content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
from pathlib import Path
def fssurf_to_gifti(surf, fn=None):
"""
Converts FreeSurfer `surf` surface file to GIFTI format
Parameters
----------
obj : str or os.PathLike
FreeSurfer surface file to be converted
fn : str or os.PathLike, None
Output filename. If not supplied uses i... | 70e4709d9941da2db9b55702063503c1f692beb4 | 49,488 |
def dihedral_ranking_score(structure, residues, sec_struct_column="sec_struct_3state",
original=True):
"""
Assess quality of structure model by twist of
predicted alpha-helices and beta-sheets.
This function re-implements the functionality of
make_alpha_beta_score_table.... | 358141dce6678a25f89fc3660ae61eba6140cd77 | 49,489 |
def kernel(request):
"""Console kernel fixture"""
# Get kernel instance
kernel = get_kernel()
kernel.namespace_view_settings = {'check_all': False,
'exclude_private': True,
'exclude_uppercase': True,
... | 5f7937e5b307048cb28c38bde5c5fea7f38e35d0 | 49,490 |
from typing import Counter
def character_replacement(s: str, k: int) -> int:
"""https://leetcode.com/problems/longest-repeating-character-replacement"""
counter = Counter()
left = 0
max_length = 0
current_max_frequency = 0
for right, char in enumerate(s):
counter[char] += 1
cu... | ad67c5fbff990c0701d0c487b5aa6832d8bc2691 | 49,491 |
def build_sampler(tparams, options, use_noise, trng, sampling=True):
""" Builds a sampler used for generating from the model
Parameters
----------
See build_model function above
Returns
-------
f_init : theano function
Input: annotation, Output: initial lstm state and memory
... | 7ab927b5efd202841a4fe4a53338f0f2e9deb41a | 49,492 |
import hashlib
import time
def generate_tag_version():
""" Generates a new unique identifier for tag version."""
hash_value = hashlib.md5("{0}{1}{2}".format(
randrange(0, MAX_TAG_KEY), get_thread_id(), time.time()
).encode('utf8')).hexdigest()
return hash_value | a74389b2ede195d80887c18cd963bcf0fbe13f98 | 49,494 |
def _stem_words_list(list_words):
"""Stem words using a nltk stemmer
:param list_words: A list of strings representing words to stem
:rtype: A list of strings representing stemmed words
"""
stemmer = snowball.SnowballStemmer('english')
list_words_stemmed = {_stem(stemmer, word) for word in list... | a10cacc95e84b0abde38b2fa15a864b9cb8587c7 | 49,495 |
def read_data(location, type):
"""
This helps us read various filetypes directly into pyspark datframes. This is an allround solution.
"""
ftype = {
'avro' : "com.databricks.spark.avro",
'parquet' : "parquet",
'csv' : "com.databricks.spark.csv",
'json' : "json"
}
... | 4cc63fe1eead340e611552fddb863062bb5faca4 | 49,496 |
from typing import Optional
def get_app_user_assignments(id: Optional[str] = None,
opts: Optional[pulumi.InvokeOptions] = None) -> AwaitableGetAppUserAssignmentsResult:
"""
Use this data source to retrieve the list of users assigned to the given Okta application (by ID).
## E... | c5662bf77b608e6396bbd98f6521f247072e48e3 | 49,497 |
def clean_hotel_location(string):
"""
"""
if string is not None:
r = HTMLParser.HTMLParser().unescape(string)
r = commons.limpieza_barras_por_espacios(r)
if r.find('(') >= 0:
r = r[:r.find('(')]
if r.find('•') >= 0:
r = r[:r.find('•')]
if r.find('Chatl') >= 0:
r='El Chalten'
r=decutf_... | 3cdaf987d4e03eaf784c48d063cec97449e43817 | 49,498 |
from spatialpandas import GeoDataFrame, GeoSeries
from shapely.geometry.base import BaseGeometry
def from_shapely(data):
"""Converts shapely based data formats to spatialpandas.GeoDataFrame.
Args:
data: A list of shapely objects or dictionaries containing
shapely objects
Returns:
... | cb8ea3c5964dd5599e18d58c370d23d5d85d7f98 | 49,499 |
def handle(req):
"""handle a request to the function
Args:
req (str): request body
"""
ret_str = 'Hello OpenFaas. I received the following text:\n'
return ret_str + req | 9d4d4957bcd05c945b3e702f311cb81b8af74d73 | 49,500 |
def rlmErr(ols, w, spDcache):
"""
Robust LM error test. Implemented as presented in eq. (8) of Anselin et
al. (1996) [Anselin1996a]_
NOTE: eq. (8) has an errata, the power -1 in the denominator should be inside the square bracket.
...
