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Tencent/CMONGO | c40380caa14e05509f46993aa8b8da966b09b0b5 | src/third_party/scons-2.5.0/scons-local-2.5.0/SCons/Tool/__init__.py | python | _call_linker_cb | (env, callback, args, result = None) | return result | Returns the result of env['LINKCALLBACKS'][callback](*args)
if env['LINKCALLBACKS'] is a dictionary and env['LINKCALLBACKS'][callback]
is callable. If these conditions are not met, return the value provided as
the *result* argument. This function is mainly used for generating library
info such as versioned suffixes, symlink maps, sonames etc. by delegating
the core job to callbacks configured by current linker tool | Returns the result of env['LINKCALLBACKS'][callback](*args)
if env['LINKCALLBACKS'] is a dictionary and env['LINKCALLBACKS'][callback]
is callable. If these conditions are not met, return the value provided as
the *result* argument. This function is mainly used for generating library
info such as versioned suffixes, symlink maps, sonames etc. by delegating
the core job to callbacks configured by current linker tool | [
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] | def _call_linker_cb(env, callback, args, result = None):
"""Returns the result of env['LINKCALLBACKS'][callback](*args)
if env['LINKCALLBACKS'] is a dictionary and env['LINKCALLBACKS'][callback]
is callable. If these conditions are not met, return the value provided as
the *result* argument. This function is mainly used for generating library
info such as versioned suffixes, symlink maps, sonames etc. by delegating
the core job to callbacks configured by current linker tool"""
Verbose = False
if Verbose:
print '_call_linker_cb: args=%r' % args
print '_call_linker_cb: callback=%r' % callback
try:
cbfun = env['LINKCALLBACKS'][callback]
except (KeyError, TypeError):
if Verbose:
print '_call_linker_cb: env["LINKCALLBACKS"][%r] not found or can not be used' % callback
pass
else:
if Verbose:
print '_call_linker_cb: env["LINKCALLBACKS"][%r] found' % callback
print '_call_linker_cb: env["LINKCALLBACKS"][%r]=%r' % (callback, cbfun)
if(callable(cbfun)):
if Verbose:
print '_call_linker_cb: env["LINKCALLBACKS"][%r] is callable' % callback
result = cbfun(env, *args)
return result | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/statistics.py | python | pvariance | (data, mu=None) | return _convert(ss/n, T) | Return the population variance of ``data``.
data should be an iterable of Real-valued numbers, with at least one
value. The optional argument mu, if given, should be the mean of
the data. If it is missing or None, the mean is automatically calculated.
Use this function to calculate the variance from the entire population.
To estimate the variance from a sample, the ``variance`` function is
usually a better choice.
Examples:
>>> data = [0.0, 0.25, 0.25, 1.25, 1.5, 1.75, 2.75, 3.25]
>>> pvariance(data)
1.25
If you have already calculated the mean of the data, you can pass it as
the optional second argument to avoid recalculating it:
>>> mu = mean(data)
>>> pvariance(data, mu)
1.25
This function does not check that ``mu`` is actually the mean of ``data``.
Giving arbitrary values for ``mu`` may lead to invalid or impossible
results.
Decimals and Fractions are supported:
>>> from decimal import Decimal as D
>>> pvariance([D("27.5"), D("30.25"), D("30.25"), D("34.5"), D("41.75")])
Decimal('24.815')
>>> from fractions import Fraction as F
>>> pvariance([F(1, 4), F(5, 4), F(1, 2)])
Fraction(13, 72) | Return the population variance of ``data``. | [
"Return",
"the",
"population",
"variance",
"of",
"data",
"."
] | def pvariance(data, mu=None):
"""Return the population variance of ``data``.
data should be an iterable of Real-valued numbers, with at least one
value. The optional argument mu, if given, should be the mean of
the data. If it is missing or None, the mean is automatically calculated.
Use this function to calculate the variance from the entire population.
To estimate the variance from a sample, the ``variance`` function is
usually a better choice.
Examples:
>>> data = [0.0, 0.25, 0.25, 1.25, 1.5, 1.75, 2.75, 3.25]
>>> pvariance(data)
1.25
If you have already calculated the mean of the data, you can pass it as
the optional second argument to avoid recalculating it:
>>> mu = mean(data)
>>> pvariance(data, mu)
1.25
This function does not check that ``mu`` is actually the mean of ``data``.
Giving arbitrary values for ``mu`` may lead to invalid or impossible
results.
Decimals and Fractions are supported:
>>> from decimal import Decimal as D
>>> pvariance([D("27.5"), D("30.25"), D("30.25"), D("34.5"), D("41.75")])
Decimal('24.815')
>>> from fractions import Fraction as F
>>> pvariance([F(1, 4), F(5, 4), F(1, 2)])
Fraction(13, 72)
"""
if iter(data) is data:
data = list(data)
n = len(data)
if n < 1:
raise StatisticsError('pvariance requires at least one data point')
T, ss = _ss(data, mu)
return _convert(ss/n, T) | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/gtk/_core.py | python | Window.AddChild | (*args, **kwargs) | return _core_.Window_AddChild(*args, **kwargs) | AddChild(self, Window child)
Adds a child window. This is called automatically by window creation
functions so should not be required by the application programmer. | AddChild(self, Window child) | [
"AddChild",
"(",
"self",
"Window",
"child",
")"
] | def AddChild(*args, **kwargs):
"""
AddChild(self, Window child)
Adds a child window. This is called automatically by window creation
functions so should not be required by the application programmer.
"""
return _core_.Window_AddChild(*args, **kwargs) | [
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google/earthenterprise | 0fe84e29be470cd857e3a0e52e5d0afd5bb8cee9 | earth_enterprise/src/fusion/portableglobe/cutter/cgi-bin/common/portable_globe.py | python | Globe.HasImagery | (self) | return self.has_imagery_ | Returns whether glx has imagery. | Returns whether glx has imagery. | [
"Returns",
"whether",
"glx",
"has",
"imagery",
"."
] | def HasImagery(self):
"""Returns whether glx has imagery."""
return self.has_imagery_ | [
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DanielSWolf/rhubarb-lip-sync | 5cface0af3b6e4e58c0b829c51561d784fb9f52f | rhubarb/lib/webrtc-8d2248ff/webrtc/tools/barcode_tools/barcode_decoder.py | python | decode_frames | (input_directory, zxing_path) | return helper_functions.perform_action_on_all_files(
directory=input_directory, file_pattern='frame_',
file_extension='png', start_number=1, action=_decode_barcode_in_file,
command_line_decoder=zxing_path) | Decodes the barcodes overlaid in each frame.
The function uses the Zxing command-line tool from the Zxing C++ distribution
to decode the barcode in every PNG frame from the input directory. The frames
should be named frame_xxxx.png, where xxxx is the frame number. The frame
numbers should be consecutive and should start from 0001.
The decoding results in a frame_xxxx.txt file for every successfully decoded
barcode. This file contains the decoded barcode as 12-digit string (UPC-A
format: 11 digits content + one check digit).
Args:
input_directory(string): The input directory from where the PNG frames are
read.
zxing_path(string): The path to the zxing binary. If specified as None,
the PATH will be searched for it.
Return:
(bool): True if the decoding succeeded. | Decodes the barcodes overlaid in each frame. | [
"Decodes",
"the",
"barcodes",
"overlaid",
"in",
"each",
"frame",
"."
] | def decode_frames(input_directory, zxing_path):
"""Decodes the barcodes overlaid in each frame.
The function uses the Zxing command-line tool from the Zxing C++ distribution
to decode the barcode in every PNG frame from the input directory. The frames
should be named frame_xxxx.png, where xxxx is the frame number. The frame
numbers should be consecutive and should start from 0001.
The decoding results in a frame_xxxx.txt file for every successfully decoded
barcode. This file contains the decoded barcode as 12-digit string (UPC-A
format: 11 digits content + one check digit).
Args:
input_directory(string): The input directory from where the PNG frames are
read.
zxing_path(string): The path to the zxing binary. If specified as None,
the PATH will be searched for it.
Return:
(bool): True if the decoding succeeded.
"""
if not zxing_path:
zxing_path = 'zxing.exe' if sys.platform == 'win32' else 'zxing'
print 'Decoding barcodes from PNG files with %s...' % zxing_path
return helper_functions.perform_action_on_all_files(
directory=input_directory, file_pattern='frame_',
file_extension='png', start_number=1, action=_decode_barcode_in_file,
command_line_decoder=zxing_path) | [
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root-project/root | fcd3583bb14852bf2e8cd2415717cbaac0e75896 | interpreter/llvm/src/utils/benchmark/tools/gbench/report.py | python | color_format | (use_color, fmt_str, *args, **kwargs) | return fmt_str.format(*args, **kwargs) | Return the result of 'fmt_str.format(*args, **kwargs)' after transforming
'args' and 'kwargs' according to the value of 'use_color'. If 'use_color'
is False then all color codes in 'args' and 'kwargs' are replaced with
the empty string. | Return the result of 'fmt_str.format(*args, **kwargs)' after transforming
'args' and 'kwargs' according to the value of 'use_color'. If 'use_color'
is False then all color codes in 'args' and 'kwargs' are replaced with
the empty string. | [
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] | def color_format(use_color, fmt_str, *args, **kwargs):
"""
Return the result of 'fmt_str.format(*args, **kwargs)' after transforming
'args' and 'kwargs' according to the value of 'use_color'. If 'use_color'
is False then all color codes in 'args' and 'kwargs' are replaced with
the empty string.
"""
assert use_color is True or use_color is False
if not use_color:
args = [arg if not isinstance(arg, BenchmarkColor) else BC_NONE
for arg in args]
kwargs = {key: arg if not isinstance(arg, BenchmarkColor) else BC_NONE
for key, arg in kwargs.items()}
return fmt_str.format(*args, **kwargs) | [
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AutoRally/autorally | 48bae14fe4b2d56e5ca11fd2fec3d7dfac7a0e75 | autorally_gazebo/nodes/autorally_controller.py | python | AutoRallyCtrlr.spin | (self) | Control the vehicle. | Control the vehicle. | [
"Control",
"the",
"vehicle",
"."
