content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def _init_basemap(border_colour):
"""Initializes basemap.
:param border_colour: Colour (in any format accepted by matplotlib) of
political borders.
:return: narr_row_limits: length-2 numpy array of (min, max) NARR rows to
plot.
:return: narr_column_limits: length-2 numpy array of (min, ... | aeec84f7973972abd93bc344fc7f2028d216c4b5 | 25,800 |
def makeFigure():
"""Get a list of the axis objects and create a figure"""
ax, f = getSetup((9, 12), (5, 2))
cellTarget = "Treg"
epitopesDF = pd.DataFrame(columns={"Classifier", "Epitope"})
posCorrs1, negCorrs = CITE_RIDGE(ax[4], cellTarget)
for x in posCorrs1:
epitopesDF = epitopesDF.a... | e0c4cf34630171e489f195d14a3d29f8d0fa10e1 | 25,801 |
def get_data_frame(binary_tables, all_inputs):
"""
Gets a data frame that needs QM reduction and further logic.
Also removes the all_inputs from the DataFrame.
:param binary_tables: contains a tables with True and False outputs.
:param all_inputs: columns
:return: Pandas DataFrame.
"""
... | e40a914f19242ee82cd0c3e0f706f97f6c71e9fa | 25,802 |
def compute_shift_delay_samples(params_delays,vector_seconds_ref,freq_sample,seconds_frame,pair_st_so,data_type=0,\
front_time=None,cache_rates=[],cache_delays=[]):
"""
Compute number of samples to shift signal (always positive since reference station is closest to source).
... | 5cf35bd1b2187d107f8fd5809dd7db9822d5c110 | 25,803 |
from typing import Dict
from typing import Tuple
def classification_metrics_function(
logits: jnp.ndarray,
batch: base_model.Batch,
target_is_onehot: bool = False,
metrics: base_model.MetricNormalizerFnDict = _CLASSIFICATION_METRICS,
) -> Dict[str, Tuple[float, int]]:
"""Calculates metrics for the c... | defcde9e70822721a866a5af62c472386251b0e8 | 25,804 |
import _io
def create_validator_delegation_withdrawal(
params: DeployParameters,
amount: int,
public_key_of_delegator: PublicKey,
public_key_of_validator: PublicKey,
path_to_wasm: str
) -> Deploy:
"""Returns a standard withdraw delegation deploy.
:param params: Standard parameters used whe... | d4395928cdc32da03775f0944b4d3d2ef802e534 | 25,805 |
def get_host_finding_vulnerabilities_hr(vulnerabilities):
"""
Prepare human readable json for "risksense-get-host-finding-detail" command.
Including vulnerabilities details.
:param vulnerabilities: vulnerabilities details from response.
:return: list of dict
"""
vulnerabilities_list = [{
... | 8f0689441f2fef41bbd5da91c802dfb8baa2b979 | 25,806 |
from typing import Optional
from typing import List
import copy
def train_on_file_dataset(
train_dataset_path: str,
valid_dataset_path: Optional[str],
feature_ids: List[str],
label_id: str,
weight_id: Optional[str],
model_id: str,
learner: str,
task: Optional[TaskType] = Task.CLASSIFIC... | 16e692adc9e72d06678680e13ef50636e6f17450 | 25,807 |
def db_fixture():
"""Get app context for tests
:return:
"""
return db | 4c780071e5a092870a676685aede295365de6ad9 | 25,808 |
def login_required(route_function):
"""
这个函数看起来非常绕
是实现装饰器的一般套路
"""
def f(request):
u = current_user(request)
if u is None:
log('非登录用户')
return redirect('/login')
else:
return route_function(request)
return f | 44cff97ad32257e4dc4cfe5d7e3b79ea643986ef | 25,809 |
def cuTypeConverter(cuType):
""" Converts calendar user types to OD type names """
return "recordType", CalendarDirectoryRecordMixin.fromCUType(cuType) | a4afcfe912fc1d853ee841ed215c099c352ace0c | 25,810 |
def add_viz_sphere(
sim: habitat_sim.Simulator, radius: float, pos: mn.Vector3
) -> habitat_sim.physics.ManagedRigidObject:
"""
Add a visualization-only sphere to the world at a global position.
Returns the new object.
