_id stringlengths 2 7 | title stringlengths 1 88 | partition stringclasses 3
values | text stringlengths 75 19.8k | language stringclasses 1
value | meta_information dict |
|---|---|---|---|---|---|
q233200 | to_ds9_meta | train | def to_ds9_meta(shape_meta):
"""
Makes the meta data DS9 compatible by filtering and mapping the valid keys
Parameters
----------
shape_meta: dict
meta attribute of a `regions.Shape` object
Returns
-------
meta : dict
DS9 compatible meta dictionary
"""
# meta k... | python | {
"resource": ""
} |
q233201 | _to_io_meta | train | def _to_io_meta(shape_meta, valid_keys, key_mappings):
"""
This is used to make meta data compatible with a specific io
by filtering and mapping to it's valid keys
Parameters
----------
shape_meta: dict
meta attribute of a `regions.Region` object
valid_keys : python list
Con... | python | {
"resource": ""
} |
q233202 | Shape.convert_coords | train | def convert_coords(self):
"""
Process list of coordinates
This mainly searches for tuple of coordinates in the coordinate list and
creates a SkyCoord or PixCoord object from them if appropriate for a
given region type. This involves again some coordinate transformation,
... | python | {
"resource": ""
} |
q233203 | Shape._convert_sky_coords | train | def _convert_sky_coords(self):
"""
Convert to sky coordinates
"""
parsed_angles = [(x, y)
for x, y in zip(self.coord[:-1:2], self.coord[1::2])
if (isinstance(x, coordinates.Angle) and isinstance(y, coordinates.Angle))
... | python | {
"resource": ""
} |
q233204 | Shape._convert_pix_coords | train | def _convert_pix_coords(self):
"""
Convert to pixel coordinates, `regions.PixCoord`
"""
if self.region_type in ['polygon', 'line']:
# have to special-case polygon in the phys coord case
# b/c can't typecheck when iterating as in sky coord case
coords =... | python | {
"resource": ""
} |
q233205 | Shape.to_region | train | def to_region(self):
"""
Converts to region, ``regions.Region`` object
"""
coords = self.convert_coords()
log.debug(coords)
viz_keywords = ['color', 'dash', 'dashlist', 'width', 'font', 'symsize',
'symbol', 'symsize', 'fontsize', 'fontstyle', 'use... | python | {
"resource": ""
} |
q233206 | Shape.check_crtf | train | def check_crtf(self):
"""
Checks for CRTF compatibility.
"""
if self.region_type not in regions_attributes:
raise ValueError("'{0}' is not a valid region type in this package"
"supported by CRTF".format(self.region_type))
if self.coordsys... | python | {
"resource": ""
} |
q233207 | Shape.check_ds9 | train | def check_ds9(self):
"""
Checks for DS9 compatibility.
"""
if self.region_type not in regions_attributes:
raise ValueError("'{0}' is not a valid region type in this package"
"supported by DS9".format(self.region_type))
if self.coordsys no... | python | {
"resource": ""
} |
q233208 | Shape._validate | train | def _validate(self):
"""
Checks whether all the attributes of this object is valid.
"""
if self.region_type not in regions_attributes:
raise ValueError("'{0}' is not a valid region type in this package"
.format(self.region_type))
if self.... | python | {
"resource": ""
} |
q233209 | read_crtf | train | def read_crtf(filename, errors='strict'):
"""
Reads a CRTF region file and returns a list of region objects.
Parameters
----------
filename : `str`
The file path
errors : ``warn``, ``ignore``, ``strict``, optional
The error handling scheme to use for handling parsing errors.
... | python | {
"resource": ""
} |
q233210 | CRTFParser.parse_line | train | def parse_line(self, line):
"""
Parses a single line.
"""
# Skip blanks
if line == '':
return
# Skip comments
if regex_comment.search(line):
return
# Special case / header: parse global parameters into metadata
global_par... | python | {
"resource": ""
} |
q233211 | CRTFRegionParser.parse | train | def parse(self):
"""
Starting point to parse the CRTF region string.
