content stringlengths 22 815k | id int64 0 4.91M |
|---|---|
def fetch_last_posts(conn) -> list:
"""Fetch tooted posts from db"""
cur = conn.cursor()
cur.execute("select postid from posts")
last_posts = cur.fetchall()
return [e[0] for e in last_posts] | 30,800 |
def update_click_map(selectedData, date, hoverData, inputData):
"""
click to select a airport to find the detail information
:param selectedData:
:param date:
:param hoverData:
:return:
"""
timestamp = pd.to_datetime(date) if date else 0
fig = px.scatter_geo(
airports_info,
... | 30,801 |
def configure_blueprints(app: Flask):
"""
Configure blueprints.
"""
app.register_blueprint({{cookiecutter.blueprint_name}}) | 30,802 |
def EncoderText(model_name, vocab_size, word_dim, embed_size, num_layers, use_bi_gru=False, text_norm=True, dropout=0.0):
"""A wrapper to text encoders. Chooses between an different encoders
that uses precomputed image features.
"""
model_name = model_name.lower()
EncoderMap = {
'scan': Enco... | 30,803 |
def feat_extract(pretrained=False, **kwargs):
"""Constructs a ResNet-Mini-Imagenet model"""
model_urls = {
'resnet18': 'https://download.pytorch.org/models/resnet18-5c106cde.pth',
'resnet34': 'https://download.pytorch.org/models/resnet34-333f7ec4.pth',
'resnet52': 'https://do... | 30,804 |
def compose_all(
mirror: Union[str, Path],
branch_pattern: str = "android-*",
work_dir: Optional[Path] = None,
force: bool = False,
) -> Path:
"""Iterates through all the branches in AOSP and create the source maps.
This methods:
- list all the existing branches and filter those matchin... | 30,805 |
def rearrange_digits(input_list):
"""
Rearrange Array Elements so as to form two number such that their sum is maximum.
Args:
input_list(list): Input List
Returns:
(int),(int): Two maximum sums
"""
n = len(input_list)
heap_sort(input_list)
decimal_value = 1
n1 = 0
... | 30,806 |
def _partial_ema_scov_update(s:dict, x:[float], r:float=None, target=None):
""" Update recency weighted estimate of scov-like matrix by treating quadrants individually """
assert len(x)==s['n_dim']
# If target is not supplied we maintain a mean that switches from emp to ema
if target is None:
... | 30,807 |
def test_scalar_zero(py_c_vec: PyCVec):
"""Check zero behaviour with division ops."""
Vec, Angle, Matrix, parse_vec_str = py_c_vec
for x, y, z in iter_vec(VALID_NUMS):
vec = Vec(x, y, z)
assert_vec(0 / vec, 0, 0, 0)
assert_vec(0 // vec, 0, 0, 0)
assert_vec(0 % vec, 0, 0, 0)
... | 30,808 |
def refresh_rates(config, path="rates.json"):
"""Fetch and save the newest rates
Arguments:
config {currency.config} -- Config object
Keyword Arguments:
path {str} -- path or filename of Rates JSON to be saved
(default: {"rates.json"})
Returns:
dict -- fe... | 30,809 |
def add_all_files(root_dir: str = 'data/') -> List[Path]:
"""Recursively iterates over a directory and returns all files with paths
Args:
root_dir: the starting directory to search from
Returns:
List of all files found, with paths relative to the root_dir
"""
root_path = Path(root_... | 30,810 |
def migrate_component_indicators_data(apps, schema_editor):
"""
Adds the Indicator object from Component.indicator to the
many-to-many relationship in Component.indicators
"""
Component = apps.get_model('goals', 'Component')
for component in Component.objects.select_related('indicator')... | 30,811 |
def _get_chrome_options():
"""
Returns the chrome options for the following arguments
"""
chrome_options = Options()
# Standard options
chrome_options.add_argument("--disable-infobars")
chrome_options.add_argument('--ignore-certificate-errors')
# chrome_options.add_argument('--no-sandbo... | 30,812 |
def add_document(dbname, colname, doc, url=cc.URL_KRB, krbheaders=cc.KRBHEADERS) :
"""Adds document to database collection.
