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sonyxperiadev/WebGL | 0299b38196f78c6d5f74bcf6fa312a3daee6de60 | Tools/Scripts/webkitpy/common/system/autoinstall.py | python | AutoInstaller._is_downloaded | (self, target_name, url) | return version.strip() == url.strip() | Return whether a package version has been downloaded. | Return whether a package version has been downloaded. | [
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"""Return whether a package version has been downloaded."""
version_path = self._url_downloaded_path(target_name)
_log.debug('Checking %s URL downloaded...' % target_name)
_log.debug(' "%s"' % version_path)
if not os.path.exists(version_path):
# Then no package version has been downloaded.
_log.debug("No URL file found.")
return False
with codecs.open(version_path, "r", "utf-8") as file:
version = file.read()
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windystrife/UnrealEngine_NVIDIAGameWorks | b50e6338a7c5b26374d66306ebc7807541ff815e | Engine/Extras/ThirdPartyNotUE/emsdk/Win64/python/2.7.5.3_64bit/Lib/site-packages/pip/vendor/distlib/_backport/tarfile.py | python | TarFile.addfile | (self, tarinfo, fileobj=None) | Add the TarInfo object `tarinfo' to the archive. If `fileobj' is
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/scipy/py2/scipy/signal/_peak_finding.py | python | peak_prominences | (x, peaks, wlen=None) | return _peak_prominences(x, peaks, wlen) | Calculate the prominence of each peak in a signal.
The prominence of a peak measures how much a peak stands out from the
surrounding baseline of the signal and is defined as the vertical distance
between the peak and its lowest contour line.
Parameters
----------
x : sequence
A signal with peaks.
peaks : sequence
Indices of peaks in `x`.
wlen : int, optional
A window length in samples that optionally limits the evaluated area for
each peak to a subset of `x`. The peak is always placed in the middle of
the window therefore the given length is rounded up to the next odd
integer. This parameter can speed up the calculation (see Notes).
Returns
-------
prominences : ndarray
The calculated prominences for each peak in `peaks`.
left_bases, right_bases : ndarray
The peaks' bases as indices in `x` to the left and right of each peak.
The higher base of each pair is a peak's lowest contour line.
Raises
------
ValueError
If a value in `peaks` is an invalid index for `x`.
Warns
-----
PeakPropertyWarning
For indices in `peaks` that don't point to valid local maxima in `x`
the returned prominence will be 0 and this warning is raised. This
also happens if `wlen` is smaller than the plateau size of a peak.
Warnings
--------
This function may return unexpected results for data containing NaNs. To
avoid this, NaNs should either be removed or replaced.
See Also
--------
find_peaks
Find peaks inside a signal based on peak properties.
peak_widths
Calculate the width of peaks.
Notes
-----
Strategy to compute a peak's prominence:
1. Extend a horizontal line from the current peak to the left and right
until the line either reaches the window border (see `wlen`) or
intersects the signal again at the slope of a higher peak. An
intersection with a peak of the same height is ignored.
2. On each side find the minimal signal value within the interval defined
above. These points are the peak's bases.
3. The higher one of the two bases marks the peak's lowest contour line. The
prominence can then be calculated as the vertical difference between the
peaks height itself and its lowest contour line.
Searching for the peak's bases can be slow for large `x` with periodic
behavior because large chunks or even the full signal need to be evaluated
for the first algorithmic step. This evaluation area can be limited with the
parameter `wlen` which restricts the algorithm to a window around the
current peak and can shorten the calculation time if the window length is
short in relation to `x`.
However this may stop the algorithm from finding the true global contour
line if the peak's true bases are outside this window. Instead a higher
contour line is found within the restricted window leading to a smaller
calculated prominence. In practice this is only relevant for the highest set
of peaks in `x`. This behavior may even be used intentionally to calculate
"local" prominences.
.. versionadded:: 1.1.0
References
----------
.. [1] Wikipedia Article for Topographic Prominence:
https://en.wikipedia.org/wiki/Topographic_prominence
Examples
--------
>>> from scipy.signal import find_peaks, peak_prominences
>>> import matplotlib.pyplot as plt
Create a test signal with two overlayed harmonics
>>> x = np.linspace(0, 6 * np.pi, 1000)
>>> x = np.sin(x) + 0.6 * np.sin(2.6 * x)
Find all peaks and calculate prominences
>>> peaks, _ = find_peaks(x)
>>> prominences = peak_prominences(x, peaks)[0]
>>> prominences
array([1.24159486, 0.47840168, 0.28470524, 3.10716793, 0.284603 ,
0.47822491, 2.48340261, 0.47822491])
Calculate the height of each peak's contour line and plot the results
>>> contour_heights = x[peaks] - prominences
>>> plt.plot(x)
>>> plt.plot(peaks, x[peaks], "x")
>>> plt.vlines(x=peaks, ymin=contour_heights, ymax=x[peaks])
>>> plt.show()
Let's evaluate a second example that demonstrates several edge cases for
one peak at index 5.
>>> x = np.array([0, 1, 0, 3, 1, 3, 0, 4, 0])
>>> peaks = np.array([5])
>>> plt.plot(x)
>>> plt.plot(peaks, x[peaks], "x")
>>> plt.show()
>>> peak_prominences(x, peaks) # -> (prominences, left_bases, right_bases)
(array([3.]), array([2]), array([6]))
Note how the peak at index 3 of the same height is not considered as a
border while searching for the left base. Instead two minima at 0 and 2
are found in which case the one closer to the evaluated peak is always
chosen. On the right side however the base must be placed at 6 because the
higher peak represents the right border to the evaluated area.
>>> peak_prominences(x, peaks, wlen=3.1)
(array([2.]), array([4]), array([6]))
Here we restricted the algorithm to a window from 3 to 7 (the length is 5
samples because `wlen` was rounded up to the next odd integer). Thus the
only two candidates in the evaluated area are the two neighbouring samples
and a smaller prominence is calculated. | Calculate the prominence of each peak in a signal. | [
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] | def peak_prominences(x, peaks, wlen=None):
"""
Calculate the prominence of each peak in a signal.
The prominence of a peak measures how much a peak stands out from the
surrounding baseline of the signal and is defined as the vertical distance
between the peak and its lowest contour line.
Parameters
----------
x : sequence
A signal with peaks.
peaks : sequence
Indices of peaks in `x`.
wlen : int, optional
A window length in samples that optionally limits the evaluated area for
each peak to a subset of `x`. The peak is always placed in the middle of
the window therefore the given length is rounded up to the next odd
integer. This parameter can speed up the calculation (see Notes).
Returns
-------
prominences : ndarray
The calculated prominences for each peak in `peaks`.
left_bases, right_bases : ndarray
The peaks' bases as indices in `x` to the left and right of each peak.
The higher base of each pair is a peak's lowest contour line.
Raises
------
ValueError
If a value in `peaks` is an invalid index for `x`.
Warns
-----
PeakPropertyWarning
For indices in `peaks` that don't point to valid local maxima in `x`
the returned prominence will be 0 and this warning is raised. This
also happens if `wlen` is smaller than the plateau size of a peak.
Warnings
--------
This function may return unexpected results for data containing NaNs. To
avoid this, NaNs should either be removed or replaced.
See Also
--------
find_peaks
Find peaks inside a signal based on peak properties.
peak_widths
Calculate the width of peaks.
Notes
-----
Strategy to compute a peak's prominence:
1. Extend a horizontal line from the current peak to the left and right
until the line either reaches the window border (see `wlen`) or
intersects the signal again at the slope of a higher peak. An
intersection with a peak of the same height is ignored.
2. On each side find the minimal signal value within the interval defined
above. These points are the peak's bases.
3. The higher one of the two bases marks the peak's lowest contour line. The
prominence can then be calculated as the vertical difference between the
peaks height itself and its lowest contour line.
Searching for the peak's bases can be slow for large `x` with periodic
behavior because large chunks or even the full signal need to be evaluated
for the first algorithmic step. This evaluation area can be limited with the
parameter `wlen` which restricts the algorithm to a window around the
current peak and can shorten the calculation time if the window length is
short in relation to `x`.
However this may stop the algorithm from finding the true global contour
line if the peak's true bases are outside this window. Instead a higher
contour line is found within the restricted window leading to a smaller
calculated prominence. In practice this is only relevant for the highest set
of peaks in `x`. This behavior may even be used intentionally to calculate
"local" prominences.
.. versionadded:: 1.1.0
References
----------
.. [1] Wikipedia Article for Topographic Prominence:
https://en.wikipedia.org/wiki/Topographic_prominence
Examples
--------
>>> from scipy.signal import find_peaks, peak_prominences
>>> import matplotlib.pyplot as plt
Create a test signal with two overlayed harmonics
>>> x = np.linspace(0, 6 * np.pi, 1000)
>>> x = np.sin(x) + 0.6 * np.sin(2.6 * x)
Find all peaks and calculate prominences
>>> peaks, _ = find_peaks(x)
>>> prominences = peak_prominences(x, peaks)[0]
>>> prominences
array([1.24159486, 0.47840168, 0.28470524, 3.10716793, 0.284603 ,
0.47822491, 2.48340261, 0.47822491])
Calculate the height of each peak's contour line and plot the results
>>> contour_heights = x[peaks] - prominences
>>> plt.plot(x)
>>> plt.plot(peaks, x[peaks], "x")
>>> plt.vlines(x=peaks, ymin=contour_heights, ymax=x[peaks])
>>> plt.show()
Let's evaluate a second example that demonstrates several edge cases for
one peak at index 5.
>>> x = np.array([0, 1, 0, 3, 1, 3, 0, 4, 0])
>>> peaks = np.array([5])
>>> plt.plot(x)
>>> plt.plot(peaks, x[peaks], "x")
>>> plt.show()
>>> peak_prominences(x, peaks) # -> (prominences, left_bases, right_bases)
(array([3.]), array([2]), array([6]))
Note how the peak at index 3 of the same height is not considered as a
border while searching for the left base. Instead two minima at 0 and 2
are found in which case the one closer to the evaluated peak is always
chosen. On the right side however the base must be placed at 6 because the
higher peak represents the right border to the evaluated area.
>>> peak_prominences(x, peaks, wlen=3.1)
(array([2.]), array([4]), array([6]))
Here we restricted the algorithm to a window from 3 to 7 (the length is 5
samples because `wlen` was rounded up to the next odd integer). Thus the
only two candidates in the evaluated area are the two neighbouring samples
and a smaller prominence is calculated.
"""
x = _arg_x_as_expected(x)
peaks = _arg_peaks_as_expected(peaks)
wlen = _arg_wlen_as_expected(wlen)
return _peak_prominences(x, peaks, wlen) | [
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panda3d/panda3d | 833ad89ebad58395d0af0b7ec08538e5e4308265 | direct/src/showbase/VFSImporter.py | python | VFSLoader._compile | (self, filename, source) | return code | Compiles the Python source code to a code object and
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pytorch/pytorch | 7176c92687d3cc847cc046bf002269c6949a21c2 | torch/ao/quantization/fx/quantization_patterns.py | python | QuantizeHandler.should_insert_observer_for_output | (
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plumonito/dtslam | 5994bb9cf7a11981b830370db206bceb654c085d | 3rdparty/opencv-git/3rdparty/jinja2/compiler.py | python | CodeGenerator.macro_body | (self, node, frame, children=None) | return frame | Dump the function def of a macro or call block. | Dump the function def of a macro or call block. | [
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# real solution would be "nonlocal" all the identifiers that are
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miyosuda/TensorFlowAndroidMNIST | 7b5a4603d2780a8a2834575706e9001977524007 | jni-build/jni/include/tensorflow/models/rnn/ptb/reader.py | python | ptb_iterator | (raw_data, batch_size, num_steps) | Iterate on the raw PTB data.
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raw_data: one of the raw data outputs from ptb_raw_data.
batch_size: int, the batch size.
num_steps: int, the number of unrolls.
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Args:
raw_data: one of the raw data outputs from ptb_raw_data.
batch_size: int, the batch size.
num_steps: int, the number of unrolls.
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ValueError: if batch_size or num_steps are too high.
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data_len = len(raw_data)
batch_len = data_len // batch_size
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y = data[:, i*num_steps+1:(i+1)*num_steps+1]
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nyuwireless-unipd/ns3-mmwave | 4ff9e87e8079764e04cbeccd8e85bff15ae16fb3 | utils/check-style.py | python | PatchChunkLine.write | (self, f) | ! Write to file
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@param self The current class
@param f file
@return exception if invalid type
"""
if self.__type == self.SRC:
f.write('-%s\n' % self.__line)
elif self.__type == self.DST:
f.write('+%s\n' % self.__line)
elif self.__type == self.BOTH:
f.write(' %s\n' % self.__line)
else:
raise Exception('invalid patch') | [
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wlanjie/AndroidFFmpeg | 7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf | tools/fdk-aac-build/armeabi-v7a/toolchain/lib/python2.7/inspect.py | python | getabsfile | (object, _filename=None) | return os.path.normcase(os.path.abspath(_filename)) | Return an absolute path to the source or compiled file for an object.
