content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def zero_pad(number, padding=_DEFAULT_PADDING):
"""Converts an int into a zero padded string.
Args:
number(int): The number to convert.
padding(int): The number of chars in the output. Note that if you pass for
example number=23456 and padding=4, the output will still be '23456',
i.e. it will n... | 7045756f51c2dd66c690ea4b92081e52b6c9373b | 3,601,846 |
def header_categories(_request=None):
"""
Required for header category navigation.
"""
categories = Category.objects.all()
return {"nav_categories": list(categories)} | 9276260af126e664b174d89b8cb74fcb7d823447 | 3,601,847 |
import json
def get_all_cards():
"""
Return all cards
"""
cards = [item for item in card_collection.values()]
response = json.loads(models.CardResponse(cards=cards).json())
return JSONResponse(content=response) | 2ab4f75b70a0344b67dbce7561cf2a73489fa6d6 | 3,601,848 |
from typing import List
def contest_from(description: ContestDescription) -> PlaintextBallotContest:
"""
Construct a `BallotContest` from a specific `ContestDescription` with all false fields.
This function is useful for filling contests and selections when a voter undervotes a ballot.
:param descrip... | d42388debe7c0cb6f3025bdf1903bc2b18942767 | 3,601,849 |
def ranking_ativo_func(pa_long_ativo):
"""
o ranking_ativo retorna o ranking de price action dos ativos
Parameters
----------
pa_long_ativo : dataframe
dataframe do price action por ativo
Returns
-------
Retorna o ranking de retorno classificado por ativo com as seguintes colun... | 89c87c7452461875fb75e5ba4948259a586e20f2 | 3,601,850 |
def createURIString(valueString, delimiter, vocab):
"""This function takes a delimiter separted string of values and returns a string
in which every of these values is prefixed with the specified vocab URI.
>>> createURIString('nl;fr;de', ';', 'http://id.loc.gov/vocabulary/languages/')
'http://id.loc.gov/vo... | 6fb6898b1531b5741dd890452c9ddd9e4db6f205 | 3,601,851 |
def illustrate_shuffle():
"""
Illustrate how shuffling in time changes the autocorrelation
"""
# Generate some data
np.random.seed(2)
details = sim_exp.behav_details['landau']
t = sim_behav.time_vector(details['fs'],
details['t_start'],
... | 56a4c0771a043381da59d33d53d98875b2333200 | 3,601,852 |
import requests
from bs4 import BeautifulSoup
def get_page(url, **kwargs):
"""Pulls in the HTML from a URL and returns the results as a BeautifulSoupt object.
Parameters
----------
url : str
The URL to scrape
Returns
-------
soup : bs4.BeautifulSoup
The BeautifulSoup rep... | 392c83be8b24bdeb27cf482c9df72c30b4b945dc | 3,601,853 |
def yn_ask(msg):
"""Ask for a [y/n] user response
returns the response
"""
resp=ask(msg)
while not (resp=='y' or resp=='n'):
pmsg="Please respond with a 'y' or 'n':"
resp=ask(pmsg)
if resp=='y':
resp=True
else:
resp=False
return resp | 82a8b7cb70fdbee4b6fdd75d8e781c8714db98fe | 3,601,854 |
def simple_is_valid(position, velocity, acceleration, jerk):
"""
Checks values against constant bounds.
"""
p_end = 10.0
v_max = 10.0
a_max = 10.0
j_max = 10.0
if position < 0.0 or position > p_end + traj.discrete_time_parameterization.POSITION_THRESHOLD:
return False
if velo... | 19ad21a0d7df1bb04373d86633c3a4afe0a3ee82 | 3,601,855 |
def get_counter(given_name):
"""
Assuming the given name adheres to the naming convention of crab this
will extract the counter element of the name.
:param given_name: Name to extract from
:type given_name: str or pm.nt.DependNode
:return: int
"""
parts = given_name.split('_')
for... | 15cba70e0ab2c258af565026b6e04385981d74dc | 3,601,856 |
def _get_default_attributes_dict(name, **kwargs):
"""
@param kwargs any initial item values can be passed in this
argument
@return dictionary with default properties of any attribute
of CIM class, instance or instance name
"""
if not isinstance(name, basestring):
raise TypeError("nam... | 9ebe6e782235ac0f988714fb37c9d6418d3d45e9 | 3,601,858 |
def change_cm(request, cm_id, success_url='mai_main'):
"""
View changing used CM.
