content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
import eazy.igm
def simulate_eazy_sed_from_coeffs(
eazycoeffs, eazytemplatedata, z,
returnfluxunit='', returnwaveunit='A',
limitwaverange=True, savetofile='',
**outfile_kwargs):
"""
Generate a simulated SED from a given set of input eazy-py coefficients
and eazypy templat... | 41c975efa4136e9958c2b5680db2e6f9a67a4291 | 3,656,100 |
def get_timezones_all():
"""Dump the list of timezones from ptyz into a format suitable
for use with the Django Forms API's ChoiceField
"""
# TODO: Find a more user-friendly way of managing 500+ timezones
output = []
for tz in all_timezones:
output.append( (tz, tz) )
return output | e00bd0bc3321b9ab91526e67200ce3ef3629014a | 3,656,101 |
def create_logistic_vector(input_vector, cutoff):
"""
Creates a vector of 0s and 1s based on an input vector of numbers with a cut-off point.
"""
output_vector = np.zeros(len(input_vector))
n = 0
for i in range(len(input_vector)):
if input_vector[i] > cutoff:
output_vector[i... | bb4756f745f56fae7d8d4f0b1a1758ef6d70fb5a | 3,656,102 |
def profile(username):
""" user profile """
user = User.query.filter_by(username=username).first_or_404()
return render_template("user/profile.jinja.html", user=user) | 31e2a1b108c0652356cea92f32e9077105733726 | 3,656,103 |
def action_rescale(action):
"""Rescale Distribution actions to exp one"""
return np.array([0 if abs(a) < 0.5 else 10 ** (a-3) if a > 0 else -(10 ** (-a - 3)) for a in action * 3]) | 534509b76410eaeadee599e1ac510def8243e7ba | 3,656,104 |
def multi_knee(points: np.ndarray, t1: float = 0.99, t2: int = 3) -> np.ndarray:
"""
Recursive knee point detection based on the curvature equations.
It returns the knee points on the curve.
Args:
points (np.ndarray): numpy array with the points (x, y)
t1 (float): coefficient of determ... | ee44d9f51c843a0fb8e18f10057b5c6510dd8f3a | 3,656,105 |
def parse_dotted_path(path):
"""
Extracts attribute name from dotted path.
"""
try:
objects, attr = path.rsplit('.', 1)
except ValueError:
objects = None
attr = path
return objects, attr | 4685fad6461286b957a8d0056df2146fdd0f2e55 | 3,656,106 |
def resource_media_fields(document, resource):
""" Returns a list of media fields defined in the resource schema.
:param document: the document eventually containing the media files.
:param resource: the resource being consumed by the request.
.. versionadded:: 0.3
"""
media_fields = app.confi... | b54bc5f7fd35626866d70ce6d46bf0b84b9cf1b8 | 3,656,107 |
import os
import logging
def read_config_file(f):
"""Read a config file."""
if isinstance(f, basestring):
f = os.path.expanduser(f)
try:
config = ConfigObj(f, interpolation=False, encoding='utf8')
except ConfigObjError as e:
log(LOGGER, logging.ERROR, "Unable to parse line {0... | 7dd67233c8ab1a09568b0cca143a96e27ba15722 | 3,656,108 |
from typing import List
from typing import Tuple
def _parse_moving(message: List[str]) -> Tuple[Actions, str]:
"""Parses the incoming message list to determine if movement is found.
Args:
message: list of words in the player message
Returns: a tuple of the action and direction
"""
short... | 9785cbeb39dbc9ba980f605b648fb77855fe863d | 3,656,109 |
def _Net_forward_all(self, blobs=None, **kwargs):
"""
Run net forward in batches.
Take
blobs: list of blobs to extract as in forward()
kwargs: Keys are input blob names and values are blob ndarrays.
Refer to forward().
Give
all_outs: {blob name: list of blobs} dict.
"""
... | f5b6acf347e4fb85e0148d2d176042559f93b6a1 | 3,656,110 |
def email_members_old(request, course_prefix, course_suffix):
"""
Displays the email form and handles email actions
Right now this is blocking and does not do any batching.
Will have to make it better
"""
error_msg=""
success_msg=""
form = EmailForm()
if request.metho... | eeafa4d9c4ca0b0ad1b7ffaecceb03c188e02813 | 3,656,111 |
def Padding_op(Image, strides, offset_x, offset_y):
"""
Takes an image, offset required to fit output image dimensions with given strides and calculates the
padding it needs for perfect fit.