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if _filename is None:
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bigtreetech/BIGTREETECH-SKR-V1.3 | b238aa402753e81d551b7d34a181a262a138ae9e | BTT SKR V1.4/Firmware/Marlin-bugfix-2.0.x-SKR-V1.4/Marlin/src/lcd/extui/lib/ftdi_eve_touch_ui/ftdi_eve_lib/extras/svg2cpp.py | python | Parser.process_svg_path_data | (self, id, d) | Breaks up the "d" attribute into individual commands
and calls "process_svg_path_data_cmd" for each | Breaks up the "d" attribute into individual commands
and calls "process_svg_path_data_cmd" for each | [
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"""Breaks up the "d" attribute into individual commands
and calls "process_svg_path_data_cmd" for each"""
self.d = d
while (self.d):
if self.eat_token('\s+'):
pass # Just eat the spaces
elif self.eat_token('([LMHVZlmhvz])'):
cmd = self.m.group(1)
# The following commands take no arguments
if cmd == "Z" or cmd == "z":
self.process_svg_path_data_cmd(id, cmd, 0, 0)
elif self.eat_token('([CScsQqTtAa])'):
print("Unsupported path data command:", self.m.group(1), "in path", id, "\n", file=sys.stderr)
quit()
elif self.eat_token('([ ,]*[-0-9e.]+)+'):
# Process list of coordinates following command
coords = re.split('[ ,]+', self.m.group(0))
# The following commands take two arguments
if cmd == "L" or cmd == "l":
while coords:
self.process_svg_path_data_cmd(id, cmd, float(coords.pop(0)), float(coords.pop(0)))
elif cmd == "M":
while coords:
self.process_svg_path_data_cmd(id, cmd, float(coords.pop(0)), float(coords.pop(0)))
# If a MOVETO has multiple points, the subsequent ones are assumed to be LINETO
cmd = "L"
elif cmd == "m":
while coords:
self.process_svg_path_data_cmd(id, cmd, float(coords.pop(0)), float(coords.pop(0)))
# If a MOVETO has multiple points, the subsequent ones are assumed to be LINETO
cmd = "l"
# Assume all other commands are single argument
else:
while coords:
self.process_svg_path_data_cmd(id, cmd, float(coords.pop(0)), 0)
else:
print("Syntax error:", d, "in path", id, "\n", file=sys.stderr)
quit() | [
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BlzFans/wke | b0fa21158312e40c5fbd84682d643022b6c34a93 | cygwin/lib/python2.6/email/feedparser.py | python | FeedParser.__init__ | (self, _factory=message.Message) | _factory is called with no arguments to create a new message obj | _factory is called with no arguments to create a new message obj | [
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self._factory = _factory
self._input = BufferedSubFile()
self._msgstack = []
self._parse = self._parsegen().next
self._cur = None
self._last = None
self._headersonly = False | [
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thpatch/thcrap | 9a0ebc52ebc775d93a44ddfe19d1bed0c512958f | scripts/repo_update.py | python | patch_files_walk | (repo_top, path, ignored) | Yields string for every valid patch file in [path] whose file name does
not match the wildmatch patterns in [ignored], treated relative to
[repo_top]. If another `thcrap_ignore.txt` is found along the directory
hierarchy, its contents are added to a copy of [ignored], which is then
used for this directory and its subdirectories. | Yields string for every valid patch file in [path] whose file name does
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[repo_top]. If another `thcrap_ignore.txt` is found along the directory
hierarchy, its contents are added to a copy of [ignored], which is then
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not match the wildmatch patterns in [ignored], treated relative to
[repo_top]. If another `thcrap_ignore.txt` is found along the directory
hierarchy, its contents are added to a copy of [ignored], which is then
used for this directory and its subdirectories."""
local_ignore = thcrap_ignore_get(path)
if len(local_ignore) >= 1:
ignored = set(ignored).union(local_ignore)
spec = PathSpec.from_lines('gitwildmatch', ignored)
for i in os.scandir(path):
if spec.match_file(os.path.relpath(i.path, repo_top)) == False:
if i.is_dir():
yield from patch_files_walk(repo_top, i.path, ignored)
else:
yield i.path | [
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Xilinx/Vitis-AI | fc74d404563d9951b57245443c73bef389f3657f | tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/python/client/session.py | python | SessionInterface.partial_run | (self, handle, fetches, feed_dict=None) | Continues the execution with additional feeds and fetches. | Continues the execution with additional feeds and fetches. | [
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] | def partial_run(self, handle, fetches, feed_dict=None):
"""Continues the execution with additional feeds and fetches."""
raise NotImplementedError('partial_run') | [
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tensorflow/tensorflow | 419e3a6b650ea4bd1b0cba23c4348f8a69f3272e | tensorflow/python/framework/config.py | python | get_logical_device_configuration | (device) | return context.context().get_logical_device_configuration(device) | Get the virtual device configuration for a `tf.config.PhysicalDevice`.
Returns the list of `tf.config.LogicalDeviceConfiguration`
objects previously configured by a call to
`tf.config.set_logical_device_configuration`.
For example:
>>> physical_devices = tf.config.list_physical_devices('CPU')
>>> assert len(physical_devices) == 1, "No CPUs found"
>>> configs = tf.config.get_logical_device_configuration(
... physical_devices[0])
>>> try:
... assert configs is None
... tf.config.set_logical_device_configuration(
... physical_devices[0],
... [tf.config.LogicalDeviceConfiguration(),
... tf.config.LogicalDeviceConfiguration()])
... configs = tf.config.get_logical_device_configuration(
... physical_devices[0])
... assert len(configs) == 2
... except:
... # Cannot modify virtual devices once initialized.
... pass
Args:
device: `PhysicalDevice` to query
Returns:
List of `tf.config.LogicalDeviceConfiguration` objects or
`None` if no virtual device configuration has been set for this physical
device. | Get the virtual device configuration for a `tf.config.PhysicalDevice`. | [
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] | def get_logical_device_configuration(device):
"""Get the virtual device configuration for a `tf.config.PhysicalDevice`.
Returns the list of `tf.config.LogicalDeviceConfiguration`
objects previously configured by a call to
`tf.config.set_logical_device_configuration`.
For example:
>>> physical_devices = tf.config.list_physical_devices('CPU')
>>> assert len(physical_devices) == 1, "No CPUs found"
>>> configs = tf.config.get_logical_device_configuration(
... physical_devices[0])
>>> try:
... assert configs is None
... tf.config.set_logical_device_configuration(
... physical_devices[0],
... [tf.config.LogicalDeviceConfiguration(),
... tf.config.LogicalDeviceConfiguration()])
... configs = tf.config.get_logical_device_configuration(
... physical_devices[0])
... assert len(configs) == 2
... except:
... # Cannot modify virtual devices once initialized.
... pass
Args:
device: `PhysicalDevice` to query
Returns:
List of `tf.config.LogicalDeviceConfiguration` objects or
`None` if no virtual device configuration has been set for this physical
device.
"""
return context.context().get_logical_device_configuration(device) | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_cocoa/richtext.py | python | RichTextParagraph.MoveToList | (*args, **kwargs) | return _richtext.RichTextParagraph_MoveToList(*args, **kwargs) | MoveToList(self, RichTextObject obj, wxList list) | MoveToList(self, RichTextObject obj, wxList list) | [
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"""MoveToList(self, RichTextObject obj, wxList list)"""
return _richtext.RichTextParagraph_MoveToList(*args, **kwargs) | [
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casadi/casadi | 8d0f80a4d0fe2054384bfb9748f7a0f6bae540ff | misc/cpplint.py | python | _NestingState.CheckCompletedBlocks | (self, filename, error) | Checks that all classes and namespaces have been completely parsed.
Call this when all lines in a file have been processed.
Args:
filename: The name of the current file.
error: The function to call with any errors found. | Checks that all classes and namespaces have been completely parsed. | [
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] | def CheckCompletedBlocks(self, filename, error):
"""Checks that all classes and namespaces have been completely parsed.
Call this when all lines in a file have been processed.
Args:
filename: The name of the current file.
error: The function to call with any errors found.
"""
# Note: This test can result in false positives if #ifdef constructs
# get in the way of brace matching. See the testBuildClass test in
# cpplint_unittest.py for an example of this.
for obj in self.stack:
if isinstance(obj, _ClassInfo):
error(filename, obj.starting_linenum, 'build/class', 5,
'Failed to find complete declaration of class %s' %
obj.name)
elif isinstance(obj, _NamespaceInfo):
error(filename, obj.starting_linenum, 'build/namespaces', 5,
'Failed to find complete declaration of namespace %s' %
obj.name) | [
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nsnam/ns-3-dev-git | efdb2e21f45c0a87a60b47c547b68fa140a7b686 | utils/grid.py | python | GraphicRenderer.get_data_rectangle | (self) | return(x_start, y_start, self.__width - x_start, self.__data.get_height()) | ! Get Data Rectangle
@param self this object
@return rectangle | ! Get Data Rectangle | [
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"""! Get Data Rectangle
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y_start = self.__top_legend.get_height()
x_start = self.__data.get_data_x_start()
return(x_start, y_start, self.__width - x_start, self.__data.get_height()) | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_carbon/_core.py | python | BookCtrlBase.HitTest | (*args, **kwargs) | return _core_.BookCtrlBase_HitTest(*args, **kwargs) | HitTest(Point pt) -> (tab, where)
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"""
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Returns the page/tab which is hit, and flags indicating where using
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"""
return _core_.BookCtrlBase_HitTest(*args, **kwargs) | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemDefectReporter/v1/AWS/common-code/Lib/urllib3/util/timeout.py | python | Timeout.clone | (self) | return Timeout(connect=self._connect, read=self._read,
total=self.total) | Create a copy of the timeout object
Timeout properties are stored per-pool but each request needs a fresh
Timeout object to ensure each one has its own start/stop configured.
:return: a copy of the timeout object
:rtype: :class:`Timeout` | Create a copy of the timeout object | [
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""" Create a copy of the timeout object
Timeout properties are stored per-pool but each request needs a fresh
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:return: a copy of the timeout object
:rtype: :class:`Timeout`
"""
# We can't use copy.deepcopy because that will also create a new object
# for _GLOBAL_DEFAULT_TIMEOUT, which socket.py uses as a sentinel to
# detect the user default.
return Timeout(connect=self._connect, read=self._read,
total=self.total) | [
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netket/netket | 0d534e54ecbf25b677ea72af6b85947979420652 | netket/optimizer/qgt/qgt_jacobian_dense_logic.py | python | stack_jacobian_tuple | (ok_re_im) | return res | stack the real and imaginary parts of ΔOⱼₖ along a new axis.
First all the real part then the imaginary part.
Re[S] = Re[(ΔOᵣ + i ΔOᵢ)ᴴ(ΔOᵣ + i ΔOᵢ)] = ΔOᵣᵀ ΔOᵣ + ΔOᵢᵀ ΔOᵢ = [ΔOᵣ ΔOᵢ]ᵀ [ΔOᵣ ΔOᵢ]
Args:
ok_re_im : a tuple (ΔOᵣ, ΔOᵢ) of two PyTrees representing the real and imag part of ΔOⱼₖ | stack the real and imaginary parts of ΔOⱼₖ along a new axis.
First all the real part then the imaginary part. | [
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"""
stack the real and imaginary parts of ΔOⱼₖ along a new axis.
First all the real part then the imaginary part.
Re[S] = Re[(ΔOᵣ + i ΔOᵢ)ᴴ(ΔOᵣ + i ΔOᵢ)] = ΔOᵣᵀ ΔOᵣ + ΔOᵢᵀ ΔOᵢ = [ΔOᵣ ΔOᵢ]ᵀ [ΔOᵣ ΔOᵢ]
Args:
ok_re_im : a tuple (ΔOᵣ, ΔOᵢ) of two PyTrees representing the real and imag part of ΔOⱼₖ
"""
re, im = ok_re_im
re_dense = ravel(re)
im_dense = ravel(im)
res = jnp.stack([re_dense, im_dense], axis=0)
return res | [
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"]... | https://github.com/netket/netket/blob/0d534e54ecbf25b677ea72af6b85947979420652/netket/optimizer/qgt/qgt_jacobian_dense_logic.py#L157-L173 | |
hanpfei/chromium-net | 392cc1fa3a8f92f42e4071ab6e674d8e0482f83f | third_party/catapult/perf_insights/third_party/cloudstorage/storage_api.py | python | ReadBuffer._get_segment | (self, start, request_size, check_response=True) | Get a segment of the file from Google Storage.
Args:
start: start offset of the segment. Inclusive. Have to be within the
range of the file.
request_size: number of bytes to request. Have to be small enough
for a single urlfetch request. May go over the logical range of the
file.
check_response: True to check the validity of GCS response automatically
before the future returns. False otherwise. See Yields section.
Yields:
If check_response is True, the segment [start, start + request_size)
of the file.
Otherwise, a tuple. The first element is the unverified file segment.
The second element is a closure that checks response. Caller should
first invoke the closure before consuing the file segment.
Raises:
ValueError: if the file has changed while reading. | Get a segment of the file from Google Storage. | [
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] | def _get_segment(self, start, request_size, check_response=True):
"""Get a segment of the file from Google Storage.
Args:
start: start offset of the segment. Inclusive. Have to be within the
range of the file.
request_size: number of bytes to request. Have to be small enough
for a single urlfetch request. May go over the logical range of the
file.
check_response: True to check the validity of GCS response automatically
before the future returns. False otherwise. See Yields section.
Yields:
If check_response is True, the segment [start, start + request_size)
of the file.
Otherwise, a tuple. The first element is the unverified file segment.
The second element is a closure that checks response. Caller should
first invoke the closure before consuing the file segment.
Raises:
ValueError: if the file has changed while reading.
"""
end = start + request_size - 1
content_range = '%d-%d' % (start, end)
headers = {'Range': 'bytes=' + content_range}
status, resp_headers, content = yield self._api.get_object_async(
self._path, headers=headers)
def _checker():
errors.check_status(status, [200, 206], self._path, headers,
resp_headers, body=content)
self._check_etag(resp_headers.get('etag'))
if check_response:
_checker()
raise ndb.Return(content)
raise ndb.Return(content, _checker) | [
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commaai/openpilot | 4416c21b1e738ab7d04147c5ae52b5135e0cdb40 | common/logging_extra.py | python | SwagLogger.findCaller | (self, stack_info=False, stacklevel=1) | return rv | Find the stack frame of the caller so that we can note the source
file name, line number and function name. | Find the stack frame of the caller so that we can note the source
file name, line number and function name. | [
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] | def findCaller(self, stack_info=False, stacklevel=1):
"""
Find the stack frame of the caller so that we can note the source
file name, line number and function name.
