content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def mvw_ledoit_wolf(prices,
weight_bounds=(0.,1.),
rf = 0.,
options = None):
"""
Calculates the mean-variance weights given a DataFrame of returns.
Wraps mean_var_weights with ledoit_wolf covariance calculation method
Args:
* prices (... | 086f6430d189fd12509d56ce4a96a351a178979b | 3,651,100 |
def _PadLabels3d(logits, labels):
"""Pads or slices 3-d labels to match logits.
Covers the case of 2-d softmax output, when labels is [batch, height, width]
and logits is [batch, height, width, onehot]
Args:
logits: 4-d Pre-softmax fully-connected output.
labels: 3-d, but not necessarily matching in si... | 223f7dfea9ebc970e62dbe71e2f27dfb5c9f161d | 3,651,101 |
def intx():
"""Returns the default int type, as a string.
(e.g. 'int16', 'int32', 'int64').
# Returns
String, the current default int type.
"""
return _INTX | 57661ef00953e07228ff81abc93ec22c216797ff | 3,651,102 |
import json
def dev_end_hardware_script() -> Response:
"""Designate the end of a hardware script in flask log.
Can be invoked by: curl http://localhost:4567/development/end_hardware_script
"""
return Response(json.dumps({}), mimetype="application/json") | 714b448642180753e639992f2d101841074aeefd | 3,651,103 |
def _init_train(opt):
"""Common initilization stuff for all training process."""
ArgumentParser.validate_prepare_opts(opt)
if opt.train_from:
# Load checkpoint if we resume from a previous training.
checkpoint = load_checkpoint(ckpt_path=opt.train_from)
fields = load_fields(opt.save... | bb2a043d1a59f996b303aabf9db724ced3505dbf | 3,651,104 |
import os
import fnmatch
def main(wf):
"""Run workflow script."""
opts = docopt.docopt(__doc__, argv=wf.args, version=wf.version)
if opts['list']:
return list_actions(opts)
dry_run = opts['--nothing']
log.info('=' * 50)
log.debug('opts=%r', opts)
log.info('looking for workflows us... | 7d62c3e498374097eaf232bc8195da908a370dbd | 3,651,105 |
def compare(isamAppliance1, isamAppliance2):
"""
Compare Update Servers between two appliances
"""
ret_obj1 = get_all(isamAppliance1)
ret_obj2 = get_all(isamAppliance2)
for obj in ret_obj1['data']:
del obj['uuid']
for obj in ret_obj2['data']:
del obj['uuid']
return ibms... | e29025ca0af897f10b3b8498f8def86841b76c97 | 3,651,106 |
from rasterio import Affine, features
from gisutils import get_authority_crs
from fiona.crs import from_epsg, to_string
def rasterize(feature, grid, id_column=None,
include_ids=None,
crs=None, epsg=None, proj4=None,
dtype=np.float32, **kwargs):
"""Rasterize a feature onto... | 474fd8dc871d6d2b64eb459f2c026be764f6a48d | 3,651,107 |
import random
def get_random():
"""
Retrieves the current issue of XKCD, chooses an issue 1 - current issue #, and returns a json object.
Returns null if an requests error occurs.
"""
return get_issue(random.randint(1, int(get_current()["num"]))) | 10fbf75681901722510b0b9fbb2de298eb80b45e | 3,651,108 |
def get_fasta_readlengths(fasta_file):
"""
Get a sorted list of contig lengths
:return: (tuple)
"""
lens = []
with open_fasta_reader(fasta_file) as f:
for record in f:
lens.append(len(record.sequence))
lens.sort()
return lens | 769cf5af50ba684c107a1312d2aeaab2721a29c6 | 3,651,109 |
def postprocess(p, gt, width_and_height, p_binary, false_positives=False, false_negatives=False):
"""
This function does matching and then postprocessing of p's and gt's
:param p: the objects given from rcnn
:param gt: the objects we get from the ground truth
:param width_and_height: the width and h... | dd83de4547f7c1461b64fcd2dfa4c3df54aefd10 | 3,651,110 |
from csb.bio.structure import TorsionAngles
import numpy
def deg(x):
"""
Convert an array of torsion angles in radians to torsion degrees
ranging from -180 to 180.
@param x: array of angles
@type x: numpy array
@rtype: numpy array
"""
func = numpy.vectorize(TorsionAngles.d... | 95e37a0c644df1562e417c1ad61e4788bd46c279 | 3,651,111 |
import timeit
def run_median_trial():
"""Generate table for Median Trial."""
tbl = DataTable([10,15,15],['N', 'median_time', 'sort_median'])
trials = [2**k+1 for k in range(8,20)]
for n in trials:
t_med = 1000*min(timeit.repeat(stmt='assert(linear_median(a) == {}//2)'.format(n),
... | ed4c5ebe8bd6259c4adc45c4b023cc5bb96a1055 | 3,651,112 |
def regroup(X, N):
"""
Regroups the rows and columns of X such that rows/cols
that are N apart in X, are adjeacent in Y. If N is a
2 element vector, N[0] is used for rows and N[1] is used
for columns.
