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smilehao/xlua-framework | a03801538be2b0e92d39332d445b22caca1ef61f | ConfigData/trunk/tools/protobuf-2.5.0/protobuf-2.5.0/python/build/lib/google/protobuf/internal/python_message.py | python | _AddSlots | (message_descriptor, dictionary) | Adds a __slots__ entry to dictionary, containing the names of all valid
attributes for this message type.
Args:
message_descriptor: A Descriptor instance describing this message type.
dictionary: Class dictionary to which we'll add a '__slots__' entry. | Adds a __slots__ entry to dictionary, containing the names of all valid
attributes for this message type. | [
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] | def _AddSlots(message_descriptor, dictionary):
"""Adds a __slots__ entry to dictionary, containing the names of all valid
attributes for this message type.
Args:
message_descriptor: A Descriptor instance describing this message type.
dictionary: Class dictionary to which we'll add a '__slots__' entry.
"""
dictionary['__slots__'] = ['_cached_byte_size',
'_cached_byte_size_dirty',
'_fields',
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'_is_present_in_parent',
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'__weakref__'] | [
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||
wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_carbon/_controls.py | python | CheckListBox.Check | (*args, **kwargs) | return _controls_.CheckListBox_Check(*args, **kwargs) | Check(self, unsigned int index, int check=True) | Check(self, unsigned int index, int check=True) | [
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"""Check(self, unsigned int index, int check=True)"""
return _controls_.CheckListBox_Check(*args, **kwargs) | [
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|
hanpfei/chromium-net | 392cc1fa3a8f92f42e4071ab6e674d8e0482f83f | third_party/catapult/third_party/gsutil/third_party/boto/boto/kms/layer1.py | python | KMSConnection.re_encrypt | (self, ciphertext_blob, destination_key_id,
source_encryption_context=None,
destination_encryption_context=None, grant_tokens=None) | return response | Encrypts data on the server side with a new customer master
key without exposing the plaintext of the data on the client
side. The data is first decrypted and then encrypted. This
operation can also be used to change the encryption context of
a ciphertext.
:type ciphertext_blob: blob
:param ciphertext_blob: Ciphertext of the data to re-encrypt.
:type source_encryption_context: map
:param source_encryption_context: Encryption context used to encrypt
and decrypt the data specified in the `CiphertextBlob` parameter.
:type destination_key_id: string
:param destination_key_id: Key identifier of the key used to re-encrypt
the data.
:type destination_encryption_context: map
:param destination_encryption_context: Encryption context to be used
when the data is re-encrypted.
:type grant_tokens: list
:param grant_tokens: Grant tokens that identify the grants that have
permissions for the encryption and decryption process. | Encrypts data on the server side with a new customer master
key without exposing the plaintext of the data on the client
side. The data is first decrypted and then encrypted. This
operation can also be used to change the encryption context of
a ciphertext. | [
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] | def re_encrypt(self, ciphertext_blob, destination_key_id,
source_encryption_context=None,
destination_encryption_context=None, grant_tokens=None):
"""
Encrypts data on the server side with a new customer master
key without exposing the plaintext of the data on the client
side. The data is first decrypted and then encrypted. This
operation can also be used to change the encryption context of
a ciphertext.
:type ciphertext_blob: blob
:param ciphertext_blob: Ciphertext of the data to re-encrypt.
:type source_encryption_context: map
:param source_encryption_context: Encryption context used to encrypt
and decrypt the data specified in the `CiphertextBlob` parameter.
:type destination_key_id: string
:param destination_key_id: Key identifier of the key used to re-encrypt
the data.
:type destination_encryption_context: map
:param destination_encryption_context: Encryption context to be used
when the data is re-encrypted.
:type grant_tokens: list
:param grant_tokens: Grant tokens that identify the grants that have
permissions for the encryption and decryption process.
"""
if not isinstance(ciphertext_blob, six.binary_type):
raise TypeError(
"Value of argument ``ciphertext_blob`` "
"must be of type %s." % six.binary_type)
ciphertext_blob = base64.b64encode(ciphertext_blob)
params = {
'CiphertextBlob': ciphertext_blob,
'DestinationKeyId': destination_key_id,
}
if source_encryption_context is not None:
params['SourceEncryptionContext'] = source_encryption_context
if destination_encryption_context is not None:
params['DestinationEncryptionContext'] = destination_encryption_context
if grant_tokens is not None:
params['GrantTokens'] = grant_tokens
response = self.make_request(action='ReEncrypt',
body=json.dumps(params))
if response.get('CiphertextBlob') is not None:
response['CiphertextBlob'] = base64.b64decode(
response['CiphertextBlob'].encode('utf-8'))
return response | [
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|
arkenthera/electron-vibrancy | 383153ef9ccb23a6c7517150d6bb0794dff3115e | scripts/cpplint.py | python | NestingState.CheckCompletedBlocks | (self, filename, error) | Checks that all classes and namespaces have been completely parsed.
Call this when all lines in a file have been processed.
Args:
filename: The name of the current file.
error: The function to call with any errors found. | Checks that all classes and namespaces have been completely parsed. | [
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"and",
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] | def CheckCompletedBlocks(self, filename, error):
"""Checks that all classes and namespaces have been completely parsed.
Call this when all lines in a file have been processed.
Args:
filename: The name of the current file.
error: The function to call with any errors found.
"""
# Note: This test can result in false positives if #ifdef constructs
# get in the way of brace matching. See the testBuildClass test in
# cpplint_unittest.py for an example of this.
for obj in self.stack:
if isinstance(obj, _ClassInfo):
error(filename, obj.starting_linenum, 'build/class', 5,
'Failed to find complete declaration of class %s' %
obj.name)
elif isinstance(obj, _NamespaceInfo):
error(filename, obj.starting_linenum, 'build/namespaces', 5,
'Failed to find complete declaration of namespace %s' %
obj.name) | [
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||
aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Gems/CloudGemWebCommunicator/AWS/common-code/lib/AWSIoTPythonSDK/core/greengrass/discovery/models.py | python | CoreConnectivityInfo.connectivityInfoList | (self) | return list(self._connectivity_info_dict.values()) | The list of connectivity information that this Greengrass core has. | [] | def connectivityInfoList(self):
"""
The list of connectivity information that this Greengrass core has.
"""
return list(self._connectivity_info_dict.values()) | [
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||
wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/gtk/richtext.py | python | RichTextObject.GetTopMargin | (*args, **kwargs) | return _richtext.RichTextObject_GetTopMargin(*args, **kwargs) | GetTopMargin(self) -> int | GetTopMargin(self) -> int | [
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"""GetTopMargin(self) -> int"""
return _richtext.RichTextObject_GetTopMargin(*args, **kwargs) | [
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|
xhzdeng/crpn | a5aef0f80dbe486103123f740c634fb01e6cc9a1 | caffe-fast-rcnn/python/caffe/coord_map.py | python | crop | (top_from, top_to) | return L.Crop(top_from, top_to,
crop_param=dict(axis=ax + 1, # +1 for first cropping dim.
offset=list(-np.round(b).astype(int)))) | Define a Crop layer to crop a top (from) to another top (to) by
determining the coordinate mapping between the two and net spec'ing
the axis and shift parameters of the crop. | Define a Crop layer to crop a top (from) to another top (to) by
determining the coordinate mapping between the two and net spec'ing
the axis and shift parameters of the crop. | [
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"""
Define a Crop layer to crop a top (from) to another top (to) by
determining the coordinate mapping between the two and net spec'ing
the axis and shift parameters of the crop.
"""
ax, a, b = coord_map_from_to(top_from, top_to)
assert (a == 1).all(), 'scale mismatch on crop (a = {})'.format(a)
assert (b <= 0).all(), 'cannot crop negative offset (b = {})'.format(b)
assert (np.round(b) == b).all(), 'cannot crop noninteger offset ' \
'(b = {})'.format(b)
return L.Crop(top_from, top_to,
crop_param=dict(axis=ax + 1, # +1 for first cropping dim.
offset=list(-np.round(b).astype(int)))) | [
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|
Kitware/VTK | 5b4df4d90a4f31194d97d3c639dd38ea8f81e8b8 | Utilities/Maintenance/FindNeededModules.py | python | get_users_file_headers | (path) | return headers | Get the set of VTK headers in a user's file or files with a common name in the path.
:param path: The file name or the file name without the extension.
:return: headers as the key and the corresponding filenames as the value. | Get the set of VTK headers in a user's file or files with a common name in the path.
:param path: The file name or the file name without the extension.
:return: headers as the key and the corresponding filenames as the value. | [
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"""
Get the set of VTK headers in a user's file or files with a common name in the path.
:param path: The file name or the file name without the extension.
:return: headers as the key and the corresponding filenames as the value.
"""
c = Constants()
headers = collections.defaultdict(set)
name, ext = os.path.splitext(path)
if ext:
if ext in c.valid_ext:
if not os.path.isfile(path):
raise Exception('No such file: ' + path)
with open(path) as data:
# Read the file looking for includes.
for line in data:
m = c.header_pattern.match(line.strip())
if m:
# We have a header name, split it from its path (if the path exists).
header_parts = os.path.split(m.group(1))
m = c.vtk_include_pattern.match(header_parts[1])
if m:
headers[m.group(1)].add(os.path.split(path)[1])
else:
raise Exception('Unrecognised extension:' + path)
else:
for ext in c.valid_ext:
fn = name + ext
if os.path.isfile(fn):
with open(fn) as data:
# Read the file looking for includes.
for line in data:
m = c.header_pattern.match(line.strip())
if m:
# We have a header name, split it from its path (if the path exists).
header_parts = os.path.split(m.group(1))
m = c.vtk_include_pattern.match(header_parts[1])
if m:
headers[m.group(1)].add(os.path.split(path)[1])
return headers | [
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|
weichengkuo/DeepBox | c4f8c065b6a51cf296540cc453a44f0519aaacc9 | caffe-fast-rcnn/scripts/cpp_lint.py | python | GetPreviousNonBlankLine | (clean_lines, linenum) | return ('', -1) | Return the most recent non-blank line and its line number.
Args:
clean_lines: A CleansedLines instance containing the file contents.
linenum: The number of the line to check.
Returns:
A tuple with two elements. The first element is the contents of the last
non-blank line before the current line, or the empty string if this is the
first non-blank line. The second is the line number of that line, or -1
if this is the first non-blank line. | Return the most recent non-blank line and its line number. | [
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] | def GetPreviousNonBlankLine(clean_lines, linenum):
"""Return the most recent non-blank line and its line number.
Args:
clean_lines: A CleansedLines instance containing the file contents.
linenum: The number of the line to check.
Returns:
A tuple with two elements. The first element is the contents of the last
non-blank line before the current line, or the empty string if this is the
first non-blank line. The second is the line number of that line, or -1
if this is the first non-blank line.
"""
prevlinenum = linenum - 1
while prevlinenum >= 0:
prevline = clean_lines.elided[prevlinenum]
if not IsBlankLine(prevline): # if not a blank line...
return (prevline, prevlinenum)
prevlinenum -= 1
return ('', -1) | [
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|
hanpfei/chromium-net | 392cc1fa3a8f92f42e4071ab6e674d8e0482f83f | third_party/catapult/third_party/gsutil/third_party/httplib2/python3/httplib2/__init__.py | python | parse_uri | (uri) | return (groups[1], groups[3], groups[4], groups[6], groups[8]) | Parses a URI using the regex given in Appendix B of RFC 3986.
(scheme, authority, path, query, fragment) = parse_uri(uri) | Parses a URI using the regex given in Appendix B of RFC 3986. | [
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] | def parse_uri(uri):
"""Parses a URI using the regex given in Appendix B of RFC 3986.
(scheme, authority, path, query, fragment) = parse_uri(uri)
"""
groups = URI.match(uri).groups()
return (groups[1], groups[3], groups[4], groups[6], groups[8]) | [
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|
PaddlePaddle/Paddle | 1252f4bb3e574df80aa6d18c7ddae1b3a90bd81c | python/paddle/distributed/fleet/base/fleet_base.py | python | Fleet.init | (self, role_maker=None, is_collective=False, strategy=None) | Initialize role_maker in Fleet.
This function is responsible for the distributed architecture
what you want to run your code behind.
Args:
role_maker (RoleMakerBase, optional): A ``RoleMakerBase`` containing the configuration
of environment variables related to distributed training.If you did not initialize
the rolemaker by yourself, it will be automatically initialized to PaddleRoleMaker.
The default value is None.
is_collective (Boolean, optional): A ``Boolean`` variable determines whether the program
runs on the CPU or GPU. False means set distributed training using CPU, and True means
GPU.The default value is False.The default value is False.
strategy (DistributedStrategy): Extra properties for distributed training.
For details, please refer to paddle.distributed.fleet.DistributedStrategy. Default: None.
Returns:
None
Examples1:
.. code-block:: python
import paddle.distributed.fleet as fleet
fleet.init()
Examples2:
.. code-block:: python
import paddle.distributed.fleet as fleet
fleet.init(is_collective=True)
Examples3:
.. code-block:: python
import paddle.distributed.fleet as fleet
role = fleet.PaddleCloudRoleMaker()
fleet.init(role)
Examples4:
.. code-block:: python
import paddle.distributed.fleet as fleet
strategy = fleet.DistributedStrategy()
fleet.init(strategy=strategy) | Initialize role_maker in Fleet. | [
"Initialize",
"role_maker",
"in",
"Fleet",
"."
] | def init(self, role_maker=None, is_collective=False, strategy=None):
"""
Initialize role_maker in Fleet.
This function is responsible for the distributed architecture
what you want to run your code behind.
Args:
role_maker (RoleMakerBase, optional): A ``RoleMakerBase`` containing the configuration
of environment variables related to distributed training.If you did not initialize
the rolemaker by yourself, it will be automatically initialized to PaddleRoleMaker.
The default value is None.
is_collective (Boolean, optional): A ``Boolean`` variable determines whether the program
runs on the CPU or GPU. False means set distributed training using CPU, and True means
GPU.The default value is False.The default value is False.
strategy (DistributedStrategy): Extra properties for distributed training.
For details, please refer to paddle.distributed.fleet.DistributedStrategy. Default: None.
Returns:
None
Examples1:
.. code-block:: python
import paddle.distributed.fleet as fleet
fleet.init()
Examples2:
.. code-block:: python
import paddle.distributed.fleet as fleet
fleet.init(is_collective=True)
Examples3:
.. code-block:: python
import paddle.distributed.fleet as fleet
role = fleet.PaddleCloudRoleMaker()
fleet.init(role)
Examples4:
.. code-block:: python
import paddle.distributed.fleet as fleet
strategy = fleet.DistributedStrategy()
fleet.init(strategy=strategy)
"""
if strategy is None:
strategy = DistributedStrategy()
self._user_defined_strategy = copy.deepcopy(strategy)
if role_maker is None:
if isinstance(is_collective, bool):
self._is_collective = is_collective
self._role_maker = PaddleCloudRoleMaker(
is_collective=self._is_collective)
else:
raise ValueError(
"`is_collective` should be instance of `bool`, but got {}".
format(type(is_collective)))
else:
if isinstance(role_maker, RoleMakerBase):
self._role_maker = role_maker
self._is_collective = role_maker._is_collective
else:
raise ValueError(
"`role_maker` should be subclass of `RoleMakerBase`, but got {}".
format(type(role_maker)))
self._role_maker._generate_role()
import paddle.distributed.fleet as fleet
fleet.util._set_role_maker(self._role_maker)
self.strategy_compiler = StrategyCompiler()
if self._role_maker._is_non_distributed() and self._is_collective:
if paddle.fluid.core.is_compiled_with_cuda():
gpus_num = paddle.fluid.core.get_cuda_device_count()
if gpus_num != 1:
raise ValueError(
"CUDA_VISIBLE_DEVICES shoule be set only 1 card if you use `python` to launch fleet program."