"""
self.convert_meta()
self.coordsys = self.meta.get('coord', 'image').lower()
self.set_coordsys()
self.convert_coordinates()
self.make_shape() | python | {
"resource": ""
} |
q233212 | CRTFRegionParser.set_coordsys | train | def set_coordsys(self):
"""
Mapping to astropy's coordinate system name
# TODO: needs expert attention (Most reference systems are not mapped)
"""
if self.coordsys.lower() in self.coordsys_mapping:
self.coordsys = self.coordsys_mapping[self.coordsys.lower()] | python | {
"resource": ""
} |
q233213 | CRTFRegionParser.convert_coordinates | train | def convert_coordinates(self):
"""
Convert coordinate string to `~astropy.coordinates.Angle` or `~astropy.units.quantity.Quantity` objects
"""
coord_list_str = regex_coordinate.findall(self.reg_str) + regex_length.findall(self.reg_str)
coord_list = []
if self.region_type... | python | {
"resource": ""
} |
q233214 | CRTFRegionParser.convert_meta | train | def convert_meta(self):
"""
Parses the meta_str to python dictionary and stores in ``meta`` attribute.
"""
if self.meta_str:
self.meta_str = regex_meta.findall(self.meta_str + ',')
if self.meta_str:
for par in self.meta_str:
if par[0] is no... | python | {
"resource": ""
} |
q233215 | fits_region_objects_to_table | train | def fits_region_objects_to_table(regions):
"""
Converts list of regions to FITS region table.
Parameters
----------
regions : list
List of `regions.Region` objects
Returns
-------
region_string : `~astropy.table.Table`
FITS region table
Examples
--------
>... | python | {
"resource": ""
} |
q233216 | write_fits_region | train | def write_fits_region(filename, regions, header=None):
"""
Converts list of regions to FITS region table and write to a file.
Parameters
----------
filename: str
Filename in which the table is to be written. Default is 'new.fits'
regions: list
List of `regions.Region` objects
... | python | {
"resource": ""
} |
q233217 | make_example_dataset | train | def make_example_dataset(data='simulated', config=None):
"""Make example dataset.
This is a factory function for ``ExampleDataset`` objects.
The following config options are available (default values shown):
* ``crval = 0, 0``
* ``crpix = 180, 90``
* ``cdelt = -1, 1``
* ``shape = 180, 360... | python | {
"resource": ""
} |
q233218 | _table_to_bintable | train | def _table_to_bintable(table):
"""Convert `~astropy.table.Table` to `astropy.io.fits.BinTable`."""
data = table.as_array()
header = fits.Header()
header.update(table.meta)
name = table.meta.pop('name', None)
return fits.BinTableHDU(data, header, name=name) | python | {
"resource": ""
} |
q233219 | read_ds9 | train | def read_ds9(filename, errors='strict'):
"""
Read a DS9 region file in as a `list` of `~regions.Region` objects.
Parameters
----------
filename : `str`
The file path
errors : ``warn``, ``ignore``, ``strict``, optional
The error handling scheme to use for handling parsing errors.
... | python | {
"resource": ""
} |
q233220 | DS9Parser.set_coordsys | train | def set_coordsys(self, coordsys):
"""
Transform coordinate system
# TODO: needs expert attention
"""
if coordsys in self.coordsys_mapping:
self.coordsys = self.coordsys_mapping[coordsys]
else:
self.coordsys = coordsys | python | {
"resource": ""
} |
q233221 | DS9Parser.run | train | def run(self):
"""
Run all steps
"""
for line_ in self.region_string.split('\n'):
for line in line_.split(";"):
self.parse_line(line)
log.debug('Global state: {}'.format(self)) | python | {
"resource": ""
} |
q233222 | DS9Parser.parse_meta | train | def parse_meta(meta_str):
"""
Parse the metadata for a single ds9 region string.
Parameters
----------
meta_str : `str`
Meta string, the metadata is everything after the close-paren of the
region coordinate specification. All metadata is specified as
... | python | {
"resource": ""
} |
q233223 | DS9Parser.parse_region | train | def parse_region(self, include, region_type, region_end, line):
"""
Extract a Shape from a region string
"""
if self.coordsys is None:
raise DS9RegionParserError("No coordinate system specified and a"
" region has been found.")