Attributes
----------
ols : OLS_dev
... | edeedf967275934cc82d82369ae3ed3d4cabbdec | 49,501 |
import numpy
def max_ts(timeseries, nodata=-9999):
"""Maximum value of the time series.
:param timeseries: Time series.
:type timeseries: numpy.ndarray
:param nodata: nodata of the time series. Default is -9999.
:type nodata: int
:returns: Maximum value of time series.
"""
ts = fixs... | 77044f43b6fd8cb7fc872a18f7eb551f17225e7c | 49,502 |
def get_hole_declarations(program_vars):
"""Helper function for creating hole declaration with a grammar blow."""
grammar_spec = """
(
(Start Int (
(Variable Int)
(+ Start Start)
))
)
"""
grammar = templates.load_gramar_from_SYGUS_spec(grammar_spec... | 8c6f8161cd0e36447e65acb55963a5ae8cee93a9 | 49,503 |
def unit_scalar_to_str(value, n_digits=6):
""" Convert a UnitScalar to a string representation to display in text box.
"""
dimless_labels = [None, 'dimensionless', '1']
if value is None:
return ""
elif isinstance(value, UnitScalar):
number = value.tolist()
if isinstance(numbe... | b4512432862976bdd1327dc6d72bc8b97a9d8d9d | 49,504 |
def find_paths(iterable, searchfor, max_=0, searchtype='key', **kwargs):
"""Returns paths to 'searchfor'. If 'max_' is 0 all matches will be found"""
return objects.FindPath(iterable, searchfor, max_, searchtype, **kwargs).paths | fb458563e09085f1ef69e1d9711ff5c8ca21fc1b | 49,505 |
import csv
def process_overlap_files(inputfiles, header):
"""
:param inputfiles:
:param header:
:return:
"""
cage_cov = {'+': dict(), '-': dict()}
feat_count = col.Counter()
skip_partial = 0
for inpf in inputfiles:
with open(inpf, 'r', newline='') as infile:
row... | 1f8eb6856d261d4b845ee2967956180822dc92ac | 49,506 |
def where(cond, true_vals, false_vals=None):
"""
Use `true_vals` where `cond` is True, `false_vals` where `cond` is False
to build a merged dataset. The result will be empty where `cond` is empty.
`false_vals` are optional and if not provided, this will behave nearly the same as
`true_vals.filter(c... | 45883feeb0cfa8b24dbd53f18981677bb921d65d | 49,507 |
import ssl
def create_ssl_context(verify=True, cafile=None, capath=None):
"""Set up the SSL context.
"""
# This is somewhat tricky to do it right and still keep it
# compatible across various Python versions.
try:
# The easiest and most secure way.
# Requires either Python 2.7.9 o... | fe8db07f3d0043224cb3ca739fa43a1e3e69fdae | 49,508 |
def extract_domain(url):
"""Extract domain name from URL string"""
o = urlparse(url)
if o.scheme == '' and o.netloc == '':
o = urlparse("//" + url.lstrip("/"))
return o.netloc | 98ea9dbedb095f29e231095623baf7e24756d1f4 | 49,509 |
def diamond_graph(create_using=None):
"""Return the Diamond graph. """
description=[
"adjacencylist",
"Diamond Graph",
4,
[[2,3],[1,3,4],[1,2,4],[2,3]]
]
G=make_small_undirected_graph(description, create_using)
return G | 59909cabc48c5f7468af25ba4f045bf9440df86c | 49,510 |
def tensor_setitem_by_tuple_with_tensor(data, tuple_index, value):
"""Assigns the tensor by tuple with tensor value."""
op_name = const_utils.TENSOR_SETITEM
tuple_index = _transform_ellipsis_to_slice(data, tuple_index, op_name)
tuple_index, not_expanded_dim = remove_expanded_dims(tuple_index, F.shape(da... | fec629b57afd7b9e3ceb1ff8dd92501f2e297b03 | 49,511 |
def arpls(y, lam, ratio=1e-6, niter=1000, progressCallback=None):
"""
Return the baseline computed by asymmetric reweighted penalized least squares smoothing, arPLS.
Ref: Baseline correction using asymmetrically reweighted penalized least squares smoothing
Sung-June Baek, Aaron Park, Young-Jin Ahn a... | 94ba343ebc7ec9b039bdef2e1d1e67da2a11b521 | 49,512 |
def compressnumbers(s):
"""Take a string that's got a lot of numbers and try to make something
that represents that number. Tries to make
unique strings from things like usb-0000:00:14.0-2
"""
n = ''
currentnum = ''
for i in s:
if i in '0123456789':
#Exclude... | 952fe1a56a1864ce41031bb9bbea0fd440f9c3ef | 49,513 |
async def plot_index_bar_chart(tag_dict):
"""
Plots the index bar chart.