)
if paddle.fluid.framework.in_dygraph_mode():
if self.worker_num() == 1:
# if worker_num is 1, should construct default topology & hcg
self._topology = tp.CommunicateTopology()
self._hcg = tp.HybridCommunicateGroup(self._topology)
return
if parallel_helper._is_parallel_ctx_initialized():
warnings.warn(
"The dygraph parallel environment has been initialized.")
else:
# FLAGS_nccl_nrings is used for dynamic graph multi-stream communication
if "FLAGS_nccl_nrings" in os.environ:
warnings.warn(
"You have set the environment variable FLAGS_nccl_nrings "
"outside the program, so the nccl_comm_num in "
"DistributedStrategy will not take effect here.")
else:
os.environ["FLAGS_nccl_nrings"] = str(
self._user_defined_strategy.nccl_comm_num)
paddle.distributed.init_parallel_env()
# hybrid parallel not support for npu/xpu
if self._user_defined_strategy.heter_ccl_mode == False:
# init hybrid parallel environment in dygraph
if tp._HYBRID_PARALLEL_GROUP is None:
self._init_hybrid_parallel_env()
else:
warnings.warn(
"The dygraph hybrid parallel environment has been initialized."
)
elif self._is_collective:
use_sharding = self._user_defined_strategy.sharding
# global group
global_rank = self.worker_index()
global_world_size = self.worker_num()
# NOTE(wangxi): see sharding_optimizer
global_ring_id = 3 if use_sharding else 0
global_ranks = list(range(global_world_size))
if tp._HYBRID_PARALLEL_GROUP is None: tp._CommunicateGroup()
cg = tp._HYBRID_PARALLEL_GROUP
self._hcg = cg
cg.set_comm_group('global', global_rank, global_world_size,
global_ring_id, global_ranks)
use_tensor_parallel = self._user_defined_strategy.tensor_parallel
use_mp = use_sharding or use_tensor_parallel
# hybrid group
if use_mp is False: return
mp_degree_sharding = 1
mp_degree_tensor_parallel = 1
if use_sharding:
sharding_configs = self._user_defined_strategy.sharding_configs
mp_degree_sharding = int(sharding_configs['mp_degree'])
if use_tensor_parallel:
tensor_parallel_configs = self._user_defined_strategy.tensor_parallel_configs
mp_degree_tensor_parallel = int(tensor_parallel_configs[
'tensor_parallel_degree'])
if use_sharding and use_tensor_parallel:
assert mp_degree_sharding == mp_degree_tensor_parallel
mp_degree = mp_degree_sharding if use_sharding else mp_degree_tensor_parallel
if mp_degree > 1:
assert global_world_size % mp_degree == 0
# NOTE(wangxi): mp_ring_id sync with sharding_optimizer.py _build_groups
mp_ring_id = 0
mp_rank = global_rank % mp_degree
mp_group_id = global_rank // mp_degree
mp_group_ranks = [
idx for idx in global_ranks
if idx // mp_degree == mp_group_id
]
cg.set_comm_group('model', mp_rank, mp_degree, mp_ring_id,
mp_group_ranks) | [
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||
pytorch/pytorch | 7176c92687d3cc847cc046bf002269c6949a21c2 | benchmarks/tensorexpr/attention.py | python | BahdanauAttention.forward | (self, att_query, att_keys, normalize_bias, linear_att) | return out | Calculate Bahdanau score
:param att_query: b x t_q x n
:param att_keys: b x t_k x n
return b x t_q x t_k scores | Calculate Bahdanau score | [
"Calculate",
"Bahdanau",
"score"
] | def forward(self, att_query, att_keys, normalize_bias, linear_att):
"""
Calculate Bahdanau score
:param att_query: b x t_q x n
:param att_keys: b x t_k x n
return b x t_q x t_k scores
"""
b, t_k, n = att_keys.size()
t_q = att_query.size(1)
att_query = att_query.unsqueeze(2).expand(b, t_q, t_k, n)
att_keys = att_keys.unsqueeze(1).expand(b, t_q, t_k, n)
sum_qk = att_query + att_keys + normalize_bias
out = torch.tanh(sum_qk).matmul(linear_att)
return out | [
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|
PaddlePaddle/Paddle | 1252f4bb3e574df80aa6d18c7ddae1b3a90bd81c | python/paddle/tensor/math.py | python | erfinv_ | (x, name=None) | return _C_ops.erfinv_(x) | r"""
Inplace version of ``erfinv`` API, the output Tensor will be inplaced with input ``x``.
Please refer to :ref:`api_tensor_erfinv`. | r"""
Inplace version of ``erfinv`` API, the output Tensor will be inplaced with input ``x``.
Please refer to :ref:`api_tensor_erfinv`. | [
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r"""
Inplace version of ``erfinv`` API, the output Tensor will be inplaced with input ``x``.
Please refer to :ref:`api_tensor_erfinv`.
"""
check_type(x, 'x', (paddle.Tensor, Variable), 'erfinv')
return _C_ops.erfinv_(x) | [
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PyMesh/PyMesh | 384ba882b7558ba6e8653ed263c419226c22bddf | python/pymesh/meshutils/generate_tube.py | python | generate_tube | (p0, p1, r0_out, r1_out, r0_in, r1_in, num_segments=16,
with_quad=False) | return form_mesh(vertices, faces) | Generate generalized tube (i.e. cylinder with an axial hole).
Args:
p0 (``np.ndarray``): Bottom center.
p1 (``np.ndarray``): Top center.
r0_out (``float``): Bottom outer radius.
r1_out (``float``): Top outer radius.
r0_in (``float``): Bottom inner radius.
r1_in (``float``): Top inner radius.
num_segments (``int``): Number of segments to a discrete circle consists.
with_quad (``bool``): Output a quad mesh instead.
Returns:
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with_quad=False):
""" Generate generalized tube (i.e. cylinder with an axial hole).
Args:
p0 (``np.ndarray``): Bottom center.
p1 (``np.ndarray``): Top center.
r0_out (``float``): Bottom outer radius.
r1_out (``float``): Top outer radius.
r0_in (``float``): Bottom inner radius.
r1_in (``float``): Top inner radius.
num_segments (``int``): Number of segments to a discrete circle consists.
with_quad (``bool``): Output a quad mesh instead.
Returns:
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"""
assert(len(p0) == 3)
assert(len(p1) == 3)
Z = np.array([0, 0, 1], dtype=float)
p0 = np.array(p0, dtype=float)
p1 = np.array(p1, dtype=float)
axis = p1 - p0
l = norm(axis)
if l <= 1e-12:
axis=Z
N = num_segments
angles = [2*math.pi*i/float(N) for i in range(N)]
rim = np.array([[math.cos(theta), math.sin(theta), 0.0]
for theta in angles])
rot = Quaternion.fromData(Z, axis).to_matrix()
bottom_outer_rim = np.dot(rot, rim.T).T * r0_out + p0
bottom_inner_rim = np.dot(rot, rim.T).T * r0_in + p0
top_outer_rim = np.dot(rot, rim.T).T * r1_out + p1
top_inner_rim = np.dot(rot, rim.T).T * r1_in + p1
vertices = np.vstack([
bottom_outer_rim,
bottom_inner_rim,
top_outer_rim,
top_inner_rim])
if with_quad:
top = np.array([
[2*N+i, 2*N+(i+1)%N, 3*N+(i+1)%N, 3*N+i]
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bottom = np.array([
[(i+1)%N, i, N+i, N+(i+1)%N]
for i in range(N)])
inner = np.array([
[3*N+i, 3*N+(i+1)%N, N+(i+1)%N, N+i]
for i in range(N)])
outer = np.array([
[ i, (i+1)%N, 2*N+(i+1)%N, 2*N+i]
for i in range(N)])
faces = np.vstack([top, bottom, inner, outer])
else:
top = np.array([
[ [2*N+i, 2*N+(i+1)%N, 3*N+i],
[3*N+i, 2*N+(i+1)%N, 3*N+(i+1)%N]
] for i in range(N)])
bottom = np.array([
[ [(i+1)%N, i, N+i],
[(i+1)%N, N+i, N+(i+1)%N]
] for i in range(N)])
inner = np.array([
[ [3*N+i, 3*N+(i+1)%N, N+i],
[ N+i, 3*N+(i+1)%N, N+(i+1)%N]
] for i in range(N)])
outer = np.array([
[ [ i, (i+1)%N, 2*N+i],
[2*N+i, (i+1)%N, 2*N+(i+1)%N]
] for i in range(N)])
faces = np.vstack([
top.reshape((-1, 3)),
bottom.reshape((-1, 3)),
inner.reshape((-1, 3)),
outer.reshape((-1, 3)) ])
return form_mesh(vertices, faces) | [
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|
wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/msw/_controls.py | python | TextAttr.HasLineSpacing | (*args, **kwargs) | return _controls_.TextAttr_HasLineSpacing(*args, **kwargs) | HasLineSpacing(self) -> bool | HasLineSpacing(self) -> bool | [
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"""HasLineSpacing(self) -> bool"""
return _controls_.TextAttr_HasLineSpacing(*args, **kwargs) | [
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|
Yelp/MOE | 5b5a6a2c6c3cf47320126f7f5894e2a83e347f5c | moe/optimal_learning/python/data_containers.py | python | HistoricalData.__str__ | (self, pretty_print=True) | String representation of this HistoricalData object.
pretty-print'ing produces output that is easily read by humans.
Disabling it prints the member arrays to the screen in full precision; this is convenient for
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:param pretty_print: enable pretty-printing for formatted, human-readable output
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pasting into C++ or other debugging purposes.
:param pretty_print: enable pretty-printing for formatted, human-readable output
:type pretty_print: bool
:return: string representation
:rtype: string
"""
if pretty_print:
sample_point_list = self.to_list_of_sample_points()
return pprint.pformat(sample_point_list)
else:
out_string = repr(self._points_sampled) + '\n'
out_string += repr(self._points_sampled_value) + '\n'
out_string += repr(self._points_sampled_noise_variance)
return out_string | [
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pytorch/pytorch | 7176c92687d3cc847cc046bf002269c6949a21c2 | caffe2/python/core.py | python | ExecutionStep.SetReportNet | (self, report_net, report_interval) | DEPRECATED. Use RunEveryMillis instead. | DEPRECATED. Use RunEveryMillis instead. | [
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self._assert_can_mutate()
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self._step.report_net = get_net_name(report_net)
self._step.report_interval = report_interval | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/AWSPythonSDK/1.5.8/docutils/utils/math/math2html.py | python | NumberCounter.reset | (self) | Reset the counter. | Reset the counter. | [
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||
vslavik/poedit | f7a9daa0a10037e090aa0a86f5ce0f24ececdf6a | deps/boost/libs/predef/tools/ci/build_log.py | python | BuildOutputProcessor.add_input | (self, input) | Add a single build XML output file to our data. | Add a single build XML output file to our data. | [
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] | def add_input(self, input):
'''
Add a single build XML output file to our data.
'''
events = xml.dom.pulldom.parse(input)
context = []
for (event,node) in events:
if event == xml.dom.pulldom.START_ELEMENT:
context.append(node)
if node.nodeType == xml.dom.Node.ELEMENT_NODE:
x_f = self.x_name_(*context)
if x_f:
events.expandNode(node)
# expanding eats the end element, hence walking us out one level
context.pop()
# call handler
(x_f[1])(node)
elif event == xml.dom.pulldom.END_ELEMENT:
context.pop() | [
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||
Kitware/ParaView | f760af9124ff4634b23ebbeab95a4f56e0261955 | Wrapping/Python/paraview/servermanager.py | python | InputProperty.__setitem__ | (self, idx, value) | Given a list or tuple of values, sets a slice of values [min, max) | Given a list or tuple of values, sets a slice of values [min, max) | [
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] | def __setitem__(self, idx, value):
"""Given a list or tuple of values, sets a slice of values [min, max)"""
if isinstance(idx, slice):
indices = idx.indices(len(self))
for i, j in zip(range(*indices), value):
op = value[i-min]
self.SMProperty.SetInputConnection(i, op.SMProxy, op.Port)
self._UpdateProperty()
elif idx >= len(self) or idx < 0:
raise IndexError
else:
self.SMProperty.SetInputConnection(idx, value.SMProxy, value.Port)
self._UpdateProperty() | [
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||
aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/mailbox.py | python | Mailbox.__init__ | (self, path, factory=None, create=True) | Initialize a Mailbox instance. | Initialize a Mailbox instance. | [
"Initialize",
"a",
"Mailbox",
"instance",
"."
] | def __init__(self, path, factory=None, create=True):
"""Initialize a Mailbox instance."""
self._path = os.path.abspath(os.path.expanduser(path))
self._factory = factory | [
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||
wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_cocoa/dataview.py | python | DataViewEvent.SetCache | (*args, **kwargs) | return _dataview.DataViewEvent_SetCache(*args, **kwargs) | SetCache(self, int from, int to) | SetCache(self, int from, int to) | [
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] | def SetCache(*args, **kwargs):
"""SetCache(self, int from, int to)"""
return _dataview.DataViewEvent_SetCache(*args, **kwargs) | [
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|
SpenceKonde/megaTinyCore | 1c4a70b18a149fe6bcb551dfa6db11ca50b8997b | megaavr/tools/libs/serial/tools/list_ports_common.py | python | list_links | (devices) | return links | \
search all /dev devices and look for symlinks to known ports already
listed in devices. | \
search all /dev devices and look for symlinks to known ports already
listed in devices. | [
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] | def list_links(devices):
"""\
search all /dev devices and look for symlinks to known ports already
listed in devices.
"""
links = []
for device in glob.glob('/dev/*'):
if os.path.islink(device) and os.path.realpath(device) in devices:
links.append(device)
return links | [
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|
hughperkins/tf-coriander | 970d3df6c11400ad68405f22b0c42a52374e94ca | tensorflow/python/summary/event_accumulator.py | python | EventAccumulator.Histograms | (self, tag) | return self._histograms.Items(tag) | Given a summary tag, return all associated histograms.
Args:
tag: A string tag associated with the events.
Raises:
KeyError: If the tag is not found.
Returns:
An array of `HistogramEvent`s. | Given a summary tag, return all associated histograms. | [
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] | def Histograms(self, tag):
"""Given a summary tag, return all associated histograms.
Args:
tag: A string tag associated with the events.
Raises:
KeyError: If the tag is not found.
Returns:
An array of `HistogramEvent`s.
"""
return self._histograms.Items(tag) | [
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|
FreeCAD/FreeCAD | ba42231b9c6889b89e064d6d563448ed81e376ec | src/Mod/Draft/draftfunctions/move.py | python | move_vertex | (object, vertex_index, vector) | Needed for SubObjects modifiers.
Implemented by Dion Moult during 0.19 dev cycle (works only with Draft Wire). | Needed for SubObjects modifiers.
Implemented by Dion Moult during 0.19 dev cycle (works only with Draft Wire). | [
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] | def move_vertex(object, vertex_index, vector):
"""
Needed for SubObjects modifiers.
Implemented by Dion Moult during 0.19 dev cycle (works only with Draft Wire).
"""
points = object.Points
points[vertex_index] = points[vertex_index].add(vector)
object.Points = points | [
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||
baidu-research/tensorflow-allreduce | 66d5b855e90b0949e9fa5cca5599fd729a70e874 | tensorflow/python/profiler/pprof_profiler.py | python | Samples.add | (self, datum, location_ids) | Adds a sample data point.
Args:
datum: `ProfileDatum` to add a sample for.
location_ids: List of numberic location ids for this
sample. | Adds a sample data point. | [
"Adds",
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"sample",
"data",
"point",
"."
] | def add(self, datum, location_ids):
"""Adds a sample data point.
Args:
datum: `ProfileDatum` to add a sample for.
location_ids: List of numberic location ids for this
sample.
