nwo stringlengths 5 86 | sha stringlengths 40 40 | path stringlengths 4 189 | language stringclasses 1 value | identifier stringlengths 1 94 | parameters stringlengths 2 4.03k | argument_list stringclasses 1 value | return_statement stringlengths 0 11.5k | docstring stringlengths 1 33.2k | docstring_summary stringlengths 0 5.15k | docstring_tokens list | function stringlengths 34 151k | function_tokens list | url stringlengths 90 278 |
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netease-youdao/hex | d7b8773dae8dde63f3807cef1d48c017077db727 | tools/patch_util.py | python | from_file | (filename) | return patch | read and parse patch file
return PatchInfo() object | read and parse patch file
return PatchInfo() object | [
"read",
"and",
"parse",
"patch",
"file",
"return",
"PatchInfo",
"()",
"object"
] | def from_file(filename):
""" read and parse patch file
return PatchInfo() object
"""
info("reading patch from file %s" % filename)
fp = open(filename, "rb")
patch = PatchInfo(fp)
fp.close()
return patch | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/importlib-metadata/py2/importlib_metadata/__init__.py | python | Distribution._convert_egg_info_reqs_to_simple_reqs | (sections) | Historically, setuptools would solicit and store 'extra'
requirements, including those with environment markers,
in separate sections. More modern tools expect each
dependency to be defined separately, with any relevant
extras and environment markers attached directly to that
requirement. This method converts the former to the
latter. See _test_deps_from_requires_text for an example. | Historically, setuptools would solicit and store 'extra'
requirements, including those with environment markers,
in separate sections. More modern tools expect each
dependency to be defined separately, with any relevant
extras and environment markers attached directly to that
requirement. This method converts the former to the
latter. See _test_deps_from_requires_text for an example. | [
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"""
Historically, setuptools would solicit and store 'extra'
requirements, including those with environment markers,
in separate sections. More modern tools expect each
dependency to be defined separately, with any relevant
extras and environment markers attached directly to that
requirement. This method converts the former to the
latter. See _test_deps_from_requires_text for an example.
"""
def make_condition(name):
return name and 'extra == "{name}"'.format(name=name)
def parse_condition(section):
section = section or ''
extra, sep, markers = section.partition(':')
if extra and markers:
markers = '({markers})'.format(markers=markers)
conditions = list(filter(None, [markers, make_condition(extra)]))
return '; ' + ' and '.join(conditions) if conditions else ''
for section, deps in sections.items():
for dep in deps:
yield dep + parse_condition(section) | [
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ideawu/ssdb | f229ba277c7f7d0ca5a441c0c6fb3d1209af68e4 | deps/cpy/antlr3/tree.py | python | Tree.freshenParentAndChildIndexes | (self) | Set the parent and child index values for all children | Set the parent and child index values for all children | [
"Set",
"the",
"parent",
"and",
"child",
"index",
"values",
"for",
"all",
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] | def freshenParentAndChildIndexes(self):
"""Set the parent and child index values for all children"""
raise NotImplementedError | [
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y123456yz/reading-and-annotate-mongodb-3.6 | 93280293672ca7586dc24af18132aa61e4ed7fcf | mongo/src/third_party/scons-2.5.0/scons-local-2.5.0/SCons/Tool/GettextCommon.py | python | _detect_xgettext | (env) | return None | Detects *xgettext(1)* binary | Detects *xgettext(1)* binary | [
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"(",
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] | def _detect_xgettext(env):
""" Detects *xgettext(1)* binary """
if env.has_key('XGETTEXT'):
return env['XGETTEXT']
xgettext = env.Detect('xgettext');
if xgettext:
return xgettext
raise SCons.Errors.StopError(XgettextNotFound,"Could not detect xgettext")
return None | [
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hanpfei/chromium-net | 392cc1fa3a8f92f42e4071ab6e674d8e0482f83f | third_party/catapult/telemetry/telemetry/internal/platform/profiler/android_profiling_helper.py | python | CreateSymFs | (device, symfs_dir, libraries, use_symlinks=True) | return output_kallsyms | Creates a symfs directory to be used for symbolizing profiles.
Prepares a set of files ("symfs") to be used with profilers such as perf for
converting binary addresses into human readable function names.
Args:
device: DeviceUtils instance identifying the target device.
symfs_dir: Path where the symfs should be created.
libraries: Set of library file names that should be included in the symfs.
use_symlinks: If True, link instead of copy unstripped libraries into the
symfs. This will speed up the operation, but the resulting symfs will no
longer be valid if the linked files are modified, e.g., by rebuilding.
Returns:
The absolute path to the kernel symbols within the created symfs. | Creates a symfs directory to be used for symbolizing profiles. | [
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"""Creates a symfs directory to be used for symbolizing profiles.
Prepares a set of files ("symfs") to be used with profilers such as perf for
converting binary addresses into human readable function names.
Args:
device: DeviceUtils instance identifying the target device.
symfs_dir: Path where the symfs should be created.
libraries: Set of library file names that should be included in the symfs.
use_symlinks: If True, link instead of copy unstripped libraries into the
symfs. This will speed up the operation, but the resulting symfs will no
longer be valid if the linked files are modified, e.g., by rebuilding.
Returns:
The absolute path to the kernel symbols within the created symfs.
"""
logging.info('Building symfs into %s.' % symfs_dir)
for lib in libraries:
device_dir = os.path.dirname(lib)
output_dir = os.path.join(symfs_dir, device_dir[1:])
if not os.path.exists(output_dir):
os.makedirs(output_dir)
output_lib = os.path.join(output_dir, os.path.basename(lib))
if lib.startswith('/data/app'):
# If this is our own library instead of a system one, look for a matching
# unstripped library under the out directory.
unstripped_host_lib = _FindMatchingUnstrippedLibraryOnHost(device, lib)
if not unstripped_host_lib:
logging.warning('Could not find symbols for %s.' % lib)
logging.warning('Is the correct output directory selected '
'(CHROMIUM_OUTPUT_DIR)? Did you install the APK after '
'building?')
continue
if use_symlinks:
if os.path.lexists(output_lib):
os.remove(output_lib)
os.symlink(os.path.abspath(unstripped_host_lib), output_lib)
# Copy the unstripped library only if it has been changed to avoid the
# delay.
elif not _FileMetadataMatches(unstripped_host_lib, output_lib):
logging.info('Copying %s to %s' % (unstripped_host_lib, output_lib))
shutil.copy2(unstripped_host_lib, output_lib)
else:
# Otherwise save a copy of the stripped system library under the symfs so
# the profiler can at least use the public symbols of that library. To
# speed things up, only pull files that don't match copies we already
# have in the symfs.
if not os.path.exists(output_lib):
pull = True
else:
host_md5sums = md5sum.CalculateHostMd5Sums([output_lib])
try:
device_md5sums = md5sum.CalculateDeviceMd5Sums([lib], device)
except:
logging.exception('New exception caused by DeviceUtils conversion')
raise
pull = True
if host_md5sums and device_md5sums and output_lib in host_md5sums \
and lib in device_md5sums:
pull = host_md5sums[output_lib] != device_md5sums[lib]
if pull:
logging.info('Pulling %s to %s', lib, output_lib)
device.PullFile(lib, output_lib)
# Also pull a copy of the kernel symbols.
output_kallsyms = os.path.join(symfs_dir, 'kallsyms')
if not os.path.exists(output_kallsyms):
device.PullFile('/proc/kallsyms', output_kallsyms)
return output_kallsyms | [
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ceph/ceph | 959663007321a369c83218414a29bd9dbc8bda3a | qa/tasks/rook.py | python | task | (ctx, config) | Deploy rook-ceph cluster
tasks:
- kubeadm:
- rook:
branch: wip-foo
spec:
mon:
count: 1
The spec item is deep-merged against the cluster.yaml. The branch, sha1, or
image items are used to determine the Ceph container image. | Deploy rook-ceph cluster | [
"Deploy",
"rook",
"-",
"ceph",
"cluster"
] | def task(ctx, config):
"""
Deploy rook-ceph cluster
tasks:
- kubeadm:
- rook:
branch: wip-foo
spec:
mon:
count: 1
The spec item is deep-merged against the cluster.yaml. The branch, sha1, or
image items are used to determine the Ceph container image.
"""
if not config:
config = {}
assert isinstance(config, dict), \
"task only supports a dictionary for configuration"
log.info('Rook start')
overrides = ctx.config.get('overrides', {})
teuthology.deep_merge(config, overrides.get('ceph', {}))
teuthology.deep_merge(config, overrides.get('rook', {}))
log.info('Config: ' + str(config))
# set up cluster context
if not hasattr(ctx, 'rook'):
ctx.rook = {}
if 'cluster' not in config:
config['cluster'] = 'ceph'
cluster_name = config['cluster']
if cluster_name not in ctx.rook:
ctx.rook[cluster_name] = argparse.Namespace()
ctx.rook[cluster_name].remote = list(ctx.cluster.remotes.keys())[0]
# image
teuth_defaults = teuth_config.get('defaults', {})
cephadm_defaults = teuth_defaults.get('cephadm', {})
containers_defaults = cephadm_defaults.get('containers', {})
container_image_name = containers_defaults.get('image', None)
if 'image' in config:
ctx.rook[cluster_name].image = config.get('image')
else:
sha1 = config.get('sha1')
flavor = config.get('flavor', 'default')
if sha1:
if flavor == "crimson":
ctx.rook[cluster_name].image = container_image_name + ':' + sha1 + '-' + flavor
else:
ctx.rook[cluster_name].image = container_image_name + ':' + sha1
else:
# hmm, fall back to branch?
branch = config.get('branch', 'master')
ctx.rook[cluster_name].image = container_image_name + ':' + branch
log.info('Ceph image is %s' % ctx.rook[cluster_name].image)
with contextutil.nested(
lambda: rook_operator(ctx, config),
lambda: ceph_log(ctx, config),
lambda: rook_cluster(ctx, config),
lambda: rook_toolbox(ctx, config),
lambda: wait_for_orch(ctx, config),
lambda: rook_post_config(ctx, config),
lambda: wait_for_osds(ctx, config),
lambda: ceph_config_keyring(ctx, config),
lambda: ceph_clients(ctx, config),
):
if not hasattr(ctx, 'managers'):
ctx.managers = {}
ctx.managers[cluster_name] = CephManager(
ctx.rook[cluster_name].remote,
ctx=ctx,
logger=log.getChild('ceph_manager.' + cluster_name),
cluster=cluster_name,
rook=True,
)
try:
if config.get('wait-for-healthy', True):
healthy(ctx=ctx, config=config)
log.info('Rook complete, yielding')
yield
finally:
to_remove = []
ret = _shell(ctx, config, ['ceph', 'orch', 'ls', '-f', 'json'], stdout=BytesIO())
if ret.exitstatus == 0:
r = json.loads(ret.stdout.getvalue().decode('utf-8'))
for service in r:
if service['service_type'] in ['rgw', 'mds', 'nfs', 'rbd-mirror']:
_shell(ctx, config, ['ceph', 'orch', 'rm', service['service_name']])
to_remove.append(service['service_name'])
with safe_while(sleep=10, tries=90, action="waiting for service removal") as proceed:
while proceed():
ret = _shell(ctx, config, ['ceph', 'orch', 'ls', '-f', 'json'], stdout=BytesIO())
if ret.exitstatus == 0:
r = json.loads(ret.stdout.getvalue().decode('utf-8'))
still_up = [service['service_name'] for service in r]
matches = set(still_up).intersection(to_remove)
if not matches:
break
log.info('Tearing down rook') | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/xml/dom/minidom.py | python | ElementInfo.isEmpty | (self) | return False | Returns true iff this element is declared to have an EMPTY
content model. | Returns true iff this element is declared to have an EMPTY
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bulletphysics/bullet3 | f0f2a952e146f016096db6f85cf0c44ed75b0b9a | examples/pybullet/gym/pybullet_envs/minitaur/envs/minitaur_rainbow_dash.py | python | MinitaurRainbowDash._ResetPoseForLeg | (self, leg_id, add_constraint) | Reset the initial pose for the leg.
Args:
leg_id: It should be 0, 1, 2, or 3, which represents the leg at
front_left, back_left, front_right and back_right.
add_constraint: Whether to add a constraint at the joints of two feet. | Reset the initial pose for the leg. | [
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"""Reset the initial pose for the leg.
Args:
leg_id: It should be 0, 1, 2, or 3, which represents the leg at
front_left, back_left, front_right and back_right.
add_constraint: Whether to add a constraint at the joints of two feet.