Parameters:
X: m by n matrix to be regrouped.
N: Integer or two element vector... | 7ad92b878cb6a55820ef9ad92c68e934184d725d | 3,651,113 |
def return_estimators(n_components):
"""Returns all of the estimators that can be used to generate models.
A larger selection of possible estimators have been commented out, but
could be uncommented."""
estimators = [
('PCArandom',
decomposition.PCA(n_components=n_components, svd_solve... | 680aa1d50c4e2db0e4d3df9e60749350df437bb8 | 3,651,114 |
def _check_type_picks(picks):
"""helper to guarantee type integrity of picks"""
err_msg = 'picks must be None, a list or an array of integers'
if picks is None:
pass
elif isinstance(picks, list):
if not all(isinstance(i, int) for i in picks):
raise ValueError(err_msg)
... | 79493f75db8e57f32a6369ad18900e0632d2bc18 | 3,651,115 |
def get_test_standard_scaler_str():
"""
Get a pandas projection code str
"""
test_code = cleandoc("""
standard_scaler = StandardScaler()
encoded_data = standard_scaler.fit_transform(df)
""")
return test_code | fd6e1daa7e0dddb603437e5b35c283a11e68ec00 | 3,651,116 |
from typing import List
from typing import Tuple
import re
def add_command(
command_list: List[Tuple[re.Pattern, callable]], func: callable, command_str: str
) -> List[Tuple[re.Pattern, callable]]:
"""Add a function and the command pattern to the command list.
Args:
func: Function it will be call... | f8076e4a6b37722591eae04a67feb1c25e606b84 | 3,651,117 |
def get_clusters_and_critical_nodes(G, k, rho_star, phi_in):
"""
The implementation of the main body of the partitioning Algorithm.
The main while-loop of the algorithm is executed as long as a refinement is still possible.
:param phi_in: An algorithm parameter used to lower bound the inner conductance... | e7374c9cad30a87477ee5b9ce4d0a0e9cb7de041 | 3,651,118 |
def get_edges_out_for_vertex(edges: list, vertex: int) -> list:
"""Get a sublist of edges that have the specified vertex as first element
:param edges: edges of the graph
:param vertex: vertex of which we want to find the corresponding edges
:return: selected edges
"""
return [e for e in edge... | 21485073df1c754e7c8e2b7dd9cafef284e601e7 | 3,651,119 |
def pellet_plot_multi_unaligned(FEDs, shade_dark, lights_on,
lights_off,**kwargs):
"""
FED3 Viz: Plot cumulaive pellet retrieval for multiple FEDs, keeping the
x-axis to show absolute time.
Parameters
----------
FEDs : list of FED3_File objects
FED3 files... | 3601e8ecff20a3d7978f7261ebaa5236d662a25e | 3,651,120 |
import time
def sync_via_mrmsdtw(f_chroma1: np.ndarray,
f_chroma2: np.ndarray,
f_DLNCO1: np.ndarray = None,
f_DLNCO2: np.ndarray = None,
input_feature_rate: float = 50,
step_sizes: np.ndarray = np.array([[1, 0], [... | 00dac7bdde14597e0daece958e65761ec01d1494 | 3,651,121 |
def simulate_beta_binomial(
K, D, sigma2, theta, mu=0, invlink=logistic, seed=None):
"""Simulates from binomial Gaussian process with Beta latent noise.
Args:
K: Cell-state kernel, for example as generated by create_linear_kernel
or create_rbf_kernel.
D: Array of total counts.
... | de4648af70a6b35c7b7f5edc2c151a98db6d7603 | 3,651,122 |
def convert_to_floats(tsi):
"""
A helper function that tax all of the fields of a TaxSaveInputs model
and converts them to floats, or list of floats
"""
def numberfy_one(x):
if isinstance(x, float):
return x
else:
return float(x)
def numberfy(x):
... | a6f93f402c547435fa9fe611481084215f52f13b | 3,651,123 |
def properties_filter(mol):
"""
Calculates the properties that contain logP, MW, HBA, HBD, TPSA, NRB
"""
#frag = Chem.rdmolops.GetMolFrags(mol) # remove '.'