e... | python | {
"resource": ""
} |
q233224 | DS9RegionParser.parse | train | def parse(self):
"""
Convert line to shape object
"""
log.debug(self)
self.parse_composite()
self.split_line()
self.convert_coordinates()
self.convert_meta()
self.make_shape()
log.debug(self) | python | {
"resource": ""
} |
q233225 | DS9RegionParser.split_line | train | def split_line(self):
"""
Split line into coordinates and meta string
"""
# coordinate of the # symbol or end of the line (-1) if not found
hash_or_end = self.line.find("#")
temp = self.line[self.region_end:hash_or_end].strip(" |")
self.coord_str = regex_paren.sub... | python | {
"resource": ""
} |
q233226 | DS9RegionParser.convert_coordinates | train | def convert_coordinates(self):
"""
Convert coordinate string to objects
"""
coord_list = []
# strip out "null" elements, i.e. ''. It might be possible to eliminate
# these some other way, i.e. with regex directly, but I don't know how.
# We need to copy in order ... | python | {
"resource": ""
} |
q233227 | DS9RegionParser.convert_meta | train | def convert_meta(self):
"""
Convert meta string to dict
"""
meta_ = DS9Parser.parse_meta(self.meta_str)
self.meta = copy.deepcopy(self.global_meta)
self.meta.update(meta_)
# the 'include' is not part of the metadata string;
# it is pre-parsed as part of th... | python | {
"resource": ""
} |
q233228 | PixCoord._validate | train | def _validate(val, name, expected='any'):
"""Validate that a given object is an appropriate `PixCoord`.
This is used for input validation throughout the regions package,
especially in the `__init__` method of pixel region classes.
Parameters
----------
val : `PixCoord`
... | python | {
"resource": ""
} |
q233229 | PixCoord.to_sky | train | def to_sky(self, wcs, origin=_DEFAULT_WCS_ORIGIN, mode=_DEFAULT_WCS_MODE):
"""Convert this `PixCoord` to `~astropy.coordinates.SkyCoord`.
Calls :meth:`astropy.coordinates.SkyCoord.from_pixel`.
See parameter description there.
"""
return SkyCoord.from_pixel(
xp=self.x... | python | {
"resource": ""
} |
q233230 | PixCoord.from_sky | train | def from_sky(cls, skycoord, wcs, origin=_DEFAULT_WCS_ORIGIN, mode=_DEFAULT_WCS_MODE):
"""Create `PixCoord` from `~astropy.coordinates.SkyCoord`.
Calls :meth:`astropy.coordinates.SkyCoord.to_pixel`.
See parameter description there.
"""
x, y = skycoord.to_pixel(wcs=wcs, origin=ori... | python | {
"resource": ""
} |
q233231 | PixCoord.separation | train | def separation(self, other):
r"""Separation to another pixel coordinate.
This is the two-dimensional cartesian separation :math:`d` with
.. math::
d = \sqrt{(x_1 - x_2) ^ 2 + (y_1 - y_2) ^ 2}
Parameters
----------
other : `PixCoord`
Other pixel ... | python | {
"resource": ""
} |
q233232 | skycoord_to_pixel_scale_angle | train | def skycoord_to_pixel_scale_angle(skycoord, wcs, small_offset=1 * u.arcsec):
"""
Convert a set of SkyCoord coordinates into pixel coordinates, pixel
scales, and position angles.
Parameters
----------
skycoord : `~astropy.coordinates.SkyCoord`
Sky coordinates
wcs : `~astropy.wcs.WCS`... | python | {
"resource": ""
} |
q233233 | assert_angle | train | def assert_angle(name, q):
"""
Check that ``q`` is an angular `~astropy.units.Quantity`.
"""
if isinstance(q, u.Quantity):
if q.unit.physical_type == 'angle':
pass
else:
raise ValueError("{0} should have angular units".format(name))
else:
raise TypeErr... | python | {
"resource": ""
} |
q233234 | _silence | train | def _silence():
"""A context manager that silences sys.stdout and sys.stderr."""
old_stdout = sys.stdout
old_stderr = sys.stderr
sys.stdout = _DummyFile()
sys.stderr = _DummyFile()
exception_occurred = False
try:
yield
except:
exception_occurred = True
# Go ahead... | python | {
"resource": ""
} |
q233235 | use_astropy_helpers | train | def use_astropy_helpers(**kwargs):
"""
Ensure that the `astropy_helpers` module is available and is importable.
This supports automatic submodule initialization if astropy_helpers is
included in a project as a git submodule, or will download it from PyPI if
necessary.