"""
x = np.array(list(tag_dict.keys()))
y = np.array(list(tag_dict.values()))
plt.clf()
plt.bar(x, y, color="green")
plt.xticks(fontsize=7)
plt.xlabel("Index", fontsize=7)
plt.ylabel("Number", fontsize=7)
... | 8afe547bdf55f5991b48f1f7c170e1bb5ccc3453 | 49,514 |
def _get_tile_output_shape(shape, multiples):
"""compute output shape of tile"""
if multiples is None:
return shape
if not isinstance(shape, (list, tuple)):
raise TypeError("Input shape of Tile must be of type list or tuple")
if not isinstance(multiples, (list, tuple)):
raise Ty... | ca787b55bed7591c6cf46aa6908d2c8d7053e755 | 49,515 |
from typing import Dict
import copy
def get_clinical_strat(params: Parameters, stratified_adjusters: Dict[str, Dict[str, float]]) -> Stratification:
"""
Stratify the infectious compartments of the covid model by "clinical" status, into the following five groups:
NON_SYMPT = "non_sympt"
As... | 566d5feb02f01b7082054968c73561caa758201e | 49,516 |
import requests
import logging
def service_is_ready():
"""
Used to show the "Haystack is loading..." message
"""
url = API_QUERY_ENDPOINT
try:
if requests.get(url).status_code < 400:
return True
except Exception as e:
logging.exception(e)
sleep(2) # To avoi... | 761bc784837767411c65ebedc8c054f156a08214 | 49,517 |
def medianfilt(img, kernel_shape):
"""[summary]
Aplies a median filter to an image, but adds the necessary padding to mantain the aspect ratio.
Args:
img (numpy array): Image array.
kernel_shape (tuple): Tuple indicating kernel shape.
Returns:
output (numpy array): processed... | 666ca3aa31cea2dbc8ba1dcf80ead5c1bd6a0fd0 | 49,518 |
import typing
def cik(apikey: str, cik_id: str) -> typing.List[typing.Dict]:
"""
Query FMP /cik/ API.
FORM 13F get company name by cik
:param apikey: Your API key.
:param cik_id: CIK value
:return: A list of dictionaries.
"""
path = f"cik/{cik_id}"
query_vars = {"apikey": apikey}
... | 1809dffd9a36a19f3d0c5c3e5069b476a7f122d3 | 49,519 |
def dec_indicator(encoded):
"""decode a Fudge Indicator.
Returns:
A Singleton INDICATOR object"""
return INDICATOR | 55cad8be678dd41c706c905a5d79b6e0d78cff62 | 49,520 |
def unordered_inverse(matrix):
"""
Takes in a matrix of values and maps each distinct row to a unique value
ex [[1 2 3] becomes [1,2,1]
[4 5 6]
[1 2 3]]
"""
num_rows = matrix.shape[0]
result = np.zeros((num_rows,))
state_map = dict()
state_count = 0
for index,row in enumerate(matrix):
row = row.... | 3dea723ee10375e0452d03caff64e107cea8e72e | 49,522 |
def _build_predict_signature(input_tensor, output_tensor_x, output_tensor_y):
"""Helper function for building a predict SignatureDef."""
input_tensor_info = tf.saved_model.utils.build_tensor_info(input_tensor)
signature_inputs = {"input": input_tensor_info}
output_tensor_info_x = tf.saved_model.utils.build_ten... | 481465ec77e4632cc4fd50a5c2df1f0dd83e2844 | 49,523 |
def filter_error_nodes(nodes):
"""Filter out ERROR nodes from the given node list.
:param nodes: candidate nodes for filter.
:return: a tuple containing the chosen nodes' IDs and the undecided
(good) nodes.
"""
good = []
bad = []
not_created = []
for n in nodes:
if ... | 409236f4f31abaecc999fb3fbc766d138c5c3618 | 49,524 |
def ds_cnn_params():
"""Parameters for toy "depthwise convolutional neural network" stride model."""
params = Params()
params.model_name = 'ds_cnn'
params.cnn1_kernel_size = '(3,2)'
params.cnn1_dilation_rate = '(1,1)'
params.cnn1_strides = '(2,1)'
params.cnn1_padding = 'same'
params.cnn1_filters = 4
p... | 086f34623b8500dbff09a13a724f7f6eaa957b63 | 49,526 |
import csv
def LoadVNSIM(nsim_csv):
"""Returns dictionary with degraded file key and mean nsim value.
The CSV should have three values: reference path, degraded path, nsim value
Args:
nsim_csv: Path to CSV file with NSIM values, format described above.
Returns:
Dictionary with degraded file key and... | 919d1dcffab7e4a78e0ced2cbeee01126d586c27 | 49,527 |
def getCharOverlapCount(from1, to1, from2, to2):
"""Calculates the number of overlapping characters of the two given areas."""
