content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def get_exploration_summary_from_model(exp_summary_model):
"""Returns an ExplorationSummary domain object.
Args:
exp_summary_model: ExplorationSummary. An ExplorationSummary model
instance.
Returns:
ExplorationSummary. The summary domain object correspoding to the
given... | c6561670f976e28a3869eb89c4be3ba884808da0 | 13,616 |
def get_service(api_name, api_version, scope, key_file_location,
service_account_email):
"""Get a service that communicates to a Google API.
Args:
api_name: The name of the api to connect to.
api_version: The api version to connect to.
scope: A list auth scopes to authorize for the appl... | 6c333f43c5feb5b44128b8f592586804eba68e1e | 13,617 |
from IsabelaFunctions.langlais_coeff import glm as g
from IsabelaFunctions.langlais_coeff import hlm as h
import tqdm
def model_map(lon, lat, alt, comp, binsize = 0.1, nmax = 134, a = 3393.5):
"""
Calculates a map of one component of the crustal magnetic field field model, for a given altitude.
Param... | 9a49e4a1f31180cd7a26f2028c5e45d077103346 | 13,618 |
def parse_command(incoming_text):
"""
incoming_text: A text string to parse for docker commands
returns: a fully validated docker command
"""
docker_action = ''
parse1 = re.compile(r"(?<=\bdocker\s)(\w+)")
match_obj = parse1.search(incoming_text)
if match_obj:
docker_ac... | abe82ae2fe29014b3441889c973a412a536b78f1 | 13,619 |
def angle_connectivity(ibonds):
"""Given the bonds, get the indices of the atoms defining all the bond
angles
A 'bond angle' is defined as any set of 3 atoms, `i`, `j`, `k` such that
atom `i` is bonded to `j` and `j` is bonded to `k`
Parameters
----------
ibonds : np.ndarray, shape=[n_bond... | 86c992a1a8ac2d3c6b1fbc5a137ef0734a3079ed | 13,621 |
def BOPDS_PassKeyMapHasher_IsEqual(*args):
"""
:param aPKey1:
:type aPKey1: BOPDS_PassKey &
:param aPKey2:
:type aPKey2: BOPDS_PassKey &
:rtype: bool
"""
return _BOPDS.BOPDS_PassKeyMapHasher_IsEqual(*args) | 8da04f1755e3d2f7d10ad3ecf5ec6b0d00ca5fcb | 13,622 |
def dms2dd(s):
"""convert lat and long to decimal degrees"""
direction = s[-1]
degrees = s[0:4]
dd = float(degrees)
if direction in ('S','W'):
dd*= -1
return dd | cb76efbf8c3b6a75bcc26593fab81a8ef3e16bbf | 13,624 |
def setna(self, value, na=np.nan, inplace=False):
""" set a value as missing
Parameters
----------
value : the values to set to na
na : the replacement value (default np.nan)
Examples
--------
>>> from dimarray import DimArray
>>> a = DimArray([1,2,-99])
>>> a.setna(-99)
di... | 6ada601dee346d5440a64ffdbf8d2642873bdb08 | 13,625 |
def hbox(*items, **config):
""" Create a DeferredConstraints object composed of horizontal
abutments for a given sequence of items.
"""
return LinearBoxHelper('horizontal', *items, **config) | cdfe16a35c73a2f8406207a0262b4210ce86146f | 13,626 |
def find_columns(clause):
"""locate Column objects within the given expression."""
cols = util.column_set()
visitors.traverse(clause, {}, {'column':cols.add})
return cols | 86b4c866a8fbe20ab1d4b0a34e4940155df00744 | 13,627 |
def _preprocess_data(smiles, labels, batchsize = 100):
"""
prepares all input batches to train/test the GDNN fingerprints implementation
"""
N = len(smiles)
batches = []
num_bond_features = 6
for i in range(int(np.ceil(N*1./batchsize))):
array_rep = utils.array_rep_from_smi... | 3456fe2059e386088d359ec0c2d54dff2d7fac25 | 13,628 |
def linear_activation_forward(A_prev, W, b, activation, keep_prob=1):
"""
Implement the forward propagation for the LINEAR->ACTIVATION layer
Arguments:
A_prev -- activations from previous layer (or input data): (size of previous layer, number of examples)
W -- weights matrix: numpy array of shape (... | 0e4d12142224bfb46af0afb547abe3dde0aa6811 | 13,629 |
def load_image(image_path, size):
"""
Load an image as a Numpy array.
