content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def create_chord_arpeggio(chords_duration, notes_list, density):
"""
コードをアルペジオで弾く場合のリズムと音を決定
Parameters
chord_duration: int/float
そのコードを継続する時間
0.5→1拍
notes_lsit: list[int]
コードの構成音
density: 0 or 1
0: 密度低め
1: 密度高め
Rerturns
list(tuple(int, int/float)... | fb716d6204bc956288a863bbcd5cbbaa68cdddf6 | 3,596,629 |
def get_p_val(rank_table):
"""
Input:
"""
r = 1-rank_table["rank"]*1./(rank_table["out_of"]+1)
r.sort()
r.name = "p_value"
return r | 387b819f1a028e42bedd301e2324c0b25c159ca8 | 3,596,630 |
def shift_tokens_right(input_ids, pad_token_id, decoder_start_token_id):
"""
Shift input ids one token to the right.
"""
shifted_input_ids = input_ids.new_zeros(input_ids.shape)
shifted_input_ids[:, 1:] = input_ids[:, :-1].clone()
shifted_input_ids[:, 0] = decoder_start_token_id
assert pad_... | c25ba549849d3781f9a03f2c25cb8c9277c201b2 | 3,596,631 |
def CasadiMeta_git_describe(*args):
"""
git_describe() -> char const *
"""
return _casadi.CasadiMeta_git_describe(*args) | d47809e0b7a627fd3831a3e71d66229e74e4c052 | 3,596,632 |
def index(request):
"""
总览
:param request:
:return:
"""
return render(request, 'overview.html', {'active_nav': 'overview'}) | f9bbb5b8a5c11b01f78d90c273f263600ae75951 | 3,596,633 |
def delete_page():
""" Delete instruction document page """
return event_handler_for(request).get_response() | b71a8a124af272c0bf9ab6f8c0f0fdc5ce50bd58 | 3,596,634 |
def free_space_path_loss(freq: float, distance: float) -> float:
"""Calculate free-space path loss
Standard formula, also known as (one of) the Friis formula(e).
Args:
freq: A `float` with the frequency of the transmitter.
Unites are GHz.
distance: A `float` with the path len... | a4cd466c27b5f6c024247413aeda2f5105803e00 | 3,596,635 |
from re import VERBOSE
def migrate(engine_from, engine_to, tables, chunk_size=DEFAULT_CHUNK_SIZE, collation=None,
create=True, drop=False, fill=True, filtering_cols=None, filtering_row=None,
mssql_from=DEFAULT_DB_MSSQL, mssql_to=DEFAULT_DB_MSSQL, schema=DEFAULT_SCHEMA,
test=ASSERT,... | ee83cc8cc23e421546ac00d8e99dd35734bba43b | 3,596,637 |
def next_child(license):
"""Return the node defined at the top of the given license.
A node object is returned.
"""
nchild, nmeta = license[:2]
if nchild == 0:
return Node([], license[2:2+nmeta], 2+nmeta)
children = []
index = 2
for _ in range(nchild):
child = next_child... | 78db559221257ec7d243f809751a015f11ce62d2 | 3,596,638 |
from typing import Optional
import math
def viewer(
structure: Structure,
show_unitcell: bool = True,
show_bonds: bool = True,
show_outside_bonds: bool = False,
show_polyhedrons: bool = True,
local_env_strategy: Optional[NearNeighbors] = None,
show_magmom: bool = False,
magmom_scale: f... | 96ec2ee0fa46940c69a3b7ca39931096723ff58d | 3,596,639 |
def _complexity_delay_entropyratio(
signal,
delay_max=20,
dimension_max=5,
surrogate_n=5,
surrogate_method="random",
show=False,
):
"""Joint-optimization using Entropy Ratio method.
* Gautama, T., Mandic, D. P., & Van Hulle, M. M. (2003, April). A differential entropy based
method... | ef7bcfcff7418b20e6e7c75efd60d2cef8e62dc8 | 3,596,640 |
def _change_galician_cc_token_before_subtree(sentence, token):
"""Determine the token directly preceding a subtree in a sentence.
Args:
sentence (`Sentence`): The sentence.
token (`Token`): The root token of the subtree.
