content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def normalize_time_window(time_window, values_per_time_point):
"""
Bring all values in time window to -1, 1 range and center them around 0.
:param time_window: vector of values for set of time points
:param values_per_time_point: number of numeric values describing one time
... | 4ee9fb63dfe30736f4c33ab1d97bd49d1f4aa944 | 71,234 |
def mean(nums):
"""
Gets mean value of a list of numbers
:param nums: contains numbers to be averaged
:type nums: list
:return: average of nums
:rtype: float or int
"""
counter = 0
for i in nums:
counter += i
return counter / len(nums) | d3ea7af8792f4fdd503d5762b5c0e54765ce2d99 | 71,235 |
def process_data(dr): # 统一输入单词的长度，不足补0，此方法会增加训练时间
"""
:param dr: class data reader
:return: process X, Y
"""
return dr.XTrain, dr.XTest, dr.YTrain, dr.YTest # 这是为了统一一个表达方式，和之前的章节一样 | cc05605d77e25ed7363da3de9407d1f51b7dbf4b | 71,236 |
def conv_block(x, growth_rate, name, activation,
momentum, epsilon):
"""Convolutional block defined in Densenet architecture,
It is its base layers
Args:
x: input tensor form the precedent layer
growth_rate : float number, growth rate or number of filters (ref. paper)
... | 125597246999c38630c8c9392e0ef874dbe863df | 71,237 |
def question_2(data):
"""
Plots 2 graphs: Temperature change as a function of 'DayOfYear', and STD of daily
temperatures as a function of 'Month'.
Parameters
----------
data: preprocessed of city temperature dataset
Returns
-------
A tuple of:
1. A design matrix... | 610067d77957ef36170e97d7152e2e1bc1b84e11 | 71,238 |
def map_id_to_value(nodes, value):
"""Maps Node id to another value"""
return remove_colons(nodes).set_index('id')[value].to_dict() | b1f20a25df51cd93d13e16de197affbb768908e9 | 71,239 |
def PlotAA(df, eom=9, show_plot=True):
"""
Summary
-------
Plot of annual average bar chart.
No documentation as of 2018-10-31.
Future Development
------------------
1. Add comma separator to y-axis.
2. Add option to view by Sacramento Index Water Year Types.
"""
# Obtain ... | b258b0ecee7676a994558d9b2f89583b89a425b3 | 71,240 |
from .parser import read
def df_from_sas(target, meta_df, skiprows=None, nrows=None, chunksize=None):
"""Deprecated. Use pyhcup.parser.read()"""
print "WARNING: pyhcup.sas.df_from_sas() is deprecated and is scheduled for removal in pyhcup 0.1.6; use pyhcup.parser.read()"
result = read(target, meta_df... | 4afd2fd61dcd6af489cb63977ff8ad1dc222749d | 71,241 |
def all(functions):
"""Returns function that returns True when all components return True."""
def apply_to(*args, **kwargs):
return conjoin(functions, *args, **kwargs)
return apply_to | 6279be8d9e1977454e24d35d3cc94228f64dda35 | 71,242 |
def CombineProvenanceConst_get_decorator_type_name():
"""CombineProvenanceConst_get_decorator_type_name() -> std::string"""
return _RMF.CombineProvenanceConst_get_decorator_type_name() | 6542246ac76545da6f98ada6f15653850b6ccc5e | 71,243 |
def BuildVRTInternalObjects(*args):
"""
BuildVRTInternalObjects(char const * dest, int object_list_count, GDALBuildVRTOptions options, GDALProgressFunc callback=0,
void * callback_data=None) -> Dataset
"""
return _gdal.BuildVRTInternalObjects(*args) | e5eb1aef230c79e6ff68a8f57fed0ef106c2e181 | 71,244 |
from typing import Tuple
def _has_line_of_sight(matrix: np.ndarray, start: Tuple[int, int],
end: Tuple[int, int]) -> bool:
"""
Return True if two points on a grid have line of sight.
Return True if start == end.
"""
if start == end:
return True
start_y, start_x ... | fa9ecdb54fba90c43586f710b58bc51f37992048 | 71,245 |
def threshold1(x, col, thresh):
""" 1-dimensional classification using a threshold function.
"""
return x[:, col] <= thresh | 5814ab93fe41e2e92f4648bfee1f8033ff0864b6 | 71,246 |
import torch
def compute_rank(predictions, targets):
"""Compute the rank (between 1 and n) of of the true target in ordered predictions
Example:
>>> import torch
>>> compute_rank(torch.tensor([[.1, .7, 0., 0., .2, 0., 0.],
... [.1, .7, 0., 0., .2, 0., 0.],
... | 0aed5b14ef9b0f318239e98aa02d0ee5ed9aa758 | 71,249 |
def load_dataset(dataset_path, sequence_length, src_vocab_file, tgt_vocab_file, batch_size, buffer_size):
"""Create a tf.data Dataset.