"""
resp = post(url+dbname+'/'+colname+'/', headers=krbheaders, json=doc)
logger.debug('add_document: %s\n to %s/%s resp: %s' % (str(doc), dbname, colname, resp.text))
return ... | 30,813 |
def legendre(n, monic=0):
"""Returns the nth order Legendre polynomial, P_n(x), orthogonal over
[-1,1] with weight function 1.
"""
if n < 0:
raise ValueError("n must be nonnegative.")
if n==0: n1 = n+1
else: n1 = n
x,w,mu0 = p_roots(n1,mu=1)
if n==0: x,w = [],[]
hn = 2.0/(2*... | 30,814 |
def cal_sort_key(cal):
"""
Sort key for the list of calendars: primary calendar first,
then other selected calendars, then unselected calendars.
(" " sorts before "X", and tuples are compared piecewise)
"""
if cal["selected"]:
selected_key = " "
else:
selected_key =... | 30,815 |
def test_env_dtm_formats(fmts, inp, exp):
"""
If $DTM_FORMATS is set, its value should be added at the beginning of the
default parseable input formats.
"""
pytest.dbgfunc()
with tbx.envset(DTM_FORMATS=fmts):
a = dt(inp)
assert a() == exp | 30,816 |
def get_data_loader():
"""Safely downloads data. Returns training/validation set dataloader."""
mnist_transforms = transforms.Compose(
[transforms.ToTensor(),
transforms.Normalize((0.1307, ), (0.3081, ))])
# We add FileLock here because multiple workers will want to
# download data, an... | 30,817 |
def preview_game_num():
"""retorna el numero de la ultima partida jugada"""
df = pd.read_csv('./data/stats.csv', encoding="utf8")
x = sorted(df["Partida"],reverse=True)[0]
return x | 30,818 |
def ensure_is_dir(d, clear_dir=False):
""" If the directory doesn't exist, use os.makedirs
Parameters
----------
d: str
the directory we want to create
clear_dir: bool (optional)
if True clean the directory if it exists
"""
if not os.path.exists(d):
os.makedirs(d)
... | 30,819 |
def XCO(
directed = False, preprocess = "auto", load_nodes = True, load_node_types = True,
load_edge_weights = True, auto_enable_tradeoffs = True,
sort_tmp_dir = None, verbose = 2, cache = True, cache_path = None,
cache_sys_var = "GRAPH_CACHE_DIR", version = "4.46", **kwargs
) -> Graph:
"""Return XC... | 30,820 |
async def test_wikidata_search_does_not_rank_aliases_high_enough(best_match_id, mock_aioresponse):
"""
Matches on aliases are not ranked high enough by the default search profile.
"""
assert (
await best_match_id('GER', typ='Q6256') ==
'Q183') | 30,821 |
def test_setURL_valid_URL_but_no_settings(caplog):
"""Test setURL"""
iface = MagicMock(autospec=SerialInterface)
url = "https://www.meshtastic.org/d/#"
with pytest.raises(SystemExit) as pytest_wrapped_e:
anode = Node(iface, 'bar', noProto=True)
anode.radioConfig = 'baz'
anode.set... | 30,822 |
def rasterize_layer_by_ref_raster(src_vector, ref_raster, use_attribute, all_touched=False, no_data_value=0):
"""Rasterize vector data. Get the cell value in defined grid of ref_raster
from its overlapped polygon.
Parameters
----------
src_vector: Geopandas.GeoDataFrame
Which vector data to... | 30,823 |
def wraplatex(text, width=WIDTH):
""" Wrap the text, for LaTeX, using ``textwrap`` module, and ``width``."""
return "$\n$".join(wrap(text, width=width)) | 30,824 |
def test_simple_sql(engine_testaccount):
"""
Simple SQL by SQLAlchemy
"""
result = engine_testaccount.execute('show databases')
rows = [row for row in result]
assert len(rows) >= 0, 'show database results' | 30,825 |
def register(request):
"""
Render and process a basic registration form.
"""
ctx = {}
if request.user.is_authenticated():
if "next" in request.GET:
return redirect(request.GET.get("next", 'control:index'))
return redirect('control:index')
if request.method == 'POST':
... | 30,826 |
def green_agg(robots: List[gs.Robot]) -> np.ndarray:
"""
This is a dummy aggregator function (for demonstration) that just saves
the value of each robot's green color channel
"""
out_arr = np.zeros([len(robots)])
for i, r in enumerate(robots):
out_arr[i] = r._color[1]
return out_arr | 30,827 |
def tcp_port_open_locally(port):
"""
Returns True if the given TCP port is open on the local machine
"""
sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
result = sock.connect_ex(("127.0.0.1", port))
return result == 0 | 30,828 |
def wrap(text, width=80):
"""
Wraps a string at a fixed width.
