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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/tools/python3/src/Lib/smtplib.py | python | SMTP.auth_cram_md5 | (self, challenge=None) | return self.user + " " + hmac.HMAC(
self.password.encode('ascii'), challenge, 'md5').hexdigest() | Authobject to use with CRAM-MD5 authentication. Requires self.user
and self.password to be set. | Authobject to use with CRAM-MD5 authentication. Requires self.user
and self.password to be set. | [
"Authobject",
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".",
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] | def auth_cram_md5(self, challenge=None):
""" Authobject to use with CRAM-MD5 authentication. Requires self.user
and self.password to be set."""
# CRAM-MD5 does not support initial-response.
if challenge is None:
return None
return self.user + " " + hmac.HMAC(
self.password.encode('ascii'), challenge, 'md5').hexdigest() | [
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|
albertz/openlierox | d316c14a8eb57848ef56e9bfa7b23a56f694a51b | tools/DedicatedServerVideo/gdata/tlslite/TLSRecordLayer.py | python | TLSRecordLayer.getCipherImplementation | (self) | return self._writeState.encContext.implementation | Get the name of the cipher implementation used with
this connection.
@rtype: str
@return: The name of the cipher implementation used with
this connection. Either 'python', 'cryptlib', 'openssl',
or 'pycrypto'. | Get the name of the cipher implementation used with
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] | def getCipherImplementation(self):
"""Get the name of the cipher implementation used with
this connection.
@rtype: str
@return: The name of the cipher implementation used with
this connection. Either 'python', 'cryptlib', 'openssl',
or 'pycrypto'.
"""
if not self._writeState.encContext:
return None
return self._writeState.encContext.implementation | [
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|
francinexue/xuefu | b6ff79747a42e020588c0c0a921048e08fe4680c | ctpx/ctp2/ctptd.py | python | CtpTd.onRspQryBrokerTradingAlgos | (self, BrokerTradingAlgosField, RspInfoField, requestId, final) | 请求查询经纪公司交易算法响应 | 请求查询经纪公司交易算法响应 | [
"请求查询经纪公司交易算法响应"
] | def onRspQryBrokerTradingAlgos(self, BrokerTradingAlgosField, RspInfoField, requestId, final):
"""请求查询经纪公司交易算法响应"""
pass | [
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||
may0324/DeepCompression-caffe | 0aff6c1287bda4cfc7f378ed8a16524e1afabd8c | python/caffe/draw.py | python | choose_color_by_layertype | (layertype) | return color | Define colors for nodes based on the layer type. | Define colors for nodes based on the layer type. | [
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] | def choose_color_by_layertype(layertype):
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"""
color = '#6495ED' # Default
if layertype == 'Convolution' or layertype == 'Deconvolution':
color = '#FF5050'
elif layertype == 'Pooling':
color = '#FF9900'
elif layertype == 'InnerProduct':
color = '#CC33FF'
return color | [
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|
wlanjie/AndroidFFmpeg | 7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf | tools/fdk-aac-build/armeabi/toolchain/lib/python2.7/codecs.py | python | IncrementalDecoder.reset | (self) | Resets the decoder to the initial state. | Resets the decoder to the initial state. | [
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||
aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemMetric/v1/AWS/python/windows/Lib/fsspec/utils.py | python | stringify_path | (filepath) | return filepath | Attempt to convert a path-like object to a string.
Parameters
----------
filepath: object to be converted
Returns
-------
filepath_str: maybe a string version of the object
Notes
-----
Objects supporting the fspath protocol (Python 3.6+) are coerced
according to its __fspath__ method.
For backwards compatibility with older Python version, pathlib.Path
objects are specially coerced.
Any other object is passed through unchanged, which includes bytes,
strings, buffers, or anything else that's not even path-like. | Attempt to convert a path-like object to a string. | [
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"path",
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] | def stringify_path(filepath):
""" Attempt to convert a path-like object to a string.
Parameters
----------
filepath: object to be converted
Returns
-------
filepath_str: maybe a string version of the object
Notes
-----
Objects supporting the fspath protocol (Python 3.6+) are coerced
according to its __fspath__ method.
For backwards compatibility with older Python version, pathlib.Path
objects are specially coerced.
Any other object is passed through unchanged, which includes bytes,
strings, buffers, or anything else that's not even path-like.
"""
if hasattr(filepath, "__fspath__"):
return filepath.__fspath__()
elif isinstance(filepath, pathlib.Path):
return str(filepath)
return filepath | [
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|
psi4/psi4 | be533f7f426b6ccc263904e55122899b16663395 | psi4/driver/procrouting/proc.py | python | run_scf_gradient | (name, **kwargs) | return ref_wfn | Function encoding sequence of PSI module calls for
a SCF gradient calculation. | Function encoding sequence of PSI module calls for
a SCF gradient calculation. | [
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] | def run_scf_gradient(name, **kwargs):
"""Function encoding sequence of PSI module calls for
a SCF gradient calculation.
"""
dft_func = False
if "dft_functional" in kwargs:
dft_func = True
optstash = proc_util.scf_set_reference_local(name, is_dft=dft_func)
# Bypass the scf call if a reference wavefunction is given
ref_wfn = kwargs.get('ref_wfn', None)
if ref_wfn is None:
ref_wfn = run_scf(name, **kwargs)
if core.get_option('SCF', 'REFERENCE') in ['ROHF', 'CUHF']:
ref_wfn.semicanonicalize()
if hasattr(ref_wfn, "_disp_functor"):
disp_grad = ref_wfn._disp_functor.compute_gradient(ref_wfn.molecule(), ref_wfn)
ref_wfn.set_variable("-D Gradient", disp_grad)
grad = core.scfgrad(ref_wfn)
if ref_wfn.basisset().has_ECP():
core.print_out("\n\n ==> Adding ECP gradient terms (computed numerically) <==\n")
# Build a map of atom->ECP number
old_print = ref_wfn.get_print()
ref_wfn.set_print(0)
delta = 0.0001
natom = ref_wfn.molecule().natom()
mints = core.MintsHelper(ref_wfn)
ecpgradmat = core.Matrix("ECP Gradient", natom, 3)
ecpgradmat.zero()
ecpgrad = np.asarray(ecpgradmat)
Dmat = ref_wfn.Da_subset("AO")
Dmat.add(ref_wfn.Db_subset("AO"))
def displaced_energy(atom, displacement):
mints.basisset().move_atom(atom, displacement)
E = Dmat.vector_dot(mints.ao_ecp())
mints.basisset().move_atom(atom, -1*displacement)
return E
for atom in range(natom):
for xyz in range(3):
transvec = core.Vector3(0.0)
transvec[xyz] += delta
# +1 displacement
Ep1 = displaced_energy(atom, 1*transvec)
# -1 displacement
Em1 = displaced_energy(atom, -1*transvec)
# +2 displacement
Ep2 = displaced_energy(atom, 2*transvec)
# -2 displacement
Em2 = displaced_energy(atom, -2*transvec)
# Evaluate
ecpgrad[atom, xyz] = (Em2 + 8*Ep1 - 8*Em1 - Ep2) / (12*delta)
ecpgradmat.symmetrize_gradient(ref_wfn.molecule())
ecpgradmat.print_atom_vector()
grad.add(ecpgradmat)
grad.print_atom_vector()
ref_wfn.set_print(old_print)
ref_wfn.set_gradient(grad)
ref_wfn.set_variable("SCF TOTAL GRADIENT", grad) # P::e SCF
if ref_wfn.functional().needs_xc():
ref_wfn.set_variable("DFT TOTAL GRADIENT", grad) # overwritten later for DH -- TODO when DH gradients # P::e SCF
else:
ref_wfn.set_variable("HF TOTAL GRADIENT", grad) # P::e SCF
# Shove variables into global space
for k, v in ref_wfn.variables().items():
core.set_variable(k, v)
optstash.restore()
return ref_wfn | [
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|
giuspen/cherrytree | 84712f206478fcf9acf30174009ad28c648c6344 | pygtk2/modules/core.py | python | CherryTree.anchor_edit_dialog | (self, pixbuf, iter_insert, iter_bound=None) | Anchor Edit Dialog | Anchor Edit Dialog | [
"Anchor",
"Edit",
"Dialog"
] | def anchor_edit_dialog(self, pixbuf, iter_insert, iter_bound=None):
"""Anchor Edit Dialog"""
if "anchor" in dir (pixbuf):
anchor_curr_name = pixbuf.anchor
dialog_title = _("Edit Anchor")
else:
anchor_curr_name = ""
dialog_title = _("Insert Anchor")
ret_anchor_name = support.dialog_img_n_entry(self.window, dialog_title, anchor_curr_name, "anchor")
if not ret_anchor_name: return
pixbuf.anchor = ret_anchor_name
if iter_bound != None: # only in case of modify
image_justification = self.state_machine.get_iter_alignment(iter_insert)
image_offset = iter_insert.get_offset()
self.curr_buffer.delete(iter_insert, iter_bound)
iter_insert = self.curr_buffer.get_iter_at_offset(image_offset)
else: image_justification = None
self.image_insert(iter_insert, pixbuf, image_justification) | [
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wlanjie/AndroidFFmpeg | 7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf | tools/fdk-aac-build/armeabi/toolchain/lib/python2.7/bsddb/dbtables.py | python | bsdTableDB.ListTableColumns | (self, table) | Return a list of columns in the given table.
[] if the table doesn't exist. | Return a list of columns in the given table.
[] if the table doesn't exist. | [
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"""Return a list of columns in the given table.
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CRYTEK/CRYENGINE | 232227c59a220cbbd311576f0fbeba7bb53b2a8c | Code/Tools/waf-1.7.13/crywaflib/compile_settings_windows.py | python | load_release_windows_settings | (conf) | Setup all compiler and linker settings shared over all windows configurations for
the 'debug' configuration | Setup all compiler and linker settings shared over all windows configurations for
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"""
Setup all compiler and linker settings shared over all windows configurations for
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"""
v = conf.env
conf.load_windows_common_settings() | [
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mantidproject/mantid | 03deeb89254ec4289edb8771e0188c2090a02f32 | tools/Pylint/run_pylint.py | python | create_dir_if_required | (path) | Create the given directory if it doesn't exist
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"""
Create the given directory if it doesn't exist
Arguments:
path (str): Absolute path to a directory
"""
if path and not os.path.exists(path):
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/pandas/py2/pandas/core/indexes/base.py | python | Index._reset_identity | (self) | return self | Initializes or resets ``_id`` attribute with new object. | Initializes or resets ``_id`` attribute with new object. | [
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"""
Initializes or resets ``_id`` attribute with new object.
"""
self._id = _Identity()
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mapsme/omim | 1892903b63f2c85b16ed4966d21fe76aba06b9ba | tools/python/stylesheet/webcolors/webcolors.py | python | rgb_to_rgb_percent | (rgb_triplet) | return tuple(map(lambda d: specials.get(d, '%.02f%%' % ((d / 255.0) * 100)),
rgb_triplet)) | Convert a 3-tuple of integers, suitable for use in an ``rgb()``
color triplet, to a 3-tuple of percentages suitable for use in
representing that color.
This function makes some trade-offs in terms of the accuracy of
the final representation; for some common integer values,
special-case logic is used to ensure a precise result (e.g.,
integer 128 will always convert to '50%', integer 32 will always
convert to '12.5%'), but for all other values a standard Python
``float`` is used and rounded to two decimal places, which may
result in a loss of precision for some values.
Examples:
>>> rgb_to_rgb_percent((255, 255, 255))
('100%', '100%', '100%')
>>> rgb_to_rgb_percent((0, 0, 128))
('0%', '0%', '50%')
>>> rgb_to_rgb_percent((33, 56, 192))
('12.94%', '21.96%', '75.29%')
>>> rgb_to_rgb_percent((64, 32, 16))
('25%', '12.5%', '6.25%') | Convert a 3-tuple of integers, suitable for use in an ``rgb()``
color triplet, to a 3-tuple of percentages suitable for use in
representing that color. | [
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"""
Convert a 3-tuple of integers, suitable for use in an ``rgb()``
color triplet, to a 3-tuple of percentages suitable for use in
representing that color.
This function makes some trade-offs in terms of the accuracy of
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special-case logic is used to ensure a precise result (e.g.,
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convert to '12.5%'), but for all other values a standard Python
``float`` is used and rounded to two decimal places, which may
result in a loss of precision for some values.
Examples:
>>> rgb_to_rgb_percent((255, 255, 255))
('100%', '100%', '100%')
>>> rgb_to_rgb_percent((0, 0, 128))
('0%', '0%', '50%')
>>> rgb_to_rgb_percent((33, 56, 192))
('12.94%', '21.96%', '75.29%')
>>> rgb_to_rgb_percent((64, 32, 16))
('25%', '12.5%', '6.25%')
"""
# In order to maintain precision for common values,
# 256 / 2**n is special-cased for values of n
# from 0 through 4, as well as 0 itself.
specials = {255: '100%', 128: '50%', 64: '25%',
32: '12.5%', 16: '6.25%', 0: '0%'}
return tuple(map(lambda d: specials.get(d, '%.02f%%' % ((d / 255.0) * 100)),
rgb_triplet)) | [
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BVLC/caffe | 9b891540183ddc834a02b2bd81b31afae71b2153 | scripts/cpp_lint.py | python | RemoveMultiLineCommentsFromRange | (lines, begin, end) | Clears a range of lines for multi-line comments. | Clears a range of lines for multi-line comments. | [
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"""Clears a range of lines for multi-line comments."""