Args:
dataset_path: Path to the files to load text from
sequence_length: Maximun Length of the Sequence
vocab_file: Location of vocab file
batch... | b831403cbdf3ee2351aab72099031cf3dd780af7 | 71,250 |
def udfize_lambda_string(code: str):
"""Return a string with the code as a function"""
return "lambda input: ({})".format(code)
# return "lambda input: (%s)" % code | c519c8ec408b00f033878b6083d4a922f32d2ac9 | 71,253 |
import json
def load_scalabel_frames( scalabel_frames_path ):
"""
Loads Scalabel frames from a file. Handles both raw sequences of Scalabel frames
as well as labels exported from Scalabel.ai's application.
Raises ValueError if the data read isn't of a known type.
Takes 1 argument:
scalab... | 7e5467d0f184dba1e3efc724391931ed4053a683 | 71,254 |
def ovs_version_str(host):
""" Retrieve OVS version and return it as a string """
mask_cmd = None
ovs_ver_cmd = "ovs-vsctl get Open_vSwitch . ovs_version"
with host.sudo():
if not host.exists("ovs-vsctl"):
raise Exception("Unable to find ovs-vsctl in PATH")
mask_cmd = host.r... | 607ffbb2ab1099e86254a90d7ce36d4a9ae260ed | 71,255 |
def maximum_displacement(initial_velocity):
"""Derived from s = 0.5 u + u t + 0.5 a t^2 at t = u and a = -1.
The (0.5 u) term comes from the order of rules of the motion of the
probe, the displacement changes before the velocities are
updated."""
return int(0.5 * initial_velocity * (1 + initial_vel... | c4b71ad83d787cae9ad9abe7d044b0e2d66b9cc0 | 71,256 |
from typing import List
def csv_rows(s: str) -> List[List[str]]:
"""Returns a list of list of strings from comma-separated rows"""
return [row.split(',') for row in s.split('\n')] | 7a6ea8c0f69801cfb1c0369c238e050502813b63 | 71,257 |
import math
def getRotationMatrix(a, b, c):
""" Compute Rotation Matrix given RPY euler angles. """
# Roll
R_x = np.array([[1, 0, 0],
[0, math.cos(a), -math.sin(a)],
[0, math.sin(a), math.cos(a)]
])
# pitch
R_y = np.array([[math.cos(b),... | 5b68425a0b3244579528fd601b52c43add5de03e | 71,258 |
def GetMatchURL(soup):
"""Gets the ongoing match URL"""
live_match_url = soup.find("a", attrs={"class": "match-status-3"})["href"]
return live_match_url | bae3658c46976c7d43234e063d78eeea027d3095 | 71,260 |
def get_flattened_axes(x):
"""
Ordered list of axis visible to MKLDNN
"""
return Axes.as_flattened_list(x) | aa4ec87d1a2bbe254eb88f9356f1a76aaaf71f43 | 71,261 |
def get_service(service_name):
"""
Gets the service VerificationService, checks if there is already one in the
memory, if so return that one.
:param service_name: e.g. phone, email
"""
# Check if service_name in USER_VERIFICATIOn
if not settings.USER_VERIFICATION.get(service_name, None):
... | 38eeece00518fd638df8246878a597cee825bd5e | 71,262 |
def wait_to_fetch(ctx, interval):
"""Check if an unscored solution exists in a database by calling query every "interval" seconds.
:param ctx: Click context
:param interval: int: Interval to access a database (second)
:return solution_id: ID of a solution that has not been scored.
"""
w... | 372da8b7e4c19b6d2d0f728753a1584a3ccd40cb | 71,263 |
def ctab2inchiKey():
"""
Converts CTAB to InChi Keys. CTAB is either single molfile or SDF file.
cURL examples:
curl -X POST --data-binary @aspirin.mol ${BEAKER_ROOT_URL}ctab2inchiKey
curl -X POST -F "file=@aspirin.mol" ${BEAKER_ROOT_URL}ctab2inchiKey
"""
data = list(request.files.values())[0].fil... | 8cadc1683e4f644f673751e95f560a45822593a4 | 71,264 |
def matmul(a: ndarray,
b: ndarray) \
-> ndarray:
"""
Matrix product of two arrays.