#if len(frag) > 1:
#return False
MW_s = Descriptors.MolWt(mol) # MW
if MW_s < 250 or MW_s > 750:
return False
A... | bc124620baddb828b4c5cb82e0b0374bdb51bad7 | 3,651,124 |
def _create_certificate_chain():
"""
Construct and return a chain of certificates.
1. A new self-signed certificate authority certificate (cacert)
2. A new intermediate certificate signed by cacert (icert)
3. A new server certificate signed by icert (scert)
"""
caext = X509Exten... | 156a61e8159b1826def8fa33d5c5965add2c7f2e | 3,651,125 |
def build_job_spec_name(file_name, version="develop"):
"""
:param file_name:
:param version:
:return: str, ex. job-hello_world:develop
"""
name = file_name.split('.')[-1]
job_name = 'job-%s:%s' % (name, version)
return job_name | 55a45052852e6b24cb4370f7efe5c213da83e423 | 3,651,126 |
import torch
def draw_mask(im: torch.Tensor, mask: torch.Tensor, t=0.2, color=(255, 255, 255), visualize_instances=True):
"""
Visualize mask where mask = 0.
Supports multiple instances.
mask shape: [N, C, H, W], where C is different instances in same image.
"""
assert len(mask.shap... | 45d12dbc695755f0231ca2a8d0f8d1cdf2f423ff | 3,651,127 |
def view_about():
"""
shows the about page
:return:
:rtype:
"""
return render_template('about.html', title="About Flask AWS Template") | a364842c165864aba34605f3ffdd8c1d412015e8 | 3,651,128 |
import numpy
def viterbi(observed_values,
transition_probabilities,
emission_probabilities,
initial_distribution,
file_name,
log=True):
"""Calculates the viterbi-path for a given hidden-markov-model, heavily
inspired by Abhisek Janas Blogpost "Implem... | b063e5c5bbf566afb0f16175d9d229bef7a953f1 | 3,651,129 |
def extract_psf_fitting_names(psf):
"""
Determine the names of the x coordinate, y coordinate, and flux from
a model. Returns (xname, yname, fluxname)
"""
if hasattr(psf, 'xname'):
xname = psf.xname
elif 'x_0' in psf.param_names:
xname = 'x_0'
else:
raise ValueError... | cee108dd1f97e506b60ba621c7f08efa7b5c33d7 | 3,651,130 |
def parseargs(p):
"""
Add arguments and `func` to `p`.
:param p: ArgumentParser
:return: ArgumentParser
"""
# TODO: Implement --date, --time and -t
p.set_defaults(func=func)
p.description = (
"Update the access and modification times of each "
+ "FILE to the current tim... | b6689761da04ebf3ac7e1b9682b4291c5dd4e9c1 | 3,651,131 |
def config_check_conformance(cookie, dn):
""" Auto-generated UCS XML API Method. """
method = ExternalMethod("ConfigCheckConformance")
method.cookie = cookie
method.dn = dn
xml_request = method.to_xml(option=WriteXmlOption.DIRTY)
return xml_request | 598fbd665dcf18a35104400bf7debfc64347c3b5 | 3,651,132 |
def get_dist_to_port(geotiff):
"""
Extract "truth" dist_to_port from geotiff
"""
with Geotiff(geotiff) as tif:
dist_to_port = tif.values
return dist_to_port | 1a77c2ac905eea2d1796529297168dac394b4bdb | 3,651,133 |
import inspect
def build_dataset_exporter(
dataset_type, strip_none=True, warn_unused=True, **kwargs
):
"""Builds the :class:`DatasetExporter` instance for the given parameters.
Args:
dataset_type: the :class:`fiftyone.types.dataset_types.Dataset` type
strip_none (True): whether to exclud... | 6a21c90ee2a9c297ad86515f5078221459b1fb01 | 3,651,134 |
def conditions(x):
"""
This function will check whether the constraints that apply to
our optimization are met or not.
"""
if ( (10/x[0]) > 66.0 ):
return False
elif ( (10/x[0] + 12/x[1]) > 88.0 ):
return False
elif ( (10/x[0] + 12/x[1] + 7/x[2]) > 107.0 ):
return ... | 263fdc3fd07aa656982401f71071fcd684b8625f | 3,651,135 |
import scipy
from typing import Mapping
from typing import OrderedDict
import logging
def load_reco_param(source):
"""Load reco parameterisation (energy-dependent) from file or dictionary.
Parameters
----------
source : string or mapping
Source of the parameterization. If string, treat as fil... | 9d707f3403e0225223b6fe081158d31476b8281c | 3,651,136 |
def get_commit_ancestors_graph(refenv, starting_commit):
"""returns a DAG of all commits starting at some hash pointing to the repo root.
