content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def templateSummary():
"""
"""
# Load Model
tablename = "survey_template"
s3db[tablename]
s3db.survey_complete
crud_strings = s3.crud_strings[tablename]
def postp(r, output):
if r.interactive:
if len(get_vars) > 0:
dummy, template_id = get_vars.viewi... | 6151e040b8e1c2491b3e282d0bb90fe278bf6dd8 | 32,710 |
def get_main_image():
"""Rendering the scatter chart"""
yearly_temp = []
yearly_hum = []
for city in data:
yearly_temp.append(sum(get_city_temperature(city))/12)
yearly_hum.append(sum(get_city_humidity(city))/12)
plt.clf()
plt.scatter(yearly_hum, yearly_temp, alpha=0.5)
plt... | b9845a44b868353e878b53beb6faf9c17bdf07d6 | 32,712 |
def get_PhotoImage(path, scale=1.0):
"""Generate a TKinter-compatible photo image, given a path, and a scaling
factor.
Parameters
----------
path : str
Path to the image file.
scale : float, default: 1.0
Scaling factor.
Returns
-------
img : `PIL.ImageTk.PhotoImage ... | 02402574e0641a1caced9fe0b07434db5c84dee5 | 32,713 |
import gc
def MCLA(hdf5_file_name, cluster_runs, verbose = False, N_clusters_max = None):
"""Meta-CLustering Algorithm for a consensus function.
Parameters
----------
hdf5_file_name : file handle or string
cluster_runs : array of shape (n_partitions, n_samples)
verbose : bool, o... | f7059c0afd6f346d82ec36eae90f6c3fa8459dad | 32,714 |
from datetime import datetime
def iso_date(iso_string):
""" from iso string YYYY-MM-DD to python datetime.date
Note: if only year is supplied, we assume month=1 and day=1
This function is not longer used, dates from lists always are strings
"""
if len(iso_string) == 4:
iso_string =... | 7f29b22744d384187e293c546d4c28790c211e99 | 32,716 |
def summary_dist_xdec(res, df1, df2):
"""
res is dictionary of summary-results DataFrames.
df1 contains results variables for baseline policy.
df2 contains results variables for reform policy.
returns augmented dictionary of summary-results DataFrames.
"""
# create distribution tables groupe... | 408bf1c8916d5338dbc01f41acb57dcc37e009e9 | 32,717 |
def moore_to_basu(moore, rr, lam):
"""Returns the coordinates, speeds, and accelerations in BasuMandal2007's
convention.
Parameters
----------
moore : dictionary
A dictionary containg values for the q's, u's and u dots.
rr : float
Rear wheel radius.
lam : float
Steer... | f599c2f5226dc4a12de73e1ddc360b6176d915ed | 32,719 |
def get_username(sciper):
"""
return username of user
"""
attribute = 'uid'
response = LDAP_search(
pattern_search='(uniqueIdentifier=' + sciper + ')',
attribute=attribute
)
return response[0]['attributes'][attribute][0] | 9da92bb2f1b0b733a137ed0bf62d8817c9c13ed8 | 32,720 |
def number_to_string(s, number):
"""
:param s: word user input
:param number: string of int which represent possible anagram
:return: word of alphabet
"""
word = ''
for i in number:
word += s[int(i)]
return word | 7997b20264d0750e2b671a04aacb56c2a0559d8c | 32,721 |
def mean(num_lst):
"""
Calculates the mean of a list of numbers
Parameters
----------
num_lst : list
List of numbers to calculate the average of
Returns
-------
The average/mean of num_lst
Examples
--------
>>> mean([1,2,3,4,5])
3.0
"""
... | bc6f86fc793bad165afc8f319a3094f3fae91361 | 32,722 |
import pandas
def development_create_database(df_literature, df_inorganics, df_predictions, inp):
"""
Create mass transition database.
Create mass transition database based on literature, inorganic and prediction data.
Parameters
----------
df_literature : dataframe
Dataframe wit... | 58b52d84ca98d770d3ace4a0b4dae4b369883284 | 32,723 |
import requests
from typing import IO
import hashlib
def _stream_to_file(
r: requests.Response,
file: IO[bytes],
chunk_size: int = 2**14,
progress_bar_min_bytes: int = 2**25,
) -> str:
"""Stream the response to the file, returning the checksum.