:param image_path: Path of the image
:param size: Target size
:return Image array, normalized between 0 and 1
"""
image = img_to_array(load_img(image_path, target_size=size)) / 255.
return image | 3d9a790b762f800a222c26578dc0572587b091fb | 13,631 |
import signal
def _signal_exit_code(signum: signal.Signals) -> int:
"""
Return the exit code corresponding to a received signal.
Conventionally, when a program exits due to a signal its exit code is 128
plus the signal number.
"""
return 128 + int(signum) | 050eee98632216fddcbd71e4eb6b0c973f6d4144 | 13,632 |
import csv
def make_template_matrix(msigdb_file, blacklist, checkblacklist=True):
"""
Retrieve all genes and pathways from given msigdb .gmt file
Output:
sorted gene by pathways pandas dataframe. Entries indicate membership
"""
all_db_pathways = []
all_db_genes = []
# Get a set o... | b8068089279dfbe3b3cfc8b16dee016cc0994746 | 13,633 |
def unwrap_key(
security_control: SecurityControlField, wrapping_key: bytes, wrapped_key: bytes
):
"""
Simple function to unwrap a key received.
"""
validate_key(security_control.security_suite, wrapping_key)
validate_key(security_control.security_suite, wrapped_key)
unwrapped_key = aes_key_... | 7720ad8905f6818b1a3fa4132b040560a9ae0dfa | 13,634 |
def checkOwnership(obj, login_session):
"""
This function helps to check if the current logged in user
is the creator of the given category or a given item.
This function return True if the current user owns the category,
otherwise, it will return False.
"""
# the user has logged in at ... | 851d2dafae633ed92698af525b1c717091edb2b7 | 13,635 |
import logging
def transform_file_name(original_file_name):
"""
Now, this is just whatever I felt like. Whee.
So in this function I could have just used 0 and 1 as my indices directly when I look at the different parts of
the file name, but it's generally better to name these sorts of things, so peop... | daa5b3be0ae7a40c9d20ac4a8aa37c51dec89c89 | 13,637 |
import pandas
def remove_overlapping_cells(graph):
"""
Takes in a graph in which each node is a cell and edges connect cells that
overlap eachother in space. Removes overlapping cells, preferentially
eliminating the cell that overlaps the most cells (i.e. if cell A overlaps
cells B, C, and D, wher... | bd133c5ddd59f950d34ba16fb7bc3ff0215f0cf2 | 13,638 |
def main_page(request) :
"""Renders main page and gets the n (matrix demension number)"""
if request.method != 'POST' :
form = InputForm()
else :
form = InputForm(data=request.POST)
if form.is_valid() :
return redirect('calculator:set_demensions')
context ... | a6131ea837c8d9b986e8579a40ada1f7a0a3bb64 | 13,639 |
def int2fin_reference(n):
"""Calculates a checksum for a Finnish national reference number"""
checksum = 10 - (sum([int(c) * i for c, i in zip(str(n)[::-1], it.cycle((7, 3, 1)))]) % 10)
return "%s%s" % (n, checksum) | f21e66cb917631797d62ecc8ba2728b18d36ae1c | 13,640 |
def COLSTR(str, tag):
"""
Utility function to create a colored line
@param str: The string
@param tag: Color tag constant. One of SCOLOR_XXXX
"""
return SCOLOR_ON + tag + str + SCOLOR_OFF + tag | abe3d9111a30ebb678d1f1a2011d3b8a3ad39a75 | 13,641 |
def get_instance_pricing(instance_types):
"""
Get the spot and on demand price of an instance type
in all the regions at current instant
:param instance_types: EC2 instance type
:return: a pandas DataFrame with columns as
region, spot price and on demand price
"""
all_regions = ... | 62dba0e3c3f46ac460178da0bc4d615869819f83 | 13,642 |
import itertools
async def get_user_groups(request):
"""Returns the groups that the user in this request has access to.
This function gets the user id from the auth.get_auth function, and passes
it to the ACL callback function to get the groups.
Args:
request: aiohttp Request object
Ret... | 9fd62d6f971c871ce290700f3abb7eb467692533 | 13,643 |
def plot_bivariate_correlations(df, path=None, dpi=150):
"""
Plots heatmaps of 2-variable correlations to the Target function
The bivariate correlations are assmebled using both the arithmatic and geometric means for
two subplots in the figure.
