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Jiramew/spoon | a301f8e9fe6956b44b02861a3931143b987693b0 | spoon_server/database/redis_wrapper.py | python | RedisWrapper.zremrangebyrank | (self, name, low, high) | [] | def zremrangebyrank(self, name, low, high):
self._connection.zremrangebyrank(name, low, high) | [
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Louis-me/appiumn_auto | 950a7853e412ce37855ed006bbaa845ca19c9463 | Common/operateElement.py | python | operate_click | (mOperate,cts) | [] | def operate_click(mOperate,cts):
if mOperate["find_type"] == common.find_element_by_id or mOperate["find_type"] == common.find_element_by_name or mOperate["find_type"] == common.find_element_by_xpath:
elements_by(mOperate, cts).click()
if mOperate["find_type"] == common.find_elements_by_id or mOperate["find_type"] == common.find_elements_by_name:
elements_by(mOperate, cts)[mOperate["index"]].click()
# 记录运行过程中的一些系统日志，比如闪退会造成自动化测试停止
if common.SELENIUM_APPIUM == common.APPIUM:
# errorLog.get_error(log=mOperate["log"], devices=mOperate["devices"])
pass | [
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ajinabraham/OWASP-Xenotix-XSS-Exploit-Framework | cb692f527e4e819b6c228187c5702d990a180043 | external/Scripting Engine/Xenotix Python Scripting Engine/Lib/lib2to3/pytree.py | python | generate_matches | (patterns, nodes) | Generator yielding matches for a sequence of patterns and nodes.
Args:
patterns: a sequence of patterns
nodes: a sequence of nodes
Yields:
(count, results) tuples where:
count: the entire sequence of patterns matches nodes[:count];
results: dict containing named submatches. | Generator yielding matches for a sequence of patterns and nodes. | [
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"""
Generator yielding matches for a sequence of patterns and nodes.
Args:
patterns: a sequence of patterns
nodes: a sequence of nodes
Yields:
(count, results) tuples where:
count: the entire sequence of patterns matches nodes[:count];
results: dict containing named submatches.
"""
if not patterns:
yield 0, {}
else:
p, rest = patterns[0], patterns[1:]
for c0, r0 in p.generate_matches(nodes):
if not rest:
yield c0, r0
else:
for c1, r1 in generate_matches(rest, nodes[c0:]):
r = {}
r.update(r0)
r.update(r1)
yield c0 + c1, r | [
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home-assistant/core | 265ebd17a3f17ed8dc1e9bdede03ac8e323f1ab1 | homeassistant/components/blackbird/media_player.py | python | BlackbirdZone.update | (self) | Retrieve latest state. | Retrieve latest state. | [
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] | def update(self):
"""Retrieve latest state."""
state = self._blackbird.zone_status(self._zone_id)
if not state:
return
self._attr_state = STATE_ON if state.power else STATE_OFF
idx = state.av
if idx in self._source_id_name:
self._attr_source = self._source_id_name[idx]
else:
self._attr_source = None | [
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huuuuusy/Mask-RCNN-Shiny | b59944ae08fda8dfc19d27a22acd59f94d8beb4f | mrcnn/utils.py | python | Dataset.source_image_link | (self, image_id) | return self.image_info[image_id]["path"] | Returns the path or URL to the image.
Override this to return a URL to the image if it's availble online for easy
debugging. | Returns the path or URL to the image.
Override this to return a URL to the image if it's availble online for easy
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"""Returns the path or URL to the image.
Override this to return a URL to the image if it's availble online for easy
debugging.
"""
return self.image_info[image_id]["path"] | [
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scikit-image/scikit-image | ed642e2bc822f362504d24379dee94978d6fa9de | skimage/transform/pyramids.py | python | pyramid_laplacian | (image, max_layer=-1, downscale=2, sigma=None, order=1,
mode='reflect', cval=0, multichannel=False,
preserve_range=False, *, channel_axis=-1) | Yield images of the laplacian pyramid formed by the input image.
Each layer contains the difference between the downsampled and the
downsampled, smoothed image::
layer = resize(prev_layer) - smooth(resize(prev_layer))
Note that the first image of the pyramid will be the difference between the
original, unscaled image and its smoothed version. The total number of
images is `max_layer + 1`. In case all layers are computed, the last image
is either a one-pixel image or the image where the reduction does not
change its shape.
Parameters
----------
image : ndarray
Input image.
max_layer : int, optional
Number of layers for the pyramid. 0th layer is the original image.
Default is -1 which builds all possible layers.
downscale : float, optional
Downscale factor.
sigma : float, optional
Sigma for Gaussian filter. Default is `2 * downscale / 6.0` which
corresponds to a filter mask twice the size of the scale factor that
covers more than 99% of the Gaussian distribution.
order : int, optional
Order of splines used in interpolation of downsampling. See
`skimage.transform.warp` for detail.
mode : {'reflect', 'constant', 'edge', 'symmetric', 'wrap'}, optional
The mode parameter determines how the array borders are handled, where
cval is the value when mode is equal to 'constant'.
cval : float, optional
Value to fill past edges of input if mode is 'constant'.
multichannel : bool, optional
Whether the last axis of the image is to be interpreted as multiple
channels or another spatial dimension. This argument is deprecated:
specify `channel_axis` instead.
preserve_range : bool, optional
Whether to keep the original range of values. Otherwise, the input
image is converted according to the conventions of `img_as_float`.
Also see https://scikit-image.org/docs/dev/user_guide/data_types.html
channel_axis : int or None, optional
If None, the image is assumed to be a grayscale (single channel) image.
Otherwise, this parameter indicates which axis of the array corresponds
to channels.
.. versionadded:: 0.19
``channel_axis`` was added in 0.19.
Returns
-------
pyramid : generator
Generator yielding pyramid layers as float images.
References
----------
.. [1] http://persci.mit.edu/pub_pdfs/pyramid83.pdf
.. [2] http://sepwww.stanford.edu/data/media/public/sep/morgan/texturematch/paper_html/node3.html | Yield images of the laplacian pyramid formed by the input image. | [
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"of",
"the",
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"pyramid",
"formed",
"by",
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"image",
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] | def pyramid_laplacian(image, max_layer=-1, downscale=2, sigma=None, order=1,
mode='reflect', cval=0, multichannel=False,
preserve_range=False, *, channel_axis=-1):
"""Yield images of the laplacian pyramid formed by the input image.
Each layer contains the difference between the downsampled and the
downsampled, smoothed image::
layer = resize(prev_layer) - smooth(resize(prev_layer))
Note that the first image of the pyramid will be the difference between the
original, unscaled image and its smoothed version. The total number of
images is `max_layer + 1`. In case all layers are computed, the last image
is either a one-pixel image or the image where the reduction does not
change its shape.
Parameters
----------
image : ndarray
Input image.
max_layer : int, optional
Number of layers for the pyramid. 0th layer is the original image.
Default is -1 which builds all possible layers.
downscale : float, optional
Downscale factor.
sigma : float, optional
Sigma for Gaussian filter. Default is `2 * downscale / 6.0` which
corresponds to a filter mask twice the size of the scale factor that
covers more than 99% of the Gaussian distribution.
order : int, optional
Order of splines used in interpolation of downsampling. See
`skimage.transform.warp` for detail.
mode : {'reflect', 'constant', 'edge', 'symmetric', 'wrap'}, optional
The mode parameter determines how the array borders are handled, where
cval is the value when mode is equal to 'constant'.
cval : float, optional
Value to fill past edges of input if mode is 'constant'.
multichannel : bool, optional
Whether the last axis of the image is to be interpreted as multiple
channels or another spatial dimension. This argument is deprecated:
specify `channel_axis` instead.
preserve_range : bool, optional
Whether to keep the original range of values. Otherwise, the input
image is converted according to the conventions of `img_as_float`.
Also see https://scikit-image.org/docs/dev/user_guide/data_types.html
channel_axis : int or None, optional
If None, the image is assumed to be a grayscale (single channel) image.
Otherwise, this parameter indicates which axis of the array corresponds
to channels.
.. versionadded:: 0.19
``channel_axis`` was added in 0.19.
Returns
-------
pyramid : generator
Generator yielding pyramid layers as float images.
References
----------
.. [1] http://persci.mit.edu/pub_pdfs/pyramid83.pdf
.. [2] http://sepwww.stanford.edu/data/media/public/sep/morgan/texturematch/paper_html/node3.html
"""
_check_factor(downscale)
# cast to float for consistent data type in pyramid
image = convert_to_float(image, preserve_range)
if sigma is None:
# automatically determine sigma which covers > 99% of distribution
sigma = 2 * downscale / 6.0
current_shape = image.shape
smoothed_image = _smooth(image, sigma, mode, cval, channel_axis)
yield image - smoothed_image
if channel_axis is not None:
channel_axis = channel_axis % image.ndim
shape_without_channels = list(current_shape)
shape_without_channels.pop(channel_axis)
shape_without_channels = tuple(shape_without_channels)
else:
shape_without_channels = current_shape
# build downsampled images until max_layer is reached or downscale process
# does not change image size
if max_layer == -1:
max_layer = math.ceil(math.log(max(shape_without_channels), downscale))
for layer in range(max_layer):
if channel_axis is not None:
out_shape = tuple(
math.ceil(d / float(downscale)) if ax != channel_axis else d
for ax, d in enumerate(current_shape)
)
else:
out_shape = tuple(math.ceil(d / float(downscale))
for d in current_shape)
resized_image = resize(smoothed_image, out_shape, order=order,
mode=mode, cval=cval, anti_aliasing=False)
smoothed_image = _smooth(resized_image, sigma, mode, cval,
channel_axis)
current_shape = resized_image.shape
yield resized_image - smoothed_image | [
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scanny/python-pptx | 71d1ca0b2b3b9178d64cdab565e8503a25a54e0b | pptx/chart/data.py | python | _BaseDataPoint.number_format | (self) | return number_format | The formatting template string that determines how the value of this
data point is formatted, both in the chart and in the Excel
spreadsheet; for example '#,##0.0'. If not specified for this data
point, it is inherited from the parent series data object. | The formatting template string that determines how the value of this
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"""
The formatting template string that determines how the value of this
data point is formatted, both in the chart and in the Excel
spreadsheet; for example '#,##0.0'. If not specified for this data
point, it is inherited from the parent series data object.
"""
number_format = self._number_format
if number_format is None:
return self._series_data.number_format
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spywhere/Javatar | e273ec40c209658247a71b109bb90cd126984a29 | core/build_system.py | python | _BuildSystem.reset | (self) | Reset the instance variables to clear the build | Reset the instance variables to clear the build | [
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] | def reset(self):
"""
Reset the instance variables to clear the build
"""
self.failed = False
self.building = False
self.builders = []
self.create_log = False
self.finish_callback = None
self.cancel_callback = None | [
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conjure-up/conjure-up | d2bf8ab8e71ff01321d0e691a8d3e3833a047678 | conjureup/ui/views/destroy.py | python | DestroyView._build_footer | (self) | return footer_pile | [] | def _build_footer(self):
footer_pile = Pile([
Padding.line_break(""),
Color.frame_footer(
Columns([
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('fixed', 13, self._build_buttons())
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francisck/DanderSpritz_docs | 86bb7caca5a957147f120b18bb5c31f299914904 | Python/Core/Lib/lib2to3/pytree.py | python | BasePattern.__new__ | (cls, *args, **kwds) | return object.__new__(cls) | Constructor that prevents BasePattern from being instantiated. | Constructor that prevents BasePattern from being instantiated. | [
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"""Constructor that prevents BasePattern from being instantiated."""
return object.__new__(cls) | [
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gcovr/gcovr | 09e89b5287fa5a11408a208cb34aea0efd19d4f5 | gcovr/gcov.py | python | process_datafile | (filename, covdata, options, toerase) | r"""Run gcovr in a suitable directory to collect coverage from gcda files.
Params:
filename (path): the path to a gcda or gcno file
covdata (dict, mutable): the global covdata dictionary
options (object): the configuration options namespace
toerase (set, mutable): files that should be deleted later
workdir (path or None): the per-thread work directory
Returns:
Nothing.
Finding a suitable working directory is tricky.
The coverage files (gcda and gcno) are stored next to object (.o) files.
However, gcov needs to also resolve the source file name.
The relative source file paths in the coverage data
are relative to the gcc working directory.
Therefore, gcov must be invoked in the same directory as gcc.
How to find that directory? By various heuristics.
This is complicated by the problem that the build process tells gcc
where to run, where the sources are, and where to put the object files.
We only know the object files and have to work everything out in reverse.
If present, the *workdir* argument is always tried first.
