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openid/python-openid | afa6adacbe1a41d8f614c8bce2264dfbe9e76489 | openid/extensions/pape.py | python | Request.parseExtensionArgs | (self, args, is_openid1, strict=False) | Set the state of this request to be that expressed in these
PAPE arguments
@param args: The PAPE arguments without a namespace
@param strict: Whether to raise an exception if the input is
out of spec or otherwise malformed. If strict is false,
malformed input will be ignored.
@param is_openid1: Whether the input should be treated as part
of an OpenID1 request
@rtype: None
@raises ValueError: When the max_auth_age is not parseable as
an integer | Set the state of this request to be that expressed in these
PAPE arguments | [
"Set",
"the",
"state",
"of",
"this",
"request",
"to",
"be",
"that",
"expressed",
"in",
"these",
"PAPE",
"arguments"
] | def parseExtensionArgs(self, args, is_openid1, strict=False):
"""Set the state of this request to be that expressed in these
PAPE arguments
@param args: The PAPE arguments without a namespace
@param strict: Whether to raise an exception if the input is
out of spec or otherwise malformed. If strict is false,
malformed input will be ignored.
@param is_openid1: Whether the input should be treated as part
of an OpenID1 request
@rtype: None
@raises ValueError: When the max_auth_age is not parseable as
an integer
"""
# preferred_auth_policies is a space-separated list of policy URIs
self.preferred_auth_policies = []
policies_str = args.get('preferred_auth_policies')
if policies_str:
for uri in policies_str.split(' '):
if uri not in self.preferred_auth_policies:
self.preferred_auth_policies.append(uri)
# max_auth_age is base-10 integer number of seconds
max_auth_age_str = args.get('max_auth_age')
self.max_auth_age = None
if max_auth_age_str:
try:
self.max_auth_age = int(max_auth_age_str)
except ValueError:
if strict:
raise
# Parse auth level information
preferred_auth_level_types = args.get('preferred_auth_level_types')
if preferred_auth_level_types:
aliases = preferred_auth_level_types.strip().split()
for alias in aliases:
key = 'auth_level.ns.%s' % (alias,)
try:
uri = args[key]
except KeyError:
if is_openid1:
uri = self._default_auth_level_aliases.get(alias)
else:
uri = None
if uri is None:
if strict:
raise ValueError('preferred auth level %r is not '
'defined in this message' % (alias,))
else:
self.addAuthLevel(uri, alias) | [
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"... | https://github.com/openid/python-openid/blob/afa6adacbe1a41d8f614c8bce2264dfbe9e76489/openid/extensions/pape.py#L194-L253 | ||
readthedocs/commonmark.py | d031003aa23cfce1787cfb29c1eb109b369ca5b7 | commonmark/inlines.py | python | InlineParser.handleDelim | (self, cc, block) | return True | Handle a delimiter marker for emphasis or a quote. | Handle a delimiter marker for emphasis or a quote. | [
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"""Handle a delimiter marker for emphasis or a quote."""
res = self.scanDelims(cc)
if not res:
return False
numdelims = res.get('numdelims')
startpos = self.pos
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contents = '\u2019'
elif cc == '"':
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else:
contents = self.subject[startpos:self.pos]
node = text(contents)
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# Add entry to stack for this opener
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... | https://github.com/readthedocs/commonmark.py/blob/d031003aa23cfce1787cfb29c1eb109b369ca5b7/commonmark/inlines.py#L311-L342 | |
statsmodels/statsmodels | debbe7ea6ba28fe5bdb78f09f8cac694bef98722 | statsmodels/sandbox/predict_functional.py | python | _make_exog_from_formula | (result, focus_var, summaries, values, num_points) | return dexog, fexog, fvals | Create dataframes for exploring a fitted model as a function of one variable.
This works for models fit with a formula.
Returns
-------
dexog : data frame
A data frame in which the focus variable varies and the other variables
are fixed at specified or computed values.
fexog : data frame
The data frame `dexog` processed through the model formula. | Create dataframes for exploring a fitted model as a function of one variable. | [
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"a",
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"variable",
"."
] | def _make_exog_from_formula(result, focus_var, summaries, values, num_points):
"""
Create dataframes for exploring a fitted model as a function of one variable.
This works for models fit with a formula.
Returns
-------
dexog : data frame
A data frame in which the focus variable varies and the other variables
are fixed at specified or computed values.
fexog : data frame
The data frame `dexog` processed through the model formula.
"""
model = result.model
exog = model.data.frame
if summaries is None:
summaries = {}
if values is None:
values = {}
if exog[focus_var].dtype is np.dtype('O'):
raise ValueError('focus variable may not have object type')
colnames = list(summaries.keys()) + list(values.keys()) + [focus_var]
dtypes = [exog[x].dtype for x in colnames]
# Check for variables whose values are not set either through
# `values` or `summaries`. Since the model data frame can contain
# extra variables not referenced in the formula RHS, this may not
# be a problem, so just warn. There is no obvious way to extract
# from a formula all the variable names that it references.
varl = set(exog.columns.tolist()) - set([model.endog_names])
unmatched = varl - set(colnames)
unmatched = list(unmatched)
if len(unmatched) > 0:
warnings.warn("%s in data frame but not in summaries or values."
% ", ".join(["'%s'" % x for x in unmatched]),
ValueWarning)
# Initialize at zero so each column can be converted to any dtype.
ix = range(num_points)
fexog = pd.DataFrame(index=ix, columns=colnames)
for d, x in zip(dtypes, colnames):
fexog[x] = pd.Series(index=ix, dtype=d)
# The values of the 'focus variable' are a sequence of percentiles
pctls = np.linspace(0, 100, num_points).tolist()
fvals = np.percentile(exog[focus_var], pctls)
fvals = np.asarray(fvals)
fexog.loc[:, focus_var] = fvals
# The values of the other variables may be given by summary functions...
for ky in summaries.keys():
fexog.loc[:, ky] = summaries[ky](exog.loc[:, ky])
# or they may be provided as given values.
for ky in values.keys():
fexog.loc[:, ky] = values[ky]
dexog = patsy.dmatrix(model.data.design_info, fexog,
return_type='dataframe')
return dexog, fexog, fvals | [
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saltstack/salt | fae5bc757ad0f1716483ce7ae180b451545c2058 | salt/states/salt_proxy.py | python | configure_proxy | (name, proxyname="p8000", start=True) | return ret | Create the salt proxy file and start the proxy process
if required
Parameters:
name:
The name of this state
proxyname:
Name to be used for this proxy (should match entries in pillar)
start:
Boolean indicating if the process should be started
Example:
.. code-block:: yaml
salt-proxy-configure:
salt_proxy.configure_proxy:
- proxyname: p8000
- start: True | Create the salt proxy file and start the proxy process
if required | [
"Create",
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"salt",
"proxy",
"file",
"and",
"start",
"the",
"proxy",
"process",
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] | def configure_proxy(name, proxyname="p8000", start=True):
"""
Create the salt proxy file and start the proxy process
if required
Parameters:
name:
The name of this state
proxyname:
Name to be used for this proxy (should match entries in pillar)
start:
Boolean indicating if the process should be started
Example:
.. code-block:: yaml
salt-proxy-configure:
salt_proxy.configure_proxy:
- proxyname: p8000
- start: True
"""
ret = __salt__["salt_proxy.configure_proxy"](proxyname, start=start)
ret.update({"name": name, "comment": "{} config messages".format(name)})
return ret | [
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Qiskit/qiskit-terra | b66030e3b9192efdd3eb95cf25c6545fe0a13da4 | qiskit/visualization/bloch.py | python | Bloch.add_vectors | (self, vectors) | Add a list of vectors to Bloch sphere.
Args:
vectors (array_like):
Array with vectors of unit length or smaller. | Add a list of vectors to Bloch sphere. | [
"Add",
"a",
"list",
"of",
"vectors",
"to",
"Bloch",
"sphere",
"."
] | def add_vectors(self, vectors):
"""Add a list of vectors to Bloch sphere.
Args:
vectors (array_like):
Array with vectors of unit length or smaller.
"""
if isinstance(vectors[0], (list, np.ndarray)):
for vec in vectors:
self.vectors.append(vec)
else:
self.vectors.append(vectors) | [
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pyscf/pyscf | 0adfb464333f5ceee07b664f291d4084801bae64 | pyscf/gto/mole.py | python | Mole.intor | (self, intor, comp=None, hermi=0, aosym='s1', out=None,
shls_slice=None, grids=None) | return moleintor.getints(intor, self._atm, bas, env,
shls_slice, comp, hermi, aosym, out=out) | Integral generator.
Args:
intor : str
Name of the 1e or 2e AO integrals. Ref to :func:`getints` for the
complete list of available 1-electron integral names
Kwargs:
comp : int
Components of the integrals, e.g. int1e_ipovlp_sph has 3 components.
hermi : int
Symmetry of the integrals
| 0 : no symmetry assumed (default)
| 1 : hermitian
| 2 : anti-hermitian
grids : ndarray
Coordinates of grids for the int1e_grids integrals
Returns:
ndarray of 1-electron integrals, can be either 2-dim or 3-dim, depending on comp
Examples:
>>> mol.build(atom='H 0 0 0; H 0 0 1.1', basis='sto-3g')
>>> mol.intor('int1e_ipnuc_sph', comp=3) # <nabla i | V_nuc | j>
[[[ 0. 0. ]
[ 0. 0. ]]
[[ 0. 0. ]
[ 0. 0. ]]
[[ 0.10289944 0.48176097]
[-0.48176097 -0.10289944]]]
>>> mol.intor('int1e_nuc_spinor')
[[-1.69771092+0.j 0.00000000+0.j -0.67146312+0.j 0.00000000+0.j]
[ 0.00000000+0.j -1.69771092+0.j 0.00000000+0.j -0.67146312+0.j]
[-0.67146312+0.j 0.00000000+0.j -1.69771092+0.j 0.00000000+0.j]
[ 0.00000000+0.j -0.67146312+0.j 0.00000000+0.j -1.69771092+0.j]] | Integral generator. | [
"Integral",
"generator",
"."
] | def intor(self, intor, comp=None, hermi=0, aosym='s1', out=None,
shls_slice=None, grids=None):
'''Integral generator.
Args:
intor : str
Name of the 1e or 2e AO integrals. Ref to :func:`getints` for the
complete list of available 1-electron integral names
Kwargs:
comp : int
Components of the integrals, e.g. int1e_ipovlp_sph has 3 components.
hermi : int
Symmetry of the integrals
| 0 : no symmetry assumed (default)
| 1 : hermitian
| 2 : anti-hermitian
grids : ndarray
Coordinates of grids for the int1e_grids integrals
Returns:
ndarray of 1-electron integrals, can be either 2-dim or 3-dim, depending on comp
Examples:
>>> mol.build(atom='H 0 0 0; H 0 0 1.1', basis='sto-3g')
>>> mol.intor('int1e_ipnuc_sph', comp=3) # <nabla i | V_nuc | j>
[[[ 0. 0. ]
[ 0. 0. ]]
[[ 0. 0. ]
[ 0. 0. ]]
[[ 0.10289944 0.48176097]
[-0.48176097 -0.10289944]]]
>>> mol.intor('int1e_nuc_spinor')
[[-1.69771092+0.j 0.00000000+0.j -0.67146312+0.j 0.00000000+0.j]
[ 0.00000000+0.j -1.69771092+0.j 0.00000000+0.j -0.67146312+0.j]
[-0.67146312+0.j 0.00000000+0.j -1.69771092+0.j 0.00000000+0.j]
[ 0.00000000+0.j -0.67146312+0.j 0.00000000+0.j -1.69771092+0.j]]
'''
if not self._built:
logger.warn(self, 'Warning: intor envs of %s not initialized.', self)
# FIXME: Whether to check _built and call build? ._bas and .basis
# may not be consistent. calling .build() may leads to wrong intor env.
#self.build(False, False)
intor = self._add_suffix(intor)
bas = self._bas
env = self._env
if 'ECP' in intor:
assert(self._ecp is not None)
bas = numpy.vstack((self._bas, self._ecpbas))
env[AS_ECPBAS_OFFSET] = len(self._bas)
env[AS_NECPBAS] = len(self._ecpbas)
if shls_slice is None:
shls_slice = (0, self.nbas, 0, self.nbas)
elif '_grids' in intor:
assert grids is not None
env = numpy.append(env, grids.ravel())
env[NGRIDS] = grids.shape[0]
env[PTR_GRIDS] = env.size - grids.size
return moleintor.getints(intor, self._atm, bas, env,
shls_slice, comp, hermi, aosym, out=out) | [
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c0rv4x/project-black | 2d3df00ba1b1453c99ec5a247793a74e11adba2a | black/workers/patator/patator_task.py | python | PatatorTask.client_connected_cb | (self, reader, writer) | Callback which is called, after unix socket (the socket which is responsible
for transporting socket data) receives a new connection | Callback which is called, after unix socket (the socket which is responsible
for transporting socket data) receives a new connection | [
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] | def client_connected_cb(self, reader, writer):
""" Callback which is called, after unix socket (the socket which is responsible
for transporting socket data) receives a new connection """
self.loop.create_task(self.poll_status(reader)) | [
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inspurer/WorkAttendanceSystem | 1221e2d67bdf5bb15fe99517cc3ded58ccb066df | V2.0/venv/Lib/site-packages/pip-9.0.1-py3.5.egg/pip/_vendor/requests/sessions.py | python | Session.get | (self, url, **kwargs) | return self.request('GET', url, **kwargs) | Sends a GET request. Returns :class:`Response` object.
:param url: URL for the new :class:`Request` object.
:param \*\*kwargs: Optional arguments that ``request`` takes.
:rtype: requests.Response | Sends a GET request. Returns :class:`Response` object. | [
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".",
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":",
"class",
":",
"Response",
"object",
"."
] | def get(self, url, **kwargs):
"""Sends a GET request. Returns :class:`Response` object.
:param url: URL for the new :class:`Request` object.
:param \*\*kwargs: Optional arguments that ``request`` takes.
:rtype: requests.Response
"""
kwargs.setdefault('allow_redirects', True)
return self.request('GET', url, **kwargs) | [
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cassieeric/python_crawler | b50b5b55404e32164dc82ff0c23cdae0c4b168ae | weixin_crawler/project/Application/gzh_crawler/__init__.py | python | GZHCrawler.gzh_report | (self,gzh) | :param gzh:
:return:生成公众号历史文章数据报告 | :param gzh:
:return:生成公众号历史文章数据报告 | [
":",
"param",
"gzh",
":",
":",
"return",
":",
"生成公众号历史文章数据报告"
] | def gzh_report(self,gzh):
"""
:param gzh:
:return:生成公众号历史文章数据报告
"""
pass | [
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kubernetes-client/python | 47b9da9de2d02b2b7a34fbe05afb44afd130d73a | kubernetes/client/models/v1beta1_flow_schema_status.py | python | V1beta1FlowSchemaStatus.conditions | (self) | return self._conditions | Gets the conditions of this V1beta1FlowSchemaStatus. # noqa: E501
`conditions` is a list of the current states of FlowSchema. # noqa: E501
:return: The conditions of this V1beta1FlowSchemaStatus. # noqa: E501
:rtype: list[V1beta1FlowSchemaCondition] | Gets the conditions of this V1beta1FlowSchemaStatus. # noqa: E501 | [
"Gets",
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"conditions",
"of",
"this",
"V1beta1FlowSchemaStatus",
".",
"#",
"noqa",
":",
"E501"
] | def conditions(self):
"""Gets the conditions of this V1beta1FlowSchemaStatus. # noqa: E501
`conditions` is a list of the current states of FlowSchema. # noqa: E501
:return: The conditions of this V1beta1FlowSchemaStatus. # noqa: E501
:rtype: list[V1beta1FlowSchemaCondition]
"""
return self._conditions | [
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] | https://github.com/kubernetes-client/python/blob/47b9da9de2d02b2b7a34fbe05afb44afd130d73a/kubernetes/client/models/v1beta1_flow_schema_status.py#L56-L64 | |
akirafukui/vqa-mcb | 172775b2ec927456eecbe1aa5878b673482f2a54 | train/v4/train_v4.py | python | make_vocab_files | () | return question_vocab, answer_vocab | Produce the question and answer vocabulary files. | Produce the question and answer vocabulary files. | [
"Produce",
"the",
"question",
"and",
"answer",
"vocabulary",
"files",
"."