"""
knee_friction_force = 0
half_pi = math.pi / 2.0
knee_angle = -2.1834
leg_position = minitaur.LEG_POSITION[leg_id]
self._pybullet_client.resetJointState(self.quadruped,
self._joint_name_to_id["motor_" + leg_position +
"L_joint"],
self._motor_direction[2 * leg_id] * half_pi,
targetVelocity=0)
self._pybullet_client.resetJointState(self.quadruped,
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self._motor_direction[2 * leg_id + 1] * knee_angle,
targetVelocity=0)
if add_constraint:
if leg_id < 2:
self._pybullet_client.createConstraint(
self.quadruped, self._joint_name_to_id["knee_" + leg_position + "R_joint"],
self.quadruped, self._joint_name_to_id["knee_" + leg_position + "L_joint"],
self._pybullet_client.JOINT_POINT2POINT, [0, 0, 0], KNEE_CONSTRAINT_POINT_SHORT,
KNEE_CONSTRAINT_POINT_LONG)
else:
self._pybullet_client.createConstraint(
self.quadruped, self._joint_name_to_id["knee_" + leg_position + "R_joint"],
self.quadruped, self._joint_name_to_id["knee_" + leg_position + "L_joint"],
self._pybullet_client.JOINT_POINT2POINT, [0, 0, 0], KNEE_CONSTRAINT_POINT_LONG,
KNEE_CONSTRAINT_POINT_SHORT)
if self._accurate_motor_model_enabled or self._pd_control_enabled:
# Disable the default motor in pybullet.
self._pybullet_client.setJointMotorControl2(
bodyIndex=self.quadruped,
jointIndex=(self._joint_name_to_id["motor_" + leg_position + "L_joint"]),
controlMode=self._pybullet_client.VELOCITY_CONTROL,
targetVelocity=0,
force=knee_friction_force)
self._pybullet_client.setJointMotorControl2(
bodyIndex=self.quadruped,
jointIndex=(self._joint_name_to_id["motor_" + leg_position + "R_joint"]),
controlMode=self._pybullet_client.VELOCITY_CONTROL,
targetVelocity=0,
force=knee_friction_force)
else:
self._SetDesiredMotorAngleByName("motor_" + leg_position + "L_joint",
self._motor_direction[2 * leg_id] * half_pi)
self._SetDesiredMotorAngleByName("motor_" + leg_position + "R_joint",
self._motor_direction[2 * leg_id + 1] * half_pi)
self._pybullet_client.setJointMotorControl2(
bodyIndex=self.quadruped,
jointIndex=(self._joint_name_to_id["knee_" + leg_position + "L_joint"]),
controlMode=self._pybullet_client.VELOCITY_CONTROL,
targetVelocity=0,
force=knee_friction_force)
self._pybullet_client.setJointMotorControl2(
bodyIndex=self.quadruped,
jointIndex=(self._joint_name_to_id["knee_" + leg_position + "R_joint"]),
controlMode=self._pybullet_client.VELOCITY_CONTROL,
targetVelocity=0,
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] | https://github.com/bulletphysics/bullet3/blob/f0f2a952e146f016096db6f85cf0c44ed75b0b9a/examples/pybullet/gym/pybullet_envs/minitaur/envs/minitaur_rainbow_dash.py#L91-L170 | ||
wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_cocoa/propgrid.py | python | PGArrayEditorDialog.SetDialogValue | (*args, **kwargs) | return _propgrid.PGArrayEditorDialog_SetDialogValue(*args, **kwargs) | SetDialogValue(self, wxVariant value) | SetDialogValue(self, wxVariant value) | [
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",",
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] | https://github.com/wxWidgets/wxPython-Classic/blob/19571e1ae65f1ac445f5491474121998c97a1bf0/src/osx_cocoa/propgrid.py#L3190-L3192 | |
eclipse/sumo | 7132a9b8b6eea734bdec38479026b4d8c4336d03 | tools/contributed/sumopy/coremodules/demand/origin_to_destination_wxgui.py | python | AddODflowTool.deactivate | (self) | This call by metacanvas signals that the tool has been
deactivated and can now interact with metacanvas. | This call by metacanvas signals that the tool has been
deactivated and can now interact with metacanvas. | [
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"now",
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] | def deactivate(self):
"""
This call by metacanvas signals that the tool has been
deactivated and can now interact with metacanvas.
"""
self._is_active = False
self.unhighlight_zones()
self._canvas.draw()
self.deactivate_select() | [
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HKUST-Aerial-Robotics/Teach-Repeat-Replan | 98505a7f74b13c8b501176ff838a38423dbef536 | utils/pose_utils/build/devel/_setup_util.py | python | find_env_hooks | (environ, cmake_prefix_path) | return lines | Generate shell code with found environment hooks
for the all workspaces. | Generate shell code with found environment hooks
for the all workspaces. | [
"Generate",
"shell",
"code",
"with",
"found",
"environment",
"hooks",
"for",
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"workspaces",
"."
] | def find_env_hooks(environ, cmake_prefix_path):
'''
Generate shell code with found environment hooks
for the all workspaces.
'''
lines = []
lines.append(comment('found environment hooks in workspaces'))
generic_env_hooks = []
generic_env_hooks_workspace = []
specific_env_hooks = []
specific_env_hooks_workspace = []
generic_env_hooks_by_filename = {}
specific_env_hooks_by_filename = {}
generic_env_hook_ext = 'bat' if IS_WINDOWS else 'sh'
specific_env_hook_ext = environ['CATKIN_SHELL'] if not IS_WINDOWS and 'CATKIN_SHELL' in environ and environ['CATKIN_SHELL'] else None
# remove non-workspace paths
workspaces = [path for path in cmake_prefix_path.split(os.pathsep) if path and os.path.isfile(os.path.join(path, CATKIN_MARKER_FILE))]
for workspace in reversed(workspaces):
env_hook_dir = os.path.join(workspace, 'etc', 'catkin', 'profile.d')
if os.path.isdir(env_hook_dir):
for filename in sorted(os.listdir(env_hook_dir)):
if filename.endswith('.%s' % generic_env_hook_ext):
# remove previous env hook with same name if present
if filename in generic_env_hooks_by_filename:
i = generic_env_hooks.index(generic_env_hooks_by_filename[filename])
generic_env_hooks.pop(i)
generic_env_hooks_workspace.pop(i)
# append env hook
generic_env_hooks.append(os.path.join(env_hook_dir, filename))
generic_env_hooks_workspace.append(workspace)
generic_env_hooks_by_filename[filename] = generic_env_hooks[-1]
elif specific_env_hook_ext is not None and filename.endswith('.%s' % specific_env_hook_ext):
# remove previous env hook with same name if present
if filename in specific_env_hooks_by_filename:
i = specific_env_hooks.index(specific_env_hooks_by_filename[filename])
specific_env_hooks.pop(i)
specific_env_hooks_workspace.pop(i)
# append env hook
specific_env_hooks.append(os.path.join(env_hook_dir, filename))
specific_env_hooks_workspace.append(workspace)
specific_env_hooks_by_filename[filename] = specific_env_hooks[-1]
env_hooks = generic_env_hooks + specific_env_hooks
env_hooks_workspace = generic_env_hooks_workspace + specific_env_hooks_workspace
count = len(env_hooks)
lines.append(assignment('_CATKIN_ENVIRONMENT_HOOKS_COUNT', count))
for i in range(count):
lines.append(assignment('_CATKIN_ENVIRONMENT_HOOKS_%d' % i, env_hooks[i]))
lines.append(assignment('_CATKIN_ENVIRONMENT_HOOKS_%d_WORKSPACE' % i, env_hooks_workspace[i]))
return lines | [
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] | https://github.com/HKUST-Aerial-Robotics/Teach-Repeat-Replan/blob/98505a7f74b13c8b501176ff838a38423dbef536/utils/pose_utils/build/devel/_setup_util.py#L195-L244 | |
gimli-org/gimli | 17aa2160de9b15ababd9ef99e89b1bc3277bbb23 | pygimli/solver/solver.py | python | checkCFL | (times, mesh, vMax, verbose=False) | return c | Check Courant-Friedrichs-Lewy condition.
For advection and flow problems. CFL Number should be lower then 1 to
ensure stability.
Parameters
---------- | Check Courant-Friedrichs-Lewy condition. | [
"Check",
"Courant",
"-",
"Friedrichs",
"-",
"Lewy",
"condition",
"."
] | def checkCFL(times, mesh, vMax, verbose=False):
"""Check Courant-Friedrichs-Lewy condition.
For advection and flow problems. CFL Number should be lower then 1 to
ensure stability.
Parameters
----------
"""
if pg.isScalar(times):
dt = times
else:
dt = times[1] - times[0]
dx = min(mesh.h())
# min(entity.shape().h()
# if mesh.dimension() == 1:
# dx = min(mesh.cellSizes())
# else:
# dx = min(mesh.boundarySizes())
c = vMax * dt / dx
if c > 1:
pg.warn("Courant-Friedrichs-Lewy Number:", c,
"but should be lower 1 to ensure movement inside a cell "
"per timestep. ("
"vMax =", vMax,
"dt =", dt,
"dx =", dx,
"dt <", dx/vMax,
" | N > ", int(dt/(dx/vMax))+1, ")")
if verbose:
pg.info("Courant-Friedrichs-Lewy Number:", c)
return c | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/tools/python/src/Lib/plat-riscos/riscospath.py | python | walk | (top, func, arg) | Directory tree walk with callback function.
For each directory in the directory tree rooted at top (including top
itself, but excluding '.' and '..'), call func(arg, dirname, fnames).
dirname is the name of the directory, and fnames a list of the names of
the files and subdirectories in dirname (excluding '.' and '..'). func
may modify the fnames list in-place (e.g. via del or slice assignment),
and walk will only recurse into the subdirectories whose names remain in
fnames; this can be used to implement a filter, or to impose a specific
order of visiting. No semantics are defined for, or required of, arg,
beyond that arg is always passed to func. It can be used, e.g., to pass
a filename pattern, or a mutable object designed to accumulate
statistics. Passing None for arg is common. | Directory tree walk with callback function. | [
"Directory",
"tree",
"walk",
"with",
"callback",
"function",
"."
] | def walk(top, func, arg):
"""Directory tree walk with callback function.
For each directory in the directory tree rooted at top (including top
itself, but excluding '.' and '..'), call func(arg, dirname, fnames).
dirname is the name of the directory, and fnames a list of the names of
the files and subdirectories in dirname (excluding '.' and '..'). func
may modify the fnames list in-place (e.g. via del or slice assignment),
and walk will only recurse into the subdirectories whose names remain in
fnames; this can be used to implement a filter, or to impose a specific
order of visiting. No semantics are defined for, or required of, arg,
beyond that arg is always passed to func. It can be used, e.g., to pass
a filename pattern, or a mutable object designed to accumulate
statistics. Passing None for arg is common."""
try:
names= os.listdir(top)
except os.error:
return
func(arg, top, names)
for name in names:
name= join(top, name)
if isdir(name) and not islink(name):
walk(name, func, arg) | [
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krishauser/Klampt | 972cc83ea5befac3f653c1ba20f80155768ad519 | Python/python2_version/klampt/sim/simulation.py | python | DefaultActuatorEmulator.process | (self,commands,dt) | return | Commands: a dictionary of values outputted from the controller module,
or None if no command was issued. | Commands: a dictionary of values outputted from the controller module,
or None if no command was issued. | [
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] | def process(self,commands,dt):
"""Commands: a dictionary of values outputted from the controller module,
or None if no command was issued. """
if commands == None: return
c = self.controller
defaultVals = set(['torquecmd','qcmd','dqcmd','tcmd'])
if 'qcmd' in commands:
dqcmd = commands['dqcmd'] if 'dqcmd' in commands else [0.0]*len(commands['qcmd'])
if 'torquecmd' in commands:
c.setPIDCommand(commands['qcmd'],dqcmd,commands['torquecmd'])
else:
c.setPIDCommand(commands['qcmd'],dqcmd)
elif 'dqcmd' in commands:
assert 'tcmd' in commands
c.setVelocity(commands['dqcmd'],commands['tcmd'])
elif 'torquecmd' in commands:
c.setTorque(commands['torquecmd'])
for (k,v) in commands.iteritems():
if k not in defaultVals:
print "Sending command",k,v,"to low level controller"
c.sendCommand(k,v)
return | [
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neopenx/Dragon | 0e639a7319035ddc81918bd3df059230436ee0a1 | Dragon/python/dragon/vm/caffe/net_spec.py | python | to_proto | (*tops) | return net | Generate a NetParameter that contains all layers needed to compute
all arguments. | Generate a NetParameter that contains all layers needed to compute
all arguments. | [
"Generate",
"a",
"NetParameter",
"that",
"contains",
"all",
"layers",
"needed",
"to",
"compute",
"all",
"arguments",
"."
] | def to_proto(*tops):
"""Generate a NetParameter that contains all layers needed to compute
all arguments."""
layers = OrderedDict()
autonames = Counter()
for top in tops:
top.fn._to_proto(layers, {}, autonames)
net = caffe_pb2.NetParameter()
net.layer.extend(layers.values())
return net | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_cocoa/_misc.py | python | ConfigBase_Create | (*args) | return _misc_.ConfigBase_Create(*args) | ConfigBase_Create() -> ConfigBase
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create the "best" implementation of wx.Config available for the
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Create and return a new global config object. This function will
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"""
return _misc_.ConfigBase_Create(*args) | [
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apple/turicreate | cce55aa5311300e3ce6af93cb45ba791fd1bdf49 | deps/src/libxml2-2.9.1/python/libxml2.py | python | xmlNode.hasNsProp | (self, name, nameSpace) | return __tmp | Search for an attribute associated to a node This attribute
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apache/kudu | 90895ce76590f10730ad7aac3613b69d89ff5422 | build-support/iwyu/fix_includes.py | python | _GetSymbolNameFromForwardDeclareLine | (line) | return symbol_name | Given a forward declare line to add from iwyu output, get symbol.
Two possibilities: In or not in namespace(s).
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symbolname_re = re.compile(r'([A-Za-z0-9_]+)')
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namespaces_in_line = iwyu_namespace_re.findall(line.replace(
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hanpfei/chromium-net | 392cc1fa3a8f92f42e4071ab6e674d8e0482f83f | tools/site_compare/operators/equals.py | python | Compare | (file1, file2, **kwargs) | Compares two images to see if they're identical.
Args:
file1: path to first image to compare
file2: path to second image to compare
kwargs: unused for this operator
Returns:
None if the images are identical
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"""Compares two images to see if they're identical.
Args:
file1: path to first image to compare
file2: path to second image to compare
kwargs: unused for this operator
Returns:
None if the images are identical
A tuple of (errorstring, image) if they're not
"""
kwargs = kwargs # unused parameter
im1 = Image.open(file1)
im2 = Image.open(file2)
if im1.size != im2.size:
return ("The images are of different size (%s vs %s)" %
(im1.size, im2.size), im1)
diff = ImageChops.difference(im1, im2)
if max(diff.getextrema()) != (0, 0):
return ("The images differ", diff)
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/traitlets/py3/traitlets/config/configurable.py | python | Configurable.class_config_rst_doc | (cls) | return '\n'.join(lines) | Generate rST documentation for this class' config options.
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"""Generate rST documentation for this class' config options.
Excludes traits defined on parent classes.