"""
request.session['user'].cm_id = int(cm_id)
request.session.modified = True
messages.success(request, _('Cluster Manager changed.'))
return redirect(request.META['HTTP_REFERER'] or success_url) | 807d041a131d33e7cf36df655e842baa76f11157 | 3,601,860 |
import six
from datetime import datetime
def obj_to_dict(obj, *filter_fields, **kwargs):
"""
filter_fields: 指定输出字段(默认输出所有)
示例: obj_to_dict(obj, 'field1', 'field2', filter_fields=['field3', 'field4'])
exclude_fields: 指定不要输出字段
limit_deep: 限制递归深度, 默认5层. 设为0则不限制递归深度(不建议设为0!)
p... | 08b732094cc2408bed317400af2163beed774eb0 | 3,601,861 |
def envelope_flattop_cos(t, t_pulse, t_rise, t_start=0,
normalize=True, **not_needed_kwargs):
"""
Envelope for a flattopped pulse with cosine-shaped edges.
Parameters
----------
t : float
Time at which the value of the envelope is to be returned.
t_pulse : float... | ae1cad59edb6d10c6ee194424e7d706c1f475f5a | 3,601,862 |
def parse_float(string:str) -> float:
"""
A function to parse string characters into float
-> string: str => a string of chars, ex : "abc12a.a3"
----
=> float: numbers present inside the string passed in, ex : 12.3
"""
if not isinstance(string, str):
raise TypeError('string must be ... | 305c945979d4eb880d53207a9a1466f46cb7d981 | 3,601,863 |
def check_for_string_unmapped_values(string):
"""
:type string: str
:rtype: str
"""
unmapped_values = ""
for s in string:
if s not in known_values:
unmapped_values += s
return unmapped_values | 61925733563ed96dbb0c23bf7b18d53074a94ac6 | 3,601,864 |
def invert_dict(dct):
"""Inverts a dictionary from A -> B into one from B -> [A]"""
ret = defaultdict(list)
for k, v in dct.items():
ret[v].append(k)
return ret | 9b69709aa7c518b85ededae24877376825838169 | 3,601,865 |
from typing import List
from typing import Dict
def createWordsLines(wordsTable: List, col_lengths: List[int], border: Dict[str, str], centered: bool, extra_spaces: int = 2) -> str:
""" Creates the part of table with the words as a multiline string.
Args:
wordsTable (List): The list of the words of t... | ec903ede975f832ed599ec9278465ab2ba8336fd | 3,601,866 |
from pathlib import Path
import json
def read_jupyter_as_json(filepath: Path) -> Path:
"""
Read in rendered notebook-- read in the JSON representation that is 'under
the hood'
:param filepath: path to jupyter notebook.
"""
with open(filepath, "r") as fout:
contents = fout.read()
... | d91344b1bddcd0e1078effe6dd7947f7e04ea6af | 3,601,867 |
from typing import Dict
def node_to_bel(node: Dict, graph, hgnc_manager: HgncManager, chebi_manager: ChebiManager, species) -> BaseEntity:
"""Convert node dictionary to BEL node object."""
node_types = node['entity_type']
identifier, name, namespace = get_valid_node_parameters(node, hgnc_manager, chebi_m... | 70ea7751b94b14f9e3fe1396ac954421ebfbf0b1 | 3,601,868 |
def styled_text(text, new_styles, old_styles=None, supplement_style=False):
"""Return a styled text tuple that can be used within urwid.Text.
.. note::
If an urwid.Text instance is passed in as the ``text`` parameter,
alignment values will be lost and must be explicitly re-added by the
... | 1283433859d9207bd73c512fc307b68ec781c98c | 3,601,869 |
def cdf_function_1(cd: ChemicalDiagram):
"""inclusion: one of the connected components contains only C N H"""
sets = []
for scd in cd.get_components():
sets.append(set(scd.get_element_list()))
return {"C", "N", "H"} in sets | 00b53571798fe1e086fe8df6f36fc369c2cabced | 3,601,870 |
def _imports(graph: mapry.Graph) -> str:
"""
Generate the import declaration.
:param graph: mapry definition of the object graph
:return: generated code
"""
import_set = set() # type: Set[str]
if graph.classes:
import_set.add("fmt")
if mapry.needs_type(a_type=graph, query=map... | 78b983c7b0e2f30f7b0ca47fa98bed716120c69c | 3,601,871 |
def _to_db_str(sequential_list):
"""Convert a list or tuple object to a string of database format."""