# Having // dummy comments makes the lines non-empty, so we will not get
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for i in range(begin, end):
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemMetric/v1/AWS/python/windows/Lib/numpy/lib/nanfunctions.py | python | nanprod | (a, axis=None, dtype=None, out=None, keepdims=np._NoValue) | return np.prod(a, axis=axis, dtype=dtype, out=out, keepdims=keepdims) | Return the product of array elements over a given axis treating Not a
Numbers (NaNs) as ones.
One is returned for slices that are all-NaN or empty.
.. versionadded:: 1.10.0
Parameters
----------
a : array_like
Array containing numbers whose product is desired. If `a` is not an
array, a conversion is attempted.
axis : {int, tuple of int, None}, optional
Axis or axes along which the product is computed. The default is to compute
the product of the flattened array.
dtype : data-type, optional
The type of the returned array and of the accumulator in which the
elements are summed. By default, the dtype of `a` is used. An
exception is when `a` has an integer type with less precision than
the platform (u)intp. In that case, the default will be either
(u)int32 or (u)int64 depending on whether the platform is 32 or 64
bits. For inexact inputs, dtype must be inexact.
out : ndarray, optional
Alternate output array in which to place the result. The default
is ``None``. If provided, it must have the same shape as the
expected output, but the type will be cast if necessary. See
`ufuncs-output-type` for more details. The casting of NaN to integer
can yield unexpected results.
keepdims : bool, optional
If True, the axes which are reduced are left in the result as
dimensions with size one. With this option, the result will
broadcast correctly against the original `arr`.
Returns
-------
nanprod : ndarray
A new array holding the result is returned unless `out` is
specified, in which case it is returned.
See Also
--------
numpy.prod : Product across array propagating NaNs.
isnan : Show which elements are NaN.
Examples
--------
>>> np.nanprod(1)
1
>>> np.nanprod([1])
1
>>> np.nanprod([1, np.nan])
1.0
>>> a = np.array([[1, 2], [3, np.nan]])
>>> np.nanprod(a)
6.0
>>> np.nanprod(a, axis=0)
array([3., 2.]) | Return the product of array elements over a given axis treating Not a
Numbers (NaNs) as ones. | [
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"""
Return the product of array elements over a given axis treating Not a
Numbers (NaNs) as ones.
One is returned for slices that are all-NaN or empty.
.. versionadded:: 1.10.0
Parameters
----------
a : array_like
Array containing numbers whose product is desired. If `a` is not an
array, a conversion is attempted.
axis : {int, tuple of int, None}, optional
Axis or axes along which the product is computed. The default is to compute
the product of the flattened array.
dtype : data-type, optional
The type of the returned array and of the accumulator in which the
elements are summed. By default, the dtype of `a` is used. An
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out : ndarray, optional
Alternate output array in which to place the result. The default
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keepdims : bool, optional
If True, the axes which are reduced are left in the result as
dimensions with size one. With this option, the result will
broadcast correctly against the original `arr`.
Returns
-------
nanprod : ndarray
A new array holding the result is returned unless `out` is
specified, in which case it is returned.
See Also
--------
numpy.prod : Product across array propagating NaNs.
isnan : Show which elements are NaN.
Examples
--------
>>> np.nanprod(1)
1
>>> np.nanprod([1])
1
>>> np.nanprod([1, np.nan])
1.0
>>> a = np.array([[1, 2], [3, np.nan]])
>>> np.nanprod(a)
6.0
>>> np.nanprod(a, axis=0)
array([3., 2.])
"""
a, mask = _replace_nan(a, 1)
return np.prod(a, axis=axis, dtype=dtype, out=out, keepdims=keepdims) | [
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|
wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/msw/glcanvas.py | python | GLCanvas.SetupPalette | (*args, **kwargs) | return _glcanvas.GLCanvas_SetupPalette(*args, **kwargs) | SetupPalette(self, Palette palette) | SetupPalette(self, Palette palette) | [
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"""SetupPalette(self, Palette palette)"""
return _glcanvas.GLCanvas_SetupPalette(*args, **kwargs) | [
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|
ChromiumWebApps/chromium | c7361d39be8abd1574e6ce8957c8dbddd4c6ccf7 | tools/telemetry/third_party/pyserial/serial/serialutil.py | python | SerialBase.getBaudrate | (self) | return self._baudrate | Get the current baud rate setting. | Get the current baud rate setting. | [
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"""Get the current baud rate setting."""
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|
benoitsteiner/tensorflow-opencl | cb7cb40a57fde5cfd4731bc551e82a1e2fef43a5 | tensorflow/python/training/saver.py | python | Saver.set_last_checkpoints_with_time | (self, last_checkpoints_with_time) | Sets the list of old checkpoint filenames and timestamps.
Args:
last_checkpoints_with_time: A list of tuples of checkpoint filenames and
timestamps.
Raises:
AssertionError: If last_checkpoints_with_time is not a list. | Sets the list of old checkpoint filenames and timestamps. | [
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] | def set_last_checkpoints_with_time(self, last_checkpoints_with_time):
"""Sets the list of old checkpoint filenames and timestamps.
Args:
last_checkpoints_with_time: A list of tuples of checkpoint filenames and
timestamps.
Raises:
AssertionError: If last_checkpoints_with_time is not a list.
"""
assert isinstance(last_checkpoints_with_time, list)
self._last_checkpoints = last_checkpoints_with_time | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/scipy/py2/scipy/io/mmio.py | python | mmwrite | (target, a, comment='', field=None, precision=None, symmetry=None) | Writes the sparse or dense array `a` to Matrix Market file-like `target`.
Parameters
----------
target : str or file-like
Matrix Market filename (extension .mtx) or open file-like object.
a : array like
Sparse or dense 2D array.
comment : str, optional
Comments to be prepended to the Matrix Market file.
field : None or str, optional
Either 'real', 'complex', 'pattern', or 'integer'.
precision : None or int, optional
Number of digits to display for real or complex values.
symmetry : None or str, optional
Either 'general', 'symmetric', 'skew-symmetric', or 'hermitian'.
If symmetry is None the symmetry type of 'a' is determined by its
values. | Writes the sparse or dense array `a` to Matrix Market file-like `target`. | [
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"""
Writes the sparse or dense array `a` to Matrix Market file-like `target`.
Parameters
----------
target : str or file-like
Matrix Market filename (extension .mtx) or open file-like object.
a : array like
Sparse or dense 2D array.
comment : str, optional
Comments to be prepended to the Matrix Market file.
field : None or str, optional
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precision : None or int, optional
Number of digits to display for real or complex values.
symmetry : None or str, optional
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||
miyosuda/TensorFlowAndroidMNIST | 7b5a4603d2780a8a2834575706e9001977524007 | jni-build/jni/include/tensorflow/python/summary/event_accumulator.py | python | _Remap | (x, x0, x1, y0, y1) | return y0 + (x - x0) * float(y1 - y0) / (x1 - x0) | Linearly map from [x0, x1] unto [y0, y1]. | Linearly map from [x0, x1] unto [y0, y1]. | [
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"""Linearly map from [x0, x1] unto [y0, y1]."""
return y0 + (x - x0) * float(y1 - y0) / (x1 - x0) | [
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|
facebookincubator/BOLT | 88c70afe9d388ad430cc150cc158641701397f70 | mlir/python/mlir/dialects/linalg/opdsl/ops/core_named_ops.py | python | conv_1d_nwc_wcf | (
I=TensorDef(T1, S.N, S.OW * S.SW + S.KW * S.DW, S.C),
K=TensorDef(T2, S.KW, S.C, S.F),
O=TensorDef(U, S.N, S.OW, S.F, output=True),
strides=IndexAttrDef(S.SW),
dilations=IndexAttrDef(S.DW)) | Performs 1-D convolution.
Numeric casting is performed on the operands to the inner multiply, promoting
them to the same data type as the accumulator/output. | Performs 1-D convolution. | [
"Performs",
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"-",
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"."
] | def conv_1d_nwc_wcf(
I=TensorDef(T1, S.N, S.OW * S.SW + S.KW * S.DW, S.C),
K=TensorDef(T2, S.KW, S.C, S.F),
O=TensorDef(U, S.N, S.OW, S.F, output=True),
strides=IndexAttrDef(S.SW),
dilations=IndexAttrDef(S.DW)):
"""Performs 1-D convolution.
Numeric casting is performed on the operands to the inner multiply, promoting
them to the same data type as the accumulator/output.
"""
implements(ConvolutionOpInterface)
domain(D.n, D.ow, D.f, D.kw, D.c)
O[D.n, D.ow,
D.f] += TypeFn.cast(U, I[D.n, D.ow * S.SW + D.kw * S.DW,
D.c]) * TypeFn.cast(U, K[D.kw, D.c, D.f]) | [
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||
apiaryio/snowcrash | b5b39faa85f88ee17459edf39fdc6fe4fc70d2e3 | tools/gyp/pylib/gyp/msvs_emulation.py | python | MsvsSettings.HasExplicitAsmRules | (self, spec) | return self._HasExplicitRuleForExtension(spec, 'asm') | Determine if there's an explicit rule for asm files. When there isn't we
need to generate implicit rules to assemble .asm files. | Determine if there's an explicit rule for asm files. When there isn't we
need to generate implicit rules to assemble .asm files. | [
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] | def HasExplicitAsmRules(self, spec):
"""Determine if there's an explicit rule for asm files. When there isn't we
need to generate implicit rules to assemble .asm files."""
return self._HasExplicitRuleForExtension(spec, 'asm') | [
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|
turi-code/SFrame | 796b9bdfb2fa1b881d82080754643c7e68629cd2 | oss_src/unity/python/sframe/util/cloudpickle.py | python | CloudPickler.save_function | (self, obj, name=None) | Registered with the dispatch to handle all function types.
Determines what kind of function obj is (e.g. lambda, defined at
interactive prompt, etc) and handles the pickling appropriately. | Registered with the dispatch to handle all function types. | [
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""" Registered with the dispatch to handle all function types.
Determines what kind of function obj is (e.g. lambda, defined at
interactive prompt, etc) and handles the pickling appropriately.
"""
write = self.write
if name is None:
name = obj.__name__
modname = pickle.whichmodule(obj, name)
# print('which gives %s %s %s' % (modname, obj, name))
try:
themodule = sys.modules[modname]
except KeyError:
# eval'd items such as namedtuple give invalid items for their function __module__
modname = '__main__'
if modname == '__main__':
themodule = None
if themodule:
self.modules.add(themodule)
if getattr(themodule, name, None) is obj:
return self.save_global(obj, name)
# if func is lambda, def'ed at prompt, is in main, or is nested, then
# we'll pickle the actual function object rather than simply saving a
# reference (as is done in default pickler), via save_function_tuple.
if islambda(obj) or obj.__code__.co_filename == '<stdin>' or themodule is None:
#print("save global", islambda(obj), obj.__code__.co_filename, modname, themodule)
self.save_function_tuple(obj)
return
else:
# func is nested
klass = getattr(themodule, name, None)
if klass is None or klass is not obj:
self.save_function_tuple(obj)
return
if obj.__dict__:
# essentially save_reduce, but workaround needed to avoid recursion
self.save(_restore_attr)
write(pickle.MARK + pickle.GLOBAL + modname + '\n' + name + '\n')
self.memoize(obj)
self.save(obj.__dict__)
write(pickle.TUPLE + pickle.REDUCE)
else:
write(pickle.GLOBAL + modname + '\n' + name + '\n')
self.memoize(obj) | [
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||
SFTtech/openage | d6a08c53c48dc1e157807471df92197f6ca9e04d | openage/convert/service/debug_info.py | python | debug_game_version | (debugdir, loglevel, args) | Create debug output for the detected game version.
:param debugdir: Output directory for the debug info.
:type debugdir: Directory
:param loglevel: Determines how detailed the output is.
:type loglevel: int
:param args: CLI arguments.
:type args: Namespace | Create debug output for the detected game version. | [
"Create",
"debug",
"output",
"for",
"the",
"detected",
"game",
"version",
"."
] | def debug_game_version(debugdir, loglevel, args):
"""
Create debug output for the detected game version.
:param debugdir: Output directory for the debug info.
:type debugdir: Directory
:param loglevel: Determines how detailed the output is.
:type loglevel: int
:param args: CLI arguments.
:type args: Namespace
"""
if loglevel < 2:
return
# Log game version
logfile = debugdir.joinpath("init/")["game_version"]
logtext = ""
logtext += (
f"game edition:\n"
f" - {args.game_version[0]}\n"
)
if len(args.game_version[1]) > 0:
logtext += "game expansions:\n"
for expansion in args.game_version[1]:
logtext += f" - {expansion}\n"
else:
logtext += "game expansions: none detected"
with logfile.open("w") as log:
log.write(logtext) | [
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||
hanpfei/chromium-net | 392cc1fa3a8f92f42e4071ab6e674d8e0482f83f | third_party/catapult/third_party/mapreduce/mapreduce/shuffler.py | python | _MergingReader.from_json | (cls, json) | return cls(json["offsets"],
json["max_values_count"],
json["max_values_size"]) | Restore reader from json state. | Restore reader from json state. | [
"Restore",
"reader",
"from",
"json",
"state",
"."