Returns:
str: The ID of the token directly preceding the root token and all of its dep... | 21eebf0ba9ec02af4a7c65e8631a95e83b68372e | 3,596,641 |
def home_add(request, item_container):
""" neues Home-Verzeichnis anlegen """
class DmsItemForm(forms.Form):
name = forms.CharField(max_length=60,
widget=forms.TextInput(attrs={'size':20}) )
app_name = 'home'
my_title = _(u'Home-Verzeichnis anlegen')
# --- Sind Daten vorha... | 0aecc3b5b4a649fd1dfd40a6ee80409e534f90d0 | 3,596,642 |
import torch
def get_jacobian(inputs, func, **kwargs):
"""
Return Jacobian matrix of size m x n
of a function f: R^n -> R^m
"""
size = inputs.size()
n = size[0]
# Input dim
if (len(size)) > 1:
dim_input = size[1]
else:
dim_input = 1
test = func(inputs, **kw... | 5ff764a11512ed3813956c7549562761b430092f | 3,596,643 |
def get_active_users_this_semester() -> int:
"""
Count the number of users registered for at least one course this semester
:return: The number of users registered for at least one course this semester
"""
return (
User.query.join(InCourse, User.id == InCourse.owner_id)
.join(Course... | 2192a61b4e3cd1a220c4839f58e7321caee2327c | 3,596,644 |
def get_headers(file_path):
"""
Gets the headers.
:param file_path: File path.
:return: Headers.
"""
h = Headers()
h.add('Content-Disposition', 'attachment', filename=file_path)
return h | ba9301052e34370c6c090922f9ff11f6a42a8fb7 | 3,596,645 |
from typing import Callable
from typing import Union
from typing import List
import random
def padding(policy="random"):
"""
Overview:
Fill the nested buffer list to the same size as the largest list.
The default policy `random` will randomly select data from each group
and fill it int... | 9cd15bb122485cbcc7c5cde4c9660b7b019285f1 | 3,596,646 |
def generate_create_simulations_result_table_sql():
""" Generates an SQL statement to create a table on the database where the results of the simulations are stored.
It uses the output params file defined by the user to define the schema of the table. All the columns
representing an output parameter... | d2e7a115257fd1ae325ce9bfae0b5a31835e77ca | 3,596,647 |
def write_series(all_series: str, number: int, issn: str) -> str:
"""
Write series information to XML snippet.
:param all_series: A string containing 1+ series separated by || double pipes. Series number information, if provided, is separated by ; colon.
:param number: An int or np.nan containing serie... | b9499d6f88f6db171dbb17ad653bc612e1cdf7c7 | 3,596,648 |
import torch
def explained_variance(ypred,y):
"""
FROM: Open AI Baselines
Computes fraction of variance that ypred explains about y.
Returns 1 - Var[y-ypred] / Var[y]
interpretation:
ev=0 => might as well have predicted zero
ev=1 => perfect prediction
ev<0 => worse t... | e7220bbbdcf8a3918bc9f63aa6817470fd4ad160 | 3,596,649 |
from typing import Optional
import array
def z_snapshot(state: State, contraction_options: Optional[dict] = None) -> array:
"""
<state| S^z | state> for all positions of S^z
"""
if contraction_options is None:
contraction_options = {}
return expval_snapshot(state, sz, hermitian=True, **con... | 51450255436086deae09e1e182bdce6049c97bd3 | 3,596,650 |
def turn(p1, p2, p3):
"""
0 if the points are colinear
1 if the points define a left-turn
-1 if the points define a right-turn
"""
# Compute the z-coordinate of the vectorial product p1p2 x p2p3
z = (p2[0] - p1[0]) * (p3[1] - p1[1]) - (p2[1] - p1[1]) * (p3[0]- p1[0])
return 0 if z == 0 e... | 2b8dccbe0111d9cd655f4a6a8bc2131b73f3a3ee | 3,596,651 |
from typing import List
from typing import Tuple
def get_edge_colours_and_widths(graph: nx.Graph, path: List[Tuple[int, int]]) -> Tuple[List[str], List[int]]:
"""
Get properties for plotting the graph.
When using networkx's graph visualization tool it is possible to customize
the colour and width of ... | 903644696d59a35b86674d4ef2c394547d68f4ea | 3,596,652 |
def discriminator_output_class(input_net, class_num):
"""Output Layer for Domain Classification in the Discriminator.
The original paper use convolution layer where the kernel size is the height
and width of the Tensor. We use an equivalent operation here where we first
flatten the Tensor to shape (batch_size,... | bf746e3a6e9e4ac18af5ccf15406af86a9bed6e0 | 3,596,653 |
def sign(
data, pkey_buffer, pkey_pass=_ffi.NULL, digest_name="sha1"):
"""
Sign data with private key. Returns binary signature
:param unicode data: Data to sign
:param bytes pkey_buffer: Private key
:param unicode pkey_pass: Private key's passphrase
:param str digest_name: Message dige... | b4fabdd7daca63bb8c2b77534b5e4e512a444a31 | 3,596,654 |
def change_point_score(distances, window_size):
"""
Gives the change point score for each time stamp. A change point score > 0 indicates that a new segment starts at that time stamp.