"""
lines = []
classname = cls.__name__
for k, trait in sorted(cls.class_traits(config=True).items()):
ttype = trait.__class__.__name__
termline = classname + '.' + trait.name
# Choices or type
if 'Enum' in ttype:
# include Enum choices
termline += ' : ' + trait.info_rst()
else:
termline += ' : ' + ttype
lines.append(termline)
# Default value
try:
dvr = trait.default_value_repr()
except Exception:
dvr = None # ignore defaults we can't construct
if dvr is not None:
if len(dvr) > 64:
dvr = dvr[:61]+'...'
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dvr = dvr.replace("\\n", "\\\\n")
lines.append(indent("Default: ``%s``" % dvr))
lines.append("")
help = trait.help or 'No description'
lines.append(indent(dedent(help)))
# Blank line
lines.append('')
return '\n'.join(lines) | [
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hanpfei/chromium-net | 392cc1fa3a8f92f42e4071ab6e674d8e0482f83f | third_party/catapult/third_party/webapp2/webapp2_extras/sessions.py | python | SessionStore.__init__ | (self, request, config=None) | Initializes the session store.
:param request:
A :class:`webapp2.Request` instance.
:param config:
A dictionary of configuration values to be overridden. See
the available keys in :data:`default_config`. | Initializes the session store. | [
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"""Initializes the session store.
:param request:
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:param config:
A dictionary of configuration values to be overridden. See
the available keys in :data:`default_config`.
"""
self.request = request
# Base configuration.
self.config = request.app.config.load_config(self.config_key,
default_values=default_config, user_values=config,
required_keys=('secret_key',))
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miyosuda/TensorFlowAndroidDemo | 35903e0221aa5f109ea2dbef27f20b52e317f42d | jni-build/jni/include/tensorflow/contrib/factorization/python/ops/gmm_ops.py | python | GmmAlgorithm._define_full_covariance_probs | (self, shard_id, shard) | Defines the full covariance probabilties per example in a class.
Updates a matrix with dimension num_examples X num_classes.
Args:
shard_id: id of the current shard.
shard: current data shard, 1 X num_examples X dimensions. | Defines the full covariance probabilties per example in a class. | [
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Updates a matrix with dimension num_examples X num_classes.
Args:
shard_id: id of the current shard.
shard: current data shard, 1 X num_examples X dimensions.
"""
diff = shard - self._means
cholesky = tf.batch_cholesky(self._covs + self._min_var)
log_det_covs = 2.0 * tf.reduce_sum(tf.log(
tf.batch_matrix_diag_part(cholesky)), 1)
x_mu_cov = tf.square(tf.batch_matrix_triangular_solve(
cholesky, tf.transpose(diff, perm=[0, 2, 1]),
lower=True))
diag_m = tf.transpose(tf.reduce_sum(x_mu_cov, 1))
self._probs[shard_id] = -0.5 * (
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naver/sling | 5671cd445a2caae0b4dd0332299e4cfede05062c | webkit/Tools/Scripts/webkitpy/thirdparty/mod_pywebsocket/mux.py | python | _LogicalStream.send_ping | (self, body='') | Overrides Stream.send_ping | Overrides Stream.send_ping | [
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"""Overrides Stream.send_ping"""
self._logger.debug('Sending ping on logical channel %d: %r' %
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self._write_inner_frame(common.OPCODE_PING, body, end=True)
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Polidea/SiriusObfuscator | b0e590d8130e97856afe578869b83a209e2b19be | SymbolExtractorAndRenamer/lldb/scripts/Python/static-binding/lldb.py | python | SBTypeMemberFunction.GetArgumentTypeAtIndex | (self, *args) | return _lldb.SBTypeMemberFunction_GetArgumentTypeAtIndex(self, *args) | GetArgumentTypeAtIndex(self, uint32_t arg0) -> SBType | GetArgumentTypeAtIndex(self, uint32_t arg0) -> SBType | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | contrib/gizmos/osx_cocoa/gizmos.py | python | TreeListCtrl.SetItemPyData | (*args, **kwargs) | return _gizmos.TreeListCtrl_SetItemPyData(*args, **kwargs) | SetItemPyData(self, TreeItemId item, PyObject obj) | SetItemPyData(self, TreeItemId item, PyObject obj) | [
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natanielruiz/android-yolo | 1ebb54f96a67a20ff83ddfc823ed83a13dc3a47f | jni-build/jni/include/external/bazel_tools/tools/android/incremental_install.py | python | Adb.Push | (self, local, remote) | return self._ExecParallel(["push", local, remote]) | Invoke 'adb push' in parallel. | Invoke 'adb push' in parallel. | [
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"""Invoke 'adb push' in parallel."""
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/scipy/scipy/stats/_multivariate.py | python | wishart_gen.__call__ | (self, df=None, scale=None, seed=None) | return wishart_frozen(df, scale, seed) | Create a frozen Wishart distribution.
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"""
Create a frozen Wishart distribution.
See `wishart_frozen` for more information.
"""
return wishart_frozen(df, scale, seed) | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/tkinter/__init__.py | python | Misc.bindtags | (self, tagList=None) | Set or get the list of bindtags for this widget.
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mindspore-ai/mindspore | fb8fd3338605bb34fa5cea054e535a8b1d753fab | mindspore/python/mindspore/nn/metrics/confusion_matrix.py | python | _calculate_fnr | (fn, p) | return fn, p | Calculate fnr. | Calculate fnr. | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/scipy/py3/scipy/signal/ltisys.py | python | StateSpace.__mul__ | (self, other) | return StateSpace(np.asarray(a, dtype=common_dtype),
np.asarray(b, dtype=common_dtype),
np.asarray(c, dtype=common_dtype),
np.asarray(d, dtype=common_dtype)) | Post-multiply another system or a scalar
Handles multiplication of systems in the sense of a frequency domain
multiplication. That means, given two systems E1(s) and E2(s), their
multiplication, H(s) = E1(s) * E2(s), means that applying H(s) to U(s)
is equivalent to first applying E2(s), and then E1(s).
Notes
-----
For SISO systems the order of system application does not matter.
However, for MIMO systems, where the two systems are matrices, the
order above ensures standard Matrix multiplication rules apply. | Post-multiply another system or a scalar | [
"Post",
"-",
"multiply",
"another",
"system",
"or",
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] | def __mul__(self, other):
"""
Post-multiply another system or a scalar
Handles multiplication of systems in the sense of a frequency domain
multiplication. That means, given two systems E1(s) and E2(s), their
multiplication, H(s) = E1(s) * E2(s), means that applying H(s) to U(s)
is equivalent to first applying E2(s), and then E1(s).
Notes
-----
For SISO systems the order of system application does not matter.
However, for MIMO systems, where the two systems are matrices, the
order above ensures standard Matrix multiplication rules apply.
"""
if not self._check_binop_other(other):
return NotImplemented
if isinstance(other, StateSpace):
# Disallow mix of discrete and continuous systems.
if type(other) is not type(self):
return NotImplemented
if self.dt != other.dt:
raise TypeError('Cannot multiply systems with different `dt`.')
n1 = self.A.shape[0]
n2 = other.A.shape[0]
# Interconnection of systems
# x1' = A1 x1 + B1 u1
# y1 = C1 x1 + D1 u1
# x2' = A2 x2 + B2 y1
# y2 = C2 x2 + D2 y1
#
# Plugging in with u1 = y2 yields
# [x1'] [A1 B1*C2 ] [x1] [B1*D2]
# [x2'] = [0 A2 ] [x2] + [B2 ] u2
# [x1]
# y2 = [C1 D1*C2] [x2] + D1*D2 u2
a = np.vstack((np.hstack((self.A, np.dot(self.B, other.C))),
np.hstack((zeros((n2, n1)), other.A))))
b = np.vstack((np.dot(self.B, other.D), other.B))
c = np.hstack((self.C, np.dot(self.D, other.C)))
d = np.dot(self.D, other.D)
else:
# Assume that other is a scalar / matrix
# For post multiplication the input gets scaled
a = self.A
b = np.dot(self.B, other)
c = self.C
d = np.dot(self.D, other)
common_dtype = np.find_common_type((a.dtype, b.dtype, c.dtype, d.dtype), ())
return StateSpace(np.asarray(a, dtype=common_dtype),
np.asarray(b, dtype=common_dtype),
np.asarray(c, dtype=common_dtype),
np.asarray(d, dtype=common_dtype)) | [
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MegEngine/MegEngine | ce9ad07a27ec909fb8db4dd67943d24ba98fb93a | imperative/python/megengine/amp/grad_scaler.py | python | GradScaler.unscale | (self, grad_tensors: Iterable[Tensor]) | return self | r"""Unscale all ``grad_tensors``'s grad.
Args:
grad_tensors: Tensors needed to unscale grads. Should be all tensors
that are affected by ``target`` tensor in GradManager's backward. | r"""Unscale all ``grad_tensors``'s grad. | [
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r"""Unscale all ``grad_tensors``'s grad.
Args:
grad_tensors: Tensors needed to unscale grads. Should be all tensors
that are affected by ``target`` tensor in GradManager's backward.
"""
if self.growth_interval == 0:
# use float64 for better precision
inv_scale = Tensor(1.0 / self.scale_factor)
for tensor in grad_tensors:
if tensor is None or getattr(tensor, "grad", None) is None:
continue
tensor.grad *= inv_scale
return self
# to support tracing, _check_gradients should be applied to every grad.
if self._check_gradients(
[x.grad for x in grad_tensors], 1.0 / self.scale_factor
):
self._found_non_finite = True
for tensor in grad_tensors:
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/urllib/request.py | python | FancyURLopener.http_error_302 | (self, url, fp, errcode, errmsg, headers, data=None) | Error 302 -- relocated (temporarily). | Error 302 -- relocated (temporarily). | [
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"302",
"--",
"relocated",
"(",
"temporarily",
")",
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] | def http_error_302(self, url, fp, errcode, errmsg, headers, data=None):
"""Error 302 -- relocated (temporarily)."""
self.tries += 1
try:
if self.maxtries and self.tries >= self.maxtries:
if hasattr(self, "http_error_500"):
meth = self.http_error_500
else:
meth = self.http_error_default
return meth(url, fp, 500,
"Internal Server Error: Redirect Recursion",
headers)
result = self.redirect_internal(url, fp, errcode, errmsg,
headers, data)
return result
finally:
self.tries = 0 | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/setuptools/py3/setuptools/_distutils/command/register.py | python | register.send_metadata | (self) | Send the metadata to the package index server.
Well, do the following:
1. figure who the user is, and then
2. send the data as a Basic auth'ed POST.
First we try to read the username/password from $HOME/.pypirc,
which is a ConfigParser-formatted file with a section
[distutils] containing username and password entries (both
in clear text). Eg:
[distutils]
index-servers =
pypi
[pypi]
username: fred
password: sekrit
Otherwise, to figure who the user is, we offer the user three
choices:
1. use existing login,
2. register as a new user, or
3. set the password to a random string and email the user. | Send the metadata to the package index server. | [
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] | def send_metadata(self):
''' Send the metadata to the package index server.
Well, do the following:
1. figure who the user is, and then
2. send the data as a Basic auth'ed POST.
First we try to read the username/password from $HOME/.pypirc,
which is a ConfigParser-formatted file with a section
[distutils] containing username and password entries (both
in clear text). Eg:
[distutils]
index-servers =
pypi
[pypi]
username: fred
password: sekrit
Otherwise, to figure who the user is, we offer the user three
choices:
1. use existing login,
2. register as a new user, or
3. set the password to a random string and email the user.
'''
# see if we can short-cut and get the username/password from the
# config
if self.has_config:
choice = '1'
username = self.username
password = self.password
else:
choice = 'x'
username = password = ''
# get the user's login info
choices = '1 2 3 4'.split()
while choice not in choices:
self.announce('''\
We need to know who you are, so please choose either:
1. use your existing login,
2. register as a new user,
3. have the server generate a new password for you (and email it to you), or
4. quit
Your selection [default 1]: ''', log.INFO)
choice = input()
if not choice:
choice = '1'
elif choice not in choices:
print('Please choose one of the four options!')
if choice == '1':
# get the username and password
while not username:
username = input('Username: ')
while not password:
password = getpass.getpass('Password: ')
# set up the authentication
auth = urllib.request.HTTPPasswordMgr()
host = urllib.parse.urlparse(self.repository)[1]
auth.add_password(self.realm, host, username, password)
# send the info to the server and report the result
code, result = self.post_to_server(self.build_post_data('submit'),
auth)
self.announce('Server response (%s): %s' % (code, result),
log.INFO)
# possibly save the login
if code == 200:
if self.has_config:
# sharing the password in the distribution instance
# so the upload command can reuse it
self.distribution.password = password
else:
self.announce(('I can store your PyPI login so future '
'submissions will be faster.'), log.INFO)
self.announce('(the login will be stored in %s)' % \
self._get_rc_file(), log.INFO)
choice = 'X'
while choice.lower() not in 'yn':
choice = input('Save your login (y/N)?')
if not choice:
choice = 'n'
if choice.lower() == 'y':
self._store_pypirc(username, password)
elif choice == '2':
data = {':action': 'user'}
data['name'] = data['password'] = data['email'] = ''
data['confirm'] = None
while not data['name']:
data['name'] = input('Username: ')
while data['password'] != data['confirm']:
while not data['password']:
data['password'] = getpass.getpass('Password: ')
while not data['confirm']:
data['confirm'] = getpass.getpass(' Confirm: ')
if data['password'] != data['confirm']:
data['password'] = ''
data['confirm'] = None
print("Password and confirm don't match!")
while not data['email']:
data['email'] = input(' EMail: ')
code, result = self.post_to_server(data)
if code != 200:
log.info('Server response (%s): %s', code, result)
else:
log.info('You will receive an email shortly.')
log.info(('Follow the instructions in it to '
'complete registration.'))
elif choice == '3':
data = {':action': 'password_reset'}
data['email'] = ''
while not data['email']:
data['email'] = input('Your email address: ')
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mantidproject/mantid | 03deeb89254ec4289edb8771e0188c2090a02f32 | qt/python/mantidqt/mantidqt/widgets/fitpropertybrowser/fitpropertybrowser.py | python | FitPropertyBrowser.move_x_range | (self, start_x, end_x) | Let the tool know that the Fit range has been changed in the FitPropertyBrowser.