"""
f = sys._getframe(3)
#On some versions of IronPython, currentframe() returns None if
#IronPython isn't run with -X:Frames.
if f is not None:
f = f.f_back
orig_f = f
while f and stacklevel > 1:
f = f.f_back
stacklevel -= 1
if not f:
f = orig_f
rv = "(unknown file)", 0, "(unknown function)", None
while hasattr(f, "f_code"):
co = f.f_code
filename = os.path.normcase(co.co_filename)
# TODO: is this pylint exception correct?
if filename == _srcfile: # pylint: disable=comparison-with-callable
f = f.f_back
continue
sinfo = None
if stack_info:
sio = io.StringIO()
sio.write('Stack (most recent call last):\n')
traceback.print_stack(f, file=sio)
sinfo = sio.getvalue()
if sinfo[-1] == '\n':
sinfo = sinfo[:-1]
sio.close()
rv = (co.co_filename, f.f_lineno, co.co_name, sinfo)
break
return rv | [
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xhzdeng/crpn | a5aef0f80dbe486103123f740c634fb01e6cc9a1 | lib/transform/torch_image_transform_layer.py | python | TorchImageTransformLayer.reshape | (self, bottom, top) | Reshaping happens during the call to forward. | Reshaping happens during the call to forward. | [
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"""Reshaping happens during the call to forward."""
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | wx/lib/agw/aui/auibook.py | python | CommandNotebookEvent.SetDispatched | (self, b) | Sets the event as dispatched (used for automatic :class:`AuiNotebook` ).
:param `b`: whether the event was dispatched or not. | Sets the event as dispatched (used for automatic :class:`AuiNotebook` ). | [
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] | def SetDispatched(self, b):
"""
Sets the event as dispatched (used for automatic :class:`AuiNotebook` ).
:param `b`: whether the event was dispatched or not.
"""
self.dispatched = b | [
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qgis/QGIS | 15a77662d4bb712184f6aa60d0bd663010a76a75 | python/plugins/processing/gui/wrappers.py | python | EnumWidgetWrapper.__init__ | (self, *args, **kwargs) | .. deprecated:: 3.4
Do not use, will be removed in QGIS 4.0 | .. deprecated:: 3.4
Do not use, will be removed in QGIS 4.0 | [
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] | def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
"""
.. deprecated:: 3.4
Do not use, will be removed in QGIS 4.0
"""
from warnings import warn
warn("EnumWidgetWrapper is deprecated and will be removed in QGIS 4.0", DeprecationWarning) | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/site-packages/pip/_vendor/distlib/util.py | python | parse_name_and_version | (p) | return d['name'].strip().lower(), d['ver'] | A utility method used to get name and version from a string.
From e.g. a Provides-Dist value.
:param p: A value in a form 'foo (1.0)'
:return: The name and version as a tuple. | A utility method used to get name and version from a string. | [
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] | def parse_name_and_version(p):
"""
A utility method used to get name and version from a string.
From e.g. a Provides-Dist value.
:param p: A value in a form 'foo (1.0)'
:return: The name and version as a tuple.
"""
m = NAME_VERSION_RE.match(p)
if not m:
raise DistlibException('Ill-formed name/version string: \'%s\'' % p)
d = m.groupdict()
return d['name'].strip().lower(), d['ver'] | [
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CaoWGG/TensorRT-CenterNet | f949252e37b51e60f873808f46d3683f15735e79 | onnx-tensorrt/third_party/onnx/third_party/pybind11/tools/clang/cindex.py | python | Cursor.enum_type | (self) | return self._enum_type | Return the integer type of an enum declaration.
Returns a Type corresponding to an integer. If the cursor is not for an
enum, this raises. | Return the integer type of an enum declaration. | [
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] | def enum_type(self):
"""Return the integer type of an enum declaration.
Returns a Type corresponding to an integer. If the cursor is not for an
enum, this raises.
"""
if not hasattr(self, '_enum_type'):
assert self.kind == CursorKind.ENUM_DECL
self._enum_type = conf.lib.clang_getEnumDeclIntegerType(self)
return self._enum_type | [
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bigartm/bigartm | 47e37f982de87aa67bfd475ff1f39da696b181b3 | 3rdparty/protobuf-3.0.0/python/mox.py | python | MockMethod._CheckAndCreateNewGroup | (self, group_name, group_class) | return self | Checks if the last method (a possible group) is an instance of our
group_class. Adds the current method to this group or creates a new one.
Args:
group_name: the name of the group.
group_class: the class used to create instance of this new group | Checks if the last method (a possible group) is an instance of our
group_class. Adds the current method to this group or creates a new one. | [
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] | def _CheckAndCreateNewGroup(self, group_name, group_class):
"""Checks if the last method (a possible group) is an instance of our
group_class. Adds the current method to this group or creates a new one.
Args:
group_name: the name of the group.
group_class: the class used to create instance of this new group
"""
group = self.GetPossibleGroup()
# If this is a group, and it is the correct group, add the method.
if isinstance(group, group_class) and group.group_name() == group_name:
group.AddMethod(self)
return self
# Create a new group and add the method.
new_group = group_class(group_name)
new_group.AddMethod(self)
self._call_queue.append(new_group)
return self | [
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Samsung/veles | 95ed733c2e49bc011ad98ccf2416ecec23fbf352 | veles/external/pydev/reload.py | python | Reload._update | (self, namespace, name, oldobj, newobj, is_class_namespace=False) | Update oldobj, if possible in place, with newobj.
If oldobj is immutable, this simply returns newobj.
Args:
oldobj: the object to be updated
newobj: the object used as the source for the update | Update oldobj, if possible in place, with newobj. | [
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] | def _update(self, namespace, name, oldobj, newobj, is_class_namespace=False):
"""Update oldobj, if possible in place, with newobj.
If oldobj is immutable, this simply returns newobj.
Args:
oldobj: the object to be updated
newobj: the object used as the source for the update
"""
try:
notify_info2('Updating: ', oldobj)
if oldobj is newobj:
# Probably something imported
return
if type(oldobj) is not type(newobj):
# Cop-out: if the type changed, give up
notify_error('Type of: %s changed... Skipping.' % (oldobj,))
return
if isinstance(newobj, types.FunctionType):
self._update_function(oldobj, newobj)
return
if isinstance(newobj, types.MethodType):
self._update_method(oldobj, newobj)
return
if isinstance(newobj, classmethod):
self._update_classmethod(oldobj, newobj)
return
if isinstance(newobj, staticmethod):
self._update_staticmethod(oldobj, newobj)
return
if hasattr(types, 'ClassType'):
classtype = (types.ClassType, type) #object is not instance of types.ClassType.
else:
classtype = type
if isinstance(newobj, classtype):
self._update_class(oldobj, newobj)
return
# New: dealing with metaclasses.
if hasattr(newobj, '__metaclass__') and hasattr(newobj, '__class__') and newobj.__metaclass__ == newobj.__class__:
self._update_class(oldobj, newobj)
return
if namespace is not None:
if oldobj != newobj and str(oldobj) != str(newobj) and repr(oldobj) != repr(newobj):
xreload_old_new = None
if is_class_namespace:
xreload_old_new = getattr(namespace, '__xreload_old_new__', None)
if xreload_old_new is not None:
self.found_change = True
xreload_old_new(name, oldobj, newobj)
elif '__xreload_old_new__' in namespace:
xreload_old_new = namespace['__xreload_old_new__']
xreload_old_new(namespace, name, oldobj, newobj)
self.found_change = True
# Too much information to the user...
# else:
# notify_info0('%s NOT updated. Create __xreload_old_new__(name, old, new) for custom reload' % (name,))
except:
notify_error('Exception found when updating %s. Proceeding for other items.' % (name,))
traceback.print_exc() | [
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miyosuda/TensorFlowAndroidMNIST | 7b5a4603d2780a8a2834575706e9001977524007 | jni-build/jni/include/tensorflow/python/framework/ops.py | python | Tensor.consumers | (self) | return self._consumers | Returns a list of `Operation`s that consume this tensor.
Returns:
A list of `Operation`s. | Returns a list of `Operation`s that consume this tensor. | [
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] | def consumers(self):
"""Returns a list of `Operation`s that consume this tensor.
Returns:
A list of `Operation`s.
"""
return self._consumers | [
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trilinos/Trilinos | 6168be6dd51e35e1cd681e9c4b24433e709df140 | packages/seacas/libraries/ioss/src/visualization/catalyst/phactori/PhactoriDriver.py | python | FigureBlockIndicesFromBlockListRecurse1 | (includeIndexList, includeBlockList,
inCsdata, inMetaData, ioFlatIndexCounter, inForceSetting) | recursively go through multiblock dataset to determine flat indices\n of blocks to be included; we are assuming only leaf blocks are\n actually named | recursively go through multiblock dataset to determine flat indices\n of blocks to be included; we are assuming only leaf blocks are\n actually named | [
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] | def FigureBlockIndicesFromBlockListRecurse1(includeIndexList, includeBlockList,
inCsdata, inMetaData, ioFlatIndexCounter, inForceSetting):
"recursively go through multiblock dataset to determine flat indices\n of blocks to be included; we are assuming only leaf blocks are\n actually named"
icsdClassname = inCsdata.GetClassName()
if PhactoriDbg(100):
if inMetaData == None:
thisBlockName = None
else:
thisBlockName = inMetaData.Get(vtk.vtkCompositeDataSet.NAME())
myDebugPrint3("FigureBlockIndicesFromBlockListRecurse1 " + \
str(thisBlockName) + " index: " + str(int(ioFlatIndexCounter[0])) + \
" inForceSetting: " + str(inForceSetting) + " classname: " + \
str(icsdClassname) + "\n")
ioFlatIndexCounter[0] += 1
if icsdClassname == "vtkMultiBlockDataSet":
thisIsLeaf = False
nonLeafType = 0
elif icsdClassname == "vtkExodusIIMultiBlockDataSet":
thisIsLeaf = False
nonLeafType = 1
elif icsdClassname == "vtkMultiPieceDataSet":
thisIsLeaf = False
nonLeafType = 2
elif icsdClassname == "vtkPartitionedDataSet":
thisIsLeaf = False
nonLeafType = 3
else:
thisIsLeaf = True
nonLeafType = -1
if not thisIsLeaf:
if inForceSetting == 1:
includeIndexList.append(int(ioFlatIndexCounter[0]) - 1)
includeOrExcludeAllSubBlocks = 1
if PhactoriDbg(100):
myDebugPrint3("this non-leaf block added inForceSetting == 1\n")
elif inForceSetting == -1:
includeOrExcludeAllSubBlocks = -1
if PhactoriDbg(100):
myDebugPrint3("this non-leaf block not added inForceSetting == -1\n")
else:
includeOrExcludeAllSubBlocks = 0
#this is a non-leaf node, but we want to add it (or not) depending on
#the filter settings
if inMetaData == None:
thisBlockName = None
else:
thisBlockName = inMetaData.Get(vtk.vtkCompositeDataSet.NAME())
if (thisBlockName != None) and (thisBlockName in includeBlockList):
if PhactoriDbg(100):
myDebugPrint3("include list, append nonleaf " + str(thisBlockName) + \
" ndx " + str(int(ioFlatIndexCounter[0]) - 1) + "\n")
includeIndexList.append(int(ioFlatIndexCounter[0]) - 1)
includeOrExcludeAllSubBlocks = 1
if PhactoriDbg(100):
myDebugPrint3("includeOrExcludeAllSubBlocks set to 1\n")
else:
if PhactoriDbg(100):
myDebugPrint3("include list, exclude nonleaf " + str(thisBlockName) + \
" ndx " + str(int(ioFlatIndexCounter[0]) - 1) + "\n")
if nonLeafType == 2:
numBlocks = inCsdata.GetNumberOfPieces()
elif nonLeafType == 3:
numBlocks = inCsdata.GetNumberOfPartitions()
else:
numBlocks = inCsdata.GetNumberOfBlocks()
if PhactoriDbg(100):
myDebugPrint3("recursing, flat index: " + \
str(ioFlatIndexCounter[0]) + \
" num blocks: " + \
str(numBlocks) + "\n")
for ii in range(0, numBlocks):
if nonLeafType == 2:
oneBlock = inCsdata.GetPiece(ii)
elif nonLeafType == 3:
oneBlock = inCsdata.GetPartition(ii)
else:
oneBlock = inCsdata.GetBlock(ii)
oneBlockMetaData = inCsdata.GetMetaData(ii)
if PhactoriDbg(100):
myDebugPrint3("oneBlockMetaData: " + str(oneBlockMetaData) + "\n")
#myDebugPrint3("name: " + \
# oneBlockMetaData.Get(vtk.vtkCompositeDataSet.NAME()) + "\n")
if oneBlock != None:
if oneBlockMetaData != None:
theBlockName = oneBlockMetaData.Get(vtk.vtkCompositeDataSet.NAME())
if PhactoriDbg(100):
myDebugPrint3("name for block " + str(ii) + ": " + \
str(theBlockName) + "\n")
else:
if PhactoriDbg(100):
myDebugPrint3("block " + str(ii) + " meta data was None\n")
FigureBlockIndicesFromBlockListRecurse1(includeIndexList, includeBlockList,
oneBlock, oneBlockMetaData, ioFlatIndexCounter,
includeOrExcludeAllSubBlocks)
else:
#I think we need to count here to be okay with pruned stuff; maybe
#we need to set extract block to no pruning (?)