:param Image:
:param strides:
:param offset_x:
:param offset_y:
:return: Padded image
"""
... | d3f046069a597f2d7e3204b543f1f60c8e1e5b23 | 3,656,112 |
def area_triangle(point_a: array_like, point_b: array_like, point_c: array_like) -> np.float64:
"""
Return the area of a triangle defined by three points.
The points are the vertices of the triangle. They must be 3D or less.
Parameters
----------
point_a, point_b, point_c : array_like
... | 0c21ca96f8a6fd4d088cf0fa47a260b3bc582966 | 3,656,113 |
import os
def file_exists(target, parse=False):
"""Checks if a file exists"""
if parse:
target = envar_parser(target)
if os.path.isfile(target):
return True
else:
return False | 99332f2fd2d434a19372b453a6235f4f2d7f5ab3 | 3,656,114 |
def test_valid(line):
"""Test for 40 character hex strings
Print error on failure"""
base_error = '*** WARNING *** line in torrent list'
if len(line) != 40:
print(base_error, 'incorrect length:', line)
elif any(char not in HEX for char in line):
print(base_error, 'has non-hex digits... | ca6517a8dd622b07703b30af7842685b9b6d5865 | 3,656,115 |
def readIMAGCDF(filename, headonly=False, **kwargs):
"""
Reading Intermagnet CDF format (1.0,1.1,1.2)
"""
debug = kwargs.get('debug')
cdfdat = cdf.CDF(filename)
if debug:
logger.info("readIMAGCDF: FOUND IMAGCDF file created with version {}".format(cdfdat.version()))
if debug:
... | 9d87de2c650b140cf42cab4814659cf842f4b5a5 | 3,656,116 |
def custom_formatter(code, msg):
""" 自定义结果格式化函数
:param code: 响应码
:param msg: 响应消息
"""
return {
"code": code,
"msg": "hello",
"sss": "tt",
} | 59a7e3f9f03f9afc42b8faec6ebe23f5373d0bf0 | 3,656,117 |
def get_sampler_callback(rank, num_replicas, noniid=0, longtail=0):
"""
noniid: noniid controls the noniidness.
- noniid = 1 refers to completely noniid
- noniid = 0 refers to iid.
longtail: longtail controls the long-tailness.
- Class i takes (1-longtail) ** i percent of data.
... | 05e526ba903ebd834f248d965253344136e8a8a8 | 3,656,118 |
def alloc_bitrate(frame_nos, chunk_frames, pref_bitrate, nrow_tiles, ncol_tiles):
"""
Allocates equal bitrate to all the tiles
"""
vid_bitrate = []
for i in range(len(chunk_frames)):
chunk = chunk_frames[i]
chunk_bitrate = [[-1 for x in range(ncol_tiles)] for y in range(nrow_tiles)]
chunk_weight = [[1. for ... | 1883f480852d49e63c0408c9ef0daeba9e50db6b | 3,656,119 |
from typing import Collection
from typing import Any
def file_filter(extensions: Collection[str]) -> Any:
"""Register a page content filter for file extensions."""
def wrapper(f):
for ext in extensions:
_file_filters[ext] = f
return f
return wrapper | bef1a304497ffaac3f294607d8a393e505c1eb19 | 3,656,120 |
def epc_calc_img_size(reg_dict):
"""
Calcalute the output image size from the EPC660 sensor
Parameters
----------
reg_dict : dict
Returns
----------
int
The number of rows
int
The number of columns in the image
"""
col_start, col_end, row_start, row_end ... | 698b6ae6a99f8f9621c40ffaee2ab5ea5e584ce1 | 3,656,121 |
def simple_url_formatter(endpoint, url):
"""
A simple URL formatter to use when no application context
is available.
:param str endpoint: the endpoint to use.
:param str url: the URL to format
"""
return u"/{}".format(url) | 74f3e68fe10f7cc6bf8bfe81a7349a995bb79fa3 | 3,656,122 |
from typing import List
def generate_service(
name: str,
image: str,
ports: List[str] = [],
volumes: List[str] = [],
dependsOn: List[str] = [],
) -> str:
"""
Creates a string with docker compose service specification.
Arguments are a list of values that need to be added to each section... | 581e37e69d73ab5b6c0ac533bd91e7b5cb5187d9 | 3,656,123 |
def read_integer(msg=None, error_msg=None):
"""
Asks the user for an integer value (int or long)
:param msg: The message, displayed to the user.
:param error_msg: The message, displayed to the user, in case he did not entered a valid int or long.
:return: An int or a long from the user.
"""
... | c3067b436f57583b89ca02bff5e01802845ebf69 | 3,656,124 |
def set_async_call_stack_depth(maxDepth: int) -> dict:
"""Enables or disables async call stacks tracking.