] | def make_vocab_files():
"""
Produce the question and answer vocabulary files.
"""
print 'making question vocab...', config.QUESTION_VOCAB_SPACE
qdic, _ = VQADataProvider.load_data(config.QUESTION_VOCAB_SPACE)
question_vocab = make_question_vocab(qdic)
print 'making answer vocab...', config.ANSWER_VOCAB_SPACE
_, adic = VQADataProvider.load_data(config.ANSWER_VOCAB_SPACE)
answer_vocab = make_answer_vocab(adic, config.NUM_OUTPUT_UNITS)
return question_vocab, answer_vocab | [
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"make_que... | https://github.com/akirafukui/vqa-mcb/blob/172775b2ec927456eecbe1aa5878b673482f2a54/train/v4/train_v4.py#L135-L145 | |
holland-backup/holland | 77dcfe9f23d4254e4c351cdc18f29a8d34945812 | holland/core/config/config.py | python | BaseConfig.lookup | (self, key, safe=True) | return result | Lookup a configuration item based on the
dot-separated path. | Lookup a configuration item based on the
dot-separated path. | [
"Lookup",
"a",
"configuration",
"item",
"based",
"on",
"the",
"dot",
"-",
"separated",
"path",
"."
] | def lookup(self, key, safe=True):
"""
Lookup a configuration item based on the
dot-separated path.
"""
parts = key.split(".")
# lookup key as a . separated hierarchy path
section = self
result = None
count = 0
for count, name in enumerate(parts):
if not isinstance(section, Section):
result = None
break
result = section.get(name)
section = result
if not result and not safe:
raise KeyError("%r not found (%r)" % (key, parts[count]))
if isinstance(result, bytes):
return result.decode("utf-8")
return result | [
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"... | https://github.com/holland-backup/holland/blob/77dcfe9f23d4254e4c351cdc18f29a8d34945812/holland/core/config/config.py#L105-L125 | |
MediaBrowser/plugin.video.emby | 71162fc7704656833d8b228dc9014f88742215b1 | resources/lib/library.py | python | Library.startup | (self) | return False | Run at startup.
Check databases.
Check for the server plugin. | Run at startup.
Check databases.
Check for the server plugin. | [
"Run",
"at",
"startup",
".",
"Check",
"databases",
".",
"Check",
"for",
"the",
"server",
"plugin",
"."
] | def startup(self):
''' Run at startup.
Check databases.
Check for the server plugin.
'''
self.started = True
Views().get_views()
Views().get_nodes()
try:
if get_sync()['Libraries']:
self.sync_libraries()
elif not settings('SyncInstallRunDone.bool'):
with self.sync(self, self.server) as sync:
sync.libraries()
Views().get_nodes()
xbmc.executebuiltin('ReloadSkin()')
return True
self.get_fast_sync()
return True
except LibraryException as error:
LOG.error(error.status)
if error.status in 'SyncLibraryLater':
dialog("ok", heading="{emby}", line1=_(33129))
settings('SyncInstallRunDone.bool', True)
sync = get_sync()
sync['Libraries'] = []
save_sync(sync)
return True
elif error.status == 'CompanionMissing':
dialog("ok", heading="{emby}", line1=_(33099))
settings('kodiCompanion.bool', False)
return True
elif error.status == 'StopWriteCalled':
self.verify_libs = True
raise
except Exception as error:
LOG.exception(error)
return False | [
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projecthamster/hamster | 19d160090de30e756bdc3122ff935bdaa86e2843 | src/hamster/lib/fact.py | python | Fact.end_time | (self) | return self.range.end | Fact range end.
Deprecated, use self.range.end instead. | Fact range end. | [
"Fact",
"range",
"end",
"."
] | def end_time(self):
"""Fact range end.
Deprecated, use self.range.end instead.
"""
return self.range.end | [
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sigmavirus24/github3.py | f642a27833d6bef93daf5bb27b35e5ddbcfbb773 | src/github3/users.py | python | _User.followers | (self, number=-1, etag=None) | return self._iter(int(number), url, ShortUser, etag=etag) | r"""Iterate over the followers of this user.
:param int number: (optional), number of followers to return. Default:
-1 returns all available
:param str etag: (optional), ETag from a previous request to the same
endpoint
:returns: generator of :class:`User <User>`\ s | r"""Iterate over the followers of this user. | [
"r",
"Iterate",
"over",
"the",
"followers",
"of",
"this",
"user",
"."
] | def followers(self, number=-1, etag=None):
r"""Iterate over the followers of this user.
:param int number: (optional), number of followers to return. Default:
-1 returns all available
:param str etag: (optional), ETag from a previous request to the same
endpoint
:returns: generator of :class:`User <User>`\ s
"""
url = self._build_url("followers", base_url=self._api)
return self._iter(int(number), url, ShortUser, etag=etag) | [
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astroML/astroML | f66558232f6d33cb34ecd1bed8a80b9db7ae1c30 | astroML/plotting/tools.py | python | devectorize_axes | (ax=None, dpi=None, transparent=True) | return ax | Convert axes contents to a png.
This is useful when plotting many points, as the size of the saved file
can become very large otherwise.
Parameters
----------
ax : Axes instance (optional)
Axes to de-vectorize. If None, this uses the current active axes
(plt.gca())
dpi: int (optional)
resolution of the png image. If not specified, the default from
'savefig.dpi' in rcParams will be used
transparent : bool (optional)
if True (default) then the PNG will be made transparent
Returns
-------
ax : Axes instance
the in-place modified Axes instance
Examples
--------
The code can be used in the following way::
>>> import matplotlib.pyplot as plt
>>> import numpy as np
>>> from astroML.plotting.tools import devectorize_axes
>>> fig, ax = plt.subplots()
>>> x, y = np.random.random((2, 10000))
>>> ax.scatter(x, y) # doctest: +IGNORE_OUTPUT
>>> devectorize_axes(ax) # doctest: +IGNORE_OUTPUT
The resulting figure will be much smaller than the vectorized version. | Convert axes contents to a png. | [
"Convert",
"axes",
"contents",
"to",
"a",
"png",
"."
] | def devectorize_axes(ax=None, dpi=None, transparent=True):
"""Convert axes contents to a png.
This is useful when plotting many points, as the size of the saved file
can become very large otherwise.
Parameters
----------
ax : Axes instance (optional)
Axes to de-vectorize. If None, this uses the current active axes
(plt.gca())
dpi: int (optional)
resolution of the png image. If not specified, the default from
'savefig.dpi' in rcParams will be used
transparent : bool (optional)
if True (default) then the PNG will be made transparent
Returns
-------
ax : Axes instance
the in-place modified Axes instance
Examples
--------
The code can be used in the following way::
>>> import matplotlib.pyplot as plt
>>> import numpy as np
>>> from astroML.plotting.tools import devectorize_axes
>>> fig, ax = plt.subplots()
>>> x, y = np.random.random((2, 10000))
>>> ax.scatter(x, y) # doctest: +IGNORE_OUTPUT
>>> devectorize_axes(ax) # doctest: +IGNORE_OUTPUT
The resulting figure will be much smaller than the vectorized version.
"""
if ax is None:
ax = plt.gca()
fig = ax.figure
axlim = ax.axis()
# setup: make all visible spines (axes & ticks) & text invisible
# we need to set these back later, so we save their current state
_sp = {}
_txt_vis = [t.get_visible() for t in ax.texts]
for k in ax.spines:
_sp[k] = ax.spines[k].get_visible()
ax.spines[k].set_visible(False)
for t in ax.texts:
t.set_visible(False)
_xax = ax.xaxis.get_visible()
_yax = ax.yaxis.get_visible()
_patch = ax.patch.get_visible()
ax.patch.set_visible(False)
ax.xaxis.set_visible(False)
ax.yaxis.set_visible(False)
# convert canvas to PNG
extents = ax.bbox.extents / fig.dpi
output = BytesIO()
plt.savefig(output, format='png', dpi=dpi,
transparent=transparent,
bbox_inches=Bbox([extents[:2], extents[2:]]))
output.seek(0)
im = image.imread(output)
# clear everything on axis (but not text)
ax.lines = []
ax.patches = []
ax.tables = []
ax.artists = []
ax.images = []
ax.collections = []
# Show the image
ax.imshow(im, extent=axlim, aspect='auto', interpolation='nearest')
# restore all the spines & text
for k in ax.spines:
ax.spines[k].set_visible(_sp[k])
for t, v in zip(ax.texts, _txt_vis):
t.set_visible(v)
ax.patch.set_visible(_patch)
ax.xaxis.set_visible(_xax)
ax.yaxis.set_visible(_yax)
if plt.isinteractive():
plt.draw()
return ax | [
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"... | https://github.com/astroML/astroML/blob/f66558232f6d33cb34ecd1bed8a80b9db7ae1c30/astroML/plotting/tools.py#L12-L103 | |
standardebooks/tools | f57af3c5938a9aeed9e97e82b2c130424f6033e5 | se/vendor/kindleunpack/mobi_html.py | python | XHTMLK8Processor.buildXHTML | (self) | return self.used | [] | def buildXHTML(self):
# first need to update all links that are internal which
# are based on positions within the xhtml files **BEFORE**
# cutting and pasting any pieces into the xhtml text files
# kindle:pos:fid:XXXX:off:YYYYYYYYYY (used for internal link within xhtml)
# XXXX is the offset in records into divtbl
# YYYYYYYYYYYY is a base32 number you add to the divtbl insertpos to get final position
# pos:fid pattern
posfid_pattern = re.compile(br'''(<a.*?href=.*?>)''', re.IGNORECASE)
posfid_index_pattern = re.compile(br'''['"]kindle:pos:fid:([0-9|A-V]+):off:([0-9|A-V]+).*?["']''')
parts = []
print("Building proper xhtml for each file")
for i in range(self.k8proc.getNumberOfParts()):
part = self.k8proc.getPart(i)
[partnum, dir, filename, beg, end, aidtext] = self.k8proc.getPartInfo(i)
# internal links
srcpieces = posfid_pattern.split(part)
for j in range(1, len(srcpieces),2):
tag = srcpieces[j]
if tag.startswith(b'<'):
for m in posfid_index_pattern.finditer(tag):
posfid = m.group(1)
offset = m.group(2)
filename, idtag = self.k8proc.getIDTagByPosFid(posfid, offset)
if idtag == b'':
replacement= b'"' + utf8_str(filename) + b'"'
else:
replacement = b'"' + utf8_str(filename) + b'#' + idtag + b'"'
tag = posfid_index_pattern.sub(replacement, tag, 1)
srcpieces[j] = tag
part = b"".join(srcpieces)
parts.append(part)
# we are free to cut and paste as we see fit
# we can safely remove all of the Kindlegen generated aid tags
# change aid ids that are in k8proc.linked_aids to xhtml ids
find_tag_with_aid_pattern = re.compile(br'''(<[^>]*\said\s*=[^>]*>)''', re.IGNORECASE)
within_tag_aid_position_pattern = re.compile(br'''\said\s*=['"]([^'"]*)['"]''')
for i in range(len(parts)):
part = parts[i]
srcpieces = find_tag_with_aid_pattern.split(part)
for j in range(len(srcpieces)):
tag = srcpieces[j]
if tag.startswith(b'<'):
for m in within_tag_aid_position_pattern.finditer(tag):
try:
aid = m.group(1)
except IndexError:
aid = None
replacement = b''
if aid in self.k8proc.linked_aids:
replacement = b' id="aid-' + aid + b'"'
tag = within_tag_aid_position_pattern.sub(replacement, tag, 1)
srcpieces[j] = tag
part = b"".join(srcpieces)
parts[i] = part
# we can safely replace all of the Kindlegen generated data-AmznPageBreak tags
# with page-break-after style patterns
find_tag_with_AmznPageBreak_pattern = re.compile(br'''(<[^>]*\sdata-AmznPageBreak=[^>]*>)''', re.IGNORECASE)
within_tag_AmznPageBreak_position_pattern = re.compile(br'''\sdata-AmznPageBreak=['"]([^'"]*)['"]''')
for i in range(len(parts)):
part = parts[i]
srcpieces = find_tag_with_AmznPageBreak_pattern.split(part)
for j in range(len(srcpieces)):
tag = srcpieces[j]
if tag.startswith(b'<'):
srcpieces[j] = within_tag_AmznPageBreak_position_pattern.sub(
lambda m:b' style="page-break-after:' + m.group(1) + b'"', tag)
part = b"".join(srcpieces)
parts[i] = part
# we have to handle substitutions for the flows pieces first as they may
# be inlined into the xhtml text
# kindle:embed:XXXX?mime=image/gif (png, jpeg, etc) (used for images)
# kindle:flow:XXXX?mime=YYYY/ZZZ (used for style sheets, svg images, etc)
# kindle:embed:XXXX (used for fonts)
flows = []
flows.append(None)
flowinfo = []
flowinfo.append([None, None, None, None])
# regular expression search patterns
img_pattern = re.compile(br'''(<[img\s|image\s][^>]*>)''', re.IGNORECASE)
img_index_pattern = re.compile(br'''[('"]kindle:embed:([0-9|A-V]+)[^'"]*['")]''', re.IGNORECASE)
tag_pattern = re.compile(br'''(<[^>]*>)''')
flow_pattern = re.compile(br'''['"]kindle:flow:([0-9|A-V]+)\?mime=([^'"]+)['"]''', re.IGNORECASE)
url_pattern = re.compile(br'''(url\(.*?\))''', re.IGNORECASE)
url_img_index_pattern = re.compile(br'''[('"]kindle:embed:([0-9|A-V]+)\?mime=image/[^\)]*["')]''', re.IGNORECASE)
font_index_pattern = re.compile(br'''[('"]kindle:embed:([0-9|A-V]+)["')]''', re.IGNORECASE)
url_css_index_pattern = re.compile(br'''kindle:flow:([0-9|A-V]+)\?mime=text/css[^\)]*''', re.IGNORECASE)
for i in range(1, self.k8proc.getNumberOfFlows()):
[ftype, format, dir, filename] = self.k8proc.getFlowInfo(i)
flowpart = self.k8proc.getFlow(i)
# links to raster image files from image tags
# image_pattern
srcpieces = img_pattern.split(flowpart)
for j in range(1, len(srcpieces),2):
tag = srcpieces[j]
if tag.startswith(b'<im'):
for m in img_index_pattern.finditer(tag):
imageNumber = fromBase32(m.group(1))
imageName = self.rscnames[imageNumber-1]
if imageName is not None:
replacement = b'"../Images/' + utf8_str(imageName) + b'"'
self.used[imageName] = 'used'
tag = img_index_pattern.sub(replacement, tag, 1)
else:
print("Error: Referenced image %s was not recognized as a valid image in %s" % (imageNumber, tag))
srcpieces[j] = tag
flowpart = b"".join(srcpieces)
# replacements inside css url():
srcpieces = url_pattern.split(flowpart)
for j in range(1, len(srcpieces),2):
tag = srcpieces[j]
# process links to raster image files
for m in url_img_index_pattern.finditer(tag):
imageNumber = fromBase32(m.group(1))
imageName = self.rscnames[imageNumber-1]
osep = m.group()[0:1]
csep = m.group()[-1:]
if imageName is not None:
replacement = osep + b'../Images/' + utf8_str(imageName) + csep
self.used[imageName] = 'used'
tag = url_img_index_pattern.sub(replacement, tag, 1)
else:
print("Error: Referenced image %s was not recognized as a valid image in %s" % (imageNumber, tag))
# process links to fonts
for m in font_index_pattern.finditer(tag):
fontNumber = fromBase32(m.group(1))
fontName = self.rscnames[fontNumber-1]
osep = m.group()[0:1]
csep = m.group()[-1:]
if fontName is None:
print("Error: Referenced font %s was not recognized as a valid font in %s" % (fontNumber, tag))
else:
replacement = osep + b'../Fonts/' + utf8_str(fontName) + csep
tag = font_index_pattern.sub(replacement, tag, 1)
self.used[fontName] = 'used'
# process links to other css pieces
for m in url_css_index_pattern.finditer(tag):
num = fromBase32(m.group(1))
[typ, fmt, pdir, fnm] = self.k8proc.getFlowInfo(num)
replacement = b'"../' + utf8_str(pdir) + b'/' + utf8_str(fnm) + b'"'
tag = url_css_index_pattern.sub(replacement, tag, 1)
self.used[fnm] = 'used'
srcpieces[j] = tag
flowpart = b"".join(srcpieces)
# store away in our own copy
flows.append(flowpart)