entry_list = []
for _entry in sequential_list:
# I know only text type need to be converted by now. More types could
# be added in the future when we know.
if isinstance(_entry, str)... | 42a4e008964c0accb3e596dc75859641e999a0f4 | 3,601,872 |
def generate_personalized_recommendations(
submission_ids: list,
data: list,
index: str,
nbrs_model: NearestNeighbors = None,
):
"""
Generate personalized recommendations
for a given submission ids, given data, index, and nearest neighbors model
submission_ids: list, list of IDs that we... | 8d9cfada05de4a787e023b35afdac7c87499a2ea | 3,601,873 |
import glob
def get_file_sets(root_path, resnet_version, dlc_network_shuffle= 'shuffle2',dlc_network_iteration = '500000', filtered=False):
""" function intended to fetch the proper network file sets for a given session. A session directory
may have multiple predictions from unique DLC networks saved to a fol... | d7920667545dece6d6c4fccc6075a14c8eb53837 | 3,601,874 |
import time
def retry(ex, tries=4, delay=3, backoff=2, logger=log):
"""Retry calling the decorated function using exponential backoff based on
* http://www.saltycrane.com/blog/2009/11/trying-out-retry-decorator-python/
* http://wiki.python.org/moin/PythonDecoratorLibrary#Retry
:param ex: the excepti... | 61a743b3f6260bac1ed82afe132ab94579848358 | 3,601,875 |
def parse_errors(root_dir, lines):
"""
Parse and add special markers to all error found in the `ERRORS` section.
:param root_dir: This is the test root dir found in the pytest report.
:param lines: All reported output lines from the `ERRORS` section.
:returns: The original input list augmented wit... | f52cd2ab5e01330247930be88bf0bfda5654a9dd | 3,601,877 |
def air_port_add(request):
""" Add new air_port and see the list of air_ports packages """
success_message, error_message = None, None
form = AirPortForm
air_ports = AirPort.objects.all()
if request.method=="POST":
form = AirPortForm(request.POST)
if form.is_valid():
... | d8264c1265c8cb538cb7990117a9249099314ee2 | 3,601,878 |
def pull_address_data(url=None):
"""
Libraries with active extended wi-fi programs have their websites listed.
Access websites and pull street address and zip code. If an street address
intersection is given e.g.,
"16 Brighton First Rd. at Brighton Beach Ave."
remove the int... | d17029b3a04050cfc5cc51215eb0671f59d5e5e9 | 3,601,879 |
import requests
from typing import Match
def get_match(match_id):
"""Returns Score dicts list of the recent scores of the user"""
payload = {KEY_API_KEY: constants.OSU_API_KEY, KEY_MATCH: get_from_string(match_id)}
request = requests.get(URL_GET_MATCH, params=payload)
if request.status_code != 200:
... | 5ccfc596ff87c68283bd1cd77036a052d6e2d07f | 3,601,880 |
from typing import Tuple
import logging
async def test_send_custom_json(node: str) -> Tuple[str, float]:
"""Builds but doesn't send a custom_json not async."""
try:
hive = beem.Hive(node=node, nobroadcast=True, wif=Config.posting_keys)
data = {"something": "here"}
start = timer()
... | 12e27f679fd5cc4d62346f6f703eab44872c8b3e | 3,601,881 |
def transform_rows_nonlinear_and_categorical02(data, **kwargs):
"""
Nonlinear and categorical row transformation 02. 7 numerical data sources (x^4, log, exp2, log1p, x^5, log10, log2) and 3 categorical (8, 4 and 2 categories).
"""
sources_transformers = [
lambda x: np.power(x, 4),
lambd... | 8a277a860b017766d8aa154527fc27a44ec52da5 | 3,601,882 |
def histogram(s):
"""to check s in string"""
d={}
for c in s:
d[c]=1+d.get(c,0)
return d | 4b643a05f97ae0829235b1296e37ee73ad8807f4 | 3,601,883 |
def format_rot_dist_consts(rot_dists):
""" Format the rotational distortion constants.
"""
# Build rotational dists string
rot_dists_string = ''
for i, const in enumerate(rot_dists):
rot_dists_string += ' '.join(map(str, const))
if (i+1) != len(rot_dists):
rot_dists_str... | dbcb285f6886f6065ddd02497d12a230e1d74dff | 3,601,884 |
def read_get_schema(data):
"""Reads and parses a GSC ('Get Schema') request."""
return {"user": read(data, "S", 0), "group": read(data, "S", 2),
"schema": read(data, "S", 4),
"session_id": read(data, "S", 6)} | a84706b9e9fd8341c44cda718705b40839581b97 | 3,601,885 |
def svn_txdelta_send_string(*args):
"""svn_txdelta_send_string(svn_string_t const * string, svn_txdelta_window_handler_t handler, void * handler_baton, apr_pool_t pool) -> svn_error_t"""
return _delta.svn_txdelta_send_string(*args) | 630f0a58a289ff2a252f84089f94f8c2f2ab3359 | 3,601,886 |
def _to_spdx(lic):
"""
we are munging this stuff from conda-build
d_license = {'agpl3': ['AGPL-3', 'AGPL (>= 3)', 'AGPL',
'GNU Affero General Public License'],
'artistic2': ['Artistic-2.0', 'Artistic License 2.0'],
'gpl2': ['GPL-2', 'GPL (>= 2)',... | 66aaa5fa8428ec680ab347b9a33ed7f03f18281c | 3,601,888 |
import logging
def remote_ring(host: str, command: list, log: logging.Logger):
"""Remote ring over ssh. Returns `True` on success.