:param progress_bar_min_bytes: Minimum number of ... | 44d0529a5fdb0a14ac4dcddbfecf23442678a75a | 32,724 |
def get_user(key: str, user: int, type_return: str = 'dict', **kwargs):
"""Retrieve general user information."""
params = {
'k': key,
'u': user,
'm': kwargs['mode'] if 'mode' in kwargs else 0,
'type': kwargs['type_'] if 'type_' in kwargs else None,
'event_days': kwargs['event_days'] if 'event_days' in kwargs els... | 1b7a5c144267c012a69aff2f02f771d848e8883a | 32,725 |
def infer_schema(example, binary_features=[]):
"""Given a tf.train.Example, infer the Spark DataFrame schema (StructFields).
Note: TensorFlow represents both strings and binary types as tf.train.BytesList, and we need to
disambiguate these types for Spark DataFrames DTypes (StringType and BinaryType), so we requ... | bd952c278fafa809342b27755e2208b72bd25964 | 32,726 |
import collections
def create_batches_of_sentence_ids(sentences, batch_equal_size, max_batch_size):
"""
Groups together sentences into batches
If max_batch_size is positive, this value determines the maximum number of sentences in each batch.
If max_batch_size has a negative value, the function dynamically create... | 8db116e73e791d7eb72f080b408bb52d60481db7 | 32,728 |
def com_com_distances_axis(universe, mda_selection_pairs, fstart=0, fend=-1, fstep=1, axis='z'):
"""Center of mass to Center of mass distance in one dimension (along an axis).
This function computes the distance between the centers of mass between pairs of MDAnalysis atoms selections
across the the MD traje... | 7005d13e1f18597865ca5c5dc14ec09efd7c63e1 | 32,729 |
def min_vertex_cover(G, sampler=None, **sampler_args):
"""Returns an approximate minimum vertex cover.
Defines a QUBO with ground states corresponding to a minimum
vertex cover and uses the sampler to sample from it.
A vertex cover is a set of vertices such that each edge of the graph
is incident ... | b8681077d0bbb8504cdf5c96250e668bbcfe6d4e | 32,730 |
def quantile_bin_array(data, bins=6):
"""Returns symbolified array with equal-quantile binning.
Parameters
----------
data : array
Data array of shape (time, variables).
bins : int, optional (default: 6)
Number of bins.
Returns
-------
symb_array : array
Conver... | 87d8c64a30581b700d1a4674e4527882be99444f | 32,732 |
import _socket
def wrap_socket(sock: _socket.socket) -> AsyncSocket:
"""
Wraps a standard socket into an async socket
"""
return AsyncSocket(sock) | 70a6829bdf9048514ffe5bd5b831952f1ecd8e89 | 32,733 |
def _calculate_outer_product_steps(signed_steps, n_steps, dim_x):
"""Calculate array of outer product of steps.
Args:
signed_steps (np.ndarray): Square array with either pos or neg steps returned
by :func:`~estimagic.differentiation.generate_steps.generate_steps` function
n_steps (i... | 18aeadc5cb7866e6b99b5da9a2b9e6bc6ebb7c44 | 32,734 |
def compute_lima_on_off_image(n_on, n_off, a_on, a_off, kernel):
"""Compute Li & Ma significance and flux images for on-off observations.
Parameters
----------
n_on : `~gammapy.maps.WcsNDMap`
Counts image
n_off : `~gammapy.maps.WcsNDMap`
Off counts image
a_on : `~gammapy.maps.Wc... | a9bde10722cbed4dab79f157ee478c9b5ba35d86 | 32,735 |
def data_preprocess(ex, mode='uniform', z_size=20):
"""
Convert image dtype and scale imge in range [-1,1]
:param z_size:
:param ex:
:param mode:
:return:
"""
image = ex['image']
image = tf.image.convert_image_dtype(image, tf.float32)
image = tf.reshape(image, [-1])
image = i... | 95131b5e03afbc0a3c797570a48d49ca93f15116 | 32,736 |
def p2wpkh(pubkey: PubKey, network: str = 'mainnet') -> bytes:
"""Return the p2wpkh (bech32 native) SegWit address."""
network_index = _NETWORKS.index(network)
ec = _CURVES[network_index]
pubkey = to_pubkey_bytes(pubkey, True, ec)
h160 = hash160(pubkey)
return b32address_from_witness(0, h160, ne... | ecb4c60871e0dc362d3576d2f02d8e07cd47614e | 32,737 |
import re
def is_not_from_subdomain(response, site_dict):
"""
Ensures the response's url isn't from a subdomain.