ioFlatIndexCounter[0] += 1
if includeOrExcludeAllSubBlocks == 1:
if PhactoriDbg(100):
myDebugPrint3("leaf block None index " + \
str(int(ioFlatIndexCounter[0]) - 1) + \
" appended due to includeOrExcludeAllSubBlocks == 1\n\n")
includeIndexList.append(int(ioFlatIndexCounter[0]) - 1)
else:
if PhactoriDbg(100):
myDebugPrint3("force include is not on, so check include list\n")
includeThisBlock = False
if (includeBlockList != None) and (oneBlockMetaData != None):
thisBlockName = oneBlockMetaData.Get(vtk.vtkCompositeDataSet.NAME())
if PhactoriDbg(100):
myDebugPrint3("include list not None, thisBlockName " + str(thisBlockName) + "\n"
"includeBlockList " + str(includeBlockList) + "\n")
if (thisBlockName != None) and (thisBlockName in includeBlockList):
includeThisBlock = True
if PhactoriDbg(100):
myDebugPrint3("leaf block None index " + \
str(int(ioFlatIndexCounter[0]) - 1) + \
" included due to name being in includeBlockList\n")
includeIndexList.append(int(ioFlatIndexCounter[0]) - 1)
if includeThisBlock == False:
if PhactoriDbg(100):
myDebugPrint3("leaf block None index " + \
str(int(ioFlatIndexCounter[0]) - 1) + \
" excluded due to includeOrExcludeAllSubBlocks != 1\n")
else:
if inForceSetting != -1:
if inForceSetting == 1:
if PhactoriDbg(100):
myDebugPrint3("this leaf block will be added inForceSetting == 1\n")
FigureBlockIndicesFromBlockListOneBlock(includeIndexList,
includeBlockList, inMetaData, ioFlatIndexCounter, inCsdata, inForceSetting)
else:
if PhactoriDbg(100):
myDebugPrint3("this leaf block not added inForceSetting == -1\n") | [
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SequoiaDB/SequoiaDB | 2894ed7e5bd6fe57330afc900cf76d0ff0df9f64 | tools/server/php_linux/libxml2/lib/python2.4/site-packages/libxml2.py | python | parserCtxt.parserHandleReference | (self) | TODO: Remove, now deprecated ... the test is done directly
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wlanjie/AndroidFFmpeg | 7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf | tools/fdk-aac-build/armeabi/toolchain/lib/python2.7/idlelib/AutoComplete.py | python | AutoComplete.autocomplete_event | (self, event) | Happens when the user wants to complete his word, and if necessary,
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"""Happens when the user wants to complete his word, and if necessary,
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completion)
"""
if hasattr(event, "mc_state") and event.mc_state:
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return
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rapidsai/cudf | d5b2448fc69f17509304d594f029d0df56984962 | python/cudf/cudf/core/column/numerical.py | python | NumericalColumn.can_cast_safely | (self, to_dtype: DtypeObj) | return False | Returns true if all the values in self can be
safely cast to dtype | Returns true if all the values in self can be
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"""
Returns true if all the values in self can be
safely cast to dtype
"""
if self.dtype.kind == to_dtype.kind:
if self.dtype <= to_dtype:
return True
else:
# Kinds are the same but to_dtype is smaller
if "float" in to_dtype.name:
finfo = np.finfo(to_dtype)
lower_, upper_ = finfo.min, finfo.max
elif "int" in to_dtype.name:
iinfo = np.iinfo(to_dtype)
lower_, upper_ = iinfo.min, iinfo.max
if self.dtype.kind == "f":
# Exclude 'np.inf', '-np.inf'
s = cudf.Series(self)
# TODO: replace np.inf with cudf scalar when
# https://github.com/rapidsai/cudf/pull/6297 merges
non_infs = s[
((s == np.inf) | (s == -np.inf)).logical_not()
]
col = non_infs._column
else:
col = self
min_ = col.min()
# TODO: depending on implementation of cudf scalar and future
# refactor of min/max, change the test method
if np.isnan(min_):
# Column contains only infs
return True
return (min_ >= lower_) and (col.max() < upper_)
# want to cast int to uint
elif self.dtype.kind == "i" and to_dtype.kind == "u":
i_max_ = np.iinfo(self.dtype).max
u_max_ = np.iinfo(to_dtype).max
return (self.min() >= 0) and (
(i_max_ <= u_max_) or (self.max() < u_max_)
)
# want to cast uint to int
elif self.dtype.kind == "u" and to_dtype.kind == "i":
u_max_ = np.iinfo(self.dtype).max
i_max_ = np.iinfo(to_dtype).max
return (u_max_ <= i_max_) or (self.max() < i_max_)
# want to cast int to float
elif self.dtype.kind in {"i", "u"} and to_dtype.kind == "f":
info = np.finfo(to_dtype)
biggest_exact_int = 2 ** (info.nmant + 1)
if (self.min() >= -biggest_exact_int) and (
self.max() <= biggest_exact_int
):
return True
else:
filled = self.fillna(0)
return (
cudf.Series(filled).astype(to_dtype).astype(filled.dtype)
== cudf.Series(filled)
).all()
# want to cast float to int:
elif self.dtype.kind == "f" and to_dtype.kind in {"i", "u"}:
iinfo = np.iinfo(to_dtype)
min_, max_ = iinfo.min, iinfo.max
# best we can do is hope to catch it here and avoid compare
if (self.min() >= min_) and (self.max() <= max_):
filled = self.fillna(0, fill_nan=False)
return (cudf.Series(filled) % 1 == 0).all()
else:
return False
return False | [
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tensorflow/tensorflow | 419e3a6b650ea4bd1b0cba23c4348f8a69f3272e | tensorflow/python/keras/distribute/distributed_file_utils.py | python | remove_temp_dir_with_filepath | (filepath, strategy) | Removes the temp path for file after writing is finished.
Args:
filepath: Original filepath that would be used without distribution.
strategy: The tf.distribute strategy object currently used. | Removes the temp path for file after writing is finished. | [
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"""Removes the temp path for file after writing is finished.
Args:
filepath: Original filepath that would be used without distribution.
strategy: The tf.distribute strategy object currently used.
"""
remove_temp_dirpath(os.path.dirname(filepath), strategy) | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/numpy/py2/numpy/distutils/system_info.py | python | system_info.check_libs | (self, lib_dirs, libs, opt_libs=[]) | return info | If static or shared libraries are available then return
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Checks for all libraries as shared libraries first, then
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"""
exts = self.library_extensions()
info = None
for ext in exts:
info = self._check_libs(lib_dirs, libs, opt_libs, [ext])
if info is not None:
break
if not info:
log.info(' libraries %s not found in %s', ','.join(libs),
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hifiberry/hifiberry-os | 88c05213fb3e6230645cb4bf8eb8fceda8bd07d4 | buildroot/package/lmsmpris/src/audiocontrol2.py | python | print_state | (signalNumber=None, frame=None) | Display state on USR2 | Display state on USR2 | [
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"""
Display state on USR2
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if mpris is not None:
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wlanjie/AndroidFFmpeg | 7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf | tools/fdk-aac-build/armeabi-v7a/toolchain/lib/python2.7/mailbox.py | python | MH._dump_sequences | (self, message, key) | Inspect a new MHMessage and update sequences appropriately. | Inspect a new MHMessage and update sequences appropriately. | [
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pending_sequences = message.get_sequences()
all_sequences = self.get_sequences()
for name, key_list in all_sequences.iteritems():
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key_list.append(key)
elif key in key_list:
del key_list[key_list.index(key)]
for sequence in pending_sequences:
if sequence not in all_sequences:
all_sequences[sequence] = [key]
self.set_sequences(all_sequences) | [
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ChromiumWebApps/chromium | c7361d39be8abd1574e6ce8957c8dbddd4c6ccf7 | third_party/jinja2/compiler.py | python | CodeGenerator.position | (self, node) | return rv | Return a human readable position for the node. | Return a human readable position for the node. | [
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"""Return a human readable position for the node."""
rv = 'line %d' % node.lineno
if self.name is not None:
rv += ' in ' + repr(self.name)
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kristjankorjus/Replicating-DeepMind | 68539394e792b34a4d6b430a2eb73b8b8f91d8db | Hybrid/tools/scoreanalyzer.py | python | ScoreAnalyzer.sandbox | (self) | The main place to try out things | The main place to try out things | [
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""" The main place to try out things """
print self.scores.keys()
print self.scores[1] | [
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opengm/opengm | decdacf4caad223b0ab5478d38a855f8767a394f | src/interfaces/python/opengm/opengmcore/__init__.py | python | getStartingPointMasked | (imgArg, mask, maskIdx=1) | return points.astype(label_type) | maps 3d starting points to gm indices | maps 3d starting points to gm indices | [
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"""
maps 3d starting points to gm indices
"""
points = numpy.zeros(mask[mask==maskIdx].shape, dtype=numpy.uint32)
_opengmcore._getStartingPointMasked(mask, imgArg, points)
return points.astype(label_type) | [
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Xilinx/Vitis-AI | fc74d404563d9951b57245443c73bef389f3657f | models/AI-Model-Zoo/caffe-xilinx/python/caffe/draw.py | python | get_edge_label | (layer) | return edge_label | Define edge label based on layer type. | Define edge label based on layer type. | [
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"""Define edge label based on layer type.
"""
if layer.type == 'Data':
edge_label = 'Batch ' + str(layer.data_param.batch_size)
elif layer.type == 'Convolution' or layer.type == 'Deconvolution':
edge_label = str(layer.convolution_param.num_output)
elif layer.type == 'InnerProduct':
edge_label = str(layer.inner_product_param.num_output)
else:
edge_label = '""'
return edge_label | [
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redpony/cdec | f7c4899b174d86bc70b40b1cae68dcad364615cb | python/cdec/configobj.py | python | Section.iterkeys | (self) | return iter((self.scalars + self.sections)) | D.iterkeys() -> an iterator over the keys of D | D.iterkeys() -> an iterator over the keys of D | [
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] | https://github.com/redpony/cdec/blob/f7c4899b174d86bc70b40b1cae68dcad364615cb/python/cdec/configobj.py#L742-L744 | |
ChromiumWebApps/chromium | c7361d39be8abd1574e6ce8957c8dbddd4c6ccf7 | chrome/tools/webforms_extractor.py | python | FormsExtractor.__init__ | (self, input_dir=_REGISTRATION_PAGES_DIR,
output_dir=_EXTRACTED_FORMS_DIR, logging_level=None) | Creates a FormsExtractor object.
Args:
input_dir: the directory of HTML files.
output_dir: the directory where the registration form files will be
saved.
logging_level: verbosity level, default is None.
Raises:
IOError exception if input directory doesn't exist. | Creates a FormsExtractor object. | [
"Creates",
"a",
"FormsExtractor",
"object",
"."
] | def __init__(self, input_dir=_REGISTRATION_PAGES_DIR,
output_dir=_EXTRACTED_FORMS_DIR, logging_level=None):
"""Creates a FormsExtractor object.
Args:
input_dir: the directory of HTML files.
output_dir: the directory where the registration form files will be
saved.
logging_level: verbosity level, default is None.
Raises:
IOError exception if input directory doesn't exist.
"""
if logging_level:
if not self.log_handlers['StreamHandler']:
console = logging.StreamHandler()
console.setLevel(logging.DEBUG)
self.log_handlers['StreamHandler'] = console
self.logger.addHandler(console)
self.logger.setLevel(logging_level)
else:
if self.log_handlers['StreamHandler']:
self.logger.removeHandler(self.log_handlers['StreamHandler'])
self.log_handlers['StreamHandler'] = None
self._input_dir = input_dir
self._output_dir = output_dir
if not os.path.isdir(self._input_dir):
error_msg = 'Directory "%s" doesn\'t exist.' % self._input_dir
self.logger.error('Error: %s', error_msg)
raise IOError(error_msg)
if not os.path.isdir(output_dir):
os.makedirs(output_dir)
self._form_location_comment = '' | [
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windystrife/UnrealEngine_NVIDIAGameWorks | b50e6338a7c5b26374d66306ebc7807541ff815e | Engine/Extras/ThirdPartyNotUE/emsdk/Win64/python/2.7.5.3_64bit/Lib/calendar.py | python | monthrange | (year, month) | return day1, ndays | Return weekday (0-6 ~ Mon-Sun) and number of days (28-31) for
year, month. | Return weekday (0-6 ~ Mon-Sun) and number of days (28-31) for
year, month. | [
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"year",
"month",
"."
] | def monthrange(year, month):
"""Return weekday (0-6 ~ Mon-Sun) and number of days (28-31) for
year, month."""
if not 1 <= month <= 12:
raise IllegalMonthError(month)
day1 = weekday(year, month, 1)
ndays = mdays[month] + (month == February and isleap(year))
return day1, ndays | [
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PaddlePaddle/Paddle | 1252f4bb3e574df80aa6d18c7ddae1b3a90bd81c | python/paddle/fluid/framework.py | python | IrNode.remove_input | (self, node) | Remove a node from inputs.
Args:
node(IrNode): the node being removed. | Remove a node from inputs. | [
"Remove",
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] | def remove_input(self, node):
"""
Remove a node from inputs.
Args:
node(IrNode): the node being removed.
"""
self.node.remove_input(node.node) | [
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macchina-io/macchina.io | ef24ba0e18379c3dd48fb84e6dbf991101cb8db0 | platform/JS/V8/tools/gyp/tools/graphviz.py | python | WriteGraph | (edges) | Print a graphviz graph to stdout.
|edges| is a map of target to a list of other targets it depends on. | Print a graphviz graph to stdout.
|edges| is a map of target to a list of other targets it depends on. | [
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"depends",
"on",
"."
] | def WriteGraph(edges):
"""Print a graphviz graph to stdout.
|edges| is a map of target to a list of other targets it depends on."""
# Bucket targets by file.
files = collections.defaultdict(list)
for src, dst in edges.items():
build_file, target_name, toolset = ParseTarget(src)
files[build_file].append(src)
print 'digraph D {'
print ' fontsize=8' # Used by subgraphs.
print ' node [fontsize=8]'
# Output nodes by file. We must first write out each node within
# its file grouping before writing out any edges that may refer
# to those nodes.
for filename, targets in files.items():
if len(targets) == 1:
# If there's only one node for this file, simplify
# the display by making it a box without an internal node.
target = targets[0]
build_file, target_name, toolset = ParseTarget(target)
print ' "%s" [shape=box, label="%s\\n%s"]' % (target, filename,
target_name)
else:
# Group multiple nodes together in a subgraph.
print ' subgraph "cluster_%s" {' % filename
print ' label = "%s"' % filename
for target in targets:
build_file, target_name, toolset = ParseTarget(target)
print ' "%s" [label="%s"]' % (target, target_name)
print ' }'
# Now that we've placed all the nodes within subgraphs, output all
# the edges between nodes.
for src, dsts in edges.items():
for dst in dsts:
print ' "%s" -> "%s"' % (src, dst)
print '}' | [
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weolar/miniblink49 | 1c4678db0594a4abde23d3ebbcc7cd13c3170777 | third_party/WebKit/Tools/Scripts/webkitpy/common/checkout/scm/git.py | python | Git.create_patch | (self, git_commit=None, changed_files=None) | return self._prepend_svn_revision(self._run(command, decode_output=False, cwd=self.checkout_root)) | Returns a byte array (str()) representing the patch file.