Parameters
----------
maxDepth: int
Maximum depth of async call stacks. Setting to `0` will effectively disable collecting async
call stacks (default).
"""
return {
... | f3767d85dc12913b11c6b13bb66f866460198672 | 3,656,125 |
def percError(predicted, observed):
"""Percentage Error
Parameters
==========
predicted : array-like
Array-like (list, numpy array, etc.) of predictions
observed : array-like
Array-like (list, numpy array, etc.) of observed values of scalar
quantity
Returns
=======
... | 168affcb5af47563c15d27c6e662b0cf6411eca2 | 3,656,126 |
def _dict_eq(a, b):
"""
Compare dictionaries using their items iterators and loading as much
as half of each into a local temporary store. For comparisons of ordered
dicts, memory usage is nil. For comparisons of dicts whose iterators
differ in sequence maximally, memory consumption is O(N). Exec... | 68292489e4f6f8f213f4d17cf799052cb99ece37 | 3,656,127 |
from typing import Dict
from typing import List
def avoid_snakes(my_head: Dict[str, int], snakes: List[dict], possible_moves: List[str]) -> List[str]:
"""
my_head: Dictionary of x/y coordinates of the Battlesnake head.
e.g. {"x": 0, "y": 0}
snakes: List of dictionaries of x/y coordinates for e... | dcdd80522486ec1c6001aa8990f2bfaf88235ec1 | 3,656,128 |
from django.core.servers.basehttp import FileWrapper
import zipfile
import logging
import os
import tarfile
import traceback
def getChipZip(request, path):
"""Download the AutoPH file, converted to zip compression"""
logger = logging.getLogger(__name__)
path = os.path.join("/", path)
try:
nam... | af836e47967e830e1a36ade074bca655efc8fcbc | 3,656,129 |
def m_unicom_online_time2_0(seq):
"""
获取联通手机在网时长所对应的code
:param seq: 联通在网时长区间
:return: code
example：
:seq: [0-1]
:return 1
"""
if not seq:
return []
if seq[0] in ["[0-1]", "(1-2]", "[3-6]"]:
seq = ["(0_6)"]
elif seq... | 4a242d76f3d2708b5ad590830156a44fd22e7267 | 3,656,130 |
def convert_config_gui_structure(config_gui_structure, port, instance_id,
is_port_in_database, conf):
"""
Converts the internal data structure to a dictionary which follows the
"Configuration file structure", see setup.rst
:param config_gui_structure: Data structure used... | 3f46a621261ba097918fb5b5d27bd7611910a623 | 3,656,131 |
def message_similarity_hard(m1, m2):
"""
Inputs: One dimension various length numpy array.
"""
return int(np.all(m1==m2)) | 8f649a295853c34d692fb96a0a7facbc82d67ddb | 3,656,132 |
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: defualt 3, the kernel size of middle conv layer at main path
filters: list of integers, the n... | 38a898a3b52f12490584206dfa6ea6b9819a1240 | 3,656,133 |
def convert_to_squad(story_summary_content, question_content, set_type):
"""
:param story_summary_content:
:param question_content:
:param category_content:
:param set_type:
:return: formatted SQUAD data
At initial version, we are just focusing on the context and question, nothing more,
... | 5b884ef521af4d5835fef25f01cb1f11d68cfafb | 3,656,134 |
import select
import time
import sys
import os
def push_output(process, primary_fd, out_buffer: TextBuffer, process_state: ProcessState,
is_interactive_session: bool, on_error: callable):
"""
Receive output from running process and forward to streams, capture
:param process:
:param p... | accb4fa66d8746766b4552c09d22b3d2fd3502c0 | 3,656,135 |
def check_conditions(conditions, variable_dict, domain_dict, domain_list):
"""A function that checks if the generated variables pass the conditions and generates new ones until they do.
:param conditions: The conditions of the template.
:param variable_dict: List of variables.
:param domain_dict: the do... | fffd9889d3c149f56041753522aee245135cf0ee | 3,656,136 |
def set_pin_on_teaching_page(request,
section_label,
pin=True):
"""
if pin=True, pin the section on teaching page
if pin=False, unpin the section from teaching page
@except InvalidSectionID
@except NotSectionInstructorException
@except Us... | 385940e3adc286a923a94a3205b56c3817ee6284 | 3,656,137 |
from typing import Any
def inject_python_resources() -> dict[str, Any]:
"""
Inject common resources to be used in Jinja templates.