Parameters
----------
... | python | {
"resource": ""
} |
q233236 | _Bootstrapper.config | train | def config(self):
"""
A `dict` containing the options this `_Bootstrapper` was configured
with.
"""
return dict((optname, getattr(self, optname))
for optname, _ in CFG_OPTIONS if hasattr(self, optname)) | python | {
"resource": ""
} |
q233237 | _Bootstrapper.get_local_directory_dist | train | def get_local_directory_dist(self):
"""
Handle importing a vendored package from a subdirectory of the source
distribution.
"""
if not os.path.isdir(self.path):
return
log.info('Attempting to import astropy_helpers from {0} {1!r}'.format(
's... | python | {
"resource": ""
} |
q233238 | _Bootstrapper.get_local_file_dist | train | def get_local_file_dist(self):
"""
Handle importing from a source archive; this also uses setup_requires
but points easy_install directly to the source archive.
"""
if not os.path.isfile(self.path):
return
log.info('Attempting to unpack and import astropy_he... | python | {
"resource": ""
} |
q233239 | _Bootstrapper._directory_import | train | def _directory_import(self):
"""
Import astropy_helpers from the given path, which will be added to
sys.path.
Must return True if the import succeeded, and False otherwise.
"""
# Return True on success, False on failure but download is allowed, and
# otherwise r... | python | {
"resource": ""
} |
q233240 | _Bootstrapper._check_submodule | train | def _check_submodule(self):
"""
Check if the given path is a git submodule.
See the docstrings for ``_check_submodule_using_git`` and
``_check_submodule_no_git`` for further details.
"""
if (self.path is None or
(os.path.exists(self.path) and not os.path... | python | {
"resource": ""
} |
q233241 | sdot | train | def sdot( U, V ):
'''
Computes the tensorproduct reducing last dimensoin of U with first dimension of V.
For matrices, it is equal to regular matrix product.
'''
nu = U.ndim
#nv = V.ndim
return np.tensordot( U, V, axes=(nu-1,0) ) | python | {
"resource": ""
} |
q233242 | SmolyakBasic.set_values | train | def set_values(self,x):
""" Updates self.theta parameter. No returns values"""
x = numpy.atleast_2d(x)
x = x.real # ahem
C_inv = self.__C_inv__
theta = numpy.dot( x, C_inv )
self.theta = theta
return theta | python | {
"resource": ""
} |
q233243 | tauchen | train | def tauchen(N, mu, rho, sigma, m=2):
"""
Approximate an AR1 process by a finite markov chain using Tauchen's method.
:param N: scalar, number of nodes for Z
:param mu: scalar, unconditional mean of process
:param rho: scalar
:param sigma: scalar, std. dev. of epsilons
:param m: max +- std. ... | python | {
"resource": ""
} |
q233244 | rouwenhorst | train | def rouwenhorst(rho, sigma, N):
"""
Approximate an AR1 process by a finite markov chain using Rouwenhorst's method.
:param rho: autocorrelation of the AR1 process
:param sigma: conditional standard deviation of the AR1 process
:param N: number of states
:return [nodes, P]: equally spaced nodes ... | python | {
"resource": ""
} |
q233245 | tensor_markov | train | def tensor_markov( *args ):
"""Computes the product of two independent markov chains.
:param m1: a tuple containing the nodes and the transition matrix of the first chain
:param m2: a tuple containing the nodes and the transition matrix of the second chain
:return: a tuple containing the nodes and the ... | python | {
"resource": ""
} |
q233246 | dynare_import | train | def dynare_import(filename,full_output=False, debug=False):
'''Imports model defined in specified file'''
import os
basename = os.path.basename(filename)
fname = re.compile('(.*)\.(.*)').match(basename).group(1)
f = open(filename)
txt = f.read()
model = parse_dynare_text(txt,full_output=full... | python | {
"resource": ""
} |
q233247 | _shocks_to_epsilons | train | def _shocks_to_epsilons(model, shocks, T):
"""
Helper function to support input argument `shocks` being one of many
different data types. Will always return a `T, n_e` matrix.