Ideally, the build process only runs gcc from *one* directory
and the user can provide this directory as the ``--object-directory``.
If it exists, we try that path as a workdir,
If the path is relative,
it is resolved relative to the gcovr cwd and the object file location.
We next try the ``--root`` directory.
TODO: should probably also be the gcovr start directory.
If none of those work, we assume that
the object files are in a subdirectory of the gcc working directory,
i.e. we can walk the directory tree upwards.
All of this works fine unless gcc was invoked like ``gcc -o ../path``,
i.e. the object files are in a sibling directory.
TODO: So far there is no good way to address this case. | r"""Run gcovr in a suitable directory to collect coverage from gcda files. | [
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"."
] | def process_datafile(filename, covdata, options, toerase):
r"""Run gcovr in a suitable directory to collect coverage from gcda files.
Params:
filename (path): the path to a gcda or gcno file
covdata (dict, mutable): the global covdata dictionary
options (object): the configuration options namespace
toerase (set, mutable): files that should be deleted later
workdir (path or None): the per-thread work directory
Returns:
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Finding a suitable working directory is tricky.
The coverage files (gcda and gcno) are stored next to object (.o) files.
However, gcov needs to also resolve the source file name.
The relative source file paths in the coverage data
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How to find that directory? By various heuristics.
This is complicated by the problem that the build process tells gcc
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We only know the object files and have to work everything out in reverse.
If present, the *workdir* argument is always tried first.
Ideally, the build process only runs gcc from *one* directory
and the user can provide this directory as the ``--object-directory``.
If it exists, we try that path as a workdir,
If the path is relative,
it is resolved relative to the gcovr cwd and the object file location.
We next try the ``--root`` directory.
TODO: should probably also be the gcovr start directory.
If none of those work, we assume that
the object files are in a subdirectory of the gcc working directory,
i.e. we can walk the directory tree upwards.
All of this works fine unless gcc was invoked like ``gcc -o ../path``,
i.e. the object files are in a sibling directory.
TODO: So far there is no good way to address this case.
"""
logger = Logger(options.verbose)
logger.verbose_msg("Processing file: {}", filename)
abs_filename = os.path.abspath(filename)
errors = []
potential_wd = []
if options.objdir:
potential_wd = find_potential_working_directories_via_objdir(
abs_filename, options.objdir, error=errors.append
)
# no objdir was specified or objdir didn't exist
consider_parent_directories = not potential_wd
# Always add the root directory
potential_wd.append(options.root_dir)
if consider_parent_directories:
wd = os.path.dirname(abs_filename)
while wd != potential_wd[-1]:
potential_wd.append(wd)
wd = os.path.dirname(wd)
for wd in potential_wd:
done = run_gcov_and_process_files(
abs_filename,
covdata,
options=options,
logger=logger,
toerase=toerase,
error=errors.append,
chdir=wd,
)
if options.delete:
if not abs_filename.endswith("gcno"):
toerase.add(abs_filename)
if done:
return
logger.warn(
"GCOV produced the following errors processing {filename}:\n"
"\t{errors}\n"
"\t(gcovr could not infer a working directory that resolved it.)",
filename=filename,
errors="\n\t".join(errors),
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kubernetes-client/python | 47b9da9de2d02b2b7a34fbe05afb44afd130d73a | kubernetes/client/models/v1_glusterfs_persistent_volume_source.py | python | V1GlusterfsPersistentVolumeSource.endpoints_namespace | (self, endpoints_namespace) | Sets the endpoints_namespace of this V1GlusterfsPersistentVolumeSource.
EndpointsNamespace is the namespace that contains Glusterfs endpoint. If this field is empty, the EndpointNamespace defaults to the same namespace as the bound PVC. More info: https://examples.k8s.io/volumes/glusterfs/README.md#create-a-pod # noqa: E501
:param endpoints_namespace: The endpoints_namespace of this V1GlusterfsPersistentVolumeSource. # noqa: E501
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"""Sets the endpoints_namespace of this V1GlusterfsPersistentVolumeSource.
EndpointsNamespace is the namespace that contains Glusterfs endpoint. If this field is empty, the EndpointNamespace defaults to the same namespace as the bound PVC. More info: https://examples.k8s.io/volumes/glusterfs/README.md#create-a-pod # noqa: E501
:param endpoints_namespace: The endpoints_namespace of this V1GlusterfsPersistentVolumeSource. # noqa: E501
:type: str
"""
self._endpoints_namespace = endpoints_namespace | [
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koursaros-ai/nboost | 38123ba9ad52d33afd844a38b46ca702a00cfa6c | nboost/plugins/rerank/transformers.py | python | PtTransformersRerankPlugin.get_logits | (self, query: str, choices: List[str]) | :param query:
:param choices:
:return: logits | :param query:
:param choices:
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"""
:param query:
:param choices:
:return: logits
"""
input_ids, attention_mask, token_type_ids = self.encode(query, choices)
with torch.no_grad():
logits = self.rerank_model(input_ids,
attention_mask=attention_mask,
token_type_ids=token_type_ids)[0]
logits = logits.detach().cpu().numpy()
return logits | [
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tomplus/kubernetes_asyncio | f028cc793e3a2c519be6a52a49fb77ff0b014c9b | kubernetes_asyncio/client/models/v1_node_system_info.py | python | V1NodeSystemInfo.container_runtime_version | (self, container_runtime_version) | Sets the container_runtime_version of this V1NodeSystemInfo.
ContainerRuntime Version reported by the node through runtime remote API (e.g. docker://1.5.0). # noqa: E501
:param container_runtime_version: The container_runtime_version of this V1NodeSystemInfo. # noqa: E501
:type: str | Sets the container_runtime_version of this V1NodeSystemInfo. | [
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"""Sets the container_runtime_version of this V1NodeSystemInfo.
ContainerRuntime Version reported by the node through runtime remote API (e.g. docker://1.5.0). # noqa: E501
:param container_runtime_version: The container_runtime_version of this V1NodeSystemInfo. # noqa: E501
:type: str
"""
if self.local_vars_configuration.client_side_validation and container_runtime_version is None: # noqa: E501
raise ValueError("Invalid value for `container_runtime_version`, must not be `None`") # noqa: E501
self._container_runtime_version = container_runtime_version | [
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dropbox/dropbox-sdk-python | 015437429be224732990041164a21a0501235db1 | dropbox/team_log.py | python | EventTypeArg.is_no_expiration_link_gen_create_report | (self) | return self._tag == 'no_expiration_link_gen_create_report' | Check if the union tag is ``no_expiration_link_gen_create_report``.
:rtype: bool | Check if the union tag is ``no_expiration_link_gen_create_report``. | [
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"""
Check if the union tag is ``no_expiration_link_gen_create_report``.
:rtype: bool
"""
return self._tag == 'no_expiration_link_gen_create_report' | [
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pgmpy/pgmpy | 24279929a28082ea994c52f3d165ca63fc56b02b | pgmpy/models/ClusterGraph.py | python | ClusterGraph.get_cardinality | (self, node=None) | Returns the cardinality of the node
Parameters
----------
node: any hashable python object (optional)
The node whose cardinality we want. If node is not specified returns a
dictionary with the given variable as keys and their respective cardinality
as values.
Returns
-------
int or dict : If node is specified returns the cardinality of the node.
If node is not specified returns a dictionary with the given
variable as keys and their respective cardinality as values.
Examples
--------
>>> from pgmpy.models import ClusterGraph
>>> from pgmpy.factors.discrete import DiscreteFactor
>>> student = ClusterGraph()
>>> factor = DiscreteFactor(['Alice', 'Bob'], cardinality=[2, 2],
... values=np.random.rand(4))
>>> student.add_node(('Alice', 'Bob'))
>>> student.add_factors(factor)
>>> student.get_cardinality()
defaultdict(<class 'int'>, {'Alice': 2, 'Bob': 2})
>>> student.get_cardinality(node='Alice')
2 | Returns the cardinality of the node | [
"Returns",
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"""
Returns the cardinality of the node
Parameters
----------
node: any hashable python object (optional)
The node whose cardinality we want. If node is not specified returns a
dictionary with the given variable as keys and their respective cardinality
as values.
Returns
-------
int or dict : If node is specified returns the cardinality of the node.
If node is not specified returns a dictionary with the given
variable as keys and their respective cardinality as values.
Examples
--------
>>> from pgmpy.models import ClusterGraph
>>> from pgmpy.factors.discrete import DiscreteFactor
>>> student = ClusterGraph()
>>> factor = DiscreteFactor(['Alice', 'Bob'], cardinality=[2, 2],
... values=np.random.rand(4))
>>> student.add_node(('Alice', 'Bob'))
>>> student.add_factors(factor)
>>> student.get_cardinality()
defaultdict(<class 'int'>, {'Alice': 2, 'Bob': 2})
>>> student.get_cardinality(node='Alice')
2
"""
if node:
for factor in self.factors:
for variable, cardinality in zip(factor.scope(), factor.cardinality):
if node == variable:
return cardinality
else:
cardinalities = defaultdict(int)
for factor in self.factors:
for variable, cardinality in zip(factor.scope(), factor.cardinality):
cardinalities[variable] = cardinality
return cardinalities | [
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mongodb/pymodm | be1c7b079df4954ef7e79e46f1b4a9ac9510766c | pymodm/fields.py | python | IntegerField.__init__ | (self, verbose_name=None, mongo_name=None,
min_value=None, max_value=None, **kwargs) | :parameters:
- `verbose_name`: A human-readable name for the Field.
- `mongo_name`: The name of this field when stored in MongoDB.
- `min_value`: The minimum value that can be stored in this field.
- `max_value`: The maximum value that can be stored in this field.
.. seealso:: constructor for
:class:`~pymodm.base.fields.MongoBaseField` | :parameters:
- `verbose_name`: A human-readable name for the Field.
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- `mongo_name`: The name of this field when stored in MongoDB.
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rigetti/pyquil | 36987ecb78d5dc85d299dd62395b7669a1cedd5a | pyquil/quantum_processor/_base.py | python | AbstractQuantumProcessor.qubits | (self) | A sorted list of qubits in the quantum_processor topology. | A sorted list of qubits in the quantum_processor topology. | [
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Kozea/cairocffi | 2473d1bb82a52ca781edec595a95951509db2969 | cairocffi/pixbuf.py | python | decode_to_pixbuf | (image_data, width=None, height=None) | return Pixbuf(pixbuf), format_name | Decode an image from memory with GDK-PixBuf.
The file format is detected automatically.
:param image_data: A byte string
:param width: Integer width in pixels or None
:param height: Integer height in pixels or None
:returns:
A tuple of a new :class:`PixBuf` object
and the name of the detected image format.
:raises:
:exc:`ImageLoadingError` if the image data is invalid
or in an unsupported format. | Decode an image from memory with GDK-PixBuf.
