content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
from typing import Tuple
from typing import List
from typing import Type
from typing import _Final
def build_type(tp) -> Tuple[str, List[Type]]:
"""
Build typescript type from python type.
"""
tokens = tokenize_python_type(tp)
dependencies = [
token
for token in tokens
if t... | 475362488b7fe07db035ce70ddb3ac40580412dd | 3,651,043 |
def laplacian_radial_kernel(distance, bandwidth=1.0):
"""Laplacian radial kernel.
Parameters
----------
distance : array-like
Array of non-negative real values.
bandwidth : float, optional (default=1.0)
Positive scale parameter of the kernel.
Returns
-------
weight : ar... | fd5f777b0d21e3a7673a6589a76dd50f48384029 | 3,651,044 |
def build_eslog_config_param(
group_id,
task_name,
rt_id,
tasks,
topic,
table_name,
hosts,
http_port,
transport,
es_cluster_name,
es_version,
enable_auth,
user,
password,
):
"""
es参数构建
:param group_id: 集群名
:param task_name: 任务名
:param rt_id: rt... | 826b8d97ef14792845b4ced98ab5dcb3f36e57f3 | 3,651,045 |
def disclosure(input_df, cur_period):
"""
Reading in a csv, converting to a data frame and converting some cols to int.
:param input_df: The csv file that is converted into a data frame.
:param cur_period: The current period for the results process.
:return: None.
"""
input_df = pd.read_csv... | 65702fa309884206f284b35c48e2e8c8a34aef2b | 3,651,046 |
def kitchen_sink():
"""Combines all of the test data."""
return word_frequencies.load(_KITCHEN_SINK_DATA) | 4e0b0d38465fb02cd4f8aeb5e54c2f6bcbdf2cda | 3,651,048 |
import torch
def sim_matrix(a, b, eps=1e-8):
"""
added eps for numerical stability
"""
a = normalize_embeddings(a, eps)
b = normalize_embeddings(b, eps)
sim_mt = torch.mm(a, b.transpose(0, 1))
return sim_mt | d0caa5ce6e9f86b861910221321b80752b4f24e4 | 3,651,049 |
def read_addon_xml(path):
"""Parse the addon.xml and return an info dictionary"""
info = dict(
path='./', # '/storage/.kodi/addons/plugin.video.vrt.nu',
profile='special://userdata', # 'special://profile/addon_data/plugin.video.vrt.nu/',
type='xbmc.python.pluginsource',
)
tree... | 6ead602b97c12bfd78ddc7194102a84793aa631b | 3,651,050 |
import requests
def get_submission_list(start_timestamp, end_timestamp, args=None):
"""
Scrapes a subreddit for submissions between to given dates. Due to limitations
of the underlying service, it may not return all the possible submissions, so
it will be necessary to call this method again. The metho... | 7fa053c27787136420a9004721c1954318deeedb | 3,651,051 |
def loadDataSet():
"""
load data from data set
Args:
Returns:
dataSet: train input of x
labelSet: train input of y
"""
# initialize x-trainInput,y-trainInput
dataSet = []
labelSet = []
# open file reader
fr = open('testSet.txt')
for line in fr.readlines():
# strip() -- get rid of the space on bot... | 38f42a8a7c6b12e3d46d757d98565222e931149f | 3,651,052 |
def xds_read_xparm_new_style(xparm_file):
"""Parse the XPARM file to a dictionary."""
data = map(float, " ".join(open(xparm_file, "r").readlines()[1:]).split())
starting_frame = int(data[0])
phi_start, phi_width = data[1:3]
axis = data[3:6]
wavelength = data[6]
beam = data[7:10]
spac... | ba5a851c68c54aa0c9f82df1dc2334f427c8cea8 | 3,651,053 |
def clear_bit(val, offs):
"""Clear bit at offset 'offs' in value."""
return val & ~(1 << offs) | e50e5f8ccc3fe08d9b19248e290c2117b78379ee | 3,651,054 |
def get_org_details(orgs):
"""Get node and site details, store in Org object"""
org_details = []
for org in orgs:
org_id = org['id']
org_name = org['name']
org_longname = org['longname']
Org = namedtuple('Org', ['org_id', 'org_name', 'org_longname'])
org_details.exten... | 94bec33c2fbee35210ca61f6b8d3694d198c80ee | 3,651,055 |
import logging
def flush_after(handler, delay):
"""Add 'handler' to the queue so that it is flushed after 'delay' seconds by the flush thread.
Return the scheduled event which may be used for later cancellation (see cancel()).