] | def from_json(cls, json):
"""Restore reader from json state."""
return cls(json["offsets"],
json["max_values_count"],
json["max_values_size"]) | [
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|
Xilinx/Vitis-AI | fc74d404563d9951b57245443c73bef389f3657f | tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/python/eager/wrap_function.py | python | _lift_single_variable | (old_variable, graph, variable_holder) | return new_variable | Lifts `old_variable` out of the `FuncGraph` `graph`. | Lifts `old_variable` out of the `FuncGraph` `graph`. | [
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] | def _lift_single_variable(old_variable, graph, variable_holder):
"""Lifts `old_variable` out of the `FuncGraph` `graph`."""
new_variable = resource_variable_ops.UninitializedVariable(
shape=old_variable.shape,
dtype=old_variable.dtype,
name=old_variable.op.name,
trainable=old_variable.trainable,
extra_handle_data=old_variable.handle)
new_variable._initializer_op = old_variable._initializer_op # pylint: disable=protected-access
graph.add_capture(new_variable.handle, old_variable.handle)
# Now that we've added the new variable to graph.captures,
# graph.capture will use that cached value and do some post-processing
# on the capture like recording it on the tape.
graph.capture(new_variable.handle)
# pylint: disable=protected-access
variable_name = new_variable.name.split(":")[0]
variable_holder._variables_by_name[variable_name] = new_variable
graph._weak_variables.append(weakref.ref(new_variable))
# pylint: enable=protected-access
graph.watch_variable(new_variable)
return new_variable | [
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|
vslavik/poedit | f7a9daa0a10037e090aa0a86f5ce0f24ececdf6a | deps/boost/tools/build/src/build/generators.py | python | Generator.target_types | (self) | return self.target_types_ | Returns the list of target types that this generator produces.
It is assumed to be always the same -- i.e. it cannot change depending
list of sources. | Returns the list of target types that this generator produces.
It is assumed to be always the same -- i.e. it cannot change depending
list of sources. | [
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] | def target_types (self):
""" Returns the list of target types that this generator produces.
It is assumed to be always the same -- i.e. it cannot change depending
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"""
return self.target_types_ | [
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|
windystrife/UnrealEngine_NVIDIAGameWorks | b50e6338a7c5b26374d66306ebc7807541ff815e | Engine/Extras/ThirdPartyNotUE/emsdk/Win64/python/2.7.5.3_64bit/Lib/distutils/command/config.py | python | dump_file | (filename, head=None) | Dumps a file content into log.info.
If head is not None, will be dumped before the file content. | Dumps a file content into log.info. | [
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"info",
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] | def dump_file(filename, head=None):
"""Dumps a file content into log.info.
If head is not None, will be dumped before the file content.
"""
if head is None:
log.info('%s' % filename)
else:
log.info(head)
file = open(filename)
try:
log.info(file.read())
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||
NVIDIA/DALI | bf16cc86ba8f091b145f91962f21fe1b6aff243d | docs/examples/use_cases/tensorflow/efficientdet/pipeline/anchors_utils/argmax_matcher.py | python | ArgMaxMatcher._set_values_using_indicator | (self, x, indicator, val) | return x * (1 - indicator) + val * indicator | Set the indicated fields of x to val.
Args:
x: tensor.
indicator: boolean with same shape as x.
val: scalar with value to set.
Returns:
modified tensor. | Set the indicated fields of x to val. | [
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"""Set the indicated fields of x to val.
Args:
x: tensor.
indicator: boolean with same shape as x.
val: scalar with value to set.
Returns:
modified tensor.
"""
indicator = tf.cast(indicator, x.dtype)
return x * (1 - indicator) + val * indicator | [
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alibaba/weex_js_engine | 2bdf4b6f020c1fc99c63f649718f6faf7e27fdde | jni/v8core/v8/build/gyp/pylib/gyp/generator/android.py | python | AndroidMkWriter.NormalizeLdFlags | (self, ld_flags) | return clean_ldflags | Clean up ldflags from gyp file.
Remove any ldflags that contain android_top_dir.
Args:
ld_flags: ldflags from gyp files.
Returns:
clean ldflags | Clean up ldflags from gyp file.
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""" Clean up ldflags from gyp file.
Remove any ldflags that contain android_top_dir.
Args:
ld_flags: ldflags from gyp files.
Returns:
clean ldflags
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clean_ldflags = []
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clean_ldflags.append(flag)
return clean_ldflags | [
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|
nucleic/atom | 9f0cb2a8101dd63c354a98ebc7489b2c616dc82a | atom/atom.py | python | Atom.__getstate__ | (self) | return state | The base implementation of the pickle getstate protocol.
This base class implementation handles the generic case where
the object and all of its state are pickable. This includes
state stored in Atom members, as well as any instance dict or
slot attributes. Subclasses which require further customization
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"""The base implementation of the pickle getstate protocol.
This base class implementation handles the generic case where
the object and all of its state are pickable. This includes
state stored in Atom members, as well as any instance dict or
slot attributes. Subclasses which require further customization
should reimplement this method and modify the dict generated by
this base class method.
"""
state = {}
state.update(getattr(self, "__dict__", {}))
slots = copyreg._slotnames(type(self))
if slots:
for name in slots:
state[name] = getattr(self, name)
for key in self.members():
state[key] = getattr(self, key)
return state | [
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|
ricardoquesada/Spidermonkey | 4a75ea2543408bd1b2c515aa95901523eeef7858 | python/configobj/validate.py | python | is_option | (value, *options) | return value | This check matches the value to any of a set of options.
>>> vtor.check('option("yoda", "jedi")', 'yoda')
'yoda'
>>> vtor.check('option("yoda", "jedi")', 'jed')
Traceback (most recent call last):
VdtValueError: the value "jed" is unacceptable.
>>> vtor.check('option("yoda", "jedi")', 0)
Traceback (most recent call last):
VdtTypeError: the value "0" is of the wrong type. | This check matches the value to any of a set of options.
>>> vtor.check('option("yoda", "jedi")', 'yoda')
'yoda'
>>> vtor.check('option("yoda", "jedi")', 'jed')
Traceback (most recent call last):
VdtValueError: the value "jed" is unacceptable.
>>> vtor.check('option("yoda", "jedi")', 0)
Traceback (most recent call last):
VdtTypeError: the value "0" is of the wrong type. | [
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"""
This check matches the value to any of a set of options.
>>> vtor.check('option("yoda", "jedi")', 'yoda')
'yoda'
>>> vtor.check('option("yoda", "jedi")', 'jed')
Traceback (most recent call last):
VdtValueError: the value "jed" is unacceptable.
>>> vtor.check('option("yoda", "jedi")', 0)
Traceback (most recent call last):
VdtTypeError: the value "0" is of the wrong type.
"""
if not isinstance(value, basestring):
raise VdtTypeError(value)
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raise VdtValueError(value)
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|
miyosuda/TensorFlowAndroidMNIST | 7b5a4603d2780a8a2834575706e9001977524007 | jni-build/jni/include/tensorflow/models/image/cifar10/cifar10_input.py | python | inputs | (eval_data, data_dir, batch_size) | return _generate_image_and_label_batch(float_image, read_input.label,
min_queue_examples, batch_size,
shuffle=False) | Construct input for CIFAR evaluation using the Reader ops.
Args:
eval_data: bool, indicating if one should use the train or eval data set.
data_dir: Path to the CIFAR-10 data directory.
batch_size: Number of images per batch.
Returns:
images: Images. 4D tensor of [batch_size, IMAGE_SIZE, IMAGE_SIZE, 3] size.
labels: Labels. 1D tensor of [batch_size] size. | Construct input for CIFAR evaluation using the Reader ops. | [
"Construct",
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] | def inputs(eval_data, data_dir, batch_size):
"""Construct input for CIFAR evaluation using the Reader ops.
Args:
eval_data: bool, indicating if one should use the train or eval data set.
data_dir: Path to the CIFAR-10 data directory.
batch_size: Number of images per batch.
Returns:
images: Images. 4D tensor of [batch_size, IMAGE_SIZE, IMAGE_SIZE, 3] size.
labels: Labels. 1D tensor of [batch_size] size.
"""
if not eval_data:
filenames = [os.path.join(data_dir, 'data_batch_%d.bin' % i)
for i in xrange(1, 6)]
num_examples_per_epoch = NUM_EXAMPLES_PER_EPOCH_FOR_TRAIN
else:
filenames = [os.path.join(data_dir, 'test_batch.bin')]
num_examples_per_epoch = NUM_EXAMPLES_PER_EPOCH_FOR_EVAL
for f in filenames:
if not tf.gfile.Exists(f):
raise ValueError('Failed to find file: ' + f)
# Create a queue that produces the filenames to read.
filename_queue = tf.train.string_input_producer(filenames)
# Read examples from files in the filename queue.
read_input = read_cifar10(filename_queue)
reshaped_image = tf.cast(read_input.uint8image, tf.float32)
height = IMAGE_SIZE
width = IMAGE_SIZE
# Image processing for evaluation.
# Crop the central [height, width] of the image.
resized_image = tf.image.resize_image_with_crop_or_pad(reshaped_image,
width, height)
# Subtract off the mean and divide by the variance of the pixels.
float_image = tf.image.per_image_whitening(resized_image)
# Ensure that the random shuffling has good mixing properties.
min_fraction_of_examples_in_queue = 0.4
min_queue_examples = int(num_examples_per_epoch *
min_fraction_of_examples_in_queue)
# Generate a batch of images and labels by building up a queue of examples.
return _generate_image_and_label_batch(float_image, read_input.label,
min_queue_examples, batch_size,
shuffle=False) | [
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|
mantidproject/mantid | 03deeb89254ec4289edb8771e0188c2090a02f32 | qt/python/mantidqtinterfaces/mantidqtinterfaces/Muon/GUI/Common/fitting_widgets/tf_asymmetry_fitting/tf_asymmetry_fitting_model.py | python | TFAsymmetryFittingModel._update_tf_asymmetry_single_fit_functions_after_sequential | (self, workspaces: list, functions: list) | Updates the TF single fit functions after a sequential fit has been run on the Sequential fitting tab. | Updates the TF single fit functions after a sequential fit has been run on the Sequential fitting tab. | [
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"""Updates the TF single fit functions after a sequential fit has been run on the Sequential fitting tab."""
dataset_names = self.fitting_context.dataset_names
for workspace_index, workspace_name in enumerate(workspaces):
if workspace_name in dataset_names:
dataset_index = dataset_names.index(workspace_name)
self.update_tf_asymmetry_single_fit_function(dataset_index, functions[workspace_index]) | [
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||
chromiumembedded/cef | 80caf947f3fe2210e5344713c5281d8af9bdc295 | tools/make_distrib.py | python | create_tar_archive | (input_dir, format) | Creates a tar archive of the specified input directory. | Creates a tar archive of the specified input directory. | [
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] | def create_tar_archive(input_dir, format):
""" Creates a tar archive of the specified input directory. """
# Supported formats include "gz" and "bz2".
tar_file = input_dir + '.tar.' + format
tf = tarfile.open(tar_file, "w:" + format)
# The default tar format changed from GNU_FORMAT to PAX_FORMAT in Python 3.8.
# However, PAX_FORMAT generates additional @PaxHeader entries and truncates file
# names on Windows, so we'll stick with the previous default.
tf.format = tarfile.GNU_FORMAT
tf.add(input_dir, arcname=os.path.basename(input_dir))
tf.close() | [
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||
wlanjie/AndroidFFmpeg | 7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf | tools/fdk-aac-build/x86/toolchain/lib/python2.7/distutils/file_util.py | python | move_file | (src, dst, verbose=1, dry_run=0) | return dst | Move a file 'src' to 'dst'.
If 'dst' is a directory, the file will be moved into it with the same
name; otherwise, 'src' is just renamed to 'dst'. Return the new
full name of the file.
Handles cross-device moves on Unix using 'copy_file()'. What about
other systems??? | Move a file 'src' to 'dst'. | [
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] | def move_file (src, dst, verbose=1, dry_run=0):
"""Move a file 'src' to 'dst'.
If 'dst' is a directory, the file will be moved into it with the same
name; otherwise, 'src' is just renamed to 'dst'. Return the new
full name of the file.
Handles cross-device moves on Unix using 'copy_file()'. What about
other systems???
"""
from os.path import exists, isfile, isdir, basename, dirname
import errno
if verbose >= 1:
log.info("moving %s -> %s", src, dst)
if dry_run:
return dst
if not isfile(src):
raise DistutilsFileError("can't move '%s': not a regular file" % src)
if isdir(dst):
dst = os.path.join(dst, basename(src))
elif exists(dst):
raise DistutilsFileError(
"can't move '%s': destination '%s' already exists" %
(src, dst))
if not isdir(dirname(dst)):
raise DistutilsFileError(
"can't move '%s': destination '%s' not a valid path" % \
(src, dst))
copy_it = 0
try:
os.rename(src, dst)
except os.error, (num, msg):
if num == errno.EXDEV:
copy_it = 1
else:
raise DistutilsFileError(
"couldn't move '%s' to '%s': %s" % (src, dst, msg))
if copy_it:
copy_file(src, dst, verbose=verbose)
try:
os.unlink(src)
except os.error, (num, msg):
try:
os.unlink(dst)
except os.error:
pass
raise DistutilsFileError(
("couldn't move '%s' to '%s' by copy/delete: " +
"delete '%s' failed: %s") %
(src, dst, src, msg))
return dst | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/scipy/py3/scipy/stats/_multivariate.py | python | dirichlet_gen.var | (self, alpha) | return _squeeze_output(out) | Compute the variance of the dirichlet distribution.