# I do not think this case exists and even if it does exist, it needs to be done in a separate
# pass to prevent inlining a flow piece into another flow piece before the inserted one or the
# target one has been fully processed
# but keep it around if it ends up we do need it
# flow pattern not inside url()
# srcpieces = tag_pattern.split(flowpart)
# for j in range(1, len(srcpieces),2):
# tag = srcpieces[j]
# if tag.startswith(b'<'):
# for m in flow_pattern.finditer(tag):
# num = fromBase32(m.group(1))
# [typ, fmt, pdir, fnm] = self.k8proc.getFlowInfo(num)
# flowtext = self.k8proc.getFlow(num)
# if fmt == b'inline':
# tag = flowtext
# else:
# replacement = b'"../' + utf8_str(pdir) + b'/' + utf8_str(fnm) + b'"'
# tag = flow_pattern.sub(replacement, tag, 1)
# self.used[fnm] = 'used'
# srcpieces[j] = tag
# flowpart = b"".join(srcpieces)
# now handle the main text xhtml parts
# Handle the flow items in the XHTML text pieces
# kindle:flow:XXXX?mime=YYYY/ZZZ (used for style sheets, svg images, etc)
tag_pattern = re.compile(br'''(<[^>]*>)''')
flow_pattern = re.compile(br'''['"]kindle:flow:([0-9|A-V]+)\?mime=([^'"]+)['"]''', re.IGNORECASE)
for i in range(len(parts)):
part = parts[i]
[partnum, dir, filename, beg, end, aidtext] = self.k8proc.partinfo[i]
# flow pattern
srcpieces = tag_pattern.split(part)
for j in range(1, len(srcpieces),2):
tag = srcpieces[j]
if tag.startswith(b'<'):
for m in flow_pattern.finditer(tag):
num = fromBase32(m.group(1))
if num > 0 and num < len(self.k8proc.flowinfo):
[typ, fmt, pdir, fnm] = self.k8proc.getFlowInfo(num)
flowpart = flows[num]
if fmt == b'inline':
tag = flowpart
else:
replacement = b'"../' + utf8_str(pdir) + b'/' + utf8_str(fnm) + b'"'
tag = flow_pattern.sub(replacement, tag, 1)
self.used[fnm] = 'used'
else:
print("warning: ignoring non-existent flow link", tag, " value 0x%x" % num)
srcpieces[j] = tag
part = b''.join(srcpieces)
# store away modified version
parts[i] = part
# Handle any embedded raster images links in style= attributes urls
style_pattern = re.compile(br'''(<[a-zA-Z0-9]+\s[^>]*style\s*=\s*[^>]*>)''', re.IGNORECASE)
img_index_pattern = re.compile(br'''[('"]kindle:embed:([0-9|A-V]+)[^'"]*['")]''', re.IGNORECASE)
for i in range(len(parts)):
part = parts[i]
[partnum, dir, filename, beg, end, aidtext] = self.k8proc.partinfo[i]
# replace urls in style attributes
srcpieces = style_pattern.split(part)
for j in range(1, len(srcpieces),2):
tag = srcpieces[j]
if b'kindle:embed' in tag:
for m in img_index_pattern.finditer(tag):
imageNumber = fromBase32(m.group(1))
imageName = self.rscnames[imageNumber-1]
osep = m.group()[0:1]
csep = m.group()[-1:]
if imageName is not None:
replacement = osep + b'../Images/'+ utf8_str(imageName) + csep
self.used[imageName] = 'used'
tag = img_index_pattern.sub(replacement, tag, 1)
else:
print("Error: Referenced image %s in style url was not recognized in %s" % (imageNumber, tag))
srcpieces[j] = tag
part = b"".join(srcpieces)
# store away modified version
parts[i] = part
# Handle any embedded raster images links in the xhtml text
# kindle:embed:XXXX?mime=image/gif (png, jpeg, etc) (used for images)
img_pattern = re.compile(br'''(<[img\s|image\s][^>]*>)''', re.IGNORECASE)
img_index_pattern = re.compile(br'''['"]kindle:embed:([0-9|A-V]+)[^'"]*['"]''')
for i in range(len(parts)):
part = parts[i]
[partnum, dir, filename, beg, end, aidtext] = self.k8proc.partinfo[i]
# links to raster image files
# image_pattern
srcpieces = img_pattern.split(part)
for j in range(1, len(srcpieces),2):
tag = srcpieces[j]
if tag.startswith(b'<im'):
for m in img_index_pattern.finditer(tag):
imageNumber = fromBase32(m.group(1))
imageName = self.rscnames[imageNumber-1]
if imageName is not None:
replacement = b'"../Images/' + utf8_str(imageName) + b'"'
self.used[imageName] = 'used'
tag = img_index_pattern.sub(replacement, tag, 1)
else:
print("Error: Referenced image %s was not recognized as a valid image in %s" % (imageNumber, tag))
srcpieces[j] = tag
part = b"".join(srcpieces)
# store away modified version
parts[i] = part
# finally perform any general cleanups needed to make valid XHTML
# these include:
# in svg tags replace "perserveaspectratio" attributes with "perserveAspectRatio"
# in svg tags replace "viewbox" attributes with "viewBox"
# in <li> remove value="XX" attributes since these are illegal
tag_pattern = re.compile(br'''(<[^>]*>)''')
li_value_pattern = re.compile(br'''\svalue\s*=\s*['"][^'"]*['"]''', re.IGNORECASE)
for i in range(len(parts)):
part = parts[i]
[partnum, dir, filename, beg, end, aidtext] = self.k8proc.partinfo[i]
# tag pattern
srcpieces = tag_pattern.split(part)
for j in range(1, len(srcpieces),2):
tag = srcpieces[j]
if tag.startswith(b'<svg') or tag.startswith(b'<SVG'):
tag = tag.replace(b'preserveaspectratio',b'preserveAspectRatio')
tag = tag.replace(b'viewbox',b'viewBox')
elif tag.startswith(b'<li ') or tag.startswith(b'<LI '):
tagpieces = li_value_pattern.split(tag)
tag = b"".join(tagpieces)
srcpieces[j] = tag
part = b"".join(srcpieces)
# store away modified version
parts[i] = part
self.k8proc.setFlows(flows)
self.k8proc.setParts(parts)
return self.used | [
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microsoft/unilm | 65f15af2a307ebb64cfb25adf54375b002e6fe8d | xtune/src/transformers/modeling_tf_bert.py | python | TFBertMainLayer._prune_heads | (self, heads_to_prune) | Prunes heads of the model.
heads_to_prune: dict of {layer_num: list of heads to prune in this layer}
See base class PreTrainedModel | Prunes heads of the model.
heads_to_prune: dict of {layer_num: list of heads to prune in this layer}
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twilio/twilio-python | 6e1e811ea57a1edfadd5161ace87397c563f6915 | twilio/rest/numbers/v2/regulatory_compliance/bundle/evaluation.py | python | EvaluationInstance.date_created | (self) | return self._properties['date_created'] | :returns: The date_created
:rtype: datetime | :returns: The date_created
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rcorcs/NatI | fdf014f4292afdc95250add7b6658468043228e1 | en/parser/nltk_lite/draw/chart.py | python | ChartView._analyze_edge | (self, edge) | Given a new edge, recalculate:
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"""
c = self._chart_canvas
if isinstance(edge, TreeEdge):
lhs = edge.lhs()
rhselts = []
for elt in edge.rhs():
if isinstance(elt, cfg.Nonterminal):
rhselts.append(str(elt.symbol()))
else:
rhselts.append(repr(elt))
rhs = ' '.join(rhselts)
else:
lhs = edge.lhs()
rhs = ''
for s in (lhs, rhs):
tag = c.create_text(0,0, text=s,
font=self._boldfont,
anchor='nw', justify='left')
bbox = c.bbox(tag)
c.delete(tag)
width = bbox[2] #+ ChartView._LEAF_SPACING
edgelen = max(edge.length(), 1)
self._unitsize = max(self._unitsize, width/edgelen)
self._text_height = max(self._text_height, bbox[3] - bbox[1]) | [
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securesystemslab/zippy | ff0e84ac99442c2c55fe1d285332cfd4e185e089 | zippy/lib-python/3/plat-sunos5/IN.py | python | ntohl | (x) | return (x) | [] | def ntohl(x): return (x) | [
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yaqwsx/KiKit | 14de7f60b64e6d03ce638e78d279915d09bb9ac7 | kikit/panelize_ui_impl.py | python | obtainPreset | (presetPaths, validate=True, **kwargs) | return preset | Given a preset paths from the user and the overrides in the form of named
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presetChain = [":default"] + list(presetPaths)
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for name, section in kwargs.items():
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google/TensorNetwork | e12580f1749493dbe05f474d2fecdec4eaba73c5 | tensornetwork/backends/abstract_backend.py | python | AbstractBackend.item | (self, tensor) | Return the item of a 1-element tensor.
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encode/django-rest-framework | c5be86a6dbf3d21b00a296af5994fa075826bf0b | rest_framework/schemas/coreapi.py | python | SchemaGenerator.get_links | (self, request=None) | return links | Return a dictionary containing all the links that should be
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links = LinkNode()
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link = view.schema.get_link(path, method, base_url=self.url)
subpath = path[len(prefix):]
keys = self.get_keys(subpath, method, view)
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holzschu/Carnets | 44effb10ddfc6aa5c8b0687582a724ba82c6b547 | Library/lib/python3.7/site-packages/asn1crypto/util.py | python | extended_datetime.utcoffset | (self) | return self.tzinfo.utcoffset(self.replace(year=2000)) | :return:
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yihui-he/KL-Loss | 66c0ed9e886a2218f4cf88c0efd4f40199bff54a | detectron/roi_data/fast_rcnn.py | python | add_fast_rcnn_blobs | (blobs, im_scales, roidb) | return valid | Add blobs needed for training Fast R-CNN style models. | Add blobs needed for training Fast R-CNN style models. | [
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"""Add blobs needed for training Fast R-CNN style models."""
# Sample training RoIs from each image and append them to the blob lists
for im_i, entry in enumerate(roidb):
frcn_blobs = _sample_rois(entry, im_scales[im_i], im_i)
for k, v in frcn_blobs.items():
blobs[k].append(v)
# Concat the training blob lists into tensors
for k, v in blobs.items():
if isinstance(v, list) and len(v) > 0:
blobs[k] = np.concatenate(v)
# Add FPN multilevel training RoIs, if configured
if cfg.FPN.FPN_ON and cfg.FPN.MULTILEVEL_ROIS:
_add_multilevel_rois(blobs)
# Perform any final work and validity checks after the collating blobs for
# all minibatch images
valid = True
if cfg.MODEL.KEYPOINTS_ON:
valid = keypoint_rcnn_roi_data.finalize_keypoint_minibatch(blobs, valid)
return valid | [
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IdentityPython/pysaml2 | 6badb32d212257bd83ffcc816f9b625f68281b47 | src/saml2/response.py | python | LogoutResponse.__init__ | (self, sec_context, return_addrs=None, timeslack=0,
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StatusResponse.__init__(self, sec_context, return_addrs, timeslack,
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JulianEberius/SublimePythonIDE | d70e40abc0c9f347af3204c7b910e0d6bfd6e459 | server/lib/python2/rope/base/codeanalyze.py | python | CachingLogicalLineFinder._init_logicals | (self) | Should initialize _starts and _ends attributes | Should initialize _starts and _ends attributes | [
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edfungus/Crouton | ada98b3930192938a48909072b45cb84b945f875 | clients/python_clients/cf_demo_client/cf_env/lib/python2.7/site-packages/itsdangerous.py | python | Signer.get_signature | (self, value) | return base64_encode(sig) | Returns the signature for the given value | Returns the signature for the given value | [
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JasonKessler/scattertext | ef33f06d4c31f9d64b551a7ab86bf157aca82644 | scattertext/PValGetter.py | python | get_p_vals | (df, positive_category, term_significance) | return term_significance.get_p_vals(X) | Parameters
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boto/boto | b2a6f08122b2f1b89888d2848e730893595cd001 | boto/cloudsearch2/search.py | python | SearchResults.next_page | (self) | Call Cloudsearch to get the next page of search results
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:return: the following page of search results
"""
if self.query.page <= self.num_pages_needed:
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Jorl17/open-elevation | 677f9de1b6c1a10b48028f36e072bf8b6ba19b9e | gdal_interfaces.py | python | GDALTileInterface.read_summary_json | (self) | [] | def read_summary_json(self):
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] | https://github.com/Jorl17/open-elevation/blob/677f9de1b6c1a10b48028f36e072bf8b6ba19b9e/gdal_interfaces.py#L157-L161 | ||||
aiidateam/aiida-core | c743a335480f8bb3a5e4ebd2463a31f9f3b9f9b2 | aiida/orm/autogroup.py | python | Autogroup.set_exclude | (self, exclude) | Set the list of classes to exclude in the autogrouping.
:param exclude: a list of valid entry point strings (might contain '%' to be used as
string to be matched using SQL's ``LIKE`` pattern-making logic), or ``None``
to specify no include list. | Set the list of classes to exclude in the autogrouping. | [
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] | def set_exclude(self, exclude):
"""Set the list of classes to exclude in the autogrouping.
:param exclude: a list of valid entry point strings (might contain '%' to be used as
string to be matched using SQL's ``LIKE`` pattern-making logic), or ``None``
to specify no include list.
"""
if isinstance(exclude, str):
exclude = [exclude]
self.validate(exclude)
if exclude is not None and self.get_include() is not None:
# It's ok to set None, both as a default, or to 'undo' the exclude list
raise exceptions.ValidationError('Cannot both specify exclude and include')
self._exclude = exclude | [
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miguelgrinberg/Flask-Migrate | c051a000c1518a71e0a5d045c1f8065b9add5122 | src/flask_migrate/__init__.py | python | stamp | (directory=None, revision='head', sql=False, tag=None) | stamp' the revision table with the given revision; don't run any
migrations | stamp' the revision table with the given revision; don't run any
migrations | [
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] | def stamp(directory=None, revision='head', sql=False, tag=None):
"""'stamp' the revision table with the given revision; don't run any
migrations"""
config = current_app.extensions['migrate'].migrate.get_config(directory)
command.stamp(config, revision, sql=sql, tag=tag) | [
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mars-project/mars | 6afd7ed86db77f29cc9470485698ef192ecc6d33 | mars/tensor/base/atleast_3d.py | python | atleast_3d | (*tensors) | return ExecutableTuple(new_tensors) | View inputs as tensors with at least three dimensions.
Parameters
----------
tensors1, tensors2, ... : array_like
One or more tensor-like sequences. Non-tensor inputs are converted to
tensors. Tensors that already have three or more dimensions are
preserved.
Returns
-------
res1, res2, ... : Tensor
A tensor, or list of tensors, each with ``a.ndim >= 3``. Copies are
avoided where possible, and views with three or more dimensions are
returned. For example, a 1-D tensor of shape ``(N,)`` becomes a view
of shape ``(1, N, 1)``, and a 2-D tensor of shape ``(M, N)`` becomes a
view of shape ``(M, N, 1)``.
See Also
--------
atleast_1d, atleast_2d
Examples
--------
>>> import mars.tensor as mt
>>> mt.atleast_3d(3.0).execute()
array([[[ 3.]]])