The file format is detected automatically. | [
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:param image_data: A byte string
:param width: Integer width in pixels or None
:param height: Integer height in pixels or None
:returns:
A tuple of a new :class:`PixBuf` object
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:raises:
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"""
loader = ffi.gc(
gdk_pixbuf.gdk_pixbuf_loader_new(), gobject.g_object_unref)
error = ffi.new('GError **')
if width and height:
gdk_pixbuf.gdk_pixbuf_loader_set_size(loader, width, height)
handle_g_error(error, gdk_pixbuf.gdk_pixbuf_loader_write(
loader, image_data, len(image_data), error))
handle_g_error(error, gdk_pixbuf.gdk_pixbuf_loader_close(loader, error))
format_ = gdk_pixbuf.gdk_pixbuf_loader_get_format(loader)
format_name = (
ffi.string(gdk_pixbuf.gdk_pixbuf_format_get_name(format_))
.decode('ascii')
if format_ != ffi.NULL else None)
pixbuf = gdk_pixbuf.gdk_pixbuf_loader_get_pixbuf(loader)
if pixbuf == ffi.NULL: # pragma: no cover
raise ImageLoadingError('Not enough image data (got a NULL pixbuf.)')
return Pixbuf(pixbuf), format_name | [
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Tautulli/Tautulli | 2410eb33805aaac4bd1c5dad0f71e4f15afaf742 | lib/html5lib/_inputstream.py | python | HTMLUnicodeInputStream.position | (self) | return (line + 1, col) | Returns (line, col) of the current position in the stream. | Returns (line, col) of the current position in the stream. | [
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zhl2008/awd-platform | 0416b31abea29743387b10b3914581fbe8e7da5e | web_flaskbb/Python-2.7.9/Tools/scripts/texi2html.py | python | TexinfoParser.open_minus | (self) | [] | def open_minus(self): self.write('-') | [
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ewels/MultiQC | 9b953261d3d684c24eef1827a5ce6718c847a5af | multiqc/modules/deeptools/bamPEFragmentSizeDistribution.py | python | bamPEFragmentSizeDistributionMixin.parse_bamPEFragmentSizeDistribution | (self) | return len(self.deeptools_bamPEFragmentSizeDistribution) | Find bamPEFragmentSize output. Supports the --outRawFragmentLengths option | Find bamPEFragmentSize output. Supports the --outRawFragmentLengths option | [
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"""Find bamPEFragmentSize output. Supports the --outRawFragmentLengths option"""
self.deeptools_bamPEFragmentSizeDistribution = dict()
for f in self.find_log_files("deeptools/bamPEFragmentSizeDistribution", filehandles=False):
parsed_data = self.parseBamPEFDistributionFile(f)
for k, v in parsed_data.items():
if k in self.deeptools_bamPEFragmentSizeDistribution:
log.warning("Replacing duplicate sample {}.".format(k))
self.deeptools_bamPEFragmentSizeDistribution[k] = v
if len(parsed_data) > 0:
self.add_data_source(f, section="bamPEFragmentSizeDistribution")
self.deeptools_bamPEFragmentSizeDistribution = self.ignore_samples(self.deeptools_bamPEFragmentSizeDistribution)
if len(self.deeptools_bamPEFragmentSizeDistribution) > 0:
# Write data to file
self.write_data_file(self.deeptools_bamPEFragmentSizeDistribution, "deeptools_frag_size_dist")
config = {
"id": "fragment_size_distribution_plot",
"title": "deeptools: Fragment Size Distribution Plot",
"ylab": "Occurrence",
"xlab": "Fragment Size (bp)",
"smooth_points": 50,
"xmax": 1000,
"xDecimals": False,
"tt_label": "<b>Fragment Size (bp) {point.x}</b>: {point.y} Occurrence",
}
self.add_section(
name="Fragment size distribution",
anchor="fragment_size_distribution",
description="Distribution of paired-end fragment sizes",
plot=linegraph.plot(self.deeptools_bamPEFragmentSizeDistribution, config),
)
return len(self.deeptools_bamPEFragmentSizeDistribution) | [
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markj3d/Red9_StudioPack | 1d40a8bf84c45ce7eaefdd9ccfa3cdbeb1471919 | core/Red9_Audio.py | python | AudioNode.endTime | (self) | return (self.endFrame / r9General.getCurrentFPS()) * 1000 | : PRO_PACK : Maya end time of the sound node in milliseconds | : PRO_PACK : Maya end time of the sound node in milliseconds | [
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'''
: PRO_PACK : Maya end time of the sound node in milliseconds
'''
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wistbean/learn_python3_spider | 73c873f4845f4385f097e5057407d03dd37a117b | stackoverflow/venv/lib/python3.6/site-packages/twisted/protocols/policies.py | python | TimeoutFactory.callLater | (self, period, func) | return reactor.callLater(period, func) | Wrapper around
L{reactor.callLater<twisted.internet.interfaces.IReactorTime.callLater>}
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"""
Wrapper around
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for test purpose.
"""
from twisted.internet import reactor
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TurboGears/tg2 | f40a82d016d70ce560002593b4bb8f83b57f87b3 | tg/configurator/base.py | python | Configurator.update_blueprint | (self, config) | Add options from ``config`` to the configuration blueprint. | Add options from ``config`` to the configuration blueprint. | [
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ninthDevilHAUNSTER/ArknightsAutoHelper | a27a930502d6e432368d9f62595a1d69a992f4e6 | vendor/penguin_client/penguin_client/api/_deprecated_ap_is_api.py | python | DeprecatedAPIsApi.get_zone_by_zone_id_using_get_with_http_info | (self, zone_id, **kwargs) | return self.api_client.call_api(
'/api/zones/{zoneId}', 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='Zone', # noqa: E501
auth_settings=auth_settings,
async_req=params.get('async_req'),
_return_http_data_only=params.get('_return_http_data_only'),
_preload_content=params.get('_preload_content', True),
_request_timeout=params.get('_request_timeout'),
collection_formats=collection_formats) | Get zone by zone ID # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.get_zone_by_zone_id_using_get_with_http_info(zone_id, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str zone_id: zoneId (required)
:param bool i18n: i18n
:return: Zone
If the method is called asynchronously,
returns the request thread. | Get zone by zone ID # noqa: E501 | [
"Get",
"zone",
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"ID",
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"noqa",
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] | def get_zone_by_zone_id_using_get_with_http_info(self, zone_id, **kwargs): # noqa: E501
"""Get zone by zone ID # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.get_zone_by_zone_id_using_get_with_http_info(zone_id, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str zone_id: zoneId (required)
:param bool i18n: i18n
:return: Zone
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['zone_id', 'i18n'] # noqa: E501
all_params.append('async_req')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
params = locals()
for key, val in six.iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method get_zone_by_zone_id_using_get" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'zone_id' is set
if ('zone_id' not in params or
params['zone_id'] is None):
raise ValueError("Missing the required parameter `zone_id` when calling `get_zone_by_zone_id_using_get`") # noqa: E501
collection_formats = {}
path_params = {}
if 'zone_id' in params:
path_params['zoneId'] = params['zone_id'] # noqa: E501
query_params = []
if 'i18n' in params:
query_params.append(('i18n', params['i18n'])) # noqa: E501
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# HTTP header `Accept`
header_params['Accept'] = self.api_client.select_header_accept(
['application/json;charset=UTF-8']) # noqa: E501
# Authentication setting
auth_settings = [] # noqa: E501
return self.api_client.call_api(
'/api/zones/{zoneId}', 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='Zone', # noqa: E501
auth_settings=auth_settings,
async_req=params.get('async_req'),
_return_http_data_only=params.get('_return_http_data_only'),
_preload_content=params.get('_preload_content', True),
_request_timeout=params.get('_request_timeout'),
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linxid/Machine_Learning_Study_Path | 558e82d13237114bbb8152483977806fc0c222af | Machine Learning In Action/Chapter4-NaiveBayes/venv/Lib/collections/__init__.py | python | UserString.ljust | (self, width, *args) | return self.__class__(self.data.ljust(width, *args)) | [] | def ljust(self, width, *args):
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keras-team/keras-contrib | 3fc5ef709e061416f4bc8a92ca3750c824b5d2b0 | keras_contrib/layers/crf.py | python | CRF.get_energy | (self, y_true, input_energy, mask) | return total_energy | Energy = a1' y1 + u1' y1 + y1' U y2 + u2' y2 + y2' U y3 + u3' y3 + an' y3 | Energy = a1' y1 + u1' y1 + y1' U y2 + u2' y2 + y2' U y3 + u3' y3 + an' y3 | [
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"""
input_energy = K.sum(input_energy * y_true, 2) # (B, T)
# (B, T-1)
chain_energy = K.sum(K.dot(y_true[:, :-1, :],
self.chain_kernel) * y_true[:, 1:, :], 2)
if mask is not None:
mask = K.cast(mask, K.floatx())
# (B, T-1), mask[:,:-1]*mask[:,1:] makes it work with any padding
chain_mask = mask[:, :-1] * mask[:, 1:]
input_energy = input_energy * mask
chain_energy = chain_energy * chain_mask
total_energy = K.sum(input_energy, -1) + K.sum(chain_energy, -1) # (B, )
return total_energy | [
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buke/GreenOdoo | 3d8c55d426fb41fdb3f2f5a1533cfe05983ba1df | runtime/python/lib/python2.7/site-packages/ZSI-2.0-py2.7.egg/ZSI/schema.py | python | _GetPyobjWrapper.WrapImmutable | (cls, pyobj, what) | return newobj | return a wrapper for pyobj, with typecode attribute set.
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what -- typecode describing the data
'''
d = cls.types_dict
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rembo10/headphones | b3199605be1ebc83a7a8feab6b1e99b64014187c | lib/cherrypy/wsgiserver/wsgiserver2.py | python | format_exc | (limit=None) | Like print_exc() but return a string. Backport for Python 2.3. | Like print_exc() but return a string. Backport for Python 2.3. | [
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try:
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return ''.join(traceback.format_exception(etype, value, tb, limit))
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sympy/sympy | d822fcba181155b85ff2b29fe525adbafb22b448 | sympy/physics/mechanics/jointsmethod.py | python | JointsMethod.loads | (self) | return self._loads | List of loads on the system. | List of loads on the system. | [
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mozilla/zamboni | 14b1a44658e47b9f048962fa52dbf00a3beaaf30 | lib/es/management/commands/reindex.py | python | run_indexing | (index, index_name, ids) | Index the objects.
- index: name of the index
Note: `ignore_result=False` is required for the chord to work and trigger
the callback. | Index the objects. | [
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] | def run_indexing(index, index_name, ids):
"""Index the objects.
- index: name of the index
Note: `ignore_result=False` is required for the chord to work and trigger
the callback.
"""
indexer = INDEXER_MAP[index_name]
indexer.run_indexing(ids, ES, index=index) | [
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SebKuzminsky/pycam | 55e3129f518e470040e79bb00515b4bfcf36c172 | pycam/Gui/__init__.py | python | BaseUI.load_startup_workspace | (self) | return self.load_workspace_from_file(filename, remember_uri=False,
default_content=DEFAULT_WORKSPACE) | [] | def load_startup_workspace(self):
filename = pycam.Gui.Settings.get_workspace_filename()
return self.load_workspace_from_file(filename, remember_uri=False,
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deepgully/me | f7ad65edc2fe435310c6676bc2e322cfe5d4c8f0 | libs/sqlalchemy/sql/elements.py | python | _find_columns | (clause) | return cols | locate Column objects within the given expression. | locate Column objects within the given expression. | [
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traverse(clause, {}, {'column': cols.add})
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deepgully/me | f7ad65edc2fe435310c6676bc2e322cfe5d4c8f0 | libs/sqlalchemy/orm/events.py | python | AttributeEvents.set | (self, target, value, oldvalue, initiator) | Receive a scalar set event.
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zhl2008/awd-platform | 0416b31abea29743387b10b3914581fbe8e7da5e | web_flaskbb/lib/python2.7/site-packages/sqlalchemy_utils/types/password.py | python | Password.__eq__ | (self, value) | return False | [] | def __eq__(self, value):
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ambakick/Person-Detection-and-Tracking | f925394ac29b5cf321f1ce89a71b193381519a0b | utils/visualization_utils.py | python | draw_keypoints_on_image | (image,
keypoints,
color='red',
radius=2,
use_normalized_coordinates=True) | Draws keypoints on an image.
Args:
image: a PIL.Image object.
keypoints: a numpy array with shape [num_keypoints, 2].
color: color to draw the keypoints with. Default is red.
radius: keypoint radius. Default value is 2.
use_normalized_coordinates: if True (default), treat keypoint values as
relative to the image. Otherwise treat them as absolute. | Draws keypoints on an image. | [
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keypoints,
color='red',
radius=2,
use_normalized_coordinates=True):
"""Draws keypoints on an image.
Args:
image: a PIL.Image object.
keypoints: a numpy array with shape [num_keypoints, 2].
color: color to draw the keypoints with. Default is red.
radius: keypoint radius. Default value is 2.
use_normalized_coordinates: if True (default), treat keypoint values as
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"""
draw = ImageDraw.Draw(image)
im_width, im_height = image.size
keypoints_x = [k[1] for k in keypoints]
keypoints_y = [k[0] for k in keypoints]
if use_normalized_coordinates:
keypoints_x = tuple([im_width * x for x in keypoints_x])
keypoints_y = tuple([im_height * y for y in keypoints_y])
for keypoint_x, keypoint_y in zip(keypoints_x, keypoints_y):
draw.ellipse([(keypoint_x - radius, keypoint_y - radius),
(keypoint_x + radius, keypoint_y + radius)],
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oilshell/oil | 94388e7d44a9ad879b12615f6203b38596b5a2d3 | Python-2.7.13/Lib/pickletools.py | python | read_uint1 | (f) | r"""
>>> import StringIO
>>> read_uint1(StringIO.StringIO('\xff'))
255 | r"""
>>> import StringIO
>>> read_uint1(StringIO.StringIO('\xff'))
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r"""
>>> import StringIO
>>> read_uint1(StringIO.StringIO('\xff'))
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] | https://github.com/oilshell/oil/blob/94388e7d44a9ad879b12615f6203b38596b5a2d3/Python-2.7.13/Lib/pickletools.py#L201-L211 | ||
tendenci/tendenci | 0f2c348cc0e7d41bc56f50b00ce05544b083bf1d | tendenci/bin/tendenci.py | python | Command.create_parser | (self, command_name=None) | return parser | [] | def create_parser(self, command_name=None):
if command_name is None:
prog = None
else:
# hack the prog name as reported to ArgumentParser to include the command
prog = "%s %s" % (prog_name(), command_name)
parser = ArgumentParser(
description=getattr(self, 'description', None), add_help=False, prog=prog
)
self.add_arguments(parser)
return parser | [
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Symbo1/wsltools | 0b6e536fc85c707a1c81f0296c4e91ca835396a1 | wsltools/utils/faker/providers/address/pt_BR/__init__.py | python | Provider.bairro | (self) | return self.random_element(self.bairros) | Randomly returns a bairro (neighborhood) name.