"""
node_name = datum.node_exec_stats.node_name
if node_name in self._node_name_to_sample:
sample = self._node_name_to_sample[node_name]
sample.location_id.extend(location_ids)
else:
sample = profile_pb2.Sample()
# Sample stores 3 values: count, all_time, op_time
sample.value.extend([0, 0, 0])
label = sample.label.add()
label.key = self._string_table.index_of('node_name')
label.str = self._string_table.index_of(node_name)
label = sample.label.add()
label.key = self._string_table.index_of('op_type')
label.str = self._string_table.index_of(datum.op_type)
self._node_name_to_sample[node_name] = sample
sample.value[0] += 1
sample.value[1] += datum.node_exec_stats.all_end_rel_micros
sample.value[2] += (
datum.node_exec_stats.op_end_rel_micros -
datum.node_exec_stats.op_start_rel_micros) | [
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||
klzgrad/naiveproxy | ed2c513637c77b18721fe428d7ed395b4d284c83 | src/build/android/pylib/results/flakiness_dashboard/json_results_generator.py | python | ConvertTrieToFlatPaths | (trie, prefix=None) | return result | Flattens the trie of paths, prepending a prefix to each. | Flattens the trie of paths, prepending a prefix to each. | [
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"to",
"each",
"."
] | def ConvertTrieToFlatPaths(trie, prefix=None):
"""Flattens the trie of paths, prepending a prefix to each."""
result = {}
for name, data in trie.items():
if prefix:
name = prefix + '/' + name
if len(data) != 0 and not 'results' in data:
result.update(ConvertTrieToFlatPaths(data, name))
else:
result[name] = data
return result | [
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|
wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | wx/lib/agw/customtreectrl.py | python | GenericTreeItem.GetCurrentCheckedImage | (self) | Returns the current item check image.
:return: An integer index that can be used to retrieve the item check image inside
a :class:`ImageList`. | Returns the current item check image. | [
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] | def GetCurrentCheckedImage(self):
"""
Returns the current item check image.
:return: An integer index that can be used to retrieve the item check image inside
a :class:`ImageList`.
"""
if self._type == 0:
return None
checked = self.IsChecked()
if checked > 0:
if self._type == 1: # Checkbox
if checked == wx.CHK_CHECKED:
return self._checkedimages[TreeItemIcon_Checked]
else:
return self._checkedimages[TreeItemIcon_Undetermined]
else: # Radiobutton
return self._checkedimages[TreeItemIcon_Flagged]
else:
if self._type == 1: # Checkbox
return self._checkedimages[TreeItemIcon_NotChecked]
else: # Radiobutton
return self._checkedimages[TreeItemIcon_NotFlagged] | [
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||
Dovyski/cvui | d1b40267bdee34fcc193a375911415222f1409b3 | cvui.py | python | printf | (theWhere, theX, theY, theFontScale, theColor, theFmt) | Display a piece of text that can be formated using `C stdio's printf()` style. For instance
if you want to display text mixed with numbers, you can use:
```
printf(frame, 10, 15, 0.4, 0xff0000, 'Text: %d and %f', 7, 3.1415)
```
Parameters
----------
theWhere: np.ndarray
image/frame where the component should be rendered.
theX: int
position X where the component should be placed.
theY: int
position Y where the component should be placed.
theFontScale: float
size of the text.
theColor: uint
color of the text in the format `0xRRGGBB`, e.g. `0xff0000` for red.
theFmt: str
formating string as it would be supplied for `stdio's printf()`, e.g. `'Text: %d and %f', 7, 3.1415`.
See Also
----------
text() | Display a piece of text that can be formated using `C stdio's printf()` style. For instance
if you want to display text mixed with numbers, you can use: | [
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] | def printf(theWhere, theX, theY, theFontScale, theColor, theFmt):
"""
Display a piece of text that can be formated using `C stdio's printf()` style. For instance
if you want to display text mixed with numbers, you can use:
```
printf(frame, 10, 15, 0.4, 0xff0000, 'Text: %d and %f', 7, 3.1415)
```
Parameters
----------
theWhere: np.ndarray
image/frame where the component should be rendered.
theX: int
position X where the component should be placed.
theY: int
position Y where the component should be placed.
theFontScale: float
size of the text.
theColor: uint
color of the text in the format `0xRRGGBB`, e.g. `0xff0000` for red.
theFmt: str
formating string as it would be supplied for `stdio's printf()`, e.g. `'Text: %d and %f', 7, 3.1415`.
See Also
----------
text()
"""
print('This is wrapper function to help code autocompletion.') | [
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crosslife/OpenBird | 9e0198a1a2295f03fa1e8676e216e22c9c7d380b | cocos2d/tools/bindings-generator/backup/clang-llvm-3.3-pybinding/cindex.py | python | Cursor.objc_type_encoding | (self) | return self._objc_type_encoding | Return the Objective-C type encoding as a str. | Return the Objective-C type encoding as a str. | [
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if not hasattr(self, '_objc_type_encoding'):
self._objc_type_encoding = \
conf.lib.clang_getDeclObjCTypeEncoding(self)
return self._objc_type_encoding | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/AWSPythonSDK/1.5.8/boto3/resources/response.py | python | build_empty_response | (search_path, operation_name, service_model) | return response | Creates an appropriate empty response for the type that is expected,
based on the service model's shape type. For example, a value that
is normally a list would then return an empty list. A structure would
return an empty dict, and a number would return None.
:type search_path: string
:param search_path: JMESPath expression to search in the response
:type operation_name: string
:param operation_name: Name of the underlying service operation.
:type service_model: :ref:`botocore.model.ServiceModel`
:param service_model: The Botocore service model
:rtype: dict, list, or None
:return: An appropriate empty value | Creates an appropriate empty response for the type that is expected,
based on the service model's shape type. For example, a value that
is normally a list would then return an empty list. A structure would
return an empty dict, and a number would return None. | [
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based on the service model's shape type. For example, a value that
is normally a list would then return an empty list. A structure would
return an empty dict, and a number would return None.
:type search_path: string
:param search_path: JMESPath expression to search in the response
:type operation_name: string
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:type service_model: :ref:`botocore.model.ServiceModel`
:param service_model: The Botocore service model
:rtype: dict, list, or None
:return: An appropriate empty value
"""
response = None
operation_model = service_model.operation_model(operation_name)
shape = operation_model.output_shape
if search_path:
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# a path of ``foo.bar[0].baz``, we first find the shape for ``foo``,
# then the shape for ``bar`` (ignoring the indexing), and finally
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if shape.type_name == 'structure':
shape = shape.members[item]
elif shape.type_name == 'list':
shape = shape.member
else:
raise NotImplementedError(
'Search path hits shape type {0} from {1}'.format(
shape.type_name, item))
# Anything not handled here is set to None
if shape.type_name == 'structure':
response = {}
elif shape.type_name == 'list':
response = []
elif shape.type_name == 'map':
response = {}
return response | [
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|
aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/AWSPythonSDK/1.5.8/botocore/credentials.py | python | CredentialResolver.remove | (self, name) | Removes a given ``Credentials`` instance from the chain.
:param name: The short name of the credentials instance to remove.
:type name: string | Removes a given ``Credentials`` instance from the chain. | [
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] | def remove(self, name):
"""
Removes a given ``Credentials`` instance from the chain.
:param name: The short name of the credentials instance to remove.
:type name: string
"""
available_methods = [p.METHOD for p in self.providers]
if name not in available_methods:
# It's not present. Fail silently.
return
offset = available_methods.index(name)
self.providers.pop(offset) | [
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lawy623/SVS | b7c7ae367c82a4797ff4a896a2ff304f02e7f724 | caffe/python/caffe/coord_map.py | python | inverse | (coord_map) | return ax, 1 / a, -b / a | Invert a coord map by de-scaling and un-shifting;
this gives the backward mapping for the gradient. | Invert a coord map by de-scaling and un-shifting;
this gives the backward mapping for the gradient. | [
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] | def inverse(coord_map):
"""
Invert a coord map by de-scaling and un-shifting;
this gives the backward mapping for the gradient.
"""
ax, a, b = coord_map
return ax, 1 / a, -b / a | [
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|
lammps/lammps | b75c3065430a75b1b5543a10e10f46d9b4c91913 | tools/i-pi/ipi/utils/inputvalue.py | python | Input.fetch | (self) | Dummy function to retrieve data. | Dummy function to retrieve data. | [
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||
NERSC/timemory | 431912b360ff50d1a160d7826e2eea04fbd1037f | scripts/gprof2dot.py | python | Profile.validate | (self) | Validate the edges. | Validate the edges. | [
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] | def validate(self):
"""Validate the edges."""
for function in compat_itervalues(self.functions):
for callee_id in compat_keys(function.calls):
assert function.calls[callee_id].callee_id == callee_id
if callee_id not in self.functions:
sys.stderr.write('warning: call to undefined function %s from function %s\n' % (str(callee_id), function.name))
del function.calls[callee_id] | [
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||
aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/windows/Lib/_pyio.py | python | IOBase._unsupported | (self, name) | Internal: raise an OSError exception for unsupported operations. | Internal: raise an OSError exception for unsupported operations. | [
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] | def _unsupported(self, name):
"""Internal: raise an OSError exception for unsupported operations."""
raise UnsupportedOperation("%s.%s() not supported" %
(self.__class__.__name__, name)) | [
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||
pmq20/node-packer | 12c46c6e44fbc14d9ee645ebd17d5296b324f7e0 | lts/deps/v8/third_party/jinja2/sandbox.py | python | SandboxedEnvironment.unsafe_undefined | (self, obj, attribute) | return self.undefined('access to attribute %r of %r '
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attribute,
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return self.undefined('access to attribute %r of %r '
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attribute,
obj.__class__.__name__
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|
catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/tools/python3/src/Lib/numbers.py | python | Complex.real | (self) | Retrieve the real component of this number.
This should subclass Real. | Retrieve the real component of this number. | [
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"""Retrieve the real component of this number.
This should subclass Real.
"""
raise NotImplementedError | [
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||
mantidproject/mantid | 03deeb89254ec4289edb8771e0188c2090a02f32 | scripts/SANS/sans/algorithm_detail/mask_workspace.py | python | mask_with_mask_files | (mask_info, inst_info, workspace) | return workspace | Apply mask files to the workspace
Rolling our own MaskDetectors wrapper since masking is broken in a couple
of places that affect us here.
Calling MaskDetectors(Workspace=ws_name, MaskedWorkspace=mask_ws_name) is
not something we can do because the algorithm masks by ws index rather than
detector id, and unfortunately for SANS the detector table is not the same
for MaskingWorkspaces as it is for the workspaces containing the data to be
masked. Basically, we get a mirror image of what we expect. Instead, we
have to extract the det IDs and use those via the DetectorList property.
:param mask_info: a SANSStateMask object.
:param workspace: the workspace to be masked.
:return: the masked workspace. | Apply mask files to the workspace | [
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"to",
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"workspace"
] | def mask_with_mask_files(mask_info, inst_info, workspace):
"""
Apply mask files to the workspace
Rolling our own MaskDetectors wrapper since masking is broken in a couple
of places that affect us here.
Calling MaskDetectors(Workspace=ws_name, MaskedWorkspace=mask_ws_name) is
not something we can do because the algorithm masks by ws index rather than
detector id, and unfortunately for SANS the detector table is not the same
for MaskingWorkspaces as it is for the workspaces containing the data to be
masked. Basically, we get a mirror image of what we expect. Instead, we
have to extract the det IDs and use those via the DetectorList property.
:param mask_info: a SANSStateMask object.
:param workspace: the workspace to be masked.
:return: the masked workspace.
"""
mask_files = mask_info.mask_files
if mask_files:
idf_path = inst_info.idf_path
# Mask loader
load_name = "LoadMask"
load_options = {"Instrument": idf_path,
"OutputWorkspace": EMPTY_NAME}
load_alg = create_unmanaged_algorithm(load_name, **load_options)
mask_alg = create_unmanaged_algorithm("MaskDetectors")
file_paths = [find_full_file_path(i) for i in mask_files]
# Find full file path returns an empty string, so we need to remake it
missing_file_paths = [mask_files[i] for i, path in enumerate(file_paths) if not path]
if missing_file_paths:
err_str = "The following mask files are missing:"
err_str += "\n".join(missing_file_paths)
raise FileNotFoundError(err_str)
# Masker
for mask_file in file_paths:
# Get the detector ids which need to be masked
load_alg.setProperty("InputFile", mask_file)
load_alg.execute()
masking_workspace = load_alg.getProperty("OutputWorkspace").value
# Could use MaskDetectors directly with masking_workspace but it does not
# support MPI. Use a two step approach via a and b instead.
# a) Extract detectors to mask from MaskWorkspace
det_ids = masking_workspace.getMaskedDetectors()
# b) Mask the detector ids on the instrument
mask_alg.setProperty("Workspace", workspace)
mask_alg.setProperty("DetectorList", det_ids)
mask_alg.execute()
workspace = mask_alg.getProperty("Workspace").value
return workspace | [
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|
apache/trafodion | 8455c839ad6b6d7b6e04edda5715053095b78046 | core/sqf/src/seatrans/hbase-trx/src/main/python/thrift1/gen-py/hbase/Hbase.py | python | Iface.enableTable | (self, tableName) | Brings a table on-line (enables it)
Parameters:
- tableName: name of the table | Brings a table on-line (enables it) | [
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] | def enableTable(self, tableName):
"""
Brings a table on-line (enables it)
Parameters:
- tableName: name of the table
"""
pass | [
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||
wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | demo/snippets/ellipse.py | python | path_ellipse | (cr, x, y, width, height, angle=0) | x - center x
y - center y
width - width of ellipse (in x direction when angle=0)
height - height of ellipse (in y direction when angle=0)
angle - angle in radians to rotate, clockwise | x - center x
y - center y
width - width of ellipse (in x direction when angle=0)
height - height of ellipse (in y direction when angle=0)
angle - angle in radians to rotate, clockwise | [
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] | def path_ellipse(cr, x, y, width, height, angle=0):
"""
x - center x
y - center y
width - width of ellipse (in x direction when angle=0)
height - height of ellipse (in y direction when angle=0)
angle - angle in radians to rotate, clockwise
"""
cr.save()
cr.translate(x, y)
cr.rotate(angle)
cr.scale(width / 2.0, height / 2.0)
cr.arc(0.0, 0.0, 1.0, 0.0, 2.0 * M_PI)
cr.restore() | [
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||
weolar/miniblink49 | 1c4678db0594a4abde23d3ebbcc7cd13c3170777 | third_party/WebKit/Tools/Scripts/webkitpy/thirdparty/BeautifulSoup.py | python | PageElement.findPreviousSiblings | (self, name=None, attrs={}, text=None,
limit=None, **kwargs) | return self._findAll(name, attrs, text, limit,
self.previousSiblingGenerator, **kwargs) | Returns the siblings of this Tag that match the given
criteria and appear before this Tag in the document. | Returns the siblings of this Tag that match the given
criteria and appear before this Tag in the document. | [
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limit=None, **kwargs):
"""Returns the siblings of this Tag that match the given
criteria and appear before this Tag in the document."""
return self._findAll(name, attrs, text, limit,
self.previousSiblingGenerator, **kwargs) | [
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|
windystrife/UnrealEngine_NVIDIAGameWorks | b50e6338a7c5b26374d66306ebc7807541ff815e | Engine/Extras/ThirdPartyNotUE/emsdk/Win64/python/2.7.5.3_64bit/Lib/site-packages/win32com/client/gencache.py | python | GetClassForCLSID | (clsid) | Get a Python class for a CLSID
Given a CLSID, return a Python class which wraps the COM object
Returns the Python class, or None if no module is available.
Params
clsid -- A COM CLSID (or string repr of one) | Get a Python class for a CLSID
Given a CLSID, return a Python class which wraps the COM object
Returns the Python class, or None if no module is available.
Params
clsid -- A COM CLSID (or string repr of one) | [
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"""Get a Python class for a CLSID
Given a CLSID, return a Python class which wraps the COM object
Returns the Python class, or None if no module is available.