"""
n_e = len(model.calibration['exogenous'])
# if we have a DataFrame, convert it to a dict and rely on the method bel... | python | {
"resource": ""
} |
q233248 | clear_all | train | def clear_all():
"""
Clears all parameters, variables, and shocks defined previously
"""
frame = inspect.currentframe().f_back
try:
if frame.f_globals.get('variables_order'):
# we should avoid to declare symbols twice !
del frame.f_globals['variables_order']
... | python | {
"resource": ""
} |
q233249 | nonlinear_system | train | def nonlinear_system(model, initial_dr=None, maxit=10, tol=1e-8, grid={}, distribution={}, verbose=True):
'''
Finds a global solution for ``model`` by solving one large system of equations
using a simple newton algorithm.
Parameters
----------
model: NumericModel
"dtcscc" model to be ... | python | {
"resource": ""
} |
q233250 | gauss_hermite_nodes | train | def gauss_hermite_nodes(orders, sigma, mu=None):
'''
Computes the weights and nodes for Gauss Hermite quadrature.
Parameters
----------
orders : int, list, array
The order of integration used in the quadrature routine
sigma : array-like
If one dimensional, the variance of the no... | python | {
"resource": ""
} |
q233251 | newton | train | def newton(f, x, verbose=False, tol=1e-6, maxit=5, jactype='serial'):
"""Solve nonlinear system using safeguarded Newton iterations
Parameters
----------
Return
------
"""
if verbose:
print = lambda txt: old_print(txt)
else:
print = lambda txt: None
it = 0
e... | python | {
"resource": ""
} |
q233252 | qzordered | train | def qzordered(A,B,crit=1.0):
"Eigenvalues bigger than crit are sorted in the top-left."
TOL = 1e-10
def select(alpha, beta):
return alpha**2>crit*beta**2
[S,T,alpha,beta,U,V] = ordqz(A,B,output='real',sort=select)
eigval = abs(numpy.diag(S)/numpy.diag(T))
return [S,T,U,V,eigval] | python | {
"resource": ""
} |
q233253 | ordqz | train | def ordqz(A, B, sort='lhp', output='real', overwrite_a=False,
overwrite_b=False, check_finite=True):
"""
QZ decomposition for a pair of matrices with reordering.
.. versionadded:: 0.17.0
Parameters
----------
A : (N, N) array_like
2d array to decompose
B : (N, N) array_li... | python | {
"resource": ""
} |
q233254 | parameterized_expectations_direct | train | def parameterized_expectations_direct(model, verbose=False, initial_dr=None,
pert_order=1, grid={}, distribution={},
maxit=100, tol=1e-8):
'''
Finds a global solution for ``model`` using parameterized expectations
function. Requires... | python | {
"resource": ""
} |
q233255 | numdiff | train | def numdiff(fun, args):
"""Vectorized numerical differentiation"""
# vectorized version
epsilon = 1e-8
args = list(args)
v0 = fun(*args)
N = v0.shape[0]
l_v = len(v0)
dvs = []
for i, a in enumerate(args):
l_a = (a).shape[1]
dv = numpy.zeros((N, l_v, l_a))
na... | python | {
"resource": ""
} |
q233256 | bandpass_filter | train | def bandpass_filter(data, k, w1, w2):
"""
This function will apply a bandpass filter to data. It will be kth
order and will select the band between w1 and w2.
Parameters
----------
data: array, dtype=float
The data you wish to filter
k: number, int
The order ... | python | {
"resource": ""
} |
q233257 | dprint | train | def dprint(s):
'''Prints `s` with additional debugging informations'''
import inspect
frameinfo = inspect.stack()[1]
callerframe = frameinfo.frame
d = callerframe.f_locals
if (isinstance(s,str)):
val = eval(s, d)
else:
val = s
cc = frameinfo.code_context[0]
... | python | {
"resource": ""
} |
q233258 | non_decreasing_series | train | def non_decreasing_series(n, size):
'''Lists all combinations of 0,...,n-1 in increasing order'''
if size == 1:
return [[a] for a in range(n)]
else:
lc = non_decreasing_series(n, size-1)
ll = []
for l in lc:
last = l[-1]
for i in range(last, n):
... | python | {
"resource": ""
} |
q233259 | higher_order_diff | train | def higher_order_diff(eqs, syms, order=2):
'''Takes higher order derivatives of a list of equations w.r.t a list of paramters'''
import numpy
eqs = list([sympy.sympify(eq) for eq in eqs])
syms = list([sympy.sympify(s) for s in syms])
neq = len(eqs)
p = len(syms)
D = [numpy.array(eqs)]
... | python | {
"resource": ""
} |
q233260 | get_ranked_players | train | def get_ranked_players():
"""Get the list of the first 100 ranked players."""
rankings_page = requests.get(RANKINGS_URL)
root = etree.HTML(rankings_page.text)
player_rows = root.xpath('//div[@id="ranked"]//tr')
for row in player_rows[1:]:
player_row = row.xpath('td[@class!="country"]//text... | python | {
"resource": ""
} |
q233261 | Rank.difference | train | def difference(cls, first, second):
"""Tells the numerical difference between two ranks."""