>>> x = mt.arange(3.0)
>>> mt.atleast_3d(x).shape
(1, 3, 1)
>>> x = mt.arange(12.0).reshape(4,3)
>>> mt.atleast_3d(x).shape
(4, 3, 1)
>>> for arr in mt.atleast_3d([1, 2], [[1, 2]], [[[1, 2]]]).execute():
... print(arr, arr.shape)
...
[[[1]
[2]]] (1, 2, 1)
[[[1]
[2]]] (1, 2, 1)
[[[1 2]]] (1, 1, 2) | View inputs as tensors with at least three dimensions. | [
"View",
"inputs",
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"with",
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"three",
"dimensions",
"."
] | def atleast_3d(*tensors):
"""
View inputs as tensors with at least three dimensions.
Parameters
----------
tensors1, tensors2, ... : array_like
One or more tensor-like sequences. Non-tensor inputs are converted to
tensors. Tensors that already have three or more dimensions are
preserved.
Returns
-------
res1, res2, ... : Tensor
A tensor, or list of tensors, each with ``a.ndim >= 3``. Copies are
avoided where possible, and views with three or more dimensions are
returned. For example, a 1-D tensor of shape ``(N,)`` becomes a view
of shape ``(1, N, 1)``, and a 2-D tensor of shape ``(M, N)`` becomes a
view of shape ``(M, N, 1)``.
See Also
--------
atleast_1d, atleast_2d
Examples
--------
>>> import mars.tensor as mt
>>> mt.atleast_3d(3.0).execute()
array([[[ 3.]]])
>>> x = mt.arange(3.0)
>>> mt.atleast_3d(x).shape
(1, 3, 1)
>>> x = mt.arange(12.0).reshape(4,3)
>>> mt.atleast_3d(x).shape
(4, 3, 1)
>>> for arr in mt.atleast_3d([1, 2], [[1, 2]], [[[1, 2]]]).execute():
... print(arr, arr.shape)
...
[[[1]
[2]]] (1, 2, 1)
[[[1]
[2]]] (1, 2, 1)
[[[1 2]]] (1, 1, 2)
"""
new_tensors = []
for x in tensors:
x = astensor(x)
if x.ndim == 0:
x = x[np.newaxis, np.newaxis, np.newaxis]
elif x.ndim == 1:
x = x[np.newaxis, :, np.newaxis]
elif x.ndim == 2:
x = x[:, :, None]
new_tensors.append(x)
if len(new_tensors) == 1:
return new_tensors[0]
return ExecutableTuple(new_tensors) | [
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cloudmarker/cloudmarker | 0dd2daadfa0203b3d1062e5067b14e4e0f189697 | cloudmarker/events/azwebappclientcertevent.py | python | AzWebAppClientCertEvent.eval | (self, record) | Evaluate Azure web app to check if client cert is disabled.
Arguments:
record (dict): A web app record.
Yields:
dict: An event record representing a web app with client
certificate (mTLS) disabled. | Evaluate Azure web app to check if client cert is disabled. | [
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] | def eval(self, record):
"""Evaluate Azure web app to check if client cert is disabled.
Arguments:
record (dict): A web app record.
Yields:
dict: An event record representing a web app with client
certificate (mTLS) disabled.
"""
com = record.get('com', {})
if com is None:
return
if com.get('cloud_type') != 'azure':
return
ext = record.get('ext', {})
if ext is None:
return
if ext.get('record_type') != 'web_app_config':
return
if ext.get('client_cert_enabled'):
return
yield from _get_azure_web_app_client_cert_event(com, ext) | [
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matplotlib/matplotlib | 8d7a2b9d2a38f01ee0d6802dd4f9e98aec812322 | lib/matplotlib/backends/backend_cairo.py | python | _cairo_font_args_from_font_prop | (prop) | return name, slant, weight | Convert a `.FontProperties` or a `.FontEntry` to arguments that can be
passed to `.Context.select_font_face`. | Convert a `.FontProperties` or a `.FontEntry` to arguments that can be
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] | def _cairo_font_args_from_font_prop(prop):
"""
Convert a `.FontProperties` or a `.FontEntry` to arguments that can be
passed to `.Context.select_font_face`.
"""
def attr(field):
try:
return getattr(prop, f"get_{field}")()
except AttributeError:
return getattr(prop, field)
name = attr("name")
slant = getattr(cairo, f"FONT_SLANT_{attr('style').upper()}")
weight = attr("weight")
weight = (cairo.FONT_WEIGHT_NORMAL
if font_manager.weight_dict.get(weight, weight) < 550
else cairo.FONT_WEIGHT_BOLD)
return name, slant, weight | [
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mozilla/addons-server | cbfb29e5be99539c30248d70b93bb15e1c1bc9d7 | src/olympia/scanners/tasks.py | python | _run_scanner_for_url | (scanner_result, url, scanner, api_url, api_key) | Inner function to run a scanner on a particular URL via RPC and add results
to the given scanner_result. The caller is responsible for saving the
scanner_result to the database. | Inner function to run a scanner on a particular URL via RPC and add results
to the given scanner_result. The caller is responsible for saving the
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"""
Inner function to run a scanner on a particular URL via RPC and add results
to the given scanner_result. The caller is responsible for saving the
scanner_result to the database.
"""
with requests.Session() as http:
adapter = make_adapter_with_retry()
http.mount('http://', adapter)
http.mount('https://', adapter)
json_payload = {
'api_key': api_key,
'download_url': url,
}
response = http.post(
url=api_url, json=json_payload, timeout=settings.SCANNER_TIMEOUT
)
try:
data = response.json()
except ValueError:
# Log the response body when JSON decoding has failed.
raise ValueError(response.text)
if response.status_code != 200 or 'error' in data:
raise ValueError(data)
scanner_result.results = data | [
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biolab/orange3 | 41685e1c7b1d1babe680113685a2d44bcc9fec0b | Orange/widgets/visualize/owviolinplot.py | python | ViolinPlot.order_items | (self) | [] | def order_items(self):
assert self.__group_var is not None
indices = self._sorted_group_indices
for i, index in enumerate(indices):
violin: ViolinItem = self.__violin_items[index]
box: BoxItem = self.__box_items[index]
median: MedianItem = self.__median_items[index]
strip: StripItem = self.__strip_items[index]
sel_rect: QGraphicsRectItem = self.__selection_rects[index]
if self.__orientation == Qt.Vertical:
x = i * self._max_item_width
violin.setX(x)
box.setX(x)
median.setX(x)
strip.setX(x)
sel_rect.setX(x)
else:
y = - i * self._max_item_width
violin.setY(y)
box.setY(y)
median.setY(y)
strip.setY(y)
sel_rect.setY(y)
sign = 1 if self.__orientation == Qt.Vertical else -1
side = "bottom" if self.__orientation == Qt.Vertical else "left"
ticks = [[(i * self._max_item_width * sign,
self.__group_var.values[index])
for i, index in enumerate(indices)]]
self.getAxis(side).setTicks(ticks) | [
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oilshell/oil | 94388e7d44a9ad879b12615f6203b38596b5a2d3 | Python-2.7.13/Lib/gettext.py | python | NullTranslations.add_fallback | (self, fallback) | [] | def add_fallback(self, fallback):
if self._fallback:
self._fallback.add_fallback(fallback)
else:
self._fallback = fallback | [
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jgagneastro/coffeegrindsize | 22661ebd21831dba4cf32bfc6ba59fe3d49f879c | App/dist/coffeegrindsize.app/Contents/Resources/lib/python3.7/pandas/core/series.py | python | Series.to_frame | (self, name=None) | return df | Convert Series to DataFrame.
Parameters
----------
name : object, default None
The passed name should substitute for the series name (if it has
one).
Returns
-------
data_frame : DataFrame | Convert Series to DataFrame. | [
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"."
] | def to_frame(self, name=None):
"""
Convert Series to DataFrame.
Parameters
----------
name : object, default None
The passed name should substitute for the series name (if it has
one).
Returns
-------
data_frame : DataFrame
"""
if name is None:
df = self._constructor_expanddim(self)
else:
df = self._constructor_expanddim({name: self})
return df | [
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matsui528/nanopq | 4c1d724494a71f9736b15928a8c03b0ba13ffd19 | nanopq/pq.py | python | PQ.decode | (self, codes) | return vecs | Given PQ-codes, reconstruct original D-dimensional vectors
approximately by fetching the codewords.
Args:
codes (np.ndarray): PQ-cdoes with shape=(N, M) and dtype=self.code_dtype.
Each row is a PQ-code
Returns:
np.ndarray: Reconstructed vectors with shape=(N, D) and dtype=np.float32 | Given PQ-codes, reconstruct original D-dimensional vectors
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] | def decode(self, codes):
"""Given PQ-codes, reconstruct original D-dimensional vectors
approximately by fetching the codewords.
Args:
codes (np.ndarray): PQ-cdoes with shape=(N, M) and dtype=self.code_dtype.
Each row is a PQ-code
Returns:
np.ndarray: Reconstructed vectors with shape=(N, D) and dtype=np.float32
"""
assert codes.ndim == 2
N, M = codes.shape
assert M == self.M
assert codes.dtype == self.code_dtype
vecs = np.empty((N, self.Ds * self.M), dtype=np.float32)
for m in range(self.M):
vecs[:, m * self.Ds : (m + 1) * self.Ds] = self.codewords[m][codes[:, m], :]
return vecs | [
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salesforce/cloudsplaining | c932ea61de7b0f12d77bb4144fee343245d68d3f | cloudsplaining/scan/user_details.py | python | UserDetailList.get_all_iam_statements_for_user | (
self, name: str
) | return None | Returns a list of all StatementDetail objects across all the policies assigned to the user | Returns a list of all StatementDetail objects across all the policies assigned to the user | [
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] | def get_all_iam_statements_for_user(
self, name: str
) -> Optional[List[StatementDetail]]:
"""Returns a list of all StatementDetail objects across all the policies assigned to the user"""
for user_detail in self.users:
if user_detail.user_name == name:
return user_detail.all_iam_statements
return None | [
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replit-archive/empythoned | 977ec10ced29a3541a4973dc2b59910805695752 | cpython/Lib/mhlib.py | python | Folder.parsesequence | (self, seq) | Parse an MH sequence specification into a message list.
Attempt to mimic mh-sequence(5) as close as possible.
Also attempt to mimic observed behavior regarding which
conditions cause which error messages. | Parse an MH sequence specification into a message list.
Attempt to mimic mh-sequence(5) as close as possible.
Also attempt to mimic observed behavior regarding which
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"""Parse an MH sequence specification into a message list.
Attempt to mimic mh-sequence(5) as close as possible.
Also attempt to mimic observed behavior regarding which
conditions cause which error messages."""
# XXX Still not complete (see mh-format(5)).
# Missing are:
# - 'prev', 'next' as count
# - Sequence-Negation option
all = self.listmessages()
# Observed behavior: test for empty folder is done first
if not all:
raise Error, "no messages in %s" % self.name
# Common case first: all is frequently the default
if seq == 'all':
return all
# Test for X:Y before X-Y because 'seq:-n' matches both
i = seq.find(':')
if i >= 0:
head, dir, tail = seq[:i], '', seq[i+1:]
if tail[:1] in '-+':
dir, tail = tail[:1], tail[1:]
if not isnumeric(tail):
raise Error, "bad message list %s" % seq
try:
count = int(tail)
except (ValueError, OverflowError):
# Can't use sys.maxint because of i+count below
count = len(all)
try:
anchor = self._parseindex(head, all)
except Error, msg:
seqs = self.getsequences()
if not head in seqs:
if not msg:
msg = "bad message list %s" % seq
raise Error, msg, sys.exc_info()[2]
msgs = seqs[head]
if not msgs:
raise Error, "sequence %s empty" % head
if dir == '-':
return msgs[-count:]
else:
return msgs[:count]
else:
if not dir:
if head in ('prev', 'last'):
dir = '-'
if dir == '-':
i = bisect(all, anchor)
return all[max(0, i-count):i]
else:
i = bisect(all, anchor-1)
return all[i:i+count]
# Test for X-Y next
i = seq.find('-')
if i >= 0:
begin = self._parseindex(seq[:i], all)
end = self._parseindex(seq[i+1:], all)
i = bisect(all, begin-1)
j = bisect(all, end)
r = all[i:j]
if not r:
raise Error, "bad message list %s" % seq
return r
# Neither X:Y nor X-Y; must be a number or a (pseudo-)sequence
try:
n = self._parseindex(seq, all)
except Error, msg:
seqs = self.getsequences()
if not seq in seqs:
if not msg:
msg = "bad message list %s" % seq
raise Error, msg
return seqs[seq]
else:
if n not in all:
if isnumeric(seq):
raise Error, "message %d doesn't exist" % n
else:
raise Error, "no %s message" % seq
else:
return [n] | [
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openshift/openshift-tools | 1188778e728a6e4781acf728123e5b356380fe6f | openshift/installer/vendored/openshift-ansible-3.11.28-1/roles/lib_vendored_deps/library/oc_adm_registry.py | python | DeploymentConfig.exists_volume_mount | (self, volume_mount) | return volume_mount_found | return whether a volume mount exists | return whether a volume mount exists | [
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''' return whether a volume mount exists '''
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if not exist_volume_mounts:
return False
volume_mount_found = False
for exist_volume_mount in exist_volume_mounts:
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break
return volume_mount_found | [
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fofix/fofix | 7730d1503c66562b901f62b33a5bd46c3d5e5c34 | fofix/core/Image.py | python | drawImage | (image, scale=(1.0, -1.0), coord=(0, 0), rot=0, color=(1, 1, 1, 1),
rect=(0, 1, 0, 1), stretched=0, fit=CENTER, alignment=CENTER,
valignment=CENTER) | return True | Draws the image/surface to screen
:param image: The OpenGL surface
:param scale: Scale factor (between 0.0 and 1.0, second value must be negative due to texture flipping)
:param coord: Where the image will be translated to on the screen
:param rot: How many degrees it will be rotated
:param color: The color of the image (R, G, B, A)
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:param rect: The surface rectangle, this is used for cropping the texture.
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:param alignment: Adjusts the texture so the coordinate for x-axis placement can either be
on the left side (0), center point (1), or right(2) side of the image
:param valignment: Adjusts the texture so the coordinate for y-axis placement can either be
on the bottom side (0), center point (1), or top(2) side of the image
:rtype: boolean | Draws the image/surface to screen | [
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] | def drawImage(image, scale=(1.0, -1.0), coord=(0, 0), rot=0, color=(1, 1, 1, 1),
rect=(0, 1, 0, 1), stretched=0, fit=CENTER, alignment=CENTER,
valignment=CENTER):
"""
Draws the image/surface to screen
:param image: The OpenGL surface
:param scale: Scale factor (between 0.0 and 1.0, second value must be negative due to texture flipping)
:param coord: Where the image will be translated to on the screen
:param rot: How many degrees it will be rotated
:param color: The color of the image (R, G, B, A)
(values are between 0.0 and 1.0, Alpha is 1.0 by default)
:param rect: The surface rectangle, this is used for cropping the texture.
Any other values will have the image maintain its size passed by scale
:param alignment: Adjusts the texture so the coordinate for x-axis placement can either be
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:param valignment: Adjusts the texture so the coordinate for y-axis placement can either be
on the bottom side (0), center point (1), or top(2) side of the image
:rtype: boolean
"""
if not isinstance(image, ImgDrawing):
return False
image.setRect(rect)
image.setScale(scale[0], scale[1], stretched)
image.setPosition(coord[0], coord[1], fit)
image.setAlignment(alignment)
image.setVAlignment(valignment)
image.setAngle(rot)
image.setColor(color)
image.draw()
return True | [
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AppScale/gts | 46f909cf5dc5ba81faf9d81dc9af598dcf8a82a9 | AppServer/google/appengine/ext/ndb/context.py | python | Context._use_memcache | (self, key, options=None) | return flag | Return whether to use memcache for this key.
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key: Key instance.
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Args:
key: Key instance.
options: ContextOptions instance, or None.
Returns:
True if the key should be cached in memcache, False otherwise.