Arguments
---------
text : str
Text to be wrapped
width : int
Line width
Returns
-------
str
Wrapped string
"""
return "\n".join(
[text[i:i + width] for i in range(0, len(text), w... | 30,829 |
def parallel_vector(R, alt, max_alt=1e5):
"""
Generates a viewing and tangent vectors
parallel to the surface of a sphere
"""
if not hasattr(alt, '__len__'):
alt = np.array([alt])
viewer = np.zeros(shape=(3, len(alt)))
tangent = np.zeros_like(viewer)
viewer[0] = -(R+max_alt*2)
... | 30,830 |
def load_datasets(parser, args):
"""Loads the specified dataset from commandline arguments
Returns:
train_dataset, validation_dataset
"""
args = parser.parse_args()
dataset_kwargs = {
"root": Path(args.train_dir),
}
source_augmentations = Compose(
[globals()["_aug... | 30,831 |
def stock_total_deal_money():
"""
总成交量
:return:
"""
df = stock_zh_index_spot()
# 深证成指：sz399001，上证指数：sh00001
ds = df[(df['代码'] == 'sz399001') | (df['代码'] == 'sh000001')]
return ds['成交额'].sum() / 100000000 | 30,832 |
def reboot(WorkspaceId):
"""Reboot a specific AWS Workspace instance."""
client = aws()
console.log(
Panel('Attemptng reboot of workspaceId: ' + WorkspaceId,
title='INFO',
style=info_fmt))
response = client.reboot_workspaces(RebootWorkspaceRequests=[
{
... | 30,833 |
def _ls(dir=None, project=None, all=False, appendType=False, dereference=False, directoryOnly=False):
"""
Lists file(s) in specified MDSS directory.
:type dir: :obj:`str`
:param dir: MDSS directory path for which files are listed.
:type project: :obj:`str`
:param project: NCI project identi... | 30,834 |
def print_subs(valid_subs:list):
"""
Words of length 2
ab
ac
ca
Words of length 3
cab
"""
max_len = -1
for sub in valid_subs:
if len(sub) > max_len: max_len = len(sub)
output = [[] for _ in range(max_len)]
for sub in valid_subs: output[len(sub)-1].append(sub... | 30,835 |
def uploadMetadata(doi, current, delta, forceUpload=False, datacenter=None):
"""
Uploads citation metadata for the resource identified by an existing
scheme-less DOI identifier (e.g., "10.5060/FOO") to DataCite. This
same function can be used to overwrite previously-uploaded metadata.
'current' and 'delta'... | 30,836 |
def one_away(string_1: str, string_2: str)-> bool:
"""DP, classic edit distance
funny move, we calculate the LCS and then substract from the len() of the biggest string in O(n*m)
"""
if string_1 == string_2: return False
@lru_cache(maxsize=1024)
def dp(s_1, s_2, distance=0):
"""standard ... | 30,837 |
async def reset_alarm_panel(hass, cluster, entity_id):
"""Reset the state of the alarm panel."""
cluster.client_command.reset_mock()
await hass.services.async_call(
ALARM_DOMAIN,
"alarm_disarm",
{ATTR_ENTITY_ID: entity_id, "code": "4321"},
blocking=True,
)
await hass.... | 30,838 |
def test(net, loss_normalizer):
"""
Tests the Neural Network using IdProbNet on the test set.
Args:
net -- (IdProbNet instance)
loss_normalizer -- (Torch.Tensor) value to be divided from the loss
Returns:
3-tuple -- (Execution Time, End loss value,
Model's predictio... | 30,839 |
def scale_from_matrix(matrix):
"""Return scaling factor, origin and direction from scaling matrix.