Parameters
----------
%(_dirichlet_doc_default_callparams)s
Returns
-------
v : ndarray or scalar
Variance of the Dirichlet distribution. | Compute the variance of the dirichlet distribution. | [
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"""
Compute the variance of the dirichlet distribution.
Parameters
----------
%(_dirichlet_doc_default_callparams)s
Returns
-------
v : ndarray or scalar
Variance of the Dirichlet distribution.
"""
alpha = _dirichlet_check_parameters(alpha)
alpha0 = np.sum(alpha)
out = (alpha * (alpha0 - alpha)) / ((alpha0 * alpha0) * (alpha0 + 1))
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ApolloAuto/apollo-platform | 86d9dc6743b496ead18d597748ebabd34a513289 | ros/vision_opencv/image_geometry/src/image_geometry/cameramodels.py | python | PinholeCameraModel.getDeltaX | (self, deltaU, Z) | return Z * deltaU / fx | :param deltaU: delta u in pixels
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:type Z: float
:rtype: float
Compute delta X, given Z in cartesian space and delta u in pixels.
For given Z, this is the inverse of :meth:`getDeltaU`. | :param deltaU: delta u in pixels
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/msw/_misc.py | python | TimeSpan_Week | (*args) | return _misc_.TimeSpan_Week(*args) | TimeSpan_Week() -> TimeSpan | TimeSpan_Week() -> TimeSpan | [
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liulei01/DRBox | b5c76e033c555c9009590ab384e1f7bd3c66c237 | scripts/cpp_lint.py | python | CheckSpacingForFunctionCall | (filename, line, linenum, error) | Checks for the correctness of various spacing around function calls.
Args:
filename: The name of the current file.
line: The text of the line to check.
linenum: The number of the line to check.
error: The function to call with any errors found. | Checks for the correctness of various spacing around function calls. | [
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"""Checks for the correctness of various spacing around function calls.
Args:
filename: The name of the current file.
line: The text of the line to check.
linenum: The number of the line to check.
error: The function to call with any errors found.
"""
# Since function calls often occur inside if/for/while/switch
# expressions - which have their own, more liberal conventions - we
# first see if we should be looking inside such an expression for a
# function call, to which we can apply more strict standards.
fncall = line # if there's no control flow construct, look at whole line
for pattern in (r'\bif\s*\((.*)\)\s*{',
r'\bfor\s*\((.*)\)\s*{',
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break
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# " (something)(maybe-something)" or
# " (something)(maybe-something," or
# " (something)[something]"
# Note that we assume the contents of [] to be short enough that
# they'll never need to wrap.
if ( # Ignore control structures.
not Search(r'\b(if|for|while|switch|return|new|delete|catch|sizeof)\b',
fncall) and
# Ignore pointers/references to functions.
not Search(r' \([^)]+\)\([^)]*(\)|,$)', fncall) and
# Ignore pointers/references to arrays.
not Search(r' \([^)]+\)\[[^\]]+\]', fncall)):
if Search(r'\w\s*\(\s(?!\s*\\$)', fncall): # a ( used for a fn call
error(filename, linenum, 'whitespace/parens', 4,
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elif Search(r'\(\s+(?!(\s*\\)|\()', fncall):
error(filename, linenum, 'whitespace/parens', 2,
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if (Search(r'\w\s+\(', fncall) and
not Search(r'#\s*define|typedef', fncall) and
not Search(r'\w\s+\((\w+::)*\*\w+\)\(', fncall)):
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if Search(r'[^)]\s+\)\s*[^{\s]', fncall):
# If the closing parenthesis is preceded by only whitespaces,
# try to give a more descriptive error message.
if Search(r'^\s+\)', fncall):
error(filename, linenum, 'whitespace/parens', 2,
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else:
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||
tensorflow/tensorflow | 419e3a6b650ea4bd1b0cba23c4348f8a69f3272e | tensorflow/python/distribute/values.py | python | MirroredVariable._write_object_proto | (self, proto, options) | Update a SavedObject proto for the caller.
If a DistributedVariable object supports this method, it will be called when
saving with a pre-built `SavedObject` proto representing the object, plus an
instance of `SaveOptions`. This method is then free to modify that proto
instance.
`DistributedVariable` with `AUTO` or `ON_WRITE` synchronization optionally
write out information about their components to the
`experimental_distributed_variable_components` field of a
`SavedVariable` (depending on the `SaveOptions` variable policy).
Args:
proto: A pre-built `SavedObject` proto for this object. It is assumed this
will be a `SavedVariable` instance.
options: A `SaveOptions` instance. | Update a SavedObject proto for the caller. | [
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] | def _write_object_proto(self, proto, options):
"""Update a SavedObject proto for the caller.
If a DistributedVariable object supports this method, it will be called when
saving with a pre-built `SavedObject` proto representing the object, plus an
instance of `SaveOptions`. This method is then free to modify that proto
instance.
`DistributedVariable` with `AUTO` or `ON_WRITE` synchronization optionally
write out information about their components to the
`experimental_distributed_variable_components` field of a
`SavedVariable` (depending on the `SaveOptions` variable policy).
Args:
proto: A pre-built `SavedObject` proto for this object. It is assumed this
will be a `SavedVariable` instance.
options: A `SaveOptions` instance.
"""
super(MirroredVariable, self)._write_object_proto(proto, options)
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||
baidu/tera | dbcd28af792d879d961bf9fc7eb60de81b437646 | src/sdk/python/TeraSdk.py | python | Client.Close | (self) | 销毁这个client，释放底层资源，以后不得再使用这个对象 | 销毁这个client，释放底层资源，以后不得再使用这个对象 | [
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] | def Close(self):
"""
销毁这个client，释放底层资源，以后不得再使用这个对象
"""
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||
MegEngine/MegEngine | ce9ad07a27ec909fb8db4dd67943d24ba98fb93a | imperative/python/megengine/utils/network.py | python | NodeFilter.as_dict | (self) | return collections.OrderedDict((i.name, i) for i in self) | r"""construct an ordered dict to map from node names to objects in
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|
hanpfei/chromium-net | 392cc1fa3a8f92f42e4071ab6e674d8e0482f83f | third_party/catapult/third_party/gsutil/third_party/boto/boto/route53/connection.py | python | Route53Connection.create_zone | (self, name, private_zone=False,
vpc_id=None, vpc_region=None) | return Zone(self, zone['CreateHostedZoneResponse']['HostedZone']) | Create a new Hosted Zone. Returns a Zone object for the newly
created Hosted Zone.
:type name: str
:param name: The name of the domain. This should be a
fully-specified domain, and should end with a final period
as the last label indication. If you omit the final period,
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the Amazon Route 53 delegation servers returned in
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:param private_zone: Set True if creating a private hosted zone.
:type vpc_id: str
:param vpc_id: When creating a private hosted zone, the VPC Id to
associate to is required.
:type vpc_region: str
:param vpc_id: When creating a private hosted zone, the region of
the associated VPC is required. | Create a new Hosted Zone. Returns a Zone object for the newly
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"""
Create a new Hosted Zone. Returns a Zone object for the newly
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:type name: str
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zone = self.create_hosted_zone(name, private_zone=private_zone,
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|
y123456yz/reading-and-annotate-mongodb-3.6 | 93280293672ca7586dc24af18132aa61e4ed7fcf | mongo/buildscripts/idl/idl/errors.py | python | ParserError.__init__ | (self, error_id, msg, file_name, line, column) | Construct a parser error with source location information. | Construct a parser error with source location information. | [
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# type: (unicode, unicode, unicode, int, int) -> None
""""Construct a parser error with source location information."""
# pylint: disable=too-many-arguments
self.error_id = error_id
self.msg = msg
super(ParserError, self).__init__(file_name, line, column) | [
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MicBosi/VisualizationLibrary | d2a0e321288152008957e29a0bc270ad192f75be | src/external/freetype/src/tools/docmaker/tohtml.py | python | HtmlFormatter.make_html_word | ( self, word ) | return html_quote( word ) | analyze a simple word to detect cross-references and styling | analyze a simple word to detect cross-references and styling | [
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"""analyze a simple word to detect cross-references and styling"""
# look for cross-references
m = re_crossref.match( word )
if m:
try:
name = m.group( 1 )
rest = m.group( 2 )
block = self.identifiers[name]
url = self.make_block_url( block )
return '<a href="' + url + '">' + name + '</a>' + rest
except:
# we detected a cross-reference to an unknown item
sys.stderr.write( \
"WARNING: undefined cross reference '" + name + "'.\n" )
return '?' + name + '?' + rest
# look for italics and bolds
m = re_italic.match( word )
if m:
name = m.group( 1 )
rest = m.group( 3 )
return '<i>' + name + '</i>' + rest
m = re_bold.match( word )
if m:
name = m.group( 1 )
rest = m.group( 3 )
return '<b>' + name + '</b>' + rest
return html_quote( word ) | [
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|
hanpfei/chromium-net | 392cc1fa3a8f92f42e4071ab6e674d8e0482f83f | third_party/catapult/devil/devil/android/ports.py | python | IsDevicePortUsed | (device, device_port, state='') | return False | Checks whether the specified device port is used or not.
Args:
device: A DeviceUtils instance.
device_port: Port on device we want to check.
state: String of the specified state. Default is empty string, which
means any state.
Returns:
True if the port on device is already used, otherwise returns False. | Checks whether the specified device port is used or not. | [
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] | def IsDevicePortUsed(device, device_port, state=''):
"""Checks whether the specified device port is used or not.
Args:
device: A DeviceUtils instance.
device_port: Port on device we want to check.
state: String of the specified state. Default is empty string, which
means any state.
Returns:
True if the port on device is already used, otherwise returns False.
"""
base_urls = ('127.0.0.1:%d' % device_port, 'localhost:%d' % device_port)
netstat_results = device.RunShellCommand(
['netstat', '-a'], check_return=True, large_output=True)
for single_connect in netstat_results:
# Column 3 is the local address which we want to check with.
connect_results = single_connect.split()
if connect_results[0] != 'tcp':
continue
if len(connect_results) < 6:
raise Exception('Unexpected format while parsing netstat line: ' +
single_connect)
is_state_match = connect_results[5] == state if state else True
if connect_results[3] in base_urls and is_state_match:
return True
return False | [
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isl-org/Open3D | 79aec3ddde6a571ce2f28e4096477e52ec465244 | util/check_style.py | python | _glob_files | (directories, extensions) | return file_paths | Find files with certain extensions in directories recursively.
Args:
directories: list of directories, relative to the root Open3D repo directory.
extensions: list of extensions, e.g. ["cpp", "h"].
Return:
List of file paths. | Find files with certain extensions in directories recursively. | [
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] | def _glob_files(directories, extensions):
"""
Find files with certain extensions in directories recursively.
Args:
directories: list of directories, relative to the root Open3D repo directory.
extensions: list of extensions, e.g. ["cpp", "h"].
Return:
List of file paths.
"""
pwd = Path(os.path.dirname(os.path.abspath(__file__)))
open3d_root_dir = pwd.parent
file_paths = []
for directory in directories:
directory = open3d_root_dir / directory
for extension in extensions:
extension_regex = "*." + extension
file_paths.extend(directory.rglob(extension_regex))
file_paths = [str(file_path) for file_path in file_paths]
file_paths = sorted(list(set(file_paths)))
return file_paths | [
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|
aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/site-packages/botocore/retryhandler.py | python | delay_exponential | (base, growth_factor, attempts) | return time_to_sleep | Calculate time to sleep based on exponential function.
The format is::
base * growth_factor ^ (attempts - 1)
If ``base`` is set to 'rand' then a random number between
0 and 1 will be used as the base.
Base must be greater than 0, otherwise a ValueError will be
raised. | Calculate time to sleep based on exponential function. | [
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"function",
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] | def delay_exponential(base, growth_factor, attempts):
"""Calculate time to sleep based on exponential function.
The format is::
base * growth_factor ^ (attempts - 1)
If ``base`` is set to 'rand' then a random number between
0 and 1 will be used as the base.
Base must be greater than 0, otherwise a ValueError will be
raised.
"""
if base == 'rand':
base = random.random()
elif base <= 0:
raise ValueError("The 'base' param must be greater than 0, "
"got: %s" % base)
time_to_sleep = base * (growth_factor ** (attempts - 1))
return time_to_sleep | [
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|
NVIDIA/MDL-SDK | aa9642b2546ad7b6236b5627385d882c2ed83c5d | src/mdl/jit/llvm/dist/bindings/python/llvm/object.py | python | Symbol.address | (self) | return lib.LLVMGetSymbolAddress(self) | The address of this symbol, in long bytes. | The address of this symbol, in long bytes. | [
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"""The address of this symbol, in long bytes."""
if self.expired:
raise Exception('Symbol instance has expired.')
return lib.LLVMGetSymbolAddress(self) | [
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|
wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | wx/lib/agw/supertooltip.py | python | SuperToolTip.SetBodyImage | (self, bmp) | Sets the main body bitmap for :class:`SuperToolTip`.
:param `bmp`: the body bitmap, a valid :class:`Bitmap` object. | Sets the main body bitmap for :class:`SuperToolTip`. | [
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"""
Sets the main body bitmap for :class:`SuperToolTip`.