"""
return dict(
isinstance=isinstance,
zip=zip,
enumerate=enumerate,
len=len,
str=str,
bool=bool,
int=int,
... | 98fb7fbf39f20b9972ef5c0d35ae12b2864580b2 | 3,656,138 |
def get_feature_subsets_options(study, data_types):
"""Given a study and list of data types, get the relevant feature
subsets
"""
feature_subsets = ['custom']
if 'expression' in data_types:
try:
feature_subsets.extend(study.expression.feature_subsets.keys())
except Attrib... | d9310f00ff001f5ddc643998c7544df6ba5382b5 | 3,656,139 |
import json
def possibilities(q=0, *num):
"""
:param q: Número de quadrados a considerar
:param num: Em quantos quadrados a soma do nº de bombas é 1
:return:
pos -> Possibilidade de distribuição das bombas
tot -> Número de quadrados nos quais só há uma bomba
i -> Início da contagem dos qua... | 94c126a1bacf5bb242ad2935f949ab146f847001 | 3,656,140 |
import re
def parse_page_options(text):
"""
Parses special fields in page header. The header is separated by a line
with 3 dashes. It contains lines of the "key: value" form, which define
page options.
Returns a dictionary with such options. Page text is available as option
named "text".
... | b90b1adb7d5d6f8716b9d4e00b0e4b533393f725 | 3,656,141 |
def _read_16_bit_message(prefix, payload_base, prefix_type, is_time,
data, offset, eieio_header):
""" Return a packet containing 16 bit elements
"""
if payload_base is None:
if prefix is None:
return EIEIO16BitDataMessage(eieio_header.count, data, offset)
... | b552d06b314d47ee3ae928ebcee678c65bd24f84 | 3,656,142 |
def test_linear():
""" Tests that KernelExplainer returns the correct result when the model is linear.
(as per corollary 1 of https://arxiv.org/abs/1705.07874)
"""
np.random.seed(2)
x = np.random.normal(size=(200, 3), scale=1)
# a linear model
def f(x):
return x[:, 0] + 2.0*x[:, 1... | 6e716d6505162aa49507b026672455d357ab7c2b | 3,656,143 |
def csm_shape(csm):
"""
Return the shape field of the sparse variable.
"""
return csm_properties(csm)[3] | a74357086a9d7233cabed1c6ddc14fdbdbe0b41f | 3,656,144 |
def hyperlist_to_labellist(hyperlist):
"""
:param hyperlist:
:return: labellist, labels to use for plotting
"""
return [hyper_to_label(hyper) for hyper in hyperlist] | 9587694d783ccbd122b58894a2d80ee5e58dc900 | 3,656,145 |
import json
def _pretty_print_dict(dictionary):
"""Generates a pretty-print formatted version of the input JSON.
Args:
dictionary (dict): the JSON string to format.
Returns:
str: pretty-print formatted string.
"""
return json.dumps(_ascii_encode_dict(dictionary), indent=2, sort_k... | 17e94d18f824253540fd968c726721542f25a95e | 3,656,146 |
def _bivariate_kdeplot(x, y, filled, fill_lowest,
kernel, bw, gridsize, cut, clip,
axlabel, cbar, cbar_ax, cbar_kws, ax, **kwargs):
"""Plot a joint KDE estimate as a bivariate contour plot."""
# Determine the clipping
if clip is None:
clip = [(-np.inf, n... | ecb60ec3ffdc746f40b89158ef3c5b3a03e85bfc | 3,656,147 |
import os
import scipy
def load_file(path):
"""
Load single cell dataset from file
"""
if os.path.exists(DATA_PATH+path+'.h5ad'):
adata = sc.read_h5ad(DATA_PATH+path+'.h5ad')
elif os.path.isdir(path): # mtx format
adata = read_mtx(path)
elif os.path.isfile(path):
if p... | bed61b35bf6bf6777f3350d34e754cd80acca327 | 3,656,148 |
def unified_load(namespace, subclasses=None, recurse=False):
"""Provides a unified interface to both the module and class loaders,
finding modules by default or classes if given a ``subclasses`` parameter.
"""
if subclasses is not None:
return ClassLoader(recurse=recurse).load(namespace, subcla... | 62f5f4e17d3d232bfa72090a836f89f782068b53 | 3,656,149 |
def generate_free_rooms(room_times: dict) -> dict:
"""
Generates data structure for getting free rooms for each time.