Args:
distances: postprocessed dissimilarity measure for all time stamps
window_size: window size used in TD for CPD... | 6f631306d25ff0b88c45a06bfdce7a0558620e95 | 3,596,655 |
def gentorque(x, p):
"""
INPUTS:
x: generator or rotor speed
p= (RtGnSp, RtTq , Rgn2K , SlPc , SpdGenOn)
RtGnSp Rated generator speed for simple variable-speed generator control (HSS side) (rpm)
RtTq Rated generator torque/constant generator torque in Region 3 for simple variable-spee... | a600dbddeb232cfaef9286a2c6b8a089f1511872 | 3,596,656 |
def make_sample_her_transitions(replay_strategy, replay_k, reward_fun):
"""
Creates a sample function that can be used for HER experience replay.
:param replay_strategy: (str) the HER replay strategy; if set to 'none', regular DDPG experience replay is used
(can be 'future' or 'none').
:param r... | 8351e28710c845833e147c2d2dc69e56c6d33795 | 3,596,657 |
def bjmm_depth_3_complexity(n, k, w, mem=inf, hmap=1, memory_access=0):
"""
Complexity estimate of BJMM algorithm in depth 3
[MMT11] May, A., Meurer, A., Thomae, E.: Decoding random linear codes in 2^(0.054n). In: International Conference
on the Theory and Application of Cryptology and Information Sec... | 11e6596c71cb995e123808699f4a77324589ae42 | 3,596,658 |
import asyncio
async def collect_regions_prices(config: Config, regions: list[Region]) -> Box:
"""Get the current prices for multiple regions."""
prices_tasks = [awattprice.prices.get_current_prices(region, config, fall_back=False) for region in regions]
regions_prices = await asyncio.gather(*prices_tasks... | c264179cd0d25a75e40b581252521bf984c31f42 | 3,596,660 |
def decode_bboxes(score_thresh, scores, bboxes, anchors, scale=128, best_only=False):
"""
wi, hi : NN input shape
mediapipe/calculators/tflite/tflite_tensors_to_detections_calculator.cc
# Decodes the detection tensors generated by the model, based on
# the SSD anchors and the specification in the op... | a1a31c8aefd40b14554de273020d1a68e137fceb | 3,596,661 |
def calcExpEntropy(data, feature):
"""
Calculate the expected entropy from splitting on the specified feature.
Note: it's not guaranteed that we check all possible features--we only iterate over those
feature values encountered in the data. That's okay since a feature with 0 frequency would
... | 2d1628ca970c49397a21abc23fe1c746a9b7eb83 | 3,596,662 |
def get_abs_rel_destination_path(dst_root, src):
"""Obtain absolute path from a proto file path combined with destination root.
Creates the parent directory if necessary.
Args:
dst_root: destination root path.
src: source path.
"""
rel_dst_path = get_destination_path(src)
dst =... | f1a3c0da2d4c68eb4cbf8f721b16b4fd37832322 | 3,596,663 |
def find(node):
"""Find current canonical representative equivalent to node.
Adjust the parent pointer of each node along the way to the root
to point directly at the root for inverse-Ackerman-fast access.
"""
if node.parent is None:
return node
root = node
while root.parent is not ... | c9827af585c2bcd284640213bb92ae951659abf8 | 3,596,664 |
def is_a_shape(node):
"""
Checks node type to determine if the given node is a shape or not
:param node: str
:return: bool
"""
if not maya.cmds.objectType(node, isAType='shape'):
return False
return True | fb3590010a22a920004973f578d120a4860fc554 | 3,596,665 |
from datetime import datetime
import requests
import json
def promapi():
"""
Retun Prometheus query result in HTML
"""
report_date = datetime.today().strftime('%B %Y')
duration = '[' + str(24) + 'h]'
response = requests.get(Prometheus_URL + '/api/v1/query',
params={
'query': ... | c639f40e78eb1e61497e7dd0e93beea83fafd5d0 | 3,596,666 |
def scatter(ab):
"""
"""
ab.sel = "TO SC BT BT BT BT SA"
fr = ab.iflg("SC")
a_opol, b_opol = ab.rpol_(fr=fr-1)
a_npol, b_npol = ab.rpol_(fr=fr)
a_odir, b_odir = ab.rdir(fr=fr-1,to=fr)
a_ndir, b_ndir = ab.rdir(fr=fr,to=fr+1)
a_ct = costheta_( np.cross(a_opol, a_ndir ), a_opol )
... | 06fa968915b3b903df91ddbb2e989fbf9eee328e | 3,596,667 |
def wheel(np, pos):
""" Input a value 0 to 255 to get a color value.