Parameters
----------
df: dataframe
path: ... | d5dc7da98228aa7b7865510bd4dcd6531e7049bc | 13,644 |
from torch.utils.data import DataLoader
def create_datastream(dataset_path, **kwargs):
""" create data_loader to stream images 1 by 1 """
if osp.isfile(osp.join(dataset_path, 'calibration.txt')):
db = ETH3DStream(dataset_path, **kwargs)
elif osp.isdir(osp.join(dataset_path, 'image_left')):
... | 145f8c44e8e718fea9a9bdabf5e1f9497a00241a | 13,645 |
def is_contained(target, keys):
"""Check is the target json object contained specified keys
:param target: target json object
:param keys: keys
:return: True if all of keys contained or False if anyone is not contained
Invalid parameters is always return False.
"""
if not target or not key... | 948196d4b470788199506bd7768e03554fa67b40 | 13,646 |
def map(x, in_min, in_max, out_min, out_max):
"""
Map a value from one range to another
:param in_min: minimum of input range
:param in_max: maximum of input range
:param out_min: minimum of output range
:param out_max: maximum of output range
:return: The value scaled ... | 4117af35b0061df1fd271306accf198692442dac | 13,647 |
import requests
def get_points(sess: requests.Session, console: Console, status: Status, projectID: int):
"""
Get all exisiting points in a project
"""
base_url = f"https://mapitfast.agterra.com/api/Points"
resp = sess.get(base_url, params={"projectId": projectID})
points_obj_list = list()
... | c5f1fce542b06d1680637750f51c3bd7a6e6ebc4 | 13,648 |
def calculate_discounted_returns(rewards):
"""
Calculate discounted reward and then normalize it
(see Sutton book for definition)
Params:
rewards: list of rewards for every episode
"""
returns = np.zeros(len(rewards))
next_return = 0 # 0 because we start at the last timestep
for... | 538c3d5636bc6105ddf603f0928e4e891fea774c | 13,649 |
def parse_binskim_old(bin_an_dic, output):
"""Parse old version of binskim."""
current_run = output['runs'][0]
if 'results' in current_run:
rules = output['runs'][0]['rules']
for res in current_run['results']:
if res['level'] != 'pass':
if len(res['formattedRuleMe... | bd927aa972148b1171dcf2d5c60aa219cf4527b6 | 13,651 |
import operator
def binary_elementwise_compute(
ifm: te.Tensor,
ifm2: te.Tensor,
lut: te.Tensor,
operator_type: str,
ifm_scale: float,
ifm_zero_point: int,
ifm2_scale: float,
ifm2_zero_point: int,
ofm_scale: float,
ofm_zero_point: int,
ifm_channels: int,
ifm2_channels: ... | 2bbac91e8606512180b6a652538eeac23e369c7c | 13,652 |
def x_power_dependence(n, dep_keys, ctfs=list(), force_zero=None, **kwargs):
"""Returns a fit function that allows x^n depdendence on the constants
associated with each of the dep_keys
y(x) = (a0 * b0 + a1 * b1 + ...) * x^n
where each of the a's are fit parameters and each of the b's are either
... | 49b1a605001003b52f38f7f469a7c7bfafd43d6b | 13,653 |
from typing import Iterable
def get_subseqs(s, ops):
"""Returns a list of sequences given when applying the list of (ops)
on them, until a constant one is found, thus:
new[0] = next seq of s with ops[0]
new[i] = next seq of new[i-1] with op[i]
If 'ops' is not a list, then the s... | 3ad7a955c7b55596f327ae52d34368451ef79737 | 13,654 |
def update_s(C,k):
"""
Args: C: 2d array
k: 1d array
Return: 1d array
"""
if np.shape(C)[0]==0:
s = np.array([1])
else:
temp = np.dot(C,k)
s = np.append(temp,1)
return s | ce4604d71b05d328d6b8b60bea9f611d8d12f6eb | 13,656 |
def test_handler_callback_failure():
"""Test failure mode for inappropriate handlers."""
class BadHandler(object):
def handler(self, one):
return 'too many'
ob = EventTest()
handler = BadHandler()
with pytest.raises(TypeError):
ob.PublicEvent += handler.handler
... | c5d8daf4cca81ef8dee8ba5a10b9e572899bd23e | 13,657 |
def get_chord_type(chord):
"""'Parses' input for a chord and returns the type of chord from it"""
cleaned_chord = chord[1:]
cleaned_chord = cleaned_chord.replace('b', '')
cleaned_chord = cleaned_chord.replace('#', '')
mapping = {
'7': 'seven',
'9': 'nine',
'm7': 'minor7',
... | 4a753eb31f1e33340a7aa4df6942c4752b208fdd | 13,658 |
from typing import Union
def transpile(model: Union[SympyOpt, Model]) -> SympyOpt:
"""Transpile optimization problem into SympyOpt model
Only accepts SympyOpt or Docplex model.