:param `bmp`: the body bitmap, a valid :class:`Bitmap` object.
"""
self._embeddedImage = bmp
if self._superToolTip:
self._superToolTip.Invalidate() | [
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openvinotoolkit/openvino | dedcbeafa8b84cccdc55ca64b8da516682b381c7 | thirdparty/itt_collector/runtool/sea_runtool.py | python | TaskCombiner.context_switch | (self, time, cpu, prev, next) | Called to process context switch events on CPU.
:param cpu: CPU number (int)
:param prev: previous task description (dict. Example: {'tid': 2935135, 'state': 'S', 'name': u'vtplay', 'prio': 31})
:param next: next task description (dict. see above) | Called to process context switch events on CPU.
:param cpu: CPU number (int)
:param prev: previous task description (dict. Example: {'tid': 2935135, 'state': 'S', 'name': u'vtplay', 'prio': 31})
:param next: next task description (dict. see above) | [
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"""
Called to process context switch events on CPU.
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:param prev: previous task description (dict. Example: {'tid': 2935135, 'state': 'S', 'name': u'vtplay', 'prio': 31})
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Xilinx/Vitis-AI | fc74d404563d9951b57245443c73bef389f3657f | tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/python/eager/function.py | python | Function._create_graph_function | (self, args, kwargs, override_flat_arg_shapes=None) | return graph_function | Create a `ConcreteFunction` from `args` and `kwargs`. | Create a `ConcreteFunction` from `args` and `kwargs`. | [
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"""Create a `ConcreteFunction` from `args` and `kwargs`."""
if self.input_signature is None:
arglen = len(args)
else:
arglen = len(self.input_signature)
base_arg_names = self._function_spec.arg_names[:arglen]
num_missing_args = arglen - len(self._function_spec.arg_names)
missing_arg_names = [self._function_spec.vararg_name] * num_missing_args
# Produce a list of missing args of the form ["arg_0", "arg_1", ...],
# where arg is based on the self._function_spec.vararg_name.
missing_arg_names = [
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]
arg_names = base_arg_names + missing_arg_names
graph_function = ConcreteFunction(
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self._name,
self._python_function,
args,
kwargs,
self.input_signature,
autograph=self._autograph,
autograph_options=self._autograph_options,
arg_names=arg_names,
override_flat_arg_shapes=override_flat_arg_shapes,
capture_by_value=self._capture_by_value),
self._function_attributes,
# Tell the ConcreteFunction to clean up its graph once it goes out of
# scope. This is not the default behavior since it gets used in some
# places (like Keras) where the FuncGraph lives longer than the
# ConcreteFunction.
shared_func_graph=False)
return graph_function | [
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|
sdhash/sdhash | b9eff63e4e5867e910f41fd69032bbb1c94a2a5e | sdhash-ui/cherrypy/_cpchecker.py | python | Checker._compat | (self, config) | Process config and warn on each obsolete or deprecated entry. | Process config and warn on each obsolete or deprecated entry. | [
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"""Process config and warn on each obsolete or deprecated entry."""
for section, conf in config.items():
if isinstance(conf, dict):
for k, v in conf.items():
if k in self.obsolete:
warnings.warn("%r is obsolete. Use %r instead.\n"
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(k, self.obsolete[k], section))
elif k in self.deprecated:
warnings.warn("%r is deprecated. Use %r instead.\n"
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else:
if section in self.obsolete:
warnings.warn("%r is obsolete. Use %r instead."
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cinder/Cinder | e83f5bb9c01a63eec20168d02953a0879e5100f7 | src/freetype/tools/glnames.py | python | dump_encoding | ( file, encoding_name, encoding_list ) | dump a given encoding | dump a given encoding | [
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"""dump a given encoding"""
write = file.write
write( " /* the following are indices into the SID name table */\n" )
write( "#ifndef DEFINE_PS_TABLES_DATA\n" )
write( "#ifdef __cplusplus\n" )
write( ' extern "C"\n' )
write( "#else\n" )
write( " extern\n" )
write( "#endif\n" )
write( "#endif\n" )
write( " const unsigned short " + encoding_name +
"[" + repr( len( encoding_list ) ) + "]\n" )
write( "#ifdef DEFINE_PS_TABLES_DATA\n" )
write( " =\n" )
write( " {\n" )
line = " "
comma = ""
col = 0
for value in encoding_list:
line += comma
line += "%3d" % value
comma = ","
col += 1
if col == 16:
col = 0
comma = ",\n "
write( line )
write( "\n" )
write( " }\n" )
write( "#endif /* DEFINE_PS_TABLES_DATA */\n" )
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||
aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/concurrent/futures/process.py | python | _sendback_result | (result_queue, work_id, result=None, exception=None) | Safely send back the given result or exception | Safely send back the given result or exception | [
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"exception"
] | def _sendback_result(result_queue, work_id, result=None, exception=None):
"""Safely send back the given result or exception"""
try:
result_queue.put(_ResultItem(work_id, result=result,
exception=exception))
except BaseException as e:
exc = _ExceptionWithTraceback(e, e.__traceback__)
result_queue.put(_ResultItem(work_id, exception=exc)) | [
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lfortran/lfortran | 6c96b79f5d86746cb2ec5acc86d4b0272ea34631 | grammar/asdl.py | python | parse | (filename) | Parse ASDL from the given file and return a Module node describing it. | Parse ASDL from the given file and return a Module node describing it. | [
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] | def parse(filename):
"""Parse ASDL from the given file and return a Module node describing it."""
with open(filename) as f:
parser = ASDLParser()
return parser.parse(f.read()) | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/tools/python/src/Lib/lib-tk/Tkinter.py | python | PanedWindow.__init__ | (self, master=None, cnf={}, **kw) | Construct a panedwindow widget with the parent MASTER.
STANDARD OPTIONS
background, borderwidth, cursor, height,
orient, relief, width
WIDGET-SPECIFIC OPTIONS
handlepad, handlesize, opaqueresize,
sashcursor, sashpad, sashrelief,
sashwidth, showhandle, | Construct a panedwindow widget with the parent MASTER. | [
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] | def __init__(self, master=None, cnf={}, **kw):
"""Construct a panedwindow widget with the parent MASTER.
STANDARD OPTIONS
background, borderwidth, cursor, height,
orient, relief, width
WIDGET-SPECIFIC OPTIONS
handlepad, handlesize, opaqueresize,
sashcursor, sashpad, sashrelief,
sashwidth, showhandle,
"""
Widget.__init__(self, master, 'panedwindow', cnf, kw) | [
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tensorflow/tensorflow | 419e3a6b650ea4bd1b0cba23c4348f8a69f3272e | tensorflow/python/keras/backend.py | python | sum | (x, axis=None, keepdims=False) | return math_ops.reduce_sum(x, axis, keepdims) | Sum of the values in a tensor, alongside the specified axis.
Args:
x: A tensor or variable.
axis: An integer, the axis to sum over.
keepdims: A boolean, whether to keep the dimensions or not.
If `keepdims` is `False`, the rank of the tensor is reduced
by 1. If `keepdims` is `True`,
the reduced dimension is retained with length 1.
Returns:
A tensor with sum of `x`. | Sum of the values in a tensor, alongside the specified axis. | [
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] | def sum(x, axis=None, keepdims=False):
"""Sum of the values in a tensor, alongside the specified axis.
Args:
x: A tensor or variable.
axis: An integer, the axis to sum over.
keepdims: A boolean, whether to keep the dimensions or not.
If `keepdims` is `False`, the rank of the tensor is reduced
by 1. If `keepdims` is `True`,
the reduced dimension is retained with length 1.
Returns:
A tensor with sum of `x`.
"""
return math_ops.reduce_sum(x, axis, keepdims) | [
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|
RobotLocomotion/drake | 0e18a34604c45ed65bc9018a54f7610f91cdad5b | tools/workspace/drake_visualizer/_drake_visualizer_builtin_scripts/show_hydroelastic_contact.py | python | _BodyContact.clean | (self, timestamp: int) | Removes all contacts that don't match the given timestamp. | Removes all contacts that don't match the given timestamp. | [
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] | def clean(self, timestamp: int):
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to_remove = []
for key, contact in self._contacts.items():
if contact.timestamp != timestamp:
contact.clear()
to_remove.append(key)
for key in to_remove:
del self._contacts[key]
if len(self) == 0:
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||
wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | wx/lib/agw/hypertreelist.py | python | TreeListHeaderWindow.SetCustomRenderer | (self, renderer=None) | Associate a custom renderer with the header - all columns will use it
:param `renderer`: a class able to correctly render header buttons
:note: the renderer class **must** implement the method `DrawHeaderButton` | Associate a custom renderer with the header - all columns will use it | [
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"""
Associate a custom renderer with the header - all columns will use it
:param `renderer`: a class able to correctly render header buttons
:note: the renderer class **must** implement the method `DrawHeaderButton`
"""
self._headerCustomRenderer = renderer | [
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tensorflow/tensorflow | 419e3a6b650ea4bd1b0cba23c4348f8a69f3272e | tensorflow/python/keras/engine/keras_tensor.py | python | KerasTensor.dtype | (self) | return self._type_spec._dtype | Returns the `dtype` symbolically inferred for this Keras output. | Returns the `dtype` symbolically inferred for this Keras output. | [
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"""Returns the `dtype` symbolically inferred for this Keras output."""
# TODO(kaftan): This is only valid for normal/sparse/ragged tensors.
# may need to raise an error when it's not valid for a type_spec,
# but some keras code (e.g. build-related stuff) will likely fail when
# it can't access shape or dtype
return self._type_spec._dtype | [
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OGRECave/ogre-next | 287307980e6de8910f04f3cc0994451b075071fd | Tools/BlenderExport/ogrepkg/base.py | python | Log.__init__ | (self) | return | Constructor. | Constructor. | [
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"""Constructor.
"""
Singleton.__init__(self)
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self.clear()
return | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/pandas/py2/pandas/io/sql.py | python | _wrap_result | (data, columns, index_col=None, coerce_float=True,
parse_dates=None) | return frame | Wrap result set of query in a DataFrame. | Wrap result set of query in a DataFrame. | [
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] | def _wrap_result(data, columns, index_col=None, coerce_float=True,
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"""Wrap result set of query in a DataFrame."""
frame = DataFrame.from_records(data, columns=columns,
coerce_float=coerce_float)
frame = _parse_date_columns(frame, parse_dates)
if index_col is not None:
frame.set_index(index_col, inplace=True)
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root-project/root | fcd3583bb14852bf2e8cd2415717cbaac0e75896 | main/python/cmdLineUtils.py | python | isTree | (rootFile,pathSplit) | Return True if the object, corresponding to (rootFile,pathSplit), inherits from TTree | Return True if the object, corresponding to (rootFile,pathSplit), inherits from TTree | [
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"""
Return True if the object, corresponding to (rootFile,pathSplit), inherits from TTree
"""
if pathSplit == []: return False # the object is the rootFile itself
else: return isTreeKey(getKey(rootFile,pathSplit)) | [
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] | https://github.com/root-project/root/blob/fcd3583bb14852bf2e8cd2415717cbaac0e75896/main/python/cmdLineUtils.py#L223-L228 |
||
SequoiaDB/SequoiaDB | 2894ed7e5bd6fe57330afc900cf76d0ff0df9f64 | driver/python/pysequoiadb/collectionspace.py | python | collectionspace.__getattr__ | (self, name) | support client.cs to access to collection.
eg.
cc = client()
cs = cc.test
cl = cs.test_cl # access to collection named 'test_cl'
and we should pass '__members__' and '__methods__',
becasue dir(cc) will invoke __getattr__("__members__") and
__getattr__("__methods__").
if success, a collection object will be returned.
Exceptions:
pysequoiadb.error.SDBBaseError | support client.cs to access to collection. | [
"support",
"client",
".",
"cs",
"to",
"access",
"to",
"collection",
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] | def __getattr__(self, name):
"""support client.cs to access to collection.
eg.
cc = client()
cs = cc.test
cl = cs.test_cl # access to collection named 'test_cl'
and we should pass '__members__' and '__methods__',
becasue dir(cc) will invoke __getattr__("__members__") and
__getattr__("__methods__").
if success, a collection object will be returned.
Exceptions:
pysequoiadb.error.SDBBaseError
"""
if '__members__' == name or '__methods__' == name:
pass
else:
cl = collection()
try:
rc = sdb.cs_get_collection(self._cs, name, cl._cl)
raise_if_error(rc, "Failed to get collection: %s" % name)
except SDBBaseError:
del cl
raise
return cl | [
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||
natanielruiz/android-yolo | 1ebb54f96a67a20ff83ddfc823ed83a13dc3a47f | jni-build/jni/include/tensorflow/models/rnn/translate/translate.py | python | self_test | () | Test the translation model. | Test the translation model. | [
"Test",
"the",
"translation",
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] | def self_test():
"""Test the translation model."""
with tf.Session() as sess:
print("Self-test for neural translation model.")