"""
flag = ContextOptions.use_memcache(options)
if flag is None:
flag = self._memcache_policy(key)
if flag is None:
flag = ContextOptions.use_memcache(self._conn.config)
if flag is None:
flag = True
return flag | [
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elimintz/justpy | 42275e9c6e00373f09affd7d781a278383171807 | justpy/chartcomponents.py | python | HighCharts.select_point | (self, point_list, websocket) | return True | point_list is list of of dictionaries whose keys are:
'id': the chart id
'series': the series index
'point': the point index
Values are all integers
Example:
{'id': chart_id, 'series': msg.series_index, 'point': msg.point_index} | point_list is list of of dictionaries whose keys are:
'id': the chart id
'series': the series index
'point': the point index
Values are all integers
Example:
{'id': chart_id, 'series': msg.series_index, 'point': msg.point_index} | [
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'point': the point index
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"""
await websocket.send_json({'type': 'select_point', 'data': point_list})
# Return True not None so that the page does not update
return True | [
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twilio/twilio-python | 6e1e811ea57a1edfadd5161ace87397c563f6915 | twilio/rest/video/v1/room/__init__.py | python | RoomPage.get_instance | (self, payload) | return RoomInstance(self._version, payload, ) | Build an instance of RoomInstance
:param dict payload: Payload response from the API
:returns: twilio.rest.video.v1.room.RoomInstance
:rtype: twilio.rest.video.v1.room.RoomInstance | Build an instance of RoomInstance | [
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] | def get_instance(self, payload):
"""
Build an instance of RoomInstance
:param dict payload: Payload response from the API
:returns: twilio.rest.video.v1.room.RoomInstance
:rtype: twilio.rest.video.v1.room.RoomInstance
"""
return RoomInstance(self._version, payload, ) | [
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aiidateam/aiida-core | c743a335480f8bb3a5e4ebd2463a31f9f3b9f9b2 | aiida/backends/sqlalchemy/migrations/versions/b8b23ddefad4_dbgroup_name_to_label_type_to_type_string.py | python | upgrade | () | The upgrade migration actions. | The upgrade migration actions. | [
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"migration",
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"."
] | def upgrade():
"""The upgrade migration actions."""
# dropping
op.drop_constraint('db_dbgroup_name_type_key', 'db_dbgroup')
op.drop_index('ix_db_dbgroup_name', 'db_dbgroup')
op.drop_index('ix_db_dbgroup_type', 'db_dbgroup')
# renaming
op.alter_column('db_dbgroup', 'name', new_column_name='label')
op.alter_column('db_dbgroup', 'type', new_column_name='type_string')
# creating
op.create_unique_constraint('db_dbgroup_label_type_string_key', 'db_dbgroup', ['label', 'type_string'])
op.create_index('ix_db_dbgroup_label', 'db_dbgroup', ['label'])
op.create_index('ix_db_dbgroup_type_string', 'db_dbgroup', ['type_string']) | [
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napari/napari | dbf4158e801fa7a429de8ef1cdee73bf6d64c61e | napari/utils/perf/_config.py | python | _patch_perf_timer | (parent, callable: str, label: str) | Patches the callable to run it inside a perf_timer.
Parameters
----------
parent
The module or class that contains the callable.
callable : str
The name of the callable (function or method).
label : str
The <function> or <class>.<method> we are patching. | Patches the callable to run it inside a perf_timer. | [
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] | def _patch_perf_timer(parent, callable: str, label: str) -> None:
"""Patches the callable to run it inside a perf_timer.
Parameters
----------
parent
The module or class that contains the callable.
callable : str
The name of the callable (function or method).
label : str
The <function> or <class>.<method> we are patching.
"""
@wrapt.patch_function_wrapper(parent, callable)
def perf_time_callable(wrapped, instance, args, kwargs):
with perf_timer(f"{label}"):
return wrapped(*args, **kwargs) | [
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deanishe/zothero | 5b057ef080ee730d82d5dd15e064d2a4730c2b11 | src/lib/workflow/workflow.py | python | Workflow.data_serializer | (self, serializer_name) | Set the default cache serialization format.
.. versionadded:: 1.8
This serializer is used by :meth:`store_data()` and
:meth:`stored_data()`
The specified serializer must already by registered with the
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"""Set the default cache serialization format.
.. versionadded:: 1.8
This serializer is used by :meth:`store_data()` and
:meth:`stored_data()`
The specified serializer must already by registered with the
:class:`SerializerManager` at `~workflow.workflow.manager`,
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:param serializer_name: Name of serializer to use by default.
"""
if manager.serializer(serializer_name) is None:
raise ValueError(
'Unknown serializer : `{0}`. Register your serializer '
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self.logger.debug('default data serializer: %s', serializer_name)
self._data_serializer = serializer_name | [
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wummel/linkchecker | c2ce810c3fb00b895a841a7be6b2e78c64e7b042 | linkcheck/HtmlParser/htmllib.py | python | HtmlPrettyPrinter.comment | (self, data) | Print HTML comment.
@param data: the comment
@type data: string
@return: None | Print HTML comment. | [
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"""
Print HTML comment.
@param data: the comment
@type data: string
@return: None
"""
data = data.encode(self.encoding, "ignore")
self.fd.write("<!--%s-->" % data) | [
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thenetcircle/dino | 1047c3458e91a1b4189e9f48f1393b3a68a935b3 | dino/storage/cassandra_interface.py | python | IDriver.msgs_select | (self, to_user_id: str) | find all messages sent to a user id/room id
:param to_user_id: either a user id or room uuid
:return: all messages to this user/room | find all messages sent to a user id/room id | [
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] | def msgs_select(self, to_user_id: str):
"""
find all messages sent to a user id/room id
:param to_user_id: either a user id or room uuid
:return: all messages to this user/room
""" | [
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ajinabraham/OWASP-Xenotix-XSS-Exploit-Framework | cb692f527e4e819b6c228187c5702d990a180043 | external/Scripting Engine/Xenotix Python Scripting Engine/packages/IronPython.StdLib.2.7.4/content/Lib/Queue.py | python | Queue.put | (self, item, block=True, timeout=None) | Put an item into the queue.
If optional args 'block' is true and 'timeout' is None (the default),
block if necessary until a free slot is available. If 'timeout' is
a positive number, it blocks at most 'timeout' seconds and raises
the Full exception if no free slot was available within that time.
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is immediately available, else raise the Full exception ('timeout'
is ignored in that case). | Put an item into the queue. | [
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"""Put an item into the queue.
If optional args 'block' is true and 'timeout' is None (the default),
block if necessary until a free slot is available. If 'timeout' is
a positive number, it blocks at most 'timeout' seconds and raises
the Full exception if no free slot was available within that time.
Otherwise ('block' is false), put an item on the queue if a free slot
is immediately available, else raise the Full exception ('timeout'
is ignored in that case).
"""
self.not_full.acquire()
try:
if self.maxsize > 0:
if not block:
if self._qsize() == self.maxsize:
raise Full
elif timeout is None:
while self._qsize() == self.maxsize:
self.not_full.wait()
elif timeout < 0:
raise ValueError("'timeout' must be a positive number")
else:
endtime = _time() + timeout
while self._qsize() == self.maxsize:
remaining = endtime - _time()
if remaining <= 0.0:
raise Full
self.not_full.wait(remaining)
self._put(item)
self.unfinished_tasks += 1
self.not_empty.notify()
finally:
self.not_full.release() | [
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quantopian/pgcontents | 51f8febcf6ece4e88b047768b9ce18553162d63c | pgcontents/pgmanager.py | python | PostgresContentsManager._directory_model_from_db | (self, record, content) | return model | Build a directory model from database directory record. | Build a directory model from database directory record. | [
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"""
Build a directory model from database directory record.
"""
model = base_directory_model(to_api_path(record['name']))
if content:
model['format'] = 'json'
model['content'] = list(
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return model | [
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pypa/pipenv | b21baade71a86ab3ee1429f71fbc14d4f95fb75d | pipenv/vendor/tomlkit/items.py | python | Float.__init__ | (self, _, trivia, raw) | [] | def __init__(self, _, trivia, raw): # type: (float, Trivia, str) -> None
super(Float, self).__init__(trivia)
self._raw = raw
self._sign = False
if re.match(r"^[+\-].+$", raw):
self._sign = True | [
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... | https://github.com/pypa/pipenv/blob/b21baade71a86ab3ee1429f71fbc14d4f95fb75d/pipenv/vendor/tomlkit/items.py#L453-L460 | ||||
numba/numba | bf480b9e0da858a65508c2b17759a72ee6a44c51 | numba/cuda/simulator/cudadrv/nvvm.py | python | get_supported_ccs | () | return () | [] | def get_supported_ccs():
return () | [
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BigBrotherBot/big-brother-bot | 848823c71413c86e7f1ff9584f43e08d40a7f2c0 | b3/fake.py | python | FakeClient.__init__ | (self, console, **kwargs) | Object constructor.
:param console: The console implementation | Object constructor.
:param console: The console implementation | [
"Object",
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".",
":",
"param",
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":",
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] | def __init__(self, console, **kwargs):
"""
Object constructor.
:param console: The console implementation
"""
self.console = console
self.message_history = [] # this allows unittests to check if a message was sent to the client
b3.clients.Client.__init__(self, **kwargs) | [
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... | https://github.com/BigBrotherBot/big-brother-bot/blob/848823c71413c86e7f1ff9584f43e08d40a7f2c0/b3/fake.py#L265-L272 | ||
kuri65536/python-for-android | 26402a08fc46b09ef94e8d7a6bbc3a54ff9d0891 | python-modules/twisted/twisted/news/nntp.py | python | NNTPClient.gotXHeader | (self, headers) | Override for notification when getXHeader() action is successful | Override for notification when getXHeader() action is successful | [
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] | https://github.com/kuri65536/python-for-android/blob/26402a08fc46b09ef94e8d7a6bbc3a54ff9d0891/python-modules/twisted/twisted/news/nntp.py#L166-L167 | ||
zhreshold/mxnet-ssd | 821a1c5049679f798976c8bf58b460ffaa098458 | evaluate/evaluate_net.py | python | evaluate_net | (net, path_imgrec, num_classes, mean_pixels, data_shape,
model_prefix, epoch, ctx=mx.cpu(), batch_size=1,
path_imglist="", nms_thresh=0.45, force_nms=False,
ovp_thresh=0.5, use_difficult=False, class_names=None,
voc07_metric=False, frequent=20) | evalute network given validation record file
Parameters:
----------
net : str or None
Network name or use None to load from json without modifying
path_imgrec : str
path to the record validation file
path_imglist : str
path to the list file to replace labels in record file, optional
num_classes : int
number of classes, not including background
mean_pixels : tuple
(mean_r, mean_g, mean_b)
data_shape : tuple or int
(3, height, width) or height/width
model_prefix : str
model prefix of saved checkpoint
epoch : int
load model epoch
ctx : mx.ctx
mx.gpu() or mx.cpu()
batch_size : int
validation batch size
nms_thresh : float
non-maximum suppression threshold
force_nms : boolean
whether suppress different class objects
ovp_thresh : float
AP overlap threshold for true/false postives
use_difficult : boolean
whether to use difficult objects in evaluation if applicable
class_names : comma separated str
class names in string, must correspond to num_classes if set
voc07_metric : boolean
whether to use 11-point evluation as in VOC07 competition
frequent : int
frequency to print out validation status | evalute network given validation record file | [
"evalute",
"network",
"given",
"validation",
"record",
"file"
] | def evaluate_net(net, path_imgrec, num_classes, mean_pixels, data_shape,
model_prefix, epoch, ctx=mx.cpu(), batch_size=1,
path_imglist="", nms_thresh=0.45, force_nms=False,
ovp_thresh=0.5, use_difficult=False, class_names=None,
voc07_metric=False, frequent=20):
"""
evalute network given validation record file
Parameters:
----------
net : str or None
Network name or use None to load from json without modifying
path_imgrec : str
path to the record validation file
path_imglist : str
path to the list file to replace labels in record file, optional
num_classes : int
number of classes, not including background
mean_pixels : tuple
(mean_r, mean_g, mean_b)
data_shape : tuple or int
(3, height, width) or height/width
model_prefix : str
model prefix of saved checkpoint
epoch : int
load model epoch
ctx : mx.ctx
mx.gpu() or mx.cpu()
batch_size : int
validation batch size
nms_thresh : float
non-maximum suppression threshold
force_nms : boolean
whether suppress different class objects
ovp_thresh : float
AP overlap threshold for true/false postives
use_difficult : boolean
whether to use difficult objects in evaluation if applicable
class_names : comma separated str
class names in string, must correspond to num_classes if set
voc07_metric : boolean
whether to use 11-point evluation as in VOC07 competition
frequent : int
frequency to print out validation status
"""
# set up logger
logging.basicConfig()
logger = logging.getLogger()
logger.setLevel(logging.INFO)
# args
if isinstance(data_shape, int):
data_shape = (3, data_shape, data_shape)
assert len(data_shape) == 3 and data_shape[0] == 3
#model_prefix += '_' + str(data_shape[1])
# iterator
eval_iter = DetRecordIter(path_imgrec, batch_size, data_shape,
path_imglist=path_imglist, **cfg.valid)
# model params
load_net, args, auxs = mx.model.load_checkpoint(model_prefix, epoch)
# network
if net is None:
net = load_net
else:
net = get_symbol(net, data_shape[1], num_classes=num_classes,
nms_thresh=nms_thresh, force_suppress=force_nms)
if not 'label' in net.list_arguments():
label = mx.sym.Variable(name='label')
net = mx.sym.Group([net, label])
# init module
mod = mx.mod.Module(net, label_names=('label',), logger=logger, context=ctx,
fixed_param_names=net.list_arguments())
mod.bind(data_shapes=eval_iter.provide_data, label_shapes=eval_iter.provide_label)
mod.set_params(args, auxs, allow_missing=False, force_init=True)
# run evaluation
if voc07_metric:
metric = VOC07MApMetric(ovp_thresh, use_difficult, class_names,
roc_output_path=os.path.join(os.path.dirname(model_prefix), 'roc'))
else:
metric = MApMetric(ovp_thresh, use_difficult, class_names,
roc_output_path=os.path.join(os.path.dirname(model_prefix), 'roc'))
results = mod.score(eval_iter, metric, num_batch=None,
batch_end_callback=mx.callback.Speedometer(batch_size,
frequent=frequent,
auto_reset=False))
for k, v in results:
print("{}: {}".format(k, v)) | [
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reddit-archive/reddit | 753b17407e9a9dca09558526805922de24133d53 | r2/r2/models/ip.py | python | set_account_ip | (account_id, ip, date=None) | Set an IP address as having accessed an account.
Updates all underlying datastores. | Set an IP address as having accessed an account. | [
"Set",
"an",
"IP",
"address",
"as",
"having",
"accessed",
"an",
"account",
"."
] | def set_account_ip(account_id, ip, date=None):
"""Set an IP address as having accessed an account.
Updates all underlying datastores.
"""
# don't store private IPs, send event + string so we can investigate this
if ip_address(ip).is_private:
g.stats.simple_event('ip.private_ip_storage_prevented')
g.stats.count_string('private_ip_storage_prevented', ip)
return
if date is None:
date = datetime.datetime.now(g.tz)
m = Mutator(CONNECTION_POOL)
m.insert(IPsByAccount._cf, str(account_id), {date: ip}, ttl=CF_TTL)
m.insert(AccountsByIP._cf, ip, {date: str(account_id)}, ttl=CF_TTL)
m.send() | [
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mozillazg/pypy | 2ff5cd960c075c991389f842c6d59e71cf0cb7d0 | rpython/rlib/rposix_stat.py | python | make_stat_result | (tup) | return os.stat_result(positional, kwds) | Turn a tuple into an os.stat_result object. | Turn a tuple into an os.stat_result object. | [
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"tuple",
"into",
"an",
"os",
".",
"stat_result",
"object",
"."