"""
obj_attr_mgr = sim.get_object_template_manager()
sphere_template = ob... | cc8f47c8b32ad2f4bf7c0e159d19dac048546aea | 25,811 |
import torch
def get_normalize_layer(dataset: str) -> torch.nn.Module:
"""Return the dataset's normalization layer"""
if dataset == "imagenet":
return NormalizeLayer(_IMAGENET_MEAN, _IMAGENET_STDDEV)
elif dataset == "cifar10":
return NormalizeLayer(_CIFAR10_MEAN, _CIFAR10_STDDEV) | 52d5d0a744e0e10db1f54d83dfb9b7a8b779c49d | 25,812 |
def summer_69(arr):
"""
Return the sum of the numbers in the array,
except ignore sections of numbers starting
with a 6 and extending to the next 9 (every 6 will be followed by at least one 9).
Return 0 for no numbers.
:param arr: list of integers
:return: int
"""
get_result = 0
... | d155a739afe131025b654002bebb51b25325bd1e | 25,813 |
def get_notebook_title(nb_json, default=None):
"""Determine a suitable title for the notebook.
This will return the text of the first header cell.
If that does not exist, it will return the default.
"""
cells = nb_json['cells']
for cell in cells:
if cell['cell_type'] == 'heading':
... | 4a20fe9890371ab107d0194e791c6faf9901d714 | 25,814 |
import os
import sys
def get_local_server_dir(subdir = None):
"""
Get the directory at the root of the venv.
:param subdir:
:return:
"""
figures_dir = os.path.abspath(os.path.join(sys.executable, '..', '..', '..'))
if subdir is not None:
figures_dir = os.path.join(figures_dir, subd... | 1e540157786cd0ea2ffa9bd1fabdb3d48bcb37f5 | 25,815 |
import torch
def extract_sequence(sent,
annotations,
sources,
label_indices):
"""
Convert the annotations of a spacy document into an array of observations of shape
(nb_sources, nb_bio_labels)
"""
sequence = torch.zeros([len(sent), len... | 1d988fe82b19d583438b8bf1ceb00671de566fca | 25,816 |
def is_valid_password_1(password):
"""
>>> is_valid_password_1("111111")
True
>>> is_valid_password_1("223450")
False
>>> is_valid_password_1("123789")
False
"""
has_double = any(password[c] == password[c+1] for c in range(len(password)-1))
is_ascending = all(password[c] <= passw... | 8544e15a7d50c025073a3ac51b9f5b8809341d2e | 25,817 |
def mean(x, axis=None, keepdims=False):
"""Mean of a tensor, alongside the specified axis.
Parameters
----------
x: A tensor or variable.
axis: A list of integer. Axes to compute the mean.
keepdims: A boolean, whether to keep the dimensions or not.
If keepdims is False, the rank of the tensor is reduce... | 9f8d1b98a5f1dd37a91493fb822437885e04468e | 25,818 |
def frame_pass_valid_sample_criteria(frame, image_type):
"""Returns whether a frame matches type criteria"""
return frame_image_type_match(frame, image_type) | cf5b51dfe63e7667a14b41c9793a66aa065663e8 | 25,819 |
def embed(tokenizer, text):
"""
Embeds a text sequence using BERT tokenizer
:param text: text to be embedded
:return: embedded sequence (text -> tokens -> ids)
"""
return tokenizer.convert_tokens_to_ids(tokenizer.tokenize(text)) | 453d411d9c460dfc28cb54c7a6a807290905bed3 | 25,820 |
def exponent_fmt(x, pos):
""" The two args are the value and tick position. """
return '{0:.0f}'.format(10 ** x) | 46e2104e966ec452fb510a411b1907090d55daf3 | 25,821 |
def _unpack(arr, extent, order='C'):
"""
This is a helper method that handles the initial unpacking of a data array.
ParaView and VTK use Fortran packing so this is convert data saved in
C packing to Fortran packing.
"""
n1,n2,n3 = extent[0],extent[1],extent[2]
if order == 'C':
arr =... | 2d7054da8ffc5773bfd151973bf3b06c84c2e735 | 25,822 |
import torch
def unzip(list):
"""unzip the tensor tuple list
Args:
list: contains tuple of segemented tensors
"""
T, loss = zip(*list)
T = torch.cat(T)
mean_loss = torch.cat(loss).mean()
return T, mean_loss | 5ed656aa8221c7bc5bd8a43b80fe0efd07d4df24 | 25,823 |
def ergs_to_lsun(luminosity):
"""
From luminostiy in erg/s to Lsun
"""
lum = u.Quantity(luminosity, u.erg / u.s)
return lum.to(u.L_sun) | fa7e572f5509b0408520e15433141e6da88daae1 | 25,824 |
def decode(code, P):
"""
Decode an RNS representation array into decimal number
:param P: list of moduli in order from bigger to smaller [pn, .., p2, p1, p0]
>>> decode(code=[5, 3, 1], P=[7,6,5])
201
"""
lcms = np.fromiter(accumulate(P[::-1], np.lcm), int)[::-1]
n = code[-1] % P[-1]
... | 422128ef0d0da62b404b6e8c0b927221505ead17 | 25,825 |
def is_collection(obj):
"""
Check if a object is iterable.