:param model: model to be transpiled
:raises ValueError: if the argument is of inappropriate type
:return: transpiled m... | f2b4895cb980e535166d9749eb93925722981828 | 13,660 |
def definition():
"""View of the finances with subtotals generated."""
return sql.format(source=source) | c0b9add49b9c7403328449b8989e29739be267a9 | 13,661 |
import math
def random_mini_batches(X, Y, mini_batch_size = 32, seed = 0):
"""
Creates a list of random minibatches from (X, Y)
Arguments:
X -- input data, of shape (input size, number of examples) (m, Hi, Wi, Ci)
Y -- true "label" vector (containing 0 if control, 1 if case), of shape (1, number ... | 8baa63be638a1706c49176a51013524594a59452 | 13,662 |
def file_base_features(path, record_type):
"""Return values for BASE_SCHEMA features."""
base_feature_dict = {
"record_id": path,
"record_type": record_type,
# "utc_last_access": os.stat(path).st_atime,
"utc_last_access": 1600000000.0,
}
return base_feature_dict | 12f16684002892d7af59a1e26e8a40501098ca4f | 13,663 |
def split_ref(ref):
"""
セル参照をセル文字と1ベース行番号文字に分割する。
Params:
ref(str):
Returns:
Tuple[str, str]: 列、行
"""
m = re_cellref.match(ref)
if m:
return m.group(1), m.group(2)
return None, None | 1ae8e058a47ad0410b7131d4b89061dea822ed68 | 13,664 |
def table_definition(dataset):
"""print an azure synapse table definition for a kartothek dataset"""
index_col = list(dataset.dataset_metadata.index_columns)[
0
] ##works only with one index column
cols = synapse_columns(
dataset.dataset_metadata.table_meta[dataset.table], index_col
... | 75a2f55fa31025899e9adb05e20dbc89ae8dabd4 | 13,665 |
import itertools
def node_extractor(dataframe, *columns):
"""
Extracts the set of nodes from a given dataframe.
:param dataframe: dataframe from which to extract the node list
:param columns: list of column names that contain nodes
:return: list of all unique nodes that appear in the provided data... | 7a4ab889257a0f2c5ddfe18e65d0a7f5f35d8d98 | 13,667 |
def _get_bag(environ, bag_name):
"""
Get the named bag out of the store.
"""
store = environ['tiddlyweb.store']
bag = Bag(bag_name)
try:
bag = store.get(bag)
except NoBagError as exc:
raise HTTP404('%s not found, %s' % (bag.name, exc))
return bag | db4e2425f6c4d839fa091c08b524ea8ecd3c7c27 | 13,668 |
def missing_values_operation(files):
"""Will take iterable file objects and eliminate features or samples with missing values or inputing missing values if necessary"""
for i in files:
with open(i,'rw') as f:
if missing_values(f)==True:
file_data=load_data(i)
... | df5a6f6809605107db9b008b877fa913a3dc686d | 13,669 |
def _object_id(value):
"""Return the object_id of the device value.
The object_id contains node_id and value instance id
to not collide with other entity_ids.
"""
object_id = "{}_{}".format(slugify(_value_name(value)),
value.node.node_id)
# Add the instance id if... | 34c21de533a99ffdabfdabf21540492f7ce33b7f | 13,670 |
def _apply_attention_constraint(
e, last_attended_idx, backward_window=1, forward_window=3
):
"""Apply monotonic attention constraint.
**Note** This function is copied from espnet.nets.pytorch_backend.rnn.attention.py
"""
if e.size(0) != 1:
raise NotImplementedError(
"Batch atten... | 213ef514a9cff31134185e38c57d46921eba763a | 13,671 |
from bs4 import BeautifulSoup
import re
def parse_reolink(email):
"""Parse Reolink tracking numbers."""
tracking_numbers = []
soup = BeautifulSoup(email[EMAIL_ATTR_BODY], 'html.parser')
links = [link.get('href') for link in soup.find_all('a')]
for link in links:
if not link:
c... | cc96d35edb2ace40d83464f4cc3bed1c91480f0f | 13,673 |
def HMF(state, Delta, N):
"""Computes the result of the MF hamiltonian acting on a given state."""