Parameters
----------
refenv : lmdb.Environment
lmdb environment where the commit refs are stored
starting_commit : string
commit hash to start c... | 078819cf0291a5e4e1e8ad4ea409f475c0df93fd | 3,651,137 |
def is_verification_handshake(rjson):
"""
Determines if the request is the Slack application APIs verification handshake
:rtype: bool
"""
# Check body contains the right keys
for x in ['token', 'challenge', 'type']:
if x not in rjson:
return False
# Check type is correct... | 1ceccd9ca578bd09e9629cd59e565bc523502030 | 3,651,138 |
def template_node(scope_key):
""" Create and return a new template node.
Parameters
----------
scope_key : object
The key for the local scope in the local storage maps.
Returns
-------
result : TemplateNode
A new compiler template node.
"""
node = TemplateNode()
... | 4cd9721dd9f9f91cb84326391630274b8f5764a7 | 3,651,139 |
def GetAutoResult(chroot_path, buildbucket_id):
"""Returns the conversion of the result of 'cros buildresult'."""
# Calls 'cros buildresult' to get the status of the tryjob.
build_result = GetStatusFromCrosBuildResult(chroot_path, buildbucket_id)
# The string returned by 'cros buildresult' might not be in the... | 705fbc011c11fa67d0b61f130a3b6f024a6dcd44 | 3,651,140 |
def rft(x):
"""
Real Fourier Transform
"""
# XXX figure out what exactly this is doing...
s = x.shape[-1]
xp = np.zeros(x.shape,dtype="complex64")
xp[...,1:s/2] = x[...,1:-1:2]+x[...,2::2]*1.j
xp[...,0] = x[...,0]/2.
xp[...,s/2] = x[...,-1]/2.
return np.array(nmr_reorder(np.fft... | 3a65f0a0059df4c74b223f3284e996b82d7ebf02 | 3,651,141 |
def yam_path(manifestsdir):
"""Bundletracker manifest."""
return join(manifestsdir, 'yam.json') | 5d1b5162bd8285d8e33c822a3b5edcc996452719 | 3,651,142 |
def single_from(iterable):
"""Check that an iterable contains one unique value, and return it."""
unique_vals = set(iterable)
if len(unique_vals) != 1:
raise ValueError('multiple unique values found')
return unique_vals.pop() | c8fb8864083195ad913ff1ddf0114b5a50068902 | 3,651,143 |
import requests
def vthash(filehash: str):
"""Returns the analysis data class for a file in VirusTotal's database"""
endpoint_path = f'/files/{filehash}'
endpoint = f"{api_base_url}{endpoint_path}"
r = requests.get(endpoint, headers=header)
if r.status_code == 404 and r.json()['error']['code'] ... | bf4f334ad7a35e1141f9e00a44544fdd0709b411 | 3,651,144 |
def prod(x, axis=None, keepdims=False):
"""
product of all element in the array
Parameters
----------
x : tensor_like
input array
axis : int, tuple of ints
axis or axes along which a product is performed
keepdims : bool
keep dimensionality or not
Returns
---... | 8962e7b6abd16c9354f076c0c6d718b82fe44223 | 3,651,145 |
from typing import List
import difflib
def menu(queue: List[str] = None):
"""Fred Menu"""
fred_controller = FredController(queue)
an_input = "HELP_ME"
while True:
# There is a command in the queue
if fred_controller.queue and len(fred_controller.queue) > 0:
# If the comman... | b8133dd748f0a48099359b6503edee6c9f875fb6 | 3,651,146 |
def generic_repr(name, obj, deferred):
"""
Generic pretty printer for NDTable and NDArray.
Output is of the form::
Array(3, int32)
values := [Numpy(ptr=60597776, dtype=int64, shape=(3,))];
metadata := [contigious]
layout := Identity;
[1 2 3]
"""
... | c9de29b792d943420b02455752f01a9c12fcf66c | 3,651,147 |
def build_model(X, y, ann_hidden_dim, num_passes=20000):
"""
:param ann_hidden_dim: Number of nodes in the hidden layer
:param num_passes: Number of passes through the training data for gradient descent
:return: returns the parameters of artificial neural network for prediction using forward propagation... | bccdf828050af8a6ff5943eb84b574756f9f54ab | 3,651,148 |
def g_square_dis(dm, x, y, s):
"""G square test for discrete data.