:return: Result of check.
:rtype: bool
"""
return hasattr(obj, '__iter__') and not isinstance(obj, str) | 70fa0262ea7bf91a202aade2a1151d467001071e | 25,826 |
import hashlib
def file_md5(fpath):
"""Return the MD5 digest for the given file"""
with open(fpath,'rb') as f:
m = hashlib.md5()
while True:
s = f.read(4096)
if not s:
break
m.update(s)
return m.hexdigest() | 40b355b9a628d286bf86b5199fd7e2a8bea354de | 25,827 |
import os
def strip_path(full_path):
"""Returns the filename part of full_path with any directory path removed.
:meta private:
"""
return os.path.basename(full_path) | 327736cb77d9aa409a5790efd51895318d970382 | 25,828 |
import os
def update():
"""
Updates the Database
Returns
-------
None.
"""
os.system("git submodule update --recursive --remote")
return None
# %% Load USA data | 3c9b7817c6512fd7fe018d3642fe6e9106d85b7c | 25,829 |
def move(column, player):
"""Apply player move to the given column"""
index = _index_of(column, None)
if index < 0:
print('Entire column is occupied')
return False
column[index] = player
return True | 9c728c4c764154390478e27408f5bc25acaacf1d | 25,830 |
def calculate_costs(points, centric_point):
""" Returns the accumulated costs of all point in `points` from the centric_point """
if len(points) == 1:
return points[0].hyp()
_part = (points - centric_point)**2
_fin = []
for point in _part:
_fin.append(point.hyp())
return (np.array(_fin)).sum() | c35e00dabb3e85d5136afc3f5696a73aad607470 | 25,831 |
def formatUs(time):
"""Format human readable time (input in us)."""
if time < 1000:
return f"{time:.2f} us"
time = time / 1000
if time < 1000:
return f"{time:.2f} ms"
time = time / 1000
return f"{time:.2f} s" | 7546db60e3977e07dbbbad0a3ab767865840c2e3 | 25,832 |
from typing import Dict
from typing import List
from typing import Union
def parse_annotations(ann_filepath: str) -> Dict[int, List[Label]]:
"""Parse annotation file into List of Scalabel Label type per frame."""
outputs = defaultdict(list)
for line in load_file_as_list(ann_filepath):
gt = line.st... | 1ef42147fa4cb44b1ebd37f861444e502d0ea9b9 | 25,833 |
import os
def bel_graph_loader(from_dir: str) -> BELGraph:
"""Obtains a combined BELGraph from all the BEL documents in one folder.
:param from_dir: The folder with the BEL documents.
:return: A corresponding BEL Graph.
"""
logger.info("Loading BEL Graph.")
files = [
os.path.join(from... | f7369c3a3abb9ab1d0d43411ca92e3edc601b8e4 | 25,834 |
from typing import Dict
from typing import List
from typing import Optional
from typing import Union
from typing import Any
def apply(lang1: Dict[List[str], float], lang2: Dict[List[str], float], parameters: Optional[Dict[Union[str, Parameters], Any]] = None) -> float:
"""
Calculates the EMD distance between ... | c87d171018a6eddef6572a0bd3639952499fca44 | 25,835 |
import collections
def reInpainting(image, ground_truth, teethColor):
"""
if pixel has pink color (marked for teeth) and not in range of teeth => fill by teethColor
"""
isTeeth, isNotTeeth = 0, 0
threshold = calculateThreshhold(image, teethColor)
# print(f"Threshold: {threshold}")
for ... | c5f8a71c9c1bbf6e3b4c03b477901b9669d9f72c | 25,836 |
def data_for_cylinder_along_z(center_x, center_y, radius, height_z):
"""
Method for creating grid for cylinder drawing. Cylinder will be created along Z axis
:param center_x: Euclidean 3 dimensional center of drawing on X axis
:param center_y: Euclidean 3 dimensional center of drawing on Y axis
:par... | 2582860582564e7b8a4e9ba6e89d0740d44fa069 | 25,837 |
def _configure_learning_rate(num_samples_per_epoch, global_step):
"""Configures the learning rate.