"""
if not isinstance(handler, logging.Handler):
raise TypeError(... | a8cb8197643dbd092f709bed0726d076997e4715 | 3,651,056 |
def _ExtractCLPath(output_of_where):
"""Gets the path to cl.exe based on the output of calling the environment
setup batch file, followed by the equivalent of `where`."""
# Take the first line, as that's the first found in the PATH.
for line in output_of_where.strip().splitlines():
if line.startswith('LOC:'... | 6a0c0d4aa74b4e84de69de023e2721edd95c36bd | 3,651,057 |
import math
def logGamma(x):
"""The natural logarithm of the gamma function.
Based on public domain NETLIB (Fortran) code by W. J. Cody and L. Stoltz<BR>
Applied Mathematics Division<BR>
Argonne National Laboratory<BR>
Argonne, IL 60439<BR>
<P>
References:
<OL>
<LI>W. J. Cody and K. E. Hillstrom, 'Chebyshev Appro... | 36128e9a4b765dcc85ef42866fdbe7d16140ea1d | 3,651,058 |
def regional_validity(query_point, regional_inclusion, regional_exclusions):
""" regional_validity
Returns whether a coordinate point is inside a polygon and outside of excluded regions.
Input: A Point object, a Polygon Object of the inclusion region; a list of Polygon Objects of excluded regions.
Output: True if t... | 68e06b3d89e4783130f123d6c91dc5c43a9788ba | 3,651,059 |
def get_word_vector_list(doc, w2v):
"""Get all the vectors for a text"""
vectors = []
for word in doc:
try:
vectors.append(w2v.wv[word])
except KeyError:
continue
return vectors | f228c2100b6a622fdb677954257e2d1590dcc0ff | 3,651,060 |
def solve(lines, n):
"""Apply the rules specified in the input lines to the starting
pattern for n iterations.
The number of lit pixels in the final pattern is returned.
"""
rules = load_rulebook(lines)
pattern = START
for _ in range(n):
pattern = enhance(pattern, rules)
return s... | 781c349bfa186ac04daea60fe7e954431787ea15 | 3,651,061 |
def _to_plotly_color(scl, transparence=None):
"""
converts a rgb color in format (0-1,0-1,0-1) to a plotly color 'rgb(0-255,0-255,0-255)'
"""
plotly_col = [255 * _c for _c in mplc.to_rgba(scl)] if len(scl) == 3 else [255 * _c for _c in mplc.to_rgb(scl)]
if transparence is not None:
assert 0.... | 95b7686f913c69792e18f127176db68a3f72622f | 3,651,062 |
def dense_attention_block(seqs_repr, is_training, num_layers,
decay_variable, decay_constant,
units, dropout, query_dropout,
l2_scale, name=''):
"""
"""
for i in range(num_layers):
with tf.variable_scope('dense_attention{}'.format... | db50dd5e4d8d61622a9f989ec0ae9c02c5a4cfe1 | 3,651,063 |
def generate_schema_type(app_name: str, model: object) -> DjangoObjectType:
"""
Take a Django model and generate a Graphene Type class definition.
Args:
app_name (str): name of the application or plugin the Model is part of.
model (object): Django Model
Example:
For a model wit... | b57cd78cce59dacf1fdb1d14c667405b6cfdcc90 | 3,651,064 |
def do_authorize():
"""
Send a token request to the OP.
"""
oauth2.client_do_authorize()
try:
redirect = flask.session.pop("redirect")
return flask.redirect(redirect)
except KeyError:
return flask.jsonify({"success": "connected with fence"}) | 1e19f501ac6da94058619e8dd5905d6cd2ab1a69 | 3,651,065 |
import re
def get_windows():
"""
Return all windows found by WM with CPU, fullscreen, process name, and class information.
"""
# Basic window information
result = check_output('nice -n 19 wmctrl -l -p', shell=True)
lines = [a for a in result.decode('utf8').split('\n') if a != '']
windows =... | dd0f6f702592cf7f2fdd8541959682890dcc271e | 3,651,066 |
import google
def get_google_open_id_connect_token(service_account_credentials):
"""Get an OpenID Connect token issued by Google for the service account.
This function:
1. Generates a JWT signed with the service account's private key
containing a special "target_audience" claim.