The colours are a transition r - g - b - back to r.
Source: Adafruit tutorials
"""
if pos < 0 or pos > 255:
r = g = b = 0
elif pos < 85:
r = int(pos * 3)
g = int(255 - pos * 3)
b = 0
... | 77212a0e7e34fe0a7a65c706820b2f7882165785 | 3,596,669 |
def make_faces(mesh, vectors): # no dep
"""
Initialize a dictionary of `Face` objects.
Parameters
----------
mesh : `compas.Mesh`
A COMPAS mesh.
vectors : `dict`
A mapping of face keys to vectors {fkey: vector}
Notes
-----
Faces and vectors keys are assumed to matc... | 098950887861c060bfdd5e9cf53f301b63799e46 | 3,596,671 |
def create_unit_classes(units):
"""Creates an ordered list of UnitClasses. Any and all UnitClasses required for the test inputs should appear here.
"""
t1mex = UnitClass("T1 Mass Extractor")
t1mex.set('a', units['uab1103'])
t1mex.set('e', units['ueb1103'])
t1mex.set('r', units['urb1103'])
t... | 441ec280fec7b5935f5e55c8bc4a464098aac48a | 3,596,672 |
def forward_propagation(X, parameters, training, istanh1, istanh2, batchnorm, dropout = 1.0, regression = False):
"""
Implements the forward propagation for the model: LINEAR -> RELU -> LINEAR -> RELU -> LINEAR -> SOFTMAX
Arguments:
X -- input dataset placeholder, of shape (input size, number of exampl... | 2b132731f5c3c83abb04328929a4f3239d475e43 | 3,596,673 |
def worker_number(worker_id):
"""Get the current worker number."""
id_as_str = "".join(ch for ch in worker_id if ch.isdigit())
if len(id_as_str) == 0:
return 0
return int(id_as_str) | 3cd6ca7e665fefda9427476e39de5ea23f843f72 | 3,596,675 |
def moving_average_convergence_divergence(data, short_period, long_period):
"""
Moving Average Convergence Divergence.
Formula:
EMA(DATA, P1) - EMA(DATA, P2)
"""
check_for_period_error(data, short_period)
check_for_period_error(data, long_period)
macd = ema(data, short_period) - ema(da... | bcede112c3c864f733138b516fd6fc6f7d6a1bce | 3,596,676 |
from typing import Optional
def get_team(name: Optional[str] = None,
parent: Optional[str] = None,
opts: Optional[pulumi.InvokeOptions] = None) -> AwaitableGetTeamResult:
"""
Use this data source to get information about a specific [team](https://v1.developer.pagerduty.com/documentat... | 744eddff4ad555c092720ae55a038dd350379c81 | 3,596,677 |
import torch
def bbox_iou(box1, box2, x1y1x2y2=True):
"""
Returns the IoU of two bounding boxes
"""
if not x1y1x2y2:
# Transform from center and width to exact coordinates
b1_x1, b1_x2 = box1[:, 0] - box1[:, 2] / 2, box1[:, 0] + box1[:, 2] / 2
b1_y1, b1_y2 = box1[:, 1] - box1[:... | 0ce3f23c829243f094250c7327f0e16422f3270a | 3,596,679 |
import typing
def borda_exp(
num_seats,
candidates: typing.List[Candidate],
votes: typing.List[Vote],
do_explain=False,
**kwargs,
) -> typing.List[Candidate]:
"""Borda Count with parametrized exponential weighting."""
weight = kwargs["weight"]
candidates = {c.id: BordaCandidate(c.id) ... | 3235d6829e2a6f53861548c4c358c5ed671ee7e3 | 3,596,680 |
def cumulative_gaussian_distribution(z):
"""standard cumulative Gaussian distribution"""
return 0.5*(1 + erf(z/2**0.5)) | 634020551c82b9b653ae3a40f3c7f43f82d8ad35 | 3,596,681 |
def load_drug_descriptors_old(ncols=None, scaling='std', add_prefix=True):
"""Load drug descriptor data, sub-select columns of drugs descriptors
randomly if specificed, impute and scale the selected data, and return a
pandas dataframe.
Parameters
----------
ncols : int or None
n... | a7274d177da8bb564fe498c8bc6638ebadeabb36 | 3,596,682 |
def alpha(r, w):
"""
Computes dimensionless parameter involving the radial distance and the beam
radius for calculation convenience.