Args:
num_samples_per_epoch: The number of samples in each epoch of training.
global_step: The global_step tensor.
Returns:
A `Tensor` representing the learning rate.
Raises:
ValueError: if
""... | c1395b7521b6a55e8a77c50b47dca920f8c27dc0 | 25,838 |
def cpm(adata: ad.AnnData) -> ad.AnnData:
"""Normalize data to counts per million."""
_cpm(adata)
return adata | ec0a2a0ed61965e8c78ebf59fab569f2a4954790 | 25,839 |
def argon2_key(encryption_password, salt):
"""
Generates an encryption key from a password using the Argon2id KDF.
"""
return argon2.low_level.hash_secret_raw(encryption_password.encode('utf-8'), salt,
time_cost=RFC_9106_LOW_MEMORY.time_cost, memory_cost=RFC_9106_LOW_MEMORY.memory_cost,
... | eaf5a0f3ca0ee12e22b0ddb9594dcd1734ef91e8 | 25,840 |
def print_policy_analysis(policies, game, verbose=False):
"""Function printing policy diversity within game's known policies.
Warning : only works with deterministic policies.
Args:
policies: List of list of policies (One list per game player)
game: OpenSpiel game object.
verbose: Whether to print po... | 51379d78dc3dd924da41dc00e8d6236d72b68f3c | 25,841 |
def model_fn(is_training=True, **params):
"""
Create base model with MobileNetV2 + Dense layer (n class).
Wrap up with CustomModel process.
Args:
is_training (bool): if it is going to be trained or not
params: keyword arguments (parameters dictionary)
"""
baseModel = MobileNetV2... | 2a14d803c5d521f453ce30a641d8736364e64ac0 | 25,842 |
import argparse
def make_arg_parser():
"""
Create the argument parser.
"""
parser = argparse.ArgumentParser(description="Scrap WHOIS data.")
parser.add_argument("--config", help="uwhoisd configuration")
parser.add_argument(
"--log",
default="warning",
choices=["critical... | f9c94b23589ed77fc3db950549d21f371e156eb1 | 25,843 |
def roundToElement(dateTime, unit):
""" Returns a copy of dateTime rounded to given unit
:param datetime.datetime: date time object
:param DtUnit unit: unit
:return: datetime.datetime
"""
year = dateTime.year
month = dateTime.month
day = dateTime.day
hour = dateTime.hour
minute ... | 226f532e9e729d155d14135e4025015e8b00b2e0 | 25,844 |
def tuple_factory(colnames, rows):
"""
Returns each row as a tuple
Example::
>>> from cassandra.query import tuple_factory
>>> session = cluster.connect('mykeyspace')
>>> session.row_factory = tuple_factory
>>> rows = session.execute("SELECT name, age FROM users LIMIT 1")
... | 5526647a414b397ac9d71c35173718c01385a03b | 25,845 |
def is_error(splunk_record_key):
"""Return True if the given string is an error key.
:param splunk_record key: The string to check
:type splunk_record_key: str
:rtype: bool
"""
return splunk_record_key == 'error' | 26371ec9c5941fbf07a84c6904ea739b02eb97ba | 25,846 |
def parse_network_info(net_bond, response_json):
"""
Build the network info
"""
out_dict = {}
ip_list = []
node_count = 0
# Build individual node information
for node_result in response_json['result']['nodes']:
for node in response_json['result']['nodes']:
if node['no... | 2c83aa72d6ee0195a42339546d1fded84f85680f | 25,847 |
async def create_or_update(hub, ctx, name, resource_group, **kwargs):
"""
.. versionadded:: 1.0.0
Create or update a network security group.
:param name: The name of the network security group to create.