"""
return ndarray(af.matmul(a._af_array, b._af_array)) | afdf18f72fcaf915e32b829d696eb605887254d1 | 71,266 |
def flam2epp(lam, flam, ddisp):
"""
Convert flux density [erg/s/cm2/A] to photons per pixel [photons/s/cm2/pixel]
Args:
lam (array-like):
wavelength array associated to the spectrum
flam (array-like):
spectrum in units of erg/s/cm2/A
ddisp (float):
... | 4018c7346bf842b93f25a72b4249269ad245f31b | 71,267 |
def demo_delete(id, **kwargs):
"""
swagger_from_file: Swagger/demo/del.yml
"""
return quickly_del(Demo, id) | 499045763cecd62e67334045b031929de61c5070 | 71,268 |
from numpy import sum
def load_LSRK(file,lstype='2S',has_emb=False):
"""
Load low storage methods of the types 2S/2S*/3S*/2S_pair/3S_pair
from a file containing the low-storage coefficient arrays.
If has_emb=True, the method has an embedded method that
requires an extra register.
... | c8bef2e6973f73720c10e757cd01e536d027c67c | 71,270 |
import calendar
def create_disjunctive_constraints(solver, flat_vars):
"""
Create constrains that forbids multiple events from taking place at the same time.
Returns a list of `SequenceVar`s, one for each day. These are then used in the first
phase of the solver.
"""
events_for_day = [[] for _... | f7f8592ac00c8cac9808bb80d425ff1c1cf10b9e | 71,271 |
def interp_quad(x, y, d, rLCFS, r):
"""Function 'interp' used for kinetic profiles.
"""
f = interp1d(x, np.log(y), kind="quadratic", assume_sorted=True, copy=False)
idx = np.searchsorted(r, rLCFS)
core = np.exp(f(np.clip(r[:idx] / rLCFS, 0, x[-1])))
edge = core[..., [idx - 1]] * np.exp(
... | d877c4521cc29046ca827f7235e2401d808b8257 | 71,272 |
def generateWalkJumpSample(adjacency_list, p, jump_probability):
"""
Generate random walk sample from real graph
"""
sample_network = dict()
nodes = set()
edges = set()
number_of_edges = sum([len(adjacency_list[u]) for u in adjacency_list.keys()]) / 2
desired_num_edges = int(p * number_o... | fa3c1ea0df20c97e2587c2f55e954a6680856d9b | 71,273 |
def pick_cluster(session,picks,pickwindow,pickaveraging_norm,counter):
"""
Cluster picks from different components on the same station.
"""
# | | /\
# | | / \ /\
# | | /\ /\ / ... | 00ad6ca61efbd7093c827b0d57271c41ece1bc22 | 71,274 |
def echo():
"""
Method used to test how Python is handling PowerBuilder requests.
Will decode data sent from PB and return it to the requester.
:return: Decoded data sent from the requester.
"""
try:
return request.data.decode("utf-8"), 200
except UnicodeDecodeError as why_ude:
... | 9b077c0603baef42dac91f7dd47020af110f2866 | 71,275 |
def minhash_xor_192(features_32, masks=PERMS_192_NP):
"""Numpy & Numba supported implementation"""
hashes = np.full(192, np.uint32(MAX_UINT32))
for f in features_32:
hashes = np.minimum(hashes, np.bitwise_xor(masks, f))
return hashes | 67d1c913bb6cc8596b04c19fb28deccfd76ba198 | 71,278 |
def fit_nelson_siegel_yield(tau, y, theta_0=None):
"""For details, see here.
Parameters
----------
tau : array, shape (n_,)
y : array, shape (n_,)
theta_0: array, shape (4,)
Returns
-------
theta : array, shape (4,)
"""
n_ = len(tau)
def minimization_... | feeeeef81cab003d006bf3d64076cf119c6f6c6f | 71,279 |
def magic_string(string: str, filename: str = None):
""" Returns tuple of (num_of_matches, array_of_matches)
arranged highest confidence match first
If filename is provided it will be used in the computation.
:param string: string representation to check
:param filename: original filename
:retu... | 8ce083418921a9a3da675a8ddbb144df29e096d2 | 71,280 |
import torch
def correct_resize_label(tensor, size):
"""
Resize torch.Tensor label
Parameters
----------
tensor : torch.Tensor
size : Tuple[int]
Returns
-------
resized_tensor : torch.Tensor
"""
device = tensor.device
tensor = tensor.detach().cpu()
resized = []
... | e2c6601e6c17fa894c0b6f83f61087d9f75e32b6 | 71,281 |
def read_data1(filename):
"""
This function reads the data from .txt file.