"""
ssh = ["/usr/bin/ssh",
"-t",
"-o", "ConnectTimeout=1",
"-o", "StrictHostKeyChecking=no",
host]
return system_call(ssh + com... | a3a05e98c49ca2af9f9c10625e8d9ad9baa00536 | 3,601,889 |
def geometry2layer(dataset, geom):
""" Convert geometry to a virtual-memory layer. """
# create layer
layer = dataset.CreateLayer(
'geom', geom.GetSpatialReference(), geom.GetGeometryType()
)
# add feature
feature = ogr.Feature(layer.GetLayerDefn())
feature.SetGeometry(geom)
laye... | fbbc6cd5c5dee6af790113bc6297a49aa6479a0d | 3,601,890 |
import numpy
def plane_fit(coordinates, center=None):
"""
Compute n-dimensional plane to a series or coordinates and return the
normal to that plane
:param coordinates: coordinates to fit a plane to
:type coordinates: :numpy:ndarray
:param center: point on the plane used as origin for t... | 4922b42c7c8a6c4faa7227386396ebc93bc1bafb | 3,601,891 |
def atanh(x : float) -> float:
"""
Inverse trigonometric function
Domain (-1 < x < 1)
"""
if not -1 < x < 1:
raise ValueError("Math domain error not in (-1,+1)")
return 0.5*functions.ln((1+x)/(1-x)) | a63ac82383d90d3c790035a901fbdabfca098b3b | 3,601,892 |
from typing import NamedTuple
from typing import Optional
def prepare_data_for_train(
# pylint: disable=g-bare-generic
input_tables: list,
preprocess_metadata: dict,
model_feature_columns: Optional[list] = None,
# pylint: enable=g-bare-generic
) -> NamedTuple(
'Outputs',
[
('time_s... | 112b340de85aee8199c528e830a76427cb3d18aa | 3,601,893 |
from typing import Any
import glob
import ast
import importlib
def process_args(args) -> Any:
"""
Validates args
:param args:
:return:
"""
possible_extensions = {'.g', '.gml', '.txt', '.gml', '.mat'}
graph_names = {fname[: fname.find(ext)].split('/')[-1]
for ext in poss... | 24432c251479b9bd3e7ad351075043ac64048d81 | 3,601,894 |
def vendor_factory(vendor_name):
"""
Given a full name of a vendor, retrieve or create the canonical
`~trigger.netdevices.Vendor` object.
Vendor instances are cached to improve startup speed.
:param vendor_name:
The vendor's full manufacturer name (e.g. 'CISCO SYSTEMS')
"""
return ... | d475c16e8c9561056564064ad0165efed9a6005b | 3,601,895 |
def hierachical_rollout2(
env,
scheduler,
worker,
skill_horizon=1,
max_path_length=np.inf,
render=False,
render_kwargs=None,
exclude_obs_ind=None,
obs_ind=None,
goal_ind=None,
):
"""
The following value for the following keys will b... | cbe1e7162aa77e8145a880d6f62a5006c98df55a | 3,601,896 |
def pyscv_get_widget(*args):
"""
pyscv_get_widget(py_this) -> TWidget *
"""
return _ida_kernwin.pyscv_get_widget(*args) | 22633cfbe0b62785150fc7ff5c1b5dedd7a5c801 | 3,601,898 |
def linear_scale_between(x1: float, x2: float, y1: float, y2: float, x: float, *, clamp=True, easing_func=None) -> float:
"""Standard linear interpolation function, optionally clamped (between y1 and y2)"""
pct = (x - x1) / (x2 - x1)
if easing_func:
pct = easing_func(pct)
if clamp:
pc... | f488346a4fe07b82f1281b646c3a39171b5fe757 | 3,601,899 |
def api_chart_scores(request):
"""
Used by report page line chart.
Returns JSON in format needed for line chart.
Used to load and chart a scoped set of Lighthouse runs.
"""
urlId = request.GET.get('urlid', None)
rangeType = request.GET.get('range', None)
## Validate that... | bdf8820fa7f670ffc09fc24c058eca2b47b9b76a | 3,601,900 |
def sel_init_cen(features, k):
"""
随机选择K个初始聚类中心
:param features: [[r,g,b],[r,g,b]...]
:return: centors=[cen1,cen2...]