Params
clsid -- A COM CLSID (or string repr of one)
"""
# first, take a short-cut - we may already have generated support ready-to-roll.
clsid = str(clsid)
if CLSIDToClass.HasClass(clsid):
return CLSIDToClass.GetClass(clsid)
mod = GetModuleForCLSID(clsid)
if mod is None:
return None
try:
return CLSIDToClass.GetClass(clsid)
except KeyError:
return None | [
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||
Tencent/CMONGO | c40380caa14e05509f46993aa8b8da966b09b0b5 | src/third_party/scons-2.5.0/scons-local-2.5.0/SCons/Tool/cvf.py | python | generate | (env) | Add Builders and construction variables for compaq visual fortran to an Environment. | Add Builders and construction variables for compaq visual fortran to an Environment. | [
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] | def generate(env):
"""Add Builders and construction variables for compaq visual fortran to an Environment."""
fortran.generate(env)
env['FORTRAN'] = 'f90'
env['FORTRANCOM'] = '$FORTRAN $FORTRANFLAGS $_FORTRANMODFLAG $_FORTRANINCFLAGS /compile_only ${SOURCES.windows} /object:${TARGET.windows}'
env['FORTRANPPCOM'] = '$FORTRAN $FORTRANFLAGS $CPPFLAGS $_CPPDEFFLAGS $_FORTRANMODFLAG $_FORTRANINCFLAGS /compile_only ${SOURCES.windows} /object:${TARGET.windows}'
env['SHFORTRANCOM'] = '$SHFORTRAN $SHFORTRANFLAGS $_FORTRANMODFLAG $_FORTRANINCFLAGS /compile_only ${SOURCES.windows} /object:${TARGET.windows}'
env['SHFORTRANPPCOM'] = '$SHFORTRAN $SHFORTRANFLAGS $CPPFLAGS $_CPPDEFFLAGS $_FORTRANMODFLAG $_FORTRANINCFLAGS /compile_only ${SOURCES.windows} /object:${TARGET.windows}'
env['OBJSUFFIX'] = '.obj'
env['FORTRANMODDIR'] = '${TARGET.dir}'
env['FORTRANMODDIRPREFIX'] = '/module:'
env['FORTRANMODDIRSUFFIX'] = '' | [
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||
krishauser/Klampt | 972cc83ea5befac3f653c1ba20f80155768ad519 | Python/python2_version/klampt/math/optimize.py | python | OptimizationProblem.addSymbolicConstraint | (self,func,context,varorder=None,blackbox=False) | adds a constraint from a symbolic Function or Expression
(see symbolic module). This will be "smart" in that AND Expressions will be
converted to multiple constraints, inequalities will be converted to inequality
constraints, and bounds will be converted to bound constraints. All other
constraints will be treated as feasibility constraints | adds a constraint from a symbolic Function or Expression
(see symbolic module). This will be "smart" in that AND Expressions will be
converted to multiple constraints, inequalities will be converted to inequality
constraints, and bounds will be converted to bound constraints. All other
constraints will be treated as feasibility constraints | [
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"""adds a constraint from a symbolic Function or Expression
(see symbolic module). This will be "smart" in that AND Expressions will be
converted to multiple constraints, inequalities will be converted to inequality
constraints, and bounds will be converted to bound constraints. All other
constraints will be treated as feasibility constraints"""
if varorder is None: varorder = context.variables
if symbolic.is_op(func,"and"):
for a in func.args:
self.addSymbolicConstraint(self,a,context,varorder)
elif symbolic.is_op(func,"le"):
if symbolic.is_var(func.args[0]) and symbolic.is_const(func.args[1]):
#x <= c
x = symbolic.to_var(func.args[0])
xmax = symbolic.to_const(func.args[1])
indices = context.getFlatVarRanges(varorder)
xindex = [i for i,v in enumerate(varorder) if v.name == x.name][0]
ai,bi = indices[xindex],indices[xindex+1]
n = indices[-1]
if self.bounds is None:
self.bounds = (np.array([-float('inf')]*n),np.array([float('inf')]*n))
self.bounds[1][ai:bi] = np.minimum(self.bounds[1][ai:bi],xmax)
elif symbolic.is_var(func.args[1]) and symbolic.is_const(func.args[0]):
#c <= x
xmin = symbolic.to_const(func.args[0])
x = symbolic.to_var(func.args[1])
indices = context.getFlatVarRanges(varorder)
xindex = [i for i,v in enumerate(varorder) if v.name == x.name][0]
ai,bi = indices[xindex],indices[xindex+1]
n = indices[-1]
if self.bounds is None:
self.bounds = (np.array([-float('inf')]*n),np.array([float('inf')]*n))
self.bounds[0][ai:bi] = np.maximum(self.bounds[0][ai:bi],a)
else:
h = symbolic.simplify(func.args[0]-func.args[1])
if func.args[0].returnType().is_scalar() and func.args[1].returnType().is_scalar():
#need to convert to a vector
h = symbolic.flatten(h)
hpy,varorder = context.makeFlatFunction(h,varorder)
dhpy,varorder = context.makeFlatFunctionDeriv(h,varorder)
self.addInequality(hpy,dhpy)
elif symbolic.is_op(func,"ge"):
c = (func.args[1] <= func.args[0])
self.addSymbolicConstraint(c,context,varorder)
elif symbolic.is_op(func,"eq"):
g = symbolic.simplify(func.args[0]-func.args[1])
if func.args[0].returnType().is_scalar() and func.args[1].returnType().is_scalar():
#need to convert to a vector
g = symbolic.flatten(g)
gpy,varorder = context.makeFlatFunction(g,varorder)
dgpy,varorder = context.makeFlatFunctionDeriv(g,varorder)
self.addEquality(gpy,dgpy)
elif symbolic.is_op(func):
if func.functionInfo is symbolic_linalg.bound_contains and symbolic.is_const(func.args[0]) and symbolic.is_const(func.args[1]) and symbolic.is_var(func.args[2]):
#bound constraint
xmin = symbolic.to_const(func.args[0])
xmax = symbolic.to_const(func.args[1])
x = symbolic.to_var(func.args[2])
indices = context.getFlatVarRanges(varorder)
xindex = [i for i,v in enumerate(varorder) if v.name == x.name][0]
ai,bi = indices[xindex],indices[xindex+1]
n = indices[-1]
if self.bounds is None:
self.bounds = ([-float('inf')]*n,[float('inf')]*n)
for i,a,b in zip(range(ai,bi),xmin,xmax):
self.bounds[0][i] = max(self.bounds[0][i],a)
self.bounds[1][i] = min(self.bounds[1][i],b)
else:
#it's a generic boolean
if not blackbox:
print "OptimizationProblem.addSymbolicConstraint(): Warning, turning function",func,"into black box function"
fpy,varorder = context.makeFlatFunction(func,varorder)
self.addFeasibilityTest(fpy)
else:
#it's a generic boolean
if not blackbox:
print "OptimizationProblem.addSymbolicConstraint(): Warning, turning function",func,"into black box function"
fpy,varorder = context.makeFlatFunction(func,varorder)
self.addFeasibilityTest(fpy) | [
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||
mongodb/mongo | d8ff665343ad29cf286ee2cf4a1960d29371937b | buildscripts/packager.py | python | unpack_binaries_into | (build_os, arch, spec, where) | Unpack the tarfile for (build_os, arch, spec) into directory where. | Unpack the tarfile for (build_os, arch, spec) into directory where. | [
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"""Unpack the tarfile for (build_os, arch, spec) into directory where."""
rootdir = os.getcwd()
ensure_dir(where)
# Note: POSIX tar doesn't require support for gtar's "-C" option,
# and Python's tarfile module prior to Python 2.7 doesn't have the
# features to make this detail easy. So we'll just do the dumb
# thing and chdir into where and run tar there.
os.chdir(where)
try:
sysassert(["tar", "xvzf", rootdir + "/" + tarfile(build_os, arch, spec)])
release_dir = glob('mongodb-linux-*')[0]
for releasefile in "bin", "LICENSE-Community.txt", "README", "THIRD-PARTY-NOTICES", "MPL-2":
print("moving file: %s/%s" % (release_dir, releasefile))
os.rename("%s/%s" % (release_dir, releasefile), releasefile)
os.rmdir(release_dir)
except Exception:
exc = sys.exc_info()[1]
os.chdir(rootdir)
raise exc
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||
openmm/openmm | cb293447c4fc8b03976dfe11399f107bab70f3d9 | wrappers/python/openmm/app/internal/charmm/topologyobjects.py | python | Residue.__contains__ | (self, thing) | return thing in self.atoms | True if an atom is present in this residue | True if an atom is present in this residue | [
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""" True if an atom is present in this residue """
return thing in self.atoms | [
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|
hanpfei/chromium-net | 392cc1fa3a8f92f42e4071ab6e674d8e0482f83f | third_party/catapult/third_party/gsutil/third_party/boto/boto/sns/connection.py | python | SNSConnection.subscribe | (self, topic, protocol, endpoint) | return self._make_request('Subscribe', params) | Subscribe to a Topic.
:type topic: string
:param topic: The ARN of the new topic.
:type protocol: string
:param protocol: The protocol used to communicate with
the subscriber. Current choices are:
email|email-json|http|https|sqs|sms|application
:type endpoint: string
:param endpoint: The location of the endpoint for
the subscriber.
* For email, this would be a valid email address
* For email-json, this would be a valid email address
* For http, this would be a URL beginning with http
* For https, this would be a URL beginning with https
* For sqs, this would be the ARN of an SQS Queue
* For sms, this would be a phone number of an
SMS-enabled device
* For application, the endpoint is the EndpointArn
of a mobile app and device. | Subscribe to a Topic. | [
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"a",
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] | def subscribe(self, topic, protocol, endpoint):
"""
Subscribe to a Topic.
:type topic: string
:param topic: The ARN of the new topic.
:type protocol: string
:param protocol: The protocol used to communicate with
the subscriber. Current choices are:
email|email-json|http|https|sqs|sms|application
:type endpoint: string
:param endpoint: The location of the endpoint for
the subscriber.
* For email, this would be a valid email address
* For email-json, this would be a valid email address
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* For sms, this would be a phone number of an
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params = {'TopicArn': topic,
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|
natanielruiz/android-yolo | 1ebb54f96a67a20ff83ddfc823ed83a13dc3a47f | jni-build/jni/include/tensorflow/contrib/layers/python/layers/utils.py | python | collect_named_outputs | (collections, name, outputs) | return outputs | Add `Tensor` outputs tagged with name to collections.
It is useful to collect end-points or tags for summaries. Example of usage:
logits = collect_named_outputs('end_points', 'inception_v3/logits', logits)
assert logits.tag == 'inception_v3/logits'
Args:
collections: A collection or list of collections. If None skip collection.
name: String, name to represent the outputs, ex. 'inception_v3/conv1'
outputs: Tensor, an output tensor to collect
Returns:
The outputs Tensor to allow inline call. | Add `Tensor` outputs tagged with name to collections. | [
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] | def collect_named_outputs(collections, name, outputs):
"""Add `Tensor` outputs tagged with name to collections.
It is useful to collect end-points or tags for summaries. Example of usage:
logits = collect_named_outputs('end_points', 'inception_v3/logits', logits)
assert logits.tag == 'inception_v3/logits'
Args:
collections: A collection or list of collections. If None skip collection.
name: String, name to represent the outputs, ex. 'inception_v3/conv1'
outputs: Tensor, an output tensor to collect
Returns:
The outputs Tensor to allow inline call.
"""
# Remove ending '/' if present.
if name[-1] == '/':
name = name[:-1]
if collections:
ops.add_to_collections(collections, NamedOutputs(name, outputs))
return outputs | [
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|
geemaple/leetcode | 68bc5032e1ee52c22ef2f2e608053484c487af54 | leetcode/203.remove-linked-list-elements.py | python | Solution.removeElements | (self, head, val) | return new_head.next | :type head: ListNode
:type val: int
:rtype: ListNode | :type head: ListNode
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"""
:type head: ListNode
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:rtype: ListNode
"""
new_head = ListNode(0)
new_head.next = head
cur = new_head
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|
google/syzygy | 8164b24ebde9c5649c9a09e88a7fc0b0fcbd1bc5 | third_party/numpy/files/numpy/lib/function_base.py | python | bartlett | (M) | return where(less_equal(n,(M-1)/2.0),2.0*n/(M-1),2.0-2.0*n/(M-1)) | Return the Bartlett window.
The Bartlett window is very similar to a triangular window, except
that the end points are at zero. It is often used in signal
processing for tapering a signal, without generating too much
ripple in the frequency domain.
Parameters
----------
M : int
Number of points in the output window. If zero or less, an
empty array is returned.
Returns
-------
out : array
The triangular window, normalized to one (the value one
appears only if the number of samples is odd), with the first
and last samples equal to zero.
See Also
--------
blackman, hamming, hanning, kaiser
Notes
-----
The Bartlett window is defined as
.. math:: w(n) = \\frac{2}{M-1} \\left(
\\frac{M-1}{2} - \\left|n - \\frac{M-1}{2}\\right|
\\right)
Most references to the Bartlett window come from the signal
processing literature, where it is used as one of many windowing
functions for smoothing values. Note that convolution with this
window produces linear interpolation. It is also known as an
apodization (which means"removing the foot", i.e. smoothing
discontinuities at the beginning and end of the sampled signal) or
tapering function. The fourier transform of the Bartlett is the product
of two sinc functions.
Note the excellent discussion in Kanasewich.
References
----------
.. [1] M.S. Bartlett, "Periodogram Analysis and Continuous Spectra",
Biometrika 37, 1-16, 1950.
.. [2] E.R. Kanasewich, "Time Sequence Analysis in Geophysics",
The University of Alberta Press, 1975, pp. 109-110.
.. [3] A.V. Oppenheim and R.W. Schafer, "Discrete-Time Signal
Processing", Prentice-Hall, 1999, pp. 468-471.
.. [4] Wikipedia, "Window function",
http://en.wikipedia.org/wiki/Window_function
.. [5] W.H. Press, B.P. Flannery, S.A. Teukolsky, and W.T. Vetterling,
"Numerical Recipes", Cambridge University Press, 1986, page 429.
Examples
--------
>>> np.bartlett(12)
array([ 0. , 0.18181818, 0.36363636, 0.54545455, 0.72727273,
0.90909091, 0.90909091, 0.72727273, 0.54545455, 0.36363636,
0.18181818, 0. ])
Plot the window and its frequency response (requires SciPy and matplotlib):
>>> from numpy import clip, log10, array, bartlett, linspace
>>> from numpy.fft import fft, fftshift
>>> import matplotlib.pyplot as plt
>>> window = bartlett(51)
>>> plt.plot(window)
[<matplotlib.lines.Line2D object at 0x...>]
>>> plt.title("Bartlett window")
<matplotlib.text.Text object at 0x...>
>>> plt.ylabel("Amplitude")
<matplotlib.text.Text object at 0x...>
>>> plt.xlabel("Sample")
<matplotlib.text.Text object at 0x...>
>>> plt.show()
>>> plt.figure()
<matplotlib.figure.Figure object at 0x...>
>>> A = fft(window, 2048) / 25.5
>>> mag = abs(fftshift(A))
>>> freq = linspace(-0.5,0.5,len(A))
>>> response = 20*log10(mag)
>>> response = clip(response,-100,100)
>>> plt.plot(freq, response)
[<matplotlib.lines.Line2D object at 0x...>]
>>> plt.title("Frequency response of Bartlett window")
<matplotlib.text.Text object at 0x...>
>>> plt.ylabel("Magnitude [dB]")
<matplotlib.text.Text object at 0x...>
>>> plt.xlabel("Normalized frequency [cycles per sample]")
<matplotlib.text.Text object at 0x...>
>>> plt.axis('tight')
(-0.5, 0.5, -100.0, ...)
>>> plt.show() | Return the Bartlett window. | [
"Return",
"the",
"Bartlett",
"window",
"."
] | def bartlett(M):
"""
Return the Bartlett window.
The Bartlett window is very similar to a triangular window, except
that the end points are at zero. It is often used in signal
processing for tapering a signal, without generating too much
ripple in the frequency domain.
Parameters
----------
M : int
Number of points in the output window. If zero or less, an
empty array is returned.
Returns
-------
out : array
The triangular window, normalized to one (the value one
appears only if the number of samples is odd), with the first
and last samples equal to zero.