:param filename: reading directory
:return: lists of word_ids, words, emphasis probabilities, POS tags
"""
lines = read_lines(filename) + ['']
word_id_lst, word_id_lsts = [], []
post_lst, post_lsts = [], []
se... | c31de2ff853c799078468d675d7a7adf4bb2fa12 | 71,282 |
def workflow_add_tags(object_id, input_params={}, always_retry=True, **kwargs):
"""
Invokes the /workflow-xxxx/addTags API method.
For more info, see: https://documentation.dnanexus.com/developer/api/introduction-to-data-object-metadata/tags#api-method-class-xxxx-addtags
"""
return DXHTTPRequest('/... | 440d39e622f1dc6336118ce9704a187842e2ca06 | 71,283 |
def login(var=random.randint(0, 1000), error=None):
"""
The function can get a POST or GET requests.
if the request is GET: returns the html login_page template
if the request is POST: checks the data(email and password) in the users database.
"""
global clients_connecting
if request.method ... | 1e397ec4dc571f2c21893b70993c7b5a296293cb | 71,284 |
def get_body(request):
"""
Return the body of a concrete publication.
"""
context = request['context']
entities = request['entities']
feed = context['feed']
ordinal = entities['ordinal'][0]['value']
body = feed[ordinal]['summary_detail']['value']
context['body'] = body
return con... | 53080b1727f0230a30b9fc4435d455a06e927be3 | 71,285 |
def get_default_snapshot_id(project):
""" Generate a snapshot id from data on the given project.
:param project: project object
:return: snapshot id
"""
def snapshot_id_from_branch_name(name):
return "{}:HEAD".format(name.replace('/', ':'))
default_branch = project.git.get_default_branc... | 2c542678036541372fa675e61b4f5a969cd5ab0f | 71,286 |
import random
def filter_shuffle(seq):
"""
Basic shuffle filter
:param seq: list to be shuffled
:return: shuffled list
"""
try:
result = list(seq)
random.shuffle(result)
return result
except:
return seq | 3f2dce2133ba32d8c24d038afaecfa14d37cbd4e | 71,287 |
def read_vcf_file(vcf_file_address):
"""
Reading the vcf file
input: vcf file
outputs:
lines_list: list of string. each string is a line of phased vcf file.
var_pos_het_list: genomic position of phased hetrozygous variants in the vcf file.
line_number_het_list: list... | f4e9718d8fc21f5c1dc37aa570f6bf1615b82452 | 71,288 |
def ipd_download_new_or_modified(organizer: Organizer, info: IpdDownloadInfo) -> bool:
"""
Accepts new files or files with a more recent modification date.
"""
resolved_file = organizer.resolve(info.path)
if not resolved_file.exists():
return True
if not info.modification_date:
P... | 36cbf48347b6bc4e7557cb06f316dbd912ae6e44 | 71,289 |
def sushi_report_all(request):
"""Report from SUSHI, shared common data."""
return parse_sushi_file(request.param) | 9ae44e8ea80c74d1580662e9ce1bbd530214356a | 71,290 |
def get_package_list_from_file(path):
"""
Create a list of packages to install from a provided .txt file
Parameters
__________
path: Filepath to the text file (.txt) containing the list of packages to install.
Returns
______
List of filepaths to packages to install.
Notes
... | 91ef3e634e98afd116d2be9c803620f672acd950 | 71,291 |
def property_view(request, slug, property_id):
"""
"""
return render(request, 'property/property.html', {'slug': slug, 'id': property_id}) | 05b28046274cfb1f09bfbe9c352888202b4fb485 | 71,292 |
def read_comment_line(line, verbose=0):
"""
Use pyleri to parse an extxyz comment line
"""
result = grammar.parse(line)
parsed_part = result.tree.children[0].string
if not result.is_valid:
raise SyntaxError(f"Failed to parse entire input line, only '{parsed_part}'. "
... | dfdbea582dcfa14f5e3aefec89eb3959cde67685 | 71,293 |
def escaped_commands(line):
"""Transform escaped commands - %magic, !system, ?help + various autocalls.
"""
if not line or line.isspace():
return line
lineinf = LineInfo(line)
if lineinf.esc not in tr:
return line
return tr[lineinf.esc](lineinf) | 84dea2fba22c7a7da6d75e8257b597c68aab67ef | 71,294 |
def has_postgres() -> bool:
""" Whether to use postgres """
return find_spec("asyncpg") is not None | 0d6348f52fb01114bc57cc539d3874815da16ec8 | 71,295 |
def passthru(func):
"""Return value of function by same name in proxied object.