"""
# 选取随机数
rands = [(int)(np.random.random() * (features.shape[0])) for _ in range(k)]
# 选取初始中心
centors = [features[rands[i]] for i in range(k)]
return centors | e61b3029297a610e04bca1b50067f7f32b11dad5 | 3,601,902 |
def cfgargparse(
cfgspecfile,
parser,
parse=True,
cfgfileopt="--cfgfile",
cfgfile="config.cfg",
exc=[],
extraopts=None,
args=None,
getparser=False,
getargs=True,
**kwargs,
):
"""Merge configuration and commandline arguments
Parameters
----------
cfgspecfile:
... | 911bcfa13c1bbc5b977582b40953b4a5716bab49 | 3,601,903 |
import ast
def _is_ast_str(node):
"""Determine whether this node represents a string."""
allowed_types = [ast.Str]
if hasattr(ast, "Bytes"):
allowed_types += [ast.Bytes]
if hasattr(ast, "JoinedStr"):
allowed_types += [ast.JoinedStr]
if hasattr(ast, "FormattedValue"):
allowed_types += [ast.Format... | 132af7142404f885684ce6559d1472c622c9cd10 | 3,601,904 |
def as_dict(self, **kwargs):
"""
Convert this object in a json serializable dict (can be use in __init__).
Optional keyword input parameter is for internal use only
and may prevent json serializability.
"""
DataKeeper_dict = dict()
DataKeeper_dict["name"] = self.name
DataKeeper_dict["ph... | c2c9535a39d21a5946df41d67df29fd43b3f3692 | 3,601,905 |
def translate_xmile(xmile_file):
""" Translate an xmile model file into a python class.
Functionality is currently limited.
"""
py_model_file = build_python(xmile_file)
return py_model_file | 5740e05b91d966c6d5ea33752bb38010c522c5fe | 3,601,906 |
def access_token_url():
""" URL for exchanging a verifier for an access token. """
return _BASE_URL_V1 % 'oauth/access_token/' | 9422c7b8ceae38d9ae92a89b4dbd55c71fd32175 | 3,601,907 |
def SetSpDiff(ea, delta):
"""
Setup modification of SP made by the instruction
@param ea: end address of the instruction
i.e.the last address of the instruction+1
@param delta: the difference made by the current instruction.
@return: 1-ok, 0-failed
"""
return idaapi.add_user... | 606c7ec20dab0a5af1bb8f8d5e69f4e95163cee3 | 3,601,908 |
import itertools
def score(data, synth, targets=[]):
""" Compute the total variation distance between marginals of data and synth.
:param data: an mbi.Dataset object
:param synth: an mbi.Dataset object
:param targets: A list of columns in the data domain
"""
workload = list(itertools.combinat... | 4a8ca07b1197ca567678291cbaf3585b6f7843bf | 3,601,909 |
import torch
def create_train_and_validation_engines(train_func, val_func=None, device='cpu'):
"""
Helper function for creating an ignite Engine object with helpful defaults.
This sets up an Engine that has four handlers attached to it:
- prepare_batch: before a batch is passed to train_func or val_f... | 6f0591196be25c5d1592200ac28b0317af54b22c | 3,601,910 |
import lifelines
def median_survival_times(model_or_survival_function) -> float:
"""
Compute the median survival time of survival function(s).
Parameters
-----------
model_or_survival_function: lifelines model or DataFrame
This can be a univariate lifelines model, or a DataFrame of one o... | 93e22de3c9673c12b9052fd2338ce2a304ba2a56 | 3,601,911 |
import random
def create_bank(num_accounts=1):
"""Returns a new bank with the given number of
accounts."""
names = ("Brandon", "Molly", "Elena", "Mark", "Tricia",
"Ken", "Jill", "Jack")
bank = Bank()
upper_pin = num_accounts + 1000
for pin_number in range(1000, upper_pin):
... | a7c131d80520e7f8b7285fc10d24724091a75d82 | 3,601,912 |
def Linear(source, target):
"""
Performs basic linear interpolation in between a source and a target.
"""
if target.frame <= source.frame:
raise ValueError("Target frame must be greater than source frame "
"(source = {0}, target = {1})".format(source.frame, target.frame))
fdiff = fl... | 89e6fb8ec03324cc971eee60291a1008b3834e32 | 3,601,913 |
def gaussian_mask(S):
""" mask significant intensities in spectrum
Parameters
----------
S : np.array, size=(m,n), dtype=complex
array with spectrum, i.e.: S = np.fft.fft2(I)
Returns
-------
M : np.array, size=(m,n), dtype=bool
frequency mask
See Al... | a8cf0847dd796aead0577ce48c2511710af7546b | 3,601,914 |
import tqdm
def get_data(data_type: str, left_flank_size: int, right_flank_size: int, n_bins: int = 100,
bin_value_type: str = 'mean') -> pd.DataFrame:
"""
Generates histone modification data by bins for each gene.