"""
M = jnp.array(matrix, dtype=jnp.float64, copy=False)
M33 = M[:3, :3]
factor = jnp.trace(M33) - 2.0
try:
# direction: unit eigenvector corresponding to eigenvalue factor
w, V = jnp.linalg.eig(M33)
... | 30,840 |
def get_fort44_info(NDX, NDY, NATM, NMOL, NION, NSTRA, NCL, NPLS, NSTS, NLIM):
"""Collection of labels and dimensions for all fort.44 variables, as collected in the
SOLPS-ITER 2020 manual.
"""
fort44_info = {
"dab2": [r"Atom density ($m^{-3}$)", (NDX, NDY, NATM)],
"tab2": [r"Atom tempe... | 30,841 |
def lens2memnamegen_first50(nmems):
"""Generate the member names for LENS2 simulations
Input:
nmems = number of members
Output:
memstr(nmems) = an array containing nmems strings corresponding to the member names
"""
memstr=[]
for imem in range(0,nmems,1):
if (imem < 10)... | 30,842 |
def initialize_settings(tool_name, source_path, dest_file_name=None):
""" Creates settings directory and copies or merges the source to there.
In case source already exists, merge is done.
Destination file name is the source_path's file name unless dest_file_name
is given.
"""
settings_dir = os... | 30,843 |
def preprocess_output(fp_hdf_out, raw_timestamps, output, output_timestamps, average_window=1000, dataset_name='aligned'):
"""
Base file for preprocessing outputs (handles M-D case as of March2020).
For more complex cases use specialized functions (see for example preprocess_output in util.tetrode module)
... | 30,844 |
def landing_pg():
"""Landing page."""
landing = st.sidebar.selectbox("Welcome", ["Home", "Interactive"])
if landing == "Home":
landing_src()
else:
interactive() | 30,845 |
def test_list_boolean_length_nistxml_sv_iv_list_boolean_length_1_4(mode, save_output, output_format):
"""
Type list/boolean is restricted by facet length with value 5.
"""
assert_bindings(
schema="nistData/list/boolean/Schema+Instance/NISTSchema-SV-IV-list-boolean-length-1.xsd",
instance... | 30,846 |
def get_stopword_list(filename=stopword_filepath):
""" Get a list of stopword from a file """
with open(filename, 'r', encoding=encoding) as f:
stoplist = [line for line in f.read().splitlines()]
return stoplist | 30,847 |
def annotate(d, text='', filename='notes.txt'):
"""Create a file FILENAME in the directory D with contents TEXT."""
f = open(os.path.join(d, filename), 'w')
f.write(text)
f.close() | 30,848 |
def test_create_file_obj_deleted(new_dataset):
"""Test for the case where this file only exists in ancestor commits"""
hexsha = new_dataset.repo.repo.head.commit
new_dataset.remove('dataset_description.json')
tree = new_dataset.repo.repo.commit(hexsha).tree
assert create_file_obj(
new_datase... | 30,849 |
def append_composite_tensor(target, to_append):
"""Helper function to append composite tensors to each other in the 0 axis.
In order to support batching within a fit/evaluate/predict call, we need
to be able to aggregate within a CompositeTensor. Unfortunately, the CT
API currently does not make this easy... | 30,850 |
def check_index(ind, dimension):
"""Check validity of index for a given dimension
Examples
--------
>>> check_index(3, 5)
>>> check_index(5, 5)
Traceback (most recent call last):
...
IndexError: Index is not smaller than dimension 5 >= 5
>>> check_index(6, 5)
Traceback (most rece... | 30,851 |
def to_text(value):
"""Convert an opcode to text.
*value*, an ``int`` the opcode value,
Raises ``dns.opcode.UnknownOpcode`` if the opcode is unknown.
Returns a ``str``.
"""
return Opcode.to_text(value) | 30,852 |
def prompt_merge(target_path,
additional_uris,
additional_specs,
path_change_message=None,
merge_strategy='KillAppend',
confirmed=False,
confirm=False,
show_advanced=True,
show_verbosi... | 30,853 |
def _demo_mm_inputs(input_shape, num_classes):
"""Create a superset of inputs needed to run test or train batches.
Args:
input_shape (tuple):
input batch dimensions
num_classes (int):
number of semantic classes
"""
(N, C, H, W) = input_shape
rng = np.random.R... | 30,854 |
def clean_vm(root):
"""Remove vagrant VM from specified path"""
v = vagrant.Vagrant(root=root)
print(" - Cleanig VM ", root)
try:
v.destroy()
except Exception as err:
print(err)
try:
os.remove(root + "/Vagrantfile")
except FileNotFoundError:
pass | 30,855 |
def get_ephemeral_port(sock_family=socket.AF_INET, sock_type=socket.SOCK_STREAM):
"""Return an ostensibly available ephemeral port number."""