#order such that from1 is always prior from2
if from1 > from2:
tmp = from1
from1 = from2
from2 = tmp
tmp = to1
to1 = to2
to2 = tmp
... | 66ea7cbc9408d41de002c96e40705d4dd45f9ad5 | 49,528 |
def getPressure():
"""
Method to get the angular position of the rocket.
This method is only activated when the route /getAng is accessed.
Data collected here is to be directly displayed as numbers on ReactApp.
"""
pressure = {'PTop':PT1,'PBottom':PT2,'P3':PT3}
f = open("./AvionicsData/pressure.txt","a+")
f... | 7ec8261c091f2f832ac31ff4e8aff7c0494bfcfa | 49,529 |
import warnings
def label_color(label):
""" Return a color from a set of predefined colors. Contains 80 colors in total.
Args
label: The label to get the color for.
Returns
A list of three values representing a RGB color.
If no color is defined for a certain label, the color gre... | d08bcecdcc3c48f58b879fbbfd44a973c031693a | 49,530 |
from pathlib import Path
def file_path(cfg):
"""
Return the directory containing the description files as an absolute path.
Returns None if the configuration does not define this.
"""
try:
desc_path = Path(cfg['descriptions_dir'])
except KeyError:
raise ConfigKeyMissingError('... | 34e8fb69fabdc6f014d52dbaf2b978dfb9022a9a | 49,531 |
def angle_average(galactic_frame_func):
"""
@returns Angle-averaged function
"""
@np.vectorize
def angle_averaged(v_galactic_frame):
"""
@returns Angle-averaged evaluation of function
"""
v = v_galactic_frame * np.ones_like(COS_THETA)
integrand = galactic_fram... | 9964a21289e400dc1f147cb4a8bc625c7e1fe5ea | 49,533 |
def create():
"""Create new event."""
form = CreateEventForm(request.form, csrf_enabled=False)
print ("form received")
if form.validate_on_submit():
print ("valid")
RecEvent.create(title=form.title.data, date=form.date.data, time=form.time.data,
location=form.loca... | 71751dcae0db1b7fc70784ad6fae3fc7e22bbd18 | 49,534 |
def get_version():
"""
Obtain the version of the ITU-R P.1853 recommendation currently being used.
Returns
-------
version: int
Version currently being used.
"""
global __model
return __model.__version__ | 87eb4e26e20089976e5863b65c7457e91c6844ed | 49,535 |
def _random_bernoulli(shape, probs, dtype=tf.int32, seed=None, name=None):
"""Returns samples from a Bernoulli distribution."""
with tf.name_scope(name, "random_bernoulli", [shape, probs]):
probs = tf.convert_to_tensor(probs)
random_uniform = tf.random_uniform(shape, dtype=probs.dtype, seed=seed)
return... | ba60cecbcc0ac7698839e6bb60f2ebdd0b698c59 | 49,539 |
import re
def tokenize(text):
"""Return tokenized form of text
Parameters
----------
text : str
string to be tokenized
Returns
-------
list
tokens of string text
"""
# Normalize and remove punctuations and extra chars such as (, #
text = re.sub(r'[... | 3f360e4fa253249e65ce66cdcdc292d99f344610 | 49,540 |
import string
import csv
def ReadData(name):
"""
Reads data from several files.
"""
f = open('%s-n.txt' % name,'rt')
n = string.atoi(f.readline())
f.close()
gammas = []
f = open('%s-gammas.csv' % name,'rt')
for row in csv.reader(f,quoting=csv.QUOTE_NONNUMERIC):
... | 24116b6fe7e1bcc0c003a4717520aa539dd7f3a0 | 49,541 |
from typing import Optional
from typing import List
def split_and_strip_without(
string: str, exclude, separator_regexp: Optional[str] = None
) -> List[str]:
"""Split a string into items, and trim any excess spaces
Any items in exclude are not in the returned list
>>> split_and_strip_without('fred, ... | 14d4496679a1c759e8f2752c8e6b052a810ba8ea | 49,542 |
def _current_season():
"""Return the current NHL season"""
endpoint = "seasons/current"
data = _api_request(endpoint)
if data:
season = data['seasons'][0]['seasonId']
return season
else:
raise JockBotNHLException('Unable to retrieve current NHL season') | df8ab4d7df4fc4071a4738eaea398f24b9c5cd9f | 49,543 |
from typing import Tuple
def load_file(path: str) -> Tuple[TestCase, ...]:
"""Load test cases from a file.
Parameters
----------
path : str
File path.
Returns
-------
Tuple[TestCase, ...]
Test cases.