] | def make_stat_result(tup):
"""Turn a tuple into an os.stat_result object."""
assert len(tup) == len(STAT_FIELDS)
assert float not in [type(x) for x in tup]
positional = []
for i in range(N_INDEXABLE_FIELDS):
name, TYPE = STAT_FIELDS[i]
value = lltype.cast_primitive(TYPE, tup[i])
positional.append(value)
kwds = {}
if sys.platform == 'win32':
kwds['st_atime'] = tup[7] + 1e-9 * tup[-5]
kwds['st_mtime'] = tup[8] + 1e-9 * tup[-4]
kwds['st_ctime'] = tup[9] + 1e-9 * tup[-3]
kwds['st_file_attributes'] = tup[-2]
kwds['st_reparse_tag'] = tup[-1]
else:
kwds['st_atime'] = tup[7] + 1e-9 * tup[-3]
kwds['st_mtime'] = tup[8] + 1e-9 * tup[-2]
kwds['st_ctime'] = tup[9] + 1e-9 * tup[-1]
for value, (name, TYPE) in zip(tup, STAT_FIELDS)[N_INDEXABLE_FIELDS:]:
if name.startswith('nsec_'):
continue # ignore the nsec_Xtime here
kwds[name] = lltype.cast_primitive(TYPE, value)
return os.stat_result(positional, kwds) | [
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holzschu/Carnets | 44effb10ddfc6aa5c8b0687582a724ba82c6b547 | Library/lib/python3.7/site-packages/pip/_internal/index.py | python | PackageFinder.__init__ | (
self,
find_links, # type: List[str]
index_urls, # type: List[str]
allow_all_prereleases=False, # type: bool
trusted_hosts=None, # type: Optional[Iterable[str]]
session=None, # type: Optional[PipSession]
format_control=None, # type: Optional[FormatControl]
platform=None, # type: Optional[str]
versions=None, # type: Optional[List[str]]
abi=None, # type: Optional[str]
implementation=None, # type: Optional[str]
prefer_binary=False # type: bool
) | Create a PackageFinder.
:param format_control: A FormatControl object or None. Used to control
the selection of source packages / binary packages when consulting
the index and links.
:param platform: A string or None. If None, searches for packages
that are supported by the current system. Otherwise, will find
packages that can be built on the platform passed in. These
packages will only be downloaded for distribution: they will
not be built locally.
:param versions: A list of strings or None. This is passed directly
to pep425tags.py in the get_supported() method.
:param abi: A string or None. This is passed directly
to pep425tags.py in the get_supported() method.
:param implementation: A string or None. This is passed directly
to pep425tags.py in the get_supported() method.
:param prefer_binary: Whether to prefer an old, but valid, binary
dist over a new source dist. | Create a PackageFinder. | [
"Create",
"a",
"PackageFinder",
"."
] | def __init__(
self,
find_links, # type: List[str]
index_urls, # type: List[str]
allow_all_prereleases=False, # type: bool
trusted_hosts=None, # type: Optional[Iterable[str]]
session=None, # type: Optional[PipSession]
format_control=None, # type: Optional[FormatControl]
platform=None, # type: Optional[str]
versions=None, # type: Optional[List[str]]
abi=None, # type: Optional[str]
implementation=None, # type: Optional[str]
prefer_binary=False # type: bool
):
# type: (...) -> None
"""Create a PackageFinder.
:param format_control: A FormatControl object or None. Used to control
the selection of source packages / binary packages when consulting
the index and links.
:param platform: A string or None. If None, searches for packages
that are supported by the current system. Otherwise, will find
packages that can be built on the platform passed in. These
packages will only be downloaded for distribution: they will
not be built locally.
:param versions: A list of strings or None. This is passed directly
to pep425tags.py in the get_supported() method.
:param abi: A string or None. This is passed directly
to pep425tags.py in the get_supported() method.
:param implementation: A string or None. This is passed directly
to pep425tags.py in the get_supported() method.
:param prefer_binary: Whether to prefer an old, but valid, binary
dist over a new source dist.
"""
if session is None:
raise TypeError(
"PackageFinder() missing 1 required keyword argument: "
"'session'"
)
# Build find_links. If an argument starts with ~, it may be
# a local file relative to a home directory. So try normalizing
# it and if it exists, use the normalized version.
# This is deliberately conservative - it might be fine just to
# blindly normalize anything starting with a ~...
self.find_links = [] # type: List[str]
for link in find_links:
if link.startswith('~'):
new_link = normalize_path(link)
if os.path.exists(new_link):
link = new_link
self.find_links.append(link)
self.index_urls = index_urls
# These are boring links that have already been logged somehow:
self.logged_links = set() # type: Set[Link]
self.format_control = format_control or FormatControl(set(), set())
# Domains that we won't emit warnings for when not using HTTPS
self.secure_origins = [
("*", host, "*")
for host in (trusted_hosts if trusted_hosts else [])
] # type: List[SecureOrigin]
# Do we want to allow _all_ pre-releases?
self.allow_all_prereleases = allow_all_prereleases
# The Session we'll use to make requests
self.session = session
# The valid tags to check potential found wheel candidates against
valid_tags = get_supported(
versions=versions,
platform=platform,
abi=abi,
impl=implementation,
)
self.candidate_evaluator = CandidateEvaluator(
valid_tags=valid_tags, prefer_binary=prefer_binary,
)
# If we don't have TLS enabled, then WARN if anyplace we're looking
# relies on TLS.
if not HAS_TLS:
for link in itertools.chain(self.index_urls, self.find_links):
parsed = urllib_parse.urlparse(link)
if parsed.scheme == "https":
logger.warning(
"pip is configured with locations that require "
"TLS/SSL, however the ssl module in Python is not "
"available."
)
break | [
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edfungus/Crouton | ada98b3930192938a48909072b45cb84b945f875 | clients/esp8266_clients/venv/lib/python2.7/site-packages/pip/utils/appdirs.py | python | _get_win_folder_from_registry | (csidl_name) | return directory | This is a fallback technique at best. I'm not sure if using the
registry for this guarantees us the correct answer for all CSIDL_*
names. | This is a fallback technique at best. I'm not sure if using the
registry for this guarantees us the correct answer for all CSIDL_*
names. | [
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"the",
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"answer",
"for",
"all",
"CSIDL_",
"*",
"names",
"."
] | def _get_win_folder_from_registry(csidl_name):
"""
This is a fallback technique at best. I'm not sure if using the
registry for this guarantees us the correct answer for all CSIDL_*
names.
"""
import _winreg
shell_folder_name = {
"CSIDL_APPDATA": "AppData",
"CSIDL_COMMON_APPDATA": "Common AppData",
"CSIDL_LOCAL_APPDATA": "Local AppData",
}[csidl_name]
key = _winreg.OpenKey(
_winreg.HKEY_CURRENT_USER,
r"Software\Microsoft\Windows\CurrentVersion\Explorer\Shell Folders"
)
directory, _type = _winreg.QueryValueEx(key, shell_folder_name)
return directory | [
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oilshell/oil | 94388e7d44a9ad879b12615f6203b38596b5a2d3 | Python-2.7.13/Parser/asdl.py | python | ASDLParser.p_field_3 | (self, (type, _, name)) | return Field(type, name, opt=True) | field ::= Id ? Id | field ::= Id ? Id | [
"field",
"::",
"=",
"Id",
"?",
"Id"
] | def p_field_3(self, (type, _, name)):
" field ::= Id ? Id "
return Field(type, name, opt=True) | [
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thingsboard/thingsboard-gateway | 1d1b1fc2450852dbd56ff137c6bfd49143dc758d | thingsboard_gateway/connectors/snmp/snmp_uplink_converter.py | python | SNMPUplinkConverter.convert | (self, config, data) | return result | [] | def convert(self, config, data):
result = {
"deviceName": self.__config["deviceName"],
"deviceType": self.__config["deviceType"],
"attributes": [],
"telemetry": []
}
try:
if isinstance(data, dict):
result[config[0]].append({config[1]["key"]: {str(k): str(v) for k, v in data.items()}})
elif isinstance(data, list):
if isinstance(data[0], str):
result[config[0]].append({config[1]["key"]: ','.join(data)})
elif isinstance(data[0], dict):
res = {}
for item in data:
res.update(**item)
result[config[0]].append({config[1]["key"]: {str(k): str(v) for k, v in res.items()}})
elif isinstance(data, str):
result[config[0]].append({config[1]["key"]: data})
elif isinstance(data, bytes):
result[config[0]].append({config[1]["key"]: data.decode("UTF-8")})
else:
result[config[0]].append({config[1]["key"]: data})
log.debug(result)
except Exception as e:
log.exception(e)
return result | [
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pwnieexpress/pwn_plug_sources | 1a23324f5dc2c3de20f9c810269b6a29b2758cad | src/set/src/core/scapy.py | python | PcapReader.fileno | (self) | return self.f.fileno() | [] | def fileno(self):
return self.f.fileno() | [
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")"
] | https://github.com/pwnieexpress/pwn_plug_sources/blob/1a23324f5dc2c3de20f9c810269b6a29b2758cad/src/set/src/core/scapy.py#L10397-L10398 | |||
wechatpy/wechatpy | 5f693a7e90156786c2540ad3c941d12cdf6d88ef | wechatpy/client/api/invoice.py | python | WeChatInvoice.scan_title | (self, scan_text) | return self._post(
"scantitle",
data={
"scan_text": scan_text,
},
) | 根据扫描码，获取用户发票抬头
商户扫用户“我的—个人信息—我的发票抬头”里面的抬头二维码后，通过调用本接口，可以获取用户抬头信息
详情请参考
https://mp.weixin.qq.com/wiki?id=mp1496554912_vfWU0
:param scan_text: 扫码后获取的文本
:return: 用户的发票抬头数据
:rtype: dict | 根据扫描码，获取用户发票抬头
商户扫用户“我的—个人信息—我的发票抬头”里面的抬头二维码后，通过调用本接口，可以获取用户抬头信息
详情请参考
https://mp.weixin.qq.com/wiki?id=mp1496554912_vfWU0 | [
"根据扫描码，获取用户发票抬头",
"商户扫用户“我的—个人信息—我的发票抬头”里面的抬头二维码后，通过调用本接口，可以获取用户抬头信息",
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"""
根据扫描码，获取用户发票抬头
商户扫用户“我的—个人信息—我的发票抬头”里面的抬头二维码后，通过调用本接口，可以获取用户抬头信息
详情请参考
https://mp.weixin.qq.com/wiki?id=mp1496554912_vfWU0
:param scan_text: 扫码后获取的文本
:return: 用户的发票抬头数据
:rtype: dict
"""
return self._post(
"scantitle",
data={
"scan_text": scan_text,
},
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travisgoodspeed/goodfet | 1750cc1e8588af5470385e52fa098ca7364c2863 | client/ATMEL_USART.py | python | USART.crStartBreak | (self) | [] | def crStartBreak(self):
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openstack/cloudkitty | 78da8eac53c56566191aad548f035158877ccfe5 | cloudkitty/utils/__init__.py | python | iso2dt | (iso_date) | return trans_dt | iso8601 format to datetime. | iso8601 format to datetime. | [
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] | def iso2dt(iso_date):
"""iso8601 format to datetime."""
iso_dt = timeutils.parse_isotime(iso_date)
trans_dt = timeutils.normalize_time(iso_dt)
return trans_dt | [
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wistbean/fxxkpython | 88e16d79d8dd37236ba6ecd0d0ff11d63143968c | vip/qyxuan/projects/Snake/venv/lib/python3.6/site-packages/pip-19.0.3-py3.6.egg/pip/_vendor/ipaddress.py | python | _split_optional_netmask | (address) | return addr | Helper to split the netmask and raise AddressValueError if needed | Helper to split the netmask and raise AddressValueError if needed | [
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"""Helper to split the netmask and raise AddressValueError if needed"""
addr = _compat_str(address).split('/')
if len(addr) > 2:
raise AddressValueError("Only one '/' permitted in %r" % address)
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kivy/kivy | fbf561f73ddba9941b1b7e771f86264c6e6eef36 | kivy/core/window/__init__.py | python | WindowBase.on_keyboard | (self, key, scancode=None, codepoint=None,
modifier=None, **kwargs) | Event called when keyboard is used.
.. warning::
Some providers may omit `scancode`, `codepoint` and/or `modifier`. | Event called when keyboard is used. | [
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] | def on_keyboard(self, key, scancode=None, codepoint=None,
modifier=None, **kwargs):
'''Event called when keyboard is used.
.. warning::
Some providers may omit `scancode`, `codepoint` and/or `modifier`.
'''
if 'unicode' in kwargs:
Logger.warning("The use of the unicode parameter is deprecated, "
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# Quit if user presses ESC or the typical OSX shortcuts CMD+q or CMD+w
# TODO If just CMD+w is pressed, only the window should be closed.
is_osx = platform == 'darwin'
if WindowBase.on_keyboard.exit_on_escape:
if key == 27 or all([is_osx, key in [113, 119], modifier == 1024]):
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securesystemslab/zippy | ff0e84ac99442c2c55fe1d285332cfd4e185e089 | zippy/benchmarks/src/benchmarks/sympy/sympy/solvers/recurr.py | python | rsolve_poly | (coeffs, f, n, **hints) | Given linear recurrence operator `\operatorname{L}` of order
`k` with polynomial coefficients and inhomogeneous equation
`\operatorname{L} y = f`, where `f` is a polynomial, we seek for
all polynomial solutions over field `K` of characteristic zero.
The algorithm performs two basic steps:
(1) Compute degree `N` of the general polynomial solution.
(2) Find all polynomials of degree `N` or less
of `\operatorname{L} y = f`.
There are two methods for computing the polynomial solutions.
If the degree bound is relatively small, i.e. it's smaller than
or equal to the order of the recurrence, then naive method of
undetermined coefficients is being used. This gives system
of algebraic equations with `N+1` unknowns.
In the other case, the algorithm performs transformation of the
initial equation to an equivalent one, for which the system of
algebraic equations has only `r` indeterminates. This method is
quite sophisticated (in comparison with the naive one) and was
invented together by Abramov, Bronstein and Petkovsek.
It is possible to generalize the algorithm implemented here to
the case of linear q-difference and differential equations.
Lets say that we would like to compute `m`-th Bernoulli polynomial
up to a constant. For this we can use `b(n+1) - b(n) = m n^{m-1}`
recurrence, which has solution `b(n) = B_m + C`. For example:
>>> from sympy import Symbol, rsolve_poly
>>> n = Symbol('n', integer=True)
>>> rsolve_poly([-1, 1], 4*n**3, n)
C0 + n**4 - 2*n**3 + n**2
References
==========
.. [1] S. A. Abramov, M. Bronstein and M. Petkovsek, On polynomial
solutions of linear operator equations, in: T. Levelt, ed.,
Proc. ISSAC '95, ACM Press, New York, 1995, 290-296.
.. [2] M. Petkovsek, Hypergeometric solutions of linear recurrences
with polynomial coefficients, J. Symbolic Computation,
14 (1992), 243-264.
.. [3] M. Petkovsek, H. S. Wilf, D. Zeilberger, A = B, 1996. | Given linear recurrence operator `\operatorname{L}` of order
`k` with polynomial coefficients and inhomogeneous equation
`\operatorname{L} y = f`, where `f` is a polynomial, we seek for
all polynomial solutions over field `K` of characteristic zero. | [
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"""
Given linear recurrence operator `\operatorname{L}` of order
`k` with polynomial coefficients and inhomogeneous equation
`\operatorname{L} y = f`, where `f` is a polynomial, we seek for
all polynomial solutions over field `K` of characteristic zero.
The algorithm performs two basic steps:
(1) Compute degree `N` of the general polynomial solution.
(2) Find all polynomials of degree `N` or less
of `\operatorname{L} y = f`.
There are two methods for computing the polynomial solutions.
If the degree bound is relatively small, i.e. it's smaller than
or equal to the order of the recurrence, then naive method of
undetermined coefficients is being used. This gives system
of algebraic equations with `N+1` unknowns.
In the other case, the algorithm performs transformation of the
initial equation to an equivalent one, for which the system of
algebraic equations has only `r` indeterminates. This method is
quite sophisticated (in comparison with the naive one) and was
invented together by Abramov, Bronstein and Petkovsek.