Args:
dm: the data matrix to be used (as a numpy.ndarray).
x: the first node (as an integer).
y: the second node (as an integer).
s: the set of neibouring nodes of x and y (as a set()).
levels: levels of ... | 2f0f0b44a919177c0f5775a34e0493c62720a21d | 3,651,149 |
def start(name):
"""
Start the specified service
CLI Example:
.. code-block:: bash
salt '*' service.start <service name>
"""
cmd = "/usr/sbin/svcadm enable -s -t {0}".format(name)
retcode = __salt__["cmd.retcode"](cmd, python_shell=False)
if not retcode:
return True
... | 607b559281c6b13002d7237b8c4409533074d0bc | 3,651,150 |
from typing import Dict
def line_coloring(num_vertices) -> Dict:
"""
Creates an edge coloring of the line graph, corresponding to the optimal
line swap strategy, given as a dictionary where the keys
correspond to the different colors and the values are lists of edges (where edges
are specified as ... | 423e626ecbf4f48e0a192241375484a077fbe0b2 | 3,651,151 |
def flatten_outputs(predictions, number_of_classes):
"""Flatten the prediction batch except the prediction dimensions"""
logits_permuted = predictions.permute(0, 2, 3, 1)
logits_permuted_cont = logits_permuted.contiguous()
outputs_flatten = logits_permuted_cont.view(-1, number_of_classes)
return out... | c58fb965443a5402e9bec32afaebe9376c74653f | 3,651,152 |
def get_r_vals(cell_obj):
"""Get radial distances for inner and outer membranes for the cell object"""
r_i = cell_obj.coords.calc_rc(cell_obj.data.data_dict['storm_inner']['x'],
cell_obj.data.data_dict['storm_inner']['y'])
r_o = cell_obj.coords.calc_rc(cell_obj.data.data_di... | d51c926791845006dfe9a97cbd9c82c041ea701b | 3,651,153 |
def get_all_migrations(ctxt, inactive=0):
"""Get all non-deleted source hypervisors.
Pass true as argument if you want deleted sources returned also.
"""
return db.migration_get_all(ctxt, inactive) | c8e8ae084ca42d560e79412e4ff56d79059055a6 | 3,651,154 |
def extract(input_data: str) -> tuple:
"""take input data and return the appropriate data structure"""
rules = input_data.split('\n')
graph = dict()
reverse_graph = dict()
for rule in rules:
container, contents = rule.split('contain')
container = ' '.join(container.split()[:2])
... | f71cdc23fdfaf6ef0d054c0c68e513db66289c12 | 3,651,155 |
def get_total_indemnity(date_of_joining, to_date):
"""To Calculate the total Indemnity of an employee based on employee's Joining date.
Args:
date_of_joining ([date]): Employee's Joining Date
to_date ([data]): up until date
Returns:
total_allocation: Total Indemnity Allocation calc... | 1b09d0dc7971ab4c3d63c303a93f64da924dcfa4 | 3,651,156 |
import os
def run_species_phylogeny_iqtree(roary_folder, collection_dir, threads=8, overwrite=False, timing_log=None):
"""
Run iqtree to create phylogeny tree from core gene alignment. If the list of samples has
not changed, and none of the samples has changed, the existing tree will be kept unless
ov... | a5a6cd8e77cc3622264f4827753a2260e38d9f70 | 3,651,157 |
def api_2_gamma_oil(value):
"""
converts density in API(American Petroleum Institute gravity) to gamma_oil (oil relative density by water)
:param value: density in API(American Petroleum Institute gravity)
:return: oil relative density by water
"""
return (value + 131.5) / 141.5 | 20e625f22092461fcf4bc2e2361525abf8051f97 | 3,651,158 |
def compute_metrics(pred, label):
"""Compute metrics like True/False Positive, True/False Negative.`
MUST HAVE ONLY 2 CLASSES: BACKGROUND, OBJECT.
Args:
pred (numpy.ndarray): Prediction, one-hot encoded. Shape: [2, H, W], dtype: uint8
label (numpy.ndarray): Ground Truth, one-hot encoded.... | be8415c997197c06a5998671ffe09e70c6d3719c | 3,651,159 |
import jinja2
def expand_template(template, variables, imports, raw_imports=None):
"""Expand a template."""
if raw_imports is None:
raw_imports = imports
env = jinja2.Environment(loader=OneFileLoader(template))
template = env.get_template(template)
return template.render(imports=imports, variables=varia... | c5ebe1610a6e2fa9e0b18afa7d23652c1f7c25ba | 3,651,160 |
from typing import Any
from operator import truth
def __contains__(container: Any, item: Any, /) -> bool:
"""Check if the first item contains the second item: `b in a`."""
container_type = type(container)
try:
contains_method = debuiltins._mro_getattr(container_type, "__contains__")
except Att... | b58a5f400895df472f83a5e2410dff9cd112fc91 | 3,651,161 |
def generate_search_url(request_type):
"""Given a request type, generate a query URL for kitsu.io."""
url = BASE_URL_KITSUIO.format(request_type)
return url | 9508d909fb8eb018770b2191f7d62ccb3881f285 | 3,651,162 |
from typing import Callable
def register_magic(func: Callable[[Expr], Expr]):
"""
Make a magic command more like Julia's macro system.