2. Sends it to t... | 08e483865d26772112ffaf9837692f001598ced5 | 3,651,067 |
def term_to_atoms(terms):
"""Visitor to list atoms in term."""
if not isinstance(terms, list):
terms = [terms]
new_terms = []
for term in terms:
if isinstance(term, And):
new_terms += term_to_atoms(term.to_list())
elif isinstance(term, Or):
new_terms += te... | 6262ea7b1df124a4717d1452a23c33175b5da7a8 | 3,651,068 |
def expr_max(argv):
"""
Max aggregator function for :class:`Expression` objects
Returns
-------
exp : :class:`Expression`
Max of given arguments
Examples
--------
>>> x = so.VariableGroup(10, name='x')
>>> y = so.expr_max(2*x[i] for i in range(10))
"""
return expr... | 182157a627b12db6c41c79a99f135a7a493d4410 | 3,651,069 |
def handle_size(bytes_in=False, bytes_out=False):
"""
a function that converts bytes to human readable form. returns a
string like: 42.31 TB. example:
your_variable_name = make_readable(value_in_bytes)
"""
tib = 1024 ** 4
gib = 1024 ** 3
mib = 1024 ** 2
kib = 1024
if bytes_in:
... | 6e2b3b758e1afc1cea43bbe7ac0c6179b1d32c5f | 3,651,070 |
def return_elapsed(gs):
"""Returns a description of the elapsed time of recent operations.
Args:
gs: global state.
Returns:
A dictionary containing the count, minimum elapsed time,
maximum elapsed time, average elapsed time, and list of elapsed time
records.
"""
assert isinstance(gs, global_state.... | af832a3bac239e24f610e39c5dee8fde6a1a25c8 | 3,651,071 |
def calculate_per_class_lwlrap(truth, scores):
"""Calculate label-weighted label-ranking average precision.
Arguments:
truth: np.array of (num_samples, num_classes) giving boolean ground-truth
of presence of that class in that sample.
scores: np.array of (num_samples, num_classes) giving the classi... | 7cc9187f96d0899d0ce554164df553cc9b5f79a0 | 3,651,072 |
import hashlib
import zipfile
from datetime import datetime
def generate_manifest(name, p, h=None):
""" generate_manifest(name, p, h) -> mapping
Generates a mapping used as the manifest file.
:param name: a dotted package name, as in setup.py
:param p: the zip file with package content.... | 13c10ae405dbc6fe5acf92180e7981d07fdb9c60 | 3,651,074 |
def benchrun(methods,
model,
case_args,
filename,
cpus=1,):
"""
Parameters
----------
methods : list of str
Voter systems to be assessed by the election model.
model : func
Election model running function as
... | 414c96deb9a8d2f64b6808323465f8647aa5e48a | 3,651,075 |
def retry( exceptions,times=3,sleep_second=0):
"""
Retry Decorator
Retries the wrapped function/method `times` times if the exceptions listed
in ``exceptions`` are thrown
:param times: The number of times to repeat the wrapped function/method
:type times: Int
:param Exceptions: Lists of exceptions that trigg... | de715a0f903386358265c3fe4a13f1d91bcb177e | 3,651,076 |
def positiveId(obj):
"""Return id(obj) as a non-negative integer."""
result = id(obj)
if result < 0:
result += _address_mask
assert result > 0
return result | 5d3f987c621cf3d43ac31e9300a4d54ba208a7a0 | 3,651,077 |
def compute_annualized_total_return_over_months(df, column_price, months):
"""
Computed the annualized total return over the specified number of months.
This is equivalent to Compound Annual Growth Rate (CAGR).
Note: If the period is less than one year, it is best not to use annualized total return as... | a75886ae85ab5bb146d93bd159a0a2a32f950678 | 3,651,079 |
from functools import reduce
def build_sparse_ts_from_distributions(start_date, end_date, seasonalities, time_interval, dist_dict, **kwargs):
"""constructs a time series with given distributions and seasonalities in a given frequency time_interval"""
ts_list = []
for (name, dist), seasonality in zip(dist_... | 81d2ebc32a2b62ed967377faf90b3b58e7c753ff | 3,651,080 |
def preprocess_label(labels, scored_classes, equivalent_classes):
""" convert string labels to binary labels """
y = np.zeros((len(scored_classes)), np.float32)
for label in labels:
if label in equivalent_classes:
label = equivalent_classes[label]
if label in scored_classes:
... | 3e2465bb0db04afaaca0576f6c97847bd0fd2b2e | 3,651,081 |
import math
def vec_abs(field: SampledField):
""" See `phi.math.vec_abs()` """
if isinstance(field, StaggeredGrid):
field = field.at_centers()
return field.with_values(math.vec_abs(field.values)) | 91395513b7e457bdfdded484db1069e8c3b95805 | 3,651,084 |
def spoofRequest(app):
"""
Make REQUEST variable to be available on the Zope application server.