] | def spin(self):
"""Control the vehicle."""
last_time = rospy.get_time()
while not rospy.is_shutdown():
t = rospy.get_time()
delta_t = t - last_time
last_time = t
frontBrake = 0.0;
speed = 0.0;
chassisSt = chassisState()
chassisSt.runstopMotionEnabled = self.getrunstop();
if (self._cmd_timeout > 0.0 and
t - self._last_cmd_time > self._cmd_timeout):
# Too much time has elapsed since the last command. Stop the
# vehicle.
steer_ang_changed, center_y = \
self._ctrl_steering(self._last_steer_ang, 0.0, 0.001)
self._ctrl_axles(0.0, 0.0, 0.0, steer_ang_changed, center_y)
elif delta_t > 0.0:
with self.chassisCmdLock:
foundSteering = False
foundThrottle = False
foundFrontBrake = False
steer_ang = 0.0
steer_ang_vel = 0.0
foundSteering = False
accel = 0.0
if not chassisSt.runstopMotionEnabled:
chassisSt.throttle = 0.0;
chassisSt.throttleCommander = 'runstop';
foundThrottle = True
for cmd,priority in self.commandPriorities:
#rospy.logwarn("looking for chassis commander %s with priority %d", cmd, priority)
if cmd in self.chassisCmds:
if abs(self.chassisCmds[cmd].steering) <= 1.0 and \
(rospy.Time.now()-self.chassisCmds[cmd].header.stamp) < \
rospy.Duration.from_sec(0.2) and\
not foundSteering:
#rospy.loginfo("%s in control of steering", cmd);
steer_ang = -math.radians(25)*self.chassisCmds[cmd].steering
steer_ang_vel = 0.0
chassisSt.steering = self.chassisCmds[cmd].steering
chassisSt.steeringCommander = self.chassisCmds[cmd].sender
foundSteering = True
if abs(self.chassisCmds[cmd].throttle) <= 1.0 and \
(rospy.Time.now()-self.chassisCmds[cmd].header.stamp) < \
rospy.Duration.from_sec(0.2) and\
not foundThrottle:
#rospy.loginfo("%s in control of throttle", cmd);
if self.chassisCmds[cmd].throttle >= 0.0:
speed = self.rear_axle_max_effort*self.chassisCmds[cmd].throttle
else:
speed = self.rear_axle_brake_effort*self.chassisCmds[cmd].throttle
accel = 0.0
chassisSt.throttle = self.chassisCmds[cmd].throttle
chassisSt.throttleCommander = self.chassisCmds[cmd].sender
foundThrottle = True
if self.chassisCmds[cmd].frontBrake >= 0.0 and \
self.chassisCmds[cmd].frontBrake <= 1.0 and \
(rospy.Time.now()-self.chassisCmds[cmd].header.stamp) < \
rospy.Duration.from_sec(0.2) and\
not foundFrontBrake:
#the brake acts to slow any movement
frontBrake = numpy.sign(self.wheelSpeedFront)*(-self.front_axle_brake_effort*self.chassisCmds[cmd].frontBrake)
chassisSt.frontBrake = self.chassisCmds[cmd].frontBrake
chassisSt.frontBrakeCommander = self.chassisCmds[cmd].sender
foundFrontBrake = True
else:
frontBrake = 0
steer_ang_changed, center_y = self._ctrl_steering(steer_ang, steer_ang_vel, delta_t)
self._ctrl_axles(speed, accel, delta_t, steer_ang_changed, center_y)
# Publish the steering and axle joint commands.
chassisSt.header.stamp = rospy.Time.now()
self.chassisStatePub.publish(chassisSt)
self._left_steer_cmd_pub.publish(self._theta_left)
self._right_steer_cmd_pub.publish(self._theta_right)
if self._left_front_axle_cmd_pub:
self._left_front_axle_cmd_pub.publish(frontBrake)
if self._right_front_axle_cmd_pub:
self._right_front_axle_cmd_pub.publish(frontBrake)
if self._left_rear_axle_cmd_pub:
self._left_rear_axle_cmd_pub.publish(speed)
if self._right_rear_axle_cmd_pub:
self._right_rear_axle_cmd_pub.publish(speed)
try:
self._sleep_timer.sleep()
except rospy.exceptions.ROSTimeMovedBackwardsException:
continue | [
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MegaGlest/megaglest-source | e3af470288a3c9cc179f63b5a1eb414a669e3772 | mk/linux/symbolstore.py | python | Dumper.GlobalInit | (cls, module=multiprocessing) | Initialize the class globals for the multiprocessing setup; must
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wlanjie/AndroidFFmpeg | 7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf | tools/fdk-aac-build/armeabi-v7a/toolchain/lib/python2.7/lib-tk/ttk.py | python | Treeview.move | (self, item, parent, index) | Moves item to position index in parent's list of children.
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RamadhanAmizudin/malware | 2c6c53c8b0d556f5d8078d6ca0fc4448f4697cf1 | Fuzzbunch/fuzzbunch/command.py | python | FbCmd.do_help | (self, input) | Print out help | Print out help | [
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ApolloAuto/apollo-platform | 86d9dc6743b496ead18d597748ebabd34a513289 | ros/third_party/lib_x86_64/python2.7/dist-packages/geodesy/utm.py | python | UTMPoint.toPoint | (self) | return pt | :returns: corresponding `geometry_msgs/Point`_ message.
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/pandas/core/arrays/datetimelike.py | python | AttributesMixin._check_compatible_with | (
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/Jinja2/py3/jinja2/runtime.py | python | Undefined._undefined_message | (self) | return (
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/numba/datamodel/manager.py | python | DataModelManager.register | (self, fetypecls, handler) | Register the datamodel factory corresponding to a frontend-type class | Register the datamodel factory corresponding to a frontend-type class | [
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"""Register the datamodel factory corresponding to a frontend-type class
"""
assert issubclass(fetypecls, types.Type)
self._handlers[fetypecls] = handler | [
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gimli-org/gimli | 17aa2160de9b15ababd9ef99e89b1bc3277bbb23 | pygimli/physics/ert/ertScheme.py | python | DataSchemeBase.addInverse | (self, addInverse=False) | Add inverse value to create a full dataset. | Add inverse value to create a full dataset. | [
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] | def addInverse(self, addInverse=False):
"""
Add inverse value to create a full dataset.
"""
self.addInverse_ = addInverse | [
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benoitsteiner/tensorflow-opencl | cb7cb40a57fde5cfd4731bc551e82a1e2fef43a5 | tensorflow/python/ops/variable_scope.py | python | _PartitionInfo.single_slice_dim | (self, shape) | return slice_dim | Returns the slice dim when the variable is partitioned only in one dim.
Args:
shape: Tuple or list of `int` indicating the shape of one specific
variable partition.
Returns:
`int` representing the dimension that the variable is partitioned in, or
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Raises:
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ValueError: If `shape` is not the same length as `self.full_shape`. If
the variable is partitioned in more than one dimension. | Returns the slice dim when the variable is partitioned only in one dim. | [
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"""Returns the slice dim when the variable is partitioned only in one dim.
Args:
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variable partition.
Returns:
`int` representing the dimension that the variable is partitioned in, or
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Raises:
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"""
if not isinstance(shape, collections_lib.Sequence) or isinstance(
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raise TypeError(
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type(shape).__name__)
if len(shape) != len(self.full_shape):
raise ValueError(
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shape), self.full_shape, len(self.full_shape)))
for i in xrange(len(shape)):
if self.var_offset[i] + shape[i] > self.full_shape[i]:
raise ValueError(
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self.var_offset, shape, self.full_shape, i))
slice_dim = None
for i in xrange(len(shape)):
if shape[i] == self.full_shape[i]:
continue
if slice_dim is not None:
raise ValueError(
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slice_dim = i
return slice_dim | [
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Illumina/hap.py | 84011695b2ff2406c16a335106db6831fb67fdfe | src/python/Somatic/Strelka.py | python | extractStrelkaIndelFeatures | (vcfname, tag, avg_depth=None) | return df | Return a data frame with features collected from the given VCF, tagged by given type
:param vcfname: name of the VCF file
:param tag: type of variants
:param avg_depth: average chromosome depths from BAM file | Return a data frame with features collected from the given VCF, tagged by given type
:param vcfname: name of the VCF file
:param tag: type of variants
:param avg_depth: average chromosome depths from BAM file | [
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""" Return a data frame with features collected from the given VCF, tagged by given type
:param vcfname: name of the VCF file
:param tag: type of variants
:param avg_depth: average chromosome depths from BAM file
"""
features = ["CHROM", "POS", "REF", "ALT", "FILTER",
"I.NT", "I.SOMATIC", "I.QSI_NT", "I.EVS", "I.EVSF", "I.SomaticEVS",
"I.SGT", "I.RC", "I.RU",
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"S.1.TAR", "S.2.TAR",
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"S.1.TOR", "S.2.TOR",
"S.1.BCN50", "S.2.BCN50",
"S.1.FDP50", "S.2.FDP50",
]
cols = ["CHROM",
"POS",
"REF",
"ALT",
"LENGTH",
"INDELTYPE",
"FILTER",
"NT",
"NT_REF",
"EVS",
"QSI_NT",
"N_DP",
"T_DP",
"N_DP_RATE",
"T_DP_RATE",
"N_BCN",
"T_BCN",
"N_FDP",
"T_FDP",
"N_AF",
"T_AF",
"SGT",
"RC",
"RU",
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"IC",
"IHP",
"MQ",
"MQ0",
"tag"]
records = []
vcfheaders = list(extractHeaders(vcfname))
evs_featurenames = {}
for l in vcfheaders:
if '##indel_scoring_features' in l:
try:
xl = str(l).split('=', 1)
xl = xl[1].split(",")
for i, n in enumerate(xl):
evs_featurenames[i] = n
cols.append("E." + n)
logging.info("Scoring feature %i : %s" % (i, n))
except:
logging.warn("Could not parse scoring feature names from Strelka output")
if not avg_depth:
avg_depth = {}
for l in vcfheaders:
x = str(l).lower()
x = x.replace("##meandepth_", "##maxdepth_")
x = x.replace("##depth_", "##maxdepth_")
if '##maxdepth_' in x:
p, _, l = l.partition("_")
xl = str(l).split('=')
xchr = xl[0]
avg_depth[xchr] = float(xl[1])
logging.info("%s depth from VCF header is %f" % (xchr, avg_depth[xchr]))
has_warned = {}
for vr in vcfExtract(vcfname, features):
rec = {}
for i, ff in enumerate(features):
rec[ff] = vr[i]
rec["tag"] = tag
if "I.SomaticEVS" in rec:
try:
rec["I.EVS"] = float(rec["I.SomaticEVS"])
except:
rec["I.EVS"] = -1.0
else:
try:
rec["I.EVS"] = float(rec["I.EVS"])
except:
rec["I.EVS"] = -1.0
# fix missing features
for q in ["I.QSI_NT", "I.RC", "I.IC", "I.IHP",
"S.1.DP", "S.2.DP",
"S.1.BCN50", "S.2.BCN50",
"S.1.FDP50", "S.2.FDP50"]:
if q not in rec or rec[q] is None:
rec[q] = 0
if not ("feat:" + q) in has_warned:
logging.warn("Missing feature %s" % q)
has_warned["feat:" + q] = True
for q in ["S.1.TAR", "S.2.TAR",
"S.1.TIR", "S.2.TIR",
"S.1.TOR", "S.2.TOR"]:
if q not in rec or rec[q] is None:
rec[q] = [0, 0]
if not ("feat:" + q) in has_warned:
logging.warn("Missing feature %s" % q)
has_warned["feat:" + q] = True
NT = rec["I.NT"]
NT_is_ref = int(NT == "ref")
QSI_NT = int(rec["I.QSI_NT"])
n_DP = float(rec["S.1.DP"])
t_DP = float(rec["S.2.DP"])
in_del = 0
max_len = len(rec["REF"])
min_len = len(rec["REF"])
for a in rec["ALT"]:
if len(a) > len(rec["REF"]):
in_del |= 1
else:
in_del |= 2
min_len = min(len(a), min_len)
max_len = max(len(a), max_len)
ilen = max_len - min_len
n_DP_ratio = 0
t_DP_ratio = 0
if avg_depth:
try:
n_DP_ratio = n_DP / float(avg_depth[rec["CHROM"]])
t_DP_ratio = t_DP / float(avg_depth[rec["CHROM"]])
except:
if not rec["CHROM"] in has_warned:
logging.warn("Cannot normalize depths on %s" % rec["CHROM"])
has_warned[rec["CHROM"]] = True
elif "DPnorm" not in has_warned:
logging.warn("Cannot normalize depths.")