Args:
r: radial distance from the center axis of the beam
w: radius at which the field amplitude fall to 1/e
Returns:
dimensionless parameter
... | 0f38467042077f8771a3b456ffd753e9a009025d | 3,596,684 |
def as_shr(data):
"""
Take data as either `fun`, `img`, `omegar`, `omegac`, or `mat`
and convert to `omegar` (unless already).
Parameters
----------
data: ndarray
Returns
-------
omegar: ndarray(shape=(N**2,), dtype=float)
"""
if data.ndim == 2:
if data.shape[0] == ... | e9a80afb0f30e63f7e07fdc09a8ce90928d7de01 | 3,596,685 |
import math
def calc_mach(var_lambda: float, gamma=1.4) -> float:
""""
Returns Mach number instead superficial velocity
Parameters
----------
var_lambda: float
superficial velocity of flow
gamma: float
isentropic exponent (default 1.4)
Returns
-------
M: float
... | c12aafd8d4d9fc4c544e73da890d311e3613d4d1 | 3,596,686 |
import string
import re
def rm_non_textual_punct(dfcol):
""" Aggressively remove almost all punctuation (except .,?:;- ) """
text_punct = '.,?:;-' #this also removes + <> $ %
nontext_punct = [char for char in string.punctuation if char not in text_punct]
nontext_punct = re.escape(''.join(nontext_punct... | ff9dfc87ec0015b4a0d0ca5d83db3b116e476470 | 3,596,688 |
def get_reference_value_from_spec(openapi_spec: dict, reference_path: str) -> dict:
"""Follows the reference path passed in and returns the object at the end of the path
Args:
openapi_spec (dict): The openapi.json specification object
reference_path (str): a path formatted as "#/foo/bar/baz"
... | c32962a3b008825de4c5108d8d1a3ad5db179b17 | 3,596,689 |
def tf_serialize_example(f0, f1, f2):
"""Use the tf.data.Dataset.map method to apply a function to each element
of a Dataset. The mapped function must operate in TensorFlow graph mode:
It must operate on and return tf.Tensors. A non-tensor function, like
serialise_example, can be wrapped with tf.py_func... | 7699fde753de5b873ca900f4d475027d6507f6d0 | 3,596,690 |
def hide_keys(dictionary, keys_to_hide, new_value="xxx"):
"""
Return a copy of the given dictionary on which specified keys will be replaced by the new_value word (or 'xxx').
:param dictionary: a dictionary
:param keys_to_hide: keys to hide in the output dictionary
:param new_value: replacement str... | d6b8bc7958c637212899c048a9958ac3d2755894 | 3,596,691 |
def simulate_multiple_examples(examples, method=RK4, duration=30, step_size=0.001):
"""Solve multiple examples. Usually used in conjunction with
`create_perturbations` function.
Args:
examples (list of class instances): list of examples we want to solve,
e.g. `DoublePendulum`
me... | ff7431a79c52cec0c6e33a282d22b430efe693b9 | 3,596,692 |
def respond(request: HttpRequest):
"""Responds to a serverside sitetable request.
:param request:
"""
return Table.respond(request) | a04ff149bd5ca99e9484082b968a15db1c4d8f50 | 3,596,693 |
def gen_coron_mask(self):
"""
Generate coronagraphic mask transmission images.
Output images are in 'sci' coordinates.
"""
mask = self.image_mask
pupil = self.pupil_mask
oversample = self.oversample
mask_dict = {}
if (not self.is_coron) and (not self.is_lyot):
mask_dict['DE... | 6648ee15ce1e8a6e36600a2cafd32208143c198b | 3,596,695 |
def get_latest_iter(wt_dir, wt_type='best'):
""" Get latest weights. """
latest_iter = get_most_recent_iteration(label=wt_type, wt_dir=wt_dir)
return latest_iter | 5423f9ced017c6a1333712bdbb582f0a8c144fc8 | 3,596,696 |
def saveSceneIfDirty(prompt=True):
"""
Prompt the user to save if the scene is modified, or has never been saved.
Returns True if the save was successful, or the scene has not been modified.