Proxied object is located as an attribute named `_wrapped` in proxy object.
"""
@wraps(func)
def _wrapper(self, *args, **kwargs):
name = func.__name__
return getattr(self._wrapped, func.__name__)(*args,... | bc33e482b9b0c46f4e48f9dbe1367e60d47f5d04 | 71,296 |
def _sources_from_virtual_sink_port(sink_port, _traversed=None):
"""
Resolve the source port that is connected to the given virtual sink port.
Use the get source from virtual source to recursively resolve subsequent ports.
"""
source_ports_per_virtual_connection = (
# there can be multiple p... | 3a378632702afe62166f5ee75b43ba930b712a75 | 71,297 |
def parse_jcamp_line(line,f):
"""
Parse a single JCAMP-DX line
Extract the Bruker parameter name and value from a line from a JCAMP-DX
file. This may entail reading additional lines from the fileobj f if the
parameter value extends over multiple lines.
"""
# extract key= text f... | 84061c3f4bc42a62e308d5f93877e5c55d85efc1 | 71,298 |
def get_grounded_agent(gene_name):
"""Return a grounded Agent based on an HGNC symbol."""
db_refs = {'TEXT': gene_name}
if gene_name in hgnc_map:
gene_name = hgnc_map[gene_name]
hgnc_id = hgnc_client.get_hgnc_id(gene_name)
if not hgnc_id:
hgnc_id = hgnc_client.get_current_hgnc_id(gen... | e4501fefe4d1617bd9d32679fd966b101708297d | 71,299 |
def _check_header(line, length):
"""check if headers
first_header_line :: <=>+
second_header_line :: <->+
normal_header :: <#>+<span_element>
"""
if length * '=' == line:
return {'prev_block_type': 'h1'}
if length * '-' == line:
return {'prev_block_type': 'h2'}
if length ... | 4674750c2c7bcd39327c1818a8d81f3e6671ec3b | 71,300 |
def power_spectrum(kx, ky, n):
"""
Calcs power specturm, which is proportional of k**n = (kx,ky)**n
:param kx:
:param ky:
:param n:
:return:
"""
if kx == 0 and ky == 0:
return 0
else:
return np.sqrt(kx ** 2 + ky ** 2) ** n | 1d0775bb55701fa7fa08066ed7c1ae5265d49fe2 | 71,301 |
def unwrapText(text):
"""Unwrap text to display in message boxes. This just removes all
newlines. If you want to insert newlines, use \\r."""
# Removes newlines
text = text.replace("\n", "")
# Remove double/triple/etc spaces
text = text.lstrip()
for i in range(10):
text = text.repl... | f37aafa3a003b3b06b8e9e1a03c833d05c5c0deb | 71,302 |
import urllib
import json
def get_sources(meals):
"""
Function to retrieve meals list from the api
"""
get_latest_url = 'http://www.themealdb.com/api/json/v1/1/latest.php'
get_category_url = 'http://www.themealdb.com/api/json/v1/1/list.php?c=list'
get_search_url = 'http://www.themealdb.com/a... | b93695fe79da47f52d2d4e3f863de26210292802 | 71,303 |
import urllib
def get_queue_length(queue_name, xqueue_session):
""" Returns the length of the queue """
try:
success, response = util._http_get(xqueue_session, urllib.parse.urljoin(settings.XQUEUE_INTERFACE['url'], urls.XqueueURLs.get_queuelen), {'queue_name': queue_name})
if not success:
... | 61fc0c73f300c93aaad449fd4386179601e8a5d2 | 71,304 |
from typing import Callable
from typing import List
from typing import Tuple
from typing import Union
from typing import Sequence
import torch
def calc_exact_shapley_values(
fn: Callable,
num_features: int,
shapley_factors: List[Tuple[List[int], int]],
new_data: Union[Tensor, Sequence[Tensor]],
ba... | 4b62855bb2eea715cb2920e5b218af6940768328 | 71,306 |
def imshow_det_rbboxes(img,
bboxes=None,
labels=None,
segms=None,
class_names=None,
score_thr=0,
bbox_color='green',
text_color='green',
... | 63d225dc0d016fdc434ea35fc65844ec9dc5c128 | 71,307 |
def lab2rgb(lab:np.ndarray):
"""
input lab as pytorch tensor of size (batch_size, 3, h, w) or (3, h, w)
"""
if ndim(lab)==4:
channel_idx=1
if int_shape(lab)[1]==3:
channel_idx = 1
elif int_shape(lab)[-1]==3:
channel_idx = -1
rgb=xyz2rgb(lab2xyz(la... | 969c7676cd3c030171ec7451b96274ea4ab7e349 | 71,308 |
def feed_clf(filename):
"""
prepare data for classifier
1. 6 subcategories: ['valueScore', 'locationScore', 'sleepScore', 'roomScore', 'cleanScore', 'serviceScore']
2. find sentences contain ['value', 'location', 'sleep', 'room', 'clean', 'service']
3. if the related score is 1,2, put nega... | cfb3a38d5fa73f650ff30b3ad382feb29117d084 | 71,309 |
def _play(agents, game_state, time_limit, match_id):
""" Run a match between two agents by alternately soliciting them to
select a move and applying it to advance the game state.