"""
# create data format
free_rooms = {'M': {},
'Tu': {},
'W': {},
'Th': {},
'F': {}
}
#... | e60df355acd84e60c08ba34a45a2131d8d4519b4 | 3,656,150 |
def code_parse_line(li, pattern_type="import/import_externa"):
"""
External Packages
"""
### Import pattern
if pattern_type == "import":
if li.find("from") > -1:
l = li[li.find("from") + 4 : li.find("import")].strip().split(",")
else:
l = li.strip().split("impor... | 347b3d0c3192978beb4c26a1950d86482812310b | 3,656,151 |
def get_high(pair, path="https://api.kraken.com/0/public"):
""" Get the last 24h high price of `pair`.
Parameters
----------
pair : str
Code of the requested pair(s). Comma delimited if several pair.
path : str
Path of the exchange to request.
Returns
-------
float or d... | 8443ad24450e8f7bd2b6fac339e5e2b9149685c1 | 3,656,152 |
def SIx():
"""
Reads in future LENS SI-x data
Returns
----------
leafmean : array leaf indices (ens x year x lat x lon)
latmean : array last freeze indices (ens x year x lat x lon)
lat : array of latitudes
lon : array of longitudes
lstfrz : list last freeze indices
"""
... | 0ac033577d73c6567ebef10437a7e44e51bf5c79 | 3,656,153 |
import scipy
def make_truncnorm_gen_with_bounds(mean, std, low_bound, hi_bound):
"""
low_bound and hi_bound are in the same units as mean and std
"""
assert hi_bound > low_bound
clipped_mean = min(max(mean, low_bound), hi_bound)
if clipped_mean == low_bound:
low_sigma = -0.01 * std
... | 8e957d99141a56f804bebf931098fa147d066bb8 | 3,656,154 |
from invenio_app_ils.ill.api import BORROWING_REQUEST_PID_TYPE
from invenio_app_ils.ill.proxies import current_ils_ill
from invenio_app_ils.items.api import ITEM_PID_TYPE
from invenio_app_ils.proxies import current_app_ils
from invenio_app_ils.errors import UnknownItemPidTypeError
def resolve_item_from_loan(item_pid)... | f58ea857a445f2e6e01f426656f87a2032ea8306 | 3,656,155 |
import os
def lascolor(strPathInLAS, strPathOutLAS, strPathTif, strAdlSwitches = None):
""" Function lascolor
args:
strPathInLAS = input LAS file
strPathOutLAS = output LAS file
strPathTif = Tif source of RGB values
strAdlSwitches = optional additional switc... | 59400923bd0148a3659f7988596b1b7b2d4a70b6 | 3,656,156 |
def delta(s1, s2):
""" Find the difference in characters between s1 and s2.
Complexity: O(n), n - length of s1 or s2 (they have the same length).
Returns:
dict, format {extra:[], missing:[]}
extra: list, letters in s2 but not in s1
missing: list, letters in s1 but not in s2... | e439b5a4cf634f5e53fbf845b5774342cedeb404 | 3,656,157 |
def mean_predictive_value(targets, preds, cm=None, w=None, adjusted=False):
"""
:purpose:
Calculates the mean predictive value between a discrete target and pred array
:params:
targets, preds : discrete input arrays, both of shape (n,)
cm : if you have previously calculated a confus... | 9e7b7047d0dcf79509e544ca8bb0d621d1ce283d | 3,656,158 |
def delta(phase,inc, ecc = 0, omega=0):
"""
Compute the distance center-to-center between planet and host star.
___
INPUT:
phase: orbital phase in radian
inc: inclination of the system in radian
OPTIONAL INPUT:
ecc:
omega:
//
OUTPUT:
distance center-to-center, doubl... | 797d84618ade3e84b63a1a40e7728de77d5465ca | 3,656,159 |
def theoritical_spectrum(peptide_sequence):
"""Returns the theoritical spectrum of a given amino acid sequence.
INPUT :
peptide_sequence: string. The peptide sequence to get its theoritical spectrum
OUTPUT:
.: List. The theoritical spectrum of the given peptide sequence.
"""
linear_... | 1808daed80b553fe3a5a2b38e178956e4a0d7de0 | 3,656,160 |
def is_amazon(source_code):
"""
Method checks whether a given book is a physical book or a ebook giveaway for a linked Amazon account.