:param obj response: The scrapy response
:param dict site_dict: The site object from the JSON-File
:return bool: Determines if the response's url is from a subdomain
"""
root... | d3fa99cc8a91942de5f3ec9cb8249c62c7488821 | 32,738 |
import random
def get_affiliation():
"""Return a school/organization affiliation."""
return random.choice(AFFILIATIONS) | 41356c95447352b9ab96db5783efb5ce511e0d00 | 32,739 |
def update_item_feature(train, num_item, user_features, lambda_item, nz_users_indices, robust=False):
"""
Update item feature matrix
:param train: training data, sparse matrix of shape (num_item, num_user)
:param num_item: number of items
:param user_features: factorized user features, dense matrix ... | 95b56754830cdcd8ddbfcabc25adcad1698903af | 32,740 |
def generate_mutation(model, mutation_type):
"""
Generate a model mutation.
Create the mutation class
Parameters:
model (dict): the model dictionary from settings
mutation_type (str): the mutation type (create, delete, update)
Returns:
graphene.Mutation.Field: the mutation field
""... | 1e1c39a76508c8f33179087786c08203af57c036 | 32,741 |
def _wf_to_char(string):
"""Wordfast &'XX; escapes -> Char"""
if string:
for code, char in WF_ESCAPE_MAP:
string = string.replace(code, char.encode('utf-8'))
string = string.replace("\\n", "\n").replace("\\t", "\t")
return string | 9270f4ff5a03265956d006bd08d04e417a0c5a14 | 32,743 |
from datetime import datetime
def agg_15_min_load_profile (load_profile_df):
"""
Aggregates 1-Hz load profile by taking average demand over 15-min
increments.
"""
s_in_15min = 15 * 60
# prepare idx slices
start_idxs = np.arange(0, len(load_profile_df), s_in_15min)
end_idxs = np.... | 6a92abf10b6f976d4b48bc7e6bfb4c0e44b1f4c5 | 32,744 |
def get_gitbuilder_hash(project=None, branch=None, flavor=None,
machine_type=None, distro=None,
distro_version=None):
"""
Find the hash representing the head of the project's repository via
querying a gitbuilder repo.
Will return None in the case of a 404... | 980abab1d3ff8bf1acdd0aec43f6ce5d5a2b6c45 | 32,746 |
def get_b16_add_conv_config():
"""Returns the ViT-B/16 configuration."""
config = ml_collections.ConfigDict()
config.patches = ml_collections.ConfigDict({'size': (16, 16)})
config.split = 'non-overlap'
config.slide_step = 12
config.hidden_size = 768
config.transformer = ml_collections.Config... | eae5f7f33acaf5931b11c7ed2f6d1b554c8a5254 | 32,747 |
def real_proto(request) -> programl_pb2.ProgramGraph:
"""A test fixture which enumerates one of 100 "real" protos."""
return request.param | 84f604626a1545e370aa92ab509329cc23e26aa5 | 32,748 |
def flat(arr):
"""Return arr flattened except for last axis."""
shape = arr.shape[:-1]
n_features = arr.shape[-1]
return arr.reshape(np.product(shape), n_features) | 8b9dd1b92c4fffe087345fa74fbc535e2ee41fbf | 32,749 |
from datetime import datetime
import time
def wait_while(f_logic, timeout, warning_timeout=None, warning_text=None, delay_between_attempts=0.5):
"""
Внутренний цик выполняется, пока вычисление `f_logic()` трактуется как `True`.
"""
warning_flag = False
start_time = datetime.now()
while True:... | 0261083b54b1572833ea146663862fce5fe690a5 | 32,751 |
def acute_lymphocytic_leukemia1():
"""Human Acute Lymphocytic Leukemia dataset (Patient 1).
This dataset was introduced in :cite:`Gawad_2014` and was used in:
* :cite:`B-SCITE` Figure 5.
* :cite:`infSCITE` Figure S16.
The size is n_cells × n_muts = 111 × 20
Returns
-------
:class:`an... | 76f15e7a19da71fe5e4451104698dfaffdbf1799 | 32,752 |
def extract_module(start_queue, g, locality="top", max_to_crawl=100, max_depth=10):
"""
([rdflib.URI], rdflib.Graph) -> rdflib.Graph
resource (rdflib.URI): resource for which we extract module
g (rdflib.Graph): RDF graph
"""
ontomodule = Graph()
ontomodule.namespace_manager = g.namespace_m... | 78e60670a8c8ed53471062380d5a9cf0aab70848 | 32,753 |
import torch
def softmax(x):
"""Softmax activation function
Parameters
----------
x : torch.tensor
"""
return torch.exp(x) / torch.sum(torch.exp(x), dim=1).view(-1, 1) | 739219efe04174fe7a2b21fb8aa98816679f8389 | 32,754 |
def comp_raw_bool_eqs(eq1str, eq2str):
""" Will compare two boolean equations to see if they are the same.