Args:
prompt (bool): If True, prompt the user, or attempt to automatically save where possible
"""
... | 4a14f727baf1cb203c8d208cfdaece6305e0805d | 3,596,697 |
def verify_results(settings, rdata, expected, wrapper,
model, atol, rtol):
"""Verify test results"""
amount_species, variables = get_amount_and_variables(settings)
# verify states
simulated = pd.DataFrame(
rdata['y'],
columns=[obs['name']
for obs in w... | c4c699b43c281f75828f5c7b60c16b021f78a2da | 3,596,698 |
def getList(sub, pred=None, db=None):
"""Attempts to return a list from sub (subject that is)
passed in if it is a Collection or a Container (Bag,Seq or Alt)"""
if not db:
if isinstance(sub, rdfSubject):
db = sub.db
else:
db = rdfSubject.db
if isinstance(sub, rdfS... | 98339bdb99d73b6ca026eae0653a10366f3b4257 | 3,596,699 |
from typing import Counter
def construct_vocab(self, *args, remove_punctuation=True, threshold=5,
startseq='<start>', endseq='<end>', unkseq='<unk>', padseq='<pad>'):
"""
Generate vocabulary object from all the captions
Parameters:
*args(pd.DataFrame): tokens dataframe
r... | 2fe242e835ddc3088aeadaad5cdf2fb1f273bfc6 | 3,596,700 |
def nircam_reorder(A, B, order):
"""Changes coefficient order from y**2 xy x**2 to x**2 xy y**2
Parameters
----------
A
B
order
Returns
-------
"""
terms = (order + 1) * (order + 2) // 2
A2 = np.zeros((terms))
B2 = np.zeros((terms))
for i in range(order + 1):
... | 28c4926fd11b955e71d8e8fa538ca96dfa3baa65 | 3,596,701 |
def hardness_region_competence(neighbors_idx, labels, safe_k):
"""Calculate the Instance hardness of the sample based on its neighborhood. The sample is deemed hard to
classify when there is overlap between different classes in the region of competence. This method does not
takes into account the target lab... | e2985c6d7459575346f77fe8a1458f8c574d6c60 | 3,596,702 |
def list_file_info(base, pattern, name_index=0, type=None):
"""
Constructs a list of tuples containing information about the files as indicated by the pattern.
The name_index should correspond to the index in the resulting tuple that contains the name of the file, default is 0
@param base path for files... | 41619bb1b1007dd9b5e59c56f0508bf4549531db | 3,596,703 |
def client(app):
""" Create test client for the app"""
return app.test_client() | 65eca0cc91d1131762cf698d32a3fe9bbf40e3d6 | 3,596,704 |
def get_seq(_seq, _start, _end):
"""
:param _seq:
:param _start: !!! should be SSR start position on genome (begin from 1, not 0)
:param _end: !!! should be SSR end position on genome (begin from 1, not 0)
:return:
"""
if _start <= 200:
return _seq.seq[0: _end+200]
elif _end >= ... | c42db6e6a50fa46c30e948ac6f007d5c92e07708 | 3,596,705 |
def distance(point_p, point_q, coordinate_system="cartesian"):
"""
Calculate the distance between two points in Cartesian or spherical coordinates
Parameters
----------
point_p : list or tuple or 1d-array
List, tuple or array containing the coordinates of the first point in the
foll... | e48773e3ef019cb305b503e1d05098a1027140a0 | 3,596,706 |
def storage_client(supabase: Client) -> SupabaseStorageClient:
"""Creates the storage client for the whole storage tests run"""
return supabase.storage() | 4f1d7837480b90e8a2fff4bc6fb1018393814010 | 3,596,708 |
import numpy.ma as MA
import numpy as N
from atmconst import AtmConst
def press2alt(arg, P0=None, T0=None, missing=1e+20, invert=0):
"""Calculate elevation given pressure (or vice versa).
Calculations are made assuming that the temperature distribution
follows the 1976 Standard Atmosphere. Technically t... | f125f5228f6cd435f1ccb2c158d898c52c9289a1 | 3,596,709 |
def verifica_dirs():
"""
Essa função é executada no momento da inicialização durante a barra de progresso, para verificar a existência dos di
retórios necessários para salvar os arquivos PDF's. Caso algum dele ou deles não existam, os mesmos serão criados.
:return: None
"""
outputs_directory = r... | fea200b0c7cdd560b552f13388c7c2a97eff58f6 | 3,596,710 |
def function(fn=None, **kwargs):
"""
Wraps a function with an AutoDiff Function instance, converting it to a
symbolic representation.
The function is compiled the first time it is called.
Use:
@function
def python_function(...):
return do_something()
python_fun... | 46dab8a3f451fd81a6b9e4e551c524b9f3972d04 | 3,596,711 |
from scipy.interpolate import interp1d
import numpy as np
def getFMext(wave,R,source):
"""
Input: wavelength in microns, nominal R = 3.1
source='f99' for Fitzpatrick 1999 or ='fmunred' for fmunred.pro
source='f99 tables' reproduces common misunderstanding from that paper
... | ad33a445e4d5ff67f8d962884955ea9349379338 | 3,596,712 |
def gamma2v(gamma):
""" See eq ? TT2015
"""
v = (1./3.)*np.sin(3.*gamma)
return v | 5a500f064a679ea7ee2d3ec1040ec8427771942b | 3,596,713 |
import re
def get_weight(tail):
"""Given the tail of a mime type header (the bit after the first ``;``),
find the ``q`` (weight, or quality) parameter.