#kinetic term: sum_i(eps(i)*(n_i,up + n_i,down))
kinetic_state = dict_list_sum(
[dict_prod(eps(i, N), dict_sum(number_op(state, i, 0, N), number_op(state, i, 1, N))) for i in range(N)])
#interaction term: sum_i( ... | 3c608d42a328e05fd59c55cbaeded3b6d0b4970b | 13,674 |
def calculate_probability_of_multicoincidence(ambient_size: int = 0,
set_sizes: tuple = (),
intersection_size: int = 0):
"""
Calculates the probability that subsets of a set of a given size, themselves of
prescribed ... | 1d9deb083f0a0397b067f6efa989a94d68d11b69 | 13,675 |
def check_date(option, opt, value):
"""check a file value
return the filepath
"""
try:
return DateTime.strptime(value, "%Y/%m/%d")
except DateTime.Error :
raise OptionValueError(
"expected format of %s is yyyy/mm/dd" % opt) | 3f817bf2286b459b11ded67abba33b654b090caf | 13,676 |
def no_cloud_fixture():
"""Multi-realization cloud data cube with no cloud present."""
cloud_area_fraction = np.zeros((3, 10, 10), dtype=np.float32)
thresholds = [0.265, 0.415, 0.8125]
return cloud_probability_cube(cloud_area_fraction, thresholds) | 5128c40485fdbc9c8646bec25d1949aac4cddb58 | 13,677 |
from typing import Iterable
def make_slicer_query(
database: Database,
base_table: Table,
joins: Iterable[Join] = (),
dimensions: Iterable[Field] = (),
metrics: Iterable[Field] = (),
filters: Iterable[Filter] = (),
orders: Iterable = (),
):
"""
Creates a pypika/SQL query from a lis... | 31821bdbb0ab94c8971a70d35c1165f5245d90fb | 13,678 |
def build_grid_generator(cfg, input_shape):
"""
Built an grid generator from `cfg.MODEL.GRID_GENERATOR.NAME`.
"""
grid_generator = cfg.MODEL.GRID_GENERATOR.NAME
return GRID_GENERATOR_REGISTRY.get(grid_generator)(cfg, input_shape) | 5f6edbaeece026fc56068aec0fc75549a71ce4a8 | 13,679 |
def main_page(request):
"""
This function is used to display the main page of programme_curriculum
@param:
request - contains metadata about the requested page
"""
return render(request, 'programme_curriculum/mainpage.html') | fdee3342d369112abb2560c4ecfda17a8dfe01e4 | 13,680 |
def _write_detailed_dot(graph, dotfilename):
"""Create a dot file with connection info
digraph structs {
node [shape=record];
struct1 [label="<f0> left|<f1> mid\ dle|<f2> right"];
struct2 [label="<f0> one|<f1> two"];
struct3 [label="hello\nworld |{ b |{c|<here> d|e}| f}| g | h"];
struct1:f1... | 793983b56b8fff32fde4e9dc5379a93e4edcb16e | 13,681 |
import functools
def ResidualBlock(name, input_dim, output_dim, filter_size, inputs, resample=None, he_init=True, bn=False):
"""
resample: None, 'down', or 'up'
"""
if resample=='down':
conv_shortcut = MeanPoolConv
conv_1 = functools.partial(lib.ops.conv2d.Conv2D, input_dim=inpu... | 8871553f11975edef2a1b0bbf96aff8c54417adf | 13,682 |
def timer(func):
"""Logging elapsed time of funciton (decorator)."""
@wraps(func)
def wrapper(*args, **kwargs):
with timing(func.__name__):
return func(*args, **kwargs)
return wrapper | eb38d9856f59328188ac24e66f3bb4f9356ebe89 | 13,684 |
def peak_ana(x, y, nb=3, plotpoints_axis=None):
""" nb = number of point (on each side) to use as background"""
## get background
xb = np.hstack((x[0:nb], x[-(nb):]))
yb = np.hstack((y[0:nb], y[-(nb):]))
a = np.polyfit(xb, yb, 1)
b = np.polyval(a, x)
yf = y - b
yd = np.diff(yf)
## d... | 1f9ea444b09684ac7764ced8ba5ca3fdbd3e8593 | 13,685 |
from jams.distributions import sep_fs_mean, sep_fs_std
def sample_sep01(nn, xi=1., beta=0.):
"""
Samples from the skew exponential power distribution with location zero and scale one.
Definition
----------
def sample_sep01(nn, xi=1., beta=0.):
Input
-----
... | dbeda8efa38db5d55b688c4bfc30350262c39f32 | 13,687 |
def pandas_from_feather(file: str = None) -> pd.DataFrame:
""" Load a feather file to a pandas DataFrame.
Uses pyarrow to load a csv file into a [pyarrow.Table](https://arrow.apache.org/docs/python/generated/pyarrow.Table.html) and convert to pandas format.
Args:
file (str): the feathe... | 2bd7679581690095865d9f9d2cae85cf9d736f8d | 13,688 |
def email_coas():
"""
Email certificates of analysis to their recipients.