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Kitware/ParaView | f760af9124ff4634b23ebbeab95a4f56e0261955 | ThirdParty/cinema/paraview/tpl/cinema_python/images/querymaker_specb.py | python | QueryMaker_SpecB.translateQuery | (self, query, colorDefinitions={}) | return allLayers | Receives a UI query and returns a set of LayerRasters consisting of all
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ricardoquesada/Spidermonkey | 4a75ea2543408bd1b2c515aa95901523eeef7858 | media/webrtc/trunk/tools/gyp/pylib/gyp/generator/make.py | python | MakefileWriter.WriteList | (self, value_list, variable=None, prefix='',
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/gtk/_misc.py | python | ConfigBase.GetAppName | (*args, **kwargs) | return _misc_.ConfigBase_GetAppName(*args, **kwargs) | GetAppName(self) -> String | GetAppName(self) -> String | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/tools/python3/src/Lib/zipapp.py | python | create_archive | (source, target=None, interpreter=None, main=None,
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_carbon/_misc.py | python | Clipboard.Get | (*args, **kwargs) | return _misc_.Clipboard_Get(*args, **kwargs) | Get() -> Clipboard
Returns global instance (wxTheClipboard) of the object. | Get() -> Clipboard | [
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] | def Get(*args, **kwargs):
"""
Get() -> Clipboard
Returns global instance (wxTheClipboard) of the object.
"""
return _misc_.Clipboard_Get(*args, **kwargs) | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | wx/lib/masked/timectrl.py | python | TimeCtrl.SetInsertionPoint | (self, pos) | This override records the specified position and associated cell before
calling base class' function. This is necessary to handle the optional
spin button, because the insertion point is lost when the focus shifts
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calling base class' function. This is necessary to handle the optional
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## dbg('TimeCtrl::SetInsertionPoint', pos, indent=1)
BaseMaskedTextCtrl.SetInsertionPoint(self, pos) # (causes EVT_TEXT event to fire)
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LiquidPlayer/LiquidCore | 9405979363f2353ac9a71ad8ab59685dd7f919c9 | deps/node-10.15.3/deps/v8/PRESUBMIT.py | python | _CheckHeadersHaveIncludeGuards | (input_api, output_api) | Ensures that all header files have include guards. | Ensures that all header files have include guards. | [
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"""Ensures that all header files have include guards."""
file_inclusion_pattern = r'src/.+\.h'
def FilterFile(affected_file):
black_list = (_EXCLUDED_PATHS +
input_api.DEFAULT_BLACK_LIST)
return input_api.FilterSourceFile(
affected_file,
white_list=(file_inclusion_pattern, ),
black_list=black_list)
leading_src_pattern = input_api.re.compile(r'^src/')
dash_dot_slash_pattern = input_api.re.compile(r'[-./]')
def PathToGuardMacro(path):
"""Guards should be of the form V8_PATH_TO_FILE_WITHOUT_SRC_H_."""
x = input_api.re.sub(leading_src_pattern, 'v8_', path)
x = input_api.re.sub(dash_dot_slash_pattern, '_', x)
x = x.upper() + "_"
return x
problems = []
for f in input_api.AffectedSourceFiles(FilterFile):
local_path = f.LocalPath()
guard_macro = PathToGuardMacro(local_path)
guard_patterns = [
input_api.re.compile(r'^#ifndef ' + guard_macro + '$'),
input_api.re.compile(r'^#define ' + guard_macro + '$'),
input_api.re.compile(r'^#endif // ' + guard_macro + '$')]
skip_check_pattern = input_api.re.compile(
r'^// PRESUBMIT_INTENTIONALLY_MISSING_INCLUDE_GUARD')
found_patterns = [ False, False, False ]
file_omitted = False
for line in f.NewContents():
for i in range(len(guard_patterns)):
if guard_patterns[i].match(line):
found_patterns[i] = True
if skip_check_pattern.match(line):
file_omitted = True
break
if not file_omitted and not all(found_patterns):
problems.append(
'%s: Missing include guard \'%s\'' % (local_path, guard_macro))
if problems:
return [output_api.PresubmitError(
'You added one or more header files without an appropriate\n'
'include guard. Add the include guard {#ifndef,#define,#endif}\n'
'triplet or omit the check entirely through the magic comment:\n'
'"// PRESUBMIT_INTENTIONALLY_MISSING_INCLUDE_GUARD".', problems)]
else:
return [] | [
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CoolProp/CoolProp | 381c8535e5dec3eec27ad430ebbfff8bc9dfc008 | dev/scripts/fit_ancillary_ODRPACK.py | python | saturation_density | (Ref, ClassName, form='A', LV='L', perc_error_allowed=0.3, fName=None, add_critical=True) | return the_string | Parameters
----------
Ref : string
The fluid name for the fluid that will be used to generate the saturation data
ClassName : The name of the class that will be used in the C++ code
form : string
If ``'A'``, use a term of the form | [] | def saturation_density(Ref, ClassName, form='A', LV='L', perc_error_allowed=0.3, fName=None, add_critical=True):
"""
Parameters
----------
Ref : string
The fluid name for the fluid that will be used to generate the saturation data
ClassName : The name of the class that will be used in the C++ code
form : string
If ``'A'``, use a term of the form
"""
if fName is None:
Tc = Props(Ref, 'Tcrit')
pc = Props(Ref, 'pcrit')
rhoc = Props(Ref, 'rhocrit')
Tmin = Props(Ref, 'Tmin')
print("%s %s %s" % (Ref, Tmin, Props(Ref, 'Ttriple')))
TT = np.linspace(Tmin, Tc - 1, 1000)
TT = list(TT)
# Add temperatures around the critical temperature
if add_critical:
for dT in [1e-10, 1e-9, 1e-8, 1e-7, 1e-6, 1e-5, 1e-4, 1e-3, 1e-2, 1e-1]:
TT.append(Tc - dT)
TT = np.array(sorted(TT))
p = Props('P', 'T', TT, 'Q', 0, Ref)
rhoL = Props('D', 'T', TT, 'Q', 0, Ref)
rhoV = Props('D', 'T', TT, 'Q', 1, Ref)
else:
Tc = 423.27
pc = 3533
rhoc = 470
Tmin = 273
lines = open(fName, 'r').readlines()
TT, p, rhoL, rhoV = [], [], [], []
for line in lines:
_T, _p, _rhoL, _rhoV = line.split(' ')
TT.append(float(_T))
p.append(float(_p))
rhoL.append(float(_rhoL))
rhoV.append(float(_rhoV))
TT = np.array(TT)
# Start with a large library of potential powers
n = [i / 6.0 for i in range(1, 200)] # +[0.35+i/200.0 for i in range(1,70)]+[0.05+0.01*i for i in range(1,70)]
x = 1.0 - TT / Tc
if LV == 'L':
rho_EOS = rhoL
elif LV == 'V':
rho_EOS = rhoV
else:
raise ValueError
if form == 'A':
y = np.array(rho_EOS) / rhoc - 1
elif form == 'B':
y = (np.log(rho_EOS) - np.log(rhoc)) * TT / Tc
else:
raise ValueError
max_abserror = 0
while len(n) > 3:
print("%s %s" % (max_abserror, len(n)))
def f_p(B, x):
# B is a vector of the parameters.
# x is an array of the current x values.
return sum([_B * x**(_n) for _B, _n in zip(B, n)])
linear = Model(f_p)
mydata = Data(x, y)
myodr = ODR(mydata, linear, beta0=[0] * len(n))
myoutput = myodr.run()
beta = myoutput.beta
sd = myoutput.sd_beta
if form == 'A':
rho_fit = (f_p(myoutput.beta, x) + 1) * rhoc
elif form == 'B':
rho_fit = np.exp(f_p(myoutput.beta, x) * Tc / TT) * rhoc
else:
raise ValueError
print('first,last %s %s %s %s %s %s' % (TT[0], TT[-1], rho_fit[0], rho_fit[-1], rho_EOS[0], rho_EOS[-1]))
max_abserror = np.max(np.abs(rho_fit / rho_EOS - 1)) * 100
dropped_indices = [i for i in range(len(n)) if abs(sd[i]) < 1e-15]
if dropped_indices:
for i in reversed(sorted(dropped_indices)):
n.pop(i)
print('popping... %s terms remaining' % len(n))
continue
if max_abserror > perc_error_allowed:
break # The last good run will be used
else:
print(max_abserror)
Ncoeffs = str(list(myoutput.beta)).lstrip('[').rstrip(']')
tcoeffs = str(n).lstrip('[').rstrip(']')
maxerror = max_abserror
if form == 'A':
code_template = textwrap.dedent(
"""
for (int i=1; i<={count:d}; i++)
{{
summer += N[i]*pow(theta,t[i]);
}}
return reduce.rho*(summer+1);
""".format(count=len(n))
)
elif form == 'B':
code_template = textwrap.dedent(
"""
for (int i=1; i<={count:d}; i++)
{{
summer += N[i]*pow(theta,t[i]);
}}
return reduce.rho*exp(reduce.T/T*summer);
""".format(count=len(n))
)
else:
raise ValueError
# Find the least significant entry (the one with the largest relative standard error)
# and remove it
n.pop(np.argmax(np.abs(sd / beta)))
# Remove elements that are not
template = textwrap.dedent(
"""
double {name:s}Class::rhosat{LV:s}(double T)
{{
// Maximum absolute error is {error:f} % between {Tmin:f} K and {Tmax:f} K
const double t[] = {{0, {tcoeffs:s}}};
const double N[] = {{0, {Ncoeffs:s}}};
double summer=0,theta;
theta=1-T/reduce.T;
\t{code:s}
}}
""")
the_string = template.format(tcoeffs=tcoeffs,
Ncoeffs=Ncoeffs,
name=ClassName,
Tmin=Tmin,
Tmax=TT[-1],
error=maxerror,
code=code_template,
LV=LV
)
f = open('anc.txt', 'a')
f.write(the_string)
f.close()
return the_string | [
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KratosMultiphysics/Kratos | 0000833054ed0503424eb28205d6508d9ca6cbbc | applications/CoSimulationApplication/CoSimulationApplication.py | python | __ModuleInitDetail | () | Create a DataCommunicator that only contains rank zero and is undefined in other ranks
This is necessary for solvers that can only run in serial
It is defined as a function to avoid polluting the Kratos namespace with local variables. | Create a DataCommunicator that only contains rank zero and is undefined in other ranks
This is necessary for solvers that can only run in serial
It is defined as a function to avoid polluting the Kratos namespace with local variables. | [
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"""
Create a DataCommunicator that only contains rank zero and is undefined in other ranks
This is necessary for solvers that can only run in serial
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"""
import KratosMultiphysics as KM
if KM.IsDistributedRun():
from KratosMultiphysics.mpi import DataCommunicatorFactory
data_comm_name = "co_simulation_data_comm_rank_zero"
world_data_comm = KM.ParallelEnvironment.GetDataCommunicator("World")
ranks = [0]
DataCommunicatorFactory.CreateFromRanksAndRegister(world_data_comm, ranks, data_comm_name) | [
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bundy-dns/bundy | 3d41934996b82b0cd2fe22dd74d2abc1daba835d | tools/query_cmp/src/lib/compare_rrset.py | python | header_cmp | (buf, msg1, msg2, diff) | return(True) | Compare the header of msg1 and msg2.
@param buf: the formatted difference for output.
@type buf: dict
@param diff: the key is each flag in the header, the value is
True for different and False for same
@type diff: dict | Compare the header of msg1 and msg2. | [
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""" Compare the header of msg1 and msg2.
@param buf: the formatted difference for output.
@type buf: dict
@param diff: the key is each flag in the header, the value is
True for different and False for same
@type diff: dict
"""
header1 = get_header_field(msg1)
header2 = get_header_field(msg2)
list = ['id', 'qr', 'opcode', 'aa', 'tc', 'rd', \
'ra', 'ad', 'cd', 'rcode', 'qdcount', 'ancount', \
'nscount', 'arcount']
for header in list:
diff[header] = header1[header] != header2[header]
buf['header'] = ''
for key in list:
if diff[key]:
buf['header'] = buf['header'] + \
'%-*s%-*s%-*s\n' % (POS_TITLE, key, \
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header2[key])
for key in diff.keys():
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Slicer/Slicer | ba9fadf332cb0303515b68d8d06a344c82e3e3e5 | Base/Python/slicer/util.py | python | updateVolumeFromArray | (volumeNode, narray) | Sets voxels of a volume node from a numpy array.
:raises RuntimeError: in case of failure
Voxels values are deep-copied, therefore if the numpy array
is modified after calling this method, voxel values in the volume node will not change.
Dimensions and data size of the source numpy array does not have to match the current
content of the volume node. | Sets voxels of a volume node from a numpy array. | [
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] | def updateVolumeFromArray(volumeNode, narray):
"""Sets voxels of a volume node from a numpy array.
:raises RuntimeError: in case of failure
Voxels values are deep-copied, therefore if the numpy array
is modified after calling this method, voxel values in the volume node will not change.
Dimensions and data size of the source numpy array does not have to match the current
content of the volume node.