This allows acquisition to work properly
"""
_policy=PermissiveSecurityPolicy()
_oldpolicy=setSecurityPolicy(_policy)
newSecurityManager(None, OmnipotentUser().__of__(app.acl_users))
info = ... | d1b3bd1a37d69f6500d23e55b5318b6519ed04be | 3,651,085 |
def data_to_percentage(data_list: pd.DataFrame) -> pd.DataFrame:
"""
Takes a dataframe with one or more columns filled with digits and returns a
dataframe with the percentages corresponding to the number of times the
numbers 1-9 appear in each column.
Args:
data_list: a dataframe of integer... | 18316ddf999419290d572e77d2934241359e45a3 | 3,651,086 |
from .models.models import EncoderClassifier
import torch
def create_classifier_from_encoder(data:DataBunch, encoder_path:str=None, path=None,
dropout1=0.5, device: torch.device = torch.device('cuda', 0), **kwargs):
"""Factory function to create classifier from encoder to allo... | 736cfec768b6d659ab6fa1f087474a482409b66e | 3,651,087 |
from typing import Hashable
def filter_string(
df: pd.DataFrame,
column_name: Hashable,
search_string: str,
complement: bool = False,
case: bool = True,
flags: int = 0,
na=None,
regex: bool = True,
) -> pd.DataFrame:
"""Filter a string-based column according to whether it contains ... | 9e5598a4afcff41ec5dc67c38b68efbacf3f09ec | 3,651,088 |
from typing import List
from typing import Dict
from typing import Union
import functools
def on_demand_feature_view(
features: List[Feature], inputs: Dict[str, Union[FeatureView, RequestDataSource]]
):
"""
Declare an on-demand feature view
:param features: Output schema with feature names
:param... | 0ea45df22cb167ad2aa919a0be40f2a11574a69a | 3,651,089 |
from typing import cast
def get_error_string(ftdi):
"""
get_error_string(context ftdi) -> char *
Get string representation for last error code
Parameters:
-----------
ftdi: pointer to ftdi_context
Returns:
--------
Pointer: to error string
"""
errstr = ftdi_get_er... | e0d3eaa19014fff9840e7a8e629651107ae25495 | 3,651,090 |
def DenseNet52k12(growth_rate = 12,
reduction = 0.5):
"""
Parameters:
----------
Returns
-------
"""
return DenseNet(reduction = reduction,
growth_rate = growth_rate,
layers=52) | a295bcae685ae36bcbe356099d404403f7b8c0b6 | 3,651,091 |
def construct_fid_mask(catalog):
"""
Constructs the fidelity mask based off my results, not Robertos
:param catalog:
:return:
"""
line_widths = [i for i in range(3, 21, 2)]
fid_catalog = load_table("fidelity_snr.out", start=0)
fid_limit = 0.4
six_fids = []
for width in line_widt... | 81f50ae4dd092482eb406bef331075245989d2f3 | 3,651,092 |
def _run_job(tgt, fun, arg, kwarg, tgt_type, timeout, retry):
"""
Helper function to send execution module command using ``client.run_job``
method and collect results using ``client.get_event_iter_returns``. Implements
basic retry mechanism.
If ``client.get_event_iter_returns`` return no results, `... | e23c189063e5d7df542d8e774acf655f4af61289 | 3,651,094 |
def _set_rank_colorbar(ax, img, norm):
""" Set color bar for rankshow on the right of the ax
"""
divider = make_axes_locatable(ax)
cax = divider.append_axes("right", size="5%", pad=0.05)
plt.colorbar(img, cax=cax)
y_tick_values = cax.get_yticks()
boundary_means = [np.mean((y_tick_values[... | f21f59ac69c79cf9449d28710abdeeb730004077 | 3,651,095 |
from typing import Optional
from pathlib import Path
import importlib
def destination(stub: str) -> Optional[Path]:
"""Determine stub path
Only handle micropython stubs, ignoring
any cPython stdlib equivalents.
"""
prefix, _, suffix = stub.partition(".")
if importlib.util.find_spec(prefix): ... | 8b2552513dbeaa9dc09cb85703b736e17c4788b5 | 3,651,096 |
def train_IPCA(X,n_dims,batch_size,model='ipca'):
"""
name: train_IPCA
Linear dimensionality reduction using Singular Value Decomposition of
centered data, keeping only the most significant singular vectors to
project the data to a lower dimensional space.
returns: the transformer model
"""... | 282c885a562b5b3dbe356050ef5f270f49d7014d | 3,651,098 |
def _str_cell(cell: Cell) -> str:
"""Строковое представление клетки.
Данной строкой клетка будет выводится на экран.
"""
if cell.is_open:
if cell.is_empty:
return " "
elif cell.value:
return f" {cell.value} "
elif cell.is_flagged:
return "[F]"
e... | 2e4428196601a726b488e3ec4d966072033c5bfe | 3,651,099 |
def mvw_ledoit_wolf(prices,
weight_bounds=(0.,1.),
rf = 0.,
options = None):
"""
Calculates the mean-variance weights given a DataFrame of returns.