# We expect that the operating system is polite enough to not hand out the
# same ephemeral port before we can explicitly bind it a second time.
s = socket.socket... | 30,856 |
def iterMergesort(list_of_lists, key=None):
# Based on http://code.activestate.com/recipes/511509-n-way-merge-sort/
# from Mike Klaas
""" Perform an N-way merge operation on sorted lists.
@param list_of_lists: (really iterable of iterable) of sorted elements
(either by naturally or by C{key})... | 30,857 |
def main():
"""
Let this thing fly
"""
args = get_args()
# connect this thing
si = vmware_lib.connect(args.host, args.user, args.password, args.port, args.insecure)
content = si.RetrieveContent()
vm_object = None
if args.template_folder:
folder = vmware_lib.get_obj(content... | 30,858 |
def tear_down():
"""
tear down test environment
"""
# destroy test database
from django.db import connection
connection.creation.destroy_test_db("not_needed")
# teardown environment
from django.test.utils import teardown_test_environment
teardown_test_environment() | 30,859 |
def IR_guess_model(spectrum: ConvSpectrum, peak_args: Optional[dict] = None) -> tuple[Model, dict]:
"""
Guess a fit for the IR spectrum based on its peaks.
:param spectrum: the ConvSpectrum to be fit
:param peak_args: arguments for finding peaks
:return: Model, parameters
"""
min_intensity,... | 30,860 |
def virus_monte_carlo(initial_infected, population, k):
""" Generates a list of points to which some is infected
at a given value k starting with initial_infected infected.
There is no mechanism to stop the infection from reaching
the entire population.
:param initial_infected: The amount of people... | 30,861 |
def threadsafe_generator(f):
"""
A decorator that takes a generator function and makes it thread-safe.
"""
def g(*a, **kw):
return threadsafe_iter(f(*a, **kw))
return g | 30,862 |
def test_heirarchical_data(heirarchical_data_structure, settings_number_of_columns_5):
"""Testing that heirarchical data can be handled by VMC (even though this is NOT recommended"""
instance = EvenVMCView()
rows = instance.process_entries(heirarchical_data_structure)
for row in range(len(rows) - 1):
... | 30,863 |
def lastmsg(self):
"""
Return last logged message if **_lastmsg** attribute is available.
Returns:
last massage or empty str
"""
return getattr(self, '_last_message', '') | 30,864 |
def _callback_on_all_dict_keys(dt, callback_fn):
"""
Callback callback_fn on all dictionary keys recursively
"""
result = {}
for (key, val) in dt.items():
if type(val) == dict:
val = _callback_on_all_dict_keys(val, callback_fn)
result[callback_fn(key)] = val
return re... | 30,865 |
def ovb_partial_r2_bound(model=None, treatment=None, r2dxj_x=None, r2yxj_dx=None,
benchmark_covariates=None, kd=1, ky=None):
"""
Provide a Pandas DataFrame with the bounds on the strength of the unobserved confounder.
Adjusted estimates, standard errors and t-values (among other qu... | 30,866 |
def top_ngrams(df, n=2, ngrams=10):
"""
* Not generalizable in this form *
* This works well, but is very inefficient and should be optimized or rewritten *
Takes a preposcessed, tokenized column and create a large list.
Returns most frequent ngrams
Arguments:
df = name of DataFrame wit... | 30,867 |
def install_openvpn(instance, arg, verbose=True):
""" """
install(instance, {"module":"openvpn"}, verbose=True)
generate_dh_key(instance, {"dh_name":"openvpn", "key_size":"2048"})
server_conf = open("simulation/workstations/"+instance.name+"/server_openvpn.conf", "w")
server_conf.write("port 1... | 30,868 |
def filter_params(module: Module, train_bn: bool = True) -> Generator:
"""Yields the trainable parameters of a given module.