:param source_code:
:return:
"""
for line in source_code:
if "Your Amazon Account" in line:
return True
return False | 31c50622b4bb97a05d8cabb94c58f6e0a8f58971 | 3,656,161 |
import os
import sys
import subprocess
def transdecodeToPeptide(sample_name, output_dir, rerun_rules, sample_dir,
mets_or_mags = "mets", transdecoder_orf_size = 100,
nt_ext = ".fasta", pep_ext = ".faa", run_transdecoder = False):
"""
Use TransDecoder to conve... | b22f520808104e4fc471c4af5a2288a5f23b84ae | 3,656,162 |
def data_dim(p):
""" Return the dimensionality of the dataset """
dataset_class = DATASETS[p.dataset]
return dataset_class(p).get_in_dim() | 25e32039733e8599c22d696f28bfffbf8b97cf02 | 3,656,163 |
import torch
def create_supervised_evaluator(model, metrics=None,
device=None, non_blocking=False,
prepare_batch=_prepare_batch,
output_transform=
lambda x, y, y_pred: (y_pred, y,)):
"""... | 2af4cc7b12a76c3c12940353a072d8b715fec8c1 | 3,656,164 |
import typing
def historical_earning_calendar(
apikey: str, symbol: str, limit: int = DEFAULT_LIMIT
) -> typing.Optional[typing.List[typing.Dict]]:
"""
Query FMP /historical/earning_calendar/ API.
Note: Between the "from" and "to" parameters the maximum time interval can be 3 months.
:param apike... | 7f231b253ef4f462ab89826d58546a3259bdd3d2 | 3,656,165 |
def config_section_data():
"""Produce the default configuration section for app.config,
when called by `resilient-circuits config [-c|-u]`
"""
config_data = u"""[fn_query_tor_network]
base_url = https://onionoo.torproject.org/details
#The Flag can be 'Running','Exit' for more information on flag sett... | 239436c9b2141e17f6158aab20d7951d79359fcd | 3,656,166 |
def show_object_id_by_date(
move_data,
create_features=True,
kind=None,
figsize=(21, 9),
return_fig=True,
save_fig=True,
name='shot_points_by_date.png',
):
"""
Generates four visualizations based on datetime feature:
- Bar chart trajectories by day periods
- Bar char... | 18bbd54adfba6ecfd0959904d99698cfaac4b198 | 3,656,167 |
def raw_escape(pattern, unix=None, raw_chars=True):
"""Apply raw character transform before applying escape."""
return _wcparse.escape(util.norm_pattern(pattern, False, raw_chars, True), unix=unix, pathname=True, raw=True) | e4df84b21b737f199a7314818cc7f892f93be1b8 | 3,656,168 |
def interpolate_effective_area_per_energy_and_fov(
effective_area,
grid_points,
target_point,
min_effective_area=1. * u.Unit('m2'),
method='linear',
):
"""
Takes a grid of effective areas for a bunch of different parameters
and interpolates (log) effective areas to given value of those p... | 58c32f49c96ed7ceb14e734f1386ef0015920204 | 3,656,169 |
def extract_edge(stats:np.ndarray, idxs_upper:np.ndarray, runner:int, max_index:int, maximum_offset:float, iso_charge_min:int = 1, iso_charge_max:int = 6, iso_mass_range:int=5)->list:
"""Extract edges.
Args:
stats (np.ndarray): Stats array that contains summary statistics of hills.
idxs_upper ... | 8101a024c20d169f470d4e6632272e0ad00c484b | 3,656,170 |
def _neq_attr(node, attr, gens, container):
"""
Calcs fitness based on the fact that node's target shall not have an attr
with a certain value.
"""
trg_nd = container.nodes[gens[node]]
if attr[0] in trg_nd and attr[1] == trg_nd[attr[0]]:
return 10.1
return 0.0 | adfa39aa60d0777b2b05f174a9cf61a847e55b1d | 3,656,171 |
def getItem( user, list, itempk ):
"""
Get a single item from a list.
:param user: user who owns list
:param list: list containing item
:param itempk: private key of item
:return: item or None
"""
itemType = list.itemType
item = None
if itemType == 'Item':
ite... | f0d2c3a6d1881e0e1288aae451a556ebe856242e | 3,656,172 |
def metric_divergence(neighborhood_vectors: np.ndarray, dL: float, polarity: int) -> float:
"""
Calculates the divergence of a sampling volume neighborhood.
Note: For JIT to work, this must be declared at the top level.
@param neighborhood_vectors: Sampling volume neighborhood vectors (six 3D vectors)... | 87dd2b19c654143ed54f3783059ece50eb32ec71 | 3,656,173 |
import argparse
def parse_args():
"""
Parse command line arguments.