"""
with open(path, "r") as file:
return tuple(
... | 127bda88dc5aa98690a6f6bb7e5d793f3db7ac99 | 49,544 |
def get_interfaces():
"""
Returns a list of your computer's IP configuration:
['lo0', 'gif0', 'stf0', 'XHC20', 'en0', 'p2p0', 'awdl0',
'en1', 'bridge0', 'utun0']
"""
interfaces = netifaces.interfaces()
return interfaces | 7b8837c221f02baa70c6e6c3b848e8444f6daf50 | 49,545 |
import re
def clean_python_name(s):
"""Method to convert string to Python 2 object name.
Inteded for use in dataframe column names such :
i) it complies to python 2.x object name standard:
(letter|'_')(letter|digit|'_')
ii) my preference to use lowercase and adhere
... | d77eaa81607aabf8cae62e2a9c36a51e8428aac4 | 49,546 |
import tempfile
def mktemp_dump(data):
"""Create a temporary file under the current plugin tmp directory and write
data to the file.
"""
ftmp = tempfile.mktemp(dir=HotSOSConfig.PLUGIN_TMP_DIR)
with open(ftmp, 'w') as fd:
fd.write(data)
return ftmp | 80dd7c499c6a27b1aabb90d42234f28483b7915b | 49,549 |
def get_leagues_by_team(team_ids):
"""
https://developer.riotgames.com/api/methods#!/985/3352
Args:
team_ids (str | list<str>): the team ID(s) to get leagues for
Returns:
dict<str, list<League>>: the team(s)' leagues
"""
# Can only have 10 teams max if it's a list
if isinst... | 004cb182ca85062b6552224eea35423313348fdb | 49,550 |
def generate_asset_name (asset_id, block_index):
"""Create asset_name from asset_id."""
if asset_id == 0: return config.BTC
elif asset_id == 1: return config.XCP
if asset_id < 26**3:
raise exceptions.AssetIDError('too low')
if enabled('numeric_asset_names'): # Protocol change.
if ... | 5937da288062d9d9f98894e4534c3bd36feef3a3 | 49,551 |
from typing import Deque
def parse_object(tokens: Deque[Token]) -> JSONObject:
"""Parses an object out of JSON tokens"""
obj: JSONObject = {}
# special case:
if tokens[0].type == 'right_brace':
tokens.popleft()
return obj
while tokens:
token = tokens.popleft()
if... | f7d7ac489dd03c04e6820f430c9d6cd09376c222 | 49,552 |
def calc_Asym_vs_emin_energies(det_df,
dict_index_to_det, singles_hist_e_n, e_bin_edges_sh,
bhp_nn_e, e_bin_edges,
emins, emax, angle_bin_edges,
plot_flag=True, show_flag = False, save_flag=True):
"""
Calculate Asym for variable emi... | 4fb19fee0af8f1a2c9425e59c2634f8b49b72978 | 49,553 |
def get_best_of_n_avg(seq, n=3):
"""compute the average of first n numbers in the list ``seq``
sorted in ascending order
"""
return sum(sorted(seq)[:n])/n | 6166bbeda10d81356a86151901f33a26f0ff1035 | 49,554 |
def py2_earth_hours_left(start_date=BITE_CREATED_DT):
"""Return how many hours, rounded to 2 decimals, Python 2 has
left on Planet Earth (calculated from start_date)"""
return round((PY2_DEATH_DT - start_date) / timedelta(hours=1), 2) | e958cfbcbe3f1d6d6c00e52a26c9dd4591b7c0f0 | 49,556 |
from typing import Dict
from typing import Tuple
def merge_model_results(results: Dict[str, Dict[Tuple[str, int], pd.DataFrame]]) -> pd.DataFrame:
"""
Combine the results of running :func:`util.analyze_model` across a corpus
into a single dataframe.
:param results: Mapping from model name to dict... | f231d47bca582158ac09065966bad83ea3427a02 | 49,557 |
def _float_feature(value):
"""Wrapper for inserting float features into Example proto."""
return tf.train.Feature(float_list=tf.train.FloatList(value=value)) | 2d286fd444e16fac47f76507cd68be99919346fe | 49,558 |
def valid_bytes_128_after(valid_bytes_48_after):
"""
Fixture that yields a :class:`~bytes` that is 128 bits and is ordered "greater than" the
result of the :func:`~valid_bytes_128_after` fixture.
"""
return valid_bytes_48_after + b'\0' * 10 | 03e39e1b2d58b97184b30d57367ef5ca5b636f0e | 49,559 |
def const_coeffs(s=0.0, py=0.0, pz=0.0, px=0.0):
"""
Creates coefficients for seperated tunnelling to each orbital.
The energies are set to zero.