Args:
module: A given module
train_bn: If True, leave the BatchNorm layers in training mode
Returns:
Generator
"""
children = list(module.children())... | 30,869 |
def rossoporn_parse(driver: webdriver.Firefox) -> tuple[list[str], int, str]:
"""Read the html for rossoporn.com"""
#Parses the html of the site
soup = soupify(driver)
dir_name = soup.find("div", class_="content_right").find("h1").text
dir_name = clean_dir_name(dir_name)
images = soup.find_all("... | 30,870 |
def pid_from_context(_, context, **kwargs):
"""Get PID from marshmallow context."""
pid = (context or {}).get('pid')
return pid.pid_value if pid else missing | 30,871 |
def score_text(text, tokenizer, preset_model, finetuned_model):
""" Uses rule-based rankings. Higher is better, but different features have different scales.
Args:
text (str/ List[str]): one story to rank.
tokenizer (Pytroch tokenizer): GPT2 Byte Tokenizer.
preset_model (Pytorch model)... | 30,872 |
def get_bot_list(swarming_server, dimensions, dead_only):
"""Returns a list of swarming bots."""
cmd = [
sys.executable, 'swarming.py', 'bots',
'--swarming', swarming_server,
'--bare',
]
for k, v in sorted(dimensions.iteritems()):
cmd.extend(('--dimension', k, v))
if dead_only:
cmd.append(... | 30,873 |
def running_on_kaggle() -> bool:
"""Detect if the current environment is running on Kaggle.
Returns:
bool:
True if the current environment is on Kaggle, False
otherwise.
"""
return os.environ.get("KAGGLE_KERNEL_RUN_TYPE") == "Interactive" | 30,874 |
def _get_picture_from_attachments(path):
"""Get picture bytes from telegram server"""
url = 'https://api.telegram.org/file/bot' + API_TOKEN + '/' + path
pic_path = './photos/pic.jpg'
curl_command = f'curl {url} > {pic_path}'
data = subprocess.run(curl_command, shell=True)
if data.returncode !... | 30,875 |
def parse_cards(account_page_content):
"""
Parse card metadata and product balances from /ClipperCard/dashboard.jsf
"""
begin = account_page_content.index(b'<!--YOUR CLIPPER CARDS-->')
end = account_page_content.index(b'<!--END YOUR CLIPPER CARDS-->')
card_soup = bs4.BeautifulSoup(account_page_c... | 30,876 |
def __setitem__(x, key, value, /):
"""
Note: __setitem__ is a method of the array object.
"""
pass | 30,877 |
def interaction_time_data_string(logs, title):
"""
times = utils.valid_values_for_enum((models.LogEntry.TIME_CHOICES))
contexts_map = dict(models.LogEntry.TIME_CHOICES)
counts = {contexts_map[k]: v
for k, v in _counts_by_getter(logs, lambda l: l.time_of_day).items()
}... | 30,878 |
def main() -> None:
"""
Load the data from a csv file and insert it into a MongoDB database.
"""
import json
with open("script_constants.json", "r") as file:
constants = json.load(file)
pokemon_data_filename = constants["Pokemon_data_filename"]
pokemon = extract_data_from_csv(pokemo... | 30,879 |
def _label_boost(boost_form, label):
"""Returns the label boost.
Args:
boost_form: Either NDCG or PRECISION.
label: The example label.
Returns:
A list of per list weight.
"""
boost = {
'NDCG': math.pow(2.0, label) - 1.0,
'PRECISION': 1.0 if label >= 1.0 else 0.0,
}
return boost[b... | 30,880 |
def iterate_orthologous_lexical_matches(prefix) -> Iterable[MappingTuple]:
"""Generate orthologous relations between lexical matches from different species."""
names = pyobo.get_id_name_mapping(prefix)
species = pyobo.get_id_species_mapping(prefix)
provenance = get_script_url(__file__)
count = 0
... | 30,881 |
def has_matching_ts_templates(reactant, bond_rearr):
"""
See if there are any templates suitable to get a TS guess from a template
Arguments:
reactant (autode.complex.ReactantComplex):
bond_rearr (autode.bond_rearrangement.BondRearrangement):
Returns:
bool:
"""
mol_gra... | 30,882 |
def get_commands(xml: objectify.ObjectifiedElement):
"""
Returns an action and the room from the xml string.