Wraps mean_var_weights with ledoit_wolf covariance calculation method
Args:
* prices (... | 086f6430d189fd12509d56ce4a96a351a178979b | 3,651,100 |
def _PadLabels3d(logits, labels):
"""Pads or slices 3-d labels to match logits.
Covers the case of 2-d softmax output, when labels is [batch, height, width]
and logits is [batch, height, width, onehot]
Args:
logits: 4-d Pre-softmax fully-connected output.
labels: 3-d, but not necessarily matching in si... | 223f7dfea9ebc970e62dbe71e2f27dfb5c9f161d | 3,651,101 |
def intx():
"""Returns the default int type, as a string.
(e.g. 'int16', 'int32', 'int64').
# Returns
String, the current default int type.
"""
return _INTX | 57661ef00953e07228ff81abc93ec22c216797ff | 3,651,102 |
import json
def dev_end_hardware_script() -> Response:
"""Designate the end of a hardware script in flask log.
Can be invoked by: curl http://localhost:4567/development/end_hardware_script
"""
return Response(json.dumps({}), mimetype="application/json") | 714b448642180753e639992f2d101841074aeefd | 3,651,103 |
def _init_train(opt):
"""Common initilization stuff for all training process."""
ArgumentParser.validate_prepare_opts(opt)
if opt.train_from:
# Load checkpoint if we resume from a previous training.
checkpoint = load_checkpoint(ckpt_path=opt.train_from)
fields = load_fields(opt.save... | bb2a043d1a59f996b303aabf9db724ced3505dbf | 3,651,104 |
def compare(isamAppliance1, isamAppliance2):
"""
Compare Update Servers between two appliances
"""
ret_obj1 = get_all(isamAppliance1)
ret_obj2 = get_all(isamAppliance2)
for obj in ret_obj1['data']:
del obj['uuid']
for obj in ret_obj2['data']:
del obj['uuid']
return ibms... | e29025ca0af897f10b3b8498f8def86841b76c97 | 3,651,106 |
import random
def get_random():
"""
Retrieves the current issue of XKCD, chooses an issue 1 - current issue #, and returns a json object.
Returns null if an requests error occurs.
"""
return get_issue(random.randint(1, int(get_current()["num"]))) | 10fbf75681901722510b0b9fbb2de298eb80b45e | 3,651,108 |
def get_fasta_readlengths(fasta_file):
"""
Get a sorted list of contig lengths
:return: (tuple)
"""
lens = []
with open_fasta_reader(fasta_file) as f:
for record in f:
lens.append(len(record.sequence))
lens.sort()
return lens | 769cf5af50ba684c107a1312d2aeaab2721a29c6 | 3,651,109 |
def postprocess(p, gt, width_and_height, p_binary, false_positives=False, false_negatives=False):
"""
This function does matching and then postprocessing of p's and gt's
:param p: the objects given from rcnn
:param gt: the objects we get from the ground truth
:param width_and_height: the width and h... | dd83de4547f7c1461b64fcd2dfa4c3df54aefd10 | 3,651,110 |
from csb.bio.structure import TorsionAngles
import numpy
def deg(x):
"""
Convert an array of torsion angles in radians to torsion degrees
ranging from -180 to 180.
@param x: array of angles
@type x: numpy array
@rtype: numpy array
"""
func = numpy.vectorize(TorsionAngles.d... | 95e37a0c644df1562e417c1ad61e4788bd46c279 | 3,651,111 |
import timeit
def run_median_trial():
"""Generate table for Median Trial."""
tbl = DataTable([10,15,15],['N', 'median_time', 'sort_median'])
trials = [2**k+1 for k in range(8,20)]
for n in trials:
t_med = 1000*min(timeit.repeat(stmt='assert(linear_median(a) == {}//2)'.format(n),
... | ed4c5ebe8bd6259c4adc45c4b023cc5bb96a1055 | 3,651,112 |
def regroup(X, N):
"""
Regroups the rows and columns of X such that rows/cols
that are N apart in X, are adjeacent in Y. If N is a
2 element vector, N[0] is used for rows and N[1] is used
for columns.
Parameters:
X: m by n matrix to be regrouped.
N: Integer or two element vector... | 7ad92b878cb6a55820ef9ad92c68e934184d725d | 3,651,113 |
def return_estimators(n_components):
"""Returns all of the estimators that can be used to generate models.