"""
cc = np.array([s, py, pz, px]) != 0.0
coeffs = np.empty((sum(cc),4),)
ene = np.zeros(sum(cc))
if s != 0.0:
coeffs[sum(cc[:1])-1] ... | 634d56731cdc07f28819a0e560193010457152cf | 49,560 |
from re import VERBOSE
import math
def calcIntraElectroHydrophobic(pdb, interface, depthDistances):
"""
Calculated possible electro interactions, excluding 1-2 and 1-3 interactions
(already included in angle and bond interactions
"""
HYDROPHOBIC_CHARGED_CUTOFF_DISTANCE = 6 # we could have 6?
... | a35674c36467d07c9225ae94bbc5f255a3d9c550 | 49,561 |
def positional_encoding(position: int, d_model: int) -> tf.Tensor:
"""Returns the positional encoding for a given position and timestamp"""
angle_rads = get_angles(np.arange(position)[:, np.newaxis],
np.arange(d_model)[np.newaxis, :],
d_model)
# apply... | 294281053a256d95b27066499909ec9bd78c4000 | 49,562 |
from typing import List
def add_multiple_of_row_of_square_matrix(matrix: List[List], source_row: int, k: int, target_row: int):
"""
add k * source_row to target_row of matrix m
"""
n = len(matrix)
row_operator = make_identity(n)
row_operator[target_row][source_row] = k
return multiply_matr... | 2ff7a31e0c52a34973510661a8e266f8c10abfcb | 49,563 |
import torch
def shadow_mapping(cam_results, light_results, rays, ppc, light_ppc, image_shape, batch_size, fine_sampling):
"""
cam_result: result dictionary with `depth_*`, `opacity_*`
light_result: result dictionary with `depth_*`, `opacity_*`
rays: generated rays
ppc: [Batch_size] Camera Poses:... | 8ff43760a1b09900edd70e5a9f0171d83ad756cf | 49,564 |
def get_panelists():
"""Retrieve a list of panelists and their corresponding
information"""
return panelists.get_panelists(database_connection) | db6ac71d72d3ac53f38c484a09c9ac91e3ac2ecb | 49,565 |
def count_distinct_col(curs, table_name, col='y'):
"""Queries to find number of distinct values of col column in table in
database.
Args:
curs (sqlite3.Cursor): cursor to database
table_name (str): name of table to query
col (str): name of column to find number of distinct values fo... | c346b8463eeb4faec645917831f7bde8f42ed5e1 | 49,566 |
def reduce_dataset_by_column_value(df, colname, values):
"""Returns the passed dataframe, with only the passed column values"""
col_ids = df[colname].unique()
nvals = len(col_ids)
# Reduce dataset
reduced = df.loc[df['locus_tag'].isin(values)]
# create indices and values for probes
new_ids... | ee8411dd5e1152b1ae1a9b78a70396c03a0c0f7c | 49,569 |
def limitsSql(pageToken=0, pageSize=None):
"""
Takes parsed pagination data, spits out equivalent SQL 'limit' statement.
:param pageToken: starting row position,
can be an int or string containing an int
:param pageSize: number of records requested for this transaciton,
can be an int or... | 9b188d405afb0c367a5f61b46c50a7c7a63e4879 | 49,570 |
def split(df):
"""
Splits the given dataframe into a 8/2 split for training and testing
:param df:the dataframe you want to split
:return:
"""
training, test = train_test_split(df, test_size=0.2, random_state=42)
train, val = train_test_split(training, test_size=0.2, random_state=42)
re... | 0b4e99332a25ccc971abf099d90f3c8466741019 | 49,572 |
def test_wait_within_timeout():
"""Test that we can wait for a job terminating before timeout.
"""
i = 0
def cond():
nonlocal i
j = i
i += 1
return j
job = InstrJob(cond, 0)
assert job.wait_for_completion(refresh_time=0.01)
assert i == 2 | 48e01ca620829294e21aa54da0b0a811d89d2c52 | 49,573 |
def module_method(fn):
"""Decorates a function as a module method.
The `module_method` allows modules to have multiple methods that make use of
the modules parameters.
Example::
class MyLinearModule(nn.Module):
def apply(self, x, features, kernel_init):
kernel = self.param('kernel', (x.shap... | 02f0d422e0ca6352d56d6e3e9b05b1f288f55762 | 49,577 |
import re
def add_http_if_no_scheme(url):
"""Add http as the default scheme if it is missing from the url."""
match = re.match(r"^\w+://", url, flags=re.I)
if not match:
parts = urlparse(url)
scheme = "http:" if parts.netloc else "http://"
url = scheme + url
return url | ea7799616c0616fda85814139b7a36264cbc9e40 | 49,582 |
def _check_half_window(half_window, allow_zero=False):
"""
Ensures the half-window is an integer and has an appropriate value.