has_warned["DPnorm"] = True
# extract observed AF from strelka counts. TIR = ALT; TAR = REF
try:
n_af = float(rec["S.1.TIR"][0]) / (float(rec["S.1.TIR"][0]) + float(rec["S.1.TAR"][0]))
except:
n_af = 0
try:
t_af = float(rec["S.2.TIR"][0]) / (float(rec["S.2.TIR"][0]) + float(rec["S.2.TAR"][0]))
except:
t_af = 0
# Gather the computed data into a dict
qrec = {
"CHROM": rec["CHROM"],
"POS": int(rec["POS"]),
"REF": rec["REF"],
"ALT": ",".join(rec["ALT"]),
"LENGTH": ilen,
"INDELTYPE": in_del,
"FILTER": ",".join(rec["FILTER"]),
"NT": NT,
"NT_REF": NT_is_ref,
"QSI_NT": QSI_NT,
"N_DP": n_DP,
"T_DP": t_DP,
"N_DP_RATE": n_DP_ratio,
"T_DP_RATE": t_DP_ratio,
"N_AF": n_af,
"T_AF": t_af,
"SGT": rec["I.SGT"],
"tag": tag
}
# fields with defaults
fields = [
{"n": "EVS", "s": "I.EVS", "def": 0, "t": float},
{"n": "VQSR", "s": "I.VQSR", "def": 0, "t": float},
{"n": "RC", "s": "I.RC", "def": 0, "t": int},
{"n": "RU", "s": "I.RU", "def": ""},
{"n": "RU_LEN", "s": "I.RU", "def": 0, "t": len},
{"n": "IC", "s": "I.IC", "def": 0, "t": int},
{"n": "IHP", "s": "I.IHP", "def": 0, "t": int},
{"n": "MQ", "s": "I.MQ", "def": 0.0, "t": float},
{"n": "MQ0", "s": "I.MQ0", "def": 0.0, "t": float},
{"n": "N_BCN", "s": "S.1.BCN50", "def": 0.0, "t": float},
{"n": "T_BCN", "s": "S.2.BCN50", "def": 0.0, "t": float},
{"n": "N_FDP", "s": "S.1.FDP50", "def": 0.0, "t": float},
{"n": "T_FDP", "s": "S.2.FDP50", "def": 0.0, "t": float},
]
for fd in fields:
try:
res = rec[fd["s"]]
if "t" in fd:
res = fd["t"](res)
except:
res = fd["def"]
qrec[fd["n"]] = res
# ESF features
try:
for i, v in enumerate(rec["I.EVSF"]):
if i in evs_featurenames:
try:
qrec["E." + evs_featurenames[i]] = float(v)
except:
# failure to parse
pass
except:
pass
for k, v in evs_featurenames.iteritems():
if not "E." + v in qrec:
qrec["E." + v] = 0
records.append(qrec)
if records:
df = pandas.DataFrame(records, columns=cols)
else:
df = pandas.DataFrame(columns=cols)
return df | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemMetric/v1/AWS/python/windows/Lib/numba/pycc/platform.py | python | Toolchain.get_python_library_dirs | (self) | return list(self._py_lib_dirs) + self._math_info['library_dirs'] | Get the library directories necessary to link with Python. | Get the library directories necessary to link with Python. | [
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Get the library directories necessary to link with Python.
"""
return list(self._py_lib_dirs) + self._math_info['library_dirs'] | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | wx/tools/Editra/src/extern/aui/auibook.py | python | AuiTabCtrl.OnEraseBackground | (self, event) | Handles the ``wx.EVT_ERASE_BACKGROUND`` event for :class:`AuiTabCtrl`.
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facebook/proxygen | a9ca025af207787815cb01eee1971cd572c7a81e | build/fbcode_builder/shell_quoting.py | python | shell_quote | (s) | return (
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psi4/psi4 | be533f7f426b6ccc263904e55122899b16663395 | psi4/driver/qcdb/libmintsbasisset.py | python | BasisSet.zero_ao_basis_set | () | return BasisSet() | Returns an empty basis set object.
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hfinkel/llvm-project-cxxjit | 91084ef018240bbb8e24235ff5cd8c355a9c1a1e | lldb/examples/python/crashlog.py | python | Interactive.do_quit | (self, line) | return True | Quit command | Quit command | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/scikit-learn/py3/sklearn/mixture/_bayesian_mixture.py | python | BayesianGaussianMixture._estimate_wishart_tied | (self, nk, xk, sk) | Estimate the tied Wishart distribution parameters.
Parameters
----------
X : array-like, shape (n_samples, n_features)
nk : array-like, shape (n_components,)
xk : array-like, shape (n_components, n_features)
sk : array-like, shape (n_features, n_features) | Estimate the tied Wishart distribution parameters. | [
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_, n_features = xk.shape
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self.degrees_of_freedom_ = (
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_carbon/_core.py | python | MenuItem.GetFont | (*args, **kwargs) | return _core_.MenuItem_GetFont(*args, **kwargs) | GetFont(self) -> Font | GetFont(self) -> Font | [
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eclipse/omr | 056e7c9ce9d503649190bc5bd9931fac30b4e4bc | jitbuilder/apigen/cppgen.py | python | CppGenerator.get_impl_class_name | (self, c) | return "TR::{}".format(self.get_class_name(c)) | Returns the name of a given class in the JitBuilder implementation,
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/pathlib2/pathlib2/__init__.py | python | Path.write_text | (self, data, encoding=None, errors=None) | Open the file in text mode, write to it, and close the file. | Open the file in text mode, write to it, and close the file. | [
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google-coral/edgetpu | 5020de9386ff370dcc1f63291a2d0f98eeb98adb | edgetpu/learn/imprinting/engine.py | python | ImprintingEngine.__init__ | (self, model_path, keep_classes=False) | Args:
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self._num_classes = 0
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self._num_classes = tmp.total_output_array_size() | [
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Polidea/SiriusObfuscator | b0e590d8130e97856afe578869b83a209e2b19be | SymbolExtractorAndRenamer/lldb/scripts/Python/static-binding/lldb.py | python | SBDebugger.GetFormatForType | (self, *args) | return _lldb.SBDebugger_GetFormatForType(self, *args) | GetFormatForType(self, SBTypeNameSpecifier arg0) -> SBTypeFormat | GetFormatForType(self, SBTypeNameSpecifier arg0) -> SBTypeFormat | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/scikit-learn/py3/sklearn/externals/_pep562.py | python | Pep562.__getattr__ | (self, name) | Attempt to retrieve the attribute from the module, and if missing, use the overridden function if present. | Attempt to retrieve the attribute from the module, and if missing, use the overridden function if present. | [
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s9xie/hed | 94fb22f10cbfec8d84fbc0642b224022014b6bd6 | scripts/cpp_lint.py | python | _NestingState.InNamespaceBody | (self) | return self.stack and isinstance(self.stack[-1], _NamespaceInfo) | Check if we are currently one level inside a namespace body.
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deepmind/reverb | ef3c8f0be1b720a741d2dee335e15e44668c291a | reverb/trajectory_dataset.py | python | TrajectoryDataset.from_table_signature | (cls,
server_address: str,
table: str,
max_in_flight_samples_per_worker: int,
num_workers_per_iterator: int = -1,
max_samples_per_stream: int = -1,
rate_limiter_timeout_ms: int = -1,
get_signature_timeout_secs: Optional[int] = None,
max_samples: int = -1) | return cls(
server_address=server_address,
table=table,
shapes=shapes,
dtypes=dtypes,
max_in_flight_samples_per_worker=max_in_flight_samples_per_worker,
num_workers_per_iterator=num_workers_per_iterator,
max_samples_per_stream=max_samples_per_stream,
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max_samples=max_samples) | Constructs a TrajectoryDataset using the table's signature to infer specs.
Note: The target `Table` must specify a signature which represent the entire
trajectory (as opposed to a single timestep). See `Table.__init__`
(./server.py) for more details.
Args:
server_address: Address of gRPC ReverbService.
table: Table to read the signature and sample from.
max_in_flight_samples_per_worker: See __init__ for details.
num_workers_per_iterator: See __init__ for details.
max_samples_per_stream: See __init__ for details.
rate_limiter_timeout_ms: See __init__ for details.
get_signature_timeout_secs: Timeout in seconds to wait for server to
respond when fetching the table signature. By default no timeout is set
and the call will block indefinitely if the server does not respond.
max_samples: See __init__ for details.
Returns:
TrajectoryDataset using the specs defined by the table signature to build
`shapes` and `dtypes`.
Raises:
ValueError: If `table` does not exist on server at `server_address`.
ValueError: If `table` does not have a signature.
errors.DeadlineExceededError: If `get_signature_timeout_secs` provided and
exceeded.
ValueError: See __init__. | Constructs a TrajectoryDataset using the table's signature to infer specs. | [
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ValueError: If `table` does not have a signature.
errors.DeadlineExceededError: If `get_signature_timeout_secs` provided and
exceeded.
ValueError: See __init__.
"""
client = reverb_client.Client(server_address)
info = client.server_info(get_signature_timeout_secs)
if table not in info:
raise ValueError(
f'Server at {server_address} does not contain any table named '
f'{table}. Found: {", ".join(sorted(info.keys()))}.')
if not info[table].signature:
raise ValueError(
f'Table {table} at {server_address} does not have a signature.')
shapes = tree.map_structure(lambda x: x.shape, info[table].signature)
dtypes = tree.map_structure(lambda x: x.dtype, info[table].signature)
return cls(
server_address=server_address,
table=table,
shapes=shapes,
dtypes=dtypes,
max_in_flight_samples_per_worker=max_in_flight_samples_per_worker,
num_workers_per_iterator=num_workers_per_iterator,
max_samples_per_stream=max_samples_per_stream,
rate_limiter_timeout_ms=rate_limiter_timeout_ms,
max_samples=max_samples) | [
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wujixiu/helmet-detection | 8eff5c59ddfba5a29e0b76aeb48babcb49246178 | old-version/ssd_vgg.py | python | CaffeDetection.detect | (self, image_file, conf_thresh=0.2, topn=20) | return result | SSD detection | SSD detection | [
"SSD",
"detection"
] | def detect(self, image_file, conf_thresh=0.2, topn=20):
'''
SSD detection
'''
# set net to batch size of 1
# image_resize = 300
image = caffe.io.load_image(image_file)
self.net.blobs['data'].reshape(1, 3, self.image_resize, self.image_resize)
#Run the net and examine the top_k results
transformed_image = self.transformer.preprocess('data', image)
self.net.blobs['data'].data[...] = transformed_image
# Forward pass.
detections = self.net.forward()['detection_out']
# Parse the outputs.
det_label = detections[0,0,:,1]
det_conf = detections[0,0,:,2]
det_xmin = detections[0,0,:,3]
det_ymin = detections[0,0,:,4]
det_xmax = detections[0,0,:,5]
det_ymax = detections[0,0,:,6]