:param data_type: 'seq' or 'histone' data
:param left_flank_size: number ... | 108fbcb77feb0734ecc564ef8bf4eaf782551c39 | 3,601,915 |
def make_dict_from_config(path, config_file):
"""
Function to make a dict from a configuration file
Parameters
---------------
path: str
path dir to the config file
config_file: str
config file name
Returns
----------
dict with the config file infos
"""
# open a... | fd928dde7bb9ea3d360237c34bc7c46f9f26b07a | 3,601,916 |
def is_walrus_assignment(node: LN) -> bool:
"""Return True iff `node` is of the shape ( test := test )"""
inner = unwrap_singleton_parenthesis(node)
return inner is not None and inner.type == syms.namedexpr_test | 5c9b594187d3e91330cb3089fe7bc21fafafa3f2 | 3,601,917 |
def extract_domain(email_address):
"""
Given an email address, extract the domain name from it. This is done by finding the @ and
then splicing the email address and returning everything found after the @. If no @ is found
then the entire email address string is returned.
:param email_address:
... | 3e09c9cef431c09d126d8de6854990dc9351ef0d | 3,601,919 |
def get_sweep_info(pul, pgf, group_idx, series_idx):
"""
Find the associated record in the StimTree from the PulseTree
"""
pul_series = pul["ch"][group_idx]["ch"][series_idx]
num_sweeps_in_recorded_data = pul_series["hd"]["SeNumberSweeps"]
pul_sweep = pul_series["ch"][0]
stim_idx = pul_swee... | ebb2f125f9dbf45f80e088d63314a6fd10069a06 | 3,601,920 |
def build_model(args: Namespace) -> nn.Module:
"""
Builds a MoleculeModel, which is a message passing neural network + feed-forward layers.
:param args: Arguments.
:return: A MoleculeModel containing the MPN encoder along with final linear layers with parameters initialized.
"""
output_size = a... | 1eaa94e714f44bdaeb4afd1a71f4e5cdf876294a | 3,601,921 |
import pandas as pd
def google_scholar(root="./", download=True, full=False) -> Dataset:
"""Google Scholar dataset (Agrawal, et al.).
The Google Scholar dataset contains an academic coauthorship graph: the
nodes are authors, and two authors are connected by an edge if either
author listed the other a... | 87876024913826b8d9769a78f72cd944057c04ce | 3,601,922 |
def standard_form(ich, stereo=True):
""" Return an InChI string in standard form.
Eventually we should just designate standard-form as standard InChI
ordering for all but the hardcoded exceptions, put at the end.
:param ich: InChI string
:type ich: str
:param stereo: parame... | 554fa9d538e8b6e4f9983725f570ce28a6d6ae34 | 3,601,923 |
def check_solution(model, solution):
"""
Helper function. if solution is None, attempts to get it from the model.
:param model:
:param solution:
:return:
"""
if solution is None:
try:
solution = model.solution
except AttributeError:
raise AttributeErr... | a03ee5e2033ee99caa0fd761f9d78d3d597a906b | 3,601,924 |
import torch
from unittest.mock import Mock
def test_batch_verification_calls_custom_input_output_mappings():
""" Test that batch gradient verification can support different input and outputs with user-provided mappings. """
model = MultipleInputModel()
def input_mapping(inputs):
assert isinstanc... | 367d7389bd09762d8059a2e66e4c7d9a64aacd76 | 3,601,925 |
def gather_files(files_in):
"""
Args:
files_in (str):
"""
cubes = iris.load(files_in)
cubes.sort(key=lambda x: x.name())
unify_time_units(cubes)
# Add the names of custom output fields
replace_names(cubes)
# Remove hybrid height cubes and add as coordinates instead
rep... | edf84eaf418d58fc18e90949fe87a89d4c38f5c2 | 3,601,926 |
def pose_disambiguation(x2, K, C2, R2, X_n):
"""
Returns the pose that minimizes reprojection error.
:param x2: 2D points corresponding to X_n
:param K: camera intrinsic matrix
:param C2: four configurations of camera centers
:param R2: four configurations of rotations
:param X_n: four sets ... | a85926460e9d8a68267958977205a31f627601c4 | 3,601,927 |
import yaml
def dict_from_yaml(yaml_file):
"""Gets the dict representation of a YAML file."""
try:
yaml_dict = yaml.safe_load(yaml_file)
assert isinstance(yaml_dict, dict)
return yaml_dict
except yaml.YAMLError as e:
raise InvalidInputException(e) | 94ea65e958cfb814658dfe320f4e020ae9fe338f | 3,601,928 |
def plot_quantile_returns_violin(return_by_q,
ylim_percentiles=None,
ax=None):
"""
Plots a violin box plot of period wise returns for factor quantiles.