Instead of using string, you can register a magic that uses Expr as the
input and return a modified Expr. It is usually easier and safer to
execute metaprogrammin... | 06d93f8a48758dc39679af396c10a54927e3696e | 3,651,163 |
import os
def flowcellDirFastqToBwaBamFlow(self, taskPrefix="", dependencies=set()) :
"""
Takes as input 'flowcellFastqDir' pointing to the CASAVA 1.8 flowcell
project/sample fastq directory structure. For each project/sample,
the fastqs are aligned using BWA, sorted and merged into a single
BAM f... | 6f18083fc2c9e4a260e87c332d40d9322f2c7bc1 | 3,651,164 |
def ValidatePregnum(resp):
"""Validate pregnum in the respondent file.
resp: respondent DataFrame
"""
# read the pregnancy frame
preg = nsfg.ReadFemPreg()
# make the map from caseid to list of pregnancy indices
preg_map = nsfg.MakePregMap(preg)
# iterate through the respondent pre... | a51f3af130cbad4a5cd3d3c9707788f783302000 | 3,651,165 |
def is_super_admin(view, view_args, view_kwargs, *args, **kwargs):
"""
Permission function for things allowed exclusively to super admin.
Do not use this if the resource is also accessible by a normal admin, use the is_admin decorator instead.
:return:
"""
user = current_user
if not user.is_... | 503550fcd52e62053d42a3059aba298009d3eb01 | 3,651,166 |
def normalize_depth(val, min_v, max_v):
"""
print 'nomalized depth value'
nomalize values to 0-255 & close distance value has high value. (similar to stereo vision's disparity map)
"""
return (((max_v - val) / (max_v - min_v)) * 255).astype(np.uint8) | 431cda7af30ef1127c60069b6958ef4d8234eaae | 3,651,167 |
def parse_iori_block(block):
"""Turn IORI data blocks into `IoriData` objects.
Convert rotation from Quaternion format to Euler angles.
Parameters
----------
block: list of KVLItem
A list of KVLItem corresponding to a IORI data block.
Returns
-------
iori_data: IoriData
... | b9ad59677e51c30b2bec51a0503fc2718cde0f7d | 3,651,168 |
def ungap_all(align):
"""
Removes all gaps (``-`` symbols) from all sequences of the :class:`~data.Align`
instance *align* and returns the resulting ~data.Container instance.
"""
result = data.Container()
for n,s,g in align:
result.append(n, s.translate(None, '-'), g)
... | 511b6aeb7fc262b733a97b5180a23c7f044fea06 | 3,651,169 |
def expandBcv(bcv):
"""If the bcv is an interval, expand if.
"""
if len(bcv) == 6:
return bcv
else:
return "-".join(splitBcv(bcv)) | abfb1bf31acca579fecb526d571b32cefa7ecd61 | 3,651,170 |
import os
def get_starting_dir_abs_path() -> str:
"""
Returns the absolute path to the starting directory of the project. Starting directory is used for example for
turning relative paths (from Settings) into absolute paths (those paths are relative to the starting directory).
"""
if _starting_dir... | af91f10a2dd9af8ba010f75fe295acb2406e9372 | 3,651,171 |
def cluster_profile_platform(cluster_profile):
"""Translate from steps.cluster_profile to workflow.as slugs."""
if cluster_profile == 'azure4':
return 'azure'
if cluster_profile == 'packet':
return 'metal'
return cluster_profile | 0a01f566562002fe43c3acbb00d5efcc09d25314 | 3,651,172 |
def get_price_lambda_star_lp_1_cvxpy(w: np.ndarray, c_plus: np.ndarray, psi_plus: np.ndarray) \
-> float:
"""
Computes lambda_star based on dual program of the projection of w_star.
:param w: current state in workload space.
:param c_plus: vector normal to the level set in the monotone region '... | 0a1a658cd86a0253fe3caf8a5e162393926b351a | 3,651,173 |
import typing
import random
def _get_nodes(
network: typing.Union[NetworkIdentifier, Network],
sample_size: typing.Optional[int],
predicate: typing.Callable,
) -> typing.List[Node]:
"""Decaches domain objects: Node.