The names were taken from the city of Belo Horizonte - Minas Gerais
:example 'Serra' | Randomly returns a bairro (neighborhood) name.
The names were taken from the city of Belo Horizonte - Minas Gerais | [
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"-",
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] | def bairro(self):
"""
Randomly returns a bairro (neighborhood) name.
The names were taken from the city of Belo Horizonte - Minas Gerais
:example 'Serra'
"""
return self.random_element(self.bairros) | [
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saltstack/salt | fae5bc757ad0f1716483ce7ae180b451545c2058 | salt/thorium/calc.py | python | __virtual__ | () | return HAS_STATS | The statistics module must be pip installed | The statistics module must be pip installed | [
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"""
The statistics module must be pip installed
"""
return HAS_STATS | [
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sahana/eden | 1696fa50e90ce967df69f66b571af45356cc18da | modules/s3/s3import.py | python | S3Importer._decode_data | (field, value) | Try to decode string data into their original type
Args:
field: the Field instance
value: the stringified value
TODO:
Replace this by ordinary decoder | Try to decode string data into their original type | [
"Try",
"to",
"decode",
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"data",
"into",
"their",
"original",
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] | def _decode_data(field, value):
"""
Try to decode string data into their original type
Args:
field: the Field instance
value: the stringified value
TODO:
Replace this by ordinary decoder
"""
if field.type == "string" or \
field.type == "password" or \
field.type == "upload" or \
field.type == "text":
return value
elif field.type == "integer" or \
field.type == "id":
return int(value)
elif field.type == "double" or \
field.type == "decimal":
return float(value)
elif field.type == "boolean":
if value and not str(value)[:1].upper() in ["F", "0"]:
return "T"
else:
return "F"
elif field.type == "date":
return value # @todo fix this to get a date
elif field.type == "time":
return value # @todo fix this to get a time
elif field.type == "datetime":
return value # @todo fix this to get a datetime
else:
return value | [
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sagemath/sage | f9b2db94f675ff16963ccdefba4f1a3393b3fe0d | src/sage/rings/number_field/number_field_rel.py | python | NumberField_relative.subfields | (self, degree=0, name=None) | return ans | Return all subfields of this relative number field self of the given degree,
or of all possible degrees if degree is 0. The subfields are returned as
absolute fields together with an embedding into self. For the case of the
field itself, the reverse isomorphism is also provided.
EXAMPLES::
sage: PQ.<X> = QQ[]
sage: F.<a, b> = NumberField([X^2 - 2, X^2 - 3])
sage: PF.<Y> = F[]
sage: K.<c> = F.extension(Y^2 - (1 + a)*(a + b)*a*b)
sage: K.subfields(2)
[
(Number Field in c0 with defining polynomial x^2 - 24*x + 96, Ring morphism:
From: Number Field in c0 with defining polynomial x^2 - 24*x + 96
To: Number Field in c with defining polynomial Y^2 + (-2*b - 3)*a - 2*b - 6 over its base field
Defn: c0 |--> -4*b + 12, None),
(Number Field in c1 with defining polynomial x^2 - 24*x + 120, Ring morphism:
From: Number Field in c1 with defining polynomial x^2 - 24*x + 120
To: Number Field in c with defining polynomial Y^2 + (-2*b - 3)*a - 2*b - 6 over its base field
Defn: c1 |--> 2*b*a + 12, None),
(Number Field in c2 with defining polynomial x^2 - 24*x + 72, Ring morphism:
From: Number Field in c2 with defining polynomial x^2 - 24*x + 72
To: Number Field in c with defining polynomial Y^2 + (-2*b - 3)*a - 2*b - 6 over its base field
Defn: c2 |--> -6*a + 12, None)
]
sage: K.subfields(8, 'w')
[
(Number Field in w0 with defining polynomial x^8 - 12*x^6 + 36*x^4 - 36*x^2 + 9, Ring morphism:
From: Number Field in w0 with defining polynomial x^8 - 12*x^6 + 36*x^4 - 36*x^2 + 9
To: Number Field in c with defining polynomial Y^2 + (-2*b - 3)*a - 2*b - 6 over its base field
Defn: w0 |--> (-1/2*b*a + 1/2*b + 1/2)*c, Relative number field morphism:
From: Number Field in c with defining polynomial Y^2 + (-2*b - 3)*a - 2*b - 6 over its base field
To: Number Field in w0 with defining polynomial x^8 - 12*x^6 + 36*x^4 - 36*x^2 + 9
Defn: c |--> -1/3*w0^7 + 4*w0^5 - 12*w0^3 + 11*w0
a |--> 1/3*w0^6 - 10/3*w0^4 + 5*w0^2
b |--> -2/3*w0^6 + 7*w0^4 - 14*w0^2 + 6)
]
sage: K.subfields(3)
[] | Return all subfields of this relative number field self of the given degree,
or of all possible degrees if degree is 0. The subfields are returned as
absolute fields together with an embedding into self. For the case of the
field itself, the reverse isomorphism is also provided. | [
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"""
Return all subfields of this relative number field self of the given degree,
or of all possible degrees if degree is 0. The subfields are returned as
absolute fields together with an embedding into self. For the case of the
field itself, the reverse isomorphism is also provided.
EXAMPLES::
sage: PQ.<X> = QQ[]
sage: F.<a, b> = NumberField([X^2 - 2, X^2 - 3])
sage: PF.<Y> = F[]
sage: K.<c> = F.extension(Y^2 - (1 + a)*(a + b)*a*b)
sage: K.subfields(2)
[
(Number Field in c0 with defining polynomial x^2 - 24*x + 96, Ring morphism:
From: Number Field in c0 with defining polynomial x^2 - 24*x + 96
To: Number Field in c with defining polynomial Y^2 + (-2*b - 3)*a - 2*b - 6 over its base field
Defn: c0 |--> -4*b + 12, None),
(Number Field in c1 with defining polynomial x^2 - 24*x + 120, Ring morphism:
From: Number Field in c1 with defining polynomial x^2 - 24*x + 120
To: Number Field in c with defining polynomial Y^2 + (-2*b - 3)*a - 2*b - 6 over its base field
Defn: c1 |--> 2*b*a + 12, None),
(Number Field in c2 with defining polynomial x^2 - 24*x + 72, Ring morphism:
From: Number Field in c2 with defining polynomial x^2 - 24*x + 72
To: Number Field in c with defining polynomial Y^2 + (-2*b - 3)*a - 2*b - 6 over its base field
Defn: c2 |--> -6*a + 12, None)
]
sage: K.subfields(8, 'w')
[
(Number Field in w0 with defining polynomial x^8 - 12*x^6 + 36*x^4 - 36*x^2 + 9, Ring morphism:
From: Number Field in w0 with defining polynomial x^8 - 12*x^6 + 36*x^4 - 36*x^2 + 9
To: Number Field in c with defining polynomial Y^2 + (-2*b - 3)*a - 2*b - 6 over its base field
Defn: w0 |--> (-1/2*b*a + 1/2*b + 1/2)*c, Relative number field morphism:
From: Number Field in c with defining polynomial Y^2 + (-2*b - 3)*a - 2*b - 6 over its base field
To: Number Field in w0 with defining polynomial x^8 - 12*x^6 + 36*x^4 - 36*x^2 + 9
Defn: c |--> -1/3*w0^7 + 4*w0^5 - 12*w0^3 + 11*w0
a |--> 1/3*w0^6 - 10/3*w0^4 + 5*w0^2
b |--> -2/3*w0^6 + 7*w0^4 - 14*w0^2 + 6)
]
sage: K.subfields(3)
[]
"""
if name is None:
name = self.variable_name()
abs = self.absolute_field(name)
from_abs, to_abs = abs.structure()
abs_subfields = abs.subfields(degree=degree)
ans = []
for K, from_K, to_K in abs_subfields:
from_K = K.hom([from_abs(from_K(K.gen()))])
if to_K is not None:
to_K = RelativeNumberFieldHomomorphism_from_abs(self.Hom(K), to_K*to_abs)
ans.append((K, from_K, to_K))
ans = Sequence(ans, immutable=True, cr=ans!=[])
return ans | [
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openid/python-openid | afa6adacbe1a41d8f614c8bce2264dfbe9e76489 | openid/store/filestore.py | python | _removeIfPresent | (filename) | Attempt to remove a file, returning whether the file existed at
the time of the call.
six.text_type -> bool | Attempt to remove a file, returning whether the file existed at
the time of the call. | [
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] | def _removeIfPresent(filename):
"""Attempt to remove a file, returning whether the file existed at
the time of the call.
six.text_type -> bool
"""
try:
os.unlink(filename)
except OSError as why:
if why.errno == ENOENT:
# Someone beat us to it, but it's gone, so that's OK
return 0
else:
raise
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# File was present
return 1 | [
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... | https://github.com/openid/python-openid/blob/afa6adacbe1a41d8f614c8bce2264dfbe9e76489/openid/store/filestore.py#L43-L59 | ||
ganeti/ganeti | d340a9ddd12f501bef57da421b5f9b969a4ba905 | lib/opcodes_base.py | python | _AutoOpParamSlots._GetSlots | (mcs, attrs) | return [pname for (pname, _, _, _) in params] | Build the slots out of OP_PARAMS. | Build the slots out of OP_PARAMS. | [
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] | def _GetSlots(mcs, attrs):
"""Build the slots out of OP_PARAMS.
"""
# Always set OP_PARAMS to avoid duplicates in BaseOpCode.GetAllParams
params = attrs.setdefault("OP_PARAMS", [])
# Use parameter names as slots
return [pname for (pname, _, _, _) in params] | [
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d4nj1/TLPUI | 83e41298674cac7487dd4f4d64f8552617d40b6c | tlpui/uihelper.py | python | get_flag_image | (locale: str) | return Gtk.Image().new_from_pixbuf(flagpixbuf) | Fetch flag image from icons folder. | Fetch flag image from icons folder. | [
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] | def get_flag_image(locale: str) -> Gtk.Image:
"""Fetch flag image from icons folder."""
flagpixbuf = GdkPixbuf.Pixbuf.new_from_file_at_size(f"{settings.icondir}flags/{locale}.png", width=16, height=16)
return Gtk.Image().new_from_pixbuf(flagpixbuf) | [
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sagemath/sage | f9b2db94f675ff16963ccdefba4f1a3393b3fe0d | src/sage/modular/arithgroup/arithgroup_perm.py | python | sl2z_word_problem | (A) | return output | r"""
Given an element of `{\rm SL}_2(\ZZ)`, express it as a word in the generators L =
[1,1,0,1] and R = [1,0,1,1].
The return format is a list of pairs ``(a,b)``, where ``a = 0`` or ``1``
denoting ``L`` or ``R`` respectively, and ``b`` is an integer exponent.
See also the function :func:`eval_sl2z_word`.
EXAMPLES::
sage: from sage.modular.arithgroup.arithgroup_perm import eval_sl2z_word, sl2z_word_problem
sage: m = SL2Z([1,0,0,1])
sage: eval_sl2z_word(sl2z_word_problem(m)) == m
True
sage: m = SL2Z([0,-1,1,0])
sage: eval_sl2z_word(sl2z_word_problem(m)) == m
True
sage: m = SL2Z([7,8,-50,-57])
sage: eval_sl2z_word(sl2z_word_problem(m)) == m
True | r"""
Given an element of `{\rm SL}_2(\ZZ)`, express it as a word in the generators L =
[1,1,0,1] and R = [1,0,1,1]. | [
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r"""
Given an element of `{\rm SL}_2(\ZZ)`, express it as a word in the generators L =
[1,1,0,1] and R = [1,0,1,1].
The return format is a list of pairs ``(a,b)``, where ``a = 0`` or ``1``
denoting ``L`` or ``R`` respectively, and ``b`` is an integer exponent.
See also the function :func:`eval_sl2z_word`.