See Also
--------
blackman, hamming, hanning, kaiser
Notes
-----
The Bartlett window is defined as
.. math:: w(n) = \\frac{2}{M-1} \\left(
\\frac{M-1}{2} - \\left|n - \\frac{M-1}{2}\\right|
\\right)
Most references to the Bartlett window come from the signal
processing literature, where it is used as one of many windowing
functions for smoothing values. Note that convolution with this
window produces linear interpolation. It is also known as an
apodization (which means"removing the foot", i.e. smoothing
discontinuities at the beginning and end of the sampled signal) or
tapering function. The fourier transform of the Bartlett is the product
of two sinc functions.
Note the excellent discussion in Kanasewich.
References
----------
.. [1] M.S. Bartlett, "Periodogram Analysis and Continuous Spectra",
Biometrika 37, 1-16, 1950.
.. [2] E.R. Kanasewich, "Time Sequence Analysis in Geophysics",
The University of Alberta Press, 1975, pp. 109-110.
.. [3] A.V. Oppenheim and R.W. Schafer, "Discrete-Time Signal
Processing", Prentice-Hall, 1999, pp. 468-471.
.. [4] Wikipedia, "Window function",
http://en.wikipedia.org/wiki/Window_function
.. [5] W.H. Press, B.P. Flannery, S.A. Teukolsky, and W.T. Vetterling,
"Numerical Recipes", Cambridge University Press, 1986, page 429.
Examples
--------
>>> np.bartlett(12)
array([ 0. , 0.18181818, 0.36363636, 0.54545455, 0.72727273,
0.90909091, 0.90909091, 0.72727273, 0.54545455, 0.36363636,
0.18181818, 0. ])
Plot the window and its frequency response (requires SciPy and matplotlib):
>>> from numpy import clip, log10, array, bartlett, linspace
>>> from numpy.fft import fft, fftshift
>>> import matplotlib.pyplot as plt
>>> window = bartlett(51)
>>> plt.plot(window)
[<matplotlib.lines.Line2D object at 0x...>]
>>> plt.title("Bartlett window")
<matplotlib.text.Text object at 0x...>
>>> plt.ylabel("Amplitude")
<matplotlib.text.Text object at 0x...>
>>> plt.xlabel("Sample")
<matplotlib.text.Text object at 0x...>
>>> plt.show()
>>> plt.figure()
<matplotlib.figure.Figure object at 0x...>
>>> A = fft(window, 2048) / 25.5
>>> mag = abs(fftshift(A))
>>> freq = linspace(-0.5,0.5,len(A))
>>> response = 20*log10(mag)
>>> response = clip(response,-100,100)
>>> plt.plot(freq, response)
[<matplotlib.lines.Line2D object at 0x...>]
>>> plt.title("Frequency response of Bartlett window")
<matplotlib.text.Text object at 0x...>
>>> plt.ylabel("Magnitude [dB]")
<matplotlib.text.Text object at 0x...>
>>> plt.xlabel("Normalized frequency [cycles per sample]")
<matplotlib.text.Text object at 0x...>
>>> plt.axis('tight')
(-0.5, 0.5, -100.0, ...)
>>> plt.show()
"""
if M < 1:
return array([])
if M == 1:
return ones(1, float)
n = arange(0,M)
return where(less_equal(n,(M-1)/2.0),2.0*n/(M-1),2.0-2.0*n/(M-1)) | [
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|
floooh/oryol | eb08cffe1b1cb6b05ed14ec692bca9372cef064e | fips-files/generators/util/png.py | python | Reader.asDirect | (self) | return x,y,pixels,meta | Returns the image data as a direct representation of an
``x * y * planes`` array. This method is intended to remove the
need for callers to deal with palettes and transparency
themselves. Images with a palette (colour type 3)
are converted to RGB or RGBA; images with transparency (a
``tRNS`` chunk) are converted to LA or RGBA as appropriate.
When returned in this format the pixel values represent the
colour value directly without needing to refer to palettes or
transparency information.
Like the :meth:`read` method this method returns a 4-tuple:
(*width*, *height*, *pixels*, *meta*)
This method normally returns pixel values with the bit depth
they have in the source image, but when the source PNG has an
``sBIT`` chunk it is inspected and can reduce the bit depth of
the result pixels; pixel values will be reduced according to
the bit depth specified in the ``sBIT`` chunk (PNG nerds should
note a single result bit depth is used for all channels; the
maximum of the ones specified in the ``sBIT`` chunk. An RGB565
image will be rescaled to 6-bit RGB666).
The *meta* dictionary that is returned reflects the `direct`
format and not the original source image. For example, an RGB
source image with a ``tRNS`` chunk to represent a transparent
colour, will have ``planes=3`` and ``alpha=False`` for the
source image, but the *meta* dictionary returned by this method
will have ``planes=4`` and ``alpha=True`` because an alpha
channel is synthesized and added.
*pixels* is the pixel data in boxed row flat pixel format (just
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When returned in this format the pixel values represent the
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"""Returns the image data as a direct representation of an
``x * y * planes`` array. This method is intended to remove the
need for callers to deal with palettes and transparency
themselves. Images with a palette (colour type 3)
are converted to RGB or RGBA; images with transparency (a
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note a single result bit depth is used for all channels; the
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image will be rescaled to 6-bit RGB666).
The *meta* dictionary that is returned reflects the `direct`
format and not the original source image. For example, an RGB
source image with a ``tRNS`` chunk to represent a transparent
colour, will have ``planes=3`` and ``alpha=False`` for the
source image, but the *meta* dictionary returned by this method
will have ``planes=4`` and ``alpha=True`` because an alpha
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*pixels* is the pixel data in boxed row flat pixel format (just
like the :meth:`read` method).
All the other aspects of the image data are not changed.
"""
self.preamble()
# Simple case, no conversion necessary.
if not self.colormap and not self.trns and not self.sbit:
return self.read()
x,y,pixels,meta = self.read()
if self.colormap:
meta['colormap'] = False
meta['alpha'] = bool(self.trns)
meta['bitdepth'] = 8
meta['planes'] = 3 + bool(self.trns)
plte = self.palette()
def iterpal(pixels):
for row in pixels:
row = map(plte.__getitem__, row)
yield array('B', itertools.chain(*row))
pixels = iterpal(pixels)
elif self.trns:
# It would be nice if there was some reasonable way of doing
# this without generating a whole load of intermediate tuples.
# But tuples does seem like the easiest way, with no other way
# clearly much simpler or much faster. (Actually, the L to LA
# conversion could perhaps go faster (all those 1-tuples!), but
# I still wonder whether the code proliferation is worth it)
it = self.transparent
maxval = 2**meta['bitdepth']-1
planes = meta['planes']
meta['alpha'] = True
meta['planes'] += 1
typecode = 'BH'[meta['bitdepth']>8]
def itertrns(pixels):
for row in pixels:
# For each row we group it into pixels, then form a
# characterisation vector that says whether each pixel
# is opaque or not. Then we convert True/False to
# 0/maxval (by multiplication), and add it as the extra
# channel.
row = group(row, planes)
opa = map(it.__ne__, row)
opa = map(maxval.__mul__, opa)
opa = zip(opa) # convert to 1-tuples
yield array(typecode,
itertools.chain(*map(operator.add, row, opa)))
pixels = itertrns(pixels)
targetbitdepth = None
if self.sbit:
sbit = struct.unpack('%dB' % len(self.sbit), self.sbit)
targetbitdepth = max(sbit)
if targetbitdepth > meta['bitdepth']:
raise Error('sBIT chunk %r exceeds bitdepth %d' %
(sbit,self.bitdepth))
if min(sbit) <= 0:
raise Error('sBIT chunk %r has a 0-entry' % sbit)
if targetbitdepth == meta['bitdepth']:
targetbitdepth = None
if targetbitdepth:
shift = meta['bitdepth'] - targetbitdepth
meta['bitdepth'] = targetbitdepth
def itershift(pixels):
for row in pixels:
yield map(shift.__rrshift__, row)
pixels = itershift(pixels)
return x,y,pixels,meta | [
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|
aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/linux_x64/lib/python3.7/site-packages/pip/_vendor/distlib/_backport/tarfile.py | python | TarInfo.create_pax_header | (self, info, encoding) | return buf + self._create_header(info, USTAR_FORMAT, "ascii", "replace") | Return the object as a ustar header block. If it cannot be
represented this way, prepend a pax extended header sequence
with supplement information. | Return the object as a ustar header block. If it cannot be | [
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"""Return the object as a ustar header block. If it cannot be
represented this way, prepend a pax extended header sequence
with supplement information.
"""
info["magic"] = POSIX_MAGIC
pax_headers = self.pax_headers.copy()
# Test string fields for values that exceed the field length or cannot
# be represented in ASCII encoding.
for name, hname, length in (
("name", "path", LENGTH_NAME), ("linkname", "linkpath", LENGTH_LINK),
("uname", "uname", 32), ("gname", "gname", 32)):
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if len(info[name]) > length:
pax_headers[hname] = info[name]
# Test number fields for values that exceed the field limit or values
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# The pax header has priority. Avoid overflow.
info[name] = 0
continue
val = info[name]
if not 0 <= val < 8 ** (digits - 1) or isinstance(val, float):
pax_headers[name] = str(val)
info[name] = 0
# Create a pax extended header if necessary.
if pax_headers:
buf = self._create_pax_generic_header(pax_headers, XHDTYPE, encoding)
else:
buf = b""
return buf + self._create_header(info, USTAR_FORMAT, "ascii", "replace") | [
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|
Slicer/SlicerGitSVNArchive | 65e92bb16c2b32ea47a1a66bee71f238891ee1ca | Base/Python/slicer/release/midasdata.py | python | itemExists | (folderID, itemName, token, communicator) | return False | Check if an item exists in a folder based on its name
folderID -- ID of the folder.
itemName -- Name of the item to check for.
token -- Authentication token.
communicator -- Midas session communicator.
Returns a boolean indicating if the item exists or not. | Check if an item exists in a folder based on its name
folderID -- ID of the folder.
itemName -- Name of the item to check for.
token -- Authentication token.
communicator -- Midas session communicator.
Returns a boolean indicating if the item exists or not. | [
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folderID -- ID of the folder.
itemName -- Name of the item to check for.
token -- Authentication token.
communicator -- Midas session communicator.
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folderChildren = communicator.folder_children(token, folderID)
folder_children_items = folderChildren["items"]
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Caffe-MPI/Caffe-MPI.github.io | df5992af571a2a19981b69635115c393f18d1c76 | python/caffe/io.py | python | datum_to_array | (datum) | Converts a datum to an array. Note that the label is not returned,
as one can easily get it by calling datum.label. | Converts a datum to an array. Note that the label is not returned,
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"""Converts a datum to an array. Note that the label is not returned,
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"""
if len(datum.data):
return np.fromstring(datum.data, dtype=np.uint8).reshape(
datum.channels, datum.height, datum.width)
else:
return np.array(datum.float_data).astype(float).reshape(
datum.channels, datum.height, datum.width) | [
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||
ricardoquesada/Spidermonkey | 4a75ea2543408bd1b2c515aa95901523eeef7858 | addon-sdk/source/python-lib/simplejson/encoder.py | python | floatstr | (o, allow_nan=True) | return text | Check for specials. Note that this type of test is processor- and/or
platform-specific, so do tests which don't depend on the internals. | Check for specials. Note that this type of test is processor- and/or
platform-specific, so do tests which don't depend on the internals. | [
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"""
Check for specials. Note that this type of test is processor- and/or
platform-specific, so do tests which don't depend on the internals.
"""
if o != o:
text = 'NaN'
elif o == INFINITY:
text = 'Infinity'
elif o == -INFINITY:
text = '-Infinity'
else:
return FLOAT_REPR(o)
if not allow_nan:
raise ValueError("Out of range float values are not JSON compliant: %r"
% (o,))
return text | [
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|
wlanjie/AndroidFFmpeg | 7baf9122f4b8e1c74e7baf4be5c422c7a5ba5aaf | tools/fdk-aac-build/armeabi-v7a/toolchain/lib/python2.7/lib-tk/Tkinter.py | python | Misc.winfo_rgb | (self, color) | return self._getints(
self.tk.call('winfo', 'rgb', self._w, color)) | Return tuple of decimal values for red, green, blue for
COLOR in this widget. | Return tuple of decimal values for red, green, blue for
COLOR in this widget. | [
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"""Return tuple of decimal values for red, green, blue for
COLOR in this widget."""
return self._getints(
self.tk.call('winfo', 'rgb', self._w, color)) | [
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|
oracle/graaljs | 36a56e8e993d45fc40939a3a4d9c0c24990720f1 | graal-nodejs/deps/v8/tools/vim/ninja_output.py | python | GetNinjaOutputDirectory | (v8_root, configuration=None) | Returns <v8_root>/<output_dir>/(Release|Debug|<other>).
The configuration chosen is the one most recently generated/built, but can be
overriden via the <configuration> parameter. Detects a custom output_dir
specified by GYP_GENERATOR_FLAGS. | Returns <v8_root>/<output_dir>/(Release|Debug|<other>). | [
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"""Returns <v8_root>/<output_dir>/(Release|Debug|<other>).
The configuration chosen is the one most recently generated/built, but can be
overriden via the <configuration> parameter. Detects a custom output_dir
specified by GYP_GENERATOR_FLAGS."""
output_dirs = []
generator_flags = os.getenv('GYP_GENERATOR_FLAGS', '').split(' ')
for flag in generator_flags:
name_value = flag.split('=', 1)
if (len(name_value) == 2 and name_value[0] == 'output_dir' and
os.path.isdir(os.path.join(v8_root, name_value[1]))):
output_dirs = [name_value[1]]
if configuration:
output_dir = 'out' if len(output_dirs) == 0 else output_dirs[-1]
return os.path.join(os.path.join(v8_root, output_dir), configuration)
if not output_dirs:
for f in os.listdir(v8_root):
if re.match(r'out(\b|_)', f):
if os.path.isdir(os.path.join(v8_root, f)):
output_dirs.append(f)
def generate_paths():
for out_dir in output_dirs:
out_path = os.path.join(v8_root, out_dir)
for config in os.listdir(out_path):
path = os.path.join(out_path, config)
if os.path.exists(os.path.join(path, 'build.ninja')):
yield path
def approx_directory_mtime(path):
# This is a heuristic; don't recurse into subdirectories.
paths = [path] + [os.path.join(path, f) for f in os.listdir(path)]
return max(filter(None, [safe_mtime(p) for p in paths]))
def safe_mtime(path):
try:
return os.path.getmtime(path)
except OSError:
return None
try:
return max(generate_paths(), key=approx_directory_mtime)
except ValueError:
raise RuntimeError('Unable to find a valid ninja output directory.') | [
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||
google/syzygy | 8164b24ebde9c5649c9a09e88a7fc0b0fcbd1bc5 | third_party/websocket-client/websocket.py | python | WebSocket.gettimeout | (self) | return self.sock.gettimeout() | Get the websocket timeout(second). | Get the websocket timeout(second). | [
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] | def gettimeout(self):
"""
Get the websocket timeout(second).
"""
return self.sock.gettimeout() | [
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|
potassco/clingo | e0c91d8f95cc28de1c480a871f9c97c30de83d40 | libpyclingo/clingo/ast.py | python | Comparison | (comparison: int, left: AST, right: AST) | return AST(p_ast[0]) | Construct an AST node of type `ASTType.Comparison`. | Construct an AST node of type `ASTType.Comparison`. | [
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'''
Construct an AST node of type `ASTType.Comparison`.
'''
p_ast = _ffi.new('clingo_ast_t**')
_handle_error(_lib.clingo_ast_build(
_lib.clingo_ast_type_comparison, p_ast,
_ffi.cast('int', comparison),
left._rep,
right._rep))
return AST(p_ast[0]) | [
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|
Xilinx/Vitis-AI | fc74d404563d9951b57245443c73bef389f3657f | tools/Vitis-AI-Quantizer/vai_q_tensorflow1.x/tensorflow/contrib/timeseries/python/timeseries/state_space_models/state_space_model.py | python | StateSpaceModel._exogenous_input_step | (
self, current_times, current_exogenous_regressors, state) | return state | Update state with exogenous regressors.
Allows both increases and decreases in uncertainty.