Parameters
----------
return_by_q : pd.DataFrame - MultiIndex
DataFrame w... | 9c993c45a0fc655c581943ef6a99b279461fd0d8 | 3,601,929 |
def str_to_dict(value):
"""
Convert a newline terminated string of key=value into a dictionary.
Parameters
----------
value : str
The string object to convert to a dictionary
Returns
-------
dict
Dictionary based on the string
"""
result_dict = {}
for item ... | 97a11fdbb715fad2da2e5866e30472a1b49e2c5e | 3,601,930 |
def degTodms(ideg):
"""
Converts degrees to degrees:minutes:seconds
:param ideg: objects coordinate in degrees
:type ideg: float
:return: degrees:minutes:seconds
:rtype: string
"""
if (ideg < 0):
s = -1
else:
s = 1
ideg = abs(ideg)
deg = int(ideg) + 0.
m... | 169cf4a89e7a2bd8526cf32acd1e88ec62d0237f | 3,601,932 |
def convert_rgb565(image):
"""Converts the RGB image into a byte array in RGB565 format"""
data = bytearray(128 * 160 * 2)
i = 0
for (r, g, b) in image.getdata():
w = rgb888_to_rgb565(r, g, b)
data[i] = w >> 8
i += 1
data[i] = w & 0xff
i += 1
return data | e2fd92e73499a640280fa65936dd2603cade22d1 | 3,601,933 |
from datetime import datetime
from typing import Tuple
from typing import Dict
import random
def _create_new_row(
table: Table,
primary_key: int,
parent_key: int = None,
batch_id: int = None,
timestamp: datetime = datetime.now(),
) -> Tuple:
"""
Create a new row for a table. Substitute cr... | 2683930a49f33e25c97687b63687d70fcde709d4 | 3,601,934 |
def char_to_string(arr):
"""Like netCDF4.chartostring, but faster and more flexible.
"""
# based on: http://stackoverflow.com/a/10984878/809705
arr = np.asarray(arr)
kind = arr.dtype.kind
if kind not in ['U', 'S']:
raise ValueError('argument must be a string')
return arr.view(kind + ... | c25446c0a2d028249ad7e30fe6fd70245baea617 | 3,601,935 |
import pandas
import numpy
def rolling_stat(stat, x, window):
"""
Calculate rolling statistics `stat` of `x` with sliding `window`.
Parameters
----------
stat : 'snr', 'cv', 'fano', 'mean', 'median', ...
Name (`str`) of the rolling statistics supported by pandas
and `getstat` (e.g... | 54ff5a66925390e291dc86eec60437abb4c0ecaf | 3,601,937 |
from typing import OrderedDict
def evaluate_box_proposals(dataset, roidb):
"""Evaluate bounding box object proposals."""
res = _empty_box_proposal_results()
areas = {'all': '', 'small': 's', 'medium': 'm', 'large': 'l'}
for limit in [100, 1000]:
for area, suffix in areas.items():
s... | e0a5ba8bad0711f0d1285925642029c64da54fde | 3,601,939 |
def breakbarrier(self, *qargs):
"""Apply :class:`~qiskit.circuit.Barrier`. If qargs is None, applies to all."""
#from .barrier import Barrier
qubits = []
if not qargs: # None
for qreg in self.qregs:
for j in range(qreg.size):
qubits.appen... | 22addde668d669e9574f4f929248b16ebb0481db | 3,601,940 |
def build_command(input_device, rates, bits, buffers, sox_effects):
"""
:param input_device: device index e.g. 2
:param rates: [input, output] e.g. [48000, 48000]
:param bits: [input, output] e.g. [16, 16]
:param buffers: [input, sox] e.g. [512, 1024]
:param sox_effects: [left, right] e.g. [['eq... | 8c17f55ef8ff3d0abc8ffbdbe85a2d98306a6b37 | 3,601,941 |
def filter_sparse(timestamps):
"""
Create a sparse set of timestamps, by keeping only 1 timestamp for every 10 minute
interval.