"""
# Get the certificate data.
# Email links (optional attachments) to the contacts.
return NotImplementedError | b09c6650c498618b77a5e0beab0caf63a2cbf99d | 13,690 |
import random
def dropout(x, key, keep_rate):
"""Implement a dropout layer.
Arguments:
x: np array to be dropped out
key: random.PRNGKey for random bits
keep_rate: dropout rate
Returns:
np array of dropped out x
"""
# The shenanigans with np.where are to avoid having to re-jit if
# keep ... | f9686e64a11e17ca35eefacaa8f0b356cc0f065e | 13,691 |
def band_spd_spin_polarized(
folder,
output='band_spd_sp.png',
scale_factor=2,
order=['s', 'p', 'd'],
color_dict=None,
legend=True,
linewidth=0.75,
band_color='black',
unprojected_band_color='gray',
unprojected_linewidth=0.6,
fontsize=7,
annotations=['$\\uparrow$ ', '$\\d... | 4cd0ef74a2ad4ce46d28aad296a9156ec91dc301 | 13,692 |
def initial_queries(bo):
"""
script which explores the initial query points of a BayesianOptimization
instance, reports errors to Slack
Input: instance of a BayesianOptimization
"""
# loop to try a second time in case of error
errcount = 0
for i in range(2):
try:
bo.m... | 3419cd89724a23296688f321469a68c8209d2a25 | 13,693 |
def cell2AB(cell):
"""Computes orthogonalization matrix from unit cell constants
:param tuple cell: a,b,c, alpha, beta, gamma (degrees)
:returns: tuple of two 3x3 numpy arrays (A,B)
A for crystal(x) to Cartesian(X) transformations A*x = np.inner(A,x) =X
B (= inverse of A) for Cartesian to c... | 970acf484a701efcdb024e7cad5981ded314209e | 13,695 |
def sendMessage(qry):
"""
Message sending handling, either update if the query suggests it otherwise send the message.
:param qry: current query
:return: Status of Message sending.
"""
try: getUserName()
except: return _skypeError()
if(qry == "skype update"):
_writeFriends()
... | c13e187170015d3e9a786ceb7cb9a364928fa8c0 | 13,697 |
def scrape_detail_page(response):
"""
get detail page info as dict type
"""
root = lxml.html.fromstring(response.content)
ebook = {
'url': response.url,
'title': root.cssselect('#bookTitle')[0].text_content(),
'price': root.cssselect('.buy')[0].text,
'content': [h3.te... | 5c3b7e743cd109fe2d05e0cc261e46884c673421 | 13,698 |
import tqdm
from pathlib import Path
import torch
def reload_from_numpy(device, metadata, reload_dir):
"""Reload the output of voice conversion model."""
conv_mels = []
for pair in tqdm(metadata["pairs"]):
file_path = Path(reload_dir) / pair["mel_path"]
conv_mel = torch.load(file_path)
... | 7cf5b2c1f12886f8fcded9072a86c53384b93760 | 13,699 |
def jaccard_similarity_coefficient(A, B, no_positives=1.0):
"""Returns the jaccard index/similarity coefficient between A and B.
This should work for arrays of any dimensions.
J = len(intersection(A,B)) / len(union(A,B))
To extend to probabilistic input, to compute the intersection, use ... | fe408565827f61323513d7d3b562bd79a23e47ec | 13,700 |
def get_argument_from_call(call_node: astroid.Call,
position: int = None,
keyword: str = None) -> astroid.Name:
"""Returns the specified argument from a function call.
:param astroid.Call call_node: Node representing a function call to check.
:param int... | e4b7e054c4728f5b74bcbbe1678816a910f64bda | 13,701 |
def snake_string(ls):
"""
Question 7.11: Write a string sinusoidally
"""
result = []
strlen = len(ls)
for idx in xrange(1, strlen, 4):
result.append(ls[idx])
for idx in xrange(0, strlen, 2):
result.append(ls[idx])
for idx in xrange(3, strlen, 4):
result.append(l... | 391f7cef4289c5746f77598501aeaa7ae93d31bc | 13,702 |
def _prepare_memoization_key(args, kwargs):
"""
Make a tuple of arguments which can be used as a key
for a memoized function's lookup_table. If some object can't be hashed
then used its __repr__ instead.
"""
key_list = []
for arg in args:
try:
hash(arg)
key_li... | c83e08c42886ba0e7f6e4defe5bc8f53f5682657 | 13,703 |
def kl_divergence_with_logits(p_logits = None,
q_logits = None,
temperature = 1.):
"""Compute the KL between two categorical distributions from their logits.