Parameters
----------
half_window : int, optional
The half-window used for the smoothing functions. Used
to pad the left and right edges of the data to redu... | 4e40b307242f3c1137251903b227144a4deb53d6 | 49,583 |
async def get_run_controller(
runId: str,
task_runner: TaskRunner = Depends(get_task_runner),
engine_store: EngineStore = Depends(get_engine_store),
run_store: RunStore = Depends(get_run_store),
) -> RunController:
"""Get a RunController for the current run.
This ensures that a run exists and i... | 10e08c4096764ee2e181083699d353edea551409 | 49,585 |
import io
import click
def get_pixel_ratio(img, img_path):
"""
Tries to read file metadata from dm file. If normal .tif images are provided
instead, prompts user for the nm/pixel ratio, which can be found using the
measurement tool in ImageJ or similar. For example, a scale bar of 100nm corresponds to... | 5d50e4b4db7620256d62f359fca8608216a54b95 | 49,586 |
def gauss_kern(size, sizey=None): # smooth test
""" Returns a normalized 2D gauss kernel array for convolutions """
size = int(size)
if not sizey:
sizey = size
else:
sizey = int(sizey)
x, y = np.mgrid[-size:size+1, -sizey:sizey+1]
g = np.exp(-(x**2/float(size)+y**2/float(sizey))... | ea0d9a4266942ae4e40d6815d6391ac4532ad808 | 49,587 |
def full_clean(string_in):
"""Call of my string cleaning functions in order"""
#print('string_in = %s' % string_in)
if string_in is None:
return string_in
elif type(string_in) == unicode:
string_in = string_in.encode('UTF-8')
elif type(string_in) not in [str, unicode]:
return... | d4325f997bcf0c71d569155d72240ae7d11661de | 49,588 |
def partitioned_variable_assign(partitioned_var, new_value):
"""Assign op for partitioned variables.
Args:
partitioned_var: A partitioned tensorflow variable
new_value: Value to be assigned to the variable var
Returns:
A tensorflow op that groups the assign ops for each of the variable slices
"""
... | f61f32ee5c948a1efe82ec329472eb841a4d8b78 | 49,589 |
from typing import Optional
from typing import Set
def process_df(
df: pd.DataFrame,
version: Optional[str] = None,
skip_databases: Optional[Set[str]] = None,
) -> DGIProcessor:
"""Get a processor that extracted INDRA Statements from DGI content based
on the given dataframe.
Parameters
--... | c63489b20073eda59cf15cb96e3fcfd5499a9efc | 49,590 |
def coerce_levels(image_numpy, levels=255, method="divide", reference_image = [], reference_norm_range = [.075, 1], mask_value=0, coerce_positive=True):
""" In volumes with huge outliers, the divide method will
likely result in many zero values. This happens in practice
quite often. TO-DO: find a b... | 9bf458c551d71a7d43841209d2e5d3aad5d6da15 | 49,591 |
from typing import List
def merge_and_count(ll: List[int], lr: List[int]) -> (int, List[int]):
"""
:param ll:
:param lr:
:return:
>>> merge_and_count([1, 2, 4], [3, 5])
(1, [1, 2, 3, 4, 5])
>>> merge_and_count([1, 2, 6], [3, 5])
(2, [1, 2, 3, 5, 6])
"""
result = []
coun... | b513ce03b317a2cc5332aa3c50abd612380b08b6 | 49,592 |
def get_ap_bboxes(img, model, dataset_name, verbose=False):
"""
Detect appearance based foreground bounding boxes on a frame by a pre-trained object detector.
Args:
img (ndarray): The frame to be detected.
model (nn.Module): The loaded detector.
dataset_name (str): The name of datase... | 41f5dcec8868cf19e10ba98a5a5ff91b375bf618 | 49,593 |
def delete_user_entitlement(user, organization=None, detect=None):
"""Remove user from an organization.
:param user: Email ID or ID of the user.
:type user: str
"""
organization = resolve_instance(detect=detect, organization=organization)
if '@' in user:
user = resolve_identity_as_id(use... | c9b5d440f42eeb5da0746974a1b598cab72d4e03 | 49,595 |
import struct
def encode_string(input_string):
"""Encode the string value in binary using utf-8
as well as its length (valuable info when decoding
later on). Length will be encoded as an unsigned
short (max 65535).
"""
input_string_encoded = input_string.encode("utf-8")
length = len(input... | ecb26ce97cbebfe79b694e96b6e16d50069858b4 | 49,596 |
def resnet152(block, layers, pretrained=False, **kwargs):
"""Constructs a ResNet-152 model.