# so we always get a Rank instance even if string were passed in
first, second = cls(first), cls(second)
rank_list = list(cls)
return abs(rank_list.index(first) - rank_list.index(second)) | python | {
"resource": ""
} |
q233262 | _CardMeta.make_random | train | def make_random(cls):
"""Returns a random Card instance."""
self = object.__new__(cls)
self.rank = Rank.make_random()
self.suit = Suit.make_random()
return self | python | {
"resource": ""
} |
q233263 | twoplustwo_player | train | def twoplustwo_player(username):
"""Get profile information about a Two plus Two Forum member given the username."""
from .website.twoplustwo import ForumMember, AmbiguousUserNameError, UserNotFoundError
try:
member = ForumMember(username)
except UserNotFoundError:
raise click.ClickExc... | python | {
"resource": ""
} |
q233264 | p5list | train | def p5list(num):
"""List pocketfives ranked players, max 100 if no NUM, or NUM if specified."""
from .website.pocketfives import get_ranked_players
format_str = '{:>4.4} {!s:<15.13}{!s:<18.15}{!s:<9.6}{!s:<10.7}'\
'{!s:<14.11}{!s:<12.9}{!s:<12.9}{!s:<12.9}{!s:<4.4}'
click.echo(form... | python | {
"resource": ""
} |
q233265 | psstatus | train | def psstatus():
"""Shows PokerStars status such as number of players, tournaments."""
from .website.pokerstars import get_status
_print_header('PokerStars status')
status = get_status()
_print_values(
('Info updated', status.updated),
('Tables', status.tables),
('Players', ... | python | {
"resource": ""
} |
q233266 | Notes.notes | train | def notes(self):
"""Tuple of notes.."""
return tuple(self._get_note_data(note) for note in self.root.iter('note')) | python | {
"resource": ""
} |
q233267 | Notes.labels | train | def labels(self):
"""Tuple of labels."""
return tuple(_Label(label.get('id'), label.get('color'), label.text) for label
in self.root.iter('label')) | python | {
"resource": ""
} |
q233268 | Notes.add_note | train | def add_note(self, player, text, label=None, update=None):
"""Add a note to the xml. If update param is None, it will be the current time."""
if label is not None and (label not in self.label_names):
raise LabelNotFoundError('Invalid label: {}'.format(label))
if update is None:
... | python | {
"resource": ""
} |
q233269 | Notes.append_note | train | def append_note(self, player, text):
"""Append text to an already existing note."""
note = self._find_note(player)
note.text += text | python | {
"resource": ""
} |
q233270 | Notes.prepend_note | train | def prepend_note(self, player, text):
"""Prepend text to an already existing note."""
note = self._find_note(player)
note.text = text + note.text | python | {
"resource": ""
} |
q233271 | Notes.get_label | train | def get_label(self, name):
"""Find the label by name."""
label_tag = self._find_label(name)
return _Label(label_tag.get('id'), label_tag.get('color'), label_tag.text) | python | {
"resource": ""
} |
q233272 | Notes.add_label | train | def add_label(self, name, color):
"""Add a new label. It's id will automatically be calculated."""
color_upper = color.upper()
if not self._color_re.match(color_upper):
raise ValueError('Invalid color: {}'.format(color))
labels_tag = self.root[0]
last_id = int(labels... | python | {
"resource": ""
} |
q233273 | Notes.del_label | train | def del_label(self, name):
"""Delete a label by name."""
labels_tag = self.root[0]
labels_tag.remove(self._find_label(name)) | python | {
"resource": ""
} |
q233274 | Notes.save | train | def save(self, filename):
"""Save the note XML to a file."""