:param resource_group: The resource group name assigned to the
network security group... | 251ee69d6077d2fd4ffda8c9da53b8ae84c9a696 | 25,848 |
def download_media_suite(req, domain, app_id):
"""
See Application.create_media_suite
"""
return HttpResponse(
req.app.create_media_suite()
) | fe0f5e0b5598b2368fd756a7f6bee89035813317 | 25,849 |
def non_numeric(string: str) -> str:
""" Removes all numbers from the string """
return ''.join(letter for letter in string if not letter.isdigit()) | fe16297c4cf1b144fb583986a5c01ea02920787e | 25,850 |
import re
def prepare_xs(path, numbergroup=1):
"""Prepare the needed representation of cross-section data
Paramteres:
-----------
path : str
filename of cross-section data
numbergroup : int
number of energies neutron multigroup
Returns:
--------
energies : iter... | 5f6ffd4e7954984d43ebc00c108d268797831256 | 25,851 |
def shiftField(field, dz):
"""Shifts the z-coordinate of the field by dz"""
for f in field:
if f.ID == 'Polar Data':
f.set_RPhiZ(f.r, f.phi, f.z + dz)
elif f.ID == 'Cartesian Data':
f.set_XYZ(f.x, f.y, f.z + dz)
return field | c3c592356dc21688049a94291d075879a12012ee | 25,852 |
def pair_equality(dataframe, column_1, column_2, new_feature_name):
"""
Adds a new binary feature to an existing dataframe which, for every row,
is 1 if and only if that row has equal values in two given columns.
:param dataframe:
Dataframe to add feature to
:param column_1:
Name of... | d82a02c49399351aa62b712664bb9500390ebf81 | 25,853 |
import networkx
import itertools
def compute_diagram(PhenosObj, FnameJson=None, FnameImage=None, Silent=False):
"""
todo: finish code
todo: add unit tests
computes the phenotype diagram from the phenotypes object obtained from :ref:`phenotypes_compute_json`.
save the diagram as json data with *Fn... | f2cfa298807f7969d93dafd76d403d4d8bddcb11 | 25,854 |
def identity_block(input_tensor, kernel_size, filters, stage, block):
"""The identity block is the block that has no conv layer at shortcut.
# Arguments
input_tensor: input tensor
kernel_size: default 3, the kernel size of middle conv layer at main path
filters: list of integers, the fil... | 3d33a0bec933697eae642199fe7b24e90e45e15b | 25,855 |
from typing import Optional
def find_linux_kernel_memory(
pml4: PageTable, mem: Memory, mem_range: Interval
) -> Optional[MappedMemory]:
"""
Return virtual and physical memory
"""
# TODO: skip first level in page tables to speed up the search
# i = get_index(mem_range.begin, 0)
# pdt = pag... | 6b08bfb2c8a0f98ef250a8268a076b72496bd89f | 25,856 |
def cnn_encoder(inputs, is_train=True, reuse=False, name='cnnftxt', return_h3=False):
""" 64x64 --> t_dim, for text-image mapping """
w_init = tf.random_normal_initializer(stddev=0.02)
gamma_init = tf.random_normal_initializer(1., 0.02)
df_dim = 64
with tf.variable_scope(name, reuse=reuse):
... | 9c66cd9a2b9589da89572779dc01117b7f349fee | 25,857 |
def cmp_id(cls1, cls2, idx1, idx2):
"""Compare same particles between two clusters and output numbers
Parameters
----------
cls1,cls2: Cluster object
idx1,idx2: Indices of detected particles in the clusters.
Output
------
The number of same particles.
"""
partId1 = cls1.gas_id[... | b3ebf4a3c98da18a84545caff446e0d1732208a0 | 25,858 |
def get_clinical_cup():
"""
Returns tuple with clinical cup description
"""
return ("8", "2", "M", "01", 25) | fac133ea74fbe30b50e551fdd7cdce349cc02a3a | 25,859 |
def to_utm_bbox(bbox: BBox) -> BBox:
"""Transform bbox into UTM CRS
:param bbox: bounding box
:return: bounding box in UTM CRS
"""
if CRS.is_utm(bbox.crs):
return bbox
lng, lat = bbox.middle
utm_crs = get_utm_crs(lng, lat, source_crs=bbox.crs)
return bbox.transform(utm_crs) | 80e67ce402ba1551a5282f93fc629be78255e96a | 25,860 |
def define_actions(action):
"""
Define the list of actions we are using.
Args
action: String with the passed action. Could be "all"
Returns
actions: List of strings of actions
Raises
ValueError if the action is not included in H3.6M
"""
actions = ["walking", "wiping", "lifting", "co-exis... | 45bfbd20971a04f566feeed0de509b21be83963b | 25,861 |
def gen_order_history_sequence(uid, history_grouped, has_history_flag):
""" 用户订单历史结果构成的序列 """
# 311 天的操作记录
sequence = ['0'] * 311
if has_history_flag == 0:
return sequence
df = history_grouped[uid]
for i in df['days_from_now']:
sequence[i] = str(df[df['days_from_now'] == i].shap... | 9f9e93549ea4c35971f87957b74e44e258d79d49 | 25,862 |
def _get_plugin_type_ids():
"""Get the ID of each of Pulp's plugins.