Patch files are effectively binary since they may contain
files of multiple different encodings. | Returns a byte array (str()) representing the patch file.
Patch files are effectively binary since they may contain
files of multiple different encodings. | [
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] | def create_patch(self, git_commit=None, changed_files=None):
"""Returns a byte array (str()) representing the patch file.
Patch files are effectively binary since they may contain
files of multiple different encodings."""
# Put code changes at the top of the patch and layout tests
# at the bottom, this makes for easier reviewing.
config_path = self._filesystem.dirname(self._filesystem.path_to_module('webkitpy.common.config'))
order_file = self._filesystem.join(config_path, 'orderfile')
order = ""
if self._filesystem.exists(order_file):
order = "-O%s" % order_file
command = [self.executable_name, 'diff', '--binary', '--no-color', "--no-ext-diff", "--full-index", "--no-renames", order, self._merge_base(git_commit), "--"]
if changed_files:
command += changed_files
return self._prepend_svn_revision(self._run(command, decode_output=False, cwd=self.checkout_root)) | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/pandas/py2/pandas/core/internals/blocks.py | python | DatetimeBlock.to_native_types | (self, slicer=None, na_rep=None, date_format=None,
quoting=None, **kwargs) | return np.atleast_2d(result) | convert to our native types format, slicing if desired | convert to our native types format, slicing if desired | [
"convert",
"to",
"our",
"native",
"types",
"format",
"slicing",
"if",
"desired"
] | def to_native_types(self, slicer=None, na_rep=None, date_format=None,
quoting=None, **kwargs):
""" convert to our native types format, slicing if desired """
values = self.values
i8values = self.values.view('i8')
if slicer is not None:
i8values = i8values[..., slicer]
from pandas.io.formats.format import _get_format_datetime64_from_values
fmt = _get_format_datetime64_from_values(values, date_format)
result = tslib.format_array_from_datetime(
i8values.ravel(), tz=getattr(self.values, 'tz', None),
format=fmt, na_rep=na_rep).reshape(i8values.shape)
return np.atleast_2d(result) | [
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sc0ty/subsync | be5390d00ff475b6543eb0140c7e65b34317d95b | subsync/__init__.py | python | synchronize | (sub, ref, out, *, onError=None, options={}, offline=False, updateAssets=True) | return res | Synchronize single subtitle file.
This is simplified high level synchronization API. For finer-grained
control use `SyncController` object.
Parameters
----------
sub: SubFile or InputFile or dict
Input subtitle description, proper object instance or `dict` with
fields same as arguments to `InputFile` constructor.
ref: RefFile or InputFile or dict
Reference description, proper object instance or `dict` with fields
same as arguments to `InputFile` constructor.
out: OutputFile or dict
Output subtitle description, proper object instance or `dict` with
fields same as arguments to `OutputFile` constructor.
onError: callable, optional
Error callback for non-terminal errors. Terminal errors will raise
exception. For details see `SyncController` constructor.
options: dict, optional
Override default synchronization options, see `SyncController.configure`.
offline: bool, optional
Prevent any communication with asset server. If required assets are
missing, they will not be downloaded and synchronization will fail.
updateAssets: bool, optional
Whether to update existing assets if update is available online. Has no
effect with `offline`=`True`.
Returns
-------
tuple of (subsync.synchro.controller.SyncJobResult, subsync.synchro.controller.SyncStatus)
Synchronization result.
Notes
-----
This function runs synchronously - it will block until synchronization
finishes. For non-blocking synchronization use `SyncController` instead.
Example
-------
>>> sub = { 'path': './sub.srt', 'lang': 'rus' }
>>> ref = { 'path': './movie.avi', 'stream': 2, 'lang': 'eng' }
>>> out = { 'path': './out.srt' }
>>> subsync.synchronize(sub, ref, out)
(SyncJobResult(success=True, terminated=False, path='out.srt'), SyncStatus(correlated=True, maxChange=0.010168457031248579, progress=0.5212266710947953, factor=0.9999998222916713, points=289, formula=1.0000x+0.010, effort=0.5004523633099243)) | Synchronize single subtitle file. | [
"Synchronize",
"single",
"subtitle",
"file",
"."
] | def synchronize(sub, ref, out, *, onError=None, options={}, offline=False, updateAssets=True):
"""Synchronize single subtitle file.
This is simplified high level synchronization API. For finer-grained
control use `SyncController` object.
Parameters
----------
sub: SubFile or InputFile or dict
Input subtitle description, proper object instance or `dict` with
fields same as arguments to `InputFile` constructor.
ref: RefFile or InputFile or dict
Reference description, proper object instance or `dict` with fields
same as arguments to `InputFile` constructor.
out: OutputFile or dict
Output subtitle description, proper object instance or `dict` with
fields same as arguments to `OutputFile` constructor.
onError: callable, optional
Error callback for non-terminal errors. Terminal errors will raise
exception. For details see `SyncController` constructor.
options: dict, optional
Override default synchronization options, see `SyncController.configure`.
offline: bool, optional
Prevent any communication with asset server. If required assets are
missing, they will not be downloaded and synchronization will fail.
updateAssets: bool, optional
Whether to update existing assets if update is available online. Has no
effect with `offline`=`True`.
Returns
-------
tuple of (subsync.synchro.controller.SyncJobResult, subsync.synchro.controller.SyncStatus)
Synchronization result.
Notes
-----
This function runs synchronously - it will block until synchronization
finishes. For non-blocking synchronization use `SyncController` instead.
Example
-------
>>> sub = { 'path': './sub.srt', 'lang': 'rus' }
>>> ref = { 'path': './movie.avi', 'stream': 2, 'lang': 'eng' }
>>> out = { 'path': './out.srt' }
>>> subsync.synchronize(sub, ref, out)
(SyncJobResult(success=True, terminated=False, path='out.srt'), SyncStatus(correlated=True, maxChange=0.010168457031248579, progress=0.5212266710947953, factor=0.9999998222916713, points=289, formula=1.0000x+0.010, effort=0.5004523633099243))
"""
task = SyncTask(sub, ref, out)
assets = assetManager().getAssetsForTasks([ task ])
if not offline and (assets.missing() or updateAssets):
listUpdater = assetManager().getAssetListUpdater()
if not listUpdater.isRunning() and not listUpdater.isUpdated():
listUpdater.run()
listUpdater.wait()
assets.validate()
if not offline:
if updateAssets:
downloadAssets = assets.hasUpdate()
else:
downloadAssets = assets.notInstalled()
for asset in downloadAssets:
downloader = asset.downloader()
try:
downloader.run()
downloader.wait(reraise=True)
except:
downloader.terminate()
raise
assets.validate(localOnly=True)
res = (None, None)
def onJobEnd(task, status, result):
nonlocal res
res = (result, status)
sync = SyncController(onJobEnd=onJobEnd, onError=onError)
try:
sync.configure(**options)
sync.synchronize(task)
sync.wait()
except:
sync.terminate()
raise
return res | [
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mantidproject/mantid | 03deeb89254ec4289edb8771e0188c2090a02f32 | qt/python/mantidqtinterfaces/mantidqtinterfaces/Muon/GUI/Common/contexts/fitting_contexts/model_fitting_context.py | python | ModelFittingContext.y_parameters | (self) | return self._y_parameters | Returns the available y parameters for the selected results table. | Returns the available y parameters for the selected results table. | [
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"""Returns the available y parameters for the selected results table."""
return self._y_parameters | [
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wlanjie/AndroidFFmpeg | 7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf | tools/fdk-aac-build/x86/toolchain/lib/python2.7/lib2to3/fixer_util.py | python | Attr | (obj, attr) | return [obj, Node(syms.trailer, [Dot(), attr])] | A node tuple for obj.attr | A node tuple for obj.attr | [
"A",
"node",
"tuple",
"for",
"obj",
".",
"attr"
] | def Attr(obj, attr):
"""A node tuple for obj.attr"""
return [obj, Node(syms.trailer, [Dot(), attr])] | [
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generalized-intelligence/GAAS | 29ab17d3e8a4ba18edef3a57c36d8db6329fac73 | algorithms/src/LocalizationAndMapping/icp_lidar_localization/fast_gicp/thirdparty/Sophus/py/sophus/se3.py | python | Se3.__mul__ | (self, right) | left-multiplication
either rotation concatenation or point-transform | left-multiplication
either rotation concatenation or point-transform | [
"left",
"-",
"multiplication",
"either",
"rotation",
"concatenation",
"or",
"point",
"-",
"transform"
] | def __mul__(self, right):
""" left-multiplication
either rotation concatenation or point-transform """
if isinstance(right, sympy.Matrix):
assert right.shape == (3, 1), right.shape
return self.so3 * right + self.t
elif isinstance(right, Se3):
r = self.so3 * right.so3
t = self.t + self.so3 * right.t
return Se3(r, t)
assert False, "unsupported type: {0}".format(type(right)) | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/gtk/_windows.py | python | SplitterEvent.GetSashPosition | (*args, **kwargs) | return _windows_.SplitterEvent_GetSashPosition(*args, **kwargs) | GetSashPosition(self) -> int
Returns the new sash position while in EVT_SPLITTER_SASH_POS_CHANGING
and EVT_SPLITTER_SASH_POS_CHANGED events. | GetSashPosition(self) -> int | [
"GetSashPosition",
"(",
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">",
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] | def GetSashPosition(*args, **kwargs):
"""
GetSashPosition(self) -> int
Returns the new sash position while in EVT_SPLITTER_SASH_POS_CHANGING
and EVT_SPLITTER_SASH_POS_CHANGED events.
"""
return _windows_.SplitterEvent_GetSashPosition(*args, **kwargs) | [
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mantidproject/mantid | 03deeb89254ec4289edb8771e0188c2090a02f32 | Framework/PythonInterface/plugins/algorithms/WorkflowAlgorithms/ReflectometryILLPreprocess.py | python | ReflectometryILLPreprocess.version | (self) | return 1 | Return the version of the algorithm. | Return the version of the algorithm. | [
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] | def version(self):
"""Return the version of the algorithm."""
return 1 | [
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] | https://github.com/mantidproject/mantid/blob/03deeb89254ec4289edb8771e0188c2090a02f32/Framework/PythonInterface/plugins/algorithms/WorkflowAlgorithms/ReflectometryILLPreprocess.py#L93-L95 | |
QMCPACK/qmcpack | d0948ab455e38364458740cc8e2239600a14c5cd | utils/afqmctools/afqmctools/wavefunction/mol.py | python | write_nomsd_single | (fh5, psi, idet) | Write single component of NOMSD to hdf.
Parameters
----------
fh5 : h5py group
Wavefunction group to write to file.
psi : :class:`scipy.sparse.csr_matrix`
Sparse representation of trial wavefunction.
idet : int
Determinant number. | Write single component of NOMSD to hdf. | [
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] | def write_nomsd_single(fh5, psi, idet):
"""Write single component of NOMSD to hdf.
Parameters
----------
fh5 : h5py group
Wavefunction group to write to file.
psi : :class:`scipy.sparse.csr_matrix`
Sparse representation of trial wavefunction.
idet : int
Determinant number.
"""
base = 'PsiT_{:d}/'.format(idet)
dims = [psi.shape[0], psi.shape[1], psi.nnz]
fh5[base+'dims'] = numpy.array(dims, dtype=numpy.int32)
fh5[base+'data_'] = to_qmcpack_complex(psi.data)
fh5[base+'jdata_'] = psi.indices
fh5[base+'pointers_begin_'] = psi.indptr[:-1]
fh5[base+'pointers_end_'] = psi.indptr[1:] | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/site-packages/pip/_vendor/distlib/_backport/tarfile.py | python | TarFile.gzopen | (cls, name, mode="r", fileobj=None, compresslevel=9, **kwargs) | return t | Open gzip compressed tar archive name for reading or writing.
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"""Open gzip compressed tar archive name for reading or writing.
Appending is not allowed.
"""
if len(mode) > 1 or mode not in "rw":
raise ValueError("mode must be 'r' or 'w'")
try:
import gzip
gzip.GzipFile
except (ImportError, AttributeError):
raise CompressionError("gzip module is not available")
extfileobj = fileobj is not None
try:
fileobj = gzip.GzipFile(name, mode + "b", compresslevel, fileobj)
t = cls.taropen(name, mode, fileobj, **kwargs)
except IOError:
if not extfileobj and fileobj is not None:
fileobj.close()
if fileobj is None:
raise
raise ReadError("not a gzip file")
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/idlelib/tree.py | python | wheel_event | (event, widget=None) | return 'break' | Handle scrollwheel event.
For wheel up, event.delta = 120*n on Windows, -1*n on darwin,
where n can be > 1 if one scrolls fast. Flicking the wheel
generates up to maybe 20 events with n up to 10 or more 1.
Macs use wheel down (delta = 1*n) to scroll up, so positive
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"""Handle scrollwheel event.
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generates up to maybe 20 events with n up to 10 or more 1.
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"""
up = {EventType.MouseWheel: event.delta > 0,
EventType.ButtonPress: event.num == 4}
lines = -5 if up[event.type] else 5
widget = event.widget if widget is None else widget
widget.yview(SCROLL, lines, 'units')
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Ewenwan/MVision | 97b394dfa48cb21c82cd003b1a952745e413a17f | vSLAM/矩阵变换python函数.py | python | random_quaternion | (rand=None) | return numpy.array((numpy.sin(t1)*r1,
numpy.cos(t1)*r1,
numpy.sin(t2)*r2,
numpy.cos(t2)*r2), dtype=numpy.float64) | Return uniform random unit quaternion.
rand: array like or None
Three independent random variables that are uniformly distributed
between 0 and 1.
