:
:return:
"""
headers = None
header_indexes = None
# Each data type will have a list
data = defaultdict(list)
static_data... | 28f2c53c9302269fc3d3e9d34867e6845fa3c13d | 71,991 |
def validate_actions(data):
"""
Validate an Action configuration dictionary, as imported from actions.yml,
for example.
The method returns a validated and sanitized configuration dictionary.
:arg data: The configuration dictionary
:rtype: dict
"""
# data is the ENTIRE schema...
cle... | 9e027ccf74d9ec2c610e237fd0b9dca9f7ac9e8b | 71,992 |
def LIGHTNING(conf):
"""Get Lightning Color code from config"""
return conf.get_color("colors", "color_lghtn") | 08781e469c7262228904e883594e475be634816b | 71,993 |
from re import A
def ecef2lla(xyz):
# TODO
# [ ] make it vectorizable ?
"""
Function: ecef2lla(xyz)
---------------------
Converts ECEF X, Y, Z coordinates to WGS-84 latitude, longitude, altitude
Inputs:
-------
xyz : 1x3 vector containing [X, Y, Z] coordinate
O... | 1b9c004c0fd0d3ffa1075e710be955c18fb33d69 | 71,994 |
from django.contrib.auth.models import User
import os
import sys
def _get_user_workspace(app_class, user_or_request):
"""
Get the file workspace (directory) for the given User.
Args:
app_class(TethysApp): tethys app
user_or_request(User or HttpRequest): User or request object.
Returns:
... | 1d70f36c11a606afb148aa4d53684f5fb7142c24 | 71,995 |
def process_ordinal(X):
"""ordinal numeric value preprocessing."""
# missing value imputation
X = median_impute(X, strategy='median')
# remove any low info columns (high variance)
X = remove_low_info(X)
# remove low variance variables
X = remove_low_variance(X)
# scaling
X = scale... | 9e144dc6e1e2e145feda80a94ac493acdf44522a | 71,996 |
def devname_from_index(if_index):
"""Return Windows adapter name for given Windows interface index"""
return ifaces.devname_from_index(if_index) | 69b5ef2a33451ca755a8388fad5de3fcac0e60d2 | 71,997 |
import io
import locale
def purchase_order_pdf(request, pk):
""" Función para imprimir la orden de ventas
"""
response = HttpResponse(content_type='application/pdf')
pdf_name = _("purchase_order.pdf")
response['Content-Disposition'] = 'attachment; filename=%s' % pdf_name
# Los productos de la... | 6d5be05cfbc32aecb904c724fa406371e822e5c2 | 71,998 |
def chrxor(st1, st2, strf1, ar1, strf2, ar2, fun1, fun2):
"""Takes two strings and applies a function to each charater in the string.
Function is some function that takes characters and turns them into integers.
This could be something to turn them into ascii order, or simply map them to another range of integers.... | d463e21e55bf41ce9dee612d77810c2000210477 | 71,999 |
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