Args:
current_times: A [batch size] Tensor of times for the exogenous values
being input.
current_exogenous_regressors: A [batch size x exogenous input dimension]
Tensor of exogenous values for each part of the batch.
state: A tuple of (mean, covariance, previous_times) having shapes
mean; [batch size x state dimension]
covariance; [batch size x state dimension x state dimension]
previous_times; [batch size]
Returns:
Updated state taking the exogenous regressors into account. | Update state with exogenous regressors. | [
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"state",
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"regressors",
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] | def _exogenous_input_step(
self, current_times, current_exogenous_regressors, state):
"""Update state with exogenous regressors.
Allows both increases and decreases in uncertainty.
Args:
current_times: A [batch size] Tensor of times for the exogenous values
being input.
current_exogenous_regressors: A [batch size x exogenous input dimension]
Tensor of exogenous values for each part of the batch.
state: A tuple of (mean, covariance, previous_times) having shapes
mean; [batch size x state dimension]
covariance; [batch size x state dimension x state dimension]
previous_times; [batch size]
Returns:
Updated state taking the exogenous regressors into account.
"""
if self._configuration.exogenous_noise_decreases:
state = self._exogenous_noise_decreasing(
current_times, current_exogenous_regressors, state)
if self._configuration.exogenous_noise_increases:
state = self._exogenous_noise_increasing(
current_times, current_exogenous_regressors, state)
return state | [
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|
hanpfei/chromium-net | 392cc1fa3a8f92f42e4071ab6e674d8e0482f83f | third_party/catapult/devil/devil/android/sdk/shared_prefs.py | python | SharedPrefs.__repr__ | (self) | return '<{cls} file {filename} for {package} on {device}>'.format(
cls=type(self).__name__, filename=self.filename, package=self.package,
device=str(self._device)) | Get a useful printable representation of the object. | Get a useful printable representation of the object. | [
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] | def __repr__(self):
"""Get a useful printable representation of the object."""
return '<{cls} file {filename} for {package} on {device}>'.format(
cls=type(self).__name__, filename=self.filename, package=self.package,
device=str(self._device)) | [
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] | https://github.com/hanpfei/chromium-net/blob/392cc1fa3a8f92f42e4071ab6e674d8e0482f83f/third_party/catapult/devil/devil/android/sdk/shared_prefs.py#L203-L207 |
|
microsoft/TSS.MSR | 0f2516fca2cd9929c31d5450e39301c9bde43688 | TSS.Py/src/TpmTypes.py | python | TPM2_PolicyLocality_REQUEST.toTpm | (self, buf) | TpmMarshaller method | TpmMarshaller method | [
"TpmMarshaller",
"method"
] | def toTpm(self, buf):
""" TpmMarshaller method """
buf.writeByte(self.locality) | [
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||
wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | wx/lib/pubsub/core/topicdefnprovider.py | python | exportTopicTreeSpec | (moduleName = None, rootTopic=None, bak='bak', moduleDoc=None) | Using TopicTreeSpecPrinter, exports the topic tree rooted at rootTopic to a
Python module (.py) file. This module will define module-level classes
representing root topics, nested classes for subtopics etc. Returns a string
representing the contents of the file. Parameters:
- If moduleName is given, the topic tree is written to moduleName.py in
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using bak as the filename extension. If bak is None, existing module file
gets overwritten.
- If rootTopic is specified, the export only traverses tree from
corresponding topic. Otherwise, complete tree, using
pub.getDefaultTopicTreeRoot() as starting point.
- The moduleDoc is the doc string for the module ie topic tree. | Using TopicTreeSpecPrinter, exports the topic tree rooted at rootTopic to a
Python module (.py) file. This module will define module-level classes
representing root topics, nested classes for subtopics etc. Returns a string
representing the contents of the file. Parameters: | [
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"""Using TopicTreeSpecPrinter, exports the topic tree rooted at rootTopic to a
Python module (.py) file. This module will define module-level classes
representing root topics, nested classes for subtopics etc. Returns a string
representing the contents of the file. Parameters:
- If moduleName is given, the topic tree is written to moduleName.py in
os.getcwd(). By default, it is first backed up, it it already exists,
using bak as the filename extension. If bak is None, existing module file
gets overwritten.
- If rootTopic is specified, the export only traverses tree from
corresponding topic. Otherwise, complete tree, using
pub.getDefaultTopicTreeRoot() as starting point.
- The moduleDoc is the doc string for the module ie topic tree.
"""
if rootTopic is None:
from .. import pub
rootTopic = pub.getDefaultTopicMgr().getRootAllTopics()
elif py2and3.isstring(rootTopic):
from .. import pub
rootTopic = pub.getDefaultTopicMgr().getTopic(rootTopic)
# create exporter
if moduleName is None:
capture = py2and3.StringIO()
TopicTreeSpecPrinter(rootTopic, fileObj=capture, treeDoc=moduleDoc)
return capture.getvalue()
else:
filename = '%s.py' % moduleName
if bak:
_backupIfExists(filename, bak)
moduleFile = open(filename, 'w')
try:
TopicTreeSpecPrinter(rootTopic, fileObj=moduleFile, treeDoc=moduleDoc)
finally:
moduleFile.close() | [
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||
nasa/fprime | 595cf3682d8365943d86c1a6fe7c78f0a116acf0 | Autocoders/Python/src/fprime_ac/parsers/XmlSerializeParser.py | python | XmlSerializeParser.get_comment | (self) | return self.__comment | Return text block string of comment for serializable class. | Return text block string of comment for serializable class. | [
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] | def get_comment(self):
"""
Return text block string of comment for serializable class.
"""
return self.__comment | [
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] | https://github.com/nasa/fprime/blob/595cf3682d8365943d86c1a6fe7c78f0a116acf0/Autocoders/Python/src/fprime_ac/parsers/XmlSerializeParser.py#L316-L320 |
|
FreeCAD/FreeCAD | ba42231b9c6889b89e064d6d563448ed81e376ec | src/Mod/Draft/drafttaskpanels/task_polararray.py | python | TaskPanelPolarArray.set_focus | (self, key=None) | Set the focus on the widget that receives the key signal. | Set the focus on the widget that receives the key signal. | [
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] | def set_focus(self, key=None):
"""Set the focus on the widget that receives the key signal."""
if key is None or key == "x":
self.form.input_c_x.setFocus()
self.form.input_c_x.selectAll()
elif key == "y":
self.form.input_c_y.setFocus()
self.form.input_c_y.selectAll()
elif key == "z":
self.form.input_c_z.setFocus()
self.form.input_c_z.selectAll() | [
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||
aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/site-packages/boto3/docs/service.py | python | ServiceDocumenter.document_service | (self) | return doc_structure.flush_structure() | Documents an entire service.
:returns: The reStructured text of the documented service. | Documents an entire service. | [
"Documents",
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"entire",
"service",
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] | def document_service(self):
"""Documents an entire service.
:returns: The reStructured text of the documented service.
"""
doc_structure = DocumentStructure(
self._service_name, section_names=self.sections,
target='html')
self.title(doc_structure.get_section('title'))
self.table_of_contents(doc_structure.get_section('table-of-contents'))
self.client_api(doc_structure.get_section('client'))
self.paginator_api(doc_structure.get_section('paginators'))
self.waiter_api(doc_structure.get_section('waiters'))
if self._service_resource:
self._document_service_resource(
doc_structure.get_section('service-resource'))
self._document_resources(doc_structure.get_section('resources'))
self._document_examples(doc_structure.get_section('examples'))
return doc_structure.flush_structure() | [
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|
mindspore-ai/mindspore | fb8fd3338605bb34fa5cea054e535a8b1d753fab | mindspore/python/mindspore/_extends/parallel_compile/tbe_compiler/tbe_adapter.py | python | tbe_initialize | (job: TbeJob) | return res | Tbe Initialize
:param job:
:return: | Tbe Initialize
:param job:
:return: | [
"Tbe",
"Initialize",
":",
"param",
"job",
":",
":",
"return",
":"
] | def tbe_initialize(job: TbeJob):
"""
Tbe Initialize
:param job:
:return:
"""
os.environ["CONTEXT_MODELCOMPILING"] = "TRUE"
soc_info = get_soc_info(job.content)
res = te_set_version(*soc_info)
if not res:
job.error("Set version failed")
res = _tune_init(job)
if not res:
job.error("Tune init failed")
lock_file = os.path.join(job.content["SocInfo"]["op_debug_dir"], "kernel_meta", "file.lock")
local_lock = LocalLock(lock_file)
try:
local_lock.lock()
res = _cann_kb_load(job)
if res == 1:
job.error("Cann kb load failed")
res = _parallel_compilation_init(job)
if not res:
job.error("Parallel compilation failed")
except RuntimeError:
job.error("Initialize failed with RuntimeError")
finally:
local_lock.unlock()
job.result = "Success"
return res | [
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|
hughperkins/tf-coriander | 970d3df6c11400ad68405f22b0c42a52374e94ca | tensorflow/contrib/learn/python/learn/datasets/base.py | python | load_iris | (data_path=None) | return load_csv_with_header(
data_path,
target_dtype=np.int,
features_dtype=np.float) | Load Iris dataset.
Args:
data_path: string, path to iris dataset (optional)
Returns:
Dataset object containing data in-memory. | Load Iris dataset. | [
"Load",
"Iris",
"dataset",
"."
] | def load_iris(data_path=None):
"""Load Iris dataset.
Args:
data_path: string, path to iris dataset (optional)
Returns:
Dataset object containing data in-memory.
"""
if data_path is None:
module_path = path.dirname(__file__)
data_path = path.join(module_path, 'data', 'iris.csv')
return load_csv_with_header(
data_path,
target_dtype=np.int,
features_dtype=np.float) | [
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|
omnisci/omniscidb | b9c95f1bd602b4ffc8b0edf18bfad61031e08d86 | Benchmarks/run_benchmark.py | python | clear_system_caches | () | Clears system caches | Clears system caches | [
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] | def clear_system_caches():
"""
Clears system caches
"""
try:
os.system('sudo sh -c "/bin/echo 3 > /proc/sys/vm/drop_caches"')
except Exception as e:
errormessage = "Clear system caches failed with error: " + str(e)
logging.error(errormessage) | [
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||
ApolloAuto/apollo-platform | 86d9dc6743b496ead18d597748ebabd34a513289 | ros/third_party/lib_aarch64/python2.7/dist-packages/rosdistro/dependency_walker.py | python | DependencyWalker.get_depends_on | (self, pkg_name, depend_type, ignore_pkgs=None) | return depends_on | Return a set of package names which depend on the package. | Return a set of package names which depend on the package. | [
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] | def get_depends_on(self, pkg_name, depend_type, ignore_pkgs=None):
'''Return a set of package names which depend on the package.'''
ignore_pkgs = ignore_pkgs or []
depends_on = set([])
for name in self._distribution_instance.release_packages.keys():
if name in ignore_pkgs:
continue
pkg = self._distribution_instance.release_packages[name]
repo = self._distribution_instance.repositories[pkg.repository_name].release_repository
if repo is None or repo.version is None:
continue
deps = self._get_dependencies(name, depend_type)
if pkg_name in deps:
depends_on.add(name)
return depends_on | [
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|
EricLYang/courseRepo | 60679ec7ec130fe0cff9d26b704f1e286e5fde13 | 9_class/arcodelocal/build/catkin_generated/installspace/_setup_util.py | python | _prefix_env_variable | (environ, name, paths, subfolders) | return prefix_str | Return the prefix to prepend to the environment variable NAME, adding any path in NEW_PATHS_STR without creating duplicate or empty items. | Return the prefix to prepend to the environment variable NAME, adding any path in NEW_PATHS_STR without creating duplicate or empty items. | [
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] | def _prefix_env_variable(environ, name, paths, subfolders):
'''
Return the prefix to prepend to the environment variable NAME, adding any path in NEW_PATHS_STR without creating duplicate or empty items.
'''
value = environ[name] if name in environ else ''
environ_paths = [path for path in value.split(os.pathsep) if path]
checked_paths = []
for path in paths:
if not isinstance(subfolders, list):
subfolders = [subfolders]
for subfolder in subfolders:
path_tmp = path
if subfolder:
path_tmp = os.path.join(path_tmp, subfolder)
# skip nonexistent paths
if not os.path.exists(path_tmp):
continue
# exclude any path already in env and any path we already added
if path_tmp not in environ_paths and path_tmp not in checked_paths:
checked_paths.append(path_tmp)
prefix_str = os.pathsep.join(checked_paths)
if prefix_str != '' and environ_paths:
prefix_str += os.pathsep
return prefix_str | [
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|
CGRU/cgru | 1881a4128530e3d31ac6c25314c18314fc50c2c7 | afanasy/python/services/service.py | python | service.doPost | (self) | return post_cmds | Missing DocString
:return: | Missing DocString | [
"Missing",
"DocString"
] | def doPost(self):
"""Missing DocString
:return:
"""
post_cmds = []
if not afcommon.checkBlockFlag(self.taskInfo['block_flags'], 'skipthumbnails'):
post_cmds.extend(self.generateThumbnail(False))
# post_cmds.extend(['ls -la > ' + self.taskInfo['store_dir'] + '/afile'])
return post_cmds | [
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|
kamyu104/LeetCode-Solutions | 77605708a927ea3b85aee5a479db733938c7c211 | Python/range-sum-query-mutable.py | python | NumArray.sumRange | (self, i, j) | return self.__sum(j) - self.__sum(i-1) | sum of elements nums[i..j], inclusive.
:type i: int
:type j: int
:rtype: int | sum of elements nums[i..j], inclusive.
:type i: int
:type j: int
:rtype: int | [
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] | def sumRange(self, i, j):
"""
sum of elements nums[i..j], inclusive.
:type i: int
:type j: int
:rtype: int
"""
return self.__sum(j) - self.__sum(i-1) | [
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|
catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/numpy/py2/numpy/lib/mixins.py | python | _disables_array_ufunc | (obj) | True when __array_ufunc__ is set to None. | True when __array_ufunc__ is set to None. | [
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] | def _disables_array_ufunc(obj):
"""True when __array_ufunc__ is set to None."""
try:
return obj.__array_ufunc__ is None
except AttributeError:
return False | [
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||
apple/turicreate | cce55aa5311300e3ce6af93cb45ba791fd1bdf49 | deps/src/libxml2-2.9.1/python/libxml2.py | python | xmlDoc.schemaValidateDoc | (self, ctxt) | return ret | Validate a document tree in memory. | Validate a document tree in memory. | [
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"memory",
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] | def schemaValidateDoc(self, ctxt):
"""Validate a document tree in memory. """
if ctxt is None: ctxt__o = None
else: ctxt__o = ctxt._o
ret = libxml2mod.xmlSchemaValidateDoc(ctxt__o, self._o)
return ret | [
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|
catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/scipy/scipy/signal/wavelets.py | python | morlet | (M, w=5.0, s=1.0, complete=True) | return output | Complex Morlet wavelet.
Parameters
----------
M : int
Length of the wavelet.
w : float, optional
Omega0. Default is 5
s : float, optional
Scaling factor, windowed from ``-s*2*pi`` to ``+s*2*pi``. Default is 1.
complete : bool, optional
Whether to use the complete or the standard version.
Returns
-------
morlet : (M,) ndarray
See Also
--------
scipy.signal.gausspulse
Notes
-----
The standard version::
pi**-0.25 * exp(1j*w*x) * exp(-0.5*(x**2))
This commonly used wavelet is often referred to simply as the
Morlet wavelet. Note that this simplified version can cause
admissibility problems at low values of `w`.
The complete version::
pi**-0.25 * (exp(1j*w*x) - exp(-0.5*(w**2))) * exp(-0.5*(x**2))
This version has a correction
term to improve admissibility. For `w` greater than 5, the
correction term is negligible.
Note that the energy of the return wavelet is not normalised
according to `s`.
The fundamental frequency of this wavelet in Hz is given
by ``f = 2*s*w*r / M`` where `r` is the sampling rate.
Note: This function was created before `cwt` and is not compatible
with it. | Complex Morlet wavelet. | [
"Complex",
"Morlet",
"wavelet",
"."