The equations can be written using the characters '&', '+' and '!'
for 'and', 'or' and 'not' respectively.
"""
(eqn1, eqn1vars) = OqeFuncUtils.get_vars_bool_eqn(eq1str)
(eqn2, eqn2v... | ce7af289add4294bf8a2a7835414cfb51358bc92 | 32,755 |
def get_integrated_scene(glm_files, start_scene=None):
"""Get an integrated scene.
Given a set of GLM files, get a scene where quantities are summed or
averaged or so.
"""
ms = satpy.MultiScene.from_files(
glm_files,
"glm_l2",
time_threshold=10,
group... | 71744bc23f961e630013ace0a85b1788f92924ff | 32,756 |
def _pt_to_test_name(what, pt, view):
"""Helper used to convert Sublime point to a test/bench function name."""
fn_names = []
pat = TEST_PATTERN.format(WHAT=what, **globals())
regions = view.find_all(pat, 0, r'\1', fn_names)
if not regions:
sublime.error_message('Could not find a Rust %s fun... | 580cacda4b31dff3fd05f4218733f5f0c6388ddb | 32,757 |
def load_log_weights(log_weights_root, iw_mode):
"""Loads the log_weights from the disk. It assumes a file structure of <log_weights_root>/<iw_mode>/*.npy
of mulyiple npy files. This function loads all the weights in a single numpy array, concatenating all npy files.
Finally, it caches the result in a file ... | 78f633d55e1d3eedc31851a315294e6a15d381a0 | 32,758 |
import requests
import logging
def pipelines_is_ready():
"""
Used to show the "pipelines is loading..." message
"""
url = f"{API_ENDPOINT}/{STATUS}"
try:
if requests.get(url).status_code < 400:
return True
except Exception as e:
logging.exception(e)
sleep(1)... | 219b0935092d09311a05816cf0c4345f9abee9f6 | 32,759 |
import cmath
def gamma_from_RLGC(freq,R,L,G,C):
"""Get propagation constant gamma from RLGC transmission line parameters"""
w=2*np.pi*freq
return cmath.sqrt((R+1j*w*L)*(G+1j*w*C)) | 9e4f09dc233f87b3fa52b9c7488b7fb65791289d | 32,761 |
from typing import Optional
from typing import List
from typing import Union
from pathlib import Path
def get_abs_paths(paths: Optional[List[Union[str, Path]]]) -> List[Union[str, Path]]:
"""Extract the absolute path from the given sources (if any).
:param paths: list of source paths, if empty this functions... | 93a785fbf679664b96c5228a9cf008cba7793765 | 32,762 |
async def async_setup_gateway_entry(hass: core.HomeAssistant, entry: config_entries.ConfigEntry) -> bool:
"""Set up the Gateway component from a config entry."""
host = entry.data[CONF_HOST]
euid = entry.data[CONF_TOKEN]
# Connect to gateway
gateway = IT600Gateway(host=host, euid=euid)
try:
... | d70644b2c4423798007272777bb9c081e79fc778 | 32,763 |
import requests
def import_from_github(username, repo, commit_hash):
"""Import a GitHub project into the exegesis database. Returns True on
success, False on failure.
"""
url = 'https://api.github.com/repos/{}/{}/git/trees/{}?recursive=1'.format(
username, repo, commit_hash)
headers = {'Ac... | a685fc79ad374ab499823696102d22b5d49201ed | 32,764 |
def substructure_matching_bonds(mol: dm.Mol, query: dm.Mol, **kwargs):
"""Perform a substructure match using `GetSubstructMatches` but instead
of returning only the atom indices also return the bond indices.
Args:
mol: A molecule.
query: A molecule used as a query to match against.
... | 1b6f4f7e17defae555ea750941be5ec71047cc87 | 32,767 |
def remove_element(nums, val):
"""
:type nums: List[int]
:type val: int
:rtype: int
"""
sz = len(nums)
while sz > 0 and nums[sz - 1] == val:
sz -= 1
i = 0
while i < sz:
if nums[i] == val:
nums[i], nums[sz - 1] = nums[sz - 1], nums[i]
sz -= 1
... | 4d29e8a8d43f191fe83ab0683f5dff005db799ec | 32,768 |
def get_fm_file(file_name):
"""Read facilitymatcher file into dataframe. If not present, generate the file
via script"""
file_meta = set_facilitymatcher_meta(file_name, category='')
df = load_preprocessed_output(file_meta, paths)
if df is None:
log.info('%s not found in %s, writing facility ... | b83743b8f56376148b12fc13c3731471cd24b6a5 | 32,769 |
def call_dot(instr):
"""Call dot, returning stdout and stdout"""
dot = Popen('dot -T png'.split(), stdout=PIPE, stderr=PIPE, stdin=PIPE)
return dot.communicate(instr) | f77c9f340f3fcbebb101c5f59d57c92b56147a11 | 32,770 |
def add_bank_member_signal(
banks_table: BanksTable,
bank_id: str,
bank_member_id: str,
signal_type: t.Type[SignalType],
signal_value: str,
) -> BankMemberSignal:
"""
Add a bank member signal. Will deduplicate a signal_value + signal_type
tuple before writing to the database.