# Get detections with confidence higher than 0.6.
top_indices = [i for i, conf in enumerate(det_conf) if conf >= conf_thresh]
top_conf = det_conf[top_indices]
top_label_indices = det_label[top_indices].tolist()
top_labels = get_labelname(self.labelmap, top_label_indices)
top_xmin = det_xmin[top_indices]
top_ymin = det_ymin[top_indices]
top_xmax = det_xmax[top_indices]
top_ymax = det_ymax[top_indices]
result = []
for i in xrange(min(topn, top_conf.shape[0])):
xmin = top_xmin[i] # xmin = int(round(top_xmin[i] * image.shape[1]))
ymin = top_ymin[i] # ymin = int(round(top_ymin[i] * image.shape[0]))
xmax = top_xmax[i] # xmax = int(round(top_xmax[i] * image.shape[1]))
ymax = top_ymax[i] # ymax = int(round(top_ymax[i] * image.shape[0]))
score = top_conf[i]
label = int(top_label_indices[i])
label_name = top_labels[i]
result.append([xmin, ymin, xmax, ymax, label, score, label_name])
return result | [
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y123456yz/reading-and-annotate-mongodb-3.6 | 93280293672ca7586dc24af18132aa61e4ed7fcf | mongo/buildscripts/eslint.py | python | _lint_files | (eslint, files) | return True | Lint a list of files with ESLint | Lint a list of files with ESLint | [
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"ESLint"
] | def _lint_files(eslint, files):
"""Lint a list of files with ESLint
"""
eslint = ESLint(eslint, _get_build_dir())
lint_clean = parallel.parallel_process([os.path.abspath(f) for f in files], eslint.lint)
if not lint_clean:
print("ERROR: ESLint found errors. Run ESLint manually to see errors in "\
"files that were skipped")
sys.exit(1)
return True | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/pandas/py3/pandas/core/indexes/multi.py | python | MultiIndex._is_memory_usage_qualified | (self) | return any(f(level) for level in self._inferred_type_levels) | return a boolean if we need a qualified .info display | return a boolean if we need a qualified .info display | [
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] | def _is_memory_usage_qualified(self) -> bool:
"""return a boolean if we need a qualified .info display"""
def f(level):
return "mixed" in level or "string" in level or "unicode" in level
return any(f(level) for level in self._inferred_type_levels) | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | wx/tools/Editra/src/syntax/syndata.py | python | SyntaxDataBase.GetProperties | (self) | return list() | Get the Properties List
@return: list of tuples [('fold', '1'),] | Get the Properties List
@return: list of tuples [('fold', '1'),] | [
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"""Get the Properties List
@return: list of tuples [('fold', '1'),]
"""
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may0324/DeepCompression-caffe | 0aff6c1287bda4cfc7f378ed8a16524e1afabd8c | scripts/cpp_lint.py | python | _CppLintState.SetVerboseLevel | (self, level) | return last_verbose_level | Sets the module's verbosity, and returns the previous setting. | Sets the module's verbosity, and returns the previous setting. | [
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"""Sets the module's verbosity, and returns the previous setting."""
last_verbose_level = self.verbose_level
self.verbose_level = level
return last_verbose_level | [
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mindspore-ai/mindspore | fb8fd3338605bb34fa5cea054e535a8b1d753fab | mindspore/python/mindspore/nn/layer/normalization.py | python | _BatchNorm.__init__ | (self,
num_features,
eps=1e-5,
momentum=0.9,
affine=True,
gamma_init='ones',
beta_init='zeros',
moving_mean_init='zeros',
moving_var_init='ones',
use_batch_statistics=None,
device_num_each_group=1,
process_groups=0,
input_dims='2d',
data_format='NCHW') | Initialize _BatchNorm. | Initialize _BatchNorm. | [
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num_features,
eps=1e-5,
momentum=0.9,
affine=True,
gamma_init='ones',
beta_init='zeros',
moving_mean_init='zeros',
moving_var_init='ones',
use_batch_statistics=None,
device_num_each_group=1,
process_groups=0,
input_dims='2d',
data_format='NCHW'):
"""Initialize _BatchNorm."""
super(_BatchNorm, self).__init__()
validator.check_value_type('num_features', num_features, [int], self.cls_name)
if num_features < 1:
raise ValueError(f"For '{self.cls_name}', the 'num_features' must be at least 1, but got {num_features}.")
if momentum < 0 or momentum > 1:
raise ValueError(f"For '{self.cls_name}', the 'momentum' should be a number in range [0, 1], "
f"but got {momentum}.")
self.input_dims = input_dims
self.format = validator.check_string(data_format, ['NCHW', 'NHWC'], 'format', self.cls_name)
if context.get_context("device_target") != "GPU" and self.format == "NHWC":
raise ValueError(f"For '{self.cls_name}', the 'NHWC' format only support in GPU target, but got device "
f"target {context.get_context('device_target')}.")
self.use_batch_statistics = use_batch_statistics
if self.use_batch_statistics is not None and not isinstance(self.use_batch_statistics, bool):
raise ValueError(f"For '{self.cls_name}', the 'use_batch_statistics' should be a boolean value or None,"
f" but got {use_batch_statistics}.")
self.num_features = num_features
self.eps = eps
self.moving_mean = Parameter(initializer(
moving_mean_init, num_features), name="mean", requires_grad=False)
self.moving_variance = Parameter(initializer(
moving_var_init, num_features), name="variance", requires_grad=False)
self.gamma = Parameter(initializer(
gamma_init, num_features), name="gamma", requires_grad=affine)
self.beta = Parameter(initializer(
beta_init, num_features), name="beta", requires_grad=affine)
self.group_device_num = validator.check_positive_int(device_num_each_group, "device_num_each_group",
self.cls_name)
self.process_groups = process_groups
self.is_global = False
self.parallel_mode = context.get_auto_parallel_context("parallel_mode")
global SYNC_BN_GROUP_NAME
# for GlobalBatchNorm
if self.group_device_num != 1:
self.rank_id = get_rank()
self.rank_size = get_group_size()
self.device_list = [i for i in range(0, self.rank_size)]
self.rank_list = self.list_group(self.device_list, self.group_device_num)
self.rank_list_idx = len(self.rank_list)
self._create_global_groups()
# for SyncBatchNorm
if self.process_groups != 0:
self.rank_id = get_rank()
self.rank_size = get_group_size()
if self.process_groups is not None:
validator.check_isinstance("process_groups", self.process_groups, list)
self._check_rank_ids(self.process_groups, self.rank_size)
self._create_sync_groups()
elif self.rank_size > 1:
self.is_global = True
self.group_device_num = self.rank_size
self.device_list = [i for i in range(0, self.rank_size)]
if context.get_context("device_target") == "Ascend":
if SYNC_BN_GROUP_NAME == "":
SYNC_BN_GROUP_NAME = "sync_bn_group0"
management.create_group(SYNC_BN_GROUP_NAME, self.device_list)
elif context.get_context("device_target") == "GPU":
if SYNC_BN_GROUP_NAME == "":
SYNC_BN_GROUP_NAME = "nccl_world_group"
self.shape = P.Shape()
self.reduce_mean = P.ReduceMean(keep_dims=True)
self.square = P.Square()
self.sqrt = P.Sqrt()
self.cast = P.Cast()
self.dtype = P.DType()
self.reshape = P.Reshape()
self._target = context.get_context("device_target")
self.is_graph_mode = context.get_context("mode") == context.GRAPH_MODE
self.momentum = 1.0 - momentum
if context.get_context("enable_ge"):
self.is_ge_backend = True
else:
self.is_ge_backend = False
self.bn_train = P.BatchNorm(is_training=True,
epsilon=self.eps,
momentum=self.momentum,
data_format=self.format)
if self.is_global:
self.bn_train = inner.SyncBatchNorm(epsilon=self.eps,
momentum=self.momentum,
group=SYNC_BN_GROUP_NAME,
device_num=self.group_device_num)
self.bn_infer = P.BatchNorm(is_training=False, epsilon=self.eps, data_format=self.format)
if _is_in_auto_parallel_mode():
data_parallel_strategy = ((1,), (1,))
data_parallel_strategy_one = ((1,), ())
else:
data_parallel_strategy = None
data_parallel_strategy_one = None
self.sub_mean = P.Sub().shard(data_parallel_strategy)
self.sub_var = P.Sub().shard(data_parallel_strategy)
self.mul_mean = P.Mul().shard(data_parallel_strategy_one)
self.mul_var = P.Mul().shard(data_parallel_strategy_one)
self.assign_sub_mean = P.AssignSub().shard(data_parallel_strategy)
self.assign_sub_var = P.AssignSub().shard(data_parallel_strategy) | [
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Tencent/TNN | 7acca99f54c55747b415a4c57677403eebc7b706 | third_party/flatbuffers/python/flatbuffers/builder.py | python | Builder.Place | (self, x, flags) | Place prepends a value specified by `flags` to the Builder,
without checking for available space. | Place prepends a value specified by `flags` to the Builder,
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"""
Place prepends a value specified by `flags` to the Builder,
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N.enforce_number(x, flags)
self.head = self.head - flags.bytewidth
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ricardoquesada/Spidermonkey | 4a75ea2543408bd1b2c515aa95901523eeef7858 | python/mozbuild/mozbuild/makeutil.py | python | Rule.dump | (self, fh) | Dump the rule to the given file handle. | Dump the rule to the given file handle. | [
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'''
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fh.write(' %s' % ' '.join(self.dependencies()))
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windystrife/UnrealEngine_NVIDIAGameWorks | b50e6338a7c5b26374d66306ebc7807541ff815e | Engine/Extras/ThirdPartyNotUE/emsdk/Win64/python/2.7.5.3_64bit/Lib/lib-tk/turtle.py | python | TurtleScreenBase._drawimage | (self, item, (x, y), image) | Configure image item as to draw image object
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self.cv.coords(item, (x * self.xscale, -y * self.yscale))
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eventql/eventql | 7ca0dbb2e683b525620ea30dc40540a22d5eb227 | deps/3rdparty/spidermonkey/mozjs/python/mozbuild/mozbuild/frontend/context.py | python | SourcePath.translated | (self) | return mozpath.normpath(ret) | Returns the corresponding path in the objdir.
Ideally, we wouldn't need this function, but the fact that both source
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"""Returns the corresponding path in the objdir.
Ideally, we wouldn't need this function, but the fact that both source
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objdir (aka pseudo-rework), this is needed.
"""
if self.value.startswith('/'):
ret = mozpath.join(self.context.config.topobjdir, self.value[1:])
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ret = mozpath.join(self.context.objdir, self.value)
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mantidproject/mantid | 03deeb89254ec4289edb8771e0188c2090a02f32 | scripts/SANS/SANSUtility.py | python | CummulativeTimeSeriesPropertyAdder.extract_sample_logs_from_workspace | (self, lhs, rhs) | When adding specific logs, we need to make sure that the values are added correctly.
:param lhs: the lhs workspace
:param rhs: the rhs workspace | When adding specific logs, we need to make sure that the values are added correctly.
:param lhs: the lhs workspace
:param rhs: the rhs workspace | [
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"""
When adding specific logs, we need to make sure that the values are added correctly.
:param lhs: the lhs workspace
:param rhs: the rhs workspace
"""
run_lhs = lhs.getRun()
run_rhs = rhs.getRun()
# Get the cumulative time s
for element in self._time_series:
if (run_lhs.hasProperty(element)
and run_rhs.hasProperty(element)):
# Get values for lhs
property_lhs = run_lhs.getProperty(element)
self._original_times_lhs[element] = property_lhs.times
self._original_values_lhs[element] = property_lhs.value
# Get values for rhs
property_rhs = run_rhs.getProperty(element)
self._original_times_rhs[element] = property_rhs.times
self._original_values_rhs[element] = property_rhs.value
for element in self._single_valued:
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# Get the values for lhs
property_lhs = run_lhs.getProperty(element)
self._original_single_valued_lhs[element] = property_lhs.value
# Get the values for rhs
property_rhs = run_rhs.getProperty(element)
self._original_single_valued_rhs[element] = property_rhs.value
log_name_start_time = "start_time"
if (run_lhs.hasProperty(log_name_start_time)
and run_rhs.hasProperty(log_name_start_time)):
def convert_to_date(val):
return DateAndTime(val) if isinstance(val, str) else val
self._start_time_lhs = convert_to_date(run_lhs.getProperty(log_name_start_time).value)
self._start_time_rhs = convert_to_date(run_rhs.getProperty(log_name_start_time).value) | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/llvmlite/ir/builder.py | python | IRBuilder.block | (self) | return self._block | The current basic block. | The current basic block. | [
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"""
The current basic block.