] | def morlet(M, w=5.0, s=1.0, complete=True):
"""
Complex Morlet wavelet.
Parameters
----------
M : int
Length of the wavelet.
w : float, optional
Omega0. Default is 5
s : float, optional
Scaling factor, windowed from ``-s*2*pi`` to ``+s*2*pi``. Default is 1.
complete : bool, optional
Whether to use the complete or the standard version.
Returns
-------
morlet : (M,) ndarray
See Also
--------
scipy.signal.gausspulse
Notes
-----
The standard version::
pi**-0.25 * exp(1j*w*x) * exp(-0.5*(x**2))
This commonly used wavelet is often referred to simply as the
Morlet wavelet. Note that this simplified version can cause
admissibility problems at low values of `w`.
The complete version::
pi**-0.25 * (exp(1j*w*x) - exp(-0.5*(w**2))) * exp(-0.5*(x**2))
This version has a correction
term to improve admissibility. For `w` greater than 5, the
correction term is negligible.
Note that the energy of the return wavelet is not normalised
according to `s`.
The fundamental frequency of this wavelet in Hz is given
by ``f = 2*s*w*r / M`` where `r` is the sampling rate.
Note: This function was created before `cwt` and is not compatible
with it.
"""
x = linspace(-s * 2 * pi, s * 2 * pi, M)
output = exp(1j * w * x)
if complete:
output -= exp(-0.5 * (w**2))
output *= exp(-0.5 * (x**2)) * pi**(-0.25)
return output | [
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|
hanpfei/chromium-net | 392cc1fa3a8f92f42e4071ab6e674d8e0482f83f | third_party/catapult/third_party/pyfakefs/pyfakefs/fake_tempfile.py | python | FakeTempfileModule.FakeReturnedMktempValues | (self) | return self._mktemp_retvals | For validation purposes, mktemp()'s return values are stored. | For validation purposes, mktemp()'s return values are stored. | [
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] | def FakeReturnedMktempValues(self):
"""For validation purposes, mktemp()'s return values are stored."""
return self._mktemp_retvals | [
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|
google/swiftshader | 8ccc63f045d5975fb67f9dfd3d2b8235b0526990 | third_party/SPIRV-Headers/tools/buildHeaders/bin/makeExtinstHeaders.py | python | mk_extinst | (name, grammar_file) | Generate one C header from a grammar | Generate one C header from a grammar | [
"Generate",
"one",
"C",
"header",
"from",
"a",
"grammar"
] | def mk_extinst(name, grammar_file):
"""Generate one C header from a grammar"""
script = '../../../tools/buildHeaders/bin/generate_language_headers.py'
subprocess.check_call(['python3',
script,
'--extinst-name=' + name,
'--extinst-grammar=' + grammar_file,
'--extinst-output-base=' + name])
subprocess.check_call(['dos2unix', name + '.h']) | [
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||
wangkuiyi/mapreduce-lite | 1bb92fe094dc47480ef9163c34070a3199feead6 | src/mapreduce_lite/scheduler/worker.py | python | MapOnlyWorker.get_worker_cmd | (self) | return cmd_map_worker | Get commands for map wokers | Get commands for map wokers | [
"Get",
"commands",
"for",
"map",
"wokers"
] | def get_worker_cmd(self):
""" Get commands for map wokers
"""
options = self.options
rank = self.rank
map_worker_id = rank
task = options.all_tasks[rank]
executable = '%s/%s %s' %(task['tmp_dir'],
options.remote_executable,
options.cmd_args)
param = (executable,
task['input_path'],
task['output_path'],
task['log_filebase'],
options.num_map_worker,
options.reduce_workers,
map_worker_id,
task['class'],
task['input_format'],
task['output_format'])
cmd_map_worker = """ %s
--mr_input_filepattern="%s"
--mr_output_files="%s"
--mr_log_filebase="%s"
--mr_num_map_workers=%s
--mr_reduce_workers=%s
--mr_map_worker_id=%s
--mr_map_only=true
--mr_mapper_class=%s
--mr_input_format=%s
--mr_output_format=%s
""" % param
return cmd_map_worker | [
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|
gtcasl/gpuocelot | fa63920ee7c5f9a86e264cd8acd4264657cbd190 | ocelot/scripts/build_environment.py | python | getLibCXXPaths | () | return (inc_path, lib_path) | Determines libc++ path
returns (inc_path, lib_path) | Determines libc++ path | [
"Determines",
"libc",
"++",
"path"
] | def getLibCXXPaths():
"""Determines libc++ path
returns (inc_path, lib_path)
"""
# determine defaults
if os.name == 'posix':
inc_path = '/usr/include'
lib_path = '/usr/lib/libc++.so'
else:
raise ValueError, 'Error: unknown OS. Where is libc++ installed?'
# override with environement variables
if 'LIBCXX_INC_PATH' in os.environ:
inc_path = os.path.abspath(os.environ['LIBCXX_INC_PATH'])
if 'LIBCXX_LIB_PATH' in os.environ:
lib_path = os.path.abspath(os.environ['LIBCXX_LIB_PATH'])
return (inc_path, lib_path) | [
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|
PixarAnimationStudios/USD | faed18ce62c8736b02413635b584a2f637156bad | pxr/usdImaging/usdviewq/appController.py | python | AppController._isHUDVisible | (self) | return self._dataModel.viewSettings.showHUD and self._dataModel.viewSettings.showHUD_Info | Checks if the upper HUD is visible by looking at the global HUD
visibility menu as well as the 'Subtree Info' menu | Checks if the upper HUD is visible by looking at the global HUD
visibility menu as well as the 'Subtree Info' menu | [
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"as",
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"as",
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"Subtree",
"Info",
"menu"
] | def _isHUDVisible(self):
"""Checks if the upper HUD is visible by looking at the global HUD
visibility menu as well as the 'Subtree Info' menu"""
return self._dataModel.viewSettings.showHUD and self._dataModel.viewSettings.showHUD_Info | [
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|
miyosuda/TensorFlowAndroidMNIST | 7b5a4603d2780a8a2834575706e9001977524007 | jni-build/jni/include/tensorflow/contrib/learn/python/learn/monitors.py | python | ValidationMonitor.__init__ | (self, x=None, y=None, input_fn=None, batch_size=None,
eval_steps=None,
every_n_steps=100, metrics=None, early_stopping_rounds=None,
early_stopping_metric="loss",
early_stopping_metric_minimize=True, name=None) | Initializes a ValidationMonitor.
Args:
x: See `BaseEstimator.evaluate`.
y: See `BaseEstimator.evaluate`.
input_fn: See `BaseEstimator.evaluate`.
batch_size: See `BaseEstimator.evaluate`.
eval_steps: See `BaseEstimator.evaluate`.
every_n_steps: Check for new checkpoints to evaluate every N steps. If a
new checkpoint is found, it is evaluated. See `EveryN`.
metrics: See `BaseEstimator.evaluate`.
early_stopping_rounds: `int`. If the metric indicated by
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`early_stopping_metric_minimize` for this many steps, then training
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early_stopping_metric: `string`, name of the metric to check for early
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early_stopping_metric_minimize: `bool`, True if `early_stopping_metric` is
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stops decreasing), False if `early_stopping_metric` is expected to
increase. Typically, `early_stopping_metric_minimize` is True for
loss metrics like mean squared error, and False for performance
metrics like accuracy.
name: See `BaseEstimator.evaluate`.
Raises:
ValueError: If both x and input_fn are provided. | Initializes a ValidationMonitor. | [
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] | def __init__(self, x=None, y=None, input_fn=None, batch_size=None,
eval_steps=None,
every_n_steps=100, metrics=None, early_stopping_rounds=None,
early_stopping_metric="loss",
early_stopping_metric_minimize=True, name=None):
"""Initializes a ValidationMonitor.
Args:
x: See `BaseEstimator.evaluate`.
y: See `BaseEstimator.evaluate`.
input_fn: See `BaseEstimator.evaluate`.
batch_size: See `BaseEstimator.evaluate`.
eval_steps: See `BaseEstimator.evaluate`.
every_n_steps: Check for new checkpoints to evaluate every N steps. If a
new checkpoint is found, it is evaluated. See `EveryN`.
metrics: See `BaseEstimator.evaluate`.
early_stopping_rounds: `int`. If the metric indicated by
`early_stopping_metric` does not change according to
`early_stopping_metric_minimize` for this many steps, then training
will be stopped.
early_stopping_metric: `string`, name of the metric to check for early
stopping.
early_stopping_metric_minimize: `bool`, True if `early_stopping_metric` is
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stops decreasing), False if `early_stopping_metric` is expected to
increase. Typically, `early_stopping_metric_minimize` is True for
loss metrics like mean squared error, and False for performance
metrics like accuracy.
name: See `BaseEstimator.evaluate`.
Raises:
ValueError: If both x and input_fn are provided.
"""
super(ValidationMonitor, self).__init__(every_n_steps=every_n_steps,
first_n_steps=-1)
# TODO(mdan): Checks like this are already done by evaluate.
if x is None and input_fn is None:
raise ValueError("Either x or input_fn should be provided.")
self.x = x
self.y = y
self.input_fn = input_fn
self.batch_size = batch_size
self.eval_steps = eval_steps
self.metrics = metrics
self.early_stopping_rounds = early_stopping_rounds
self.early_stopping_metric = early_stopping_metric
self.early_stopping_metric_minimize = early_stopping_metric_minimize
self.name = name
self._best_value_step = None
self._best_value = None
self._early_stopped = False
self._latest_path = None
self._latest_path_step = None | [
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||
sonyxperiadev/WebGL | 0299b38196f78c6d5f74bcf6fa312a3daee6de60 | Tools/Scripts/webkitpy/style/checkers/cpp.py | python | replaceable_check | (operator, macro, line) | return match(match_this, line) and not search(r'NULL|&&|\|\|', line) | Determine whether a basic CHECK can be replaced with a more specific one.
For example suggest using CHECK_EQ instead of CHECK(a == b) and
similarly for CHECK_GE, CHECK_GT, CHECK_LE, CHECK_LT, CHECK_NE.
Args:
operator: The C++ operator used in the CHECK.
macro: The CHECK or EXPECT macro being called.
line: The current source line.
Returns:
True if the CHECK can be replaced with a more specific one. | Determine whether a basic CHECK can be replaced with a more specific one. | [
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] | def replaceable_check(operator, macro, line):
"""Determine whether a basic CHECK can be replaced with a more specific one.
For example suggest using CHECK_EQ instead of CHECK(a == b) and
similarly for CHECK_GE, CHECK_GT, CHECK_LE, CHECK_LT, CHECK_NE.
Args:
operator: The C++ operator used in the CHECK.
macro: The CHECK or EXPECT macro being called.
line: The current source line.
Returns:
True if the CHECK can be replaced with a more specific one.
"""
# This matches decimal and hex integers, strings, and chars (in that order).
match_constant = r'([-+]?(\d+|0[xX][0-9a-fA-F]+)[lLuU]{0,3}|".*"|\'.*\')'
# Expression to match two sides of the operator with something that
# looks like a literal, since CHECK(x == iterator) won't compile.
# This means we can't catch all the cases where a more specific
# CHECK is possible, but it's less annoying than dealing with
# extraneous warnings.
match_this = (r'\s*' + macro + r'\((\s*' +
match_constant + r'\s*' + operator + r'[^<>].*|'
r'.*[^<>]' + operator + r'\s*' + match_constant +
r'\s*\))')
# Don't complain about CHECK(x == NULL) or similar because
# CHECK_EQ(x, NULL) won't compile (requires a cast).
# Also, don't complain about more complex boolean expressions
# involving && or || such as CHECK(a == b || c == d).
return match(match_this, line) and not search(r'NULL|&&|\|\|', line) | [
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|
Illumina/manta | 75b5c38d4fcd2f6961197b28a41eb61856f2d976 | scratch/util/largeIntrachromFilter.py | python | resolveRec | (recEqualSet, recList) | determine which of a set of vcf records presumed to refer to the same inversion are kept
right now best is a record with PASS in the filter field, and secondarily the high quality | determine which of a set of vcf records presumed to refer to the same inversion are kept
right now best is a record with PASS in the filter field, and secondarily the high quality | [
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"""
determine which of a set of vcf records presumed to refer to the same inversion are kept
right now best is a record with PASS in the filter field, and secondarily the high quality
"""
if not recEqualSet: return
bestIndex=0
bestSS=0.
bestPos=0
bestIsPass=False
for (index,rec) in enumerate(recEqualSet) :
assert rec.pos > 0
isNewPass=((not bestIsPass) and rec.isPass)
isHighQual=((bestIsPass == rec.isPass) and (rec.pos < bestPos)) #(rec.ss > bestSS))
if (isNewPass or isHighQual) :
bestIndex = index
bestPos = rec.pos
bestIsPass = rec.isPass
# potentially could reward two non-pass inversion calls here:
# if not bestIsPass and (len(recEqualSet) == 2) :
# if (recEqualSet[0].isInv3 and reEqualSet[1].isInv5) or
# recEqualSet[1].isInv3 and reEqualSet[0].isInv5)) :
recList.append(recEqualSet[bestIndex]) | [
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||
hughperkins/tf-coriander | 970d3df6c11400ad68405f22b0c42a52374e94ca | tensorflow/python/debug/cli/curses_ui.py | python | CursesUI._screen_create_command_textbox | (self, existing_command) | Create command textbox on screen.
Args:
existing_command: (str) A command string to put in the textbox right
after its creation. | Create command textbox on screen. | [
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"""Create command textbox on screen.
Args:
existing_command: (str) A command string to put in the textbox right
after its creation.
"""
# Display the tfdbg prompt.
self._stdscr.addstr(self._max_y - self._command_textbox_height, 0,
self.CLI_PROMPT, curses.A_BOLD)
self._stdscr.refresh()
self._command_window.clear()
# Command text box.
self._command_textbox = textpad.Textbox(
self._command_window, insert_mode=True)
# Enter existing command.
self._auto_key_in(existing_command) | [
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aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/windows/Lib/site-packages/requests/help.py | python | info | () | return {
'platform': platform_info,
'implementation': implementation_info,
'system_ssl': system_ssl_info,
'using_pyopenssl': pyopenssl is not None,
'pyOpenSSL': pyopenssl_info,
'urllib3': urllib3_info,
'chardet': chardet_info,
'cryptography': cryptography_info,
'idna': idna_info,
'requests': {
'version': requests_version,
},
} | Generate information for a bug report. | Generate information for a bug report. | [
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] | def info():
"""Generate information for a bug report."""
try:
platform_info = {
'system': platform.system(),
'release': platform.release(),
}
except IOError:
platform_info = {
'system': 'Unknown',
'release': 'Unknown',
}
implementation_info = _implementation()
urllib3_info = {'version': urllib3.__version__}
chardet_info = {'version': chardet.__version__}
pyopenssl_info = {
'version': None,
'openssl_version': '',
}
if OpenSSL:
pyopenssl_info = {
'version': OpenSSL.__version__,
'openssl_version': '%x' % OpenSSL.SSL.OPENSSL_VERSION_NUMBER,
}
cryptography_info = {
'version': getattr(cryptography, '__version__', ''),
}
idna_info = {
'version': getattr(idna, '__version__', ''),
}
system_ssl = ssl.OPENSSL_VERSION_NUMBER
system_ssl_info = {
'version': '%x' % system_ssl if system_ssl is not None else ''
}
return {
'platform': platform_info,
'implementation': implementation_info,
'system_ssl': system_ssl_info,
'using_pyopenssl': pyopenssl is not None,
'pyOpenSSL': pyopenssl_info,
'urllib3': urllib3_info,
'chardet': chardet_info,
'cryptography': cryptography_info,
'idna': idna_info,
'requests': {
'version': requests_version,
},
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|
catboost/catboost | 167f64f237114a4d10b2b4ee42adb4569137debe | contrib/python/pandas/py2/pandas/io/pytables.py | python | WORMTable.write | (self, **kwargs) | write in a format that we can search later on (but cannot append
to): write out the indices and the values using _write_array
(e.g. a CArray) create an indexing table so that we can search | write in a format that we can search later on (but cannot append
to): write out the indices and the values using _write_array
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""" write in a format that we can search later on (but cannot append
to): write out the indices and the values using _write_array
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"""
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||
wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | src/osx_carbon/combo.py | python | ComboCtrl.SetPopupAnchor | (*args, **kwargs) | return _combo.ComboCtrl_SetPopupAnchor(*args, **kwargs) | SetPopupAnchor(self, int anchorSide)
Set side of the control to which the popup will align itself. Valid
values are wx.LEFT, wx.RIGHT and 0. The default value 0 means that the
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"""
SetPopupAnchor(self, int anchorSide)
Set side of the control to which the popup will align itself. Valid
values are wx.LEFT, wx.RIGHT and 0. The default value 0 means that the
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"""
return _combo.ComboCtrl_SetPopupAnchor(*args, **kwargs) | [
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|
kamyu104/LeetCode-Solutions | 77605708a927ea3b85aee5a479db733938c7c211 | Python/finding-pairs-with-a-certain-sum.py | python | FindSumPairs.count | (self, tot) | return sum(cnt * self.__count2[tot-x] for x, cnt in self.__count1.iteritems()) | :type tot: int
:rtype: int | :type tot: int
:rtype: int | [
":",
"type",
"tot",
":",
"int",
":",
"rtype",
":",
"int"
] | def count(self, tot):
"""
:type tot: int
:rtype: int
"""
return sum(cnt * self.__count2[tot-x] for x, cnt in self.__count1.iteritems()) | [
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|
hpi-xnor/BMXNet-v2 | af2b1859eafc5c721b1397cef02f946aaf2ce20d | python/mxnet/ndarray/utils.py | python | array | (source_array, ctx=None, dtype=None) | Creates an array from any object exposing the array interface.