A larger selection of possible estimators have been commented out, but
could be uncommented."""
estimators = [
('PCArandom',
decomposition.PCA(n_components=n_components, svd_solve... | 680aa1d50c4e2db0e4d3df9e60749350df437bb8 | 3,651,114 |
def _check_type_picks(picks):
"""helper to guarantee type integrity of picks"""
err_msg = 'picks must be None, a list or an array of integers'
if picks is None:
pass
elif isinstance(picks, list):
if not all(isinstance(i, int) for i in picks):
raise ValueError(err_msg)
... | 79493f75db8e57f32a6369ad18900e0632d2bc18 | 3,651,115 |
def get_test_standard_scaler_str():
"""
Get a pandas projection code str
"""
test_code = cleandoc("""
standard_scaler = StandardScaler()
encoded_data = standard_scaler.fit_transform(df)
""")
return test_code | fd6e1daa7e0dddb603437e5b35c283a11e68ec00 | 3,651,116 |
from typing import List
from typing import Tuple
import re
def add_command(
command_list: List[Tuple[re.Pattern, callable]], func: callable, command_str: str
) -> List[Tuple[re.Pattern, callable]]:
"""Add a function and the command pattern to the command list.
Args:
func: Function it will be call... | f8076e4a6b37722591eae04a67feb1c25e606b84 | 3,651,117 |
def get_clusters_and_critical_nodes(G, k, rho_star, phi_in):
"""
The implementation of the main body of the partitioning Algorithm.
The main while-loop of the algorithm is executed as long as a refinement is still possible.
:param phi_in: An algorithm parameter used to lower bound the inner conductance... | e7374c9cad30a87477ee5b9ce4d0a0e9cb7de041 | 3,651,118 |
def get_edges_out_for_vertex(edges: list, vertex: int) -> list:
"""Get a sublist of edges that have the specified vertex as first element
:param edges: edges of the graph
:param vertex: vertex of which we want to find the corresponding edges
:return: selected edges
"""
return [e for e in edge... | 21485073df1c754e7c8e2b7dd9cafef284e601e7 | 3,651,119 |
def pellet_plot_multi_unaligned(FEDs, shade_dark, lights_on,
lights_off,**kwargs):
"""
FED3 Viz: Plot cumulaive pellet retrieval for multiple FEDs, keeping the
x-axis to show absolute time.
Parameters
----------
FEDs : list of FED3_File objects
FED3 files... | 3601e8ecff20a3d7978f7261ebaa5236d662a25e | 3,651,120 |
import time
def sync_via_mrmsdtw(f_chroma1: np.ndarray,
f_chroma2: np.ndarray,
f_DLNCO1: np.ndarray = None,
f_DLNCO2: np.ndarray = None,
input_feature_rate: float = 50,
step_sizes: np.ndarray = np.array([[1, 0], [... | 00dac7bdde14597e0daece958e65761ec01d1494 | 3,651,121 |
def simulate_beta_binomial(
K, D, sigma2, theta, mu=0, invlink=logistic, seed=None):
"""Simulates from binomial Gaussian process with Beta latent noise.
Args:
K: Cell-state kernel, for example as generated by create_linear_kernel
or create_rbf_kernel.
D: Array of total counts.
... | de4648af70a6b35c7b7f5edc2c151a98db6d7603 | 3,651,122 |
def convert_to_floats(tsi):
"""
A helper function that tax all of the fields of a TaxSaveInputs model
and converts them to floats, or list of floats
"""
def numberfy_one(x):
if isinstance(x, float):
return x
else:
return float(x)
def numberfy(x):
... | a6f93f402c547435fa9fe611481084215f52f13b | 3,651,123 |
def properties_filter(mol):
"""
Calculates the properties that contain logP, MW, HBA, HBD, TPSA, NRB
"""
#frag = Chem.rdmolops.GetMolFrags(mol) # remove '.'
#if len(frag) > 1:
#return False
MW_s = Descriptors.MolWt(mol) # MW
if MW_s < 250 or MW_s > 750:
return False
A... | bc124620baddb828b4c5cb82e0b0374bdb51bad7 | 3,651,124 |
def _create_certificate_chain():
"""
Construct and return a chain of certificates.
1. A new self-signed certificate authority certificate (cacert)
2. A new intermediate certificate signed by cacert (icert)
3. A new server certificate signed by icert (scert)
"""
caext = X509Exten... | 156a61e8159b1826def8fa33d5c5965add2c7f2e | 3,651,125 |
def build_job_spec_name(file_name, version="develop"):
"""
:param file_name:
:param version:
:return: str, ex. job-hello_world:develop
"""
name = file_name.split('.')[-1]
job_name = 'job-%s:%s' % (name, version)
return job_name | 55a45052852e6b24cb4370f7efe5c213da83e423 | 3,651,126 |
import torch
def draw_mask(im: torch.Tensor, mask: torch.Tensor, t=0.2, color=(255, 255, 255), visualize_instances=True):
"""
Visualize mask where mask = 0.