EXAMPLES::
sage: from sage.modular.arithgroup.arithgroup_perm import eval_sl2z_word, sl2z_word_problem
sage: m = SL2Z([1,0,0,1])
sage: eval_sl2z_word(sl2z_word_problem(m)) == m
True
sage: m = SL2Z([0,-1,1,0])
sage: eval_sl2z_word(sl2z_word_problem(m)) == m
True
sage: m = SL2Z([7,8,-50,-57])
sage: eval_sl2z_word(sl2z_word_problem(m)) == m
True
"""
A = SL2Z(A)
output=[]
## If A00 is zero
if A[0,0]==0:
c=A[1,1]
if c != 1:
A=A*Lm**(c-1)*Rm*Lmi
output.extend([(0,1-c),(1,-1),(0,1)])
else:
A=A*Rm*Lmi
output.extend([(1,-1),(0,1)])
if A[0,0]<0: # Make sure A00 is positive
A=SL2Z(-1)*A
output.extend([(1,-1), (0,1), (1,-1), (0,1), (1,-1), (0,1)])
if A[0,1]<0: # if A01 is negative make it positive
n=(-A[0,1]/A[0,0]).ceil() #n s.t. 0 <= A[0,1]+n*A[0,0] < A[0,0]
A=A*Lm**n
output.append((0, -n))
## At this point A00>0 and A01>=0
while not (A[0,0]==0 or A[0,1]==0):
if A[0,0]>A[0,1]:
n=(A[0,0]/A[0,1]).floor()
A=A*SL2Z([1,0,-n,1])
output.append((1, n))
else: #A[0,0]<=A[0,1]
n=(A[0,1]/A[0,0]).floor()
A=A*SL2Z([1,-n,0,1])
output.append((0, n))
if A==SL2Z(1):
pass #done, so don't add R^0
elif A[0,0]==0:
c=A[1,1]
if c != 1:
A=A*Lm**(c-1)*Rm*Lmi
output.extend([(0,1-c),(1,-1),(0, 1)])
else:
A=A*Rm*Lmi
output.extend([(1,-1),(0,1)])
else:
c=A[1,0]
if c:
A=A*Rm**(-c)
output.append((1,c))
output.reverse()
return output | [
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haiwen/seahub | e92fcd44e3e46260597d8faa9347cb8222b8b10d | seahub/two_factor/views/utils.py | python | ExtraSessionStorage._set_validated_step_data | (self, validated_step_data) | [] | def _set_validated_step_data(self, validated_step_data):
self.data[self.validated_step_data_key] = validated_step_data | [
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kubernetes-client/python | 47b9da9de2d02b2b7a34fbe05afb44afd130d73a | kubernetes/client/models/v1_endpoint_conditions.py | python | V1EndpointConditions.serving | (self) | return self._serving | Gets the serving of this V1EndpointConditions. # noqa: E501
serving is identical to ready except that it is set regardless of the terminating state of endpoints. This condition should be set to true for a ready endpoint that is terminating. If nil, consumers should defer to the ready condition. This field can be enabled with the EndpointSliceTerminatingCondition feature gate. # noqa: E501
:return: The serving of this V1EndpointConditions. # noqa: E501
:rtype: bool | Gets the serving of this V1EndpointConditions. # noqa: E501 | [
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] | def serving(self):
"""Gets the serving of this V1EndpointConditions. # noqa: E501
serving is identical to ready except that it is set regardless of the terminating state of endpoints. This condition should be set to true for a ready endpoint that is terminating. If nil, consumers should defer to the ready condition. This field can be enabled with the EndpointSliceTerminatingCondition feature gate. # noqa: E501
:return: The serving of this V1EndpointConditions. # noqa: E501
:rtype: bool
"""
return self._serving | [
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IJDykeman/wangTiles | 7c1ee2095ebdf7f72bce07d94c6484915d5cae8b | experimental_code/tiles_3d/venv_mac_py3/lib/python2.7/site-packages/pip/_internal/configuration.py | python | Configuration.save | (self) | Save the currentin-memory state. | Save the currentin-memory state. | [
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# type: () -> None
"""Save the currentin-memory state.
"""
self._ensure_have_load_only()
for fname, parser in self._modified_parsers:
logger.info("Writing to %s", fname)
# Ensure directory exists.
ensure_dir(os.path.dirname(fname))
with open(fname, "w") as f:
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00nanhai/captchacker2 | 7609141b51ff0cf3329608b8101df967cb74752f | svm.py | python | svm_model.get_sv_indices | (self) | return sv_indices[:total_sv] | [] | def get_sv_indices(self):
total_sv = self.get_nr_sv()
sv_indices = (c_int * total_sv)()
libsvm.svm_get_sv_indices(self, sv_indices)
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ryu577/pyray | 860b71463e2729a85b1319b5c3571c0b8f3ba50c | pyray/shapes/twod/plane.py | python | xzplane | (draw, r, y, shift = np.array([1000, 1000, 0, 0]), scale = 300) | Draws an x-z plane on the draw object of an image. | Draws an x-z plane on the draw object of an image. | [
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"""
Draws an x-z plane on the draw object of an image.
"""
extent = 2.8
pln = np.array(
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pln = np.dot(pln, np.transpose(r))
pln = pln * scale + shift[:3]
draw.polygon([(pln[0][0],pln[0][1]),(pln[1][0],pln[1][1]),(pln[2][0],pln[2][1]),(pln[3][0],pln[3][1])], (0,102,255,70)) | [
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Ciphey/Ciphey | 4e5cc80a3cfdd5361ddb2d99322ed9b3ba54dc90 | ciphey/basemods/Searchers/ausearch.py | python | PriorityWorkQueue.get_work_chunk | (self) | return self._queues.pop(best_priority) | Returns the best work for now | Returns the best work for now | [
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"""Returns the best work for now"""
if len(self._sorted_priorities) == 0:
return []
best_priority = self._sorted_priorities.pop(0)
return self._queues.pop(best_priority) | [
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trailofbits/manticore | b050fdf0939f6c63f503cdf87ec0ab159dd41159 | manticore/native/cpu/x86.py | python | X86Cpu.CMP | (cpu, src1, src2) | Compares two operands.
Compares the first source operand with the second source operand and sets the status flags
in the EFLAGS register according to the results. The comparison is performed by subtracting
the second operand from the first operand and then setting the status flags in the same manner
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temp = SRC1 - SignExtend(SRC2);
ModifyStatusFlags; (* Modify status flags in the same manner as the SUB instruction*)
The CF, OF, SF, ZF, AF, and PF flags are set according to the result.
:param cpu: current CPU.
:param dest: destination operand.
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"""
Compares two operands.
Compares the first source operand with the second source operand and sets the status flags
in the EFLAGS register according to the results. The comparison is performed by subtracting
the second operand from the first operand and then setting the status flags in the same manner
as the SUB instruction. When an immediate value is used as an operand, it is sign-extended to
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temp = SRC1 - SignExtend(SRC2);
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The CF, OF, SF, ZF, AF, and PF flags are set according to the result.
:param cpu: current CPU.
:param dest: destination operand.
:param src: source operand.
"""
arg0 = src1.read()
arg1 = Operators.SEXTEND(src2.read(), src2.size, src1.size)
# Affected Flags o..szapc
cpu._calculate_CMP_flags(src1.size, arg0 - arg1, arg0, arg1) | [
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plotly/plotly.py | cfad7862594b35965c0e000813bd7805e8494a5b | packages/python/plotly/plotly/graph_objs/_surface.py | python | Surface.connectgaps | (self) | return self["connectgaps"] | Determines whether or not gaps (i.e. {nan} or missing values)
in the `z` data are filled in.
The 'connectgaps' property must be specified as a bool
(either True, or False)
Returns
-------
bool | Determines whether or not gaps (i.e. {nan} or missing values)
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The 'connectgaps' property must be specified as a bool
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Determines whether or not gaps (i.e. {nan} or missing values)
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linxid/Machine_Learning_Study_Path | 558e82d13237114bbb8152483977806fc0c222af | Machine Learning In Action/Chapter4-NaiveBayes/venv/Lib/site-packages/pip/_vendor/cachecontrol/controller.py | python | CacheController.__init__ | (self, cache=None, cache_etags=True, serializer=None) | [] | def __init__(self, cache=None, cache_etags=True, serializer=None):
self.cache = cache or DictCache()
self.cache_etags = cache_etags
self.serializer = serializer or Serializer() | [
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chribsen/simple-machine-learning-examples | dc94e52a4cebdc8bb959ff88b81ff8cfeca25022 | venv/lib/python2.7/site-packages/sklearn/cluster/k_means_.py | python | KMeans._transform | (self, X) | return euclidean_distances(X, self.cluster_centers_) | guts of transform method; no input validation | guts of transform method; no input validation | [
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"""guts of transform method; no input validation"""
return euclidean_distances(X, self.cluster_centers_) | [
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amymcgovern/pyparrot | bf4775ec1199b282e4edde1e4a8e018dcc8725e0 | pyparrot/utils/vlc.py | python | MediaPlayer.get_full_title_descriptions | (self) | return info | Get the full description of available titles.
@return: the titles list
@version: LibVLC 3.0.0 and later. | Get the full description of available titles. | [
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] | def get_full_title_descriptions(self):
'''Get the full description of available titles.
@return: the titles list
@version: LibVLC 3.0.0 and later.
'''
titleDescription_pp = ctypes.POINTER(TitleDescription)()
n = libvlc_media_player_get_full_title_descriptions(self, ctypes.byref(titleDescription_pp))
info = ctypes.cast(ctypes.titleDescription_pp, ctypes.POINTER(ctypes.POINTER(TitleDescription) * n))
return info | [
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ConsenSys/ethjsonrpc | fe525bdcd889924687ba1646fc46cef329410e22 | ethjsonrpc/client.py | python | EthJsonRpc.db_getHex | (self, db_name, key) | return self._call('db_getHex', [db_name, key]) | https://github.com/ethereum/wiki/wiki/JSON-RPC#db_gethex
TESTED | https://github.com/ethereum/wiki/wiki/JSON-RPC#db_gethex | [
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'''
https://github.com/ethereum/wiki/wiki/JSON-RPC#db_gethex
TESTED
'''
warnings.warn('deprecated', DeprecationWarning)
return self._call('db_getHex', [db_name, key]) | [
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benedekrozemberczki/ClusterGCN | 718d17ff588a65792fd821a1fe2af0f646e49ebd | src/clustering.py | python | ClusteringMachine.random_clustering | (self) | Random clustering the nodes. | Random clustering the nodes. | [
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"""
Random clustering the nodes.
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self.clusters = [cluster for cluster in range(self.args.cluster_number)]
self.cluster_membership = {node: random.choice(self.clusters) for node in self.graph.nodes()} | [
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pygae/clifford | 0b6cffb9a6d44ecb7a666f6b08b1788fc94a0ab6 | clifford/tools/g3c/object_fitting.py | python | fit_circle | (point_list) | return layout.MultiVector(val_fit_circle(np.array([p.value for p in point_list]))) | Performs Leo Dorsts circle fitting technique | Performs Leo Dorsts circle fitting technique | [
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"""
Performs Leo Dorsts circle fitting technique
"""
return layout.MultiVector(val_fit_circle(np.array([p.value for p in point_list]))) | [
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lovelylain/pyctp | fd304de4b50c4ddc31a4190b1caaeb5dec66bc5d | example/pyctp2/trader/trade_command.py | python | OpenInstruction.__init__ | (self,order,position) | [] | def __init__(self,order,position):
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googleads/google-ads-python | 2a1d6062221f6aad1992a6bcca0e7e4a93d2db86 | google/ads/googleads/v9/services/services/shared_set_service/client.py | python | SharedSetServiceClient.common_folder_path | (folder: str,) | return "folders/{folder}".format(folder=folder,) | Return a fully-qualified folder string. | Return a fully-qualified folder string. | [
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dpp/simply_lift | cf49f7dcce81c7f1557314dd0f0bb08aaedc73da | elyxer.py | python | PostLayout.number | (self, layout) | Generate a number and place it before the text | Generate a number and place it before the text | [
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holzschu/Carnets | 44effb10ddfc6aa5c8b0687582a724ba82c6b547 | Library/lib/python3.7/site-packages/sympy/geometry/polygon.py | python | Triangle.vertices | (self) | return self.args | The triangle's vertices
Returns
=======
vertices : tuple
Each element in the tuple is a Point
See Also
========
sympy.geometry.point.Point
Examples
========
>>> from sympy.geometry import Triangle, Point
>>> t = Triangle(Point(0, 0), Point(4, 0), Point(4, 3))
>>> t.vertices
(Point2D(0, 0), Point2D(4, 0), Point2D(4, 3)) | The triangle's vertices | [
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"""The triangle's vertices
Returns
=======
vertices : tuple
Each element in the tuple is a Point
See Also
========
sympy.geometry.point.Point
Examples
========
>>> from sympy.geometry import Triangle, Point
>>> t = Triangle(Point(0, 0), Point(4, 0), Point(4, 3))
>>> t.vertices
(Point2D(0, 0), Point2D(4, 0), Point2D(4, 3))
"""
return self.args | [
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kylebebak/Requester | 4a9f9f051fa5fc951a8f7ad098a328261ca2db97 | deps/requests/models.py | python | Response.ok | (self) | return True | Returns True if :attr:`status_code` is less than 400.