# Create model with vocabularies of 10, 2 small buckets, 2 layers of 32.
model = seq2seq_model.Seq2SeqModel(10, 10, [(3, 3), (6, 6)], 32, 2,
5.0, 32, 0.3, 0.99, num_samples=8)
sess.run(tf.initialize_all_variables())
# Fake data set for both the (3, 3) and (6, 6) bucket.
data_set = ([([1, 1], [2, 2]), ([3, 3], [4]), ([5], [6])],
[([1, 1, 1, 1, 1], [2, 2, 2, 2, 2]), ([3, 3, 3], [5, 6])])
for _ in xrange(5): # Train the fake model for 5 steps.
bucket_id = random.choice([0, 1])
encoder_inputs, decoder_inputs, target_weights = model.get_batch(
data_set, bucket_id)
model.step(sess, encoder_inputs, decoder_inputs, target_weights,
bucket_id, False) | [
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||
deepmind/open_spiel | 4ca53bea32bb2875c7385d215424048ae92f78c8 | open_spiel/python/jax/nfsp.py | python | ReservoirBuffer.sample | (self, num_samples) | return random.sample(self._data, num_samples) | Returns `num_samples` uniformly sampled from the buffer.
Args:
num_samples: `int`, number of samples to draw.
Returns:
An iterable over `num_samples` random elements of the buffer.
Raises:
ValueError: If there are less than `num_samples` elements in the buffer | Returns `num_samples` uniformly sampled from the buffer. | [
"Returns",
"num_samples",
"uniformly",
"sampled",
"from",
"the",
"buffer",
"."
] | def sample(self, num_samples):
"""Returns `num_samples` uniformly sampled from the buffer.
Args:
num_samples: `int`, number of samples to draw.
Returns:
An iterable over `num_samples` random elements of the buffer.
Raises:
ValueError: If there are less than `num_samples` elements in the buffer
"""
if len(self._data) < num_samples:
raise ValueError("{} elements could not be sampled from size {}".format(
num_samples, len(self._data)))
return random.sample(self._data, num_samples) | [
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|
cms-sw/cmssw | fd9de012d503d3405420bcbeec0ec879baa57cf2 | Configuration/PyReleaseValidation/python/relval_machine.py | python | convert_keys_to_string | (dictionary) | Recursively converts dictionary keys to strings.
Utility to help deal with unicode keys in dictionaries created from json requests.
In order to pass dict to function as **kwarg we should transform key/value to str. | Recursively converts dictionary keys to strings.
Utility to help deal with unicode keys in dictionaries created from json requests.
In order to pass dict to function as **kwarg we should transform key/value to str. | [
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] | def convert_keys_to_string(dictionary):
""" Recursively converts dictionary keys to strings.
Utility to help deal with unicode keys in dictionaries created from json requests.
In order to pass dict to function as **kwarg we should transform key/value to str.
"""
if isinstance(dictionary, str):
return str(dictionary)
elif isinstance(dictionary, collections.Mapping):
return dict(map(convert_keys_to_string, dictionary.items()))
elif isinstance(dictionary, collections.Iterable):
return type(dictionary)(map(convert_keys_to_string, dictionary))
else:
return dictionary | [
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||
okex/V3-Open-API-SDK | c5abb0db7e2287718e0055e17e57672ce0ec7fd9 | okex-python-sdk-api/venv/Lib/site-packages/pip-19.0.3-py3.8.egg/pip/_vendor/cachecontrol/controller.py | python | CacheController._urlnorm | (cls, uri) | return defrag_uri | Normalize the URL to create a safe key for the cache | Normalize the URL to create a safe key for the cache | [
"Normalize",
"the",
"URL",
"to",
"create",
"a",
"safe",
"key",
"for",
"the",
"cache"
] | def _urlnorm(cls, uri):
"""Normalize the URL to create a safe key for the cache"""
(scheme, authority, path, query, fragment) = parse_uri(uri)
if not scheme or not authority:
raise Exception("Only absolute URIs are allowed. uri = %s" % uri)
scheme = scheme.lower()
authority = authority.lower()
if not path:
path = "/"
# Could do syntax based normalization of the URI before
# computing the digest. See Section 6.2.2 of Std 66.
request_uri = query and "?".join([path, query]) or path
defrag_uri = scheme + "://" + authority + request_uri
return defrag_uri | [
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|
plumonito/dtslam | 5994bb9cf7a11981b830370db206bceb654c085d | 3rdparty/opencv-git/doc/pattern_tools/svgfig.py | python | Frame.__init__ | (self, xmin, xmax, ymin, ymax, *d, **kwds) | Acts like Fig, but draws a coordinate frame around the data. You also need to supply plot ranges.
Frame(xmin, xmax, ymin, ymax, obj, obj, obj..., keyword options...)
xmin, xmax required minimum and maximum x values (in the objs' coordinates)
ymin, ymax required minimum and maximum y values (in the objs' coordinates)
obj optional list drawing primitives
keyword options keyword list options defined below
The following are keyword options, with their default values:
x, y 20, 5 upper-left corner of the Frame in SVG coordinates
width, height 75, 80 width and height of the Frame in SVG coordinates
flipx, flipy False, True flip the sign of the coordinate axis
minusInfinity -1000 if an axis is logarithmic and an object is plotted at 0 or
a negative value, -1000 will be used as a stand-in for NaN
xtitle None if a string, label the x axis
xticks -10 request ticks according to the standard tick specification
(see help(Ticks))
xminiticks True request miniticks according to the standard minitick
specification
xlabels True request tick labels according to the standard tick label
specification
xlogbase None if a number, the axis and transformation are logarithmic
with ticks at the given base (10 being the most common)
(same for y)
text_attr {} a dictionary of attributes for label text
axis_attr {} a dictionary of attributes for the axis lines | Acts like Fig, but draws a coordinate frame around the data. You also need to supply plot ranges. | [
"Acts",
"like",
"Fig",
"but",
"draws",
"a",
"coordinate",
"frame",
"around",
"the",
"data",
".",
"You",
"also",
"need",
"to",
"supply",
"plot",
"ranges",
"."
] | def __init__(self, xmin, xmax, ymin, ymax, *d, **kwds):
"""Acts like Fig, but draws a coordinate frame around the data. You also need to supply plot ranges.
Frame(xmin, xmax, ymin, ymax, obj, obj, obj..., keyword options...)
xmin, xmax required minimum and maximum x values (in the objs' coordinates)
ymin, ymax required minimum and maximum y values (in the objs' coordinates)
obj optional list drawing primitives
keyword options keyword list options defined below
The following are keyword options, with their default values:
x, y 20, 5 upper-left corner of the Frame in SVG coordinates
width, height 75, 80 width and height of the Frame in SVG coordinates
flipx, flipy False, True flip the sign of the coordinate axis
minusInfinity -1000 if an axis is logarithmic and an object is plotted at 0 or
a negative value, -1000 will be used as a stand-in for NaN
xtitle None if a string, label the x axis
xticks -10 request ticks according to the standard tick specification
(see help(Ticks))
xminiticks True request miniticks according to the standard minitick
specification
xlabels True request tick labels according to the standard tick label
specification
xlogbase None if a number, the axis and transformation are logarithmic
with ticks at the given base (10 being the most common)
(same for y)
text_attr {} a dictionary of attributes for label text
axis_attr {} a dictionary of attributes for the axis lines
"""
self.xmin, self.xmax, self.ymin, self.ymax = xmin, xmax, ymin, ymax
self.d = list(d)
defaults = {"x": 20, "y": 5, "width": 75, "height": 80,
"flipx": False, "flipy": True, "minusInfinity": -1000,
"xtitle": None, "xticks": -10, "xminiticks": True, "xlabels": True,
"x2labels": None, "xlogbase": None,
"ytitle": None, "yticks": -10, "yminiticks": True, "ylabels": True,
"y2labels": None, "ylogbase": None,
"text_attr": {}, "axis_attr": {},
}
defaults.update(kwds)
kwds = defaults
self.x = kwds["x"]; del kwds["x"]
self.y = kwds["y"]; del kwds["y"]
self.width = kwds["width"]; del kwds["width"]
self.height = kwds["height"]; del kwds["height"]
self.flipx = kwds["flipx"]; del kwds["flipx"]
self.flipy = kwds["flipy"]; del kwds["flipy"]
self.minusInfinity = kwds["minusInfinity"]; del kwds["minusInfinity"]
self.xtitle = kwds["xtitle"]; del kwds["xtitle"]
self.xticks = kwds["xticks"]; del kwds["xticks"]
self.xminiticks = kwds["xminiticks"]; del kwds["xminiticks"]
self.xlabels = kwds["xlabels"]; del kwds["xlabels"]
self.x2labels = kwds["x2labels"]; del kwds["x2labels"]
self.xlogbase = kwds["xlogbase"]; del kwds["xlogbase"]
self.ytitle = kwds["ytitle"]; del kwds["ytitle"]
self.yticks = kwds["yticks"]; del kwds["yticks"]
self.yminiticks = kwds["yminiticks"]; del kwds["yminiticks"]
self.ylabels = kwds["ylabels"]; del kwds["ylabels"]
self.y2labels = kwds["y2labels"]; del kwds["y2labels"]
self.ylogbase = kwds["ylogbase"]; del kwds["ylogbase"]
self.text_attr = dict(self.text_defaults)
self.text_attr.update(kwds["text_attr"]); del kwds["text_attr"]
self.axis_attr = dict(self.axis_defaults)
self.axis_attr.update(kwds["axis_attr"]); del kwds["axis_attr"]
if len(kwds) != 0:
raise TypeError, "Frame() got unexpected keyword arguments %s" % kwds.keys() | [
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||
opencv/opencv | 76aff8478883858f0e46746044348ebb16dc3c67 | samples/dnn/speech_recognition.py | python | FilterbankFeatures.frame | (self, x, frame_length, hop_length) | return np.lib.stride_tricks.as_strided(x, shape=shape, strides=strides) | Slices a data array into (overlapping) frames.
args:
x : array to frame
frame_length : length of frame
hop_length : Number of steps to advance between frames
return : A framed view of `x` | Slices a data array into (overlapping) frames.
args:
x : array to frame
frame_length : length of frame
hop_length : Number of steps to advance between frames
return : A framed view of `x` | [
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args:
x : array to frame
frame_length : length of frame
hop_length : Number of steps to advance between frames
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'''
if x.shape[-1] < frame_length:
raise Exception(
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" for frame_length={:d}".format(x.shape[-1], frame_length)
)
x = np.asfortranarray(x)
n_frames = 1 + (x.shape[-1] - frame_length) // hop_length
strides = np.asarray(x.strides)
new_stride = np.prod(strides[strides > 0] // x.itemsize) * x.itemsize
shape = list(x.shape)[:-1] + [frame_length, n_frames]
strides = list(strides) + [hop_length * new_stride]
return np.lib.stride_tricks.as_strided(x, shape=shape, strides=strides) | [
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|
BlzFans/wke | b0fa21158312e40c5fbd84682d643022b6c34a93 | cygwin/lib/python2.6/pydoc.py | python | HTMLDoc.docother | (self, object, name=None, mod=None, *ignored) | return lhs + self.repr(object) | Produce HTML documentation for a data object. | Produce HTML documentation for a data object. | [
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] | def docother(self, object, name=None, mod=None, *ignored):
"""Produce HTML documentation for a data object."""
lhs = name and '<strong>%s</strong> = ' % name or ''
return lhs + self.repr(object) | [
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openthread/openthread | 9fcdbed9c526c70f1556d1ed84099c1535c7cd32 | tools/otci/otci/otci.py | python | OTCI.dns_set_config | (self,
server: Tuple[Union[str, ipaddress.IPv6Address], int],
response_timeout: int = None,
max_tx_attempts: int = None,
recursion_desired: bool = None) | Set DNS client query config. | Set DNS client query config. | [
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server: Tuple[Union[str, ipaddress.IPv6Address], int],
response_timeout: int = None,
max_tx_attempts: int = None,
recursion_desired: bool = None):
"""Set DNS client query config."""
cmd = f'dns config {str(server[0])} {server[1]}'
if response_timeout is not None:
cmd += f' {response_timeout}'
assert max_tx_attempts is None or response_timeout is not None, "must specify `response_timeout` if `max_tx_attempts` is specified."
if max_tx_attempts is not None:
cmd += f' {max_tx_attempts}'
assert recursion_desired is None or max_tx_attempts is not None, 'must specify `max_tx_attempts` if `recursion_desired` is specified.'
if recursion_desired is not None:
cmd += f' {1 if recursion_desired else 0}'
self.execute_command(cmd) | [
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||
catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/scipy/py2/scipy/signal/signaltools.py | python | sosfiltfilt | (sos, x, axis=-1, padtype='odd', padlen=None) | return y | A forward-backward digital filter using cascaded second-order sections.
See `filtfilt` for more complete information about this method.
Parameters
----------
sos : array_like
Array of second-order filter coefficients, must have shape
``(n_sections, 6)``. Each row corresponds to a second-order
section, with the first three columns providing the numerator
coefficients and the last three providing the denominator
coefficients.
x : array_like
The array of data to be filtered.
axis : int, optional
The axis of `x` to which the filter is applied.
Default is -1.
padtype : str or None, optional
Must be 'odd', 'even', 'constant', or None. This determines the
type of extension to use for the padded signal to which the filter
is applied. If `padtype` is None, no padding is used. The default
is 'odd'.
padlen : int or None, optional
The number of elements by which to extend `x` at both ends of
`axis` before applying the filter. This value must be less than
``x.shape[axis] - 1``. ``padlen=0`` implies no padding.