If no valid ``q`` parameter is found, default to ``1``, as per the spec.
"""
match = re.search(q_match, tail)
if match:
try:
... | 352848d3d31c8dda2c17ef89d27d9c24623a8ded | 3,596,714 |
from typing import Optional
from typing import Callable
def in_range(_min: Optional[Number] = None, _max: Optional[Number] = None) -> Callable[[Number], bool]:
"""
Creates a number range validator
* It can work for any number type
Args:
_max (Optional[Number]): max value
_min (Optiona... | 2e719dd82453781738174d9707e9ad220c33228d | 3,596,715 |
import re
def login():
"""
1. 获取参数和判断是否有值
2. 从数据库查询出指定的用户
3. 校验密码
4. 保存用户登录状态
5. 返回结果
"""
# 1. 获取参数和判断是否有值
mobile = request.json.get("mobile")
password = request.json.get("password")
if not all([mobile, password]):
current_app.logger.error("参数不足")
return jso... | 6681780641a53a78dd6454af4ec264a806a7afa3 | 3,596,716 |
def get_crop_numpy(im: np.ndarray, pos: np.ndarray, sample_sz: np.ndarray, output_sz: np.ndarray = None,
mode: str = 'constant', avg_chans=(0, 0, 0), max_scale_change=None):
"""Sample an image patch.
args:
im: Image
pos: center position of crop
sample_sz: size to crop... | e56d92a5f6bcf91e9dc8941ba33568c920347fcf | 3,596,718 |
from typing import Callable
from typing import Iterable
import functools
def folder(function: Callable[[Range, Domain], Range],
initial: Range) -> Map[Iterable[Domain], Range]:
"""
Returns function that cumulatively applies given binary function
starting from given initial object in direction f... | 3e85929812974d57e94e1fbd1b6eaf925cff8d10 | 3,596,719 |
def ang2pix_hdr(coord,hdr,zero_offset=True):
"""
Apply forward (ra,dec)->(x,y) TAN transformation
A convenience function for calling ang2pix, with the transformations
described in a dictionary in the usual FITS header style for WCS
transformations.
Parameters
----------
coord... | 227b3f0eba449d95c4fcc05c19d96d6dbe65ff1e | 3,596,720 |
from .optuna import OptunaSuggest
def collapse_suggest_config(config: dict) -> dict:
"""Use the default value of OptunaSuggest for config items.
So that the configs can be used in the case that optuna is opted out.
Args:
config: The configuration dictionary
Returns:
The collapsed con... | f69ba41fdba0cf820a0bd22ff71a53bc13b27a8e | 3,596,721 |
def vmprofilestable():
"""
retrieves vm profiles in table
"""
baseconfig = Kbaseconfig()
profiles = baseconfig.list_profiles()
return render_template('vmprofilestable.html', profiles=profiles) | 40f65ea0f60bc99e62bc63b52dc3df561d6eda73 | 3,596,722 |
import requests
def get_google_sheet_df(
access_token: str,
google_sheet_id: str,
sheet_name: str = 'portfolio',
_range: str = 'A:Z'
) -> pd.DataFrame:
"""from: https://stackoverflow.com/questions/52365907/how-to-access-google-sheets-data-using-python-requests-module"""
url = ... | 35a110cc89c285329205aabfc9239ab5c37fd30f | 3,596,723 |
import random
def active_sample(network, size, evaluate):
"""
Sample from affected genes as null model.
"""
sample = random.sample(network.nodes(), size)
subnet = network.subgraph(sample)
result = evaluate(subnet)
return result | d5f7ecf87e6b72b5930fe066e13fd593626fd352 | 3,596,724 |
def get_cluster(name=None, project=None, region=None, zone=None):
"""
Get info about a cluster within GKE from its name and zone.
"""
__args__ = dict()
__args__['name'] = name
__args__['project'] = project
__args__['region'] = region
__args__['zone'] = zone
__ret__ = pulumi.runtime.... | b436e38ae83f0beb3e4dbd53667a529773e986c4 | 3,596,727 |
import requests
def attendance(regular=True, playoffs=True,
start_season=None, end_season=None):
"""
Query the NHL attendance number from 1975 to 2019 from the NHL records API.
The attendance represents annual attendance numbers for all teams.