"""
vshape = tuple(reversed(narray.shape))
if len(vshape) == 3:
# Scalar volume
vcomponents = 1
elif len(vshape) == 4:
# Vector volume
vcomponents = vshape[0]
vshape = vshape[1:4]
else:
# TODO: add support for tensor volumes
raise RuntimeError("Unsupported numpy array shape: "+str(narray.shape))
vimage = volumeNode.GetImageData()
if not vimage:
import vtk
vimage = vtk.vtkImageData()
volumeNode.SetAndObserveImageData(vimage)
import vtk.util.numpy_support
vtype = vtk.util.numpy_support.get_vtk_array_type(narray.dtype)
# Volumes with "long long" scalar type are not rendered correctly.
# Probably this could be fixed in VTK or Slicer but for now just reject it.
if vtype == vtk.VTK_LONG_LONG:
raise RuntimeError("Unsupported numpy array type: long long")
vimage.SetDimensions(vshape)
vimage.AllocateScalars(vtype, vcomponents)
narrayTarget = arrayFromVolume(volumeNode)
narrayTarget[:] = narray
# Notify the application that image data is changed
# (same notifications as in vtkMRMLVolumeNode.SetImageDataConnection)
import slicer
volumeNode.StorableModified()
volumeNode.Modified()
volumeNode.InvokeEvent(slicer.vtkMRMLVolumeNode.ImageDataModifiedEvent, volumeNode) | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_carbon/_misc.py | python | DateTime_GetCurrentMonth | (*args, **kwargs) | return _misc_.DateTime_GetCurrentMonth(*args, **kwargs) | DateTime_GetCurrentMonth(int cal=Gregorian) -> int | DateTime_GetCurrentMonth(int cal=Gregorian) -> int | [
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"""DateTime_GetCurrentMonth(int cal=Gregorian) -> int"""
return _misc_.DateTime_GetCurrentMonth(*args, **kwargs) | [
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Xilinx/Vitis-AI | fc74d404563d9951b57245443c73bef389f3657f | tools/Vitis-AI-Quantizer/vai_q_tensorflow2.x/tensorflow_model_optimization/python/core/quantization/keras/quantize_wrapper.py | python | QuantizeWrapper._weight_name | (name) | return name.split(':')[0].split('/')[-1] | Extracts the weight name from the full TensorFlow variable name.
For example, returns 'kernel' for 'dense_2/kernel:0'.
Args:
name: TensorFlow variable name.
Returns:
Extracted weight name. | Extracts the weight name from the full TensorFlow variable name. | [
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] | def _weight_name(name):
"""Extracts the weight name from the full TensorFlow variable name.
For example, returns 'kernel' for 'dense_2/kernel:0'.
Args:
name: TensorFlow variable name.
Returns:
Extracted weight name.
"""
return name.split(':')[0].split('/')[-1] | [
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RobotLocomotion/drake | 0e18a34604c45ed65bc9018a54f7610f91cdad5b | tools/performance/benchmark_tool.py | python | CpuSpeedSettings.set_cpu_governor | (self, governor) | Set the CPU governor to the given name string. | Set the CPU governor to the given name string. | [
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] | https://github.com/RobotLocomotion/drake/blob/0e18a34604c45ed65bc9018a54f7610f91cdad5b/tools/performance/benchmark_tool.py#L89-L91 | ||
google/mysql-protobuf | 467cda676afaa49e762c5c9164a43f6ad31a1fbf | protobuf/python/google/protobuf/service_reflection.py | python | _ServiceStubBuilder.__init__ | (self, service_descriptor) | Initializes an instance of the service stub class builder.
Args:
service_descriptor: ServiceDescriptor to use when constructing the
stub class. | Initializes an instance of the service stub class builder. | [
"Initializes",
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"instance",
"of",
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"service",
"stub",
"class",
"builder",
"."
] | def __init__(self, service_descriptor):
"""Initializes an instance of the service stub class builder.
Args:
service_descriptor: ServiceDescriptor to use when constructing the
stub class.
"""
self.descriptor = service_descriptor | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/windows/Lib/mailbox.py | python | Mailbox.get_message | (self, key) | Return a Message representation or raise a KeyError. | Return a Message representation or raise a KeyError. | [
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"""Return a Message representation or raise a KeyError."""
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pmq20/node-packer | 12c46c6e44fbc14d9ee645ebd17d5296b324f7e0 | lts/tools/inspector_protocol/jinja2/debug.py | python | ProcessedTraceback.render_as_text | (self, limit=None) | return ''.join(lines).rstrip() | Return a string with the traceback. | Return a string with the traceback. | [
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] | def render_as_text(self, limit=None):
"""Return a string with the traceback."""
lines = traceback.format_exception(self.exc_type, self.exc_value,
self.frames[0], limit=limit)
return ''.join(lines).rstrip() | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/scipy/py3/scipy/interpolate/_fitpack_impl.py | python | bisplev | (x, y, tck, dx=0, dy=0) | return z[0][0] | Evaluate a bivariate B-spline and its derivatives.
Return a rank-2 array of spline function values (or spline derivative
values) at points given by the cross-product of the rank-1 arrays `x` and
`y`. In special cases, return an array or just a float if either `x` or
`y` or both are floats. Based on BISPEV from FITPACK.
Parameters
----------
x, y : ndarray
Rank-1 arrays specifying the domain over which to evaluate the
spline or its derivative.
tck : tuple
A sequence of length 5 returned by `bisplrep` containing the knot
locations, the coefficients, and the degree of the spline:
[tx, ty, c, kx, ky].
dx, dy : int, optional
The orders of the partial derivatives in `x` and `y` respectively.
Returns
-------
vals : ndarray
The B-spline or its derivative evaluated over the set formed by
the cross-product of `x` and `y`.
See Also
--------
splprep, splrep, splint, sproot, splev
UnivariateSpline, BivariateSpline
Notes
-----
See `bisplrep` to generate the `tck` representation.
References
----------
.. [1] Dierckx P. : An algorithm for surface fitting
with spline functions
Ima J. Numer. Anal. 1 (1981) 267-283.
.. [2] Dierckx P. : An algorithm for surface fitting
with spline functions
report tw50, Dept. Computer Science,K.U.Leuven, 1980.
.. [3] Dierckx P. : Curve and surface fitting with splines,
Monographs on Numerical Analysis, Oxford University Press, 1993. | Evaluate a bivariate B-spline and its derivatives. | [
"Evaluate",
"a",
"bivariate",
"B",
"-",
"spline",
"and",
"its",
"derivatives",
"."
] | def bisplev(x, y, tck, dx=0, dy=0):
"""
Evaluate a bivariate B-spline and its derivatives.
Return a rank-2 array of spline function values (or spline derivative
values) at points given by the cross-product of the rank-1 arrays `x` and
`y`. In special cases, return an array or just a float if either `x` or
`y` or both are floats. Based on BISPEV from FITPACK.
Parameters
----------
x, y : ndarray
Rank-1 arrays specifying the domain over which to evaluate the
spline or its derivative.
tck : tuple
A sequence of length 5 returned by `bisplrep` containing the knot
locations, the coefficients, and the degree of the spline:
[tx, ty, c, kx, ky].
dx, dy : int, optional
The orders of the partial derivatives in `x` and `y` respectively.
Returns
-------
vals : ndarray
The B-spline or its derivative evaluated over the set formed by
the cross-product of `x` and `y`.
See Also
--------
splprep, splrep, splint, sproot, splev
UnivariateSpline, BivariateSpline
Notes
-----
See `bisplrep` to generate the `tck` representation.
References
----------
.. [1] Dierckx P. : An algorithm for surface fitting
with spline functions
Ima J. Numer. Anal. 1 (1981) 267-283.
.. [2] Dierckx P. : An algorithm for surface fitting
with spline functions
report tw50, Dept. Computer Science,K.U.Leuven, 1980.
.. [3] Dierckx P. : Curve and surface fitting with splines,
Monographs on Numerical Analysis, Oxford University Press, 1993.
"""
tx, ty, c, kx, ky = tck
if not (0 <= dx < kx):
raise ValueError("0 <= dx = %d < kx = %d must hold" % (dx, kx))
if not (0 <= dy < ky):
raise ValueError("0 <= dy = %d < ky = %d must hold" % (dy, ky))
x, y = map(atleast_1d, [x, y])
if (len(x.shape) != 1) or (len(y.shape) != 1):
raise ValueError("First two entries should be rank-1 arrays.")
z, ier = _fitpack._bispev(tx, ty, c, kx, ky, x, y, dx, dy)
if ier == 10:
raise ValueError("Invalid input data")
if ier:
raise TypeError("An error occurred")
z.shape = len(x), len(y)
if len(z) > 1:
return z
if len(z[0]) > 1:
return z[0]
return z[0][0] | [
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ApolloAuto/apollo-platform | 86d9dc6743b496ead18d597748ebabd34a513289 | ros/ros_comm/rospy/src/rospy/topics.py | python | _PublisherImpl.get_stats | (self) | return (self.resolved_name, self.message_data_sent,
[(c.id, c.stat_bytes, c.stat_num_msg, not c.done) for c in conn] ) | Get the stats for this topic publisher
@return: stats for topic in getBusStats() publisher format::
[topicName, messageDataBytes, connStats],
where connStats is::
[id, bytes, numMessages, connected]*
@rtype: list | Get the stats for this topic publisher | [
"Get",
"the",
"stats",
"for",
"this",
"topic",
"publisher"
] | def get_stats(self): # STATS
"""
Get the stats for this topic publisher
@return: stats for topic in getBusStats() publisher format::
[topicName, messageDataBytes, connStats],
where connStats is::
[id, bytes, numMessages, connected]*
@rtype: list
"""
# save reference to avoid lock
conn = self.connections
return (self.resolved_name, self.message_data_sent,
[(c.id, c.stat_bytes, c.stat_num_msg, not c.done) for c in conn] ) | [
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Xilinx/Vitis-AI | fc74d404563d9951b57245443c73bef389f3657f | tools/Vitis-AI-Quantizer/vai_q_tensorflow2.x/tensorflow_model_optimization/python/core/internal/tensor_encoding/core/encoding_stage.py | python | _tf_style_update_state | (update_state_fn) | return actual_initial_state_fn | Method decorator for `tf_style_adaptive_encoding_stage`. | Method decorator for `tf_style_adaptive_encoding_stage`. | [
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"decorator",
"for",
"tf_style_adaptive_encoding_stage",
"."
] | def _tf_style_update_state(update_state_fn):
"""Method decorator for `tf_style_adaptive_encoding_stage`."""
def actual_initial_state_fn(self, state, state_update_tensors, name=None):
"""Modified `update_state` method."""
values = list(state.values()) + list(state_update_tensors.values())
with tf.compat.v1.name_scope(name, self.name + UPDATE_STATE_SCOPE_SUFFIX,
values):
state = tf.nest.map_structure(tf.convert_to_tensor, state)
state_update_tensors = tf.nest.map_structure(tf.convert_to_tensor,
state_update_tensors)
return update_state_fn(self, state, state_update_tensors, name=name)
return actual_initial_state_fn | [
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Komnomnomnom/swigibpy | cfd307fdbfaffabc69a2dc037538d7e34a8b8daf | swigibpy.py | python | EClient.replaceFA | (self, pFaDataType, cxml) | return _swigibpy.EClient_replaceFA(self, pFaDataType, cxml) | replaceFA(EClient self, faDataType pFaDataType, IBString const & cxml) | replaceFA(EClient self, faDataType pFaDataType, IBString const & cxml) | [
"replaceFA",
"(",
"EClient",
"self",
"faDataType",
"pFaDataType",
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"const",
"&",
"cxml",
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] | def replaceFA(self, pFaDataType, cxml):
"""replaceFA(EClient self, faDataType pFaDataType, IBString const & cxml)"""
return _swigibpy.EClient_replaceFA(self, pFaDataType, cxml) | [
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tensorflow/tensorflow | 419e3a6b650ea4bd1b0cba23c4348f8a69f3272e | tensorflow/python/ops/math_ops.py | python | angle | (input, name=None) | r"""Returns the element-wise argument of a complex (or real) tensor.
Given a tensor `input`, this operation returns a tensor of type `float` that
is the argument of each element in `input` considered as a complex number.
The elements in `input` are considered to be complex numbers of the form
\\(a + bj\\), where *a* is the real part and *b* is the imaginary part.
If `input` is real then *b* is zero by definition.
The argument returned by this function is of the form \\(atan2(b, a)\\).
If `input` is real, a tensor of all zeros is returned.
For example:
```
input = tf.constant([-2.25 + 4.75j, 3.25 + 5.75j], dtype=tf.complex64)
tf.math.angle(input).numpy()
# ==> array([2.0131705, 1.056345 ], dtype=float32)
```
Args:
input: A `Tensor`. Must be one of the following types: `float`, `double`,
`complex64`, `complex128`.
name: A name for the operation (optional).
Returns:
A `Tensor` of type `float32` or `float64`. | r"""Returns the element-wise argument of a complex (or real) tensor. | [
"r",
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"wise",
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] | def angle(input, name=None):
r"""Returns the element-wise argument of a complex (or real) tensor.
Given a tensor `input`, this operation returns a tensor of type `float` that
is the argument of each element in `input` considered as a complex number.
The elements in `input` are considered to be complex numbers of the form
\\(a + bj\\), where *a* is the real part and *b* is the imaginary part.
If `input` is real then *b* is zero by definition.
The argument returned by this function is of the form \\(atan2(b, a)\\).
If `input` is real, a tensor of all zeros is returned.
For example:
```
input = tf.constant([-2.25 + 4.75j, 3.25 + 5.75j], dtype=tf.complex64)
tf.math.angle(input).numpy()
# ==> array([2.0131705, 1.056345 ], dtype=float32)
```
Args:
input: A `Tensor`. Must be one of the following types: `float`, `double`,
`complex64`, `complex128`.
name: A name for the operation (optional).
Returns:
A `Tensor` of type `float32` or `float64`.
"""
with ops.name_scope(name, "Angle", [input]) as name:
input = ops.convert_to_tensor(input, name="input")
if input.dtype.is_complex:
return gen_math_ops.angle(input, Tout=input.dtype.real_dtype, name=name)
else:
return array_ops.where(input < 0, np.pi * array_ops.ones_like(input),
array_ops.zeros_like(input)) | [
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BitMEX/api-connectors | 37a3a5b806ad5d0e0fc975ab86d9ed43c3bcd812 | auto-generated/python/swagger_client/models/instrument.py | python | Instrument.opening_timestamp | (self) | return self._opening_timestamp | Gets the opening_timestamp of this Instrument. # noqa: E501
:return: The opening_timestamp of this Instrument. # noqa: E501
:rtype: datetime | Gets the opening_timestamp of this Instrument. # noqa: E501 | [
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"opening_timestamp",
"of",
"this",
"Instrument",
".",
"#",
"noqa",
":",
"E501"
] | def opening_timestamp(self):
"""Gets the opening_timestamp of this Instrument. # noqa: E501
:return: The opening_timestamp of this Instrument. # noqa: E501
:rtype: datetime
"""
return self._opening_timestamp | [
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miyosuda/TensorFlowAndroidMNIST | 7b5a4603d2780a8a2834575706e9001977524007 | jni-build/jni/include/tensorflow/python/summary/event_file_inspector.py | python | inspect | (logdir='', event_file='', tag='') | Main function for inspector that prints out a digest of event files.