Args:
p_logits: [..., dim] array with logits for the first distribution.
q_logits: [..., ... | 1950dea9e5c6d040ce464e0861b09469742810c4 | 13,704 |
from typing import Any
from datetime import datetime
def convert_bosch_datetime(dt: Any = None) -> datetime:
"""Create a datetime object from the string (or give back the datetime object) from Bosch. Checks if a valid number of milliseconds is sent."""
if dt:
if isinstance(dt, str):
if dt.... | 845e9de019b700b2ab37ebb4a1b577d0bd068638 | 13,705 |
def day_log_add_id(day_log):
"""
その日のログにID(day_id)を割り振る
:param day_log:
:return:
"""
for v in range(len(day_log)):
day_log[v]['day_id'] = v + 1
return day_log | c4608b07e86c074a11cf78d171490ec152092eeb | 13,706 |
def cisco_ios_l3_acl_parsed():
"""Cisco IOS L3 Interface with ip address, acl, description and vlan."""
vlan = Vlan(id="300", encapsulation="dot1Q")
ipv4 = IPv4(address="10.3.3.13", mask="255.255.255.128")
acl_in = ACL(name="Common_Client_IN", direction="in")
acl_out = ACL(name="TEST_ACL_03", direct... | 25c7ad34695499bb6426ff71a9893c233b54a925 | 13,707 |
def brillance(p, g, m = 255):
"""
p < 0 : diminution de la brillance
p > 0 : augmentation de la brillance
"""
if (p + g < m + 1) and (p + g > 0):
return int(p + g)
elif p + g <= 0:
return 0
else:
return m | b40169e487521c146c4c0777517492205951cf16 | 13,708 |
def payback(request):
"""
微信支付回调函数
:param request:
:return:
"""
return HttpResponse('payback') | e178abe0effe6359a664dca434e181390c1a56c1 | 13,710 |
from datetime import datetime
def get_index_shares(name, end_date=None):
"""获取某一交易日的指数成分股列表
symbols = get_index_shares("上证50", "2019-01-01 09:30:00")
"""
if not end_date:
end_date = datetime.now().strftime(date_fmt)
else:
end_date = pd.to_datetime(end_date).strftime(date_fmt)
... | 7a9e2890d0508b00d15da4688980736776199cfa | 13,711 |
def erfcx(x):
"""Elementwise scaled complementary error function.
.. note::
Forward computation in CPU cannot be done if
`SciPy <https://www.scipy.org/>`_ is not available.
Args:
x (:class:`~chainer.Variable` or :ref:`ndarray`): Input variable.
Returns:
~chainer.Variable... | 60f1655a6e390ca935f80d33e0d9156879b56c41 | 13,712 |
def fetch_data_async(blob, start_index, end_index, rpc=None):
"""Asynchronously fetches data for a blob.
Fetches a fragment of a blob up to `MAX_BLOB_FETCH_SIZE` in length. Attempting
to fetch a fragment that extends beyond the boundaries of the blob will return
the amount of data from `start_index` until the ... | 518f1ef45c19b8a7be55940d9abdeaf0fe014835 | 13,713 |
def get_legal_moves(color, size, board):
"""
Get Legal Moves
"""
legal_moves = {}
for y in range(size):
for x in range(size):
reversibles = get_reversibles(color, size, board, x, y)
if reversibles:
legal_moves[(x, y)] = reversibles
return legal_... | eaab0b7fededbe660b02974f675877b97e3327f4 | 13,714 |
def edition(self, key, value):
"""Translates edition indicator field."""
sub_a = clean_val("a", value, str)
if sub_a:
return sub_a.replace("ed.", "")
raise IgnoreKey("edition") | 715724dffb4ef6d72c173afbf8186acfdf9f20e3 | 13,715 |
from typing import Dict
from typing import Set
import itertools
def get_site_data(hostname: str) -> SiteData:
"""Get metadata about a site from the API"""
url = f"https://{hostname}/w/api.php"
data = dict(
action="query",
meta="siteinfo",
siprop="|".join(
[
... | 83ca853c6fb2ebadf6473b8f5da0008b145717b0 | 13,716 |
def clear_monitor(nodenet_uid, monitor_uid):
"""Leaves the monitor intact, but deletes the current list of stored values."""
micropsi_core.runtime.get_nodenet(nodenet_uid).get_monitor(monitor_uid).clear()
return True | ad39c344f41fcf307f85d09add71eeeac66b30c1 | 13,717 |
def loadGrammarFrom(filename, data=None):
"""Return the text of a grammar file loaded from the disk"""
with open(filename, 'r') as f:
text = f.read()
lookup = mako.lookup.TemplateLookup(directories=[relativePath('grammars')])
template = mako.template.Template(text, lookup=lookup)
#
base_... | 0a0bbd0f2af5db4c673d7dbd31259a3977adb9cf | 13,718 |
def create_generator_selfatt(generator_inputs, generator_outputs_channels, flag_I=True):
"""
Add Conditional Self-Attention Modual to the U-Net Generator.