The user can specify to return either the ... | c3fe53193528e5bad1f1cf1bf2d0eae420e5ee57 | 3,596,728 |
def get_other_dims(da, dims_exclude):
"""
Returns all dimensions in provided dataset excluding dim_exclude
| Author: Dougie Squire
| Date: 22/04/2018
Parameters
----------
da : xarray DataArray
Array to retreive dimensions from
... | 506a8b7193ea95480c83e3d69a31774f77d4fbcc | 3,596,729 |
def standard_split(text, row_length):
"""text = abcdefghijklmnopqrstuvwxyz and row_length = 5
abcde
fghij
klmno
pqrst
uvwxy
z returns ['afkpuz', 'bglqv', 'chmrw', 'dinsx', 'ejoty']
"""
output = []
text_length = len(text)
# Takes output column by index in turn, taking e.g... | 3a4732433b58777dcf08529b98b90f890e680a29 | 3,596,730 |
def initialize_opencv(filename, framesize, codec, fps: float = 30.0):
""" wrapper around opencv VideoWriter """
if codec == 0:
filename = filename + '_%06d.bmp'
fourcc = 0
fps = 0
else:
# filename = filename + '.avi'
fourcc = cv2.VideoWriter_fourcc(*codec)
# fourc... | b23eb23745b19c010581f9cb72c873c08fbe14df | 3,596,732 |
def gen_pie_plot(df):
"""Generates pie plots.
Shows the distribution of numbers drawn per ball (e.g. how many times the number 42 was drawn
for ball n°3).
Args:
df(dataframe): pandas dataframe containing all the draw results for the lottery
(dates/balls/stars).
Returns:
... | 8443adf8214e4d86b73f8104cc82b649e1e56482 | 3,596,733 |
def _process_frame_wob(frame):
"""
wob画面のみを切り取り、正規化する
"""
frame = frame[75:75+210, 10:10+160, :].astype(np.float32)
frame *= (1.0 / 255.0)
return frame | 426143a2e2bc7493ef93f696975c787799e0bd1d | 3,596,734 |
def lstm(num_hidden, indata, prev_state, param, seqidx, layeridx, dropout=0., num_hidden_proj=0):
"""LSTM Cell symbol"""
if dropout > 0.:
indata = mx.sym.Dropout(data=indata, p=dropout)
i2h = mx.sym.FullyConnected(data=indata,
weight=param.i2h_weight,
... | 8e9a7388644145ced4ebc5088b802264dedd742c | 3,596,735 |
def create_app(test_config=None):
"""
Returns a Flask web application with the default configuration pinging a TFX serving instance
on http://localhost:8503/v1/models/alpha:predict
"""
app = Flask(__name__, instance_relative_config=True)
app.config.from_mapping(
TFX_ENDPOINT='http://loca... | f1750fed0acc3be4c0bc1ee151bce0a6ac8df58b | 3,596,736 |
def median(x):
"""Return the median of a list of values."""
m, r = divmod(len(x), 2)
if r:
return sorted(x)[m]
return sum(sorted(x)[m - 1:m + 1]) / 2 | 337584e40c61bd198496355e38f4a8d4da9310fa | 3,596,737 |
def _get_args(tp):
"""Backport of typing.get_args for Python 3.6"""
return getattr(tp, "__args__", ()) | f265cb6d8d85601d9ee6f20be8f78c8d9819c920 | 3,596,738 |
def get_field(self, field_name):
"""Get the value of variables stored in Solution.
Parameters
----------
self : Solution
an Solution object
field_name : str
name of the field to return
Returns
-------
field: array
an array of field values
"""
... | 3d106d995a98407a64a61235d9a106e35968d20c | 3,596,739 |
def write_index():
"""Create markup for a new form submit with all tests.
"""
entries = []
for entry in get_tests():
if entry.title:
title = "".join(entry.title)
entries.append(TR_TD_COLS_4 % title)
if entry.url:
url = "".join(entry.url)
en... | 85a8bf192ce6ce4dc9414c4903a90de00ae40339 | 3,596,741 |
import json
def alchemy_json_encoder(revisit_self=False, fields_to_expand=[], fields_to_include=[], fields_to_ignore=[],
fields_to_replace={}, fields_to_transform={}):
"""Serialize SQLAlchemy result into JSon
Inpsired by: http://stackoverflow.com/questions/5022066/how-to-serialize-sq... | 69a7f38e3859d7d6a9675951050bf8700bf5a8d1 | 3,596,742 |
def portfolio_labels(statespace, n):
"""
Generate a collection of credit rating states emulating a snapshot of portfolio data. Suitable for mappings and transformations of credit rating states
:type statespace: The state space to use for the simulation
:param int n: The number of distinct entities to ge... | 78372ca2b0321c170da22bc7388018fa51f634aa | 3,596,744 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.