Args:
logdir: A log directory that contains event files.
event_file: Or, a particular event file path.
tag: An optional tag name to query for.
Raises:
ValueError: If neither logdir and event_file are given, or both are given. | Main function for inspector that prints out a digest of event files. | [
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] | def inspect(logdir='', event_file='', tag=''):
"""Main function for inspector that prints out a digest of event files.
Args:
logdir: A log directory that contains event files.
event_file: Or, a particular event file path.
tag: An optional tag name to query for.
Raises:
ValueError: If neither logdir and event_file are given, or both are given.
"""
if logdir and event_file:
raise ValueError(
'Must specify either --logdir or --event_file, but not both.')
if not (logdir or event_file):
raise ValueError('Must specify either --logdir or --event_file.')
print(PRINT_SEPARATOR +
'Processing event files... (this can take a few minutes)\n' +
PRINT_SEPARATOR)
inspection_units = get_inspection_units(logdir, event_file, tag)
for unit in inspection_units:
if tag:
print('Event statistics for tag {} in {}:'.format(tag, unit.name))
else:
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print('These tags are in {}:'.format(unit.name))
print_dict(get_unique_tags(unit.field_to_obs))
print(PRINT_SEPARATOR)
print('Event statistics for {}:'.format(unit.name))
print_dict(get_dict_to_print(unit.field_to_obs), show_missing=(not tag))
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deepmind/streetlearn | ccf1d60b9c45154894d45a897748aee85d7eb69b | streetlearn/python/environment/instructions_base.py | python | InstructionsBase._update_shortest_path | (self, streetlearn, start_pano_id) | Update the target of the shortest paths and color panos along that path.
Args:
streetlearn: the streetlearn environment.
start_pano_id: a string for the current pano ID, for computing the optimal
path. | Update the target of the shortest paths and color panos along that path. | [
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"""Update the target of the shortest paths and color panos along that path.
Args:
streetlearn: the streetlearn environment.
start_pano_id: a string for the current pano ID, for computing the optimal
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"""
step = self._current_step + 1
logging.info(self._pano_by_step)
logging.info('Reached step %d', step)
if step in self._pano_by_step:
target_pano_id = self._pano_by_step[step]
self._shortest_path, num_panos = self._shortest_paths(
streetlearn, target_pano_id, start_pano_id)
logging.info('Shortest path from %s to waypoint/goal %s covers %d panos',
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wlanjie/AndroidFFmpeg | 7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf | tools/fdk-aac-build/x86/toolchain/lib/python2.7/curses/wrapper.py | python | wrapper | (func, *args, **kwds) | Wrapper function that initializes curses and calls another function,
restoring normal keyboard/screen behavior on error.
The callable object 'func' is then passed the main window 'stdscr'
as its first argument, followed by any other arguments passed to
wrapper(). | Wrapper function that initializes curses and calls another function,
restoring normal keyboard/screen behavior on error.
The callable object 'func' is then passed the main window 'stdscr'
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"""Wrapper function that initializes curses and calls another function,
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The callable object 'func' is then passed the main window 'stdscr'
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stdscr.keypad(1)
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# works around a minor bit of over-conscientiousness in the curses
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try:
curses.start_color()
except:
pass
return func(stdscr, *args, **kwds)
finally:
# Set everything back to normal
if 'stdscr' in locals():
stdscr.keypad(0)
curses.echo()
curses.nocbreak()
curses.endwin() | [
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wlanjie/AndroidFFmpeg | 7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf | tools/fdk-aac-build/x86/toolchain/lib/python2.7/lib-tk/turtle.py | python | RawTurtle._write | (self, txt, align, font) | return end | Performs the writing for write() | Performs the writing for write() | [
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"""Performs the writing for write()
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item, end = self.screen._write(self._position, txt, align, font,
self._pencolor)
self.items.append(item)
if self.undobuffer:
self.undobuffer.push(("wri", item))
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apple/turicreate | cce55aa5311300e3ce6af93cb45ba791fd1bdf49 | deps/src/libxml2-2.9.1/python/libxml2.py | python | createEntityParserCtxt | (URL, ID, base) | return parserCtxt(_obj=ret) | Create a parser context for an external entity Automatic
support for ZLIB/Compress compressed document is provided
by default if found at compile-time. | Create a parser context for an external entity Automatic
support for ZLIB/Compress compressed document is provided
by default if found at compile-time. | [
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"""Create a parser context for an external entity Automatic
support for ZLIB/Compress compressed document is provided
by default if found at compile-time. """
ret = libxml2mod.xmlCreateEntityParserCtxt(URL, ID, base)
if ret is None:raise parserError('xmlCreateEntityParserCtxt() failed')
return parserCtxt(_obj=ret) | [
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intel/caffe | 3f494b442ee3f9d17a07b09ecbd5fa2bbda00836 | examples/rfcn/tools/rpn_generate.py | python | parse_args | () | return args | Parse input arguments | Parse input arguments | [
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] | def parse_args():
"""
Parse input arguments
"""
parser = argparse.ArgumentParser(description='Test a Fast R-CNN network')
parser.add_argument('--gpu', dest='gpu_id', help='GPU id to use',
default=0, type=int)
parser.add_argument('--def', dest='prototxt',
help='prototxt file defining the network',
default=None, type=str)
parser.add_argument('--net', dest='caffemodel',
help='model to test',
default=None, type=str)
parser.add_argument('--cfg', dest='cfg_file',
help='optional config file', default=None, type=str)
parser.add_argument('--wait', dest='wait',
help='wait until net file exists',
default=True, type=bool)
parser.add_argument('--imdb', dest='imdb_name',
help='dataset to test',
default='voc_2007_test', type=str)
parser.add_argument('--set', dest='set_cfgs',
help='set config keys', default=None,
nargs=argparse.REMAINDER)
if len(sys.argv) == 1:
parser.print_help()
sys.exit(1)
args = parser.parse_args()
return args | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | wx/lib/agw/ultimatelistctrl.py | python | UltimateListCtrl.DeleteColumn | (self, col) | return True | Deletes the specified column.
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"""
Deletes the specified column.
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self._mainWin.DeleteColumn(col)
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domino-team/openwrt-cc | 8b181297c34d14d3ca521cc9f31430d561dbc688 | package/gli-pub/openwrt-node-packages-master/node/node-v6.9.1/deps/v8_inspector/third_party/jinja2/jinja2/utils.py | python | LRUCache.items | (self) | return result | Return a list of items. | Return a list of items. | [
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apple/turicreate | cce55aa5311300e3ce6af93cb45ba791fd1bdf49 | deps/src/libxml2-2.9.1/python/libxml2class.py | python | ValidCtxt.validateRoot | (self, doc) | return ret | Try to validate a the root element basically it does the
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- [ VC: Root Element Type ] it doesn't try to recurse or
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"""Try to validate a the root element basically it does the
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apply other check to the element """
if doc is None: doc__o = None
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ret = libxml2mod.xmlValidateRoot(self._o, doc__o)
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NVIDIA/DALI | bf16cc86ba8f091b145f91962f21fe1b6aff243d | docs/examples/use_cases/tensorflow/efficientdet/pipeline/tf/preprocessor.py | python | _compute_new_dynamic_size | (image, min_dimension, max_dimension) | return tf.stack(tf.unstack(new_size) + [num_channels]) | Compute new dynamic shape for resize_to_range method. | Compute new dynamic shape for resize_to_range method. | [
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"""Compute new dynamic shape for resize_to_range method."""
image_shape = tf.shape(image)
orig_height = tf.to_float(image_shape[0])
orig_width = tf.to_float(image_shape[1])
num_channels = image_shape[2]
orig_min_dim = tf.minimum(orig_height, orig_width)
# Calculates the larger of the possible sizes
min_dimension = tf.constant(min_dimension, dtype=tf.float32)
large_scale_factor = min_dimension / orig_min_dim
# Scaling orig_(height|width) by large_scale_factor will make the smaller
# dimension equal to min_dimension, save for floating point rounding errors.
# For reasonably-sized images, taking the nearest integer will reliably
# eliminate this error.
large_height = tf.to_int32(tf.round(orig_height * large_scale_factor))
large_width = tf.to_int32(tf.round(orig_width * large_scale_factor))
large_size = tf.stack([large_height, large_width])
if max_dimension:
# Calculates the smaller of the possible sizes, use that if the larger
# is too big.
orig_max_dim = tf.maximum(orig_height, orig_width)
max_dimension = tf.constant(max_dimension, dtype=tf.float32)
small_scale_factor = max_dimension / orig_max_dim
# Scaling orig_(height|width) by small_scale_factor will make the larger
# dimension equal to max_dimension, save for floating point rounding
# errors. For reasonably-sized images, taking the nearest integer will
# reliably eliminate this error.
small_height = tf.to_int32(tf.round(orig_height * small_scale_factor))
small_width = tf.to_int32(tf.round(orig_width * small_scale_factor))
small_size = tf.stack([small_height, small_width])
new_size = tf.cond(
tf.to_float(tf.reduce_max(large_size)) > max_dimension,
lambda: small_size,
lambda: large_size,
)
else:
new_size = large_size
return tf.stack(tf.unstack(new_size) + [num_channels]) | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/tools/python3/src/Lib/importlib/_bootstrap_external.py | python | PathFinder._path_importer_cache | (cls, path) | return finder | Get the finder for the path entry from sys.path_importer_cache.
If the path entry is not in the cache, find the appropriate finder
and cache it. If no finder is available, store None. | Get the finder for the path entry from sys.path_importer_cache. | [
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"""Get the finder for the path entry from sys.path_importer_cache.
If the path entry is not in the cache, find the appropriate finder
and cache it. If no finder is available, store None.
"""
if path == '':
try:
path = _os.getcwd()
except FileNotFoundError:
# Don't cache the failure as the cwd can easily change to
# a valid directory later on.
return None
try:
finder = sys.path_importer_cache[path]
except KeyError:
finder = cls._path_hooks(path)
sys.path_importer_cache[path] = finder
return finder | [
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Xilinx/Vitis-AI | fc74d404563d9951b57245443c73bef389f3657f | tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/contrib/layers/python/ops/sparse_ops.py | python | _multiplier_helper | (shape) | return multipliers | Returns moving offset for each dimension given shape. | Returns moving offset for each dimension given shape. | [
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] | def _multiplier_helper(shape):
"""Returns moving offset for each dimension given shape."""
multipliers = []
for dim in reversed(shape):
if multipliers:
multipliers.append(dim * multipliers[-1])
else:
multipliers.append(dim)
multipliers.reverse()
return multipliers | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/curses/textpad.py | python | Textbox.edit | (self, validate=None) | return self.gather() | Edit in the widget window and collect the results. | Edit in the widget window and collect the results. | [
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] | def edit(self, validate=None):
"Edit in the widget window and collect the results."
while 1:
ch = self.win.getch()
if validate:
ch = validate(ch)
if not ch:
continue
if not self.do_command(ch):
break
self.win.refresh()
return self.gather() | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemMetric/v1/AWS/common-code/Lib/numpy/distutils/misc_util.py | python | get_pkg_info | (pkgname, dirs=None) | return read_config(pkgname, dirs) | Return library info for the given package.
Parameters
----------
pkgname : str
Name of the package (should match the name of the .ini file, without
the extension, e.g. foo for the file foo.ini).
dirs : sequence, optional
If given, should be a sequence of additional directories where to look
for npy-pkg-config files. Those directories are searched prior to the
NumPy directory.
Returns
-------
pkginfo : class instance
The `LibraryInfo` instance containing the build information.
Raises
------
PkgNotFound
If the package is not found.
See Also
--------
Configuration.add_npy_pkg_config, Configuration.add_installed_library,
get_info | Return library info for the given package. | [
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] | def get_pkg_info(pkgname, dirs=None):
"""
Return library info for the given package.
Parameters
----------
pkgname : str
Name of the package (should match the name of the .ini file, without
the extension, e.g. foo for the file foo.ini).
dirs : sequence, optional
If given, should be a sequence of additional directories where to look
for npy-pkg-config files. Those directories are searched prior to the
NumPy directory.
Returns
-------
pkginfo : class instance
The `LibraryInfo` instance containing the build information.
Raises
------
PkgNotFound
If the package is not found.
See Also
--------
Configuration.add_npy_pkg_config, Configuration.add_installed_library,
get_info
"""
from numpy.distutils.npy_pkg_config import read_config
if dirs:
dirs.append(get_npy_pkg_dir())
else:
dirs = [get_npy_pkg_dir()]
return read_config(pkgname, dirs) | [
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sdhash/sdhash | b9eff63e4e5867e910f41fd69032bbb1c94a2a5e | sdhash-ui/cherrypy/_cpdispatch.py | python | test_callable_spec | (callable, callable_args, callable_kwargs) | Inspect callable and test to see if the given args are suitable for it.
When an error occurs during the handler's invoking stage there are 2
erroneous cases:
1. Too many parameters passed to a function which doesn't define
one of *args or **kwargs.
2. Too little parameters are passed to the function.
There are 3 sources of parameters to a cherrypy handler.
1. query string parameters are passed as keyword parameters to the handler.
2. body parameters are also passed as keyword parameters.
3. when partial matching occurs, the final path atoms are passed as
positional args.
Both the query string and path atoms are part of the URI. If they are
incorrect, then a 404 Not Found should be raised. Conversely the body
parameters are part of the request; if they are invalid a 400 Bad Request. | Inspect callable and test to see if the given args are suitable for it. | [
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"""
Inspect callable and test to see if the given args are suitable for it.