Callin... | 214f064f152648c78d7ee5c6b56fb81c62cb4164 | 32,771 |
from typing import List
def map_zones(full_system) -> List[Zone]:
"""Map *zones*."""
zones = []
if full_system:
for raw_zone in full_system.get("body", dict()).get("zones", list()):
zone = map_zone(raw_zone)
if zone:
zones.append(zone)
return zones | e5996460bc66a2882ac1cabee79fdff6e4da71cd | 32,774 |
def betternn(x, keep_prob):
"""
Builds a network that learns to recognize digits
:param x: input tensor of shape (N_examples, 784) as standard MNIST image is 28x28=7845
:param keep_prob: probability for dropout layer
:return: y - a tensor of shape (N_examples, 10) with
values equal to probabilit... | 83b1155daa564b257fc1379811ddbde72d18ec4f | 32,775 |
def get_valid_scsi_ids(devices, reserved_ids):
"""
Takes a list of dicts devices, and list of ints reserved_ids.
Returns:
- list of ints valid_ids, which are the SCSI ids that are not reserved
- int recommended_id, which is the id that the Web UI should default to recommend
"""
occupied_ids ... | a5b4341fbee75e7d555c917587678dc5ea918b9f | 32,776 |
def check_password_and_delete(target: dict, password) -> dict:
"""
:param target:
:param password:
:return:
"""
if "password" in target:
if md5(str(password).encode()).hexdigest() == target["password"]:
target = dell(target["password"])
Bash().delete({
... | c06f5064d8a85065c3312d09bda9b9602b772ae1 | 32,777 |
def lingodoc_trigger_to_BIO(doc):
"""
:type doc: nlplingo.text.text_theory.Document
"""
ret = []
for sentence in doc.sentences:
token_labels = []
for token_index, token in enumerate(sentence.tokens):
token_labels.append(EventTriggerFeatureGenerator.get_event_type_of_toke... | 7237650ef6e9649b3d0e14867d907c9f6aa5b71a | 32,778 |
def build_coiled_coil_model():
"""Generates and returns a coiled-coil model."""
model_and_info = build_and_record_model(
request, model_building.HelixType.ALPHA)
return jsonify(model_and_info) | 9eeca3d1de581559129d3a4fe529c4e13727bd71 | 32,779 |
def get_input_fn(config, is_training,
num_cpu_threads=4):
"""Creates an `input_fn` closure to be passed to TPUEstimator."""
input_files = []
for input_pattern in config.pretrain_tfrecords.split(","):
input_files.extend(tf.io.gfile.glob(input_pattern))
def input_fn(params):
"""The actu... | 23992d8d4fd1bd09f12aa4c28c695a47edca420e | 32,780 |
def control_modes_available():
"""API to call the GetCtrlModesCountSrv service to get the list of available modes
in ctrl_pkg (autonomous/manual/calibration).
Returns:
dict: Execution status if the API call was successful, list of available modes
and error reason if call fails.
... | eec46b860791d305cce14659a633b461c73143f0 | 32,781 |
def reproject_bbox(source_epsg=4326, dest_epsg=None, bbox=None):
"""
Basic function to reproject given coordinate
bounding box (in WGS84).
"""
# checks
# reproject bounding box
l, b, r, t = bbox
return transform_bounds(src_crs=source_epsg,
dst_crs=dest_e... | 449a1cb793cb2239ed9d46449d03f77500fab031 | 32,782 |
from bs4 import BeautifulSoup
import re
def parse_cluster_card_info(soup: BeautifulSoup):
"""
App lists from GET requests follow a redirect to the /cluster page, which
contains different HTML and selectors.
:param soup: A BeautifulSoup object of an app's card
:return: A dictionary of available ba... | 0d4d0ba75a4e29b4d33e1f1a4e40239adcd80626 | 32,784 |
def get_joint_occurrence_df(df, row_column, col_column, top_k=10):
"""
Form a DataFrame where:
- index is composed of top_k top values in row_column.
- columns are composed of top_k top values in col_column.