Parameters
----------
agents : tuple
agents[i] is an instance of isolation.Agent class (namedtuple)
game_st... | 2162f3d84856966699834066c227e4c163c0cfa9 | 71,311 |
import torch
def prepare_batch_tensor(batch, device, non_blocking, new_shape=None):
"""Prepare the batch data for training/inference, move data to GPU, reshape
the target if necessary.
Args:
batch (torch.Tensor): A batch of data.
device (torch.device or str): Device to load the backbone a... | 95594fea61dd598e2c6442211bc2ee72cad8af03 | 71,312 |
def get_case_ids_modified_with_owner_since(domain, owner_id, reference_date, until_date=None):
"""
Gets all cases with a specified owner ID that have been modified
since a particular reference_date (using the server's timestamp)
"""
return [
row['id'] for row in CommCareCase.get_db().view(
... | c5353088960671c14e1e48ad1f3fa497fdfff205 | 71,313 |
def getSubNode(prgNode, NodeName):
""" Find Sub-Node in Programm Node
Arguments:
prgNode {ua PrgNode} -- Programm node to scan
NodeName {[type]} -- Name of Sub-Node to find
Returns:
ua Node -- Sub-Node
"""
for child in prgNode.get_children():
if child.get_display_na... | 2da431eff566d7e2c76d4ca4646e15f762c00d4d | 71,314 |
def clean_data(df):
"""
Clean data and create categories Columns.
:param df: Pandas Dataframe. Dataframe Input
:return: Pandas Dataframe. Dataframe cleaned with categories at your own column
"""
# create a dataframe of the 36 individual category columns
categories = df['categories'].str.sp... | 38a6dec9e59c7e6ce10e9b66180332ac61c7c7bc | 71,315 |
def seq2ngrams(seq, n):
"""
'AGAMQSASM' => [['AGA', 'MQS', 'ASM'], ['GAM','QSA'], ['AMQ', 'SAS']]
"""
a, b, c = zip(*[iter(seq)] * n), zip(*[iter(seq[1:])] * n), zip(*[iter(seq[2:])] * n)
str_ngrams = []
for ngrams in zip(a, b, c):
for ngram in ngrams:
str_ngrams.append("".jo... | d207183aba274dc2c374dec5b9c6dc9c8c8e8847 | 71,316 |
def check_genotypes(glstring):
"""
Takes a GL String, and checks to see if any unphased genotypes
contain more than one locus. A list of tuples is returned. Each
tuple consists of the genotype, a set of loci found in the genotype,
and a text string. For unphased genotypes, the text string is either
... | 2dc0b0e3cbc148b90173e957dc5e0be738309623 | 71,319 |
def stations_by_river(stations):
"""This function returns a Python dict (dictionary) that maps river
names (the key) to a list of station objects on a given river."""
y = {}
for n in stations:
if n.river not in y:
y[n.river] = [n.name]
else: y[n.river].append(n.name)
ret... | 1e1023cdad87a3fdd5921d08448a4a2e9ceb311c | 71,320 |
def summary(request):
"""
View function for Summary of site.