with open(filename, 'w') as fp:
fp.write(str(self)) | python | {
"resource": ""
} |
q233275 | _BaseHandHistory.board | train | def board(self):
"""Calculates board from flop, turn and river."""
board = []
if self.flop:
board.extend(self.flop.cards)
if self.turn:
board.append(self.turn)
if self.river:
board.append(self.river)
return tuple... | python | {
"resource": ""
} |
q233276 | _BaseHandHistory._parse_date | train | def _parse_date(self, date_string):
"""Parse the date_string and return a datetime object as UTC."""
date = datetime.strptime(date_string, self._DATE_FORMAT)
self.date = self._TZ.localize(date).astimezone(pytz.UTC) | python | {
"resource": ""
} |
q233277 | _SplittableHandHistoryMixin._split_raw | train | def _split_raw(self):
"""Split hand history by sections."""
self._splitted = self._split_re.split(self.raw)
# search split locations (basically empty strings)
self._sections = [ind for ind, elem in enumerate(self._splitted) if not elem] | python | {
"resource": ""
} |
q233278 | ForumMember._get_timezone | train | def _get_timezone(self, root):
"""Find timezone informatation on bottom of the page."""
tz_str = root.xpath('//div[@class="smallfont" and @align="center"]')[0].text
hours = int(self._tz_re.search(tz_str).group(1))
return tzoffset(tz_str, hours * 60) | python | {
"resource": ""
} |
q233279 | get_current_tournaments | train | def get_current_tournaments():
"""Get the next 200 tournaments from pokerstars."""
schedule_page = requests.get(TOURNAMENTS_XML_URL)
root = etree.XML(schedule_page.content)
for tour in root.iter('{*}tournament'):
yield _Tournament(
start_date=tour.findtext('{*}start_date'),
... | python | {
"resource": ""
} |
q233280 | _filter_file | train | def _filter_file(src, dest, subst):
"""Copy src to dest doing substitutions on the fly.
"""
substre = re.compile(r'\$(%s)' % '|'.join(subst.keys()))
def repl(m):
return subst[m.group(1)]
with open(src, "rt") as sf, open(dest, "wt") as df:
while True:
l = sf.readline()
... | python | {
"resource": ""
} |
q233281 | BaseEndpoint._fixup_graphql_error | train | def _fixup_graphql_error(self, data):
'''Given a possible GraphQL error payload, make sure it's in shape.
This will ensure the given ``data`` is in the shape:
.. code-block:: json
{"errors": [{"message": "some string"}]}
If ``errors`` is not an array, it will be made into ... | python | {
"resource": ""
} |
q233282 | BaseEndpoint.snippet | train | def snippet(code, locations, sep=' | ', colmark=('-', '^'), context=5):
'''Given a code and list of locations, convert to snippet lines.
return will include line number, a separator (``sep``), then
line contents.
At most ``context`` lines are shown before each location line.
A... | python | {
"resource": ""
} |
q233283 | _create_non_null_wrapper | train | def _create_non_null_wrapper(name, t):
'creates type wrapper for non-null of given type'
def __new__(cls, json_data, selection_list=None):
if json_data is None:
raise ValueError(name + ' received null value')
return t(json_data, selection_list)
def __to_graphql_input__(value, in... | python | {
"resource": ""
} |
q233284 | _create_list_of_wrapper | train | def _create_list_of_wrapper(name, t):
'creates type wrapper for list of given type'
def __new__(cls, json_data, selection_list=None):
if json_data is None:
return None
return [t(v, selection_list) for v in json_data]
def __to_graphql_input__(value, indent=0, indent_string=' '):... | python | {
"resource": ""
} |
q233285 | add_query_to_url | train | def add_query_to_url(url, extra_query):
'''Adds an extra query to URL, returning the new URL.
Extra query may be a dict or a list as returned by
:func:`urllib.parse.parse_qsl()` and :func:`urllib.parse.parse_qs()`.
'''
split = urllib.parse.urlsplit(url)
merged_query = urllib.parse.parse_qsl(sp... | python | {
"resource": ""
} |
q233286 | connection_args | train | def connection_args(*lst, **mapping):
'''Returns the default parameters for connection.
Extra parameters may be given as argument, both as iterable,
positional tuples or mapping.
By default, provides:
- ``after: String``
- ``before: String``
- ``first: Int``
- ``last: Int``
''... | python | {
"resource": ""
} |
q233287 | msjd | train | def msjd(theta):
"""Mean squared jumping distance.