"""
nodeset = [i for i in get_nodes(network) if predicate(i)]
if samp... | f3be401c2fd0adf58f10b679d254ff2075f4546b | 3,651,174 |
def cdl_key():
"""Four-class system (grain, forage, vegetable, orchard. Plus 5: non-ag/undefined"""
key = {1: ('Corn', 1),
2: ('Cotton', 1),
3: ('Rice', 1),
4: ('Sorghum', 1),
5: ('Soybeans', 1),
6: ('Sunflower', 1),
7: ('', 5),
8: (''... | 634a35d2962695dd0ef1b38a0c353498ca3dea89 | 3,651,175 |
def colmeta(colname, infile=None, name=None, units=None, ucd=None, desc=None,
outfile=None):
"""
Modifies the metadata of one or more columns. Some or all of the name,
units, ucd, utype and description of the column(s),
identified by "colname" can be set by using some or all of the listed ... | 15fc5b53e4ebd3563b00ef771a707d2ad2473ad7 | 3,651,176 |
def get_confusion_matrix_chart(cm, title):
"""Plot custom confusion matrix chart."""
source = pd.DataFrame([[0, 0, cm['TN']],
[0, 1, cm['FP']],
[1, 0, cm['FN']],
[1, 1, cm['TP']],
], columns=["actual valu... | 28884c46a51f3baf51dc5a6f3c0396a5c8f24e10 | 3,651,177 |
def get_ppo_plus_eco_params(scenario):
"""Returns the param for the 'ppo_plus_eco' method."""
assert scenario in DMLAB_SCENARIOS, (
'Non-DMLab scenarios not supported as of today by PPO+ECO method')
if scenario == 'noreward' or scenario == 'norewardnofire':
return md(get_common_params(scenario), {
... | 26bb3db0cf14eceea86cd659332c9bbc0195ab9b | 3,651,178 |
def field_display(name):
"""
Works with Django's get_FOO_display mechanism for fields with choices set. Given
the name of a field, returns a producer that calls get_<name>_display.
"""
return qs.include_fields(name), producers.method(f"get_{name}_display") | 7fbc17dddfa398934496099f605f6cee97a802ad | 3,651,179 |
import time
def set_trace(response):
"""
Set a header containing the request duration and push detailed trace to the MQ
:param response:
:return:
"""
if TRACE_PERFORMANCE:
req_time = int((time.time() - g.request_start) * 1000)
trace = {
"duration": req_time,
... | 1b7067daaf9fd3b72cf9b2db9a78b33b64bf8fb9 | 3,651,180 |
from typing import Dict
from typing import List
def extract_attachments(payload: Dict) -> List[Image]:
"""
Extract images from attachments.
There could be other attachments, but currently we only extract images.
"""
attachments = []
for item in payload.get('attachment', []):
# noinspe... | afb9d959e680c51fc327d6c7e5f5e74fdc5db5e6 | 3,651,181 |
from ...model_zoo import get_model
def yolo3_mobilenet1_0_custom(
classes,
transfer=None,
pretrained_base=True,
pretrained=False,
norm_layer=BatchNorm, norm_kwargs=None,
**kwargs):
"""YOLO3 multi-scale with mobilenet base network on custom dataset.
Parameters
... | 2da86fe66538e3cd9a21c456c00312a217ab5ca0 | 3,651,182 |
def calculate_levenshtein_distance(str_1, str_2):
"""
The Levenshtein distance is a string metric for measuring the difference between two sequences.
It is calculated as the minimum number of single-character edits necessary to transform one string into another
"""
distance = 0
buffer_re... | 949d54fbcbd2169aa06cedc7341e98c12412d03c | 3,651,183 |
from datetime import datetime
def make_datetime(value, *, format_=DATETIME_FORMAT):
"""
>>> make_datetime('2001-12-31T23:59:59')
datetime.datetime(2001, 12, 31, 23, 59, 59)
"""
return datetime.datetime.strptime(value, format_) | 5c6d79ae0ddc9f4c47592a90ed3232f556df0a49 | 3,651,184 |
import inspect
def named_struct_dict(typename, field_names=None, default=None, fixed=False, *, structdict_module=__name__,
base_dict=None, sorted_repr=None, verbose=False, rename=False, module=None, qualname_prefix=None,
frame_depth=1):
"""Returns a new subclass of Stru... | 465ac4783697b749c092d96fa8af498e67f15d51 | 3,651,185 |
from .pytorch.pytorch_onnxruntime_model import PytorchONNXRuntimeModel
def PytorchONNXRuntimeModel(model, input_sample=None, onnxruntime_session_options=None):
"""
Create a ONNX Runtime model from pytorch.