The default value is::
3 * (2 * len(sos) + 1 - min((sos[:, 2] == 0).sum(),
(sos[:, 5] == 0).sum()))
The extra subtraction at the end attempts to compensate for poles
and zeros at the origin (e.g. for odd-order filters) to yield
equivalent estimates of `padlen` to those of `filtfilt` for
second-order section filters built with `scipy.signal` functions.
Returns
-------
y : ndarray
The filtered output with the same shape as `x`.
See Also
--------
filtfilt, sosfilt, sosfilt_zi, sosfreqz
Notes
-----
.. versionadded:: 0.18.0
Examples
--------
>>> from scipy.signal import sosfiltfilt, butter
>>> import matplotlib.pyplot as plt
Create an interesting signal to filter.
>>> n = 201
>>> t = np.linspace(0, 1, n)
>>> np.random.seed(123)
>>> x = 1 + (t < 0.5) - 0.25*t**2 + 0.05*np.random.randn(n)
Create a lowpass Butterworth filter, and use it to filter `x`.
>>> sos = butter(4, 0.125, output='sos')
>>> y = sosfiltfilt(sos, x)
For comparison, apply an 8th order filter using `sosfilt`. The filter
is initialized using the mean of the first four values of `x`.
>>> from scipy.signal import sosfilt, sosfilt_zi
>>> sos8 = butter(8, 0.125, output='sos')
>>> zi = x[:4].mean() * sosfilt_zi(sos8)
>>> y2, zo = sosfilt(sos8, x, zi=zi)
Plot the results. Note that the phase of `y` matches the input, while
`y2` has a significant phase delay.
>>> plt.plot(t, x, alpha=0.5, label='x(t)')
>>> plt.plot(t, y, label='y(t)')
>>> plt.plot(t, y2, label='y2(t)')
>>> plt.legend(framealpha=1, shadow=True)
>>> plt.grid(alpha=0.25)
>>> plt.xlabel('t')
>>> plt.show() | A forward-backward digital filter using cascaded second-order sections. | [
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"""
A forward-backward digital filter using cascaded second-order sections.
See `filtfilt` for more complete information about this method.
Parameters
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The extra subtraction at the end attempts to compensate for poles
and zeros at the origin (e.g. for odd-order filters) to yield
equivalent estimates of `padlen` to those of `filtfilt` for
second-order section filters built with `scipy.signal` functions.
Returns
-------
y : ndarray
The filtered output with the same shape as `x`.
See Also
--------
filtfilt, sosfilt, sosfilt_zi, sosfreqz
Notes
-----
.. versionadded:: 0.18.0
Examples
--------
>>> from scipy.signal import sosfiltfilt, butter
>>> import matplotlib.pyplot as plt
Create an interesting signal to filter.
>>> n = 201
>>> t = np.linspace(0, 1, n)
>>> np.random.seed(123)
>>> x = 1 + (t < 0.5) - 0.25*t**2 + 0.05*np.random.randn(n)
Create a lowpass Butterworth filter, and use it to filter `x`.
>>> sos = butter(4, 0.125, output='sos')
>>> y = sosfiltfilt(sos, x)
For comparison, apply an 8th order filter using `sosfilt`. The filter
is initialized using the mean of the first four values of `x`.
>>> from scipy.signal import sosfilt, sosfilt_zi
>>> sos8 = butter(8, 0.125, output='sos')
>>> zi = x[:4].mean() * sosfilt_zi(sos8)
>>> y2, zo = sosfilt(sos8, x, zi=zi)
Plot the results. Note that the phase of `y` matches the input, while
`y2` has a significant phase delay.
>>> plt.plot(t, x, alpha=0.5, label='x(t)')
>>> plt.plot(t, y, label='y(t)')
>>> plt.plot(t, y2, label='y2(t)')
>>> plt.legend(framealpha=1, shadow=True)
>>> plt.grid(alpha=0.25)
>>> plt.xlabel('t')
>>> plt.show()
"""
sos, n_sections = _validate_sos(sos)
# `method` is "pad"...
ntaps = 2 * n_sections + 1
ntaps -= min((sos[:, 2] == 0).sum(), (sos[:, 5] == 0).sum())
edge, ext = _validate_pad(padtype, padlen, x, axis,
ntaps=ntaps)
# These steps follow the same form as filtfilt with modifications
zi = sosfilt_zi(sos) # shape (n_sections, 2) --> (n_sections, ..., 2, ...)
zi_shape = [1] * x.ndim
zi_shape[axis] = 2
zi.shape = [n_sections] + zi_shape
x_0 = axis_slice(ext, stop=1, axis=axis)
(y, zf) = sosfilt(sos, ext, axis=axis, zi=zi * x_0)
y_0 = axis_slice(y, start=-1, axis=axis)
(y, zf) = sosfilt(sos, axis_reverse(y, axis=axis), axis=axis, zi=zi * y_0)
y = axis_reverse(y, axis=axis)
if edge > 0:
y = axis_slice(y, start=edge, stop=-edge, axis=axis)
return y | [
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|
echronos/echronos | c996f1d2c8af6c6536205eb319c1bf1d4d84569c | external_tools/ply_info/example/BASIC/basparse.py | python | p_number | (p) | number : INTEGER
| FLOAT | number : INTEGER
| FLOAT | [
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":",
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'''number : INTEGER
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p[0] = eval(p[1]) | [
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windystrife/UnrealEngine_NVIDIAGameWorks | b50e6338a7c5b26374d66306ebc7807541ff815e | Engine/Extras/ThirdPartyNotUE/emsdk/Win64/python/2.7.5.3_64bit/Lib/site-packages/pip/commands/search.py | python | transform_hits | (hits) | return package_list | The list from pypi is really a list of versions. We want a list of
packages with the list of versions stored inline. This converts the
list from pypi into one we can use. | The list from pypi is really a list of versions. We want a list of
packages with the list of versions stored inline. This converts the
list from pypi into one we can use. | [
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"""
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"""
packages = {}
for hit in hits:
name = hit['name']
summary = hit['summary']
version = hit['version']
score = hit['_pypi_ordering']
if score is None:
score = 0
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packages[name] = {'name': name, 'summary': summary, 'versions': [version], 'score': score}
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packages[name]['summary'] = summary
packages[name]['score'] = score
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package_list = sorted(packages.values(), key=lambda x: x['score'], reverse=True)
return package_list | [
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|
miyosuda/TensorFlowAndroidDemo | 35903e0221aa5f109ea2dbef27f20b52e317f42d | jni-build/jni/include/tensorflow/contrib/learn/python/learn/estimators/base.py | python | TensorFlowEstimator.save | (self, path) | Saves checkpoints and graph to given path.
Args:
path: Folder to save model to. | Saves checkpoints and graph to given path. | [
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"""Saves checkpoints and graph to given path.
Args:
path: Folder to save model to.
"""
if self._graph is None:
raise NotFittedError
# Copy model dir into new path.
_copy_dir(self.model_dir, path)
# Save model definition.
all_params = self.get_params()
params = {}
for key, value in all_params.items():
if not callable(value) and value is not None:
params[key] = value
params['class_name'] = type(self).__name__
model_def = json.dumps(
params,
default=lambda o: o.__dict__ if hasattr(o, '__dict__') else None)
_write_with_backup(os.path.join(path, 'model.def'), model_def) | [
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||
vslavik/poedit | f7a9daa0a10037e090aa0a86f5ce0f24ececdf6a | deps/boost/libs/metaparse/tools/benchmark/generate.py | python | Mode.description | (self) | The description of the mode | The description of the mode | [
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] | def description(self):
"""The description of the mode"""
if self.identifier == 'bmp':
return 'Using BOOST_METAPARSE_STRING'
elif self.identifier == 'man':
return 'Generating strings manually' | [
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||
windystrife/UnrealEngine_NVIDIAGameWorks | b50e6338a7c5b26374d66306ebc7807541ff815e | Engine/Extras/ThirdPartyNotUE/emsdk/Win64/python/2.7.5.3_64bit/Lib/popen2.py | python | Popen3.__init__ | (self, cmd, capturestderr=False, bufsize=-1) | The parameter 'cmd' is the shell command to execute in a
sub-process. On UNIX, 'cmd' may be a sequence, in which case arguments
will be passed directly to the program without shell intervention (as
with os.spawnv()). If 'cmd' is a string it will be passed to the shell
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that the object should capture standard error output of the child
process. The default is false. If the 'bufsize' parameter is
specified, it specifies the size of the I/O buffers to/from the child
process. | The parameter 'cmd' is the shell command to execute in a
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will be passed directly to the program without shell intervention (as
with os.spawnv()). If 'cmd' is a string it will be passed to the shell
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that the object should capture standard error output of the child
process. The default is false. If the 'bufsize' parameter is
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will be passed directly to the program without shell intervention (as
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specified, it specifies the size of the I/O buffers to/from the child
process."""
_cleanup()
self.cmd = cmd
p2cread, p2cwrite = os.pipe()
c2pread, c2pwrite = os.pipe()
if capturestderr:
errout, errin = os.pipe()
self.pid = os.fork()
if self.pid == 0:
# Child
os.dup2(p2cread, 0)
os.dup2(c2pwrite, 1)
if capturestderr:
os.dup2(errin, 2)
self._run_child(cmd)
os.close(p2cread)
self.tochild = os.fdopen(p2cwrite, 'w', bufsize)
os.close(c2pwrite)
self.fromchild = os.fdopen(c2pread, 'r', bufsize)
if capturestderr:
os.close(errin)
self.childerr = os.fdopen(errout, 'r', bufsize)
else:
self.childerr = None | [
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||
adobe/chromium | cfe5bf0b51b1f6b9fe239c2a3c2f2364da9967d7 | tools/valgrind/suppressions.py | python | GlobToRegex | (glob_pattern, ignore_case=False) | return ''.join(regex) | Translate glob wildcards (*?) into regex syntax. Escape the rest. | Translate glob wildcards (*?) into regex syntax. Escape the rest. | [
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] | def GlobToRegex(glob_pattern, ignore_case=False):
"""Translate glob wildcards (*?) into regex syntax. Escape the rest."""
regex = ''
for char in glob_pattern:
if char == '*':
regex += '.*'
elif char == '?':
regex += '.'
elif ignore_case and char.isalpha():
regex += '[%s%s]' % (char.lower(), char.upper())
else:
regex += re.escape(char)
return ''.join(regex) | [
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|
apache/mesos | 97d9a4063332aae3825d78de71611657e05cf5e2 | support/cpplint.py | python | ProcessGlobalSuppresions | (lines) | Updates the list of global error suppressions.
Parses any lint directives in the file that have global effect.
Args:
lines: An array of strings, each representing a line of the file, with the
last element being empty if the file is terminated with a newline. | Updates the list of global error suppressions. | [
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] | def ProcessGlobalSuppresions(lines):
"""Updates the list of global error suppressions.
Parses any lint directives in the file that have global effect.
Args:
lines: An array of strings, each representing a line of the file, with the
last element being empty if the file is terminated with a newline.
"""
for line in lines:
if _SEARCH_C_FILE.search(line):
for category in _DEFAULT_C_SUPPRESSED_CATEGORIES:
_global_error_suppressions[category] = True
if _SEARCH_KERNEL_FILE.search(line):
for category in _DEFAULT_KERNEL_SUPPRESSED_CATEGORIES:
_global_error_suppressions[category] = True | [
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||
mapnik/mapnik | f3da900c355e1d15059c4a91b00203dcc9d9f0ef | scons/scons-local-4.1.0/SCons/Node/__init__.py | python | Node.is_literal | (self) | return 1 | Always pass the string representation of a Node to
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"""Always pass the string representation of a Node to
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return 1 | [
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|
gem5/gem5 | 141cc37c2d4b93959d4c249b8f7e6a8b2ef75338 | ext/ply/example/calc/calc.py | python | p_statement_expr | (p) | statement : expression | statement : expression | [
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||
google/nucleus | 68d3947fafba1337f294c0668a6e1c7f3f1273e3 | nucleus/io/bedgraph.py | python | NativeBedGraphReader.query | (self) | Returns an iterator for going through the records in the region.
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||
cinder/Cinder | e83f5bb9c01a63eec20168d02953a0879e5100f7 | docs/generateDocs.py | python | process_ci_prefix_tag | (bs4, tag, in_path) | Finds the referenced tag's object if existent and adds the path to the prefix file to the class to be parsed later
:param tag: The ci tag with a defined prefix attribute
:param in_path: The path to the refix content
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] | def process_ci_prefix_tag(bs4, tag, in_path):
"""
Finds the referenced tag's object if existent and adds the path to the prefix file to the class to be parsed later
:param tag: The ci tag with a defined prefix attribute
:param in_path: The path to the refix content
:return:
"""
in_path = in_path.replace('\\', '/')
in_dir = get_path_dir(in_path)
obj_ref = find_ci_tag_ref(tag)
if obj_ref and type(obj_ref) is SymbolMap.Class:
# get tag content
prefix_content = ""
for c in tag.contents:
content = c.encode("utf-8", errors="replace")
prefix_content += content
# generate bs4 from content and update links as reltive from the template path
# could alternatively set the absolute paths of content, which would then be turned into rel paths later
new_bs4 = generate_bs4_from_string(prefix_content)
update_links(new_bs4, in_dir, in_path, TEMPLATE_PATH)
# get updated body content and assign as prefix_content
prefix_content = ""
for c in new_bs4.body:
content = c.encode("utf-8", errors="replace")
prefix_content += content
obj_ref.define_prefix(prefix_content) | [
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||
tensorflow/tensorflow | 419e3a6b650ea4bd1b0cba23c4348f8a69f3272e | tensorflow/python/keras/engine/compile_utils.py | python | MetricsContainer._get_metric_objects | (self, metrics, y_t, y_p) | return [self._get_metric_object(m, y_t, y_p) for m in metrics] | Convert user-supplied metrics to `Metric` objects. | Convert user-supplied metrics to `Metric` objects. | [
"Convert",
"user",
"-",
"supplied",
"metrics",
"to",
"Metric",
"objects",
"."