"""
return self._block | [
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hanpfei/chromium-net | 392cc1fa3a8f92f42e4071ab6e674d8e0482f83f | tools/json_schema_compiler/idl_schema.py | python | Main | () | Dump a json serialization of parse result for the IDL files whose names
were passed in on the command line. | Dump a json serialization of parse result for the IDL files whose names
were passed in on the command line. | [
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'''
Dump a json serialization of parse result for the IDL files whose names
were passed in on the command line.
'''
if len(sys.argv) > 1:
for filename in sys.argv[1:]:
schema = Load(filename)
print json.dumps(schema, indent=2)
else:
contents = sys.stdin.read()
idl = idl_parser.IDLParser().ParseData(contents, '<stdin>')
schema = IDLSchema(idl).process()
print json.dumps(schema, indent=2) | [
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hanpfei/chromium-net | 392cc1fa3a8f92f42e4071ab6e674d8e0482f83f | third_party/catapult/third_party/gsutil/third_party/boto/boto/support/layer1.py | python | SupportConnection.describe_trusted_advisor_check_summaries | (self, check_ids) | return self.make_request(action='DescribeTrustedAdvisorCheckSummaries',
body=json.dumps(params)) | Returns the summaries of the results of the Trusted Advisor
checks that have the specified check IDs. Check IDs can be
obtained by calling DescribeTrustedAdvisorChecks.
The response contains an array of TrustedAdvisorCheckSummary
objects.
:type check_ids: list
:param check_ids: The IDs of the Trusted Advisor checks. | Returns the summaries of the results of the Trusted Advisor
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gem5/gem5 | 141cc37c2d4b93959d4c249b8f7e6a8b2ef75338 | src/dev/riscv/HiFive.py | python | HiFive.attachPlic | (self) | Count number of PLIC interrupt sources | Count number of PLIC interrupt sources | [
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"""Count number of PLIC interrupt sources
"""
plic_srcs = [self.uart_int_id]
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if hasattr(device, "interrupt_id"):
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seqan/seqan | f5f658343c366c9c3d44ba358ffc9317e78a09ed | util/py_lib/pyratemp.py | python | escape | (s, format=HTML) | return unicode(s) | Replace special characters by their escape sequence.
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- `NONE`: nothing is replaced
- `HTML`: replace &<>'" by &...;
- `LATEX`: replace \#$%&_{} (TODO! - this is very incomplete!)
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"""Replace special characters by their escape sequence.
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- `NONE`: nothing is replaced
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- `LATEX`: replace \#$%&_{} (TODO! - this is very incomplete!)
:Returns:
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:Exceptions:
- `ValueError`: if `format` is invalid.
:TODO: complete LaTeX-escaping, optimize speed
"""
#Note: If you have to make sure that every character gets replaced
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# which is about 2-3 times slower (but maybe needs less memory).
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s = s.replace(u">", u">")
s = s.replace(u'"', u""")
s = s.replace(u"'", u"'")
elif format == LATEX:
#TODO: which are the "reserved" characters for LaTeX?
# are there more than these?
s = s.replace("\\", u"\\backslash{}") #must be done first!
s = s.replace("#", u"\\#")
s = s.replace("$", u"\\$")
s = s.replace("%", u"\\%")
s = s.replace("&", u"\\&")
s = s.replace("_", u"\\_")
s = s.replace("{", u"\\{")
s = s.replace("}", u"\\}")
else:
raise ValueError('Invalid format (only None, HTML and LATEX are supported).')
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ideawu/ssdb | f229ba277c7f7d0ca5a441c0c6fb3d1209af68e4 | deps/cpy/antlr3/streams.py | python | CharStream.getCharPositionInLine | (self) | The index of the character relative to the beginning of the line 0..n-1 | The index of the character relative to the beginning of the line 0..n-1 | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_carbon/_core.py | python | Window.ConvertDialogSizeToPixels | (*args, **kwargs) | return _core_.Window_ConvertDialogSizeToPixels(*args, **kwargs) | ConvertDialogSizeToPixels(self, Size sz) -> Size
Converts a point or size from dialog units to pixels. Dialog units
are used for maintaining a dialog's proportions even if the font
changes. For the x dimension, the dialog units are multiplied by the
average character width and then divided by 4. For the y dimension,
the dialog units are multiplied by the average character height and
then divided by 8. | ConvertDialogSizeToPixels(self, Size sz) -> Size | [
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ConvertDialogSizeToPixels(self, Size sz) -> Size
Converts a point or size from dialog units to pixels. Dialog units
are used for maintaining a dialog's proportions even if the font
changes. For the x dimension, the dialog units are multiplied by the
average character width and then divided by 4. For the y dimension,
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"""
return _core_.Window_ConvertDialogSizeToPixels(*args, **kwargs) | [
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lballabio/quantlib-old | 136336947ed4fea9ecc1da6edad188700e821739 | gensrc/gensrc/addins/c.py | python | CAddin.generateHeader | (self, func, suffix) | return CAddin.BUFFER_FUNCDEC % {
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HKUST-Aerial-Robotics/Teach-Repeat-Replan | 98505a7f74b13c8b501176ff838a38423dbef536 | utils/quadrotor_msgs/src/quadrotor_msgs/msg/_Serial.py | python | Serial.serialize | (self, buff) | serialize message into buffer
:param buff: buffer, ``StringIO`` | serialize message into buffer
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"""
serialize message into buffer
:param buff: buffer, ``StringIO``
"""
try:
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buff.write(_struct_3I.pack(_x.header.seq, _x.header.stamp.secs, _x.header.stamp.nsecs))
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length = len(_x)
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_x = _x.encode('utf-8')
length = len(_x)
if python3:
buff.write(struct.pack('<I%sB'%length, length, *_x))
else:
buff.write(struct.pack('<I%ss'%length, length, _x))
_x = self
buff.write(_struct_2B.pack(_x.channel, _x.type))
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length = len(_x)
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zerollzeng/tiny-tensorrt | e7bdb8f82934342a0f22ce68dfefdb8e15eb72b2 | third_party/pybind11/tools/clang/cindex.py | python | Type.get_ref_qualifier | (self) | return RefQualifierKind.from_id(
conf.lib.clang_Type_getCXXRefQualifier(self)) | Retrieve the ref-qualifier of the type. | Retrieve the ref-qualifier of the type. | [
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Retrieve the ref-qualifier of the type.
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etotheipi/BitcoinArmory | 2a6fc5355bb0c6fe26e387ccba30a5baafe8cd98 | armoryengine/PyBtcWallet.py | python | PyBtcWallet.detectHighestUsedIndex | (self, startFrom=0, writeResultToWallet=False, fullscan=False) | return highestIndex | This method is used to find the highestUsedChainIndex value of the
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If you have a wallet IMPORT, though, or a wallet that has been used
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self.freshImportFindHighestIndex()
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] | def detectHighestUsedIndex(self, startFrom=0, writeResultToWallet=False, fullscan=False):
"""
This method is used to find the highestUsedChainIndex value of the
wallet WITHIN its address pool. It will NOT extend its address pool
in this search, because it is assumed that the wallet couldn't have
used any addresses it had not calculated yet.
If you have a wallet IMPORT, though, or a wallet that has been used
before but does not have this information stored with it, then you
should be using the next method:
self.freshImportFindHighestIndex()
which will actually extend the address pool as necessary to find the
highest address used.
"""
if fullscan:
startFrom = 0
highestIndex = max(self.highestUsedChainIndex, 0)
for a160 in self.linearAddr160List[startFrom:]:
addr = self.addrMap[a160]
scrAddr = Hash160ToScrAddr(a160)
if self.cppWallet.getAddrTotalTxnCount(scrAddr) > 0:
highestIndex = max(highestIndex, addr.chainIndex)
if writeResultToWallet:
self.highestUsedChainIndex = highestIndex
self.walletFileSafeUpdate( [[WLT_UPDATE_MODIFY, self.offsetTopUsed, \
int_to_binary(highestIndex, widthBytes=8)]])
return highestIndex | [
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weolar/miniblink49 | 1c4678db0594a4abde23d3ebbcc7cd13c3170777 | v8_4_5/build/landmine_utils.py | python | memoize | (default=None) | return memoizer | This decorator caches the return value of a parameterless pure function | This decorator caches the return value of a parameterless pure function | [
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] | def memoize(default=None):
"""This decorator caches the return value of a parameterless pure function"""
def memoizer(func):
val = []
@functools.wraps(func)
def inner():
if not val:
ret = func()
val.append(ret if ret is not None else default)
if logging.getLogger().isEnabledFor(logging.INFO):
print '%s -> %r' % (func.__name__, val[0])
return val[0]
return inner
return memoizer | [
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Project-OSRM/osrm-backend | f2e284623e25b5570dd2a5e6985abcb3790fd348 | third_party/flatbuffers/python/flatbuffers/builder.py | python | Builder.PlaceUOffsetT | (self, x) | PlaceUOffsetT prepends a UOffsetT to the Builder, without checking
for space. | PlaceUOffsetT prepends a UOffsetT to the Builder, without checking
for space. | [
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] | def PlaceUOffsetT(self, x):
"""PlaceUOffsetT prepends a UOffsetT to the Builder, without checking
for space.
"""
N.enforce_number(x, N.UOffsetTFlags)
self.head = self.head - N.UOffsetTFlags.bytewidth
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Polidea/SiriusObfuscator | b0e590d8130e97856afe578869b83a209e2b19be | SymbolExtractorAndRenamer/llvm/bindings/python/llvm/disassembler.py | python | Disassembler.get_instructions | (self, source, pc=0) | Obtain multiple instructions from an input source.
This is like get_instruction() except it is a generator for all
instructions within the source. It starts at the beginning of the
source and reads instructions until no more can be read.
This generator returns 3-tuple of:
long address of instruction.
long size of instruction, in bytes.
str representation of instruction. | Obtain multiple instructions from an input source. | [
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] | def get_instructions(self, source, pc=0):
"""Obtain multiple instructions from an input source.
This is like get_instruction() except it is a generator for all
instructions within the source. It starts at the beginning of the
source and reads instructions until no more can be read.
This generator returns 3-tuple of:
long address of instruction.
long size of instruction, in bytes.
str representation of instruction.
"""
source_bytes = c_char_p(source)
out_str = cast((c_byte * 255)(), c_char_p)
# This could probably be written cleaner. But, it does work.
buf = cast(source_bytes, POINTER(c_ubyte * len(source))).contents
offset = 0
address = pc
end_address = pc + len(source)
while address < end_address:
b = cast(addressof(buf) + offset, POINTER(c_ubyte))
result = lib.LLVMDisasmInstruction(self, b,
c_uint64(len(source) - offset), c_uint64(address),
out_str, 255)
if result == 0:
break
yield (address, result, out_str.value)
address += result
offset += result | [
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Z3Prover/z3 | d745d03afdfdf638d66093e2bfbacaf87187f35b | src/api/python/z3/z3.py | python | is_bv_value | (a) | return is_bv(a) and _is_numeral(a.ctx, a.as_ast()) | Return `True` if `a` is a Z3 bit-vector numeral value.