"""
brokers = []
all_trades = Transaction.objects.filter(type='Buy').values()
for i in all_trades:
if i['broker'] not in brokers:
brokers.append(i['broker'])
summList = []
for i in brokers:
IPOPL... | df06ceb8aad283c61c13a5b3120c28a47d1b41ab | 71,321 |
def Tensor2Image(img):
"""
input (FloatTensor)
output (PIL.Image)
"""
img = img.cpu()
img = img * 0.5 + 0.5
img = transforms.ToPILImage()(img)
return img | dbf6510ef907a74adbbaa53415832212fb84a3aa | 71,322 |
def lc_ksvd(X, y, D, Q, alpha=1, beta=1, lambda1=1, lambda2=1,
sparse_coder=None, max_iter=2, approx=False, mmap=False, verbose=False, n_jobs=1):
"""
X: the data matrix with shape (n_features,n_samples)
y: the vector that contains the label of each datapoint
Q: a matrix with shape (n_atoms,n... | 2a46353a84357d314416b06303ff19b1472ca4c0 | 71,323 |
import re
def parse_align_seq(align_seq, ref_base, max_insertion_size):
"""
解析比对结果中某个位置的所有碱基
"""
base_list = []
it = re.finditer(pattern, align_seq)
for match in it:
base = match.group()
if base.startswith("^") or base == "$":
continue
elif base == "." or ba... | 3cadfa627f4398e9397474bdd914f3007da7a8da | 71,324 |
from typing import Tuple
def xyz_to_bev(
xyz: NDArrayFloat,
voxel_resolution: Tuple[float, float, float],
grid_size_m: Tuple[float, float, float],
cmap: NDArrayFloat,
) -> NDArrayByte:
"""Convert a set of points in Cartesian space to a bird's-eye-view image.
Args:
xyz: (N,3) List of p... | e06c154dcf1a725fa3a52c37d45556df0ac55909 | 71,325 |
import six
def determine_position(position, img, mark):
"""
Options:
TL: top-left
TR: top-right
BR: bottom-right
BL: bottom-left
C: centered
R: random
X%xY%: relative positioning on both the X and Y axes
X%xY: relative positioning on the X axis a... | b4a4ee83778723dceea6a10441d714f0c9b31064 | 71,326 |
def is_serializable_descendant(base):
"""
Args:
base (type): Base class to examine
Returns:
(bool): True if `base` is a descendant of `Serializable` (but not `Serializable` itself)
"""
if "Serializable" in globals(): # We're doing a forward reference here, class is defined below
... | 1b2da0de39148ead3b9177496b7cdbd6895e3533 | 71,328 |
def part_2(input_data: str) -> int:
"""Need to rack an 'aim'.
Commands mean different:
down X increases your aim by X units.
up X decreases your aim by X units.
forward X does two things:
It increases your horizontal position by X units.
It increases your depth by... | 60cf6a884bb6a0a9c69d214a0b883ab7321f7d1b | 71,329 |
def doTest(n):
"""Runs a test. returns score."""
score = 0
l = list(range(1,16))
for i in l:
if input("what is {} to the power of 3? ".format(i)) == str(i**3):
score += 1
print("Correct.")
else:
print("Wrong, the correct answer is {}".format(i**3)... | 83f32bec718e7459218b8863e229d5ecbd479d2c | 71,330 |
def binarize_time_series(layer_state, threshold, absolute=False):
"""
Given a threshold return a binary matrix of 0's or 1's based on threshold
:param layer_state: TxN matrix where N is the number of neurons.
:param threshold: threshold above which the value is considered 1.
:param absolute: whether... | ae4b4059cc4eb85f07461e330c7389dbaa5efc83 | 71,331 |
def compoundInterestPresentValue(p, r, c, n):
"""Compound interest present value
Returns: present value
Input values:
p : principal
r : interest rate
c : number of compounding periods in a year
n : (c * t), total number of compounding periods
"""
pv = (p / ((1 + (r / c)) ** n))
... | eef2b1628caa7d0f986f6bfd06f336083e9cb76a | 71,332 |
def ResourcePageDetails(request, pk):
"""
Retrieve, update or delete a job posting.
"""
try:
resource_page = ResourcePage.objects.get(pk=pk)
except Resource.DoesNotExist:
return HttpResponse(status=500)
if request.method == "GET":
serializer = ResourcePageSerializer(reso... | 98e0ed57ffb2581bc69bc6fdcc2cc8e145f043c8 | 71,333 |
def cifar10_classification_model():
"""
CIFAR10 classification
"""
return get_model(
False,
(3, 32, 32),
[7,7,7],
[1,2,2],
[32,64,128],
10,
1,
13,
0.9,
1,
1,
1,
False,
False,
False,
... | f2d780f4e9568c0a7362d5a7858a898589713378 | 71,334 |
def build_turbine_loc(turbine_x, turbine_y):
"""
Make a DataFrame containing plant layout info
(wind turbine locations).
Args:
turbine_x (np.array): wind turbine locations (east-west).
turbine_y (np.array): wind turbine locations (north-south).
Returns:
turbineLoc (pd.DataF... | 2786e0539bcabbf099cfd540b90f84976b9b1b38 | 71,335 |
from typing import Dict
from typing import Any
def _BigQueryToElwc(pipeline: beam.Pipeline, exec_properties: Dict[str, Any],
split_pattern: str) -> beam.pvalue.PCollection:
"""Read from BigQuery and transform to ExampleListWithContext.