Supports multiple instances.
mask shape: [N, C, H, W], where C is different instances in same image.
"""
assert len(mask.shap... | 45d12dbc695755f0231ca2a8d0f8d1cdf2f423ff | 3,651,127 |
def view_about():
"""
shows the about page
:return:
:rtype:
"""
return render_template('about.html', title="About Flask AWS Template") | a364842c165864aba34605f3ffdd8c1d412015e8 | 3,651,128 |
import numpy
def viterbi(observed_values,
transition_probabilities,
emission_probabilities,
initial_distribution,
file_name,
log=True):
"""Calculates the viterbi-path for a given hidden-markov-model, heavily
inspired by Abhisek Janas Blogpost "Implem... | b063e5c5bbf566afb0f16175d9d229bef7a953f1 | 3,651,129 |
def extract_psf_fitting_names(psf):
"""
Determine the names of the x coordinate, y coordinate, and flux from
a model. Returns (xname, yname, fluxname)
"""
if hasattr(psf, 'xname'):
xname = psf.xname
elif 'x_0' in psf.param_names:
xname = 'x_0'
else:
raise ValueError... | cee108dd1f97e506b60ba621c7f08efa7b5c33d7 | 3,651,130 |
def config_check_conformance(cookie, dn):
""" Auto-generated UCS XML API Method. """
method = ExternalMethod("ConfigCheckConformance")
method.cookie = cookie
method.dn = dn
xml_request = method.to_xml(option=WriteXmlOption.DIRTY)
return xml_request | 598fbd665dcf18a35104400bf7debfc64347c3b5 | 3,651,132 |
def get_dist_to_port(geotiff):
"""
Extract "truth" dist_to_port from geotiff
"""
with Geotiff(geotiff) as tif:
dist_to_port = tif.values
return dist_to_port | 1a77c2ac905eea2d1796529297168dac394b4bdb | 3,651,133 |
import inspect
def build_dataset_exporter(
dataset_type, strip_none=True, warn_unused=True, **kwargs
):
"""Builds the :class:`DatasetExporter` instance for the given parameters.
Args:
dataset_type: the :class:`fiftyone.types.dataset_types.Dataset` type
strip_none (True): whether to exclud... | 6a21c90ee2a9c297ad86515f5078221459b1fb01 | 3,651,134 |
def conditions(x):
"""
This function will check whether the constraints that apply to
our optimization are met or not.
"""
if ( (10/x[0]) > 66.0 ):
return False
elif ( (10/x[0] + 12/x[1]) > 88.0 ):
return False
elif ( (10/x[0] + 12/x[1] + 7/x[2]) > 107.0 ):
return ... | 263fdc3fd07aa656982401f71071fcd684b8625f | 3,651,135 |
def get_commit_ancestors_graph(refenv, starting_commit):
"""returns a DAG of all commits starting at some hash pointing to the repo root.
Parameters
----------
refenv : lmdb.Environment
lmdb environment where the commit refs are stored
starting_commit : string
commit hash to start c... | 078819cf0291a5e4e1e8ad4ea409f475c0df93fd | 3,651,137 |
def is_verification_handshake(rjson):
"""
Determines if the request is the Slack application APIs verification handshake
:rtype: bool
"""
# Check body contains the right keys
for x in ['token', 'challenge', 'type']:
if x not in rjson:
return False
# Check type is correct... | 1ceccd9ca578bd09e9629cd59e565bc523502030 | 3,651,138 |
def template_node(scope_key):
""" Create and return a new template node.
Parameters
----------
scope_key : object
The key for the local scope in the local storage maps.
Returns
-------
result : TemplateNode
A new compiler template node.
"""
node = TemplateNode()
... | 4cd9721dd9f9f91cb84326391630274b8f5764a7 | 3,651,139 |
def GetAutoResult(chroot_path, buildbucket_id):
"""Returns the conversion of the result of 'cros buildresult'."""