Each Pulp plugin adds one (or more?) content unit type to Pulp. Each of
these content unit types is identified by a certain unique identifier. For
example, the `Python type`_ has an ID of ``python_package``.
:returns: A set of pl... | 0c31a239980a2427f1fb115d890eea9d92edf396 | 25,863 |
def scale_48vcurrent(value, reverse=False, pcb_version=0):
"""
Given a raw register value and the PCB version number, find out what scale and offset are needed, convert the raw
value to Amps (if reverse=False), or convert a value in Amps to raw (if reverse=True).
For now, raw values are hundredths of a... | 562a9354f1648203ba9854f2404e00365e12f67f | 25,864 |
import pickle
def get_graph(graph_name):
"""Return graph, input can be string with the file name (reuse previous created graph),
or a variable containing the graph itself"""
# open file if its a string, or just pass the graph variable
if '.p' not in graph_name:
graph_name = add_extension(gra... | 0efe5cb90b6f8bf1fc59853704cf7e07038fb8fb | 25,865 |
import traceback
import sys
def max_function(context, nodeset, string):
"""
The dyn:max function calculates the maximum value for the nodes passed as
the first argument, where the value of each node is calculated dynamically
using an XPath expression passed as a string as the second argument.
htt... | 4a10eec7d82417d7950116a4f4d4313d7c81d27e | 25,866 |
def get_transfer_encodings():
"""Return a list of supported content-transfer-encoding values."""
return transfer_decoding_wrappers.keys() | c42dfd886b1080e6a49fe4dabc2616967855a7f0 | 25,867 |
def is_name_valid(name: str, rules: list) -> bool:
""" Determine whether a name corresponds to a named rule. """
for rule in rules:
if rule.name == name:
return True
return False | 41e9f88d86a078ca6386f1d0d6b7123233c819b9 | 25,868 |
def fig2data(fig, imsize):
"""
:param fig: Matplotlib figure
:param imsize:
:return:
"""
canvas = FigureCanvas(fig)
ax = fig.gca()
# ax.text(0.0, 0.0, "Test", fontsize=45)
# ax.axis("off")
canvas.draw()
image = np.fromstring(canvas.tostring_rgb(), dtype="uint8")
width,... | 5a8b7bf34d6aa3849f20b5ca140c572c5cad0e57 | 25,869 |
def draw_agent_trail(img, trail_data, rgb, vision):
""" draw agent trail on the device with given color.
Args:
img : cv2 read image of device.
trail_data : data of trail data of the agent
rgb : (r,g,b) tuple of rgb color
Returns:
img : updated image ... | 9524cb10cbe1ed7dceb8714c7ace443be64e8767 | 25,870 |
def get_total_received_items(scorecard):
""" Gets the total number of received shipments in the period (based on Purchase Receipts)"""
supplier = frappe.get_doc('Supplier', scorecard.supplier)
# Look up all PO Items with delivery dates between our dates
data = frappe.db.sql("""
SELECT
SUM(pr_item.received_q... | 856e5b42a1b572a6fa7150b789eb8754a045677d | 25,871 |
def generate_default_filters(dispatcher, *args, **kwargs):
"""
Prepare filters
:param dispatcher: for states
:param args:
:param kwargs:
:return:
"""
filters_list = []
for name, filter_data in kwargs.items():
if filter_data is None:
# skip not setted filter name... | e307b9933280bfc91ef25ac306586c3cc6cf8c94 | 25,872 |
def linear_map(x, init_mat_params=None, init_b=None, mat_func=get_LU_map,
trainable_A=True, trainable_b=True, irange=1e-10,
name='linear_map'):
"""Return the linearly transformed, y^t = x^t * mat_func(mat_params) + b^t,
log determinant of Jacobian and inverse map.
Args:
... | 1286fc8087288f94b1ef63388fc6c8636d061b2f | 25,873 |
def isolated_70():
"""
Real Name: b'Isolated 70'
Original Eqn: b'INTEG ( isolation rate symptomatic 70+isolation rate asymptomatic 70-isolated recovery rate 70\\\\ -isolated critical case rate 70, init Isolated 70)'
Units: b'person'
Limits: (None, None)
Type: component
b''
"""
retur... | b1185a6a03759830f7cfeaefae34389699e62c48 | 25,874 |
def db_retry(using=None, tries=None, delay=None, max_delay=None, backoff=1, jitter=0, logger=logging_logger):
"""Returns a retry decorator.