Parameters:
None
Returns:
parser arguments
"""
parser = argparse.ArgumentParser(description='LeNet model')
optional = parser._action_groups.pop()
required = parser.add_argument_group('required arguments')
required.add_argument('--datase... | 6a93e1083ebc8fad5f0698b2e0a4eb125af2806f | 3,656,174 |
def tag(request):
"""
Add/Remove tag to email
"""
if request.is_ajax():
mail = request.POST.get("mail")
tag = request.POST.get("tag")
op = request.POST.get("op")
mail = get_object_or_404(Mail, pk=mail)
if op == "ADD":
mail.tags.add(tag)
elif op... | b1f5c2e65393be1d68a03b01c522214413e5b321 | 3,656,175 |
def sid_to_smiles(sid):
"""Takes an SID and prints the associated SMILES string."""
substance = pc.Substance.from_sid(sid)
cid = substance.standardized_cid
compound = pc.get_compounds(cid)[0]
return compound.isomeric_smiles | e243e201a8ac4e4ee63332454a8b8c64f0f43692 | 3,656,176 |
def view_static(request, **kwargs):
"""Outputs static page."""
template = kwargs.get('template', None)
if not template:
raise Http404
template = '.'.join([template, 'html'])
title = kwargs.get('title', 'static page')
img = kwargs.get('img', 'bgag.jpg')
return render_to_response(temp... | b6997e86175688f9b1293b0888faeb337bb5f3b6 | 3,656,177 |
def start_call(called_ident, skicall):
"""When a call is initially received this function is called.
Unless you want to divert to another page, this function should return called_ident which
would typically be the ident of a Responder or Template page dealing with the call.
If a ServeFile excep... | 0353d81273ea6638858bf18271f4480895ca1db1 | 3,656,178 |
def getmemory():
"""
Returns the memory limit for data arrays (in MB).
"""
return NX_MEMORY | f6850ac2ad5854f9798ef480e9ca105bf31644ed | 3,656,179 |
import this
def get_object_syncing_state():
""" Get a dictionary mapping which object trackers are active.
The dictionary contains name:bool pairs that can be fed back into
the func:`set_object_syncing_state()` function.
"""
states = {
"selection": bool(this._on_selection_changed_cb_id),
... | c6fa40e7945b8186db06cc00b461fc2fe6a16c36 | 3,656,180 |
def determine_nohit_score(cons, invert):
"""
Determine the value in the matrix assigned to nohit given SeqFindr options
:param cons: whether the Seqfindr run is using mapping consensus data
or not
:param invert: whether the Seqfindr run is inverting (missing hits to
... | d0539b5ac4dda8b4a15c6800fb4a821cb305b319 | 3,656,181 |
def estimate_csd(lfp, coord_electrode, sigma, method='standard', diam=None,
h=None, sigma_top=None, tol=1E-6, num_steps=200,
f_type='identity', f_order=None):
"""
Estimates current source density (CSD) from local field potential (LFP)
recordings from multiple depths of the ... | eefe158dc93d9d2be23f7754b658c1f812cd8524 | 3,656,182 |
def library_get_monomer_desc(res_name):
"""Loads/caches/returns the monomer description objec MonomerDesc
for the given monomer residue name.
"""
assert isinstance(res_name, str)
try:
return MONOMER_RES_NAME_CACHE[res_name]
except KeyError:
pass
mon_desc = library_construct... | 98b4790995bd1d2eba96775e99826fae7b7cfc8a | 3,656,183 |
def parse_single_sequence_example(
serialized, context_features=None, sequence_features=None,
example_name=None, name=None):
# pylint: disable=line-too-long
"""Parses a single `SequenceExample` proto.
Parses a single serialized [`SequenceExample`](https://www.tensorflow.org/code/tensorflow/core/example/e... | 89309aab313b89224a87cb3cf7f4d56356981885 | 3,656,184 |
import scipy
import os
def getBase64PNGImage(pD, cmapstr, logfloor_quantile=0):
"""
Get an image as a base64 string
"""
D = np.array(pD)
if logfloor_quantile > 0:
floor = np.quantile(pD.flatten(), logfloor_quantile)
D = np.log(D + floor)
c = plt.get_cmap(cmapstr)
D = D-np.m... | 9fa7a41624d14943e48221e9277320324f575d33 | 3,656,185 |
import sys
def method_dispatcher(*args, **kwargs):
"""Try to dispatch to the right HTTP method handler.
If an HTTP method isn't on the approved list, defer
to the error handler. Otherwise, the HTTP Method is
processed by the appropriate handler.