"""
if len(timestamps) == 0:
return []
ok = [timestamps[0]]
for vis_ts, ir_ts in sorted(timestamps, key=lambda x: x[0]):
if (vis_ts - ok[-1][0]) >... | 12030e7f9151c2c846d4fd7f0c31bcc1c28104ae | 3,601,942 |
from pathlib import Path
def main() -> int:
""" Execute the setup command."""
def data_files(*paths):
""" Expand path contents for the `data_files` config variable. """
for path in map(Path, paths):
if path.is_dir():
for root, _, files in walk(str(path)):
... | 21538616157f4916184936c4ecf559cdb85eead7 | 3,601,946 |
from typing import Union
def conditional_join(
df: pd.DataFrame,
right: Union[pd.DataFrame, pd.Series],
*conditions,
how: str = "inner",
sort_by_appearance: bool = False,
) -> pd.DataFrame:
"""
This is a convenience function that operates similarly to ``pd.merge``,
but allows joins on... | e70c1bc31111312d3c8df0b6b6556000673a923b | 3,601,947 |
def prepare_results(cursor_description, rows):
"""
Generate result in JSON format with an entry consisting of key value pairs.
:param cursor_description: a tuple with query result columns
:param rows: list of returned sql query values
:return: dictionary
"""
if rows is None or len(rows) == 0... | 8fcc48f0a732a200c65d27817349a0de1a5f1172 | 3,601,948 |
from typing import List
def merge_rgb(images: List[Image]) -> List[Image]:
"""Variant of images_to_stack that makes an RGB from 3 images."""
if not (len(images) == 3 and all(isinstance(x, Image) for x in images)):
raise ValueError(
trans._("merge_rgb requires 3 images layers", deferred=Tru... | c8dd9952a78f93720714ad8c5482fe5679ffc347 | 3,601,949 |
def signed_in_users(session=None, today=None, full_name=True):
"""Return list of names of currently signed in users.
:param session: SQLAlchemy session through which to access the database.
:param today: (optional) The current date as a `datetime.date` object. Used for testing.
:param full_name: (optio... | 55e394f778af9786c0ee3ba98b1bdcd20530b32e | 3,601,951 |
def eval_hess_f(Y):
"""
compute the hessian of f in the forward mode of AD
"""
Y = algopy.UTPM.init_hessian(Y)
retval = eval_f(Y)
hessian = algopy.UTPM.extract_hessian(5, retval)
return hessian | 67272b4ae62def8cd993f77ec5751dbec71900b5 | 3,601,952 |
from typing import Tuple
import re
def get_name_version_from_requires_dist(string_parse: str) -> Tuple[str, str]:
"""Extract the name and the version from `requires_dist` present in
PyPi`s metadata
:param string_parse: requires_dist value from PyPi metadata
:return: Name and version of a package
... | 55545ec1b30a4db1944932070434d26205beefbd | 3,601,954 |
import torch
def _rescale(dat, mn_out=0, mx_out=511):
""" Rescales image intensities between mn_out and mx_out.
"""
dtype = dat.dtype
device = dat.device
dat[(dat == dat.min()) | ~torch.isfinite(dat) | (dat == dat.max())] = 0
# Make scaling to set image intensities between mn_out and mx_out
... | 3b502094e22fe97fadfeb4ff987774385442c52e | 3,601,955 |
import pkg_resources
def walk(module_name, dirname, topdown=True):
"""
Copy of :func:`os.walk`, please refer to its doc. The only difference is that we walk in a package_resource
instead of a plain directory.
:type module_name: basestring
:param module_name: module to search in
:type dirname: ... | 8a001a4673b9a123f4c4260f2226eff0c360b698 | 3,601,956 |
def get_triplet_columns(data: DataFrame) -> DataFrame:
"""
Remove all columns except (protein, mutation, interactor) triplets.
Parameters
----------
data : <DataFrame>
The input dataframe whose non-triplet columns to be removed.
Returns
-------
triplet_data : <DataF... | 9749479ea5b1fda2370541d89de33d2d9e018bbc | 3,601,957 |
from typing import Iterable
def test_alias() -> None:
"""Test that columns and indices can be aliased."""
class Schema(pa.SchemaModel):
col_2020: Series[int] = pa.Field(alias=2020)
idx: Index[int] = pa.Field(alias="_idx", check_name=True)
@pa.check(2020)
@classmethod
... | c83ecc20002d5e0e85be3ad168705a7adf09ede4 | 3,601,958 |
def p_methods(data, pv_index=0, alpha = 0.05):
"""
A summary dataframe with columns for the p-values, adjusted p-values for both Bonferroni and
Benjamini-Hochberg (BH), adjusted significancelevel for Bonferroni and the critical value for BH
Args:
- data: dataframe or array containing at least a ... | 2d7a9d6d0ff983f6fbc6811f96663b35f450754b | 3,601,959 |
def create_client_entities(count, id_or_name=False):
"""Creates a list of client-style entities with random keys."""
return [
entity.to_client_entity()
for entity in create_entities(count, id_or_name=id_or_name)
] | a38c0b5c16746c264fd26dcc78b90d3b35681555 | 3,601,960 |
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