This attribute checks if the status code of the response is between
400 and 600 to see if there was a client error or a server error. If
the status code, is between 200 and 400, this will return True. This
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400 and 600 to see if there was a client error or a server error. If
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hsokooti/RegNet | 28a8b6132677bb58e9fc811c0dd15d78913c7e86 | functions/setting/setting_utils.py | python | get_global_step | (setting, requested_global_step, current_experiment) | return global_step | get the global step of saver in order to load the requested network model:
'Last': search in the saved_folder to find the last network model
'Auto': use the global step defined in the function load_global_step_from_predefined_list()
'#Number' : otherwise the number that is requested will be used.
:param setting:
:param requested_global_step:
:param current_experiment:
:return: global_step | get the global step of saver in order to load the requested network model:
'Last': search in the saved_folder to find the last network model
'Auto': use the global step defined in the function load_global_step_from_predefined_list()
'#Number' : otherwise the number that is requested will be used.
:param setting:
:param requested_global_step:
:param current_experiment:
:return: global_step | [
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'Auto': use the global step defined in the function load_global_step_from_predefined_list()
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:param setting:
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"""
model_folder = address_generator(setting, 'ModelFolder', current_experiment=current_experiment)
saved_folder = model_folder + 'Saved/'
if requested_global_step == 'Last':
saved_itr_list = []
for file in os.listdir(saved_folder):
if file.endswith('meta'):
saved_itr_list.append(int(os.path.splitext(file.rsplit('-')[1])[0]))
global_step = str(max(saved_itr_list))
logging.info('Loading Network:' + current_experiment + ', GlobalStepLoad=' + global_step)
elif requested_global_step == 'Auto':
global_step = load_global_step_from_predefined_list(current_experiment)
logging.info('Loading Network:' + current_experiment + ', GlobalStepLoad=' + global_step)
else:
global_step = requested_global_step
return global_step | [
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rackerlabs/mimic | efd34108b6aa3eb7ecd26e22f1aa155c14a7885e | mimic/canned_responses/fastly.py | python | FastlyResponse.create_version | (self, service_id) | return create_version | Returns POST service with response json.
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JiYou/openstack | 8607dd488bde0905044b303eb6e52bdea6806923 | packages/source/keystone/keystone/openstack/common/jsonutils.py | python | to_primitive | (value, convert_instances=False, level=0) | Convert a complex object into primitives.
Handy for JSON serialization. We can optionally handle instances,
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To handle cyclical data structures we could track the actual objects
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"""Convert a complex object into primitives.
Handy for JSON serialization. We can optionally handle instances,
but since this is a recursive function, we could have cyclical
data structures.
To handle cyclical data structures we could track the actual objects
visited in a set, but not all objects are hashable. Instead we just
track the depth of the object inspections and don't go too deep.
Therefore, convert_instances=True is lossy ... be aware.
"""
nasty = [inspect.ismodule, inspect.isclass, inspect.ismethod,
inspect.isfunction, inspect.isgeneratorfunction,
inspect.isgenerator, inspect.istraceback, inspect.isframe,
inspect.iscode, inspect.isbuiltin, inspect.isroutine,
inspect.isabstract]
for test in nasty:
if test(value):
return unicode(value)
# value of itertools.count doesn't get caught by inspects
# above and results in infinite loop when list(value) is called.
if type(value) == itertools.count:
return unicode(value)
# FIXME(vish): Workaround for LP bug 852095. Without this workaround,
# tests that raise an exception in a mocked method that
# has a @wrap_exception with a notifier will fail. If
# we up the dependency to 0.5.4 (when it is released) we
# can remove this workaround.
if getattr(value, '__module__', None) == 'mox':
return 'mock'
if level > 3:
return '?'
# The try block may not be necessary after the class check above,
# but just in case ...
try:
# It's not clear why xmlrpclib created their own DateTime type, but
# for our purposes, make it a datetime type which is explicitly
# handled
if isinstance(value, xmlrpclib.DateTime):
value = datetime.datetime(*tuple(value.timetuple())[:6])
if isinstance(value, (list, tuple)):
o = []
for v in value:
o.append(to_primitive(v, convert_instances=convert_instances,
level=level))
return o
elif isinstance(value, dict):
o = {}
for k, v in value.iteritems():
o[k] = to_primitive(v, convert_instances=convert_instances,
level=level)
return o
elif isinstance(value, datetime.datetime):
return timeutils.strtime(value)
elif hasattr(value, 'iteritems'):
return to_primitive(dict(value.iteritems()),
convert_instances=convert_instances,
level=level + 1)
elif hasattr(value, '__iter__'):
return to_primitive(list(value),
convert_instances=convert_instances,
level=level)
elif convert_instances and hasattr(value, '__dict__'):
# Likely an instance of something. Watch for cycles.
# Ignore class member vars.
return to_primitive(value.__dict__,
convert_instances=convert_instances,
level=level + 1)
else:
return value
except TypeError, e:
# Class objects are tricky since they may define something like
# __iter__ defined but it isn't callable as list().
return unicode(value) | [
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tomplus/kubernetes_asyncio | f028cc793e3a2c519be6a52a49fb77ff0b014c9b | kubernetes_asyncio/client/models/v1alpha1_flow_schema_list.py | python | V1alpha1FlowSchemaList.__ne__ | (self, other) | return self.to_dict() != other.to_dict() | Returns true if both objects are not equal | Returns true if both objects are not equal | [
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"""Returns true if both objects are not equal"""
if not isinstance(other, V1alpha1FlowSchemaList):
return True
return self.to_dict() != other.to_dict() | [
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openembedded/openembedded-core | 9154f71c7267e9731156c1dfd57397103e9e6a2b | meta/lib/oeqa/runtime/cases/multilib.py | python | MultilibTest.test_check_multilib_libc | (self) | Check that a multilib image has both 32-bit and 64-bit libc in. | Check that a multilib image has both 32-bit and 64-bit libc in. | [
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] | def test_check_multilib_libc(self):
"""
Check that a multilib image has both 32-bit and 64-bit libc in.
"""
self.archtest("/lib/libc.so.6", "ELF32")
self.archtest("/lib64/libc.so.6", "ELF64") | [
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learningequality/ka-lite | 571918ea668013dcf022286ea85eff1c5333fb8b | kalite/distributed/static/js/distributed/perseus/ke/build/clean-exercises.py | python | main | () | Handle running this program from the command-line. | Handle running this program from the command-line. | [
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"""Handle running this program from the command-line."""
# Handle parsing the program arguments
arg_parser = argparse.ArgumentParser(
description='Clean up HTML exercise files.')
arg_parser.add_argument('html_files', nargs='+',
help='The HTML exercise files to clean up.')
args = arg_parser.parse_args()
for filename in args.html_files:
# Parse the HTML tree. The parser in lint_i18n_strings properly
# handles utf-8, which the default lxml parser doesn't. :-(
html_tree = lxml.html.html5parser.parse(
filename, parser=lint_i18n_strings.PARSER)
with open(filename, 'w') as f:
f.write(lint_i18n_strings.get_page_html(html_tree)) | [
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titusjan/argos | 5a9c31a8a9a2ca825bbf821aa1e685740e3682d7 | argos/inspector/pgplugins/pgctis.py | python | AbstractRangeCti.calculateRange | (self) | Calculates the range depending on the config settings. | Calculates the range depending on the config settings. | [
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return rangeFunction(self.subsampleCti.configValue) | [
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holzschu/Carnets | 44effb10ddfc6aa5c8b0687582a724ba82c6b547 | Library/lib/python3.7/site-packages/sympy/polys/densetools.py | python | dup_primitive | (f, K) | Compute content and the primitive form of ``f`` in ``K[x]``.
Examples
========
>>> from sympy.polys import ring, ZZ, QQ
>>> R, x = ring("x", ZZ)
>>> f = 6*x**2 + 8*x + 12
>>> R.dup_primitive(f)
(2, 3*x**2 + 4*x + 6)
>>> R, x = ring("x", QQ)
>>> f = 6*x**2 + 8*x + 12
>>> R.dup_primitive(f)
(2, 3*x**2 + 4*x + 6) | Compute content and the primitive form of ``f`` in ``K[x]``. | [
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"""
Compute content and the primitive form of ``f`` in ``K[x]``.
Examples
========
>>> from sympy.polys import ring, ZZ, QQ
>>> R, x = ring("x", ZZ)
>>> f = 6*x**2 + 8*x + 12
>>> R.dup_primitive(f)
(2, 3*x**2 + 4*x + 6)
>>> R, x = ring("x", QQ)
>>> f = 6*x**2 + 8*x + 12
>>> R.dup_primitive(f)
(2, 3*x**2 + 4*x + 6)
"""
if not f:
return K.zero, f
cont = dup_content(f, K)
if K.is_one(cont):
return cont, f
else:
return cont, dup_quo_ground(f, cont, K) | [
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kanzure/nanoengineer | 874e4c9f8a9190f093625b267f9767e19f82e6c4 | cad/src/utilities/GlobalPreferences.py | python | pref_skip_redraws_requested_only_by_Qt | () | return res | If enabled, GLPane paintGL calls not requested by our own gl_update calls
are skipped, as an optimization. See comments where used for details
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#bruce 080516 moved this here, revised default to be off on Windows
"""
If enabled, GLPane paintGL calls not requested by our own gl_update calls
are skipped, as an optimization. See comments where used for details
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"""
if sys.platform == "win32":
# Windows -- enabling this causes bugs on at least one system
choice = Choice_boolean_False
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#bruce 080512 made this True, revised prefs_key
choice = Choice_boolean_True
res = debug_pref("GLPane: skip redraws requested only by Qt?",
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prefs_key = "GLPane: skip redraws requested only by Qt?"
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Cadene/tensorflow-model-zoo.torch | 990b10ffc22d4c8eacb2a502f20415b4f70c74c2 | models/research/object_detection/utils/np_box_ops.py | python | intersection | (boxes1, boxes2) | return intersect_heights * intersect_widths | Compute pairwise intersection areas between boxes.
Args:
boxes1: a numpy array with shape [N, 4] holding N boxes
boxes2: a numpy array with shape [M, 4] holding M boxes
Returns:
a numpy array with shape [N*M] representing pairwise intersection area | Compute pairwise intersection areas between boxes. | [
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] | def intersection(boxes1, boxes2):
"""Compute pairwise intersection areas between boxes.
Args:
boxes1: a numpy array with shape [N, 4] holding N boxes
boxes2: a numpy array with shape [M, 4] holding M boxes
Returns:
a numpy array with shape [N*M] representing pairwise intersection area
"""
[y_min1, x_min1, y_max1, x_max1] = np.split(boxes1, 4, axis=1)
[y_min2, x_min2, y_max2, x_max2] = np.split(boxes2, 4, axis=1)
all_pairs_min_ymax = np.minimum(y_max1, np.transpose(y_max2))
all_pairs_max_ymin = np.maximum(y_min1, np.transpose(y_min2))
intersect_heights = np.maximum(
np.zeros(all_pairs_max_ymin.shape),
all_pairs_min_ymax - all_pairs_max_ymin)
all_pairs_min_xmax = np.minimum(x_max1, np.transpose(x_max2))
all_pairs_max_xmin = np.maximum(x_min1, np.transpose(x_min2))
intersect_widths = np.maximum(
np.zeros(all_pairs_max_xmin.shape),
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return intersect_heights * intersect_widths | [
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autonomousvision/differentiable_volumetric_rendering | 5a190104b9f8143125beed714d33f265f5006f30 | im2mesh/dvr/models/depth_function.py | python | DepthFunction.run_Bisection_method | (d_low, d_high, n_secant_steps, ray0_masked,
ray_direction_masked, decoder, c, logit_tau) | return d_pred | Runs the bisection method for interval [d_low, d_high].
Args:
d_low (tensor): start values for the interval
d_high (tensor): end values for the interval
n_secant_steps (int): number of steps
ray0_masked (tensor): masked ray start points
ray_direction_masked (tensor): masked ray direction vectors
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''' Runs the bisection method for interval [d_low, d_high].