# Calls 'cros buildresult' to get the status of the tryjob.
build_result = GetStatusFromCrosBuildResult(chroot_path, buildbucket_id)
# The string returned by 'cros buildresult' might not be in the... | 705fbc011c11fa67d0b61f130a3b6f024a6dcd44 | 3,651,140 |
def rft(x):
"""
Real Fourier Transform
"""
# XXX figure out what exactly this is doing...
s = x.shape[-1]
xp = np.zeros(x.shape,dtype="complex64")
xp[...,1:s/2] = x[...,1:-1:2]+x[...,2::2]*1.j
xp[...,0] = x[...,0]/2.
xp[...,s/2] = x[...,-1]/2.
return np.array(nmr_reorder(np.fft... | 3a65f0a0059df4c74b223f3284e996b82d7ebf02 | 3,651,141 |
def yam_path(manifestsdir):
"""Bundletracker manifest."""
return join(manifestsdir, 'yam.json') | 5d1b5162bd8285d8e33c822a3b5edcc996452719 | 3,651,142 |
def single_from(iterable):
"""Check that an iterable contains one unique value, and return it."""
unique_vals = set(iterable)
if len(unique_vals) != 1:
raise ValueError('multiple unique values found')
return unique_vals.pop() | c8fb8864083195ad913ff1ddf0114b5a50068902 | 3,651,143 |
import requests
def vthash(filehash: str):
"""Returns the analysis data class for a file in VirusTotal's database"""
endpoint_path = f'/files/{filehash}'
endpoint = f"{api_base_url}{endpoint_path}"
r = requests.get(endpoint, headers=header)
if r.status_code == 404 and r.json()['error']['code'] ... | bf4f334ad7a35e1141f9e00a44544fdd0709b411 | 3,651,144 |
def prod(x, axis=None, keepdims=False):
"""
product of all element in the array
Parameters
----------
x : tensor_like
input array
axis : int, tuple of ints
axis or axes along which a product is performed
keepdims : bool
keep dimensionality or not
Returns
---... | 8962e7b6abd16c9354f076c0c6d718b82fe44223 | 3,651,145 |
from typing import List
import difflib
def menu(queue: List[str] = None):
"""Fred Menu"""
fred_controller = FredController(queue)
an_input = "HELP_ME"
while True:
# There is a command in the queue
if fred_controller.queue and len(fred_controller.queue) > 0:
# If the comman... | b8133dd748f0a48099359b6503edee6c9f875fb6 | 3,651,146 |
def generic_repr(name, obj, deferred):
"""
Generic pretty printer for NDTable and NDArray.
Output is of the form::
Array(3, int32)
values := [Numpy(ptr=60597776, dtype=int64, shape=(3,))];
metadata := [contigious]
layout := Identity;
[1 2 3]
"""
... | c9de29b792d943420b02455752f01a9c12fcf66c | 3,651,147 |
def build_model(X, y, ann_hidden_dim, num_passes=20000):
"""
:param ann_hidden_dim: Number of nodes in the hidden layer
:param num_passes: Number of passes through the training data for gradient descent
:return: returns the parameters of artificial neural network for prediction using forward propagation... | bccdf828050af8a6ff5943eb84b574756f9f54ab | 3,651,148 |
def g_square_dis(dm, x, y, s):
"""G square test for discrete data.
Args:
dm: the data matrix to be used (as a numpy.ndarray).
x: the first node (as an integer).
y: the second node (as an integer).
s: the set of neibouring nodes of x and y (as a set()).
levels: levels of ... | 2f0f0b44a919177c0f5775a34e0493c62720a21d | 3,651,149 |
def start(name):
"""
Start the specified service
CLI Example:
.. code-block:: bash
salt '*' service.start <service name>
"""
cmd = "/usr/sbin/svcadm enable -s -t {0}".format(name)
retcode = __salt__["cmd.retcode"](cmd, python_shell=False)
if not retcode:
return True
... | 607b559281c6b13002d7237b8c4409533074d0bc | 3,651,150 |
from typing import Dict
def line_coloring(num_vertices) -> Dict:
"""
Creates an edge coloring of the line graph, corresponding to the optimal
line swap strategy, given as a dictionary where the keys
correspond to the different colors and the values are lists of edges (where edges
are specified as ... | 423e626ecbf4f48e0a192241375484a077fbe0b2 | 3,651,151 |
def flatten_outputs(predictions, number_of_classes):
"""Flatten the prediction batch except the prediction dimensions"""
logits_permuted = predictions.permute(0, 2, 3, 1)
logits_permuted_cont = logits_permuted.contiguous()
outputs_flatten = logits_permuted_cont.view(-1, number_of_classes)
return out... | c58fb965443a5402e9bec32afaebe9376c74653f | 3,651,152 |
def get_r_vals(cell_obj):
"""Get radial distances for inner and outer membranes for the cell object"""
r_i = cell_obj.coords.calc_rc(cell_obj.data.data_dict['storm_inner']['x'],
cell_obj.data.data_dict['storm_inner']['y'])
r_o = cell_obj.coords.calc_rc(cell_obj.data.data_di... | d51c926791845006dfe9a97cbd9c82c041ea701b | 3,651,153 |
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