It is possible to generalize the algorithm implemented here to
the case of linear q-difference and differential equations.
Lets say that we would like to compute `m`-th Bernoulli polynomial
up to a constant. For this we can use `b(n+1) - b(n) = m n^{m-1}`
recurrence, which has solution `b(n) = B_m + C`. For example:
>>> from sympy import Symbol, rsolve_poly
>>> n = Symbol('n', integer=True)
>>> rsolve_poly([-1, 1], 4*n**3, n)
C0 + n**4 - 2*n**3 + n**2
References
==========
.. [1] S. A. Abramov, M. Bronstein and M. Petkovsek, On polynomial
solutions of linear operator equations, in: T. Levelt, ed.,
Proc. ISSAC '95, ACM Press, New York, 1995, 290-296.
.. [2] M. Petkovsek, Hypergeometric solutions of linear recurrences
with polynomial coefficients, J. Symbolic Computation,
14 (1992), 243-264.
.. [3] M. Petkovsek, H. S. Wilf, D. Zeilberger, A = B, 1996.
"""
f = sympify(f)
if not f.is_polynomial(n):
return None
homogeneous = f.is_zero
r = len(coeffs) - 1
coeffs = [ Poly(coeff, n) for coeff in coeffs ]
polys = [ Poly(0, n) ] * (r + 1)
terms = [ (S.Zero, S.NegativeInfinity) ] *(r + 1)
for i in xrange(0, r + 1):
for j in xrange(i, r + 1):
polys[i] += coeffs[j]*binomial(j, i)
if not polys[i].is_zero:
(exp,), coeff = polys[i].LT()
terms[i] = (coeff, exp)
d = b = terms[0][1]
for i in xrange(1, r + 1):
if terms[i][1] > d:
d = terms[i][1]
if terms[i][1] - i > b:
b = terms[i][1] - i
d, b = int(d), int(b)
x = Dummy('x')
degree_poly = S.Zero
for i in xrange(0, r + 1):
if terms[i][1] - i == b:
degree_poly += terms[i][0]*FallingFactorial(x, i)
nni_roots = list(roots(degree_poly, x, filter='Z',
predicate=lambda r: r >= 0).keys())
if nni_roots:
N = [max(nni_roots)]
else:
N = []
if homogeneous:
N += [-b - 1]
else:
N += [f.as_poly(n).degree() - b, -b - 1]
N = int(max(N))
if N < 0:
if homogeneous:
if hints.get('symbols', False):
return (S.Zero, [])
else:
return S.Zero
else:
return None
if N <= r:
C = []
y = E = S.Zero
for i in xrange(0, N + 1):
C.append(Symbol('C' + str(i)))
y += C[i] * n**i
for i in xrange(0, r + 1):
E += coeffs[i].as_expr()*y.subs(n, n + i)
solutions = solve_undetermined_coeffs(E - f, C, n)
if solutions is not None:
C = [ c for c in C if (c not in solutions) ]
result = y.subs(solutions)
else:
return None # TBD
else:
A = r
U = N + A + b + 1
nni_roots = list(roots(polys[r], filter='Z',
predicate=lambda r: r >= 0).keys())
if nni_roots != []:
a = max(nni_roots) + 1
else:
a = S.Zero
def _zero_vector(k):
return [S.Zero] * k
def _one_vector(k):
return [S.One] * k
def _delta(p, k):
B = S.One
D = p.subs(n, a + k)
for i in xrange(1, k + 1):
B *= -Rational(k - i + 1, i)
D += B * p.subs(n, a + k - i)
return D
alpha = {}
for i in xrange(-A, d + 1):
I = _one_vector(d + 1)
for k in xrange(1, d + 1):
I[k] = I[k - 1] * (x + i - k + 1)/k
alpha[i] = S.Zero
for j in xrange(0, A + 1):
for k in xrange(0, d + 1):
B = binomial(k, i + j)
D = _delta(polys[j].as_expr(), k)
alpha[i] += I[k]*B*D
V = Matrix(U, A, lambda i, j: int(i == j))
if homogeneous:
for i in xrange(A, U):
v = _zero_vector(A)
for k in xrange(1, A + b + 1):
if i - k < 0:
break
B = alpha[k - A].subs(x, i - k)
for j in xrange(0, A):
v[j] += B * V[i - k, j]
denom = alpha[-A].subs(x, i)
for j in xrange(0, A):
V[i, j] = -v[j] / denom
else:
G = _zero_vector(U)
for i in xrange(A, U):
v = _zero_vector(A)
g = S.Zero
for k in xrange(1, A + b + 1):
if i - k < 0:
break
B = alpha[k - A].subs(x, i - k)
for j in xrange(0, A):
v[j] += B * V[i - k, j]
g += B * G[i - k]
denom = alpha[-A].subs(x, i)
for j in xrange(0, A):
V[i, j] = -v[j] / denom
G[i] = (_delta(f, i - A) - g) / denom
P, Q = _one_vector(U), _zero_vector(A)
for i in xrange(1, U):
P[i] = (P[i - 1] * (n - a - i + 1)/i).expand()
for i in xrange(0, A):
Q[i] = Add(*[ (v*p).expand() for v, p in zip(V[:, i], P) ])
if not homogeneous:
h = Add(*[ (g*p).expand() for g, p in zip(G, P) ])
C = [ Symbol('C' + str(i)) for i in xrange(0, A) ]
g = lambda i: Add(*[ c*_delta(q, i) for c, q in zip(C, Q) ])
if homogeneous:
E = [ g(i) for i in xrange(N + 1, U) ]
else:
E = [ g(i) + _delta(h, i) for i in xrange(N + 1, U) ]
if E != []:
solutions = solve(E, *C)
if not solutions:
if homogeneous:
if hints.get('symbols', False):
return (S.Zero, [])
else:
return S.Zero
else:
return None
else:
solutions = {}
if homogeneous:
result = S.Zero
else:
result = h
for c, q in list(zip(C, Q)):
if c in solutions:
s = solutions[c]*q
C.remove(c)
else:
s = c*q
result += s.expand()
if hints.get('symbols', False):
return (result, C)
else:
return result | [
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pgq/skytools-legacy | 8b7e6c118572a605d28b7a3403c96aeecfd0d272 | python/londiste/setup.py | python | LondisteSetup.build_tgargs | (self) | return tgargs | Build trigger args | Build trigger args | [
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tgargs = []
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Cadene/tensorflow-model-zoo.torch | 990b10ffc22d4c8eacb2a502f20415b4f70c74c2 | models/research/object_detection/core/losses.py | python | WeightedSmoothL1LocalizationLoss._compute_loss | (self, prediction_tensor, target_tensor, weights) | return tf.reduce_sum(anchorwise_smooth_l1norm) | Compute loss function.
Args:
prediction_tensor: A float tensor of shape [batch_size, num_anchors,
code_size] representing the (encoded) predicted locations of objects.
target_tensor: A float tensor of shape [batch_size, num_anchors,
code_size] representing the regression targets
weights: a float tensor of shape [batch_size, num_anchors]
Returns:
loss: a (scalar) tensor representing the value of the loss function | Compute loss function. | [
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"loss",
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"""Compute loss function.
Args:
prediction_tensor: A float tensor of shape [batch_size, num_anchors,
code_size] representing the (encoded) predicted locations of objects.
target_tensor: A float tensor of shape [batch_size, num_anchors,
code_size] representing the regression targets
weights: a float tensor of shape [batch_size, num_anchors]
Returns:
loss: a (scalar) tensor representing the value of the loss function
"""
diff = prediction_tensor - target_tensor
abs_diff = tf.abs(diff)
abs_diff_lt_1 = tf.less(abs_diff, 1)
anchorwise_smooth_l1norm = tf.reduce_sum(
tf.where(abs_diff_lt_1, 0.5 * tf.square(abs_diff), abs_diff - 0.5),
2) * weights
if self._anchorwise_output:
return anchorwise_smooth_l1norm
return tf.reduce_sum(anchorwise_smooth_l1norm) | [
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owid/covid-19-data | 936aeae6cfbdc0163939ed7bd8ecdbb2582c0a92 | scripts/scripts/shared.py | python | _sum_aggregate | (df, name, include=None, exclude=None) | return df | [] | def _sum_aggregate(df, name, include=None, exclude=None):
df = df.copy()
if include:
df = df[df["location"].isin(include)]
if exclude:
df = df[~df["location"].isin(exclude)]
df = df.groupby("date").sum().reset_index()
df["location"] = name
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... | https://github.com/owid/covid-19-data/blob/936aeae6cfbdc0163939ed7bd8ecdbb2582c0a92/scripts/scripts/shared.py#L133-L141 | |||
windelbouwman/ppci | 915c069e0667042c085ec42c78e9e3c9a5295324 | ppci/wasm/binary/writer.py | python | BinaryFileWriter.write_type_definition | (self, type_definition) | Write out a `type` definition entry. | Write out a `type` definition entry. | [
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] | def write_type_definition(self, type_definition):
""" Write out a `type` definition entry. """
self.write(b"\x60") # form
self.write_vu32(len(type_definition.params)) # params
for _, paramtype in type_definition.params:
self.write_type(paramtype)
self.write_vu1(len(type_definition.results)) # returns
for rettype in type_definition.results:
self.write_type(rettype) | [
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triaquae/triaquae | bbabf736b3ba56a0c6498e7f04e16c13b8b8f2b9 | TriAquae/models/django/contrib/gis/gdal/geomtype.py | python | OGRGeomType.__ne__ | (self, other) | return not (self == other) | [] | def __ne__(self, other):
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HypothesisWorks/hypothesis | d1bfc4acc86899caa7a40f892322e1a69fbf36f4 | hypothesis-python/src/hypothesis/core.py | python | seed | (seed: Hashable) | return accept | seed: Start the test execution from a specific seed.
May be any hashable object. No exact meaning for seed is provided
other than that for a fixed seed value Hypothesis will try the same
actions (insofar as it can given external sources of non-
determinism. e.g. timing and hash randomization).
Overrides the derandomize setting, which is designed to enable
deterministic builds rather than reproducing observed failures. | seed: Start the test execution from a specific seed. | [
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] | def seed(seed: Hashable) -> Callable[[TestFunc], TestFunc]:
"""seed: Start the test execution from a specific seed.
May be any hashable object. No exact meaning for seed is provided
other than that for a fixed seed value Hypothesis will try the same
actions (insofar as it can given external sources of non-
determinism. e.g. timing and hash randomization).
Overrides the derandomize setting, which is designed to enable
deterministic builds rather than reproducing observed failures.
"""
def accept(test):
test._hypothesis_internal_use_seed = seed
current_settings = getattr(test, "_hypothesis_internal_use_settings", None)
test._hypothesis_internal_use_settings = Settings(
current_settings, database=None
)
return test
return accept | [
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postlund/pyatv | 4ed1f5539f37d86d80272663d1f2ea34a6c41ec4 | pyatv/protocols/dmap/__init__.py | python | DmapAudio.volume_up | (self) | Increase volume by one step. | Increase volume by one step. | [
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"""Increase volume by one step."""
await self.apple_tv.ctrl_int_cmd("volumeup") | [
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zhl2008/awd-platform | 0416b31abea29743387b10b3914581fbe8e7da5e | web_hxb2/lib/python3.5/site-packages/bs4/builder/_html5lib.py | python | Element.getNameTuple | (self) | [] | def getNameTuple(self):
if self.namespace == None:
return namespaces["html"], self.name
else:
return self.namespace, self.name | [
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kennethreitz-archive/requests3 | 69eb662703b40db58fdc6c095d0fe130c56649bb | requests3/http_models.py | python | Request.prepare | (self) | return p | Constructs a :class:`PreparedRequest <PreparedRequest>` for transmission and returns it. | Constructs a :class:`PreparedRequest <PreparedRequest>` for transmission and returns it. | [
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] | def prepare(self):
"""Constructs a :class:`PreparedRequest <PreparedRequest>` for transmission and returns it."""
p = PreparedRequest()
p.prepare(
method=self.method,
url=self.url,
headers=self.headers,
files=self.files,
data=self.data,
json=self.json,
params=self.params,
auth=self.auth,
cookies=self.cookies,
hooks=self.hooks,
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return p | [
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broadinstitute/viral-ngs | e144969e4c57060d53f38a4c3a270e8227feace1 | assembly.py | python | vcf_to_seqs | (vcfIter, chrlens, samples, min_dp=0, major_cutoff=0.5, min_dp_ratio=0.0) | Take a VCF iterator and produce an iterator of chromosome x sample full sequences. | Take a VCF iterator and produce an iterator of chromosome x sample full sequences. | [
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] | def vcf_to_seqs(vcfIter, chrlens, samples, min_dp=0, major_cutoff=0.5, min_dp_ratio=0.0):
''' Take a VCF iterator and produce an iterator of chromosome x sample full sequences.'''
seqs = {}
cur_c = None
for vcfrow in vcfIter:
try:
for c, start, stop, s, alleles in vcfrow_parse_and_call_snps(
vcfrow, samples, min_dp=min_dp,
major_cutoff=major_cutoff,
min_dp_ratio=min_dp_ratio
):
# changing chromosome?
if c != cur_c:
if cur_c is not None:
# dump the previous chromosome before starting a new one
for s in samples:
seqs[s].replay_deletions() # because of the order of VCF rows with indels
yield seqs[s].emit()
# prepare base sequences for this chromosome
cur_c = c
for s in samples:
name = len(samples) > 1 and ("%s-%s" % (c, s)) or c
seqs[s] = MutableSequence(name, 1, chrlens[c])
# modify sequence for this chromosome/sample/position
if len(alleles) == 1:
# call a single allele
seqs[s].replace(start, stop, alleles[0])
elif all(len(a) == 1 for a in alleles):
# call an ambiguous SNP
seqs[s].replace(start, stop, alleles_to_ambiguity(alleles))
else:
# mix of indels with no clear winner... force the most popular one
seqs[s].replace(start, stop, alleles[0])
except:
log.exception("Exception occurred while parsing VCF file. Row: '%s'", vcfrow)
raise
# at the end, dump the last chromosome
if cur_c is not None:
for s in samples:
seqs[s].replay_deletions() # because of the order of VCF rows with indels
yield seqs[s].emit() | [
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oracle/graalpython | 577e02da9755d916056184ec441c26e00b70145c | graalpython/lib-python/3/encodings/utf_8_sig.py | python | StreamReader.decode | (self, input, errors='strict') | return codecs.utf_8_decode(input, errors) | [] | def decode(self, input, errors='strict'):
if len(input) < 3:
if codecs.BOM_UTF8.startswith(input):
# not enough data to decide if this is a BOM
# => try again on the next call
return ("", 0)
elif input[:3] == codecs.BOM_UTF8:
self.decode = codecs.utf_8_decode
(output, consumed) = codecs.utf_8_decode(input[3:],errors)
return (output, consumed+3)
# (else) no BOM present
self.decode = codecs.utf_8_decode
return codecs.utf_8_decode(input, errors) | [
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huggingface/transformers | 623b4f7c63f60cce917677ee704d6c93ee960b4b | src/transformers/utils/dummy_pt_objects.py | python | XLMWithLMHeadModel.forward | (self, *args, **kwargs) | [] | def forward(self, *args, **kwargs):
requires_backends(self, ["torch"]) | [
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ray-project/ray | 703c1610348615dcb8c2d141a0c46675084660f5 | python/ray/cluster_utils.py | python | Cluster.list_all_nodes | (self) | return nodes | Lists all nodes.
TODO(rliaw): What is the desired behavior if a head node
dies before worker nodes die?
Returns:
List of all nodes, including the head node. | Lists all nodes. | [
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] | def list_all_nodes(self):
"""Lists all nodes.
TODO(rliaw): What is the desired behavior if a head node
dies before worker nodes die?
Returns:
List of all nodes, including the head node.