>>> b = BitVec('b', 32)
>>> is_bv_value(b)
False
>>> b = BitVecVal(10, 32)
>>> b
10
>>> is_bv_value(b)
True | Return `True` if `a` is a Z3 bit-vector numeral value. | [
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] | def is_bv_value(a):
"""Return `True` if `a` is a Z3 bit-vector numeral value.
>>> b = BitVec('b', 32)
>>> is_bv_value(b)
False
>>> b = BitVecVal(10, 32)
>>> b
10
>>> is_bv_value(b)
True
"""
return is_bv(a) and _is_numeral(a.ctx, a.as_ast()) | [
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turi-code/SFrame | 796b9bdfb2fa1b881d82080754643c7e68629cd2 | oss_src/unity/python/sframe/util/cloudpickle.py | python | CloudPickler.save_inst | (self, obj) | Inner logic to save instance. Based off pickle.save_inst
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"""Inner logic to save instance. Based off pickle.save_inst
Supports __transient__"""
cls = obj.__class__
memo = self.memo
write = self.write
save = self.save
if hasattr(obj, '__getinitargs__'):
args = obj.__getinitargs__()
len(args) # XXX Assert it's a sequence
pickle._keep_alive(args, memo)
else:
args = ()
write(pickle.MARK)
if self.bin:
save(cls)
for arg in args:
save(arg)
write(pickle.OBJ)
else:
for arg in args:
save(arg)
write(pickle.INST + cls.__module__ + '\n' + cls.__name__ + '\n')
self.memoize(obj)
try:
getstate = obj.__getstate__
except AttributeError:
stuff = obj.__dict__
#remove items if transient
if hasattr(obj, '__transient__'):
transient = obj.__transient__
stuff = stuff.copy()
for k in list(stuff.keys()):
if k in transient:
del stuff[k]
else:
stuff = getstate()
pickle._keep_alive(stuff, memo)
save(stuff)
write(pickle.BUILD) | [
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ValveSoftware/source-sdk-2013 | 0d8dceea4310fde5706b3ce1c70609d72a38efdf | sp/src/thirdparty/protobuf-2.3.0/python/google/protobuf/internal/decoder.py | python | _SkipFixed64 | (buffer, pos, end) | return pos | Skip a fixed64 value. Returns the new position. | Skip a fixed64 value. Returns the new position. | [
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] | def _SkipFixed64(buffer, pos, end):
"""Skip a fixed64 value. Returns the new position."""
pos += 8
if pos > end:
raise _DecodeError('Truncated message.')
return pos | [
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microsoft/onnxruntime | f92e47e95b13a240e37caf7b36577983544f98fc | orttraining/orttraining/python/training/_utils.py | python | state_dict_original_dimension_key | () | return 'original_dim' | Returns the original dimension key name in the state dictionary | Returns the original dimension key name in the state dictionary | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemDefectReporter/v1/AWS/common-code/Lib/setuptools/command/easy_install.py | python | easy_install.expand_dirs | (self) | Calls `os.path.expanduser` on install dirs. | Calls `os.path.expanduser` on install dirs. | [
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] | def expand_dirs(self):
"""Calls `os.path.expanduser` on install dirs."""
dirs = [
'install_purelib',
'install_platlib',
'install_lib',
'install_headers',
'install_scripts',
'install_data',
]
self._expand_attrs(dirs) | [
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rootm0s/Protectors | 5b3f4d11687a5955caf9c3af30666c4bfc2c19ab | OWASP-ZSC/module/readline_windows/pyreadline/lineeditor/history.py | python | LineHistory.next_history | (self, current) | Move forward through the history list, fetching the next command. | Move forward through the history list, fetching the next command. | [
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"the",
"history",
"list",
"fetching",
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"next",
"command",
"."
] | def next_history(self, current): # (C-n)
'''Move forward through the history list, fetching the next command. '''
if self.history_cursor < len(self.history) - 1:
self.history_cursor += 1
current.set_line(self.history[self.history_cursor].get_line_text()) | [
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gem5/gem5 | 141cc37c2d4b93959d4c249b8f7e6a8b2ef75338 | ext/ply/example/BASIC/basparse.py | python | p_number | (p) | number : INTEGER
| FLOAT | number : INTEGER
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] | def p_number(p):
'''number : INTEGER
| FLOAT'''
p[0] = eval(p[1]) | [
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miyosuda/TensorFlowAndroidDemo | 35903e0221aa5f109ea2dbef27f20b52e317f42d | jni-build/jni/include/tensorflow/python/ops/array_ops.py | python | zeros | (shape, dtype=dtypes.float32, name=None) | return output | Creates a tensor with all elements set to zero.
This operation returns a tensor of type `dtype` with shape `shape` and
all elements set to zero.
For example:
```python
tf.zeros([3, 4], int32) ==> [[0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0]]
```
Args:
shape: Either a list of integers, or a 1-D `Tensor` of type `int32`.
dtype: The type of an element in the resulting `Tensor`.
name: A name for the operation (optional).
Returns:
A `Tensor` with all elements set to zero. | Creates a tensor with all elements set to zero. | [
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] | def zeros(shape, dtype=dtypes.float32, name=None):
"""Creates a tensor with all elements set to zero.
This operation returns a tensor of type `dtype` with shape `shape` and
all elements set to zero.
For example:
```python
tf.zeros([3, 4], int32) ==> [[0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0]]
```
Args:
shape: Either a list of integers, or a 1-D `Tensor` of type `int32`.
dtype: The type of an element in the resulting `Tensor`.
name: A name for the operation (optional).
Returns:
A `Tensor` with all elements set to zero.
"""
with ops.op_scope([shape], name, "zeros") as name:
try:
shape = tensor_shape.as_shape(shape)
output = constant(0, shape=shape, dtype=dtype, name=name)
except (TypeError, ValueError):
shape = ops.convert_to_tensor(shape, dtype=dtypes.int32, name="shape")
output = fill(shape, constant(0, dtype=dtype), name=name)
assert output.dtype.base_dtype == dtypes.as_dtype(dtype).base_dtype
return output | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_cocoa/_core.py | python | Image.Copy | (*args, **kwargs) | return _core_.Image_Copy(*args, **kwargs) | Copy(self) -> Image
Returns an identical copy of the image. | Copy(self) -> Image | [
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] | def Copy(*args, **kwargs):
"""
Copy(self) -> Image
Returns an identical copy of the image.
"""
return _core_.Image_Copy(*args, **kwargs) | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/scipy/py2/scipy/interpolate/fitpack2.py | python | UnivariateSpline.get_coeffs | (self) | return data[9][:n-k-1] | Return spline coefficients. | Return spline coefficients. | [
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] | def get_coeffs(self):
"""Return spline coefficients."""
data = self._data
k, n = data[5], data[7]
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/msw/richtext.py | python | RichTextBuffer.SetStyleSheet | (*args, **kwargs) | return _richtext.RichTextBuffer_SetStyleSheet(*args, **kwargs) | SetStyleSheet(self, wxRichTextStyleSheet styleSheet) | SetStyleSheet(self, wxRichTextStyleSheet styleSheet) | [
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"""SetStyleSheet(self, wxRichTextStyleSheet styleSheet)"""
return _richtext.RichTextBuffer_SetStyleSheet(*args, **kwargs) | [
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MtnViewJohn/context-free | 757d7bde9742f201cec61bd195dda98093edd1e8 | src-scintilla/scripts/FileGenerator.py | python | GenerateFile | (inpath, outpath, commentPrefix, retainDefs, *lists) | Generate 'outpath' from 'inpath'. | Generate 'outpath' from 'inpath'. | [
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] | def GenerateFile(inpath, outpath, commentPrefix, retainDefs, *lists):
"""Generate 'outpath' from 'inpath'.
"""
try:
with codecs.open(inpath, "r", "UTF-8") as infile:
original = infile.read()
updated = CopyWithInsertion(original, commentPrefix,
retainDefs, lists)
UpdateFile(outpath, updated)
except IOError:
print("Can not open %s" % inpath) | [
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esa/pagmo | 80281d549c8f1b470e1489a5d37c8f06b2e429c0 | PyGMO/topology/__init__.py | python | _to_networkx | (self) | return retval | Export topology as a networkx DiGraph. | Export topology as a networkx DiGraph. | [
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"networkx",
"DiGraph",
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] | def _to_networkx(self):
"""
Export topology as a networkx DiGraph.
"""
try:
import networkx as nx
except ImportError:
raise ImportError('Could not import the networkx module.')
retval = nx.DiGraph()
for i in range(self.number_of_vertices):
if self.get_num_adjacent_vertices(i):
retval.add_edges_from([(i, n)
for n in self.get_adjacent_vertices(i)])
else:
retval.add_node(i)
return retval | [
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neoml-lib/neoml | a0d370fba05269a1b2258cef126f77bbd2054a3e | NeoML/Python/neoml/Dnn/Conv.py | python | TransposedConv3D.filter_size | (self) | return self._internal.get_filter_height(), self._internal.get_filter_width(), self._internal.get_filter_depth() | Gets the filter size. | Gets the filter size. | [
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] | def filter_size(self):
"""Gets the filter size.
"""
return self._internal.get_filter_height(), self._internal.get_filter_width(), self._internal.get_filter_depth() | [
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apple/swift-lldb | d74be846ef3e62de946df343e8c234bde93a8912 | third_party/Python/module/pexpect-4.6/pexpect/spawnbase.py | python | SpawnBase.expect_list | (self, pattern_list, timeout=-1, searchwindowsize=-1,
async_=False, **kw) | This takes a list of compiled regular expressions and returns the
index into the pattern_list that matched the child output. The list may
also contain EOF or TIMEOUT(which are not compiled regular
expressions). This method is similar to the expect() method except that
expect_list() does not recompile the pattern list on every call. This
may help if you are trying to optimize for speed, otherwise just use
the expect() method. This is called by expect().
Like :meth:`expect`, passing ``async_=True`` will make this return an
asyncio coroutine. | This takes a list of compiled regular expressions and returns the
index into the pattern_list that matched the child output. The list may
also contain EOF or TIMEOUT(which are not compiled regular
expressions). This method is similar to the expect() method except that
expect_list() does not recompile the pattern list on every call. This
may help if you are trying to optimize for speed, otherwise just use
the expect() method. This is called by expect(). | [
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'''This takes a list of compiled regular expressions and returns the
index into the pattern_list that matched the child output. The list may
also contain EOF or TIMEOUT(which are not compiled regular
expressions). This method is similar to the expect() method except that
expect_list() does not recompile the pattern list on every call. This
may help if you are trying to optimize for speed, otherwise just use
the expect() method. This is called by expect().