:param args: Expect arguments in format (http_metho... | 7c680aae25de4b158db0befa0963923ddb903f8a | 3,656,186 |
def _seqfix(ref_seq, seq, comp_len, rev):
""" Fill or trim a portion of the beginning of a sequence relative to a
reference sequence
Args:
ref_seq (str): reference sequence e.g. germline gene
seq (str): sequence to compare to reference
comp_len (int): length of s... | 222ba3a8e2c4bced8ebcde6662890c10a0b41cf8 | 3,656,187 |
import torch
from typing import Tuple
def get_dedup_tokens(logits_batch: torch.Tensor) \
-> Tuple[torch.Tensor, torch.Tensor]:
"""Converts a batch of logits into the batch most probable tokens and their probabilities.
Args:
logits_batch (Tensor): Batch of logits (N x T x V).
Returns:
... | 885048842e6d1b50cd5b98c5b455aeb71e49c191 | 3,656,188 |
def com(im):
"""
Compute the center of mass of im.
Expects that im is leveled (ie zero-centered). Ie, a pure noise image should have zero mean.
Sometimes this is improved if you square the im first com(im**2)
Returns:
y, x in array form.
"""
im = np.nan_to_num(im)
mass = np.sum(i... | 5e1a7c20075df3fe5804213e5fdddd4f46d276c6 | 3,656,189 |
def get_fitting_custom_pipeline():
"""
Pipeline looking like this
lagged -> custom -> ridge
"""
lagged_node = PrimaryNode('lagged')
lagged_node.custom_params = {'window_size': 50}
# For custom model params as initial approximation and model as function is necessary
custom_node =... | 3ed78dc2f83110b0ac7dd4622a76511d0316404f | 3,656,190 |
def get_regularizable_variables(scope):
"""
Get *all* regularizable variables in the scope.
:param scope: scope to filter variables by
:return:
"""
return tf.get_collection(REGULARIZABLE_VARS, scope) | 67a6673be12af47128a453e413778f18f4344eaa | 3,656,191 |
import glob
def load(midi_path: str, config: dict):
"""
returns a 3-tuple of `tf.Dataset` each returning `(input_seq, target_seq)`, representing train,
validation, and test portions of the overall dataset. `input_seq` represents the `inp_split`
portion of each midi sequence in `midi_path`.
"""
batch... | 38d890a78cf85ce43cbdb783246ef1a5e7e2cd06 | 3,656,192 |
import re
def _parse_docstring(doc):
"""Extract documentation from a function's docstring."""
if doc is None:
return _Doc('', '', {}, [])
# Convert Google- or Numpy-style docstrings to RST.
# (Should do nothing if not in either style.)
# use_ivar avoids generating an unhandled .. attribut... | ff4e3ce300748c32c2e65129c381f1e74912f4a1 | 3,656,193 |
def extract_remove_outward_edges_filter(exceptions_from_removal):
"""
This creates a closure that goes through the list of tuples to explicitly state which edges are leaving from the first argument of each tuple.
Each tuple that is passed in has two members. The first member is a string representing a sing... | 543e5823b8375cbdec200988ea5dd0c4f2d23d05 | 3,656,194 |
import torch
def ln_addTH(x : torch.Tensor, beta : torch.Tensor) -> torch.Tensor:
"""
out = x + beta[None, :, None]
"""
return x + beta[None, :, None] | 77e556c41a33a8c941826604b4b595ea7d456f9a | 3,656,195 |
def drude2(tags, e, p):
"""dielectric function according to Drude theory for fitting"""
return drude(e, p[0], p[1], p[2], p[3]) | 8032c61df099f6c1ac671f2b81c3bb93d1f81317 | 3,656,196 |
def ParseFile(path):
"""Parse function names and comments from a .h path.
Returns mapping from function name to comment.
"""
result = {}
with open(path, 'r') as fp:
lines = fp.readlines()
i = 0
n = len(lines)
while i < n:
line = lines[i]
m = MCRE.match(line)
if m and not m.g... | 6319137de084aaf366b28e76af52cc1911298d8b | 3,656,197 |
from typing import Dict
def get_records(data: Dict[_Expr, Dict], column_order):
"""Output data as a list of records"""
def cell_callback(expr, i, val, spreadsheet_data):
spreadsheet_data[-1].append(val)
return spreadsheet_data
def row_callback(spreadsheet_data):
spreadsheet_data[-1... | 8a8eb0e69c9dabe6dfc59c9b5637fdf4ee2d2dd1 | 3,656,198 |
import torch
def support_mask_to_label(support_masks, n_way, k_shot, num_points):
"""
Args:
support_masks: binary (foreground/background) masks with shape (n_way, k_shot, num_points)
"""
support_masks = support_masks.view(n_way, k_shot*num_points)
support_labels = []
for n in range(sup... | e6d73dc93e1e0b54d805d9c8b69785168dd2621e | 3,656,199 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.