>>> q = random_quaternion()
>>> numpy.allclose(1.0, vector_norm(q))
True
>>> q = random_quaternion(numpy.random.random(3))
>>> q.shape
(4,) | Return uniform random unit quaternion.
rand: array like or None
Three independent random variables that are uniformly distributed
between 0 and 1.
>>> q = random_quaternion()
>>> numpy.allclose(1.0, vector_norm(q))
True
>>> q = random_quaternion(numpy.random.random(3))
>>> q.shape
(4,) | [
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"""Return uniform random unit quaternion.
rand: array like or None
Three independent random variables that are uniformly distributed
between 0 and 1.
>>> q = random_quaternion()
>>> numpy.allclose(1.0, vector_norm(q))
True
>>> q = random_quaternion(numpy.random.random(3))
>>> q.shape
(4,)
"""
if rand is None:
rand = numpy.random.rand(3)
else:
assert len(rand) == 3
r1 = numpy.sqrt(1.0 - rand[0])
r2 = numpy.sqrt(rand[0])
pi2 = math.pi * 2.0
t1 = pi2 * rand[1]
t2 = pi2 * rand[2]
return numpy.array((numpy.sin(t1)*r1,
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google/syzygy | 8164b24ebde9c5649c9a09e88a7fc0b0fcbd1bc5 | third_party/numpy/files/numpy/polynomial/laguerre.py | python | poly2lag | (pol) | return res | poly2lag(pol)
Convert a polynomial to a Laguerre series.
Convert an array representing the coefficients of a polynomial (relative
to the "standard" basis) ordered from lowest degree to highest, to an
array of the coefficients of the equivalent Laguerre series, ordered
from lowest to highest degree.
Parameters
----------
pol : array_like
1-d array containing the polynomial coefficients
Returns
-------
cs : ndarray
1-d array containing the coefficients of the equivalent Laguerre
series.
See Also
--------
lag2poly
Notes
-----
The easy way to do conversions between polynomial basis sets
is to use the convert method of a class instance.
Examples
--------
>>> from numpy.polynomial.laguerre import poly2lag
>>> poly2lag(np.arange(4))
array([ 23., -63., 58., -18.]) | poly2lag(pol) | [
"poly2lag",
"(",
"pol",
")"
] | def poly2lag(pol) :
"""
poly2lag(pol)
Convert a polynomial to a Laguerre series.
Convert an array representing the coefficients of a polynomial (relative
to the "standard" basis) ordered from lowest degree to highest, to an
array of the coefficients of the equivalent Laguerre series, ordered
from lowest to highest degree.
Parameters
----------
pol : array_like
1-d array containing the polynomial coefficients
Returns
-------
cs : ndarray
1-d array containing the coefficients of the equivalent Laguerre
series.
See Also
--------
lag2poly
Notes
-----
The easy way to do conversions between polynomial basis sets
is to use the convert method of a class instance.
Examples
--------
>>> from numpy.polynomial.laguerre import poly2lag
>>> poly2lag(np.arange(4))
array([ 23., -63., 58., -18.])
"""
[pol] = pu.as_series([pol])
deg = len(pol) - 1
res = 0
for i in range(deg, -1, -1) :
res = lagadd(lagmulx(res), pol[i])
return res | [
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tfwu/FaceDetection-ConvNet-3D | f9251c48eb40c5aec8fba7455115c355466555be | example/model-parallel-lstm/lstm.py | python | lstm | (num_hidden, indata, prev_state, param, seqidx, layeridx, dropout=0.) | return LSTMState(c=next_c, h=next_h) | LSTM Cell symbol | LSTM Cell symbol | [
"LSTM",
"Cell",
"symbol"
] | def lstm(num_hidden, indata, prev_state, param, seqidx, layeridx, dropout=0.):
"""LSTM Cell symbol"""
if dropout > 0.:
indata = mx.sym.Dropout(data=indata, p=dropout)
i2h = mx.sym.FullyConnected(data=indata,
weight=param.i2h_weight,
bias=param.i2h_bias,
num_hidden=num_hidden * 4,
name="t%d_l%d_i2h" % (seqidx, layeridx))
h2h = mx.sym.FullyConnected(data=prev_state.h,
weight=param.h2h_weight,
bias=param.h2h_bias,
num_hidden=num_hidden * 4,
name="t%d_l%d_h2h" % (seqidx, layeridx))
gates = i2h + h2h
slice_gates = mx.sym.SliceChannel(gates, num_outputs=4,
name="t%d_l%d_slice" % (seqidx, layeridx))
in_gate = mx.sym.Activation(slice_gates[0], act_type="sigmoid")
in_transform = mx.sym.Activation(slice_gates[1], act_type="tanh")
forget_gate = mx.sym.Activation(slice_gates[2], act_type="sigmoid")
out_gate = mx.sym.Activation(slice_gates[3], act_type="sigmoid")
next_c = (forget_gate * prev_state.c) + (in_gate * in_transform)
next_h = out_gate * mx.sym.Activation(next_c, act_type="tanh")
return LSTMState(c=next_c, h=next_h) | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/numpy/py3/numpy/polynomial/laguerre.py | python | lagadd | (c1, c2) | return pu._add(c1, c2) | Add one Laguerre series to another.
Returns the sum of two Laguerre series `c1` + `c2`. The arguments
are sequences of coefficients ordered from lowest order term to
highest, i.e., [1,2,3] represents the series ``P_0 + 2*P_1 + 3*P_2``.
Parameters
----------
c1, c2 : array_like
1-D arrays of Laguerre series coefficients ordered from low to
high.
Returns
-------
out : ndarray
Array representing the Laguerre series of their sum.
See Also
--------
lagsub, lagmulx, lagmul, lagdiv, lagpow
Notes
-----
Unlike multiplication, division, etc., the sum of two Laguerre series
is a Laguerre series (without having to "reproject" the result onto
the basis set) so addition, just like that of "standard" polynomials,
is simply "component-wise."
Examples
--------
>>> from numpy.polynomial.laguerre import lagadd
>>> lagadd([1, 2, 3], [1, 2, 3, 4])
array([2., 4., 6., 4.]) | Add one Laguerre series to another. | [
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] | def lagadd(c1, c2):
"""
Add one Laguerre series to another.
Returns the sum of two Laguerre series `c1` + `c2`. The arguments
are sequences of coefficients ordered from lowest order term to
highest, i.e., [1,2,3] represents the series ``P_0 + 2*P_1 + 3*P_2``.
Parameters
----------
c1, c2 : array_like
1-D arrays of Laguerre series coefficients ordered from low to
high.
Returns
-------
out : ndarray
Array representing the Laguerre series of their sum.
See Also
--------
lagsub, lagmulx, lagmul, lagdiv, lagpow
Notes
-----
Unlike multiplication, division, etc., the sum of two Laguerre series
is a Laguerre series (without having to "reproject" the result onto
the basis set) so addition, just like that of "standard" polynomials,
is simply "component-wise."
Examples
--------
>>> from numpy.polynomial.laguerre import lagadd
>>> lagadd([1, 2, 3], [1, 2, 3, 4])
array([2., 4., 6., 4.])
"""
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hanpfei/chromium-net | 392cc1fa3a8f92f42e4071ab6e674d8e0482f83f | third_party/catapult/third_party/gsutil/third_party/boto/boto/dynamodb2/table.py | python | Table.query_count | (self, index=None, consistent=False, conditional_operator=None,
query_filter=None, scan_index_forward=True, limit=None,
exclusive_start_key=None, **filter_kwargs) | return count_buffer | Queries the exact count of matching items in a DynamoDB table.
Queries can be performed against a hash key, a hash+range key or
against any data stored in your local secondary indexes. Query filters
can be used to filter on arbitrary fields.
To specify the filters of the items you'd like to get, you can specify
the filters as kwargs. Each filter kwarg should follow the pattern
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Optionally accepts an ``index`` parameter, which should be a string of
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(Default: ``None``)
Optionally accepts a ``consistent`` parameter, which should be a
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consistent reads)
Optionally accepts a ``query_filter`` which is a dictionary of filter
conditions against any arbitrary field in the returned data.
Optionally accepts a ``conditional_operator`` which applies to the
query filter conditions:
+ `AND` - True if all filter conditions evaluate to true (default)
+ `OR` - True if at least one filter condition evaluates to true
Optionally accept a ``exclusive_start_key`` which is used to get
the remaining items when a query cannot return the complete count.
Returns an integer which represents the exact amount of matched
items.
:type scan_index_forward: boolean
:param scan_index_forward: Specifies ascending (true) or descending
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the results are returned in order of ASCII character code values.
For Binary, DynamoDB treats each byte of the binary data as
unsigned when it compares binary values.
If ScanIndexForward is not specified, the results are returned in
ascending order.
:type limit: integer
:param limit: The maximum number of items to evaluate (not necessarily
the number of matching items).
Example::
# Look for last names equal to "Doe".
>>> users.query_count(last_name__eq='Doe')
5
# Use an LSI & a consistent read.
>>> users.query_count(
... date_joined__gte=1236451000,
... owner__eq=1,
... index='DateJoinedIndex',
... consistent=True
... )
2 | Queries the exact count of matching items in a DynamoDB table. | [
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"""
Queries the exact count of matching items in a DynamoDB table.
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can be used to filter on arbitrary fields.
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consistent reads)
Optionally accepts a ``query_filter`` which is a dictionary of filter
conditions against any arbitrary field in the returned data.
Optionally accepts a ``conditional_operator`` which applies to the
query filter conditions:
+ `AND` - True if all filter conditions evaluate to true (default)
+ `OR` - True if at least one filter condition evaluates to true
Optionally accept a ``exclusive_start_key`` which is used to get
the remaining items when a query cannot return the complete count.
Returns an integer which represents the exact amount of matched
items.
:type scan_index_forward: boolean
:param scan_index_forward: Specifies ascending (true) or descending
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is Number, the results are returned in numeric order. For String,
the results are returned in order of ASCII character code values.
For Binary, DynamoDB treats each byte of the binary data as
unsigned when it compares binary values.
If ScanIndexForward is not specified, the results are returned in
ascending order.
:type limit: integer
:param limit: The maximum number of items to evaluate (not necessarily
the number of matching items).
Example::
# Look for last names equal to "Doe".
>>> users.query_count(last_name__eq='Doe')
5
# Use an LSI & a consistent read.
>>> users.query_count(
... date_joined__gte=1236451000,
... owner__eq=1,
... index='DateJoinedIndex',
... consistent=True
... )
2
"""
key_conditions = self._build_filters(
filter_kwargs,
using=QUERY_OPERATORS
)
built_query_filter = self._build_filters(
query_filter,
using=FILTER_OPERATORS
)
count_buffer = 0
last_evaluated_key = exclusive_start_key
while True:
raw_results = self.connection.query(
self.table_name,
index_name=index,
consistent_read=consistent,
select='COUNT',
key_conditions=key_conditions,
query_filter=built_query_filter,
conditional_operator=conditional_operator,
limit=limit,
scan_index_forward=scan_index_forward,
exclusive_start_key=last_evaluated_key
)
count_buffer += int(raw_results.get('Count', 0))
last_evaluated_key = raw_results.get('LastEvaluatedKey')
if not last_evaluated_key or count_buffer < 1:
break
return count_buffer | [
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macchina-io/macchina.io | ef24ba0e18379c3dd48fb84e6dbf991101cb8db0 | platform/JS/V8/tools/gyp/pylib/gyp/generator/analyzer.py | python | _GetCompileTargets | (matching_targets, supplied_targets) | return result | Returns the set of Targets that require a build.
matching_targets: targets that changed and need to be built.
supplied_targets: set of targets supplied to analyzer to search from. | Returns the set of Targets that require a build.
matching_targets: targets that changed and need to be built.
supplied_targets: set of targets supplied to analyzer to search from. | [
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"""Returns the set of Targets that require a build.
matching_targets: targets that changed and need to be built.
supplied_targets: set of targets supplied to analyzer to search from."""
result = set()
for target in matching_targets:
print 'finding compile targets for match', target.name
_AddCompileTargets(target, supplied_targets, True, result)
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Xilinx/Vitis-AI | fc74d404563d9951b57245443c73bef389f3657f | tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/python/data/util/nest.py | python | assert_same_structure | (nest1, nest2, check_types=True) | Asserts that two structures are nested in the same way.
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nest1: an arbitrarily nested structure.
nest2: an arbitrarily nested structure.
check_types: if `True` (default) types of sequences should be same as
well. For dictionary, "type" of dictionary is considered to include its
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Raises:
ValueError: If the two structures do not have the same number of elements or
if the two structures are not nested in the same way.
TypeError: If the two structures differ in the type of sequence in any of
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] | def assert_same_structure(nest1, nest2, check_types=True):
"""Asserts that two structures are nested in the same way.
Args:
nest1: an arbitrarily nested structure.
nest2: an arbitrarily nested structure.
check_types: if `True` (default) types of sequences should be same as
well. For dictionary, "type" of dictionary is considered to include its
keys. In other words, two dictionaries with different keys are considered
to have a different "type". If set to `False`, two iterables are
considered same as long as they yield the elements that have same
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Raises:
ValueError: If the two structures do not have the same number of elements or
if the two structures are not nested in the same way.
TypeError: If the two structures differ in the type of sequence in any of
their substructures. Only possible if `check_types` is `True`.
"""
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facebookincubator/BOLT | 88c70afe9d388ad430cc150cc158641701397f70 | clang/tools/scan-build-py/lib/libscanbuild/clang.py | python | get_arguments | (command, cwd) | return decode(last_line) | Capture Clang invocation.
:param command: the compilation command
:param cwd: the current working directory
:return: the detailed front-end invocation command | Capture Clang invocation. | [
"Capture",
"Clang",
"invocation",
"."
] | def get_arguments(command, cwd):
""" Capture Clang invocation.