- cell values are the number of times that the index and
column values occur together in... | 19701a0a355733c1eb8d3aa3046fc6e00daed120 | 32,785 |
def get_total_obs_num_samples(obs_length=None,
num_blocks=None,
length_mode='obs_length',
num_antennas=1,
sample_rate=3e9,
block_size=134217728,
... | 0d5c3de03723c79d31c7f77ece29226daaf4f442 | 32,786 |
def number(
x: Scalar,
c: str = 'csl',
w: int = 5,
) -> str:
"""
Return a notation of the number x in context c.
Input:
x (Scalar): number
c (str): context
w (int): width of the output string
Output:
s (str): notation of x
"""
S = 0 if x>=0 else 1 # ... | 3a36d66f9166e82bb51e39e483f9366f83f72ff8 | 32,788 |
def remove_helm_repo(repos_array):
"""
Execute 'helm repo remove' command on input values
repos_array is an array of strings as:
['stable', 'local', 'nalkinscloud', ...]
:param repos_array: array of strings
:return: return code and value from execution command as dict
"""
status = 0
... | 4b2a778122caaabf1b7cca971d2d9f2b57dbf84e | 32,789 |
def evaluate_fio(baselines: dict, results: dict, test_name: str, failures: int,
tolerance: int) -> int:
"""
Evaluate the fio test results against the baseline.
Determine if the fio test results meet the expected threshold and display
the outcome with appropriate units.
Parameters
... | d5ad4ca319163409a526fe9d8b43be13de49680a | 32,790 |
def f1_3D(x1, x2, x3):
"""
x1 dependant
from example 2.1 in iterative methods
"""
return -0.2*x2 - 0.2*x3 + 0.8 | 09e5a337f5fa62a4c3cddd9ae0dd701867c52b22 | 32,791 |
import typing
def encrypt(message: typing.Union[str, bytes], n: int, e: int) -> bytes:
"""
Encrypt MESSAGE with public key specified by N and E
"""
pub_key = rsa.PublicKey(n, e)
if isinstance(message, str):
message = message.encode("utf-8")
elif isinstance(message, bytes):
pass... | fb89606b0d3263c5d10479970868c5336d14679b | 32,792 |
def _safe_div(numerator, denominator):
"""Divides two tensors element-wise, returning 0 if the denominator is <= 0.
Args:
numerator: A real `Tensor`.
denominator: A real `Tensor`, with dtype matching `numerator`.
Returns:
0 if `denominator` <= 0, else `numerator` / `denominator`
"""
t = tf.trued... | 04e9856b1283bf83cd63bb56c65f1d1e2667bcc6 | 32,793 |
def build_embedding_model():
""" Build model by stacking up a preprocessing layer
and an encoding layer.
Returns
-------
tf.keras.Model
The embedding model, taking a list of strings as input,
and outputting embeddings for each token of the input strings
"""
# Links for the... | ecf835f8543d9815c3c88b5b596c0c14d9524b66 | 32,794 |
def event_date_row(event_names_and_dates):
""" Returns the third row of the attendance csv. This is just a list of event dates.
:param list[(str, datetime)] event_names_and_dates:
A list of names and dates for each event that should appear on the csv
:returns:
the row to be printed
:rt... | 5b51eaef8cde99040a1aff9a0c6abaaef5e52896 | 32,795 |
def moving_tajima_d(ac, size, start=0, stop=None, step=None, min_sites=3):
"""Calculate the value of Tajima's D in moving windows of `size` variants.
Parameters
----------
ac : array_like, int, shape (n_variants, n_alleles)
Allele counts array.
size : int
The window size (number of... | df5217180cf5b25ccb09ee88974d82290bff43ce | 32,796 |
def sample_member(user, name='Attila'):
"""
Create and return a sample tag
:param user:
:param name:
:return:
"""
return Member.objects.create(user=user, name=name) | ac171a5da2495436596bd6e597b0b9ea498c8bcf | 32,797 |
import uuid
def _create_feed(client, customer_id):
"""Creates a page feed with URLs
Args:
client: an initialized GoogleAdsClient instance.
customer_id: a client customer ID str.
Returns:
A FeedDetails instance with information about the newly created feed.
"""
# Retrieve ... | 738e940abd1a7ec90382c4011b26d757c8a916a4 | 32,798 |
def cal_pj_task_ind(_st_date, _ed_date):
"""
计算产品研发中心资源投入到非产品事务的指标。
:param _st_date: 起始日期
:param _ed_date: 截止日期
:return: 统计指标
"""
global extTask
_pj_info = handler.get_project_info("project_t")
# logging.log(logging.WARN, ">>> cal_pj_task_ind( %s, %s )" % (_st_date, _ed_date))
... | 7a998a01a87abbc1f80147cf067b231429124001 | 32,799 |
def get_page_index(obj, amongst_live_pages=True):
"""
Get oage's index (a number) within its siblings.