] | def _get_metric_objects(self, metrics, y_t, y_p):
"""Convert user-supplied metrics to `Metric` objects."""
metrics = nest.flatten(metrics)
return [self._get_metric_object(m, y_t, y_p) for m in metrics] | [
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|
windystrife/UnrealEngine_NVIDIAGameWorks | b50e6338a7c5b26374d66306ebc7807541ff815e | Engine/Extras/ThirdPartyNotUE/emsdk/Win64/python/2.7.5.3_64bit/Lib/cookielib.py | python | time2netscape | (t=None) | return "%s %02d-%s-%04d %02d:%02d:%02d GMT" % (
DAYS[wday], mday, MONTHS[mon-1], year, hour, min, sec) | Return a string representing time in seconds since epoch, t.
If the function is called without an argument, it will use the current
time.
The format of the returned string is like this:
Wed, DD-Mon-YYYY HH:MM:SS GMT | Return a string representing time in seconds since epoch, t. | [
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] | def time2netscape(t=None):
"""Return a string representing time in seconds since epoch, t.
If the function is called without an argument, it will use the current
time.
The format of the returned string is like this:
Wed, DD-Mon-YYYY HH:MM:SS GMT
"""
if t is None: t = time.time()
year, mon, mday, hour, min, sec, wday = time.gmtime(t)[:7]
return "%s %02d-%s-%04d %02d:%02d:%02d GMT" % (
DAYS[wday], mday, MONTHS[mon-1], year, hour, min, sec) | [
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|
apple/swift-lldb | d74be846ef3e62de946df343e8c234bde93a8912 | utils/vim-lldb/python-vim-lldb/vim_ui.py | python | UI.hideWindow | (self, name) | return True | Hides window pane specified by name | Hides window pane specified by name | [
"Hides",
"window",
"pane",
"specified",
"by",
"name"
] | def hideWindow(self, name):
""" Hides window pane specified by name """
if not self.paneCol.havePane(name):
sys.stderr.write("unknown window: %s" % name)
return False
self.paneCol.hide([name])
return True | [
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|
google/certificate-transparency | 2588562fd306a447958471b6f06c1069619c1641 | python/ct/crypto/asn1/types.py | python | Any._convert_value | (cls, value) | The value of an Any is the undecoded value. | The value of an Any is the undecoded value. | [
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] | def _convert_value(cls, value):
"""The value of an Any is the undecoded value."""
# Always return the undecoded value for consistency; the
# decoded/decoded_value properties can be used to retrieve the
# decoded contents.
if isinstance(value, Any):
# This gets ambiguous real fast (do we keep the original tags or
# replace with our own tags?) so we ban it.
raise TypeError("Instantiating Any from another Any is illegal")
elif isinstance(value, Abstract):
return value.encode()
else:
raise TypeError("Cannot convert %s to %s" % (type(value),
cls.__name__)) | [
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||
pytorch/ELF | e851e786ced8d26cf470f08a6b9bf7e413fc63f7 | src_py/rlpytorch/sampler/sample_methods.py | python | epsilon_greedy | (state_curr, args, node="pi") | return sample_multinomial(state_curr, args, node=node, greedy=True) | epsilon greedy sampling
Args:
state_curr(dict): current state containing all data
args(dict): customized arguments for sampling. `epsilon` is used
node(str): name string for policy, default is "pi"
Returns:
A list of actions using epsilon greedy sampling. | epsilon greedy sampling | [
"epsilon",
"greedy",
"sampling"
] | def epsilon_greedy(state_curr, args, node="pi"):
''' epsilon greedy sampling
Args:
state_curr(dict): current state containing all data
args(dict): customized arguments for sampling. `epsilon` is used
node(str): name string for policy, default is "pi"
Returns:
A list of actions using epsilon greedy sampling.
'''
return sample_multinomial(state_curr, args, node=node, greedy=True) | [
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|
ricardoquesada/Spidermonkey | 4a75ea2543408bd1b2c515aa95901523eeef7858 | python/mozbuild/mozbuild/frontend/sandbox.py | python | Sandbox.__init__ | (self, context, builtins=None) | Initialize a Sandbox ready for execution. | Initialize a Sandbox ready for execution. | [
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] | def __init__(self, context, builtins=None):
"""Initialize a Sandbox ready for execution.
"""
self._builtins = builtins or self.BUILTINS
dict.__setitem__(self, '__builtins__', self._builtins)
assert isinstance(self._builtins, ReadOnlyDict)
assert isinstance(context, Context)
self._context = context
self._execution_stack = []
# We need to record this because it gets swallowed as part of
# evaluation.
self._last_name_error = None | [
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||
raymondlu/super-animation-samples | 04234269112ff0dc32447f27a761dbbb00b8ba17 | samples/cocos2d-x-3.1/CocosLuaGame2/frameworks/cocos2d-x/tools/bindings-generator/generator.py | python | build_namespace | (cursor, namespaces=[]) | return namespaces | build the full namespace for a specific cursor | build the full namespace for a specific cursor | [
"build",
"the",
"full",
"namespace",
"for",
"a",
"specific",
"cursor"
] | def build_namespace(cursor, namespaces=[]):
'''
build the full namespace for a specific cursor
'''
if cursor:
parent = cursor.semantic_parent
if parent:
if parent.kind == cindex.CursorKind.NAMESPACE or parent.kind == cindex.CursorKind.CLASS_DECL:
namespaces.append(parent.displayname)
build_namespace(parent, namespaces)
return namespaces | [
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|
ChromiumWebApps/chromium | c7361d39be8abd1574e6ce8957c8dbddd4c6ccf7 | third_party/re2/re2/unicode.py | python | Scripts | (unicode_dir=_UNICODE_DIR) | return scripts | Returns dict mapping script names to code lists.
Args:
unicode_dir: Unicode data directory
Returns:
dict mapping script names to code lists | Returns dict mapping script names to code lists. | [
"Returns",
"dict",
"mapping",
"script",
"names",
"to",
"code",
"lists",
"."
] | def Scripts(unicode_dir=_UNICODE_DIR):
"""Returns dict mapping script names to code lists.
Args:
unicode_dir: Unicode data directory
Returns:
dict mapping script names to code lists
"""
scripts = {}
def DoLine(codes, fields):
"""Process single Scripts.txt line, updating scripts."""
(_, name) = fields
scripts.setdefault(name, []).extend(codes)
ReadUnicodeTable(unicode_dir+"/Scripts.txt", 2, DoLine)
return scripts | [
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|
baidu-research/tensorflow-allreduce | 66d5b855e90b0949e9fa5cca5599fd729a70e874 | tensorflow/python/profiler/pprof_profiler.py | python | profile | (graph, run_metadata, output_dir=None) | return profile_files | Generate profiles in pprof format.
See https://github.com/google/pprof/blob/master/proto/profile.proto
for pprof proto format.
Args:
graph: A `Graph` object.
run_metadata: A `RunMetadata` proto.
output_dir: (string) Directory to output pprof profile to.
Profile files for each device will be stored in compressed
serialized proto format. If output_dir is None, profile protos
will be printed to stdout instead.
Returns:
List of output files created by this profile call.
(Note: this list will be empty if output_dir is None) | Generate profiles in pprof format. | [
"Generate",
"profiles",
"in",
"pprof",
"format",
"."
] | def profile(graph, run_metadata, output_dir=None):
"""Generate profiles in pprof format.
See https://github.com/google/pprof/blob/master/proto/profile.proto
for pprof proto format.
Args:
graph: A `Graph` object.
run_metadata: A `RunMetadata` proto.
output_dir: (string) Directory to output pprof profile to.
Profile files for each device will be stored in compressed
serialized proto format. If output_dir is None, profile protos
will be printed to stdout instead.
Returns:
List of output files created by this profile call.
(Note: this list will be empty if output_dir is None)
"""
profiles = get_profiles(graph, run_metadata)
output_file_template = None
if output_dir:
if not os.path.isdir(output_dir):
os.makedirs(output_dir)
time_suffix = time.strftime('%Y%m%d%H%M%S')
output_file_template = os.path.join(
output_dir, '%s_' + time_suffix + '.pb.gz')
profile_files = []
for device, pprof_proto in profiles.items():
if output_file_template is None:
print('No output directory specified, printing to stdout instead.')
print(pprof_proto)
else:
device_name = str(device).strip('/').translate(
maketrans('/:', '__'))
profile_file = output_file_template % device_name
profile_files.append(profile_file)
with gzip.open(profile_file, 'w') as output_file:
print('Writing profile to %s...' % profile_file)
output_file.write(pprof_proto.SerializeToString())
return profile_files | [
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|
MythTV/mythtv | d282a209cb8be85d036f85a62a8ec971b67d45f4 | mythtv/programs/scripts/internetcontent/nv_python_libs/xsltfunctions/tedtalksXSL_api.py | python | xpathFunctions.stripSubstring | (self, string, startText, terminatorChar) | return string[:index].strip() | Return a substring terminated by specific character(s)
return a substring | Return a substring terminated by specific character(s)
return a substring | [
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'''Return a substring terminated by specific character(s)
return a substring
'''
index = string.find(startText)
if index == -1:
return ''
string = string[index+len(startText):]
index = string.find(terminatorChar)
if index == -1:
return ''
return string[:index].strip() | [
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hanpfei/chromium-net | 392cc1fa3a8f92f42e4071ab6e674d8e0482f83f | third_party/catapult/third_party/gsutil/gslib/translation_helper.py | python | LifecycleTranslation.BotoLifecycleFromMessage | (cls, lifecycle_message) | return boto_lifecycle | Translates an apitools message to a boto lifecycle object. | Translates an apitools message to a boto lifecycle object. | [
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] | def BotoLifecycleFromMessage(cls, lifecycle_message):
"""Translates an apitools message to a boto lifecycle object."""
boto_lifecycle = boto.gs.lifecycle.LifecycleConfig()
if lifecycle_message:
for rule_message in lifecycle_message.rule:
boto_rule = boto.gs.lifecycle.Rule()
if (rule_message.action and rule_message.action.type and
rule_message.action.type.lower() == 'delete'):
boto_rule.action = boto.gs.lifecycle.DELETE
if rule_message.condition:
if rule_message.condition.age:
boto_rule.conditions[boto.gs.lifecycle.AGE] = (
str(rule_message.condition.age))
if rule_message.condition.createdBefore:
boto_rule.conditions[boto.gs.lifecycle.CREATED_BEFORE] = (
str(rule_message.condition.createdBefore))
if rule_message.condition.isLive:
boto_rule.conditions[boto.gs.lifecycle.IS_LIVE] = (
str(rule_message.condition.isLive))
if rule_message.condition.numNewerVersions:
boto_rule.conditions[boto.gs.lifecycle.NUM_NEWER_VERSIONS] = (
str(rule_message.condition.numNewerVersions))
boto_lifecycle.append(boto_rule)
return boto_lifecycle | [
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|
miyosuda/TensorFlowAndroidMNIST | 7b5a4603d2780a8a2834575706e9001977524007 | jni-build/jni/include/tensorflow/python/ops/control_flow_ops.py | python | GradLoopState.history_map | (self) | return self._history_map | The map that records all the tensors needed for backprop. | The map that records all the tensors needed for backprop. | [
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] | def history_map(self):
"""The map that records all the tensors needed for backprop."""
return self._history_map | [
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|
catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/scipy/py2/scipy/io/netcdf.py | python | netcdf_variable._get_missing_value | (self) | return missing_value | Returns the value denoting "no data" for this variable.
If this variable does not have a missing/fill value, returns None.
If both _FillValue and missing_value are given, give precedence to
_FillValue. The netCDF standard gives special meaning to _FillValue;
missing_value is just used for compatibility with old datasets. | Returns the value denoting "no data" for this variable. | [
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] | def _get_missing_value(self):
"""
Returns the value denoting "no data" for this variable.
If this variable does not have a missing/fill value, returns None.
If both _FillValue and missing_value are given, give precedence to
_FillValue. The netCDF standard gives special meaning to _FillValue;
missing_value is just used for compatibility with old datasets.
"""
if '_FillValue' in self._attributes:
missing_value = self._attributes['_FillValue']
elif 'missing_value' in self._attributes:
missing_value = self._attributes['missing_value']
else:
missing_value = None
return missing_value | [
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|
wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_carbon/_core.py | python | Window.MacIsWindowScrollbar | (*args, **kwargs) | return _core_.Window_MacIsWindowScrollbar(*args, **kwargs) | MacIsWindowScrollbar(self, Window sb) -> bool | MacIsWindowScrollbar(self, Window sb) -> bool | [
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] | def MacIsWindowScrollbar(*args, **kwargs):
"""MacIsWindowScrollbar(self, Window sb) -> bool"""
return _core_.Window_MacIsWindowScrollbar(*args, **kwargs) | [
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