Args:
d_low (tensor): start values for the interval
d_high (tensor): end values for the interval
n_secant_steps (int): number of steps
ray0_masked (tensor): masked ray start points
ray_direction_masked (tensor): masked ray direction vectors
decoder (nn.Module): decoder model to evaluate point occupancies
c (tensor): latent conditioned code c
logit_tau (float): threshold value in logits
'''
d_pred = (d_low + d_high) / 2.
for i in range(n_secant_steps):
p_mid = ray0_masked + d_pred.unsqueeze(-1) * ray_direction_masked
with torch.no_grad():
f_mid = decoder(p_mid, c, batchwise=False,
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ind_low = f_mid < 0
d_low[ind_low] = d_pred[ind_low]
d_high[ind_low == 0] = d_pred[ind_low == 0]
d_pred = 0.5 * (d_low + d_high)
return d_pred | [
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JulianEberius/SublimePythonIDE | d70e40abc0c9f347af3204c7b910e0d6bfd6e459 | server/lib/python2/rope/refactor/occurrences.py | python | Finder.find_occurrences | (self, resource=None, pymodule=None) | Generate `Occurrence` instances | Generate `Occurrence` instances | [
"Generate",
"Occurrence",
"instances"
] | def find_occurrences(self, resource=None, pymodule=None):
"""Generate `Occurrence` instances"""
tools = _OccurrenceToolsCreator(self.pycore, resource=resource,
pymodule=pymodule, docs=self.docs)
for offset in self._textual_finder.find_offsets(tools.source_code):
occurrence = Occurrence(tools, offset)
for filter in self.filters:
result = filter(occurrence)
if result is None:
continue
if result:
yield occurrence
break | [
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tdozat/Parser-v1 | 0739216129cd39d69997d28cbc4133b360ea3934 | lib/models/rnn.py | python | _dynamic_rnn_loop | ( cell, inputs, initial_state, ff_keep_prob, recur_keep_prob, parallel_iterations, swap_memory, sequence_length=None) | return (final_outputs, final_state) | Internal implementation of Dynamic RNN.
Args:
cell: An instance of RNNCell.
inputs: A `Tensor` of shape [time, batch_size, depth].
initial_state: A `Tensor` of shape [batch_size, depth].
parallel_iterations: Positive Python int.
swap_memory: A Python boolean
sequence_length: (optional) An `int32` `Tensor` of shape [batch_size].
Returns:
Tuple (final_outputs, final_state).
final_outputs:
A `Tensor` of shape [time, batch_size, depth]`.
final_state:
A `Tensor` of shape [batch_size, depth].
Raises:
ValueError: If the input depth cannot be inferred via shape inference
from the inputs. | Internal implementation of Dynamic RNN. | [
"Internal",
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] | def _dynamic_rnn_loop( cell, inputs, initial_state, ff_keep_prob, recur_keep_prob, parallel_iterations, swap_memory, sequence_length=None):
"""Internal implementation of Dynamic RNN.
Args:
cell: An instance of RNNCell.
inputs: A `Tensor` of shape [time, batch_size, depth].
initial_state: A `Tensor` of shape [batch_size, depth].
parallel_iterations: Positive Python int.
swap_memory: A Python boolean
sequence_length: (optional) An `int32` `Tensor` of shape [batch_size].
Returns:
Tuple (final_outputs, final_state).
final_outputs:
A `Tensor` of shape [time, batch_size, depth]`.
final_state:
A `Tensor` of shape [batch_size, depth].
Raises:
ValueError: If the input depth cannot be inferred via shape inference
from the inputs.
"""
state = initial_state
assert isinstance(parallel_iterations, int), "parallel_iterations must be int"
# Construct an initial output
input_shape = array_ops.shape(inputs)
(time_steps, batch_size, _) = array_ops.unpack(input_shape, 3)
inputs_got_shape = inputs.get_shape().with_rank(3)
(const_time_steps, const_batch_size, const_depth) = inputs_got_shape.as_list()
if const_depth is None:
raise ValueError(
"Input size (depth of inputs) must be accessible via shape inference, "
"but saw value None.")
# Prepare dynamic conditional copying of state & output
zero_output = array_ops.zeros(
array_ops.pack([batch_size, cell.output_size]), inputs.dtype)
if sequence_length is not None:
min_sequence_length = math_ops.reduce_min(sequence_length)
max_sequence_length = math_ops.reduce_max(sequence_length)
time = array_ops.constant(0, dtype=dtypes.int32, name="time")
with ops.op_scope([], "dynamic_rnn") as scope:
base_name = scope
output_ta = tensor_array_ops.TensorArray(
dtype=inputs.dtype, size=time_steps,
tensor_array_name=base_name + "output")
input_ta = tensor_array_ops.TensorArray(
dtype=inputs.dtype, size=time_steps,
tensor_array_name=base_name + "input")
if isinstance(ff_keep_prob, ops.Tensor) or ff_keep_prob < 1:
inputs = nn_ops.dropout(inputs, ff_keep_prob, noise_shape=array_ops.pack([1, batch_size, const_depth]))
input_ta = input_ta.unpack(inputs)
if isinstance(recur_keep_prob, ops.Tensor) or recur_keep_prob < 1:
ones = array_ops.ones(array_ops.pack([batch_size, cell.output_size]), inputs.dtype)
state_dropout = nn_ops.dropout(ones, recur_keep_prob)
state_dropout = array_ops.concat(1, [ones] * (cell.state_size // cell.output_size - 1) + [state_dropout])
else:
state_dropout = 1.
def _time_step(time, state, output_ta_t):
"""Take a time step of the dynamic RNN.
Args:
time: int32 scalar Tensor.
state: Vector.
output_ta_t: `TensorArray`, the output with existing flow.
Returns:
The tuple (time + 1, new_state, output_ta_t with updated flow).
"""
input_t = input_ta.read(time)
# Restore some shape information
input_t.set_shape([const_batch_size, const_depth])
call_cell = lambda: cell(input_t, state*state_dropout)
if sequence_length is not None:
(output, new_state) = _rnn_step(
time=time,
sequence_length=sequence_length,
min_sequence_length=min_sequence_length,
max_sequence_length=max_sequence_length,
zero_output=zero_output,
state=state,
call_cell=call_cell,
skip_conditionals=True)
else:
(output, new_state) = call_cell()
output_ta_t = output_ta_t.write(time, output)
return (time + 1, new_state, output_ta_t)
(_, final_state, output_final_ta) = control_flow_ops.while_loop(
cond=lambda time, _1, _2: time < time_steps,
body=_time_step,
loop_vars=(time, state, output_ta),
parallel_iterations=parallel_iterations,
swap_memory=swap_memory)
final_outputs = output_final_ta.pack()
# Restore some shape information
final_outputs.set_shape([
const_time_steps, const_batch_size, cell.output_size])
return (final_outputs, final_state) | [
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llSourcell/AI_For_Music_Composition | 795f8879158b238e7dc78d07e4451dcf54a2126c | musegan/utils/midi_io.py | python | save_midi | (filepath, phrases, config) | Save a batch of phrases to a single MIDI file.
Arguments
---------
filepath : str
Path to save the image grid.
phrases : list of np.array
Phrase arrays to be saved. All arrays must have the same shape.
pause : int
Length of pauses (in timestep) to be inserted between phrases.
Default to 0. | Save a batch of phrases to a single MIDI file. | [
"Save",
"a",
"batch",
"of",
"phrases",
"to",
"a",
"single",
"MIDI",
"file",
"."
] | def save_midi(filepath, phrases, config):
"""
Save a batch of phrases to a single MIDI file.
Arguments
---------
filepath : str
Path to save the image grid.
phrases : list of np.array
Phrase arrays to be saved. All arrays must have the same shape.
pause : int
Length of pauses (in timestep) to be inserted between phrases.
Default to 0.
"""
if not np.issubdtype(phrases.dtype, np.bool_):
raise TypeError("Support only binary-valued piano-rolls")
reshaped = phrases.reshape(-1, phrases.shape[1] * phrases.shape[2],
phrases.shape[3], phrases.shape[4])
pad_width = ((0, 0), (0, config['pause_between_samples']),
(config['lowest_pitch'],
128 - config['lowest_pitch'] - config['num_pitch']),
(0, 0))
padded = np.pad(reshaped, pad_width, 'constant')
pianorolls = padded.reshape(-1, padded.shape[2], padded.shape[3])
write_midi(filepath, pianorolls, config['programs'], config['is_drums'],
tempo=config['tempo']) | [
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home-assistant/core | 265ebd17a3f17ed8dc1e9bdede03ac8e323f1ab1 | homeassistant/util/volume.py | python | cubic_feet_to_cubic_meter | (cubic_feet: float) | return cubic_feet * 0.0283168466 | Convert a volume measurement in cubic feet to cubic meter. | Convert a volume measurement in cubic feet to cubic meter. | [
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"in",
"cubic",
"feet",
"to",
"cubic",
"meter",
"."
] | def cubic_feet_to_cubic_meter(cubic_feet: float) -> float:
"""Convert a volume measurement in cubic feet to cubic meter."""
return cubic_feet * 0.0283168466 | [
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DataXujing/YOLO-V3-Tensorflow | 20562d0c22965a904c6648997b66dfdf1c96be4d | utils/eval_utils.py | python | calc_iou | (pred_boxes, true_boxes) | return iou | Maintain an efficient way to calculate the ios matrix using the numpy broadcast tricks.
shape_info: pred_boxes: [N, 4]
true_boxes: [V, 4]
return: IoU matrix: shape: [N, V] | Maintain an efficient way to calculate the ios matrix using the numpy broadcast tricks.
shape_info: pred_boxes: [N, 4]
true_boxes: [V, 4]
return: IoU matrix: shape: [N, V] | [
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... | def calc_iou(pred_boxes, true_boxes):
'''
Maintain an efficient way to calculate the ios matrix using the numpy broadcast tricks.
shape_info: pred_boxes: [N, 4]
true_boxes: [V, 4]
return: IoU matrix: shape: [N, V]
'''
# [N, 1, 4]
pred_boxes = np.expand_dims(pred_boxes, -2)
# [1, V, 4]
true_boxes = np.expand_dims(true_boxes, 0)
# [N, 1, 2] & [1, V, 2] ==> [N, V, 2]
intersect_mins = np.maximum(pred_boxes[..., :2], true_boxes[..., :2])
intersect_maxs = np.minimum(pred_boxes[..., 2:], true_boxes[..., 2:])
intersect_wh = np.maximum(intersect_maxs - intersect_mins, 0.)
# shape: [N, V]
intersect_area = intersect_wh[..., 0] * intersect_wh[..., 1]
# shape: [N, 1, 2]
pred_box_wh = pred_boxes[..., 2:] - pred_boxes[..., :2]
# shape: [N, 1]
pred_box_area = pred_box_wh[..., 0] * pred_box_wh[..., 1]
# [1, V, 2]
true_boxes_wh = true_boxes[..., 2:] - true_boxes[..., :2]
# [1, V]
true_boxes_area = true_boxes_wh[..., 0] * true_boxes_wh[..., 1]
# shape: [N, V]
iou = intersect_area / (pred_box_area + true_boxes_area - intersect_area + 1e-10)
return iou | [
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blockcypher/explorer | 3cb07c58ed6573964921e343fce01552accdf958 | emails/trigger.py | python | send_and_log | (subject, body_template, to_user=None, to_email=None,
to_name=None, body_context={}, from_name=None, from_email=None,
cc_name=None, cc_email=None, replyto_name=None, replyto_email=None,
fkey_objs={}) | return se | Send and log an email | Send and log an email | [
"Send",
"and",
"log",
"an",
"email"
] | def send_and_log(subject, body_template, to_user=None, to_email=None,
to_name=None, body_context={}, from_name=None, from_email=None,
cc_name=None, cc_email=None, replyto_name=None, replyto_email=None,
fkey_objs={}):
"""
Send and log an email
"""
# TODO: find a better way to handle the circular dependency
from emails.models import SentEmail
assert subject
assert body_template
assert to_email or to_user
if to_user:
to_email = to_user.email
to_name = to_user.get_full_name()
if not from_email:
from_name, from_email = split_email_header(POSTMARK_SENDER)
body_context_modified = body_context.copy()
body_context_modified['BASE_URL'] = BASE_URL
unsub_code = simple_pw_generator(num_chars=10)
verif_code = simple_pw_generator(num_chars=10)
body_context_modified['unsub_code'] = unsub_code
body_context_modified['verif_code'] = verif_code
# Generate html body
html_body = render_to_string('emails/'+body_template, body_context_modified)
send_dict = {
'html_body': html_body,
'from_info': cat_email_header(from_name, from_email),
'to_info': cat_email_header(to_name, to_email),
'subject': subject, # may be overwritten below
}
if cc_email:
send_dict['cc_info'] = cat_email_header(cc_name, cc_email)
if replyto_email:
send_dict['replyto_info'] = cat_email_header(replyto_name, replyto_email)
else:
send_dict['replyto_info'] = 'BlockCypher <contact@blockcypher.com>'
if EMAIL_DEV_PREFIX:
send_dict['subject'] += ' [DEV]'
else:
# send_dict['bcc_info'] = ','.join([POSTMARK_SENDER, ])
pass
# Log everything
se = SentEmail.objects.create(
from_email=from_email,
from_name=from_name,
to_email=to_email,
to_name=to_name,
cc_name=cc_name,
cc_email=cc_email,
body_template=body_template,
body_context=body_context,
subject=subject,
unsub_code=unsub_code,
verif_code=verif_code,
auth_user=fkey_objs.get('auth_user', to_user),
address_subscription=fkey_objs.get('address_subscription'),
transaction_event=fkey_objs.get('transaction_event'),
address_forwarding=fkey_objs.get('address_forwarding'),
)
postmark_send(**send_dict)
return se | [
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khalim19/gimp-plugin-export-layers | b37255f2957ad322f4d332689052351cdea6e563 | export_layers/pygimplib/_lib/future/future/backports/http/cookiejar.py | python | CookieJar.__len__ | (self) | return i | Return number of contained cookies. | Return number of contained cookies. | [
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"contained",
"cookies",
"."