:param obj:
Wagtail page object
:param amongst_live_pages:
Get index amongst live pages if True or all pages if False.
:return:
Index of a page if found or None if page d... | fd1950533a398019ab0d3e208a1587f86b134a13 | 32,801 |
import requests
def contact_ocsp_server(certs):
"""Sends an OCSP request to the responding server for a certificate chain"""
chain = convert_to_oscrypto(certs)
req = create_ocsp_request(chain[0], chain[1])
URI = extract_ocsp_uri(certs[0])
data = requests.post(URI, data=req, stream=True, headers={'... | 15c32e72d41e6db275f5ef1d91ee7ccf05eb8cde | 32,802 |
import warnings
def reset_index_inplace(df: pd.DataFrame, *args, **kwargs) -> pd.DataFrame:
"""
Return the dataframe with an inplace resetting of the index.
This method mutates the original DataFrame.
Compared to non-inplace resetting, this avoids data copying, thus
providing a potential speedup... | 6c10d67ffdaf195c0a9eea3ae473bb0e93e6e9ef | 32,803 |
def get_current_user():
"""Get the current logged in user, or None."""
if environment.is_local_development():
return User('user@localhost')
current_request = request_cache.get_current_request()
if local_config.AuthConfig().get('enable_loas'):
loas_user = current_request.headers.get('X-AppEngine-LOAS-Pe... | 3b80285c87358dc33595ca97ecee3cf38cf96034 | 32,805 |
import calendar
import time
def genericGetCreationDate(page):
"""
Go to each date position and attempt to get date
"""
randSleep()
allDates = []
signaturePositions = findSignatures(page)
for p in signaturePositions:
timestamp = getTimestampFromSERP(p, page)
# print('times... | 3d3f6e9a0b1ce9b49f887ba4d1d99493b75d2f9e | 32,806 |
def depth(data):
"""
For each event, it finds the deepest layer in which the shower has
deposited some E.
"""
maxdepth = 2 * (data[2].sum(axis=(1, 2)) != 0)
maxdepth[maxdepth == 0] = 1 * (
data[1][maxdepth == 0].sum(axis=(1, 2)) != 0
)
return maxdepth | aa48c88c516382aebe2a8b761b21f650afea82b1 | 32,807 |
def transform_user_extensions(user_extension_json):
"""
Transforms the raw extensions JSON from the API into a list of extensions mapped to users
:param user_extension_json: The JSON text blob returned from the CRXcavator API
:return: Tuple containing unique users list, unique extension list, and exten... | 89d91781028eb4335fff2c9bca446f50b5e91a3f | 32,809 |
def shower_array_rot(shower_array, alt, az):
"""
Given a series of point on the Z axis, perform a rotation of alt around Y and az around Z
Parameters
----------
shower_array: numpy array of shape (N,3) giving N points coordinates
alt: altitude shower direction - float
az: azimuth shower dir... | d98a6a4589b8945e8dff1272608307915f499fd6 | 32,810 |
from typing import Optional
def get_dscp_configuration(dscp_configuration_name: Optional[str] = None,
resource_group_name: Optional[str] = None,
opts: Optional[pulumi.InvokeOptions] = None) -> AwaitableGetDscpConfigurationResult:
"""
Use this data source t... | 80e0a388581cd7028c7a8351737808e578778611 | 32,811 |
def aggregate_returns(df_daily_rets, convert_to):
"""
Aggregates returns by week, month, or year.
Parameters
----------
df_daily_rets : pd.Series
Daily returns of the strategy, noncumulative.
- See full explanation in tears.create_full_tear_sheet (returns).
convert_to : str
... | 7ccf2763420df055a59f15b679ba2c8265744a41 | 32,812 |
import random
def impute(x,nu):
"""
Impute to missing values: for each row of x this function find the nearest row in eucledian distance
in a sample of nu rows of x and replace the missing value of the former row
with the corrisponding values of the... | e13562e28eaafcfaa7848eae9cca7ac9d435d1f4 | 32,814 |
def get_data_splits(comment_type_str=None, ignore_ast=False):
"""Retrieves train/validation/test sets for the given comment_type_str.