Like :meth:`expect`, passing ``async_=True`` will make this return an
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'''
if timeout == -1:
timeout = self.timeout
if 'async' in kw:
async_ = kw.pop('async')
if kw:
raise TypeError("Unknown keyword arguments: {}".format(kw))
exp = Expecter(self, searcher_re(pattern_list), searchwindowsize)
if async_:
from ._async import expect_async
return expect_async(exp, timeout)
else:
return exp.expect_loop(timeout) | [
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HKUST-Aerial-Robotics/Teach-Repeat-Replan | 98505a7f74b13c8b501176ff838a38423dbef536 | utils/quadrotor_msgs/src/quadrotor_msgs/msg/_AuxCommand.py | python | AuxCommand.serialize_numpy | (self, buff, numpy) | serialize message with numpy array types into buffer
:param buff: buffer, ``StringIO``
:param numpy: numpy python module | serialize message with numpy array types into buffer
:param buff: buffer, ``StringIO``
:param numpy: numpy python module | [
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"""
serialize message with numpy array types into buffer
:param buff: buffer, ``StringIO``
:param numpy: numpy python module
"""
try:
_x = self
buff.write(_struct_2d.pack(_x.current_yaw, _x.kf_correction))
buff.write(self.angle_corrections.tostring())
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except struct.error as se: self._check_types(struct.error("%s: '%s' when writing '%s'" % (type(se), str(se), str(_x))))
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baidu-research/tensorflow-allreduce | 66d5b855e90b0949e9fa5cca5599fd729a70e874 | tensorflow/contrib/distributions/python/ops/binomial.py | python | Binomial.logits | (self) | return self._logits | Log-odds of drawing a `1`. | Log-odds of drawing a `1`. | [
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"""Log-odds of drawing a `1`."""
return self._logits | [
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ARM-software/armnn | 5e9965cae1cc6162649910f423ebd86001fc1931 | python/pyarmnn/examples/speech_recognition/preprocess.py | python | MFCC.mel_scale | (self, freq, use_htk_method) | return mel | Gets the mel scale for a particular sample frequency.
Args:
freq: The sampling frequency.
use_htk_method: Boolean to set whether to use HTK method or not.
Returns:
the mel scale | Gets the mel scale for a particular sample frequency. | [
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] | def mel_scale(self, freq, use_htk_method):
"""
Gets the mel scale for a particular sample frequency.
Args:
freq: The sampling frequency.
use_htk_method: Boolean to set whether to use HTK method or not.
Returns:
the mel scale
"""
if use_htk_method:
return 1127.0 * np.log(1.0 + freq / 700.0)
else:
mel = freq / self.FREQ_STEP
if freq >= self.MIN_LOG_HZ:
mel = self.MIN_LOG_MEL + np.log(freq / self.MIN_LOG_HZ) / self.LOG_STEP
return mel | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/site-packages/pkg_resources/_vendor/pyparsing.py | python | ParseResults.append | ( self, item ) | Add single element to end of ParseResults list of elements.
Example::
print(OneOrMore(Word(nums)).parseString("0 123 321")) # -> ['0', '123', '321']
# use a parse action to compute the sum of the parsed integers, and add it to the end
def append_sum(tokens):
tokens.append(sum(map(int, tokens)))
print(OneOrMore(Word(nums)).addParseAction(append_sum).parseString("0 123 321")) # -> ['0', '123', '321', 444] | Add single element to end of ParseResults list of elements. | [
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print(OneOrMore(Word(nums)).parseString("0 123 321")) # -> ['0', '123', '321']
# use a parse action to compute the sum of the parsed integers, and add it to the end
def append_sum(tokens):
tokens.append(sum(map(int, tokens)))
print(OneOrMore(Word(nums)).addParseAction(append_sum).parseString("0 123 321")) # -> ['0', '123', '321', 444]
"""
self.__toklist.append(item) | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/email/encoders.py | python | encode_quopri | (msg) | Encode the message's payload in quoted-printable.
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orig = msg.get_payload(decode=True)
encdata = _qencode(orig)
msg.set_payload(encdata)
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SpenceKonde/megaTinyCore | 1c4a70b18a149fe6bcb551dfa6db11ca50b8997b | megaavr/tools/libs/pymcuprog/nvmspi.py | python | NvmAccessProviderCmsisDapSpi.write | (self, memory_info, offset, data) | Write the memory with data
:param memory_info: dictionary for the memory as provided by the DeviceMemoryInfo class
:param offset: relative offset within the memory type
:param data: the data to program
:return: None | Write the memory with data | [
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"""
Write the memory with data
:param memory_info: dictionary for the memory as provided by the DeviceMemoryInfo class
:param offset: relative offset within the memory type
:param data: the data to program
:return: None
"""
# Make sure the data is aligned to a memory page
data_aligned, offset_aligned = utils.pagealign(data,
offset,
memory_info[DeviceMemoryInfoKeys.PAGE_SIZE],
memory_info[DeviceMemoryInfoKeys.WRITE_SIZE])
if memory_info[DeviceMemoryInfoKeys.NAME] != MemoryNames.FLASH:
raise PymcuprogNotSupportedError("Currently only Flash memory is supported by write for SPI/ISP")
write_chunk_size = memory_info[DeviceMemoryInfoKeys.PAGE_SIZE]
n_chunk = math.ceil(len(data_aligned)/write_chunk_size)
bar = progress_bar.ProgressBar(n_chunk, hide=n_chunk == 1)
while data_aligned:
bar.step()
if len(data_aligned) < write_chunk_size:
write_chunk_size = len(data_aligned)
chunk = data_aligned[0:write_chunk_size]
self.logger.debug("Writing %d bytes to address 0x%06X", write_chunk_size, offset_aligned)
self.isp.write_flash_page(offset_aligned, chunk)
offset_aligned += write_chunk_size
data_aligned = data_aligned[write_chunk_size:] | [
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vslavik/poedit | f7a9daa0a10037e090aa0a86f5ce0f24ececdf6a | deps/boost/tools/build/src/build/feature.py | python | subfeature | (feature_name, value_string, subfeature, subvalues, attributes = []) | Declares a subfeature.
feature_name: Root feature that is not a subfeature.
value_string: An optional value-string specifying which feature or
subfeature values this subfeature is specific to,
if any.
subfeature: The name of the subfeature being declared.
subvalues: The allowed values of this subfeature.
attributes: The attributes of the subfeature. | Declares a subfeature.
feature_name: Root feature that is not a subfeature.
value_string: An optional value-string specifying which feature or
subfeature values this subfeature is specific to,
if any.
subfeature: The name of the subfeature being declared.
subvalues: The allowed values of this subfeature.
attributes: The attributes of the subfeature. | [
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""" Declares a subfeature.
feature_name: Root feature that is not a subfeature.
value_string: An optional value-string specifying which feature or
subfeature values this subfeature is specific to,
if any.
subfeature: The name of the subfeature being declared.
subvalues: The allowed values of this subfeature.
attributes: The attributes of the subfeature.
"""
parent_feature = validate_feature (feature_name)
# Add grist to the subfeature name if a value-string was supplied
subfeature_name = __get_subfeature_name (subfeature, value_string)
if subfeature_name in __all_features[feature_name].subfeatures:
message = "'%s' already declared as a subfeature of '%s'" % (subfeature, feature_name)
message += " specific to '%s'" % value_string
raise BaseException (message)
# First declare the subfeature as a feature in its own right
f = feature (feature_name + '-' + subfeature_name, subvalues, attributes + ['subfeature'])
f.set_parent(parent_feature, value_string)
parent_feature.add_subfeature(f)
# Now make sure the subfeature values are known.
extend_subfeature (feature_name, value_string, subfeature, subvalues) | [
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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/_internal/index/package_finder.py | python | CandidateEvaluator.sort_best_candidate | (
self,
candidates, # type: List[InstallationCandidate]
) | return best_candidate | Return the best candidate per the instance's sort order, or None if
no candidate is acceptable. | Return the best candidate per the instance's sort order, or None if
no candidate is acceptable. | [
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self,
candidates, # type: List[InstallationCandidate]
):
# type: (...) -> Optional[InstallationCandidate]
"""
Return the best candidate per the instance's sort order, or None if
no candidate is acceptable.
"""
if not candidates:
return None
best_candidate = max(candidates, key=self._sort_key)
return best_candidate | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemDefectReporter/v1/AWS/common-code/Lib/urllib3/packages/six.py | python | _SixMetaPathImporter.get_code | (self, fullname) | return None | Return None
Required, if is_package is implemented | Return None | [
"Return",
"None"
] | def get_code(self, fullname):
"""Return None
Required, if is_package is implemented"""
self.__get_module(fullname) # eventually raises ImportError
return None | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/scipy/scipy/io/idl.py | python | _read_int64 | (f) | return np.int64(struct.unpack('>q', f.read(8))[0]) | Read a signed 64-bit integer | Read a signed 64-bit integer | [
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] | def _read_int64(f):
'''Read a signed 64-bit integer'''
return np.int64(struct.unpack('>q', f.read(8))[0]) | [
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epiqc/ScaffCC | 66a79944ee4cd116b27bc1a69137276885461db8 | clang/tools/scan-build-py/libscanbuild/arguments.py | python | create_intercept_parser | () | return parser | Creates a parser for command-line arguments to 'intercept'. | Creates a parser for command-line arguments to 'intercept'. | [
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""" Creates a parser for command-line arguments to 'intercept'. """
parser = create_default_parser()
parser_add_cdb(parser)
parser_add_prefer_wrapper(parser)
parser_add_compilers(parser)
advanced = parser.add_argument_group('advanced options')
group = advanced.add_mutually_exclusive_group()
group.add_argument(
'--append',
action='store_true',
help="""Extend existing compilation database with new entries.
Duplicate entries are detected and not present in the final output.
The output is not continuously updated, it's done when the build
command finished. """)
parser.add_argument(
dest='build', nargs=argparse.REMAINDER, help="""Command to run.""")
return parser | [
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apiaryio/drafter | 4634ebd07f6c6f257cc656598ccd535492fdfb55 | tools/gyp/pylib/gyp/msvs_emulation.py | python | MsvsSettings.GetCompilerPdbName | (self, config, expand_special) | return pdbname | Get the pdb file name that should be used for compiler invocations, or
None if there's no explicit name specified. | Get the pdb file name that should be used for compiler invocations, or
None if there's no explicit name specified. | [
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] | def GetCompilerPdbName(self, config, expand_special):
"""Get the pdb file name that should be used for compiler invocations, or
None if there's no explicit name specified."""
config = self._TargetConfig(config)
pdbname = self._Setting(
('VCCLCompilerTool', 'ProgramDataBaseFileName'), config)
if pdbname:
pdbname = expand_special(self.ConvertVSMacros(pdbname))
return pdbname | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/pandas/py3/pandas/io/formats/latex.py | python | RowStringConverter._compose_cline | (self, i: int, icol: int) | return "".join(lst) | Create clines after multirow-blocks are finished. | Create clines after multirow-blocks are finished. | [
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"""
Create clines after multirow-blocks are finished.
"""
lst = []
for cl in self.clinebuf:
if cl[0] == i:
lst.append(f"\n\\cline{{{cl[1]:d}-{icol:d}}}")
# remove entries that have been written to buffer
self.clinebuf = [x for x in self.clinebuf if x[0] != i]
return "".join(lst) | [
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apache/incubator-mxnet | f03fb23f1d103fec9541b5ae59ee06b1734a51d9 | python/mxnet/gluon/utils.py | python | _brief_print_list | (lst, limit=7) | return ', '.join(["'%s'"%str(i) for i in lst]) | Print at most `limit` elements of list. | Print at most `limit` elements of list. | [
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"""Print at most `limit` elements of list."""
lst = list(lst)
if len(lst) > limit:
return _brief_print_list(lst[:limit//2], limit) + ', ..., ' + \
_brief_print_list(lst[-limit//2:], limit)
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/gtk/_core.py | python | PyApp_GetMacAboutMenuItemId | (*args) | return _core_.PyApp_GetMacAboutMenuItemId(*args) | PyApp_GetMacAboutMenuItemId() -> long | PyApp_GetMacAboutMenuItemId() -> long | [
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rsummers11/CADLab | 976ed959a0b5208bb4173127a7ef732ac73a9b6f | panreas_hnn/hed-globalweight/scripts/cpp_lint.py | python | _SetOutputFormat | (output_format) | Sets the module's output format. | Sets the module's output format. | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | wx/lib/agw/toasterbox.py | python | ToasterBox.GetUseFocus | (self) | return self._usefocus | Returns whether :class:`ToasterBox` will steal the focus from the parent application. | Returns whether :class:`ToasterBox` will steal the focus from the parent application. | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/msw/propgrid.py | python | PropertyGridInterface.GetSelectedProperties | (*args, **kwargs) | return _propgrid.PropertyGridInterface_GetSelectedProperties(*args, **kwargs) | GetSelectedProperties(self) -> wxArrayPGProperty | GetSelectedProperties(self) -> wxArrayPGProperty | [
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tensorflow/tensorflow | 419e3a6b650ea4bd1b0cba23c4348f8a69f3272e | tensorflow/python/ops/sparse_ops.py | python | _convert_to_sparse_tensor | (sp_input) | return sp_input | Convert `sp_input` to `SparseTensor` and return it.