:param using: database alias from settings.DATABASES.
:param tries: the maximum number of attempts.
-1 means infinite.
None - get fr... | 5727bb89f55a8cc68cea2a35ea256b79b6b852da | 25,875 |
from typing import Collection
def A000142(start: int = 0, limit: int = 20) -> Collection[int]:
"""Factorial numbers: n! = 1*2*3*4*...*n
(order of symmetric group S_n, number of permutations of n letters).
"""
sequence = []
colors = []
x = []
for i in range(start, start + limit):
se... | c0c709529bb7926369912ea195aec5fba17f7887 | 25,876 |
import idwgopt.idwgopt_default as idwgopt_default
def default(nvars):
""" Generate default problem structure for IDW-RBF Global Optimization.
problem=idwgopt.default(n) generate a default problem structure for a
an optimization with n variables.
(C) 2019 by A. Bemporad.
"""
problem = idw... | 6e865ffdab0b3913c793357b6cb2688a6cd4dc00 | 25,877 |
from point import Point
from line import Segment
from polygon import Polygon
def convex_hull(*args):
"""
Returns a Polygon representing the convex hull of a set of 2D points.
Notes:
======
This can only be performed on a set of non-symbolic points.
Example:
========
>>> from ... | ee1c1fd65dfe849a36a6dfc8e86a4e1e2ee8ca69 | 25,878 |
from typing import Dict
def find_namespaces(tree: ElementTree) -> Dict[str, str]:
"""
Finds the namespaces defined in the ElementTree of an XML document. It looks for namespaces
defined in the root element of the XML document. To avoid namespaces being left out, they shall
all be defined in the root e... | 8b2a523c9d7152280fa609563e94eda4facebe4b | 25,879 |
def filterStories(stories, triggerlist):
"""
Takes in a list of NewsStory instances.
Returns: a list of only the stories for which a trigger in triggerlist fires.
"""
filteredStories = []
for story in stories:
for trig in triggerlist:
if trig.evaluate(story) and story not in... | 1fcf2592e22c97cd13919dbfe5b8a4acde682761 | 25,880 |
def lcs(a, b):
"""
Compute the length of the longest common subsequence between two sequences.
Time complexity: O(len(a) * len(b))
Space complexity: O(min(len(a), len(b)))
"""
# This is an adaptation of the standard LCS dynamic programming algorithm
# tweaked for lower memory consumption.
... | 0201e9efade98aece854e05d0910192251e5f63c | 25,881 |
def save(config, filename="image.img", host=None):
"""Save the Image File to the disk"""
cmd = DockerCommandBuilder(host=host).save(config.getImageName()).set_output(filename).build()
return execute(cmd) | 628dca6307b6a5d975e90e08649f20790bc8b639 | 25,882 |
from typing import Dict
from typing import Any
import sys
def klass_from_obj_type(cm_json: Dict) -> Any:
"""Get reference to class (n.b. not an instance) given the value for a key 'obj_type' in the given json dict"""
module_name, klass_path = cm_json['obj_type'].rsplit('.', 1)
# @todo make this load from ... | daf9c4d8579d3da7383abdfc38c9af0d4161d302 | 25,883 |
def lines2bars(lines, is_date):
"""将CSV记录转换为Bar对象
header: date,open,high,low,close,money,volume,factor
lines: 2022-02-10 10:06:00,16.87,16.89,16.87,16.88,4105065.000000,243200.000000,121.719130
"""
if isinstance(lines, str):
lines = [lines]
def parse_date(x):
return arrow.get(... | 4d2049d08f885de3b999b1537a48c03088f45da3 | 25,884 |
import torch
def pgd_linf_untargeted(model, X, y, epsilon=0.1, alpha=0.01, num_iter=20, randomize=False):
""" Construct FGSM adversarial examples on the examples X"""
if randomize:
delta = torch.rand_like(X, requires_grad=True)
delta.data = delta.data * 2 * epsilon - epsilon
else:
... | b19091048d269853c6b55c4d96d5919c4efcfbe6 | 25,885 |
def cal_NB_pvalue (treatTotal,controlTotal,items):
"""calculate the pvalue in pos of chromosome.