When an error occurs during the handler's invoking stage there are 2
erroneous cases:
1. Too many parameters passed to a function which doesn't define
one of *args or **kwargs.
2. Too little parameters are passed to the function.
There are 3 sources of parameters to a cherrypy handler.
1. query string parameters are passed as keyword parameters to the handler.
2. body parameters are also passed as keyword parameters.
3. when partial matching occurs, the final path atoms are passed as
positional args.
Both the query string and path atoms are part of the URI. If they are
incorrect, then a 404 Not Found should be raised. Conversely the body
parameters are part of the request; if they are invalid a 400 Bad Request.
"""
show_mismatched_params = getattr(
cherrypy.serving.request, 'show_mismatched_params', False)
try:
(args, varargs, varkw, defaults) = inspect.getargspec(callable)
except TypeError:
if isinstance(callable, object) and hasattr(callable, '__call__'):
(args, varargs, varkw, defaults) = inspect.getargspec(callable.__call__)
else:
# If it wasn't one of our own types, re-raise
# the original error
raise
if args and args[0] == 'self':
args = args[1:]
arg_usage = dict([(arg, 0,) for arg in args])
vararg_usage = 0
varkw_usage = 0
extra_kwargs = set()
for i, value in enumerate(callable_args):
try:
arg_usage[args[i]] += 1
except IndexError:
vararg_usage += 1
for key in callable_kwargs.keys():
try:
arg_usage[key] += 1
except KeyError:
varkw_usage += 1
extra_kwargs.add(key)
# figure out which args have defaults.
args_with_defaults = args[-len(defaults or []):]
for i, val in enumerate(defaults or []):
# Defaults take effect only when the arg hasn't been used yet.
if arg_usage[args_with_defaults[i]] == 0:
arg_usage[args_with_defaults[i]] += 1
missing_args = []
multiple_args = []
for key, usage in arg_usage.items():
if usage == 0:
missing_args.append(key)
elif usage > 1:
multiple_args.append(key)
if missing_args:
# In the case where the method allows body arguments
# there are 3 potential errors:
# 1. not enough query string parameters -> 404
# 2. not enough body parameters -> 400
# 3. not enough path parts (partial matches) -> 404
#
# We can't actually tell which case it is,
# so I'm raising a 404 because that covers 2/3 of the
# possibilities
#
# In the case where the method does not allow body
# arguments it's definitely a 404.
message = None
if show_mismatched_params:
message="Missing parameters: %s" % ",".join(missing_args)
raise cherrypy.HTTPError(404, message=message)
# the extra positional arguments come from the path - 404 Not Found
if not varargs and vararg_usage > 0:
raise cherrypy.HTTPError(404)
body_params = cherrypy.serving.request.body.params or {}
body_params = set(body_params.keys())
qs_params = set(callable_kwargs.keys()) - body_params
if multiple_args:
if qs_params.intersection(set(multiple_args)):
# If any of the multiple parameters came from the query string then
# it's a 404 Not Found
error = 404
else:
# Otherwise it's a 400 Bad Request
error = 400
message = None
if show_mismatched_params:
message="Multiple values for parameters: "\
"%s" % ",".join(multiple_args)
raise cherrypy.HTTPError(error, message=message)
if not varkw and varkw_usage > 0:
# If there were extra query string parameters, it's a 404 Not Found
extra_qs_params = set(qs_params).intersection(extra_kwargs)
if extra_qs_params:
message = None
if show_mismatched_params:
message="Unexpected query string "\
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raise cherrypy.HTTPError(404, message=message)
# If there were any extra body parameters, it's a 400 Not Found
extra_body_params = set(body_params).intersection(extra_kwargs)
if extra_body_params:
message = None
if show_mismatched_params:
message="Unexpected body parameters: "\
"%s" % ", ".join(extra_body_params)
raise cherrypy.HTTPError(400, message=message) | [
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psnonis/FinBERT | c0c555d833a14e2316a3701e59c0b5156f804b4e | bert/run_classifier.py | python | _truncate_seq_pair | (tokens_a, tokens_b, max_length) | Truncates a sequence pair in place to the maximum length. | Truncates a sequence pair in place to the maximum length. | [
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"""Truncates a sequence pair in place to the maximum length."""
# This is a simple heuristic which will always truncate the longer sequence
# one token at a time. This makes more sense than truncating an equal percent
# of tokens from each, since if one sequence is very short then each token
# that's truncated likely contains more information than a longer sequence.
while True:
total_length = len(tokens_a) + len(tokens_b)
if total_length <= max_length:
break
if len(tokens_a) > len(tokens_b):
tokens_a.pop()
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/pandas/py2/pandas/core/internals/blocks.py | python | CategoricalBlock._try_coerce_result | (self, result) | return result | reverse of try_coerce_args | reverse of try_coerce_args | [
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""" reverse of try_coerce_args """
# GH12564: CategoricalBlock is 1-dim only
# while returned results could be any dim
if ((not is_categorical_dtype(result)) and
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result = _block_shape(result, ndim=self.ndim)
return result | [
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mindspore-ai/mindspore | fb8fd3338605bb34fa5cea054e535a8b1d753fab | mindspore/python/mindspore/ops/operations/nn_ops.py | python | LSTM.__init__ | (self, input_size, hidden_size, num_layers, has_bias, bidirectional, dropout) | Initialize LSTM. | Initialize LSTM. | [
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self.hidden_size = validator.check_positive_int(hidden_size, "hidden_size", self.name)
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self.dropout = validator.check_value_type("dropout", dropout, [float], self.name)
self.dropout = validator.check_float_range(dropout, 0, 1, Rel.INC_BOTH, 'dropout', self.name)
if bidirectional:
self.num_directions = 2
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self.num_directions = 1 | [
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yrnkrn/zapcc | c6a8aa30006d997eff0d60fd37b0e62b8aa0ea50 | tools/clang/bindings/python/clang/cindex.py | python | Cursor.tls_kind | (self) | return TLSKind.from_id(self._tls_kind) | Return the thread-local storage (TLS) kind of this cursor. | Return the thread-local storage (TLS) kind of this cursor. | [
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"""Return the thread-local storage (TLS) kind of this cursor."""
if not hasattr(self, '_tls_kind'):
self._tls_kind = conf.lib.clang_getCursorTLSKind(self)
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generalized-intelligence/GAAS | 29ab17d3e8a4ba18edef3a57c36d8db6329fac73 | deprecated/algorithms/sfm/dataset.py | python | DataSet._exif_overrides_file | (self) | return os.path.join(self.data_path, 'exif_overrides.json') | Path to the EXIF overrides file. | Path to the EXIF overrides file. | [
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | wx/lib/agw/fourwaysplitter.py | python | FourWaySplitter.OnSize | (self, event) | Handles the ``wx.EVT_SIZE`` event for :class:`FourWaySplitter`.
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Handles the ``wx.EVT_SIZE`` event for :class:`FourWaySplitter`.
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parent = wx.GetTopLevelParent(self)
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hanpfei/chromium-net | 392cc1fa3a8f92f42e4071ab6e674d8e0482f83f | third_party/catapult/third_party/WebOb/webob/response.py | python | Response.encode_content | (self, encoding='gzip', lazy=False) | Encode the content with the given encoding (only gzip and
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self.app_iter = list(gzip_app_iter(self._app_iter))
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msracver/Deep-Image-Analogy | 632b9287b42552e32dad64922967c8c9ec7fc4d3 | scripts/cpp_lint.py | python | FindPreviousMatchingAngleBracket | (clean_lines, linenum, init_prefix) | return False | Find the corresponding < that started a template.
Args:
clean_lines: A CleansedLines instance containing the file.
linenum: Current line number.
init_prefix: Part of the current line before the initial >.
Returns:
True if a matching bracket exists. | Find the corresponding < that started a template. | [
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"""Find the corresponding < that started a template.
Args:
clean_lines: A CleansedLines instance containing the file.
linenum: Current line number.
init_prefix: Part of the current line before the initial >.
Returns:
True if a matching bracket exists.
"""
line = init_prefix
nesting_stack = ['>']
while True:
# Find the previous operator
match = Search(r'^(.*)([<>(),;\[\]])[^<>(),;\[\]]*$', line)
if match:
# Found an operator, update nesting stack
operator = match.group(2)
line = match.group(1)
if nesting_stack[-1] == '>':
# Expecting opening angle bracket
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nesting_stack.append(operator)
elif operator == '<':
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break
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microsoft/ivy | 9f3c7ecc0b2383129fdd0953e10890d98d09a82d | ivy/ivy_logic_utils.py | python | or_clauses2 | (clauses1,clauses2) | return clauses1 + clauses2 | Take the logical or of two clause sets. | Take the logical or of two clause sets. | [
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""" Take the logical or of two clause sets. """
if not clauses1 or not clauses2: return []
if [] in clauses1: return clauses2
if [] in clauses2: return clauses1
used = used_symbols_clauses(clauses1 + clauses2);
v = bool_const(UniqueRenamer('__ts',used)())
clauses1 = [[Literal(1,v)] + c for c in clauses1]
clauses2 = [[Literal(0,v)] + c for c in clauses2]
return clauses1 + clauses2 | [
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cvmfs/cvmfs | 4637bdb5153178eadf885c1acf37bdc5c685bf8a | cpplint.py | python | CheckCStyleCast | (filename, clean_lines, linenum, cast_type, pattern, error) | return True | Checks for a C-style cast by looking for the pattern.
Args:
filename: The name of the current file.
clean_lines: A CleansedLines instance containing the file.
linenum: The number of the line to check.
cast_type: The string for the C++ cast to recommend. This is either
reinterpret_cast, static_cast, or const_cast, depending.
pattern: The regular expression used to find C-style casts.
error: The function to call with any errors found.
Returns:
True if an error was emitted.
False otherwise. | Checks for a C-style cast by looking for the pattern. | [
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"""Checks for a C-style cast by looking for the pattern.
Args:
filename: The name of the current file.
clean_lines: A CleansedLines instance containing the file.
linenum: The number of the line to check.
cast_type: The string for the C++ cast to recommend. This is either
reinterpret_cast, static_cast, or const_cast, depending.
pattern: The regular expression used to find C-style casts.
error: The function to call with any errors found.
Returns:
True if an error was emitted.
False otherwise.
"""
line = clean_lines.elided[linenum]
match = Search(pattern, line)
if not match:
return False
# Exclude lines with keywords that tend to look like casts
context = line[0:match.start(1) - 1]
if Match(r'.*\b(?:sizeof|alignof|alignas|[_A-Z][_A-Z0-9]*)\s*$', context):
return False
# Try expanding current context to see if we one level of
# parentheses inside a macro.
if linenum > 0:
for i in xrange(linenum - 1, max(0, linenum - 5), -1):
context = clean_lines.elided[i] + context
if Match(r'.*\b[_A-Z][_A-Z0-9]*\s*\((?:\([^()]*\)|[^()])*$', context):
return False
# operator++(int) and operator--(int)
if context.endswith(' operator++') or context.endswith(' operator--'):
return False
# A single unnamed argument for a function tends to look like old
# style cast. If we see those, don't issue warnings for deprecated
# casts, instead issue warnings for unnamed arguments where
# appropriate.
#
# These are things that we want warnings for, since the style guide
# explicitly require all parameters to be named:
# Function(int);
# Function(int) {
# ConstMember(int) const;
# ConstMember(int) const {
# ExceptionMember(int) throw (...);
# ExceptionMember(int) throw (...) {
# PureVirtual(int) = 0;
# [](int) -> bool {
#
# These are functions of some sort, where the compiler would be fine
# if they had named parameters, but people often omit those
# identifiers to reduce clutter:
# (FunctionPointer)(int);
# (FunctionPointer)(int) = value;
# Function((function_pointer_arg)(int))
# Function((function_pointer_arg)(int), int param)
# <TemplateArgument(int)>;
# <(FunctionPointerTemplateArgument)(int)>;
remainder = line[match.end(0):]
if Match(r'^\s*(?:;|const\b|throw\b|final\b|override\b|[=>{),]|->)',
remainder):
# Looks like an unnamed parameter.
# Don't warn on any kind of template arguments.
if Match(r'^\s*>', remainder):
return False
# Don't warn on assignments to function pointers, but keep warnings for
# unnamed parameters to pure virtual functions. Note that this pattern
# will also pass on assignments of "0" to function pointers, but the
# preferred values for those would be "nullptr" or "NULL".
matched_zero = Match(r'^\s=\s*(\S+)\s*;', remainder)
if matched_zero and matched_zero.group(1) != '0':
return False
# Don't warn on function pointer declarations. For this we need
# to check what came before the "(type)" string.
if Match(r'.*\)\s*$', line[0:match.start(0)]):
return False
# Don't warn if the parameter is named with block comments, e.g.:
# Function(int /*unused_param*/);
raw_line = clean_lines.raw_lines[linenum]
if '/*' in raw_line:
return False
# Passed all filters, issue warning here.
error(filename, linenum, 'readability/function', 3,
'All parameters should be named in a function')
return True
# At this point, all that should be left is actual casts.
error(filename, linenum, 'readability/casting', 4,
'Using C-style cast. Use %s<%s>(...) instead' %
(cast_type, match.group(1)))
return True | [
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microsoft/CNTK | e9396480025b9ca457d26b6f33dd07c474c6aa04 | Examples/Image/Detection/FastRCNN/BrainScript/fastRCNN/imdb.py | python | imdb.competition_mode | (self, on) | Turn competition mode on or off. | Turn competition mode on or off. | [
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] | def competition_mode(self, on):
"""Turn competition mode on or off."""
pass | [
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citizenfx/fivem | 88276d40cc7baf8285d02754cc5ae42ec7a8563f | vendor/chromium/mojo/public/tools/bindings/pylib/mojom/generate/translate.py | python | _Parameter | (module, parsed_param, interface) | return parameter | Args:
module: {mojom.Module} Module currently being constructed.
parsed_param: {ast.Parameter} Parsed parameter.
union: {mojom.Interface} Interface this parameter belongs to.