comment_type_str -- Return, Param, Summary, or None (if None, uses all comment types)
ignore_ast -- Skip loading ASTs (they take a long time)"""
dataset, high_level... | b9451c5539c7ce235b7bb7f3251e3caa8e4b77c7 | 32,815 |
from typing import Tuple
def get_slide_roi_masks(slide_path, halo_roi_path, annotation_name, slide_id:str=None,
output_dir:str=None) -> Tuple[np.ndarray, np.ndarray, np.ndarray]:
"""get roi masks from slides
Given a slide, halo annotation xml file, generate labels from xml polygons,
then crop ... | b79e9b8d93416c404110b56582b4ae1e9030bd7c | 32,816 |
def generate_stop_enex_nb(entries: tp.Array2d,
ts: tp.Array,
stop: tp.MaybeArray[float],
trailing: tp.MaybeArray[bool],
entry_wait: int,
exit_wait: int,
pick_first:... | a34108bd324498e70155f5dcc8c8c4364982c43f | 32,817 |
def mangle_type(typ):
"""
Mangle Numba type
"""
if typ in N2C:
typename = N2C[typ]
else:
typename = str(typ)
return mangle_type_c(typename) | 944952e184d1d33f9424c9e1118920f69f757e86 | 32,818 |
def lorentz(sample_len=1000, sigma=10, rho=28, beta=8 / 3, step=0.01):
"""This function generates a Lorentz time series of length sample_len,
with standard parameters sigma, rho and beta.
"""
x = np.zeros([sample_len])
y = np.zeros([sample_len])
z = np.zeros([sample_len])
# Initial conditi... | c8dc9de84dde15453fe99ed8fb55eddcdd628648 | 32,819 |
def draw_lane_lines_on_all_images(images, cols=2, rows=3, figsize=(15, 13)):
"""
This method calls draw_windows_and_fitted_lines Fn for each image and then show the grid of output images.
"""
no_of_images = len(images)
fig, axes = plt.subplots(rows, cols, figsize=figsize)
indexes = range(cols * r... | 27975a95836b784fece0547375b4d79868bbd3b6 | 32,820 |
import re
def get_field_order(address, latin=False):
"""
Returns expected order of address form fields as a list of lists.
Example for PL:
>>> get_field_order({'country_code': 'PL'})
[[u'name'], [u'company_name'], [u'street_address'], [u'postal_code', u'city']]
"""
rules = get_validation_r... | d86c36ab1026fdad6e0b66288708786d8d2cb906 | 32,821 |
def env_start():
""" returns numpy array """
global maze, current_position
current_position = 500
return current_position | ed377adedc48159607a4bb08ea6e3624575ec723 | 32,822 |
def bootstrap_acceleration(d):
""" Bootstrap (BCA) acceleration term.
Args:
d : Jackknife differences
Returns:
a : Acceleration
"""
return np.sum(d**3) / np.sum(d**2)**(3.0/2.0) / 6.0 | fbd9a05934d4c822863df0ba0b138db840f34955 | 32,823 |
def normalize_map(x):
"""
normalize map input
:param x: map input (H, W, ch)
:return np.ndarray: normalized map (H, W, ch)
"""
# rescale to [0, 2], later zero padding will produce equivalent obstacle
return x * (2.0/255.0) | f750df26c8e6f39553ada82e247e21b2e3d6aabd | 32,824 |
def today():
"""Get the today of int date
:return: int date of today
"""
the_day = date.today()
return to_int_date(the_day) | 81c497cdf33050b6e8de31b0098d10acfb555444 | 32,825 |
from datetime import datetime
def contact(request):
"""Renders the contact page."""
assert isinstance(request, HttpRequest)
return render(
request,
'app/contact.html',
{
'title':'联系我们',
'message':'你可以通过以下方式和我们取得联系',
'year':datetime.now().year,
... | 65056534556a8503d897b38468b43da968d4223d | 32,826 |
import math
def plagdet_score(rec, prec, gran):
"""Combines recall, precision, and granularity to a allow for ranking."""
if (rec == 0 and prec == 0) or prec < 0 or rec < 0 or gran < 1:
return 0
return ((2 * rec * prec) / (rec + prec)) / math.log(1 + gran, 2) | f8debf876d55296c3945d0d41c7701588a1869b6 | 32,827 |
def continuum(spec,bin=50,perc=60,norder=4):
""" Derive the continuum of a spectrum."""
nx = len(spec)
x = np.arange(nx)
# Loop over bins and find the maximum
nbins = nx//bin
xbin1 = np.zeros(nbins,float)
ybin1 = np.zeros(nbins,float)
for i in range(nbins):
xbin1[i] = np.mean(x[i... | 42709c9361707ef8b614030906e9db5ea38087b3 | 32,828 |
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