:param command: the compilation command
:param cwd: the current working directory
:return: the detailed front-end invocation command """
cmd = command[:]
cmd.insert(1, '-###')
cmd.append('-fno-color-diagnostics')
output = run_command(cmd, cwd=cwd)
# The relevant information is in the last line of the output.
# Don't check if finding last line fails, would throw exception anyway.
last_line = output[-1]
if re.search(r'clang(.*): error:', last_line):
raise ClangErrorException(last_line)
return decode(last_line) | [
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tensorflow/tensorflow | 419e3a6b650ea4bd1b0cba23c4348f8a69f3272e | tensorflow/python/ops/session_ops.py | python | _get_handle_mover | (graph, feeder, handle) | return result | Return a move subgraph for this pair of feeder and handle. | Return a move subgraph for this pair of feeder and handle. | [
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] | def _get_handle_mover(graph, feeder, handle):
"""Return a move subgraph for this pair of feeder and handle."""
dtype = _get_handle_feeder(graph, feeder)
if dtype is None:
return None
handle_device = TensorHandle._get_device_name(handle)
if feeder.op.device == handle_device:
return None
# Now we know we have to move the tensor.
graph_key = TensorHandle._get_mover_key(feeder, handle)
result = graph._handle_movers.get(graph_key)
if result is None:
# Create mover if we haven't done it.
holder, reader = _get_handle_reader(graph, handle, dtype)
with graph.as_default(), graph.device(feeder.op.device):
mover = gen_data_flow_ops.get_session_handle(reader)
result = (holder, mover)
graph._handle_movers[graph_key] = result
return result | [
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cybermaggedon/cyberprobe | f826dbc35ad3a79019cb871c0bc3fb1236130b3e | indicators/cyberprobe/indicators.py | python | load_indicator | (obj) | return ii | Loads an indicator from a Python dict object | Loads an indicator from a Python dict object | [
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] | def load_indicator(obj):
""" Loads an indicator from a Python dict object """
des = load_descriptor(obj["descriptor"])
ii = Indicator(des, id = obj["id"])
ii.value = load_value(obj)
return ii | [
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HyeonwooNoh/caffe | d9e8494a2832d67b25dee37194c7bcb9d52d0e42 | scripts/cpp_lint.py | python | CheckCStyleCast | (filename, linenum, line, raw_line, cast_type, pattern,
error) | return True | Checks for a C-style cast by looking for the pattern.
Args:
filename: The name of the current file.
linenum: The number of the line to check.
line: The line of code to check.
raw_line: The raw line of code to check, with comments.
cast_type: The string for the C++ cast to recommend. This is either
reinterpret_cast, static_cast, or const_cast, depending.
pattern: The regular expression used to find C-style casts.
error: The function to call with any errors found.
Returns:
True if an error was emitted.
False otherwise. | Checks for a C-style cast by looking for the pattern. | [
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] | def CheckCStyleCast(filename, linenum, line, raw_line, cast_type, pattern,
error):
"""Checks for a C-style cast by looking for the pattern.
Args:
filename: The name of the current file.
linenum: The number of the line to check.
line: The line of code to check.
raw_line: The raw line of code to check, with comments.
cast_type: The string for the C++ cast to recommend. This is either
reinterpret_cast, static_cast, or const_cast, depending.
pattern: The regular expression used to find C-style casts.
error: The function to call with any errors found.
Returns:
True if an error was emitted.
False otherwise.
"""
match = Search(pattern, line)
if not match:
return False
# Exclude lines with sizeof, since sizeof looks like a cast.
sizeof_match = Match(r'.*sizeof\s*$', line[0:match.start(1) - 1])
if sizeof_match:
return False
# operator++(int) and operator--(int)
if (line[0:match.start(1) - 1].endswith(' operator++') or
line[0:match.start(1) - 1].endswith(' operator--')):
return False
# A single unnamed argument for a function tends to look like old
# style cast. If we see those, don't issue warnings for deprecated
# casts, instead issue warnings for unnamed arguments where
# appropriate.
#
# These are things that we want warnings for, since the style guide
# explicitly require all parameters to be named:
# Function(int);
# Function(int) {
# ConstMember(int) const;
# ConstMember(int) const {
# ExceptionMember(int) throw (...);
# ExceptionMember(int) throw (...) {
# PureVirtual(int) = 0;
#
# These are functions of some sort, where the compiler would be fine
# if they had named parameters, but people often omit those
# identifiers to reduce clutter:
# (FunctionPointer)(int);
# (FunctionPointer)(int) = value;
# Function((function_pointer_arg)(int))
# <TemplateArgument(int)>;
# <(FunctionPointerTemplateArgument)(int)>;
remainder = line[match.end(0):]
if Match(r'^\s*(?:;|const\b|throw\b|=|>|\{|\))', remainder):
# Looks like an unnamed parameter.
# Don't warn on any kind of template arguments.
if Match(r'^\s*>', remainder):
return False
# Don't warn on assignments to function pointers, but keep warnings for
# unnamed parameters to pure virtual functions. Note that this pattern
# will also pass on assignments of "0" to function pointers, but the
# preferred values for those would be "nullptr" or "NULL".
matched_zero = Match(r'^\s=\s*(\S+)\s*;', remainder)
if matched_zero and matched_zero.group(1) != '0':
return False
# Don't warn on function pointer declarations. For this we need
# to check what came before the "(type)" string.
if Match(r'.*\)\s*$', line[0:match.start(0)]):
return False
# Don't warn if the parameter is named with block comments, e.g.:
# Function(int /*unused_param*/);
if '/*' in raw_line:
return False
# Passed all filters, issue warning here.
error(filename, linenum, 'readability/function', 3,
'All parameters should be named in a function')
return True
# At this point, all that should be left is actual casts.
error(filename, linenum, 'readability/casting', 4,
'Using C-style cast. Use %s<%s>(...) instead' %
(cast_type, match.group(1)))
return True | [
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apache/incubator-mxnet | f03fb23f1d103fec9541b5ae59ee06b1734a51d9 | python/mxnet/onnx/mx2onnx/_op_translations/_op_translations_opset12.py | python | convert_mul_scalar | (node, **kwargs) | return scalar_op_helper(node, 'Mul', **kwargs) | Map MXNet's _mul_scalar operator attributes to onnx's Mul operator.
Creates a new node for the input scalar value, adds it to the initializer
and return multiple created nodes. | Map MXNet's _mul_scalar operator attributes to onnx's Mul operator.
Creates a new node for the input scalar value, adds it to the initializer
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"""Map MXNet's _mul_scalar operator attributes to onnx's Mul operator.
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and return multiple created nodes.
"""
return scalar_op_helper(node, 'Mul', **kwargs) | [
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echronos/echronos | c996f1d2c8af6c6536205eb319c1bf1d4d84569c | external_tools/ply_info/example/yply/yparse.py | python | p_rules | (p) | rules : rules rule
| rule | rules : rules rule
| rule | [
"rules",
":",
"rules",
"rule",
"|",
"rule"
] | def p_rules(p):
'''rules : rules rule
| rule'''
if len(p) == 2:
rule = p[1]
else:
rule = p[2]
# Print out a Python equivalent of this rule
embedded = [ ] # Embedded actions (a mess)
embed_count = 0
rulename = rule[0]
rulecount = 1
for r in rule[1]:
# r contains one of the rule possibilities
print "def p_%s_%d(p):" % (rulename,rulecount)
prod = []
prodcode = ""
for i in range(len(r)):
item = r[i]
if item[0] == '{': # A code block
if i == len(r) - 1:
prodcode = item
break
else:
# an embedded action
embed_name = "_embed%d_%s" % (embed_count,rulename)
prod.append(embed_name)
embedded.append((embed_name,item))
embed_count += 1
else:
prod.append(item)
print " '''%s : %s'''" % (rulename, " ".join(prod))
# Emit code
print_code(prodcode,4)
print
rulecount += 1
for e,code in embedded:
print "def p_%s(p):" % e
print " '''%s : '''" % e
print_code(code,4)
print | [
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wlanjie/AndroidFFmpeg | 7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf | tools/fdk-aac-build/armeabi/toolchain/lib/python2.7/lib2to3/pytree.py | python | Base.__eq__ | (self, other) | return self._eq(other) | Compare two nodes for equality.
This calls the method _eq(). | Compare two nodes for equality. | [
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] | def __eq__(self, other):
"""
Compare two nodes for equality.
This calls the method _eq().
"""
if self.__class__ is not other.__class__:
return NotImplemented
return self._eq(other) | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/tools/python/src/Lib/pydoc.py | python | TextDoc.docother | (self, object, name=None, mod=None, parent=None, maxlen=None, doc=None) | return line | Produce text documentation for a data object. | Produce text documentation for a data object. | [
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"object",
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] | def docother(self, object, name=None, mod=None, parent=None, maxlen=None, doc=None):
"""Produce text documentation for a data object."""
repr = self.repr(object)
if maxlen:
line = (name and name + ' = ' or '') + repr
chop = maxlen - len(line)
if chop < 0: repr = repr[:chop] + '...'
line = (name and self.bold(name) + ' = ' or '') + repr
if doc is not None:
line += '\n' + self.indent(str(doc))
return line | [
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y123456yz/reading-and-annotate-mongodb-3.6 | 93280293672ca7586dc24af18132aa61e4ed7fcf | mongo/buildscripts/idl/idl/writer.py | python | EmptyBlock.__exit__ | (self, *args) | Do nothing. | Do nothing. | [
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# type: (*str) -> None
"""Do nothing."""
pass | [
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natanielruiz/android-yolo | 1ebb54f96a67a20ff83ddfc823ed83a13dc3a47f | jni-build/jni/include/tensorflow/contrib/distributions/python/ops/bijector.py | python | _Bijector.inverse | (self, x, name='inverse') | Returns the inverse bijector evaluation, i.e., X = g^{-1}(Y).
Args:
x: `Tensor`. The input to the "inverse" evaluation.
name: The name to give this op.
Returns:
`Tensor`. | Returns the inverse bijector evaluation, i.e., X = g^{-1}(Y). | [
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"""Returns the inverse bijector evaluation, i.e., X = g^{-1}(Y).
Args:
x: `Tensor`. The input to the "inverse" evaluation.
name: The name to give this op.
Returns:
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"""
with ops.name_scope(self.name):
with ops.op_scope([x], name):
x = ops.convert_to_tensor(x)
try:
return self._inverse(x)
except NotImplementedError:
return self._inverse_and_inverse_log_det_jacobian(x)[0] | [
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musescore/MuseScore | a817fea23e3c2be30847b7fde5b01746222c252e | thirdparty/freetype/src/tools/glnames.py | python | dump_array | ( the_array, write, array_name ) | dumps a given encoding | dumps a given encoding | [
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"encoding"
] | def dump_array( the_array, write, array_name ):
"""dumps a given encoding"""
write( " static const unsigned char " + array_name +
"[" + repr( len( the_array ) ) + "L] =\n" )
write( " {\n" )
line = ""
comma = " "
col = 0
for value in the_array:
line += comma
line += "%3d" % ord( value )
comma = ","
col += 1
if col == 16:
col = 0
comma = ",\n "
if len( line ) > 1024:
write( line )
line = ""
write( line + "\n };\n\n\n" ) | [
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protocolbuffers/protobuf | b5ab0b7a18b7336c60130f4ddb2d97c51792f896 | python/setup.py | python | GetVersion | () | Gets the version from google/protobuf/__init__.py
Do not import google.protobuf.__init__ directly, because an installed
protobuf library may be loaded instead. | Gets the version from google/protobuf/__init__.py | [
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"""Gets the version from google/protobuf/__init__.py
Do not import google.protobuf.__init__ directly, because an installed
protobuf library may be loaded instead."""
with open(os.path.join('google', 'protobuf', '__init__.py')) as version_file:
exec(version_file.read(), globals())
global __version__
return __version__ | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/pandas/py3/pandas/core/dtypes/common.py | python | ensure_python_int | (value: int | np.integer) | return new_value | Ensure that a value is a python int.
Parameters
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value: int or numpy.integer
Returns
-------
int
Raises
------
TypeError: if the value isn't an int or can't be converted to one. | Ensure that a value is a python int. | [
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"""
Ensure that a value is a python int.
Parameters
----------
value: int or numpy.integer
Returns
-------
int
Raises
------
TypeError: if the value isn't an int or can't be converted to one.