:param model: 1. Pytorch model to be converted to ONNXRuntime for inference
... | d925b67c3628995d75d1ea6c687e5beb022fdbd8 | 3,651,186 |
import os
def get_model_python_path():
"""
Returns the python path for a model
"""
return os.path.dirname(__file__) | 5ddd66f8b0c37b8a84eab614c4e3efd6efe9d9ef | 3,651,187 |
def intensity_variance(mask: np.ndarray, image: np.ndarray) -> float:
"""Returns variance of all intensity values in region of interest."""
return np.var(image[mask]) | e967b4cd3c3a896fba785d8c9e5f8bf07daa620d | 3,651,188 |
def permute_array(arr, axis=0):
"""Permute array along a certain axis
Args:
arr: numpy array
axis: axis along which to permute the array
"""
if axis == 0:
return np.random.permutation(arr)
else:
return np.random.permutation(arr.swapaxes(0, axis)).swapaxes(0, axis) | ce5f6d571062f36888d22836579332034f4fe924 | 3,651,189 |
import os
import errno
def convertGMLToGeoJSON(config, outputDir, gmlFilepath, layerName, t_srs='EPSG:4326',
flip_gml_coords=False):
""" Convert a GML file to a shapefile. Will silently exit if GeoJSON already exists
@param config A Python ConfigParser containing the section ... | 70ee0676d13a647d42a39313d5be1545042f73c7 | 3,651,190 |
def dsmatch(name, dataset, fn):
"""
Fuzzy search best matching object for string name in dataset.
Args:
name (str): String to look for
dataset (list): List of objects to search for
fn (function): Function to obtain a string from a element of the dataset
Returns:
First e... | 0835c0da3773eedab95c78e1b4f7f28abde0d8fd | 3,651,191 |
import os
import re
def _generate_flame_clip_name(item, publish_fields):
"""
Generates a name which will be displayed in the dropdown in Flame.
:param item: The publish item being processed.
:param publish_fields: Publish fields
:returns: name string
"""
# this implementation generates n... | 847956c6897a873145c78adbcf6530f0a47a9259 | 3,651,192 |
def f(q):
"""Constraint map for the origami."""
return 0.5 * (np.array([
q[0] ** 2,
(q[1] - q[0]) ** 2 + q[2] ** 2 + q[3] ** 2,
(q[4] - q[1]) ** 2 + (q[5] - q[2]) ** 2 + (q[6] - q[3]) ** 2,
q[4] ** 2 + q[5] ** 2 + q[6] ** 2,
q[7] ** 2 + q[8] ** 2 + q[9] ** 2,
(q[7... | 77c3617a76cb2e184b1f22404f1db8be8212a4c9 | 3,651,193 |
def resize(clip, newsize=None, height=None, width=None):
"""
Returns a video clip that is a resized version of the clip.
Parameters
------------
newsize:
Can be either
- ``(height,width)`` in pixels or a float representing
- A scaling factor, like 0.5
- A fu... | 5a8541e1320d37bd47aa35978794d849af358cb6 | 3,651,194 |
def calc_rt_pytmm(pol, omega, kx, n, d):
"""API-compatible wrapper around pytmm
"""
vec_omega = omega.numpy()
vec_lambda = C0/vec_omega*2*np.pi
vec_n = n.numpy()
vec_d = d.numpy()
vec_d = np.append(np.inf, vec_d)
vec_d = np.append(vec_d, np.inf)
vec_kx = kx.numpy().reshape([-1,1])... | def2fb22d2e72a873794838601bc74a7c65cb9c3 | 3,651,195 |
def statistic_bbox(dic, dic_im):
""" Statistic number of bbox of seed and image-level data for each class
Parameters
----------
dic: seed roidb dictionary
dic_im: image-level roidb dictionary
Returns
-------
num_bbox: list for number of 20 class's bbox
num_bbox_im: list for numb... | 782314baeab7fbec36c9ea56bcec57d5a508a918 | 3,651,196 |
def github_youtube_config_files():
"""
Function that returns a list of pyGithub files with youtube config channel data
Returns:
A list of pyGithub contentFile objects
"""
if settings.GITHUB_ACCESS_TOKEN:
github_client = github.Github(settings.GITHUB_ACCESS_TOKEN)
else:
... | 166ca3653173feee7513097c9313ebb5ab3b4d17 | 3,651,197 |
def reverse_uint(uint,num_bits=None):
"""
This function takes an unsigned integer and reverses all of its bits.
num_bits is number of bits to assume are present in the unsigned integer.
If num_bits is not specified, the minimum number of bits needed to represent the unsigned integer is assumed.
If n... | a3197aa3f199a5677a15e053c0455c0216d07827 | 3,651,198 |
def min_by_tail(lhs, ctx):
"""Element ↓
(any) -> min(a, key=lambda x: x[-1])
"""
lhs = iterable(lhs, ctx=ctx)
if len(lhs) == 0:
return []
else:
return min_by(lhs, key=tail, cmp=less_than, ctx=ctx) | 88fce303e6ff95f89e57ebd05c575810238497ea | 3,651,199 |
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