"""
s = 0.
for p in theta.dtype.names:
s += np.sum(np.diff(theta[p], axis=0) ** 2)
return s | python | {
"resource": ""
} |
q233288 | StaticModel.loglik | train | def loglik(self, theta, t=None):
""" log-likelihood at given parameter values.
Parameters
----------
theta: dict-like
theta['par'] is a ndarray containing the N values for parameter par
t: int
time (if set to None, the full log-likelihood is returned)
... | python | {
"resource": ""
} |
q233289 | StaticModel.logpost | train | def logpost(self, theta, t=None):
"""Posterior log-density at given parameter values.
Parameters
----------
theta: dict-like
theta['par'] is a ndarray containing the N values for parameter par
t: int
time (if set to None, the full posterior is returned)... | python | {
"resource": ""
} |
q233290 | FancyList.copyto | train | def copyto(self, src, where=None):
"""
Same syntax and functionality as numpy.copyto
"""
for n, _ in enumerate(self.l):
if where[n]:
self.l[n] = src.l[n] | python | {
"resource": ""
} |
q233291 | ThetaParticles.copy | train | def copy(self):
"""Returns a copy of the object."""
attrs = {k: self.__dict__[k].copy() for k in self.containers}
attrs.update({k: cp.deepcopy(self.__dict__[k]) for k in self.shared})
return self.__class__(**attrs) | python | {
"resource": ""
} |
q233292 | ThetaParticles.copyto | train | def copyto(self, src, where=None):
"""Emulates function `copyto` in NumPy.
Parameters
----------
where: (N,) bool ndarray
True if particle n in src must be copied.
src: (N,) `ThetaParticles` object
source
for each n such that where[n] is True, cop... | python | {
"resource": ""
} |
q233293 | ThetaParticles.copyto_at | train | def copyto_at(self, n, src, m):
"""Copy to at a given location.
Parameters
----------
n: int
index where to copy
src: `ThetaParticles` object
source
m: int
index of the element to be copied
Note
----
Basical... | python | {
"resource": ""
} |
q233294 | MetroParticles.Metropolis | train | def Metropolis(self, compute_target, mh_options):
"""Performs a certain number of Metropolis steps.
Parameters
----------
compute_target: function
computes the target density for the proposed values
mh_options: dict
+ 'type_prop': {'random_walk', 'inde... | python | {
"resource": ""
} |
q233295 | BaumWelch.backward | train | def backward(self):
"""Backward recursion.
Upon completion, the following list of length T is available:
* smth: marginal smoothing probabilities
Note
----
Performs the forward step in case it has not been performed before.
"""
if not self.filt:
... | python | {
"resource": ""
} |
q233296 | predict_step | train | def predict_step(F, covX, filt):
"""Predictive step of Kalman filter.
Parameters
----------
F: (dx, dx) numpy array
Mean of X_t | X_{t-1} is F * X_{t-1}
covX: (dx, dx) numpy array
covariance of X_t | X_{t-1}
filt: MeanAndCov object
filtering distribution at time t-1
... | python | {
"resource": ""
} |
q233297 | filter_step | train | def filter_step(G, covY, pred, yt):
"""Filtering step of Kalman filter.
Parameters
----------
G: (dy, dx) numpy array
mean of Y_t | X_t is G * X_t
covX: (dx, dx) numpy array
covariance of Y_t | X_t
pred: MeanAndCov object
predictive distribution at time t
Returns
... | python | {
"resource": ""
} |
q233298 | MVLinearGauss.check_shapes | train | def check_shapes(self):
"""
Check all dimensions are correct.
"""
assert self.covX.shape == (self.dx, self.dx), error_msg
assert self.covY.shape == (self.dy, self.dy), error_msg
assert self.F.shape == (self.dx, self.dx), error_msg
assert self.G.shape == (self.dy, ... | python | {
"resource": ""
} |
q233299 | sobol | train | def sobol(N, dim, scrambled=1):
""" Sobol sequence.
Parameters
----------
N : int
length of sequence
dim: int
dimension
scrambled: int
which scrambling method to use:
+ 0: no scrambling
+ 1: Owen's scrambling
+ 2: Faure-Tezuka
... | python | {
"resource": ""
} |
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