:param xml:
:return:
"""
return xml.body.attrib["action"] | 30,883 |
def compression_point(w_db, slope = 1, compression = 1,
extrapolation_point = None, axis = -1):
"""Return input referred compression point"""
interpol_line = calc_extrapolation_line(w_db, slope, extrapolation_point,
axis)
return cross(interp... | 30,884 |
def main():
"""
calculates a hilbert pseudocurve of p iterations.
Scale the pseudocurve to match the desired image.
Move along the curve and sample image and to get average color at each segment
Output gcode corresponding the coordinates and scaled Z levels.
If no image is given, a flat hilbert... | 30,885 |
def pattern_remove_incomplete_region_or_spatial_path(
perception_graph: PerceptionGraphPattern
) -> PerceptionGraphPattern:
"""
Helper function to return a `PerceptionGraphPattern` verifying
that region and spatial path perceptions contain a reference object.
"""
graph = perception_graph.copy_as... | 30,886 |
def test_multiplication():
"""test multiplication (f*g) for both value and derivative"""
assert f_5.get()[0] == f.get()[0] * g.get()[0]
assert f_5.get()[1] == f.get()[0] * g.get()[1] + f.get()[1] * g.get()[0]
"""test multiplication (g*f) for both value and derivative"""
assert f_6.get()[0] == g.get(... | 30,887 |
def other_shifted_bottleneck_distance(A, B, fudge=default_fudge, analysis=False):
"""Compute the shifted bottleneck distance between two diagrams, A and B (multisets)"""
A = pu.SaneCounter(A)
B = pu.SaneCounter(B)
if not A and not B:
return 0
radius = fudge(upper_bound_on_radius(A, B))
e... | 30,888 |
def getCountdown(c):
"""
Parse into a Friendly Readable format for Humans
"""
days = c.days
c = c.total_seconds()
hours = round(c//3600)
minutes = round(c // 60 - hours * 60)
seconds = round(c - hours * 3600 - minutes * 60)
return days, hours, minutes, seconds | 30,889 |
def from_aiida_type(x):
"""Turn Aiida types into their corresponding native Python types."""
raise TypeError(f"Do not know how to convert {type(x)} to native Python type") | 30,890 |
def fromPSK(valstr):
"""A special version of fromStr that assumes the user is trying to set a PSK.
In that case we also allow "none", "default" or "random" (to have python generate one), or simpleN
"""
if valstr == "random":
return genPSK256()
elif valstr == "none":
return bytes([0])... | 30,891 |
def init_app(_):
"""Initializes backend""" | 30,892 |
def get_subpackages(name):
"""Return subpackages of package *name*"""
splist = []
for dirpath, _dirnames, _filenames in os.walk(name):
if osp.isfile(osp.join(dirpath, "__init__.py")):
splist.append(".".join(dirpath.split(os.sep)))
return splist | 30,893 |
def list_hierarchy(class_name, bases):
"""
Creates a list of the class hierarchy
Args:
-----
class_name: name of the current class
bases: list/tuple of bases for the current class
"""
class_list = [Uri(class_name)]
for base in bases:
if base.__name__ not in IGNORE_C... | 30,894 |
def output_mesh(mesh, config):
"""Outputs mesh in formats specified in config.
:param mesh MeshInfo: tetrahedral mesh.
:param config Config: configuration for mesh build.
"""
if not config.output_format:
return
logger.info('Outputting mesh in formats: {}'
.format(', '.join(config... | 30,895 |
def move_mouse_to_specific_location(x_coordinate, y_coordinate):
"""Moves the mouse to a specific point"""
LOGGER.debug("Moving mouse to (%d,%d)", x_coordinate, y_coordinate)
pyautogui.moveTo(x_coordinate, y_coordinate)
return Promise.resolve((x_coordinate, y_coordinate)) | 30,896 |
def rss():
"""Return ps -o rss (resident) memory in kB."""
return float(mem("rss")) / 1024 | 30,897 |
def load_pickle_file(filename):
"""Read a pickle file, return a generator"""
with open(filename, "rb") as f:
while True:
try:
yield pickle.load(f)
except EOFError:
break | 30,898 |
def compare_words(
word1_features,
word2_features,
count=10,
exclude=set(),
similarity_degree=0.5,
separate=False,
min_feature_value=0.3
):
"""
Сравнение двух слов на основе списка похожих (или вообще каких-либо фич слова).
Возвращает 3 списка: характерные для первог... | 30,899 |
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