Returns:
{mojom.Parameter} AST parameter. | Args:
module: {mojom.Module} Module currently being constructed.
parsed_param: {ast.Parameter} Parsed parameter.
union: {mojom.Interface} Interface this parameter belongs to. | [
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"""
Args:
module: {mojom.Module} Module currently being constructed.
parsed_param: {ast.Parameter} Parsed parameter.
union: {mojom.Interface} Interface this parameter belongs to.
Returns:
{mojom.Parameter} AST parameter.
"""
parameter = mojom.Parameter()
parameter.mojom_name = parsed_param.mojom_name
parameter.kind = _Kind(
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parameter.ordinal = (
parsed_param.ordinal.value if parsed_param.ordinal else None)
parameter.default = None # TODO(tibell): We never have these. Remove field?
parameter.attributes = _AttributeListToDict(parsed_param.attribute_list)
return parameter | [
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hszhao/PSPNet | cf7e5a99ba37e46118026e96be5821a9bc63bde0 | scripts/cpp_lint.py | python | _ClassifyInclude | (fileinfo, include, is_system) | return _OTHER_HEADER | Figures out what kind of header 'include' is.
Args:
fileinfo: The current file cpplint is running over. A FileInfo instance.
include: The path to a #included file.
is_system: True if the #include used <> rather than "".
Returns:
One of the _XXX_HEADER constants.
For example:
>>> _ClassifyInclude(FileInfo('foo/foo.cc'), 'stdio.h', True)
_C_SYS_HEADER
>>> _ClassifyInclude(FileInfo('foo/foo.cc'), 'string', True)
_CPP_SYS_HEADER
>>> _ClassifyInclude(FileInfo('foo/foo.cc'), 'foo/foo.h', False)
_LIKELY_MY_HEADER
>>> _ClassifyInclude(FileInfo('foo/foo_unknown_extension.cc'),
... 'bar/foo_other_ext.h', False)
_POSSIBLE_MY_HEADER
>>> _ClassifyInclude(FileInfo('foo/foo.cc'), 'foo/bar.h', False)
_OTHER_HEADER | Figures out what kind of header 'include' is. | [
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] | def _ClassifyInclude(fileinfo, include, is_system):
"""Figures out what kind of header 'include' is.
Args:
fileinfo: The current file cpplint is running over. A FileInfo instance.
include: The path to a #included file.
is_system: True if the #include used <> rather than "".
Returns:
One of the _XXX_HEADER constants.
For example:
>>> _ClassifyInclude(FileInfo('foo/foo.cc'), 'stdio.h', True)
_C_SYS_HEADER
>>> _ClassifyInclude(FileInfo('foo/foo.cc'), 'string', True)
_CPP_SYS_HEADER
>>> _ClassifyInclude(FileInfo('foo/foo.cc'), 'foo/foo.h', False)
_LIKELY_MY_HEADER
>>> _ClassifyInclude(FileInfo('foo/foo_unknown_extension.cc'),
... 'bar/foo_other_ext.h', False)
_POSSIBLE_MY_HEADER
>>> _ClassifyInclude(FileInfo('foo/foo.cc'), 'foo/bar.h', False)
_OTHER_HEADER
"""
# This is a list of all standard c++ header files, except
# those already checked for above.
is_cpp_h = include in _CPP_HEADERS
if is_system:
if is_cpp_h:
return _CPP_SYS_HEADER
else:
return _C_SYS_HEADER
# If the target file and the include we're checking share a
# basename when we drop common extensions, and the include
# lives in . , then it's likely to be owned by the target file.
target_dir, target_base = (
os.path.split(_DropCommonSuffixes(fileinfo.RepositoryName())))
include_dir, include_base = os.path.split(_DropCommonSuffixes(include))
if target_base == include_base and (
include_dir == target_dir or
include_dir == os.path.normpath(target_dir + '/../public')):
return _LIKELY_MY_HEADER
# If the target and include share some initial basename
# component, it's possible the target is implementing the
# include, so it's allowed to be first, but we'll never
# complain if it's not there.
target_first_component = _RE_FIRST_COMPONENT.match(target_base)
include_first_component = _RE_FIRST_COMPONENT.match(include_base)
if (target_first_component and include_first_component and
target_first_component.group(0) ==
include_first_component.group(0)):
return _POSSIBLE_MY_HEADER
return _OTHER_HEADER | [
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ValveSoftware/source-sdk-2013 | 0d8dceea4310fde5706b3ce1c70609d72a38efdf | mp/src/thirdparty/protobuf-2.3.0/python/google/protobuf/internal/containers.py | python | BaseContainer.__ne__ | (self, other) | return not self == other | Checks if another instance isn't equal to this one. | Checks if another instance isn't equal to this one. | [
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"""Checks if another instance isn't equal to this one."""
# The concrete classes should define __eq__.
return not self == other | [
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kamyu104/LeetCode-Solutions | 77605708a927ea3b85aee5a479db733938c7c211 | Python/range-sum-query-immutable.py | python | NumArray.__init__ | (self, nums) | initialize your data structure here.
:type nums: List[int] | initialize your data structure here.
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self.accu = [0]
for num in nums:
self.accu.append(self.accu[-1] + num), | [
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priyankchheda/algorithms | c361aa9071573fa9966d5b02d05e524815abcf2b | priority_queue/minheap.py | python | MinHeap.get_min | (self) | return self.data[1] | get_min returns the minimum value (i.e. root) in the heap,
without removing it. Returns None, if the heap is empty. | get_min returns the minimum value (i.e. root) in the heap,
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"""
if self.is_empty():
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return self.data[1] | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/pexpect/pexpect/screen.py | python | screen.cursor_unsave | (self) | Restores cursor position after a Save Cursor. | Restores cursor position after a Save Cursor. | [
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] | def cursor_unsave (self): # <ESC>[u
'''Restores cursor position after a Save Cursor.'''
self.cursor_restore_attrs() | [
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CRYTEK/CRYENGINE | 232227c59a220cbbd311576f0fbeba7bb53b2a8c | Editor/Python/windows/Lib/site-packages/pip/_vendor/requests/packages/urllib3/util/ssl_.py | python | resolve_ssl_version | (candidate) | return candidate | like resolve_cert_reqs | like resolve_cert_reqs | [
"like",
"resolve_cert_reqs"
] | def resolve_ssl_version(candidate):
"""
like resolve_cert_reqs
"""
if candidate is None:
return PROTOCOL_SSLv23
if isinstance(candidate, str):
res = getattr(ssl, candidate, None)
if res is None:
res = getattr(ssl, 'PROTOCOL_' + candidate)
return res
return candidate | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/windows/Lib/site-packages/pip/_vendor/urllib3/connectionpool.py | python | HTTPConnectionPool.close | (self) | Close all pooled connections and disable the pool. | Close all pooled connections and disable the pool. | [
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] | def close(self):
"""
Close all pooled connections and disable the pool.
"""
if self.pool is None:
return
# Disable access to the pool
old_pool, self.pool = self.pool, None
try:
while True:
conn = old_pool.get(block=False)
if conn:
conn.close()
except queue.Empty:
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wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_cocoa/aui.py | python | AuiNotebook.ShowWindowMenu | (*args, **kwargs) | return _aui.AuiNotebook_ShowWindowMenu(*args, **kwargs) | ShowWindowMenu(self) -> bool | ShowWindowMenu(self) -> bool | [
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"""ShowWindowMenu(self) -> bool"""
return _aui.AuiNotebook_ShowWindowMenu(*args, **kwargs) | [
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wlanjie/AndroidFFmpeg | 7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf | tools/fdk-aac-build/armeabi/toolchain/lib/python2.7/lib-tk/Tkinter.py | python | Place.place_forget | (self) | Unmap this widget. | Unmap this widget. | [
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] | def place_forget(self):
"""Unmap this widget."""
self.tk.call('place', 'forget', self._w) | [
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benoitsteiner/tensorflow-opencl | cb7cb40a57fde5cfd4731bc551e82a1e2fef43a5 | tensorflow/python/debug/cli/analyzer_cli.py | python | DebugAnalyzer.get_tensor_filter | (self, filter_name) | return self._tensor_filters[filter_name] | Retrieve filter function by name.
Args:
filter_name: Name of the filter set during add_tensor_filter() call.
Returns:
The callable associated with the filter name.
Raises:
ValueError: If there is no tensor filter of the specified filter name. | Retrieve filter function by name. | [
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] | def get_tensor_filter(self, filter_name):
"""Retrieve filter function by name.
Args:
filter_name: Name of the filter set during add_tensor_filter() call.
Returns:
The callable associated with the filter name.
Raises:
ValueError: If there is no tensor filter of the specified filter name.
"""
if filter_name not in self._tensor_filters:
raise ValueError("There is no tensor filter named \"%s\"" % filter_name)
return self._tensor_filters[filter_name] | [
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catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/prompt-toolkit/py3/prompt_toolkit/layout/processors.py | python | merge_processors | (processors: List[Processor]) | return _MergedProcessor(processors) | Merge multiple `Processor` objects into one. | Merge multiple `Processor` objects into one. | [
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"one",
"."
] | def merge_processors(processors: List[Processor]) -> Processor:
"""
Merge multiple `Processor` objects into one.
"""
if len(processors) == 0:
return DummyProcessor()
if len(processors) == 1:
return processors[0] # Nothing to merge.
return _MergedProcessor(processors) | [
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apple/turicreate | cce55aa5311300e3ce6af93cb45ba791fd1bdf49 | deps/src/libxml2-2.9.1/python/libxml2.py | python | xpathContext.xpathRegisterAllFunctions | (self) | Registers all default XPath functions in this context | Registers all default XPath functions in this context | [
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] | def xpathRegisterAllFunctions(self):
"""Registers all default XPath functions in this context """
libxml2mod.xmlXPathRegisterAllFunctions(self._o) | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/base64.py | python | b64decode | (s, altchars=None, validate=False) | return binascii.a2b_base64(s) | Decode the Base64 encoded bytes-like object or ASCII string s.
Optional altchars must be a bytes-like object or ASCII string of length 2
which specifies the alternative alphabet used instead of the '+' and '/'
characters.
The result is returned as a bytes object. A binascii.Error is raised if
s is incorrectly padded.
If validate is False (the default), characters that are neither in the
normal base-64 alphabet nor the alternative alphabet are discarded prior
to the padding check. If validate is True, these non-alphabet characters
in the input result in a binascii.Error. | Decode the Base64 encoded bytes-like object or ASCII string s. | [
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] | def b64decode(s, altchars=None, validate=False):
"""Decode the Base64 encoded bytes-like object or ASCII string s.
Optional altchars must be a bytes-like object or ASCII string of length 2
which specifies the alternative alphabet used instead of the '+' and '/'
characters.
The result is returned as a bytes object. A binascii.Error is raised if
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If validate is False (the default), characters that are neither in the
normal base-64 alphabet nor the alternative alphabet are discarded prior
to the padding check. If validate is True, these non-alphabet characters
in the input result in a binascii.Error.
"""
s = _bytes_from_decode_data(s)
if altchars is not None:
altchars = _bytes_from_decode_data(altchars)
assert len(altchars) == 2, repr(altchars)
s = s.translate(bytes.maketrans(altchars, b'+/'))
if validate and not re.fullmatch(b'[A-Za-z0-9+/]*={0,2}', s):
raise binascii.Error('Non-base64 digit found')
return binascii.a2b_base64(s) | [
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ValveSoftware/source-sdk-2013 | 0d8dceea4310fde5706b3ce1c70609d72a38efdf | sp/src/thirdparty/protobuf-2.3.0/python/google/protobuf/reflection.py | python | _AddSerializeToStringMethod | (message_descriptor, cls) | Helper for _AddMessageMethods(). | Helper for _AddMessageMethods(). | [
"Helper",
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"()",
"."
] | def _AddSerializeToStringMethod(message_descriptor, cls):
"""Helper for _AddMessageMethods()."""
def SerializeToString(self):
# Check if the message has all of its required fields set.
errors = []
if not self.IsInitialized():
raise message_mod.EncodeError(
'Message is missing required fields: ' +
','.join(self.FindInitializationErrors()))
return self.SerializePartialToString()
cls.SerializeToString = SerializeToString | [
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yuxng/PoseCNN | 9f3dd7b7bce21dcafc05e8f18ccc90da3caabd04 | lib/gt_single_data_layer/layer.py | python | GtSingleDataLayer._shuffle_roidb_inds | (self) | Randomly permute the training roidb. | Randomly permute the training roidb. | [
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"."
] | def _shuffle_roidb_inds(self):
"""Randomly permute the training roidb."""
self._perm = np.random.permutation(np.arange(len(self._roidb)))
#print self._roidb[self._perm[14]]['meta_data']
#print self._roidb[self._perm[15]]['meta_data']
#print self._roidb[self._perm[16]]['meta_data']
self._cur = 0 | [
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windystrife/UnrealEngine_NVIDIAGameWorks | b50e6338a7c5b26374d66306ebc7807541ff815e | Engine/Extras/ThirdPartyNotUE/emsdk/Win64/python/2.7.5.3_64bit/Lib/fractions.py | python | Fraction._richcmp | (self, other, op) | Helper for comparison operators, for internal use only.
Implement comparison between a Rational instance `self`, and
either another Rational instance or a float `other`. If
`other` is not a Rational instance or a float, return
NotImplemented. `op` should be one of the six standard
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] | def _richcmp(self, other, op):
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Implement comparison between a Rational instance `self`, and
either another Rational instance or a float `other`. If
`other` is not a Rational instance or a float, return
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"""
# convert other to a Rational instance where reasonable.
if isinstance(other, Rational):
return op(self._numerator * other.denominator,
self._denominator * other.numerator)
# comparisons with complex should raise a TypeError, for consistency
# with int<->complex, float<->complex, and complex<->complex comparisons.
if isinstance(other, complex):
raise TypeError("no ordering relation is defined for complex numbers")
if isinstance(other, float):
if math.isnan(other) or math.isinf(other):
return op(0.0, other)
else:
return op(self, self.from_float(other))
else:
return NotImplemented | [
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