] | def __len__(self):
"""Return number of contained cookies."""
i = 0
for cookie in self: i = i + 1
return i | [
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rhiever/reddit-analysis | 0fc309c9091cf2b219c2e664b6cf17b39141e2ef | redditanalysis/__init__.py | python | tokenize | (text) | Return individual tokens from a block of text. | Return individual tokens from a block of text. | [
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] | def tokenize(text):
"""Return individual tokens from a block of text."""
def normalized_tokens(token):
"""Yield lower-case tokens from the given token."""
for sub in TOKEN_RE.findall(token):
if sub:
yield sub.lower()
for token in text.split(): # first split on whitespace
if URL_RE.search(token): # Ignore invalid tokens
continue
for sub_token in normalized_tokens(token):
if sub_token.endswith("'s"): # Fix possessive form
sub_token = sub_token[:-2]
yield sub_token | [
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pypa/pipenv | b21baade71a86ab3ee1429f71fbc14d4f95fb75d | pipenv/patched/notpip/_vendor/requests/cookies.py | python | RequestsCookieJar.copy | (self) | return new_cj | Return a copy of this RequestsCookieJar. | Return a copy of this RequestsCookieJar. | [
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] | def copy(self):
"""Return a copy of this RequestsCookieJar."""
new_cj = RequestsCookieJar()
new_cj.set_policy(self.get_policy())
new_cj.update(self)
return new_cj | [
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dipu-bd/lightnovel-crawler | eca7a71f217ce7a6b0a54d2e2afb349571871880 | sources/en/n/novelcake.py | python | NovelCake.read_novel_info | (self) | Get novel title, autor, cover etc | Get novel title, autor, cover etc | [
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"novel",
"title",
"autor",
"cover",
"etc"
] | def read_novel_info(self):
'''Get novel title, autor, cover etc'''
logger.debug('Visiting %s', self.novel_url)
soup = self.get_soup(self.novel_url)
possible_title = soup.select_one('.post-title h1')
for span in possible_title.select('span'):
span.extract()
# end for
self.novel_title = possible_title.text.strip()
logger.info('Novel title: %s', self.novel_title)
self.novel_cover = self.absolute_url(
soup.select_one('.summary_image a img')['data-src'])
logger.info('Novel cover: %s', self.novel_cover)
self.novel_author = ' '.join([
a.text.strip()
for a in soup.select('.author-content a[href*="series-author"]')
])
logger.info('%s', self.novel_author)
self.novel_id = soup.select_one('#manga-chapters-holder')['data-id']
logger.info('Novel id: %s', self.novel_id)
response = self.submit_form(chapter_list_url, data={
'action': 'manga_get_chapters',
'manga': self.novel_id,
})
soup = self.make_soup(response)
for a in reversed(soup.select(".wp-manga-chapter a")):
chap_id = len(self.chapters) + 1
vol_id = 1 + len(self.chapters) // 100
if chap_id % 100 == 1:
self.volumes.append({"id": vol_id})
# end if
self.chapters.append(
{
"id": chap_id,
"volume": vol_id,
"title": a.text.strip(),
"url": self.absolute_url(a["href"]),
}
) | [
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ducksboard/libsaas | 615981a3336f65be9d51ae95a48aed9ad3bd1c3c | libsaas/services/googlespreadsheets/resource.py | python | SpreadsheetsResource.create | (self, obj) | return request, parsers.parse_xml | Create a new resource.
:var obj: a Python object representing the resource to be created,
usually in the same as returned from `get`. Refer to the upstream
documentation for details. | Create a new resource. | [
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] | def create(self, obj):
"""
Create a new resource.
:var obj: a Python object representing the resource to be created,
usually in the same as returned from `get`. Refer to the upstream
documentation for details.
"""
self.require_collection()
request = http.Request('POST', self.get_url(), self.wrap_object(obj))
return request, parsers.parse_xml | [
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roam-qgis/Roam | 6bfa836a2735f611b7f26de18ae4a4581f7e83ef | ext_libs/cx_Freeze/hooks.py | python | load_Numeric | (finder, module) | the Numeric module optionally loads the dotblas module; ignore the error
if this modules does not exist. | the Numeric module optionally loads the dotblas module; ignore the error
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"""the Numeric module optionally loads the dotblas module; ignore the error
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zhl2008/awd-platform | 0416b31abea29743387b10b3914581fbe8e7da5e | web_flaskbb/lib/python2.7/site-packages/jinja2/utils.py | python | LRUCache.__reversed__ | (self) | return iter(tuple(self._queue)) | Iterate over the values in the cache dict, oldest items
coming first. | Iterate over the values in the cache dict, oldest items
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ucfopen/canvasapi | 3f1a71e23c86a49dbaa6e84f6c0e81c297b86e36 | canvasapi/folder.py | python | Folder.create_folder | (self, name, **kwargs) | return Folder(self._requester, response.json()) | Creates a folder within this folder.
:calls: `POST /api/v1/folders/:folder_id/folders \
<https://canvas.instructure.com/doc/api/files.html#method.folders.create>`_
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] | def create_folder(self, name, **kwargs):
"""
Creates a folder within this folder.
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<https://canvas.instructure.com/doc/api/files.html#method.folders.create>`_
:param name: The name of the folder.
:type name: str
:rtype: :class:`canvasapi.folder.Folder`
"""
response = self._requester.request(
"POST",
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name=name,
_kwargs=combine_kwargs(**kwargs),
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return Folder(self._requester, response.json()) | [
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wummel/patool | 723006abd43d0926581b11df0cd37e46a30525eb | patoolib/programs/rar.py | python | list_rar | (archive, compression, cmd, verbosity, interactive, password=None) | return cmdlist | List a RAR archive. | List a RAR archive. | [
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] | def list_rar (archive, compression, cmd, verbosity, interactive, password=None):
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cmdlist.append('v')
else:
cmdlist.append('l')
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cmdlist.extend(['-p-', '-y'])
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cmdlist.append('-p%s' % password)
cmdlist.extend(['--', archive])
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chribsen/simple-machine-learning-examples | dc94e52a4cebdc8bb959ff88b81ff8cfeca25022 | venv/lib/python2.7/site-packages/pip/_vendor/requests/models.py | python | Response.json | (self, **kwargs) | return complexjson.loads(self.text, **kwargs) | Returns the json-encoded content of a response, if any.
:param \*\*kwargs: Optional arguments that ``json.loads`` takes. | Returns the json-encoded content of a response, if any. | [
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] | def json(self, **kwargs):
"""Returns the json-encoded content of a response, if any.
:param \*\*kwargs: Optional arguments that ``json.loads`` takes.
"""
if not self.encoding and self.content and len(self.content) > 3:
# No encoding set. JSON RFC 4627 section 3 states we should expect
# UTF-8, -16 or -32. Detect which one to use; If the detection or
# decoding fails, fall back to `self.text` (using chardet to make
# a best guess).
encoding = guess_json_utf(self.content)
if encoding is not None:
try:
return complexjson.loads(
self.content.decode(encoding), **kwargs
)
except UnicodeDecodeError:
# Wrong UTF codec detected; usually because it's not UTF-8
# but some other 8-bit codec. This is an RFC violation,
# and the server didn't bother to tell us what codec *was*
# used.
pass
return complexjson.loads(self.text, **kwargs) | [
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phonopy/phonopy | 816586d0ba8177482ecf40e52f20cbdee2260d51 | phonopy/interface/qe.py | python | PwscfIn._set_nat | (self) | [] | def _set_nat(self):
self._tags["nat"] = int(self._values[0]) | [
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] | https://github.com/phonopy/phonopy/blob/816586d0ba8177482ecf40e52f20cbdee2260d51/phonopy/interface/qe.py#L285-L286 | ||||
yt-project/yt | dc7b24f9b266703db4c843e329c6c8644d47b824 | yt/fields/derived_field.py | python | ValidateGridType.__init__ | (self) | This validator ensures that the data handed to the field is an actual
grid patch, not a covering grid of any kind. | This validator ensures that the data handed to the field is an actual
grid patch, not a covering grid of any kind. | [
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] | def __init__(self):
"""
This validator ensures that the data handed to the field is an actual
grid patch, not a covering grid of any kind.
"""
FieldValidator.__init__(self) | [
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] | https://github.com/yt-project/yt/blob/dc7b24f9b266703db4c843e329c6c8644d47b824/yt/fields/derived_field.py#L568-L573 | ||
andresriancho/w3af | cd22e5252243a87aaa6d0ddea47cf58dacfe00a9 | w3af/core/data/parsers/pynarcissus/jsparser.py | python | Variables | (t, x) | return n | [] | def Variables(t, x):
n = Node(t)
while True:
t.mustMatch(IDENTIFIER)
n2 = Node(t)
n2.name = n2.value
if t.match(ASSIGN):
if t.token.assignOp:
raise t.newSyntaxError("Invalid variable initialization")
n2.initializer = Expression(t, x, COMMA)
n2.readOnly = not not (n.type_ == CONST)
n.append(n2)
x.varDecls.append(n2)
if not t.match(COMMA): break
return n | [
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google/clusterfuzz | f358af24f414daa17a3649b143e71ea71871ef59 | src/clusterfuzz/_internal/datastore/data_types.py | python | Testcase._ensure_metadata_is_cached | (self) | Ensure that the metadata for this has been cached. | Ensure that the metadata for this has been cached. | [
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] | def _ensure_metadata_is_cached(self):
"""Ensure that the metadata for this has been cached."""
if hasattr(self, 'metadata_cache'):
return
try:
cache = json_utils.loads(self.additional_metadata)
except (TypeError, ValueError):
cache = {}
setattr(self, 'metadata_cache', cache) | [
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Zulko/easyAI | a5cbd0b600ebbeadc3730df9e7a211d7643cff8b | easyAI/AI/NonRecursiveNegamax.py | python | StateObject.swap_alpha_beta | (self) | [] | def swap_alpha_beta(self):
(self.alpha, self.beta) = (self.beta, self.alpha) | [
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uqfoundation/multiprocess | 028cc73f02655e6451d92e5147d19d8c10aebe50 | py3.8/multiprocess/util.py | python | get_logger | () | return _logger | Returns logger used by multiprocess | Returns logger used by multiprocess | [
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] | def get_logger():
'''
Returns logger used by multiprocess
'''
global _logger
import logging
logging._acquireLock()
try:
if not _logger:
_logger = logging.getLogger(LOGGER_NAME)
_logger.propagate = 0
# XXX multiprocessing should cleanup before logging
if hasattr(atexit, 'unregister'):
atexit.unregister(_exit_function)
atexit.register(_exit_function)
else:
atexit._exithandlers.remove((_exit_function, (), {}))
atexit._exithandlers.append((_exit_function, (), {}))
finally:
logging._releaseLock()
return _logger | [
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Qirky/FoxDot | 76318f9630bede48ff3994146ed644affa27bfa4 | FoxDot/lib/OSC3.py | python | OSCStreamingServer.stop | (self) | Stop the server thread and close the socket. | Stop the server thread and close the socket. | [
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] | def stop(self):
""" Stop the server thread and close the socket. """
self.running = False
self._server_thread.join()
self.server_close() | [
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