When a field has no value in BigQuery, a feature with no ... | 68a854cdd054cac5739a744ea69a05d35bff6d4f | 71,336 |
def clean_spiketimes(spikeTimes, mindT=0.7):
"""
Clean up spike time array, removing all less than mindT
spikeTimes is a 1-D list or array
mindT is difference in time, same units as spikeTimes
If 1 or 0 spikes in array, just return the array
"""
if len(spikeTimes) > 1:
dst = np.diff(... | 6e5667961243ac6a51173f7da6eb661f78c9d368 | 71,337 |
from pathlib import Path
def euler(radius = 3, angle = 90, p = 1.0, use_eff = False, num_pts = 720):
""" Create an Euler bend (also known as "racetrack" or "clothoid" curves)
that adiabatically transitions from straight to curved. By default,
`radius` corresponds to the minimum radius of curvature of the... | e3808021e512bef6b6f4642f3a657893712dd317 | 71,339 |
import numpy
def best_dice(l_a, l_b):
"""
Best Dice function
:param l_a: list of binary instances masks
:param l_b: list of binary instances masks
:return: best dice estimation
"""
result = 0
for a in l_a:
best_iter = 0
for b in l_b:
inter = 2 * float(numpy.... | d00c668fe8c97fa2a78a62ac94492c665dc4a311 | 71,340 |
def isTestHub(node):
"""Check if a node is a Plugable 7-Port Hub
(Model USB2-HUB7BC)
The topology of this device is a 4-port hub,
with another 4-port hub connected on port 4.
"""
if not isinstance(node, find_usb_devices.USBDeviceNode):
return False
if 'Test HUB' not in node.desc:
return False
if... | c5255364d3fee0e5f30d08f0d1e6bb8273b63343 | 71,341 |
def dither(tensor, shape, amount, time=0.0, speed=1.0):
"""
"""
height, width, channels = shape
white_noise = basic([height, width], [height, width, 1], time=time, speed=speed,
distrib=ValueDistribution.simplex)
return effects.blend(tensor, white_noise, amount) | 7134eb292d276c735f23f27969aaf5ad77ada933 | 71,343 |
def hex_list_to_dec(hex_list):
"""Takes a hexidecimal number as a list of its digits represented as
strings. Returns the base 10 conversion of the hex as an integer.
"""
hex_dict = gen_hex_dict()
hex_list.reverse()
dec_sum = 0
for i, h in enumerate(hex_list):
dec_sum += hex_dict[h] ... | f1814bea274e7c156dc471a88131d6a053a5a1e5 | 71,346 |
def path_to_tensor(img_path):
"""
Getting a tensor from a given path.
"""
# Loading the image
img = image.load_img(img_path, target_size=(512, 512))
# Converting the image to numpy array
x = image.img_to_array(img)
# convert 3D tensor to 4D tensor with shape (1, 512, 512, 3)
x = ... | 42cf19b3f26afa02ba124ed8dd7f6b8fa7335ea1 | 71,348 |
def preorder(root):
"""Preorder depth-first traverse a binary tree."""
ans = []
stack = [root]
while stack:
node = stack.pop()
if node:
ans.append(node.val)
stack.extend([node.right, node.left])
return ans | e322df77a973f30b0745b36540a0f66b2ce29e6d | 71,349 |
def scramble(a, axis=0):
"""
Return an array with the values of `a` independently shuffled along the
given axis
"""
b = a.swapaxes(axis, -1)
n = a.shape[axis]
idx = np.random.choice(n, n, replace=False)
b = b[..., idx]
return b.swapaxes(axis, -1) | 94720f93886fd72163ede0e79c7423095a2a08bd | 71,350 |
def cylindrical_to_cartesian(ro, phi, z, degrees=True):
"""
Convert cylindrical coordinates (ro, phi, zeta) to cartesian (x, y, z).
Parameters
----------
ro: (N,) ndarray
Radial distance.
phi: (N,) ndarray
Angular position.
z: (N,) ndarray
Altitude.
degrees: bool... | 8393d936c316605718fe20d7ae44cf9771394214 | 71,352 |
async def _get_subscribers_prompt(channel: str) -> str:
"""Take prompt about channel subscribers"""
subscribers = await MediatorDependency.mediator.channels.get_subscribers(channel)
prompt = f"<b>{channel} subscribers:</b>\n"
if subscribers:
prompt += "".join(f"/{s.telegram_id} - {s.name}\n" for... | cd5dc28ddffd777dc75b8dbc8a5ba28ced5ab1c8 | 71,353 |
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