Args:
pretrained (bool): If True, returns a model pre-trained on ImageNet
"""
model = ResNet(block, layers, **kwargs)
if pretrained:
model.load_state_dict(model_zoo.load_url(model_urls['resnet... | b9e291a6c958b70e684d46bb63a31583d91e514b | 49,597 |
def parse_vmin_vmax(container, field, vmin, vmax):
""" Parse and return vmin and vmax parameters. """
field_dict = container.fields[field]
if vmin is None:
if 'valid_min' in field_dict:
vmin = field_dict['valid_min']
else:
vmin = -6 # default value
if vmax is No... | a7c096e4648662a5efe59c38de016e586c718ffb | 49,602 |
import json
def to_dict(url: str) -> dict:
"""Method to convert and return as dictionary."""
return json.loads(fetch_data(url)) | d75ade236379f61d0443610f91e2d090077028fe | 49,603 |
def polygon_iou(poly1, poly2):
"""Compute the IoU of polygons."""
return polygon_geo_cpu.polygon_iou(poly1, poly2) | 8e7bec12e3e0dfd99a040e5e256fedb6526a16de | 49,604 |
def fit( X, y, batch_size = 4, validation_split = 0.05, epochs = 1250, learning_rate=0.001):
"""Fit a BNN with mean field posterior and trainable prior to a data set X,y.
Args:
X (np.array): Input data x (features)
y (np.array): Input data y (target)
batch_size (int, optional): Batch si... | 2e3e940e4e0cc2a4537cf5e3619da58f5632aad4 | 49,605 |
import math
def jacob_f(x, u):
"""
Jacobian of Motion Model
motion model
x_{t+1} = x_t+v*dt*cos(yaw)
y_{t+1} = y_t+v*dt*sin(yaw)
yaw_{t+1} = yaw_t+omega*dt
v_{t+1} = v{t}
so
dx/dyaw = -v*dt*sin(yaw)
dx/dv = dt*cos(yaw)
dy/dyaw = v*dt*cos(yaw)
dy/dv = dt*sin(yaw)
""... | 4e9c88a8187d4c8bc76a7f954a68570ffb4a08bf | 49,606 |
from datetime import datetime
def save_by_name(admin: dict):
"""
Save a new admin with field name as index
:return:
"""
name = admin.get('name')
if not name:
raise Error(10003, 'Field name required!')
admin['updated_at'] = china_tz(datetime.now())
admin['created_at'] = china_tz... | 7fe9db58896df4ce443e8919896a7fabc4f2fcfa | 49,608 |
from typing import Any
def create(tknzr_name: str, **kwargs: Any) -> BaseTknzr:
"""Create tokenizer instance by tokenizer's name.
Tokenizer's arguments are collected in ``**kwargs`` and are passed directly to tokenizer's constructor.
Parameters
----------
tknzr_name: str
Name of the tokenizer to creat... | 5f01ec7a380f715c71174bafd1ba7c51bbaf3c22 | 49,609 |
def logitRegression(data):
"""
训练模型，并画出模型的ROC曲线
"""
data = transLabel(data)
features = ["age", "education_num", "capital_gain", "capital_loss", "hours_per_week"]
labels = "label_code"
trainSet, testSet = train_test_split(data, test_size=0.3, random_state=2310)
model = trainModel(trainSet... | ca0357cdb6aae5b847b86082a39308dce319a572 | 49,610 |
import copy
def jet_libes_get_data(exp_id=None, data_name=None, no_data=False,
options={}, coordinates=None, data_source="JET_LIBES"):
""" Data read function for the JET Li-BES diagnostic
data_name: channel data can be reached under: "BES-ADCxx", "JPF/DH/KY6D-DOWN:xxx",
... | e58e92b2e3878867eccde22b6976bbbc3fa04b23 | 49,611 |
import numbers
def is_numlike(obj):
"""return true if *obj* looks like a number"""
return isinstance(obj, (numbers.Number, np.number)) | b31365cf1e71d96b88d7a61b595fd85a7196cc81 | 49,612 |
def float2bin(afloat: float):
"""소수점 이하의 값이 있는 실수를 이진수로 변환
Args:
afloat: 이진수로 변환할 실수
Returns:
이진수 ('0b' prefix가 없는 실수의 형태)
"""
integer_part = int(afloat) # 정수부분
decimal_part = afloat - integer_part # 소수부분
decimal_bin = "." # 소수부문에 대한 이진표현
while decimal_part != 0.0:
... | 7873450858b3753a5da1f6a70f96d82204e37f8b | 49,614 |
def get_sequential_param_pairs(params, name1, name2):
"""Returns a dict of two sets of sequentially named parameters using the
value of name1 as the key and the value of name2 of the value.
"""
one = get_sequential_params(params, name1)
two = get_sequential_params(params, name2)
if len(one) != l... | fa2e810391e60c89acd43b7931212090a2adb9db | 49,615 |
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