By default, 256x256 => 256x256
Args:
generator_inputs: a tensor of input images, [b, h, w, n], with each pixel value [-1, 1].
generator_... | bfcc81955c7849e84053c45ea7a593570059bf28 | 13,719 |
def by_tag(articles_by_tag, tag):
""" Filter a list of (tag, articles) to list of articles by tag"""
for a in articles_by_tag:
if a[0].slug == tag:
return a[1] | 642472a89cb624ed02a6e8ec488b72856ac231a9 | 13,720 |
def experiment(dataset='SUPPORT', quantiles=(0.25, 0.5, 0.75), prot_att='race',
groups=('black', 'white'), model='dcm', adj='KM',
cv_folds=5, seed=100, hyperparams=None, plot=True, store=False):
"""Top level interface to train and evaluate proposed survival models.
This is the top le... | 79ec44d4d62a42dea4f7e612cd4291ce8fbc5585 | 13,721 |
def ldns_str2rdf_type(*args):
"""LDNS buffer."""
return _ldns.ldns_str2rdf_type(*args) | d121f8534c64b7597d775e5443b706c962ec738a | 13,722 |
import hashlib
import _crypt
def scramble(password, message):
"""scramble message with password"""
scramble_length = 20
sha_new = partial(hashlib.new, 'sha1')
if not password:
return b''
stage1 = sha_new(password).digest()
stage2 = sha_new(stage1).digest()
buf = sha_new()
buf.... | 9ad006a5626d7b4ca3f8220dc4cbdd719a3cbac8 | 13,723 |
def dp_port_id(switch: str, port: str) -> str:
"""
Return a unique id of a DP switch port based on switch name and port name
:param switch:
:param port:
:return:
"""
return 'port+' + switch + ':' + port | 479891e41b51114744dcbb2b177180c19cd1bfd5 | 13,724 |
import requests
def request_item(zip_code, only_return_po_boxes=False, spatial_reference='4326'):
"""
Request data for a single ZIP code, either routes or PO boxes.
Note that the spatial reference '4326' returns latitudes and longitudes of results.
"""
url = BASE_URL.format(
zip_code=str(... | 956a2a86f0960a888046bfd5a8e3c2d7c56bc9dc | 13,725 |
def smoothen_histogram(hist: np.array) -> np.array:
""" Smoothens a histogram with an average filter.
The filter as defined as multiple convolutions
with a three-tap box filter [1, 1, 1] / 3.
See AOS section 4.1.B.
Args:
hist: A histogram containing gradient orientation counts.
... | bdcc5de3df5aa2aad33653cce237f7f07d825b9d | 13,726 |
from typing import Tuple
def end_point(min_radius: float, max_radius: float) -> Tuple[int, int]:
"""
Generate a random goal that is reachable by the robot arm
"""
# Ensure theta is not 0
theta = (np.random.random() + np.finfo(float).eps) * 2 * np.pi
# Ensure point is reachable
r = np.rando... | 8d6a79195108e8354fad986f93da5f089b6df0d7 | 13,727 |
def expand_tile(value, size):
"""Add a new axis of given size."""
value = tf.convert_to_tensor(value=value, name='value')
ndims = value.shape.ndims
return tf.tile(tf.expand_dims(value, axis=0), [size] + [1]*ndims) | 50adf652fff47418d1f8f1250a2a6d01f712da76 | 13,728 |
from typing import Mapping
from typing import Any
def parse_header(
info: Mapping[str, Any],
field_meta_data: Mapping[str, FieldMetaData],
component_meta_data: Mapping[str, ComponentMetaData]
) -> Mapping[str, MessageMemberMetaData]:
"""Parse the header.
Args:
info (Mapping[st... | a8043c62070c540712074c60e01e3c9c3ebfe99b | 13,729 |
def amina_choo(update, context): #3.2.1
"""Show new choice of buttons"""
query = update.callback_query
bot = context.bot
keyboard = [
[InlineKeyboardButton("Yes", callback_data='0'),
InlineKeyboardButton("No", callback_data='00')],
[InlineKeyboardButton("Back",callback_data='3.... | b43d2e6d63e111b9a2f70fd71e5da765ef923746 | 13,730 |
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