"""
pvalue = 1
(treatCount,controlCount,pos)=items
pvalue = negativeBinomail(treatCount,treatTotal,controlCount,controlTotal)
return (pvalue,treatCount,controlCount,pos) | f68809ffb40949c2d4ca1486870ec421d48bbfb5 | 25,886 |
def handle_watches(connection, author):
"""Return an array of watches for the author."""
database = connection['test']
collection = database['watches']
watches = []
# this should not except
for post in collection.find({"author" : ObjectId(author)}):
watches.append(cleanup_watc... | bfb765e30d249fac30fdbf567006283be1808e6c | 25,887 |
def new_mm(*args, figsize, **kwargs):
"""Wrapper for plt.subplots, using figsize in millimeters
:rtype: figure, axes
"""
return plt.subplots(*args, figsize=(figsize[0] / 25.4, figsize[1] / 25.4), **kwargs) | 7111f1fd8261d3367bff03fd36ed86cc26917fe8 | 25,888 |
def compute_center_of_mass(coordinates, masses):
"""
Given coordinates and masses, return center of mass coordinates.
Also works to compute COM translational motion.
Args:
coordinates ({nparticle, ndim} ndarray): xyz (to compute COM) or velocities (COM velocity)
masses ({nparticle,} arr... | d190c20930209e180524c07c8bf8fef9ab95734b | 25,889 |
def chars_count(word: str):
"""
:param word: string to count the occurrences of a character symbol for.
:return: a dictionary mapping each character found in word to the number of times it appears in it.
"""
res = dict()
for c in word:
res[c] = res.get(c, 0) + 1
return res | 30c27b23c04909a65264247d068e9e2c695c6ecc | 25,890 |
def do_expressiondelete(**kwargs):
"""
Worker to remove expression from engine
proexpobj: expression object
profileexplist: expression list object
return 0 if expression deleted
"""
proexpobj = kwargs.get('proexpobj')
profileexplist = kwargs.get('profileexplist')
if profileexplist.... | 4d4f26aca34417026ac326d237f817b88afe525c | 25,891 |
import csv
def read_csv_as_nested_dict(filename, keyfield, separator, quote):
"""
Inputs:
filename - name of CSV file
keyfield - field to use as key for rows
separator - character that separates fields
quote - character used to optionally quote fields
Output:
Returns a ... | b86a19e531ac2d0c815839714ee93fbc618e911d | 25,892 |
def msgpackb(lis):
"""list -> bytes"""
return create_msgpack(lis) | 4e2667ff32c58be09620cd8360ff0207406a7871 | 25,893 |
from azureml._execution import _commands
from azureml.core.runconfig import RunConfiguration
from azureml._project.project import Project
def prepare_compute_target(experiment, source_directory, run_config):
"""Prepare the compute target.
Installs all the required packages for an experiment run based on run_... | d6a7f2f45483c2e0a42bcb03407791ca781318ab | 25,894 |
def streaming_ndarray_agg(
in_stream,
ndarray_cols,
aggregate_cols,
value_cols=[],
sample_cols=[],
chunksize=30000,
add_count_col=False,
divide_by_count=False,
):
"""
Takes in_stream of dataframes
Applies ndarray-aware groupby-sum or groupby-mean: treats ndarray_cols as ... | a47a3f82444dc1ef7d5eb5f63d7dd77c862fc605 | 25,895 |
from typing import List
def get_cropped_source_data(
stack_list: List[str], crop_origin: np.ndarray, crop_max: np.ndarray
) -> np.ndarray:
"""
Read data from the given image files in an image stack
:param List[str] stack_list: List of filenames representing images in a stack
:param np.ndarray cro... | 40f2537417a99d070979ba206de7c6e91a313b02 | 25,896 |
def valid_random_four_channel_images() -> str:
"""
Make a folder with 5 valid images that have 4 channels.
:return: path to the folder
"""
# use .png because that supports 4 channels
return make_folder_with_files('.png', file_type='image', resolution=(300, 300), n_files=6, channels=4) | 6b39f46467b4ded5a773964255293a3b587d9b6d | 25,897 |
def build_template(spec) -> Template:
"""Build a template from a specification.
The resulting template is an object that when called with a set of
bindings (as produced by a matcher from `build_matcher`), returns
an instance of the template with names substituted by their bound values.
This is a g... | ef44befe0a937b786a48b1e1ddf729f5c1327e3b | 25,898 |
def flatten_objective(expr):
"""
- Decision variable: Var
- Linear: sum([Var]) (CPMpy class 'Operator', name 'sum')
wsum([Const],[Var]) (CPMpy class 'Operator', name 'wsum')
"""
if __is_flat_var(expr):
return (expr, [])... | 65cea292a03bca4a8bece31e5b2b6d32ae07a77a | 25,899 |
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