Parameters
----------
source_array : array_like
An object exposing the array interface, an object whose `__array__`
method returns an array, or any (nested) sequence.
ctx : Context, optional
Device context (default is the current default context).
dtype : str or numpy.dtype, optional
The data type of the output array. The default dtype is ``source_array.dtype``
if `source_array` is an `NDArray`, `float32` otherwise.
Returns
-------
NDArray, RowSparseNDArray or CSRNDArray
An array with the same contents as the `source_array`.
Examples
--------
>>> import numpy as np
>>> mx.nd.array([1, 2, 3])
<NDArray 3 @cpu(0)>
>>> mx.nd.array([[1, 2], [3, 4]])
<NDArray 2x2 @cpu(0)>
>>> mx.nd.array(np.zeros((3, 2)))
<NDArray 3x2 @cpu(0)>
>>> mx.nd.array(np.zeros((3, 2)), mx.gpu(0))
<NDArray 3x2 @gpu(0)>
>>> mx.nd.array(mx.nd.zeros((3, 2), stype='row_sparse'))
<RowSparseNDArray 3x2 @cpu(0)> | Creates an array from any object exposing the array interface. | [
"Creates",
"an",
"array",
"from",
"any",
"object",
"exposing",
"the",
"array",
"interface",
"."
] | def array(source_array, ctx=None, dtype=None):
"""Creates an array from any object exposing the array interface.
Parameters
----------
source_array : array_like
An object exposing the array interface, an object whose `__array__`
method returns an array, or any (nested) sequence.
ctx : Context, optional
Device context (default is the current default context).
dtype : str or numpy.dtype, optional
The data type of the output array. The default dtype is ``source_array.dtype``
if `source_array` is an `NDArray`, `float32` otherwise.
Returns
-------
NDArray, RowSparseNDArray or CSRNDArray
An array with the same contents as the `source_array`.
Examples
--------
>>> import numpy as np
>>> mx.nd.array([1, 2, 3])
<NDArray 3 @cpu(0)>
>>> mx.nd.array([[1, 2], [3, 4]])
<NDArray 2x2 @cpu(0)>
>>> mx.nd.array(np.zeros((3, 2)))
<NDArray 3x2 @cpu(0)>
>>> mx.nd.array(np.zeros((3, 2)), mx.gpu(0))
<NDArray 3x2 @gpu(0)>
>>> mx.nd.array(mx.nd.zeros((3, 2), stype='row_sparse'))
<RowSparseNDArray 3x2 @cpu(0)>
"""
if spsp is not None and isinstance(source_array, spsp.csr.csr_matrix):
return _sparse_array(source_array, ctx=ctx, dtype=dtype)
elif isinstance(source_array, NDArray) and source_array.stype != 'default':
return _sparse_array(source_array, ctx=ctx, dtype=dtype)
else:
return _array(source_array, ctx=ctx, dtype=dtype) | [
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||
ricardoquesada/Spidermonkey | 4a75ea2543408bd1b2c515aa95901523eeef7858 | media/webrtc/trunk/tools/gyp/pylib/gyp/xcode_emulation.py | python | XcodeSettings.GetProductType | (self) | Returns the PRODUCT_TYPE of this target. | Returns the PRODUCT_TYPE of this target. | [
"Returns",
"the",
"PRODUCT_TYPE",
"of",
"this",
"target",
"."
] | def GetProductType(self):
"""Returns the PRODUCT_TYPE of this target."""
if self._IsBundle():
return {
'executable': 'com.apple.product-type.application',
'loadable_module': 'com.apple.product-type.bundle',
'shared_library': 'com.apple.product-type.framework',
}[self.spec['type']]
else:
return {
'executable': 'com.apple.product-type.tool',
'loadable_module': 'com.apple.product-type.library.dynamic',
'shared_library': 'com.apple.product-type.library.dynamic',
'static_library': 'com.apple.product-type.library.static',
}[self.spec['type']] | [
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||
aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/idlelib/codecontext.py | python | CodeContext.__init__ | (self, editwin) | Initialize settings for context block.
editwin is the Editor window for the context block.
self.text is the editor window text widget.
self.context displays the code context text above the editor text.
Initially None, it is toggled via <<toggle-code-context>>.
self.topvisible is the number of the top text line displayed.
self.info is a list of (line number, indent level, line text,
block keyword) tuples for the block structure above topvisible.
self.info[0] is initialized with a 'dummy' line which
starts the toplevel 'block' of the module.
self.t1 and self.t2 are two timer events on the editor text widget to
monitor for changes to the context text or editor font. | Initialize settings for context block. | [
"Initialize",
"settings",
"for",
"context",
"block",
"."
] | def __init__(self, editwin):
"""Initialize settings for context block.
editwin is the Editor window for the context block.
self.text is the editor window text widget.
self.context displays the code context text above the editor text.
Initially None, it is toggled via <<toggle-code-context>>.
self.topvisible is the number of the top text line displayed.
self.info is a list of (line number, indent level, line text,
block keyword) tuples for the block structure above topvisible.
self.info[0] is initialized with a 'dummy' line which
starts the toplevel 'block' of the module.
self.t1 and self.t2 are two timer events on the editor text widget to
monitor for changes to the context text or editor font.
"""
self.editwin = editwin
self.text = editwin.text
self._reset() | [
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||
aws/lumberyard | f85344403c1c2e77ec8c75deb2c116e97b713217 | dev/Tools/Python/3.7.10/mac/Python.framework/Versions/3.7/lib/python3.7/idlelib/parenmatch.py | python | ParenMatch.set_timeout_none | (self) | Highlight will remain until user input turns it off
or the insert has moved | Highlight will remain until user input turns it off
or the insert has moved | [
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] | def set_timeout_none(self):
"""Highlight will remain until user input turns it off
or the insert has moved"""
# After CHECK_DELAY, call a function which disables the "paren" tag
# if the event is for the most recent timer and the insert has changed,
# or schedules another call for itself.
self.counter += 1
def callme(callme, self=self, c=self.counter,
index=self.text.index("insert")):
if index != self.text.index("insert"):
self.handle_restore_timer(c)
else:
self.editwin.text_frame.after(CHECK_DELAY, callme, callme)
self.editwin.text_frame.after(CHECK_DELAY, callme, callme) | [
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||
wxWidgets/wxPython-Classic | 19571e1ae65f1ac445f5491474121998c97a1bf0 | samples/ide/activegrid/tool/ProjectEditor.py | python | GetDocCallback | (filepath) | return doc, docModel | Get the Document used by the IDE and the in-memory document model used by runtime engine | Get the Document used by the IDE and the in-memory document model used by runtime engine | [
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"IDE",
"and",
"the",
"in",
"-",
"memory",
"document",
"model",
"used",
"by",
"runtime",
"engine"
] | def GetDocCallback(filepath):
""" Get the Document used by the IDE and the in-memory document model used by runtime engine """
docMgr = wx.GetApp().GetDocumentManager()
try:
doc = docMgr.CreateDocument(filepath, docMgr.GetFlags()|wx.lib.docview.DOC_SILENT|wx.lib.docview.DOC_OPEN_ONCE|wx.lib.docview.DOC_NO_VIEW)
if doc:
AddProjectMapping(doc)
else: # already open
for d in docMgr.GetDocuments():
if os.path.normcase(d.GetFilename()) == os.path.normcase(filepath):
doc = d
break
except Exception,e:
doc = None
aglogging.reportException(e, stacktrace=True)
if doc and doc.GetDocumentTemplate().GetDocumentType() == WsdlAgEditor.WsdlAgDocument:
# get referenced wsdl doc instead
if doc.GetModel().filePath:
if os.path.isabs(doc.GetModel().filePath): # if absolute path, leave it alone
filepath = doc.GetModel().filePath
else:
filepath = doc.GetAppDocMgr().fullPath(doc.GetModel().filePath) # check relative to project homeDir
if not os.path.isfile(filepath):
filepath = os.path.normpath(os.path.join(os.path.dirname(doc.GetFilename()), doc.GetModel().filePath)) # check relative to wsdlag file
if not os.path.isfile(filepath):
filename = os.sep + os.path.basename(doc.GetModel().filePath) # check to see if in project file
filePaths = findDocumentMgr(doc).filePaths
for fp in filePaths:
if fp.endswith(filename):
filepath = fp
break
try:
doc = docMgr.CreateDocument(filepath, docMgr.GetFlags()|wx.lib.docview.DOC_SILENT|wx.lib.docview.DOC_OPEN_ONCE|wx.lib.docview.DOC_NO_VIEW)
except Exception,e:
doc = None
aglogging.reportException(e, stacktrace=True)
if doc:
AddProjectMapping(doc)
else: # already open
for d in docMgr.GetDocuments():
if os.path.normcase(d.GetFilename()) == os.path.normcase(filepath):
doc = d
break
else:
doc = None
if doc:
docModel = doc.GetModel()
else:
docModel = None
return doc, docModel | [
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|
include-what-you-use/include-what-you-use | 208fbfffa5d69364b9f78e427caa443441279283 | mapgen/iwyu-mapgen-cpython.py | python | main | (pythonroot) | return 0 | Entry point. | Entry point. | [
"Entry",
"point",
"."
] | def main(pythonroot):
""" Entry point. """
# Collect all include names in the root. These are the private includes.
included_names = []
for fname in iterfiles(pythonroot, '*.h'):
included_names.extend(parse_include_names(fname))
# Discard duplicates and remove Python.h itself.
included_names = set(included_names)
included_names.remove('Python.h')
# Print mappings from name -> Python.h.
print('[')
print(',\n'.join(generate_imp_lines(sorted(included_names))))
print(']')
return 0 | [
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] | https://github.com/include-what-you-use/include-what-you-use/blob/208fbfffa5d69364b9f78e427caa443441279283/mapgen/iwyu-mapgen-cpython.py#L67-L84 |
|
OpenGenus/cosmos | 1a94e8880068e51d571543be179c323936bd0936 | code/data_structures/src/list/singly_linked_list/operations/find/find.py | python | Node.__repr__ | (self) | return self.data | Node representation as required | Node representation as required | [
"Node",
"representation",
"as",
"required"
] | def __repr__(self):
""" Node representation as required"""
return self.data | [
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|
mysql/mysql-workbench | 2f35f9034f015cbcd22139a60e1baa2e3e8e795c | modules/db.mysql/db_mysql_fe_grt.py | python | createScriptForCatalogObjects | (path, catalog, objectCreationParams) | return 1 | Create a CREATE script with the catalog objects. The catalog must have been previously processed
with generateSQLCreateStatements(), so that the objects have their temp_sql attributes set with
their respective SQL CREATE statements. | Create a CREATE script with the catalog objects. The catalog must have been previously processed
with generateSQLCreateStatements(), so that the objects have their temp_sql attributes set with
their respective SQL CREATE statements. | [
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"""Create a CREATE script with the catalog objects. The catalog must have been previously processed
with generateSQLCreateStatements(), so that the objects have their temp_sql attributes set with
their respective SQL CREATE statements.
"""
def object_heading(type, name):
text = """
-- ----------------------------------------------------------------------------
-- %s %s
-- ----------------------------------------------------------------------------
""" % (type, name)
return text
import time
file = open(path, "w+")
file.write("""-- ----------------------------------------------------------------------------
-- MySQL Workbench Migration
-- Migrated Schemata: %s
-- Source Schemata: %s
-- Created: %s
-- Workbench Version: %s
-- ----------------------------------------------------------------------------
""" % (", ".join([s.name for s in catalog.schemata]), ", ".join([s.oldName for s in catalog.schemata]), time.ctime(), Version.fromgrt(grt.root.wb.info.version)))
preamble = catalog.customData["migration:preamble"]
if preamble and preamble.temp_sql:
#file.write(object_heading("Preamble script", ""))
file.write(preamble.temp_sql+"\n")
for schema in catalog.schemata:
file.write(object_heading("Schema", schema.name))
file.write(schema.temp_sql+";\n")
for table in schema.tables:
file.write(object_heading("Table", "%s.%s" % (schema.name, table.name)))
file.write(table.temp_sql+";\n")
for view in schema.views:
file.write(object_heading("View", "%s.%s" % (schema.name, view.name)))
file.write(view.temp_sql+";\n")
for routine in schema.routines:
file.write(object_heading("Routine", "%s.%s" % (schema.name, routine.name)))
file.write(routine.temp_sql)
for table in schema.tables:
for trigger in table.triggers:
file.write(object_heading("Trigger", "%s.%s" % (schema.name, trigger.name)))
file.write(trigger.temp_sql+";\n")
postamble = catalog.customData["migration:postamble"]
if postamble and postamble.temp_sql:
#file.write(object_heading("Postamble script", ""))
file.write(postamble.temp_sql+"\n")
file.close()
return 1 | [
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] | https://github.com/mysql/mysql-workbench/blob/2f35f9034f015cbcd22139a60e1baa2e3e8e795c/modules/db.mysql/db_mysql_fe_grt.py#L230-L290 |
|
Xilinx/Vitis-AI | fc74d404563d9951b57245443c73bef389f3657f | models/AI-Model-Zoo/caffe-xilinx/examples/pycaffe/layers/pascal_multilabel_datalayers.py | python | check_params | (params) | A utility function to check the parameters for the data layers. | A utility function to check the parameters for the data layers. | [
"A",
"utility",
"function",
"to",
"check",
"the",
"parameters",
"for",
"the",
"data",
"layers",
"."
] | def check_params(params):
"""
A utility function to check the parameters for the data layers.
"""
assert 'split' in params.keys(
), 'Params must include split (train, val, or test).'
required = ['batch_size', 'pascal_root', 'im_shape']
for r in required:
assert r in params.keys(), 'Params must include {}'.format(r) | [
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||
arvidn/libtorrent | 717fc489aa1d3380b7f5f7e5167ba076a60035e6 | tools/benchmark_checking.py | python | rm_file_or_dir | (path) | Attempt to remove file or directory at path | Attempt to remove file or directory at path | [
"Attempt",
"to",
"remove",
"file",
"or",
"directory",
"at",
"path"
] | def rm_file_or_dir(path):
""" Attempt to remove file or directory at path
"""
try:
shutil.rmtree(path)
except Exception:
pass
try:
os.remove(path)
except Exception:
pass | [
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] | https://github.com/arvidn/libtorrent/blob/717fc489aa1d3380b7f5f7e5167ba076a60035e6/tools/benchmark_checking.py#L101-L112 |
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