Args:
sp_input: `SparseTensor` or `SparseTensorValue`.
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Returns:
`sp_input` converted to `SparseTensor`.
Raises:
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"""
if isinstance(sp_input, sparse_tensor.SparseTensorValue):
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ChromiumWebApps/chromium | c7361d39be8abd1574e6ce8957c8dbddd4c6ccf7 | tools/python/google/httpd_utils.py | python | ApacheHttpd.__init__ | (self, start_command, stop_command, port_list,
cygserver_path=None) | Args:
start_command: command list to call to start the httpd
stop_command: command list to call to stop the httpd if one has been
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port_list: list of ports expected to respond on the local machine when
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cygserver_path: Path to cygserver.exe. If specified, exe will be started
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start_command: command list to call to start the httpd
stop_command: command list to call to stop the httpd if one has been
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port_list: list of ports expected to respond on the local machine when
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cygserver_path: Path to cygserver.exe. If specified, exe will be started
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stop_command: command list to call to stop the httpd if one has been
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port_list: list of ports expected to respond on the local machine when
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cygserver_path: Path to cygserver.exe. If specified, exe will be started
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self._http_server_proc = None
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continental/ecal | 204dab80a24fe01abca62541133b311bf0c09608 | lang/python/core/ecal/core/core.py | python | subscriber.set_qos_reliability | (self, qpolicy) | return sub_set_qos_reliability(self.thandle, qpolicy) | set quality of service reliability mode
:param qpolicy: 0 = best_effort_reliability_qos, 1 = reliable_reliability_qos
:type qpolicy: int | set quality of service reliability mode | [
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""" set quality of service reliability mode
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:type qpolicy: int
"""
return sub_set_qos_reliability(self.thandle, qpolicy) | [
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wlanjie/AndroidFFmpeg | 7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf | tools/fdk-aac-build/armeabi/toolchain/lib/python2.7/base64.py | python | encodestring | (s) | return "".join(pieces) | Encode a string into multiple lines of base-64 data. | Encode a string into multiple lines of base-64 data. | [
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"""Encode a string into multiple lines of base-64 data."""
pieces = []
for i in range(0, len(s), MAXBINSIZE):
chunk = s[i : i + MAXBINSIZE]
pieces.append(binascii.b2a_base64(chunk))
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miyosuda/TensorFlowAndroidMNIST | 7b5a4603d2780a8a2834575706e9001977524007 | jni-build/jni/include/tensorflow/models/image/cifar10/cifar10_input.py | python | read_cifar10 | (filename_queue) | return result | Reads and parses examples from CIFAR10 data files.
Recommendation: if you want N-way read parallelism, call this function
N times. This will give you N independent Readers reading different
files & positions within those files, which will give better mixing of
examples.
Args:
filename_queue: A queue of strings with the filenames to read from.
Returns:
An object representing a single example, with the following fields:
height: number of rows in the result (32)
width: number of columns in the result (32)
depth: number of color channels in the result (3)
key: a scalar string Tensor describing the filename & record number
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label: an int32 Tensor with the label in the range 0..9.
uint8image: a [height, width, depth] uint8 Tensor with the image data | Reads and parses examples from CIFAR10 data files. | [
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"""Reads and parses examples from CIFAR10 data files.
Recommendation: if you want N-way read parallelism, call this function
N times. This will give you N independent Readers reading different
files & positions within those files, which will give better mixing of
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Args:
filename_queue: A queue of strings with the filenames to read from.
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width: number of columns in the result (32)
depth: number of color channels in the result (3)
key: a scalar string Tensor describing the filename & record number
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label: an int32 Tensor with the label in the range 0..9.
uint8image: a [height, width, depth] uint8 Tensor with the image data
"""
class CIFAR10Record(object):
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result = CIFAR10Record()
# Dimensions of the images in the CIFAR-10 dataset.
# See http://www.cs.toronto.edu/~kriz/cifar.html for a description of the
# input format.
label_bytes = 1 # 2 for CIFAR-100
result.height = 32
result.width = 32
result.depth = 3
image_bytes = result.height * result.width * result.depth
# Every record consists of a label followed by the image, with a
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record_bytes = label_bytes + image_bytes
# Read a record, getting filenames from the filename_queue. No
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reader = tf.FixedLengthRecordReader(record_bytes=record_bytes)
result.key, value = reader.read(filename_queue)
# Convert from a string to a vector of uint8 that is record_bytes long.
record_bytes = tf.decode_raw(value, tf.uint8)
# The first bytes represent the label, which we convert from uint8->int32.
result.label = tf.cast(
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# from [depth * height * width] to [depth, height, width].
depth_major = tf.reshape(tf.slice(record_bytes, [label_bytes], [image_bytes]),
[result.depth, result.height, result.width])
# Convert from [depth, height, width] to [height, width, depth].
result.uint8image = tf.transpose(depth_major, [1, 2, 0])
return result | [
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mantidproject/mantid | 03deeb89254ec4289edb8771e0188c2090a02f32 | scripts/reduction_gui/reduction/diffraction/diffraction_adv_setup_script.py | python | AdvancedSetupScript.to_script | (self) | return script | 'Public' method to save the current GUI to string via str() and general class ReductionScript | 'Public' method to save the current GUI to string via str() and general class ReductionScript | [
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""" 'Public' method to save the current GUI to string via str() and general class ReductionScript
"""
# 1. Form (partial) script
parnamevaluedict = self.buildParameterDict()
script = ""
for parname in self.parnamelist:
parvalue = parnamevaluedict[parname]
if parvalue != "" and parname != "Instrument" and parname != "Facility":
if str(parvalue) == "True":
parvalue = "1"
elif str(parvalue) == "False":
parvalue = "0"
if not isinstance(parvalue, dict):
script += "%-10s = \"%s\",\n" % (parname, parvalue)
else:
script += "%-10s = %s,\n" % (parname, parvalue)
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return script | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/idlelib/configdialog.py | python | VarTrace.clear | (self) | Clear lists (for tests). | Clear lists (for tests). | [
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] | def clear(self):
"Clear lists (for tests)."
# Call after all tests in a module to avoid memory leaks.
self.untraced.clear()
self.traced.clear() | [
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FreeCAD/FreeCAD | ba42231b9c6889b89e064d6d563448ed81e376ec | src/Mod/Arch/importIFClegacy.py | python | IfcSchema.readTypes | (self) | return types | Parse all the possible types from the schema,
returns a dictionary Name -> Type | Parse all the possible types from the schema,
returns a dictionary Name -> Type | [
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"""
Parse all the possible types from the schema,
returns a dictionary Name -> Type
"""
types = {}
for m in re.finditer("TYPE (.*) = (.*);", self.data):
typename, typetype = m.groups()
if typetype in self.SIMPLETYPES:
types[typename] = typetype
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types[typename] = "#" + typetype
return types | [
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mantidproject/mantid | 03deeb89254ec4289edb8771e0188c2090a02f32 | scripts/Inelastic/dos/load_euphonic.py | python | euphonic_calculate_modes | (filename: str, cutoff: float = 20.,
gamma: bool = True,
acoustic_sum_rule: Optional[str] = 'reciprocal') | return modes | Read force constants file with Euphonic and sample frequencies/modes
:param filename: Input data
:param cutoff:
Sampling density of Brillouin-zone. Specified as real-space length
cutoff in Angstrom.
:param gamma:
Shift sampling grid to include the Gamma-point.
:param acoustic_sum_rule:
Apply acoustic sum rule correction to force constants: options are
'realspace' and 'reciprocal', specifying different implementations of
the correction. If None, no correction is applied. This option is
referred to as "asr" in the Euphonic python API and command-line tools.
:returns: euphonic.QpointPhononModes | Read force constants file with Euphonic and sample frequencies/modes | [
"Read",
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] | def euphonic_calculate_modes(filename: str, cutoff: float = 20.,
gamma: bool = True,
acoustic_sum_rule: Optional[str] = 'reciprocal'):
"""
Read force constants file with Euphonic and sample frequencies/modes
:param filename: Input data
:param cutoff:
Sampling density of Brillouin-zone. Specified as real-space length
cutoff in Angstrom.
:param gamma:
Shift sampling grid to include the Gamma-point.
:param acoustic_sum_rule:
Apply acoustic sum rule correction to force constants: options are
'realspace' and 'reciprocal', specifying different implementations of
the correction. If None, no correction is applied. This option is
referred to as "asr" in the Euphonic python API and command-line tools.
:returns: euphonic.QpointPhononModes
"""
from math import ceil
from euphonic.cli.utils import force_constants_from_file
from euphonic.util import mp_grid
fc = force_constants_from_file(filename)
recip_lattice_lengths = np.linalg.norm(
fc.crystal.reciprocal_cell().to('1/angstrom').magnitude, axis=1)
mp_sampling = [ceil(x)
for x in (cutoff * recip_lattice_lengths / (2 * np.pi))]
qpts = mp_grid(mp_sampling)
if gamma:
mp_sampling = np.array(mp_sampling, dtype=int)
# Shift directions with even number of samples by half the grid spacing
offsets = ((mp_sampling + 1) % 2) * (0.5 / mp_sampling)
qpts += offsets
logger.notice('Calculating phonon modes on {} grid'.format(
'x'.join(map(str, mp_sampling))))
modes = fc.calculate_qpoint_phonon_modes(qpts, asr=acoustic_sum_rule)
return modes | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/msw/xrc.py | python | XmlNode.AddPropertyName | (*args, **kwargs) | return _xrc.XmlNode_AddPropertyName(*args, **kwargs) | AddPropertyName(self, String name, String value) | AddPropertyName(self, String name, String value) | [
"AddPropertyName",
"(",
"self",
"String",
"name",
"String",
"value",
")"
] | def AddPropertyName(*args, **kwargs):
"""AddPropertyName(self, String name, String value)"""
return _xrc.XmlNode_AddPropertyName(*args, **kwargs) | [
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ArduPilot/ardupilot | 6e684b3496122b8158ac412b609d00004b7ac306 | libraries/AP_HAL_ChibiOS/hwdef/scripts/chibios_hwdef.py | python | write_ROMFS | (outdir) | create ROMFS embedded header | create ROMFS embedded header | [
"create",
"ROMFS",
"embedded",
"header"
] | def write_ROMFS(outdir):
'''create ROMFS embedded header'''
romfs_list = []
for k in romfs.keys():
romfs_list.append((k, romfs[k]))
env_vars['ROMFS_FILES'] = romfs_list | [
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