"""
nodes = list(self.worker_nodes)
if self.head_node:
nodes = [self.head_node] + nodes
return nodes | [
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pyqtgraph/pyqtgraph | ac3887abfca4e529aac44f022f8e40556a2587b0 | pyqtgraph/parametertree/parameterTypes/file.py | python | _set_filepicker_kwargs | (fileDlg, **kwargs) | Applies a dict of enum/flag kwarg opts to a file dialog | Applies a dict of enum/flag kwarg opts to a file dialog | [
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NO_MATCH = object()
for kk, vv in kwargs.items():
# Convert string or list representations into true flags
# 'fileMode' -> 'FileMode'
formattedName = kk[0].upper() + kk[1:]
# Edge case: "Options" has enum "Option"
if formattedName == 'Options':
enumCls = fileDlg.Option
else:
enumCls = getattr(fileDlg, formattedName, NO_MATCH)
setFunc = getattr(fileDlg, f'set{formattedName}', NO_MATCH)
if enumCls is NO_MATCH or setFunc is NO_MATCH:
continue
if enumCls is fileDlg.Option:
builder = fileDlg.Option(0)
# This is the only flag enum, all others can only take one value
if isinstance(vv, str): vv = [vv]
for flag in vv:
curVal = getattr(enumCls, flag)
builder |= curVal
# Some Qt implementations turn into ints by this point
outEnum = enumCls(builder)
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outEnum = getattr(enumCls, vv)
setFunc(outEnum) | [
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apache/tvm | 6eb4ed813ebcdcd9558f0906a1870db8302ff1e0 | python/tvm/topi/broadcast.py | python | greater | (lhs, rhs) | return _cpp.greater(lhs, rhs) | Compute (lhs>rhs) with auto-broadcasting
Parameters
----------
lhs : tvm.te.Tensor or Expr
The left operand
rhs : tvm.te.Tensor or Expr
The right operand
Returns
-------
ret : tvm.te.Tensor or Expr
Returns Expr if both operands are Expr.
Otherwise returns Tensor. | Compute (lhs>rhs) with auto-broadcasting | [
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"""Compute (lhs>rhs) with auto-broadcasting
Parameters
----------
lhs : tvm.te.Tensor or Expr
The left operand
rhs : tvm.te.Tensor or Expr
The right operand
Returns
-------
ret : tvm.te.Tensor or Expr
Returns Expr if both operands are Expr.
Otherwise returns Tensor.
"""
return _cpp.greater(lhs, rhs) | [
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pandas-dev/pandas | 5ba7d714014ae8feaccc0dd4a98890828cf2832d | pandas/core/computation/engines.py | python | AbstractEngine._evaluate | (self) | Return an evaluated expression.
Parameters
----------
env : Scope
The local and global environment in which to evaluate an
expression.
Notes
-----
Must be implemented by subclasses. | Return an evaluated expression. | [
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"""
Return an evaluated expression.
Parameters
----------
env : Scope
The local and global environment in which to evaluate an
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Notes
-----
Must be implemented by subclasses.
"""
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debian-calibre/calibre | 020fc81d3936a64b2ac51459ecb796666ab6a051 | src/calibre/ebooks/rtf2xml/paragraph_def.py | python | ParagraphDef.__write_para_def_beg | (self) | Requires:
nothing
Returns:
nothing
Logic:
Print out the beginning of the pargraph definition tag, and the markers
that let me know when I have reached this tag. (These markers are
used for later parsing.) | Requires:
nothing
Returns:
nothing
Logic:
Print out the beginning of the pargraph definition tag, and the markers
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"""
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Returns:
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Logic:
Print out the beginning of the pargraph definition tag, and the markers
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"""
self.__get_num_of_style()
table = self.__att_val_dict.get('in-table')
if table:
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self.__write_obj.write('mi<mk<in-table__\n')
else:
self.__write_obj.write('mi<mk<not-in-tbl\n')
left_indent = self.__att_val_dict.get('left-indent')
if left_indent:
self.__write_obj.write('mi<mk<left_inden<%s\n' % left_indent)
is_list = self.__att_val_dict.get('list-id')
if is_list:
self.__write_obj.write('mi<mk<list-id___<%s\n' % is_list)
else:
self.__write_obj.write('mi<mk<no-list___\n')
self.__write_obj.write('mi<mk<style-name<%s\n' % self.__att_val_dict['name'])
self.__write_obj.write(self.__start_marker)
self.__write_obj.write('mi<tg<open-att__<paragraph-definition')
self.__write_obj.write('<name>%s' % self.__att_val_dict['name'])
self.__write_obj.write('<style-number>%s' % self.__att_val_dict['style-num'])
tabs_list = ['tabs-left', 'tabs-right', 'tabs-decimal', 'tabs-center',
'tabs-bar', 'tabs']
"""
for tab_item in tabs_list:
if self.__att_val_dict[tab_item] != '':
the_value = self.__att_val_dict[tab_item]
the_value = the_value[:-1]
self.__write_obj.write('<%s>%s' % (tab_item, the_value))
"""
if self.__att_val_dict['tabs'] != '':
the_value = self.__att_val_dict['tabs']
# the_value = the_value[:-1]
self.__write_obj.write('<%s>%s' % ('tabs', the_value))
keys = sorted(self.__att_val_dict)
exclude = frozenset(['name', 'style-num', 'in-table'] + tabs_list)
for key in keys:
if key not in exclude:
self.__write_obj.write('<%s>%s' % (key, self.__att_val_dict[key]))
self.__write_obj.write('\n')
self.__write_obj.write(self.__start2_marker)
if 'font-style' in keys:
face = self.__att_val_dict['font-style']
self.__write_obj.write('mi<mk<font______<%s\n' % face)
if 'caps' in keys:
value = self.__att_val_dict['caps']
self.__write_obj.write('mi<mk<caps______<%s\n' % value) | [
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nucleic/enaml | 65c2a2a2d765e88f2e1103046680571894bb41ed | enaml/core/enaml_ast.py | python | ASTVisitor.default_visit | (self, node, *args, **kwargs) | The default node visitor method.
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"""
msg = "no visitor found for node of type `%s`"
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] | https://github.com/nucleic/enaml/blob/65c2a2a2d765e88f2e1103046680571894bb41ed/enaml/core/enaml_ast.py#L364-L374 | ||
LinkedInAttic/indextank-service | 880c6295ce8e7a3a55bf9b3777cc35c7680e0d7e | storefront/boto/ec2/connection.py | python | EC2Connection.get_all_reserved_instances | (self, reserved_instances_id=None) | return self.get_list('DescribeReservedInstances',
params, [('item', ReservedInstance)]) | Describes Reserved Instance offerings that are available for purchase.
:type reserved_instance_ids: list
:param reserved_instance_ids: A list of the reserved instance ids that will be returned.
If not provided, all reserved instances will be returned.
:rtype: list
:return: A list of :class:`boto.ec2.reservedinstance.ReservedInstance` | Describes Reserved Instance offerings that are available for purchase. | [
"Describes",
"Reserved",
"Instance",
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"available",
"for",
"purchase",
"."
] | def get_all_reserved_instances(self, reserved_instances_id=None):
"""
Describes Reserved Instance offerings that are available for purchase.
:type reserved_instance_ids: list
:param reserved_instance_ids: A list of the reserved instance ids that will be returned.
If not provided, all reserved instances will be returned.
:rtype: list
:return: A list of :class:`boto.ec2.reservedinstance.ReservedInstance`
"""
params = {}
if reserved_instances_id:
self.build_list_params(params, reserved_instances_id, 'ReservedInstancesId')
return self.get_list('DescribeReservedInstances',
params, [('item', ReservedInstance)]) | [
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IronLanguages/ironpython3 | 7a7bb2a872eeab0d1009fc8a6e24dca43f65b693 | Src/StdLib/Lib/urllib/request.py | python | HTTPPasswordMgrWithDefaultRealm.find_user_password | (self, realm, authuri) | return HTTPPasswordMgr.find_user_password(self, None, authuri) | [] | def find_user_password(self, realm, authuri):
user, password = HTTPPasswordMgr.find_user_password(self, realm,
authuri)
if user is not None:
return user, password
return HTTPPasswordMgr.find_user_password(self, None, authuri) | [
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openstack/octavia | 27e5b27d31c695ba72fb6750de2bdafd76e0d7d9 | octavia/api/v2/controllers/quotas.py | python | QuotasController.put | (self, project_id, quotas) | return self._convert_db_to_type(db_quotas, quota_types.QuotaResponse) | Update any or all quotas for a project. | Update any or all quotas for a project. | [
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] | def put(self, project_id, quotas):
"""Update any or all quotas for a project."""
context = pecan_request.context.get('octavia_context')
if not project_id:
raise exceptions.MissingAPIProjectID()
self._auth_validate_action(context, project_id, constants.RBAC_PUT)
quotas_dict = quotas.to_dict()
self.repositories.quotas.update(context.session, project_id,
**quotas_dict)
db_quotas = self._get_db_quotas(context.session, project_id)
return self._convert_db_to_type(db_quotas, quota_types.QuotaResponse) | [
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DataDog/integrations-core | 934674b29d94b70ccc008f76ea172d0cdae05e1e | docs/developer/.scripts/33_render_status.py | python | render_latest_version_progress | () | return lines | [] | def render_latest_version_progress():
valid_checks = sorted(get_testable_checks())
total_checks = len(valid_checks)
supported_checks = 0
lines = ['## New version support', '', None, '', '??? check "Completed"']
for check in valid_checks:
skip_check = False
with open(get_tox_file(check)) as tox_file:
for line in tox_file:
if line.startswith('[testenv:latest]'):
supported_checks += 1
status = 'X'
break
elif line.startswith('# SKIP-LATEST-VERSION-CHECK'):
skip_check = True
break
else:
status = ' '
if skip_check:
total_checks -= 1
continue
lines.append(f' - [{status}] {check}')
percent = supported_checks / total_checks * 100
formatted_percent = f'{percent:.2f}'
lines[2] = f'[={formatted_percent}% "{formatted_percent}%"]'
lines[4] = f'??? check "Completed {supported_checks}/{total_checks}"'
return lines | [
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apache/libcloud | 90971e17bfd7b6bb97b2489986472c531cc8e140 | libcloud/compute/drivers/azure_arm.py | python | AzureNodeDriver.ex_get_volume | (self, id) | return self._to_volume(r.object) | Fetch information about a volume.
:param id: The complete resource path to the volume resource.
:type id: ``str``
:return: The StorageVolume object
:rtype: :class:`.StorageVolume` | Fetch information about a volume. | [
"Fetch",
"information",
"about",
"a",
"volume",
"."
] | def ex_get_volume(self, id):
"""
Fetch information about a volume.
:param id: The complete resource path to the volume resource.
:type id: ``str``
:return: The StorageVolume object
:rtype: :class:`.StorageVolume`
"""
r = self.connection.request(id, params={"api-version": RESOURCE_API_VERSION})
return self._to_volume(r.object) | [
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... | https://github.com/apache/libcloud/blob/90971e17bfd7b6bb97b2489986472c531cc8e140/libcloud/compute/drivers/azure_arm.py#L1779-L1791 | |
traveller59/second.pytorch | 3aba19c9688274f75ebb5e576f65cfe54773c021 | torchplus/train/fastai_optim.py | python | split_bn_bias | (layer_groups) | return split_groups | Split the layers in `layer_groups` into batchnorm (`bn_types`) and non-batchnorm groups. | Split the layers in `layer_groups` into batchnorm (`bn_types`) and non-batchnorm groups. | [
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"groups",
"."
] | def split_bn_bias(layer_groups):
"Split the layers in `layer_groups` into batchnorm (`bn_types`) and non-batchnorm groups."
split_groups = []
for l in layer_groups:
l1, l2 = [], []
for c in l.children():
if isinstance(c, bn_types): l2.append(c)
else: l1.append(c)
split_groups += [nn.Sequential(*l1), nn.Sequential(*l2)]
return split_groups | [
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... | https://github.com/traveller59/second.pytorch/blob/3aba19c9688274f75ebb5e576f65cfe54773c021/torchplus/train/fastai_optim.py#L14-L23 | |
modflowpy/flopy | eecd1ad193c5972093c9712e5c4b7a83284f0688 | flopy/mfusg/mfusgwel.py | python | MfUsgWel._get_kper_data | (kper, first, stress_period_data) | return itmp, kper_data | Gets boundary condition stress period data for a given stress period.
Parameters:
----------
kper: int
stress period (base 0)
first : int
First stress period for which stress period data is defined
stress_period_data : Numpy recarray or int or None
Flopy boundary condition stress_period_data object
(with a "data" attribute that is keyed on kper)
Returns
-------
itmp : int
Number of boundary conditions for stress period kper
kper_data : Numpy recarray
Boundary condition data for stress period kper | Gets boundary condition stress period data for a given stress period. | [
"Gets",
"boundary",
"condition",
"stress",
"period",
"data",
"for",
"a",
"given",
"stress",
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"."
] | def _get_kper_data(kper, first, stress_period_data):
"""
Gets boundary condition stress period data for a given stress period.
Parameters:
----------
kper: int
stress period (base 0)
first : int
First stress period for which stress period data is defined
stress_period_data : Numpy recarray or int or None
Flopy boundary condition stress_period_data object
(with a "data" attribute that is keyed on kper)
Returns
-------
itmp : int
Number of boundary conditions for stress period kper
kper_data : Numpy recarray
Boundary condition data for stress period kper
"""
kpers = list(stress_period_data.data.keys())
# Fill missing early kpers with 0
kper_data = None
if kper < first:
itmp = 0
elif kper in kpers:
kper_data = deepcopy(stress_period_data.data[kper])
kper_vtype = stress_period_data.vtype[kper]
if kper_vtype == np.recarray:
itmp = kper_data.shape[0]
lnames = [name.lower() for name in kper_data.dtype.names]
for idx in ["k", "i", "j", "node"]:
if idx in lnames:
kper_data[idx] += 1
elif (kper_vtype == int) or (kper_vtype is None):
itmp = kper_data
# Fill late missing kpers with -1
else:
itmp = -1
return itmp, kper_data | [
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facebookresearch/hgnn | 2a22fdb479996c2318f85ad36d2750a383011773 | gnn/RiemannianGNN.py | python | RiemannianGNN.forward | (self, node_repr, adj_list, weight, mask) | return node_repr | Args:
node_repr: [node_num, embed_size]
node_repr is in Euclidean space.
If node_repr is in hyperbolic space, invoke log_map_zero first.
adj_list: [node_num, max_neighbor] adjacency list
weight: [node_num, max_neighbor] weights of the adjacency list
mask: [node_num, 1] 1 denote real node, 0 padded node
Return:
[node_num, embed_size] in hyperbolic space | Args:
node_repr: [node_num, embed_size]
node_repr is in Euclidean space.
If node_repr is in hyperbolic space, invoke log_map_zero first.
adj_list: [node_num, max_neighbor] adjacency list
weight: [node_num, max_neighbor] weights of the adjacency list
mask: [node_num, 1] 1 denote real node, 0 padded node
Return:
[node_num, embed_size] in hyperbolic space | [
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"""
Args:
node_repr: [node_num, embed_size]
node_repr is in Euclidean space.
If node_repr is in hyperbolic space, invoke log_map_zero first.
adj_list: [node_num, max_neighbor] adjacency list
weight: [node_num, max_neighbor] weights of the adjacency list
mask: [node_num, 1] 1 denote real node, 0 padded node
Return:
[node_num, embed_size] in hyperbolic space
"""
# split the adjacency list and weights based on edge types
adj_list, weight = self.split_input(adj_list, weight)
# gnn layers
for step in range(self.args.gnn_layer):
node_repr = self.manifold.log_map_zero(node_repr) * mask if step > 0 else node_repr * mask
combined_msg = self.get_combined_msg(step, node_repr, adj_list, weight, mask)
combined_msg = self.dropout(combined_msg) * mask
node_repr = self.manifold.exp_map_zero(combined_msg) * mask
node_repr = self.apply_activation(node_repr) * mask
return node_repr | [
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... | https://github.com/facebookresearch/hgnn/blob/2a22fdb479996c2318f85ad36d2750a383011773/gnn/RiemannianGNN.py#L156-L177 |
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