"""
if not is_scalar(value):
raise TypeError(
f"Value needs to be a scalar value, was type {type(value).__name__}"
)
try:
new_value = int(value)
assert new_value == value
except (TypeError, ValueError, AssertionError) as err:
raise TypeError(f"Wrong type {type(value)} for value {value}") from err
return new_value | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemMetric/v1/AWS/python/windows/Lib/psutil/_pswindows.py | python | net_if_addrs | () | return ret | Return the addresses associated to each NIC. | Return the addresses associated to each NIC. | [
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facebook/hermes | b1b1a00ab468ec1b397b31b71587110044830970 | lldb/Stack.py | python | _heuristic_search_ip_in_stack | (leaf_frame) | return 0 | Heuristically unwind native stack frames to search for local variable ip if available | Heuristically unwind native stack frames to search for local variable ip if available | [
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"""Heuristically unwind native stack frames to search for local variable ip if available"""
frame = leaf_frame
while frame is not None:
ip = frame.FindVariable("ip")
if ip is not None:
return ip.GetValueAsUnsigned()
frame = frame.get_parent_frame()
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_cocoa/_misc.py | python | Caret.MoveXY | (*args, **kwargs) | return _misc_.Caret_MoveXY(*args, **kwargs) | MoveXY(self, int x, int y) | MoveXY(self, int x, int y) | [
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SmileiPIC/Smilei | 07dcb51200029e10f626e1546558c1ae7599c8b1 | validation/easi/machines/irene.py | python | MachineIrene.run | (self, arguments, dir) | Run a simulation | Run a simulation | [
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"""
Run a simulation
"""
from math import ceil
command = self.RUN_COMMAND % arguments
if self.options.nodes:
self.NODES = self.options.nodes
else:
self.NODES = int(ceil(self.options.mpi/2.))
ppn = 24
with open(self.smilei_path.exec_script, 'w') as f:
f.write( self.script.format(command=command, env=self.env, account=self.options.account, nodes=NODES, ppn=ppn, max_time=self.options.max_time, mpi=self.options.mpi, omp=self.options.omp, dir=dir) )
self.launch_job(command, self.JOB, dir, self.options.max_time_seconds, self.smilei_path.output_file, repeat=2) | [
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ApolloAuto/apollo-platform | 86d9dc6743b496ead18d597748ebabd34a513289 | ros/genpy/src/genpy/generator.py | python | string_serializer_generator | (package, type_, name, serialize) | Generator for string types. similar to arrays, but with more
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Generator for string types. similar to arrays, but with more
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:param name: spec field name, ``str``
:param serialize: if ``True``, generate code for
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# don't optimize in deserialization case as assignment doesn't
# work
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# optimize as string serialization accesses field twice
yield "_x = %s%s"%(_serial_context, name)
var = "_x"
else:
var = _serial_context+name
# the length generator is a noop if serialize is True as we
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base_type, is_array, array_len = genmsg.msgs.parse_type(type_)
# - don't serialize length for fixed-length arrays of bytes
if base_type not in ['uint8', 'char'] or array_len is None:
for y in len_serializer_generator(var, True, serialize):
yield y #serialize string length
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#serialize length and string together
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base_type, is_array, array_len = genmsg.msgs.parse_type(type_)
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if array_len is None:
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yield INDENT+"%s = %s.encode('utf-8')"%(var,var) #For unicode-strings in Python2, encode using utf-8
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mantidproject/mantid | 03deeb89254ec4289edb8771e0188c2090a02f32 | qt/python/mantidqtinterfaces/mantidqtinterfaces/HFIR_4Circle_Reduction/peak_integration_utility.py | python | gaussian_peak_intensity | (parameter_dict, error_dict) | return peak_intensity, intensity_error | calculate peak intensity as a Gaussian
the equation to calculate Gaussian from -infinity to +infinity is
I = A\times s\times\\sqrt{2\\pi}
:param parameter_dict:
:param error_dict:
:return: | calculate peak intensity as a Gaussian
the equation to calculate Gaussian from -infinity to +infinity is
I = A\times s\times\\sqrt{2\\pi}
:param parameter_dict:
:param error_dict:
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"""
calculate peak intensity as a Gaussian
the equation to calculate Gaussian from -infinity to +infinity is
I = A\times s\times\\sqrt{2\\pi}
:param parameter_dict:
:param error_dict:
:return:
"""
# check input
assert isinstance(parameter_dict, dict), 'Parameters {0} must be given as a dictionary but not a {1}.' \
''.format(parameter_dict, type(parameter_dict))
assert isinstance(error_dict, dict), 'Errors {0} must be given as a dictionary but not a {1}.' \
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# get the parameters from the dictionary
try:
gauss_a = parameter_dict['A']
gauss_sigma = parameter_dict['s']
except KeyError as key_err:
raise RuntimeError('Parameter dictionary must have "A", "s" (for sigma) but now only {0}. Error message: {1}'
''.format(parameter_dict.keys(), key_err))
# I = A\times s\times\sqrt{2 pi}
peak_intensity = gauss_a * gauss_sigma * numpy.sqrt(2. * numpy.pi)
# calculate error
# \sigma_I^2 = 2\pi (A^2\cdot \sigma_s^2 + \sigma_A^2\cdot s^2 + 2\cdot A\cdot s\cdot \sigma_{As})
try:
error_a_sq = error_dict['A2']
error_s_sq = error_dict['s2']
error_a_s = error_dict['A_s']
except KeyError as key_err:
raise RuntimeError('Error dictionary must have "A2", "s2", "A_s" but not only found {0}. FYI: {1}'
''.format(error_dict.keys(), key_err))
intensity_error = numpy.sqrt(2/numpy.pi * (gauss_a**2 * error_s_sq + error_a_sq * gauss_sigma**2
+ 2 * gauss_a * gauss_sigma * error_a_s))
return peak_intensity, intensity_error | [
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yyzybb537/libgo | 4af17b7c67643c4d54aa354dcc77963ea07847d0 | third_party/boost.context/tools/build/src/build/feature.py | python | validate_value_string | (f, value_string) | Checks that value-string is a valid value-string for the given feature. | Checks that value-string is a valid value-string for the given feature. | [
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"""
assert isinstance(f, Feature)
assert isinstance(value_string, basestring)
if f.free() or value_string in f.values():
return
values = [value_string]
if f.subfeatures():
if not value_string in f.values() and \
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values = value_string.split('-')
# An empty value is allowed for optional features
if not values[0] in f.values() and \
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raise InvalidValue ("'%s' is not a known value of feature '%s'\nlegal values: '%s'" % (values [0], f.name(), f.values()))
for v in values [1:]:
# this will validate any subfeature values in value-string
implied_subfeature(f, v, values[0]) | [
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Yelp/MOE | 5b5a6a2c6c3cf47320126f7f5894e2a83e347f5c | moe/optimal_learning/python/interfaces/log_likelihood_interface.py | python | GaussianProcessLogLikelihoodInterface.get_hyperparameters | (self) | Get the hyperparameters (array of float64 with shape (num_hyperparameters)) of this covariance. | Get the hyperparameters (array of float64 with shape (num_hyperparameters)) of this covariance. | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_cocoa/_controls.py | python | ToolBarBase.AddSimpleTool | (self, id, bitmap,
shortHelpString = '',
longHelpString = '',
isToggle = 0) | return self.DoAddTool(id, '', bitmap, wx.NullBitmap, kind,
shortHelpString, longHelpString, None) | Old style method to add a tool to the toolbar. | Old style method to add a tool to the toolbar. | [
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shortHelpString = '',
longHelpString = '',
isToggle = 0):
'''Old style method to add a tool to the toolbar.'''
kind = wx.ITEM_NORMAL
if isToggle: kind = wx.ITEM_CHECK
return self.DoAddTool(id, '', bitmap, wx.NullBitmap, kind,
shortHelpString, longHelpString, None) | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_cocoa/richtext.py | python | RichTextFileHandler.CanLoad | (*args, **kwargs) | return _richtext.RichTextFileHandler_CanLoad(*args, **kwargs) | CanLoad(self) -> bool | CanLoad(self) -> bool | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_carbon/_core.py | python | GridSizer.GetEffectiveRowsCount | (*args, **kwargs) | return _core_.GridSizer_GetEffectiveRowsCount(*args, **kwargs) | GetEffectiveRowsCount(self) -> int | GetEffectiveRowsCount(self) -> int | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_carbon/grid.py | python | GridCellAttr.__init__ | (self, *args, **kwargs) | __init__(self, GridCellAttr attrDefault=None) -> GridCellAttr | __init__(self, GridCellAttr attrDefault=None) -> GridCellAttr | [
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"""__init__(self, GridCellAttr attrDefault=None) -> GridCellAttr"""
_grid.GridCellAttr_swiginit(self,_grid.new_GridCellAttr(*args, **kwargs))
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fnplus/interview-techdev-guide | eaca1b6db4b27e9813aaec25a199b1baa4f9439b | Algorithms/Searching & Sorting/Exponential Search/exponential_search.py | python | binary_search | (arr, s, e, x) | return -1 | #arr: the array in which we need to find an element (sorted, increasing order)
#s: start index
#e: end index
#x: element we are looking for | #arr: the array in which we need to find an element (sorted, increasing order)
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#search until arr becomes empty []
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elif x<arr[m]: #if x<arr[m] search only in the left array
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tensorflow/tensorflow | 419e3a6b650ea4bd1b0cba23c4348f8a69f3272e | tensorflow/python/framework/function.py | python | _get_kwarg_as_str_attr | (attr_name, value) | Creates an AttrValue for a python object. | Creates an AttrValue for a python object. | [
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if isinstance(value, str):
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nasa/fprime | 595cf3682d8365943d86c1a6fe7c78f0a116acf0 | Autocoders/Python/src/fprime_ac/generators/visitors/SerialCppVisitor.py | python | SerialCppVisitor.publicVisit | (self, obj) | Defined to generate public stuff within a class.
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c.name = obj.get_name()
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c.args_scalar_array_string = self._get_args_proto_string_scalar_init(obj)
c.members = self._get_conv_mem_list(obj)
self._writeTmpl(c, "publicVisit") | [
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pisa-engine/pisa | 0efb7926d4928c8aae672ba4d7a1419891f2676d | script/ext/baker.py | python | Baker.apply | (self, scriptname, cmd, args, kwargs, instance=None) | return cmd.fn(*newargs, **newkwargs) | Calls the command function. | Calls the command function. | [
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"""
Calls the command function.
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# Create a list of positional arguments: arguments that are either
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# Rearrange the arguments into the order Python expects
newargs = []
newkwargs = kwargs.copy()
for name in cmd.argnames:
if name in cmd.keywords:
if not args:
break
# keyword arg
if cmd.has_varargs:
# keyword params are not replaced by bare args if the func
# also has varags but they must be specified as positional
# args for proper processing of varargs
value = cmd.keywords[name]
if name in newkwargs:
value = newkwargs[name]
del newkwargs[name]
newargs.append(value)
elif not name in newkwargs:
newkwargs[name] = args.pop(0)
else:
# positional arg
if name in newkwargs:
newargs.append(newkwargs[name])
del newkwargs[name]
else:
if args:
newargs.append(args.pop(0))
else:
# This argument is required but we don't have a bare
# arg to fill it
msg = "Required argument %r not given"
raise CommandError(msg % (name), scriptname, cmd)
if args:
if cmd.has_varargs:
newargs.extend(args)
else:
msg = "Too many arguments to %r: %s"
raise CommandError(msg % (cmd.name, args), scriptname, cmd)
if not cmd.has_kwargs:
for k in newkwargs:
if k not in cmd.keywords:
raise CommandError("Unknown option --%s" % k,
scriptname, cmd)
if cmd.is_method and instance is not None:
return cmd.fn(instance, *newargs, **newkwargs)
return cmd.fn(*newargs, **newkwargs) | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_carbon/stc.py | python | StyledTextCtrl.GetPunctuationChars | (*args, **kwargs) | return _stc.StyledTextCtrl_GetPunctuationChars(*args, **kwargs) | GetPunctuationChars(self) -> String | GetPunctuationChars(self) -> String | [
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"""GetPunctuationChars(self) -> String"""
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cms-sw/cmssw | fd9de012d503d3405420bcbeec0ec879baa57cf2 | DQMServices/Components/python/HTTP.py | python | RequestManager.put | (self, task) | Add a new task. The task object should be a tuple and is
passed to ``request_init`` callback passed to the constructor. | Add a new task. The task object should be a tuple and is
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"""Add a new task. The task object should be a tuple and is
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self.queue.append(task) | [
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mongodb/mongo | d8ff665343ad29cf286ee2cf4a1960d29371937b | buildscripts/idl/idl/syntax.py | python | SymbolTable.add_struct | (self, ctxt, struct) | Add an IDL struct to the symbol table and check for duplicates. | Add an IDL struct to the symbol table and check for duplicates. | [
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# type: (errors.ParserContext, Struct) -> None
"""Add an IDL struct to the symbol table and check for duplicates."""
if not self._is_duplicate(ctxt, struct, struct.name, "struct"):
self.structs.append(struct) | [
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krishauser/Klampt | 972cc83ea5befac3f653c1ba20f80155768ad519 | Python/python2_version/klampt/robotsim.py | python | Simulator.getStatus | (self) | return _robotsim.Simulator_getStatus(self) | getStatus(Simulator self) -> int
Returns an indicator code for the simulator status. The return result is one of
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"""
getStatus(Simulator self) -> int
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return _robotsim.Simulator_getStatus(self) | [
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SequoiaDB/SequoiaDB | 2894ed7e5bd6fe57330afc900cf76d0ff0df9f64 | tools/server/php_linux/libxml2/lib/python2.4/site-packages/libxml2.py | python | xpathParserContext.xpathNamespaceURIFunction | (self, nargs) | Implement the namespace-uri() XPath function string
namespace-uri(node-set?) The namespace-uri function returns
a string containing the namespace URI of the expanded name
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defaults to the context node. | Implement the namespace-uri() XPath function string
namespace-uri(node-set?) The namespace-uri function returns
a string containing the namespace URI of the expanded name
of the node in the argument node-set that is first in
document order. If the node-set is empty, the first node
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"""Implement the namespace-uri() XPath function string
namespace-uri(node-set?) The namespace-uri function returns
a string containing the namespace URI of the expanded name
of the node in the argument node-set that is first in
document order. If the node-set is empty, the first node
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libxml2mod.xmlXPathNamespaceURIFunction(self._o, nargs) | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/tools/python/src/Lib/lib2to3/pgen2/driver.py | python | Driver.parse_tokens | (self, tokens, debug=False) | return p.rootnode | Parse a series of tokens and return the syntax tree. | Parse a series of tokens and return the syntax tree. | [
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] | def parse_tokens(self, tokens, debug=False):
"""Parse a series of tokens and return the syntax tree."""
# XXX Move the prefix computation into a wrapper around tokenize.
p = parse.Parser(self.grammar, self.convert)
p.setup()
lineno = 1
column = 0
type = value = start = end = line_text = None
prefix = u""
for quintuple in tokens:
type, value, start, end, line_text = quintuple
if start != (lineno, column):
assert (lineno, column) <= start, ((lineno, column), start)
s_lineno, s_column = start
if lineno < s_lineno:
prefix += "\n" * (s_lineno - lineno)
lineno = s_lineno
column = 0
if column < s_column:
prefix += line_text[column:s_column]
column = s_column
if type in (tokenize.COMMENT, tokenize.NL):
prefix += value
lineno, column = end
if value.endswith("\n"):
lineno += 1
column = 0
continue
if type == token.OP:
type = grammar.opmap[value]
if debug:
self.logger.debug("%s %r (prefix=%r)",
token.tok_name[type], value, prefix)
if p.addtoken(type, value, (prefix, start)):
if debug:
self.logger.debug("Stop.")
break
prefix = ""
lineno, column = end
if value.endswith("\n"):
lineno += 1
column = 0
else:
# We never broke out -- EOF is too soon (how can this happen???)
raise parse.ParseError("incomplete input",
type, value, (prefix, start))
return p.rootnode | [
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